|
13 | 13 | }, |
14 | 14 | { |
15 | 15 | "cell_type": "code", |
16 | | - "execution_count": 1, |
| 16 | + "execution_count": null, |
17 | 17 | "metadata": {}, |
18 | 18 | "outputs": [], |
19 | 19 | "source": [ |
|
31 | 31 | }, |
32 | 32 | { |
33 | 33 | "cell_type": "code", |
34 | | - "execution_count": 2, |
| 34 | + "execution_count": null, |
35 | 35 | "metadata": {}, |
36 | 36 | "outputs": [], |
37 | 37 | "source": [ |
|
50 | 50 | }, |
51 | 51 | { |
52 | 52 | "cell_type": "code", |
53 | | - "execution_count": 3, |
54 | | - "metadata": {}, |
55 | | - "outputs": [ |
56 | | - { |
57 | | - "name": "stdout", |
58 | | - "output_type": "stream", |
59 | | - "text": [ |
60 | | - "Stats: {'labels-added': 6, 'relationships-created': 10, 'nodes-created': 6, 'properties-set': 6}\n" |
61 | | - ] |
62 | | - } |
63 | | - ], |
| 53 | + "execution_count": null, |
| 54 | + "metadata": {}, |
| 55 | + "outputs": [], |
64 | 56 | "source": [ |
65 | 57 | "create_graph_query = '''\n", |
66 | | - "CREATE (nAlice:User {id:'Alice'})\n", |
67 | | - ",(nBridget:User {id:'Bridget'})\n", |
68 | | - ",(nCharles:User {id:'Charles'})\n", |
69 | | - ",(nDoug:User {id:'Doug'})\n", |
70 | | - ",(nMark:User {id:'Mark'})\n", |
71 | | - ",(nMichael:User {id:'Michael'})\n", |
72 | | - "CREATE (nAlice)-[:FOLLOW]->(nBridget)\n", |
73 | | - ",(nAlice)-[:FOLLOW]->(nCharles)\n", |
74 | | - ",(nMark)-[:FOLLOW]->(nDoug)\n", |
75 | | - ",(nMark)-[:FOLLOW]->(nMichael)\n", |
76 | | - ",(nBridget)-[:FOLLOW]->(nMichael)\n", |
77 | | - ",(nDoug)-[:FOLLOW]->(nMark)\n", |
78 | | - ",(nMichael)-[:FOLLOW]->(nAlice)\n", |
79 | | - ",(nAlice)-[:FOLLOW]->(nMichael)\n", |
80 | | - ",(nBridget)-[:FOLLOW]->(nAlice)\n", |
81 | | - ",(nMichael)-[:FOLLOW]->(nBridget);\n", |
| 58 | + "MERGE (nAlice:User {id:'Alice'})\n", |
| 59 | + "MERGE (nBridget:User {id:'Bridget'})\n", |
| 60 | + "MERGE (nCharles:User {id:'Charles'})\n", |
| 61 | + "MERGE (nDoug:User {id:'Doug'})\n", |
| 62 | + "MERGE (nMark:User {id:'Mark'})\n", |
| 63 | + "MERGE (nMichael:User {id:'Michael'})\n", |
| 64 | + "\n", |
| 65 | + "MERGE (nAlice)-[:FOLLOW]->(nBridget)\n", |
| 66 | + "MERGE (nAlice)-[:FOLLOW]->(nCharles)\n", |
| 67 | + "MERGE (nMark)-[:FOLLOW]->(nDoug)\n", |
| 68 | + "MERGE (nMark)-[:FOLLOW]->(nMichael)\n", |
| 69 | + "MERGE (nBridget)-[:FOLLOW]->(nMichael)\n", |
| 70 | + "MERGE (nDoug)-[:FOLLOW]->(nMark)\n", |
| 71 | + "MERGE (nMichael)-[:FOLLOW]->(nAlice)\n", |
| 72 | + "MERGE (nAlice)-[:FOLLOW]->(nMichael)\n", |
| 73 | + "MERGE (nBridget)-[:FOLLOW]->(nAlice)\n", |
| 74 | + "MERGE (nMichael)-[:FOLLOW]->(nBridget);\n", |
82 | 75 | "'''\n", |
83 | 76 | "\n", |
84 | 77 | "with driver.session() as session:\n", |
|
95 | 88 | }, |
96 | 89 | { |
97 | 90 | "cell_type": "code", |
98 | | - "execution_count": 4, |
99 | | - "metadata": {}, |
100 | | - "outputs": [ |
101 | | - { |
102 | | - "data": { |
103 | | - "text/html": [ |
104 | | - "<div>\n", |
105 | | - "<style scoped>\n", |
106 | | - " .dataframe tbody tr th:only-of-type {\n", |
107 | | - " vertical-align: middle;\n", |
108 | | - " }\n", |
109 | | - "\n", |
110 | | - " .dataframe tbody tr th {\n", |
111 | | - " vertical-align: top;\n", |
112 | | - " }\n", |
113 | | - "\n", |
114 | | - " .dataframe thead th {\n", |
115 | | - " text-align: right;\n", |
116 | | - " }\n", |
117 | | - "</style>\n", |
118 | | - "<table border=\"1\" class=\"dataframe\">\n", |
119 | | - " <thead>\n", |
120 | | - " <tr style=\"text-align: right;\">\n", |
121 | | - " <th></th>\n", |
122 | | - " <th>name</th>\n", |
123 | | - " <th>partition</th>\n", |
124 | | - " </tr>\n", |
125 | | - " </thead>\n", |
126 | | - " <tbody>\n", |
127 | | - " <tr>\n", |
128 | | - " <th>0</th>\n", |
129 | | - " <td>Mark</td>\n", |
130 | | - " <td>0</td>\n", |
131 | | - " </tr>\n", |
132 | | - " <tr>\n", |
133 | | - " <th>1</th>\n", |
134 | | - " <td>Michael</td>\n", |
135 | | - " <td>1</td>\n", |
136 | | - " </tr>\n", |
137 | | - " <tr>\n", |
138 | | - " <th>2</th>\n", |
139 | | - " <td>Charles</td>\n", |
140 | | - " <td>2</td>\n", |
141 | | - " </tr>\n", |
142 | | - " <tr>\n", |
143 | | - " <th>3</th>\n", |
144 | | - " <td>Doug</td>\n", |
145 | | - " <td>0</td>\n", |
146 | | - " </tr>\n", |
147 | | - " <tr>\n", |
148 | | - " <th>4</th>\n", |
149 | | - " <td>Alice</td>\n", |
150 | | - " <td>1</td>\n", |
151 | | - " </tr>\n", |
152 | | - " <tr>\n", |
153 | | - " <th>5</th>\n", |
154 | | - " <td>Bridget</td>\n", |
155 | | - " <td>1</td>\n", |
156 | | - " </tr>\n", |
157 | | - " </tbody>\n", |
158 | | - "</table>\n", |
159 | | - "</div>" |
160 | | - ], |
161 | | - "text/plain": [ |
162 | | - " name partition\n", |
163 | | - "0 Mark 0\n", |
164 | | - "1 Michael 1\n", |
165 | | - "2 Charles 2\n", |
166 | | - "3 Doug 0\n", |
167 | | - "4 Alice 1\n", |
168 | | - "5 Bridget 1" |
169 | | - ] |
170 | | - }, |
171 | | - "execution_count": 4, |
172 | | - "metadata": {}, |
173 | | - "output_type": "execute_result" |
174 | | - } |
175 | | - ], |
| 91 | + "execution_count": null, |
| 92 | + "metadata": {}, |
| 93 | + "outputs": [], |
176 | 94 | "source": [ |
177 | 95 | "streaming_query = \"\"\"\n", |
178 | 96 | "CALL algo.scc.stream('User','FOLLOW')\n", |
|
196 | 114 | "The first and biggest component has members Alice, Bridget, and Michael, while the second component has Doug and Mark.\n", |
197 | 115 | "Charles ends up in his own component becuase there isn't an outgoing relationship from that node to any of the others." |
198 | 116 | ] |
| 117 | + }, |
| 118 | + { |
| 119 | + "cell_type": "markdown", |
| 120 | + "metadata": {}, |
| 121 | + "source": [ |
| 122 | + "We can also call a version of the algorithm that will store the result as a property on a\n", |
| 123 | + "node. This is useful if we want to run future queries that use the result." |
| 124 | + ] |
| 125 | + }, |
| 126 | + { |
| 127 | + "cell_type": "code", |
| 128 | + "execution_count": null, |
| 129 | + "metadata": {}, |
| 130 | + "outputs": [], |
| 131 | + "source": [ |
| 132 | + "write_query = \"\"\"\n", |
| 133 | + "CALL algo.scc('User','FOLLOW', {write:true,partitionProperty:'partition'})\n", |
| 134 | + "YIELD loadMillis, computeMillis, writeMillis, setCount, maxSetSize, minSetSize;\n", |
| 135 | + "\"\"\"\n", |
| 136 | + "\n", |
| 137 | + "with driver.session() as session:\n", |
| 138 | + " session.write_transaction(lambda tx: tx.run(write_query))" |
| 139 | + ] |
| 140 | + }, |
| 141 | + { |
| 142 | + "cell_type": "markdown", |
| 143 | + "metadata": {}, |
| 144 | + "source": [ |
| 145 | + "## Graph Visualisation\n", |
| 146 | + "\n", |
| 147 | + "Sometimes a picture can tell more than a table of results and this is often the case with graph algorithms. \n", |
| 148 | + "Let's see how to create a graph visualization using neovis.js.\n", |
| 149 | + "\n", |
| 150 | + "First we'll create a div into which we will generate the visualisation." |
| 151 | + ] |
| 152 | + }, |
| 153 | + { |
| 154 | + "cell_type": "code", |
| 155 | + "execution_count": null, |
| 156 | + "metadata": {}, |
| 157 | + "outputs": [], |
| 158 | + "source": [ |
| 159 | + "%%html\n", |
| 160 | + "<style type=\"text/css\"> \n", |
| 161 | + ".output_wrapper, .output {\n", |
| 162 | + " height:auto !important;\n", |
| 163 | + " max-height:600px;\n", |
| 164 | + "}\n", |
| 165 | + ".output_scroll {\n", |
| 166 | + " box-shadow:none !important;\n", |
| 167 | + " webkit-box-shadow:none !important;\n", |
| 168 | + "}\n", |
| 169 | + "\n", |
| 170 | + "#viz {\n", |
| 171 | + " width: 300px;\n", |
| 172 | + " height: 350px;\n", |
| 173 | + " font: 22pt arial;\n", |
| 174 | + "}\n", |
| 175 | + "</style> \n", |
| 176 | + "<div id=\"viz\"></div>" |
| 177 | + ] |
| 178 | + }, |
| 179 | + { |
| 180 | + "cell_type": "markdown", |
| 181 | + "metadata": {}, |
| 182 | + "source": [ |
| 183 | + "Next we need to define the query that the visualization will be generated from, along with config \n", |
| 184 | + "that describes which properties will be used for node size, node colour, and relationship width. \n", |
| 185 | + "\n", |
| 186 | + "We'll then define a JavaScript variable that contains all our parameters." |
| 187 | + ] |
| 188 | + }, |
| 189 | + { |
| 190 | + "cell_type": "code", |
| 191 | + "execution_count": null, |
| 192 | + "metadata": {}, |
| 193 | + "outputs": [], |
| 194 | + "source": [ |
| 195 | + "from IPython.core.display import Javascript\n", |
| 196 | + "import json\n", |
| 197 | + "from scripts.algo import viz_config, render_image\n", |
| 198 | + "\n", |
| 199 | + "config = viz_config(\"Strongly Connected Components\")\n", |
| 200 | + "query = config[\"query\"]\n", |
| 201 | + "labels_json = config[\"labels_json\"]\n", |
| 202 | + "relationships_json = config[\"relationships_json\"]\n", |
| 203 | + "\n", |
| 204 | + "json_graph = {\n", |
| 205 | + " \"query\": query,\n", |
| 206 | + " \"labels\": labels_json,\n", |
| 207 | + " \"relationships\": relationships_json,\n", |
| 208 | + " \"host\": host,\n", |
| 209 | + " \"user\": user,\n", |
| 210 | + " \"password\": password\n", |
| 211 | + "}\n", |
| 212 | + "\n", |
| 213 | + "Javascript(\"\"\"window.jsonGraph={};\"\"\".format(json.dumps(json_graph)))" |
| 214 | + ] |
| 215 | + }, |
| 216 | + { |
| 217 | + "cell_type": "markdown", |
| 218 | + "metadata": {}, |
| 219 | + "source": [ |
| 220 | + "Now we're ready to call neovis.js and generate our graph visualisation. \n", |
| 221 | + "The following code will create an interactive graph into the div defined above.\n", |
| 222 | + "It will also extract an image representation of the graph and display that in the cell below." |
| 223 | + ] |
| 224 | + }, |
| 225 | + { |
| 226 | + "cell_type": "code", |
| 227 | + "execution_count": null, |
| 228 | + "metadata": {}, |
| 229 | + "outputs": [], |
| 230 | + "source": [ |
| 231 | + "%%javascript\n", |
| 232 | + "var output_area = this;\n", |
| 233 | + "requirejs(['neovis.js'], function(NeoVis){ \n", |
| 234 | + " var config = {\n", |
| 235 | + " container_id: \"viz\",\n", |
| 236 | + " server_url: window.jsonGraph.host,\n", |
| 237 | + " server_user: window.jsonGraph.user,\n", |
| 238 | + " server_password: window.jsonGraph.password,\n", |
| 239 | + " labels: window.jsonGraph.labels,\n", |
| 240 | + " relationships: window.jsonGraph.relationships,\n", |
| 241 | + " initial_cypher: window.jsonGraph.query\n", |
| 242 | + " };\n", |
| 243 | + " \n", |
| 244 | + " let viz = new NeoVis.default(config);\n", |
| 245 | + " viz.render();\n", |
| 246 | + " \n", |
| 247 | + " viz.onVisualizationRendered(function(ctx) {\n", |
| 248 | + " let imageSrc = ctx.canvas.toDataURL();\n", |
| 249 | + " let kernel = IPython.notebook.kernel;\n", |
| 250 | + " let command = \"image_src = '\" + imageSrc + \"'\";\n", |
| 251 | + " kernel.execute(command);\n", |
| 252 | + " \n", |
| 253 | + " var cell_element = output_area.element.parents('.cell');\n", |
| 254 | + " var cell_idx = Jupyter.notebook.get_cell_elements().index(cell_element);\n", |
| 255 | + " var cell = Jupyter.notebook.get_cell(cell_idx+1);\n", |
| 256 | + " cell.set_text(\"render_image(image_src)\")\n", |
| 257 | + " cell.execute();\n", |
| 258 | + " });\n", |
| 259 | + "});" |
| 260 | + ] |
| 261 | + }, |
| 262 | + { |
| 263 | + "cell_type": "code", |
| 264 | + "execution_count": null, |
| 265 | + "metadata": {}, |
| 266 | + "outputs": [], |
| 267 | + "source": [] |
199 | 268 | } |
200 | 269 | ], |
201 | 270 | "metadata": {}, |
|
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