Elecciones 2016.ipynb

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 "cells": [
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as pl\n",
    "import openpyxl\n",
    "import dateutil\n",
    "import datetime\n",
    "import pickle\n",
    "import pystan\n",
    "import seaborn as sns\n",
    "import os\n",
    "from hashlib import md5\n",
    "import matplotlib\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.9.0.0\n"
     ]
    }
   ],
   "source": [
    "matplotlib.get_backend()\n",
    "print(pystan.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Análisis de los sondeos electorales 2016\n",
    "\n",
    "Vamos a plantearnos como ejercicio analizar los sondeos electorales. Para ello cogemos como datos los sondeos recopilados en la página web de la Wikipedia para las elecciones de 2015 y para las de 2016. Consideramos sólo los partidos PP, PSOE, IU, Podemos y Ciudadanos. El resto de partidos se consideran metidos dentro de un mismo saco, que vienen siendo alrededor del 15% en cada sondeo.\n",
    "\n",
    "Para modelar la evolución temporal de los sondeos para cada partido, usamos un modelado con variables latentes. La idea es que los resultados de los sondeos son sólo una estimación ruidosa y sesgada de la intención de voto real de los votantes. Por tanto, considamos que $\\theta_i(t_j)$ es la subyacente intención de voto para el partido $i$ en el tiempo $t_j$. Esta variable se observa de forma ruidosa para cada empresa $k$ que realiza el sondeo, y además incluye un cierto sesgo. Por tanto, nuestro modelo de observación es:\n",
    "\n",
    "$$\n",
    "y_{ik}(t_j) \\sim N(\\theta_i(t_j) + b_{ik}, \\sigma_{k}(t_j)^2)\n",
    "$$\n",
    "\n",
    "donde $b_{ik}$ es el bias que introduce la empresa de sondeos $k$ sobre el partido $i$ y $\\sigma_{ik}^2$ es la varianza del sondeo realizado en el tiempo $t_j$ por la empresa $k$. Para los resultados de las elecciones, elegimos una varianza muy pequeña y no incluimos los sesgos, porque es el único momento en el que tenemos acceso directo a las intenciones subyacentes:\n",
    "\n",
    "$$\n",
    "y_{ik}(\\mathrm{elecciones}) \\sim N(\\theta_i(t_j), \\sigma_{k}(\\mathrm{elecciones})^2).\n",
    "$$\n",
    "\n",
    "Es obvio que la suma de porcentajes de cada partido debe sumar 1 en cada sondeo, por lo cual debemos asegurarnos de que\n",
    "\n",
    "$$\n",
    "\\sum_i \\theta_i(t_j) = 1.\n",
    "$$\n",
    "\n",
    "Además, es lógico asumir que, dadas suficientes casas de sondeo, los biases sumen 0 para cada partido:\n",
    "\n",
    "$$\n",
    "\\sum_k b_{ik} = 0.\n",
    "$$\n",
    "\n",
    "Por último, asumimos un proceso autoregresivo Markoviano para modelar la variación temporal de la intención de voto real para cada partido. Es decir, en cada sondeo, la intención de voto estará dada por una variable Gaussiana con media igual a la intención de voto anterior, y una varianza que debemos estimar para cada partido:\n",
    "\n",
    "$$\n",
    "\\theta_i(t_j) \\sim N(\\theta_i(t_{j-1}), \\sigma_i^2)\n",
    "$$\n",
    "\n",
    "Como es un parámetro de escala, definimos un prior poco informativo sobre $\\sigma_i$:\n",
    "\n",
    "$$\n",
    "\\sigma_i \\sim IG(0.01,0.01).\n",
    "$$\n",
    "\n",
    "Por último, debemos definir un prior para $\\theta_i(t_0)$, para el cual escogemos una distribución de Dirichlet con $\\alpha=1$:\n",
    "\n",
    "$$\n",
    "\\theta_i(t_0) \\sim \\mathrm{Dir}(\\alpha).\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modelo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Definimos algunas funciones útiles para el parsing de la base de datos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def stan_cache(model_code, model_name=None, **kwargs):\n",
    "    \"\"\"Use just as you would `stan`\"\"\"\n",
    "    code_hash = md5(model_code.encode('ascii')).hexdigest()\n",
    "    if model_name is None:\n",
    "        cache_fn = 'cached-model-{}.pkl'.format(code_hash)\n",
    "    else:\n",
    "        cache_fn = 'cached-{}-{}.pkl'.format(model_name, code_hash)\n",
    "    try:\n",
    "        sm = pickle.load(open(cache_fn, 'rb'))\n",
    "    except:\n",
    "        sm = pystan.StanModel(model_code=model_code)\n",
    "        with open(cache_fn, 'wb') as f:\n",
    "            pickle.dump(sm, f)\n",
    "    else:\n",
    "        print(\"Using cached StanModel\")\n",
    "    return sm.sampling(**kwargs)\n",
    "\n",
    "def toenglish(s):\n",
    "    spanish = ['ene', 'abr', 'ago', 'dic', 'de mayo de']\n",
    "    english = ['jan', 'apr', 'aug', 'dec', 'may']\n",
    "    for (j, month) in enumerate(spanish):\n",
    "        s = s.replace(month, english[j])\n",
    "    return s\n",
    "\n",
    "def getPercentage(s):\n",
    "    if (s[0] not in ['0','1','2','3','4','5','6','7','8','9']):\n",
    "        return 0\n",
    "    else:\n",
    "        if (s.find('%') != -1):\n",
    "            return float(s.split('%')[0].replace(',','.')) / 100.0\n",
    "        else:\n",
    "            return float(s.split('\\n')[0].replace(',','.')) / 100.0\n",
    "\n",
    "def getSigma(s):\n",
    "    left = s.find('(')\n",
    "    right = s.find(')')    \n",
    "    if (s[left+1:right] in ['?', '-']):\n",
    "        return 0.03\n",
    "    else:\n",
    "        return 1.0 / np.sqrt(float(s[left+1:right]))\n",
    "\n",
    "def weeksDifference(d1, d2):\n",
    "    monday1 = (d1 - datetime.timedelta(days=d1.weekday()))\n",
    "    monday2 = (d2 - datetime.timedelta(days=d2.weekday()))\n",
    "\n",
    "    return int((monday2 - monday1).days / 7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Leemos el fichero de datos obtenido de la Wikipedia y hacemos el parsing. Escogemos sólo aquellos sondeos en los que hay información para todos los partidos. Podríamos también escoger aquellos parciales porque el modelado Bayesiano los podría aceptar."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "3 - Invymark 2016-04-29 00:00:00 - s=2.89 : PP=28.70 - PSOE=19.40 - UP=25.50 - CS=15.40 - Resto=11.00\n",
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      "5 - CIS 2016-04-10 00:00:00 - s=2.00 : PP=27.40 - PSOE=21.60 - UP=23.10 - CS=15.60 - Resto=12.30\n",
      "6 - Invymark 2016-04-15 00:00:00 - s=3.00 : PP=28.60 - PSOE=20.40 - UP=24.60 - CS=15.80 - Resto=10.60\n",
      "7 - NC Report 2016-04-14 00:00:00 - s=3.24 : PP=30.70 - PSOE=21.20 - UP=26.80 - CS=14.50 - Resto=6.80\n",
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      "10 - CIS 2016-01-11 00:00:00 - s=2.00 : PP=28.80 - PSOE=20.50 - UP=16.90 - CS=13.30 - Resto=20.50\n",
      "11 - GAD3 2016-01-21 00:00:00 - s=3.53 : PP=30.10 - PSOE=21.30 - UP=22.90 - CS=13.40 - Resto=12.30\n",
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      "15 - Resultados de las elecciones 2015-12-20 00:00:00 - s=0.01 : PP=28.72 - PSOE=22.01 - UP=24.33 - CS=13.93 - Resto=11.01\n",
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      "26 - GAD3 2015-12-11 00:00:00 - s=1.17 : PP=28.30 - PSOE=21.20 - UP=21.80 - CS=18.10 - Resto=10.60\n",
      "27 - Metroscopia 2015-12-10 00:00:00 - s=1.89 : PP=25.30 - PSOE=21.00 - UP=24.10 - CS=18.20 - Resto=11.40\n",
      "28 - DYM 2015-12-09 00:00:00 - s=3.14 : PP=26.70 - PSOE=17.00 - UP=25.40 - CS=23.20 - Resto=7.70\n",
      "29 - Encuestamos 2015-12-07 00:00:00 - s=2.36 : PP=26.70 - PSOE=24.90 - UP=21.30 - CS=16.20 - Resto=10.90\n",
      "30 - Celeste-Tel 2015-12-04 00:00:00 - s=2.89 : PP=28.20 - PSOE=23.10 - UP=20.00 - CS=18.80 - Resto=9.90\n",
      "31 - Metroscopia 2015-11-29 00:00:00 - s=2.89 : PP=22.70 - PSOE=22.50 - UP=22.30 - CS=22.60 - Resto=9.90\n",
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      "35 - Celeste-Tel 2015-11-23 00:00:00 - s=2.89 : PP=27.50 - PSOE=23.90 - UP=18.50 - CS=18.90 - Resto=11.20\n",
      "36 - Simple Lógica 2015-11-17 00:00:00 - s=2.40 : PP=26.50 - PSOE=20.40 - UP=21.40 - CS=21.90 - Resto=9.80\n",
      "37 - Encuestamos 2015-11-17 00:00:00 - s=2.36 : PP=26.20 - PSOE=25.70 - UP=22.20 - CS=15.00 - Resto=10.90\n",
      "38 - CIS 2015-11-16 00:00:00 - s=0.76 : PP=28.60 - PSOE=20.80 - UP=19.30 - CS=19.00 - Resto=12.30\n",
      "39 - GAD3 2015-11-20 00:00:00 - s=2.89 : PP=28.50 - PSOE=22.80 - UP=20.00 - CS=16.40 - Resto=12.30\n",
      "40 - TNS Demoscopia 2015-11-09 00:00:00 - s=3.16 : PP=26.30 - PSOE=19.60 - UP=19.70 - CS=20.20 - Resto=14.20\n",
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      "43 - TNS Demoscopia 2015-11-02 00:00:00 - s=3.16 : PP=26.70 - PSOE=19.30 - UP=19.80 - CS=19.80 - Resto=14.40\n",
      "44 - Metroscopia 2015-11-02 00:00:00 - s=2.67 : PP=23.50 - PSOE=21.00 - UP=23.30 - CS=22.50 - Resto=9.70\n",
      "45 - DYM 2015-10-26 00:00:00 - s=3.16 : PP=27.00 - PSOE=18.20 - UP=19.90 - CS=20.30 - Resto=14.60\n",
      "46 - TNS Demoscopia 2015-10-26 00:00:00 - s=3.16 : PP=26.00 - PSOE=20.50 - UP=14.60 - CS=19.20 - Resto=19.70\n",
      "47 - Encuestamos 2015-10-24 00:00:00 - s=2.36 : PP=23.50 - PSOE=26.30 - UP=23.10 - CS=15.20 - Resto=11.90\n",
      "48 - Invymark 2015-10-19 00:00:00 - s=2.89 : PP=28.60 - PSOE=23.90 - UP=16.50 - CS=18.30 - Resto=12.70\n",
      "49 - GAD3 2015-10-19 00:00:00 - s=1.96 : PP=27.70 - PSOE=21.80 - UP=19.20 - CS=17.60 - Resto=13.70\n",
      "50 - TNS Demoscopia 2015-10-12 00:00:00 - s=3.16 : PP=26.90 - PSOE=21.00 - UP=18.50 - CS=17.80 - Resto=15.80\n",
      "51 - CIS 2015-10-12 00:00:00 - s=2.00 : PP=29.10 - PSOE=25.30 - UP=15.50 - CS=14.70 - Resto=15.40\n",
      "52 - Invymark 2015-10-05 00:00:00 - s=2.89 : PP=27.60 - PSOE=24.60 - UP=18.10 - CS=17.20 - Resto=12.50\n",
      "53 - Metroscopia 2015-10-01 00:00:00 - s=2.36 : PP=23.40 - PSOE=23.50 - UP=19.70 - CS=21.50 - Resto=11.90\n",
      "54 - TNS Demoscopia 2015-10-05 00:00:00 - s=3.16 : PP=27.00 - PSOE=21.90 - UP=19.30 - CS=16.50 - Resto=15.30\n",
      "55 - NC Report 2015-10-02 00:00:00 - s=3.33 : PP=33.80 - PSOE=24.80 - UP=15.40 - CS=11.70 - Resto=14.30\n",
      "56 - Encuestamos 2015-09-23 00:00:00 - s=2.50 : PP=26.20 - PSOE=26.10 - UP=24.00 - CS=11.00 - Resto=12.70\n",
      "57 - TNS Demoscopia 2015-09-14 00:00:00 - s=3.10 : PP=29.00 - PSOE=22.00 - UP=20.70 - CS=13.20 - Resto=15.10\n",
      "58 - Metroscopia 2015-09-11 00:00:00 - s=2.36 : PP=23.40 - PSOE=24.60 - UP=23.60 - CS=16.10 - Resto=12.30\n",
      "59 - Demoscopia Servicios 2015-09-11 00:00:00 - s=2.36 : PP=31.70 - PSOE=25.60 - UP=22.10 - CS=10.50 - Resto=10.10\n",
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      "71 - TNS Demoscopia 2015-08-03 00:00:00 - s=3.05 : PP=25.70 - PSOE=22.90 - UP=21.90 - CS=13.60 - Resto=15.90\n",
      "72 - TNS Demoscopia 2015-07-23 00:00:00 - s=2.36 : PP=28.80 - PSOE=24.20 - UP=24.50 - CS=11.10 - Resto=11.40\n",
      "73 - TNS Demoscopia 2015-07-27 00:00:00 - s=3.16 : PP=26.80 - PSOE=23.00 - UP=21.60 - CS=13.70 - Resto=14.90\n",
      "74 - Metroscopia 2015-07-22 00:00:00 - s=3.16 : PP=23.10 - PSOE=23.50 - UP=23.70 - CS=16.00 - Resto=13.70\n",
      "75 - Metroscopia 2015-07-24 00:00:00 - s=2.36 : PP=30.50 - PSOE=25.10 - UP=22.60 - CS=10.60 - Resto=11.20\n",
      "76 - TNS Demoscopia 2015-07-20 00:00:00 - s=3.28 : PP=27.10 - PSOE=22.60 - UP=21.50 - CS=13.50 - Resto=15.30\n",
      "77 - TNS Demoscopia 2015-07-13 00:00:00 - s=3.16 : PP=26.10 - PSOE=22.20 - UP=21.90 - CS=13.60 - Resto=16.20\n",
      "78 - GAD3 2015-07-08 00:00:00 - s=3.16 : PP=29.10 - PSOE=25.50 - UP=18.60 - CS=12.10 - Resto=14.70\n",
      "79 - Invymark 2015-07-06 00:00:00 - s=2.89 : PP=27.70 - PSOE=23.30 - UP=23.90 - CS=11.50 - Resto=13.60\n",
      "80 - Encuestamos 2015-07-20 00:00:00 - s=2.58 : PP=26.00 - PSOE=25.40 - UP=25.20 - CS=9.20 - Resto=14.20\n",
      "81 - CIS 2015-07-09 00:00:00 - s=2.01 : PP=28.20 - PSOE=24.90 - UP=19.40 - CS=11.10 - Resto=16.40\n",
      "82 - Simple Lógica 2015-07-09 00:00:00 - s=3.10 : PP=26.20 - PSOE=23.10 - UP=20.30 - CS=18.40 - Resto=12.00\n",
      "83 - Simple Lógica 2015-07-07 00:00:00 - s=3.02 : PP=30.70 - PSOE=27.40 - UP=18.10 - CS=10.20 - Resto=13.60\n",
      "84 - Metroscopia 2015-07-02 00:00:00 - s=3.16 : PP=23.00 - PSOE=22.50 - UP=25.50 - CS=15.00 - Resto=14.00\n",
      "85 - NC Report 2015-06-27 00:00:00 - s=3.33 : PP=31.20 - PSOE=24.40 - UP=16.90 - CS=11.60 - Resto=15.90\n",
      "86 - Invymark 2015-06-22 00:00:00 - s=2.89 : PP=25.90 - PSOE=23.00 - UP=24.90 - CS=13.20 - Resto=13.00\n",
      "87 - Encuestamos 2015-06-20 00:00:00 - s=2.63 : PP=25.70 - PSOE=25.20 - UP=25.70 - CS=9.80 - Resto=13.60\n",
      "88 - Encuestamos 2015-06-26 00:00:00 - s=2.36 : PP=29.20 - PSOE=24.40 - UP=23.00 - CS=11.80 - Resto=11.60\n",
      "89 - Encuestamos 2015-06-17 00:00:00 - s=2.36 : PP=27.00 - PSOE=26.10 - UP=24.30 - CS=10.30 - Resto=12.30\n",
      "90 - TNS Demoscopia 2015-06-15 00:00:00 - s=3.16 : PP=23.80 - PSOE=22.10 - UP=23.60 - CS=15.50 - Resto=15.00\n",
      "91 - NC Report 2015-06-06 00:00:00 - s=3.33 : PP=29.70 - PSOE=24.20 - UP=17.00 - CS=11.60 - Resto=17.50\n",
      "92 - NC Report 2015-06-05 00:00:00 - s=3.02 : PP=29.60 - PSOE=26.80 - UP=17.60 - CS=10.30 - Resto=15.70\n",
      "93 - Metroscopia 2015-06-02 00:00:00 - s=2.24 : PP=24.50 - PSOE=23.00 - UP=25.60 - CS=13.00 - Resto=13.90\n",
      "94 - Invymark 2015-05-25 00:00:00 - s=2.89 : PP=25.40 - PSOE=22.00 - UP=24.40 - CS=15.20 - Resto=13.00\n",
      "95 - Encuestamos 2015-05-15 00:00:00 - s=3.16 : PP=23.00 - PSOE=24.30 - UP=25.50 - CS=14.90 - Resto=12.30\n",
      "96 - Encuestamos 2015-05-08 00:00:00 - s=3.02 : PP=28.70 - PSOE=26.20 - UP=17.80 - CS=12.00 - Resto=15.30\n",
      "97 - Encuestamos 2015-04-28 00:00:00 - s=3.16 : PP=22.90 - PSOE=24.00 - UP=25.70 - CS=15.80 - Resto=11.60\n",
      "98 - NC Report 2015-04-20 00:00:00 - s=3.33 : PP=28.60 - PSOE=23.80 - UP=19.70 - CS=12.00 - Resto=15.90\n",
      "99 - NC Report 2015-04-22 00:00:00 - s=3.16 : PP=22.00 - PSOE=21.00 - UP=21.00 - CS=19.40 - Resto=16.60\n",
      "100 - CIS 2015-04-12 00:00:00 - s=2.01 : PP=25.60 - PSOE=24.30 - UP=21.30 - CS=13.80 - Resto=15.00\n",
      "101 - GESOP 2015-04-13 00:00:00 - s=3.16 : PP=23.50 - PSOE=19.10 - UP=23.80 - CS=17.70 - Resto=15.90\n",
      "102 - Simple Lógica 2015-04-13 00:00:00 - s=3.07 : PP=21.30 - PSOE=21.10 - UP=25.40 - CS=20.80 - Resto=11.40\n",
      "103 - Simple Lógica 2015-04-09 00:00:00 - s=3.00 : PP=26.60 - PSOE=19.70 - UP=25.30 - CS=16.60 - Resto=11.80\n",
      "104 - Metroscopia 2015-04-09 00:00:00 - s=3.16 : PP=20.80 - PSOE=21.90 - UP=27.10 - CS=19.40 - Resto=10.80\n",
      "105 - Metroscopia 2015-04-07 00:00:00 - s=3.02 : PP=29.50 - PSOE=26.60 - UP=17.90 - CS=12.10 - Resto=13.90\n",
      "106 - NC Report 2015-04-02 00:00:00 - s=3.33 : PP=29.70 - PSOE=23.50 - UP=20.10 - CS=10.50 - Resto=16.20\n",
      "107 - Encuestamos 2015-03-26 00:00:00 - s=3.33 : PP=23.70 - PSOE=23.60 - UP=25.50 - CS=14.70 - Resto=12.50\n",
      "108 - Invymark 2015-03-23 00:00:00 - s=3.00 : PP=26.40 - PSOE=20.30 - UP=23.80 - CS=14.80 - Resto=14.70\n",
      "109 - Simple Lógica 2015-03-13 00:00:00 - s=3.07 : PP=23.00 - PSOE=18.70 - UP=26.10 - CS=19.70 - Resto=12.50\n",
      "110 - Simple Lógica 2015-03-09 00:00:00 - s=3.16 : PP=22.00 - PSOE=19.10 - UP=26.30 - CS=18.80 - Resto=13.80\n",
      "111 - Simple Lógica 2015-03-06 00:00:00 - s=3.02 : PP=30.90 - PSOE=26.40 - UP=17.10 - CS=11.70 - Resto=13.90\n",
      "112 - Metroscopia 2015-03-04 00:00:00 - s=3.16 : PP=18.60 - PSOE=20.20 - UP=28.10 - CS=18.40 - Resto=14.70\n",
      "113 - Invymark 2015-02-26 00:00:00 - s=3.00 : PP=27.80 - PSOE=21.50 - UP=27.40 - CS=6.40 - Resto=16.90\n",
      "114 - NC Report 2015-02-14 00:00:00 - s=3.00 : PP=29.30 - PSOE=22.80 - UP=28.00 - CS=3.30 - Resto=16.60\n",
      "115 - NC Report 2015-02-12 00:00:00 - s=2.36 : PP=29.60 - PSOE=20.10 - UP=28.70 - CS=7.30 - Resto=14.30\n",
      "116 - NC Report 2015-02-11 00:00:00 - s=3.16 : PP=22.50 - PSOE=19.50 - UP=27.60 - CS=13.40 - Resto=17.00\n",
      "117 - Simple Lógica 2015-02-09 00:00:00 - s=3.07 : PP=26.80 - PSOE=17.80 - UP=33.00 - CS=8.50 - Resto=13.90\n",
      "118 - Simple Lógica 2015-02-06 00:00:00 - s=3.02 : PP=31.90 - PSOE=24.40 - UP=22.80 - CS=6.20 - Resto=14.70\n",
      "119 - Metroscopia 2015-02-04 00:00:00 - s=3.16 : PP=20.90 - PSOE=18.30 - UP=34.20 - CS=12.20 - Resto=14.40\n",
      "120 - Invymark 2015-02-02 00:00:00 - s=3.00 : PP=26.10 - PSOE=20.10 - UP=30.30 - CS=3.80 - Resto=19.70\n",
      "121 - CIS 2015-01-12 00:00:00 - s=2.00 : PP=27.30 - PSOE=22.20 - UP=29.10 - CS=3.10 - Resto=18.30\n",
      "122 - Sigma Dos 2015-01-19 00:00:00 - s=3.16 : PP=27.10 - PSOE=21.40 - UP=31.10 - CS=5.00 - Resto=15.40\n",
      "123 - GAD3 2015-01-16 00:00:00 - s=3.16 : PP=29.30 - PSOE=19.20 - UP=24.80 - CS=6.30 - Resto=20.40\n",
      "124 - Sigma Dos 2015-01-14 00:00:00 - s=2.36 : PP=29.40 - PSOE=19.40 - UP=30.90 - CS=4.60 - Resto=15.70\n",
      "125 - Simple Lógica 2015-01-14 00:00:00 - s=3.12 : PP=24.50 - PSOE=18.60 - UP=35.40 - CS=5.80 - Resto=15.70\n",
      "126 - Metroscopia 2015-01-08 00:00:00 - s=3.16 : PP=19.20 - PSOE=23.50 - UP=33.50 - CS=8.10 - Resto=15.70\n",
      "127 - Metroscopia 2015-01-06 00:00:00 - s=3.16 : PP=24.60 - PSOE=19.00 - UP=31.20 - CS=5.00 - Resto=20.20\n",
      "128 - GESOP 2014-12-15 00:00:00 - s=3.00 : PP=26.10 - PSOE=19.80 - UP=29.70 - CS=3.80 - Resto=20.60\n",
      "129 - DYM 2014-12-13 00:00:00 - s=3.00 : PP=26.10 - PSOE=16.70 - UP=35.20 - CS=4.20 - Resto=17.80\n",
      "Número de sondeos incluidos : 130 de 120 posibles\n"
     ]
    }
   ],
   "source": [
    "wb = openpyxl.load_workbook(\"data/sondeos.xlsx\")\n",
    "ws = wb.active\n",
    "\n",
    "empresas = ['GAD3', 'Encuestamos', 'GESOP', 'Metroscopia', 'Celeste-Tel','Demoscopia Servicios', 'Simple Lógica', 'CIS', \n",
    "            'TNS Demoscopia', 'Invymark', 'NC Report', 'El Espanol', 'DYM', 'Sondaxe', 'Sigma Dos', 'Resultados de las elecciones']\n",
    "\n",
    "empresaSondeoAll = []\n",
    "sondeosAll = []\n",
    "dateAll = []\n",
    "sigmaAll = []\n",
    "\n",
    "wbnew = openpyxl.Workbook()\n",
    "\n",
    "# grab the active worksheet\n",
    "wsnew = wbnew.active\n",
    "wsnew.append(['Encuestador','Fecha','Muestra','PP','PSOE','PODEMOS','Cs','IU'])\n",
    "\n",
    "otrosPartidos = ['F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'R']\n",
    "\n",
    "nSondeos = 302\n",
    "loopSondeos = 0\n",
    "for i in range(130):\n",
    "    empresa = ws['A{0}'.format(i+2)].value\n",
    "    for (loop, emp) in enumerate(empresas):\n",
    "        if (empresa.find(emp) != -1):\n",
    "            empresaSondeo = loop\n",
    "\n",
    "    if (empresaSondeo == len(empresas)-1):\n",
    "        sigma = 0.0001\n",
    "    else:\n",
    "        sigma = getSigma(empresa)\n",
    "        \n",
    "    PP = getPercentage(ws['C{0}'.format(i+2)].value)\n",
    "    PSOE = getPercentage(ws['D{0}'.format(i+2)].value)\n",
    "    IU = getPercentage(ws['E{0}'.format(i+2)].value)\n",
    "    PODEMOS = getPercentage(ws['P{0}'.format(i+2)].value)\n",
    "    CS = getPercentage(ws['Q{0}'.format(i+2)].value)\n",
    "\n",
    "    total = PP + PSOE + IU + PODEMOS + CS\n",
    "    otros = 1.0 - total    \n",
    "\n",
    "    tmp = ws['B{0}'.format(i+2)].value\n",
    "    if (isinstance(tmp, datetime.date)):\n",
    "        date = tmp\n",
    "    else:\n",
    "        date = dateutil.parser.parse(toenglish(ws['B{0}'.format(i+2)].value.split('-')[-1].lower()))    \n",
    "\n",
    "    tmp = date.year + (date.month-1.0) / 12.0\n",
    "\n",
    "    sondeo = [PP, PSOE, IU+PODEMOS, CS, otros]\n",
    "    \n",
    "    if (0 not in sondeo):\n",
    "        \n",
    "        loopSondeos += 1\n",
    "\n",
    "        sondeosAll.append(sondeo)\n",
    "        sigmaAll.append(sigma)\n",
    "    \n",
    "        dateAll.append(date)\n",
    "        empresaSondeoAll.append(empresaSondeo+1)\n",
    "\n",
    "        print (\"{0} - {1} {7} - s={8:4.2f} : PP={2:4.2f} - PSOE={3:4.2f} - UP={4:4.2f} - CS={5:4.2f} - Resto={6:4.2f}\".format(i, \n",
    "            empresas[empresaSondeo], PP*100, PSOE*100, (IU+PODEMOS)*100, CS*100, otros*100, date, sigma*100))\n",
    "        \n",
    "        wsnew.append([empresas[empresaSondeo],'{0}/{1}/{2}'.format(date.day,date.month,date.year-2000),1.0/sigma**2,PP*100,PSOE*100,(IU+PODEMOS)*100,CS*100,0.0])       \n",
    "        \n",
    "wbnew.save('new.xlsx')\n",
    "sondeosAll = np.array(sondeosAll)\n",
    "\n",
    "nSondeos, nPartidos = sondeosAll.shape\n",
    "nEmpresas = len(empresas)\n",
    "\n",
    "print (\"Número de sondeos incluidos : {0} de {1} posibles\".format(loopSondeos,120))\n",
    "\n",
    "# Compute week of every poll\n",
    "weekAll = []\n",
    "for i in range(nSondeos):\n",
    "    weekAll.append(weeksDifference(dateAll[nSondeos-1], dateAll[i]) + 1)\n",
    "\n",
    "nDates = max(weekAll)\n",
    "\n",
    "# Reverse all lists\n",
    "sondeosAll = sondeosAll[::-1]\n",
    "empresaSondeoAll.reverse()\n",
    "weekAll.reverse()\n",
    "sigmaAll.reverse()\n",
    "\n",
    "dictionary = {'NPartidos': nPartidos, 'NSondeos': nSondeos, 'NEmpresas': nEmpresas-1, 'NDates': nDates, 'empresa': empresaSondeoAll, 'sondeos': sondeosAll, \n",
    "'date': weekAll, 'sigmaSondeo': sigmaAll, 'alpha': np.ones(nPartidos)*1.0}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Leemos el modelo que hemos definido y hacemos el sampling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date.year-2000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "f = open('model.stan', 'r')\n",
    "model = f.read()\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using cached StanModel\n"
     ]
    }
   ],
   "source": [
    "out = stan_cache(model, model_name='elecciones', data=dictionary, chains=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Resultados\n",
    "Extraemos algunas de las cantidades interesantes para hacer algunas representaciones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "thetaChain = out.extract('theta')['theta']\n",
    "theta = np.percentile(thetaChain, [50.0, 50.0-68/2.0, 50.0+68/2], axis=0)\n",
    "houseChain = out.extract('house')['house']\n",
    "house = np.percentile(houseChain, [50.0, 50.0-68/2.0, 50.0+68/2], axis=0)\n",
    "sigmaChain = out.extract('sigma')['sigma']\n",
    "sigma = np.percentile(sigmaChain, [50.0, 50.0-68/2.0, 50.0+68/2], axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sondeos y variación subyacente\n",
    "En esta representación vemos la variación de las estimaciones de voto en puntos para cada una de las encuestas que hemos considerado y la estimación subyacente que hemos inferido. Como se ve, la varianza de la estimación subyacente cambia con el tiempo, siendo muy pequeña en la fecha de las elecciones, marcada con una línea vertical."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "            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",
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       "\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": {
      "text/html": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colors = [\"blue\", \"red\", \"violet\", \"orange\", \"yellow\"]\n",
    "labelsPartidos = ['PP', 'PSOE', 'PODEMOS+IU', 'Cs', 'Otros']\n",
    "labelsEmpresas = ['GAD3', 'Encuest', 'GESOP', 'Metroscopia', 'Celeste',' Demosc. S.', 'S. Lógica', 'CIS', 'TNS Demos.', \n",
    "                  'Invymark', 'NC Rep.', 'Netquest']\n",
    "f, ax = pl.subplots(figsize=(13,8))\n",
    "for i in range(5):\n",
    "    ax.plot(weekAll, sondeosAll[:,i], '.', color=sns.xkcd_rgb[colors[i]], linewidth=2)\n",
    "    ax.plot(np.arange(max(weekAll))+1, theta[0,:,i], color=sns.xkcd_rgb[colors[i]], linewidth=2)\n",
    "    ax.fill_between(np.arange(max(weekAll))+1, theta[1,:,i], theta[2,:,i], color=sns.xkcd_rgb[colors[i]], alpha=0.3)\n",
    "ax.set_xlabel('Semana')\n",
    "ax.set_ylabel('Fracción de votos')\n",
    "ax.axvline(49)\n",
    "pl.savefig(\"sondeos.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Estimación de voto actual\n",
    "A continuación pongo la estimación de voto actual y sus intervalos de confianza."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "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": {
      "text/html": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = pl.subplots()\n",
    "sns.boxplot(data=thetaChain[:,-1,:], ax=ax)\n",
    "ax.set_xticks(np.arange(5))\n",
    "ax.set_xticklabels(labelsPartidos, rotation=90)\n",
    "boxes = ax.artists\n",
    "for (i, box) in enumerate(boxes):\n",
    "    box.set_facecolor(sns.xkcd_rgb[colors[i]])\n",
    "pl.savefig(\"estimacionActual.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A continuación represento la evolución temporal del voto por cada partido político, incluyendo las incertidumbres estimadas para cada sondeo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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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PgBSzLnTZ5G7fZZN6WLNb7HP30LoCrExZTMJ9J3q6uqjDMO4FoAfwCuWZV0WCAQe5EmouOWjurp6T9M0efZK3tZCr9d7Js+U269fv84NDQ2PGoaxBYAwz3hpWdaHmfqjAUgmCeX2dw1A3IOuXCRerAOtUACEy6IYZ4IGILmsQrV3i7lWtXKlNke5lCrkmVCsc0EDkFxWROZ39ZmQWUb5KlFMWbdYAJIv4arW0x4BSHNafNIBEBVXJZUy6ea6GJuM9vmtmzriwKtWxLqYjQua6jp2yhVjvM5tSqEOFbcyyLU8PxM0AMlVipnfL+Za1QAk8/zkWqLQACTX/rl9n58LGoC4lZq78vpMcCevXEoXU9aF0hVytoDkItBs3tUAxD0vw5GzCjjQAEQDkGz2ZTHf0QCkeaRfzB9ADUAKP8dtHYBsf6cXX40IxwRZKA6I3iOFX6fOBVp7OhOKPWYNQOx1rQGIBiD5PuK0BSTfEm3e+jQAaR55a+Wq7cu5UIpG80gusRV+LsyevAwzhjTE/mD6gajgoGsAkqcJ0WdCngSpUE0xZV2oc0FbQFr4xHOUny8XLG0BST3ZGoAobIIWXEQDkOaZnGL+ALan285iyrlQikbzrNCmAGTGDUsx+3Zh9aCPtoDkZ0aKuVbb05mgLSD5Wa8516ItIMWzgHw7rwEHXS34EW/e2BH9e/uazCdV5p+7sgN235LHJlB/inGgtSUAogIyncOsrSgbGoCo769cShZjbxb7h7c9KTlt0QVLW0By2fGZ39VnQmYZ5atEMWVdKF2hXVhAVJUy2UIp5sS3JAuICgD5cGY9jhtbFxNliQ+YMqYKNT29ynuwGLJuyQDE7dpVLd+WlA0NQJS3V04Fi7E3NQDJacpcvdyWzgQ+8GQSuuaAuFoOSoX1maAkprwUKqasNQCxpzAbC4iqUtbaAIjbcamUT0dCVwEgE15ZjXHPromLctxpFRi6b6nyBizGJtMARHl6WmRBDUCaZ1qKsTc1AGmeuW1rVtFUAKQ5EhHqPdI867W9ybnY56AGIBqAxCRAQ8OqAAp6HKiUzxWAfPRjPY4d02gBmTqmCsFWZAF5fGQlhty6MiY2mZtZPo/YTAepypy5neO2pmxoAJLPFSmvK9NaLVQvdLuFkmxivW3dAqIBSP7Xkd6b+ZdpS7wI1wBEA5BWAUBaIweEWnbuOrscF92/WgOQ5jtXc25JA5CcRahUgVY2lMSUc6FiyrlQikbOQsmiAp0HJAuhuXylmGu1PfGztAXE5cIsVHHtgtVIQi/E7XiuFhC3fUpeJ8U40DQAKdRubZ56NQBpHjkXY28W+4e3PSk57ckCsuvjPnTdxZP3jaP3SN5FmrLC9ibnYp+DhbqY0CR0hf1S7MUuC8PrVtlXKa8BiLaAKGyJFlVEA5DmmY5in4PNne2+PY63UIpG86zQxFbSkdDNEmDgy350DJh57Vp7XDPtDaQXY7wagOR1m2ZfWXNYQJIV9Y3X96BQiy4dKHAOs0IAEM5vcELqyngl39zbCd06N94SqZDQVUBOutkvxgGuLSDZ78eW8KYGIM0zC8XYm8X+4S3Uud/SzkBHzm0ZgFSf4UHtg5G46Le53ovNT1SP0Kiyy/QeUZFS7mXam5yLfQ4W6lzQFpAUe6G1AxAZCKDfawDSOPGtEYCozDEFlsnLvC25W2gAkvsPukoN7e1Hvz2Ot1CKhsr6yncZbQHJt0Sb1tce90gxLiU0ACn8WlZqQVtAMnNAVJRTDUA0AGkryoYGIEpHZ86FtLKRswiVKiimnNvKmcAFnY6ErjkgSksxY6FirtViAIFijVcDkIxLsXkKtDUAks6tKVsXLA1A3K3FlmwBka0PlTnWFhB368Bt6WL9GOl23c5UduXbo5zbCwDZ/6MSlHXLvwNIe1wz7QkIFGt+NQDJ7gzP+1vNDUCopSCZE5GPwWkAkijFYmxwDUDysZKLV4e2gDSP7IuxN4v9w9velCsNQHLbS3qP5CY/1bfbm5yLfQ4W6lzI/xWA6grKslwyAJG5EtHq3RKjZVyJ9gZAnr+yA3bb0h8XpSahZ7lo07yW6SDVFpDMMtcAJLOM8lEi01rNRxup6tDtFkqyTS9/CqVoNM8IElvReUAKL3W9NwsvY6eFYsq6UOdCqwcgE8+rwPB7VsXmSOZy0lYBSC7KqQy4fTizHseNFZnMS33AW2OqUGNnMtcAJP+HTaZDJZc51i5Y+Z8vWmOmuStU67rdQkm2qUKuLSDNI+tCtKIBSCGkqvdIMc4ELvVinvsagNjrnh8qL72/BMeOEUpyiQ9Y1yD+qAGILyYHFX6ADIBMeGU1xj27Jn7KjDutAkP3LY39P1WGH7+0EkNuW9lE7m7BXvIRWYxNpl2wCv9DVcgWtAWkkNJtrLsYe7PYP7zFUDaKKedCKRrNs0ITW9EApPBSL+ZabU97s9jnYKHOhVZpAbn6wT9xM1GSnW3Gler+vYUSTh+3SrGKC5bbOmVHQS4ckFxux2UA5KMf6+PgjltApoypQjCFBeTCwSWYMHmdBiA5nvGZDnDZHLud+1RAr1CHSo4icf26BiCuRZbVC5nWalaVKryk21UQUh6KcDm3lTOBi0MDkDwsigxV6L1ZeBk7LRRT1oU6F1olAHn5/SU4xraA+L1AfVhMUUsAIG6BSUsDILT/yRyQe19djZuebrSOOBtDlsgwnQuQbNsWY5O1RguIBiCNK0gDkOb5ESzG3iz2zV97umXVACT3faT3SO4yVKmhvcm52OegBiD2qkwmoY89pQxX/EcoxRqAqLtgybgzFIAkk+4Pv345Pp9roz1ySrRVAMJldPiuwv2sUE+mg/Ttr9fFXd2429u+25XEuiL7XhUAtyVlQwOQQq3OxHozrdVC9UK3WyjJNp3fQikazTOCxFa0BaTwUtd7s/AydloopqwLdS60SgvID6FlGHDusti8UC5CWwUgb3/2Dw68akVsvFQpdnsLTgnmMu4MrfOtmzpig04mtjtPyPq0/fx4ZFp9kx3nFoCkU5KLscnomEcfW4rxz62NjZHLiLugOST8Qhw1mcarAUhmqWsAkllG+SiRaa3mo41Udeh2CyVZDUDyLVm9VvMt0dT1tTc5cykUc8wagNjrMNkC0h4AyIOT/8Lwf4tIX1QpdgtAkgnmztamACIdALnrrHJcNGl1EzCSLwAis76o3upne/TRMR+9uw8vfGRHNQBASfjZ1p/uvUyHigYgmaWuAUhmGeWjRKa1mo82NABpm4pGodZGunq1BaTwUtdnQuFl7LRQTFlrAJInAPLclR2wO8ltkWr55EJCd6ssq3BALpzwB+59TdzK88dRit0SlCnBPBsLCAUg9HNbAiDJFpCphIRfiKMm06GiAUhmqWsAkllG+SiRaa3mow0NQDQAydc6ygaArPmdYeruIrhKNtnS9R7J1+ylr6e9yZlLo5hj1gAkBwCS7HqUya2mpQGQhyb/hbOJBcRRit0CEDouGQdE1QLiFoDIZJrO+rLtFuqclmwI784RJ3PBau0ckHRgW3NAcv+hLOYPQnsjR+vx5r5eM9XQls4EPtbki4ml30fxwVHChXjPF/1YbxuziUg0AMm0ShL/rs9Ad/LKpXQxZa0BSA4AJF1ui1QLoqUBEBUOiFtuiCwMb0sHINTlTpaLxO0mf3nGWpxjJ7P0eYGGDFHV3NafrnymQ4VaQHjAhVP3L49VJ7OMqILttqRsaAtIPlekvK5Ma7VQvdDtFkqyTZXJQikazTOCxFaSz4U/3ovgszOFe+2/HvBho709GoDkODF6b+YoQBevF1PWhToX2iwJXXbbz12PMrnVtGQAQon2VHGWcUMoMMnGCkFJ6Lm4YGXTdioLSCEAyGUPr8Rj7wizO31kQQ1cnBkZi2Y6VB6dshpXPCaivPGQ01PHClK8DICogm0NQDJOTcYCmeYuYwVZFtDtZik4l6+1RzkXStFwKfq8FE8GIL+8GMa3o8XtUv/xXmx6lFcDkBwl3R73SDGssXyaiinrQp0LOQOQYDB4DIBrGWM+wzCeDIVCN9I1HQwG9wZwG2OMXzf8FA6Hh86fP3/5wIEDvYsWLbrfMIydGWNRAKdblvVFpv2gSkKXKbytkQNCLSBUKb7pv6tSckNkwCQbENAeAMijU1fHQzl7PUA4IlZhcwIQGtmNupMlgyOH/yMDIMk8HxnYLiQAKcaZ8PffdWAs0+mR378X8wchnz+CbNFvCG/bJyYc73dzYHTfOKWg2sp4VVdBexxvoRQNLvNinwsagKiufPVy7XGP5PPsVZe0BiBNZNWrV68NvV7v5z6fb8CsWbOWB4PBKdFo9Jba2tq37cJmMBj82TTNfebMmWMFAoGbDcOIhEKhq2pqai6MRqNbWZY1LBAI8F+/VyzL4v/lYET65ApAVLgCrcUCQhVnfjs+bazIWi4DJs0BQOjEydpTdf9qLgsIVebPOcSP+14XfsItAYDQOabuYdQaRfODUJkXgwNSrDNBAxA3P2WJZTUASS279qhcFQqAtIRzQQOQ7M8I2ZvtcY9oAJK/dZSTBSQYDJ7EGNvLsqzT7RuOkxlje3JQQbrILR+Rfv36+RsaGh4yDOO7UCh0RyAQeAfA9ZZlfcTL8v83DOO6UCj0sQYgQgLO5pZZQGT8ABkwaQsAJBc3MNm6onK87qRSXPekiDjWnCR0mQWE9m30MaUY/7zomwoASQe2C2UBKdaZoAFI4+pWBRTOG6rltbKRvx/edDUVU86FAiAt4VyQARBKPOfkdIeorqNgZV7vxVyrxQACxRov1Qeb+7euULpCbEyZl5i8RDAYHM0Yq7As6xobgAxijI20LOsA+lYgENjGMIxpANYxxna2LOu3QCAwB8DBlmXNtwHIEwDesCzrGQ1A1ADIs9PXxPNycIX0uIFlsRdlwETFLS3BtWdkJfpt6o0nIlRR/uncFcICotIHt6GQ6ZiHH+LHRNsC0pyJCFUAiGzsMgtIkQBIUc6E5j6Ui/2DkO7HVxVQaACS/tevWMpGMdstIAAp+rlQaABCgcwBH5egdKOc1CtXqlkx10x7AgLFknOxf28KdS7ktEMCgcDlAMqSAMgllmUdlGr3VFdXn20YxsmWZe0aCARCAA6kAMQwjNdCodBzmQDITGsZ+p9jZ0IfWYkht66MvcIzd/fv3Ri61cmWzr93Mol/c28ndO/SNPpFsuKc6t1v7+uEbp3Fu1zJdcrQOmXfy8bEo045faP9dxZcly4d8M7n/+CAK0UmdFrmGQ5A7heJAe86uxzH2wBk2tfr4jJ5fGQl9tuupEmfJ55fEU9uyN236u3IT9QC8MQoAUCccfI2aHvOZ5lM6djou7xPdM6c8dPvp4zpCOqC5aYP6WSaah6ovA7e0Ys3vrCFYedcOWW/Ulc/Bm4K8wONzzFd01SetG8y+cvmON1aFwdpx5z2f6pxFutMWLKkOBwQPnfN3bazZmTtcgDSsI3gdPi+l3M6KABRKZ+qXbdtudkbTtlM482mTpV32mO7hTgTuKxbwrnw8wuJJPTNjhYkdA4cpuwmgpAMfMmP6UcKF1wOIsq6qR+RtJ4DZpSgrJkBSEs8i1T2WTZlirE3izm/VB+UnfsJ/XO5dtPNQaF0hdiYspl8551gMJjgcsXNrAD2CIVCZ/Iy3bt3L6+oqNi7trb2def/Kysr/7Asq2MgEHjXMIxrQqHQDPuAesc0zWvmzp37Sbo+cQ7Iwr/C2OyEhbFik2/sisFX/xX7/Ok9G2GHGqEs0jL8+53P+yP2/c9P90CPrk2jX9A26btPXdkFJ45Z0uRdWobWKfteNqYv566N9423ddxeHZoUpWXoGB+bsgKn3/ZPrPzDl3bG0AM6xj6/8emquEz4904ZKoeRx3XErc8KUEOfW8/qhJGTBLjjst2md0lc1rQu+lkmU9pvWj55zpy5UZlLlT7Q8fM6D965Iu0yp+UvOaYDbn++LlaeW0C+mNgd/Tbzp30/H3+UrRvZXCbL0xmjm/VnGPxoye9TrDMhv6No3bVFFgq0NsIAACAASURBVC7Enz17xgax4YIF8PTokXZAbsvTynJ5t3VLuW32vhBnApdUSzgXfpmyDtOOE795+z3bEZseIC7mVv4WwdN9xe/o4Pc6YfLe4vfvhNmdUblx+stKugpoPW7fbZurqW2NqqXPbyH7V6hzIScFpE+fPt0ikcgMxthOVVVVy+rq6jjQuC8UCk3mS2/77bf31dXVLYhEIoPmzZs3KxgMcq7IEaFQ6JBgMHgxY6wv54sEg8EaxthbHTt2DHz11VciULfk4QCE3hbTW+Gxp5bhNDtPArVEuLWA8FwKx45pVELX2T164aoO2M3Oop4vCwiPWDXcTjLIScbTbq5Cn54CIDkoPxcLCJUPlcP951fEkxu2FAsI7Su3vuw7oKnlRmYFoGOjVhxqGZKtKWpluP7kUlz7hOBZcBkdvmvhrB90jtuKBaRYZ0JzWyHo3BWi7XSWhUy3f26tEqrltQWkeRSqTPNbqF4U8qazJZwLv7+bmAek2yABLrQFJPsVVcy12twWH20ByX6dyN7MCYDwSqurq48yDONanqbAjmR1WSAQeJAxNplbPqqrq/c0TfMO29qy0Ov1njlr1qw/bFL6vU4YXtM0L5g7d+70TENMjoJFibk0T4IK4VrWVnIuBadcqQ94a4zIwyDjGbjlH4y4vw7PfCBMvvy56IhSjD5W3NhnIqGrcEAob4BGn6KfeYK7K/4jck1cd2IprntKKODctScXDghNapiOvzDkNuFCl0CsHpkIQLY7T9xKyeqh46FjoNwY2XzLSOgtIQpWayOhF+tMaG4OCOVZcDcndEsdujbTeSb7ezoeRyY/5ObkgLhtKxt5ZBpvNnWqvNMe2y2Ur3dLOBdkiQjzRULXHBCVXZWfMsXYm8WcX6oPyn7raP+yCaAgBQkGUKhzIWcAkp/lpF5LMgA5ejcfXvi40Wji5EnIBYDQXAoeE4iQwMCp6qdkX9cAZFIdnpneCEBGHFGGUceKbNepAAiNzJQvAEKT+7UFADLiiBLc+bLw6eXjOeuQ9C5YLRmA0ESEsjC8NEO66vorZGQL9d2cn5LFyISuAYiYOw1A8rOGaS3FUK6c35tCKRr5l1LmGlUzoWsAklmW6ZTT9kJCX/p9NB4hjXOFOm1tZi+4LN7MdC5oAJKFUN2+kgxATtvPj0emNSrwj1xciQN3KEmwUMjyTtC2ZYDlwsElmDBZKLM0i3q+LCCvcBese1bF6ucK5tt2Lg9aP7VQ0MhMFIBwS9BFRwpFmyrUMgsIBR20TDoA4jYLucwCQq1Wsn4kkNYvrYRjJUm2blw0SZDwaT3DDvDjoSliTTQXAAlHWAwwckRvmuq43jlUaBQsul6TAbazZmWWv9/+jmD784W1qBhRsNzu53yUzwaA5Ko4awCiAUg+1m6qOjIpGoVsVwOQxjC8bkPyFvOGvJhrRgOQQu3IxHozzbEGIM0wD4WygMgACFVsOSdg8C6CE5AvAEKVdGrdoPUP3acEj70jQBB/HCvMDU/WYeIbQtGmGbxV3JTyCUBkCe/o2KjCTG/yZf0YfWwpxj9nu4K5BCAnDPTh6enCKsatIaOOrZSuTMYYJs9Yh+H3ChB4+C5evPKJiILFOUU91/egwc6MznGFaQIe04DHA/D/r28A1oUZIhGehlsAD35QcMsZnxOvx4DfA/j9Bkq8QKnfQIdyA1UVJrjLoM9rgB/gMgCSIDcP4n3Zb4AX075pjNY17IASDNzaj9+WRDD6YQHKNACRH0jNDUDctqddsBrnLtMPb6F+dtpjuxqAaADiZj+1pz2iLSBuVoZaWfWrWrX6Cl4qEwfEyQbu1gVLBYBwonOq7Ny5uGBRJZ1yDhIsIKeW4YpHBUeDWmGG3bEcb3zZqIQ6wqcAhCqw9GY9VwAydmgZrnissU9TbG4MXQB0bLKbfNrX4Qf744BKBlJkFhBazx79THw4S/jNcTByx1kiOhh/Vq6OYuGSKFavY1i9lmHlWoapX63DMx8IwMJBRZRjCQDXnliGXt3SR0zLZsFza0k4BmoYPB4Dndcrw6+LVsVDHN84tAxX27I968ASTHpLgM/DdvLi1c/FfO/T34t3vm2c+wsOK8V2AR/+qYtixCQBpjQAkc+OW0CQXJNbC4jb9loaAJGN1+24stkv7UnJ4fIp5ng1AGkEIP96wIfPzhS/C9wast426V1utAUkm92d3TvF2CMagGQ3V+neavUAhCqeMl/4XFywqKLuFoDILAMyJV0GQGh+DGolufHJOtyXwgIiszbkE4DIrDKyscn6ROfv4B28KQEVnYNkfodDmJcBkB0CJs44sAw//hLBz39E8eeyKCIRweuJMoaGMPDL4ghWCWNLwtOlg4GuVSaqKgx0LDfQscJARYmB0hIDZX6gvMRAhzLxr7LMcOV65TTED9IOHcvwy28cgAjgwIHP9U8JcMctGw9NEQCEft6lrxefzG4EIEP2KcGgbf0agCiekbkqzhqACNJ9rnJUma5iKBvFBgLFcmtpLwBk6+u86HVSYx6QqbuLM5a6XWkAknl3tqe9qQFI5vXgtkSrBCA0CkBC5u5LK7EvSbrnRE4qNAChQIOH8D1ubGMI31SWAbcAJJkP4Yxx0uur4hGrTh7kwxPvitsambWByuGBCytx5gQRfeqWYeUY9ZBw2xlxeAnufEUcxrcOK8emG3riIYkvPaoUt70oNPULDivB3a825cbIxiazylBgcs7B/jigkhGu9+3vwdvfCp8omTWkogRY1eix5nZPZFWeu1vxvH4csHAXK+5axV2vSvwGyv1AWYkAKRzIcPcrDmo4iOF8EVUActSuPrw4Q8xxsgVkyN5+VPfw4s+lUdzzmpgjbQGRT2WuirMGIBqAZHVQKLxUTKWuLQOQ+U+E8cP14tLG9AEDJ/vRMWDGwvC6ASAyX3sVC0gh/fSLBVrbS7sagCgcXi6LaABiC8ytC5YMaCSH8HX4GrJ5UXHBUgEg1DJw8VGluMMGCpQbcv7gEvzbJtQPHeTHY+8K/gj9fOp+fjxqk/qvPbEUa+oN3PK8uI2nEcG8JhC2o4Odd1gJ7rHByH8uqcSG63F+g4Gf/oxg2J1NQ+zKrCEUUFAOSHKgAUeWlx1TinHPC2W73yYmZv1KwpURgXOuxfpVZgwgdO5gopQr/ga3WCDGw+AWkK9rBajhP/7MdsE6dCdfDEisWM3Ev1Us5rq1pp7/Q8yFy3HXcrnvYsW5O916lQaqKj1g0Sis30T/dwp68HlI9KdPTxNzFojv+Wa1u5bA+ZG1Pf3WKgR7pHYha+9RsNoyAIl++zUi++8l9uzU92H23y7t8lSRRaFdsHJxOctm76m8U0wgUCylri0DkO+uqcfP/238jdjmei82P9HbIgBIrsAk1VrNtc62vkfcykcDEJUV4a6MBiBZAhAZ0KAhfClfo9AAZOi+fjz2tgAUR+/qwwv2TflBO3jxps0TGXFEKe58WSjsMtce+v1ZB/rx+1KGVz9LmxsywWXozrMqYko+f+YtasCN/xXtUWCz59ZefPBDU+7K8ENKMPF1YboYM7QUVz4m3q3e2EStrZxTOW62gYGfFzsqeeNfKOji3x63hx/7b+9HOAz4fRxkJC777/7XEJcLlVcmDgh34VqzDqhbw7BkRRR/LY9i8TIBUhrCDPVhYJ0DVtYxrFwjgEwuoCXT9qYcli/vrkKPrhqApJKZitKdTtYt2QKSLwBCx8iBjANqaN4TmRzdylcDkMbVVkzg05YByPwnw/jhupZpAXGrDCefTRqAZPplFH/PJeSyBiBqMnZTSgOQLAGIDGhQS0q+OCDUAnL3OeXYenNfTMl95v21eNy2Ygzc2oPpP4hb88H/8mGyDRqCPUyEFopbnz229OLDH8UBXNPTxFz7Zp27BXHFmD9UgVVdSFt0M/G/30Ubg3f2xywgHHz9syKKp94XoOio3Xx40c7XQl2JqFXlhIF+PG3nRDlsZy9e/VT0dbveJr6el9q64fSxohQpeRx8PO+Nr0Kghwd1qxn+WBrFqnUsFr0qHGZoiAJfhhpwx0sC7FD3tUwARFU+tBwHLRyILFvFsLSO/zeKCHxY/M86vPWlAHp9NzEx27bmbFBlYPFyMTfUAkJdsI7c1Ye9tvGjxGtg5dooLn5AR8HKNDduFeTk+ooFQFTa1QAk0+yr/b2YQEBbQNTmKF2pdHlAVDggvIwDWCgJXcUFi+eJmH6k+O2jSeFU3s0miZwGIGrrpT0CkHyA20JdTGgAYq9bty5YMqChkgiOlqEEa0pCp65ZZx9UgvvfFJaBcw8twY5BnnQeeGb6Grz1lVDSqeuQ2lYsXilqoSgvAVbbfI31KoGlwmPL9SMbP7doPHxxVdr6KI/ojjPL4wr881d2iBHMOZ+kbk0U6xoA7nrGQ+vm63FDQqfAjVqquGXLic6mo2CpzYwGII1yUrFimE8+h+hJx8Ze8k57H8a2wq1L5V3vd3NgdE+fKV5bQBrno5jAp1CKhtquzG+pbADI9nd68dWIRitJ1Db+qwAQekNOCeyFBiAy7kmuiqfKbBRzrWYD0jUAKUFZN3f6SyHdtd31RGVFFrhM8qGiQkLnkaOcZH8yYm4uAMRtGN50AGTbLbz4e3kU731fHw/LSvNanL5/CSrLTPz8RwTvfl+PlYKeIX023dDEL38K6wG1VGy9uQc//CQsJtQysseWHnz4o/ieWyeG7luCR6YKhHD+YSX4t831GDLIH7e+7N7Pi49miUN7k65mzDrD3Y/W1ov/5vOpLAVWpohYRdugVpzkMLyp+pKQuPHs8rjck9fKugaGxcujqLO5INySwnkgfIw+O+eH27G6ASAytzkNQBijgSlU5kADkEYpqYCIXAAIdd+SgRENQDQAUdm3bsok6woqJPTqMzyofdBO/EQa0wAkteQ1AHGzInMrm0nWhbSuFepios0CkGSSOL+95k9LBiDjTy+PRVGKRoEFf0XioVi3r/bgK5skrbKED9/Fh1c+EQOmSisN76rCBznnkBJUb+yN55Wg78s+Uw7I/N/D8TGcPMiPJ2x3sf2382Hq16J/O1R78KU9tsDGZpyITS0ah+/swyufivLbbWHi6//ZpGxCGKdWla02BWb+IiSVTwAikz0npXN3s+WrOSdEcEC4i9faBoYIJ3wwsc046Z0DFcpB0QBEZUWnL9MaMqG7BTwqoIByMaiEZC5YKnVSgEDLywCISluFACBu5ZnNKsv0g59NnSrvFLPdQikaKuPOd5nkc0GFhK4tIO5moZhrNVcLSL/LPZh1swCb/cd7selR6XN+tVYOSK6WMG0BIXtC1QLiNhpVc1pAfvs7gu3PXxYb1cVHlsb5Bw7nYNnKKN74oh7TvklN/ub8ip5dzVj27Z/+bMrdkN2UywDIKfv68R+bwD50Hz8ee0f4rl51Qik6lJvxzNqXH1eKm58V5ocrTyjFmKfFZ1qvDIBQ9yHOWXjJJsnLOCAyd6P9+nsxzU7AN/wgPya+KfpKQ/juFDDwuSXk0hwARHZk8yzrPIs6TzrI+SbcIsRBytp6gFtTeA6ScJShvKIM835dGbe8XH5sKW62s8BTSxOdG/r53ENKsFUvX4wjwtfO6Ec0ByTTz2iuCqwKF4P2wW17svJU4aeuUPkCIJ4XXoW5x8BYdRqAANkoOZnWXqa/F1Opa8sAhJLQDS+w16vpw/C65YAU2gVL5Yb7gI9LULqRuPDKVfHMtE7534u5VrPZm1QmgXNNWPeKy0wORqpP96UdsgYgKivCXZk2awFxG42q0ACkbnUUi/6JYlkdw7zfw7j0QTvvBolMxcO+cjL3nAWReChYPp2UJ8HdoAZU+2JhZCe9uSYhGZ0z9VQ5PW9wCe6xQ++OP608rpzeNLQMV9nZtq8/uRTXPiHAxKijS3HLC+IzT7y4QScTTj6Vl6/tiCOuXxH72xOjKnHyLYKwMemCCpx1t0ii99illehQZqI+wvDB9+vimc0p0NipxoPP5zY1cx+3pw/P2hnJ6Rho+OBhB/jx0JSmoIOG8G0pAERlKzoH+A+hZRhwrgCldw+vwAUThTxHHF6KO18R88Hzsoy087XcdkZ5fA09enElBm7jjwGdX/8KY9BoMUc6D4h8BtwCguSaWgIA8Tz1HCIn2rwMwrOgIMWc9Ag8Rxwd674U1Hz4PiJHDxZDLC2Fd+p0GH36thoAomJhUdmLyWVam3KVzRjpO4W86cy1b9m8n84FSwZAqAVElohQpti3BABCye80qaKM2O4WpCSXL+9utCqQ3hYAyIKZKzBlN+EWL+MX0blXWQfp9lchz4U2C0DcRqOSARCaQI9nJN93QElsrmRkc/r9y9d0iCWaW7oyGnPJ4TknuPsNJQrvtY0X73/flChBozqdvr8fD08VSjeNzPTqp2vjiemogj/u1DJc9qggh9D+yzKhy/Jy3H9+BXYI+uIAhL4v+0yV3pv+uwr32knx6AI/91A/7n1NjIe6Tl0wuAR322Dp5lPKcPl/mo7hyF29eGmGkBd9t7UDkJfeXxJP+EiTMMoSMtI544EMnOSUqj/UhTxUVPuQr3Jt0QVL5tqU8L0EgERefgHRs04T4i0pgXfaB00ABXW1itx1G6Jjb4hPhzn+DnhOHaYBiKEtIPnao8WoR9UFa/GMCD4ZKrwNTD8QFT9N0ACk6ay1JQCy+VADPz0mPCW4NaTvCBHcR/a0FAuIDIDIALBsHavuyULqCu0CgKS7CXYmIR8AhPv7f1MbxmHXiRvo288ox/pVnvg88xCs83+P4tM5DXjn26buVdy1aoeAF//q40OZj+FG28WJulRd/X+l6LG+F+WlBr4I1ccTC559kB/32+5IsqzjMgAiy5zO+/P4yA7xzO5uAcgrM9bGyf8qinRCZnNCBqfj2aWvB5/Mbmo9ae0A5OoH/8TNz6aPKDB2aBmusK1WVJ4agDD21w9z0bBNHwFMc4y6pHIw52IBUbmxzwWAhG+4Buyeu5oACmmdH05H5OjDRHluAeGApaaPawAis7bQ8crG7paELstRojL3KvPLy2gLiKqkWma5JhYQSR6Q0H1hzLmj6SVgLgCEum/lKwqWiguWtoCkX4tUhhqAqO1bDUCInJIPFZVM4oUGIDxcq2PpWFoXjbvJcD5EWYmBOb+G8e28CL6bH47n23CGRC0dVx5fikAP4YdICdyDd/Zisp0T44ELKzCovx/lJSaenb4GF00SrlwJWcSPKcV4O0M4VVRVLCDJeUAuO64M42zF2C0AoXNDs5lTQEE/Ux4HzX1Cyxy1qxcvtkELyMvvL8ExY+pic0nnjFvNnEhiQ/cpwWPv2DGLyZ7QAEQDkASLRrIF5O0PY4BCiTDukgOiYm2RARAVYCIDAioAJFc3Ow1A1BSUllqK6gosyvDn9Cg+O1Nc/NE8IH99EsGMIblbQBa+Fk4ZwjcXAKISNpaW0QBEAxAuAQqetQUkjycUPVRCC8L4qrYh7gv/3OWV2LGPP+bqtPDvKHa8QPjUf3xHJ2y+oRkDCakenrWal99lhCj/0jUdceQNworBI1ONflgo+WNOKYvlW+BkYl7+QttP//Yzy7F+R2HpWLIiEs8jsckGJhb+FW2S+Xrj9U389rcgP110eAnuekUoldS96qMf18W5DjxyEicz84fmCpEBEJlFQwWAUFcubgF5YlSHuGuQWwDy8oy1OOcewWWgSjV1H6KfqUuVDIC45YC4zQNC21UBrrku7VQcEBo2euwpZbjCdkWjn7UFpFHy/ExoKRYQmWKsqmw7o8rFAiLjgKgAELdRsGTWFrdySGcVSgUENADJ9eRp+n4hbzrz39vMNVJdYdG0CFbURjD3TvG7y5WyjfYWv9lUgc+FAzJrfEPKEL4agGSeK7clsr0c0BYQP9bbxnQl7kKeC63aBesrqwH83/VPCdeVYfv7sUONP5bN+58VEYx+RHw/7rRydOlgwu8Tmb6dMKjhiIhSxKMV/fR7JB55iEcVuvd1AQqGDvLjMTt8rCzfArd08IhGn8xuwEezGrBkhfArdB4OIPps4gHP8bFtL2/MtD9ikk0yJiR0HmWqzyZedO5g4rG31+D5j5q6aakAEBmngyq2NAGiDLAUigNCb/VlbY8+thTj7UhQ1AJCAQi1+tDPm6wP/Pq3kD4HVO+Mq0JNT3mIPdU8IK52rWLhVABEBhTpnGkOSPsBINS1SYUDogRepr4Ps796MkFZGN4mFhDb2qIBiOIBkKJYtspV9i2KNwupaOTat2zepwDk93ci+GdmBLV21KPtJnjQ82DhbSCzMrh1waIWEMMHMBdJDFXcq2RkYm0BUV8d7QWAUBdAbQFRXx8ZS9JDhYOPN7/gkZYEWOA36NefVI4eXT0JRG8aGlbWAHV5kuXI4Lks9ukvSOh/LY/ELS891jdjFpHkZ78BPvTv7cUW3Two8TViPUpCp8Tr56/ogN22EkSoR6eujt9809tueisvs4BQhZ26PnGLhpMPRabM0raSo2C5tYBQDgi1rFA5UUWalpFxRmQWkGP38OK5D1NnPRx3WgWG7lsqXVutEYAkBEfQJPSCWUBUFGnvi6/C2L1p6FoV1yMZZ0Hm2qQCQCLTpsSzlnPg4NnvgNjaL4QFhLZljLsd3tPOiLWlIjdVq5C2gGT8WUxbQNUVrT0BkOpzTQTP9sJbZuYNgFAScM0ID+beKdwWVJIYFguA/PFeJO6WRq1CsgWlSegiQgF3deu0tTtLQm67uJGTJiOhy1wA3QLp5H4W8lxo9RaQia+vwZtfNloKhuxTgkHb+nMCIMfu4cNzH4o6KemZW0+23cKD5asYfv0rGrN60KdrlYEBvb3xJHsy4PP3iggueUC4dV1+fClufkaEWaW+/FQpptYAtwBExR2LuvZQQJArAKEckAsHl2CCHeGKWkCoIk2zsFO50jL7bOvBO9+Jg526bG25qYkff2kKAnm5G4aU4YwDy6X7n/aTRzobcqsIL1wsFywVC4gGII3TmasLFs19kbxIZIo0t0rEI01JQtfmAkBUiOTm3RMRvWB4rMu8LceiUSwAQsGOWwBCLSx0LHxsmQCIMWEi2IVCDrI+ZENOL6YlIpscB7IDTgMQINkCwgFIl2096LqLgfp/DEzdXVxiUiuDTHGjQIOCC/o9T2z37WihIBQagMiiH6mEYtUApO1EwZK5AGoAkiv0I+87FpBbnluN1z9fF8s6vfBvsYj4D0afnh6U+g1w96offhKK6oDeHvi9Bvw+A106GOjS0USpH1i5hmHlWoaldQy1v0VioCKbZ+DWXuy5lR+bb2Ri6UoWd6+iAIRHyIpEEXOv4i5fR98kCMfUEkHdq1Ru5VUsIBRQUAvIfedVxPkZMkCQTwBCx0kBjyxiF+0TteLQDOl0ro7fw4tnJBaQw3f2Y+IFHZQACB8z5/k015OtC5YGILkBkKgk94UqADHOuyhlpCm3ireyBSQFkdwtAAk//VRcUedKu/eEE2PDVcmQLnXBklhb3MqB1k9dzloCAHHLL8r17Mg38NEAJDUA6by1B9xVquMWBqbtKW62ZQCEc0N6HCrceFsaAKEgIhn4fHBU03FRTooGIG0HgCQk2iQugBqA5HoiJwGQxYtXoN+ZS2PKfqEfSgDn5iKnxRMG+vH0dLG5KdCg7lWcnF5VbmL9jia6dTbRfX0TXo+RkEMkXwCERpCiddLPlANy7qGlKXN0UMU2GwDy3JUdsPuWwo0swbJwaSWG3CYsC7RPsohYFxxegrttcr5pAtEU2FCWB6RHF2DhksaVwRP1HbCDcJ1L9dB+agBS6B2V//qzsYDIcl+oApAmFpAUoWtlFhD6rgyAqBDJ2xIAMW6+DezyS4X4Se4SDUBy3y/tGYAsXrQCc+4Jo66WIRpm+PM98QvOLSAcgPDoWJyr8eUFjdYKR2nf+lovfrhefM/zgwx8RWRO1wCkMQmem0SEbpMeplv52YL0fHJASro2Ws5kiR5z372NNThjlrlgUTBJXQA1AMnjLDgWEB7a9sl312LBX1FM+0a4S+2+pRcVpUaMaM4tI9N/EIfHbv28MasI/+6fOoYlK6IxLkRlmRH7V1UuLCbf/k9YTDgX4Yrjy2LcjZ/+iMRJ7pwD8oRNSOcRqxzyuwyA8PC8O9X44PMmerrJco5Qlx8VC8hdL62Kh9ulyrgsyhR17aFgJFcLCLWmcCvLlDGC9O0WgNB+y0LO0qVEQRcloW+3hYGv/2dbxQC8d0t6Ejqdj2/u7YRunRtzt+Rx6aasSltAcpdwNgAkKsl9oQxAnnwuzrPwPPAIzMObZhunACQBsJSUAOts3pokZ4kKkdy4/Gqwm28UZ5aCC1YuFhDO72CXXRJryzvtfRjbCgK7zN2LKr107DJQZpwyDOw/D8XF7yRD1AAkD/tj0W8Ib5s5R04hfb1zH4X7Gvi5MOfVZfj45KbBXAIXmFivnzjn1/4dxfdXNvI1HACy2f+Z+Pm/jTdf21zvxeYnejUAsd3VuNKtAUjTjOTuV6raG24ACLWEaQCiJl+lUskk9HmLIildnqglwi0JffjBJfhXH3GLLyOnJwOQjuUGPB4RZcvhEFCFn4KLXAAIBQ4yfgcFI7I8ILRvMpcoVQtIsjXFIX2rABBZGF7Ke5FZQGRRsHp3MzDv90brWCYSeksGIDLiv3bBajwusgEgCS5CJPdFNgCEKuQy16Nkly2nHRULSAK4oDk+fD6gQShXtEzDxHuAa68QTVw/Fr7h58U+UgDCv3fKyELgJrip+f1AvbD4UsAl5ZtQFzcCuKQAhACcmAXEdjnTAETpZzFWSMWVLh0Xpi0CkD9/WxELjbtoagSrf2NoWC7kWbI+0HeUF/4qA+uWMnx3WVMLSGC4B9bExqS3O97nRff9NABx+DIagLRcC4gGIOrnpquSuQIQGTChQIPm41ABIDefWobLHxUhf2UKYy4AhCrjlMdBlXeZkk6FK+ubzCVKFYBQUMT7N3VMFYKKFhAZiKL5XNdQZAAAIABJREFUOCgHhEbKkgEQagHhgPC98aI/sqc1AhCZ657qZmpLykauACSdUiYloRMLiAoAyZcFJJmc7sx3IQBIsptafG0RFykZAJG9K3VLI/LMhQNCCekqGefT7RfnxrG1cEA0AEmczeQwvHW/RDH75kZAUboh0GeEN+ZW7QCQHSd68cVwAUa0BaTp7sglClZLcMGi7nM9jwYWvCDGGDjXRN8R4tJZ9tB3eRQsxgDKsXGbX0P1t9oppy0gbiVWgPLNDUBCCxsw1o5SNWQfHx5/R9w4ThheEU9E6DY8rVsLyH4DvJj2TdMQs1QJpVGmVCwgspwgqhwQGaBS4YDIsp+rJCKkmdBVAIhKHhANQAqwUZuxytYAQGTuWPmygNDoTzILSML3F48G7hgfmyVZBKqEUMBJNxyOi5QsDG+CixuxniS3Fdl/r7R94H/MFAULl10NjBOuaBqANHW1as8ckL//rospijwKFgUgTp4ObgnpdZoHc24RwKTPSBNzbhVuVzSXQiE4ILs+7kPXXZomQ5QlLqQEefquzPe/WFGwVEIK58KZoPUf8HEJSjdSD+aaLwCyw11elPc0NQDJ8XdefeZybChfr2cLQNarNGJRqJaujMbzd3DXrKoK8f38ReF4IsLrTy5D/94+cLeqT2fXx60blCuhAjpyccF6dMpqXPGYsKpQxVyWy0OW14NaSZK5GqlygqQDILJbdxmgkpHhZWFmKadDlgl9xBEluPNl4XdJ+0rBSHtwwco1RHBbtoCo3HyrKmX5soCo5rxwzkkVDgjOvRC4d0JcgXfyfSQAjXMvhO9aoZy7BSC0Dzj9LODhSaJ7BFBg9FXA+Jvi38dcp/r0TXAHovyRfAGQBPcw4oqmAYgGIM4e4roCJexy4rmTiHCzk0z8+kIU0bWArwpx16y+l3viVhLqOy+LgiX7XhaGd/GMCD4ZKi4xzRJg4MuC2E6VahkwoVna6bvznwjHyfLJCRCdG3r6bqGjYLVGALLp8Qb63yQPVMPnKyHPhh8YMN6Lr0Y0DbWcL103uZ5sLSB0LXJQ3esk4Q2iapEqpK6QMwAJBoPHALiWMeYzDOPJUCgkfu3sp3fv3gNM0/y3YRjljLHVhmEMD4VCP/Ts2bOsrKxssWEYtU7ZUCjEmY1pQ1tRAPLLn2HMmNWASx4UOTVuP6McNZt4YzwMTjQ/6RYRdem5Kzpg4/V5eF5g0T9RHHrNitj3L13dERt3NVHqBayFERwzVoTGpeFwb/rvqpTRoty6WsksBtQSQctc9vBKPPaOULTpI7NcqESWkkW+ysYFS8WlzC0AoSCCAhBaDwUgMgtI357A7AVCaq3dBUsm55YMQIpxJlA3mfYCQIzrx4LZXA+qeGPIacDjj4gN4PPB+85HMVCQAEBIGZkFJAGAEM4IJb/jmOOB55+JH1GOZSSBhE7dqyh5f+r7cCwgFKSo5AGRuaJRa4jKOpApCwkAddr7CO8nLDXZ5BORtSH7PtsIPy3dBasY54IMgHCgYTBg7t0RRIT6EHsoANnmJg++v6ppMsFkRTRVdCwahYiClNB9Ycy5o9GbwSG2qwCT6jM8MT6L8zjvfndNfQJZ3vl7AmDxA1FB4YIGIEIQXXYGlnwqZGJ4gb1eFWBQ9iTn2aDzQXO9uN3vquWzBSB0LZo+YODkpqA3nUWqxQKQXr16bej1ej/3+XwDZs2atTwYDE6JRqO31NbWvu0INRgM/gjgrFAoNCMQCOxjGMZtoVBo22AwuBtj7BLLso5QnQBejgIQ/v+U6EyBA72VV1HiZPXQbN4qFhCVtj6cWY/jbLBDLRr0XVkmdLdJ6qiVIJmroWIBoTkxVGSq0j9ZmVwAyPCD/Zj4hn3CJi2oRy6uxIFpwvC2ZBcslfXkZv84ZQt1qBTrTGiPAIRaQBIAyKD9gHenxZeFAwoarrsKuO9u8b3XC4TtEKMSgECBCSWt0/C/tA8xsPPuxzBq+iRYQBJyfCRxPeLJHCnJnUT0iikHBpCcmC/BPYyMhfeBEvMdgOMWOLRkAOIWaKha+wp1JvA5LNa5kA6AdNjMxOqFDHPuDCMs7iqx2RATPz8uXLB6n21g3v3iPpQqmMmKqAMEKDABv2S2cQZ13/rrkwhmDGlqAZEBE3pLLbWAPBnGD9eJxqgFJBmwOAeCDIDQ23HZb4oKByRfFhCVety6YCXMEc2rAMCZR9nYW6sFpMfhJha+0jSaW6u3gASDwZMYY3tZlnU6n7RgMHgyY2xPy7KG2ZNoBAKBoZZl/Yf/f58+fbpEIhHLsqwuwWBwBGPs/wzDiDDGwoZhjOYgJZMy1dwAhAKTsaeW4YosyeZUkZzwymqMe1a4V9FHFoaXktBVFHxZbg1ZGN50FpCWDED4OI8bWBYT4ZBbluPtb5vyZPjfMiUibGkARGbdkAHATHsm1d8LpWwU60xoLwAkQfGWuB4lWECocp4ETJx1IQUIBCxIAQixjHDrg+/ikbFqVSwgsshg1AJC6/F9PwfotnGs/gTrzE47A5/bV5lksbdVC0hrBCDFOhcoAAleYCJ0t1DEuKWDAxD+LLeimHu7sCxwsOBYCqjL1i5PeLHBzsJ1RWYBkWWi5u84yq3M1UoGTGh5FQ7IFsNM/O+h1ByWVBYQ6r5Fb8dVAAh3FdtgV0+TywEV4KDCAVGpxy0Akc2RigWE8ke2HO1Blx09rYID0mYtIMFgcDRjrMKyrGtsADKIMTbSsqwDUi3gYDB4P2PMywFKTU3NhdFo1G9Z1q3V1dX9DcN4vaSkZMuZM2cuTadQ5QpAZJYOle8fH1mZMsSuCteDKpUf/ViPY8cIdy+ZBUSWByRfAERWTzIHpKUBEGol4cBp3+2E3+bQW5enJOrzv2VKRKgBSDYQJvU7xToT2hoAkUWXCo+6OCFfhjMLCRYQQjDHYUcAr74sih16BPCa/ZlMn1sAkuCCRV2zJNnVc7GAKAGQJJezVBYQleSPdEUncHCeeg6RE4+N/dmtJSWbnZXJBauVApCi6AoUgFBOR7/LPajY1IBhJIbhpfNFAQgnp/c8xIvyjRMTEVL3KhULiIpSLeOAUAAis2Lwcc2yI31REr2MA5LsvpXJCpDsKrbXy3702rUKDtmfy09ljIUGILI+0DkyPACzPdo0B6QEZd1SMzIKdVnJ10pOHJBAIHA5gLIkAMLdqg5KOnjNYDA4gTG2k2mag+bOnSu0b/IEAoGXGWMP19bWvp4JgCxZIiJb8IcDhwOvEpwOHjaWk8f5w5XKAecui33myeW6dxHRJmTlVb5/YlQlTrZ5Jbwt2q7zmbYl6wP9/v7zK3D2v1c16ee0r9fFwc6E4eW4cKJwVKXtUkBEPycQuM8ux0X3N31XpZ5v70tMyqcyHpV6ZWVov6ms6diuO6kU1z25NiYL/v1+NgC5kydlfE58zzeMsz5239KD56/qlFYPoONKHnM2CoSbd3hfu3TpgJnWMvQ/p+l6pXXJ5O+mPaesUHI65rT/U7VbrDPh75lzUb+1TcAlPvv81tzoLm7N6cOVuIZtRHlZGf43Wo6H23W4ANQNyfvUczD3E3cusvL0XfpZ1jYHII7S63nqOTgE8/AjDyI6WiQETHCjunsiohcMF99ThVzBAsLrp22l+oxzLmh036KWF8pDIZ/pGGn9CckTSbvm+Nvj4+Lvmv1FokMqT/8PiRYQZy5AARch5nsmPYLIWacJmRAXL1q/bO9wABLnfTz1HMI2AEm3VrLZh6necc4E+junsnZla1p1rRfqTOB9L9a5sODHFZiyq+BSUgCyx/M+RNYBDSsYGuqAb0cL6zmPirXubyHtDfcy8Of7QtGIAZYeBsp7mGBhhg+OEm5UPByrE36V35BPP1K4AdNbZx4xqcehjcTfKbuJ/vDbe0fp4wpzpu95W0799N3f343gszNFf6gFhFs0onYORvou/Zx8O56KB0H7Vn2mB7UPNPJQtr3Bix0uXA90raqMhfZftm+U6plRgrIUUbBk79I52mhf4A+bLMDD8Pa7OH0Y3h/HNySMncqCroN8nQPJ9TjnAl3TdC4p2Vz2me+BboMaI6+lWnOp2i2ErsDbyUkBSXa54mZWAHuEQqEznUH069fP39DQ8CwnoZeWlh75/fffx7TtYDB4ejQanVpbW7vQ/v9XAdwXCoWmpJtAbgGhf/9y7lrsfN4fsa8+vWcj7FBTGvu88K8wNjshVjV+froHenQVB4CsvMr3k2/sisFX/xVvi7brfKZtyfpAv+d9TvXuG5+uirf18KWdcfpt/zRpl/aHfqblZe/SdmWf6VjSyVQ2Hln/aHuyfsvevfWsThg5SSjqvMzBO1fEPj82ZUVcRv238OLb/4kflFMPKMeDl26Q9kyQzVOhDpJU9ar0QaWMmz4b/Povz0+xzoTIwoX4s2fP2GjW/+IL/L3jjrHPGy5YAE+PHk1GScvLyvCXZPVWPfoolp96aqze9V57DWWHHBL7LCtP+yTrH31XVv+a11/H0kMPjbVVdtZZWDNJRKai5f0HHoj6t95qMmZanoIX3n+nTtnnkqOOwroXX2xSZ4fbb0fdJQIQlY8cidW33tpkDjrecw9WnCeSIVIgQL+n7XL5+HfYoYk86TzVf/llfI4rrr4aq24UsU9ofypGjcKqW25p0mdav2z50/pp39KtlTxvJWl1srXr9vtUDRTiTODtFOtcWPlbBE/3Fb+dg9/rhMl7i9+OE2Z3RkV3E4u/asA/s8L4+EJxCbjz+ArMfnAtls9rVLL59zvdVI6q3l5Ewwyr/ojg00vFpR6vc4PtxKXn4q8b4vXvcV8lPjxHEEtoGdof3ofKjYUyqPJ9cv+dd3+Zsg7TjhOXsJsd5sPPrzbN/E7fpZ93GlOOz68UY9nuqjIMGFnZpD+0/F4Pd8D7p4v7Y08pcPj09dC5T2KOLZWx0LHLFnou9cjepXNUfbIftU8IwLjtqFLscGWHtFt43gtrG8deAuxxX6Ms6BwX+hygY6PzQdccn8uvbxJu/vT7XW6rQL8zytOuueY8F3JSQPr06dMtEonM4JaNqqqqZXV1ddx6wUHEZGcQwWDwMcZYiWVZJ/LfZ/L9/QDqQqHQyOrq6r6maU4pLS3t4wAU2SRyAKJiAZG9r2LpoJYUWr4QFhBqDXj+yg7YfSuBwlUsIDIrjFsLiKye1mQBeWb6mrilZ6eAgc8tgVMP2sGLRy6pSnsmaAtI/o7MYp0JbcECQm+qqYWFWkCoZcS4eDSYk8uDWkBOPgV4Ika7AzweIGIfu8ecADz/tPh+0L7Au/b136jLgVtuFt9ffg1w8w2xj8bdE8EcqwqxLFCit8wyQi0gxqnDwB59qOkio8Rz6uaUgwWERgbjGdsjZ9oWEEpOJxYl2cqnFhDP3RMRseWgYj3JdTe1RQtIsc4F2W1xggVhegSfnS6Udn5z7C1HLNrUsh8a7zprLjbRqUaAhRU/RTD7ZsGzkFlA6A00LaN0qy+xjBTCAsJv/q17xVi4G9Ivz4gxyywm9HvuKrbhbp6YBb81WkC6HQT8/qbYrRsfBux4p7i8lj3UerLDBC8qeppxi1RzWkBmv7oMM062AxkQzhK1ZtFgBJufbOKnJ8Qcc6vYXjwKVlCEfm7VFhA+oOrq6qMMw7iW320BeMWyrMsCgcCDjLHJjLG5Ho8nBID/c2LKMh5ut1+/fus1NDQ8ahjGFjxeBGPsAsuyPsx0eKtyQGT1qHA9aDQtWj5fHBDKOUjOzTFlTBVqkrOIK3BPKKdDhYSukseEu5N16ywOXf64jYKl0oaMAJ/gXnZpJYbcJm6T6NjoPD3LAcgk+yZnCwNf/08cpK0xEWFrJqEX60ygHBAVf3/VyECyPCAJ+Sa4C9a+jS5Y4W2Fa5cs94eMHE3bovXTJIOUG5LgenTyUOCJx8RGPXQw8Jp9B7TXPsD774jvBx8JTH6pyWfj+jFg114Z+55+xoUXAxPuEOWPPxF45inxecipwOOPis8HHAxMeaPJcUvHSEPsIimhofOiSihgmnE+gYROXbAIJ4X2ITlimPcEfh8mf2j9CWAwKUJX2kqy/GNb5IAU61ygHBAZh4LyBbYd50XJegZYhMGaFMGy78XvCM8VssVpHlTVmKj7uTGj+nYTvOhxkCfGJaEkZVkeELf8CFkULLccEFlSQgo6OBGb2XFcZOWTZVje3WiRJHSZnOkcrb878PdH9iY1gb1fTx+GN5tM6NxixnkmkXoWyzkTWSuCHETDgn/CXeSia1nMHZB/Z3oFSIj9KzHinz0lwuLUdeNKfHHbcsydkGih46PodrCB399IkcWCx1poDIKVMiBCqwzDm+X5mtNrbQ2AJOfmGHdaBYbuW5oQXlgF+GgA0ghA3CYijCleKUJ95rRQFV922v0htCzOWWrtAERx6Hkrxs+ExS++ivDRg0WdJSXAOnHfQUnDMjCRjlisAkA4f8Fz6hmx9mTlpWDkhVdh7jGwybsUgHAF3nuaqD/8+qtgp3FPVwC77Q587PyCEnFSoHHgIcBbNq1un/2Bd6ba7+4JfPyB+HzdTQAP0cufi0cBd9huS2cMBx6cKL4/4WTg6SfEZ/r9fgcB0+xrRMI3Scj8TqNpSRIaFhyAJIEU33DbJUyyCjUAydv2LFpFyYkIlQDITR6UdBXRsbilY844orkB2GBPE513AObeZkfTGmWiqq8HXQYYqKtFPCpSvgBIAulbIZcH5YBQzosMUGywp4HFHzRVWml5Wg/9zJXWVACEKuo0fLFq2FdnwaiANRoFi5ZPHjvl6TjJGcs2Bdb80rg8NznGwKZHexEW3nixh4Myj1+AgVULovjqAifxoA/1Kxk+HSr+f5sbPKjYxASLNoILDjBijAF7CXHSe+wfT07m8mFRUU9lRRl++3IVQrbVioJGatGJkStSYBFeftubvDHezJrFDN+OEv3XAERxQooJQGTJ8dxGwaKWhOTcHFPHVCGoLSAxgvmQW4XVQ2YloRYQGjVslxoTn8wVu55bQN4dJ2Sa7ik2AKFRRGT9bA1heBW3cV6L8TPhj6uuRXSMcB2iT6EAiEoGcBnooBYalJbCO3V6k+zhCfX7fOC5PLBeF0S//gK45y4xxI17AL8JnlvC06MnsNDOxOlW0htsCCz+U7w1YHvgm6/EZwpeZMDkgIOAKQKMGK9OATtMWIUouEgGVuwywR8pBABJyGNCAdTFo+G7TFh8ZE9LBiAJEbqIRcZtdKzksRcy2o3bZZiP8skARCny0p9RLP2exRRFauko3wRY/avolb8zUC9oJfFwvjFlEwxfniMUunwBkOT8II5c6FgSMqETK4YKAFGxgLRVAOJbH2iwAw44cuWR0Sp7GTFgVdYDsUhppkcAhrr5EcwebwPP0Z5YMII5tzcN65yPtZuqDr4/O3Ysw1+/rI4HTeg1zMR8O+zyZkMN/PyYQB1dBwJ/TRe10GhfmxxvoNteQhdat5Thu8s0AHE1X20NgFDw8hzngGwpOCBuXb/yZQHht+88a3xy4i/ep5bggkXBiCxvyn79PZj2rTBRHrWrF/ecl54DEtukRbaAaADi6hhIKByzgLz0GsJHHSa+bwYLSHIGcKdDKqAjOf8FBxfmiUMQnVeL6MCdRVW77wl8ZFso+PocejrMffZD5NuvGy0U1UGglnu3NvPTuQvwzxLRKM0tQpX8K64Fxl4vfgAffQrsVOHylOxaFj1JhLdNCNU76RF4jjg69j1VtpVcsI4/CXjmySZ1JlhwNABJuWA0ABFiqV8exZJvGOrmNSqcfS4zsfon4NeXomCE410z0kRVb5sbUhvBHNsyki8AkpAfRGIBkWVClwEQGpJXxgEptAWEhhqWnV6FsIAkhEpWODbNUqCqxkCnrUx4OzHU/lsADh4Vjav6s+2QxzSvjEK1WRVJBUB4u04fKAChn7sfBiziIZ44ZeJcE523FutVA5AspoErG9RdhSqk9EZcVnUuHJBCWEBk1hO3CRDbMgCRcUlUAMiwA/y4cWj66BYxxagVAJAstov0lbakbPAzQYUDkk8XLJ50D+NE5CVKyk64db/oUuCu20QZAooSLCB+P8yxtwFVHcGWLgMbdZEof9RxwIvPis+mCYNzTJYvA6u1gCVJ13bJs7xFb+B/88S3Bx0KvPma+LzL7sAntssW5WKcfibw8AOizMC9genvic88fPGi39SXHbGYJHBJzhsB3HOnqOfOfwMjzo99TMhdMvoqYPxNcVl5p30QswopARCF/CYagNghqr9LHZY6Nh8G0LVr/kNzqy+g/JbMxgLi9IBzQH6dHIm7qDgK5upFDLX3h7HWNhL6OgG9h3nQsTqRG0IVe5qPQ8UNjFo3VDgg82kmdIkFJCGLOgEytJ/0swyAJAOrztuaTS4rZS5YyTlEBr6cnnNRCACSLllkRS+gKmhgzSKAz3MsHHMKNya+RrrtZ4AZwB9TRYHuhxgo38gETO5iZceXjSLmksX/cQ4HBzOCy2HE+BziX1N3rGiDsMAlu2qlAiCB801YNijacH/gT9vDVgZGNADJ8YxpDgDC3aIO31VERKCuPQk5KAgxOhcXLNm7L89Yi3PuEc6Ifi9Qb5PDVIjdbknoyZwDmTJeLAuIBiA5bpoUr7clZSMZgKiQvFWzZKtwQGhuC+Pm28Auv1RInEagInNg3H0/2AVni29GXQnPVlvHPrJ/liB64Tni+623AX74Pv3Ee7xAxD4YZJYIapWg3BBCTk8ACzIOyHEnAs/aJPQd/wV88ZnoG026Q3tLgQyt8/QzgIcfFK9OmAh2ochdYpwyLCHBIrcKeU4dpgZAgn2A0JwmstIuWCL/TcIaJpyjZIG1pTMhNm7GGCWhq7hgUZlQRbrvKBMdthA3x4s/C+OnRxM10667GdhwbxM/3iAs7wmuTT7ErSa5ABCVRIQyDkj1GZ5YZK/kx60FJBcAkuxOlinpYSEASDoLyJZXetChl4kIBwCGgYaVDMtnMyz7MYrlP7IEbkj6g1n9r54ykXvG38mI5aNZ9zdDmHueG4C3ErGIbDwwACevR+oBj0/wUhpE1GXpU9oNWPu7+HP3Q4FF9h2UDICks0gV8lxwz4ZRl21BShYKgFCFn2cnd6JRyQDI2FPKcMV/RJzlQgCQm/67Cve+JhLr0UcFgFCrULKF6KCrxcqV9Zn/LV8AhAIbCl5o25QDQ/s69tQyXPGokK+sHm0ByX6LFfJQyb5X2b3ZXAAkwXJBLCA0SlKyIh0fUULyvsaoU+aE+wB/CdjM78G+/Az48oumQuDWip6bwNhsczA+cY6FgmY5l/Ey8gVAZCT0U4cBTojdqk4xK02TZ9/9gbftqzlq2bnkcuB2O/wvtSiVlMD79ocwavqoARBuHXq7afqoQgAQvgYc97DsVmvmtzJZY91yQKIfvo+IE6CBcI6Se9KWzgQ+tnwCkAG3e2M31qbXwC8vheM331SGXGGMKY8xsnpqcvcuT3nxyYlN/e5VlO1cAIjMAuKWA0IBCHXxomRwCtxk2djNEiDfFhCVKGS0TPL6D5zrQfBcD5bPAtb8GYXpa1SPOQn8zxlR/PKkcMEq3VAkO163WNTCLWHxuxjb6sEtIdySwcFEdJ0AEU7m9cynQBYlkqJdpaqBR3Or6GnAUyHW6vJZAkinm49CngutHoCkU6RTTYDMBStZ4XeiUVEAMvwQPya+LhLXyKwSKsqyTBmn774yYy2GZ2kBkbmlqbSrCkAoX4XKmbYhK/PhzHocN1YkM+Jgb53tUzt2aBmueEyADipfFZnSeRr8Ly8mfyYO+RFHlGDUsSK5Uron049+pvez/Xsx220r7haFBCAJyhsBEQluVzQHx7U3AtdfLZYDzUJ+7gXAvXeL70deDtxqK97czen3ReLXjD4bdQP+sK+wrroOHn7LzzkR8+fFQ+ZKI1MdewLwnJ3vY+hpwGOPiJppRCxqnSF8DZx7EXCvTXJXiYJFyww7G3iIp3cCQHkidFymB4jaN7HDzgIeEokUwYGYbf2hYXtl4Y4TwvDSPhBQli8AYlx2Fdi4pu5h2e75TO9lOhPcApDIXbchOrYxQINjXUruRyEVjUxjLsTf8wlAuPJfsSnwz/cMi2eEMf8Re796gI0PNPHHu1FExE9X7NlwEPDnu+IzjVTE84nMvUMosbs940OXAWbM1SYXAOKWhE7BiNsoWCoAhFoZaDZ2CqAKwQFRASB/vNeYNT55zXHw0WeESCq57p9ozPoRXsVgeG0SOgm/nC0HhLtXxULurgXCa4B1S7irF0PDMsDXkVtDjFiQAx6elwOE8Go7NG8J4C0BSkv8WLpgHX7+r1hDW5xp4n8PiM+U6yGLgpVun8ksUoU8FzQA6S0WHFX4uVLsRKOiCvXQfUrw2DtOOpPGqSyEBSQXDkihAEgycHCsRHRRq5SZ8MpqjHuWnNZ2BckhiZ16VQAIldcJA314erpANRqApD5yCnmoFEKZSFdnIQFIsvKWsh8keR8o32HIacDjtvJ/1jnApPvkwygtBQLBRrcr4rbEXaTMXr1j7yYCkJOApwXhGjys7MR7xOdLLwduswEOTSBI3bRIT8w330H0oH3ENw/+BzjjFPH54suAO8aJzzxvxtO2C9YZZwMP2kCDKv/ks3HXvTA4Z+X998A+mt6YDJFKgIcuflS4Y+Gsc4FJ98Y+yqJm8YSMTr4VKQAh4XbzBkCOOR7s+WfiPZcp8Pla96kACHWjkkUMk0XBin44HZGj7QAN3ALC+TU1AtDSpy2dCXxc+QYgPJQrvwn/5fkIvrtSXHDxKERdd/CgfjnD/McjMVed5IdHHvrVTvBHScPbjPGgtIuJkq4G6pcyfDZM/Gbt/pwP621pwvQnAhOZBcQtCZ3WUwgLiIxnIeu/bN+ogDIKZFwDEBqq1gD2fqMpJ2XVb1Gs/B9DZA3DyoUsTvjOFoDkckZkIqF33dPAXylCKm/yf8Cv/xUtbzDQgMdvxEAQBz7aAuJyRpJdsPIFGOhuAAAgAElEQVRlAZHd3NPvqVtQoS0guUTBkkXWUg3jKruBSwYOjpWITqFKmY9+rMexY5paQJJDEjuWERUAQsfGQcedLwugeN2JpTjrkIqMqyzTrWPGCrIsUMx2tQVkr9ispcsDkqC8UYsG+WxcPArMyZ1B+Q4nDQWetJMDStaHcchgGNv2B7aoBlYsb+SApAAgLBxGlJPQ7ehSOH8E8G9B7k4gdJ9zAXCfbW2hfaaASCFnhwwI4MprgTEiwhVOOxN4xCawEwDCXcsMbgUBEPngvUZLB5UDIeYn5BZ55AngtJObjIsCEKpsJyRkJAAkIQEi5b+cMRy+MePT7lgKcCjHhwcTcNzDstzyGV/LBEASuDOER6PEfdIckIzydwrIyNT0e+5TX2vnZKDggjZS3hNYbUfFpmWcpIe8LI1IxIGJv4MBTxlXFBm+PE+AnX2n+1HRQ+QooY8KCV0WSjcXDgitk2ZIp25XMguICh+HAhAKNGRkdhUA8tubYXxp5/LwdgDCQg0BT0q426PyTOgciPz+TgQ/3iisty0RgGx0IPDHW2I81OpGCemaA6K8/VMXzCcAoWRzFYI1zU3hlgNC3ZFUXKFUAAhV2CnokGVXzxWAJAMHx0pEZ0qljCwPCh3D/edX4Ox/CxK+BiA5bpoUr7el2858WkBiiaNWr44RwlFXh+h334BddK6Q4ElDgCcfF5+JMp8AQA4/EnjFzjYumzYSdYoq6gkkdApkzrsInkMOA7puAPb7IkQP2U/8yFw/FuzaK0QrlEPBExt+aAeBp32gyfhI/ym3JSEcLkkgmBA+l7icGU88C3bycaKVK68DxlwX+0jHlWC12XNvgAOS5Geb/sD334pvL7oYuEtkYFfJOJ8AQCjI8vuBeuEym5AF3iUAoRyfYnFAKOCSARC3lpHkKWhLZwIfWyEsILxequjSKEQUjHQ7EPjdVgapnDccZODPd4WVRAZApMDkRg8qNzXhX8+A6bcjK5UAiz+N4JuLhWJMSegUCKgAELdRsGQAhH6vEgFMdkzKgIaMzK4CQGacug5/fSTkX745YqGV+cOT+O10txyAJM9731Ee8EhpTh6QPqNMdLSDFMjGk+v3qSwgNA8IBR3U6qYCQHQiQsXZyRWAyMjmbgGIjNxNgYbMHUkFgNAyb93UEQdeJcjjKuBCll09VwCiwu9wW0ZGqv/m3k7o1llEHaGPyjxxq8d1TwkCP48IdtzAsoyrq5iWiFQ5VzJ2OMcCbUnZSAdAPOTGN/rLz4jsICJOGY88Gc8obj7+NIzKDmBr1wBruYNuGPD6YXg8iS5PFBScOAR4ygYj3HXKSp+Pg9+im323jLVNgYYUgFByN791TxGWFtTSQfkpLgEIDRFMrQYJLkwy0v2425EqmaD53xdivu1s5UpEF/zayIuhLls0UhZdzyNGAnfeKr655S7ADk0stYBQ0CFxM0sAIEcdB99E2/VLso9aWiJCDUDcH3jJAESFd0BbkbkAUUV3p0lefH6WsFBQALL5UAM/2Unh/F2AejttDq2/y44GNtzTROUWBuqXIZ4UTgWYxM6RKIuRmut+imKunRCvx5HAQvv+g1ofigVAZLlIVCwgsiSMCYR6QmbPBECW/hjBB0c2xDOTd+wLrJgtZsQtAOEWn2iU4cOjhdtc9TkmNhnsjUWqisb+MfHfsOBzsAab7O3PnvWQCoBstL+RMiACXYsagLg/O6Rv5ApAZGRzFcVWlp1bBgpk7khuAQhVxrNxcUrFZ0kOvUsF7jYKlgpAkJXJBYDIrEoagGTecG0ZgOCcC4H7Jggh8DwbdhZxtvgPsFEjxPeELE5BQLLkEm7v9z8ImCoyfUsfSu4mIEIGNGJRsDp0iBPWo47rkUJYWhx8GPCGnWGKdojyPqgLFrWAyBR1YjVICClMo3hRUjYpTwGL49YWXbUK0Xemgjm8Esr7oICOc2DW2lH/unUXxHz+kPIJHBAa2YmCLzp2agHZaxDwvs0K9njhfe/jWJ4R2aMBSOYzpKWX4LrC7MnLMGOIUBJVIi+pjIkqulTBpgRzCkA2PRn45Qn7OFoPqF+a2AqPrsWjEzm5RTb9PxPrbWWipLOR4JpFgQmtgWZs77ITsOTzpqNoTgBCierJYXs/OEpYJFUAiCwJIx3LDnd5sfEhIrN3OgBStRUwfXADVsxp5Oh0/H/2vgRMjqJ8/6uemVzkAMKVkEAIme7dhPtUUQgiyCEgBJT7EASRG0QOgRDuW1AOFQEREOEvQjgkXBKOoEj8SQgh270xgEkIR4KBhWCyM13/p6Z7dmtmp6arp7u6Zqe/eR4eJjvVVV1vffX29/ZXX9UkgM/meVg1IkA+/nsR5l3bu7XxDrdlYfQe3r1Uf9wCLeX5sLHv/sLbarf4BZRETHm3rOpzP/pUQikMGzoYlr23Et74mdfuJkcReOf3Xp/4CMiEkwgsuN37OwoQmVktWaaeABHtusRXLZNsLlryIxIgooiDaDlSFAESdomTyElvFgEiwloUAZGJKqEACZ5MLS1A9toH4Kkne0AonyLORx74sy9qCRDKlu68NRfcmc8DsNPH63222gbgjf/zSnB5GcA52BVLkpZ9DPTMU0rFjXsfBLL1tkDWXbfkdBe28pKDK/IXBNvSAu9s8044vxyL/z7tSoDyki3uxPCK3bq4fgq3FP72XgBP911fwt8zn1dTkTA+7SqAqed7rZxxNsBNN3jfTzoV4PZf9kX5iGMA7vudh8nPfwnZw48ufS9cejHQW/zduvireEz4vk/IAyzo7CkZlEje3wUIv1RMlJxeDXYrcQLrG/MVZl36X3j7Bv+sHAAIOnsimDkrHV2RYz/uSIB3fdFR7QCWc0bYrlpfvCdukW3tOmRD0pMobJ6WgaFsC9VB3kZy7HwI5nSu/MCF+Vd7OyFtuB/AEv+dBO+Qtv/E6Dmlnb9nFTkgcQkQ0SGMIsz5dlmOxjz/lHK+PI/2mtsArPBpe4PdAb5yu/wSLBYBmXdDN3w8q1fQbLiPAdvfPEDGhEpl2HJftjVv4XPvjBEWLfF+8P4rHWJIve19Sc7bBWud9YfCkvldXiTH30ntlUO87/xyt62uzMAbF3giZfyxBBb659ZMOIHAyG09kYQnoUsPVW/BagEiij6IquZzK6LkgPBLsKqTp2tFHMLmgPAihXfGwy5xqic0RBglGQEJK0BkokooQIInVis5G9VLsCpyNXI5MC69CsiYsRVLn2oJEPrJJ0Df/BfQf/1fSXzA6qod7wYPAfhypQcu78Dzy4r4t/p8Ivl1NwEZPbqUmE1X/Q/c7+5TqoZ31EU7HfHOZEVyNJ8DctyJAHf6W9ry0QouSRn408b5MlMvA1reOpiPGvBLoQQJ+BXihbtWJEAqkuWvvxngJ6d7ePK4jVyn97R3/rDFA6YAPPJwqXiFQOOjTqK+b7s9wD9f99rKZCD7wqs1d4Iqz5z+KEAqIlbcsr00C5AkIyC8o8s7/CIBwiIabAnVl0sofLGEwpLpnohgJ2azbVplP8w5pf5W9uvsBLBslnclnwdQkSx/jgFvX+e1tf7uAB8+65VnZ1aUz6mQOQldlAOiQoCI7oe/B5EA2XyqAXOnef0dPBbgS39DgGHtAF3++aWs77s+Xv9kdj7CwgRInwjI7VkYvXvtCIjsWNYrV/bL+MM1w+Ky9fUZGLZJBrpXUFi5xIU5F3siBXNAJEeoWoCIog+i6kTngERZghVl1ymZdkUCRCQuZHM9RBg1swCRiSqhAAmeTC0tQE4/C+BmL4kZTj4NMl/ZqfS1Isl7jz0BnvEPr1t3vdIOVLCqSnAwx3aT8b1vznmHXLD9bIUjzd2H8cKrkJnk54C8v6Qn0iEjQNjuRsbW23p94K7lk6Ph4EMAuK1iyxZQ4fALyvC7J8EZPwG46Xrvcl6MfHcKwKOe81/xEfxdRoBU5JjwZ5GcfjbAzX5kpKIxbt9MfqvhHb8K8Nrf+txaRf38eO+9L+R+528pLJgqxWdmgHvE9zzHjBN6/FgEz7LGSoTZBYvffEB0mnyaBQjvrIXNARGNnmgJlsgZHnckgXfv9d6Us12who3ru5NVxS5YV2bAXUXg83cofGa7sPy1vlv7yljWmlsCrJjjlZzwYwILbvPq4cXImlsDrPD3fuDr3OH2LPzjJO+VvCjiwDu//C5YzSZAhmwEsPI/Xu9G7QOw1A+O82KE/RYUHasWICw6UV5SNumnGcif4B3poOrTqADhx4/lz4zZ1xNJK9934Zmdg5fEqfQVGs+IUYVyQL3VAkQUfRBVo1qAyOzYxN8bCpA1YfRIL9lcFPUR4SWKKrHE8zN+7b2pZpGq3bcdGGitmIQeCFHTFugTAdl3f4DHp3v3e/AhQIYPB1i0qHTaeE9ugag3w4YBYTsybbUNkC22LO06Raf+zCvNv6UXCRD+IL+bbwc4/aTSpSKhEUWAVGwPyy83EkUBBFESXoCIll1VRBz4PBEuCZ0XLGEFSIVY4AUkfyAjP2b8Mjv+pHV+e2Q++sMn5h96JORu9s4cYZ/SzmerVnmbEHzxRSnKVWS7iJ33E68Af77J1deDYbYBsAMVC90A3d1Au1d7yyYMtlaCe6QSAoRFcNg95QYAZDMA2RyUDrFk4jZjeP9n7RfYmhoKMHgIGBusD+uOXQ8+frMDurf0luRViERRJIsfi4EDIfPEswDrrQd0QSe4U/b16vnnW2CM3aim9at0NHSQR9RdsET3HFaA8MthWJ7IsE2M0tIpfs0/L0BESeibT8sAAVJKbmbXG1kv4flTx4X/POi94eejIfz9s+Vc7LA79tlwPwJLHvPEyMivASx/1fs7HwFhuzrNv9ark7U7d6r3plyUVC4SIG1nZqDj5961onNAZM77CPumf8yBBBb/ua9wG3MAwOJHvP5GjYDwAoTdHzsnRuWnUQGyxdQsvDnNE5Ns97TJj3qRHhHu1X1QyQv9XoCIog8iQ1C9BCusABHdp8wSrDRGQGQEGwqQYBpUSSrBrcdboo8Akal+9GiA9/1E5/0PAJjuPZXIz28BY511e2qoSEIXLK+qOHzwupsAzjnDI3tuG9uwAoR3+Pm37qKT2Su2ZuUcUVEiOf/mvEKACARFxfa819wA7rlnl/rIX8tv51ux+9i//gnFb3tnrlRs58vhUyFAuFPRYdLmAPPm1h9RJgicDq/MN3YGePkl7zt/+ONXvgbwd9/T2uWbYFz3c4B3Fpa26aXd3UDYAmxKSmKBZLNQZHk/5bNdDj0S4AFvQT9/KKSMmQWVYeKHcKKFui6Q7lUwfJ014dMlH4F78gleu1dcA/Rn53rVfXUngL/562z4Bn50MsCvfGF15DFg7DIZIJOrOF8m8/qbYGw8ruZttRInsA4mLUBEEQHead/pDzkY5u96tfI9Ciw5mWTEbphImPADyCehb3wEwHv+2aRDN2UnbfcKjyBbHDIOYOW7Xin+vJL8jwl0+tGTzS7K9JyFIeovLzp4QaRagPDtik4Cn3RBBuZd6Qkilni+1N9ThOXObH9juByQ/iJAxh1m9JyczvpdjvSgAAmaETV+j7oLVlzb8F559GC44B7vNG92cnqYQ/Nkuo0CpPFteFGABFtYKzkbdQUI6+h66wNsMMrLA/F3jeJzQOolpAsFyGVXA1x0nuccnn8R0Ksu875zb93DCpAKccFFGXgBIjqZXdSuMKIhOMCu4vBBwRa7bDeq4uHe8iSRAAF24vbTM0s7TVXkrXDtirb8rYi27P0dgL884Rk0G0v21GcfPicl2NyDS7D6StmenggBwwD4/HPvOmY/H33ofd9hRyAbjAYYskZp97JSdG3EmgBMtA4dWiEmghutXaK83ean7yyG4uk/9ro+7YreSNyU7wM8/KB3MZ8jU5WLlCkv2/tkec8BlyhAor9z5R033qmWESD8m3K2jW7XvymsXESh8D/qRTWqxEhYAcLvvsVExNCN2WnqAB88X4SPX+m7W5LIRsd814DFj3oRED6XZKPvA/zHN72v3Z+FVw/33qzzERD+Wr5+1QJE1C5/D/zSMnb44LKXvV9bWYBUHAyJEZBGadm7LqoAiWsb3qO/NRDuea5qzbjkoXkyCKAAaVyAVJ/RsvWE4LWZuARLxiqbs0wfAXLMcQC/u9O72dPPhsx2O3jcwTlisgKk+O9OgEsu9Opip2f7b6GFW9RGECAicVEZAZkJxYP28+5HsAWuSESUlv50e9mqFQf8Pf1CT4RCdBBhxSF3AgFCTjmjYmeq8k5TFbtg8cuHRFv+8rknl1zei//e+wD8xV/Aze92xZz/ZR/rN85BgwHWXgtgyFCAIUOADBkCsMbQkjApbbU8Yk0ga67pCRYmYNZYoxRtqf4EChBeaPBiBAVIBZSqIiBxCRD+ZtmJ56s+odD9KUCRHUX0P1r6/5cfU3jjXM/J32JapnQIYWn5lr9ZEvv76uUU5lzkvdWfeL4Bb1/lCQd+KRcfJeEFBbBVQ15x4E8GrwCSK1Oxs9bZRs9BfLwAkYmAiIQbnwwtwlmUk1IRAeE7wIElipI0koTeXyIgohwQjIA08MiIKkDi2oaXPwkdIyC9AymTAC+zjCrKQYQoQIInVktHQH7wQ4C7/IPmzvop1HoTHCRAKNsBa/BgoP/9L1B/GUyFY191TkcZ8WgRkNriQpiEzi2FkhEOoohDRRRDsCxKRoDwS7BKERB2eGJbe0UERJgsL8AT+K2DTzoF4PZbPKj55XD7Hwgw3T99bcr3AB5+yCvDJ8iPGgWwdKn3d2b851xQEgOkWPROSy+yJVhs70uWj1EAd/7bvWesbL4lAMsfYp/Nt2CL9wG++Bygqwug6zOAL71IeEMfJraYcGHnoDDBsu56QNZfHwZvNAb+5xrg/srrrzACUmczBGb3bIkX/fADoP6yQIyANE8ERMZeeCfxW88PgAFrAhRYeiMTDX7KwepPaOmMC/bZ7uYszD7dFyyXZmDQeqQUleMFyLq7EPj4xb75ERsfBfCef7aqaAkTf8/8Mi1+21s+CV2UA6JEgJxt9BzIyN/n6P0A3ve3Jq4XJYmShN7MOSBhI0/VdqnSV4g+G2VmUYxlGhEgvMNbvX3ud3fy1v3JOMWic0D4RHjMASnCtqd42W5hc1TCJqGL6hdtNFDPDDECEuMkTbiqPhEQCQHCdseCW3/h3SnvzE69DDJsjf1G48BYZ50K5zlsZCHsEqyK06655U8iAcIvhZIRIKIyIgEiFCyCCAhfjzAHpCpRurzzmCjJnRcg/G5UcMllAJdc5I0ffyDj9w4FeOgB7+8/PhXgNv9ske12BJjtn9C2w1cgO/0poExkfPwx0M+7SqKEsAiR/wmTA0LZAYrLl3l1/fcTgJUrve2a2RKulV+UToMvCZUVKwA+XdG7jCzMPOG3GuavW3skwCf+Mdt8JIhFXVzXO9yR/d//GDfdCpnDjqzZskpHI0xX4yrbnyIgoj7LvKXmy/CRiG/OYPvzslPWKXz4UhE6b/fsgHfI+cTzdScDfDyzbCi9kRHRvW18hAHv3efVyQsQftvhLS7NwJv+Vq8i0RH276IIyMaHAbz3h753yyeepzECggIkLkZpcAmWSICwBPby8pywAoSPgPCJ8ChA9AsQmShMtUmiAIlxkiZclawAcd+aC/Say7274w/uYyeln3tW6c/GU89Dhp0Z4X8qzoMQRAfiygERnQOSpACpWFpWlYdSTiTPPvMCFPbwksorRAe3lEu0C1aFCPr1XeCe+AMPdw7bCjHCRUB4AVKxvTAvOPny/C5YLHIx901vVA3DOwfEPwmdFotAP/7IEwir/ldy2osvzgS4/iqv/KFHADzgZ/Zy2zo3YuYsybwUOWECZeUXAF+s9HbgYu1+9hnAxx+W8k3Iso/B/eijniVzjbRV6xrjll9Dhom0Gh8UIHIoyyzBYid0v35G321sVbwpFwkQfjnT0ucL8NqJ3v3w2/Cu/y2AD5/z+82v6+KgWG83gI+er4/NxJ8a8La/axYvQMYdCvCu/z5gu19mYfap3j2EFR3CXbB+nYW/+/0auC7AqhorMcf/gMDCu7yIDx+dGb4ZwGdvef1qhRwQGUxFS9zwHBC5ud9QDkhcAoQXHQOyAKv9kytRgPQOnozzLyP2wi7BkjQfYTEUIFER1Hd9HwFy1DEAv/dOz2Y7VBnb7wBk0GBw//IY0Hvu6nOjFcuLuDM3WEEZAVJxHge3HW6UCIjonniRoiICIkpa54VGWAFScc+cSJFZ+iWKgFQIEH4ZEpcbUlGGnfXCRIb/Mc48BzLn+xGUGqbLnwMC++wL8OTjXqlcDsjlVwNhhyUSAwgTaTF/yjkgKxYuAveMk73a9/suwGOPet/ZEjB2TDL7bLUNwBv+cc787lj77AdGWzvAwEHAlhPS668uFcclWNEXfYgECDtjYfaZvdudsi1y2ad669q4t2uVESDvPVyAf/m5JHy0QrQkic/1EC3Z4s2ebe9a7i9/1gYvRra6IgMDRhowZDSBASMAntnFA0jGcRYJEOt0A+ybeyN8taZi/mQCnbd6AqQiAsLltrDk/S0vqr9df71zQFQIy+q+1PJRZMQwRkBiJOg4l2CFjYCIEs9RgPQOMAqQcMauU/isu+7w6E/jcN1VUrqPAOG2wiX3/AGye32n1K77EpdjMXBgz8GDUQUIOe9CoFf3jazwb/LDbsOrTYAItuFVLUB4rCqEw1nnAtx4jWc3InHB533wkS0+4b3K8siZP4Xs+f7mAjWssnDnb4Ce758DwnbE4pcxXXMjGEceA/STT7ylV2wJ1+dfAGURDXY2CDsjhAkV/kyQEJYfmITOn3uCu2AJkU16CVb+hxnovMNLBuc/oiTgECZRt2gUASJKGG87KwMdN3p92egQgP/80bsFXpiM2ofA0ifrH5K4/rcIfPicV6acFM92/1q9AuCN8xuLhmx7cwb+ebp3bxsfSuC9B/x74CM4nLgwTzbAudUTKSLB1WoCRCbSIbO8rzTmBECVr9DvHJB6BxHK5ByIEpRl3spfeexguOBuL+EQIyC9Bwjy7CgjQERsGlcOSCPErlMIrLPOMFi2rKtnh9FG7j/sNSpJJey9RC1fLUCqE8Ez7BTs6lPEBct/qk+6lomAkIMPAVrjFHLRwXyi/jbDEizRUqgoAoTvb0UfuTHgsaoQIEf9AOD3ftRKdMDiTt8AmOXvp8k3tsdeAM88VRNu4/JrIHOCd0hkrU/hp2cB/d1v+/40cCBkn32plFxf/SkdaPjll0BZvgdLUl+12hMnXV1A2QGHJRHjJ7rnBtTcAav8wB8+fDAIt+EV9Rd3waoYkqQFiCgCIjoILirvla+XESCdd3bDvKs8p513yGUSxvmzPzbYE+CDGV7LFWLk2wSWPl1fjORPysBaW3pJ8fz2wvzWuKJIB38Y4oQTCCz4jdeWMRDA9TcjXX8PgA+f8e5trW0B/vtP7zvf3ygREB7nPV8ZCF9+SHtOQtcVAeFtSOZARxlhUm2XKn2FfilA/vzCcvjeFV0lnEQ7UPEgxrYEixMgacwBiYswRfWgAFGNcG/9KkkluV54LTUiQETLfxoSINw5IKXzI7i35WUs+AiICJ+wAkS0FCpsQrrMUigVAqR6294yLhWHEu62B8DzvlfBAVchUg45AuCPfo4Gv4VvHQEC3/wW5P7o75xVY0AKd90B9DzvsEX+zBG201fmgINCm3gp94Ntgcz+77pAP/vUy/lgp6+zRPHySeyrvUMRh49YAz5d8iG4Z5ziOXt4Dkh4zCmli+Z+BjO+7nmo9da5h6lcZtkLnwMiOgguTJv1ysoIENESLF6A8N9FQmDUngSWzqixg9YhBN77o/f3TY4l8M7dtc8cGTIWYINdMzDMApjzM08Q5U8i0Hm7v0TqLAM6bvSiFezU+PJ3/jDEjY8EeM87F7Tiwy/3GnMQwOI/eT+LBBd/DggrM/HM+sspUYDEZbG99fRLAXLRHR/CVQ/23fpQRQTkpbmr4ftXemKHj3pUR1L2vuizUplWTkKP3/z61hgUiYgSYal3/0Htquq7znZVhVVVYSWqt88SrKpE5Oyhh5cuFeUiRF2CVZEDctyJAHf+2rvVOm/La/VFdH/C5VuCZPD+IkAqtu0VLIkDQQQE+OVVfGSEX0LGj0U14PseALk77xGaasUSLO7Qw2qBGretl05GX70K1h5EYNnf/wXFffcoNUFu/AXQs07zmjvmeIBydGb/KQDTH/b+zifjs9ynLbYoHVTIxA490xMymAMS3eUJez5F1IPggmwsSQHC9wUyAOCvOOOjIXyS+5gpAIt98+T7MWgDgP994P2FLy/zPTcCSuelsM+AtQBW/9f7Pu4ogHf9bYTHHgSwKECA8CehowAZCINH1Z4bKl9WRp6NlmUdDABTKaU5Qsh9tm17RwL7nwkTJmxjGMYvCSFDKKUrCSEn2bb95uTJk7Pvv//+rwghX6W0lFF3nOM4/wiabMzZeOSF5XBwQhGQmx9dCVfXEDsoQIJGqrHfgxxyFCCN4Vp9lUpS0cEJH7/ZAd1b+stiNAqQiuVfId+W8wJEFDGpKNPPBYjoFPWKCAgvQPjDBw8+BKDGsreKawVlSg79UcdC9vqbhZNJtARLtQAp3RsBYMsyeZvmsYKbbwPwT0hnB23CzTd4/eC2Jib3PgiZnScDZcu/3n0H3O/s7gmQf70NxoZjavZbJSewBnXwgooICA8e7/yLtoeNehBcEOMnKUD4vmy4jwFLnuybAM4fdFidwD50PMDn73CnKALAqL0ILH3Ki4DwAqT9PAPmX+3Vv/Z2BD6Z3TfysuH+AEumewiNP5bAQj/yggKkV1CEXZqVpK8QSYCMHz9+/Ww2+1oul9tm3rx5n1qWNcN13Ws7OzufLXfCsiy20dmJtm3PMk3zW4SQ623b3sqyrDMopZs5jnO8aZrMc3jUcRz2/7pbGiSdA/LyW6t7lnslGQHhH0R8foCMAy5TpimhxXUAACAASURBVB6pBYmAIEKM8ntQ21H7Jrq3oHaj9KkZsVblbOjihCQEiOhcDD4CUn3CuLH1ttKmk2YBwjvYFVsBc9GHinNABNGNCgHC7UjW56EakITefeWlADdd32fsmkKAiKI/3LbDzFazLCIS4qOKE0rOoSZfQZcAYedxrLmFd1Igv3sSnysgmwRcHkIZR5LlJgzaoK9bxy/B2vR4A/79W8/NEokm4ba3v8nB30/wDj3koyF8BIQ/W4QXIyQHsNkFWaBFgHfuLcAX7/U1ztyaAN3eMWLeQYs1vMHBYwG+XOQVYcnj79zjCZMtLzdgzoXeBSIBwve3ukzQEixWL+8nfPKG269zQGSpQSUvRBIglmUdQSnd1XGc41hnLMs6klK6CxMVfueIaZpHO45T2hOzvb19ZLFYdBzHGWmaJtt9eprjOKXsQfZvQsgltm2/Ug8Ynbtg8UnoqiMg1cbO8hvZR8YBlylTD2Ndzrioz/y9Ru2bqN+6+qyzXRVLsHRxQhQBwguLagez+Mifes6q4BOlK5Y5/eJ2cE/zEppFW+/KkH1cAkR0NkfYgwirl6Y1eg4I33eZLXlFWwFXCBCJCEhFnshWWwO88S/fsclAduarNRPJy/fa1BEQUWSHF2UDBnjJ8v5ZJzL2p9LR0MULaRAgMs/Njlu7oePn3nopXixEESAy0ZC2MwzouMkTBdaZGVizzRNl//vEhTnn970fkZ0O2Qhg5X+8XyvOGTkS4F0/H4TPYZERILx4YVsT54/rPYhUxk9AASLDKvXLRBUg51JK13Ac5+KSgVnWbpTScxzH8badqfpYlvUrSmnWj3rMZ2fYOo6zkBUzTZOZ0ZOO4/gbvtW+cVUCRAQT7/A+dflw2OtCL9eD33pXxTa8IlKRccBlytQzC11OsQyRRu2bDLGUxV706RVcgy6sVTkblmVp4QSRAIHzLoLcWeeUBkJmB6Y+AuSm68Flb8OrPv1RgIiEia4kdNH9VBxEKIqA8NENLgekYhcv/iBCthPaM/72PbvvCbn7H6o7OSuS0Ln6ZTYTCJ71AQ/loCVYfN85fKo3QDCuuREyx5bfBQbflSpO8H0DLbyQpADhIwIqIiCiSIrMc3P2T1bD4kf7hhPiEiAVeS45ANcLklREWLa7KVsSP+wYm9WfAbxxnrcN74QfEVjwK+8N63q7EvjoBe/7xocZ8N4fvHueeH4G3vZ38eIFSP7HBnTe5pXhBcgGuwN84K/D4ZPQ+fvkz0NhOGzwTZbUIjc32aqUZhMgojsPG2mrrkclL0QSIKZpng8Ag6sEyNmO4+xd/by2LOtmSumOhmHs1tHR0WWapg0Ae/EChBDyuG3bdZ8MTIDMdVbA1j/24nS8KGCH140e2deImNO6zcle+d+fMxSOuu7znmvLJ6GLBo+/dsYVw2HPn3kChG9XdA/8taJ7q2fubOBHjhwGy5f3btEqU6dMmbDtBk3MuH6v1We+7qh9E91nULtx9a/W5K4eY1Vt8fV6wif+c0B0ccKyuR2wegs/B+THpwHc9guvu7kcZJ9/GYz2iSUBUs4TMU49A9xf3tQHarazFL9sip0dUpiyn1du0CDIPvti6YA3tj1vz2ngv7gdin4EhD8cMDdnPpDRG0oPJ39/omv5MgPenA8wyquf/zu/O1bY7/z989/5enLPvADd/knoovpl7l90Ld8un4RuTLsS3KkXlPpbkfjP5Ybw41d44P6eyBRsux3AP2d7Y5HJQvaFV0o2IfqwgwiLh3/Pa+v8i8C9ykttDDum0oPPFSxzEW/TPFYVff/2XgBP19hqmEVAmN3X2C64Hgeq4ATWni5eWPTWZzBjJ28XLLY8SZRoW8aEOWvlXbNkyn80qwizjvK8bYNzvCc/MgDW4pZgzTzQO3SPCZPyQYRh22ICpFY9rN6yzYj6O/+W2hEQdj98nbW+y+S2fOWOHPz9h32XZvEOP8OTnVa+cgmFZa+7PQcj8gKB/84LBP47O7V8yWPeiIm2EeaXgW3M7dDFjxF/LT8u9eYs7ycwASIaj0bmfdA1jfooYe2s+j5U+Qoluw3qdL3fq5dcsTArAOxs2/YJ5esmTZo0oLu7+0GWhD5o0KAD58yZ84VPSGzJ1VSWG1L+t2EYF3d0dLxar00mQBZ/XIBxhy4uFfvbLRvAV0/xtlN494ExMGbdbJ/L+fLTL1sX9r/o455rt28bVBcCUVt8u6J74K8V3VtY/GXqlCkTtt1mKd/KfUsaY9LoSWl1blQXJxQXL4YPx44t3dnAKVNg1cO9W6+MuO02WOOkk4Avs+YDD8CKQw/1esJt3brOP/4BA7bfvqeH/DUjn3sOBu62W+m31a+/Dst22KH0fejll8PnF3qH2q31+OPw3333LX1ff9EiyIypnfBbC0K+LdG1ojIyf2d9K9+z6Dt///x3mWv5MjL3L3MPa1x0EXxxmef8D7vhBug629sal7+3EXffDZ8ee2zp7/z4ffnEEz1jkdl8cyjOndsDe9kmRKbMX8vXH3ZMo8xpfkx5rPj74W2Pt+Pht9wCQ0/2T1EPcRMqOIE1r4sXPl9ShAcmflJC4NC314ahG9Z/yx22/L9u+AJmX7qyD8L7/3VNWG9bb0nPR//shunf9F6A7nrnMJhwkOdzhG2Lr4evn29cVKd9/5fw0o+9F6+bnzYI5v7if6XvrJ7yvYm+7/HgcHjm+96LV5nvX71uDfjbOSU3D/gT0nn8u/5TgD9u7m1fZR07AOy7PYG21TmD4I3rvHvb8fIh8NqFHrabnzoI5v7S+zu/hGzbCwfDPy/3dkQdPTkL78/0oir8Z8zuWVj8bN+/izDsU4HgDzLjIVuXynJh7azWvajihUgCpL29fVSxWJzFIhsjRoxY0dXV9QQA3Gbbtr8vQYl47qGUDnQch+2F2XNMqGVZZ1FKJ7LlWJZltVFKnxo+fLg5e/ZsP3hXe0iiRkBkIiZ8y1EiIFGNqlHF21/bLZFLjaiPaDwaiSqJsAlqNyqmzdiuiredujihIgLC75bEIiB/faX0JlgUJTCuuQHccz3HtjoCIopKFP/8Jyie+ANvWLklOs0QAeHf0ov6LHqTz0d2eCwqcFAQAeHvh78HPu8jw0eafnMXFE/w8K+O1JQjWHwUA762E8CrpXddXgRk5qy60QH+Wr7dZouAVGyAwJ1HwzApH8Apy10q33Tq4oVmiIAseqwAs8/0HGDmkO/66AAYbhkQ9s10lAjIu38q9EQc+GhClAiI6AyR6nNPyvbHR5T4yBEvKPgIyMRzDXj7mvonmAN731zWFtx3PgIydgqBRQ/7BxfyUSouGhVmjpRXLGAERBY1cblIAoRVm8/np7BIBnuP6O9kdZ5pmndQSqdTSjsymQxbasX+88+rBGrb9raTJk3KdXd331rehtcwjNM6OjpmBnUpag6IKF9D1K5MDojo/JGgvgT9rjM/QMfp3GUBoqPttGGtcl2nDk7gc0Aqko/PPAdy519UmmqNnAMiSgwvXHox0Fv6LuFKMgmdOcP8EqzCVt4SNNG5IRWHCb5Re3kYf/I7nw/D4yBqV6Z+mbNO+HsAfkvl8y4EevXlHm0Kzg3h75mJCPcIbxkV8DkgU74PudvvqEu//LW8k98MOSC8fYu+MztsRICo2JiiDLQOXuB3kAx63rLfw66X58uLckDmXdMNnXf0vHuFLadlYZPDs6HbkskBEeW8iA4i5He7En0XLcESCRDRifD8QZD2bQWYf2PfqMTml2Rg7iUeVvwJ6Xydot2x+PFdbzLAR743yQscfowaOb2c9xNWvk/h6W/Ee8hlPRtt1EcJa9PV96DSV4gsQGQmdZxlUIDEiWbtuho19DjuTFfbaWxXpbMRhy3I1tHnIEJ+m1JuN6A4BUjF7liCJOiwzmrYXbCSFCCilwMygoIfR5nyIgECgnwHkfARCpAfngS5K67pXwLkT4+BsfPk0j3z/RKKkSbbhld2LsdZjvFCkgKEd9T5JPTFj1dGQCazCIjpRUDCOLBxCRB+G14VAoTHgXf4eQHy8au1c2eqBcKLU7ylWfx9bnKkAe/c6yfU81GPHAD118+M2Bzg094Vlz1mxd8bChC52YYChMMJBYic0UQppcsZFzk5Ufoie62uPutst2UFSNU2peXdgOIUILyTTLilL60aAZGZm2EFlEg4VAgQfkMBfscnLgLSqgLko4cfg8JB+3sUxjZAeHpmaVtdkQCpOB2+ybbhleXhOMs1iwDhhQN7kz9mXy9PNUkBItqGVybqwUc6eAdeFAERRUx4AcL33TwpA87tXtSDTxLn742PgIgSzyuECX9KOydMUIAEb8RQPQdRgNQRIDLLn/hlVLgEK5jidTnFMk5O8N03VkJXn3W227IChN+mlDliz71cOvNBRoAYVaeXi5xq3kmuWId/9Q1Az/PzSQTLnEQWGtaB5yMgUerkr613D0G2Gvb+pQSI6LyPX9/Vcz5LqwqQDy6cCu4VvVtAl4W0UIAIhLcsI6p0NGTvIc5ySQsQ3mHmDwSM6yDCKBEQ0Ta8zSBARDkjW0zNwpvT/NwZLndDJHzGfNeoudVw25mZnjNQ4hQgSW7XH8U3Cit0UYDUYaHqCAgKkDgp26sryNGIv8XeGnW1ncZ2W1WAVCxL4ZaiiARIxcnbAwdC9pkXew5wkxEghM9N4HbUSnIJVssKkCoxCau9JRmiM0R4zCuWYO1/IMD0P3swnXUu5M77WV0aa4YckI/+/HjlFtDMLv0toMuHQgpPfueEtyxfowAJH5XgnbtmFiDNHAERnSEiEiYiAcILDT7vAwVIuKV+KEBQgGgVArqccZ3iR1efdbabBgHCJ+MKBcgxxwP93W97WIc/wE1KgBx8CND/1/f81LACRMZRFCWDy1wrU6bZIiC8mOR3K5MRIBVLuQ49EuAB/8jkfiJA+I0VMlwOSEX07b6HehLtKw7HrIrkyYw9CpDWFSB8ErpMDohoqZWKJViinBGRMJFZ+jXmQAKL/+ztfEUULcHCCIgMq9Qv0++T0MNGQG4/ZQ046RZvj+qw14pOQpepp5Gh0umc6tiJCgVII1bS2DWt5GxUJ6FXOK3cbkBCAcItm/IOLnyl9KaZfaQECJcDwp/FoEKAqJ4jUQSIjCWGTULnx7LikMSnX4ByFEBqKVc/FyC8LckIEH43MJlxKdtVq7yUKM3dhJPQmzkC0l8EiCh/hBcjohwQ/tpR3yaw9GlPgPAffoz4nBSZOcJHu/gldjLXxlGmUX8Ql2DFgb5fRyNLsF6auxq+f2VXqYaBOYAZV4yAtrF9DyysdZuibXhViQ7+Hho1uKhw62pXtXNVDxddfdbZbqs4G5EFyFXXAz3/J5555FjOyEuBS7AqHOn7H+o5NZtEyAGRnbcqbUa1AOH7KCXubr4d6OknlS5DAeKdeo8CRG6moADpTTiuWIKVA9h1et+duGR2xOLLyEQieFHAO/x8PosoyZ0XHXw9FUutBNENPsrDL8dKowCRmy3iUipfVqYiAnLzoyvh6ge90zLZ5+ofrAFH717/BPRyWRQgUc033PUqnSsUIL0IqCSVcCMevXSfbXi5vAFVS7BEAiTKLliySKicI/1RgIgiTa20BAsjILKzo7ccCpBeAVKdhF7rLJJmECCixHNegIiSzfkyvADhDyvk+7jT73Ow7tfYdllyn/4aAZHrHQoQKZwaiYC8/NZq+N4VvRGQp68YARZGQIR4q3RwggZZV9tpbLeVIiAVW5ZWnctR60A23tHmoxbsgLvssy8FLsFCARI0k4N/l4mAACcmRREQFQKk4kBGLsKlalkdj1aZi/gcEBQgwfZUXQIFSLgIiGibXNHfVURARInnMhEQXlyIRErFIYkDASY/4kWCZD4oQGRQClcmFREQPorx0M+GwTc2Y4e2y30wAiKHU1yl0igEdOTbtFoEpHrL0rI9ik6E5p3fesm7IicZBUj0GS/CtuKQR35XsWdegMIeu5Yaljl1PUoEBAVI9PHVXQMKkF4BwueAsPMytpzq+UCi/ACZv6sQIOaPM+Dc1vdMEFHyO78cixcgomVa+R9map5KL2OrKEBkUApXJnUCJGzuBi9A/u/WNWHU2vIhu3BD0bd02pxxhkDa+qyzvy0VAeG3LA0ZAeEFSHXybtoESD3OittWRdgWLr0Y6C039bmVLAqQEiaYAyL3ZNUpQPjlPc1wDogoB0SEZFgBItrqViYHhL+WP4hQlAMiEj6i/BS+foyAyM0dvpTKl5UoQALGAwVIeIONckXcTo7svaSx3VYSIPxyFX7ZDltelf3BD/uYgSgC0ogACesYy9qkqFyr2CpGQGqPMC7BijpDvOuTFiAi51ZGgMjkI8R5EGE5BySKAJFJBpcRIDI5HWEjIDIiRQZzHh+MgMQzLyvETfxVqq2xkRwQXkRgBCR4fHQ5OBgBCR6buEqofKsR1z3K1tMnCf3cCwGuudy7nB3IxnI62idWVIcCRBbd3nJx84JMDkjFrmJcBEQmF6NVl2CJtjKuF8mTGe1W4gQdAkS0vEckHD6aVYRXj+4uDY0hkY/A18PEzph9e3fyLM/NRXM/gxlfX1Wqk8/diCsCwtvRGxevhnf/4PYxLdFWuqJdsEQREFE9IuEjs0MX7oIlwwSVZVTyQr+MgCxb1gVhDoFBARLO6OJ2NMK0rqvtNLbbqhEQUudgwbItqhIgMo5xmPlQq2yr26poiREfaZLBOS4BwtolW20bddikrw+KgKAAkYOyWSIgouVM9m0FmH9joaczQVGJxY8XYPaZXnljAMDkR3sTqIMECJ8Dwhz4tpNzdUGUOTui4n5yAK6npSCsAOGjFTLLrmTO+JCJgKTlHBC52SIuhQKEw6YRUokiQFjTrf7ArzY9Xf1FrKNShfz1KklF/i7iKdnnHBD+YMGqXa1QgDSOeVK8oESA/PAkgDtu9zo/7UrInXRKXSD4e0AB0rjN6LyyEV9BxvHm+8SXF23xKqrz41eLMOso+QjIvGu6hQnUYQQIc843nlL/HDQZHPiIjEg4MEzW2rLvLlMy54CIll1VnPHBnQOCERA1s02lr4AREIkxS+rB2yxCQFd/UYBIGGNMRVSSSky3KF1NtQCpt6sVChBpWPsUTIoXUIAAsJ3xRNvwYgREzoZ1ChD+pGyZhG6ZfIS4IiAqBIgo6hFWgIgiF/zfJ52fgXlXeTtliXbBwgiI3ByRKaXSV0ABIjECST14UYBgtEnCHGMpopJUYrnBEJXUEyDVSeUoQEIAW1U0KR4UOdiRlmC1UASEHxYhVm/MBzLaOzld9tNKnMD6HFWAyIgCUQQkrACRWQ4UJQfkg78W4e8neNEWJhY2+Gb93TzDRkAm/3kArLmFF+molyxftkW+flGkQyQieAHCl8EIiOxMD1dOJS+gAJEYi6QevChAUIBImGMsRVSSSiw3GKISlQJEdBsVCdQhk6NDdK1m0Vbno7gECF8PvzOa6GwYHuxmXoKFAkRuBjUiQMImhjezAJHZCliEZDMIEFFUpRkEiIw4lbNS+VI6eV9VvigKEInx1znwug6p09EuGwrEWsIgYyiSdgEicjZFEZNqyFGAxGCEgiriEiDuSy9A8aD9vVa4Aw1lxri/CBCRGJFJ0q/1wkuVo6HOWsQ1NyJAwiaGJylAZJZgvT19Rc28EpmoBI9kfxQgfBRJFPGR6ZfIosKK07htXqdvpIoXUIBIWInOgdchBHT1FwWIhDHGVAQFSC+QFadeP/0CGFsH73iEAiQmQ6xRTVwCpHjT9eBeeWmfFlCA1B67VuIE1sNGBEjYxPAkBYhMEvqsS/8Lb9/Qd2ettAkQmbNXZJa98TMlrDiNmyF1+WUqeQEFiISV6Bx4FCASAxRDkTSOsaq3GjEMR6gqGlmChRGQUBCXCic1R+ISIO5LM6F40H5eRwcOBFjlnY8gEx3ACEh4+2i2KxoRILygCLvMRnRQnUwSuowzrCsCIsKBd/K3vykLG37H21lLBkOZHBB+CRa/y5ZoCZbonBE+ET5KBCSsOI17PiTFv9X3jQKEQ6QRUsFteMNNBV2GnqSTU2uSpUnsqSSVcNYWvbQOAcLbqmi3oug9E7+pbmVbjUuAVNTzp8fA2Hmy9JDw1+bmzAcYFS6hW7qhGgXL/BvWrkQHO8reSytxAutzI75CFAdVtQAJm4QeJQdEZrmRSBDJXCsjQLaYmoU3p/Wee+Ku9iw57DkjcQkQGWElO9caKafLL1PJCxgBkbAEnQPfyo5GLegRawmDjKGISlKJ4fZCVYECJBRcDRdOam6qECAyUQ8emP4oQBoeWP/CVuKEVhcg1dvbluem6CT0sEuwZJYbiZaEyVwrI0DGHWYEnrTO777F27+KJVgigRl13slenxT/1no5q2q1BAoQidHXOfAoQCQGKIYiaRxjVaQSw3CEqgIFSCi4Gi6c1BwRCZCwkYgoEQEUIA2bSdNc2CwREBEgYaMt9URE3AJEZrmRKAIic62MAOGXXbGT38sREH67XX67YxQgaqaeyhcTKEAkxiypB28t5YkCRGKAYiiSxjFuVQHCkoyL3961ZBUyb74bSUJndTe6VCaquba6rTaDAOHHd9myLqA06qjJX6/TrlqFE5opAtIfBYjMcqMkc0C2+3kWZp/pLcdCAZI8H6niBRQgEs+FVn/gN4vwaYaHvi5nQ0e7qkhFYkrFWqQ6AoICJFZ4eypLigerIxfGhhuWTgYPO0eiREDSykWtwgkoQABkkrKjiCNegPBLoWQiO6Ldw+qdqP7iFC8JBAUIChA1TziJWhsJq2ISugSwXJGkHI1ad6Wr7TS22yrORlQB0qijmkabaUQIhGMfABQg0JDgCotzrRdPrcIJKEDSLUDi2nmMnyOYAxKVYfpejxEQCUzR0ZAAKaYiiHVMQAZUo3JdZzI96G0FBUgyiCc1N1GAoACJw6IbeVkp8/ZeJmogyk0QObQy2/AmmQMig4PqCAifA8JHPWQiIChA4phBXh0qfYXIAsSyrIMBYCqlNEcIuc+27ctqdd00zWmEkKJt26WTocaOHTt48ODBHxFCOsvlbdtmJ4DVXW3bCKlgBCScMSblaGAEJLmzFZJ826mDE/gtS8MuwcIIiBw/JMULKEBaU4Do4IWwy/ZkHG8UIB4CcQkQPr+jYuvdHIDb7bWFAqQ1fYVIAmT8+PHrZ7PZ13K53Dbz5s371LKsGa7rXtvZ2flseZKOHz9+RDabvREAvk8IubYsQCzL+jql9GzHcQ6Qe/x5pVCAhEGrsbJJORooQFqPVHRxQhQB0tgs0Tt2SSyFqiVak2gXBUjrCRBdvIACxHPxwm7DKyPEogiQirNCuB2uRFvvhhUgMiJRJuokiljJRLgafa6IrtPllzVtBMSyrCMopbs6jnMcA82yrCMppbs4jnN8GUTTNI8BgHUBYCgfAbEs60xK6WHsb5TSAiHkXNu2ZwUNWiMCJKjOoN91DnwSD3xdjgYKEL1OrIr13ro4AQVIEItF/z0pHkQB0noCRBcvoADxBIiMoBA52yJHPYoAqT4rpNx2xda7ESIgKECi8325hmYWIOdSStdwHOdiX4DsRik9x3GcPau7b1nWVBbAKEdATNM8DQAGOo5zXT6f35oQ8sTAgQM3mzt37n/rQYcCJD7Dajalze4nKSenWUSXzv4qEiBaOAEFSOvwAgqQlhQgWngBBUhzCpCKs0IEZ3yItt6VyQFBARLf86BpBYhpmucDwOAqAcKWVe0dJECqfzdN8xFK6Z2dnZ1PBAmQ5cuT34Zs5MhhgO3GZ9T1xA9inQzO66wzPNISzFp32QycwBzY7i3bS7fHDq8jozdUAigjZrTV+KGtHj+2DW8jOEe1gzSOrwpOYBbSDLwgY6ksUjDj66tKRdkym8Gj5Cmy4tpZA2HwBvWvDdsWizjMPNDbipZte7vWlkZPl8q2uuitz2DGTo3dP4+PzL1V3M8jA2CtLbz7kbmWL7PT73Ow3k6ZPteyPvL9rfV9Twmcw/arnnjpsY2Q7crYXlAZnXykihfkZ1cNdKqXXLEwKwDsbNv2CUECxLKs41zXfbqzs3MxK2tZ1mMAcJtt2zOCBEjQQOHviAAiEIwAIYzS4v00AycUFy+GD8eOLXVs/UWLIDNmTLydxNr6BQJoB+GHSQUn+M/3iuXZzeorfL6kCA9M/KQE3KFvrw1DN/QcY5lP2GvDlv/on90w/ZsrSrey/1/XhPW2zfW5rbB1ivolU4/ofmSuFZXh/876yPe31nfVY8TjI9MvGTvpj2VU8UIkB6S9vX1UsVicRSndccSIESu6urpY9IKJiOnVIFcvwbIs61cA0GXb9jn5fH6iYRgzBg0a1D5nzpwvggQIRiLUmrAupc16pavtNLar4q1GM3BC1DffsrMrjTbTSCRCFk9RuUZxjmoHjbarq79xtKuCE9h9NQMvyOAj8/a+Xj1hbCZsW80WARFFfGT6JSrD/10UAdn+piy8foZ3KnrYCIiMDcQ1vlHbqr4+jG3F2ba3TDz+1RIlfy/qjebz+SmEEJbfMQAAHnUc5zzTNO+glE7nl1NVC5BJkyat3d3dfTchZFMAKFBKT3Mc56Wg+8EckCCEov+uKy+hLEDSlHivC2uV6zrTwAloq9F5RraGRudIo9srl++r0XZl+1VPcOniQBV5YeV+9gdeCJusXctJVDV2Uc4BCWuTMjiIDuYLey2f5C46IZ3PBzEGAuz6yAAYv9MICJvjExaHJMc36N508pEqXogsQIJAi/t3FCBxI9q3Pl2Gjk6d+rHlnStVpJJcL7yWdHAC2mpyo9woH6EACTdGKl9KhLuTeEo3wgsyznO9u2vUVmV6XO/eyu0umvtZTw5L2G1m+XuQwSFJAZL/YQY67yj23OKWl2Zhh9PXQgEiYzgRy6jkBRQgEoOjklR0kVkztotOnYQxxlREJanEdIvS1TTiaEhXXqcg8kIcKAbX0SjOKECCseVLtBInNPpiQsbxNQWSPgAAIABJREFU1vXsTLMA6RMBeXQAjP8aRkDCzfDGSqvkBRQgEmPS6ANQouq6RdLWLgqQqBYjf71KUpG/i3hKogCJB8egWvobH6EACRrRyt9biRNQgAC0UgSE33q3vGuWqqVuugRm0GzVyb+qVkugAAkadTybQgKh+IronGRpIrRWcjZQgMQ3/5rx4dsoJ6AACWcXrcQJKEBaV4AwYTVkNIE0Pa91v5xFAeJzqQ5no9EHYDj671s6be3qnmRpIrRWcjZ0cALaalR2k7++UR5EASKPcdmeVTka4e4kntI6eKFRW5XpcZqXYPEREBQgyZ+Dp4oXMAIiMfNVkkorvXGUgDKwCGIdCFEsBVCARIcRbTU6hjI1IM4yKEUv00qc0GgEJCqKKm0VBYh3CCMKEBQgUedpw9e32lsNFCCVCKgkcMS6F4FWcjZ0cAJGQBqm8NAXIieEhqyhC1qJE1CA4BKshiZBwEW6uEj38wYjIL5h6HA2dBld2trVPclwCZYKylZfpw5OQFtVP67lFtLGgzr7q8rRSM5aelvSwQs6xy7O55fMbmCibXhlxlpUv+zfMQdEBuV4yqh8MYFLsCTGqFVIRaKrpSK6+quzbV191tluqzgbOhwNtFVZNoleTuccidOpk0VCZ39bhRNaMQJSz3502IwKASLqY7UwQQEiyybRy6EA4TDU4WzomNxpdHDS2GedttUqzoYOTkBbjf5gk61B5xxBASI7Ss1XTgcvpMlWUYAka/M6bUuVr4AREAkb0jnwaXoAolMnYYwxFVH5ViOmW5SuRoejgbYqPTyRCyL/RoZQqoJW4gSMgEgNeeRCjc5NmSVe/M1hBETfyhSVvIACRGIKNjrJJKquWyRt7aJTF9Vi5K9XSSrydxFPSRQg8eAYVEva+CiN/VX1pjPItlT8roMX0mgzjbwkRQES3uJ12pYqXkABImEHOge+kckt0aWmFD4oQKKOnPz1KEDksRKVRF6IjqFMDYizDErRy7QSJ2AEJLo9yNTQ6NxEASKDbmWZRrEO31LfdlGA+JjgW42o5hR8vS5DRwESPDZxlWglZ0MHJ6CtxmWJwfXo4qM0tqvK0Qge5fhL6OCFNNpMIy9JUYCEt3edtqWKFzACImEHOge+kckt0SWMgFQhkMYxVkUqUe0v7PU6HA0UIGFHqfHyaZybuni/VTgBIyCNz7cwVzY6N1GAhEHZK9so1uFbwgiIEDMdzobOgdf1INLRru5JpqPPOm2rVZwNHZyAthr1sSZ/vc45gpwgP07NVlIHL6CtylkBChA5nPhSOm1Lla+AERAJO9A58Gl6AKJTJ2GMMRXBJVjRgUReiI6hTA2IswxK0cu0EidgBCS6PcjU0OjcRAEig27fSIQufxAFiD8W+FYjvOGGvaJRUgnbTq3yutpOY7uqSCUOOwhThw5OQLEcZoSilU3j3Gw1RyOaBTR2tQ5eQFuVGysUIHI4YQQkPE5Kr0BSUQpvqXJdJKqzbV191tkuCpBoc0nn2OlyULHdaDYjc7VOu2oVTsAIiIylRS+TlK3iOSD6/DKVkVFcgiUxB5OaZNW3krZ2UYBIGGNMRVSSSky3KF2NjpcSaKvSwxO5YNp4UGd/UYBEM1edY9fKLwdQgKAAiTYzY7pah7OBpBLT4ElUg1hLgBRDERQg0UFEW42OoUwNiLMMStHLtBInYAQkuj3I1JDU3EQBggJExh6Vl0EBohxiXIJF1WNcbiEpAq8VXWuVt506OAEjIOmYI638VrmVOQEFSDLzM6nnFwoQFCDJWHRAKzqcjaQmWa0HQpoegOjUJTfFWultpw5OQFtN1lbTxIM6nzet8lICBUgy8zMpW0UBggIkGYtGAdKDQFKTu1mEDzp1yU0xFCDRsU7b/MT+RrcZmRp04owCRGaExGV0jh2K9GhjJ3O1rvHV7Rup4gVMQpewOl1Gl7Z2dU+ytBG4KlKRmFKxFsEISKxwCitLGx+lsb+twgkYAUFOUIGALk7Q7Rup4gUUIBJWqsvo0tau7kmGAkRiMjRhERQgyQxK2vgojf1V5WgkY6GVrejghTTaTNqemzr6q9s3UsULKEAkmBFJRQKkmIog1jEBGVANLsGKjjPaanQMZWpAnGVQil6mlTgBIyDR7UGmBpybMijFU0Yn1ihA/DHEtxrxGHO9WnQZum6Vr+PNhi6sW8nZ0MEJaKvqeajcgs45gpyQ3DjH3ZIOXkBbjXsUa9eXNpx1P2+aVoBYlnUwAEyllOYIIffZtn1ZLZMxTXMaIaRo2/al7PfJkydn33///V8RQr5KKXUB4DjHcf4RZL5IKkEIRf9d1+TWPcnQ2YhuO6yGNHAC2mo8tiJTiy4+SmO7qhyNtPBCGm0mbc9NHf3V/bxRxQuRlmCNHz9+/Ww2+1oul9tm3rx5n1qWNcN13Ws7OzufLT9Yxo8fPyKbzd4IAN8nhFxbFiBtbW2nu667ueM4x5um2Q4AjzqOw/7PxIjwgwJE5pEdrYwuEtU9yXQQiy6sVUVA0sIJaKvROCbM1TrnCHJCmJESl00LL6CtxmMvQbWkDWfdz5umFCCWZR1BKd3VcZzj/DccR1JKd2GiomxApmkeAwDrAsBQPgJimuZzADDNcZyXWVn2b0LIJbZtv4ICxEMAJ1kQDcX3e9qwViVA0sIJaZyfaZwjKEDi4di08ALOkXjsJaiWtOGs+3nTrALkXErpGo7jXOwLkN0opec4jrNntQFZljUVAGg5AmKa5nwA2MdxnIW+ALkXAJ50HOePKEBQgCxb1gU0JSeS63JyVJCKZVmp4ATdDwRdNoPtBrlG0X/X6Vyp4ATfN0gFL+gcO5yb0edeUA26xlf380YVL0RagmWa5vkAMLhKgJztOM7eEgLEBoC9eAFCCHnctu2HggTI8uXJO6cjRw4DbDdoekb/nU1wxDo6jkE1eEQ6PNL8r9VGWjih/EBAWw2ytOi/IydEx1CmBlWc4L9gRF9BZhAaLINzpEHgQl6mC2fdzxsVvkKpTyHxryhuWVbFkisWZgWAnW3bPkFCgLAlV1Nt257lE9RzhmFc3NHR8WqQAIlyz3gtIoAIeAgQwug03g9yQrx4Ym2IQJIIqOAEdv/IC0mOIraFCMSLgCpeiOSAtLe3jyoWi7MopTuOGDFiRVdX1xMAcJtt29ODBIhlWWdRSieyfBHLstoopU8NHz7cnD17dneQAMFIRLzGVV1bWlV+2t5mq3irkRZO0P1GKm22iv1Vy/lle1bBCazutPCCrmcntqt+fujkfJ1tq4yMRhIgDJR8Pj+FRTIAYIC/k9V5pmneQSmd3tnZyQRJ6VOdAzJp0qQB3d3dt5a34TUM47SOjo6ZQWaEu2AFIRT997Suc0zbGlpV6zrTwAm9DtswwHyl6JxTrwZdfJTGdlVxAvoKOEfiRCBtc1P380YVL0QWIHEalUxdKEBkUIpWRtfk1j3JUIBEsxtdV+vgBLTV5EZbFx+lsV1VjkZy1tLbkg5eSKPNpO25qaO/up83qngBBYgEMyKpSIAUUxHEOiYgA6pRtQ1vMndf2YoOR0P3A0HHQxDnZjLWrRNnVY5GMsjp5wWdY4ecoN7KdI2v7ueNKl5AASJhs7qMLm3t6p5kaSNwVaQiMaViLYICJFY4hZWljY/S2N9W4QRmxDp4IY02k7bnpo7+6vaNVPECChCJZzeSigRIMRVBrGMCEiMgyoFEW1UOcakBxDk5nFU5Gsn0ACMgmI+m1tJ0cZFuHlTFCyhAJOxVl9GlrV3dk0zHmw2dY6yKVCSmVKxFdLzpRFuNdQjrVqZzjiAnJDfOcbekgxfQVuMexdr1pQ1n3c8bVb4CChCJ+ZI2Y9fVX92TDJ0NicnQhEV0OBpoq8kZgi4+SmO7qhyN5KyltyUdvJBGm0nbc1NHf3U/b1TxAgoQCWZEUpEAKaYiiHVMQAZUg0no0XFGW42OoUwNiLMMStHLtBInMDRQgES3iaAacG4GIRTf7zqxRgHijyOSSnwGLapJl6HrVvk63mzowrqVnA0dnIC2qp6Hyi3onCPICcmNc9wt6eAFtNW4R7F2fWnDWffzBgUICpBkZrbGpE/dkwydjcRMLNaGdDgaaKuxDmHdytLmbOjsrypHIzlr6W1JBy/oHLu0Pb/S1F/dzxtVvIBLsCSYEUlFAqSYiiDWMQEZUA1GQKLjjLYaHUOZGhBnGZSil2klTmBooACJbhNBNeDcDEIovt91Yo0CBCMg8VmyhHOq4+2CbpWvo8+tSCqJGapGTkBbTW6Udc4R5ITkxjnullCAxI1o3/pwbqrHuNyCTqxRgGh0NnQOfJoegOjUJUtmqkgluV54LelwNNBWkxtl5N9ksMYISHSc0VajYyhTQ9pw1v28UeUr4BIsCWtPm7Hr6q/uSZYmsddKzgYKEAkSi6GILl7AdmMYPIkqWokTdL2YQFuVMLQYiqQNZ92+EQoQjIDEMG3lqtA1uXVPMhQgcvbRbKVQgCQzIrp4AdtNbnxVORrJ9KCyFR28gLaazEinDWfdvpEqXsAIiMR8SZux6+qv7kmGAkRiMjRhER2OBtpqcoagi4/S2K4qRyM5a+ltSQcvpNFm0vbc1NFf3c8bVbyAAkSCGZFUJECKqQhiHROQAdW00nILHY6G7geCjocgzs3k5qau8VXlaCSDHEZAli3rAkqTQxs5IR1Yq+IFFCAS9oOTTAKkmIog1jEBiQJEOZBoq8ohLjWAOCeHsypHI5keoABBAaLW0nRxkW4eVMULKEAk7FWX0aWtXd2TTNdbR13tqiIViSkVaxGMgMQKp7CytPFRGvvbKpzAjFgHL6TRZnQ9v9LUrm7fSBUvoACReHYjqUiAFFMRxDomIDECohxItFXlEGMEJOHlNKocjWQsBSMgGAFRa2m6OB8FiNpxla4d32pIQ9VwwbROsjS9UcEckIanR8+FuuYJtht97GRqSCPOKEBkLENcJo02k7bnpo7+ogCJNi9juxoFSGxQNt1SC92TTAex6HxgtYqzoYMT0FbV81C5BZ1zBDkhuXGOuyUdvIC2Gvco1q4vbTjrft6o8hVwCZbEfEmbsevqr+5Jhs6GxGRowiI6HA201eQMQRcfpbFdVY5GctbS25IOXkijzaTtuamjv7qfN6p4AQWIBDMiqUiAFFMRxDomIAOqwSVY0XFGW42OoUwNiLMMStHLtBInMDRQgES3iaAacG4GIRTf7zqxRgHijyOSSnwGLapJl6HrVvk63mzowrqVnA0dnIC2qp6Hyi3onCPICcmNc9wt6eAFtNW4R7F2fWnDWffzBgUICpBkZrbGffd1TzJ0NhIzsVgb0uFooK3GOoR1K0ubs6Gzv6ocjeSspbclHbygc+zS9vxKU391P29U8QIuwZJgRiQVCZBiKoJYxwRkQDUYAYmOM9pqdAxlakCcZVCKXqaVOIGhgQIkuk0E1YBzMwih+H7XiTUKEIyAxGfJEs6pjrcLulW+jj63IqkkZqgaOQFtNblR1jlHkBOSG+e4W0IBEjeifevDuake43ILOrFGAaLR2dA58Gl6AKJTlyyZqSKV5HrhtaTD0UBbTW6UkX+TwRojINFxRluNjqFMDWnDWffzRpWvEHkJlmVZBwPAVEppjhByn23bl/EG1NbWNtp13fsIIetTSpcSQg6xbXvZ2LFjBw8ePPgjQkhnubxt29syf6KeAepwNtJm7Lr6q3uSpUnsqXQ20sAJaKsybkI8ZXTxURrbVeVoMEtIAy+k0WbS9tzU0V/dzxtVvBBJgIwfP379bDb7Wi6X22bevHmfWpY1w3Xdazs7O58tP3pM03yEEPKwbdv35fP5Yw3D2N227cMsy/o6pfRsx3EOCPOYQgESBq3GyuoiUd2TTAex6MJalQBJCyegrTbGLY1cpXOOICc0MmJ9r0kLL6CtxmMvQbWkDWfdz5umFCCWZR1BKd3VcZzj/DccR1JKd3Ec53j278mTJ2eXLl26zLbtkQBQBICMZVnL2b8tyzqNUnoYIaRIKS0QQs61bXtWkOGhAAlCKPrvuia37kmGzkZ020kLJ6CtRrcV2Rp08VEa21XlaKSFF9JoM2l7buror+7njSpeiBQBsSzrXErpGo7jXOwLkN0opec4jrMn+zd765HL5V63bXuj8sPGsqz/ZLPZHYrF4vdd1x3gOM51+Xx+a0LIEwMHDtxs7ty5/633YEIBIvvYbrycLhLVPcl0EIsurFVFQNLCCWirjfNL2Ct1zhHkhLCjVbt8WngBbTUeewmqJW04637eNKUAMU3zfAAYXCVA2LKqvRlg7e3to1zXfa1KgCwqFArb/vvf//6INzK2VItSemdnZ+cTQQJk+fIuoHUzRYLMN9zvzNhHjhwG2G443BopjVg3glr4azwCHx7pBUStVtPCCeUHAvJCeNsLewVyQljEGiuvihPY3aSFF9BWG7O9sFelDWfdzxsVvkKpT2EHni9vWVbFkisWZgWAnW3bPoGV45ZgrQ0Arr8Eiy3JWseyrGNc1326s7NzMStrWdZjAHCbbdszggRIlHvGaxEBRMBDgBBG4/F+kBPixRNrQwSSREAFJ/jPd/QVkhxIbAsRiBEBVbwQyQFhEY5isTiLUrrjiBEjVnR1dbHoBRMR08t9N01zOiHkT7Zt32ua5tEA8F2WeG5Z1q8AoMu27XPy+fxEwzBmDBo0qH3OnDlfBAkQjETEaFk1qtL1dkG3yk/b22wVbzXSwgloq2o5iK9dFx+lsV0VnMDGMi28kEabSdtzU0d/dT9vVPFCJAHCQMnn81MIIVMBYAAAPOo4znmmad5BKZ3OllPl8/kxhmHcDQCjAGC567qHs6jHpEmT1u7u7r6bELIpABQopac5jvNS0GMNc0CCEIr+u671leVJlrZ117r6q2pdZxo4AW01Os/I1qCLj9LYripOQF9B1tobK5dGW9X13NTRru7njSpeiCxAGpsujV+FAqRx7GSv1EVmuieZDmLRhbWqJHRZG4uznA5OQFuNcwTr16VzjiAnJDfOcbekgxfQVuMexdr1pQ1n3c8bFCC+HSKpqJ/guia37kmGzoZ621LRgg5OQFtVMZLobOi2K1WORnLW0tuSDl7Q9ezEdpOxMF04tyovYAREwm51GV3a2tU9yVCASEyGJiyiw9FAW03OENLGgzr7iwIkml3rHLu0Pb/S1F/dzxtVvIACRIJvkFQkQIqpCGIdE5AB1eASrOg4o61Gx1CmBsRZBqXoZVqJExgaOl5MoK1Gt0OZGtKGMwoQGatIoAySinqQdU1u3ZMsTW9UWsnZ0MEJaKvqeajcgi4+SmO7qt50JmctvS3p4IU02kzanps6+qv7eaOKFzACIsGMSCoSIMVUBLGOCUiMgCgHEm1VOcSlBhDn5HBW5Wgk04PKVlCAqEcd56Z6jJvhRYwqXkABImE/OMkkQIqpCGIdE5AoQJQDibaqHGIUIDQZjMtCT5WjkVwvMAJCE7YZHRGBtHGv7hcxqngBBYgEM6bN2HX1V/ckSxuRqiIViSkVaxEdbzrRVmMdwrqV6eKjNLbbKpzADEoHL6TRZtL23NTRX93PG1W8gAJE4jmKpCIBUkxFEOuYgMQIiHIg0VaVQ4wRkITfZqtyNJKxlMpWUICoRx05UD3G5RZ0Yq2KF1CASNiPzoHXobZ19Ve3yk8T1piELjHxJURc2mwG+xvdboJq0MW/rcQJGAEJsrJ4ftdpq2niIt2+EQoQf77gW414iKNeLbpIRfckSxOhtZKzoYMT0FbV81AzvPlDTkhunONuSQcv6Hp2YrtxW0/t+nThrPt5gwIEBUgyM0zjrjO6Jxk6G4mZWKwN6XA00FZjHcK6lel66KexXVWORnLW0tuSDl5Io82k7bmpo7+6nzeqeAGXYEkwI5KKBEgxFUGsYwIyoBqMgETHGW01OoYyNSDOMihFL9NKnMDQQAES3SaCasC5GYRQfL/rxBoFCEZA4rNkCec0jSpfR59bkVQSM1SNnKD7jVTabBX7q35WoQCJjrFOPsc5En38gmrQNb66nzcoQDQ6G7qMLm3t6p5kaSNwVaQSROJx/67jTSfaatyjKK4vbTyos7+twgkYAUlmfuq01TQ9r3U/b1TxAi7BkpinOMkkQIqpCGIdE5ASUS5VpJJMD3pbQQGSDOI4N1sf51bhBBQgrW+rKECSG2NVvIACRGIM8cErAVJMRRDrmIBEAaIcSLRV5RCXGkCck8NZlaORTA8qW9HxYgJtNZmRThvOunlQFS+gAJGYL2kzdl391T3J0vRGpZXWe+twNNBWJYgzpiK6+CiN7apyNGIyhVDV6OCFNNpM2p6bOvqr+3mjihdQgEhQGpKKBEgxFUGsYwISIyDKgURbVQ4xRkDwJPSGjQwFSMPQSV+IHCgNVeSCOrFGAeIPH5JKZDsOrECXoetW+TrebOjCGiMggdMgsIDOsUubrWJ/A80xcoFW4gQGBvoKkU0isALkwECIYiugE2sUIChAYjPkoIp0GToKkKCRie/3VnI2dDgaaKvx2WJQTbr4KI3tqnI0gsZYxe86eCGNNoMvB1RYb986ddqWKl7AJVgStqNz4NM0udGpkzDGmIqgAIkOJPJCdAxlakCcZVCKXqaVOAEjINHtQaYGnJsyKMVTRifWKEAwAhKPFUvUosvQUYBIDE5MRVrJ2dDxphNtNSZDlKhGFx+lsV1VjobEMMdeRAcvpNFm0vSSVNf46n7eqOIFjIBI0J4uo0tbu7onWdqIVBWpSEypWIvocDTQVmMdwrqVpY0Hdfa3VTgBIyDJzE+dtpqm57Xu540qXkABIjFPcZJJgBRTEcQ6JiADqsEISHSc0VajYyhTA+Isg1L0Mq3ECShAotuDTA04N2VQiqeMTqxRgPhjqONtp86BR5Ufz+QNqiWNY6yKVIKwjvt3HZyg+41UmnghjXNT1/i2CiegAImbZWvXh3MzGZx1P29U8QJGQCTsByeZBEgxFUGsYwISIyDKgURbVQ5xqQHEOTmcVTkayfSgshUdLybQVpMZ6bThrJsHVfFCZAFiWdbBADCVUpojhNxn2/ZlvAm2tbWNdl33PkLI+pTSpYSQQ2zbXjZ58uTs+++//ytCyFcppS4AHOc4zj+CzBdJJQih6L/rmty6J5mut4662lVFKmngBLTV6DwjW4MuPkpju6o4gY11GnghjTaj6/mVpnZ1P29U8UIkATJ+/Pj1s9nsa7lcbpt58+Z9alnWDNd1r+3s7Hy2/HAxTfMRQsjDtm3fl8/njzUMY3fbtg+zLOsMSulmjuMcb5pmOwA86jgO+z8TI8IPChDZx3bj5XSRqO5JliZCU7XeOy2cgLbaOL+EvVIXH6WxXVWORlp4IY02k7bnpo7+6n7eqOKFSALEsqwjKKW7Oo5znP+G40hK6S5MVLB/syjH0qVLl9m2PRIAigCQsSxrOfu3aZpPA8A0x3FeZmVN03yOEHKJbduvoADxEEgbmaWxzzrHWAWppIUT0FbDyojGy+ucIzqcDZ39VcEJvm+AvkLjUyDwSp02k7Y5oqO/up83qnghqgA5l1K6huM4F/sksxul9BzHcfZk/2ZvPXK53Ou2bW9UnkGWZf3HMIwdi8XiXwFgH8dxFvoC5F4AeNJxnD+iAEEBsmxZF1AayLuxFUgjgasgFcuyUsEJuh8IOh6CaZwjacNZBSf4vkEqeAHnSGyP5LoVpQ1n3c8bVbwQSYCYpnk+AAyuEiBnO46zNwOsvb19lOu6r1ULkEKhsF0mk2GRj714AUIIedy27YeCBMjy5ck7pyNHDgNsVz25MGJBrJPBeZ11hkea/7XuMi2cUH4goK0mY6uIczI4q+AE/wUj+goKhxCfmwrB5arWhbPu540qXojkgFiWVbHkii2/AICdbds+gQHGLcFa28/tYEuw2JKsdUzTfIYQcrFt27N8gnrOMIyLOzo6Xk3GlLAVRAARiBsB5IS4EcX6EIH+jwDyQv8fQ+wBIhA3ApEECItwFIvFWZTSHUeMGLGiq6vrCQC4zbbt6eUbNU1zOiHkT7Zt32ua5tEA8F3HcQ6wLOssSulEli9iWVYbpfSp4cOHm7Nnz+6Ou5NYHyKACCSDAHJCMjhjK4hAf0IAeaE/jRbeKyKQDAKRBAi7xXw+P4UQMhUABvg7WZ1nmuYdlNLpnZ2dT+Tz+TGGYdwNAKMAYLnruod3dnYunjRp0oDu7u5by9vwGoZxWkdHx8xkuo2tIAKIgCoEkBNUIYv1IgL9FwHkhf47dnjniIAKBCILEBU3hXUiAogAIoAIIAKIACKACCACiEBrIoACpDXHFXuFCCACiAAigAggAogAIoAINCUCKECacljwphABRAARQAQQAUQAEUAEEIHWRAAFSGuOK/YKEUAEEAFEABFABBABRAARaEoEUIA05bDgTSECiAAigAggAogAIoAIIAKtiUC/ESCWZR0MAFMppTlCyH22bV+mckjy+fxwQsgrhULhOwsXLvzPhAkTJmUymd8CwAhK6Vtffvnl0YsWLfoyznvwtyY+FgDYGeCvjx49+sQPP/ywzXXdO1S2y/pgmubVhJB9KaUuIeQu27Z/3t7evlkSbbP2Lcu6DgBG2rb9gyTatSzrAUrp1oSQlf4YTisWiwtUj3E+n9+X7RpHCBlCKX3GcZwzVPfXNM0TCSE/8u2KUEo3Zod+FovFa1X3N875UauuJHlBByf4c4NtWZ44LyAnQMtygs/5LckLSXICw1EHL+jyFdLGCT7/oq+gyFfoFwJk/Pjx62ez2ddyudw28+bN+9SyrBmu617b2dn5rAoHJ5/Pf4UQ8htCiNnd3W0yAWJZ1r8A4FTbtl8xTXMaISRn2/YFcbVvWdb2lNLfrl69esd33333f5Zl3QMArE12doqydv0H0d6EkJ/atr3ruHHjBg4YMODtTCazp+u6D6pu25/guwHAAwDwBBMgqrH2++ysXr16h3fffXdFeQxVt2tZ1iYA8LJhGNvPnz/2Y03nAAAgAElEQVT/I8uy/kopvYYQckUSOLN+Tpw4MV8sFmcYhvF113X/klS7cc0Tvp4keUEHJ/hzQwsvmKaJnOC9GFHN+9o5oZV4IUlO8MVHanyFNHIC+gpqfYV+IUDYCeuU0l0dxznOfyhXnMAet3NjmuadLApAKb23UChMzmQyrmEYL9q2vSlra8KECWMzmczM8r/jaH/ChAkTDMMY5TjOy77Rn00ImQQAu6hsl7v3DAAUJ06cuHGxWHzJdd2dVPeZtT1p0qS1C4XCk4SQP1JKt3Rd92LV7fpt/hsAXqGUbkQIedh13btUt8veWgHAaNu2f+L3fYMvv/xyQC6XeyGhMWYO1TOEkHuKxeKLqvsbx7yoV0eSvKCDE3yu0ckLyAmKeb8ZOMF/prYELyTJCf5zOm2+Qmo4gfNP0FdQxIP9RYCcSyldw3Gci8tvzCml5ziOs6dKJ8c0zXcKhcIu2Wx2FCHkOtu2d/bby1iW9YVt24NUtL/pppuul8lkXiOE3A4A30mqXcuyLqOUnkkIech13d8YhnGt6rZN03zIMIzbXNdly4J2oZT+WjXWpmm2A8Alq1evPrFYLK4aPHjwEwDwHCFkL5X9NU3zNgBYBQBthBB2MOfjrus+mQTO/sPyG4SQX9q2vZVpmjuqxlnF3ODrtCwrcV7QxQms3zp4ATmhtTmh1XhBByf4GKbGV0gLJ/jjir6CQl+hXwgQ0zTPB4DBVQLkbMdx9lbp5JSdDcMwNsxkMtdUOaddtm0Pibv9tra2cZRS5hDfx95SJ9VuuR9jx44dzBxyQgg7lX53lX22LOt45oyziIBpmkczAVIsFu9Ius+WZX2XUnqqv6yOF5mxjrFlWb8BgK8bhvGNQqHwuWEYj1FKZ9YQPrG2Wx5by7Lup5Q+7TjO7ydMmPDVpHGOe67o4AUdnMBw08kLyAkVL55inZu6OcF/odcyvKCDE3gBkhZfIY2c4M8V9BUA2Av4WHiwXwgQy7IqllyxMCsA7Gzb9glxOzV8fZyzQTOZDFsmM4H9ns/nxxBC/uo4jhln+6ZpbkUIYeLjStu2b/OXeilvN5/PT8xms8b8+fPf8ifZjyml2xJCGMZ5VX1my4EopRsQQooAsDaLcgHAo0yIqGy3ra1t22KxOKqzs5NhzRLwDwSAkwkhG6ls1zTNSwkha9m2faqP80mU0u1U48zamjx5cnbp0qVLBg0aNH7OnDlfJGVbcc6P6rp08ELSnODbZ+K8gJzQ+pzQiryggxOqBEjL+gpp4wT/xQ/6Cl7KgRI/tF8IkPb29lHFYnEWpXTHESNGrOjq6mKO4222bU9X6eCUnQ2WhG6a5hwAOIXlaFiWdTGldC3Hcc6Mq/18Pr8uIeRNQshJtm0/Wq5Xdbu+uJhCCDlj9OjRuy5ZsiRjGAaLgPzadd2LVPa5SuyVIiAsCV11n/23/7/PZrNbA8DqQqHA7OlOSinbVEDZGJumuQMA/L5QKOy4cOHCz03TfJhFQVzXPV1lu/4Ysx2/fuk4zteTtK245ketenTwQpKc4I+bFl7I5/PICS3OCa3ICzo4gRcgrewrpI0T2Liir+A9eVX5ZP1CgHBO8lQAGMDekjuOc55K58YHfSFLQmekwtS/YRhsG97hAPAOIeSwjo6OrrjuwbKsyymlZxBCHABg48K24n3Sdd0HVLZbvn/WPgAcQCktAMCDjuNc6W89zLYAVtJnkQBJol3Lsph4/CGlNEMI+X+2bV+YRLumaR4DAGcDQJYQ8pxt26dNmDBhYiaTUYpzW1vbQZTSA23bPqyMu2qbjmtu1KvHfygmxgumaSbGCazfOnkBOaG1OcF/w9tyvJA0J6TJV0gbJ/gcjL6CIv+33wiQJJwZbAMRQAQQAUQAEUAEEAFEABFABNQigAJELb5YOyKACCACiAAigAggAogAIoAIcAigAEFzQAQQAUQAEUAEEAFEABFABBCBxBBAAZIY1NgQIoAIIAKIACKACCACiAAigAigAEEbQAQQAUQAEUAEEAFEABFABBCBxBBAAZIY1NgQIoAIIAKIACKACCACiAAigAigAEEbQAQQAUQAEUAEEAFEABFABBCBxBBAAZIY1NgQIoAIIAKIACKACCACiAAigAigANFsA5ZluZTSeYSQbv9WBgHAK9ls9pR58+at1nl7pmk+lclkfjB//vyl9e7Dsqz/A4A9bNte1uj9mqbZXSgUNmWHPjZah8x1pmleaBhGR0dHx59kymMZREAHAsgLHurICzqsD9tsRgSQE5ATmtEuo9wTCpAo6MVwrWVZRcMwxpSd/MmTJ2eXLl36EqX0Zcdxzo2hiYarYIRHCBnT0dHxfsOVSF5omubqQqEwIQEB8gKl9I7Ozs4/SN4aFkMEEkcAeaHH2UBeSNz6sMFmRAA5ATmhGe0yyj2hAImCXgzX1nLyTdO8hhDSbtv2fm1tbV9zXfdaABhGCGGC4PqOjo77J06cuHGhUPg7IeT/KKWbZjKZ/SilwymlvwAA9v8ipfTSzs7OhydNmrRBd3f3LwFgHCEkRyl92nGc8wHA9d+qXAgAewPAaAC43XGc60zTvI8QchiLzmSz2QNd12V13gAAAyilowkhs4cNG3bo7Nmzu/k+mKa5NyHkIkppjhBSAIBLbNueUQ1VW1sbu98rKaX/I4T8jVJ6YlmAyNRhWdZxAHCIbdu7s7rz+fy6hmF0dnd3b5zNZtn93UwpXZ/9Rgi5x7btGy3LOoNSehkAsEjNBYZhPOHjtT2llGH7t0GDBp01Z86cLyzLOhIAzqKUdhNCigBwjm3br8Qw5FgFIhCIAPIC8kKgkWCBVCGAnICc0GoGjwJE84hWk4ppmhsCwPMAcGsul7u/UCjMp5Qe5DjOy/l8fgwh5DVCyPcymcziYrH4DiHkmx0dHTMBIGNZ1nsAcIpt249OmDBhQiaTebqrq2vzYcOGTaeUMmHxZxZhef/999nb/9ccx7mBtQ8AZ9u2/fO2trbNXdf9p2EYIzs6OrrYb4ZhbMiiM5Zl/c513T90dnY+s9122+W6urrmUEp/5jjOI+zNDCFkbLFYHGwYxmMAsAtbjuWLJCYudujs7FxchtqyrHUAYAEh5BsdHR1zTdM8hhByZ3d39yaZTCYnU8fo0aOHDB06dJHrulstWLBgkWmaZxNCJtm2fbxlWbbrulNZlGPcuHFrDhgw4EVK6TXs36ZpvgAAv3Ec5wHLsu4GgNW2bZ/IdAr37xNM01xmGMZOHR0dtmma3yKE7GTb9jTN5oLNpwQB5AXkhZSYOnZTEgHkBOQESVPpN8VQgGgeKn5dJ6U0w962U0r/7DjOFZZlfZu9sXccZ/vybZqmeRMAfJnNZn9VLBb/nc1mh7BckXw+v7VhGE/btr0e3yXmqA8bNqwLAOYwJ5v9RikdxISMbdvHsPZd1813dnb+m/1mWVahWCxuwpx6nvCYcFmyZMlehmFMpJSaALA/IeRM27bvLZejlO7P7pcQwvI4ym2tCQAnO47zF64PBxBCzrNte0fub58XCoWJuVxuH5k62HWmad4CAB84jnO5ZVlvua57vGEYK/zla+tygucMANjRtu1DmQApL8GyLOsD13W/2dnZ+bZf31YA8JTjOKMsy2KRpAMBgN33c67rTu/s7Fyl2Vyw+ZQggLzgDbRpmsgLKbF57GZ9BJATkBNabY6gANE8onyUofpW2FIkAJjGCxDfMV6VyWRuKRQKnY7jDGDXtbe3b+a67vO2bZeWHflioo0QsoRSusJ13bU6Ozs/Y39nUYFBgwYVy1EOPs+DT/qsioC8CgAdrus+mclk3qKU/ppSepfjOL8vCxDXdZnDvpvjOAeU76GtrW10R0fHhwDAljGVnQr2+/mO4+zA3eun3d3dm2ez2f1k6mDXsYgNpfRRSulhAHCH4zhb5PP5iYSQFx3H4QUIW0r1VcdxDq4SIB8Vi8VdFyxYMM+vb1vXdWeUr2VRJEIIi36we9rQcZyt2bI1zSaDzacAAeSFHg5DXkiBvWMXgxFATkBOCLaS/lUCBYjm8aqX6D1p0qS1C4VCh78E66UJEyaMNQyDLcE6MpPJLCgUCgscx8mxLrBlUZ999pkNAKc6jvOkaZrjAeD1TCZjuq77CAC8aNv2RWPHjh08ZMiQvwLAI7ZtX1sjrNuzG1VZjADAp7lc7pPu7u7RCxcu/JBFWwghL1NKT+3s7Lybi4AMB4C/EUJ29pdW7UAIecF1XYtfgsX61d3d3WkYxrc7Ojpm5/P5KYZhPMSWYOVyuSEydXDChQkj9rnftu1b/SVmbxuGMY3lymy++eZrrVq16kWWE2Lb9p2WZT1LKb3XF06/A4BVtm3/CAAMy7LuZFGozz///MShQ4d2uq67y4IFCxa0tbWNo5R2DBo0aCTLD9FsMth8ChBAXkBeSIGZYxdDIICcgJwQwlz6RVEUIJqHqZw/Idppyk9Cvw4AhjInGQB+4TjOHX5+RU8EhHXDsqwt2O8AwJY9sYjDz1gCuC9c2N83BQAmWP7iOM45fhJ6KX+j3D6/G5Vpmn8khGxHCDmEUsqWRh0DAB8DQBchhDnib9m2fQFPjJZl7Q8AF7OcFHZPlNIL+OVXnHDYjVJ6o5+oPhsADuju7t6O7YIlWweryzTNo1m+DEuML0d4TNNsJ4T8glK6np90fz9b0uaXP5UQci5L0C8UCg/mcrmbKKXbMVxYEnp3d/cZCxcu/NQ0zUMJIT9jAsVPUGcC5j7N5oLNpwQB5IXSBhbICymxd+xmMALICcgJwVbSv0qgAOlf49V0dzt+/PgRLDrCL/FqupvEG0IEEIFEEUBeSBRubAwRaHoEkBOafogSv0EUIIlD3joN5vP5rxBCHiaEPMsS2lunZ9gTRAARaBQB5IVGkcPrEIHWRAA5oTXHNWqvUIBERRCvRwQQAUQAEUAEEAFEABFABBABaQRQgEhDhQURAUQAEUAEEAFEABFABBABRCAqAihAoiKI1yMCiAAigAggAogAIoAIIAKIgDQCKECkocKCiAAigAggAogAIoAIIAKIACIQFQEUIFERxOsRAUQAEUAEEAFEABFABBABREAaARQg0lBhQUQAEUAEEAFEABFABBABRAARiIoACpCoCOL1iAAigAggAogAIoAIIAKIACIgjQAKEGmosCAigAggAogAIoAIIAKIACKACERFAAVIVATxekQAEUAEEAFEABFABBABRAARkEYABYg0VFgQEUAEEAFEABFABBABRAARQASiIoACJCqCeD0igAggAogAIoAIIAKIACKACEgjgAJEGiosiAggAogAIoAIIAKIACKACCACURFAARIVQbweEUAEEAFEABFABBABRAARQASkEUABIg0VFkQEEAFEABGQQcCyrE1s235HpiyWQQQQAUQAEUgfAihA0jfmsfa4ra1tV9d1zwGA7QHAAIC3AeBqx3GejLUhrAwRQASaAgHLsnYCgAsA4GsAQCilCwghd9m2fRu7QcuyTqaU7uE4zv5NccN4E4gAIoAIIAJNhwAKkKYbkv5zQ6ZpHkUIuZYQcsIGG2zwl5kzZ1LTNL8HAHcQQg63bXt6/+kN3ikigAgEIdDW1nYQpfQOALhw1apV97/77rsrJkyY8NVMJnM7AMyzbftw0zQvIYRsY9v2fkH14e+IACKACCAC6UQABUg6xz1yr8eOHTt4yJAhSwkhR3V0dDzGV+i/AR2SyWSeKhaLvwaAdkLIcgB41LbtnwIAjXwDWAEigAgkisC4ceMGDRw48D8AcKpt2w/yjefz+XUJITYAnMFeQPjR0AWO47RbluUCwC2U0sMB4HeO45ydz+d/RAg5kxCyHqX0bULIubZtv8LqNE3zVAA4CwCGE0IWAMAltm0/lWhnsTFEABFABBABpQigAFEKb+tWblnWbgDwmG3bwwGgWKunlmW9RCmd4TjOlfl8foxhGK9SSn/kOM5fWhcZ7Bki0JoIsOWWlNInR40aNXzmzJmF6l5alnUPpbRACHkPALYrR0B8AfLAqFGjjv7ggw8GA8DBruteYRjGdzo6Ov5lmuaRAHCrYRibFYvFjGEYb1FKJzmOs7Ctre0Hrute5jjOGHxx0Zp2hb1CBBCBdCKAAiSd4x6516ZpHkIIuc627bGiyizLegYABgHAjYSQ5zs6OroiN4wVIAKIgBYETNM8lC25FM150zSvAoAtCfn/7L0JnCRFsT8e1cdMd8+1yy7HLpcuTNceCiyggCAsLCKi+BREUS45RIEnCoqAfx4InqDP8ycq6PMJ8ryRU5ZLuRZBV2DBga2aZbkXRHbnPru78v/Jqu6erO7OqcyuqsmpqajPhw+101mZkZGRUfGtyIjQHgWAfVgAYlnW+3t7e2+jhOu6fj8h5C7TNL9amUg+n79H07R7CoXC/6VSqV5N074HAL8zDOMfAEA9KHghB5ADyAHkwBziAAKQObSYMzmV7u7uQxKJxB2GYXTUekD23HPPtq1bt1rJZLK1tbX1ywBwFCGEApU7ksnkp5555plXZ5JWHAs5gBzwz4GlS5eusizrrs7OzrZ169YVGnhAfgUAYwBAPSAuAKJp2ts2bNhAwQQ9YrWBEHJFb2/v/zEAhB7bKpimeXY+nz9Y07TPA8DBADBBCPmuaZoU3OCFHEAOIAeQA3OEAwhA5shCzvQ0VqxY0VIoFCiQ+IRpmjey4+u6/lVCyPsTicSnBwcH/7Z58+bR7u7u3RKJxM8AYJNhGKfNNL04HnIAOeCPA/vuu296cHDwRU3T/sswjJ+yvS1dunQxjeWwLOvERCKxTy0AKZVK+27cuPEx+gz1jBJC7qNHMxkA8mdN0+4DgKsty9q9t7f3EQBI6rr+LgD4IyHk3aZpPuBvBvg0cgA5gBxADswWDiAAmS0rEUE6dF0/HQC+RuM6Fi9efOvzzz+fam1tPREAvg8AH6NfOanXo7Oz85Lh4eEMIYQClScMw6Bpe/FCDiAHIsaB7u7uozVN+4WmaZe0tLT8qrW1dXhwcPAAAPgBAGwwTfMjuq5fBABHGoaxqgw4LBaA0KNcAPDfiUTi6A0bNjxBY0A0Tbta07SVANBuWdZ9lmUdsXHjxr/m8/m9NE17uFQqvW3jxo09EWMXkoscQA4gB5ADHA4gAEHR8MWBfD7/QQD4HM10RWsCaJr2FA0w7e3tvSufz9O/UcNiL0JISdO0WzOZzH+uX79+xNeg+DByADmgjAP5fP7tAPD/0Togmqa1AADNVPWzSh2Q3XfffQXNgEcISZmmuaOu68UygLA9IGVQchYhhGbMWqRp2jOapl20YcOGv9Df8vn8J2hWLELIdpqm/cuyrK/19vb+XNmEcWDkAHIAOYAcCJwDCEACZyl2iBxADiAHkAPIAeQAcgA5gBxADvA44BuA6Lp+HABcRghJa5r2S8MwaNBx9dJ1/TAA+BYhJAkAzxWLxVM2bdo0QOtIZLPZ1zVN6600NgyDnh3GGhEor8iBCHMAdUKEFw9JRw4o4EB3dzet+fJQsVh836ZNm2itmepF44ssy/qlpmnbE0Jo7anjDcN4QwGZOCRyADkQIAd8AZAlS5Zsn0qlHk2n03v39PQM6Lq+xrKsq3p7e+8u05jQdf35RCJx+DPPPGPSNI2appUMw7hE1/WDCCGfM02THuHBCzmAHJgDHECdMAcWEaeAHJhBDnR3d++vado1mqblC4VCvhaA5PP5P2qa9gfDMH7Z3d19aiKReJdhGB+bQRJxKOQAciAEDvgCILqun0gIOdQ0TRqMTLObnEQIOcQ0zTMYWqnno1TOmkQzp6w3TfO/dV0/jxDyMQpIysWraCXctSHMEbtEDiAHZogDqBNmiNE4DHJgjnAgn8//TNO0/yGEXF8sFlexAGTVqlWpV1999Q3DMBaU073TzGhbDcPYhlcAd46wBaeBHJjzHPALQGigYJtpmpeWAchqQsgFpmkeyXIun8/T4lS0KB3N6X6AaZqvLF269DOWZbWYpvnN7u7ulZqm3dba2vqWp556qm/Ocx0niByYoxzQdR11whxdW5wWciBMDuTzeXpE+xAWgFCPajqd/rthGLtUxtZ1/cVUKvX2np6e18KkB/tGDiAHwuWALwCSz+cvBoBsDQChx6qOakR2d3f3pzRNO8k0zQNrf6duVkLIzyrVcsOdNvaOHEAOhMEB1AlhcBX7RA7MfQ40AiDLli1bZFnWozUA5KVisbjPs88++/rc5wrOEDkwdzngC4DUHrmixy9o9VrDMM6kLFu8eHGura3tsAqooP9ub29/zTTNTlpDwrKsO3t7e18ue09uoSlbDcNYMx27i8US2bp15rO4brNNG+C4M7MRkNczw+fttuv0tf8bURknnUDnj7I6M7KKfJ4ZPoehE0QpbwRAmCNY9MiVVS5OSY9kLfQ6gmVZFtG0wFWc6HSwHXJgznCA1lcIYzK+OqVfJ0ql0lpCyH5dXV39Q0NDt5VBxM2UWFo5d2ho6KVSqbSaFpEqF677oGEY79N1/ccAMESL0nV3dy9PJBJrMpnMMq8aEYQQ8sYbQ0BmMFcWZf3ChR2A44Yhgu4+kdfh85iOQPm87bbBA5C46IQKD1EvhC+vqBPC53GYOkGU+kYAhD6bz+dv1jTt94ZhXJ/P508BgA+IJK+htsKWLTNrK4jOtdKOyvaCBR2AdMpyrnH7qPCzst+isvYLFwZvK9g88Lvs3d3dx2qadhkA0IJUN5mmeVE+n7+WEHIz9Xx0d3cfkkgkvl0e6+VUKnUmPbu5YsWKbQqFws81TdsNAIqEkHNN03zAix4EIF4c8v+7qhc+GnX+1060h7AACB0/DjoBZVVU0vy3U6WP4jhuGB8lRCUgn89vqgSh19gQOyUSCVqIchEAbLEs64TKyYnp+lZhK4jOlQUgKj5iIJ2yHAi+vSr9IjuTMG0F3wBEdjJ+26tQKqoEJW7jolHnd3eIPx+mUhGnIpiWKnQCymowayfSS9z0oMr5qgQgIrIg00aVXpChUdVay9CoUtfNVTqjxtOw9AICEAEJV6Uk4jauyk0ZN14jABHY+B5N4igzKr7WIp/9y6pID3NJJ9D5IgARWXWxNqr2oBh1U62iQqdKW6cZniIAKXNNhVJRJdRxG1flpowbr+eSsaFCJ6Csyr7Gmm8fx72pCuiFZWg0v/rNP6lKL8hQrEq2ZWhUqevmKp1R42lYegE9IAISrkpJxG1clZsybrxGACKw8dED4uJAHPeIKiCgatywDA3/u02+BwQg8jzjPaFq78vOICp0qrR1muFpWHoBAYjAaqgS6riNq3JTxo3XCEAENj4CEAQgMct+GJah4X+3yfeAAESeZwhAguOZV0+qbA4vump/D9NWQAAisBqqBCVu4yIAERDGgJqEqVQCIlG4G1WGRtz2J85XWCR9NVTJZwQgvpZO+mFVay1LKNIpyzHv9lHiaVh6AQGIt5zYNRNUucTjNC4CEAFhDKgJAhD/jES94J+HIj0gn0W45L/NXNIJlBuqPkzIrIQq2ZahUeV7ea7SGTWeIgApS6IKpaJKScRtXJWbMm68nkvGhgqdgLIqaxo03z6Oe1PVh6ewDI3mV7/5J1XpBRmKVcm2DI0qdd1cpTNqPA1LL6AHREDCVSmJuI2rclPGjdcIQAQ2vkeTOMqMKsMYx/Uvr149zCWdgB4Qr9WW+12VrpOjEpSdVpGlU6WtI0trmHoBAYjAaqjafHEbV+WmjBuvw1QqAlsq0CaqvnTGUWYQCAQqug07UylXYX3pDJ9r9SOo0gsyc1W11jI0qnwvz1U6o8bTsPQCAhABCVelJOI2rspNGTdeIwAR2PjoAXFxII57JG6AKyxDw/9uk+8BAYg8z3hPqNr7sjOICp0qbZ1meBqWXkAAIrAaqoQ6buOq3JRx4zUCEIGNjwAEAQim4fW/URT1gAAkOMarej/KziAqdKq0dZrhKQKQMtdUKBVVQh23cVVuyrjxGgGIrBqubx9HmYmbRyBu8w3L0PC/2+R7UGEryFKpSocgnbIcCL59lNY+LL2AHhABuVIlKHEbFwGIgDAG1AQBiH9Gxm1/4nz9y4xIDyr5HJahITLvoNsgAAmOo6pkUnYGUaFTpa3TDE/D0gsIQARWQ5VQx21clZsybrxGACKw8T2axFFm4uYRiNt8wzI0/O82+R4QgMjzjPeEKl0nO4Oo0KnS1mmGp2HpBQQgAquhSqjjNq7KTRk3XiMAEdj4CEBcHIjjHkEA4n+fqOoBAUhwnFe192VnEBU6Vdo6zfAUAUiZayqUiiqhjtu4Kjdl3HiNAERWDde3j6PMxM0gj9t8wzI0/O82+R5U2AqyVKrSIUinLAeCbx+ltQ9LL6AHRECuVAlK3MZFACIgjAE1QQDin5Fx2584X/8yI9KDSj6HZWiIzDvoNghAguOoKpmUnUFU6FRp6zTD07D0AgIQgdVQJdRxG1flpowbrxGACGx8jyZxlJm4eQTiNt+wDA3/u02+BwQg8jzjPaFK18nOICp0qrR1muFpWHoBAYjAaqgS6riNq3JTxo3XCEAENj4CEBcH4rhHEID43yeqekAAEhznVe192RlEhU6Vtk4zPEUAUuaaCqWiSqjjNq7KTRk3XiMAkVXD9e3jKDNxM8jjNt+wDA3/u02+BxW2giyVqnQI0inLgeDbR2ntw9IL6AERkCtVghK3cRGACAhjQE0QgPhnZNz2J87Xv8yI9KCSz2EZGiLzDroNApDgOKpKJmVnEBU6Vdo6zfA0LL2AAERgNVQJddzGVbkp48ZrBCACG9+jSRxlJm4egbjNNyxDw/9uk+8BAYg8z3hPqNJ1sjOICp0qbZ1meBqWXkAAIrAaqoQ6buOq3JRx4zUCEIGNjwDExYE47hEEIP73iaoeEIAEx3lVe192BlGhU6Wt0wxPEYCUuaZCqagS6riNq3JTxo3XCEBk1XB9+zjKTNwM8rjNNyxDw/9uk+9Bha0gS6UqHYJ0ynIg+PZRWvuw9BM5uwgAACAASURBVAJ6QATkSpWgxG1cBCACwhhQEwQg/hkZt/2J8/UvMyI9qORzWIaGyLyDboMAJDiOqpJJ2RlEhU6Vtk4zPA1LLyAAEVgNVUIdt3FVbsq48RoBiMDG92gSR5mJm0cgbvMNy9Dwv9vke0AAIs8z3hOqdJ3sDKJCp0pbpxmehqUXEIAIrIYqoY7buCo3Zdx4jQBEYOMjAHFxII57BAGI/32iqgcEIMFxXtXel51BVOhUaes0w9NZC0B0XT8OAC4jhKQ1TfulYRhfZieo6/phAPAtQkgSAJ4rFounbNq0aWDVqlWpzZs3/1jTtAMIIRYAnG6a5t+8mKNCqagS6riNq3JTxo3XYQKQOOgElFUvTR3c73Hcm6qAT1iGRnDSIN6TCltBnDqnpSrZRjplORB8+yitfVh6wZcHZMmSJdunUqlH0+n03j09PQO6rq+xLOuq3t7eu8vLldB1/flEInH4M888Y+bz+a9rmlYyDOOSpUuXfsayrLeapnlGPp9fBgA3maZJ/0/BCPdSoVRUCUrcxlWpkOPG67AASFx0Aspq8C9kXo9x3JsIQPzLlwpbQZZqVbKNdMpyIPj2UVr7WQlAdF0/kRByqGmap9Pl0XX9JELIIRRUMMtFPR+lFStWtBQKhZ9qmvaEYRjfzufz9wDA5aZpPkjb0n9rmvYlwzAeQgCi9uuIyo2hauw4jhuGUomLTkAAEvwLGQGIer0fhk6YOUlxj4QAJDjOq3o/ys4gKnSqfH80w9Ow9IIvD4iu6xcSQtpM07y0DEBWE0IuME3zSHaS+Xx+T03T7gKACULIAaZpvpLP558BgPeaprmpDECuB4DbTdP8NQIQ9S8iFV/gVG5KVYpL5bhhKJW46ASUVdnXWPPtVe4RFXpQ5XzD0AnNr7y/JxGA+OMf+7QqmZSdQVToVPn+aIanYekFXwAkn89fDADZGgDyOdM0j2o0ye7u7k9pmnaSaZoH5vN5AwDewwIQTdNuNQzjt14AZMuWISBElo3Nt6dCvWBBB+C4zfNQ9EnktSin/LVzFHWnr/3fiIK46ITKCwT1gj85FHkadYIIl/y3CUsn+KesuR4QgDTHt0ZPRcWwjwqdCEDKH9n9iGjtkSt6/AIADjYM40za7+LFi3NtbW2H9fb23lb5d3t7+2umaXbm8/l7NU271DCMtfQ3egQrkUhcumHDhoe9AIgfmvFZ5AByoLz5Naqug71QJwTLT+wNOTCTHNBC0AkzST87FgKQ4DgfFcM+KnQiAAkAgCxbtmxRqVRaSwjZr6urq39oaIgCjasNw7iZdr/vvvumh4aGXiqVSqs3btzYo+s6jRX5oGEY79N1/XxCyHIaL6Lr+lJCyB2dnZ35devWFbwACHoiglMsvK8dKr7sVjalirHj+JU1DA9IXHQCymq4OojtPY57U5UODEMnzJykuEdCABIc56Ni2EeFTgQgAQAQ2kV3d/exmqZdBgAt5UxWF+Xz+WsJITdTz0d3d/chiUTi2zTjHAC8nEqlzuzp6XmtHJT+w0oa3kQice6GDRvu89oyKpSKKqGO27gqN2XceB1WFqy46ASUVS9NHdzvcdybqmJPwjrrHZw0iPekwlYQp65sgNlHYTvgjTdm9lg50inLgeDbq9JrsjMJ01YI/AiG7ORk26tQKqoEJW7jolEnuxuabx+mUmmequaeVKETUFabW6tmnoqbHlQ5XwQgzUho88+oWmtZipFOWY55t48ST8PSCwhAvOVEWbEgVQKqalw06gSEMaAmCED8M1LVPsFx/a+dSA9x5HNYhoYIv4Nuo+rDhMw8VMmYDI0q38tzlc6o8TQsvYAAREDCVSmJuI2rclPGjdcIQAQ2vkeTOMqMiuMiyGf/sirSw1zSCXS+CEBEVl2sjao9KEbdVKuo0KnS1mmGpwhAylxToVRUCXXcxlW5KePG67lkbKjQCSirsq+x5tvHcW+qAnphGRrNr37zT6rSCzIUq5JtGRpV6rq5SmfUeBqWXkAPiICEq1IScRtX5aaMG68RgAhsfPSAuDgQxz2iCgioGjcsQ8P/bpPvAQGIPM94T6ja+7IziAqdKm2dZngall5AACKwGqqEOm7jqtyUceM1AhCBjY8ABAGIggxFKnVRWIaG/90m3wMCEHmeIQAJjmdePana51501f4epq2AAERgNVQJStzGRQAiIIwBNQlTqQREonA3qgyNuO1PnK+wSPpqqJLPKgCIruvHAcBlhJC0pmm/NAzjyywDly9fvmupVLoOADoJIf2WZZ28cePGl7yYrEoveNHF/q5qrWVoVPlenqt0Ro2nYekFBCACEq5KScRtXJWbMm68RgAisPHRA4IeEPSA+N8o0/SwZMmS7VOp1KPpdHrvnp6eAV3X11iWdVVvb+/dlcfy+fx1hJCHe3t7f5zP5/8TAPYzTfMkL8IQgHhxSPx3Ve9HcQqdllGhM0q0hmkrIAARkHBVQh23cVVuyrjxOkylIrClAm2iytCIo8yoik3AcQPdMg07U6ETdF0/kRByqGmap1OidF0/iRByiGmaZzAA5JcAsN40zW/m8/kLNE3b3TCMT3pxRJVe8KILPSAyHJJrq0ony1EZLbAUpl5AACIgOaqEOm7jIgAREMaAmoSpVAIiUbgbVYZG3PYnzldYJH01VMnnsI5a8Bii6/qFhJA20zQvLQOQ1YSQC0zTPJIBIEs0TXsYAIoAkCKEvMM0zU1eTFalF7zoQgAiwyG5tqr2jhyVCEAq/EIAIiA5qoQ6buMiABEQxoCaIADxz8i47U+cr3+ZEelBJZ9nGoDk8/mLASBbA0A+Z5rmUQwAeZAQcmVvb+9t+Xz+GAD4kmmae3jxkgKQLVuGgBCvlup+p2u9YEEHIJ3BrEFU+FmxdaKy9gsXdoaCFULpNBhRatyLiq8aKl8IcTp6gAAkzJ3j7hsBiH9eo17wz0ORHpDPIlzy30aFTqg9ckWPZAHAwYZhnElnpOv6QkLIM6ZpbluZoa7rrycSiWXPPPPMlulmTW0F/1zBHpADyAFNo9oh+CuUToMnc6pHBCBhctfpW9ULX+XYquasctyZ/toZluSq0Akoq2GtZn2/KvdInD4AqQAgy5YtW1QqldYSQvbr6urqHxoaug0ArjYM42YGcLxICDnRNM0HdF0/EACuMwxjNy8JRA+IF4fEf4+KZyEqdFbeH+gBEZfBWdFShbGBL8CZW3rk9czwWoWxEdbMVOgEBCBhrSYCEJU6UMVHie7u7mM1TbsMAFoA4CbTNC/K5/PXEkJupseuli5dui8h5P8RQrIAMAQA/2ma5hNeEqhKL3jRxf6uaq1laFSp6+YqnVHjaVh6AT0gAhKuSknEbVyVmzJuvEYAIrDxPZrEUWbi5hGI23zDMjT87zb5HhCAyPOM94QqXSc7g6jQqdLWaYanYekFBCACq6FKqOM2rspNGTdeIwAR2PgIQFwciOMeQQDif5+o6gEBSHCcV7X3ZWcQFTpV2jrN8BQBSJlrKpSKKqGO27gqN2XceI0ARFYN17ePo8zEzSCP23zDMjT87zb5HlTYCrJUqtIhSKcsB4JvH6W1D0svoAdEQK5UCUrcxkUAIiCMATVBAOKfkXHbnzhf/zIj0oNKPodlaIjMO+g2CECC46gqmZSdQVToVGnrNMPTsPQCAhCB1VAl1HEbV+WmjBuvEYAIbHyPJnGUmbh5BOI237AMDf+7Tb4HBCDyPOM9oUrXyc4gKnSqtHWa4WlYegEBiMBqqBLquI2rclPGjdcIQAQ2PgIQFwfiuEcQgPjfJ6p6QAASHOdV7X3ZGUSFTpW2TjM8RQBS5poKpaJKqOM2rspNGTdeIwCRVcP17eMoM3EzyOM237AMDf+7Tb4HFbaCLJWqdAjSKcuB4NtHae3D0gvoARGQK1WCErdxEYAICGNATRCA+Gdk3PYnzte/zIj0oJLPYRkaIvMOug0CkOA4qkomZWcQFTpV2jrN8DQsvYAARGA1VAl13MZVuSnjxmsEIAIb36NJHGUmbh6BuM03LEPD/26T7wEBiDzPeE+o0nWyM4gKnSptnWZ4GpZeQAAisBqqhDpu4/rZlNrgZuj80R72ag6e9SSQzsUCKzvVJG68RgAiJR4NG8dRZuJmkMdtvmEZGv53m3wPCEDkeYYAJDieefWk6v3hRVft72HaCghABFZDlaDEbVwEIALCGFCTMJVKQCQKd6PK0Ijb/sT5Coukr4Yq+YwAxNfSST+saq1lCUU6ZTnm3T5KPA1LLyAA8ZYTUCUocRsXAYiAMAbUBAGIf0bGbX/ifP3LjEgPKvkclqEhMu+g26j6MCEzD1VrLUOjn/ey7Dh+20eFn1HjaVh6AQGIgMSrEuq4jetnU+IRLAFBZpogAJHjV6PWcdufOF//MiPSg0o+h2VoiMw76DYIQILjqCqZlJ1BVOj0Y+vI8sRv+zBtBd8ARNf14wDgMkJIWtO0XxqG8WV2wrvvvvveiUTiB5qm5Qgho5qmnWUYxpM777xzNpvNvq5pWm+lvWEY+wAAmY5hKpSKKqGO27h+NiUCEDk1E6ZSiYNO8COrcitV3zpuegHn61dixJ4PUyeIURBsKxW2guwMVMk20inLgeDbR2ntw/ow4QuALFmyZPtUKvVoOp3eu6enZ0DX9TWWZV3V29t7d2W5dF3/JwB80jCMtfl8/nBN075lGMZeuq4fRAj5nGmaH5RZWhVKRZWgxG1cP0YdAhCZXQT2scIwlEpcdIIfWZVbKQQgcdODKucbhk7wK+/NPq/CVpClVdVaI52yHAi+fZTWPiy94AuA6Lp+IiHkUNM0T6fLo+v6SYSQQ0zTPKO8XFo+nz/FNM3/pf9etmzZglKpZJqmuUDX9fMIIR/TNK1ECClqmnYhBSley6xCqagSlLiNK2LU8YAGAhCvneP+PSwAEhedICKrcisi3jpuegHnKy4bflqGpRP80OTnWRW2giy9qmQb6ZTlQPDto7T2sxWAXEgIaTNN89IyAFlNCLnANM0jGy2Xrus/JoSkKEBZunTpZyzLajFN85vd3d0rNU27rbW19S1PPfVU33RLrUKpqBKUuI0rYtQhAAlGEYZlbOi6HgudICKrwawUekDipgdVzjcsQyOsvTDbbAXZeapaa6RTlgPBt4/S2oelF3x5QPL5/MUAkK0BIPRY1VE1y5XQdf17hJD9EonE6g0bNgzVLmc+n/8jIeRnvb29t3kplS1bhoBMGykSrLBQQVmwoANw3GD5WtsbBRcdVzu1PIbPeRKsjvpaHmybobOn6n3w/i5KcRzXeOHCTl/7vxFv46ITKgAE9YLoDmu+XRz3piq5CkMnNL/y/p5U8bFSluIoGaEqauLMVX6q/IDVDE9nJQCpPXJFj18AwMGGYZxZmeSKFStaCoXCb2gQeiaTOWb9+vUj9Ddd10+3LOvO3t7el8v/vgUArjYMY40XAJFlILaPBgdI/8tQ+MpuNrHpS54Fbd5OdYTz2og8Gw0uzByVmkZff8FeqBOC5Sf2hhyYSQ6EoRNmkn52LAQgwXEegVJwvKz0FCWezkoAsmzZskWlUmkt9Wx0dXX1Dw0NUe8FBRE3V5is6/ovCCGtpmmeAAAl5u8/BoAhwzAu6O7uXp5IJNZkMpllFYDCW26qVNATEfxmYHtU9sURPSDhLizTu6P8gveAxEUnUFYq2yfokZ2RfRLH9Q1DJ8zIYjUYBAFIcJyPkrEcBU9N5f0RBVrDOq5t88CviHZ3dx+radplANACADeZpnlRPp+/lhByMyFkQzKZNACA/jdRHovQdLsrVqyYXygUfq5pGv3kXSSEnGua5gNe9KhQKqo2X+zGHdwMnT9yjmDR41W8I1iVNoNnuY9gNfq7lzyp/hqhco3D+qoRB52g8gWiUmZUvDBxvqJazF+7MA0Nf5Q197QKW0GWUlWyjXTKciD49lFa+7BsBd8AJPhlmb5HFUpFlaDEblwEIDO2neaSsaFCJyAAmTFRtT1NCHzC5/dc0gmUW6r0gsxKqZJtGRpV6rq5SmfUeIoApOI+IYS88cbMB6HjC1BWFci3ZzNcoQdEnn8yT8wlY0OVoaHKeMBxZSS9+bZx5HNYhkbzq9D8k6r0ggzFqmRMhsaoGcsqbDVZfkaNp2HpBfSACEiOKiURu3E5HhAXMDnpLui4/gh71fAIloDwcpogAGmed5UnY7c/0RPhX2gEelApV2EZGgLTDrwJApDgWKpKJmVnEBU6EYA4K4sAREDCVQl17MZFACIgjcE0QQDin4+x258IQPwLjUAPKuUKAYjAAgXYRNVay04B6ZTlmHf7KPE0LL2AAMRbTvAMsgCPgmjCO4KFHpAguOvuAwGIf56qeoHguP7XTqSHOPI5LENDhN9Bt0EPSHAcVbUXZGcQFTrRA4IeEGHZrgj1lk1GtVAee/xHuCPJhqo2k59xeZXKRaaOAESES8G0QQDin49+9omf0XFcP9wTfzaOfEYAIi4fQbRUJWOytCOdshzzbh8lnoalF9AD4i0nVQ8IAhBvZiEA8eYR20KVEkIAIrdOjVqrXDsVgZY4X/8yI9KDSj6HZWiIzDvoNugBCY6jqmRSdgZRoRM9IOgBEZZt9IAIswoQgIjzSqUSQgAit04IQJzCiwh8/MuNVw8q+YwAxGt1gv1d1VrLzgLplOWYd/so8TQsvYAeEG85QQ+IAI8qTWQBCC++g03DKxsDMvyRG6H0poMlqI6ncRWWUpFifACNVX3pVPUCwXEDEBqBLuLI57miE+jyqtILAqJVbaJKxmRoVPmhbK7SGTWehqUXEIAISDh6QASYVG4SFAAZPvkuaL/OSbc7xKTeZe/ZOJzkc/dD+2+PtduTVAaGT74brG2XCROu6kWgctywlIow0wNqqMrQULl26IkISHim6SaO6ztXdAICkGD3h6q9IDuLqNCJAMRZWQQgAhKOAESASYoBSMvD34Hsg1+tEjp2xFUwufI0YcJVKS6V484VYwMBiLCY+2qoUlYRcPlaOqGH59KxTAQgQksu3EjV3hcmsGJ/KDomKksnAhAEIMIygwBEmFXSMSC841XSHpDnH4D23xxjE+p4QO4Ba9ulwoSrUrAqx0UAIiweDRuqXDs0yP2tncjTcVzfuaITEICISLh4G1V7QZzCskGLAESWZZ7tw/wwgR4QT/ZPxQdgFixvZvk5gjV8zA3QfuMJ9iAjx94AbX9w7nlHsNhYD3ZcjAERWCcNYK4YG+gB8V7vIFqoMkJw3CBWz7uPMA0N79GDb6FKL8jMRJVsy9BI2yKdshzzbh8lnoZlK8QOgMgayOzmQwAisKmYauYitVJcwIEBIKPvuhJyd19YB0BG3vcTaLvtk/bf2ViPZtaVnY0qZaBy3LCUireUBNtClaGhcu3msgckkXgVFiw40BaSLVvWAiGLMPtWsFumYW8IQGaAyTVDqNIhsjNFOmU55t0+SjwNy1ZAANK52FNS8AiWJ4uqDWSBANt+dPU3IHfvRQ64SLaAVpqsAyDjb/80ZP72g+p4lVgP2XFrZ6RKGagcNyylIi4twbREABIMH716mSlZRQCiLt3xXNEJ9juEEPLGG0NAiJdkq/t9pvaU3xkinX45WP98lHgall5AAOIBQFxf6DmZmUS+9DcjvqoE1M+4skCAbT++16mQeeLndaxij2CNHn4l5O5xPCMk2QrDp9xrx3rIjosABI9gNbMn2Wf87BM/Y8/1cWcDAGFp2Lp1LZRKi/wsmdSzKtc3LENDigEBNUYAEhAj8QhWcIxkelK1z2UnE6ZnFAEIApA6efSzMWSBQGLzY9BxvZNud/TAiyG39utlcNHYA+KKEzn6GigudwLPZcdFAIIARFYRo8zMzJd5BCAzw+dG8owAxK9WkHvez7tWbiR/rZFOf/xr9HSUeBqWXkAAggBk1gCQkSO/D21rznXACCcGhAUg1DNiLd4bAUgTujHMrxpNkOPrEVVfOlW9QOb6uAhAEID4Ugjlh1XpBRnaVe1lGRrtD3wRyS4VFTqjxlMEIAEpFdkv5XgES05VyfKX9YCwAISXBYs9goUARG5t2NYIQJrnXeVJVS+7uT4uAhAEIP53J8aABMFD1bpOdg6qdKMsnQhAHI7FzgPCGrysAcsTIAQgclsrDADiynxVE5yOHhC59WFfKGF91WiOouafUvWlU9XLbq6PiwAEAUjz2mDqSVV6QYZ2VXtZhsaoGcsqMgTK8jNqPA3LVkAAUj7CgwBkigN+lKJsPQ4RD0ht5qsKpfQ4Vqn73Q6Slkz/W7vefubcjPJR/WUJPSB+Vq389UbRsYS5LqsIQBCA+N+d6AEJgoeq31Oyc1ClG2XpRACCHhC7wF3lCzoCkGAASPK5+6H9t8fanbF1Onj8FQEgI0dfA223nun0mUiDZhXse/bIFpspq5msZKoUl8pxw/qq0Ywy9vOMqi+dKtdOxVe+mZovApB4ARBd148DgMsIIWlN035pGMaXWX2wYsWKHYrF4k8BYEdCyHAqlTrx6aeffsFLZ6jSC150sb/P1J6SoalRW6TTLwfrn48ST8OyFWLhAeEVu4s6APH71Z8Lunx82W15+DuQffCr1a4rdTr8ABAWXIy97RzI/v2Hdnejqy6H3H2X2fe84HRRtaFKGagcNyylIsrzoNqpMjRUrh0CkKCkp3E/mIY3XP5Wel+yZMn2qVTq0XQ6vXdPT8+ArutrLMu6qre39+5KG13X7yaE/NY0zWvz+Tz9ErXaNM2PeFGoSi940YUARIZDcm1V6WQ5Kp3WUaE1zNMSCEAifARrNgKQ5PMPQPtvnNS4jgfkHrtOR1AAhAUdCECaUXtTyg8BSPP8U/kCUfXimqlx0QMSHw+IrusnEkIONU3zdLqndF0/iRByiGmaZ9B/L1u2bIFlWU8bhrE9/feKFStaJicnd+7t7X3Wa/ciAPHikPjvM7X3xSlq3DIqdKp8f8jyGAEIw7FmlAp6QOREzs8mDiMGxFWIkPF6IACRW9faL28IQJrnn8oXiJ/96WfGMzUuApBYAZALCSFtpmleWgYgqwkhF5imeST9dz6ffzsAUJf3A5qmrQaAF0ul0jkbN258yUuWm7EVvPoM+veZ2lN+6UY6/XKw/vko8TQsWwE9IE16QNi4hGZiDkTE2UtAZ6MHRIQmHiAUSsMbAgBh6Rk6+0mwOhaLLE8gbbzWOJBBGnQS5leNsGjm9avK0FC5dngEy1vKaoGMZYlXM8cjWN78DaJFPp+/GACyNQDkc6ZpHkX7X7p06TsIIQ9ZlvX+3t7e23RdP50QcqJpmod6jU/1wpYtQ0CIV0t1v1MdsmBBByCdwaxBVPhZ+YAVlbVfuLAzFKwQSqfBiFLjXpoxNoLygIwe/RPI3fpJmzCSbAWtNGHfIwCZWiseAHEZ+SfdVa1+7qpszhQi5NYBEQAgbJ8ia4MAJMwdG37fzeiEIKhCABIEF+v7CMoDggBEbn1UfJSoPXJFj2QBwMGGYdhZR/L5/BIAeMI0zU7675133jmbzWb/bZpmu9fsqF7waoO/IweQA94c0DSqHYK/Quk0eDKnemzG2AgKgEzsdSq0PvHzuumJGLnN8MTLwBHxNoQx7nR9IgCR47jXGsv1Jt5ahbEhTp1cy2Z0gtwIjVuHuXbTGc9hjjvt3vaRnEKG3whA4nMEa9myZYtKpdJaQsh+XV1d/UNDQ7cBwNWGYdxckRld1/9JCLnQNM3bly5d+iFCyLmGYRzsJVPoAfHikPjvUfEsRIVOyvmo0Oq8b2apB8Qrhd7uu+++dyKR+IGmaTlCyKimaWcZhvHkqlWrUps3b/6xpmkHEEIsADjdNM2/eW2JZoyNoADI6LuuhNzdF9okEqYgHgKQqVXzA0BcAebv+T7k7jjX7lg2BgQ9IF67yFF+YZ3rjIJO8OaQd4swgQACkAPtBdiyZS0QsgiaOXIWlAdkYOB6mJx06JmJK0y58gKYYemE6cbt7u4+VtM0ms6wBQBuMk3zonw+fy0h5GZ67Gr58uXdxWLxGgBYSA8cWJZ1ysaNGzd6rUUztoJXn0H/rmqtZeeBdMpyzLt9lHgall7w5QERTKH3TwD4pGEYa/P5/OGapn3LMIy9dF3/LCHkLTTbRT6fX1ZWPPT/FIxwr2aUSlAAhD0WNHr4lZC7xwEjCECCASCuFLsIQLw1mI8WYQGQqOgEH6yrPhrmCwQBiFoAkk6vhXnzTrLXmpBW6Ou7CUolPQix8ewjTLmajQDEkyFNNmjGVmhyqKYfU7XWsgQjnbIc824fJZ7OSgDilUKPepny+fwppmn+L10OmlKvVCqZpmkuyOfz9wDA5aZpPkh/o//WNO1LhmE8FAUAIvuV3Vsc61t4CehcOII1uvobkLv3IudFn0iBZhXt+7FVl0O2XOODDfgXScMruzYYA9KMdDZ+Jio6IYgZe+1PP2MgAFELQLLZq6G9/VvVJRwaugLGx2l4QvhXmHKFACT89ZMZQdVay9BI2yKdshzzbh8lns5WADJtCr3aJdB1/ceEkFTZ6/EMALzXNM1NZQByPQDcbprmrxGAOBzwElA/AGS6Z73GnfYlNrgZOn+0h92E9QzxgtDH9zoVMg3iasb3PRsy6652gAkT8I8AxFuxibQIywOi63okdIIIj7za+NknXn0jAFELQOo9IDdDqZT3WrZAfg9TrhCABLJEgXWiaq1lJ4B0ynLMu32UeDorAYhXCj1mCRK6rn+PBpolEonVGzZsGMrn8wYAvIcFIJqm3WoYxm+9AIhsyjpq/HZc7RjF7DGq4ZPvAksgDW/l2dEP3QC5359Q1w9N3Uo6g0/d6hWkxM5LlobpnvUa1wuAVPhF+dt+3RF2c969K66G8YBM5t8LLebtdUOxnpHxt50DmUpVdObIFttGdo2Hz5n5NLyiqfj8rHctI8MKLJsNOoEa79ts4xiwW7euBZn0q96vjakWfvaJ1zjTzSHMcb0MVFFZ9ZrfdL/Xzp3GgDQzrh85sVdDgAAAIABJREFUYJ+lMSCFwszGgDQzXz88p8+GpRP80tXs83gEq1nO1T8XJWO5mXix4Dgl3lOUeDorAYhXCj26FLRyaaFQ+A0NQs9kMsesX79+hP69fOTqMhobUvl3IpG4dMOGDQ97ARDxJXZakv6XofCV3ez75Kk3QunnTqXu5AnXQXLlR6btjvss00/6kmdBm7eTLFm+27O0ydLg59lp14fhderch6D4/YPs5rx7dj1gvzMAHv2p0/2+JwGso04x+nArQNFJeQwHnwfwwHec+0QawCrUrWviw9eA9Vs7i6M9bmKXtwmvsSwffS9iuQOR9RBpI0NPGKn1ZodO2AwAe5ZZsR4Agv84IMPn5trOhTk0N3MAdu5/oJu+yY788NDPs02SOwseC0MnqJoWApDgOB8lYxkBSHDrTnsK67SE3bcfUgVT6P2CENJqmiZ1HZQq4+m6fj4hZDk9jqXr+lJCyB2dnZ35devWORYl52omtR775Xj08G9A7p5yzEGyFUY+fg9Y29LY98aX61n0gHiKC8svEQ8I65FyHbtKpEErg4vR918DuVscQDHZ/V5o6a33jLgSBDDekKh4QLY+Z0D7Dx0vHc+bFQUPyGzQCbwv336+iDcS/DA9EXH2gNDjT11dUwHgAwM3wbx5+0oXa/Oz3uyzfX1roVQSL2LoqSQ9GoQpV9MNjR4Qvysn/zwa9vI885bhDnjjjdldgLJi2EcBLM1aAEKZOF0KPULIhmQySY9a0f/Kn7CBGIaxz4oVK9KFQuGHlTS8iUTi3A0bNtznJY7NfNVg4w9qYw7GjrgKJleeNi0AqcQ0sMeF2EDn4Y/cCKU3NfuVjj9jL+U022NA2PS5vHuWjzxwwbZhM2URBqS42ux/PmQf+bbNWFpdvbjnx6YVq9kQhL5lk1E9JsjLquZnvWsZEKZSUa0TePETftKy8gBI7QskqDHiHANSGwA+PHwFtLefJW1U+FkLrITu9Sae/b83YyvM9Ky83vEzTQ/3Q+wM1QDyO9+o8BMBiLPSvjwgfoWlmeebUSqs4camz6XBzcOn3AvWtku5pKR6/gBtt5Wrn7Nf5dnsTakMDJ9897SelGbm6rWZ/BikMxGE7gJpx9wA7Tc68TO86uci4MIVhH7gxZBb+/W6PscQgHiKW5gAxHPwgBvU6oRUaj3Mn/9Be5S+vj9Csegcx/JjkDZ6vlF9Cr9jVFgz2wDITBrktQHg/f03w/z5+yAACXjfzORHiZBJb9h9M7bCTNPp9Y6faXoQgMwcx6O09rMyBmTmlmpqpGaUCq8OCE3vWlzuxIPwrta/XA6Zv/2g7mdZT0ozvPIS0LkMQMYOuhiyDznggvWeUI9G2xqnQCF7jx4QOQlDACIfnC5SoXuuAhAeqJOTOrHWLA/7+6+HYvFApYUIaSKDmT6CpeJoxlzSCVTSmrEVxCQ0uFZe7/jgRvLXE9Lpj3+Nno4STxGAlFewGaXipxBh6ukboe1WJ/6APfLj8qTYHhAaS8L3pDQjvl4COhcAyOiBF0Fu7Tfq+cvGcTDeE9ZLwgMjYys+CtmeX9l9Uo9JYb9zpmU/HsFqRjpnzzPoAeGvhSwg4rUPy6vUiHIRoCcifbJzZ/ucSY9P7Vy89L7I3JtpgwCkGa75e0bVWstSjXTKcsy7fZR4igBEEQBJbH4MOq53UsmyX+VncwyICDAJ6wiW6yXO8I53HGti+XHQ+vTv6nbrKANA3MUKmeB05ggWC0bG8v8BWfNmZ832Px8mD/kiApAaDswlY2M2AZCgPAUiR7C2bjWr6Ya3bGns0ZE1wtn29Pha5Shbf/+1MG/eJ2wpCvJYGwKQeg6oMkzmkk6gXG3mY6W32RhsC1VrLTsLpFOWY97to8RTBCAhABCRI1gsAGGNYtlq297iKP8i4oGIKAGQUQZEuDxMDADhFSt0tWf6GXvzEZB97i4HgKz8BEwe4Rzl4l3oAWlGOmfPM6oBCAsEeIa6LLdmGwAZGLgSuroutKfB3rMghQeC/M69UayNSJ+y4IvtEz0gIhye3W0QgAS3PlEyllUcX2yG01HiKQKQgACI62u6HYQ+fRpeEQDCxijwMhiFIaBzAYC4PBdvOweyDQoLuo67aQnQiFXHThaMzCUAwqsg71fm5tLXTgQgAH48IDyvBwsuwgAgotnKEIA08/aQf2Yu6QQ6ewQg8jLA/UiHWbCCY2a5JwQgMcyCJRs8jgCk+X3H8o53BIsFIK4MV5wYkIndj4TWjWtsoggnjdtcAiA8HiIAmZLLuQhApjvKVXlxBXUECwFIvY5DD0jzen+2PIkAJLiViJKxjB6Q4Nad9hTmh4nYpeEd2/88yD7iVNIWScOrCoCIHAtyBdcztUiiegRLBIDwaoW4PCA7HwzZlx6w1zjqR7AQgHgrUwQgYh4Q3nEpBCAIQMI2NLx3cfAtEIAEx1MEIMHxstJTlHiKR7B8HMFKPnc/tP/22DLoaAGtNGnfBxUD4vdrdCPRFgEgrnkxtUjCAiAi/bJz4RnP3KDyVZdD7r7L7C548Ta8WiHs38cXvhUybzzlAJAVH4XJ99WnUWbpFOF18OrH6bGihHiFCBGAeHMeAUh0AAgP7LBHyGZDFix2b850VWVVhkmYXzq9d3HwLRCABMdTVTIpO4Oo0KlSvzTDUwQgPgBIy8PfgeyDX63jOwUO1uK9p12P2ewBqZ1Xpaq7CFBoJguWSL8iAIQXVM56QHgZx3iFCMf2PRuy6652QCZzNGuuAhD2SJuIHNcK+VwyNqIAQGQDov0cwRLxaPAMftZLEkYMCAIQ79e/KiNqLukE+z1ACJlp8Oi9uu4WqtYa6ZTlQPDto7T2CEB8AJDk8w9A+2+cgoMkOeUBETHcZhsAYUEA9eBUa5QwtUhEgIJKAOIKKmeqy7tABPN3kUKEhR32gfRr/6jTEghAGivOuWRsxAmAyBrwPEARBgARyYglSz+lU0UQusovlKoMk7mkExCABGswq5JJ2VlEhU6V+qUZniIA8QFAWGObNX5ZAMIzyP0AkKCyVA2d/SRYHYttDvCyIg3PQAyICLAR8YCwa8Cm4eXFd4gAkOI23ZDa2osARFC7zCVjAwGI+wiWiAeEB0z8eEAQgAhuPo9mqoyouaQTEIAEI4uVXlTJpOwsokInAhBnZWMXhM47uiILQGqBTKVYIZuGdyYBiMi47GaeaQ+IO/3xlBeKBSDu+I4UaFbRJlkEgIy/5XjI/PPXjpeLEezx3Y6CiQ9dN60ei2IMCB7BmlrSZgCIiLFcKzS82ASROiBBHcES8SCwx7dq65JUCgvGDYD0918PhcKBUvaMKmNG5bhhfemUYnxAjfEIVkCMZGIV8UhbPHkall5AAFKOAWE9HaxnxOUBOfwbkLvnIsfITbaCVpqoM5BFgICIJ4FnFPM8ICLjqgQgIsUEXUewtBRoRByAsLEhkx27QMvQi846aUkYPvU+sLZdxtUcsxmAJHvvhPYbT7BpZ1MWIwBxAxBZEBAlADIw8D2YnDzanvBsAyAswGHvReqS8NagNv6lVNoTmkmtmU6vhXnzTnL0AGmFvr6boFTShS0IlUCgmfkKT4zTED0gfjko/7wqGZOlFOmU5Zh3+yjxFAFIeT2b+arhSld7zA1Vg44HNHh/n9jrVGh94ud1ksXLgoUekMeg4hlyFxNMgkZKdXz0cwTLBUA63wQtg89X+68E5/NUwmwDICIeHwQgMwNApjP4K7EJsuBHpGJ4S8st0NX12bLx3AJ9fTfbxnMYAIQHIkSC0EUAiMiRMJYnQQGQbPZqaG//VlVQhoaugPHxE70tg3ILVQaCynHDMjSEmR5gw2ZshQCHF+pK1VoLEcc0QjplOebdPko8DUsvoAdExgPyrishd/eFjlGAHhAgnU5cCu9ye4+uhNw9Du/GVp4B2cd/6vCRDUJnKqGzfx/+0K+g/fcftdu7smCxaXuZezYNL4EEDJ/2AFjbLuXSGUUAUusNKXW/21vj1bxQwlIqUoQE0JgaGn19D0HleBFbtZsa0cXinvYoIsZ7LTmqAEgudyW0tf2kSk7FeBaZg+wRrNkMQFjatm5dC6XSImGJcXtAWkDTnPTrIgCQtlNlIKgcd67oBPvdglmwhPeKV0NVMulFV+3vUaFTpX5phqdh6QUEIBIAZOTYG6DtD+XjMEwGqqh7QNgA9uk2hsjRMVa4Uz1/gLbbPukADSb7GGs8s3EfowdcALm/ftNuP770A5DZcJMDWPb/DGQf+Z4DQA65DHL3X27f86qoj2+jQ2ar4YyrJWD41PsjdQRLxAOCAGRK0uYiAGlpuRW6uj7jyDChHpBboFTKC4GoqACQ2viUClAUoV8ERLBgjR5jq/BT5FmVBoIqIwqPYMmaZv7bq1prWcqRTlmOebePEk8RgJTXs5mvGkEdwWIBCGskRhGA8IoYBglAWv9yOWT+Vl8EkAccxpZ/BLJP/8YBHSs/AdnHry0DkPMh+8i3nfu3ngjZp345LQCZbN8JWoZfrmqAqB3BYtMrs7xy8e3AiyG39uv2HOlxLPSANPaA8OInRA1SVR4Q1ggXiQFhj0uJeDRk27NeJfbezxGsmQQgzcT8qDIQVI4blqHhbY4F36IZWyF4KqbvUdVay84T6ZTlmHf7KPE0LL2AHpAmPSBRByC8IoZBApDU0zdO1SnheEBG3nUVtN39BQdc7HEKZJ/8hX1fXKCDlkwDSWXsf6c2r3ParPgoZHt+NS0Ameh8E7SWY0BoRqzRD14HxfxRXI3gqjZ+8l1QWjR9cUpv1SLeoqKE+v5+G7T95lj7QfZ4nxt0XAS5td9w2jBH1xCAuI9gDQ2dBx0d33H4ZHsPnPiJZo7kzAYAInKMTBZQyLZHACK+p/22VGWYoAfE78rJP69qrWUpRTplOebdPko8RQBSXs9mvmoE5QEZZWJAog5AXMUZmSKGQQIQXgyI6wgW4+kg6RxohdFpd+7Emw+H1ufuqQMgbJ+TkkHoLjqZNWYzi3mrk+ZaVJTQ4C1XQOaBr9Z1ws5rYvlx0Pr07+raIABxA5CxsXdDNntnlU+V+InaoORKg+myN/EACO/LP/t3nudC5AgQrxK6SED3XPKA8LwtIjwUiZeZbteqMhBUjhuWodGcdvT3VDO2gr8R5Z9WtdaylCKdshzzbh8lnoalF9AD4uEB4cUxzDYAwtLDZkhi73mpesOKARECIG89CbJPXV+3W4vb7wnW/DeDVhwHbfAVSL3+lPNFW5vKoDW66grI3XdpHRhxBaHbMSDTB6Hz1ngmAUjfutuh7dfHOHNkEhzwjl2hB2RKZGpjQEZHj4Fc7kaHlwRgcPDHMDl5BNcDEiQAGRz8EnR2fqk8duPsVSLGcxgARNaLwcuCxXqYwj6ChQDE25AJqgV6QILipHg/UTJCVaSGFuek0zIq/IwSrWHqhdgBEF68Bq8OCC+OIYoARITm6TaGryB0NtvVvudAdt0PbYVhtXRAYnLIvi/NezMk+5+z78dWXQ7Wgt3s+8SWZyF732V1uoiNE2EN9fosWNMHofPWeCYByJZNBnRcvYcDppgEBxgD4v0KqgUg4+OHQCZzf/XBRhmkWKAQJAAZHT0Bcrkbph07bADCGu0sWPADQNzH2tKgaQV7jghAvOVTtoUqIypMQ0OWB0G0Rw9IEFyMlmGvau80w+mo0BqmXog8ABExikWK9/EACC+OQcSYn8k6ICIeEBGagwQgPMN+bMXxkO1xqpaz19h+50H2UefsPgtAki88DJl1V9t/d1U5X3E8ZMr9sIZ6oW0xpEc2V7v2CkLnrbEqAIJZsOTUeS0AGRk5HtraHPkiJA19fbfWZZASMZxt8Jt4FRYscCposx4BHoCp94DUZ68KG4AMD58B7e3lNNckBZpWLujJxMaIBJKzgfrj44dBJvPnuoVh+cjOnZ2jyDE2XpyL6Do1khh3FqwroavLSQNO+ywUVnsKmSoDQeW4YR218GR2CA0QgATHVFUyKTuDqNA5nZ0lO+ew2yMAYThcq1TCBiC8+AARY342A5DpCtnxNrErluYjN0LpTQdPK/suw57xgBQWLIX0lg32s1ZrFyQmBhzQsT+T7YrxgKSf/BW09N5eN1apY0dIDr1i/330QCZAm7piy61lg9DZOJ9IAhBiAUwMgVYYA9KxA3d9wlQqYSvE2v5rAcjQ0DnQ0eF42OiX+/HxT9v3rEEqati6jdjvuooDVupK8PpSFQNSGwNT4RcFYxXPBQ+AuAHUFHghDJAhJAma5hQSrQVcjWptzAYAMjh4MXR2Olnj6NwnJ4/zFFNVxozKcRGAeIpFoA1UrbXsJJBOWY55t48ST8PSC+gBKRfT43lAXEb3yXdB+3VHOC/es56sFuKTBRrSoOnsJ8HqcIr+8bw5PA8IW4Gc14at/D5dUT5X6l4mToFnqLM8HV96DGQ2OOfy2YvNfOUCIEf+NxQXLgdItkDyhQchd1/5XD0TA8L2M77XqZBpUKWetvHygLB0sqmWlQGQE++Ajl++x57eyJHfg7Y1Tj2I0Xd+EXIPfs2+d/HqbedAabcjAErjoBVG7MAHktkGSm96J1cLxgWAsMamXwAyMvJJV3HACnN5XoAwAAivRgbrrXB7QBKgaVadHPAAyNjYeyGbrQf7bAc0robKjy2HnPazzQOCAETMIArL0PAePfgW6AEJjqdRMpajEKti23IaQBRoDdNWQAASMABhA7plgQmrLnjAh+d5Yf8+uvobkLv3Irs7tgCgXwBSm7q3Qq8QAFn+EciUa3y4AMj+54O1494ApQJow69Xq6UPM+lwXUDmrSdCplwHhO1ndNWXpkBKjQdkbPXXoLDvmVxtrAyAEAu00Tdgm9QQDD73FORuPsMx6g6+BLIPfMW53+tUyJaB1cSb3wWtz91t/3186bGQ2fAHZ40TKRg77MtAunauzpGk26G060EIQJiv3X4BCGvk0/S+la/9fK9B80Ho6fS9MG/eJ+z1Y48MsQCE531gje3R0WMhlyvLCccDIub10EDTqD/Rfbk9I42rjYt4QHhgTdRT1UjQ2XFZrxjlz8SEw9vpLlUGgspxEYB4SUWwv6taa9lZIJ2yHPNuHyWehqUXEIAEAEB4Rf1UARCeN0A6ToTxvNDt5ErdK+ABSW64CdrLRjWb2WlyxwOg5ZW/OgY2BSA77AmlbZeBNt4PHdc7HiYeAGFjPSrHt4rbvRUmVn4c2u78nP1sKTMfkuN9VQ0wueyDMPZ+p6hhQ0Nl82PVcUP3gJQmQet/ARIjr9vz1cCCznmdMPTay5C9w/F00PiXStA9m3aYjX+Z3OlAaHl5bXU6E3t9HIq7HV79NwIQ5whWkB4QXgxIbeA5K2ONAuBFYkBYAEIBwsTEyXa3LADhjcsCEPaeF5DO64cFXKOjR0Mud6tNA+sBYecqGwMikjEMAYi3IRNUizC/dAZFo0w/6AGR4db0baNkLEfBq0C5HSWeIgAp7w+VMSA845RX1C8oADL6/msgd4vzBV/IA3L4lVVPgogHpDYepAIChmoACDsfNlNTIw+ItvVZSBu3QfaBL9dpNraY4Ng7vgCT+50N0NIOvIKALg/Fkd+HtjXn2n1OvPVj0PrU/zn3Kz4CrT1OFfWJ7faC1tefcIwlyUKEoQCQ0iQktm4CbeR1AAo6kikALWHTR78AdHZmuQCk2LETpIamqrpXmFnnAVn9FSCdOyEAseM+pmJA/AIQ3pEn3rGrWo9AX594ELr7i33jYoosPbUFF6c8MlPxDrVHjyqB2OwRLJ4nhZeG1w1GprwevGxiPA+ISMaw2QBAtm41YZttnEQEIuDRr9mnyjBBAOJ35eSfV7XWspQinbIc824fJZ7OWgCi6zqN5ruMEJLWNO2XhmHUW5wAkM/nL9c0rWQYxhV0aXbeeedsNpt9XdO03spSGYaxT9lm5K6eXwAiclyIjYkQOZ7DK+rnB4Dw4i1EAAgLKERiQEQBiAsgHHMDtN94gr1OtTzVBl6C5KuPQ+u6n0DqlUftNlZuW0iM/tu+Z9PnDp10J1iL6bLXxLcw4Ic3LgVBret+DKlXHwMruwASY1vsfsZ3PRQyL/zFASB2HZDp0/CKrLG3OmFa0ONk1MMxthW0sX6A8T4X6GD7agRAxvc9eyrrl5YAjQaW12QAG9vzVMiu/7n994n8+6H41g+7SFTpAVGhE/r6HoL58z9o82CmAUhQMSCsoT429gHIZm+qrmnFk8ICEB6I4HlARNLwsmCEB0B448oCEN7RL5Eq7SJAgOXn8PAp0N7+i6p8jI873tLproqBgADEi1Oz83f0gAS3LlEyltEDEty623aZBjArAciSJUu2T6VSj6bT6b17enoGdF1fY1nWVb29vc5BdQBYsmRJVyqV+jYAfETTtKsqAETX9YMIIZ8zTdOxGgSv2QhAeNmhRABIbRHACht48RayAIQHLnjFCl3913hAhADI+AAkX3gAWp/4X0g/P1WLgTWYx1aeDtnHf2ZPlYKI4nKnAB8vAJ477hmPQOqF+yF7zxdBI05WHnpNbrcHtLz+ZPXfMxKETkFH//OQGHoNNHr8K5EASKQ8pboKQF59EbJrzrPbFxcuhdQbTpYw3kVAA83271AvjwalRXsDaW0HoGCFELAWLoXxd32D+3xYSkWVTvADQFiDmk0HS5kn4gGZrvJ4sbinvQbu+JProVBwvqiz1/QeEMeTwgMgbhDk7QERKSYoAkBEPBQ8D8jw8FnQ3v4jR4aZLFsiVeYRgHiqFukGYekEaUICegABSECMjNhxIQQgwa077SlMveArBkTX9RMJIYeapnk6JVTX9ZMIIYeYpulE0zqej48DwLYA0M56QHRdP48Q8jH6N0JIUdO0Cw3DmDrUzuEhVSps0TZeYUH2cZGsU7wsWLyv437S8PJiRliaefEWsxqAFCch9ezd0LruR5B6+RHXCrJej9EDL4Tc2isdwyOVgeGT7waLxoAMbobOHznF+NjjXzwAQsGb1bkjZP/8X5B+9q7qeBOL3gatr/7d6T/sI1iFMUj8uwcSQ5sdwFE+WiWkAiZHbKCR2fIUWM8/AtrksNBjoo0GPrMRIDOvYfOwlIoqnTDbAUg6vRbmzTupbGx7B2vXehkaxYDwU+k2BiCyxQR5oEakhkh//xTIYgGI2+vROEMXApDmsuOwfBYBaLWKISydIKqvgm6HACQ4jqIHJDheVnqKEk9npQdE1/ULCSFtpmleWgYgqwkhF5imeWTtcum6TktZk4oHJJ/P04P8raZpfrO7u3ulpmm3tba2vuWpp56aih5usObNABAR0ZlJACKSTYo1xnkxIGwchmyAuagHhAacVkAB7xn7CFbHIjtdbuvfr4b0pntslhd2XQXpF+6z71kAUhskX/FQiACQsf3Pg+wjTrHCCnihQd1tt5wJWnHU/rusByTZe2f1ONnoe74PuTucGJNp0/AWxm3gQWnWUmkREbM9E4mBFyH50l8h+fo/IdH/QtWLwXZQ6twZkoMvOTzcfiWk//W4w8M9T4Ps+v9x5rjzO6HlpQcdPlAPyOJ9gKRzDgDSElDadgVMHFpfPZ5VfmEoFVU6QSUA4RUlZL0p2ezV0N7+rTo54aWrrTXyK4XzeDEgIh6Q2mNdFWJEDH5eLAk/FmYKZLGeFF7AO1ujRIQeEQM7bkewEIC4txcCELHXkkirKBnL6AERWVHxNmF+mPDlAcnn8xcDQLYGgNBjVUd5AZDa3/P5/B8JIT/r7e29bTrWUKWy9TkD2n/ofCmn2ZIqtTnoV3NSzmolzl6nJQUglX6owV85FkSN07Y/OLEOY0d9H7J/coxTdlweDdQ47bjaoXPk+KnCfdS70fZr59gRmx2Kpd/17Cl3QdsvnOxQo0f/BHK3frLuWZYGNpCavZdtM3zOk3bGm+ocjr2hygu236GzngBt4HlIb/oLtD7yPcdAXn4slLbbo5rNaWzfsyC7zjluwRb7oyBi5JR7wNp2qW3MV8aiY1dqn6R6/jA155o6IBS8FPY4ATI3nQEtG++w+x/f+WDIvPSAwyMtCSOn0RiQpVyR4K1xQ3myipB4vQe0gRdBSwgAj4khSPRtguTWjZB85e+QGHQHlJNEGhI7LIeJ+Xlo6fmdI2dMFiwWuPHux/c4GaxuRz4qlx0D8qbp0/AuXNjpa/83YqgqndDf/xDMm9c4BqRQcIrOUQOtEkzMGrm1R7BKJefYFL2SyfXV2BIRY5ttQw3vSl/UA9LVVe8B2bp1LVjWojr6agFIsehU7k6nb2GKIU4VFmTHdRdidBdl7Ogog3cmJS8PQPFBzZXQ2TlVVbySLphXE4SXPYwFHSJHwgYGroWuLid9Ltsny0NWJtn1ro0BmZiYPgbELSt/rMoWbyyucmniB/rCX7CgA7ZsGbL1r+jF0twMnY6RGbxOEKU/6HYIQILjKAKQ4HhZ6SlKPA3jYyXlgy8DpPbIFT1+AQAHG4ZRV3Sh1gOi6/rplmXd2dvba1tkuq7fAgBXG4axZrqlpkqF9L8Mha/sZjdLnfsQFL/vGFrpS54Fbd5UJiAZkSk9/hso3eCkuoRkGlKffRQSi1ZAqed2KP3cAQuJD18D1m+dqbHj8u6TJ1w31WcqA6nPPGz3ydKf+MB3wbrps9U+E7u8zb5n2yRPvbFKg3bAmUD+ek3d1Fga2PbsvWwbyk96VXjN6zf5sV8AKY6DdfPn7Src1Q22+mIg9zrVh7XjfgLkdw5wcs35k3dAovuwujmza1m87Ytg3fff9ctJefrZv9oGfGH9jUCu/6jTZoc9AF4rx4CsPB5aTnCCT3kXu8ba+64EcptjXFF+0fUglgVkYDPAwMtAhv5lH4rUOEetCLUYtj4P1vMPA3nhUYABp1K765q3C2hv2h8Si94CsG0etGQayMgWKJVlK/G+K8Eq0wAHngOw1kkpy7vXVl8MyV32dQ1B40GSu6+adt6aRlVgsJcqnQBAvUQVEEYLMDreIYBPAcCmRzk+AAAgAElEQVQh5cN4AwBwVvnv3wcA52MCAP2O4sgpAD3Kt5JhCtsvPTboyAbAqQDgJAFwXzcAgPPBwt3XZgCoABu6fysqcj0AOEVGAdg2LH20z8rcaA6PH3iMez4A0LA7elGddl35nu2TnpL9afnvLfSTQfmepZ+9v5zmGmnQD40zcmoOAdCYp2L5vpWmR2D4UKGf7ZPle+18Kzzk0UPXqdIny0OWNSw/KXCppOKm/KFjT3exz4qM5dHdjPzM0szjyfSEhKETZmTqDQZBABIc56NkLKMHJLh1pz3NWg/IsmXLFpVKpbWEkP26urr6h4aGqPeCgoiba1nQAID8mB71Nwzjgu7u7uWJRGJNJpNZtn79+pHp2BeWB6T19nOrKV3p+OMHnA+Th3wRZD0grJdhfL9PQ+bRKWPB/lq/92muL/21Hgpr8d729FlvwOiHboDc750Xsst7wNTikPVuiHhJRD0gY+/+DrQ89lNI/rsHSEt7NZaBPS41dtBFkH3ICYp2pQZmvFZcD8jTN1bTELPPsl4l1oNVap0HyYl+eyzqNSi8u2JcNpYs1xofejlk/+IYWsMfvQkgnYPE0KtOcHeS7/GgRRSTL62F1ItrITH8mmsgWijQ6trVjnMp7vIOIF27TP2uAXR2ZGHoXy9D9k/1dUBcR9eY4oMub8j+5wOhxRyZS5UHRJVOGBy8ATo7HSBPyFRswejoKVAsOh8oNG0rdHQ4AGJ09MOQy/223D4FmuYYzv3910CxSAGxkybZ7XGYOlYkEk/BekDYr9O8r/dsG74H5Fbo6nLkhHdsaWTkeGhr+3Xd3Ng+ecexeN4Qd2atKQ+ISA0RXlYr2axcfjwgIyMfgra23zv7evgUGB/nH0+kbWaDB6Svz4T5851kBSIeDfSAuPU7ApDG77tm/ooApBmuTf9MlHg6Kz0glL3d3d3HappGtTn9jHaTaZoX5fP5awkhN7PHqWoByIoVK7YpFAo/1zSNujKKhJBzTdN0zs1MczUTAyIShJ75Uy0A+RxMHHyxDUAq6WbZ+ACRYHA2RsOJV5g6atQoroJN/+uqucEcfWLjMJTGgHzgF9B+0yn2ShXefBikn/uzfT++z5mQ+YfjoWGrk/OKI9al8LWPAXTAG29MHT9g43PYtMLss2wbtmAfLXRIgeR0F7vGY++8GLIPOoCFViTnHt0iBLShV+wUwMnNj0NyazWbtP2s1bkTFHd8O5QW7QUWBRycjFhedUBc9T6Y42e1AMSuJs9cKtPwqtAJIyOXQFvbT+qWeWTEDUAqR4fGxw+BTGYqS1vlwaGhC8Gy3gSWNR8sayFkMr+GtraKp2Cqe9Z4Fjk+xBrh7L1sDAhboHB4+Axob3doY49L8ebGo5lXzVwkCJ0HxHjz5R19E6lLwksRzIsHYWMiagHI2Jg3AFmwwDH+eevl9a5q9vdm0/9GNQZENG03jRVNJBJ/NQwjI8JbBCAiXBJrEyVjGT0gYmsq2mrWekBEJxBku7AASOrpG6HtVudYBD2XP/zxv9jGJ2ucUq9Bcfd3221cAdMn3VWtpM0DJmy6XVfaXqaehiwA4Y7F9Ok3DS8vCH3sgM9D9q/uoNrC7kdCofs9kCtX9ObVI2HjXmQBCNsnD4Cw8sYFIMUJp1bH+ACknr8Psvd9yQEdyz8M2aedL+M0FsNa4Bz1o7VN0i88ANrQq3YF8wSt8TEx6BJtWuuEejiKO78DSOeOQmLvBUAmdzoAWl52qsa75rXyE5B93DlSYleTn0UARGjiATaiOmFo6FvQ0VHOrEYctzG9RkffD4XC0c4aalursQujo8dDLlfxEiRB05w0zkNDF4NlLSlTZ0Eq9Vdoa/tfRy8wcRMiX+9r40EqdUqCAiCsV4IdS8QD4vaGvBey2dvrVkQEgPBADQ+AsCCCx0N+oHrjwHYEIM7SRRGAiKTtpnMr1w27W9O0AwzDSIqoDwQgIlwSa4MARIxPMq2ixNNZ6wGRYXgQbcMCIK50u0xtCj4AeRk6f7SXPSVuIT8GmLDGclAAhJeVSiTDldCzJ98FVtsODbNgje13HmQfdQJa6VV486EwufJU0Mb6GgIQnucmKADC8pSVsyoAsT0Wr9leC7tgYWGcRhjbnonEK49B9hHnzLyrSvtBXwRtog/Sm+6F5BazofhabdtDadFKKO64L1gL8nJpeNlK6K++BNk1zhGikaN+CG1/Oseh5+3/Cdm//T/HAE6kQbMK9v3owZdA7oGvOG0OvBishbsDJJz52G1pEPqu0wehh6VUgtjnMn1QncDzgBCiweTkO4GQbYDG52SzzunQkZEToK2Nxhc4ICWXoyFotQCEGnWboKPD8YiNjh4HuZyTKGBw8Dzo7HTkXyRDVBgeEB4AYf/Oekl4YIFXCV0WgNQG81cA18DAd5nA+SkQwQMgbnqmwCErEwMD36seRUMA4nAmigBEJG03nVs+n78aAO7RNO13CEBktGMwbaNkLKMHJJg1r/SCHhCGnzMBQFhPhAuAHHMDlLZbDom+5yDR/xzk7nQyqYytuhSy99kF3u3CehVPCq9GSVQByOjqb0DuXifgtLhwGaTeeMa+L+x6MEzu8wknOHt0azWNrcgxtZkAIIWVH4fka+sBSLFhHEfipb9D9m9O9q6JNx0Grc87x8lYg5/+2+rcGYo77AkkMw9Idp59tIp0VAKIm9v0WmkCOhZuC4PDBWj79bGOEcwA15Ejvw9ta5xg6dEDL4bcWscYZv9OwV1pt8OBxqFo41sBCqMAiTRYixyA3OgKU6k0x4nmn6I6YWDg/6oGqWxPxeKukEq9YD82PPxpKJWczHX0YgHI8PA50N7uJASgR7va2pzkBqOjx0Aud6OzdkOfgI4OxzM1MPBF6Or6mn3f13cdzJ/vJLno6/s1zJ9/vH2/Zcu9YFk70MwXkEhsgcqxH14aXvYIFg+AsKCDbSMStyISA8IDDjwAwo8TuRK6upyYHB6IGxk5CdrarrfbEDIFRghpXEuFXXveESwKOEdGvjutmPCKJ4qk/5WVv9r2jY5giRwDiygA8Uzl393dfXQikfigYRin6bpuGYbhBGh5XOgB8eKQ+O8IQMR5JdoySjwN62Nl4FlwRJnfbDuVAGR8z1Og9OZDAZIp0Ea3VL/0u9KmrvpS9TjP0EdvgY5fvd95wdJaGeUUwbIAhI09qTU8K/EpIh4NkVohrn5sD8h2VU8PG1TOrt/okd8F0rYQSKkI1vwl0Pnzg+2fVQEQK7MNJKghDgCljsVAsts4noPiJGilSQD6n1UArUT/Nu6qol4rlzTovbR4XygsORysBd1TZ3uaFWA6JiFAWjuA5BYCmb8rLNxxR+AV12TXm3dP42IK+9i1QF1HA6erYzLXAAhbB6RY3B5SqX+VjVaAUokeo6PG6xAkk696rpxlLYBicTewrMV2GtRs9ib7meHhT0F7O82d4QYg4+Pvgkzm7rq/s4BlaOjz0NHhHFkcGvocdHQ4Wd0GB68AQuaXfWGD0NXlxCsNDl4AnZ3ftO8HBi6FyUma4a0VeADE7TWYCqpnDfsw6oDwwIhI6l133MdU8UR+rErjwoUiR9pGR98FuZyzRhTI9PXdBqWSzpWFqACQIOlUoRO80nbTI1rpdPqWVCq1uqenZ1jX9ZKMB0Q2lbGncgi4QbMplwMmw7M7pNOTRdINosTTsNJzIwApi01dIcJFK0Ebfg1a/vZDyKxzjA6azWjssC8D6dp5GgByebX2xegh/wW5+7/sGBSzAIDwvDM8YDL6vh/ZRntuTTk7E1PLg91to+/5HpDWTijtsBeAlpyqZi4QGxOGB6SwQIf0FkNaIdhrDFq1OODksg9BIX8kQEoo5rHxeFYJgJSAtM4HktsGrPbtAbLbVI9qVb6CyAKQ0QMvgtzaqaxiw6fcW1dNPq4AZHz8QMhk1paNzQQMD18KlrWjKwZkbOz9kM06x64oyJBNSFws7gKp1Ivl52laZqdgA+sZcQOQi6tHuWicSeVY1+DglfbxMHrxY1RSMDz8BSiVlkAiYVSBCevpYOfDCiLfA8Jm/roWKrU8eEUAeR4KEQDirlFyHlRqkfAACOup4YEm1gMi4h3o6PgoZDKPVlkzNHQFjI/TrPGNryANe1lFJOMBEaFT1DOiAoB4pe2m6frLeZ5pfndqr9Bc1k9YlrWqt7fXHYRXw2j6sVKW99geOYAcqOdAWOm5EYA0ACCjh30Ncn92vkRO7nQgtLzsGDP0mtjr41Ckx11G/g25NefZfxs75EuQvb8cxMwWkWPuR/7jZ1DadjmQebuCNvJGw7gKXhC6rAeEzRTFHptig79FMmhRzw49alQJKifpNtAKTpbkySXvgpZNzhfF0SO/DaUd9wNroS4dnB8UAGG3TPZXH4KWF50K7PQqbr+nnVCAejMg2QKEptNNtNjxEjQ7mdb3PGT++X/OWi4/HrJPO8HJbBC6sFIqTtiAhbR0AGlpA9LaBaRrJ34WrHLWLxEAYh+16naSILTeeQFknpiqQ9GomnxcAcjk5F7Q0vJEdcnGxk6AyUl3TZTW1t9DJnNnw2WdnKS1eFogkfgXJBKvQCIxJrz8k5NvgZaWfzr7YvQDkMs53hPWqBYBILWZrCpzSCafqB4DY4HW6Oh7IZdzAsnZo0pjY4dANutk+xoaOgs6OpxioGzmK5HK40EBEB5gYcEUr0ChOwnAVAyICABpa/tsNc6Hpmnu6/sTlEp57rqKGPbCQiHZsFkAUpv0oFh06s7MZgAik7abzkX2CBZ6QCSFj9M8Sl/rmyniGQyX5HqJEk/RA1Je2+mOYLGZplhREEnDy3pAaOByJSjZnQY1YadWTQxttmtDVAKCrcx8SIz3OUbrOy+B7IPl4GAGgNhegux8gFLR/tzadhMtZFYfwM7WAamk6hUBIG6g0eIcNaJAYekHoGWDYwSxFw+MjBz6ZWj7y385c6H1JTp2gNzdX6h7nj12xhrGstnBwgAgrXecD5knneJrtBL62GrqtWJqb9TMhheEPv62c6C0ywF8rUJrgxQn7eBvWv+EZBeANW9XgEyXsCZqdA7UlYKZiQFh+Zz+x88gd49zfp4Cq+FT/lytJl+Rm7gCkLGxwyGbvcfhDaHeg0tsDwh7pVKPVtPrsnVDatu7g9CPhVzuD3Y3pdJCSCbfEF5ntmGptBiSSVo0DmBi4h1ASCcAZFxB8pOTe0NLy2PlOSRgZOQc22BOpx+CXO431b9rmmXfs56XiYk9obWVFqJze3cmJ/eElhbn7+w1OPh56Ox0jocNDFwMXV1OnNHAwJehq8vRBYODX4DOzqvKf5+K3ZD1gPDaj429G7LZekAom2WLF6PhBiBz8whWFAEIFSjRtN20rewRLDade1ObNeSHohQHEIXg7qjwk4pVVGgN0zMaeQ/IyPt+Am23ORW2nVobd9tHUdjLE4CM9UG65/eQu9epjssCkLG9z4TsY/WVx3l6iRq8GnFSek7sdRq0PvE/9r0NQHIL7Hs2foQ91+/HA8Krs0GPjWmWU2SNaCnQaCB2zcWCkbGVp0P28Z/ZLSbffDikX3kUtEmnunlp3hJI9m9yeMSAq8Gz1lfTzs4GANJy/9emAOQeJ8PE4V+BxL+ehMToFqcidk1NDhaATOx8ELS+9JDDr0Qaxg65xAEvWsqO/bG9J6kckHTOiePILgBoaZM/w1NeAy8lxCZBYAGIqz4NxoAQNgZkdPSjkMv9yubwyMhpUCzuVy0sWBF9N7CYyoI1MnJGub3TkheEPjr6IcjlnMJ2k5MroKWlx74vFneEVOoVR37I1NGsuk3X5B9YsMR2wQbSW1YGEonxuhFqj6ZVwAt7VIx3z3pzhoc/Ae3tTqD94OD50NnpZJDjBaGL1P7geUBkAQ71hlS+/LMM8HMEi2fYN7mEno95eUBEaqywfJjNHhBPZvhogEHoPphX86jXeyq4kfz1FBU66SyjQisCEEYmaz0g42//NGT+5q42PrnyNJcUNwQgNC3r4CuQ6H8etLGtkBh4qRq7wQIQlwEPmn3MiMY6WJkuyKxzCp8VqKH+nPPFlXeNv/0cKO34dvtruSuAff/PQPYRJwPT0IlrwNpxX/uepZn1gLCZkLh1NrQEaPTrfM3FFgbkgRG2wF3t82OHXAbZ+y+3/zzGBNuLxJbwAtJFPCA8UMP7wp9+9IeQu88pNDa66nIo7OektKXVzLXBl0EbfQPAKoFmx2dYkDJugcxjTkE3UsO7sUOvgMm3ndU0wPBSp15KSASA8DxQcfWADAxcDl1dzvr39f0PlEpvhkSCegTpnqDfXDRIJHpg3rzz7Ta0MnZ7u5PRyl0HRAyAjI0dBdnsn8p9TWXKGhq6CDo6nDgdCmwqBQ0nJg6F1ta/2H8vFGjGLQpUxkDThquekVJpW0gm/+3IJFPZ3UuepvudjXUpFhdDKuV4Ydj4kZGRU6GtzTnax4IRFnDR6vK5nMMvd8zL6dDe7ny8EKl+zgMm7HE1EQDCyxjG8qLeA3K78BEsBCB+pE7dswhAguO913squJH89RQVOukso0IrAhBGJmsBCK/aOCvGdQCkfTtIvvCQ82WfftGmXzq3PFsFIMVt8pDaWl/3YewdXwBrkZOik5cFa2KPk6D1SSdtZO1FA7WLi/eF0vZ7QOYRJw0ka/CP73ES0JSx1IPDxomMHXQRZB8qBxwztSB4ma/GVp4B2cfLBjXTngUBYytPg+zjjneGTTdbWLgM0uX0ujSCj9a4SL36uEMre6TsHRdA7mEnSw/rQRFJPcxrw9uUgQEQjm6rjaeoNKPzcoK7l/rTitM87aWEEIB4s57qBNYDUvslvtEX8VRqPUzVqZg6UtTf/wOwLJodiUr/ONCYiwqY4RnkfADSOPBcJAaELZRIgQwhC0DTBoHSXQmeLxZ3hlTqJZtBhcISSKcd72ShQI9qOfrLsrJSMSz2fiYaEJIrx8E4R0vZPlnAwvOYDA7+F3R2Ogk4+vuvgXnznCKvtWChEvwuktqX92xtOuJCYbU9FrvGo6NHQS7ngETZNLwIQLz34GxsgQAkuFXxek8FN5K/nqJCJ8/W8Tf7cJ5GAMLw1XcMyKceh8SWjaCVxqe+ahMCKeM2aO1xzlazV2GXgyH94gP2n1yVsblpeKeyYLk8KUx2Jbb/8e6jIdN7q/0nO8vWoVfYcRcUFLTfeJL998nlx0HL004BNPaiX/fZL/2Ve17tiKETboeOG95bnUu27CUY3/dsyKyjdZ7qL3ZsFoDUep4qT0YRgLjiKRjARsFtcfkx4ezqcq9eCpMHQOqyti3e2+7R87ghM25Yub1DZViDzoMEILVHeFgjtr//azBvnpOcYnj4o9De7hzzYuMXRDJf8QBIMvk0tLc7xQ3ZIHHWK+MOQn8nZDIPlttP1chweyumjopNTBwAra1/tduXSttBMvl63Viya1cq7QDJ5Gv2YyMjH69WjWfnODR0NnR0OPqF9U6JHM0SqTgvAkBGRj4EbW3OkbmhoXNgfNyp4cS72GNLCEBkpWJ2tEcAEtw6eL2nghvJX09RodN+V5cT0EQhTiksWyHyMSDTfU2viLIrqPd91wC0ZKppUBP/fhpanvoNJPuerUp+qWtXSA44hclc8SCrLgdrAa0pwPeAuGuCMCl5D73CHiP14sOQ3NpbHYuNGaF/rGbZYgDO+N5nTB0RYqthcwAID5iMrboMsvdVjlBN0Wa1dEJisj6jIQVE4+/4fNX7wqYVdh3nSrYCLahnv9wFqr/PNg8Ia+TTwPPM351ic2xMjj+1yH/aSwkhAPHm/MwBkKl0te4UshdBZ6fjoezv/zrMm+fEkvX3Xwnz5tUX2mNrggwOfsP2btCrpeX2as0RdtY8AMLGnrDtWQBCj0gViwfZP6fTd1bjVnhem+FhGk83zz4ORrOAZbOO0U7roqRSjo5kwRFvdcbG/qNadZ715oyMfAza2pyMc/3934J58z5v3/OCzUU8I+wROtp+cvI4u08WPLIAZHT0PTAy4uxx3oUAxHvfzfYWCECCWyGv91RwI/nrKSp00llGhVb0gDAy6bcQYaVoXqL/BUj/8zeQ+teTdRLvAh1MRizbAzJvF7sSNkyOQPuNTh55Nu0tF4AwQeiJ15+G7INOhWT2ojUoJvY5A0q7vhO0sb6pQocrPwHZx52gz3H9A5AxnKxWY3udCtlyKtbRgy6G3EPlKtlHfAva7nJe7KOrroDcfZc67Zm5lLbpdgGhRtt+fI+Twdpxnyodo/ufB7lHyl9oazwFMtXfvWITarNthH0ECwGIP6Wv+umZAiCsd0SkIjkvWLiv77cwf/6HbbZt3fpbAKBZ0wqQTP6jetyLNfKp14CQnagv1DaqK8UQ3UHlrAdkqjL7yMgJUCzuT81xu4hhJXCeBSBub8XUsTE2bsXtkfm6DUKSyZcglXoMWludpA28iw3GHxk5HtranDTXbGFH1kviTrfrnXFLBICMj+8NmUwlqxgNnv8RTE46Ka0bXVEEILxYGAxCV62h+ONHyQjFLFjBylGU1h49IOW1bwqAbNkInT+lL2GA0Xd/G9Lm7ZB67s/VgnO0Pkdh54MgU852xQUgh30NCkuPBtKxiFvvYuTIH0Dbmk87Bn9tGt4GWbAKO+wD6df+4ZJsKzPPDlhPP3uX0w8DQFz3Kz4K2Z7yMZDlx0G2fExrbK+PQ/aJ/y0/OxXrMbn7UdCy0TkHzV6FHfezs13Ri/XI2Gl4u3aC3J1OsO7E8uOgtcFRMNEAc5Ht65WWdjrwUumfG4TOISC97qeQu/ciZ/41MTOVtMgitDfTxksJ8Y5a4RGsKW4HCUAGBr4Hk5NHVzt3x4pM/cYCEF72Jz4A+WM1/oRNG8saipSOri6nACjbJp2+pxpPwRrtbOB2bc0OOh9N64NM5lpoby/rhbEjIZtdY/fPBsuzYGR8/N2uWim0Fkk2+x4YHByzizfSy51N7DjI5ZyjomwtEnZfsGBkfPxgyGSc460TE2+H1ta/1W0hEQ9I7fGqjg7Hu8EenSoWOyGVmvLyTk7uAwMD9cdaKwQgAGlGm82uZ9ADEtx6eL2nghvJX09RoZPOMiq0ogeEkUlpADK6FdK9d1SreVOwkfz303aP9KhV4a3HQ2m7t0Bi66aGWbDG9j8PsuWv/sMn3QUlj7P2ruNeR10NbX862x6Ll4aXBRSljh3tGiOaHQA7dRUWLIP0lmfsP4wv+xBknnGORYyxAIS9ZwHLnqdCdv1UwbpKr1b7DpAYds5uu2I7lh4LmQ1OrQM692L3e6Dj+iOcfwsEt4sciZtOxQSxKWUBCC8IfTYcweLFdCAAmZIivwCENd5phe2+vpuhVKKB6PRY1C3Q1fVZ+579jQdAeICCnzr1eigUDrT7Fyl+x47Lpq5lje16AOIcSWptvRY6Ox0vKY2DqBjqfX0/gfnznVTmAwNXQFeX4zEdHj4N2tvLiSpIGkZGLoD29m4YHCzYgeoOzZuqVd3dR61Og7a2yrPTpyOmKYRLpe2rAIQFLyIAZGzsAMhmndgWdl4sT0qlNkgmnSKq9CoUVkB/vxN71+jiAZBagDqdLmv2N680vCw4ZeUKPSBujiMAaVYC658L4r0cHDX8nqJCJ51BVGhFAMLI23RZsOpSuva/AInXn4LE+ED1GFGlq8kVH4aC/r6pWBAmCxbrARk54ipou8spxDd88l1QWjR9sC/vuBCthG6nAE21uDNosWCBehzm7wqpFx6E1MY1kJgcnnbPltoXQ3LYSaU5ucPe0PKac8Rg8k2HQcvzf7bvSSoLWtGp5MymmB3b7/9v70vAJCmq/F9kVfV09TnMgDAjCA5dmd0zusi9LgiDCAKegK7IKeLKKsqi/PkDHpzqLqiriwsqrIvCsAorx8CgnCIwg7LMX3fQgY6omYHlmgWZs6+ZrqqM/xd5dEdVd3ZmVmVWdFa++r75prsrMuLFL168jF+8ePG+BPmn7eNUVcfGJHlGPnoz8LYe6LrjZPt5Of7ksEuhY5WzmJHiPpJIQLyC0GczAfEiJhiEPjUfhd8tWGNjH62KvRgaugp27LCPV3Z0XAOdnfZ12+LjftcIAdm27fsSqZkDW7bcYxGeIARkzpxboKfnCns+8iwQYuf1aYyATHpkvImSuM74AJg/X4PNm8X1wCXht4C2tjuhq8tJ+sknj4HJnhSZmIyP90Nb2+CMdk1OJCkTCnmBPTJyBnR22rcNytcLexGQUmkB5HIbJ9odG/skDA9/01MOeSy2b79CwryaoM7YkTq/nI6AVOtMGxBiJ5pFAuINMhKQOhVwmseStFhOwlExAXGSMMUjWM6ksHY7n1kBnbc7i2IpAHqCgHBuJ57b9rKVPI5sfQk6HrVvrxFxFuMHfBrKbz+qaprJ1/DKBKQq18aHb4TSgH0rkrzQkzOwV3lAPnQjuLERlmxtnaC9OQhkfBhIpQRQ2Qna63+CvHsl719/Gcy32gRH+wuD/BNXWT/LRKMRkzJ2wLmQ/4O9mKoNrndvxBo79IuQf9rOqzJy8m1gx6tMfVHXJlB0vSSzgYBk1/wHdD5wvt2H466D8n6nzgjbbI4BCUs0kICEJyBTPSD3TuSIaGu7b+IolO0Bsb8LS0Bkz0g+fwN0ddmZx8XHJTVBCEhn59eho+O2KfrsRUBE33bssI+EentA/AmIkJ/zBVD7cveSZ2jo/0J3t505vfr64smkj8LTIXKK5HIUcrnfAyF2Alf5mJYcUC97dryyunsRkB07DoH2dvuIl8irsmXLrwLnARkdPa0Kc5mgNmKPvZ6djoCMjJxbRYTdZ5GAeI8AEpDotDNJi2UkINGNu6gJPSASnsKobL/3Kmh/Yuqi2Frkd+4GmVd+D2TnNjvjdWkU2h+/GjKCjIg9u/0/DeVF750yQjIBGT5p2WSA+dH/NBkfYOWFeMTK05F54fFJz4CUgb3q79ORI7llkQTvv2+FzofsKyEFKZggILJHRj5e9Y7TII0+IwcAACAASURBVP9newFS7n07ZLe9YL9UnRRr4mcz1wlayT5uUN7tHZD9y58n6s//3s5aXEVAjvwa5B//hvV3mVgIAiI8KF2326RL9oDMZgLidTzJa1rK5eWkj+gBidaQxVVbo0ewqo/5NBYD4nUEqzqOYxXMnWtfsc258ICII196ZB6Q2qziNmkyYiEg1R6ZHBAiPCNiZ/5O2GUXe5No27ZLobfX9paOjv4tdHSIwHtBTL4Elcpi6+dM5vcTSQxlPSmX94Rs9hXbZo0dA/n8w049J0NHh31UNIgHZGzsKMjn7eSPo6PHwMjIpFdrOr2c2QMySVDj0OnpPSCTMUGCCLseEK+rjIXXZufOMy3xMAg9jlGKpk5c2EeDo1tLUvAU8iZFViQgko5ai43V90PnL5xFsbzI//RK+/pckQVcoFYag/aV10Bm87qJGkRSP3P3d1RrvVkGMvw6dDxsX5kpez12vOtsaHdumrJegsdeCyLTettT36vyDHj93W3IK3ha3n0fO/LrYM7rs+TXtr40GZMiEZAdUozG+IKDoG3j6ikz2DNoXb7RS4ptkfOD1BKQylveCT0/tJMvylnYgxAQ2TMU1MxEMSmDegFcmbwIyGzIA4IeEH/NiZKAzJQHxOsWLNmDEoSAVMcXRB8DIuclEei5O/Ztbf8Jvb1TrwUOGiw/nQek+jaw6Re91UeYJknK9u1XA+e7WAkPc7nfQEeHfTuWV+Z3+e/bt09efSzfcOXlAZEJiAhaHx21vTNeH69ElapiQOS4DxlPmYB4xTIhAfG3IapKRPG+a4bsKGf0KCcJUzyC5Yz/TDEgo8f9M/DOt9gld2yD9t9937pqVhy7cgO7xS7+2HuvAt67F4BZsbwklV0HgIy+ORFsXXXs6n3XQMcj9ktbzoydefGJSc+A5QERnpF+qPq7nwdE7PwVH4Suu06zF/jvuwZKB5wNZGgjZDc8Ah0P2p6RHfseD+3rf23LABoQMJ2/nwDt6+1brapur/K6NUsiIKPv/RZ0/MY+liYfm5qJgFR9d9x1E8ecqp7/4I+hc4Ud0Molz1DQ6atiUsoEpCrrvOTxCip/2HJ+/UUC4o9oLQGRF2UyIZBr8lpgBiUgXjv/XgRk69bpiUaQoPVq78mj4GYPl48kyYvSqR6Q+ywPS9wERODuZiGXF721R5jccdi06QngvBM07U3I56+FfP7RKYMt7/bLX1bn9ZjMch43AanVD3/tDF/CtQnbtj0Avb2up2x6r4es616xTEhAwo9Bs57ws//NksOvHZTTD6Hw3ycJUyQgzvjWEpCxpVdA/rd2UKZ705S2eT3M+f33QRvbYpGPylsPheyrv5/QECvZ39uPAnOXfcHcVbcC0b2Cx6sW16fcBeW9j7DqCRIDEsQDUHUFbKYNhs961DriJS+KS7vvB7nX10zIP65/EEoDJ4L20lOQ/6MIbgfYudd7YM7LdlZkz9uxjvgq5J2jazLJipKA1GZIdz1DQaenikkpY12bdT6s/EH76Zbz6y8SEH9E4yQgXos3r9iHmY9aTQ02D0tAZOJUu+PtHsuRiYkcAyITEDlhn1fsiewZ8YoBkeWRF+czHWFy5ZT7Xh1rMxlcPzb2Xsjn7Qs15M+OHUdCe/vjtt0fPRY6Ouwry72C1uWbsvw9IByy2cdgl10+Y9U5MnI6dHYus37evv0rzg1pObF9ZF0EIP4XeVbsf5p0GNY9GEssr44gW5z3WB4f60ISj49rE0ZGxAUIk7FCbnGZdMzsAbGPilXr8EowzYXTthznUQv/WRx9CYwBiQ5Tv/dUdC01VlNS5BS9TIqscdqFxGdCrw2m1oZfhbY/3AzELAHPdcDOQ86zvAP5lXamYssDcvTVUFryCYA53RPaHoSADH3+WTC7beMddmHoNa1qr4B1F7xVBGTvIyH3P/bLVnx2vPvLVr/aVn0X8qtvcPqVBWLaN+KMSXEi8s8y6QhCQEaPuQbKfcdPHMEK5AGRAu9tD4jtGQr6UTEpqz0gl0LeSegoe7yCyh+2nF9/w+pZ0ONncRqVsBg0Wl4sNDZvZjBvnn2dbe3C2TQXTGkiqAfEi4B4eUBkT0eQYPMgR7Zk4WW5a3e83XJe1/B6HZeS658pEH66I1hBCEh1gPzkjVJy3+V6ZG/O6OhkUsVKZQ/IZOyrw+XP2Nh+kM/bGzTDw6dCV5edaV2O7dmxYz9ob7fLTE9AOBDyBmQyG4GQv0Ams34iiF6OW5Gz0ofTW0FGytatZYK0CELiEhabxOSsa55tcjIH5s1bCNu2/R56e20S5BX3UR0D8k/Q22vnMxI5YkqlY4GQnaBpr0Bvr+1N37TpcTDNvaYVvZVsgo0Z52++OTSRsybceDWntJ/9b44U/q2gnP4YhS2RJEzRA+KM7hQPiHSsqLTnuyH3in0fvNmzJ+x49wXAu/aouvZ29IivQengzwFk51TpiyoCUnUFrOUB+Y21YJcXxTsOPg/an7GTawkCNfypx6wy7fd9btrEgKNLr4SO315ulZd/DkJARg+7BDpWOWQt0wYjJ/98Itg+CAGRvSlBPEC1k1bFpMQYkLCmc3aVr4eABE0050VA5MV89ZWwk9fq5nL+weaNEBAvD4hXPojaK3y3bBFHs+x8J+4nbgLidTzOi8i0tf0cenu/aok3NvYxyOftHEjyR741a3x8CbS1rbW+Hhr6NHR3u7lINCDEPrpaTUB2WGRD016CbPYFyGReg0xmHWSzg6Bpk4kL3fbK5T6oVPaFSuUtwHnXhFfDNHe1SEQUH0I49PTkYPv2l6Cnx7bjw8PnQleXHTi/bdtXoLf3W87PX4PeXucCkZHToLPTvqBE3DxWqbzL+pmQzdDTYx8jRgISxQhFV4eK91090qOc9aA28zNJwhQJiDOWMxGQiZfEwgNh50F/D5DL2wZ4dNNEHpDtf/9HO/5jho8nGYnBAzIlBuTAcyzJqnbl5YzqIk7EKZNb+d2JXBxcm/SAyKRj7ODzIO+QlyAEpDbb+dh7vjoRbB+WgATJWl47DComZdXVySffBp132jE5eAtW9EY3jhpVE5AgZ+/DxoCEjV2RvQZeBKSr64uQz98/MQQjI+fB6Ki9M+5+Zh8BmQycHxk5Ezo77ZwjY2PHQj5vH7vy+giSkMm8MeXr0dEjoVT6OLS1PQbZrCAfr1v/XIJSj44KEsT5fDDN+cB5B3Ced/7vAtPstogKQLt165n42TTnWZ6O6T7CBvb05GFo6FXo7raJg5xXRb7WWP55ZOQs6Oz8mVUeCQh6QOrRY69nVLyX65E/KXKKviVF1jg9o4k/glVaeAjkXrPvdxef8f6PQGnxyRMJBq2BHtk0kQk9yKJYFQERBKFSeL/VDy8CIpfJrfzOpLeCZIFw5wjWQZ+XjmblrONo1kvppNsmAt69fpYJCxcekI/9YiLYPggBETdHVeU+6Zn+vPFsMnSzmYB44rT9tYmjcbJOe8Um1dYTp1Gp58XRyDO1Ry2CBN1G6QGp9kRMf61uEE9HELm9jo55XccqB4ZPJSBfgNHRL1dBP9sIiFe+FTkuo1yeD9nsphlVSL6qd6aCIiN7pbIPmOZcaG9/0Co6NnYi5PN32++X8YOBkBHQtM3W/4SMTuQvCavDgpgIIsL5XKs9ER/iHsPK57thdJRDR8dNDgG5BLq7bc+0FwEZHf0QdHTY2d3Hxo5zPCDiCNYm6OiwidumTY+AaS6aVtRWsgmig3gEK6xGepdP0mIZ84BEN+7W+pkAoAfEwbTWAyJDPT7wMSgt/uhU9Me2QuevvmD9vZUIiNcRrPHCB6CtOLnT6QIShIBUHd8KGAMyIt98FeDmr5mmhwpD10oExCs/DRKQagTiIiCNeDriJiBTj2CtmJKMbzYTEJlMzZnzr9DTY+c0ksmF/HO5vAdks1NjRuxnMlCpiONUC0DECFUqC6FSeRsAdFh1atoG6O52c5ecBR0dtmdhagyIiB0ZcrwobzjEZAwIEf8EQRl2/omfd1r/6vnIx8zk3Cjl8tuto2O1OHi1MTp6NoyMfB0JSD2DEMMzKt539XQD5awHtZmfSRKmSEA8CIg5pxc0kXRQ7PosvRLM+ftWjzoHqMzXoeemQ1qOgFQfwZr0dFR5MaSjWWEJiEhEKOcB8fKA1N585Q5AELI33cK42TsYrURAvPLTIAHxfhl4xR/YC9GNMH++HdxefWvTvdDbe4Gz8Ju8IrURT0cQAuJFnIJ4QFQFoXvlGfEKQpdv0/IaG69byORR3rnzIJgzZ2qeJFFmdPQjUCoJb7MdF2KnchU3VYljUu1AyEswd+6l1jcjI6dCZ6cd2D40dBGYpnjHiJuv6vmYDjHZbF0/LLwTmrYNCNlqERmRyFHcEpbJ7ADON9XtXXEl41wEt2dB08YcXc2Bm5iylW2CNaIYhF6Pgk77TJIWy81eP9QLcpIwRQLiviY455s2UOi+wU6ON3bolyD/9Pfsn2sJCCdQ3vtwIDu2TXtcxUtxqhak0pGiOG7B8sraHeQIVnbNf0zk4pBJx5h8BEs6mhUlAalKSijffIUekFD2qF4j5HXblVd+mlZebDS60KiHgHR0iCtSp2bTVkVAvJIkyl4DmYDIf5d1Iw4PSBwEpNqbQ0AEbtuLTvvIgPgIktHRsXzK30WZ7dt/BOPjxwJAxSEhgohMXo/b1iYTTDnD+y+hUtnVii0hZLvl6bCfE7daRfOZjAF5Gbq7bRIk51IplRZDLvec0y+57/LPGRge/qp141Vb2/2Qz98zIZybmLKVbQISkGh00a2l3vdUtFL415YUOUVPkiLrrD6CZRjGxwHgcs55jhCyjFJ69XRqouv6lYSQCqX0KvH90qVLs6+99tqPCCHv5lykLodzGGOTwRweujZTEHoVAXHIB7R1el6Z66XOVcdYpAX1bCYg8tGpuI5gVd2QpU16XKryiGAMiL+VlErUa4SCXM870y1kcRoVFTahkes2Z/I8eHtA7oPe3n9wFoHqPSBeOTi8khgmnYDIZKpUejvkcvYxJPlTmxFe/s5rEe6W8SKYUzOhj1leMvvGrO2gaaMOqREeEvEvPDHxC0KXc6DIfRod/TB0dNzrEJZTJpJCZjLPQVeXvUknguC3bFk+5eiduyCKa6czlFGMqHCjGxMRiTFjNfXa/2bIJreBckaPeJIwjcsuNBSEvmjRot2z2ezTuVzugLVr124zDOMB0zSvLRaLD7vDtWjRot5sNisO636CEHKtS0D6+/v/wTTNdzLGPqPr+gAA3MMYE/+7PvFpRzwQAeEA5b3fA4J8WIbVI2DXS6Vqj7G45eImICKAu7z4JKs5r2t45SB0Tw+IdPOVfG2vV3C97Bmp8p7UXMNbe0PWBC5nPDSRRV4mI3gEy99o1WuEghCQmfCPi4CosgnNJiBeeStmgwfEizTN5OlxNTUpHhCZgIyP90Nb2+CUyVadEX7SMyLiP7ZsuX/aRbhbiVdiRBEkbi/gq68vnmxcvL5ErIeI/RBxH+MidN3JASL+Ljwm4n/heRGvX3F1b/Vr2I+AjI6eAh0dv3AIxWTSxiC3YG3d+lMolexkurWfuGyCvxWMpwQSkOhwrfc9FZ0EwWpKipzWupQAJOG4WJx2oSECYhjG6Zzzoxhj1t2xhmGcwTk/UpAKV110Xf8UAOwGAF2yB0TX9UcA4ErGmJW+W/xOCLmCUrpyJlXzIyCV+QWo7H04QM4OJrQGOiQBqTrGErMHJLv2Tuhcca79MsnMgeGzROK+Aaj6e423wVx4gFW+6hYsKz+IyCEyADIxEUelSofbV2164VCVCbwmgF2+hlc+diWIjXu7lkw6kIAEM5QTuhmxEQqq63EZFVU2QSUB8cpt4UUEwv5d1qggwfOqCIjsHQiaXd1NEulFjrz+LhOQ0dFjoKPD3vMS5MJe3ItjVpdCT48dSL5jxwC0tz9v/SzKj4xMPT4n4yy3u2PHe6G9fTIbu5/3JJgFGHdiPkT8h7i9UPwTcotbq3bA3LkchoZegu5uO2Dc6xpemYwEISCYByTY6DSrVJIWoUlZLCdBTms9FvG7Py6djWutYGHQiNCGYVzMOe9kjF0m6jEM42jO+UWMseNq6zUMQ2RU4q4HRNd18Tb4AGNsgyir6/qtAHA/Y8ze2vH4TCEgUo6MkROuh/LAiQBZcSZ38hN0UeY+0cwYkDmPXQnt//WDCWHdTOi1f3cLyLkpam/Bcp+Vc4vIHhOvK1qrEvEddulkbpHMHBj52M+nvYZ3bP/PQP6P/2a/HNEDUvc0itoIBdX1uIyKKpuABORuKJf3s/QwKgJSm4tkOl2tjpWY3jswk1clCgIiEgt2dtoJCkdHj4eOjl9bP8sekLGxAyCf/4P19+kzoVdPYZmA1CZ8tIO49brnvN+DLs6bNz8P8+bZ3orNm++w8ogIr0om8yfo6bETEQ4Pfw66un7o9GsyWF5kby+VloK4PUtcGdzTYydzRALih35zv4/a/sclPcoZPbJJwnRWHsHSdV1EyOVrCMiFjLETaodrGgJCAeB4mYAQQu6jlApL6/mxko69QKHreicIXSIgQ5/7A/BecZVi9UcsytygdXGMivvkppDLD5/5EHTdIoIVAYbPexbMbjuvhVedYdvKPncXdNz7WatO4QEZ+dSjVpbzqr/LgeRnPgSTHpDvQn6lvcMnPBIjZ9sZ0gUBcZPpWTdZOblFRGxL5+0n2+Wz7TBy1sOWx0QQELePo8dfBx2/Pt8qM/rhG6Gy519PBvwffgnkV0pZ0i1ZB6qwkPEKgvWUsSIA8+d3w6ZNQ1ZAaTM+8piNfuw26PilnYhQ9MXFOi45hBGKsr9B9c82fj0NbUBMh4kqm9CIvogF8rx59k1Xmzevsq5ldT9e32Uya2CXXU60im3bdhP09v7dlOe9np2pPT89k5/duvVumDvXlkGWO4jMImakUrEJi/yZSbbpdDWfrw7GHx6+CnbsON2zTjkgXZZZxlOWTf676K9LsrLZR2HuXBvzsbF3Qz7/O9uuSR4QcfuT7V0QZaoJyNjYtTNCLbe7ffs1E5nEhZenVPqQ3zA19L2L85YtDHbZZapeyn3fvv2r0NPzTau9oaHzobv7OgeHNti61T4qFlTf4rIJDYHRwMN4BKsB8GoeTdJiGT0g0Y27qCmuzUqr7kZErT1yJY5fAMARlFJ7RS19piEg4sjV5ZTSVaKYOIKladplg4ODT80kkzAqfOsrUPqGfd0u+cA/Ar/fvikk97X1QObuOeVxubxXGfkhuXz2/JVQvu7wKfV71Rm2LfOlZybqz5x2C2T2/4TVVuWPt0PltjNtsbQsgGm/SIU82tsOtn4u/9fPwLzDhpq8/wrIHWPjUFl7P1RutmNJMmffBZklH7DLP3oNmL+2nFX2dyddB5m/ORdkGbS/vXGiTtEW6VkwifUBpwL/g30dpfx8ELymDMos+oMsv8DLxU7GehaJO6MoYfSPEGFaov2osgmN9eI1AHAX42sAQE6e6fXdHwHA3pgAuA0AbNIKID/v9exM7YXpSdj6ZZlFFvH9p2lMrvNOYc59BHoCAOxNDbFDDyCOQvXXPCPXKdp1cZOx8pJN/vuNAGATLoCfAMAlzs9Cjf12Kw4FgKed8p8EAHuh7v2R2xVl7U0ZAC/cwoxb0LJe4ytkcPVNlk3cB/OfUuWCZJ0NAMH1LQ6bELS3UZdDAhIdokhAosPSrSlJmM5KD8jAwMCCSqWyinN+aG9v79ahoaEVAHADpdS++1D61BIQwzC+zDlfLOJFDMPo55z/uqenR1+9erWdttvjU+sBGT79V9C1zHa4eO24B90VnlAMyWMStwdE9j7IO+5t4mjW05NHs1zZ5DIi1mPCW3H8dVDe71SrmKcH5MUnoPMXNjGxPSAi3qS/yoMhPCYT3pOzHgKzcw/JA3LppMdFBKhbMSfVzyfdAzJy1kPQ+TN7gVSPByesmWo1D4gqm5AWD4jQL78d8kY8ILncKujtPcO2EXwObN16z0TA9XS6Kre1bdutUCrZO/byRy7j5QHxkjmXq8634u7qd3R8HTo6BPGr/sTtAfHyHIWd9zOV9xtf2QOybds10Nt7sW2vhr4E3d3ubVfCA2IfFUMPSJSjE21dSVqEJsGzkBQ8XTueFExnJQERIBYKhZOFJ8O5DF3cZHWJrus3cc6XF4tFQUisTy0BWbJkSVupVLrevYZX07TzBwcHf+s3vWtjQOQbnOT4CLmeoOfi3We8bouK+xYsWX5xBKvzPudolkcQuhxsLpIEygSk6y7nGNFJk0ewvGJAqv5+0m0w8aw4gtS5x0QOFRlr+cYuL7ySeAuWTKDqkd9Pf2u/j9pgBtX1ON2qKmxCK8SABNWdyRgBNnF0LMjtW0Fuwcrnb4Curu9MiCIHXE+nq2GTJ9bGlbgNedVTex2uK091HpDJwPORkVOgs9MOI6yOAZk8pjU8fBaMjYlXlvdHxkpe5MvXHQcdr7Dl/MZXDsCXZZN/3r79Cti50/agBxkjd0EU10IjLAZRlEcPSBQo2nVE/Z6KTrLqmpIiZ9IwjcsuRH4EIy7FcutNCwGpSkR4+KTnoYqkSIkIvQjI6PuugdKB1iVlnrdg1UNAZDmQgNSv9VEbzNlAQOpHo74nG11o1JMHRF6gRnULVtDe+y1QGwlCFx6QuXMnPSByzoh6CUjQfk1Xzkser1uwhobOg+7u662q5AX52NhRkM8/5hCT1icgcp4XJCCNaGC8z0Zt/+OSFuWMHtkkYYoExBn/oASkkUXxbPCAyAREPhYl78p7eUByq/8NOh61z0fzTBsMnzUZLN7zQzt4X64HCchrk14e6dIB9IBEb3TjqLFRAjKTTEEW861EQKqv+a0+UqWCgMjyiCNe4+P2ES+ZAAqPRlfXz6y/ywREHpfR0ROgo+NXSEA2VV+yIOt+nF7ROOa9X51x2gW/toN+n6RFaFKOCyVBTmtDGK/hbSwIPegki7KcFQPy7OMTtzaJnf/OB+wAwah25ZNOQOY8eBG0//fNE7C71/MGSV4nH7MSx5EqC+ycI+Ijk6KosK7VDRWTsoqAIQGJcro2pa44FxqzmYB4HTsLIrPXUaKZdstVExBxa1alYt9QFpaAyCRF5AfZudO+Qcvrk5QjWHLch+zxQQ+IiGHivJGjmc0wXired/X0C+WsB7WZn0kSpugBccay2QRE7IJD78IpGSuDLOaD7KB7LeqDeEC88n3k/t9PoOMROzDR9oBMBouH9YAgAZFvRJr9RgiPYEU/RtPV2MgRrEYl9HtxIQGxj2DJHpDao1nj4+LGqGQSkOr4lxwQYt/bggSkejyRgDRqaSaf97M50bXUWE1JkVP0MimyxukZbdkYkKiOYIUlIGGnTyMExOtZmZg0GgOCBAQJSFidbnZ5FQuNJBKQILEAreoBCRtIPps9IJ2d098AhgQECUhctjdJi2U8ghWtFiABkfCcKQYkqpuZaneRw3hAwg593ATEKxO6VwyIICyu9wSPYPknrQw73rXlozbs6AFpdESCPR8ku3eQBX+w1qpLRa0zcu2tSkC84nS88A9CMOsZuyDP+F0ygB6QICjiEaxgKAUrFafNCSZBsFJJkRM9IPZ4Jt4DMnr0P0kB13Ng2MptYWfnnu64URA1DkJAgtQTpEwcBCRIrIZMQESG9K47nAzpmTYglXFL9DQSEPmq5SDj12iZqA1mUL2Pc1ejUUzCPq/CA4IExB6luEiWqwNy/Y3EgLQSAZFvAMMYEG9rocIuhLVdUdv/sO0HLY9yBkUqeLkkYYoxIM641npAdrzr7FAB10HUIykExGuxGZaAtD31Pcg/+c0p0AQlIPKDQRfAXuOgYlJWHdf7/LNgdsd77KoKr4hvwgiKPxKQIJbAuwwSELUERMZfju+Qf5aTHso/e+UikUd7NnhAvAKog+QBwSB09IA0ZuGqn1bxXq5H/qTIKfqWFFnjXCsk3wMiHRniGeEBEVfO2tm5W90DEhUBybz4BHTd7mRIr8MDUo+hQAJiIxC1EQqq93EalSj1IUhdKnY6gxCQILLXUyZqnZFlSMoRLFlOcatVT88/Wt2Qfw5LOpJOQGQvj3zLWVAvVSvZBDGWKuxC2Pkc51wOK8tM5VHOKNGM590fvYSTcqIHxEG3nhiQILdRVe1K15CX6WJAohrsICSi1hPhth32Jq4g5euJAYkKizgW5EFkQw9IEJRmbxkVCw2vo0HNQCnOxUASCYi88K5dhO+yy4nWkATxeiABAYhrodGMeVHbhgq7ELafcc7lsLIgAYkSMf+6kjT2cdmFxHtA5LwVXrkpkIDYR4qCEBCBYfetx1rla+Mhgu6u+0897xKqJmWrtBt0jFppt1PFQgMJiD2Hg+6u12sTvHCuTph4E8yda+f1SDMB8fL4BB2jVrIJQhdU2IWweq7qvYNyhkUg+vJJGnskIM7415MJPYkEJMiufBBC4XXbldffkYAMAefRGxuvGqM2QkhAmjN2SECSRUC2bq3O6u6nJUmMAUECUj2qSED8tDz491G/p4K3HK5kUuS0NoQjjv8Mh1Tw0nFuTKAHZJpxaGYQehAS4XUzU5BnkYAEm2iqjIHKduPa1QiGeHSlVCw0kIDMfgKybdv3obf3AktQzufAli33QKViBFI8mYBs334F9PRcYT0X9ihXoMZqCvnZBDkIPUiwOXpA6hmF5jzjN9bNkcK/FZTTH6OwJZKEaVxrBSQgSECqjmahByTZHpCgRjDOXY2gMkRVDglIVEjOfKRKxQuzkSNYIyPnQmfnjyfAGRq6CnbsOD0QWG1t90rkpQ0Isa8mRwISCL5QhQzDEGnpL+ec5wghyyilV8sV9PX1HaBp2g8IIR2c81FCyOcopc/6NaLCLvjJVPu9ijkVVkZRHuWsB7WZn0kSpkhAnLFMSxA6HsFKDxFQkbkVCUjjLxRVL5A42w0bhN44ijPXEISAeF23u23bv0Bv7z9YDdgekOVQqeiBRO7oM7H+JAAAIABJREFUuKaKvLgPzQYCIntn6rntygsAFTZh0aJFu2ez2adzudwBa9eu3WYYxgOmaV5bLBYfduU0DOPPAHAupXSVruvvI4R8h1L6Lr+BRALih1Dw7+O0OcGl8C+ZFDmTRuqQgHgQkKQnIgxyjAqPYPkbnkZLqDJcKtuNy6g0OhZhn1e10FA5dnGR1qQQEFlHvK5ElolJ2BiQtrb7JPIyuzwgrURADMM4nXN+FGPsHDGmhmGcwTk/kjH2GWeMia7rZzHGfip+HxgYmF+pVBhjbL6fnVBlF/zkkr9XZUPCyJi0xXJctjEsZn7lkzT2ca0VEn8EK+mJCD13o6SrgJGA+E3lxr9XZQxUthuXUWl8NMLVoGqhoXLs4nrJtioBCeu5kBf5wpMyPv6hcErZQGk/vWoxAnIx57yTMXaZQ0CO5pxfxBg7bjoIDcP4Eec8KxEUT6RV2YUwQ+831mHqirMsyhk9uknCNK61QuIJiJy3IqpEhLWqpkpR6m03iFcFb8GqHuV6sW7ULKlsNy6j0igmYZ9XtdBQOXZIQCa1JIgHpBECIh9zCqub9ZT30ysvAlJPW7W78c22CbquXwoA+RoCciFj7ISa/miGYfwL5/xQTdOOHhwcHPLrr3Vce1Nzj/L6yTTd2mL+/G5AOcMiN315MXeSgKeQPimy2vaoJxauEEul0ajS9LU0IwYkzQREEBOvxItBr3htZPz9Xr6N1D3Ts2lst9mLjbjGDglIdMjONg+I+6Kuh3AFvf1pOvTiWuQHGSk/WxSXd0ZFDEjtkStxJAsAjqCUftbFasmSJW2lUul2EYTe3t5+0po1a0aC4CjsQpByWAYRQARmRoAQYR2i/8RSafRiTtbYjDwgrUpAvMalmdcO++mG38vX7/l6v09ju0hA6tUW+7lW1BkkIPbYzmYCUntDlx1cH+x6Yb9NmGbbhIGBgQWVSmWV8Gz09vZuHRoaWgEAN1BKl7uyGobxM875HMbYaQBQCTpr0QMSFCn/cknarUcPiP94himBHhAJrXoIyPAn7oLKPkeEwbyqbNIWGmE9FUhAWnMxOdsWG3VPQJ8H0QMSHbJIQGY/Aam9oSvM9cKz0SYUCoWTCSGXA0AbANzDGLtE1/WbOOfLOeeDmUyGAoD4t9ORn1NKDxSXm83UH1V2IcxsVLW2CCOjys2WVpUzaZjGtTHRsh6QzAuPQ9cdJ1v6y7PtMHzmw2DuNhBWn1t2p1MGAgkIEpC6JsYseUjVQkPV4gHbDaZ4rXoEq/aGri1b7g18vfBsJCDBRjN8KVV2IYykquZyGBmTtliu57hmWDyiKJ+ksUcC4m59iMCyDRS6b/gr6y9yELpIomcuPMD6e9tT34P8k9+c0JOxY6+F8f0/XZfeqFKUZrWLBAQJSF0TY5Y8pGqh0az5WQszthtM8VqVgLRSDEiwkayvlCq7EEZaVXM5jIxIQMKiFax8ksYeCYhEQLY8swI6b3e8G1oOiFmyvh0+6TaoFN5v/Zx58Qnouv0k62fbA/IImLv1B9OMmlKqFKVZ7SIBQQJS18SYJQ+pWmg0a34iARG3sHTDm2+Gu9EoDQQkyhu6VAShx2lCVNmFMH1SZUPCyIgEJCxawconaeyRgEgEZPu9V0H7E5PeDXe4ZQIiL6rTFgMSTP0nSyEBQQISVmdmU3lVCw1VLxBsN5j2NUJAvDKwB2u5sVJ+4xtXgDwSkMbGrZ6n/ca6njrjeAbljB7VJGGKBET2gKy+Hzp/4Xg3PDwgYQOxZ1IvVYqStnZV7rSkDetWWmwgAYn+5ThdjUmbI0hAwulFK9kE6+QD5zys1ywcYo2XVjWnwkqOcoZFzL98kjBFAiIRkKoYkMMuhY5V/2h96+UBkZPu+avF1BKqFCVt7SIBqUc763umlRYbqhYaaZufSetvqxKQRvrlt9EW10KjPivV2FOq7EIYqVXNqTAyqnwvt6qcScM0LrvQ8C1YhmF8HAAu55znCCHLKKVXy0rT39+/0DTNZYSQ3TnnGwkhp1BK39xrr73y+Xz+DUJI0S0f9Go9mYCMHHcddD5wPhKQsDN1hvIqjaKqttPYblxGRYVNULHTmUadqScWo1HTVC/OjSzUZ/MRrEb6hQSkUW2M9vl6dTtaKfxrQzn9MQpbIkmYxrVWaIiALFq0aPdsNvt0Lpc7YO3atdsMw3jANM1ri8Xiw+5g6Lp+NyHkTkrpskKhcLamacdQSk81DONwzvmFjLETwwxcbR4QJCBh0AtWVuXEUNV2GtuNw6iosglIQILN7UZKJW2ONLJQRwLSiKbMjmfRAxLdOKia+2F7kBQ50QNij2xDBMQwjNM550cxxs4RlRmGcQbn/EjG2GfE70uXLs1u3LjxTUrpfCeDacYwjE3id8Mwzuecn0oIqXDOy4SQiymlq/wUrp5EhHgEyw/V6u9VTmJVbaex3TgIiCqbgAQk3Byvp3TS5ggSkHCj3ErHMkXPkYCEG38/75gK72fYHqiyUWHlRAISDQG5mHPeyRi7zCEgR3POL2KMHSd+F7uhuVzuGUrp29wBMgzjpWw2e0ilUvmEaZptjLFvFwqF/QkhK+bMmfOOP/3pT1tmGkwkIPWoerhnVE5iVW2nsd2YCIgSm4AEJNwcr6d00uYIEpBwo4wEJBxeUZRWNafCyo5yhkXMv3ySMI1jrdCwB0TX9UsBIF9DQMSxqhNE5QMDAwtM03y6hoC8XC6XD1y/fv0b8hCJo1qc858Ui8UVfgRk8wsUuq63ExGOnHwbdN55mvXz8JmTiQjFLVhussKhzz8LvGehv0Z4lBCKMn9+N2zaFO4e+robdB5MW7vurgBi3ajm+D9vG7+ehjyg07WiyiY0e26irvrrWFQl6rWDgoDMm3eYJcbmzavANBcEFkl+dsuWVVCpBH82cCN1vm8a6ddMssVlExrFo97n0QNSL3JTn0vSYjkJnhr3/ZEEWePcmGhoAVJ75EocvwCAIyilnxUAS0ew5gGAKfIDGoYhjmTtahjGp0zTfLBYLL4iyhqGcS8A3EApfcCPgPCtr0DpG/taxTJn3wWVm+0rebPnrwTtbQdbP8tlcl9bD2TuntHNRqwJEWgBBAgRpiXajyqbEG0vsLbWQOA1ANjP6coaAAizCdXIs3GjF59scdiEuNHwqh8JSHTIIwGJDku3piRhOis9IMLDUalUVnHOD+3t7d06NDQkvBeCRCx3QdZ1fTkh5JeU0lt1XT8LAD4qAs8Nw/gRAAxRSi8qFAqLNU17oL29fWDNmjUjfgRE9oAIr0fXLcdaj8ieDvSA1D9h6t1xrL/FySdVtZ3GduPwgKiyCegBiWL2zVxH0uZII54C9IDEr09xt4AEJDqEk7RYToJXQYxMkjCdlQREgFgoFE4mhFwOAG0AcA9j7BJd12/inC8Xx6kKhcKemqbdDADCh73JNM3ThNdjyZIl80ql0s2EEOHKKHPOz2eMPeE3ZWpjQIbOeAi6b7UJiBxsjokI/ZD0/l7lxFDVdhrbjcuoqLAJGANS/3wP+mTS5gjGgAQdWbtcnEctwkkSTWkkINHgmLTFMhKQ6MY9brsQ+RGMaLs+tTYkIHEjrJaZJ22R0+hoqOxvXASkUUzCPq9qoaFy7FS8ZJPWXyQg4WYSEpBweEVRWtWcCis7yhkWMf/yScI0rrUCEhB/PVHmKlOloKraVbnToqrPKtuNy6gEmFKRFkECEimcnpWp1NVmEy7MA9IcnYqzFVV2IUyfVM2pMDKqfC+3qpxJwzSutQISkAAarspIpK1dlZMybVi30m6nqoVGGnWm2URAlU1AAhLgxTjLi6iyC2FgUWVDwsioag6GlTFJciZJ1jjXCkhAAmi5KiORtnZVTsq0YR2nUQkwpSItomqhkUadQQISqepOW5mfXjVytGwm6VvJJoh+qrILYTTEb6zD1BVnWZQzenSThCl6QJzxxxiQ6CdCbY0qJ4aqttPYblxGJX4NrW5B1UIjjTqDBCR+7fbTKyQgwcZAlV0IJp1dym+sw9QVZ1mUM3p0k4RpXGsF9IAE0CtVipK2dlUa5LRh3Uq7naoWGmnUGSQgAV4YDRbx0yskIMEAVmUXgkmHBCQMTkHL+s2doPU0o1xSZI1zrYAEJICmqVKUtLWLBCSAMkZUJE6jEpGIgatRtdBI2/xMU38xBiTw9Ju1BVXZhTCAqJpTYWRU+V5uVTmThil6QBxNxCNYYadk+PIqjaKqttPYblxGJbzGNfaEqoVGGnUGPSCN6WqQp/30Cj0gQVDEGJBgKAUr5aeTwWqJv1RS5EQC4ngA41eJaFuYiYAMf+IuqOxzhNUgJiKsH3eVk1hV22lsFwlI/XNE5QskjbrabOIzmz0gjWmt99Ot5BUVvVS1MRFmfFTN5TAyqrR1rSpn0jCNa62Q+CNYIx/8MXSuONfSU55th+EzHwZzt4GwejtjeVVGIm3tqpyUacO6lRYbqhYaadSZZhMBVTYBCUikr1AllamyC2E6q8qGhJFR1RwMK2OS5EySrHGuFRJJQN58cwg4t9Wz7anvQf7Jb07o6tix18L4/p+uR3c9n1FlJNLWrspJmTas4zQqkU6+AJWpWmikUWeQgARQyAaLqNSruHY6G4SkrsdV2YUwwqoa6zAyqnwvt6qcScM0LruQeAKSefEJ6Lr9JMkD8giYu/WH1Vv0gEgIqDSKqtpOY7txGZVIJ1+AylQtNNKoM2khICoXCCr1qlVsghg/VXYhgMmaKKJqrMPIqHIutKqcScM0LruQeAIix3rIMSBhFXem8qqMRNraVTkp04Y1ekAatxBp1BkkII3rjV8NKvUqroWGX5/j+B4JSHSoqtLJsD1Iipwq1zr1YBqXXWgpArL9c88C71kYFl/f8qqUOm3tqpyUacMaCYjvtPctkEadQQLiqxYNF1CpV3EtNBoGpY4KkIDUAZrHI6p0MmwPkiKnyrVOPZjGZReQgAQYDVVKnbZ2VU7KtGGNBCTAxPcpkkadQQLSuN741aBSr+JaaPj1OY7vkYBEh6oqnQzbg6TIqXKtUw+mcdkFJCABRkOVUqetXZWTMm1YIwEJMPGRgFQhkMY5kjbCFddCo/HZFr4GJCDhMfN6QtXcD9uDpMipcq1TD6Zx2QUkIAFGQ5VSp61dlZMybVgjAQkw8ZGAIAHZtRvkWxcb1xr/GlTaorgWGv69jr4EEpDoMFWlk2F7kBQ5Va516sE0LruABCTAaKhS6rS1q3JSpg1rJCABJj4SECQgSEAanyiKakACEh3wqt6PYXuQFDlVrnXqwRQJiINarVGJMuP5bHM/qppMqtpVOSlV9Vllu3EZlbAGrtHyqhYaKscubUeDsL+NzhL/51tpU0L0VpVd8Ed6soQqGxJGRpXv5VaVM2mYxrVWQA9IAA1XZSTS1q7KSZk2rFtpsaFqoZFGnUEiEOCF0WARlXoV10KjQUjqelyVXQgjrKqxDiOjyvdyq8qZNEzjsgtIQAJouCojkbZ2VU7KtGGNBCTAxPcpkkadQQLSuN741aBSr+JaaPj1OY7vkYBEh6oqnQzbg6TIqXKtUw+mcdkFJCABRkOVUqetXZWTMm1YIwEJMPGRgFQhkMY5kjbCFddCo/HZFr4GJCDhMfN6QtXcD9uDpMipcq1TD6Zx2QUkIAFGQ5VSp61dlZMybVgjAQkw8ZGAIAHBIPTGJ4qiGpCARAe8qvdj2B4kRU6Va516MEUC4qCGQehh1Sd8eZWTWFXbaWw3LqMSXuMae0LVQiONOpM2j0Da+tsqNkFYFFV2IYw1U2VDwsiYtMWyijkbFs+kYRqXXUAPSADNUWUk0tauykmZNqzRAxJg4qMHBD0g6AFpfKIoqgEJSHTAq3o/hu1BUuRUudapB1MkIOgBCas3dZdXOYlVtZ3GduMyKnUrXp0PqlpopFFnVOwuIs51ToyQj7XSpgR6QEIO/izdbAnbC1W2IqycSEBsxNADEkBzVCl12tpVOSnThnUrLTaQgAQwYhEUSeMcSRvhapVNCSQgEUx4qQpVcz9sL5Iip8q1Tj2YxmUXkIAEGA1VSp22dlVOyrRhjQQkwMSfpbuCadTVtBEBVf2Na6HR+GwLX4OqjYkwkqqay2FkVPleblU5k4ZpXHahYQJiGMbHAeByznmOELKMUnq1rDT9/f0LTdNcRgjZnXO+kRByCqX0zaVLl2Zfe+21HxFC3s05NwHgHMbYf/kpHAah+yHU+PcqjaKqttPYblxGRbVNaHwGBKshjTqjamGM7QbTyUZKqdqUqNde+PUVCYgfQsG/V2Xrgktol0yKnEmSNU670BABWbRo0e7ZbPbpXC53wNq1a7cZhvGAaZrXFovFh13F0XX9bkLInZTSZYVC4WxN046hlJ5qGMYFnPN3MMY+o+v6AADcwxgT/wsy4vlBAhJ2SoYvr3ISq2o7je3GQUBmg00Ir/H1PZFGnUEiUJ+uhHlKpV7FYRNm6nsj9sIPUyQgfggF/16VTgaXEAlIWKyClp+1BMQwjNM550cxxs4RnTEM4wzO+ZGCVIjfhZdj48aNb1JK5wNABQAyhmFsEr/ruv4gAFzJGHtSlNV1/RFCyBWU0pVIQNROJpXGRlXbaWw3jsXGbLAJQQ1ro+XSqDNIQBrVGv/nVepVHDZhph7XaS82U0rnOWuKwJuV/sg3v4SqsQ7bU5QzLGL+5ZOEaVx2oSEPiGEYF3POOxljlzkE5GjO+UWMsePE72J3I5fLPUMpfZs7HIZhvKRp2qGVSuU3APABxtgGh4DcCgD3M8Z+EYaA+A9z4yVUKUra2hUjlbY+q+xvHEYlLTYBdbVxuxq0BpVzJG2EKw6b4ENA6lpDZLPZQ9auXfu/s22tEFSn3XKqdBvlDItA9OWTNPZx2YWGCIiu65cCQL6GgFzIGDtBDNfAwMAC0zSfriUg5XL5oEwmIzwfx8sEhBByH6X0Dj+jsmnTEHAevUJ41SgUZf78bsB248ccsY4f48nFc09D8386SdNiE1wM0S7Er69oE+LHOE6bMJP0ddqLl8vl8oHr169/Y7atFcKOlCrdRjnDIhB9+SSN/a67Rr9WsGxOI7DWHrkS7lQAOIJS+llRr3QES7hLRWyHOIIljmTtquv6Q4SQyyilq0RZcQRL07TLBgcHn2pEJnwWEUAE1CGANkEd9tgyIpA0BBqxF35HsJKGBcqLCKQNgYYIiPBwVCqVVZzzQ3t7e7cODQ2tAIAbKKXLXSB1XV9OCPklpfRWXdfPAoCPMsZONAzjy5zzxSJexDCMfs75r3t6evTVq1eX0jYI2F9EoFUQQJvQKiOJ/UAE4kegEXsRv3TYAiKACMSJQEMERAhWKBROJoRcDgBtzk1Wl+i6fhPnfHmxWFxRKBT21DTtZgBYAACbTNM8rVgsvrJkyZK2Uql0vXsNr6Zp5w8ODv42zs5i3YgAIhA/AmgT4scYW0AEWgWBeu1Fq/Qf+4EIpBWBhglIWoHDfiMCiAAigAggAogAIoAIIAKIQHgEkICExwyfQAQQAUQAEUAEEAFEABFABBCBOhFAAlIncPgYIoAIIAKIACKACCACiAAigAiERwAJSHjM8AlEABFABBABRAARQAQQAUQAEagTASQgdQKHjyECiAAigAggAogAIoAIIAKIQHgEEkNADMP4OABczjnPEUKWUUqvDt/d4E8UCoUeQsjKcrn8wQ0bNrzU19e3JJPJ/BsA9HLO/zw2NnbWyy+/PBa8Rv+SztXEZwOASLP4zMKFC899/fXX+03TvCnOdoVkuq7/EyHkQ5xzkxDy75TS7w0MDLyjGW2L9g3D+DYAzKeUfroZ7RqG8XPO+f6EkFFnZK6sVCrr4h7jQqHwIXFrHCGkg3P+EGPsgrj7q+v6uYSQv3f0inDO9xZJPyuVyrVx99df6xsr0Uy7oMImOHNDXFnedLuANgFa1iY4Nj/xdsFv/vf39y80TXMZIWR3zvlGQsgplNI3G7M69T3tJ2tfX98Bmqb9wHk3jBJCPkcpfba+1up/yk9Ot+ZCobC/pmm/o5S2199a/U/6yblkyZI9yuWyWLO9lXM+nM1mT3/uuef+p/4W63vST87FixfvXalUbgGAHs75VtM0z1y3bt3L9bXW2FO17zi5tjjmUiIIyKJFi3bPZrNP53K5A9auXbvNMIwHTNO8tlgsPtwY3NM/XSgU/poQciMhRC+VSrogIIZh/BEAvkgpXanr+pWEkByl9CtRtW8YxsGc838bHx8/9MUXX9xhGMbPAEC0KXKnxNau8yI6gRDyfymlR+2zzz5z2transtkMseZpnl73G07C6yjAeDnALBCEJC4sXb6zMbHxw958cUXt7pjGHe7hmG8HQCe1DTt4Oeff/4NwzB+wzm/hhDyzWbgLPq5ePHiQqVSeUDTtMNN0/xVs9qNap7I9TTTLqiwCc7cUGIXdF1Hm2BvjMRt95XbhKTahSDzX9f1uwkhd1JKlxUKhbM1TTuGUnpqHPZopjqDyGoYxp8B4FyRnFnX9fcRQr5DKX1XM2UNIqeQZ6+99srn8/mHRRoFSmmmmTKKtoLIaRjGw5zzOxhjN+m6LpJjH80Y+0QzZQ0ip67rt3DOnyoWiz/Sdf0LAHAoY+yMZsop2pruHSfLEMdcSgQBERnWOedHMcbOcV7KZ3DOjxRJDOMYJF3XfyK8AJzzW8vl8tJMJmNqmvY4pXRf0V5fX99emUzmt+7vUcjQ19fXp2naAsbYk84C+UJCyBIAODLOdiXZhRGpOGz8CdM0D4u7z6LtJUuWzCuXy/cTQn7BOd/PNM3L4m7XaXM9AKzknL9NvKBM0/z3uNsVHi4AWEgp/T9O3/cYGxtry+VyjzVpjMWC6iFCyM8qlcrjcfc3inkxUx3NtAsqbIJja1TaBbQJMdv92WATnHdq4uyC3/xfunRpduPGjW9SSuc7WdMzhmFsppTOa3YWdT9ZAYCIRM2MsZ+K8RgYGJhfqVQYY0zI3rRPADktWXRdvwEAHiGE/KcKAuInp8DPNM3nKKW7O+/atvHx8b2KxaJ47zft4yeng+UyAFjDGPu2rusXEUL6KKXnNk1Ip6Had5zYeHdliGsuJYWAXMw572SMXeYYy6M55xcxxo6Lc5B0XX+hXC4fmc1mFxBCvk0pPcJpTxiykbhcj/vuu+9bMpnM04SQHwLAB5vVrmEYV3POv0QIucM0zRs1Tbs27rZ1Xb9D07QbTNMUx4KO5Jz/OG6sdV0fAIArxsfHz61UKjvz+fwKx5geH2d/HaO9EwD6CSEiMed9pmne3wycHUP3HkLID8Sumq7rh8aNc5xz07EDTbcLqmyC6K8Ku4A2gbS0TUiyXTAMY8b5L3afc7ncM5TSt7m2yDCMl7LZ7CFr167937jtk1y/n6y1shiG8SPOeTauTVavvgeRUxwj1jTtROe0gkkp1ZqJZRDbr+v6IQBwPQA8QQgRJyxeqlQq5zX7aFMQPHVdX0QIeQoAygCQ5Zz/DWNsQ7Mxddtz33EyAYlrLiWCgOi6fikA5GsIyIWMsRPiHCR3IDRNe2smk7mmZnE6RCntiLr9/v7+fTjnYkG8TOxSN6tdtx+Oa3UFIURkpRfuapl0RdpnwzCEB6tfeATE7o8gIJVK5aZm99kwjI9yzr/oHKuLs783AsDhmqa9p1wuD2uadi/n/LeETFnkRIqz9PK9jXP+IGPslr6+vnc3G+eo54oKu6DCJgjcVNoFtAmx2kClNsFZzCXSLvjN/4GBgQWmaT5dQ0BeLpfLB65fv/6NqO3RTPX5ySo9qxmG8S+c80M1TTt6cHBwaDbJ6SxE781ms0evXbt22DCMigoPiB+e/f39f8M5X2ma5oeLxeIKwzDO4Zyfzhg7ajbh6WwAPCmOYgs5dV0/SWyOMsb+qplyym1NR0DimkuJICCGYVQduRJuLQA4glIqzvXF9pEWGzyTyYhjMn2isUKhsCch5DeMMT3KxnVdfxchRJCPb1FKb3COesXebqFQWJzNZrXnn39enEEVx3Q+zzk/kBAiMC7E1WdxHIhzvgchpAIA84SXCwDuEUQkznb7+/sPrFQqC8SEdwyAmPTnEULeFme7uq5fRQjZhVL6RQfnz3HOD4obZ9GW40J9tb29fdGaNWtGmqVbUc6P2rpU2IVm2wRHP5tuF9AmWAuBlrYJSbcLfvNfOjYijlyZACBOLogjWbsqOILlu4ZZsmRJW6lUul0Eobe3t58k7HSc9nO6uv0wFQt5ALgEAAQxEuvH/QDgv03TXFosFrc3S14/OYVXQcjFGOsRMjmbKH9hjHU1S0bnHT/juBuGsSvn/HnG2G6uXIZhvKFp2sDzzz+/qZmyum1NR0DimkuJICCCfVUqlVViV6C3t3fr0NCQWDjeQCldHucAyQOh6/oaAPiCiNEwDOMyzvkujLEvRdV+oVDYjRDyrHPzxT2SMsTarkMuTiaEXLBw4cKjXn311YymacID8mPTNL8eZ59rWLflARFu3bixdnb/b8lms/sDwHi5XBb69BPOubhUILYxdtzCt5TL5UM3bNgwrOv6ncILYprmP8TZrjPG4savHzDGDm+mbkU1P6arR4VdaKZNcMZNiV0oFApoE1rcJiTdLgSZ/7quLyeE/JJSeqvwsgPARxljJ8Zpl+q1VeLiGc75HMbYac0mSK7MQTCV+2cYhpIjWEHkFEH9nPOLGWP39/f3f4xzfr50oqMpKhBQzpcc78wThmEcBgC3RBlfHLaj0xEQZyMs8rmUCAIiLZIvB4A2sUvOGBMsPNaPrusbRBC6OAsndgQ1TRNXuglG/QIh5NQo3aOGYXyDc34BIYQ5OwviKt77TdP8eZztSqz7GwBwIudcnEO8nTH2LefqYXEFcCx99iIgzWjXMAxBHv+Oc55xAum+1ox2dV3/FABcKM56EkIeoZSe39fXtziTycSKs2OAT5JvgIlbp2OdnE7lzkK5aXahmTbB2UFTZheETUKbYF2/HuvcVGUThH4l3S6cRXmvAAAKe0lEQVRMN/91Xb+Jc75ceLjFaQVN024GABFzt8k0zdOKxeIrzbBNtW3MJCvnfDCTyVAAEP9EnKD4cErpgc716U0T2Q/TGgKi5AiW15pQHntx42O5XBZHHIXHa7tpmmetW7duXdOAnOEdJcvZ399/EOf8XznnecezJDZB/7vZcrrtye+4uOdSYgiIqsHAdhEBRAARQAQQAUQAEUAEEAFEIDoEkIBEhyXWhAggAogAIoAIIAKIACKACCACPgggAUEVQQQQAUQAEUAEEAFEABFABBCBpiGABKRpUGNDiAAigAggAogAIoAIIAKIACKABAR1ABFABBABRAARQAQQAUQAEUAEmoYAEpCmQY0NIQKIACKACCACiAAigAggAogAEhDUAUQAEUAEEAFEABFABBABRAARaBoCSECaBjU2hAggAogAIoAIIAKIACKACCACSEAU64DIJMo5X0sIKTmitAPAymw2+4W1a9eOqxRP1/VfZzKZTz///PMbZ5LDMIw/AMCxlNI365VX1/VSuVzeVyR9rLeOIM/puv41TdMGBwcHfxmkPJZBBFQggHbBRh3tggrtwzYRAUQAEYgfASQg8WM8YwuGYVQ0TdvTXeQvXbo0u3Hjxic4508yxi5WKZ5YBBFC9hwcHHwtbjl0XR8vl8t9TSAgj3HObyoWi/8Rd5+wfkSgXgTQLkwQELQL9SoRPocIIAKIwCxGAAmI4sGZbpGv6/o1hJABSumH+/v7/8Y0zWsBoJsQIgjBdwYHB29bvHjx3uVy+feEkD9wzvfNZDIf5pz3cM6vAwDxf4VzflWxWLxzyZIle5RKpR8AwD6EkBzn/EHG2KUAYDo7rV8DgBMAYCEA/JAx9m1d15cRQk4V3plsNnuSaZqizu8CQBvnfCEhZHV3d/cnV69eXZL7oOv6CYSQr3POc4SQMgBcQSl9oBbm/v5+Ie+3OOc7CCG/45yf6xKQIHUYhnEOAJxCKT1G1F0oFHbTNK1YKpX2zmazQr5/4ZzvLr4jhPyMUvrPhmFcwDm/GgCEp+YrmqatcPA6mHMusP1de3v7l9esWTNiGMYZAPBlznmJEFIBgIsopSsVqws2nxIE0C6gXUiJqmM3EQFEIKUIIAFRPPC1Cw1d198KAI8CwPW5XO62crn8POf8Y4yxJwuFwp6EkKcJIX+byWReqVQqLxBC3js4OPhbAMgYhvE/APAFSuk9fX19fZlM5sGhoaF3dnd3L+ecC2Jxl/CwvPbaa2L3/2nG2HdF+wBwIaX0e/39/e80TfP/aZo2f3BwcEh8p2naW4V3xjCMn5qm+R/FYvGhgw46KDc0NLSGc/5VxtjdYreWELJXpVLJa5p2LwAcKY5jOSRJkItDisXiKy7UhmHsCgDrCCHvGRwc/JOu658ihPykVCq9PZPJ5ILUsXDhwo6urq6XTdN817p1617Wdf1CQsgSSulnDMOgpmleLrwc++yzz9y2trbHOefXiN91XX8MAG5kjP3cMIybAWCcUnqu4CnS75/Vdf1NTdMOGxwcpLquv48Qchil9ErF6oLNpwQBtAtoF1Ki6thNRAARSCkCSEAUD7x81ptznhG77Zzzuxhj3zQM4/1ix54xdrArpq7r3weAsWw2+6NKpbI+m812iFiRQqGwv6ZpD1JK3yJ3SSzUu7u7hwBgjVhki+845+2CyFBKPyXaN02zUCwW14vvDMMoVyqVt4tFvbwIEsTl1VdfPV7TtMWccx0APkII+RKl9Fa3HOf8I0JeQoiI43DbmgsA5zHGfiX14URCyCWU0kOlvw2Xy+XFuVzuA0HqEM/puv6vAPC/jLFvGIbxZ9M0P6Np2lbn+NpuEuG5AAAOpZR+UhAQ9wiWYRj/a5rme4vF4nNOfe8CgF8zxhYYhiE8SScBgJD7EdM0lxeLxZ2K1QWbTwkCaBfsgdZ1He1CSnQeu4kIIALpQgAJiOLxlr0MtaKIo0gAcKVMQJyF8c5MJvOv5XK5yBhrE88NDAy8wzTNRyml1rEjh0z0E0Je5ZxvNU1zl2KxuF38XXgF2tvbK66XQ47zkIM+azwgTwHAoGma92cymT9zzn/MOf93xtgtLgExTVMs2I9mjJ3oytDf379wcHDwdQAQx5jcRYX4/lLG2CGSrNtKpdI7s9nsh4PUIZ4THhvO+T2c81MB4CbG2F8VCoXFhJDHGWMyARFHqd7NGPt4DQF5o1KpHLVu3bq1Tn0Hmqb5gPus8CIRQoT3Q8j0VsbY/uLYmmKVweZTgADahQkbhnYhBfqOXUQEEIH0IYAERPGYzxTovWTJknnlcnnQOYL1RF9f316apokjWGdkMpl15XJ5HWMsJ7ogjkVt376dAsAXGWP367q+CACeyWQyummadwPA45TSr++11175jo6O3wDA3ZTSa6c56jFxG5VLRgBgWy6X21wqlRZu2LDhdeFtIYQ8yTn/YrFYvFnygPQAwO8IIUc4R6sOIYQ8ZpqmIR/BEv0qlUpFTdPePzg4uLpQKJysadod4ghWLpfrCFKHRFwEMRKf2yil1ztHzJ7TNO1KESvzzne+c5edO3c+LmJCKKU/MQzjYc75rQ5x+ikA7KSU/j0AaIZh/ER4oYaHh8/t6uoqmqZ55Lp169b19/fvwzkfbG9vny/iQxSrDDafAgTQLqBdSIGaYxcRAUQgxQggAVE8+G78hNdNU04Q+rcBoEsskgHgOsbYTU58xYQHRHTDMIy/Et8DgDj2JDwOXxUB4A5xEX/fFwAEYfkVY+wiJwjdit9w25dvo9J1/ReEkIMIIadwzsXRqE8BwF8AYIgQIhbif6aUfkVeLBmG8REAuEzEpAiZOOdfkY9fScThaM75PzuB6qsB4MRSqXSQuAUraB2iLl3XzxLxMiIw3vXw6Lo+QAi5jnP+Fifo/jZxpM0p/0VCyMUiQL9cLt+ey+W+zzk/SOAigtBLpdIFGzZs2Kbr+icJIV8VBMUJUBcEZplidcHmU4IA2gXrAgu0CynRd+wmIoAIpA8BJCDpG/NIe7xo0aJe4R2Rj3hF2gBWhgggAolDAO1C4oYMBUYEEAFEoKkIIAFpKtyt1VihUPhrQsidhJCHRUB7a/UOe4MIIAL1IIB2oR7U8BlEABFABNKFABKQdI039hYRQAQQAUQAEUAEEAFEABFQigASEKXwY+OIACKACCACiAAigAggAohAuhBAApKu8cbeIgKIACKACCACiAAigAggAkoRQAKiFH5sHBFABBABRAARQAQQAUQAEUgXAkhA0jXe2FtEABFABBABRAARQAQQAURAKQJIQJTCj40jAogAIoAIIAKIACKACCAC6UIACUi6xht7iwggAogAIoAIIAKIACKACChFAAmIUvixcUQAEUAEEAFEABFABBABRCBdCCABSdd4Y28RAUQAEUAEEAFEABFABBABpQggAVEKPzaOCCACiAAigAggAogAIoAIpAsBJCDpGm/sLSKACCACiAAigAggAogAIqAUASQgSuHHxhEBRAARQAQQAUQAEUAEEIF0IYAEJF3jjb1FBBABRAARQAQQAUQAEUAElCKABEQp/Ng4IoAIIAKIACKACCACiAAikC4E/j/pX0dUDcQpdwAAAABJRU5ErkJggg==\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labelsPartidos = ['PP', 'PSOE', 'PODEMOS+IU', 'Cs', 'Otros']\n",
    "f, ax = pl.subplots(nrows=2, ncols=3, figsize=(10,8))\n",
    "ax = ax.flatten()\n",
    "for i in range(5):\n",
    "    ax[i].plot(weekAll, sondeosAll[:,i], '.', color=sns.xkcd_rgb[colors[i]], linewidth=2)\n",
    "    ax[i].set_ylim([0,0.35])\n",
    "    ax[i].errorbar(weekAll, sondeosAll[:,i], fmt='none', yerr=sigmaAll, color=sns.xkcd_rgb[colors[i]], linewidth=2, ecolor=sns.xkcd_rgb[colors[i]])\n",
    "    ax[i].plot(np.arange(max(weekAll))+1, theta[0,:,i], color=sns.xkcd_rgb[colors[i]], linewidth=2)\n",
    "    ax[i].fill_between(np.arange(max(weekAll))+1, theta[1,:,i], theta[2,:,i], color=sns.xkcd_rgb[colors[i]], alpha=0.3)\n",
    "    ax[i].set_xlabel('Semana')\n",
    "    ax[i].set_xlabel('Porcentaje de votos')\n",
    "    ax[i].set_title(labelsPartidos[i])\n",
    "pl.tight_layout()\n",
    "pl.savefig(\"porPartido.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sesgos por casa encuestadora\n",
    "Represento a continuación las estimaciones de sesgo para cada una de las empresas encuestadoras, lo que muestra algún efecto curioso en Demoscopia Servicios que sería interesante analizar y entender por qué pasa. Nótese que un sesgo positivo implica que esa empresa subestima los votos y hace falta corregirlo por esa cantidad para obtener las observaciones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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"
    }
   ],
   "source": [
    "f, ax = pl.subplots(ncols=3, nrows=2, figsize=(12,10))\n",
    "ax = ax.flatten()\n",
    "for i in range(5):\n",
    "    sns.boxplot(data=houseChain[:,:,i], ax=ax[i])\n",
    "    ax[i].set_xticks(np.arange(12))\n",
    "    ax[i].set_xticklabels(labelsEmpresas, rotation=90)\n",
    "    ax[i].set_title(labelsPartidos[i])\n",
    "pl.tight_layout()\n",
    "pl.savefig(\"bias.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Variabilidad\n",
    "Por último, aquí muestro la variabilidad intrínseca de la estimación subyacente de voto para cada partido. Es lógico que Podemos y Cs tengan una variabilidad mayor por su largo crecimiento en el último año."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "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"
    },
    {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = pl.subplots(figsize=(10,6))\n",
    "sns.boxplot(data=sigmaChain, ax=ax)\n",
    "ax.set_xticks(np.arange(5))\n",
    "ax.set_xticklabels(labelsPartidos, rotation=90)\n",
    "boxes = ax.artists\n",
    "for (i, box) in enumerate(boxes):\n",
    "    box.set_facecolor(sns.xkcd_rgb[colors[i]])\n",
    "pl.savefig(\"variabilidad.png\", facecolor=f.get_facecolor(), edgecolor='none')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Push de la página web"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "f = open('elecciones2015/index.html','r')\n",
    "lines = f.readlines()\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "fecha = datetime.datetime.now()\n",
    "lines[29] = \"\"\"<a id=\"welcome-to-github-pages\" class=\"anchor\" href=\"#welcome-to-github-pages\" aria-hidden=\"true\"><span aria-hidden=\"true\" class=\"octicon octicon-link\"></span></a>Resultado {0}/{1}/{2}</h3>\\n\"\"\".format(fecha.day,fecha.month,fecha.year)\n",
    "\n",
    "theta = np.percentile(thetaChain, [50.0, 50.0-95/2.0, 50.0+95/2], axis=0)\n",
    "\n",
    "lines[33] = \"\"\"<td style='height: 50px; background: #02B3F4; color: white; font-size: 25px; border-radius: 1px 10px 0px 0px;'>{0:4.1f}-{1:4.1f}-{2:4.1f}</td>\\n\"\"\".format(theta[1,-1,0]*100,theta[0,-1,0]*100,theta[2,-1,0]*100)\n",
    "lines[34] = \"\"\"<td style='height: 50px; background: #8E1744; color: white; font-size: 25px; border-radius: 1px 10px 0px 0px;'>{0:4.1f}-{1:4.1f}-{2:4.1f}</td>\\n\"\"\".format(theta[1,-1,2]*100,theta[0,-1,2]*100,theta[2,-1,2]*100)\n",
    "lines[35] = \"\"\"<td style='height: 50px; background: #FF0202; color: white; font-size: 25px; border-radius: 1px 10px 0px 0px;'>{0:4.1f}-{1:4.1f}-{2:4.1f}</td>\\n\"\"\".format(theta[1,-1,1]*100,theta[0,-1,1]*100,theta[2,-1,1]*100)\n",
    "lines[36] = \"\"\"<td style='height: 50px; background: #FF800E; color: white; font-size: 25px; border-radius: 1px 10px 0px 0px;'>{0:4.1f}-{1:4.1f}-{2:4.1f}</td>\\n\"\"\".format(theta[1,-1,3]*100,theta[0,-1,3]*100,theta[2,-1,3]*100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "f = open('elecciones2015/index.html','w')\n",
    "f.writelines(lines)\n",
    "f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.system('./update.sh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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