{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy as sp\n",
    "from scipy.linalg import eigh\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as matplotlib\n",
    "import networkx as nx\n",
    "from networkx.algorithms import bipartite\n",
    "import random as random\n",
    "import seaborn as sns # gives a better presentation for matplotlib\n",
    "sns.set()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "Anyi_Data = pd.read_excel('link_table.xlsx').set_index('ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>source</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ID</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>822</th>\n",
       "      <td>173</td>\n",
       "      <td>356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>823</th>\n",
       "      <td>195</td>\n",
       "      <td>503</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>824</th>\n",
       "      <td>195</td>\n",
       "      <td>515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>825</th>\n",
       "      <td>195</td>\n",
       "      <td>516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>826</th>\n",
       "      <td>195</td>\n",
       "      <td>426</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>827 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     source  target\n",
       "ID                 \n",
       "0         0     263\n",
       "1         0     262\n",
       "2         0     256\n",
       "3         0     228\n",
       "4         0     227\n",
       "..      ...     ...\n",
       "822     173     356\n",
       "823     195     503\n",
       "824     195     515\n",
       "825     195     516\n",
       "826     195     426\n",
       "\n",
       "[827 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Anyi_Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "B = nx.from_pandas_edgelist(Anyi_Data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.is_bipartite(B)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "lines, nodes = nx.bipartite.sets(B)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "660"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nodes)+len(lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0038028233779371866"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nx.density(B)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Adjacency_matrix = nx.bipartite.biadjacency_matrix(B,lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "cls_c = nx.bipartite.closeness_centrality(B,lines)\n",
    "dg_c = nx.bipartite.degree_centrality(B,nodes)\n",
    "btn_c = nx.bipartite.betweenness_centrality(B,nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics = pd.DataFrame.from_dict(cls_c,orient= 'index',columns = ['closeness_c'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics['degree_c'] = pd.DataFrame.from_dict(dg_c,orient= 'index')\n",
    "metrics['betweenness_c'] = pd.DataFrame.from_dict(btn_c,orient= 'index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics['pagerank'] = pd.DataFrame.from_dict(nx.pagerank(B),orient= 'index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>closeness_c</th>\n",
       "      <th>degree_c</th>\n",
       "      <th>betweenness_c</th>\n",
       "      <th>pagerank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.129165</td>\n",
       "      <td>0.013575</td>\n",
       "      <td>0.032125</td>\n",
       "      <td>0.003225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.111564</td>\n",
       "      <td>0.011312</td>\n",
       "      <td>0.010479</td>\n",
       "      <td>0.002989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.111706</td>\n",
       "      <td>0.018100</td>\n",
       "      <td>0.026519</td>\n",
       "      <td>0.004715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.095717</td>\n",
       "      <td>0.004525</td>\n",
       "      <td>0.003038</td>\n",
       "      <td>0.001594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.131611</td>\n",
       "      <td>0.006787</td>\n",
       "      <td>0.024661</td>\n",
       "      <td>0.001588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>0.151850</td>\n",
       "      <td>0.018349</td>\n",
       "      <td>0.030163</td>\n",
       "      <td>0.002226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>0.151057</td>\n",
       "      <td>0.018349</td>\n",
       "      <td>0.013486</td>\n",
       "      <td>0.002188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>0.180269</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>0.122277</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800</th>\n",
       "      <td>0.162963</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.006173</td>\n",
       "      <td>0.001142</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>660 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     closeness_c  degree_c  betweenness_c  pagerank\n",
       "0       0.129165  0.013575       0.032125  0.003225\n",
       "1       0.111564  0.011312       0.010479  0.002989\n",
       "2       0.111706  0.018100       0.026519  0.004715\n",
       "3       0.095717  0.004525       0.003038  0.001594\n",
       "4       0.131611  0.006787       0.024661  0.001588\n",
       "..           ...       ...            ...       ...\n",
       "796     0.151850  0.018349       0.030163  0.002226\n",
       "797     0.151057  0.018349       0.013486  0.002188\n",
       "798     0.180269  0.004587       0.000000  0.000769\n",
       "799     0.122277  0.004587       0.000000  0.000695\n",
       "800     0.162963  0.009174       0.006173  0.001142\n",
       "\n",
       "[660 rows x 4 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics.to_csv('bipartite.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "new = pd.DataFrame(np.array(range(metrics.index.max()+1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "new = new.merge(metrics,left_index=True, right_index=True, how='left').drop(0,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "new.to_csv('new.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "closeness_c      0.095821\n",
       "degree_c         0.006787\n",
       "betweenness_c    0.000052\n",
       "pagerank         0.001815\n",
       "Name: 5, dtype: float64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.loc[5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        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>closeness_c</th>\n",
       "      <th>degree_c</th>\n",
       "      <th>betweenness_c</th>\n",
       "      <th>pagerank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>closeness_c</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.254155</td>\n",
       "      <td>0.340935</td>\n",
       "      <td>-0.123765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>degree_c</th>\n",
       "      <td>0.254155</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.542326</td>\n",
       "      <td>0.770618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>betweenness_c</th>\n",
       "      <td>0.340935</td>\n",
       "      <td>0.542326</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.534098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pagerank</th>\n",
       "      <td>-0.123765</td>\n",
       "      <td>0.770618</td>\n",
       "      <td>0.534098</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               closeness_c  degree_c  betweenness_c  pagerank\n",
       "closeness_c       1.000000  0.254155       0.340935 -0.123765\n",
       "degree_c          0.254155  1.000000       0.542326  0.770618\n",
       "betweenness_c     0.340935  0.542326       1.000000  0.534098\n",
       "pagerank         -0.123765  0.770618       0.534098  1.000000"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "G1 = nx.projected_graph(B,nodes)\n",
    "G2 = nx.bipartite.weighted_projected_graph(B,nodes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "G3 = nx.bipartite.weighted_projected_graph(B,lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def graph_metrics(G, annex = ''):\n",
    "    cls = nx.closeness_centrality(G)\n",
    "    dg = nx.degree_centrality(G)\n",
    "    btn = nx.betweenness_centrality(G)\n",
    "    prk = nx.pagerank(G)\n",
    "    \n",
    "    G_metrics = pd.DataFrame.from_dict(cls, orient= 'index',columns = ['closeness'+annex])\n",
    "    G_metrics['degree'+annex] = pd.DataFrame.from_dict(dg, orient = 'index')\n",
    "    G_metrics['betweenness'+annex] = pd.DataFrame.from_dict(btn, orient = 'index')\n",
    "    G_metrics['pagerank'+annex] = pd.DataFrame.from_dict(prk, orient = 'index')\n",
    "    \n",
    "    return G_metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd1 = graph_metrics(G1,'_Z')\n",
    "pd2 = graph_metrics(G2,'_P')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd3 = graph_metrics(G3,'_L')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_P = metrics.loc[nodes]\n",
    "metrics_P = metrics_P.merge(pd1, left_index=True, right_index = True).merge(pd2, left_index = True, right_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>closeness_c</th>\n",
       "      <th>degree_c</th>\n",
       "      <th>betweenness_c</th>\n",
       "      <th>pagerank</th>\n",
       "      <th>closeness_Z</th>\n",
       "      <th>degree_Z</th>\n",
       "      <th>betweenness_Z</th>\n",
       "      <th>pagerank_Z</th>\n",
       "      <th>closeness_P</th>\n",
       "      <th>degree_P</th>\n",
       "      <th>betweenness_P</th>\n",
       "      <th>pagerank_P</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>0.149335</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.003070</td>\n",
       "      <td>0.001170</td>\n",
       "      <td>0.178832</td>\n",
       "      <td>0.015873</td>\n",
       "      <td>0.002671</td>\n",
       "      <td>0.002470</td>\n",
       "      <td>0.178832</td>\n",
       "      <td>0.015873</td>\n",
       "      <td>0.002671</td>\n",
       "      <td>0.002365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>0.128987</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.154304</td>\n",
       "      <td>0.006803</td>\n",
       "      <td>0.000067</td>\n",
       "      <td>0.001433</td>\n",
       "      <td>0.154304</td>\n",
       "      <td>0.006803</td>\n",
       "      <td>0.000067</td>\n",
       "      <td>0.001679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>0.127996</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000755</td>\n",
       "      <td>0.153072</td>\n",
       "      <td>0.004535</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001080</td>\n",
       "      <td>0.153072</td>\n",
       "      <td>0.004535</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>0.150850</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.003862</td>\n",
       "      <td>0.001175</td>\n",
       "      <td>0.180368</td>\n",
       "      <td>0.013605</td>\n",
       "      <td>0.002953</td>\n",
       "      <td>0.002373</td>\n",
       "      <td>0.180368</td>\n",
       "      <td>0.013605</td>\n",
       "      <td>0.002953</td>\n",
       "      <td>0.002599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>0.129078</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.006079</td>\n",
       "      <td>0.001381</td>\n",
       "      <td>0.154412</td>\n",
       "      <td>0.009070</td>\n",
       "      <td>0.004535</td>\n",
       "      <td>0.001951</td>\n",
       "      <td>0.154412</td>\n",
       "      <td>0.009070</td>\n",
       "      <td>0.004535</td>\n",
       "      <td>0.001886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>796</th>\n",
       "      <td>0.151850</td>\n",
       "      <td>0.018349</td>\n",
       "      <td>0.030163</td>\n",
       "      <td>0.002226</td>\n",
       "      <td>0.181856</td>\n",
       "      <td>0.038549</td>\n",
       "      <td>0.032126</td>\n",
       "      <td>0.005256</td>\n",
       "      <td>0.181856</td>\n",
       "      <td>0.038549</td>\n",
       "      <td>0.032126</td>\n",
       "      <td>0.005140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>797</th>\n",
       "      <td>0.151057</td>\n",
       "      <td>0.018349</td>\n",
       "      <td>0.013486</td>\n",
       "      <td>0.002188</td>\n",
       "      <td>0.180590</td>\n",
       "      <td>0.020408</td>\n",
       "      <td>0.009978</td>\n",
       "      <td>0.003541</td>\n",
       "      <td>0.180590</td>\n",
       "      <td>0.020408</td>\n",
       "      <td>0.009978</td>\n",
       "      <td>0.004036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>798</th>\n",
       "      <td>0.180269</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000769</td>\n",
       "      <td>0.215332</td>\n",
       "      <td>0.006803</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.215332</td>\n",
       "      <td>0.006803</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>799</th>\n",
       "      <td>0.122277</td>\n",
       "      <td>0.004587</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000695</td>\n",
       "      <td>0.145401</td>\n",
       "      <td>0.009070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001400</td>\n",
       "      <td>0.145401</td>\n",
       "      <td>0.009070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800</th>\n",
       "      <td>0.162963</td>\n",
       "      <td>0.009174</td>\n",
       "      <td>0.006173</td>\n",
       "      <td>0.001142</td>\n",
       "      <td>0.194874</td>\n",
       "      <td>0.045351</td>\n",
       "      <td>0.006428</td>\n",
       "      <td>0.003747</td>\n",
       "      <td>0.194874</td>\n",
       "      <td>0.045351</td>\n",
       "      <td>0.006428</td>\n",
       "      <td>0.003830</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>442 rows × 12 columns</p>\n",
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      ],
      "text/plain": [
       "     closeness_c  degree_c  betweenness_c  pagerank  closeness_Z  degree_Z  \\\n",
       "218     0.149335  0.009174       0.003070  0.001170     0.178832  0.015873   \n",
       "222     0.128987  0.009174       0.000089  0.001241     0.154304  0.006803   \n",
       "223     0.127996  0.004587       0.000000  0.000755     0.153072  0.004535   \n",
       "224     0.150850  0.009174       0.003862  0.001175     0.180368  0.013605   \n",
       "225     0.129078  0.009174       0.006079  0.001381     0.154412  0.009070   \n",
       "..           ...       ...            ...       ...          ...       ...   \n",
       "796     0.151850  0.018349       0.030163  0.002226     0.181856  0.038549   \n",
       "797     0.151057  0.018349       0.013486  0.002188     0.180590  0.020408   \n",
       "798     0.180269  0.004587       0.000000  0.000769     0.215332  0.006803   \n",
       "799     0.122277  0.004587       0.000000  0.000695     0.145401  0.009070   \n",
       "800     0.162963  0.009174       0.006173  0.001142     0.194874  0.045351   \n",
       "\n",
       "     betweenness_Z  pagerank_Z  closeness_P  degree_P  betweenness_P  \\\n",
       "218       0.002671    0.002470     0.178832  0.015873       0.002671   \n",
       "222       0.000067    0.001433     0.154304  0.006803       0.000067   \n",
       "223       0.000000    0.001080     0.153072  0.004535       0.000000   \n",
       "224       0.002953    0.002373     0.180368  0.013605       0.002953   \n",
       "225       0.004535    0.001951     0.154412  0.009070       0.004535   \n",
       "..             ...         ...          ...       ...            ...   \n",
       "796       0.032126    0.005256     0.181856  0.038549       0.032126   \n",
       "797       0.009978    0.003541     0.180590  0.020408       0.009978   \n",
       "798       0.000000    0.001142     0.215332  0.006803       0.000000   \n",
       "799       0.000000    0.001400     0.145401  0.009070       0.000000   \n",
       "800       0.006428    0.003747     0.194874  0.045351       0.006428   \n",
       "\n",
       "     pagerank_P  \n",
       "218    0.002365  \n",
       "222    0.001679  \n",
       "223    0.001008  \n",
       "224    0.002599  \n",
       "225    0.001886  \n",
       "..          ...  \n",
       "796    0.005140  \n",
       "797    0.004036  \n",
       "798    0.001115  \n",
       "799    0.001340  \n",
       "800    0.003830  \n",
       "\n",
       "[442 rows x 12 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics_P"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_L = metrics.loc[lines]\n",
    "metrics_L = metrics_L.merge(pd3, left_index=True, right_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.002549</td>\n",
       "      <td>0.006502</td>\n",
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       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>0.120628</td>\n",
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       "      <td>0.011613</td>\n",
       "      <td>0.001330</td>\n",
       "      <td>0.181742</td>\n",
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       "      <td>0.008783</td>\n",
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       "     closeness_c  degree_c  betweenness_c  pagerank  closeness_L  degree_L  \\\n",
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       "217     0.107327  0.006787       0.011289  0.001862     0.161338  0.013825   \n",
       "\n",
       "     betweenness_L  pagerank_L  \n",
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       "2         0.013978    0.006551  \n",
       "3         0.000000    0.001483  \n",
       "4         0.015110    0.007812  \n",
       "..             ...         ...  \n",
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       "216       0.001058    0.003850  \n",
       "217       0.009512    0.003530  \n",
       "\n",
       "[218 rows x 8 columns]"
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     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "metrics_L"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
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       "      <td>0.194051</td>\n",
       "      <td>1.000000</td>\n",
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       "      <td>0.533094</td>\n",
       "      <td>0.477161</td>\n",
       "      <td>0.492349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>degree_Z</th>\n",
       "      <td>0.532981</td>\n",
       "      <td>0.504101</td>\n",
       "      <td>0.499845</td>\n",
       "      <td>0.425562</td>\n",
       "      <td>0.533094</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>0.903196</td>\n",
       "      <td>0.533094</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>0.890874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>betweenness_Z</th>\n",
       "      <td>0.478288</td>\n",
       "      <td>0.391484</td>\n",
       "      <td>0.998947</td>\n",
       "      <td>0.339208</td>\n",
       "      <td>0.477161</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.547575</td>\n",
       "      <td>0.477161</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.543571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pagerank_Z</th>\n",
       "      <td>0.503880</td>\n",
       "      <td>0.700475</td>\n",
       "      <td>0.558407</td>\n",
       "      <td>0.636125</td>\n",
       "      <td>0.503453</td>\n",
       "      <td>0.903196</td>\n",
       "      <td>0.547575</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.503453</td>\n",
       "      <td>0.903196</td>\n",
       "      <td>0.547575</td>\n",
       "      <td>0.994154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>closeness_P</th>\n",
       "      <td>0.999878</td>\n",
       "      <td>0.261410</td>\n",
       "      <td>0.485328</td>\n",
       "      <td>0.194051</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.533094</td>\n",
       "      <td>0.477161</td>\n",
       "      <td>0.503453</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.533094</td>\n",
       "      <td>0.477161</td>\n",
       "      <td>0.492349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>degree_P</th>\n",
       "      <td>0.532981</td>\n",
       "      <td>0.504101</td>\n",
       "      <td>0.499845</td>\n",
       "      <td>0.425562</td>\n",
       "      <td>0.533094</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>0.903196</td>\n",
       "      <td>0.533094</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>0.890874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>betweenness_P</th>\n",
       "      <td>0.478288</td>\n",
       "      <td>0.391484</td>\n",
       "      <td>0.998947</td>\n",
       "      <td>0.339208</td>\n",
       "      <td>0.477161</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.547575</td>\n",
       "      <td>0.477161</td>\n",
       "      <td>0.491673</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.543571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pagerank_P</th>\n",
       "      <td>0.492855</td>\n",
       "      <td>0.740852</td>\n",
       "      <td>0.555402</td>\n",
       "      <td>0.673788</td>\n",
       "      <td>0.492349</td>\n",
       "      <td>0.890874</td>\n",
       "      <td>0.543571</td>\n",
       "      <td>0.994154</td>\n",
       "      <td>0.492349</td>\n",
       "      <td>0.890874</td>\n",
       "      <td>0.543571</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               closeness_c  degree_c  betweenness_c  pagerank  closeness_Z  \\\n",
       "closeness_c       1.000000  0.264371       0.486720  0.196626     0.999878   \n",
       "degree_c          0.264371  1.000000       0.414377  0.980422     0.261410   \n",
       "betweenness_c     0.486720  0.414377       1.000000  0.362549     0.485328   \n",
       "pagerank          0.196626  0.980422       0.362549  1.000000     0.194051   \n",
       "closeness_Z       0.999878  0.261410       0.485328  0.194051     1.000000   \n",
       "degree_Z          0.532981  0.504101       0.499845  0.425562     0.533094   \n",
       "betweenness_Z     0.478288  0.391484       0.998947  0.339208     0.477161   \n",
       "pagerank_Z        0.503880  0.700475       0.558407  0.636125     0.503453   \n",
       "closeness_P       0.999878  0.261410       0.485328  0.194051     1.000000   \n",
       "degree_P          0.532981  0.504101       0.499845  0.425562     0.533094   \n",
       "betweenness_P     0.478288  0.391484       0.998947  0.339208     0.477161   \n",
       "pagerank_P        0.492855  0.740852       0.555402  0.673788     0.492349   \n",
       "\n",
       "               degree_Z  betweenness_Z  pagerank_Z  closeness_P  degree_P  \\\n",
       "closeness_c    0.532981       0.478288    0.503880     0.999878  0.532981   \n",
       "degree_c       0.504101       0.391484    0.700475     0.261410  0.504101   \n",
       "betweenness_c  0.499845       0.998947    0.558407     0.485328  0.499845   \n",
       "pagerank       0.425562       0.339208    0.636125     0.194051  0.425562   \n",
       "closeness_Z    0.533094       0.477161    0.503453     1.000000  0.533094   \n",
       "degree_Z       1.000000       0.491673    0.903196     0.533094  1.000000   \n",
       "betweenness_Z  0.491673       1.000000    0.547575     0.477161  0.491673   \n",
       "pagerank_Z     0.903196       0.547575    1.000000     0.503453  0.903196   \n",
       "closeness_P    0.533094       0.477161    0.503453     1.000000  0.533094   \n",
       "degree_P       1.000000       0.491673    0.903196     0.533094  1.000000   \n",
       "betweenness_P  0.491673       1.000000    0.547575     0.477161  0.491673   \n",
       "pagerank_P     0.890874       0.543571    0.994154     0.492349  0.890874   \n",
       "\n",
       "               betweenness_P  pagerank_P  \n",
       "closeness_c         0.478288    0.492855  \n",
       "degree_c            0.391484    0.740852  \n",
       "betweenness_c       0.998947    0.555402  \n",
       "pagerank            0.339208    0.673788  \n",
       "closeness_Z         0.477161    0.492349  \n",
       "degree_Z            0.491673    0.890874  \n",
       "betweenness_Z       1.000000    0.543571  \n",
       "pagerank_Z          0.547575    0.994154  \n",
       "closeness_P         0.477161    0.492349  \n",
       "degree_P            0.491673    0.890874  \n",
       "betweenness_P       1.000000    0.543571  \n",
       "pagerank_P          0.543571    1.000000  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics_P.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Dual Syntax Graph P\\n')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"white\")\n",
    "\n",
    "fig,axes = plt.subplots(2,2,figsize = (15,15),sharex=True, sharey=True)\n",
    "\n",
    "plt.subplot(221)\n",
    "plt.scatter(metrics_P['degree_c'],metrics_P['degree_P'])\n",
    "plt.title('Degree_centrality\\n',size =15)\n",
    "plt.subplot(222)\n",
    "plt.scatter(metrics_P['closeness_c'],metrics_P['closeness_P'])\n",
    "plt.title('Closeness_centrality\\n',size =15)\n",
    "plt.subplot(223)\n",
    "plt.scatter(metrics_P['betweenness_c'],metrics_P['betweenness_P'])\n",
    "plt.title('Betweenness_centrality\\n',size =15)\n",
    "plt.subplot(224)\n",
    "plt.scatter(metrics_P['pagerank'],metrics_P['pagerank_P'])\n",
    "plt.title('Pagerank_centrality\\n',size =15)\n",
    "\n",
    "fig.add_subplot(111, frameon=False)\n",
    "plt.tick_params(labelcolor='none', top=False, bottom=False, left=False, right=False)\n",
    "\n",
    "plt.xlabel('\\nBipartite Graph A',size=15)\n",
    "plt.ylabel('Dual Syntax Graph P\\n',size = 15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats\n",
    "def draw_sub(data,A,B,name):\n",
    "    x1=data[A]\n",
    "    x2=data[B]\n",
    "    corr = stats.spearmanr(x1, x2, nan_policy='omit')\n",
    "    plt.scatter(x1,x2)\n",
    "    xlim1,xlim2 = plt.xlim()\n",
    "    ylim1,ylim2 = plt.ylim()\n",
    "    plt.text(0.65*(xlim2-xlim1)+xlim1, 0.05*(ylim2-ylim1)+ylim1, f\"r value: {corr[0]:.2f}***\\n\\np value: {corr[1]:.2f}\",size=18)\n",
    "    plt.title(name, size=22)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Dual Syntax Graph L\\n')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x1080 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"white\")\n",
    "\n",
    "fig,axes = plt.subplots(2,4,figsize = (30,15),sharex=True, sharey=True)\n",
    "\n",
    "plt.subplot(241)\n",
    "#plt.scatter(metrics_P['degree_c'],metrics_P['degree_P'])\n",
    "#plt.title('Degree_centrality\\n',size =15)\n",
    "draw_sub(metrics_L, 'degree_c', 'degree_L', 'Degree_centrality\\n')\n",
    "\n",
    "plt.subplot(242)\n",
    "#plt.scatter(metrics_P['closeness_c'],metrics_P['closeness_P'])\n",
    "#plt.title('Closeness_centrality\\n',size =15)\n",
    "draw_sub(metrics_L, 'closeness_c', 'closeness_L', 'Closeness_centrality\\n')\n",
    "\n",
    "plt.subplot(243)\n",
    "#plt.scatter(metrics_P['betweenness_c'],metrics_P['betweenness_P'])\n",
    "#plt.title('Betweenness_centrality\\n',size =15)\n",
    "draw_sub(metrics_L, 'betweenness_c', 'betweenness_L', 'Betweenness_centrality\\n')\n",
    "\n",
    "plt.subplot(244)\n",
    "#plt.scatter(metrics_P['pagerank'],metrics_P['pagerank_P'])\n",
    "#plt.title('Pagerank_centrality\\n',size =15)\n",
    "draw_sub(metrics_L, 'pagerank', 'pagerank_L', 'PageRank\\n')\n",
    "\n",
    "plt.subplot(245)\n",
    "#plt.scatter(metrics_L['degree_c'],metrics_L['degree_L'])\n",
    "#plt.title('Degree_centrality\\n',size =15)\n",
    "draw_sub(metrics_P, 'degree_c', 'degree_P', 'Degree_centrality\\n')\n",
    "\n",
    "plt.subplot(246)\n",
    "#plt.scatter(metrics_L['closeness_c'],metrics_L['closeness_L'])\n",
    "#plt.title('Closeness_centrality\\n',size =15)\n",
    "draw_sub(metrics_P, 'closeness_c', 'closeness_P', 'Closeness_centrality\\n')\n",
    "\n",
    "plt.subplot(247)\n",
    "#plt.scatter(metrics_L['betweenness_c'],metrics_L['betweenness_L'])\n",
    "#plt.title('Betweenness_centrality\\n',size =15)\n",
    "draw_sub(metrics_P, 'betweenness_c', 'betweenness_P', 'Betweenness_centrality\\n')\n",
    "\n",
    "plt.subplot(248)\n",
    "#plt.scatter(metrics_L['pagerank'],metrics_L['pagerank_L'])\n",
    "#plt.title('Pagerank_centrality\\n',size =15)\n",
    "draw_sub(metrics_P, 'pagerank', 'pagerank_P', 'PageRank\\n')\n",
    "\n",
    "fig.add_subplot(211, frameon=False)\n",
    "plt.tick_params(labelcolor='none', top=False, bottom=False, left=False, right=False)\n",
    "\n",
    "#plt.xlabel('\\nBipartite Graph A',size=25)\n",
    "plt.ylabel('Primal Syntax Graph P\\n',size = 28)\n",
    "\n",
    "fig.add_subplot(212, frameon=False)\n",
    "plt.tick_params(labelcolor='none', top=False, bottom=False, left=False, right=False)\n",
    "\n",
    "plt.xlabel('\\nBipartite Graph A',size=28)\n",
    "plt.ylabel('Dual Syntax Graph L\\n',size = 28)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "G2_edgelist = nx.to_pandas_edgelist(G2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "G2_edgelist.to_csv('Dual_linkList.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_P.to_csv('Dual_metrics.csv',decimal=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "closeness_c      0.204385\n",
       "degree_c         0.009174\n",
       "betweenness_c    0.033571\n",
       "pagerank         0.001180\n",
       "closeness_Z      0.245000\n",
       "degree_Z         0.029478\n",
       "betweenness_Z    0.033353\n",
       "pagerank_Z       0.003648\n",
       "closeness_P      0.245000\n",
       "degree_P         0.029478\n",
       "betweenness_P    0.033353\n",
       "pagerank_P       0.003621\n",
       "Name: 274, dtype: float64"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics_P.loc[274]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_L.to_csv('Primal_metrics.csv',decimal=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_dual = new.merge(metrics_P,left_index=True, right_index=True, how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_dual.to_csv('new_dual.csv',decimal=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "All_data = pd.read_excel('Synthesis.xlsx', sheet_name='Meta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes_nominated = All_data[['Node_ID','Type']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['closeness_c',\n",
       " 'degree_c',\n",
       " 'betweenness_c',\n",
       " 'pagerank',\n",
       " 'closeness_P',\n",
       " 'degree_P',\n",
       " 'betweenness_P',\n",
       " 'pagerank_P']"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[b for b in list(metrics_P.columns) if b not in ['closeness_Z', 'degree_Z', 'betweenness_Z', 'pagerank_Z']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'metrics_P' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-3-4a87ed614e92>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m All_data = All_data.drop([c for c in [b for b in metrics_P.columns \n\u001b[0m\u001b[1;32m      2\u001b[0m                                       if not b in ['closeness_Z', 'degree_Z', 'betweenness_Z', 'pagerank_Z']]],\n\u001b[1;32m      3\u001b[0m                           axis=1).merge(metrics_P, how='left', left_on = 'Node_ID', right_index = True)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'metrics_P' is not defined"
     ]
    }
   ],
   "source": [
    "All_data = All_data.drop([c for c in [b for b in metrics_P.columns \n",
    "                                      if not b in ['closeness_Z', 'degree_Z', 'betweenness_Z', 'pagerank_Z']]],\n",
    "                          axis=1).merge(metrics_P, how='left', left_on = 'Node_ID', right_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "All_data[['Node_ID']+[c for c in metrics_P.columns]].to_csv('nominated_metrics.csv',decimal=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "All_data = pd.read_excel('Synthesis.xlsx', sheet_name='Meta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ID', '地段', 'Spot_ID', 'Node_ID', 'Street Node', 'Multiple', 'Type',\n",
       "       'Behaviour', 'closeness_c', 'degree_c', 'betweenness_c', 'pagerank',\n",
       "       'closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P',\n",
       "       'R100_Intensity', 'R100整合度', 'R560_Intensity', 'logR56整合度',\n",
       "       'R100_Choice', 'logR100选择度', 'R560_Choice', 'logR560选择度', 'Local_Vote',\n",
       "       'Non-local_Vote', '提名差', 'Representing', 'Gathering', '预测游客数量',\n",
       "       '预测本地人数量', 'Tourist_count', '游客方差', '游客时间', 'Tourist_percentage',\n",
       "       'Local_count', '本地人方差', '本地人时间', 'Local_percentage'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All_data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_corr = All_data[['Node_ID','closeness_c', 'degree_c', 'betweenness_c', 'pagerank',\n",
    "       'closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P', 'R100_Intensity', 'R560_Intensity', \n",
    "       'R100_Choice', 'R560_Choice','Local_Vote','Non-local_Vote', 'Representing', 'Gathering', \n",
    "        'Local_count', 'Local_percentage', 'Tourist_count', 'Tourist_percentage']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_corr = All_data[[\n",
    "       'degree_P', 'closeness_P', 'betweenness_P', 'pagerank_P', \n",
    "                      'Local_Vote','Non-local_Vote', 'Representing', 'Gathering', \n",
    "        'Local_count', 'Local_percentage', 'Tourist_count', 'Tourist_percentage']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 446,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "def test(df):\n",
    "    dfData = df.corr()\n",
    "    dfData = dfData.round(2)\n",
    "    fig,ax = plt.subplots(figsize=(20,20)) # 设置画面大小\n",
    "    sns.heatmap(dfData, annot=True, center=0, square=True, vmax=1, vmin=-1, cmap=\"RdBu_r\")\n",
    "    label_x = ax.get_xticklabels()\n",
    "    plt.setp(label_x, rotation=45, horizontalalignment='right')\n",
    "    plt.show()\n",
    "test(data_corr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "\n",
    "df_corr = pd.DataFrame() # Correlation matrix\n",
    "df_p = pd.DataFrame()  # Matrix of p-values\n",
    "for x in data_corr.columns:\n",
    "    for y in data_corr.columns:\n",
    "        corr = stats.spearmanr(data_corr[x], data_corr[y], nan_policy='omit')\n",
    "        df_corr.loc[x,y] = corr[0]\n",
    "        df_p.loc[x,y] = corr[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from scipy import stats\n",
    "\n",
    "df_corr = pd.DataFrame() # Correlation matrix\n",
    "df_p = pd.DataFrame()  # Matrix of p-values\n",
    "for x in data_corr.columns:\n",
    "    for y in data_corr.columns:\n",
    "        if x==y:\n",
    "            df_corr.loc[x,y] = 1\n",
    "            df_p.loc[x,y] = 0\n",
    "        else:\n",
    "            tmp_data = data_corr[[x,y]].dropna()\n",
    "            corr = stats.pearsonr(tmp_data[x], tmp_data[y])\n",
    "            df_corr.loc[x,y] = corr[0]\n",
    "            df_p.loc[x,y] = corr[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "def heatmap(dfData, vmax = 1, vmin =-1):\n",
    "    dfData = dfData.round(2)\n",
    "    fig,ax = plt.subplots(figsize=(20,20)) # 设置画面大小\n",
    "    sns.heatmap(dfData, annot=True, center=0, square=True, vmax=vmax, vmin=vmin, cmap=\"RdBu_r\")\n",
    "    label_x = ax.get_xticklabels()\n",
    "    plt.setp(label_x, rotation=45, horizontalalignment='right')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = np.zeros_like(df_corr)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "with sns.axes_style(\"white\"):\n",
    "    f, ax = plt.subplots(figsize=(20, 20))\n",
    "    ax = sns.heatmap(df_corr.round(2), mask=mask,  annot=True, center=0, square=True, vmax=1, vmin=-1, cmap=\"RdBu_r\")\n",
    "    label_x = ax.get_xticklabels()\n",
    "    plt.setp(label_x, rotation=45, horizontalalignment='right')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 454,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dzmQOYVzqjMswDCOKSnK/HcyIBmd8m0jkEDUUk6Ttstu7z++PfrPnNJE9M7U/tfbz+Xj0eFiXz1qvtR6r1Gu/1/vz7W99OxOfeTYnnXhSjjvuh1m06G+vpv3m1t/khOOX/rtTkTTkXr322mv55bXXZsK99+WpJ5/Occcdn9NOO3WJEQpFv1eLFpVS8QU3qrKy2T+0z29vvy3HHnv8igm5kmjIM9Vth2456cQTc8opJ+fAgwamWbOKrLnmmmnevHkjJi2vhtynTp065frrbkjnzlukoqIixxx9TN555+3MmjUrBx54UM4797y0adMmbdu2zZFHHpXHHn+sEa8Alp+Vsvz562tfDzzwQPr165dSqZRdd901zz77bCZPnpwBAwakf//+mTJlSqZPn54k2XjjjdO9e/ckyf7775/nnnuu/nj/9m//liRf+vlvfOMbeeyxx3LiiSfmT3/6U0466aRUV1dnypQpOfvss9OvX7+cfvrp+eSTT/Lhhx8mSXbddddUVFRkiy22yLx5877ymnbfffckSefOnTNv3rzMmzcvs2bNyp577pkkOeCAA5bfDQQAWMHWX3/9zJnzfv3y7Dmz07btmmnTpk39uhkzZuTFF1+sXx4w4ID8+c9/zvz5HyVJXpn6Surq6rLjjjs2XvAyaMi9+v0zv883v/GNbLTRRkmSQw85NK9Pf73+75lN4V6tv956ef/9v80BMmfOnLRt2zatW7dp8D6vvjo1dXW16bZDt8YLXgYNeaaqq6vTrduOGXP32Nw1+u76kVBrrtluqeMVVUPu07Rp03LvveOX+FypVEpVVVXuvXd8pk2bttR6WBWtlOXPXzVr1ixnnnlmZs+enZtuuil1dXU58sgj6+cDuuuuu3LCCSckyRK/CUulUiorK+uXW7VqlSRf+vmNN944Dz74YPr27ZsXXnghAwcOzKJFi9KiRYv6ff+6/1/fU2/ZcvE72F/0k4cv8vf7V1ZWZiWbaxsAoMF23WXXTJ78//LWjLeSJKNGjUrPnj2X2Of9D97PGYNPr//h2X33TUjnzTunXbvFE8u+8Pzz6d69e4P/PrWqasi92nqrrfP8C8/XT0Pw+OOPp2PHTvWT8DaFe7Xzzrtk8p8mZ8bbM5Ikd48Znb323Psf2ueFF1/ITjsW+z4lDXum5syZk6OOPrJ+Hqnrr78ufXr3Kfy9+b8acp+aNavIz//z55k5c2aS5M4770iXLbpkvfXWy+uvv57hI4anrq4un332WUbecXu+993vNfZlwHKxUpc/yeJS58wzz8wvf/nLbL311hk/fnyqq6tTW1ubk046KQ8//HCSxTOxT506NUkyZsyY7LHHHksdq0ePHl/4+d/+9rcZPnx4vve97+WnP/1p5s6dm1KplI033jjjxy9ugZ955pkcdthhy8xaWVmZ2tqGfRvCGmuskQ033DBPPfVUkmTChAkNvicAAOW29tprZ+jQi/OT007Lvn375PXXX8uZg8/MlClT0n9A/ySLXzs5/rjjc+RRR6T/gP554MEHMnz4iPpjzJgxIx036FiuS2g0DblXPXr0yDFHH5Ojjj4y/fvvn5Ejb6+fxiBpGvfqa19bOxdd+LMMHvzv6T9gv7z++us5/d8H5+VXXs5BBw9c5j5/9fbbM7LBBhuU6xIaTUOeqU022STH/uCHOfiQ76d3n++lZmFNzjhj8FccuVgacp86d94i55xzbk486UfZt2+fPPb4Y7nsssuTJCeeeFLWXHPN9Nu/X/bv3y/bb/+NDBx4YDkvCf5pK+VXvR9xxBF54oknllh/zDHHZIMNNsgGG2yQ+++/P3V1ddl9991zzjnn/P/vYx6Y7bffPm+//Xa6dOmSoUOHpk2bNunSpcsSQ/V++ctfLvX5v074/O6776aysjKHHXZYDjzwwLzxxhv1Ez43b948F154YbbbbrsMGTIkO+20UwYMGJAk9ed48803c9xxx6VXr17ZdNNNl5jw+dZbb02nTp0yadKkjBgxIrfddlveeOONnHPOOampqUmXLl0yefLkPPDAA416vwGAYmmsr3qn6Wisr3pf1TXmV73TNBT9q96nTi3uV71vtdXK91XvK13588/4ssJoZTdixIgcdNBBad++fR555JFMmDAhw4cXf9Z9AGDFUf6wvCl/Gkb5w/Km/Fl1rYzljz+hymiDDTbIMccck6qqqrRt2zYXX3xxuSMBAADACrfqD0NZtRRi5A8AAIsZ+cPyZuRPwxj5w/JW9JE/r7xS3JE/W2+98o38KfbTBAAAANDEKX8AAAAACkz5AwAAAFBgyh8AAACAAlP+AAAAABSY8gcAAACgwJQ/AAAAAAVWVe4AAAAAQNNSKpXKHaFJMfIHAAAAoMCUPwAAAAAFpvwBAAAAKDDlDwAAAECBKX8AAAAACkz5AwAAAFBgyh8AAACAAqsqdwAAAACgaSmVyp2gaTHyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYMofAAAAgAJT/gAAAAAUWFW5AwAAAABNS6lUKneEJsXIHwAAAIACU/4AAAAAFJjyBwAAAKDAlD8AAAAABWbCZwAAmpxbb3m+3BFWGUcctWO5I6wSPFMN43mC8lD+AAAUSGWVgd0AwJL87QAAAACgwIz8AQAAABpVqdwBmhgjfwAAAAAKTPkDAAAAUGDKHwAAAIACU/4AAAAAFJjyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgVWVOwAAAADQtJRKpXJHaFKM/AEAAAAoMOUPAAAAQIEpfwAAAAAKTPkDAAAAUGDKHwAAAIACU/4AAAAAFJjyBwAAAKDAqsodAAAAAGhaSqVyJ2hajPwBAAAAKDDlDwAAAECBKX8AAAAACkz5AwAAAFBgyh8AAACAAlP+AAAAABSY8gcAAACgwJQ/AAAAAAVWVe4AAAAAQNNSKpXKHaFJMfIHAAAAoMCUPwAAAAAFpvwBAAAAKDBz/gAAQJl12rBddthxw1Q2q8jcuZ/kmd+9mYUL68odq9E99dSTufKqK1NTU5MttuiSoT8bmtVXX32JfV577bVc/POh+fjjBamsbJYLf3pRttlmm/rt7777bg459OCMG3tP1lprrca+hJWGZ2qxhjxTlw67NA8//HDWXHPNJMkmm2ycX1xxZU477dTMePvt+v1mzZqZHbvtmP/6r1824hXA8lHYkT+1tbW59tpr873vfS+9e/dOr169ct111y1zUqnJkyfnsssuS5KMHTs2Q4YM+afP//jjj+fqq6/+pz8PAEDT0LJVVXbbY9P892OvZezdk7Pg48+zw44bljtWo5s7d27OPe/cXHXV1Xng/gezYadO+cUvrlhin08//TTH/vAHOeaYH2TsmLE54YQf5cyzBtdvHz/+nhxx5KDMmTOnseOvVDxTizXkmUqSl176Y664/IqMGzsu48aOyy+uuDJJctVVV9ev+4+L/iNrrLFGzjvv/Ma+DFguClv+XHTRRZk8eXJGjRqVBx54IGPGjMmzzz6bkSNHfulnpk+fnr/85S/L5fzf+ta3cuqppy6XYwEAUFwdO66ZD95fkPnzP0+SvDp1djbbfO0yp2p8z0x8Jl27ds3GX984SXLwwYfkvvvvW+KHt89MfCYbbbhR9txjzyRJz7171v9Dfc6cOXn8icfzqxt+1ejZVzaeqcUa8kzV1NRk6tSpuenXN6Xf/vvl1FNPyZ///OcljlNTU5Ozzzk7Zw85O+uvv35jXgIsN4V87eu9997Lvffem6effjpt27ZNkqy++uq54IILMn369Lz22mv52c9+lk8++SRz587Ncccdlz59+uSaa67JJ598kmuvvTYdOnTIjBkzMmjQoPz5z3/OzjvvnKFDhyZJbrjhhjz44IOpq6vLbrvtlsGDB2fWrFk59thjs9Zaa6VVq1bp2895mEMAACAASURBVLdv/vCHP+SSSy5Jz549s99+++X3v/99Pv3001x66aXp2rVrXnvttQwZMiR1dXXp1q1bnn766Tz66KPlvHUAADSy1VZrkerqmvrl6uqatGhRlebNK5vUazrvvfte1lvvb/+w7tChQxYsWJDq6ur613RmvPVW1llnnZx3/rmZNm1a1lhjjZxx+hlJkvbt2+eaq4eXJfvKxjO1WEOeqTlz5qR79+459ZRTsvnmnfPrm3+dH5/844y5e0wqKiqSJGPHjkn79uvm29/+TlmuA5aHQo78mTx5cjbbbLP6dzb/arPNNkuvXr1y11135cQTT8yYMWNy6623ZtiwYWnbtm1OOeWU9OzZMz/60Y+SLH5fePjw4XnwwQfz9NNP5/XXX8/TTz+dKVOm5O67784999yT2bNn5957702SvPnmm7nsssty8803L5WpXbt2ufvuu3PwwQfn+uuvT5IMGTIkp556asaPH58NN9wwdXVN5w9iAAAW++s/MP/esqYrKKJFpUX5olvRrNnf/smysLY2T//u6Rx44EG5a/TdOeyww3P8CSekpqZm6Q82YZ6pxRryTHXq1CnXX3dDOnfeIhUVFTnm6GPyzjtvZ9asWfX7/ObW3+SE43/UGJGbllKBf62ECln+JEv+gffQQw+lX79+6du3bw444IAMGTIkn3/+ea6//vpcddVV+eSTT77wGN26dUu7du3SokWLbLTRRvnwww/z7LPPZvLkyRkwYED69++fKVOmZPr06UmStddeO506dfrCY+2+++5Jks6dO2fevHmZN29eZs2alT33XDxk9YADDlielw8AwCpiQfXnadOmRf1ym9Va5PPPalNbu6iMqRrf+uuvnzlz3q9fnj1ndtq2XTNt2rSpX9e+fftsuumm+bft/i1J8q2e38qiRXV55513Gj3vyswztVhDnqlp06bl3nvHL/G5UqmUqqrFL8m8MvWV1NXVZccdd2yc0LCCFLL86dq1a954440sWLAgSfLd734348ePz7XXXpsPP/wwp512Wh599NFsttlmOe200770OH/9DZ8sLpNKpVLq6upy5JFHZvz48Rk/fnzuuuuunHDCCUmSVq1afemxWrZsWX+cJKmsrGxyzTsAAEv788yPsm771dO27eK/L265ZYe8/faHZU7V+HbdZddMnvz/8taMt5Iko0aNSs+ePZfYZ/fdds/MmbPy8ssvJ0leeOH5VFRUfOkPYJsqz9RiDXmmmjWryM//8+eZOXNmkuTOO+9Ily26ZL311kuSvPD88+nevfuXjqaCVUUh5/zZYIMNst9+++Wss87Kf/7nf6Zt27apra3Nk08+mWbNmuWZZ57Jgw8+mA4dOuT2229PktTV1aWysjK1tbXLPHaPHj1yzTXX5KCDDkrLli1z0kknpX///tlpp53+oYxrrLFGNtxwwzz11FPZc889M2HChH/6egEAWHV99lltfv/UG9n7W53TrLJZPp7/WZ5+6o1yx2p0a6+9doYOvTg/Oe20LKxdmA033DD/+fNLMmXKlJx/wfkZN3Zc1l133YwYPjz/8bP/yKeffpIWLVrk6quuqf9BK4t5phZryDPVufMWOeecc3PiST/KokWL0qFDh1x22eX1x5gxY0Y6btCxjFcBy0chy58kufDCC3PzzTfniCOOSF1dXaqrq9O9e/f86le/ypNPPplDDz00LVu2zJZbbpmOHTtm5syZ2W677TJixIhcfvnl2XTTTb/wuD179syrr76agw46KHV1ddl9993Tv3//Jd4Jbahhw4blnHPOyVVXXZUuXbosc+QQAADFNXPmR5k586Nyxyi7PffYs/6bvP6qXbt2GTd2XP1yt247ZtSdo5Z5nFdenrpC8q1KPFOLNeSZ2q/vftmv735f+Pnzz79gheaDxlJR8u5R2YwYMSIHHXRQ2rdvn0ceeSQTJkzI8OG+oQAAYEW7+cZJ5Y6wyjjiKHOdNMSttzxf7girBM9Tw1VWFXKWlnp//OOfyx1hhfnGNzYod4SlFHbkz6pggw02yDHHHJOqqqq0bds2F198cbkjAQAAAAWj/CmjAQMGZMCAAeWOAQAAABRYsceRAQAAADRxRv4AAAAAjcr0w43LyB8AAACAAlP+AAAAABSY8gcAAACgwJQ/AAAAAAWm/AEAAAAoMOUPAAAAQIEpfwAAAAAKrKrcAQAAAICmpVQqd4KmxcgfAAAAgAJT/gAAAAAUmPIHAAAAoMCUPwAAAAAFpvwBAAAAKIMJEyakd+/e2WeffXL77bcvtX3q1KkZMGBAevXqlXPPPTe1tbVJkhdeeCEDBgxI3759c8IJJ+Sjjz5a5nmUPwAAAACNbPbs2bnyyiszcuTI3HPPPRk1alSmT5++xD6DBw/OBRdckIcffjilUimjR49Okpx99tkZNmxYJkyYkM033zw33XTTMs+l/AEAAABYTubPn5+ZM2cu9Wv+/PlL7Ddx4sT06NEj7dq1S5s2bdKrV6889NBD9dtnzZqVzz77LNtvv32SZMCAAfXbH3jggWy++eZZuHBhZs+enbZt2y4zU9VyvkYAAACAJus3v/lNRowYsdT6H//4xzn55JPrl+fMmZN11123frl9+/aZPHnyl25fd911M3v27CRJ8+bNM23atBx99NGpqqrKv//7vy8zk/IHAAAAaFSlUqncEVaYI488Mv37919q/d+Pzlm0aFEqKirql0ul0hLLX7W9S5cumThxYu6888785Cc/yZ133vmlmbz2BQAAALCctG3bNp06dVrq19+XP+utt17ef//9+uX3338/7du3/9LtH3zwQdq3b5/PP/88jz32WP36/fbbL9OmTVtmJuUPAAAAQCPbZZdd8uyzz2bu3Ln59NNP88gjj2SPPfao396xY8e0bNkyL774YpJk/Pjx2WOPPVJVVZWLLrooU6ZMSZI8+OCD+eY3v7nMc3ntCwAAAKCRdejQIT/5yU9yxBFHZOHChRk4cGC22267/PCHP8wpp5ySbbfdNpdffnnOO++8LFiwINtss02OOOKIVFZW5sorr8wFF1yQurq6dOjQIRdffPEyz1VRKvKLdgAA8AVuvnFSuSOsMo44asdyR1gl3HrL8+WOsErwPDVcZVWxX9R54YWZ5Y6wwnTr1qncEZZS7KcJAAAAoIlT/gAAAAAUmPIHAAAAoMBM+AwAAAA0KrMPNy4jfwAAAAAKTPkDAAAAUGDKHwAAAIACM+cPAABNztHHdi93hFVGXe2ickdYJbRbq025IwB8KSN/AAAAAApM+QMAAABQYMofAAAAgAJT/gAAAAAUmAmfAQAAgEZVKpXKHaFJMfIHAAAAoMCUPwAAAAAFpvwBAAAAKDDlDwAAAECBKX8AAAAACkz5AwAAAFBgyh8AAACAAqsqdwAAAACgaSmVyp2gaTHyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYMofAAAAgAJT/gAAAAAUWFW5AwAAAABNSymlckdoUoz8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYMofAAAAgAJT/gAAAAAUmPIHAAAAoMCqyh0AAAAAaFpKpXInaFqM/AEAAAAoMOUPAAAAQIF57QsAAFgpPPXUk7nyqitTU1OTLbbokqE/G5rVV1+9fvv48ffklt/8pn55wYKPM3v27Dzx+H+nqqoq//Gzi/Lqq6+mdevW6d9/QA4/7PByXEajePXVF/PQI7entrY266+3UQ4YcGJatWrzD+0zb94H+eV15+TUky/Paqu1bexLaBRf9UwlyW9v/21Gjrw9LVu2ymabbprzzjs/7dq1y8cff5zzzz8v//vm/2bRolL279cvxx77wzJdCfxrjPwBAADKbu7cuTn3vHNz1VVX54H7H8yGnTrlF7+4Yol9+vXbP+PGjsu4seMyetTorLPOOjn33POyzjrr5NJLL0mbNm0y4d77csfIO/O73z2dJ5/87zJdzYq1YMFHuWvMf+XwQwfnjH+/Jl/7Woc89PDt/9A+L/7Pk7n+Vxdk/vy5jR2/0TTkmZo0aVJuuunG/PqmmzNu7LjsscceufDCnyZJrhl+TTp06JB7x0/I6FGjc+eoO/PSS38sx6XAv2yVKX8mTZqUQYMGrZBjDx8+PMOHD18hx26os88+O7NmzSprBgAAKJdnJj6Trl27ZuOvb5wkOfjgQ3Lf/fel9CWzwt5004352tfWzvcP+n6S5OVXXs5+ffulsrIyLVq0yJ577JlHHnmkseI3qten/7906rR51lln/SRJ9+698seXfrfEvVrWPvPnz80rr/whxxx9XlnyN5aGPFMvv/Jydu6xc9Zbb70kybe//Z3895P/nZqampxz9jkZPPjMJMn777+fmpqarL76Go1+HbA8rDLlT9FNmjTpS//HBgAARffeu+9lvfXWr1/u0KFDFixYkOrq6qX2/fDDD3PLb27JkLOG1K/bbrvtcu+E8Vm4cGGqq6vz6KOP5v3332+U7I3to4/+knZrrl2/vGbbtfP555/k888/bdA+bdt+LYMOPzPrrrNBo+ZubA15prbbbrs8N2lSZv158Q/ix40bl4ULF+ajj+aloqIiVVVVOfOsM9Nv//2y0447ZZNNNmn064DlYZUvf6677rr07t07ffv2zSWXXJK6urokyS233JJevXqld+/eueyyy5Ikr732WgYNGpQDDjgge++9d+64444Gn2fixInZb7/90rdv3xx//PFZsGBBFi1alKFDh6ZPnz7Zd999c8MNNyRZepTSkCFDMnbs2MycOTP7779/Bg8enH333TdHHnlk5s2blxtuuCFz5szJcccdlw8//HA53h0AAFg1LCotSkXF0uubNVv6nyyj7xqdnnv3zIYbbli/7szBZ6WioiIHDByQk0/5cXbeZZc0b958RUYum1JpUZKlb9b/vVcN2afoGvJMdduhW0468cSccsrJOfCggWnWrCJrrrnmEs/OsEuH5ZnfT8xHH32UX177y8aIDsvdKv07/6mnnsoTTzyRMWPGZNy4cZkxY0buvPPOTJ48OSNHjszdd9+de++9Ny+//HKmTJmSu+66KyeeeGLGjBmTW2+9NcOGDWvQeWpqanLGGWfk0ksvzYQJE7LFFltk3LhxueOOO/Luu+/m3nvvzV133ZVHHnkkTz755DKP9eqrr+boo4/Offfdl7Zt22bChAk57rjj0r59+9xwww1Za621lsOdAQCAVcv666+fOXP+NlJn9pzZadt2zbRp02apfR968MH0799/iXULFizI6f9+Ru4dPyG/vunmlEqlbLTRRis8dzm0W3PdzP/4b3P1zJ8/N61br54WLVr9Q/sUXUOeqerq6nTrtmPG3D02d42+Oz17fitJsuaa7fL73/8+c+bMSZKsttpq6d27T6a+8krjXgQsJ6t0+fPcc8+lT58+ad26daqqqnLAAQfk2WefzfPPP5+99947a6yxRqqqqnLLLbeka9euGTJkSD7//PNcf/31ueqqq/LJJ5806DzTpk1Lhw4dstVWWyVJTj/99AwaNCiTJk1K//79U1lZmdatW6dv37559tlnl3mstddeO1tvvXWSpHPnzvnoo4/+tZsAAAAFsOsuu2by5P+Xt2a8lSQZNWpUevbsudR+H330Ud5+5+1sv/03llg/avSojBixeB7PDz74IGPG3J0+ffZd4bnLoXPnf8s7b7+eDz54N0ky6Q+PZOutdvyH9ym6hjxTc+bMyVFHH5kFCxYkSa6//rr06d0nFRUVeejhB/Nfv/yvlEql1NTU5KGHH0z37t0b+zIKq1Qq7q+V0Spd/ixatGipdbW1tamqqkrF/xnfN3v27MyfPz+nnXZaHn300Wy22WY57bTTGnye5s2bL3G8jz/+OO+9995S5y+VSqmrq0tFRcUS8/csXLiw/r9btmxZ/99/vx8AADRVa6+9doYOvTg/Oe207Nu3T15//bWcOfjMTJkyJf0H/G2Uz9tvv5111ll3qVe6jvvhcXlv9uzs169vjj7mqPz4xydn2223bezLaBSrr75mBg48Kb8deXmuuPLUvPfejPTpfURmzpyeq4efscx9mpKGPFObbLJJjv3BD3PwId9P7z7fS83CmpxxxuAki18lXLDg4/Tbf78MPPCAbLP1Nhk0qGndQ4qjqtwB/hU9evTItddem+9///upqqrKmDFj0qNHj3Tr1i1nnHFGTj755LRs2TKnn356TjzxxDzzzDN58MEH06FDh9x+++KvOfzrHEHLsskmm+Qvf/lLpk+fns033zw33nhj/fnvueee7L333qmpqcmECRNywgknZK211so777yTzz//PJ9++mlefPHF7Lrrrss8R2VlZYOyAABAUe25x57Zc489l1jXrl27jBs7rn552223zcMPPbzUZ1dbbbWMGD5ihWdcWWzZ5ZvZsss3l1jXps0aOfXky5e5z9+75Od3r5B8K4uGPFOHHXZYDjvssKU+27Zt21xx+S9WeEZoDKtU+fPCCy/kG9/42/DOvn37Zq+99soBBxyQ2tra7Lbbbjn88MNTVVWVww8/PAcffHAWLVqU73znO9lll11y8skn59BDD03Lli2z5ZZbpmPHjpk5c+ZXnrdly5a57LLLcuaZZ2bhwoXZaKONMmzYsLRo0SJvvfVW+vXrl4ULF6Zv3775zne+kyTZc88906dPn3Ts2DE77LDDV55jr732ynHHHZcbb7xxiYnrAAAAAP4VFSXvHQEAAF+irnbpqRZY2r3jXy53hFXCfv22KXeEVUZl1So9S8tXmvjs2+WOsMLssvPKN9n8KjXyZ0UbNGhQ5s+fv9T6gw8+OIccckgZEgEAAAD8a5Q//8dtt91W7ggAAAAAy1Wxx5EBAAAANHFG/gAAAACNyvTDjcvIHwAAAIACU/4AAAAAFJjyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYFXlDgAAAAA0LaVSuRM0LUb+AAAAABSY8gcAAACgwJQ/AAAAAAWm/AEAAAAoMOUPAAAAQIEpfwAAAAAKTPkDAAAAUGBV5Q4AAAAANC2lUqncEZoUI38AAAAACkz5AwAAAFBgyh8AAACAAlP+AAAAABSY8gcAAACgwJQ/AAAAAAWm/AEAAAAoMOUPAAAAQIFVlTsAAAAA0LSUSuVO0LQofwAAAP5F+/XbptwRVgm33vJ8uSOsMo4+tnu5I1Agyh8AAOBLVVaZKaIh6moXlTsCwJfyJzkAAABAgSl/AAAAAApM+QMAAABQYMofAAAAgAJT/gAAAAAUmG/7AgAAABpVqVQqd4QmxcgfAAAAgAJT/gAAAAAUmPIHAAAAoMCUPwAAAAAFpvwBAAAAKDDlDwAAAECBKX8AAAAACkz5AwAAAFBgVeUOAAAAADQtpVK5EzQtRv4AAAAAFJjyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYFXlDgAAAAA0LaVSqdwRmhQjfwAAAAAKTPkDAAAAUGDKHwAAAIACU/4AAAAAFJjyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAVjFPPfVk9u/fL737fC+n/eS0LFiw4Av3K5VKOfvsIfn1zb9eYv38+fOzf/9+mTJlSmPEXWl12rBd+g3YNgMGbpe9em6e5s0ryx2p6SgV+NdK6J8ufyZNmpRBgwYtzyz1hg8fnuHDh6+QYy9vK+oeAAAAfJG5c+fm3PPOzVVXXZ0H7n8wG3bqlF/84oql9nvjjTdyzDFH55FHH1li/VNPP5WDD/l+3nzzzcaKvFJq2aoqu+2xaf77sdcy9u7JWfDx59lhxw3LHQtWCCN//kV/+MMfyh0BAABoQp6Z+Ey6du2ajb++cZLk4IMPyX3335dSackhB3fcMTIHHDAwvfbptcT623/721x6ybCsu+66jRV5pdSx45r54P0FmT//8yTJq1NnZ7PN1y5zKlgxqpb3Aa+77rrce++9qayszK677prBgwensrIyt9xyS+64445UVlZm7733zuDBg/Paa6/lZz/7WT755JPMnTs3xx13XA455JAGnadnz5757ne/m4kTJyZJfv7zn2frrbfOjBkzcuGFF2bevHlp1apVzj///Gy99dYZMmRI5s2blxkzZmTw4MFp1apVLrnkkpRKpWywwQa54oor0rp16wwbNix/+MMfUldXlwEDBuSoo47KpEmTcv3116dVq1Z544030qVLl1x++eUZNmxYkuTAAw/MXXfdld/+9rcZP358Pv300zRv3jxXXHFFNt1000yaNClDhw5NZWVltt9++7zxxhu57bbbvjQrAADAl3nv3fey3nrr1y936NAhCxYsSHV1dVZfffX69eedd36SZOLEZ5b4/A03/Kpxgq7kVlutRaqra+qXq6tr0qJFVZo3r8zChXVlTAbL33Itf5566qk88cQTGTNmTJo3b56TTz45d955Z7bddtuMHDkyY8aMSevWrXPsscdmypQpGT9+fE488cTsvPPOeeedd7Lffvs1uPxJkjZt2uSee+7JE088kbPOOisTJkzIWWedlQsuuCBbb711pk+fnpNOOikPP/xwkqRdu3a57rrrUlNTk7322is33XRTttpqq1xxxRUZN25cqqoW345x48alpqYmP/jBD9K1a9ckyR//+Mc8+OCDad++fQ466KD8/ve/z3nnnZfbbrstd911VxYsWJDHHnsst912W1q1apWrr746t99+e4YMGZIzzzwz119/fbbccssMHTq0Pv+ysgIAAHyRRaVFqahYen2zZl7s+EdUfNFNTJYaQQVFsFzLn+eeey59+vRJ69atkyQHHHBA7rnnnnz22WfZe++9s8YaayRJbrnlliTJVlttld/97ne5/vrr89prr+WTTz75h8530EEHJVk8CmjIkCF57733MmXKlJx99tn1+3zyySf58MMPkyTbbbddkmTatGnp0KFDttpqqyTJ6aefniQ55ZRTMnXq1Dz33HP1n502bVo233zzdO7cOeutt16SZLPNNstHH320RJbVV189V1xxRe6///689dZb+d3vfpetttoqr732WtZee+1sueWWSZKBAwfm4osvTnV19ZdmXWuttf6h+wAAADQd66+/fiZPnly/PHvO7LRtu2batGlTxlSrngXVn2fd9n8bKdVmtRb5/LPa1NYuKmMqWDGWa/mzaNHSv0lqa2tTVVW1RKs6e/bstG7dOueee27atm2bvffeO71798599933D53vryN1/nruurq6tGjRIuPHj69f/95776Vdu3ZJklatWiVJmjdvvkSejz/+ONXV1amrq8vgwYOzzz77JFk8kdpqq62Wl156KS1btqzfv6KiYqk2+N13382gQYNy+OGHZ4899sg666yTqVOnprKy8gvvy6JFi5aZFQAA4IvsusuuueyyYXlrxlvZ+OsbZ9SoUenZs2e5Y61y/jzzo+zU/etp27Zl5s//PFtu2SFvv/1huWPBCrFcxwX26NEj999/fz777LPU1tZmzJgx6dGjR7p165annnoq1dXVqa2tzemnn54pU6bkmWeeySmnnJJvf/vbefrpp5MkdXUNf7fy/vvvT5I8+uij2WyzzdKxY8dsvPHG9YXKM888k8MOO2ypz22yySb5y1/+kunTpydJbrzxxtxxxx3p0aNHRo8enYULF6a6ujqHHnpoXnrppWVmqKysTG1tbf70pz/l61//eo466qhsu+22eeyxx1JXV5dNN9008+fPz7Rp05IkEyZMSJKsscYaDcoKAADwf6299toZOvTi/OS007Jv3z55/fXXcubgMzNlypT0H9C/3PFWGZ99VpvfP/VG9v5W5/QfuF3W+lrr/GHSjHLHghXiXxr588ILL+Qb3/hG/XLfvn2z11575YADDkhtbW122223HH744amqqsrhhx+egw8+OIsWLcp3vvOd7LLLLjn55JNz6KGHpmXLltlyyy3TsWPHzJw5s8Hn/5//+Z/cfffdad26dS655JIkyWWXXZYLL7wwN954Y5o3b54rr7xyqXc5W7ZsmcsuuyxnnnlmFi5cmI022ijDhg1LixYtMmPGjPTv3z+1tbUZMGBAunfvnkmTJn1phm9961vp169fRo8enTvuuCO9e/dOqVTKjjvumNdffz0tWrTIsGHDctZZZ6VZs2bZZJNN6kcgNSQrAADA39tzjz2z5x57LrGuXbt2GTd23FL7/vzn//mFx3js0cdXSLZVycyZH2XmzI++ekeWu1LMrdSYKkqr6GxWPXv2zK233ppOnTqVO8oyLVq0KJdffnl+/OMfp02bNrn55psze/bsDBkypNzRAACA5aTOPDENcustz5c7wirj6GO7lzvCCvXEf79R7ggrTM+9Nyt3hKUs9696X54GDRqU+fPnL7X+4IMPLkOaf06zZs3Srl27DBw4MM2bN0/Hjh1z8cUXlzsWAAAA0ESssiN/AAAAVhZG/jSMkT8NZ+TPqmtlHPmzXCd8BgAAAGDlovwBAAAAKIMJEyakd+/e2WeffXL77bcvtX3q1KkZMGBAevXqlXPPPTe1tbVJkhdffDEDBw5Mv379cuSRR2bWrFnLPI/yBwAAAKCRzZ49O1deeWVGjhyZe+65J6NGjcr06dOX2Gfw4MG54IIL8vDDD6dUKmX06NH164cOHZrx48enb9++GTp06DLPpfwBAAAAWE7mz5+fmTNnLvXr77/QauLEienRo0fatWuXNm3apFevXnnooYfqt8+aNSufffZZtt9++yTJgAED8tBDD6WmpiannnpqttxyyyRJly5d8u677y4z00r9bV8AAABA8RT5q6d+85vfZMSIEUut//GPf5yTTz65fnnOnDlZd91165fbt2+fyZMnf+n2ddddN7Nnz06LFi3Sr1+/JMmiRYsyYsSIfPvb315mJuUPDpE8jwAAIABJREFUAAAAwHJy5JFHpn///kutb9u27RLLixYtSkVFRf1yqVRaYvmrttfU1GTIkCGpra3N8ccfv8xMyh8AAACA5aRt27ZLFT1fZL311ssLL7xQv/z++++nffv2S2x///3365c/+OCD+u3V1dX50Y9+lHbt2uXaa69N8+bNl3kuc/4AAAAANLJddtklzz77bObOnZtPP/00jzzySPbYY4/67R07dkzLli3z4osvJknGjx9fv33w4MH5+te/nquuuiotWrT4ynMZ+QMAAADQyDp06JCf/OQnOeKII7Jw4cIMHDgw2223XX74wx/mlFNOybbbbpvLL7885513XhYsWJBtttkmRxxxRF555ZU8/vjj2XzzzetfL2vfvn1+9atffem5KkqlIk+zBAAAsOLV1S4qd4RVwq23PF/uCKuMo4/tXu4IK9TjT7xR7ggrzLd6blbuCEvx2hcAAABAgSl/AAAAAApM+QMAAABQYCZ8BgAAABpVaZHphxuTkT8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYMofAAAAgAJT/gAAAAAUWFW5AwAAAABNS6lU7gRNi5E/AAAAAAWm/AEAAAAoMOUPAAAAQIEpfwAAAAAKTPkDAAAAUGDKHwAAAIACU/4AAAAAFJjyBwAAAKDAqsodAAAAYFVXWeXn6vCPKJVK5Y7QpPgTCgAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYMofAAAAgAKrKncAAAAAoGkplUrljtCkGPkDAAAAUGDKHwAAAIACU/4AAAAAFJjyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAAqsqtwBAAAAgKalVCp3gqbFyB8AAACAAlP+AAAAABSY8gcAAACgwJQ/AAAAAAWm/AEAAAAoMOUPAAAAQIEpfwAAAAAKrKrcAQAAAICmpVQqlTtCk2LkDwAAAECBKX8AAAAACkz5AwAAAFBgyh8AAACAAlP+AAAAABSY8gcAAACgwJQ/AAAAAAVWVe4AAAAAUA6dNmyXHXbcMJXNKjJ37id55ndvZuHCunLHguVO+QMAAECT07JVVXbbY9M8MOHlzJ//ebrtuGF22HHDPDfxrXJHaxJKpVK5IzQpK91rXxdddFH69euX3r17p2vXrunXr1/69euXMWPG/NPHPPfcc/OnP/3pS7dfc801eeGFF/7p4y8Po0ePzn333VfWDAAAAE1Fx45r5oP3F2T+/M+TJK9OnZ3NNl+7zKlgxVjpRv789Kc/TZLMnDkzRxxxRMaPH/8vH/Piiy9e5vbnn38+3bt3/5fP86/4n//5n+y0005lzQAAANBUrLZai1RX19QvV1fXpEWLqjRvXunVLwpnpRv580XefPPNDBo0KH379s33v//9TJ48OUkyZMiQjB07tn6/Ll26JEmGDx+eH/zgB+ndu3dGjhyZQYMGZdKkSXnvvfdy+OGHZ8CAARk4cGBeeuml3HPPPZkyZUrOO++8TJs27UszzJo1K0cccUT23XffDBw4MK+++mqSZMyYMdl3333Tt2/fDBkyJNXV1UtkSZKxY8dmyJAhSZKePXvmqquuysCBA9OnT59MmTIlEydOzBNPPJFrrrkmv/vd75bvzQMAAGApFRUVX7je60gU0SpR/gwePDiDBg3KhAkTcvbZZ+fUU09NTU3NMj9TU1OTBx54IIceemj9urvvvjt77bVXxo4dm1NOOSUvvvhi9t9//3Tt2jVDhw5dorD5exdddFF69eqV++67LyeffHKuvfbaTJs2Ldddd11uu+22TJgwIa1bt86IESO+8nratWuXu+++OwcffHCuv/767LLLLunZs2dOOeWU7L777g2/MQAAAPxTFlR/njZtWtQvt1mtRT7/rDa1tYvKmApWjJW+/Kmurs7bb7+dffbZJ0my/fbbZ80118z//u//LvNz22233VLrdt555/z617/O6aefnnnz5uXwww9vcI7nn38+/fr1S5Lsueeeufrqq/P8889n7733zlprrZUk+f73v5/nnnvuK4/114Knc+fOmTdvXoMzAAAAsHz8eeZHWbf96mnbtmWSZMstO+Tttz8scypYMVb68ueLhtyVSqXU1dWloqKifvvChQuX2KdVq1ZLfW6HHXbI/fffn9122y0PPPBATjjhhAbnqKr62/RIpVIp06dPz6JFSzbCpVIptbW1S2X/v+uSpGXLxX+4fNkwQwAAAFaszz6rze+feiN7f6tz+g/cLmt9rXX+MGlGuWPBCrHSlz+rr756OnXqlEceeSRJ8tJLL+WDDz5I586d065du0yfPj1J8thjj33lsYYNG5Z77703/fv3zwUXXJBXXnklSVJZWZm6umVP6NWtW7fcf//9SZKJEyfm/PPPz0477ZQnnniifvTO6NGj6yeOXmuttfL666+nVCrliSee+MpsDckAAADA8jNz5kcZP25Kxt09OY898lpqPvdvMopppfu2ry9y2WWX5cILL8zw4cPTvHnzDB8+PC1atMghhxyS0047LX379k2PHj2y7rrrLvM4gwYNyumnn56xY8emsrIyl156aZLFr2H99Kc/zaWXXppvfvObX/jZCy64IOedd15GjhyZ1q1bZ+jQodl8881z/PHHZ9CgQVm4cGG22WabXHTRRUmS008/PSeccELWWWed7LDDDvnww2UPH9xll13yi1/8ImussUa++93v/hN3CQAAAFYN5tVuXBUlU5kDAADQCG6+cVK5I6wyjj62e7kjrFD33/9quSOsMH36bFnuCEtZJUb+NJZLL700EydOXGp9165dc/HFF5chEQAAAMC/Rvnzf5x11lnljgAAAACwXK30Ez4DAAAA8M9T/gAAAAAUmPIHAAAAoMCUPwAAAAAFpvwBAAAAKDDf9gUAAAA0qlKpVO4ITYqRPwAAAAAFpvwBAAAAKDDlDwAAAECBKX8AAAAACkz5AwAAAFBgyh8AAACAAlP+AAAAABRYVbkDAAAAAE1LqVQqd4QmxcgfAAAAgAJT/gAAAAAUmPIHAAAAoMCUPwAAAAAFpvwBAAAAKDDlDwAAAECBKX8AAAAACkz5AwAAAFBgVeUOAAAAADQtpVK5EzQtRv4AAAAAFJjyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAArMV70DAADQKI4+tnu5I0CTpPwBAAAAGlVpUancEZoUr30BAAAAFJjyBwAAAKDAlD8AAAAABab8AQAAACgw5Q8AAABAgSl/AAAAAApM+QMAAABQYMofAAAAgAKrKncAAAAAoGkplcqdoGkx8gcAAACgwJQ/AAAAAAWm/AEAAAAoMOUPAAAAQIEpfwAAAAAKTPkDAAAAUGDKHwAAAIACqyp3AAAAAKBpKZVK5Y7QpBj5AwAAAFBgyh8AAACAAlP+AAAAABSY8gcAAACgwJQ/AAAAAAWm/AEAAAAoMOUPAAAAQIEpfwAAAAAKrKrcAQAAAIAmplQqd4ImxcgfAAAAgAJT/gAAAAAUmPIHAAAAoMCUPwAAAABlMGHChPTu3Tv77LNPbr/99qW2T506NQMGDEivXr1y7rnnpra2dontV111VYYPH/6V51H+AAAAADSy2bNn58orr8zIkSNzzz33ZNSoUZk+ffoS+wwePDgXXHBBHn744ZRKpYwePTpJ8vHHH+ecc87JzTff3KBzLbP8ueiii9KvX7/07t07Xbt2Tb9+/dKvX7+MGTPmn7y05Nxzz82f/vSnL91+zTXX5IUXXvinj9+YVqWsAAD8f+zdZ0BU19bw8f9QBEQ6IiCIBQUFFHsXxW7sJTbsSq4KtmiwYY2xYrxqNMZoxJLYNfYawYaNiFhio1lALIgIggIz7wefmQvG5Mm9z3sdw1m/L2GYOWHNdp+2zt5rCyGEEB+Ps2fPUq9ePaytrSlevDitW7fm0KFDuvcfPnxITk4Ovr6+AHTt2lX3/vHjxylbtiyDBg36S3/rT5d6nz59OgAPHjygf//+/Pzzz//RFypozpw5f/r+xYsXqVu37v/573wIf6dYhRBCCCGEEEII8d+XkZFBRkbG735vaWmJpaWl7vXjx48pWbKk7rWDgwOxsbF/+H7JkiVJTU0FoHPnzgB/acoX/C/Jn/dJSEhg2rRppKenU7x4caZMmULVqlWZOHEiderUoWvXrgB4eHhw69Ytli1bRkxMDCkpKQQEBHDw4EGCgoJwc3Nj/PjxvHr1CgMDA6ZOnUpiYiLXrl1j6tSpLF++HA8Pj/fGMHHiRExMTLh69SpZWVkMHz6czp07k5WVxaxZs7hz5w75+fkMGzaM9u3bs3PnTnbt2kV6ejrNmjWjZ8+eTJo0ibS0NExNTfnyyy/x9PRk9+7dhIeHo1ar8fLyYvr06ZiYmNCoUSNat25NdHQ0hoaGLFmyhOjo6EKxvnjxgq+//pqcnBwyMjKYNGkSLVq04NGjR4wfP54XL15QqVIlLl68yMmTJ/8wViGEEEIIIYQQoqjTaPQdwX9PeHg4y5cv/93vg4KCCA4O1r1Wq9WoVCrda41GU+j1//b+v+PfTv5MmDCBwMBAWrVqRUxMDKNHj+bw4cN/us2bN284cOAAAAcPHgRg+/btNG3alKFDh3Ly5Emio6MZMmQIO3bsICgo6A8TP1r3799ny5YtPHv2jK5du9KwYUPCw8Px8vJi/vz5ZGZm0qtXL6pVqwa8nUt34MABjIyMCAwMpHXr1vTt25fIyEhWrlxJUFAQW7duZfPmzZiYmBAWFsaaNWsYMWIET548oX79+oSGhjJv3jw2bdrExIkTC8U6atQovvzySypUqEBUVBRfffUVLVq0YM6cObRt25a+ffty9OhR9u3bB8DKlSvfG6urq+u/+08ihBBCCCGEEEKIj8SAAQPo0qXL735fcNQPgKOjY6FSMk+ePMHBwaHQ+0+ePNG9fvr0aaH3/x3/VvInKyuLe/fu0apVKwB8fX2xsrIiPj7+T7erWrXq735Xv359goOD+e233/Dz8yMgIODfCYWuXbtibGyMo6MjNWrUIDo6mrNnz5KTk6OrSfTq1Svu3LkDQJUqVTAyevt1L168yOLFiwHw8/PDz8+PjRs3kpSUxKeffgpAbm4uVapU0f29xo0bA1CxYsX31vlZuHAhJ06c4NChQ1y5coWsrCwAzpw5w9y5cwFo2bKl7h/7j2KV5I8QQgghhBBCCPH39e70rj/SoEEDli1bRlpaGmZmZhw5coTZs2fr3i9dujQmJiZER0dTs2ZNfv75Z5o0afIfxfRvJX807xmXpdFoyM/PR6VS6d7Pzc0t9BlTU9PfbVezZk32799PREQEBw4cYNeuXX+5SjWAoaGh7me1Wo2RkRFqtZqFCxfi5eUFvM2KWVlZsXfv3kIxaJNA2vjj4uLIz8+nbdu2TJ06FXib6MrPz9d9zsTEBKDQ9yyoT58+1K1bl7p161K/fn3Gjx+vi/N9n/+jWIUQQgghhBBCCFH0lSpVirFjx9K/f39yc3Pp3r07VatWZdiwYYwaNQofHx8WLVrE1KlTyczMxMvLi/79+/9Hf+vfWuq9RIkSuLi4cOTIEQBiYmJ4+vQpFStWxNraWrck2bFjx/7X/9eCBQvYs2cPXbp0Ydq0ady4cQN4mywpmHT5IwcPHkSj0fDw4UNiY2OpWbMm9erV46effgLeFkbq2LEjKSkpv9u2Vq1a7N+/H3g7Aic0NJS6dety9OhRnj17hkajYcaMGYSHh/9pDNpY09PTSUxMZPTo0TRp0oTjx4/rvkP9+vXZu3cvAJGRkbqiT381ViGEEEIIIYQQQhRNHTp0YN++fRw+fJhhw4YBsHr1anx8fADw9PRk+/btHDp0iLCwMIoVK1Zo++Dg4EJ1hP7Iv5X8gbfTmzZs2ECHDh2YNWsWy5Yto1ixYvTu3Zvz58/ToUMHfv3110IVqd+nX79+HD58mE6dOhEUFMT8+fOBt9Orpk+fzq+//vqn2+fk5NCtWzc+++wzZs2ahY2NDUFBQeTk5NC+fXsGDBjAhAkTKFOmzO+2nTZtGkeOHKFTp04sW7aM2bNn4+npSVBQEAMGDOCTTz5BrVYTGBj4pzFoY42Pj6d79+588skntG3blqysLHJycnj16hVTpkzhyJEjdO7cmYMHD+qGfv3VWIUQQgghhBBCCCH+L1Sa981J+si9u7LYx2z9+vU0aNAAd3d3rl+/TmhoKDt37tR3WEIIIYQQQgghhN7s3H5V3yH813Tt7qPvEH7n317t60OZP38+Z8+e/d3vvb299RDNf87NzY1x48ZhYGCAiYlJoeJNQgghhBBCCCGEEP9tf8uRP0IIIYQQQgghhPj7kpE/H9ZHO/JHCCGEEEIIIYQQRZOMQ/mw/u2Cz0IIIYQQQgghhBDi70OSP0IIIYQQQgghhBBFmCR/hBBCCCGEEEIIIYowSf4IIYQQQgghhBBCFGGS/BFCCCGEEEIIIYQowiT5I4QQQgghhBBCCFGESfJHCCGEEEIIIYQQoggz0ncAQgghhBBCCCGEUBaNRqPvEBRFRv4IIYQQQgghhBBCFGGS/BFCCCGEEEIIIYQowiT5I4QQQgghhBBCCFGESfJHCCGEEEIIIYQQogiT5I8QQgghhBBCCCFEESbJHyGEEEIIIYQQQogiTJI/QgghhBBCCCGEEEWYJH+EEEIIIYQQQgghijAjfQcghBBCCCGEEEIIZdFo9B2BssjIHyGEEEIIIYQQQogiTJI/QgghhBBCCCGEEEWYJH+EEEIIIYQQQgghijBJ/gghhBBCCCGEEEIUYZL8EUIIIYQQQgghhCjCJPkjhBBCCCGEEEIIUYRJ8kcIIYQQQgghhBCiCDPSdwBCCCGEEEIIIYRQFo1Go+8QFEVG/gghhBBCCCGEEEIUYZL8EUIIIYQQQgghhCjCJPkjhBBCCCGEEEIIUYRJ8kcIIYQQQgghhBCiCJPkjxBCCCGEEEIIIUQRJskfIYQQQgghhBBCiCJMkj9CCCGEEEIIIYQQRZgkf4QQQgghhBBCCCGKMCN9ByCEEEIIIYQQQghl0Wj0HYGyyMgfIYQQQgghhBBCiCJMkj9CCCGEEEIIIYQQRZgkf4QQQgghhBBCCCGKMEn+CCGEEEIIIYQQQhRhkvwRQgghhBBCCCGEKMIk+SOEEEIIIYQQQghRhEnyR/wlGlmH7z8mbSf+r968eVOoH0mfEuLDKbi/qdVqPUbycZN2EkJ/3rx5o+8QhBB/A0b6DkB8/OLj4zl06BC5ubl07dqV0qVLY2AgecM/k5aWhrW1NQYGBqhUKjQaDSqVSt9hfXS2bt2KlZUVFhYWNGjQQN/hfJTi4uIICwvDysoKJycnRo0aJX3pT6jV6t8dn2T/+99JG/0xlUrFlStXcHR0pFSpUu/tY+JtO8XGxuLi4oKtra2005+Ii4ujQoUK+g7jb0X60x+LiorizZs31KtXj7y8PMzNzfUd0kdHe46TfvTx0ajlgeaHZDhjxowZ+g5CfLwSEhIYPXo0lStX5pdffuHy5cvUq1eP4sWL6zu0j9aMGTPYuHEjUVFRZGRk4OXlJTdV7xEaGsrZs2dJT09nx44dWFtbU7FiRX2H9VGJj48nJCSEhg0b4uPjw6pVq8jPz6dmzZr6Du2jlJ+fj6GhIRqNhkePHvHs2TOsra1l/3uP/Pz8QhfA0ka/p71ZuHXrFnPnzmXLli00b94cCwsL1Gq1tNn/0LbT7du3mT17Ntu3b6dVq1aYm5tLO71HQkICM2bMwNzcnCtXrlC5cmV9h/TRKdin0tLSyMrKwtraWt9hfZQ0Gg2XL18mIiKCzZs3U6ZMGVxcXCShX4C2LU6ePMnevXs5f/489vb2WFpaSiLoI3Dt6iN9h/Bf413VSd8h/I70ePGH4uLiGD9+PJ999hmBgYH89NNP3Lt3j/379+s7tI/W7NmzSUtLY968ebi4uHDy5Enu3bun77A+Ol9++SWZmZn89NNPhIaG0qpVKy5evKjvsD4qd+7cITQ0lH79+hEYGEi7du0YMmQIaWlp+g7to6TRaDA0NEStVvOPf/yD9evXM3r0aMLDw/Ud2kdHrVbr2mrVqlX88MMPnDt3jpcvX+o7tI+KSqUiIiKCSZMm0aFDB7y9vRk6dCgPHz7EwMBApjb9D207TZ48mfbt21OhQgUGDx7MkydPpJ3eo1y5cnTv3p2xY8eye/dufYfzUVKpVERGRvL555/zyy+/0Lp1a2JjYwGZ9lyQNrnavn17Hj58yN27d1Gr1eTl5elGnYu3/SkqKoqFCxfSvHlzduzYwY8//kh+fr6+QxPig5Pkj3iv9PR0pkyZQvXq1Wnfvj0AxYoVo0mTJlhaWuo5uo/ThAkTSE9PZ+nSpbi6ujJw4ECSk5N59uyZvkP7qMyYMYOIiAi+/vprAIoXL46Liwt5eXlyofI/1Go1ISEh5OTk0KlTJ93v09LSePPmjdxMvYf2Cef48eOpW7cugwcPRq1WU6JECVJTU/Uc3cfFwMAAjUbD4MGDUalUxMfHM3fuXB49KrpP3/5TJ0+epH///vTs2ZP58+fTqVMnRo4cSWpqqiQ2Cvjll1/o378/ffv2ZfHixbRs2ZLhw4eTlpYm7fQ/Ct5oenp60qdPH1JSUoiIiNBfUB8hjUbD/fv3Wb58Od988w3u7u5UrFgRGxsbkpOTZTTL/9CO3szPzyc3N5fJkyfz2WefsXfvXn755RdARnTC23ZSq9UcO3aMSZMm8erVK0qVKsXgwYPZuXMnWVlZ+g5RiA9Kkj/ivczMzPDx8cHIyIizZ88CsG3bNs6dOye1Wd4jNjaWmzdvUqNGDd3vtCMRDA0N9RjZx6d+/foAHD58GIDU1FQ2bdpE1apV5ULlfxgYGLBixQoePnzI/PnzAdi8eTOnT59m6NChMky5gFOnThV6Xbp0afz8/Jg4cSLdu3enc+fOjBs3jvv37ys+uZiSkqL7+fjx43h4eBAYGMjDhw/p168f+fn5XLlyBVDu0/V3v3d+fj6JiYm6n3v06IGpqSmff/65bmSLEr3bTmq1mocPH+p+7tOnDyqVinHjxvH8+XPFtpNWwdF2mzZtIiMjgylTphAaGsqsWbN0x7HXr1/rOVL90fYplUqFra0tDRo04Ndff+Xbb79l5cqVPH78mNGjR8toDQr3p5EjRzJnzhwiIiIICAigUqVKnDhxguPHj7N3717FjujU9qfs7GwMDAxwcnJi8+bNLFq0iLCwMEqXLk14eDj379/Xc6RCfFhS80f8jlqtxtjYmFq1anHp0iXi4uKIiIggMjKSlStX4uDgIPP432Fubk7JkiW5dOkS6enpODo6MmrUKFq2bEmbNm30Hd5Hxd3dHRcXFxYsWIBGo2HNmjW0bduW3r176zu0j0ZeXh6Wlpa0b9+eqVOn8ssvv5CUlMSSJUtwdHT8Xb0WpcrNzWXFihUcO3aMEydOUKdOHQ4fPkxoaCiDBg2iX79+vHjxgkOHDtG5c2fMzMz0HbLeXL9+nfDwcBwcHMjIyMDCwoLTp0+zYsUKWrZsSd++ffn66695+vQpdevWVezxXaVScfHiRa5cuUJ2djYNGzbkyy+/xMzMjKpVq3L9+nVSUlKwsrIiKysLHx8ffYesFyqVikuXLnHt2jVyc3OpVasWM2fOxNbWlipVqnDjxg0ePXqEmZkZOTk5eHl56TtkvdEWmNVoNIwePZorV65w7do17t69S4cOHahQoQJz5sxhx44dmJiYKLattAXDd+3aRYMGDQgLC2Pnzp0cO3YMKysrrl69SkZGBi1bttR3qHqnPT5/9913APj5+REREcHNmzcZMWIEycnJ7N+/n8zMTFq3bq3PUPVCW+MnJiaGQYMGUadOHZydnVm3bh3BwcHUqFGD27dvc+TIEbp37y4zGvRMav58WJL8Eb+jrYZfrFgxfH19iY2NJSoqigEDBhQa2aLUm4P3KVasGM7OzqjVak6ePMmCBQsICAigf//+gKyk865y5crh4uLC3LlzcXd3JyQkBHib9JCkxtuRP9oEUOfOnQkPD6dKlSp07NhR9xml9yftyLrGjRuzYMEC4uPjGT58OLVr1+bBgwckJibi6urKokWLcHR0pF27dvoOWa+MjIy4c+cOixYtwsTEBD8/P/bt20e5cuUIDAzExMSEbdu24ePjo8ibT21C9cqVK3z++eeoVCr27t2LnZ0dQ4cOZebMmdy6dYv169czceJE8vLyeP36NdWrV9d36B+Utp1iYmIYO3Ys+fn5/Pzzz7i4uBAQEMDUqVOJi4tj3bp1TJo0iby8PPLz86lWrZq+Q9cb7bF6+vTplCtXjnnz5mFnZ8edO3e4evUqnTt3pkmTJri4uNC1a1c9R/vhaa+PLl26xM8//8zBgwcpXrw4o0eP5uDBg8THx5OQkMCGDRvo06cP5cqV03fIelPwweuoUaNISUlhypQpVK5cmfLly3P8+HGuX7/O8OHDadasmS7xo7RrUG3NqG3btgHw/fffExAQQOXKldm0aRMHDhxg3759BAUF4evrq+dohSR/PixJ/oj30iaATExMqF69OqmpqaSmppKXl0eZMmXkBv09tAkgQ0NDnj59ire3N56enrr3lXTi/SvKlSuHu7s7u3fvxtraGg8PD+lXBWgTQBYWFrRp04avvvqKhw8f0rRpU8X3pYK1DgAcHR15+vQpZ86cwc/Pj+bNm3PhwgXi4+OxsbFh2rRpgPIugOFfNwtmZmbExsYSFxeHlZUVVatWxcvLi3PnzrFz50527tyJra0tY8eO1XfIH9TTp0/Jzc3FzMyMS5cuceLECYYNG0ZAQAD29vb8+OOPlC5dmunTp1OtWjXc3d3Jy8tj7dq1DBs2DFtbW31/hQ/i6dOnqNVqTE1NuXTpEpGRkQQGBtKvXz+sra3ZuHEjHh4eTJkyBS8vLzw8PMjofgF3AAAgAElEQVTPz2ft2rUMGTJEMe1UUMEb9adPn7Ju3ToePHhA9+7dcXV1xdDQkFu3bhEVFYW/v78uQaa0kdXa0XZffPEFAQEBeHt7ExkZSUZGBtOnT+fGjRvk5+fTvXt3/Pz8FHkc19IWcX7+/DkODg5s3bqVkiVLUqVKFWxtbSlbtiw7d+7EwMCAqlWrAso87z169IiQkBBGjBjBqFGjcHBwYPz48QwdOpRevXrh6+tLy5YtqVWrliLb52MjyZ8PS5I/4g9pE0DGxsb4+vpy5swZ7t69S/Xq1RU9feLPaBNAZmZmnD59mri4OGrVqiUnlj9Qrlw5nJ2dmThxInXq1MHJ6eM7SOpTwRFA7dq1Y/r06bRo0ULxy5drC8iuXLmSxMRELC0tGTNmDNu2bSM6Opp27drh4eFBhw4daNSoEfCvqRdKkp+fr6sLkZ6ejre3Nx06dCAlJYX9+/fzySef0LZtW2rVqkXVqlUZOHAgoJybz9evX7NlyxacnJywsbHh4MGDfP/999SrV4+KFSvi6OiIg4MD3333HTk5OdSsWZOjR49y+vRpQkJCqFSpkr6/wgeRnZ3N1q1bcXJywtraml27drFu3ToaN25M+fLlcXR0xM7OjhUrVqBSqahWrRqHDx8mMjKSSZMmKaad3qXdhzZs2ICxsTGffvopBw4c4MqVKzRv3pwyZcqQn5+PlZVVoZFRStj33vXrr79StmxZevTogYeHBz4+PqxatQpjY2OGDh1K3bp1KVOmDKDM9ilo165drFq1iu7du+Pr68v8+fNxcnKiYsWK2NraUrduXWrXrq37vBLby8jIiNjYWLp164aJiQmVK1cmIyODyZMn06xZMzw9PXUJaSW2z8dGkj8fliR/xJ8qOAWsZs2aeHh44OTkJJnyP6FNAGVnZ2NsbKzYmhAF/Vl/KV++PE2aNNE9pVIa7Y32H7WRgYEBb968wdrammHDhmFnZ6fYfe/27dvY2dmhVqvp378/RkZGGBkZcezYMa5cucKCBQvYsmULy5cv58WLFzRp0kS3rRLbTJskGzp0KGfPnmXZsmWUK1cOJycnXr9+zb59+/jll1+oVq1aoafESkiSvXz5kuLFi1OzZk1yc3NZsmQJI0eOxMzMjI0bN1KnTh0cHBxwdHTE0dGRsmXL4uLigq+vL/7+/opKVBsaGuLl5YWhoSFLly5lzJgxaDQatmzZQoMGDbC3t8fJyQkHBwfc3NxwdXWlWrVqtGjRQlHtpFWwJtvz58/Zvn07ycnJuLq60rVrV3bt2sWlS5do3rw55cqV040QVtJ1lfa7av977949Vq1aRYcOHTA3N8fa2porV65w7tw5cnNz8fb21nfIevNujT+1Ws2rV684dOgQ7du3p1q1asyePRsbGxsqV66sq1+jxP6UnJxMeno6dnZ2bN26lTt37uiuA1QqFbdv32bHjh20atUKCwsLPUcttK7GpvzvH/qb8pHkj/jYvO/k8L7faaeAJScnU6xYMUxNTT9kmB+Nd5+I/9ET8mLFilGlShVd4kcpT9K13r1Y+aPvrv2chYUFRkZGirpY0dY3UqlUnD9/nsTERN2TzYI0Gg1GRkYAREVFoVarsbKyUkw7aR04cIDDhw/TtGlTTp48SUpKCvPmzaNOnTr4+fnx448/YmlpSVBQEFWrVuXTTz/Vd8h6M3/+fDw8PDA3N2f8+PGUKVOGOXPmYGdnx6lTp3BycqJ58+ZkZWWRm5tLly5ddNsqoV/l5uayZcsWYmJiKFGihK74bkxMDMOHD+fFixd8++231KhRg1KlSlG2bFmcnJxQq9UYGRlhbGys76/wwWhHzF2+fJnz58/z4MEDYmNjCQ4OJjk5mTVr1lCnTh3s7e11iUXtiGEltVNB2uLO9+/fx9HREV9fXy5evMjdu3dxc3Ojffv2fP/99xgbGxeqr6WEfQ/+dY0ZGRnJd999x71792jUqBFqtZrw8HB8fX1JSkri8OHDNGnShJycHGrVqqXvsPVG25/CwsJo0KABDg4OWFpakpGRwb59++jevTsVKlQgJiaGxo0b67ZTWn86ceIE48aNIyYmhnv37jFlyhQWLlxITEwMcXFxrF27lsWLF+uSiVLk+eNxTZI/H1TRf7wn/pD2gBkVFcXy5ctZt24dN2/eLHTC0H7G0NCQ3bt3ExYWRm5urh6j1h9tokKj0XDjxg0yMzPf+4RcW4ckIyODZcuWKW66ScElSBcsWMDq1avJzs7+3ee0U1IyMjLo27cv9+/fV8zFyuPHj1m8eDFxcXEA7N69m9TUVKDwEsoFk2F79uxh5syZGBsbK6adCnJzc+Pw4cPExsZiYWHBzZs3efbsGQBWVlZ4e3vz5MkTjIyMdEV41Wq1PkPWm5SUFA4cOACAmZkZHTp0AKB9+/bUrVuXsLAwSpQoQb9+/Zg8eTKgrKXdDQ0NqVGjBkeOHGHChAl4eXkxaNAgMjMzWbhwIZ999hlNmzZlzJgxvHr1Sre/Kek4rmVgYMD58+dZunQp3t7edOvWjfT0dMLCwhg7diw1a9Zk1KhR5OTk6NpHie30rl27djFq1Ch+++03HBwcCAwM5PHjx6xYsYKUlBQ2bNhAjx499B3mB1cw8RMWFoa7u7tu1cGGDRtSs2ZNQkNDmT9/PjNmzKB06dLcunWL3NxcRR2joPD5S6VSsXPnTgIDAwHw9PSkfv36JCYmMmHCBOrUqcOkSZP0FapeaPuDSqUiOjqapUuXsmTJElq2bMmGDRtYu3Yte/fupWHDhpiYmDBt2jRSU1OJjIzUPVATQonkDK1g2kz5ggULcHd35/jx46xevVqX3MnPz9dd9O7du5cNGzYwceJE7O3t9Rm2XmhXFlKr1QwePJg1a9awevXq332uYEIjODiYevXqKe5CWJsg69+/P8WKFUOlUpGTk0NmZqYuMZaXl6drp9GjRzNx4kRcXV31HPmHU7x4cW7dusXGjRt1o+m0F3rvJl/hbeJnw4YNfPPNNzg7O+slZn3RaDSo1Wq8vLwIDAzk5MmTlC1bltq1a7N3715dAujOnTu8efOm0LZK2/e0GjZsyM2bN4G3SeiIiAjde126dMHT05O8vLxC2ygloaid1ubi4sKbN28oXrw4p0+fxt3dnU8//ZTs7Gxmz57NyJEjWblyJcWLF9d3yHqj0Wh48eIFc+fOxdbWlmrVqlGtWjXatGlDVlYWc+fOJSQkhCVLlih2NLCW9tym1aRJEzp27MiCBQu4du0apUqVYujQoTx69Ij09HRsbGwA5SRdtQ+ANBoNWVlZ7Nq1i+XLl/PJJ59gYGCAsbEx+/fvJyAggPXr19OhQweuXbvGsmXLGDFihOIeehR82Hj79m1ycnI4e/YsGRkZDBkyBICqVatSsWJFunTporhRLC9evODq1au6148fP6ZPnz6UKVOGpKQkvv76a/bv38+CBQvo0qULXl5eXLp0iZkzZxIWFkapUqX0GL0Q+iXTvhQsLy+PrVu3MnnyZDIyMrh48SKzZs3ixIkTWFhYYGVlBby98Vy/fj3z58+nYsWKeo5aPwou1erl5cXkyZMpXrw4J06cQKVS4eDgQF5eHkZGRrrET3BwcKGie0VdwVEq0dHRPHjwgKlTp3L37l127NjB1q1bMTIyokKFChgZGfHy5UuCg4MJCgpSVDvl5+djamqKv78/+/fv5+HDhzx+/JijR4+SmprKyZMnMTY2Jj8/HxsbG/bt20d4eDjz5s3D3d1d3+F/UE+ePMHc3Bx4uw8+f/6cY8eO0alTJ4oXL86vv/7KsmXLOH36NKampoSEhOg54o9DxYoVWbVqFRYWFnTp0oUpU6bw6tUr3dQBU1NTOnbsqO8wPzjtMerBgwcADBo0iPLly3P48GHu3btHmzZtMDc358GDBzg7Oyt2SWltO6lUKkxNTXFwcGDNmjXY2Njg4+ODi4sLxsbG/Pbbb5QtW5by5cvrO2S9KjjadfHixRw/fpycnBzKli2LnZ0d3333HeXKlWPLli14e3vTu3dv3bZKSGi8efOGL774AisrK6ysrLCwsGDv3r24ublx6tQpGjVqhJ2dHT/99BOnTp2iY8eOPHv2jJs3bzJ69GjFnfe0CWq1Ws2oUaOIjIzk8OHDXL9+nSVLlrBp0yb27NnDzp07sbS0ZPjw4brtlNCfAE6fPs2+fft4+PAhT5480S2O8eDBA1QqFa1bt+b27dscPHgQf39/KlasiJ2dHT179sTNzU3f4Yt3yLSvD0ulUcpjB/E7arWaGTNmkJiYSF5eHgsXLqRkyZIMHz6csLAwrK2tOXDgAGvWrGH+/PmKOwHDv0byaC1evJhXr16Rk5NDTk4O9+7dIysri9WrV+Ps7Fwo8aOkOeoF2+nNmzdkZmbSoUMHLC0tqVKlCs2bNychIQEDAwOGDx/Oy5cvGTJkCF988YWi2kl7cZaamkqpUqV4/fo1s2bNIjIykk8++YTKlStz6tQpcnNzGTp0KC9evGD27NmsWLFCcfvfrl27WLlyJWPGjMHX11c34mnChAnY29sTEhLCq1evuHHjBgYGBtSoUQNQ5qpe27dvx8fHR5dYBTh+/DiXLl0iJCSEW7dusXr1aqysrChWrJguSaakmwWtEydOMHfuXExNTfHx8WHOnDlERkayf/9+ihUrhq2tLX369MHR0VHfoeqFtk+cP3+eixcv4ubmRqVKlUhLSyM0NJQRI0bQtWtX3agga2trfYf8UdBoNAwdOpSKFSvi5OREcnIyWVlZdOrUidjYWI4dO0bFihWZNWuW7vNK2veuXLlCz549MTMz4/Llyzx//hyNRsOkSZNYtWoVsbGxhIeHM2zYMF0BbO0DNaWaOnUqlpaWfP755yQmJrJs2TKcnJwICQlh69atGBoa0q1bN0B5/QkgJCSEn3/+mZkzZ9KzZ08AAgMDCQgIwMPDg5CQEKZMmaLYh9Z/Jz9t/FXfIfzX9A6ooe8QfkdG/iiI9uRw8+ZNUlJSyM7OpmLFihw7doy2bdvSpEkTYmNjOXDgAM2bN8fS0pKIiAg+++wzxd14QuFlkg8cOEB+fj5lypThzJkzeHh40L9/fwYPHsyFCxfw8vLC2tqaadOmMWjQIEWNZCn41HP8+PFER0dTvnx5+vbtS/v27WnatCm+vr7s2bOH4sWLU7duXc6dO0eLFi2oWbOmvsP/oFQqFREREUyYMIELFy7w7Nkzxo0bx927dzEyMqJTp0507doVPz8/XFxcyMvLo0uXLoocgWBubo6Liwvbtm0jNjaW2NhYGjRogKOjI48ePaJatWqYmZnh7OysW1FIKStVFZSRkcHs2bOJj49n+/bt1KhRA2NjY6ysrFi1ahUeHh54e3vTtGlT/P39adSoEaDMJFliYiLh4eFMmTKFQYMGMW/ePOLi4hg8eDAlS5YkOjqaFi1aUKVKFX2HqjcqlYqTJ08yZ84cWrZsyXfffUdmZia9evXC3d2dmTNnYmlpiZeXl+KnesG/rqvOnTvH5cuXWbBggS5ZfeXKFUqUKEGfPn3w9/enXbt2gLL2Pe20XScnJ6Kjo0lKSsLb2xtPT0+ePHnCjz/+yLNnz/j222/p378/derU0S2QoZQ20iq4MMibN2/Yv38/nTt3pnTp0lhaWuLq6srhw4fx9/enevXquuOU0vqTto1UKhW2trbcunULBwcHnJ2duXv3rq7Wz6BBg6hXr97vthMfHxn582HJyB+FOXbsGKtWraJ+/fpcvHiRjh07YmZmxrp163B0dCQhIYGQkBD8/f31HepHQa1WM3LkSAwNDWnRogWdO3cG3p6YV69eTXx8PCqVikWLFvHmzRvS0tIU+cRYo9EQHBxM5cqVadGiBRYWFmRkZODp6UmPHj0wNTXF3t6er7/+GlDuE72EhATWrl1LixYtMDQ0ZP369TRo0ICAgADGjRuHubk506dPl5uqAlJSUnj8+DELFy6kfPnyGBgYcOnSJYYPH84nn3yi7/D0SntBm5OTo1uhKiUlBUdHRz799FPu3LnDpUuXmDp1qq7+VsHtlEKj0fD06VNmz55NRkYGc+bMoXTp0mRnZ9O+fXt8fX0JCwsr9HkltY+WRqMhJyeHBQsW0LdvX7Kyspg1axYrVqzgt99+w9fXl0uXLlGiRAndTZVSvTsqODExkcWLFxMUFESFChUwNDRk1apVpKenF5qOqqS+pf2uiYmJ2NnZYWJiwu3bt/n000/58ssv6dq1K0eOHCEqKoqmTZvi5+enqPYpSNufNBoNjx8/BuDo0aPcuXOHESNGUKpUKV6+fElQUBBffvmlomokvuvs2bPcvn0bZ2dnWrVqxcqVK/n111+ZOnUqJUqU4MaNGzg7O1OhQgXF9qe/Gxn582Ep7+5LwVJTU1m3bh0//PAD+/btw9DQkDZt2pCamsratWu5d+8eFhYWugMmKGM++p9ZuXIlZcuW5YsvvuDEiRN8++23JCUl0bx5c7KzsylXrhxBQUHA2+XdlZT4KXhSTUlJwcDAgIYNGxIZGUl8fDz79u1j8ODBrFq1iidPnuDh4aHbTmmJH7VazaNHj+jfv7/uIvfNmzeYmZmxevVq3rx5w+LFi7l7964kft7h5OSEk5MTGzduJCoqioSEBA4fPkxiYqK+Q9M7lUqFRqPB1NQUU1NTpk+fzrVr10hISGDs2LHUqlWLqKgosrKyMDExKbSdEhSsXVOyZEn69evHmjVriIiIoFmzZjg7O7N3715atWrFb7/9hqenp+7zSqIdOaBSqTAzM8Pe3p5Zs2bx6tUrvvnmG6ysrFi8eDGrV6+mRYsWgLKSGO8qONp11qxZ2NnZ4ezsjImJCefOnePNmzd4e3tz9epVqlatWmhbJbWZdlWvOXPmYGlpSatWrRg2bBg//PADAwYMIDExUXfcAmX3KW1/Gjp0KObm5pQoUYJOnTpx//59wsLC6NixI1u3bqVMmTKKTPxo+8b169f56quv8PX15fLly8TFxTF8+HCWL1/O9OnTefToEd9//z0uLi6Asva3vzMZhvJhybQvhXj69ClGRkb8+uuvpKens3fvXubOnUtcXBxbtmyhY8eOODo6YmtrC6DIC2D41woLWklJSbx8+ZKFCxfy4sUL1Go1b968wd3dnb59+1KnTh2g8HBdJSjYTtrV4dLS0pg3bx6Ojo50796dESNGcOjQIdq2batbWUFpF3cFv6+lpSWWlpbs3LkTT09P3NzcKFmyJE5OTuzevZvatWsrvnDqH/UPbX9zdXXFx8eHxo0b07ZtWz1E+PHRtpf2GOTg4ICHhwfNmjXD2toaMzMzWrZsqecoPzxtX4qIiGDjxo3s37+fRo0a4eLiwsmTJ3UF1e3s7Bg4cCAODg6KOjbB2xWYtKsoxcbGEh0djZOTE1lZWVy5coVPP/2U2rVrk5SUREREBK1atdKtKqS0tipIm3QdOHAgNjY2lC9fnu7du1OuXDkOHz7MhQsX2LJlC7a2toouQn/t2jXCw8P56quvqFKlCmfPnuX+/ft07NiRhg0bEhERQYMGDXTnPSX3KYDJkydjb2/P/Pnz8fPzw83NjRcvXlCqVClOnTpF6dKlmTx5MqC8aymVSsXFixf55ptvGD9+PAEBAZibmxMTE8OdO3cYPnw4np6etGzZUpFlKv7urhblaV/VPr5pX8p6/K4w2pNDdHQ0oaGhbNy4kWLFivHDDz+wYsUK3NzciI6O5tWrV+Tm5mJoaKiYecPvU7DGz+nTpylRogSVK1cGYMiQITRr1gxzc3PGjh2rW5ZbS0ntVvCp55QpUzA3N8fOzo5atWpx5MgRcnNzSU5OZvny5VhaWipyxAH8a//TFpP18PCgT58+qFQqQkND+eqrr6hVqxbVq1fn66+/1q2up0TR0dFUr15dt7Ttu/1EO71CO0Kh4CgyJfUprXennEDhY5BGo8HFxQUXFxeaNWsGKKsuBLw91pw6dYply5Yxb948Zs6cyfz58/nuu+8wNTVl/fr15OXl0b17d4yNjfUd7gf34sULwsLC6N69O3l5eYSEhGBhYcGhQ4cYOHAgtWrV4syZM+zcuZMXL14QFBRE6dKl9R32RyMpKQkrKysKPj/Nz8/H3d2dDh068PjxY92oH6XtewCZmZls27aN+Ph4ypcvT/ny5cnPz2ffvn2sXLmSfv36sXjxYoyMjBR7HH+XjY0N9evXB94ew1NTU9m0aRMrV66kY8eOFCtWDFBmf4J/HdO9vb2pVauWburpnj17WLJkCWPGjJF+JMRfIMmfIkylUhETE8OcOXMYPHgwtra2tGnThmLFirFkyRIaNWrEunXrmDZtmiIvft+lTWgMGDCAGjVqcPDgQRo0aMDYsWNJT09n06ZNnDt3DmdnZ93QdyXS3qCPGDGCBg0aYG9vz6JFi6hevTqZmZls376dkydPUqlSJUUP59YmfsLCwujSpQunTp3i3r17hISEYGhoyOjRo/n666+pU6eOohM/UVFRbNu2jaSkJDp37vyHCSBtwqNg4kNpfWry5Mm0bduWxo0b/+kNgDZBq/3ZwMBAkTcLsbGxzJw5k6SkJNRqNaGhoSxfvpw+ffrQqVMnypYtWyg5rRT5+floNBpsbW1Zv349Dx484Ntvv6VChQpMnjyZPXv20LVrV2xsbHjy5AmWlpa4u7sr8jj+R9Rqta7Ic/Xq1QE4d+4cAI6Ojrop4EoqQq/tH3l5eZQoUYIePXqQmJhIaGgos2fPpmnTpuTl5bFv3z6eP3+um74kfeqt7Oxs1q1bR+PGjXUrD9ra2mJkZKRL/CixPyUkJGBmZkbNmjXZtm0bPXv2pGzZsnTq1Il69eqh0WhwdHSUfiTEXyTTvoqwFy9eYGlpyU8//YShoSH+/v6ULVsWV1dXXr9+TW5uLr169dKt/iLgn//8J2XKlGH06NHs3r2bTz75BHt7e7KyssjMzKRs2bKMHj0aUN5Ur4Li4+OJi4tj6NChLF26lC5dulC5cmWOHj1Kr169aN26tW5ajlKfUmVmZvL9998zffp0KleuzMmTJ7GysiIqKor+/ftTqlQpSpQooZubrlS2tra8ePGCGzdukJ6ejoeHx+8SQNqET0ZGBkuXLsXb21uRtZFSUlKYOHEitWrVwtXV9b3HIG1bZWZmkp6eTokSJfQU7YdX8ObTwMCAyMhIdu7cyY0bN5gzZw6urq58//331KhRg7p161KyZEl9h/zBZWZmEh4eTs2aNXF2diY3N5fTp09TuXJl3N3d8ff35/jx40RFRVGjRg28vb0LTQcXb9nY2GBsbMyPP/5ImTJlcHZ2Zs2aNdja2hZa7VMpbabd906dOsXmzZv57bffsLa2xs/Pj4sXL3LhwgX8/PwoX748derUUVR9xL+qadOmbNiwgaNHj2Jqaso333xDiRIldKvEgXL6E7z9rsePH2fhwoWkpKSwdu1aOnfuTIMGDRg/fjz29vZUrVoVNzc37O3t9R2u+D+QaV8flvLuyIo4baHmuLg4Jk6cSHx8PJs2beLKlSu6lZbc3d0ZNmwYgYGBuiGmSvXu9C03NzfMzMwICAigTZs2tG/fnn79+vH8+XO6detG7969ddspKaGRn59f6LWzszOZmZl88skn1KtXj759+3Lr1i3dSjDamwUlPaUqKCYmhtTUVLKysrh37x4///wz3bt3p0aNGpw4cYJhw4bRrl076tatq9tnlUbbp8zNzenRoweVK1cmOjqa3bt365IaGo1Gl8x4+fIlI0aMwN/fH2traz1H/2Fp2yogIIAZM2YwaNAgoqKiMDAwKHQMK9hW/fr1Izk5WV8hf3Dam8+oqCjCw8M5c+YMAQEB3Lt3D09PT1xdXbl48SJJSUn6DlWv3rx5g5GREWPGjOHHH3+kWbNmdOnShWPHjnH27FlUKhVffvkl5ubm5OXl6Tvcj8IfHaO7detG69atGTduHMHBwZiamjJixIgPHN3HQbvc/bx582jfvj27du3iyJEjlC9fnmHDhpGSksK0adMAFHf8/iu0+9r27dvx9PQkPj6ecuXKMXfuXOCP+2BRlpSUxDfffMPKlSuxtrYmLy8PtVpNo0aNWLVqFaGhoaSmpv7uOl4I8edk2lcRo82Ub968mZycHNasWUP//v1Zu3YtgYGB5Obm8sUXX+g7zI9CwaU1ExIScHFxwc7OjsWLFzNgwACGDh0KgKurK2ZmZoW2VVJCo2CNn3/+858UL16c9u3b4+3tDUDp0qXJy8vjwIEDlCtXrtC2SnpKpXX9+nVCQkJYv349ixYtIicnhw0bNhAYGMjVq1fx9fUlMDBQN4xbiW1UsL7W5s2bsbCwoFevXhgaGhIdHY1KpaJTp04YGBjoRvwEBwczZswYatWqpe/wP6iC092ysrLo0aMH5ubmDB48mLVr11K/fn3UajVqtRojIyNdW02ZMgVfX199h//BqFQqzpw5w/z58xk4cCCvX7/GyclJt+8lJSVx//59Jk2apOiCoLa2tpQqVYrIyEj8/f2xtbWlf//+bN26lV27dpGbm4ufn5/uplPJ/rdaZJaWlgQEBNCsWTOKFSumG0mmxIdD2v1vwoQJqNVqzM3NGTp0KMeOHaNmzZoEBwfrbtKV1DYF3bp1i/Lly7+3zIKRkZHuWD9u3LhCfU1p/UkrOzsbb29vLly4QEREBIsWLeLy5ctcvXqVL774gjNnzmBnZ6fvMIX425HkTxHz+PFjlixZQlhYGNbW1ly/fp2dO3fSq1cvVq5cyaBBg+jevbviVxUqmNDo168fBgYGPHnyhF27dtGvXz/Onj3Lo0ePuHfvHtbW1oq6iSpIO3JHo9EwevRoSpQoQVJSEsnJybRv3568vDx27tzJTz/9ROnSpfn888912yktqaHRaEhOTiY0NJQaNWroVjh79uwZKSkpLF26lMOHDzN27Fg8PT31HK1+FVzW1sXFhcjISH799VemT5+OoaEhly5dIisri4CAAF68eFG4kI4AACAASURBVMGYMWMIDg5WXOKn4HHqH//4B0ZGRlSqVIkxY8YAMGzYMFavXk39+vUxMDAgIyOD0aNHK66t8vPzyc/PZ+vWrYwcOZKqVaty6NAhunXrho+PD9u3b+fVq1e8fv0aV1dXxR6ftFPimjdvTnh4OOfPn2fu3LmMHDmSgQMHsmbNGvbs2YOPjw/W1taKvOHU+qu1yPLy8nQPQLSU0m7a9lCpVBgYGFCpUiXCw8N5+fIly5Ytw8nJiX/84x+4u7vrHhYpVXx8PBs3bsTPz4/MzEzatWunewCkZWhoSF5eHkZGRmRlZfHkyRPKli2ruP50//59TE1NsbGxITU1lfnz57NhwwacnZ3Zt28f2dnZALpaiUo8ngvxfyE1f4oI7cEvLS2No0ePEhgYiIWFBdbW1ty+fZsDBw5QtWpVxo0bh42Njb7D1TvtiWL16tWULFmSBQsWcOPGDRYuXMjChQspU6YMRkZGlClThgkTJgDKPMFov++aNWt4/vw5CxYsoGvXrhw4cIDk5GTatGlD7969ady4MR06dACU95Sq4AWwpaUlBgYGREVFUbJkSRwdHbG0tKRkyZJcv36dQYMG0axZM0X2pXd99dVXODg4EBoaSkJCAgcOHCAuLo5Ro0aRlJSEubk5VapUYdKkSQwcOJA6deroO+QPTjv1LSgoiOrVq1OzZk02b97Mo0eP6NOnDxUqVGDEiBF06NABY2Njhg0bxujRowvVHCnKtPuRdoTYy5cv2bp1K1u3bsXZ2ZnevXuzb98+atasiZubm+5mQWn7nradjh07xuLFizl06BCDBg2iTJkyXLt2jcuXL+tqaPXo0UORy96/66/WItOOtlNaLTJtO5w9e5alS5fy8OFDDAwMuHLlCj179sTX15ekpCQOHTpE586dFT/Vy8bGhpSUFKZOnUp2djZdunT53WcK9qfRo0dTt25dRdWy0S6SERISwu3bt8nLy6NixYoYGRlx/fp1Xr9+zdq1axk8eDCurq6660ylH6uKAqn582FJ8udvTDsHWJv0KV68OFZWVty8eZOLFy9Su3ZtSpQoQUpKCikpKSQkJFClShXMzc112ynZ999/zy+//ELdunXx8vKiefPm3L17lzlz5jB8+HBq1aqFj48PoLyERn5+vu77pqamcvbsWc6cOYOHhweurq74+fmxf/9+zpw5Q4MGDXTD3ZVW40d7AXz69Gn27NnDhQsX6Nq1KyYmJuzYsQMnJydcXV2pWLEizZs3x83NTbGJn4J9Ct5Oj6tXrx5Xr17FxsaGkJAQQkNDSUpKYsiQIbqRK40aNVLcSMWCfSQmJoZLly4xY8YMLl26hKWlJWlpaVy+fJkuXbrQtm1bKlWqRFxcHM2bN9ctL13Uadvo/Pnz7N69m+fPn2NqakrHjh3p3bs3derUwdLSkp9//pkOHTooekU9lUrFyZMnWbZsGZ9//jn79+9n27Zt9O/fHw8PD65fv853331Hz549qVSpkr7D1SvtcapYsWJ4eHjw9OlTYmJiyMjIKJQA0o7K09Yi6927NxUqVNB3+B+MNvEzc+ZMWrduTdmyZWnXrh3Z2dncuHGD8PBwjh49yj/+8Q9q1qyp73D1puB5T9uv0tLSsLGxwd7evtDy7QWnOI8cOZJq1arpM/QP7v79+0ycOJHZs2cTEBCAj48PVlZWWFpa8uDBA+7fv0/fvn1p3LixvkMV/5/FXim69QmrVnPWdwi/I8mfvzHtaIPIyEgWLVrErVu3OHr0KPXr1ycxMZG1a9diZGTEt99+y+DBg7lz5w5169bFwsJCbj55W8snISGB1NRU7OzsKFWqFP7+/sTExBAbG0vTpk0LjepQioK1kM6dO4eNjQ2NGzfm9evXXLhwAWtra8qUKYOfnx+vXr0qNCJDSe0Eb79vREQE//znP+nWrRubNm0iJiaGcePGkZOTw7p163B2dsbFxUXXNkprIyjcpw4ePEh2djbm5ua66Tk+Pj6UKVOG+Ph4SpUqRcuWLYG3N/hKW4r73eNU8eLFefz4MSYmJty6dYsRI0YQHx/P6dOnUalUtGrVCng7UkFJq1dpExpz5syhRYsWfPvttxgaGtKpUyeuXLlCWFgYGzZsYOTIkbqluJUkPT2dtLQ00tLSsLCwYOPGjXTv3p0KFSqQkpJCfn6+LuHTokUL2rRpQ8WKFfUdtl4VrEX2008/8eDBA7p166ZLtr58+VKXANJOswwODlbkaLv8/HxOnTpFrVq16NOnD6VLl8bQ0JA7d+7g4+NDjx49aNmyJTVq1FDsAw/tFC61Ws3atWvJzc1l6NChZGdns2XLFlxcXChVqhSZmZmYmZmRkZHBqFGjCA4OVlx/Sk5OxsDAgISEBPr166d7kHj48GGio6MJDQ2lfv36VKhQQbH9qSi7eqXojvz5GJM/UvPnb+jp06fcvHmThg0bcvv2bebOnct3333H6tWrefLkCdWrV8fLy4sTJ07w9OlTFi5cSLFixUhMTMTISJn/5AVrZ8ycORNra2tKlSrF8OHDWbp0KUePHgWgatWqLFmyRLed0k4wBdupf//+qFQqbty4wTfffEPnzp3Zt28fW7duJTc3l/r169OrVy9AmVPitE6fPs2SJUu4desW5ubmjBs3js2bN9OtWzdevnypmwqmZNo+1bdvX+zt7TEyMmLOnDm8fPmSo0eP0q5dOyZPnkzp0qUJCQkBlNmnCu5/wcHBWFpaUrp0aUaOHMn27duJjY2lePHiJCQk0LZtWwYMGKDb1tDQUI+Rf3j5+fkcO3aMpUuXkpWVhbGxMUOGDOHcuXMYGhoyZswYNBoNlStXVlxfunv3LpMnT8bc3BwHBwc6d+6Mqakptra27Nmzh9q1azNixAjatm1LUFAQq1evlqW3kVpkf4V2pGtaWhqPHj3i/Pnz9OzZE2NjYzIzM4mKiiIoKAhXV9dC2yiRNvEzcuRI7OzssLOzQ61W06tXL2xsbFi1ahWLFy9m6NChNGnShKCgIEX2p1OnTrFhwwY+++wzYmJi2LFjBz169ACgWLFiuimD2kLZSu1PQvz/IiN//mY0Gg2bNm0iMjJS90TYw8MDU1NTdu/ezVdffcWFCxd4+PAhPXv25PXr1+zbt4/169czZ84c3Nzc9P0V9EKlUumKpnp6euLh4cHEiRMZOHAgdevW5dSpU/z222+4u7sruohcwVpI9vb2LFiwACsrK5YsWULNmjWpXbs2CQkJaDSaQgUcldZOAE+ePMHc3JxDhw5x6NAhLl26xFdffYWrqythYWE0a9aMhg0b6go/K9327dvJzs4mLCwMf39/TE1NycrKIjk5mePHj2Ntba1bCliJ+x78az8aOXIkpUuXZsiQIdSuXRszMzOePXvGkydPWLFiBSVLllRkkqzgVC9TU1OSk5PZtGkTx44d45tvvsHKyopx48bRr18/ypYtqxsJpZT2AYiLi2Ps2LEMGDCAMWPGUL16dSpXrkxeXh7Vq1fnwIEDdO3alaSkJNLT0wkMDKRs2bL6DvujIbXI/txvv/2mm5bTvn17zp49q1s5LiEhgW3btuHv76+oWjXv2rZtG/b29pQoUYKDBw/y6NEjZs+ezZ07d9ixYwcLFy5k8ODB1KhRAzc3N9q3b090dDT+/v6KG6WYmJjInDlz6NKlC/7+/ri7uzNlyhRycnJ0RbK7dOkix6giTkb+fFjKHAbyN6W98A0MDOTLL7/k+PHjVK5cmR9++AGVSsXmzZuxtbVl6dKlutWp6tevj5GREYGBgTg7f3wd8EO6ceMG3t7e9OvXj+DgYGbMmEFycjJJSUkMHz6cM2fOKPZpVcEbyEOHDhEZGalbDrlXr16oVCqmTft/7d15dI3n2vjx786wk8gok0hERiIDoRGUxhDTiaHFq4qQoKRonCpaFqpaQw01lUNUa6iptG9NpVEiVae0kpJDY0jEkBJJSBAZyLD37w+//bxJtT19z9vakuf6rGUte3hWrn2v+5mu576vexYzZszg5ZdfVm3RcEM7ZWVlsWzZMqKjo4mJiSE+Pp5hw4bh6elJSkoKeXl5FBcXq7ad4PE6WTqdjhs3bqDX69FqtRQUFDB16lRmzZqlFFj/te3UprS0FDMzM8aOHassY3vy5EllClNoaCgDBgwA1NdWGo2G1NRU3n//fWbOnImfnx/JyclER0fj5uZGVlYW5ubmNVZeUpPKyko2b97M4MGD6devHwBubm5s3bqVVatWYWdnx+3bt2ncuDHr169n3rx5tG7dWlUJxF8yTPUycHR0pFWrVnz11Vc0b96ccePGKdNQ33zzTWWfnDNnDjY2NkaJ2Rj0ej0lJSV89NFHWFpaUlpaCsDkyZN57733GDFiBCUlJcTHxxMQEGDkaI1Hp9NhaWlJgwYNyMnJwdnZmXr16tGlSxciIiJo2bIltra27N+/n7i4OKWu5LPPPmvkyI3jzp07ODs7s3//ftq1a8ezzz7L+vXrSUpK4saNG0yZMoXnnntO1ccoIf5sMvKnFjEc+E6cOEFiYiJXr16lrKyMyMhI7O3tsbGx4d69e2zfvp2BAwcqyR4PDw9sbW2NGbpRVK+dodfruXPnDps3b2bPnj306dOHl156iR9//JEzZ87Qu3dvgoKClO+q6STzyxojXl5eaDQarl27RklJCQEBAYSEhFBVVcWFCxfo1q0boL52gkf7YFJSEgkJCZSUlHDx4kXs7Ozo06cPy5cv59SpU3z++edMnTpVdcUaq6te4yc9PR29Xo+1tTV37twhNzeX4OBg6tWrx759+2jWrBmNGzcG1FcwHB7f/wA2b96Ms7OzUoOltLSU69evM2jQIAIDAwH1JX6qqqooKipi8ODBNG/enNjYWJycnJSCvFu3bmX37t2MHTtWdU/PDUxMTDhw4AChoaFKkfSjR4+yYcMGEhISuH79OhqNBn9/f6Kjo3nuuecAdT3oqE5qkf17hvN8ZWUlVlZWhIaGcu7cOW7fvo2rqyve3t707t2b9u3b88ILLxASEqLKawOA8vJyzMzMCAgIYPXq1ezevZuwsDACAwOJioqiX79+tGrVij179tCwYUPlGkFN7VX9AVpubi6enp74+/tTWFhIamoqgYGB+Pr60q5dOzp06KBcG6ilfdRKRv48WTLyp5bJyclRliP38/MjISGBwsJCPDw8WLp0Kd7e3rz22muqmjP8a6oXbly/fj329va8+OKLeHt7889//pNBgwah0+n48ssvCQ4OrrGtmk4y1WuMTJw4EScnJ6qqqhgxYgTFxcWcPn0anU5H//79GTFiRI1t1dROBvn5+SxfvpwlS5bg4OBAenq6UrPmiy++ID8/H0DVK+bo9XqlT40bN46qqiosLCyoV68e7u7uZGVlMXz4cOzt7bG1taVdu3bKtmrrU9WPU++//z46nY6WLVsybNgwpk+fTmVlJaGhoaxevfqxUWRqSfxUX87dwcGBZcuWERcXx5dffkmfPn2Ii4vj9u3b5OXlUb9+fdUWBNXr9VRUVHDr1i2uX7+uvFe/fn0SEhJwdXWlUaNG9OjRQ0ngq53UIvt9ht+anJzM7t27qaiooHfv3owaNYr169eTmJhIZGQkzZo1qzG9WS3tU51Op0Or1aLT6Zg5cyZRUVHk5OSwc+dORo0ahZWVFatWrSIlJYVmzZoRExOjbKum9jL0pyVLlhAeHs4PP/zAjBkz6Nq1K4cPH2bFihW8/vrrqp42KMRfTUb+1DLl5eUcOXKEiIgInJycCA0NZf/+/WRmZhIdHc2IESMICgpS1QXKrzExMUGn0zF+/HhMTExwcXEhMDCQzp07c+3aNVatWsWBAwdwd3dn2rRpxg7XaDQaDXq9ngkTJhAWFkbfvn2ZMWMGgwYNIiIiglu3bnH8+HFcXFyUkWRq7luFhYUcOnSIuLg4bG1tcXBw4MKFCxw6dAg3NzfCwsKUaQFqZegb8+bNU+pGeXh4UF5eTnZ2NjExMXh4eBAcHMz48eMB9fYpw7LR48ePx9LSkmeeeYY1a9bQvHlzoqKi2LNnD2lpaaquh2QoMJuQkMDFixcJCQmhT58+vPLKKwQEBBAQEIC9vT3u7u44Ojoq26iNRqPB1NQUW1tbEhISaNSoET4+Pri6umJjY8OPP/7ImjVr6NevnxR3rkZqkf02jUbDiRMnWLZsGbNnz+b8+fMcPHiQ+Ph4mjVrxt69e7l79y7NmzdXivGqlaFfLF++nCtXrjBhwgQiIyP55ptvOHXqFF5eXvj7+xMeHq4U6tfpdKrqTwDZ2dksWbKENWvWYG1tzcmTJxkzZgzOzs44OTlx6dIlmjZtqhzLhTrIyJ8nS0b+1DK2trYEBgZy8uRJrKys8PT0JCoqig8//JDAwEBlepfaTijVGS7Q9u3bh7W1NTNnzmTXrl288847pKSksH79esrLyykvL8fPzw9Q3xSK6vLz8/Hx8eFvf/sbb731FjNnzqSyspLFixczefJkPD09a4wkU1PfMvSl69ev4+TkhKenJ8HBwSxZsoSJEydSv359fHx8yM7OJjk5maCgIJydnVXVRtVVvzm6f/8+nTp1AiAoKIiHDx+SmpqKk5OTst+BOve9zz77jH79+mFubs4PP/yAVqvl7bffBqB58+aMHj2ayZMns27dOioqKpQbKzW21ZkzZ1i5ciU9e/akrKyMiRMnMnv2bDZv3szw4cNZtWqVjGSpJiIigosXL7J06VJu3bpFkyZNKCsrY+HChaqfjgpSi+x/6+bNm0ybNo2srCwuXbrEP/7xD5YuXUqXLl2Ii4vDzMyMevXqGTtMo6l+zrt37x7Z2dk8fPiQs2fP0rx5c+bOncv06dP56KOPmD17tjJCSq39yc7OjrZt2/LFF18ohfq///57duzYwcaNG/H391dlmQq10+v1xg5BVWTkTy1jamqKu7s7Bw8e5OjRo2RlZbFhwwamTJlCixYtjB2eURlqZ1S/8b548SIzZ87EzMyM9u3bY2ZmxtWrV+nWrZvyZEFtdUZ+WWOkoqKCTZs28fnnnzNw4EAGDx7M/fv3OXLkCM8//3yNeixqS2poNBqOHDnC1KlTSU9PJycnh+bNm3Pz5k3Wrl2LmZkZCQkJjBo1ioyMDNq0aaPKC5cLFy4oSS9D/7p58yZXr16lcePG1K9fn0aNGrFz505at25dY3SU2vpUXl4eGzdu5MSJE3Tq1Ini4mIOHjzIf/3XfwFgb2+PlZUV165do02bNkoxWrUdp+DRylVTpkwhJiaGoUOH0rp1azw9PVm/fj3jx4/H19cXS0tLWQmmGlNTU0JCQnB2dmbLli1kZGSQnZ3N8OHD6dKliyqP4wZSi+zf+2X/SEtLY/HixVy+fJkVK1bQoEED9u/fj4+PD2FhYTI9h0fnsJiYGJo1a0a/fv24dOkS2dnZ2Nvb4+rqSteuXXnw4EGNleHUsg8a+tPdu3cpLi5Gq9WyZcsWTp8+zYoVK/D09CQ/P5/c3Fy6dOmCpaWlsUMWRnDmXznGDuEv06KljPwRfwI/Pz8mTZrEyZMnyc7O5u23365RN0ONqtfOMKxGYWFhwZAhQxg2bBjOzs44Ojpy4sQJ7OzsamyrlpMw1GynTZs2YWpqSmRkJH379mXBggW0bt2anJwcVqxYoSyTbKCmdjI4ffo0K1euZPny5Wzbto3k5GQ6dOjA4MGDadSoEXl5eSxevBitVsvVq1eVp8RqkpqayuzZs5kyZQqdO3dWkhUtWrRQnuYFBgbyzTff4O7urhQxVitXV1cmTZrExx9/zLvvvsucOXNwcHAgPj6eVatWAZCUlKSs2Gigxv3PwcEBW1tbduzYQf/+/TExMaFFixbY2NiQm5tLr169AHUmpn+PlZUVvXr1olOnTlhbW/Pw4UOlQLFa20lqkf0xGo2GY8eOce7cOQBiYmI4duwYDx48wNnZmePHj5OSksKgQYOMHKlxGUbuGPpGp06diI2NZfv27YwdO5Z169Zx4MABKioqaNmyJQMHDgTUd6zSaDQcPnyYdevWUVJSwsCBA2nbti27du1i9+7dVFVVcfDgQSZPnqyaBKsQxqbRy1grUUfodDqGDx9OkyZNMDc3p7S0FFNTU8aMGcPWrVtJSUmhadOmvPfee8YO1agMF7+hoaHcvXuXL7/8kuPHj/OPf/yDH374AXNzc7y8vFRb56D67924cSPl5eWMHDmSRYsW4ejoyOnTpwkNDWXo0KFcvnyZffv2cerUKRYtWkSzZs2MHP2T9/DhQ/bu3cu+ffsYOXIkXbp0UT67fPkyKSkppKWl0aRJE0aNGgWor0/9kl6vJysri4SEBOzt7Xn99dd58803KSoqQqvV4u7uzty5c40d5hNn6BcXLlygpKQEV1dXLC0tmT9/PlZWVsyfP5+MjAwmT57MBx98gI+Pj7FDrhXUOsXk18ydOxdzc3OmTp1KWloaqampZGZmEhcXR2ZmJubm5nTt2hVQ13Gq+r43ceJEBg8ezHfffcf9+/dZvHgxCxYs4OHDh9y7d49XX32Vzp07Gzvkp8LZs2cJDAzEzMyMbdu2MX/+fHbu3ImTkxPLli2jY8eOSpJajS5fvszs2bOZPn068OiaKjg4GF9fXzIzM7lz5w7t27enbdu2qtrfRE1bNqUaO4S/zLDYp28BJkn+iFrt7Nmz+Pr6Ym1tzeHDh9m/fz/Lli0D4MqVK6xZs4awsDDCwsK4ceOGUoNEbRfD1X/v/v37uXLlCi+//DLx8fFERkYSEhJCgwYNcHBwoKysTFlZSG3tZLj4SEtLo7CwkPv371NcXIy3tzf5+fn079+fUaNGYWlpyWuvvUZAQAApKSl4eHgoBbHVqLy8nD179rB3715GjRpVIwH0+uuv07lzZ1544QVAfX3q9xim7VpYWPDWW2/x888/KwVUQZ1tdejQIRISEmjVqhUXLlxg2LBhhIeHM2nSJK5evUpISAjDhw9X/WhX8cdVv6mcOnUqnTp1olevXpSXl3P69Gk2bNjAggULcHBwULZR476XkpLCjh076Ny5M3369AFg2rRpFBQUsG7dOoqLiykvL8fR0VG1N+rV+8W2bdtISUlh4MCBtGvXDlNTU9auXcvq1av5/PPPcXJyUnXh4uvXr7N48WKKi4uVafLXrl0jLi6O6dOnK9fjQkjy58lS15lN1Ck//vgj06dP59tvv0Wv1+Pg4EB+fj43bz6qGu/j44OlpSUajQZ/f3/VJn7gf1YVunnzJmZmZuTk5DB+/Hg6dOhAdHQ0+/btIzExEUtLSyXxo6Y6BwaG1U2mTZvG7t27OXHiBCdPnmT58uVKYdDbt28THx9PQEAAAOHh4apO/ABotVpeeOEFnn/+eT7++GNSUlIAGDJkCPfu3VMSP2rsUzqdTvm/Xq+v8To7O5tBgwZx//59JkyYgLu7u5L4UUtb3b17l59//hl4VFx269atfPLJJ4SEhFBZWUlYWBhlZWUsXbqUoKAgHjx4oCR+5NmV+D0XLlwAUGqRAQQHB3Pu3DmuX7+OVqulbdu2lJaWcuvWrRrbqmHf+6XS0lKOHj3KxYsXlffmzJmDlZUVxcXF2NjYqHpFPajZLwYOHIivry+HDx/m+++/B2Dw4MH4+/uza9euGnUl1ahRo0a0bNkSjUZDSkoKJSUleHl50a9fP4qKiowdnhCqJQWfRa2k0+nw8PDAysqKPXv2YGVlhaurK3l5eeh0OmxtbZVaEZ6ensoNFajrosVw0aHRaNi8eTO7du1izJgxLF++HDs7Owy7/4YNG2jZsmWNaUtqaicDwyo5c+bMISYmBm9vb4qKipQVv1avXs2UKVNo27atsUN96piamtKkSRM0Gg2ffPIJS5YsoXHjxqxbtw5QZ9LVUGMLHq1+ptFolLpQ7777LpmZmQwaNAhvb28sLCxUd5zKzMxk/Pjx7N+/n59++omIiAh++uknLl++zP79+1m8eDHp6els3ryZfv360b59e/77v/+b06dP061bN1W0kfjPpKamMn36dNzd3fH29laOPXq9npSUFM6dO8etW7dYs2YNTk5OvPTSS0aO2Lj0ej3e3t4EBgaybt06vL298fb2Ji0tjT179hAVFYW1tbWxwzSaAwcO4OXlhUaj4Y033iA5OZnvvvuOl156iYsXL5Kenk5+fj6bNm2ie/fujBs3TtlWjccpwzL2rVq1Ijc3l7S0NGVk67p163j++efx8PAwdpjiKSEFn58sSf6IWqf6DdWNGzc4evQo58+fp0mTJlhYWJCens6WLVv4+uuvsbKy4o033jByxMaj0WiUC4/Q0FC2b9+Oqakpo0eP5uOPPyYtLY1t27bRuHFjxo8fb+Rojauqqorjx4/z6aefEhgYSHBwMLa2tvz8888UFRUxcuRIIiMjefbZZ1U75P3fMTU1xd/fn5KSEmxsbFi+fDmg7sSPTqfjlVdeYe/evdy4cQNnZ2cuXrzIsWPHWLhwIebm5jg6OhISEgKop87I5cuXmT59OsOGDSMmJoZFixbRrl07rly5wtGjR5k9ezZNmzbl0qVLZGRk0KVLF2xtbenevTvPPPOMKlfVE3+ck5MTVlZW7NixAwcHB6U+lJubG76+vjx48IBTp04RHBysXCOoZd+Dx3+rRqNBr9fj5eWFh4cHc+fO5cSJE/z000+MGDFCOT6p0YwZM7h27Ro9evTg1Vdfxc3NjdGjR/P111+TkZFBTEwMpaWlnD9/HisrK1577TVAXf3plzQajZIACgsL4+rVqxw6dIiMjAzGjx/Pc889p3wuhCR/niz1LU0jaj3DUq0vvfQSgYGBhIeH4+rqyieffEJsbCxt2rShrKyMoqIinn32WUCdN5+GC4/Y2FhcXFwYN24c8fHxnDp1Cg8PDz7//HMuXLiATqdT9ZQ4A1NTU6KioigtLSUpKQl3d3c6dOiAh4cHhw4dws3NTXnyKRcsv02r1TJs2DBlhIta+5ThOLVixQpCQ0Np/IxzSQAAFYFJREFU1aoVSUlJ7N27l2eeeYa1a9cCUFFRgbm5ubKdGvrWpUuXmDVrFi+++CIDBgygqqqK3r174+3tTVRUFJWVlWzdupUTJ07w6aefMnv2bGW1qvr16ytTU4X4LRYWFsp00/Xr1wMotch8fX1ZuXKlKmuRFRcXY21trSR7fi0B1K1bNywtLXnrrbcYOnQokZGRqk1kTJ8+nezsbLZs2UJhYSFmZmZK8eLVq1fz8ssvKys3VqeW/lRWVkZVVRU2NjaPfWZiYqK0w4gRI9BoNPz0009UVVVRUlKi6pFkQhiTjPwRtVJiYiI5OTksXryYiIgInnnmGY4dO8bBgwdp2LAhEREReHp6AuqpnfFLhgu1oqIikpKSuH//PsnJydy7dw97e3uaNWuGl5cX3t7egHouVn6PqakpTZs2Ra/Xs2TJEi5dusTBgwcZPny4UuNH/HvVp1iouU9t2LCBTz75hAULFtC0aVPq1atHVlYWubm51K9fHxcXF2UUo1qUlZURHR2Nt7c3kydPpqqqipEjR/Ldd99x48YNLCwsqKiowNXVlcrKSkaNGkX79u1Ve/Mp/nOGqagA27dvx9PTEw8PD4YMGUJVVRVTp04F1HOcKioqYvXq1fz8888EBwcrtQB/mQCqqqrC29ubgIAA5syZg6+vL35+fkaM3DhmzZpFamoq9+/fJzw8HHt7exISEoiIiFCKgzdt2pTz58/XWP1MLf3p4cOHbNmyBTMzM0pLS7GwsECr1db4jkajobKyEhMTE1q2bMnJkycpLCwkLCzsse8K9fpXWt0d+RP6FI78qftHJ1Enubi4KIVCDYUcDfU0CgoKanxXTTcMmZmZSp2fjz/+mIyMDAYMGEBQUBA9e/YkPDycpKQk3n33XXJzc2tsq4aLlT/CwsKC3r17ExMTQ1paGp07d1aefIr/HTXte4ByLDLo27cvfn5+yrSS8PBwunbtyp07d7hy5YoxQjQ6Kysr3nzzTTIzM9m1axeTJk3C19eXBQsWEBAQwOnTp9mxYwfHjx8nKiqK1q0frZShtr4k/hyGYvT9+vXjgw8+oEOHDtjb2yujgdQ09cQwxTQjI4Pdu3crv736ua164sLd3Z2hQ4cqCTQ1Wb16Nffv3ycxMZG4uDgmTJjAvXv3iI2NZdSoUWRmZlJaWsqaNWuUUa4GaulPFhYWNGzYkJkzZzJixAjy8/Mf+45er1faJykpifLycqKjo391pJAQ4smQkT+iVqpXrx7p6elUVlZiY2ODg4MD+/btY+zYsfTt29fY4RnFpUuX2Lx5MyYmJnz55ZfcuXOHDz74gJCQEAoKCvjnP//JjBkz8PLyIiAggPbt2xs75KeWqakpAQEBWFtb89lnnylFQ4X4LdVr/Kxbt46zZ89SUlJCTEwMJ0+e5MCBA/Tq1Qt3d3d8fX1p06aNsUM2Gj8/Pxo2bMg777yDlZUVH3zwAb6+voSFhdGjRw/69+9Pu3bt8Pf3N3aoog6QWmSPfqtWqyUoKIi8vDzOnj3LvXv3CAgIUEYAwf/UCdy9ezfz589nxowZqizM6+npycCBA4FHK8Tp9XrmzZvH6NGjcXNzY8mSJZw4cYL69esrC2eoaXSiIXHo7e3Njz/+qKzC6ODgoExjrt4e+/btY82aNUydOlUZlS+EwRkZ+fNESfJH1EqWlpZ4e3tz5MgRPvvsMxITE9FqtYwePRpQ10nYwNHRkWvXrjFr1iwsLS1ZsGABPj4+JCUlYW9vz+HDh3FxcaFPnz60aNECUGc7/VFmZmb4+vpia2tLSEgIdnZ2xg5JPMUM9Q2GDx+OVqultLSUixcvcurUKSZNmsQ333zDzp076d+/v1KzRs37n4+PD02aNOGrr77CycmJpk2bAo9qINna2irLJAvxZzA1NSUkJIQePXoA6kr8GEbzXLlyhZKSEjp27EhBQQGnT5+mqKioRgJIo9Gwd+9etmzZwqJFi2jcuLGxwzcKw8gUQ5KjZcuW6PV6Fi5cSHx8POPGjaNNmzbKw0Y19qeLFy9y+/ZtoqKicHNzY8OGDdSvXx9fX1+qqqqU9ti3bx+bNm1i8eLFktAXv0qSP0+WJH9EreXo6EhYWJiyRPmYMWMAdZ2EgRonWa1WS2VlJXfv3sXZ2ZmIiAhatGiBi4sLJ06cwNXVlfDwcGVbtd54/lFmZmYEBARI4kf8pmXLlnHo0CE6depEUlISN2/e5L333iMiIgI/Pz++++47HBwcGDJkCCUlJYSFhSnbqn3/8/b2plGjRixduhQrKyuCgoJUVwNJPDlqrUWm0WhITk5m8uTJHD16lLS0NP7+979TWFjImTNnuHXrFkFBQcqo4Y0bN7JgwQJVTvf6perH6NDQUHQ6HRMnTqRnz554eHgo0+bU1p++/fZbZsyYAUCDBg2IiIjAzMyMbdu2kZOTQ0pKCm3btmXv3r1s3LiRhQsXSuJH/CZJ/jxZstqXqNVsbGxo1qyZ8lptJ+HqU02Sk5Oxs7Nj9uzZHDhwgLVr12JmZkarVq0IDg5m165dqmqbP4vab9DF7xswYADx8fF8+OGHtGjRgvz8fHJzc3Fzc8PHxwdra2vy8/NxdnYmLi4OUPeIn1+KjIykqqqKefPmERERgaurq7SN+EuprX+lpaWxatUq1q9fT1ZWFq+++ip6vZ4FCxZQXl7O2bNn6dq1K2lpaaxdu5Zly5bJjfpviI2Nxd/fHx8fH+U9NfSnvLw8Hjx4gJeXFzdu3OD9999n1apVmJmZce3aNRYuXEhMTAxOTk4kJiYSGRnJ3bt3OXLkCIsWLZL+JMRTRKOXKqZC1Go6nY6xY8fi6enJ3bt3uXfvHh999BGbN2/myJEjFBcXEx0dTb9+/QC58RTiz5adnc24ceNo0qQJ9vb2tG7dmtatW9OwYUPGjh1Lx44dGTp0qLHDfKoVFBTg5ORk7DCEqHO+/fZbMjMz6dOnD9u3b6d79+7ExcXRsWNHJkyYADwq7nz58mVMTEykvt0fpKZR5qtXr6Z79+54eXnx4MED1q5dS0lJCbm5uVhbW1NVVUV+fj7btm2jvLxcWcnLsLqsEL9n88ZUY4fwlxk+orWxQ3iMTPsSopZLSEjAy8uLsWPHsmnTJgYMGICNjQ3t2rXDw8MDHx8fJfED6nhKJcRfKTExkbt37+Lk5ERRURFubm706NGDzz77jIyMDODR0tJff/01lpaWvPnmm0aO+OlXr149Y4cgRJ1geMBz8+ZNysvLKSgowMbGhry8PAoKCujbty+3b9/m0KFD9OnTBy8vL3Q6HY6OjsoS5uLfU8O1lKEvhYeHU1payvvvv0+DBg0wMTHh3r17DBw4kOHDh9O8eXPS09OJjIxEq9UqtZIsLS2N/RNELSDTvp4smfYlRC1TWVlZY2lRU1NT9Ho9r776Kj179qR///5MnDiR2NhY2rZtq3xPTU+phPirpKenM3HiRAB69epFVlYWbdq0wcfHh5iYGBYuXIiZmRnTp0+npKSEZ599FpD9TwjxZGg0Gg4fPsxHH30EwFtvvUVwcDAzZ86kffv2XLt2jZ9++omEhAT8/PwA5NgkfpUhwfX9999z9epVioqK2LNnD9HR0QwYMIDvv/+elStX8u233zJ+/HhlpS/pT+J/QyYhPVmydwpRi5w7dw4zMzOqqqqYP38+H374IVevXmXlypUEBwfz8ssvA5CTk8ODBw9qbCsnYyH+74KDg1m3bh0+Pj54eXmxcOFCmjRpwuHDhzl+/DiFhYV8+umn5OXlKYkftdUiE0IYz88//8zy5cuZP38+y5YtIzg4GHi0SurKlSsZN24cQ4YMISQkxMiRitrgwoULvP3220RGRrJq1Sqqqqr48MMPOXPmDBkZGVhbWzN58mS6d+8uN/FC1AIy8keIWiI1NZXZs2czadIkkpKSsLKyUk60Dx8+JDk5GRMTE86fP0+TJk2UG08hxJ8rIiKCadOm8c4779CsWTMGDRrEoEGDAHjllVe4f/8+QUFByvfVMD1ACGFchik6d+/exdraGl9fXwDKy8tZu3YtERERxMbGAuDp6Sn1/8RvMvSN8vJyduzYgVarJT8/H1dXV+bNm8esWbPYsmULo0aNUhZdkf4kRO0gNX+EqCWcnJywsrJi+/btlJSUsHTpUlq3bk1gYCCFhYU0adKE+vXrExAQwGuvvQagzLsWQvy5DMuUL1iwADs7OwIDAwGws7PD1dUVkP1PCPHXM9x0FxcXY2FhgaWlJenp6eTm5tKsWTO0Wi2nTp0iLy+Pbt26KQV45dgkfotGo+Gf//wnxcXFdOvWjezsbC5fvkz9+vVxdXWlS5cuHDlyhBYtWuDi4qJsI8R/4l91ueZPKw9jh/AYSf4IUUuYmZnh7++PXq9nz549+Pn54evri62tLadPn8bX15eYmBhlKLfUGBHir+Xr60vjxo1ZsmQJFhYWhISE1LgAlothIcRfTaPR8O2337Jy5UqOHj1KZmYm9vb2PHjwgC+++AJTU1PWrl1LTEwMHh5P342IeDodO3aM+Ph4evXqRZcuXUhJSeHatWvY2NjQoEEDunXrpiR+hPi/kOTPkyXTvoSoRSwsLBgwYAAmJiZ8+eWXAHTt2pXr168row0MJPEjxF+vS5cuPHjwgH/961/GDkUIoUJpaWnMmTOHuXPncvPmTXJzczl9+jSDBw+msrKS1NRU3n77bdq0aWPsUEUtcOfOHezs7IiOjsbU1JSXXnqJHTt2EBcXx8qVK/nqq6/w9fXF2tpaHnAIUQtJ8keIWsbc3Jy+ffsCMH36dHx8fAgJCWHkyJFGjkwIdYqKiiIqKsrYYQghVOjcuXN0796dtm3botPpuHbtGpmZmVhZWfH6669TUVGhrMIkxO+5cuUKGzZsoGvXrjz33HMMHjwYvV7P0KFD2blzJ2PHjqWsrAwbGxtjhyqE+A9J8keIWsjS0pJ+/fpRXl5ORUUFI0aMAGSqlxBCCFFXlZaWUq9ePeB/zvceHh4cO3aMq1ev4u3tjY+PDxqNhtu3bwOPpowL8Uc0aNAAa2trvvnmG0xNTWnTpg1DhgzhwIEDvPLKK3z11VdYWVkZO0whxP+BnBGEqKXMzc158cUX0Wq1gCwnLYQQQtRVxcXFTJkyhQEDBtCjRw/lfO/l5YWLiwvJyckEBQXh5OREeno6MTExgNQeE7+uoKCAhw8f4u7uzg8//MDVq1eprKwkLi6OdevW8c0331BVVUW9evXw9/fnjTfekMSPEHWA3CkKUYsZEj8gF3hCCCFEXaXVaomIiGDbtm0kJycr73t7e9OzZ090Oh0rVqxg+fLlTJw4kRYtWhgxWvE0y8rKYuLEieh0Oo4fP86cOXOoqqpiz549LFu2jF69emFvb88XX3zB1KlTiYiIkP4k/jJ6fd399zSSkT9CCCGEEEI8xbRarTLad/369cCjgvM6nY4OHTpgYmLC7du3GTFiBA0aNFCWgBeiusuXLzN58mTi4+Np1KgR8+bNY+LEiXTr1o2hQ4cydepUNmzYwJIlSygqKuLevXt4enpKfxKijpCRP0IIIYQQQjzltFotL7zwAs8//zwff/wxSUlJmJiYcPz4ccaMGUO7du1o0KABIKOBxeOysrJ49dVXycjIwM/PD3i0Mqytra3ynXfeeYcbN25QUFCAnZ0dnp6egPQnIeoKGfkjhBBCCCFELWBIAAF8+umnnDlzhh07drBw4UI6depk5OjE0+r69etMmzaNsWPHotFoGDNmDAkJCXTr1o1p06bx2Wef4ezszIULFygvL5dkjxB1lCR/hBBCCCGEqCUMCaCKigoWLVrE3Llz6d27N/r/X2RCbtzFL+n1esaOHUvXrl0BKCwsZPz48axevZqRI0fSv39/+vTpw7Fjx3j99ddxdHQ0csRCiL+CRq9/WssRCSGEEEIIIX5NeXk5BQUFNGzYUBI/4g8z1O/55JNP2LJlCx999BFlZWUUFBRgbW1NaGio1PgRT8ym9SnGDuEvEzsq3NghPEZG/gghhBBCCFHLaLVaGjZsqLyWm3XxRxj6SUxMDBqNhiFDhrBq1Srat2//2HeEEHWLJH+EEEIIIYSoxeRmXfwnhg8fjk6no7y83NihCCGeAEn+CCGEEEIIIYQKxcbGAshUL2EUUoHmyZKl3oUQQgghhBBCxSTxI0TdJ8kfIYQQQgghhBBCiDpMkj9CCCGEEEIIIYQQdZgkf4QQQgghhBBCCCHqMEn+CCGEEEIIIYQQQtRhkvwRQgghhBBCCCGEqMMk+SOEEEIIIYQQQghRh0nyRwghhBBCCCGEEKIOMzN2AEIIIYQQQgghhFAXvV5v7BBURUb+CCGEEEIIIYQQQtRhkvwRQgghhBBCCCGEqMMk+SOEEEIIIYQQQghRh0nyRwghhBBCCCGEEMII9u3bR69evejRowdbt2597PPz588zYMAAevbsyYwZM6isrAQgJyeH6Oho/va3vzFu3DhKSkp+9+9I8kcIIYQQQgghhBDiCcvLy2PZsmVs27aN3bt3s2PHDi5dulTjO2+88QazZs3i4MGD6PV6du7cCcA777zD0KFDSUxMJCQkhNWrV//u35LkjxBCCCGEEEIIIcQTdvz4cdq1a4eDgwP16tWjZ8+eJCYmKp/fuHGDBw8e0LJlSwAGDBhAYmIiFRUVpKSk0LNnzxrv/x5Z6l0IIYQQQgghhBDiT1JUVERRUdFj79vZ2WFnZ6e8zs/Px8XFRXnt6urKmTNnfvNzFxcX8vLyuHPnDjY2NpiZmdV4//dI8kcIIYQQQgghhBBP1MjRbY0dwl9m5cqVrFq16rH34+PjmTBhgvJap9Oh0WiU13q9vsbr3/r8l98DHnv9S5L8EUIIIYQQQgghhPiTxMbG0r9//8ferz7qB8DNzY3U1FTl9a1bt3B1da3x+a1bt5TXt2/fxtXVFUdHR+7fv09VVRWmpqaPbfdrpOaPEEIIIYQQQgghxJ/Ezs6ORo0aPfbvl8mf9u3bc+LECQoLCykrK+Prr7+mY8eOyuceHh5YWFjw448/ArBnzx46duyIubk5rVu35sCBAwDs3r27xna/RqPX6/V/8u8UQgghhBBCCCGEEP/Gvn37WLt2LRUVFQwcOJAxY8YwZswY/v73v9O8eXMuXLjAzJkzKS4uJjg4mPfeew+tVsuNGzeYNm0aBQUFNGzYkKVLl2Jvb/+bf0eSP0IIIYQQQgghhBB1mEz7EkIIIYQQQgghhKjDJPkjhBBCCCGEEEIIUYdJ8kcIIYQQQgghhBCiDpPkjxBCCCGEEEIIIUQdJskfIYQQQgghhBBCiDpMkj9CCCGEEEIIIYQQdZgkf4QQQgghhBBCCCHqMEn+CCGEEEIIIYQQQtRh/w9izeVyw2fOpAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = np.zeros_like(df_p)\n",
    "mask[np.tril_indices_from(mask)] = True\n",
    "with sns.axes_style(\"white\"):\n",
    "    f, ax = plt.subplots(figsize=(20, 20))\n",
    "    ax = sns.heatmap(df_p.round(2), mask=mask,  annot=True, center=0, square=True, vmax=0.08, vmin=0, \n",
    "                     cmap=\"Purples_r\")\n",
    "    label_x = ax.get_xticklabels()\n",
    "    plt.setp(label_x, rotation=45, horizontalalignment='right')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "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>closeness_P</th>\n",
       "      <th>degree_P</th>\n",
       "      <th>betweenness_P</th>\n",
       "      <th>pagerank_P</th>\n",
       "      <th>Local_Vote</th>\n",
       "      <th>Non-local_Vote</th>\n",
       "      <th>Representing</th>\n",
       "      <th>Gathering</th>\n",
       "      <th>Local_count</th>\n",
       "      <th>Local_percentage</th>\n",
       "      <th>Tourist_count</th>\n",
       "      <th>Tourist_percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>closeness_P</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.678</td>\n",
       "      <td>0.710</td>\n",
       "      <td>0.109</td>\n",
       "      <td>0.050</td>\n",
       "      <td>0.949</td>\n",
       "      <td>0.761</td>\n",
       "      <td>0.421</td>\n",
       "      <td>0.425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>degree_P</th>\n",
       "      <td>0.001</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.928</td>\n",
       "      <td>0.934</td>\n",
       "      <td>0.814</td>\n",
       "      <td>0.864</td>\n",
       "      <td>0.978</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.738</td>\n",
       "      <td>0.329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>betweenness_P</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.355</td>\n",
       "      <td>0.804</td>\n",
       "      <td>0.282</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.331</td>\n",
       "      <td>0.990</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pagerank_P</th>\n",
       "      <td>0.002</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.800</td>\n",
       "      <td>0.994</td>\n",
       "      <td>0.939</td>\n",
       "      <td>0.806</td>\n",
       "      <td>0.882</td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.714</td>\n",
       "      <td>0.936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Local_Vote</th>\n",
       "      <td>0.678</td>\n",
       "      <td>0.928</td>\n",
       "      <td>0.355</td>\n",
       "      <td>0.800</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.422</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Non-local_Vote</th>\n",
       "      <td>0.710</td>\n",
       "      <td>0.934</td>\n",
       "      <td>0.804</td>\n",
       "      <td>0.994</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.106</td>\n",
       "      <td>0.256</td>\n",
       "      <td>0.166</td>\n",
       "      <td>0.529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Representing</th>\n",
       "      <td>0.109</td>\n",
       "      <td>0.814</td>\n",
       "      <td>0.282</td>\n",
       "      <td>0.939</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.372</td>\n",
       "      <td>0.868</td>\n",
       "      <td>0.067</td>\n",
       "      <td>0.911</td>\n",
       "      <td>0.548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gathering</th>\n",
       "      <td>0.050</td>\n",
       "      <td>0.864</td>\n",
       "      <td>0.024</td>\n",
       "      <td>0.806</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.015</td>\n",
       "      <td>0.372</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.612</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Local_count</th>\n",
       "      <td>0.949</td>\n",
       "      <td>0.978</td>\n",
       "      <td>0.331</td>\n",
       "      <td>0.882</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.106</td>\n",
       "      <td>0.868</td>\n",
       "      <td>0.005</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.792</td>\n",
       "      <td>0.011</td>\n",
       "      <td>0.927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Local_percentage</th>\n",
       "      <td>0.761</td>\n",
       "      <td>0.320</td>\n",
       "      <td>0.990</td>\n",
       "      <td>0.630</td>\n",
       "      <td>0.422</td>\n",
       "      <td>0.256</td>\n",
       "      <td>0.067</td>\n",
       "      <td>0.612</td>\n",
       "      <td>0.792</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.111</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tourist_count</th>\n",
       "      <td>0.421</td>\n",
       "      <td>0.738</td>\n",
       "      <td>0.036</td>\n",
       "      <td>0.714</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.166</td>\n",
       "      <td>0.911</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.011</td>\n",
       "      <td>0.111</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tourist_percentage</th>\n",
       "      <td>0.425</td>\n",
       "      <td>0.329</td>\n",
       "      <td>0.736</td>\n",
       "      <td>0.936</td>\n",
       "      <td>0.321</td>\n",
       "      <td>0.529</td>\n",
       "      <td>0.548</td>\n",
       "      <td>0.568</td>\n",
       "      <td>0.927</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    closeness_P  degree_P  betweenness_P  pagerank_P  \\\n",
       "closeness_P               0.000     0.001          0.000       0.002   \n",
       "degree_P                  0.001     0.000          0.000       0.000   \n",
       "betweenness_P             0.000     0.000          0.000       0.000   \n",
       "pagerank_P                0.002     0.000          0.000       0.000   \n",
       "Local_Vote                0.678     0.928          0.355       0.800   \n",
       "Non-local_Vote            0.710     0.934          0.804       0.994   \n",
       "Representing              0.109     0.814          0.282       0.939   \n",
       "Gathering                 0.050     0.864          0.024       0.806   \n",
       "Local_count               0.949     0.978          0.331       0.882   \n",
       "Local_percentage          0.761     0.320          0.990       0.630   \n",
       "Tourist_count             0.421     0.738          0.036       0.714   \n",
       "Tourist_percentage        0.425     0.329          0.736       0.936   \n",
       "\n",
       "                    Local_Vote  Non-local_Vote  Representing  Gathering  \\\n",
       "closeness_P              0.678           0.710         0.109      0.050   \n",
       "degree_P                 0.928           0.934         0.814      0.864   \n",
       "betweenness_P            0.355           0.804         0.282      0.024   \n",
       "pagerank_P               0.800           0.994         0.939      0.806   \n",
       "Local_Vote               0.000           0.000         0.000      0.000   \n",
       "Non-local_Vote           0.000           0.000         0.000      0.015   \n",
       "Representing             0.000           0.000         0.000      0.372   \n",
       "Gathering                0.000           0.015         0.372      0.000   \n",
       "Local_count              0.002           0.106         0.868      0.005   \n",
       "Local_percentage         0.422           0.256         0.067      0.612   \n",
       "Tourist_count            0.008           0.166         0.911      0.002   \n",
       "Tourist_percentage       0.321           0.529         0.548      0.568   \n",
       "\n",
       "                    Local_count  Local_percentage  Tourist_count  \\\n",
       "closeness_P               0.949             0.761          0.421   \n",
       "degree_P                  0.978             0.320          0.738   \n",
       "betweenness_P             0.331             0.990          0.036   \n",
       "pagerank_P                0.882             0.630          0.714   \n",
       "Local_Vote                0.002             0.422          0.008   \n",
       "Non-local_Vote            0.106             0.256          0.166   \n",
       "Representing              0.868             0.067          0.911   \n",
       "Gathering                 0.005             0.612          0.002   \n",
       "Local_count               0.000             0.792          0.011   \n",
       "Local_percentage          0.792             0.000          0.111   \n",
       "Tourist_count             0.011             0.111          0.000   \n",
       "Tourist_percentage        0.927             0.000          0.000   \n",
       "\n",
       "                    Tourist_percentage  \n",
       "closeness_P                      0.425  \n",
       "degree_P                         0.329  \n",
       "betweenness_P                    0.736  \n",
       "pagerank_P                       0.936  \n",
       "Local_Vote                       0.321  \n",
       "Non-local_Vote                   0.529  \n",
       "Representing                     0.548  \n",
       "Gathering                        0.568  \n",
       "Local_count                      0.927  \n",
       "Local_percentage                 0.000  \n",
       "Tourist_count                    0.000  \n",
       "Tourist_percentage               0.000  "
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_p.round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Node_ID</th>\n",
       "      <th>Multiple</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>643</td>\n",
       "      <td>643,642,641,646,647,690,692,691,726,725,727,644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>624</td>\n",
       "      <td>624,627,625,626,622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>623</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>630</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>368</td>\n",
       "      <td>367,368,364,366,365,359,392,385,390,428,432,43...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>439</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>623</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>736</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>241</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>293</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>763</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>561</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>451</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>279</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>561</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>284</td>\n",
       "      <td>267,280,281,284,291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>312</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>369</td>\n",
       "      <td>377,379,378,372,371,370,369,374,373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>371</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>373</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>504</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>233</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>705</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>268</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>277</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>489</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>693</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>367</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>450</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>493</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>302</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>318</td>\n",
       "      <td>317,318,329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>326</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>515</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>404</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>266</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>470</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>423</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>588</td>\n",
       "      <td>555,554,343,342,564,589,588,758,759,776,777,78...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>223</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>550</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>499</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>408</td>\n",
       "      <td>399,407,408,414,413,418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>346</td>\n",
       "      <td>372,455,456,452,451,450,488,489,490,493,491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>489</td>\n",
       "      <td>489,502,501,515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>345</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>346</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>337</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>274</td>\n",
       "      <td>276,274,324,568,567,566,573,587,588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>467</td>\n",
       "      <td>470,467,466</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Node_ID                                           Multiple\n",
       "0       643    643,642,641,646,647,690,692,691,726,725,727,644\n",
       "1       624                                624,627,625,626,622\n",
       "2       623                                                NaN\n",
       "3       630                                                NaN\n",
       "4       368  367,368,364,366,365,359,392,385,390,428,432,43...\n",
       "5       439                                                NaN\n",
       "6       623                                                NaN\n",
       "7       736                                                NaN\n",
       "8       241                                                NaN\n",
       "9       293                                                NaN\n",
       "10      763                                                NaN\n",
       "11      561                                                NaN\n",
       "12      451                                                NaN\n",
       "13      279                                                NaN\n",
       "14      561                                                NaN\n",
       "15      284                                267,280,281,284,291\n",
       "16      312                                                NaN\n",
       "17      369                377,379,378,372,371,370,369,374,373\n",
       "18      371                                                NaN\n",
       "19      373                                                NaN\n",
       "20      504                                                NaN\n",
       "21      233                                                NaN\n",
       "22      705                                                NaN\n",
       "23      268                                                NaN\n",
       "24      277                                                NaN\n",
       "25      489                                                NaN\n",
       "26      693                                                NaN\n",
       "27      367                                                NaN\n",
       "28      450                                                NaN\n",
       "29      493                                                NaN\n",
       "30      302                                                NaN\n",
       "31      318                                        317,318,329\n",
       "32      326                                                NaN\n",
       "33      515                                                NaN\n",
       "34      404                                                NaN\n",
       "35      266                                                NaN\n",
       "36      470                                                NaN\n",
       "37      423                                                NaN\n",
       "38      588  555,554,343,342,564,589,588,758,759,776,777,78...\n",
       "39      223                                                NaN\n",
       "40      550                                                NaN\n",
       "41      499                                                NaN\n",
       "42      408                            399,407,408,414,413,418\n",
       "43      346        372,455,456,452,451,450,488,489,490,493,491\n",
       "44      489                                    489,502,501,515\n",
       "45      345                                                NaN\n",
       "46      346                                                NaN\n",
       "47      337                                                NaN\n",
       "48      274                276,274,324,568,567,566,573,587,588\n",
       "49      467                                        470,467,466"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All_data[['Node_ID','Multiple']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes_nom = list(All_data['Node_ID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [],
   "source": [
    "multi_nodes = [line.split(',') for line in All_data['Multiple'] if not str(line)=='nan']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [],
   "source": [
    "for li in multi_nodes:\n",
    "    nodes_nom += [int(c) for c in li]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "metadata": {},
   "outputs": [],
   "source": [
    "nodes_nom_s = set(nodes_nom)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "123"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(nodes_nom_s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "metadata": {},
   "outputs": [],
   "source": [
    "lines_nom_s = set(list(All_data['Street Node'].dropna()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9"
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(lines_nom_s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_P['nominated'] = metrics_P.apply(lambda x: x.name in nodes_nom_s, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_L['nominated'] = metrics_L.apply(lambda x: x.name in lines_nom_s, axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=array([ 6.36575021, 12.05837107,  5.9433677 ,  9.29639184]), pvalue=array([4.90078375e-10, 4.04550230e-29, 5.69559269e-09, 6.86706315e-19]))"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import ttest_ind\n",
    "\n",
    "m1 = metrics_P[metrics_P['nominated']==True]\n",
    "m2 = metrics_P[metrics_P['nominated']==False]\n",
    "\n",
    "ttest_ind(m1[['closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P']],\n",
    "          m2[['closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "123"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(m1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "318"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(m2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cohen_d(x1,x2):\n",
    "    n1=len(x1)\n",
    "    n2=len(x2)\n",
    "    t=ttest_ind(x1,x2, nan_policy='omit')[0]\n",
    "    return t* np.sqrt(1.0/n1+1.0/n2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.6759316343831172\n",
      "1.2803886725495928\n",
      "0.6310819787862848\n",
      "0.9871146550604512\n"
     ]
    }
   ],
   "source": [
    "for item in ['closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P']:\n",
    "    print(cohen_d(m1[item],m2[item]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [],
   "source": [
    "m1_B = m1.merge(All_data[['Node_ID','Behaviour']],how='left',left_index=True,right_on='Node_ID').set_index('Node_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "m1_B = m1_B.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=array([-0.23140006,  0.88252485,  1.19643399,  2.56207595]), pvalue=array([0.81738238, 0.37918706, 0.23379164, 0.01159184]))"
      ]
     },
     "execution_count": 189,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_B_1 = m1_B[m1_B['Behaviour']==1]\n",
    "m_B_2 = m1_B[m1_B['Behaviour']==0]\n",
    "\n",
    "ttest_ind(m_B_1[['closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P']],\n",
    "          m_B_2[['closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.051641070268500025\n",
      "0.19695123826184496\n",
      "0.26700568882568304\n",
      "0.5717731660901166\n"
     ]
    }
   ],
   "source": [
    "for item in ['closeness_P', 'degree_P', 'betweenness_P', 'pagerank_P']:\n",
    "    print(cohen_d(m_B_1[item],m_B_2[item]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=array([3.14559062, 7.33921697, 7.34108698, 7.95830935]), pvalue=array([1.89092782e-03, 4.30339249e-12, 4.25554364e-12, 9.75937464e-14]))"
      ]
     },
     "execution_count": 190,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m3 = metrics_L[metrics_L['nominated']==True]\n",
    "m4 = metrics_L[metrics_L['nominated']==False]\n",
    "\n",
    "ttest_ind(m3[['closeness_L', 'degree_L', 'betweenness_L', 'pagerank_L']],\n",
    "          m4[['closeness_L', 'degree_L', 'betweenness_L', 'pagerank_L']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0708682702658336\n",
      "2.498524291968219\n",
      "2.4991609059531767\n",
      "2.70928483180123\n"
     ]
    }
   ],
   "source": [
    "for item in ['closeness_L', 'degree_L', 'betweenness_L', 'pagerank_L']:\n",
    "    print(cohen_d(m3[item],m4[item]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_P1 = metrics_P.merge(All_data[['Node_ID','Behaviour']],how='left',left_index=True,right_on='Node_ID').set_index('Node_ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics_P1['Behaviour'] = metrics_P1['Behaviour'].fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fad39b6f588>"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2304x504 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"white\")\n",
    "\n",
    "fig,axes = plt.subplots(1,4,figsize = (32,7),sharex=True, sharey=True)\n",
    "\n",
    "plt.subplot(141)\n",
    "plt.scatter(metrics_P1[metrics_P1['nominated']==True]['degree_P'],\n",
    "            metrics_P1[metrics_P1['nominated']==True]['pagerank_P'],c='orange',alpha=0.9, label = 'nominated')\n",
    "plt.scatter(metrics_P1[metrics_P1['Behaviour']==1]['degree_P'],\n",
    "            metrics_P1[metrics_P1['Behaviour']==1]['pagerank_P'],c='red',alpha=0.9, label = 'monitored')\n",
    "plt.scatter(metrics_P1[metrics_P1['nominated']==False]['degree_P'],\n",
    "            metrics_P1[metrics_P1['nominated']==False]['pagerank_P'],c='steelblue',alpha=0.7, label = 'not mentioned')\n",
    "\n",
    "plt.xlabel('Degree Centrality P',size=25)\n",
    "plt.ylabel('Page Rank P',size = 25)\n",
    "\n",
    "plt.legend(frameon=False, fontsize = 20)\n",
    "\n",
    "plt.subplot(142)\n",
    "plt.scatter(metrics_P[metrics_P['nominated']==True]['closeness_P'],\n",
    "            metrics_P[metrics_P['nominated']==True]['betweenness_P'],c='orange',alpha=0.9, label = 'nominated')\n",
    "plt.scatter(metrics_P1[metrics_P1['Behaviour']==1]['closeness_P'],\n",
    "            metrics_P1[metrics_P1['Behaviour']==1]['betweenness_P'],c='red',alpha=0.9, label = 'monitored')\n",
    "plt.scatter(metrics_P[metrics_P['nominated']==False]['closeness_P'],\n",
    "            metrics_P[metrics_P['nominated']==False]['betweenness_P'],c='steelblue',alpha=0.7, label = 'not mentioned')\n",
    "\n",
    "\n",
    "plt.xlabel('Closeness Centrality P',size=25)\n",
    "plt.ylabel('Betweenness Centrality P',size = 25)\n",
    "plt.legend(frameon=False, fontsize = 20)\n",
    "\n",
    "plt.subplot(143)\n",
    "plt.scatter(metrics_L[metrics_L['nominated']==True]['degree_L'],\n",
    "            metrics_L[metrics_L['nominated']==True]['pagerank_L'],c='orange',alpha=0.9, label = 'nominated')\n",
    "plt.scatter(metrics_L[metrics_L['nominated']==False]['degree_L'],\n",
    "            metrics_L[metrics_L['nominated']==False]['pagerank_L'],c='steelblue',alpha=0.7, label = 'not mentioned')\n",
    "\n",
    "\n",
    "plt.xlabel('Degree Centrality L',size=25)\n",
    "plt.ylabel('Page Rank L',size = 25)\n",
    "plt.legend(frameon=False, fontsize = 20)\n",
    "\n",
    "plt.subplot(144)\n",
    "plt.scatter(metrics_L[metrics_L['nominated']==True]['closeness_L'],\n",
    "            metrics_L[metrics_L['nominated']==True]['betweenness_L'],c='orange',alpha=0.9, label = 'nominated')\n",
    "plt.scatter(metrics_L[metrics_L['nominated']==False]['closeness_L'],\n",
    "            metrics_L[metrics_L['nominated']==False]['betweenness_L'],c='steelblue',alpha=0.7, label = 'not mentioned')\n",
    "\n",
    "\n",
    "plt.xlabel('Closeness Centrality L',size=25)\n",
    "plt.ylabel('Betweenness Centrality L',size = 25)\n",
    "plt.legend(frameon=False, fontsize = 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=array([2.50179221, 1.97016458, 1.00194882, 2.01809185]), pvalue=array([0.01597644, 0.05485657, 0.32161   , 0.04943559]))"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_1 = All_data[All_data['Behaviour']==1]\n",
    "all_2 = All_data[All_data['Behaviour'].fillna(0)==0]\n",
    "\n",
    "ttest_ind(all_1[['Local_Vote','Non-local_Vote', 'Representing', 'Gathering']],\n",
    "          all_2[['Local_Vote','Non-local_Vote', 'Representing', 'Gathering']].dropna())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7076136954408359\n",
      "0.5572466935066906\n",
      "0.2833939211566731\n",
      "0.5708025717095432\n"
     ]
    }
   ],
   "source": [
    "for item in ['Local_Vote','Non-local_Vote', 'Representing', 'Gathering']:\n",
    "    print(cohen_d(all_1[item],all_2[item]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "All_data['Node_B'] = All_data.apply(lambda x: x['Street Node'] if not np.isnan(x['Street Node']) else x['Node_ID'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "All_data_B = All_data.merge(metrics, how='left', left_on = 'Node_B', right_index = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['ID', '地段', 'Spot_ID', 'Node_ID', 'Street Node', 'Multiple', 'Type',\n",
       "       'Behaviour', 'R100_Intensity', 'R100整合度', 'R560_Intensity', 'logR56整合度',\n",
       "       'R100_Choice', 'logR100选择度', 'R560_Choice', 'logR560选择度', 'Local_Vote',\n",
       "       'Non-local_Vote', '提名差', 'Representing', 'Gathering', '预测游客数量',\n",
       "       '预测本地人数量', 'Tourist_count', '游客方差', '游客时间', 'Tourist_percentage',\n",
       "       'Local_count', '本地人方差', '本地人时间', 'Local_percentage', 'closeness_c_x',\n",
       "       'degree_c_x', 'betweenness_c_x', 'pagerank_x', 'closeness_Z',\n",
       "       'degree_Z', 'betweenness_Z', 'pagerank_Z', 'closeness_P', 'degree_P',\n",
       "       'betweenness_P', 'pagerank_P', 'Node_B', 'closeness_c_y', 'degree_c_y',\n",
       "       'betweenness_c_y', 'pagerank_y'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "All_data_B.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 455,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_corr_B = All_data_B[[\n",
    "       'degree_c_y','closeness_c_y', 'betweenness_c_y', 'pagerank_y',\n",
    "                      'Local_Vote','Non-local_Vote', 'Representing', 'Gathering', \n",
    "        'Local_count', 'Local_percentage', 'Tourist_count', 'Tourist_percentage']].rename(columns = \n",
    "                    {'closeness_c_y':'Closeness_B', 'degree_c_y':'Degree_B', \n",
    "                     'betweenness_c_y': 'Betweenness_B', 'pagerank_y':'Page Rank_B'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_corr_B = All_data_B[[\n",
    "       'degree_P','closeness_P', 'betweenness_P', 'pagerank_P', 'pagerank_y',\n",
    "                      'Local_Vote','Non-local_Vote', 'Representing', 'Gathering', \n",
    "        'Local_count', 'Local_percentage', 'Tourist_count', 'Tourist_percentage']].rename(columns = \n",
    "                    {'closeness_c_y':'Closeness_B', 'degree_c_y':'Degree_B', \n",
    "                     'betweenness_c_y': 'Betweenness_B', 'pagerank_y':'Page Rank_B'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_corr_B = pd.DataFrame() # Correlation matrix\n",
    "df_p_B = pd.DataFrame()  # Matrix of p-values\n",
    "for x in data_corr_B.columns:\n",
    "    for y in data_corr_B.columns:\n",
    "        if x==y:\n",
    "            df_corr_B.loc[x,y] = 1\n",
    "            df_p_B.loc[x,y] = 0\n",
    "        else:\n",
    "            tmp_data = data_corr_B[[x,y]].dropna()\n",
    "            corr = stats.pearsonr(tmp_data[x], tmp_data[y])\n",
    "            df_corr_B.loc[x,y] = corr[0]\n",
    "            df_p_B.loc[x,y] = corr[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hS+ADOoYAAAAACkowBAAAAFBQgiEAAACAghIMAQAAABSU4dMAAABAVdXUGD7dWOgYAgAAACgowRAAAABAQQmGAAAAAArKjCEAAACgqkplfSqNhTsBAAAAUFCCIQAAAICCEgwBAAAAFJQZQwAAAEBV1ZRLDV0CH9AxBAAAAFBQgiEAAACAghIMAQAAABSUGUN8qPtfeiuX3vd0FtbW5csd2+akb22V1s2bLnPvvf8zMafc9kjuO27vJMn8RYtz9t1/zz/efieVJJusvmp+8s0eadHUPzkAAICiK5kx1GjoGGKZZsybn+F3PJqz9twmI4/4VtZo1zqX3PvUMve+Pn1OLvrrU6lU/rn2u4eeS21dXa47bNdcd+guWbC4Nr9/6LkqVQ8AAAB8HCtcMDRw4MA88sgjDV3GZ3LTTTdlq622Sr9+/dKvX7/ssssuOfnkk7N48eKGLq3ew69Mysart89a7VdOkuzdfYPc9ezrqfxr+pP3O4OG3vpwjtlx8yXWu6/ZMYdu0zU1pVLKNTXZsHO7TJo9r2r1AwAAAB9thQuGvih69+6d0aNHZ/To0bnjjjvy/PPP58Ybb2zosupNnv1eOq/cqv64U5uWmbtgUeYuXDK8+sVd47PX5uvnyx3bLbHec93VsvYHodLbs+bmuvH/kx2/subyLxwAAAD42Br1wJdKpZJzzz03Y8eOTblczn777bfE67/85S9zyy23pFwuZ5tttsmQIUPy3nvv5bjjjsu0adOSJEcddVR23HHHvPbaaxk2bFhmzpyZFi1a5OSTT87GG2+c448/Pq1bt84//vGPTJ48OUcddVT23nvvzJ07N8OHD8+LL76Y2traHH744enTp0+ef/75DB06NIsXL07z5s1zxhlnZI011sjPfvazvPjii0mSAw44IPvuu+/Hvs5yuZwtttii/vzGoFKppLSMRz7L/7L4p7+/mHJNKd/ebL28NXPuMt/nuUnTM+SmB7Jvjy9nuw2+tLzKBQAAAD6FRh0M3XXXXfn73/+eW2+9NYsWLcoBBxyQBQsWJEnuu+++/PWvf83IkSPTtGnTHH300bn++uvTqlWrrLHGGrnyyivz3HPP5ZZbbsmOO+6Yn/70pxk6dGg23njjvPTSSznqqKMyZsyYJMmkSZNy7bXX5n/+539y0EEHZe+9987ll1+erl275qyzzsq7776b/v37Z7PNNstVV12VQw45JLvttltuvvnmPPnkk5kyZUpmzZqVUaNGZfLkyTnvvPM+UTA0Y8aM3H///TniiCOWy+f4aXRu0yoT3nqn/njqnPfSpkWztGz2z38ytz3zauYvWpwDfjsmi2vrsmBxbQ747Zhc9J1e6bhyy9z97Os56+7HM2TnHtm169oNcRkAAAA0QqWyB5gai0YdDD322GPZbbfd0qxZszRr1iyjR4/OwIEDkyQPP/xwdt9997Rs2TJJsvfee2fUqFH58Y9/nPPPPz+TJ0/O9ttvn6OOOipz587NhAkTcsIJJ9S/97x58zJjxowkyTbbbJNSqZT/+q//ysyZM5MkDz74YObPn5+RI0fW73/xxRfzjW98I8OHD8+4cePSu3fv7LDDDpk9e3ZeeeWVHHbYYenVq1d+8pOffOS1/fWvf02/fv1SqVRSqVSy8847p0+fPp/r5/dZ9Fx3tVz01yfz+vQ5Wav9yhn5xP+m15eX7Pi5atDO9T+/NXNu+v/mrlx76C5Jkr+9+GbOHfv3XLzfN7Lx6u2rWjsAAADw8TTqYKhJkyYp/cujSxMnTsy8ee8PMK6rq1tq/+LFi7POOuvkzjvvzLhx43LPPffkt7/9bf70pz/VB0v/Z9KkSWnX7v25OM2bN0+SJX5XXV1dzjnnnHTt2jVJMm3atLRt2zZNmzZN9+7dc8899+T3v/997r333px22mm5/fbb88ADD+S+++7Lnnvumdtvvz1t2rT50Gvr3bt3zjzzzM/w6Sxf7VdqkaG7b5Xjb34gi+rq0qVd6wzrs3WefXt6TrvzsfoA6MNcdM/731J22p2P1a9t1qVDfvrNry7v0gEAAICPqVEHQ1tuuWX+8Ic/pH///lm8eHG++93v5t13302S9OzZM5dffnn222+/NGnSJCNHjkzPnj3zxz/+MW+88UZOOOGE9OrVKzvssEMqlUrWWWedjB49Ov369csDDzyQoUOHZuzYsR/6u3v27Jnrrrsup512WqZMmZI99tgj119/fc4///z06dMn/fv3z/rrr58zzjgjf/nLX3LLLbfkwgsvzHbbbZeHHnoob7/99n8MhlYE26z/pWyz/pJdQm1bNl9mKPSldivlbz/au/545BHfWu71AQAAAJ9Now6Gdt5550yYMCF77bVX6urqctBBB+XOO+9Mkuywww557rnnsvfee2fx4sXZdtttc+CBB2b+/Pk57rjj0rdv35TL5QwZMiRt2rTJOeeck2HDhuXXv/51mjZtmgsuuGCJDqF/N3jw4AwbNix9+vRJbW1thgwZkrXWWivf//73c+KJJ+bSSy9N06ZNM2zYsGy00Ua5++67s/vuu6d58+b59re/nQ033LBaHxMAAACsUGrKH/73ONVVqlQqlYYugk9n9u+GNnQJjU6bQ4Y3dAkAAAB8hGf2/+I+ZbLpdXc0dAmfSKPuGFqR/f73v8/NN9+81HqnTp3yq1/9qgEqAgAAAFiSYGg5Ofjgg3PwwQc3dBkAAAAAH0owBAAAAFRVqcaMocaipqELAAAAAKBhCIYAAAAACkowBAAAAFBQZgwBAAAAVVVT1qfSWLgTAAAAAAUlGAIAAAAoKMEQAAAAQEEJhgAAAAAKyvBpAAAAoKpK5VJDl8AHdAwBAAAAFJRgCAAAAKCgBEMAAAAABWXGEAAAAFBVpbI+lcbCnQAAAAAoKMEQAAAAQEEJhgAAAAAKyowhAAAAoKpKNfpUGgt3AgAAAKCgBEMAAAAABSUYAgAAACgoM4YAAACAqqop61NpLNwJAAAAgIISDAEAAAAUlGAIAAAAoKAEQwAAAAAFZfj0CmzupHcauoRG5eXbn05+s11Dl9GobHP/uIYuAQAAYCklw6cbDXcCAAAAoKAEQwAAAAAFJRgCAAAAKCgzhgAAAICqMmOo8XAnAAAAAApKMAQAAABQUIIhAAAAgIIyYwgAAACoqlKNPpXGwp0AAAAAKCjBEAAAAEBBCYYAAAAACsqMIQAAAKCqSuVyQ5fAB3QMAQAAABSUYAgAAACgoARDAAAAAAUlGAIAAAAoKMOnAQAAgKoqlfWpNBbuBAAAAEBBCYYAAAAACkowBAAAAFBQZgwBAAAAVVVTo0+lsXAnAAAAAApKMAQAAABQUIIhAAAAgIIyYwgAAACoqlJZn0pj4U4AAAAAFJRgCAAAAKCgBEMAAAAABWXGEAAAAFBVZgw1HoIhPlTz9btm5e37pVRukkVT3sysO65JZeH8Ze/9cre06zsok8//UZKk1KJV2u7SP007d0ll0YLMe/rhzHv8vmqWv9yt8rWvZe3vfS81zZpm7v/+b14648zUzptX/3rHXXfJl/bbr/64yUorpVmnThm/515ZNGNGQ5QMAAAASxAMsUw1LVun7e4D887V56V2xtSsvH2/rLxDv8we8/+W2ltepWPa7LhXUirVr7XZae9UFi3I1F+dmpRqsso+30vtrHey4KUJ1byM5aZJu3bZ4Gcn5Jkjf5D5Eydm7SO/n7WP/H5ePu/8+j1T7xqTqXeNSZKUyuVscuklmXjNNUIhAAAAGo3l2rv1yCOPZODAgR97/4gRIzJ+/PjlWFHjMHHixGyyySbp169f9thjj+y+++455JBDMmnSpIYurV6z9TbKordfS+2MqUmSeU+MS8uNt1x6Y5OmafftgzN77Mgllpuutlbem/BoUqkkdbVZ8NKEtNiwezVKr4pVttwy7z73fOZPnJgkmXTzqHTceecP3b/GgQOyaMaMTB59S7VKBAAAgI/UqB7qe+yxx1JbW9vQZVRFp06dMnr06IwaNSq33357Ntxww5x99tkNXVa98srtUjv7n50ttbNnpqZFy5SatVhiX9vdDsi8J+7P4qlvLrG+6K1X03KTrZKampSaNk+LDTdPuXWbqtReDc06d8rCKZPrjxdMnZomrVun3KrVUnubtG2bNfr3zysXX1zNEgEAAOAjLfdHyWbMmJHDDjssU6ZMSbdu3XLKKafk4YcfzogRI7J48eJ06dIlp556au67775MmDAhJ510Uvr165eXXnopF154YV555ZXsuuuueeCBB9KhQ4ccdthh+e///u+0bds2w4YNy8yZM9OiRYucfPLJ2XjjjTNt2rQMHTo0kyZNSqlUyo9+9KN8/etfz8UXX5zJkyfntddey5tvvpnvfOc7OfLII3PTTTdl3LhxmTVrVt54441ss802GTZsWJLkyiuvzJ133pna2tpsu+22GTJkSObOnZvjjjsu06ZNS5IcddRR2XHHHfO73/0uN998c2pqatKtW7cMHz78E31OW2+9dc4///yP3lgtpQ/JDCt19T+26rFdUleb955+KOW27ZfYNvsvN6VN7z3T4dATUvfu7Cx49fk0W2O95VlxVZVKNalUll6v1NUttbbat7+dd8bdnwVvvV2FygAAABq/Uk2j6lNpMLfeemsuv/zyLF68OIMGDcqAAQOWeP2SSy7JyJEj06bN+40W++67bwYMGJC33norQ4YMyTvvvJN111035557blZaaaVPVcNyD4YmTpyYSy65JGuvvXaOPfbYXHnllfnzn/+cP/zhD2nbtm2uv/76nHvuuTn99NMzcuTIDB48OF27ds1uu+2WSqWShx9+OKuuumoeffTR9O7dO6+88ko23XTT7L///hk6dGg23njjvPTSSznqqKMyZsyYnH766dl7772z4447ZsqUKTnggAMyatSoJMkLL7yQa665JnPmzMlOO+1U/4E/8cQTue2221Iul7Prrrtm//33z+TJkzNhwoTceOONKZVKGTJkSG655ZbU1dVljTXWyJVXXpnnnnsut9xyS7bffvtcccUVGTduXMrlck488cRMnjw5nTt3/lif0aJFizJmzJhsvvnmy+0+fFJ1s6en2ZfWqT8ur9wude/NTWXRwvq1lpv2TKlps3Q49ISkXE6pSdN0OPSETL/hsqSmJrPvGZXK/PeHMa/0tV2y+IPH0r4IFkyenNYbb1R/3LxDhyyaPTt185cezt1hx955+cKLqlkeAAAAjdzkyZNzwQUX5KabbkqzZs3Sv3//bL311tlggw3q90yYMCHnn39+undfcjTLz3/+8xxwwAHZfffdc+mll+ayyy7LkCFDPlUdyz0Y2mKLLbLOOuskSfr27Zvjjz8+pVIpBx10UJKkrq4ubdu2XeKc1q1bZ911180LL7yQhx9+OIMGDcpjjz2WlVZaKT179sy8efMyYcKEnHDCCfXnzJs3LzNmzMiDDz6Yl19+OSNGjEiSLF68OG+88UaS97tymjVrllVXXTXt2rXLnDlzkiTdu3dP69atkyRrrrlmZs2alYceeihPP/109tprryTJ/Pnz86UvfSl77713zj///EyePDnbb799jjrqqJTL5XTv3j377LNPdtxxxxxyyCEfGQpNmTIl/fr1S5IsXLgw3bp1y49+9KPP8lF/rha88lxW3nGvlFfpmNoZU9Oq+7aZ/+LTS+x556pz6n8ut22fDt89KdN+e0aSZOVvfDul5i0y++4bUtNq5bTa7OuZOfo3Vb2G5Wnmo49mncFHpUWXLpk/cWJW22OPTB93/1L7yiu3Tos11sicZ55pgCoBAACottmzZ2f27NlLrbdp06a+8ydJHnzwwfTs2TPt2rVLkuyyyy656667Mnjw4Po9EyZMyBVXXJE333wzW265ZX7605+mpqYmjz32WC699NIkyV577ZUDDzyw8QZDTZr881dUPnj2pkePHvnlL3+ZJFmwYEHmzp271Hnbb799Hnjggbz88ssZNmxYDjrooNTU1GSHHXZIXV1dmjVrltGjR9fvnzRpUtq1a5e6urpcddVV9R/slClTsuqqq2bs2LFp3rx5/f5SqVRfz7LWa2trM2jQoBxyyCFJ3r+x5XI5K620Uu68886MGzcu99xzT37729/mjjvuyGWXXTBD8foAACAASURBVJYnn3wyf/vb3/Ld73435557brbaaqsP/Vz+b8ZQY1U3793Muv2PWWXP76ZUbpLFM6dm5q1/SNPV1krbbw2oD4A+zLsPjUm7voPS4bsnJinl3XG3ZdHbr1en+CpYNHNmXvrFGfnKaaem1KRJ5r/5Vl487bS03nDDrH/8T/PUIYcmSVqu0SUL33knlYLMzgIAACi6q666KpdccslS64MHD87RRx9dfzxlypR07Nix/rhTp055+ul/NmTMnTs3G220UYYMGZK11147xx9/fC677LIMGDAgrVu3rs9bOnbsmMmT/zkD95Na7sHQ448/nrfeeiurrbZaRo0alUGDBuWPf/xjXnnllay77rq57LLLMnny5Jx55pkpl8v1w6e/8Y1v5Pvf/3422WSTrLLKKmnatGnuueeeHHfccVlppZWyzjrrZPTo0enXr18eeOCBDB06NGPHjk3Pnj1z7bXX5gc/+EFeeumlDBgwIH/5y18+cd09e/bMiBEjsu+++6Z58+Y56qijsueee2bevHl54403csIJJ6RXr17ZYYcdMnPmzAwYMCA33nhjunfvnkmTJuWFF174j8HQimDB//4jC/73H0usLZr0+jJDodpZ0zP5vOPqjysLF2TGyCuXe40NacbDD2fGww8vsfbuCy/Uh0JJ8u7zz+fv/fevdmkAAACNWqn8xZ0xNGjQoOy5555Lrf9rt1Dy/hNUpVKp/rhSqSxxvNJKK+VXv/pV/fGhhx6an/3sZznggAOW2JdkqeNPYrkHQxtssEF+9rOfZerUqenZs2eOPPLIbLzxxjnmmGNSV1eXzp0755xz3n8kabvttsspp5ySs846Kz169EilUqkPV7baaqu8+OKL9cOUzjnnnAwbNiy//vWv07Rp01xwwQUplUo56aSTMnTo0PTt2zdJcvbZZ9c/JvZJ9O7dO88//3z23Xff1NbWZrvttsuee+5ZP3y6b9++KZfLGTJkSNq3b5/99tsv++yzT1q2bJl11103e++99+f0CQIAAAArin9/ZOzDrLbaahk/fnz98dSpU9OpU6f647feeisPPvhg9tlnnyTvB0dNmjRJ+/btM2fOnNTW1qZcLi913idVqlSW9d1KrAjePuOohi6hUXn59qc/elPBbHP/uIYuAQAAYClvnXZkQ5ew3HzppMs/1r7Jkydn//33z4033piWLVumf//+OfXUU9OtW7ckyfTp07PbbrvlxhtvTJcuXXLiiSdm7bXXzve+970cccQR6du3b/r27ZvLL788U6ZMySmnnPKp6l3uHUNFNX78+Jx66qnLfO3KK6/82N9YBgAAAHzxdO7cOccee2wOOuigLFq0KPvss0+6deuWww8/PD/84Q+z6aabZvjw4TnyyCOzaNGi9OjRo34O8imnnJLjjz8+l19+eVZfffWcf/75n7oOHUMrMB1DS9IxtDQdQwAAQGP0Rf57dvUTLm3oEj6RL+60JwAAAAD+I8EQAAAAQEEJhgAAAAAKyvBpAAAAoKpqyvpUGgt3AgAAAKCgBEMAAAAABSUYAgAAACgowRAAAABAQRk+DQAAAFRVqUafSmPhTgAAAAAUlGAIAAAAoKAEQwAAAAAFZcYQAAAAUFWlsj6VxsKdAAAAACgowRAAAABAQQmGAAAAAArKjCEAAACgqswYajzcCQAAAICCEgwBAAAAFJRgCAAAAKCgzBgCAAAAqqpUo0+lsXAnAAAAAApKMAQAAABQUIIhAAAAgIISDAEAAAAUlOHTK7Bbz/5LQ5fQqOx/Uf+GLqFRmTfpnUw+++iGLqPR6fyTixu6BAAAKLyacrmhS+ADOoYAAAAACkowBAAAAFBQgiEAAACAgjJjCAAAAKiqUlmfSmPhTgAAAAAUlGAIAAAAoKAEQwAAAAAFZcYQAAAAUFVmDDUe7gQAAABAQQmGAAAAAApKMAQAAABQUGYMAQAAAFVVqtGn0li4EwAAAAAFJRgCAAAAKCjBEAAAAEBBCYYAAAAACsrwaQAAAKCqSmV9Ko2FOwEAAABQUIIhAAAAgIISDAEAAAAUlBlDAAAAQFWZMdR4uBMAAAAABSUYAgAAACgowRAAAABAQZkxBAAAAFRVqUafSmPhTgAAAAAUlGAIAAAAoKAEQwAAAAAFZcYQAAAAUFWlmnJDl8AHdAwBAAAAFJSOIT7Umt/8RrYaelzKzZpl+j9eyH0/PDGL5sxdYs86u++Ur55wdCp1dVkwY1b+9t8nZ86rbyRJNj5s/3xl4D4pt2iRaU/9I/cdfWLqFi5qiEv5XNz/4pu55N6nsnBxXb7cqV1O7rN1Wjdvusy9974wMUNveSh/G/KdJdYnzZ6bQ37351x3+G5p16p5Ncperpqt1zWte/VNqUmTLJ7yVmbfdW0qC+cvc2/zDbqlTZ+BmXrhkPcXSqWsvNN30mzNDZIkC15+Nu/eO6papQMAABAdQ5+bgQMH5pFHHvnY+zfccMP069cve+yxR/r27Zv+/fvnhRdeWI4VfjItVl0l21/yi/z5oB/mhq12y+zX3shWp/xoiT3lFs2zwxVn588Dj85NvfbM63fdk23OOjFJsk6fndP18ANz+x6H5k9f65MmLVpk0x8c3ABX8vmYMXd+fn7bIzl77+1y05F9ssYqrXPJX59c5t7Xp8/JhX95IpXKkuu3Pf1KjvjDXzL13feqUPHyV2rZOm13G5BZo3+Td359WmpnTUvrb3x7mXvLq3RM6x32SFKqX2vRdas0ad857/zujLzz+zPTbM0N0nzDzatUPQAAAIlgqEGNHj06o0aNyq233prdd989Q4cObeiS6nXpvU2mPvFMZr/8WpLk2d9cny9/p+8Se0rlckqlUpq1WTlJ0mSlVqmdvzBJ8l/9++XpS3+XBTNnJZVKxh13Sl78f6OrexGfo4dfmZSNV181a7V//1r36bFB7vzHa6n8W/ozf9HinDz6oRy7U/cl1qfOmZf7/mdiLt5/+2qVvNw1X/crWTTp9dTOmJokmffE/Wmx8RZLb2zSNG13Pyjv3nPTkuulUkpNmyXlJimVmyTlJqksXlyFygEAAPg/K8yjZI888kguu+yyNGnSJBMnTky3bt1y+umn59JLL81DDz2UWbNmpVOnTrngggvSoUOH3HHHHRkxYkRatWqVjTbaKLW1tTnzzDPz9NNP54wzzsj8+fOzyiqr5Oc//3nWXHPNDBw4MG3bts2LL76YCy+8MI8//nhGjx6d9957L02bNs15552X9dZbL7179863v/3t3H///Xnvvfdy1llnZZNNNqmv85133smgQYNyzDHHZKeddvrY17f11lvn/PPPXx4f3aey0hqr5903J9Ufz31rUpq1WTlNV16p/nGyxXPnZdxxw9JvzHWZP31mSuWa3LLrAUmStuuvk5YdV81uf/pVWq3eKZMeGp9HTjm3Qa7l8zB59rx0btOq/rhTm1aZu2BR5i5cvMTjZKff8Vj26r5+vtyp3RLnd1y5Vc7ZZ7uq1VsNNSuvkto5M+qP6+bMTE3zlik1a7HE42RtdumfeU89kEVT3lri/PkTHkmLDbun4w9OS2pqsvCV57PwfydUrX4AAKABGT7daKxQHUNPPPFETjzxxNx1111ZsGBBrrrqqrz88su5/vrrM2bMmKy++uq55ZZbMn369PziF7/IVVddlRtvvDGzZs1KkixcuDAnnXRSzjvvvNx888055JBDcvLJJ9e//4YbbpgxY8ZkzTXXzNixY3P11Vfntttuy/bbb59rrrmmfl+7du1y4403pn///rniiivq1+fMmZMjjjgigwcP/kShUKVSye23357u3bt/9OYqKdXUZKlnoZJUauvqf15l4/9Kj5/8IDf03D3XbNwrT5x3RXb+w4gkSU3TJumy/dcz9tBjcvMO+6T5Ku2y5UnHVK3+z1tdpZJSaen18r8s/mn8i2lSU0q/zdevYmUNqFRa9r+Ryj//jbTcfLukri7zn3l4qX0rbbNb6t57N1Mv+VmmXXZyalq2Sqstey/XkgEAAFjSCtMxlCRbbrll1ltvvSRJv379csMNN+Tkk0/On/70p7zyyit58skns9Zaa2X8+PHp3r17OnfunCTZY489Mnbs2Lz66qt54403cuSRR9a/57vvvlv/c7du3ZIkrVu3znnnnZfbb789r776asaNG5eNNtqoft92273f+fHlL385d999d/36Kaeckg4dOuSb3/zmx7qefv36JXk/sFp//fUzfPjwT/OxLBfvTnwrnb7arf54pS91zvwZM7N43j/n46zZe9tMfuSJ+mHTz/76mnztF8eneft2mTtpal659c/13UUv3nBLvjrkB9W9iM/Ram1aZcKb79QfT53zXtq0aJaWzf75v9CtT7+c+Ytrc8Cv7syiuros+ODni/p/Ix1XbrWst12h1c2enqarr11/XLNy29S9NzdZtLB+reWmW6fUpGnaD/rp+48efvDzzJGXp8WXN8vsv9yY1NWmsrA27014NC023DzzHvtrQ1wOAABAIa1QwVC5/M9Ws0qlklKplMMOOywHH3xwdtlll9TU1KRSqaSmpiZ1dXVLnV9XV5cuXbpk9Oj3Z93U1tZm2rRp9a+3aNEiSfL2229n4MCBOfDAA9OrV6906NAhzz33XP2+5s3f/zap0r+1kBx++OG57777ct1112XAgAEfeT3/V0djNPGvD6TnqT9Nm/XWzuyXX8tGh/TPa3cs+Qf7tKf+ka6HD0jLjqvmvanvZJ3dd8qc1yZmwfSZeWX0mKy35655/uo/pXb+gqzzrR0z9YkV9zGhnuutngv/8kRenz4na7VfOSP//mK+8V9rLLHnD4fuUv/zWzPfzX5X3plrD9+t2qVWzYJXn0/rHfZMeZWOqZ0xNa023zYLXnpmiT3Tr/7n44M1bdpn1UN/lulXnZUkWTR5Ylps2D2LXn8xqalJ8w02zaK3Xq3mJQAAABTeChUMPf7445k8eXI6duyYUaNGpUePHunYsWP233//zJgxI/fee2+++c1vpkePHhk+fHimTJmSjh075o477kjz5s2z3nrrZdasWRk/fny22GKLjBw5MrfeemuuvvrqJX7PM888k7XXXjsHH3xw5s+fnxEjRmS11Vb7yPo22mijbL/99tl///2z00471XcsrYjmT5ue+wb/LDtfdVFqmjbN7FffyL3f/2k6bL5Jeo04NTf12jNvjXskT138m/S59Q+pW7QoC2bMyt0DjkqSPPuba9N8lbbZ656RKZXLmfb0sxl3bOMZrv1JtV+pRYb26Zmfjrw/i2rr0mWV1vn5t3vm2bfeyWm3P/qFDoA+TGXeu5l95zVp2++wlMrl1M6cllm3X50mq62ZNrscUB8AfZg5fx2ZNjvvm1UPOymp1GXhay9k7iNjq1Q9AADQoGpWqMk2X2grVDDUqVOn/OQnP8nkyZOzzTbbpF+/fhk8eHD69n3/27I22WSTTJw4Me3bt89JJ52UQw89NM2aNUuXLl3Spk2bNGvWLBdddFFOP/30LFiwIK1bt85ZZy39x+s222yT6667Lt/61rdSqVSy5ZZb5sUXX/xYNa6zzjoZMGBAhg8fnksvvfRzvf5qe+PPf8sbf/7bEmsLnpyVm3rtWX/87K+vzbO/vnapcyt1dfn72Zfm72ev2J/Bv9p2gy9l2w2+tMRa25bNlxkKfald64z7yXeW+T7jT9x/udTXEBa+/Gymv/zsEmuLJ81bZihUN3t6pl744/rjyvx5mXXr75d3iQAAAPwHpcq/f992I/XII4/kkksuWaq7Z1lmzJiRq6++OoMHD05NTU1OO+20rL322hk4cGAVKq2eK1f5SkOX0Kjsf1H/hi6hUZk36Z2P3lRAnX9ycUOXAAAAhTdv5Ir7rdUfpdXeP/7oTY3ICtUx9HG1a9cus2fPTp8+fVIul9O1a9fsu+++Va3h9ddfz9FHH73M10477bRsuummVa0HAAAA4N+tMMHQ1ltvna233vpj7S2VSjnppJOWc0X/2VprrdWoh0sDAABAQyn9y5dL0bBMewIAAAAoKMEQAAAAQEEJhgAAAAAKaoWZMQQAAAB8QdSYMdRY6BgCAAAAKCjBEAAAAEBBCYYAAAAACkowBAAAAFBQhk8DAAAA1WX4dKOhYwgAAACgoARDAAAAAAUlGAIAAAAoKDOGAAAAgKoq1ehTaSzcCQAAAICCEgwBAAAAFJRgCAAAAKCgzBgCAAAAqqum3NAV8AEdQwAAAAAFJRgCAAAAKCjBEAAAAEBBmTEEAAAAVJcZQ42GjiEAAACAghIMAQAAABSUYAgAAACgoARDAAAAAAVl+DQAAABQVaUafSqNhWBoBTbw6qMbuoRGZfH0qQ1dQqOycPa8hi6h0em47daZf9eVDV1Go9Ni1yMaugQAAKCBiOgAAAAACkowBAAAAFBQHiUDAAAAqqum3NAV8AEdQwAAAAAFJRgCAAAAKCjBEAAAAEBBmTEEAAAAVJcZQ42GjiEAAACAghIMAQAAABSUYAgAAACgoMwYAgAAAKqqVDZjqLHQMQQAAABQUIIhAAAAgIISDAEAAAAUlGAIAAAAoKAMnwYAAACqq0afSmPhTgAAAAAUlGAIAAAAoKAEQwAAAAAFZcYQAAAAUF015YaugA/oGAIAAAAoKMEQAAAAQEEJhgAAAAAKyowhAAAAoKpKZgw1GjqGAAAAAApKMAQAAABQUIIhAAAAgIIyYwgAAACorhp9Ko2FOwEAAABQUDqG+FB/e/aVXHzHg1m4uDZfXr1Dhu23Y1q3aL7Enuvvf+r/s3fncVHV+x/H38OigIigsSVqZaY3rczsutQv910ixSVzySUtLTWvmWiK4pL7Cq5tLldzww1zS80t0erezD1viyYqm6AsCgzM/P7QJgnMJZhB5/V8PHg8POd8zsznexaQD5/zHa06cFQGg1SuTCmFtm+k0iXdJEn1Ry6Uj6e7Jfb1+jXU6rkqVh1DQdr/v/OK2P2DsrJNquTjqZGta8m9uHO+sbt/jFHoxmjtHdI+1/rYlHT1+OxLfd67hTzdiue77/3E5YmnVappWxkcnWWMi1HSus9kzszIFePZvINcq9WU6Vq6JCk7MVaXVi6QwclZnoFdVDzgUUlSZsyvuhz1b5mzjVYfR0Hae/wXzY7ap6ycHD3xsLdGd2qa5775fO/3WvX1DzJIKveQp0JfbaoyJd2Uei1Toz/fpl/jkmQ2mxX4z6rq2fifthkIAAAAALtQJApDMTExat68uSpWrCiDwSCj0SgfHx9NmDBBfn5+hfKea9eu1cSJE+Xv7y9JysnJUVZWlt5//301btz4rl/v0KFDioiI0NKlS+8oPiQkRAcPHlSpUqVkMpnk4uKisWPHqkqVolE4SUq7qlErd2jRO+1VwdtTMzd9rVlfHNAHwQ0sMSfOxWvx7v9q1eDXVNK1uKZv3Kc5Ww9qZPuGOhOfLA83F60a/JoNR1FwktMzFLbpkD55vYnKly6p2bsOK2LXYYW0eD5P7G9JqZq583uZzbnXbzryqxbuPaqEtGtWyrpwObi5q3TbHor/aIKyL8WrVNN28mzaTslR/84VV6z847q0coGyzv2ca33J+q1lcHBQbMQoSVLp9r1Vsl5LpezcYLUxFLSktKsKXb5Viwd2UgUfL83YuFezNu7TBx3++J5y4lyclnz1nVa9300lXYtr2vrdmrP5a4V2bKI5m7+Wr2dJTev5sq5mGhU8cZGeqxigZx592IajAgAAAPAgKzKPkvn4+GjDhg1av369vvjiC1WuXFmTJ08u1Pds2LChNmzYoA0bNmjTpk16//33FRoaWqjvebMBAwZow4YNioqK0ptvvqkRI0ZY7b1vJ/rH31S1nK8qeHtKktrXfUpb/vujzDdVO54s56ONw67/cptpzFb8lXSVKuEiSTp85qIcHQzqEbFG7acu04Lth5RjMtlkLAXh4K+xetK/jMqXLilJalfjcW05fjbX8ZCkDGO2Rm6I1qDGz+Zan5B6VXtOxyi8U31rpVzoXCpVVdb5M8q+FC9JSvvmK7k9Uyt3kKOTivmXV8n/ayHfd8JUplM/OZYqLUnKPHNaKbs3SWazZDbLeOE3OXmWsfYwClT0qbOqVt5PFXy8JEkdXnhGm/9z8k/3ja82juh5032TJk+36/fN0LYN9K+gepKkxJQ0ZWXnyN31/u8sAwAAAFB0FYmOofzUqlVL06dPlyRt2bJFn332mTIyMpSVlaUPP/xQNWrU0OnTpxUSEqKcnBzVrFlTe/fu1ZdffqnExESFhoYqNjZWBoNBgwcPVt26dW/7nufPn1epUqUkSXFxcRo+fLhSU1MVHx+vNm3aaODAgVq7dq327dunK1eu6Ny5c3rhhRc0evToXK+zePFi7dixQwsXLpSrq+sdjTc1NVUPPfTQ3R2kQhR3OU1+Nz0G5lvKXWkZWUrPzMr1WIyzo6N2Hf1ZY1btlLOTo/o2ry1JyjGZVKtSOQ1s9YKMJpP6f7xRJVyKqctLz+Z5r/tBXMpV+Xq4WZZ9PNyUnmlUelZ2rsfJxm/+Vm2frahKPp659vcu6aYp7f7Pavlag2Op0sq5kmRZzklJloOLmwzFXSyPkzl6eCrjl5NK2bFOxvjzKvliMz3Uub/i5oYp86fjf7yWZxmVrNtESRsWW30cBSk2OUW+niUty76eJW993xz5n8JWbJezk5P6tXhBkmQwGOTkaNCwJZu144fTavj043rkRpEJAAAAeJAYHBxtnUKREBUVpXnz5ik7O1uvv/66OnfunGv7jh07FB4eLrPZrICAAE2YMEGlSpXSunXrNG3aNJUpc/2P6/Xr19egQYPuKYciWRgyGo3atm2bqlevLpPJpBUrVmj+/PkqXbq01qxZo4ULF2r+/PkKCQnRwIEDVa9ePS1atEg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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = np.zeros_like(df_corr_B)\n",
    "mask[np.triu_indices_from(mask)] = True\n",
    "with sns.axes_style(\"white\"):\n",
    "    f, ax = plt.subplots(figsize=(20, 20))\n",
    "    ax = sns.heatmap(df_corr_B.round(2), mask=mask,  annot=True, center=0, square=True, vmax=1, vmin=-1, cmap=\"RdBu_r\")\n",
    "    label_x = ax.get_xticklabels()\n",
    "    plt.setp(label_x, rotation=45, horizontalalignment='right')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = np.zeros_like(df_p_B)\n",
    "mask[np.tril_indices_from(mask)] = True\n",
    "with sns.axes_style(\"white\"):\n",
    "    f, ax = plt.subplots(figsize=(20, 20))\n",
    "    ax = sns.heatmap(df_p_B.round(2), mask=mask,  annot=True, center=0, square=True, vmax=0.08, vmin=0, \n",
    "                     cmap=\"Purples_r\")\n",
    "    label_x = ax.get_xticklabels()\n",
    "    plt.setp(label_x, rotation=45, horizontalalignment='right')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 460,
   "metadata": {},
   "outputs": [],
   "source": [
    "metrics['nominated'] = metrics.apply(lambda x: x.name in nodes_nom_s.union(lines_nom_s), axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 462,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ttest_indResult(statistic=array([6.38739256, 5.03822707, 6.05617607, 3.89916159]), pvalue=array([4.30652950e-10, 6.87795573e-07, 2.99728528e-09, 1.11624391e-04]))"
      ]
     },
     "execution_count": 462,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m5 = metrics[metrics['nominated']==True]\n",
    "m6 = metrics[metrics['nominated']==False]\n",
    "\n",
    "ttest_ind(m1[['closeness_c', 'degree_c', 'betweenness_c', 'pagerank']],\n",
    "          m2[['closeness_c', 'degree_c', 'betweenness_c', 'pagerank']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 463,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f95819e9e80>"
      ]
     },
     "execution_count": 463,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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5platWqXTp08rIiJCHh4eWr16tR599FFFR0crKytLkhQVFaUTJ07oww8/1LJly2QymdS3b1/l5eXZzvf+++/rqaee0ueff67AwECNGjVKZrNZo0ePtnVQq1evLlTHvHnzNHv2bL3yyitKSEhQx44dNWDAAP3444+2Y1avXi0/Pz99/vnn6tGjh9577z0dOnRIkrRixQotXbpU0dHRWrNmjdq2batnn31WycnJkqSYmBjFx8fr3Xff1ZIlS7RlyxZlZmbe/H8gALjF0T/SPwIo3wiKpehg0lkt2HpYmVlmeXu4KDPLrAVbD5dJZ/jMM8+obdu2atiwofr06aOjR4/KbDZr586d+vXXXzV9+nQFBQUpKChIs2bN0uHDh7Vr1y55enrKwcFBVatWlaenZ5Hn79mzp1q3bq1GjRqpXbt2cnd31/Dhw1W/fn0999xzunTpklJSUpScnKwNGzZo+vTpCg4OVoMGDTR16lSlpKTo66+/tp2vS5cu6tKli+666y4NGjRImZmZOnnypKpVqyYnJye5ubkVmlJjsVi0ZMkS9e/fX126dFG9evX08ssvq02bNlq4cKHtuICAAA0dOlT169fXwIED5enpqR9++EGSNH/+fL366qtq166dAgMD1b9/f913332KjY2VxWLRihUrNHDgQIWEhKhhw4Z699135eDgUML/tQDg1kL/SP8IoPzjGsVSlLA3Sa7OjnJ3sf6arzwm7E1ScGCNUn3twMBA288eHh6SpLy8PP3000+qVauW/Pz8bPv9/f1Vu3Zt/fTTT3rwwQeLdf66devafnZzc1Pt2rVlMpkkSS4uLpIks9msU6dOSZI6depk9/ycnBydOHFC7du3lyTVq1fvmvVez9mzZ3X+/Hk1bdrUrv2+++7Tpk2brlmrJFWtWlV5eXnKysrSqVOn9Pbbbys6Otq232w2y9nZWefPn1dGRoYaN25s2+fv7y9fX9/r1gUAuD76R/pHAOUfQbEUnT6fLW8PF7s2N2cHnTmfXeqv7eTkVKjNYrHI1dX1msdbLBZZLJZin9/R0f7/OlWqXHtwOj8/X05OTlqzZo2to7zitttu+9N6r+d676WgoMC27ezsfN1jpkyZYtfZ/fHcf6zjWrUCt7zkOClxnJSVJFUNlIKipIAIo6tCOUX/SP8IoPxj6mkpqunlrhxzvl1bjjlf/l7uBlUk3XnnnTp16pTt4nxJSk1N1alTp1S/fv0Sf7369esrNzdXOTk5qlu3rurWrSsfHx+9++67SkpKuqlze3h4yNfX1+7ieknav39/sd5LtWrV5OPjo9TUVFttdevW1SeffKKvv/5aXl5e8vHx0cGDB23POXfunE6fPn1TdQOVTnKc9O1LUnaK5OBmffz2JWs7cA30j/SPAMo/gmIpCm8RqEvmPGVfzpPFYlH25TxdMucpvEWgYTW1adNGd999t4YPH65Dhw7p0KFDevXVVxUYGKgHHnhAknXqyfHjx3X27M1fK1K/fn116NBBr7/+uvbu3avjx4/rjTfe0Pfff1/sjrdq1ar65Zdf7FaCu+LFF1/UvHnztGHDBiUlJSkmJkY7d+4sckW6P+rbt69iYmK0ceNGJScnKyYmRsuXL1e9evVkMpn03HPPae7cufryyy/1008/adSoUcrPz//zEwO3ksRxksUiOThLJpP10WKxtgPXQP9I/wig/GPqaSkKDqyhFx9prIS9STpzPlv+Xu4Kb9ug1K+/uB6TyaSYmBhNnDhRvXv3loODg0JCQjRz5kzbFJTIyEhNnjxZ+/fvt1vG+6965513NHnyZA0aNEhms1lNmjTRRx99pOrVqxfr+U8//bTeeOMNhYeHa/fu3Xb7nnnmGWVnZ2vq1Kk6e/asGjRooHnz5qlFixbFOndkZKQuXbqkqVOnKiMjQ4GBgXr//fd13333SZL69Okjs9ms6OhoXbp0Sb1799Yvv/xyY78AoLLLSrKOJF6tipO1HbgG+kcr+kcA5ZnJciMT7yuJlJQUPfzww9q2bZvq1KljdDkAULFtbPrfaadXXe+Ub5bc60idDxT9vDLCZ/6N4fcFALeGP/u8Z+opAODmBEVZp5zmm61TTvPN1u2gKKMrAwAAfxFBEQBwcwIipJbzrSOI+TnWx5bzWfUUAIAKjGsUAQA3LyCCYAgAQCXCiCIAAAAAwA5BEQAAAABgh6AIAAAAALBDUAQAAAAA2CEoAgAAAADsEBQBAAAAAHYIigAAAAAAOwRFAAAAAIAdgiIAAAAAwA5BEQAAAABgh6AIAAAAALBDUAQAAAAA2CEoAgAAAADsEBQBAAAAAHYIigAAAAAAOwRFAAAAAIAdgiIAAAAAwA5BEQAAAABgh6AIAAAAALBDUAQAAAAA2CEoAgAAAADsEBQBAAAAAHYIigAAAAAAOwRFAAAAAIAdgiIAABXMunXr1LlzZz366KNavnx5of1z5sxR+/bt1a1bN3Xr1u2axwAAcD2ORhcAAACKLzU1VTNnzlRcXJycnZ311FNPqVWrVrrrrrtsxxw6dEgzZsxQs2bNDKwUAFCRMaIIAEAFsmvXLrVu3Vqenp5yd3dXaGioNm3aZHfMoUOHNH/+fIWFhWncuHG6fPmyQdUCACoqgiIAABVIWlqafHx8bNu+vr5KTU21bWdlZalRo0YaMWKE1qxZo99//10xMTFGlAoAqMAIigAAVCAFBQUymUy2bYvFYrddtWpVLVy4UHfeeaccHR31wgsvaMeOHUaUCgCowAiKAABUIP7+/kpPT7dtp6eny9fX17Z96tQprV692rZtsVjk6MiSBACAG0NQBACgAmnTpo12796tc+fOKScnR1u2bFFISIhtv6urq6ZOnark5GRZLBYtX75cjzzyiIEVAwAqIoIiAAAViJ+fn4YNG6bIyEh1795dXbt2VXBwsPr166fExER5e3tr3LhxGjBggDp16iSLxaLnn3/e6LIBABUMc1EAAKhgwsLCFBYWZte2cOFC28+hoaEKDQ0t67IAAJUII4oAAAAAADsERQAo75LjpI1Npc88rY/JcUZXBAAAKjmmngJAeZYcJ337kmSxSA5uUnaKdVuSAiKMrQ0AAFRajCgCQHmWOO6/IdFZMpmsjxaLtR0AAKCUEBQBoDzLSpKqONm3VXGytgMAAJQSgiIAlGdVA6WCXPu2glxrOwAAQCkhKAJAeRYUZZ1ymm+2TjnNN1u3g6KMrgwAAFRiBEUAKM8CIqSW8yX3OlJ+jvWx5XwWsgEAAKWKVU8BoLwLiCAYAgCAMsWIIgAAAADADkERAAAAAGCHoAgAAAAAsENQBAAAAADYISgCAAAAAOwQFAEAAAAAdgiKAAAAAAA7ZRoU161bp86dO+vRRx/V8uXLC+0/cuSIIiIiFBoaqtGjRysvL0+SdOrUKfXq1UudOnXSgAEDlJWVJUn67bff1K9fP4WHh6tHjx46cuRIWb4dAAAAAKiUyiwopqamaubMmYqNjVV8fLxWrlypY8eO2R0zYsQIRUVFafPmzbJYLFq1apUkaezYserZs6c2bdqke++9VzExMZKkxYsXq0GDBkpISNDAgQM1bty4sno7AAAAAFBplVlQ3LVrl1q3bi1PT0+5u7srNDRUmzZtsu0/efKkLl26pKZNm0qSIiIitGnTJuXm5uq7775TaGioXbskFRQU2EYXc3Jy5OrqWlZvBwAAAAAqLceyeqG0tDT5+PjYtn19fXXw4MEi9/v4+Cg1NVXnz5+Xh4eHHB0d7dol6YUXXtA///lPPfTQQ8rKytJHH31URu8GAAAAACqvMhtRLCgokMlksm1bLBa77aL2//E4Sbbt8ePHq1evXtq5c6c++ugjDRs2zDbCCAAAAAD4a8osKPr7+ys9Pd22nZ6eLl9f3yL3Z2RkyNfXV97e3rpw4YLy8/MLPW/btm164oknJEnNmjVTjRo1dPz48bJ4OwAAAABQaZVZUGzTpo12796tc+fOKScnR1u2bFFISIhtf+3ateXi4qJ9+/ZJktauXauQkBA5OTmpRYsW2rhxoyQpPj7e9ryGDRvqyy+/lCQlJSUpLS1N9erVK6u3BAAAAACVUpkFRT8/Pw0bNkyRkZHq3r27unbtquDgYPXr10+JiYmSpGnTpmny5Mnq1KmTsrOzFRkZKUmKjo7WqlWr1LlzZ+3du1dDhw6VJE2ZMkWff/65unbtquHDh+udd95RtWrVyuotAQAAAEClVGaL2UhSWFiYwsLC7NoWLlxo+7lhw4ZavXp1oefVrl1by5YtK9QeGBiopUuXlnyhAAAAAHALK7MRRQAAAABAxUBQBAAAAADYISgCAAAAAOwQFAEAAAAAdgiKAAAAAAA7BEUAAAAAgB2CIgAAAADADkERAAAAAGCHoAgAAAAAsENQBAAAAADYISgCAAAAAOwQFAEAAAAAdgiKAAAYKDs7WxcvXjS6DAAA7DgaXQAAALeC//u//9P69etlMpnUrVs33XnnnRo3bpxWrFghSXr44Yc1efJkeXh4GFwpAAAERQAASt2//vUvDR48WHXq1JG7u7uWLl2qHj16aP369XrllVdUUFCgJUuWaO7cuRoxYoTR5QIAQFAEAKC0zZ49W/3799fgwYMlSevXr9eIESM0adIkPf7445KkBg0aaPLkyQRFAEC5wDWKAACUsp9//lldu3a1bT/22GOqUqWK7r33XltbUFCQUlNTjSgPAIBCCIoAAJSynJwcu2sPHRwc5OzsLFdXV7u2/Px8I8oDAKAQgiIAAGXAZDIZXQIAAMXGNYoAAJSBLVu22I0qFhQUaNu2bapRo4Yk6cKFC0aVBgBAIQRFAADKwNixYwu1TZkyxW6bUUcAQHlBUAQAoJT9+OOPRpcAAMAN4RpFAAAAAIAdgiIAAAAAwA5BEQAAAABgh6AIAAAAALBDUAQAoAwtW7ZMmZmZRpcBAMB1ERQBAChDixcv1t///ncNHjxY27ZtU35+vtElAQBQCEERAIAytH37di1atEienp4aOXKkHnroIU2cOFFHjhwp9jnWrVunzp0769FHH9Xy5cuLPO5f//qXOnToUBJlAwBuMdxHEQCAMtayZUu1bNlSUVFR2r59u7Zu3aqePXsqICBATzzxhB5//HFVr179ms9NTU3VzJkzFRcXJ2dnZz311FNq1aqV7rrrLrvjMjIy9M4775TF2wEAVEKMKAIAYJCUlBQdPXpUR48eVW5urmrVqqWEhAR16NBBX3755TWfs2vXLrVu3Vqenp5yd3dXaGioNm3aVOi4t956S4MHDy7ttwAAqKQYUQQAoAydPXtW69evV0JCgg4fPqy7775bTzzxhMLDw+Xt7S1Jmj59uqKjo9WxY8dCz09LS5OPj49t29fXVwcPHrQ7ZunSpWrcuLGaNGlSum8GAFBpERQBAChDISEhuu2229SlSxdNmDBBjRo1KnRMkyZNtHv37ms+v6CgQCaTybZtsVjsto8ePaotW7bo448/1pkzZ0r+DQAAbgkERQAAytB7772ndu3aydGxcBd89uxZ1ahRQx07drzmaKIk+fv7a+/evbbt9PR0+fr62rY3bdqk9PR0PfHEE8rNzVVaWpp69uyp2NjYkn8zAIBKi2sUAQAoQy+//LJ+//33Qu2nTp0qMhxerU2bNtq9e7fOnTunnJwcbdmyRSEhIbb9r7zyijZv3qy1a9dqwYIF8vX1JSQCAG4YI4oAAJSyjRs36uuvv5ZknSo6YcIEubi42B2TkpKiqlWr/um5/Pz8NGzYMEVGRio3N1c9evRQcHCw+vXrp1deeUVBQUGl8h4AALcWgiIAAKWsefPmWr16tSwWiyTrgjROTk62/SaTSZ6enpo6dWqxzhcWFqawsDC7toULFxY6rk6dOtq+fftNVA4AuFURFAEAKGX+/v766KOPJEmjRo3S6NGj5eHhYXBVAAAUjaAIAEApS01NlZ+fnyRp6NChysrKUlZW1jWPvXIcAABGIigCAFDK2rVrp507d6pGjRpq27at3e0srrhym4sjR44YUCEAAPYIigAAlLIlS5botttus/18raAIAEB5QlAEAKCUtWzZ0vZzq1atDKwEAIDiISgCAFDKXnjhhWIfe2XRGwAAjERQBACglLFADQCgoiEoAgBQyiZPnr+W0qMAACAASURBVGx0CQAA3BCCIgAAZezHH3/U0aNHVVBQIMm64qnZbFZiYqImTJhgcHUAABAUAQAoU4sWLdLUqVNVpUoV2y0xCgoKZDKZWOgGAFBuVDG6AAAAbiXLly/XoEGDlJiYKG9vb3311VfauHGjGjRooJCQEKPLAwBAEkERAIAylZaWpu7du8vBwUENGzbUwYMHVb9+fY0cOVKrV682ujwAACQRFAEAKFMeHh66fPmyJCkwMFBHjx6VJNWtW1enTp0ysjQAAGwIigAAlKGWLVtq+vTpSktLU1BQkDZv3qwLFy5o+/bt8vT0NLo8AAAkERQBAChTb7zxhlJSUrRx40Z17txZVapUUcuWLTVx4kQ9++yzRpcHAIAkVj0FAKBM/f7770pISJDZbJazs7M+/fRTffvtt/Ly8lJwcLDR5QEAIImgCKCUHUw6q4S9STp9Pls1vdwV3iJQwYE1jC4LMEyfPn00b948Wyh0c3NT27ZtDa4KAAB7Nzz19LffflNsbKyWL1+utLS00qgJQCVxMOmsFmw9rMwss7w9XJSZZdaCrYd1MOms0aUBhqlevbrMZrPRZQAAcF1Fjijm5uZq1qxZWrt2rSTpH//4h3r27KkePXrozJkzkqTp06fr448/ZqoMgGtK2JskV2dHubtYP2quPCbsTWJUEbes9u3bq1+/furQoYMCAgLk6upqt79///4GVQYAwP8UGRTfe+89rV27VpGRkXJ1ddXKlSu1YcMGBQQEaOXKlbJYLHrrrbc0d+5czZ07tyxrBlBBnD6fLW8PF7s2N2cHnTmfbVBFgPE2b94sLy8v7d+/X/v377fbZzKZCIoAgHKhyKC4YcMGTZo0SSEhIZKkkJAQderUSWPGjJGfn58kadiwYXrhhRfKplIAFU5NL3dlZpltI4mSlGPOl7+Xu4FVAcbavn17kfssFksZVgIAQNGKvEYxLS1NDRo0sG0HBgbK2dlZNWvWtLX5+fnpwoULpVshgAorvEWgLpnzlH05TxaLRdmX83TJnKfwFoFGlwYY5uGHH1ZmZmah9rS0NLVp08aAigAAKKzIEcX8/Hw5OTnZtTk4OMjBwcGujW8/ARQlOLCGXnyksRL2JunM+Wz5e7krvG0Drk/ELWfHjh1KTEyUJJ08eVILFiyQu7v9yHpSUpLy8/ONKA8AgEKKDIomk0kmk6ksawFQCQUH1iAY4pZXp04dTZo0yfbl6ubNm+2+eDWZTKpatareeusto0oEAMBOkUHRYrFoyJAhdqOKZrNZb7zxhm2Fttzc3NKvEACACu7OO+/U5s2bJUm9e/fWnDlzdNtttxlcFQAARSsyKD7++OOF2sLDwwu11alTp2QrAgCgElu2bJnRJQAA8KeKDIqTJ08uyzoAALgl/Pzzz5owYYL2799/zZk5hw4dMqAqAADsFRkUAQBAyRs7dqxOnTqloUOHqnr16kaXAwDANREUAQAoQ4mJiVq8eLGaNGlidCkAABSpyPsoAgCAkufp6SlnZ2ejywAA4LoIigAAlKH+/ftr0qRJOnHihAoKCowuBwCAayrW1NOtW7fqkUceKdR+4sQJjR49WrGxsSVeGAAAldHixYuVnJyszp07y2QyqUoV++9sWcwGAFAeFCsoDh8+XDNnzlTHjh0lSQUFBfrwww81Z84c3XnnnaVaIAAAlcmLL75odAkAAPypYgXFsWPH6tVXX9X06dNVp04dvfnmmzpx4oReeeUVPf/888V+sXXr1mnu3LnKy8vTs88+q169etntP3LkiEaPHq2srCy1aNFCY8eOlaOjo06dOqURI0bo7NmzqlevnqZNm6aqVavq4sWLio6O1vHjxyVJEydO1D333HMDbx8AgLJ1rfsUAwBQ3hTrGsWIiAhNmjRJr732mnr06KEaNWpo3bp16tu3rxwcHIr1QqmpqZo5c6ZiY2MVHx+vlStX6tixY3bHjBgxQlFRUdq8ebMsFotWrVolyRpUe/bsqU2bNunee+9VTEyMJOu9HmvWrKn4+HgNHz5cY8aMuYG3DgCAMb777jv17dtXHTp00MmTJzV79mzFx8cbXRYAADbFXsymS5cumjZtmhwcHPTkk0+qTp06N/RCu3btUuvWreXp6Sl3d3eFhoZq06ZNtv0nT57UpUuX1LRpU0nWcLpp0ybl5ubqu+++U2hoqF27xWLRli1bbFN4QkJCNGnSpBuqCQCAsrZjxw717dtXNWvWVEZGhgoKCmQymTR69Gh9/vnnRpcHAICk60w9veeee2QymQq15+XlaciQIXYjicW58D4tLU0+Pj62bV9fXx08eLDI/T4+PkpNTdX58+fl4eEhR0dHu/azZ8/K2dlZsbGx+uqrr+Ti4qI333zzT+sAAMBIc+bM0euvv65evXpp/fr1kqTBgwerevXq+uijj/TEE08YXCEAANcJiuPHj79mUPyrrnxjeoXFYrHbLmr/H4+TJJPJpPz8fGVkZKhatWpauXKl/v3vf2vQoEHatm1bidUMAEBJO3bsmEJCQgq1t2/fXtOmTTOgIgAACisyKEZERJToC/n7+2vv3r227fT0dPn6+trtT09Pt21nZGTI19dX3t7eunDhgvLz8+Xg4GB7npeXlxwdHdW1a1dJ0oMPPqjs7GydPXtWNWrUKNHaAQAoKV5eXkpOTlZAQIBd+6FDh3T77bcbVBUAAPaKteppQUGBNmzYoAMHDig3N1cWi8W2z2Qyady4cX96jjZt2mj27Nk6d+6c3NzctGXLFo0fP962v3bt2nJxcdG+fft03333ae3atQoJCZGTk5NatGihjRs3KiwsTPHx8QoJCZGzs7PatGmjDRs2qGfPnjpw4IDc3Nzk5eX1F34NAACUjX/84x8aO3as7XKJX3/9VXv27NGMGTP09NNPG1wdAABWxQqKkyZN0vLly3X33XerWrVqf+mF/Pz8NGzYMEVGRio3N1c9evRQcHCw+vXrp1deeUVBQUGaNm2a3nrrLV28eFH33HOPIiMjJUnR0dEaOXKk5s6dq5o1a2rGjBmSrLfDiIqKUmxsrBwdHTVz5sxCNy4GAKA8eemll3ThwgW9/PLLMpvN6tOnjxwdHfX8889r0KBBRpcHAIAkyWS5eniwCG3bttWLL75Y6L6HFVVKSooefvhhbdu27YZXbwUAVCzl9TM/Oztbx48fl5OTkwIDA+Xq6mp0SZLK7+8LAFCy/uzzvljDbxcvXtRDDz1U4sUBAHArOXjwoC5fvixJcnd3V1BQkH799VcdOXLE4MoAALBXrKD48MMP293zEAAA3Jjo6Gj985//1P79++3aP//8c/Xs2VMTJ040qDIAAAor1jWK/v7++uCDD7R9+3YFBgbK2dnZbv/Vi9IAAAB7K1as0Pr16zVjxgy1atXKbt+8efO0fv16RUVFqVGjRiW+6jiAW8/BpLNK2Juk0+ezVdPLXeEtAhUcyF0BcGOKFRT379+vJk2aSJJOnTpVqgUBAFDZrFy5UiNHjtRjjz1WaJ/JZFJYWJjS09O1fPlygiKAm3Iw6awWbD0sV2dHeXu4KDPLrAVbD+vFRxoTFnFDihUUly1bVtp1AABQaSUlJal169bXPaZdu3b64IMPyqgiAJVVwt4kuTo7yt3F+mf+lceEvUkERdyQYgVFSTp37pxOnDihgoICSZLFYpHZbFZiYqIGDBhQagUCAFDRubm5KSsr67rH5OXlycnJqYwqAlBZnT6fLW8PF7s2N2cHnTmfbVBFqKiKFRTj4+MVFRUls9ksk8kki8Uik8kkSbrjjjsIigAAXEdwcLA2bdqkhg0bFnnMhg0b9Le//a0MqwJQGdX0cldmltk2kihJOeZ8+Xu5G1gVKqJirXo6b948de/eXVu3blX16tUVFxenBQsWqGbNmnrppZdKu0YAACq0Z599Vh9++KFWrFiha92+ODY2VosWLVJkZKQB1QGoTMJbBOqSOU/Zl/NksViUfTlPl8x5Cm8RaHRpqGCKNaKYkpKiuXPnKiAgQA0bNlRaWpratWun0aNHa/bs2Vx4DwDAdTzwwAMaNmyYxo8frzlz5ujee+9V9erV9dtvvykxMVG///67Bg0apEceecToUgFUcMGBNfTiI42VsDdJZ85ny9/LXeFtG3B9Im5YsYKim5ubqlSxDj7WrVtXR48eVbt27dSoUSP98ssvpVogAACVQZ8+ffTAAw/os88+0+HDh5WUlCQvLy9169ZNERERTDsFUGKCA2sQDHHTihUUmzVrpkWLFmn06NFq3Lix1q5dqxdffFHff/+9qlatWto1AgBQKTRu3FjR0dFGlwEAwJ8qVlAcPny4+vTpozvuuENPPfWU5s+fr1atWikrK4vrKQAAAABUPMlxUuI4KStJqhooBUVJAVxSd0WxgmLDhg315ZdfKicnRx4eHlq1apW2bNkib2/va948GAAAlJ5169Zp7ty5ysvL07PPPqtevXrZ7d+6davef/99FRQUKCgoSOPGjZOzs7NB1QJAOZQcJ337kmSxSA5uUnaKdVsiLP5XsVY9lazXKXp7e0uSfHx81KtXLz322GP65JNPSq04AABgLzU1VTNnzlRsbKzi4+O1cuVKHTt2zLY/Oztb48aN0+LFi7VhwwZdvnxZa9asMbBiACiHEsf9NyQ6SyaT9dFisbZD0nWCosVi0YcffqiIiAj985//1PLly+32//TTT3rqqac0ceLEUi8SAABY7dq1S61bt5anp6fc3d0VGhqqTZs22fa7u7tr+/btuv3225WTk6OzZ8+qevXqBlYMAOVQVpJUxcm+rYqTtR2SrhMUZ82apWnTpql69eq67bbbNHnyZFtYXLhwoSIiIpSUlKTJkyeXWbEAAFQGJ0+e1MWLFyVJ3333ncaNG6e1a9cW67lpaWny8fGxbfv6+io1NdXuGCcnJ+3YsUPt2rXT+fPn9dBDD5Vc8QBQGVQNlApy7dsKcq3tkHSdoLhhwwYNGzZMH3/8sRYsWKCJEydq+fLlmjFjhqZPn67Q0FB98cUX6t69e1nWCwBAhbZp0yaFhobq+++/16+//qoXX3xR3333ncaMGaOPP/74T59fUFAgk8lk27ZYLHbbV7Rt21Z79uxR+/btNWbMmBJ8BwBQCQRFWaec5putU07zzdbtoCijKys3igyKaWlpCg0NtW137txZSUlJWrFihd577z1NmzZNXl5eZVIkAACVRUxMjAYOHKgHH3xQa9eulZ+fnxISEvTuu+/q008//dPn+/v7Kz093badnp4uX19f23ZmZqZ27txp2w4LC9P//d//leybAICKLiBCajlfcq8j5edYH1vOZyGbqxQZFM1ms6pVq2bbdnJykouLi15//XW7AAkAAIrvxIkTttk4X3/9tdq3by+TyaR77rlHp0+f/tPnt2nTRrt379a5c+eUk5OjLVu2KCQkxLbfYrFoxIgROnXqlCTrCGbz5s1L580AQEUWECF1PiA9mWl9JCTaKfaqp1fcf//9pVEHgL8iOU7a2FT6zNP6mBxndEUA/oSXl5cyMjKUkZGhQ4cO6cEHH5QkHT16VLfffvufPt/Pz0/Dhg1TZGSkunfvrq5duyo4OFj9+vVTYmKivLy8NH78eL300ksKDw/XiRMnNGLEiNJ+WwCASua691G81jUPVarccLYEUBq4/w9QIXXp0kWvvfaaXF1d5efnpwceeEAbN27UhAkT1KNHj2KdIywsTGFhYXZtCxcutP3csWNHdezYsUTrBgDcWq4bFCdPnixXV1fbdm5urmbMmCEPDw+748aPH1861QEo2tX3/5Gsj/lmaztBESi3RowYoVq1aunXX39Vz5495eDgoMzMTPXq1UsDBgwwujwAACRdJyjef//9OnPmjF1bs2bNbNNlrrjWqCOAMpCVZB1JvBr3/wHKvSpVqqh37952bZ06dZK3t7dBFQEAUFiRQXHZsmVlWQeAG1U10Drd9MqIosT9f4AK4LffftO7776ryMhI/e1vf9PAgQO1Y8cO3XHHHVqwYIHq1q1rdIkAjJIcZ50ZlJVk7c+DopglBMNwwSFQUXH/H6BCmjhxovbv3y8nJyd98cUX2r17t2bMmKEGDRpo8uTJRpcHwChX1h7ITrFfe4CF6mAQgiJQUXH/H6BC2rFjh6ZMmaL69etr+/bteuihh/TYY49p6NCh+u6774wuD4BRrl57wGSyPlos1nbAANddzAZA+XYwv60SshfpdGa2aprcFZ4fqGCjiwJwXWazWT4+PpKkXbt26eWXX5ZkveaflcWBWxhrD6CcoUcCKqiDSWe1YOthZWaZ5e3hoswssxZsPayDSWeNLg3AdTRs2FCff/65Pv30U50/f17t2rWT2WzWhx9+qIYNGxpdHgCjVA20rjVwNdYegIFuKChmZGRoz549unTpks6e5Y9RwEgJe5Pk6uwodxdHmUwmubs4ytXZUQl7k4wuDcB1vPHGG4qNjdW4cePUp08f1apVS5MmTdK2bds0YsQIo8sDYBTWHkA5U6ypp2azWWPGjFFcXJyqVKmizZs3a8qUKbp48aLmzJmjatWqlXadAP7g9PlseXu42LW5OTvozPlsgyoCUBxNmzbVzp07deHCBd12222SpD59+ui1114rdJ9iALeQK2sMsOopyolijSjOmTNHiYmJio2NlYuL9Q/Tvn376syZM5o6dWqpFgjg2mp6uSvHnG/XlmPOl7+Xu0EVASiugoIC/fvf/9bs2bOVmZmp06dPy2w2G10WgL/oYNJZTVi9T4MWfq0Jq/f99ctAAiKkzgekJzOtj4REGKhYQfGLL77QW2+9pebNm9vamjVrpvHjx2v79u2lVhyAooW3CNQlc56yL+fJYrEo+3KeLpnzFN4i0OjSAFxHWlqawsLC9NZbb2nu3Lm6cOGCFi9erLCwMB07dszo8gDcINYMQGVVrKCYlpamWrVqFWq//fbbdeHChRIvCsCfCw6soRcfaSzPqs46f/GyPKs668VHGis4sIbRpQG4jilTpuhvf/ubvvnmG9ssnalTp+ree+/VO++8Y3B1AG4UawagsirWNYqNGjXStm3b9Nxzz9m1r1q1ihXaAAMFB9YgGAIVzJ49e7Ro0SI5Ozvb2jw8PPTqq6+qV69eBlYG4K9gzQBUVsUKiq+99pr69u2rAwcOKC8vTwsXLtTx48f1/fffa8GCBaVdIwAAlcalS5fk5ORUqN1sNstisRhQEYCbUdPLXZlZZrm7/O/PatYMQGVQrKmnLVq00KeffionJyfVrVtXiYmJqlWrluLi4tSmTZvSrhEAgErjwQcf1MKFC+1C4YULFzRjxgy1atXKwMoA/BWsGYDKqlgjipJ1+ikrnAIAcHPefPNN9e7dW3//+991+fJlDR48WCkpKfLy8tLixYuNLg/ADbqyZkDC3iSdOZ8tfy93hbdtwKUhKD3JcWVyG5ViBcVRo0Zds91kMsnJyUn+/v7q1KmT6tWrV6LFAQBQ2fj7+yshIUHr16/XkSNH5OTkpLvuukvh4eG2xW0AVCysGYAykxwnffuSZLFIDm5Sdop1WyrxsFisoGg2m7Vx40b5+PgoKChIknT48GGdOXNGTZs21bfffqu5c+dq0aJFuv/++0u0QAAAKhs3Nzc9+eSTRpcBAKhoEsf9NyT+d0E0B2cp32xtNyIouri4qHPnzpo8ebJtlba8vDy9/fbbcnJy0rhx4zRr1izNnDlTsbGxJVogAACVSXp6ut5//30dOHBAZrO50P7NmzcbUBUAoFSU9DTRrCTrSOLVqjhZ20tYsYLi5s2btWrVKrulvB0dHdW3b1/94x//0Lhx4xQREaElS5aUeIEAAFQmUVFR+s9//qNu3bqpevXqRpcDACgtpTFNtGqg9TwO/8tlKsi1tpewYgVFV1dXpaSk6M4777RrT0lJkaOj9RSXL1+2C5JAZXAw6awS9ibp9Pls1fRyV3iLQK5BAHBT9u3bp1mzZrFqOABUdqUxTTQoyho2883WkcSCXMlksraXsGLdHqN79+4aPXq01qxZo59//lnHjx9XXFyc3n77bYWFhem3337T9OnT1aJFixIvEDDKwaSzWrD1sDKzzPL2cFFmllkLth7WwaSzRpcGoAJzdnaWn5+f0WUAAEpbVpI1zF3tZqeJBkRILedL7nWk/BzrY8v5xq16Onz4cOXn52vs2LG6fPmyLBaLXF1d1bNnTw0bNkw7duxQZmampk2bVuIFAkZJ2JskV2dH2w10rzwm7E1iVBHAX9azZ0+9//77mjJlitzc3P78CQCAiqm0pokGRJRKMPyjYgVFBwcHjRw5UkOHDtXx48fl4OCgwMBAubq6SpI6duyojh07lmqhQFk7fT5b3h72S9W7OTvozPlsgyoCUBn85z//0Z49e3T//ffLx8en0GUbLGYDAJVEGU4TLQ3FCoqSdO7cOZ04cUIFBQWSpIMHD8psNisxMVEDBgwotQIBo9T0cldmltk2kihJOeZ8+Xu5G1gVgIquadOmatq0qdFlAABK25VRv5Jc9bQMFSsoxsfHKyoqSmazWSaTSRaLRSaTSZJ0xx13EBRRKYW3CNSCrYclWUcSc8z5umTOU3jbBgZXBqAiGzx4sNElAADKShlNEy0NxQqK8+bNU/fu3dWvXz/16NFDixcv1tmzZxUdHa2XXnqptGsEDBEcWEMvPtJYCXuTdOZ8tvy93BXetgHXJwK4af/5z3904MAB5ebmymKx2NpNJhP9KgCgXChWUExJSdHcuXMVEBCghg0bKi0tTe3atdPo0aM1e/ZsRURUzJQM/JngwBoEQwAl6oMPPtDs2bNVvXp1eXh42O0jKAIAyotiBUU3NzdVqWK9k0bdunV19OhRtWvXTo0aNdIvv/xSqgUCAFCZrFmzRgMGDNCQIUOMLgUAgCIV6z6KzZo106JFi3T58mU1btxYX331lSTp+++/V9WqVUu1QAAAKpOMjAx1797d6DIAALiuYgXF4cOHa9u2bVq2bJm6du2qM2fOqFWrVhoxYoTCw8NLu0YAACqN1q1b69tvvzW6DAAArqtYU08bNmyoL7/8Ujk5OfLw8NCqVau0ZcsWeXt767HHHivtGgHjJMdV2CWNAZRPrVq10qRJk/TNN9+obt26he6j2L9/f4MqAwDgf64bFLOzs/XNN9/I2dlZzZo1k7e3tyTJx8dHvXr1KpMCAcMkx1lvkmqxSA5uUnaKdVsiLAL4y5YtWyYvLy/t379f+/fvt9tnMpkIigBwKytHgxRFBsUff/xRffv2VUZGhiTJ19dXc+bMUXBwcJkVBxgqcdx/Q+J/v+13cJbyzdZ2giKAv2j79u1GlwAAKI/K2SBFkdcoTp8+XQEBAVqxYoVWrVqlevXqaezYsWVZG2CsrCSpipN9WxUnazsA3KTvv/9ecXFxunjxoo4dO6a8vDyjSwIAGOnqQQqTyfposVjbDVDkiOKBAwe0dOlSNWrUSJI0YcIEhYaGKjs7W+7u7mVWIGCYqoHWb3Icrrp+qCDX2g4Af9GFCxc0ePBg7dmzRyaTSffff7+mTZumX375RYsXL5a/v7/RJQJA+VaOpmeWqKwk60ji1QwcpChyRDErK0u33367bTsgIEAODg7KzMwsk8IAwwVFWb/NyTdbv83JN1u3g6KMrgxABTZ16lTl5+drx44dcnV1lSSNHj1a1apV0zvvvGNwdQBQzl2ZnpmdYj89MznO6MpuXtVA66DE1QwcpCgyKBYUFKhKFfvdjo6Oys/PL/WigHIhIEJqOV9yryPl51gfW86vHN9YATDMjh079Prrr8vPz8/WFhAQoLffflu7d+82sDIAqADK2fTMElXOBimKdXsM4JYVEEEwBFCifvvtN912222F2l1cXHT58mUDKgKACqScTc8sUVf+5iwn02qvGxSXLl0qN7f//YfIz89XbGxsoQ6OpbwBACie++67T5999plee+01W1t+fr4WLFigpk2bGlgZAFQAlX0NiXI0SFFkUKxVq5bWrVtn13b77bdr8+bNdm3c8wmV2cGks0rYm6TT57NV08td4S0CFRxYw+iyAFRgb7zxhnr37q09e/YoNzdXEyZM0PHjx/X7779r8eLFRpcHAOVbUJT1msR8s3UksSCXNSRKSZFBkfs84VZ3MOmsFmw9LFdnR3l7uCgzy6wFWw/rxUcaExYB/GUNGjRQQkKCYmNj5e3tLScnJ3Xt2lXPPPOM3SJyAIBrKGfTMyszrlEEipCwN0l5BRadPJelS7n5cnVy0G3uzkrYm0RQBHBT/Pz8NGzYMOXl5cnBwUEmk8nokgCg4ihH0zMrM4IiUISfU39Xxu85yi+QCiwWmXPzlXXJLHNegdGlAajg4uPjNW/ePKWkpOiLL77Qhx9+KF9fXw0aNOj/s3fv8VHVd+L/X+ecuSdAEshNQCMWsSrR/coipVW3tYrlW2JlcXerLXvpSq367cNur7u6VK3brvuwa1v70Irby9rKrpYihq0/0NaWukVrg9VQQURhhGBIyD2Z+znn8/vjZCYZMrlPMjPJ+/l46DCfuX3OzIjnPe/P5/3O9dSEEEIIYIT2GELMdr2RBHFToQBd01BA3FT0RuK5npoQooDt2LGDr3/963zsYx9LtaE677zzePTRR3n00UdzPDshhBDCIYGiEMOImxbOajCFEy4qNM0ZF0KIifrBD37AP//zP3PzzTdjGAYAH//4x/na177Gk08+mePZCSGEEA5ZeirEMAxdx+sC01bYSqFrGi5Dw9Dl9xUhxMS98847GdtgXHzxxbS0tORgRkIIIcRQcsYrxDCWVM5BoeHzGBT73Pg8BgqNsyvn5HpqQogCVl1dzRtvvDFk/MUXX6S6ujoHMxJCCCGGmtZAcefOnaxdu5arr76axx9/fMjtBw8eZP369axZs4Y77rgD0zQBePfdd7nxxhu55ppr+MxnPkMoFEp73MmTJ1m5ciVNTU3TchwiPzUG27l32z5uffQFbdpQJwAAIABJREFU7t22j8Zg+6Seb+MVy5hf7EFDI2HaaGjML/aw8YplWZqxEGI2+ru/+zvuuusutm7dilKKl19+mW9/+9t84xvf4BOf+ESupyeEEEIA0xgotrS08MADD7B161Z27NjBE088wVtvvZV2ny9+8Yts3ryZ3bt3o5RK7dW4++67ueGGG9i1axcXXnghDz30UOoxtm1zxx13kEgkputQRB5qDLbzrZ838lqwnRMdIV7rvz6ZYLG2Zj63f/QiLqqZz8KyIi7qvy6tMYQQk/EXf/EX3HrrrTzyyCNEo1HuuOMOtm/fzpe//GU++clP5np6QgghBDCNgeLevXtZtWoVJSUlBAIB1qxZw65du1K3nzhxgmg0mtq3sX79enbt2kUikeD3v/89a9asSRtP+o//+A9Wr15NaWnpdB2KyEOP7XmTjt4YSoHXZaAUdPTGeGzPm5N63tqa+dy54RK+e9Nl3LnhEgkSRX44vh2euRh+WuJcHt+e6xmJceju7uaGG25gz5497N27l4aGBvbs2cNf/dVf5XpqQgghRMq0BYqtra2Ul5enrldUVKRt2j/99vLyclpaWujs7KS4uBiXy5U2DvDHP/6Rl156ib/927+dpqMQ+epoaw+GrmEYGmhgGBqGrnG0tSfXUxMiu45vh5c/DeEmMPzO5cuflmCxgKxevZpPfvKT/OhHP6Kvr4/i4uJcT0kIIYQYYtoCRdu20ZxeAwAopdKuD3f76fcD0DSNSCTC3Xffzb333pvqQyVmL6XAsm1C0QS9kTihaALLtkHlemZCZNn+e5wvvOEBTXMulXLGRUH4r//6L1atWsWuXbu45pprWLt2Lffffz+vvPJKrqcmhBBCpExbhFVVVcWpU6dS10+dOkVFRcWwt7e1tVFRUUFZWRm9vb1YlpX2uIaGBtrb2/nMZz7DtddeS2trK5s2beLIkSPTdUgij1TM9RFN2Fi2AgWWrYgmbMrn+nI9NSGyKxQE3Z0+prudcVEQamtrufXWW/nv//5v9u7dyy233MLx48f55Cc/yfvf//4xPcdoxeF+8YtfcO2111JXV8ctt9xCd3d3tg9DCCHEDDdtgeLq1at58cUX6ejoIBKJ8Oyzz3L55Zenbl+4cCFer5d9+/YB8PTTT3P55ZfjdrtZsWIFzzzzDAA7duzg8ssv57LLLuP555/n6aef5umnn6aiooItW7awZMmS6TokkUeK/R7cLg1d01CArmm4XRrFfk+upyZEdhXVgH1a8S474YyLgmFZFq+++ipPPvkkTz31FL/5zW/wer1ceOGFoz52tOJwfX193HXXXWzZsoX6+nqWLVvGgw8+OJWHI4QQYgZyTdcLVVZW8rnPfY6NGzeSSCTYsGEDtbW13HTTTXz2s59l+fLl3H///dx555309fVxwQUXsHHjRgC++tWv8pWvfIWHH36Y6upq/v3f/326pi0KRCRusqRiLq09UWIJC6/bcLKMcTPXUxMiu5ZvdvYkWnEnk2gnnCWoyzfnemZijD71qU+llpkuX76cSy+9lFtvvZWLLroIwzBGffzg4nBAqjjcbbfdBkAikeCrX/0qlZWVACxbtoydO3dO0dEIUbgag+3UNwRp7gxTXRqgbkWNFK0TYpBpCxQB1q1bx7p169LGHn300dSfzzvvPLZt2zbkcQsXLuTHP/7xiM/9/PPPZ2eSoiBVlwboCsVZWj0vNRaOmZQXSUZRzDCL1zuX++9xlpsW1ThBYnJc5L0jR44QjUZZvXo1l112GatWreK8884b8+MzFYdrbGxMXS8tLeWqq64CIBqNsmXLFmm7IcRpGoPtbHnuAD6Pi7JiL12hOFueO8Cmq86XYFGIftMaKAoxVepW1LDluQMA+D0GkbhFNG5Sd8W5OZ6ZEFNg8XoJDAvYr371K9555x327t3Liy++yMMPP4ymaaxcuZJVq1Zxww03jPj40YrDJfX29nLrrbdy3nnncd1112X9OIQoZPUNQXweFwGvcyqcvKxvCEqgKEQ/KRcqZoTamvlcuXwhzZ0hXg2209wZ4srlC+UveyFEXjrrrLP4+Mc/zne+8x127NjBunXr+PWvf83Xvva1UR87WnE4cLKON9xwA8uWLeNf/uVfsj5/IQpdc2cYvyd9qbffY3CyM5yjGQmRfySjKHImm3sDGoPt7GwIEjdtXLpG3LTZ2RDknKp5EiwKIfJKKBTi5Zdf5re//S0vvvgiR44cYenSpfzN3/wNH/zgB0d9/OrVq3nwwQfp6OjA7/fz7LPPpgWYlmVx880385GPfIRbbrllKg9FiIKV3LKSzCQCROIWVaWBHM5KiPwigaLIiWzvDXhszyHa++K4XRpul46tFO19cR7bc4j7a1ZPwREIIcTEXHrppbhcLv70T/+UG264gQ996ENUV1eP+fGjFYc7efIkBw4cwLIsdu/eDcCFF14omUUhBpEtK0KMTgJFkRPZ3htwpKUXt6Fh6M5qakPTwLA52tKbvUkLIUQWfPvb3+bSSy+luLg4bTwej7Nnz55UIZqRjFQcbvny5bzxxhvZm7AQM1BtzXw2XXU+9Q1BTnaGqSoNUHfFubIKSYhBJFAUOdHcGaas2Js2Npm9AZoGSqWPKQUMre8ghBA5ddttt/Hb3/52yPiJEyf4/Oc/n1bBVAgxdWpr5ktgKMQIJFAUOZHtvQFnV8zl0LudRBMWtlLomoauw7IzSrM1ZSGEmLCtW7fy/e9/H3CqlP75n/85up5eT66np4ezzz47F9MTQgghhpBAUeRE3YoavvXzRt45lSBh2bgNnTl+NxsnuDfg/csqeeNEJ0oplAKFQimN9y+rzPLMhRBi/NavX09PTw+2bfOd73yHj370owQCAz+MaZpGUVERV199dQ5nKYQQQgyQQFHkTv9aUe206xPxelMni8qK6IokiCUsvG6DEr+b15s6ke5hQohc8/l83HzzzQBUV1ezdu1avF7vKI8SQgghckcCRZET9Q1Byub4WbRg4CsYjpkTLmbT3BmmfJ6fipKBX+iVUtIPSQiRd6677jq6u7v5z//8T44ePcoXvvAFfv/737N06VLOOeecXE9PCCGEAEAf/S5CZF+2G91WlwaIxK20MemHJITIR0ePHuUjH/kIP/vZz9i5cyfhcJhnn32WDRs28Morr+R6ekIIIQQggaLIkWwHdnUraojGTcIxE6UU4Zjp9ENaUZOF2QohRPZ84xvfYM2aNezevRu32w3A/fffzzXXXMM3v/nNHM9OCCGEcEigKHKibkUNHb0RDjZ1sv+ddg42ddLRG5lwYJfsh1RS5KGzL0ZJkYdNV50vZa+FEHnntdde4xOf+ETamK7rbNq0iQMHDuRoVkIIIUQ62aMockfTRr4+TtIPSQhRKGKx2JCx9vZ2PB5PDmYjhBBCDCUZRZET9Q1Byop9vHdRKcvPms97F5VSVuyjviGY66kJIcSU+tCHPsS3vvUtQqFQauz48eN8/etf58/+7M9yNzEhhBBiEAkURU5ku5iNEEIUin/8x3+ku7ubSy+9lEgkwvXXX8/VV1+Nx+Phy1/+cq6nJ4QQQgCy9FTkSHVpgK5QnIB34CsoVUqFELPB3LlzeeKJJ9i7dy8HDx7E7XazdOlS3ve+9+V6akIIIUSKBIoiJ+pW1LDlOadog99jEIlbTpXSK87N8cyEEGJ6rF69mtWrV/P2229j23aupyOEEEKkkUBR5ESySml9Q5CTnWGqSgPUXXGuFKMRQsxYe/bs4emnn0bTNDZs2MCKFSu47bbb+M1vfgPAe9/7Xr73ve9RUVGR45kKIYQQEiiKHJIqpUKI2eJnP/sZmzdvZtWqVQQCAW699VY+8IEPcPjwYf7t3/4N27b57ne/y0MPPcRdd92V6+kKIYQQEiiK3GkMtlPfEKS5M0x1aYC6FTUSOAohZqQf/ehH3HnnnXz84x8HYO/evXzqU5/igQce4JprrgGgvLycr3zlKxIoCiGEyAsSKIqcaAy2c9+OV+kKxTBtRbC1l4NNXXz5YxdLsCiEmHHeeecdPvCBD6Sur169GsMwWLp0aWrsPe95Dx0dHbmYnhBCCDGEtMcQOfHw7tdp641i2goA01a09UZ5ePfrOZ6ZEEJkXzweJxBIr+rsdrvxeDyp67quY1nWdE9NCCGEyEgyimLMvvvMfna/1kTctPG4dNZctIjb1i6f0HMFT/Wm/qwBKsO4EEIIIYQQIjckUBRj8t1n9vM/+44BYGiQMO3U9YkEi/2JRDQGLtWgcSGEmGkee+wx/H5/6rplWWzdupV58+YBEA6HczU1IYQQYggJFMWY7H6tCQDDcEI7A7Asxe7XmiYUKCYDw9PjQi3DfYUQotCdccYZ7Ny5M21swYIF7N69O22surp6OqclhBBCDEsCRTEmcdPGOC2K0/szixNRU17M0VN9GceFEGKmef7553M9BSGEEGJcpJiNGBOPSx+yLNRW4HZN7Ct0yzUXMr/Yg0vX0ACXrjG/2MMt11w4+ckKIYQQQgghJkUyimJM1ly0iP/ZdwzLUujawF7CNRctmtDz1dbM5/r3ncO2l47QG0kwx+9mw6ol0hpjEqQvpRBCCCGEyBbJKIoxuW3tclYtLQcNLAVosGpp+YSrnjYG2/nl/hNUlxZxUc18qkuL+OX+EzQG27M78VmiMdjOlucO0BWKU1bspSsUZ8tzB/Lv/fzDl+C//bBVcy7/8KVcz0gIIYQQQmQggaIYk8ZgO229MS5cXMbK95Rz4eIy2npjEw5E6huC+DwuAl4XmqYR8LrweVzUNwSzO/FZoiDezz98CQ7eD3YU0JzLg/dLsCiEEEIIkYckUBRjUt8QxLQVJzpC/PF4Jyc6Qpi2mnAg0twZxm+dgtbfwLu7oPU3+K1TnOyU8vAT0dwZxu8x0sb8HiO/3s9DD+LUudVx6tvqzvVDD+Z0WkIIIYQQYijZoyjG5EhLD209ESwbbKWIJyxC0TjxCVY9rfZ20tV6mIARAc0AK0Kk4zBVFUuzPPPZobo0QFcoTsA78J90JG5RVRrI4axOk8wkpunPLAohhBBCiLwiGUUxJr2RBDFTYdoKW4FpK2KmojcSn9Dz1Xl+QFR5CdsBFBC2A0SVlzrPD7I78VmibkUN0bhJOGailCIcM4nGTepW1OR6agN0H0M7Z6r+cSGEEEIIkU8kUBRj0hNJZBzvHWZ8NLXGr9lU+SQlrl46zXmUuHrZVPkktcavJzHL2au2Zj6brjqfkiIPnX0xSoo8bLrq/Pyqerrs/+FkFG2cgNF2ri/7fzmdlhBCCCGEGEqWnopJOT0/NGZFNdRqB6id89bAmBWHQE0WZjU71dbMz6/A8HR/8m/O5aEHneWmus8JEpPjQgghhBAib0hGUeTG8s2gaU5wqJRzqWnOuJi5FqyCucvAPc+5XLAq1zMSQgghhBAZSEZRjImugZ0hfaifXptkrBavdy733wOhIBTVOEFiclzMPMe3w8ufdn4YMPwQbnKug3zuQgghhBB5RgJFMSYBt0Ff3Mo4PlGN1hXUh79Pc1eYai1AnVVD7WQmOdsd357fgff+e/qDRI9z3fA4meT99+TXPIUQQggBOH206xuCNHeGqS4NULeiJr+3uYiskqWnYkwiw7TBGG58NI3BdrY8d4CuUJyyYi9doThbnjtAY7B9MtOcvZLZunBTerbu+PZcz2xAKAi6O31MdzvjQgghhMgrcq4mJFAUY2JnWnc6wvho6huC+DwuAl4XmqYR8LrweVzUNwQnMctZbHC2TtOcS6Wc8XxRVAP2aVVy7YQzLoQQQoi8IudqQpaezlD5vlSguTNMWbE3bczvMTjZGc7RjApcKOhkEgfLt2zd8s1OltOKO3OzE1LASAghClW+b3cQkybnakIyijNQY7Cdb/3Pa7wWbOfdjhCv9V+fzFKB4fKGE22PUV0aIHLansdI3KKqNDDBZ5zlCiFbt3g9rHwEAovAijiXKx+REwshhCg0hbDdQYzs+HZ45mL4aYlzmeGzk3M1IYHiDPTYnkOc7IrQG0kQjlv0RhKc7Irw2J5DuZ5aSt2KGqJxk3DMRClFOGYSjZvUrajJ9dQKU6G0G1m8Hta+Ctd3OZcSJAohROEphO0O49AYbOfebfu49dEXuHfbvpm/B2+Mgb6cqwkJFGegg02dWGog26cAS8EbTZ25nFaa2pr5bLrqfEqKPHT2xSgp8rDpqvPzanlsQZFsnRBCiOkyUnGyMWSq8km+FmyZ0uB1jIF+3pyrFdh3aiaRPYozULIQ6eAWhwpITKxA6ZSprZkvgWE2LV4vgaEQQoipV1TTn43yDIzZCXCXFFy/3MEFW4DUZX1DMGfnKMng1edxpQWvWQvSxlHXIOfnatKDOackozgDJQNEddqlluG+Y+U2Mj96uHEhhBBCzFDDbXfQtIJbktrcGcbvSe8JneuCLVNebbQQ6hokzbBlzoVGMooz0By/m56I8xeAOm1czFyNLz9F/e8O0Rwpotofou7SZdSuvC7X0xJCCDHTJDM5p1c9fenv8r8C92mqSwN0heKpTCLkvmDLlFcbLaQq5IVQ1X0Gk4ziDHTBopJxjY+FrZyMZDJ/mPzzBNsoiixrfPkptuw5QVfMRZmrl66Yiy17TtD48lO5npoQQoiZKFNxskLKVPXLx4ItU15ttJDqGhTgd2omkUBxBnq9qWtc42PhNpyviq5ruHQNXdfSxkVu1f/uED4tSsAVR9Mh4Irj06LU/y5/Kt0KIYSY4QqlAvcgeVOwZZBpCV4LpQp5AX6nZhJZejoD9UUT6BqpYA7AthV90cQIjxrZ0up5HHq3E9sGWyl0TcPt0lhaPS8bUxaT1BwposzVmzbm1+OcjMzJ0YyEEELMOsMtSc3XIKRfzgu2nCYZvNY3BDnZGaaqNEDdFefm1RynTYF+p2YKCRRnIE3TsGyFbaWvCzX0iRee2XjFuXzr5430RhKYlo3L0Jnjd7PxinMnO12RBdX+EF0xDwE9nhqL2B6q/KEczkoIIcSsIxW4syLfgtecku9Uzsi6wRnI78r8sQ43Pha1NfO5/f/WclHNfBaWFXFR/3X5Syw/1F26jKjyETY9KBvCpoeo8lF36bJcT00IIYQQQhQgySjOQOGENa7xsZJft/JX7crr2IRT9fRkZA5V/hB1ly6UqqdCCCGEEGJCJFCcgYarRCoVSme22pXXUbsy17MQQgghhBAzgSw9FUIIIYQQopAd3w7PXAw/LXEuj2/P9YzEDCAZRSGEEEIIIQrV8e3w8qed9hGGH8JNznWQIjBiUiRQFEIIIYQQhen49lFbJzQG26lvCNLcGaa6NEDdipqZVXNh/z39QaLHuW54nH6D+++RQFFMiiw9FWIsZEmHEEIIkV+SmbRwU3ombdD/oxuD7Wx57gBdoThlxV66QnG2PHeAxmB7DieeZaEg6O70Md3tjIvsmmXngxIozlgqwz9iQsbwPyIhhJhOO3fuZO3atVx99dU8/vjjw97vS1/6Etu3y99VYoYanEnTNOdSKWe8X31DEJ/HRcDrQtM0Al4XPo+L+obgiE/dGGzn3m37uPXRF7h32778DiyLasBOpI/ZCWdcZM8sPB+UQHFGGi4olGBxQsbwPyIhhJguLS0tPPDAA2zdupUdO3bwxBNP8NZbbw25z80338zu3btzNEshpsEYMmnNnWH8HiPtLn6PwcnO8JCnSwaHf/vd57n7pw00tYcKIwu5fLNzfmLFnfMTK+5cX7451zObWWbh+aDsURRiNKEgjaHzqO/4EM2JCqrdrdSVPU+teiPXMxNCzEJ79+5l1apVlJSUALBmzRp27drFbbfdlrrPzp07ufLKK1P3EWJGKqrpz+54BsZOy6RVlwboCsUJeAdOeSNxi6rSQNpTJZeo+jwuInEL24bW7gg+t8HcgPP89Q3B/NzbmNyHOMpeTTFJoaCTSQQwI2D2gbIg3ulkFWfg+y2BYp6Y8RutC1hjfAX/euJGuu0SLAyC8bM4EFnKV2oepzbXkxNCzDqtra2Ul5enrldUVNDY2Jh2n7//+78HYN++fdM6NyGm1fLNztI/K+5kEu3EkExa3Yoatjx3AHAyiZG4RTRuUnfFuWlPNXiJasy0cbs0bBtauiPMDXiGzULmjcXrZ2SgkleSP0woCxLd/YMK0GdslVlZepoHZsVG6wL2UNMGOuz52GjoWNhodNjzeahpQ66nJoSYhWzbRtO01HWlVNp1IWaNxeth5SMQWARWxLlc+UjayXptzXw2XXU+JUUeOvtilBR52HTV+UN+jB+8RNXrNrCVwtA1YgkLyJyFFLNMcomv2TtoUAfP3Bm7BFUyinlg8K9YQOoyb5c4zDLH4lUAKAxsQOu/lhwXQojpVFVVRUNDQ+r6qVOnqKioyOGMhMihMWTSamvmj3o+NXiJauU8H8faQljKxuvWCcfMjFlIMcskv2cvXA8o0FzgngOGzwkUZ2CVWcko5oHxbLQei2JP5vh/uHExMhsDhY5CAzQUGgodG2PUxwohRLatXr2aF198kY6ODiKRCM8++yyXX355rqclREGrW1FDNG4SjpnM9XuonOtD1yDgdQ+bhRSz0OL1ULIcPPPBV+4EiTBjq8xK5JAHqksDNLWH6A7HiSYsfG6DeQEPi+YXTewJdUjmvQbT5GeBCdFQ/UHi0HEhhJhulZWVfO5zn2Pjxo0kEgk2bNhAbW0tN910E5/97GdZvnx5rqcoRMFJLlGtbwhysjPMogXF3HLNhRIciqHGsDd2ppBAMQ9csKiUl95swbYVtoJY3KQ3EmfNRYsm9HyhqJVxvG+YcTEygwQ2HtKDb4VBYriHCCHElFq3bh3r1q1LG3v00UeH3O9f//Vfp2tKQhS8sSxRFWI2VZmVQDEP/PZQC7ZygkQF2ApQit8eauG6VUvG/XzSRTG7PFoCW2lYuHGCRSdI9GoSKAohhBAiC45vnxWBx4wxS6rMTutixJ07d7J27VquvvpqHn/88SG3Hzx4kPXr17NmzRruuOMOTNME4N133+XGG2/kmmuu4TOf+QyhUAiAt99+mxtvvJFrr72Wv/zLv+TgwYPTeThZc7i5G8seCOQUYNnOuMi9CqMVGxc6FgaJ/sqnLsqN1lxPTQghhBCF7vh2ZyljuMnp0xducq4f357rmYlZbtoCxZaWFh544AG2bt3Kjh07eOKJJ3jrrbfS7vPFL36RzZs3s3v3bpRSPPnkkwDcfffd3HDDDezatYsLL7yQhx56CIA777yTm266iaeffprbb7+dL3/5y9N1OFkVTWReEjrcuJhexe44bhLogEJHB9wkKHbHcz01IYQQQhS6/fc4VTMNj7PXzfBkrd1CY7Cde7ft49ZHX+Debfuk9ZoYl2kLFPfu3cuqVasoKSkhEAiwZs0adu3albr9xIkTRKNRLr74YgDWr1/Prl27SCQS/P73v2fNmjVp4wDXX389l112GQDLli2jubl5ug4nr3lcmT/W4cbFyCK2lyXed5hr9ODXosw1eljifYeo7c311IQQQghR6EJBpyjKYLp70u0WpE93jh3fDs9cDD8tcS4LMEM8bZFDa2sr5eXlqesVFRW0tLQMe3t5eTktLS10dnZSXFyMy+VKGwcnaDQMp0XBd77zHT784Q9Px6HkPZ9bH1KjU+sfF+NX7Q/h1m2WBpq4sPhtlgaacOs2Vf5QrqcmhBBCiEJXVONUzhwsC+0WBvfp1jSNgH0KX99r1D/1rYINXArGDFlOPG2Rg23baNpA+KKUSrs+3O2n3w8Ycr/77ruP1157jX/6p3+awiMoHMU+N26XhkvX0DVw6Rpul8Ycn3v0B4sh6i5dRlT5CJselA1h00NU+ai7dFmupyaEEEKIQrd8s7Pk1Io7S06teFbaLaT16Y40Q9d+/KqLk2ZVwQYuBWMKlxNPp2kLFKuqqjh16lTq+qlTp6ioqBj29ra2NioqKigrK6O3txfLsoY8zjRNvvCFL7B//34ee+wx5syZM01Hk9/OqZpHWZHXCbRxAuuyIi9LqublemoFqXbldWy6uJsSo5PORIASo5NNF3dTu/K6XE9NCCGEyAuyF24SFq+HlY9AYBFYEedy5SOTrqpZXRogEu+vd9F7GFBEVIAqT1vBBi4FY4qWE0+3aWuPsXr1ah588EE6Ojrw+/08++yzfO1rX0vdvnDhQrxeL/v27eOSSy7h6aef5vLLL8ftdrNixQqeeeYZ1q1bx44dO7j88ssBuO++++jr6+MHP/gBHo9nug5limRqXjG0yftYXLColJcPt+I2dAIeg4Sl6AzFuWBR6eSmOFsd305tz7eoXawGGqv2aHD8vbOiNLIQQggxkuReOJ/HlbYXbtNV5+ddX8LGYDv1DUGaO8NUlwaoW1GTH3OcgnYLdStq2PLcAQD8iTARVURUeakre9q5QwEGLgWjqKZ/2emg+CQLy4mn27RlFCsrK/nc5z7Hxo0b+djHPsZHP/pRamtruemmm9i/fz8A999/P9/4xje45pprCIfDbNy4EYCvfvWrPPnkk6xdu5aGhgZuv/12Ojo6ePzxxzl69CjXX3891157Lddee+10HU6WZbfz4etNnZxRVoTPY2DaCp/H4IyyIl5v6pz4FGezGbJ8QAghhJiokTKGQ/bCeV34PC7qG4K5m3AGs624S23NfDZddT4lRR46qaDE1c2mqiepLT7s3KEAA5eCMUXLiafbtGUUAdatW8e6devSxh599NHUn8877zy2bds25HELFy7kxz/+8ZDxAwcOZH+SM0BzZ5jyuT4q5vlTY0opTnaGczirzPL2l73BQkFnI/Jg8iucEEKIWWK0jGFzZ5iy4vRK4H6PkXfnHYMDWiB1Wd8QzL9zjyyprZnvHNvxd+DlO52gRfWvjirAwKVgJLPD++9xzheLapz3usBWok1roCimR3VpgK5QPPUXIEAkblFVGsjhrIZqDLZz345X6QrFMG1FsLWXg01dfPm3Q+ZBAAAgAElEQVRjF+fXX9gzZPmAEEIIMRGjBViFct5RKAHtlJghgUtBmYLlxNNN+iXMQHUraojGTcIxE6UU4ZhJNG5St6Im11NL8/Du12nrDWPaNqAwbZu23jAP734911NLN0OWDwghhBATkVY9s9/gACvTeUdHb4SuUDzrxW0mUzQnrbhLv3wMaKfM4vWw9lW4vsu5LPAgRkw9CRRnoLQ16X0xSoo8ebmh/EhrF0ML9mj943lkiqqRCSGEEIVgtADr9PMOUM4PqpDVvYCT2mN4fDt15teItjQQbv4dKtyctz+kC5EvZOlpXtDIZtVTGLQmPa8N9ztFHv5+MQOWDwghhBATkVY902MQiVtOgHXFuan7DD7vuHfbPkDL+l7ACe8x7G9+XutSbKrqoL7jg5xsh6pKqLvq/QVwviREbkigmDcmHhQKIYQQQkyVZMawviHIyc4wVaUB6q44d9gAa6r2Ak74eQdVL6+d8xa1c95ytpEEFkHNq5OaU6EoiOKBIu9IoChySJE5QJ5YWxAhhBBCTI3xrFSaquI2E37eWV69vJD6XIr8IoHiBD310hG2vXSEnkiCuX43G1Yt4bpVS3I9rQIzXBZVsqtCCCFEPhspQzWWpaoTMeHnneXVy2djWxCRHXm4GSz/PfXSEbb84iBtvTHipk1bb4wtvzjIUy8dyfXUhBBCCCGm1GhFZaaqqN6En3eWVy8frWqtEMORjOIE/PDXh7BPWx1pK2dcsopCCCGEmMnGkqGaqqJ6E3reWd5DsFD6XIr8I4HiBMQS9rjGhRBCCCFmgsZgO3842oZlK/weF5Xz/MwNePI/QzWLq5dP1VJgMfPJ0lORQ8MVrZFiNkIIIUS+SS451TUNl66RMG2OtfXRE45Pb4bq+HZ45mL4aYlzeXz79LxugSqU/trjIt+BaSEZRZEzOjY2RsZxIYQQQuSX5JLTM8oCHGsLYegKTcGJjhCV8/zTk6Hq74notLvwO0VqXv60c9sszRgONlyRocLorz1G8h2YNpJRFDnj0eKAjYYCVP+l3T8uhBBCiHySLIoyL+DlzAVFuAwDWylsW01fhmpQT0Q0zblUyhk/TWOwnXu37ePWR1/g3m37UsV2Ct4w2bTRigzNGOP4DojJkYxiHqgu8dPcFck4Phn53sJjqfcIh6LvwcbARkNHoWOx1CvVY4UQQojpMJ5G7IOLoswLeJkX8BKOmZQUeaYvWzXGnohj6R1YkE3oR8im1TecNTvaYMzyvpjTSTKKE1AxxzOu8dH8w7qLmBdwp43NC7j5h3UXTej5wAkSf/irQ4RjFn63QThm8cNfHcqrFh4bzz1KuauNgB7CR5SAHqLc1cbGc4/mempCCCHE1MijvVXjzUDVraghGjcJx0yUUoRjplMUZUXNtMz13m37uPXYv3HvsU009i0duDFDT8TBlVk1TSPgdeHzuKhvCKaeryCzbyNk02ZNG4yiGuczH2wW9cWcThIoTsAXP/Z/xjU+mtqa+dz555dw2XurWFo1l8veW8Wdf37JpH792fbSEWKmTThu0h1JEI6bxEybbXkUKNa6X+L2qke4yL+fhZ5mLvLv5/aqR6h1v5TrqQkhhBDZl8wGhZvSs0E5ChZHC6ZOl6uiKGlBXWkVXeZctpy8nsbe9wzbE3G0oGm8x543QkEnezZYfzatujRAJG6l3TQj22DM8r6Y00mWnk7AN+tfJVNlzm/Wv8p/fvbKCT1ntjcZt/XGyDRHZzxPhILUzvNTW/LYwJhSEBq6DFcIIYQoeIOzQeBcWnFnPAdFOJo7w5QVe9PGRstA5aIoSnrfxmoCGtB1jPr2K6hd0JOxJ+JovQMncux5oaim/4eGQavY+rNpdefPkjYYs7wv5nSSjOIEnOzOHMgMN54bBdB6QpYOCCGEmE1GyAblQqFkoIZkB/3V+KtWcrL4alj7asYAYbRlsoVy7EOMkE2bkW0whrN4vfPZX9817HdATJ4EiiJ3ZOmAEEKI2STPfiDN5Z7D8RgS1EWaiZx8maq+Z4fd5zla0FQoxz7E4vWw8hEILAIr4lyufCQVKNXWzOfODZfw3Zsu484Nk9vGJIQsPRW5I0sHhBBCzCbLNzt7Eq24k0m0E6BpNC74KvXb9k179c1kMFXfEORkZ5iq0gB1V5ybd8FF3YpBSyqtU0Q6DhNVXuoq94zYQ2+4ZbLJaqfhuElnKIbXpbOkal7GY5/Oyqhjfq3F6+VcSUwLCRRFbslfdkIIIWaLDD+QNi74KlteW4DPEx+2jcNUKoRG7GkB7TvNVLl6qJv/a2qL3wLGt89zcNuMhWVFA/v4MgRlY2mxkS3T+VpCjJUEikIIIYQQ0+W0H0jrt+3D54nP/N53k5QKaH96pVMxVtMGbhzHPs/0wjgjv9/jue9kTedrFZKC7HU5g8gexQnRxjkuhBBCCDHUTO99l+p/+OgL3Ltt3+T7FE5yn+d43u/p/Gxm+vdgInLS6zKP+pzmA8koTpgEhUIIIYSYnNHaOBSyKVlOOcw+z7EWwhv2/fZ2OoHBoJoJ1aVnTdtnM53fg6xk6Y5vH1hC7Sl1ihImurJab2Las6zJPqdKpfc5hVm7TUoCRSGEEEIIcrPMLa1QyyR630313Mf6/IPv1xWKMcfnzu6J/iQL4WV8v0Nt1BXf19+fcCBAqDtzC1teW5B+3ynqS5it78FoGoPtfOvnjfRGEiQScVpPvcuRt17h9pqfU/v+jWN7HwcHVGgQescZd83NanA17b0uk31OsSHWBsoCdHjl8xIoCiGEEELMVrkqJpKNyqPDzf3K5Qt5valz0sHjSO8NkAoM/R6Djr4YZcU+XLpGR1+M9r4Yp3qjLJpfxLyAd9gT/XEFupMohJfx/fZ+n1rXoYEm9oZTIKe27W42XfXLaakKO10VaB/b8yYdvTFcmolX9WApnQ6zlMeaPsD9Yw3wkgGV4YHoqYFxKwTu8nEVFxrJtGfbQ0FAg0QPTt9xDbCcQPj49lkZLEqgKIQQQohZLx+KiahhxkcLojLNvS8S5ycvHObsirmTDnyHe28e2/Mm0biZCiDfONFFwrQxNI22vhi6pmHZimjc4lhbiDMXgNswhpzoT2WQPtx7l/a8P/016P70B/YXyMlqVdjByzUzZEKnowLt0dYeDF3DsEIAGJqNUhZHY2c6wd9YArxQ0Mm8Qn/WTQNU/58ZV3GhkUxXljWlqAa6/shAkIhzqelZCXwLkRSzmQDXMO/acONCCCGEyG/jLSaSrSItoxXsGEtBj0xz7wrHsSxFwOtC0zQCXhc+j4v6huC45zjce3O0tScVQGqahmkrDF2juSuCoYPPY6BpYCuFocG7HeGMTe0HB6KTnetgT710hLufbOD3b52ivTdKU1tf5mIokyyQMybJ5ZqnLW+d7mIpSvUXjE0GdYCm9f9EMdYAb/D7pRmkfuLQ+r8jWXrvklnWkiIPnX0xSoo8U5vhX74ZsPuvKFLHZRRnJfAtRJJRnIC/v/K9fO+5gxnHhRBCCFF4xrPMLZsZsOGzdYcoafDyypE2DF1jYVkRmubKmOkcbu5+j0FPOE5Ld4RowsLr0unoc4/vjRnh+ZUiLYD0ug1M08KybXTNQNM1Z8xSWLZC18n4Hk3FXrTGYDs/eeEwtgKvW8e0bVp6olTO9aUC0FSm0XsPddxHbeAQjeHzqe/4IM2Jcqorz6Qu2J6dwGTwck1ILW+d7kzVkso5HG7uAdzoKoGNTkK5WOp7Z+wB3vLN8OLfOMVrBgWcGEXOMY2juNBoprXP5+L1EDgTIk2gbCfwdRU7l4FF0zOHPCM5sAm4btUSbr7qvSyY48Xr0lkwx8vNV72X61YtyfXUhBBCCDGKTNnAuhU1ROMm4ZiJUopwzMyY/YLsZsCaO8MkTIs3m7vZf6yDN5u76eqL8ua73XSF4iilsG3FsbY+esJxYGgQlWnuLl3D5zY41tZHwrTxGDqxhE13KDbu7Odw782SyjlE4gOBQuU8HwlLoWsatq2w+v/8nqq5nFM1jz85e0HGk/7q0kDa88Dk96LVNwQxLYXHpaNpGoauY+hOpvXIye70LK0qZ0vfV3iqZwNbTl5PlyqnbP6Zzni22jGEgk7GbrAsLdEcj41XLGN+sQfN5SOBGw3FfFcXG8u3jz/AS62V1p1/7LgTUK18ZNLBb9bbqozVJf/uVHH1lIF3gRMkZjHwLTSSUZyg61YtkcBQCCGEKDAjZQPHWkwkWxmwxmA7rd1heiMmhq7hceuYlsWJzhhet0HA68LrcWFaFpaleOtkD26XjkvXOKt8Tup5MhVC+cTlS/nJC4dRCnQDLGWDBuX9GbXBxzXaHsjhCq0AaXvI3IZBkdcgHIe+qHNMZ5QGcBn6iHvLpmIvWnK5rGkpDMPZb6ZrGpG4haFrlM05PYu7gG2dG6iuLBoY73+urOxTLarpX3bqGRjL9vLWMaitmc/tH73I+Sxb36XKep26OTuoLY/C8jEGePvvAd0D/uKBMas/SFz76qTnmKvCUsCkq+rONBIozliDN+KePi6EEELMTiMVrblzwyVjOhHNRjXG5Mmw2b8lylbOc2j9f46bNt3hGJXzfBxt7SWWcO5oWjaaBu929NE4aFlkpiV69Q1BInGLmGnjdRssLPMx1+9JC2gHn5S7dI3Xgu28fLiVc8+Yx8YrllFbM5/GYDsP7fojx9pDKKVo6Y5wwaJSrlu1JC2A9HkMfB4XZ5QVkzAt3u0M09IdYV6Rd8ST/Kmo+FldGsCyFa3dEbDA0DUSpsLVvxw2057L3kiCJZVT1PR+kv0fYZyVYUconDPwXbkEWAd8ZXzHMriYTVIWs6M5Lyw1iaq6M40EijPU+3x7eTH6/ozjzl8KQgghxOyTzAZOZu9eNjJgyZNhgIDXIJqwse2Bn3MtW3G4uYeFpYG0n30NXcPt0gjFLB7bc4j7a1YP+xrnVM0bEtCGY2ZaQJuch2nZHG8PoWsaHpfOO6f6Ui02fvri23T0xZ0iKEBvJMH3n38DcFZYJU/e7922D3CW4uJ1Ma/ISzhmUlLkGfUEP3l7MhBKLuOdaGCQ/Iwq5vnpCsWIxi0MQ+MTly3l9abOjIH+HL+bSNyadDuGZED39slu4v1B+pLKs6g7cwu1bXePnKkaJsAb+GFB0RWK0dQe4g9H2/jEZUuHrnCb6sbxU5wdnfb+iWJYEijOUHdd+Evu+iO8FH0fCh0Nm1W+F7nrwl/mempCCCFEzlSXBmhqD9HaHXGCov69ewkzlpahG0k2MmDJk2Gn2IuFrmkoTWGrVLMBbFvR1BFyeoADukZqv50GHG3pTT1fpmzTWALa5s4wsbhJU0c4tRbJbWi4XE52cNtLR+gOOxUulRpYr2Taim0vHXGClP7gpvnIp3DpBm+ymJjtwes2qJzrG9MJfraXGw7+jFy65nxG/Rm4c/pfqy8SpyscJxK3cOkaH7zwDN440TXi+5Vp3oPf9wsWlfLL/ScwLZuucByURjhm0uQKsaVzAZuu+uXIWcBhArz6hrMw+zOkuubsP42bNj/5zWHOqZqX/pxTXThntOzoKG1ARuP3uHjjRBemrfC5DSrn+XEZ+tT1TxTDkkBxgjY99CveaR/4i++s+QG23PLBHM7oNB95mbtYCZ3/OjBW+qfwkZdzNychhBAix+pW1HD3TxvGtHdvJJOtxpg8GY4mLCzbKViTzCYmgzGntYQzpuHssbOVIhK3nGDOcGoSDhdkXbl8IT6Pi6OtPaDg7Mo5QwIvy7JTQWLyteOWjW6F8be9THd4OSYuBm9nUf3/6g4n0oIbvx7jcLQGtxYCXaM3YdHVF2WO0Ufjj1ZRWxEdNmiYiuWGw31GtcYerjSe5SetH8RSLlwuL7Zy8+xrTZzRH4x09sVG/QEg0/v+k98cpnyen65IwulXqOtYlqI7HGdhWdHIxzNCgNfc+SBdIac3ZXLPpdvlBKH37fgDJUXegeWoY1wa+tRLR9j20hF6Ignm+t1sGGv9jZH28U0ym9kYbKejN0LctHEbGvGERbC1l7I5XjZOVf9EMSwJFCfACRJDaWPvtIfY9NCv8i5YFEIIIcSA2pr5zO1fYjjc3r0Jn0CPUWOwnXc7+uiLpmfqknRA052g0NCdCqJoAwFkcg/j0uoSIHOQ1ReJ85MXDnN2xVzOX1Sayo6drr0vBgxkMZP/TuDilLkAKxUgDq19oGnA/nt46tSVbOtYS7tVgkLDUjqWbfff3ca0dbac+iSbtK3UZggaGoPtvHKkDaUUXo+Lynk+5gW8k19umCmzBTT+6ptsa7kZUxm4tQQJE9xuMFxu2vtiuAydK5cv5PWmTh557sCw+wEzve+mrejq6SEWj+ImDrqB4SoilnA7x9P6LjzzqczZthECvGQm3Oce2EMZNy1sG0JRkyWVcweysHP+jFrtf0dcGvrUS0f44a8OYeg6frdBOGbxw18dAhh7sJgp8JtkNrO+IUjZHD9zAh5auqPEEhZul05ZsXdq9yce3w77/gHCx53rRWfC//nmrN+rKIHiBJweJI42LoQQQoj8cfrevZ5wnDdOdGHZipu/t4emjhBuw5jYCfQYPLbnEKGYha5rmFZ6kTlneSmAQgMs26ZYC5PAwLINLFwYuoamabx/WSX3btvH7w63UuR1UVniZ17A2dvVFY5jWWrUDF2kP3hMn4WNjcEpcz4uEsRJL/CSohTffesynu35MwxMtFSQ6UFD4cLEo8VQmo5Pj1HfdTW1RYfSgoZkVs4JiMG0LI61hThzAbgNY9wFggZ6I3ZSxzepDaQ3uG+MXMSWlo/TZwXwajFCdgAbHcMM48IioQxM8xA/+WUzZy/wUTa3athlsBn30hkJorEYPj2KqVwYysKKh/B6i4j0nKQqvq9/f1+GbNsIe//qzq/hD0fbnEyby/kRIWYq3IaGf1CbFoD6+N9R6/7tiIVztr10BEPX8bidrLRH14gnGFhOPFGTLHSTfE8Dmiv1XVZK0dn/g8aUOL4dfnsj2NGBsVDQ6RUJszpYlEBRCCGEEHkl0347YOwVH0eR3LvXF03Q3Bki2l9R1OfSeafNqezpcTtZvUwn0OOqPpnh2A40OUFpJrYCFLh1DUO3iVs25e42vHqCpnglEduPrQy8LoOd/dmXIq+LWMJOBVjzAl4icStjZc8jJ7u5d9u+/vYRLkxLZaiHrgM2MdvTn1G0+sfSM4qmrdjZvQYNiwAJNBR2f4tuhYZXi6IBLj2OX49yMr5gSNCQzMotLCviWFsfmtIwNMW7HWHm+N2A4tZHXxj2fR5cOKYnkqB8rh/LsnnxpM3/8hXmaD3cUPoE15X9f2D4qW/9U3xaHL8RxbQNbHQUirDtQ0NhYHEqMR9T0wiEXgXPxQT81am5Dn79TNVvS2jhlDaXEqOXFnMBlu18BgtoJtqnqFvwi+GzbSPs/atdPJ9PXLaUn/zmMLGEjd9j4NJsDF2jct5AYOb3GJzsK4UPPjLiPsGeSAK/O/374TY0eiOJId+GcZlkoZtsVBQet1c+nx4kJpmh7O3rLFASKAohhBAib2Ta9/WtnzeCUpTN8Wet0MmVyxfyo18fSgWJGs7evGQxmXjCxt2/B9BtaHSHE9y7bR9HWnpo742iaRoa0Nod4cjJbm7/6EXDBjGDC53sbAgOGyQOlrAVCpMKow2XrojZHmwMvFoMJ2ibQ3tfnDlGH1U0ccxcgEKnpT2O21gAKGIJm/3HOlIFQaJxk+5Igqb2EF2hGF2h+LBNszzECRgxeqwiNIyM90sehkInQgD7tHv12UW4SXCO9zgR20eVpy0VNCTfm2Q2tKokwJkLip1KtHETWylnCSPasJ/54EqgLd0RLBv6oskCPy5A0auK+WHnXwOK60r/h+ZEJWWuHirdBsdiZ/TP2eg/DoWLBCGK8aoob0bOJhaJ4w10ZyzKk6lYkEtF+OCcP/Ji6BIStgtNU8zR+1hkHOMC/yHqu67ikdZyqj1t1JU9T23RmwOB8yg9/K5btYRzqualiigZeow5fg8KxZvN3cQSVn+PzeJhl4Ym33fLVvRFE/i9rtRe14Sl+oPzEYxWqGaSbUCmoqfmqIbNdtpZa/lRqCRQFEIIIUTeyLTv651TTpZj0YLsFTp5vakTTUsv0KLUwJ9N207dFk1Y2ErRFYrTHYoTSzi9DH1uA4WivS8+pFVFpoD3R78+hG07y0tHixU1wKWZGDqc5zvM7q7LSeDChUm1q5k25cOtQUtnD+f6OzjTm+BkbD7hmA7RU7gND30xE6WclhidfbH+JatwtLV35BfHWT5qKqv//cjUl3nwTMFO28s4wMJFzHJh6S7qSn4Gmkbjgq+m3puBbGgfZy4oZmn1PMIxk+bOEB6XQVNHiFjCwus2KPG70z7z+oYgpq14tyOEZZORwkCpOFs7/4rXYxfQnKjiWHwhCbyo/uxnko6NiQcFxPDhVhZuLY5pWQRP9bG0NA7PXJwKkmqXb+bK5Rez7aUj9EYSzPG7eV9xM2+E3kO15xRLfE6AHLU9XDDvFL/s/DA+1UOZq5sucw5bTv4Fmyq2Uls+aOvSKD38BhfoaQy2863/eY3mzjhuQ0MHEqZNR1/mCr6Dv5NnlPhp6ggTipr9mWcNy7bZsGrp8B/1WArVTLJh/VT01JyULLX8KFQSKAohhBAibzR3hnHpGoc7QkQTFj63QTiWQAH7jrRiObELLkNjrt8z4nON5O2T3UQT1rC3KwXxhAVoJCybirk+Al4XkYSztxAUMdNCtzQsW3GgqSt1ct4YbOe+HX+gOxwHNAzd2UeWzF6OhQLK3d00x8vY2fXh1HgCFyfMRRjEiOHCZi6Ho2dTrPcRtT2YGLzeCjbWkOczx5DJTJa1sdHptf2QCqYGyt2M/njQsNHQsdE4Fl/E+f43wVsOKz9P/e/OxOdxlhdWlvg51ua0ADnZFcZl6KmMYktPBEPXQCl6w3Gnf2BHHzd/bw+tPVEicRNN01BDjksNmovCxE2v8tEUP4O4Mkhw2h66fnZqL6aderiGAiuBpoC+N9P2Fzb+6pv8su8rVJcuYEmlk/36VfNqilUL7aqEqO3Bp8eYp3exre0qqouiBKInwIYAMfrsCu5792ZKQiX4/3MvoBGJm0OW2Q7OTCeDuuT9vG4XHpeJZSunHck8P9GENbQSas18vln/Ki3d0VRZIr9HJ24qogmLsmIvG1Zl6Mk42FgL1ST//MrnoWs/vHA9BBbDJf8+YpZz8FLuOzdcMvw8sun49pFvH2MmdKaSQFEIIYQQecPvcfFWczcuw+kV2BWKZ8y+JSxFe1+Mm7+3h1uuuXDUjMPpJ6N9URMdUMNk93RNc9pQuHSUgphp09wRGrpsVO+vFapUqiXFL/efoDsc77+vImE5FSrH63i8MsOojgVYgwrMdJt+OpiLBvi0KBHlS3vE6SHe6CFfMjs4eA/bWILEwffWUTjLc70eL5R/gC29q9hknc/BplfpCsWwlMLQNHTNCWKjCSgtSlDkc9EdTjjVXk975YQFR0/1oWsDvSZHpmFjYGBxPLEQE+8o9wfQ8RDFrZnElBev1cVCTydR25cWJNV3fBifeodAWRXgZLrjSqfVrKBI78OjxUkoFy1mJQmls8R4GzQDlE23WUxLohyle1ngLeVwcw8acFZ5cdoy27cPvsBP/pDAtAGlEcMHaLgNjaMtPVgKDA0WzS+mqjTAyc4wx9v7UAosW2FZNlueO8CCOV5Odg/sw1NAOG5TXuyhpNjHd2+6bPS3ZayFao5vdwrBmH2kquWGj2UsDpPt/pnj9srnh7/NWz6r9yeCBIpCCCGEyCsqtfQzlrBGXaIZbOtLnVgCaZmXUNSktcfpyRY3B7J5R1p7U+tMMz3/WQuK8XsM3m7pwec2sGyb7nCczlB8yFwHljwqDp/s4vDJbnSs/uzUwJLNMSXzJsjCg7NA1MarJ4hY6Sfzw+Xbhsp0y0jLTkenAF0fqMj58O7Xae+Npl7J7P8cDB08LoMTHSHOKCtCU6fveExnq/HMS8NCZzynvTE8LHEfY647CsombLoo96QXPGlOVFCmd6SNWZbCRiNkF2Fodv+eUuezidgeAkYCDA8tcadAjqFivN3SS8JyFu++2dxNkdeNZSv++b9eJGZqaHhwAt5kdlcRT/3uoLAUHGvrJtp9jDazFKWcLLZp27T0RKmc6+Olt05lPM62vjjnLS4b25sy1kI1++8BM7mfc2DOWOEh2cep6J85LqFjw9+28ntT//p5TgJFIYQQosDs3LmThx9+GNM0+eu//mtuvPHGtNsPHjzIHXfcQSgUYsWKFdx99924XNPzv/xk5u5ISw+xhIXHpXNO1bwxVwbt6Ivh0qEvNpCBGykDppSTjXpszyGicQufx4VL1zj0bjeJZNPu01pQDM5COU3sB4LIgB6jymexv9WLZSsS/WtdhwZ6pw8MCgpTmbihvQfHbryRpZM567LmZvn1JhPhOsffFzX5w9E2iryuYQvoWLbTCsSFTXdHE5ryoeMaFBxlfu6xG+55hntunWBsMWepJty6IqoM6kp20ti3lPqOD9EcX0CXORfL5aWi/1E94TjOV80JDC2lEVY+3FqCOXoPUeXjVLSMdmsBif7g3vnBwk69qlLQF0v0v+3K2WOZujXTPJN/0mlJlAI2hqbjdRsYulO9tiscT+2/zfQMyarCoxproZpQkIFKuYNfbGhxmIwtRibbP3PchvkbZpZnE2F8/9UIIYQQIsdaWlp44IEH2Lp1Kzt27OCJJ57grbfeSrvPF7/4RTZv3szu3btRSvHkk09Oy9ySy8ia2kN09sUIxyy6wnGa+rN+jcH2UR/fHYpjK2c5oqGPLRDoCsU42tKbyky09EQxTScjdXqQeDodGy+R/t10NrpKEG4/TCSRwFaKSNxKLSGdXNA0nSaXBcwu532LmxadI1RZBYibNmFT0WHOJYFnhCAx82tk7zPSMEjg1uI0JaopcXWz6YydoME97/VXm00AACAASURBVHya/+35E96KnkWbWcLRaBW/P9zK7w63cvBEJ/R/jyyM/vkrdGVxvv8QC7QWTlrV/UGi8zqZTsWVcuIvlRbAnP6ZDnecGoaK43Y5P1Ykl1APf6SMPXO3eD0seD/EOyB60rlc8P6hAVVRDc6y5dPmqOlDso/VpYEh85vydhiDBRaT8b0MnDU9r5/nJFAUQgghCsjevXtZtWoVJSUlBAIB1qxZw65du1K3nzhxgmg0ysUXXwzA+vXr026fSsllZN3heKqZt6FrdEUS+Dwu6huCoz6+fK4PNOcEVyk1YjYxKRRLgEaqb2AommDMZWOURQIvXmIU6WESeChx9YAyh3vAWJ95Eib7Gvka0I69GE52n3O8FIvc73Ke902qXSe5c/FD1F5xC99s+zK9au6gAE7DyeSCrqnUmEJDx8KgvxgSbi7wvs7L0Uud4jjjOqrxvR86pvPKlgIFCdPJWg73m8vcwCjtMAb7w5fgRD0Dx66c63/4Uvr9lm8GVzLQs0kdjREYkn2sW1FDNG4SjpkopQjHTKcdxliznJNVevH4xmcZCRSFEEKIAtLa2kp5eXnqekVFBS0tLcPeXl5ennb7VEruDYwmrFQ2UNc0YglrTMvJmjvDlM/zc+aCInweZ8mdoWsY2sgnLJYNZ1fMTWUmhltml0mxEaJIj+B3xTnb9y4r5+zn/2/vzsOiKtsHjn9nhmEVAlQ0QbFcSM2FUlFL3ErcAFlKU1HLBSNyy30rl1Izc2/BNXPLEndLwjdNL03N15+hor5SmJAL5sYm25zfHyMnR9lEljHvz3V51Zwz58x9bnjm5jnnOc+ZVCMC+ROpNJhrB9aUi+4KVfVXSVdsqGqZBM2/hOqBXE413neqQYvxYRT/9L4cdKl3O4HGTpTxwSkaNCjYatM5ldEAw90Jfkzl3YPTFDNVBizQaQxY6IztTquFas52VLDWY6Ez/Sy9TkMj94e4D/DsInKH5f5zNVS5u/we1QOh5Sqwc//nvbY1jMvuu/qY+zgMRztLbqRk4GhnWXYT2QBc2v1wy58wco+iEEII8RgxGAymz/9TFJPXha0vTU872XIzNRNrvY6sbAM6nQaDYpy2vyjDyXK3f8rWiqdsrbiVlsFf19MwKArPuDhw8s/red4Z6GhrSd82ddUHdWu1kPt0iIKuSOp1GnLQoyWL9Bwr7his8HPeCoasQp4dKIqjqA/YKC9acrAgm5qWF0kz2HBHscbvJQ+oHlD4xkrOPcenwU6baryyp2ix16ZwKasqFmSTRdGu4CkYHwGTnXPvcNqCfyeNkyhpcbCxwMne2vgMwqY1+fLH01RzsuXPv1Oxsbx7X65BITPb8HBX7gx38ohBc3f5fQp5HuS97n02ZJlTj+ne41LyPqYnkJwuK5bSuOFbCCGEKFzVqlVJSvpnBsOkpCRcXFzyXX/t2jWT9aUpdxjZU7aW5BgMZGYZyDEoONroizSc7P5haHqd8blw77/WlE/6teT5Gk7YWlkYrzJqNVSwtqCmiz31qzuZXJnQa7XYWlpga6lDq9U8MOxOq9VQvaIttao6YGFpTYZiiZ0uncFVvqGRzSnQaLDUZFPwBCJF6UiWfGfTgiwsNZnoycSadKxJp2T+/nj0WHVkYhqLaVwl+1dSyeZWRw7u+gs46JK5keOEo+4mgz3O0Kj5P51Ei7u/SHkeh0Z3d6ipcSKbLEWPXpNNFYurPGt9gaf1V6iou1akWLQaDfY2FlhbWGBrqcdel46Vmtu8s6jFgIIGnUbD2KBWLB7UmknBL9KoZkWedrJFb6GjRiU7LHQ6snKMJ4/qVnvq4TpoWus8Pl+5u/wx9W88phIkHcViGFI1krx+qYzLhRBCiNLTqlUrDh06xPXr10lPTycqKgpvb291vaurK1ZWVhw7dgyArVu3mqwvTbmdNbeKdjhVsMbWSoeTrSVulSoUaThZYcPQ+rbxwNXJlvpuTrz4bCWecXHAQqtRO6CNalZkUvCLvP96U1ydbalV9SlefLYSDao7U6eqA3NCWjAnpAW1XOxxtLPGwcYSt8qVqO5sxdhnNtHI5jewdYPmX+JTR3vPHWj/1PyWbgZ8X6xxd53m7pMCjf+esrbARm+BXqe9O+NkSTF2PizIwlqbhYf173zkPpet3mvZWvsNfCvsoKjdMA3GR1HkM+CRB6+uFLQvA5ZkYK1Jp6Lub+rbxPGc1f+wJAMtOViRgQVZ9+2/sOgKi6vo8f2j8EluXGwysdDCWJdPWOw+nkntDDTyN308QmfP6iZ7vDc6RWeHhhw0aKhqcYUG1qdx1SdioQW/l5rh93Jz7K3ASXOD/E426DRgo9fxtJMNk4Obqr/HNSta09juDFV1V9CiYEH23adp/pMbBR0ajY4uL7g/0M5yT8DodTrqVHWgVhUHqjxlQ982HkVNoJHHu3c/L7dNGIyvPd59uP2Yk3/jMZUgGXpaDAGDVsLSN/kuqQ3JOfbY65IJrrzPuFwIIYQoRVWqVGHEiBH07duXrKwsgoODadSoEYMGDWLo0KE0bNiQTz75hEmTJpGSkkKDBg3o27dvmcX3qMPICto+tyO57dd4Lt9IMw6ta1P3gfcX9r4H17WiUU1fk32E9wC+2cru/xnIUizQa7LwqaMlvIe/+p7dJxLIyjZgodVQyd4KextLrC0tAIXryXfIyDZgpTc+SDwlPZNLN9LIvPvgxdzHbWgAS72W7GwD/0zQahzEaKXJ5M1KGwiocQ6e7giXooyPF7CraZwUpHogXIwkPGYarn/e4MukN1DQc28HxEJr7GZqNWBjaYG9jSXPVrGngZsTUScSuHAt5e6srvfLf6CoBgUbbQZO2us8a30Bv6d+ANvqbMt8i8spGjz08ZCdxh3Fhqr6q2RrKnAs9XmyDBr0FlqefsqaS7fumDzbUqOBGs62JCVnkHbPLJiWOg2WOi0pd5dpNeDiYENqRiYpGTkoivE+wLwiddCl0st5E1g6892NrtzK0KmPO/mHQiV7W2q7PY1f0/Y0qjk0z2MGCO/SEPjn56630FK7ij1Xb98hOT0LB1srWlrt5WamJZezqlDVJhm/Fm7qVcnBLrmPjknmeko6GVkGdYZTnQasLC14xsWBvnn9ruZoqKM/RXd9FKeyXuCyrgE5OgeuJRv3Y2+jJ7jFswS0ePaBuIvabgrl+bHxv2cXGYdmaq2NHarc5Y+jf+MxlSCNojzMLd//DgkJCXTo0IE9e/bg5uZW3uEIIYQoRfKd/3AkX0II8WQo7Ptehp4KIYQQQgghhDAhHUUhhBBCCCGEECakoyiEEEIIIYQQwoR0FIUQQgghhBBCmJCOohBCCCGEEEIIE9JRFEIIIYQQQghhQjqKQgghhBBCCCFMSEdRCCGEEEIIIYQJ6SgKIYQQQgghhDAhHUUhhBBCCCGEECakoyiEEEIIIYQQwoR0FIUQQgghhBBCmLAo7wDKQ05ODgCXL18u50iEEEKUttzv+tzvflEwqZFCCPFkKKw+PpEdxaSkJAB69+5dzpEIIYQoK0lJSbi7u5d3GGZPaqQQQjxZ8quPGkVRlHKIp1zduXOHkydPUrlyZXQ6XXmHI4QQohTl5OSQlJTE888/j7W1dXmHY/akRgohxJOhsPr4RHYUhRBCCCGEEELkTyazEUIIIYQQQghhQjqKQgghhBBCCCFMSEdRCCGEEEIIIYQJ6SgKIYQQQgghhDAhHUUhhBBCCCGEECakoyiEEEIIIYQQwoR0FIUQQgghhBBCmJCOYgG2b99Oly5d6NixI2vXrn1gfWxsLIGBgfj4+DBx4kSys7MB+Ouvv+jduzedOnXi7bffJjU1FYAjR47g5eWFv78//v7+jB8/3mxizjV//nwWLVqkvr59+zaDBw+mc+fO9O7dm6SkJLOP2ZzzfOzYMYKDg/H396dfv34kJiYC5p3n/GI25zz/+uuvBAYG4uvry5AhQ7h16xZg3nnOL2ZzznOu06dP8/zzz6uvSzvPJR1vWeT4cVHc3CYkJNC7d2/8/f0JCQlRvyfKM9ZcY8aMITIyUn2dX402tzjz++41x1hz3d+2Sktx47x69SqDBw+me/fu9OzZk4SEBLONtazbVGFxRkdH4+/vj5+fH2FhYWqNKuv29CixlnWbKm6cucqqPRVIEXm6fPmy0q5dO+XGjRtKamqq4uvrq/zvf/8zeU/Xrl2V48ePK4qiKOPHj1fWrl2rKIqiDB48WNmxY4eiKIqyePFi5eOPP1YURVGWL1+ufPHFF2YZ8+3bt5Xx48crjRo1UhYuXKi+f+rUqcqXX36pKIqibN68WRk2bJjZx2zOeW7Xrp0SGxurKIqifPvtt8qQIUMURTHvPOcXsznn+ZVXXlHfO2fOHGXu3LmKoph3nvOL2ZzzrCiKkpaWpvTs2VOpW7euuqw081wa8ZZ2jh8Xj5LbUaNGqf+/evVq5b333iv3WC9fvqyEhoYqjRo1UjZt2qQuz69Gm1uc+X33mmOsipJ32zK3OPv166esW7dOURRFWbduXYnXgJKMtSzbVGFxJicnKy+99JJy+fJlRVEUZf78+cr06dMVRSnb9vSosZZlm3qUOBWl7NpTYeSKYj4OHjxIixYtcHR0xNbWFh8fH3744Qd1fWJiInfu3KFJkyYABAYG8sMPP5CVlcXRo0fx8fExWQ4QExPDgQMH1CsGly5dMouYAfbs2UPNmjV58803Tfa5d+9efH19AejWrRs///wzWVlZZh2zueY5MzOTYcOG8dxzzwHg4eGhxmaueS4oZnPNM8CuXbuoXbs2WVlZXLlyBQcHB8B881xQzOacZ4BZs2bRr18/k32WZp5LI97SzvHj4lFyazAYSElJASA9PR1ra+tyjRWMZ/M7dOhA586d1WUF1WhzirOg715zizVXXm3LnOK8fv06Z86coWfPngAEBQUxfPhws4wVyrZNFRZnVlYW77//PlWqVAH++X0s6/b0KLGWdZsqbpy5yqo9FUY6ivm4evUqlStXVl+7uLhw5cqVfNdXrlyZK1eucOPGDSpUqICFhYXJcgB7e3tCQkLYvn07bdq0YcSIEWYRM0D37t0ZPHgwOp0u331aWFhQoUIFrl+/btYxm2ueLS0t8ff3B4wFYPHixbzyyisPbGNOeS4oZnPNM4Ber+fs2bO0adOGw4cP07Vr1we2Mac8FxSzOed5z5493Llzh06dOuW7z5LOc2nEW9o5flw8Sm6HDRvGqlWraN26NStWrGDQoEHlGivAwIEDee2110yWFVSjzSnOgr57zS1WyL9tmVOcFy9epFq1asyaNYugoCCGDh2KXq83y1ihbNtUYXE6OTnx6quvAnDnzh0iIiJ45ZVXyrw9PUqsZd2mihsnlG17Kox0FPNhMBjQaDTqa0VRTF7nt/7+9wHq62nTptGxY0cA3njjDc6fP09ycnK5x/wwFEVBqy25X5vSiNnc85yZmcmoUaPIzs4mNDQ0z88wtzznFbO559nDw4ODBw8SFhaW7x/+5pbnvGI21zwnJSXx+eefM3ny5EI/oyTzXBrxlnaOHxeP8vs7duxYpk2bxv79+5k6dSrh4eEoilJuseanoBpdGh617halXpSU4sb6MN8FJaG4cWZnZ3P69GlatGjBpk2b6NChA+PGjSvNUB/p51+WbaqocSYnJzN48GCee+45AgICyrw9PUqsucqqTRU3zrJuT4WRjmI+qlatajIBQ1JSEi4uLvmuv3btGi4uLjg7O5OcnExOTo7JdgaDgc8//1xdnuv+q2HlEXNBXFxcuHbtGmD8kk1NTcXR0dFsYzb3PKempjJw4ECys7P5/PPP1bOZ5pznvGI25zxnZGQQHR2tLvfz8+Ps2bOA+eY5v5jNOc979+7l5s2b6mQLAP7+/qSkpJRqnks63uTk5FLP8eOiuLm9fv06v//+u3o23MfHh6SkJG7cuFFuseYnvxptbnFC/vWitBQ31oK+C8wpzsqVK2NnZ0e7du0A47D43377rVRizFXcWMu6TRUlzqtXr9KrVy88PDz48MMPgbJvT48SK5RtmypunGXdngojHcV8tGrVikOHDnH9+nXS09OJiorC29tbXe/q6oqVlRXHjh0DYOvWrXh7e6PX62natCm7du0CYMuWLXh7e6PVavnxxx/ZvXu3urxx48bY2tqWe8wFadOmDVu2bAGM91A1bdq0RBtWScds7nkePXo07u7uzJ8/H0tLS3Ubc85zXjGbc54tLCyYOnUqJ0+eBOD777/nhRdeAMw3z/nFbM55fu2114iOjmbr1q1s3bpVXVehQoVSzXNJx2tvb1/qOX5cFDe3Tk5OWFlZ8euvvwLGmQXt7OxwdnYut1jzk1+NNrc4If96UVqKG2tB3wXmFGeNGjWoWrUq+/btA+Cnn36iQYMGpRLjo8Za1m2qsDhzcnIYMmQInTt3ZuLEieqVsbJuT48SK5RtmypunGXdngpVqlPlPOa2bdumdO3aVenYsaMSERGhKIqiDBw4UPntt98URVGU2NhYJSgoSPHx8VFGjhypZGRkKIqiKAkJCUqfPn2Uzp07K2+99ZZy8+ZNRVEU5dy5c0qPHj2ULl26KH369FH++usvs4k518KFC01mEL1x44YSGhqqdOnSRenRo4dy8eJFs4/ZXPN86tQppW7dukqXLl0UPz8/xc/PTxk4cKCiKOab54JiNtc8K4qiHD16VAkICFD8/PyUQYMGKZcuXVIUxXzzXFDM5pzne907M1tp57mk4y2LHD8uipvbEydOKMHBwUq3bt2UHj16KKdOnSr3WHONHTvWZDbJ/Gq0OcVZ0HevucV6v7KYpbG4ccbFxSl9+vRRunbtqvTo0UP5448/zDbWsm5TBcUZFRWleHh4qL+Lfn5+yoQJExRFKfv2VNxYy6NNFTen9yrvWU81ilKKNxEIIYQQQgghhHjsyNBTIYQQQgghhBAmpKMohBBCCCGEEMKEdBSFEEIIIYQQQpiQjqIQQgghhBBCCBPSURRCCCGEEEIIYUI6iuKJ0r59ezw8PNR/zz//PB06dGD27Nnl9jDTknLo0CGGDBlCy5Yt8fT0pHv37qxfv56Sntj4/Pnz7N2795H2MW7cOPr37w/A4cOH8fDw4PLlywBcunSJnTt3Fnvf9/58PTw8aNKkCYGBgfz000+PFLMQQjyuMjMzWb58Od27d8fT05NWrVoxZMgQYmJi1PckJCTg4eGhPrvvSfXDDz/Qt29fmjdvzosvvkjPnj3V5wSWpOPHj6vPJC2ukJAQJk6cCEBkZCT169dX1z1Krc79Xbj3n6enJ7179+b48eOPFLN4vEhHUTxxBg0axIEDBzhw4AC7du3ivffeY+fOnQwcOJDMzMzyDq9Yli9fzsCBA6lbty4rVqxgy5Yt9OrVizlz5vD++++X6GeFhYWZ/HHxqDw9PTlw4AAuLi4ATJgwgf379z/SPqdMmcKBAwfYv38/kZGRtG/fnvDwcM6cOVMSIQshxGMjPT2d3r17s379et566y22bNnCsmXLcHR0pHfv3vzyyy/lHaLZmD59OuPHj6d169asWbOGb7/9lg4dOjB69GgiIiJK9LP69OnDhQsXSmx/Xbp04eeff1Zfl0St/uyzz9RaunHjRmrXrs3AgQO5evXqo4YrHhMW5R2AEGXN1taWypUrq69r1KiBu7s7QUFBbNq0iTfeeKMco3t4p0+fZu7cuUycOJHevXury93d3alQoQIjRowgKCiIxo0bl8jnlfQVSktLS5OfR0nsv0KFCuo+XVxcCA8PZ/v27Wzfvp3nnnvukfcvhBCPi/nz5xMfH8+OHTuoUqWKunzWrFn8/fffTJ8+nR07dpRjhOZhz549rFmzhoiICNq0aaMuf/bZZwFYsGABvr6+PP300yXyeSVdS62trbG2ti7R/T/11FMmtXTSpEls27aN6OhoevXq9cj7F+ZPrigKATRo0IAXX3zRZHjJuXPnGDBgAI0bN8bb25spU6Zw+/ZtdX1qaioTJ06kefPmNG/enNmzZxMSEsKiRYsAWLRoESEhIQwdOpQXXniBefPmARAdHY2fnx8NGzakU6dOLF++HIPBoO730qVL6jatWrVixIgRXLlyJd/Yv/32WxwdHenZs+cD6zp16sSqVauoW7cuAAaDgS+++IJ27drRpEkTgoKC2Ldvn/r+yMhIOnXqxDfffEP79u3x9PSkb9++xMXFAcZhLn/++SeLFy+mffv2gHE47+zZs/Hx8aFFixacOnWKhIQEhg4dipeXFw0aNKB9+/YsW7Ysz/jvHXo6btw4Dh06xObNm/Hw8ODHH3+kfv36JCUlqe9XFIV27drx1Vdf5ZuTvNja2qLRaB5qGyGEeJxlZmYSGRlJcHCwSScx15QpU5g7d26e343Z2dksXbqUjh070rBhQ3x9fU1q5LVr1wgPD8fLy4smTZrQv39/YmNj1fW3bt1i/PjxeHl50bx5cwYNGsTvv/+urh83bhwTJkxgxowZeHl50bJlS0aNGmVyG0hhdXjv3r10796dRo0a8fLLLzN9+nQyMjIASEtLY/z48bRq1YqGDRvy+uuvc+jQoXxz9c0339CgQQOTTmKuXr16sXLlSipWrKjmddasWbz88su88MIL9OnTh//7v/9T379o0SIGDBjAkiVLePnll2nWrBlDhgxRa3n79u3Jyclh/PjxhISEAMbbJhYsWIC3tzfe3t4kJSVx5swZBg0aRNOmTXn++efx8fFhy5YtecZ/79DT+2v1qlWraN68ucmoqdTUVJo0aUJ0dHS+ObmfXq/H0tJSaukTRDqKQtxVt25dzp07B8CVK1cICQmhbt26bN68mYULF3L+/HnCw8PV948bN45ff/2VxYsX89VXX3H69GmOHj1qss8jR45QvXp1Nm/eTHBwMPv27WPUqFH07duXnTt3Mnr0aFavXs1nn30GGAtbSEgIVlZWbNiwgeXLl5OVlUW/fv3yHRZ76tQpGjZsiE6ne2CdVqulZcuW2NjYADB37lwiIyOZNm0aW7duJSAggPDwcA4fPqxuk5CQwPbt21m4cCErVqzgr7/+Yvr06YCx+Lm6uvLWW2/x3XffqdusX7+e6dOn8+WXX1KvXj3efvttMjMzWb16Nbt27cLf3585c+aY/BGRl4kTJ9K0aVM6d+7MgQMHaNu2LQ4ODib3LB49epSkpCR8fX0L3Feu7OxsduzYQVxcHP7+/kXaRggh/g0uXrzI7du38x1RUr169XxHWcyaNYvly5czcuRItm3bRteuXRk5ciS7d+8GYOrUqWRnZ7Nu3ToiIyOxs7Pj3XffBYwn9AYPHszVq1dZtmwZ69ato1q1avTq1YsbN26on7Ft2zZycnJYv349kydPZvfu3axevRoovA5fv36d8PBwevbsyffff8+cOXPYtWsXS5cuBVDfv3z5cnbt2kW9evV45513SEtLy/N4T506RZMmTfJcZ2dnR7NmzbC0tARgzJgxHD16lPnz57Np0yZatGhB3759+eOPP9RtDh8+zNmzZ1m5ciXz5s3j+PHjLFy4EIDvvvsOnU7HhAkT1JPLYDzx++WXX7J48WLs7Ox46623cHFxYePGjWzdupVmzZoxadIkrl27lmecue6v1X5+fqSlpZmcGI6KisLGxibPjnFecu9zBejYsWORthGPPxl6KsRdDg4O6pnMdevW4ebmxtixY9X18+bNw9vbm+PHj1OpUiWioqLUs3S569u1a2eyT41Gw7vvvqsOBxkzZgxvvPEGwcHBgHHYa2pqKpMnTyYsLIydO3eSnp7OrFmz1I7fp59+ipeXF1FRUXTr1u2BuG/dukWNGjUKPb7U1FRWr17NokWLaN26NWAcnnrmzBkiIiLw8vICICsri6lTp1KrVi3AeB/F/PnzAXB0dESn02Fra4uzs7O67/bt26t5uHPnDgEBAXTt2lU9gx0eHs4XX3zB2bNnqVevXr4x2tvbo9frsba2Voe7dOvWjW3btqmT32zduhVvb2+Tz7/fpEmT+OCDDwDIyMggJyeHPn36qMckhBBPgtyrbw4ODg+1XUpKCuvXr2fKlCl06tQJgCFDhqj1wsfHhwsXLuDh4YGbmxtWVlZMmzaN8+fPYzAY+OWXX4iJieHIkSNUqFABMHYsf/nlFzZu3EhoaChgrCmTJk1Cp9Px7LPPsmPHDvXKXGF12MrKiqysLKpWrYqrqyuurq4sW7YMW1tbAC5cuICdnR1ubm7Y29szduxYfHx88jypCsZaam9vX2huLly4wPfff8+OHTuoU6cOYKxxx44dY+XKlUybNg0wdpY/+ugjKlSoQJ06dfDz8+PgwYMAav2yt7fH0dFR3XdAQIBaI//++2/69+9PSEiIerI3NDSUb7/9lvj4eCpVqpRvjHnV6tatW7Nt2zZeffVVwFhLu3Xrhl6vz3c/AwYMQKs1XlO6c+cOBoOBUaNGqVdWxb+fdBSFuCs1NVUtErGxscTGxuLp6fnA++Li4tQbue89++js7EzNmjVN3lu5cmWTewZiY2OJiYlhw4YN6jKDwcCdO3dITEzk9OnTXL9+naZNm5rsJz09XR3+eT8nJydu3bpV6PHFxcWRmZnJsGHD1C9+MHYM7y04Go0Gd3d39bWDgwNZWVkF7rt69erq/1tbW9OnTx927drFb7/9xoULF4iNjcVgMJgMsS2qwMBAvv76a+Li4nBzc2P37t3MnDmzwG1GjBhBhw4dAGNxO3nyJLNmzSInJ0ftQAohxL+dk5MTADdv3nyo7X7//Xeys7N54YUXTJY3a9aM//znP4BxspSxY8cSFRVFs2bN8Pb2pnv37mi1Wk6fPk1OTo56UjJXRkaGSS2rUaOGScfNwcFBHZ5ZWB0OCgqic+fOhIaGUrVqVV566SVeffVV9YTtgAEDCAsLU2cCb926Nf7+/lhZWeWbq6LU0tOnTwPw+uuvmyzPzMw0GflTqVIltZOce2wPU0srVqxIr169nP6YgwAACYVJREFU2LJlC7GxscTHx6sTsuXk5BQa5/0CAwMZOXIkt2/fJj09ncOHDzNmzJgCt5k5cyYNGjQAjCOeDh8+zCeffAIYJwYU/37SURTirlOnTqlfiHq9npdeeolJkyY98D5nZ2d1qGZhN4vf20nM3e/AgQPzHDZZpUoV9Ho9tWvXZvHixQ+sz+9Mp6enJ5s3b8ZgMJh0AMHYCR0yZAiBgYFqJ3bRokUmHUHAZDutVouFhelXQ2HHeW/hTUtLo1evXuTk5ODj44OXlxeNGzd+4GprUdWvX5/nnnuO7du34+HhgU6no23btgVuU7FiRZNj9PDw4OrVqyxYsIBRo0aZFG8hhPi3qlGjBhUrVuTEiRN06dLlgfWHDx82uQqWK3eI5f1ycnLU+tCpUydatWrFvn37OHjwIJ999hmrVq1i48aN6PV6HB0d2bhx4wP7yL3il9/n5NabwuqwRqNh/vz5hIeHs2/fPg4cOMA777zD66+/zgcffEDTpk3V5QcOHGDt2rWsWLGCNWvWULt27Qf26enpyYkTJ/I87pSUFN555x3eeecd9Qrchg0bHqjx9x5PQceWn3tr6dWrV+nRowdVqlShXbt2tG3bFhcXF4KCggrcR37atm2LnZ0du3fv5tatW9SpU8fkcRp5cXFxMaml9erVU4fzSkfxySD3KAoBnDlzhuPHj6tDO2vXrk1cXBzVqlXD3d0dd3d3tFotH330EZcuXcLDwwONRmNSVG7evFnoVNe1a9cmPj5e3ae7uzvnzp1TJ7qpU6cOCQkJODo6qusrVqzIzJkz1fsn7xcQEMDt27dZv379A+t27tzJvn37qFSpEu7u7uj1eq5cuWLy+du3bycyMrLIuSrsJvYjR44QGxvL119/TXh4OD4+PqSlpWEwGIo0C1te+w8ICCA6Opro6Gh8fX0LHCqTn9zPLumZ5oQQwlxptVoCAgLYtGnTA5OiKYpCREQEf/zxh8nM0wA1a9ZEr9c/8Jy/Y8eOUbt2bbKzs5k9ezaJiYn4+voyc+ZMdu7cSWJiIkeOHKFOnTrqVczcWuPm5sb8+fMfuJc/P4XV4ZiYGGbOnEnt2rUZMGAAK1euZMSIEWzevBmAxYsX89///pdXX32VqVOnEhUVhcFgyPeZukFBQZw+fdrkPr5ca9as4ejRo7i6uqrDTf/++2+TWrpq1Sr27NlTpGODwmvpjz/+SGpqKmvXriU0NJT27dur93cWp5bq9Xq6deum1tKAgIAix3ovRVGkjj5BpKMonjhpaWkkJSWRlJTExYsX2bJlC4MGDaJZs2b4+fkBxvvybt++zbhx4zh79iwxMTGMHDmS+Ph4atasSfXq1enYsSPTpk3j6NGjnD17ltGjR5Oenl7gl//bb7/Nzp07iYiIID4+nr179zJlyhSsra2xtLTE19cXJycnhg8fTkxMDOfOneO9997jxIkTanG6X926dQkPD+fDDz9k3rx5nD17lri4OFasWMHkyZPp06cPTZs2xcbGhv79+zN37lx27drFxYsXWb16NUuWLDEZ7lIYOzs74uPj852JNfd+iO3bt5OYmMihQ4cYPnw4QJGeU2lnZ0dCQgKJiYnqMj8/P+Lj44tc3FJSUtSf8ZUrV4iOjuarr76iffv2RboHRQgh/i3CwsJwc3OjV69e7Nixg4sXL3L8+HGGDh3K0aNH+fDDDx+oW9bW1rz55pvMnz+fH374gfj4eCIiIoiKiuLNN9/EwsKCU6dOMWXKFE6cOMHFixf55ptv0Ov1NGjQgJYtW9KkSROGDx/Or7/+yh9//MGkSZP46aef1Fm4C1NYHba3t2ft2rV8+umn/Pnnn8TGxvLTTz/RqFEjABITE5k6dSqHDx8mMTGRbdu2kZycnO/EPm3atCE4OJhhw4axfPly4uLiOHv2LPPmzWPhwoWMGjUKV1dX3N3d6dKlC5MnT2bfvn38+eefzJs3jw0bNjzUffB2dnacP3+ev//+O8/1Tk5OpKSksHv3bhITE9mzZ4/6XOSi1tL7a3VgYCAHDx7k5MmTRZoQ7tatW2otvXTpEpGRkWzfvl39W0n8+8nQU/HEWbp0qTormp2dHa6urvTq1Yv+/fur90pUrlyZlStX8sknn/D6669jbW2Nl5cXCxYsUIeTzJgxg2nTphEaGoqFhQVvvPEGcXFxBV7t8vb25uOPPyYiIoKFCxfi7OxM9+7dGTFiBGAszitXrmTWrFn069cPjUZDkyZN+Oqrrwq8eTwsLIxatWrx9ddfs2HDBjIzM3nmmWeYOHGiyTCV4cOHo9fr+fjjj7l27RrVq1dn2rRpBAYGFjl//fv3Z8aMGRw4cCDPqcYbNWrEmDFjWLp0KXPmzKFatWoEBwfz888/ExMTU+hzKnv37s2oUaPo0qUL0dHRVK5cGWdnZ15++WUSExPV4cEFmTZtmjqUysLCgipVqhAYGEhYWFiRj1MIIf4N7OzsWLNmDUuXLmXx4sVcunQJe3t7GjduzDfffJPvBGO597N/9NFH3Lhxg1q1avHpp5/SuXNnwDiL9kcffURoaCipqanUqVOHJUuWqEMVlyxZwuzZswkLCyMzM5N69eqxbNmyPId95qWwOlyzZk2WLFnCwoULWb16NXq9ntatWzN+/HjAOKnZ7Nmzee+997h58ybu7u7MnDlTnXgtLzNmzKBx48Zs3LiRzz//HDCO9FmwYIE6CUzu++bOncuECRNITk6mVq1aLFq0iJYtWxbp2MB4j99nn33GwYMH83zkRefOnYmJiWHGjBmkpaVRo0YNwsLCiIiIICYmBm9v7wL3f3+t1mq11K9fn5o1a+Lq6lrgZDi57q2Zer0eV1dXQkNDZdjpE0SjyPVjIR5aRkYG+/fvp1WrVur9FllZWXh5eTFlyhS6d+9ezhH++wQGBuLr68ubb75Z3qEIIYQQj53s7Gzatm3LlClT5BEXokjkiqIQxWBpackHH3yAt7c3gwYNwmAwsHLlSvR6faFn+cTDiY6O5sSJE8THxxf7ngohhBDiSZWZmcl//vMf9u/fj6WlZbEnlxNPHrmiKEQxnTp1io8//piTJ09iMBjw9PRk9OjRBT4nUDy8oKAg/vrrLz744AN8fHzKOxwhhBDisWIwGGjdujWWlpbMmTPngUdwCZEf6SgKIYQQQgghhDAhs54KIYQQQgghhDAhHUUhhBBCCCGEECakoyiEEEIIIYQQwoR0FIUQQgghhBBCmJCOohBCCCGEEEIIE9JRFEIIIYQQQghh4v8BeC2sOuIojaoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1080x540 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(style=\"white\")\n",
    "\n",
    "fig,axes = plt.subplots(2,1,figsize = (15,7.5),sharex=True, sharey=True)\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.scatter(metrics[metrics['nominated']==True]['degree_c'],\n",
    "            metrics[metrics['nominated']==True]['pagerank'],c='orange',alpha=0.9, label = 'nominated')\n",
    "plt.scatter(metrics[metrics['nominated']==False]['degree_c'],\n",
    "            metrics[metrics['nominated']==False]['pagerank'],c='steelblue',alpha=0.7, label = 'not mentioned')\n",
    "\n",
    "plt.xlabel('Degree Centrality B',size=15)\n",
    "plt.ylabel('Page Rank B',size = 15)\n",
    "\n",
    "plt.legend(frameon=False, fontsize = 'large')\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.scatter(metrics[metrics['nominated']==True]['closeness_c'],\n",
    "            metrics[metrics['nominated']==True]['betweenness_c'],c='orange',alpha=0.9, label = 'nominated')\n",
    "plt.scatter(metrics[metrics['nominated']==False]['closeness_c'],\n",
    "            metrics[metrics['nominated']==False]['betweenness_c'],c='steelblue',alpha=0.7, label = 'not mentioned')\n",
    "\n",
    "\n",
    "plt.xlabel('Closeness Centrality B',size=15)\n",
    "plt.ylabel('Betweenness Centrality B',size = 15)\n",
    "plt.legend(frameon=False, fontsize = 'large')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 519,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = data_corr[['Local_count','Tourist_count']]\n",
    "indep = data_corr.drop(['Local_count','Tourist_count','Local_percentage','Tourist_percentage'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 545,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "reg1 = LinearRegression().fit(indep.loc[pred.dropna().index].dropna(),\n",
    "                             pred['Local_count'].loc[indep.loc[pred.dropna().index].dropna().index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 546,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-2.20280269e+01, -2.58684152e+01, -1.20097979e+00,  4.61669564e+02,\n",
       "        2.05578632e-01,  8.99380599e-02, -1.36409229e+00, -8.67221187e-01])"
      ]
     },
     "execution_count": 546,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg1.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 547,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6667451940643561"
      ]
     },
     "execution_count": 547,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg1.score(indep.loc[pred.dropna().index].dropna(),\n",
    "                             pred['Local_count'].loc[indep.loc[pred.dropna().index].dropna().index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 548,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "reg2 = LinearRegression().fit(indep.loc[pred.dropna().index].dropna(),\n",
    "                             pred['Tourist_count'].loc[indep.loc[pred.dropna().index].dropna().index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 549,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2.14721557e+01, -9.27124974e+00,  5.73021473e+00, -1.96985441e+02,\n",
       "       -3.07108681e-02, -5.49928508e-02,  5.98920069e-01,  7.76613011e-01])"
      ]
     },
     "execution_count": 549,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg2.coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 551,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.46669214696698513"
      ]
     },
     "execution_count": 551,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reg2.score(indep.loc[pred.dropna().index].dropna(),\n",
    "                             pred['Tourist_count'].loc[indep.loc[pred.dropna().index].dropna().index])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 561,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:            Local_count   R-squared:                       0.667\n",
      "Model:                            OLS   Adj. R-squared:                  0.500\n",
      "Method:                 Least Squares   F-statistic:                     4.001\n",
      "Date:                Thu, 29 Oct 2020   Prob (F-statistic):            0.00881\n",
      "Time:                        14:59:44   Log-Likelihood:                -30.154\n",
      "No. Observations:                  25   AIC:                             78.31\n",
      "Df Residuals:                      16   BIC:                             89.28\n",
      "Df Model:                           8                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==================================================================================\n",
      "                     coef    std err          t      P>|t|      [0.025      0.975]\n",
      "----------------------------------------------------------------------------------\n",
      "const              4.7004      2.142      2.195      0.043       0.160       9.240\n",
      "degree_P         -22.0280     21.749     -1.013      0.326     -68.134      24.078\n",
      "closeness_P      -25.8684      9.513     -2.719      0.015     -46.035      -5.702\n",
      "betweenness_P     -1.2010      5.282     -0.227      0.823     -12.398       9.996\n",
      "pagerank_P       461.6696    210.808      2.190      0.044      14.777     908.562\n",
      "Local_Vote         0.2056      0.098      2.097      0.052      -0.002       0.413\n",
      "Non-local_Vote     0.0899      0.120      0.752      0.463      -0.164       0.343\n",
      "Representing      -1.3641      1.085     -1.258      0.227      -3.663       0.935\n",
      "Gathering         -0.8672      0.961     -0.902      0.380      -2.905       1.171\n",
      "==============================================================================\n",
      "Omnibus:                        2.131   Durbin-Watson:                   2.117\n",
      "Prob(Omnibus):                  0.345   Jarque-Bera (JB):                1.122\n",
      "Skew:                           0.039   Prob(JB):                        0.571\n",
      "Kurtosis:                       1.965   Cond. No.                     2.18e+04\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "[2] The condition number is large, 2.18e+04. This might indicate that there are\n",
      "strong multicollinearity or other numerical problems.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/nbai/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py:2542: FutureWarning: Method .ptp is deprecated and will be removed in a future version. Use numpy.ptp instead.\n",
      "  return ptp(axis=axis, out=out, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "Y = pred['Local_count']\n",
    "X = indep\n",
    "X = sm.add_constant(X)\n",
    "model = sm.OLS(Y,X, missing = 'drop')\n",
    "results = model.fit()\n",
    "print(results.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 562,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:          Tourist_count   R-squared:                       0.467\n",
      "Model:                            OLS   Adj. R-squared:                  0.200\n",
      "Method:                 Least Squares   F-statistic:                     1.750\n",
      "Date:                Thu, 29 Oct 2020   Prob (F-statistic):              0.162\n",
      "Time:                        15:02:57   Log-Likelihood:                -31.137\n",
      "No. Observations:                  25   AIC:                             80.27\n",
      "Df Residuals:                      16   BIC:                             91.24\n",
      "Df Model:                           8                                         \n",
      "Covariance Type:            nonrobust                                         \n",
      "==================================================================================\n",
      "                     coef    std err          t      P>|t|      [0.025      0.975]\n",
      "----------------------------------------------------------------------------------\n",
      "const              4.3213      2.227      1.940      0.070      -0.401       9.043\n",
      "degree_P          21.4722     22.621      0.949      0.357     -26.482      69.426\n",
      "closeness_P       -9.2712      9.894     -0.937      0.363     -30.246      11.704\n",
      "betweenness_P      5.7302      5.494      1.043      0.312      -5.916      17.376\n",
      "pagerank_P      -196.9854    219.259     -0.898      0.382    -661.794     267.823\n",
      "Local_Vote        -0.0307      0.102     -0.301      0.767      -0.247       0.185\n",
      "Non-local_Vote    -0.0550      0.124     -0.442      0.664      -0.319       0.209\n",
      "Representing       0.5989      1.128      0.531      0.603      -1.793       2.990\n",
      "Gathering          0.7766      1.000      0.777      0.449      -1.343       2.896\n",
      "==============================================================================\n",
      "Omnibus:                       10.863   Durbin-Watson:                   1.618\n",
      "Prob(Omnibus):                  0.004   Jarque-Bera (JB):                9.861\n",
      "Skew:                           1.089   Prob(JB):                      0.00722\n",
      "Kurtosis:                       5.173   Cond. No.                     2.18e+04\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
      "[2] The condition number is large, 2.18e+04. This might indicate that there are\n",
      "strong multicollinearity or other numerical problems.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/nbai/anaconda3/lib/python3.6/site-packages/numpy/core/fromnumeric.py:2542: FutureWarning: Method .ptp is deprecated and will be removed in a future version. Use numpy.ptp instead.\n",
      "  return ptp(axis=axis, out=out, **kwargs)\n"
     ]
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "Y = pred['Tourist_count']\n",
    "X = indep\n",
    "X = sm.add_constant(X)\n",
    "model = sm.OLS(Y,X, missing = 'drop')\n",
    "results = model.fit()\n",
    "print(results.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_Cognition = All_data[['ID','地段','Local_Vote','Non-local_Vote', 'Representing', 'Gathering']].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import KMeans\n",
    "\n",
    "kmeans = KMeans(n_clusters=3).fit(data_Cognition[['Representing','Gathering']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_Cognition['cluster']=kmeans.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fad3544a2b0>"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from adjustText import adjust_text\n",
    "\n",
    "plt.subplots(figsize=(8,8))\n",
    "\n",
    "labels = ['Imaged Places', 'Central Places', 'Gathering Places']\n",
    "colors = ['darkorange', 'steelblue','green']\n",
    "markers = ['o', '^', 's']\n",
    "\n",
    "for i in range(3):\n",
    "    plt.scatter(data_Cognition[data_Cognition['cluster']==i]['Gathering'],\n",
    "            data_Cognition[data_Cognition['cluster']==i]['Representing'],\n",
    "                c=colors[i],alpha=0.9, label = labels[i], marker=markers[i])\n",
    "\n",
    "texts = [plt.text(data_Cognition['Gathering'].iloc[i], data_Cognition['Representing'].iloc[i], \n",
    "                  int(data_Cognition['ID'].iloc[i]), fontsize =15, ) for i in range(len(data_Cognition))]\n",
    "\n",
    "adjust_text(texts)\n",
    "\n",
    "plt.xlabel('Factor 2: Gathering Axis',size=18)\n",
    "plt.ylabel('Factor 1: Representing Axis',size=18)\n",
    "\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "by_label = dict(zip(labels, handles))\n",
    "\n",
    "plt.legend(by_label.values(), by_label.keys(), frameon=False, loc = (0.55, 0.75), prop = {'size':15})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fad34e370b8>"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from adjustText import adjust_text\n",
    "\n",
    "plt.subplots(figsize=(8,8))\n",
    "\n",
    "labels = ['Imaged Places', 'Central Places', 'Gathering Places']\n",
    "colors = ['darkorange', 'steelblue','green']\n",
    "markers = ['o', '^', 's']\n",
    "\n",
    "for i in range(3):\n",
    "    plt.scatter(data_Cognition[data_Cognition['cluster']==i]['Non-local_Vote'],\n",
    "            data_Cognition[data_Cognition['cluster']==i]['Local_Vote'],\n",
    "                c=colors[i],alpha=0.9, label = labels[i], marker=markers[i])\n",
    "\n",
    "texts = [plt.text(data_Cognition['Non-local_Vote'].iloc[i], data_Cognition['Local_Vote'].iloc[i], \n",
    "                  int(data_Cognition['ID'].iloc[i]), fontsize =15, ) for i in range(len(data_Cognition))]\n",
    "\n",
    "adjust_text(texts)\n",
    "\n",
    "corr = stats.spearmanr(data_Cognition['Non-local_Vote'], data_Cognition['Local_Vote'], nan_policy='omit')\n",
    "xlim1,xlim2 = plt.xlim()\n",
    "ylim1,ylim2 = plt.ylim()\n",
    "plt.text(0.68*(xlim2-xlim1)+xlim1, 0.05*(ylim2-ylim1)+ylim1, f\"r value: {corr[0]:.2f}***\\n\\np value: {corr[1]:.2f}\",size=17)\n",
    "\n",
    "plt.xlabel('Nomination by Non-locals',size=18)\n",
    "plt.ylabel('Nomination by Villagers',size=18)\n",
    "\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "by_label = dict(zip(labels, handles))\n",
    "\n",
    "plt.legend(by_label.values(), by_label.keys(), frameon=False, loc = (0.05, 0.75), prop = {'size':15})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fad353d1f98>"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from adjustText import adjust_text\n",
    "\n",
    "plt.subplots(figsize=(8,8))\n",
    "\n",
    "labels = ['Imaged Places', 'Central Places', 'Gathering Places']\n",
    "colors = ['darkorange', 'steelblue','green']\n",
    "markers = ['o', '^', 's']\n",
    "\n",
    "data_Cognition['Nomi_diff'] = data_Cognition['Local_Vote']-data_Cognition['Non-local_Vote']\n",
    "x1 = data_Cognition[['ID','Nomi_diff','cluster']].sort_values(by='Nomi_diff')\n",
    "x1['rank'] = range(len(data_Cognition))\n",
    "\n",
    "for i in range(3):\n",
    "    plt.scatter(x1[x1['cluster']==i]['rank'],\n",
    "            x1[x1['cluster']==i]['Nomi_diff'],\n",
    "                c=colors[i],alpha=0.9, label = labels[i], marker=markers[i])\n",
    "\n",
    "texts = [plt.text(x1['rank'].iloc[i], x1['Nomi_diff'].iloc[i], \n",
    "                  int(x1['ID'].iloc[i]), fontsize =15, ) for i in range(len(data_Cognition))]\n",
    "\n",
    "adjust_text(texts)\n",
    "\n",
    "plt.xlabel('Ranking of Nomination Difference',size=18)\n",
    "plt.ylabel('Nomination difference by Local/Non-local',size=18)\n",
    "\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "by_label = dict(zip(labels, handles))\n",
    "\n",
    "plt.legend(by_label.values(), by_label.keys(), frameon=False, loc = (0.05, 0.75), prop = {'size':15})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fad3a70c128>"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from adjustText import adjust_text\n",
    "\n",
    "plt.subplots(2,1,figsize = (16,7))\n",
    "\n",
    "labels = ['Imaged Places', 'Central Places', 'Gathering Places']\n",
    "colors = ['darkorange', 'steelblue','green']\n",
    "markers = ['o', '^', 's']\n",
    "\n",
    "plt.subplot(121)\n",
    "for i in range(3):\n",
    "    plt.scatter(data_Cognition[data_Cognition['cluster']==i]['Gathering'],\n",
    "            data_Cognition[data_Cognition['cluster']==i]['Representing'],\n",
    "                c=colors[i],alpha=0.9, label = labels[i], marker=markers[i])\n",
    "\n",
    "texts = [plt.text(data_Cognition['Gathering'].iloc[i], data_Cognition['Representing'].iloc[i], \n",
    "                  int(data_Cognition['ID'].iloc[i]), fontsize =15, ) for i in range(len(data_Cognition))]\n",
    "\n",
    "adjust_text(texts)\n",
    "\n",
    "plt.xlabel('Factor 2: Gathering Axis',size=18)\n",
    "plt.ylabel('Factor 1: Representing Axis',size=18)\n",
    "\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "by_label = dict(zip(labels, handles))\n",
    "\n",
    "plt.legend(by_label.values(), by_label.keys(), frameon=False, loc = (0.55, 0.75), prop = {'size':15})\n",
    "\n",
    "plt.subplot(122)\n",
    "data_Cognition['Nomi_diff'] = data_Cognition['Local_Vote']-data_Cognition['Non-local_Vote']\n",
    "x1 = data_Cognition[['ID','Nomi_diff','cluster']].sort_values(by='Nomi_diff',ascending=False)\n",
    "x1['rank'] = range(len(data_Cognition))\n",
    "\n",
    "for i in range(3):\n",
    "    plt.scatter(x1[x1['cluster']==i]['rank'],\n",
    "            x1[x1['cluster']==i]['Nomi_diff'],\n",
    "                c=colors[i],alpha=0.9, label = labels[i], marker=markers[i])\n",
    "\n",
    "texts = [plt.text(x1['rank'].iloc[i], x1['Nomi_diff'].iloc[i], \n",
    "                  int(x1['ID'].iloc[i]), fontsize =15, ) for i in range(len(data_Cognition))]\n",
    "\n",
    "adjust_text(texts)\n",
    "\n",
    "plt.xlabel('Ranking of Nomination Difference',size=18)\n",
    "plt.ylabel('Nomination difference by Local/Non-local',size=18)\n",
    "\n",
    "handles, labels = plt.gca().get_legend_handles_labels()\n",
    "by_label = dict(zip(labels, handles))\n",
    "\n",
    "plt.legend(by_label.values(), by_label.keys(), frameon=False, loc = (0.55, 0.75), prop = {'size':15})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=66.27413270224531, pvalue=3.869561924968606e-14)"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import f_oneway\n",
    "\n",
    "x = [data_Cognition[data_Cognition['cluster']==i]['Gathering'] for i in range(3)]\n",
    "\n",
    "f_oneway(x[0],x[1],x[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "F_onewayResult(statistic=64.27879543699545, pvalue=6.453573559807502e-14)"
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.stats import f_oneway\n",
    "\n",
    "x = [data_Cognition[data_Cognition['cluster']==i]['Representing'] for i in range(3)]\n",
    "\n",
    "f_oneway(x[0],x[1],x[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "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>ID</th>\n",
       "      <th>地段</th>\n",
       "      <th>Local_Vote</th>\n",
       "      <th>Non-local_Vote</th>\n",
       "      <th>Representing</th>\n",
       "      <th>Gathering</th>\n",
       "      <th>cluster</th>\n",
       "      <th>Nomi_diff</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1.0</td>\n",
       "      <td>白果树</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.52694</td>\n",
       "      <td>-0.40605</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2.0</td>\n",
       "      <td>包想商铺</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.10848</td>\n",
       "      <td>0.75272</td>\n",
       "      <td>0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>3.0</td>\n",
       "      <td>更楼</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.27115</td>\n",
       "      <td>-0.34721</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>4.0</td>\n",
       "      <td>古道野路</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.31043</td>\n",
       "      <td>-0.54090</td>\n",
       "      <td>0</td>\n",
       "      <td>-5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>5.0</td>\n",
       "      <td>古樟树</td>\n",
       "      <td>38.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.81433</td>\n",
       "      <td>-0.27861</td>\n",
       "      <td>1</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>6.0</td>\n",
       "      <td>闺秀楼</td>\n",
       "      <td>18.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.96734</td>\n",
       "      <td>-0.33666</td>\n",
       "      <td>1</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>7.0</td>\n",
       "      <td>和气巷</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.42370</td>\n",
       "      <td>-0.21394</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>8.0</td>\n",
       "      <td>荷花池</td>\n",
       "      <td>42.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>-0.94450</td>\n",
       "      <td>5.09923</td>\n",
       "      <td>2</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>9.0</td>\n",
       "      <td>横街</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.19865</td>\n",
       "      <td>0.32207</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.0</td>\n",
       "      <td>后街</td>\n",
       "      <td>14.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>1.48162</td>\n",
       "      <td>1.13031</td>\n",
       "      <td>1</td>\n",
       "      <td>-9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11.0</td>\n",
       "      <td>后街碾坊</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.27344</td>\n",
       "      <td>-0.57248</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>12.0</td>\n",
       "      <td>花海入口</td>\n",
       "      <td>16.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.97225</td>\n",
       "      <td>0.29919</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>13.0</td>\n",
       "      <td>花海</td>\n",
       "      <td>16.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.97225</td>\n",
       "      <td>0.29919</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>14.0</td>\n",
       "      <td>黄氏宗祠</td>\n",
       "      <td>24.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.70078</td>\n",
       "      <td>0.55051</td>\n",
       "      <td>1</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>15.0</td>\n",
       "      <td>金刚寺</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.22010</td>\n",
       "      <td>0.22976</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>16.0</td>\n",
       "      <td>京台池塘</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.63983</td>\n",
       "      <td>-0.16498</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>17.0</td>\n",
       "      <td>京台村委会</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.91473</td>\n",
       "      <td>0.72349</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>18.0</td>\n",
       "      <td>京台古戏台</td>\n",
       "      <td>21.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2.77999</td>\n",
       "      <td>-0.62553</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>19.0</td>\n",
       "      <td>京台旧小学</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-0.02976</td>\n",
       "      <td>-0.27777</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20.0</td>\n",
       "      <td>京台士大夫第</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.21116</td>\n",
       "      <td>-0.47809</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21.0</td>\n",
       "      <td>京台文化大院</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.18369</td>\n",
       "      <td>-0.39049</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22.0</td>\n",
       "      <td>刘氏宗祠</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.01196</td>\n",
       "      <td>-0.50662</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>23.0</td>\n",
       "      <td>六甲香火堂</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.37381</td>\n",
       "      <td>-0.25607</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>24.0</td>\n",
       "      <td>罗田小学</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.31968</td>\n",
       "      <td>-0.11101</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>25.0</td>\n",
       "      <td>民俗馆</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.13342</td>\n",
       "      <td>-0.48706</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>26.0</td>\n",
       "      <td>奇石馆</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.17028</td>\n",
       "      <td>0.31283</td>\n",
       "      <td>0</td>\n",
       "      <td>6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>27.0</td>\n",
       "      <td>前街</td>\n",
       "      <td>42.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.21068</td>\n",
       "      <td>5.21173</td>\n",
       "      <td>2</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>28.0</td>\n",
       "      <td>三看路</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>-0.08547</td>\n",
       "      <td>-0.26590</td>\n",
       "      <td>0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>29.0</td>\n",
       "      <td>士大夫第</td>\n",
       "      <td>28.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>3.45644</td>\n",
       "      <td>0.44469</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>30.0</td>\n",
       "      <td>寿康井</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.70591</td>\n",
       "      <td>-0.77694</td>\n",
       "      <td>0</td>\n",
       "      <td>-3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>31.0</td>\n",
       "      <td>双德门</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.25123</td>\n",
       "      <td>0.38467</td>\n",
       "      <td>0</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>32.0</td>\n",
       "      <td>水南池塘</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-0.36978</td>\n",
       "      <td>0.32231</td>\n",
       "      <td>0</td>\n",
       "      <td>-5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>33.0</td>\n",
       "      <td>水南村后广场</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.79020</td>\n",
       "      <td>0.04199</td>\n",
       "      <td>0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>34.0</td>\n",
       "      <td>水南村口广场</td>\n",
       "      <td>16.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-1.07120</td>\n",
       "      <td>1.88810</td>\n",
       "      <td>0</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>35.0</td>\n",
       "      <td>水南非遗街</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>-0.02656</td>\n",
       "      <td>0.32121</td>\n",
       "      <td>0</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>36.0</td>\n",
       "      <td>水南酒吧</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.00263</td>\n",
       "      <td>0.56499</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>37.0</td>\n",
       "      <td>水南入村道路</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.21688</td>\n",
       "      <td>-0.37573</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>38.0</td>\n",
       "      <td>水南戏台</td>\n",
       "      <td>20.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.40533</td>\n",
       "      <td>1.78585</td>\n",
       "      <td>0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>39.0</td>\n",
       "      <td>太婆古樟</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.59929</td>\n",
       "      <td>-0.27158</td>\n",
       "      <td>0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>40.0</td>\n",
       "      <td>唐樟</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.73883</td>\n",
       "      <td>1.30588</td>\n",
       "      <td>0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>41.0</td>\n",
       "      <td>万赤线公路</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>-0.19319</td>\n",
       "      <td>0.06529</td>\n",
       "      <td>0</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>42.0</td>\n",
       "      <td>沃野来祥</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-0.26567</td>\n",
       "      <td>-0.35108</td>\n",
       "      <td>0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>43.0</td>\n",
       "      <td>曦庐墨庄</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.04863</td>\n",
       "      <td>-0.13122</td>\n",
       "      <td>1</td>\n",
       "      <td>-11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>44.0</td>\n",
       "      <td>写生基地</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>-0.66815</td>\n",
       "      <td>0.09088</td>\n",
       "      <td>0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>45.0</td>\n",
       "      <td>星拱辰垣</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>-0.01110</td>\n",
       "      <td>-0.59204</td>\n",
       "      <td>0</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>46.0</td>\n",
       "      <td>秀宿</td>\n",
       "      <td>10.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.62923</td>\n",
       "      <td>0.59206</td>\n",
       "      <td>0</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>47.0</td>\n",
       "      <td>绣花楼</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.10985</td>\n",
       "      <td>0.06442</td>\n",
       "      <td>0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>48.0</td>\n",
       "      <td>游客服务中心</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.06793</td>\n",
       "      <td>-0.53674</td>\n",
       "      <td>0</td>\n",
       "      <td>-4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      ID      地段  Local_Vote  Non-local_Vote  Representing  Gathering  \\\n",
       "34   1.0     白果树         1.0             0.0      -0.52694   -0.40605   \n",
       "29   2.0    包想商铺        10.0             0.0      -1.10848    0.75272   \n",
       "25   3.0      更楼         2.0             2.0      -0.27115   -0.34721   \n",
       "31   4.0    古道野路         1.0             6.0       0.31043   -0.54090   \n",
       "37   5.0     古樟树        38.0            30.0       4.81433   -0.27861   \n",
       "13   6.0     闺秀楼        18.0            11.0       1.96734   -0.33666   \n",
       "49   7.0     和气巷         3.0             1.0      -0.42370   -0.21394   \n",
       "17   8.0     荷花池        42.0            11.0      -0.94450    5.09923   \n",
       "44   9.0      横街         6.0             8.0       0.19865    0.32207   \n",
       "4   10.0      后街        14.0            23.0       1.48162    1.13031   \n",
       "5   11.0    后街碾坊         0.0             2.0      -0.27344   -0.57248   \n",
       "32  12.0    花海入口        16.0            14.0       0.97225    0.29919   \n",
       "47  13.0      花海        16.0            14.0       0.97225    0.29919   \n",
       "24  14.0    黄氏宗祠        24.0            22.0       2.70078    0.55051   \n",
       "39  15.0     金刚寺        10.0             2.0      -0.22010    0.22976   \n",
       "10  16.0    京台池塘         3.0             0.0      -0.63983   -0.16498   \n",
       "26  17.0   京台村委会         7.0             1.0      -0.91473    0.72349   \n",
       "2   18.0   京台古戏台        21.0            20.0       2.77999   -0.62553   \n",
       "6   19.0   京台旧小学         2.0             5.0      -0.02976   -0.27777   \n",
       "0   20.0  京台士大夫第         6.0             2.0       0.21116   -0.47809   \n",
       "1   21.0  京台文化大院         2.0             2.0      -0.18369   -0.39049   \n",
       "22  22.0    刘氏宗祠         2.0             3.0      -0.01196   -0.50662   \n",
       "36  23.0   六甲香火堂         3.0             1.0      -0.37381   -0.25607   \n",
       "45  24.0    罗田小学         2.0             3.0      -0.31968   -0.11101   \n",
       "21  25.0     民俗馆         5.0             1.0      -0.13342   -0.48706   \n",
       "28  26.0     奇石馆         9.0             3.0      -0.17028    0.31283   \n",
       "43  27.0      前街        42.0            24.0       0.21068    5.21173   \n",
       "42  28.0     三看路         4.0             3.0      -0.08547   -0.26590   \n",
       "20  29.0    士大夫第        28.0            23.0       3.45644    0.44469   \n",
       "41  30.0     寿康井         3.0             6.0       0.70591   -0.77694   \n",
       "7   31.0     双德门         5.0            11.0       0.25123    0.38467   \n",
       "14  32.0    水南池塘         2.0             7.0      -0.36978    0.32231   \n",
       "8   33.0  水南村后广场         4.0             0.0      -0.79020    0.04199   \n",
       "23  34.0  水南村口广场        16.0             5.0      -1.07120    1.88810   \n",
       "15  35.0   水南非遗街         4.0             8.0      -0.02656    0.32121   \n",
       "11  36.0    水南酒吧        11.0             9.0       0.00263    0.56499   \n",
       "48  37.0  水南入村道路         2.0             2.0      -0.21688   -0.37573   \n",
       "35  38.0    水南戏台        20.0             6.0      -0.40533    1.78585   \n",
       "46  39.0    太婆古樟         0.0             1.0      -0.59929   -0.27158   \n",
       "33  40.0      唐樟        20.0            15.0       0.73883    1.30588   \n",
       "38  41.0   万赤线公路         3.0             5.0      -0.19319    0.06529   \n",
       "27  42.0    沃野来祥         3.0             1.0      -0.26567   -0.35108   \n",
       "3   43.0    曦庐墨庄        11.0            22.0       2.04863   -0.13122   \n",
       "9   44.0    写生基地         5.0             2.0      -0.66815    0.09088   \n",
       "16  45.0    星拱辰垣         0.0             4.0      -0.01110   -0.59204   \n",
       "30  46.0      秀宿        10.0            14.0       0.62923    0.59206   \n",
       "12  47.0     绣花楼        10.0             3.0       0.10985    0.06442   \n",
       "40  48.0  游客服务中心         1.0             5.0       0.06793   -0.53674   \n",
       "\n",
       "    cluster  Nomi_diff  \n",
       "34        0        1.0  \n",
       "29        0       10.0  \n",
       "25        0        0.0  \n",
       "31        0       -5.0  \n",
       "37        1        8.0  \n",
       "13        1        7.0  \n",
       "49        0        2.0  \n",
       "17        2       31.0  \n",
       "44        0       -2.0  \n",
       "4         1       -9.0  \n",
       "5         0       -2.0  \n",
       "32        0        2.0  \n",
       "47        0        2.0  \n",
       "24        1        2.0  \n",
       "39        0        8.0  \n",
       "10        0        3.0  \n",
       "26        0        6.0  \n",
       "2         1        1.0  \n",
       "6         0       -3.0  \n",
       "0         0        4.0  \n",
       "1         0        0.0  \n",
       "22        0       -1.0  \n",
       "36        0        2.0  \n",
       "45        0       -1.0  \n",
       "21        0        4.0  \n",
       "28        0        6.0  \n",
       "43        2       18.0  \n",
       "42        0        1.0  \n",
       "20        1        5.0  \n",
       "41        0       -3.0  \n",
       "7         0       -6.0  \n",
       "14        0       -5.0  \n",
       "8         0        4.0  \n",
       "23        0       11.0  \n",
       "15        0       -4.0  \n",
       "11        0        2.0  \n",
       "48        0        0.0  \n",
       "35        0       14.0  \n",
       "46        0       -1.0  \n",
       "33        0        5.0  \n",
       "38        0       -2.0  \n",
       "27        0        2.0  \n",
       "3         1      -11.0  \n",
       "9         0        3.0  \n",
       "16        0       -4.0  \n",
       "30        0       -4.0  \n",
       "12        0        7.0  \n",
       "40        0       -4.0  "
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_Cognition.sort_values(by='ID')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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