{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EGS master catalogue\n",
    "## Preparation of HST CANDELS-3D data\n",
    "\n",
    "The catalogue comes from `dmu0_CANDELS-3D-HST`.\n",
    "\n",
    "In the catalogue, we keep:\n",
    "\n",
    "- The identifier (it's unique in the catalogue);\n",
    "- The position;\n",
    "- The stellarity;\n",
    "- The kron magnitude, there doesn't appear to be aperture magnitudes. This may mean the survey is unusable.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This notebook was run with herschelhelp_internal version: \n",
      "0246c5d (Thu Jan 25 17:01:47 2018 +0000) [with local modifications]\n",
      "This notebook was executed on: \n",
      "2018-02-07 19:28:11.002418\n"
     ]
    }
   ],
   "source": [
    "from herschelhelp_internal import git_version\n",
    "print(\"This notebook was run with herschelhelp_internal version: \\n{}\".format(git_version()))\n",
    "import datetime\n",
    "print(\"This notebook was executed on: \\n{}\".format(datetime.datetime.now()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "#%config InlineBackend.figure_format = 'svg'\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rc('figure', figsize=(10, 6))\n",
    "\n",
    "from collections import OrderedDict\n",
    "import os\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.table import Column, Table\n",
    "import numpy as np\n",
    "\n",
    "from herschelhelp_internal.flagging import  gaia_flag_column\n",
    "from herschelhelp_internal.masterlist import nb_astcor_diag_plot, remove_duplicates\n",
    "from herschelhelp_internal.utils import astrometric_correction, flux_to_mag"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "OUT_DIR =  os.environ.get('TMP_DIR', \"./data_tmp\")\n",
    "try:\n",
    "    os.makedirs(OUT_DIR)\n",
    "except FileExistsError:\n",
    "    pass\n",
    "\n",
    "RA_COL = \"candels_ra\"\n",
    "DEC_COL = \"candels_dec\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## I - Column selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: '0.3631uJy' did not parse as fits unit: Numeric factor not supported by FITS [astropy.units.core]\n",
      "WARNING: UnitsWarning: '[Msun]' did not parse as fits unit: Invalid character at col 0 [astropy.units.core]\n"
     ]
    }
   ],
   "source": [
    "imported_columns = OrderedDict({\n",
    "        'ID': \"candels_id\",\n",
    "        'RAJ2000': \"candels_ra\",\n",
    "        'DEJ2000': \"candels_dec\",\n",
    "        'S/G':  \"candels_stellarity\",\n",
    "        'F140Wap': \"f_ap_candels_f140w\",\n",
    "        'e_F140Wap': \"ferr_ap_candels_f140w\",\n",
    "        'F140W': \"f_candels_f140w\",\n",
    "        'e_F140W': \"ferr_candels_f140w\",\n",
    "        'F160Wap': \"f_ap_candels_f160w\",\n",
    "        'e_F160Wap': \"ferr_ap_candels_f160w\",\n",
    "        'F160W': \"f_candels_f160w\",\n",
    "        'e_F160W': \"ferr_candels_f160w\",\n",
    "        'F606W': \"f_candels_f606w\",\n",
    "        'e_F606W': \"ferr_candels_f606w\",\n",
    "        'F814W': \"f_candels_f814w\",\n",
    "        'e_F814W': \"ferr_candels_f814w\",\n",
    "        'F125W': \"f_candels_f125w\",\n",
    "        'e_F125W': \"ferr_candels_f125w\"\n",
    "\n",
    "    })\n",
    "\n",
    "\n",
    "catalogue = Table.read(\"../../dmu0/dmu0_CANDELS-3D-HST/data/CANDELS-3D-HST_EGS.fits\")[list(imported_columns)]\n",
    "for column in imported_columns:\n",
    "    catalogue[column].name = imported_columns[column]\n",
    "\n",
    "epoch = 2012 #Year of publication\n",
    "\n",
    "# Clean table metadata\n",
    "catalogue.meta = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/herschelhelp_internal/herschelhelp_internal/utils.py:76: RuntimeWarning: divide by zero encountered in log10\n",
      "  magnitudes = 2.5 * (23 - np.log10(fluxes)) - 48.6\n",
      "/opt/herschelhelp_internal/herschelhelp_internal/utils.py:80: RuntimeWarning: invalid value encountered in true_divide\n",
      "  errors = 2.5 / np.log(10) * errors_on_fluxes / fluxes\n",
      "/opt/herschelhelp_internal/herschelhelp_internal/utils.py:76: RuntimeWarning: invalid value encountered in log10\n",
      "  magnitudes = 2.5 * (23 - np.log10(fluxes)) - 48.6\n"
     ]
    }
   ],
   "source": [
    "# Adding flux and band-flag columns\n",
    "for col in catalogue.colnames:\n",
    "    if col.startswith('f_'):\n",
    "        \n",
    "        errcol = \"ferr{}\".format(col[1:])\n",
    "        \n",
    "        #Calculate mags, errors including the fact that fluxes are in units of 0.3631 uJy\n",
    "        mag, error = flux_to_mag(np.array(catalogue[col]) * 0.3631e-6, np.array(catalogue[errcol] * 0.3631e-6))\n",
    "        \n",
    "        \n",
    "        # magnitudes are added\n",
    "        catalogue.add_column(Column(mag, name=\"m{}\".format(col[1:])))\n",
    "        catalogue.add_column(Column(error, name=\"m{}\".format(errcol[1:])))\n",
    "        \n",
    "        \n",
    "        #Correct flux units to uJy\n",
    "        catalogue[col] = catalogue[col] * 0.3631\n",
    "        catalogue[col].unit = u.microjansky\n",
    "        catalogue[errcol] = catalogue[errcol] * 0.3631\n",
    "        catalogue[errcol].unit = u.microjansky        \n",
    "\n",
    "        if ('125' in col) or ('814' in col) or ('606' in col) :\n",
    "            # We add nan filled aperture photometry for consistency\n",
    "            catalogue.add_column(Column(np.full(len(catalogue), np.nan), name=\"m_ap{}\".format(col[1:])))\n",
    "            catalogue.add_column(Column(np.full(len(catalogue), np.nan), name=\"merr_ap{}\".format(col[1:])))\n",
    "            catalogue.add_column(Column(np.full(len(catalogue), np.nan), name=\"f_ap{}\".format(col[1:])))\n",
    "            catalogue.add_column(Column(np.full(len(catalogue), np.nan), name=\"ferr_ap{}\".format(col[1:])))\n",
    "\n",
    "        \n",
    "\n",
    "        \n",
    "        # Band-flag column\n",
    "        if \"ap\" not in col:\n",
    "            catalogue.add_column(Column(np.zeros(len(catalogue), dtype=bool), name=\"flag{}\".format(col[1:])))\n",
    "        \n",
    "# TODO: Set to True the flag columns for fluxes that should not be used for SED fitting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<Table masked=True length=10>\n",
       "<table id=\"table139915632334272-274490\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>candels_id</th><th>candels_ra</th><th>candels_dec</th><th>candels_stellarity</th><th>f_ap_candels_f140w</th><th>ferr_ap_candels_f140w</th><th>f_candels_f140w</th><th>ferr_candels_f140w</th><th>f_ap_candels_f160w</th><th>ferr_ap_candels_f160w</th><th>f_candels_f160w</th><th>ferr_candels_f160w</th><th>f_candels_f606w</th><th>ferr_candels_f606w</th><th>f_candels_f814w</th><th>ferr_candels_f814w</th><th>f_candels_f125w</th><th>ferr_candels_f125w</th><th>m_ap_candels_f140w</th><th>merr_ap_candels_f140w</th><th>m_candels_f140w</th><th>merr_candels_f140w</th><th>flag_candels_f140w</th><th>m_ap_candels_f160w</th><th>merr_ap_candels_f160w</th><th>m_candels_f160w</th><th>merr_candels_f160w</th><th>flag_candels_f160w</th><th>m_candels_f606w</th><th>merr_candels_f606w</th><th>m_ap_candels_f606w</th><th>merr_ap_candels_f606w</th><th>f_ap_candels_f606w</th><th>ferr_ap_candels_f606w</th><th>flag_candels_f606w</th><th>m_candels_f814w</th><th>merr_candels_f814w</th><th>m_ap_candels_f814w</th><th>merr_ap_candels_f814w</th><th>f_ap_candels_f814w</th><th>ferr_ap_candels_f814w</th><th>flag_candels_f814w</th><th>m_candels_f125w</th><th>merr_candels_f125w</th><th>m_ap_candels_f125w</th><th>merr_ap_candels_f125w</th><th>f_ap_candels_f125w</th><th>ferr_ap_candels_f125w</th><th>flag_candels_f125w</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th>deg</th><th>deg</th><th></th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<tr><td>0</td><td>1</td><td>215.22238159</td><td>53.00418472</td><td>1</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>8181.01</td><td>0.0142633</td><td>9871.96</td><td>0.119445</td><td>650.167</td><td>0.0137945</td><td>1018.46</td><td>0.0208539</td><td>9100.38</td><td>0.0221371</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>14.118</td><td>1.89294e-06</td><td>13.914</td><td>1.31368e-05</td><td>False</td><td>16.8674</td><td>2.3036e-05</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>16.3801</td><td>2.22315e-05</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>14.0024</td><td>2.64111e-06</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>1</td><td>2</td><td>215.09658813</td><td>52.91805267</td><td>0</td><td>1.27368</td><td>0.026954</td><td>94.2571</td><td>1.99465</td><td>1.44895</td><td>0.0135948</td><td>107.227</td><td>0.590618</td><td>33.016</td><td>0.646136</td><td>53.0308</td><td>0.983674</td><td>91.661</td><td>1.09769</td><td>23.6374</td><td>0.0229766</td><td>18.9642</td><td>0.0229762</td><td>False</td><td>23.4974</td><td>0.010187</td><td>18.8242</td><td>0.00598035</td><td>False</td><td>20.1032</td><td>0.0212483</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>19.5887</td><td>0.0201395</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>18.9945</td><td>0.0130023</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>2</td><td>3</td><td>215.16146851</td><td>52.95946121</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.501477</td><td>0.0196452</td><td>26.0713</td><td>0.540293</td><td>9.57604</td><td>0.46386</td><td>13.7909</td><td>0.688946</td><td>24.01</td><td>1.17067</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.6494</td><td>0.0425332</td><td>20.3596</td><td>0.0225004</td><td>False</td><td>21.447</td><td>0.0525927</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>21.051</td><td>0.0542396</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>20.449</td><td>0.0529379</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>3</td><td>4</td><td>215.30529785</td><td>53.0529213</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.299735</td><td>0.0272783</td><td>0.410267</td><td>0.0348703</td><td>0.161358</td><td>0.01191</td><td>0.166961</td><td>0.0186666</td><td>0.40787</td><td>0.0460701</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.2082</td><td>0.0988104</td><td>24.8673</td><td>0.0922813</td><td>False</td><td>25.8805</td><td>0.0801396</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.8435</td><td>0.121388</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.8737</td><td>0.122637</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>4</td><td>5</td><td>215.0418396</td><td>52.87127304</td><td>2</td><td>686.441</td><td>0.0484012</td><td>825.29</td><td>0.0581904</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>77.0135</td><td>0.0104097</td><td>256.265</td><td>0.0160425</td><td>nan</td><td>nan</td><td>16.8085</td><td>7.65557e-05</td><td>16.6085</td><td>7.65542e-05</td><td>False</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>19.1836</td><td>0.000146756</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>17.8783</td><td>6.79683e-05</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>5</td><td>6</td><td>215.30380249</td><td>53.05212021</td><td>0</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.614547</td><td>0.0301939</td><td>0.982875</td><td>0.0523772</td><td>0.662803</td><td>0.0140367</td><td>0.952157</td><td>0.021835</td><td>1.01254</td><td>0.0746969</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.4286</td><td>0.0533444</td><td>23.9188</td><td>0.0578586</td><td>False</td><td>24.3465</td><td>0.0229935</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.9532</td><td>0.0248983</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.8865</td><td>0.0800967</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>6</td><td>7</td><td>215.26712036</td><td>53.02758408</td><td>2</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.156994</td><td>0.0271098</td><td>0.217729</td><td>0.0420288</td><td>0.0891047</td><td>0.0130001</td><td>0.154561</td><td>0.0201441</td><td>0.242536</td><td>0.0484702</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.9103</td><td>0.187486</td><td>25.5552</td><td>0.209582</td><td>False</td><td>26.5252</td><td>0.158405</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.9273</td><td>0.141505</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.4381</td><td>0.216981</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>7</td><td>8</td><td>215.3032074</td><td>53.05295563</td><td>2</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.134234</td><td>0.0190722</td><td>0.20843</td><td>0.0333133</td><td>0.0766141</td><td>0.0135208</td><td>0.122259</td><td>0.0213884</td><td>0.207802</td><td>0.0320127</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.0803</td><td>0.154263</td><td>25.6026</td><td>0.173533</td><td>False</td><td>26.6892</td><td>0.191609</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.1818</td><td>0.189942</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.6059</td><td>0.167262</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>8</td><td>9</td><td>215.30378723</td><td>53.05344391</td><td>2</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.175435</td><td>0.0192356</td><td>0.203365</td><td>0.0247638</td><td>0.0824963</td><td>0.0101552</td><td>0.109899</td><td>0.0157996</td><td>0.158192</td><td>0.0235928</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.7897</td><td>0.119045</td><td>25.6293</td><td>0.13221</td><td>False</td><td>26.6089</td><td>0.133653</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.2975</td><td>0.15609</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.902</td><td>0.161927</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
       "<tr><td>9</td><td>10</td><td>215.27868652</td><td>53.03592682</td><td>2</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.125879</td><td>0.0176125</td><td>0.252413</td><td>0.0423629</td><td>0.0961598</td><td>0.0190417</td><td>0.206353</td><td>0.0290712</td><td>0.235794</td><td>0.0426751</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.1501</td><td>0.151912</td><td>25.3947</td><td>0.182221</td><td>False</td><td>26.4425</td><td>0.214999</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.6135</td><td>0.152959</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.4687</td><td>0.196502</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td></tr>\n",
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       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
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       "        \"order\": [],\n",
       "        \"iDisplayLength\": 50,\n",
       "        \"aLengthMenu\": [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        \"pagingType\": \"full_numbers\"\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "catalogue[:10].show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## II - Removal of duplicated sources"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We remove duplicated objects from the input catalogues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/astropy/table/column.py:1096: MaskedArrayFutureWarning: setting an item on a masked array which has a shared mask will not copy the mask and also change the original mask array in the future.\n",
      "Check the NumPy 1.11 release notes for more information.\n",
      "  ma.MaskedArray.__setitem__(self, index, value)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The initial catalogue had 41200 sources.\n",
      "The cleaned catalogue has 41067 sources (133 removed).\n",
      "The cleaned catalogue has 133 sources flagged as having been cleaned\n"
     ]
    }
   ],
   "source": [
    "\n",
    "SORT_COLS = ['merr_candels_f140w', \n",
    "             'merr_candels_f160w', \n",
    "             'merr_candels_f606w', \n",
    "             'merr_candels_f814w',\n",
    "             'merr_candels_f125w']\n",
    "FLAG_NAME = 'candels_flag_cleaned'\n",
    "\n",
    "nb_orig_sources = len(catalogue)\n",
    "\n",
    "catalogue = remove_duplicates(catalogue, RA_COL, DEC_COL, sort_col=SORT_COLS,flag_name=FLAG_NAME)\n",
    "\n",
    "nb_sources = len(catalogue)\n",
    "\n",
    "print(\"The initial catalogue had {} sources.\".format(nb_orig_sources))\n",
    "print(\"The cleaned catalogue has {} sources ({} removed).\".format(nb_sources, nb_orig_sources - nb_sources))\n",
    "print(\"The cleaned catalogue has {} sources flagged as having been cleaned\".format(np.sum(catalogue[FLAG_NAME])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## III - Astrometry correction\n",
    "\n",
    "We match the astrometry to the Gaia one. We limit the Gaia catalogue to sources with a g band flux between the 30th and the 70th percentile. Some quick tests show that this give the lower dispersion in the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gaia = Table.read(\"../../dmu0/dmu0_GAIA/data/GAIA_EGS.fits\")\n",
    "gaia_coords = SkyCoord(gaia['ra'], gaia['dec'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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XZ08XQDQ7wfvHYyfSReU1TKqaNdo1M8bnYeGTjMOiHFQEV2IaEowUmza3bwjV\nMLtWc9H88SfgcP7FYuOQakCr20NJrpWcgzqCqYhxsJ1Yf+9Ix8RjR1UV7AoMLbDR6NKpa9MxgSy7\nQmmODVUJf0MSzk6mzaevWNfmDegIFjh9Nzb+IdRYzqu32nGwnW8zxtEScF/qK4RQJNlFIdE7pq4X\nZ9ftidgJtz0eO35fmjp1auMQ+exiCX+S6ZdpCXneE48v4Dsn3fBVDm2eWJNuV18gNOkFb48Nk4Pq\n3c1eCjOMQIWaTIy7bv+27firvAKnhTyHhU7dINOmxvWMEg4lxQFZvmpRwTehJVI1F80fSG07Ptx2\neuMaT2VfIUmvO5LseiCZRuO/qFJlJ1kbQBKJLmAJiwLFcU7wCOdPh8dIMNGF+pP45JVDmEC2w5KS\nGKfqt0rWjqoqqECWqiZtx6mE+pYIqWzH6WgnlX2F0B159SAKqWgzitI7qsKHk1SeTmpMpcqKdBKR\nSLc23BdJVYwl14VHkp0gCIKQ9kiyEwRBENIeSXaCIAhC2iPJThAEQUh7JNkJgiAIaY8kO0EQBCHt\nkWQnCIIgpD2S7ARBEIS0R5KdIAiCkPbIcmFRSMWCBqlcqy4VC72qik9hIBk7enLrjYWQuJRqV5KP\nr26kJsbg0+RLZjm1VC35ZJhmStaXSeUSVKmKcbJ2UnVOfc1OoiFZsakm5n2/iwoJUtn1QLgFYxM5\nLpV2EkE3TDo0g5pWDZfXxEgwYRmGSYdm8tGeDjo8RsKJT9NNdjd5+LK6A003MRI6L19HXpShUJyh\nHuzUE/NHVQjEJNkYf1LRQYNLx5tEjDu9h8RYE4uNL9G1unWqWzV0IzE7fa0dd13dPxk7EHlR6G/T\nTm/FWAhFKrsoxKo71ZVI1Vwq7YTbHsmGbsKOejdb9rl9i0C36+Q7LQyKQ6rFNE0ME2ravDR16gC8\nvqOVsf0cjCx2YInRjlc36PSaLP+qhV2NGgB7m71MHuxkYI4Na4wr6vtX4C/Ns+G0+u7Z8jN8UkFu\nb+wpT8Enf1OSG/rdicR4Z72bzQdjXNHi5ch8G8cNysCixiar449x7UFdP4BWt4d+WRaKMiNr0HXF\nMHx2Klt8Mk5+O4NyrOQ4Ylc/6Gvt2I9//2hSO9+WneB9E5Ha6e0YC4eQZBcDscpn9CTREetF1dPn\nsdrxGibtHl+l0dxFdbqpU6fNo1OSYyPLHr0DNEyfnapWLUTI0zBh0z43e5o1TizLJMuuRkxWpmni\nNeDL6k77rH0BAAAgAElEQVTe+aYNLciORzf5uMLFwGyNE0ozsKlKWDHVwPkD/bNUijKtIefusKoM\nK7DT0OGlrr2r8np3G6pCiI5dyOexxlg/WM1VdgQSlJ/dTRo1rV4ml2QwINsaNZEbhkm7ZlDdGiqW\nagL72nWaO42D2oFElNgxTZ+CRGPnIR07P7oJlS3eUF27KHaC49CVb7sdR/s8nhvSVNiJJTY9fVes\ndlIRY+EQfTLZuVwuFi5cyOrVq2lubmbEiBH85je/4eSTTw67/6pVq3jyySfZvXs3OTk5/PjHP+am\nm24iIyMDgFGjRmGz2bo1iC+//BK73R6zX9Hu3GJtdD1dVKmwYxgmBrC5rpMd9Z6Inb7XgD3NGjl2\nlZJcW7fqzF+xVLVotHoiP11rdhu8tbONkYV2xg10ohLakWq6QYvb4MWtLdS0eiPaqW3z8vr2Vo4d\n4OTIAnu3qlMBMmwKpbk2bJbIHWhRlo1cp0lVi0ZHGIFaBaIqlAfb8sehW4wPVmFb9nWyPUqM3brJ\nR3s7GJxj5fiSDKxdErnfTnWLN2qM3brJNw1aRFV4wzDRjPAK5cG0e0y213siKpb3pXbcU0KIZKfr\n/vEkhGhJ5tu2k6oYCz76ZLKbP38+X331FUuWLGHw4MG88sorzJ49m9dee41hw4aF7Lt69Wpuvvlm\nHnjgAc444wzKy8u58sorsVgs3HbbbYH9lixZwgknnJC0b5GeFcTb4FJpJ/ii0k1odOl8WtlBhxbb\nYF6rx2B7vZtB2VbynBZURcEwTVo6darbvDHp35nA9gYPla0aU0ozKciwYJommm7ywe4OPtrbEZMd\nrwFf1HSyq0njpLIMnFYVi6qgKjA4x0quIzZtNptF4Yh8Gy1uX7VkmL4kZ1WhNM9Gpi32x9XhYtx0\nMMbtMca4utXL37e3MmFgBkPyfUOmhmnSHKeYboPrkLJ6hlVFUXyx39/h5UBHbNN9THy6hs2dBqW5\nVqxq6KSGeNpgb7XjVNhJVCOua5JJ1J/esJOoDaEPTlBpbm5m5cqVXH/99QwdOhSHw8HMmTMZPnw4\ny5YtC7v/nDlzOOuss7BarYwcOZJp06bx6aef9qqfXcfqD6cdv2ZeXbuXL6pdvF/eHnOi82OYUNXq\nZXeTh1a3zu4mD5WtsSW6YDo0k/fL21mzt50DHTp//ryB1XtiS3TBNLh03tjRRqNLJ9ehMrLITp4z\nPnFVRVHIc1o4qshOvlOlKFNlRJE9rkQXbMsf4y+rXbxX3h5zovPjNWBttYsPdrfT6tbZ06RR3Rq/\nmK5mwO4mL1WtGq1ug28atJgTXTAur8mOBo1Wj+8ZrP8cEyGV7ThVdvwJL1Xn1NfsCPHR5yq7rVu3\nomka48aNC9k+fvx4Nm7c2G3/6dOnd9tWUVHBoEGhU2P/93//l9tvv53GxkZGjhzJjTfeyKRJk5Ly\nNfjOMVlS0Xi/qHLF3QF3pUMz2dOsJe3LrkaNrfvcFLn0hG0Ypu/508BsS8wTV8JhURUG51hTEuMv\nq120eZKL8YEOX6JL1p8Wt0mLWyPZ1y7aPCY59sSnrAeTqk64r3TmqbrG+1pf8X2kz1V2DQ0NAOTn\n54dsLygooL6+vsfjX3nlFT766COuu+66wLYxY8YwZswYXnnlFd555x1GjRrFFVdcQWVlZWqdFwRB\nEPokfS7ZRaOnO5rFixczf/58HnnkEcaPHx/YvmLFCq655hqys7MpKCjg9ttvJysri9dee623XRYE\nQRD6AH1uGLOoqAiApqYmBgwYENje2NhIcXFx2GMMw+COO+5g9erVPPvssyGJLhxWq5XBgwdTV1eX\nOscFQRCEPkufq+zGjh2L3W5nw4YNIdvXrVsX8RnbnXfeycaNG1m+fHm3RLd161YWLFiAYRx6gO/x\neKioqOCII45I/QkIgiAIfY4+l+xycnK48MILWbRoEeXl5bhcLpYsWUJVVRUzZ85k06ZNnHXWWVRX\nVwPwzjvv8Pbbb7NkyZKQStBPUVERK1as4P7776etrY3m5mYWLFgAwIwZM77VcxMEQRAOD31uGBPg\ntttu4/777+fiiy+mvb2d0aNHs3jxYkpKSqisrKS8vBxN880YXLp0Ka2trZxxxhnd7Lz55puUlJTw\n9NNP89BDD3H66aejaRoTJ07k+eefp7Cw8Ns+NUEQBOEwoJiycmhSxLN+XW/aAPj71y1Jv3qQKlya\nwV8e+T2nzro5KTvHDXLyk6OysVmSG4RIVYxf396S9KsHAGP6OVI0hdwk2VcP8p2qb53UJF7vgL6j\nZpDOdlLli58n3tueMlt+DqciQr9+ORE/63PDmIIgCIKQaiTZCYIgCGmPJLskSMUIsNcwqWrxUtuq\nJaxbBj45l3e+aeObendSfu2saeDJt9azo7ohYRvgW4My16Fij7Bgcywo+BQR1la56PQmLvPa6PLy\n329W8NCH1biTsNPi1qMushwr7R6Df+5up7Yt2ZVqkvfFME12N3r4tLIjqRgHPErRU5G+8nSlL55P\nX4nNd40+OUHlu0Bwg0tksVnTNGly6dS264FFipvdHkpzfZI7saLpJsu3NvPatlY03aSm1Ut5o8YJ\nZRlhpWsi0eHWePXT7Wzdux9NN9izr5kxQ4o5f8ooMh22mO34sVkU7FaF4YU26tt19nfocXXNmQfV\nDQzTt5J/TVsrxw30qSHEGmfTNHn9X43c+49qPF4Di6rwxrYm/t/ZQ5hUmh2zL4Zp8tW+TrYd8KAn\n0c/ohu/3aXH75IfqO3xqCBMHZ+CwxnvfaYb5d3w3Fh2aQUWzJyApVNPWyoSBTobGEeOAB12uh0Se\nK3XtxJO1k+hC0OH86Yt2ZNmw+JAJKnESTWwx3PZweHSTymaNTm94+Zlch8qgnOjyMwDbD7h5aM0B\nmjt13EFLUCr4tNpG93Mwur8jqladaZps3rOf5R9vQ9d1tKBVia2qgtWicuFJRzP+yP5xX1wvPXYf\nF117q0/9wDCpbPbi6qEyUhUYlG0l19ldY8+iQL7TEtDOi0Z1i4f/fnMvX9W5un2n06rw45F5/Ndp\nJT3eENR3ePmkooNOr5lUomvp1Klq9anKBtdPquI7r0klGZTldpeh6k6wE0qY7T3/RrphUtOm0dzZ\nXfPPF2OVKWVZZMdw05WK6yHS/vFI/MRiJ14bqbLTG7FJxE44vk8TVCTZxUGygoymaVLf4WVfD8Ki\n4Ot0BudayQ3TGbs0g2fXN/LP3R14ovTAVhUyrCpThmRSmNHdTnO7mxc/+oo9+5vxRBnCsltVhvTL\n42enjCY/y9mD54fwJzs/hmnSHFTNdiXbrlKaG1093Z/Ix/Z3cFRx90SuGyZL1x/g0TW1aHrkBGW3\nKDitKvOnlXL6iLxun3sNkw01LnY3aUklOU03qW7V6PCYRBsktChQlGnhhJJMMiMmmVgSWvR9Wt06\nlS0ahhl5ENQf4zH9HYwKE2OILRHF0hmn2s53ZZ94zjuWfRJNeJLshBBScSfW6TWoaNbQ9NiftChA\nlk1hcJBY6foaF3/6pJ4OzQhR+46GRYHhB4VV/Tpqn31dxetf7ETXjZg6c8tB0dFzJo5gytElUatF\nP12THQQLwnppOyhWalGgNNdKZg+K6V3PKcumcuKQTPKdvkS+80Ant7yxh6pmT48VpB+nVWFSaRbz\np5VRnOUbrq1t1fi00oVmmHHL7/gxTZNGl0+rDmL7zf1JZvxAByMLg19NiFTNRfz2bvv6ng1rtHl6\nvtHyY1Eg06ZyUlCM4fBUJj1VW4fLTl+p2hJNepLsBCCxYZSuxxqmyf52nQaXgZngO1GqAplW+L8t\nLayr6YxazUXCqoDVonBUPry9dhv7WzqiVnORsFtVinMzmXX6OAqyM6LuGy7Z+TFMk3aPQZvbYEC2\nr5pLRGPGosAReVY+Lm9m6YZ6PGGGhnvCqoLdonLjqQMZlJdBbZs3qWrO7TWobPHi0RNLlhYFchwq\np5RlkuXwV3mJ3Ln7REObOnVq2nTMKNVcT/6MLLQzdsChKi+ZZ3p++sLzuFQ+1/OTitgkayfWY79P\nyU4mqPRAskKLDR3+RAeJvvxrmPD4F43srE98goTXBK/X5Ln3N+H1aiR6i+PxGjS1d5KT4UjMwEFU\nRSHHrpJtj015PBK6Ccs2NvDPnU0hzxvjwWuA1zD4ul7DUK0k+5L27iaNZCY26ia0eQwy7GqSvih0\naAbVrfFNDgrnj0lqhEeTHXZLpZ1gRfNESTZZBh+XajtCKPLqQRRS0WYSvZvuijvJCRJ+DMNI+rxU\nVU3NBZVE5xmMWzcSTnTBOK3JJhcfqQiNRVFSYscwUyPKqqpKCiLjo68IvPYVP1JtR3JdeCTZCYIg\nCGmPJDtBEAQh7ZFkJwiCIKQ9MkFFEARBSBkrNtUkdFxvz+KUyk4QBEFIeyTZCYIgCGmPJDtBEAQh\n7ZFkJwiCIKQ9kuwEQRCEtEeSXRT6klxUX/IllVpaqViJRSEV656AV09evDRV+JbnSpGtVKyokaKV\ngITIpGqZr77UV/QlJNn1QDIN0DRN8p0qTmuySy2ZnDkim1yHii3BX0zBt+DxOZNGkmm3YE1QQVwF\n2js13tu0G49XTzg+Xt2gud3NjuoGPF695wMi4NE0+lk6MV3NYCRux/B0snLVW9TXVaO5OxOyYZom\nmm7Q0uFG042EYxOQMTTNg+0mMTuGaWK3KPQgi9gjFsWn9m6ayV8P/v9P1E7wsX3RTqKEE3hN1o4Q\nirxnF4VEF2gNbnB2q8qwAltA7iW+pnhIqqUk184NJxbzfnkbn1Z0xLXQsE31aaVdNDaf/lkDuHhy\nCY++vYUvdh3AHW+iUXxuvbdxN5t27+OXU8dQnJuJzRqbKrppmnh1gzXbKnlrfTle3WD4wAIuPvUY\nMhxWrJbY7BiGgeb18spbH7Jmw1YAMvoNIefIcagWC2aMtxeK7kHraGXvc7fSvuMzPn/YzkXX3crZ\nl8zGZnegqLHdXWi6QaPLyyubDnCgXcNuUZhQlkf/HDuWGG2A77caVmDnvNG5ZNvVgwoKGm5v7CnP\nNH3KDw0unbo2b8IVmV9y6NiBDoYflBwK7tyTFVRNpZ14RhpSYSfVAq/Bx6QqNkIoIvETI7HKZ0Rr\ndJru0xTr0HqSoYmuX1bbpvHSlmYaXXpUTTu/Cva0EdkcX5rZTSvui137efD1jbg0b1S5H1UholSN\nAkwZNZifTBqJzRqqYNBV4kfz6jS2d7L0n1upaWwLsWOzqJwzcTjHHzUYqyW6EoJH09i1t5rn/vYO\nLW0dob7aHOQPn4A1txhFjZY4TQzNTdPnr1G98mFMjyvk09IRo7nhgWfoX3IEdmdkKSPDNNENk/d3\nNPJFRVu3z/vn2Jk4JA97D+dkUXyCshcck8uo4lBFCdM0aejwUheD6K9h+FThK1o0OmPU9IvkT3Gm\nhRNKM8kIM5xwOIRZU2UnGbHUw2En2dhEozckfhIlFS+VJ6RnV11dnfAXDh48OOFj+zqpEFtscetU\ntXgjJJDuwpvhMEyTNXvbeX9XO7rZPRnZVCjNs3HhMXnkOSN3+i6PlyX//BfvbqmKmPBUiKqyDZCX\n6WDmD0dT1i8P+8Eqz5/sDMPEaxi8s34Xq7+qiPoMqaQwm0t+NJa8TEe3alHXddwejedXvsumr3dF\n9cdRMJDc4ROwWKyYSpfO2utGa97PnmdvxlX5VUQbiqpy9iWz+fn1t2OzO1C7VJ2ablDT4uG1LQdo\n6YxcIVtUhXGDsykryMSiQtff1qrC+AFOzh6ZjcMauQqMdrPkr+b2tXk54Ep8OFcFLCocX5JJaZ6t\nx/17U5j1cNuJZCNVdr5tgddwSLIDjj766ITEA1VV5auvIncg6UDXRp9Io9MNk5pWLy1u/9169Gou\nEo0uneVbm6hp9aIZvjtyq6pw3uhcxvZ3xOzTtuomFq5cT1O7G7fXiFrNRWPcEf3495OPxm61sOLx\nhZx39S3UNrax9IOtNLbF9ixMVRR+NHYIp//gSGwHKyKPprFp2ze8tOqfuNyemOwoFit5R47DXlTi\nq/JMA0PzcOD9p6l7dwkY3pjsFA8q4/qFT3Hk0eNxZGQGqqc3vqrnq7qOng0cpCDTxuQj8nBaLaiq\nglX1qa1fNDaPITEkFvC1vRa3QXXroZslwzTp1HzVXDJSRxYFSnKtTByciT2OZ7rhhFD9f8dDb9o5\nXAKvqegrIvmSiJ2uSLLDl+wWLVpEXl5ezF/U1NTEb3/7W/71r3/F7+V3kFTcWbV7DPY2aRgJqpj7\n/dhY6+L17W2MKLQz/ehcMhOYyaLpBv/3yU6eX7PT/2guITLsVmZMOYp/vb4E5dgZrPumNiE7RTkZ\n/OKUUeQ4bfzvq2+zc29VQnZsOYXkDBmDt6mWvc/9F579exKyc/I5/86V8x9jT5PGG/9qwBVtDDkC\nigJH989izOAcTizN4LRh2VgTmEGiGyZ7mzVa3QY1bRpNnYnPJLWpvhukE0ozGZCd+GP8VFwPqerI\n+6qdZJNTqp/NSbLDl+w+/vhjioqKYv6iAwcOcMopp7Bt27b4vfyOkopp+BXNGi3uVEx7TzxhBnPO\n/W8k7wrQvGYZeSfNTMqGt60Bs7kW3UguPm1rX6GjfH1SNgCOvm0ltuIhSdvZcMO4bs9Q46XRpfN+\neVtSqugAQ/NtHDc4I6GkG0yqXkkRO73vi5/vU7KLeBv33nvvUVhYGPjbMAxqamooKSkJbNu2bRsj\nRozAavWZKSws5L333kvaYUEQBOH7RaJqCRBboow41lVSUhK4g6iurmb69On88Y9/DNln/vz5zJgx\ng9pa3zCVqqohyTBRXC4X8+bN4/TTT2fixIn8/Oc/5+OPP464/6pVq5gxYwYTJkzg1FNP5Z577sHl\nOjS7rqGhgRtvvJFTTz2VyZMnc+mll7Jly5ak/RQEQRC+G8T0YGfhwoVkZ2dz+eWXh2y/5557KCgo\n4L777kupU/Pnz2f9+vUsWbKENWvWMGPGDGbPns2uXd1n4K1evZqbb76ZX//616xdu5YlS5bw7rvv\n8vDDDwf2ueGGG2hoaODFF1/kn//8J8cddxxXXHEFjY2NKfVbEARB6JvElOw+//xz7r77bo4++uiQ\n7cOHD+fWW2/l888/T5lDzc3NrFy5kuuvv56hQ4ficDiYOXMmw4cPZ9myZWH3nzNnDmeddRZWq5WR\nI0cybdo0Pv30UwC2b9/OZ599xi233MLAgQPJyspizpw5KIrC3/72t5T5LQiCIPRdYpp65Xa7Iz4U\ntdlsuN3ulDm0detWNE1j3LhxIdvHjx/Pxo0bu+0/ffr0btsqKioYNMg3hrtx40ZsNltIorZarYwZ\nMyasPUEQBCH9iKmymzx5MosWLaKlpSVk+759+7jnnnuYOHFiyhxqaGgAID8/P2R7QUEB9fX1PR7/\nyiuv8NFHH3HdddcF7OXl5XVL1vn5+THZEwRBEL77xFTZ/dd//Re/+tWvOOmkkygrKyMrK4uWlhYq\nKyvJz8/nr3/9a2/7CfT8bsnixYv585//zCOPPML48eOTticIgiCkBzElu6FDh7Jy5UpWrFjBli1b\naGlpYdiwYfzyl7/kggsuIDs7O2UO+d/ra2pqYsCAAYHtjY2NFBcXhz3GMAzuuOMOVq9ezbPPPhuS\n6IqKimhubu72fkpTU1NEe4IgCEJ6EfNyCQUFBVxxxRW96QsAY8eOxW63s2HDBs4888zA9nXr1nHa\naaeFPebOO+9k48aNLF++PCRBAkyYMAFN09i6dStjx44FwOPxsHnzZv7zP/+z905EEARB6DPEvKaU\ny+XihRde4I477mD27Nns27cPwzBYu3ZtSh3KycnhwgsvZNGiRZSXl+NyuViyZAlVVVXMnDmTTZs2\ncdZZZwUWqn7nnXd4++23WbJkSbdEB74Zo6eeeioLFy6krq6OtrY2HnjgARwOB+eee25KfU+UTJtC\npi25IVXDNGlw6XQmuZxGu8egf//+gYUCEiU3K4OivGzUJFflGNiviKHDhiVlA2DyyT/imMk/TMqG\nYrGhOLKS9iXDprKj3p30b+U1TPIclqTXzFEVaHUnrk0Ih9bsbPMkd06GadKYgnYsCF2JqUerqKjg\n0ksvpa6ujiFDhlBRUYHb7aa8vJzLLruMP//5z0ydOjVlTt12223cf//9XHzxxbS3tzN69GgWL15M\nSUkJlZWVlJeXo2kaAEuXLqW1tZUzzjijm50333yTkpISHnzwQRYsWMC5556LpmlMmDCBZ555Jqnh\n165ii4k+/zNNk8IMCwUZFlo6dWra9LgXYG73GFS0ePALbRdnWuiXZY1rOSrTNNlU62Ll120MKStl\n8ODB7N27NzBhKFZURWH8iFLGDCvhw13vcsKPJrJ6/XbqGlt6PjgIu9XCiWOHUzqgEEyT8ePH8e67\n73WbJNUTxQV5zJpxJoP6FWIaXtavfoun7p5Le0tTXHYyj/wBQy69H2umb63YRNcOPWZgJueMLmJD\nbSdb9rmZMNDJ0AJ73Hps+9q91HcYDMi2UpxppaLFQ4cWn0eqAoOzrTisKjWtOg0undJcW1TlhXB4\ndJPK5kOSQtl2hcG5triXH+vQDCqbtYPLn+kUZqj0z46vHfvpKqiazELQ/n8nc42n0o5o1yVGTHp2\n1157LU1NTTzwwAMMHjyYCRMm8Le//Y2ysjIeffRRPvroo7DvwKUrXRtbIovFhjvGME1ME6oPqiH0\nhG6Y1LRpNHeG6pz5ZVrK8uwxLQjd5NJZ/lUz1S1aiD6eYei4XC527SrH4+lZaaA4L5upE0aR4bBh\nsVj44Nk/MHXWzXh1nb019Xz61S60GMRihwws4uRxI3yKB37hU9PAqxusX7+O9es39FiFqIrCv514\nHGeeejw2iyVgR/dquF0unrr7t3zy1is9+qI6siiZcQu5E85CtTkD2+NNdrlOC+eNLWZQrh2b5dBv\nYlEg32lhSlkm2faefyuXZlBxMCEEf79hmrR06lS3RZKO6uKPQ6Ukx4aqBLdZEwWF4kyVflnWHtuy\naZoc6PCyP4zOnqrA4BwruY7oOn7ga8e1bd5u7VjBJ39UmmeLeWHzSMKsXbcdLjup6itStUB1X1ob\nMxn8y4UltBB0MJMmTeLpp58OTPwITna7d+/m/PPPZ8OGDSlyu++SCrHFWPYzTJMOj0FVqzfiIr8+\nTTwNw4zc6SpAvlNlYLYNS5i7bMM0+aSinfe+Ca+Jd9BbDMOguqqaun37wn6P1aIyefSRDCvpj9Wi\n4l+M2p/sAEzDwOPV+XjTTir2ha8WMx12TvnBSPoV5ERULNe9Xtra23n33Xc5cOBA2H1KBhRz2YVn\nU5Cbg80WfvDC7ergm81f8uhtv6ahLrx2Y84xp1L2i3uwOrMwLZEleKIlPgWYVJbDj0bmY1WVsFWK\ngi85jOnvYFSxI+w+hmlS2+qlqdPAjLDgt2maGCZUtmi0RhhOtKpQmmMj065GrJj8SaYszxZWuBWg\nUzN8kkJ69HPPsCmU5tqwRZAMag3SdoxmJ8+pMjDbGrYdQ8+df7yCqj3ZSfYa/7btROL7lOxiGsZU\nVTXikJ+maWlfTsd6ofi1ppIVf1QVhSy7yshCO7VtXhqD5Fu8hklli0a7p2fVahNo6jRocbspzbWR\n4ziUQOravLy0palHtXNQUFULJSUlFPcr5ptvdtHZeUiXbnBxPj/8wUjsNiuqGvnuW1FVHHaVUycc\nxb6GFj7cuINOjxb4fFTZACaOHuqreqIpelut5OXmct5557Ft27/47LPP8Xp9unQ2q4VzTzuJUyaO\nw2q1RI2xIyOToyeexMMrv2Dpw3fxzrLFgd/Hkl3IkJnzyBpxAord2WOcFYWwgrTFWTZmjC+mIMMa\nUs11xQR0E7buc1PeqHHSkEzygwR32zy+4b1DCSFCklIULIovSbV7DKpatZCbpQKnhUHZVhSlhw4f\n0AyT8kbNd7OUc2go0TBN9rV5aXBFTrrBdjo0kx31HvpnqRRlHqoWvYZJVbNGexgh2nB2mjsNWt0e\nSnKtIe0YYuvwgyuiSEOJ8doJt++33Vf0ZEc4REyV3SWXXEJpaSkLFy4EQiu73//+92zZsoXnn3++\n1509HKRCbDEZO4Zh4tZNKpo16to1ahN4pge+LinH7nsGsnp3O59UdKAbke+mw2NiGCb79tVRv38/\nJ44dxuB+BRGrsODKLsSKaeLVDdZ+tYu6xlamTjiKvKwMLBHsRMLQdTrdbt577z0yrQqzLjiTrAxn\n3JNrPJ0d1OzZxR9vvoyOoqMpufBWLDYnphqfP3CoSjt1eD6Th+RgVZW4f3OLAiMK7RzTz0Ftm5c2\nT88JoSv+Kq+2zUu7ZlCWa8NhUeKeMOQ/n9I8Gwq+qjH+duOzY7f4xGFdmklde+LtOMumUJJnI7hY\nTGRo0X9cXxJmDfd3onZi4XBXdqmQ9Qkm6cru6quv5pprrmH9+vVMmTIFr9fLokWL2LVrF9u2beOp\np55KmbN9iWTulpJtuH5UVcGp+IYta1t1Ep2jZgKtHoOXP2+g1a0nqIHm6ywHDRzAj8Yega8Ii18k\nVlEUbFYLJ4wZhqKoqApRq7lIqBYLmZmZ/GLGuZTk2rBa409OAHZnJkNGHsMZv/876yuawepIWLgW\n4JeTBjIwx3ZwSDd+dBN2NnhQFSXisF1P+Ks8fyXn3xYv/qpzT5PW47492XHrJrsavUkJA5tAm2bi\n0U0yrPHfSED3Ki942+G2k6gN/3HRKtfvOzFdjVOnTuUvf/kLQ4YM4a233sIwDD788EOKi4t59tln\nOfHEE3vbz8OCaSY/LKAoiV2QXW00u42EE50fE98zkgQEtkOwqCqqqiSU6ELsWCy+zjzJ+GTYrQkn\nFj+KqtLQaYLVkZQdEyjKSt4fSDosgO9myXcvkYrOL5lbAPA/3UzWCoDdkprrKvj/+4qdZG0k8QZJ\nWhPzeM/xxx/P8ccf35u+CILQG8hNviDE/lL5pk2bQt5xWrFiBXfffTdvv/12rzgmCIIgCKkipmT3\nxtW11nsAACAASURBVBtvMHPmTHbv3g3Ak08+ye233866deu4+eabWbFiRW/6KAiCIAhJEVOyW7x4\nMb/97W8ZP348pmny7LPPcvXVV/Paa69x11138dxzz/W2n4IgCIKQMDElu/Lycs455xwANm/eTEND\nAxdddBEAU6ZMYc+ePb3noSAIgiAkSUzJzmazBabFrlmzhiOOOIKSkhLA91K5YciirYIgCELfJaZk\nN2rUKJYuXcqmTZt44YUX+PGPfxz47P3332fo0KG95qAgCIIgJEtMye7666/npZde4mc/+xlOp5PL\nL78cgH/84x888MADzJo1q1edFARBEIRkiOk9u+OPP57Vq1eza9cuRo4cSUZGBgDDhg3j8ccf54c/\nTE4nTBAEQRB6k5jfs6uvr6elpSWQ6AC+/PJLysrKesUxQYgHWTRCEHzISmHhiSnZffHFF5x//vm8\n9tprIdtff/11ZsyYwfr163vFucONbzX75NSbg/9Lxs4RXRa+TZQh+cnbMU3ff0mKkGNRwGFViFGq\nLJI3tBxc6zOZGCvA+MFZ2CxKUguOqAps2+fCm8gqx0EYJmi6SXJp3DzoU3LnBL74JGvFb0MJ8i1R\nO22e5JTVobsYaqI2+podITwxqx4MGzaMO+64A7vdHthumib33nsvW7du5YUXXuhVRw8XiYokpmIl\n867f3eLW+WRvB60eAz2JNl3X5uXTig68uok3DjsWBWwWhRPKMhmQZaHRpVPXrvuSX5j9I6ke2FQo\nzLBw0dg8CpwW3i9v47NKV9yLUxumSftB+RuLqnB8iZMBOfErZCtAYYbKgGwbNS0eHv24hpoWD+44\ngqwc/J/i7AxyM+0MyLZyYlkm9jiVBvwqA2V5NrLtFkIjG58du8WnVmC3KDHL8oSz41cZAKhu0RJQ\nYfCJwhZkqAzItqLpPpkqtzcx9YQB2RYKMywJKw2kQlD127CTTF8RK6lWPUi1ikG8JC3eetxxx/Hq\nq68yZMiQbp9VVFRw3nnnsW7duuS87OP0FdFG0zTZUe9mU507quBlT3gNk821nXzT4IkpcVoUGFZo\nZ/xAZ0gy0XSTmlYv7Z7uC1V3TXaq4rNzxrAsTijLDBEPrWvz8uKWZpo6Y1mo2sRrQGWzRlsXkdKB\n2VamlGVgU3tOMiq+5F2aGypSapgm725v5PkNB/DqZo/xURXfYtT9cjNDFoC2KDB+oINhhQ6sMSg7\nKECBU2Vgji2MsKoZtFd0FOimHwfQ6fWpnEcTXA22oSqE1Y9rcxtU9iAcHGzHZqFbjE3TpMGlU9em\nx9SGFSDTplASRgj2cAmzpspObwu8RuP7lOximqCSkZFBXV1d2GRXW1uL0+lM3LvvCLGIJMYq/hiL\ngGQkO4qicFSxk9I8O59VdlDfoSdU5VlVhQmDMziiwM4nezvo1IywVZ5VAadN5cQhmRRmdJfQsVkU\nhuTbaHHrVLd4MU3CqjPYVCjJsXHhmFzynN3tDMi2ct0JhXyyt4P3y9t9w5Jh7BimSXOnTk2rN6we\nWm2bl79/3cqxA50cWWCPKJGjAP2yLBR3SQjgG/abNqqQSWU5/M8nNezY3xm2ylMPlnP98zLIdtq7\nfa6bsL7Gze5GjROHZJJpU8P6oxyMT2mencyIY7r+4yInPQXIsPqqMHuYsWqnVWVEoZ36Di/72iOL\n/ypAnsMn2hrO32yHysgiO3Vt0ZTTfdVcv0yV4qzuMVYUhaJMK7kOC1UtGh1RRFxVBUpyrOQ41IjX\nBPS+MGs8dlLdV4TbN9Fq7vuKZd68efN62mnPnj0899xzlJaWkp2djaIoNDQ0sHr1aubNm8ePfvQj\nTj/99G/B3cNLV7mecBdHLI3Ov1+04Yue7NgsCkfm28hxqNS1+caDEqnyMmwqI4rsKArUd+iHfMRX\nmRzTzxHoqKPhsKoUZFjQDBP3way5Z+Mahk84GbtF4bzRuZw5IhtnFDuKojAk3874AU6qWjU6NCOQ\n0EzTV83tafIcHI6LjGFCdauX2jYvA7MtWBQlUCn5E8LQAju5ju6dcGhsLPxwaC6D8xxsqmkHzIA/\nigI5DhuDCrNw2qLfM3Z6TXbWezAxfdUWQbIwQHGmhSF5duwxyQIpYf+tKjAox8LAHGvUYVxFUci0\nW8hzWnBpBnrQnYkCWFU4Is9GUZY1THV5CFVRyHFYyLKrtHuMEFkZX4xVjsy3k+uMrhhvURXynCpO\nq0Kbx+g2aJvrUDgy306GLXyi63puXf9OJCFEu8ZjtZPqviJZO5H4srw+4WPDMXpA5Mrq2yArK7JE\nV0zDmG1tbcyZM4dPP/00JLCmaXLyySfzyCOPkJNzeE/y26Zr2BJtcKmw4/YafFntoqLFm5APflrd\nOp9WuGh06RRkqEwpy+w2hBUL7R6DqhaN9575A9fcdDvTj87pMVl2xTRNNtS4WLm9DY9uUt/uZV97\nbENewagKHNPfweh+DqyqwqBsC/nO6EkuHG1unWe+qOPTPa2oikL/vEwyHbY4vYFsu8qJZRkUZlpx\nWhWfgrg10Rk6vooqx64wODf+Z5WmadLk0qk9+Ny1MMOnZB8tyYXDME32t3up7zBQFBiQZaEgI3qS\nC4dumFS3arS6TSwKlOTZyLYnFptUVT2psNOX+oqufJ+GMWNKdn62bNnC5s2baW1tpbCwkLFjx3L0\n0UenxMnvKqlQBU6VsvDftjXjSi7f+TrAToN8Z8930tHIdSj/v70zj4+iyvb4r3rNns4mWViEIFHT\niUbCgGwjeSIgMLwYRyMzQRCXgIA6PhUBNSB8FAEVg+OwC+KGGDYBDTPvKYsjyhKQMMqSoCFhCdlX\nujtd74+mm967qqs6qXTO9/PJJ+mqW78+dXJvnb63qs/BP9ctwbI3Xhdkz+7TDfjkRA2ahRXKRtbt\nYdB2C+AdEOx587tLaNCDd0Cw5+Xh0QhUCPOxSm5a3gtSeVeh3YzByKLNyAoIuiZ0BiNkMkawj1v1\nRqgUjGAfizWupKQjdhXyrhTsON2zW758OR577DFotVpotVrRDCPExXRxEPboMcMwiHByb84bW/jO\n5pyhlDM2S21CEHoRBkwPojQZ2jw39ECAwEAHmP5XQgMUYPKLGF9rUYpQPRwwfR2F7kERYsNppHz8\n8ce4cuWKr20hCIIgCJ/AKdg988wzWLJkiaV4K0EQBEF0JjgtYxYUFKCmpgZjxoxBQEAAgoODbfYz\nDIP9+/f7xECCIAiCEAqnYNevXz9f20EQBEEQPoNTsHvjjTdc7tPr9aioqBDNIIIgCIIQG8GPcp07\ndw5ZWVli2EIQBEEQPoHTzO7atWt49913ceDAAdTU1Njsq62tRUxMjKhGtbS0YPHixdi3bx/q6urQ\nt29fzJo1C0OGDHHanmVZfPzxx1i2bBlGjRqFN99802Z/UlISlEqlw+PMR44csUlsTRAEQfgnnILd\nu+++iy+//BJDhw5FYWEhMjIy0NTUhB9//BFjx45Fbm6uqEYtWLAAp06dwtq1axEfH4+tW7ciNzcX\n27dvR58+fWza6nQ6PP7442BZFrGxsS41165di4EDB4pqJ0EQRFeio780LgROy5jffPMNli1bhrff\nfhtKpRIvvPAC1q5diz179uDXX39FXV2daAbV1dVh586dmDlzJnr37g21Wo3s7GwkJibis88+c2jf\n2tqKoUOHYsOGDdBoNKLZ0RkJVsoE15gDALUY3zAGBJUhMqOQQZQvuYvw/XYAwE3BCtG0pEKbkb1e\nO48g/BdOw/bKlSuWJzLlcjl0Oh0AoHv37njxxRfdPsDCl+LiYuj1eqSkpNhsT01NxfHjxx3ah4WF\n4cknn4RM5v5UPvroI4wcORLp6el45JFHcPjwYUF2il1sUYwCr3/sHYyxt4QiOsi74KCUMeijUaFv\npAp9IlROM+dzIVDBoFuwErWtbSir06HNy0KmLMtieK9gvDsmDtkp4fAmWYiMAUb0DsKtMQHX/eud\nLabM+3LMz7gJfx8fj9tjXCecdYcmQIYn0yMEFzANVDDoGa6AjPG+/7HXK0icrtLhbLUelxv1MArQ\nMv8WazwIwR91xPJxV4XT5SM0NBSXL18GAERGRqKkpMSyr0ePHjh9Wrz8atXV1QDgMEuLiIhAVZV3\nGbqTk5ORnJyMrVu3Yu/evUhKSsLUqVNx4cIFr/ScZRz3pvOJrSNjGASpZPjjzcH4Q0Igr+AQHSjH\nLVEqBCpNtgQqGPSNVPEKnOZSLL0jVJaaY/XXWJyu0qGulV9laXNbuYyBSiHDf98aivyxcbglivs9\n1oRQBZ65OwrDegVDLrNOQcXPx6EqU0mbsAA55DJTaZpX7onBzIGRCFJy+0AgY4BhPYMwa1A0EsKU\ndrZwt0fGAPGhctwcoYRKLvO63+jbWJyv1aO83mCpS1fVbMTZKh2aPRcUtMFX48Gbi7qzkjhCdMQ4\nJ7F0AOE+7spwumc3bNgwvPDCC9i4cSMGDBiAt956CyEhIdBoNFi3bh2ioqJ8bScA77N8FxQU2Lye\nN28eCgsLsX37djz99NOcdVxlQOdSv8qXOvbtFDIGPcOViA9V4MfyFlQ0uM4Obc68r5TbJt5lGOZ6\nEVAFIgLkKKvXo9VNWfNQlQwJYUrIGUd7jCxQXm9AjYvim87Oyf68VAoZuoXIsCDjJnxX2oQPi2pd\n2qOUAaP6huKueFPAt7XHnD/UczFUhQyID1WYloft1ofVChmG9gpGekIgVhyqxk/lLS51YkMUeEgb\nDk2AzO7c7QOe+/93iEqGhDAFZIDD/wrgViONZVmX9exYAHojcL5Gj/AAGWJDnNezs9ayt8H8txj9\n2FPtRy46XGrd8dVxZqsrDV/q8PExwTHYvfDCC3j++edhNBrx1FNPYd++fXjssccAmJY1Fy1aJJpB\n5sBZW1uLbt26WbbX1NQgOjpalPdQKBSIj4+3zFa54KlTcR1UYuhwKTsilzGQyxjc3SMIVxoN+LG8\nxaYAKQNTwdTIQLlNfTV7ZAwDlRzoE6G6XlnaYHORlDNAQpipFIu7LPUsgCY9izNVOnQLliHSSdFU\nLgNXrZBhxPVK5+/9UIVjF1tt9idGqvBgchgCFDI3iZ89B5mI6xd7xknwNqOUM1DK5fjb4CgUX7mG\nFYeqUNt6Y1akkAH3JobgDwlBToKuvT2uA7CcMQXdELV7H3u6ALYajLhQp4fOQ6VyFkBdqxEN13RO\nK5UD7dePuQQHrjrtUVDVGx1fXiuIG3AKdjExMdi4caPl9TfffINDhw5Br9dDq9UiPj5eNIO0Wi1U\nKhWKioowatQoy/ajR49ixIgRvPWKi4uxdetWzJkzx3JfT6fToaysDGPGjPF4vDdFG62P4/tJzlrH\n1ZIMHx2FjEFsqAJj+4Xi2MUWlNbqEayUoXuYEnIZt1I15lleZKAc4Wo5LtTr0aQ3QhMgR1yI6b4R\nV3tYAJebjKhp1aFHuKmWG18fK+UyhMuBF4dGo+hiK/7+YzUMRhZ/ujUMSdFqtzNHuzODfZBRyRl0\nD1NALWccZnOuUCtkuCM2AO+Pi8f6ozX4Z0kTbtYo8WdtOIIUDBSc7HEegMMDGMSFKDn72NkF0Lre\nnPOq4o6wMD1gVFZnQLCqDQnX6+V1VD8WQ8dVcBAyxsXScfeaiw7N8jzjMthNmjQJK1asQFhYmMO+\noKAgp4Gnrq4OM2fOtAmMfAkNDUVWVhby8/PRr18/xMbG4pNPPkF5eTmys7Nx4sQJvPjii1i3bh2n\nIBsVFYWCggIoFArMmDEDbW1tWLZsGQAgMzPT7bFCOo+zew58dVzdc+CrI2MYyOTAXfGBiA6So0nP\nelUrzKzTS6NEm5GFXOZdzTEWwLU2Fr/V6pEYqeIVLK1RK2TonxCId+6PxW+1BsgZuF12c86NIKMJ\nYBAXqnQ703WFXMYgUMZgav8I3NM7BLo2lkfQdW7PzRolAhWOS6icVK73P32bEaU1ehiM5pDOT4sF\n0KhjUVanx80apUWbry2A8H7sTMfbsWnW8dYW8zFCz0ksHZrlecblIww//fQTDAZ+lUD1ej1++ukn\nwUbNmTMHgwYNwsSJEzFw4EAUFhZizZo1SEhIQEtLC0pLS6HXm6p5btu2DSkpKUhJScGxY8ewfft2\ny+vy8nLExsZi3bp1OHXqFDIyMnDPPfegoqICn3zyCSIjI93awbLCPiWZbyZb31T2Vsdaz1sUMgbX\n2oQXHpUxDJReBrob3KjFJvScDEZTIVP+gc7WHk2AHDKBPlYrZGAYeBnobiBnGAQ6uVfIB4Zh0GqA\nVaDzHnNtQin0Y2sdIYihY30uUtEhnOOyUvmtt96KuLg4j4/0W2M0GnHp0iX85z//Ec3AjsRoZAVd\nbMRErE9r/6m8Bi+/CWCH5+Ww95e8jqdfeMXl/hCVDN3D3D8EwYUrTQZUNgkvqHqzRoFggVW/AXF8\nLGeAftEqwR9MGq6Z7tMJrX8bHSTHTcFywX1QrH5MOq7hc93iW6lc6l8q96pS+YwZM3xiDEEQBEG0\nNxTsCIIgCL/HzxIfEQRBEIQjFOwIgiAIv4fT9+wIgiAI/0bqD58IhWZ2BEEQhN9DwY4gCILwewQH\nu6NHj+LAgQNi2EIQBEEQPkHwPbu5c+fi/PnzfvNFcoIgCML/EBzsFi9ejNbWVs8NOyEMIzyjgRjJ\nWc0aYtiikgPXDMLTR/HNsegMQxsrio9Vshspnb2HRauBRaDSu7yhFhWWhUrOoNVghBAfsez1Hwjz\njULGXvcLtwTQrhCjkrmY/difdYRgskGwjF/ichnz2LFjlork7vJkpqam4g9/+INvrOtgnCWM5Yp9\n0Ub7RK98dOxtEaLTO0KFyECZl5WyWTAAogJluCVKiRAV4/XlkwGgsdghzMeaQAV6apRQMN5ezk3v\nfamxDRcbDGgzeudjI8uiQWeEzlJnz7qiAndbGAARgTLLRUuIbwIUMiRGKhGg8O5/xcCUukwTIJdU\nPxai4656QkfqiH2tIGxxGewmTZqEyspKy9/19fXtZpSU4DuoXGVkF0PHOlks18FgP5BkDIPYUCX6\nRCqhknO/ADIAVHIGfSKUiA01VcnupVGhR7jCVLCVh06wksEtUSpEXa9pJ4ZvQlQy3BKtQkQAn0Du\nWEOuttWIs9U6NOqMMHJMcGlkWRiMLMrqDCirM1zPQ8kANmV7PGP2ce/rPjYnpeZ7AbT2DcOYEm73\niVChW7CMR8AzBV1NgAz9olUIUdsmgu7ofixEx/5YMXxs/tvaVr46ZsS65hC2uFzGjIqKQm5uLvr1\n6weWZfHqq69CrVa7FDKXzfFHuJbP8NThfKHjrp27/QEKGfpGqlxWrbZ5PwAxwTJEOym4GqqW45Yo\nGS41GlDX6l5HxgAJoQqEBTgmWxbDNzKGQVyYEppAIy7U66F3W6TUeaFUwFQl4Pc6A0JVMsSHmer1\nuVraNLIs6lrbcKmxzUXyZ/MCq+v3MwUWBjFBMkQHO/oYsC0D441vGIZBVLASYQEsyuv1aNazLn3D\nwFRNonu40lLtwF7L/H4d3Y/N2z1d8LmUz+Gj055jXIgOcQOXwe61115Dfn4+ioqKwDAMTp486bIC\nQldxtKvByWUg2eu4WwLh6k9XF0CuOgzDIPr6BfBCnR6tBtsLIAMgQGG66KnclKyRyxgkhCkREWjK\nsG9fUoYBEKY21YrzVOFADB8HKk2BvLLJgKsOBUvtLXNNg86IM1U6xIbIEX69/I8Z02wOuFCvR4ve\n06dv6/e2vXdm8rHMo48B9/2E6/9cKWfQS6NE/TUjKhoMdgHaFHSjgmS4yUXQtbfH01Ie3/HgzTnZ\nv7fUdJy95qMjho8JN8FuxIgRlgKtt956K7788ktERUW1m2FSxtmSB98O52qpQoiOs+1cMC+d1ba0\n4VJTG1jW9HBOt2A5IgK5l3UJUsrQN0plqYptmiEA3cOUCFbx+5aLUB8zDIObQpQID2BxoV6PawYW\nrNvZlXOMLFDR0IbaVqOpuvv11cmq5jZUNrXxvCNnPctjIPPCx4A4vgkPkCNEJUNFgx4N10w6agWD\n7mFKS51BrlqANPqxub2z5T8xdLwJKlK6VnR1XAa7+fPn47nnnkNYWBgyMzPdLmF2Raw7oJBOZx4M\nQjuuUB2GYRARpEBogBy1LW3QBMqh8KLOnIxh0C1ECU2A0XJvztunG8XwsVphus9YWq1DS5v3Pm7W\nszhTpYMmUIZmHYtrXj+daLLhpmAZIgIVXvkYEMc3chmDHuEqNOmM0BmM0PAMuvb2SKEfmzUAccam\n1HTE8HFXxeVHuIKCAssTmdu2bUNjYyN0Op3LH8I/UMgYRAV5F+isUStkpkrbEhiYDMNAxWO24goW\nQE1Lm4BAd4PoIO8DndgEq2SCAh1BdAZczuxSU1ORm5sLwPSJxLyk6QyGYXDq1CnxrSMIgiAIEXAZ\n7PLz87Fz507U1dVhxYoVmDx5MoKDg9vTNoIgCKId8PeKB4CbYKfRaJCTkwMAOHToEKZNm4awsLB2\nM4wgCIIgxIJTurCPPvrI13YQBEEQhM9wGeyGDh2KnTt3IiIiAkOHDnUrwjAM9u/fL7pxBEEQBCEG\nLoPdsGHDoFQqAZgCHz2pRRAEQXRWXAa7N954w/L3m2++2S7GEARBEIQvcBnsSktLeQn17t1bsDEE\nQRAE4QtcBrsxY8bwWrqk4q0EQRCEVOG0jNnS0oKVK1firrvuwp133ong4GA0NDTgyJEjOHXqFP72\nt7+1i7FSg2sZD65aQu6Lmm3xVx2hxIYqEBnIorxBD12bUDXbZM58iQ4yZXPxNx+LYYtYOv7aj8Ww\npaviMthlZmZa/n7llVcwadIkTJ061abNlClTsGrVKnz//fcYN26c76yUGPbJWL0ts2F9nJCaVM50\nvBkMvtAxv/b2nKztsdbkq6OQMZArgUSragj8sE4i7Vi9gAsBCgbdwxRQyhhJ/K+oH/teR2wfO7ON\n4AanhIGFhYW49957ne4bNWoU/vnPf4pqVEtLC/Ly8pCRkYH+/fvj4YcfxsGDB122Z1kWmzZtQlpa\nGmbPnu2wv7q6Gs8//zyGDx+OAQMGYNKkSTh58qRXtll3MnNHc5WxnauOvR5XHWcXFrOOs8zvfHXs\n93HVceUbPjrW52KvwxVn5yRjGMQEKdD3evVuDipwrEV3vfQBx0rkDIDYEDl6R5jK+Mhkwv9XUvax\n1PqxP/nY+oevTleHU7DT6/U4c+aM031nz56FXq8X1agFCxbg2LFjWLt2Lb7//ntkZmYiNzcXJSUl\nDm11Oh0effRRfPPNN4iNjXWq9+yzz6K6uhqbN2/Gt99+i7vuugtTp05FTU0NZ5s8fWLlOqicDSR7\nHfv3c6Vj/b6+0OE6qLj6RiwdoT6WyRhLWaNuIXI38zPrIOesFWPVzrk95soPEdfr4Xn6X3k6J+v2\n9hpS8rGU+rG9jjsNf/QxYYJTsBsxYgRefvllvPfeeygsLMS+fftQWFiIZcuWYc6cORg2bJhoBtXV\n1WHnzp2YOXMmevfuDbVajezsbCQmJuKzzz5zaN/a2oqhQ4diw4YN0Gg0DvtPnz6NQ4cO4cUXX0Rs\nbCyCg4MxY8YMMAyDHTt2cLLJ00CyxlUH5LO8425Qia3D9ZxcDU4xfCOWDl/fyBgGkQFy3BKlQpDS\nur2z2ZxLJcBJYVg5A3QPk6OnRgml1WzOnT3+6GPqx/x1xPINYQundGHz589HXl4eVq9ebTOLk8vl\nGDFiBObPny+aQcXFxdDr9UhJSbHZnpqaiuPHjzu0DwsLw5NPPulS7/jx41Aqlbj11lst2xQKBZKT\nk53qWcO1w9njqhML0XG2nY+Os4HZETq+8I0QHZmMgQxAL40SV5sMqGw2P73C917IjWXNUJUMCWFK\nMAx4lzjyRx9TP25fHW+O7wpwCnYhISFYunQpFi5ciPPnz6OxsRFBQUHo2bMnQkJCRDWouroaABxm\naREREaiqqvJKLzw83OGfr9FocPXqVY/HC+k05kEllo5QDUD4k1xS1BHDxzKGQZOe/0MndtYAAOLD\nlJALqFXnrz6mfuxeR0wfE45wCnZmAgICbGZI7Y3Yn1Y86bEsIPQt6ROW7xFtgNM1wiV0EfU9YvlY\njOuWPyK8fLPIREVFAQBqa2ttttfU1CA6Otorvbq6OodOVFtb65UeQRAE0fmQXLDTarVQqVQoKiqy\n2X706FGkp6fz1ktLS4Ner0dxcbFlm06nw88//+yVHkEQBNH5kFywCw0NRVZWFvLz81FaWoqWlhas\nXbsW5eXlyM7OxokTJzB69GhUVFRw0ktMTMTw4cOxePFiXL58GY2NjVi6dCnUanWX+iI8QRBEV0Zy\nwQ4A5syZg0GDBmHixIkYOHAgCgsLsWbNGiQkJKClpQWlpaWWp0K3bduGlJQUpKSk4NixY9i+fbvl\ndXl5OQBg2bJliIuLw7hx4zB06FCcOXMG69evF/3hGoIgCEKaMCyHO6Isy2LlypVobW3Fs88+a9k+\na9Ys3H777cjNzfWpkR2F0ch6/H5UeyH0aa+O0MnLy0NeXp5k7PFEabUOzQbhDwgkRaugEKHfSMk3\nYulIyRZ/1eFz3Vr5r9MAgAdS4wS9p1SIiQl1uY/TzG7lypX44IMPLA+PmElLS8Pq1auxatUqYRYS\nBEEQhA/hFOwKCgqwePFi5OTk2GyfMmUK3nzzTWzZssUnxhEEQRCEGHAKdpcuXUJycrLTfcnJybh0\n6ZKoRhEEQRCEmHAKdr169cK+ffuc7tu1axe6d+8uqlEEQRAEISacMqhMmTIFr7zyCg4dOgStVovg\n4GDU19fjyJEjOHjwIBYsWOBrOzsEMbIQiJmrTio3wcXKpCE1HZlIzyazLPnYkxb1Y9/pEM7hFOwe\neOAByOVyrFmzBoWFhQAAmUyGpKQkLFmyxK+/r+ZtsHKXDV2ojjcD3Pr9rTPFC9Ux/+2tjr2mtxpi\n6MSHKnCxwYBGHetV5jAGgIwBdG0sFDLv80D6s4+tX1M/dtQQomO8ftylJgPiQ5W8ju0KcM6NJ1mp\nkgAAIABJREFUOWHCBEyYMAHXrl1DfX09IiIioFDwSq3Z6bDPSM6187nqrGLqONvuTsO6vX3W947Q\n8aVvvNVRyhn01KjQcM2I8no9jCzXdJksGDDQBMgQG6qwVDogH3vWcbbdnYZ1e+rHNzAaWTQbjCiv\nN8BgBOJdP4HfZeG1cNPY2Iji4mIcPXoUOp0OANDW1ubhqM4Pw/Artmg+xpmOfTt3Oub3dafjDmtb\n7HWst3WEjj1S8nGoWoZbolTQBMg4VbNTyhjcHKFEfJjSpqQP+dj3BV67uo+NLIs2I4vyBgN+qzUF\nOsI5nKZmbW1tWLp0KTZt2gS9Xg+GYVBYWIi6ujo89thj+PDDD9GtWzdf29rhuFs64fqp0NNs0Rsd\n+/bOPr22h46rAcznE7NUfCyXMYgPU0ITaMSFOj0MRvtZnmk2FxUkw03BCrda5GPvdKgfu/exkWVR\n39qGS41taKPbfR7hNLN7//338cUXX2D69On49NNPERAQAMCUxzImJgbvvvuuT42UEvaf3Pguf1jr\nAHDQcfUpmI+OtZ3e6Fj/5qNj/+lYiG+k4uMgpQx9o1SICroxy2MABCgYJEYq0S1Eycs/Znusf3d1\nH7vSsbbTGx3r3/7kY6ORhb6Nxe+1epQ3UKDjCqeZ3bZt25CXl+fwIEpISAiee+45TJs2zSfGSRlz\nJzb/7a0G4P0NaV/qeKth1hFqi1g6YvhGxjDoFqKEJsCIiw0GhKoYRAa5n81xsaejfSOWDvVj3+uY\nj2vWt6FZz+JKYxuVX+QJp2BXVVWFO+64w+m+mJgYNDY2impUZ8G6E4uhJSUdoYh5PlLxsVohQy8N\n95mcrxHLN1Lysdg6QpGaj2tajKhtpRtz3sBpGTMhIQGHDx92uq+oqAixsbGiGkUQBEEQYsJpZjdy\n5EgsWLAAFRUVGDx4MADg9OnT2LdvH/Lz8/HXv/7Vp0YSBEEQhBA4BbsZM2bg6tWreP/997FixQqw\nLIunn34acrkcWVlZmD59uq/tJAiCIAiv4RTslEolFi1ahGeeeQYnT55EY2MjwsPDodVqHcr+EARB\nEITU4JwCxWg0QqFQoH///ggPD/elTQRBEAQhKh6D3b///W+sXr0ahw8fhl6vB2D6ysHQoUPx+OOP\nuyz9QxAEQRBSwW2wW7NmDZYuXYrExERMmjQJcXFxMBgMOH/+PP73f/8XDz/8MObMmYOJEye2l70E\nQRAEwRuXwe748eN4++23MXv2bEyePNlh/7x58/Dee+9h0aJFSE5Odvk9PIIgCILoaFx+z+7jjz/G\nmDFjnAY6AJDL5XjuuecwZswYrFmzxlf2EQRBEIRgXAa7w4cPIysry6NAdnY2jh49KqpRnQWxsk6I\nqSWmTVKAfOx7yMe+R6zzCVfLEBPkuRoHVx5IjcMDqXEiqUkbl8uYlZWVuPnmmz0K9OjRAzU1NWLa\n1Cmw7rxCcvCJoWM/kMTQEZLLz1c65GPf65CPfa8jxMfBKhmClDJoAllcqDOgxeBfHwp8ictgp9fr\noVarPQrI5XK/+xTmDlflQvgOBlclRKSow1fDrGOf9d1bHXc2ctHxZx/7Qsd+Gxcd+/bkY9/5mGEA\nFRjcHKFEbUsbLje1wdh1LsFe4zLY8S2t0RVw10mtL+qu2lhrOGtjX8rDnf/F1nF1Tp7acNXheuEi\nH3d+H9vrkI+90/HkYxnDQBMgR1iAHOX1BjTqKEG0O1wGO5ZlMX78eI8BryvM6rh+EvM0OL3Rcdae\nj46rQeVpIImt4wvfkI8dNcztyce+0ZGaj2UyBjIAPcIVaLxmREWDgerbucBlsMvMzGxPOyQL3yUH\nc1vrQWW/zxsd89/eaACQpI75tVR8LEQDIB/z1elo3/iTj2UMg1C1DLeoVLjYqOd8XFfCZbB74403\n2tMOSeJp6cQdfJZOOpsOl2Wl9tCRom/E0iEf+16H65IkVx0pnJOcAeJDlF4d7+9wqmfXVRFjhZZh\nxLv3KRUdqdghto6YWuRj32uJ5WN/+18RzuGcCLo9aWlpweLFi7Fv3z7U1dWhb9++mDVrFoYMGeK0\n/cGDB5Gfn4+zZ88iNDQUw4YNw8svv4zAwEAAQFJSEpRKxwrTR44cgUql8vn5EARBEB2LJGd2CxYs\nwLFjx7B27Vp8//33yMzMRG5uLkpKShzanj9/Hrm5uRg7diz279+PjRs34uTJk1iwYIFNu7Vr1+Ln\nn3+2+aFARxAE0TWQXLCrq6vDzp07MXPmTPTu3RtqtRrZ2dlITEzEZ5995tD+888/R58+fZCTk4PA\nwED06NED06dPx44dO1BdXd0BZ0AQBEFIDckFu+LiYuj1eqSkpNhsT01NxfHjxx3aFxUVITU11aGt\nwWBAcXGxZdtHH32EkSNHIj09HY888ggOHz7smxMgCIIgJIfkgp15NqbRaGy2R0REoKqqyml7+2Ky\nERERAGBpn5ycjOTkZGzduhV79+5FUlISpk6digsXLvjiFAiCIAiJIblg5w6+TyuZ2xcUFGDatGkI\nCQlBREQE5s2bh+DgYGzfvt0XZhIEQRASQ3LBLioqCgBQW1trs72mpgbR0dEO7aOjo522BYCYmBin\n76FQKBAfH4/Lly+LYTJBEAQhcSQX7LRaLVQqFYqKimy2Hz16FOnp6Q7t09LSHO7lmb9SkJKSguLi\nYixcuBBG4428cTqdDmVlZejVq5dvToIgCIKQFJILdqGhocjKykJ+fj5KS0vR0tKCtWvXory8HNnZ\n2Thx4gRGjx6NiooKAKZ6emVlZfjwww/R2tqKkpIS5Ofn489//jNCQ0MRFRWFgoICvPXWW2hsbERd\nXR0WLlwIgFKiEQRBdBUkF+wAYM6cORg0aBAmTpyIgQMHorCwEGvWrEFCQgJaWlpQWloKvd6U/617\n9+5YvXo1du3ahQEDBiAnJwfDhg3D7NmzAQCxsbFYt24dTp06hYyMDNxzzz2oqKjAJ598gsjISLd2\niJHQwFXeO0I8yL++h3zse8TyMSVicQ7DUi92idBcdUIS34qtIzTRrDc6eXl5yMvL46RDPva9DvnY\n9zpS8THX4ysrG7x6H6kSExPqcp8k04VJBW8TtDorF+JN0llXpUjE1OEzqMTQcVVKhXwsng75uGN1\n7Ldx0bA+RizfELZQsOMAn8zmrjqds9IivtZxddGz13G2n4st5m1cBydXHfKxLeTjzuljb3XE8jFh\nCwU7jngaVFw7nKfB0JE6ztpy0fE0ON1drFzpOGsrtg75mHxsr2FuK5aP2+N/RUGOGxTseOJscPLt\ndM4GA9cB4Gsd82tvBpK9b+w1vdURwx5/9bGUdMjHvtfx1jcEBTuv4LvMwEXH+rU3OlyXTnytY+8b\nsXTIx7YaAPnYlzr+6uOujCS/etBZELPDCdUyH++vOmIgtXOSmo4YSO2cpKYjBhTovIOCHUEQBOH3\nULAjCIIg/B4KdgRBEITfQ8GOIAiC8Hso2BEEQRB+DwU7giAIwu+hYEcQBEH4PRTsCIIgCL+Hgh1B\nEATh91CwIxygDA0EQfgbFOy8xDpnnnViVm907PU6WkcsDWu7OlrHXk8qOkI0pKZjrycVHSEaUtOx\n1yO4Q4mgvcA+Gas3yWKdZS73Jlms2DrWx3iTdNb6GCHJa8nH3HW8TVZMPm5/nY70cVeHgh0PXHVS\nvh2Qi46z/Xx0uA4qZwNJTB1f+IZ8TD52pdFeOp3NxwQFO064GwDWeBpUYut40jC3dTWoOkrHWVvy\nMfnYlYa5LfmYvw5xAwp2HuDbiVwNKinomF9zHUj2OvaDypsBJoYO+dj3OuRj3+v42seELRTs3CDk\n05JYywxifXITQ8d+UElJx1sN83HkY8869tv46pCPPevYb+OrQwHPNfQ0phtYVviyAMMwomhY/yYd\n5zpSsoV0pG2Lv+qYAp4gM/wWCnYEQRCE30PBjiAIgvB7KNgRBEEQfg8FO4IgCMLvoWBHEARB+D2S\nDHYtLS3Iy8tDRkYG+vfvj4cffhgHDx502f7gwYPIzs5Geno6RowYgVdffRUtLS2W/dXV1Xj++ecx\nfPhwDBgwAJMmTcLJkyfb41QIgiAICSDJYLdgwQIcO3YMa9euxffff4/MzEzk5uaipKTEoe358+eR\nm5uLsWPHYv/+/di4cSNOnjyJBQsWWNo8++yzqK6uxubNm/Htt9/irrvuwtSpU1FTU9Oep0UQBEF0\nEJILdnV1ddi5cydmzpyJ3r17Q61WIzs7G4mJifjss88c2n/++efo06cPcnJyEBgYiB49emD69OnY\nsWMHqqurcfr0aRw6dAgvvvgiYmNjERwcjBkzZoBhGOzYsaMDzpAgCIJobySXQaW4uBh6vR4pKSk2\n21NTU3H8+HGH9kVFRUhNTXVoazAYUFxcjEuXLkGpVOLWW2+17FcoFEhOTnaqRxAEQfgfkgt21dXV\nAACNRmOzPSIiAlVVVU7bh4eHO7QFgKqqKst++6wEGo0GV69edWvLtm3bcOKENAKiWCmA2lPn22+/\nRV5enmTsaQ8N0uk8tvirDsuymD9/vmBb/A3JBTt38O0Entp72p+Z+d/IzPxvrzsfa5e3R0o6QgYU\nV528vDyXwU7KvhFLpz18zFXDX3XIx+51iBtI7p5dVFQUAKC2ttZme01NDaKjox3aR0dHO20LADEx\nMYiKikJdXZ1DJ6itrXWqZ42zRK9csU4M6yzRK1cNX+l4e07mT56+8A352D99LJYO+Zi7DuGI5IKd\nVquFSqVCUVGRzfajR48iPT3doX1aWprDvbcjR45ApVIhJSUFaWlp0Ov1KC4utuzX6XT4+eefnerZ\nw7cDOhtI1jpcB4OzAWB+bf0+YuhwwdlA8tY3YumQj51rSM3HrnTs7fWkY38e9jpc6Eo+JmyRXLAL\nDQ1FVlYW8vPzUVpaipaWFqxduxbl5eXIzs7GiRMnMHr0aFRUVAAAsrOzUVZWhg8//BCtra0oKSlB\nfn4+/vznPyM0NBSJiYkYPnw4Fi9ejMuXL6OxsRFLly6FWq3GuHHjONvFZXBy+WTlaTC4Gkj2GmLq\neDonTwOJq4697c507G13p+MK8jH52JVOV/MxcQPJBTsAmDNnDgYNGoSJEydi4MCBKCwsxJo1a5CQ\nkICWlhaUlpZCr9cDALp3747Vq1dj165dGDBgAHJycjBs2DDMnj3bords2TLExcVh3LhxGDp0KM6c\nOYP169cjJCSEl12uBiffT1auBhWXgWSvY/3+Yup4M5Dc+YarDvmYu461LeRj8jHhHoblOv8nbLB3\nm7cdzhc6Qjq/mDrmB1Sk5BuxdKTiY6E65GPf60jNx9ZUVjYI1pASMTGhLvdJcmbXGbD+RCWk01lr\niKUjBLMdYugItceffSwVHfKx73Wk5uOuCgU7wgGa7BME4W9QsCMIgiD8Hgp2BEEQhN9DwY4gCILw\neyjYEQRBEH4PBTuCIAjC76FgRxAEQfg9FOwIgiAIv4eCHUEQBOH3ULAjHKDsDARB+BsU7ARgnWy2\nIzXE1nGXrb0j7BGqIyVb/FVHSrb4q45YtnRVOlWlcqlgn/3cOpO5UB3r197oeFv2wz7hrVg65m1i\n+IZ87F7Hn3zsrQ75mHAFBTseuMqAzndQia1jr2Hex3VQtZeO/T53Gs50yMddx8f2OuRjYToEBTvO\neOpUXAeVGDquBoArHVftuOp4GlRcBpwYOuRj8jH5mL8OYYKCnQe4DCRrXA1Ovp/AXA0qITrWx/DR\ncTeoxNDxJx97q0M+9r1OV/MxYQsFOzcI6Tz2HdAbHftBJYaOtxpi6wg9J7F0fOFjof3GrOOtLeZj\nuoKPhep4q2E+Rqo+poDnCD2N6QEhnYZhGJsfoTaIqSMEMXSsz0UqOvZ6QnWEIDXfSNXHHf2/kqqP\nCUco2LnB6oMWQRBEp4CuW86hYEcQBEH4PRTsCIIgCL+Hgh1BEATh91CwIwiCIPweCnYEQRCE30PB\njiAIgvB7KNgRBEEQfg8FO4IgiC5KwYmLKDhxsaPNaBco2BEEQRB+j+RyY5aVlWHRokU4ceIEWJbF\nHXfcgblz56JHjx4uj9mwYQM2b96MiooKxMXF4aGHHsLkyZMBAIcOHcKkSZOgUqlsjrnjjjuwadMm\nt7YwjHe12KwRIzmrWUMsW/xVRwhSPSep6QhBquckNR0hsCwLUMYwp0gq2On1ejzxxBNITU3FV199\nBYVCgTfeeAOPP/44vvrqKyiVSodjtm3bhuXLl+Pvf/877rrrLpw4cQJPPfUUwsPDkZmZaWn3888/\n87bHOkEr304sNJO5Mx0hSYbF0LFPVCvUN2Lp+JOPXemQj32v09l9bDSy0BtZXKg3IDFS5fmALoak\nljEPHDiA3377DS+//DIiIyMRFhaGl156CWVlZfjuu++cHrNx40ZkZWVh0KBBUKlUSE9PR1ZWFjZs\n2CCKTa4yrbvDWWd1lmndk4a9jnWyWL469olmvdGxP9b8t7e+sU98Sz52rUM+7po+5qLDsiyMLIvK\nZgPOVuvRaqDkmM6QVLArKipCz549ERERYdmm0WjQo0cPHD9+3KG9TqfDL7/8gtTUVJvtqamp+PXX\nX9HS0mLZ9tJLL2HYsGEYPHgwZs2ahYsXud+U5TqonA0kZzqeOrGzgWSvY/1+XHScwUWHy6dnPr5x\npSNFH/PVcQb5mHzsTseTbzzpGI0sWg0szlXrcbXZ6LId0c7BzmAwoL6+3uVPTU0NwsPDHY6LiIhA\nVVWVw/ba2lq0tbU5HBMREQGj0Yja2loEBwcjNTUVGRkZ+Ne//oVPP/0UlZWVePLJJ2EwGHjZ72pQ\n8V1OEUPH3WDwNJD46Ni38aTj7ILDV8f6HOzPybpNe+tYQz4mH3M9J1/5uM3I4mKjASU1eujaaDbn\niXa9Z/fjjz9iypQpLvc//PDDLvdx6RjOjtFqtfjiiy8s23r16oXXXnsNEyZMQFFREdLT03lrAo6d\nj699vtBxtp2PjrMBLkTH+mLFVwMgH/PRkYJvyMeOGoD4PmZZoElvREWDAQaazHGmXYPd4MGD8euv\nv7rcv3z5ctTW1jpsr6mpQXR0tMN2jUYDhULhcExNTQ0UCoXNcqg1vXr1AgBcvnyZj/k2WHdAbwKx\ntY5QDbF0hNrgTEcMe/zRx/6oQz72vU5NiwEN11g06CjK8UVS9+zS0tJQVlZms2R59epV/P77705n\nYCqVCsnJyQ73844cOQKtVgu1Wo3du3fjww8/tNl/7tw5AEDPnj3FPwk/wN09AoIgOo5mPQU6b5FU\nsBsyZAj69u2LRYsWoaamBtXV1Vi4cCH69euHwYMHAwA2bdqEnJwcyzGTJ09GQUEB/v3vf0On0+Hg\nwYPYunWrZblUpVJhyZIl2LVrF/R6PX7//Xe8/vrr+MMf/oCUlJQOOU+CIAiifZHU9+zkcjlWrVqF\nBQsWICMjAwzDYPDgwVi1ahXkcjkA0xLlb7/9Zjnm/vvvR319PV555RVcunQJ8fHxmDt3LkaPHg0A\nuPfee7Fo0SKsXLkSc+fOhVqtxqhRo/A///M/HXKOBEEQRPvDsLRmJQgx7lOIoSFFnddeew3z58+X\nhD1S840/6kjJFn/VKa/Xo7bV8zJm8k1qTnor/3UaAPBAapwgu6RCTEyoy32SWsYkCIIgCF9AMzuC\nIAjC76GZHUEQBOH3ULAjCIIg/B4KdgRBEITfQ8GOIAiC8Hso2BEEQRB+DwU7giAIwu+hYEcQBEH4\nPRTsCK9oaWlBXl4eMjIy0L9/fzz88MM4ePCgy/YHDx5EdnY20tPTMWLECLz66qs2xXUJ9/D19549\ne5CZmYm0tDQMHz4cr7/+OvmbI3x9bc3UqVORlJTkYwsJr2AJwgtmz57N/ulPf2JLSkrY1tZW9tNP\nP2W1Wi177tw5h7alpaWsVqtlN27cyDY3N7O///47m5mZyc6ePbsDLO+c8PH3d999xyYnJ7N79uxh\n9Xo9e/r0aXb48OHsokWLOsDyzgcfX1uzefNmtn///my/fv3ayVKCDzSzI3hTV1eHnTt3YubMmejd\nuzfUajWys7ORmJiIzz77zKH9559/jj59+iAnJweBgYHo0aMHpk+fjh07dqC6uroDzqBzwdffdXV1\nmDFjBkaPHg2FQoFbbrkF9913H3744YcOsL5zwdfXZi5evIglS5YgNze3Ha0l+CCpqgdE56C4uBh6\nvd6hRFJqaqpDbUEAKCoqQmpqqkNbg8GA4uJiDBs2zKf2dnb4+nv8+PEO28rKyhAX5x/Jfn0JX1+b\nmTdvHh588EEqGyZhaGZH8MY8G9NoNDbbIyIibArvWrcPDw93aAvAaXvCFr7+tmfr1q04cOAAnn76\naZ/Y50944+vNmzejoqICzzzzjM/tI7yHZnaEqPAtYSJG6ZSujCf/rVmzBu+//z7effddh9k1wQ9n\nvq6oqMCSJUuwatUqqNXcyuoQHQPN7AjeREVFAQBqa2ttttfU1CA6OtqhfXR0tNO2ABATE+MjK/0H\nvv4GAKPRiLlz52LDhg3YsGED7r33Xp/b6Q/w9bV5+TItLa1d7CO8h4IdwRutVguVSoWioiKb7UeP\nHkV6erpD+7S0NIf7HUeOHIFKpaJ7HBzg628AePXVV3H8+HFs2bKFZnQ84OPr8vJyHDx4EFu2bMHA\ngQMxcOBATJ8+HQAwcOBA7Nq1q93sJjjQ0Y+DEp2T1157jR07dixbUlLCNjc3s2vWrGHvvPNO9sKF\nC+zx48fZUaNGseXl5SzLsmxZWRl7xx13sOvXr2dbWlrYc+fOsWPGjGHnz5/fwWfReeDj78LCQnbA\ngAHspUuXOtjqzglXXxsMBvbixYs2P7t372b79evHXrx4kW1ubu7oUyGsoHt2hFfMmTMHb731FiZO\nnIimpibcdtttWLNmDRISEnDhwgWUlpZCr9cDALp3747Vq1fjrbfewrJlyxAWFoZx48bh+eef7+Cz\n6Dzw8ffHH3+MhoYGp0uXX3/9NRISEtrb/E4FV1/L5XLExsbaHBsZGQkADtuJjocqlRMEQRB+D92z\nIwiCIPweCnYEQRCE30PBjiAIgvB7KNgRBEEQfg8FO4IgCMLvoWBHEARB+D0U7AjJMXv2bCQlJTn8\nDBgwAE8++aTb7PPvvPMOkpKSMHfuXEE25OTk4KGHHrK8TkpKwtKlSy2v/+///g/33HMPtFotjhw5\nAsCUOqp///64//77Ob9PRkaG5fwKCgoE2SwF8vPzLeeTk5PT0eYQhAUKdoQkiYyMxIEDByw/+/bt\nwwcffACDwYCcnBz88ssvDse0tbWhoKAAt912G/bs2SNqZe4DBw5g2rRpltfvvfcegoODsWfPHmi1\nWvzyyy/44osv8Je//AXr16/npf3YY4/hwIEDvIKkVDGfy5gxYzraFIKwgYIdIUlkMhliYmIsP926\ndUN6ejry8/OhVCqxadMmh2P279+Pq1ev4o033sC1a9fwzTffiGZPTEwMgoODLa/r6urQr18/9OjR\nA2q1GvX19QCA9PR0dOvWjZd2UFAQYmJiEBAQIJq9HUVwcLDfnAvhX1CwIzoVwcHB6NmzJy5evOiw\nb8uWLbj77rtx2223Yfjw4fjyyy85aR4+fBgTJkyAVqvFyJEjsW3bNoc25mXMCxcuICkpCeXl5di9\ne7dluc68ZPfEE08gIyND0Dl+9913yM7Oxp133om0tDQ88MAD2Lt3r4M9a9asweOPPw6tVovS0lIA\npkK5f/3rX3HnnXdi6NChmDt3rqXCBMuy+Mc//oFRo0YhNTUVgwYNwowZM1BWVmbR1el0eOeddzBm\nzBikpqZixIgRWL58OQwGg837FxQUYNy4cUhJScHIkSPxwQcfwGg0CjpvgvAlFOyITkVraysuXLjg\nkN+xqqoK3377LR544AEAQFZWFn766SebC7kzampqkJubi7CwMGzZsgXvvPMOvvrqK5w7d85p+7i4\nOBw4cACxsbH4r//6Lxw4cAAffPAB8vPzAQDLli3Dli1bvD6/3377DdOnT0e/fv2wbds2bN++HUOG\nDMEzzzyDU6dO2bT94osvMHjwYHzzzTdISEhASUkJJk+ejN69e+OLL77A8uXLcfjwYTz33HMATB8G\nVq5ciRdeeAFff/01Vq1ahfr6ejz11FMWzfnz5+PDDz/E1KlT8dVXX+G5557Dxo0bsWTJEkub7du3\nY968eXjooYcsbT744AP84x//8Pq8CcLXUCJootNw5coVLF68GC0tLXjkkUds9m3btg2BgYEYOXIk\nAOCPf/wjIiMjsXXrVsyaNcul5j//+U80NDRg4cKF6NWrFwDg7bffxuDBg522l8vliImJgVwuh1qt\nttTjM1diDwsLsyQD9obY2Fjs2LEDcXFxCAoKAgDMmDEDq1atwvfff4/bb7/d0jY8PByPPfaY5fWm\nTZsQGBiIvLw8yOVyAKZSPzt27EBjYyOKi4sRFxdnSRAdHx+Pd999FxUVFTAajaisrERBQQGmT5+O\nBx98EADQs2dPXLhwAX//+98xY8YMhIaGYvXq1cjIyMCkSZMAAL169UJlZaWlyjdBSBEKdoQkqaqq\nsimIaTQa0draCq1Wi5UrV+K2226zab9lyxaMGTPGUi1aqVTiT3/6E7Zt24aZM2e6rOh9+vRpBAUF\nWQIdYApYiYmJPjgrz6jVapw9exYLFizAuXPn0NTUZNlnX1A0OTnZ5vXPP/+M22+/3RLoAGDIkCEY\nMmQIAGDEiBHYvHkzJk+ejAkTJmDQoEGIi4uzBOeTJ0/CaDQ6BPq7774by5cvx6+//gqtVoszZ85g\n/PjxNm0effRR4SdPED6Egh0hSTQaDT7//HPL62PHjuGll17CtGnTLBdvM0ePHkVJSQlKSkpsjjHz\nww8/4O6773b6Pk1NTU4fpggODna4T9Ue7N27F7NmzcL999+PmTNnIjo6GgzD4L777nNqozX19fWI\ni4tzqf3HP/4RGzduxMaNG7Fo0SI0NDTgjjvuwEsvvYT+/fujsbERgOmJSpnsxh0Oc2Hjb+hcAAAD\nvklEQVSUyspKy4M49u9NEFKHgh0hSeRyuc1sq1evXvj6668xf/58DBw4EKGhoZZ9W7ZsQd++fW2+\nB2dm7ty5+PLLL10Gu6CgILS2tjpsb2hoQGBgoAhnwo8dO3YgNjYWy5YtswScK1eucDo2KioKdXV1\nbtukp6cjPT0dBoMBR44cwYoVK/DEE0/g22+/tSzFLl26FP369XOqr1arIZPJPL4PQUgNekCF6DTM\nmzcPDQ0NNg9LNDU1Yc+ePRg7dixuu+02h5/x48dj7969llmLPb1790Zzc7PNAyk1NTUoKSnx+fk4\nQ6/XIywszGZmtXXrVgA3Zliu0Gq1OHnyJHQ6nWXbDz/8gEceeQRXrlzB/v37cebMGQCAQqHAwIED\n8fLLL6OpqQmlpaXQarWQy+W4fPkyevXqZfmJioqCUqlESEgIlEolkpKScPToUZv3Xr9+vdt7owTR\n0VCwIzoN3bt3x/Tp07F582b89NNPAIDdu3ejubkZY8eOdXrMmDFjcO3aNezatcvp/pEjRyIgIAAL\nFy7EL7/8gpMnT+Jvf/uboIdMzCxbtgwTJ07kdcydd96Js2fPYvfu3SgrK8Pq1atx/PhxxMXF4Zdf\nfnE7y8vJyYFer8dLL72E8+fP49ixY1i0aBFUKhVuuukmFBQUYMaMGThw4AAqKipw+vRprF+/HtHR\n0UhMTER0dDQefPBB5OfnY+fOnSgrK8OxY8cwbdo0TJkyxVIJferUqThw4ABWrVqF8vJy7N2715I5\nhSCkCgU7olMxZcoUJCYmYt68ebh27Rq+/PJLJCcn2yx5WhMbG4u0tDSXqbhuuukmrFixAleuXMGD\nDz6IZ599FuPHj0dKSopgWysrK/Hbb7/xOmbSpEkYP348XnvtNWRlZeHs2bN466238Oijj+Lw4cOY\nPXu2y2N79OiBdevW4dKlS5gwYQJmzpwJrVaL5cuXAwBef/113H333Zg7dy7uu+8+TJ48GY2NjVi3\nbh1CQkIAmJ7e/Mtf/oJ33nkHo0ePRm5uLuLi4rBhwwYolUoAwPjx4/H666+joKAAo0aNwuLFi/Hk\nk0/aZJghCKnBsJ7WRgiC8BkZGRnIzMzEzJkzO9oUUZk9ezbKy8vx0UcfdbQpBAGAZnYE0eE0Nzej\nsrLS6YMynY2mpia/ORfCv6BgRxAdzLp16zB06FDs3r27o00RjPlc9uzZ09GmEIQNtIxJEARB+D00\nsyMIgiD8Hgp2BEEQhN9DwY4gCILweyjYEQRBEH4PBTuCIAjC76FgRxAEQfg9/w9WUXThqEltMQAA\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40a781d1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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KBAI8/fTTvPvuu9TV1TFo0CDuvvtupk+fft62So6GEEKI3iQZORoZkQyaqSTQ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40a53b2a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb_astcor_diag_plot(catalogue[RA_COL], catalogue[DEC_COL], \n",
    "                    gaia_coords.ra, gaia_coords.dec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RA correction: -0.06336958314250296 arcsec\n",
      "Dec correction: -0.19814636340669267 arcsec\n"
     ]
    }
   ],
   "source": [
    "delta_ra, delta_dec =  astrometric_correction(\n",
    "    SkyCoord(catalogue[RA_COL], catalogue[DEC_COL]),\n",
    "    gaia_coords\n",
    ")\n",
    "\n",
    "print(\"RA correction: {}\".format(delta_ra))\n",
    "print(\"Dec correction: {}\".format(delta_dec))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "catalogue[RA_COL] +=  delta_ra.to(u.deg)\n",
    "catalogue[DEC_COL] += delta_dec.to(u.deg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PEnG/J5m2QGCddCNQObh9iSbdvm2ByKTX97uBMel17273U+YyQhVqOjHuO/2L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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40a554d940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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px22YuAyDU4HKhF5fiHiTQEMI0bs1LvxmWRAOA3ZSmyNETyOBhhCid1MK0jyA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f40a53eb5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nb_astcor_diag_plot(catalogue[RA_COL], catalogue[DEC_COL], \n",
    "                    gaia_coords.ra, gaia_coords.dec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## IV - Flagging Gaia objects"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "catalogue.add_column(\n",
    "    gaia_flag_column(SkyCoord(catalogue[RA_COL], catalogue[DEC_COL]), epoch, gaia)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "145 sources flagged.\n"
     ]
    }
   ],
   "source": [
    "GAIA_FLAG_NAME = \"candels_flag_gaia\"\n",
    "\n",
    "catalogue['flag_gaia'].name = GAIA_FLAG_NAME\n",
    "print(\"{} sources flagged.\".format(np.sum(catalogue[GAIA_FLAG_NAME] > 0)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## V - Flagging objects near bright stars"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# VI - Saving to disk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "catalogue.write(\"{}/CANDELS.fits\".format(OUT_DIR), overwrite=True)"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python (herschelhelp_internal)",
   "language": "python",
   "name": "helpint"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}