GW2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Anaconda3\\lib\\site-packages\\pandas\\io\\data.py:33: FutureWarning: \n",
      "The pandas.io.data module is moved to a separate package (pandas-datareader) and will be removed from pandas in a future version.\n",
      "After installing the pandas-datareader package (https://github.com/pydata/pandas-datareader), you can change the import ``from pandas.io import data, wb`` to ``from pandas_datareader import data, wb``.\n",
      "  FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib as plt\n",
    "import pytz\n",
    "from datetime import datetime\n",
    "\n",
    "import zipline as zp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "url = \"http://www.gw2shinies.com/api/json/history/19721\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "ename": "HTTPError",
     "evalue": "HTTP Error 500: Internal Server Error",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-4-4173be6a4339>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mecto_history\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread_json\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;32mC:\\Anaconda3\\lib\\site-packages\\pandas\\io\\json.py\u001b[0m in \u001b[0;36mread_json\u001b[1;34m(path_or_buf, orient, typ, dtype, convert_axes, convert_dates, keep_default_dates, numpy, precise_float, date_unit)\u001b[0m\n\u001b[0;32m    184\u001b[0m     \"\"\"\n\u001b[0;32m    185\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 186\u001b[1;33m     \u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0m_\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_filepath_or_buffer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath_or_buf\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    187\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcompat\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstring_types\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    188\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\site-packages\\pandas\\io\\common.py\u001b[0m in \u001b[0;36mget_filepath_or_buffer\u001b[1;34m(filepath_or_buffer, encoding, compression)\u001b[0m\n\u001b[0;32m    256\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    257\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0m_is_url\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 258\u001b[1;33m         \u001b[0mreq\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_urlopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    259\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mcompression\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'infer'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    260\u001b[0m             \u001b[0mcontent_encoding\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mheaders\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Content-Encoding'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36murlopen\u001b[1;34m(url, data, timeout, cafile, capath, cadefault, context)\u001b[0m\n\u001b[0;32m    159\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    160\u001b[0m         \u001b[0mopener\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0m_opener\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 161\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mopener\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0murl\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    162\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    163\u001b[0m \u001b[1;32mdef\u001b[0m \u001b[0minstall_opener\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mopener\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mopen\u001b[1;34m(self, fullurl, data, timeout)\u001b[0m\n\u001b[0;32m    468\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mprocessor\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprocess_response\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprotocol\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    469\u001b[0m             \u001b[0mmeth\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprocessor\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 470\u001b[1;33m             \u001b[0mresponse\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmeth\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    471\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    472\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mhttp_response\u001b[1;34m(self, request, response)\u001b[0m\n\u001b[0;32m    578\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;36m200\u001b[0m \u001b[1;33m<=\u001b[0m \u001b[0mcode\u001b[0m \u001b[1;33m<\u001b[0m \u001b[1;36m300\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    579\u001b[0m             response = self.parent.error(\n\u001b[1;32m--> 580\u001b[1;33m                 'http', request, response, code, msg, hdrs)\n\u001b[0m\u001b[0;32m    581\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    582\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mresponse\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36merror\u001b[1;34m(self, proto, *args)\u001b[0m\n\u001b[0;32m    506\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mhttp_err\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    507\u001b[0m             \u001b[0margs\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'default'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'http_error_default'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0morig_args\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 508\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_call_chain\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    509\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    510\u001b[0m \u001b[1;31m# XXX probably also want an abstract factory that knows when it makes\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36m_call_chain\u001b[1;34m(self, chain, kind, meth_name, *args)\u001b[0m\n\u001b[0;32m    440\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mhandler\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mhandlers\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    441\u001b[0m             \u001b[0mfunc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhandler\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmeth_name\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 442\u001b[1;33m             \u001b[0mresult\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    443\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mresult\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    444\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mC:\\Anaconda3\\lib\\urllib\\request.py\u001b[0m in \u001b[0;36mhttp_error_default\u001b[1;34m(self, req, fp, code, msg, hdrs)\u001b[0m\n\u001b[0;32m    586\u001b[0m \u001b[1;32mclass\u001b[0m \u001b[0mHTTPDefaultErrorHandler\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mBaseHandler\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    587\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mhttp_error_default\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mreq\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 588\u001b[1;33m         \u001b[1;32mraise\u001b[0m \u001b[0mHTTPError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mreq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfull_url\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmsg\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhdrs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfp\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    589\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    590\u001b[0m \u001b[1;32mclass\u001b[0m \u001b[0mHTTPRedirectHandler\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mBaseHandler\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mHTTPError\u001b[0m: HTTP Error 500: Internal Server Error"
     ]
    }
   ],
   "source": [
    "ecto_history = pd.read_json(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ecto_history[\"timestamp\"] = pd.to_datetime(ecto_history[\"timestamp\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'ecto_history' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-5-7f2f18adcc9a>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mecto_history\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m: name 'ecto_history' is not defined"
     ]
    }
   ],
   "source": [
    "ecto_history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d7a40b748>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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tnl+Ur/nr+s7ed1otDkdyjzC151TtQWFE9Ai++/07oHG2ktUKbY1gKRRtodXi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\nCJVDSEhISMgY/j/dFouOU86VVAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x17d7a466dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ecto_history.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x0000017D04A62630>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D073376A0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D073832B0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D073BD6A0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000017D0740D198>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D074482E8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D07490EB8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D074CCEF0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000017D0751B048>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D0754FD30>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D075651D0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D075A9780>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x0000017D075E6CF8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D07634438>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D07670CF8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x0000017D076BE9E8>]], dtype=object)"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.scatter_matrix(ecto_history, diagonal=\"hist\", figsize=(10,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>buy</th>\n",
       "      <th>demand</th>\n",
       "      <th>sell</th>\n",
       "      <th>supply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>748.000000</td>\n",
       "      <td>748.000000</td>\n",
       "      <td>748.000000</td>\n",
       "      <td>748.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>4227.192513</td>\n",
       "      <td>180823.223262</td>\n",
       "      <td>4527.169786</td>\n",
       "      <td>94641.937166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>701.270677</td>\n",
       "      <td>33827.703764</td>\n",
       "      <td>784.969740</td>\n",
       "      <td>34085.280531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2899.000000</td>\n",
       "      <td>106167.000000</td>\n",
       "      <td>3010.000000</td>\n",
       "      <td>10552.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3511.750000</td>\n",
       "      <td>154664.250000</td>\n",
       "      <td>3794.750000</td>\n",
       "      <td>69031.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4558.500000</td>\n",
       "      <td>193104.000000</td>\n",
       "      <td>4830.000000</td>\n",
       "      <td>92148.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4863.000000</td>\n",
       "      <td>206603.000000</td>\n",
       "      <td>5148.500000</td>\n",
       "      <td>117634.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5299.000000</td>\n",
       "      <td>479291.000000</td>\n",
       "      <td>5581.000000</td>\n",
       "      <td>169913.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               buy         demand         sell         supply\n",
       "count   748.000000     748.000000   748.000000     748.000000\n",
       "mean   4227.192513  180823.223262  4527.169786   94641.937166\n",
       "std     701.270677   33827.703764   784.969740   34085.280531\n",
       "min    2899.000000  106167.000000  3010.000000   10552.000000\n",
       "25%    3511.750000  154664.250000  3794.750000   69031.250000\n",
       "50%    4558.500000  193104.000000  4830.000000   92148.000000\n",
       "75%    4863.000000  206603.000000  5148.500000  117634.500000\n",
       "max    5299.000000  479291.000000  5581.000000  169913.000000"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_history.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th>buy</th>\n",
       "      <th>demand</th>\n",
       "      <th>sell</th>\n",
       "      <th>supply</th>\n",
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       "      <th>2016-05-27 23:43:01</th>\n",
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       "      <th>2016-05-27 21:28:01</th>\n",
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       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
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       "    <tr>\n",
       "      <th>2016-05-27 20:28:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 20:13:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 19:58:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 19:43:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 19:28:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
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       "    <tr>\n",
       "      <th>2016-05-27 19:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:43:02</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:28:02</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 16:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 16:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 16:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-18 08:28:01</th>\n",
       "      <td>3271</td>\n",
       "      <td>137146</td>\n",
       "      <td>3400</td>\n",
       "      <td>115865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-17 08:28:01</th>\n",
       "      <td>3188</td>\n",
       "      <td>126117</td>\n",
       "      <td>3392</td>\n",
       "      <td>107711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-15 22:58:01</th>\n",
       "      <td>3182</td>\n",
       "      <td>126117</td>\n",
       "      <td>3500</td>\n",
       "      <td>98408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-14 03:43:01</th>\n",
       "      <td>3161</td>\n",
       "      <td>118366</td>\n",
       "      <td>3162</td>\n",
       "      <td>106135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-13 01:28:01</th>\n",
       "      <td>3245</td>\n",
       "      <td>131769</td>\n",
       "      <td>3484</td>\n",
       "      <td>110922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-11 23:58:01</th>\n",
       "      <td>3255</td>\n",
       "      <td>140696</td>\n",
       "      <td>3482</td>\n",
       "      <td>100850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-10 18:58:01</th>\n",
       "      <td>3226</td>\n",
       "      <td>136678</td>\n",
       "      <td>3227</td>\n",
       "      <td>116000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-09 18:43:01</th>\n",
       "      <td>3238</td>\n",
       "      <td>139466</td>\n",
       "      <td>3364</td>\n",
       "      <td>121174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-08 18:28:01</th>\n",
       "      <td>3127</td>\n",
       "      <td>135605</td>\n",
       "      <td>3363</td>\n",
       "      <td>119693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-07 13:28:01</th>\n",
       "      <td>3212</td>\n",
       "      <td>122079</td>\n",
       "      <td>3214</td>\n",
       "      <td>117897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-06 09:28:01</th>\n",
       "      <td>3286</td>\n",
       "      <td>131639</td>\n",
       "      <td>3356</td>\n",
       "      <td>116452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-05 08:58:01</th>\n",
       "      <td>3235</td>\n",
       "      <td>128057</td>\n",
       "      <td>3391</td>\n",
       "      <td>118494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-04 08:28:01</th>\n",
       "      <td>3228</td>\n",
       "      <td>127424</td>\n",
       "      <td>3466</td>\n",
       "      <td>105107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-03 06:28:01</th>\n",
       "      <td>3222</td>\n",
       "      <td>128638</td>\n",
       "      <td>3396</td>\n",
       "      <td>120513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-04-02 01:58:01</th>\n",
       "      <td>3368</td>\n",
       "      <td>121993</td>\n",
       "      <td>3465</td>\n",
       "      <td>106151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-31 19:28:01</th>\n",
       "      <td>3203</td>\n",
       "      <td>127504</td>\n",
       "      <td>3232</td>\n",
       "      <td>119008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-30 18:13:01</th>\n",
       "      <td>3218</td>\n",
       "      <td>125689</td>\n",
       "      <td>3219</td>\n",
       "      <td>124544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-29 12:43:01</th>\n",
       "      <td>3199</td>\n",
       "      <td>120107</td>\n",
       "      <td>3351</td>\n",
       "      <td>135479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-28 11:28:01</th>\n",
       "      <td>3193</td>\n",
       "      <td>117378</td>\n",
       "      <td>3356</td>\n",
       "      <td>128235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-27 05:58:01</th>\n",
       "      <td>3127</td>\n",
       "      <td>115123</td>\n",
       "      <td>3300</td>\n",
       "      <td>125586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-26 05:58:01</th>\n",
       "      <td>3166</td>\n",
       "      <td>112163</td>\n",
       "      <td>3397</td>\n",
       "      <td>119099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-24 19:58:01</th>\n",
       "      <td>3130</td>\n",
       "      <td>115136</td>\n",
       "      <td>3226</td>\n",
       "      <td>117547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-23 18:28:01</th>\n",
       "      <td>3200</td>\n",
       "      <td>117911</td>\n",
       "      <td>3201</td>\n",
       "      <td>126927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-22 14:58:01</th>\n",
       "      <td>3190</td>\n",
       "      <td>119404</td>\n",
       "      <td>3359</td>\n",
       "      <td>128116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-21 14:28:01</th>\n",
       "      <td>3161</td>\n",
       "      <td>119320</td>\n",
       "      <td>3355</td>\n",
       "      <td>128707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-20 13:43:01</th>\n",
       "      <td>3226</td>\n",
       "      <td>115082</td>\n",
       "      <td>3325</td>\n",
       "      <td>123016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-19 08:28:01</th>\n",
       "      <td>3101</td>\n",
       "      <td>110669</td>\n",
       "      <td>3365</td>\n",
       "      <td>130634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-18 06:58:01</th>\n",
       "      <td>3107</td>\n",
       "      <td>109839</td>\n",
       "      <td>3367</td>\n",
       "      <td>125702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-17 05:28:01</th>\n",
       "      <td>3106</td>\n",
       "      <td>106167</td>\n",
       "      <td>3404</td>\n",
       "      <td>122538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-16 00:13:01</th>\n",
       "      <td>3257</td>\n",
       "      <td>131874</td>\n",
       "      <td>3258</td>\n",
       "      <td>111438</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>748 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      buy  demand  sell  supply\n",
       "2016-05-27 23:43:01  4907  211139  5245  106366\n",
       "2016-05-27 23:28:01  4925  206603  5115  115478\n",
       "2016-05-27 23:13:01  4925  206603  5115  115478\n",
       "2016-05-27 22:58:01  4925  206603  5115  115478\n",
       "2016-05-27 22:43:01  4925  206603  5115  115478\n",
       "2016-05-27 22:28:01  4925  206603  5115  115478\n",
       "2016-05-27 22:13:01  4925  206603  5115  115478\n",
       "2016-05-27 21:58:02  4925  206603  5115  115478\n",
       "2016-05-27 21:43:01  4925  206603  5115  115478\n",
       "2016-05-27 21:28:01  4925  206603  5115  115478\n",
       "2016-05-27 21:13:01  4925  206603  5115  115478\n",
       "2016-05-27 20:58:01  4925  206603  5115  115478\n",
       "2016-05-27 20:43:01  4925  206603  5115  115478\n",
       "2016-05-27 20:28:01  4925  206603  5115  115478\n",
       "2016-05-27 20:13:01  4925  206603  5115  115478\n",
       "2016-05-27 19:58:01  4925  206603  5115  115478\n",
       "2016-05-27 19:43:01  4925  206603  5115  115478\n",
       "2016-05-27 19:28:01  4925  206603  5115  115478\n",
       "2016-05-27 19:13:01  4912  206794  5503   92148\n",
       "2016-05-27 18:58:01  4912  206794  5503   92148\n",
       "2016-05-27 18:43:02  4912  206794  5503   92148\n",
       "2016-05-27 18:28:01  4912  206794  5503   92148\n",
       "2016-05-27 18:13:01  4912  206794  5503   92148\n",
       "2016-05-27 17:58:01  4912  206794  5503   92148\n",
       "2016-05-27 17:43:01  4912  206794  5503   92148\n",
       "2016-05-27 17:28:02  4912  206794  5503   92148\n",
       "2016-05-27 17:13:01  4912  206794  5503   92148\n",
       "2016-05-27 16:58:01  4912  206794  5503   92148\n",
       "2016-05-27 16:43:01  4912  206794  5503   92148\n",
       "2016-05-27 16:28:01  4912  206794  5503   92148\n",
       "...                   ...     ...   ...     ...\n",
       "2015-04-18 08:28:01  3271  137146  3400  115865\n",
       "2015-04-17 08:28:01  3188  126117  3392  107711\n",
       "2015-04-15 22:58:01  3182  126117  3500   98408\n",
       "2015-04-14 03:43:01  3161  118366  3162  106135\n",
       "2015-04-13 01:28:01  3245  131769  3484  110922\n",
       "2015-04-11 23:58:01  3255  140696  3482  100850\n",
       "2015-04-10 18:58:01  3226  136678  3227  116000\n",
       "2015-04-09 18:43:01  3238  139466  3364  121174\n",
       "2015-04-08 18:28:01  3127  135605  3363  119693\n",
       "2015-04-07 13:28:01  3212  122079  3214  117897\n",
       "2015-04-06 09:28:01  3286  131639  3356  116452\n",
       "2015-04-05 08:58:01  3235  128057  3391  118494\n",
       "2015-04-04 08:28:01  3228  127424  3466  105107\n",
       "2015-04-03 06:28:01  3222  128638  3396  120513\n",
       "2015-04-02 01:58:01  3368  121993  3465  106151\n",
       "2015-03-31 19:28:01  3203  127504  3232  119008\n",
       "2015-03-30 18:13:01  3218  125689  3219  124544\n",
       "2015-03-29 12:43:01  3199  120107  3351  135479\n",
       "2015-03-28 11:28:01  3193  117378  3356  128235\n",
       "2015-03-27 05:58:01  3127  115123  3300  125586\n",
       "2015-03-26 05:58:01  3166  112163  3397  119099\n",
       "2015-03-24 19:58:01  3130  115136  3226  117547\n",
       "2015-03-23 18:28:01  3200  117911  3201  126927\n",
       "2015-03-22 14:58:01  3190  119404  3359  128116\n",
       "2015-03-21 14:28:01  3161  119320  3355  128707\n",
       "2015-03-20 13:43:01  3226  115082  3325  123016\n",
       "2015-03-19 08:28:01  3101  110669  3365  130634\n",
       "2015-03-18 06:58:01  3107  109839  3367  125702\n",
       "2015-03-17 05:28:01  3106  106167  3404  122538\n",
       "2015-03-16 00:13:01  3257  131874  3258  111438\n",
       "\n",
       "[748 rows x 4 columns]"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_history.index = pd.DatetimeIndex(ecto_history.timestamp)\n",
    "ecto_history = ecto_history.drop(\"timestamp\", 1)\n",
    "ecto_history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d7c05e320>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_history[[\"sell\", \"buy\"]].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>buy</th>\n",
       "      <th>demand</th>\n",
       "      <th>sell</th>\n",
       "      <th>supply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>buy</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.791262</td>\n",
       "      <td>0.971653</td>\n",
       "      <td>0.176321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>demand</th>\n",
       "      <td>0.791262</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.787649</td>\n",
       "      <td>-0.043864</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sell</th>\n",
       "      <td>0.971653</td>\n",
       "      <td>0.787649</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.094304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>supply</th>\n",
       "      <td>0.176321</td>\n",
       "      <td>-0.043864</td>\n",
       "      <td>0.094304</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             buy    demand      sell    supply\n",
       "buy     1.000000  0.791262  0.971653  0.176321\n",
       "demand  0.791262  1.000000  0.787649 -0.043864\n",
       "sell    0.971653  0.787649  1.000000  0.094304\n",
       "supply  0.176321 -0.043864  0.094304  1.000000"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_history.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d7bdd24e0>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_history[[\"supply\", \"demand\"]].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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/rt9nePHsXzbNvvyp55SKiEBtQBffTWyx7djB7K5/fj7bxxfkyap+4z0IADPn1fqf//Tf4sAFMJFBGAc88IL0sheiA82bIC7NT2xaZNSnTopdcUVcCMKdhYsUKpPH4w1v/5qX+fYMSzfutW+/OBBWFpLl4a1MJI88IBSNWr4r/Pnnzi+hg1T9xnpQQASKTVnjv5bBKAQLiIA45jnnsOgcOFCrI9EEPxZvx4JF+mJ9euV6tYNCQ5erktBqXnzdA28n36yr3PkCJZv2WJffuCAUrVqRSfh5r77EMfpx8WLOL5gsYJehCIAx42LvgDs10//LQJQCBcRgHHMs89iUJCfT0jv3HmnUg0axPoonNxxh1K9eiE20ctyJcDqdO21GGvOn7ev88wzWH7PPfblTz4JYVSpElrwBeOnn/D7hMLmzdivH//9L44vMTG0fbpJLwLQ7GQiAlAIFxGAccyhQ/6DsiCkF+64A7F26YnVq5W6+mq4gTdtivXRpF9mzVJq2DCMNefO2dfhsWjDBvtyLrpdrRomrsE4fhzu4lDYuBFdRvz4/XccXzBXsRciAIWMiAjAOGb//tg2VxeEUFmzJvXWl2hxyy14qF91FSyUgp0ZM5QaNQpjzddf29fhseiuu+zL9+2D+/Wyy5AQEoznn0f3kVC46y6lypb1X+fXX3F8VaqEtk83IgCFjIgIwDjm8cdj21xdEEJl9WpkgaYnli6Fa7NvX6Vuuy3WR5N+mT5dJzh4jTU8Fq1da1/+6KNKXX45JgH79wf/zKNHlSpaNLTjW7tWqVKl/Nf5+WccXzBLoRehCMDx46MvAK++Wv8tAlAIFxGAcczevRgUPv881kciCP7ceivcf+mJhQuVuv56pQYOVGrFilgfTfpl6lSlbrwRY80XX9jXefRRLF+zxr58717EgNar590v2OTIEaUuvTS041uzBuVl/PjxRxxfmTKh7dONCEAhIyICMI7ZvRuDwpkz9uUXL3rX7RKEtGTFiuCB+mnNnDlwbQ4dimLHgp3Jk5WaNAm9dD/91L7Onj0Yi1av9l7esCFeXv2CTZ59Fl1DQmHVKhSY9uP8eRxfqG5lNyIAhYyICMA45qGHMCh88IF9+eLFGLgFIdYsW4YSIOmJGTPg2hw5Uqm5c2N9NOmXpCSlbroJbSe9Jpu7dmEsuvVW+3Luu9y4sVIPPxz8M59+Gn2DQ2HFCqUKFfJf57vvcHzBhKIXKRGAdeqk7jNCOQYRgEIkEQEYx2zfjkHhnXfsy6dNQ/aeIMSaxYtDz+pMK6ZMgWtz3DjEuQl2Jk1S6uablcqTR6nTp+3r8GR0+XL78l270IWjeXOsG4xDh/B5obB0qVIFCviv8+23OL6CBUPbpxtT+HkJwAkToi8A+/bVf4sAFMJFBGAcs3UrBoU33rAvv/lmpQYPTttjEjIO//tfaDXbQmHhwuBxWmnNTTdp61ZSUqyPJv0ycSLEcr58Sr3/vn0dnowuWWJfvnOnUk2bKnXlld7t4kwOHIDFMRQWLVIqb17/db7+GscXbD0vRAAKGRERgHHMli0YFE6etC+fONFZNkAQUsKpU0oVLhyZfc2fn3r3W7QYPx4JDtOm4f+CnQkTcI4KFvT2Ntx/P8aiRYvsy3fsgPWvbVt07gjGk08qlT17aMc3f75SuXL5r/PVVzg+L1G5ezeSgbwQAShkREQAxjGbNmFQePFF+/Jx45Tq2TNtjymj8cEH6BWbGXnhhdAD8YMxZ07k9hUpbrgBRY45GUSwM24c4iUvvVSpN9+0r3PvvRiL5s+3L3/wQaVatFCqY0d07gjGvn1KZckS2vHNnh1cLJ49i+PLmtW+fPlyiFMv0osA7NNH/y0CUAgXEYBxzPr1GBSef96+fPRopbp0SdtjymgcOxa8xlhG5emng8dWhcqsWaEH9acVI0agz+2iRcgEFuyMGYPfr2hRWIVt3HMPxqI5c+zLt22D+7dLF+9uISZcViY5Ofi6M2YEF4tffKGF2z//BC6fMkWp1q29txcBKGRERADGMevWYVA4csS+fMQIpdq1S9tjymgcPqxUsWKxPorY8PjjqY+ZcjNjhlK5c0dmX5Fi6FCIvxUr/N1/mZ3Ro2FlK1HCO9xkwwaMRTNn2pfff79SrVqF3nXlkUewv7//Dr7u1KnBxeJnn2nh9tdfgcuHDVOqZUvv7UMRgFwrUQSgEC+IAIxj1qzBoODVWmnoUP9BTQjOU09FLg4u3ti1K3KibepUpXLkiMy+IsXgwShPc9ttztiq9MDzz9stVbFg1CiUySlVSqmXX7avc9ddGIumTbMv37pVqTZtlOrdG32hg8E1Tv/8M/i6N98cXCx+8okWbhcuBC7v0UOpZs28txcBKGRERADGMatWYVDwaq00eDDqbgmpZ//+9Be7llZs3Ro50TZ5cugxXWlFv36oW3fnnbBMpSfy51fq3XdTt+1ff6G24f/+F5ljGTECsX1lyyp14oR9nbVrMRZNmWJffu+9iLG7+mrvYtEmXFfwv/8Nvu6kSVj3jz+81zlzRgs32+OueXP/sdJLABYsqNT336edAOzdW/8tAlAIFxGAccyKFRgUvFor9e+P/ptC6tm3D+UvMiMbNqD7QyRISvKOv4oVffrAir5pk1KdOsX6aJzkyOGdcBGMc+dwrn/9NTLHMmwYyvhUqOAdb8zeCK9yOlu2KNW+PYop33JL8M/kuoK//RZ8XS7A7CcWP/xQC7cffghcnpCALiVe2ARgcjL+PXFCBKAQn4gAjGOWLsWg8Mgj9uV9+ypVq1baHlNG45FH0l/sWlrBD/VIwFYaW/xVrOjRA3G07J5ML7Cw8Eq4CMaXX2L7H3+MzPFwq7zKlZV67jn7OuyNmDjRvvyee5ABzG73YDz4IPb388/B1x0zJrhY/OADZAoTQSC7KVZMqfr1vbe3CcDu3XUVBhGAQjwiAjCOWbgQg8LOnfblPXsqVa1a2h5TRmPXrvQXu5ZWLFsWeiZmMDhD8uLF8PcVKbp2VeruuyE2mjeP9dFo/vrLv75nMDjh4bvvInM8112HAs/VqqFHr41bbsFnetVTZCsrJ94EY9u20EXsqFHBxeL77yOhiQg1AU3++QflYerW9d7eJgD59dJLaScAe/XSf4sAFMJFBGAcM28eBoXt2+3Lu3WD20ZIPdu3p7/YtbRi7lxcX5GIJRs3LnSXXlrRoQMsU9ynNr1w4YJ/fc9gfPQRtv/668gcz7XXYjJQo4Z3whlPFsaMsS/fsAElYDieMBhcWPr77/2P69VXlRo+3Nu1y7z7LuL1smRBSRiTH3/E9omJ3tv7CcCXX9bWz2gJQP4sEYBCJBEBGMfMno1BYetW+/JOnTJvDbtIwe320lPsWlrB5TVCycQMBrvpfvop/H1FijZt8Pvu26dUvXqxPhrNzz/jXL3wQuq2f+89bP+f/0TmeAYNQrxxzZpKHTxoX2fxYnzm6NH25evXw+LKJWWCcd992N+333qvU6eOUnv3KjVkSHCL59tvK1WoEKz5H3/sXMYJIpdd5r29nwB85ZW0E4BmYX8RgEK4iACMY6ZPx6DgVVm/XTsUbxVSz+bN6S92La2IpNuW3XTnz4e/r0jRsiUsvAcPQtykFzirNLV9mN98E9t/+mno23z6KSyHNgYMQLZ07dpo0WaDw1FGjLAvv+suxMyNG4dxKxjc5tLPipmYCOvt4MFY95tvvNd98010MsmTR6nTp53L2IJXo4b39n4C8NVXRQAK8YkIwDhmyhQMCnffbV/eujXcHkLq4QK36Sl2La0YMQLf/fffI7cvP4tOWtO0KeJnDx9WqmrVWB+NhvvWHj6cuu1ZkJw5E/o206crNXasfVm/fkjyqFfPu+IAh6Ncf719+bp1KLUzcaJ3qRgT7ixy9qz3OjVrIlt4wACs++WX3uu+/jp6URcsGFheZ/9+bO93DfgJwNdeExewEJ+IAIxjbroJg8K6dfblLVpk3gzWSHHnnZETQfEGW1YiUU5k2DB7AH4sueIKpfbsQWmT8uVjfTSazz/HuXr66dRtz2VJPvgg9G0mT0YsnQ2u3degAVyuNjgc5brr7MvXroX1KikJ41YweOL1+efe69SoAQvuNddgXXdsn8lrryHTt3DhwPI6DzyA2MBKlby39xOAp07hX850FwugEC9kGgH45Zeh9aCMJzjrbM0a+/ImTbybnwuhcfvtwTMMMyp9+kTuu3Oclt9DOq2pV0+pxx6DYCpTJtZHo+GYNK94u2AcPYrt33kn9G2SkiD4bfTtizHmiivgcrUxYwY+02sft9+OEiZTpyK0IBjc5/yTT7zXqVYNMZy9ewd3eZ88iVZ2xYtDDJqsWQNxyJOAWbMC29X5CcA33khbAXj2LJ5nIgCFcMk0AnDfvvQV5xMJxo7FoLBypX15w4aRy+LMrHB9M78Mw2hy9Ki3hTfadOkSue9+7bUpj0uLNomJcP+98grEQXrh/fdxrp54InXbP/OMFiahMmkSLGk2uH1bkyYoi2SDE4YGDLAvX7MGE4qZM71dzSZsefdzY1epgljBHj2Cr/vyy0iIK106sJ3dnDl4NvAkgMWWiZ8A5JjLtBCA/F1z5hQBmN5YTkRvE9EvRPQVEe0gorKudeoQ0TEi+p2IviSi+Zb9LPx3+9+I6CgR1YrCPphMIwD37sWAkZEYPRqDgVdh1Xr1sDyUdkqCHe62YisemxasWhW7NmWtW+O7+5XiCJVBg7Avr0SDWJCQgLImp06lr2QpFhSPPZa67Q8c0MkJoXLjjRAXNnr2xCSkeXOlduywr8P9eL1E5OrVcCXPmYOEoGBwazl3woZJxYpKbdyIclfB1n3xRQi88uUDs6snTkS4DFdMSKkAfOuttBeARCIA0xtLiehyIspO+EEeJKI3jOX5iehrIlpCRDmJKJGIzhLRJGOdqUT0BRHVJKJcRLSMIPLyRnAfJplGAO7ejV6WGQkOrPcqrJqYmHndl5GCy1tEqqZaSlmxInZtypo0iVziRv/+KY9LizZVqyLR4s03USIkvcBJHF4dfoKxbx+2f+ml0LcZN877OrvqKmTxXnklCjTbmDQJcXR9+tiXr1oFcbhggXesoQmHXrz3nvc65cvDVdy5c/B1T5xQqlw5ezeTkSOxj+LF8XdKBeDbb+NfjsmOpgC86ioRgPFCXSL6h4gu+ffvoUT0LRFlNdaZSERnjL8/JaIJxt/ZiOgcEQ2O4D5MMo0A3LUrfc3yI8HQoRgI5s2zL09IwPJIdQTIjMyfj3Pol40YTZYsUapt29h8dt26kRO/HKifkri0aFOhglLHjiErtECBWB+NhluLPfxw6rbfswfbp6SO4Jgx3u3wunWD0OK6iTYmTFAqVy5nkoLJrbdiErB4MeJBg3HbbVpceVG2LCyTHToEX/eFF/B716gBF7nJoEG4PosUwd8pFYDvvCMCUAhkGkGMMbcR0UHXOk0JIjE/4UdMJqLGrnWeIqJVEdyHSaYRgDt2pK9BPhJwXNWsWfblVatiuV95BMEfzm787LPYfP6CBXBPxYLq1SMnfvv21fFS6YUyZWAZOn0a9eHSC5zE8dBDqdt+xw5sn5I6gqNHK9WsmX1Z165IoGvXDjF3NsaOxfjqFa6wYgXiA5cvh+AKBsfe+l0vpUohtrBNm+Axj8eOwWVcq1Zgck2vXrBKshU4pQKQC2+nhQAUF3B80J4Qf9fBeG8zET3kWi+BIN5KE+IFk4mohmudnUS0KYL7MMk0AnDbNgTOZiS4/tXUqfblFSumv8D7eIOLbbu7B6QVs2fHrk1Z+fL47pHI3O3VC/tyZ2AqhVZckepakRJKlEACyJkz6avfMydxeLV4DAa3UfPq22tj5EiUebHRuTN6+XbsiPp8NkaPhgWta1f7chZ+K1fCEhiMW2/Fdzh1ynudEiUgFK+8Mvi6zz0H92/duoHJNR07woXNBoKUCkBO2mEB6NdTOLWIBTB+6E5EPxFRD9f76dYCOH78eJWUlKSSkpLUoUOHIn/1pgN4UIxEY/v0ArvVkmnfbooAACAASURBVJLsy8uVCx4cLfgzeTLO4Ycfxubzp0+PXZuyYsUiZ/1ky4U7A1MpiNxrrw3/M1LKpZfCavTZZ+mrXBIncXi5W4PB3WtSMpQPG4ZOHzY6dsQ+u3TxLqU1YoRSJUt6xxEuXYoSMbfdBmtwMDj56uRJ73WKFcN6zZsHX5eLfTdooNSjjzqXtWiBazBfPvydngVg48aHFFGSIkpS48ePFwGYzhhMEH/tLcuGUGD83iQKHr/3HRENisA+MnUM4L334gb6449YH0nk6N0blosbb7QvL1UqeGyM4A9n9vkFmEeTyZNjV74of/7IWT+7d8e+TpwIXNarF7pNpDX58uF3PXsWx5Ze+j1zEoeXuzUYd9+N7b3attkYOhQufxvt22P87N4dySA2rr8eFuP27e3LlyxBkWguCB2MZcuCJ7IULgxhyclKfus+8wy+X+PGgbGV9etDSHLR/NQKwKSk6AtAvo/EApj+mEBEPxJRc4/l+QmlWRYTUW4iqk1E/yFnBu8UIvqcULYlD6G0zFlyZgGHuw+TTCMAubVQRvqqPXrgIe1VV4stODa3mxAa48fHVkRPmoSCt7EgWzZ890iUbuGagseOBS6rXt07ezSa5MwJ9+/XX+PY0ku/5927cTybNqVuey6hkpIyMtddhyQJG23bKnXffRBua9d6b1+1qnfC0qJFEJnr10PEBGPJEu8JA1OoEHoQc73T48e9133qKSTF2UrZJCRA2HIYQEoF4LvvOgVgNGMARQCmX5KJ6E8i+vXf12///msKwkQiep6ILhDKucy17GcBEX1DqPN3lAJr+EViH0ymEYAbN+KmyUgZsd26IbN55Ej78ksvxXd+8cW0Pa6MxA034By+/npsPn/8eO8HczT5+2/9oIlE6ZZOnbCvI0ec7//xB4SmVw26aJGcjOP5/HOMCUTpp98zJ3F49fgOxurV2H7PntC3GTxY18Fz06YNQmj69PHuOjR4MCzVrVrZly9cCCvhxo2IKQzGwoX4Ds8/771OwYKogHD55d6TC+bgQRxf69Zo/WZSvjze4zCAlApALgOTUgF45Ejg53ghAlCIBplGAHJroViV84gGnTqhFIJXA/YCBfCdU5INKDgZPhznMCVFdSPJ6NHeD+Zo8uuv+kETCfc3l+pw97flEhpeyQPR4q+/8Llff41OJ0RK/fZb2h6DFxyv7G5HFiocP7dzZ+jbDBgAl6qNVq2QRMc9gb22r1fPO2N9/nzcS1u24FoIBpdfctfsM8mXDxUQ6tSxTy5MDhxAXVR2Z5sULYq4QBZjKRWAXAg6pQJw5UoRgEJsyTQCcN063DR+7YLijfbt4XbxCqDPkwfFWd11r4TQ4R62tuSFtGD4cF2fLC05dw7fO3fuyLi/27XD/twlOHbtwvtpXez6wgV87vnzCAshSj8F0zlc5Y47Urf9okXY/sEHQ9+mXz+dBOGmZUvsq39/ZOfauOYa9Apu2tS+fO5cJIps3epdb9C9PpF/JnOePEiSqlUL6/qNc08+CWHGGc0mefPqzOt//km5AOTOLSkVgJzpHAoiAIVokGkE4B136HiNjELr1hj8vPpv5siBwW3//rQ9rowEtzDziy+KJkOGwNWVWkaOTJ2w+eILTB4uvTQytfu4rZy7BMeCBXABt2sX/mekhJ9+0jHBphhMD7C34rbbUrc9i6f77w99m6uv9i6F07w5ahIOGoRyLjb69MF6XiWLuAXc9u0QlMHg+ptui7FJrlxKTZmC4s5E/lnPjz8OC2X37ji/DIcCvPKKjgNNqQB84w2nAOQkEP4OXtxyi15erZr/8fNncds7EYBCJMg0ApAry/vVioo3WrZEWQOvsgpZsmj3hpA6+vULHl8UTQYN0tmJqSFHjtS5cLk4ctGikYl/5Fpt7sSEfv0wifGKHYsWbOG8eBFxiESRaXkXCXiy6mVtC8aMGdg+JVnEffpoC5ibpk3hTr7uOiRn2OjZE5a9hg3ty2fNQjjDzp3eBadNZs60W4xNsmdH6RUueO830X3sMcQK9urltKyy+OdM3osXUy4AT53Cv9wPmQVgo0b+ApBd9bx/vx7JIgCFaJBpBCDHW2SkhIimTTHrtpVVYFdG+fJwswmpgx+MfvFF0aRfv9TXqGPrxltvpXzbN96A9a948cjEP7ZogWNxJybUq4fvmNbdTr78Esfzv//hRaTUV1+l7TF4wV0wvKxtweDalRs3hr5Nz55aALnh0inXX4/kDBvdu8ONf/nl9uUzZ6Ld3O7doRU25wLsfqVssmZFCaxKlbDu4497r7t3LybL7jjG77/XseFESv3+e8oF4GuvOf+uWxfxpLb9mCxf7hSAN9zgvS7vq2tXEYBC5Mg0ApDN7X5BxfFGo0You9CtW+CyP//E901I8G7gLgSHCxj7uaKiSe/eWqikFLZs+Vm9X30V8VtuXnxRqdKlkYDyyisp/2w3TZviWNyTkWrV8OBr0iT8z0gJn34K17NSWihHouNJJOAaeDZrW9++wSsZTJyI7b1q9tngDhO2R0GjRhDuw4cjOcNGly4QgV7xb9Ono1zVo4+i7l4wpk7F8ezbh79nzw7MQCbCPrljjZ+nY88exCgOHIhnAfPFF9j2xx/xr5n85P4sr9errwYKQBbhfgKQf2fe/5gx3uuKABSiQaYRgHyzZaRGJ/XrY0CwBdD/97/4vvXrp76grKAHXD9XVDThB/N//5vybflh5ifgHnrIXgD4yBGlqlRBv9xIWM0bN8axuBMTKlZErUMv12G0OH3a6VrPlk2pTz5J22Pwgkug2KxtOXMGD0cYOxbbs6vzwoXgrfbYtWgTlw0bwoI2ahRi+Wx07IjJSq1a9uXTpqGk0RNPhFYomQUUi7ohQ+BiZdjDMXo0Jio267LJww/jGrzuOhSPZj74AHHSnAjEsaEpEYAcP2gKwHHjggvApUudAnDcOOfykye1VVAEoBANMo0AXLzYOaPMCNSti0HXFkDPD/8WLVJfT0zAg40oMHkhreACyqm5Rc+fDx72sHEjWga62b8fZTPKl49MAswVV+BY3DXYypaNTbu7d95xJtfkyhWZgteRYM4cnKt585zvs6XSXcjYzciRWI9dnffdhyQcP/g6s5XJql8fMXRjxsCVa6NdO2QJX3aZffmUKXDXHjjgLRJNOKGCRV3//s6C91yncvhw9ATOls0/1GXnTlihhw1zCutTpxDnyq5fvmdSIgBfftlfAC5bZj8mLnbN+58wwbmce72bn8+/kwhAIRJEXADOn59+yimY8Kza3QYonklMhEvjyisDl7FLo2PH1JeTEBDYTpSyrgqhkJyMB3Ow9mNcP+/771P+Gdzhwq+Y7sqVeAC62bMHlp+KFf23D5X69XEs7hpsJUogE9irD2204Ac/ky8fEgHSAxz/Nnu2830WPatW+W/PpYs4ieSuuxAn5wdPdGxW0Hr1MHEePx6WPButW8O65tVO7uab4Zp++mlk7QaDWzCyqOvVC+KN4RCXoUPxO+bJ4y+Md+xAvPSoUciSZl54AZMcTv7g5CAWXt98o4W31+ullwIFIFth/ayAbJRQCv+6W3qKABSiTcQFYKFC/jFHe/YgcyutmTfPboGIBvv3p6wKf2pJSMCgaMuq4+4GPXviIS+kjpYtcR4feSSy+2WLQ7C4MxagqUlQ+PxzbOuXwDJvnr3+G5frqFIlMnGz9erhWNw12AoXRjakl+UoWrz0krPAdsGCsAqmB9j6NX26830O6zBdoTYGDnRantasQTa432SjfXtsYxPBderAAj5xIlyzNlq2RJ2/KlW8v9NNN+FarFrV//iVghgiQoiCUhA+ZrkrPheDByNZ6ZJLcM168eCDOMaxY5ElzXCLOC7/8s03TtHG976fADxxInUCkOs18udMnOhcLgJQiDYRF4D58/vHHC1fbk9aiDZck+mee6L/WUlJiE2JNtWqYaCxZdWx9WfgQGfMi5AyvJIXwuXnn7HfYGWJOHv2s89S/hkffYRt/RJYbroJ2ZTJyc7377kHVqFq1ZQ6fDjln+2GuzW4wxEKFlTq9tvTvt/x8887W+wVLozM57Sma1cIdZMJE3Cupkxxvs/XTP/+/vu8+mqst2gR/uYEOL8yN23bYh3bOahdG5Pam27ynrw3awYXccWK9uWTJmFcPHbMex0T7sHNoq5tW2e1A55ADRiAa6hYMf+6h9u2odTQjTc6zysnpXBMIWeHm8KLeyt7vY4fDxSAY8YEF4DsleLPcZ/b/v1FAArRJeICMHdu/wbec+fiwZLWcF2p1LZXSgnjxjndFdGiUiUMGrasuv/8B9/XL3NPCA7HrgWLu0opHGsULCmpSROsl5r4NG6z5pfAwq3u/vzT+f7atXjg1qgRmQzoWrVghVq3zvl+njyIQ6xcWb934IAWL9Hi2WedorNYsdi0+8uXLzBGk/tPJyU53+eSJcEKKXNJF44hZFfja695b8OFum2T91q1cA1NnhxopWIaN8YyWzypUtp6eOKE9zomLKBY1DVr5nxucIzzNdcgiaNMmcDwApP778d3ZEsk8+CDmGSZmeBuAch1Gb1ezz8fKAD5N/QTgAsWOD/H/XvbBGDnziIAhcgRcQGYLZt/ltrkyaG1Aoo006bhpvHqZRlJhg/3bs8WScqXhzvDFj/FZS7GjvUO3M7sHD8eXNhxo/lIhw58+y32G6xET8OGWC81HWy4QK1fAss112Add9zuLbfgAVSzZmQy5y+7DGLn9tud72fPjodz+fL6vXHjYOmIJgcO4LsxpUqlfbs/rj/ojrEcNszuEvzqK7zv5WZlOFN01iz8zZ1B/MqkcKiDLd7zssvgKuVMXhtXXAHLWpky9uUTJmD5yy+H1tt69GgcD4u6Bg2cwpezdXv3RgJPpUr+3p377oMVcdo0Z7IFW7qVgiX8008DBeDtt/sLwGPHUicAud8xf47bvW5zAYsAFCJJRAUgz6L8XEZjxoTWCijScFkBr4ysSDJ4cHA3TSQoXRqzSFv81EcfYWCcNMk7bide2bs3MkJ+5kzvLipM7dq4bu67D1aHP/4I/3OV0q6mYO2+OHYuNd04ODjd78HfqRPW+eYb5/sLF6Lwb2JiZFoJ1qiBWC0zgYHHi127cC0zzZrhYR1N9u1zZh6XK5f27f44Ucsdo3nttXjfLbY4pjN37kCXvUmHDliHEzY4qcRtfTVp3hzr2Hrv1qiBXrlczNlG/foQnCVL2pdzAslrr8HaGgzOZN68GX8nJjpLBf3wA5b36IFJRI0aSm3Y4L2/LVsQ5zhrlvM73HEHEkyUgoX6zJlAAbhmjb8APHo0UACygPUTgByXzp8zdapzuQhAIdpEVABylpqfy2jIkLQv+qqUDqxOjTv0+ecD43T8uPpqdJCINiVKIKbSFj/1/vuwuEydGphdFu9Mnx4ZgT1yJKwlflx2mX4QDR8eaMFKLfwwZyuNF4mJWI+tU/PnK/Xhh6F9Blsm/BKSOMbx00+d78+YAetx3bqRKYFTtSquV7MIL48Xjz+OjiNKIRYrXz4Ikmji7khRsSIe5OFw4YK9jIoXfA24x8v+/SFq3GLLFCc//ui939atIbY5WcQrqcSErwOb2K9WDcKQ+/naqFsXk1EvccfJF2++iXjLYHBoAnczqVYN9wLD7vCuXdHysnZt/8LXbOmbNw/3PbN8OdotKgXR/OGHgQKQ24h6vY4cCRSAo0YFF4BsmeXPcWdY21zAPGETAShEgogIwEOHlPr4Y51Kf+CA97p9+8Kcn9ZwdXwzAyxUunULrELvR/fueEWbokVxXLYSD++8g8y4WbP8WwzFI6NHw/UTLty/1I+qVWFJ3bABwn7BgvA/VyncL0T+/T+V0o3uX3gBf9esGXqG+TPPYNudO73XYYHp7hfMQfuXXx6Z2pmVK6Pmn5mQxJmczzyjVJEieI8TV6JdGPrBB50is2rV8JNd7rsvtD63zFtv2cfLPn2UKlAg8Np47z0k2eXP7x8S0KwZLKqTJuHv8eMhkljo2OBC3Xv3Bi6rWhUiZ948CDMbiYn4bb3EHdcQdNdf9OL663E869fj7/Llna5vDqHgMkkNGyJu1YuNG2E9W7QIpWOYuXO1IORSQG4BuHq1vwA8fDh1ApDrPfLnuJ9NIgCFaBMRAdiuHZIruP+hX0/GLl282wVFE84qcwfahkK7dinry9mhg707R6QpVAhZlWXLBi574w08VBcs8B6045VrromMwG7aNLg1umJFPLDuuguCMZjFLlROn8b1yO4nL6pUcYZVVK4c2E3Di/37sa1feQxuo+VOELjhBnzXBg3soiClVKyIYzeTOziQ/4UXMFlRCnU6iaJfF3DrVqf4T0hAnFs43HUXEhJCbdv3wgv28bJ7d1jS3Ilkb74Jy1716v7HesUVuG7YhTxqFH5nW71QhmNNbZOFypVhHeWwAGb+fIQyKAVL+cqVGJNsjB6NSgzceSMYXMuQ3dYlSjjDBLjKQatW+LdZM/9J+t13w1q4bBlCdBgzsaVAAZ04ZQov7s3s9Xr22dQJQK5MwZ/jHltsLmARgEIkiYgAbNgQNx8H5vo9MK68Mu1rfimls8rMavKh0qJFYFV+P668MvoxTEphwLrvPnvczauvYtBctixtElJCITk5MkWF27ePjMCuWjV4W6qyZeGeXLsWluBIxVO+9x6ux2CuzgoVsB5n8pYuHXprv717se3Wrd7rFCrktDAyQ4Yge5T7wIZLuXIQWeZ9xHFcr76qaxHOmgWxEkqx4HDYtMl5DdWq5e+5CAVOFjh9OrT1n3zSPl526oRzMGSI8/2TJ3EttmmD+96LevVgkWPL/9Ch2MavGDQX6raVUuFi4EuWoNgzU6aMjhmsXh3xdAUK2Pc/ciQsXmfOwKIeDI6D5CL2hQpB/DIcQ8tZ8q1b+xfIXr8ewvrWW53hI2PGaMtboUIQ2W4BuHKlvwC87z7n31WravHmJwBnzXJ+jrvwt1gAhWgTEQFYrRpuLI7L8Ou20bBhaIVAIw0H5abGGnbFFYEBun40apQ2iS5c/d7WyeGllzBAr1qlVL9+0T+WUOBB29Yp5vz50PdTv35kMskvucS7cwFTsiTEy223IYbI3a4ptbD7L9jnlymD9dgNW7iwdosFY+dObOslGJOTkSmeM2dgHNo11+DaadIkMjUQy5SB5d98yLEb7913dV/eYcMweQqlVlw43Hmn04pct66/5yIUWCj4udxNduywj5dt20IAm5YqpVBCpWxZvL9kifd+a9XCmDViBP4eOBC/p1/yhVehbqV0O0AzXk4pCCa2RFapAiubl3VvxAiIf65OEIxBg3A8nCSVJ4+zdzOXa+Es/Y4dnfGlbu68Ewkja9Y4E7+GDNFW6SJFdOa8KbxuvdVfAIbyssGlyfhz3H2WRQAK0SYiArB4ccR/sFner7TGZZc5C7CmFSNGILDaPaiGQu3aKUukqFsXMTXRJmdOWA9sbhducbR2bXA3Y1rBcW+2YrPFi4ee3FCpEqyy4fDHHziWYDXJihbFhGXlSojOSBX45gdNsID4EiUQv7V7N/7Omzf0eNQHHsBncCC9mwsX9Dlwt7rr3h0PzebNdTeGcChVCpM/MxGBJwQff4x7UylYfnr0CK1USDisWeNM1IqEq3vZMnsslxd3320fL1u0wBhidr5QCm7YSpWQLDBunPd+q1eHF4Jj3fr2hdDxu9bq1EEZFFud1LJlIT7d1rMcOXTSSMWKSJTysu4NGwaXMdcn9ctiVkpb0LiLUdaszu0++wx/16qFf6+6yr/CA9e1XLfOWVD66qu15bB4cVij3QKQC2lHWgDOmOH8HLeXySYAuWWfCEAhEqRaACYnw+WrFGZmCxbom9uvZlqFCs5YjrTi+usRy3X11Snftnp1Z+ZYMBIS7MWZI03WrHBb2Vp5PfccYnc2bAie6ZpWcIC1u61acjJETrCuGEyhQvbuJymBxYfNeur+rMREWD9atnQGkIfDK6/gOxMhG9aLwoXx++7YgfOUNWvo8aibN2P/XtmR3PaqQYNAkde+PSyHLVt6xxBu24ZJXygUL444LdOF/tln+D5szUlOxkNv4MDQMkXD4ZZbnAKrUSMtslPLokX4TTt3Dv0YbONl48Z4XXON833uo3v77f6TukqVYCniye5VV8EdzHGWNmrVwnVmK69Upgw8CqtW6fGTe/Gy1bRcObiPWci7uf56xBByLcNgcZL9+mG9FSt0tjgREg2VQs9idrcSQeQuXuy9v9tvR+LY3Xc7O1F17aot6iVLItveLQBXrIiOAOTyPPw57goVthhAEYBCJEm1ADx6FLNGHgjmzNFFNP0qshctGlodqEgzZAhu8KuuQiKIzdXhRfnyKYujq1gx+kHsXEPtyBH7rPuZZyBc770XD/P0AMfXuGN1OHnIr4Ugw8VzL788vGN54w3sxyaeTfLnh+VqyRK4Q91WmdRy4gTuAyL/Fl3c5mrrVt2vNNRM5PXrsT7HUbnhWpFt2wbes82bQ3S2auU9oUtMDL1HctGi2JfZhYE/3xQFffsigD7Y7xIuixc749maNQtu6bxwQSm/oXLuXHg4QrVecgyYO56vfn2cK3cpqf37cc7dGcxuypaFQGRrXadOyAj2is9TCsddtKjdilaqFO5N02rKNQy5xmTp0jh/WbPa98+u1nPnsF2weprczm7ZMt32jUiXv+FscU5iGjjQ/7647TZcW2bhZ6UQO8gxsmXKOPv6KoV/ly+PjgDk5gQ8li9c6FxuswBWrCgCUIgcqRaA+/ZhRvndd7gYp0/XN6WfuMqb1ztTLJoMHgyLWMeOmPWlpJxHiRLBCwablCoFK2A04VnxiRP2mJqDB1EyZPt2/+y/tOTkSRyzu8Athw74tRBkOHHArAmWGp56CpZrWx9ck9y58bBduBBCMFL1HY8dg6Umf35kHnqRNy+s5ps26azZUDu7cAFbr2LTr72Gh363boFWwvr18XBv29Y7iaRq1dDj3QoXRna8GUPJtSpZFPz5J9y/SUlwL0aTefN0jJxSsHQG68qyaFGgVc5kxgyML9mzB3dxKqV7/ro7WNSuDStijx7O97lv7Z49/mVyiheHIGJrXdu2ODa/7NsaNWDFM8fFnj1xbZYoAdcou1GVQr1DIp0gVKIEJgMsaNxcdx0mUXz/XrjgfSxKwVpHBKHObROJMFlQSmfRlyiBf4cOhQD3YtUq/HbcEYRp1EjHYJYv72zrppQWodEQgFOnag8Af1cTmwA0XyIAhXBJtQDcvRsXIafN33yzdvG5G74z3HA72rN7GwMGQDS0aoXyHykp51GokNONynUPvShc2NnbNBpwDNtrr9kH3SeegIX24YdjU3jbBpe9cLukeTAPJUOY4wiDJU8EY/t27COYNSJbNpQBmjsXcVmm+ygcDh9G8lSlSnDXe5EzJ6wzd96pJ1tc4DcY7GK89Vb78iNHcJ2acVDMZZdhEsGuYBtly4beIq9QIZw7Mwv/rbfwPj/gL1xAmSgukPvPP6HtOzVwoWumTRv/bGmlcN7z5dNuSDeTJ0N4EXmvY3LddfbxskYNWPDc19rDD8M1zPe2F5deimQ3dhO3aIEJjF/2bbVquB/MyUWFChjrihVDeMZdd+nEGb5neQJQtCiOiy25bgYPhpD6+WcWL97HopTuZ7xggbYQZ82qx11+1nAW+6hRgVm0Jhy/uG2bc0KcmIhsbKVwL5pdPZTCv0uXRlcA8ljuTuwRAShEm1QLwAcfxEXIpSZuvFGpt9/G/71aDnHQec6cKf64sOnXD7O9Jk0wwE6ZErjOf/+Ll5vcuZ2zxk6ddEeIzz6DZcYkb97QGp6HA5/Ld9/Fv3/95Vz+2GOwFvC/6QEumOouA8SB1+6WWDZ4Xb+SFqGwZg3EDZGOZXXDrpmuXTFhqFkTVqxI8NRTOA+mBcJG1qyI0VuzRsfY+iUAmCxerC0YNrgd2nXXBVof+GHYqZN3j9WiRUMvSVOgAKw6ZnFjbgtmioL27XXMVSgiKrXcfLOz126HDrrtmBdjx+K4uCSPm4kT8dsQQawHg0WOe7ysXBlC0h1L+OCDEHMcC+hF/vywsrNYa9QIAsgrPo8/s25d5+SiVCm4nYsUQSvCDRt0j2ZOYuKalJdeCrHIllw3AwfClcru3B9+8D4WpRCqQ4TJwKef4j7gOn1KacNDnjyIu+ROI16sWIFj2LnTWay7cmU97nAxcBZY3BVkyZLoCMApU7CMC6LPm4c6iYwIQCHaBBWAM2Zgpu6Gax9xfMSYMRgkiLyzFLlMTJYs3jdqtOjbF9a/evXw0LFl9U6bFlgnkBMUmjbV77VurTsadO0amGWZLZt3T8xI8csvOJdsEXML1z17MPAfOJAyd+np0/5Z3OFw8CBce+5eptxKya+FIPPUU1jXq+l8qMycqdtNeSUysGumTx9cG5xdGQn4d7G5Xxm2mLdsCWseh1iw69IveUQpbUkziy+bbNuGfY8eHWgRL1kScV9dunj3WM2f39va7yZfPjzQzDJML78MkcGi4McfcY+uW4e/beWCIsWNNzongZ07+/eSVQqJDFmzetcSHTsWoTDZsiFJIRht2tjHy3LlcJ7ckw12Xx475l8mJ1cufDcWkPXq4Zz6jbsVK2JybLroixRBkkfhwojf3bRJx8+xq5QtwJdcou9jm3AfMADXMFu7ggnkbt2wHhePzpNHZ+kqpcsoZcsGYTthgn+pruXLYYXkcZEpUUK3WaxeHWOQW2jxRCrSApD703MMNL8uXsRxBhOAX38tAlAIj6ACsGZNe+eBjRtxEQ4bph9KHOPFqftuuPclUejV8iNFr154mCUkYNCwtUcbPRpuLVOccJKLmXTQtKl2lbRo4XSfsWjg1lbRgoOwOZvVbYXkme6zz6bMXXr33ZGpsWdj3z6cf7fo2rcP74VSiHfnTohI7h2bWrgwbfbs3g9rbm04cCAG60qVIlfe5/HH8WAeOtQ7HpWv8iTeDwAAIABJREFUvU6d8BBiC/u112KyFayjDmcZevW/vusuPGi57ZvJJZfgIdu9u3fdwezZvRNM3OTJA0ujWdyYSxWZoqB5cz25PHcutH2nBu50wnTv7t9LVimImPbtMfngKghffKGX8zXFBYWDUb8+vCErV2ICx5aokiVhSXQXk+fi1S+95F9JIWtWiH9O/qpZU2eEe8Umli+P+9600ObPj7jDQoVw7W3Zovd54AD2x8lD+fOjViARBL2bfv1gheTxMVj2eJcu+B7cP7hQIbikOUyEk7iIIHgnTfIPjVi6FNef2yOSJ4+2unHYg1toLVoUXQHIFnB+cXmgYALwhhtEAArhEVQAliljdwHxLL1ZM/w7dKjOoPIqU2H2WYyme8dGjx6wAhYtqoWrG24/ZAblc+C9mdRRv752H9Wv73SfsTXDL+MuEnA8GFtV3c3hOfnj+edTVlR31arwa+x5sXs3Zt+lSjkTPrZvx3cIpRAvt74LN5GoZ0/ducDsq/rPPzrOiGfm11+P7NVy5cLPPmb27kUg/5Qp3sWl2c3fuzce6DzBuuYaHZvlR1KStqLYYLfYjBmw4JvkygWLY48e9tpwnI3t133BJGdOWLXMOpxHjqCAsCkK2CVOhESDaMF16ZhevYKL2Z498X353HBmKcOlTsqVC+ysYqNqVdwLy5fD8sQF8gsXhphp1cq5/p13wjX6+uveE0y2Gi9bBk8Ffw6H7HhZjcuWhegyBXrOnLBEFSyIe8Rsn8cx4PxsyJNHX5+2xwkXFuewimC/badOOM9Tp8ISXaIE3N5ceJpjn4lgXb75Zt372MbixfhuTz6pKzTwxOObb/A3xwO6hdbChdERgDffrMduc9077xQBKKQNQQVggQL2gZEbZLOgGjQIrgki73pMr74K643NYhVtunXT7YWI7AWh+YYzLZgssMzi1TVraldWQoLTksBZbmbV+mjANdxYpLitJVu3woIQzFrgZtEibeUyrRuRYPt2uBybN3fWluMZL5eU8GPpUojucBOJmjZF2QrTraQULBscX8itDceMgUgrWRK/fSTg5JxbbnEW1zVhN//gwbDmsdvtqqtgyQh2DjgezSy+bDJrFqzeCxc66xuyiDh71lsYsTj1K75rkj07zqP5XTmWjUXBf/4Dgf3YYxgn/BKtQsFv+2uv1WEcSkHIeWVLMx07QvAULgwL1NKlTms5JzrUrBmaNbtYMdTfW7wYCRTc07tAAfw27lIvXIblvfdgcbPBombNGj2RK19ex2r/8Qf+z72lmVKlcA64zBH/Jrt24bPef9+ZQLF1K5az2zxnTl3myT0ZVQr75hqD2bIhdtqPDh1wfU+ejOu+QgVYzLlgOYtNIgjUqVP9u/RwH+NDh3QMMmefszGCu8G4hdaCBdERgDxB42cMv+66SwSgkDb4CkCe5dsGeXdtpGuu0QG0Xi6nY8d07TMOAv7tt5RbA+fMQUmClNC5s24Hx8frpmdPzN5799bvcbmDEiX0e1Wq6AdZuXJO9xmXNAml3VE48HGx9YTLIzCbN2MQPXUqeLFjk+nTkXRw7hwe2pGMw7r3XmTU9u7tjHviVkuhFOKdMgWWinATiapWhXvcdCsphcGee47ywHzTTYjvKlIEv30k2LEDD+h77/XuG82TiVGjYC3g+KSOHfFgzpLFv9zIyJFY35bwpJSOg7v1Vme7QBZ358/jwW2L6eVjc9cu8yJrVlhozELsXNdOKS0K2AqTLx+ETiisXx+YSHPxIq5fLzdyv37OiV7//t7Z0gyXiileHAJkwQKnO5H32aRJaOVxcuWCoJo/H6KMLbq5c0MUurP3OZP1zBnvMjnssdiwQcctlyypXZsXLsD66Z4UlCgBUcxjH4cf7NiBpLYPPsD/WZSySGG3ebZsur/1998HHlefPvo6ypkT38GPdu1g5b/pJl3TlCdtSjkLNl96Kb6PX5/3+fMxaX/2WWQ8K4UkDzMzmksfuYXW/PnREYA33YRlPJkXASikNQ4BeOONzmK8HJvg7lGolNMsniULLAUcoO/lcjpwQFdu5+K3Q4bAFZUSBg+2u3D96NhRz7iInO2AmM6dMeiaD2ROsihYUL9Xtqwu0VCkiNN9xsWwiaJbxuLzz3UNO6JAax1n7L3zjvPYg3HjjYgt41ZLL74YuWPmYxowwPmbc7JCKC3HRozATJ4otFprXnCMW0KCdisphVgwfrjywDx9OiYPl1wSuezuBx6Ai+6JJ7yLhnOv3EmTYN1g60SrVui6wA90LzikwSy+bDJ0KCy+69bBqshwWZbff9euOzdcmsOv9AbD1+iUKc4OFo89pl3qLAr49yhcGK7OUOjbF0k6JuxWO33avk2vXjqTXyltvfOjYUO4RMuUwX0xa5az3FPv3thnhw7emdMMW+p69cI53LlT36dZs+KcX3GFc5slSxDH5tdOjYX5/ffr7QsX1uVNfv0VQs/tLi1WDBMGLtHEQnLbNrh3P/wQx8iilEsMsXWYCL8fkV10m5bkvHm9fxemTRudrMduW7NguVmwuWhRbc32Yu5cfD+uv6mUdi0z/Pu6hda8edERgJMmYRnHcYsAFNIahwCsV89Z14sHGltw7ezZcA0QQQR164YZPZF3Ov6ePbAuEekYkPr1/bO3bPTtm/LuFu3a6cr7RLqcgUnr1hAA5sDLZVZMi1OxYjq+Jk8ep/vsgw/0Z3B9uXBaLR89an//k0+0ULElMnC80Icf4hhDZfhwuEhCKeqdUriQLMdKMTwTDlaIVyk8ZDm5IVgWrBcnT8LC9Msv2uWoFB6oJUti33/+qa//efNwXvLmDT/55K+/YFnnDi2cCWuDHwwzZ+LhxrFxjRvrJCy/bEpuJeXlGmNL7ObNzvuJP/eff7APm2WMW3G5hZcNdinPmqVLkyiF8YDvNbYyVamC2MBSpXR2ZjBatQrM6meBarr3TcwWYEpBLPu1ElMK1sn9+xFTe+wYxi0zFo8TSfr0Ce5O5hjeESNwPT/wACx/fK7uvDOwfBNbsfy6afCk4eGHtbjOn19bzH76Cb+pWywVKYJzyNcBTwK2boWV7MwZHcOrlBZFt92mj5lb+tkSPHr21F4bd9ytjVatELoybhwKTDdsiGcM/2ZcU5QI9+zcuc7C3m5mz8Z3PnFCT+KeesoZ2924MSzrbqHFE9RIC8CJE53njV/cwUcEoBBtHAKwRg1nSROuteQOEFcKg1/NmlheowaCdjmb08vldP/9EE5Zs8JSlpyMwSnUumZM167+dbBstG7trOfUrl3gOk2bwrKYkIBBbfVqZ3NwzlwuUAADEg98pvvszTd1j9fffsNMOm/e1MXTcXyf272rFIQdxxnmzh04o+bel599ljJ3dP/+sNKyO8eslRYuXI3fnYHJ5VjcLbFstG6Nh04w65cfV12lr1GzBZg5E//xR1yj2bLBSjZ0KCYBfv1UQ2HcOIiue+6BxfnjjyHkbdaczz/HtcTxSw88gGOrVw/WFCL/WKo+fSD+bfevUrrIs7u12JkzesIzaJA9qYuvDy/rogmHKSxY4Jx4PfSQrslWsCDGm/Ll8XBnkRUKtWoF9upmgepVW9Jd92/4cO/QFYbFabVqcCVOmoTrg3+7Tp0wfg4dGtw1zm7ciRMR57Z5M35rtgxu2YKYNJOZM/Fb+hVT5tCQxx/XluWcOXXZlB9+gBvebIOnFNyt06bBza2UDmXZvBnH+ckncFM3aIDlnMG6cqVuUcjb2BI8rrpKJxNdeqkzS9qsfce0bIlrYcwYfX2acYQcb04Ei+yCBbhHlMI5bNTIGVrE5+6VV/SEa9cup5udxwK30JozJzoC8MYb9T1srssx0dwPmS3oIgCFSOMQgOXLO+N92MxuZoYxkyZhwCPCzdm2rW4F5PVQuPtuiLdcuSBgeJbON26otG0LUZUSF+CVV2rhkDWrHuhMLr8cwrZMGe3+27cPD1EiXd6AuzNwxq9p1XjlFQhEFhHsQrZlUiqFwSohwV4YlQdUWyzU++/rQHDbjHr1aoitUJuvM1ddhbg4DuiOZEmYZcvgfuKHHnPNNfphE4y6dXXWcGriE99+G78nZ/61a6fdSo89ht+VH2Lcq3bZMrgIs2RxWlMfeggiPSX07YsHCjel50QPWzFqFodcw2zTJhzDZZfpuEk/S0r37rDsmKU9TDjjdu9ep7Xp7be10HUnSzBcCNjd1k8pTHbM8AcWNcuWOWvbPfCAznTlWnOlSiFxqUaN0OpCKgWrrDupiy33bN11w250JlgnCaVgkXrpJV0uhJNseFxgF+WECd6TYIZjcydPxljKD312XT/4YGD9zilTIBq4cLDN+suTFk52YPHAFv3vvoM71h0DXbAgBDBb+FiUbNyo4zO5cLhSEFNEuDa5XNJ33+H6/PzzwOMy611yZxGlsK6tdV7z5piIjhql42SvvVZ3y+Cag0R4bpm9ndl6aZ6f6dPxe5kx0Rs3Oottt2ypxxbzNXt2dAQgtwLkZ4RbAPbqhX+51JoIQCHSOARgsWLOOBiu9WQGbjNjx+LmJEKpiJYtESNC5O1yYgtQ/vwYoPkm9uuvabJ9O6w+TZtiu/PnQ9tOKQwofGOVLGmv51azJh6sBQpoV+6WLXgo8efxgFqunHbjmNbEY8f0+ufOadeL2YDchPexb1/gMh60bT1yzYe0e0atFGJ0Bg7UiQyhJtq0bYsHHVs+g5UaSQnswpo61SkcOnfGZwUrxKsUBvtnnsH6tmDzYHA3Bcas/7Z8Odxj7I7kXrW33KJn42az+zJlQhcpTJcusLSsWwe3WHIyJhQffRS47unTEJws5tetw29eubKuTWbG7Lrp0AHXqVe8bEIChMLBg87uLCdP6tiooUPtrlGeHNrEZfXqztAFFiyrVjnjazkpSClcZ9wZ5LXXYL164gnv78b88w8EirtHM5cJ8QorMBMKlAreSUIp3GdvvIEY2See0Ek2X36J5ZwkMnOmvc6oCbfhmz4d9wJbdDns4JFHAjvmcK079jzw55qwZ4CTHdg6x5bBb76BGDMnrUphTF6xQgs87oKxfr0WdWYJFW5jt2SJngifP4/f4tNPA4+ra1ddNJyLjCul6/m5J6hNmuD7Dx+O7bp0cYr0Z5/FvUiEmL5ly2CtVkpPnM3zM20ankvcflAp3Nec9awUvAscW2u+zNChSArA8eOxzPQymQKQX/ny2fc5erQIQCE8HAKwQAFnwgcLOnfvVqUQbzF3Lm744cNxw/LsycvlxK40Hkg3bPDev5vkZDyYjx+HpY4I+wiVJk30zV2vnr2eW5UqcENmyYIgbyIIQi5efPastmYULqwLWzdrhpn7ww9DEFSrpgeg/fsx4OTIYXfZcPyHaRFj2Mqyf3/gsjfe0PFH/NA04cKnbGEKNQ6xSRPs78UXITZYyEYCdsNwQDbTvDk+x8tKanLJJfqhYXONB8MsZquUM8lh2jRYCfh8sshetQqTHB54OfawePHQsj1NWrXCg3zNGl1DrkwZu8jnBB6OnVy5EgK4dGn9UPJrn9eqFcSY293HcDLD0aPOWpFmp4lhw+yFqjnj32a9L1HCeV5YIKxd6+ykYlpgOOavUCE8pDkgPxhsMXPH9HJRYq/izg0bQmQx7s4gNvLkgShv0ABW06FD8RlsoW/aFN97+XItRrzgBJhZsyAWV67EvrhW6oEDOluVMUWqVwHzd9/FOH70KIQRn3ueCH75JTw37hCYvHkhQll0mm09WZgeOKDLIPXujfcXLnRasb0yfM1OK2XL6uudXbnueMZGjSC0hw5FOEuvXvAccDz6009D6BLhPJnllHhcNs8PW0/NEjo8HjFswXULrZkzoyMA2YLsfvFzkV9cOk0EoBBpHAIwe3anEOFAc054MLnuOoiMxERYCBo00LWh3PE4DDdg5zIKN9+MAd9d8NQGDzJPP60FWSiFgxmzwGznzogbUso58yxTRhcC5WywadMwUPPAxvE3OXPqOKjLL8exlC6tG7XzTPj++/H9ata093xlS6M7408pPTjaWrO9+qpOSGC3mcnChXh4s3smVGtZ7dr4TVgEVKwYWDMstUyejEGcsxmZOnVw7ZlZmV5wfbisWe2uJsYWIK8ULBqm9cMM/h89GoM998Hlgru33w4LLg+8HHt46aXBu0e4ueIK3AMrV+oHVr16dgvwG29gosHZ04sX4/cpUkTHYPlZyZo2xb4HDnS+n5CAyQz3VnVnQ5q9ZkeORMC/G074sgmdggWd54Xv3bvvdsYacqKSUrBUnjgBa8f772O9UFoSsqXKPUaxldirwkCdOs7x46abAruhmJjZ9k2aIH5s4EC8x2KGRaX5vbzgcWHePEymly7Fvri+HVsITUaOxORJKQi2998P3O/rr+OaOX4ckwUWyBxP/MUXEH/uGoO5ciHEgD+TLahr1mjhaCZNdOyIifK8efozfv1Vi2Q3nTrphLKKFXXpJR5v3d1DGjZEWMJ112lLnVnq5eBBXGdEOCb2LimlPSfm+eFC0R99pGOn3VZfzt52C60ZM8IXgLZwJe4tbb6yZAkUgF4vEYBCuPy/AORAbbOW0sqVeDCbvROZ/v11Ha3HH8eAyu2GvGL6ODaGLR7dumHW1bChfX0TFkqPPYYBpECBlD18edaeMydmldWqYcAqXFgXpS5aVLtseeAbMQID/iWXYFbMGXhEEF08AO3YAVGycyfOV+7ceDjddhvcU5Mn291Cr7+Oc5wtW2BxbB4cba24Xn5ZF3jmwHmTuXPhMuFajqFayypXxgyZXUjdu4fe7isYbGVZudKZOFOpEqxuwbpKsDvrm290NwYbFy7g97K1pHJ3bzATUvr3x8OGa9GdPAl31bp1sFzx786FbvPn9+6z60WtWrCYc1yfUrBI2uIfWeSzq3T2bLiv8+fX7iM/C2SDBnjQm+daKdwDXFT6iy9wXZulgkxX3+jR9tg4jve1hW/kyOF0G3NB7S1bnKEXnKikFK6BY8e0O7xt29CSgtgV7Q7peOIJvO/uccyw+5thC5EXZpxbixbwdlx9tbbWKaULCbO482PdOliV2SvCxYYPH8ZYwMWPTczJii3sQykt5rkAPGcF//mnnpS2ahWYYZwjB9zXXIza9IAQwa1q1tBr3hzXzKxZOubuwgVcm7aYZbM0DifTKIVxkygwnrd+ffymgwY5zxGHM+zfr5sQ1Kqli2QrpeM/zfPDAv/TTzHeKgUBb04QOnfWRg/zxVUHwnnZSoJxHKUIQCFW/L8A5LpPpnibMwdizR2MrBQGbhYGBw/CwsUX7rXXBq6vFGZzixdDwB09ikE4KSkw1sUGu5x27MAAV7++d4cD5uxZbWliK0uBAtiuQgUdb8OuZI5NzJVLt+np2RPWhRIlMLjyNkS6LluFCpjd8oDZsqVOzOD6VBs3Yhbs5vhxWD8qVXLWo1NKZ6TZ6pPxdkpBtD33nHP5zJlazIdSeZ8pWRLfn3/TmTO9kwiYn36COAvGDTdATPDDjylaFK7KYPUgzexHrweNUtrdxYke589DZP31l07oYEzLD7up2MLz4ot4IK5fD1HPvzvvN1eu0LJgTSpVwv2xeLEuHzRwoD3Tlh/i3NZv8mRMmrJnx8SERZUXtWvjweuOj8uaFQ97Ivx27sLC3KZOKTykuO+1CbcWc9fT5AmHeV64Nt22bc7JnjkRqFoV93jWrLhWu3Txjgk1rzWuPODui8zWfi9RZ4oQpbR3Qim7tca0crVpA3HKYQFsqaxZE/eNO6nGxtKluvbg4MHapb9vHyaPJ05oMcaYgsWMozM5fhzb8eTBrBnIXozmzQPH3GzZ4PXgmN/nnsN2bJn89lu8xxbCevUw/kyf7ixLwxNlN5xxrhSsy888g/+z4HLHc9erB6Hdv78u4bJihY7Ze+IJHWtdp44Ok1AKk2oi5/nhxDPzfLivMS4z4xZa06aFLwBtJatuuCFwvaxZ7SJUBKAQDf5fAHIygmktmDgRVgS3K4JvFg7q5Zkh9zA0A2tNevTAw5/LKJQpA8FUvrx9fRN+YG3ejEFmwIDgcTYvvKAHNA7cLlkSwrVUKe0+4g4U7F4sWlRnpjZvDuHGZSnOnMEDmI+FCAMtZxjfcAMGO24XNXo0Bnd3oD3DVe6HDg20tLA7wiZ0zYKm1avrAZWZOlU//LiQ67336gLczN9/a0GjFIRr1qwQt3Xr4kHPHQW86NrVmVHpBdf/46b2TK5cmO3bsk3//FO76Tmj+e+/ddaoDQ4CZ9G7eDH+/uEHJKKY9cLMOKAmTSC627XDw4rd4Js24frhgZdL+mTL5h1f50Xx4ri2zONwZ0UzL7yAe4PLVYwfj2ueSLsf163z/qwaNXDPmWKbEwg4ieTvvwMzxc3yLOPH22v9cayUO/aOXY3meeGxZdcunWSglFOMJyTobhVffql7Nbs5dQqimK27mzfjd3DHy3HJHLNGp0m5chBLDIsMPq/uyYh57XFLOE5e4nGwWjXch888g/9//jm+k43ZszFWcHePKVOwrwcfhGXNVh/SbFfn7mDDsEjj8AHOJFdKu2cbNdJjB5MlC6xqbAnmov5c8P/cOadVslo1WN6mTNH3299/e1smTYsuC2WldOyje1yqUwdC++qrtXX2jju0yHvsMRwLEcT2XXfp0A724pjnZ8IEjInmsXLMJsPPJ7fQmjo1fAFomyCbnalEAAqx4P8FICcjmLEr11+Pm6pkycCLt0MHPaPjIPLbb8c+vLJ6r7wSQo4HgKJFMYB7NTY3YVfE2rWYyc6day/lYnL4sM6UrVULrpq330Z8S5EiOplg+XJn/9NKlfDAJcKDqUcP7TJ65x2IpNy58QDLlw9/8wO1Qwd9zl55Rdeueu89rOu2LnBphS1bAr+PKSovXnRaCI8c0c3jbb1Hk5K0FeaSS3RCQcuWEFXMnXfqz01OxsOURXHDhgjIL1DAv+ROrVr+QoThmnJcD1Ip3XKqc2d77bRBg7QL3KxPV6IEXLQ2eJb//vs4b8WLa2HB5SAY0xLH5T24aO3hwzjHW7ZAZBNp1zPHhIWSwGSSPz/2P2eOLsbLcWAMu8OOHIGl6tFH8ZAbMULHDXXrZhcqJhUrYqJkHiO70bmwtVLOODGlnL+PV3IEW0rcBdnZGsSdcpTSbshHH3V2PTF7ECcm6jZc585hImorQM3ChOvBrVgBIeC2lvFD1G39ZNiiz3CGetOm2Je7vM0nn2jXIVuK2rXT44dS2rPx8su4/2+/3R4+o5S+PzkkgbtCbNiAscmM8WVYoCilxaYbjt/k+50z2ZXSVvP69Z1jOl/LR47o+Dj2bnANvO+/19ZFpSBOmzbF9+AM4+RkjOlc4sWkdWvEiCulJ+NK6YLS7tqBiYnaes3X4KZNuprC3r062e6KK3ScrFK6SPSzz+r9jRuHe58nIxcv4n43wwC4O4xbaLE4D+fljklOTtadetwvEYBCWvH/AvD0aVxUZnZY794IPLa1EmvVSpdYOHEC1rxVq7APs5euCQdec6xMgQK4kXnQ8YO7RbBLYts2Z+YiYw4kBw/qh5zZ8osz5TjOZcQIXari++9xfGXK4O+iRfEw4o4RXKqiSBEcU/nyEE3sJqhSBQM6Wxi43hi72N31/nbuxEB69iwGarOsCIvK/v3xvtnT1wzU5/NpYj64ixbFcWfLhuM2rXUtWmj3GWc4E8GC0rQp3suWzT/homjR4PF7SmE2v3q1s6UUxw8NHKgD3E0aNtQu2jff1H16OWnABhcBfv11PJBLlcLD++OPdSkNxgweL10a1wS75jjo/f778TvnyKELFrNwdfdr9SM5GTP8zp3hcmQhunq1s9RSiRI4Vv6N2Xo8eLDOSGzRAv/azhlTujREjWlt5eu8TRstAsz4NqVg3eJtbrrJ3gmIJydmVq9SOgPTPC9sddm/32kFN7PB69bV8WA//AALItd8M9m3D79liRI47ilTcC7ck0guq+LVMYgt9MzixXggN2iAY3GXzuExQyltnWzZEtcDJxJwbDNP9mbN8u7ywrGna9dCeLCwX7UKvwsnc5iYLkvuSuKG+yt/8AHGPvOeKVgQE+A6dZwFzdlt/9JLur80J8Fx/NsPP2A5f5+CBXEd33ijLliulPfErFUr3WWqfn1dn5HHdXeISs2amLj07KnjULdt05PVPXt0I4ImTXDNsjjkcCHz/HAogznZcXeb4cm6W2hxwlU4L3cZrhUrvNcVASikFf8vANkaxq4fpSAG587VM1+Tpk3h0lEKN3zx4pgJE3lnwLHbgrPlcuTQPSqDFSrmOmx8Mx4+rAc25o8/YKHhyvL79mn3h+km5QK/zz6LfbVq5YzxadFC15jKmhUPI64Sz7E5FSrggcwlabgmYvbssFpxXB4nFCily9+YcJFT/n+xYlokTp0Ki1fnzhj8smbVwcQHD+pMZk5wMTEz3EqX1jE97dtrqxHP3NmSyOeALRH8cL/sMu+Ma7YoBeujqpS2YJg9YD/7DN/rhhvssWalSumwhBdfxENWKXvcI8OTmRdfxDVQt66OyRwzxpkYYLqOOLOSHzj8MN2+Hdd33rzawsHlNdyuRz9YYLdpA+HCXVbcpWmyZYMAOHAAvzEH9vftqx8ciYn4TjZxxhQtCteXOanjiUiFCvrYk5PxAGfXtpnFytmTbpYtw7XuDg/gZC3zvHCHFS6RxJhxdw0aaLfyr7/qjNfff8ex8PiwaxfCBWrUgLt06FBMHniix6xYgeOz1ftUKjCGlN3RiYmwVvXvD6HPk1nTInf11RBqTZpgwschBCx++L4aNgzn1bS4M0OGQOByVjrHdC5YgMmGWeeTMYuW2+55pfS9xdZys6Yjjz81azpbW/I9zN1C/vxTx3hyLPRPP+l9saegf39MYkzrKBfLdsM1EpWCxY5L/PD3dpeOSUiA+OveHedq0SJn60AOJyBCmI5ZU5JDCR59VO+P4485ROGnnwIzlvv10y5p88XnIJyXu2sRP89sL1tjM56QAAAgAElEQVQcoghAIRr8vwDkjFazPl7DhroxtTuGoUEDfYNxvAnHWtn67CqlA4SbNtWzfW43586AdcOzfK6K/uqr2rXBcA0tLreyezf+Tk52Bn3zjJXdHGbnj7/+wvET4aFChIcR14hit1zNmnBRdOiAdXr10nWphg/XnQxKltSzzLp1A8t9mAIkORnuZ3ZdjB0LodOkibau/vgjjvHRR7XlrnHjwBIzo0frmo4VK+JhwQ8ljulaswYPBRZV/OAigoWHB9Trr7eLM6V0bJStVpybzp3hxuEEE6V0BirH6Jj89Rd+Jy7czPGSSjk7RSQn47dh6y9fU4cP68LPXNvP3YeYHxz8EPzqKy162D3/0EM4xoIFde08zmx1W2n8YIHdvLnTssa9Tvk7E0H0sbWc47i6dtX3Y/nyEHF+BYcLFsRvbWak8jFky6bbeinlfBiamdJmLKnJvHn47uY+lNIB+KZFjsNLzCQCpTCZ4303bqwffBcvQlhMm6atudxf9oEHINBWr8YEpVs3WKnYcsUsWAAx4pVg5i6+zbF41avjXu7RA+efY96ef17HKnMyRv36uDe5zA5bFTlZqVUr/GsrjMzW8E2bcF9wYeUpUzC+cL26r7/G9ayUDqFRKrCQNfPww3A7c0cQM1mMJy/sOuXJJE9M2Hp7/jzi9Yh0u7JfftFdNHj9kSNx/fGEWqnA2EqmRQvci3zsHHvHsdbudnDVq+Mcdemis/OffFInJD70kE7MYi8Lhy1wYpAZ3zdqFMZDtnbzpMSMPRw40O6WTUoKXwC6KxJwn1/ba+3a0PY5apQIQCE8/l8AclcOs8du9eq63IM7Tb92bW1iZ/fI/PlY12z3xPzzj7YyXHmlTnBgAWEmItioXBk3fM+eWP/0aWfmolKY/RLpnp48i/3rL2dvUXZJPfggBBcRxCM/RHh2VqMG/p0wQcf9sFWmUSM8nAcM0A/12rXx/7Fj8f8nn9SuR6VgyXDHyq1c6YyZbNlSu0quvRbnKiFBByKfOYP/JybqTMPmzfXgygwfrkVZ9eqwMhFhFsxZvU2b4kHLltTTp7Xlc8kSXaR382bveEsuVu0lEE3atkUcEItopXT4gNs1q5SO5eOAdbMVFV9/Fy7owZSPga3Z+/fDktm5s34wDRiAhwnDCQ/siv79d+2aZGG2ezcEQ5Ei2vLImcZZsthLPNjgh07DhrimWIib5TW4Zt6JE7r3KovNRo0gWHPnxmSqfn3vjHulsN6CBc7OJxwDReRs88cFmJVyFjJ2x0wy06bhnnJn3544gXNiWqu5H7UpopRy/ubNm2v32//+h4fupElazLNbkROIzp/H9yteXCefmXFW06fjWnHHBiqlLZ5mWAO74StUwCShfXtcG+wmN0MuuBxL7dq4p3nCy1ZmdqlyGImtpzF3xrj3XnwWjyNjxuB+5y4wt9yi4xg5O10pZ0ydCffN5Xvn8GF9r7GFksc8tkpduKCFH5eKYTckZ6r++qt2J/MkIikJFjx2NyvlnZzSrJnOlm7ZUo9XnEjDIpepWhXnpFMnHZtnfhf+nkQYV7Zv12MUT/zNUJcRIzBp4XJnbO00XbODB9uFFrupw3m5DRx+AjDUlwhAIVz+XwByYVdzgC5RQtfZ4hk4Y6byc/uh2bPxb5s2GCTM1H6zhEe7drrO3q+/OkWSjeRkDIaDBuFhliOHtiqYs35OFGFBxbPY33931srjh/369RhICxSAe4H7vLJbgoO8J0/W8SEckN+mDdyT/8fed4dJUaVfX2DIOUkYQKKDgGQcQHLOCAZAQRARURBRQIICIiDRrJgwAgqYMybMaV0x65p1XXfV37e6oq5hYd7vj+Pxfau6qsN0zwyMdZ6nH5gO1dUV7j33DefMmIHJjitWDowdO6rzCH1egzxCqXFFjB+vReVHHonfXK+erkxfegkkOCtL0yG0MLJgikkEZPHCCzFIM7rz+efYxvPPaw3m7t0gAiSKTAO+/z5W+Jxgr7lGo5S8boK6WP2guC9JnwiKsFu2VJHoe+/V+qsXXsBEXbYszvOtt6qAbceOOBeTJ2NyufJKjSpSTPeOO7TGj0XzVr5IRFNmTGPl5anw7PbtIMmMntapo7WkXEQ4F+zjHAR2nbdt601Fs65URBsmnnpKu3/37cM1lp2NY1C1Ko7LwIGaovSTUJKcdeu89XhccDnn7Q62tVvLl6sclN8tgZg9GwSIwsDE44+DNNnj8vHHuGdtCl9EC/NFsNBZuVLv6YUL8b08l8w2WLmPiRPxGiM+1k/5jDNwfILql0kC7Jh26aW43+rVw4TfvTsWTbQNs4uPqVNBJnJy8H+WzVD7U0SzB1lZwXZ0vGcZ0Rw7Fu+fOBHHlSnc5cu1icemfa2wssVNN2F7vD4feECjoEzPNmyohE/EmxZlFy+jUBwLf/xRo/VcyCxdiuvE1keGlWbYqJ8dr7p3x7b8pTFNmmAMGzBAax9feEG1T+kjzfvAdq5z4U/dQRF1tGHDy+OPx9aehzVlzJ6dPlnzOzGR8EcEMEJR4g8CeMcdWP3ZRgOmhSiP4r9BubL9+GN8dsECDJg9e6qtFvHZZxoVGDJEGxx+/TVcO4pgBGTZMkzyVap4U7bEySdjciUR4Cr2u+80dSeidVAXXIDIXrNmIKQc7Lnio9XTOedgYF61Sps2Ro5U55SKFTFw0jR84UKktNauxXEhSV23LlaU1z/B2rRY//44juXLY8DngN6pE/7P+iursUUcd5zW+nXsiPRH7dqYIPr1w+DYs6emffftA0Hm5DBnjkYe8vLwWTZd5OZq8wHrtsL8ny1Y+2MN2W+/Hc8z0rRxow7kO3Zg8uJktWmTRpe7dsXrNHDfs0d1zrho2bJFxWPZeejX/mKjx6uvatryiiuQlt+6FdtnqUCDBtpwwwWIP5W4dm2wqLOIRiZzcrwOG5zs8/IQLXMOZNX6FteqhWvprru0q3n8eC18z8nxym+Q5Fx+uVd7j/tNskHYBRIlSkS83coW06fjPDEiQ9x/PwhM6dJa18UUod9xxHq79uuH72JUn125rBFm5JypWhG1e2Pa2RK66dMR0SlZMraDnREv647DUowaNUC62rcHCeKikPe9iNar0suX4431wa1TB9/RoUNwfWxuLq79W2/FOR4xAu8/8kjc30zhLl6skVrbPWs7gi3YDMFI744duGZFNApO/Tx65Vq7SEbwWHJCUvTf/2pzy4cf4nzS0cf661LiK+j3skxlwACtZWzTBtt/5RXv+w8+GOSzb1+VkHntNc1WcBwrXRrzCWtDRXThb60lJ09W0fZSpXA+/eoWLC/yP2bNSp+scXHy/PO4NyMCGKGgsdw596Vz7gfn3FPOudYB7/mDAG7ZgkmedXXWdSGIoGVna7Ev0w1nnYWbiqlFWwv4+us6SIwcCWLDlGtY4TDx5puoh9m4EQPrQQepuKytraC1UlYW9p+aTt984xVOZQ3LggWI2tGTkwMCpQkoznr++Ziwzz1XV9i8gZcuVUV6ao8tW4ZBfc4cr5SD7X4l/KnPCy9U4pWbqytxdrzdfLNOLiQHVLC3OPZY7czt2hXno0kTjWQsW4bVu1XxJxkqXRoTKCdaEUSaVq/G+apUSQnfBRfg80EkwQ+SJxsxYBMMddguvVTrfC6+GN9bpQomGXZMiijxY3e2CCa+yy9XC71Nm5RQH344Jty+fb2pM2qbWeutm27S9/Xtq1HOJk10O6zLszWeIrie6tULtqIjMW3SxFuLyHQyJ1nnUCdp65pYjvDQQ0rSZ87UiGiFCt5FAEnO9dd7tfdYU+ec1/XHTtzWFcMvUUOccAIWJawvI3bswHXL43L99ThPFSp4ib+I12d40CB8L1OJbMp46CFdVIl4I+Z5ebgmfv011hv3hBO0dstff2WzEQRlRCpVwjWYk4MFFMeoG29UIsZ61QYNcI9lZ2tk6e9/x3uaN+ck7T3OBEtEduzA/Umrwf798bf1CCfxtEoGbETxY+NGLGqZpr3pJs0UsAyG4xUJOhfYP/ygpRVUW6Au4i+/aFr6jTdAxFgqYDuW7T5adOmiequsBRZRLT8uzomGDbEw7t1bMwd/+5tG7Zg6L1cO5PmOO3Shw4U/pYJEvF3lZcviuvFHr6dNCyZaQZZtqT4YDXcOiw0e14gARigIzHfOfe6ca+WcK+ucu8A59w/nXAXf+/4ggNddh0GPAx5r4v7739h2eRGQReo9MRp36qm4oQ8/HJMGV8YiXsP5sWNBSHgzB60aX3lFa5Juvx2r4ptvxkB/8MEaxaMtlwj289lnMYm8847WFP3jHyBiXGVS8++UUzBR9O6Nm58F3+wEY1H62rWYEOfOVQN7pkbWrNEJedcuDJCrV4PUjBvnLUL310CJxFptbdumK9lWrTT9WLYsiLKVDyA5GDHCu9rlMaa3bq9eGHDatMHxOfhg9b218jesOatQAdEhGyG67DJMUiwUp4Av9cvCBHctDj0Uk4PV86O4KyM+GzboMZo7F5PtoYeCCNjaNEYFbHc3CQW7uy+/XOU2WEDfvbu3OJzdnUzti2hUkhHHnTuxvRYttJj9vfdwrlu39spNsKbJpp8I+tPWr69e2iK62PrnP9WD9b77vN3BTJXt2qVF/EuWgNwx2mfLCzipb9vm1d5jGpoLIMLKilhhanpK+3HssUit+6MoJK3UpuzZE9dapUreSJGIRtVFkOacOVM7XzdsAMmhHAmvxcWLgxtfWH9n94+qBP7yFasFR/BclymD39CwIY6vczg/V12lqVhq+NWpg0VfxYoqC8Ra5g4dMFZdfrlXE5FgUxpdV/r2xedzc3HMmKo/7TRtzLONbJQq8oOpbI6PGzfqIoGfZ5kHF/V2EXjEEUinsp6bZS2//ab37YsvgvTSyeWVV7SEwYo8W1D5QUTrqUVAJJ2LrRvMzsa936OHftaW/TDSSV3Nu+/W48SFv3XXscerUiUsKPx2fUHOHJwn0iVrTLc7h0VVRAAjFCQ+cc7NMn+Xcs597Zw73ve+PwjgZZdhpWkHAkZ5/LZJIioubAeQKVNAIlmcXqmSpl9sDc24cZgAOdjTps3ipJO0DmnlSkz8LO7NydEoHru4OOB98w2+/447dAL49FOk93bv1u1nZSGKd8opiEiOHq1F3rS0o5/opZdixT9zptYgkfhcdpmKBL/yClb+F12E6Ejfvl7TdavJRdhJUETTsCKalitTBtsfOBADWalS2H926Y4Zo2SPGDVKSeGAASAmubkafRs5EvtuIxcspK5aFQTSTvzvvAPCwwmZk+G4cVj9sxNSBCQxyIe3WTPUB9m084oVahE4eTIILo/R+PH4m165VjeOUQQbPWanH2Ug1q/XgZ/uDawdJHg8bITHWhsOHaqEslUrleJgPVSfPprOEsHxGzsWk6xf2oK1arVq4XjZZpQKFUAqKWJ755262BDRFOELL2ja7JJLQAYZ7bGCzxRkvu8+7yKE3aVZWd7rzk7Q1h+Z+nh+jBoFwu7vguYxo+xHixa4xqtU8UZ+RbS7UwTX40knaRr+8svxHKPqPDdhsjR2gcftXXGFty6PYA2blZ5iZN85nKeaNVVyas8eb2f02WdjLKheXSOUjCpyou/dGwtS+qT7Ub8+FtUcF9nQ0Lo1rjHWgk6ZopEq22E7dao2u1mw5pUR4A0b9NhxsVSpEl5jzScJ8S+/4Nxdcw0IknPadLd3r6aln3gC55XHhMLXIhrZ9KNjR61fHD0a5zcvD9dhyZKx80u9eiDa3brpNnlN//yz3hscq+xx5sLfKhNYG71q1XBN+stxwiJ9YZHBVB7U2HQOv4uOPhEBjJBpVHHO5Tnncn3PP+Kc2xDwXvn+++9l7Vp1F7jvPkxS7BILuqmtbARrSMaNw2DWtq229zNCZw3Sjz8epIX1QAzxW4wbp7UrEyci9cNUXLt2XucOEaTkWMRPwkAbo/ff93Y5imDCHTIEN+PxxyPCwgFk61ZE3CiNc/XVWLVNnaqrXqaHN21SPar33sNvpLZXq1Yq8SLibTQgrL2Tfc++fVqQzZqvM87ABNGwIaKprP865pjYdBC7DPn/3FxEzVgc3q6danHxXHJQrVUL/9pIS14eBuXBg0FImZbq0we/n5OjCD572WUSgwYNkAa1ERjWijLlt2KF1k326AESMXkyzqWd/DnB2/IENhWwZm/FCq2VortH69beCAWP9yWXaHqZFmzUw6OGYtu2elx37wZJmD7da5XWoQMI5ty5ILznnaeT9m23YX8rV8Y5sykqEtlHH8V3bdvm1eNjPeru3VoDunkzIiWMjFh7L5Js2pLl5SFSyPRdnTrec2TvQZuaXbUquNN40CBEwSpV8j5/0UWYkNm5WbmyEmKmEAl77Y8Zg/NPIkHXh6uvxr3ILmnbOGLh7z4dOBD3pp8Yiqj2pMXmzer+8/TT2M8ZM/D3//2f9zjQ37tSJU3rM2LHtPKIEbgv/I0vBMcjak126YIx6eCDcf+wLODYYzVzYstYrM6nxQUXgFwwIrlihYp60/mCclWs4SbZ/O03jLvr16v2HeeEffs0+n///Rg/GG20vzFoMS/iLdUYOxblHcw+1KzpFcAXwfV59tnIJtEn2mZ9rroK+1ajBu4lHkcRXfhbZYJx49RZplYtkGK/vFFYrR/rr9N5fP01vsM5LHTCCCBVGCICGCG/aOBAAHN8z29zzl3re+4PArh8uWpRXXGF18w8SGfOFjzzRh41CoNoq1ZqlM7CdOvjSJkFpvoYnbEYPhw1Vr/+isFx+3adiFlHZ+t+3nhDI4qc9NmU8fbb6uBAVK8OErN4MQbT5s3Vtum++zAAUYLixhs1/ciIFWvfbrtNI6dffIEJ+ptvMKHVrOmNnthaL8LflECdqq++0uabQw5BmmnDBhz3bt2Q0mTEx65uicGD9ZgeeSQm0JEjdfs0nBdR/TKu6OvVw/b9jR28Prp316gErfIs0e3WLX6UhguG//wHx37BAi3uZ+rpp59AaJ58EgP59Omq5i+i5KFUKb0GmLpk2nzxYk0VcwLwR7NJiJcs0Ygzyd0ll+A8PvMM3tOpE47lpZdiIq5bFyTKpvgYZfnf/7AQGDNGSdKmTZjMy5aN7UamDR2jhFu26PeL6IT87rsaLXrwQRCJt95CuUaJErpo44LoqadwHLduxTF49VWk61q39tZCWq9Wmy5bs8Yb3SV698Yxo/4bsWoVPj91qkbQhg7F8bSpfxFvI8Mxx4AYMPrNVPJFF2E8qVABJDYs8uWvPevRA8ewcePY9CJVCyxuu039nt98E//yev/iC0SWKZ+0bBlIcpkyGN+cQ6OLvbcnTMC4Zju8LdiwxLrbdu1wf9SogfuUUV1rxWmzGGecoQ45FrTX4wJ50SJdRLBcoVQpnDfaoPEe2LtXBbhJhlibmJeniwqOeWyW4oJJJFyg2mqgUnCZEb3mzWOtLGvXxvjdubMuHFnq8OWXujg66CBkCnbu1Eg3F/5WmcDWRNeti/vU7zTDrE5BPFgaQFIfJjlTunQq240IYIRYpBwBnDlzpnTpcqa0bXumZGXtlMWLve4B/sJ56lyxi4w1TAMHYtA+5BBdNfGmt8XbJ58MEkdR36AUJkVUd+9GFOGNN1QSgrVvTJuJeCUCmFqidt5rr4FAvfuubr9OHQwYK1eCgFStqjpSH36IAZ4dmbfdpg0JnAhoNXXvvZg8nfPKUFBLkH68Ipq25mpQJFjCpWZNjT5+/TUIcNOmOAfOoS7n+ON1YGcK1cK6Bhx7rKYdRRDdcE4JPAdYdvU1auS1YCMoa3P22TopVa+OyYLRSBFMpFZihGDUw6bvJ07E95J8MrL6z39qhy0nGlvIPX68dpLzeFJKZvt2PH/WWVp8zi5A2w0uorVyJ5+spJVdq0yn0TKwa1clkhTYfeIJrR0Vid0+62N//RVkkc4xI0agGJygTMa2bbrosDZ1LMr/5BO93l58ERMGZXWqVlWC8O67uD+eew7n89JLcU28/DII/iWXeF0Q7EKEIsUi3q5bi9xcTOK0ACPOPRckYv58FVTv3RsTuj/yNnSoRqnHj8ffbMRh1+3KlSDdzoEUhdW+2QiTiKa0g5oS6Odtcfvt2rjBpjZGvz76yNudv3IlrtsSJfAaxxjnQFJEsGCZNCnY0YPj55dfqt90q1ZYnJQpAyLMRVK/fvp5W+fINLQfPP4i2L85czQ6TytO5zAe8HgxJZ6Xp1F2Ohv17avnmETxuuuwX0z3c5Ehok1SftgOZioUcEHA5rALL9R5pmZNEO0OHbCvvK4pGcZSnHr1cC6sSDwX/nYBa6/pBg1wb/iDDplw/Ah7sA6VC6IwAsjobPhjpzh3pmRnnynOzYwIYIRABNUAfuPi1AByRVm1KiZL601qi3ZFYr1DWUfWowfSF02balEzV/hnnaXWV6edhnA9i9P9dXAimuZatUqbUd5+W28gEewr07pMdYloCosrupdfjq0FatgQg8eFF+rk6hewZm3jXXepoPD8+RhYKKz82GM6UVhJGmqUWdcJkVhJnaAB87DDVMrgp5+wX926aU3inDlY2TM6dOKJsVGRPn1UUJp1g5wY6tfHdlgEzyYcStI0a4ZogU1tiuhE8cADqgvoHEiCLahu2lTTMSJILc6Zg0H3b3/T6+Xzz9VXlQM6SftLL+HfH37QAm+bMpw0SQds1htSSmbLFjx/6qma9mJdm51MRPQ3jBypsixM561cCdL88st6fVME+MknMekxikGhV3tN2u1/9RUmPd4XAwZ4O7dJwHjer73WG3276iqdSEisGHW6/378zm7dVGCXXfcvvYTzvX49FjjWGcKCkU0Rb2Tuwgu9QuVEu3ZaK2tr6UiUVq/WDs8uXbDgIrFiCQTTtCK4X/r21Un8rruQhWDTR+XKIG7+kgmCVo0Eo11BKUlGeC3uukvlUZhqpNPE22+DbPF+WLtWS1xIiihJw992ww0gGP60t4hXd+/ppxGlbN5cS0nGj1erwdxcjbLaMczWw1pY4W528/Ma6tBBa3ibNNHj9fnnSvIomzR5Mr6vRw+MHSJ6rV90ERYwbMQgiRXxilVbWEtM3kO7d+N+7NwZx3/yZG1kql4d91/btoigc/HO6+CSSzRiPHmyV1yeY4hVJmDaWQTHm/eNBT9XEA8GS5zDfcr5wf9gfWaiB7YVRQAjBGOec+4zB+mX8s651c65L1ycLuDp09W8fOBATXeIeMPnIt4UHpGVhRv5yCMRcejeHekM2ntRPFUExOzgg7Vtn99tkZODVXF2tkZYPvkE30viQ3svEa+/LG2kWNT73HOaciGaNQMhueoq7RqzaUwRnbwfekiLxJlmZKTm+edBlv2pMGpK+bW6/M0oQfWVQ4agvocaZscco7U2zuFcPPusTp7+TmIRr/US94URrjZtvM0oXIFTkiYnBxOEf5siiGiwhu/99zFxbN3q9YStUwcRV06G552HY5eVpVHHsmVBYGixR/kKSnfccotKgvz1rzhuVu7mpJPUa5UiyIzOMlJ64olaOM/f5veApWBy585KLHh9z5uHyYpuJ337aors0UeVrNSqpV3yfjkSEa2xXLpUBX+7dfPKttChhJ3nGzdqRFYEJRjOIQrGiBilkK69FkRh6lQ9Z/RtZZfzypWYnG20xsLWSNnjfPHFKktkkZOjdo62pIH33rXX6mTVujVIKMkSo2Q2+j1lCo4J/a0ffBD/nzMH1wRT5P7FKGEj3iKa6g8iJC+9hHHO4r77QN6pVeocFjLO4fzb1POFF6L8wjksEsuUQZQxyDOdLigWJFK//KLe4o0a4Z51DuecYw/dhfLysG+ffoptsBTFD1snW64ciAYzL507q0hy27Z6vOw+MhI/fjzGiNxc1Wbkgnj5cswJtFG0LilB9dwiOJdM8zIYwGuRmp4TJmhUs2pV3A+tW3vLjWrXxjVN55bGjXFuSKRFgpUJ7AKHXfRsgiEWLCg4Akh5IP4dRgCrVo0IYITM4Dzn3L+ccz+6JHQAuSpr2hTEy0Z/pkxREU2R4Fo2SmKMH4/BvlMnDB4jRmDwGjlSJ9h58zChU8eOtk8W2dmYhBYv1oGDxcqUArHpNiuaSx0zSrXs2uUdRERUYPimmzS1aaOeItql9sQTKjRKsspo3OuvYyD2RxSmT8frfos2a0kngonqiSe87zn5ZEwwdDGYNg2ROUZ8rIyJSHBhfLduOvFRxoAku2dPr0QPJ0mSmzZtQB7C/H2Z8r/nnlgJFRFdxTI1e9ZZqmPIlTBrMpmipScqa4+WLNF0IOuh2rdXV4UZMzCoWz9oOljQZnDCBE07L1yIBUEQQatQAdthxJQpumnTMLmwzmvgQI0E0RJQBETm+uu18N76i4qAbLz4Iq7LqVPxnnbtvGUVrG9kB+Oll6o0jgiuEd5z48fjeuZ+nn8+9m3DBiVrjPTRp3vpUpwjaztnccIJeo/bkg8W+vtx8MFYuDjn1dNjNJoWks5hkm/QwNvFKeK1MJw2DeeXSgHcTy5uuFDwEz3Cn1KvXx9jQ1CJRZAc04MPgugwWle+PK5RLvJsne1ll2nH8J49uN7vuis20iei0WQbJWUqPC9Pa0nr1VMJoalTtd6tWTP8y4gg75+w1Pzpp2sUrVIlXA9czOfmqnD7EUcokaZTiwgWlYMG4XPZ2bhmWLfJ+3D+fNxnbOyz3t7Wr9iCkXgRbRS67TaMPVysWuWBypXxPpI11tA1aoTzx2a85s3x+2xk+9RTcXzHj9fvt1Ftjv2ff+7dR5afFMSD38W/WV/qf9SoERHACIWHPwjgMcfgpmrTBpOm1VA6/XSvWHHQoFalCibsyZNBCtq0wfbq1tVtshtv0SJEgFhnaOtWiCDxaaZmOCk2aYJVpAjIIrvdliwB+eNN9sgjsTd8u3Z4bscOEBjnVNvOolo1DC733ovPsJaMDSkffACCZevAREAUnIstbvZH/IJEsLduxaDLzrpnn89A0lEAACAASURBVMVkxoiP32x99uxYH126boiooTvT7KNHe2s82QAwYQLOe4cOGID9aXmLSpUwIVI4lilfRtRKlNCo2Mknq/YYywa4km/ZEhMDNe9IVseN80YVq1XDNcMC89mzMflYZwl2ajKKduSRSvjOO09dDb780vtbli0Defj1V32uXDlEXqdP12agYcM0wmJljWbOxPM8Pz/84N0+NfFOO00bI1q0QKqaWLAAExft0DZsUHFsESWh+/bhGmR0tGxZfG7sWK8YLlNib72Fe2nhQpyjnTu95J+wUWQbxbGdyBZ16qjgtnXUoHQP7w/n8N5GjWLF221z2Smn4FqgaDEbC1gewhReWITJ3wnPxibKmljYlCXBMYL1djVr6v7v2qVdzSLIGjA9/PPP+K7Nm4Nt54IWy+++q41BFMeuWVPTyjNmaJkE09KsJeX9E0bMbaNUtWoglYyqde+upQRDhmhNHJ09RFSYevhwHKPDDtOGGUbGZ8zAtcxF9wMPaDmPPU4WOTlai7ljB47funX4zSTpw4craatYEYSN5Sqsr+Z21q7FeJWTg+v/xRe1BnzaNJwLG7m2CwRGVa0OpIjqPhbEg5HbRAQw2Qe2FRHACOnhDwJIMeEuXXCB2c7UtWu9mklBMgo1a2KwOuUU/J/eq6x9smKsdNpgF+vq1d5Ow7y82IidiEY8OKDl5Kh8AFeV3N5xx6nhNqN1lIwR0d/5wAMaXQlyPFi2DKmPxx5Tg/K1a7Uh5R//QJrK1ryJaCrTL6Dtn8CqVfNaeIlgpZ2VpWkVYt8+TKZcDRO2vpLo2FGLvEk6mAKZMsWbPmJajVIphx+O48+UYBAaNMB2Bg70RpWoP9aihf5Oa3zOsgGmZrOzEWFh1yejth07aqqfv8c5jSLMnYs0FqOEIhoVYYMOozRff41rkJpm1qM6DDVr4reddhoajZzD5xlJvOMOJSsbNyJqwho3vy8vI12UsylRAr/bRnJ5zbKAfc0abz3Xnj3apTx9uurv1aiBSXfKFKQxKZ308MOIdLz7LibTs85CyvqBB4J16WzkyGoCMjXvBxtOnPPe27yG2ElbvToWE02aqFYerwGryThzJhZRJP1MYZP4nXgijl1YlykzGET58jhv/m5rHhs/CeYYQOceirtzETd4sBLJTZtUi3HvXixyr746NgsgElwu89e/6vdQHLtyZY0Os9mkRAlNCVLAm0SIDRh+2FKbWrXwO9kN27OnerAfc4w2VP3tb7qg4AJh4ED1euZrjEJOnIhrhY06djE0a1awL7gVbGfDHgMLtLIcMECbx8qVw2/k7ydZa98e4xplo1q3xnfyehHBtZCd7b1urSxWhw6xjTkiWCQWFAH85BOV83IuvAkkIoARChN/EMD+/XETsvvW1s0wVM9BwFryEHXq4KaaMwf/MlQfhBUr8B0kbJdd5u0a9TeZWJQtqwOMLSy2NTHUdBszBtuhgLSdqCil8cQTiEQ55/Uu9uPVVzHZsmP53XfxmW+/xYrbb/F29tk6cFv4bdtYC+dHv35eD1fC72sqokQhLw9EIy/P23W3aBH2hTWD11zjNZKnJh0HYh4bFk0H4bDD8JsnTlQ7NRGtDxw7ViOIbFqwAzm1vSpXBllgNIFRusqVvR7JdCSgX+3ChZikrcsF65eYRm3dGv/+9784Z7y2g0Sq/WjSBGRj9mxNvR91lKZlrfn8M89gwnnvPZ0sLYYPR/SBUapy5TDpM0IrAqLFCKNzuJ7Z1ezH7Nka7WjYEJG02bNBbJiWZsSaHc0zZ6L84J57vOl6wtq/2WvHilFblC2rpOSzzxD1fO89lXRilqB9eywmmjVTAkFbrMMO0+854wyMIb164W82sTCCd8YZOB62lszCilczCv3ZZ8ESSTw2FvQcbtAAf1PcvUQJkFS7cLvpJlwfXAQ3aoRrzu+KIhI8ltn7hcLcZcviHDqn0fysLJUF4RjFa5cWin5YRYC6dRFp5xjUp486CU2disyLiDci+cILOAa9e+O6atZMX+NvGT0aJJOOOXQQEsHiOCg13by5uj39/e84riNGYIzhmNirlzbilSmDsahUKXwnx71u3XDvsT62bVtcG9ZmcPx4LJ7poiPiHXe7dNH6XQvOSwXxeOMN79/pegGLRAQwQvr4gwBygGMdihXmfP55nXDokOBPdzRogJt24UJEHKxoqR8chBj1s5ZXIsFpE6J6dR24bARh4UIlDNdeixU7u3PpJmDlV9iN+eKLOpH506gW7JQbPBgrSWpi/fILUsJ2/0U0kmPTYyLyR6pdRCOaNjJJXHll8Ao/CEwVUpLiX//yCh5TW892SVowepKbC+LPyJnfXs6iVy8Q/XnzVFpEBNHhEiWwT4yoklA6p2UD7NIsUQKf2b4dhNIKpNoaRBJq2g8uXYqJyaaJL78cC4k1azB51qmjtVZXX61dlmxCiIeuXfH5s85S/9zx4zXycMstSlaouWctsSwodcNIa5UquFesbMmtt4JQsnFp6dJYn2hi/nyNfLZsCTJxzjleKYzbb0ck95NPsG8nnwySescdqndpYdPNVjqFnZ4W1j2GzVU334zJmPp7JAtsWGnRQp/jfWjrws46C8eFpQm02uvdG+lVdr0G1cyKaLOIiLfz2opaEzZ6S7CLl52kvFaqV1eNQJLVrVtxbXAR3Lw5xoCg7mo2lLB2TwTHlpp11CQsWVLHDNbzli2r9wIjlFQasDXPFsxQiOB3v/aavta/v2rk0dpSRHVS7f+7dsU40KiRvsba3379cI+xU5vXmohex35Y/c3ffsPvPeggfJbp2dxc/U1ZWTpu22BD374gv+efj6h3x464dqzL0tixWDzz/hTx6qJSR9UPqkEUxoPp/ogARihKVHHOyZlnfv+HVQ+7FK16/hdfYKL+9VcM+LNne03dRbAi5qRdtqy6WASBERoW/DKVQNgiaT+yszV1YTv87IC2eTPSHQMH4nvYkWjJGHUKX39dm0uscrwfjF60a4d6ubw8jUbZ9DPBdIKfbJx0kqZo/BERi337VFokERiV2rxZCaVNj3Ngu+++4M/PmIHoCSd+Hjd/7ZQF06nr12ujgYjafV1/vUYoWHNjuyE7ddL9/fe/kXLs0sU7MDJlI6KSI9Su42rdEm+mxVaswPVXqpSmem6+GUTJ35EZBt4HZ5+tThuTJqk23/XXK1lhd+TDDwd32PLaZHNF7dp4v60F3bkTx3/KFLy2eHG468W55yqB6NgR99vatd4OXxIEpqVPOAHfu21b8ARtdTptbe0NN8QubmxUq2JFRLEuvRSTdps2mj6uUEE7Mlu21MYGRuIZBRbBcS5TRqONtB3r0gXb27ABZSjUrPSDEkYimmr+/vtgx4xbb/VaNIqo7BCPK72XmzXTiB+PyY4dWHxQS7BVK5wnW45gYbvfRbBoZcTs44/V/YEL4yVL8FrFinov3Hmnd0wMIrEi4TI5IiDyixdjf+jAI4IIPD2aGZ1r3x4R6fr19R7igrVLF2RtWHJgx+9nngkmwhR1J1jb99JLmqZv316j0yVLgng75/WPHjYMiyiOeV264Le89ZYS1REjQF7pqS7ilRzq1StY2sj6rBf0g+NLRAAjFCWqOOfEue+lenVMYKxNsFp1e/diMGYaYsQIjQgSTJmsWYP3WpFmPy67DO/lgH3//d66JHsz+9GihRYv244zK9Nw551YATLlR5kX2tKJoLDdOaTI6GTi1+yzyMvDSrRWrdgi9O++0yJf4oILgn8DIxULF6qbSFCkMxUw/c3Gk08/xeTKFff69Xg+KHIioub2detiQKbERVC3JUGisnmzprFE1Bd01y6VZaAenO2S7N5d65F++w1puQ4dEDFi5MN69j72GJ6jnMLatfjbFsJv2oSBftkyRC6c00aa7dsxkdmu4XjgsVy8WPUPTzxRo4w2NcrICGvD/GBTEpsesrPxfka/RNQxgvWS8+cHy/uI4HxT8qhnTyXLthPyxhtBwJmKPfZY/P7Nm4OjH2vXagG+7a6/6Sb1kiUonr1njy70SMhLldIU7bZtWn7RqpU3ciiC64Id8ezApBQT97tlS2yPXeK1amkU2MISWC7ofv1Vr20LSjpZcGxjLduAAUp2WN/H7737bhAU1vy1b486tKC0oojqXxI2esfFhXOIgjmn3djsQuZrVropzGPYdrv6MWQIomXly3s7zF97TX8Lz22jRii7qF1bv5fnr2VLXOts/tq6VQk1JWVsg6BIrPoBm2i+/FJLUA49VAm4c3rt2NQ6fx8jwl27gvyz1lUERHfECL1HRLzd4/36xbocieg4WRgPLqAjAhihKPEHAXQOK1wqwPsL5Rs1UuLWqpVO7gTrrS65RCcCv9wGwU40Sr9YEU8RpGX9Ol1Eu3bazcWaNRGvjtlDD2EfadG2bh3+tXIVRx2F5774QuVe/LVCfnDiZoQjHtavjz1GIkoGevbEdzoXHOlMBRQMpnj2hx96B1w2RYSl5M85BzVU1KujjV+QnAMxZw7e89hjWCxQRuKJJ3AuORH89huig7VqeQuv+/bFpM/uQ3YScnHhnNdRg2lYRksvugh/285tNpIsXqzXIxtp7r0XkQ1GKhOBUdNly5RQTJ+u5QX+7tiKFbGAsFEHghFidoAzWs6ieBGNetMCcc6ccNuz9es14sKSja1bVVJERIXLKb0yYgTOL4mhH7ar1Opr3nKLV+RbxOsde9BBKMC3Iro20kNvYxJjq2VniSYbw9j4wzKQOnUwLjHK5NdxtMeEjWo2g7B4sbeWVCQ4rU0nD6YyuUAcPBjHxuqIsqmMx/rww7E4YP2lH34fcvv9JLrOqRwVFRiqV9fXlizxRpcfeSS2SUwk1lrSYvhwLGwqV/Y23tEeUESjfBUqYFFZrZq3uaVkSURhb71Vo9a2HOLXX3Gf2ZS3COYPZkxEcD9kZeH7WKfZrBnGLRLNe+7Bv/Z3jxmDhSPHrB49EBG39n59+mCbttHHShsNGhTrnCSiY8qB8BCJCGCE9OEhgC+/rIXI/hVcjx64qZzDROJf7VJWhak652IHAWLTJrzO9JaduES8rh5+dO+upM9aSdk2f6bCSIhoGWblOfhbSChq1AiWLwj6jQ8+GP99ItiWXYESnKgOOQT7GKQdlio2bMDgTkL53nuIBDFVRsJNGyk/Vq7UyNO//qXk2K83aMFaojff9Do8MDLBqNiXX2K/cnO181EE5GT6dC0loJfn4MHaYWnTZvv24fySLDOqe8op+h5GVubPV/LPRhrKfPgj12GgXtqKFUpGTjtNI2J+geT69fF7rLwOceON+EydOiA8LVvGEiW6Q3TsiAl31qzYzlbisss0Ksdzdd99XocLNlZReqVfPxDyIPIj4u0qtb7ZQbVmn32mBKtBA0QeKd/jnLfznT7KbLooXVqJFL2hRfR6Iomj5FOZMiCYbHAJ0nEU8RJy24zDWjGLK6+MFX2n1A/tIHk/jBun0U3qO+7cib+pJdijB/ab0UM/7O8Uwbkh2SZBd049rJnhqFULf1eqhIW5HU/CBL3totiPUaMQNateXRvlRLBvVk6JqedTTsH/bV1r6dJYyN19t3b/+6PEdevGSlvxOiFmz9bjR4vHBg1wrEhCH3wQ/zIqKKKNVOzG790biyS7CO3eHcfLBhV691adz4ULtT7aggvlA+EhEhHACOmjinNOSpcGAaRgblDqcsIE7XxzLjbV1bkznqeVlXOxDRAEV7qshWPdGEHrryBs367EgJITIlj1cYX38ssY0A47DASL6SWbap082ftc48bemrMg9O+Pz7CbLR6uvjq2dorPDxmCQfSRR4JTfKnikksw8devr1ZJ9erpREzbOn+amrjoIk2X//yzdqjFi3QyGvzNN15nA9sdW6mSptYmTNAOSxFMPmPH6iTGyaRfP0QTnIOkTBiuuQbvsU0SO3aAaM6Zoyb2TPWRiITVafnBSX71ahXAPeMM/X3r1nmlkVq1AgkP8kC++26NHn//PQiyc96ISF4eoqEHHYRjcsopaIixepzEXXcpqWHX9FNPeX1nN2xACo8yJF274t8rr1T5JQsbGbSWY/Z8ElY2hLVdEyZoGYiNdlEuifcz5VlEQETYpMCIKyO6FNXmwuX551UTz6/jKIJFJe83S4TXrfMKAouor7cFu/pJ4E88Eb9x8mStY+T1yIYMEox+/XDug2ryRGLrFtesUTF71o86p9FSjml16uDv7GyQW5u2fuml4IajXr2U6PgxZgzIVu3aXt1U28Qlosd5zhwQcEsO2bDyyCM4702bxjbxdemi+o6E3yN73TpNG7NRp3ZtjF9cPPJ42LmAOpP0Qu7fHwSdZRp792IuOussby1iz55e3c0gcFF5IDxEIgIYIX1Ucc5Jv34ggB99hJW4X9RYRG1yWNDvl5JgxIWFu86FNzHQQoqm7v6mDzZxJIIVf6WjhIjWEObkYBVNaQ0r9MtUN7+zbVtMgvFw7LGxE3cYvv1W/Sstbr1VybJfzy+/uOIKJVkUwD3oIE3jsdkiSFZHBMT3kENU8Z8ipWFNI9xmqVKIzNmasOuuUymHhg3Ve/Scc7zka9w4nGPWMT31FF7v1QsTlV0QBIEROhbMi2hx/axZGhljpIdExEYT4oGyDevXazRq3jyVvFi1ypt+7tYNESCrZ0lQYoRklxqU/igJSWK7dkj/+sWNg8Cu4d27vZEvdiuz0Yikc8MGLJz8YGMEJVS4WCCptnj9dU2lU5h3xAhEl5zzyhrxOLLpoVIljURXrqz/Z00n6/iYBnQOC7633tIId1DTlK1De+EFrf2kxzSxd2+wVAmlfhgFnTkTYweJuB2fuJjgtTRkCCJgQc01IiCKNtq7dKl2yLNhpWRJjCvO6UKUpRCtW+OasfWuP/yAiNfHH2MsY8MXZVKCcPTRGMPq1/em9in9QuTk4HsXL8Z+2exMhQo6BlLOhmURxNixsY0odMMhPv9ca5RPPhlp3CpVcI7Zxb1rF/61x5XC4PPmIYo4aBCudS7SfvwR1/qyZd6MQ5iAuAUF5IvyUblyRAAjFB6qOOdk2rTv5YUXMMCtWxecymCBMoV6/bp3jNqwbsNPuCxY3MtUB7XjqBF31VXJSaAcf7ySSLotiGg6oEkTRPZOOw3btx25M2d606/jxnlrsoLA7fg9JFPB/fejrqZEieTkSJIBo2HXXKPpJhJBEfUtDms2uflmDDwcMClIG5QmIR54QKMGFH/+f//Pm1pq2xbnuEwZDK4tW+rnTzgBjSpMLz73HFJC3boh8hCWTiO2bMF3UvJCRJuJTjlFm1RIyChMHBZZ9oPX5MUX6+9buFBrFc87z5taHDIEEQzroU2QBPG4UBbHpgV5vJwDMT7hBNWcjId58/CZDz/0psHOOw+RFU6mzZvj3/PPBzn2g41T/k7doG7Tl17SVDq1OHv1QhSuWTNvsxUlllhbV6OGNlPYSCOVAawjEJuBvvrK2ywRFBmmJImI1+nDT04GDMD58/vossaU52j+fJCb2bOxoLGdqPTk5uJl1Cj8Pn+tJHHooSqrw21Tc5EEvVw5XaSwW5Vi1N274//+VHbv3iD0Zcpo+YsV8fZj3DiQ4UaN1I1DRO89ggsUpr5t2QQJyquvIqqZnY3x2kaVZ89WSR4iniwYO7XLlcO2GbUmIbY1qxRTZ3PPsGEYA2xnesuWWLjZmuNu3eKXtIjoOFqUD9bQ+x9lyuj/GViJCGCEdFHFOSdz52p3xBVXxHb9iSAa5BwGmqys2E5CpkeZOnMuvLmBJJE6c5ZAiKjURiJYjS/bUUjT+Tp1sHomobH7c+aZwcr98UCrIL9FXSpgNCgofZNfMMX7/vtqLWet9O66C4Qz7Hzs2IHPs+6S9VzxUt3/+Y+meViz8+WX3shYnz4qGXTHHV5SxwgsJwqSis6d8V7qnYVh+3bvNSSidYRTp6r9HQkZIzxWbige9u0Dmbr8ciVRS5ao1t6553rJHtPm/o5TESUvbOjo1w9/W402+/zw4SCuI0fG12IUUY3Hr79GbV6JEnh+8WKcR54bRpMWLgwW6iWx9d+LVuSXYLRWRP6Qj2rfHo02fnz2mXfB2Lq1yt/YRjFOfKeeqp8l2dizRyNlzsXWJ4uo84mI15rQRrp++UVJJTtgCZ4jpvWXLsX2zj4biwabTmRZA+tLjz4avyuo5EMEEV0bTZ85U+ufeW1VqaILBaZw2Sw0bJg2BlmsXKnesdQW9X+XxXHHYaHStCkWSxRRf+YZb8Max/ING/CvjQ7S0vG997R2298QtX59rK86m4WCQJmkEiV08eEcts/fT1BGixqZI0diP634d9OmKLWxC3xrOxgG1qYX1eO887S0xk/6GHl1Tvc3IoAR0kUV55ycf74SwH/8I9jBg16k992HwdA/2LEbkQSH6cQgsLiXK12KpdKrl9GLRLAyGVYeginJcuVw4x93nE6MxIIFwXpV8cAiYb+7RyqgfVaQXEh+cfPNGIjz8kCEn30WxdtMQT/wgMq0BIFdjYz0zJqFv61sQyKwu5PEQwQRrNGjMSD//LOXOJOgMcr4yiuYJMKIhB8smGfdp4jWEZ5wgtZ9skaQjSp++Y94aNgQ0Q2SqOXLEfVo0MBr0yaipDmoppMpZEZmeK+w0YJgicH48ZhA43V0Euxw//lnr0f33Lk4xkylcuKePTvY85rHjqk0NkxZmy/C+glTPLxpU2+ak2DHMNN4Q4ciGuyXhGEZg3U+YRPE//6n5yArK/g4PPWUkhgbtbz9dk1hv/iiTqL+zmAeO0YG16wBwVuyBOfbdpRyLORi4rjj8N1Bjiki6su9eTOOL23tRPR31ayJ2krnNIXbvDnGLV4XfkFrRgydU+mYVq3CI/eTJmFxf8ghXvtGS+hF1EGJKVEbHaRH8uefq3SR35d4y5bYxiHbWe7HWWep7JJzuljjWGkj1hzzTz8dkdTx4zVlXrEiiGmDBtgHa1d6+OFaIhQGW79e2A82w/E+4PwVEcAIBYkqzjm59NLvA28IC04Mr76Kgc9fSD5iBF7nIBuvhovFvVZmpEIFJSzWlioeZs3CICCiEiYi3gLyfv1Qk+IXAF6yJFy3KwxMO372WWqfs/jwQ92vTOHvf1dywXojm1579FFvIbcfLGonqafEiy3aTgQe/9mzlXSddBIiEkHp3HnzsEhgOo9i0nQISYQHHsA+2kH96acxEU+YgOYJ57TRiJ28YZN0EHJzUdNIsnLBBbqfZ52lMkYiWiMb1LSRl4cIHMkONcD8Opms55s+HROqFa8NwxVXgBTl5XlLKawweqlSGk2YNk3r7CyefRYTvdXQE4nV6BRBBN/qEG7eHK7Px8UYa3qnT4duGwv9WQdL9QDb1JOd7V1IVqoUvpBh45cI7lN+3/33awfyRRdpmt1vscffzdq8yy5DlmPVKkQNbR3kO+/gvYwsnngiCI6Nglmw/qxhQ9SpWskqXlv16mEB5ZxaBObk4D5mw5rfmnHvXlxX7duriH2LFuGR+ylTMHa3bo20LyN7NmUuot9HQmSjg/Sz/b//w71QvbpaMBI2HU9YHUU/zj4bx5BjNokfyzbsguXUU3XxtWAB6kFZ2sJr8KCDsHDh4kEkfmqcYHOi/0HSW5APZoRYauUcxtSIAEYoSFRxzslNNyUmgHl5mPB+/BHRCbviE9FV46uvYuXldwqxePJJvNeG5GvX1pqoGTPiu3IQnIT9lmp5edqtPHIkyKo/IrliReI6Mz+Y3k6neYMTTVCzQCaQk4M0pZXLeP/9WKcSC9Y0cRCnppu/Ri0emHI+6SRtzJg3D5GnIOHhc8/1kmDbuGNtCMNAWRcb7WB07uijUVNWtqxOtJRZ8V+38fDoo3pNlSqF1Ba9dS3BElFRb3Zw+mHT73Q78XtAs8Rg3jykgfv0waQUDzfeqA0ZNnpnvXGtpdhxxynJsfjLX0CgmArl/j70UKy+nXV+oMCu1cmzYG0WydLKlZjQmWqmUsB11+Fv63zStKm39i47O3xcefNNVS+wUjePPaZ6ecccA0JXpw6OsQW7cRnVffxxEBOmQdnYJKJ1jVwwnXIKJuiwe6xfP0Sqa9TABD9qlDe1n5WFyD1Tn0zhtmqF+4rR5aAmtV9+8Ypd+wWXLU46CcSsXTuM0yyBscdIRKPzLLOwcjN16+K5n37SY241GEVwT9qIqYi3JtmPxYs1ymmbYd57z0vKuW/z5gXPEY0agdhWq6YNJFxgWtvQMHCB739YjctMPtiZ75zWX1sCaElfRAAjFASqOOfkrrsSE0CLOXO8N7yI3sBvvIHJgF14QaDvpq1VadxYrZbY6ZUI1IJiis0Wn1eqpESrX79Yvb21a5OvByNY+/Pdd6l9zoKuI0G1YplA69aYtFkPkwyY0uJAy/SplfNIBDafWC9SSnv4NddEEO2wKdD33kMKJyyV6AcXEbZcgSSG8kBVq2p6iM0NQfVvyaBMGURgmCo8+WSvxRjTZWEabBYTJ+K9VudQREsMli8HgenRA92t8bBjh0ZoSHKZZmTK0FqKHXmkVzuReOMNTJwffuhdLLGu0sLqvg0ZovttvbYJlnfw/RQNZqH/f/6D5xltos+3CL7XNiAceqi3Hs3iww+1AYZuLSIa2RTBmPTkk7g+SI4J1hj670tKg1hy98kneI5ZEBKmsGtryBA0o5Qti+8dMMDrslOuHCJw1Gzkouaww3BfMSIfRmCsj3P9+uGR+5NPxvjQqZPXOcN6E4vo/c/SEKunx071fft0GxSiJygPY+EXw7ZYulTdh2rUwO93Tr3NrWvHnDl4TJ/uvVZEdPFYoYKmxzknJFNaYhUsCoMAUsIpjACyvpME8MQTNaMhEhHACOmjinNOnngiNQJ4772x3Ym0kHvnHVys8fTWWNxrO+NIXEQwSV16aeL9oJzCv/6F7dmuY/qtTpuG+iO/BdjFFweL9sYDUzTpWLfl5SGaFJQqzATatdMmmzAhbj8YN1ADsgAAIABJREFU0WD6jY0FQTI2YaDWmW1coAB1MtHODz/EBNmwYXIyO1xE7N6tzzE9O3w4CFndut4yg1KlgtOfyaB8efwupjTHjfNK0GzdqlGTRGBTElPC/m1cfDEWLdbrOgy7d+tijA0FX3/t7ZC3lmKDBqHeyo+//Q2/0dr6iWBCzckBqSCZtqLRo0apiwe7+P0oU0ajZU8+CcLKiBsjNJQqsnaM7dp5U5O5ud6/LawOnLW1Y20pj81XX2Gx4V8ckTz7vZcZmbTXzRdf4DnKy8ydi78nTgzet1GjtMllyhSMR1aqpVIlRMzYEcwUbvv2uB8WLsTzYQujlSu1djFerd2MGTh+ubkgsZS2ocg2QU/cxx/Hv1aUv1EjXUzTfWPVKu9vf+klVQiYMAHfVaVKePPc+ecjQlyyJLZP6ShGo220luVB1lOd6NABY1/p0ho9pHh327YgtPHAZrjCIoCU2wojgNZUgfJOFhEBjJAuqjjn5NVXUyOAQaDsxvvvo/4vnt4aazz83pCs54qnZm+xYgVWUR99FFscTv/ZOXMQ/veLW2/fnlyjiUVeXuJOsmRQrVpyvy8/6NRJUzfJpqo5obGQfOVK/B2U0gsDI3d9+2qqivIzQREnP2gdZwWs44GLCNuQwzTyoEGYuBs3xoRAVKqU3L4EoXJlDMisXRsyRI+XiNYkssM1HljrR6kVgiUG11+PGrZk6pYsbDe21RC0kYQePby1iwS1OHfv9trlsT5s3TqNeF1yiQopT56Myb906fAuc54TEZQlZGVpJJWLNkZfbOT/8MO99YeDBoU3TzF69sMPXp09XhNWrDwITFVbUi+CiKU/CsUyDioVLFqEv8PGk6OP1kXVwIEgKjYaVa0ayB6j1BwXO3fGsadLSlgK9cILtes2XqRt5kwQyh49vItmdoATGzfiWqDeoU0PN2miqWOOu9aHWQQZBfoH16mD32M1H/244AI0ypQrBwkX1uLxGrGRvgULcP/YCDfRvbtqzLLpi42Fbdokri0m8SwsAsigiSWAtgkkL0+zWxEBjFAQqOKck48+Sp8AUtbj449x87PwOgi0XbITfd++0GE6/XQMOMlEUrjSf+MNr+aTiNptnXMOyKg1Ui9qNGqUHFHID3JzdQANc2Lxg9EYRl0pyptKs8uhh4LAHH64kmTW6bFRJx44YIc1E/hB71Yb5WQUi76fJ5zgjWLWqhVb/J8sLGkvXRrRORvFZUQymfQ1nSX8wtx//StS99u2Yfvt28cX4w4CU/+jRmk9Igv3ncNiyF//JqKE4Nlnva4QTOctWaJRvLVrNaq7ahXu13iSSrVra/PNL79gH0ngSRoZfWHNpghIsNUbPfpolV7xg6UV33yDiBzP80cfIQLJ2s0wkHytXOl9nvtlU8Ykm3TzILljGtaP447TNHHr1lqnS9SqhfuGUiYUTM7Nxft5P/pLBgirw2e7//2YPRvnok8fTXl//z2uMVsPvWUL7qPnn8d77GK+eXNVT6Ds0LJlXlkd68tbtSquoYoVgz2cRXDOWe/YoYNGwdjUZM8J092TJ8faJA4YoFmHr7/W8y4SvzuauPvuwiWAxx2n/2cDkyWAREQAIxQUqjjn5Jtv0ieAjGr8/e8YZCgyGgTKHdgV7YgR6rXrXHKdoPRjtcr/RMeO2M4FF2DVGq8ppbDxxBPppZHj4YgjUG/knLcmMh44ebLhgKboQZZbYaD+mE3ls2YyyM/WDxbAV6qUXO3h22/j/awhE1Eh5J49g2vnGjRAYX9+UKuW6rNVrYpJkdprIrqoSaZx5uyzg8/Pnj2YpCnKbI9lsmAzxpAhKiFDDcCsLOy3rV0k2EDy0ENeJyC6PcyZo808y5drtOvOO/G5IF9aomFDpOWJunURZSJJEFFZH9vpOmCAt1Fo6lR1+/DDOpjYBgGmhl9+2esMEfR5PwEV0W5SS/ZZv0hhZta6WlkgiylTtO6zWjWvTzePB39XuXKawu3eHeMYayzD7mdbkxnWjCOCZpGqVXFcbUr8nnu8Xbv33Yf3vfQS3mMbOg45RNUTmDk45xyvgLdtJCpbFuNdhQqxXe/ExRfjGjvoILVZdE7LLWgYIILo7tSpwXXio0Zp+vrbb71Rx5YtvSVHQaDWbSYIIGuU4z3oRx8RwAhFhSrOOfn++/QJ4OzZuFD/+U9EEOJZuVF13w4INF9ftgwTVZAWoR80dac4rwXdFi69FBNgvMG/OKF3bxUTDbPi84OTH9OlLHwPs44LAlP4tguRRdzJ1HNytZ+VlVztIesWrZsKJ56w2rnmzWNTfMmiTh21kqpfH9e4rYPlZJjMvp97bvzzc999INTJdkRbcKLt109T8XSUqF4dE62/eF5Eu3K3b/feS889h8+fdJJG4xYtUsFmEnG/VIxF8+ZeiZTDD8eCzTpbcPK13bHDhnkbiM48M37dbtWqWDxMmqSLDka377/fW8sWhJIlY69VRrHtfnHBRCHw9evxd1BqXQRlB8OHqzJBxYre2tUGDZTAtW+vtaE9e6JRjQu6IAFsEZwznpt4zV/z5oFgDhniJcx33eWNrD71lDZ1OedNux96qEYLuWibP99bWsF0O9Pqjz2G76VMlx+XX44FVoMGIKfLlmHfmP6ky4mIppuDfLLHjdN6yR9/9ErPJHMvUZ/W/+CCLdGD3f3OafOTfQwY4P2bc15EACMUFTJGAFkI/c03wULRFkz32ZTG1Km4SffuxcCTyAlCROUerC4ZMXAgasquuQYTn01rFWf0768TUpBlVhjKl9cubKZRUul2ZsdqrVoawWBUKZHHsn2vc7HyKEH46afYdC4npPbtMan50aZNct3lQahfX2tUW7TA8bITEycr1hzFAy22ws4PZTSaNVO/1GRBOR7bQUxHiYYNcX78tVMiWj943XXeCf/FF/Hbjz1Wo0RnnqkOLr/8AmLjF/61aNPG68dLn2bbFMDJ1wpfjxnjdQRatswbSfSjUSOksK0XLRsrrrsuPH1MlCmjjS4Ehe2tHA/TxWymYYQuKLUugvRv9+4gvaVL472WDDVu7LWrI/r0ATG85ZbYGmYLajXaGtAgLFgAYkUyzsXC7bd7Mzb/+Q+icqzVtuS+TRsV9SbRmzPHG/3kvcCygp07EQkMu6+vugr3U7Nm2Le5czF289zZemk2nIwfHxutPfFERH+dw/yRna2R1nj6iIR1scoPAaQUlHNeL2s+hg71/k3lDEsAbRMIERHACAWFjBFArry+/RYTTryBmgODLYJ/4onUnCdENPURpDw/ahQGlRtvxL9h8hHFDUOGKMEI82IOQrt2SshpifTjj8l/vl8/SFvYlf6+fZhwKGwbD5w0nENUIj9gFDEnJ7jjr0sXbzopFTRqpBFSlipce62+npeHv8OiNBas6Qo7P489hgnr4IOTi4RbsIbSNlW1aIHvO/RQTCT+OjeiVCkQJ5sOpN3X0KHaKXrqqV4NtmbNYoXhLTp18sqozJ8fS3gYabOT/fjx3uaC666L37h12GGorR08GAs/ESVrK1Yk7vovX94rzyKiaVArwcLJnZIxXDCFaZfOnYtj37IlriPnvB3gzZsHSyX174/7+fbbvW4cftDVw9ZBBoHyLmzgqVkTJG/79mBJLFrT2frAdu10cc9ayNNO8wr3s1Hq3Xfx70MPgfh+9FHwfrHTulUrkKIZM/B+RhAZeRfRum/b5EScdpqmVfPycExYa5nMYooGBfklgEw/k7zZ17p2VbMERqVtxLBuXXwmiABu2YL50Y+IAEZIFxkjgBSx3bMHN1484WG6Mvz73+l95623ItV7zTWxE8r48YiGbNkCEhJvAC1OGDFCU4zJkJEgsIkkFQI5dKjWDtrmk2rVkktjcvJyLnn5Gj9YM9SwYXDBd8+eib11w9CkiTbudO+efGQzCJQE2bcv+PWnnsL3ZWdrQ0CyqFsXpKVdO+00ZUNUly64F9asCf5shQqIDloyQBmVHj00hWqtzERA/ii7EoQjjvB6w37/fWx0mW40rLMUAfmz3sD79sW/po84AlHPHj1w3xNZWejijTcmiaBmzH5ORJuN/NGjrCytJ6UXt1+WhFi0CBGeTp1wbP33SE5O8L4NHozI6TPPhNc+iqgAul9b0Q+O0YyqMkJ2223B22d63y4IOnZUjUU2kpx0Uqx+YqlS2kTywANe32c/qAHZoQPKAiZNQsSQRNJG8+kTf9RRGuUl5s3DOEQdy/btddHWpIlmOMLAazC/BJALuzACSAcgZjuYNUtEAMMQEcAI6SJjBPD883HR/ve/WO3G03777TfUz9j6rfyAnp8XXRQ7gNKeiV188YrUixOOPBIDIVfB+QGlFFL5/OjRGNBKlvQSm/nzY+VOgmDt+6jdlSqo5VarVnC65+ijE/uBhqF5cy0iHzgQ3+MnC8li48ZYb2oLTuisw0oFDRuibu+QQ5R4t2mD/e3TB//6IydE9erQgqRrhwgiRDVrglCyOWTCBBX7FkFqMZ51Y//+scLxfjz9NPbN6uNNn+51W0mEYcNwbDt08EbsKlcGaUgk+1StWqzME/XkXn7Z+3z58ur7TA3DsGanZctASnr10vS3Tf+3bh1MoIcNw3HLy4tPfKl/6ddW9OO88/A6x+bmzUF6tm4Nrtnmb+/USZ/r3Fn3lffbpEmx56liRZVGuvde9QoPAo9fbi4I/5gxWIywjs42Ql18MV4fMya2XnPJEizOqGNJWRiR5KLpTPfnlwCy9CaIAHbrhjnKOSx+vvjCO+aRAAbVAIYhIoAR0kXGCCDrH377DRNOfgV3UwGL5VesUCFUYuZMrHDZ2h8mIFvccPTRiHb4vY9Twe23p/75Y4/FxEBPy1Rhi6bzGxlmZ2PFisHlBHl5+SfFW7ZoFyZX8tu25W9b11+vrhVBoKNJPPusMFCP0Qpqt2+P7xs8GPvtF3En6tXDwszanlHTrWlTraP1T77//S/IQBiGDUssBk4ZHUvQX3rJ2yyRCBMmILppya8IrslevRK779SqFesWQdcPf3NPlSoaBaXuZlhklWPj0KHaLGcXSe3aQbLIj5EjY8e1IFD+iKU1YfXTLA3hNpkyv+UWL+knPvhAI8dEbq5KvjBqP25cbHd9rVpqrcYxOKw5hRqQvXqBSA4cCBLHVLuVVqLLy6hR+L/F6tVII1PHcuBApJdFdGEUD7Sgyy8BpG1gEAHs3l1TvjZCGxHACEWJjBFArn7y8jDhhGliZRK0qaIlnMW8eZq2cy62S7i4Yvx4SDLE0zxLhHvu8Up0JIOJE5F683uApoISJXCu8ns5kkSWKBFuh5UJUL8rFZFmi82bY60JLRh1q1LFa5eXDEh+bDNO584gxSNHYr/D0uCNGyMSZOvRKKRcu7Zq/Q0d6m3WSISxYyF6Gw+stbPC3amC8i+2+F8Ek39ODiJx8VC3bmzpABuL/GUJNWuq0woJTlhklcTg6KNBEv3nvlOnYH/mI4/0yquEgd3vfh9nPyhXQwLXpQsI9003eeV2CKo15Obqc927qyg2U7QjR8Z2ljdooGoCFFj2O98QfH3gQGyne3dteilZ0lsGsXGjdofbJiwRVXwgmbKOUtnZiccEeqLnlwCyBCaIAB5xBMZm//jG64uLq4gARihMZIwAXnKJRo06d46fEsoU6FJAg3CLpUu19d+5+M4kxQkTJ2KFH9Q1liwefBBps1Rw0kkg3EGRhGTBDsl0NBJJIv/yl/xvIxEoep6qSDOxY0f840vSFU87LQzUDrTCu7m5iIow/cgGCT9atcJEZIvlaQ1XrpzuM4W2k8WECYkjWX/9K/YtGf3PMJx9NhoBqlVD5JJo0QLP+WvG/MjOjm0U2LMHhM0f4axTRwkfO5jD5I4oyzR5Msi/dVoR0dSnH0cdFWzb5wdrqt95J9YRyYJNClyc9+qF6N8NNwSrNpBQ2prQnj012scFV69esdHPFi004sgI6RdfBO8XrStHjABJbdsW50sEY4KNgl97LSLZw4bFLkKuvRbXPeu9jztOSXoyDkNchOSXAF58cXwCSOcP/7UUEcAIRYWMEcArr9SoU9eu4ZIImQSN3qdOjV3dr16NFAcFOcMspIobpkxBqiGebEQiPPpo7CSVCKeeijonW+yfKsqXx7lKpza0TBlsI9XUaSqgk0ciZ4Ew3HNPfGcapvTKlAnvnAwDTe9LltSu7iOOQFSEHZJhNoRvvx3bQPDee3pMeX9365Za+vvEE72af0F4/XV8R6q6hxarVmGSLV3aK4Z82GHxfzcxcWJwnVqQo06DBuq08thj2P7GjcHbpafrzJkoTWjc2Pv6EUcEawgee6z6c8cD5VJeeCF+ZJlZGkq2DB4M0rRpk1r1WVBE2zaI9OnjlRFyDoTNH1U+7DDsu3PqcR0mT8MszdixIFHNmun4U6WKt3nk+utRU8p9t2DKmeU+J5+sdZp168bWcfpB3cP8EkA2dwURwB49kOZ3LlZdwTlELkUiAhihcJExAsjVlwgudt54BQlKVIwbF6sJdemlSK2wEy2eUG1xwrRpqI9Jx/pu1y7VpUoWJEVBkYxkUbly/BRWMqhQAdsI8x3NBCinkUhXLAwPPxzfmYaOJvFEfcPQubPWVNELundvLJQmT8bzVtMuEVgHxkdeHposUknVzpjhtQoLAp1UUtU9tLjiCsimOOdtPOrSRVORmUKTJqoZyAYW1pv5ccMNSiT27Yvthu3dO9guccKEcGkZC0biHnxQI2dBYIqS+pmjR2OcvOYateqzYE2hbRDp18871mZlocHCHxHu0gXEn9eb/5xYUH9vwgSQ5bp19f7wX/833wwSOnAgiKsFXWlYhnLGGapXmUxDFXUPkyWAdK/hg5HeMALI4+Fv0okIYISiQsYI4A03qB9vnz7oCi5osPtt+PDYepBrr0Wk4i9/wc3kF4ourpgxA6v5/DZjiCAdl2rTDAfJMCmMZFCtWvwUVjKoWhX7EeY6kAmwlipV3UriiSe0TikITL05l7okjnWOoNRK//44n9OmaUQmWdDNhY/ffsMEu3Nn8tuYMydxLRs7Ttm4kh9s3owIqHPeOqtevfCc9d9NF4ccohHFF1/E9sPS4oxMWekci/79vV7DxKRJwaLdQShbFgQkXqkLBavZsTt+PFK3V10VrNtKXU1aAIqAeNnmi7Jlcd/6yXWvXqjBY+TVufDu/scfx+tTpoDgVaoU7ty0ZQsIaf/+sTJMDz+M7VC3cPFiTXcn4zFO3cNkCSBT13yw5jGMAPL+85e4WAJIGRjbeBOGiABGSBcZI4CbN2uR+IAB4R1xmcQ77yBq1KdP7OC7axduOOp4JXIBKC6YNQsRhXgEIxHy8qDynwqoPejvzEsFtWrFT2Eluw3nwjXHMgHW+thGg1Tw+uvQ5gsDC8PjTZph6NULYtfOoStaBAuC1q2R+nMu2CYvDJ9+6p3IfvwRHcGJNNUsFi3yWoUF4cMPsf1EdVrxcO+9IA7OeWVTBg3Cc5msC23VSjULX301PrG+/Xa8HtYkMnhwMNF75ZXkXHFEQMJmzgx2FCEYXVqwAH+feCK+98orvVZ9BIWe+/TR5zZu1OYiEUTcS5SIXRAMGqSyQ9dcg3/DBKopvzJ9Oo5ViRLh49e2bVjk9OkTG8nmduhqsnIl0voiyXXUU/cwWQJ4//3ev/0afva1nj3x+5yDwLVFUAQwGUQEMEK6yBgB3LZN04ZDhnhN3QsKH3yAFSi72YLwzjveQaG4Y84cFJUXtvMJC77zK40igkE/1eaToG04F95xmAkwwpYOoYjX6MLIi3PQdksF/fqplypT6cOGIQI+Zw62mUr3MqORTM9/+y0mq1QEqj//PDGRodxKoihNPJAA+DvgR43C8++/n/9t+9GunV7rTF/7NQSJe+/F636bOWL4cG1WyC/q1cPCO16klY4lLM859VSQwcsv91r1ERR6DuoQJnhd+BdDo0erYw6JUVAtpYhKAJ1+utYDkhD5Qdu6Xr0QdLBgtoeuUNQMFAFBfuON8N8hos4lzul4Fo8APvSQ9++NG70EkDqJJICnnor/+wX2nUMDkkhEACMULjJGAO+8Uy/iqVNTizLkF599homuVavwgnzWMAVZHRVHzJ+PFAhFewsLVMEPsixKFg0apN584kfDhtgP1r8VBFjUXlCNJnQ08acyk8Hgwah7sl3go0ZhUcCJzK91Fw9ffIHPNG6sEcn86BMmAv3BE03S8cBov/8aoudqfgXGgzBggF7r77+P7Qf5T4toatK6nFiMHo0GjXTQtCnun3ilN1y4sGHurLNQD3jJJUqULEhg4vm6V68efN7GjVPbO9bGhel7svt23jx14whbwN59N9xIrNc1wQgeCSs7hkWSk1TieSQB69EjPgH0ewez2ccSOP7dqxcIrnOxOo3290YEMEJhImME8L77Cp90MFWWnR2u8v7ZZ95VYXHHokVILzZrVrjfy7Tom2/mfxuNG4fX/iSLJk3iRxsyAeq+FVSjCbs6nQt3dQjD8OGIArEcQwSTe8+emqZPRWqF91jHjhpZtRIzmQK/xy+4nAoYRWzY0Ps8uy/9qbd0YEXFmSYP8p8WUVITRhCvvz7/5QQE3V7iyfOwFo9e0Oecg7TkRRcFd+9T6DmoQ5gIK7mYMgWkyzltPqGQuh9MoZ9zjtZThll3Uvw/qBOduoUkfdYjvlKlxNesrXcVgYLEWWeFE0B2f/PBVHcYAWQE3q9yEBHACEWFjBHAhx8ufNJB66OKFcNTR19+qTfgnwFLloBIFbbwNdMf6UTemjfXKHJ+ccgh2I8wP9RMgNqSmUwpWtDRJChdlAhHHomIl42gHHMMoji0a6SlXTL46it8pk8flaUpXTp1eZpEYNrbyrekCo4H/vrK6dPVH7YgwDEmrDGGDhOpHPdUwU7neBH4m27Ce1ifTQelDRuCrfpoVRavrrBOHbzHXzM8Y4Zew+vWxb8n2XyxfLnKAYVZdz74IOpZc3NjU+7sWmY94913a/NfMpqatt7VIowA+r2DGWENIoC9e6v3r9/WLyKAEYoKGSOAn32WnGRBJrFnj95gYV2fnFj69i3cfSsqLF+OOrh0HDnyg02bgtMbqSAnJ1YjLVW0apW/yFkqYM1SQTWaWFs8axmWDI45Bk4dLVrocxMmoA5w9WpsMxWpFYoMjxyJKArTbGGivvkFGw5Slb2xoDOF9a4VgRxIOl3xicBjFEa+WJuWyIosHbDTOR6BvuUWvIfNKBs2IPK3bl2wF/HevXj/0KHh26xfP/h+Y7TLObXCC5tmWKe9Zo2W7IQFEx55BAS/S5fYzmPWLB51lL43Jwf/L1cu8YKNZQjJEkDWnDLaft118Qkgt+O/pyMCGKGokDECWBT4+We9wcImJA4K8epYihNWrUJdzmGHFe73bt6cnvagCFb26Xo2s/A81chZKmCtWUE2mpQsifrWVDFhAtJeVvdy0iREBtkdHFYuEQQSswkTUFvHFF1YR2d+8f332G6qsjd+VKgQG+1fsKBgvcC572HHlVGtghQnp/5hvDQ3a1fpBX3llXDfWL0arhl+0Is3SCKGaNTI23BELFqkYzMbKsL8oll7d/HFWnNqFzAWjz+O1zp2RITPggsA+k4/95wSq7JlEzciUfjaT8AWLAgmgM884yWAXARbhyC+t08fWJY6F3usnNOyhUceiQhghMLDAU0AuUJ1Lry+5Kef8Hq8OpbihLVrIaVS2LqH27enn3Zu1y59y77OnYMH2UyCUYqCbDQpWzZ/acsTTgD5s/6tU6agKJ86Zan4JHMBNX06IstMf2d6yOB9mqr8kB9168aKGi9bFhsVzCS4EA3rjGZ3abKSLvnBmDGJ62e3bcN+UDP1hhugp7dqVbhVX8mSwRIxRJMmwZ37y5fr2Lx0Kf71O2AQrN278kpN4zNy58dTT+E76XjjR6lSEDwXUZ1YkeTKFphCTpYA8t5gdJk1lnYRw/f27YsaxyByZwmgiMo3JUJEACOkiwOaAIrgho8X8fnf/xKnMYoTLrwQg3Zh6x5+/HG4F2qy6NQpfceWrl3Vk7qgwEhBqhItqaBixfz5OZ90EtLoVrtt2jRM8CxST0W+hmUWc+ci2kO3hWQnqVRwzz3pE/ecHE0BEqtXg+gUFLgQtfp4FmwuCLNCywSOOy7xPU89QnpB33qrSPfuiNCRNPlRpkywRAzRvLn62Fqw7s85dc4Jkz6i1NCmTdp4ErYQpP1n27bBTTeVK8MCTgSRRUoClSql1ohhYLmQP1gQRAApAu6cEm86vtjzXK6cEkASYT/8BDBZRAQwQro44Alg+fJY3YWBaYwRIwpvn4oSVPvv2rWo9yR15OYitZMOevbEoFuQ+OEHdDgWZJ1htWr583M+5RSkpOyCZ8YMEMMbb8S1sXt38ttjR/J552GyZyNBQUZY08HhhyMKanHzzfj9BYlSpZDqDQJrywpymJ02LVjKxYLWZSQvlFRZvhyi0EEoXx7lA2HIyQlO11pbNBKosEUDm2g2b9bxunXr4Pe++CLqDlu3hg6fH3XqQBBbRBdqe/cmZ6vIcgd/PXkQAaTtn3Oqf8v7yxJA1oeOG6dRUT8iAhihqHDAE8CqVeP7X4pgFTtqVOHsT1GDoqvWwP1AwRFHeFOX+UHfvmhWKGjEE3LOBGrXzp8m4qxZWBBZMjBrFkRoWQOWilQP05sXXogGmyuuiL/gKmoMHJieH3V+UaNGeFPQTz+hk9bf/ZlJLFyoDh9hoCA1HTR27kSkbenScIJcqZLI2LHh22zdOrjcxDZEsPs1LEvDyBu7esuVC69h/stfQLgOPTS467pxY/X//fZbbJdR7EQ1u9Tf9EsR+QngCSdoDaxz6lrCxZHf8/jdd7EPK1eGE8Aw2Zt4iAhghHRxwBPAWrUSS4dUrJh4dVxcwDTfgSh706tX+sR10KD0m1H2B9Srlz9NxDPPxPm3Rf1z5+KxY0fwBBcPlAK59lpM9KtXFw7Bzi+OOgrxIIgOAAAgAElEQVSCwoWNTIpM5we//pq48YkuG7feir+fegqE6dxz1TPXj6pVgzUCibZtEXX3Y/NmJUxnnIF//fp3BInaPffg7xo1UA8chN27EeHOyUE9qh+tWikR5rXLCGOiBiPW9Pn1Av0E0Eb+ndMU+M03BxNAgl34fkQEMEJR4YAngPXrJ24+qFYt/iBWnMBC5Hj2Tfsr+vXz1q7lB8OHpy8mvT+gUaP8aSLOn4/zbyM6X32FB83rU2lGYH3bbbchOrt4sVdken/DokWIUkaIBR1JGGl7+WVErxYvRplAEGrUCNYIJDp0CK6vZr2hc0jJMhUbBEbo6OaUnR3exPbGGxjPmzcPlt3p1AlaqERWlnYZhxEz/374Bd79BNCmsp1T2zoSwLDmMNZF+hERwAhFhQOeADZunLjj9aCD4g9ixQnU+ho4sKj3JHUMGpT+fo8eHe4jeiChWbP8Oeuw4H7WrNjX6F2aqBjegjVZDzyASM+sWcXj+P4ZwQ5uOpK8+SYifAsXipx2WvBnatcO1ggkunSB9qQfjDaWK4e61Hh1o2z8oD5l8+bhXdvvvIMIdNOmcOrwo2dPNLUQVaqo00iiKC3rXf2WcX4CaLVOndOFGsfeMAJIGSY/nEtcxhSEiABGSBcHPAE85JDENm/Z2aoNVdxx660HbtfzsGHp7/fRRxe+JWFBICcnf846y5bh/M+fH/va44/jtVRFnJ0TefppdNJOnhzu0hBh/wadK6hT98EHqI+ePz94wSCCCGG8sbNr1+AGEl5rNWsiGh1EfAjq99EOr21bEMsg/O1vaExp3BjXpB+DBkEKi6hXD+9zLjmJoe3bY4mqnwDaSKZzqjXItHcY0bzkknACGO/4hCEigBHSxQFPANu0iW9VJIIJa+LEwtmfogbrvA7ErudRo9Jv1hk/vmBFfwsLbdqEa6HFA0V3ly6NfY3CtanqF5YqhdqroUPREOC3WotwYODJJ72pVooun3km6vSCkJ0tcvzx4ds84giR00+Pff7557W7dfLk+KLmdL555RX8nZsbrmLw4YcgrQ0bBjurHHecyNVX69/Nmmk0Mr/+4H4CaAmi7eDdsiU+AaQOpx+1auWv4z8igPsPJjnnnnPO/ds593/OuV3Oue6+91Rzzm11zv3HOfetc26zc66q7z1HO+fec8795Jx7xzk3pgC2YXHAE8AOHeJ3qYkgSuiXhiiuoNRDPOmG/RVjx8ZquKWKSZPSF5PeH9ChQ7gURjysWYPzv3p17GsvvZS/ibB+fRTSjx6NFH26Wo0RigZcADz2GP6m6PL06do560ejRuEi0SJo3AqyAGXaNScHi+9E2pwlS2p3ep8+0CcMwqef4r3Z2cGC5j/+6E3Rtm2rAtj//nf8fQiDnwBa2Pq9226LH2mkX7of//53/px1IgK4/+BU59xA51xF51wp59wZzrk9zrn65j0POucedc5Vd87VcM495py7x7ye65z72Tl35O/bGOuc+69zrmOGt2FxwBPA3NzE5K5163Cdq+KG++7DIJMukSoKHHMM9LLSwdSphW+DVxA4/HC4HaQK1hnR7suCk/J336W2TUY8jjlGpFu38PRchP0bjMqxdm7fPkj6DB+OLvEgNGkSLhItgsatVatin6f7SceOiMpnZcXft8qVtTZ12LDwsh5qKtatiwVNInTrppI0qV73RCICSP/yu++OTwCvvjp/qd4wRARw/8Z3zrnRv/+/kXMuzznXxrze9vfnGvz+9w3OuTt927jLOXfd7/8/OAPb8OOAJ4A9eybW/erQAUKpfwaw0D9dIlUUmDAh/VT99Onpi0nvD+jePX9uLhQCp9uDxVtv4bUwT9ZEmDgRqelENbcR9k8wAvzss/pc06aQTgmqGRVBOUW8xfPAgcEOQJ98gu/q2RN1uYlsDT/9VP9/1FHhMlb//KfWFjJlHA/9+4tcdBE+k99pLhEBZE3szp34OyyaR6/gTCEigPsvcp1zvznnGv/+9yiHSJwfvzjnRvz+/93OuQW+1xc55/76+/9HZ2AbfhzwBLB//8S6X4cfHq5zVdzATr8gc/f9HZMmwbc2Hcycmb6Y9P6A3r3z5+bCNNMtt8S+RjmMn3/O3z5NnYoGm4K0VYtQcHjlFZx/Gznr0weWgwsXBn8mJwfnPQxXXRVsgUdf3cGDUY5CS7ZkMGlSuBzU119ju5UrI6KdCKNGiZx/fnoLn0QEsGlT/P+pp+ITQDqFZAoRASx43OgQYdv3+7/+x66AzzR0zn3qnFtunpvonPtXwHu/cs4d9/v/P3LOneJ7fYZz7oMMbsOPA54ADh2Kzsd46NGjaNwBigK7dmGQORBrHk88UX0884szzjgwXVD8GDAgf5E2prtuvz32tU8/xWthgryJMGMGRLaHDcvf5yMULXbvxvm3hO2EE/Dc4sXBn2ndOn/ZE7pqjBmDhrTy5ZP/7PTp4TqmtGsrW1bktdcSb2v8eNXGzK91YyICyG79l1+OTwApE5MpRASw4FHBodYu7FHZ9/7mzrlPnHOrfc/HiwAO//3/iaJ3mdiGH1WcczJz5kw588wz5cwzz5SdQf46+zFGjYLAZjz07Rsuc1DcwELvA7Hm8eSTw/XIksW8eemLSe8PGDIkf7+DUYb774997ccfoYeZXx/f2bNRy/VncdUpbnjjDVwb1rP4nHPw3LnnBn+mbdv8ZU9++w2RsWnTcC1XqJD8Z884AwugINCtwzaNxMNJJ2Hxn07kOxEBpOoAj29Yk9U336QvR7Zz584/5mrnZkYEcD9CW+fcP51ziwNea+QQRbT1e+1+f87W793h+5yt38vENvw44COAjz2G1FY8DBqEyevPgBdewCCUbiStKHDqqemfp4ULD0wRbD9Gjszf76AUxeOPZ36f5s3DtuMJA0fYf/H22zh/1umC1pFBskEiqJ8OcwlJBnPn4jpOxT5w0SKM2UGgWLP/d4Th9NORUnbO6+CRChIRwBYt8P8PPkhebzATiCKA+w+6O0jAzI7znvudczudczWdc7UcOnjvNq/nOkT4RjvnspxzRzlIuXTM8DYsDngCmAxGjAiXOShuYJ1POoN2UWHOHJGzz05vG0uWFI8U5dix+RPF3r7dK6qbSdBl5EAsL4gg8t57OH92wUx7uOXLgz/TuXN6Ufn58xHJrlw5+c+cfz6ihkH4+WclYsl4Wi9ciIi1c155mFSwcGE4AbzyStUjZIfyZ5/l73tSRUQA9x/scs7tdZB++eH3xx7n3ELznmrOuS0OGn7fOeducbEn7igHDb//OufedZBzscjENiz+FARwzJiiMYgvCrz2GgahAzHl/dVX+dPDsjj//PTFpPcHHHssooCp4s47cf537878Pp133oEbXY6gEaqPP9bn3nkHz1n7NIvcXDRW5RcLF6KWtWrV5D+zfn34Iu5//1MilijzI4Lf1b8/3h/mRZwI8QigBcnpnj35+55UERHACOniT0EAx41DGP/PAEp9hCn7F3dccMGBqYHox/HH56/WjjqQ772X+X1avfrAXVxEEPnoI5y/zz/X5/bswXNBWn4ikCMKcvpIFosXQ4uvevXkP7NlS7j7CL2pnYMrSCJcdRV0QZ3Lf+1rsgSwsBERwAjp4k9BACdODFarL45gmidM2LW44667RFauLOq9SB9TpkB4OVUwpVcQaSiKTP9Zr60DHewC//JL7/PVqgU7x4hAxy+dxeS550I4vEaN5D+TlweR6jCULBkbyQzD3XdDMzAd4hYRwAjFFX8KAjh1aniXW3HDhx9ikEq3li5C0WLatPxpOT72WMEVotPLNEwyJML+Ddao+css2rYVWbs2+DN9+qRXP710KRpJatXK/zb8KF06+UXOiy9q13B+ERHACMUVfwoC+NJLyXWMFQdwlR9N0gc2Tj01f80WFKMtiDokdoyGNQxE2L/x5Zc4f99+631+1Ci4ZQShf//0Ir7LlyMFW7t2/rfhR7ly+B1//3vi99KRJJEVXTxEBDBCccWfggD+mfDFFxikliwp6j2JkA5mz47vwBAG+r3mV+w5HqgxuGZN5rcdoeDx1VfBi4NPP40lhcSgQeE2cclgxQpYzdWpk/9t+FGpEn7HP/6R+L0//YT3JrKii4eIAEYorogIYDEDLZiiKM2Bjblz8yfA+/LL6UU74mHrVlxbYdGiCPs3fvgBkbhff03+M0OHpldOsmoVdPLq1s3/NvyoWhXX4b/+ldz7q1RJzYrOj/2VALZrFxHACOkhIoDFDP/3fxikikMjxJ8ZF10E2ZVUsXt3apprqeD223FtXXllwWw/QsEj1U7YESPCfYKTwZo1Ik2aiNSvn/9t+MGmjmTrXFu0SM2Kzo/9lQB+/31EACOkh4gAFjPQgzNK0/058fPPIjffXDDbvvdeXFubNhXM9iPsfzjyyPTqidetE2nUSKRBg8zt00EHxbdc86NnT5GKFfP/fREBjFBcERHAYoYffsAgtX59Ue9JhOKGnTtxbW3eXNR7EqGwcNRR6SkobNiA6F/Dhpnbp/r1g5tZwnDMMelFxSMCGKG4IiKAxQy//IJB6uKLi3pPIhQ37NqFa2vHjqLekwiFhWOPDfcJTgYXXYSI3cEHZ2yXpGFDXIf/+U9y7581KzUnEj8iAhihuCIigMUMe/dikLrssqLekwjFDc89h2vr3nuLek8iFBYmTBBZtiz/n7/0UohAN26csV2SJk1SkzpauTI1JxI/IgIYobgiIoDFDLRK2rixqPckQnHDX/6Ca+vhh4t6TyIUFiZOTE9R4PLLEX1r2jRz+9S8Oa7Dn35K7v2bNqFxJL+ICGCE4oqIABZDZGVBtDdChEzi9dcxAe7aVdR7EqGwsGUL3GXyiyuvFKlQQaRZs8ztU8uWuA5//jm5999/f3pC1BEBjFBcERHAYohy5USuv76o9yJCccO772ICfP75ot6TCAcKrr4aIswtWmRum61b4zpMVs/w/fdFOnXK//dFBDBCcUVEAIshKlUSuemmot6LCMUNH32ECfCvfy3qPYlwoODaa0VKlRI55JDMbbNtW1yHe/dmbpvxEBHACMUVEQEshqhWDambCBEyCdoMvvVWUe9JhAMFmzbhmmnZMnPb7NgR20xV1Dq/WLQoIoARiiciAlgMUauWyG23FfVeRChu+PprTIAffFDUexLhQMENN+CaadUqc9vs0qVwiZglgN99V3jfmwgRAYyQLiICWAxRt26k1RYh86DLzOefF/WeRDhQcPPNuGZat87cNrt1EylZMnPbSwRLAJNtPCkMRAQwQrqICGAxRIMGInfdVdR7EaG44aefMAl+9VVR70mEAwWbN+OaOeywzG2zRw+R0qUzt71EsATwl18K73sTISKAEdJFRACLIRo3jsR6IxQMdu4svNqrCAc+tm4FcWrbNnPb7NNHpGzZzG0vESwBTLbzuDAQEcAI6SIigMUQLVqIPPhgUe9FhAgR/uzYtg3EqX37zG2zf3+R8uUzt71EsATwt98K73sTISKAEdJFRACLIYYNE9m9u6j3IkKECH927NgB4tShQ+a2OXgwpK4KCxEBjFBcERHACBEiRIhQILjjDhCndISY/Rg2TKRKlcxtLxEsAfzf/wrvexMhIoAR0kVEACNEiBAhQoHg7rtBnLp0ydw2R42C1mlhwRLAwhKfTgYRAYyQLiICGCFChAgRCgT33gvidPjhmdvmmDEiNWtmbnuJYAngvn2F972JEBHACOkiIoARIkSIEKFAcP/9IE5du2Zum0cfLVK7dua2lwiWAO5PHfARAYyQLiICGCFChAgRCgQPPgji1K1b5rY5frxInTqZ214iRAQwQnFFRAAjRIgQIUKBYOdOEKcjjsjcNo8/XqR+/cxtLxEsAdyfEBHACOkiIoARIkSIEKFA8OijIE49emRum5Mnw+2osBARwAjFFREBjBAhQoQIBYLHHwdx6tUrc9ucOlWkUaPMbS8RIgIYobgiIoARIkSIEKFA8OSTIE69e2dum9OnizRpkrntJUJEACMUV0QEMEKECBEiFAiefhrEqW/fzG3z/7d35+FyVHUax783CSEJCTuC7BAIiJFAggmEQYiJ7BD2JSyiiAECmLAEAmGTPTIgOwMCM6wiqyKYYRscFlFRRAwgg7JkRAZRRJTFkdT88daZOl23b264t/tWV/X7eZ5+cru6b+V03eo6vzrnd8457LAkGT68cfvrjgNAqyoHgGZm1hSPPqrAaeLExu3zyCO13nlfcQBoVeUA0MzMmuLxxxU4TZrUuH1On54k66/fuP11xwGgVZUDQDMza4onn1TgtPXWjdvnsccmyQYbNG5/3TnxRAeAVk0OAM3MrCl+8hMFTtts07h9Hn98kowc2bj9dccBoFWVA0AzM2uKp55S4LTddo3b54knJsmoUY3b36L8fw4ArYocAJqZWVM8/bQCp+23b9w+TzklSTbeuHH7644DQKsqB4BmZtYUzzyjwGnHHRu3z9NPT5IxYxq3v+44ALSqcgBoZmZN8eyzCpx23rlx+zzrrCQZO7Zx++uOA0CrKgeAZmbWFM89p8Bp8uTG7fPcc5Nk000bt7/uOAC0qnIAaGZmTfHCCwqcdt21cfs8//wkGT++cfvrjgNAqyoHgGZm1hQvvqjAabfdGrfPCy9Mki22aNz+uuMA0KrKAaCZmTXFSy8pcNpjj8bt85JLkmTLLRu3v+44ALSqcgBoZmZN8fLLCpz23LNx+7z88iSZMKFx++uOA0CrKgeAZmbWFK++qsBp770bt8+rrmrs2sLdcQBoVeUA0MzMmmL+fAVO++zTuH0++WSSnHNO4/bXHQeA9nF8DVgAfD23fWngJuDPwJ+AG4Clcu/ZA3ge+BswD9i1CfuIOQA0M7OmeP11BU5TphRdkp4LAeALLxRdkloOAFvPesBvgF/QOQC8F7gfWAZYFngAuDt6fRzwPrAL0B/YDXgPGN3gfcQcAJqZWVO88YaCp/33L7okPRcCwFbjALC19AOeBHYG/oPaAHB11Co4Mtq2Ybpt1fT5tcAduX3eCVyd/rxGA/aR5wDQzMya4s03FTwdcEDRJek5B4C2KGajLlnoHADujFri8j4Adkx//jlwfO71WcBT6c+TG7CPPAeAZmbWFG+9peDpi18suiQ95wCwfV2HWtg+Sv/NPx5O37cR8ArK0YPOAeD+wO/r7P8NYEr680vA1NzrhwIvNnAfeQ4AzcysKd5+W8HTQQcVXZKeO+kkB4DtagjKtevqMQwYADyD8u6Cj9MCuEP6c3etd43YR96SQDJt2rRkxowZyYwZM5K5c+cWfV6bmVkFvPOOgqcvf7nokvRcKwWAc+fO/f+6etq0aQ4AW8AaqIXwTeAP6ePvaBTus+l7Vk/fE+fvjUq3xfl7t+f2HefvNWIfeW4BNDOzpnj3XQVPBx9cdEl6rpUCwJhbAFtDB7By7vEEcCGwYvS+e4C5wHLA8mgE713R6+NQC99k1Kq4OwoiRzd4HzEHgGZm1hTvvafg6ZBDii5JzzkAtI/rYerPA3gjmsPvbeB6Ov/hdkdz+L0HPEdtt3Kj9hFzAGhmZk3xwQcKnqZOLbokPecA0KrKAaCZmTXF3/+u4OnQQ4suSc85ALSqcgBoZmZN8Y9/KHg6/PCiS9JzDgCtqhwAmplZUyxYoOBp2rSiS9JzDgCtqhwAmplZ03R0JMmRRxZdip5zAGhV5QDQzMyapn//JDnqqKJL0XMOAK2qHACamVnTDByYJNOnF12KnnMAaFXlANDMzJpm0KAkmTGj6FL0nANAqyoHgGZm1jRDhiTJMccUXYqecwBoVeUA0MzMmmbYsCQ57riiS9FzDgCtqhwAmplZ0yy1VJLMnFl0KXrOAaBVlQNAMzNrmmWWSZITTii6FD3nANCqygGgmZk1zXLLJcmsWUWXouccAFpVOQA0M7Om+cQnFESV1ezZDgCtmhwAmplZ06y0koKosnIAaFXlANDMzJpm5ZWT5JRTii5FzzkAtKpyAGhmZk2z2mpJcuqpRZei5xwAWlU5ADQzs6ZZY40kOf30okvRc08/nSRjxxZdis4cAFpvOQA0M7OmWWutJDnjjKJLUT0OAK23HACamVnTDB+eJGeeWXQpqscBoPWWA0AzM2uaESOS5Oyziy5F9TgAtN5yAGhmZk2z/vpJcs45RZeiehwAWm85ADQzs6bZYIMkOe+8oktRPQ4ArbccAJqZWdN85jNJMmdO0aWoHgeA1lsOAM3MrGlGjUqS888vuhTV4wDQessBoJmZNc3GGyfJBRcUXYrqcQBoveUA0MzMmmbMmCS58MKiS1E9DgCttxwAmplZ04wdmyQXXVR0KarHAaD1lgNAMzNrmk03TZKLLy66FNXjANB6ywGgmZk1zfjxSXLppUWXonocAFpvOQA0M7Om2WKLJLnssqJLUT0OAK23HACamVnTbLllklxxRdGlqB4HgNZbDgDNzKxpJkxIkiuvLLoU1eMA0HrLAaCZmTXNpElJctVVRZeiehwAWm85ADQzs6Y5/fQkefTRoktRPQ4ArbccAJqZmZWMA0DrLQeAZmZmJeMA0HrLAaCZmVnJOAC03nIAaGZmVjIOAK23HACamZmVjANA6y0HgGZmZiXjANB6ywGgmZlZyTgAtN5yAGhmZlYyDgCttxwAmpmZlYwDQOstB4BmZmYl4wDQessBoJmZWck4ALTecgBoZmZWMg4ArbccAJqZmZWMA8DWsgpwI/AW8BfgWWBk9PrSwE3An4E/ATcAS+X2sQfwPPA3YB6wa+71Ruwj5gDQzMysZBwAto5lgJeBOShIAxgOLB+9517g/vS9ywIPAHdHr48D3gd2AfoDuwHvAaMbvI9Y5QLAuXPnFl2EluNjUp+PS2c+Jp35mNTy8eisiGPiALB1nAH8ZCGvrw4soLZFcMN026rp82uBO3K/dydwdfrzGg3YR17lAsAZM2YUXYSW42NSn49LZz4mnfmY1PLx6KyIY+IAsHX8CPg2Crb+iLpgZwMd6es7o5a4vA+AHdOffw4cn3t9FvBU+vPkBuwjzwFgG/Axqc/HpTMfk858TGr5eHTmALCarkMtbB+l/+YfD6fv+y/gH8C+qOt1Q+A14Lj09f2B39fZ/xvAlPTnl4CpudcPBV5s4D7ylgSS+fPnJ++8804lHtOmTSu8DK328DHxcfEx8THx8ajWMZk/f74DwCYbgnLtunoMS9/3M9QKGDsh2rawFsAd0p+7a71rxD7yVkEnkB9++OGHH374Ub7HKlihrgaeyG2LA8DVUStinL83Kt0W5+/dnttHnL/XiH3kdaCTZ0k//PDDDz/88KNUj1XIUs2sIKNRS9xeQD/g08ArwPToPfcAc4Hl0OjgB4C7otfHoRa+ycAAYHc0lcvoBu/DzMzMzBpkB+CXwLsoJ/C43OtLo3kC/wy8DVyPIvjY7mgAyXvAc2g6l0bvw8zMzMzMrJLcNWJmZmaV0UHn4MbBTmeLFV2AFjQw/dfni/gcMTMrgWHdv6XSOlCOabAVsH0xRWlpewI/RSPnTQYDlwLHFF2QFjEIOB9NkzW44LK0ikHAIWj2C5OhwNpFF8Ks3Z2K5l7cquBytIK1gIfQvJBbF1yWVvIp4FHgdbK5MQ2ORRPU30vntcPb0UFkx2NjfEwAZqB17H+AAp5+C397WzgN+B90k+BzxKwAuwO/QVPqjCm4LK3gbDTAZ07RBWkxO6DJ2K+JtrV7JbYa8EPgD8BnunhPu3UFrw48AmzXxevtdjwADgaeBjYruiAtoAPN8XsPqnPGptv7F1Yisza1FWr1mxFtW5Ysj6ndfA4Fw1fktg1H0wK1s8+jVtGZ6fMjgZuA89C0SO1oXRTsXJw+Xxk4Czic9j0m04AH059HAFeic+TgwkpUrCHoHNk9fT4cOADYkvZNufkndI6EG8hVUauo80XNmih/9z0A3Zmelf58Nark/wNVYiv1aen6Tr7lKjwfDJyELthTgcfR6i9PAy/QdStPFQ1K/x2Q/tsfOBp4GS2P+Bjq+rwTzYW5C+3ZuvNV1Ar4I3RcrkHdfO+hYKhdhL/92ejc2Ax17/0zuq78HrggfU87tRwPBn6F8mWno+nFvg28gxYWWL+4ovWJeteES4Hb0p9vQtfWp4DvkvVCtdM5YtYnQvLxgGjbJNQK+D9oDsQt0Bf0h8AlfVq65osvRstSm+8YLjiboM/+R5SbMpCspWcu1b9rXw3Nf3kS2fEK3TOfRpVWPrC5Hrg//bmqQeD+KOBdJn0ejsmyqEK/DXV/Bl8B/gQs0VcF7GMHk82BGnff7YvmSb0f2DXd1gF8AV1nqrys1uZoLlnIridrAr9Awe/tKL8YFBDehQLkKgt1Tn+yY3ICCvguQt+dpVGKybdRsGxmDbQl8Gvgji5ePw3YL7dtJnAfsGLzilWYGSif7QmyVVziSmxnFOxAFtCMAj4EPtkXBSzIFGAeWbL6P6Xb47vx4WTHKgTDRwG/pZrBzmrA3WhJyFfRDVMQjsunyL4nIX1iPdTKU7W8rzVR/tYCtDpTOAbhnNgMeBJ4P30v6JisDbwE7NRH5exLG6IW4HdRK3nebeh43ZQ+D8fqWuDfqGbXZ6hz7qzz2lfRog7PAxtE2zdE15Gtml04s3bQD7Vc/AKNyHuNrAKLWwEHo4tQBxqWDzALfYGrVqnvhUaynhz9GyrtcGEehI5dP7LjtA+q2KoYEAcHoFaujVD397lkQd7CumRuRnf1VbQ58K8on+0/URfvyulrCzsmBwPfoxqVe9wSfBBwOeopmEeW/xhfT2aigOewaNvnUGrJ0lTLaqhn4Ap0nnyXLKgZGL3nQ+D71H7+S6heC+DC6pxwPJZH58IC1LsSfBa1AI7ok5KatYHd0bxt66AL1JPRa1111w1EzfH55fbKJF85h8+6NFlC9jnAw3Q/1ctG6Lid2rDStYb81AuLASukP5+AAuRd6Www6sqbADyLAqPhTSpj0ZZALU46dXwAABOlSURBVHwA26JWwH2o/91ZBp135wK/Q8ESXby3rEagawnohuEjsm7NUMGviI7BAjQI5EqU+xZax6p0PEC9J8ujQOdBlAcZhMD4BLR06PdQ3t8clE+7Rd8Vs88srM4Jx2MXlPv3ALqWDAQuA26leo0OZn1mBLV3mUPJvnQTUTdMyOGKuz2XQt00x6J8wO9Q/rv1YWgwx2bUfpYQHK6MgpeLyEb5htcGoQr8NtSVN5PqWBF1zTyO8pIm0blSXhJdnL+FWjDyr90GvIK6f6viAJT2cDawdxfvuT19T0jeD+dLB7pheh3dVKzb+VdLZ3/09z8GzeeXtzQaNPZA+nxA7vX9gdmo1bQqrTrbo3zG9aJtcSvv2eiYfD59vnj6bwfq/n4A5RM/RDXOEVi0Oufw9Hl8rCaiWRceQwOo5gKfaGpJzSpqPOqSeQrdaU5DFTVkldTSaMTvS9FrwSqoRewJ9MUMynq3fjjwVzSg41eoS2Jc9Ppi0ft+hCr/vCPQagZDo21lH522ATpP/gX9na8H5qNBC0G4eE9BK34cEr22XPrvGGpvIMo6j1cHatG8FgW0R6c//y/KVQp/+zi37zVqV/wIA0NGkuVNltkwlPf4Cmq5egblbNUb9LElyqfdIdq2OPX1p7zXk7XQtfU1FKi8C3yRrLUqnB8jUY7k1dRvyepP9h0qu97WOaBBVOuh/L+g7NdYsz41HH0Rj0OV2Znorura9PX4CzUGVeoh92RNsgtSPMAhvyxamayNuh02T58vhVr67iYLAkOQMxBdsL+FWgEnk82LGFdW+daNsgmf5UBqu2QArkKjNrdNn8cV/LUoef0cNJXH4bW/WtrAL7Y6CnDibuyT0217RtvCZz0X3Vhsj1pCr6QauX7BJuj7ElrFV0E3Qn8kC3bD+bQEupmYh4Ll76ObqXygV9ZrSXA++pzB2ehmuV639gyU47Yt6kk4ty8K2Md6W+fUm1e1g2pcT8z61DTgx9Hzfmg6hvfJWvNCBbU4atn5HXALytPZJ7e/snwJu5rPL+RqxdNybIq6X75JFsyFlopx6A71bVTJ7Zhu78j9W3Yd6EL9PVRZh+M1AiVsX0rndUqPQOfIb6ifD1gFe6J8pNWpPffvA24g6wIPrw1Ex2QBGllftZylMN8jZN+VZVArz+W57aCuzAWoJXAu1VvrdjC6GTg22jYUBYWPk80YEFoBO9CUWq+jY3IHOl5VuY5A7+ucrlIszKwb+QDtIFSBxQHRMJSA+/M6v38G+hLeQzknIo0/5wBgDWpbYKagymotap2M8rPiruAl0MX6QzTyuSqWRINWvoZGYIauzCNQl29+PrbZqCs8tIJ1oJatBXSe2qLMFdlEFPBtGm1bD33OMAltqMh3QpVWeG+Yz+4j1EL2KcpvPMpXWyfaFm6gNkqfh+/bFDT1S9x6sxXwd3Q84mtJmc+R1VHQF6yErhtHUfu5Nkct56flfn9nlELwINWZPL7d6xyzwo1Bd1BXoLvRsFrDfuhOdLfc+7dFgVAYaTYI5WO8SdbKBeXNzZmO5o0Kq5dsn24fAPyFbIBCuEitgga4xKN+j0EX8bhSK3t37ww0CfEtaNDCC9R2Vf0BBcOxT6JKK744T6B24usyH5fhKPn+ZXRcPkTnT8hLeghVTlBbqb2cvi9Yl2x0b5mti4K2X6PvzlsocAGtzzoX+Ebud9ZGlXvoFh+Aeg/i1pwwfVIZrY8CvSfSx0yyXoLbUA/CCrnfuQENcgnXz0+j7s79m13YPuI6x6xgg9CcUW+jFRrOAV5EicagyvtB1D0T5/GFiTXjyWjzo/HK0t0bWw11Wf4MJd2vh+bfildjOAWNLFszfR6Cl/+icx5bUPaLUn/gyygXZ2y0/Wo0V1/ompuKliobT+eKax06V+Bl777aBFVW50fbTkHnT8h/nYgC4LhCG4CmwjkwfV7WwCZvO7S84Xnp8+XRShUvRe85CwXM8cTNK6PW47j1NFbGa0lwFGrtPQsdj/NQnmf4249ALb9fonaQy9logFnVuM4xaxHT0MoMYW3e/mii2afIkrIPQRV/3LKzKro4xd07QVlbczpQC97F1E49sAO68ISuzn6o5esWNMEoKCh6ErVkxPsL7y+7fmgQS6i0w936DNS9G/sBOhZnoLv8n6A5uKo0mCGYgCr4QdG21VGrRJwneh5qIQ4tg8eg1QrqfX/KbG+UCxrbBQXJ4XqyHurOewndKAwEjkethlVbDecTKP81Dv6HoBuEOD/6QpQLuG+07QZqR4RXhescsxYxEuXfQJafdBJqnQj6oS/if6OL0vT056voelqGMqjX8rQeOiaQBSyT0ai0pcguNBujLp3X0Lx3H9A5X6dq8pM7g5abCq1fIQhaDo3gewBN5nxend+rimFklVYwBQW9A6itmL6BKrVfofNpLNUR3+yEFW1Ca8zxqMUvthpKIfgFCgTnodbUqhmK8oJDOkC4Xr5Adt0FnSdXoNHwt6GBUT+jc65xFbRznWPW8uagZnnIgqB+KAfjAnT3tm+d3yuLvVi0JbdC5T0HDeaA2qBxJTTR8RF0ntC46gagZPZn6DzSOxhCbcJ71btnwvlyJVl3Vv71xclGdlZdR/q4n9pcx6AfaiEbm/udqgqfbX0U4OVvHAajLvCpdP2dqqqq1zlmhequiTxcnAaiSn2vRdxv2Sr1oagF5pH0+aJUOD+m9uKzahfvK3ueX6iwF9VnUd5jMJHaij5e57XMx6Weep8n3Ew8RTboAfRdGtT57aX1cVIalkXft7jbbhPqX4/Kdi2JfZyyTwP+vVkFaSGuc8xKInwZt0T5S8Fs6q9TW+Yv4QTUZRuWVFrYZxmLRjN2oBa/O1GuUn4pu7IHOPEx6NfFz3kzyVYzeRCdN1Weg2sCStRfmM+gbl7QoJk/owlsB3f5G+XRk1G426IWQFBe14dovswyXz9i+eOxOzCqi/eGz/wAauUDOBR9b7ZpfNFaXjvVOWaFGoTyksKKDF0FLF9DzfHjUJ7K89SOuiqr+OIxCLgOBXbdmYpWIDgDVebXkOWtVEH+Lv08tHLJLBaeazMA5Sj9BR2XS5pSumLUawnthwYyfD16Xs8ZKI9rHmod/UIzCliA+PNuivKztiCbqLqr68llqAXwKfR9q8rxyFsK5e79Fi2J2JXl0Q3CDDRQ6nlqp46qknavc8wKUa9yGozuxLuapgT0hX0CTar5BtldKpS/hSsIFdYGKHAJ8/l1dXd5Hzoe91I7OW/V7kZXQ6N57wdORNNW3Es2gXGsA+VuPY0qvZWj16o4Gi/8rb+B5rVbmNvQvHdfbWqJirE4muLmr+im6E10roS/ef4aMSh9zx+Bw6LtZV4Ksp5/RvM8XrAI790JXU9+R+dJ0MvMdY5Zi4mnJOmPvmgzouf1PEbn9SXLEux0dPFz8G9o6pbQgjcbtWAN7OJ3BqMRjJOibf2pVuUFCvQeJUvCBgV1T6G5yIbW+Z3FyOZBhPLn+eX/pvuh7v4wLUkH6q67DwW/Xfk81QyCd0TLjs0hOx9ORV3/YcBC/PcPx3MnalvMy3Itqaersu+JApib0ede2PfgCyhoruKUSNB+dY5Z4fKV1xKoi/NZNF1JcDGqwBYm7vYrY0W2sDLvgpaW+lz6fCXU5XBl+jw+jvUu4mW/KHV1bA5EFdjFuffNRKszDGLhlVqZj0tXeW2j0LxsPyBbf3Q3tIxZvWNR5uA31tXxmIVuluLRzZ8Evo3meAxBcfjd/PEo47UkyLdYjkarncTbHkof+dzgvKrcPLrOMStYB7WVb/xFGkGWfxO6X6ajubfqzecWK+uSS5sB3yPLqTmAbKBH8BBqtQjHYAoKCsOM8vWCmapU7sGX0KjmdaNtP0XdevHUFOOAd+m8tm8VjUStnVPQigOgkasXoi7MndHEzi/R+ZyqivjcXwkFM6Glah3gO2QDXIJ90fdpZtNLV7wNUZrEb9Ayft8iG908Et1ELepI1rJynWPWYlZAM+vfAlyEpl4ITkAtGbNQsu0v+7pwfWgcCvBCS9Y81EIR56itjS7UB6TPl0DJ/VVccilva5Sk/ghaiuoRdH6AEvsXoByc0IpxDpr/sEoBcKi8wmcagLo1/4BaMB5DeWs7kVVI30RBzgOoNWOHvipsH8i3uAwFrkcDNh5HFXowBQ1ciPP5FkfXnTuove6U2RIocImDlr1Q0HcS6tIejQKds8k+93XoOtION0yuc8wKkF8w/EhUed2Epll4DXXThMlm+6HA6Bk0fcn7ZCtdVNHRqOL6HJqn7lVUccW5OXeh3JQ10+djqJ23rezWR0srDYm29Uc5SodG285CQV8IkK9Ln9+Cgp2XybrLq2Br9BnjeRw3QUHNitG2m1GgF1amGIKOw5/Q8anKlB2hxTzkuE5Ea7J+B7VsHYBGZIaRz59Elf0PqT1e61KdeQ470GdegIKXYEtqV+44FK3f+wywR7ptUPp7s6nWTZPrHLOCjUYXnPvIWjFWQHfr8TQCp6M1R2dS21S/IerO+ojaHI2qCBfcVVAFdmu67ToUzKwfvfdGdKE+qS8L2AeGomWTwvJJG0avjUWjnkEBzfVo1F281uiS6GJ9JrBdswtbgC+hYC+erPoUVEktRhYwr41GaYaWvvA9GkXteVR2ocX8EvRd2QfdOAQ7oxHN/0u2rvE2KF3g0jr7K3sXXvg7fxPlsr1FdpM4FH2+zwLPofNoExTkXE/WFbwX1TlHXOeYtYjN0YV4AdnC4ouRzTm1EZpz6Xk0y/yjqFsv77dohCNU6y4Vss+zP+rK+yJqqXgB5esMR12cp6DKLb8UU5ltiiqmG9HnGkLtxXgTFAhfibo4byXr4voc2VJ2p6F57NZIn5d5gMdS1I5AHQBcjkY9j063HQW8Hr0n5DT9mqx7vMqORgHwTuh6siRqIf13YD4KCH+OWoVB3aNHoBaxKlgOzc0H2fyPt6GpS36IvidBv/T5ydG2J9AN14FNL2nfc51j1iK2QdOY3AS8QjafHWR3oqenz3cC/gH8C52Tb+8h+zJW1SD02eeii/tuqKXjNRQkxWuPlr3VIpiNgpu80DU3Al2sX6X28+8H3E3txKuvooC5zKtXzEKrTtyAuihDIDsR5fPNSZ+vgLp2Z0W/uyYKihY2oW/ZxS3mt6Jc2dDV9y1qz6WfoSBgItUyCw0Au5Xatby/jnIaN0Kfe4t0+wboWIRpTS5H19yd+qKwBXCdY1aAr6EltuIuvLVRS8W6KDcrXirnMDRdRXAaGnk1ldoWnKNRpbhRw0vcOkJANxF4mCx/aSDV/tzPos86GFXqE1Fr4DWo63MAylt6GFV4e6Q/v4amx4EsKNgPtYCVuYX0MjRtyX+jFqzLyL4LJ6PWnZDLdyAa7XwPSup/A3VxVmnFl3riFvNHUG7X0ui4hRU7pqPBQF+idoqTKrTkXI7Oj3logu+QC7krGuAwEAWCP063L4muqz9GI8Pvo/vRrWXhOsesBXwB3XW+hUaZjSRrxbkf2B5djP9K1k13Fkrevhy13nyHzom7/dAi5GNpH2eilr/8tB1l7tbsynTUXfMYqpjeRt1296Jz4vj0fZugvJwr6ZwDWYVKPVgLBXmnA19Bk1o/gVboWAtVVtegSh1gMsqHvAJ1fbWT0GJ+H7Be+u8vUdfdM9SubVulc2RtdI6chm4Q7kXd25PRTUN4z9/Qus6gm6JxdL3ebxm5zjFrITejO9CHUCvOaen2+8mCmWfI8nJWBQ5Kfy8eqVa1JZcWVaikPo0qs5lUq+Lqyn6ooppKNi3DYuhO/WZqu3Tj8yI/FUhVjtWJZC19Q1AL6F9QF+d9KG/poKIK1yLCeTAJdY2fiYLivchGtwZVOS9iJ6Lc2D1RoDIP3QS8i4JhUAvoArKbhSpynWPWIiahLpnZKNn6NVSp/wrdeQFMQBelSXV+H6rZyvVxhIvQXajCh2pWYIviu2QtgLGQ9F5VS6Ag7zqyHK/xaBDQR+j7831gWCGlaz1noa7Q8bntVb6WhHPkX9FNwih0vnyXrEVrKLWj5avIdY5ZC7kUXZg+hfInrkJfvnjx9XvRFzbmu6/MYNQC1A6rFMTCSNY1UIDzU7I5utrN3mjwy6G57dugQLAdJu3tTtxi/gP0fWmn68jeKEXgK9G25QoqS5Fc55i1iHXQskNzUD7GADR1SbyqRdWT1HtrKprjrKoLr9czFHXj3YByei4ptjgt4UaUozS6uze2sXZvMb8RTf8yJn3eTp89cJ1j1kJmoqT+Xbp5n+/A6mvHizjoon0qtVNbtHP3zHg0jcXRtO85sSjatcUcfI4ErnPMWkTIT7md2srcbFH1p70rtCBMdGxda8cW85jPEdc5Zi3lADQKbUh3bzTL8V26fRy+UTBwnWNmZmZmZlYst+aYmVlfcZ1jZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZmZpXzf0rStyVEQAuGAAAAAElFTkSuQmCC\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d7bc9b5f8>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_history.supply.diff().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d02d68ac8>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_history['2016-05':'2016-02'][[\"supply\", \"demand\"]].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "url_daily = \"http://www.gw2shinies.com/api/json/history-daily/19721\"\n",
    "ecto_daily_history = pd.read_json(url_daily)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "ecto_daily_history[\"timestamp\"] = pd.to_datetime(ecto_daily_history[\"timestamp\"])\n",
    "ecto_daily_history.index = pd.DatetimeIndex(ecto_daily_history.timestamp)\n",
    "ecto_daily_history = ecto_daily_history.drop(\"timestamp\", 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d040f1198>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_daily_history[[\"supply\", \"demand\"]].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\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 overriden (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",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x17d0416b8d0>"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_daily_history[[\"sell\", \"buy\"]].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>buy</th>\n",
       "      <th>demand</th>\n",
       "      <th>sell</th>\n",
       "      <th>supply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2016-05-27 23:43:01</th>\n",
       "      <td>4907</td>\n",
       "      <td>211139</td>\n",
       "      <td>5245</td>\n",
       "      <td>106366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 23:28:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 23:13:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 22:58:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 22:43:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 22:28:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 22:13:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 21:58:02</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 21:43:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 21:28:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 21:13:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 20:58:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 20:43:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 20:28:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 20:13:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 19:58:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 19:43:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 19:28:01</th>\n",
       "      <td>4925</td>\n",
       "      <td>206603</td>\n",
       "      <td>5115</td>\n",
       "      <td>115478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 19:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:43:02</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 18:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:28:02</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 17:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 16:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 16:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 16:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 07:13:02</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 06:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 06:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 06:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 06:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 05:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 05:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 05:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 05:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 04:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 04:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 04:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 04:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 03:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 03:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 03:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 03:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 02:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 02:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 02:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 02:13:02</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 01:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 01:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 01:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 01:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 00:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 00:43:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 00:28:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-27 00:13:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-05-26 23:58:01</th>\n",
       "      <td>4912</td>\n",
       "      <td>206794</td>\n",
       "      <td>5503</td>\n",
       "      <td>92148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                      buy  demand  sell  supply\n",
       "2016-05-27 23:43:01  4907  211139  5245  106366\n",
       "2016-05-27 23:28:01  4925  206603  5115  115478\n",
       "2016-05-27 23:13:01  4925  206603  5115  115478\n",
       "2016-05-27 22:58:01  4925  206603  5115  115478\n",
       "2016-05-27 22:43:01  4925  206603  5115  115478\n",
       "2016-05-27 22:28:01  4925  206603  5115  115478\n",
       "2016-05-27 22:13:01  4925  206603  5115  115478\n",
       "2016-05-27 21:58:02  4925  206603  5115  115478\n",
       "2016-05-27 21:43:01  4925  206603  5115  115478\n",
       "2016-05-27 21:28:01  4925  206603  5115  115478\n",
       "2016-05-27 21:13:01  4925  206603  5115  115478\n",
       "2016-05-27 20:58:01  4925  206603  5115  115478\n",
       "2016-05-27 20:43:01  4925  206603  5115  115478\n",
       "2016-05-27 20:28:01  4925  206603  5115  115478\n",
       "2016-05-27 20:13:01  4925  206603  5115  115478\n",
       "2016-05-27 19:58:01  4925  206603  5115  115478\n",
       "2016-05-27 19:43:01  4925  206603  5115  115478\n",
       "2016-05-27 19:28:01  4925  206603  5115  115478\n",
       "2016-05-27 19:13:01  4912  206794  5503   92148\n",
       "2016-05-27 18:58:01  4912  206794  5503   92148\n",
       "2016-05-27 18:43:02  4912  206794  5503   92148\n",
       "2016-05-27 18:28:01  4912  206794  5503   92148\n",
       "2016-05-27 18:13:01  4912  206794  5503   92148\n",
       "2016-05-27 17:58:01  4912  206794  5503   92148\n",
       "2016-05-27 17:43:01  4912  206794  5503   92148\n",
       "2016-05-27 17:28:02  4912  206794  5503   92148\n",
       "2016-05-27 17:13:01  4912  206794  5503   92148\n",
       "2016-05-27 16:58:01  4912  206794  5503   92148\n",
       "2016-05-27 16:43:01  4912  206794  5503   92148\n",
       "2016-05-27 16:28:01  4912  206794  5503   92148\n",
       "...                   ...     ...   ...     ...\n",
       "2016-05-27 07:13:02  4912  206794  5503   92148\n",
       "2016-05-27 06:58:01  4912  206794  5503   92148\n",
       "2016-05-27 06:43:01  4912  206794  5503   92148\n",
       "2016-05-27 06:28:01  4912  206794  5503   92148\n",
       "2016-05-27 06:13:01  4912  206794  5503   92148\n",
       "2016-05-27 05:58:01  4912  206794  5503   92148\n",
       "2016-05-27 05:43:01  4912  206794  5503   92148\n",
       "2016-05-27 05:28:01  4912  206794  5503   92148\n",
       "2016-05-27 05:13:01  4912  206794  5503   92148\n",
       "2016-05-27 04:58:01  4912  206794  5503   92148\n",
       "2016-05-27 04:43:01  4912  206794  5503   92148\n",
       "2016-05-27 04:28:01  4912  206794  5503   92148\n",
       "2016-05-27 04:13:01  4912  206794  5503   92148\n",
       "2016-05-27 03:58:01  4912  206794  5503   92148\n",
       "2016-05-27 03:43:01  4912  206794  5503   92148\n",
       "2016-05-27 03:28:01  4912  206794  5503   92148\n",
       "2016-05-27 03:13:01  4912  206794  5503   92148\n",
       "2016-05-27 02:58:01  4912  206794  5503   92148\n",
       "2016-05-27 02:43:01  4912  206794  5503   92148\n",
       "2016-05-27 02:28:01  4912  206794  5503   92148\n",
       "2016-05-27 02:13:02  4912  206794  5503   92148\n",
       "2016-05-27 01:58:01  4912  206794  5503   92148\n",
       "2016-05-27 01:43:01  4912  206794  5503   92148\n",
       "2016-05-27 01:28:01  4912  206794  5503   92148\n",
       "2016-05-27 01:13:01  4912  206794  5503   92148\n",
       "2016-05-27 00:58:01  4912  206794  5503   92148\n",
       "2016-05-27 00:43:01  4912  206794  5503   92148\n",
       "2016-05-27 00:28:01  4912  206794  5503   92148\n",
       "2016-05-27 00:13:01  4912  206794  5503   92148\n",
       "2016-05-26 23:58:01  4912  206794  5503   92148\n",
       "\n",
       "[96 rows x 4 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ecto_daily_history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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