{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2 Investigating the red sources\n",
    "\n",
    "We will look at three lists of objects\n",
    "\n",
    "- HELP 500 um flux over 70 mJy\n",
    "- ESA/IPAC 500 um flux over 70 mJy\n",
    "- HELP XID+ masterlist 500 um fluxes above 70 mJy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "#%config InlineBackend.figure_format = 'svg'\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "#plt.rc('figure', figsize=(10, 6))\n",
    "from matplotlib_venn import venn2, venn2_circles, venn2_unweighted\n",
    "from matplotlib_venn import venn3, venn3_circles\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from astropy.table import Table\n",
    "from astropy.coordinates import SkyCoord\n",
    "import astropy.units as u\n",
    "import numpy as np\n",
    "\n",
    "import pyvo as vo\n",
    "import time\n",
    "from pymoc import MOC\n",
    "\n",
    "from herschelhelp_internal.masterlist import merge_catalogues, nb_merge_dist_plot\n",
    "from herschelhelp.utils import clean_table, inMoc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "help_blind = Table.read('./data/dmu22_XID+SPIRE_HELP_BLIND_Matched_MF_500_70mJy.fits')\n",
    "esa_blind = Table.read('../dmu22_IRSA/data/irsa_catalog_search_results_tbl_500.csv')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "esa_blind['ra'].unit = u.deg\n",
    "esa_blind['dec'].unit = u.deg\n",
    "for c in esa_blind.colnames:\n",
    "    esa_blind[c].name = 'esa_' + c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=5</i>\n",
       "<table id=\"table4715480400\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>esa_spscid</th><th>esa_det</th><th>esa_ra</th><th>esa_dec</th><th>esa_ra_err</th><th>esa_dec_err</th><th>esa_pos_flag</th><th>esa_astrom_flag</th><th>esa_nmap</th><th>esa_ndet</th><th>esa_dupl_flag</th><th>esa_flux</th><th>esa_flux_err</th><th>esa_fluxtml_err</th><th>esa_conf_err</th><th>esa_snr</th><th>esa_insterr_flag</th><th>esa_fluxsus</th><th>esa_fluxsus_err</th><th>esa_fluxdao</th><th>esa_fluxdao_err</th><th>esa_fluxtm2</th><th>esa_fluxtm2_err</th><th>esa_fwhm1</th><th>esa_fwhm1_err</th><th>esa_fwhm2</th><th>esa_fwhm2_err</th><th>esa_rot</th><th>esa_rot_err</th><th>esa_pntsrc_flag</th><th>esa_extsrc_flag</th><th>esa_lowfwhm_flag</th><th>esa_largegal_flag</th><th>esa_mapedge_flag</th><th>esa_ssocont_flag</th><th>esa_q3ctile</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>str25</th><th>str3</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str1</th><th>str1</th><th>int64</th><th>int64</th><th>str1</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str1</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str9</th><th>str10</th><th>str6</th><th>str6</th><th>str5</th><th>str6</th><th>float64</th><th>float64</th><th>str1</th><th>str1</th><th>str1</th><th>str1</th><th>str1</th><th>str1</th><th>int64</th></tr></thead>\n",
       "<tr><td>HSPSC500A_J2248.24-4439.6</td><td>PLW</td><td>342.0601</td><td>-44.66</td><td>2.1</td><td>1.5</td><td>F</td><td>F</td><td>1</td><td>1</td><td>F</td><td>23.0</td><td>5.7</td><td>1.8</td><td>5.6</td><td>4.0</td><td>F</td><td>19.8</td><td>2.5</td><td>35.9</td><td>14.4</td><td>22.7</td><td>4.1</td><td>40.6</td><td>4.2</td><td>31.1</td><td>3.5</td><td>44.2</td><td>16.4</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>F</td><td>6610338672980000767</td></tr>\n",
       "<tr><td>HSPSC500A_J2248.24-3504.0</td><td>PLW</td><td>342.0608</td><td>-35.0678</td><td>3.2</td><td>2.5</td><td>F</td><td>F</td><td>2</td><td>1</td><td>F</td><td>47.2</td><td>14.9</td><td>6.3</td><td>14.0</td><td>3.2</td><td>F</td><td>31.0</td><td>9.1</td><td>33.7</td><td>14.0</td><td>79.2</td><td>25.4</td><td>68.3</td><td>15.9</td><td>33.9</td><td>5.5</td><td>49.9</td><td>9.5</td><td>F</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>1265902921430597631</td></tr>\n",
       "<tr><td>HSPSC500A_J2248.24-2919.6</td><td>PLW</td><td>342.0612</td><td>-29.3283</td><td>2.9</td><td>2.5</td><td>F</td><td>F</td><td>1</td><td>1</td><td>F</td><td>45.6</td><td>11.9</td><td>6.2</td><td>10.8</td><td>3.8</td><td>F</td><td>36.4</td><td>8.5</td><td>62.9</td><td>21.1</td><td>82.4</td><td>25.3</td><td>54.2</td><td>10.3</td><td>52.0</td><td>9.5</td><td>57.5</td><td>167.5</td><td>F</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>1275437886266671103</td></tr>\n",
       "<tr><td>HSPSC500A_J2248.24-3046.4</td><td>PLW</td><td>342.0613</td><td>-30.7742</td><td>3.7</td><td>3.1</td><td>F</td><td>F</td><td>1</td><td>1</td><td>F</td><td>38.3</td><td>11.8</td><td>6.5</td><td>10.8</td><td>3.2</td><td>F</td><td>39.4</td><td>9.4</td><td>14.7</td><td>5.9</td><td>32.9</td><td>13.1</td><td>31.9</td><td>7.4</td><td>31.4</td><td>7.4</td><td>115.3</td><td>180.0</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>F</td><td>1268858408686059519</td></tr>\n",
       "<tr><td>HSPSC500A_J2248.26-3450.3</td><td>PLW</td><td>342.0659</td><td>-34.8386</td><td>3.5</td><td>0.5</td><td>F</td><td>F</td><td>2</td><td>2</td><td>F</td><td>63.7</td><td>13.9</td><td>5.1</td><td>13.4</td><td>4.6</td><td>F</td><td>66.9</td><td>7.9</td><td>36.2</td><td>4.9</td><td>58.4</td><td>10.6</td><td>35.7</td><td>3.8</td><td>30.9</td><td>3.4</td><td>27.9</td><td>25.6</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>F</td><td>1266008474546864127</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "        esa_spscid        esa_det ... esa_ssocont_flag     esa_q3ctile    \n",
       "                                  ...                                     \n",
       "          str25             str3  ...       str1              int64       \n",
       "------------------------- ------- ... ---------------- -------------------\n",
       "HSPSC500A_J2248.24-4439.6     PLW ...                F 6610338672980000767\n",
       "HSPSC500A_J2248.24-3504.0     PLW ...                F 1265902921430597631\n",
       "HSPSC500A_J2248.24-2919.6     PLW ...                F 1275437886266671103\n",
       "HSPSC500A_J2248.24-3046.4     PLW ...                F 1268858408686059519\n",
       "HSPSC500A_J2248.26-3450.3     PLW ...                F 1266008474546864127"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "esa_blind[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x123096550>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(esa_blind['esa_ra'],esa_blind['esa_dec'], s=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "for c in help_blind.colnames:\n",
    "    help_blind[c].name = 'blind_' + c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "218296 42567 19220\n"
     ]
    }
   ],
   "source": [
    "print(len(esa_blind), np.sum(esa_blind['esa_flux']>70), np.sum(esa_blind['esa_fluxsus']>70))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "124892"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(esa_blind['esa_fluxsus']/esa_blind['esa_fluxsus_err']>5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "101352\n"
     ]
    }
   ],
   "source": [
    "help_moc = MOC(filename ='../../dmu2/help_coverage_MOC.fits')\n",
    "in_help = inMoc(esa_blind['esa_ra'],esa_blind['esa_dec'],help_moc)\n",
    "\n",
    "print(np.sum(in_help))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "218296 42567 19220\n"
     ]
    }
   ],
   "source": [
    "print(len(esa_blind), np.sum(esa_blind['esa_flux']>70), np.sum(esa_blind['esa_fluxsus']>70))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "esa_blind = esa_blind[(esa_blind['esa_fluxsus']>70) & in_help]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3874"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(esa_blind)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "help_blind['blind_RA'].name = 'ra'\n",
    "help_blind['blind_Dec'].name = 'dec'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "266 2117\n"
     ]
    }
   ],
   "source": [
    "m = help_blind['ra'] < 0 \n",
    "print(np.sum(m), len(help_blind))\n",
    "help_blind['ra'][m] += 360."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1224caac8>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(help_blind['ra'],help_blind['dec'], s=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=5</i>\n",
       "<table id=\"table4786192568\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>blind_HELP_ID</th><th>ra</th><th>dec</th><th>blind_F_SPIRE_250</th><th>blind_FErr_SPIRE_250_u</th><th>blind_FErr_SPIRE_250_l</th><th>blind_F_SPIRE_350</th><th>blind_FErr_SPIRE_350_u</th><th>blind_FErr_SPIRE_350_l</th><th>blind_F_SPIRE_500</th><th>blind_FErr_SPIRE_500_u</th><th>blind_FErr_SPIRE_500_l</th><th>blind_Bkg_SPIRE_250</th><th>blind_Bkg_SPIRE_350</th><th>blind_Bkg_SPIRE_500</th><th>blind_Sig_conf_SPIRE_250</th><th>blind_Sig_conf_SPIRE_350</th><th>blind_Sig_conf_SPIRE_500</th><th>blind_Rhat_SPIRE_250</th><th>blind_Rhat_SPIRE_350</th><th>blind_Rhat_SPIRE_500</th><th>blind_n_eff_SPIRE_250</th><th>blind_n_eff_SPIRE_500</th><th>blind_n_eff_SPIRE_350</th><th>blind_Pval_res_250</th><th>blind_Pval_res_350</th><th>blind_Pval_res_500</th><th>blind_flag_spire_250</th><th>blind_flag_spire_350</th><th>blind_flag_spire_500</th><th>blind_F_BLIND_MF_SPIRE_250</th><th>blind_FErr_BLIND_MF_SPIRE_250</th><th>blind_F_BLIND_MF_SPIRE_350</th><th>blind_FErr_BLIND_MF_SPIRE_350</th><th>blind_F_BLIND_MF_SPIRE_500</th><th>blind_FErr_BLIND_MF_SPIRE_500</th><th>blind_r</th><th>blind_P</th><th>blind_RA_pix</th><th>blind_Dec_pix</th><th>blind_F_BLIND_pix_SPIRE</th><th>blind_FErr_BLIND_pix_SPIRE</th><th>blind_flag</th><th>blind_field</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><th></th><th></th><th></th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th></th><th></th><th>deg</th><th>deg</th><th>mJy</th><th>mJy</th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>bytes33</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><th>bool</th><th>bool</th><th>bool</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>bytes13</th></tr></thead>\n",
       "<tr><td>HELP_BLIND_J132035.199+340823.944</td><td>200.14666093222147</td><td>34.139984460626756</td><td>5585.709</td><td>5585.7417</td><td>5585.6445</td><td>2149.6992</td><td>2149.81</td><td>2149.446</td><td>659.279</td><td>659.7341</td><td>658.2682</td><td>-1.460162</td><td>-2.159969</td><td>-3.4670208</td><td>7.2524767</td><td>4.448374</td><td>3.1155865</td><td>nan</td><td>nan</td><td>0.9995246</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>True</td><td>True</td><td>True</td><td>6390.488777765193</td><td>6.475020475713654</td><td>2371.1640106039195</td><td>6.544042884037684</td><td>735.0517441505609</td><td>6.452658666321968</td><td>0.7965170388143706</td><td>1.0</td><td>200.1476401466958</td><td>34.139150647568016</td><td>5808.073027312961</td><td>6.622847430622127</td><td>0.0</td><td>HATLAS-NGP</td></tr>\n",
       "<tr><td>HELP_BLIND_J131503.697+243709.274</td><td>198.76540292122607</td><td>24.619242858594557</td><td>3730.1772</td><td>3730.2734</td><td>3729.9421</td><td>1502.2577</td><td>1506.5585</td><td>1497.7003</td><td>516.32574</td><td>518.7789</td><td>512.27045</td><td>-1.2838266</td><td>-2.7109509</td><td>-4.1480207</td><td>5.668097</td><td>4.231518</td><td>3.2830224</td><td>nan</td><td>1.0000073</td><td>0.9995233</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>True</td><td>True</td><td>True</td><td>3994.117869072061</td><td>6.324876530541631</td><td>1567.0040038706527</td><td>5.598440312095881</td><td>536.9172365043631</td><td>6.311143787466074</td><td>0.7807693245774889</td><td>1.0</td><td>198.76448128689057</td><td>24.618414825611595</td><td>3833.333240383705</td><td>6.203769866835555</td><td>0.0</td><td>HATLAS-NGP</td></tr>\n",
       "<tr><td>HELP_BLIND_J125440.864+285621.115</td><td>193.6702686733103</td><td>28.939198567126557</td><td>3371.739</td><td>3371.7888</td><td>3371.6328</td><td>1765.58</td><td>1765.6238</td><td>1765.4854</td><td>860.104</td><td>860.21045</td><td>859.85803</td><td>-0.5651935</td><td>-1.9437292</td><td>-3.5710735</td><td>25.787022</td><td>13.055087</td><td>6.358543</td><td>nan</td><td>nan</td><td>nan</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>True</td><td>True</td><td>True</td><td>4336.075321306187</td><td>5.561965754359003</td><td>2297.586230671728</td><td>5.613884128048924</td><td>1073.6664924712218</td><td>5.879615410558071</td><td>0.7623766258950777</td><td>1.0</td><td>193.66935390611053</td><td>28.93833936573529</td><td>3333.2032635538617</td><td>5.457766939853846</td><td>0.0</td><td>HATLAS-NGP</td></tr>\n",
       "<tr><td>HELP_BLIND_J133955.603+282402.670</td><td>204.9816801055134</td><td>28.400741740256905</td><td>2135.466</td><td>2135.4993</td><td>2135.387</td><td>1049.1398</td><td>1049.2178</td><td>1048.9945</td><td>472.19516</td><td>472.7262</td><td>471.0313</td><td>-0.8959201</td><td>-1.7262993</td><td>-2.8792737</td><td>8.486645</td><td>4.9961395</td><td>4.03243</td><td>nan</td><td>nan</td><td>0.9992486</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>1.0</td><td>1.0</td><td>1.0</td><td>True</td><td>True</td><td>True</td><td>2504.0886134660827</td><td>5.852280827955278</td><td>1168.3056811014544</td><td>5.838565811620903</td><td>527.4015769955221</td><td>6.492418954889658</td><td>0.8113158679247728</td><td>1.0</td><td>204.98138554544394</td><td>28.401032976576335</td><td>2152.6956528993496</td><td>5.738864517699985</td><td>0.0</td><td>HATLAS-NGP</td></tr>\n",
       "<tr><td>HELP_BLIND_J130125.252+291849.285</td><td>195.35521522575544</td><td>29.313690334163766</td><td>1762.0795</td><td>1762.3076</td><td>1761.5529</td><td>661.7097</td><td>662.2488</td><td>660.5981</td><td>217.47719</td><td>219.12042</td><td>214.50778</td><td>-1.4513615</td><td>-2.020604</td><td>-3.6917322</td><td>4.4567766</td><td>4.031373</td><td>3.614342</td><td>nan</td><td>1.000221</td><td>0.99962765</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>1.0</td><td>1.0</td><td>0.0</td><td>True</td><td>True</td><td>False</td><td>1851.6291091763517</td><td>6.026787479063286</td><td>696.6617160954174</td><td>5.580877219928563</td><td>236.4402131547448</td><td>5.930806503390525</td><td>0.7922672534032332</td><td>1.0</td><td>195.3548913282094</td><td>29.31396069609381</td><td>1846.0224374904212</td><td>5.906271642088381</td><td>0.0</td><td>HATLAS-NGP</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "          blind_HELP_ID                   ra         ... blind_flag blind_field\n",
       "                                         deg         ...                       \n",
       "             bytes33                   float64       ...  float64     bytes13  \n",
       "--------------------------------- ------------------ ... ---------- -----------\n",
       "HELP_BLIND_J132035.199+340823.944 200.14666093222147 ...        0.0  HATLAS-NGP\n",
       "HELP_BLIND_J131503.697+243709.274 198.76540292122607 ...        0.0  HATLAS-NGP\n",
       "HELP_BLIND_J125440.864+285621.115  193.6702686733103 ...        0.0  HATLAS-NGP\n",
       "HELP_BLIND_J133955.603+282402.670  204.9816801055134 ...        0.0  HATLAS-NGP\n",
       "HELP_BLIND_J130125.252+291849.285 195.35521522575544 ...        0.0  HATLAS-NGP"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "help_blind[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2117\n"
     ]
    }
   ],
   "source": [
    "print(len(help_blind))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rc1Le0MHh+nauyU3SVaO83OUzJtLY3sPb+04wPiJEu9kCkBZ6dU7eL60lPCRIF/r2ASLCTfNSaers5aVtVcREhJA9YZzVsdQY0qaYGrb6tm721bSyKDue0GAdN+8Lgm02PlcwibhIO09vOUZtS5fVkdQYcqvQi8hSESkVkTIR+dYg++8UkV2ur49FZI675yrfs+XwSYJEKMjW1rwvCbcH8YXzMwmy2fjT5qO0dvVaHUmNkSG7bkQkCHgMuBKoBApFZJ0xZu+Aw44AFxtjGkVkGfAkUODmucqHdPf2U3yskVlpMUSHhVgdx28880n5mLxPXKSduxZN4qmPDvOXLce4a3Em4Xb9rczfudOiXwiUGWMOG2N6gOeA5QMPMMZ8bIw5tczNFiDN3XOVb9lW3kh3n4PFOmmWz0qPi+C2/HSqGjt58PntOsY+ALhzMTYVqBjwvBIoOMvxdwNvDPdcEVkJrATIyNA5sr2Rwxg2Hz5J+vhw0uMirI6jRiAnJYZrZiXz2u7j/M/r+3j4upwxe++R/Pai8+efG3cK/WB3wgzaBBCRS3EW+guHe64x5kmcXT7k5+drE8MLldW2Ud/Ww2fz04Y+WHm9C6ZMICEqlN99dITkmDC+siTb6kjKQ9wp9JVA+oDnaUD16QeJyGzgKWCZMebkcM5VvqHwaAMR9iByU2KsjqJGycPX5VDT3MV/vbYPe7CNuxZnWh1JeYA7ffSFwFQRyRIRO7ACWDfwABHJAF4CPm+MOTCcc5VvaO3qZd/xFuZnjNcbpPxIkE345e1zuTInkUfWlvCXzUetjqQ8YMhPrDGmD7gPWA/sA14wxpSIyCoRWeU67BEgHnhcRHaISNHZzvXA96E8bNuxRhwG8jN1SKW/sQfbeOyOeVwxM5GH15bw63cP6rw4fsatO2ONMa8Dr5+27YkBj78CfMXdc5VvcRhD4bFGsiZEkhClywT6I3uwjcfvnMe/r97FTzYcoKali+/ekKuT1fkJnQJBDelwXTsN7T1cMTPR6ijKg+zBNn566xwmRofy2/cPc+xkB7+4LU/XAPYD2tmqhlR4tIHwkCDOS9E1SP2dzSY8tGwmP/zMLD450sB1v/qI4mMNVsdSI6SFXp1Vc4fzImxeeqyuIBVAVizM4KV7zickyMatT2zme6/spb27z+pY6hzpJ1ed1Su7qulzGObp1LYBJzc1htceuJA7Cybx+01HuOrnH/Dy9iq9k9YHaaFXZ7V6WyWJ0aGkxIZZHUVZICoshO/fmMvfVi0mOjyEB5/fwTWPfsgrO6vp7XdYHU+5SQu9OqOy2ja2lzcxL2M8Ijr6IpAtyIzjtfsv5Fe3z6W338H9z25nyY/e41fvHKS6qdPqeGoIOupGndHqbZUE2YQ8XSpQ4bxQe/2cFK6ZlczG0lr++PFRfvrWAX729gHOnxzPzfPSWJqbRIRdy4q30X8RNah+h2HNtiounpZAlE5HrAYIsgmXz0zk8pmJVDR0sHpbJS9tq+IbL+zk4Zf3sGxWMjfPS6MgKw6bjsP3Clro1aA2HzpJTUsX375uJi2dOtrCX410Jsn0uAgevGIaX798KoVHG1ldXMlru4/zYnElaePDufvCLFYsyNA57y2mffRqUC/vqCIqNFhvklJuEREWZsXxo1tmU/gfV/DoijySY8L47it7WfK/7/Knj4/qaB0LaYtefUpnTz9v7qlhWW4SYSHaElPDE24PYnleKsvzUvnk8El+8fZBvrOuhNXbKvmfm2ZZHS8gaYtefcrb+07Q1t3HTXNTrY6ifFxBdjzPfLWAR1fkUd3UyU2Pb6LwiN5pO9a00KtPWbujiqToMAp0uUA1CkSE5XmpvP2Ni1k8eQJrdlSxbme1duWMIe26Uf+gob2HjaV1fPnCLJ25UJ3VuVzIvXJmIg6H4aOyetq7+7htQTo2vUfD47TQq3/w2u7j9DkMN+Zpt40afUE24ZpZyYwLDebNkhpCg23cNDdVb8jzMC306h+8vL2K6YlRzEyOsjqK8mMXTUugu6+f90rrCLcHsSw32epIfk376NXflZ/soPhYI8vnpmgLS3ncFTMTKciK48OD9eyparY6jl/TQq/+bu2OKgCWa7eNGgMiwrWzk0kbH87qbZWcbOu2OpLf0kKvADDGsGZHFQVZcaTGhlsdRwWIYJuN2xdkIALPFpbTpzNieoQWegXAnqoWDte1c6OOnVdjbHyknVvmpVPd1MUHB+utjuOXtNArANZsr8IeZOMavSimLJCTEs2s1Bg2ltZqF44HaKFX9PU7WLezmktnJBAToTNVKmtcOyuZIJuwbmc1xujNVKNJC73iw7J66tu6+cy8NKujqAAWHR7CVTmJHKxtY7eOwhlVbhV6EVkqIqUiUiYi3xpk/wwR2Swi3SLyzdP2HRWR3SKyQ0SKRiu4Gj1rtlURGxHCpdMnWh1FBbiC7HhSYsJYX1JDn0MvzI6WIQu9iAQBjwHLgBzgdhHJOe2wBuAB4CdneJlLjTF5xpj8kYRVo6+1q5f1JTVcPzsFe7D+gqesZRPhqvOSaOzopehoo9Vx/IY7n+yFQJkx5rAxpgd4Dlg+8ABjTK0xphDo9UBG5UFv7Kmhu8/BTfN0tI3yDlMnjiMzPpL39tfS06et+tHgTqFPBSoGPK90bXOXATaISLGIrDzTQSKyUkSKRKSorq5uGC+vRuKlbZVkTYhkrq4Lq7yEiHD1eYm0dvex+fBJq+P4BXcK/WD3wg/nkvgFxph5OLt+7hWRiwY7yBjzpDEm3xiTn5CQMIyXV+eqsrGDLYcbdFIp5XUmxUcyPTGKDw7U0d3bb3Ucn+dOoa8E0gc8TwOq3X0DY0y1689aYA3OriDlBdbucP4z6gIjyhtdNmMinb39FB7TvvqRcqfQFwJTRSRLROzACmCdOy8uIpEiEnXqMXAVsOdcw6rRY4zhpW2VLMyMIz0uwuo4Sn1KelwEmfERbCqr10VKRmjIQm+M6QPuA9YD+4AXjDElIrJKRFYBiEiSiFQC3wC+LSKVIhINJAIfichOYCvwmjHmTU99M8p9uyqbOVTXzmf0IqzyYkumJtDc2cvuqiaro/g0t+ajN8a8Drx+2rYnBjyuwdmlc7oWYM5IAirPWLO9CnuwjWWzdMoD5b2mJ0WRMC6UDw/WMydNBwycKx04HYB6XVMeXJmTSEy4TnmgvJdNhCVTJ3C8uYuyujar4/gsLfQB6P3SOhrae/iMXoRVPiAvPZZIexBbDjdYHcVnaaEPQKu3VRIfaeeiaTqMVXm/4CAb+Zlx7D/eQnVTp9VxfJIW+gBT39bNW3tPcNPcVEKC9J9f+YaFmXEAPLe13OIkvkkXBw8gz3xSzocH6+hzGMaFBvPMJ/qhUb5hfKSdaYlRPFdYwf2XT9VGyjDp31YAMcZQeLSRSXERTIwOszqOUsNSkB1HbavzN1I1PFroA8jRkx3Ut3WT7/o1WClfMi0xitTYcJ7ecszqKD5HC30AKTraQGiwjVmpMVZHUWrYbCLctiCdjw+dpKKhw+o4PkULfYBo7uhlT3Uzc9Jjdd555bNunp+GiHPkmHKffuIDxN+KK+jtN38fvaCUL0qNDeeCyRN4sbgSh85/4zYt9AHA4TA8veUYGXERpMSGWx1HqRG5NT+NysZOthzRuerdpYU+AHxwsI6jJztYnB1vdRSlRuyqnCSiQoN5sUi7b9ylhT4A/GXzMSaMC+W81Giroyg1YuH2IK6bk8Lre47T2qWrl7pDC72fq2jo4N3SWu5YmE6wTf+5lX+4ZX4aXb0ONpTomHp36Cffz/3p46PYRLi9IMPqKEqNmnkZsaSND2ftTrcXuwtoWuj9WHNnL89uLee62ckkx+hFWOU/RITleSlsKqunrrXb6jheTwu9H3tuazntPf18dUm21VGUGnXL81Lpdxhe333c6iheTwu9n+rpc/CHTUc5f3I8uXonrPJD0xKjmJEUxdodVVZH8Xpa6P3Uq7uqqWnpYuVF2ppX/uuGvBS2lTfplAhD0ELvhxwOw5MfHGZ6YhQX6+Iiyo9dPzsFgHV6UfasdD56P/TWvhPsr2nlZ5+dg4hYHUepUTPYGgqT4iL48+ajjI+wn/XcOwJ45Jm26P2MMYZfvnOQzPgIbpiTYnUcpTxuTnosJ1q6qWnusjqK13Kr0IvIUhEpFZEyEfnWIPtniMhmEekWkW8O51w1ut7dX0tJdQv3XjqFYF2FRwWA3NQYbAI7K5usjuK1hqwEIhIEPAYsA3KA20Uk57TDGoAHgJ+cw7lqlJxqzafHhXPj3FSr4yg1JsaFBjNl4jh2VjbhMDqj5WDcafItBMqMMYeNMT3Ac8DygQcYY2qNMYXA6RNPDHmuGj3vldays7KZr10yRdfUVAFlTlosTR29OvrmDNypBqlAxYDnla5t7nD7XBFZKSJFIlJUV1fn5surUxwOw4/XH2BSfAS3zE+zOo5SYyonOZpgm7CjQrtvBuNOoR9s2Ia7vx+5fa4x5kljTL4xJj8hQYcEDtcru6rZd7yFb1w5TVvzKuCEhgQxMzma3VXN9OuCJJ/iTkWoBNIHPE8D3B20OpJzlZt6+hz8dMMBZiRF/X1csVKBZk5aDB09/Ryua7M6itdxp9AXAlNFJEtE7MAKYJ2brz+Sc5Wbni+qoLyhg39fOgObTcfNq8A0NTGK0GAbuyqbrY7idYa8YcoY0yci9wHrgSDg98aYEhFZ5dr/hIgkAUVANOAQkQeBHGNMy2DneuqbCUStXb384q0DLMyM45Lp2uWlAldIkI2c5GhKjjezvD9FhxcP4NadscaY14HXT9v2xIDHNTi7Zdw6V42exzce4mR7D3/40ky9C1YFvNlpsWyvaOJgbRszk3VFtVP0R54Pq2jo4HcfHeEzc1OZnRZrdRylLDdl4jjCQ4LYpTdP/QMt9D7sf9eXYhP416XTrY6ilFcIsgm5qdHsO95KT5/D6jheQwu9jyo82sArO6tZedFkXT1KqQFmp8XS0++g9ESr1VG8hhZ6H9TX7+Dhl/eQGhvOPRdPtjqOUl4la0Ik40KDtftmAC30Puivn5Szv6aVh6+bSbg9yOo4SnkVmwi5qTGU1rTS1dtvdRyvoIXex9S3dfPTDaUsmTqBq89LsjqOUl5pTloMfQ7DvuMtVkfxCrrwiI/5p78U097dz/xJ43l2a8XQJygVgNLjIogJD2F3VTNzM8ZbHcdy2qL3IdvLGyk+1sgFU+KZGBVmdRylvJZNhFmpMRw80UZHT5/VcSynLXoLDLYc2lAcxvCbjYeIDgvm0ukTPZBKKf8yOy2Gj8rq2VvdQn5mnNVxLKUteh9RdLSRqqZOluUmExqiF2CVGkpqbDhxkXad+wYt9D6ho7uP9SU1ZE2IZHZajNVxlPIJIsKctBgO1bXR0nX6mkiBRQu9D3hr3wm6+/q5fnaKzmej1DDMSY/FQMC36rXQe7mqpk62HmlgUXY8STF6AVap4ZgYFUZKbBg7A3zlKS30XsxhDK/srCYiNJgrZiZaHUcpn5SXFktVUyeHAnhBEi30XmxHeRPlDR0sOy+JML0Aq9Q5mZ0WiwBrt1dZHcUyWui9VGdPP2+U1JARF0Fehk5BrNS5ig4PITshkpd3VGNMYK4nq4XeS72z/wQd3X3cMCcFm16AVWpE8tJjKW/oYFt5YPbVa6H3QjXNXWw5fJKFWXGkxOoUxEqNVG5KDOEhQazeVml1FEtoofcyxhjW7awmLCSIK3P0AqxSoyE0JIhluUm8srM6IGe01ELvZXZVNnP0ZDtX5yQRYdcZKpQaLbfMT6O1q48Ne09YHWXMaaH3It29/byx5zipseHMz9QZ95QaTYuy40mNDefF4sDrvtFC70XeLa2lpUsvwCrlCTabcPO8VD46WEdNc5fVccaUFnovUdvaxaayevInjSc9LsLqOEr5pZvnp+EwBNxFWbcKvYgsFZFSESkTkW8Nsl9E5Jeu/btEZN6AfUdFZLeI7BCRotEM7y+MMby68zj2YBtX6apRSnnMpPhICrLieL6wAocjcMbUD1noRSQIeAxYBuQAt4tIzmmHLQOmur5WAr85bf+lxpg8Y0z+yCP7n5LqFsrq2rhyZiLjQvUCrFKedEdBBuUNHXxUVm91lDHjTot+IejbStkAAA5ASURBVFBmjDlsjOkBngOWn3bMcuDPxmkLECsiyaOc1S/19Dl4bfdxkmPCWJgVb3Ucpfze0twk4iLt57QAkK9yp9CnAgMXJ610bXP3GANsEJFiEVl5pjcRkZUiUiQiRXV1dW7E8g/vH6ilubOX62enEGTTC7BKeVpocBC3zk/jrX0nONESGBdl3Sn0g1Wf0zu3znbMBcaYeTi7d+4VkYsGexNjzJPGmHxjTH5CQoIbsXzfybZuPjhYT156LJkTIq2Oo1TAuH1hBv0OwwuFFUMf7AfcKfSVQPqA52lAtbvHGGNO/VkLrMHZFaSAV3cdJ9gmLM3VC7BKjaXMCZFcOGUCz24tp6/fYXUcj3On0BcCU0UkS0TswApg3WnHrAPuco2+WQQ0G2OOi0ikiEQBiEgkcBWwZxTz+6z9x1soPdHK5TMmEh0WYnUcpQLOXYsnUd3cxfoS/79TdshCb4zpA+4D1gP7gBeMMSUiskpEVrkOex04DJQB/wd8zbU9EfhIRHYCW4HXjDFvjvL34HN6+hy8squaiVGhLJ48weo4SgWky2cmkhkfwVMfHbY6ise5NZbPGPM6zmI+cNsTAx4b4N5BzjsMzBlhRr/z7v4TNHb08tUl2XoBVimLBNmEL1+YxSNrSyg+1sj8Sf477YjeGTvG9la38JHrDtgsvQCrlKVumZ9GTHgIv/PzVr0W+jHU7zA8tGY34fZgvQCrlBeIsAdzR0EGb+6poaKhw+o4HqOFfgw9veUYOyuauHZWsk5BrJSX+MLiTIJtNh7feMjqKB6jhX6MHG/u5H/f3M+SqROYkxZjdRyllEtSTBi3LUjnb0UVftuq10I/Rr6ztoR+Y/jvG2chOgWxUl7la5dOxibCY++VWR3FI7TQj4H1JTVs2HuCr18+jYx4nYJYKW+THBPO7QvTebG40i9b9VroPexkWzf/sWY3M5Ki+MqSLKvjKKXO4GuXTsFmEx5956DVUUadFnoPMsbw0Eu7aens4xcr8ggJ0r9upbxVYnQYXzw/k9XbKtld2Wx1nFGllceD/lZcyYa9J/jXq6czIyna6jhKqSHcd9kU4iPt/OcrJTjvA/UPWug95FBdG99dV8Ki7DjuvlC7bJTyBdFhIfzb1TMoPtbI2h2nz93ou7TQe0BHTx/3PF1MaEgQP/tsHjad5kApn3HL/DRmp8Xwgzf20drVa3WcUaGFfpQZY/iPNXs4WNvGoyvySIkNtzqSUmoYbDbhuzecR11rN99/da/VcUaFFvpR9odNR1mzvYoHL5/GkqmBsYCKUv5mbsZ4Vl08mReKKtlQUmN1nBHTQj+K3txTw/df28tVOYncf9kUq+MopUbgwSumkZMczUMv7aa+rdvqOCOihX6UbCtv5OvPbScvPZZHV8zVfnmlfJw92MYvVuTR2t3HA89up9eHV6LSQj8KdlU28cXfbyUpJoyn7son3B5kdSSl1CiYlhjFD26axceHTvLIWt8dcqlTKI7QtvJGvvC7rcREhPD03QXEjwu1OpJSahTdPD+NQ3VtPL7xEJMTIvnKkmyrIw2bFvoReK+0lvuf2U78ODvPfnWRjrBRyk9986rpHKlv579e20eQTfjSBb51b4x23ZwDYwy/ff8QX/5jIelxETy/crEWeaX8mM0m/GJFHlefl8h3X9nLr9896FPdOFroh6mutZtVTxfzgzf2c01uMqvvWUxSTJjVsZRSHhYaHMRjd8zjprmp/GTDAb75t120d/dZHcst2nXjJofDsGZ7Fd9/bS8dPf08tGwGKy/K1rnllQogwUE2fnrrHNLHh/Or98rYXtHIL1fMJTfVuxcT0kI/BGMMb++r5acbStlf08rcjFh+fMscpkwcZ3U0pZQFbDbhG1dNZ1F2PF9/fgc3/Pojbp2fzr9cNY2J0d75270W+jOobe1izbYqni+s4HB9O5PiI/jFbXlcPyeFIB0jr1TAO3/KBN7654v41btl/HnzUdburOKGOSl8btEkZqfFWh3vH7hV6EVkKfAoEAQ8ZYz54Wn7xbX/GqAD+KIxZps753qL5o5edlY2UXyskY2ltex0zUedP2k89102hevnpOh88kqpfxAbYefh63K4a/EkfrPxEGt3VPNCUSXZEyK5dMZE1xrRsYyPtFuaU4a6ciwiQcAB4EqgEigEbjfG7B1wzDXA/TgLfQHwqDGmwJ1zB5Ofn2+KioqG/c00d/bS7zD0ORw4HNBvDP39ho7ePtq6+mjrdn61dPZR29rFiZZuyhvaOVLXTnVzl+t7gbz0WC6bPpGluUlMTYwado6hPPNJ+ai/plLq7O4oyPD4e7R09bJ2RzVv7T3BlkMn6XHdTZs2PpzshHFMiosgKSaM2IgQYsPtjI8IISYihAh7MPZgG2HBtnO+F0dEio0x+YPtc6dFvxAoM8Ycdr3Yc8ByYGCxXg782Th/amwRkVgRSQYy3Th31BT8z9t09bp/m3JcpJ2MuAgWZcczeeI48tJjyU2NISY8xBPxlFJ+LjoshM8vmsTnF02ivbuPnRVN7KpqZk9VM0dPtrO9vJHWrjOP1ImPtFP88JWjnsudQp8KVAx4Xomz1T7UMalunguAiKwEVrqetolIqRvZRuQYsN3Tb+I0Aagfm7caNZp57Phibp/LfKfVAdxwDJBHzvn0SWfa4U6hH+zK4+n9PWc6xp1znRuNeRJ40o08PkdEis70K5W30sxjxxdz+2LmQOZOoa8E0gc8TwNOX2PrTMfY3ThXKaWUB7kzjKQQmCoiWSJiB1YA6047Zh1wlzgtApqNMcfdPFcppZQHDdmiN8b0ich9wHqcQyR/b4wpEZFVrv1PAK/jHHFThnN45ZfOdq5HvhPv5otdUpp57Phibl/MHLCGHF6plFLKt+kdQEop5ee00CullJ/TQu9BIrJUREpFpExEvmV1HneIyO9FpFZE9lidxV0iki4i74nIPhEpEZGvW51pKCISJiJbRWSnK/N3rc7kLhEJEpHtIvKq1VmUe7TQe4hr+ofHgGVADnC7iORYm8otfwSWWh1imPqAfzHGzAQWAff6wN91N3CZMWYOkAcsdY1Y8wVfB/ZZHUK5Twu95/x96ghjTA9wavoHr2aM+QBosDrHcBhjjp+aRM8Y04qzCKVam+rsjFOb62mI68vrR0aISBpwLfCU1VmU+7TQe86ZpoVQHiQimcBc4BNrkwzN1QWyA6gF3jLGeH1m4BfAvwHuTyqlLKeF3nPcnv5BjQ4RGQesBh40xrRYnWcoxph+Y0wezjvGF4pIrtWZzkZErgNqjTHFVmdRw6OF3nPcmTpCjRIRCcFZ5P9qjHnJ6jzDYYxpAjbi/ddGLgBuEJGjOLsiLxORp62NpNyhhd5zdPqHMeJa+OZ3wD5jzM+szuMOEUkQkVjX43DgCmC/tanOzhjzkDEmzRiTifP/87vGmM9ZHEu5QQu9hxhj+oBT0z/sA17whekfRORZYDMwXUQqReRuqzO54QLg8zhbmDtcX9dYHWoIycB7IrILZ6PgLWOMDldUHqFTICillJ/TFr1SSvk5LfRKKeXntNArpZSf00KvlFJ+Tgu9Ukr5OS30Sinl57TQK8uJSL9r7HuJa9reb4iIzbUvX0R+eZZzM0XkjrFL+6n37nTNV+MVROQ217TYOiZf/Z0WeuUNOo0xecaY84Arca4//B0AY0yRMeaBs5ybCVhS6F0OuearcZtrCmuPMMY8D3zFU6+vfJMWeuVVjDG1wErgPnG65FTrVEQuHnDn63YRiQJ+CCxxbftnVyv7QxHZ5vo633XuJSKyUUReFJH9IvJX19QJiMgCEfnY9dvEVhGJcs0s+WMRKRSRXSLyT+7kF5GXRaTY9dvJygHb20TkeyLyCbD4DO95nuvxDtd7TnWd+7kB23976geFa2Gbba7XeGcU/xmUvzHG6Jd+WfoFtA2yrRFIBC4BXnVtewW4wPV4HBA8cL9rewQQ5no8FShyPb4EaMY5uZwN5zQPFwJ24DCwwHVctOt1VwLfdm0LBYqArNMyZgJ7TtsW5/ozHNgDxLueG+Czrsdnes9fAXcOOCYcmOn6vkNc2x8H7gIScE6DnTXwfQd8r68O9netX4H5FTzMnwtKjZXBpnneBPxMRP4KvGSMqXQ1ygcKAX4tInlAPzBtwL6txphKAFe/eibO4n/cGFMIYFzTG4vIVcBsEbnFdW4Mzh8cR4bI/YCI3OR6nO4656Qry2rX9ulneM/NwH+4Fvd4yRhzUEQuB+YDha7vNRzn/PWLgA+MMUdcr+FTi8WosaWFXnkdEcnGWRhrcbZoATDG/FBEXsPZh79FRK4Y5PR/Bk4Ac3C23LsG7Ose8Lgf5/9/YfB1AgS43xizfhi5L8E5C+ViY0yHiGwEwly7u4wx/QNe+1PvaYx5xtW1cy2wXkS+4jr2T8aYh057rxvOkFupT9E+euVVRCQBeAL4tTHGnLZvsjFmtzHmRzi7UmYArUDUgMNicLaWHThntBzqwud+IEVEFrjeI0pEgnHOOnqPa557RGSaiEQO8VoxQKOryM/A2ep2+z1dP+AOG2N+iXNK69nAO8AtIjLRdWyciEzC2fV0sYhkndo+RDYVwLRFr7xBuKsrJQTnQt9/AQabV/5BEbkUZ2t8L/AGziXt+kRkJ86FzR8HVovIrcB7QPvZ3tgY0yMitwG/cs0L34mzVf4Uzq6dba6LtnXAjUN8H28Cq1xTD5cCW4b5nrcBnxORXqAG+J4xpkFEvg1scA057QXuNcZscV3sfcm1vRbniCWlPkWnKVbqHIlzfdpXjTFetQSgqwvpm8aY66zOoryDdt0ode76gRhvu2EK5281jVZnUd5DW/RKKeXntEWvlFJ+Tgu9Ukr5OS30Sinl57TQK6WUn/v/7dnOXgb41a4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "nb_merge_dist_plot(\n",
    "    SkyCoord(help_blind['ra'], help_blind['dec']),\n",
    "    SkyCoord(esa_blind['esa_ra'], esa_blind['esa_dec'])\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "match_dist=20.*u.arcsec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Given the graph above, we use 0.8 arc-second radius\n",
    "master_catalogue = merge_catalogues(help_blind, esa_blind, \"esa_ra\", \"esa_dec\", radius=match_dist)\n",
    "master_catalogue = clean_table(master_catalogue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=5</i>\n",
       "<table id=\"table4873430072\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>blind_HELP_ID</th><th>ra</th><th>dec</th><th>blind_F_SPIRE_250</th><th>blind_FErr_SPIRE_250_u</th><th>blind_FErr_SPIRE_250_l</th><th>blind_F_SPIRE_350</th><th>blind_FErr_SPIRE_350_u</th><th>blind_FErr_SPIRE_350_l</th><th>blind_F_SPIRE_500</th><th>blind_FErr_SPIRE_500_u</th><th>blind_FErr_SPIRE_500_l</th><th>blind_Bkg_SPIRE_250</th><th>blind_Bkg_SPIRE_350</th><th>blind_Bkg_SPIRE_500</th><th>blind_Sig_conf_SPIRE_250</th><th>blind_Sig_conf_SPIRE_350</th><th>blind_Sig_conf_SPIRE_500</th><th>blind_Rhat_SPIRE_250</th><th>blind_Rhat_SPIRE_350</th><th>blind_Rhat_SPIRE_500</th><th>blind_n_eff_SPIRE_250</th><th>blind_n_eff_SPIRE_500</th><th>blind_n_eff_SPIRE_350</th><th>blind_Pval_res_250</th><th>blind_Pval_res_350</th><th>blind_Pval_res_500</th><th>blind_flag_spire_250</th><th>blind_flag_spire_350</th><th>blind_flag_spire_500</th><th>blind_F_BLIND_MF_SPIRE_250</th><th>blind_FErr_BLIND_MF_SPIRE_250</th><th>blind_F_BLIND_MF_SPIRE_350</th><th>blind_FErr_BLIND_MF_SPIRE_350</th><th>blind_F_BLIND_MF_SPIRE_500</th><th>blind_FErr_BLIND_MF_SPIRE_500</th><th>blind_r</th><th>blind_P</th><th>blind_RA_pix</th><th>blind_Dec_pix</th><th>blind_F_BLIND_pix_SPIRE</th><th>blind_FErr_BLIND_pix_SPIRE</th><th>blind_flag</th><th>blind_field</th><th>flag_merged</th><th>esa_spscid</th><th>esa_det</th><th>esa_ra_err</th><th>esa_dec_err</th><th>esa_pos_flag</th><th>esa_astrom_flag</th><th>esa_nmap</th><th>esa_ndet</th><th>esa_dupl_flag</th><th>esa_flux</th><th>esa_flux_err</th><th>esa_fluxtml_err</th><th>esa_conf_err</th><th>esa_snr</th><th>esa_insterr_flag</th><th>esa_fluxsus</th><th>esa_fluxsus_err</th><th>esa_fluxdao</th><th>esa_fluxdao_err</th><th>esa_fluxtm2</th><th>esa_fluxtm2_err</th><th>esa_fwhm1</th><th>esa_fwhm1_err</th><th>esa_fwhm2</th><th>esa_fwhm2_err</th><th>esa_rot</th><th>esa_rot_err</th><th>esa_pntsrc_flag</th><th>esa_extsrc_flag</th><th>esa_lowfwhm_flag</th><th>esa_largegal_flag</th><th>esa_mapedge_flag</th><th>esa_ssocont_flag</th><th>esa_q3ctile</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><th></th><th></th><th></th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th>mJy</th><th></th><th></th><th>deg</th><th>deg</th><th>mJy</th><th>mJy</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>bytes33</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><th>bool</th><th>bool</th><th>bool</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>bytes13</th><th>bool</th><th>str25</th><th>str3</th><th>float64</th><th>float64</th><th>str1</th><th>str1</th><th>int64</th><th>int64</th><th>str1</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str1</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str9</th><th>str10</th><th>str6</th><th>str6</th><th>str5</th><th>str6</th><th>float64</th><th>float64</th><th>str1</th><th>str1</th><th>str1</th><th>str1</th><th>str1</th><th>str1</th><th>int64</th></tr></thead>\n",
       "<tr><td>HELP_BLIND_J005850.021-290120.932</td><td>14.708420259504996</td><td>-29.022481017107122</td><td>98.77845</td><td>99.968735</td><td>96.31086</td><td>124.7146</td><td>129.38513</td><td>119.92359</td><td>88.531494</td><td>93.95626</td><td>82.83312</td><td>-0.54408854</td><td>-1.4693842</td><td>-1.8779491</td><td>6.8054605</td><td>6.2304897</td><td>5.475402</td><td>0.9997964</td><td>0.99895924</td><td>1.0013632</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.786</td><td>0.011</td><td>0.001</td><td>True</td><td>False</td><td>False</td><td>99.09233133618805</td><td>5.862384227497036</td><td>118.15742275589417</td><td>5.720645273573185</td><td>80.3255683900608</td><td>5.94356267031562</td><td>0.9293925089320924</td><td>1.0</td><td>14.708420259504994</td><td>-29.022481017107122</td><td>81.98030787099047</td><td>5.744384913631275</td><td>0.0</td><td>HATLAS-SGP</td><td>False</td><td>HSPSC500A_J0058.83-2901.3</td><td>PLW</td><td>0.2</td><td>1.9</td><td>F</td><td>F</td><td>2</td><td>2</td><td>F</td><td>93.0</td><td>18.5</td><td>4.4</td><td>18.2</td><td>5.0</td><td>F</td><td>103.1</td><td>6.0</td><td>62.3</td><td>5.1</td><td>82.7</td><td>9.2</td><td>37.6</td><td>2.5</td><td>28.8</td><td>2.0</td><td>156.5</td><td>7.4</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>F</td><td>1504927953216077823</td></tr>\n",
       "<tr><td>HELP_BLIND_J143202.684-005219.298</td><td>218.01118256749152</td><td>-0.8720270859434005</td><td>92.0684</td><td>94.78802</td><td>88.62687</td><td>105.01896</td><td>105.90154</td><td>103.5048</td><td>79.769844</td><td>80.46397</td><td>78.449684</td><td>-0.545455</td><td>-1.7080371</td><td>-2.6340785</td><td>3.8569703</td><td>4.1428137</td><td>3.7074745</td><td>0.9996251</td><td>0.9987531</td><td>0.99879545</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>0.108</td><td>0.99</td><td>0.003</td><td>False</td><td>True</td><td>False</td><td>86.55175551801368</td><td>4.305081050854975</td><td>98.74367129812639</td><td>4.141099879684436</td><td>89.14762223794504</td><td>4.648646893866144</td><td>0.9545790985977408</td><td>1.0</td><td>218.01145900137752</td><td>-0.872304291458213</td><td>83.30401071244134</td><td>4.217607263838142</td><td>0.0</td><td>GAMA-15</td><td>False</td><td>HSPSC500A_J1432.04-0052.3</td><td>PLW</td><td>0.2</td><td>1.1</td><td>F</td><td>F</td><td>2</td><td>2</td><td>F</td><td>80.8</td><td>12.3</td><td>3.7</td><td>11.9</td><td>6.6</td><td>F</td><td>70.3</td><td>5.4</td><td>97.9</td><td>11.6</td><td>120.1</td><td>11.9</td><td>52.2</td><td>3.2</td><td>41.4</td><td>2.3</td><td>135.1</td><td>14.0</td><td>F</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>4029353874031640575</td></tr>\n",
       "<tr><td>HELP_BLIND_J234742.246-505502.041</td><td>356.926025537202</td><td>-50.9172335929534</td><td>598.07623</td><td>598.8127</td><td>596.6423</td><td>237.13483</td><td>238.16872</td><td>234.99754</td><td>93.14271</td><td>96.2304</td><td>88.49542</td><td>-1.7151464</td><td>-1.9628683</td><td>-2.3646576</td><td>2.80155</td><td>2.8657365</td><td>0.29085663</td><td>0.999973</td><td>0.99908364</td><td>0.99877393</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>1.0</td><td>0.0</td><td>0.0</td><td>True</td><td>False</td><td>False</td><td>625.6430004473278</td><td>7.564444264029623</td><td>255.41551288254598</td><td>6.388365107389981</td><td>92.76635856307797</td><td>6.826082580660209</td><td>0.8142882664242782</td><td>1.0</td><td>-3.0749122273576184</td><td>-50.91672077859669</td><td>630.6899994670647</td><td>7.3969487177920366</td><td>0.0</td><td>SSDF</td><td>False</td><td>HSPSC500A_J2347.70-5055.0</td><td>PLW</td><td>1.9</td><td>1.3</td><td>F</td><td>F</td><td>1</td><td>1</td><td>F</td><td>93.9</td><td>14.6</td><td>6.2</td><td>14.1</td><td>6.4</td><td>F</td><td>99.5</td><td>9.2</td><td>78.2</td><td>9.2</td><td>84.7</td><td>13.0</td><td>36.0</td><td>3.2</td><td>29.5</td><td>2.8</td><td>5.7</td><td>18.0</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>F</td><td>6617727391118655487</td></tr>\n",
       "<tr><td>HELP_BLIND_J133535.509+332231.864</td><td>203.89795334847224</td><td>33.375517694228094</td><td>247.39622</td><td>247.52312</td><td>247.0695</td><td>162.83945</td><td>163.17282</td><td>162.14287</td><td>93.51171</td><td>95.176346</td><td>90.58793</td><td>-1.9765978</td><td>-3.0043278</td><td>-3.6996837</td><td>4.0515957</td><td>3.8353555</td><td>2.8812099</td><td>0.99990565</td><td>0.9993557</td><td>0.9993201</td><td>2000.0</td><td>2000.0</td><td>2000.0</td><td>1.0</td><td>1.0</td><td>0.017</td><td>True</td><td>True</td><td>False</td><td>304.6756554232607</td><td>6.1986276940553084</td><td>175.20419458345066</td><td>5.507390349497625</td><td>94.35960810625575</td><td>6.531757003785</td><td>0.764058099511886</td><td>1.0</td><td>203.8988893799687</td><td>33.37465550928671</td><td>249.35024378983059</td><td>6.157150364962375</td><td>0.0</td><td>HATLAS-NGP</td><td>False</td><td>HSPSC500A_J1335.59+3322.5</td><td>PLW</td><td>1.2</td><td>1.1</td><td>F</td><td>F</td><td>1</td><td>1</td><td>F</td><td>107.5</td><td>16.9</td><td>6.2</td><td>16.2</td><td>6.4</td><td>F</td><td>90.4</td><td>9.3</td><td>113.8</td><td>14.6</td><td>147.8</td><td>18.4</td><td>46.8</td><td>3.5</td><td>42.9</td><td>3.1</td><td>57.6</td><td>32.0</td><td>F</td><td>T</td><td>F</td><td>T</td><td>F</td><td>F</td><td>4503041075463585791</td></tr>\n",
       "<tr><td>HELP_BLIND_J230131.400-521531.117</td><td>345.3808354087208</td><td>-52.25864372004371</td><td>86.358665</td><td>89.13272</td><td>81.687164</td><td>93.17893</td><td>96.41197</td><td>89.19958</td><td>80.33117</td><td>82.44211</td><td>76.59557</td><td>-1.3162462</td><td>-2.4850252</td><td>-2.219413</td><td>1.9391605</td><td>2.1729171</td><td>0.539811</td><td>0.99924093</td><td>1.0002862</td><td>0.99972296</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><td>False</td><td>False</td><td>False</td><td>85.69859791575458</td><td>6.906774615419661</td><td>92.80452174264356</td><td>5.802316907674272</td><td>88.7556240018308</td><td>7.028137251744165</td><td>0.9421256960488016</td><td>1.0</td><td>-14.618756970440675</td><td>-52.258943855617716</td><td>72.19817974126349</td><td>6.780223271325235</td><td>0.0</td><td>SSDF</td><td>False</td><td>HSPSC500A_J2301.52-5215.5</td><td>PLW</td><td>2.3</td><td>1.5</td><td>F</td><td>F</td><td>1</td><td>1</td><td>F</td><td>93.4</td><td>18.0</td><td>7.1</td><td>17.7</td><td>5.2</td><td>F</td><td>87.6</td><td>10.2</td><td>141.0</td><td>20.0</td><td>115.8</td><td>19.7</td><td>44.1</td><td>4.6</td><td>38.2</td><td>3.8</td><td>17.0</td><td>27.1</td><td>T</td><td>F</td><td>F</td><td>F</td><td>F</td><td>F</td><td>6587609568610615295</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "          blind_HELP_ID                   ra         ...     esa_q3ctile    \n",
       "                                         deg         ...                    \n",
       "             bytes33                   float64       ...        int64       \n",
       "--------------------------------- ------------------ ... -------------------\n",
       "HELP_BLIND_J005850.021-290120.932 14.708420259504996 ... 1504927953216077823\n",
       "HELP_BLIND_J143202.684-005219.298 218.01118256749152 ... 4029353874031640575\n",
       "HELP_BLIND_J234742.246-505502.041   356.926025537202 ... 6617727391118655487\n",
       "HELP_BLIND_J133535.509+332231.864 203.89795334847224 ... 4503041075463585791\n",
       "HELP_BLIND_J230131.400-521531.117  345.3808354087208 ... 6587609568610615295"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "master_catalogue[(master_catalogue['blind_F_SPIRE_500'] > 0) & (master_catalogue['esa_fluxsus'] > 0)][:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "master_catalogue['ra'].name = 'blind_ra'\n",
    "master_catalogue['dec'].name = 'blind_dec'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(np.isnan(master_catalogue['blind_ra']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 4535\n"
     ]
    }
   ],
   "source": [
    "m = master_catalogue['blind_ra'] < 0 \n",
    "print(np.sum(m), len(master_catalogue))\n",
    "master_catalogue['blind_ra'][m] += 360."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x12279f5f8>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(master_catalogue['blind_ra'],master_catalogue['blind_dec'], s=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4535"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(master_catalogue)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## XID+ VO objects (after first ingestion missing fields)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [],
   "source": [
    "cross_query = \"\"\"\n",
    "SELECT\n",
    "    db.help_id,\n",
    "    db.ra,\n",
    "    db.dec,\n",
    "    db.f_spire_500,\n",
    "    db.ferr_spire_500\n",
    "FROM herschelhelp.main AS db\n",
    "JOIN TAP_UPLOAD.t1 AS tc\n",
    "ON 1=CONTAINS(POINT('ICRS', db.ra, db.dec),\n",
    "CIRCLE('ICRS', tc.blind_ra, tc.blind_dec, 20.0/3600.))\n",
    "WHERE db.f_spire_500 IS NOT NULL\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "full_query = \"\"\"\n",
    "SELECT\n",
    "    db.help_id,\n",
    "    db.ra,\n",
    "    db.dec,\n",
    "    db.f_spire_500,\n",
    "    db.ferr_spire_500\n",
    "FROM herschelhelp.main AS db\n",
    "WHERE db.f_spire_500 IS NOT NULL\n",
    "\"\"\"\n",
    "\n",
    "# construct a service; I’ve taken the URL from TOPCAT’s\n",
    "# TAP service browser # (\"Selected TAP Service\" near the\n",
    "# foot of the dialog)\n",
    "service = vo.dal.TAPService(\n",
    "    \"https://herschel-vos.phys.sussex.ac.uk/__system__/tap/run/tap\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: W50: ?:?:?: W50: Invalid unit string 'mJy/Beam' [astropy.io.votable.tree]\n",
      "WARNING:astropy:W50: ?:?:?: W50: Invalid unit string 'mJy/Beam'\n",
      "WARNING: UnknownElementWarning: None:13:287: UnknownElementWarning: Unknown element errorSummary [pyvo.utils.xml.elements]\n",
      "WARNING:astropy:UnknownElementWarning: None:13:287: UnknownElementWarning: Unknown element errorSummary\n",
      "WARNING: UnknownElementWarning: None:13:336: UnknownElementWarning: Unknown element message [pyvo.utils.xml.elements]\n",
      "WARNING:astropy:UnknownElementWarning: None:13:336: UnknownElementWarning: Unknown element message\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-121-11a9beb1cc5b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mjob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0mjob_url\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mjob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mphases\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'COMPLETED'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Job {} running after {} seconds.'\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mjob\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mphase\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mround\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mstart_time\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/pyvo/dal/tap.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m(self, phases, timeout)\u001b[0m\n\u001b[1;32m    782\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    783\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 784\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwait_for_statechange\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    785\u001b[0m             \u001b[0;31m# use the cached value\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    786\u001b[0m             \u001b[0mcur_phase\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_job\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mphase\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/pyvo/dal/tap.py\u001b[0m in \u001b[0;36m_update\u001b[0;34m(self, wait_for_statechange, timeout)\u001b[0m\n\u001b[1;32m    526\u001b[0m                 response = self._session.get(\n\u001b[1;32m    527\u001b[0m                     self.url, stream=True, timeout=timeout, params={\n\u001b[0;32m--> 528\u001b[0;31m                         \u001b[0;34m\"WAIT\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"-1\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    529\u001b[0m                     }\n\u001b[1;32m    530\u001b[0m                 )\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/requests/sessions.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, url, **kwargs)\u001b[0m\n\u001b[1;32m    541\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    542\u001b[0m         \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msetdefault\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'allow_redirects'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 543\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'GET'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    544\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    545\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0moptions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/requests/sessions.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json)\u001b[0m\n\u001b[1;32m    528\u001b[0m         }\n\u001b[1;32m    529\u001b[0m         \u001b[0msend_kwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msettings\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 530\u001b[0;31m         \u001b[0mresp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0msend_kwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    531\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    532\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mresp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/requests/sessions.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, **kwargs)\u001b[0m\n\u001b[1;32m    641\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    642\u001b[0m         \u001b[0;31m# Send the request\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 643\u001b[0;31m         \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0madapter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    644\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    645\u001b[0m         \u001b[0;31m# Total elapsed time of the request (approximately)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/requests/adapters.py\u001b[0m in \u001b[0;36msend\u001b[0;34m(self, request, stream, timeout, verify, cert, proxies)\u001b[0m\n\u001b[1;32m    447\u001b[0m                     \u001b[0mdecode_content\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    448\u001b[0m                     \u001b[0mretries\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmax_retries\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m                     \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    450\u001b[0m                 )\n\u001b[1;32m    451\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36murlopen\u001b[0;34m(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, **response_kw)\u001b[0m\n\u001b[1;32m    675\u001b[0m                 \u001b[0mbody\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    676\u001b[0m                 \u001b[0mheaders\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 677\u001b[0;31m                 \u001b[0mchunked\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mchunked\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    678\u001b[0m             )\n\u001b[1;32m    679\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    424\u001b[0m                     \u001b[0;31m# Python 3 (including for exceptions like SystemExit).\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    425\u001b[0m                     \u001b[0;31m# Otherwise it looks like a bug in the code.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 426\u001b[0;31m                     \u001b[0msix\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_from\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    427\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mSocketTimeout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mBaseSSLError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mSocketError\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    428\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_raise_timeout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0murl\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout_value\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mread_timeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/urllib3/packages/six.py\u001b[0m in \u001b[0;36mraise_from\u001b[0;34m(value, from_value)\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/urllib3/connectionpool.py\u001b[0m in \u001b[0;36m_make_request\u001b[0;34m(self, conn, method, url, timeout, chunked, **httplib_request_kw)\u001b[0m\n\u001b[1;32m    419\u001b[0m                 \u001b[0;31m# Python 3\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    420\u001b[0m                 \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 421\u001b[0;31m                     \u001b[0mhttplib_response\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconn\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetresponse\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    422\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    423\u001b[0m                     \u001b[0;31m# Remove the TypeError from the exception chain in\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/http/client.py\u001b[0m in \u001b[0;36mgetresponse\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1352\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1353\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1354\u001b[0;31m                 \u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbegin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1355\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mConnectionError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1356\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/http/client.py\u001b[0m in \u001b[0;36mbegin\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    305\u001b[0m         \u001b[0;31m# read until we get a non-100 response\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    306\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 307\u001b[0;31m             \u001b[0mversion\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstatus\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreason\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_read_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    308\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mstatus\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mCONTINUE\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    309\u001b[0m                 \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/http/client.py\u001b[0m in \u001b[0;36m_read_status\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    266\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    267\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_read_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 268\u001b[0;31m         \u001b[0mline\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreadline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_MAXLINE\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"iso-8859-1\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    269\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mline\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0m_MAXLINE\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    270\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mLineTooLong\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"status line\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/socket.py\u001b[0m in \u001b[0;36mreadinto\u001b[0;34m(self, b)\u001b[0m\n\u001b[1;32m    584\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    585\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 586\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    587\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    588\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_timeout_occurred\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/ssl.py\u001b[0m in \u001b[0;36mrecv_into\u001b[0;34m(self, buffer, nbytes, flags)\u001b[0m\n\u001b[1;32m   1010\u001b[0m                   \u001b[0;34m\"non-zero flags not allowed in calls to recv_into() on %s\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1011\u001b[0m                   self.__class__)\n\u001b[0;32m-> 1012\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1013\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1014\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0msocket\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv_into\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/ssl.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m    872\u001b[0m             \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Read on closed or unwrapped SSL socket.\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    873\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 874\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    875\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mSSLError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    876\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mSSL_ERROR_EOF\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msuppress_ragged_eofs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/herschelhelp_internal/lib/python3.6/ssl.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m    629\u001b[0m         \"\"\"\n\u001b[1;32m    630\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mbuffer\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 631\u001b[0;31m             \u001b[0mv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    632\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    633\u001b[0m             \u001b[0mv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#No index on flux columns makes full searches very slow\n",
    "#job = service.submit_job(full_query, maxrec=50000) #,uploads = {'t1': master_catalogue}\n",
    "job = service.submit_job(cross_query,uploads = {'t1': master_catalogue})\n",
    "start_time = time.time()\n",
    "job.run()\n",
    "job_url = job.url\n",
    "job.wait(phases='COMPLETED')\n",
    "print('Job {} running after {} seconds.'.format(job.phase, round(time.time() - start_time)))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'COMPLETED'"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "job.phase"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: W27: None:2:1109: W27: COOSYS deprecated in VOTable 1.2 [astropy.io.votable.tree]\n",
      "WARNING:astropy:W27: None:2:1109: W27: COOSYS deprecated in VOTable 1.2\n",
      "WARNING: W06: None:2:2421: W06: Invalid UCD 'phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz' [astropy.io.votable.tree]\n",
      "WARNING:astropy:W06: None:2:2421: W06: Invalid UCD 'phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz'\n",
      "WARNING: W06: None:2:2692: W06: Invalid UCD 'stat.error;phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz' [astropy.io.votable.tree]\n",
      "WARNING:astropy:W06: None:2:2692: W06: Invalid UCD 'stat.error;phot.flux;em.IR.400-750GHz': Unknown word 'em.IR.400-750GHz'\n",
      "WARNING: AstropyDeprecationWarning: Using the table property is deprecated. Please use se to_table() instead. [pyvo.dal.query]\n",
      "WARNING:astropy:AstropyDeprecationWarning: Using the table property is deprecated. Please use se to_table() instead.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Converting column help_id type from object to string\n"
     ]
    }
   ],
   "source": [
    "result = job.fetch_result()\n",
    "help_cross = clean_table(result.table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "813"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(help_cross)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "483"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(help_cross['f_spire_500']/ help_cross['ferr_spire_500']> 2.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "for c in help_cross.colnames:\n",
    "    help_cross[c].name = 'help_' + c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=5</i>\n",
       "<table id=\"table4809435792\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>help_help_id</th><th>help_ra</th><th>help_dec</th><th>help_f_spire_500</th><th>help_ferr_spire_500</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>deg</th><th>uJy</th><th>uJy</th></tr></thead>\n",
       "<thead><tr><th>str27</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>HELP_J105113.293+571426.581</td><td>162.805388495703</td><td>57.2407168068532</td><td>64519.34</td><td>3462.4805</td></tr>\n",
       "<tr><td>HELP_J104903.996+562747.847</td><td>162.266649012298</td><td>56.4632909082802</td><td>52667.715</td><td>5448.2188</td></tr>\n",
       "<tr><td>HELP_J104904.471+562744.554</td><td>162.268627360024</td><td>56.4623761157497</td><td>4000.137</td><td>6147.4854</td></tr>\n",
       "<tr><td>HELP_J160549.034+551620.943</td><td>241.454307653057</td><td>55.2724841364993</td><td>71144.78</td><td>1803.28</td></tr>\n",
       "<tr><td>HELP_J161615.412+543721.745</td><td>244.064217138057</td><td>54.6227069154993</td><td>53578.842</td><td>4331.73</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "        help_help_id            help_ra      ... help_ferr_spire_500\n",
       "                                  deg        ...         uJy        \n",
       "           str27                float64      ...       float64      \n",
       "--------------------------- ---------------- ... -------------------\n",
       "HELP_J105113.293+571426.581 162.805388495703 ...           3462.4805\n",
       "HELP_J104903.996+562747.847 162.266649012298 ...           5448.2188\n",
       "HELP_J104904.471+562744.554 162.268627360024 ...           6147.4854\n",
       "HELP_J160549.034+551620.943 241.454307653057 ...             1803.28\n",
       "HELP_J161615.412+543721.745 244.064217138057 ...             4331.73"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "help_cross[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n",
      "/Users/rs548/GitHub/herschelhelp_internal/herschelhelp_internal/masterlist.py:392: StringTruncateWarning: truncated right side string(s) longer than 1 character(s) during assignment\n",
      "  merged_catalogue[colname][merged_catalogue[colname].mask] = False\n"
     ]
    }
   ],
   "source": [
    "master_catalogue['ra'] = master_catalogue['blind_ra']\n",
    "master_catalogue['dec'] = master_catalogue['blind_dec']\n",
    "master_catalogue = merge_catalogues(master_catalogue, help_cross, \"help_ra\", \"help_dec\", radius=match_dist)\n",
    "master_catalogue = clean_table(master_catalogue)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "master_catalogue['help_f_spire_500'].convert_unit_to(u.mJy)\n",
    "master_catalogue['help_ferr_spire_500'].convert_unit_to(u.mJy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## compare sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "master_catalogue['blind_F_SPIRE_500'][master_catalogue['blind_F_SPIRE_500'] > 1E10] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.488e+03, 2.710e+02, 1.200e+02, 6.900e+01, 4.700e+01, 3.500e+01,\n",
       "        2.100e+01, 1.600e+01, 1.200e+01, 4.000e+00, 6.000e+00, 2.000e+00,\n",
       "        2.000e+00, 3.000e+00, 2.000e+00, 2.000e+00, 1.000e+00, 2.000e+00,\n",
       "        0.000e+00, 0.000e+00, 2.000e+00, 0.000e+00, 1.000e+00, 1.000e+00,\n",
       "        0.000e+00, 1.000e+00, 1.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        1.000e+00, 1.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 1.000e+00,\n",
       "        2.000e+00, 1.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        1.000e+00, 1.000e+00]),\n",
       " array([  70.001854,   99.27207 ,  128.54228 ,  157.8125  ,  187.08272 ,\n",
       "         216.35292 ,  245.62314 ,  274.89334 ,  304.16357 ,  333.43378 ,\n",
       "         362.704   ,  391.9742  ,  421.24442 ,  450.51465 ,  479.78485 ,\n",
       "         509.05508 ,  538.32526 ,  567.5955  ,  596.8657  ,  626.1359  ,\n",
       "         655.4061  ,  684.67633 ,  713.9466  ,  743.2168  ,  772.487   ,\n",
       "         801.7572  ,  831.0274  ,  860.29767 ,  889.5679  ,  918.8381  ,\n",
       "         948.1083  ,  977.3785  , 1006.64874 , 1035.919   , 1065.1891  ,\n",
       "        1094.4594  , 1123.7296  , 1152.9998  , 1182.27    , 1211.5402  ,\n",
       "        1240.8104  , 1270.0807  , 1299.3508  , 1328.6211  , 1357.8912  ,\n",
       "        1387.1615  , 1416.4318  , 1445.7019  , 1474.9722  , 1504.2423  ,\n",
       "        1533.5126  ], dtype=float32),\n",
       " <a list of 50 Patch objects>)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(master_catalogue['blind_F_SPIRE_500'], bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([3.862e+03, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 3.000e+00, 2.000e+00, 0.000e+00, 1.000e+00,\n",
       "        2.000e+00, 4.000e+00]),\n",
       " array([7.01000000e+01, 3.02949800e+03, 5.98889600e+03, 8.94829400e+03,\n",
       "        1.19076920e+04, 1.48670900e+04, 1.78264880e+04, 2.07858860e+04,\n",
       "        2.37452840e+04, 2.67046820e+04, 2.96640800e+04, 3.26234780e+04,\n",
       "        3.55828760e+04, 3.85422740e+04, 4.15016720e+04, 4.44610700e+04,\n",
       "        4.74204680e+04, 5.03798660e+04, 5.33392640e+04, 5.62986620e+04,\n",
       "        5.92580600e+04, 6.22174580e+04, 6.51768560e+04, 6.81362540e+04,\n",
       "        7.10956520e+04, 7.40550500e+04, 7.70144480e+04, 7.99738460e+04,\n",
       "        8.29332440e+04, 8.58926420e+04, 8.88520400e+04, 9.18114380e+04,\n",
       "        9.47708360e+04, 9.77302340e+04, 1.00689632e+05, 1.03649030e+05,\n",
       "        1.06608428e+05, 1.09567826e+05, 1.12527224e+05, 1.15486622e+05,\n",
       "        1.18446020e+05, 1.21405418e+05, 1.24364816e+05, 1.27324214e+05,\n",
       "        1.30283612e+05, 1.33243010e+05, 1.36202408e+05, 1.39161806e+05,\n",
       "        1.42121204e+05, 1.45080602e+05, 1.48040000e+05]),\n",
       " <a list of 50 Patch objects>)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(master_catalogue['esa_fluxsus'], bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([189., 112.,  83., 105., 122.,  82.,  46.,  15.,  15.,   7.,   7.,\n",
       "         12.,   2.,   2.,   3.,   1.,   1.,   1.,   2.,   0.,   1.,   0.,\n",
       "          1.,   0.,   0.,   1.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "          1.,   1.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "          0.,   0.,   0.,   0.,   0.,   1.]),\n",
       " array([  1336.6826  ,  16365.676948,  31394.671296,  46423.665644,\n",
       "         61452.659992,  76481.65434 ,  91510.648688, 106539.643036,\n",
       "        121568.637384, 136597.631732, 151626.62608 , 166655.620428,\n",
       "        181684.614776, 196713.609124, 211742.603472, 226771.59782 ,\n",
       "        241800.592168, 256829.586516, 271858.580864, 286887.575212,\n",
       "        301916.56956 , 316945.563908, 331974.558256, 347003.552604,\n",
       "        362032.546952, 377061.5413  , 392090.535648, 407119.529996,\n",
       "        422148.524344, 437177.518692, 452206.51304 , 467235.507388,\n",
       "        482264.501736, 497293.496084, 512322.490432, 527351.48478 ,\n",
       "        542380.479128, 557409.473476, 572438.467824, 587467.462172,\n",
       "        602496.45652 , 617525.450868, 632554.445216, 647583.439564,\n",
       "        662612.433912, 677641.42826 , 692670.422608, 707699.416956,\n",
       "        722728.411304, 737757.405652, 752786.4     ]),\n",
       " <a list of 50 Patch objects>)"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(master_catalogue['help_f_spire_500'], bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'ESA blind 500 [mJy]')"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 560x560 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = (master_catalogue['blind_F_SPIRE_500'] > 0) & (master_catalogue['esa_fluxsus'] > 0)\n",
    "plt.figure(1, figsize=(4, 4), dpi=140)\n",
    "plt.scatter(master_catalogue['blind_F_SPIRE_500'][m], master_catalogue['esa_fluxsus'][m], s=0.2)\n",
    "plt.plot([50,2000],[50,2000])\n",
    "plt.xscale('log')\n",
    "plt.yscale('log')\n",
    "plt.xlim([45,2000])\n",
    "plt.ylim([45,2000])\n",
    "plt.xlabel('HELP blind 500 [mJy]')\n",
    "plt.ylabel('ESA blind 500 [mJy]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'HELP XID+ 500 [mJy]')"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 560x560 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = (master_catalogue['blind_F_SPIRE_500'] > 0) & (master_catalogue['help_f_spire_500'] > 0)\n",
    "plt.figure(1, figsize=(4, 4), dpi=140)\n",
    "plt.scatter(master_catalogue['blind_F_SPIRE_500'][m], master_catalogue['help_f_spire_500'][m], s=0.2)\n",
    "plt.plot([50,2000],[50,2000])\n",
    "plt.xscale('log')\n",
    "plt.yscale('log')\n",
    "#plt.xlim([45,2000])\n",
    "#plt.ylim([45,2000])\n",
    "plt.xlabel('HELP blind 500 [mJy]')\n",
    "plt.ylabel('HELP XID+ 500 [mJy]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[661, 2418, 1456]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[np.sum((master_catalogue['blind_F_SPIRE_500'] > 0) &  ~(master_catalogue['esa_fluxsus'] > 0)), #HELP only\n",
    "    np.sum(~(master_catalogue['blind_F_SPIRE_500'] > 0) &  (master_catalogue['esa_fluxsus'] > 0)),     #ESA only\n",
    "    np.sum(np.sum((master_catalogue['blind_F_SPIRE_500'] > 0) &  (master_catalogue['esa_fluxsus'] > 0)))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2418"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(~(master_catalogue['blind_F_SPIRE_500'] > 0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib_venn._common.VennDiagram at 0x11e359748>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cxjQCV7ouoxgOzaW3t057bYbRZQlqbujU+U4pmHrgAtdFFEu4g9MYgzdfMxT98zsuCvnfO+Q+0kZ5nbpspXAucV1AsYT9QLocmO66iGI4Po0+zdsMt9oM0f91RAOFpGCmmLiZ7bqIYghvcBozCbjCdRnFsj10A8ZlJFf0UH2dpqhI4YSi1RnO4PS6aFcT4MXbh+quJ3liGlWu65DS8KdHKdcoWymQWSZuprguotDCGZzeu6Jprosolp0XkXJdg5SOugzRPz+qUbZSMIFvdYYvOI1pIgRL6g1KRckcblVrU852dTc1V6nLVgrjAhM39a6LKKRwBeeZUbShed57FtOX0X6bMoI/U5etFIYBlrouopDCdkBdRMC3Chtu38JwTLWR3NVniH74mLpspSAWB3lBhPAEpzERQtRFC3BiCv19tVrwQM7txk6qZyS18bXkXQ0Q2Kkp4QlOuIgQrEU71J7F6oaT84uA+dAxBacURGDXrw1HcBpTAaxwXUYxpSJk2mZpwQMZ3eU91CzoU5et5N1cEzeBPAaFIzi90AzVyNLDc+nLRMMxT1Um7kNtZFzXIIETARa6LqIQgh+cxtQAr3NdRrHtWxSCv63kzbI+qpcn6HNdhwROILtrw3BwvZyQLOI+qKeWgdNN4Wphy8R9qM11BRJAU0zcNLkuIt+CHZzeerSBfMdzPvsWaSFvyd28JFXXaFEEyb/FrgvIt2AHp7fPZmDnEp3LkTmUu65B/Om/H9N5ccm7RSZuApU1gXoyZzFmKjDPdRnF1l1PUptVy3i1pKi49RQJ13VIoFQTsDmdwQ1OuNh1AS4cnK85eTIx7+4I15gAKYq5rgvIp2AGpzG1wHzXZbigblqZqCkpKi7t0QhbyatW1wXkUzCD01slKKjP7ZwSNQz0NKibVibuzhOa1yl5VWviptl1EfkSvHAxJkrAV+Y/l0Pz1E0r+XFxguqmlPZxlbwKTHdt8ILT2wElkMs8jeZIayD/nuJABMxbT2gZPsmrwHTXBvFAu8x1AS4kK0h3TgrnGwYpjFtPU2ks1nUdEhhTTdxUuy4iH4IVnN4UlMD0o+eifQZJTPjmrErh1GeIXt+lQUKSNwaY47qIfAhWcIb03CZA20y1DCT/3nbSdQUSMIE4zxmc4DSmHFjgugxXOlo0DUXyb3GfNrqWvJodhFWEfP8EhlgI4QyPRA0D/dXhfO5SeHed0NrHkjflwAzXRUxU0IIzlNpma9qAFM71nVRFNEhI8meW6wImKhjBaUwlMN11Ga4c8/37NyllNZbI8oRanZI301wXMFHBCE5vflBoR5SenKJuWimsG7rUqyF5M83Eja+P10EJzkCM1BqP7nqSqQotyi2FtbJbb84kb6KArze39n9wGlNGQOYGjUfHNNKua5Dga05TMadf3bWSNy2uC5gI/wcnzCSko2kBTk7VoA0pjhu7NC1F8sbX5zmDEJzzXBfg0qkmIq5rkHC4ukuvNckbtTgdC+35zYzB9tSHt7UtxdWapLIhpVMDkheNJm58u7a2v4PTmClAresyXDndRNKW+fxvKL5RBuaabu2YInnj21an3w+6oW1tggYGSfFd1+W6AgkQ357nVHD62MkpriuQsFnWS6VWEZI8UYuz6LxF3UO5hdigrkYN1pDiqrRElvSqu1bywrdzOf0bnF5o+nr1iYnqrdHAICm+Jb1kXNcggVBt4qbCdRHj4efgDHVHZaKGlI34+u8nPrVEW1tL/jS6LmA8/Hzgneq6AJe6Jmkyurgxv09LPEreKDiLLNTB2TlJAzTEjakpyisz6q6VvGhwXcB4+DM4vYFBvnynki9doX724lIZmAv61OMheTHJdQHj4c/g1MAguht8+7eTAFjSpznEkhdqcRZRqLtpARJ1Os8k7iztdV2BBIQv+878GpyhHlGbMVjtwSkuze/XHGLJi0oTN1Wui8iVX4Mz1C3OvmpSrmuQcJs6QEW5BghJfviu1em/4NTAIHprdX5J3IqAuaBfA4QkL3x3PPdfcEI9IR8Y1Furd/riXmu/3sBJXvhuhys/BmeN6wJc6w39b0BKwZSU5hJLXvhuX04Fpw/11uqAJe5NSYW750fyRoODikDBWaMDlrg3RWc4JT/U4iyC0Adnf5Uv/24SMJPSeh1KXig4i8B3J5LzLVWhFqe415jy5fFDSo+6aosg9C3OtLYTkxJQn9EiHJIXanEWgYJTwSkloMJSVqVFEGTiFJxFoOCMqqtWSkPzgFaxkgkrM3FT4bqIXPirq8WYSsjPGpmfhBU/gdVHoDUFFbXQ2Qq7vw4/vRFODr3to9D8V/DGV2FZDzRUQu9UOPwOeOLL8Pzg7Y5CxZ/Cqu3QehBaT0ILYB6DT98CHfmoO2OwtsyXb3jG5ZsbuGrHCRa1J2g93ccsC9E3LOB7f3olz4z2sy8eoTn+BLG0pXJxM09+6Tb+bej3Nx6l+TO/5fPn+vm3LOZfPrSS50b63v1bWfzoLm5pT3DBQJrqyihdzdXse9dFPPj6+RzM/Zn605QUmUO+ay+MYD+TWM9KDvE6EkxngEai9NDILq7iEa5gz3l/fhfN/BsxMlQyiyf54NmvNbqp4Fes4jitdNJKn3ds4H18mgvOc2x4mgt5jtvoYRYD1FHBKRrZw3U8wiWBep1VAknXRYyVv4IzD63NNHANvGcD3NAI7ZfChhro64BJu2Hxi9A8NDj/FpbeA/8TYAm81ALt3VBzEGavhaUMCc5XoP6ncBdAPXRUQqI/z4OZUuVkyNObBz/47V7e2puiuSJCd1WU070pmsfycxkL//gsd4/lto2VHFzYxMbh1y+ZwuGRbv/ZJ7hjw2HeVhXh1NxGNtaU092dpKGthwXbjjMrbMHpuoa8+C2vZw+3U0k7zWylii66mMZxVvBLVtDBv3D7mf/1s2SAB0Z5rR2jni3esYEKOoiQID3KseE+Xs8r/FciJJjGi9maWmhnJT9nJZ38IzewbTxPtwRVAl2uixgrvwXnhN/bvgdu2gA3XANrHocfV3H2YgKJId3XT8Lkz8L/qINTP4N/WA0nznVbgAuh+3PwlbfDvqWQWAAf2w0XTbTmoVLRcAXnXcv4wZIpHLu4hROfe5Lb1x/izrH83N+v46aOBAuum8NP1x7gD8532+YaDtyzmgfHcr8/2MTFGw7ztln1bPzft/Cdxqqz12vtD9lI04agLLo3g70s5otcw86zrn+GhTzK/2IDf8gqNjHSBgv3cxOdLGApP2XLOV5rzXRzE19hKfuYSoKv8jFOnufY0E+ErbyVCL28l88yb0gv2GOs4Gn+hOd4Y4CC01ddtX77J59Qvceg/Gfw5kZo/0/4j+GhCVDDmXfQn4Q7klD9l/DD1cNCc/htAeZA/1/B1qWQmEid55MqD9eqQX9wEdsubnnt7/58Nhxm6roD3HlJC48uauZAPuv59U7eHi2jL7aK7w0PTYDKaEBaYGMUDcqr8TZefE1oAlzDThp5lTS1bGXWa76/nals4U7m8yizzvNaa6SfG9nK1DEeG45TS5pqajh0VmgC3MDLgCVJ/Zjuyx98NW7Dby3OCQXnV2BpP9ReBev6oSwGl+yAlgZIvAu2vgnaB2+bBjbC5VXQ/Sl49V+h9WFYnAGzEg78BbxaPkLwFlomNG3N8UllMF9/lrury+n41PU89OguLhjtZ3qSNH75GVYlBqieXMXp1fPZetFUTg2/3Zq9zOpOMmN2Ay8219D3o5e5aM9JZldESV4+gx1h6qIdFAlKcJ5PWXYx+8iwRe3TGB7ibirp4J08xAujv9bGbAadROkmwSz2M4nWIa/HtbwOMEwJTGsTFJwFNaFf7gswDyACmQXwmZMwffB7PwR7I/znGrgP4D9hSj/UToe9V8O718OqwdveD3wV9t8HX7+B1x5gCywMh6px+/t13NzRy4IPr+QLdRVjG/HZ1sOyth6WDX79yC7Sy6by+Odu4qfRsjO/75fbmAtQHaX7gw/yyRO9Zw6UT+6D+7ex/u9u5vu1FeHZNSQS9NfjXpo4yVLKOc1FHDrrez/lZjpZwBv5wohduBNRBqzk33mWD/B9/poWXqSSbrqYRgcXM4UXeTu/yOtjuuWr3k+/BeeEfrknvS3JWAO3tsD+b8Pnb4ej98Gcz8F7n4Bb3wvt/wee2JW9bRu0dsCMD8L3PgGbDkD1p+GODXDDu+DDh+Hv8vC8xixT5q93ZsW0/iDTnjnIWy+aym/etJjdo92+vpLkyhk8tGouL140jfaeJOVr93PBr3by9s3t3HrPGtKfu4mfDd7+dD8NADtPcF1NOcfvXsGXV81l76ajTPvBS7x77ymu+vxTnPrbm7m/kM+zlERsgF+P/US4nw9giXIJPyU65E3Cq0xjG29lLr/hytFfa+NyB89RRzdP8Mcc5vrfX1/NEZawjsn0FeRx3fDV68hXKc8Ef7k2+/MRSN0P3/gg7JsD/X8OO78J3zJgH4RbAdLZ21oouxN+8W145kJI3AIdz8IPZ8CeIzD/q7Bw4k8r16chw6UymG88x/uropz+1HVjeye+YDJd96z2po9Mq6V//mS633sJL312NV8uL6P7pTZuOdh5ZiS3PfOaMB+8jG+/YymvTqmh/+YLOPDXq/hGtIy+ze28vjvpuzek4xaxAX09pjF8lz+ik0XM5CnezPqzvvcQ76ec07yzgK2+B7iWx/koM3mW9/BX/AV/yp38DVWcYC0f4T5uKthjF5+Cs1TVQi/AdNh3DZwe+r0/gCON0H4apu6A6pbsbQE+AJuG39fK7HXr8LrvxK0vPcNNJ3qZ/66L+MHk6onNB1vUTOfsBl6xEH16v9e9D1Ad9V4TVVFO3nzB2QNBFkymq6maPWlLxbOHzpwCEB/KAN/hvbRxFS2s578Pm5N5PzfRxXxu5AfUFWju4TZaeJH30MzLfID/n4Ucp5YBLuEgH+QbVNDBFt7Gaf+tuhMEfntnPKERi/OhbQ1QPSQUh6rKXn8CKm6FduNNByxrHWGUbEP2tn1QPpGacmWC+f5+wg53MQcw927kE/e+ZkYmbO/gxrf8OzfOqmfjt97MN0e7v5pyugF6U2eGybc2chSgIjLy66cy4r1Oegf8NbR+IlK+aieMQRrDd3gfR7iWaTzLB7mXyLBWdYf3WuMxPsFjI9zHIW7kHm6kmY18dPTX2oheYRmWCNN59TXfqyHFJHZxjCvZxXQuY9+4HqO0+Go0eqiC853w6r1AO69tEXRB5CRMjUL/cuiqgcws2HUQFj0KM5dy9lD13TADYG6eVgQaKwXnyBY2sb3MvHZQTk+SxiPdLK+r4Oj0OnbOqh/b9JSj3V5Ls7WR44PX3TSfPf/2MsmeJFM6+4k2VJ49IORUn/eaWNhU3NeES4EKzrND8zk+xHfPOq85aCbbfz/Sdqg+GjnBcqo5ymR2MpGpUIML6PeeY8rJ4FSU8sAseeirI5vfgnNCv9w7oH0+bNkDyz4A138X1g5+77/B7f1QcwmsH5yfeSc88U+w6CvwlvfBP03Ge5H+DKY/B9eWQ99HYPPEnlKOfPXyKp6PXsk6YN3w6+/fyuJ7N7J8Zj3bhy+59/BO5q2ay4Hq8rMPgn+3lls6ellYX8GR1fPOTDGZUkP/gsms33GCG764jjf9zevPnN/6xgau6koys7manRdOOfs0QJCljb/OTZ3T0NCcyvN8kH8dMTQB/svIrzWeZjGPsZwmtr9myb1czWcnW4D93MA+nmTuWdNRLuQUF1JOJ0tHXt3Kh3x1ZPNbcE64Of91+NE74FP3wnufghWz4OhemLMPltRDx79kp6MA/ANs+A1cugVWLoDPLIMtCah+BS5LQ/mfwHcvHNaNuxru6oQ6gDa8CdMfg7uqoB/gM/DwnXhdfuMRTQXkQDVGX13P9btPegOwTvR6v8/nDnP9nz3MhQCXTmfj3Steu1zeWPzHZt7xnReY3lLH9oZKTg6kKT/azQWn+2ktLyPxgUv5btmw3/bHr+Znn3yMxRuP8sb3/4KF0+vYd7KXaYe6uLi8jMQfX8YPJ/aM/SUw827+nTdzhGspo5962vgP3vSa2yznxQmtD3svd9HvHRvozi6m8CvuIuodG1jFwyzNHhuuYA/PsZ42ruL7xLNL7nXSRQsdXALASkd+3HEAABoASURBVH58znD3H3XVFtCE/0/vgPaH4W8/Dv/lVbhoNyyrgdPXwJqvw0OXDlkvMQJsgO/cDbseh+t/BzdGYGA27PoI/OoTsGP4/b8Al3Vx9nqqW+Gywc93eu9UJxKcoRrQtfskC3ef5Jqh13X0srCj1wvTyVV0wPiCc8V01r9yjMuO9bDgYKd3QKspp2PZVH7zvkt4dKRFEFob6fnirfzdPz3LW/acYsXmYyyoiNAzfxLr717Bg5fNONO1GwbJoLwau7P/sxkq2c0bR7xNI8cnFJxHuIzksLWWj585NnBi2LHhQ9zLg+xgF9dwjEvJUEGUHprZxJU8ylXsGnctpcdXwWms9dEbFmPqgHe7LsOlVITMw38QrvCU0vX/zaRvXT1VrusQ3/uJjdmTo9+sNPjtAFywNWD9IpqmjKDOnRPfadfesJIf/a4LyIW/gtPaDARqtYxxKUv7q1tDgqujPDw79UhB+eq47q/g9IS+1RlJq8Up7mXAnowoOGXCBmzM+qoxoOD0oYhanFICEmWkbVCmo4hLvuqmBQWnL0UH1OIU9zqHb7MlMj6+6qYFBacvlSfV4hT3TkX0OpS8UIuzCEIfnFUJtTjFvZPBmXwvbik4iyD0wVmt4JQS0KHglPxQV20R9LguwLXqhC//bhIwx8s1MEjyQi3OIlBwhv43IKXgmIJT8kMtzoKzthsKtHmsT1T3aO6cuLe9yndrXUtp6nRdQK78F5yeUC2kPVx1QsEpbiUM6fby4m7iLoHlu234FJw+VJEkYrQIgjh0sDLcvT6SNxa1OIsm1MEJUNkXmJ3fxYd2VumNm+RFl9+W2wP/Bme76wJcq+vSqi3izpZq3x47pLT4rrUJfg1Oa08T8gFCdac1h07c2aaBQZIfr9ks3g/8GZyeUHfXNvjy5SZB0GdIt1VoYJDkhVqcRRb24NTIWnFifyUDrmuQwPDdiFrwd3CG+jxn3Wm94xc3dlbp/LrkjYKzyELd4oymKavo0zt/Kb5tVVoxSPIiA3S5LmI8/BucGiBETY+mpEjxvVKj3g7Ji04bs74c5Ojf4PQcdF2AS40nNJdOiutYlKRWDJI88e3pNr8H5z7XBbjU1O77v5/4zHN1Oj0gedPmuoDx8vuBdz+Et9XVdEzv/KW4nqzXaG7Jm2OuCxgvfwentf34+F3LRFX3Eo0mdZ5TiiNhSG+pptJ1HRIIKaDDdRHj5e/g9IS6u7bhpLrOpDheqqXfGo2olbxo9+vAIAhGcO51XYBLkzu09J4Ux1P1Ck3JG1/3FPo/OK3txKfrHeZD87EA/A2l5KUgs75O3bSSN749vwlBCE7PXtcFuDL5OOVYtTqlsHZW0d9fFpjjhbinFmcJCO15zvIBIrVdOs8phbWuXm/OJG+6bMz2ui5iIoISnMcAX/8hJmJKm4JTCmttvaY+Sd74urUJQQlOay0hbnW2HNLcOimcvRX0abUgySMFZwl51XUBrjS3UWEy4V0IQgrrgcl6bUle7XddwEQFJzitbQNOuC7DhUiGsoaT4V7wXgojYUivaaDKdR0SGCdtzPpyR5ShghOcnm2uC3Bl6lHtkSj5t6aRvgGNppX88X1rE4IXnNshnEvQtRzSOSjJrwzY+ydT4boOCZRAjEUJVnBamwR2uy7DhUkdlEcG1OqU/NleRV9bhd6QSd4EZm3xYAWn5xXXBbhgwEw9Qr/rOiQ4ftakJfYkrw74eX3aoYIXnNYeB466LsOF2Xt1oJP8OB1h4BktsSf5FYjzmxDE4PSEstU57TBVZSl118rEPdZIUjuhSB5lgAOui8iXoAbnHqDbdRHFVmYxU9o0LUUmJg32F5PV2pS8arMxG5hTScEMTm8loc2uy3Bh1l7XFYjfPV9L76koUdd1SKAEppsWghqcni1An+siiq3lEJUmrZVeZHzSYL8zTSNpJe/2uC4gn4IbnNYOAC+4LqPYomnKmto1ulbG56l6eo9oCork1xEbs52ui8in4AanZwvg++WdctUaypmsMlEDkLl3mhY8kLzb7rqAfAt2cFqbATa4LqPYZuynSoshSK4enUTfCZ3blPxKEcBFaYIdnADW7gQ6XJdRTGUWM+Ogumtl7PoM6R9M0UhaybvdNmYDt19w8IPTs951AcU2f5taDjJ2P2+iLxHRvq6Sd4Hc7jEcwWntQeCQ6zKKqfEUFTVdanXK6LrLSN3XRLXrOiRwOm3MHnFdRCGEIzg9z7ouoNhad+k8p4zux80k+7V1mORf4AYFDQrPP4u17QTwJPX5tO6i0mQ0p1PO7WSEgYcmq7UpBaHgDIhnITxBUpEkMqUtfItAyNj9cwuptNaklfw7ZGM2sMuehis4re0ENrouo5gWbAnZ31jG7LlaEk/Xq7UpBRHIQUGDwnhQfYEQTU+ZcowqDRKS4XrKSH1phqafSEF0E/DTYuELTm9RhDWEqMv2gm0aJCRn+2YLA92afiKF8bKN2UAfX8MXnADWdhCidWzn7KYqmiTlug4pDS/U0PtEg7popSD6gW2uiyi0cAanZyNw3HURxRDJUNa6S/t0CiQM6S/N0Hq0UjBbgrhS0HDhDU6vy/a3EI5uzIVbtN2YwLda6O+MqotWCiINvOK6iGIIb3ACWHsSeN51GcVQkSQy84CmpoTZphp6f9tIjes6JLC225jtdV1EMYQ7OD2bgGOuiyiGCzdRTgbrug4pvoQh/fcztM+mFIzFO5aGgoLTWos3yjbwXbY1CcpnHCAU7wjlbN9qof+UtgyTwtkbtM2qz0fBCWDtKeAZ12UUw9KNanWGzcON9KiLVgosNK1NUHCeYe0WYIvrMgqtJkH5zP1qdYbFtip6v9Gi0JSCOmxjNhSnuwYpOM+2DjjsuohCW7qRCi3+HnwdEZKx2VRYrUUrhRW6nacUnEN5U1QeAwLdV1/dS3TmPo2wDbJ+Q/ozc0CbU0uB7Q5baxMUnK9lbT/wCAR7wYClm9TqDKoM2C/NIHmgUgsdSEFlCGFrExScI/Pmdz4OwR1EU9VLdM5unesMovubSDyjXU+k8DaHaSTtUArOc7F2P7DedRmFtHSj1rANmhdrSHx/KrWu65DASxKi9b6HU3Cej7UvEeBdzMsHiFz4crC7pMPkaDn9fzuLKtd1SCi8YGM2tNsVKjhH9yTQ5rqIQpm3neqabu3X6XenIwx8eg5l/WX6n5aC6wI2uy7CJf2TjcYbafsIcMJ1KYVgwCzfENxzuWHQXUbqL1qhvVxL6klRbLAxG/iV1s5HwTkW1vYBvwROuS6lEKYepar5qAYK+VHCkP7LVjJHKhSaUhTtNmZ3ui7CNQXnWFnbCzwEnHZdSiFcvIGopqf4S78h/elWUvs07USKJxRLk45GwZkLaxN44Rm4Idi13ZTP3aFWp1/0G9KfmU1qVxWVrmuR0NhmY/ao6yJKgYIzV9b2AA8SwJbnshepqUpolG2p6zOk/985pLbWKDSlaHoJ+PS8XCg4x8MLzwcI2IChMou5dB0ZrAYLlarsOc3UjmqFphTVujBPPxlOwTle3jnPB4HjrkvJp+Z2qmbtU5dtKeopI/WXraTVPStFtt/G7C7XRZQSBedEeOvaPkTA5nku30BVRR8DruuQMzoiJD/RSmZPlQYCSVElgbWuiyg1Cs6JsjaJN1UlMO/IoinKlm/QUnylYnsVvf9zPpFDGj0rxfc7G7PdrosoNQrOfLA2hbW/wdspIBDnB2ccpHrqYRKu6wi7xxtIfLKVKm0PJg4ctDG7zXURpUjBmU/WbgQeJiBbkl36DJXl/Wp5upAG+52pJP5hBjVpbUQtxZcEnnBdRKlScOabtQeAnxGAVYYqkkQue5qURtkWV58hHZ9N/y+aqHFdi4TWMzZme1wXUaoUnIVg7Wng58B+16VM1NQ2qubtUJdtsRyPkvzYPDIv1mqXE3Fmt43ZV10XUcoUnIXiDRp6BHjRdSkTtewFaupOaweVQttWRe9H5hHRurPi0GnURTsqBWchWWuxdgPwn+Dfc4VlFnPFE5SVpQj1jgiFkgb7wCR6NAhIHEsBj9mY1VS0URhrdfqqKIyZDKwCprkuZbz2LaD35Supdl1HkByLkvzCTOyrWglI3HtCXbRjo+AsJmMMsBy4AvzZsthwA4m22Rq0MlEZsI82kvj2NKoHtPm0uLfdxuwa10X4hf5hi8nrun0JuA/w5S4Dlz1NVW2nzndOREeE5Kfn0P/16dQqNKUEnECrA+VELU5XvNbnRcCVQNRxNTlJ1DDw5B2YVIW/6i4Fv2kg8c0WqvoVmFIaBoCf2Zj1/fS5YlJwumZMA3AjMNN1Kblob6Fv/WoqKdPk/LE4FWHgyzNIa5qJlJjfaAH33Ck4S4Uxy4CrwD9TEXYuJbFthc53nk8a7JMN9H6jhao+tTKltGyxMasu2nFQV1upsHYLxuzH67pd6LqcsVi4lZpTzSSOzlF4jmRTDb3/PI3ogUr9fqTkHATWuS7Cr9TiLEXGNOEFaKvrUkaTLiPz1O0MdDdqOsWgvRX0fasFNteoW1ZKUgfwgOZrjp+Cs5QZ04IXoDNcl3I+/ZWkn7yDTH+1f7qZC+F4lOR3ppF+ul5zXaVkdQM/tzGrZTQnQMHpB8bMxpv7OdV1KefSU8fAU28I50jb7jJSP5pC8qFJVFvtZCKlKwn8wsbsSdeF+J2C00+MmY8XoJNclzKSk830r7uZchsJxyCYfkP6wcn0/biZak0vkRKXAX5pY/aI60KCQMHpN978z0XACkowQI/Mpvf566gK8jSVY1GSD00m9etJGikrvqFpJ3mk4PQzY2YBr8MbRFQyQbVnMYnNK4M1kjQDdnM1ffc1YV6o06Af8ZX1NmY3uS4iSBScQWBMPbAMuBBK46C+ZQU9u5dS67qOiUoY0msa6buviYr28nAPfhJf2mxj9mnXRQRN6AZyBJK1XcB6jHkOmAssAWbhsBW6bCO16Sg9+xb5MzwPl9P/i8lkHmukcqDMn89BQm8nmqtZEGpxBpUxdcDi7KXBVRkvXUHP/oX+CJ7jUZLP1jHweANRbfMlPrcdb5swHeALQMEZBt5eoK3ZSwtF3hVn05X0HFhQmuF5oIL+Z+pIrWmg/EAlFa7rEcmDbcBTCs3CUXCGjTEVwBy8EJ1Dkc6JbryKnoMXuA/PNNhdVfStrcc+VU/F8XKdrpBA2Wpj9inXRQSdgjPMvKkt0zjTGm0u5MNtvJrEwfnFHW2bAdseJbW7ioENtfB0PZWJiD83ERcZhQYCFYmCU84wpgqYgheggx8byeMgo0K3PE9HGNhdycC2athcTdmr1VRorqWEwMs2Zp9xXURYKDjl/IyJAk2cCdLm7Nfj7uLMx1SVNNjOCOm2cga2V5F5pYayrdWUn4qq61VC5yUbs79zXUSYKDgld14XbwNQDdRkP57rMuLcx/Pt5TkAmc4IqVNRMsej2OPl2LZyOFaOORalrL2c6KmoultFgI02Zp91XUTYKDilsLwWaxX8PugGu33Nuz5I89qpXDtgiAwYTNJgBgxmQF2rIqOxeCsCveS6kDBScIpTJm5mAreBpoKIjFEKb+3Zfa4LCSsFpzhn4qYJeCMEa31bkQLoAR6xMXvcdSFhpuCUkmDipg64A5jsuhaREnUceFibULun4JSSYeKmAlgNzHNbiUjJ2Qs8bmM25boQUXBKCTJxswJvw+6S2SpNxKGX8AYC6WBdIhScUpJM3MwGbqJEtkkTcSADrLUxu811IXI2BaeUrOx5z9vwFl8QCZMEXtfsYdeFyGspOKWkmbiJANfjbdItEgb7gTU2ZvtcFyIjU3CKL5i4WQpcR5G3RBMpogzwrBY1KH0KTvENEzfTgFvB/fZkInnWibeoQbvrQmR0Ck7xleyUleuARa5rEcmTnXgbTw+4LkTGRsEpvmTiZh5wA95C8iJ+lAKetjH7qutCJDcKTvEtEzdVeK3PBa5rEclRB17X7CnXhUjuFJzieyZuLsAbeas5n1LqUsALeHtoZlwXI+OjEYolyBizxhhjjTH3jOG2NntZPeS61UOuH+1yz7D7+172+u/lUO/3RrjfjDHmtDHmOWPMZ40xBZuLaWN2N/ATvGXJRErVQeA+G7MbFZr+FnVdgBTc06N8f38eH+sYsCP7eQSYC6zMXj5kjLnZWrs5j4/3ezZme4FHTdwsAq4FKgvxOCLj0As8Y2N2p+tCJD8UnAFnrb2+iA/3a2vt3UOvMMa8HvgRMB34N2PMpbaA5wdszO4wcXMQuBItmiDubcNbZ7bfdSGSPwpOKShr7W+NMR8HfgxcAlwMbCroY3qtzydM3GzGa31OL+TjiYzgFPCkjdmjrguR/NM5TimG3wz5fHGxHtTG7HEbsw9kH7+7WI8roZYCnsM7l6nQDCi1OKUYnG4PZmN2l4mbfXit3RXodS/5lwFeBZ7XRtPBpwOIFMNNQz53Mtk7uwHwCyZuXgWuAha6qEMCaRfwnI3Z064LkeJQcJa2mDEmNpE7MMaMNhBnvrV270QeY5THXw18JfvlJuDlQj3WWNiY7QEez57/vBpocVmP+NpBvEXZj7suRIpLwVnaDjD6dJHrRvn+aNNR8rl10R3GmLXZzyNAKzAz+/Ux4D2FHFGbCxuzbcAvTNzMBC7jTJ0iozmGF5jaKzOkFJyl7bvW2nvOd4PRWpRFno4yLXsBsEAX3iopvwK+am3pvTPPHvwOm7hpAS7FC3uRkZwENthY4XpoxB8UnJJP3x8+j9Mvsi3Qh03cTMEL0PmOS5LScQzvNMNeGyuNHhNxS8EpMkT2fNVjJm4m4QXoQhyPChZn9gGbNK1EhlNwiowgu2vFb03cPA8sx9v/s8JtVVIEKWA78Ip2LpFzUXCKnIeN2U7gaRM364ELgKVoJG4QdQJbgG02ZpOui5HSpuAUGYPsPNDtwHYTN03AErxWqBaT968M3pSSrcB+nb+UsVJwBtyQ6SHn8qS19tMjXP9fjTFvPs/PnbbWhnIDaRuzJ4B1w1qhWg/XP9qAncAuG7P5nI4lIaHgDL7R5nmea4pIJedvTYX+tWNjNo23jdqO7GCiJXhBWue0MBnJKbyw3JntfhcZN1Mi89FFAiM7pWVe9tLktJhw68VbDm+Hjdl218VIcCg4RQrIxE0D3pzQeWhQUTGcwjtvuR84pPOWUggKTpEiMXFTw5mW6Ey0rV8+JIFDeGF5wMasto+TglNwijhg4iaKtzzhDLyBRS3ovPFYWKAdLygPAsdszGbcliRho+AUKQEmbsqAKXghOnipclpUaUjiDWBrz14OaySsuKbgFClRJm4m4wXoNLxBRpMJdqt0MCR/H5QaASulSMEp4hMmbgzQgBeiTUAjMCn7sdxhabnqw9s5Z/DSgReS2ghafEHBKRIA2YFHk4B6oBqoyX4ceilG16/Fazn2cCYYO4d83mVjdqAIdYgUjIJTJCSy51GrODtIy4ZdzHk+H8ALxeEfBy8DCkUJAwWniIhIDjSPTEREJAcKThERkRwoOEVERHKg4BQREcmBglNERCQHCk4REZEcKDhFRERyoOAUERHJgYJTREQkBwpOERGRHCg4RUREcqDgFBERyYGCU0REJAcKThERkRwoOEVkVMaYNcYYO5bLCD97pTHmXmPMDmNMwhjTa4zZb4xZb4z5R2PMXcaY8lEef9GQx9hauGcqMrqo6wJExFcOAPvHemNjTBz4DGc2wj4AHAeagMuBK4GPAnOAg+e5qw8M+XyJMeZaa+263EoXyQ8Fp4jk4rvW2nvGckNjzNuAv85++QXgi9ba40O+Xw/cjheKmfPcTwR4X/bLU8Ak4P2AglOcUFetiBTKh7Iff22t/dTQ0ASw1nZZa39irb3DWnv4PPfzBmAm0IPXOgV4lzGmJv8li4xOwSkihbIg+/GlCd7PYDft/cB/4HX11gPvnOD9ioyLglNECqUz+/FaY4wZzx0YY5qBt2S//L61dgD4Ufbr90+wPpFxUXCKSKE8lP14A/AzY8xtxpjaHO/jPUAF3sCh32av+372443GmAUj/pRIASk4RSQXsVGmo3xvyG2/CDyZ/fytwCNApzFmizHme8aYPxxDkA62Kv+PtTYDYK19AXgZb6SuWp1SdMba10y7EhE5izFmDbCK0aej/Mpa+/khPxcF7gb+GLiC175ZPw78ubX2hyM85mXA89kvl1prtw353ieAv8dric4dDFWRYlBwisiohgRnfKzTUUa4j0ZgJd78zTcAqzkTpO+01t437PZfAz4CPGutvWrY91rwQjMK3G6tfWQ8NYmMh7pqRaQorLWnrbWPW2u/YK29GW/xg/bstz839LbGmErgv2W//MEI99WG1/ULZy+OIFJwCk4RccJa+zzwN9kvLzTGTBry7bfhrS4E8LVzLO33puz332qMmVykskW0cpCIOLVjyOcVQz4fbEX2AN3n+fkmoBL4Q+Br+S1NZGRqcYpIQWTPQ47mhuzHk3gDhTDGzAFuyV7/bmvt9HNdgH/O3k7dtVI0Ck4RKZQHjDE/Nca8efjyeMaYRmPMJ4G/yF71r0NGxv4R3rGpDfjVKI9xb/bjpcaYS/JVuMj5qKtWRHLxAWPMLaPc5m5r7U688Ht79pI2xuzCW6S9CW83lMrs7R8kuxh8doWhu7PX/9BamzrfA1lrXzDGvARcjNfq/LOcn5FIjjQdRURGNWQ6ylhcaq3dmF0u7xbgVmAFMAOYire92GFgA/Aja+3gCkMYY1YBa7JfLrfWvjKG2j4O/APQAcy01ibHWKfIuCg4RUREcqBznCIiIjlQcIqIiORAwSkiIpIDBaeIiEgOFJwiIiI5UHCKiIjkQMEpIiKSAwWniIhIDhScIiIiOVBwioiI5EDBKSIikgMFp4iISA4UnCIiIjlQcIqIiORAwSkiIpIDBaeIiEgOFJwiIiI5+L999iXUQMhCugAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 560x560 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1, figsize=(4, 4), dpi=140)\n",
    "venn2(subsets = (\n",
    "    np.sum((master_catalogue['blind_F_SPIRE_500'] > 70) &  ~(master_catalogue['esa_fluxsus'] > 0)), #HELP only\n",
    "    np.sum(~(master_catalogue['blind_F_SPIRE_500'] > 70) &  (master_catalogue['esa_fluxsus'] > 0)),     #ESA only\n",
    "    np.sum(np.sum((master_catalogue['blind_F_SPIRE_500'] > 0) &  (master_catalogue['esa_fluxsus'] > 0)))\n",
    "), set_labels = ('HELP blind > 70 mJy', 'ESA blind > 70 mJy'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(master_catalogue['esa_fluxsus'] > 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib_venn._common.VennDiagram at 0x11ecd3b38>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 560x560 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1, figsize=(4, 4), dpi=140)\n",
    "venn2(subsets = (\n",
    "    np.sum((master_catalogue['help_f_spire_500'] > 0) &  ~(master_catalogue['blind_F_SPIRE_500'] > 0)), #HELP only\n",
    "    np.sum(~(master_catalogue['help_f_spire_500'] > 0) &  (master_catalogue['blind_F_SPIRE_500'] > 0)),     #ESA only\n",
    "    np.sum(np.sum((master_catalogue['help_f_spire_500'] > 0) &  (master_catalogue['blind_F_SPIRE_500'] > 0)))\n",
    "), set_labels = ('HELP XID+ > 70 mJy', 'HELP blind > 70 mJy'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 560x560 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(1, figsize=(4, 4), dpi=140)\n",
    "in_help_blind = master_catalogue['blind_F_SPIRE_500'] > 0\n",
    "in_help_xid = master_catalogue['help_f_spire_500'] > 0\n",
    "in_esa_blind = master_catalogue['esa_fluxsus'] > 0\n",
    "\n",
    "help_blind_only = np.sum(in_help_blind & ~in_help_xid & ~in_esa_blind)\n",
    "help_xid_only = np.sum(~in_help_blind & in_help_xid & ~in_esa_blind)\n",
    "xid_hblind = np.sum(in_help_blind & in_help_xid & ~in_esa_blind)\n",
    "esa_blind_only = np.sum(~in_help_blind & ~in_help_xid & in_esa_blind)\n",
    "help_blind_esa_blind = np.sum(in_help_blind & ~in_help_xid & in_esa_blind)\n",
    "xid_esa_blind = np.sum(~in_help_blind & in_help_xid & in_esa_blind)\n",
    "everything = np.sum(in_help_blind & in_help_xid & in_esa_blind)\n",
    "venn3(subsets = (\n",
    "    help_blind_only, #help blind only\n",
    "    help_xid_only, #help xid\n",
    "    xid_hblind, \n",
    "    esa_blind_only, \n",
    "    help_blind_esa_blind, \n",
    "    xid_esa_blind, \n",
    "    everything\n",
    "), set_labels = ('HELP Blind >70 mJy', 'HELP XID+ > 70mJy', 'ESA Blind > 70 mJy'), alpha = 0.5);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "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",
      "WARNING:astropy:UnitsWarning: 'mJy/Beam' did not parse as fits unit: At col 4, Unit 'Beam' not supported by the FITS standard. Did you mean beam?\n",
      "/Users/rs548/miniconda3/envs/herschelhelp_internal/lib/python3.6/site-packages/astropy/io/fits/util.py:905: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  b = array.view(dt_int, np.ndarray)\n"
     ]
    }
   ],
   "source": [
    "master_catalogue.write('./data/full_match_esa_help_xid_over_70mjy.fits', overwrite=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (herschelhelp_internal)",
   "language": "python",
   "name": "helpint"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}