{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final Processing of SA13 Blind source catalogue\n",
    "\n",
    "![HELP LOGO](https://avatars1.githubusercontent.com/u/7880370?s=100&v=4>)\n",
    "\n",
    "\n",
    "The final processing stage requires:\n",
    "1. Quick validation of blind catalogues and Bayesian Pvalue maps\n",
    "2. Skewness level\n",
    "3. Adding flag to catalogue\n",
    "4. Merging MF catalogue with XID+ flux densities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "from astropy.table import Table,hstack\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pylab as plt\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.table import Column\n",
    "\n",
    "import herschelhelp_internal\n",
    "from herschelhelp_internal.utils import gen_help_id\n",
    "import numpy.core.defchararray as np_f\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cat=Table.read('./data/dmu22_XID+SPIRE_SA13_BLIND.fits')\n",
    "cat['RA'].unit=u.deg\n",
    "cat['Dec'].unit=u.deg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=10</i>\n",
       "<table id=\"table112092148848\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>HELP_ID</th><th>RA</th><th>Dec</th><th>F_SPIRE_250</th><th>FErr_SPIRE_250_u</th><th>FErr_SPIRE_250_l</th><th>F_SPIRE_350</th><th>FErr_SPIRE_350_u</th><th>FErr_SPIRE_350_l</th><th>F_SPIRE_500</th><th>FErr_SPIRE_500_u</th><th>FErr_SPIRE_500_l</th><th>Bkg_SPIRE_250</th><th>Bkg_SPIRE_350</th><th>Bkg_SPIRE_500</th><th>Sig_conf_SPIRE_250</th><th>Sig_conf_SPIRE_350</th><th>Sig_conf_SPIRE_500</th><th>Rhat_SPIRE_250</th><th>Rhat_SPIRE_350</th><th>Rhat_SPIRE_500</th><th>n_eff_SPIRE_250</th><th>n_eff_SPIRE_500</th><th>n_eff_SPIRE_350</th><th>Pval_res_250</th><th>Pval_res_350</th><th>Pval_res_500</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>deg</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th>mJy/Beam</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>bytes27</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th></tr></thead>\n",
       "<tr><td>8</td><td>197.855149993</td><td>42.5671160212</td><td>67.8592</td><td>70.8763</td><td>64.6702</td><td>61.9552</td><td>63.8792</td><td>59.3428</td><td>45.0168</td><td>49.4403</td><td>40.5577</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>0.999346</td><td>0.999348</td><td>0.998874</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>16</td><td>197.893045015</td><td>42.4977312992</td><td>44.0255</td><td>48.5561</td><td>39.9203</td><td>31.6237</td><td>35.3951</td><td>27.8582</td><td>19.0988</td><td>23.9203</td><td>14.2767</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>0.999268</td><td>0.998481</td><td>0.999528</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.001</td><td>0.0</td></tr>\n",
       "<tr><td>23</td><td>197.952630645</td><td>42.4605772106</td><td>47.8785</td><td>52.8323</td><td>42.9732</td><td>36.9955</td><td>41.9094</td><td>32.1833</td><td>44.4419</td><td>51.9702</td><td>37.1096</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>0.999853</td><td>0.999552</td><td>0.998209</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.001</td><td>0.0</td></tr>\n",
       "<tr><td>35</td><td>197.864409222</td><td>42.49879897</td><td>29.5685</td><td>34.166</td><td>25.0656</td><td>27.9472</td><td>31.6208</td><td>24.1863</td><td>7.34832</td><td>11.0765</td><td>3.43822</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>0.999546</td><td>1.00016</td><td>1.00098</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>66</td><td>197.897155093</td><td>42.5113478736</td><td>47.7785</td><td>52.0938</td><td>43.4461</td><td>70.8185</td><td>74.0807</td><td>67.4937</td><td>58.0083</td><td>62.633</td><td>53.7125</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>0.99885</td><td>1.00044</td><td>1.00039</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.001</td><td>0.0</td></tr>\n",
       "<tr><td>101</td><td>197.930695344</td><td>42.5099996023</td><td>25.2612</td><td>28.7756</td><td>21.9671</td><td>21.5853</td><td>25.5749</td><td>17.6083</td><td>15.1688</td><td>19.4054</td><td>10.742</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>1.00196</td><td>1.0018</td><td>0.999545</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>105</td><td>197.931033478</td><td>42.5297219563</td><td>21.7857</td><td>25.296</td><td>18.4972</td><td>30.4202</td><td>33.3535</td><td>27.3395</td><td>24.3927</td><td>28.5369</td><td>20.1483</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>0.999197</td><td>1.00171</td><td>0.999674</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.007</td><td>0.0</td></tr>\n",
       "<tr><td>123</td><td>198.002314994</td><td>42.4806095401</td><td>17.5904</td><td>22.2433</td><td>12.9469</td><td>2.89647</td><td>6.45764</td><td>0.853462</td><td>5.1742</td><td>9.7608</td><td>1.88636</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>1.0002</td><td>0.999584</td><td>1.00069</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>202</td><td>197.943605894</td><td>42.4539024374</td><td>19.699</td><td>24.5401</td><td>14.5753</td><td>10.6107</td><td>16.202</td><td>5.30745</td><td>2.29366</td><td>4.45961</td><td>0.690519</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>0.999728</td><td>1.00261</td><td>0.999986</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.0</td><td>0.0</td><td>0.0</td></tr>\n",
       "<tr><td>206</td><td>197.964198464</td><td>42.5336412393</td><td>8.40086</td><td>11.5089</td><td>5.13179</td><td>3.92352</td><td>6.83111</td><td>1.4877</td><td>1.53595</td><td>3.50255</td><td>0.389238</td><td>-0.0708282</td><td>-0.0872433</td><td>-0.05502</td><td>0.005978</td><td>0.00867867</td><td>0.0115186</td><td>1.00035</td><td>0.999029</td><td>0.999893</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.001</td><td>0.0</td><td>0.0</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=10>\n",
       "          HELP_ID                 RA      ... Pval_res_350 Pval_res_500\n",
       "                                 deg      ...                          \n",
       "          bytes27              float64    ...   float32      float32   \n",
       "--------------------------- ------------- ... ------------ ------------\n",
       "8                           197.855149993 ...          0.0          0.0\n",
       "16                          197.893045015 ...        0.001          0.0\n",
       "23                          197.952630645 ...        0.001          0.0\n",
       "35                          197.864409222 ...          0.0          0.0\n",
       "66                          197.897155093 ...        0.001          0.0\n",
       "101                         197.930695344 ...          0.0          0.0\n",
       "105                         197.931033478 ...        0.007          0.0\n",
       "123                         198.002314994 ...          0.0          0.0\n",
       "202                         197.943605894 ...          0.0          0.0\n",
       "206                         197.964198464 ...          0.0          0.0"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Look at Symmetry of PDFs to determine depth level of catalogue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(cat['FErr_SPIRE_250_u']-cat['F_SPIRE_250'])/(cat['F_SPIRE_250']-cat['FErr_SPIRE_250_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(cat['F_SPIRE_250']),y=skew, kind='hex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 250 $\\mathrm{\\mu m}$ depth is ~ 6mJy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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SMcaYBjdrE5QfKD0Zn4wXrpSdzykDeY/OlEsqbieOxhjT6GZdglJV+nMBu7MBI5s4BAo7B30SuYDOtIvr2NmUMaax7ezPTXcI02bWnUrkfC2bnIq08MdykzHGNLZZl6BqaX0nNY4zxhgzfWZdgjLGGDM7WIIyxhjTkCxBGWOMaUizMkFVu7+kVGn1O8lU7Y6XMcaM1axLUElXaI5XTj9COEcqmIKcEajiBcpAXglULVEZY8wYzLp5UCJCRzpGc0LpHvTwgj1nVAK0JR2aE05dV5RQVRTozQb05QIAenPQmXKJu+DYahbGGFPVrEtQRXFXWNgcYyAfTtpNuEJHqv6TcwNVsl64ikXpWZofwPYBn1RMmJd2AWzZJWOMiTBrExSECaA54dKccKdsn9v7PfJB5ecznpLzlWRs1l1dNcaYSWVHSWOMMQ3JEpQxxpiGZAnKGGMa2LzmxHSHMG0sQU2yVEyo1s3DFqo1xpjqZnWRxHRoTbq0JqE/H7A7M3xV9YQrYZsPCUvRrYrPGGMqq9sZlIjsJyK3i8hGEXlcRD5eZoyIyDdE5BkReVREjqhXPFNFRMLqwbjD3q0x0nHBEehMu8xvcok5MjTGGGNMZfU8g/KAv1XVh0SkFVgvIr9R1SdKxpwKHFD4cwzwn4X/z3giggAdKXdoWSVLSsYYU7u6nUGp6mZVfajwdS+wEdh3xLB3Av+tofuADhFZXK+YpkNx1QhLTsYYMzZTUiQhIsuB1wD3j3hqX+Clku+7GJ3EEJHzRWSdiKzbtm1bvcKsG0tOxpixmOnHvMlS9wQlIi3AT4FPqOrukU+X+ZFRK6qq6hWqulZV1y5cuLAeYRpjTMOwY16orglKROKEyelaVb2hzJAuYL+S75cAr9QzJmOMMTNDPav4BPgusFFV/63CsJuADxSq+Y4Fdqnq5nrFVA/WQsMYY+qjnlV8xwHvB/4gIhsKj30GWAqgqt8GbgHeBjwDDAAfrGM8k6rYUqP4tbXQMMaYyVW3BKWqd1Olca2Gpx8frVcM9RKo4gfQPeiTD5SWhENr0kGwgghjjJkstpLEGBTPmnZlAgZKemr05QIG8wEdKZdk4R21RGWMmQw7+3PTHcK0sQQ1Bt2DPlm/fLt4X2HHoM+iJpe49XoyxpgJsyPpGHhB+eRUykomjDFmcliCMsYY05AsQRljjGlIlqDGwMoejDFm6liRxBgsaI7hB7Az45P3R99tak04xF2xXk/GGDMJLEGNgYjgOsqCJpdMXtmV9QkUkjGhM+XiiJWXG2Mm11xu+W4JaoyKfZ7ScUjFY3iBEnPEVpIwxphJZglqnIqJKu7YWZMxxtRDTUUSInK8iHyw8PVCEVlR37BmDktOxhhTH1UTlIhcAlwM/N/CQ3Hgf+oZlDHGGFPLGdTpwDuAfgBVfQVorWdQxhhjTC0JKldYdVwBRKS5viEZY4wpmsuLxdaSoH4sIv8FdIjIXwG3AVfWNywznVR16I8xxkyXqlV8qnqpiJwC7AYOBD6vqr+pe2RmWgSqZPJKf96nPeUSc7ASemPMtKipzLyQkCwpzVLFPldBAN0Zn1xhlYxt/T7puNCRcoeWebKqRWPMVKmYoESkl/LdI4SwGW5b3aIyUyrrKRlP6S9pwlg0mFcyeY+FzTGszZUxZipVTFCqapV6c0R/PiDjVb7fpIS9sOKuZShjzNSJOoNqU9XdIjKv3POqurN+YRljjAFbi6+SHwCnAesJP0SX3nxQYGUd4zLGGDPHRV3iO63wf1vWyBhjzJSrZamj39bymJm5WhMObUmnYkNGV8JFcW1elDFmKkXdg0oBTcACEelkzyW+NmCfKYjNTJG4K8RcoSnu0JPxhxVMtCQcWiOSlzHG1EvUPagPA58gTEbr2ZOgdgOX1zkuM4WKrUMQ6Ey75H2lPxfQnnIRsYm6xpjpEXUP6uvA10XkY6r6H1MYk5lGjggJFxJp1yblGmOmVS1LHf2HiLwOWF46XlX/O+rnROR7hFWAW1X10DLPtxO27Vha2O6lqnrVmKI3dWGJyRjTCKomKBG5Btgf2AD4hYcViExQwNXANyPGfRR4QlX/TEQWAk+KyLWqOneX7jXGGDOklrX41gKH6BhLuFT1ThFZHjUEaJXw43oLsBPwxrIPY4wxs1cta9c8Buxdh31/EzgYeAX4A/BxVR29GBwgIueLyDoRWbdt27Y6hGKMMY3DjnmhWhLUAuAJEfm1iNxU/DMJ+34L4WXDfYDDgW+KSNkFaFX1ClVdq6prFy5cOAm7nr0ma66SzXkyZvrYMS9UyyW+f6jTvj8IfLlw6fAZEXkeOAh4oE77m9XCBoOQ9ZVU4bc6nmKHYuuNjBduR8a5HWOMmahaqvh+JyLLgANU9TYRaQLcSdj3i8DJwF0ishdhM8TnJmG7c0oxoQzkAnZnAxSIOdCZcom5tc9hKp4x9Y/YTkfKJT6G7RhjzGSppYrvr4DzgXmE1Xz7At8mTC5RP3cdcCLhShRdwCVAHEBVvw38E3C1iPyB8IP6xaq6fdyvZA4KVPECpXvQxyu5e+cFsG3AJx0TOtPhZ4mos6BAFT+A7kGP/IjtbB/wSRW2Y2dTxpipVMslvo8CRwP3A6jq0yKyqNoPqepZVZ5/BXhzLUGa8nYO+GT9yveKBj2lyVNS8ehbjd2DfmQ/qIynZD0lXWU7xhgzmWo54mRL5yaJSIzynXaNMcaYSVNLgvqdiHwGSIvIKcBPgF/UNyxjjDFzXS0J6tPANsK5Sh8GbgE+V8+gjDHGmFoSVBr4nqq+R1XPBL5XeMxMs4QrxKr8Bp0aahriTvXtWG2EMdNjZ3+OH9z/4nSHMS1qSVC/ZXhCSgO31SccMxatSYeFzTHay/RrijmwsMkl7krVSbetSYdFFbbjOrCgySVZw3aMMWYy1VLFl1LVvuI3qtpXmAtlplmxj1NzwhnWbLA16dCScIbG1LIdittJFLaTD7fTnHCsvNwYMy1qSVD9InKEqj4EICJHAoP1DcuMhYggAh2FuUrFx8a1HcLJuZIKSzVtgq4xZrrUkqA+DvxERF4pfL8YeG/9QjLj5Uh4GW6iZzvF7VhyMsZMp8gEJSIOkCBcI+9AwhUf/qiq+SmIzYzDZF2Ks0t6xpjpFpmgVDUQka+p6msJ224YY4yZQvOaE7zvmKXTHca0qKWK739F5N1iH6mNMcZMoVruQX0SaAZ8ERkkvMynqlq2d5NpfJNxn8oYY+qtlnYbrVMRiJkaQXEukyUpY0yDq3qJT0J/ISL/r/D9fiJydP1DM5MpbKkRtubY3OuxOxsQqNrkW2NMw6rlHtS3gNcC7yt83wdcXreIzKRSVQJV+nMBW/q8obYafbmArX0eWU8L3XgtURljGkst96COUdUjRORhAFXtFpFEneMyk2R3JiDjB8MaGhb5CjsG/XApo2qL8RljpsXO/lz1QbNULUelvIi4FHpAichCoMzhzjSifKBlk1OpwE6ejDENqJYE9Q3gRmAvEfln4G7gX+oalTHGmDmvliq+a0VkPXBy4aF3qerG+oZljDFmrqvlHhRAE1C8zGe9oIwxxtRdLWXmnwe+D8wDFgBXiYh11J0h5je5LGqOEXfLz3lqigupmPV6MsY0nlrOoM4CXqOqGQAR+TLwEPDFegZmJoeIEHOUhU0ug3llV9YnUIg70Jl2cR2xCbvGNLB5zXO3aLqWBLUJSAGZwvdJ4Nl6BWQmXzEBpeOQisfIeUoyJsOeM8aYRlNLgsoCj4vIbwjvQZ0C3C0i3wBQ1QvrGJ+ZRMWGhMmYJSZjTOOrJUHdWPhTdEd9QjFTxZKTMWYmqKXM/PtTEYgxxhhTyta3McYY05DqlqBE5HsislVEKnbiFZETRWSDiDwuIr+rVyzGGGNmnnqeQV0NvLXSkyLSQbhS+jtUdTXwnjrGYiZZcQV0mz9ljKmXyHtQIrIE+HPg9cA+wCDwGPBL4FZVrbgMqareKSLLIzb/PuAGVX2xMH7rmCI30yZQJeeFLTzaUy6OozhWeGGMmWQVz6BE5Crge0AO+ArhhN2/AW4jPDO6W0TeMIF9vwroFJE7RGS9iHwgIpbzRWSdiKzbtm3bBHZpxqt4tuQHys5Bnx2DPhlf2dLvsTuzp/mhnVEZM3F2zAtFnUF9TVXL3T96DLih0BNq6QT3fSThIrRp4F4RuU9Vnxo5UFWvAK4AWLt2rR0Bp0HOU7K+0psbfdLcnw8Y9AIWNLnEHDuTMmai7JgXqpigKiSn0udzwDMT2HcXsF1V+4F+EbkTWAOMSlBm+vXlg6FuvOUECnmfimv+GWPMWNWyWOxxIvIbEXlKRJ4TkedF5LlJ2PfPgdeLSExEmoBjAGvjYYwxBqhtJYnvAhcB6wG/1g2LyHXAicACEekCLgHiAKr6bVXdKCK/Ah4l7ND7nWpnbcYYM9fM5ZbvtSSoXap661g3rKpn1TDmq8BXx7ptY4wxs1/FBCUiRxS+vF1EvgrcQLhwLACq+lCdYzMT5AfKroxP3BVaEs6E1uBrjjvEHKWvTJEEgCMQd8Nqv4nsJ9AwZkegNela+boxc1hkFd+I79eWfK3AGyc/HDMZVMNE0psNUCBTmLPUmXZJxsY3NzsZE5KxMNF1D/pk/T0FE01xh/aUw0RSiaoykA/YlQljFmAg79GRcknHbUUuY+aiqCq+kwBEZKWqDiuKEJGV9Q7MjE/WC+geDJsSFlOIAr7CjgGfZCygIxU2KhyL4lmRKzCvySXnhUmwPeXiOkzoTCfnK92DHn4wPGZV6B706SskVythN2ZuqeWj6fVlHvvJZAdiJs4PlO0DPn5JciqlhMlgosd5R8KzqflNLrEJJqdAlW39Hl4QHbNVrxsz90TdgzoIWA20i8gZJU+1EXbYNQ0m0PDSWNSsPhGGLqFNxGT1lKpl4QnLTWau+8H9L/K+YyayLsLMFHUP6kDgNKAD+LOSx3uBv6pnUMYYY0zUPaifAz8Xkdeq6r1TGJMxxhgTuVjs6SIyT1XvFZGFIvJ9EfmDiPyosMq5McYYUzdRRRL/rKo7C19/E9gAnArcClxV78DM+NSyqqTd0zHGzARRCcot+XqVqv67qnap6tXAwvqGZcYj5kA6Fp1+ggC8oHEWR3YEmhPVU2beb5yYjTFTIypB3SEiXxCRdOHrdwGIyEnArimJzoyJiDCvKcbC5rD8e+RhPx0T9mqJEXcbZ+KriNCRirGoOUZ8RMwCJF1hUUuMxDgnGBsz081rTszJCj6ITlAXEC7i+iRhO/YbRKRYwff+KYjNjFPCdVjUHKMtGa7u4AosaHKZ1xQb8wTdqRJ3hYXNsaEVKZzChOAFzTGboGvMHBVVxZcH/gH4BxFpB2KqumOqAjMTIyK0JF2aE87Q941ORGhOuDTFZ07Mxpj6qem6iaruKk1OhUm8ZgYQkRl3oJ+JMRtjJt94L+z/76RGYYwxxowQtdTRNyo9Rbi6hDHGGFM3UUsdfRD4W0p6QJWo2ozQmHJyXoCIELfVX42piXXULe9B4DFVvWfkEyLyD3WLyMxKfqD0ZHyynqJAc1xoS1lDQmNMZVEJ6kwgU+4JVV1Rn3DMbDOyeWJRf14Z8Dw6Uy6pmBVFGGNGq1gkoao7VXWg9LGSNvDGVKWqbO3zRiWnPc+HDQltkQhjTDljreL7Tl2iMLNSoOBVaJ5YJII1IzTGlDXWBGWHEmOMMVNirAnqH+sShTHGGDNCVJHEEBHZF1gG7BSRNwCo6p31DMwYY0y4WOxcVTVBichXgPcCTwB+4WEFLEFNMVW1ajdjzJxRyxnUu4ADVbXchN1pMRcP1IEqwsx67Y6EfzSiUEI1LKawQgljzEi13IN6DoiPdcMi8j0R2Soij1UZd5SI+CJyZi3bzQfKoKcEOjdqk1XD19oz6LO516M/F6Cq6Ax4/SJh/6lKDQkFaEs6WDcNY0w5UWvx/QfhB98BYIOI/JaSZY9U9cIq276asFX8f0fswwW+Avy65ogLc2cSrtCZdoc+ec+Us4paqYYrLgzkAnaXzCPalQ3ozwfMS4dNCaGxX7sjQnsqRnNc6c745P3wdaVjQnvKbdj+VMaY6Rd1iW9d4f/rgZtGPFf147uq3ikiy6sM+xjwU+CoatsbKecrW/o89m5p3CZ8E7HMvJLXAAAgAElEQVQ7G5DxArxg9HNeAFv7fRY2uyQaqDtulJgrLGhyyXqKI1iHXGNMVVENC78PICIfV9Wvlz4nIh+f6I4LlYGnA29kHAmqaAZc6RqXnK9lk1OpYIa9dhEhFZ99HyaMqaed/Tl+cP+Lc7Ltey0fY88p89i5k7Dvy4CLVdWvNlBEzheRdSKybseO7ZOwa2OMaVylx7zenp3THc60iboHdRbwPmCFiJRe4msFJqP1+1rgh4X7JwuAt4mIp6o/GzlQVa8ArgBY85ojZ9h5gzHGjE3pMW/lwYfN2WNe1D2oe4DNhMnjayWP9wKPTnTHpSuii8jVwM3lkpMxxpi5Keoe1AvACyLyLmBfwsKIV1R1Sy0bFpHrgBOBBSLSBVxCoVxdVb89wbgBaI47uM7MmhtUq/lNLnk/7KFU7l5UOiYkXan7a1dVMl4YhyMwLx2b9maDGS+ge9BHgHlpd04VXOT88LUHStiqJD53XruZe6Iu8R0OfBtoB14uPLxERHqAv1HVh6I2rKo1d91V1XNrHQsQd4XOlIvrNHaJ9UQ4IiRcWNgco7+kn1LMCQ9MMbf+PZS8QOke3FMaHihs7fdoiocl4lPdbNAPwlL1XKHpIcD2AZ9ULJj1JevFuXCD3p6rPTsHfRK5gI60S2wWv3Yzd0Vd4rsa+LCq3l/6oIgcC1wFrKljXBW5TliuLMze5FQkIgjQnHBoijtkPSVdqIKr91lTbzagL1e+j9NAXhnMeyxsdolPUZl7b9Yv21dKgUFPyfR5zG9ySc7Cs6n+nM+uTPnXni1Mt5iXdknb2ZSZZaISVPPI5ASgqveJSHMdY4oULp8zuxPTSI4ICKTjU5OUfYXeXHSNuwhT9qk9UGV3NjoeBRKzdL2kcslppGRsdr52M7dFJahbReSXhCtBvFR4bD/gA8Cv6h2YGW0qzxiF6rOxlcZpENYocdTDnC3hMnNeVJHEhSJyKvBOwiIJAbqAy1X1limKzxhjzBwVuZq5qt4K3DpFsRhjjDFDKt5VFZHDSr6Oi8jnROQmEfkXEWmamvCMMcbMVVFlP1eXfP1lYBXhhN00Yfn5jDVT2lVMl1ruPxXHRZnK93k2/zZrub+miv2dnsXm4jp8EH2Jr/TfxcnAUaqaF5E7gUfqG1b9BKpkPSXrBbSl5ka5+li5jjC/yR2aEDqSAK4IfgAxt/w2AlW8QOnPBbQm3QlVXzoSTi0oxlPpMLx9wKcz5eI4s6vSc2FzjJ2DHn4w+rULYWWrHyjuLCyxN3NbVIJqF5HTCc+ykqqaB1BVFZEZ9VGt2FspKPSSyvlh+AN5j7aUQ3PJ/BFLVqFUzGHvFhk1H0qAjrRLOjZ6onDxE7zCsEmlA3mPloRDa9IZ+tQz1vc5GXPYq0XoK5m0PFLOV7b0ezQnHNomsK9GE3eFRc0xBvLBsJJzgT3v6wx/jcaUE5Wgfge8o/D1fSKyl6puEZG9gRm1pHg+UAbzSt+IuT1KOMdkIBewoCmG/RsfTkRoS7k0JRx6Mj4xgbaIFSTygZLzdFiDxaK+XMBgPmBB0/hXfBARWpMuTXGHbf0efoWPSf0l+5otKyyICM2JcDLurkx4Jtmemj2vz5hyosrMP1jh8T8RXvKbMboHy69nV5QPwsmpcfvHXlbMERY0RRZ8AtCXDYYtxTOSr+HKB80TXH3CdYRUTOjPV95XoJDxlNbk7Lrs5YjQma7+uzBmNoiq4js+6gdFpE1EDp38kIwxxpjoKr53i8g9IvJ5EXm7iBwtIm8Qkb8UkWuAmwkr+owxxtTRD+5/cbpDmBZRl/guEpFO4EzgPcBiYBDYCPyXqt49NSEaY4yZi6LabbwWuE9VrwSunLqQJl9rwglXvK5wfyQsgZ7ioGahdNzBEaU/X/6GnxDe55toD6tAdagSM0rGC1BVWpPuuPdXXNkdsGo5Y6ZY1N3Wc4DLReQpwsVhf1UokJhx0nGHVBzyfthPyC85fpaWJM/GxodTKRUTkjGhJeGEfZtKkkgqFvbwmsjbW9o8sdz8rJFyflh63p/36Ey7pMY4T6jYGLG4r/58MK7tGGPGJ+oS318DiMhBwKnA1SLSDtxOmLB+r6r+lEQ5QcW+SgkXFhUaAGY8nZWTOqdT8X123LAjcMZT+rI+HYUGixN5n0c2TxyLQGHngE8iFhQaXUbH4QVhc8DciH0Nbce1JoHGTIWq9aqq+kfgj8C/i0gaOInwntS/AWvrG97kKh5AWxIOLYmZP4GzkTkipGOQjoV/xSbyXqsqW/u8CS1npEDW06pncNX2VWwS6IidcRtTbzVNqCgUS+xDWCTxq5nebsMOKlNjst5nZfLW2qtpXbsat2N/j4ypr6giiXbgo8BZQALYBqSAvUTkPuBbqnr7lERpjDFmzok6g7qesJvu61W1p/QJETkSeL+IrFTV79YzQGOMMXNTVJHEKRHPrQfW1yUiY4wxhtrvQe0LLCsdr6p31isoU95MvClfS8wz8XUZY+qvaoISka8A7wWeAIpl5QpYgpoixXYhXqDEZkhZvKoOLdiailG2tHvodflKzK1ceCBAU1wYiFgctlb9uYDmRDiPqey+RGhOCP256H1lfSUVa/zfgzEzWS1nUO8CDlTVbL2DMaMVGywWJ6cmXaEzHTYAbNSzDj8IV5N4bmeerK+0JBz274wTd2UoUQWqwyZOx11hXsrFcXRUApbCCt7NiXDibLnGfbXalQ0YKEy4dSsk+45UjOa4jmoSKIDrwLx0jLjbmO+9MbNJLQnqOSAOWIKaQqqKr2Hjv2zJigxZX/lTX9gAsC1Z+UxgOgSq+AE8352jO7NnuY6+XMAjW7Ls1eyytD0eNjTM+MOWnsoXmw3GHdpT5V9XwnVY1Cz05wJ2ZSP6p1SRD2Brv09TXGiv0FV5ZJNAgPaUQ1PcljsyZqpElZn/B+GHxwFgg4j8lpIkpaoX1j+8uWvHwPDENFJfLiAZk4ZadmdTd57tA37Fs5st/T5eoKTjlWPuzwfEHGhJlu8lLyK0JF3yfsCAN7F4B/KK6wS0Reyr2CQQZsalVWNmk6gzqHWF/68HbhrxXNUrLCLyPeA0YKuqjuobJSJnAxcXvu0DPqKqj1SNeI6YrImpUynQ6nHXsoZeLcKzmKl5lywxGTM9osrMvw8gIh9X1a+XPiciH69h21cD3yScS1XO88AJqtotIqcCVwDH1BK0McaY2a+W60PnlHns3Go/VChD3xnx/D2q2l349j5gSQ2xGGOMmSOi7kGdBbwPWCEipZf4WoEdkxzHh4BbI2I5HzgfYOnSpZO868YUc8ALoi+JTeWFp3xhgdSolcATrpBwJbJXUy0x13JFLedroex+Yu+CLUhuGlHpMW/B3vtOczTTJ+oe1D3AZmAB8LWSx3uBRycrABE5iTBBHV9pjKpeQXgJkLVr187E2zNj1pFyUWB3JhjVANCR8PmEO/Hmf9X4gbIr4zPo6dBK8JUa9+3XHmPfthiv9Hps7h2+IrgAHSmHdLxyrAK0FSrlKr0uL1Be2pVnW384Ja85IbSPo5GgAG1Jh+aIfRkzXUqPeSsPPkxhT9v39x0zNz6kQ/Q9qBeAF0TkXcC+hHekX1HVLZO1cxE5DPgOcKqqTvZZ2YxWbA3SlnJoSTjszIS9kEobLNbzoKqq9OcCdmeDoUSjhNWDxXlEyREVhCKCK7Bva4xFzS7PdefZnQ1oigsdqeiY03Gho0LJdzGe7QM+L/TkhxVj9OeUgbxPZ8qJrA4sVdo80RKTMY0r6hLf4cC3gXbg5cLDS0SkB/gbVX1oIjsWkaXADcD7VfWpiWxrNnNEEEdZ0OSiGl7+qndVmaqytd8rOyFWAV9h+4DPXi1S9hKb4whJRzhgXpwt/T6Bjp58W2pBk0s8oqGhqvLEtiwDeR11yVMBVdg5GLDIkaoTaKvtyxjTOKIu8V0NfFhV7y99UESOBa4C1kRtWESuA04EFohIF3AJ4YRfVPXbwOeB+cC3Cp9iPVWdUQ0Qp0rxbEqZmktRvlJ1tQZHqt+/KcYalQwcCe9dRb0uX8MzpWrXdmuZElZtX8aYxhGVoJpHJicAVb1PRJqrbVhVz6ry/HnAedVDNEV2YDXGzCVRCepWEfkl4TymlwqP7Qd8APhVvQMzxhgzt0UVSVxYmED7TsIiCQG6gMtnest3Y4yZqX5w/4tzppIvcrFYVb2ViPlJxpjKJqsX1mSVwTdaPMZUU/G2cqEEvPh1XEQ+JyI3ici/iEjT1IRnpkcNU81qmo2mVSfmBlp9fT5HwgKIqG0Jta3z52u46nrFeAIlUCWY4KKBxX1oxL50DGOiYq5FLduZrDHGTJaouqerS77+MrCKcMJumrD83MwyYZNBpa9KxZwALYW5WBPdTmvCqVoN6IiwZu8Ui5rdsmMdgcWtMfZpi9GciN7Y1j6P/lwQNkssOchqISlt7vN46JUMf+rz8AONTB7lFLfbnwvY3OvRmw0IyuyrljFBlTGTGU+gykA+HLN7nGOMmWxRl/hK/6WfDBylqnkRuROwVcdnkWJn29LGiJUkC5Ncozrk5rywEWHkdlyhI+3WvFSR6wjLOxMsagl4dmduqJdUS8JhRWd8qO1IR8qhOa50D/rkywSgwO5i08KUS8wN51EN5AOeLTRYBHhpt8e2AZ+VnXGa407VSb2l3YG7Mz5eYfGP3sLE5o60S6LQ1aPimJRLovAv0gvC11Ac05cLGCwZU22idjEeP4DuQY98yXaKr724r5Fj+kv2lRw2Zs97WhzTnnJJ1RCPMeMRlaDaReR0wrOspKrmAVRVRcQ+Ns0ifbmAjKeRa+g1xYWmuDNq9YhS/YXtRPWxSsegKeGOu49VU9zh0EVJdg4GuAId6dG9nOKusLDZZeegR6ZCzygvgG0DPkGgDHhKT2Z0A8SMpzyxLcf+nXHmN5XvGVU06AUM5nVYE8YiX8P+XslYOJ+t4pjBcIwDDEaMaU86Q23rK8kU4im3naC4L1dwpPy+AoWdgz4JV3AdGMyXH9M96NOaEFor9NQyZiKiEtTvgHcUvr5PRPZS1S0isjewvf6hmamS86OTE0AqFp2cituJSk4AyZgz4SaLIlI1YYgUV7mIjqc3F9Cbix6T8aoXBfhB+cRTKlvl+VrHeDU0Ew60fOIZtq8qvysIf6f41eNRpnbx4rlurqzLF1Vm/sEKj/+J8JKfMcYYUzdj+igrIlfUKxBjjDGm1FivtdhaecYYY6ZE5ETdMrbWJQozrTpSLvlA6Rn0KXdbIuEKySq9p7JeUPUeTMIVUrGJ91/KeQHdGR9B6Ey7FVcwb0m4pOPDq+FK9ecCnu/OESh0pGMkymwn5yt/2JLhj9uzrN0nXbYooyfj82DXAF4AK+claClTwJD3lZ2DPgrMS7tl9/WnPo/rH99F1lPOXN3Gso7EqDG9WZ87N/XjBcqb9m9hcWu87JgHXx4kk1dWzIvTVqaAoWfQ57fP9dGfCzh5/xb2bRu9nVrsHPC5YeNuegZ9PnRkJ4fulRo1JusFPNedJ+MpKzrjdKRGx5P1Ap7vzjPoKSs64mXf56ynbOrJMZAPWN6RoLPMGD8IKyTzvtKRcknFbHHgmUxm2jyGtWvX6rp166Y7jFmnWJbclw3ozYVH82JjxGQsbE9RLrH4QVianvUqz3lyhEI5cuXt1KLYPDEzYl/NcaEt5Y5aNX1oIiwwUNLbyguUF3vy7BgcXgpfup1Ald0Zn/6S6jVHYGl7nEP3SpFwhbyvPLY1M9SjqjhmXtplWUecmBNuZ1cmYCC/J2YB0jGhPeXgOkLWC/jVM3080DU4tIp83IHVi1K846BWmhMOXqA8sTXL8925oQ8RMQdWdCZ4w/JmmuLhmI3bsjy7Mzcsno6Uw/KOBPFCzA90DfDIlgxBYV8xB5a2JzhxRXPV6sCivK/c/nw/d27qL0x+Dj+AHLIoyQdf08H8phiB6lDzytJ4WgtTA5Ixh0CVzb0er/R6aKHPlyPh9IGVZcaUbqd0ioGq0pcL6C3pXyaEFZ2dY5jOMMVqCmrlwYfpF6++uexzM7hIoqbXXjVBicirgE8Byyg541LVN04kuvGyBFVf4YRMGMwHNCWimwz2Zf1hDQ3LaYo7tFdpVliL/pzPrkzlfQlhr6dEhQrBYgLeuDXDMzuHNz0s3QaEpfCDhfL0kWOKbUb2a4vRtdsbOjgPG0PYt2tJexw/KL+d4v429+b45VN95H1lRONkXAnnf528som+nOIHOuoM15Fw3OGLU2wfCMqOkUI8cQfWvTxIPtBRZ5TF13XK/i2smp8sE+0ez+zI8cPHdpHJBxVj/j+HtrGoOYYfQLmiQ0dgftplV8bHK/MeSuE/89Muu7PhGXC5eXUC7NMaI+ZQ9ndaHNNWKM1vsLMpS1BV1HKJ7yeEK0dcSdWCUzPTFbviVvvH7AfKrmx0vXPx0/tEDwqBlp+nVEohslmhFM7cntyRj9wGwECFuVNhLOGf53sqDwoKG8v70WeKCtzwRG/Zy6pQ6MvlK9v6/bITo0vj6drtVW74SDgZ+Z6XBoYSZqXt7FPDpb4f/mHX0Fl2pZjjjoxKXiP3t22g8uFEC//ZHjGmOM4Lqr/PyVjDJadJUSw3H69GT3C1JChPVf+z7pGYhlLLP+bqs4ymzkw99NTy/k3acbWGndVyJayWdfimMhnM1N+9qS6q5fu8wpe/EJG/AW4EssXnVXVnnWMzxhgzh0WdQa1n+ATxT5U8p8DKegVljDHGRK0ksQJARFKqmil9TkRG15IaY4wxk6iWmtJ7anzMzDHV7kRM5QyGWnc1lfcraokpoq5jSC2tqWp5r8PbQtEDvRpajNRSsl3LdmqZ4jKyLUo5QQ3bUmqLZ6qm3cy06T3TJeoe1N6Erd7TIvIa9vzbbgOsYeEc5zrCvLRLd8Yve3AUwhvuXqCR1XW1cESYX9hXpVJjRyAfaNkJsBDe2A8UVi9K8uT2bNny8OJ2mhMO/bmgYtlyNZ4fMJDz+PWjXbxjzT60peOjyt8DDRfoXdmZCOctMToet1D6PZAPaEu6ZYtSVMOS8Q2bBzlwYYp0TEZV/Pl+QMYLeOqlbSyc10ZTMo7rjIjH98nnc/y/K+/gY+86nn0WdJJKDp8o7AVK1lOSMcEb1PKJKgjwPI/Lfnon57zx1Sye304yMbwyUDUshd/cm2d+OlzZ3ikTc9YPuGnDyxy7cj6LO9IkY8Mn5gaF1/7LJ3s5at80i1pGT7YuTi/Y1J1ncWuMprgz6v0pjunNBqRiQtylYkXkRBX3tTsblJ2wPNUmWgVYqh4VgRXnQYnIOcC5hMsbPcieBLUb+L6q3jDp0dTA5kE1lnITWus170RV2Z316csN31dr0qGlzL5KJ+r2ZgP6CqXRgSqv7A4nfpZqSTi0Jp2hkvTiz9SapFSVvK/c+eSfuO3xzXiB4opw2mGLOf2IJcRjzlDn32d2ZvnjtmyYBAuTTHdnS16XwF7NLvu2xSNKzJWtfR4v7d4zgXX/zjir90oNnZl5vnLfs9u49dGXyfkBAqxc3Mma5XsNJRjP93jqsQ08eNft5PM5HBHe/abXctFfvINkPIbrOuQD5c5NA/zoD7uGVkkvTmx2RVAU3/fZ8uLzPPmHh/C9PCLwxiMP4bx3vCHcjuMQADv6PV7clR8qr1/Q5LK0IzEUc94PuPfZ7Vxz7wv058Iy8+NXLeDc41aQjDu4IvgBPLszy+82DQytyr5m7xSnH9xK3A2nSiiQySs92WDo/ZmXdlnRGS/M+wonUmfyyq7sng8/qZjQkQqbY07m399AdVjPtX3b4hOeB9VIxpigJm2i7rtV9adj2XM9WYJqTHk//IfnFlaNqHRQnQzFZn7FlS4q7cvzlXxh9Ylyc40yXsAzO8KVGdpT5Vcb8AJlx4BXtcXFzr4M2/uyXP/gC+zsz416fl5zgo+d/CrmtaTYsDlDf5lJQn6g9OYCHBFWdMRJxctfgc96AVlfeb6wfNBISVc4aL6LqM/1D77A1t2Z0WPiLofv20ZSPO6+7Zf07BjdQaeztZnP/s0HWLZsKd97qIeu3aPnfjkCTWQgn2Xjw/fRt6tn1JiWdJJPnHUqB61Ywgs9OQbK9JZyBTpToEHAd+96jue3948a05RwOff4/XnV3m3c8Xw/W/tHz5FKusKZq9s4cEGSXVmfXJlpVI7A8o4Y7SmXXZmgbKsZIfy7lY5PfKkkPwjP3nsy/rB9WYKqruo8qNLkJCL/33StIGEaW9gkcKxLO45PzKltX/354WdbI6ViDvu1xyP7QcUcIR136K0yKfnhF7r51R9erni2tbM/xw/Xb2bN8kUVJza5jrBvW/m16kp1ZwJe2pWveG8q6yu/3ridFzdvw6swKJv3ueuBh8i/9Ad8v/yk4+7efr74oztZuvZNqFP+/Q4UXt78J7Y+uR7PK7+dvsEsP73rUd6R6iQWK78dX+He53v4zaMvka3waWAg53Pdupc5aFmASIXk7St3vzhAa7LyGo2Bwsu7wyWzoiY39+cDUnF3wvct/UDZPuA3zJzBmSTqHtSjIx8CXlV8XFUPq2dgxhhj5raoj6GbCO83fREYJExQdwF/Vv+wjDHGzHVR86DeISKnA1cAl6rqTSKSV9UXatmwiHwPOA3YqqqHlnlegK8DbwMGgHNV9aHxvAhjjDHTq5aKwLFW+kXOg1LVG4FTgRNF5CZgdIOayq4G3hrx/KnAAYU/5wO23p+ZNKpKrkp/KoDOtMui5uh7Pp0pp+qY1+zXyplH7FOxYEMEjtyvnf3nJSLvaVQqky9SVYJAaa5yf/3ARc284cC9Ks5ZUlX6n7qXvmceQCvcgwLwcNnxp5cJgvKLtqoqmcwgmmii0n1vVWXXjm3cdded5HKjC0iKFrYkOemgvSuuSA/Qkk5V3E9RW9KhP+dHrhm44ZU+rlm/bahKsJyBfEDXrnzF+3i1ygWVW9GYaDX3gxKRNcBrVfXbNW9cZDlwc4UzqP8C7lDV6wrfPwmcqKqbo7ZpVXymmqwX0F2h+WJRotAnyJFwkmveV57tzg0rqki4YVmyU5iAlAuUZ3fmh8rVAVoSwv6dYa8lzw/YOZDni7c8yaMv7x4as3JhMx896QAWtCRwHYesr6x7eYAdJSt1xx2Yl47hOpVLm3O+0jMYVhQq4c33nYPBUJk1QHvSYe2+aVoSYY+kgZzHD+/fxFN/2hNPbstz7PjFv5Lb8RIEPrhxmlefRGLh8qExkkiT2nt/JJ5G3BjiuCxauormjvl7tjM4wLYXnyY72I8GARoEeP3daH5P1aD6eXSgB/VyxFyXeCLBaaf9GQcdfPDQ63QdmJdyibmCBkrGC/jpgy/waFf30HaSiTiv2m9vmtNJXMcpe8Bvigtr90nTmQ4rOwXoSLukS5oWbu/Pc826LTyzI4MqJGLCR47dizeuah8aU6wSLeauYh+whc3umCr6is0TcxV6pc22Kr5alJxBTbzMXETeAGxR1SdF5HjgWGCjqv6ypo1HJ6ibgS+r6t2F738LXKyqkdnHEpSpZDzNE4uKfbC6B31e3JWnNemMGlO6j5d251nSFmdeykVGzJfJ5H3uf76b/7zzed71miUcvWIecXf4PC0/ULb259nwSoZ0QkhXaAchgF+Ya1ba9LA07pyv7M4GHLIoydL2xKizuJzns2l7Hz+46wle/OV/svvhX4GfG7aagbhxEvMWk179RpqWrMZpXQgjJvM6jkO6uZV5S1bSt2MLPdv+BAQjJmor4ufJ7t4OAz34g32IDF85IZGIs3jxYt75znexbPHCsnPYcp7P5p5BfvjAJpqamlm8oLMwmXf4uGKvq4MWJDhgfnLUaxcg5gotcYfbnu7m1092j+qZlYoJS9qT/O0bFjOvKazqLNcHLBULP4w0VWnqWK55YjmWoKqLquK7DDgaiInIr4GTgVuBi0TkRFX9VKWfrVG5AMv+PkXkfMLLgCxd2tj9S8z0UFW29HlVL6Xs1RIr2zyx2AerM+2Q88NusOUSRnEFjXmFduPlxqTiLsevms+qvTvwgmDUqg3F7ezdEmfvVi+yb5ICW/u8ys34REjGhDfu2zTU+XikRMxl1aI2dnz/Qvq6XkC97Kgx6ufJ73iZ9r1fRax9EUGZf55BEDDYt5uXNj4cnsVoucAFYgmCvp1IfhDQUSuN5HJ5XnrpJdJkyyanYsxL5zdzzMHL2TngR/Yced1+TSxoHt1RGcL3LO8r37j/ZV7qyZad85TxlGd3ZNi4LcurF7uUOzQFCgN5JeMp6Xh0/6nuwdFdn8eq9Ji3YO99J7ClmS2qiu8U4FAgDbwM7KuqAyLyZeBhhq9uPh5dwH4l3y8BXik3UFWvICzWYO3atXY514yi1NhbiejVARyRcAn/iDG1XOZxnXA75ZJT6XaqTQCGyp1iSyXc8smpyHGEnm1/ws+PTk5D+wl8Ys2dZZPTnljCSPygcuCqgJ8jiBgTBMq8jo6q73PW08jkpEBzIvq1A+weMUm23HbmN8Wo9sE+Gas+cder4Z5Ttb9Bpce8lQcfNmePeVEJSlVVRaT4t6z4JgXUtshsNTcBF4jID4FjgF3V7j8ZY4yZGSZjbb6oBPVLEbkLSAHfAX4sIvcBJwB3VtuwiFwHnAgsEJEu4BIgDlAotLiFsMT8GcIy8w+O/2UYY4yZbaLmQV0sIq8Nv9T7RGR/4HTCZHV9tQ2r6llVnlfgo2OM1xhjzBwRVSQhqnpv8XtVfRa4tMyYOXt91JipMLX/wCZpb421GZuHNENF3Uu6XUQ+JiLDLiSKSEJE3igi3wfOqW94xtRGIJzvUmXcQD6InMDpB4oDkWOKbTWixkDYjiIqHkdgv/Y4EfNSUVVSVdbFdQR2ZXyqHYbfetZ5JJKpijf5m5qamN/3HMmYW7EuIRl3WdTeRCLmVByTirssXraSRDxesXghHo/zwCOPE0RMglVVlneErTEqvY9JV+geDCLHABy9tJW4I1RaZD8ZE04aa0MAABa3SURBVB7q6otsJCjAtn6PIKKxYaBKKhb9t1AI536Z6qL6QaWAvwTOBlYAPYQVfQ7wv8DlqrphiuIcYvOgTJTiJN2oyrfSSbrFA6gfaGGybjgRtzhJ1y2Z41RstLezMImz3JiRcr6yc9DHD/bE40i4Svr+nXHaUi5b+jx+82wvvdlgWFWfX5gwmq1QfeZKWC24ojNBe43N71546nG++Zm/5pUXniUzELa0SDc10draxle/+V+c/OZTeW7LLr5w/X28sG03g4XZqsm4Syoe4yOnHsnaA/aha/tuvvnLB+navptMvjAm5pJMuPz1W9dy1AGLeXnLNv79qh+zqWszmWy4gkQ8HseNxTjuTW9n+aoDScWdcG5RfHjTwkB1qFw74wU8X/i9FPNZ3IWEI3zwiE6OWZJmIK+sf2UwcoJ292Cemx/fwYs9WfKFQXFXiDnCnx++gNcua6v4exSgPSU0xx1iTtgvKlFS1l9sRLirMF+tEmFYr7RZPQ+qSpHE5PSDAhCROLAAGFTV0Q1fppAlKFPNngaA0TXczQmHtqSDKry0K8+WMv2FWhJCWzL8uLs7G5Rt39EcFzpSlZszljYkFIF9WmMsbo2Nmij82NYMd20awCv0hYpq8eEILG6Nsbi18llKJarKHT+/jqu+fDFePseHL7iICz/1f0mlUsPG/HrDJi79xUNkPZ/T1h7AmccdQjLuDhvz+40vceWvHybn+Zx65Cre+/pDSMZjw8bcve5R/uOan5LJ5jhkzVqOOO4E4vHhq6Z1pl1WdIZNC/vzAbszwye5qirdmYAXenIECietaOb/HNpOekTPrFd68zz0SiaypPypbQPc9Nh2Br2A45a18e7DFtCUqJzgmwq/35Hvc7Lkg85APmBXJnpibjomI3ulWYKq4v9v786D5DjLO45/n55zVytpdy0h5AvLRoDNERsLh0BIzBVsJ9hQSYFcoYJTBAoCJFUkFFBJEeKQqqSoClWpcIQA4ShjY8wRh5gr2BSnjRXwIcs2yJIlGxlrrWOlXe0xM/3kj+6Re2d3Du1uz/bM/j5VU5rpfqfn6XdH/Uy//fb7djzUUVYoQUmnjk5VmKy0LjMxU2Oi4i3vR6ofT1oNybauaCdn421mIG8MFYOWY83dtneCWx+aaHnz7sbBaKbdVtvpxEB1go2lCps3n960zMFjMzx+fJaRtQNNy0zNVJiarTLaoszug8fZse8opTXrmsdTMDYM5lvW81nr87zwzEGeurbQtMyvxmfZcWC65VBXAU4hgA1DzYcXLQYwPBBQbNMelzNaflY+iBLwAttZsQSVxvTsp2h5JiwU6VVRsmj9A6zmtL1ZtpOxQjv5mZcLrOkkenX5wNp+XmDtt9OJoXXr2TTS/EAPsKZcYJRc6zODUoGBUuvtlEslhtauaz1qhrev63xgjA62PmzlAqPdn76QCzhtsHWzqJk1HWw3qVVyOpXtyHy6VCciIpmkBCUiIpmkBCU9qRY6tTbtQQZNuxXX5YNoqotWCh2UyQftP6uTRp5CEE2Z0cpAwRhoMxB2Mde+TD6Irp+0Elj7OapyFnUYaKUQX4dppZy3tvveyWU39/bx5OLRyVuJelu2/izrMCZZHF2Dkp7i7hybqTEx6xiwthQ0HRF7bSnHUAmOz4Rz5nA6ub4YsHltHnc4cLzKY8fnjoZuRD3lTl8b/TdpVeaMdVGZiZmQ4wt81lAxYG2bgy/AJWcOcvHpg/xo3yT/u2dizvWxwKKRu39v6xA5Mx46PMv9YzPzroGcO1LgOZvKGLDn8Cy7FiizZaTAczeVo15zcY/HxnQ/WIjqB6IR1R85Vp13jWjjYI6nDRcwg7HJGo+MV+Z91obBHBdvjjpH/OyxKW75xXGmGyaTfP7mMlc+ax35nPGLJ2b44b4T87rXP3NDkUvPWdP0x4K7MxWPIn7BU0ocnqqx72hl3jXGM9bluWhzmXxgHD5RY9/4/DKjAwFbhovkApiqOuPTtXn7Xs5H3c0Da19GV6AWR734pGdMVUKONhwE6mdJIwM5Sk1+yoaJuZ5maz6ne7Al7oOqhs6eIxWOzYSsKwWcO1KIbu6MT43CuMxDLcok55WaqfmC91x1olILmak6X951jPvHZjh7fYHXP3c960oBhbg3WD3mnx2Y5rGJKiMDOV5weplyfK9OsszPH5vmwPEqI+VoQsOBRJl6zEeno/uOorOdaPLEesz1Otx7pMLhqRqDBeO80SKlnJ3sNl0v8/CRCofqZUaKlPJPlqmGTrXm/NcDx/j5Y9NsGsrz+uesZ8OaJ3u51WP+/sMneOCJGUYHcrzyvCFGBnJNO4dUatF9U8mRxOv7tW+8wthkjaFiwMWnl1lfzp3c9+imW9g/XuHgZI1SPro/bbAQnIy5fo/TsemQyUoYT8sSxdJ4H1SyzPBArt0o86fUiy8DPe+Wk7qZS39wdw6diJJLs2+rwZyD3EJCd8Iwmoev2UGjfnDMB9Z0+vZOynTyWZ2YrYVMzYYMFpsfnKuhM1sNKeaDpjcNR2WcYt6alqknmPqoDAuVqe97Ie4pt9gyszVnuhLGiXLhMpWaM1MNKRea7xfA8Zlay3vewtApF4zRgfycHyWNMdfcyVvzmOv1U/8zNCvj/mRzb5t7cZWg2lATn2SeQ9PRFJIKbS4CBWZY0HqyuVyLpJMs0+xAdyqf1YliLqBQbj0HUT4wcoXW92BFZTqImfb1027fOylTzBmFoHXM0SgPrctA1ETZShAYw+V8y79rLjACX3r9RPOJLf3vLhFd3pNVZbkOHJ1sJ2uf1a9llksvxtzvlKBERCSTlKBERCSTlKBERDKuzzpIdEwJSjLPaN/lx4lu0JTVJx+0nwesFjafw0mySwlKMs/M2DSUbzkh4ZqCddhxVfrNaYO5aCT5BdYZUY/BfK51T0jJJnUzl56Qi0exnq2G0QSA/uQwMyMD+WUZ3Vt6k5mxtpRjsBBwZLrGTDxKRWAwXM5Rzis59SolKOkpxXzApiFjcjbELBqORwcfgehHzIbBPNPVkErNWVOcP8mg9BYlKOk5ZsZQqbMpzmX1KecDyjqy9QVdgxIRybDRNc1n/e13SlAiIpJJSlAiIpJJaqkVkb5RqTn7xytMzIZsGS6wrqxrlb1MCUpEep67MzZZZd94Fffoxu0HD82yvhRwzkix7azAkk2pNvGZ2WVm9qCZ7Taz9y6w/mwzu83Mfm5m95jZFWnGIyL958RsyL2Pz7BvPJrxtz5eROhwZDrk7l9PMzZZ0UgSPSi1BGVmOeAjwOXABcDVZnZBQ7G/BW5094uA7cBH04pHRPrT7sOzTFV93nTrdaHDYKF3m/oOT87yhTv2r3QYKyLNM6hLgN3uvsfdZ4EbgKsayjiwLn6+HjiQYjwi0oeaJaakdhMoSjalmaDOAB5JvH40Xpb0AeANZvYocAvwzoU2ZGZvMbMdZrZjbGwsjVhFRDIjecw7fvTwSoezYtJMUAv9XGn8rXM18Bl3PxO4Avi8mc2Lyd0/4e7b3H3bxo0bUwhVRCQ7kse8tcOjKx3OikkzQT0KnJV4fSbzm/DeBNwI4O4/AcrAhhRjEhGRHpFmgroT2GpmW8ysSNQJ4uaGMvuBlwOY2flECUpteCI9rps95jq5tBTNF9admNw199RySS1BuXsVeAfwLeB+ot5695nZtWZ2ZVzsr4A3m9ndwPXANa6/rEjPcndCd47PhFTD6Hnanj5apJw3giaJKjA4PlNLPY56YpqcDal0ad/7nfVaPti2bZvv2LFjpcMQkZi7Y2aE7kxXnfHp2smedWuKAeviyQTT7EXn7hycrLI/caNuYLCuFHDOcJFSPt0efKE7szXnaDxXGcBAwRgu51rte0dBnXv+83zP/fcsW6wZ0dG+ayQJEVmS0CEMnaPTNWZrc3/wTs6GTFVCRgdyFHPpJalo1uUCowN59h2NhzoaKbA+5aGOaqHjwPh0jenq3H2fqjjTlSrD5YABzVu2KEpQIrIkM/GZQ7O2mNCjRFUYyHX2s3kJCjnj6ad1b3qKaugcOtF83x2YqDjlQoenDDKHRjMXEZFMUoISEZFMUoISEZFMUoISkSUJDAYLrQ8l+cD68hqMEfVUbLVveR1lF02dJERkSUo5o5gzhkoBR6bm9uTLGQyXcxRT7ua9Ugo5o5AzhooBRxt68tW7uQ8UWicwaU4JSkSWxCw6OwoMThvMMVONupwPFgLWduEeqJVU36+cwchAjkrNOTJdo5Qz1re+B0o6oAQlIssmMKOch6cO5eObZVfPwTkwo5iDTWtW376nRa2jIrKs6mcMq/EAvZr3PQ1KUCKy7FZzs9Zq3vflpgQlIpJho2u6NzJG1ihBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJilBiYhIJqWaoMzsMjN70Mx2m9l7m5R5nZntMrP7zOwLacYjIiK9I5/Whs0sB3wEeCXwKHCnmd3s7rsSZbYC7wNe7O5HzOwpacUjIiK9Jc0zqEuA3e6+x91ngRuAqxrKvBn4iLsfAXD3gynGIyIiPSTNBHUG8Eji9aPxsqRnAM8wsx+Z2e1mdtlCGzKzt5jZDjPbMTY2llK4IiJL4+4nH0uRPObt+9Wvlym63pNmgrIFljX+1fLAVuBS4Grgk2Y2PO9N7p9w923uvm3jxo3LHqiIyFKF7lRDGJuscWwmJFxCokoe89YOjy5zpL0jtWtQRGdMZyVenwkcWKDM7e5eAfaa2YNECevOFOMSEVkW9QTkwPh0yIlKCEBl1pmqhAyXcxTz0a91s4V+s0sraZ5B3QlsNbMtZlYEtgM3N5T5GvBSADPbQNTktyfFmERElk01dCZnQx6fqJ5MTnU1h0NTNY5Nh03eLe2klqDcvQq8A/gWcD9wo7vfZ2bXmtmVcbFvAYfMbBdwG/Budz+UVkwiIsspdOLmvOZlZkOfd21DOpNmEx/ufgtwS8Oy9yeeO/Cu+CEiInKSLbW3SbeZ2Riwb5Fv3wA8sYzhLCfFtjhZjS2rcYFiW6zlju0Jd1+w53KSmX2zk3L9qOcS1FKY2Q5337bScSxEsS1OVmPLalyg2BYry7H1K43FJyIimaQEJSIimbTaEtQnVjqAFhTb4mQ1tqzGBYptsbIcW19aVdegRESkd6y2MygREekRSlAiIpJJfZGg2k2MaGYlM/tivP4OMzsnse598fIHzexVKxDbu+IJG+8xs++a2dMS62pmdlf8aBwmqhuxXWNmY4kY/iyx7o1m9sv48cYViO3Dibh+YWZHE+vSrrdPm9lBM9vZZL2Z2b/Gsd9jZs9PrEut3jqI64/jeO4xsx+b2W8k1j1sZvfGdbZjOePqMLZLzWw88Xd7f2Jd24lPU47t3Ym4dsbfr9F4Xar1tuolh4fvxQeQAx4CzgWKwN3ABQ1l/hz4ePx8O/DF+PkFcfkSsCXeTq7Lsb0UGIyfv60eW/x6YoXr7Rrg3xZ47yjRmImjwEj8fKSbsTWUfyfw6W7UW7z93wGeD+xssv4K4BtEY4S+ELijS/XWLq4X1T8PuLweV/z6YWDDCtbZpcDXl/pdSCO2hrKvBm7tVr2t9kc/nEF1MjHiVcBn4+c3AS+3aGjhq4Ab3H3G3fcCu+PtdS02d7/N3U/EL28nGvW9Gzqpt2ZeBXzH3Q97NNnkd4DlvNP9VGO7Grh+GT+/JXf/PnC4RZGrgM955HZg2Mw2k3K9tYvL3X8cfy5097vWSZ01s5TvaRqxdfW7ttr1Q4LqZGLEk2U8GsR2HDitw/emHVvSm4h+edeVLZq07HYze80yxnUqsf1h3CR0k5nVp0/JTL3FTaJbgFsTi9Ost040iz/tejsVjd81B75tZv9nZm9ZoZh+y8zuNrNvmNmz42WZqTMzGyT6QfHlxOIs1FvfSnWw2C7pZGLEZmU6ee9SdLx9M3sDsA343cTis939gJmdC9xqZve6+0NdjO2/gevdfcbM3kp0FvqyDt+bdmx124Gb3L2WWJZmvXVipb5vHTGzlxIlqN9OLH5xXGdPAb5jZg/EZxbd8jPgae4+YWZXEE3Fs5WM1Fns1cCP3D15trXS9dbX+uEMqtOJEc8CMLM8sJ7olL6T96YdG2b2CuBvgCvdfaa+3N0PxP/uAb4HXNTN2Nz9UCKe/wAu7vS9aceWsJ2GJpeU660TzeJPu97aMrPnAZ8ErvLE1DaJOjsIfJXlbepuy92PuftE/PwWoGDRHHErXmcJrb5rK1JvfW+lL4It9UF0FriHqJmnfhH12Q1l3s7cThI3xs+fzdxOEntY3k4SncR2EdFF4K0Ny0eAUvx8A/BLlvHicIexbU48fy3R7McQXeTfG8c4Ej8f7WZscblnEl2ktm7VW+JzzqH5Bf/fZ24niZ92o946iOtsouusL2pYvgZYm3j+Y+CyLtfZU+t/R6KD/P64/jr6LqQZW7y+/qN2TbfrbTU/er6Jz92rZlafGDFH1JvrPjO7Ftjh7jcDnwI+b2a7ib5k2+P33mdmNwK7gCrwdp/bVNSN2D4EDAFfivptsN/drwTOB/7dzEKiM91/cvddXY7tLyyaXLJKVG/XxO89bGb/QDRrMsC1PrfZoxuxQXTB+gaPjxCxVOsNwMyuJ+p1tsHMHgX+DijEsX+caA60K4iSwQngT+N1qdZbB3G9n+ja60fj71rVo9G5NwFfjZflgS+4+zeXK64OY/sj4G1mVgWmgO3x33XB70KXY4PoB9q33X0y8dbU622101BHIiKSSf1wDUpERPqQEpSIiGSSEpSIiGSSEpSIiGSSEpSIiGSSEpSIiGSSEpRkVsO0GXdZYpqUhnKDZnZdPO3BTjP7oZkNNWxjp5l9KR5PDTObiP89x8ym4jK7zOxzZlaI1zVOAXFXPOrHQjGUzeyn8Vhy95nZ3yfWfcbM9ia2cWG83KzJtBwi0h9j8Un/mnL3Czso95fA4+7+XAAzeyZQadyGmV0HvBX4l4b3P+TuF5pZjmiE8dcB18XrfuDuf9BBDDPAyzwaS64A/NDMvuHRaOYA73b3mxrecznReHNbgd8EPhb/KyLoDEr6w2bgV/UX7v6gJ8Y0TPgB8PRmG4lHEfkpixgt2yMT8ctC/Gh3F3yzaTlEBCUoybaBRLPYV1uU+zTwHjP7iZl90My2NhaIBwm+HLi32UbMrEx0BpMcruYlDU1857V4f87M7gIOEs37dEdi9T/GzXgfNrNSvCwzU0mIZJESlGTZlLtfGD9e26yQu99FNOPqh4gGZL3TzM6PVw/ESWMH0QCkn1pgE+fFZQ4RjYV4T2LdDxIxXOgtpu1w91rcnHgmcImZPSde9T7gWcAL4vjeEy/P0lQSIpmja1DSF+Lmta8AX4kHir0CuJ/OrmPVr0FtBr5nZlcmBqRdTCxHzex7RJPb7XT3x+JVM2b2n8Bfx6+zNJWESOboDEp6npm92MxG4udF4AJg36luJ04k7yU64znVGDaa2XD8fAB4BfBA/Hpz/K8BrwF2xm+7GfiTuDffC4HxRDITWfV0BiX94DzgY3ECCID/Ye603Kfia8AHzOwl8euXxM1/dR9coDceRB01Phv3BAyI5hz7erzuOjPbSNSkdxdRT0JoMi2HiEQ03YaIiGSSmvhERCST1MQnPcPMXgX8c8Piva16+KUQw2nAdxdY9XJ3P9StOERWAzXxiYhIJqmJT0REMkkJSkREMkkJSkREMkkJSkREMun/AaEq1uwGd9dpAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(cat['FErr_SPIRE_350_u']-cat['F_SPIRE_350'])/(cat['F_SPIRE_350']-cat['FErr_SPIRE_350_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(cat['F_SPIRE_350']),y=skew, kind='hex')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 350 $\\mathrm{\\mu m}$ depth is ~ 6mJy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n",
      "/Users/Steven/anaconda/envs/herschelhelp_internal/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6462: UserWarning: The 'normed' kwarg is deprecated, and has been replaced by the 'density' kwarg.\n",
      "  warnings.warn(\"The 'normed' kwarg is deprecated, and has been \"\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(cat['FErr_SPIRE_500_u']-cat['F_SPIRE_500'])/(cat['F_SPIRE_500']-cat['FErr_SPIRE_500_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(cat['F_SPIRE_500']),y=skew, kind='hex')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 500 $\\mathrm{\\mu m}$ depth is ~ 6mJy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add flag to catalogue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cat.add_column(Column(np.zeros(len(cat), dtype=bool),name='flag_spire_250'))\n",
    "cat.add_column(Column(np.zeros(len(cat), dtype=bool),name='flag_spire_350'))\n",
    "cat.add_column(Column(np.zeros(len(cat), dtype=bool),name='flag_spire_500'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ind_250=(cat['Pval_res_250']>0.5) | (cat['F_SPIRE_250'] < 6)\n",
    "ind_350=(cat['Pval_res_350']>0.5) | (cat['F_SPIRE_350'] < 6)\n",
    "ind_500=(cat['Pval_res_500']>0.5) | (cat['F_SPIRE_500'] < 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "27 36 127 315\n"
     ]
    }
   ],
   "source": [
    "print(ind_250.sum(),ind_350.sum(),ind_500.sum(),len(cat))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cat['flag_spire_250'][ind_250]=True\n",
    "cat['flag_spire_350'][ind_350]=True\n",
    "cat['flag_spire_500'][ind_500]=True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# set XID+ cahtalogue back to orignal order of objects, as used in MF detection files\n",
    "use = cat['HELP_ID'].astype(int) -1\n",
    "use = np.argsort(use)\n",
    "cat = cat[use]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Reads MF table, removes duplicate RA and DEC\n",
    "cat2=Table.read('./data/SA13_SPIRE_all.fits')\n",
    "del cat2['RA']\n",
    "del cat2['Dec']\n",
    "cat_all = hstack([cat,cat2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Created HELP_ID, and changes HELP to HELP_BLIND to avoid confusion with HELP-Masterlist objects\n",
    "ID = gen_help_id(cat_all['RA'], cat_all['Dec'])\n",
    "ID_new = [IDs.replace('HELP','HELP_BLIND') for IDs in ID]\n",
    "ID_new = Column(ID_new,name=\"HELP_ID\")\n",
    "cat_all['HELP_ID'] = ID_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# all flux denisties are in mJy in the final BLIND catalogues\n",
    "cat_all['F_BLIND_MF_SPIRE_250'].unit = 'mJy'\n",
    "cat_all['F_BLIND_MF_SPIRE_250'] = 1000*cat_all['F_BLIND_MF_SPIRE_250']\n",
    "cat_all['FErr_BLIND_MF_SPIRE_250'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_MF_SPIRE_250'] = 1000*cat_all['FErr_BLIND_MF_SPIRE_250']\n",
    "\n",
    "cat_all['F_BLIND_MF_SPIRE_350'].unit = 'mJy'\n",
    "cat_all['F_BLIND_MF_SPIRE_350'] = 1000*cat_all['F_BLIND_MF_SPIRE_350']\n",
    "cat_all['FErr_BLIND_MF_SPIRE_350'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_MF_SPIRE_350'] = 1000*cat_all['FErr_BLIND_MF_SPIRE_350']\n",
    "\n",
    "cat_all['F_BLIND_MF_SPIRE_500'].unit = 'mJy'\n",
    "cat_all['F_BLIND_MF_SPIRE_500'] = 1000*cat_all['F_BLIND_MF_SPIRE_500']\n",
    "cat_all['FErr_BLIND_MF_SPIRE_500'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_MF_SPIRE_500'] = 1000*cat_all['FErr_BLIND_MF_SPIRE_500']\n",
    "\n",
    "cat_all['F_BLIND_pix_SPIRE'].unit = 'mJy'\n",
    "cat_all['F_BLIND_pix_SPIRE'] = 1000*cat_all['F_BLIND_pix_SPIRE']\n",
    "cat_all['FErr_BLIND_pix_SPIRE'].unit = 'mJy'\n",
    "cat_all['FErr_BLIND_pix_SPIRE'] = 1000*cat_all['FErr_BLIND_pix_SPIRE']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# XID+ flux density vs. MF flux densities\n",
    "plt.hexbin(cat_all['F_SPIRE_250'],cat_all['F_BLIND_MF_SPIRE_250'], cmap=plt.cm.Blues,gridsize=(100,100))\n",
    "plt.plot([0,100],[0,100], color = 'red')\n",
    "plt.xlim(0,100)\n",
    "plt.ylim(0,100)\n",
    "plt.xlabel('F_SPIRE_250')\n",
    "plt.ylabel('F_BLIND_MF_SPIRE_250')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Add field name\n",
    "cat_all.add_column(Column(['SA13']*len(cat_all),name='field'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: 'mJy/Beam' did not parse as fits unit: At col 4, Unit 'Beam' not supported by the FITS standard. Did you mean beam? [astropy.units.core]\n"
     ]
    }
   ],
   "source": [
    "cat_all.write('./data/dmu22_XID+SPIRE_SA13_BLIND_Matched_MF.fits', format='fits',overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "*This is a default HELP jupyter notebook *\n",
    "\n",
    " ![HELP LOGO](https://avatars1.githubusercontent.com/u/7880370?s=75&v=4)\n",
    "\n",
    "**Authors**: S. Duivenvoorden\n",
    "\n",
    " \n",
    "For a full description of the database and how it is organised in to `dmu_products` please the top level [readme](../readme.md).\n",
    " \n",
    "The Herschel Extragalactic Legacy Project, ([HELP](http://herschel.sussex.ac.uk/)), is a [European Commission Research Executive Agency](https://ec.europa.eu/info/departments/research-executive-agency_en)\n",
    "funded project under the SP1-Cooperation, Collaborative project, Small or medium-scale focused research project, FP7-SPACE-2013-1 scheme, Grant Agreement\n",
    "Number 607254.\n",
    "\n",
    "[Acknowledgements](http://herschel.sussex.ac.uk/acknowledgements)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}