{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# GAMA-15 Selection Functions\n",
    "## Depth maps and selection functions\n",
    "\n",
    "The simplest selection function available is the field MOC which specifies the area for which there is Herschel data. Each pristine catalogue also has a MOC defining the area for which that data is available.\n",
    "\n",
    "The next stage is to provide mean flux standard deviations which act as a proxy for the catalogue's 5$\\sigma$ depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This notebook was run with herschelhelp_internal version: \n",
      "017bb1e (Mon Jun 18 14:58:59 2018 +0100)\n",
      "This notebook was executed on: \n",
      "2019-02-01 18:55:56.654833\n"
     ]
    }
   ],
   "source": [
    "from herschelhelp_internal import git_version\n",
    "print(\"This notebook was run with herschelhelp_internal version: \\n{}\".format(git_version()))\n",
    "import datetime\n",
    "print(\"This notebook was executed on: \\n{}\".format(datetime.datetime.now()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "#%config InlineBackend.figure_format = 'svg'\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rc('figure', figsize=(10, 6))\n",
    "\n",
    "import os\n",
    "import time\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.table import Column, Table, join\n",
    "import numpy as np\n",
    "from pymoc import MOC\n",
    "import healpy as hp\n",
    "#import pandas as pd #Astropy has group_by function so apandas isn't required.\n",
    "import seaborn as sns\n",
    "\n",
    "import warnings\n",
    "#We ignore warnings - this is a little dangerous but a huge number of warnings are generated by empty cells later\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from herschelhelp_internal.utils import inMoc, coords_to_hpidx, flux_to_mag\n",
    "from herschelhelp_internal.masterlist import find_last_ml_suffix, nb_ccplots\n",
    "\n",
    "from astropy.io.votable import parse_single_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "FIELD = 'GAMA-15'\n",
    "#FILTERS_DIR = \"/Users/rs548/GitHub/herschelhelp_python/database_builder/filters/\"\n",
    "FILTERS_DIR = \"/opt/herschelhelp_python/database_builder/filters/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth maps produced using: master_catalogue_gama-15_20190201.fits\n"
     ]
    }
   ],
   "source": [
    "TMP_DIR = os.environ.get('TMP_DIR', \"./data_tmp\")\n",
    "OUT_DIR = os.environ.get('OUT_DIR', \"./data\")\n",
    "SUFFIX = find_last_ml_suffix()\n",
    "#SUFFIX = \"20171016\"\n",
    "\n",
    "master_catalogue_filename = \"master_catalogue_{}_{}.fits\".format(FIELD.lower(), SUFFIX)\n",
    "master_catalogue = Table.read(\"{}/{}\".format(OUT_DIR, master_catalogue_filename))\n",
    "\n",
    "print(\"Depth maps produced using: {}\".format(master_catalogue_filename))\n",
    "\n",
    "ORDER = 10\n",
    "#TODO write code to decide on appropriate order\n",
    "\n",
    "field_moc = MOC(filename=\"../../dmu2/dmu2_field_coverages/{}_MOC.fits\".format(FIELD))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Remove sources whose signal to noise ratio is less than five as these will have been selected using forced \n",
    "# photometry and so the errors will not refelct the RMS of the map \n",
    "for n,col in enumerate(master_catalogue.colnames):\n",
    "    if col.startswith(\"f_\"):\n",
    "        err_col = \"ferr{}\".format(col[1:])\n",
    "        errs = master_catalogue[err_col]\n",
    "        fluxes = master_catalogue[col]\n",
    "        mask = fluxes/errs < 5.0\n",
    "        master_catalogue[col][mask] = np.nan\n",
    "        master_catalogue[err_col][mask] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## I - Group masterlist objects by healpix cell and calculate depths\n",
    "We add a column to the masterlist catalogue for the target order healpix cell <i>per object</i>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Add a column to the catalogue with the order=ORDER hp_idx\n",
    "master_catalogue.add_column(Column(data=coords_to_hpidx(master_catalogue['ra'],\n",
    "                                                       master_catalogue['dec'],\n",
    "                                                       ORDER), \n",
    "                                   name=\"hp_idx_O_{}\".format(str(ORDER))\n",
    "                                  )\n",
    "                           )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "# Convert catalogue to pandas and group by the order=ORDER pixel\n",
    "\n",
    "group = master_catalogue.group_by([\"hp_idx_O_{}\".format(str(ORDER))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Downgrade the groups from order=ORDER to order=13 and then fill out the appropriate cells\n",
    "#hp.pixelfunc.ud_grade([2599293, 2599294], nside_out=hp.order2nside(13))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## II Create a table of all Order=13 healpix cells in the field and populate it\n",
    "We create a table with every order=13 healpix cell in the field MOC. We then calculate the healpix cell at lower order that the order=13 cell is in. We then fill in the depth at every order=13 cell as calculated for the lower order cell that that the order=13 cell is inside."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "depths = Table()\n",
    "depths['hp_idx_O_13'] = list(field_moc.flattened(13))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=10</i>\n",
       "<table id=\"table140107839632272-83205\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>hp_idx_O_13</th></tr></thead>\n",
       "<tr><td>0</td><td>427039119</td></tr>\n",
       "<tr><td>1</td><td>427045789</td></tr>\n",
       "<tr><td>2</td><td>424938402</td></tr>\n",
       "<tr><td>3</td><td>427045790</td></tr>\n",
       "<tr><td>4</td><td>427045121</td></tr>\n",
       "<tr><td>5</td><td>427044263</td></tr>\n",
       "<tr><td>6</td><td>427045791</td></tr>\n",
       "<tr><td>7</td><td>427045792</td></tr>\n",
       "<tr><td>8</td><td>427045793</td></tr>\n",
       "<tr><td>9</td><td>427039120</td></tr>\n",
       "</table><style>table.dataTable {clear: both; width: auto !important; margin: 0 !important;}\n",
       ".dataTables_info, .dataTables_length, .dataTables_filter, .dataTables_paginate{\n",
       "display: inline-block; margin-right: 1em; }\n",
       ".paginate_button { margin-right: 5px; }\n",
       "</style>\n",
       "<script>\n",
       "\n",
       "var astropy_sort_num = function(a, b) {\n",
       "    var a_num = parseFloat(a);\n",
       "    var b_num = parseFloat(b);\n",
       "\n",
       "    if (isNaN(a_num) && isNaN(b_num))\n",
       "        return ((a < b) ? -1 : ((a > b) ? 1 : 0));\n",
       "    else if (!isNaN(a_num) && !isNaN(b_num))\n",
       "        return ((a_num < b_num) ? -1 : ((a_num > b_num) ? 1 : 0));\n",
       "    else\n",
       "        return isNaN(a_num) ? -1 : 1;\n",
       "}\n",
       "\n",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table140107839632272-83205').dataTable()\");\n",
       "    \n",
       "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
       "    \"optionalnum-asc\": astropy_sort_num,\n",
       "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
       "});\n",
       "\n",
       "    $('#table140107839632272-83205').dataTable({\n",
       "        order: [],\n",
       "        pageLength: 50,\n",
       "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        pagingType: \"full_numbers\",\n",
       "        columnDefs: [{targets: [0, 1], type: \"optionalnum\"}]\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "depths[:10].show_in_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "depths.add_column(Column(data=hp.pixelfunc.ang2pix(2**ORDER,\n",
    "                     hp.pixelfunc.pix2ang(2**13, depths['hp_idx_O_13'], nest=True)[0],\n",
    "                     hp.pixelfunc.pix2ang(2**13, depths['hp_idx_O_13'], nest=True)[1],\n",
    "                     nest = True),\n",
    "                     name=\"hp_idx_O_{}\".format(str(ORDER))\n",
    "                        )\n",
    "                 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table length=10</i>\n",
       "<table id=\"table140107839592992-859987\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>hp_idx_O_13</th><th>hp_idx_O_10</th></tr></thead>\n",
       "<tr><td>0</td><td>427039119</td><td>6672486</td></tr>\n",
       "<tr><td>1</td><td>427045789</td><td>6672590</td></tr>\n",
       "<tr><td>2</td><td>424938402</td><td>6639662</td></tr>\n",
       "<tr><td>3</td><td>427045790</td><td>6672590</td></tr>\n",
       "<tr><td>4</td><td>427045121</td><td>6672580</td></tr>\n",
       "<tr><td>5</td><td>427044263</td><td>6672566</td></tr>\n",
       "<tr><td>6</td><td>427045791</td><td>6672590</td></tr>\n",
       "<tr><td>7</td><td>427045792</td><td>6672590</td></tr>\n",
       "<tr><td>8</td><td>427045793</td><td>6672590</td></tr>\n",
       "<tr><td>9</td><td>427039120</td><td>6672486</td></tr>\n",
       "</table><style>table.dataTable {clear: both; width: auto !important; margin: 0 !important;}\n",
       ".dataTables_info, .dataTables_length, .dataTables_filter, .dataTables_paginate{\n",
       "display: inline-block; margin-right: 1em; }\n",
       ".paginate_button { margin-right: 5px; }\n",
       "</style>\n",
       "<script>\n",
       "\n",
       "var astropy_sort_num = function(a, b) {\n",
       "    var a_num = parseFloat(a);\n",
       "    var b_num = parseFloat(b);\n",
       "\n",
       "    if (isNaN(a_num) && isNaN(b_num))\n",
       "        return ((a < b) ? -1 : ((a > b) ? 1 : 0));\n",
       "    else if (!isNaN(a_num) && !isNaN(b_num))\n",
       "        return ((a_num < b_num) ? -1 : ((a_num > b_num) ? 1 : 0));\n",
       "    else\n",
       "        return isNaN(a_num) ? -1 : 1;\n",
       "}\n",
       "\n",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table140107839592992-859987').dataTable()\");\n",
       "    \n",
       "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
       "    \"optionalnum-asc\": astropy_sort_num,\n",
       "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
       "});\n",
       "\n",
       "    $('#table140107839592992-859987').dataTable({\n",
       "        order: [],\n",
       "        pageLength: 50,\n",
       "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        pagingType: \"full_numbers\",\n",
       "        columnDefs: [{targets: [0, 1, 2], type: \"optionalnum\"}]\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "depths[:10].show_in_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<i>Table masked=True length=10</i>\n",
       "<table id=\"table140107839516856-487931\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>idx</th><th>hp_idx_O_13</th><th>hp_idx_O_10</th><th>ferr_ap_decam_g_mean</th><th>f_ap_decam_g_p90</th><th>ferr_decam_g_mean</th><th>f_decam_g_p90</th><th>ferr_ap_decam_r_mean</th><th>f_ap_decam_r_p90</th><th>ferr_decam_r_mean</th><th>f_decam_r_p90</th><th>ferr_ap_decam_z_mean</th><th>f_ap_decam_z_p90</th><th>ferr_decam_z_mean</th><th>f_decam_z_p90</th><th>ferr_ap_suprime_g_mean</th><th>f_ap_suprime_g_p90</th><th>ferr_suprime_g_mean</th><th>f_suprime_g_p90</th><th>ferr_ap_suprime_r_mean</th><th>f_ap_suprime_r_p90</th><th>ferr_suprime_r_mean</th><th>f_suprime_r_p90</th><th>ferr_ap_suprime_i_mean</th><th>f_ap_suprime_i_p90</th><th>ferr_suprime_i_mean</th><th>f_suprime_i_p90</th><th>ferr_ap_suprime_z_mean</th><th>f_ap_suprime_z_p90</th><th>ferr_suprime_z_mean</th><th>f_suprime_z_p90</th><th>ferr_ap_suprime_y_mean</th><th>f_ap_suprime_y_p90</th><th>ferr_suprime_y_mean</th><th>f_suprime_y_p90</th><th>ferr_ap_omegacam_u_mean</th><th>f_ap_omegacam_u_p90</th><th>ferr_omegacam_u_mean</th><th>f_omegacam_u_p90</th><th>ferr_ap_omegacam_g_mean</th><th>f_ap_omegacam_g_p90</th><th>ferr_omegacam_g_mean</th><th>f_omegacam_g_p90</th><th>ferr_ap_omegacam_r_mean</th><th>f_ap_omegacam_r_p90</th><th>ferr_omegacam_r_mean</th><th>f_omegacam_r_p90</th><th>ferr_ap_omegacam_i_mean</th><th>f_ap_omegacam_i_p90</th><th>ferr_omegacam_i_mean</th><th>f_omegacam_i_p90</th><th>ferr_ap_gpc1_g_mean</th><th>f_ap_gpc1_g_p90</th><th>ferr_gpc1_g_mean</th><th>f_gpc1_g_p90</th><th>ferr_ap_gpc1_r_mean</th><th>f_ap_gpc1_r_p90</th><th>ferr_gpc1_r_mean</th><th>f_gpc1_r_p90</th><th>ferr_ap_gpc1_i_mean</th><th>f_ap_gpc1_i_p90</th><th>ferr_gpc1_i_mean</th><th>f_gpc1_i_p90</th><th>ferr_ap_gpc1_z_mean</th><th>f_ap_gpc1_z_p90</th><th>ferr_gpc1_z_mean</th><th>f_gpc1_z_p90</th><th>ferr_ap_gpc1_y_mean</th><th>f_ap_gpc1_y_p90</th><th>ferr_gpc1_y_mean</th><th>f_gpc1_y_p90</th><th>ferr_ap_ukidss_y_mean</th><th>f_ap_ukidss_y_p90</th><th>ferr_ukidss_y_mean</th><th>f_ukidss_y_p90</th><th>ferr_ap_ukidss_j_mean</th><th>f_ap_ukidss_j_p90</th><th>ferr_ukidss_j_mean</th><th>f_ukidss_j_p90</th><th>ferr_ap_ukidss_h_mean</th><th>f_ap_ukidss_h_p90</th><th>ferr_ukidss_h_mean</th><th>f_ukidss_h_p90</th><th>ferr_ap_ukidss_k_mean</th><th>f_ap_ukidss_k_p90</th><th>ferr_ukidss_k_mean</th><th>f_ukidss_k_p90</th><th>ferr_ap_vista_z_mean</th><th>f_ap_vista_z_p90</th><th>ferr_vista_z_mean</th><th>f_vista_z_p90</th><th>ferr_ap_vista_y_mean</th><th>f_ap_vista_y_p90</th><th>ferr_vista_y_mean</th><th>f_vista_y_p90</th><th>ferr_ap_vista_j_mean</th><th>f_ap_vista_j_p90</th><th>ferr_vista_j_mean</th><th>f_vista_j_p90</th><th>ferr_ap_vista_h_mean</th><th>f_ap_vista_h_p90</th><th>ferr_vista_h_mean</th><th>f_vista_h_p90</th><th>ferr_ap_vista_ks_mean</th><th>f_ap_vista_ks_p90</th><th>ferr_vista_ks_mean</th><th>f_vista_ks_p90</th></tr></thead>\n",
       "<thead><tr><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>uJy</th><th>uJy</th><th></th><th></th><th>uJy</th><th>uJy</th><th></th><th></th><th>uJy</th><th>uJy</th><th></th><th></th><th>uJy</th><th>uJy</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<tr><td>0</td><td>134226592</td><td>2097290</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.51850754</td><td>10.212726593017578</td><td>0.3458474</td><td>9.482696437835692</td><td>0.82162315</td><td>21.175762176513672</td><td>0.5858852</td><td>22.650573921203613</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.21023609</td><td>1.2530426263809205</td><td>nan</td><td>nan</td><td>0.0846733</td><td>1.684419703483582</td><td>0.09720915</td><td>2.402827262878418</td><td>0.10238967</td><td>3.272310304641724</td><td>0.12159265</td><td>5.122196292877198</td><td>0.2086195</td><td>8.456571483612063</td><td>0.27727032</td><td>10.322418689727783</td><td>nan</td><td>nan</td><td>0.34827091623895357</td><td>1.7889584351648204</td><td>0.8926761262395497</td><td>5.830154774472676</td><td>1.0192849307539602</td><td>7.870152226516549</td><td>0.8017508799103293</td><td>15.912243747496706</td><td>0.8516376935138238</td><td>13.664123328941049</td><td>1.3928113868969987</td><td>23.52221230958412</td><td>1.3442254196399297</td><td>20.55216296858164</td><td>2.894998788923195</td><td>26.61950913026702</td><td>3.6149968032433537</td><td>23.55141479670379</td><td>3.0393708</td><td>17.449309253692626</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>5.5880446</td><td>32.515445709228516</td><td>nan</td><td>nan</td><td>6.7122993</td><td>62.35185623168945</td><td>9.812085</td><td>75.00704956054688</td><td>0.7920463</td><td>16.3915283203125</td><td>1.8303959</td><td>18.414660453796387</td><td>1.3846154</td><td>23.359660148620605</td><td>4.017344</td><td>26.564175033569335</td><td>1.7187109</td><td>27.46394424438477</td><td>4.689211</td><td>31.738461303710938</td><td>3.610589</td><td>41.54606399536133</td><td>nan</td><td>nan</td><td>3.0994172</td><td>49.94132308959961</td><td>7.901993</td><td>50.00286598205567</td></tr>\n",
       "<tr><td>1</td><td>134226602</td><td>2097290</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.51850754</td><td>10.212726593017578</td><td>0.3458474</td><td>9.482696437835692</td><td>0.82162315</td><td>21.175762176513672</td><td>0.5858852</td><td>22.650573921203613</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.21023609</td><td>1.2530426263809205</td><td>nan</td><td>nan</td><td>0.0846733</td><td>1.684419703483582</td><td>0.09720915</td><td>2.402827262878418</td><td>0.10238967</td><td>3.272310304641724</td><td>0.12159265</td><td>5.122196292877198</td><td>0.2086195</td><td>8.456571483612063</td><td>0.27727032</td><td>10.322418689727783</td><td>nan</td><td>nan</td><td>0.34827091623895357</td><td>1.7889584351648204</td><td>0.8926761262395497</td><td>5.830154774472676</td><td>1.0192849307539602</td><td>7.870152226516549</td><td>0.8017508799103293</td><td>15.912243747496706</td><td>0.8516376935138238</td><td>13.664123328941049</td><td>1.3928113868969987</td><td>23.52221230958412</td><td>1.3442254196399297</td><td>20.55216296858164</td><td>2.894998788923195</td><td>26.61950913026702</td><td>3.6149968032433537</td><td>23.55141479670379</td><td>3.0393708</td><td>17.449309253692626</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>5.5880446</td><td>32.515445709228516</td><td>nan</td><td>nan</td><td>6.7122993</td><td>62.35185623168945</td><td>9.812085</td><td>75.00704956054688</td><td>0.7920463</td><td>16.3915283203125</td><td>1.8303959</td><td>18.414660453796387</td><td>1.3846154</td><td>23.359660148620605</td><td>4.017344</td><td>26.564175033569335</td><td>1.7187109</td><td>27.46394424438477</td><td>4.689211</td><td>31.738461303710938</td><td>3.610589</td><td>41.54606399536133</td><td>nan</td><td>nan</td><td>3.0994172</td><td>49.94132308959961</td><td>7.901993</td><td>50.00286598205567</td></tr>\n",
       "<tr><td>2</td><td>134226603</td><td>2097290</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.51850754</td><td>10.212726593017578</td><td>0.3458474</td><td>9.482696437835692</td><td>0.82162315</td><td>21.175762176513672</td><td>0.5858852</td><td>22.650573921203613</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.21023609</td><td>1.2530426263809205</td><td>nan</td><td>nan</td><td>0.0846733</td><td>1.684419703483582</td><td>0.09720915</td><td>2.402827262878418</td><td>0.10238967</td><td>3.272310304641724</td><td>0.12159265</td><td>5.122196292877198</td><td>0.2086195</td><td>8.456571483612063</td><td>0.27727032</td><td>10.322418689727783</td><td>nan</td><td>nan</td><td>0.34827091623895357</td><td>1.7889584351648204</td><td>0.8926761262395497</td><td>5.830154774472676</td><td>1.0192849307539602</td><td>7.870152226516549</td><td>0.8017508799103293</td><td>15.912243747496706</td><td>0.8516376935138238</td><td>13.664123328941049</td><td>1.3928113868969987</td><td>23.52221230958412</td><td>1.3442254196399297</td><td>20.55216296858164</td><td>2.894998788923195</td><td>26.61950913026702</td><td>3.6149968032433537</td><td>23.55141479670379</td><td>3.0393708</td><td>17.449309253692626</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>5.5880446</td><td>32.515445709228516</td><td>nan</td><td>nan</td><td>6.7122993</td><td>62.35185623168945</td><td>9.812085</td><td>75.00704956054688</td><td>0.7920463</td><td>16.3915283203125</td><td>1.8303959</td><td>18.414660453796387</td><td>1.3846154</td><td>23.359660148620605</td><td>4.017344</td><td>26.564175033569335</td><td>1.7187109</td><td>27.46394424438477</td><td>4.689211</td><td>31.738461303710938</td><td>3.610589</td><td>41.54606399536133</td><td>nan</td><td>nan</td><td>3.0994172</td><td>49.94132308959961</td><td>7.901993</td><td>50.00286598205567</td></tr>\n",
       "<tr><td>3</td><td>134226600</td><td>2097290</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.51850754</td><td>10.212726593017578</td><td>0.3458474</td><td>9.482696437835692</td><td>0.82162315</td><td>21.175762176513672</td><td>0.5858852</td><td>22.650573921203613</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.21023609</td><td>1.2530426263809205</td><td>nan</td><td>nan</td><td>0.0846733</td><td>1.684419703483582</td><td>0.09720915</td><td>2.402827262878418</td><td>0.10238967</td><td>3.272310304641724</td><td>0.12159265</td><td>5.122196292877198</td><td>0.2086195</td><td>8.456571483612063</td><td>0.27727032</td><td>10.322418689727783</td><td>nan</td><td>nan</td><td>0.34827091623895357</td><td>1.7889584351648204</td><td>0.8926761262395497</td><td>5.830154774472676</td><td>1.0192849307539602</td><td>7.870152226516549</td><td>0.8017508799103293</td><td>15.912243747496706</td><td>0.8516376935138238</td><td>13.664123328941049</td><td>1.3928113868969987</td><td>23.52221230958412</td><td>1.3442254196399297</td><td>20.55216296858164</td><td>2.894998788923195</td><td>26.61950913026702</td><td>3.6149968032433537</td><td>23.55141479670379</td><td>3.0393708</td><td>17.449309253692626</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>5.5880446</td><td>32.515445709228516</td><td>nan</td><td>nan</td><td>6.7122993</td><td>62.35185623168945</td><td>9.812085</td><td>75.00704956054688</td><td>0.7920463</td><td>16.3915283203125</td><td>1.8303959</td><td>18.414660453796387</td><td>1.3846154</td><td>23.359660148620605</td><td>4.017344</td><td>26.564175033569335</td><td>1.7187109</td><td>27.46394424438477</td><td>4.689211</td><td>31.738461303710938</td><td>3.610589</td><td>41.54606399536133</td><td>nan</td><td>nan</td><td>3.0994172</td><td>49.94132308959961</td><td>7.901993</td><td>50.00286598205567</td></tr>\n",
       "<tr><td>4</td><td>134226594</td><td>2097290</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.51850754</td><td>10.212726593017578</td><td>0.3458474</td><td>9.482696437835692</td><td>0.82162315</td><td>21.175762176513672</td><td>0.5858852</td><td>22.650573921203613</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.21023609</td><td>1.2530426263809205</td><td>nan</td><td>nan</td><td>0.0846733</td><td>1.684419703483582</td><td>0.09720915</td><td>2.402827262878418</td><td>0.10238967</td><td>3.272310304641724</td><td>0.12159265</td><td>5.122196292877198</td><td>0.2086195</td><td>8.456571483612063</td><td>0.27727032</td><td>10.322418689727783</td><td>nan</td><td>nan</td><td>0.34827091623895357</td><td>1.7889584351648204</td><td>0.8926761262395497</td><td>5.830154774472676</td><td>1.0192849307539602</td><td>7.870152226516549</td><td>0.8017508799103293</td><td>15.912243747496706</td><td>0.8516376935138238</td><td>13.664123328941049</td><td>1.3928113868969987</td><td>23.52221230958412</td><td>1.3442254196399297</td><td>20.55216296858164</td><td>2.894998788923195</td><td>26.61950913026702</td><td>3.6149968032433537</td><td>23.55141479670379</td><td>3.0393708</td><td>17.449309253692626</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>5.5880446</td><td>32.515445709228516</td><td>nan</td><td>nan</td><td>6.7122993</td><td>62.35185623168945</td><td>9.812085</td><td>75.00704956054688</td><td>0.7920463</td><td>16.3915283203125</td><td>1.8303959</td><td>18.414660453796387</td><td>1.3846154</td><td>23.359660148620605</td><td>4.017344</td><td>26.564175033569335</td><td>1.7187109</td><td>27.46394424438477</td><td>4.689211</td><td>31.738461303710938</td><td>3.610589</td><td>41.54606399536133</td><td>nan</td><td>nan</td><td>3.0994172</td><td>49.94132308959961</td><td>7.901993</td><td>50.00286598205567</td></tr>\n",
       "<tr><td>5</td><td>134228014</td><td>2097312</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.49352938</td><td>53.3856986999512</td><td>0.62597716</td><td>26.43040771484375</td><td>0.91367835</td><td>70.65121765136723</td><td>0.61311555</td><td>38.113921737670935</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.2320776</td><td>11.626157355308552</td><td>0.37541068</td><td>19.543386268615713</td><td>0.0876883</td><td>3.242756366729737</td><td>0.10756739</td><td>4.973746252059936</td><td>0.097718045</td><td>6.296526908874512</td><td>0.12499767</td><td>7.248914480209351</td><td>0.19756326</td><td>12.881778240203872</td><td>0.28195268</td><td>16.40565128326416</td><td>0.9991227480568864</td><td>76.97688294259962</td><td>0.9478306535110793</td><td>68.20247366063188</td><td>1.1178170928625137</td><td>66.05152604972315</td><td>1.322601942713443</td><td>61.37022892721748</td><td>0.8278944596423699</td><td>56.541574600609756</td><td>0.9481786556641225</td><td>50.751060175180264</td><td>1.7654012070927052</td><td>101.36779413504394</td><td>1.8381918328960145</td><td>94.2274589274823</td><td>4.151021813632829</td><td>126.31060616834179</td><td>3.330510979143962</td><td>96.35111599028552</td><td>3.5968742</td><td>507.06809997558594</td><td>6.2682734</td><td>526.9618774414063</td><td>6.188336</td><td>308.07347106933594</td><td>7.130998</td><td>322.67149353027344</td><td>5.7335763</td><td>224.19540252685536</td><td>10.871893</td><td>347.74883422851565</td><td>6.8216734</td><td>258.0086181640625</td><td>11.223945</td><td>274.2400207519531</td><td>0.8298682</td><td>29.993879318237305</td><td>2.3718386</td><td>102.0642074584961</td><td>1.4487895</td><td>67.36036682128906</td><td>4.0367875</td><td>133.2998512268067</td><td>1.7642776</td><td>88.83100357055665</td><td>5.1259313</td><td>181.34911804199226</td><td>3.6635222</td><td>163.32646179199216</td><td>10.852872</td><td>314.278549194336</td><td>3.1391466</td><td>144.1946640014649</td><td>9.223716</td><td>289.2537628173828</td></tr>\n",
       "<tr><td>6</td><td>134227976</td><td>2097312</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.49352938</td><td>53.3856986999512</td><td>0.62597716</td><td>26.43040771484375</td><td>0.91367835</td><td>70.65121765136723</td><td>0.61311555</td><td>38.113921737670935</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.2320776</td><td>11.626157355308552</td><td>0.37541068</td><td>19.543386268615713</td><td>0.0876883</td><td>3.242756366729737</td><td>0.10756739</td><td>4.973746252059936</td><td>0.097718045</td><td>6.296526908874512</td><td>0.12499767</td><td>7.248914480209351</td><td>0.19756326</td><td>12.881778240203872</td><td>0.28195268</td><td>16.40565128326416</td><td>0.9991227480568864</td><td>76.97688294259962</td><td>0.9478306535110793</td><td>68.20247366063188</td><td>1.1178170928625137</td><td>66.05152604972315</td><td>1.322601942713443</td><td>61.37022892721748</td><td>0.8278944596423699</td><td>56.541574600609756</td><td>0.9481786556641225</td><td>50.751060175180264</td><td>1.7654012070927052</td><td>101.36779413504394</td><td>1.8381918328960145</td><td>94.2274589274823</td><td>4.151021813632829</td><td>126.31060616834179</td><td>3.330510979143962</td><td>96.35111599028552</td><td>3.5968742</td><td>507.06809997558594</td><td>6.2682734</td><td>526.9618774414063</td><td>6.188336</td><td>308.07347106933594</td><td>7.130998</td><td>322.67149353027344</td><td>5.7335763</td><td>224.19540252685536</td><td>10.871893</td><td>347.74883422851565</td><td>6.8216734</td><td>258.0086181640625</td><td>11.223945</td><td>274.2400207519531</td><td>0.8298682</td><td>29.993879318237305</td><td>2.3718386</td><td>102.0642074584961</td><td>1.4487895</td><td>67.36036682128906</td><td>4.0367875</td><td>133.2998512268067</td><td>1.7642776</td><td>88.83100357055665</td><td>5.1259313</td><td>181.34911804199226</td><td>3.6635222</td><td>163.32646179199216</td><td>10.852872</td><td>314.278549194336</td><td>3.1391466</td><td>144.1946640014649</td><td>9.223716</td><td>289.2537628173828</td></tr>\n",
       "<tr><td>7</td><td>134227980</td><td>2097312</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.49352938</td><td>53.3856986999512</td><td>0.62597716</td><td>26.43040771484375</td><td>0.91367835</td><td>70.65121765136723</td><td>0.61311555</td><td>38.113921737670935</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.2320776</td><td>11.626157355308552</td><td>0.37541068</td><td>19.543386268615713</td><td>0.0876883</td><td>3.242756366729737</td><td>0.10756739</td><td>4.973746252059936</td><td>0.097718045</td><td>6.296526908874512</td><td>0.12499767</td><td>7.248914480209351</td><td>0.19756326</td><td>12.881778240203872</td><td>0.28195268</td><td>16.40565128326416</td><td>0.9991227480568864</td><td>76.97688294259962</td><td>0.9478306535110793</td><td>68.20247366063188</td><td>1.1178170928625137</td><td>66.05152604972315</td><td>1.322601942713443</td><td>61.37022892721748</td><td>0.8278944596423699</td><td>56.541574600609756</td><td>0.9481786556641225</td><td>50.751060175180264</td><td>1.7654012070927052</td><td>101.36779413504394</td><td>1.8381918328960145</td><td>94.2274589274823</td><td>4.151021813632829</td><td>126.31060616834179</td><td>3.330510979143962</td><td>96.35111599028552</td><td>3.5968742</td><td>507.06809997558594</td><td>6.2682734</td><td>526.9618774414063</td><td>6.188336</td><td>308.07347106933594</td><td>7.130998</td><td>322.67149353027344</td><td>5.7335763</td><td>224.19540252685536</td><td>10.871893</td><td>347.74883422851565</td><td>6.8216734</td><td>258.0086181640625</td><td>11.223945</td><td>274.2400207519531</td><td>0.8298682</td><td>29.993879318237305</td><td>2.3718386</td><td>102.0642074584961</td><td>1.4487895</td><td>67.36036682128906</td><td>4.0367875</td><td>133.2998512268067</td><td>1.7642776</td><td>88.83100357055665</td><td>5.1259313</td><td>181.34911804199226</td><td>3.6635222</td><td>163.32646179199216</td><td>10.852872</td><td>314.278549194336</td><td>3.1391466</td><td>144.1946640014649</td><td>9.223716</td><td>289.2537628173828</td></tr>\n",
       "<tr><td>8</td><td>134227978</td><td>2097312</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.49352938</td><td>53.3856986999512</td><td>0.62597716</td><td>26.43040771484375</td><td>0.91367835</td><td>70.65121765136723</td><td>0.61311555</td><td>38.113921737670935</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.2320776</td><td>11.626157355308552</td><td>0.37541068</td><td>19.543386268615713</td><td>0.0876883</td><td>3.242756366729737</td><td>0.10756739</td><td>4.973746252059936</td><td>0.097718045</td><td>6.296526908874512</td><td>0.12499767</td><td>7.248914480209351</td><td>0.19756326</td><td>12.881778240203872</td><td>0.28195268</td><td>16.40565128326416</td><td>0.9991227480568864</td><td>76.97688294259962</td><td>0.9478306535110793</td><td>68.20247366063188</td><td>1.1178170928625137</td><td>66.05152604972315</td><td>1.322601942713443</td><td>61.37022892721748</td><td>0.8278944596423699</td><td>56.541574600609756</td><td>0.9481786556641225</td><td>50.751060175180264</td><td>1.7654012070927052</td><td>101.36779413504394</td><td>1.8381918328960145</td><td>94.2274589274823</td><td>4.151021813632829</td><td>126.31060616834179</td><td>3.330510979143962</td><td>96.35111599028552</td><td>3.5968742</td><td>507.06809997558594</td><td>6.2682734</td><td>526.9618774414063</td><td>6.188336</td><td>308.07347106933594</td><td>7.130998</td><td>322.67149353027344</td><td>5.7335763</td><td>224.19540252685536</td><td>10.871893</td><td>347.74883422851565</td><td>6.8216734</td><td>258.0086181640625</td><td>11.223945</td><td>274.2400207519531</td><td>0.8298682</td><td>29.993879318237305</td><td>2.3718386</td><td>102.0642074584961</td><td>1.4487895</td><td>67.36036682128906</td><td>4.0367875</td><td>133.2998512268067</td><td>1.7642776</td><td>88.83100357055665</td><td>5.1259313</td><td>181.34911804199226</td><td>3.6635222</td><td>163.32646179199216</td><td>10.852872</td><td>314.278549194336</td><td>3.1391466</td><td>144.1946640014649</td><td>9.223716</td><td>289.2537628173828</td></tr>\n",
       "<tr><td>9</td><td>134227977</td><td>2097312</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.49352938</td><td>53.3856986999512</td><td>0.62597716</td><td>26.43040771484375</td><td>0.91367835</td><td>70.65121765136723</td><td>0.61311555</td><td>38.113921737670935</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.2320776</td><td>11.626157355308552</td><td>0.37541068</td><td>19.543386268615713</td><td>0.0876883</td><td>3.242756366729737</td><td>0.10756739</td><td>4.973746252059936</td><td>0.097718045</td><td>6.296526908874512</td><td>0.12499767</td><td>7.248914480209351</td><td>0.19756326</td><td>12.881778240203872</td><td>0.28195268</td><td>16.40565128326416</td><td>0.9991227480568864</td><td>76.97688294259962</td><td>0.9478306535110793</td><td>68.20247366063188</td><td>1.1178170928625137</td><td>66.05152604972315</td><td>1.322601942713443</td><td>61.37022892721748</td><td>0.8278944596423699</td><td>56.541574600609756</td><td>0.9481786556641225</td><td>50.751060175180264</td><td>1.7654012070927052</td><td>101.36779413504394</td><td>1.8381918328960145</td><td>94.2274589274823</td><td>4.151021813632829</td><td>126.31060616834179</td><td>3.330510979143962</td><td>96.35111599028552</td><td>3.5968742</td><td>507.06809997558594</td><td>6.2682734</td><td>526.9618774414063</td><td>6.188336</td><td>308.07347106933594</td><td>7.130998</td><td>322.67149353027344</td><td>5.7335763</td><td>224.19540252685536</td><td>10.871893</td><td>347.74883422851565</td><td>6.8216734</td><td>258.0086181640625</td><td>11.223945</td><td>274.2400207519531</td><td>0.8298682</td><td>29.993879318237305</td><td>2.3718386</td><td>102.0642074584961</td><td>1.4487895</td><td>67.36036682128906</td><td>4.0367875</td><td>133.2998512268067</td><td>1.7642776</td><td>88.83100357055665</td><td>5.1259313</td><td>181.34911804199226</td><td>3.6635222</td><td>163.32646179199216</td><td>10.852872</td><td>314.278549194336</td><td>3.1391466</td><td>144.1946640014649</td><td>9.223716</td><td>289.2537628173828</td></tr>\n",
       "</table><style>table.dataTable {clear: both; width: auto !important; margin: 0 !important;}\n",
       ".dataTables_info, .dataTables_length, .dataTables_filter, .dataTables_paginate{\n",
       "display: inline-block; margin-right: 1em; }\n",
       ".paginate_button { margin-right: 5px; }\n",
       "</style>\n",
       "<script>\n",
       "\n",
       "var astropy_sort_num = function(a, b) {\n",
       "    var a_num = parseFloat(a);\n",
       "    var b_num = parseFloat(b);\n",
       "\n",
       "    if (isNaN(a_num) && isNaN(b_num))\n",
       "        return ((a < b) ? -1 : ((a > b) ? 1 : 0));\n",
       "    else if (!isNaN(a_num) && !isNaN(b_num))\n",
       "        return ((a_num < b_num) ? -1 : ((a_num > b_num) ? 1 : 0));\n",
       "    else\n",
       "        return isNaN(a_num) ? -1 : 1;\n",
       "}\n",
       "\n",
       "require.config({paths: {\n",
       "    datatables: 'https://cdn.datatables.net/1.10.12/js/jquery.dataTables.min'\n",
       "}});\n",
       "require([\"datatables\"], function(){\n",
       "    console.log(\"$('#table140107839516856-487931').dataTable()\");\n",
       "    \n",
       "jQuery.extend( jQuery.fn.dataTableExt.oSort, {\n",
       "    \"optionalnum-asc\": astropy_sort_num,\n",
       "    \"optionalnum-desc\": function (a,b) { return -astropy_sort_num(a, b); }\n",
       "});\n",
       "\n",
       "    $('#table140107839516856-487931').dataTable({\n",
       "        order: [],\n",
       "        pageLength: 50,\n",
       "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        pagingType: \"full_numbers\",\n",
       "        columnDefs: [{targets: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106], type: \"optionalnum\"}]\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for col in master_catalogue.colnames:\n",
    "    if col.startswith(\"f_\"):\n",
    "        errcol = \"ferr{}\".format(col[1:])\n",
    "        depths = join(depths, \n",
    "                      group[\"hp_idx_O_{}\".format(str(ORDER)), errcol].groups.aggregate(np.nanmean),\n",
    "                     join_type='left')\n",
    "        depths[errcol].name = errcol + \"_mean\"\n",
    "        depths = join(depths, \n",
    "                      group[\"hp_idx_O_{}\".format(str(ORDER)), col].groups.aggregate(lambda x: np.nanpercentile(x, 90.)),\n",
    "                     join_type='left')\n",
    "        depths[col].name = col + \"_p90\"\n",
    "\n",
    "depths[:10].show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## III - Save the depth map table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "depths.write(\"{}/depths_{}_{}.fits\".format(OUT_DIR, FIELD.lower(), SUFFIX), overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## IV - Overview plots\n",
    "\n",
    "### IV.a - Filters\n",
    "First we simply plot all the filters available on this field to give an overview of coverage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'decam_g',\n",
       " 'decam_r',\n",
       " 'decam_z',\n",
       " 'gpc1_g',\n",
       " 'gpc1_i',\n",
       " 'gpc1_r',\n",
       " 'gpc1_y',\n",
       " 'gpc1_z',\n",
       " 'omegacam_g',\n",
       " 'omegacam_i',\n",
       " 'omegacam_r',\n",
       " 'omegacam_u',\n",
       " 'suprime_g',\n",
       " 'suprime_i',\n",
       " 'suprime_r',\n",
       " 'suprime_y',\n",
       " 'suprime_z',\n",
       " 'ukidss_h',\n",
       " 'ukidss_j',\n",
       " 'ukidss_k',\n",
       " 'ukidss_y',\n",
       " 'vista_h',\n",
       " 'vista_j',\n",
       " 'vista_ks',\n",
       " 'vista_y',\n",
       " 'vista_z'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tot_bands = [column[2:] for column in master_catalogue.colnames \n",
    "             if (column.startswith('f_') & ~column.startswith('f_ap_'))]\n",
    "ap_bands = [column[5:] for column in master_catalogue.colnames \n",
    "            if column.startswith('f_ap_') ]\n",
    "bands = set(tot_bands) | set(ap_bands)\n",
    "bands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Passbands on GAMA-15')"
      ]
     },
     "execution_count": 16,
     "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": [
    "for b in bands:\n",
    "    plt.plot(Table(data = parse_single_table(FILTERS_DIR + b + '.xml').array.data)['Wavelength']\n",
    "            ,Table(data = parse_single_table(FILTERS_DIR + b + '.xml').array.data)['Transmission']\n",
    "            , label=b)\n",
    "plt.xlabel('Wavelength ($\\AA$)')\n",
    "plt.ylabel('Transmission')\n",
    "plt.xscale('log')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.title('Passbands on {}'.format(FIELD))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### IV.a - Depth overview\n",
    "Then we plot the mean depths available across the area a given band is available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "decam_g: mean flux error: 0.28686457872390747, 3sigma in AB mag (Aperture): 24.06300454813178\n",
      "decam_r: mean flux error: 0.4288409948348999, 3sigma in AB mag (Aperture): 23.626456126132346\n",
      "decam_z: mean flux error: 0.6367666721343994, 3sigma in AB mag (Aperture): 23.197246051466713\n",
      "suprime_g: mean flux error: 0.02295534312725067, 3sigma in AB mag (Aperture): 26.804987391175665\n",
      "suprime_r: mean flux error: 0.034290555864572525, 3sigma in AB mag (Aperture): 26.36926055002271\n",
      "suprime_i: mean flux error: 0.033941492438316345, 3sigma in AB mag (Aperture): 26.380369526387902\n",
      "suprime_z: mean flux error: 0.0738983303308487, 3sigma in AB mag (Aperture): 25.535610298211445\n",
      "suprime_y: mean flux error: 0.1488315612077713, 3sigma in AB mag (Aperture): 24.775459269636265\n",
      "omegacam_u: mean flux error: 0.2787735164165497, 3sigma in AB mag (Aperture): 24.09406808006336\n",
      "omegacam_g: mean flux error: 0.10243125259876251, 3sigma in AB mag (Aperture): 25.18111565420906\n",
      "omegacam_r: mean flux error: 0.10494126379489899, 3sigma in AB mag (Aperture): 25.15483113807702\n",
      "omegacam_i: mean flux error: 0.3801940083503723, 3sigma in AB mag (Aperture): 23.757183692351212\n",
      "gpc1_g: mean flux error: 11822.918125643875, 3sigma in AB mag (Aperture): 12.525385157994386\n",
      "gpc1_r: mean flux error: 21.891621991686776, 3sigma in AB mag (Aperture): 19.356502012051372\n",
      "gpc1_i: mean flux error: 15.654806948260552, 3sigma in AB mag (Aperture): 19.720577572303192\n",
      "gpc1_z: mean flux error: 7.9404600103329, 3sigma in AB mag (Aperture): 20.457582705948532\n",
      "gpc1_y: mean flux error: 13.917084090328421, 3sigma in AB mag (Aperture): 19.848326234808873\n",
      "ukidss_y: mean flux error: 4.035210132598877, 3sigma in AB mag (Aperture): 21.19253147463123\n",
      "ukidss_j: mean flux error: 5.420261383056641, 3sigma in AB mag (Aperture): 20.872146287776452\n",
      "ukidss_h: mean flux error: 6.280020236968994, 3sigma in AB mag (Aperture): 20.712294255135795\n",
      "ukidss_k: mean flux error: 6.8160481452941895, 3sigma in AB mag (Aperture): 20.623365239657467\n",
      "vista_z: mean flux error: 0.8532747030258179, 3sigma in AB mag (Aperture): 22.879474687385816\n",
      "vista_y: mean flux error: 1.5828652381896973, 3sigma in AB mag (Aperture): 22.208587009402372\n",
      "vista_j: mean flux error: 1.5816757678985596, 3sigma in AB mag (Aperture): 22.209403210562606\n",
      "vista_h: mean flux error: 2.5936875343322754, 3sigma in AB mag (Aperture): 21.672402726322098\n",
      "vista_ks: mean flux error: 2.8268470764160156, 3sigma in AB mag (Aperture): 21.57894107532072\n",
      "decam_g: mean flux error: 5.362493515014648, 3sigma in AB mag (Total): 20.883779913223584\n",
      "decam_r: mean flux error: 7.638596534729004, 3sigma in AB mag (Total): 20.499662934436238\n",
      "decam_z: mean flux error: 0.549934983253479, 3sigma in AB mag (Total): 23.356418494389423\n",
      "suprime_g: mean flux error: 0.03472571820020676, 3sigma in AB mag (Total): 26.355568771657552\n",
      "suprime_r: mean flux error: 0.05153351277112961, 3sigma in AB mag (Total): 25.926972495544113\n",
      "suprime_i: mean flux error: 0.052601877599954605, 3sigma in AB mag (Total): 25.90469374726772\n",
      "suprime_z: mean flux error: 0.11327511817216873, 3sigma in AB mag (Total): 25.071860553398018\n",
      "suprime_y: mean flux error: 0.23561790585517883, 3sigma in AB mag (Total): 24.276676133921193\n",
      "omegacam_u: mean flux error: 0.4727758765220642, 3sigma in AB mag (Total): 23.52055859199836\n",
      "omegacam_g: mean flux error: 0.1352354735136032, 3sigma in AB mag (Total): 24.879470298194313\n",
      "omegacam_r: mean flux error: 0.13743656873703003, 3sigma in AB mag (Total): 24.861941103305234\n",
      "omegacam_i: mean flux error: 0.5915163159370422, 3sigma in AB mag (Total): 23.277280042254638\n",
      "gpc1_g: mean flux error: 12603.803998134066, 3sigma in AB mag (Total): 12.455942761107849\n",
      "gpc1_r: mean flux error: 25.88477446606786, 3sigma in AB mag (Total): 19.17458589987998\n",
      "gpc1_i: mean flux error: 17.320821705491856, 3sigma in AB mag (Total): 19.610775635092217\n",
      "gpc1_z: mean flux error: 11.32778117510822, 3sigma in AB mag (Total): 20.071834735889077\n",
      "gpc1_y: mean flux error: 17.379143403953634, 3sigma in AB mag (Total): 19.60712594616779\n",
      "ukidss_y: mean flux error: 6.816124439239502, 3sigma in AB mag (Total): 20.62335308677455\n",
      "ukidss_j: mean flux error: 7.465983867645264, 3sigma in AB mag (Total): 20.524479245260558\n",
      "ukidss_h: mean flux error: 11.642038345336914, 3sigma in AB mag (Total): 20.04212429973763\n",
      "ukidss_k: mean flux error: 12.790072441101074, 3sigma in AB mag (Total): 19.940014352535606\n",
      "vista_z: mean flux error: 2.09651255607605, 3sigma in AB mag (Total): 21.90345319382599\n",
      "vista_y: mean flux error: 3.6865522861480713, 3sigma in AB mag (Total): 21.290645868562926\n",
      "vista_j: mean flux error: 3.9484081268310547, 3sigma in AB mag (Total): 21.216141770386592\n",
      "vista_h: mean flux error: 6.629664897918701, 3sigma in AB mag (Total): 20.65346792026687\n",
      "vista_ks: mean flux error: 7.477791786193848, 3sigma in AB mag (Total): 20.522763442288657\n"
     ]
    }
   ],
   "source": [
    "average_depths = []\n",
    "for b in ap_bands:\n",
    "    \n",
    "    mean_err = np.nanmean(depths['ferr_ap_{}_mean'.format(b)])\n",
    "    print(\"{}: mean flux error: {}, 3sigma in AB mag (Aperture): {}\".format(b, mean_err, flux_to_mag(3.0*mean_err*1.e-6)[0]))\n",
    "    average_depths += [('ap_' + b, flux_to_mag(1.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(3.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(5.0*mean_err*1.e-6)[0])]\n",
    "    \n",
    "for b in tot_bands:\n",
    "    \n",
    "    mean_err = np.nanmean(depths['ferr_{}_mean'.format(b)])\n",
    "    print(\"{}: mean flux error: {}, 3sigma in AB mag (Total): {}\".format(b, mean_err, flux_to_mag(3.0*mean_err*1.e-6)[0]))\n",
    "    average_depths += [(b, flux_to_mag(1.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(3.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(5.0*mean_err*1.e-6)[0])]\n",
    "    \n",
    "average_depths = np.array(average_depths,  dtype=[('band', \"<U16\"), ('1s', float), ('3s', float), ('5s', float)])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def FWHM(X,Y):\n",
    "    \n",
    "    half_max = max(Y) / 2.\n",
    "    #find when function crosses line half_max (when sign of diff flips)\n",
    "    #take the 'derivative' of signum(half_max - Y[])\n",
    "    d = half_max - Y\n",
    "    #plot(X,d) #if you are interested\n",
    "    #find the left and right most indexes\n",
    "    low_end = X[np.where(d < 0)[0][0]]\n",
    "    high_end = X[np.where(d < 0)[0][-1]]\n",
    "    return low_end, high_end, (high_end - low_end)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data = []\n",
    "\n",
    "for b in ap_bands:\n",
    "    data += [['ap_' + b, Table(data = parse_single_table(FILTERS_DIR + b +'.xml').array.data)]]\n",
    "    \n",
    "for b in tot_bands:\n",
    "    data += [[b, Table(data = parse_single_table(FILTERS_DIR + b +'.xml').array.data)]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ap_decam_g (4180.0, 5470.0, 1290.0)\n",
      "ap_decam_r (5680.0, 7150.0, 1470.0)\n",
      "ap_decam_z (8490.0, 9960.0, 1470.0)\n",
      "ap_suprime_g (4090.0, 5460.0, 1370.0)\n",
      "ap_suprime_r (5440.0, 6960.0, 1520.0)\n",
      "ap_suprime_i (6980.0, 8420.0, 1440.0)\n",
      "ap_suprime_z (8540.0, 9280.0, 740.0)\n",
      "ap_suprime_y (9360.0, 10120.0, 760.0)\n",
      "ap_omegacam_u (3296.7, 3807.9, 511.19995)\n",
      "ap_omegacam_g (4077.9, 5369.7, 1291.8003)\n",
      "ap_omegacam_r (5640.7, 6962.8, 1322.0996)\n",
      "ap_omegacam_i (6841.5, 8373.8, 1532.2998)\n",
      "ap_gpc1_g (4260.0, 5500.0, 1240.0)\n",
      "ap_gpc1_r (5500.0, 6900.0, 1400.0)\n",
      "ap_gpc1_i (6910.0, 8190.0, 1280.0)\n",
      "ap_gpc1_z (8190.0, 9210.0, 1020.0)\n",
      "ap_gpc1_y (9200.0, 9820.0, 620.0)\n",
      "ap_ukidss_y (9790.0, 10820.0, 1030.0)\n",
      "ap_ukidss_j (11695.0, 13280.0, 1585.0)\n",
      "ap_ukidss_h (14925.0, 17840.0, 2915.0)\n",
      "ap_ukidss_k (20290.0, 23820.0, 3530.0)\n",
      "ap_vista_z (8300.0, 9260.0, 960.0)\n",
      "ap_vista_y (9740.0, 10660.0, 920.0)\n",
      "ap_vista_j (11670.0, 13380.0, 1710.0)\n",
      "ap_vista_h (15000.0, 17900.0, 2900.0)\n",
      "ap_vista_ks (19930.0, 23010.0, 3080.0)\n",
      "decam_g (4180.0, 5470.0, 1290.0)\n",
      "decam_r (5680.0, 7150.0, 1470.0)\n",
      "decam_z (8490.0, 9960.0, 1470.0)\n",
      "suprime_g (4090.0, 5460.0, 1370.0)\n",
      "suprime_r (5440.0, 6960.0, 1520.0)\n",
      "suprime_i (6980.0, 8420.0, 1440.0)\n",
      "suprime_z (8540.0, 9280.0, 740.0)\n",
      "suprime_y (9360.0, 10120.0, 760.0)\n",
      "omegacam_u (3296.7, 3807.9, 511.19995)\n",
      "omegacam_g (4077.9, 5369.7, 1291.8003)\n",
      "omegacam_r (5640.7, 6962.8, 1322.0996)\n",
      "omegacam_i (6841.5, 8373.8, 1532.2998)\n",
      "gpc1_g (4260.0, 5500.0, 1240.0)\n",
      "gpc1_r (5500.0, 6900.0, 1400.0)\n",
      "gpc1_i (6910.0, 8190.0, 1280.0)\n",
      "gpc1_z (8190.0, 9210.0, 1020.0)\n",
      "gpc1_y (9200.0, 9820.0, 620.0)\n",
      "ukidss_y (9790.0, 10820.0, 1030.0)\n",
      "ukidss_j (11695.0, 13280.0, 1585.0)\n",
      "ukidss_h (14925.0, 17840.0, 2915.0)\n",
      "ukidss_k (20290.0, 23820.0, 3530.0)\n",
      "vista_z (8300.0, 9260.0, 960.0)\n",
      "vista_y (9740.0, 10660.0, 920.0)\n",
      "vista_j (11670.0, 13380.0, 1710.0)\n",
      "vista_h (15000.0, 17900.0, 2900.0)\n",
      "vista_ks (19930.0, 23010.0, 3080.0)\n"
     ]
    }
   ],
   "source": [
    "wav_range = []\n",
    "for dat in data:\n",
    "    print(dat[0], FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission'])))\n",
    "    wav_range += [[dat[0], FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission']))]]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Depths on GAMA-15')"
      ]
     },
     "execution_count": 21,
     "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": [
    "for dat in data:\n",
    "    wav_deets = FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission']))\n",
    "    depth = average_depths['5s'][average_depths['band'] == dat[0]]\n",
    "    #print(depth)\n",
    "    plt.plot([wav_deets[0],wav_deets[1]], [depth,depth], label=dat[0])\n",
    "    \n",
    "plt.xlabel('Wavelength ($\\AA$)')\n",
    "plt.ylabel('Depth')\n",
    "plt.xscale('log')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.title('Depths on {}'.format(FIELD))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### IV.c - Depth vs coverage comparison\n",
    "\n",
    "How best to do this? Colour/intensity plot over area? Percentage coverage vs mean depth?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Depths (5 $\\\\sigma$) vs coverage on GAMA-15')"
      ]
     },
     "execution_count": 22,
     "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": [
    "for dat in data:\n",
    "    wav_deets = FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission']))\n",
    "    depth = average_depths['5s'][average_depths['band'] == dat[0]]\n",
    "    #print(depth)\n",
    "    coverage = np.sum(~np.isnan(depths['ferr_{}_mean'.format(dat[0])]))/len(depths)\n",
    "    plt.plot(coverage, depth, 'x', label=dat[0])\n",
    "    \n",
    "plt.xlabel('Coverage')\n",
    "plt.ylabel('Depth')\n",
    "#plt.xscale('log')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.title('Depths (5 $\\sigma$) vs coverage on {}'.format(FIELD))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (herschelhelp_internal)",
   "language": "python",
   "name": "helpint"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}