Simulate_recombination.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Genotypes of the founders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulated founders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:50.622244Z",
     "start_time": "2019-07-03T17:38:50.605679Z"
    },
    "hide_input": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import random as rd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:50.645085Z",
     "start_time": "2019-07-03T17:38:50.630758Z"
    }
   },
   "outputs": [],
   "source": [
    "SMALL_SIZE = 7\n",
    "MEDIUM_SIZE = 15\n",
    "BIGGER_SIZE = 20\n",
    "\n",
    "plt.rc('font', size=SMALL_SIZE)          # controls default text sizes\n",
    "plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize\n",
    "plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:50.663792Z",
     "start_time": "2019-07-03T17:38:50.652277Z"
    }
   },
   "outputs": [],
   "source": [
    "n = 16    # founders\n",
    "p = 1000  # nb of SNPs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:50.749799Z",
     "start_time": "2019-07-03T17:38:50.673122Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "F_haplo = np.array([[j for i in range(p)] for j in range(1,n+1)])    # founders' haplotypes (n founders and p SNPs)\n",
    "F_geno = np.array([[rd.randint(0,1) for snp in range(p)] for founder in range (n)])    # founders' genotypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:58.437206Z",
     "start_time": "2019-07-03T17:38:50.755879Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1080x720 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "im, ax = plt.subplots(16,1, figsize = (15,10))\n",
    "ax[0].set(title = \"Genotypes of the 16 founders\")\n",
    "for k in range (16):\n",
    "    ax[k].imshow (np.expand_dims(F_geno[k],1).T, aspect = 20)\n",
    "    ax[k].set(ylabel = \"F{}\".format(k+1))\n",
    "ax[15].set(xlabel = \"1000 SNPs (purple = identical to the founder F12/N2, yellow = different)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Real founders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "lang": "en"
   },
   "source": [
    "### Full chromosome I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:58.455385Z",
     "start_time": "2019-07-03T17:38:58.442256Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import random as rd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import pickle\n",
    "from pprint import pprint\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:58.483112Z",
     "start_time": "2019-07-03T17:38:58.466373Z"
    }
   },
   "outputs": [],
   "source": [
    "SMALL_SIZE = 7\n",
    "MEDIUM_SIZE = 15\n",
    "BIGGER_SIZE = 20\n",
    "\n",
    "plt.rc('font', size=SMALL_SIZE)          # controls default text sizes\n",
    "plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize\n",
    "plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Import genetic data*** (linkage) as a dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:59.278466Z",
     "start_time": "2019-07-03T17:38:58.490423Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          chrom   pos ref alt  genetic\n",
      "0  CHROMOSOME_I   855   G   C      0.0\n",
      "1  CHROMOSOME_I  1222   A   C      0.0\n",
      "2  CHROMOSOME_I  1291   G   T      0.0\n",
      "3  CHROMOSOME_I  1713   T   G      0.0\n",
      "4  CHROMOSOME_I  1761   G   A      0.0\n",
      "5  CHROMOSOME_I  1799   T   C      0.0\n",
      "6  CHROMOSOME_I  1902   C   G      0.0\n",
      "7  CHROMOSOME_I  1933   C   G      0.0\n",
      "8  CHROMOSOME_I  2618   T   A      0.0\n",
      "9  CHROMOSOME_I  2622   T   A      0.0\n"
     ]
    }
   ],
   "source": [
    "geneticDF = pd.read_csv(\"./Donnees_supplementaires/WS220.founder.bsqr.calls.genetic.txt\", delimiter=\"\\t\")\n",
    "pprint(geneticDF[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:38:59.863641Z",
     "start_time": "2019-07-03T17:38:59.282677Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">pos</th>\n",
       "      <th colspan=\"8\" halign=\"left\">genetic</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chrom</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_I</th>\n",
       "      <td>39817.0</td>\n",
       "      <td>7.173954e+06</td>\n",
       "      <td>5.174639e+06</td>\n",
       "      <td>855.0</td>\n",
       "      <td>2155394.00</td>\n",
       "      <td>6493036.0</td>\n",
       "      <td>12364998.00</td>\n",
       "      <td>15066925.0</td>\n",
       "      <td>39817.0</td>\n",
       "      <td>48.773637</td>\n",
       "      <td>38.214724</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.687636</td>\n",
       "      <td>39.105580</td>\n",
       "      <td>78.113818</td>\n",
       "      <td>135.188818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_II</th>\n",
       "      <td>81373.0</td>\n",
       "      <td>6.429576e+06</td>\n",
       "      <td>4.941117e+06</td>\n",
       "      <td>943.0</td>\n",
       "      <td>2168585.00</td>\n",
       "      <td>3804273.0</td>\n",
       "      <td>12051766.00</td>\n",
       "      <td>15276886.0</td>\n",
       "      <td>81373.0</td>\n",
       "      <td>50.455178</td>\n",
       "      <td>41.415471</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.760064</td>\n",
       "      <td>41.289589</td>\n",
       "      <td>78.947269</td>\n",
       "      <td>133.279335</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_III</th>\n",
       "      <td>60754.0</td>\n",
       "      <td>5.144998e+06</td>\n",
       "      <td>4.706639e+06</td>\n",
       "      <td>421.0</td>\n",
       "      <td>1159027.25</td>\n",
       "      <td>2782780.5</td>\n",
       "      <td>10499259.50</td>\n",
       "      <td>13780879.0</td>\n",
       "      <td>60754.0</td>\n",
       "      <td>51.590025</td>\n",
       "      <td>45.831267</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.814036</td>\n",
       "      <td>44.096847</td>\n",
       "      <td>88.564221</td>\n",
       "      <td>137.416947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_IV</th>\n",
       "      <td>57513.0</td>\n",
       "      <td>8.936451e+06</td>\n",
       "      <td>6.168507e+06</td>\n",
       "      <td>23876.0</td>\n",
       "      <td>2718280.00</td>\n",
       "      <td>7456621.0</td>\n",
       "      <td>15264068.00</td>\n",
       "      <td>17492235.0</td>\n",
       "      <td>57513.0</td>\n",
       "      <td>95.357527</td>\n",
       "      <td>47.581686</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.528837</td>\n",
       "      <td>97.634283</td>\n",
       "      <td>134.684918</td>\n",
       "      <td>156.272742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_V</th>\n",
       "      <td>115968.0</td>\n",
       "      <td>1.155985e+07</td>\n",
       "      <td>7.343576e+06</td>\n",
       "      <td>405.0</td>\n",
       "      <td>3409704.75</td>\n",
       "      <td>15663984.5</td>\n",
       "      <td>17708407.75</td>\n",
       "      <td>20922549.0</td>\n",
       "      <td>115968.0</td>\n",
       "      <td>70.660283</td>\n",
       "      <td>48.466181</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.893801</td>\n",
       "      <td>85.054047</td>\n",
       "      <td>100.005535</td>\n",
       "      <td>146.854729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_X</th>\n",
       "      <td>49111.0</td>\n",
       "      <td>9.626188e+06</td>\n",
       "      <td>5.073525e+06</td>\n",
       "      <td>5755.0</td>\n",
       "      <td>5214118.50</td>\n",
       "      <td>10096210.0</td>\n",
       "      <td>14227277.00</td>\n",
       "      <td>17718678.0</td>\n",
       "      <td>49111.0</td>\n",
       "      <td>58.430795</td>\n",
       "      <td>32.393336</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.910665</td>\n",
       "      <td>57.306995</td>\n",
       "      <td>87.033258</td>\n",
       "      <td>107.845644</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     pos                                                   \\\n",
       "                   count          mean           std      min         25%   \n",
       "chrom                                                                       \n",
       "CHROMOSOME_I     39817.0  7.173954e+06  5.174639e+06    855.0  2155394.00   \n",
       "CHROMOSOME_II    81373.0  6.429576e+06  4.941117e+06    943.0  2168585.00   \n",
       "CHROMOSOME_III   60754.0  5.144998e+06  4.706639e+06    421.0  1159027.25   \n",
       "CHROMOSOME_IV    57513.0  8.936451e+06  6.168507e+06  23876.0  2718280.00   \n",
       "CHROMOSOME_V    115968.0  1.155985e+07  7.343576e+06    405.0  3409704.75   \n",
       "CHROMOSOME_X     49111.0  9.626188e+06  5.073525e+06   5755.0  5214118.50   \n",
       "\n",
       "                                                      genetic             \\\n",
       "                       50%          75%         max     count       mean   \n",
       "chrom                                                                      \n",
       "CHROMOSOME_I     6493036.0  12364998.00  15066925.0   39817.0  48.773637   \n",
       "CHROMOSOME_II    3804273.0  12051766.00  15276886.0   81373.0  50.455178   \n",
       "CHROMOSOME_III   2782780.5  10499259.50  13780879.0   60754.0  51.590025   \n",
       "CHROMOSOME_IV    7456621.0  15264068.00  17492235.0   57513.0  95.357527   \n",
       "CHROMOSOME_V    15663984.5  17708407.75  20922549.0  115968.0  70.660283   \n",
       "CHROMOSOME_X    10096210.0  14227277.00  17718678.0   49111.0  58.430795   \n",
       "\n",
       "                                                                              \n",
       "                      std  min        25%        50%         75%         max  \n",
       "chrom                                                                         \n",
       "CHROMOSOME_I    38.214724  0.0  15.687636  39.105580   78.113818  135.188818  \n",
       "CHROMOSOME_II   41.415471  0.0   8.760064  41.289589   78.947269  133.279335  \n",
       "CHROMOSOME_III  45.831267  0.0   6.814036  44.096847   88.564221  137.416947  \n",
       "CHROMOSOME_IV   47.581686  0.0  60.528837  97.634283  134.684918  156.272742  \n",
       "CHROMOSOME_V    48.466181  0.0  19.893801  85.054047  100.005535  146.854729  \n",
       "CHROMOSOME_X    32.393336  0.0  34.910665  57.306995   87.033258  107.845644  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geneticDF.groupby('chrom').describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Keep only the chromosome 1 and rescale genetic distance between 0 and 50***."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:00.030664Z",
     "start_time": "2019-07-03T17:38:59.869151Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pos</th>\n",
       "      <th>genetic</th>\n",
       "      <th>genetic_scaled</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>3.981700e+04</td>\n",
       "      <td>39817.000000</td>\n",
       "      <td>39817.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>7.173954e+06</td>\n",
       "      <td>48.773637</td>\n",
       "      <td>18.039080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.174639e+06</td>\n",
       "      <td>38.214724</td>\n",
       "      <td>14.133833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>8.550000e+02</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.155394e+06</td>\n",
       "      <td>15.687636</td>\n",
       "      <td>5.802120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.493036e+06</td>\n",
       "      <td>39.105580</td>\n",
       "      <td>14.463319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.236500e+07</td>\n",
       "      <td>78.113818</td>\n",
       "      <td>28.890636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.506692e+07</td>\n",
       "      <td>135.188818</td>\n",
       "      <td>50.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                pos       genetic  genetic_scaled\n",
       "count  3.981700e+04  39817.000000    39817.000000\n",
       "mean   7.173954e+06     48.773637       18.039080\n",
       "std    5.174639e+06     38.214724       14.133833\n",
       "min    8.550000e+02      0.000000        0.000000\n",
       "25%    2.155394e+06     15.687636        5.802120\n",
       "50%    6.493036e+06     39.105580       14.463319\n",
       "75%    1.236500e+07     78.113818       28.890636\n",
       "max    1.506692e+07    135.188818       50.000000"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geneticDF_ch1 = geneticDF[geneticDF.chrom == \"CHROMOSOME_I\"]\n",
    "\n",
    "pd.options.mode.chained_assignment = None\n",
    "s = 50/max(geneticDF_ch1.genetic)\n",
    "geneticDF_ch1[\"genetic_scaled\"] = [s*g for g in geneticDF_ch1.genetic]\n",
    "geneticDF_ch1.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`linkage` = vector of the recombination probabilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:00.087143Z",
     "start_time": "2019-07-03T17:39:00.035813Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 0., ..., 0., 0., 0.])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(39817,)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.001703967582336503"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.999999999999998"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "linkage = np.diff(geneticDF_ch1.genetic_scaled)\n",
    "linkage/=sum(linkage)\n",
    "linkage = np.append([0], linkage)\n",
    "display(linkage,linkage.shape,max(linkage),sum(linkage))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:00.100155Z",
     "start_time": "2019-07-03T17:39:00.091244Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Linkage_p{}.pkl\".format(linkage.shape[0]),\"wb\") as handler:\n",
    "    pickle.dump(linkage, handler)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Plot smoothened linkage***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:04.371820Z",
     "start_time": "2019-07-03T17:39:00.104511Z"
    }
   },
   "outputs": [],
   "source": [
    "linkage_smooth = []\n",
    "pos_smooth = []\n",
    "l = 2000000\n",
    "m=max(geneticDF_ch1.pos)\n",
    "points=1000\n",
    "for k in range (l//2,m-l//2,m//points):\n",
    "    window=np.logical_and(k-l//2<geneticDF_ch1.pos,geneticDF_ch1.pos<k+l//2)\n",
    "    linkage_smooth.append(np.mean(linkage[window]))\n",
    "    pos_smooth.append(np.median(geneticDF_ch1.pos[window]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:08.246271Z",
     "start_time": "2019-07-03T17:39:04.375346Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2, ax3) = plt.subplots (1,3, figsize = (20, 6))\n",
    "fig.suptitle(\"Recombination frequencies for chromosome I\")\n",
    "ax1.scatter(geneticDF_ch1.pos, geneticDF_ch1.genetic_scaled)\n",
    "ax1.set(xlabel = \"Physical position\", ylabel = \"Genetic position\")\n",
    "ax2.scatter(geneticDF_ch1.pos, linkage, alpha=0.5, marker=\"x\")\n",
    "ax2.set(xlabel = \"Physical position\", ylabel = \"Linkage (recombination proba.)\", ylim = (0,0.002))\n",
    "ax3.plot(pos_smooth, [l*10**5 for l in linkage_smooth])\n",
    "ax3.set(xlabel = \"Physical position\", ylabel = \"Smoothed linkage (x10^-5)\")\n",
    "plt.tight_layout(rect = [0, 0, 0.95, 0.95])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Import SNPs*** = Single Nucleotide Polymorphisms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:11.823914Z",
     "start_time": "2019-07-03T17:39:08.249378Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          chrom   pos ref alt   af.all  dp.all     qual  BaseQRankSum     MQ  \\\n",
      "0  CHROMOSOME_I   855   G   C  0.56250     572  8238.09        -8.252  51.46   \n",
      "1  CHROMOSOME_I  1222   A   C  0.06250     431  2795.82       -11.496  59.94   \n",
      "2  CHROMOSOME_I  1291   G   T  0.06250     504  1119.76        -3.182  58.29   \n",
      "3  CHROMOSOME_I  1713   T   G  0.06250     455  1399.71        -9.725  57.38   \n",
      "4  CHROMOSOME_I  1761   G   A  0.43750     533  5726.51        -3.884  59.51   \n",
      "5  CHROMOSOME_I  1799   T   C  0.50000     520  6086.45        -0.706  56.92   \n",
      "6  CHROMOSOME_I  1902   C   G  0.06250     484  1640.71        -1.861  56.47   \n",
      "7  CHROMOSOME_I  1933   C   G  0.56250     517  9933.72        -8.107  56.64   \n",
      "8  CHROMOSOME_I  2618   T   A  0.46875     302  3161.96        -0.213  51.89   \n",
      "9  CHROMOSOME_I  2622   T   A  0.06250     319  1159.77        -8.278  52.18   \n",
      "\n",
      "       FS  ...  JU319  JU345  JU400  MY1  MY16  N2.ANC  PB306  PX174  PX179  \\\n",
      "0   2.559  ...    1.0    1.0    0.0  0.0   1.0     0.0    1.0    1.0    0.0   \n",
      "1   1.445  ...    0.0    0.0    0.0  0.0   0.0     0.0    0.0    0.0    0.0   \n",
      "2  15.067  ...    0.0    0.0    0.0  0.0   1.0     0.0    0.0    0.0    0.0   \n",
      "3   0.000  ...    0.0    0.0    0.0  0.0   0.0     0.0    0.0    0.0    0.0   \n",
      "4   4.238  ...    1.0    1.0    0.0  0.0   0.0     0.0    1.0    1.0    0.0   \n",
      "5   0.533  ...    1.0    1.0    0.0  1.0   0.0     0.0    1.0    1.0    0.0   \n",
      "6   7.432  ...    0.0    0.0    0.0  0.0   1.0     0.0    0.0    0.0    0.0   \n",
      "7   1.118  ...    1.0    1.0    0.0  0.0   1.0     0.0    1.0    1.0    0.0   \n",
      "8   5.575  ...    1.0    1.0    0.0  0.0   1.0     0.0    1.0    1.0    0.0   \n",
      "9   5.968  ...    0.0    0.0    0.0  0.0   0.0     0.0    0.0    0.0    0.0   \n",
      "\n",
      "   RC301  \n",
      "0    1.0  \n",
      "1    0.0  \n",
      "2    0.0  \n",
      "3    0.0  \n",
      "4    1.0  \n",
      "5    1.0  \n",
      "6    0.0  \n",
      "7    1.0  \n",
      "8    0.5  \n",
      "9    0.0  \n",
      "\n",
      "[10 rows x 34 columns]\n"
     ]
    }
   ],
   "source": [
    "callsF3DF = pd.read_csv(\"./Donnees_supplementaires/WS220.founder.bsqr.calls.F3.clean\", delimiter=\"\\t\")\n",
    "pprint(callsF3DF[:10])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:14.445318Z",
     "start_time": "2019-07-03T17:39:11.828035Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">pos</th>\n",
       "      <th colspan=\"2\" halign=\"left\">af.all</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">PX179</th>\n",
       "      <th colspan=\"8\" halign=\"left\">RC301</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
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       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chrom</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_I</th>\n",
       "      <td>39817.0</td>\n",
       "      <td>7.173954e+06</td>\n",
       "      <td>5.174639e+06</td>\n",
       "      <td>855.0</td>\n",
       "      <td>2155394.00</td>\n",
       "      <td>6493036.0</td>\n",
       "      <td>12364998.00</td>\n",
       "      <td>15066925.0</td>\n",
       "      <td>39817.0</td>\n",
       "      <td>0.198232</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>39817.0</td>\n",
       "      <td>0.161614</td>\n",
       "      <td>0.365052</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_II</th>\n",
       "      <td>81373.0</td>\n",
       "      <td>6.429576e+06</td>\n",
       "      <td>4.941117e+06</td>\n",
       "      <td>943.0</td>\n",
       "      <td>2168585.00</td>\n",
       "      <td>3804273.0</td>\n",
       "      <td>12051766.00</td>\n",
       "      <td>15276886.0</td>\n",
       "      <td>81373.0</td>\n",
       "      <td>0.264841</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>81373.0</td>\n",
       "      <td>0.393527</td>\n",
       "      <td>0.483271</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_III</th>\n",
       "      <td>60754.0</td>\n",
       "      <td>5.144998e+06</td>\n",
       "      <td>4.706639e+06</td>\n",
       "      <td>421.0</td>\n",
       "      <td>1159027.25</td>\n",
       "      <td>2782780.5</td>\n",
       "      <td>10499259.50</td>\n",
       "      <td>13780879.0</td>\n",
       "      <td>60754.0</td>\n",
       "      <td>0.231472</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>60754.0</td>\n",
       "      <td>0.356042</td>\n",
       "      <td>0.474368</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_IV</th>\n",
       "      <td>57513.0</td>\n",
       "      <td>8.936451e+06</td>\n",
       "      <td>6.168507e+06</td>\n",
       "      <td>23876.0</td>\n",
       "      <td>2718280.00</td>\n",
       "      <td>7456621.0</td>\n",
       "      <td>15264068.00</td>\n",
       "      <td>17492235.0</td>\n",
       "      <td>57513.0</td>\n",
       "      <td>0.126569</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>57513.0</td>\n",
       "      <td>0.005355</td>\n",
       "      <td>0.064915</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_V</th>\n",
       "      <td>115968.0</td>\n",
       "      <td>1.155985e+07</td>\n",
       "      <td>7.343576e+06</td>\n",
       "      <td>405.0</td>\n",
       "      <td>3409704.75</td>\n",
       "      <td>15663984.5</td>\n",
       "      <td>17708407.75</td>\n",
       "      <td>20922549.0</td>\n",
       "      <td>115968.0</td>\n",
       "      <td>0.136982</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>115968.0</td>\n",
       "      <td>0.040830</td>\n",
       "      <td>0.194536</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_X</th>\n",
       "      <td>49111.0</td>\n",
       "      <td>9.626188e+06</td>\n",
       "      <td>5.073525e+06</td>\n",
       "      <td>5755.0</td>\n",
       "      <td>5214118.50</td>\n",
       "      <td>10096210.0</td>\n",
       "      <td>14227277.00</td>\n",
       "      <td>17718678.0</td>\n",
       "      <td>49111.0</td>\n",
       "      <td>0.211154</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49111.0</td>\n",
       "      <td>0.208874</td>\n",
       "      <td>0.405053</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 248 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     pos                                                   \\\n",
       "                   count          mean           std      min         25%   \n",
       "chrom                                                                       \n",
       "CHROMOSOME_I     39817.0  7.173954e+06  5.174639e+06    855.0  2155394.00   \n",
       "CHROMOSOME_II    81373.0  6.429576e+06  4.941117e+06    943.0  2168585.00   \n",
       "CHROMOSOME_III   60754.0  5.144998e+06  4.706639e+06    421.0  1159027.25   \n",
       "CHROMOSOME_IV    57513.0  8.936451e+06  6.168507e+06  23876.0  2718280.00   \n",
       "CHROMOSOME_V    115968.0  1.155985e+07  7.343576e+06    405.0  3409704.75   \n",
       "CHROMOSOME_X     49111.0  9.626188e+06  5.073525e+06   5755.0  5214118.50   \n",
       "\n",
       "                                                       af.all            ...  \\\n",
       "                       50%          75%         max     count      mean  ...   \n",
       "chrom                                                                    ...   \n",
       "CHROMOSOME_I     6493036.0  12364998.00  15066925.0   39817.0  0.198232  ...   \n",
       "CHROMOSOME_II    3804273.0  12051766.00  15276886.0   81373.0  0.264841  ...   \n",
       "CHROMOSOME_III   2782780.5  10499259.50  13780879.0   60754.0  0.231472  ...   \n",
       "CHROMOSOME_IV    7456621.0  15264068.00  17492235.0   57513.0  0.126569  ...   \n",
       "CHROMOSOME_V    15663984.5  17708407.75  20922549.0  115968.0  0.136982  ...   \n",
       "CHROMOSOME_X    10096210.0  14227277.00  17718678.0   49111.0  0.211154  ...   \n",
       "\n",
       "               PX179          RC301                                          \\\n",
       "                 75%  max     count      mean       std  min  25%  50%  75%   \n",
       "chrom                                                                         \n",
       "CHROMOSOME_I     0.0  1.0   39817.0  0.161614  0.365052  0.0  0.0  0.0  0.0   \n",
       "CHROMOSOME_II    0.0  1.0   81373.0  0.393527  0.483271  0.0  0.0  0.0  1.0   \n",
       "CHROMOSOME_III   0.0  1.0   60754.0  0.356042  0.474368  0.0  0.0  0.0  1.0   \n",
       "CHROMOSOME_IV    0.0  1.0   57513.0  0.005355  0.064915  0.0  0.0  0.0  0.0   \n",
       "CHROMOSOME_V     0.0  1.0  115968.0  0.040830  0.194536  0.0  0.0  0.0  0.0   \n",
       "CHROMOSOME_X     0.0  1.0   49111.0  0.208874  0.405053  0.0  0.0  0.0  0.0   \n",
       "\n",
       "                     \n",
       "                max  \n",
       "chrom                \n",
       "CHROMOSOME_I    1.0  \n",
       "CHROMOSOME_II   1.0  \n",
       "CHROMOSOME_III  1.0  \n",
       "CHROMOSOME_IV   1.0  \n",
       "CHROMOSOME_V    1.0  \n",
       "CHROMOSOME_X    1.0  \n",
       "\n",
       "[6 rows x 248 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "callsF3DF.groupby('chrom').describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***The 16 founders***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:14.456748Z",
     "start_time": "2019-07-03T17:39:14.450114Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AB1', 'CB4507', 'CB4852', 'CB4855', 'CB4856', 'CB4858', 'JU319', 'JU345', 'JU400', 'MY1', 'MY16', 'N2.ANC', 'PB306', 'PX174', 'PX179', 'RC301']\n"
     ]
    }
   ],
   "source": [
    "print(list(callsF3DF.columns[18:]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Deleting all 0.5 SNP data and extracting only positions and SNPs for the 16 founders*** : loss of 7% of the SNPs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:15.278130Z",
     "start_time": "2019-07-03T17:39:14.464211Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(404536, 376143, 0.0701865841358989)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders = callsF3DF[['chrom','pos']+list(callsF3DF.columns[18:])][callsF3DF[['chrom','pos']+list(callsF3DF.columns[18:])]!=0.5].dropna(how='any')\n",
    "len(callsF3DF),len(founders),(len(callsF3DF)-len(founders))/len(callsF3DF)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Convert floats into integers***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:15.659933Z",
     "start_time": "2019-07-03T17:39:15.282698Z"
    }
   },
   "outputs": [],
   "source": [
    "founders[list(founders.columns[2:])] = founders[list(founders.columns[2:])].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:15.696873Z",
     "start_time": "2019-07-03T17:39:15.664460Z"
    }
   },
   "outputs": [
    {
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       "      <th>chrom</th>\n",
       "      <th>pos</th>\n",
       "      <th>AB1</th>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1291</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1713</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1761</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          chrom   pos  AB1  CB4507  CB4852  CB4855  CB4856  CB4858  JU319  \\\n",
       "0  CHROMOSOME_I   855    0       0       0       1       1       1      1   \n",
       "1  CHROMOSOME_I  1222    0       0       0       0       1       0      0   \n",
       "2  CHROMOSOME_I  1291    0       0       0       0       0       0      0   \n",
       "3  CHROMOSOME_I  1713    0       0       0       0       1       0      0   \n",
       "4  CHROMOSOME_I  1761    0       0       0       1       0       1      1   \n",
       "\n",
       "   JU345  JU400  MY1  MY16  N2.ANC  PB306  PX174  PX179  RC301  \n",
       "0      1      0    0     1       0      1      1      0      1  \n",
       "1      0      0    0     0       0      0      0      0      0  \n",
       "2      0      0    0     1       0      0      0      0      0  \n",
       "3      0      0    0     0       0      0      0      0      0  \n",
       "4      1      0    0     0       0      1      1      0      1  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:17.030804Z",
     "start_time": "2019-07-03T17:39:15.701568Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "    .dataframe thead tr th {\n",
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       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">pos</th>\n",
       "      <th colspan=\"2\" halign=\"left\">AB1</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">PX179</th>\n",
       "      <th colspan=\"8\" halign=\"left\">RC301</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>chrom</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_I</th>\n",
       "      <td>37525.0</td>\n",
       "      <td>7.218341e+06</td>\n",
       "      <td>5.158361e+06</td>\n",
       "      <td>855.0</td>\n",
       "      <td>2183005.0</td>\n",
       "      <td>7098199.0</td>\n",
       "      <td>12356193.00</td>\n",
       "      <td>15066925.0</td>\n",
       "      <td>37525.0</td>\n",
       "      <td>0.140493</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>37525.0</td>\n",
       "      <td>0.154244</td>\n",
       "      <td>0.361187</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_II</th>\n",
       "      <td>72349.0</td>\n",
       "      <td>6.681606e+06</td>\n",
       "      <td>4.958754e+06</td>\n",
       "      <td>943.0</td>\n",
       "      <td>2256953.0</td>\n",
       "      <td>4148900.0</td>\n",
       "      <td>12162585.00</td>\n",
       "      <td>15276886.0</td>\n",
       "      <td>72349.0</td>\n",
       "      <td>0.150645</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>72349.0</td>\n",
       "      <td>0.379729</td>\n",
       "      <td>0.485323</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_III</th>\n",
       "      <td>55544.0</td>\n",
       "      <td>5.245251e+06</td>\n",
       "      <td>4.704111e+06</td>\n",
       "      <td>421.0</td>\n",
       "      <td>1213428.5</td>\n",
       "      <td>2891256.0</td>\n",
       "      <td>10549759.50</td>\n",
       "      <td>13780879.0</td>\n",
       "      <td>55544.0</td>\n",
       "      <td>0.211310</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>55544.0</td>\n",
       "      <td>0.351397</td>\n",
       "      <td>0.477411</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_IV</th>\n",
       "      <td>55174.0</td>\n",
       "      <td>8.960969e+06</td>\n",
       "      <td>6.147024e+06</td>\n",
       "      <td>23876.0</td>\n",
       "      <td>2745629.5</td>\n",
       "      <td>7467548.5</td>\n",
       "      <td>15246185.75</td>\n",
       "      <td>17492235.0</td>\n",
       "      <td>55174.0</td>\n",
       "      <td>0.177529</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>55174.0</td>\n",
       "      <td>0.003208</td>\n",
       "      <td>0.056549</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_V</th>\n",
       "      <td>107887.0</td>\n",
       "      <td>1.136630e+07</td>\n",
       "      <td>7.311525e+06</td>\n",
       "      <td>405.0</td>\n",
       "      <td>3346520.5</td>\n",
       "      <td>15112815.0</td>\n",
       "      <td>17526757.00</td>\n",
       "      <td>20922549.0</td>\n",
       "      <td>107887.0</td>\n",
       "      <td>0.138367</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>107887.0</td>\n",
       "      <td>0.036603</td>\n",
       "      <td>0.187786</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHROMOSOME_X</th>\n",
       "      <td>47664.0</td>\n",
       "      <td>9.602687e+06</td>\n",
       "      <td>5.077594e+06</td>\n",
       "      <td>5755.0</td>\n",
       "      <td>5178930.0</td>\n",
       "      <td>10091223.5</td>\n",
       "      <td>14221393.00</td>\n",
       "      <td>17718678.0</td>\n",
       "      <td>47664.0</td>\n",
       "      <td>0.185885</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>47664.0</td>\n",
       "      <td>0.204032</td>\n",
       "      <td>0.402997</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6 rows × 136 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     pos                                                  \\\n",
       "                   count          mean           std      min        25%   \n",
       "chrom                                                                      \n",
       "CHROMOSOME_I     37525.0  7.218341e+06  5.158361e+06    855.0  2183005.0   \n",
       "CHROMOSOME_II    72349.0  6.681606e+06  4.958754e+06    943.0  2256953.0   \n",
       "CHROMOSOME_III   55544.0  5.245251e+06  4.704111e+06    421.0  1213428.5   \n",
       "CHROMOSOME_IV    55174.0  8.960969e+06  6.147024e+06  23876.0  2745629.5   \n",
       "CHROMOSOME_V    107887.0  1.136630e+07  7.311525e+06    405.0  3346520.5   \n",
       "CHROMOSOME_X     47664.0  9.602687e+06  5.077594e+06   5755.0  5178930.0   \n",
       "\n",
       "                                                          AB1            ...  \\\n",
       "                       50%          75%         max     count      mean  ...   \n",
       "chrom                                                                    ...   \n",
       "CHROMOSOME_I     7098199.0  12356193.00  15066925.0   37525.0  0.140493  ...   \n",
       "CHROMOSOME_II    4148900.0  12162585.00  15276886.0   72349.0  0.150645  ...   \n",
       "CHROMOSOME_III   2891256.0  10549759.50  13780879.0   55544.0  0.211310  ...   \n",
       "CHROMOSOME_IV    7467548.5  15246185.75  17492235.0   55174.0  0.177529  ...   \n",
       "CHROMOSOME_V    15112815.0  17526757.00  20922549.0  107887.0  0.138367  ...   \n",
       "CHROMOSOME_X    10091223.5  14221393.00  17718678.0   47664.0  0.185885  ...   \n",
       "\n",
       "               PX179          RC301                                          \\\n",
       "                 75%  max     count      mean       std  min  25%  50%  75%   \n",
       "chrom                                                                         \n",
       "CHROMOSOME_I     0.0  1.0   37525.0  0.154244  0.361187  0.0  0.0  0.0  0.0   \n",
       "CHROMOSOME_II    0.0  1.0   72349.0  0.379729  0.485323  0.0  0.0  0.0  1.0   \n",
       "CHROMOSOME_III   0.0  1.0   55544.0  0.351397  0.477411  0.0  0.0  0.0  1.0   \n",
       "CHROMOSOME_IV    0.0  1.0   55174.0  0.003208  0.056549  0.0  0.0  0.0  0.0   \n",
       "CHROMOSOME_V     0.0  1.0  107887.0  0.036603  0.187786  0.0  0.0  0.0  0.0   \n",
       "CHROMOSOME_X     0.0  1.0   47664.0  0.204032  0.402997  0.0  0.0  0.0  0.0   \n",
       "\n",
       "                     \n",
       "                max  \n",
       "chrom                \n",
       "CHROMOSOME_I    1.0  \n",
       "CHROMOSOME_II   1.0  \n",
       "CHROMOSOME_III  1.0  \n",
       "CHROMOSOME_IV   1.0  \n",
       "CHROMOSOME_V    1.0  \n",
       "CHROMOSOME_X    1.0  \n",
       "\n",
       "[6 rows x 136 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders.groupby('chrom').describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Deleting the same SNPs in genetic data and recalculate linkage***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`linkage` = vector of the recombination probabilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:18.631417Z",
     "start_time": "2019-07-03T17:39:17.035727Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(37525, 6)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders_pos_ch1 = founders.pos[founders.chrom == 'CHROMOSOME_I'].values\n",
    "geneticDF_ch1_reduced = geneticDF_ch1[[p in founders_pos_ch1 for p in geneticDF_ch1.pos]]\n",
    "geneticDF_ch1_reduced.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:18.676879Z",
     "start_time": "2019-07-03T17:39:18.639058Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0., 0., 0., ..., 0., 0., 0.])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(37525,)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.0020163750209577815"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.999999999999998"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "linkage = np.diff(geneticDF_ch1_reduced.genetic_scaled)\n",
    "linkage/=sum(linkage)\n",
    "linkage = np.append([0], linkage)\n",
    "display(linkage,linkage.shape,max(linkage),sum(linkage))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:18.690914Z",
     "start_time": "2019-07-03T17:39:18.682909Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Linkage_p{}.pkl\".format(linkage.shape[0]),\"wb\") as handler:\n",
    "    pickle.dump(linkage, handler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:21.395410Z",
     "start_time": "2019-07-03T17:39:18.693873Z"
    }
   },
   "outputs": [],
   "source": [
    "linkage_smooth = []\n",
    "pos_smooth = []\n",
    "l = 2000000\n",
    "m=max(geneticDF_ch1_reduced.pos)\n",
    "points=1000\n",
    "for k in range (l//2,m-l//2,m//points):\n",
    "    window=np.logical_and(k-l//2<geneticDF_ch1_reduced.pos,geneticDF_ch1_reduced.pos<k+l//2)\n",
    "    linkage_smooth.append(np.mean(linkage[window]))\n",
    "    pos_smooth.append(np.median(geneticDF_ch1_reduced.pos[window]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:24.159518Z",
     "start_time": "2019-07-03T17:39:21.400249Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2, ax3) = plt.subplots (1,3, figsize = (20, 6))\n",
    "fig.suptitle(\"Recombination frequencies for chromosome I\")\n",
    "ax1.scatter(geneticDF_ch1_reduced.pos, geneticDF_ch1_reduced.genetic_scaled)\n",
    "ax1.set(xlabel = \"Physical position\", ylabel = \"Genetic position\")\n",
    "ax2.scatter(geneticDF_ch1_reduced.pos, linkage,alpha=0.5,marker=\"x\")\n",
    "ax2.set(xlabel = \"Physical position\", ylabel = \"Linkage (recombination proba.)\", ylim = (0,0.002))\n",
    "ax3.plot(pos_smooth, [l*10**5 for l in linkage_smooth])\n",
    "ax3.set(xlabel = \"Physical position\", ylabel = \"Smoothed linkage (x10^-5)\")\n",
    "plt.tight_layout(rect = [0, 0, 0.95, 0.95])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\to$ Same results as previously."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Extract chromosome I***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We only keep chromosome I as a case study."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:24.259505Z",
     "start_time": "2019-07-03T17:39:24.162608Z"
    }
   },
   "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>chrom</th>\n",
       "      <th>pos</th>\n",
       "      <th>AB1</th>\n",
       "      <th>CB4507</th>\n",
       "      <th>CB4852</th>\n",
       "      <th>CB4855</th>\n",
       "      <th>CB4856</th>\n",
       "      <th>CB4858</th>\n",
       "      <th>JU319</th>\n",
       "      <th>JU345</th>\n",
       "      <th>JU400</th>\n",
       "      <th>MY1</th>\n",
       "      <th>MY16</th>\n",
       "      <th>N2.ANC</th>\n",
       "      <th>PB306</th>\n",
       "      <th>PX174</th>\n",
       "      <th>PX179</th>\n",
       "      <th>RC301</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>855</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1222</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1291</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1713</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1761</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          chrom   pos  AB1  CB4507  CB4852  CB4855  CB4856  CB4858  JU319  \\\n",
       "0  CHROMOSOME_I   855    0       0       0       1       1       1      1   \n",
       "1  CHROMOSOME_I  1222    0       0       0       0       1       0      0   \n",
       "2  CHROMOSOME_I  1291    0       0       0       0       0       0      0   \n",
       "3  CHROMOSOME_I  1713    0       0       0       0       1       0      0   \n",
       "4  CHROMOSOME_I  1761    0       0       0       1       0       1      1   \n",
       "\n",
       "   JU345  JU400  MY1  MY16  N2.ANC  PB306  PX174  PX179  RC301  \n",
       "0      1      0    0     1       0      1      1      0      1  \n",
       "1      0      0    0     0       0      0      0      0      0  \n",
       "2      0      0    0     1       0      0      0      0      0  \n",
       "3      0      0    0     0       0      0      0      0      0  \n",
       "4      1      0    0     0       0      1      1      0      1  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders[founders.chrom=='CHROMOSOME_I'][:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:24.361679Z",
     "start_time": "2019-07-03T17:39:24.265403Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(37525, 16)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders_ch1 = founders[founders.chrom=='CHROMOSOME_I'].values[:,2:]\n",
    "np.shape(founders_ch1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:28.527248Z",
     "start_time": "2019-07-03T17:39:24.365567Z"
    },
    "hide_input": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "im, ax = plt.subplots(16,1, figsize = (15,10))\n",
    "ax[0].set(title = \"Genotypes of the 16 founders\")\n",
    "for k in range (16):\n",
    "    ax[k].imshow (np.expand_dims(founders_ch1.T.astype(int)[k],1).T, aspect = 700)\n",
    "    ax[k].set(ylabel = \"F{}\".format(k+1))\n",
    "ax[15].set(xlabel = \"{} SNPs (purple = identical to the founder F12/N2, yellow = different)\".format(p))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1015 SNPs from ch. I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:28.542704Z",
     "start_time": "2019-07-03T17:39:28.532121Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from numpy.random import choice\n",
    "import random as rd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import copy \n",
    "import pickle\n",
    "from pprint import pprint\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:28.559877Z",
     "start_time": "2019-07-03T17:39:28.547945Z"
    }
   },
   "outputs": [],
   "source": [
    "SMALL_SIZE = 7\n",
    "MEDIUM_SIZE = 15\n",
    "BIGGER_SIZE = 20\n",
    "\n",
    "plt.rc('font', size=SMALL_SIZE)          # controls default text sizes\n",
    "plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize\n",
    "plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Import genetic data** (linkage) as a dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:29.083036Z",
     "start_time": "2019-07-03T17:39:28.565565Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          chrom   pos ref alt  genetic\n",
      "0  CHROMOSOME_I   855   G   C      0.0\n",
      "1  CHROMOSOME_I  1222   A   C      0.0\n",
      "2  CHROMOSOME_I  1291   G   T      0.0\n",
      "3  CHROMOSOME_I  1713   T   G      0.0\n",
      "4  CHROMOSOME_I  1761   G   A      0.0\n",
      "5  CHROMOSOME_I  1799   T   C      0.0\n",
      "6  CHROMOSOME_I  1902   C   G      0.0\n",
      "7  CHROMOSOME_I  1933   C   G      0.0\n",
      "8  CHROMOSOME_I  2618   T   A      0.0\n",
      "9  CHROMOSOME_I  2622   T   A      0.0\n"
     ]
    }
   ],
   "source": [
    "geneticDF = pd.read_csv(\"./Donnees_supplementaires/WS220.founder.bsqr.calls.genetic.txt\", delimiter=\"\\t\")\n",
    "pprint(geneticDF[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Keep only the chromosome 1 and rescale genetic distance between 0 and 50."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:29.181182Z",
     "start_time": "2019-07-03T17:39:29.087690Z"
    }
   },
   "outputs": [],
   "source": [
    "geneticDF_ch1 = geneticDF[geneticDF.chrom == \"CHROMOSOME_I\"]\n",
    "\n",
    "pd.options.mode.chained_assignment = None\n",
    "s = 50/max(geneticDF_ch1.genetic)\n",
    "geneticDF_ch1[\"genetic_scaled\"] = [s*g for g in geneticDF_ch1.genetic]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:31.994859Z",
     "start_time": "2019-07-03T17:39:29.185940Z"
    }
   },
   "outputs": [],
   "source": [
    "callsF3DF = pd.read_csv(\"./Donnees_supplementaires/WS220.founder.bsqr.calls.F3.clean\", delimiter=\"\\t\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***The 16 founders***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:32.012538Z",
     "start_time": "2019-07-03T17:39:31.999698Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['AB1', 'CB4507', 'CB4852', 'CB4855', 'CB4856', 'CB4858', 'JU319', 'JU345', 'JU400', 'MY1', 'MY16', 'N2.ANC', 'PB306', 'PX174', 'PX179', 'RC301']\n"
     ]
    }
   ],
   "source": [
    "print(list(callsF3DF.columns[18:]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Deleting all 0.5 SNP data and extracting only positions and SNPs for the 16 founders*** : loss of 7% of the SNPs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:32.697508Z",
     "start_time": "2019-07-03T17:39:32.016685Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(404536, 376143, 0.0701865841358989)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders = callsF3DF[['chrom','pos']+list(callsF3DF.columns[18:])][callsF3DF[['chrom','pos']+list(callsF3DF.columns[18:])]!=0.5].dropna(how='any')\n",
    "len(callsF3DF),len(founders),(len(callsF3DF)-len(founders))/len(callsF3DF)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Convert floats into integers***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:33.033904Z",
     "start_time": "2019-07-03T17:39:32.702213Z"
    }
   },
   "outputs": [],
   "source": [
    "founders[list(founders.columns[2:])] = founders[list(founders.columns[2:])].astype(int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Deleting the same SNPs in genetic data and recalculate linkage***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`linkage` = vector of the recombination probabilities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:33.490557Z",
     "start_time": "2019-07-03T17:39:33.038154Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1015, 6)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.arange(37525)\n",
    "founders_pos_ch1_1015 = founders.pos[founders.chrom == 'CHROMOSOME_I'][A//37==A/37].values\n",
    "geneticDF_ch1_reduced_1015 = geneticDF_ch1[[p in founders_pos_ch1_1015 for p in geneticDF_ch1.pos]]\n",
    "geneticDF_ch1_reduced_1015.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:33.520955Z",
     "start_time": "2019-07-03T17:39:33.494513Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ..., 6.9132966e-11,\n",
       "       7.1160855e-12, 0.0000000e+00])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(1015,)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.014377850379652984"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "0.9999999999999996"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "linkage = np.diff(geneticDF_ch1_reduced_1015.genetic_scaled)\n",
    "linkage/=sum(linkage)\n",
    "linkage = np.append([0], linkage)\n",
    "display(linkage,linkage.shape,max(linkage),sum(linkage))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:33.774493Z",
     "start_time": "2019-07-03T17:39:33.525202Z"
    },
    "hide_input": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1152x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "im, ax = plt.subplots (1,1, figsize = (16,3))\n",
    "ax.imshow(np.expand_dims(linkage,0), aspect = 30)\n",
    "ax.set (xlabel = \"SNPs\", title = \"Linkage\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***Save a copy of the linkage***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:33.792844Z",
     "start_time": "2019-07-03T17:39:33.780918Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Linkage_p{}.pkl\".format(linkage.shape[0]),\"wb\") as handler:\n",
    "    pickle.dump(linkage, handler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:34.044923Z",
     "start_time": "2019-07-03T17:39:33.804520Z"
    }
   },
   "outputs": [],
   "source": [
    "linkage_smooth = []\n",
    "pos_smooth = []\n",
    "l = 2000000\n",
    "m=max(geneticDF_ch1_reduced_1015.pos)\n",
    "points=100\n",
    "for k in range (l//2,m-l//2,m//points):\n",
    "    window=np.logical_and(k-l//2<geneticDF_ch1_reduced_1015.pos,geneticDF_ch1_reduced_1015.pos<k+l//2)\n",
    "    linkage_smooth.append(np.mean(linkage[window]))\n",
    "    pos_smooth.append(np.median(geneticDF_ch1_reduced_1015.pos[window]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:35.743756Z",
     "start_time": "2019-07-03T17:39:34.059108Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2, ax3) = plt.subplots (1,3, figsize = (20, 6))\n",
    "fig.suptitle(\"Recombination frequencies for chromosome I\")\n",
    "ax1.scatter(geneticDF_ch1_reduced_1015.pos, geneticDF_ch1_reduced_1015.genetic_scaled)\n",
    "ax1.set(xlabel = \"Physical position\", ylabel = \"Genetic position\")\n",
    "ax2.scatter(geneticDF_ch1_reduced_1015.pos, linkage, alpha=0.5, marker=\"x\")\n",
    "ax2.set(xlabel = \"Physical position\", ylabel = \"Linkage (recombination proba.)\", ylim = (0,0.002))\n",
    "ax3.plot(pos_smooth, [l*10**5 for l in linkage_smooth])\n",
    "ax3.set(xlabel = \"Physical position\", ylabel = \"Smoothed linkage (x10^-5)\")\n",
    "plt.tight_layout(rect = [0, 0, 0.95, 0.95])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\to$ Same results as previously."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:36.046923Z",
     "start_time": "2019-07-03T17:39:35.749222Z"
    }
   },
   "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>chrom</th>\n",
       "      <th>pos</th>\n",
       "      <th>AB1</th>\n",
       "      <th>CB4507</th>\n",
       "      <th>CB4852</th>\n",
       "      <th>CB4855</th>\n",
       "      <th>CB4856</th>\n",
       "      <th>CB4858</th>\n",
       "      <th>JU319</th>\n",
       "      <th>JU345</th>\n",
       "      <th>JU400</th>\n",
       "      <th>MY1</th>\n",
       "      <th>MY16</th>\n",
       "      <th>N2.ANC</th>\n",
       "      <th>PB306</th>\n",
       "      <th>PX174</th>\n",
       "      <th>PX179</th>\n",
       "      <th>RC301</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>855</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1222</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1291</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1713</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CHROMOSOME_I</td>\n",
       "      <td>1761</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          chrom   pos  AB1  CB4507  CB4852  CB4855  CB4856  CB4858  JU319  \\\n",
       "0  CHROMOSOME_I   855    0       0       0       1       1       1      1   \n",
       "1  CHROMOSOME_I  1222    0       0       0       0       1       0      0   \n",
       "2  CHROMOSOME_I  1291    0       0       0       0       0       0      0   \n",
       "3  CHROMOSOME_I  1713    0       0       0       0       1       0      0   \n",
       "4  CHROMOSOME_I  1761    0       0       0       1       0       1      1   \n",
       "\n",
       "   JU345  JU400  MY1  MY16  N2.ANC  PB306  PX174  PX179  RC301  \n",
       "0      1      0    0     1       0      1      1      0      1  \n",
       "1      0      0    0     0       0      0      0      0      0  \n",
       "2      0      0    0     1       0      0      0      0      0  \n",
       "3      0      0    0     0       0      0      0      0      0  \n",
       "4      1      0    0     0       0      1      1      0      1  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders[founders.chrom=='CHROMOSOME_I'][:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:36.113700Z",
     "start_time": "2019-07-03T17:39:36.050403Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1015, 16)"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "founders_ch1_1015 = founders[founders.chrom=='CHROMOSOME_I'][A//37==A/37].values[:,2:]\n",
    "np.shape(founders_ch1_1015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:39:38.611167Z",
     "start_time": "2019-07-03T17:39:36.117270Z"
    },
    "hide_input": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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R7yHg/GHEcAPw+5L+GrhZ0qKs/MvAJcBlwKXDaNfMzMzMzMwKWp4JjIjrgetr1HsYOK/dALIzjCflihZn5Q8AJ7TbnpmZmZmZmTXX8kygpO9KmlEoOzi7q6eZmZmZmZltR+oMBz0EmNx4IWk88D1gRtM1zMzMzMzMrCfVuTFMmTrTRdRvrPlcgQuANwHrgfMjYs1obtfMzMzMzGzQ1DkT2AmNuQJPAQ7PlW8idQxfBjZ0IzAzMzMzM7N+oojqmRUkbQEOiIi7s9fjSZ2y/SPi3lEJQjoTuDUiVki6LiLmZOXjImKLpMOBvSPiksJ684B52csZwFPAutGIyWyU7IJz0nqH89F6jXPSeo1z0npNuzm5V0Ts2qpS3eGgSyVtKpT9oKSMiJhas8280rkCI2JL9vRJYGbJtl6ZJxBA0vKImDWM7ZuNCeek9RLno/Ua56T1Guek9Zqxysk6ncC2p30YhhuAyyQdRjZXYETMlfQpYA9SD/i0DsRhZmZmZmbW1+rMEzjmncCKuQI/N9bbNjMzMzMzGyS9cmOY0bKwdRWzjnJOWi9xPlqvcU5ar3FOWq8Zk5xseWMYMzMzMzMz6x/9dibQzMzMzMzMKrgTaGZmZmZmNkDqThHR0yRNBC4nTSx/e0Qs7nJINkAkvR84DJgKfAXYF9gH2AGYD+wGXARsBq6OiGVdCtUGSPa5eAdwLmkeVeekdY2kccCngUnActJ8wwcBrwI+nFXz97h1jKQ9gctI8689CjyOc9K6QNLrgLOAyRFxtKQ5tMjFYp3sJpvtbbcfrgmUNBfYEBE3S7o+Io7pdkw2eCRNAb4I7BgRx0n6KPAT4EDgRuBB4NqImNO9KG1QSDofeA54GDjGOWndJOlI4AjgaeAWYH5EfEDSbGBKVs3f49Yxkg4BXh8RV0j6BrCTc9K6SdKSrBP4rVa5WKwTEYva3V6/DAedBqzKnm/uZiA20M4GrgLWZq9XknJzGrAqIrZ0KzAbLNkfNw8BTwCTcU5a980A7oqIj5P+s934D/SQnMzK/D1unXAvcKyk24BlOCetd9TJxWKdtvVLJ3A1Ww9Av+yTbSeUfB64Fbgb2CVbtCcpN1cD07LhUGadcBDwdmBO9pialTsnrVtWA+uz5/k/qIfkZFbmvLROOAk4NyIOJl3S0eCctF5RJxcbddrWL8NBJ5LGdb8A3Olx29ZJkk4DTiB1AFcAE4C92DqWezfgQmATaejdbV0K1QaMpBNJ17tMxzlpXSRpAnApsBH4KalD+C5gJ+DUrJq/x61jJM0EFpA+I38B/BjnpHWBpJ2BzwKHkkaUraRFLmbXBL5SZ2CvCTQzMzMzM7N6fHrbzMzMzMxsgLgTaGZmZmZmNkC6Pk+gpN1pMl+VpGtI16xsAk6PiBe7EqSZmZmZmVmf6IUzgR8i3aDgROCUwrLnSbdA3UCaWNbMzMzMzMxGoKNnAiXtC1xQKF5LNl+VpOIqp2blpwGzgZsK7c0D5gGMZ/z+E5g0NoGbmZltZ6bvt5FH75vQ7TDMzKyDnmX9uojYtVW9jnYCI+J+UmfuFZLOIc1X9fOS+o2JjJ8EXlOyfCGwEGCSfiUO0HtGPWYzM7Pt0dKlK3jf7m/pdhhmZtZB348lK+vU6/o1gcBX2Tpf1VUAkhZFxFxJF5Pmv5gCnNy9EM3MzMzMzPpD1zuBEbEGOL5QNjf7eUZXgjIzMzMzM+tTtW4MI+nXJZ0j6VJJ8yVNKanzJkm3jX6IZmZmZmZmNlpadgIl/QZwP/DnwEHAl4BHJR1eqDoJ+J1Rj9DMzMzMzMxGTZ0zgZ8HHgH2jIiZwB7ArcANkj4+0gAkTZT0dUlXSjouVz5T0uLsMXOk2zEzMzMzM7N6ncB3AJ+LiPUAEbE2Io4HPgZ8XtKXRxjDUcCSiDgFyJ9dPB04FfhIti0zMzMzMzMboTo3htkJ2FgsjIi/lvRfwN9K2h24bJgxTCMNNwXYnCufHBEbACS9tmzF/DyBr8ZzIZmZmZmZmbVS50zgI8C7yhZExE3AocDBwNeHGcNqUkewGM8zkiZLmgQ822T7CyNiVkTM2oFXDXPzZmZmZmZmg6NOJ/A7wMmSSntZEfEvwLuB8cOM4Qbg9yX9NXCzpEVZ+ZeBS0hnGC8dZttmZmZmZmaWU2c46EXAN6noMEbEg5LeCvyvdgOIiOeAk3JFi7PyB4AT2m3PzMzMzMzMmqtzJvAGYFNEPN8okHSwpIn5StkNY3442gGamZmZmZnZ6KnTCTwEmNx4IWk88D1gxlgFZWZmZmZmZmOjTiewjEY1CjMzMzMzM+uIOtcEjrlsaOnlwEvA7RGxOCtfALwJWA+cHxFruhakmZmZmZlZH6jbCYyaZcPVmDD+ZknXk90cBthE6hi+DGworpSfJxD4xfdjyVPAulGMy2ykdsE5ab3D+ThAxu8G8LNuh9GKc9J6jXPSek27OblXnUqKqO7LSdpC6oBtKgRTLAMgIqbWj/GVbZwJ3BoRKyRdFxFzsvJxEbFF0uHA3hFxSYt2lkfErHa3bzZWnJPWS5yP1muck9ZrnJPWa8YqJ+ucCTxvtDdaojFh/Apy1ylGxJbs6ZPAzA7EYWZmZmZm1tdadgIjohOdwBuAyyQdRjZhfETMlfQpYA/SmcfTOhCHmZmZmZlZX+uJG8NUTBj/uTabWjhqQZmNDuek9RLno/Ua56T1Guek9ZoxycmW1wSamZmZmZlZ/xjuPIFmZmZmZma2HXIn0MzMzMzMbID0xDWBI9VssnmzTpD0fuAwYCrwFWBfYB9gB2A+sBtwEbAZuDoilnUpVBsg2efiHcC5wAyck9ZFksYBnwYmActJ8/8eBLwK+HBWzd/j1jGS9gQuI82/9ijwOM5J6wJJrwPOAiZHxNGS5tAiF4t1svurtLfdfrgmUNJcYENjsvmIOKbbMdngkTQF+CKwY0QcJ+mjwE+AA4EbgQeBaxvzYJqNJUnnA88BDwPHOCetmyQdCRwBPA3cAsyPiA9Img1Myar5e9w6RtIhwOsj4gpJ3wB2ck5aN0laknUCv9UqF4t1ImJRu9vrl+Gg04BV2fPN3QzEBtrZwFXA2uz1SlJuTgNW5ea9NBtT2R83DwFPAJNxTlr3zQDuioiPk/6z3fgP9JCczMr8PW6dcC9wrKTbgGU4J6131MnFYp229UsnsDHZPPTPPtl2QsnngVuBu0nzWgLsScrN1cC0bDiUWSccBLwdmJM9pmblzknrltXA+ux5/g/qITmZlTkvrRNOAs6NiINJl3Q0OCetV9TJxUadtvXLcNCJpHHdLwB3ety2dZKk04ATSB3AFcAEYC+2juXeDbgQ2EQaendbl0K1ASPpRNL1LtNxTloXSZoAXApsBH5K6hC+C9gJODWr5u9x6xhJM4EFpM/IXwA/xjlpXSBpZ+CzwKGkEWUraZGL2TWBr9QZ2GsCzczMzMzMrB6f3jYzMzMzMxsg7gSamZmZmZkNkK7PEyhpd5rMVyXpGtI1K5uA0yPixa4EaWZmZmZm1id64Uzgh0g3KDgROKWw7HnSLVA3kCaWNTMzMzMzsxHo6JlASfsCFxSK15LNVyWpuMqpWflpwGzgpkJ784B5AOMZv/8EJtWOZfp+G3n0vgmjVs/MelPVe7ixrPizWd2GRt0if1b4M7MbfMzNtk9+79poyefSs6xfFxG7tlqn63cHlXQO8G3SxMbXRsSckjrHAuMi4rpm7UzSr8QBek/t7S5ds4L37f6WUatnZr2p6j3cWFb82axuQ6NukT8r/JnZDT7mZtsnv3dttORz6fux5J6ImNVqna5fEwh8la3zVV0FIGlRRMyVdDFp/ospwMndC9HMzMzMzKw/dL0TGBFrgOMLZXOzn2d0JSgzMzMzM7M+VevGMJLeJulLki6XtH9W9m5Jt0t6XNIPJb1vbEM1MzMzMzOzkWrZCZT0HuBO4EjgncAdkmYDt5KGcF5POqP4D5LeNoaxmpmZmZmZ2QjVGQ76F6S7cn4wu1PnnwDXAUsi4oRGJUk3AWcDh49JpGZmZmZmZjZidYaD7gt8NSK2ZK+/DrwGWFyodw3Q9i2OJE2U9HVJV0o6Llc+U9Li7DGz3XbNzMzMzMxsW3U6gTsAL+VeP5P9XFeo9xTQck6KEkeRziqewtCziKcDpwIfAT5WtqKkeZKWS1r+Mi8OY9NmZmZmZmaDpU4ncDUwo/EiIjYDfwD8R6HenqSJ39s1DViVPd+cK58cERsi4hngtWUrRsTCiJgVEbN24FXD2LSZmZmZmdlgqdMJ/CHwW/mCiLg+65zlHQX86zBiWE3qCBbjeUbSZEmTgGeH0a6ZmZmZmZkVtLwxTETMr9nWxWw9o9eOG4DLJB0G3NyYKB74MnAJIOALw2jXzMzMzMzMClp2AiV9F/hYRDySKzsY+FFEPNcoi4g7hxNA1sZJuaLFWfkDwAmlK5mZmZmZmdmw1BkOeggwufFC0njge+SuEzQzMzMzM7PtQ51OYBmNahRmZmZmZmbWEXUmix9zkiYCl5Omorg9IhZn5QuANwHrgfMjYk3XgjQzMzMzM+sDiojqCtIW4ICIuDt7PR54Gdg/Iu4dlSCkucCGiLhZ0vURcUxWfjZp2OkG4BMRsbGw3jxgXvZyBmmuwuL8hWbdtAvOSesdzkfrNc5J6zXOSes17ebkXhHRcu72up3ADcCmQjDFMgAiYmobQTa2cSZwa0SskHRdRMzJysdFxBZJhwN7R8QlLdpZHhGz2t2+2VhxTlovcT5ar3FOWq9xTlqvGaucrDMc9LzR3miJxlyBK8hdpxgRW7KnTwIzOxCHmZmZmZlZX6szT2AnOoGlcwVK+hSwB+nM42kdiMPMzMzMzKyv9cSNYSrmCvxcm00tHLWgzEaHc9J6ifPReo1z0nqNc9J6zZjkZMtrAs3MzMzMzKx/DHeeQDMzMzMzM9sOuRNoZmZmZmY2QHrimsCRajbZvFknSHo/cBgwFfgKsC+wD7ADMB/YDbgI2AxcHRHLuhSqDZDsc/EO4FzSPKrOSesaSeOATwOTgOWk+YYPAl4FfDir5u9x6xhJewKXkeZfexR4HOekdYGk1wFnAZMj4mhJc2iRi8U62f1V2ttuP1wT2GyyebNOkjQF+CKwY0QcJ+mjwE+AA4EbgQeBaxvzYJqNJUnnA88BDwPHOCetmyQdCRwBPA3cAsyPiA9Img1Myar5e9w6RtIhwOsj4gpJ3wB2ck5aN0laknUCv9UqF4t1ImJRu9vrl+Gg04BV2fPN3QzEBtrZwFXA2uz1SlJuTgNW5ea9NBtT2R83DwFPAJNxTlr3zQDuioiPk/6z3fgP9JCczMr8PW6dcC9wrKTbgGU4J6131MnFYp229UsnsDHZPPTPPtl2QsnngVuBu0nzWgLsScrN1cC0bDiUWSccBLwdmJM9pmblzknrltXA+ux5/g/qITmZlTkvrRNOAs6NiINJl3Q0OCetV9TJxUadtvXLcNCJpHHdLwB3ety2dZKk04ATSB3AFcAEYC+2juXeDbgQ2EQaendbl0K1ASPpRNL1LtNxTloXSZoAXApsBH5K6hC+C9gJODWr5u9x6xhJM4EFpM/IXwA/xjlpXSBpZ+CzwKGkEWUraZGL2TWBr9QZ2GsCzczMzMzMrB6f3jYzMzMzMxsg7gSamZmZmZkNEHcCzczMzMzMBkjXJ4uXtDtNJi2WdA3pxgWbgNMj4sWuBGlmZmZmZtYnut4JBD5Eukvdg8C1pLlaGp4nxbgBeLm4oqR5wDyAiRO0/xvfsCMAj943YUi96fttHFI+fb+NQ+oUX5et06o8306d9utsp6yNdtrKr9PQrI2qsvz6zfa9mWLcZTGWxVb1O6mqn2+/Wf0yZW20qlP1s7jvzWIoy8ni86p6Ze1WHZeq7RY1W1Z1fJqp2k5+eVW8Vfnd7H2XX7fqvdnO+6sYT3H/W+1r1TGpyqNW69SpW0erz6Rm77G6udLue8xa65VjVfX+aqiTN2XtleVlq/dLsziqYqzKvdHIzaq/IZrF36yNoqr9aLXd7V3dXOg120OMtn3I59KzrF8XEbu2WqejdweVtC9wQaF4LfAnEbFB0nURMSdXf1xEbMluwf9YRNzUrO1Zb351/NvSPQB43+5vGbJs6ZoVQ8qXrlmVqNCBAAAgAElEQVQxpE7xddk6rcrz7dRpv852ytpop638Og3N2qgqy6/fbN+bKcZdFmNZbFW/k6r6+fab1S9T1karOlU/i/veLIaynCw+r6pX1m7VcanablGzZVXHp5mq7eSXV8Vbld/N3nf5davem+28v4rxFPe/1b5WHZOqPGq1Tp26dbT6TGr2HqubK+2+x6y1XjlWVe+vhjp5U9ZeWV62er80i6MqxqrcG43crPoboln8zdooqtqPVtvd3tXNhV6zPcRo24d8Ln0/ltwTEbNardPRM4ERcT8wO18m6RzSpMU/L6m/JXv6JPCasY/QzMzMzMysv/XCcNCvsnXS4qsAJC2KiLmSLiZNgjgFOLl7IZqZmZmZmfWHEXUCJY0D3g7cHxHPDqeNiFgDHF8om5v9PGMk8ZmZmZmZmdlQI50i4rXAPwEe0GxmZmZmZrYdaHkmUNI3KxbvAAg4X9JagIj44CjFZmZmZmZmZqOsznDQo0k3Znm4Yv1fHm4AkiYClwMvAbdHxOKsfCZwZlbtgoh4YLjbMDMzMzMzs6ROJ/DjwDnA48AnI+K/Gwsk/TLwNGki9zuGGcNRwJKIuFnS9cDirPx04FQggC8AfzTM9s3MzMzMzCzT8prAiPgS8EbSZO0/lfQpSa9qLB6FGKYBq7Lnm3PlkyNiQ0Q8Q7r2cBuS5klaLmn52qc2l1UxMzMzMzOznFo3homItRFxMnAIcDipM/j7oxTDalJHsBjPM5ImS5oElN55NCIWRsSsiJi1687jRykcMzMzMzOz/tXWFBERcTfwdkl/CFxGGiI60rOBNwCXSToMuLkxRyDwZeAS0o1nvjDCbZiZmZmZmRnDnCcwIr4maQlwFrAGWDfcACLiOeCkXNHirPwB4IThtmtmZmZmZmbbajkcVNJ3Jc0olB0MbI6IT0TEkRHx0JhFaGZmZmZmZqOmzjWBhwCTGy8kjQe+B8xouoaZmZmZmZn1pGENByVdpzdqKuYKXAC8CVgPnB8Ra0Zzu2ZmZmZmZoOm1t1BO6AxV+AppLuPNmwidQxfBjZ0IzAzMzMzM7N+oojqm3tK2gIckN0ZtDEc9GVg/4i4d1SCkM4Ebo2IFZKui4g5Wfm4iNgi6XBg74i4pLDePGBe9nIG8BQjuEmN2RjYBeek9Q7no/Ua56T1Guek9Zp2c3KviNi1VaW6w0GXStpUKPtBSRkRMbVmm3mNuQJXkDs7GRFbsqdPAjNLtrUQWNh4LWl5RMwaxvbNxoRz0nqJ89F6jXPSeo1z0nrNWOVknU7geaO90RKlcwVK+hSwB6kHfFoH4jAzMzMzM+trLTuBETHmncCKuQI/N9bbNjMzMzMzGyS9cmOY0bKwdRWzjnJOWi9xPlqvcU5ar3FOWq8Zk5xseWMYMzMzMzMz6x/9dibQzMzMzMzMKrgTaGZmZmZmNkDqThHR0yRNBC4nTSx/e0Qs7nJINkAkvR84DJgKfAXYF9gH2AGYD+wGXARsBq6OiGVdCtUGSPa5eAdwLmkeVeekdY2kccCngUnActJ8wwcBrwI+nFXz97h1jKQ9gctI8689CjyOc9K6QNLrgLOAyRFxtKQ5tMjFYp3sJpvtbbcfrgmUNBfYEBE3S7o+Io7pdkw2eCRNAb4I7BgRx0n6KPAT4EDgRuBB4NqImNO9KG1QSDofeA54GDjGOWndJOlI4AjgaeAWYH5EfEDSbGBKVs3f49Yxkg4BXh8RV0j6BrCTc9K6SdKSrBP4rVa5WKwTEYva3V6/DAedBqzKnm/uZiA20M4GrgLWZq9XknJzGrAqIrZ0KzAbLNkfNw8BTwCTcU5a980A7oqIj5P+s934D/SQnMzK/D1unXAvcKyk24BlOCetd9TJxWKdtvVLJ3A1Ww9Av+yTbSeUfB64Fbgb2CVbtCcpN1cD07LhUGadcBDwdmBO9pialTsnrVtWA+uz5/k/qIfkZFbmvLROOAk4NyIOJl3S0eCctF5RJxcbddrWL8NBJ5LGdb8A3Olx29ZJkk4DTiB1AFcAE4C92DqWezfgQmATaejdbV0K1QaMpBNJ17tMxzlpXSRpAnApsBH4KalD+C5gJ+DUrJq/x61jJM0EFpA+I38B/BjnpHWBpJ2BzwKHkkaUraRFLmbXBL5SZ2CvCTQzMzMzM7N6fHrbzMzMzMxsgLgTaGZmZmZmNkC6Pk+gpN1pMl+VpGtI16xsAk6PiBe7EqSZmZmZmVmf6IUzgR8i3aDgROCUwrLnSbdA3UCaWNbMzMzMzMxGoKNnAiXtC1xQKF5LNl+VpOIqp2blpwGzgZsK7c0D5gFMnKD9x2385VeWTd9v4yvPH71vwjav8/Uay5vVa7as2etie/nt5WPLt1+m2XrNYmsWb/F5s/1u1k6zGJrFPNw6Vb+HYvxl+1lsq6hYr24cZcegThxlx7Hsd1O3Ttk+NIu9jqrfe9l2W7VddsyLWrXd7JgX22j13ij7HVXFXfeYVanze222Tqv9zddv1lZZe60+W9qtW2dbzd7HrZYVt1cVUyt13rOjodXnT7vbaXV86rZb5zjn69Vpq079qu/ahrrfMc3eE+1+f9Z5D7aKr04et/O91s4xrbM/zT57qmJoto1W35PNfndVn+157Xx2tfsdPdz3eZ3v7zqfb1VtVX3XNotpJFp9r+TrFeNsFXNVTtfdt3bztc7xrnpeFXuzOq3iK1ve7POk1fu2SrOcrnqv3HPfi+siYtdWbXf97qCSzgG+TZrY+NqImFNS51hgXERc16ydWW9+dUy5//deeb10zYpXnr9v97ds8zpfr7G8Wb1my5q9LraX314+tnz7ZZqt1yy2ZvEWnzfb72btNIuhWczDrVP1eyjGX7afxbaKivXqxlF2DOrEUXYcy343deuU7UOz2Ouo+r2XbbdV22XHvKhV282OebGNVu+Nst9RVdx1j1mVOr/XZuu02t98/WZtlbXX6rOl3bp1ttXsfdxqWXF7VTG1Uuc9Oxpaff60u51Wx6duu3WOc75enbbq1K/6rm2o+x3T7D3R7vdnnfdgq/jq5HE732vtHNM6+9Pss6cqhmbbaPU92ex3V/XZntfOZ1e739HDfZ/X+f6u8/lW1VbVd22zmEai1fdKvl4xzlYxV+V03X1rN1/rHO+q51WxN6vTKr6y5c0+T1q9b6s0y+mq98r43X52T0TMatV2168JBL7K1vmqrgKQtCgi5kq6mDT/xRTg5O6FaGZmZmZm1h+63gmMiDXA8YWyudnPM7oSlJmZmZmZWZ9q2QmUtGNEvFQo2xP4Y+CtpBu3LAe+HBGrxyRKMzMzMzMzGxV17g76vKS3NV5kN3f5CXAS8AvgOdJQzXslTR+TKM3MzMzMzGxU1OkEFm/ZeRGwBnhjRMyOiNnAG4F1wGfaDUDSRElfl3SlpONy5TMlLc4eM9tt18zMzMzMzLY1nHkC3wV8NiKeaBRkzy8EDhpGe0cBSyLiFODwXPnpwKnAR4CPDaNdMzMzMzMzK6jbCSzOI7GypM5K4LXDiGEasCp7vjlXPjkiNkTEM83alTRP0nJJy9c+tbmsipmZmZmZmeXU7QReIOmbkr4JvAy8oaTOXsBTw4hhNakjWIznGUmTJU0Cni1bMSIWRsSsiJi1687jh7FpMzMzMzOzwVJniog7gPFAY+b5e4G9S+p9IFvWrhuAyyQdBtzcmCMQ+DJwCemaxC8Mo10zMzMzMzMraNkJjIgDa7Z1JsM4ExgRz5HuNNqwOCt/ADih3fbMzMzMzMysuZbDQSV9V9KMQtnBkibmyyLi/mzidzMzMzMzM+tRda4JPASY3HghaTzwPWBG0zXMzMzMzMysJw1nigjYdu5AMzMzMzMz2w7UuTHMmMuGll4OvATcHhGLs/IFwJuA9cD5Hm5qZmZmZmY2MoooTgFYqCBtAQ6IiLuz1+NJ00TsHxHDuRto2TbmAhsi4mZJ10fEMVn52aRhpxuAT0TExsJ684B52csZpBvTrBuNmMxGyS44J613OB+t1zgnrdc4J63XtJuTe0XErq0q1e0EbgA2FYIplgEQEVPbCLKxjTOBWyNihaTrImJOVj4uIrZIOhzYOyIuadHO8oiY1e72zcaKc9J6ifPReo1z0nqNc9J6zVjlZJ3hoOeN9kZLNCaMX0HuOsWI2JI9fRKY2YE4zMzMzMzM+lqdeQI70QksnTBe0qeAPUhnHk/rQBxmZmZmZmZ9rSduDFMxYfzn2mxq4agFZTY6nJPWS5yP1muck9ZrnJPWa8YkJ1teE2hmZmZmZmb9Y7jzBJqZmZmZmdl2yJ1AMzMzMzOzAdIT1wSOVLPJ5s06QdL7gcOAqcBXgH2BfYAdgPnAbsBFwGbg6ohY1qVQbYBkn4t3AOeS5lF1TlrXSBoHfBqYBCwnzTd8EPAq4MNZNX+PW8dI2hO4jDT/2qPA4zgnrQskvQ44C5gcEUdLmkOLXCzWye6v0t52++GawGaTzZt1kqQpwBeBHSPiOEkfBX4CHAjcCDwIXNuYB9NsLEk6H3gOeBg4xjlp3STpSOAI4GngFmB+RHxA0mxgSlbN3+PWMZIOAV4fEVdI+gawk3PSuknSkqwT+K1WuVisExGL2t1evwwHnQasyp5v7mYgNtDOBq4C1mavV5JycxqwKjfvpdmYyv64eQh4ApiMc9K6bwZwV0R8nPSf7cZ/oIfkZFbm73HrhHuBYyXdBizDOWm9o04uFuu0rV86gY3J5qF/9sm2E0o+D9wK3E2a1xJgT1JurgamZcOhzDrhIODtwJzsMTUrd05at6wG1mfP839QD8nJrMx5aZ1wEnBuRBxMuqSjwTlpvaJOLjbqtK1fhoNOJI3rfgG40+O2rZMknQacQOoArgAmAHuxdSz3bsCFwCbS0LvbuhSqDRhJJ5Kud5mOc9K6SNIE4FJgI/BTUofwXcBOwKlZNX+PW8dImgksIH1G/gL4Mc5J6wJJOwOfBQ4ljShbSYtczK4JfKXOwF4TaGZmZmZmZvX49LaZmZmZmdkAcSfQzMzMzMxsgHR9nkBJu9NkvipJ15CuWdkEnB4RL3YlSDMzMzMzsz7RC2cCP0S6QcGJwCmFZc+TboG6gTSxrJmZmZmZmY1AR88EStoXuKBQvJZsvipJxVVOzcpPA2YDNxXamwfMA5g4Qfu/8Q07AvDofROGNDJ9v41Dyqfvt3FIneLrsnValefbqdN+ne2UtdFOW/l1Gpq1UVWWX7/ZvjdTjLssxrLYqn4nVfXz7TerX6WqTrPtNYu76vjnX+frlj2vqlfWbtVxqdpuUbNlVcenmart5JdXxVuV383ed/l1q96b7by/ivEU97/VvlYdk6o8arVOnbp1tPpMavYeq5sr7b7HrLVeOVZV76+GOnlT1l5ZXrZ6vzSLoyrGqtwbjdys+huiWfzN2iiq2o9W293e1c2FXrM9xGjbh3wuPcv6dRGxa6t1un53UEnnAN8mTWx8bUTMKalzLDAuIq5r1s6sN786/m3pHgC8b/e3DFm2dM2KIeVL16wYUqf4umydVuX5duq0X2c7ZW2001Z+nYZmbVSV5ddvtu/NFOMui7EstqrfSVX9fPvN6lepqtNse83irjr++df5umXPq+qVtVt1XKq2W9RsWdXxaaZqO/nlVfFW5Xez911+3ar3Zjvvr2I8xf1vta9Vx6Qqj1qtU6duHa0+k5q9x+rmSrvvMWutV45V1furoU7elLVXlpet3i/N4qiKsSr3RiM3q/6GaBZ/szaKqvaj1Xa3d3VzoddsDzHa9iGfS9+PJfdExKxW63T9mkDgq2ydr+oqAEmLImKupItJ819MAU7uXohmZmZmZmb9YUSdQEmvAbZERPUYuwoRsQY4vlA2N/t5xkjiMzMzMzMzs6Fa3hhG0nslHVEomy9pJfAM8KykR7Mhm2ZmZmZmZtbD6twd9PPA6xsvJH0SuAz4PukM3gnAvwCLJBXv7mlmZmZmZmY9pM5w0OlA/irkU4HPRMSCXNm1kv4L+DPgytELz8zMzMzMzEZTnTOBLwATc69/FVhWUm8ZsGe7AUiaKOnrkq6UdFyufKakxdljZrvtmpmZmZmZ2bbqdAK/C8zPvf434L0l9d4L/McwYjgKWBIRpwCH58pPJ511/AjwsbIVJc2TtFzS8rVPbR7Gps3MzMzMzAZLneGgnwDukvRD4CvApcDfSNobuD2r8x7gaAp3+axpGnB/9jzfk5scERsAJL22bMWIWAgshDRP4DC2bWZmZmZmNlBadgIj4nFJBwB/CSzK1hHwB9kD4EHg6Ii4cRgxrCZ1BFcw9MzkM5ImAwE8O4x2zczMzMzMrKDWPIERsRo4VtIk4K3Ar5E6bE8DD0fEyhHEcANwmaTDgJsbE8UDXwYuIXU4vzCC9s3MzMzMzCzTshMo6bvAxyLikYj4OXC7pIOBH0XEcyMNIGvjpFzR4qz8AdL0E2ZmZmZmZjZK6twY5hBgcuOFpPHA94AZYxWUmZmZmZmZjY06ncAyGtUozMzMzMzMrCNqXRM41iRNBC4HXgJuj4jFWfkC4E3AeuD8iFjTtSDNzMzMzMz6gCKqZ1aQtAU4ICLuzl6PB14G9o+Ie0clCGkusCEibpZ0fUQck5WfTRp2ugH4RERsLKw3D5iXvZwBPAWsG42YzEbJLjgnrXc4H63XOCet1zgnrde0m5N7RcSurSrV7QRuADYVgimWARARU9sIsrGNM4FbI2KFpOsiYk5WPi4itkg6HNg7Ii5p0c7yiJjV7vbNxopz0nqJ89F6jXPSeo1z0nrNWOVkneGg5432RkuUzhUYEVuyp08CMzsQh5mZmZmZWV+rM1l8JzqBpXMFSvoUsAfpzONpHYjDzMzMzMysr/XEjWEq5gr8XJtNLRy1oMxGh3PSeonz0XqNc9J6jXPSes2Y5GTLawLNzMzMzMysfwx3nkAzMzMzMzPbDrkTaGZmZmZmNkB64prAkWo22bxZJ0h6P3AYMBX4CrAvsA+wAzAf2A24CNgMXB0Ry7oUqg2Q7HPxDuBc0jyqzknrGknjgE8Dk4DlpPmGDwJeBXw4q+bvcesYSXsCl5HmX3sUeBznpHWBpNcBZwGTI+JoSXNokYvFOtn9Vdrbbj9cE9hssnmzTpI0BfgisGNEHCfpo8BPgAOBG4EHgWsb82CajSVJ5wPPAQ8DxzgnrZskHQkcATwN3ALMj4gPSJoNTMmq+XvcOkbSIcDrI+IKSd8AdnJOWjdJWpJ1Ar/VKheLdSJiUbvb65fhoNOAVdnzzd0MxAba2cBVwNrs9UpSbk4DVuXmvTQbU9kfNw8BTwCTcU5a980A7oqIj5P+s934D/SQnMzK/D1unXAvcKyk24BlOCetd9TJxWKdtvVLJ7Ax2Tz0zz7ZdkLJ54FbgbtJ81oC7EnKzdXAtGw4lFknHAS8HZiTPaZm5c5J65bVwPrsef4P6iE5mZU5L60TTgLOjYiDSZd0NDgnrVfUycVGnbb1y3DQiaRx3S8Ad3rctnWSpNOAE0gdwBXABGAvto7l3g24ENhEGnp3W5dCtQEj6UTS9S7TcU5aF0maAFwKbAR+SuoQvgvYCTg1q+bvcesYSTOBBaTPyF8AP8Y5aV0gaWfgs8ChpBFlK2mRi9k1ga/UGdhrAs3MzMzMzKwen942MzMzMzMbIO4EmpmZmZmZDRB3As3MzMzMzAZI1yeLl7Q7TSYtlnQN6cYFm4DTI+LFrgRpZmZmZmbWJ7reCQQ+RLpL3YPAtaS5WhqeJ8W4AXi5uKKkecA8gIkTtP8b37AjAI/eN2FIven7bRxSPn2/jUPqNF7ny4vrNGuruKzYTlV5q+3UbaPVfjbKG8uaxVFVVmyjrmLcZTGWxVZ1rKrq59tvVb9MnWV1fhb3f1AM2v6WqcrBhrL3Qn79svdtfllZ/X5SZ5/K3t9ly0b6GdYqtrqfBcNpu+7y0cyBbuRTVa7X+Y5s97jU+d6p+93SKgazKs6bsTcoxzi/n8+yfl1E7NpqnY7eHVTSvsAFheK1wJ9ExAZJ10XEnFz9cRGxJbsF/2MRcVOztme9+dXxb0v3AOB9u79lyLKla1YMKV+6ZsWQOo3X+fLiOs3aKi4rtlNV3mo7ddtotZ+N8sayZnFUlRXbqKsYd1mMZbFVHauq+vn2W9UvU2dZnZ/F/R8Ug7a/ZapysKHsvZBfv+x9m19WVr+f1Nmnsvd32bKRfoa1iq3uZ8Fw2q67fDRzoBv5VJXrdb4j2z0udb536n63tIrBrIrzZuwNyjHO7+f3Y8k9ETGr1TodPRMYEfcDs/Nlks4hTVr885L6W7KnTwKvGfsIzczMzMzM+lsvDAf9KlsnLb4KQNKiiJgr6WLSJIhTgJO7F6KZmZmZmVl/6HonMCLWAMcXyuZmP8/oSlBmZmZmZmZ9quUUEZIelnSxpJZjS83MzMzMzKy31ZkncAbwMeBHkn4m6XxJvznGcZmZmZmZmdkYqDtZ/KHAscB9wJ8C90m6T9InJe0zkgAkTZT0dUlXSjouVz5T0uLsMXMk2zAzMzMzM7Okbifw+Yj4VkQcBfwqcBKwGjgf+JmkuyR9TNKvDSOGo4AlEXEKcHiu/HTgVOAjpDORZmZmZmZmNkJ1O4GviIhnI+IbEfG7wK+ROmkvAH8FrBpGDNNy623OlU+OiA0R8Qzw2rIVJc2TtFzS8rVPbS6rYmZmZmZmZjltdwLzIuLpiLgiIg4C9iQNFW3XalJHsBjPM5ImS5oEPNtk+wsjYlZEzNp15/HD2LSZmZmZmdlgGbUpIrKpHr48jFVvAC6TdBhwc2OOwKytSwABXxitOM3MzMzMzAZZnU7gPsCasQogIp4jXWPYsDgrfwA4Yay2a2ZmZmZmNojqDAe9EnhdvkDSwZImjk1IZmZmZmZmNlbqdAIPASY3XkgaD3yPNH+gmZmZmZmZbUeGe02gRjOI7Kzi5cBLwO0RsTgrXwC8CVgPnJ9dd2hmZmZmZmbDNKK7g46iZnMFbiJ1DF8GNnQjMDMzMzMzs36iiKiuIG0BDoiIu7PX40mdsv0j4t5RCUI6E7g1IlZIui4i5mTl4yJii6TDgb0j4pLCevOAednLGcBTwLrRiMlslOyCc9J6h/PReo1z0nqNc9J6Tbs5uVdE7NqqUt3hoEslbSqU/aCkjIiYWrPNvMZcgSvInZ2MiC3Z0yeBmSXbWggsbLyWtDwiZg1j+2ZjwjlpvcT5aL3GOWm9xjlpvWascrJOJ/C80d5oidK5AiV9CtiD1AM+rQNxmJmZmZmZ9bWWncCIGPNOYMVcgZ8b622bmZmZmZkNkl65McxoWdi6illHOSetlzgfrdc4J63XOCet14xJTra8MYyZmZmZmZn1j347E2hmZmZmZmYV3Ak0MzMzMzMbIHWniOhpkiYCl5Mmlr89IhZ3OSQbIJLeDxwGTAW+AuwL7APsAMwHdgMuAjYDV0fEsi6FagMk+1y8AziXNI+qc9K6RtI44NPAJGA5ab7hg4BXAR/Oqvl73DpG0p7AZaT51x4FHsc5aV0g6XXAWcDkiDha0hxa5GKxTnaTzfa22w/XBEqaC2yIiJslXR8Rx3Q7Jhs8kqYAXwR2jIjjJH0U+AlwIHAj8CBwbUTM6V6UNigknQ88BzwMHOOctG6SdCRwBPA0cAswPyI+IGk2MCWr5u9x6xhJhwCvj4grJH0D2Mk5ad0kaUnWCfxWq1ws1omIRe1ur1+Gg04DVmXPN3czEBtoZwNXAWuz1ytJuTkNWBURW7oVmA2W7I+bh4AngMk4J637ZgB3RcTHSf/ZbvwHekhOZmX+HrdOuBc4VtJtwDKck9Y76uRisU7b+qUTuJqtB6Bf9sm2E0o+D9wK3A3ski3ak5Sbq4Fp2XAos044CHg7MCd7TM3KnZPWLauB9dnz/B/UQ3IyK3NeWiecBJwbEQeTLulocE5ar6iTi406beuX4aATSeO6XwDu9Lht6yRJpwEnkDqAK4AJwF5sHcu9G3AhsIk09O62LoVqA0bSiaTrXabjnLQukjQBuBTYCPyU1CF8F7ATcGpWzd/j1jGSZgILSJ+RvwB+jHPSukDSzsBngUNJI8pW0iIXs2sCX6kzsNcEmpmZmZmZWT0+vW1mZmZmZjZA3Ak0MzMzMzMbIF2fJ1DS7jSZr0rSNaRrVjYBp0fEi10J0szMzMzMrE/0wpnAD5FuUHAicEph2fOkW6BuIE0sa2ZmZmZmZiPQ0TOBkvYFLigUryWbr0pScZVTs/LTgNnATYX25gHzACZO0P5vfMOOADx634QhjUzfb+OQ8un7bRxSp/i6bJ1W5fl26rRfZztlbbTTVn6dhmZtVJXl12+2780U4y6LsSy2qt9JVf18+83qV6mq02x7deNuljPNtl/8/ZeVtfpdNPsdNtu3ZnHWUfU7rrNfrfanqt1m77ti263eV3XeX/k2i4bz3mj2uu56vapX4vz/2bv7aLnKOtHz31/SoCRCOkJYCzqALz3B7g7oHeLSXjO+QOOy78DFl6sNE254GSWiCKzWNbcviBfEFnxpvC0goxGXKIReSFodGS8XtYFRp7lKkIiAyth2I+mM8iJBJIgk+c0fexepU+yqvatOnarKqe9nrbNO1VPPfp7frvOrves5++UZdhzt7TXJsWFruv0eVvv9bBe6xdH52elW1rS9bvWqtv9V+8Bu7TfZBvXaVtbtR+v2x93Wo9/tZ12fdevXWdYZb5Wqv2tdvW4xdluu6feFupib9NetnybrVVVW9TeqW342mq5j3fesJm31eo+7/V161e31HlY97oyhn1xpj63Xd9S6Npu8D72+7zT9Ltvr89/ujrueejgzlz1rRTuM/e6gEfF+4MsUExtfk5mrK+qcACzIzGu7tbPqpc/N7910EACvP/BlM167acumGeU3bdk0o07n86pl6srb22nSfpN+qtrop632ZVq6tdGrrH35buveTWfcVTFWxdbrb9Krfnv73er30qtOt/6axt0tZ7r13/n3ryqr+xiqTAsAACAASURBVFt0+xt2W7ducTbR62/cZL3q1qdXu90+d51t132umny+2tvsNMhno9vzpstNqkmJc9hxtLfXJMeGren2e1jt97Nd6BZH52enW1nT9rrVq9r+V+0Du7XfZBvUa1tZtx+t2x93W49+t591fdatX2dZZ7xVqv6udfW6xdhtuabfF+pibtJft36arFdVWdXfqG752Wi6jnXfs5q01es97vZ36VW313tY9bgzhn5ypT22Xt9R69ps8j70+r7T9Ltsr89/u4UH/PSOzFz1rBXtMPZrAoHPsmu+qisBIuLqzFwTEZdQzH+xFHj7+EKUJEmSpPlh1oPAiNg3Mx8ZdPnM3AKc1FG2pvz93lmGJ0mSJElq0+jGMBFxdkTcFhH/PSL+Q1l2akQ8AjwYEb+OiIsjYhKOLEqSJEmSuqgdtEXE2cDHga9Q3KXziog4APgA8LfAncAq4C+BR4GPzlm0kiRJkqRZaXLk7h3AX2fm+QAR8WWKAeF5mfnhss71EfEEcDJ9DgIjYjFwBfA74NbMXF+WrwTOKatdnJl399OuJEmSJOnZmpwOeghwS9vzW8vlvtNR79tl3X69GdiQmacBx7WVnw2cAbwLOHOAdiVJkiRJHZoMAh8EXtz2vPX4hR31Xkgx51+/lgMPlI93tJUvycytmfkYsHfVghGxNiI2RsTGhx7ZUVVFkiRJktSmyemg/ydwcUQ8B/g18B+Bvwf+OiL+FfgB8D9SXCN44wAxbKYYCG5i5qD0sYhYAiTweNWCmbkOWAfFPIED9C1JkiRJU6XJIPD9wMHApRSDtOsorv37W+CbFIO0ADYC5w0Qw5eAyyPiGOCG1hyBwCfKPgNvNiNJkiRJQ1E7CMzMx4E3R8RewO+VzwHeFRH/B/AS4H5gY2bu7DeAzHwCOLWtaH1ZfjfFYFOSJEmSNCS11wRGxNcj4tDMfLI1AIyIoyJicWb+MDOvz8zvDTIAlCRJkiSNVpMbwxwNLGk9iYiFwDeAQ+cqKEmSJEnS3GgyCKwSQ41CkiRJkjQSTW4MM+d6TBh/AfBHwKPAhZm5ZWxBSpIkSdI8EJm9Z1aIiJ3AKzLz9vL5QuBp4IjMvHMoQUSsAbZm5g0RcV1mHl+Wn0dx2ulW4K8yc1vHcmuBteXTQ4FHgIeHEZM0JPthTmpymI+aNOakJo05qUnTb04ekpnL6io1HQRuBbZ3BNNZBkBm7t9HkK0+zgFuzMxNEXFtZq4uyxdk5s6IOA54QWZeWtPOxsxc1W//0lwxJzVJzEdNGnNSk8ac1KSZq5xscjroB4bdaYXKCePb7jj6ILByBHFIkiRJ0rzWZJ7AUQwCKyeMj4hzgYMojjyeNYI4JEmSJGlem4gbw/SYMP6iPptaN7SgpOEwJzVJzEdNGnNSk8ac1KSZk5ysvSZQkiRJkjR/DDpPoCRJkiRpN+QgUJIkSZKmyERcEzhb3Sabl0YhIt4IHAPsD3wSOAx4IbAHcDpwAPAxYAfwucy8ZUyhaoqU28VvAedTzKNqTmpsImIB8EFgH2AjxXzDRwLPAd5ZVnM/rpGJiIOByynmX7sP+DnmpMYgIl4EvA9YkplviYjV1ORiZ53y/ir99TsfrgnsNtm8NEoRsRT4OLBnZp4YEe8GfgC8FvgKcA9wTWseTGkuRcSFwBPAj4DjzUmNU0S8CXgD8Cvga8DpmfnWiDgWWFpWcz+ukYmIo4EXZ+anI+ILwF7mpMYpIjaUg8Dr63Kxs05mXt1vf/PldNDlwAPl4x3jDERT7TzgSuCh8vn9FLm5HHigbd5LaU6VX27uBX4JLMGc1PgdCtyWme+h+M926z/QM3KyLHM/rlG4EzghIm4GbsGc1ORokouddfo2XwaBrcnmYf6sk3YTUfgIcCNwO8W8lgAHU+TmZmB5eTqUNApHAq8EVpc/+5fl5qTGZTPwaPm4/Qv1jJwsy8xLjcKpwPmZeRTFJR0t5qQmRZNcbNXp23w5HXQxxXndvwW+43nbGqWIOAs4mWIAuAlYBBzCrnO5DwA+DGynOPXu5jGFqikTEadQXO+yAnNSYxQRi4DLgG3AjykGhK8C9gLOKKu5H9fIRMRK4AKKbeRvgO9jTmoMImJf4EPA6yjOKLufmlwsrwl8ps7UXhMoSZIkSWrGw9uSJEmSNEUcBEqSJEnSFBn7PIERcSBd5quKiKsorlnZDpydmU+NJUhJkiRJmicm4Ujg2yhuUHAKcFrHa09S3AJ1K8XEspIkSZKkWRjpkcCIOAy4uKP4Icr5qiKic5EzyvKzgGOBr3a0txZYC7CQhUcsYp+5CVySJEkaohWHb+O+uxaNOwzNA+259DiPPpyZy+qWGekgMDN/SDGYe0ZEvJ9ivqpfV9RvTWT8IPC8itfXAesA9onn5yviz4YesyRJkjRsN920idcf+LJxh6F5oD2Xvpkb7m+yzNivCQQ+y675qq4EiIirM3NNRFxCMf/FUuDt4wtRkiRJkuaHvgeBEfFc4PcpbuTyq8zcMZsAMnMLcFJH2Zry93tn07YkSZIkaaZGN4aJiIMi4tKI+CfgN8C/Ar8AnoiIf4yI/20ug5QkSZIkDUftIDAijgDuAt4MfA+4BvgJsBO4DLgDuDgivl4eJZQkSZIkTagmp4P+F+AfgTdl5u9ahRFxMXBMZh4eER8Avgv8Z+DcOYlUkiRJkjRrTU4HPQK4tH0AWLoE+JOI+B8y82GKm7uc2G8AEbE4Ij4fEZ+JiBPbyldGxPryZ2W/7UqSJEmSnq3JIPDXwMEV5a2y1iTu9wH7DxDDm4ENmXkacFxb+dnAGcC7gDOrFoyItRGxMSI2Ps1TA3QtSZIkSdOlyemgfwd8NCJ+B/wD8Dvg5cDfAJsy81/Ken8AbBkghuXAD8vH7XcaXZKZWwEiYu+qBTvnCRygb0mSJEmaKk0Ggf8JWEwxh1/ryGEA/w9wSlu9fYFPDxDDZoqB4CZmHpl8LCKWAAk8PkC7kiRJkqQOtYPA8lrAd0TEhcBhwHOBn2bm3R31Lhswhi8Bl0fEMcANrYnigU8Al1IMOD86YNuSJEmSpDa1g8CI+DpwZmb+hGJ+QCLiqIhYnJlPzDaAso1T24rWl+V3AyfPtn1JkiRJ0i5NbgxzNLCk9SQiFgLfAA6dq6AkSZIkSXOjySCwSgw1CkmSJEnSSDS5Mcyci4jFwBUUdx69NTPXl+UXAH8EPApcmJmD3H1UkiRJklRqOgismn5hmFMytOYKvCEirqO8LhDYTjEwfBrY2rlQRKwF1pZPf/PN3PAI8PAQ45Jmaz/MSU0O81GTxpzUpBlZTi48AOCno+hKu7fanOzIpUOaNBqZvcdyEbGTYgC2vSOYzjIAMrPvCeMj4hzgxszcFBHXZubqsnxBZu6MiOOAF2TmpTXtbMzMVf32L80Vc1KTxHzUpDEnNWnMSU2aucrJJkcCPzDsTitUzhWYmTvLhw8CK0cQhyRJkiTNa03mCRzFILByrsCIOBc4iOLI41kjiEOSJEmS5rWJuDFMj7kCL+qzqXVDC0oaDnNSk8R81KQxJzVpzElNmjnJydprAiVJkiRJ88eg8wRKkiRJknZDDgIlSZIkaYpMxDWBs9VtsnlpFCLijcAxwP7AJ4HDgBcCewCnAwcAHwN2AJ/LzFvGFKqmSLld/BZwPnAo5qTGKCIWAB8E9gE2Usz/eyTwHOCdZTX34xqZiDgYuJxi/rX7gJ9jTmoMIuJFwPuAJZn5lohYTU0udtYp76/SX7/z4ZrAiFgDbG1NNp+Zx487Jk2fiFgKfBzYMzNPjIh3Az8AXgt8BbgHuKY1D6Y0lyLiQuAJ4EfA8eakxiki3gS8AfgV8DXg9Mx8a0QcCywtq7kf18hExNHAizPz0xHxBWAvc1LjFBEbykHg9XW52FknM6/ut7/5cjrocuCB8vGOcQaiqXYecCXwUPn8forcXA480DbvpTSnyi839wK/BJZgTmr8DgVuy8z3UPxnu/Uf6Bk5WZa5H9co3AmcEBE3A7dgTmpyNMnFzjp9my+DwNZk8zB/1km7iSh8BLgRuJ1iXkuAgylyczOwvDwdShqFI4FXAqvLn/3LcnNS47IZeLR83P6FekZOlmXmpUbhVOD8zDyK4pKOFnNSk6JJLrbq9G2+nA66mOK87t8C3/G8bY1SRJwFnEwxANwELAIOYde53AcAHwa2U5x6d/OYQtWUiYhTKK53WYE5qTGKiEXAZcA24McUA8JXAXsBZ5TV3I9rZCJiJXABxTbyN8D3MSc1BhGxL/Ah4HUUZ5TdT00ultcEPlNnaq8JlCRJkiQ14+FtSZIkSZoiDgIlSZIkaYo4CJQkSZKkKdJ4sviIeDHw58BLKOasSGArxQXe/y0z/2mQACLiQLpMWhwRV1HcuGA7cHZmPjVIH5IkSZKkQu0gMCL2Aj5NcZvxp4F/orirVwC/D7wN+ERErAfekZm/7TOGt1Hcpe4e4BqKuVpanixj3Fr23RnbWmAtwEIWHvGyw3etzn13LXrm8YrDt80oW3H4tme93v68W1l7W7366Ke9qjrtfbRr2nZVjN3i7hVf3TJ1OtejaSxN4mkt2/6etb93Ve9jr/e2SZ1u/VX9bl+HzvXt9vfp9rhXvap2e70vvfrtVJfrVe9Pt+U76/X6W3bT7b2oeu876/eq0+v1buvTLU/6+Zw02Q41WW5S7S5x9qvb57NJDg27/15lw2q/83PXb2ztbbS306Tdfj8TVdv/btvcqvabbIM6266Lt9e2uG6f0W3f1t52XTu91r/b+nWWdcZbpWq/VFev1z6qarlu712T7Xqvtpr0W7dMr+83dd9T5uN2sh+T8h4MEsekxA4zY3mcRx/OzGV1y9TeHTQiLgPeCpwJfCUzn+54fQ/gDRS3fr4+M8/q0dZhwMUdxQ8Bf5mZWyPi2sxc3VZ/QWbuLG/B/y+Z+dVube8Tz8+t/9++zzx//YEve+bxTVs2zSi7acumZ73e/rxbWXtbvfrop72qOu19tGvadlWM3eLuFV/dMnU616NpLE3iaS3b/p61v3dV72Ov97ZJnW79Vf1uX4fO9e329+n2uFe9qnZ7vS+9+u1Ul+tV70+35Tvr9fpbdtPtvah67zvr96rT6/Vu69MtT/r5nDTZDjVZblLtLnH2q9vns0kODbv/XmXDar/zc9dvbO1ttLfTpN1+PxNV2/9u29yq9ptsgzrbrou317a4bp/Rbd/W3nZdO73Wv9v6dZZ1xlular9UV6/XPqpquW7vXZPteq+2mvRbt0yv7zd131Pm43ayH5PyHgwSx6TEDjNj+WZuuCMzV9Ut0+R00BOAszLz+qoXy0HhhnIweCnQdRCYmT8Ejm0vi4j3U0xa/OuK+jvLhw8Cz2sQqyRJkiSphyaDwOdSnP5ZZyvFRMT9+iy7Ji2+EiAirs7MNRFxCcUkiEuBtw/QtiRJkiSpTZNB4DeBv46IezPz51UVIuIg4INl3b5k5hbgpI6yNeXv9/bbniRJkiSpuyaDwDOArwP/FBG3U9wNdCvF3UF/n+JuoS8vy989R3FKkiRJkoagdhCYmVsi4qXAX1BMEfEnFKdnQnGa6I8pbgqzITO3z1WgkiRJkqTZazRPYGbuAP6u/BmqiFgMXAH8Drg1M9eX5SuBc8pqF2fm3cPuW5IkSZKmzYJxBwC8meIo4mnAcW3lZ1OcivouiukpJEmSJEmzNLRBYES8OiJuHmDR5cAD5eMdbeVLMnNrZj4G7N2lz7URsTEiNj7NUwN0LUmSJEnTZZhHApcBrxlguc0UA0GYGc9jEbEkIvYBHq9aMDPXZeaqzFy1x0CzU0iSJEnSdKm9JjAiTqqrU3r5gDF8Cbg8Io4BbmjNEQh8gmLy+QA+OmDbkiRJkqQ2TW4McxXFdBDRoG72G0BmPgGc2la0viy/Gzi53/YkSZIkSd01OR30F8CVFNfl9fppesRQkiRJkjQmTY4E3gYcUR6x6yoinhxOSJIkSZKkudLkSOAXgZ81qHcvcOEgQUTE4oj4fER8JiJObCu/ICKui4hPRcSBg7QtSZIkSdqldhCYmddl5l80qPejzPzAgHF0mytwO8Uk8k8DWwdsW5IkSZJUisze93KJiK8DZ2bmT9rKjgK+W3eKaOMgIs4BbszMTRFxbWauLssXZObOiDgOeEFmXtqx3Fpgbfn0UOAR4OFhxCQNyX6Yk5oc5qMmjTmpSWNOatL0m5OHZOayukpNrgk8GljSehIRC4FvUEwJ8f0+AuqlNVfgJtqOTmbmzvLhg8DKzoUycx2wri22jZm5akgxSbNmTmqSmI+aNOakJo05qUkzVznZZBBYpcl0Ef2onCswIs4FDqIYAZ815D4lSZIkaeoMOggcqh5zBV40nogkSZIkaX5qcndQqJ4Evu+J4UdgXX0VaaTMSU0S81GTxpzUpDEnNWnmJCeb3BhmJ8WdObe3Fe9XUQZAZu4/zAAlSZIkScPT5HTQQad9kCRJkiRNmNojgZIkSZKk+WMibgwzWxGxGLiCYmL5WzNz/ZhD0hSJiDcCxwD7A58EDgNeCOwBnA4cAHwM2AF8LjNvGVOomiLldvFbwPkU86iakxqbiFgAfBDYB9gIPA0cCTwHeGdZzf24RiYiDgYup5h/7T7g55iTGoOIeBHwPmBJZr4lIlZTk4uddQaZu31eHAmMiDXA1sy8ISKuy8zjxx2Tpk9ELAU+DuyZmSdGxLuBHwCvBb4C3ANck5mrxxelpkVEXAg8AfwION6c1DhFxJuANwC/Ar4GnJ6Zb42IY4GlZTX34xqZiDgaeHFmfjoivgDsZU5qnCJiQzkIvL4uFzvrZObV/fbX9O6gk2458ED5eMc4A9FUOw+4EniofH4/RW4uBx7IzJ3jCkzTpfxycy/wS2AJ5qTG71Dgtsx8D8V/tlv/gZ6Rk2WZ+3GNwp3ACRFxM3AL5qQmR5Nc7KzTt/kyCNzMrjdgvqyTdhNR+AhwI3A7xd1zAQ6myM3NwPLydChpFI4EXgmsLn9ad202JzUum4FHy8ftX6hn5GRZZl5qFE4Fzs/Moygu6WgxJzUpmuRiq07f5svpoIspzuv+LfAdz9vWKEXEWcDJFAPATcAi4BB2nct9APBhiilVrsnMm8cUqqZMRJxCcb3LCsxJjVFELAIuA7YBP6YYEL4K2As4o6zmflwjExErgQsotpG/Ab6POakxiIh9gQ8Br6M4o+x+anKxvCbwmTpTe02gJEmSJKkZD29LkiRJ0hRxEChJkiRJU2Ts8wRGxIF0ma8qIq6iuGZlO3B2Zj41liAlSZIkaZ4Y2pHAiNg3Il49wKJvo7hBwSnAaR2vPUlxC9StFBPLSpIkSZJmYZhHAl8LfBFY2K1CRBwGXNxR/BDlfFUR0bnIGWX5WcCxwFc72lsLrAVYvCiOeMkf7gnAfXctmtHIisO3zShfcfg27rtr0bN+dy7TXtZet6qPXst0q1P1elO94ujWV2f9ulialtX12dLZd6cmf5O6+u3r2a1+L1VtdHuPqmKti7vb36Mz/vbXerVblz9V7TZZ70F0+4zUfXb6WY+qvqrybdB1mAZNtgudZe3LdfuMddsmduqVj3XbgN3FqGNvsu8ZZxydedL0s9p0H9Z0X9a0jbp45nLf3TSOKnX7r1797u6a5sKk2R1i1O6hPZce59GHM3NZ3TJDuztoRPx74IuZ2XUQ2GW59wNfppjY+JrMXF1R5wRgQWZe262dVS99bn7vpoMAeP2BL5vx2k1bNs0ov2nLJl5/4Mue9btzmfay9rpVffRapludqteb6hVHt74669fF0rSsrs+Wzr47Nfmb1NVvX89u9XupaqPbe1QVa13c3f4enfG3v9ar3br8qWq3yXoPottnpO6z0896VPVVlW+DrsM0aLJd6CxrX67bZ6zbNrFTr3ys2wbsLkYde5N9zzjj6MyTpp/Vpvuwpvuypm3UxTOX++6mcVSp23/16nd31zQXJs3uEKN2D+259M3ccEdmrqpbpvZIYET8rGH/g/4r47Psmq/qyrLPqzNzTURcQjH/xVLg7QO2L0mSJEkqNTkd9A+AO4Fv19RbQXHKZl8ycwtwUkfZmvL3e/ttT5IkSZLUXZNB4CbgF5n5v/eqVJ4O2vcgUJIkSZI0Ok3uDvpd4BUN23vWnV0kSZIkSZOjySDwQuDP6ypl5t9nZt9TTkTE4oj4fER8JiJObCtfGRHry5+V/bYrSZIkSXq22kFbZj6cmT+YwxjeDGzIzNOA49rKzwbOAN4FnDmH/UuSJEnS1BjaZPGzsBx4oHy8o618SWZuzczHgL2rFoyItRGxMSI2PvTIjqoqkiRJkqQ2QxsERsSrI+LmARbdTDEQ7IznsYhYEhH7AI9XLZiZ6zJzVWauWrZvX9MTSpIkSdJUanJ30KaWAa8ZYLkvAZdHxDHADa05AoFPAJdS3Gzmo8MLU5IkSZKmV5PJ4k+qq1N6+SABZOYTwKltRevL8ruBkwdpU5IkSZJUrcmRwKuApNn0DzmraCRJkiRJc6rJNYG/AK6kuDlLr5+mRwwlSZIkSWPS5EjgbcAR5WmbXUXEk8MJSZIkSZI0V5ocCfwi8LMG9e6lmFi+bz0mjL8gIq6LiE9FxIGDtC1JkiRJ2iUyx38ZX0SsAbZm5g0RcV1mHl+WnwccCmwF/iozt3UstxZYWz49FHgEeHh0kUu19sOc1OQwHzVpzElNGnNSk6bfnDwkM5fVVaodBEbE14EzM/MnbWVHAd+tO0W0qYg4B7gxMzdFxLWZubosX5CZOyPiOOAFmXlpTTsbM3PVMGKShsGc1CQxHzVpzElNGnNSk2aucrLJ6aBHA0vaAlkIfIPiyNuwVE4Yn5k7y4cPAs8bYn+SJEmSNJUGnSy+yXQR/aicMD4izgUOojgMetaQ+5QkSZKkqTPoIHCoekwYf1GfTa0bWlDScJiTmiTmoyaNOalJY05q0sxJTja5JnAn8IrMvL18vhB4mmLaiDvnIihJkiRJ0txoOgjcCmxvK96vogyAzNx/mAFKkiRJkoanyemgH5jzKCRJkiRJIzER8wTOVkQsBq4AfgfcmpnrxxySpkhEvBE4Btgf+CRwGPBCYA/gdOAA4GPADuBzmXnLmELVFCm3i98Czqe4m7M5qbGJiAXAB4F9gI0Ul5UcCTwHeGdZzf24RiYiDgYup5h/7T7g55iTGoOIeBHwPmBJZr4lIlZTk4uddQaZtm++DAIrJ5uXRikilgIfB/bMzBMj4t3AD4DXAl8B7gGuac2DKc2liLgQeAL4EXC8Oalxiog3AW8AfgV8DTg9M98aEccCS8tq7sc1MhFxNPDizPx0RHwB2Muc1DhFxIZyEHh9XS521snMq/vtr8k8gbuD5cAD5eMd4wxEU+084ErgofL5/RS5uRx4oG3eS2lOlV9u7gV+STHPqzmpcTsUuC0z30Pxn+3Wf6Bn5GRZ5n5co3AncEJE3AzcgjmpydEkFzvr9G2+DAIrJ5uXRiEKHwFuBG6nuHESwMEUubkZWF6eDiWNwpHAK4HV5U/rhl3mpMZlM/Bo+bj9C/WMnCzLzEuNwqnA+Zl5FMUlHS3mpCZFk1xs1enbfDkddDHFed2/Bb7jedsapYg4CziZYgC4CVgEHMKuc7kPAD5McTfdazLz5jGFqikTEadQXO+yAnNSYxQRi4DLgG3AjykGhK8C9gLOKKu5H9fIRMRK4AKKbeRvgO9jTmoMImJf4EPA6yjOKLufmlwsrwl8ps7UXhMoSZIkSWrGw9uSJEmSNEUcBEqSJEnSFGkyWfyciogD6TJfVURcRXHNynbg7Mx8aixBSpIkSdI80fhIYETsUV642O31vSPi1QPE8DaKGxScApzW8dqTFLdA3UoxsawkSZIkaRZqjwSWtxD/CPAu4LkR8TDFHWouzsztbVX/mGKelYU92joMuLij+CHK+aoionORM8rys4Bjga92tLcWWAuwkIVHLGKfutWRJEmSpHnpcR59ODOX1dVrcjroO4EzgUsoJtb8n4BzgH8bEW/IzId6LdwuM39IMZh7RkS8n2K+ql9X1G9NZPwg8LyK19cB6wD2iefnK+LPmoYiSZIkSfPKN3PD/U3qNRkEng5cmJkXlc83RMRngL8HbouIP8/Mnw4YJ8Bn2TVf1ZUAEXF1Zq6JiEso5r9YCrx9Fn1IkiRJkmg2CHwR8J32gsy8NyL+lOL0zNsi4tjKJRvIzC3ASR1la8rf7x20XUmSJEnSszW5McxDwEGdhZm5lWJm+28D/wD8u+GGJkmSJEkatiaDwP8OHF/1Qjllw1uA9cC5Q4xLkiRJkjQHmgwCPwM8GRHPr3oxM3dm5juA84BvDTM4SZIkSdJw1Q4CM/MfMvP4zPxVTb2LMvPIfgOIiMUR8fmI+ExEnNhWvjIi1pc/K/ttV5IkSZL0bI0ni59DbwY2ZOZpwHFt5WcDZ1DMT3hm1YIRsTYiNkbExqd5au4jlSRJkqTd3NAGgRHx6oi4eYBFlwMPlI93tJUvycytmfkYsHfVgpm5LjNXZeaqPXjOAF1LkiRJ0nQZ5pHAZcBrBlhuM8VAEGbG81hELImIfYDHZxucJEmSJKnBPIERcVJdndLLB4zhS8DlEXEMcENronjgE8ClQAAfHbBtSZIkSVKbyMzeFSJ2AkkxGKuTmblwGIH1a594fr4i/mwcXUuSJEnS2H0zN9yRmavq6jU5HfQXwJUU1+X1+ml6xFCSJEmSNCa1p4MCtwFHZOYTvSpFxJPDCUmSJEmSNFeaHAn8IvCzBvXuBS4cJIgecwVeEBHXRcSnIuLAQdqWJEmSJO1Se03gSIKIWANszcwbIuK6zDy+LD8POBTYCvxVZm7rWG4tsLZ8eijwCPDw6CKXau2HOanJYT5q0piTmjTmpCZNvzl5SGYuq6vU5MYwXwfOzMyftJUdBXy37hTRpiLiHODGzNwUEddm5uqyfEFm7oyI44AXZOalNe1sbHIhpDQq5qQmifmokL/DDQAAIABJREFUSWNOatKYk5o0c5WTTU4HPRpY0hbIQuAbFEfehqVyrsDM3Fk+fBB43hD7kyRJkqSp1OTGMFWaTBfRj8q5AiPiXOAgisOgZw25T0mSJEmaOoMOAoeqPK301Lai9WX5RX02tW5oQUnDYU5qkpiPmjTmpCaNOalJMyc52XSy+Fdk5u3l84XA0xTTRtw5F0FJkiRJkuZG00HgVmB7W/F+FWUAZOb+wwxQkiRJkjQ8TU4H/cCcRyFJkiRJGomJmCdwtiJiMXAF8Dvg1sxcP+aQNEUi4o3AMcD+wCeBw4AXAnsApwMHAB8DdgCfy8xbxhSqpki5XfwWcD7F3ZzNSY1NRCwAPgjsA2ykuKzkSOA5wDvLau7HNTIRcTBwOcX8a/cBP8ec1BhExIuA9wFLMvMtEbGamlzsrDPItH3zZRBYOdm8NEoRsRT4OLBnZp4YEe8GfgC8FvgKcA9wTWseTGkuRcSFwBPAj4DjzUmNU0S8CXgD8Cvga8DpmfnWiDgWWFpWcz+ukYmIo4EXZ+anI+ILwF7mpMYpIjaUg8Dr63Kxs05mXt1vf03mCdwdLAceKB/vGGcgmmrnAVcCD5XP76fIzeXAA23zXkpzqvxycy/wS4p5Xs1JjduhwG2Z+R6K/2y3/gM9IyfLMvfjGoU7gRMi4mbgFsxJTY4mudhZp2/zZRBYOdm8NApR+AhwI3A7xY2TAA6myM3NwPLydChpFI4EXgmsLn9aN+wyJzUum4FHy8ftX6hn5GRZZl5qFE4Fzs/Moygu6WgxJzUpmuRiq07f5svpoIspzuv+LfAdz9vWKEXEWcDJFAPATcAi4BB2nct9APBhirvpXpOZN48pVE2ZiDiF4nqXFZiTGqOIWARcBmwDfkwxIHwVsBdwRlnN/bhGJiJWAhdQbCN/A3wfc1JjEBH7Ah8CXkdxRtn91ORieU3gM3Wm9ppASZIkSVIzHt6WJEmSpCniIFCSJEmSpoiDQEmSJEmaIr/XtGJE/D7F/GcPtpW9FngR8M+DTjYcEQfSZdLiiLiK4sYF24GzM/OpQfqQJEmSJBVqB4ERsTewnvL2uRHx98BJwAbgfymrZUT8I/D6zNzWZwxvo7hL3T3ANRRztbQ8Wca4FXi6Ira1wFqAxYviiJf84Z4A3HfXohn1Vhy+bUb5isO3zajT+bxqmbry9naatN+kn6o2+mmrvW7rtV7r1Hqt6nm3965OZ9zdYuqm17Ld3p+6tpr01zSWuvXr9n62P+9cn6r3qMnftL1uVVyd69LZXqd+3+NeeVGXN03i7fZe9PrctS/bq05nvW4xVsXTuf5N4un2njTJ9TpV25TO96JbzN3i7LXenX0NQ7/rPE79bO9HFcNcLTdIP732r9B8u9Etr5t8Xjq3K722a722A032w3V6fYfoFn+3Njr1Wo+6fnd3w9h2jsPuEON8NB/f9/Z1epxHH87MZXXL1N4dNCL+huL29+cAvwLeRzEB8eHA/0pxS93/Gbga+NvMvKhHW4cBF3cUPwT8ZWZujYhrM3N1W/0FmbmzvAX/v2TmV7u1veqlz83v3XQQAK8/8GUzXrtpy6YZ5Tdt2TSjTufzqmXqytvbadJ+k36q2uinrfa6rdd6rVPrtarn3d67Op1xd4upm17Ldnt/6tpq0l/TWOrWr9v72f68c32q3qMmf9P2ulVxda5LZ3ud+n2Pe+VFXd40ibfbe9Hrc9e+bK86nfW6xVgVT+f6N4mn23vSJNfrVG1TOt+LbjF3i7PXenf2NQz9rvM49bO9H1UMc7XcIP302r9C8+1Gt7xu8nnp3K702q712g402Q/X6fUdolv83dro1Gs96vrd3Q1j2zkOu0OM89F8fN/b1+mbueGOzFxVt0yT00HfBPznzLwSICJ+RjHwe0dmfrvVd0R8DPgPQNdBYGb+EDi2vSwi3k8xafGvK+rvLB8+CDyvQaySJEmSpB6aDAL/gOJUzZZ7y98/7Kh3B/D+AWL4LLsmLW4NNK/OzDURcQnFJIhLgbcP0LYkSZIkqU2TQeBjQPt5pduBn5Tl7RZR3NylL5m5heIaw/ayNeXv9/bbniRJkiSpuyZTRNwD/GnrSWbuzMw/yswfddR7GfDTYQYnSZIkSRquJkcCLwCe36DeCuCq2QQjSZIkSZpbtYPAzPxWk4Yy86T6Ws8WEYuBK4DfAbdm5vqyfCXFHUkBLs7MuwdpX5IkSZK0S5PTQefam4ENmXkacFxb+dnAGcC7gDPHEZgkSZIkzTdDGwRGxKsj4uYBFl0OPFA+br+xzJLM3JqZjwF7d+lzbURsjIiNDz3S9z1pJEmSJGnqDPNI4DLgNQMst5liIAgz43ksIpZExD7A41ULZua6zFyVmauW7btwgK4lSZIkabrUXhMYEU2v9Xv5gDF8Cbg8Io4BbmjNEQh8ArgUCOCjA7YtSZIkSWrT5O6gVwFJMRirk/0GkJlPAKe2Fa0vy+8GTu63PUmSJElSd01OB/0FcCXFdXm9fga6O6gkSZIkaXSaHAm8DTiiPGLXVUQ8OZyQJEmSJElzpcmRwC8CP2tQ717gwkGCiIjFEfH5iPhMRJzYVn5BRFwXEZ+KiAMHaVuSJEmStEvtIDAzr8vMv2hQ70eZ+YEB4+g2V+B2iknknwa2Dti2JEmSJKkUmb3v5RIRXwfOzMyftJUdBXy37hTRxkFEnAPcmJmbIuLazFxdli/IzJ0RcRzwgsy8tGO5tcDa8umhwCPAw8OISRqS/TAnNTnMR00ac1KTxpzUpOk3Jw/JzGV1lZpcE3g0sKT1JCIWAt+gmBLi+30E1EtrrsBNtB2dzMyd5cMHgZWdC2XmOmBdW2wbM3PVkGKSZs2c1CQxHzVpzElNGnNSk2aucrLJILBKk+ki+lE5V2BEnAscRDECPmvIfUqSJEnS1Bl0EDhUPeYKvGg8EUmSJEnS/NTk7qBQPQl83xPDj8C6+irSSJmTmiTmoyaNOalJY05q0sxJTja5McxOijtzbm8r3q+iDIDM3H+YAUqSJEmShqfJ6aCDTvsgSZIkSZowtUcCJUmSJEnzx0TcGGa2ImIxcAXFxPK3Zub6MYekKRIRbwSOAfYHPgkcBrwQ2AM4HTgA+BiwA/hcZt4yplA1Rcrt4reA8ynmUTUnNTYRsQD4ILAPsBF4GjgSeA7wzrKa+3GNTEQcDFxOMf/afcDPMSc1BhHxIuB9wJLMfEtErKYmFzvrDDJ3+7w4EhgRa4CtmXlDRFyXmcePOyZNn4hYCnwc2DMzT4yIdwM/AF4LfAW4B7gmM1ePL0pNi4i4EHgC+BFwvDmpcYqINwFvAH4FfA04PTPfGhHHAkvLau7HNTIRcTTw4sz8dER8AdjLnNQ4RcSGchB4fV0udtbJzKv77a/p3UEn3XLggfLxjnEGoql2HnAl8FD5/H6K3FwOPJCZO8cVmKZL+eXmXuCXwBLMSY3focBtmfkeiv9st/4DPSMnyzL34xqFO4ETIuJm4BbMSU2OJrnYWadv82UQuJldb8B8WSftJqLwEeBG4HaKu+cCHEyRm5uB5eXpUNIoHAm8Elhd/rTu2mxOalw2A4+Wj9u/UM/IybLMvNQonAqcn5lHUVzS0WJOalI0ycVWnb7Nl9NBF1Oc1/1b4Duet61RioizgJMpBoCbgEXAIew6l/sA4MMUU6pck5k3jylUTZmIOIXiepcVmJMao4hYBFwGbAN+TDEgfBWwF3BGWc39uEYmIlYCF1BsI38DfB9zUmMQEfsCHwJeR3FG2f3U5GJ5TeAzdab2mkBJkiRJUjMe3pYkSZKkKeIgUJIkSZKmyNjnCYyIA+kyX1VEXEVxzcp24OzMfGosQUqSJEnSPDGrI4ERsSgivh4Rh82imbdR3KDgFOC0jteepLgF6laKiWUlSZIkSbNQeyQwIv64x8t7A0cD/yYidgBk5r092joMuLij+CHK+aoionORM8rys4Bjga92tLcWWAuweFEc8ZI/3BOA++5aNKORFYdvm1G+4vBtM+q0nreXdy7Tra3O1zrb6VVe10/TNurWs1Xeeq1bHN3K2pfvtu7ddMZdFWNVbL3eq17129vvVr+XXnW69dcr7l5/r/lo2ta3Sq8cbKnK1brPbftrnf3Nt/e8yTr12i51e++q6s42tqbbgkHabvr6MHNgHPnUK9eb7CP72bdW9dftO0CTfUuvGKQ65s3cm5b3uH09H+fRhzNzWd0ytXcHjYid7JqQsLJK+XoAmZkLG0dctP9+4MsUExtfk5mrK+qcACzIzGu7tbPqpc/N7910EACvP/BlM167acumGeU3bdk0o07reXt55zLd2up8rbOdXuV1/TRto249W+Wt17rF0a2sfflu695NZ9xVMVbF1uu96lW/vf1u9XvpVadbf73i7vX3mo+mbX2r9MrBlqpcrfvctr/W2d98e8+brFOv7VK3966q7mxja7otGKTtpq8PMwfGkU+9cr3JPrKffWtVf92+AzTZt/SKQapj3sy9aXmP29fzm7nhjsxcVbdMk2sCt1CcNnoB8JOO1/amODr3Hor50QbxWXbNV3UlQERcnZlrIuISivkvlgJvH7B9SZIkSVKpySBwBXAecAmwDrgwMx8DiIglZZ07M/NbgwSQmVuAkzrK1pS/3ztIm5IkSZKkarU3hsnMbZl5LvBvKAaE/29EvCMqLuCTJEmSJE22xncHzcyfZua/o7iL53spTv88it7XC0qSJEmSJkjfU0Rk5n8F/gT4O+DzFDeEGVhELI6Iz0fEZyLixLbylRGxvvxZOZs+JEmSJEmFgeYJzMynM/PDwIsoThO9YxYxvBnYkJmnAce1lZ8NnAG8CzhzFu1LkiRJkkpNbgzTVWY+DDw8yxiWAz8sH+9oK1+SmVsBImLvqgXb5wk8+A9mtSqSJEmSNBUGOhJYJSJeHRE3D7DoZoqBYGc8j0XEkojYB3i8asHMXJeZqzJz1bJ9+5qeUJIkSZKm0jAPny0DXjPAcl8CLo+IY4AbWnMEAp8ALqW45vCjwwtTkiRJkqZX7SAwIk6qq1N6+SABZOYTwKltRevL8ruBkwdpU5IkSZJUrcmRwKsopoFochdQp4uQJEmSpAnW5JrAXwBXAnvX/DQ9YihJkiRJGpMmRwJvA44oT9vsKiKeHE5IkiRJkqS50uRI4BeBnzWody9w4SBB9Jgw/oKIuC4iPhURBw7StiRJkiRpl8gc/2V8EbEG2JqZN0TEdZl5fFl+HnAosBX4q8zc1rHcM/MElvUeYfbzFkrDtB/mpCaH+ahJY05q0piTmjT95uQhmbmsrlLtIDAivg6cmZk/aSs7Cvhu3SmiTUXEOcCNmbkpIq7NzNVl+YLM3BkRxwEvyMxLa9rZmJmrhhGTNAzmpCaJ+ahJY05q0piTmjRzlZNNTgc9GljSFshC4BsUR96GpXLC+MzcWT58EHjeEPuTJEmSpKk06GTxTaaL6EflhPERcS5wEMVh0LOG3KckSZIkTZ1BB4FD1WPC+Iv6bGrd0IKShsOc1CQxHzVpzElNGnNSk2ZOcrLJNYE7gVdk5u3l84XA0xTTRtw5F0FJkiRJkuZG00HgVmB7W/F+FWUAZOb+wwxQkiRJkjQ8TU4H/cCcRyFJkiRJGomJmCdwtiJiMXAF8Dvg1sxcP+aQNEUi4o3AMcD+wCeBw4AXAnsApwMHAB8DdgCfy8xbxhSqpki5XfwWcD7F3ZzNSY1NRCwAPgjsA2ykuKzkSOA5wDvLau7HNTIRcTBwOcX8a/cBP8ec1BhExIuA9wFLMvMtEbGamlzsrDPItH3zZRBYOdm8NEoRsRT4OLBnZp4YEe8GfgC8FvgKcA9wTWseTGkuRcSFwBPAj4DjzUmNU0S8CXgD8Cvga8DpmfnWiDgWWFpWcz+ukYmIo4EXZ+anI+ILwF7mpMYpIjaUg8Dr63Kxs05mXt1vf03mCdwdLAceKB/vGGcgmmrnAVcCD5XP76fIzeXAA23zXkpzqvxycy/wS4p5Xs1JjduhwG2Z+R6K/2y3/gM9IyfLMvfjGoU7gRMi4mbgFsxJTY4mudhZp2/zZRBYOdm8NApR+AhwI3A7xY2TAA6myM3NwPLydChpFI4EXgmsLn9aN+wyJzUum4FHy8ftX6hn5GRZZl5qFE4Fzs/Moygu6WgxJzUpmuRiq07f5svpoIspzuv+LfAdz9vWKEXEWcDJFAPATcAi4BB2nct9APBhirvpXpOZN48pVE2ZiDiF4nqXFZiTGqOIWARcBmwDfkwxIHwVsBdwRlnN/bhGJiJWAhdQbCN/A3wfc1JjEBH7Ah8CXkdxRtn91ORieU3gM3Wm9ppASZIkSVIzHt6WJEmSpCniIFCSJEmSpkiTyeLnVEQcSJf5qiLiKoprVrYDZ2fmU2MJUpIkSZLmiYEHgRHxfOBwiluU3pWZj9Ys0s3bKG5QcA9wDcVtelueLGPcSjGxrCRJkiRpFmoHgRFxEfDJzPzX8vkC4BLgXeXyATwdEZ/IzP9Y09ZhwMUdxQ9RzlcVEZ2LnFGWnwUcC3y1o721wFqAhSw8YhH71K2OtFtZcfg2AO67a1HX11qvt9ddcfi2Z/1u12qv9Xq3vuv6rWqzn7Y6X+8Vb+d7UbVMex+93o9e/fZ6P6riafoeSE3VfV5mW3+u9Pp8tVQ9b9Je1baw6nNb9V50xtErxl7bgSbbiTq9tund4u/WRqde61HX7+6uaS5Mmt0hxvmg7rPbbRvR+Xlq6ZZr3b671G1jun0H6rW97FYH4I67nno4M5fVvS+1dweNiB3An2bm98rn7wM+APwNsKGs9hbgvcB7MvOyuk472n8/8GWKiY2vyczVFXVOABZk5rXd2tknnp+viD/rp2tp4t20ZRMArz/wZV1fa73eXvemLZue9btdq73W6936ruu3qs1+2up8vVe8ne9F1TLtffR6P3r12+v9qIqn6XsgNVX3eZlt/bnS6/PVUvW8SXtV28Kqz23Ve9EZR68Ye20Hmmwn6vTapneLv1sbnXqtR12/u7umuTBpdocY54O6z263bUTn56mlW651++5St43p9h2o1/ayWx2AhQf89I7MXFX3vjQ5HbTz8NzbgUsz8z+1lW2MiL0ojsr1NQgEPsuu+aquBIiIqzNzTURcQjH/xdKyX0mSJEnSLAxyTeBBwP9VUf41ylMz+5GZW4CTOsrWlL/fO0B8kiRJkqQumg4CXxgRvykfPwLsWVFnT+B3Q4lKkiRJkjQnmg4C26/FC+BVwH/rqPNy4J+HEZQkSZIkaW40GQQeWVH2WEXZMorr+yRJkiRJE6p2EJiZ/3eThjLzXYMEEBGLgSsoTiW9NTPXl+UrgXPKahdn5t2DtC9JkiRJ2mXBuAMA3gxsyMzTgOPays8GzqCYj/DMqgUjYm1EbIyIjU/z1NxHKkmSJEm7uaENAiPi1RFx8wCLLgceKB/vaCtfkplbM/MxYO+qBTNzXWauysxVe/CcAbqWJEmSpOkyzCOBy4DXDLDcZoqBIMyM57GIWBIR+wCPzzY4SZIkSVKDawIj4qS6OqWXDxjDl4DLI+IY4IbWRPHAJ4BLKe5G+tEB25YkSZIktWlyd9CrgKQYjNXJfgPIzCeAU9uK1pfldwMn99ueJEmSJKm7JqeD/gK4kuK6vF4/TY8YSpIkSZLGpMmRwNuAI8ojdl1FxJPDCUmSJEmSNFeaHAn8IvCzBvXuBS4cJIiIWBwRn4+Iz0TEiW3lF0TEdRHxqYg4cJC2JUmSJEm7RGbfl/ENP4iINcDWzLwhIq7LzOPL8vOAQ4GtwF9l5raO5dYCa8unhwKPAA+PLnKp1n6Yk5oc5qMmjTmpSWNOatL0m5OHZOayukq1g8CI+DpwZmb+pK3sKOC7daeINhUR5wA3ZuamiLg2M1eX5Qsyc2dEHAe8IDMvrWlnY2auGkZM0jCYk5ok5qMmjTmpSWNOatLMVU42OR30aGBJWyALgW9QHHkblsq5AjNzZ/nwQeB5Q+xPkiRJkqZSkxvDVGkyXUQ/KucKjIhzgYMoDoOeNeQ+JUmSJGnqDDoIHKoecwVe1GdT64YWlDQc5qQmifmoSWNOatKYk5o0c5KTTa4J3Am8IjNvL58vBJ6mmDbizrkISpIkSZI0N5oOArcC29uK96soAyAz9x9mgJIkSZKk4WlyOugH5jwKSZIkSdJITMQ8gbMVEYuBK4DfAbdm5voxh6QpEhFvBI4B9gc+CRwGvBDYAzgdOAD4GLAD+Fxm3jKmUDVFyu3it4DzKe7mbE5qbCJiAfBBYB9gI8VlJUcCzwHeWVZzP66RiYiDgcsp5l+7D/g55qTGICJeBLwPWJKZb4mI1dTkYmedQabtmy+DwMrJ5qVRioilwMeBPTPzxIh4N/AD4LXAV4B7gGta82BKcykiLgSeAH4EHG9Oapwi4k3AG4BfAV8DTs/Mt0bEscDSspr7cY1MRBwNvDgzPx0RXwD2Mic1ThGxoRwEXl+Xi511MvPqfvtrMk/g7mA58ED5eMc4A9FUOw+4EniofH4/RW4uBx5om/dSmlPll5t7gV9SzPNqTmrcDgVuy8z3UPxnu/Uf6Bk5WZa5H9co3AmcEBE3A7dgTmpyNMnFzjp9my+DwMrJ5qVRiMJHgBuB2ylunARwMEVubgaWl6dDSaNwJPBKYHX507phlzmpcdkMPFo+bv9CPSMnyzLzUqNwKnB+Zh5FcUlHizmpSdEkF1t1+jZfTgddTHFe92+B73jetkYpIs4CTqYYAG4CFgGHsOtc7gOAD1PcTfeazLx5TKFqykTEKRTXu6zAnNQYRcQi4DJgG/BjigHhq4C9gDPKau7HNTIRsRK4gGIb+Rvg+5iTGoOI2Bf4EPA6ijPK7qcmF8trAp+pM7XXBEqSJEmSmvHwtiRJkiRNEQeBkiRJkjRFHARKkiRJ0hT5vUEWiog9gROBPwZ2UtwM44uZ2fctdCPiQLpMWhwRV1HcuGA7cHZmPjVIvJIkSZKkQu0gMCL+Dng4M88sn7+E4lb4y4F/AQJ4D3BuRPzbzOz3NqVvo7hL3T3ANRRztbQ8Wca4FXi6Ira1wFqAxYviiJf84Z4A3HfXohn1Vhy+bUb5isO3zajT+bxqmbry9naatN+kn6o2+mmrfZmWbm3UlXW20VRn3FUxVsXW62/Sq357+93q99KrjW799Yq7199L81fVZ69dVZ7VfW7bX6vqaz5psk5Vn++q12a7DauLrW4bMEzd2h5mn+PIp1653mQf2c8+vKq/qr9d031LrxikOuaNhqU9lx7n0Yczc1ndMrV3B42IXwDvzswN5fNvAMuAN2XmP5dlLwa+DNyXmW/p0dZhwMUdxQ8Bf5mZWyPi2sxc3VZ/QWbuLG/B/y+Z+dVuba966XPzezcdBMDrD3zZjNdu2rJpRvlNWzbNqNP5vGqZuvL2dpq036Sfqjb6aat9mZZubdSVdbbRVGfcVTFWxdbrb9Krfnv73er30quNbv31irvX30vzV9Vnr11VntV9bttfq+prPmmyTlWf76rXZrsNq4utbhswTN3aHmaf48inXrneZB/Zzz68qr+qv13TfUuvGKQ65o2GpT2Xvpkb7sjMVXXLNDkddAnwy7bnrwL+fWsACJCZ/xQR5wNX9WooM38IHNteFhHvp5i0+NcV9XeWDx8EntcgVkmSJElSD00GgT8FVgHfLp8/DiysqLeA4vrAfn2WXZMWXwkQEVdn5pqIuIRiEsSlwNsHaFuSJEmS1KbJIPAy4MMR8YPMvJlixvqLIuLHmXkfPHOd4AeB/9pvAJm5BTipo2xN+fu9/bYnSZIkSfr/2zvzMDuKqg+/P8IalpCwCAhhEQhqXNkUVAKyaZAIH4vCJwSViIgsoiKgEvZNQU1UCAiIgiAIAoYgMWFYAgoJBNkSPoRAYgyEhDUJS8j5/jh1SU9P3773ztxZzJz3efqZ6erqqrrVp6vrVJ06VZ2aSqCZjZE0ELhd0lPAI8BA4HFJFTPR9YCHgGM7raRBEARBEARBEARBh6lrn0Az+yHwEeBm3CnMbOBpYCZwO3AAsJ2Zze2kcgZBEARBEARBEARNoO59As3sMeD7zS6ApFWBXwFvAS1mdlUKHwycmKKdbWaPNjvvIAiCIAiCIAiC3kZdM4GdzL7A9WZ2OLB3JvwY4FvAkcC3u6NgQRAEQRAEQRAEyxpNUwIlfUbSxHbcuiFuVgrwTia8n5m9bGavAKtXyXOEpMmSJs+d905RlCAIgiAIgiAIgiBDM2cC1wF2asd9s3BFEFqX5xVJ/SStgW9L0QYzG2Nm25jZNuusVbRrRRAEQRAEQRAEQZCl5ppASYfUipPYtp1luAEYLWkocEtlj0Dg58AvAAHntTPtIAiCIAiCIAiCIEM9jmGuAAxXxmphjRbAzBYAh2WCrkrhjwKHNppeEARBEARBEARBUJ16zEHnAJfi6/LKjnpnDIMgCIIgCIIgCIJuop6ZwPuArdOMXVUkLWpOkYIgCIIgCIIgCILOop6ZwD/iG8PX4nHgtPYUQtKqkn4r6RJJB2fCR0q6VtJFkjZoT9pBEARBEARBEATBUmoqgWZ2rZkdUEe8J8zs1HaWo9pegYvxTeTfBl5uZ9pBEARBEARBEARBQmblvlwk3Q5828ymZ8J2Af5Ry0S07kJIJwLjzGyqpKvN7KAUvpyZLZG0N7CJmf0id98IYEQ6HQTMA15sRpmCoEmsTchk0HMIeQx6GiGTQU8jZDLoaTQqkxub2Tq1ItWzJnBXoF/lRFIfYDy+JcSDDRSojMpegVPJzE6a2ZL07wvA4PxNZjYGGJMp22Qz26ZJZQqCDhMyGfQkQh6DnkbIZNDTCJkMehqdJZP1KIFF1LNdRCMU7hUo6SRgI1wDPrrJeQZBEARBEARBEPQ62qsENpWSvQLP6p4SBUEQBEEQBEEQLJvU4x0UijeBb3hj+C5gTO0oQdClhEwGPYmQx6CnETIZ9DRCJoOeRqfIZD2OYZbdnCFUAAAWvUlEQVTgnjkXZ4LXLggDwMzWbWYBgyAIgiAIgiAIguZRjzloe7d9CIIgCIIgCIIgCHoYNWcCgyAIgiAIgiAIgmWHHuEYpqNIWhX4Fb6xfIuZXdXNRQp6EZK+CAwF1gV+CXwI2BRYATgCWB84H3gHuNzM7uimoga9iNQu3gWcgu+jGjIZdBuSlgNOB9YAJgNvAzsDKwHfTNHiOx50GZIGAqPx/deeBJ4jZDLoBiRtBpwM9DOz/SQdRA1ZzMdpz97ty8RMoKSvAC+b2S2SrjWzA7u7TEHvQ1J/4AJgRTM7WNJRwMPAEODPwGPA783soO4rZdBbkHQasAB4AjgwZDLoTiTtAwwD5gNjgSPMbH9JewH9U7T4jgddhqRdgfeZ2cWSrgRWCZkMuhNJ1ycl8LpaspiPY2a/azS/er2D9nQ2BGam/9/pzoIEvZofApcCc9P5s7hsbgjMNLMl3VWwoHeROjePA88D/QiZDLqfQcB9ZvYdfGS7MgLdSiZTWHzHg67gIeBLkiYCdxAyGfQc6pHFfJyGWVaUwFksrYBl5TcF/yXIORcYBzyAe88FGIjL5ixgw2QOFQRdwc7AJ4CD0lHx2hwyGXQXs4CX0v/ZDnUrmUxhIZdBV3AYcIqZ7YIv6agQMhn0FOqRxUqchllWzEFXxe263wDuCbvtoCuRdDRwKK4ATgX6Ahuz1JZ7feAcfEuV35vZxG4qatDLkDQcX++yJSGTQTciqS8wClgITMMVwk8DqwDfStHiOx50GZIGAyPxNvJ14EFCJoNuQNJawJnAbrhF2bPUkMW0JvDdOL12TWAQBEEQBEEQBEFQHzG9HQRBEARBEARB0IsIJTAIgiAIgiAIgqAXEUpgEARBEARBEARBLyKUwCAIgiAIgiAIgl5EKIFBkEHS5pIulvSwpHcktVSJJ0knSZopaZGkuyR9tCDeByRNkLRQ0mxJp0nq0560CtJeVdLpkqan+56XdKekr2XiDJFkkl6UtFru/qMkWS7MMsciSY9IOrIZWwlIukXSKR1NpzOQ1CLp+u4uB4CkTVL971UjXpvn18QybCdpZEH4SEkvdkJ+Netf0ghJX2xint+XNKQg3CQd1ax8CtIfJukJSW9JmtFZ+TSKpMHptw/pxDyuyLUxlePSTJwjJY2VNK9aeSTtL+lmSf+W9LqkKZK+XJLvrWkbHyTNSOl+ORdntRQ+PBP2DUnjU9v6iqRJknZvRl20l/w7mGnjB3dnuZpN+maNzJy3aSMkHS7pGUmLK99qSe+XdLekBaleNunKcpdR0q5+T9KEbihS0MsJJTAIWvNB4PPAk+moxg+AHwHnAl/A3Uv/TdJ6lQiS+gN/wzf0HAacBhwPnNpoWlX4EzACdxv8eeBo4NH0f5618K0B6uGnwCfxfZPuAH4JHFnnvYVI2h7fu25UR9LpJfwHr/97urEM2wFFCvulwB5dXJYKI4CmKYHA94EhTUyvJmkA6ErgYWAXYJ+uzL+HMA2X7+xxVub6IcAA4K8laXwHbyePA/bG26mrJX07H1HSKnjbMzZ36SRJqlHWk4FngG8A+wFPAbdJ2rvGfUHzORI4sXKSvo+/Bm4CdmLpN+p8YE1cLj6Jt6c9hWrt6kXAxztzACYIili+uwsQBD2MW8zsJoA06rh2PoKklXHF7WwzG53C7gNmAEcBP0xRj8D3b9nXzF4FxktaAxgp6Twze7WBtPJl2ALvjB9gZtdlLl1bpWPTAhwvaZSZvVGjDmaY2d/T/xMlfQBXIEfXuK+Mo4GbzGx+B9Kom9TZ7mNmb3VFfs3EzN4E/l4zYjdgZpVNa4P2sT6wBnC1mXWnkt9pSFoBWGJm71SJsiDTvhSxg5ktSTNb1Wb3vmBm2RnpiZI2wJXD/EDTZ/G9te7NhLXgAwDDgD+XlOXjuXzGp7b3OODmkvuCJmNmj+eCNgf6AJeZ2T8z4VsBN5tZh2bW0nd0pTq+lx3GzF6T9Cfg27hsBkGXEDOBQZDBzJbUEW0HvCP3x8x9C4BbgM9l4n0O+GtSACtcgyuGOzWYVp410985Bb+hyETwPKA/8PWSNKsxBdikciLpRElPSXojmUndVjZrKWl1fMYjb8rTIun6ZOY3Q25+OlbSezNxCk2d8qZBycxssqQvSnoM7/RtL2l4un/bZCK0SNKTkmrOwCTzuLGSXkvHdXXMznYYFZiDSlpJ0mhJL0uaL+lCYIWCewfIzZmfT8/n3jQLm41jko6RdJakuZJekPRLSSul68NJHWktNddrSedtzEElrZXy/E/Kc7qkYzPXj5f0QDKne15uFrx5g3XSAmwNHJop0/B0rU8q13OS3pT0mHwT3bL0ZuCz46dk0huSidKnWv1k0hgo6Zr0PBZK+qukQSV5DgdmptObUp4j07W+kn4haU6qwweUMztM78hP8mmmdFZL55X3ZUiS19clPS2pzUy+3Oxyptxs7hZcQc3HWU7SD9L7/mZ6dw7Nxcm+x//C370NqtVDLeppg3OKWYWHgHULwofi7fDiTNgU4DZ8pq9Z+VRF0lBJSyRtmgvfNIXvnQkbltqyN5I8nCdXrBvJr1SeJH01PfcVMmGz5SaYSufLpfbm8Ebybg+SPiNfgvGG3LR3h4I477b56b25O116uNIeyM3j3wccl2230j2l9Vpp2yR9StIDuBzvn651arua+BOwl6QBHarMIGiAUAKDoHG2At4B/i8X/kS6lo03LRvBzJ4DFmbi1ZtWnunAAuBnknaXzyiWMRM3Q/t+ox0KXAGcAyDpEOAk4AJ8JvKbuInUqiX374ArvvcWXPskPvr5HeBrwIcpH5mvVc7zgLNxk9hnMteuxc2G9gUeAa6T9JFqCcmVlEnAysBXgOG4qfAtlU5SlfskaflaRzt+2zm4An86cDCwMW5anM17Jdz8eDfge7jp5FyKTYuPxzvq/4ubT30DOCZdG4ubBMNSc71Cc2C5qV1Lyut0vN5/SmslYEN8FnkYcDg+ej9JUr86fzsp/2nArZkyVcz7TsM782NwE7BJwFUqWSOGD0q8Avwmk96Dmetl9UPqqN0DDMJn/A/A34G/pTopYiwufwDfTXlW1sJdAhwGnJnKNhMYK+lTJb+hjEtwk9N98OfzS0nbZco/DDfz/gtL34nLCtIZhVsjjMGVqRuBy9R2veqOeFtwAm7S/kpZ4ZrwPhSxA5CfLQKXybwpKMAZwDaS9mwwn09WyaeM24DZwKG58OH4O3orgKQDgBuA+3FZPhU3gz67wfxqydNdQF/g4ynfLXDFdg3gAynOR4B+LFW22pAUxVrtXZ9q96c0NgDGAfNxk9uLgatS+apxKfCt9P/B+DMZl/7OAa4m0241UK99gd+m9PcE7u/CdvVefGDv0yW/Owiai5nFEUccBQc+c9VSEH4y8HJB+Nfx9X8rpvO3gWML4s0CzmokrSrl+zK+LsaAt/AP++GAMnGGpOuD8RHSxcDX0rWjSBOHmfiGm24uD6yOr89ZDPwkXR8N/KnBejwJmFsQ3pLqaONM2I6pDHvmy19w7/WZ8ytSvI/m4g1P4SdlwpbDFYprStL7Ha5or5gJ2wJX2IeW/NZKeWsdm5SksUmKs1c6XwtYBJxQ8BssE/a1JAdbZMKWB/4FnJ97xnfl8vwz8PfMeRvZSOEjgRcz598AluTrveS39cEHBF4DDqlW/1XunQxckQsbgA+GnJILvxWYXiO9F4GRBeH11M/pwDxgQCasP678fKveZ5vC3p/q8NDc830Un8GqhM0gvYcF8r1aTv5Oy8RZAe+0npMJux8Yl0vrknTvkHS+eb5cKfxK4IHcs1sErFfH87+C4vdh84K4g7PlqZHuZ1NZh+fCP4S/s+sU1WMq+93p/9VSfsNL8vlqirNzPfKeu/cMfGBK6Vy5sgh4Fri8IM9FwFpV3sHKMx/coDzNBr6byWMKcB9wRAo7Gnihxm8aWeV5Zo8ZNdI4D3+X+mbCDk73jsyEtdC6jW71u6u9Jw3WqwHDcvE6vV3Nlf3MRmUrjjjae8RMYBC0DysIU8G1avHqiVPtml8w+wM+I/RV3Mx0S3zE/uoq8f+V4v2gxujsz3Hl7FW80/Z7/AMJMBX4vKRT5Z7OSkd5E+vhHe4iHjSzZzNlnAS8gC+gb5R/m9nUKtduzOSxBJ8VLMtj13TPksxsxTP4R3qbkvumANvWccyu4/dU+BA+I3lTwW/Il3kK8ExuhuXOgjLfnjt/HJ+xa5RdgIdK6h1Jn5B7WJyHDygsxDvcW7YjvzyD8dH763Lh1wJbSmrIbC9DrfrZFRgPvJqp69fw+i+TjyK2xd/3d39Der7XAe2dCXy3/Gb2Nm5psCG8u172Y7SVnxty5xXF6sbcrN0E4KO5d3+KmbUxTa/CE7R9H2aW3lGC3Pvj1fia4ytyl4cC95vZ3Cq3nwF8StJOdeSzNT4z+nMzu6MdRb0Mb6+HpPOd0/nl6XxLYCDwx1x9T8Tf/3q9f9YrT/ewdNbpM/gg4l25sFrrVsdQu637Qo00tgPGm9nCTFheFjtCI/Vq+Ixilq5sV1/Ev5dB0CWEY5ggaJyXgNUl9bHWzg/WBBamTlcl3ppt7nYTm5cbTKsQM5uHdyIuT2aeFwOHSTrHzB4uuOUsfET4wJJkz8fXKC4CnjazRZlrl+EzhCOAHwPzJP0aH7Gt5ghiZeDNKtdeqBLWZn1SHTxfci2fT6081sZN204ouLZRyX2v44pyKdZ6fVItKp2Cot+QZW3gE7gCn+dfufOXc+dv4c+pUdaixPuepIF4x+h+fNZwdsprbDvzy1N5hvlnXznvT7GM1aJW/VTquug9atQhxfrA67lOMPhv6CtpJXNnQY1QVv518G9/PfLUh+qmneuz1ElQ2buXZ6GZTW4gflWSWe444DncBC/PUIpNQQEws79J+gdukbFvtXiSNkvpTCBnhl0vZvZ0WgN2GO7N9DBcQX0sRak4Ibu1ShJl7U6WeuXpLuDUZN7+adzU8S3gVyn+p3CP1WXMofb7VXUgM7EekHXsgpktkvR6jfvqpZF6fcnaOhPrynb1zQbjB0GHCCUwCBpnGt452hw3GayQXwM4jdy6Pkkb4WuHpmXi1JNWTczsbbnDkMPS/W2UQDN7XNKNuInmxVWSeq5aJy2NKF8IXJh+y8H4upN/426ui5hPsTIMxQ4W1mWpYlHxzLZiLs4A2s4ulnU21sVNjoryKGI+PhN4acG1sn3ydsI7eKVI2tTMZtSKl6jMsKybykXmPMt83GSyaCuQRpWIepmHy2419sRn6oaZOzwijaQ3y/lB5Rnmn+970t/O8kY7H/cOeXrBtdcaTOs/wGqS+uY67u/BFabKs3uD4vegUebiM7J5+SmSp8W4iXaRs5Zs579WR7/pSOqLr2lcETfRXpC73h9fd3V0jaTOxJ9loWVAmk3+K25S+KWSwa56uBS4RNKJuNKZVSgrsjoCdz6T55k686hXnu7G5Wc3YNN0/jbwXrkTmfdQsh4w8WOKtzzI8iwZx2IFzCEne2ld7WrF0RumkXotkuOubFfXpPParCBoQyiBQdA49+Kmkvvj5kSVDskXcPOYCuOA70la3cwqHcMD8Rm2OxtMqxVyj5uLc7N04OvWoHxk/gzcCUaH9igzs5nAOZIOY6kzgSKmAxtUmdH4uKSB5g5zkLQj3iG4P12vzDS8P5W5okgPonwfxzz74GZoyDe+H5bJo4gJuJnQFDNrpINbMQetRSPmoI/gCsAw0sBA5jdkmQDsjivx7Zn9yvJWymdlK3eRPgHYX9KHrbWb9gqr4ApEdubzANr37SkaVX8UNy/dH3cQk83jyRIzwGrp1cuElMdjBe9gozyAdz73w9fbVdzT70drc7xZ+HuQZbdGMzOzdyRNxeUnO3CTnwmbiA9Q9TOz8Y3m05mkgYTr8PZuxyryvifwvJkVdfzfxcxukfQwBdvxyL2uVmaQ9iqYXWuUG3CHPNfg6/SuyVybjg+mbWJml3Qgj3rl6RF85upkYFrlXZH0aAqrx6phDK6Il1FLUXoA+GpOaa06K9sOOlqvXdKupjZ9II1914KgQ4QSGAQZkgJW2Wz9vcAakvZL57ea2UIze0PSOcCPJL2Ed8y/g3/Us3tUXYSPQt8g6VxgM3xt3QWWto1oIK08g4CbJV2GK5ILgY/iH++plKzlMLOHJI2jfAuKQiRdjI9U/h03E9sZ74gVmU1WmIQ7p/gQPqKa5QXgL3KX3yvj5kcPmtltqayz5O66T5e0EK+Xk2h8tPTrkt7ClYbD8dmrMu+RI3ElcWyq4xdxedgNd07SUnRTUvabYuqWSXOepDG46dZi4DH8N+RHyq/EPVW2yLcSeBo319wOmGNmFzaQbWUW+hhJE4FXzWx6QbwrcS99t6dnOB2fVdjSzH7AUkXickm/wT2sfpe2ZlP1lmkPSXvgs37PpLr5GfDDVDeT8Q7k5yl/vpX0hkq6De/wTs8M1tTiAtz8cKKkUXgn8z34TPA9ab1uXZjZE5L+AIyW7yP6FP58t6L17MONwChJJ+Ed533x+mwPZ+Ht0q9TujvhSlO2XNMlXQRcI+k8vG5XTnluaWbt2W6mJpK2wWeOKmZ6O0laG3cwUnm3foU/42OAAZI+kUnioTTYNJTqJoB5zsLXkea5AfdYPBx4n6T3VS5YZq/DZOaJmQ0pyyS191fh78wfzOzlzLUlko4HfpfkYByuNGyGe6Tcrx4ltF55SvlNwuspaxVydyrf+Fpm62Y2m8YGtIr4WcrvL5IuwL1rnogPlnaYJtRrV7Wrg/A2fVID6QVBx+gMbzNxxPHferDUe1/RsUkmnnCFaxb+sbob+FhBeh/AO8KLcDOd0/FNzGk0rdw9/fGZj3/gHeKF+AfmXFp7LBxCsQe1HSq/KxduwFEl+Q7HP1LzU57/JHkbrVHeR4Af5cJacA+sR+BrehbhH+iNcvE2T3EX4ErGMIq9g06uUl7DP9iT8Bm1p4D/KSpLLmyrVL75qWxP4Z2lDbtIBrMeJFfCO76v4OtIR+GDBfnn1w937DMT7+jMwjuyO5Y9Y9p6HBTutW82PpPXUhQvha2Fe5Z8IdXvNODozPVD8LUzi/DBg+1p68GvTf0X1MtmuKv2V8h4ccSVzFMzv/lx4OA66nnrVJ4FtPaKWbN+UtgG+Hrc5/HZjhm4E6UPNvJsU3jf9EwraU0G9sjFWQFXPuckGfg5buJmtPUOWupNN4UdleRjIa4s7Z6th4wcHIsPPLyJm5LeSYOeXWu9pwVxitrfKzJxZlSJY6mOl8MHbr5YkH4r2Uthy+GWAu/KVUYWCo/c/fcDf6yzDnZNaexa5frn8G/AAtxKZCpuvbF8lXe1zTOvR55SvBPSvQdlwg5MYT+u5/c040i/4Z+prFNxE+RW3nvzclYi622eb3vqNXdvp7ar6dpxuIKpavUURxzNPiquioMgCDoNScfhyuLgTFgL/oHcr+qNHc93ON5RX93MmuVoIAiCHox8s/E7cPf/nfrey/eRexXY3czurCP+ebiitan5GusgQNJ9wFgzO6O7yxL0HmKLiCAIuoIxwDqSdu3uggRBsGxjZvea2UpdNPCzDfBoLQVQ0iBJ++AmmaNCAQwqSNoetzwZ3d1lCXoXsSYwCIJOx8wWSDoU94waBEGwTGC+t+nWdUS9GDeFvhn4RacWKvhvYwBwqGXWiAZBVxDmoEEQBEEQBEEQBL2IMAcNgiAIgiAIgiDoRYQSGARBEARBEARB0IsIJTAIgiAIgiAIgqAXEUpgEARBEARBEARBLyKUwCAIgiAIgiAIgl7E/wN0k/M3gDArHgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1080x720 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "im, ax = plt.subplots(16,1, figsize = (15,10))\n",
    "ax[0].set(title = \"Genotypes of the 16 founders\")\n",
    "for k in range (16):\n",
    "    ax[k].imshow (np.expand_dims(founders_ch1_1015.T.astype(int)[k],1).T, aspect = 20)\n",
    "    ax[k].set(ylabel = \"F{}\".format(k+1))\n",
    "ax[15].set(xlabel = \"{} SNPs (purple = identical to the founder F12/N2, yellow = different)\".format(p))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Shuffle founders' genotypes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulated founders"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:41:35.682654Z",
     "start_time": "2019-07-03T17:41:35.676520Z"
    },
    "hide_input": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from numpy.random import choice\n",
    "import random as rd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import copy \n",
    "import pickle\n",
    "from pprint import pprint\n",
    "import copy\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:41:35.744528Z",
     "start_time": "2019-07-03T17:41:35.725852Z"
    }
   },
   "outputs": [],
   "source": [
    "SMALL_SIZE = 7\n",
    "MEDIUM_SIZE = 15\n",
    "BIGGER_SIZE = 20\n",
    "\n",
    "plt.rc('font', size=SMALL_SIZE)          # controls default text sizes\n",
    "plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize\n",
    "plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:41:35.802871Z",
     "start_time": "2019-07-03T17:41:35.777891Z"
    }
   },
   "outputs": [],
   "source": [
    "def recombine_linkage (parent_A,parent_B,linkage) :\n",
    "    '''Recombines 2 parents' haplotypes at a random position chosen according to linkage'''\n",
    "    r = choice(range(1,len(parent_A)),p=linkage)    # position of the recombination\n",
    "    parent = rd.randint(0,1)\n",
    "    child = np.copy([parent_A,parent_B][parent])\n",
    "    child[r:] = [parent_A,parent_B][1-parent][r:]\n",
    "    return child\n",
    "\n",
    "def sample_parents (A) :\n",
    "    '''Takes 2 parents among the individuals in a generation'''\n",
    "    parent_A = rd.choice(A)\n",
    "    parent_B = rd.choice(A)\n",
    "    while (parent_B == parent_A).all() :\n",
    "        parent_B = rd.choice(A)\n",
    "    return parent_A,parent_B\n",
    "\n",
    "def shuffle (A,G,N,p,linkage) :\n",
    "    '''Recombines founders' haplotypes (p SNPs) for G generations with N individuals at each step.'''\n",
    "    B=np.zeros((N,p),dtype=int)\n",
    "    for k in range (N):\n",
    "            (parent_A,parent_B)=sample_parents(A)                # First generation\n",
    "            B[k] = recombine_linkage(parent_A,parent_B,linkage)\n",
    "    A = np.copy(B)\n",
    "    for g in range(1,G):\n",
    "        for k in range (N):\n",
    "            (parent_A,parent_B)=sample_parents(A)\n",
    "            B[k] = recombine_linkage(parent_A,parent_B,linkage)\n",
    "        np.copyto(A,B)\n",
    "    return A\n",
    "\n",
    "def reverse_SNPs (d_haplo,F_geno) :\n",
    "    '''Converts an array of SNPs from haplotype to genotype.'''\n",
    "    g = np.copy(d_haplo)\n",
    "    for individual in g:\n",
    "        #print (list(filter(lambda x: type(x)!=np.int64, individual)))\n",
    "        for k in range (p):\n",
    "            assert type(individual[k]-1)==np.int64, individual[k]\n",
    "            individual[k]=F_geno[individual[k]-1][k]\n",
    "    return g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:41:35.851367Z",
     "start_time": "2019-07-03T17:41:35.838597Z"
    }
   },
   "outputs": [],
   "source": [
    "def iterate_and_save (n,p,G,N,I,F_haplo,F_geno,linkage) :\n",
    "    '''Simulates crossbreedings and saves the resulting genotypes (SNPs) + haplotypes in 2 binary files. '''\n",
    "    haplo = np.zeros((n+N*I,p),dtype=int)\n",
    "    haplo[:n] = F_haplo[:]\n",
    "    geno = np.zeros((n+N*I,p),dtype=int)\n",
    "    geno[:n] = F_geno[:]\n",
    "    A = np.copy(F_haplo)\n",
    "    for i in range (0,I):\n",
    "        d_haplo = shuffle (A,G,N,p,linkage)\n",
    "        haplo[n+i*N:n+(i+1)*N] = d_haplo                               # Add haplotypes of descentants (RILs)\n",
    "        geno[n+i*N:n+(i+1)*N] = reverse_SNPs(d_haplo,F_geno)     # Add the conversion into genotypes\n",
    "        if i%10 == 9 :\n",
    "            print (\"Iteration {0}/{1}\".format(i+1,I))\n",
    "    assert (F_haplo==np.array([[j for k in range(p)] for j in range(1,n+1)])).all(), F_haplo\n",
    "    assert 0 not in d_haplo\n",
    "    with open(\"Simulations_haplotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"wb\") as handler:\n",
    "        pickle.dump(haplo.tolist(),handler)   # Lists take much less space\n",
    "    with open(\"Simulations_genotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"wb\") as handler:\n",
    "        pickle.dump(geno.tolist(),handler)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resulting files :\n",
    "   - Genotypes 1,0,1,0,1, ... ,1,0,1,0,0 =  \n",
    "`[[[founder 1], ... , [founder 16]], [[[it 1 ind 1], ... ,[it 1 ind N]], ... ,[[it I ind 1], ... ,[it I ind N]]]`,\n",
    "   - Haplotypes 3,3,3,12,12, ... ,1,1,1,1,1 =  \n",
    "`[[[1,1,1,1,1,1], ... , [16,16,16,16,16,16]][[[1,1], ... ,[1,N]], ... ,[[I,1], ... ,[I,N]]]]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:41:35.905428Z",
     "start_time": "2019-07-03T17:41:35.899470Z"
    }
   },
   "outputs": [],
   "source": [
    "n = 16    # founders\n",
    "p = 1000  # nb of SNPs\n",
    "G = 20    # nb of generations\n",
    "N = 100   # number recombining individuals in a generation after sampling\n",
    "I = 100   # nb of itérations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:15.964612Z",
     "start_time": "2019-07-03T17:30:14.218199Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 10/100\n",
      "Iteration 20/100\n",
      "Iteration 30/100\n",
      "Iteration 40/100\n",
      "Iteration 50/100\n",
      "Iteration 60/100\n",
      "Iteration 70/100\n",
      "Iteration 80/100\n",
      "Iteration 90/100\n",
      "Iteration 100/100\n"
     ]
    }
   ],
   "source": [
    "F_haplo = np.array([[j for i in range(p)] for j in range(1,n+1)])    # initial array (n founders and p SNPs)\n",
    "F_geno = np.array([[rd.randint(0,1) for snp in range(p)] for founder in range (n)])\n",
    "linkage = np.array([1/(p-1) for k in range(p-1)])\n",
    "iterate_and_save (n,p,G,N,I,F_haplo,F_geno,linkage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:19.050667Z",
     "start_time": "2019-07-03T17:31:15.976674Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Simulations_haplotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"rb\") as handler:\n",
    "    haplo = pickle.load(handler)\n",
    "    F_haplo = np.array(haplo[:n])\n",
    "    d_haplo = np.array(haplo[n:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:21.847867Z",
     "start_time": "2019-07-03T17:31:19.057649Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Simulations_genotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"rb\") as handler:\n",
    "    geno = pickle.load(handler)\n",
    "    F_geno = np.array(geno[:n])\n",
    "    d_geno = np.array(geno[n:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:21.865596Z",
     "start_time": "2019-07-03T17:31:21.853703Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 1000) (10000, 1000) (16, 1000) (10000, 1000)\n"
     ]
    }
   ],
   "source": [
    "print(F_haplo.shape,d_haplo.shape,F_geno.shape,d_geno.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Real founders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "lang": "en"
   },
   "source": [
    "### Full chromosome I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:00.969120Z",
     "start_time": "2019-07-03T17:42:00.957036Z"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from numpy.random import choice\n",
    "import random as rd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import copy \n",
    "import pickle\n",
    "from pprint import pprint\n",
    "import copy\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:00.994634Z",
     "start_time": "2019-07-03T17:42:00.974059Z"
    }
   },
   "outputs": [],
   "source": [
    "SMALL_SIZE = 7\n",
    "MEDIUM_SIZE = 15\n",
    "BIGGER_SIZE = 20\n",
    "\n",
    "plt.rc('font', size=SMALL_SIZE)          # controls default text sizes\n",
    "plt.rc('axes', titlesize=MEDIUM_SIZE)     # fontsize of the axes title\n",
    "plt.rc('axes', labelsize=MEDIUM_SIZE)    # fontsize of the x and y labels\n",
    "plt.rc('xtick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('ytick', labelsize=SMALL_SIZE)    # fontsize of the tick labels\n",
    "plt.rc('legend', fontsize=SMALL_SIZE)    # legend fontsize\n",
    "plt.rc('figure', titlesize=BIGGER_SIZE)  # fontsize of the figure title"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:01.015877Z",
     "start_time": "2019-07-03T17:42:00.999454Z"
    }
   },
   "outputs": [],
   "source": [
    "def recombine_linkage (parent_A,parent_B,linkage) :\n",
    "    '''Recombines 2 parents' haplotypes at a random position chosen according to linkage'''\n",
    "    r = choice(range(len(parent_A)),p=linkage)    # position of the recombination\n",
    "    parent = rd.randint(0,1)\n",
    "    child = np.copy([parent_A,parent_B][parent])\n",
    "    child[r:] = [parent_A,parent_B][1-parent][r:]\n",
    "    return child\n",
    "\n",
    "def sample_parents (A) :\n",
    "    '''Takes 2 parents among the individuals in a generation'''\n",
    "    parent_A = rd.choice(A)\n",
    "    parent_B = rd.choice(A)\n",
    "    while (parent_B == parent_A).all() :\n",
    "        parent_B = rd.choice(A)\n",
    "    return parent_A,parent_B\n",
    "\n",
    "def shuffle (A,G,N,p,linkage) :\n",
    "    '''Recombines founders' haplotypes (p SNPs) for G generations with N individuals at each step.'''\n",
    "    B=np.zeros((N,p),dtype=int)\n",
    "    for k in range (N):\n",
    "            (parent_A,parent_B)=sample_parents(A)                # First generation\n",
    "            B[k] = recombine_linkage(parent_A,parent_B,linkage)\n",
    "    A = np.copy(B)\n",
    "    for g in range(1,G):\n",
    "        for k in range (N):\n",
    "            (parent_A,parent_B)=sample_parents(A)\n",
    "            B[k] = recombine_linkage(parent_A,parent_B,linkage)\n",
    "        np.copyto(A,B)\n",
    "    return A\n",
    "\n",
    "def reverse_SNPs (d_haplo,F_geno) :\n",
    "    '''Converts an array of SNPs from haplotype to genotype.'''\n",
    "    g = np.copy(d_haplo)\n",
    "    for individual in g:\n",
    "        #print (list(filter(lambda x: type(x)!=np.int64, individual)))\n",
    "        for k in range (p):\n",
    "            assert type(individual[k]-1)==np.int64, individual[k]\n",
    "            individual[k]=F_geno[individual[k]-1][k]\n",
    "    return g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:01.034653Z",
     "start_time": "2019-07-03T17:42:01.023826Z"
    }
   },
   "outputs": [],
   "source": [
    "def iterate_and_save (n,p,G,N,I,F_haplo,F_geno,linkage) :\n",
    "    '''Simulates crossbreedings and saves the resulting genotypes (SNPs) + haplotypes in 2 binary files. '''\n",
    "    haplo = np.zeros((n+N*I,p),dtype=int)\n",
    "    haplo[:n] = F_haplo[:]\n",
    "    geno = np.zeros((n+N*I,p),dtype=int)\n",
    "    geno[:n] = F_geno[:]\n",
    "    A = np.copy(F_haplo)\n",
    "    for i in range (0,I):\n",
    "        d_haplo = shuffle (A,G,N,p,linkage)\n",
    "        haplo[n+i*N:n+(i+1)*N] = d_haplo                               # Add haplotypes of descentants (RILs)\n",
    "        geno[n+i*N:n+(i+1)*N] = reverse_SNPs(d_haplo,F_geno)     # Add the conversion into genotypes\n",
    "        if i%10 == 9 :\n",
    "            print (\"Iteration {0}/{1}\".format(i+1,I))\n",
    "    assert (F_haplo==np.array([[j for k in range(p)] for j in range(1,n+1)])).all(), F_haplo\n",
    "    assert 0 not in d_haplo\n",
    "    with open(\"Recombinations_haplotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"wb\") as handler:\n",
    "        pickle.dump(haplo.tolist(),handler)   # Lists take much less space\n",
    "    with open(\"Recombinations_genotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"wb\") as handler:\n",
    "        pickle.dump(geno.tolist(),handler)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resulting files :\n",
    "   - Genotypes 1,0,1,0,1, ... ,1,0,1,0,0 =  \n",
    "`[[[founder 1], ... , [founder 16]], [[[it 1 ind 1], ... ,[it 1 ind N]], ... ,[[it I ind 1], ... ,[it I ind N]]]`,\n",
    "   - Haplotypes 3,3,3,12,12, ... ,1,1,1,1,1 =  \n",
    "`[[[1,1,1,1,1,1], ... , [16,16,16,16,16,16]][[[1,1], ... ,[1,N]], ... ,[[I,1], ... ,[I,N]]]]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:01.052859Z",
     "start_time": "2019-07-03T17:42:01.043118Z"
    }
   },
   "outputs": [],
   "source": [
    "p, n = np.shape(founders_ch1)    # p = nb of SNPs (37525) / n = nb of founders (16)\n",
    "G = 20    # nb of generations\n",
    "N = 50   # number recombining individuals in a generation after sampling\n",
    "I = 50   # nb of itérations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:01.087693Z",
     "start_time": "2019-07-03T17:42:01.076363Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Linkage_p{}.pkl\".format(p),\"rb\") as handler:\n",
    "    linkage = pickle.load(handler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:24.208439Z",
     "start_time": "2019-07-03T17:31:22.123069Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "F_haplo = np.array([[j for i in range(p)] for j in range(1,n+1)])    # initial array (n founders and p SNPs)\n",
    "F_geno = founders_ch1.T\n",
    "assert (reverse_SNPs (F_haplo,F_geno) == F_geno).all()\n",
    "#iterate_and_save (n,p,G,N,I,F_haplo,F_geno,linkage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:23.747438Z",
     "start_time": "2019-07-03T17:42:12.314253Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Recombinations_haplotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"rb\") as handler:\n",
    "    haplo = pickle.load(handler)\n",
    "    F_haplo = np.array(haplo[:n])\n",
    "    d_haplo = np.array(haplo[n:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:39.811333Z",
     "start_time": "2019-07-03T17:42:23.750633Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Recombinations_genotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"rb\") as handler:\n",
    "    geno = pickle.load(handler)\n",
    "    F_geno = np.array(geno[:n])\n",
    "    d_geno = np.array(geno[n:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:39.900975Z",
     "start_time": "2019-07-03T17:42:39.878062Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 37525) (2500, 37525) (16, 37525) (2500, 37525)\n"
     ]
    }
   ],
   "source": [
    "print(F_haplo.shape,d_haplo.shape,F_geno.shape,d_geno.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:42:56.305436Z",
     "start_time": "2019-07-03T17:42:39.921690Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1,ax2) = plt.subplots(2,1,figsize=(14,3))\n",
    "ax1.imshow(d_geno)\n",
    "ax2.imshow(d_haplo)\n",
    "fig.text(0.5, 0.06, 'SNPs', ha='center', va='center',fontsize=15)\n",
    "fig.text(0.08, 0.5, 'Haplotype Genotype', ha='center', va='center', rotation='vertical',fontsize=15)\n",
    "fig.text(0.5, 0.92, 'Expected prediction compared to input data for chromosomes from the training set', ha='center', va='center',fontsize=17)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1015 SNPs from ch. I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:54.900241Z",
     "start_time": "2019-07-03T17:31:54.838678Z"
    }
   },
   "outputs": [],
   "source": [
    "def recombine_linkage (parent_A,parent_B,linkage) :\n",
    "    '''Recombines 2 parents' haplotypes at a random position chosen according to linkage'''\n",
    "    r = choice(range(len(parent_A)),p=linkage)    # position of the recombination\n",
    "    parent = rd.randint(0,1)\n",
    "    child = np.copy([parent_A,parent_B][parent])\n",
    "    child[r:] = [parent_A,parent_B][1-parent][r:]\n",
    "    return child\n",
    "\n",
    "def sample_parents (A) :\n",
    "    '''Takes 2 parents among the individuals in a generation'''\n",
    "    parent_A = rd.choice(A)\n",
    "    parent_B = rd.choice(A)\n",
    "    while (parent_B == parent_A).all() :\n",
    "        parent_B = rd.choice(A)\n",
    "    return parent_A,parent_B\n",
    "\n",
    "def shuffle (A,G,N,p,linkage) :\n",
    "    '''Recombines founders' haplotypes (p SNPs) for G generations with N individuals at each step.'''\n",
    "    B=np.zeros((N,p),dtype=int)\n",
    "    for k in range (N):\n",
    "            (parent_A,parent_B)=sample_parents(A)                # First generation\n",
    "            B[k] = recombine_linkage(parent_A,parent_B,linkage)\n",
    "    A = np.copy(B)\n",
    "    for g in range(1,G):\n",
    "        for k in range (N):\n",
    "            (parent_A,parent_B)=sample_parents(A)\n",
    "            B[k] = recombine_linkage(parent_A,parent_B,linkage)\n",
    "        np.copyto(A,B)\n",
    "    return A\n",
    "\n",
    "def reverse_SNPs (d_haplo,F_geno) :\n",
    "    '''Converts an array of SNPs from haplotype to genotype.'''\n",
    "    g = np.copy(d_haplo)\n",
    "    for individual in g:\n",
    "        #print (list(filter(lambda x: type(x)!=np.int64, individual)))\n",
    "        for k in range (p):\n",
    "            assert type(individual[k]-1)==np.int64, individual[k]\n",
    "            individual[k]=F_geno[individual[k]-1][k]\n",
    "    return g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:54.932888Z",
     "start_time": "2019-07-03T17:31:54.908043Z"
    }
   },
   "outputs": [],
   "source": [
    "def iterate_and_save (n,p,G,N,I,F_haplo,F_geno,linkage) :\n",
    "    '''Simulates crossbreedings and saves the resulting genotypes (SNPs) + haplotypes in 2 binary files. '''\n",
    "    haplo = np.zeros((n+N*I,p),dtype=int)\n",
    "    haplo[:n] = F_haplo[:]\n",
    "    geno = np.zeros((n+N*I,p),dtype=int)\n",
    "    geno[:n] = F_geno[:]\n",
    "    A = np.copy(F_haplo)\n",
    "    for i in range (0,I):\n",
    "        d_haplo = shuffle (A,G,N,p,linkage)\n",
    "        haplo[n+i*N:n+(i+1)*N] = d_haplo                               # Add haplotypes of descentants (RILs)\n",
    "        geno[n+i*N:n+(i+1)*N] = reverse_SNPs(d_haplo,F_geno)     # Add the conversion into genotypes\n",
    "        if (i+1)//5==(i+1)/5 :\n",
    "            print (\"Iteration {0}/{1}\".format(i+1,I))\n",
    "    assert (F_haplo==np.array([[j for k in range(p)] for j in range(1,n+1)])).all(), F_haplo\n",
    "    assert 0 not in d_haplo\n",
    "    with open(\"Recombinations_haplotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"wb\") as handler:\n",
    "        pickle.dump(haplo.tolist(),handler)   # Lists take much less space\n",
    "    with open(\"Recombinations_genotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"wb\") as handler:\n",
    "        pickle.dump(geno.tolist(),handler)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Resulting files :\n",
    "   - Genotypes 1,0,1,0,1, ... ,1,0,1,0,0 =  \n",
    "`[[[founder 1], ... , [founder 16]], [[[it 1 ind 1], ... ,[it 1 ind N]], ... ,[[it I ind 1], ... ,[it I ind N]]]`,\n",
    "   - Haplotypes 3,3,3,12,12, ... ,1,1,1,1,1 =  \n",
    "`[[[1,1,1,1,1,1], ... , [16,16,16,16,16,16]][[[1,1], ... ,[1,N]], ... ,[[I,1], ... ,[I,N]]]]`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T19:11:59.895826Z",
     "start_time": "2019-07-03T19:11:59.872298Z"
    }
   },
   "outputs": [],
   "source": [
    "p, n = np.shape(founders_ch1_1015)    # p = nb of SNPs (37525) / n = nb of founders (16)\n",
    "G = 20    # nb of generations\n",
    "N = 100   # number recombining individuals in a generation after sampling\n",
    "I = 100   # nb of itérations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:31:54.991817Z",
     "start_time": "2019-07-03T17:31:54.970004Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Linkage_p{}.pkl\".format(p),\"rb\") as handler:\n",
    "    linkage = pickle.load(handler)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T17:33:06.004499Z",
     "start_time": "2019-07-03T17:31:54.998692Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Iteration 5/100\n",
      "Iteration 10/100\n",
      "Iteration 15/100\n",
      "Iteration 20/100\n",
      "Iteration 25/100\n",
      "Iteration 30/100\n",
      "Iteration 35/100\n",
      "Iteration 40/100\n",
      "Iteration 45/100\n",
      "Iteration 50/100\n",
      "Iteration 55/100\n",
      "Iteration 60/100\n",
      "Iteration 65/100\n",
      "Iteration 70/100\n",
      "Iteration 75/100\n",
      "Iteration 80/100\n",
      "Iteration 85/100\n",
      "Iteration 90/100\n",
      "Iteration 95/100\n",
      "Iteration 100/100\n"
     ]
    }
   ],
   "source": [
    "F_haplo = np.array([[j for i in range(p)] for j in range(1,n+1)])    # initial array (n founders and p SNPs)\n",
    "F_geno = founders_ch1_1015.T\n",
    "assert (reverse_SNPs (F_haplo,F_geno) == F_geno).all()\n",
    "iterate_and_save (n,p,G,N,I,F_haplo,F_geno,linkage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T19:14:09.118465Z",
     "start_time": "2019-07-03T19:14:05.603997Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Recombinations_haplotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"rb\") as handler:\n",
    "    haplo = pickle.load(handler)\n",
    "    F_haplo = np.array(haplo[:n])\n",
    "    d_haplo = np.array(haplo[n:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T19:14:11.319142Z",
     "start_time": "2019-07-03T19:14:09.122146Z"
    }
   },
   "outputs": [],
   "source": [
    "with open(\"Recombinations_genotypes_n{0}_p{1}_G{2}_N{3}_I{4}.pkl\".format(n,p,G,N,I),\"rb\") as handler:\n",
    "    geno = pickle.load(handler)\n",
    "    F_geno = np.array(geno[:n])\n",
    "    d_geno = np.array(geno[n:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T19:14:11.328325Z",
     "start_time": "2019-07-03T19:14:11.322039Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(16, 1015) (10000, 1015) (16, 1015) (10000, 1015)\n"
     ]
    }
   ],
   "source": [
    "print(F_haplo.shape,d_haplo.shape,F_geno.shape,d_geno.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-07-03T19:18:22.077385Z",
     "start_time": "2019-07-03T19:18:21.242369Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x216 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1,ax2) = plt.subplots(2,1,figsize=(14,3))\n",
    "ax1.imshow(d_geno, aspect = 0.007)\n",
    "ax2.imshow(d_haplo, aspect = 0.007)\n",
    "fig.text(0.5, 0.06, 'SNPs', ha='center', va='center',fontsize=15)\n",
    "fig.text(0.08, 0.5, 'Haplotype Genotype', ha='center', va='center', rotation='vertical',fontsize=15)\n",
    "fig.text(0.5, 0.92, 'Expected prediction compared to input data for chromosomes from the training set', ha='center', va='center',fontsize=17)\n",
    "plt.show()"
   ]
  }
 ],
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