{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# iGEM Human Practice Data Analysis - Box Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from __future__ import division, print_function # Makes division and printing work like python 3 (we're using 2)\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "from scipy.spatial import distance\n",
    "from tabulate import tabulate\n",
    "import csv\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 239,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_2013 = os.path.join(os.getcwd(), 'datasets', '2013N.csv')\n",
    "data2013 = pd.read_csv(data_2013)\n",
    "#data2013.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_2014 = os.path.join(os.getcwd(), 'datasets', '2014N.csv')\n",
    "data2014 = pd.read_csv(data_2014)\n",
    "#data2014.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_2015 = os.path.join(os.getcwd(), 'datasets', '2015N.csv')\n",
    "data2015 = pd.read_csv(data_2015)\n",
    "#data2015.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "coor = os.path.join(os.getcwd(), 'datasets', 'coordinates.csv')\n",
    "coordinates = pd.read_csv(coor)\n",
    "#coordinates.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#coordinates[0:1][['x', 'y', 'z']].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "distance_matrix = distance.cdist(coordinates[0:46][['x', 'y', 'z']].values, coordinates[0:46][['x', 'y', 'z']].values, 'euclidean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "p_2013 = data2013.values[:, 4:]\n",
    "p_2014 = data2014.values[:, 4:]\n",
    "p_2015 = data2015.values[:, 4:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(104, 45)\n",
      "(113, 45)\n",
      "(153, 45)\n"
     ]
    }
   ],
   "source": [
    "print(p_2013.shape)\n",
    "print(p_2014.shape)\n",
    "print(p_2015.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 247,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(104):\n",
    "    for j in range(44):\n",
    "        p_2013[i][j+1] /= float(p_2013[i][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(113):\n",
    "    for j in range(44):\n",
    "        p_2014[i][j+1] /= float(p_2014[i][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "for i in range(153):\n",
    "    for j in range(44):\n",
    "        p_2015[i][j+1] /= float(p_2015[i][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "diversity_2013 = []\n",
    "for i in range(104):\n",
    "    diversity = 0\n",
    "    for j in range(1, 44):\n",
    "        if p_2013[i][j] > 0:\n",
    "            base = p_2013[i][j]\n",
    "            for k in range(j+1, 45):\n",
    "                if p_2013[i][k] > 0:\n",
    "                    diversity += distance_matrix[j][k] * p_2013[i][j] * p_2013[i][k]\n",
    "    diversity_2013.append(diversity)\n",
    "\n",
    "#print(len(diversity_2013))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
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UUFAg6dT9QABqJ66wo8o5nU499dRT2rdvn9LT0/Xaa68ZHQkATC8kJEQzZsxQ\nZGSk2rRpo0GDBhkdCYBBuMKOKldQUKB9+/a5tnfs2GFgGgCoOZo2barmzZsbHQOAwbjCjioXEBCg\n1q1bu7avvPJKA9MAAADULBR2VDmLxaJp06YpKipK0dHRuvfee42OBAAAUGMwJAbVwt/fX40aNZIk\neXjweyIAAMC5ojkBAAAAJkZhBwAAAEyMwg4AAACYGIUdAAAA52X37t2aNGmS7rjjDn377bdGx7ns\ncdMpAABADbNq1Srt3LnTsPdPTk52rcI7e/Zsbdq0ydBVzDt06KD+/fsb9v5VjcKOavHDDz8oMTFR\nVqtVGRkZioqKMjoS4HLkyBEVFhYqMzNTkZGRRscBANNzOp0VPkbVsDj5KaOKlZSUaMyYMSotLZUk\ntWrVSv/85z8NTgWc8tlnn+mNN96QJAUGBmrevHkKDg42OBXwm1mzZkmSHnvsMYOTAL/ZsWOHnn32\nWdntdt17773q16+f0ZEua1xhR5VzOByy2+2u7ZKSEgPTAO5SUlJcj/Pz8/Xzzz9T2AHgLDp27Khr\nrrlGTqeTsl4NuOkUVc7X11cTJ06UxWKRp6enJk6caHQkwOXqq692PQ4JCVHLli0NTAMANYvFYjE6\nQq3AFXZUi7i4OO3atUuSdOWVVxqcBvjNTTfdpK+//lqFhYV66qmnVLduXaMjAQDghsKOasNv4TCr\n4OBgBQcHKzQ01OgoAACUw5AYAAAAwMQo7AAAAICJUdgBAAAAE6OwAwAAACZGYQcAAABMjMIOAAAA\nmBiFHVVmw4YN+vDDD/XLL78YHQUAAKDGYh52VInVq1dr7ty5kqTly5fr1VdfNTgRAABAzURhR5VI\nSUlxPS4oKNCePXt05MgRWa1WA1MBAADUPAyJQZXo2rWr63HdunW1bNky7d69W7t27dKCBQsMTAYA\nNcfnn3+u5ORkpaamKj8/3+g4AAzCFXZUiRtvvFFBQUH65Zdf1KFDB02ePNn13MaNG3XnnXcamA4A\nzG///v2aP3++nE6nCgoKtGjRIk2aNMnoWAAMQGFHlbnyyit15ZVXyuFwqHHjxjpw4IAkKTo62uBk\nAGB++fn5cjqdru28vDwD0wAwEkNiUOU8PDz0/PPPKzIyUs2bN9dDDz1kdCQAML127dopJiZGkuTl\n5aWhQ4canAiAUSjsqBYhISFq3ry5IiMj5ePjU+Ex+fn5stvt1ZwMAMzJarXqqaeeUkxMjGJiYtSi\nRQujIwHP78X1AAAgAElEQVQwiOmGxDz99NPav3+/Fi5ceNZjhw8frh07dpTb37dvX82ZM8e1nZmZ\nqRkzZigxMVGS1KtXLz3xxBMKCQm5dMFxzoqLizVz5kzt3LlTXbt21eTJk/XSSy9p06ZNCg0N1bRp\n09S4cWOjYwKA4SwWS6UXOQDUHqYq7AkJCVqyZInrnwDPxOl0KiMjQ7GxserTp4/bc78veydOnNC4\nceNUUlKiiRMnym636+2339bu3buVkJAgb2/vS/45IOXk5Gjz5s0KDw9X586d3Z774osvlJSUJEla\nv369QkNDtWnTJknS0aNH9fHHH+vhhx+u9swAAABmZIrCbrfb9frrr7sW2jkXWVlZstlsuummmzRk\nyJBKj3vnnXd06NAhrVixQlFRUZKkzp07684779Qnn3yikSNHXnR+uLPZbHrsscd06NAhSdL999+v\nsLAwJScny2q1KjQ01O14T0/3r2FAQEC1ZQUAADA7wwt7cXGxRowYod27dys+Pl4bN248p/PS09Ml\nyVXCK7Ny5UrFxMS4HXfdddepRYsWWrlyZZUX9jfeeEM5OTlV+h5mk5ub6yrrkrR48WLl5OTI4XBI\nkr766isFBQUpNzdXwcHBOnTokJo3b67Dhw/L399fR44c0axZs4yKX22CgoKYog0AAJyVKQp7fn6+\nZs+erQEDBqh3797ndN6ePXsk/VbYbTab/P393Y7JyclRZmam+vbtW+789u3ba926dReZ/uxycnJ0\nMidHPrXoqrHFy0uenp4qKyuTJPkGBOjEiROu58vsdrXt2NG1XexwKDQiQqEREZKkUkml/zv3clVc\nUGB0BAAAUEMYXtgDAwO1evXqcsMizmbPnj0KCAjQ9OnT9fnnn8tmsykyMlKPPPKIBg4cKEk6fPiw\nJCk8PLzc+WFhYcrLy1NeXp7q1Klz8R/kDHwCAhQzYkyVvofZtLupr3ZvSVTd+vXVrvu12rpmtRJX\nrZTV00u9Rt+mlh07GR3RUIkJi42OAAAAagjDC7uHh4c8PM5/dsn09HQVFBQoLy9PM2fOVG5urt57\n7z09+uijKi0tVXx8vAr+dxXTz8+v3Pmn77q32WxnLOwpKSkqKio673ynlZSUSBfw+Wq64PBwXTNw\nkGv76pv7qmOPG+Rh9ZQXN/pKOvXd2Lp1q9ExoP/9OZX47wFT4vsJs+K7eeldddVVFe43vLBfqJEj\nR8rhcOi2225z7Rs4cKDi4uI0a9YsDRo0yG2FuMpYLJYzPt++ffuLyrl27VoVXubDO86Vj5//2Q+q\nRby9vSv9g4nqtXbtWkmV/0UJGInvJ8yK72b1qbGFfcyY8kNMfH19NWTIEM2dO1fp6emuMe3FxcXl\njj29LzAwsGqDAgAAABfhshurcXoxJJvNpkaNGkmSsrOzyx135MgR1a1bt9yNqgAAAICZ1MjCfvjw\nYQ0cOLDCedv37dsnSWrSpInq1q2rJk2aKCUlpdxxu3btUocOHao8a22Vc+yo1i9fqi1ffamy0lKj\n4wAAANRYNXJITHh4uHJzc5WQkKDx48e7hrUcPHhQS5cuVffu3RUWFiZJ6tOnj9577z1lZGS4poDc\nsGGD9u3bpwkTJhj2GS5n9rIyLZ/3qvJPnprKMffYUV03KF67Nm2Ql4+Prrj2elmtVoNTAjCz2riG\nRWVO/xxqw/oU54I1LFAb1YjCnpmZqeTkZHXt2lWRkZGSpGeeeUYPPPCARo8erREjRqigoEAffPCB\nPD099cwzz7jOvfvuu7V8+XKNHz9ed911l4qLi/XWW2+pffv2Z1whFReuMD/PVdYlKTszU8tfe1XH\nfj14ajsrU71H31bZ6QBQK9ewqIzH/6Y9ZgID1rBA7VUjCntSUpKmTp2q6dOnuwp7bGys5s2bp/nz\n5+vFF1+Ur6+vYmJi9Oijj7qtahoSEqL3339f06dP15w5c+Tr66vY2FhNmTJF3kwvWCUC6gYpomWU\nft2bIUlq1r6Dktesdj1/MCPDqGgAapDauIYFzow1LFBbma6wn54i6PeGDh2qoUOHltsfGxur2NjY\ns75my5Yt9eabb16SfDg7i4eHBt1zv/an7JCvf4CaRLfRgT0/6fDP+yVJTdu2MzYgAABADWK6wo7L\ng6eXl1pd2dW1PfjeB7R7a5K8fXzVukvXM5wJAACA36Owo1p4+fiow3U9jI4BAABQ49TIaR0BAACA\n2oIr7ABqPbvdrrKyMjmdTlksFqPjAADghivsAGq1jIwMJSYmKjExUc8995zsdrvRkQAAcENhR7XJ\nzsrUyewjRscA3HzyyScq+9/81klJSUpNTTU4EQAA7hgSg2qx9sNFSkvcJFks6jl0uDpcf4PRkWo9\nVpI8JeMP6wJ89NFHWrVqlUFpzIGVJAHAXCjsqHLFhYWnyrokOZ36cd23FHYTqO0rSRYXF8tisahB\n48ayFRaquKhIDSIi5OHjU6tXlGQlSQAwHwo7qpyXt7f8AgNVmJ8vSaoTEmJwIpxWW1eSTFy1Ujs2\nfimLxaKew0fq1jF3GB3JNFhJEgDMhzHsqHIeVqviJt2nFh06Kfrqboq9lXIE49jtdm1ds1qS5HQ6\ntWX1FwYnAgDgzLjCjmoR1iRS/e+aaHQMQB4eHvINCFRhfp4kyS+wjr5d8qFOZh/RFddcp+irrjY4\nIfCb1M0blbJxg+o1aKCeQ0fI29fX6EgADEBhB1CrWCwWDZgwSZtWfiqrp5cC6tbVrk0bJEm/7s1Q\nWJNIBYeHG5wSkI4f+lXfLPlQcjp15Jef5RcQoOuHDDU6FgADMCQGQK0T3qyZhtz/kOIm3avS0hLX\nfqfTKVsuM+fAHArz8yWn07Vty80zMA3g7tdff9XOnTv1448/aseOHUbHuexR2AHUap1uuFFePj6S\npEZRrdSwRUuDEwGnRLRoqcg2bSVJPn7+6tzr/xmcCPjNK6+8ohMnTig3N1fPP/+8az0LVA2GxACo\n1Ro2b6E7/vKsbHm5qhfWQB5Wq9GRAEn/u2H/7nuVe+K4/AICGb8OU/n9Oh42m00lJSXy9KRWVhWu\nsAOo9XwDAhTSMIKyDtOxeHgoqH4oZR2mM3r0aFksFknSsGHD5O/vb3Ciyxu/CgEAAOC83HjjjVq/\nfr0cDofGjRtndJzLHoUdAAAA583Ly8voCLUGhR1VIv/kCWX8uF1BoWFq3r6DpFMzcJz+57P8kye0\nedVKOex2devbX/XCGhgZFwAAwLQo7Ljkimw2ffzyP1Xwv+nxeg4bIVksWv/JMnn5eKvvuLu0aeUK\nHf55vyTpSOYvum3q0wYmBgAAMC8KOy6544d+dZV1Sfp51y79sjtVTodD9rJSfb/0I9nycl3P5x47\nJqfDIYsH90ADAAD8EQ0Jl1xIeEP5BdZxbUe0jHINhZFOTVXWsUdP13aH63pQ1gEAACrBFXZccr4B\nARr68GTt2ZasoNAwte7SVYH16mn9p8vk7eOrG4ePUnizZmrRoaPsdrvCmzYzOjIAAIBpUdhRJYJC\nw3T1zX1d236BgQoMqicvHx/5+PlJkkIbNzEqHgAAQI3BOARUOXtZmb54521lZ2XqYEa61n74gdGR\nAADARdi9e7eSkpK0adMmffvtt0bHuexR2FHl7GVlKi0udm0X2QoMTAP8xl5WqrTEzfpp6xY5HA6j\n4wBAjfHaa6+pqKhIpaWlmjNnjop/9//zuPQYEoMq5+3rq6v79NOW1V/I6ump7v3jjI4ESJJW/ftt\n/ZK2S5KU+VOabhpzu8GJAKBm+P1FDi54VD0KO6pFTL8B6tjjBlk9PeXt62d0HEAOh8NV1iXp510p\nBqYBgJpl0qRJevbZZ2W323XvvffKx8fH6EiXNQo7qs3vp3oEjObh4aHw5s11eP9+SVJEi5bGBgKA\nGqRjx4665ppr5HQ61a9fP6PjXPYYww6g1oq7+17F9Bugpm2vkJe3jw6k7zE6EgDUKL9fZwVVh8IO\noNby8fOXJP2Stks/JW/RZ2/8S7nHjxmcCgAAdxR2ALXasUO/uh7by0qVe/SogWkAACiPwg6gVmtz\n1dXy8Dj1V2FweLjCmzU3NhAAAH/ATacAarXm7Ttq5P89rtxjx9QoKkpezHQA4AzeeOMN5eTkGB3D\nFE7/HGbNmmVwEnMICgrSpEmTquS1KewAar2QhhEKaRhhdAwANUBOTo5O5uTIJyDA6CiG8/A8VSML\ny8oMTmK84oKqXRSSwg4AgEmtX75UO9evV70GDTRgwt2qExxidCRI8gkIUMyIMUbHgIkkJiyu0tdn\nDDsAACZ0aP8+/bjuW9nLSnXs4AElfbnK6EgADEJhBwDAhMrPb81810BtRWEHAMCEwps1V+deveXp\n7a2wJk3UrW9/oyMBMAhj2AEAMKnrB8fr+sHxRscAYDCusAMAAAAmRmEHAAAATIzCDgAAAJgYhR0A\nAAAwMQo7AAAAYGIUdgAAAMDEKOwAar3S4mI5nU6jYwAAUCHmYQdQazkdDn31wXtK35asOsEhGnzv\nAwoKCzM6FgAAbrjCjirz09YkffzyS/pq4bsqstmMjgOUcyAjXenbkiVJeSeOa+vXXxmcCHDndDh0\nMvuISooKjY4CwEBcYUeVyDl2VF8v/kBOh0OHf/lZXj4+6jVytNGxADde3t5n3AaM5LDb9dmb/1LW\nT7vl4+enuHvuV3jTZkbHAmAArrCjShTlF8jpcLi2C/PzlHvsmGy5uQamAtyFN2uumH4DFBgcrMat\nWqtb3/5GRwJcft23V1k/7ZYkFRcW6r/rvjU2EADDUNhRJRpERqpFh46SJG9fX1k9PfX+83/Te3//\nq3ZvSTQ4HfCbFh06yV5WpgPpe/Ttkg/dftEEjOQXGChZLK5t/7p1DEwDwEgMiUGVsHh4qN+dE5V7\n/JisVqve+/szkiSHw6EtX32pNlfHGJwQOCV57RoV5uVJkvbu+FG/7turRlGtDE4FSCENI9R71K1K\n2bRewWHh6tZ3gNGRABiEwo4qY7FYFFQ/VHa7XT5+fiouPHXTVEDdIIOTAb/x8fNz2/b+wzZgpLYx\n3dU2prvRMQAYjMKOKme1WjVgwiRtXrVS3r6+6nHLMKMjAS4x/QeqIDdHJ48cUftrr1doo8ZGRwIA\nwA2FHdUiomWU4h942OgYQDm+/v7qf+dEo2MAAFApbjoFAAAATIzCDgAAgHPidDqVnZWpnGNHjY5S\nqzAkBgAAAOdkzQcLtSd5iywWi3qNGqN2MdcYHalWMN0V9qefflp33HHHOR37/fff69Zbb1Xnzp3V\npUsXjR8/Xtu3by933PDhw9WmTZty/3v4YcZUAwAAnAtbbq72JG+RdOpK+48s5lVtTHWFPSEhQUuW\nLFFMzNnn6E5MTNTdd9+t1q1b65FHHlFZWZkWLVqk22+/XYsWLVKnTp0knfpCZWRkKDY2Vn369HF7\njcaNmQ2iumRnZSrpy1Xy8vHVdYOHMLUjAAA1jLevr3z8/FVcaJMk1Q0JMThR7WGKwm632/X6669r\n7ty553zOCy+8oIiICC1ZskR+/5s3OT4+XgMGDNDs2bO1YMECSVJWVpZsNptuuukmDRkypEry48wc\ndrs+e+N1FebnS5IK8/M0+N4HDE4FAADOh6e3t+Im3auta1bLYvGQLS9XS16aqWviBqlpm3ZGx7us\nGT4kpri4WLfccoteffVVDRkyROHh4Wc9JycnR2lpaerXr5+rrEtSaGiounXrpm3btrn2paenS5Ki\noqIufXhUKn17sr56/z3t+OE7lZaUuMq6JOUdP25gMgAAcKHCmzXXgAmTZMvP1eGf9+vogSx9+c6/\nZS8rMzraZc3wK+zFxcXKz8/X7NmzNWDAAPXu3fus5wQGBuqLL75wK+unnThxQlar1bW9Z88eSb8V\ndpvNJn9//0uUHhX5dd9erV74ruR0ak/yFnn7+qpd92uVunmjZLGoc6//J0lyOhxK2bheOUePqk23\nGBasAQCghii22VyPS4uL5bDbZfU0vFZetgz/yQYGBmr16tXyPI//yFarVc2bNy+3Py0tTcnJyerR\no4dr3549exQQEKDp06fr888/l81mU2RkpB555BENHDjwUnyEMyosLFRxSYkSExZX+XuZRfbhw5LT\n6dpO+XatmjRrpis6dZKH1SrbgUwlJizWwawsHczMlCTt/OE7dbjySnl5exsVu1oVFxRIteSzAgAu\nP90HDNKa99+VvaxM3fr2l5ePj9GRLmuGF3YPDw95eFz8yJyCggI9/vjjkqRJkya59qenp6ugoEB5\neXmaOXOmcnNz9d577+nRRx9VaWmp4uPjz/i6KSkpKioquuBcdrv9gs+tqYKCg+Xl5aXS0lJ5eHio\nbr16kiT/gADlnDihQwcOKCAwULbfDZOx2+0qKiqqNYVdOvWZt27datj7l5SUSJfgzx4uPyUlJYZ+\nN09n4PuJihj9/eS7eUpUp85qOm267GVl8g0IMDqOKVyK7+ZVV11V4X7DC/ulUFhYqPvuu09paWm6\n55573GaZGTlypBwOh2677TbXvoEDByouLk6zZs3SoEGD3IbQ/FH79u0vKtvatWtVWFammBFjLup1\napqrhuQr86c0JX35hX7atUsRLaN0bdxgLZv7ipwOh44eOaJ2MdfoZOImSVLd+qG64bZx8vb1NTh5\n9UhMWCw/T89K/2BWh9PfTeCPvL29Df1uSnw/UTmjv598N3/j5ePDlfXfqcrvZo0v7Lm5ubrnnnuU\nnJysYcOG6ZFHHnF7fsyY8kXZ19dXQ4YM0dy5c5Wenq42bdpUV9xawy8wUDnZ2crJPiJJ+nVvhlI3\nb5LT4XAd4+njo1semqyco0fVrN0VtaasAwAAnI8aXdiPHTumCRMmKDU1VaNGjdLf/vY3WSyWczo3\n5H9zh9p+d9MELq0//tbdoGlT/ZyaIlturqyenmrV+UpFtGipiBYtDUpYu9XG+ytwdtxfAQDmU2ML\ne35+vqusjx8/XlOnTi13zOHDh3XXXXepf//+evDBB92e27dvnySpSZMm1ZK3NurY4wZlZ2Xp8P59\nqt+okXZt2qig+qG6KraPIqPbql6DBkZHBAAAML0aW9j//ve/KzU1VWPHjq2wrEtSeHi4cnNzlZCQ\noPHjxyswMFCSdPDgQS1dulTdu3dXWFhYdcauVayeXrr59rGyl5Xp309PVWlxsSTJKaljj57GhsOp\naVG9vGrd/RU4s9P3VwAAzKNG/K2cmZmp5ORkde3aVZGRkcrIyNDy5ctVt25dtWvXTsuXLy93zulV\nTZ955hk98MADGj16tEaMGKGCggJ98MEH8vT01DPPPFPdH6VWspeVucq6JBUV5J/haAAAAPxejSjs\nSUlJmjp1qqZPn67IyEglJiZKOnXDaWVX108X9tjYWM2bN0/z58/Xiy++KF9fX8XExOjRRx9l9dNq\n4u3rq6ti+2jrmtXysFoV06/q578HgMtFaUmJPL28zvkeLQCXH9MV9rVr15bbN3ToUA0dOtS1PWbM\nmApnf6lMbGysYmNjL0k+XJjuA+LUsUdPWb085ePHSrMAcDZOp1NrF3+g3VsSFRgcrEH33K/gBuFG\nxwJgAGb+R7Xxr1uXsg4A5+jQvr3aveXUvyjnnzihrWtWG5wIgFEo7KgWtrw8/bpvr9tYdgBA5Tz/\nML1mbVoJGoA70w2JweXn6IEsfTLvVZUUFapeg3ANffgR+fpzpR0AziSsSaS6D4hTysb1qhfWQDH9\nBhgdCYBBKOyocqmJm1VSVChJOnnksDLTUtW6q7HLngNATXBVbB9dFdvH6BgADMaQGFS5uvXr/7Zh\nsajO/1aZBQAAwNlxhR1VrmOPniq22ZT10241bXeFGjZvYXQkAACAGoPCjirn4eGhnKPZOrR/nw7t\n3ydPLy9d2au30bEAADhvhYWFKi4pUWLCYqOjwESKCwqkKrwxnCExqHLFhTbtSd7q2k7ZsN7ANAAA\nADULV9hR5bx8fOVft65submSpKCwMIMTAe6cDodKS0rk7etrdBQAJufn5yd5eSlmxLkv4IjLX2LC\nYvl5Vl2tprCjynl4eGjwvQ9o65rV8vLxVff+A42OBLicOHxYn86fp4KTJ9W669WKve0OloAHAJgK\nhR3VIqRhhG6+fZzRMYBytq75UgUnT0qS9iRvUfvrrlejllEGpwIA4DeMYQdQq3n5+Lhvs5okAMBk\nuMIOoFaL6TdAeceP6+SRI2p/3fUKaxJpdCQAANxQ2AHUan6BdRQ36T6jYwAAUCmGxAAAAAAmxhV2\nAABM6vjhQ0rflqx6YQ0UfdXVRscBYBAKO6qFvaxUe3fskLevr5q1u8LoOABMjtUkpdKSEu3cvl12\nu12StHv9dwqPiDA4lbGqejVJwKwo7KgWK996Q1k/7ZYkdekdq2vjBhucCADMrdBmc5V1ScrPy6v1\nhR2orSjsqHJFNpurrEtSxo/bKewAzojVJKWiggJlzZruWiW6S59+atutu8GpjFXVq0kCZsW3HlXO\nx9dXQWFhysnOliQ1iGxqcCIAMD/fgAANn/xn7U/ZqaCwBoqMbmN0JAAGobCjylk8PDTkvof03+/X\nydvHR5179TY6EgDUCIH1gtXh+huMjgHAYBR2VIvAevV03aAhRscAAACocSjsAAAAOC9FNpu2fLlK\nJcXF6to7VvUaNDA60mWNwg4AAIDzsnbx+9qfslOSlPXTbt3+l2fk4cF6nFWFnyyqzdEDWa4bTwGz\ncDoc2vHDd/p+6Uc6/MvPRscBgBrh+KFDrsf5J0+otLjYwDSXP66wo1p885/FSt28UbJY1HPocG6i\ngmls++ZrbVq5QpKUmrhJtz7xlALrBRucCgDM7YprrnX93dmyU2f5+PkZnOjyRmFHlSsuLDxV1iXJ\n6dSP676lsMM0srMyXY/LSkp08sgRCjsAnEXXm25W41bRKi0uUuNWrY2Oc9ljSAyqnJe3t/wCA13b\ndUJCDEwDuIvq3EWyWCRJdevXVxjrBADAOQlv1kxNotvIwtj1KscVdlQ5D6tVcZPuU9KXq+Tl46vr\nBjO9I8yj1ZVdVLd+feVkZyuyTVv+WRcAYDoUdlSLsCaRGjBhktExgAo1iGzKCrwAANPi3zAA1Hr7\ndu7Qtm++Vs6xo0ZHAQCgHK6wA6jVUjau17qE/0iStn/ztUZPmSq/wDoGpwIA4DdcYQdQq2X9tNv1\nuDA/X0cPHjQwDQAA5VHYAdRqTVq3cT32DQhQ/YhGBqYBAKA8hsQAqNXaX3e9/OrU0ckjhxXV+Ur5\n12E4DADAXM67sCckJKh///4K/N282gBQk7Xs2MnoCAAAVOq8h8Q8/fTT6tGjhx599FGtW7dOdru9\nKnIBAAAA0AVcYf/HP/6hTz/9VF9++aVWrVql4OBgDRw4UEOGDFGHDh2qIiMAAABQa513YY+Pj1d8\nfLyOHj2qzz77TJ9++qkWLlyo999/Xy1atFB8fLwGDRqkiIiIqsiLGip180atX75MXj4+6nPHeEW0\njDI6EgAAuEA52dla9/ESlRYX65oBcWrcOtroSJe1C54lJjQ0VOPHj9fSpUu1cuVKPfDAAwoICNDL\nL7+sm266SWPHjtXSpUtVWFh4KfOiBiorKdG6hP+opKhIBTk5+u7jBKMjAQCAi/D1hx8o66fdOvzz\nfq1a8BZDpKvYJZnWMSoqSj169NC1116r8PBwORwOJSYm6sknn1TPnj31r3/9Sw6H41K8FS4HFovR\nCQAAwEUoys93PS4pKpK9tNTANJe/i5rWMS0tTStWrNCqVav066+/yul0qkOHDpo4caL69++vXbt2\naf78+XrllVd07NgxPfXUU5cqN2oQT29v9Ro5RuuXL5WXj696DhthdCQAAHARuvUboK8XLZTDblfX\n2D7y9vU1OtJl7bwLe2ZmplasWKGVK1dq7969cjqdatiwoe6++24NGTJEUVG/jU3u0aOHunfvrptv\nvlnLli2jsNdibWO6q21Md6NjAACAS6B1l66KbNNW9tJSBQQFGR3nsnfehf3mm2+WJPn5+Wnw4MGK\nj4/XNddcI0slwxy8vLwUFBQkDw8WVQUAALhc+Pr7Gx2h1jjvwn7NNdcoPj5effr0kf85/oeaO3eu\n6tevf97hAAAAgNruvC97x8fHq23btmcs61u3btW8efNc25GRkedc7gEAAAD85rwL+9SpU/X111+f\n8ZivvvpKb7zxxgWHAgAAAHDKWYfELF26VGvXrnVtO51OrVy5UqmpqRUeX1paqs2bN6tevXqXLiUA\nAABQS521sN9www167rnnZLPZJEkWi0V79+7V3r17Kz3H29tbDz/88KVLCQAAANRSZy3sYWFhWrNm\njQoLC+V0OhUbG6tx48Zp7Nix5Y61WCzy9PRUcHCwvLy8qiQwAAAAUJuc0ywxISEhrsfTp09Xu3bt\n1Lhx4yoLBQAAAOCU857W8ZZbbqmKHAAAAAAqcNbCHhMTo0mTJmnixImu7XNhsVi0efPmi0sHAAAA\n1HJnLeyBgYHy9vZ22wbOl8Ph0IE9P8nLx0cNm7cwOg4AAECNcdbC/vspHSvaBs7Fl+/+W/t2/Ff/\nn707j6uq2v8//oajTCIqipqihZpYmFMGaYOpBIYDiuWsOaQN+q30plfv17LJn5bd6uJ0u2mapVTe\n63W4ZJN6zdSccCgcEsQiUXCKeeb8/vDLSTqggMDeyOv5ePB4sPfae/HZujzn7WKdvSUpIKSf7g4M\nMrgiAACA6qHMD04Cyio7M8MW1iXp2J7vDawGAACgeilXYE9JSdGaNWts28nJyZo2bZoefPBBDR8+\nXLt3766wAlH91XZ2kXv9BrZtz6ZNDawGAACgeilzYP/ll1/Up08fvfbaa0pMTJQkvfTSS/r888+V\nlpamI0eOaOLEiTp06FCFF4vqydHRUQOenqw7ArqpY4+H1HvEKKNLAgAAqDbKHNgXLVqk5ORkTZ8+\nXfXr19eFCxf09ddf6/bbb9euXbv0xRdfyN3dXX//+98ro15UU/W9Gqvn0OG6LzRMzq5uRpcDAABQ\nba3g00oAACAASURBVJQ5sO/evVtBQUEaP368nJ2dtW3bNhUUFGjgwIFycXFRixYtFBwcrIMHD1ZG\nvQAAAECNUubAnpycrJYtW9q2d+zYIQcHB91///22fe7u7srJySlXQS+++KJGjx5dqmPj4+M1ZcoU\n+fv7y9/fXzNmzNClS5fKfRwAAABgNmV+0mnTpk0VHx8vScrJydGuXbvk5eUlX19f2zGHDh3SLbfc\nUuZi1q5dq88++6xUD2e6fPmyHn/8ceXk5OiJJ55Qfn6+li9frhMnTmjt2rW2e8eX9jgAAMwoNydH\ntWrXloODg9GlADBImQN7165dtXHjRi1atEgnTpxQenq6Bg8eLOnKTPaKFSsUFRWliRMnlrrP/Px8\nLV26VIsWLSr1OStXrtS5c+e0adMmtW7dWpLUsWNHjRs3TuvXr9eQIUPKdBwAAGZitVq1NWK1Tuzf\nK/cGDdT/yWfUoHETo8sCYIAyL4n505/+pNtvv12LFi3S119/LW9vbz311FOSpFWrVmnNmjXq1KlT\nqQN7dna2Bg0apIULFyo0NFRNmpTuxSgyMlL+/v62EC5J3bt3l4+PjyIjI8t8HAAAZnIu7pRO7N8r\nSUq7fFkHvvnK4IoAGKXMM+wNGzbUp59+ql27dqmgoEDdu3eXi4uLJCk4OFhdunRRYGCgateuXar+\nsrOzlZaWpnfeeUchISHq1avXdc9JTk5WfHy8goOD7dr8/Py0ffv2Mh0HAIDZ1PrDks3aLOEEaqwy\nB/bhw4erW7duevbZZ+3aunbtWuYC3N3d9dVXX6lWrdKXUnj/9+Jm4728vJSamqrU1NRSH1e3bt0y\n1w0AQGXy8m6hgJB+it69U/W9Gsu/T4jRJQEwSJkDe3R0tDp06FBhBTg6OsrRsWwrc9LT0yVJrq6u\ndm3Ozs6SpIyMjFIfd63AHh0draysrDLVd7WcnBypjNeHmiEnJ0cHDhww9OczNlEco8dmYQ2MT+nu\nwCDdHRhkdBmmYvT4ZGyiJBUxNu++++5i95c5sHt7e9vuEmMUq9V63WMcHBxKfdy1+Pn5lbqu4mzd\nulWZeXk31AduTk5OTiX+w6wKjM3f/XLsqC6fT1KruzqobgNPo8sxnNFjU2J8omRGj0/GJkpSmWOz\nzIH9jTfe0NNPP63nnntOQUFB8vb2ts1W/1G7du1uuMDiuLldeVJmdna2XVvhPnd391IfB6DmOrZn\nt7Z9GiFJitrytYZNnyVXXhcAACZS5sD+2GOPycHBQV9++aW++uran1g/duxYuQu7lmbNmkmSzp8/\nb9eWlJQkDw8Pubm5lfo4VI28nBw5WCyyWCxGlwLY/HL899epzNRUXUw4I++2vtc4AwCAqlXmwD5w\n4EDDH97g4eEhb29vRUdH27UdPXpU7du3L9NxqHwHt27R7siNqlW7toLHjNOtd97YUiOgojRr3Uax\nhw9Jkpzd3ORZjoe+AQBQmcoc2OfPn18ZdZRZUFCQVq1apdjYWNs91nft2qW4uDhNmDChzMeh8uRm\nZ2t35EbJalVeTo52bVpPYIdp3HX/g3J1r6vfziepdcdOcqvrYXRJAAAUUebAfrX09HT99NNPSk5O\n1kMPPaTk5GTVq1evomqziY+PV1RUlLp06aIWLVpIkiZOnKgNGzZo7NixGj9+vLKzs7Vs2TL5+fkp\nNDTUdm5pj0PlcbQ4qlatWsrLzZUk1XZ2MbgioKg2nTobXQIAACUq132JLly4oKlTpyogIEAjRozQ\nM888I0las2aNHn74Ye3fv79Ci9y3b59mzJihffv22fZ5enrq448/Vrt27RQeHq4PP/xQgYGBWrZs\nmZyuerhEaY9D5bHUqq2HR49Vfa/G8vJuoZ5DhhtdEgAAQLVR5hn2S5cuaejQoTpz5oy6dOmi7Oxs\nHT16VNKV+50nJCRo4sSJ+uSTT+TrW/YPbm3dutVuX1hYmMLCwuz2t2rVSu+///51+yztcag8t95x\npxwcrsyuN/y/DwMDAADg+so8wx4eHq6zZ89q6dKlWrNmjXr27GlrGzt2rD744APl5eVp6dKlFVoo\nqrfNK5bp8+Xva8OShdr35WajywEAAKg2yhzYt27dqocffrhIUL9aQECAgoKCdOjQoRsuDjeH7MwM\n/Xz09zv1nNi/7xpHAwAA4GplDuyXL1+2ffCzJE2aNNGlS5fKXRRuLk7OLqrr+fvTIxs1a25gNQAA\nANVLmdewN23a1LZmvSRHjhxR06ZNy10Ubi4Ojo4Kffp/dOi/W1Xb2Vl3Bz5sdEkAAADVRpln2IOD\ng7V792598sknxbavWLFCBw4cUGBg4A0Xh5uHR8OGenDwY+rWb4CcXFyNLgcAAKDaKPMM+1NPPaXt\n27frlVde0erVq1VQUCBJmjlzpqKjoxUTE6OWLVvqqaeeqvBiAQCoSb77978UvXun6nk1Vt8Jk4os\nLwRQc5R5ht3d3V0REREaNmyYzpw5o9jYWFmtVq1fv14///yzQkNDFRERIQ8PnhYIAEB5nTsdpyM7\ntis/L0+XziZo31fcYQuoqcr1pFN3d3fNmTNHs2fPVlxcnFJSUuTm5qZWrVrxMCIAACqAg4PDNbcB\n1BxlnmF/9dVXdfjwYUmSxWJRmzZt1KVLF7Vr146wDgBABWly623q1LO3ajs7y6tFS90T/IjRJQEw\nSJln2NesWaOIiAh5e3urf//+6t+/v3x8fCqjNgAAarTu/UPVvX+o0WUAMFiZZ9g//fRTjRo1StnZ\n2VqyZIlCQkI0ePBgffjhh7pw4UJl1AgAAADUWGUO7B07dtT//u//avv27Vq1apWGDBmis2fPat68\neerRo4cmTJig9evXKz09vTLqBQAAAGqUMgf2Qg4ODvL399crr7yiHTt2aPny5QoLC9OJEyc0a9Ys\n3X///RVZJwAAAFAjlTuwX62goEDZ2dmyWq2SJKvVKovFUhFd4yaSn5dnu28/AAAASqdct3WUpPz8\nfH333XfavHmztmzZorS0NFksFj3wwAMaMGCAevfuXZF1opo7vH2bdm3aoFq1ayv48fFq2e4Oo0sC\nAACoFsoc2Hfu3KnNmzfr66+/VkpKiqxWqzp16qQBAwYoJCRE9evXr4w6q7Xs9HTtXRthdBmGyc/P\n18G9eyVJudnZ+uajlWrfqZPBVRkrOz1drvXqGV0GAACoBsoc2CdMmCBJuu222zRmzBgNGDBALVq0\nqPDCbhb1CGUqcHSUo6OjbTlMLYtFrrXK/cudm4JrvXqMDQAAUCplTk2jRo3SgAED1KFDh8qo56Yz\nadIko0swhV27dundd9+VxWLR66+/rlatWhldEgAAQLVQ5sA+e/bsyqgDN7nu3btr586dkkRYBwAA\nKIPrBvYpU6YoJCREISEhtu3ScHBw0MKFC2+sOgAAAKCGu25g/+abb9SuXbsi26Xh4OBQ/qoAAIB2\nbvi3ond9p/qNG+uR8ZNUt0EDo0sCYIDrBvYtW7bIw8OjyDYAAKhc507H6fD2bZKkC2fOaN+Xm9Vr\n2AiDqwJghOsG9ubNmxfZvuWWW3Ts2DGdP39eaWlpcnNzU4sWLdSmTRtm1QEAAIAKVuoPncbHx2vJ\nkiX68ssvlZmZadfu4eGhRx55RE8++aRuueWWCi0SAICapultPurYo6eid+9Ufa/Guif4EaNLAmCQ\nUgX27du3a+rUqcrIyJCzs7M6deqkJk2ayMnJSenp6Tpz5oxiYmL0ySef6D//+Y/efvttPfjgg5Vd\nOwAAN7X7QgfpvtBBRpcBwGDXDeynTp3Sc889p/z8fL3wwgsaNWqUXFxc7I5LTk7Wp59+qiVLlui5\n557Txo0beaASAAAAcIMcr3fAypUrlZ2drcWLF+uJJ54oNqxLV57oOWnSJC1dulSZmZlatWpVhRcL\nAAAA1DTXDex79uyRv79/qZe4dOvWTV27dtX3339/w8UBAAAANd11A3tSUlKR+7CXxp133qlff/21\n3EUBAAAAuOK6gT0rK0vu7u5l6tTd3V1ZWVnlLgoAAADAFdcN7Fartcz3V3d0vG63AAAAAEqBZA0A\nAACYWKnuw378+HGtX7++1J0eO3as3AUBAAAA+F2pAvuWLVu0ZcuWUndanmU0AAAAAOxdN7BPmTKl\nKuoAAAAAUAwCOwAAAGBifOgUAAAAMDECOwAAAGBiBHYANd7p6B916L9blXLxotGlAABgp1R3iQFu\n1MmTJ/Xjjz/KYrHo4sWLatiwodElAZKko7t36b9rP5EkHdy6RcNmzJSre12DqwIA4HfMsKPS5eXl\n6eWXX9bly5d14cIFvfvuu0aXBNjE/3Tc9n1mWqouJCQYWA0AAPYI7Kh02dnZSk1NtW2fP3/ewGqA\noprf3tb2vUudOmp4SzMDqwEAwB5LYlDp6tSpoz59+uiLL76QJA0aNMjgioDfte9+v9zc6+q380lq\n3aGT3OqyHAYAYC4EdlSJZ555RklJSbJYLAoODja6HKCIVh06Gl0CAAAlIrCjytSpU8foEgAAAKod\n1rADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYAAADAxAjsAAAAgIkR2AEAAAAT\nI7ADAGBSebm5OnsqVqmXLxtdCgAD8aRTAABMKC8nR/9eHK7z8b/IUqu2+j4xSd5tfY0uC4ABmGEH\nAMCEzp2O0/n4XyRJ+Xm5Ovr9boMrAmAUAjsAACZUt4GnHC0W23a9Ro0MrAaAkVgSAwCACdXz8lKf\nseN1bM8e1W/cWF2Dgo0uCYBBCOwAAJjUbX536Ta/u4wuA4DBTBHY4+Pj9cYbb2jv3r2SpIceekgz\nZ86Up6dnscf/+uuv6t279zX7XLVqlQICAiRJjz76qH744Qe7Y4KDgxUeHn6D1QMAAACVx/DAfvny\nZT3++OPKycnRE088ofz8fC1fvlwnTpzQ2rVr5eTkZHeOp6en3nzzTbv92dnZeu2119SwYUO1a9dO\nkmS1WhUbG6vAwEAFBQUVOb558+aVc1EAAABABTE8sK9cuVLnzp3Tpk2b1Lp1a0lSx44dNW7cOK1f\nv15DhgyxO8fNzU2hoaF2++fOnau8vDy99dZbqlevnqQrs/EZGRnq3bt3secAAAAAZmb4XWIiIyPl\n7+9vC+uS1L17d/n4+CgyMrLU/Zw4cUIff/yxBg0apK5du9r2x8TESFKR/gEAAIDqwtDAnpycrPj4\nePn5+dm1+fn5KTo6utR9vfPOO3JxcdHzzz9fZP/Jkycl/R7YMzIybqBiAAAAoGoZGtgTExMlSU2a\nNLFr8/LyUmpqqlJTU6/bz/Hjx7Vt2zYNGzZMjRs3LtJ28uRJ1alTR/PmzVPnzp3VuXNnBQYGlmn2\nHsDNLz8/3+gSAAAolqFr2NPT0yVJrq6udm3Ozs6SrsyI161b95r9REREyGKxaNSoUXZtMTExSk9P\nV2pqqt58802lpKRo1apVmjZtmnJzczVw4MAKuBIA1VXy+fPa9I8lSrl0SXf4B6jn0BFGlwQAQBGG\nBnar1XrdYxwcHK7ZnpWVpY0bN6pXr17F3vVlyJAhKigo0MiRI237+vbtq379+mnBggXq37+/LFc9\nSe6PoqOjlZWVdd06cX05OTmSpAMHDhhcCaT/+/twNPxjLIbb//WXSrl4UZJ0bM/3aud/r27xaWVw\nVcbKyckx/N8p4xMlMXp8MjZRkooYm3fffXex+w0N7G5ubpKu3I7xjwr3ubu7X7OPPXv2KCMjQ336\n9Cm2ffjw4Xb7XFxcFBoaqkWLFikmJka+vr4l9l/c+nqUz9atWyWVPBhRtbZu3arMvDyjyzCcpVat\na27XRE5OTob/O2V8oiRGj0/GJkpSmWPT0HemZs2aSZLOnz9v15aUlCQPDw9bqC/J9u3b5eTkpIce\neqhMP7vwoUx8CBWo2fz7hOi380n6LSlJft3vU+MWLY0uCQCAIgwN7B4eHvL29i72bjBHjx5V+/bt\nr9tHVFSU2rdvX+xMfGJiosaPH69HHnlEU6ZMKdIWFxcnSfL29i5n9QBuBm4eHho4+VmjywAAoESG\nL8IKCgrS7t27FRsba9u3a9cuxcXFKSQk5Jrn5ubmKiYmRnfeeWex7U2aNFFKSorWrl2rtLQ02/6E\nhAStW7dOAQEB8vLyqpgLAQAAACqB4Ys1J06cqA0bNmjs2LEaP368srOztWzZMvn5+dmeTBofH6+o\nqCh16dJFLVq0sJ179uxZ5ebm6pZbbimx/zlz5mjy5MkaNmyYHnvsMaWnp2v16tWqVauW5syZU+nX\nBwAAANwIw2fYPT099fHHH6tdu3YKDw/Xhx9+qMDAQC1btkxOTk6SpH379mnGjBnat29fkXN/++03\nSdf+YGpgYKAWL14sV1dXvfXWW1qxYoU6deqkiIgInn4KAAAA0zN8hl2SWrVqpffff7/E9rCwMIWF\nhdnt79Chg06cOHHd/gMDAxUYGHhDNQI3o+z0dO1dG2F0GYbLy86W1WpVbRcXo0sxXHZ6ulzr1TO6\nDADAVUwR2HHzy83N1fnz51WLW+aZRj1CmaQrz3I4Fh2t7Oxs3XLLLWrTpo3RJRnKtV49xgYAmAzp\nCVXi9ddf1/HjxyVJH330kUaPHm1wRZg0aZLRJZjC3/72N9tzH86ePaupU6eqXbt2BlcFwMz47eQV\nef/32lnr/55OX5NV9m8nCeyodGlpaTp48KBte8eOHQR2mIbjH55Y+MdtALgav4H6XXJ6uiTJtU4d\ngysxXmX/dpLAjkrn5uampk2b6ty5c5LEh31hKiNGjND333+vzMxMDRw4UG3btjW6JAAmxm8nf7dg\nwQJJ0vTp0w2u5ObHVBIqnaOjo+bOnavmzZurZcuWeu6554wuCbBp2LChOnXqpG7dumnMmDFGlwMA\ngB1m2FElvLy81KpVK0mSC3fiAAAAKDVm2AEAAAATY4YdAGBK3InjCu7E8TueE4CaisAOADAd7sTx\nO+7E8TueE4CaisAOADAd7sTxO+7EAYA17AAAAICJEdgBAAAAEyOwAwAAACZGYAcAAABMjMAOoEa7\nfPmyDh8+rO+//14REdxCEABgPgR2ADXa6tWrlZKSotzcXEVEROjkyZNGlwQAQBEEdgA1Wm5u7jW3\nAQAwGoEdQI02dOhQubi4SJKCgoJ05513GlwRAABF8eAkADVas2bNdM8996igoEBTpkwxuhwAAOww\nww4AkhwdeTkEAJgT71CoVDk5OUaXAAAAUK2xJAaVIjc3V/PmzdP+/ft166236rXXXjO6JAAAgGqJ\nGXZUit27d2v//v2SpJ9//lkbN240uCIAAIDqiRl2VAonJ6ci2/n5+Tp16pQsFouysrJsd+UAAADA\ntTHDjkoREBCgvn37ytPTUwEBAdq9e7fOnDmjX375RQsXLjS6PAAAgGqDGXZUCgcHBz355JN68skn\nlZaWphEjRtjaeJIkAABA6THDjkrn7u6ujh072rbvu+8+A6sBAACoXgjsqBIvvfSS2rVrJz8/Pz3+\n+ONGlwMAAFBtsCQGVaJ27dry8vIyugwAAIBqhxl2AAAAwMQI7AAAAICJEdgBAAAAE2MNOwAAJpWQ\nkKD4+Hi5uroaXQoAAzHDDgCACf3222+aMWOGTp8+rWPHjmnz5s1GlwTAIAR2AABM6PTp00pJSbFt\nHzlyxMBqABiJwA4AgAn5+PioXr16tu1OnToZWA0AIxHYAQAwoXr16mnBggXy8fHRnXfeqeDgYKNL\nAmzS09N16tQpnTx5UmfPnjW6nJsegR0AAJNq2rSpvL291bBhQ6NLAYp49913debMGZ07d04vvvii\nCgoKjC7ppkZgBwAAQJn8/PPPtu+TkpKUkZFhYDU3PwI7AAAAyqR379627wMCAuTu7m5gNTc/7sMO\nAACAMhk6dKh++OEH5efna+bMmUaXc9MjsKNKHDx4UAcPHpTFYtGZM2fUvHlzo0sCAAA3oPAuRhaL\nxeBKbn4siUGly83N1fz585WWlqbk5GT97W9/M7okoIiUlBQlJibqt99+M7oUAADsENhR6XJzc5WZ\nmWnbTk1NNbAaoKhvv/1Whw8f1k8//aQXXnhBaWlpRpcEAEARBHZUOjc3Nw0bNkyS5ODgoNGjRxtc\nEfC73bt3275PSkpSbGysgdUAAGCPNeyoEiNGjFBcXJwcHR3VvXt3o8sBbNq2baudO3dKklxdXeXt\n7W1wRQAAFEVgR5VxcnIyugTAzsCBA7Vjxw5lZmbqhRde4AE1AADTIbADqNEcHBzk5OSkvLw81alT\nx+hyAACwwxp2ADXaF198oaNHj+r06dOaPn26kpOTjS4JAIAiCOwAarTDhw/bvk9OTlZcXJyB1QAA\nYI/ADqBG69ixo+37evXqycfHx8BqAACwR2AHUKP16dNHd955p3x8fLRgwQLbk/sAADALPnQKoMYr\nvDNM06ZNDa4EAAB7BHYAAEwqMjJSBw4ckKurq9LS0uTu7m50SQAMwJIYAABMKC4uTu+9954yMjJ0\n8eJFrV692uiSABiEwA4AgAmlp6cX2U5LSzOoEgBGI7ADAGBCd9xxh+69915JUu3atRUWFmZwRQCM\nQmAHUOOlpqYqKSlJKSkpRpcC2FgsFv3lL39RQECA/P39ueUoUIMR2AHUaDt37tShQ4d04sQJvfDC\nC3bLEACjOTk5ydGRt2ugJuMVAECN9t1339m+P3funGJiYgysBgAAe6YI7PHx8ZoyZYr8/f3l7++v\nGTNm6NKlS9c979FHH5Wvr6/d17PPPlsh/QO4+bVp08b2vYuLi5o3b25gNQAA2DP8PuyXL1/W448/\nrpycHD3xxBPKz8/X8uXLdeLECa1du1ZOTk7Fnme1WhUbG6vAwEAFBQUVabv6Dbe8/QOoGQYNGqTv\nvvtOmZmZmjZtmho1amR0SQAAFGF4YF+5cqXOnTunTZs2qXXr1pKkjh07aty4cVq/fr2GDBlS7Hm/\n/vqrMjIy1Lt3b4WGhlZ4/wBqBkdHRzVr1kyS1LZtW4OrAQDAnuFLYiIjI+Xv728L05LUvXt3+fj4\nKDIyssTzCteZXn1eRfYPAAAAmIGhgT05OVnx8fHy8/Oza/Pz81N0dHSJ5548eVLS74E9IyOjQvtH\nxcrIyFBCQoISExOVn59vdDkAAADVhqGBPTExUZLUpEkTuzYvLy+lpqYqNTW12HNPnjypOnXqaN68\neercubM6d+6swMDAIrPmN9I/Ko7VatWLL76o2NhY/fTTT3rvvfeMLgkAAKDaMHQNe+H9jl1dXe3a\nnJ2dJV2Zma1bt65de0xMjNLT05Wamqo333xTKSkpWrVqlaZNm6bc3FwNHDjwhvovFB0draysrLJf\nHGwyMzNtvxGRpD179iggIMDAioCicnJyJEkHDhwwuBLAHuMTZsXYrHh33313sfsNDexWq/W6xzg4\nOBS7f8iQISooKNDIkSNt+/r27at+/fppwYIF6t+//w31X6i45TQoG6vVKh8fH8XFxUmSunbtWuKA\nBIywdetWSSW/UAJGYnzCrBibVcfQJTFubm6SpOzsbLu2wn3u7u7Fnjt8+PAiYV26cg/l0NBQXbhw\nQTExMTfUPyqOg4OD5s6dKx8fH7Vp00bPPPOM0SUBAABUG4bOsBfeSu38+fN2bUlJSfLw8LCF7tLy\n9PSUdGWpS+EHUiuyf5SPu7u7vL29JUkWi8XgagAAAKoPQ2fYPTw85O3tXezdWo4ePar27dsXe15i\nYqL69u2rRYsW2bUVLrvw9vYud/8AAACAWRh+H/agoCDt3r1bsbGxtn27du1SXFycQkJCij2nSZMm\nSklJ0dq1a5WWlmbbn5CQoHXr1ikgIEBeXl7l7h8AAAAwC8OfdDpx4kRt2LBBY8eO1fjx45Wdna1l\ny5bJz8/P9gTT+Ph4RUVFqUuXLmrRooUkac6cOZo8ebKGDRumxx57TOnp6Vq9erVq1aqlOXPmlKl/\nAAAAwKwMn2H39PTUxx9/rHbt2ik8PFwffvihAgMDtWzZMjk5OUmS9u3bpxkzZmjfvn228wIDA7V4\n8WK5urrqrbfe0ooVK9SpUydFREQUeappafoHAAAAzMrwGXZJatWqld5///0S28PCwhQWFma3PzAw\nUIGBgTfcPwAAAGBWhs+wAwAAACiZKWbYAQCAvfPnzyshIaHYJ3YDqDmYYQcAwIRSUlI0ffp0xcbG\n6scff9SWLVuMLgmAQQjsAACY0KlTp3Tp0iXb9v79+w2sBoCRCOwAAJjQrbfeKnd3d9u2n5+fgdUA\nMBKBHQAAE2rQoIHeeOMNtWzZUr6+vurXr5/RJQEwCB86BQDApFq0aKFbb73V6DIAGIwZdgAAAMDE\nCOwAAACAiRHYAQAAABMjsAMAAAAmRmAHAAAATIzADgAAAJgYgR0AAAAwMQI7AAAAYGIEdgAAAMDE\nCOwAAACAiRHYAQAAABMjsAMAAAAmRmAHAAAATIzADgAAAJgYgR0AAAAwMQI7AAAAYGIEdgAAAMDE\nCOwAAACAiRHYAQAAABMjsAMAAAAmRmAHAAAATIzADgAAAJgYgR0AAAAwMQI7AAAAYGK1jC4ANUNq\naqri4+NlsViUl5enWrUYegAAAKXBDDsqndVq1ezZs3X69GnFxsZq8eLFRpcEAABQbRDYUenS09MV\nFxdn246OjjawGgAAgOqFwI5K5+7urrZt29q2u3TpYmA1AAAA1QuBHVXi1VdfVevWreXr66tJkyYZ\nXQ4AAEC1wSf/UCXc3NzUrFkzSZKjI/9PBAAAKC2SEwAAAGBiBHYAAADAxAjsAAAAgIkR2AEAAAAT\n40OnqBJRUVGKioqSxWLRr7/+Km9vb6NLAiRdebBXQkKCMjMzdfLkSd1+++1GlwQAQBHMsKPS5ebm\nav78+UpPT1dKSorCw8ONLgmwWbdunWJjY5WQkKDZs2frwoULRpcEAEARBHZUury8PGVlZdm2U1NT\nDawGKComJsb2fWZmps6cOWNgNQAA2COwo9K5urpqxIgRkq7cg33MmDEGVwT87r777rN936RJjN1J\n5QAAIABJREFUE7Vp08bAagAAsMcadlSJYcOG6dSpU3J0dFS3bt2MLgewuf/++/XVV18pMzNTL774\nourUqWN0SQAAFEFgR5WpXbu20SUAxapbt67q1q0rDw8Po0sBAMAOS2IAAAAAEyOwAwAAACbGkhhU\niR9//FGHDx+WxWLRuXPn1LRpU6NLAgAAqBaYYUely8vL09y5c5WSkqLLly/r3XffNbokAACAaoPA\njkqXk5Oj9PR023ZycrKB1QAAAFQvBHZUOjc3Nw0aNEiS5ODgoGHDhhlcEQAAQPXBGnZUiXHjxunM\nmTNydHRUjx49jC4HAACg2iCwo8o4OzsbXQIAAEC1w5IYAAAAwMQI7AAAAICJEdgBAAAAEyOwAwAA\nACZmig+dxsfH64033tDevXslSQ899JBmzpwpT0/Pa563Y8cOLV26VNHR0XJ0dFTHjh31/PPPq1On\nTkWOe/TRR/XDDz/YnR8cHKzw8PCKuxAAAACgghke2C9fvqzHH39cOTk5euKJJ5Sfn6/ly5frxIkT\nWrt2rZycnIo9b+/evZo4caJuv/12TZ06VXl5eVqzZo1GjRqlNWvWqEOHDpIkq9Wq2NhYBQYGKigo\nqEgfzZs3r/TrAwAAAG6E4YF95cqVOnfunDZt2qTWrVtLkjp27Khx48Zp/fr1GjJkSLHn/b//9/90\nyy236LPPPpOrq6skaeDAgQoJCdE777yjFStWSJJ+/fVXZWRkqHfv3goNDa2aiwIAAAAqiOFr2CMj\nI+Xv728L65LUvXt3+fj4KDIysthzkpOTdfz4cfXp08cW1iWpUaNGuueee3Tw4EHbvpiYGEkq0j8A\nAABQXRg6w56cnKz4+HgFBwfbtfn5+Wn79u3Fnufu7q4vvviiSFgvdPnyZVksFtv2yZMnJf0e2DMy\nMuTm5lYR5QMAAACVztAZ9sTERElSkyZN7Nq8vLyUmpqq1NRUuzaLxaLbbrvN7rzjx48rKipKnTt3\ntu07efKk6tSpo3nz5qlz587q3LmzAgMDS5y9BwAAAMzE0Bn29PR0SSp2przwMfYZGRmqW7duqfr6\n85//LEmaNGmSbX9MTIzS09OVmpqqN998UykpKVq1apWmTZum3NxcDRw4sCIuBQAAAKgUhgZ2q9V6\n3WMcHByue0xmZqaefvppHT9+XE8++aT8/f1tbUOGDFFBQYFGjhxp29e3b1/169dPCxYsUP/+/Yss\nofmj6OhoZWVlXbcGXF9OTo4k6cCBAwZXAhTF2ISZMT5hVozNinf33XcXu9/QwF64ljw7O9uurXCf\nu7v7NftISUnRk08+qaioKA0ePFhTp04t0j58+HC7c1xcXBQaGqpFixYpJiZGvr6+Jfbv5+d33etA\n6WzdulVSyYMRMApjE2bG+IRZMTarjqFr2Js1ayZJOn/+vF1bUlKSPDw8rvkB0YsXL2rMmDGKiorS\n0KFDNXfu3FLNyEuyPZQpIyOjHJUDAAAAVcPQwO7h4SFvb29FR0fbtR09elTt27cv8dy0tDRNmDBB\nx44d09ixY/Xqq6/ahfXExET17dtXixYtsjs/Li5OkuTt7X2DVwEAAABUHsPvwx4UFKTdu3crNjbW\ntm/Xrl2Ki4tTSEhIiee9+uqrOnbsmMaMGaNZs2YVe0yTJk2UkpKitWvXKi0tzbY/ISFB69atU0BA\ngLy8vCruYgAAAIAKZviTTidOnKgNGzZo7NixGj9+vLKzs7Vs2TL5+fnZnkwaHx+vqKgodenSRS1a\ntFBsbKw2bNggDw8P3XHHHdqwYYNdv4XnzpkzR5MnT9awYcP02GOPKT09XatXr1atWrU0Z86cKr1W\nAAAAoKwMD+yenp76+OOPNW/ePIWHh8vFxUWBgYGaMWOGnJycJEn79u3TrFmzNG/ePLVo0UJ79+6V\ndOUDpyXNrhcG9sDAQC1evFjvvfee3nrrLbm4uMjf31/Tpk3j6acAAAAwPcMDuyS1atVK77//font\nYWFhCgsLs20PHz682Lu/lCQwMFCBgYE3VCMAAABgBMPXsAMAAAAoGYEdAAAAMDECOwAAAGBiBHYA\nAADAxAjsAAAAgIkR2AEAAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYA\nAADAxAjsAAAAgIkR2AEAAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYA\nAADAxAjsAAAAgIkR2AEAAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYA\nAADAxAjsAAAAgIkR2AEAAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYA\nAADAxAjsAAAAgIkR2AEAAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYA\nAADAxAjsAAAAgIkR2AEAAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYA\nAADAxAjsAAAAgIkR2AEAAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECOwAAAGBiBHYA\nAADAxEwR2OPj4zVlyhT5+/vL399fM2bM0KVLlyrsvPL2DwAAABitltEFXL58WY8//rhycnL0xBNP\nKD8/X8uXL9eJEye0du1aOTk53dB55e0fAAAAMAPDA/vKlSt17tw5bdq0Sa1bt5YkdezYUePGjdP6\n9es1ZMiQGzqvvP0DAAAAZmD4kpjIyEj5+/vbwrQkde/eXT4+PoqMjLzh88rbPwAAAGAGhs6wJycn\nKz4+XsHBwXZtfn5+2r59+w2dV97+ceM2b96sL774Qs2bN9fkyZN18uRJHTx4UBaLRQkJCZKkJUuW\nKDMzU2PGjFHHjh0Nrhg1VXp6uo4dO6bMzExt3rxZjzzyiNEloYYqKCjQihUrdPjwYdtvgr/88ktF\nRUXJ1dVV6enpqlOnjtFlooY6dOiQPvroI7m6uuqZZ56RJB05ckT5+fm2MYvKY2hgT0xMlCQ1adLE\nrs3Ly0upqalKTU1V3bp1y3Veefu/2WzevFk//vhjlf289PR0RUVFSZLi4uIUGxurpKQk5efnS5Jm\nzJghSUpJSZEkvfzyy7r33nvl6Fg1v/Bp3749ocxEqnp8/lFsbKwuXLggSVq6dKn27NljaChifJpH\nVY/NxMRE/fTTT5Kk06dP69ChQ/r5558lXXld/dOf/lTkt8VVjbFpLlU5PgsKCvT999+b5n28ODf7\n+DQ0sKenp0uSXF1d7dqcnZ0lSRkZGXaBurTnlbf/q0VHRysrK+u612JmiYmJysnJqbKfl5mZWWQ7\nOzvb9o9ckl0t+fn5ys7OlsViqZL6EhMTdeDAgSr5Wbi+qh6ff5SdnV1kOzMzU7Vr1zaoGsanmVT1\n2Pzje01xr6VG/lthbJpLVY7P/Px8U72PF+dmGZ933313sfsNDexWq/W6xzg4OJT7vPL2fzU/P7/r\n9mF2Jf3lV5b8/HzNmzdPe/fulYeHh1566SXt2rVLn332mWrVqqVnn31WkvT2228rLy9PQ4cO1ciR\nI6u0RphHVY/PPzp16pReeuklpaSkyN/fX7NmzTL0TQfmUdVjMyUlRbNmzVJ8fLxatmyp1157TYsX\nL7a9lr744otq1apVldYE86rq8fnxxx/zPm4gQwO7m5ubJPsZrqv3ubu7l/u88vaPG2OxWPS///u/\nunTpktzd3eXs7KxWrVqpb9++cnJysi036Ny5s3JyctSgQQODK0ZN1qpVKy1fvlxpaWny9PS87n/i\ngcri4eGh8PBwXbp0SZ6ensW+lgJGGTVqFO/jBjI0sDdr1kySdP78ebu2pKQkeXh42EJ3ec4rb/+4\ncQ4ODmrYsGGRfX/8B12nTh0+QAVTcHZ2JgzBFCwWi7y8vGzbxb2WAkbhfdw4ht7W0cPDQ97e3oqO\njrZrO3r0qNq3b39D55W3fwAAAMAsDL8Pe1BQkHbv3q3Y2Fjbvl27dikuLk4hISE3fF55+wcAAADM\nwMFamk9mVqJLly6pX79+slgsGj9+vLKzs7Vs2TK1bNlSn3zyiZycnBQfH6+oqCh16dJFLVq0KPV5\nZTkOAAAAMCPDA7t05S4N8+bN0/79++Xi4qIePXpoxowZ8vT0lCStW7dOs2bN0rx58xQWFlbq88p6\nHAAAAGA2pgjsAAAAAIpn+Bp2AAAAACUjsAMAAAAmRmAHAAAATIzADgAAAJgYgR0AAAAwMQI7AAAA\nYGIEdgAAAMDECOwAAACAiRHYAQAAABMjsAMAAAAmRmAHAAAATIzADgAAAJgYgR0AAAAwMQI7AAAA\nYGIEdgAAAMDECOwAAACAiRHYAQAAABMjsAMAAAAmRmAHAAAATIzADgAAAJgYgR0AAAAwMQI7AAAA\nYGIEdgAAAMDEahldAGqWAwcOGF0CAACoQHfffbfRJdz0HKxWq9XoIgAAAAAUjyUxAAAAgIkR2AEA\nAAATI7ADAAAAJkZgBwAAAEyMwA4AAACYGIEdAAAAMDECO8qkoKBAn3/+uSZMmKAePXqoffv2uv/+\n+/Xcc8/p4MGD5e63V69eGj16dIUdh5ohJydH//jHPzRgwAB16tRJXbp0UVhYmN5//33l5OTYjps5\nc6Z8fX1L3AbKo3AcXf3Vvn179erVS6+99pqSk5ONLhGwUzhuV69eXWz7r7/+Kl9fXy1cuLCKK8O1\n8OAklFpqaqqmTp2qHTt2yN/fX6NHj1b9+vWVkJCg9evXa9iwYXrxxRc1atQoo0tFDZCXl6cJEybo\n0KFDGjhwoIYOHar8/Hzt379ff/3rX7V161Z9+OGHcnJy0tChQ9WtWzejS8ZNatasWWrQoIEkKTs7\nWzExMfr000/1ww8/KCIiQhaLxeAKAXvvvvuugoOD1ahRI6NLQSkQ2FFqc+bM0Xfffaf58+dr0KBB\nRdqefPJJPfXUU5o/f77uu+8++fj4GFQlaorNmzdr7969WrhwoYKCgmz7x4wZo2XLlmnBggX65z//\nqREjRqhz587q3LmzgdXiZhYYGChvb+8i+2677Ta98sor+vbbb9WzZ0+DKgNKlpKSonnz5umvf/2r\n0aWgFFgSg1I5cOCAIiMjFRoaahfWJcnZ2Vkvv/yycnNztW7dOgMqRE1TuATrvvvus2sbMWKEateu\nrUOHDlV1WYAkKSAgQJJ08uRJgysBiterVy/95z//0e7du40uBaVAYEepbNq0SZI0adKkEo+59dZb\ntXLlSj399NNF9u/fv19jx461zXKOGTNG+/btu+7P/PzzzxUaGqoOHTqoX79+2rJly41dBG4qderU\nkSR9+umndm1ubm6KiorSm2++Kenaa9Y///xz+fr66quvvrJrGz16tAIDA23b586d04wZM3Tvvffq\nrrvu0sCBA7Vx48Yi58ycOVN9+vTR6tWrdc899+iee+7Rt99+W+7rRPV07tw5SVLLli0lXRlLEyZM\n0DvvvKPOnTurW7duOnHihCTpxIkTeuaZZ9S1a1d16NBBQ4YM0TfffFOkv8Lzv/32W4WFhemuu+5S\njx49tHDhQhUUFEj6fe1xSV9Xr0mOiYnR5MmT1bVrV3Xs2FHDhg3Tjh07quKPBiYxe/Zsubq66uWX\nXy7ymZ/ilOZ9vFevXnrppZe0YcMG9e3bV3fddZeCgoKKXSt/8OBBjRs3ztbf+PHjdeTIkQq9vpsN\ngR2lsnfvXnl5eal169bXPK5bt25yc3OzbW/ZskWjR4/W2bNn9fTTT+vpp5/W2bNnNXbs2GsG8HXr\n1mnq1KlydXXV9OnTde+99+r555/XhQsXKuyaUL0NGDBAtWvX1htvvKF+/frp3Xff1Z49e2xvPE5O\nTqXqp1evXqpTp442b95cZH9SUpL279+vfv36SZISExP12GOPadeuXRo9erT+/Oc/q0GDBpo+fbqW\nLVtW5NyzZ89q6dKlmjJlioYMGaJOnTpVwBXDrFJSUnTp0iVdunRJiYmJ2rVrl15//XX5+fmpV69e\ntuOioqK0efNmTZ8+XYMGDVKbNm105MgRDR06VEeOHNG4ceM0bdo05ebmavLkyXZB56efftLzzz+v\ngIAAzZ49Wy1bttSiRYsUEREhSfL09NSbb75p99WiRQvVrl1bDzzwgKQr/0EYOnSoYmJi9OSTT2rq\n1KnKy8vTpEmT9Pnnn1fdHxwM1bx5cz3zzDM6ffq0/vGPf5R4XFnex3fs2KG5c+cqODhYs2bNkqur\nq1599VVt377ddszOnTs1evRopaam6rnnntPTTz+thIQEjRw5Uvv376+06632rEApdO7c2Tp48GC7\n/RkZGdaLFy8W+frtt9+sVqvVmpuba33wwQetPXr0sKamptrOSU5Otj7wwAPWBx54wJqTk2O1Wq3W\nnj17WkeNGmW1Wq3WvLw8a7du3ayDBw+2tVutVuu//vUva9u2bW3HAdu2bbN269bN2rZtW9tXp06d\nrNOmTbOeOnXKdtyf//xna9u2bUvcnjFjhrVTp07WzMxM274PP/zQ2rZtW2tMTIztHH9/f2tiYqLt\nmIKCAuu0adOs7du3t164cKFI35GRkZV23TCHwr/r4r46dOhgPXTokO3YUaNGWdu2bVtkn9VqtT72\n2GPWTp06Wc+ePWvbl5WVZR00aJC1Q4cO1osXLxY5f8uWLUWOu+eee6xDhw4tscb333/f2rZtW+vH\nH39cpJbAwEBrenq6bV9ubq51xIgR1u7du1uzs7PL/4cC07v69S8nJ8fat29f61133WU9ffq01Wq1\nWuPj461t27a1hoeHl/l93NfX13rs2DHbcUlJSVZfX1/rtGnTrFar1Zqfn2/t3bu3ddiwYda8vDzb\ncenp6daHH37YGhoaWunXX10xw45SsVqtslqtdvvDw8PVrVu3Il+Fa9yPHj2qc+fOaeTIkXJ3d7ed\n4+HhoVGjRikxMVE//vijXZ/R0dG6ePGiwsLCVLt2bdv+0NBQ1atXrxKuDtXVQw89pG3btumdd95R\naGiovLy8lJGRof/85z8KDQ3V3r17S9VP//79lZGRUWQW6PPPP5efn59at26tgoICffPNN+ratatq\n1aplm029fPmygoKClJOTo507dxbps2vXrhV6rTCvBQsWaMWKFVqxYoX+8Y9/aM6cOfL29tbIkSO1\na9cu23EuLi666667bNsXLlzQ4cOHFRoaqqZNm9r2Ozs7a8KECcrKyipyvqurqx566KEix/n4+JT4\nm8cdO3bo7bffVmhoqEaOHClJunz5svbu3asePXooKyvLNpZTUlL08MMP68KFC/rhhx8q6o8GJle7\ndm3bkphXX33Vrr2s7+M+Pj5q166dbdvLy0uNGjWyjdGjR48qPj5egYGBSk5Oto2/rKws9ezZU8eO\nHVNiYmIlXnH1xV1iUCqNGzcu9k1h6NChtl+zStL8+fOVlpYm6cp6SknF3jGmVatWkqSEhAS7u3ec\nOXNG0u9rPwtZLBbdeuutN3AVuBk5OzsrJCREISEhkq78h++DDz7Qf/7zH82ZM8duqUtxunXrpkaN\nGumLL75QcHCwEhISdOjQIc2YMUPSlZCTmpqqb775xm5tcaGzZ88W2W7YsOENXhmqiy5dutjdJeaR\nRx5RUFCQXnvtNdsYrF+/vhwdf58nK3ytK+41snD5YUJCgm3fH8+Xriz9KlzDfrXTp09r2rRpuv32\n24sEsfj4eEnSRx99pI8++qjY6/njWMbNrWvXrho0aJDWrVunyMhIdezY0dZW1vdxT09Pu+OuHqO/\n/PKLJNmWaxUnISFBTZo0uYErujkR2FEqnTt31r///W/9/PPPRULzbbfdpttuu822Xa9ePVtgL25G\nvlBh29Uz6IUcHBwkSVlZWXZtxb0xoebJyMjQe++9Jz8/vyK3dJQkPz8//fWvf1VKSoq+/fZbXb58\n+br9WSwWPfLII/rXv/6lrKwsbd68WQ4ODurbt68kKT8/X5IUHBysYcOGFdtHixYt7PpEzdWgQQMF\nBATo66+/tj1A6Y9j4lqvkYWvdVe/Rv4xrJckLS1NkydPloODgxYtWiQXFxdbW+FYHjlyZJEPVF+t\nTZs2pfo5uHlMnz5dW7du1bx584p8Jqes7+PXG6OF4/q5554r8bM9hf8RQFEsiUGpDBgwQJK0cuXK\nUp/TvHlzSdKpU6fs2uLi4iSpyK+BCxUGn59//rnIfqvVapuRQs3m7Oys5cuXlzhDKF0JHQ4ODkXC\nyrUMGDBAGRkZ2rlzpzZv3ix/f3/bLI+np6dcXV2Vl5en7t27F/m67bbblJGRIVdX1wq5Ntw8CsNJ\nSSGmvK+R12K1WjV9+nTFxsZqwYIFdv+RLPyZFovFbiw3btxYOTk5jOUayNPTUy+88ILOnz+vd999\n17a/osdoYX9ubm5248/d3V35+fmlfs2uaQjsKJXu3bsrJCREERERWrNmTbHHbNy4schaNj8/P3l5\neSkiIsI26y5dmf1Zs2aNvLy81L59e7t+7rzzTjVv3lwRERHKzMy07Y+MjCzVbClufhaLRSEhIdq7\nd682bNhg1/7bb7/pyy+/VPfu3UsdPjp06KBbb71Vn332mX744Qf179/f1larVi09+OCD2r59u44f\nP17kvPnz52vy5MmMTRRx4cIFff/997rjjjtUt27dYo8pfA3cuHGj7TaQkpSTk6MVK1bIycmp2OcM\nXMvf/vY3bd26VVOmTFGPHj3s2hs3bqz27dvr3//+d5G1wrm5ufrLX/6iZ599Vnl5eWX6mbg5PPro\no+rSpYu2bdtm21fe9/GStG/fXl5eXvroo4+Unp5epL/nn39es2bN4reTJWBJDErttddeU35+vl55\n5RX985//VGBgoLy8vJSYmKivvvpKJ06cUKNGjTRz5kxJV35NNnv2bE2dOlWDBw/Wo48+Kkn65z//\nqaSkJIWHhxc78+Tg4KAXX3xRkydP1tChQzV48GAlJiZq9erVql+/fpVeM8xr5syZOnLkiGbMmKGN\nGzfqgQcekLu7u3755RetW7dOubm5eumll8rUZ//+/bVo0SI5OTkpODi4SNsLL7ygPXv2aOTIkRo5\ncqSaNWum//73v9q2bZuGDh2q22+/vSIvD9XIN998owYNGki6MsN97tw5ffbZZ8rMzNTUqVOvee7s\n2bP1+OOP69FHH9Xw4cNVp04dbdy4UdHR0Zo9e7Y8PDxKXcd///tf/f3vf1fr1q3Vtm1bbdq0qcgy\nwkaNGum+++6z/czBgwdr+PDhql+/viIjI3X48GH96U9/sl0LahYHBwe9/PLLCgsLs/2nrbzv4yW5\nur+wsDA9+uijcnZ21tq1a5WQkKC33npLtWoRTYvDnwpKzd3dXeHh4dq2bZv+9a9/ae3atTp//rzc\n3d11xx136KWXXlJYWFiRGc0+ffqoXr16WrJkiRYvXqxatWqpY8eOmjt37jXvotGzZ0+99957Wrhw\nod5++201adJEc+fOLfYBDKiZPD09tW7dOq1cuVJbtmzR4sWLlZmZqcaNGysoKEhPPfWUGjduXKY+\nCwP7Qw89ZDcr2rJlS3322WcKDw/XZ599poyMDLVo0UKzZs3S6NGjK/LSUM3MmzfP9r3FYlG9evV0\n1113ae7cuerWrds1z+3cubMiIiIUHh6uDz74QAUFBWrXrp0WL15c4hrzkvzwww+yWq2KjY3V//zP\n/9i1+/v767777rP9zIULF2rFihXKy8uTj4+P5s+fX+yTrFFz+Pr6asyYMfrggw9s+8r7Pl6Swv6W\nLl2qJUuWyNHRUbfffruWLl2qnj17VuTl3FQcrNf6RAEAAAAAQ7GGHQAAADAxAjsAAABgYgR2AAAA\nwMQI7AAAAICJEdgBAAAAEyOwAwAAACZGYAcAAABMjMAOADXIwoUL5evrK19fXy1ZsuSax77++uu2\nY3/99dcKq2HlypXy9fXVunXrynX+6NGj5evrq5SUlAqrCQDMjMAOADXU119/XWKb1WrVV199VYXV\nAABKQmAHgBrIy8tLR48eLXHm/ODBg0pMTJSbm1sVVwYA+CMCOwDUQL1795YkffPNN8W2f/nll6pb\nt666du1alWUBAIpBYAeAGujee++Vh4dHictevvrqK/3/9u4mJKo1juP4V7vjxIxHYooQalWLphrD\niLBiYkrGU0JMtSgXhdC0E+kFhQpaBOqicldQUNBQA5UZqPSKWtRszF6oqZHEJDGyjZU11mxCW0in\n5h67i9vt3vHO77MZzjn/eeY8Z/Wbh/85p7S0FIfDYTuWSCSoqqqipKSEJUuWsHHjRs6fP8/4+Lit\ntqOjg4qKCoqLiwkEApw4cYKxsbFJf/Phw4dUV1fj9/vx+XwsX76cHTt20NXV9WuTFRGZ4v74r09A\nRET+fQ6Hg9LSUtra2hgeHmbWrFnWsXg8ztDQEOvXr6e5uTnte3fu3KG6uhqHw4Fpmng8HmKxGIcO\nHaKnp4e6ujqr9tKlSxw8eJCZM2cSCoVIpVKcPHkSwzBs59PR0cGuXbvweDwEg0Hcbjd9fX3cvXuX\n7u5umpubWbhw4e+7ICIiGUyBXUQkS5mmSUtLC52dnVRUVFj7b9y4QX5+Pn6/Py2wp1Ip9u/fj2EY\nNDU1MXfuXABqa2vZs2cPTU1NBINBAoEAHz9+5PDhwxQWFnLx4kUKCwsBqKysZPv27bZzaWxsxDAM\nWlpa0v48nDp1isbGRq5fv67ALiJZSy0xIiJZyu/343K5bG0x39ph8vLy0vbfunWLd+/esXPnTius\nA+Tm5lJTUwPA5cuXgYmV+GQySWVlpRXWAYqKiti0aVPauGNjY9TU1HDkyJG0sA5QUlICwNu3b39x\ntiIiU5dW2EVEspTT6WTNmjW0t7eTTCYxDINEIsGrV684cOCArf7Zs2fARA/7sWPHbMenTZvG8+fP\nAaxPn89nq1u6dCkXLlywtnNzcykrKwPg9evX9PX1MTg4yIsXL7h37x7AT/veRUSygQJNS5/3AAAC\noElEQVS7iEgWM02Ta9eucfv2bUKhEDdv3sTtdrN69WpbbTKZBODq1as/He/Dhw8A1kuN3G63rWbG\njBm2fb29vdTX19Pd3Q1M9NjPnz8fn8/HwMDApDe0iohkCwV2EZEsFggEmD59Ou3t7VZgX7t2ra0d\nBrCeyR6JRFi5cuVfjltQUAB8D/k/+vz5c9r26Ogo4XCYZDLJvn37WLVqFfPmzSMvL48nT55w5cqV\nvzs9EZH/BfWwi4hkMZfLhd/vJxaLEY/HGRgYoLy8fNLaBQsWAN9bY340MjJCQ0MDra2tACxevBiA\nR48e2WqfPn2att3V1cXw8DDbtm0jHA7j9XqtPwz9/f0AWmEXkaymwC4ikuVM0ySVStHQ0IDL5Zq0\nHQagrKyM/Px8Tp8+zcuXL9OOHT16lLNnzzI4OAhMrNx7PB7OnTuXVtvf3297VKTT6QTsN5YODQ1x\n/PhxAL58+fJrkxQRmcLUEiMikuW+vSDp8ePHbNiwwQrQf1ZQUEB9fT21tbVs3ryZYDDI7NmzuX//\nPvF4nKKiIsLhMDDRu15XV8fu3bvZsmUL69atAyYeGenxeKwed4Bly5YxZ84cWltbef/+PV6vlzdv\n3tDZ2YnT6SQnJ4eRkZHffyFERDKUVthFRLKcYRhWT/q3YP0z5eXlRKNRVqxYQSwWIxqNMjo6SlVV\nFZFIJO0m02AwSCQSYdGiRdaNrVu3bmXv3r1pY7pcLs6cOYNpmiQSCaLRKD09PYRCIdra2vB6vTx4\n8IBPnz7985MXEZkCcsbVGCgiIiIikrG0wi4iIiIiksEU2EVEREREMpgCu4iIiIhIBlNgFxERERHJ\nYArsIiIiIiIZTIFdRERERCSDKbCLiIiIiGQwBXYRERERkQymwC4iIiIiksG+Av9eb2aYlpWIAAAA\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110e67090>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "f, ax = plt.subplots(figsize=(12, 12))\n",
    "\n",
    "# Plot the orbital period with horizontal boxes\n",
    "sns.boxplot(x=data2013.Medal, y=diversity_2013,whis=np.inf, color=\"powderblue\")\n",
    "\n",
    "# Add in points to show each observation\n",
    "sns.swarmplot(x=data2013.Medal, y=diversity_2013,size=4, color=\".3\", linewidth=0)\n",
    "sns.despine(trim=True, left=True)\n",
    "\n",
    "plt.xticks(range(4),[\"Gold\", \"Silver\", \"Bronze\",\"None\"])\n",
    "plt.title(\"Teams of 2013\", size=20)\n",
    "plt.ylabel(\"Diversity\", size=20)\n",
    "plt.xlabel(\"Medal\", size=20)\n",
    "plt.tick_params(labelsize=18)\n",
    "plt.savefig(\"2013 diversity box plot.png\", dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "diversity_2014 = []\n",
    "for i in range(113):\n",
    "    diversity = 0\n",
    "    for j in range(1, 44):\n",
    "        if p_2014[i][j] > 0:\n",
    "            base = p_2014[i][j]\n",
    "            for k in range(j+1, 45):\n",
    "                if p_2014[i][k] > 0:\n",
    "                    diversity += distance_matrix[j][k] * p_2014[i][j] * p_2014[i][k]\n",
    "    diversity_2014.append(diversity)\n",
    "\n",
    "#print(diversity_2014)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FRSklJUVffPGFfHx8JEnJycnq2rWrGjVqpHnz5l3wvKSkJEVERGjq1Knq2bPntYwMAAAA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\nrkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120521210>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "f, ax = plt.subplots(figsize=(12, 12))\n",
    "\n",
    "# Plot the orbital period with horizontal boxes\n",
    "sns.boxplot(x=data2014.Medal, y=diversity_2014,whis=np.inf, color=\"powderblue\")\n",
    "\n",
    "# Add in points to show each observation\n",
    "sns.swarmplot(x=data2014.Medal, y=diversity_2014,size=4, color=\".3\", linewidth=0)\n",
    "sns.despine(trim=True, left=True)\n",
    "\n",
    "plt.xticks(range(4),[\"Gold\", \"Silver\", \"Bronze\",\"None\"])\n",
    "plt.title(\"Teams of 2014\", size=20)\n",
    "plt.ylabel(\"Diversity\", size=20)\n",
    "plt.xlabel(\"Medal\", size=20)\n",
    "plt.tick_params(labelsize=18)\n",
    "plt.savefig(\"2014 diversity box plot.png\", dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "diversity_2015 = []\n",
    "for i in range(153):\n",
    "    diversity = 0\n",
    "    for j in range(1, 44):\n",
    "        if p_2015[i][j] > 0:\n",
    "            base = p_2015[i][j]\n",
    "            for k in range(j+1, 45):\n",
    "                if p_2015[i][k] > 0:\n",
    "                    diversity += distance_matrix[j][k] * p_2015[i][j] * p_2015[i][k]\n",
    "    diversity_2015.append(diversity)\n",
    "\n",
    "#print(diversity_2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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SeXl5cjgccjgc8vPzMx0RlZjFYlGNGjV0+PBhSVLNmjWVl5cnu91uOBkAkyji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\nRERERDLgX/tLnRgCFtpqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120271610>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "f, ax = plt.subplots(figsize=(12, 12))\n",
    "\n",
    "# Plot the orbital period with horizontal boxes\n",
    "sns.boxplot(x=data2015.Medal, y=diversity_2015,whis=np.inf, color=\"powderblue\")\n",
    "\n",
    "# Add in points to show each observation\n",
    "sns.swarmplot(x=data2015.Medal, y=diversity_2015,size=4, color=\".3\", linewidth=0)\n",
    "sns.despine(trim=True, left=True)\n",
    "\n",
    "plt.xticks(range(4),[\"Gold\", \"Silver\", \"Bronze\",\"None\"])\n",
    "plt.title(\"Teams of 2015\", size=20)\n",
    "plt.ylabel(\"Diversity\", size=20)\n",
    "plt.xlabel(\"Medal\", size=20)\n",
    "plt.tick_params(labelsize=18)\n",
    "plt.savefig(\"2015 diversity box plot.png\", dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "metadata": {},
   "outputs": [
    {
     "data": {
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Rs9erSWL19ufccybym7fv16DRgwQBUrVlTfvn0lXa9r3bp103vvvafIyEhrG/Hx8Xr88cc1evRo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\nWFs855OUAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x120271b90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"whitegrid\")\n",
    "\n",
    "f, ax = plt.subplots(figsize=(40, 10))\n",
    "\n",
    "# Plot the orbital period with horizontal boxes\n",
    "sns.boxplot(x=data2014.Track, y=diversity_2014,whis=np.inf, palette=\"Set3\", width=0.3)\n",
    "\n",
    "# Add in points to show each observation\n",
    "sns.swarmplot(x=data2014.Track, y=diversity_2014,size=4, color=\".3\", linewidth=0)\n",
    "sns.despine(trim=True, left=True)\n",
    "\n",
    "# plt.xticks(range(4),[\"Gold\", \"Silver\", \"Bronze\",\"None\"])\n",
    "plt.title(\"Teams of 2014\", size=20)\n",
    "plt.ylabel(\"Diversity\", size=20)\n",
    "plt.xlabel(\"Track\", size=20)\n",
    "plt.tick_params(labelsize=18)\n",
    "#plt.savefig(\"2014 diversity diversity box plot.png\", dpi=300)\n",
    "#plt.xticks([])\n",
    "plt.legend(loc='upper left')\n",
    "plt.tick_params(axis='x', length=0.1, width=0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "\t\n",
    "# The labels argument in ax.boxplot() sets the xticklabels of the axis, not the labels of the boxes objects (which would be used in e.g. ax.legend()).\n",
    "\n",
    "# So instead, you can access the labels you want from ax.get_xticklabels. The relevant snippet to replace in your code is:\n",
    "\n",
    "# for b in boxplot_dict['boxes']:\n",
    "#     lab = ax.get_xticklabels()[i].get_text()\n",
    "#     print(\"Label property of box {0} is {1}\".format(i, lab))\n",
    "#     b.set_facecolor(color_dict[lab]) \n",
    "#     i += 1\n",
    "# The full code would be:\n",
    "\n",
    "# from matplotlib import pyplot as plt\n",
    "# import numpy as np\n",
    "\n",
    "# data = {}\n",
    "# data['a'] = np.arange(12)+1\n",
    "# data['b'] = np.arange(14)+1\n",
    "# data['c'] = np.arange(8)+1\n",
    "\n",
    "# color_dict = {'trt_a':'orange', 'trt_b':'blue', 'trt_c':'green'}\n",
    "# controls = ['trt_a', 'trt_b', 'trt_c']\n",
    "\n",
    "# fig, ax = plt.subplots()\n",
    "\n",
    "# boxplot_dict = ax.boxplot(\n",
    "#     [data[x] for x in ['a', 'b', 'c']],\n",
    "#     positions = [1, 1.5, 2],\n",
    "#     labels = controls, \n",
    "#     patch_artist = True,\n",
    "#     widths = 0.25)\n",
    "\n",
    "# i=0\n",
    "# for b in boxplot_dict['boxes']:\n",
    "#     lab = ax.get_xticklabels()[i].get_text()\n",
    "#     print(\"Label property of box {0} is {1}\".format(i, lab))\n",
    "#     b.set_facecolor(color_dict[lab]) \n",
    "#     i += 1\n",
    "\n",
    "# ax.set_ylim([0,16])\n",
    "# plt.show()\n",
    "\n",
    "\n",
    "# color_dict = {'Measurement':'orange', 'Health & Medicine':'blue', \n",
    "#               'Information Processing':'black',\n",
    "#               'Foundational Advantage':'green',  'Software':'skyblue',\n",
    "#               'Energy':'grey', 'Art & Design Track': 'white',\n",
    "#               'New Application':'grey', 'Environment':'white',\n",
    "#               'Manufacturing':'grey', 'Policy & Practices': 'grey',\n",
    "#               'Food & Nutrition':'grey', 'Microfluidics':'grey'}\n",
    "# controls = ['Measurement', 'Health & Medicine', 'Information Processing', 'Foundational Advantage',\n",
    "#            'Software', 'Energy', 'Art & Design Track', 'New Application', 'Environment',\n",
    "#             'Manufacturing', 'Policy & Practices', 'Food & Nutrition', 'Microfluidics']\n",
    "\n",
    "\n",
    "# boxplot_dict = ax.boxplot(\n",
    "#     [data[x] for x in ['a', 'b', 'c']],\n",
    "#     positions = [1, 1.5, 2],\n",
    "#     labels = controls, \n",
    "#     # patch_artist = True,  # Legend isn't working with patch objects.. \n",
    "#     widths = 0.25)\n",
    "\n",
    "# i=0\n",
    "# for b in boxplot_dict['boxes']:\n",
    "#     lab = ax.get_xticklabels()[i].get_text()\n",
    "#     print(\"Label property of box {0} is {1}\".format(i, lab))\n",
    "#     b.set_color(color_dict[lab])\n",
    "#     b.set_label(lab)\n",
    "#     i += 1\n",
    "\n",
    "# ax.set_ylim([0,16])\n",
    "# ax.legend()\n",
    "# plt.show()"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}