Thesis Scratch Work.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "def writeHadoopResults(error, iterations, outputFile, inputName):\n",
    "    with open(outputFile, 'a+') as f:\n",
    "        f.write(inputName + \",hadoop,-,-,\" + iterations + \",\" + error + \",\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def calcElaspedTime(minA, secA, minB, secB):\n",
    "    if minA == minB:\n",
    "        return secB - secA\n",
    "    \n",
    "    AtoMinute = 60 - secA\n",
    "    MinDiff = minB - minA - 1\n",
    "    return AtoMinute + MinDiff*60 + secB"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "from IPython.display import display\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from collections import defaultdict\n",
    "%matplotlib notebook "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hadoopIterations(filename):\n",
    "    #TAKES OUTPUT FILE AND GRABS ITER COUNT\n",
    "    with open(filename) as f:\n",
    "        finalLine = \"\"\n",
    "        for line in f:\n",
    "            if \"final\" in line:\n",
    "                finalLine = line\n",
    "    value = finalLine.split(\"-\")[-2]\n",
    "    return int(value) + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def numberPoints(goal, dim):\n",
    "    GB = 1024**3\n",
    "    WRITE_PT = 18\n",
    "    PERCENTAGE = .15\n",
    "    \n",
    "    ptsNeed = goal*GB / WRITE_PT\n",
    "    pairsNeed = ptsNeed / dim\n",
    "    \n",
    "    small = math.ceil( pairsNeed * PERCENTAGE)\n",
    "    big = math.floor( pairsNeed * (1 - PERCENTAGE))\n",
    "    return small, big\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2685, 15211)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numberPoints(1.5, 5000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "math.ceil(1.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15211.342506666664\n"
     ]
    }
   ],
   "source": [
    "GB = 1024**3\n",
    "WRITE_PT = 18\n",
    "GOAL_GB = 1.5\n",
    "DIM = 5000\n",
    "\n",
    "ptsNeeded = GOAL_GB * GB / WRITE_PT\n",
    "pairsNeed = ptsNeeded / DIM\n",
    "print(pairsNeed*(1-.15))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17895.697066666664\n"
     ]
    }
   ],
   "source": [
    "print(pairsNeed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hadoopIterations(\"./hadoop/iter_count.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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5.107161933622145 4.711640121429389 5.0003850903461275 5.453222018106349 4.8044169562088905 5.067633255224704 5.95484055489916 4.337472653103311 4.5572889509262815 5.633791487564742 4.612047490522745 4.981741250473726 5.747079689931774 5.01808609478681 4.243506704328633 3.4681223606637044 4.56349195712856 4.117354086297109 3.2342651847924033 4.150775132496381 6.214090875185921 3.6700115220101996 4.731980823300868 4.948086351968723 5.058933655707296 5.284434653799686 4.1119470994253735 3.29559233984945 3.968566520133143 5.267947990882004 5.591834571738536 4.915239270771055 4.585189225416184 4.794038458700266 4.799035478070329 3.2489755932811075 6.559406657750479 6.033385283233082 4.624280552371032 6.926855673623012 4.232514993768072 4.587905013855733 3.7650742962920454 3.838522265427021 6.100037752544791 5.151468498854594 3.9586426387410043 4.967685956716279 3.619951411266702 3.4849766557719946 3.9583271958639528 6.247651331443137 5.959842771242304 5.318745203008604 5.468580545726114 5.76101573379136 3.847296701793569 5.588556251620332 4.024745304036841 4.560667031269623 5.7731867899764815 2.9511815878074175 5.537030025253495 7.356106385133163 2.862566137432488 4.447217555492668 3.8657680629371693 4.225736942422648 3.589627776045794 6.145780251955099 5.14000586013195 6.290405475286594 6.8358003310090965 6.1125117119907575 5.157992479466143 5.148808559803459 5.6518619084547534 4.65146558920812 4.794367939206948 5.3704012102438945 3.7773692054867727 4.231609953065364 4.972809381708661 4.1880782919842385 5.106853977066054 5.150167600039611 4.296022495688116 5.071132799254925 5.959480338367532 5.197946689071745 6.424241449480926 4.828292337484196 4.7143589866480475 3.498420076954444 3.804670320604105 6.3435546690658295 4.481229185833716 5.217301704689452 7.413358157722488 5.2003224578628675 5.264592463242039 3.538943292258557 3.7813424513121543 5.847533920664151 5.812326361799725 4.093408271141845 3.932666085576555 3.1454119989480054 4.714283600288587 4.102810605513398 5.737874014238193 4.895139220325745 5.377884657852962 5.437140248878401 3.345071408489459 5.14804556794055 4.288796171922298 5.461609115631851 5.562864362516972 4.758537514746997 4.749089338189146 4.865001036448315 3.3811565973855675 6.057005451996302 6.167685903072666 4.118165713862063 3.8087069044373822 6.871205782654014 6.2222960330211565 3.4097271539169425 4.140216881716379 4.4176744000248656 5.895525852263738 4.752824834988323 4.292045106206717 5.0058111102340295 4.599391759538923 4.853506861341597 5.254058602742497 5.7320164004111325 4.067639222517614 5.594179135049775 5.618364965454559 4.376348299349563 4.254016916714103 4.101458933208516 3.35666477637117 5.612712794960469 2.501700030369868 5.681112132781722 4.3705384656027135 5.466602489485247 5.885121571416462 3.178403605420324 5.961388490309554 6.4811246879060365 4.122988996167404 7.191633046144121 7.346424197100714 5.960489913857631 5.2898976549976755 4.569785758287521 5.723248474786238 7.25784463695099 6.926925850680634 4.405771139388065 5.652686790899304\n",
      "\n"
     ]
    }
   ],
   "source": [
    "r = np.random.normal(5, 1, 5000).tolist()\n",
    "s = ' '.join(map(str, r))  + \"\\n\"\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "ename": "OSError",
     "evalue": "[Errno 5] Input/output error",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-8-ba9a63e87b29>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0m_\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10000\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m         \u001b[0ml\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrandom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnormal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5000\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtolist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m         \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0;34m' '\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ml\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\"\\n\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"ugh.txt\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'a+'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mOSError\u001b[0m: [Errno 5] Input/output error"
     ]
    }
   ],
   "source": [
    "with open(\"ugh.txt\", \"w\") as f:\n",
    "    for _ in range(10000):\n",
    "        l = np.random.normal(3, 1, 5000).tolist()\n",
    "        f.write( ' '.join(map(str, l)) + \"\\n\")\n",
    "\n",
    "with open(\"ugh.txt\", 'a+') as f:\n",
    "    for _ in range(1302):\n",
    "        r = np.random.normal(5, 1, 5000).tolist()\n",
    "        f.write( ' '.join(map(str, r))  + \"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hadoopGatherCanopies(filename):\n",
    "    #GATHER CLUSTER DATA POINTS\n",
    "    with open(filename) as f:\n",
    "        clusters = {}\n",
    "        for line in f:\n",
    "            if line[0] is '{':\n",
    "                center = line.split('\"c\":[')[1]\n",
    "                center = center.split(\"]\")[0]\n",
    "                clusters[center] = []\n",
    "            elif 'distance' in line:\n",
    "                values = line.strip().split(': [')[-1][:-1]\n",
    "                clusters[center].append(values)\n",
    "    return clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def hadoopError(filename):\n",
    "    with open(filename) as f:\n",
    "        error = 0\n",
    "        for line in f:\n",
    "            if 'distance' in line:\n",
    "                value = line.split(\"distance=\")[1]\n",
    "                value = value.split(']:')[0]\n",
    "                error += float(value)\n",
    "    return error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plotClusters(canopies, name):\n",
    "    #PLOTS HADOOP/SPARK CLUSTERS --ONLY USE IF R^3\n",
    "    fig = plt.figure()\n",
    "    ax = fig.add_subplot(111, projection='3d')\n",
    "    ax.set_xlabel('x')\n",
    "    ax.set_ylabel('y')\n",
    "    ax.set_zlabel('z')\n",
    "\n",
    "    for k, v in canopies.items():\n",
    "        x,y,z = [], [], []\n",
    "        for pt in v:\n",
    "            X,Y,Z = list(map( float, pt.split(',') ) )\n",
    "            x.append(X)\n",
    "            y.append(Y)\n",
    "            z.append(Z)\n",
    "        ax.scatter(x, y, z)\n",
    "\n",
    "    plt.title(name + \" Clusters\")\n",
    "    plt.savefig(name + \".png\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [],
   "source": [
    "hadoopCanopies = hadoopGatherCanopies(\"./hadoop/results.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "493.1828392436146"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hadoopError(\"./hadoop/results.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotClusters(hadoopCanopies, \"Hadoop\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def sparkGatherCanopies(centerFile, pointsFile):\n",
    "    with open(centerFile) as f:\n",
    "        centers = {}\n",
    "        for line in f:\n",
    "            values = line.strip().split('],')\n",
    "            index = int( values[1][:-1] )\n",
    "            coord = values[0][2:]\n",
    "            centers[index] = coord\n",
    "    with open(pointsFile) as f:\n",
    "        points = defaultdict(list)\n",
    "        for line in f:\n",
    "            values = line.strip().split(\",[\")\n",
    "            index = int(values[0][1:])\n",
    "            coord = values[1][:-2]\n",
    "            points[index].append(coord)\n",
    "    canopies = {}\n",
    "    for k, v in centers.items():\n",
    "        canopies[v] = points[k]\n",
    "    return canopies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "sparkCanopy = sparkGatherCanopies(\"./spark/centers.txt\", \"./spark/points.txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotClusters(sparkCanopy, \"Spark\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sparkResults(filename, output):\n",
    "    with open(filename) as f:\n",
    "        current = f.readlines()[-4:]\n",
    "        buildTime = current[0].strip().split(\" \")[-2] \n",
    "        iterTime = current[1].strip().split(\" \")[-2] \n",
    "        iterations = current[2].strip().split(\" \")[-2] \n",
    "        cost = current[3].strip()[:-1].split(\" \")[-1]\n",
    "    with open(output, 'a+') as f:\n",
    "        f.write(\"spark,\" + buildTime + \",\" + iterTime + \",\" + iterations + \",\" + cost + \",\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "sparkResults(\"./spark/SparkDriver.log\", \"results.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}