DataAnalysis5.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import numpy as np\n",
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAd8AAAFBCAYAAAA2bKVrAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f90659b83d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = nx.karate_club_graph()\n",
    "nx.draw(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from networkx.readwrite import json_graph\n",
    "data = json_graph.node_link_data(g)\n",
    "with open('graph.json', 'w') as f:\n",
    "     json.dump(data, f, indent=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div id=\"d3-example\"></div>\n",
       "<style>\n",
       ".node {stroke: #fff; stroke-width: 1.5px;}\n",
       ".link {stroke: #999; stroke-opacity: .6;}\n",
       "</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%html\n",
    "<div id=\"d3-example\"></div>\n",
    "<style>\n",
    ".node {stroke: #fff; stroke-width: 1.5px;}\n",
    ".link {stroke: #999; stroke-opacity: .6;}\n",
    "</style>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "// We load the d3.js library from the Web.\n",
       "require.config({paths: {d3: \"http://d3js.org/d3.v3.min\"}});\n",
       "require([\"d3\"], function(d3) {\n",
       "    // The code in this block is executed when the \n",
       "    // d3.js library has been loaded.\n",
       "    \n",
       "    // First, we specify the size of the canvas containing\n",
       "    // the visualization (size of the <div> element).\n",
       "    var width = 300,\n",
       "        height = 300;\n",
       "\n",
       "    // We create a color scale.\n",
       "    var color = d3.scale.category10();\n",
       "\n",
       "    // We create a force-directed dynamic graph layout.\n",
       "    var force = d3.layout.force()\n",
       "        .charge(-120)\n",
       "        .linkDistance(30)\n",
       "        .size([width, height]);\n",
       "\n",
       "    // In the <div> element, we create a <svg> graphic\n",
       "    // that will contain our interactive visualization.\n",
       "    var svg = d3.select(\"#d3-example\").select(\"svg\")\n",
       "    if (svg.empty()) {\n",
       "        svg = d3.select(\"#d3-example\").append(\"svg\")\n",
       "                    .attr(\"width\", width)\n",
       "                    .attr(\"height\", height);\n",
       "    }\n",
       "        \n",
       "    // We load the JSON file.\n",
       "    d3.json(\"graph.json\", function(error, graph) {\n",
       "        // In this block, the file has been loaded\n",
       "        // and the 'graph' object contains our graph.\n",
       "        \n",
       "        // We load the nodes and links in the force-directed\n",
       "        // graph.\n",
       "        force.nodes(graph.nodes)\n",
       "            .links(graph.links)\n",
       "            .start();\n",
       "\n",
       "        // We create a <line> SVG element for each link\n",
       "        // in the graph.\n",
       "        var link = svg.selectAll(\".link\")\n",
       "            .data(graph.links)\n",
       "            .enter().append(\"line\")\n",
       "            .attr(\"class\", \"link\");\n",
       "\n",
       "        // We create a <circle> SVG element for each node\n",
       "        // in the graph, and we specify a few attributes.\n",
       "        var node = svg.selectAll(\".node\")\n",
       "            .data(graph.nodes)\n",
       "            .enter().append(\"circle\")\n",
       "            .attr(\"class\", \"node\")\n",
       "            .attr(\"r\", 5)  // radius\n",
       "            .style(\"fill\", function(d) {\n",
       "                // The node color depends on the club.\n",
       "                return color(d.club); \n",
       "            })\n",
       "            .call(force.drag);\n",
       "\n",
       "        // The name of each node is the node number.\n",
       "        node.append(\"title\")\n",
       "            .text(function(d) { return d.id; });\n",
       "\n",
       "        // We bind the positions of the SVG elements\n",
       "        // to the positions of the dynamic force-directed graph,\n",
       "        // at each time step.\n",
       "        force.on(\"tick\", function() {\n",
       "            link.attr(\"x1\", function(d) { return d.source.x; })\n",
       "                .attr(\"y1\", function(d) { return d.source.y; })\n",
       "                .attr(\"x2\", function(d) { return d.target.x; })\n",
       "                .attr(\"y2\", function(d) { return d.target.y; });\n",
       "\n",
       "            node.attr(\"cx\", function(d) { return d.x; })\n",
       "                .attr(\"cy\", function(d) { return d.y; });\n",
       "        });\n",
       "    });\n",
       "});"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "// We load the d3.js library from the Web.\n",
    "require.config({paths: {d3: \"http://d3js.org/d3.v3.min\"}});\n",
    "require([\"d3\"], function(d3) {\n",
    "    // The code in this block is executed when the \n",
    "    // d3.js library has been loaded.\n",
    "    \n",
    "    // First, we specify the size of the canvas containing\n",
    "    // the visualization (size of the <div> element).\n",
    "    var width = 300,\n",
    "        height = 300;\n",
    "\n",
    "    // We create a color scale.\n",
    "    var color = d3.scale.category10();\n",
    "\n",
    "    // We create a force-directed dynamic graph layout.\n",
    "    var force = d3.layout.force()\n",
    "        .charge(-120)\n",
    "        .linkDistance(30)\n",
    "        .size([width, height]);\n",
    "\n",
    "    // In the <div> element, we create a <svg> graphic\n",
    "    // that will contain our interactive visualization.\n",
    "    var svg = d3.select(\"#d3-example\").select(\"svg\")\n",
    "    if (svg.empty()) {\n",
    "        svg = d3.select(\"#d3-example\").append(\"svg\")\n",
    "                    .attr(\"width\", width)\n",
    "                    .attr(\"height\", height);\n",
    "    }\n",
    "        \n",
    "    // We load the JSON file.\n",
    "    d3.json(\"graph.json\", function(error, graph) {\n",
    "        // In this block, the file has been loaded\n",
    "        // and the 'graph' object contains our graph.\n",
    "        \n",
    "        // We load the nodes and links in the force-directed\n",
    "        // graph.\n",
    "        force.nodes(graph.nodes)\n",
    "            .links(graph.links)\n",
    "            .start();\n",
    "\n",
    "        // We create a <line> SVG element for each link\n",
    "        // in the graph.\n",
    "        var link = svg.selectAll(\".link\")\n",
    "            .data(graph.links)\n",
    "            .enter().append(\"line\")\n",
    "            .attr(\"class\", \"link\");\n",
    "\n",
    "        // We create a <circle> SVG element for each node\n",
    "        // in the graph, and we specify a few attributes.\n",
    "        var node = svg.selectAll(\".node\")\n",
    "            .data(graph.nodes)\n",
    "            .enter().append(\"circle\")\n",
    "            .attr(\"class\", \"node\")\n",
    "            .attr(\"r\", 5)  // radius\n",
    "            .style(\"fill\", function(d) {\n",
    "                // The node color depends on the club.\n",
    "                return color(d.club); \n",
    "            })\n",
    "            .call(force.drag);\n",
    "\n",
    "        // The name of each node is the node number.\n",
    "        node.append(\"title\")\n",
    "            .text(function(d) { return d.id; });\n",
    "\n",
    "        // We bind the positions of the SVG elements\n",
    "        // to the positions of the dynamic force-directed graph,\n",
    "        // at each time step.\n",
    "        force.on(\"tick\", function() {\n",
    "            link.attr(\"x1\", function(d) { return d.source.x; })\n",
    "                .attr(\"y1\", function(d) { return d.source.y; })\n",
    "                .attr(\"x2\", function(d) { return d.target.x; })\n",
    "                .attr(\"y2\", function(d) { return d.target.y; });\n",
    "\n",
    "            node.attr(\"cx\", function(d) { return d.x; })\n",
    "                .attr(\"cy\", function(d) { return d.y; });\n",
    "        });\n",
    "    });\n",
    "});"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}