{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final Processing of AKARI-SEP Blind source catalogue\n",
    "\n",
    "![HELP LOGO](https://avatars1.githubusercontent.com/u/7880370?s=100&v=4>)\n",
    "\n",
    "\n",
    "The final processing stage requires:\n",
    "1. Quick validation of blind catalogues and Bayesian Pvalue maps\n",
    "2. Skewness level\n",
    "3. Adding flag to catalogue\n",
    "4. Merging MF catalogue with XID+ flux densities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "from astropy.table import Table,hstack\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pylab as plt\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.table import Column\n",
    "\n",
    "import herschelhelp_internal\n",
    "from herschelhelp_internal.utils import gen_help_id\n",
    "import numpy.core.defchararray as np_f\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20169\n"
     ]
    }
   ],
   "source": [
    "cat=Table.read('./data/dmu22_XID+SPIRE_AKARI-SEP_BLIND.fits')\n",
    "cat['RA'].unit=u.deg\n",
    "cat['Dec'].unit=u.deg\n",
    "print(np.size(cat['RA']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=10</i>\n",
       "<table id=\"table112187370968\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>HELP_ID</th><th>RA</th><th>Dec</th><th>F_SPIRE_250</th><th>FErr_SPIRE_250_u</th><th>FErr_SPIRE_250_l</th><th>F_SPIRE_350</th><th>FErr_SPIRE_350_u</th><th>FErr_SPIRE_350_l</th><th>F_SPIRE_500</th><th>FErr_SPIRE_500_u</th><th>FErr_SPIRE_500_l</th><th>Bkg_SPIRE_250</th><th>Bkg_SPIRE_350</th><th>Bkg_SPIRE_500</th><th>Sig_conf_SPIRE_250</th><th>Sig_conf_SPIRE_350</th><th>Sig_conf_SPIRE_500</th><th>Rhat_SPIRE_250</th><th>Rhat_SPIRE_350</th><th>Rhat_SPIRE_500</th><th>n_eff_SPIRE_250</th><th>n_eff_SPIRE_500</th><th>n_eff_SPIRE_350</th><th>Pval_res_250</th><th>Pval_res_350</th><th>Pval_res_500</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>deg</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>bytes27</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th></tr></thead>\n",
       "<tr><td>161</td><td>68.8020187998</td><td>-55.6440361386</td><td>90.6751</td><td>94.6894</td><td>86.9403</td><td>56.1904</td><td>59.1176</td><td>52.3942</td><td>23.28</td><td>28.2572</td><td>18.5154</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.998708</td><td>0.998871</td><td>0.998499</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>181</td><td>68.5880998683</td><td>-55.6961908448</td><td>73.7079</td><td>77.0619</td><td>70.2107</td><td>24.2188</td><td>28.231</td><td>20.2233</td><td>18.1494</td><td>22.6425</td><td>13.7172</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.998875</td><td>0.998718</td><td>0.999774</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>541</td><td>68.8230689476</td><td>-55.5658228559</td><td>70.8249</td><td>72.371</td><td>68.5648</td><td>40.3171</td><td>43.2259</td><td>37.2499</td><td>20.4809</td><td>24.1774</td><td>16.9316</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.998847</td><td>0.999684</td><td>0.998552</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>642</td><td>68.6287515644</td><td>-55.7188357237</td><td>59.357</td><td>63.3315</td><td>55.1739</td><td>54.0893</td><td>58.3802</td><td>49.214</td><td>33.7704</td><td>38.8375</td><td>28.3352</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.999691</td><td>1.00291</td><td>0.998655</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>664</td><td>68.8008493081</td><td>-55.6279189937</td><td>51.9882</td><td>55.0119</td><td>48.8849</td><td>39.8744</td><td>43.8657</td><td>36.0955</td><td>19.6603</td><td>24.3778</td><td>14.9069</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.999397</td><td>0.999246</td><td>0.999056</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>687</td><td>68.798123027</td><td>-55.5440483187</td><td>66.2075</td><td>68.3232</td><td>63.5279</td><td>57.231</td><td>60.1696</td><td>54.6927</td><td>29.1387</td><td>32.3431</td><td>25.8108</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.999843</td><td>1.00022</td><td>0.998647</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>1689</td><td>68.7813403263</td><td>-55.5459964134</td><td>41.0318</td><td>44.0495</td><td>38.2452</td><td>18.3104</td><td>21.2739</td><td>15.515</td><td>8.96984</td><td>12.4885</td><td>5.3071</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.999731</td><td>0.998424</td><td>1.00072</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>2034</td><td>68.7248348692</td><td>-55.6716333554</td><td>15.9437</td><td>20.2787</td><td>11.5358</td><td>4.4596</td><td>8.05879</td><td>1.71683</td><td>6.42226</td><td>10.8046</td><td>2.45879</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.998484</td><td>0.99931</td><td>0.999715</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>2709</td><td>68.6765429528</td><td>-55.5603425371</td><td>41.6327</td><td>44.538</td><td>38.879</td><td>41.6931</td><td>44.4334</td><td>39.0981</td><td>28.4497</td><td>31.3598</td><td>25.4106</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>0.998543</td><td>0.998984</td><td>1.00003</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>2763</td><td>68.7218504051</td><td>-55.5480651743</td><td>35.0952</td><td>37.8051</td><td>32.3505</td><td>17.0968</td><td>20.1608</td><td>14.1521</td><td>8.89519</td><td>12.0854</td><td>5.58304</td><td>-0.0152475</td><td>-0.0258911</td><td>-0.0185354</td><td>0.00263353</td><td>0.0037064</td><td>0.0054025</td><td>1.00008</td><td>0.99852</td><td>1.00066</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=10>\n",
       "          HELP_ID                 RA      ... Pval_res_350 Pval_res_500\n",
       "                                 deg      ...                          \n",
       "          bytes27              float64    ...   float32      float32   \n",
       "--------------------------- ------------- ... ------------ ------------\n",
       "161                         68.8020187998 ...          0.0          0.0\n",
       "181                         68.5880998683 ...          0.0          0.0\n",
       "541                         68.8230689476 ...          0.0          0.0\n",
       "642                         68.6287515644 ...          0.0          0.0\n",
       "664                         68.8008493081 ...          0.0          0.0\n",
       "687                          68.798123027 ...          0.0          0.0\n",
       "1689                        68.7813403263 ...          0.0          0.0\n",
       "2034                        68.7248348692 ...          0.0          0.0\n",
       "2709                        68.6765429528 ...          0.0          0.0\n",
       "2763                        68.7218504051 ...          0.0          0.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Look at Symmetry of PDFs to determine depth level of catalogue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(cat['FErr_SPIRE_250_u']-cat['F_SPIRE_250'])/(cat['F_SPIRE_250']-cat['FErr_SPIRE_250_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(cat['F_SPIRE_250']),y=skew, kind='hex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 250 $\\mathrm{\\mu m}$ depth is ~ 6mJy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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u+2aMR2WYFU9eTIZhdC7Tdc+babQ9eYnIPOC/gI+q6r6cPmfjktcnU82nqepJwHnAxSJyRta5qnqlqq5V1bVLly6d5OgnB5Hxz3xMHm8YRhadcM+bCtqavESkiEtc16jq9Tl9TgD+A3ijqu5M2lV1S/x1G3ADcEo7Y50sJmumozmKCxNjGIZhtFdtKMDXgYdV9V9y+qwCrgfepaq/TbXPjUUeiMhc4NXAg+2KdSI0mxRFLSQYVdevsV3dCwgjrSSxpH+yPFg/frI0OZ44DcMwOpV2qg1PA94F/EZENsRtfwGsAlDVK4DPAIuBr7pcR6Cqa4FDgBvitgLwHVX9URtjHReV5bwmootmCsFc66iMjBcpSOIPlUpF9bZR6Zhy4zUMw+gS2qk2vJ0x/vBX1T8G/jij/XfAmsYzZhaJanA8tKoyrDmH1mdV6ZgsaRmG0a2YMe8BIkyVoi87E2UlKEtahmF0O2YPZRiGYXQclrzaSrvnZPnjmyLRMIxuxpYND4Dc/atYLZhYbMTCkxrlYIKMscZX7as1/RNFotfQXnuuLSEahtGNWPKaAHmzmnq1YJLckgTj5O/V4564cyRWEopIQ4KrqbYsNFw8qmvX+r0xE28YhtGFWPKaIONZlUsSVv05kSYWUdXMksygoowMmaciTJJk1iwuT6loGIbRydie1xRhW1CGYRiThyUvwzAMo+OwZcMJkvV8V24ZlJx2r+Isr5W9qkSIkWyN5dk+ZZHsl6WXD7POVdWKNZVzureFRcMwOgtLXhOg3oqpuq8k8TGXitLehS5BaCWJ+V61PbF5ilQJ6xJc4mXoMZ7aXhonTKmJ1/km1o4fxT5TlsQMw+gkLHkdAIkVU31SERGilIow3Q7gidbOjuK3QUqJmGY8iSu5Yl5/23szDKMbsOR1gOQlFEFyE8VEZjiTMSmyxGUYRrdggg3DMAyj47DkNQ7McskwDGNmYMmrBdLViw80gTmln2a4cWjuP0Z27a/aV1b/9DV0IrVYDMMwZii259WEGp/AmgPuS7N9KElp6RVt8BxM20ZB1W1DFMLUOB6JnL42phopPo0+ho22Ufm5y5SGhmF0Gpa8xiBz1kNrz15VJerZx6OMdhHwk+SWkVQybaNy4hlrslWtwmyJyzCMzsKS1xQw3oKVyUPN7U4qlrgMw+hUbM/LMAzD6Dhs5jUGmTZQGf0Sy6Uods/wUnW3wqh2aS95uJnU2OmHiiOFQMEXxU/NjlQ10zYqsZMSjR9obmEyZRMuwzA6GUteLZBOYFn3/ChOUAlhBBHOcinMEH1k7YEpoJETaySHQ3WvgmiD4CJLgKG488dKYp4lLsMwOhxLXk2oufnnKAzrE1e6eziejS4gyGkPJ7EisikLDcPoBix5tUg33O+74CMYhmEALQo2ROR0EXlf/H6piBzZ3rAMwzAMI58xk5eIfBb4JPDncVMR+P/aGZQx9Zj1lWEYnUQrM683A28ABgFUdQswv51BdRKTuRSXN1ZccqtlsoQhSvWh6EZrqsb+hmEYM5lW9rxKqqoiogAiMrfNMXUUIkLBq8rhExJFX1ZV5XQRyzS+uARTr/8YTy2vpH8izU9L8iOcEtIX8FP6yfFaXxmGYUw3rcy8/lNE/h1YJCJ/AtwCXNXesDoLEaHgS/xMVlXRJyJ4nsTfu3YvaYvb6/EEfKrPcSXnthQH1cKVUE1YySshVFf4Mss+yiZfhmF0AmMmL1X9Z+A64L+AY4DPqOpXxjpPRFaKyK0i8rCIPCQil2b0ERH5sog8LiIPiMhJqWPvEZHH4td7xvexpgcRwYuTVqvt2eNUXy1fm+bLjlltlqgMw+hUWpLKq+rNwM3jHDsAPq6q94rIfGC9iNysqhtTfc4DXhS/TgW+BpwqIgcDnwXW4u6x60XkRlXdPc4YDMMwjC4kN3mJyH6y/zh3WymqC5oNrKpbga3x+/0i8jCwHEgnrzcC31anILhTRBaJyGHAWcDNqrorjuVm4Fzg2lY/WLtIL7Wl96LyHNwTcUSl5EnddMqTbHf5gsTLfTWlVNzeWnppMmkP4nXBold7jWRGlvEctYsJrRkHknItteMkn2+8+2+GYRjtIDd5qeqkKQpF5AjgZcBddYeWA8+kvt8ct+W1Z419EXARwKpVqyYl3jzqE9RYKsDE7zAhik9IJx4RqdT1ShJcshfmASpQDpVQ02rBpK+rE5Z28ghDKHrOE9FLZRkfl8Dqy6ekYyKj3Q2RSmLx9S2JGcb0MJX3vJlM7p6XiCyIvx6c9Wr1AiIyD7df9lFV3Vd/OOOU3PJUWeOr6pWqulZV1y5durTVsMbNeAsR1yeuZiSJrODVij1ExM2aNHt2FkTZFlSqVaFHzYuqoKP+B5yXhJsn57E/m2EYk8tU3fNmOs32vL4DvB5YT2NCUeCosQYXkSIucV2jqtdndNkMrEx9vwLYErefVdf+s7Gu1ylkCTWqM7HGdh2ntCJvRjTeumITvY5hGEa7yZ15qerr469HqupR8dfk1UriEuDrwMOq+i853W4E3h2rDl8B7I33yn4MvFpEDhKRg4BXx22GYRiGMbbaUER+qqrnjNWWwWnAu4DfiMiGuO0vgFUAqnoFsA54LfA4MAS8Lz62S0Q+D9wdn/e5RLzR3eSsmNrynGEYRg3N1IZ9wBxgSTz7Se6qC4BlYw2sqreTvXeV7qPAxTnHvgF8Y6zrdCKq2rB0qIkKou6YxmKKVvfPICXsoHGtV+PG+vbEjWM8S4Hj7W8YhjFZNJt5fRD4KC5Rrad6v9sHXN7muGYcia1TXlXlhnYRfJxoQzP6J6R9Bqtvq21hbBdVv18lQI/v2sphbbvnQYjg1QUVxrFU2hOZP66IpRd/07KjhyUuwzCmiWZS+X8D/k1EPtKKo8ZsIFHsZT3zlNkuggdEkZO6t1IIMpkdhbFaMZlFpT0RPa8qg3dJrFoQ00895xVRPSf9nFeSDKVuapb0SX4pMoUlWNIyjJnCrsHSdIcwbYy556WqXxGR3wOOSPdX1W+3Ma4ZTZLEWm93vofjIch4qrj+4eT0+AU/e5w8G6i6yVfGtSxxGYYxc2lFsPG/gRcCG3CrS+DufbM2eRmGYRjTSyvehmuBl2p9EShjXIznGSvVanmULNf3Vh0uEjspSB5UbrSNyqLeNioZK9LaZckkVrONMgxjqmkleT0IHErsU2iMH5FqwoH8JJZ28fCkmvAyXTTi/2QtVSoQpRJXMnZiQ+XHzh1pwUbqW8AlMEl5HSYEEQiK59WeYbZRhmFMJa0kryXARhH5NTCaNKrqG9oWVReS3NDrJe9pU9zaQxKfo8RfMrOCZKgDw1ggUo9qYtybE2N9/+xu1URVr/hIXccSmGEY7aSV5PVX7Q5iNpG3fCjJ9Kyhf0rOmDHWuGp+tZi0xjHiuK5jGIYxWbSiNvy5iBwOvEhVbxGROTiTcsMwDMOYFsaspCwif4KrpPzvcdNy4AftDMroZEzXYxhG+xkzeeHsm07DOWugqo8BL2hnUEYrqNsnG4cINOlaf04yznjd6+sTVaWYpQlTDcNoM63seY2qailVPLGA/Xk9YfJspsApDNOKw7QKMGUiVTk/EU74dXrBpMBlvThEgXLk6oal99ei2ILKj3tV/q3r4qh8huRzpHokw0UVVWX1rLFcRQzDMMZLK8nr5yLyF0C/iLwK+DPg/7Q3rO6m3maq2i6xrF4rPoT1/bMSUqDxFFrS5zRPYEnF5vTxMB7Hz3DycLOz7Oe8sq5RLYhpicswjMmnlWXDTwHbgd/gzHrXAZ9uZ1CzhVz1n0iOIjF/rIhsc+C8c/KqMyv5FlS+Jxnt+TEZhmG0i1ZmXv3AN1T1KgAR8eO2oXYGZhiGYRh5tDLz+ikuWSX0A7e0Jxwjwc8x+fXIfy6rXsAxUeFEqNmijiBqFIiYNsMwjOmglZlXn6oOJN+o6kD8rJcxCdQXhUzafKn6GwZabU+W6fJso6A28STnpPfXkj20hhphKUuqQMFTrXyfOE2VIvDFFcisCERoXLL0kjgzCm8ahmEcKK3MvAZF5KTkGxE5GRhuX0izC2eYG7+nmmzcfpXgiVMBVo9JZS9rPCkh6Z8INSS+sMQ+h57Es7pUoolwZQTqq7OElf2yarGxqhq1Or5I4x6ZYRjGZNDKzOtS4PsisiX+/jDg7e0LaXZSMe+V+nZBE3/DdPu4fOqr16iVuKcOZDQ3HSvjBJcIbaZlGEb7aZq8RMQDeoCXAMfg7laPqGp5CmKbdXTHPb8rPoRhGDOcpslLVSMR+aKqvhJXGsUwDMMwpp1W9rx+IiJvFVsLmhbSdcAma7zW+za3oMpvn0hkhmEYrdPKntfHgLlAKCLDJGYPqgvaGtksJ50A6i2lNKe99bG1Ye8rrb9I3kTqik8WvMbKyoE6NWQSaKUuGVU3kJr4DcMwJpFWSqLMn4pAjEbSVk/ZtlHV9iy3jKZjZxST1PiAAmFUvU4Q20kVvNoEFmpV1p8Z9/hCMgzDaJlWSqKIiLxTRP5X/P1KETml/aHNbnILVo6jfSIXUVyyqj+UlxzHypk26zIMox20suf1VeCVwB/F3w8Al7ctIsMwDMMYg1b2vE5V1ZNE5D4AVd0tIj1tjsvIoVmZkqz28e49NRNbaLwxVj/Ti7RxT0zj5cf6B59r3D9sWmYYxgRpJXmVYzNeBRCRpTSaLjQgIt8AXg9sU9XjM45/ArgwFcexwFJV3SUim4D9OIOHQFXXthBnV5GVjIS4Fhe1tlEerlRJur2+3EoyWPKgcr0tVbJvlrU8mDhwJKVOJBZ8JMkniq/rqVZsoZJxXH0vrYmvemG1simGYUyIVpYNvwzcABwiIn8L3A78XQvnXQ2cm3dQVf9JVU9U1ROBPwd+rqq7Ul3Ojo/PusQFtUkmebn2qm1UIbGOksb2rAlUUu7ES40jsTQwiLITV7W2V+04ScJLE5G2jqrtnzd+lGECbBiGMRatqA2vEZH1wDlx05tU9eEWzrtNRI5oMY4LgGtb7DuraGYbRUXyXtse5SQDkfo3yfdjx9DQxvhmTHk9xWZehmFMgFZmXgBzcH/ke9SWRzlgYof6c4H/SjUr7uHo9SJy0RjnXyQi94jIPdu3b5/M0GYMdm83DCMhfc/bv2fX2Cd0Ka1I5T8DfAs4GFgCfFNEJrOS8h8Av6xbMjxNVU8CzgMuFpEz8k5W1StVda2qrl26dOkkhmUYhjHzSN/z5i86eLrDmTZaEWxcALxMVUcAROQLwL3A30xSDO+gbslQVbfEX7eJyA3AKcBtk3S97idvC6n2meSx+7d0oQOcFirONd+ml4ZhjINWlg03AX2p73uBJybj4iKyEDgT+GGqba6IzE/eA6/GTIEz8eru9xqrDD1pdL1I+lfPqfoWRgphpUpynQhDq+M2Mo49L8tNhmFMIq3MvEaBh0TkZtyd7VXA7SLyZQBVvSTrJBG5FjgLWCIim4HPAsX4nCvibm8GfqKqg6lTDwFuiP8SLwDfUdUfjfNzzQpEBL/OHkrj9oKAH6sIFejxwUv8B7WqCiyHWitrV/A8RZCaqs3QWCyzIR6y01laDp9WFppM3jCMidJK8rohfiX8rJWBVfWCFvpcjZPUp9t+B6xp5RqGQ0TQSBsfXBah6FcTTrUdUBgNGqdTyUJgVk7JSzatJK10THnjG4ZhtEorUvlvTUUghmEYhtEqrUrljQ7FLSlmKzKy9sUgR9OhmtoXO8CYsJpfhmEcGK0sGxozmMQGKnHjSBJDffmUKNTYWkoqTht9BSGMlw+TtmIqo1X3wpQwNgSTUOkpgB8rP/JW/9LCkKxeFaspbAnRMIzxY8mrg0nbLVX2llRRlPrtrAgoRVCQRJbuBBk+Sn/RJbGacVBElXJYqz9UXLLr9Z3PYsOeFtVk1IoYIymCaQnMMIzx0DR5icgK3HNY/wNYBgzjZOv/DdykqmMa9BpTi4hU3N8bjuX0z04ecaHLnIfAshKXG2/8tlGWuAzDGC+5yUtEvgksB/4v8A/ANtzzXi/G2Tn9pYh8SlXt4WHDMAxjSmk28/qiqmY9HPwgcH1c02tVe8IyDMMwjHxy1YY5iSt9vKSqj09+SEY9+Q4Xef3HJ+XTSpGT8ZF3naz2xM0ju3/2GFYqxTCMPMYbhjb5AAAgAElEQVQUbIjIacBfAYfH/V0FKNWj2huakdy7E71efWmURF1Y6RWrC/24jEorG5JJxeNqleRk5OpDzuWwMYmUQ6XoC6oa77O5PuUICp6QVFxO2qMkdk0EI+5TpbWI6WSltf8xJw7DMGpoRW34deB/AutxlY2NKSCduNJfkzfpYpXJzKxi4xQnnShlD+WKSlYTQJIo0nL65LqSUnD4nitwGYROeu+Lq9osIgTqpu4eWqmmDFCKXIXkoufGDlMfQnAKx0qhzYyclFZRJl6NqmbeaxhGlVaS115VvantkRg1NFswayxAmV2l2BOpJJCs8TMmVJVj6UuICAU/+5clnbRq2hXKUWPCSbp6GYko7+HlrGKchmHMbpqpDU+K394qIv8EXI8z6QVAVe9tc2yGYRiGkUlTtWHd92tT7xX4/ckPx5hKavfMHJpalmyF9D5V5iwrY9aUOIA09Dd9hmEYLZKbvFT1bAAROSp2eq8gIibWaDNVn4uMtoyEkNgxpfe+oNE2KmnriU8IFUrx+mH63DDet2q2z6SxbVRyju9p7XKggqYyZHIoBMIIfNGKv2Je4rKHmA3DyKIVY97rMtq+P9mBGLWkBRnpkiNJe2N/iV/15U+kUobEi8UWvlTbfYE+vzHpQVKIUhvGB5fcgqj2nDBy7UmcSedEiF+foEJ1llVRxrUhKalSvbZhGEZCsz2vlwDHAQtF5C2pQwuoraxstBGR8QkWErsnpFZ2kdz8hdrlOhGJk0era3YSC0Sy+/tedqLJrRGWe5XauA3DMNI02/M6Bng9sAj4g1T7fuBP2hmUUcvE7t95J1kyMAyj82m25/VD4Ici8kpV/dUUxmQYhmEYTcnd8xKRN4vIwar6KxFZKiLfEpHfiMj3Yrd5o0tofcnwAK+SZw81BVc3DKO7aCbY+FtV3RW/vwzYAJwH3AR8s92BGe0j7ZWoqhUxR37fqvdh2nMwKxdVqy1XLoDGdcHSApDK+ORUbqYq8jAJvWEY9TRLXn7q/dGq+q+qullVrwaWtjcs40AQiZV6GcdSaQhVV7QyUMH3xNXoyugfKURRVRo/GmhFIViR3+NqfCUVlpOkFymUAiWIlNFAKYXV5OeL80HMrgvmNJYVZylLYIZhpGiWvH4mIp8Tkf74/ZsARORsYO+URGccEM2EHmmZerW/4Of8RkTqkk8QNc6cfIGC35iESkmySl83cicV6rwW6xWQ9dcwDMNI0yx5fRhnXfco8DZcDa9EafiuKYjNmASmQls4ETVk3mzLpPGGYbRCM7VhGVcK5a9EZCFQUNWdUxWYMTlMiRSjUk6ltcSTbw+VXf4kr90wjNlLKw4bqOredOKKH2A2ZjBjCR2EZOmutr3gCf0FocevPeAJ9PhuX6t+nFBxbht1F+wpCD0FqZmZeeLsoYbjJchEABJESilyS5lBlBaFuH2zUNNiEMMwZjutlETJ4ifAqskMxJg8sqye6klmMZ46D8O06k9E8FH6C8JoqLHDR1zfS8CT2BqqzvkjiNwx57IB4GypevxspWEpzPZPDNX196W2fxS3Fzyr7WUYs51m9lBfzjuEc90wuoBKEtBG26jqcl3WOZq515VlDyWxx1VWwsmTyschNV67yWcxDGP20GzZ8H3Ag7gKyunXPUBprIFF5Bsisk1EHsw5fpaI7BWRDfHrM6lj54rIoyLyuIh8ajwfyJgYM3ImMwNDMgxjZtBs2fBu4EFVvaP+gIj8VQtjX417uPnbTfr8QlVfXze2D1wOvArYDNwtIjeq6sYWrmkYhmHMAprNvM7HuWo0oKpHjjWwqt4G7BqrXwanAI+r6u9UtQR8F3jjBMYxxsG0CiHyrm3aDMMwcshNXqq6S1WH0m0ictIkX/+VInK/iNwkIsfFbcuBZ1J9NsdtmYjIRSJyj4jcs3379kkOr/tJ1H6aep+0NyPLTkpVGQ0iIm1UBTa1n0repNvrvibvI6riD1MeGrOR9D1v/56JzA+6g5ak8in+YxKvfS9wuKquAb4C/CBuz3M1ykRVr1TVtaq6dulSc62C2iKWNe2kbaOqSSuKZfWJeYaqEiqMhvnJoeB7FH1xSkVVIlXKEZQjGCxFNTZQLiZpsKxKeyomyTP5pxZcFeaKx2HqFai7TvUcw5g9pO958xcdPN3hTBvjTV6TtoWuqvtUdSB+vw4oisgS3ExrZarrCmDLZF13tlBfiTmpSpwcg2rSShNGymjYaANVHbeqJhQRCr5HKaomk4RSqNQPISJ4nlSrQ2coCetjhbQfY21bEOV/fsMwupvxJq+/nqwLi8ihEt8FReSUOJadOKHIi0TkSBHpAd4B3DhZ151tiDQmiemmWUwzLFTDMGYoLT2kLCLLgcOBXSJyBlQEGc3OuRY4C1giIpuBzwLF+NwrcIKQD4lIAAwD71C3BhSIyIeBH+Oc7b+hqg9N4LMZ04zbl2rd7ilxqR9Psm32nJhhGN3LmMlLRP4BeDuwEefsA+6e0TR5qeoFYxy/DCelzzq2Dlg3VmzGxElKmCSuFQmeQI/EdkxjbCcl1k39BSFUKNc5yI+GihcpvQUPL37oOYhcbS8Bir5WSqgkRDjXj1aeO/NSy59Zy5CGYXQvrcy83gQco6qj7Q7GmDoq9lC4YpRJAqvYQKH4Ut3LSuyeEpLElZxTQPELUtnrSu+rDZcjfAFVqVERlkLwI6Xo187CongKlmUdBS5pVde7E/mJ+48lMMOYHbSSvH6HW+6z5NWFVKyeMtpVAdHYobCWBj2HuF6aYxsVavby3nj3vgSXuGakI4hhGFNGM2/Dr+D+oB0CNojIT0klMFW9pP3hGdNP+5NEXiKy9GQYRh7NZl73xF/X06j2s4drDMMwjGmjWTHKbwGIyKWq+m/pYyJyabsDM4zxKwmzzxivgtEwjJlPK895vSej7b2THIcxTYxVtDLvFyTTBkUVv/nVGlrCiEw7qYqwo+6UrFDrLa6q7dXzx/qchmF0Fs32vC4A/gg4UkTSy4bzcQ8TGx1MzY08EVvU3d1FoOhJxfopwQcKvpO+l+PkAy4RIYKnStr8Iq0MzMof5dAVufTrikxWZCRadQvxUwrEhoQX+yR6lavUXk9Sn9tmYobR2TTb87oD2AosAb6Yat8PPNDOoIypoVEwKJkPEHsiFCUtja/27/FhoFSf9ASf7IeR8xJIGHtAFTLk8SIuYXp57r511MeZkCwqWuIyjM6n2Z7XU8BTIvImnKu7AltU9fmpCs6YenKVfzLe/afmY40XSziGYaRptmx4InAFsBB4Nm5eISJ7gD9T1XunID7DMAzDaKDZsuHVwAdV9a50o4i8AvgmsKaNcRlTgHuouLGNuva0mwY17c7OqbcghBE1TvTJ8lziV5g+R+v6JIQRRLHjRrJEqKqUQigBvQUopNrTMWUtB2YtW1b8EzP6G4bROTRLXnPrExeAqt4pInPbGJMxBUhdlkqLzCWV1aImiSus9Bd8z/kUllOGiCKCENcMi6C+gklWInG2Uc4T0ZNawcVIoPii9PgZcvj4P1kJSTO8Es1OyjA6m2bJ6yYR+W/g21QrG68E3g38qN2BGVODSPZMRMTNgnLKelUSV7V/UuOr4QrxDCynPljmOfEMTRqf20rk8JNlD2XPgBlGZ9JMsHGJiJwHvBEn2BBcocjLY9d3o0vI9RfMWlfsMixxGUZn0tSYV1VvAm6aolgMwzAMoyVyHTZE5ITU+6KIfFpEbhSRvxOROVMTnmEYhmE00swe6urU+y8AR+MeVu7HSeiNLiaxU8q0gco9p7G0SkLe8ly9GrGxvfZgpNnnaJOx8kj6m22UYXQezZYN07ebc4CXq2pZRG4D7m9vWMZ0UW8b5UlVlp4uJOlJVfaeSNIrRSi1NuUIxApBJ3uvF4Gkc1TFvaMmHo2Vi+B7EMUVxryUniNJXkl7Mk5S0FI1O+km55htlGF0Fs2S10IReTNudtarqmUAVVURsb9Vu5gs2yip8yt07a5zqNntiZKwmhCE3gKMlBu1hxXrJhoTiIjzNEzbQylO8Sh1asGkvVi5dkoFOUYCs8RlGJ1Ds+T1c+AN8fs7ReQQVX1eRA4FdrQ/NGMmkac8bKZUzEsIiTw/9zr1bU2uk0c6cbVyXcMwOotmUvn35bQ/h1tGNAzDMIxpoZna8PRmJ4rIAhE5fvJDMqabrEmOAEXP7SElJGIHL8O0N9mfqp8x5Tt2KKOhMhxopcRK0j4SKAOliDCqbS8HESPl2vaEUgRhVK0TpqpE8ffJq+b6xGIQm5kZRkfQbNnwrSLyjzg3jfXAdqAPpzo8Gzgc+HjbIzSmlFzbKJF4KVBRcTW4Kh6F8Zqi4BKAL9VlO1HXP4qcWKN+f0xVCVP7ZqowHIAvii8QpPoPlCKKnhN/BKkNuNFA8UTpKQheKlsG6vbE/JwtWrONMozOpdmy4f8UkYOA84G3AYcBw8DDwL+r6u1TE6IxHaRto5Lv3Vd3oFG84ToUpM4MN1YJlkJtSFwAQYbnIbhklpVygsgl0Iak00TW38wCKs9qymyjDGNm06wkyiuBO1X1KuCqqQvJmCnkizGa+UZJtlfhZMU0SeNUxpvEmmOGYUwdzR5Sfg+wXkS+KyLvjVWGhmEYhjHtNFs2/FMAEXkJcB5wtYgsBG7F7YP9UlXrzcUNwzAMo+00m3kBoKqPqOq/quq5wO8Dt+P2wBpqfaURkW+IyDYReTDn+IUi8kD8ukNE1qSObRKR34jIBhG5Z3wfyZgKvGbLahmijELOb1rTcTLI2h9LLjm21VTGsYwDZhtlGDOfpq7yCbFwYxlOsPGjFkuiXA1chqsHlsWTwJmqujsuvXIlcGrq+Nmqag9Dz1B6fSGMlFIqmwjxX0OVCspp2yih6CtBWJvbCp5QwI2TKN49qCS7tHBD4vaGh4+Bou/8OerVgjXiyRwLqGrF5eoZZhtlGDObZoKNhcDFwAVAD1Wp/CEicifwVVW9Ne98Vb1NRI5ocvyO1Ld3AivGFbkx7fie0CdOAp/lghFqrY+hV5fAamyj/Pi5rLhfQiH2VkRcUqtPXAXPxZFuV6q2UeneKSvEHBpl82YbZRgzk2Yzr+tws6b/oap70gdE5GTgXSJylKp+fRLi+AC1dcMU+EnsofjvqnrlJFzDaAMigpfxHFV61lLfP88a0xPJVCVKbBDc2N6YuNLXt5xjGN1LM8HGq5ocW497cPmAEZGzcckr7ehxmqpuEZEXADeLyCOqelvO+RcBFwGsWrVqMkIyDMOYsaTveUsOXT7N0UwfYwo2AERkuYj8noickbwm4+Jxwcv/AN6oqjuTdlXdEn/dBtwAnJI3hqpeqaprVXXt0qVLJyMsY5xk2UBpxrJdTXvGvlMQuVdaRKGqjAYRQ+WowTYqjJSRIMM2KowYLEcEdbZRYaQMB1HGNdzyZhSZbZQx80nf8+YvOni6w5k2xhRsiMg/AG8HNuKqTYD7fzpzJtQqIrIKuB54l6r+NtU+F/BUdX/8/tXA5w7kWkZ78UQqtlFB6BSB6T0tAcIobScVLyviEkraHgpiW6coQoHR1MMYAyWlx1d6/OryoiqMBBEFz4k/SkH1OkNlpeApvT6UU4KQkUDxBPoKSXTxWPF4XpaDR/wf2/8yjJlBK2rDNwHHqOroeAYWkWuBs4AlIrIZ+CyuzBKqegXwGWAx8NX4RhGo6lrgEOCGuK0AfEdVfzSeaxtTT9o2qpqH0m4b6alLtcZWpDm2UUqNf2GlPYKC15hcgtiIt36uF0TZVk9RPNty+3VZ9lBmG2UYM5lWktfvcElnXMlLVS8Y4/gfA3+c0f47YE3jGcZMp7lt1CRdY9LHyrOHMtsoozP4zl1P80enzr79/mZS+a/g7kRDwAYR+SmpBKaql7Q/PMMwDMNopNnMK3G2WA/cWHfMtq+NWcjYT4od8BUmaVnSljeNbqeZVP5bACJyqar+W/qYiFza7sCMzsSTxppdUC2x0tA+zvGzCllC4pIR1xWreWBZU2KL2quFCn6uOKNunErwtSVf6tWJecuNrZAMdaCJZ7LGMYyZTCtS+fdktL13kuMwuoQeX+jJ+K3yPcFPtSfVjD1PKHp1Thhxoil42cltJIAgrK2KXAphONBYoFFtDyOnWCxHtYlGwEnzNdWfWAEZqx/T41Tao9r4FScKCaKqJVaWX2IeiYeiasqfMdU+HtLn1I9jUn+j22i253UB8EfAkSKSXjacD+zMPsswqrZRI3U1BzwRxFPKoTbaRnlKOaqdtYkIhdg2KtJaq6Zy5BSJnlQTimt3CazoE9d2doQKYQj9BXdOMkOKFEoKxbqEq8Tjk9EexXGkfBfBxeHJ+M2Gs/LKRBYom41jMzCj22i253UHsBVYAnwx1b4feKCdQRmdjyTPfmW0Z91mK7ZROUuOWUsEqtlLlMmDxVk37HTiqj8nrxJzZrvNZIwZxGxUHDbb83oKeEpE3gQsx/1/vEVVn5+q4AzDMAwji2bLhicCVwALgWfj5hUisgf4M1W9dwriMzqYgudmQPWzI98TJN6PqmkXEM8tCaZJlr3SS43JflOk8Xk14gooh1DwtcahXhWGy0pPwblxpMcqBeD7tWNFqgyXIwoi9BWkRqRRjhpLtKhWS8T0FWrbE4spv65/so9WX+oljK2yenzBT8UaqVt2LXi17c5eK55ZUhdTqIi4/cj6dmhsd/ZZrszMWJ8hiSmKGtsNo500Wza8GvigqtYUnRSRVwDfxB4kNsbAF/cqUGvz5HvgqRNwlEN3o3R7Re7GV/RhNHA3dgG8uEiYF9/so9hSKsllgYKnWlOPC1wC80RjoYhU+gYV2yipCCUAwtg2qugr5VgAAlBCGQ2VuUUPkdrkGoTQ48X90ntvJaW/4D5/jfVVRMWFP4iqxTVLkbOl8qV27284cLH2eLEwJG4PQ8WLlKInFTEJ8VcBPI0INRWrOoFKr+/WU0eCalBBpPQW3HmlsLrUGwRK0VN8kczPIMS+j6l2QS2JGVNCs+Q1tz5xAajqnbHnoGE0pXIDU8WnaoyZ2EYJ7uaudaaBAhQ9RaN0S1waRSNKGftNEeDl2EBltQcR+FI7M0v6D4xqQ8XmUF0icUUvaynVd44ZDV3SaZDoR+mfRfoa2jDrTGINo+zPVo6ypf6jYeP2oUIsotHG9jhx11OOQKXxGrmPLGQ3G8ak0yx53SQi/42r6fVM3LYSeDdgXoNGy4gIUbPbWqaAIlvYkdeeM0zzuHLa8yKdrPGngslKIjZ/MmYqzQQbl4jIecAbcYINATYDl6vquimKz+gS2u962H7sRm7MZL5z19M133e7+rCpMa+q3kRthWPDmLFM5Nmo8Y5vTJw8p37DmAi5DhtxocjkfVFEPi0iN4rI34nInKkJz+gW8u5Zee35D/pmpxBNKy/q21Nf0+2uLEpje1Z/UKJIM/tHKSeONGHOWGFO/0ir49W2O5OrrPZIqSnGmb5es1jr0ZyY8n9+1Ihdxu6f93M1jIkxltrwpPj9F3C1t76Iq+91BW7vyzBaouiBr43iBqf40waBQcETPHGqwwggsWiK0kuQbq6lsXx8JFJ6C0LBk0qf0UDZNxoxp+jRX6Ry1sBoxFPDIQf1+bxgnl/pP1yO2DEU0lMQFvX5lZlcECm7R0OKvrB4TgFPqMSzYzAAYMncAr5XVeHtHAqIFA6dV6A3/j9NFTbvK7NvNGLFgiLzer1K/+f2B+wYCjhsfoGD+v1K+7bBgGf3BSybX+Cw+e7aSfvGbaMsW1DkJUt7XUwKQ6WIp/eW6SsIyxYUK38IBKGyazjEE+HgOX6lPVLYMxKiCgf3+5XPoMBgKSKMYGGvR9FP/nWkUrfNCS2r/3JRImzxhIJX2x4lqtJ0xTebiRkTpFnySv9WnQO8XFXLInIbcH97wzK6DRHBF+gT50MoJG4XgAj9sZ1U2gbKF6G/6J7NGo2qz4UJ1erMQZy4EkYCxUMp+MJoLMMHGCpHjAbgecL+0ajyjNPO4ZC9oyGHzPUZCrQiIR8uKyPlgIV9HmFEpX8YKM/uKzO/xyNS2J/Kxs/uKzOvx6Pgwf7RqkTl6b1l5hSFou/x/EBQkZ1v2lNmblGY3+uxbSCoKA2f3RewczBgYX+B5waCSkzP7AvYNhiyeI7Hlv0Be0fcCU/tKbN1f8Dxh/QyVIrYN+raS6EysGOUw+YViHCVpR3K1v0B8+PEOViu/vyeHwyZVxR6fKk8KgCwayRiTlGY2+PV/JHh/rBofA4vsenq8aWmPUli9c+1GcZ4aZa8ForIm3FLi72qWgZQVRURm/sbE8IZ7jb++iTt9dWTRQTPU6Jy9njlDH+oUN0zSlntu4caRepB5JJYluR8sBQ1yOkB9o5m6+MHSlHmkue+0YhS2Ki5HEglmzTDgbJ7T+OHHg2Vh7eXGtpLobJ5b7nm4WtwiWL3SEjRb9whGMj5bMNBdnXrUqj0Zzx2oGTbZbmZqe1zGe2hWfL6OfCG+P2dInKIqj4vIocCO9ofmmEYhjFR6tWHrdIpKsVcwYaqvq/u9Xzc/pyqnjN1IRrdRrLsl0a1upRY2+7+pM96ODhx5qgnqlgc1QklosTRvrF9+2DAcN0TwmGkPLO3zK7h2tlapMqz+0o8P1CuuYaq8vSeEo/vHG24xjN7y/zm+eGGmeLTe0vc/MR+Bus2A7cNBtz8xAC76669byTktk2DbIv32RKGSyHXb3iOjc8N1LQHkfLrzUM8umO0JtZIlQefH+HB50dqYlVVnh8IeGLXaIMQZCSIeG4gaGgfDZRdQwFBg3DEuZxkCUdGAs0QmiSiFTLbs44Zs5emUvl6RORKVb2oXcEYs4NkFaliLxSr1hJfPpXYOin2P/RF6CtAb0EYLkeUQ61YK/lerW1U2nKpYhuFMhzAULyUGEWuCKUnymA5Yk+8d7RnJGJ+r8eSOT77S8pTu0turP0BC3o9jj64h5Gy8sjOUVdPDLfP9eIlvYQR3LtlmIE4CT2+q8TJy/rpKwi/eGqI5wcDVOHRHSVevqKfg/t8/vu3+9m4bYRI4c5nhnn10fNYc2gfNz8xwF2bhwkV7to8xGkr5/DKlXO4+9lhbn1ygEjh3q3DHLe0l9MPn8NDW/Zx4wPPE0TKjx7ewZrl83n3KcvZW1J+9uSg8zZkmEPmFXjti+dTjuCnTwwwWI4QYMPWYV519Hzm9Xg8vH2kkkif3F3mhEP7WNzvs2cktU84FLJsfoEFvR67hyMGSm45dN9owKI+jwW9Hu6n7ghD52ZSiK2ykhXdcuSsr/oKgqT6J8uQkvqe9PuMpUtj9iHjka6KyL2qetLYPaeHtWvX6j333DPdYRgtkhSLzBBuE4SN9cAAymHE7pHGPSJVrREepNv3lzRT1p3MFtLtAgwHUZw8a9ujeJD6q5dDZaAUNVgmRZGyN04EtaIF5bc7RgFq9viKnrNv8ur8E4s+lAPnGVhK/UwKHuzevZcwKFUSS9K+aulClh88v7Y+Gu4PgP6i1xDrgl5h5cIe6plTFF68uLdh30qAuT1ew8PnAhw2v1BjGjwWvb7ESsbWz0lEPV1Ky5/sqGNP0L+5+v9O6sVnwLJhS59/XDMvYNsEAjGMTPJqeyVS7KxjiRqx4fmiJtfJ8+GrT1zJOGHUeE7ybZZMoxxp5jXKcWP9seFyVfafphRWqzjXjJO01yXzIIJSudyw/BZEML+/t2GcZHabFWvRy95BSIx/6+8mIvGSbkYGGW8xTr/OUHksujxxGS2Su+eVhaqe265ADGM2Yfdewzgwxpx5iciLgU8Ah6f7q+rvtzEuwzBmPVlzvjHOsP2wWUMry4bfxzlqXEV2JQfDmDAi2QqyvKUnT6TpEuF48KRxia4ZiZ1Uw7NRmu3bp2jmc04eIUFSeCt9c9YQVYmbU4siUeDaoxD8YqVZNEJEkChAvfT/ysrgSIn+guAViqQpB5ETq/h+TXspjAgjbdirKoXJfmHt58jbKlcSUUX959ZUYql7Fg2Q+v6aLOlml3zJEm2YEnFymKjEvlUma0+tlWXDQFW/pqq/VtX1yWtSrm7MejxJ9jxq6fGFuUVp+Lu7ryC8YK7vHBpqxhHm9UjNWIkgpMerTYauinDjA8ORakUOvm80rHoERspQOeKuzcNs3DZakeFHket/1+Yh1m8ZphRGFe/AchBx75M7uOPRLQyNlomiCFQJgjKP3X83j/3sOkb27kDDMqgSBWV2PvJrfnv9vzK45XGiwD2IHJWG2XXfzWz4X69mx6//D1FpxN3Yy6MMbn6Erd//a/b/5qdoUAKNICwT7tvOr//3F3jop9cRlEYhCtEwYGRogF/efCN33XYLpdFRNApdTGHE3U/v50eP7GKoFFb20CJVntxd4uYnBtg/GlWk8M7OS9kxFLqfY8q3MIyUTbtLDJaiikRe40rLSV2ytEhMcHuPodb6K9YoDCueiylJPyl/xZRitb7d6F5y1YYicnD89hKcUOMGYDQ5rqq72h7dODG1YeeSJBqoLSev6hJHENVaCqkqe0dCBkqugnK6PVH/laPaG1ikrn040Bp1nqoyUArZO1LrduGLS3o7BkM27SlXbp1FD448qMhgOeI3z41UZm+ewBELPLwoZP1TOyjFUkIBVi3wWCCj3HfnLxgarD6LtXDZkSw8ZCXP3v1jRvZU9VBzD3shi5YdxeabrmDf49Xf6bmHr2bV2/6CXRt+yt7f/roa64IXsOj33k7puccZfvJekht977yFrPmDDzA4NMiTGzegkYupUCxy8u+/nuL8xTy9a7jmM5x25AKWLehl22BYaRdg9SF9vHhJD+U6H8o+X5jfKwR1ytG+grBsfjFT6Vn03R8a6X+75Gebt+qXNWvLktOnj3XoEuK0qg3bTQszr5Y+f7Pk9ST5i86qqke1coGpxJJXdxJEtckmoRQqO4fChhuXe+g4e4X7mX3ZPlOP7RjJrGL8xM5SjX9hwmApSHkFVhkaGmJkcH+jYnDPc0mbQokAACAASURBVJQ23UcY1F5fgxLhvucrSaXSHgbsu+t6sm7LfSuOA89vaC8uWIJK42JK//JjoG9BQ/v8I09gwRGrG9oPmd/DMS+Y23DnX9zvc+rKOQ0WVIKT2mfZQB2+sJjZ3leUTGuqguQvGY/XZsqS18xkspJXM4eNI+MEdWz8vvICXtrK4CLyDRHZJiIP5hwXEfmyiDwuIg+IyEmpY+8Rkcfi13tauZ5hGIYxO2hlz+uOFtuyuBpoJq8/D3hR/LoI+BpUliw/C5wKnAJ8VkQOavGaRpeRdltII8DcYuMRgYpjej2L+ryGPTZVpa/gUe9dq6r0FYXeQsYMwXPO6w3XFsEvFhvaNShDsa+xXaMaEUalPQzw5y9unGGJlzm7UlWCwd1E5dGGY2FplKg80theLjG6b2dj7S2Evak9vzQ7BoNcu6es/gOlqNEGKn4IPWsct/9V314Vy9STV4fM6H5y1YaxAe9yoF9EXkb1/rEAaKkYpareJiJHNOnyRuDb6n7z7hSRRSJyGHAWcHOyryYiN+OS4LWtXNfoDmr2weLfvjDePxFxbhE9BZ8FfbBrOGQkcBZEhaIwpygc1OexczhksKT44pwq+go+S+b47BgK2T0cEkSuhteCPp/56jEYu7y7pUpY1F9gQZ8yWIrYNuDqcxV9oegXmNujlCNld+LUEYUUCgUK/jz6+kIGBgYJy6NEe7YQDe6mMHcRfv98yvt2EpVHkLAEQQm/Zw5a7CMcHUKDEtHgHoL92+lZvAI96DDKu7cQ7t+JN3cRPYtXIp5fWc/XKEKDEloaJAR033aK8w5C5i1BCr0U5i4gGh1ES0MUeucgcw9GCj30zD+Y8tB+9j31ED1zFjB3xTEU++awcE4Pkfg8NxCyazji0HkF5hQ95vd4eOLKu2zZH/DCg3ucDVT87zFUVobLytwel9Q9EURgz2jE3tGIhb0e83qqG1rlSGN7KOjxvZqHtssRFETpiV03KgvAcQLLEvgkvy8ijSIfY2aRpWaciAKxmVT+NcB7gRW4IpTJ78Q+4C/GfaVslgPPpL7fHLfltTcgIhfhZm2sWjXttibGJBGlEhdU3Tg8UhuxyY1K4OB+57OX3qT1BRb3e0DUYPW0ZI7PnuGQ4XJVdSgizOv1GSorA6n9LE+E+b0+kSq7h6tBiQi9vqvHtX3/aPWmKYLnF+greuzatNEtb6iiCHgFCvMOYvS5xyv7MQogHl7PHEaeewwJg6pU3PPpWbyC6KBleF6tZ6B4HsHwfghGa5Qp4dBevJ559Cw8BK1cRIlKw0hxmL7FK8DznMQ/iigN7sXf+hiHrD4V33OJJFJXG+35gYCTl/VXJPSRur3Gx3eOcvwhfTX7XwoMlpSefg+vrn3vaETBh75C7awxiNWH9RL9QCEKoejXbrsr7g+YxAeznsQPpEP3uloifc9bcmjmbXFWkJu8VPVbwLdE5K2q+l9tun6mGKRJe2Oj6pXAleAEG5MXmjGdZK8C5d+UNP6VqT/siWTaIXkiFUPZeobri4rFlDJqhClUVIUNwpHhAXwRwjpfJw3LLq6orj0K0KDslhJrriGV2VaaKIqQsNywZBaFIX0LljSoFaIoom/uQW7pMXWKqtI/b2HmM3Rzil7mzzypVp1FRukwFDKXWaHZM32QdSuQzNZqWzcnLqi95x117Amz9p435p5XOnGJyP+b5OtvBlamvl8BbGnSbhjTxkSKKuae0e4bbK5ib/znGMZMpNme1wP1TcCLk3ZVPWESrn8j8GER+S5OnLFXVbeKyI+Bv0uJNF4N/PkkXM8wDMPoAprteW3C7W/9DTCMS16/AP6g1cFF5Fqc+GKJiGzGKQiLAKp6BbAOeC3wODAEvC8+tktEPg/cHQ/1uZn4ULTRPsY7CZjIpMH3hChsdJb3RfBFG57VErJd2QueZLb7hWKmQs4vFCllrGX6vvvfUURqXSjEQzXC8/zGpUbc/loU1hanDMslCv1ew/NjYRjgS+OybOK20bDUmKPii3I8BJutYUWavUSYt08AebZb2R6G+Q+luq/dvpw422i25/UGEXkzbm31n1X1RhEpq+pTrQ6uqheMcVyBi3OOfQP4RqvXMroLEbemXX+P9+Jj9dtPBU9c0cTRsEboUfSEwxcWeX4wYDTQyg3O9+D3VvbzyI5RtsdOEk6RKLzmRfN5dMcoj+4YrREHrDm0l20DAY/vdg8aJ/fCV6ycy8BoL3c8NUAUe/gBHLVqGbKkj/s3bCAKQ8IwRDyPQ1e9mIUnnMQjv7yJ8sgQQbmM5xc4aPlRvPjMN/HEuqsY2rmVoDSCV+yld8lKFqx9IwMbbmJ4q7OO8go9+HMWsuj0dzLy218ytOk+NCjjF3uhp585x52NF5YZ3vIoEic+9XzmrToOf+5Chp9/GsG5kyAehxy0gIP6ffaOJpZO7ud8cL9Pny+VB7iTn1/Rhz3DIQv7fPfzicUzfQUnYgm0+m8nOHcUV1i0+u+bHOuJy6606jNZMYqqS0rp3NSQnDP6GxNjBtT7Apo4bFQ6iMwFPg8cDZykqiumIrCJYA4b3Ucz26jEjsgTKm4NqspgKWSw7J7dKvrV9oFSxLbBgDlxQcZkrB1DAQ8+P8rSeQVWLSxWxtoxFPCTxwfo8eCQeYVK+1A54jfPj9DjCS99QS+9sYJuuBzx08f3snck5MjF/fS5CosEQcCDDz3Ezl27eeGxq5m3YCEAURSy6YG72PrEI6xaezYLDz28EuvW+/4fT9x2A4tOfj1zjjq5EuvQUw+w647/pP/Ik+l/4VokfuartO1J9t51HX0rj2fey16LxM+OhUN7KT25np6FS1m0+iy8+FmzsDxKtP1J+nsKvHT1CfT19cUxuerSIsLxL+hz8vbKz9ulrsVzvMpnBlewclGfz8H9BebU9IdQlblFiYUf1axRiP9Q6PWrzhyRuscTRGqtwNLUizWSmVySQKu/N/HXhhE6wnljRjtsTEHyaunzt1xJWUTWAK+Ml/tmJJa8ZhdZnnmuXRnOUAYC7M0qz4x7TinrjN88N1zjdzgW2wYDtuwPGmaMo0HEYLmx2nIYaea1I1U2bd2ZeY3hnVsy5ZheoUiU8f/9/EWL8XoaH5Bevqif5Qf1N7Qv6vNZsaDxwemiBwv7/IYbf48vrD6kL7N68vyebNuohb1epj1U3k86T2Ho/nBpTHR5vxuVsSx5TZiZkryaqg1F5AwROSb+dj4wT0Red6CRGYZhGMaBkJu8RORL/P/tnXuwJHV1xz/f7pm5j32/WJZlEQTiCy0kK5FYRssnWinQ0qQgVQmkQlmaQo1VSUmSKjXEVKGmYiqV+JaIFgUSYsyiqMEgJVZEWXGVl8gCERYILgssC+zuvXfm5I9f90xPT/c8du/ce2fu+VTNzszpX3ef38zdPvP7/U5/D1wGfCVJnvg4MAV8QNInFsg/xzkiylQYJuLi+5MmKypMJlg/FTNdIEG1OlWMyLF2Mmbr6s6l5NUTESet7RzNTFXEqRtqHT5VI3jZcSs7RHDjCF55yjGsmGg/h4CXnbCetdO1jnOcuGGaDdOdPm1eWWHdZKfA76paxKqJzr7VYhX2uRKFRxENay+BklIvsHebA1raAyVnMeiWbfhG4DRCwHoY2Gpmz0m6DPgpobqy4ywq6UUtf+GrxSEJYKZuIcuNcIGtTQQFiQOHGxyuB6mhFYn0kQH7DzV4djbYV09EbJqepGGwe99hfvH4DJVIvHDjBOumwkX/sWdm2f1EqL31go0TbFlVpWHw4FMzXH/vMxycbfDyLZO8dPMkZrD3uTmuu+cATx6sc9oxE5y1bQUAz8zU2XHPgab00mtOnCYWHJptcM1PH+Pux57lxcdO857f3srKWkS9YXzhpl/wvbse5YQNK7no9S9h46opEFx324P81+0Ps2ZFjfPPOoVtG1YiiZ/sOcCNu/dTi8U7TtvICzdPIYlHD8xy26OHaJjxiuOm+I2NEwh4dqbBfU/OMls3tq2pcsLaKlL4TB/eP8vhunHsygqnbJgIGYwFn3d6v3clsubaZDUWcw1jDlFRkIiiS5HRStT6ld3IJIKkU4aD/G14EBwfupVEucPMTpM0CTwKHGdmByXFwO1m1pey/ELia17Lk27rG42GhXUUy1cCDgkIWWmolr01Kkjt9UZYRzs8Z21rLI3k5HGstsSRhhkzc8YTB+dC6n3UOv5s3XjqUINKrObIKrU/cahONWOHoOAxWYF1U5W2RInDs3X2PTtLFMdU41ZCxOxcnQOH5mgQUckkRNSTIprTtShJ72+dG4OpmqhIbdJOjYZRTUSLo9znt2YiDnW5cu0bSWpffh1qqhICV94eJwka+YWoSCGxI//9ZOl143j+8rbE17pS5m3Na6lkBg5IX/3vNvL6pqSbgUngC8A1km4BXgN8/+j9c5z5IZE9LM4sE8jouGpJIf89/78k1VDsuMBGwZ5PSogkoohCOxi1nFaSkvaT1U57JYapasF0XSVi88q4w6eJaszUROeIpVqJqVU7U8/jSNTiqEOmSRK1Ch2+AkmA7QwSlUjUKp01udT8TDuvP0WBC4LMYlFUieg8b3oPXL9qJxlpx1EJXE6fdLvP64OSzgov7RZJJwNvJwSyaxfKQccZZZK42rd93o5fsuFIrt9HIos1TI5IpmtpdcGZB7rJQ8nMfpi+N7P7gL8vaLNshSEdx3GcxaFbqvz3JL1XUtukqaSapNdJugK4YLjuOc7CU/YjfdAf79L8jbpK25c5ZQP629WhknXxQY7fPErBsVK9p6J9CgtQljZ3lhHdgtfZQB24StIjku6S9ABwL3A+8Ekz+9IC+Og4PWmtteTtKk2br5bsM1lVYer3mgkxXW3fR4REhIJMdFbVxMYVUUf7FTWxdXWFOHP+SKH680uOmWAibqXtxwrH3zRdoZZJ81ey7eR11WahyNQeCU7eUGXDdNSWjRcJjlkRsX6q06dVExGrJzrtkxWxqtZZlbpIyxGStbuCz65Vf6vzE7ewY4c9lZjKVkvOJuekQcwD2fKk25rXIeBTwKckVYGNwEEze2qhnHOcQShK3BCgSMisLc06tVcT+1yibVhLkgpqMczVjedmG0QKVZsjRUxWYaZmPHmw3tT+SzMDp6rG04eDisbKiahpXzNpPHZglkNzxobpSjMpY+1kzP89M8fTh+tsW1Nl/VRIyti8ssL/PjnDnqfnOGFNheNXV5HEhmlj/6E6jz9XZ/VExPrpIFm1birmqUMNHnhyhlUTEVtWVahEYvPKKvsP1fnl4zNMVsTz19ea2Yobpxs89PQsAo5fU20WiVw9aex7NlSG3rSi0kwsWVEz9h8KtxesqrXLQ2U/6zQTM1KQ9WpYCIBTVSXJFklAStr2koFqJMEpzSVpBq5MO2d50i3bsImZzRLS5R1nSdNzBJYbLqT2qjovopVYrFDxzbqbV3b+16lEQeMvL3FUicSxq6rka1zGkTh+dZVqXG07dyRx0roaz1vbfsOxJNZOVVg9Wemwr5uKma5OdEzKrZmMOeO4qQ77ZDXi1A0ThX3YvKracf9UpNC3MvHcWO2DpzR7ckW1PcNQCm2LJJ2gWAYqFe0tkpMqU5JfboxoSvxR0bMYpeM4juMsNTx4Oc48UzYSKFODGDRBpOw4ZWt7cclo9EgY1NeyXAwfLTlHS1/Tho4zLqQX/uzsYWoruvm1tS2zzpIJBm12Whp/dWvdJBwJaolUxFwDDiV1xSpRWA9Ksw/TEi/hOKG9AbP1Vh2yWpLMYcDhuVAwM7VPVWKMULJlpm4ImK5GTamsZ2caTbX9WK1g1+Zrts8U961hMJspR1PLrEe19TkOa1xpB9PPrRK1Pr9G5hwRxZJOLRkow3Jhz4Pg8sWDl7OsSINThLWtl5Td+Nqyt182e9ljrKn3p4y9Ehkra2pWFW4ex4LGX6vqb8ueKmI0MwqbhR9pBq+sfUU1Yiq2psxT016LqMXGwaReV0pFECWZfMHcygsMAb29D2HNyjr6FtarjEhKaq+1jmVATCsANr8HI/c9ND/WkACSa59fvPObj5cvHrycZYmkDr3DXu2LRmZZzb32xIRW8CmyRxTYDRItq472KpCskkRUkLKQSlB1jiJFvdEo7LOKtLLSY5XYSxNjSjIIizILyxNs0kdne5d6csDXvJxlzKAyQ93a9x659Xus+bEvNUmn+WSMu3ZELMdMQ/Dg5TiO44wgHrwcx1myuHSqU4YHL8dZInSbDktTzjvqU/V57FReqRoXr2E1a2rlfRrgHL18mmkMJufkccvphidsOM4SIlJ5cU3LvUiTGspqmTWbm2VS8UMdrkbDmun0tUqroGS9YRyabaXypxmRaZFOSDMMW/b0toNYNJM18n1IjzNr4Rdz9t6z9Dj5z2Gc1+2co8eDl+MsMfoJSO1STC0dwCLmGnRIVkWRmIrUMdqLIzFVUMgyFdzNnyKV1+qUhyq/DaFBuPAUZWGmgdFxeuHTho7jOM7I4cHLcZYp6TpYp30RnEnPvcjnd0YHnzZ0nCVKkVRS01Zwo25Re2glYmTrY6WYgRIVjfR9fooxJc7IQ2VLy9TipgJU23RjNWrZ5zL2StPvYk14S/7x6UOnG0MdeUk6W9I9knZLuqRg+ycl7Uoev5T0VGZbPbNtxzD9dJylhjJrSM21o4JtRfvkN0mhLElFEKtgpAXUG2FtrKjkSaotmB4nrcNVjWAibklEiRCYKgp6h1l7NWNvJWOURyejVcvLcYoY2shLUgz8C/BGYA9wq6QdZnZX2sbMPpBp/17g5ZlDHDSz04fln+OMAm1af32ORFIJpU67aJQV5Op5zM7kirhI4opOKatsEB4kg9CTN5xuDHPkdSaw28zuN7MZ4Grg3C7tzweuGqI/jjOyzNtFfF6DwaBSVo4zfwwzeG0FHsq835PYOpD0POAk4MaMeVLSTkm3SHpb2UkkvStpt3Pv3r3z4bfjOM6SJXvNqz+3f7HdWTSGGbyKfn6VzVmcB1xrZvWM7QQz2w78AfCPkk4u2tHMPmdm281s+6ZNm47OY8cZcxZmTDR/C1WDrHkNot4xyvg1LzDM4LUH2JZ5fzzwSEnb88hNGZrZI8nz/cBNtK+HOY7ThbIgFUclpUy67NMvaep93drT8NOg0sjZex5voHMXv3bGl2EGr1uBUyWdJKlGCFAdWYOSXgCsA36Ysa2TNJG83gi8Crgrv6/jOMUUZh0SKjRPVtQscAktXcNaLKpRe/simSYRCku20utDQGoQUuLrFnQMs2n5aTxpNJVDQp3m5jkKfI1KsiqzpIExrfrcfCyTUdhyZmjZhmY2J+li4DuEv/XLzexOSZcCO80sDWTnA1db+8+xFwGfldQgBNjLslmKjuP0Jg1grerM6XNIm7dGUg05EyEiiYpCICrKDIygUNh3riBQzFkqA9Vut+T2LqGMT8W+9kOZDqSnjYw3Q71J2cyuB67P2T6Ue/+Rgv3+B3jpMH1znOVCWSDoVihz2HmEZWnwnhrv9IvLQzmO0xeDrFe19imxd9nmOP3gwctxlilxFNa6itabYtrtadCqE8qm5INYRcXTiXVgLte+uVaGzUsAK0tAccYb1zZ0nGVKUykjsna9wuTKHyUJF/Xcfg1C2xgjSiSjQnsjUuf6V6ptGGNUmhFOzW1mR66mkVUgKbQ7Y4uPvBxnmVO+9kXXIUyRhmI3KpGa+oj54xxtsMnXEnPGHx95OY4zFnjQWl74yMtxHMcZOTx4OY6zyBRnbXg2otMND16O4xRmCkK5bFSb3FM2+HS5RyzNOmwvhmmFslHpS1fKcMrwNS/HcYLqRi7rEILiRhxBw4zZRiaoEDIIZWml5lBwzIAoUjMotY4DSCHrMCulkdBI65U15aTyshypn/PWZWfE8ZGX4zhACGBxpKbWYFZbMJKI1dIOTDFgthHS5y13rLQCc14fsV4ymmqO5krGbh64nCw+8nIcp41yOalBj+PRxhkePvJyHMdxRg4feTmO00Z603B2zcqSUieRWiVIsu0bBjIL6vA9RlwR3UdxaeJGepyQFAJYcYkWZ3niwctxnDaack+J9mC6pkWzhIm1AhZZrcIQ2CKsMMCIJFkjOUcvkd+i7Y3kJB7EHJ82dBynEElBx7DADv0Vi8wSJwEn3b9IKqovvwbewxlHPHg5jlPKkgwUPupy8ODlOI7jjCAevBzHcZyRw4OX4zilpDcsD0JZ+2IZqERRYwAZKLPiZA5neeHZho7jlCKJidiYa7SKTAqoRiHzsG5hW2qfqIhIaspJZWkWsczIQGXT8bNBL5vFmG/TTzq+M/548HIcpyuSqMYQN6x5r1dKLBFFIWc+zlZVlqhFxkw+VZFwv1iR4K+RlaVqbY3Vee+X43jwchynL6TidYZUx7CjQnJQ2h34HIX3iHnQcnL4mpfjOI4zcvjIy3GcvolyslFQfKNyKiFVSdpnZw9F61dzx7jMoIGhpppHuxxVm6JHib2MfPsy353RwIOX4zh9kZWNghCU0vWv7LReW5CQiDAi2te6lGgkphOLSrMaUz1DSsqm9LAXBbFsDbJs+/SFB7DRxIOX4zgDkeoSFq1z5UV70/YAcVJzOT/qUa7dMPDE+vHDg5fjOANzpIGmbC9PyHAGZagJG5LOlnSPpN2SLinYfqGkvZJ2JY+LMtsukHRv8rhgmH46juM4o8XQRl6SYuBfgDcCe4BbJe0ws7tyTb9qZhfn9l0PfBjYThjx/yTZ98lh+es4juOMDsMceZ0J7Daz+81sBrgaOLfPfd8M3GBmTyQB6wbg7CH56TjOIuNyT86gDDN4bQUeyrzfk9jyvEPSzyVdK2nbgPs6jrOESLMG8ytYQTlDbeoc7fv1v+ZVdPymvWBDM5Oxz/bOaDDM4FX0Z5H/eXUdcKKZvQz4LnDFAPuGhtK7JO2UtHPv3r1H7KzjOPOD1B7ElLXlAtggBSlb0lGJ2kfmHL0KY+bbj3Lg8mteYJjBaw+wLfP+eOCRbAMz22dmh5O3nwd+s999M8f4nJltN7PtmzZtmhfHHcc5epQJNO12DVxFueuoaoAgVObTKOHXvMAwg9etwKmSTpJUA84DdmQbSNqSeXsOcHfy+jvAmyStk7QOeFNicxzHcZzhZRua2ZykiwlBJwYuN7M7JV0K7DSzHcD7JJ0DzAFPABcm+z4h6W8JARDgUjN7Yli+Oo6zsJRJ9qYDoqJtllPDGFQeyhkvNE5ZPtu3b7edO3cuthuO4/RBVrap2yJ3W50vFat4kGk7BkGs7x6M6TWvr/67wobjOIuCcsOsjqBTYh+fn9vO0eDBy3GcRaVspDQGIyhniHg9L8dxHGfk8ODlOI7jjBwevBzHcZyRw4OX4zgjRaqUkWdMMg2dPvGEDcdxRo5Ufip7p48HruWFBy/HcUYWD1jLl7G6SVnSXuBXXZpsBB5fIHeGzbj0ZVz6AePTF+/H4vK4mfVVAkrSt/ttO26MVfDqhaSdZrZ9sf2YD8alL+PSDxifvng/nFHAEzYcx3GckcODl+M4jjNyLLfg9bnFdmAeGZe+jEs/YHz64v1wljzLas3LcRzHGQ+W28jLcRzHGQM8eDmO4zgjx1gHL0nrJd0g6d7keV1Ju7qkXcljx0L72Q1JZ0u6R9JuSZcUbJ+Q9NVk+48knbjwXvamj35cKGlv5nu4aDH87IWkyyX9WtIdJdsl6Z+Sfv5c0hkL7WM/9NGP10ran/k+PrTQPvaDpG2Svifpbkl3Snp/QZuR+E6cATGzsX0AHwcuSV5fAnyspN0zi+1riV8xcB/wfKAG/Ax4ca7NnwKfSV6fB3x1sf0+wn5cCPzzYvvaR19+BzgDuKNk+1uBbxHUi14J/GixfT7CfrwW+MZi+9lHP7YAZySvVwG/LPjbGonvxB+DPcZ65AWcC1yRvL4CeNsi+nIknAnsNrP7zWwGuJrQpyzZPl4LvF5acqI5/fRjJDCz7wNPdGlyLvBlC9wCrJW0ZWG8658++jESmNmjZnZb8voAcDewNddsJL4TZzDGPXhtNrNHIfyRA8eUtJuUtFPSLZKWUoDbCjyUeb+Hzv+YzTZmNgfsBzYsiHf9008/AN6RTOtcK2nbwrg27/Tb11HgLEk/k/QtSS9ZbGd6kUyZvxz4UW7TOH0nTsLIC/NK+i5wbMGmvx7gMCeY2SOSng/cKOl2M7tvfjw8KopGUPl7G/pps9j04+N1wFVmdljSuwmjydcN3bP5ZxS+j364DXiemT0j6a3A14FTF9mnUiStBP4d+DMzezq/uWCXUfxOnAwjH7zM7A1l2yQ9JmmLmT2aTBP8uuQYjyTP90u6ifDrbSkErz1AdgRyPPBISZs9kirAGpbedFDPfpjZvszbzwMfWwC/hkE/39mSJxsAzOx6SZ+StNHMlpzQraQqIXBdaWZfK2gyFt+J0864TxvuAC5IXl8A/Ge+gaR1kiaS1xuBVwF3LZiH3bkVOFXSSZJqhISMfDZkto/vBG40s6X2q7JnP3JrEOcQ1i5GkR3AHyUZbq8E9qdT16OEpGPTtVNJZxKuFfu677XwJD5+EbjbzP6hpNlYfCdOOyM/8urBZcA1kv4EeBD4PQBJ24F3m9lFwIuAz0pqEP6DXmZmSyJ4mdmcpIuB7xAy9i43szslXQrsNLMdhP+4X5G0mzDiOm/xPC6mz368T9I5wByhHxcumsNdkHQVIRNvo6Q9wIeBKoCZfQa4npDdtht4DvjjxfG0O330453AeyTNAQeB85bgjyIIPzb/ELhd0q7E9lfACTBa34kzGC4P5TiO44wc4z5t6DiO44whHrwcx3GckcODl+M4jjNyePByHMdxRg4PXo7jOM7I4cHLcRzHGTk8eDkjR66Eza6yMjCSpiVdKel2SXdI+kEiI5Q9xh2S/k3SdGJ/Jnk+UdLBpM1dkr6cKDkUlQvZJalQ6UXSpKQfJxqBd0r6m8y2L0l6IHOM0xO7l/BwnB6M+03K6+vPIQAAAj9JREFUznhy0MxO76Pd+4HHzOylAJJeAMzmjyHpSuDdQF6h4T4zO11SDNwA/D5wZbLtZjP73T58OAy8LtEIrAI/kPStRN0c4C/M7NrcPm8h6AieCvwW8Onk2XGcBB95OePMFuDh9I2Z3WNmhwva3QycUnYQM6sDP+YIlMiTMhzPJG+ryaOXMoCX8HCcHnjwckaRqcxU2390aXc58EFJP5T0UUkdquiJmPFbgNvLDiJpkjDy+XbG/OrctOHJXfaPE+miXwM3mFm2ZMffJVODn0w1NvESHo7TEw9ezihy0MxOTx5vL2tkZrsI1Zs/AawHbpX0omTzVBJQdhJ0L79YcIiTkzb7gAfN7OeZbTdnfDi9WwkdM6snU5THA2dKOi3Z9JfAC4FXJP59MLF7CQ/H6YGveTljTTJl9zXga4n48lsJivX9rJula15bgJsknZOICB+pL08lJXfOBu7IKJsflvSvwJ8n772Eh+P0wEdeztgi6VWS1iWva8CLgV8NepwkyFxCGCkN6sMmSWuT11PAG4BfJO+3JM8C3gbckezmJTwcpwc+8nLGmZOBTyfBIQK+SShaeCR8HfiIpFcn71+dKcEB8NGCrEEISSNXJBmLEXCNmX0j2XalpE2EacJdhIxH8BIejtMTL4niOI7jjBw+beg4juOMHD5t6Iw8kt4MfCxnfqBbJuIQfNgA/HfBpteb2b6F8sNxlgs+beg4juOMHD5t6DiO44wcHrwcx3GckcODl+M4jjNyePByHMdxRo7/B/uzuBw6neWYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(cat['FErr_SPIRE_350_u']-cat['F_SPIRE_350'])/(cat['F_SPIRE_350']-cat['FErr_SPIRE_350_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(cat['F_SPIRE_350']),y=skew, kind='hex')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 350 $\\mathrm{\\mu m}$ depth is ~ 6mJy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(cat['FErr_SPIRE_500_u']-cat['F_SPIRE_500'])/(cat['F_SPIRE_500']-cat['FErr_SPIRE_500_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(cat['F_SPIRE_500']),y=skew, kind='hex')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 500 $\\mathrm{\\mu m}$ depth is ~ 6mJy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add flag to catalogue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat.add_column(Column(np.zeros(len(cat), dtype=bool),name='flag_spire_250'))\n",
    "cat.add_column(Column(np.zeros(len(cat), dtype=bool),name='flag_spire_350'))\n",
    "cat.add_column(Column(np.zeros(len(cat), dtype=bool),name='flag_spire_500'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "ind_250=(cat['Pval_res_250']>0.5) | (cat['F_SPIRE_250'] < 6)\n",
    "ind_350=(cat['Pval_res_350']>0.5) | (cat['F_SPIRE_350'] < 6)\n",
    "ind_500=(cat['Pval_res_500']>0.5) | (cat['F_SPIRE_500'] < 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1538 3525 8333 20169\n"
     ]
    }
   ],
   "source": [
    "print(ind_250.sum(),ind_350.sum(),ind_500.sum(),len(cat))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat['flag_spire_250'][ind_250]=True\n",
    "cat['flag_spire_350'][ind_350]=True\n",
    "cat['flag_spire_500'][ind_500]=True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20169\n"
     ]
    }
   ],
   "source": [
    "print(np.size(cat['flag_spire_250']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set XID+ cahtalogue back to orignal order of objects, as used in MF detection files\n",
    "use = cat['HELP_ID'].astype(int) -1\n",
    "use = np.argsort(use)\n",
    "cat = cat[use]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reads MF table, removes duplicate RA and DEC\n",
    "cat2=Table.read('./data/AKARI-SEP_SPIRE_all.fits')\n",
    "del cat2['RA']\n",
    "del cat2['Dec']\n",
    "cat_all = hstack([cat,cat2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Created HELP_ID, and changes HELP to HELP_BLIND to avoid confusion with HELP-Masterlist objects\n",
    "ID = gen_help_id(cat_all['RA'], cat_all['Dec'])\n",
    "ID_new = [IDs.replace('HELP','HELP_BLIND') for IDs in ID]\n",
    "ID_new = Column(ID_new,name=\"HELP_ID\")\n",
    "cat_all['HELP_ID'] = ID_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# all flux denisties are in mJy in the final BLIND catalogues\n",
    "cat_all['F_BLIND_MF_SPIRE_250'].unit = 'mJy'\n",
    "cat_all['F_BLIND_MF_SPIRE_250'] = 1000*cat_all['F_BLIND_MF_SPIRE_250']\n",
    "cat_all['FErr_BLIND_MF_SPIRE_250'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_MF_SPIRE_250'] = 1000*cat_all['FErr_BLIND_MF_SPIRE_250']\n",
    "\n",
    "cat_all['F_BLIND_MF_SPIRE_350'].unit = 'mJy'\n",
    "cat_all['F_BLIND_MF_SPIRE_350'] = 1000*cat_all['F_BLIND_MF_SPIRE_350']\n",
    "cat_all['FErr_BLIND_MF_SPIRE_350'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_MF_SPIRE_350'] = 1000*cat_all['FErr_BLIND_MF_SPIRE_350']\n",
    "\n",
    "cat_all['F_BLIND_MF_SPIRE_500'].unit = 'mJy'\n",
    "cat_all['F_BLIND_MF_SPIRE_500'] = 1000*cat_all['F_BLIND_MF_SPIRE_500']\n",
    "cat_all['FErr_BLIND_MF_SPIRE_500'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_MF_SPIRE_500'] = 1000*cat_all['FErr_BLIND_MF_SPIRE_500']\n",
    "\n",
    "cat_all['F_BLIND_pix_SPIRE'].unit = 'mJy'\n",
    "cat_all['F_BLIND_pix_SPIRE'] = 1000*cat_all['F_BLIND_pix_SPIRE']\n",
    "cat_all['FErr_BLIND_pix_SPIRE'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_pix_SPIRE'] = 1000*cat_all['FErr_BLIND_pix_SPIRE']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# XID+ flux density vs. MF flux densities\n",
    "plt.hexbin(cat_all['F_SPIRE_250'],cat_all['F_BLIND_MF_SPIRE_250'], cmap=plt.cm.Blues,gridsize=(300,300))\n",
    "plt.plot([0,100],[0,100], color = 'red')\n",
    "plt.xlim(0,100)\n",
    "plt.ylim(0,100)\n",
    "plt.xlabel('F_SPIRE_250')\n",
    "plt.ylabel('F_BLIND_MF_SPIRE_250')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add field name\n",
    "cat_all.add_column(Column(['AKARI-SEP']*len(cat_all),name='field'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: 'mJy/Beam' did not parse as fits unit: At col 4, Unit 'Beam' not supported by the FITS standard. Did you mean beam? [astropy.units.core]\n"
     ]
    }
   ],
   "source": [
    "cat_all.write('./data/dmu22_XID+SPIRE_AKARI-SEP_BLIND_Matched_MF.fits', format='fits',overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "*This is a default HELP jupyter notebook *\n",
    "\n",
    " ![HELP LOGO](https://avatars1.githubusercontent.com/u/7880370?s=75&v=4)\n",
    "\n",
    "**Authors**: S. Duivenvoorden, P. Hurley\n",
    "\n",
    " \n",
    "For a full description of the database and how it is organised in to `dmu_products` please the top level [readme](../readme.md).\n",
    " \n",
    "The Herschel Extragalactic Legacy Project, ([HELP](http://herschel.sussex.ac.uk/)), is a [European Commission Research Executive Agency](https://ec.europa.eu/info/departments/research-executive-agency_en)\n",
    "funded project under the SP1-Cooperation, Collaborative project, Small or medium-scale focused research project, FP7-SPACE-2013-1 scheme, Grant Agreement\n",
    "Number 607254.\n",
    "\n",
    "[Acknowledgements](http://herschel.sussex.ac.uk/acknowledgements)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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