{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Final Processing\n",
    "The final processing stage requires:\n",
    "1. Quick validation of catalogues and Bayesian Pvalue maps\n",
    "2. Skewness level\n",
    "3. Adding flag to catalogue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "from astropy.table import Table\n",
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import pylab as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: 'degrees' did not parse as fits unit: At col 0, Unit 'degrees' not supported by the FITS standard.  [astropy.units.core]\n",
      "WARNING: UnitsWarning: 'muJy' did not parse as fits unit: At col 0, Unit 'muJy' not supported by the FITS standard. Did you mean MJy, mJy or uJy? [astropy.units.core]\n"
     ]
    }
   ],
   "source": [
    "SERVS_cat=Table.read('../data/ELAIS_N1/MIPS/dmu26_XID+MIPS_ELAIS-N1_SERVS_cat_20170710.fits')\n",
    "SWIRE_cat=Table.read('../data/ELAIS_N1/MIPS/dmu26_XID+MIPS_ELAIS-N1_SWIRE_cat_20170725.fits')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<Table length=10>\n",
       "<table id=\"table4489847360\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>help_id</th><th>RA</th><th>Dec</th><th>F_MIPS_24</th><th>FErr_MIPS_24_u</th><th>FErr_MIPS_24_l</th><th>Bkg_MIPS_24</th><th>Sig_conf_MIPS_24</th><th>Rhat_MIPS_24</th><th>n_eff_MIPS_24</th><th>Pval_res_24</th></tr></thead>\n",
       "<thead><tr><th></th><th>degrees</th><th>degrees</th><th>muJy</th><th>muJy</th><th>muJy</th><th>MJy / sr</th><th>MJy / sr</th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>str100</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></tr></thead>\n",
       "<tr><td>HELP_J161006.621+533656.872</td><td>242.527587012</td><td>53.6157979058</td><td>10.4667</td><td>22.6099</td><td>3.04599</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161005.559+533642.824</td><td>242.523161793</td><td>53.6118954771</td><td>12.3774</td><td>25.8053</td><td>3.60663</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161008.641+533615.951</td><td>242.536005913</td><td>53.6044309555</td><td>116.806</td><td>131.279</td><td>103.169</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161002.817+533625.213</td><td>242.511735883</td><td>53.6070036615</td><td>70.9787</td><td>88.4681</td><td>52.4919</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161009.708+533610.215</td><td>242.540451147</td><td>53.6028373869</td><td>132.994</td><td>146.192</td><td>120.556</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161000.783+533454.820</td><td>242.503263565</td><td>53.5818943665</td><td>5.79204</td><td>13.5911</td><td>1.59307</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161002.558+533606.162</td><td>242.510656314</td><td>53.6017117556</td><td>18.1655</td><td>31.734</td><td>6.73982</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161005.420+533611.962</td><td>242.522583128</td><td>53.6033228215</td><td>12.266</td><td>24.3795</td><td>3.96191</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J160959.123+533542.063</td><td>242.496347238</td><td>53.5950173915</td><td>17.7358</td><td>31.0833</td><td>7.03387</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "<tr><td>HELP_J161000.625+533444.663</td><td>242.50260411</td><td>53.5790731835</td><td>52.7274</td><td>68.7187</td><td>37.6159</td><td>-0.0133419</td><td>4.90328e-06</td><td>nan</td><td>2000.0</td><td>0.0</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=10>\n",
       "                                              help_id                                                ...\n",
       "                                                                                                     ...\n",
       "                                               str100                                                ...\n",
       "---------------------------------------------------------------------------------------------------- ...\n",
       "HELP_J161006.621+533656.872                                                                          ...\n",
       "HELP_J161005.559+533642.824                                                                          ...\n",
       "HELP_J161008.641+533615.951                                                                          ...\n",
       "HELP_J161002.817+533625.213                                                                          ...\n",
       "HELP_J161009.708+533610.215                                                                          ...\n",
       "HELP_J161000.783+533454.820                                                                          ...\n",
       "HELP_J161002.558+533606.162                                                                          ...\n",
       "HELP_J161005.420+533611.962                                                                          ...\n",
       "HELP_J160959.123+533542.063                                                                          ...\n",
       "HELP_J161000.625+533444.663                                                                          ..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SERVS_cat[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "&lt;Table length=10&gt;\n",
       "<table id=\"table4481346696\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>help_id</th><th>RA</th><th>Dec</th><th>F_MIPS_24</th><th>FErr_MIPS_24_u</th><th>FErr_MIPS_24_l</th><th>Bkg_MIPS_24</th><th>Sig_conf_MIPS_24</th><th>Rhat_MIPS_24</th><th>n_eff_MIPS_24</th><th>Pval_res_24</th><th>flag_mips24</th></tr></thead>\n",
       "<thead><tr><th></th><th>degrees</th><th>degrees</th><th>muJy</th><th>muJy</th><th>muJy</th><th>MJy / sr</th><th>MJy / sr</th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>str100</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>bool</th></tr></thead>\n",
       "<tr><td>HELP_J160000.316+542000.690</td><td>240.001318675</td><td>54.3335249815</td><td>1928.47</td><td>1943.4</td><td>1913.42</td><td>-0.000955198</td><td>4.74435e-06</td><td>nan</td><td>1196.0</td><td>1.0</td><td>True</td></tr>\n",
       "<tr><td>HELP_J161145.788+525236.929</td><td>242.94078253</td><td>52.8769246635</td><td>244.531</td><td>531.299</td><td>80.7009</td><td>0.011866</td><td>5.16518e-06</td><td>1.00054</td><td>1760.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161138.168+525244.570</td><td>242.909032282</td><td>52.8790472905</td><td>239.355</td><td>531.635</td><td>65.6535</td><td>0.011866</td><td>5.16518e-06</td><td>1.00149</td><td>2000.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161143.750+525251.314</td><td>242.93229323</td><td>52.8809206325</td><td>242.255</td><td>516.11</td><td>71.3392</td><td>0.011866</td><td>5.16518e-06</td><td>1.00016</td><td>2000.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161131.547+525241.333</td><td>242.881447116</td><td>52.8781479465</td><td>262.442</td><td>560.661</td><td>81.3861</td><td>-0.00204203</td><td>4.91504e-06</td><td>1.00381</td><td>2000.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161128.756+525312.827</td><td>242.869815896</td><td>52.8868964635</td><td>256.02</td><td>554.574</td><td>68.8019</td><td>-0.00204203</td><td>4.91504e-06</td><td>1.00221</td><td>1068.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161132.773+525325.277</td><td>242.886553205</td><td>52.8903547935</td><td>68.2279</td><td>171.721</td><td>16.9382</td><td>0.377187</td><td>4.94219e-06</td><td>nan</td><td>2000.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161138.691+525423.576</td><td>242.911211156</td><td>52.9065487865</td><td>67.2236</td><td>176.488</td><td>18.5074</td><td>0.377187</td><td>4.94219e-06</td><td>nan</td><td>2000.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161138.467+525405.234</td><td>242.910280018</td><td>52.9014539065</td><td>65.6982</td><td>167.994</td><td>17.4561</td><td>0.377187</td><td>4.94219e-06</td><td>nan</td><td>2000.0</td><td>0.0</td><td>False</td></tr>\n",
       "<tr><td>HELP_J161137.367+525312.879</td><td>242.905696275</td><td>52.8869108555</td><td>65.1079</td><td>157.618</td><td>17.9052</td><td>0.377187</td><td>4.94219e-06</td><td>nan</td><td>2000.0</td><td>0.0</td><td>False</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=10>\n",
       "          help_id                 RA      ... Pval_res_24 flag_mips24\n",
       "                               degrees    ...                        \n",
       "           str100              float64    ...   float32       bool   \n",
       "--------------------------- ------------- ... ----------- -----------\n",
       "HELP_J160000.316+542000.690 240.001318675 ...         1.0        True\n",
       "HELP_J161145.788+525236.929  242.94078253 ...         0.0       False\n",
       "HELP_J161138.168+525244.570 242.909032282 ...         0.0       False\n",
       "HELP_J161143.750+525251.314  242.93229323 ...         0.0       False\n",
       "HELP_J161131.547+525241.333 242.881447116 ...         0.0       False\n",
       "HELP_J161128.756+525312.827 242.869815896 ...         0.0       False\n",
       "HELP_J161132.773+525325.277 242.886553205 ...         0.0       False\n",
       "HELP_J161138.691+525423.576 242.911211156 ...         0.0       False\n",
       "HELP_J161138.467+525405.234 242.910280018 ...         0.0       False\n",
       "HELP_J161137.367+525312.879 242.905696275 ...         0.0       False"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SWIRE_cat[0:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Look at Symmetry of PDFs to determine depth level of catalogue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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21Itaa58KfF2SJC+z1p4BPol3QLsH9XdTSJoeNUh62pF+6Zf++umXAzrmWnDg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ba87e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(SERVS_cat['FErr_MIPS_24_u']-SERVS_cat['F_MIPS_24'])/(SERVS_cat['F_MIPS_24']-SERVS_cat['FErr_MIPS_24_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(SERVS_cat['F_MIPS_24']),y=skew, kind='hex')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ERE6C/QSgW9M0XAAoiuKbgVtnOioREVl4+6mC+07gl4Hri6K4HfgQ8OSZjkpERBbevqrg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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b9da3c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "skew=(SWIRE_cat['FErr_MIPS_24_u']-SWIRE_cat['F_MIPS_24'])/(SWIRE_cat['F_MIPS_24']-SWIRE_cat['FErr_MIPS_24_l'])\n",
    "skew.name='(84th-50th)/(50th-16th) percentile'\n",
    "g=sns.jointplot(x=np.log10(SWIRE_cat['F_MIPS_24']),y=skew, kind='hex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both seem to have flux pdfs that become Gaussian at ~20$\\mathrm{\\mu Jy}$ "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Add flag to catalogue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from astropy.table import Column\n",
    "SERVS_cat.add_column(Column(np.zeros(len(SERVS_cat), dtype=bool),name='flag_mips_24'))\n",
    "SWIRE_cat.add_column(Column(np.zeros(len(SWIRE_cat), dtype=bool),name='flag_mips_24'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ind_SERVS=(SERVS_cat['Pval_res_24']>0.5) | (SERVS_cat['F_MIPS_24'] < 20.0)\n",
    "ind_SWIRE=(SWIRE_cat['Pval_res_24']>0.5) | (SWIRE_cat['F_MIPS_24'] < 20.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "SERVS_cat['flag_mips_24'][ind_SERVS]=True\n",
    "SWIRE_cat['flag_mips_24'][ind_SWIRE]=True\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "SERVS_cat.write('../data/ELAIS_N1/MIPS/dmu26_XID+MIPS_ELAIS-N1_SERVS_cat_20170725.fits', format='fits',overwrite=True)\n",
    "SWIRE_cat.write('../data/ELAIS_N1/MIPS/dmu26_XID+MIPS_ELAIS-N1_SWIRE_cat_20170725.fits', format='fits',overwrite=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:new]",
   "language": "python",
   "name": "conda-env-new-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}