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Cross repository pull request #39

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25380d5
testing .ipynb diff
amit1rrr Jul 14, 2018
47f6ccf
Modify scatter plot
amit1rrr Jul 23, 2018
42e57b4
Changed another plot
amit1rrr Jul 23, 2018
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102 changes: 29 additions & 73 deletions notebooks/02.08-Sorting.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -30,7 +30,7 @@
"cell_type": "markdown",
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T1- Post from ReviewNB

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T2- Post from ReviewNB

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T12

"metadata": {},
"source": [
"Up to this point we have been concerned mainly with tools to access and operate on array data with NumPy.\n",
"Up to this point we have ever been concerned mainly with tools to access and operate on array data with NumPy.\n",
"This section covers algorithms related to sorting values in NumPy arrays.\n",
"These algorithms are a favorite topic in introductory computer science courses: if you've ever taken one, you probably have had dreams (or, depending on your temperament, nightmares) about *insertion sorts*, *selection sorts*, *merge sorts*, *quick sorts*, *bubble sorts*, and many, many more.\n",
"All are means of accomplishing a similar task: sorting the values in a list or array.\n",
Expand All @@ -41,26 +41,24 @@
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import os\n",
"\n",
"def selection_sort(x):\n",
" for i in range(len(x)):\n",
" swap = i + np.argmin(x[i:])\n",
" (x[i], x[swap]) = (x[swap], x[i])\n",
" i += 1\n",
" (x[x], x[swap]) = (x[swap], x[i])\n",
" return x"
]
},
{
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"execution_count": 2,
"metadata": {
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},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -92,9 +90,7 @@
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"def bogosort(x):\n",
Expand All @@ -106,9 +102,7 @@
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -151,9 +145,7 @@
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -181,9 +173,7 @@
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"name": "stdout",
Expand All @@ -208,9 +198,7 @@
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"name": "stdout",
Expand All @@ -237,9 +225,7 @@
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -273,9 +259,7 @@
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"name": "stdout",
Expand All @@ -297,9 +281,7 @@
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand All @@ -323,9 +305,7 @@
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -365,9 +345,7 @@
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -398,9 +376,7 @@
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -444,9 +420,7 @@
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"X = rand.rand(10, 2)"
Expand All @@ -462,9 +436,7 @@
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -496,9 +468,7 @@
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"dist_sq = np.sum((X[:, np.newaxis, :] - X[np.newaxis, :, :]) ** 2, axis=-1)"
Expand All @@ -514,9 +484,7 @@
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand All @@ -538,9 +506,7 @@
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand All @@ -562,9 +528,7 @@
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -593,9 +557,7 @@
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -623,9 +585,7 @@
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"name": "stdout",
Expand Down Expand Up @@ -661,9 +621,7 @@
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [],
"source": [
"K = 2\n",
Expand All @@ -680,9 +638,7 @@
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"collapsed": false
},
"metadata": {},
"outputs": [
{
"data": {
Expand Down Expand Up @@ -773,9 +729,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.1"
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 0
"nbformat_minor": 1
}
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