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Browse files- pyvis/notebooks/dot.html +0 -84
- pyvis/notebooks/example.html +0 -108
- pyvis/notebooks/example.ipynb +0 -483
- pyvis/notebooks/test.dot +0 -9
pyvis/notebooks/dot.html
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<html>
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<head>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/vis-network@latest/styles/vis-network.css" type="text/css" />
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<script type="text/javascript" src="https://cdn.jsdelivr.net/npm/vis-network@latest/dist/vis-network.min.js"> </script>
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<center>
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<h1></h1>
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</center>
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<!-- <link rel="stylesheet" href="../node_modules/vis/dist/vis.min.css" type="text/css" />
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<script type="text/javascript" src="../node_modules/vis/dist/vis.js"> </script>-->
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<style type="text/css">
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#mynetwork {
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width: 500px;
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height: 500px;
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background-color: #ffffff;
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border: 1px solid lightgray;
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position: relative;
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float: left;
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}
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</style>
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</head>
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<body>
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<div id = "mynetwork"></div>
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<script type="text/javascript">
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// initialize global variables.
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var edges;
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var nodes;
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var network;
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var container;
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var options, data;
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// This method is responsible for drawing the graph, returns the drawn network
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function drawGraph() {
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var container = document.getElementById('mynetwork');
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var DOTstring = "digraph { a [label=12, entity_id=12, entity_class=\"truck\"]; b [label=7, entity_id=7,entity_class=\"bike\"]; c [label=3, entity_id=3, entity_class=\"car\"]; a -> b[label=\"solid edge\"]; a -> b [label=\"dashed edge\", style=dashed]; a -> c [label=\"dashed edge\", style=dashed]; a -> c [label=\"dotted edge\", style=dotted]; }";
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data = vis.network.dotparser.DOTToGraph(DOTstring);
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var options = data.options;
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options = Object.assign(options, {
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nodes: {
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shape: "dot"
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},
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});
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options = Object.assign(options, {"physics": {"enabled": true, "barnesHut": {"theta": 0.5, "gravitationalConstant": -2000, "centralGravity": 0.3, "springLength": 200, "springConstant": 0.04, "damping": 0.09, "avoidOverlap": 0}, "maxVelocity": 50, "minVelocity": 0.1, "solver": "barnesHut", "stabilization": {"enabled": true, "iterations": 1000, "updateInterval": 100, "onlyDynamicEdges": false, "fit": true}}})
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network = new vis.Network(container, data, options);
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return network;
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}
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drawGraph();
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</script>
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</body>
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</html>
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pyvis/notebooks/example.html
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<html>
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<head>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/vis-network@latest/styles/vis-network.css" type="text/css" />
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<script type="text/javascript" src="https://cdn.jsdelivr.net/npm/vis-network@latest/dist/vis-network.min.js"> </script>
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<center>
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<h1></h1>
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</center>
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<!-- <link rel="stylesheet" href="../node_modules/vis/dist/vis.min.css" type="text/css" />
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<script type="text/javascript" src="../node_modules/vis/dist/vis.js"> </script>-->
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<style type="text/css">
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#mynetwork {
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width: 500px;
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height: 500px;
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background-color: #ffffff;
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border: 1px solid lightgray;
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position: relative;
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float: left;
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}
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</style>
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</head>
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<body>
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<div id = "mynetwork"></div>
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<script type="text/javascript">
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// initialize global variables.
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var edges;
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var nodes;
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var network;
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var container;
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var options, data;
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// This method is responsible for drawing the graph, returns the drawn network
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function drawGraph() {
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var container = document.getElementById('mynetwork');
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// parsing and collecting nodes and edges from the python
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nodes = new vis.DataSet([{"id": 0, "label": 0, "shape": "dot"}, {"id": 1, "label": 1, "shape": "dot"}, {"id": 2, "label": 2, "shape": "dot"}, {"id": 3, "label": 3, "shape": "dot"}, {"id": 4, "label": 4, "shape": "dot"}]);
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edges = new vis.DataSet([{"from": 0, "to": 2}, {"from": 0, "to": 3}, {"from": 0, "to": 4}, {"from": 1, "to": 1}, {"from": 1, "to": 3}, {"from": 1, "to": 2}]);
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// adding nodes and edges to the graph
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data = {nodes: nodes, edges: edges};
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var options = {
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"configure": {
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"enabled": false
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},
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"edges": {
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"color": {
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"inherit": true
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},
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"smooth": {
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"enabled": true,
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"type": "dynamic"
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}
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},
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"interaction": {
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"dragNodes": true,
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"hideEdgesOnDrag": false,
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"hideNodesOnDrag": false
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},
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"physics": {
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"enabled": true,
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"stabilization": {
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"enabled": true,
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"fit": true,
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"iterations": 1000,
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"onlyDynamicEdges": false,
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"updateInterval": 50
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}
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}
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};
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network = new vis.Network(container, data, options);
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return network;
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}
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drawGraph();
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</script>
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</body>
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</html>
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pyvis/notebooks/example.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"import sys\n",
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"sys.path.append('../')\n",
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"from pyvis.network import Network"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Basic Example"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/html": [
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"\n",
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" <iframe\n",
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" width=\"500px\"\n",
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" height=\"500px\"\n",
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" src=\"example.html\"\n",
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" frameborder=\"0\"\n",
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" allowfullscreen\n",
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" ></iframe>\n",
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" "
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],
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"text/plain": [
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"<IPython.lib.display.IFrame at 0x7fbe1d273d30>"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"g = Network(notebook=True)\n",
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"g.add_nodes(range(5))\n",
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"g.add_edges([\n",
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" (0, 2),\n",
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" (0, 3),\n",
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" (0, 4),\n",
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" (1, 1),\n",
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" (1, 3),\n",
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" (1, 2)\n",
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"])\n",
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"g.show(\"example.html\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Dot File example"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {
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"scrolled": true
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},
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"outputs": [
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{
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"data": {
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"text/html": [
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"\n",
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" <iframe\n",
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" width=\"500px\"\n",
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" height=\"500px\"\n",
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" src=\"dot.html\"\n",
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" frameborder=\"0\"\n",
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" allowfullscreen\n",
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" ></iframe>\n",
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" "
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],
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"text/plain": [
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"<IPython.lib.display.IFrame at 0x7fbe3d2ead00>"
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]
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},
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"execution_count": 9,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"h = Network(notebook=True)\n",
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"h.from_DOT(\"test.dot\")\n",
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"\n",
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"# All properties have to be enclosed by double quotes and \n",
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"# there and there must be no comma at the end of a list.\n",
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"# See https://visjs.github.io/vis-network/docs/network/ for all options\n",
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"h.set_options(\"\"\"\n",
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"var options = {\n",
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" \"physics\": {\n",
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" \"enabled\": true,\n",
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" \"barnesHut\": {\n",
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" \"theta\": 0.5,\n",
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" \"gravitationalConstant\": -2000,\n",
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" \"centralGravity\": 0.3,\n",
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" \"springLength\": 200,\n",
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" \"springConstant\": 0.04,\n",
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" \"damping\": 0.09,\n",
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" \"avoidOverlap\": 0\n",
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" },\n",
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" \"maxVelocity\": 50,\n",
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" \"minVelocity\": 0.1,\n",
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" \"solver\": \"barnesHut\",\n",
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" \"stabilization\": {\n",
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" \"enabled\": true,\n",
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" \"iterations\": 1000,\n",
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" \"updateInterval\": 100,\n",
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" \"onlyDynamicEdges\": false,\n",
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" \"fit\": true\n",
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" }\n",
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" }\n",
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"}\n",
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"\"\"\")\n",
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"h.show(\"dot.html\")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
|
| 137 |
-
"source": [
|
| 138 |
-
"### Basic NetworkX example"
|
| 139 |
-
]
|
| 140 |
-
},
|
| 141 |
-
{
|
| 142 |
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"cell_type": "code",
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| 143 |
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"execution_count": 10,
|
| 144 |
-
"metadata": {},
|
| 145 |
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"outputs": [],
|
| 146 |
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"source": [
|
| 147 |
-
"import networkx as nx"
|
| 148 |
-
]
|
| 149 |
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},
|
| 150 |
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{
|
| 151 |
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"cell_type": "code",
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| 152 |
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"execution_count": 11,
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| 153 |
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"metadata": {
|
| 154 |
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"scrolled": false
|
| 155 |
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},
|
| 156 |
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"outputs": [
|
| 157 |
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{
|
| 158 |
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"data": {
|
| 159 |
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"text/html": [
|
| 160 |
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"\n",
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| 161 |
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" <iframe\n",
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| 162 |
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" width=\"500px\"\n",
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| 163 |
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" height=\"500px\"\n",
|
| 164 |
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" src=\"example.html\"\n",
|
| 165 |
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" frameborder=\"0\"\n",
|
| 166 |
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" allowfullscreen\n",
|
| 167 |
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" ></iframe>\n",
|
| 168 |
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" "
|
| 169 |
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],
|
| 170 |
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"text/plain": [
|
| 171 |
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"<IPython.lib.display.IFrame at 0x7f3ef910af40>"
|
| 172 |
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]
|
| 173 |
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},
|
| 174 |
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"execution_count": 11,
|
| 175 |
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"metadata": {},
|
| 176 |
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"output_type": "execute_result"
|
| 177 |
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}
|
| 178 |
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],
|
| 179 |
-
"source": [
|
| 180 |
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"nxg = nx.random_tree(20)\n",
|
| 181 |
-
"g.from_nx(nxg)\n",
|
| 182 |
-
"g.show(\"example.html\")"
|
| 183 |
-
]
|
| 184 |
-
},
|
| 185 |
-
{
|
| 186 |
-
"cell_type": "markdown",
|
| 187 |
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"metadata": {},
|
| 188 |
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"source": [
|
| 189 |
-
"### Disabling Physics interaction"
|
| 190 |
-
]
|
| 191 |
-
},
|
| 192 |
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{
|
| 193 |
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"cell_type": "code",
|
| 194 |
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"execution_count": 6,
|
| 195 |
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"metadata": {},
|
| 196 |
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"outputs": [
|
| 197 |
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{
|
| 198 |
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"data": {
|
| 199 |
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"text/html": [
|
| 200 |
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"\n",
|
| 201 |
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" <iframe\n",
|
| 202 |
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" width=\"500px\"\n",
|
| 203 |
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" height=\"500px\"\n",
|
| 204 |
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" src=\"example.html\"\n",
|
| 205 |
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" frameborder=\"0\"\n",
|
| 206 |
-
" allowfullscreen\n",
|
| 207 |
-
" \n",
|
| 208 |
-
" ></iframe>\n",
|
| 209 |
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" "
|
| 210 |
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],
|
| 211 |
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"text/plain": [
|
| 212 |
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"<IPython.lib.display.IFrame at 0x7f882040c6d0>"
|
| 213 |
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]
|
| 214 |
-
},
|
| 215 |
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"execution_count": 6,
|
| 216 |
-
"metadata": {},
|
| 217 |
-
"output_type": "execute_result"
|
| 218 |
-
}
|
| 219 |
-
],
|
| 220 |
-
"source": [
|
| 221 |
-
"g.toggle_physics(False)\n",
|
| 222 |
-
"g.show(\"example.html\")"
|
| 223 |
-
]
|
| 224 |
-
},
|
| 225 |
-
{
|
| 226 |
-
"cell_type": "markdown",
|
| 227 |
-
"metadata": {},
|
| 228 |
-
"source": [
|
| 229 |
-
"### Explicit coordinates to layout nodes"
|
| 230 |
-
]
|
| 231 |
-
},
|
| 232 |
-
{
|
| 233 |
-
"cell_type": "code",
|
| 234 |
-
"execution_count": 7,
|
| 235 |
-
"metadata": {},
|
| 236 |
-
"outputs": [
|
| 237 |
-
{
|
| 238 |
-
"data": {
|
| 239 |
-
"text/html": [
|
| 240 |
-
"\n",
|
| 241 |
-
" <iframe\n",
|
| 242 |
-
" width=\"500px\"\n",
|
| 243 |
-
" height=\"500px\"\n",
|
| 244 |
-
" src=\"example.html\"\n",
|
| 245 |
-
" frameborder=\"0\"\n",
|
| 246 |
-
" allowfullscreen\n",
|
| 247 |
-
" \n",
|
| 248 |
-
" ></iframe>\n",
|
| 249 |
-
" "
|
| 250 |
-
],
|
| 251 |
-
"text/plain": [
|
| 252 |
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"<IPython.lib.display.IFrame at 0x7f87dc679b50>"
|
| 253 |
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]
|
| 254 |
-
},
|
| 255 |
-
"execution_count": 7,
|
| 256 |
-
"metadata": {},
|
| 257 |
-
"output_type": "execute_result"
|
| 258 |
-
}
|
| 259 |
-
],
|
| 260 |
-
"source": [
|
| 261 |
-
"g = Network(notebook=True)\n",
|
| 262 |
-
"g.add_nodes([1,2,3],\n",
|
| 263 |
-
" value=[10, 100, 400],\n",
|
| 264 |
-
" title=[\"I am node 1\", \"node 2 here\", \"and im node 3\"],\n",
|
| 265 |
-
" x=[21.4, 21.4, 21.4], y=[100.2, 223.54, 32.1],\n",
|
| 266 |
-
" label=[\"NODE 1\", \"NODE 2\", \"NODE 3\"],\n",
|
| 267 |
-
" color=[\"#00ff1e\", \"#162347\", \"#dd4b39\"])\n",
|
| 268 |
-
"g.show(\"example.html\")"
|
| 269 |
-
]
|
| 270 |
-
},
|
| 271 |
-
{
|
| 272 |
-
"cell_type": "markdown",
|
| 273 |
-
"metadata": {},
|
| 274 |
-
"source": [
|
| 275 |
-
"### Full Game of Thrones example"
|
| 276 |
-
]
|
| 277 |
-
},
|
| 278 |
-
{
|
| 279 |
-
"cell_type": "code",
|
| 280 |
-
"execution_count": 8,
|
| 281 |
-
"metadata": {},
|
| 282 |
-
"outputs": [
|
| 283 |
-
{
|
| 284 |
-
"data": {
|
| 285 |
-
"text/html": [
|
| 286 |
-
"\n",
|
| 287 |
-
" <iframe\n",
|
| 288 |
-
" width=\"100%\"\n",
|
| 289 |
-
" height=\"750px\"\n",
|
| 290 |
-
" src=\"example.html\"\n",
|
| 291 |
-
" frameborder=\"0\"\n",
|
| 292 |
-
" allowfullscreen\n",
|
| 293 |
-
" \n",
|
| 294 |
-
" ></iframe>\n",
|
| 295 |
-
" "
|
| 296 |
-
],
|
| 297 |
-
"text/plain": [
|
| 298 |
-
"<IPython.lib.display.IFrame at 0x7f87da76e430>"
|
| 299 |
-
]
|
| 300 |
-
},
|
| 301 |
-
"execution_count": 8,
|
| 302 |
-
"metadata": {},
|
| 303 |
-
"output_type": "execute_result"
|
| 304 |
-
}
|
| 305 |
-
],
|
| 306 |
-
"source": [
|
| 307 |
-
"import pandas as pd\n",
|
| 308 |
-
"\n",
|
| 309 |
-
"got_net = Network(notebook=True, height=\"750px\", width=\"100%\", bgcolor=\"#222222\", font_color=\"white\")\n",
|
| 310 |
-
"\n",
|
| 311 |
-
"# set the physics layout of the network\n",
|
| 312 |
-
"got_net.barnes_hut()\n",
|
| 313 |
-
"got_data = pd.read_csv(\"https://www.macalester.edu/~abeverid/data/stormofswords.csv\")\n",
|
| 314 |
-
"\n",
|
| 315 |
-
"sources = got_data['Source']\n",
|
| 316 |
-
"targets = got_data['Target']\n",
|
| 317 |
-
"weights = got_data['Weight']\n",
|
| 318 |
-
"\n",
|
| 319 |
-
"edge_data = zip(sources, targets, weights)\n",
|
| 320 |
-
"\n",
|
| 321 |
-
"for e in edge_data:\n",
|
| 322 |
-
" src = e[0]\n",
|
| 323 |
-
" dst = e[1]\n",
|
| 324 |
-
" w = e[2]\n",
|
| 325 |
-
"\n",
|
| 326 |
-
" got_net.add_node(src, src, title=src)\n",
|
| 327 |
-
" got_net.add_node(dst, dst, title=dst)\n",
|
| 328 |
-
" got_net.add_edge(src, dst, value=w)\n",
|
| 329 |
-
"\n",
|
| 330 |
-
"neighbor_map = got_net.get_adj_list()\n",
|
| 331 |
-
"\n",
|
| 332 |
-
"# add neighbor data to node hover data\n",
|
| 333 |
-
"for node in got_net.nodes:\n",
|
| 334 |
-
" node[\"title\"] += \" Neighbors:<br>\" + \"<br>\".join(neighbor_map[node[\"id\"]])\n",
|
| 335 |
-
" node[\"value\"] = len(neighbor_map[node[\"id\"]]) # this value attrribute for the node affects node size\n",
|
| 336 |
-
"\n",
|
| 337 |
-
"got_net.show(\"example.html\")"
|
| 338 |
-
]
|
| 339 |
-
},
|
| 340 |
-
{
|
| 341 |
-
"cell_type": "markdown",
|
| 342 |
-
"metadata": {},
|
| 343 |
-
"source": [
|
| 344 |
-
"### Experimenting with options UI\n",
|
| 345 |
-
"Scroll down underneath the graph to play around with the physics settings to acheive optimal layout and behavior. You can use the generate options button to display the JSON representation of the configuration."
|
| 346 |
-
]
|
| 347 |
-
},
|
| 348 |
-
{
|
| 349 |
-
"cell_type": "code",
|
| 350 |
-
"execution_count": 9,
|
| 351 |
-
"metadata": {},
|
| 352 |
-
"outputs": [
|
| 353 |
-
{
|
| 354 |
-
"data": {
|
| 355 |
-
"text/html": [
|
| 356 |
-
"\n",
|
| 357 |
-
" <iframe\n",
|
| 358 |
-
" width=\"100%\"\n",
|
| 359 |
-
" height=\"750px\"\n",
|
| 360 |
-
" src=\"example.html\"\n",
|
| 361 |
-
" frameborder=\"0\"\n",
|
| 362 |
-
" allowfullscreen\n",
|
| 363 |
-
" \n",
|
| 364 |
-
" ></iframe>\n",
|
| 365 |
-
" "
|
| 366 |
-
],
|
| 367 |
-
"text/plain": [
|
| 368 |
-
"<IPython.lib.display.IFrame at 0x7f87da76ee50>"
|
| 369 |
-
]
|
| 370 |
-
},
|
| 371 |
-
"execution_count": 9,
|
| 372 |
-
"metadata": {},
|
| 373 |
-
"output_type": "execute_result"
|
| 374 |
-
}
|
| 375 |
-
],
|
| 376 |
-
"source": [
|
| 377 |
-
"got_net.show_buttons(filter_=\"physics\")\n",
|
| 378 |
-
"got_net.show(\"example.html\")"
|
| 379 |
-
]
|
| 380 |
-
},
|
| 381 |
-
{
|
| 382 |
-
"cell_type": "code",
|
| 383 |
-
"execution_count": 13,
|
| 384 |
-
"metadata": {},
|
| 385 |
-
"outputs": [],
|
| 386 |
-
"source": [
|
| 387 |
-
"got_net.set_options('''var options = {\n",
|
| 388 |
-
" \"physics\": {\n",
|
| 389 |
-
" \"barnesHut\": {\n",
|
| 390 |
-
" \"gravitationalConstant\": -80000,\n",
|
| 391 |
-
" \"springLength\": 250,\n",
|
| 392 |
-
" \"springConstant\": 0.001\n",
|
| 393 |
-
" },\n",
|
| 394 |
-
" \"maxVelocity\": 34,\n",
|
| 395 |
-
" \"minVelocity\": 0.75\n",
|
| 396 |
-
" }\n",
|
| 397 |
-
"}''')"
|
| 398 |
-
]
|
| 399 |
-
},
|
| 400 |
-
{
|
| 401 |
-
"cell_type": "code",
|
| 402 |
-
"execution_count": 10,
|
| 403 |
-
"metadata": {},
|
| 404 |
-
"outputs": [],
|
| 405 |
-
"source": [
|
| 406 |
-
"import networkx as nx"
|
| 407 |
-
]
|
| 408 |
-
},
|
| 409 |
-
{
|
| 410 |
-
"cell_type": "code",
|
| 411 |
-
"execution_count": 11,
|
| 412 |
-
"metadata": {},
|
| 413 |
-
"outputs": [
|
| 414 |
-
{
|
| 415 |
-
"data": {
|
| 416 |
-
"text/html": [
|
| 417 |
-
"\n",
|
| 418 |
-
" <iframe\n",
|
| 419 |
-
" width=\"100%\"\n",
|
| 420 |
-
" height=\"750px\"\n",
|
| 421 |
-
" src=\"nx.html\"\n",
|
| 422 |
-
" frameborder=\"0\"\n",
|
| 423 |
-
" allowfullscreen\n",
|
| 424 |
-
" \n",
|
| 425 |
-
" ></iframe>\n",
|
| 426 |
-
" "
|
| 427 |
-
],
|
| 428 |
-
"text/plain": [
|
| 429 |
-
"<IPython.lib.display.IFrame at 0x7f88443e75b0>"
|
| 430 |
-
]
|
| 431 |
-
},
|
| 432 |
-
"execution_count": 11,
|
| 433 |
-
"metadata": {},
|
| 434 |
-
"output_type": "execute_result"
|
| 435 |
-
}
|
| 436 |
-
],
|
| 437 |
-
"source": [
|
| 438 |
-
"nx_graph = nx.cycle_graph(10)\n",
|
| 439 |
-
"nx_graph.nodes[1]['title'] = 'Number 1'\n",
|
| 440 |
-
"nx_graph.nodes[1]['group'] = 1\n",
|
| 441 |
-
"nx_graph.nodes[3]['title'] = 'I belong to a different group!'\n",
|
| 442 |
-
"nx_graph.nodes[3]['group'] = 10\n",
|
| 443 |
-
"nx_graph.add_node(20, size=20, title='couple', group=2)\n",
|
| 444 |
-
"nx_graph.add_node(21, size=15, title='couple', group=2)\n",
|
| 445 |
-
"nx_graph.add_edge(20, 21, weight=5)\n",
|
| 446 |
-
"nx_graph.add_node(25, size=25, label='lonely', title='lonely node', group=3)\n",
|
| 447 |
-
"\n",
|
| 448 |
-
"nt = Network(notebook=True, height=\"750px\", width=\"100%\")\n",
|
| 449 |
-
"\n",
|
| 450 |
-
"nt.from_nx(nx_graph)\n",
|
| 451 |
-
"nt.show(\"nx.html\")"
|
| 452 |
-
]
|
| 453 |
-
},
|
| 454 |
-
{
|
| 455 |
-
"cell_type": "code",
|
| 456 |
-
"execution_count": null,
|
| 457 |
-
"metadata": {},
|
| 458 |
-
"outputs": [],
|
| 459 |
-
"source": []
|
| 460 |
-
}
|
| 461 |
-
],
|
| 462 |
-
"metadata": {
|
| 463 |
-
"kernelspec": {
|
| 464 |
-
"display_name": "Python 3",
|
| 465 |
-
"language": "python",
|
| 466 |
-
"name": "python3"
|
| 467 |
-
},
|
| 468 |
-
"language_info": {
|
| 469 |
-
"codemirror_mode": {
|
| 470 |
-
"name": "ipython",
|
| 471 |
-
"version": 3
|
| 472 |
-
},
|
| 473 |
-
"file_extension": ".py",
|
| 474 |
-
"mimetype": "text/x-python",
|
| 475 |
-
"name": "python",
|
| 476 |
-
"nbconvert_exporter": "python",
|
| 477 |
-
"pygments_lexer": "ipython3",
|
| 478 |
-
"version": "3.8.10"
|
| 479 |
-
}
|
| 480 |
-
},
|
| 481 |
-
"nbformat": 4,
|
| 482 |
-
"nbformat_minor": 2
|
| 483 |
-
}
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pyvis/notebooks/test.dot
DELETED
|
@@ -1,9 +0,0 @@
|
|
| 1 |
-
digraph {
|
| 2 |
-
a [label=12, entity_id=12, entity_class="truck"];
|
| 3 |
-
b [label=7, entity_id=7,entity_class="bike"];
|
| 4 |
-
c [label=3, entity_id=3, entity_class="car"];
|
| 5 |
-
a -> b[label="solid edge"];
|
| 6 |
-
a -> b [label="dashed edge", style=dashed];
|
| 7 |
-
a -> c [label="dashed edge", style=dashed];
|
| 8 |
-
a -> c [label="dotted edge", style=dotted];
|
| 9 |
-
}
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