{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CDFS SWIRE master catalogue\n",
    "## Preparation of COMBO data\n",
    "\n",
    "Classifying Objects by Medium-Band Observations - a spectrophotometric 17-filter survey (COMBO-17). COMBO catalogue: the catalogue comes from `dmu0_COMBO-17`.\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 total magnitude (aperture magnitudes are not provided.\n",
    "\n",
    "We don't know when the maps have been observed. We will use the year of the reference paper."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This notebook was run with herschelhelp_internal version: \n",
      "708e28f (Tue May 8 18:05:21 2018 +0100)\n"
     ]
    }
   ],
   "source": [
    "from herschelhelp_internal import git_version\n",
    "print(\"This notebook was run with herschelhelp_internal version: \\n{}\".format(git_version()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/seaborn/apionly.py:6: UserWarning: As seaborn no longer sets a default style on import, the seaborn.apionly module is deprecated. It will be removed in a future version.\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    }
   ],
   "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 import constants as const\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, mag_to_flux, flux_to_mag\n"
   ]
  },
  {
   "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 = \"combo_ra\"\n",
    "DEC_COL = \"combo_dec\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## I - Column selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "imported_columns = OrderedDict({\n",
    "    'Seq':'combo_id', \n",
    "    'ra':'combo_ra', \n",
    "    'dec':'combo_dec',  \n",
    "    #'dl':'combo_dl',\n",
    "    'stellarity':'combo_stellarity',\n",
    "    'Rmag':'m_combo_r',    #The catalogue is R selected\n",
    "    'e_Rmag':'merr_combo_r',  \n",
    "    #'Ap_Rmag':'m_ap_combo_r',\n",
    "    #'UjMag':'m_combo_uj',   #These bands are derived absolute magnitudes\n",
    "    #'e_UjMag':'merr_combo_uj', \n",
    "    #'BjMag':'m_combo_bj',   \n",
    "    #'e_BjMag':'merr_combo_bj',\n",
    "    #'VjMag':'m_combo_vj',   \n",
    "    #'e_VjMag':'merr_combo_vj',\n",
    "    #'usMag':'m_combo_us',   \n",
    "    #'e_usMag':'merr_combo_us',\n",
    "    #'gsMag':'m_combo_gs',   \n",
    "    #'e_gsMag':'merr_combo_gs',\n",
    "    #'rsMag':'m_combo_rs',   \n",
    "    #'e_rsMag':'merr_combo_rs',\n",
    "    #'UbMag':'m_combo_ub',   \n",
    "    #'e_UbMag':'merr_combo_ub',\n",
    "    #'BbMag':'m_combo_bb',   \n",
    "    #'e_BbMag':'merr_combo_bb',\n",
    "    #'VbMag':'m_combo_vb',   \n",
    "    #'e_VbMag':'merr_combo_vb',\n",
    "    #'S280Mag':'m_combo_s280', \n",
    "    #'e_S280Mag':'merr_combo_s280',\n",
    "    ##'S145Mag':'m_combo_s145', \n",
    "    #'e_S145Mag':'merr_combo_s145',\n",
    "    'W420F_E':'f_ap_combo_420', #The following values are given as fluxes\n",
    "    'e_W420F_E':'ferr_ap_combo_420',\n",
    "    'W462F_E':'f_ap_combo_462',\n",
    "    'e_W462F_E':'ferr_ap_combo_462',\n",
    "    'W485F_D':'f_ap_combo_485',\n",
    "    'e_W485F_D':'ferr_ap_combo_485',\n",
    "    'W518F_E':'f_ap_combo_518',\n",
    "    'e_W518F_E':'ferr_ap_combo_518',\n",
    "    'W571F_S':'f_ap_combo_571',   #Combined flux from two runs\n",
    "    'e_W571F_S':'ferr_ap_combo_571',\n",
    "    'W604F_E':'f_ap_combo_604',\n",
    "    'e_W604F_E':'ferr_ap_combo_604',\n",
    "    'W646F_D':'f_ap_combo_646',\n",
    "    'e_W646F_D':'ferr_ap_combo_646',\n",
    "    'W696F_E':'f_ap_combo_696',\n",
    "    'e_W696F_E':'ferr_ap_combo_696',\n",
    "    'W753F_E':'f_ap_combo_753',\n",
    "    'e_W753F_E':'ferr_ap_combo_753',\n",
    "    'W815F_S':'f_ap_combo_815',\n",
    "    'e_W815F_S':'ferr_ap_combo_815',\n",
    "    'W856F_D':'f_ap_combo_856',\n",
    "    'e_W856F_D':'ferr_ap_combo_856',\n",
    "    'W914F_D':'f_ap_combo_914', #Two runs but no combined - taking first\n",
    "    'e_W914F_D':'ferr_ap_combo_914',\n",
    "    'UF_S':'f_ap_combo_u',\n",
    "    'e_UF_S':'ferr_ap_combo_u',\n",
    "    'BF_S':'f_ap_combo_b',\n",
    "    'e_BF_S':'ferr_ap_combo_b',\n",
    "    'VF_D':'f_ap_combo_v',\n",
    "    'e_VF_D':'ferr_ap_combo_v',\n",
    "    'RF_S':'f_ap_combo_r',\n",
    "    'e_RF_S':'ferr_ap_combo_r',\n",
    "    'IF_D':'f_ap_combo_i',\n",
    "    'e_IF_D':'ferr_ap_combo_i'\n",
    "    })\n",
    "\n",
    "catalogue = Table.read(\"../../dmu0/dmu0_COMBO-17/data/table3.fits\")[list(imported_columns)]\n",
    "for column in imported_columns:\n",
    "    catalogue[column].name = imported_columns[column]\n",
    "\n",
    "epoch = 2000 #table says 1999 to 2001\n",
    "\n",
    "# Clean table metadata\n",
    "catalogue.meta = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table masked=True length=10</i>\n",
       "<table id=\"table140218184674552-108831\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>combo_id</th><th>combo_ra</th><th>combo_dec</th><th>combo_stellarity</th><th>m_combo_r</th><th>merr_combo_r</th><th>f_ap_combo_420</th><th>ferr_ap_combo_420</th><th>f_ap_combo_462</th><th>ferr_ap_combo_462</th><th>f_ap_combo_485</th><th>ferr_ap_combo_485</th><th>f_ap_combo_518</th><th>ferr_ap_combo_518</th><th>f_ap_combo_571</th><th>ferr_ap_combo_571</th><th>f_ap_combo_604</th><th>ferr_ap_combo_604</th><th>f_ap_combo_646</th><th>ferr_ap_combo_646</th><th>f_ap_combo_696</th><th>ferr_ap_combo_696</th><th>f_ap_combo_753</th><th>ferr_ap_combo_753</th><th>f_ap_combo_815</th><th>ferr_ap_combo_815</th><th>f_ap_combo_856</th><th>ferr_ap_combo_856</th><th>f_ap_combo_914</th><th>ferr_ap_combo_914</th><th>f_ap_combo_u</th><th>ferr_ap_combo_u</th><th>f_ap_combo_b</th><th>ferr_ap_combo_b</th><th>f_ap_combo_v</th><th>ferr_ap_combo_v</th><th>f_ap_combo_r</th><th>ferr_ap_combo_r</th><th>f_ap_combo_i</th><th>ferr_ap_combo_i</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th></th><th></th><th></th><th>mag</th><th>mag</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th><th>phot/m^2/s/nm</th></tr></thead>\n",
       "<tr><td>0</td><td>1</td><td>53.04655260189809</td><td>-28.06482398026151</td><td>nan</td><td>25.897972</td><td>0.2597</td><td>0.0026435487</td><td>0.0028525754</td><td>0.0019441945</td><td>0.0050782417</td><td>0.0063407477</td><td>0.0033082329</td><td>0.0128999</td><td>0.005585376</td><td>0.0042216503</td><td>0.003588988</td><td>0.00545072</td><td>0.0037927986</td><td>-0.0024629491</td><td>0.011115327</td><td>0.003668798</td><td>0.002974898</td><td>-0.0061611393</td><td>0.005189215</td><td>0.0052579027</td><td>0.002983739</td><td>0.013899683</td><td>0.007166146</td><td>-0.012559556</td><td>0.008609215</td><td>0.012575597</td><td>0.0021783262</td><td>0.008529394</td><td>0.00096643175</td><td>0.004752162</td><td>0.0016553438</td><td>0.0045423782</td><td>0.0005652418</td><td>0.007182074</td><td>0.005170131</td></tr>\n",
       "<tr><td>1</td><td>2</td><td>52.93962624603485</td><td>-28.06462837648348</td><td>nan</td><td>25.922817</td><td>0.1994</td><td>0.0049725887</td><td>0.003325123</td><td>0.0053968243</td><td>0.0028385678</td><td>0.014829304</td><td>0.0061306627</td><td>0.008219417</td><td>0.003868623</td><td>0.010431729</td><td>0.0043392056</td><td>0.011488724</td><td>0.0051987316</td><td>0.0077497284</td><td>0.008125072</td><td>0.0062717716</td><td>0.003935489</td><td>0.011430001</td><td>0.0065933266</td><td>0.008414535</td><td>0.004550586</td><td>0.02225148</td><td>0.009143417</td><td>0.0027921158</td><td>0.0074647036</td><td>0.00972669</td><td>0.002269718</td><td>0.004166309</td><td>0.0011602317</td><td>0.004172194</td><td>0.0021428019</td><td>0.0063953553</td><td>0.0005845545</td><td>0.012429478</td><td>0.005645175</td></tr>\n",
       "<tr><td>2</td><td>3</td><td>53.25214500630742</td><td>-28.065104350499013</td><td>nan</td><td>26.080927</td><td>0.2214</td><td>0.0029374603</td><td>0.0042451513</td><td>-0.0049716546</td><td>0.006426346</td><td>0.0055975555</td><td>0.005283612</td><td>0.0051286165</td><td>0.004365759</td><td>0.001201169</td><td>0.0039880085</td><td>0.011634848</td><td>0.0039788615</td><td>-0.010300942</td><td>0.016168907</td><td>0.0007932981</td><td>0.004202096</td><td>0.0021792164</td><td>0.0076979212</td><td>-0.006099478</td><td>0.0044403956</td><td>-0.011898397</td><td>0.013582071</td><td>0.020791234</td><td>0.014198382</td><td>-0.0017863943</td><td>0.0034811874</td><td>-1.936261e-05</td><td>0.0019783415</td><td>0.0032243216</td><td>0.0017577063</td><td>-0.00033004445</td><td>0.00080327026</td><td>-0.014375456</td><td>0.010974576</td></tr>\n",
       "<tr><td>3</td><td>4</td><td>53.36795775820615</td><td>-28.06517792576462</td><td>nan</td><td>24.873579</td><td>0.1563</td><td>0.0063921358</td><td>0.002596262</td><td>0.0056318273</td><td>0.0035823456</td><td>0.0056378106</td><td>0.00441638</td><td>0.006852279</td><td>0.0048438213</td><td>0.0026985586</td><td>0.003692915</td><td>0.011641119</td><td>0.00398695</td><td>0.03109488</td><td>0.013036846</td><td>0.010266774</td><td>0.0029923418</td><td>0.011409544</td><td>0.0050701248</td><td>0.011517621</td><td>0.0034736816</td><td>0.0239881</td><td>0.008725531</td><td>0.004260078</td><td>0.0067384094</td><td>0.005680313</td><td>0.0018968612</td><td>0.004119445</td><td>0.0011928168</td><td>0.006712271</td><td>0.0017643167</td><td>0.011591517</td><td>0.00048261677</td><td>0.0070293015</td><td>0.0041397894</td></tr>\n",
       "<tr><td>4</td><td>5</td><td>53.32106264525905</td><td>-28.065133475726462</td><td>nan</td><td>25.78421</td><td>0.2698</td><td>0.0025284858</td><td>0.002650288</td><td>0.0042570033</td><td>0.0038399366</td><td>0.0024411376</td><td>0.004930288</td><td>0.007873707</td><td>0.0035207903</td><td>0.0046116514</td><td>0.0032087315</td><td>0.0039657764</td><td>0.005125247</td><td>-0.016217358</td><td>0.0068417387</td><td>0.0037558703</td><td>0.0033345758</td><td>0.015191702</td><td>0.0052428073</td><td>0.007918886</td><td>0.0030483482</td><td>0.01941582</td><td>0.00747347</td><td>0.00060958724</td><td>0.006226504</td><td>-0.00013093327</td><td>0.0021074873</td><td>0.0035217772</td><td>0.0010693104</td><td>0.0020800177</td><td>0.001398662</td><td>0.0031395198</td><td>0.00058712007</td><td>-8.129975e-05</td><td>0.0038922913</td></tr>\n",
       "<tr><td>5</td><td>6</td><td>53.292097287458255</td><td>-28.065128066082178</td><td>nan</td><td>24.99502</td><td>0.0972</td><td>0.019948605</td><td>0.003718039</td><td>0.013015569</td><td>0.0038130966</td><td>0.018220054</td><td>0.004330236</td><td>0.017587243</td><td>0.0034221162</td><td>0.015128878</td><td>0.0030992394</td><td>0.017777491</td><td>0.0043656165</td><td>0.019180415</td><td>0.005748827</td><td>0.026529638</td><td>0.0037788677</td><td>0.026632128</td><td>0.0057045626</td><td>0.023708314</td><td>0.0029196017</td><td>0.02792422</td><td>0.006248071</td><td>0.043072745</td><td>0.006960825</td><td>0.021285491</td><td>0.0027309612</td><td>0.015690384</td><td>0.0012465261</td><td>0.017250473</td><td>0.0014040535</td><td>0.017349314</td><td>0.0004557142</td><td>0.027648635</td><td>0.0054054153</td></tr>\n",
       "<tr><td>6</td><td>7</td><td>53.229967825919154</td><td>-28.06503005890903</td><td>nan</td><td>25.871485</td><td>0.2882</td><td>0.0012045066</td><td>0.003897627</td><td>0.0044132513</td><td>0.0027976336</td><td>0.00458269</td><td>0.0055461624</td><td>0.009875731</td><td>0.003962219</td><td>0.0067814947</td><td>0.0033160665</td><td>0.0047813305</td><td>0.00521684</td><td>0.015544663</td><td>0.015444962</td><td>0.0058335075</td><td>0.0029255631</td><td>0.016355244</td><td>0.006035496</td><td>0.006013045</td><td>0.004282945</td><td>0.0074658045</td><td>0.0077043315</td><td>0.019086597</td><td>0.0073265885</td><td>-0.0008489177</td><td>0.002612258</td><td>0.0038235737</td><td>0.0012918167</td><td>0.005655405</td><td>0.0025813465</td><td>0.0034750535</td><td>0.0006231454</td><td>0.0018789952</td><td>0.006647257</td></tr>\n",
       "<tr><td>7</td><td>8</td><td>53.18293888014623</td><td>-28.065017040029545</td><td>nan</td><td>25.731575</td><td>0.1831</td><td>0.0062276805</td><td>0.003369402</td><td>0.013846429</td><td>0.002759924</td><td>0.018154914</td><td>0.003410117</td><td>0.014752125</td><td>0.0056991284</td><td>0.019639296</td><td>0.0032625962</td><td>0.017426182</td><td>0.0037926377</td><td>0.025695736</td><td>0.006597949</td><td>0.014325571</td><td>0.0028548185</td><td>0.0105836</td><td>0.0061909035</td><td>0.017594436</td><td>0.0030056147</td><td>0.014742221</td><td>0.0065584667</td><td>0.02460166</td><td>0.0066824746</td><td>0.010716451</td><td>0.0022642382</td><td>0.012857638</td><td>0.0012107698</td><td>0.016353952</td><td>0.001460291</td><td>0.01581362</td><td>0.00044819526</td><td>0.01675428</td><td>0.004316511</td></tr>\n",
       "<tr><td>8</td><td>9</td><td>52.9391529645356</td><td>-28.064589036789748</td><td>nan</td><td>25.013447</td><td>0.1807</td><td>0.0061064805</td><td>0.0030835005</td><td>0.005264745</td><td>0.003310161</td><td>0.002637309</td><td>0.00469066</td><td>0.00075746863</td><td>0.0046829325</td><td>0.010216046</td><td>0.0029233084</td><td>0.009667672</td><td>0.0047523654</td><td>0.0030402003</td><td>0.009100705</td><td>0.010591451</td><td>0.0036941513</td><td>0.0154705215</td><td>0.0057324325</td><td>0.016172117</td><td>0.0033903017</td><td>0.013065108</td><td>0.007177291</td><td>0.01173765</td><td>0.007377461</td><td>0.008057591</td><td>0.002709484</td><td>0.0040454385</td><td>0.0011060153</td><td>0.0039187097</td><td>0.0018148138</td><td>0.007600185</td><td>0.00052536634</td><td>0.01089189</td><td>0.005154694</td></tr>\n",
       "<tr><td>9</td><td>10</td><td>52.84114562805728</td><td>-28.06438482597608</td><td>nan</td><td>25.764791</td><td>0.1569</td><td>0.01162346</td><td>0.002631594</td><td>0.006005885</td><td>0.002787117</td><td>0.015149049</td><td>0.0048077777</td><td>0.011143516</td><td>0.0035439113</td><td>0.009884888</td><td>0.0026318</td><td>0.013119528</td><td>0.0032631063</td><td>0.020892728</td><td>0.007653941</td><td>0.014827856</td><td>0.0037116604</td><td>0.013676858</td><td>0.00508827</td><td>0.018994834</td><td>0.0031775958</td><td>0.013353675</td><td>0.006483032</td><td>0.009263921</td><td>0.010318295</td><td>0.007337054</td><td>0.0018009157</td><td>0.013336995</td><td>0.0009769341</td><td>0.012051843</td><td>0.0014065375</td><td>0.010746312</td><td>0.00044304837</td><td>0.014853776</td><td>0.0042564427</td></tr>\n",
       "</table><style>table.dataTable {clear: both; width: auto !important; margin: 0 !important;}\n",
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       "\n",
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       "        return ((a_num < b_num) ? -1 : ((a_num > b_num) ? 1 : 0));\n",
       "    else\n",
       "        return isNaN(a_num) ? -1 : 1;\n",
       "}\n",
       "\n",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table140218184674552-108831').dataTable()\");\n",
       "    \n",
       "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
       "    \"optionalnum-asc\": astropy_sort_num,\n",
       "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "catalogue[:10].show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unit conversion\n",
    "\n",
    "### Using mid wavelength\n",
    "The flux is presented in $\\textrm{photons} .\\textrm{s}^{-1} .  \\textrm{m}^{-2}  .\\textrm{nm}^{-1}$. We wish to convert these to micro Jansky; $10^{-32} \\textrm{ W} . \\textrm{m}^{-2}  . \\textrm{Hz}^{-1} $.\n",
    "\n",
    "To convert $\\textrm{photons} . \\textrm{s}^{-1} $ to $\\textrm{W}$ we must multiply by the average photon energy $h c / \\lambda$. We presume that the COMBO mid point wavelength was used.\n",
    "\n",
    "To convert $\\textrm{nm}^{-1}$ to $\\textrm{Hz}^{-1}$ we must differenciate:\n",
    "\n",
    "$c = \\nu \\lambda $\n",
    "\n",
    "$\\nu = c / \\lambda$\n",
    "\n",
    "$\\frac{d \\nu}{d \\lambda} = - c /\\lambda^{2}$\n",
    "\n",
    "$d \\lambda = -  (\\lambda^{2} / c )\\times d \\nu$\n",
    "\n",
    "\n",
    "\n",
    "The net result of this is to multiply by $\\lambda^2 / c$.\n",
    "\n",
    "Combining these two unit conversions leads to overall multiplying by $ h \\lambda$:\n",
    "\n",
    "$(\\lambda^2 / c ) \\times (h c / \\lambda) = h \\lambda$\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "flux_lambda: 0.0064185 1 / (m2 nm s)\n",
      "flux_nu: 1.78623608317308e-33 J / m2\n",
      "flux_nu in Jy: 1.78623608317308e-07 Jy\n"
     ]
    }
   ],
   "source": [
    "#Example conversion from photon s^-1 m^-2 nm^-1 to Jy\n",
    "flux_lambda = 0.0064185 * (u.m **-2) * (u.s ** -1) *( u.nm ** -1)\n",
    "\n",
    "wavelength = 420 * u.nm\n",
    "flux_nu = flux_lambda * const.h *  wavelength\n",
    "print('flux_lambda:', flux_lambda)\n",
    "#print('f_lambda:', flux_lambda.decompose())\n",
    "print('flux_nu:', flux_nu)\n",
    "print('flux_nu in Jy:',flux_nu.to(u.Jy))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Using Vega flux\n",
    "The paper provides fluxes of Vega in each band allowing conversion to Vega mag. It then provides the difference between Vega mag and AB mag per band to convert to AB. We can therefore calculate the AB magnitude and convert that back to flux to get the flux in Jy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Set wavelengths for unit conversion.\n",
    "#All from http://cds.aanda.org/component/article?access=bibcode&bibcode=2004A%252526A...421..913W\n",
    "#Wavelengths in the table column headings are marginally different to those in the paper.\n",
    "#   Band name   \\lambda    Vega AB Fphot (Vega 10^8 photons s^-1 m^-2 nm^-1)\n",
    "wavelengths = {\n",
    "    'f_ap_combo_420':   [418, -0.19, 1.571], \n",
    "    'ferr_ap_combo_420':[418, -0.19, 1.571],\n",
    "    'f_ap_combo_462':   [462, -0.18, 1.412],\n",
    "    'ferr_ap_combo_462':[462, -0.18, 1.412],\n",
    "    'f_ap_combo_485':   [486, -0.06, 1.207], \n",
    "    'ferr_ap_combo_485':[486, -0.06, 1.207],\n",
    "    'f_ap_combo_518':   [519, -0.06, 1.125],\n",
    "    'ferr_ap_combo_518':[519, -0.06, 1.125],\n",
    "    'f_ap_combo_571':   [572,  0.04, 0.932],   \n",
    "    'ferr_ap_combo_571':[572,  0.04, 0.932],\n",
    "    'f_ap_combo_604':   [605,  0.10, 0.832],\n",
    "    'ferr_ap_combo_604':[605,  0.10, 0.832],\n",
    "    'f_ap_combo_646':   [645,  0.22, 0.703], \n",
    "    'ferr_ap_combo_646':[645,  0.22, 0.703], \n",
    "    'f_ap_combo_696':   [696,  0.27, 0.621],\n",
    "    'ferr_ap_combo_696':[696,  0.27, 0.621],\n",
    "    'f_ap_combo_753':   [753,  0.36, 0.525],\n",
    "    'ferr_ap_combo_753':[753,  0.36, 0.525],\n",
    "    'f_ap_combo_815':   [816,  0.45, 0.442], \n",
    "    'ferr_ap_combo_815':[816,  0.45, 0.442], \n",
    "    'f_ap_combo_856':   [857,  0.56, 0.386],  \n",
    "    'ferr_ap_combo_856':[857,  0.56, 0.386],\n",
    "    'f_ap_combo_914':   [914,  0.50, 0.380],\n",
    "    'ferr_ap_combo_914':[914,  0.50, 0.380],\n",
    "    'f_ap_combo_u':     [365,  0.77, 0.737],\n",
    "    'ferr_ap_combo_u':  [365,  0.77, 0.737],\n",
    "    'f_ap_combo_b':     [458, -0.13, 1.371],\n",
    "    'ferr_ap_combo_b':  [458, -0.13, 1.371],\n",
    "    'f_ap_combo_v':     [538, -0.02, 1.055],\n",
    "    'ferr_ap_combo_v':  [538, -0.02, 1.055],\n",
    "    'f_ap_combo_r':     [648,  0.19, 0.725],\n",
    "    'ferr_ap_combo_r':  [648,  0.19, 0.725],\n",
    "    'f_ap_combo_i':     [857,  0.49, 0.412],\n",
    "    'ferr_ap_combo_i':  [857,  0.49, 0.412]\n",
    "}\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "25.971856598750897\n",
      "25.781856598750895\n",
      "(1.7670846750466056e-07, None)\n"
     ]
    }
   ],
   "source": [
    "#Example conversion from photon s^-1 m^-2 nm^-1 to Jy\n",
    "flux_lambda = 0.0064185 #* (u.m **-2) * (u.s ** -1) *( u.nm ** -1)\n",
    "\n",
    "mag_vega = -2.5 *np.log10(flux_lambda/(wavelengths['f_ap_combo_420'][2]*1.e8))\n",
    "print(mag_vega)\n",
    "mag_AB = mag_vega + wavelengths['f_ap_combo_420'][1]\n",
    "print(mag_AB)\n",
    "flux_converted = mag_to_flux(mag_AB)\n",
    "print(flux_converted)\n",
    "#This is different to the value calculated using mid point wavelength as we expect \n",
    "#because it should take account of the filter response better."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/ipykernel/__main__.py:20: RuntimeWarning: invalid value encountered in log10\n"
     ]
    }
   ],
   "source": [
    "#Replace 0.0 with NaN values\n",
    "for col in catalogue.colnames:\n",
    "    catalogue[col].unit = None\n",
    "    if col.startswith('m'): # | col.endswith('ra') | col.endswith('dec'):\n",
    "        catalogue[col][np.where(catalogue[col] == 0.0)] = np.nan\n",
    "\n",
    "# Add magnitude, fix flux units and add band-flag columns\n",
    "nancol = np.zeros(len(catalogue))\n",
    "nancol.fill(np.nan)\n",
    "for col in catalogue.colnames:\n",
    "    if col.startswith('f_'):\n",
    "         \n",
    "        errcol = \"ferr{}\".format(col[1:])\n",
    "        \n",
    "        #Replace mask with nan\n",
    "        catalogue[col].fill_value = np.nan\n",
    "        catalogue[errcol].fill_value = np.nan\n",
    "        \n",
    "        #Calculate magnitudes using Vega fluxes from wavelengths (values from paper)\n",
    "        magnitude = -2.5*np.log10(catalogue[col].filled()/(wavelengths[col][2]*1.e8)) + wavelengths[col][1]\n",
    "        magnitude_error = 2.5/np.log(10)*(catalogue[errcol].filled()/catalogue[col].filled() )\n",
    "\n",
    "        catalogue.add_column(Column(nancol, \n",
    "                                    name=\"m{}\".format(col[1:])))\n",
    "        catalogue.add_column(Column(nancol, \n",
    "                                    name=\"m{}\".format(errcol[1:])))\n",
    "        # Add the AB magnitudes\n",
    "        catalogue[\"m{}\".format(col[1:])] = magnitude\n",
    "        catalogue[\"m{}\".format(errcol[1:])] = magnitude_error\n",
    "    \n",
    "        flux_new, flux_new_error = mag_to_flux(magnitude, magnitude_error)\n",
    "        catalogue[col] = flux_new * 1.e6 # uJy\n",
    "        catalogue[errcol] = flux_new_error * 1.e6 # uJy \n",
    "        \n",
    "        \n",
    "        #We add NAN filled total columns because no total fluxes are present\n",
    "        if not col == 'f_ap_combo_r':\n",
    "            catalogue.add_column(Column(nancol, \n",
    "                                    name=\"m{}\".format(col[4:])))\n",
    "            catalogue.add_column(Column(nancol, \n",
    "                                    name=\"merr{}\".format(col[4:])))\n",
    "            catalogue.add_column(Column(nancol, \n",
    "                                    name=\"f{}\".format(col[4:])))\n",
    "            catalogue.add_column(Column(nancol, \n",
    "                                    name=\"ferr{}\".format(col[4:])))\n",
    "        \n",
    "        # \n",
    "        \n",
    "        # Band-flag column\n",
    "        catalogue.add_column(Column(np.zeros(len(catalogue), dtype=bool), name=\"flag{}\".format(col[4:])))\n",
    "        \n",
    "#Add total fluxes for R band\n",
    "f_combo_r, ferr_combo_r = mag_to_flux(catalogue['m_combo_r'],catalogue['merr_combo_r'])\n",
    "catalogue['f_combo_r'] = f_combo_r *1.e6 #uJy\n",
    "catalogue['ferr_combo_r'] = ferr_combo_r *1.e6 #uJy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<i>Table masked=True length=10</i>\n",
       "<table id=\"table140218184240488-755410\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>combo_id</th><th>combo_ra</th><th>combo_dec</th><th>combo_stellarity</th><th>m_combo_r</th><th>merr_combo_r</th><th>f_ap_combo_420</th><th>ferr_ap_combo_420</th><th>f_ap_combo_462</th><th>ferr_ap_combo_462</th><th>f_ap_combo_485</th><th>ferr_ap_combo_485</th><th>f_ap_combo_518</th><th>ferr_ap_combo_518</th><th>f_ap_combo_571</th><th>ferr_ap_combo_571</th><th>f_ap_combo_604</th><th>ferr_ap_combo_604</th><th>f_ap_combo_646</th><th>ferr_ap_combo_646</th><th>f_ap_combo_696</th><th>ferr_ap_combo_696</th><th>f_ap_combo_753</th><th>ferr_ap_combo_753</th><th>f_ap_combo_815</th><th>ferr_ap_combo_815</th><th>f_ap_combo_856</th><th>ferr_ap_combo_856</th><th>f_ap_combo_914</th><th>ferr_ap_combo_914</th><th>f_ap_combo_u</th><th>ferr_ap_combo_u</th><th>f_ap_combo_b</th><th>ferr_ap_combo_b</th><th>f_ap_combo_v</th><th>ferr_ap_combo_v</th><th>f_ap_combo_r</th><th>ferr_ap_combo_r</th><th>f_ap_combo_i</th><th>ferr_ap_combo_i</th><th>m_ap_combo_420</th><th>merr_ap_combo_420</th><th>m_combo_420</th><th>merr_combo_420</th><th>f_combo_420</th><th>ferr_combo_420</th><th>flag_combo_420</th><th>m_ap_combo_462</th><th>merr_ap_combo_462</th><th>m_combo_462</th><th>merr_combo_462</th><th>f_combo_462</th><th>ferr_combo_462</th><th>flag_combo_462</th><th>m_ap_combo_485</th><th>merr_ap_combo_485</th><th>m_combo_485</th><th>merr_combo_485</th><th>f_combo_485</th><th>ferr_combo_485</th><th>flag_combo_485</th><th>m_ap_combo_518</th><th>merr_ap_combo_518</th><th>m_combo_518</th><th>merr_combo_518</th><th>f_combo_518</th><th>ferr_combo_518</th><th>flag_combo_518</th><th>m_ap_combo_571</th><th>merr_ap_combo_571</th><th>m_combo_571</th><th>merr_combo_571</th><th>f_combo_571</th><th>ferr_combo_571</th><th>flag_combo_571</th><th>m_ap_combo_604</th><th>merr_ap_combo_604</th><th>m_combo_604</th><th>merr_combo_604</th><th>f_combo_604</th><th>ferr_combo_604</th><th>flag_combo_604</th><th>m_ap_combo_646</th><th>merr_ap_combo_646</th><th>m_combo_646</th><th>merr_combo_646</th><th>f_combo_646</th><th>ferr_combo_646</th><th>flag_combo_646</th><th>m_ap_combo_696</th><th>merr_ap_combo_696</th><th>m_combo_696</th><th>merr_combo_696</th><th>f_combo_696</th><th>ferr_combo_696</th><th>flag_combo_696</th><th>m_ap_combo_753</th><th>merr_ap_combo_753</th><th>m_combo_753</th><th>merr_combo_753</th><th>f_combo_753</th><th>ferr_combo_753</th><th>flag_combo_753</th><th>m_ap_combo_815</th><th>merr_ap_combo_815</th><th>m_combo_815</th><th>merr_combo_815</th><th>f_combo_815</th><th>ferr_combo_815</th><th>flag_combo_815</th><th>m_ap_combo_856</th><th>merr_ap_combo_856</th><th>m_combo_856</th><th>merr_combo_856</th><th>f_combo_856</th><th>ferr_combo_856</th><th>flag_combo_856</th><th>m_ap_combo_914</th><th>merr_ap_combo_914</th><th>m_combo_914</th><th>merr_combo_914</th><th>f_combo_914</th><th>ferr_combo_914</th><th>flag_combo_914</th><th>m_ap_combo_u</th><th>merr_ap_combo_u</th><th>m_combo_u</th><th>merr_combo_u</th><th>f_combo_u</th><th>ferr_combo_u</th><th>flag_combo_u</th><th>m_ap_combo_b</th><th>merr_ap_combo_b</th><th>m_combo_b</th><th>merr_combo_b</th><th>f_combo_b</th><th>ferr_combo_b</th><th>flag_combo_b</th><th>m_ap_combo_v</th><th>merr_ap_combo_v</th><th>m_combo_v</th><th>merr_combo_v</th><th>f_combo_v</th><th>ferr_combo_v</th><th>flag_combo_v</th><th>m_ap_combo_r</th><th>merr_ap_combo_r</th><th>flag_combo_r</th><th>m_ap_combo_i</th><th>merr_ap_combo_i</th><th>m_combo_i</th><th>merr_combo_i</th><th>f_combo_i</th><th>ferr_combo_i</th><th>flag_combo_i</th><th>f_combo_r</th><th>ferr_combo_r</th></tr></thead>\n",
       "<tr><td>0</td><td>1</td><td>53.04655260189809</td><td>-28.06482398026151</td><td>nan</td><td>25.897972</td><td>0.2597</td><td>0.072779976</td><td>0.07853472</td><td>0.059007134</td><td>0.1541268</td><td>0.20157324</td><td>0.10516918</td><td>0.43998066</td><td>0.19050205</td><td>0.15851328</td><td>0.13475825</td><td>0.2169354</td><td>0.1509511</td><td>nan</td><td>nan</td><td>0.1672752</td><td>0.13563752</td><td>nan</td><td>nan</td><td>0.28535762</td><td>0.1619339</td><td>0.7805809</td><td>0.4024377</td><td>nan</td><td>nan</td><td>0.3048325</td><td>0.05280263</td><td>0.25461265</td><td>0.028849147</td><td>0.16658625</td><td>0.058027796</td><td>0.19096106</td><td>0.023762701</td><td>0.4030444</td><td>0.29013795</td><td>26.74497</td><td>1.1715859</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.972738</td><td>2.8359458</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.638918</td><td>0.5664739</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.791416</td><td>0.47010016</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.899836</td><td>0.9230262</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.559174</td><td>0.7554926</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-4.899944</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.841421</td><td>0.8803849</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-0.9144604</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.261526</td><td>0.6161303</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.168955</td><td>0.5597641</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-0.7442409</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.189846</td><td>0.18806961</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.3853</td><td>0.123020455</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.845901</td><td>0.3781998</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.697638</td><td>0.1351062</td><td>False</td><td>24.886618</td><td>0.78158456</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.15878552</td><td>0.037980314</td></tr>\n",
       "<tr><td>1</td><td>2</td><td>52.93962624603485</td><td>-28.06462837648348</td><td>nan</td><td>25.922817</td><td>0.1994</td><td>0.13690078</td><td>0.091544256</td><td>0.16379642</td><td>0.08615202</td><td>0.4714257</td><td>0.19489464</td><td>0.28034195</td><td>0.1319482</td><td>0.39168805</td><td>0.16292743</td><td>0.45724362</td><td>0.20690608</td><td>0.32683674</td><td>0.34266642</td><td>0.2859551</td><td>0.17943466</td><td>0.5673959</td><td>0.32729888</td><td>0.45667568</td><td>0.24697047</td><td>1.2496034</td><td>0.513478</td><td>0.16832536</td><td>0.45001674</td><td>0.23577489</td><td>0.05501795</td><td>0.12436917</td><td>0.034634266</td><td>0.14625527</td><td>0.07511541</td><td>0.26886007</td><td>0.024574613</td><td>0.69751954</td><td>0.31679687</td><td>26.058985</td><td>0.7260215</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.864239</td><td>0.5710647</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.716467</td><td>0.44886005</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.280779</td><td>0.5110221</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.917648</td><td>0.45162526</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.74963</td><td>0.49130356</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.114172</td><td>1.1383218</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.259254</td><td>0.68129116</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.515284</td><td>0.6263003</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.75098</td><td>0.5871668</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.65807</td><td>0.44614282</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.834625</td><td>2.9027088</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.468756</td><td>0.25335598</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.163218</td><td>0.3023553</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.98722</td><td>0.5576245</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.326183</td><td>0.09923952</td><td>False</td><td>24.29111</td><td>0.4931157</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.15519336</td><td>0.028501911</td></tr>\n",
       "<tr><td>2</td><td>3</td><td>53.25214500630742</td><td>-28.065104350499013</td><td>nan</td><td>26.080927</td><td>0.2214</td><td>0.080871664</td><td>0.1168739</td><td>nan</td><td>nan</td><td>0.17794707</td><td>0.16796675</td><td>0.17492321</td><td>0.1489042</td><td>0.04510116</td><td>0.14974062</td><td>0.46305972</td><td>0.15835622</td><td>nan</td><td>nan</td><td>0.036169697</td><td>0.19159067</td><td>0.108178414</td><td>0.38213223</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>1.2534193</td><td>0.85596293</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.11302785</td><td>0.061615985</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>26.630508</td><td>1.5690814</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-1.4034194</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.774273</td><td>1.0248417</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.792881</td><td>0.924238</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>27.26453</td><td>3.6047592</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.735907</td><td>0.37129784</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-1.7042294</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>27.504137</td><td>5.7511387</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.314648</td><td>3.835283</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-0.79041165</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-1.2393725</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.654758</td><td>0.74145174</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-2.115799</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-110.93323</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.267036</td><td>0.59187806</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-2.6424913</td><td>False</td><td>nan</td><td>-0.8288777</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.13416192</td><td>0.027357887</td></tr>\n",
       "<tr><td>3</td><td>4</td><td>53.36795775820615</td><td>-28.06517792576462</td><td>nan</td><td>24.873579</td><td>0.1563</td><td>0.17598253</td><td>0.07147795</td><td>0.17092861</td><td>0.108725876</td><td>0.1792267</td><td>0.14039728</td><td>0.23371248</td><td>0.16520949</td><td>0.10132471</td><td>0.1386605</td><td>0.46330893</td><td>0.15867801</td><td>1.3113964</td><td>0.54981625</td><td>0.4681041</td><td>0.13643308</td><td>0.56638014</td><td>0.25168562</td><td>0.62508553</td><td>0.188524</td><td>1.3471265</td><td>0.49000937</td><td>0.25682282</td><td>0.40623134</td><td>0.1376907</td><td>0.04597988</td><td>0.12297048</td><td>0.03560704</td><td>0.23529775</td><td>0.061847884</td><td>0.48730662</td><td>0.020289179</td><td>0.39447048</td><td>0.23231676</td><td>25.786325</td><td>0.44098803</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.817963</td><td>0.69062525</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.766493</td><td>0.85051167</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.478294</td><td>0.7674982</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.385712</td><td>1.4858048</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.735323</td><td>0.37185222</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.605665</td><td>0.45520595</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.724144</td><td>0.31644738</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.51723</td><td>0.48247483</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.41015</td><td>0.32745492</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.576479</td><td>0.39493018</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.375916</td><td>1.7173711</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.052738</td><td>0.36256644</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.175497</td><td>0.3143832</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.470955</td><td>0.28538516</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.680494</td><td>0.045204997</td><td>False</td><td>24.909964</td><td>0.6394261</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.40791345</td><td>0.058722246</td></tr>\n",
       "<tr><td>4</td><td>5</td><td>53.32106264525905</td><td>-28.065133475726462</td><td>nan</td><td>25.78421</td><td>0.2698</td><td>0.069612026</td><td>0.072965376</td><td>0.12920208</td><td>0.1165439</td><td>0.07760415</td><td>0.15673465</td><td>0.2685509</td><td>0.12008465</td><td>0.17315719</td><td>0.12048068</td><td>0.15783527</td><td>0.20398143</td><td>nan</td><td>nan</td><td>0.17124534</td><td>0.1520368</td><td>0.7541307</td><td>0.260258</td><td>0.429775</td><td>0.16544043</td><td>1.0903566</td><td>0.41969627</td><td>0.036749616</td><td>0.37537137</td><td>nan</td><td>nan</td><td>0.105129294</td><td>0.031920206</td><td>0.072914585</td><td>0.04902981</td><td>0.13198495</td><td>0.024682442</td><td>nan</td><td>nan</td><td>26.79329</td><td>1.1380383</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.121826</td><td>0.9793645</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.675287</td><td>2.192827</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.327433</td><td>0.48549545</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.803898</td><td>0.75544214</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.90449</td><td>1.4031719</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-0.45804766</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.815952</td><td>0.96394956</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.206383</td><td>0.37469834</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.816896</td><td>0.41795045</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.806078</td><td>0.41791782</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>27.486868</td><td>11.09003</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-17.475887</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.34569</td><td>0.32965997</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.742964</td><td>0.73007935</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.098688</td><td>0.20304298</td><td>False</td><td>nan</td><td>-51.980495</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.17632584</td><td>0.043816086</td></tr>\n",
       "<tr><td>5</td><td>6</td><td>53.292097287458255</td><td>-28.065128066082178</td><td>nan</td><td>24.99502</td><td>0.0972</td><td>0.54920703</td><td>0.10236169</td><td>0.3950287</td><td>0.11572929</td><td>0.5792175</td><td>0.13765866</td><td>0.5998528</td><td>0.11671902</td><td>0.56805545</td><td>0.11636949</td><td>0.707533</td><td>0.17374879</td><td>0.8089147</td><td>0.242451</td><td>1.2095928</td><td>0.17229377</td><td>1.3220452</td><td>0.28318012</td><td>1.286702</td><td>0.15845318</td><td>1.5681733</td><td>0.35088024</td><td>2.5966816</td><td>0.41963995</td><td>0.5159599</td><td>0.066198446</td><td>0.46837607</td><td>0.03721024</td><td>0.6047119</td><td>0.04921881</td><td>0.7293637</td><td>0.019158186</td><td>1.551586</td><td>0.30334106</td><td>24.55066</td><td>0.20236048</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.908428</td><td>0.3180819</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.492895</td><td>0.2580395</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.454887</td><td>0.21126194</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.514023</td><td>0.22241943</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.275633</td><td>0.2666241</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.130243</td><td>0.32542098</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.693401</td><td>0.15465169</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.596884</td><td>0.2325631</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.626305</td><td>0.13370489</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.411514</td><td>0.24293451</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>22.863953</td><td>0.17546175</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.61846</td><td>0.13930161</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.723513</td><td>0.086256556</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.446129</td><td>0.08837043</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.24264</td><td>0.028519018</td><td>False</td><td>23.42306</td><td>0.21226563</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.36474696</td><td>0.032653794</td></tr>\n",
       "<tr><td>6</td><td>7</td><td>53.229967825919154</td><td>-28.06503005890903</td><td>nan</td><td>25.871485</td><td>0.2882</td><td>0.03316139</td><td>0.10730596</td><td>0.1339441</td><td>0.084909394</td><td>0.14568439</td><td>0.17631331</td><td>0.33683422</td><td>0.1351405</td><td>0.2546297</td><td>0.12451075</td><td>0.19029401</td><td>0.20762701</td><td>0.6555813</td><td>0.6513765</td><td>0.2659733</td><td>0.1333883</td><td>0.811891</td><td>0.29960817</td><td>0.32634047</td><td>0.23244429</td><td>0.41926628</td><td>0.43266153</td><td>1.1506535</td><td>0.44169024</td><td>nan</td><td>nan</td><td>0.11413825</td><td>0.03856227</td><td>0.19824885</td><td>0.09048848</td><td>0.14609061</td><td>0.026196918</td><td>0.10544547</td><td>0.3730308</td><td>27.598417</td><td>3.5133011</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.082691</td><td>0.6882663</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.991467</td><td>1.3140031</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.081459</td><td>0.43560573</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.385227</td><td>0.53091145</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.701437</td><td>1.1846309</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.358433</td><td>1.0787724</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.337904</td><td>0.5445077</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.126255</td><td>0.4006639</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.115822</td><td>0.77334327</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.843775</td><td>1.1204246</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.747639</td><td>0.41677108</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>nan</td><td>-3.3409872</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.256422</td><td>0.3668223</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.656973</td><td>0.49557215</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.988443</td><td>0.19469383</td><td>False</td><td>26.34243</td><td>3.8409717</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.16270682</td><td>0.043189224</td></tr>\n",
       "<tr><td>7</td><td>8</td><td>53.18293888014623</td><td>-28.065017040029545</td><td>nan</td><td>25.731575</td><td>0.1831</td><td>0.1714553</td><td>0.09276355</td><td>0.4202447</td><td>0.08376481</td><td>0.57714736</td><td>0.10840811</td><td>0.50315535</td><td>0.19438195</td><td>0.7374118</td><td>0.122503206</td><td>0.69355154</td><td>0.1509447</td><td>1.0836909</td><td>0.27826163</td><td>0.6531608</td><td>0.13016273</td><td>0.5253797</td><td>0.3073222</td><td>0.9548878</td><td>0.16312116</td><td>0.82789713</td><td>0.3683119</td><td>1.4831351</td><td>0.40285945</td><td>0.25976625</td><td>0.05488502</td><td>0.38381606</td><td>0.036142938</td><td>0.57328475</td><td>0.05119023</td><td>0.6648029</td><td>0.018842079</td><td>0.9402178</td><td>0.24223422</td><td>25.814623</td><td>0.5874228</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.841244</td><td>0.21641314</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.496782</td><td>0.20393857</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.645744</td><td>0.41944802</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.230724</td><td>0.18036892</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.297302</td><td>0.23629984</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.812737</td><td>0.2787868</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.36245</td><td>0.21636692</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.598816</td><td>0.6351041</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.950119</td><td>0.18547367</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.105059</td><td>0.48301843</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.472048</td><td>0.29491523</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.363543</td><td>0.22940105</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.939692</td><td>0.1022409</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.504074</td><td>0.09694848</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.343267</td><td>0.030772319</td><td>False</td><td>23.966928</td><td>0.27972504</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.18508437</td><td>0.031212874</td></tr>\n",
       "<tr><td>8</td><td>9</td><td>52.9391529645356</td><td>-28.064589036789748</td><td>nan</td><td>25.013447</td><td>0.1807</td><td>0.1681183</td><td>0.08489224</td><td>0.1597873</td><td>0.10046481</td><td>0.0838404</td><td>0.14911668</td><td>0.025835175</td><td>0.15972196</td><td>0.38358983</td><td>0.10976373</td><td>0.38476792</td><td>0.18914147</td><td>0.1282175</td><td>0.3838134</td><td>0.48290718</td><td>0.16843133</td><td>0.7679721</td><td>0.28456366</td><td>0.8776979</td><td>0.18399945</td><td>0.7337122</td><td>0.4030633</td><td>0.7076161</td><td>0.44475767</td><td>0.19531569</td><td>0.06567779</td><td>0.12076117</td><td>0.033015877</td><td>0.13736981</td><td>0.063618034</td><td>0.3195105</td><td>0.02208631</td><td>0.6112322</td><td>0.28927165</td><td>25.835962</td><td>0.54824835</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.891144</td><td>0.6826468</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.591366</td><td>1.9310666</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>27.86947</td><td>6.712395</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.940332</td><td>0.310682</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.937002</td><td>0.53371847</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.13013</td><td>3.2501032</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.69034</td><td>0.37868974</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.186636</td><td>0.40230766</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.041637</td><td>0.22761233</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.236185</td><td>0.596447</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.275505</td><td>0.68241733</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.673157</td><td>0.36509484</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.19518</td><td>0.29683822</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>26.055271</td><td>0.50282085</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.138786</td><td>0.075052015</td><td>False</td><td>24.434484</td><td>0.5138353</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.35860905</td><td>0.059683606</td></tr>\n",
       "<tr><td>9</td><td>10</td><td>52.84114562805728</td><td>-28.06438482597608</td><td>nan</td><td>25.764791</td><td>0.1569</td><td>0.32000726</td><td>0.07245082</td><td>0.18228133</td><td>0.084590256</td><td>0.4815898</td><td>0.1528397</td><td>0.38007498</td><td>0.12087315</td><td>0.37115455</td><td>0.09881796</td><td>0.52214956</td><td>0.12986971</td><td>0.88112855</td><td>0.3227968</td><td>0.6760621</td><td>0.16922964</td><td>0.6789319</td><td>0.25258642</td><td>1.0308908</td><td>0.172455</td><td>0.74991804</td><td>0.36407527</td><td>0.55848515</td><td>0.6220493</td><td>0.17785022</td><td>0.0436542</td><td>0.3981259</td><td>0.029162697</td><td>0.42247507</td><td>0.0493059</td><td>0.45177382</td><td>0.018625705</td><td>0.833565</td><td>0.23886326</td><td>25.1371</td><td>0.24581465</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.748144</td><td>0.5038514</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.693306</td><td>0.3445746</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.950327</td><td>0.34529072</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.976112</td><td>0.2890716</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.605513</td><td>0.27004573</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.037401</td><td>0.39775372</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.325033</td><td>0.27177793</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.320435</td><td>0.4039319</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>23.866968</td><td>0.18162994</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.212465</td><td>0.5271105</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.53247</td><td>1.2093095</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>25.774864</td><td>0.26649925</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.899948</td><td>0.07953011</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.835497</td><td>0.12671328</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>24.762697</td><td>0.04476267</td><td>False</td><td>24.09765</td><td>0.3111245</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>False</td><td>0.17950773</td><td>0.025940707</td></tr>\n",
       "</table><style>table.dataTable {clear: both; width: auto !important; margin: 0 !important;}\n",
       ".dataTables_info, .dataTables_length, .dataTables_filter, .dataTables_paginate{\n",
       "display: inline-block; margin-right: 1em; }\n",
       ".paginate_button { margin-right: 5px; }\n",
       "</style>\n",
       "<script>\n",
       "\n",
       "var astropy_sort_num = function(a, b) {\n",
       "    var a_num = parseFloat(a);\n",
       "    var b_num = parseFloat(b);\n",
       "\n",
       "    if (isNaN(a_num) && isNaN(b_num))\n",
       "        return ((a < b) ? -1 : ((a > b) ? 1 : 0));\n",
       "    else if (!isNaN(a_num) && !isNaN(b_num))\n",
       "        return ((a_num < b_num) ? -1 : ((a_num > b_num) ? 1 : 0));\n",
       "    else\n",
       "        return isNaN(a_num) ? -1 : 1;\n",
       "}\n",
       "\n",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table140218184240488-755410').dataTable()\");\n",
       "    \n",
       "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
       "    \"optionalnum-asc\": astropy_sort_num,\n",
       "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
       "});\n",
       "\n",
       "    $('#table140218184240488-755410').dataTable({\n",
       "        order: [],\n",
       "        pageLength: 50,\n",
       "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        pagingType: \"full_numbers\",\n",
       "        columnDefs: [{targets: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 66, 67, 69, 70, 71, 72, 73, 74, 76, 77, 78, 79, 80, 81, 83, 84, 85, 86, 87, 88, 90, 91, 92, 93, 94, 95, 97, 98, 99, 100, 101, 102, 104, 105, 106, 107, 108, 109, 111, 112, 113, 114, 115, 116, 118, 119, 120, 121, 122, 123, 125, 126, 127, 128, 129, 130, 132, 133, 134, 135, 136, 137, 139, 140, 141, 142, 143, 144, 146, 147, 149, 150, 151, 152, 153, 154, 156, 157], type: \"optionalnum\"}]\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 10,
     "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": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The initial catalogue had 63501 sources.\n",
      "The cleaned catalogue has 63501 sources (0 removed).\n",
      "The cleaned catalogue has 0 sources flagged as having been cleaned\n"
     ]
    }
   ],
   "source": [
    "SORT_COLS = ['merr_combo_u',  \n",
    "     'merr_combo_b', \n",
    "     'merr_combo_v',\n",
    "     'merr_combo_r',\n",
    "     'merr_combo_i']\n",
    "FLAG_NAME = 'combo_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": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gaia = Table.read(\"../../dmu0/dmu0_GAIA/data/GAIA_CDFS-SWIRE.fits\")\n",
    "gaia_coords = SkyCoord(gaia['ra'], gaia['dec'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/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"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "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": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RA correction: 0.18399366377366277 arcsec\n",
      "Dec correction: -0.283546868710971 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": 15,
   "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": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/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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55ZV49tlnMWHChIIyKef6JiwouHmkkj3m+lMzePBgTJs2LaPZZ599cNBBB2Ht2rU477zz8MYbb0CSJJx44okwDCOjO+KII/D888+Dcw5ZlrFt2zbcc889eP3119Ha2pq5WO3vzs7XzJkzMxc1YwwHHnggnnnmGQwePBjHHHMMJkyYkJPntWvX4qijjkI0GsX2bh1dKY6m8Qdh2IiR+HDtuznB7auHH5n5uyfFMXzfcWhpaSnoNRebbGHnbdKkSfjTn/5UtJwBYNiwYTnn4/R9+aR9l1GrSgiHZAQVqWhgy8+b03fu2LEDq1evxo9//OMCzfkXX4bTvn0ptnQZBbp8Dp95Aj7rNDA4LCGoSDjyuK9j+X/9CTu2t6BpxEhHzemzZuOIY45FWGGOOwsAQCAQcDwfwKqn55xzDn7729/illtuwZVXXomOjg7853/+Z2b05qRxSueuu+7CmjVr8NRTT+WMBF9//XV845tnoCslAFjlMGLUKDSNHIWPPngfRx5zLEzTzNTdTgMwgmpJGzQ7D5xzaJqGG264AXPmzAFjDDNmzMApp5yCRx55BL/61a+K6v1c3wQFN6IEgwcPLnivsbERra2tAKyRnWmaOaOvbFpbWzFs2DDMnz8fPT09+OEPf4gxY8YgHA5j0aJFBc886uvrCxq5+fPnQ5IkLFu2DHfeeSeGDx+OSy65JDNqam1txf777w8A6NB691Ub1DAYsa7OnO+qqY3mvJZVtWCmmlMenKipqfE0KUNR3C+zuro69PT0wDTNzOgNsHr74XAYteFgnzVoL7zwAoQQOaNem6QhkNC9TU6ob2jMaCRJoKHRet22c6drcBs8ZAgaGhsRVhgiqrMRc6nzHD9+PG6++Wbcdttt+P3vfw9JknDOOecAAIYMGeIp77/73e+wdOlS3H333Zg6dWrOZx0dHXjy0Ufw5KOPFOi2t7QAAM45/WS0bOudtv/cypexb5N1jXR3d+do7BFbNGrVufr6egDA9OnTM8fIsozDDjsMH35YeukH4Q8KbkRR8oMPAOzatQv77bcfAOuCVRQFy5Ytc2ycGhsbsXnzZnzwwQcF08+TyaSnPASDQSxYsAALFizAp59+imeeeQa33norxo0bh5kzZ2Lo0KGO+exob8P4CRO9nqpv3nrrLXz3u98tedyqVauwzz77OH7W3NwM0zSxefNmNDc3Z97fuHFjzuu+YOXKlTjkkEMwYsSI3fqezvZdOa/bd1mvBxcJMI899Bs86uO2pBtnn302Tj/9dHz66acYPHgwGhoaMH369Jzp9m689NJL+MUvfoGf/OQnjgG+rr4exxz3NZx+5lkFnw1qaAAA3HHv/UilUpn3hw4bikgkhBEjRmSe+9nYr+3f0X4Glw+NyPoHCm5EUdra2vDPf/4zc/tw69at+OCDDzBr1iwAwIwZM2CaJrq7u3HUUUc5foc9MsoeDW3ZsgXvvvsuDjjgAF/5GTt2LK677jr87ne/w4YNGzBz5kxMnToVy5YtQywWA2DdZvrkw//Djm1bceCUg/2esmcOOuggz7cl3Zg2bRpqa2vx4osvYv78+QCARCKBv/71r5lRSV/wxRdfYM2aNfj5z3++29/1v6/8BaeceW7m9d//8jIGDxmKYcObXDXfnDUbRx5zLEIKQ9DHbUkngsFg5vnUs88+C8555pmpG2+++SZ+/OMf44ILLsAll1zieMz06TOwacMn+MrEg1yDzfj9c+urmp7YM3PmTLz88su46qqrMiPwlStXYsSIEZk6fvTRR0NRFLzxxhuZZ56maWL16tU4/PDDPZ074R0KbkRRGhoacO2112LBggWZGXKNjY2Z4Nbc3Iw5c+bgmmuuwSWXXILJkydD0zR88skn+PTTT/HLX/4Szc3NaGpqwsKFC7FgwQL09PRg0aJFRRv9bK644gocdNBBmDhxIoLBIF566SWYpolDDz0UAHDRRRdh2bJl+N73vodTzr0QiXgcTz54D8aM3x9HHHdiv5VNbW0tJk+evFvfEQwGcemll+KBBx5AfX09mpub8dhjj4Fzju985zuZ4zZt2oSJEyfi5ZdfzkxO2bJlC9577z0AgK7rWL9+PV588UWEw2Ece+yxOemsXLkSiqLg5JNPdszH4w/djyce/g2e+8faknn+fNMGPHDHzTj+ayfio/fewf97bjkW/OQGx8kkNkOHDcPQYcOK3pYsRSwWw29+8xscdthhkGUZb775Jh577DHccsstGDRoUOa4n/70p1i9ejX+/Oc/AwA2bNiAK664As3NzfjGN76BNWvWZI5tbGzE6NGjAQCXX3EFzj/3XPz4ystx2rfORH1DA1p37MDq/7WexU071D0AXXLJJVixYgWuvfZazJ49G++99x5+//vf46abbsqc67Bhw3D++efjrrvughACY8aMwR/+8Ae0tLTg+9//vu/yIIpDwY0oysiRI3HZZZfhrrvuwpYtWzBp0iTceeedOQurf/7zn2Ps2LH44x//iEWLFqG2thb77bcfzj77bABWj/y+++7DzTffjB/+8IdoamrCZZddhrfeegvr1q0rmYeDDz4YK1euxNKlS8E5x3777YdFixZlAktjYyOefPJJ3H777bjz59dBUVUcMuNoXPLDazMTBiqZSy+9FJxzLFmyBB0dHZg0aRIee+wxDBkyJDN5wV5PmD1r7s0338QNN9yQef3iiy/ixRdfxMiRI/HXv/41J43nn38eM2bMQGP6+Vg+yWQS9YMaPOV37vyr8fZrf8fNN1yNYCCIC+ddhrPnnF9auJtIkoQPP/wQf/zjH5FMJrH//vvj3nvvLZjVyjnPLCsAgH/961/o7u7GRx99hPPOOy/n2DPPPBO33347AGDs2HF46Mmn8dD9i7DwFzdB0zQMHTYMhx4+A/vsO7po3saMGYOHH34Yt99+O+bNm4ehQ4fiuuuuK7hdeu211yISieDBBx9ER0cHJk6ciKVLl2YCLNF3MFFqBSiRQzn3x/dWzfXXX49169Zh+fLlFZc3Nz7eqWUmlHhlv0YVquxvyedAl8FNN92Em266qd/SmT3nAkw8+DDMufhy12O2b9uC788+Bf++8D4cdtSxqFEZIgF/5VbuyG0gylszOLpTDmsgiqBKDNGgt5msu5O3cjX5LFmV25mcNWX3nr/uaYYOjbp+Rou4iaqBC4GwwjLT6L3AACQNDt30HhFNLrAzbiCu+2sIBwIhBBI6h2bwks4lNoZh4NONn2D2ueeVPjiLmoAEn7ENskcLLxshBDSDI6F7P59yNABg+O0VAZAlqw4RlQfdlvRIvuuBlx5UX2iA0lOkv+wau0GPGwJhlSGsMiQNgZ6UKLoGKagAtQEJSUNAM00EZaAm4L5QWgjLWqolZkAIoC3OURtgaIqqGceQUufktQzyNV4a6ZTJEdM4rJBr+UFGg3LJgCLLMt56800IASRNgW3dBlJFgn1AZmhuUKGmexEmtyzOivUPZAZEA1LGn9LL9WBwgW7NzHxv0jQRDciZdJ0w0xrD1hgmaoMSAkVG5lb+TegcgLDqTKm8SQyoUSUEZH9r0AaqTfDK8rXb9vrRmxsU3Erg5gxQrJL1tabYReD0nX2lsZ9F9Hc6u6PRTYHulJm5FWkfE1KAoMIQ0wS0vFZXloC6gGT1urO+M+M8oTCE8m6daQbH1i4DmpkbMLtTArG2FIbWSGgMKwV5LHY++e8X0xR7P6dxzsJI21+F0kG71PcxBoQZMK5BRXvCRGuPmXOuI0eOwptr3kddSAbL1knAoJCMpMER13PLhwEZJ4/stIqVgRACPSkTSROAEBnbey6ATs1EQAZq8zohrhoAXRqHKnHUBnIDvRACcZ1bFmO2hln+nsV+n5DMUBOQCj6vlDaBsKDgVoRiFS/fFiff+mhv1DgdU6kayxDZRCqvMcvWMADRIBDmQLdmOdXXBBhCCsv53iwVBIAeQ1ijhKAMiQE7YgY6khzpPn1B/gSA1h6OjkQKI+tUhFXJtWHKP5/sRqqUJvt3tf8uaJxzRQCApAloCRPR9AimZDoAGkIy6kMyWroNdKc46kMShtcoYAwFI9veDoWEoGI5v2imQEACaoO5gdCtDGxSpjUKzJS1Q31ImQK70p2QsCpB5wLdGu8Nqk6doHSg96pxuoYUCYgG5HQMrLzrm8iFgpsLXnpGbhdoMV0la+zPK12jmxydGgeKNIDZGkUCGsIs571SmFygLZ4OasL2VXTXCQApLrClS8e4hoCn7V68BDU3Dec8x42lWBnY+evSOBpCzFPeJIlBAjAyqmRCeqktb+zAWBOQUJPW+CmDLi179FlMZ30WNwTihlnkuN3TZOfNDoqV2iZQgCuEgpsLfiqL3eh+2TV+yb5AveoZY+kH/86jqL5KB4zBMEVWYPMkyjwP6u/y5mC+Z4VKzN8ea4AV0Pzmze/MQcDKU1nzc5xGrH2sYYwhqPib4TnQ1ypRCM2WJIgiULNR2ZTz+1Tbb0qxzRkKbgRBEETVQcGNIAiCqDoouBEEQRBVBwU3giAIouqg4EYQBEFUHRTcXChneu2XXZO/Tqc/0kir4HUZwO6n41MhRBkz08vIW1m/p/9kymWgpqeXs7yrHI1A5V53tMTNGQpuRfBSyfIbdNJ4D3LlaoIyQ1DOvNFv6agSEM6sBPXS4AgkDIHWHgO8n8tAlhgiit2qeWsMGazF6X7SMbnlgsKFAPdRF5wW6ZfS1AUlH10WAQbLCst7I2blJShbC9n9aHSTZ/JaUpE+n7jOYXB/5ZYoQ0M4s1cEt/Xr12Pu3LmYOnUqjj76aNx77705+zWVgnOOWbNmYcKECQX7XLnh5hqQTbb9jf2vHE2phmBv1GR/5qSxG8ByNJIkIRpUMChU3BS4L9KpDcpoDEuZHZddUkJvgGHYleDYsCuFWIq7NlLZZeo3b7YmEpDRGJYz5r2OgT79XlhhaAjLUGQpJx2ntLIb5/akiYQh0J4wkUzvNFBMY+ct+/9eNQFZQmNYRlgpfT5B2Tqf2qCCBo+agMzQGJYRDSpoCMmeOgeqZGnCqlzyfOzPUqbIlFunxhFLmUU7O1wI6GlNPKMp3qHIrztEIRXvUNLZ2YkLL7wQ++23Hx544AF89tlnWLhwITjnuPrqqz19xx//+Eds377dd9pOlTnbEcDN982vJvuYvtIUy1+1aBSJ5Rn2WrcrvaQDwHM6ssQwKCxDM/L8CAssgnsxOPBFl4EalWFEVIUsWc4d5eTN6bWNxBjqgkqBgbSNKrMCw+D877WDOWA1tIYpENN5zncJAHFdQDNM1AYkKFLpvBVLx03DGENNQEZIyXX3t5ElhmhQztmFIVvjZCAtSaxgNwG7cxBSrXQKNLB2VMjfgcDt+raCFxBLceh5P0LKBNoTZoGBNBcCEEBM5wW7MKRMq0MRVhnCWZpSbQLRS8WP3J555hlomobFixfjqKOOwnnnnYcrrrgCjz/+OGKxWEl9Z2cnfv3rX+Oqq64qOw9OvepSlWtPa4rpqknDGENYldEQlhG0ra88pGNr/eQtqDAMjkhZtyozqblqenSBDbtSaIsbvnrbTkGhmEaVWc5ohAGoC0qoDylFR7fZ6fC0mXBXirtae5kC6NQ4ujXTc97sdJw6L25YHQoF0UDvrcoaxerMuG0vJEsM9SEl5/ZmRLHKxW2bHIlZmvqgnGkM7VFusa118utpIj3KzQ9sNgJWXehIWlv42JpdSdN1eyG7Q9GRNGFwMkr2S8UHt1deeQVHH300amtrM++deuqpSCaTeOutt0rq7733XkybNg1HHHHEbucl/3YLaSpHIzGGaFCxxf2WDmMMtZmG0JtGANgZ50ga5fl1+slbJCCjMSSlb1d6u7wZY4ilTOwq0jjnk+JAQue+G1q/5xRUrHNpDEkIO2zb44R9e7MxJCHiUaOmb3M2hiTH7YHc0Lm1Q0Eif4jpgimAjqSJtrjhS2PtlECBzQ8VH9w2btyI5ubmnPdGjhyJcDiMjRs3FtV+9NFHWL58Oa677rr+zCJRQQzUpV/JbYyXkdTeRDnnM1AagPwtK5WKD25dXV2IRqMF79fV1aGrq6uo9he/+AXOP/98jBkzpr+yRxAEQVQgFT+hBHAeimc/nHbi+eefx6ZNm/Dggw/2Z9YIgiDDoeLkAAAgAElEQVSICqTiR251dXXo7u4ueD8WizmO6ABA13XccccdmDdvHjjn6Orqykw+SSQSniaiEARBEHsvFT9ya25uLni2tm3bNsTj8YJncTaJRAItLS247bbbcNttt+V8dvXVV2P06NF4+eWX+y3PBEEQxJ6l4oPbzJkzsXTpUsRiscyMyZUrVyIUCuHwww931EQiETz55JM57+3cuRPXXHMNrrnmGsyYMaPf800QBEHsOSo+uM2ZMwe//e1vceWVV2LevHn4/PPPsXjxYlx44YU5ywNOPPFEHHbYYbj11luhKAqmT5+e8z1ffPEFAOCAAw7A1KlTy8pLOVY3A60p9Swy+/i4zqEZAiGFIaxKnnV+00no1jT4oMIQ6ad07GMHhWRoBkfc4zTrgMxQo/rXjGtQEUtx7OgpXDjtRI3KEJSZr/Ox8VMfEjrHtm4dqsTQFFWLrtWyMbhAyoTl5OExbwYX2BYzITMTI6MKAoq3Jxx+67bJRdrhAwWLt/synXI1MrPW0Tkt3naCAYioDAHZnyaksAGbCVwtVHxwq6+vx+OPP46bb74Zl112Gerq6jB37lxceeWVOceZpgnOucu37B75rhJeFlOWo8nW7Y6mVAOaMnmO00bcENBMs2Tj4TedfNeMhGE5XDg5P+xOOtkaWWIIqRJCirPzg43EgGhAgiwxSCytUa31RMU0taoERWbpxb8MdUEZLTEdXZqzRpGAploFNQEp41Dip/5kl0GxcjC4wPaYjm7NcmrRTGDDrhSGRCQMjiiOOi4EelImtHRgE1bCRfNmaTiSBmDbjm1s19EQljC0RoHkossPHKXKwO58JQyRyVNH0kRQBmoCcp+lk6/xe31LzDquLighZQr06O4L4AMyUBuQMyYD0aDk6AaTq2GoDZBDSTkwUU535UuEW2UqZqNUqRqTW8HGcOoDpHvtTo2H33S4sHrbxUYDqmT1xJ3S6YtztfPh1HiE0yNIN41VTv40miGwtdvICYyN6QafOWj8ns9NN92En//85wXvC2HZNLX2mHD6WRkAWQJGRVVE0o2kEKLAsqxU3oQQ0EyBmOasYbAa+hFRBdGMq7W3c81/P7/zlYsAA8tYWeXnsVg6fvKwO5qeFEcyqx7IDKjN6kg5aTKB3IfGKQ+lWLJqXcF7s6aM8PUdlcTQoc6TCoG9YOS2p/DjAWj3qCtVAyC3F+x0QaTf00yBVNoHLyj3Lmr1ko7VaIr07b10A+hy8dnODhGFWbdcSjhXOFk3lerFSoxBlYEGWUZc5zCFNfICK65hEtAQktOu7lYjI5XQhBRgXIOKjoSJmM7RVKtAYYUN0+6cT74maQhs7dKhc/dFwQKWz+VnnTpqAgzDapRMWaS/1TEdoPcaMAXQrfGsTpHD0pz0cVu6DIQVEyPqVKT7AkXPJzsdLuDoDZmnylhZJdN3AeybAF7SGYjrLhKQEBZAd8pEUM71k3TV2HcbUhyKBNeOlFveiEIouBXBS6XJv0ArUdOtGdatJ+vNUioIWA2NV8cG+5hEznOr0ukAVoPoNx0/F3V245H9uj80DMCgkOVz2d/nkzI4NnfojqMoJwSAnpRAl2JaR3tMi3OO9kRWZ8VDOnFDQCkR2PLTEcLyUBQ+nvuZXGRy5Ccdv9eQX43EGMCA+vQI1ms6MrP8QP1oAH/Ppb9MVPw6tz1FOZWlUjXl3HguNlLp63T8UqnlDFgO9AORTtYYwkc6+X/4EnnXID0C9pEOY1anym/emM96WuoOQV9p8rX9qaEHS85QcCMIgiCqDgpuBEEQRNVBwY0gCIKoOii4EQRBEFUHBTeCIAii6qDgRhAEQVQdFNxc8GPcku2DWIkaWWLwu/evKfx77ZUzrd/F6aooA1V2nA9sOtyHpne2uI8CFAV/lJYIay2Zv7ogYHDh63yEEJCY/3Q4r9zrbqA0tMTNGQpuRchevFnsGMDZFaQSNKZA2hKKedIAVqUIylLBAtZi6QghEFZl1AUlz5WKARl3Ej/pZC/69qoBChfCu2FbcLX0GNjYriNplG6ohRBp2zGO9qQJ3UPjbmta4wY27EohrvNMoCt1PilToCEsQfXYo2AABoUlNIRlTxo7bx1Jjra4Ac3gVrkVPSd7sbfla9mZNMFL/K69zja9dmde62lAYpAk75pKv1Z3V0PkQg4lLpRyj3CqWH2hyf/cyfLHi8ZypODQzFy9u9uCFQAjeTsEFNM45S0gS2gIM3e7r/TrUNrDstx0+ksjAHQlTWzPcvv/tENHXZChqVYFY3D0+tNMy1DYTrVL4zmmt/ka24C4JWZkbK0+7zRQG5AwolaBJDlr9CxzXlliGBSWkTIFujVn8127AzGyTkUg7VNVH5IsU2vN2Y/SySszpgskTRO1ARkynBwxcp1puABaYibaExwj6xQEpMIF7lyIjOWWXQZeXFss0+tC8+2BvlYrqU0gCqHgVoJivX2vnnl+Nfk6rxq74c5vaEtpAECVmNVwOfTq3dJxyxtjDDUBGSFFFHgFKhKz/AD7IJ2+0lh/W36XW7sNJB22vunSBGKpFIbWyBgUspzdRVrnZkadMnv9M8OqbVps3Yrd2q0jrhemE0txrN+VwpCIjMaInPEF4cIKYE5bpARkhsawhHiKI55262dgGSPj2kDhNkOqzNAQlpHQ05ZpQoCn89cSM9ClFZ6QwS1n/pDCUGNbk2X+k/NHBs0U2NSuoz4oYXitgrQzlWPnK5vCToj1/fmdr3wNMLDX6kBpvLYJRC8U3DzipdHckxrOrYbPNvv1ogGQMWkNyKVvJvr1spMlhvqQgpTJEdc5woqEgFzalqkcz7z8xsOPN188xdGpmehIFi84LoDtMRMdCY5RdQp0U+S4v7thbykUkBl6UhxtieLpCACtcRMdSROj6hRwYZkkF9v7izGGmqCMkGqZV4cUVnQLGlsTCcgIKtZ2ObEUR2u89P50yfTWRXVB+7Zo6bLu1Di6UymMjCpQJKR3JCiO/ftIAJT0djHFzidbV8nX6kBoCApuvsiuZJWmEWDoyrgje0wHlrlrf18wAdlqBAfqwvSbzpZu3VOHwEYzBdqTpueNM4H0aK3LgMf9UAEAOgfaE6bnjUABq0MxvFbOONF71cRSHNt7vNcfAWukq3roFNlwAWskq/qrC4H0SNGPppKv1YHSfNmhCSUEQRBE1UEjN4IgiC8xy9duc3x/b97EFKCRG0EQBFGFUHAjCIIgqg4KbgRBEETVQcGtAhHCsi/yi1yhs4RtBwo/s73sMvCr8ZsOUJ5tWDloBodZxu/ql3JOR2L+648qMd8aIYTvMqjQak1UODShxAe9C369r7/yq0mZHN2atQBblbjrwup8JAYMCsnQuWUBVar9UCTL5cFP3uxj/WiSBsfWLh2aCQQkYGSdmlnQ7IbBLfcMU7i7UeSTMgW2dulIGAKKBIyMqqgJFE/H5NYi87qgBC6A7hSHXmI2vMSA2oDVqHv/TQU2tKWwM26CMWBErYJosPjUdgagJsCgyt5t0xiAiMoQkL2vixJCoCdloj4koy4kY0fMQHuJ9X4MwOh6BaPqAmAMaO0xsKvE2r10akgYDAlDIKyYqHFYXJ5PSGaIZBbAeyvv7LLqT022rhI1X3YouHmgmO+bW0Xzq7Eb2mw3Dz29niqsWBe4ky7/O1UJaAjJvfZXeTAANaqEoMLKOh/7GC/nsyNmoFPjEGlrrxQX2Nyhoy7tVpEftO2GNmkiY9PFBdCpmQi4LOLlQmBnunG1c2hw4PNOHTUqQ1NUdbRpyrYHY8wKVvVBCSlTIJYSjp2DsIJMwPSyaFwIK+Bu6jAgRK+jydZuA6EEw4iogqDDerSgAstVJO97izVsttVXtqaYhZUQIn2u1u/DGAMDMKxGQWPYcmpxqj8NIRkHDA5Alljm9xsaUdAQBra5uK6kU8x5lTAAzeSIBiQElML82Z0vxrydT/Z5wWMZlNJkv7c3aQgLCm5FcPNwK3bh+NXkN7TIrrDpvxNpR4jaYK+TSKl0IqqEkGLZOdnOFkGZWb3lfj6fLs3yTLQb9N4bSwwCvW4VwyIyBoWt0WN2Qwuw3HJAoZUVYwwxzcTWbgNc5Ded1uuYLrBhVwpDIxIaIwoYY0iZHDGN93oq5p1TQAYawww9OkdCt95XJFiG0KywQXEL9N2aiY9aU9DMwkApYP2mm9p1NISljJOILAF1AQmy5JxO9u9hv5aZFQhliRUEfre8memRcW/s6tVJEkNAYhg9SEW3ZmJ7zBpBB2WG/QcHUOdgnSZJDAEA+9ar1mLwLL/MfM/JbKyOC4eqA9GgdQ5Ona9SZZD9Xv77u6vZ3ethIDVELhTcXPDSO8pvPLLfL6axv1/nwrWhzYfDMuMNytatSi/pyMxqlHVTQJIsr8FSdkx23so6H1NgS5cBzSxtrcQFsL3HspiqD8tZAcAtLev9uCEQNwzENMtmqlQ6lpUVR3syhcaIXPJ2rX0+NaqEsGIFArWEZVh2GZic45M2HTs92FgJAO0Jjs5kCpObgojmjQqLpSOEsPKoetdwbnWiHDtSeUiMoS4oIxqQYXJgWK0ChkLz43xNNCChtjGAzR2pLI/O4g2wzgV2JTiGRiQ0RJSCzpfTOZVz3VWyBij/uit17JcVCm4ueK0s2ZXMrz1QXHd2ZS9GQPZvQ6TKvX971fi9aBhj6NRMT16LNgJW+2pyf2WX0IXjLbNi6UiM+UrH7hw4jdaKabqT3FNgy85bWPVnL8WY1VFxMxB201gjxoz9vicNY8DQGu8WbYwxQAgkDcD7VBDruMZIcS/MgnRQvv9opWlsXbkaohCaLbknGcA6WU7PbmB6g+Wm4b/wBqq4yyhp33lj8H8+5bSBNB6ofCi2OUPBjSAIgqg6KLgRBEEQVQcFN4IgCKLqoOBGEARBFOC2W8DeAgU3giAIoupwXQpwxx13lPWFc+fOxfDhw8vO0JeKMqa80ew1m3LmJFYu5eStks+HGDhoiZszrsHt0Ucf9f1ljDGceuqpVRHc/KzzyvZ986MJyixtkJx25fCAZgqocv/nza+GC4GaAENbHL0uIyVgsHwkGfNzA0EgIDPITDg6k7hpdC7AhQwJ/rwGuYBnDYRATUBCRGWI6wJelvwxWIbKvqZzCwETzFfehBBgEJAAmB7XUglh/ZIJnSOkSp7XoHEhEFaQXovoveXtSloel4D3empygbRpT8VdD1wIpJeY9nveiEKKLuJetmwZpkyZ4umLTNP0fOzeQLbTQCnfN/t4+z2vmrAqI6hYVkh60dXcViORbT21O3nLfq+vNIm0hdjgiISeFEfC6M230/kwMNSHJAyrUSAxuFuQ9SYEMGZZiIVlDKsBdsYNtMV5kQDX+wkXDLsS3NEf0umcsj0mQ2lNKecMVWZoCMv4+vhafNqewns7NHAO14X6MgMawjIOGRlGRGWFFmQuKBJDbZYNVqnGkKeDQCxlueF4WaQvhBWcuzWOnXGOiMowMqpaC9tdXEo4tzoR27qN9O+ffWuimLOJZb9lCMtHtDZgdULcgqkQ1u9iW8v1WpC5O/C42W95uYb8agSAWMpEyrTOrUaVEJCLl7VNOe0IuZM44xrcotEoAoEAZFl2OyQHxhii0ajn4/cG3CxuilUsvxqJMdSHlELPwyxUiSEazDUN9uKZVyxvbl52fjTZjaY9SmHManhDqkC3xrM8BtOfwzL5HVmnIpRlGlwTkBFS8j0Pe5Ekyw5KyWpYh9aoGBQSGcPeXJlzo2ob9tYGWEGDYzea3RrP6WwkDWt0VRtgCCoOZQSrcbZ9PwFgXGMQo+oDeK8lic+79BzHEolZAWrayBBGRtXM+0HF2gWgJ2VCyzKPts+HwWrEA3l2YPmWTzm/GXob2pw8l9D0pHjaZcQirgus35VCY9oLkzlodvQ47ShgB7j838PusAGRrN0BDA50JE1HH1Q7r/mm4Gbao9I213bSZJ9j/uu+vL6TBs+pi/ZuE6pkGVtnO96Uk47be0QhrsFt9erVvr5IkiTfmr0FJ7+4UhXLryYgS2gIs5wLVwIQDRbf7mUg8uaksRpNjpTLvTdFYhgUkqCZAjHNvhiBYTUyBoWc7ZxkiaE+JGeNYCyyR6z5qDLD6EEBxFLW1jpWdoqPFrgAujQBVRKIpg2RAWSNOAsRALpTlu1XNChBTjdSxXZsCMgMh4wKo7kxgLe3JBDXrXMa36jiwKGhnEBtIzGGaFBBOGvbHwCQmTUqdBuZOI208xtaLxrNsEasbppdCY4uLYWmWiUzAo6lOFq6jSK3YbMDmhXUrA6b5Lqdk2YKpBJm2kTZUhmmQEx3384pZQLtCRMRleV0nAbierBGuaZrGeg8d4eP/swbYUHekh4ZCI85xlhmBKObHEHFm3fgQHrmCSEyQa3U3X7GGEIKQ0AWCKRHn6X2pmOMIahYe5JpBkdA8faspzYgYb/BAazbmUqPcUqjc6uxDsrW3178IA1umR3vW6cgrLo3ztlYtyprsKVLR31IRjRY+u6G1TmwAr0sMQQ9lgNj1sgvZXp75perQcFI2wmDA190GYioDELAh88nQ1C2RqhOW/3kIwDEdJ7eAgmOI3onTY8uwAV37XQ45qzM6yFlciQN4drJyydhCJjCdNy+qS/zRnhcCvDWW2/h2Wefdfzsueeeq9oR257CbswqtSJ7cf3Pxrr16m3TVRsryHmfxGCnU06ROW1LUwpVZr7PZ1Sd6imwZWsCMnMc4RXD4N4Dm43JvQW2bNz2DCyGLFnn5AeDI7Ntk1e8TzbafbwGNpsB2IydgMfgdu+992LLli2On23ZsgWLFi3q00wRBEEQxO7gKbh98sknmDx5suNnkydPxrp16/o0UwRBEASxO3gKbpqmuX4mhEAikeizDBEEQRDE7uIpuI0ZMwavvvqq42evvvoqRo8e3aeZIgiCIIjdwVNwmzVrFpYtW4aHH34Y3d3dAIDu7m489NBDWLZsGWbNmtWvmSQIgiAIP3haCvDd734Xa9aswV133YW7774boVAIyWQSQgiccsopuOiii/o7n0QFEVElJA339Ub5mFxge8xAQ1j2NAV8dxgakdGpWdOzvRDXOf7VksDYQQGMyFpQXYq2uIH6UO9ar1KYXKAtbiCiSqj1OGNSNwX+1ZLA4Iji2WaJC2vxPBgQzFvsXSxvH+zQIEvAmEEBz7ZPyfT0ypCPmb0p07IBc1u36JaWX2RpYLw3GYCwwpA0vM8g5gKIp0xEfCwH2FO47Qwwa8qIAc6JfzwFN0mScM899+CNN97AK6+8go6ODjQ2NuKYY47BjBkz+juPFUH2BebVIaBaNWGFIazIJaeCCyFyFkZ3JDkGhSQMq1WKXtS7k7eGsIxBYRldSRM7etwX1XIh8P6OJN78IgEugPe3axgzSMVRY2pyFtk6pAQA6NQEujQdEZVhRFR1XWgvhEBn0sT2HhNCWOvqwqqJkSU0m9p1vLq5J+29CXy8U0NnlveiE92aiW1Zi6kT6UXqxZYSfNGp4y8be6ClG+dP2nQcNiqMQWH3dHRToDtlZjo3ScNat1XMbCB9ZjA4YHCGhMFRF5RKavLrQql6YFtxKVnWZH49Gv1oFMlaqhFWLRMArcSyANvWLCkALWEiojCESgT6cq4HAmBiL3DeXL9+PW655RasWbMG0WgUs2fPxg9+8IOiVl9r167FsmXL8Pbbb2PHjh1oamrC6aefjnnz5iEYDHpO280ZwK9H496scfvcck6w7IXy1yFphjWCyK9cDJb9VFNUQTRQeFEXsxsqdU751mBCANt7DHTmWUJtjxn4y8YYevRcezCJWf+m7xPGQcNCDgHY2fmEARgSkTA4ouTkQTM4tnTpSJmFa64YgMawhCE1uYG+I2ni75tiaEuYOXlb8dBCnPH96zBpeBCHjIzkBKyUaVmQJRwtyBhCitXgZ+ctluL4+6YebO02Cta3yQwYPUjFlOGhnODDhXC08rIJypaNmnu52WfeS0BG2iXGuR4AHq3lkO50qYW+oQN1DTnZ0ZXSAFZ5R/Os5crNWymWrOqbme2VMnIbOjTq+pkvh5LXXnsNb731Ftrb23H55ZdjxIgRWLt2LfbZZx80Njbudkad6OzsxIUXXoj99tsPDzzwAD777DMsXLgQnHNcffXVrroXXngBn332GebNm4cxY8bg448/xr333ouPP/4Y9913n6e0i1WiYt58laBxOqY/NIylTW/T1ki6KQq8GbMRsKyKtnYZCCoMo6IKAorkOW/ZvepiGokxgAFNNQoawwJbuw10JEy8/lkPNnboMB3yx4X1780vEvi/7RpOaK7F8FoFxRpn+5x2xjk6kimMjKoIKgw70kHVzQRZwBrFdWopjIiqCMkMb2+N4/0dmusCZFMA/7ddw7qdKcwcW4N961Xs7DGwK+FmHm2lmzQENIOnbcME/tWi4Z/bkjC5ezqbO3R80anjq01B7FuvImkKxPXi/WDNtEYjNWn7q9yfxbkhTpkCbXGOGhWZwJRReLweArLl2+hHA/T9dScxBiYBg0IyEjpHPH1Xo1QwMrlI+2n2dg7KyRuRi6fglkgkMH/+fLzxxhuZgjz33HMxYsQIPProo2hqasL111/fLxl85plnoGkaFi9ejNraWhx11FGIxWJYvHgx5s2bh9raWkfdvHnzcgLu9OnTEQwG8bOf/QxbtmzBqFGjiqbr5daEkzdfOZpSunI09ucDoZEYgyoDqsmwPZb2SirxxEPA8j5siRnYt17tv7xJDEFmjRCWvdcJ04N7h8EtI96/fRrDWRPrYT0mLH0+Ogc2d+o5TorFdCKd1qZdKbyzLeEpb6awLJz+timWGcGVvvViHdOeMPHyhhiShijpRmIH+n9u0yBLrCDwFKNHF1BlQGFW2qXyZmlgaSR/11A0YN3aLPXsqq+uVa+akCrBFCY008MtzvTnmikg6TxzW9xPm0ABrhBPNfauu+7C+++/j/vuuw9vv/12TuNy1FFH4fXXX++3DL7yyis4+uijc4LYqaeeimQyibfeestV5zSSPPDAAwEAbW1tJdP1U1nsY8vV+PW/q1RN7yQOr+XQ6zHoJx2/5c0YQ0u3FXT9OCXVBeR0XffXcAj4sydLGNxTYMvGbsz9pJMyBRJ66cCWT0DxEkBzsW6x+Ss3L4EtG8aYp8CWr8n+f39pJMbS5eynDFhmxwc/dbvyHyztGTwFt5deegkLFizAiSeeiFAolPPZyJEjsW2b84yavmDjxo1obm4uSDMcDmPjxo2+vuvdd9+FJEkF30d8OaC+LVHpUJzqOzwFt46ODowfP97181Qq1WcZyqerqwvRaOFDw7q6OnR1dXn+ntbWVjz44IP41re+5XorkyAIgqgOPAW3ESNG4IMPPnD87P333+93hxK3GUteh+6pVApXXXUVIpEIbrjhhr7OHkEQBFFheApup5xyCpYsWYI33ngj8x5jDB9//DGeeOIJnH766f2Wwbq6uowrSjaxWMxxRJePEALXXXcd1q9fj4ceegj19fX9kU2CIAiigvA0W3L+/Pn45z//iYsvvhiDBw8GAFx++eXYuXMnDjnkkH51KGlubi54trZt2zbE43FPz85uvfVWrFq1Co8++mjRW6sEQRBE9eApuAWDQTz++ONYsWIFXnnlFezcuRMNDQ2YOXMmzjjjjKKLqXeXmTNnYunSpYjFYplnZStXrkQoFMLhhx9eVLtkyRI89dRTuOeee3DooYf2Wx4JgiCIysLzIm5ZlnHGGWfgjDPO6M/8FDBnzhz89re/xZVXXol58+bh888/x+LFi3HhhRfmTAw58cQTcdhhh+HWW28FAKxYsQJ33303Zs2aheHDh2PNmjWZY0ePHl1y0Xk5a0e+7JpyZiOWY5BTrteg3x2QeZllBmSWLnlCgv9Zclz4SwOwVrv5LYNyZ++VVd9Qfh2q2OtB+P+hfKdD04Ad8RTcYrEYUqlUTkD47//+b3z00UeYOXMmjjjiiH7LYH19PR5//HHcfPPNuOyyy1BXV4e5c+fiyiuvzDnONE1w3ruA57XXXgMALF++HMuXL8859rbbbvO0k4GXSpbf0FaSxragaonpCMoMDWEFchGfQbd0gOJrfDKekyoQkoGkCZRuqgQYWCaPmSXPHspBMwU4F45WS06YXGCfqIKvDAngg9aUqwNINko6GBqcQ5HsR9MlypsLJE2BnpRpWXF5PJ+ADDTVyGhJ+0+WyhsDYHCBLV06RkZVSMxbGegciAQYelICDN7SYQA+7dAxul5N25OVrnMmBz5p0zBmUACqxCCVqHOZczIBVfZeDwCgS7N8LWX033UnACR0EwFZ8rQWL7uDY1VtD8EqHQQNU0CVWFltApGLJ2/JK6+8EtFoNDMqeuKJJ3DbbbdBSl/0ixcvxgknnNC/Od0DlONpWOz9gdRYHncm1rWlMour64ISJgwJQpWYY5ArJx0urEDTneWnZ1twuS1KZrCCx6g6Ncf5olQ6lo9lr+eixIBoQIIsOS/kNbmAwQXWtWnoSPtL9qQ43tmaQFvc2VRZYYAqMxw3rgZjBgWySyEr9w5lIICWbgPdKSsdmVn+mbWBQt9E+1wFgJ6UCS3t1WhwgR0xHV1a4SLwFQ8txDcvvQ4AEMnYWzFIDBhWI6M+JDsGUztva1uS2NiuF56wCwxATYAhoqYXFQMYEpHRGJGtWWgOdUQAaOsx0ZYwM12bfetU7FPvFoCto8IKUJPlfVnsunP7LFjEgquUR2MxTdLgiGd5dgYkoDboXNa2TjMtw3CR975TOjaqBCtIS4X589MmlKKvvCW90t8elMW8JT3Nlnzvvfdw9NFHZ14/9dRTOOecc7B27VqccsopWLp06e7nsgLJdgrItuDJtrxx837bUxqTC+imwMc7NazdruVs/dKlcby9JYHNHSmYXIDnpZP9nV7yxoU1SunIC2SqzNAQllCj2qEgqxEBMLRGwvjGgKuXoFMZxFMc7clcM2EuLJusWO7LoesAACAASURBVIqnG3GRft8ysP28M4XVWxKZwAZYjejMsTWYvm8YQZnB9gVmsALS5OFBXDB1UF5gs4+wxzu5ZdCRMLG+LZUJbIBlk7Wly8BnnTpSJs/kDenzSRoc7YnewAZYrh4j6wIYM0hFQC4MowGZoSEsI6zKmbLiAmiJmfi0XbdGtFkNtsEFtnYZeGFdzHNgY7AMkAdHpNyAA6A1bmJju464kZsOFwJxnWPDrhR2pgObrfmsS8c7WxPoTJow8+6JKhJDY9jaAii73uVfdzbZdTS/nmqmwK6EZXflVeN2fXNhucV0aiZ68syoU9yyMUsavFDDBTo1E7GUg2G4QzqA1QDXBSXUhwrvqpTTJhC9eLotuWvXLgwbNgwAsGXLlsxzL0VRcOaZZ+JHP/pRv2ZyTzPQvnTlaLgQgLDc4Td36q7PVgSALd0GWuMm9m8MoCG9tYnndLjVuOf3aJ2OjwRkhFSBmMahmUA0wNAUVYtuwZJfBilToEcvvndcKt2wRdKu8J1JE5+0pYpuPzIyqmL4AQo+aE1i3U4dTbUKjhtXU3RLmXQOAdgByjJkThVJJ6ELbNilozEsY1iNDDNvlOtEWJXQ3BBAe8LAjh4OiVkjk2iRfeA009ompz4kYViNgqTBsXpLEm1xFwt/ByRmNbRBxf330U2BzR06ogEJTVEFEMDWmIGelLunl2YKvLdDQ0NYxoFDglAkhmhQsgJ4kXqXH+BK3qaDtdtBUgKiARl2NfN7DZXaukbA8s9MGmb6zgEQT3EkS/in9eYjfRtfYYiU2O6mnDaBsPAU3GpqajJrzVavXo26ujpMmDABgDXRRNO0/sthBWH5uPl92DswmpQp8O62hGffwJQp8HGbhumjIp6eifTmDWhL+GkwGepCMhpCEmTJu/kuYww744bn4wEgbgj8a3vccxnIEsPk4WEcuW9NxtPPY+6wqV3LGXWVYlfChBACSsk9z9IpMIbGiAoGAzpHyWelNp1Jjve396BT82cgWRdAyX3FsulOcXS3+XMmak+YaEsYOHBIwGedYzmjnVIY3NqEtsbllrAb1j513svNFECHxn1fqzJjqAv6vx7IINkfnoLbpEmT8PTTT2P06NF4+umnceSRR2Y+++KLLzB06NB+yyDhHb8z4QaSgdpxuJwyUCT/t3gGqqit20/+NOXkbSBvc33ZG2jmYQIQsft46josWLAAa9euxWmnnYbNmzfj8ssvz3y2atUqTJkypd8ySBAEQRB+8TxyW7VqFTZs2IBx48ahrq4u89ns2bMxduzY/sofQRAEQfjG8yLu2tpaTJ06teD9r33ta32aIYIgCILYXTzdlnz66adx5513On52991345lnnunTTBEEQRDE7uApuC1btgxNTU2OnzU1NWHZsmV9mimCIAiC2B08BbcvvvjC1VG/ubkZn3/+eZ9mqlIZKB/E7AWbXlElhsNGRdBU683EWmLAvvWqZRHkMR2RXrTtN28hpXBBbjG4EFi3M4nXP4tj4y6tYPFvsfyNbwxgeE3vGqdS1AcZhtbIqFWZJ19DIQS6kiZSPpYB2HQkOTqTZnqtYGna4iY+aNWwuUP3XAYdCROfd6bQmTQ8awCgSxPYFTdheNTopkBb3ERb3IRRYn2XTV1QwrhBquc8AUC3ZuJvm2L4nw092OVjaUjKFOhImtA95g2wrqGGkAzVY+VhsBxyGsMKAl6XeAAIK5JvD81y2oQvO56euUmShM7OTsfPOjo6qr7A8216/Pgt7q7Gq8ecxKy1UM0NQYyMcqxrSyHmsmZncFjGfoMDkNPTv72kkzI5urVCS6FiGlWyLJHsqc9e0mmLG3h7SwJJw3KJ2NptYnssgQOGBDA44l5d7bJTJIZBYcuOalvMQLfLeq+gzDAyajVKksQQUoGgyhBLcWgubahmcGzrNnJcX/wgAKRMoC3BUaNai7WdyiJpcKzbmUJH0lq8rpscuxImWnsMDInIjhrN4FjflsKupGmZKgNoT/YubPeyAFrnQFucI6Ii/bs5W43FNI5EVhm1JTjCClAbdF5XpkjApGFBjBkUyHQ6Sl0PBhf4YIdlGWbH21c3xzEiqmBqUwhBxblfngkCABgYOjUTqgREg7LrcpRsL0gpvQatlHlASGaoybL7igYk6Fyk3XKcNcG0xrbu6s82gfAY3CZOnIhnn30WJ598csFn//Vf/4WJEyf2ecYqBacKmF3J8j/b0xpZslwPpgwPobVHx6YOPbOoOaQw7D84gGieh10xJwjbo1LPixHFNAxW45i/MLqYRjM41rQk0dJt5Lh3cGH9+7A1hWjAwAFDAo5+lNnfJzEGMGBkrYJkWGBblouIxIChNTIG5Xkx2v6JtQEJYQU53phcCLT2GGhPFNoqlUtct4JYNChBlXsdMj7v1LG5w4AQyLGxEgB2xk20J0yMqlMzDasQloHypg69QAMACUMgaZrp38PbouGEDiR1jmhIQlDurYcJXSCWci6BpGGdT12QIaj0/u771Cn46ogwZFa4EN2pbgth/V7/3JaAyXPXLZoC2NploCUWw6RhQYxrCDh6ReZfJzrPdbAppWGMISADAVlGj85zOjNK2v0kf60aYwyqBDSEZMR1jkSepjbtmCL1c5tA9OIpuF188cW4/PLLMW/ePJx77rloampCS0sLnnnmGbz22mu4//77+zufA06pypNvi5PvouDFo7E/NTIDhtWoGFKjYuMuDSGFYVRdINM7dTsnOx0hBBKG9Q9CFBjlOmkA65ZLjYuBrVs6m9p1/N8Orahbv+0j+c7WJEZFFYwZpOQEJickiSHMgHENquU7aAg01SpFy0BiDEwSaAhLSOgcLTET27oNTzsJ+EEg7XCR5AjKVgO8bmcKOndfiG4Hetv+KhJgWL8rBd1038pGwPr5ujUOVeKoyevYuGoAdCU5VBkIq9ZOAiZ3LwP7/S5NQNEFRtUrmL5PGHVB2dVuLb9u9+gC72xJoCPpbGoNABwA58B72zVs2KXjsH3CqA+W2h3Cej+eDvTRgAx74Ffq+o6oVmenJ8URkHMDdzFNKK1RZSCkuOevr9oEohBPwe3444/HjTfeiDvvvBP/+Mc/AFgFG4lE8LOf/awqdwQAvPWK/PrfDaRGkhgkAPsNDlqvfaST0/ssobM19q0aP+ezqT2F/9uhFfVazIYLy6sQHh017BFZY9jdyd0tbynT8o7sb+eXLo1jwy7dc/AUADqSJjZ2eH/wZ9929OF6lbmNWsw70y2dE8fXQvboxGE36H/dGINRJIBmYwrLAsx+1uW1gc/eB8/TNZS+CxAtGUB7sTuXfjVA+W1CpQa45Wu3lTymv3YO8LzO7YILLsC3vvUtvPPOO2hvb0dDQwMOOeSQnA1Dq4lyKkularw26tmU8xxVKsPGyigyUnFDZsx+qOI9b8yfPyFgNaAD0WRwYQUdHzEEHPC0J1s2A9n+FTPHdoIxBrOM0bFaRp0r53pABWuK3Fj5UlMyuKVSKdxyyy0488wzMW3aNBx77LEDkS+CIAiCKJuST5gDgQBWrFgBw/Dn0E4QBEEQewpP06cmTZqEjz76qL/zQhAEQRB9gqfgdv311+OJJ57Aiy++CF33vlU9QRAEQewJ/j97bx4k2VHeaz+ZZ6mtq/eeGfXMaJlFQqvFIlkgCbEYw7UsMDayiU8f4jokXRZLEYbAYAwBDriXxcZhQwhsXbDB2OHLIvNdGwtkMGBkxCIEEkIgjTSLZkYzPUvvtVedk/n9capqaq9zarpbrZ58IhSarqpfZZ5TefLNPCffX4ZaUHLrrbdSLBZ529vehhCC4eHhttyL73//+6tWSYPBYDAYohAquF1zzTXrdqmpwbAR2NgePwbD2hMquHXbEWAjEyV3pNH3baNogpy4iEvnVfSk0pQb7DQdZZV+0VMgVv88WNXl6ZHzDgZARSxHKx+ldfDpkMfj+wqlJZIoy811w1LzcBopggTmhCNC78CutCZZTRYP2xQEkC0rRuKdbb86obXG1xqhw+8Ov96vVTPv6Ew4P54zlEbnjV6fgXbXgLCaVoePbiit8VRgBpspK5TWqFUqx9dQVqcutDD5YVIETgyhy1Gaiq/xFJw94uBa/btOAVgChmIWi0UVOGaEOAe1zqI1UbYbvtIUPcWPjxR4Yq5Evtz/XA+C0sE5ePBIgQeezjOf72+qrLWm4nn85Jf7+Pp/fp+jx0/i+32SubXG9xVPPH2SL/zXL9l/bB7PV/QbvGityVcCX8uiF74dTKctnloos1AIAnAvna6248Wiz/YRh/FEOFNhQWDEfHS5wmzO61tOrSwIkubzZbUm1/cgmrDXkLHg6k3oJG6Affv2sX//forFYtt7N9xww4pVaj3Qz+Kmm+9bo6b1/W6NsZdfXK1TzZZV3SnC95u98rqV06l+veqmCUbcJV+H0tRmGq2efWHKOZn3mC8EhpUJR7JjzGWh4HEirzrO4gQwnpRMJm2kEPgKFoqKmF01+Y1wDhrfb9X4Gh4/WeKHhwt1P80DVbur6WE7tOtGPzyleWqhzPcO5evehb84WWIkLrlgIoZjtc96PM/nyMk5/uuhxygUywD86OFfMD46wgsuu5BEzEVazbtC+L5iPpPj4b1HKZSDxWDf/cVhJg/Pct3F5zAUd7FaPCe11vhKs9xgApwtKwoiMCDudA4sEczCL5iM1e3XTuR8FouK6bRNzG6fKSml6y4wQZsTbBpyGE1oZpYrFLz2WZwEbAum00697c8VFEulMmcN2STd9llcp9+66GvKRZ+UI4OB1QDX9zPVJ5igFg6hQwzHcrkcb33rW3nggQeAzif3scceW6Uqrg86naZ+jWslNEVPka90v1VjiaBzt2Tzli1hy6ldRCUvcEHv1Rhaf/d+buutGqU1ubLiWNarmzm34inN8WyFTEnXb9IlHMFZaafrtiKCoGOtba1Tfz3CufZUYGn17f25etDtVM6mIYvxRG1LnaidSzBTzZUV396f43iuc+6oALYPO2wbcbAE+Erxzb/7KN4Fv87M7EJnjRDsPGcrF+7egS0lSmvKns9De49wcjHbtZwLtk5wxe5pbCvYvUHp5oFUJ2KWqO8aEJgBw/kTLlOpzjsWQDDLqvl6QnAb+ni2wlKpczlaBw77Mw32Z0LApprpdZdyUq5keshGSkJfD027V4TU1OrYynrRdOOubz0xkG41OR37rampdNf3Qs3c7rzzTo4cOcLnPvc53vjGN/Lxj3+cVCrFl770Jfbs2cNf/MVfDFy5ZwuNhqZhG9agGl8pPBX4O/azZPJ1YCgctwWpEFubNJYT3BZT5Cuqa7Bp1UAQ1BJOOJf5miZb8pkv+OQqvQ/IloHBc76imM15jCUs0rHee9RpIFvWFD3NaDzaOQB4eqnCntkyT8yV+5ZzPOuzUFDsGHOwZLRncUeWPQ4slPnFiVLvQQRwaLnCsZzHFqfI8ZNzPLr3ECMTnQMbBB3g3qee5vDMCS696ALyJZ8nj8z2vJ2qgcePzPHUiUV+/bk7SSZi5Pv8PhB4e5YLPtuGbcaTFueNuX3ttpZLimy5zFQyuP98Muf3tF0TQpCOWaRcyWwuGAxtGrL7lpMrK/bOl5lOB+0mTFuoKM1C0SfliPqt9TCsZZ9gZmvRCRXcvvOd7/CmN72JF7zgBQBs27aNiy++mGuuuYZ3vOMdfPGLX+SSSy5Z1YquBxob2WpqNIJMxN0wy74mFW0fSCDodKIyHLLTaOTwcjSHm6QjOXvUIUrwqJnuRr38v70/1zfoNlL2g9t2loz2yPpHT+c5kQv/u5Z9zfcf30t2ufNeip0olco8/MQhtOWG1hQrPofnc2zfFF6jgdGExe6qKXcYlIbjOZ8ov5IUwa3KSIttCAY7Q240z8WKgljoUgLWqk8YRHOmE+rqnJmZ4bzzzsOyLBzHoVAo1N+74YYb+Na3vrVqFTQYDAbDxiXMzgGDECq4jYyMkMvlANi0aRP79u2rv5fL5TouMDEYDAaD4Zki9E7c+/bt47rrruO6667jzjvvJJ1OY9s2f/mXf8lll1222vU0GAwGgyE0oYLbTTfdxKFDhwB4y1vewg9/+EPe/va3AzA9Pc173vOe1auhwWAwGAwRCRXcrr322vq/p6am+Ld/+zcee+wxhBDs2rUL1w3/INpgMBgMhtUmUhJ3DSklF1988UrXxdCALQm1PP/ZUk7CFhS8aKu9Ak20cmwpIu3srbXGtUTPXMJOeEpjax3awgmgEmWr7SoKEXmb5bNGk+Q8wVIh/A4eSdeK3Ba8qpNL3A6/atSWIBD1BPkwuFaQT1eM0BZsGeSARjnjZpH9xqJrcNu7dy9nn312pFnZIJpnC43LcFff0xBGYhYVFSSy9uusa0moUcsRBOX4SpMp98+psyWkXStyOVprzh518JTm6LLXN8jFLMH0sI1rBU4kRzOVvvlXriWqThgCXU1ErvQ5cYWKYs9smem0zaYhOLrskSn37nWlgJGYJO9pCp7PkCtxLdHzXOTKiv96KsdiMXyP7nkec7MnKeFgDU2A7D8OTcUdbn7ppVx5/jRaw1d+coh/f3SmZ/uJ2ZKXXbKNS7ZPIKVgNuczm/f7BoWUIzmZU8zli2wbtjln1MHqkYMmgMmkxXgyaD8LBZ+Tud7lCGDbsM32kaA/OZ6t8NRipWc7FcB02uacUbcaEHubINSoJaZD+LY9SJ+wlv3ImU5Xh5ILL7yQL37xi6EXi/i+zyWXXMLdd9+94WZ1nbzianRraCupyVdUx4AgBQw5ErvBqul0yunWEQQOIJKY1dmfsV85jZ9RWpMp+RzP+m2dlBQwVXOgaNF0czYRBJqxRLvG8zXZSvvgwFeag4tljmaaE4mV1hQrmiOZCp3SDFOOqBo9N9grAZaEIddqSzD2leaR40V+crSAUqAaNNB5VqG1ZmlpibnZWUDX67d43+cZveYm/PwyqOYpjABecsnZ3PSSS3Btq26nVfZ8lvIV7vrPJ3nieKatrIu3jfPrv7Id15JIeapj9xQcWa50zP1zq0Gg0aFFimDgc8FkjIlke8L9kCs5K21X3Uyqv4/SKOBYpvOAYjQuOX8ihi1FPWgqFZyPvfMlTubbf6DhWKBxrVOamt1btux3/E3t6m/XaCm21tf3Smt6sR4dSmBwl5KBHEq01uzZswfPC3cvQCm14ZIMw/gTto6kVkOTdCRxu3k2krAFyQ6+kqdTTtyWxOzATaTW3zSOaMN65vW6AGXVeSIdsziR9ViozmaGY4ItQw5CtHsQShHUYee4y8ncKU/KtCvZkraRdNY4FoxZVtPgYC7v88RsCb8h2DRqki7sHHeZy5+aWbhW0HFaQfRs0mhOWXc1usQczVT4zv4cRa/d/aXxKhENfxeLRY4fO4bne23OIhpAWlipUfBK+MUsaM05m0Z4y397HptGksSc5svZtS2mhi3e+RsX8bNDC/z99w+wXKgwmY5zw/PPZWIojmM3ByNRPW9njzrkyoqjmWBAIUXtHLTPUpWGsg+/OFFiJCa5YNIl7kgcCWelbRJOu9+jlAIJTA/bFCuao1mPih/cIt497jISt9pmgjXN7okYW4dVYGpd0Tgy+M3GE3abRojAlm7ItVANdygEwewzVrVseyav75XSGJrpea/jfe97X+gv2mgnOozdTafOfLU0loB0TOL7OrjIxeqUIwj8Ij0VPE+KUk7YUWWto9uUshlL6GoA6b09Sq1uU8lA46sg8Mpet8Kq3xd0rpofHs6zVOp3mzc45smkxWhcMpf3sWS4UXLJ0+TLHj+dKfL0ciX08yutNcePHyebzfYfIAqBdOII2+WNLzyba56zFaePZZRrWzzv3HEu2TbK9/cvMDU6hC1730oNBiGS3a7L8ayHoPfnIQhyi0XFA0eKvPS8BDvGY22G1p3KSTiwY8xBKc1Uyunb5qzqbfjLtyRYKvqMxK2Og6LWcoSE0bhFxdfYluhbt5oryFpc36er2Uh970rRNbh99rOfHegLzzvvvIErs56I0lhqF8Fqa6QQiA4O5qtRt9oagdX0v5NS4Ipo5UgpcBFoGf6YpBDM5r0Qge0UQgTem3YXs+ZOaGC24HN4qfdzoVZNqVQKF9iqKGDLaJJrLtyKa/f23axhyeD29fTEcLiKAbV5pRThF4xoAlPk8yfj4UupDVyG7EjtzRIEt6MjaACcCNdQYxBZj32CseXqTtfg9sIXvnAt62FYh0QdDQ4yelzLi3OQsW3jbcOwWILQwa2GFAI/4nmIsiq0xiDHY1jfaB15Qe0Zgdms1GAwGAwbDhPcDAaDwbDhGCiJ22AwGAyGlSLKzgBh0wbMzM1gMBgMGw4T3AwGg8Gw4TDBzWBYYQZZxTjIitEeKX6GMwizUrIzpx3cvvrVr/LVr351JeqyruiUvNnrs4NofKVRa1BOVI3Sgc1R8P9wGl9pyp6i7Cv8kL27rzRlX1H2dWhNrU61+oVBa814QhK3RaSA4FqBW0dYjdaaYVfiVBOEQ6F8LK1QizPoSrhNfwVwcqnIY0/PU6qEdRPW2FIz5Eaom9ao6u8a9veB4Hf5yZECZT+ca1HtWpjNe/gqWtv2qp9fj9eQr9euboZ2unpLhuU5z3kOQggee+yxlarTumC+4JFyepvidkpa7pfI3Op118sGqPU7G9/v5wZyOppcWVH0e9t81QiCMzy9XObwUtDRbh+x2TbsdnWN0NXgdDRT4dBSBa1h67DN2SNuV3eKWt0KVSstTXdrsFZNzTNTac1MpsKBBQ+le+d7xSwYikkEsFT0OZ7z0T00vtIsFAJrr7KvKfmabFkjRPeZnF8qsLTnhzz62T+htHCMxO6rmLz+7djxFNpymj67cN/nGXvxzaA1Qnl4+WXQikvPmeJNr3oeQ3GnzUqr4UxU/x+co1xZMZMJHFR6HU+mpHjgSIHlkiLtSi6YjBGzuzvJaK0p+5qjmQolT7Nt2OYNl48ynrBwu+wc4KvgXO2ZLZMpKYZjkhdMJxiKyTavzhq1Npcp+3gqyCscciWW7F03iH6tRtXUBlzZcjBoC6y/wvUjjd87yPUdhvXqLRmFxgUlvbwlTzu4ffnLXwbgxhtvPJ2v6cnevXv54Ac/yMMPP0w6nebGG2/k9ttvx7J6uzNkMhk+9KEP8R//8R8opXjJS17Ce9/7XsbGxvqWOZsPOuqa435jp7sa5sQrZeDa7bUwmrKvyXUwGpYi8HFs7Tx8pVku+Tw5V6bUkrUcswOPwOFYs0egrzTZss8Tc2WKLWbQ3XwFayP0bIedC7p1HrXZXabUbtBc8TV758vM5ZuNk0XtWGPB7KsRX2lO5DyWiqrpt1MqOG+Pz5ZYanH9V1pTqCjyLZMrXSlSzi7y6Gf+iPlffK/5eOwYYy9+A+kXvAbpOOjqzZXF+z7P6LX/L34hA165SWNbkt/61d38xgt24TSYILcGtaY6aM1c3mM233I8OrA2++lMoT5YaWQ6bXPuqEvgzVz7Xo1ScDznsVRsdicWwFXbE/zWRcPYUtQDVi1A7V+oMJNpL2f7iMPlW+JIQZMJMjQPvhpxGwY7K2EkPogm+L3b61bbUaNxwGeMkwfjtIPb0aNHmZqawnGcTm+vGUtLS1x//fXs2rWL2267jUOHDvHRj36UN77xjbztbW/rqb3llls4cOAA73rXu5BS8rGPfYyJiQn+6Z/+qW+5sy09UuMMBsI1rMZTG3ZbmcbZyCDlDKJROtwWMbXOQ2vwtebJuTLzhQ5W6w2MJyx2T7hYIthn7cn5EnMdHN0bqTnC1wJMo5FzN2qdhxRBl54r+5R6F8NyyWfPyVNBNukEPpS9zl+xojiaqVD0guB5cKHM08tez1lgLTCXKx7Kq/DU1/6GA/f8DbolSDUdz/hWNr36j3C27EZIm4X//DuGn//qnsczOZzgTa98Lrunx3EsWY09vdtCxdccy1aCgYOCQ4tlfna81NMX05GBefFY3AIR/D7Hsl7PZ41JR/A7Fw3zK2clkALmCz5758o993VzJFyyKcbZ1e1rug2+2sqyBYnTuFYH0XQbfLUStwSpNbi+u2GCG81b3tx88828//3vZ+fOnStf0z7cddddfOYzn+E73/kOQ0NDAHz605/mzjvv5P7776+/1spDDz3E61//ev7xH/+RK664AoBHHnmEG2+8kc9+9rO86EUv6llua3CDxu0+wjeuiq8peMEtirDYAobjVqRyILr/ndK6fvskShmzeZ/5gh964YQUMJ6QzBcieDsCl26O9bx11gmnuuFmWI3WmkePl5Cyt/Fuq+brT2Q4lvVDnzutNT/6uz/l6IPfoDh3JGTtYPoNH8Ma28rSD7/MyK/+TijN+15/NRdsnQxdBsA392b45ckyy6Xwe85NJS1itqAUYRPaa85OsnPcJdtnf75Gdo07bB9xIlmaJaoBbrWvobKvKFR034FhI44MzMlXu26dOJOCW9cFJY7jUKkEO/k+8MAD5HK5FaxeeO677z6uueaapiB2/fXXUywWeeCBB3rqJicn64EN4LLLLmPbtm3cd999A9Vl0Bu4UYIHrK333yB1m82HD2wQzAyjajRQ8qPtjg3B8UTRCCGIO713JOikWS5FGxQIIVje99NIgQ1A5RdBR9sqPRthB+4aRU9HCmwQ7DMYJbABnMz7fTeEbS8nWvCAwVasDkrUupklIGtDV4eS7du38/nPf56FhQUAHnzwQU6ePNn1i17+8pevfO2A/fv3c9VVVzW9Nj09TSKRYP/+/bzsZS/rqtuxY0fb6zt37mT//v2rUleDwWAwrA+6Brc3v/nNvPvd7+Yb3/gGQgj+7M/+rOuXrOZqyeXlZdLp9qnn8PAwy8vLA+mefvrpvuV+7av/wqOP/KzpNSlo2o06DLXVYFEQQNyOVg5Ev22hte64w3c/zWyfZ2YrxWQy/HYmNQa5dTOX7/28qBOPHi+2LYjpR27uWLRCgMwvv4t1+JcUn/5laM29iz/ktDaDlAAAIABJREFUZ+Odb9d344nZEsey0X5XxwoWXEXhaNLm0VS03zXtSsYSvZ+FtmIJeq5Q7EbU9jPI9T1IP9Kvbn/6p38a6bvOBLoGtxtuuIGrr76aAwcOcNNNN/G+972PXbt2rWXd6nRbCtuvcfRbQtuL37jhNfzGDa9pes2RwQaOUZ+5LfVb2dCCJWBkjZ659VsQ0kmzZ7b7QojuaKJuOnPBpLsmzyWenOu9gKITX3hkkcViNNGxh79DYeF4JE36outwpi8ECP3M7VWvuZLn7wrnv1fjq48v8/CxUiRNymleZBWGCyZjXLwpFuk3mk7b7Bh3IrWFWHXhxlo8c4t6O9eWMPwMPXM7k+ga3H784x9z0UUX8fznP5/Xvva1XHvttWzfvn0t6wYEM61MJtP2ejab7Tgza9TNz8+3vZ7JZBgejrJho8FgMBiebXQddt18883s27cPeGYXlOzYsaPtGdnMzAz5fL7jM7VG3YEDB9pe7/YszmAwGAzrm7A7AkCP4BaLxSiVgtsUR44coVwe5FbU6fPiF7+Y733ve2Sz2fprX/va14jH41x55ZU9dSdPnuTBBx+sv/bzn/+cw4cP8+IXv3igutgy6o21Uw4kUXS2jGCRdJqkHBnJkkoAW4ZsXCu8KOkIdo27pCLcwory/TVyZcVDM0Vmc2EtqWC56PPgkQLHs9E0BxeKZCPcbvaVZuy6NzL23FeG1shYCmvyHIQdC62JORbDQ0nyZT/0LfiS5/PLg8dZXFwMrbEkXHdukl/dlgjdfiwRJHQHt5vDaQCGY9FdAqNeq1prChWfXNmPZOuWLSsypfCaoG5rd32fyXTNc/vt3/5tkskkv/Zrv8ZHPvIR/vt//+9MT093/hIheMMb3rAqFawlce/evZvbbruNw4cP85GPfISbb765KYn7Fa94BVdccQUf+tCH6q/dcsstPPXUU/Uk7j//8z8fKIm70d6nsVH2u//demqzZdXz4bMU1C2/GolaziCafNXWKqxGA4sFn5M9lvhbAs4Zddgy5CBFsDz7RK7CgYVK15wlQbCQZDxphT7XvtI8frLEk/NllA7K3TxkcflZCeI9bJ9+cDjP9w7m8VRw7jelLJ47nej6HMlXmu89leHrT2TwVM2eTLIp7QZJ0x3QWrNU9JjNVdBa4ZdLFI88zr7Pv5vSiae6HlPq0l9j4pV/gOXEQUrmv/v3QRK36h5QL995Fjdeeylxx8a2ZFe3lUZ+enCev7tvL8WKwtMa27LZtHkziUSiq+Y5ky7/z2Wj1fOkyZU1//r4MoeWuqcgXDgV481XjDMck0gpqPianxwtcCLX/XjSMclzJl1c65QnaL92bYlaDtmp4NZP4ynd4GSjEQiSjiBud1/EUvIURzMeJU+jq8+TU31MAGS1H2ldhLMa13c3nu15bq0zt4GSuO+//37e/va3s7S0hBCi54hutb0l9+7dywc+8AEefvhhhoeHed3rXscdd9zRZL/1spe9jCuvvJKPfOQj9deWl5f58Ic/zDe/+U2UUrz0pS/lPe95D+Pj433LrAW3bt6KvSyuulnk1CyhslVPvEbitqjPbE63nEHrhoZspT1/q5dGa5jJemRaHqpPJi12jcewBMgW+y0N7JsvtXVsQ67krLSNpFnTy3LoeNbjJ0cLVHzdFDAFQWdy0ZTLzolY08P7pxbK/OvjGfIV1eSQUdNcOOVy/mSrpsQ/PTzflt9W+8R40mYs2bzooVhRHM+UqCjdPADQClUpc/K+f+LIv30C1WCY7Eydy6bf+mOcsWlw4vXXF+77PGPXvgG8In4hR2O21KaRFDe97HLOGk/jOu2P0eM2bYsrTiwX+dv79rL/ZJZSS2MUQpAeSjE5tanpGhuNS15/6Qg7x13clmBe8TX750t87cksuYY8ttG45PefN8alm+PEWgYantLM5jwemik2DawcCTvHXSaSVpvXaLe2LaAekFrf76ZRWp9ystG6zV6/FigbPS6V1pzMeSwUVD2otWvaBxQr2Y/0s9frhQluVbTWnDhxguuuu44777yTCy+8sOsXbd26dYCqrl+WS36bT10rvQxP+3nFlbzASsiueld2Mxlu1YUt53Q0laqVkNLhNEppir5mJuNhCTh/MkbKkU3+kK34KvBd3DNXouJrzkrbfR0lGuuSryh+erTAXL7dO7IRSwQDhxdsTeBagq8/kWX/Qm/bJ0sE3pgv2JogaQv+7y8X+fmxQl+NEILNaZe4LZnNlVku+r0Tdr0yXiHLU//0XpYe/yETL7+V1KWvQDgurZ1mzThZAkorVCGLg8dvXHE+V198LrbVe6m8AFJu8Bzi3372NF9/ZAZPdXeMCX46wcTkJOOjI/zaziFesWsIu4c5sVIaT2v+c3+On8wU+PWdQ9x4yQi2FF3bQm3A9/jJEk/OldkyFKyM7HU9tF53rhX4sgr6X3c1yn7QxjsFqAYRCEHMgqQjyVeCNt7bdDv4vprxdsySbd60/Y6n8bUo13cYTHBr4c477+TGG29k8+bNp1+7ZwlRlt0OYmZa2x2g1wW5UuU0EtbLrugpchUd+jxorXEswXCsdyfTqil5mkzZj1S3ubzP/YfyfZ39Gyl7igOLFZSCsAu3SxWfR2by1e1LwmlO3QoL75LhFXMsnjyOEKBl5wXM9V0BqiQcybt+81dIuBZ2HwPxGhVP8ZF/+xmFstc2W+uGbQnuesMVTA51v/XaVo6v2DHu4kjRNlvrhqc0S0UfT+meg6JGtNaMxCxsK7zDjNaB2XevgUoHFctFRdmP4i6i2ZyyGU2EX/J/Otd32M+fScGtaypAI7fffvvp1ehZSJTRUO22bVQNA2gGKWcQTW3/rrC6YAQdLa9ICIFCV+8GhS9nuRw42UdJnc17wS3UKH1arqKA8IENTmXzRbIakzbSdiItShiKu7h2+MAGkC975EoeFT/8WXCkZGrIxQ4Z2AAcSzLkhq8XBIssNIQObBC0hSiBraaJmtMIgkpEj1MQJCPm2Q16rSpVu4YMjXQNbu9+97t561vfyvbt23n3u9/d80uEEE0LOQyGMxnBAP6BA4nWhnVaLYOhJ12D249+9CPe+MY31v/dC5M1bzAYDIb1RNfg9u1vf7vjvw0Gg8FgWO9Ez440GAwGg2Gd03XmdvTo0Uhf1C3B22AwGAyGtaZrcHvZy14W6VnaaiZxGwwGg8EQha7B7UMf+lA9uFUqFf76r/+aWCzG9ddfz9TUFCdOnOCee+6hUqnwlre8Zc0qvFYMsr3ERtNEJUjI1RG38tCRd8OJtsi8qhHRV/1ZQkTe500QLd0AgmTlqLu8+76KtGweAj/IKOkGECTbD9JqBm1va9G2hQCt2h1JemqCkojSUJVau+MxtNM1uP32b/92/d9//ud/zo4dO/j0pz+NlKce091+++3cdtttHDx4cHVr+QwRppG1JkmvR02uoqpOHe32P900CUeiUV2tiVo1Gji67JFyJFvSTk9HhkZNoaLJe5pEtSWG0aRjgomkZDYXhJF+3bUUcO6ow+Yhm4dmiqESuQWwbcRhyE3xkyM5tKZvvpstYfOQzdZhl4dmCijVP0dOCkgkYoxOb+LwsZNores5hl01UlBQgn9/YomX7x7B6eEAUsNTmrKS7Dp7K3sPz4BWfctJOJLNw3EyhRIT6USoQK+rjiO/OFFk53gM1+pft5qNmyXA0+E7d0EQfG0ZLj+s1raHY1aDl2TfI0IgmE7bzOZ9ip4ONUiSIkhmTzjWmvUJzzaiOPwPQiiHkmuvvZYPfOADvPSlL21779vf/jbvf//7+a//+q9VqeAzTTcHgF5uAmH84tZCU/YDi69ap2TLwKZIdrE26vR9zaay7aiqy8jRjFf3XEzYggsmYyS7WHAppSkrzdFlr24kHZj8ChzZeYdipTUVPyintgN2xdfMZCrkK507HCmC3QXOn4gxEg/me7my4r6DOY4sVzom80oRdLLTw07dfq1QUfzgYJaDi503NbVlUM6Lz0uzfTRw8C96ih8dyrJvvkSnnOmase/mtEvKDXam9nyfQzMnOTG/1DbDWrjv80xe90a0EGzatImhoaEgiVnCr25NcOGmeN0CrPVce1pz/8E8e+bK1dcUC/PzLCwuArpt1uhYAltKbn/pDn7neVuxqsEjX1YElqvtM5jGgVTt9xEEG42eM+p2tNPqpGl8HTq07epAq+bV2GpX1UnTzd6q5Gty3Sy4Gqy3Uq5VnV1rMmXFsa4WXEEgHI5JNg/ZTW1/rfqEfqwnh5KVCG6n7VCytLRU3/6mlWKxyPLy8mA1exZQcw1obEz9GtYzrQnMmRWVlqG2p2Cx6Nd3KRb0L8eWgtG4RbGiApePakdQG20fy3ptOxEXPM3Dx4pMJS12Npgn1zTHsxWWSs11UxqWihrX0qRjzXULdhPw2na+dizB2aMu2ZLPTMbDb7jDKQScM+KwddhpOq6UK/lvu9M8vVzhOweylDyNp051bZNJq2rYe0qTcCQv2zXMsUyF7+5fplA1XA5mp3DpliSXTyebDHbjtuS6HcNctKnCf+7PkCsHlk+1T4zGbcZTzUbLtmWxY9sWNk+MsvfQDMVyuX5bUCBIDw8zPjHRZGbsKbj/cIFfnCzx8h1DjMUDOypdtQzbN1/i/kOFJrNnKSUTk5Okh4c5eeI4xWKpHkxjtuS68yd5xyt2M5Zy6xohBKmYRdzRZErNhtO1gVS26hxTfx04kvE4mffZNe4yGrfqHX6nwVdjWbXPtM5gbClIx6y2QVOrpvZaV6NlIYjbAtcSHc2TrWo5jb+pEIG93JArOZEN2mPtehCAIwXTww6JDrtKrFWfYDhFqJnb61//egqFAn//93/P6Oho/fWFhQVuvvlmUqkUX/jCF1a1ouuB0/V2XE1NzYInzNY1QH2fuZgtQpejtCZb8in5moWiz8lc9+1ualjVW4JnpR2Wij7HQ2gAUo4g4QiWSz7Hs/1vISmtmc17zOcV4wnJrvEYbh9fQ19pHj5W4MEjRYZcwVlpp+f2MLVyHj1W4MGnc2wecrj2vDTD8d5PAZXWPH6iwA8O5YjZks1Dbt+6aa05Mb/EgaPHcRyXwgNf4oLXvaOnBgI3/RefkyRfUXxrf47ZfO8957TW5HI5FudOMJly+dMbLuSybSN9yyl5gUejrzoPpDoxEpc8ZzKGJURoTQ1BsGuEa3We2bcSNQg03qFI9dnupkbjtjebUhZjCStS3aLUbxBNJ86kmVuo4PbQQw/x+7//+0gpufrqq5mcnGR2dpb7778frTWf/exnufzyy0+7os8G1usCEF8FAScKAhgPeUHWUFpz/6F8pHIAJiKWA8176oVlLC6xZLT0zR8dzlGOuAok+sIZ+MmRPJmSinQelooeJR/2/9+Ps/O1fxhKI4m+qOW254/ykvNSkep2LFNhoRitpImkxVQyWluIWdVNdSP+rlGvodosKUo5g2gGqdugmlbOpOAW6rbkc5/7XL785S/zyU9+kh//+McsLi4yOjrKS17yEt7ylrewe/fu066kwbASDHLxB5poD+ejBrZaOVHrF2giFxUZOUDd1opBztug5ayFxrA2hApuALt37+av/uqvVrMuBoPBYDCsCMZ+y2AwGAwbDhPcDAaDwbDhMMHNYDAYDBsOE9wMBoPBsOEwwS0Cg9jd1DRRtFE1SmtyZT+yZqno88RsmZO5Sihd4FLhc8GEy2RShnLZE8A5IzYXTMaYSlmhnfkmEpIXbk+yc8yhT+pZnbGEZCplMeSIUOVorZnPVxhyJWk33PGcDpdtiXPp5hixkAc0nbb5vUtHefUFaVw7nCblSnaMu5w76uCGLOeiqRhXbE1EaqMVX2NVE/zD/j5xWzDWJyewFU9pjmU89s2XyUXI1zida3WtNKvZJxgirJY8k2lNoAyTINpJ0y9PJapGa93mHFJ7vZem5GuypVOaubxisVhmOu2QctvHO80OFBopBRNJm7E4HM16XTudsbjF+RMuVtX7cDxuMRq3mMl4ZLtoko5gOu3UXU22DDlMpRz2zZc42SUhOWELpodtbCGQQhB3IOYEicKlLqlyhYriaKZCxQ/OdcwG17LarKBWElsKxhMWV2xLcGixwuGlSscEhJQjecHWBGOJwIkjYQsu2RTjgq1xfnK02DGh3ZawNW0TdyRSCBxLcN6Yw2LB50TO71jOaFxyy/PHuGRTjJgt29wwOqF04FASjKUEttCMxi1KniLXwwZtc8piOG6FcsWplZMtVb1Nq+308FKFlCPY0iPZfqWu1bXSrHSfYDhFqOD28Y9/nBMnTvC//tf/anvvPe95D1u2bOGOO+5Y8cqtBzo12k62OGutafd8bHYa6a5RDf6I1c8S2DgdXqqQdJqdOvxqOV5LOVIIpAXbhm3yZcVM1qt/b8wS7J5wGW6xSZJSIIGtwzaFimIm49VtnGwJW4ZsUq5syiGraXZPxJgeVjwxW6o7sFgi0AzFmjVCBDO3tCtJ2rBcUvXz5CvNsaxHpqRaOuIgnyzlSBI2ZMp+Rx/J00YILAHnjDlMD9s8frJUtxWTIphF7ZqINRlPi2rQ/pUtCZ4zGec7T+U4vFSpf2Uny7Dg+wTjSYuR6oAiUx1QWAJetXuI1108jN1gutzL9kprTaGiyFWgyVuyeq5jtsS1OWVlVWUkLtmcstuMtLu17dqALVehYcB2qp1mK5p982Umk5KJpN1Wx8bv6lXORtUYThEquH3ta1/j1ltv7fje8573PD7zmc9suOAWxvet9rlaRxBV0+39XhqlNflKf7f+xotAa02uoil2Mb2tHzOQa+g84rag2KccKQKfyp3jLrM5j6Qj2T7S2Si3UZN0gttn83kfX2umUnZ9VN8JSwrSruS5ZyWYyVRYKvlMJW2E6H2+LakZS0gKFcWRZY/jOR/d0fS2QSM0IzGLUkWRXaVZnBSCmC24ZHOcxaLPYkHxK2fFcaVAdnHRt6Qg6QpeuWuIY5kKPzhcYDxhYUu6/j4gsGQwoCh6mpQjuO0F44zGZVcLsNYBkqcg0zBA6NR+agOKIdcioYKZ/ua03fN4Wtu2r+k4+GpFA7PVuw1bhx3ifSzkVuJafSY03XTdfDTXA6vt9B+FUMHt2LFjnH322R3f2759OzMzMytaqfVCmAbTa6a0Gppc2a/eEqJHh9asydRv70C3DqMRDXWnfRFEj77lCGD7iNs28+qnGU9aPYNaq8YSgYVTzA7nWlH7TL6iOZ71Q9pSBbM4WduDZRWxpGBT0uL8iVjoDsqWgomkxeYhO7SvihCCsYTkbS+aaDID7qdRSrFY1PQaFLVqbAlb0nb97zAarTWLhS4O/R3QQEVRP5b1eK2utcbQTKgFJfF4nJMnT3Z879ixYziOs6KVWg+slRVPVM0g7XiQpt9rRtQNS4rItlSD2FjVgk8UIu5NCVQnrNEkAyEibjoKweYqUWXBvmcRC6qftAiFiWDgEaX9CCGq7TRq+1m/1+paaUxs60yo4Hb55Zfzuc99Dt9vfqDv+z6f//znzxjTZIPBYDA8Owh1W/LNb34zb3jDG3j1q1/N6173OjZv3syxY8f453/+Zw4ePMg//MM/rHY9DQaDwWAITehdAT75yU/ygQ98gI9+9KP117dv386nPvUpnvvc565aBQ0Gg8FgiEroPLfrrruOb33rWxw4cICFhQXGx8c599xzV7FqBoPBYDAMRuQk7vPOO4/zzjtvNepiMBgMBsOKENp+68knn+QP//APufrqq7n44ov5xS9+AcAnPvEJfvCDH6xaBQ2nz/rIgHnmMYvKDIYzh1DB7ec//zk33ngjDz30EC960YtQ6lS2UKlU4v/8n/+zahV8plCr7Ps2qMaSIlpei9bYMpzXYoMoujuH1nhKNyWW9pfogc5DYJ4S7Ty4VvRl8GHzwRpR9WMKX5gawAml5j4VpYaer6gojVLR2pwgei6Vr8K3g2pJWCLa8Qig7EcrZy2v1bXSrJP87XVHqOD2F3/xF1xyySV84xvf4MMf/nDTyb/kkkt49NFHV62CzxTZst/QUXWnMemy1RpnJTU1Z5JjGY+lkgrdedhSsHXYYfuIgy37dx6CwD7rrLTNSMwKnUtlycB1JGxiaes5CKNRWuMrTb4h8vbT+EpT8lRXH8dO1AyfxhIWO8ddUiGMmHW1bkeWPZ6YK5Mpqb4DpFo5SSd871QrZy7vMxIPktn7IQjywbYOO/z0SIGZjNe3/dTccGbzPifzHgVPBZ/veUzBewmbervp27ar78Utwa5xh4lQhtxBwB2Jy7o5dL9yull9rbSm9pmaZjX7hPXmTrLeCPXM7Wc/+xkf+9jHiMVibbluk5OTzM3NrUrlnknKPiwUfJKOIF61KernY1f7u5stziAapTQK2syG5wuKpANJp71uwcUvGHKDi18IQcoV7Bp3mct7zOZbfRUDpIBNqcDcuPZ9Y3GLQtWcud2lIvg7aQsSDYEtzDlofT2MJl9WFP12fcfzpjVaB36Zh5e8SLck43bgrl/7vrNHXbJlxUymgq9a52QapWGx4HM851ObFB1a8kg6gm3DdjBz7tABxSxBMqSjS1BO4A06k/HwdZAAP+RaxO3A/1N1sBWTAiYSFrsmYriWQAH7FirMZD2eM+mScGST/yfUdplQHGvwC81XNCXPZ8iVwSCpQ50dKUjH2r+v0VqqFVsK0g0epFMpyWhcM5Op1F1yGhEEs/Ctww6xFvuwbuV082hs1LS+v1Ka2t9roTE0Eyq4CSGwrM5bVSwuLhKPx1e0UuuFmtdi0fNJxyxkdcRYYxAPySgaDcwXfGbznV3d8xUoeoq0K3CsatgRgpglSLntRrpCCCZTDiMtnYcAhmOSzUN2W8ckhCDpWsSdoAMNjI4DlWsFnWunznmlzgEEt55yFUW3u2mtHYHSgVnyE3NlSiHtswRgSUjHZMfbkUNV/8y5vMdcdXCgtKbsaZ5e9ih1sOrPVzRPzFWYTFhMDQWzYFF1FknHrJC3PYPg6St4aqFSN41uxK5uPVP0FPlK8L4UQbC5YCrGaIdtZvIVzU9nSmxKWeyacINbOCIoZyZTIVdpL8fXsFRS1d9d1m3TBMF56zaLbPxdq3eU2wZfjTiWqA8oji5X6kG70+CrWznd3uulOd12uh40hlOECm4XX3wx99xzDy95yUva3vvmN7/JZZddttL1Wlf4GhaLftsMpR9hjFM7aSq+olDRnMj7VDrtb9KA0rBU0iRszVjCIuX27zQbO4/FgsdkMtgqpRdSCEbiNhVfU6j4JByr67YjrccDtWcD4c8BQMkLtp+phHhGVNPM5jyOZT3mC+EfZLkWxG2Ja/X+naQQTFUHB48cK7JQ8Fkq9S9ntuCzWPK5cDJGononIOy5yJQU2bJiruB3DGw1hBAkHIuYHQSQ4bhg27Dbd1Z4IuczVyiwezyw0JsvdJ7VN1L2NQsFn4mkRaJlltuLmjeoIyHldg5QjQy5kl0TwYDCVzCVah98dStnkOtuPWsg2jVkCBncbr31Vt785jfj+z433HADQggeffRR/uVf/oV77rmHv/3bv13teq4LKgriRHzoLSIuACEIpjMZL6TJb4CngtlAFK/GIVeScpxIF4xjCWzZv2NaCTIRNqes8cRcOfJimCG3/VZaL1xLMJf3yJTD/66eCnQJJ9pmnXN5v+MsqhtSCM4etklH2BTUV3Bk2es7wGmkNpMaikU7Htdqfjbbj9qAImrHPsh1t54165X1tAtAK6GC23XXXccHP/hB/uzP/oyvf/3raK15//vfz9DQEB/84Ae56qqrVrueBoPBYDCEJnQS9+te9zquv/56HnroIebm5hgbG+N5z3seyWRyNetnMBgMBkNkIjmUJBIJXvSiF61WXQwGg8FgWBH6BrdyuczXvvY1Hnzwwfqebps2beLKK6/kVa961Ybcy81gMBgMz256BrfHHnuMt771rRw7dqztAejdd9/NX/3VX/HXf/3XnH/++ataSYPBYDAYotB1eVQ2m+XNb34zuVyOd77zndx777088sgj/OxnP+PrX/8673jHO8hkMvXPnAms5SLcRATXChisbrVk3fW6csuJaH8VuGpELyflyMi7Wp8z6kRyFoHAUSPCgkQgWF1oR9TUnFyi4MjoO3u7VnSNWcg+GEprKhGtxs50us7c7r77bpaWlvjyl7/M7t27m94777zzuOWWW7j22mv5vd/7Pf75n/+Zm2++edUr+0wSqyauQvh8k8aGGEUTswTbRhxKnuZoxqPcJ9ct7Uq2pO26B2CYcjIlP0g30GDLwJopEaLnbfS/C7s0e1DNcEyidZAS0C/XLVtSPD5bihTcko7ggkmXlCPRwLFsheVS7y+I24LzJ1xeuC2JpzT/32PL/OjpQs/csNG45DcvSLN9xEEA+xcqzGS8UHU8K22zBfheiAgnBQzHBGWlWSj6JOz+y+4tAZuHbNKxICm70JAI3ktz3pjD5qHgeE452HRHAIlqniis/jW0UTRa63pyviY49+ENAM5suga3++67j9e+9rVtga2R888/n9e85jV897vf3bDBzZYw5FqBqWsf+51GennShdEIAhuo88YcFgs+J3LtLiVu1QMybgmkDFdO2Q/cSQoN1kYVpTm4WCEdE2wecjpeOIPYAJ2Opn4eROB+4fmabAeXEs/X7JsvczLvhw5sloBzRx22pO3ANaRal7PSDuOJzgMKKeDsEYfptFPX2Jbgdy4a5rpzU/zjI4scWfbayrnmnCQv3J7EEtR/ox1jDluHbfacLPfN5au1hZQr2D3hcGTZ6xh8ko5gyG12+yh6mpLvV51A2oPjaFyyKdV8DhK2JG4HyeOdBhSbUhY7x2JIQT2nMu5I4g5ky6rjQMxtGBiu5TX0bNd4KnAFajylvtIsFn3iVrhE+DOZrsHtySef5Hd/93f7fsFVV13Ft771rRWtVCtf+tKX+MxnPsPMzAy7d+/mj/7oj3jhC1/YU/MdEn6gAAAgAElEQVSFL3yBf//3f2fPnj2USiV2797N7bffzjXXXBOqTEFwu6pmKdTLYy6sd+IgGgGMxi2G4xbHMh6ZskIAk0mL8aRVt0DqVk7tNaU1szmviwOFQAPLJU22VGYqZTGWsNqSTcP63620RorAXmzMsshXFAUv0B/LeOxfqHT0VOzGZNJi94TbFGway2kcUNQC5niiphFtyd6uLTkrLfjDF07ykyN5/uXxDAVPs2PM4dXPSRO3ZZuTiyUFCQGXbYkxm/fZN98/8VwIgWtJzhl1qrZUgb+kI4PbnY0BqoYm8CVeLilcqUlVk9XjtmA6beNYoqNFmyCwY6soTbYcDCiSjuCCiVhHL8radwy5El9pMlWNJU4lyHcqB3pfD53aznrRtOpWUhM8LvAp+QQ/YGP9qv8u+ppSwe9qYWboEdyWl5eZmprq+wVTU1MsLS2taKUaueeee3j/+9/P7bffzvOf/3y+8pWv8KY3vYm7776750KWv/mbv+Haa6/lpptuIpFI8K//+q/ceuutfPKTn+TlL39533LHEu2Bo5VuXnYrrZFSIIHptE1ZBVvYSOjpRtJYTr7s8/SyFyoIKAJLplxFsXXYiXQOegWoldIkHYnWiu8fLpCvhH/G5ki4eFOs3sH3KkcAo4nAwzDhSJIdOvRWjWvBFVuT/MqWOAcWy4wn7J72ZDUrqmAgEeenR4qEMWSRQjDsSlITDrN5v2NQ60RZacpFn+dMukwk7VC/qyMD4+zxhMVUywyvW91EVVPxdf34+5UT1TtxLTWw+td3o6bsBwOKuutrV10wIM2UFbaA0UTkfac3PF3PSKlUCrXM37ZtKpXKilaqkU984hP81m/9Fn/wB38AwJVXXsljjz3G//7f/5uPfexjXXVf+cpXGB8fr/999dVXc/DgQT73uc+FCm5RbKxqF84g9kBRNFIKYiE7s8ZyForNtzb6oaktsoh+PLV/h9VAdN/JE3mffFlHsicbTVh9A1sjUghcW5AK7doPtiVQBLd2wyKFoOQpQvo7B4hgb7oolmEQ3B6cSNqhj0eIYMHI5iE78m/qhtiKp1UziP/oamtqurXSFLza44fwOm+QVVRnAD3D/cGDB3Fdt+cXPPXUUytZnyYOHz7MU089xXve8576a1JKXvnKV/IP//APPbWNga3GhRdeyAMPPLDi9VzvDLTAaoC7HGt6a0QQ/l7ks4BBztwgp0DrAQszrA0DtOkNdBmsKD2D2zvf+c6+X7CaTtX79+8HYMeOHU2v79y5k8XFRebn5zsGsW48/PDD7Ny5c0XraDAYDIb1R9fg9uEPf3gt69GR2rO84eHhptdHRkbq74cNbnfffTe//OUvede73rWylTQYDIYNzHp2/u9F1+D22te+dlUKzGQynDhxou/nGmdYbavAIj7befTRR/mf//N/cvPNN5sdDAwGg+EMYM2X2Nx77728973v7fu5PXv21Gdoy8vLpNPp+nvLy8tA+4yuE4cPH+ZNb3oTV111FX/8x388YK0NBoPB8GxizYPbjTfeyI033hjqs7Vnbfv372fr1q311/fv38/o6GjfW5Jzc3PccsstTE9P85d/+ZdYVrSNFQ0Gg8Hw7CSia93asn37ds4991zuvffe+mtKKe69916uvfbantpcLsdtt90GwF133UUikVjVuq5nBlrvs96XYA1Qv/W8SHCQ0z3QItj1fBIMg61SXvlabAjWdXADuOOOO/jKV77Cpz71KX74wx/yJ3/yJxw8eJD/8T/+R/0zDzzwABdddFHTMv877riDJ554gjvuuINDhw7x8MMP1/8LQ6eEz16fXc+asXjVPiyUIvhctmqoHLYcpTRlX1HxFSpk3o1SgRlsRWlUhOPZnKrmrIU8IAlkSz6K9uTaXnUrlBWZkh86j0hrjS0gQooXWmsSduAaEgVbBC4iYVPdBIF1k9a1dhDmmILfZaHoo0K2hVqbqfjh20/j51ZTU/vsetbELRHh9wmImu94prDu09p/8zd/k3w+z6c//Wk+9alPsXv3bu66664mdxKtNb7vNzWi+++/H4B3vOMdbd+5Z8+evuU2OhpE9U7steBlrTUASddi14TkZM5jodDgftABAUylJOMJu6tVVms5GjiZD6y9AMYTkqlUdxeMWiCbzZ+yAxuLSzYNddc0Hk/Ktfi1nSkOLJR59EQJpeia0C0FbBmyOG/MxZLhjkdpOJ71OLBQwdeBM8xzz4pjy3b7rda6SSkZTUjKviJT6n2uldZkSz7Hsj4pV+JYOtD0cJIRBD6TW4ZcHEuwVPTZM1ei4nd3a7ElbE7ZvPjcFOmYRaGiOLJcwVO9utDaO4LjWZ/FomI6bePKdtuyxuPxq5ZdfoP9li3D+y3WXhv0ulvPmtbXO2nijoVr97DfOqVCEJgMxMKO8s4whA47rDiDieKDuN41ZV9zdLlC0dNNHZsAhlzBlnR44+TaljnHsl6bN6ItYcuQ3ebwoZQmX1HMdNA0OtTLls6h2/GUPMUjx4oczXhNLixSBH6Iz5mMkXTbb1B0Ok++0hQ8xZ6TZXIt5sSWCOy7zhtzm2yo+nVaubJPsaWTUkrjac3RZY9CizWJ1sH5ybeY/nzxkx/mpjvezXTaIdVyPEprjiyXObTkNQVGSwSuJNedm+Ls0WYzBq018wWPk7lWr9FTQa0TI3HJ5pSNEKdcfGoDnK7GyRKGYs12duvleljPmk7GybV2FKsaJ0dxEQK461tPRPo8rO9UgKmpdNf31v3MbT3QyZeuXxrCWmog3MUFQWd3zqhDpqw41rDlzfSwQ7LHljeipSPzFRzNVLpuj+IpeHrZI+kIptMOlgw0M1mPXBcTRV/D0YxHoiCYHrbr+7n1Op6YLbliW5L5gs+DRwrkK4Gx9O4Jl6lUd9f0xuNR1dnavvkyx7N+17o9crzEgYUKz98aZzRu1bv/XmUMxWwS1U6qooJzdyIfzKC7aVKuRdwOZnG1AUDSEewadzuWJYVg+0iMTSmHvfMlFovBObh0c5znTSc6DlaEEEwkHUbimmOZCpmypl9gA1gqKjKlMptTgZm3gKYtWTpRVrBQ8Ek6gnjD1j3r6RpajxpbCkbjFsXqlkKa4Bak2fImHCa4hWQj+d8JIRiOWQy5klxZMeT23vOrEU0QtLoFqFbyFc3e+TIpV5Avd+8AGyl4mn3zFS6YdEOPTMcTFq/YmWLvXJl0XIa++IUQPH6ixELR7+vMD4FR7X8eyPOqXSmSbrjVt5YUjMQtHjtRZKmsQpVjScFowsKVkHCsvvuyQRDoL96UIG7BRMpmONa/frYUbBtxObxYJhvSIlZpmMn6FCqauCNC+ZZqIFfRaBQJO3x7W8/X3VpohBAkXIuYEzyfNjsAhMcEtzMYKUSkwFYjbGBr16zuRSmEYDxpRV5FuFQKF3AaiWJEDUHdSr6OXE7Cad8ypx8TyXCBrZHgWWK0g6oojaOj1c08BBkMKYKdJ0xgC8+6Xy1pMBgMBkNUTHAzGAwGw4bDBDeDwWAwbDjMMzeDwWAwrOsl/4NgZm4Gg8Fg2HCY4BYBk+8erHecTtuR7KLitmA6bZOIoLEEZEo+ZT/88kJPhUs1aMRXmk2pIC0iLDFLUPY1JU+FbhMVX2Nb0dwkHAnTaYfRWPi6CYJVjPmyH6m9Dsck44lo5QzHZHTbsAHyswa57tazxrA2mNuSIWlsxL1cKc4EzXBMko5Jloo+J3J+V9snKWhK9k3HLDIln+NZv+tS+pq9VNwOAkhFKRypSMe6uzG0OoHUU5F7HI+uuqsUPEi7kpQrKVQUMxmPSpd4KoBtwzZnjzoorcmUFbYI3De6ddpaa+bzHifzClsGdlQJFWh7pRNsGbLYMRYLTE00jCUs4rag6HUXxezg+5XW5D0o+j5p1+qbSqC1JuVKko5kLKGZyXhdk/MhKOOstI0kMF1J2IE7SaWHB6cjg7ST2mkKm+fV2k4H0cD6u4ZWW2Mwwa0v3dwEennMnQkaAYzELYZjFsezHkul5ogwEpNsHmq2aaoFuCHX4kTOY7HYrIlZgqGYaPOXrCjNfMEnaQsSDcnMWmvKfuBlWPdwFIG+l59fyat6OJ46KCSQdCQ7xl3m8z6zeb9pFjgal5w/6eK0+Et6SrNY9IlX7ZAay8pXFEebPBwFQgSOMKNxq6Ozx5AruWDCJWbLU+WIYCZ7zqjDctHneMuAwhLBgMNq8XBUGpZKPq4FQx2smlrPjxDgItg+4pAtK463WKQ5Es5K2yScZnu0WvllX5OrqKa6SQEpR3ZMPg7rt7gSmvV4Da2GxnAKE9x60OtC6uYteCZppBAgAg/J8WTglQgwPWzjStHRYLem2ZyyGU9ojmY8Kr4mHRPYspv7QvBa3tP12Yis3rY8NZFp1jXZhVU7Al8FQa3rzKwaGMeTFqNxi6PZoG67xx1GE1Zn9/VqOUVfUyr49dnJ8axHtpsjS7WcuC2JVWc9Smt2jLlMJu0m78rGukkhGI5bpKsDiuWSqs9yG4+5lbLfPDjodJ4akUKQdiVD424wCCkoJpMW40mrbeDR+D2uBa5lkasoip4mbgtS1fK6aVoHIf2sqZ5JDayP6y7MZwwmuHUlij1Or1nCs10TRielICbg3DEn+HxIjSuCmUCm5IeuX202AjSZEXej9p1lT7FUqvkn9qmbEEgLzhmxGU9YiA7BpkNJaGCx6Fd3XuhPLZiOxiU7x2NIujvuN9YNAZtSFq4d1nLt1OAg7oT7fWp125S02ZRqKLuPBoIZcMqpnumQmijtdD1rap9Za40JcO2YBSVdiNJYTt3W2XiasLrazEJG1KhqfIp8cYYIbI2cmqyF1zjVTfCi1C2qLReAa0kE/QNbEwP8rlKEC2xNGhkEuSju87U2EEXzbLke1qNGD9DmzgRMcDM8KzHXs8Fg6IUJbgaDwWDYcJjgZjAYDIYNhwluBoPBYNhwmOBmMBgMhg2HCW4Gg8Fg2HCYPLcuDJI7cqZrBkkqFSHyzjqUNEDqQMQiqGYbDCCKWpSKltVQLycquoc9VvdiTk+zHtvpRtOcTorbRtsJoBEzc+tBmAu7NYkyimaQcrr9/WzV+ErX/933PFTfd6UgYdVfDFWOa0HKCacBqg4igoQtqgEu3G9kS0jHwmsEga2VUuHOW60cSwqGYzJS8JUyyCuMUg50TuwPo2n8u59m0Gtoo2ka/46qMTRjZm5d6Gdx02l0Ooim9b1OI7Ze39dtlLeeNaoa1LJV8+BWJ4huo1ZLCtINJsUJrcmU/K52Wo11E0KQdCHuBBZcZb+zRhB4P04POySr1lFJHRgzl6rGzK1D5dZy4hJcKzBmLnrQyRUlSIwOymnckaCXS0Xr664lGE8I8hVFwdNdEts1gsC0uNHfMUw5je/1c9B4pjWdzs+zVdP6XhSN4RQmuPWh08XW7/bbRtRA+0g+qkZV/50tK8odrDw6dwRB55x0BHFbNpUnhWAkblP2FdmSqruQ9Lr4A41Fxdcsl5pNfgUwlZSMJ+22ctIxm4TSLJdOmRb3Kycds0g4muVi8w4AAhhPSCZTdpuLR6dA36uzF0KQci3itm722qwGupgVvB+2nG7Hs5KaxnMXRlN7bT1dD+tVYziFCW4hCDPa3eia2mdOR1OszjD63UhpvIi7dc6NuJZkrGEGI4Iv6VmGYwnGEzLQVIJtds5KOz33G7OlYCxuUago8iHLsaVgLCEpVhR5L7jVeVbawe2zDU2nINDrfFtSMJqwKXmKbFkhW2a5UcrpxzOh6TWjXw+axteeaY0hwAS3CNQ63SiNy2gCzWzeC/35mmYiYYUupzaDKXoeOqJm23AXx/8umqRrUfQ9VMgnXkIIEq7FlrTEsaI/5o5yrmN25+1lVrqcQTWts72NolmP192ZjllQYjAYDIYNhwluBoPBYNhwmOBmMBgMhg2HCW4Gg8Fg2HCY4GYwGAyGDYcJbgaDwWDYcJjgFoHaMuEoy4U3kkZpTabkMVfwyZa80DqtNRMJi5QjQttFJezmvKiw5YwnLIbc8LZUWmsWij5LRQ8/hPei1pp8uZrIHaFuMSvIeVvN30drTclTzBd8FgoeXkQvyajL4AfRrEUZg2g8pVkoeMwXfEqeinTOo5a3VpozHZPnFoJWF4YwyZ4bSaO1pugp8hWNrlpJFX1NqeC32Tp1K0uIwGEkZkO25FPuYpnlSEHalQgRLWm88TMxC9yERa6sKHVwQul0Hip+EOQStiDpyI5lVXxNptzgUBJ8Sc+6WQLSroWUgx9PTdPrN/JVs0OJrzSLRZ+YRc8k+E7lRKlbp79XWtNYv5XWaB1YqxUbrNUyZRX8bj2S4NfrtWo4hQlufeh0cfTrCFZS0+29tdJ41U7zVIwQ9f9rIFNW2NWOoDERuls5guCzXoO3JAQ+i0OOxLZEU0fczz2iVzlDriShIVv28VRvTc1ppOBpSp5POmbhVF1ElNZky37gR1ntAPvVTUDdMqzxs2GPp1XTqGvUdOqcG4+n5GvKBb/NvqxbOY11az1HnTS1fz/bNFpryn7QBmsDNhp0tcFBvDo46FTWeuwTDKcwwa0L/RpPp46g9b2V0NTe66TpV9bpaLTW5Cqqq1lwI54KZj21jiBMObaE0aqVlYa6SfFKH4+FZiRmUawoctWyemkAFLBU8rEFOBYUGs2PO+haO5yYLRhyLUSfujVqwswyWjW9OucGFRrIVTRFz2c4ZlEbg4Rtp1Hrtt41StPsw9npJnZV03qHIko5nd5bCU3tvbAz7TMVE9x6EKbBDDKSejZo6i74wYv9RE3aKOUk+gS1TppBjkfKoPOP0gV4WuN5p2aqYcqq3YYM29kMcqtJCIHnKzL1e7vhdEppgtOwunWL2umuddteKnqo0Jvo/f/tnXlUVNcdx78zw76pJC6JG4qCSEArm9Z9KWiLMeLxGE3SoHGrSrUaixDjQjVoqjWQiCiinkQNLrjGaLSYulePW6tFbT0oLtFEERhGlmHe3P4xznN2Zh6zOfw+5+Bx7rvfd3+/t/3eve+931XdHKhHJZzRH0M3fAS9UGIUIXdCrqYR0oal7djLF6bxrwUtWXzhEItEsPRaI2jfCNluZubP1G5GmEbIsdCY9iyBMVi8/Uz1wk3q7OUPoQcFN4IgCMLloOBGEARBuBwU3AiCIAiXg4IbQRAE4XJQcCMIgiBcDgpuBGECQe+Y0idHBOFwKLgZwZJXwNV1nV1jro4x9jLbiLltMQaFklncjqU+CdEAqjRYQl7tV70ybr6GYwwiC20T4o8I7EUMNV+jZKra9jjmLDkOGtOOEI2bxVe9l8e2rW0ToqHvtw1Dwc0IpjJiqNH9WNUcjVrnCI1mWUMab3cJmntpp9QyhUSsnZPRVrZxTJU9pLyWQz3HoGxAo2QMnFKVbUW3bVOIAAR4ihHoLYG7mdtABMBXZxuYc/zobgNzNGKRCC28JfCUmHMTolrm6/byI3ZLj21X0gR4aibxNrHdXtT3lIjgLjHvvHPUNYHQhzKUmMBUtgVjB5YradzEIjT3epG6SsHAp6B6qYIIIr28hea0o1tuKkMDY6oEU7qJkKVyJTwkIvi5iwERtHJSqtdTLVeiltNv0+A2YqqsFbrJk5t5uamSJtdx0Mv3/EKjm4PQUJooS7aBIY2uzSIA/p5u8NbL/6ltm4dElQ5MN3myoXaMbRtTtjmbRne5oTJvdwk83djLTDxMP2OJRCzSS57srOcqoc8r0XPbuXMn4uPjERERgaSkJJw7d84ifXFxMcLCwhAXF2dx24buqhs6uFxJIxKJ4O0hQaC3hM+tp77b9ZSoeg/e7vrpphpqx5R9upo6jqG8hjOY4V/OMTyr5VQ5KjU08hdZ/muNzAqgFeRe2OUuEaGFl0QvUS6/zFvCT8Wj3gZuYpXGz9PN6PazxjYwpVHfhOj2RsRiEZp5ShDg6WZwVgDdXoKhnuSrqNHddsY0YpEI/p5uOiMUquFeXzfVNjU0K4CznquENk7fczt06BAWL16MWbNmISoqCnv27MG0adOwe/duhISENKhnjCEjIwOBgYFQKBSC7dA8yMw9sFxJIxaJEOCp6sHUKDj4uBufDsRattXWK1HLKbUy+hujRsFQx6mmrJFzQL0Zc5mp2/EQA17uYnhITN/riUQi+HpI4OXGUF3PwUNierof3XaE7h/N36bqq3sj1XIOYpEI3kam7jGktfSi6UoazREKBTM9RZBuO4DznasNkRT5RqPX8Srg9D237OxsvPPOO5g5cyZ69+6NFStWoGPHjtiwYYNZ+v3796OsrAxjxoyxsaVNA3eJCP4e5gW2xiKrNy+wqVEyQCZXmhXYNPH1kDQY2DSRiFXDfJ5u5gWPxmJJG+IXAdjHguTNQtoRqrFHG0I06hEKQ8O3xKuJUwe3+/fv4+7duxgxYgRfJhaLkZCQgFOnTjWol8lkWLVqFVJTU+Hu7m5LUwmCIAgnwqmDW0lJCQCgc+fOWuXBwcGoqKjAs2fPTOrXrl2L4OBgDBs2zGY2EgRBEM6HUz9zq6ysBAAEBARolTdr1oxfHhgYaFBbUlKC7du3Y+fOnbY1kiAIgnA67B7cqqqq8MsvvzRYLzg4mP+/Oa8D67J8+XKMHj0aoaGhAi0lCIIgXlXsHtyOHDmChQsXNljv1q1bfA9NKpXC39+fXyaVSgHo9+jUnDhxApcvX8aiRYv4unV1dbzWy8sLHh4ejfKDIAiCcF7sHtzGjh2LsWPHmlVX/aytpKQEbdu25ctLSkrQvHlzo0OSd+7cQXV1NeLj4/WWxcTEYPbs2ZgxY4YA6wl74iERQW7kOzVTGoXSkqRUBEG4Ik79zK19+/YICgrCkSNH0L9/fwCAUqnU+m2I4cOHIywsTKts7969OHbsGHJyctCuXTuLbdHMKmHu9ybOrNHUOavG30MMBtXr/Q0FOTcxXrzGrfotk3OQc6bbkIgAf0+VxpLvojT9sZdGcx87m22WatT/J41tz++mjlMHNwBISUnB/Pnz0bZtW/Tq1Qv79u1DaWkpVq9ezde5cOECkpOTsWXLFsTGxqJNmzZo06aN1nouXLgANzc3QVlKdE9gczIFvEoaY2XOoBEB8PMQg1MyyORKvRRTIqjyOXq+yByi1vl5SExq1CnDNDWaGS1M2eYIjbrcGW1r6JgTotHUkcYyDaHC6YNbYmIiqqurkZeXh5ycHHTt2hXr16/Xyk7CGAPHcWbf3ZqLsYPI1IWgMRpdnakD2poa9W9n1YhFIojEQHMvCWrqlahWvEz/5eshhqgBTa1Ciep6VX5KD4kq8BnSGLNN0z5raYwtN6UxlnnD2u00RmPN84E00NNRkDMfEbN2RHARLDlwdDchaWynUc8CwBggEsGsbBJqjZIBYjM1zrYNlixZgiVLljjUNnN09tIY0jVljbkBbn3Rf10q/VbLlv5Glzl9z81RWHI3pL6jbuoaS9G8CzVXrw5MDJZrRBZohNhGGvsdB2odaQTMUdhEcOoMJQRBEIRpKLYZhoIbQRAE4XJQcCMIgiBcDgpuBEEQhMtBwY0gCIJwOSi4EQRBEC4HBTfCamh+WEoQhH2gb7gNQ9+5GUHIR9xNWaNkDEoGVeYPMIs/lDb3+x7S6GsAyz6UtlQj5xg8JLC4HTW2tM3WGs26zqwh9KHgZgRTaZXUGEtR9KprNJebo2EAnsuVqOMaTovVmHZ0Ncb8dFWNseWG0jdZQyPnGJ7XK6FkqiTTfh5iSMTGM7zY0zZHa3TLnUFDaEPBzQS6F17N37p1mppGXVanUF0ANe8f6zgGeQ33IqGxeRdvU0HO1Ils7CbEFTXGLsTWbkfJVDMx1Ctf7lWOAZV1SnhIRPDTuXFpqB1DdRqjMaRzhMbZzlVCGwpuZqB7IVCX2UIDWHYAO0rDMdW0Mgql4foMgKxeiVoO8NeYisaSdsy9O3WkpiHdq6aprleiRmF8qEvOMZTXcFqzKjTUjnq5vc4hV9MAFNSEQC+UmIlIJOIPKnMPLiEazbrOqAEAaZ0SFbXGA5smCiVQXsvZxTZHaCw5FpxZU13PobyWMxnY1DAAz+sZauuVFrdjj3PI1TSadSmwmQ8FN8JiNIerCNdAyVR/lkBHAeHMUHAjCIIgXA4KbgRBEITLQZOVEgRBEC4H9dwIgiAIl4OCG0EQBOFyUHAjCIIgXA4KbgRBEITLQcGNIAiCcDkouBEEQRAuBwU3M9m5cyfi4+MRERGBpKQknDt3zixdTU0N/vrXv2LQoEGIiIjA0KFDkZeXZ2NrG0aoP2qKi4sRFhaGuLg4G1loGUL8KSgowMSJE/HrX/8aUVFRePfdd3H69Gk7WPuS27dv48MPP0SPHj3Qr18/ZGVlgeO4BnVVVVVIS0tDTEwMoqKiMG/ePJSXl9vBYtMI8eff//430tLS8Jvf/AY9evRAQkICvvrqK9TV1dnJauMI3T9qlEolkpKSEBoaih9//NGGlhK6UHAzg0OHDmHx4sUYNWoU8vLy0KVLF0ybNg3//e9/Teo4jsPUqVNRVFSEOXPmYOPGjZg+fbqdrDaOUH/UMMaQkZGBwMBAG1tqHkL9yc3NRbt27ZCRkYHs7Gx07NgRkydPRlFRkV3srqysRHJyMkQiEXJycjBz5kxs3rwZ2dnZDWrnzJmD8+fPY9myZVixYgWuX7+OmTNn2sFq4wj15/Dhw7h37x6mTJmCDRs24L333sPmzZvx8ccf28lywzRm/6jZtWsXfv75ZxtaSRiFEQ0SHx/PFixYwP/mOI4lJiayefPmmdRt376dRUdHs6dPn9raRIsQ6o+avXv3smHDhrHVq1ez2NhYW5lpNkL9KSsr0ysbN24ce//9961uoyFyc3NZdHQ0q6qq4ss2bNjAIiMjtcp0uXz5MgsJCWEXLlzgy/71r3+xkJAQdubMGZvabAqh/hjaDwUFBSwkJIQ9ePDAJraag1B/1FRUVLC4uDi2c+dOFhISwo4fP25LcwkdqOfWAKOQjRQAAA+fSURBVPfv38fdu3cxYsQIvkwsFiMhIQGnTp0yqS0sLMSIESPw2muv2dpMs2mMPwAgk8mwatUqpKamwt3d3ZammkVj/DHU8wwLC8OzZ8+sbqchTp48iX79+sHPz48v+93vfofa2lpcuHDBpO71119HTEwMXxYZGYl27drh5MmTNrXZFEL9MbYfAKCsrMz6hpqJUH/UZGVloVevXujTp48tzSSMQMGtAUpKSgAAnTt31ioPDg5GRUWF0QuhXC7HjRs30Lp1a8ybNw+RkZGIiopCWloaZDKZze02hlB/1KxduxbBwcEYNmyYzWy0hMb6o8vVq1cRHBxsNftMUVJSomf3m2++CW9vb94vc3WAymdTOlsj1B9DXLlyBWKx2KCf9qIx/ty8eRN79uxBamqqLU0kTEDBrQEqKysBAAEBAVrlzZo101quS0VFBRQKBTZu3IiamhqsW7cOCxYsQFFRET755BPbGm0Cof4AqpN9+/btSE9Pt52BFtIYf3TZvXs3iouLMWHCBOsZaAKpVAp/f3+98oCAAEilUqvrbI217Hry5Alyc3MxatQorV6TvWmMP8uWLcOECRPQsWNHW5lHNECTnIm7qqoKv/zyS4P1NO/gdScJZA3M3qxe3qxZM2RlZfFDeO7u7khNTcW9e/fQoUMHQfbrYg9/AGD58uUYPXo0QkNDBVpqHvbyR5Pr169j2bJl+P3vf4/evXtbYG3jMGQfY8zsGZp1dY5GqD9q5HI55syZAx8fH6SlpVnbPIsR4s+hQ4dw584d5Obm2tI0ogGaZHA7cuQIFi5c2GC9W7du8T0A3bs49Z2bbo9Bjbq8V69eWs+m1BfO27dvWy242cOfEydO4PLly1i0aBFfV/2qtlQqhZeXFzw8PBrlhxp7+KPJ/fv3MW3aNPTu3RsLFiwQaLXlBAQEoKqqSq9cJpMZ7DFo6gwNt1ZVVZnlr60Q6o8axhhSU1Nx+/ZtbN++nd+3jkKIP/X19fj8888xZcoUKJVKSKVS/jFETU0NZDKZQ3ujTYkmGdzGjh2LsWPHmlVXPeZeUlKCtm3b8uUlJSVo3ry50dfhvb29teqrUd9di8XWGxG2hz937txBdXU14uPj9ZbFxMRg9uzZmDFjhgDr9bGHP2rKysrw0Ucf4c0338SaNWsgkUiEG24hnTt31nt28+jRI1RXV5t81tS5c2dcunRJr7ykpMShz0KF+qPms88+Q1FRETZt2mS3556mEOJPTU0NHj9+jMzMTGRmZmot+9Of/oQOHTrg2LFjNrOZeEmTDG6W0L59ewQFBeHIkSPo378/ANWHmZq/jTFo0CAUFRVBLpfzvZpz585BLBYjJCTE5rYbQqg/w4cP599gU7N3714cO3YMOTk5aNeunU3tNkZj9s/z588xZcoUAMD69evh7e1tc3s1GTBgAPLz87Xu5r///nt4eXkhNjbWpC4nJwcXL15EdHQ0AODatWu4f/8+BgwYYBfbjdklxB9Atf23bt2KL774gvfJ0Qjxx8fHB19//bVW2dOnTzF37lzMnTvXrkPeTR5HfYPwKnHw4EHWrVs3tnbtWnbu3DmWmprKIiIi2K1bt/g658+fZ2FhYez8+fN82YMHD1hUVBSbNm0a+8c//sEKCgpYdHQ0++STTxzhBo9Qf3TJzs52iu/chPozceJEFh4ezg4cOMCuXLmi9WcPKioqWN++fVlycjI7c+YMKygoYD179mR/+9vftOoNGzaMpaWlaZVNmjSJDRkyhP3www/s2LFjLD4+no0fP94udhtDqD8HDhxgISEhbMGCBXr7wdA3cPaiMftHk/v379N3bg6Aem5mkJiYiOrqauTl5SEnJwddu3bF+vXrtXpfjDFwHKf1UL9t27bYvHkzMjMzkZKSAj8/P7zzzjsOz7wg1B9nRag/Z86cAQCD++PWrVs2t7tZs2bYsmULMjIyMH36dAQEBODDDz9ESkqKVj2O46BUKrXK1qxZg8zMTKSnp0OpVGLw4MEOfQsXEO6Pej/s2bMHe/bs0aqbmZmJpKQk2xtvgMbsH8LxiNircPUiCIIgCAug79wIgiAIl4OCG0EQBOFyUHAjCIIgXA4KbgRBEITLQcGNIAiCcDkouBEEQRAuBwU3giAIwuWg4EbYjT179iA0NJT/6969OwYMGIC0tDSTswDU1tYiOjoaoaGhOH/+fKPt+PLLL/VmNggNDcWXX36pVXbw4EH89re/RUREBEJDQ/HgwQMAwJYtWzB06FCEh4dbPEPCrl27tLbB8+fPG+eMkyOVSrX83bp1q6NNIpoIlKGEsDsrV65EUFAQampqcPbsWeTn5+Pq1as4cOCAwdm9f/jhBz47e2FhIeLi4qxu044dO9CmTRv+d1lZGdLS0jB48GAsXboU7u7uaNWqFYqLi5GZmYnx48cjMTERbm7CTqF169YhMDDQ7vks7Y2vry927NiBx48fY/bs2Y42h2hCUHAj7E5oaCifhLlPnz4oKytDYWEhLl68iD59+ujVLywshK+vL8LDw3H06FEsWrTI6tOG9OzZU+v33bt3UV9fj5EjRyImJoYvv337NgDVzAXh4eGC2+vevbtWMG0smsm5nQmJRIKePXuitLTU0aYQTQwaliQcjjpIGJqj7MGDB7hw4QKGDx+OCRMmoKamBocOHTJ73cePH8fbb7+Nt956C0OGDMGGDRsM5svUHJZcsGABPxt3SkoKQkND8cEHH+CDDz7A/PnzAQBJSUkIDQ216vxvBw8eRHJyMvr27YsePXogMTERubm5kMvlWvXGjx+PpKQknDp1CklJSYiIiMDGjRv55Xv37sXYsWPRs2dP9OrVC2PGjMHhw4f55WfOnMF7772H2NhYREZGYsiQIZg3b55WGxUVFVi2bBkGDRrEb7vs7GwoFAqterW1tcjKykJCQgLeeust9O7dG5MmTcLNmzettl0IQgjUcyMczsOHDwEAQUFBessKCwvBGENSUhIiIyPRvHlzFBYWYty4cQ2u9/Tp05g5cyaioqKwZs0aKBQK5OXlGQyimsyYMQMRERHIyMjAxx9/jJiYGL6n+N1332HdunX80GpD88VZQmlpKYYOHYqJEyfC09MTN2/eRG5uLkpLS/XmBvvpp5+wePFi/OEPf0D79u35yTM///xz5OfnIzExEVOnToWXlxdu3LjBPy8sLS3FtGnTkJCQgKlTp8LT0xOPHj3C6dOn+XXLZDKMHz8eMpkM06dPR+fOnXH16lXk5OTg0aNHvC319fWYOHEirl+/jkmTJiE6Ohp1dXW4dOkSfv75Z3Tr1s1q24YgLIWCG2F3OI6DQqFAbW0t/vnPf6KgoACJiYl6w3xKpRL79u1DUFAQP8fXyJEj8c033+D27dvo0qWLyXaysrLQqlUrbNq0iR+y69evH4YOHWpS16FDB37dnTp10hqyVM+erjm0ai1mzZrF/58xhujoaPj7++PTTz9Fenq61uzP5eXlyM3N1bLt7t272Lx5M8aNG4eMjAy+XHNeu+vXr6O+vh5/+ctf4OPjw5ePHj2a//+WLVtw79497Nu3D127dgWgGj729PTEypUrMXnyZAQHB2Pfvn24fPkyVq9ejcTERF7vyAlTCUINDUsSdmfMmDEIDw9HVFQUZs6cibCwMKxYsUKv3tmzZ/HTTz9pXXjHjBkDQNWjM0V1dTWuXbuGhIQErWdR/v7+GDx4sJU8sS53797Fn//8ZwwcOBDh4eEIDw9Heno6OI7Te2bVsmVLveeEZ86cgVKpxLvvvmu0je7du8Pd3R0pKSk4fPiwwbdUT548ifDwcHTq1AkKhYL/U0+EevHiRQDAqVOn4O/vrxXYCMJZoJ4bYXdWrVqFoKAgyGQy7N27F/v378dnn32GxYsXa9UrLCyESCTCkCFDIJVKAajmyOvatSv279+PuXPnGny7ElC9gs4Yw+uvv663rGXLltZ3qpFUVVVhwoQJ8Pf3xx//+Ed07NgRnp6euHLlCpYvX47a2lqt+q1atdJbR3l5OQCYfFGlU6dOyM/Px8aNG5GWloaamhqEhIRgypQpePvttwGoZo5++PCh0Rdm1O2Ul5ejdevWgvwlCFtDwY2wO126dNF6W7KqqgrffvstRo8ejcjISABAZWUl/v73v4MxhpEjRxpcz4kTJ4wOgQUEBEAkEuHp06d6y548eWIlT6zH2bNnUVZWhq+++gq9evXiy//zn/+YvY4WLVoAAB4/fmzyWWBcXBzi4uLAcRyuXbuGvLw8zJ8/H23atEFsbCxatGiB5s2bY+nSpQb16oAWGBiIGzdumG0fQdgTGpYkHE56ejrc3NyQlZXFlx08eBByuRzz5s3D119/rfWXn58PDw8P7N692+g6fXx8EBkZiaNHj2q9bSiTyfDjjz/a1B8hiEQiANDqiTLGTPqoS79+/SAWi1FQUGBWffVr+qmpqQBezj4+YMAAlJaWolWrVoiIiND7U/ca+/fvj6qqKnz33Xdm20gQ9oJ6boTDad++PcaNG4etW7fiypUr+NWvfoXCwkIEBgYiOTnZ4Pdb8fHxOHLkCJ48eWJ0mHH27NmYPHkyJk2ahOTkZCgUCmzYsAE+Pj6orKy0qg9r1qxBbm4utm3bxr/8YglRUVHw8/PDokWLMGvWLDDG8O233/LDsebQsWNHTJo0CRs3bsTz588xYsQIeHt749atW1AqlZg8eTK2bduGixcvYuDAgXjjjTfw/PlzbNu2DR4eHvzH8R999BGOHj2KCRMmIDk5GV26dIFcLsfDhw9x4sQJLF26FG3atMGoUaNQWFiItLQ0/O9//0NMTAzkcjkuXbqE2NhYDBw40OLtQBDWgnpuhFMwY8YM+Pr6Ijs7Gzdv3kRxcTFGjx5t9MPkcePGQaFQYN++fUbX2bdvX6xduxZSqRRz5szBypUrMXz4cP6lFGfitddeQ25uLiQSCebOnYslS5YgJCQEaWlpFq1n/vz5WLZsGUpKSjB37lykpKTg+++/R7t27QAA3bp1Q11dHb744gtMnjwZ6enpAID8/HyEhIQAAPz8/LBjxw4kJCTgm2++wZQpUzB//nzs3r0b3bp1Q0BAAABVL3PTpk2YOHEiDh06hOnTpyM9PR03b9606gfqBCEEETP0RStBEDZh165dWLhwIY4fP47WrVsLTt/1KqFQKHDv3j2MGDECn376Kd5//31Hm0Q0AVz/zCIIJ2TIkCEAgMuXL8PX19fB1tgOqVSqlb6MIOwF9dwIwo48e/aMz8gCqFKPicWu+3SA4zgUFxfzv9u2bWvVrC4EYQwKbgRBEITL4bq3jARBEESThYIbQRAE4XJQcCMIgiBcDgpuBEEQhMtBwY0gCIJwOf4PGUQNyz0taU8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "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": 17,
   "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": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "667 sources flagged.\n"
     ]
    }
   ],
   "source": [
    "GAIA_FLAG_NAME = \"combo_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": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "catalogue.write(\"{}/COMBO.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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}