{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ciencia de Datos 2022\n",
    "\n",
    "### Alan Reyes-Figueroa"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "source": [
    "Ejemplo tomado de la documentación de la librería *MiniSom*, https://github.com/JustGlowing/minisom.\n",
    "\n",
    "In this example we will see how to use MiniSom to draw some insights from the <a href=\"https://en.wikipedia.org/wiki/Democracy_Index\">Democracy Index data</a> from Wikipedia.\n",
    "\n",
    "First, let's load the dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.patches import Patch\n",
    "%matplotlib inline\n",
    "\n",
    "from minisom import MiniSom\n",
    "from sklearn.preprocessing import minmax_scale, scale\n",
    "\n",
    "# download from wikipedia and reorganization\n",
    "import os.path\n",
    "if not os.path.isfile('democracy_index.csv'):\n",
    "    wikitables = pd.read_html('https://en.wikipedia.org/wiki/Democracy_Index',\n",
    "                              attrs={\"class\":\"sortable\"}, header=0)\n",
    "    democracy_index = wikitables[0]\n",
    "    democracy_index.columns = [c.lower().replace(' ', '_') for c in democracy_index.columns]\n",
    "    democracy_index.rename(columns={'score': 'democracy_index', \n",
    "                                    'functioning_ofgovernment': 'functioning_of_government',\n",
    "                                    'politicalparticipation': 'political_participation',\n",
    "                                    'politicalculture': 'political_culture',\n",
    "                                    'civilliberties': 'civil_liberties'}, inplace=True)\n",
    "    democracy_index.category = democracy_index.category.replace('Flawed democracy[a]', 'Flawed democracy')\n",
    "    democracy_index = democracy_index[:-1]\n",
    "    democracy_index.to_csv('democracy_index.csv')\n",
    "    print('data downloaded from Wikipedia')\n",
    "else:\n",
    "    # pre-downloaded file\n",
    "    democracy_index = pd.read_csv('democracy_index.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>rank</th>\n",
       "      <th>country</th>\n",
       "      <th>democracy_index</th>\n",
       "      <th>electoral_processand_pluralism</th>\n",
       "      <th>functioning_of_government</th>\n",
       "      <th>political_participation</th>\n",
       "      <th>political_culture</th>\n",
       "      <th>civil_liberties</th>\n",
       "      <th>category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Norway</td>\n",
       "      <td>9.87</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.64</td>\n",
       "      <td>10.00</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.71</td>\n",
       "      <td>Full democracy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Iceland</td>\n",
       "      <td>9.58</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.29</td>\n",
       "      <td>8.89</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.71</td>\n",
       "      <td>Full democracy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>9.39</td>\n",
       "      <td>9.58</td>\n",
       "      <td>9.64</td>\n",
       "      <td>8.33</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.41</td>\n",
       "      <td>Full democracy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>9.26</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.29</td>\n",
       "      <td>8.89</td>\n",
       "      <td>8.13</td>\n",
       "      <td>10.00</td>\n",
       "      <td>Full democracy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>9.22</td>\n",
       "      <td>10.00</td>\n",
       "      <td>9.29</td>\n",
       "      <td>8.33</td>\n",
       "      <td>9.38</td>\n",
       "      <td>9.12</td>\n",
       "      <td>Full democracy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0 rank      country  democracy_index  \\\n",
       "0           0    1       Norway             9.87   \n",
       "1           1    2      Iceland             9.58   \n",
       "2           2    3       Sweden             9.39   \n",
       "3           3    4  New Zealand             9.26   \n",
       "4           4    5      Denmark             9.22   \n",
       "\n",
       "   electoral_processand_pluralism  functioning_of_government  \\\n",
       "0                           10.00                       9.64   \n",
       "1                           10.00                       9.29   \n",
       "2                            9.58                       9.64   \n",
       "3                           10.00                       9.29   \n",
       "4                           10.00                       9.29   \n",
       "\n",
       "   political_participation  political_culture  civil_liberties        category  \n",
       "0                    10.00              10.00             9.71  Full democracy  \n",
       "1                     8.89              10.00             9.71  Full democracy  \n",
       "2                     8.33              10.00             9.41  Full democracy  \n",
       "3                     8.89               8.13            10.00  Full democracy  \n",
       "4                     8.33               9.38             9.12  Full democracy  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "democracy_index.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see the dataset contains a set of of social metrics related to the democracy level for each country. The goal is to use these metrics as features for our SOM so that we can create a bidimensional space where each country is mapped according to their democracity level.\n",
    "\n",
    "Let's define a set of color for the categories in which the countries are classified and also a country codes for each country. These will become handy when we will visualize the results on the map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "category_color = {'Full democracy': 'darkgreen',\n",
    "                  'Flawed democracy': 'limegreen',\n",
    "                  'Hybrid regime': 'darkorange',\n",
    "                  'Authoritarian': 'crimson'}\n",
    "colors_dict = {c: category_color[dm] for c, dm in zip(democracy_index.country,\n",
    "                                                      democracy_index.category)}\n",
    "\n",
    "country_codes = {'Afghanistan': 'AF',\n",
    " 'Albania': 'AL',\n",
    " 'Algeria': 'DZ',\n",
    " 'Angola': 'AO',\n",
    " 'Argentina': 'AR',\n",
    " 'Armenia': 'AM',\n",
    " 'Australia': 'AU',\n",
    " 'Austria': 'AT',\n",
    " 'Azerbaijan': 'AZ',\n",
    " 'Bahrain': 'BH',\n",
    " 'Bangladesh': 'BD',\n",
    " 'Belarus': 'BY',\n",
    " 'Belgium': 'BE',\n",
    " 'Benin': 'BJ',\n",
    " 'Bhutan': 'BT',\n",
    " 'Bolivia': 'BO',\n",
    " 'Bosnia and Herzegovina': 'BA',\n",
    " 'Botswana': 'BW',\n",
    " 'Brazil': 'BR',\n",
    " 'Bulgaria': 'BG',\n",
    " 'Burkina Faso': 'BF',\n",
    " 'Burundi': 'BI',\n",
    " 'Cambodia': 'KH',\n",
    " 'Cameroon': 'CM',\n",
    " 'Canada': 'CA',\n",
    " 'Cape Verde': 'CV',\n",
    " 'Central African Republic': 'CF',\n",
    " 'Chad': 'TD',\n",
    " 'Chile': 'CL',\n",
    " 'China': 'CN',\n",
    " 'Colombia': 'CO',\n",
    " 'Comoros': 'KM',\n",
    " 'Costa Rica': 'CR',\n",
    " 'Croatia': 'HR',\n",
    " 'Cuba': 'CU',\n",
    " 'Cyprus': 'CY',\n",
    " 'Czech Republic': 'CZ',\n",
    " 'Democratic Republic of the Congo': 'CD',\n",
    " 'Denmark': 'DK',\n",
    " 'Djibouti': 'DJ',\n",
    " 'Dominican Republic': 'DO',\n",
    " 'Ecuador': 'EC',\n",
    " 'Egypt': 'EG',\n",
    " 'El Salvador': 'SV',\n",
    " 'Equatorial Guinea': 'GQ',\n",
    " 'Eritrea': 'ER',\n",
    " 'Estonia': 'EE',\n",
    " 'Ethiopia': 'ET',\n",
    " 'Fiji': 'FJ',\n",
    " 'Finland': 'FI',\n",
    " 'France': 'FR',\n",
    " 'Gabon': 'GA',\n",
    " 'Gambia': 'GM',\n",
    " 'Georgia': 'GE',\n",
    " 'Germany': 'DE',\n",
    " 'Ghana': 'GH',\n",
    " 'Greece': 'GR',\n",
    " 'Guatemala': 'GT',\n",
    " 'Guinea': 'GN',\n",
    " 'Guinea-Bissau': 'GW',\n",
    " 'Guyana': 'GY',\n",
    " 'Haiti': 'HT',\n",
    " 'Honduras': 'HN',\n",
    " 'Hong Kong': 'HK',\n",
    " 'Hungary': 'HU',\n",
    " 'Iceland': 'IS',\n",
    " 'India': 'IN',\n",
    " 'Indonesia': 'ID',\n",
    " 'Iran': 'IR',\n",
    " 'Iraq': 'IQ',\n",
    " 'Ireland': 'IE',\n",
    " 'Israel': 'IL',\n",
    " 'Italy': 'IT',\n",
    " 'Ivory Coast': 'IC',\n",
    " 'Jamaica': 'JM',\n",
    " 'Japan': 'JP',\n",
    " 'Jordan': 'JO',\n",
    " 'Kazakhstan': 'KZ',\n",
    " 'Kenya': 'KE',\n",
    " 'Kuwait': 'KW',\n",
    " 'Kyrgyzstan': 'KG',\n",
    " 'Laos': 'LA',\n",
    " 'Latvia': 'LV',\n",
    " 'Lebanon': 'LB',\n",
    " 'Lesotho': 'LS',\n",
    " 'Liberia': 'LR',\n",
    " 'Libya': 'LY',\n",
    " 'Lithuania': 'LT',\n",
    " 'Luxembourg': 'LU',\n",
    " 'Macedonia': 'MK',\n",
    " 'Madagascar': 'MG',\n",
    " 'Malawi': 'MW',\n",
    " 'Malaysia': 'MY',\n",
    " 'Mali': 'ML',\n",
    " 'Malta': 'MT',\n",
    " 'Mauritania': 'MR',\n",
    " 'Mauritius': 'MU',\n",
    " 'Mexico': 'MX',\n",
    " 'Moldova': 'MD',\n",
    " 'Mongolia': 'MN',\n",
    " 'Montenegro': 'ME',\n",
    " 'Morocco': 'MA',\n",
    " 'Mozambique': 'MZ',\n",
    " 'Myanmar': 'MM',\n",
    " 'Namibia': 'NA',\n",
    " 'Nepal': 'NP',\n",
    " 'Netherlands': 'NL',\n",
    " 'New Zealand': 'NZ',\n",
    " 'North Macedonia': 'NM',\n",
    " 'Nicaragua': 'NI',\n",
    " 'Niger': 'NE',\n",
    " 'Nigeria': 'NG',\n",
    " 'North Korea': 'KP',\n",
    " 'Norway': 'NO',\n",
    " 'Oman': 'OM',\n",
    " 'Pakistan': 'PK',\n",
    " 'Palestine': 'PS',\n",
    " 'Panama': 'PA',\n",
    " 'Papua New Guinea': 'PG',\n",
    " 'Paraguay': 'PY',\n",
    " 'Peru': 'PE',\n",
    " 'Philippines': 'PH',\n",
    " 'Poland': 'PL',\n",
    " 'Portugal': 'PT',\n",
    " 'Qatar': 'QA',\n",
    " 'Republic of China (Taiwan)': 'TW',\n",
    " 'Republic of the Congo': 'CG',\n",
    " 'Romania': 'RO',\n",
    " 'Russia': 'RU',\n",
    " 'Rwanda': 'RW',\n",
    " 'Saudi Arabia': 'SA',\n",
    " 'Senegal': 'SN',\n",
    " 'Serbia': 'RS',\n",
    " 'Sierra Leone': 'SL',\n",
    " 'Singapore': 'SG',\n",
    " 'Slovakia': 'SK',\n",
    " 'Slovenia': 'SI',\n",
    " 'South Africa': 'ZA',\n",
    " 'South Korea': 'KR',\n",
    " 'Spain': 'ES',\n",
    " 'Sri Lanka': 'LK',\n",
    " 'Sudan': 'SD',\n",
    " 'Suriname': 'SR',\n",
    " 'Swaziland': 'SZ',\n",
    " 'Sweden': 'SE',\n",
    " 'Switzerland': 'CH',\n",
    " 'Syria': 'SY',\n",
    " 'Tajikistan': 'TJ',\n",
    " 'Tanzania': 'TZ',\n",
    " 'Thailand': 'TH',\n",
    " 'Timor-Leste': 'TL',\n",
    " 'Togo': 'TG',\n",
    " 'Trinidad and Tobago': 'TT',\n",
    " 'Tunisia': 'TN',\n",
    " 'Turkey': 'TR',\n",
    " 'Turkmenistan': 'TM',\n",
    " 'Uganda': 'UG',\n",
    " 'Ukraine': 'UA',\n",
    " 'United Arab Emirates': 'AE',\n",
    " 'United Kingdom': 'GB',\n",
    " 'United States': 'US',\n",
    " 'Uruguay': 'UY',\n",
    " 'Uzbekistan': 'UZ',\n",
    " 'Venezuela': 'VE',\n",
    " 'Vietnam': 'VN',\n",
    " 'Yemen': 'YE',\n",
    " 'Zambia': 'ZM',\n",
    " 'Zimbabwe': 'ZW'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are now ready 1) isolate our features, 2) scale the feature and train our SOM:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " [ 1000 / 1000 ] 100% - 0:00:00 left \n",
      " quantization error: 0.35464600769383864\n"
     ]
    }
   ],
   "source": [
    "feature_names = ['democracy_index', 'electoral_processand_pluralism', 'functioning_of_government',\n",
    "                 'political_participation', 'political_culture', 'civil_liberties']\n",
    "\n",
    "X = democracy_index[feature_names].values\n",
    "X = scale(X)\n",
    "\n",
    "size = 15\n",
    "som = MiniSom(size, size, len(X[0]),\n",
    "              neighborhood_function='gaussian', sigma=1.5,\n",
    "              random_seed=1)\n",
    "\n",
    "som.pca_weights_init(X)\n",
    "som.train_random(X, 1000, verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A social map of countries\n",
    "----\n",
    "\n",
    "Here we will plot each country in a cell that represent the winning neuron on the SOM. The country codes will be used instead of the full names of the countries to make the map more readable. The name of the countries will be colored according to their democracy status."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1008 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def shorten_country(c):\n",
    "    if len(c) > 6:\n",
    "        return country_codes[c]\n",
    "    else:\n",
    "        return c\n",
    "\n",
    "country_map = som.labels_map(X, democracy_index.country)\n",
    "    \n",
    "plt.figure(figsize=(14, 14))\n",
    "for p, countries in country_map.items():\n",
    "    countries = list(countries)\n",
    "    x = p[0] + .1\n",
    "    y = p[1] - .3\n",
    "    for i, c in enumerate(countries):\n",
    "        off_set = (i+1)/len(countries) - 0.05\n",
    "        plt.text(x, y+off_set, shorten_country(c), color=colors_dict[c], fontsize=10)\n",
    "plt.pcolor(som.distance_map().T, cmap='gray_r', alpha=.2)\n",
    "plt.xticks(np.arange(size+1))\n",
    "plt.yticks(np.arange(size+1))\n",
    "plt.grid()\n",
    "\n",
    "legend_elements = [Patch(facecolor=clr,\n",
    "                         edgecolor='w',\n",
    "                         label=l) for l, clr in category_color.items()]\n",
    "plt.legend(handles=legend_elements, loc='center left', bbox_to_anchor=(1, .95))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Features planes\n",
    "----\n",
    "\n",
    "Here we will create a map for each feature used that reflects the magnitude of the weights associated to it for each neuron."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "W = som.get_weights()\n",
    "plt.figure(figsize=(10, 10))\n",
    "for i, f in enumerate(feature_names):\n",
    "    plt.subplot(3, 3, i+1)\n",
    "    plt.title(f)\n",
    "    plt.pcolor(W[:,:,i].T, cmap=plt.cm.coolwarm)\n",
    "    plt.xticks(np.arange(size+1))\n",
    "    plt.yticks(np.arange(size+1))\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Most relevant feature plane\n",
    "----\n",
    "\n",
    "In this map we associate each neuron to the feature with the maximum weight. This segments our map in regions where specific features have high values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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33Rf+r3/9y99iscixY8c8Dx8+bBMRCQsLq6wraImJiWU5OTlehYWF1pKSEuu4ceNKRURuu+22wvXr1zf6hOMhQ4YUd+3atUZEZNy4cSc2btzofzHFdObMmSfqPk5PT/d57LHHwkpKSqynTp2yDhs2rKih/Tp37lzj5eVVO3Xq1F7jxo0rmjJlyo/bjhs37qTFYpEBAwaUBQUFVaWkpJSLiNjt9vIDBw54XUwx5VQ+AABuRmutJk+eXJiZmbknMzNzT05OTsbzzz//fVP3a61FqWZ3x3r5+/vX1n384IMPhg0bNqxk3759uz/55JP9p0+fbnYvOX8edZ/XHbk8u4569z27Dn3ebapv377ldWvOzs7e8/XXX+8TEdmwYcO+X/7yl/np6el+CQkJjqqqKvntb3/7w4oVKw6Wl5dbBg0aFLt9+3bv5cuXdy4sLLTt2rVrb2Zm5p6goKCq8vJyi4iIp6fnj3lWq1VXV1erljyeDa27joeHh66t/fEhkMrKyp9sEBAQ8OOdc+bMiXz55ZcPZWdn73nwwQe/r6ysbPDx9/DwkP/+9797U1NTT3788ccdhw8fHlV3n7e3tz67rp+s02KxSHV19UUtsF2PmAYHB+uIiIj2jAQAwDDp6ekFWuuQRjeqqqhuzSvp6x3Pw7vRTcaMGVM8adKkvg8//HBeWFhYdV5enrWoqMja1P3XXHPNqYULF/bKzMz0PPdUfkBAQE1xcfGP+ycmJp5asWJFp1/+8pfHly9f3jk5Obm0vnkUFxdbw8PDT4uILF++PPhilrl27dqOS5cuPVpcXGz517/+FfDCCy8cycjI+MnChwwZUvrOO+90njhxYsnOnTu9jh496tm/f/+KkSNHFr/++ush48aNK6k7ld+/f/+K48eP27788ku/kSNHnqqsrFS7du3ySkxMrDhw4IDnhAkTSkaPHl3avXv3zkVFRda8vDxbSkpKeUpKSvm2bdv8MjIyvIuKiqzBwcFVXl5e+pNPPgn4/vvvPRtbQ3BwcI2/v3/NF1984f/zn/+89O233+7c1Lq3bNkSmJeXZ/Xz86v97LPPOq5YsSLn3Pv79OlTuX//fp/y8nJVVlZm2bJlS+DgwYPrffzLysosPXv2rKqsrFTvv/9+527dulU1lFtUVGQpLS21TJkypWj48OGldru9X1NzbYl2LaYRERHidDrbMxIAAMMopQ42uVFbX3O0iVIqIpKUlFTx6KOPHhkxYoS9trZWPDw8dFpa2qGm7h8xYsSptLS0nBtvvLFvbW2tBAUFVW3dunVfamrqyZtuuqnP2rVrO7744ouHXnvttUOzZs2KeOmll7oGBQVVr1q1Kqe+eTz44IM/3HHHHZFpaWldhw4dWnwxy0xMTDw1YsSIqO+//95z0aJFRyMiIqrOL6aLFy8+dsstt/Sy2+0Oq9Uqy5cvz/Hx8dH3339/fnZ2tldMTEyczWbTs2bNyn/44Yfz33///QP33HNPz5KSEmtNTY2688478/r161c5ffr0yJKSEqvWWs2dOzcvODi4ZuHChd23bt0aaLFYtN1uL7/pppuKTp48aR07dmzf+Pj42Li4uLLIyMiKptbx1ltv5dxxxx0RPj4+tddee22Tj0FycnJp3dMfUlNTC88/jd+3b9+qCRMmnIiNjY2LjIysiIuLa/A0/0MPPfR9SkpKbFhY2OnY2Niy0tJSa0Pbnjx50jp+/Pi+dUdgn3zyydym5toSqqHD3K6QnJys64pp9pChUlNQ4LIsa3Cw2LdsvuB2I3Ldaa3ulutOa3W3XHdaq7vltmemUipda5187v07duzISUhIcN0E3MC519k0ei7tKS0tLcjpdPqtWrXqUNNbm9eOHTuCExISIuq7z7DnmLryl0Jj4xuR605rdbdcd1qru+W601rdLdeotQJoGq/KBwAApvTSSy8Fvfbaa13Ove1nP/tZ6Z/+9KdL+ohhUz788MPARx555CeXjurRo0flunXrDohIoUHTahcUUwAAYEr33ntv4b333ntZF7H6pKamFqempu4xeh5G4HJRAAAAMAWKKQAAAEyBYgoAAABT4DmmAAAYqLK6MsHL5tVmf48rqyurvWxebXttVKCdUEwBADCQl83L1u+PbfcmOrtm7WrW3/Ynn3wydOXKlSHx8fFlf//7379rbW5WVpbnhg0b/OfNm3dcROSrr77yXblyZdDbb7/doguxJyYmxmzfvj2ztfNqSnl5uRoxYkTU8ePHbQsXLjw6e/bsE03vdfl56KGHuj711FM/GD0PTuUDAOCG3nrrrZDPPvtsX1uUUhGRffv2ea1evfrHt9S8+uqry1paSkVE2qOUiohs3brVt6qqSmVmZu4xQymtqmrwXUFdKi0trZshweehmAIA4GamT5/e8/Dhw14TJ07sGxAQcMVjjz3247VCo6Ki4rKysjyzsrI8e/fuHTd16tReffv2jRs8eHBUaWmpEhHJyMjwGjRokD06OtrhcDhid+/e7fXII4+EOZ1O/5iYGMdvfvOb0DVr1gRcc801fUVE8vLyrCNHjuxjt9sdCQkJMdu2bfMROfMOTpMnT45ISUmJDg8P7/fkk0+G1s3D19c3UURkzZo1ASkpKdFjxozpHRkZGTdx4sTI2tpaERFZvXp1h8jIyLikpKToW2+9tUddXn3qm8ORI0dsv/jFLyIzMzN9YmJiHLt37/aqb9+Gcuobs6amRsLCwvoVFBT8+PaePXv2jM/NzbV9//33tp///Od94uPjY+Pj42P/8Y9/+NU9DtOmTes1ePDgqEmTJkU29LhkZWV5RkZGxk2ZMqVXVFRU3MSJEyM//vjjgAEDBsT06tUrfsOGDb4iIsXFxZbJkydHxMfHx8bGxjreeeedjiJn3jlq9OjRfYYOHRrVq1ev+Hnz5oWLiMyfPz+ssrLSEhMT45g4cWLkxX4/tSWKKQAAbua99947FBoaWrVp06bs2bNnH2tou0OHDnnfc889x/bv37+7Q4cONatWreokIjJ9+vTIefPmHcvKytrjdDoze/bsWbV06dIjycnJpZmZmXsef/zxn4y5ePHi7gkJCWXZ2dl7nnjiiSOzZs36sfzs37/fe9OmTdn/+c9/9j733HPd696L/Vx79+71eeWVV3L379+/+9ChQ17r1q3zLysrU/fee2+vtWvX7ktPT88qLCxs9CkM9c0hLCys+tVXXz1YN++4uLjK8/drLKe+Ma1Wq4wePfrku+++21FEZP369X7h4eGne/ToUT137tweCxYsyMvIyNj70UcfHZg3b15E3Vg7d+70/eKLL/Z/8skn3zX2uOTm5novXLjwWGZm5u4DBw54v/vuu0FOpzNz6dKlh5cuXdpNROThhx/uds011xRnZGTs3bx5c9ajjz4aXlxcbBER2bNnj+/HH3/87d69e3f//e9/77R//36PV1999YiXl1dtZmbmnrY6gt5SFFMAAFCvsLCwykGDBpWLiCQmJpbl5OR4nThxwpKXl+c5c+bMkyIivr6+OiAgoLaxcf79738H3H777YUiIhMnTiw5efKkrbCw0CoiMnr06JM+Pj66W7du1Z07d646fPjwBQWzX79+p/r06VNltVolLi6u7MCBA57//e9/vXv06FEZExNzWkRk6tSpx1s6h8Y0ltPQmNOnTz/+wQcfdBYReffddzunpqYeFxH5+uuvA++9996eMTExjgkTJvQtLS21njhxwiIiMmbMmJP+/v66buyGHpewsLDKlJSUcqvVKna7vfzaa68ttlgsMmDAgLLDhw97iYhs3Lgx8IUXXugWExPjGDJkSHRlZaXav3+/p4jIkCFDioOCgmp8fX113759Kw4cOFDvUWKj8OInAADcmM1m03WnxkVEzj1i6enp+WNRslqtury83KK1lotV3z5KKS0i4uXldW6GVFdXX3DEtL5tLnYejc3hYvdraswRI0acuv32272+//572+eff95x6dKl39dt73Q6955bQOv4+fn9pNw39Lic+zWxWCzi7e2t67apqalRdTkffPDB/oSEhJ8cAd6yZYvf+V/TqqqqCx5vI1FMAQAwUGV1ZXVzX0nf3PG8bM0/CBYREVH52WefdRQR2bJli++RI0ca3blz5861Xbt2Pf2nP/2p4y233HKyvLxcVVdXqw4dOtSUlpbWewTyyiuvLPnDH/4Q9Oyzzx5ds2ZNQKdOnao7d+7c6FHWpiQkJFTk5uZ6ZWVleUZHR58+94VXbTmHxnIaG3Ps2LEn58+f36Nv377lXbt2rRE5c7Ty6aefDn3iiSfyRES2bt3qU3dEui1dc801xcuWLevy9ttvH7JYLPL111/7DB48uNEcm82mKysr1bmF2AgUUwAADNTW1xy9mFIqIjJz5swT7777blBMTIzjiiuuONWrV6+KpvZ55513vps9e3avJ554oruHh4f+y1/+ciAlJaXcZrPp6Ohox/Tp0wuSkpJ+LEJPP/3099OnT4+w2+0OHx+f2rfffrvVz2P09/fXzz///MExY8ZEde7cuToxMfFUY9u3dA6N5TQ25owZM44PGzYsNi0tLafutjfeeCP3jjvu6Gm32x01NTVq4MCBJYMGDTrUguU36qmnnvp+zpw5PWNiYhxaaxUeHl65YcOG/Y3tM2PGjPzY2FhHW10+rKUu+lB4ayQnJ2un0ykiIntjYl2eF5u594LbjMh1p7W6W647rdXdct1pre6W256ZSql0rXXyufft2LEjJyEhocDlk3ADRUVFlg4dOtTW1tbKzJkze0ZFRVWc/8KrSynHXezYsSM4ISEhor77ePETAAC4JL344ovBMTExjqioqLji4mLrggULXFL42ysHnMoHAACXqMcff/zY+UcuX3rppaDXXnuty7m3/exnPyv905/+1OQp81GjRvXJzc39yXMhli5deri+HLgGxRQAAFw27r333sJ77723sCX7rlu37kBbzwcXh1P5AAAAMAWKKQAAAEyBYgoAAABT4DmmAAAYqLayMsHi5dVmf49rKyurLV5te21UoL00ecRUKbVSKXVMKZVRz32LlFJaKRV8scHW4IvepU3GNyLXndbqbrnutFZ3y3WntbpbrlFrbYjFy8u2NyZW2uq/tiy5dVJSUqK/+uorXxGRYcOG9S0oKLAWFBRYn3rqqZC6bXJycjzGjBnTuyXjp6amRvzhD3/o1FbzPd/WrVt9Vq9e3aHu83fffbfDww8/3LWxfRITE2NamrdkyZLQkpKSHztW3WPW0vHcSZMX2FdKXS0ipSKySmsdf87tPURkhYjEiEiS1rrJa3qde4F9AAAud828wH5SW170/+zF/dPbbEA5U0yfe+653Kuvvrqs7rasrCzP8ePHR+3bt293a8dPTU2NGD9+fNEvfvGLE60d63xVVVXy2muvBTmdTr9Vq1a1+bss1ScsLKyf0+nc261bt+r2yLvUtOoC+1rrr0TkeD13vSAii0XE0PdUBQAAFycrK8szMjIybtKkSRF2u90xZsyY3iUlJZa//e1vAbGxsQ673e6YPHlyRHl5uTp/37CwsH5Hjx61LVy4MDw3N9crJibGMXfu3PCsrCzPqKioOBGR6upqmTNnTrjdbnfY7XbH0qVLQ0VEFi1a1C0+Pj42Kioqbtq0ab1qa5t8q/ofM++8886wfv36xfbr1y82IyPDS0Tkvffe69C/f/+Y2NhYx6BBg+y5ubk2EZEFCxZ0nzZtWq/BgwdHTZo0KfJ3v/td908++aRTTEyM48033+yUlpYWNHPmzJ4iIrm5ubZRo0b1iY6OdkRHRzvWrVvnJyLi6+ubKCKyZs2agOTk5OhRo0b16dOnT9z06dN71tTUiIjIjBkzesbHx8f27ds37v777+8uIvLkk0+GHjt2zGPYsGH2gQMH2s99zEREfv3rX3eJioqKi4qKiluyZElo3dejd+/ecVOnTu3Vt2/fuMGDB0eVlpZe8Ni7gxa9+EkpNVFEjmitm3wOi1JqjlLKqZRy5ufntyQOAAC0sZycHO958+blZ2dn7wkICKh94oknusydOzdy9erVB7Kzs/dUV1fLs88+G9LQ/suWLTvco0ePyszMzD3Lly8/fN59IQcPHvTavXv3nuzs7D133HFHoYjIAw88cCwjI2Pvvn37dpeXl1vef//9DvWPfqHAwMCaXbt27Z07d+6xu+++u4eIyKhRo0r/+9//Zu7du3fPTTfddHzJkiU/np7fuXOn7xdffLH/k08++e5Xv/rV9xMmTDiRmZm5Z/bs2T85Kjtv3ryeQ4cOLcnKytqze/fuPQMGDKg4P3vXrl1+L730Um5WVtbunJwcr1WrVnUSEXn++eePZGRk7M3MzNz99ddfB2zbts3n0UcfPRYaGlq1adOm7G3btmWfO87mzZt933vvvaD09PS9Tqdz76pVq0K+/vprHxGRQ4cOed9zzz3H9u/fv7tDhw41dRnu5qKLqVLKV0QeEZHHmrO91voNrXWy1jo5JKTB728AANCOunbtenr06NGnRERuueWWwk2bNgWEh4dX9u/fv1JE5NZbby3csmVLQEvGXr9+feC8efPyPTw8RESkS5cuNSIia9euDejfv3+M3W53bN26NSAjI8OnuWPOmjXruIjI7Nmzj2/fvt1fROS7777zHDp0aJTdbnekpaV1zczM/HG8MWPGnPT392/yrO7WrVsDHnjggXwREZvNJkFBQTXnb9OvX79TDofjtM1mk//5n/85vnnzZn8RkT/+8Y+dHQ5HrMPhcOzbt897x44d3o1lbdy40f+66647GRgYWNuhQ4facePGndiwYUOAiEhYWFjloEGDykVEEhMTy3JycrwaG+ty1ZInSPcRkUgR2aGUEhEJF5FvlFIpWusfmjtI9pChUlPgureatQYHi33LZlPkutNa3S3XqLXKs1Eip1z47nh+oSIP7HPrXHf6Pna3XMN+bk3m7N9wl9Bai1LqJ6WwrKxMLVy4sNe2bdv29O3bt2rBggXdKyoqmn2AzGL5/5vWjX3XXXf1vPfee3+YMWNG0Zo1awKWLFnSvW4bPz+/5j1PoBnOf6yUUpKZmen58ssvd0lPT98bEhJSk5qaGtHUehp7XY+np+ePd1qtVl1eXu6Wl/S86EVrrXdprUO11hFa6wgROSwiAy6mlIqIS38pNDa+EbnutFZ3yzVqrS4taY2N70a57vR97G65hv3cNqC2srI6NnOvtNV/tZWVzXrBzdGjRz2//PJLPxGR9957r/Pw4cOLjxw54ln3/M1Vq1YFDR06tKSh/Tt06FBz6tSpenvEyJEji19//fWQqqoqERHJy8uzlpWVWUREunbtWl1UVGT55JNPLupU9apVqzqLiLz11ludEhMTT4mIlJSUWHv27FklIvL2228HNbRvYGBgTWlpab1zHTx4cEndUxaqq6vl+PHjF2y3a9cuv8zMTM+amhr54IMPOg8dOrTkxIkTVh8fn9rOnTvX5Obm2jZu3Pjj0xL8/PxqioqKLhjn2muvLf3ss886lpSUWIqLiy2fffZZp2uuuabBx9gdNXnEVCn1ZxEZLiLBSqnDIvK41votV08MAAB30NbXHLV4Ne8McO/evStWrlwZNH/+/F6RkZGVb775Zu6gQYNOTZ48uU9NTY0kJCSULVq0qMEXh3Tt2rUmKSmpNCoqKu7aa68tWrBgwY//wrv//vvzs7OzvWJiYuJsNpueNWtW/sMPP5w/Y8aMfIfDERceHn46ISHh1MWsq7KyUvXv3z+mtrZWvf/++9+KiDzyyCPfT5s2rU+XLl1OJycnnzp06FC9ix87dmzJc8891y0mJsaxcOHCo+fe99prrx269dZbe9nt9mCLxSIvv/zywZEjR/5kbldccUXpwoULwzMzM30GDhxYcsstt5y0Wq0SHx9fFhUVFdezZ8/KpKSk0rrtZ82aVTB27Nio0NDQqnOfZzpkyJCy6dOnFw4YMCBWROSWW27JHzx4cHlWVpbnxTwWl7MmLxfVls69XFRbXhqjIWcvmfETRuS601rdLdeotcqvm/16gZb7dZFb57rT97G75bZnZjMvF9Xu2vJST+3ByMsvrVmzJmDZsmVdNmzYsL+9sy9XrbpcFAAAANAeeEtSAADcTHR09GkzHi0dNWpUn9zc3J+cjl+6dOnhI0eO7DJqTuPHjy8ZP348zwNtJxRTAABgCuvWrTtg9BxgLE7lAwAAwBQopgAAADAFiikAAABMgeeYAgBgoOqqmgSbh7XN/h5XV9VU2zysbXptVKC9UEwBADCQzcNqe2Xe+jYb75evX9vmf9tTUlKin3vuudyrr766bNiwYX0//PDD70REVqxY0fmhhx7KFxHJycnxmDdvXo/PP//824sdPzU1NWL8+PFFv/jFL060xXzrrnvq4eGhz50jzI9T+QAAoNk2bdq0Pzg4uKawsND61ltvhdbdHhERUdWSUupK58+xuaqr2/06/jiLYgoAgJvJysryjIyMjJs0aVKE3W53jBkzpndJSYnlb3/7W0BsbKzDbrc7Jk+eHFFeXq7O3zcsLKzf0aNHbQsXLgzPzc31iomJccydOzc8KyvLMyoqKk7kTLGbM2dOuN1ud9jtdsfSpUtDRUQWLVrULT4+PjYqKipu2rRpvWpra5s1302bNvkmJibGREdHO/r16xd74sQJS1paWtDMmTN71m1zzTXX9F2zZk3AufudP8c1a9YEXHPNNX3r7p85c2bPtLS0oLp1LVq0qFtSUlL0ypUrO/31r38NvOKKK2IcDkfs2LFjexcVFdGZ2gEPMgAAbignJ8d73rx5+dnZ2XsCAgJqn3jiiS5z586NXL169YHs7Ow91dXV8uyzz4Y0tP+yZcsO9+jRozIzM3PP8uXLD593X8jBgwe9du/evSc7O3vPHXfcUSgi8sADDxzLyMjYu2/fvt3l5eWW999/v8n3G66oqFAzZszo8+KLLx7Kysras2nTpix/f/9mNdrG5lgfb2/v2vT09KwJEyaU/Pa3v+321VdfZe/Zs2fvgAEDyp544okuzclE6/AcUwAA3FDXrl1Pjx49+pSIyC233FK4dOnSbuHh4ZX9+/evFBG59dZbC1955ZVQETl2sWOvX78+cN68efkeHh4iItKlS5caEZG1a9cGPP/8810rKiosJ0+etDkcjnIRKWpsrJ07d3qHhoZWDRs2rExEpHPnzs07zNoCM2fOPCEisnHjRr8DBw54p6SkxIiIVFVVqaSkpFJX5eL/o5gCAOCGlLrgLH2b0VqLUkqfe1tZWZlauHBhr23btu3p27dv1YIFC7pXVFQ0eea2vrFERGw2mz73qQCVlZVNjuXh4XH+Pj95EAICAmrrMocMGVL8ySeffNfUmGhbFFMAAAxUXVVT3ZavpD97uagmtzt69Kjnl19+6Tdy5MhT7733Xufhw4cXr1q1KiQjI8MrPj6+ctWqVUFDhw5t8D3iO3ToUHPq1Kl6y+DIkSOLX3/99ZBx48aVeHh4SF5entVqPTOnrl27VhcVFVk++eSTThMmTGjyVfgJCQkVeXl5nps2bfIdNmxY2YkTJyz+/v61ffr0Of3mm2/61tTUyHfffeexc+dOv6bm2KdPn8r9+/f7lJeXq7KyMsuWLVsCBw8efMGR0OHDh59auHBhz7rHoqSkxPLdd9951B1NhutQTAEAMFBbX3O0OaVURKR3794VK1euDJo/f36vyMjIyjfffDN30KBBpyZPntynpqZGEhISyhYtWtTgZZa6du1ak5SUVBoVFRV37bXXFi1YsODHU/73339/fnZ2tldMTEyczWbTs2bNyn/44YfzZ8yYke9wOOLCw8NPJyQknGrOPL29vfW777574J577ulZUVFh8fb2rv3qq6+yR40aVfrKK69URkdHx0VHR5c7HI6ypua4fPnywxMmTDgRGxsbFxkZWREXF3fBPiIi3bt3r16+fHnO1KlTe58+fVqJiDz++ONHKKauRzEFAMANWSwWee+99w6de9v1119fcv311+85f9t///vfWXUfHzlyZFfdx+ef6t63b99uEREPDw9ZsWLFYRH5yQuO0tLSvk9LS/v+/PE//PDDnMbmOmzYsLIdO3Zknn/73//+93pPtTc2x9dff/2CeZ2/j4jIxIkTSyZOnLi3sXmh7fGqfAAAAJgCR0wBAHAz0dHRp+uObprJqFGj+uTm5nqde9vSpUsPp6amFhs1J7QviikAADCFdevWHTB6DjAWp/IBAABgCoYVU2twsCHjG5HrTmt1t1yj1ip+F/3WzxenofHdKNedvo/dLdewn1sATVJaX3DNWpdJTk7WTqez3fIAADCSUipda5187m07duzISUhIKDBqToDRduzYEZyQkBBR3308xxQAAANVnz6dYPP0bLsL7J8+XW3z9GzTa6MC7YViCgCAgWyenrZlU8a32XgLV69p0d/2Z555JsTX17f2rrvuKmxomylTpvRavHhxXlJSUkVYWFg/p9O5t1u3btX1bevr65tYVla2PScnx2PevHk9Pv/882/T0tKCnE6n36pVqw7Vt09zLFmyJPT+++8vqHv70GHDhvX98MMPvwsODq5p6ZgwD4opAACQxYsXN/guT3VWr1598GLHjYiIqPr888+/bdmsfqq6ulqWL1/eZfbs2cfriummTZv2t8XYMAfDimn2kKFSU+C6p9hYg4PFvmWzKXLdaa1G5sqzUSKnjl14e1vxCxV5YJ/xmeS2T65Ba3W3n1sjclcu3iLlxaddlukT6Cm3PTPEZeO3lZdffjkoLS2ti1JKYmNjy3v37l3p7+9fc8MNNxTNmjUrcteuXXtFRLKysjwnTJjQNzs7e09KSkr0c889l3v11VfX+1ae9cnKyvIcP358VN11U48cOeIxdOjQqNzcXK/U1NTCZcuWHRURefXVVzu/9tprXaqqqtSAAQNOrVq16qDNZhNfX9/EOXPm5K1fvz5w9OjRRceOHfMYNmyYvVOnTtXbtm3LPvfIbX1jiIhMmTIlYufOnX5KKT1jxoyCxx9/3IU/3GgNw4qpK38RNTa+EbnutFYjc11aIhoa34hMctsn16C1utvPrRG5riyl7TF+W3A6nd7PPfdct3/+85+Z3bp1q87Ly7M+/fTTXUREBgwYUFFVVaX27Nnj6XA4Tq9atarzDTfccKKtsnfu3Om3a9eu3f7+/rWJiYmO66+/vsjf37/2gw8+6Ox0OjO9vLz0zTff3PP1118PuuuuuwrLy8st8fHx5S+++OL3IiJ//vOfgzdt2pR9/lMIvvnmG+/6xkhISCg/evSoR10xLigosLbVWtD2OJUPAICb+eKLLwInTJhwoq7cdenS5SfPz7zhhhuOv/POO51/+9vf/vDRRx91Wr16dZucihcRGTJkSHHXrl1rRETGjRt3YuPGjf42m01nZGT4JiQkxIqIVFRUWEJDQ6tFRKxWq9x6661NFuPPP/88oL4xpkyZcjI3N9dr1qxZPSZMmFB044038i5SJkYxBQDAzWitRSnV4PUib7nllhOTJ0/uPXXq1BNKKenXr19lW2UrpS74XGutJk+eXPjKK68cOX97T0/PWput6brS2BgZGRl7Pvroo8BXX301dPXq1Z3/8pe/5LRiCXAhiikAAAaqPn26uqWvpG9oPJunZ6PbjBkzpvimm27q+/DDD+d17dq1Ji8v7yent+Pi4iotFos89thj3W+88cbjbTU3EZEtW7YE5uXlWf38/Go/++yzjitWrMjx8/OrnTRpUt+HH344LywsrDovL89aVFRktdvtFzwvws/Pr6aoqMjSrVu3C9ZU3xgBAQG1Xl5etbfeeutJu91eedttt0W25XrQtiimAAAYqK2vOdpUKRURSU5Orli4cOHRoUOHxlgsFh0fH1/Wq1evn5TASZMmHX/iiSfCn3766QuOQLZGcnJy6ZQpUyJzcnK8U1NTC+teSPXoo48eGTFihL22tlY8PDx0WlraofqK6axZswrGjh0bFRoaWrVt27bsutuTkpIq6hvD19e39vbbb4+ora1VIiJLliw53JbrQduimAIA4IbuvvvuwrvvvrvBa5YuWbIkb8mSJXnn3vbvf/87q+7jI0eO7Gps/LKysu0iItHR0afrXnh0zz33FN5zzz31Zs6ePfvE7NmzL3guad04dR555JFjjzzyyI+vHjx3Hg2NsWfPnr2NzRXmYTF6AgAAAIAIR0wBAEAL/fDDD9bhw4dHn3/7xo0bs+peeQ9cDIopAADtq7a2tlZZLJYGXxV/qejatWtNZmbmHqPngUvH2ef61jZ0P6fyAQBoXxn5+fkd6l6MA7iL2tpalZ+f30FEMhrahiOmAAC0o+rq6jt++OGHFT/88EO8cIAI7qVWRDKqq6vvaGgDiikAAO0oKSnpmIhMNHoegBnxLzUAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgCk0WUyVUiuVUseUUhnn3PasUipTKbVTKfWRUqrjxQZbg4Mvdpc2Gd+IXHdaq5G54hfq0tx6xzcik9z2yTVore72c2tErk+gp0szXT0+cDlTWuvGN1DqahEpFZFVWuv4s7eNFpH1WutqpdTTIiJa6webCktOTtZOp7P1swYA4BKglErXWicbPQ/gUtHkEVOt9Vcicvy82/6hta4+++m/RCTcBXMDAACAG2mL55jeJiJrG7pTKTVHKeVUSjnz8/PbIA4AAACXo1YVU6XUIyJSLSLvNrSN1voNrXWy1jo5JCSkNXEAAAC4jNlauqNSapaIjBeREbqpJ6rWI3vIUKkpKGhpfJOswcFi37LZFLnutFYjc+XZKJFTx1yWK36hIg/sMz6T3PbJNWit/Ny2MRN9bQE0rUXFVCk1RkQeFJFhWuuylozhyl+AjY1vRK47rdXIXJf+oWlofCMyyW2fXIPWys9tGzPR1xZA05pzuag/i8g/RSRaKXVYKXW7iLwsIgEisk4p9V+l1OsunicAAAAuc00eMdVaT6vn5rdcMBcAAAC4Md75CQAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmIJhxdQaHGzI+EbkutNajcwVv1CX5tY7vhGZ5LZPrkFr5ee2jZnoawugaUpr3W5hycnJ2ul0tlseAABGUkqla62TjZ4HcKngVD4AAABMgWIKAAAAU6CYAgAAwBRsRgVnDxkqNQUFLhvfGhws9i2bTZHrTmsVEZFno0ROHXNZrviFijywzxy57rRWd8s1aK3DVw+XwopCl8UGeQfJxikbTZPrTl9bAE0z7IipKwtTY+MbketOaxUR1/7Cb2x8I3Ldaa3ulmvQWl1ZDhsb36hcd/raAmgap/IBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmEKTxVQptVIpdUwplXHObZ2VUuuUUvvO/r/TxQZbg4Mvdpc2Gd+IXHdaq4iI+IW6NLfB8Y3Idae1uluuQWsN8g5yaWxD4xuV605fWwBNU1rrxjdQ6moRKRWRVVrr+LO3PSMix7XWTymlHhKRTlrrB5sKS05O1k6nsw2mDQCA+Sml0rXWyUbPA7hUNHnEVGv9lYgcP+/m60Xkj2c//qOI3NC20wIAAIC7aelzTLtorY+KiJz9f4PnLZRSc5RSTqWUMz8/v4VxAAAAuNy5/MVPWus3tNbJWuvkkJAQV8cBAADgEmVr4X55SqluWuujSqluInLsYgd4bc7NUlZ0soXxTfPt0FHufOOdC27PHjJUagoKXJZrDQ4W+5bNhmcamSvPRomcuuhviebzCxV5YJ8pct3tazt89XAprCh0WW6Qd5BsnLLRFLnutFYjc1cu3iLlxaddlusT6Cm3PTPkpzca9TsKQJNaesT07yIy6+zHs0Tkbxc7gCtLaWPju/KPeUPjG5FpZK5Lf+E3Nr4Bue72tXVlcWlsfCNy3WmtRua6spQ2OL5Rv6MANKk5l4v6s4j8U0SilVKHlVK3i8hTIjJKKbVPREad/RwAAABosSZP5WutpzVw14g2ngsAAADcGO/8BAAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATMGwYurboaMh41uDg12aW9/4RmQamSt+oS7NbXB8A3Ld7Wsb5B3k0tyGxjci153WamSuT6CnS3PrHd+o31EAmqS01u0WlpycrJ1OZ7vlAQBgJKVUutY62eh5AJcKTuUDAADAFCimAAAAMAWKKQAAAEzBZlTwa3NulrKiky4b37dDR7nzjXcuuD17yFCpKShwWa41OFjsWzYbnklu++S601qNzB2+ergUVhS6LDfIO0g2TtloeKaRuSsXb5Hy4tMuy/UJ9JTbnhlijtxno0ROHXNZpviFijywz3XjA5cxw46YurKUNja+K/+oNjS+EZnktk+uO63VyFxXFrWGxjci08hcV5bDxsY3JNeVpbQ9xgcuY5zKBwAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKrSqmSqn7lVK7lVIZSqk/K6W8m7uvb4eOrYlu8fjW4GCX5tY3vhGZ5LZPrjut1cjcIO8gl+bWN74RmUbm+gR6ujS3ofENyfULdWmmy8cHLmNKa92yHZUKE5EtIuLQWpcrpf5XRD7TWr/d0D7Jycna6XS2KA8AgEuNUipda51s9DyAS0VrT+XbRMRHKWUTEV8R+b71UwIAAIA7anEx1VofEZHnROSQiBwVkSKt9T/O304pNUcp5VRKOfPz81s+UwAAAFzWWlxMlVKdROR6EYkUke4i4qeUuvn87bTWb2itk7XWySEhIS2fKQAAAC5rtlbsO1JEvtNa54uIKKX+KiKDROSd5uz82pybpazoZCviG+fboaPc+caFUzEi16i1Zg8ZKjUFBS7LtQYHi33LZrfOdae1Gpm7cvEWKS8+7bJcn0BPue2ZIYZniogMXz1cCisKXZYb5B0kG6dsvOB2o9brTl9bAE1rzXNMD4nIlUopX6WUEpERIrK3uTu7sqg1Nr4RuUat1ZUForHx3SnXndZqZK4rS0RD4xuRKSIuLaWNjW/Uet3pawugaa15juk2EflARL4RkV1nx3qjjeYFAAAAN9OaU/mitX5cRB5vo7kAAADAjfHOTwAAADAFiikAAABMgWIKAAAAU6CYAgAAwBQopgAAADAFiikAAABMgWIKAAAAU6CYAgAAwBQopgAAADAFiikAAABMgWIKAAAAU6CYAgAAwBQopgAAADAFiikAAABMgWIKAAAAU6CYAgAAwBQopgAAADAFiikAAABMgWIKAAAAU6CYAgAAwBQMK6a+HToaMr4RuUat1Roc7NLchsZ3p1x3WquRuT6Bni7NrW98IzJFRIK8g1ya29D4Rq3Xnb62AJqmtNbtFpacnKydTme75QEAYCSlVLrWOtnoeQCXCk7lAwAAwBQopgAAADAFiikAAABMwWZU8GtzbpayopMuG9+3Q0e58413TJFr1FqzhwyVmoICl+Vag4PFvmWzW+cmP7lOCkpPuywz2N9TnI+OuuD2lYu3SHmx63J9Aj3ltmeGuHWuO63VyFxDfj8+GyVy6pjLMsUvVOSBfa4bH7iMGXbE1JW/iBob34hco9bqypLW2PjulOvKUtrY+K4sEI2N70657rRWI3MN+f3oylLaHuMDlzFO5QMAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwhVYVU6VUR6XUB0qpTKXUXqXUVc3d17dDx9ZEt3h8I3KNWqs1ONiluQ2N7065wf6eLs1saHyfQNfmNjS+O+W601qNzDXk96NfqEszXT4+cBlTWuuW76zUH0Vks9Z6hVLKU0R8tdYnG9o+OTlZO53OFucBAHApUUqla62TjZ4HcKmwtXRHpVSgiFwtIreKiGitT4vI6baZFgAAANxNa07l9xaRfBH5g1Jqu1JqhVLK7/yNlFJzlFJOpZQzPz+/FXEAAAC4nLWmmNpEZICIvKa1ThSRUyLy0Pkbaa3f0Fona62TQ0JCWhEHAACAy1mLT+WLyGEROay13nb28w+knmLakNfm3CxlRSdbEd843w4d5c433jFFrjut1d1y3WmtIiIrF2+R8mLXPWPHJ9BTbntmiCly3WmtRuZmDxkqNQUFLsu1BgeLfctmwzMBNE+Lj5hqrX8QkVylVPTZm0aIyJ7m7u/KP6qNjW9Erjut1d1y3WmtIuLS4tLY+EbkutNajcx1ZUFsaHwjMgE0T2uOmIqI3C0i7559Rf63IvKL1k8JAAAA7qhVxVRr/V8R4TIYAAAAaDXe+QkAAACmQDEFAACAKVBMAQAAYAoUUwAAAJgCxRQAAACmQDEFAACAKVBMAQAAYAoUUwAAAJgCxRQAAACmQDEFAACAKVBMAQAAYAoUUwAAAJgCxRQAAACmQDEFAACAKVBMAQAAYAoUUwAAAJgCxRQAAACmQDEFAACAKVBMAQAAYAoUUwAAAJiCYcXUt0NHQ8Y3Ited1upuue60VhERn0BPl+Y2NL4Rue60ViNzrcHBLs2tb3wjMgE0j9Jat1tYcnKydjqd7ZYHAICRlFLpWutko+cBXCo4lQ8AAABToJgCAADAFCimAAAAMAWbUcGvzblZyopOumx83w4d5c433jFFrjut1d1y3WmtIiIrF2+R8uLTLsv1CfSU254ZYopcd1qrkbnZQ4ZKTUGBy3KtwcFi37LZ8EwAzWPYEVNX/lFtbHwjct1pre6W605rFRGXFpfGxjci153WamSuKwtiQ+MbkQmgeTiVDwAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUWl1MlVJWpdR2pdSai9nPt0PH1ka3aHwjct1pre6W605rFRHxCfR0aW5D4xuR605rNTLXGhzs0tz6xjciE0DzKK116wZQaoGIJItIoNZ6fGPbJicna6fT2ao8AAAuFUqpdK11stHzAC4VrTpiqpQKF5FxIrKibaYDAAAAd9XaU/kvishiEaltaAOl1ByllFMp5czPz29lHAAAAC5XLS6mSqnxInJMa53e2HZa6ze01sla6+SQkJCWxgEAAOAyZ2vFvoNFZKJS6joR8RaRQKXUO1rrm5uzc/KT66Sg9HQr4hsX7O8pzkdHmSL3tTk3S1nRSZdl+nboKHe+8c4FtxuVK89GiZw65rJc8QsVeWDfBTcbsV6jHuPhq4dLYUWhy3KDvINk45SNpslduXiLlBe77ufWJ9BTbntmiOGZIiLZQ4ZKTUGBy3KtwcFi37L5gtvdab1GPcYAmtbiI6Za619prcO11hEiMlVE1je3lIqIS8thY+MbkevK4tLY+EblurSUNjK+Ees16jF2ZTlsbHyjcl1ZmBoa34hMEXFpYWpsfHdar1GPMYCmcR1TAAAAmEJrTuX/SGu9UUQ2tsVYAAAAcE8cMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZgWDEN9vc0ZHwjcn07dHRpZkPjG5UrfqEuzW1ofCPWa9RjHOQd5NLchsY3Ktcn0LU/t/WNb0SmiIg1ONiluQ2N707rNeoxBtA0pbVut7Dk5GTtdDrbLQ8AACMppdK11slGzwO4VHAqHwAAAKZAMQUAAIApUEwBAABgCjajgpOfXCcFpaddNn6wv6c4Hx1lilx3WquIiDwbJXLqmMtyxS9U5IF95sg1aK3DVw+XwopCl8UGeQfJxikbTZO7cvEWKS923feyT6Cn3PbMEMMzyW2fXKO+jwE0zbAjpq4sTI2Nb0SuO61VRFxb1Bob34hcg9bqyj+qjY1vVK4ri0tD4xuRSW775Br1fQygaZzKBwAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKFFMAAACYAsUUAAAApkAxBQAAgClQTAEAAGAKLS6mSqkeSqkNSqm9SqndSql7L2b/YH/Plka3anwjct1prSIi4hfq0twGxzci16C1BnkHuTS2ofGNyvUJdO33cn3jG5FJbvvkGvV9DKBpSmvdsh2V6iYi3bTW3yilAkQkXURu0FrvaWif5ORk7XQ6WzZTAAAuMUqpdK11stHzAC4VLT5iqrU+qrX+5uzHJSKyV0TC2mpiAAAAcC9t8hxTpVSEiCSKyLZ67pujlHIqpZz5+fltEQcAAIDLUKuLqVLKX0Q+FJH7tNbF59+vtX5Da52stU4OCQlpbRwAAAAuU7bW7KyU8pAzpfRdrfVfL2bf5CfXSUHp6dbENyrY31Ocj44yRa47rdXIXHk2SuTUMZflil+oyAP7jM80MHf46uFSWFHostgg7yDZOGWjKXKNWuvKxVukvNh1Pz8+gZ5y2zND3DrXqK8tgKa15lX5SkTeEpG9WuvnL3Z/VxaXxsY3Ited1mpkrkuLWkPjG5FpYK4r/5g3Nr4RuUat1ZUlrbHx3SnXqK8tgKa15lT+YBG5RUSuVUr99+x/17XRvAAAAOBmWnwqX2u9RURUG84FAAAAbox3fgIAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZAMQUAAIApUEwBAABgChRTAAAAmALFFAAAAKZgWDEN9vc0ZHwjct1prUbmil+oS3PrHd+ITANzg7yDXBrb0PhG5Bq1Vp9A1/78NDS+O+Ua9bUF0DSltW63sOTkZO10OtstDwAAIyml0rXWyUbPA7hUcCofAAAApkAxBQAAgClQTAEAAGAKNqOCk59cJwWlp102frC/pzgfHWWKXHdaq9vlPhslcuqYyzLFL1TkgX0X3m5Q7vDVw6WwotBlsUHeQbJxykZT5Bq11pWLt0h5seu+j30CPeW2Z4a4da5RawXQNMOOmLqyQDQ2vhG57rRWt8t1ZTlsbHyDcl1Z1Bob34hco9bqysLU2PjulGvUWgE0jVP5AAAAMAWKKQAAAEyBYgoAAABToJgCAADAFCimAAAAMAWKKQAAAEyBYgoAAABToJgCAADAFCimAAAAMAWKKQAAAEyBYgoAAABToJgCAADAFCimAAAAMAWKKQAAAEyBYgoAAABToJgCAADAFCimAAAAMAWKKQAAAEyBYgoAAABToJgCAADAFCimAAAAMAWKKQAAAEyhVcVUKTVGKZWllNqvlHroYvYN9vdsTXSLxzci153W6na5fqEuzWxwfINyg7yDXBrb0PhG5Bq1Vp9A134fNzS+O+UatVYATVNa65btqJRVRLJFZJSIHBaR/4jINK31nob2SU5O1k6ns0V5AABcapRS6VrrZKPnAVwqWnPENEVE9mutv9VanxaR90Xk+raZFgAAANyNrRX7holI7jmfHxaRgedvpJSaIyJzzn5aqZTKaEXmpSRYRAqMnkQ7Yr2XL3daq4h7rded1ipizHp7tXMecElrTTFV9dx2wfMCtNZviMgbIiJKKae7nNJwp7WKsN7LmTutVcS91utOaxVxv/UCl6LWnMo/LCI9zvk8XES+b910AAAA4K5aU0z/IyJRSqlIpZSniEwVkb+3zbQAAADgblp8Kl9rXa2UuktEvhARq4is1FrvbmK3N1qadwlyp7WKsN7LmTutVcS91utOaxVxv/UCl5wWXy4KAAAAaEu88xMAAABMgWIKAAAAU2iXYtqaty691CileiilNiil9iqldiul7jV6Tq6mlLIqpbYrpdYYPRdXU0p1VEp9oJTKPPs1vsroObmKUur+s9/DGUqpPyulvI2eU1tSSq1USh0799rKSqnOSql1Sql9Z//fycg5tqUG1vvs2e/lnUqpj5RSHQ2cYpupb63n3LdIKaWVUsFGzA1A41xeTM++dekrIjJWRBwiMk0p5XB1roGqRWSh1jpWRK4UkV9e5usVEblXRPYaPYl28pKIfK61jhGRBLlM162UChORe0QkWWsdL2de4DjV2Fm1ubdFZMx5tz0kIv9Xax0lIv/37OeXi7flwvWuE5F4rXV/OfMW079q70m5yNty4VpFKdVDzryN9qH2nhCA5mmPI6Zu9dalWuujWutvzn5cImeKS5ixs3IdpVS4iIwTkRVGz8XVlFKBInK1iLwlIqK1Pq21PmnopFzLJiI+SimbiPjKZXadYq31VyJy/LybrxeRP579+I8ickN7zsmV6luv1vofWuvqs5/+S85cj/qS18DXVkTkBRFZLPW8GQwAc2iPYlrfW5detkXtXEqpCBFJFJFtBk/FlV6UM7/oaw2eR3voLSL5IvKHs09dWKGU8jN6Uq6gtT4iIs/JmSNLR0WkSGv9D2Nn1S66aK2Pipz5R6aIhBo8n/Z0m4isNXoSrqKUmigiR7TWO4yeC4CGtUcxbdZbl15ulFL+IvKhiNyntS42ej6uoJQaLyLHtNbpRs+lndhEZICIvKa1ThSRU3J5ner90dnnVl4vIpEi0l1E/JRSNxs7K7iKUuoROfM0pHeNnosrKKV8ReQREXnM6LkAaFx7FFO3e+tSpZSHnCml72qt/2r0fFxosIhMVErlyJmnaFyrlHrH2Cm51GEROay1rjsC/oGcKaqXo5Ei8p3WOl9rXSUifxWRQQbPqT3kKaW6iYic/f8xg+fjckqpWSIyXkRm6Mv3wtZ95Mw/snac/X0VLiLfKKW6GjorABdoj2LqVm9dqpRScuY5iHu11s8bPR9X0lr/SmsdrrWOkDNf1/Va68v2qJrW+gcRyVVKRZ+9aYSI7DFwSq50SESuVEr5nv2eHiGX6Qu9zvN3EZl19uNZIvI3A+fickqpMSLyoIhM1FqXGT0fV9Fa79Jah2qtI87+vjosIgPO/kwDMBGXF9OzT6yve+vSvSLyv81469JL2WARuUXOHD3879n/rjN6Umgzd4vIu0qpnSJyhYj81tjpuMbZo8IfiMg3IrJLzvyuuKzezlEp9WcR+aeIRCulDiulbheRp0RklFJqn5x59fZTRs6xLTWw3pdFJEBE1p39XfW6oZNsIw2sFcAlgLckBQAAgCnwzk8AAAAwBYopAAAATIFiCgAAAFOgmAIAAMAUKKYAAAAwBYopAAAATIFiCgAAAFP4fzS+nOvtLTwuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Z = np.zeros((size, size))\n",
    "plt.figure(figsize=(8, 8))\n",
    "for i in np.arange(som._weights.shape[0]):\n",
    "    for j in np.arange(som._weights.shape[1]):\n",
    "        feature = np.argmax(W[i, j , :])\n",
    "        plt.plot([j+.5], [i+.5], 'o', color='C'+str(feature),\n",
    "                 marker='s', markersize=24)\n",
    "\n",
    "legend_elements = [Patch(facecolor='C'+str(i),\n",
    "                         edgecolor='w',\n",
    "                         label=f) for i, f in enumerate(feature_names)]\n",
    "\n",
    "plt.legend(handles=legend_elements,\n",
    "           loc='center left',\n",
    "           bbox_to_anchor=(1, .95))\n",
    "        \n",
    "plt.xlim([0, size])\n",
    "plt.ylim([0, size])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}