notebooks/mpld3_newjs.ipynb

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from mpld3 import enable_notebook\n",
      "enable_notebook(mpld3_url='/static/js/mpld3.js')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot([0,1],[2,3])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "[<matplotlib.lines.Line2D at 0x108131e90>]"
       ]
      },
      {
       "html": [
        "\n",
        "<style>\n",
        "\n",
        "</style>\n",
        "\n",
        "<div id=\"fig1063344302796327098156076\"></div>\n",
        "<script>\n",
        "function mpld3_load_lib(url, callback){\n",
        "  var s = document.createElement('script');\n",
        "  s.src = url;\n",
        "  s.async = true;\n",
        "  s.onreadystatechange = s.onload = callback;\n",
        "  s.onerror = function(){console.warn(\"failed to load library \" + url);};\n",
        "  document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
        "}\n",
        "\n",
        "function create_fig1063344302796327098156076(){\n",
        "  \n",
        "  mpld3.draw_figure(\"fig1063344302796327098156076\", {\"width\": 480.0, \"axes\": [{\"xlim\": [0.0, 1.0], \"yscale\": \"linear\", \"axesbg\": \"#EEEEEE\", \"texts\": [], \"zoomable\": true, \"images\": [], \"xdomain\": [0.0, 1.0], \"ylim\": [2.0, 3.2000000000000002], \"paths\": [], \"sharey\": [], \"sharex\": [], \"axesbgalpha\": null, \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"color\": \"#000000\", \"alpha\": 1.0, \"dasharray\": \"2,2\", \"gridOn\": true}, \"fontsize\": 10.0, \"position\": \"bottom\", \"nticks\": 6, \"tickvalues\": null}, {\"scale\": \"linear\", \"tickformat\": null, \"grid\": {\"color\": \"#000000\", \"alpha\": 1.0, \"dasharray\": \"2,2\", \"gridOn\": true}, \"fontsize\": 10.0, \"position\": \"left\", \"nticks\": 8, \"tickvalues\": null}], \"lines\": [{\"color\": \"#348ABD\", \"yindex\": 1, \"coordinates\": \"data\", \"dasharray\": \"10,0\", \"zorder\": 2, \"alpha\": 1, \"xindex\": 0, \"linewidth\": 1.0, \"data\": \"data01\", \"id\": \"106334430438032\"}], \"markers\": [], \"id\": \"106334430281168\", \"ydomain\": [2.0, 3.2000000000000002], \"collections\": [], \"xscale\": \"linear\", \"bbox\": [0.125, 0.125, 0.77500000000000002, 0.77500000000000002]}], \"data\": {\"data01\": [[0.0, 2.0], [1.0, 3.0]]}, \"id\": \"106334430279632\", \"toolbar\": [\"reset\", \"move\"], \"height\": 320.0});\n",
        "}\n",
        "\n",
        "if(typeof(mpld3) !== \"undefined\"){\n",
        "   // already loaded: just create the figure\n",
        "   create_fig1063344302796327098156076();\n",
        "}else if(typeof define === \"function\" && define.amd){\n",
        "   // require.js is available: use it to load d3/mpld3\n",
        "   require.config({paths: {d3: \"http://d3js.org/d3.v3.min\"}});\n",
        "   require([\"d3\"], function(d3){\n",
        "      window.d3 = d3;\n",
        "      mpld3_load_lib(\"/static/js/mpld3.js\", create_fig1063344302796327098156076);\n",
        "    });\n",
        "}else{\n",
        "    // require.js not available: dynamically load d3 & mpld3\n",
        "    mpld3_load_lib(\"http://d3js.org/d3.v3.min.js\", function(){\n",
        "        mpld3_load_lib(\"/static/js/mpld3.js\", create_fig1063344302796327098156076);})\n",
        "}\n",
        "</script>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAXwAAAECCAYAAAD9z2x7AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nwCciMggO+EREBsEBn4jIIP4fAr1d9MmONLkAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10810b3d0>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}