sentiment-text.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sentiment scores for specific topics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import os\n",
    "import re\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from IPython.display import clear_output\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATADIRECTORYSENT = \"../data/sentiment/ALL-pattern/\"\n",
    "DATADIRECTORYTEXT = \"../data/text/\"\n",
    "SENTIMENT = \"sentiment\"\n",
    "COUNT = \"count\"\n",
    "DATA = \"data\"\n",
    "LABEL = \"label\"\n",
    "HIGHLIGHT = \"highlight\"\n",
    "HIGHLIGHTLABEL = \"highlightlabel\"\n",
    "IDSTR = \"id_str\"\n",
    "TEXT = \"text\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def selectSentText(dfSent,dfText,patternText):\n",
    "    sentimentScores = [] \n",
    "    for key in dfSent.index:\n",
    "        if key in dfText.index and re.search(patternText,dfText.loc[key][TEXT],flags=re.IGNORECASE):\n",
    "            sentimentScores.append(dfSent.loc[key][1])\n",
    "    return(sentimentScores)\n",
    "\n",
    "def getSentimentPerHourText(sentDirectory,textDirectory,patternText,patternDate=\"\"):\n",
    "    fileListSent = sorted(os.listdir(sentDirectory))\n",
    "    fileListText = sorted(os.listdir(textDirectory))\n",
    "    sentimentPerHour = {}\n",
    "    for inFileName in fileListSent:\n",
    "        if re.search(patternDate,inFileName) and re.search(r\"2*z\",inFileName) and inFileName in fileListText:\n",
    "            if re.search(\"-00\",inFileName):\n",
    "                clear_output(wait=True)\n",
    "                print(inFileName)\n",
    "            try:\n",
    "                dfSent = pd.read_csv(sentDirectory+inFileName,compression=\"gzip\",header=None,index_col=0)\n",
    "                dfText = pd.read_csv(textDirectory+inFileName,compression=\"gzip\",index_col=IDSTR)\n",
    "            except: continue\n",
    "            sentimentScores = selectSentText(dfSent,dfText,patternText)\n",
    "            if len(sentimentScores) > 0:\n",
    "                hour = inFileName[0:11]\n",
    "                sentimentPerHour[hour] = { SENTIMENT:np.average(sentimentScores), COUNT:len(sentimentScores) }\n",
    "    sentimentPerHour = {key:sentimentPerHour[key] for key in sorted(sentimentPerHour.keys())}\n",
    "    return(sentimentPerHour)\n",
    "\n",
    "def getSentimentPerHourAll(sentDirectory,patternDate=\"\"):\n",
    "    fileListSent = sorted(os.listdir(sentDirectory))\n",
    "    sentimentPerHour = {}\n",
    "    for inFileName in fileListSent:\n",
    "        if re.search(patternDate,inFileName) and re.search(r\"2*z\",inFileName):\n",
    "            if re.search(\"-00\",inFileName):\n",
    "                clear_output(wait=True)\n",
    "                print(inFileName)\n",
    "            try:\n",
    "                dfSent = pd.read_csv(sentDirectory+inFileName,compression=\"gzip\",header=None,index_col=0)\n",
    "            except: continue\n",
    "            if len(dfSent) > 0:\n",
    "                hour = inFileName[0:11]\n",
    "                sentimentPerHour[hour] = { SENTIMENT:np.average(dfSent[1]), COUNT:len(dfSent) }\n",
    "    sentimentPerHour = {key:sentimentPerHour[key] for key in sorted(sentimentPerHour.keys())}\n",
    "    return(sentimentPerHour)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def makeSentimentPerDay(sentimentPerHour):\n",
    "    sentimentPerDay = {}\n",
    "    for hour in sentimentPerHour:\n",
    "        day = re.sub(\"..$\",\"12\",hour)\n",
    "        if not day in sentimentPerDay: sentimentPerDay[day] = {SENTIMENT:0,COUNT:0}\n",
    "        sentimentPerDay[day][SENTIMENT] += sentimentPerHour[hour][SENTIMENT]*sentimentPerHour[hour][COUNT]\n",
    "        sentimentPerDay[day][COUNT] += sentimentPerHour[hour][COUNT]\n",
    "    for day in sentimentPerDay:\n",
    "        sentimentPerDay[day][SENTIMENT] /= sentimentPerDay[day][COUNT]\n",
    "    return(sentimentPerDay)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "DATEFORMATHOUR = \"%Y%m%d-%H\"\n",
    "DEFAULTTITLE = \"Sentiment scores of Dutch tweets\"\n",
    "\n",
    "def visualizeSentiment(dataSources,title=DEFAULTTITLE):\n",
    "    fig,ax = plt.subplots(figsize=(9,4))\n",
    "    for i in range(0,len(dataSources)):\n",
    "        data = dataSources[i][DATA]\n",
    "        label = dataSources[i][LABEL]\n",
    "        lineData= ax.plot_date([datetime.datetime.strptime(key,DATEFORMATHOUR) for key in data],\\\n",
    "                     [data[key] for key in data],xdate=True,fmt=\"-\",label=label)\n",
    "        if HIGHLIGHT in dataSources[i]:\n",
    "            highlight = dataSources[i][HIGHLIGHT]\n",
    "            highlightlabel = dataSources[i][HIGHLIGHTLABEL]\n",
    "            color = lineData[-1].get_color()\n",
    "            ax.plot_date([datetime.datetime.strptime(key,DATEFORMATHOUR) for key in highlight],\n",
    "                         [data[key] for key in highlight],\\\n",
    "                         fmt=\"o\",color=color,label=highlightlabel)\n",
    "                \n",
    "    plt.title(title)\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    return(ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def averageSentiment(sentimentScores):\n",
    "    return(np.average([sentimentScores[key][SENTIMENT] for key in sentimentScores],\\\n",
    "                      weights=[sentimentScores[key][COUNT] for key in sentimentScores]))\n",
    "\n",
    "def writeSentiment(sentimentScores,fileName):\n",
    "    pd.DataFrame(sentimentScores).T.to_csv(fileName,index_label=\"date\")\n",
    "    \n",
    "def readSentiment(fileName):\n",
    "    return(pd.read_csv(fileName,index_col=\"date\").T.to_dict())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extract sentiment scores from tweets (takes several hours)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20200522-00.out.gz\n"
     ]
    }
   ],
   "source": [
    "QUERY = \"#corona|#covid|#flattenthecurve|#blijfthuis|#rivm|#mondkapje|#huisarts|#houvol|#zorg\"\n",
    "QUERY = \"corona|covid|flattenthecurve|blijfthuis|rivm|mondkapje|huisarts|houvol|zorg\"\n",
    "SENTDIR = \"../data/sentiment/\"\n",
    "PATTERNDATE = \"\"\n",
    "\n",
    "sentimentPerHour = getSentimentPerHourText(DATADIRECTORYSENT,DATADIRECTORYTEXT,QUERY,patternDate=PATTERNDATE)\n",
    "writeSentiment(sentimentPerHour,SENTDIR+QUERY+\".csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20190531-00.out.gz\n"
     ]
    }
   ],
   "source": [
    "sentimentPerHour = getSentimentPerHourAll(DATADIRECTORYSENT+\"../2019/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " '20190310-04': {'sentiment': 0.060314965628295705, 'count': 2220},\n",
       " '20190310-05': {'sentiment': 0.06248124115782047, 'count': 2128},\n",
       " '20190310-06': {'sentiment': 0.08531078778071337, 'count': 3259},\n",
       " '20190310-07': {'sentiment': 0.08595849329641138, 'count': 8102},\n",
       " '20190310-08': {'sentiment': 0.09197342505562672, 'count': 17478},\n",
       " '20190310-09': {'sentiment': 0.0985700108695763, 'count': 25748},\n",
       " '20190310-10': {'sentiment': 0.09767746717849818, 'count': 31033},\n",
       " '20190310-11': {'sentiment': 0.08784938886313234, 'count': 33376},\n",
       " '20190310-12': {'sentiment': 0.09030839046730299, 'count': 33623},\n",
       " '20190310-13': {'sentiment': 0.08647742461121345, 'count': 35144},\n",
       " '20190310-14': {'sentiment': 0.08897230528898491, 'count': 34838},\n",
       " '20190310-15': {'sentiment': 0.09542820301271615, 'count': 34636},\n",
       " '20190310-16': {'sentiment': 0.10352477542517387, 'count': 33830},\n",
       " '20190310-17': {'sentiment': 0.10802301496159915, 'count': 31234},\n",
       " '20190310-18': {'sentiment': 0.10630532765876109, 'count': 30447},\n",
       " '20190310-19': {'sentiment': 0.10974048569219715, 'count': 31321},\n",
       " '20190310-20': {'sentiment': 0.10573185724280727, 'count': 33663},\n",
       " '20190310-21': {'sentiment': 0.10290671007541562, 'count': 35030},\n",
       " '20190310-22': {'sentiment': 0.09195125429423963, 'count': 30001},\n",
       " '20190310-23': {'sentiment': 0.09011874528782346, 'count': 20400},\n",
       " '20190311-00': {'sentiment': 0.0830571811634504, 'count': 11165},\n",
       " '20190311-01': {'sentiment': 0.07367803376507008, 'count': 5060},\n",
       " '20190311-02': {'sentiment': 0.07554298357866272, 'count': 2887},\n",
       " '20190311-03': {'sentiment': 0.06768252136526695, 'count': 2031},\n",
       " '20190311-04': {'sentiment': 0.08455556196484935, 'count': 1946},\n",
       " '20190311-05': {'sentiment': 0.0869105123574832, 'count': 2958},\n",
       " '20190311-06': {'sentiment': 0.08922587932544879, 'count': 7367},\n",
       " '20190311-07': {'sentiment': 0.09095566198084151, 'count': 16426},\n",
       " '20190311-08': {'sentiment': 0.0983692901805781, 'count': 23384},\n",
       " '20190311-09': {'sentiment': 0.09480151491221567, 'count': 26982},\n",
       " '20190311-10': {'sentiment': 0.09327833918787444, 'count': 27655},\n",
       " '20190311-11': {'sentiment': 0.09051166299390352, 'count': 28517},\n",
       " '20190311-12': {'sentiment': 0.08685003323686254, 'count': 29771},\n",
       " '20190311-13': {'sentiment': 0.09036529452920852, 'count': 28259},\n",
       " '20190311-14': {'sentiment': 0.08969669379008542, 'count': 25687},\n",
       " '20190311-15': {'sentiment': 0.0886834043099821, 'count': 27113},\n",
       " '20190311-16': {'sentiment': 0.08771615957559001, 'count': 29806},\n",
       " '20190311-17': {'sentiment': 0.09768438886651219, 'count': 29999},\n",
       " '20190311-18': {'sentiment': 0.08589098782488361, 'count': 32669},\n",
       " '20190311-19': {'sentiment': 0.09210432138445604, 'count': 34882},\n",
       " '20190311-20': {'sentiment': 0.09703184784680334, 'count': 35301},\n",
       " '20190311-21': {'sentiment': 0.09512661158842434, 'count': 34658},\n",
       " '20190311-22': {'sentiment': 0.09163044276159299, 'count': 32429},\n",
       " '20190311-23': {'sentiment': 0.07640398812869166, 'count': 23997},\n",
       " '20190312-00': {'sentiment': 0.07191691408907062, 'count': 12745},\n",
       " '20190312-01': {'sentiment': 0.06013773432925779, 'count': 5454},\n",
       " '20190312-02': {'sentiment': 0.05232650599137919, 'count': 2798},\n",
       " '20190312-03': {'sentiment': 0.046759519571632525, 'count': 2079},\n",
       " '20190312-04': {'sentiment': 0.07115566131215953, 'count': 1777},\n",
       " '20190312-05': {'sentiment': 0.07456833854151237, 'count': 3430},\n",
       " '20190312-06': {'sentiment': 0.0919956885489627, 'count': 8415},\n",
       " '20190312-07': {'sentiment': 0.08672908866914339, 'count': 19487},\n",
       " '20190312-08': {'sentiment': 0.08213131395484477, 'count': 26106},\n",
       " '20190312-09': {'sentiment': 0.08336555824490735, 'count': 29113},\n",
       " '20190312-10': {'sentiment': 0.08070974392770555, 'count': 29232},\n",
       " '20190312-11': {'sentiment': 0.08069436505249075, 'count': 27975},\n",
       " '20190312-12': {'sentiment': 0.08096178285550688, 'count': 29610},\n",
       " '20190312-13': {'sentiment': 0.0825145348331151, 'count': 28470},\n",
       " '20190312-14': {'sentiment': 0.07483193802397867, 'count': 28037},\n",
       " '20190312-15': {'sentiment': 0.07640498633055284, 'count': 28179},\n",
       " '20190312-16': {'sentiment': 0.07915518651697337, 'count': 32311},\n",
       " '20190312-17': {'sentiment': 0.0795823839440217, 'count': 33318},\n",
       " '20190312-18': {'sentiment': 0.07953234601193006, 'count': 33405},\n",
       " '20190312-19': {'sentiment': 0.08532997289929886, 'count': 36502},\n",
       " '20190312-20': {'sentiment': 0.08539365369376278, 'count': 38637},\n",
       " '20190312-21': {'sentiment': 0.0836740604453157, 'count': 37779},\n",
       " '20190312-22': {'sentiment': 0.09188621924721871, 'count': 37809},\n",
       " '20190312-23': {'sentiment': 0.07782405759629775, 'count': 26914},\n",
       " '20190313-00': {'sentiment': 0.06634952531043936, 'count': 14091},\n",
       " '20190313-01': {'sentiment': 0.06778373901715214, 'count': 5957},\n",
       " '20190313-02': {'sentiment': 0.06901699991339129, 'count': 2961},\n",
       " '20190313-03': {'sentiment': 0.057064737681777444, 'count': 2459},\n",
       " '20190313-04': {'sentiment': 0.0779763801501749, 'count': 2028},\n",
       " '20190313-05': {'sentiment': 0.0861981483296164, 'count': 2984},\n",
       " '20190313-06': {'sentiment': 0.09731198428675905, 'count': 8518},\n",
       " '20190313-07': {'sentiment': 0.08967467529287797, 'count': 19822},\n",
       " '20190313-08': {'sentiment': 0.0864944901308613, 'count': 27516},\n",
       " '20190313-09': {'sentiment': 0.08683087994224496, 'count': 31090},\n",
       " '20190313-10': {'sentiment': 0.08681599556297252, 'count': 31301},\n",
       " '20190313-11': {'sentiment': 0.08317593416349027, 'count': 31921},\n",
       " '20190313-12': {'sentiment': 0.08498141690350466, 'count': 33424},\n",
       " '20190313-13': {'sentiment': 0.08226830160440138, 'count': 34575},\n",
       " '20190313-14': {'sentiment': 0.07993025188182135, 'count': 33533},\n",
       " '20190313-15': {'sentiment': 0.07574373995688176, 'count': 32703},\n",
       " '20190313-16': {'sentiment': 0.08084311983156646, 'count': 33992},\n",
       " '20190313-17': {'sentiment': 0.0784419410921271, 'count': 33629},\n",
       " '20190313-18': {'sentiment': 0.08320876918648433, 'count': 34528},\n",
       " '20190313-19': {'sentiment': 0.08738648218961312, 'count': 38040},\n",
       " '20190313-20': {'sentiment': 0.08792808376727258, 'count': 40980},\n",
       " '20190313-21': {'sentiment': 0.0855885410400609, 'count': 37744},\n",
       " '20190313-22': {'sentiment': 0.09086985351507144, 'count': 37399},\n",
       " '20190313-23': {'sentiment': 0.08341950243610464, 'count': 27152},\n",
       " '20190314-00': {'sentiment': 0.0693616807944751, 'count': 13660},\n",
       " '20190314-01': {'sentiment': 0.06717494199283232, 'count': 5462},\n",
       " '20190314-02': {'sentiment': 0.06582566493949778, 'count': 3024},\n",
       " '20190314-03': {'sentiment': 0.04923362931004724, 'count': 1913},\n",
       " '20190314-04': {'sentiment': 0.06843364927403978, 'count': 2079},\n",
       " '20190314-05': {'sentiment': 0.08915750847461905, 'count': 3532},\n",
       " '20190314-06': {'sentiment': 0.08948581929380527, 'count': 9209},\n",
       " '20190314-07': {'sentiment': 0.08627355467749129, 'count': 20559},\n",
       " '20190314-08': {'sentiment': 0.09025495493753252, 'count': 28345},\n",
       " '20190314-09': {'sentiment': 0.08999631271770153, 'count': 31738},\n",
       " '20190314-10': {'sentiment': 0.08932667072333399, 'count': 32742},\n",
       " '20190314-11': {'sentiment': 0.09021797183105959, 'count': 33574},\n",
       " '20190314-12': {'sentiment': 0.08471505925933191, 'count': 34488},\n",
       " '20190314-13': {'sentiment': 0.08563774451802506, 'count': 32627},\n",
       " '20190314-14': {'sentiment': 0.08813430120914958, 'count': 29561},\n",
       " '20190314-15': {'sentiment': 0.09032226902338297, 'count': 29715},\n",
       " ...}"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "writeSentiment(sentimentPerHour,SENTDIR+\"tmp.csv\")\n",
    "sentimentPerHour"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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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       "<img 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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dummy = visualizeSentiment([{DATA:{key:sentimentPerHour[key][SENTIMENT] for key in sentimentPerHour},\n",
    "                             LABEL:QUERY+\" \"+\\\n",
    "                             str(sum([sentimentPerHour[key][COUNT] for key in sentimentPerHour]))}],\\\n",
    "                           title=DEFAULTTITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "SENTDIR = \"../data/sentiment/\"\n",
    "\n",
    "sentimentPerHour = {}\n",
    "sentimentPerDay = {}\n",
    "\n",
    "for inFileName in os.listdir(SENTDIR):\n",
    "    if re.search(r\".csv$\",inFileName):\n",
    "        query = inFileName[:-4]\n",
    "        sentimentPerHour[query] = readSentiment(SENTDIR+inFileName)\n",
    "        sentimentPerDay[query] = makeSentimentPerDay(sentimentPerHour[query])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.02805679410337243"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "averageSentiment(sentimentPerHour[\"mondkapje\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotData = []\n",
    "for term in reversed(list(sentimentPerDay.keys())):\n",
    "    plotData.append({DATA:{key:sentimentPerDay[term][key][SENTIMENT] for key in sentimentPerDay[term]},\n",
    "                             LABEL:term+\" (\"+\\\n",
    "                             str(round(sum([sentimentPerDay[term][key][COUNT]\\\n",
    "                                      for key in sentimentPerDay[term]])))+\")\"})\n",
    "    \n",
    "dummy = visualizeSentiment(plotData,title=DEFAULTTITLE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotData = []\n",
    "for term in sentimentPerDay.keys():\n",
    "    plotData.append({DATA:{key:sentimentPerDay[term][key][COUNT] for key in sentimentPerDay[term]},\n",
    "                             LABEL:term+\" (\"+\\\n",
    "                             str(round(sum([sentimentPerDay[term][key][COUNT]\\\n",
    "                                      for key in sentimentPerDay[term]])))+\")\"})\n",
    "    \n",
    "dummy = visualizeSentiment(plotData,title=\"counts of Dutch tweets per day\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check query \"test\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "INFILENAME = \"20200518-12.out.gz\"\n",
    "df = pd.read_csv(DATADIRECTORYTEXT+INFILENAME,compression=\"gzip\",index_col=IDSTR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "QUERY = \"zorg\"\n",
    "\n",
    "tokens = {}\n",
    "for key in df.index:\n",
    "    for token in df.loc[key][0].split():\n",
    "        if re.search(QUERY,token,flags=re.IGNORECASE):\n",
    "            token = token.lower()\n",
    "            if token in tokens: tokens[token] += 1\n",
    "            else: tokens[token] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'zorg': 140,\n",
       " 'zorgen': 99,\n",
       " 'zorgt': 55,\n",
       " 'gezondheidszorg': 30,\n",
       " '#zorg': 27,\n",
       " 'mantelzorgers,': 24,\n",
       " 'pgb-zorgverleners': 22,\n",
       " 'zorgvrijwilligers': 22,\n",
       " 'bezorgde': 17,\n",
       " 'geldzorgen.': 15,\n",
       " 'gezondheidszorg,': 15,\n",
       " 'nooit..\\\\n👉..verzorgingshuizen': 14,\n",
       " 'bezorgen': 13,\n",
       " 'zorg.': 13,\n",
       " 'mantelzorgers': 13,\n",
       " 'zorgen.': 11,\n",
       " 'bezorgd': 11,\n",
       " 'woonzorgcentra': 11,\n",
       " 'gezorgd': 10,\n",
       " 'zorgmedewerkers': 9,\n",
       " 'zorgvuldig': 9,\n",
       " 'zorgsector': 8,\n",
       " 'zorgverleners': 8,\n",
       " 'zorg,': 8,\n",
       " 'verzorgen': 7,\n",
       " 'zorgverslindende': 7,\n",
       " 'zorgen,': 7,\n",
       " 'thuisbezorgd': 7,\n",
       " 'geldzorgen,': 6,\n",
       " 'zorgmedewerkers,': 6,\n",
       " '@zorgmama2': 6,\n",
       " 'zorgzame': 6,\n",
       " 'bezorg': 5,\n",
       " 'zorgmedewerkers.': 5,\n",
       " '#regulierezorg': 4,\n",
       " 'zorgpersoneel': 4,\n",
       " 'verzorgingstehuis': 4,\n",
       " 'zorgde': 4,\n",
       " 'bezorgd.': 4,\n",
       " 'zorggids': 4,\n",
       " 'voorzorg': 4,\n",
       " '#ouderenzorg!': 4,\n",
       " 'bezorgen.': 3,\n",
       " 'verzorgingshuis.': 3,\n",
       " 'zorgelijk,': 3,\n",
       " 'zorgen!': 3,\n",
       " 'bezorgt': 3,\n",
       " 'zorgt:': 3,\n",
       " 'zorginstelling': 3,\n",
       " 'intérieurverzorgster': 3,\n",
       " 'verzorgende': 3,\n",
       " '#ikzorg': 3,\n",
       " 'mantelzorger': 3,\n",
       " 'zorgverlener': 3,\n",
       " 'bezorger': 3,\n",
       " 'zorg!\\\\nben': 3,\n",
       " 'zorgorganisaties': 3,\n",
       " 'zorgverzekeraar': 3,\n",
       " '#zorg’': 3,\n",
       " 'zorgtaken': 3,\n",
       " 'zorgcrisis,': 3,\n",
       " 'verzorging': 3,\n",
       " 'zorgwekkende': 3,\n",
       " 'zorginstellingen': 2,\n",
       " \"'zorg\": 2,\n",
       " '#huisartsenzorg': 2,\n",
       " 'uitvaartverzorger': 2,\n",
       " 'zorgsector,': 2,\n",
       " '#onlinezorg': 2,\n",
       " 'zorginstellingen.': 2,\n",
       " 'bezorgt.': 2,\n",
       " 'verzorgers.': 2,\n",
       " 'verzorgd': 2,\n",
       " '#vanuitkeringnaarwerkenindezorg!\\\\n\\\\nhttps://t.co/rzhiczcav9': 2,\n",
       " 'thuiszorg': 2,\n",
       " 'verzorgenden': 2,\n",
       " '#gehandicaptenzorg': 2,\n",
       " 'zorghelden': 2,\n",
       " '(jeugd)zorg.\\\\nlid': 2,\n",
       " '#jeugdzorg': 2,\n",
       " 'zorgorganisaties.': 2,\n",
       " 'zorg:': 2,\n",
       " 'zorgeloos': 2,\n",
       " 'bezorgen?': 2,\n",
       " 'zorgcoach,': 2,\n",
       " '#zorgalarm': 2,\n",
       " 'zorgverzekeringen': 2,\n",
       " 'bezorger!': 2,\n",
       " 'gezondheidzorg': 2,\n",
       " 'zorgstelsel': 2,\n",
       " 'bezorgdheid.': 2,\n",
       " '\\\\nmantelzorgers,': 2,\n",
       " 'zorgelijk': 2,\n",
       " 'zorgverzekering': 2,\n",
       " 'verzorgt': 2,\n",
       " '#samenvoordezorg': 2,\n",
       " 'zorgkundige': 2,\n",
       " \"'bezorgdheid\": 2,\n",
       " 'zorgt.\\\\ndat': 2,\n",
       " 'zorg\"': 2,\n",
       " 'zorgprofs).\\\\ndementerende': 2,\n",
       " '@treantzorg': 2,\n",
       " '#hartvoordezorg': 2,\n",
       " 'zorg)': 2,\n",
       " 'bezorgder': 2,\n",
       " 'zorgvuldigheid': 2,\n",
       " 'zorgmedewerker': 2,\n",
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     "execution_count": 50,
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