{
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  {
   "cell_type": "markdown",
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    "deletable": true,
    "editable": true
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   "source": [
    "# ELAIS-N1 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",
      "2018-07-05 13:58:39.971916\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 = 'ELAIS-N1'\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_elais-n1_20171016.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))"
   ]
  },
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   "execution_count": 10,
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    "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",
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       "<thead><tr><th>idx</th><th>hp_idx_O_13</th><th>hp_idx_O_10</th><th>ferr_ap_wfc_u_mean</th><th>f_ap_wfc_u_p90</th><th>ferr_wfc_u_mean</th><th>f_wfc_u_p90</th><th>ferr_ap_wfc_g_mean</th><th>f_ap_wfc_g_p90</th><th>ferr_wfc_g_mean</th><th>f_wfc_g_p90</th><th>ferr_ap_wfc_r_mean</th><th>f_ap_wfc_r_p90</th><th>ferr_wfc_r_mean</th><th>f_wfc_r_p90</th><th>ferr_ap_wfc_i_mean</th><th>f_ap_wfc_i_p90</th><th>ferr_wfc_i_mean</th><th>f_wfc_i_p90</th><th>ferr_ap_wfc_z_mean</th><th>f_ap_wfc_z_p90</th><th>ferr_wfc_z_mean</th><th>f_wfc_z_p90</th><th>ferr_ap_megacam_u_mean</th><th>f_ap_megacam_u_p90</th><th>ferr_megacam_u_mean</th><th>f_megacam_u_p90</th><th>ferr_ap_megacam_g_mean</th><th>f_ap_megacam_g_p90</th><th>ferr_megacam_g_mean</th><th>f_megacam_g_p90</th><th>ferr_ap_megacam_r_mean</th><th>f_ap_megacam_r_p90</th><th>ferr_megacam_r_mean</th><th>f_megacam_r_p90</th><th>ferr_ap_megacam_z_mean</th><th>f_ap_megacam_z_p90</th><th>ferr_megacam_z_mean</th><th>f_megacam_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_suprime_n921_mean</th><th>f_ap_suprime_n921_p90</th><th>ferr_suprime_n921_mean</th><th>f_suprime_n921_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_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_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_irac_i3_mean</th><th>f_ap_irac_i3_p90</th><th>ferr_irac_i3_mean</th><th>f_irac_i3_p90</th><th>ferr_ap_irac_i4_mean</th><th>f_ap_irac_i4_p90</th><th>ferr_irac_i4_mean</th><th>f_irac_i4_p90</th><th>ferr_ap_irac_i1_mean</th><th>f_ap_irac_i1_p90</th><th>ferr_irac_i1_mean</th><th>f_irac_i1_p90</th><th>ferr_ap_irac_i2_mean</th><th>f_ap_irac_i2_p90</th><th>ferr_irac_i2_mean</th><th>f_irac_i2_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></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>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</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>163568991</td><td>2555765</td><td>7.743878</td><td>639.3397979736328</td><td>15.4039</td><td>845.4422363281251</td><td>6.003914</td><td>433.57851257324194</td><td>6.6958</td><td>471.21519775390607</td><td>7.843617</td><td>711.2130737304688</td><td>10.631635</td><td>860.280200195312</td><td>14.274835</td><td>1482.4726440429686</td><td>15.761008</td><td>1564.0201660156247</td><td>55.95911</td><td>3023.656726074219</td><td>57.43031595193315</td><td>3052.4401733398445</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>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>0.4865763419523362</td><td>2487.089826246271</td><td>1.410005143138388</td><td>2379.8752657275786</td><td>0.5890315507773657</td><td>3485.2645337402255</td><td>1.5075894652359496</td><td>3317.0906407542493</td><td>0.46708482608697993</td><td>3980.968874119753</td><td>1.1719755225165434</td><td>3766.03227538404</td><td>0.7499965271015302</td><td>3759.9013502505577</td><td>3.1876323072982173</td><td>3694.9212251452213</td><td>0.7009519094501205</td><td>3936.969748207869</td><td>6.529729527654593</td><td>3703.752487511755</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>1</td><td>163569023</td><td>2555765</td><td>7.743878</td><td>639.3397979736328</td><td>15.4039</td><td>845.4422363281251</td><td>6.003914</td><td>433.57851257324194</td><td>6.6958</td><td>471.21519775390607</td><td>7.843617</td><td>711.2130737304688</td><td>10.631635</td><td>860.280200195312</td><td>14.274835</td><td>1482.4726440429686</td><td>15.761008</td><td>1564.0201660156247</td><td>55.95911</td><td>3023.656726074219</td><td>57.43031595193315</td><td>3052.4401733398445</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>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>0.4865763419523362</td><td>2487.089826246271</td><td>1.410005143138388</td><td>2379.8752657275786</td><td>0.5890315507773657</td><td>3485.2645337402255</td><td>1.5075894652359496</td><td>3317.0906407542493</td><td>0.46708482608697993</td><td>3980.968874119753</td><td>1.1719755225165434</td><td>3766.03227538404</td><td>0.7499965271015302</td><td>3759.9013502505577</td><td>3.1876323072982173</td><td>3694.9212251452213</td><td>0.7009519094501205</td><td>3936.969748207869</td><td>6.529729527654593</td><td>3703.752487511755</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>2</td><td>163569021</td><td>2555765</td><td>7.743878</td><td>639.3397979736328</td><td>15.4039</td><td>845.4422363281251</td><td>6.003914</td><td>433.57851257324194</td><td>6.6958</td><td>471.21519775390607</td><td>7.843617</td><td>711.2130737304688</td><td>10.631635</td><td>860.280200195312</td><td>14.274835</td><td>1482.4726440429686</td><td>15.761008</td><td>1564.0201660156247</td><td>55.95911</td><td>3023.656726074219</td><td>57.43031595193315</td><td>3052.4401733398445</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>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>0.4865763419523362</td><td>2487.089826246271</td><td>1.410005143138388</td><td>2379.8752657275786</td><td>0.5890315507773657</td><td>3485.2645337402255</td><td>1.5075894652359496</td><td>3317.0906407542493</td><td>0.46708482608697993</td><td>3980.968874119753</td><td>1.1719755225165434</td><td>3766.03227538404</td><td>0.7499965271015302</td><td>3759.9013502505577</td><td>3.1876323072982173</td><td>3694.9212251452213</td><td>0.7009519094501205</td><td>3936.969748207869</td><td>6.529729527654593</td><td>3703.752487511755</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>3</td><td>163569022</td><td>2555765</td><td>7.743878</td><td>639.3397979736328</td><td>15.4039</td><td>845.4422363281251</td><td>6.003914</td><td>433.57851257324194</td><td>6.6958</td><td>471.21519775390607</td><td>7.843617</td><td>711.2130737304688</td><td>10.631635</td><td>860.280200195312</td><td>14.274835</td><td>1482.4726440429686</td><td>15.761008</td><td>1564.0201660156247</td><td>55.95911</td><td>3023.656726074219</td><td>57.43031595193315</td><td>3052.4401733398445</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>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>0.4865763419523362</td><td>2487.089826246271</td><td>1.410005143138388</td><td>2379.8752657275786</td><td>0.5890315507773657</td><td>3485.2645337402255</td><td>1.5075894652359496</td><td>3317.0906407542493</td><td>0.46708482608697993</td><td>3980.968874119753</td><td>1.1719755225165434</td><td>3766.03227538404</td><td>0.7499965271015302</td><td>3759.9013502505577</td><td>3.1876323072982173</td><td>3694.9212251452213</td><td>0.7009519094501205</td><td>3936.969748207869</td><td>6.529729527654593</td><td>3703.752487511755</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>4</td><td>163569020</td><td>2555765</td><td>7.743878</td><td>639.3397979736328</td><td>15.4039</td><td>845.4422363281251</td><td>6.003914</td><td>433.57851257324194</td><td>6.6958</td><td>471.21519775390607</td><td>7.843617</td><td>711.2130737304688</td><td>10.631635</td><td>860.280200195312</td><td>14.274835</td><td>1482.4726440429686</td><td>15.761008</td><td>1564.0201660156247</td><td>55.95911</td><td>3023.656726074219</td><td>57.43031595193315</td><td>3052.4401733398445</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>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>0.4865763419523362</td><td>2487.089826246271</td><td>1.410005143138388</td><td>2379.8752657275786</td><td>0.5890315507773657</td><td>3485.2645337402255</td><td>1.5075894652359496</td><td>3317.0906407542493</td><td>0.46708482608697993</td><td>3980.968874119753</td><td>1.1719755225165434</td><td>3766.03227538404</td><td>0.7499965271015302</td><td>3759.9013502505577</td><td>3.1876323072982173</td><td>3694.9212251452213</td><td>0.7009519094501205</td><td>3936.969748207869</td><td>6.529729527654593</td><td>3703.752487511755</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>5</td><td>163569015</td><td>2555765</td><td>7.743878</td><td>639.3397979736328</td><td>15.4039</td><td>845.4422363281251</td><td>6.003914</td><td>433.57851257324194</td><td>6.6958</td><td>471.21519775390607</td><td>7.843617</td><td>711.2130737304688</td><td>10.631635</td><td>860.280200195312</td><td>14.274835</td><td>1482.4726440429686</td><td>15.761008</td><td>1564.0201660156247</td><td>55.95911</td><td>3023.656726074219</td><td>57.43031595193315</td><td>3052.4401733398445</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>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>0.4865763419523362</td><td>2487.089826246271</td><td>1.410005143138388</td><td>2379.8752657275786</td><td>0.5890315507773657</td><td>3485.2645337402255</td><td>1.5075894652359496</td><td>3317.0906407542493</td><td>0.46708482608697993</td><td>3980.968874119753</td><td>1.1719755225165434</td><td>3766.03227538404</td><td>0.7499965271015302</td><td>3759.9013502505577</td><td>3.1876323072982173</td><td>3694.9212251452213</td><td>0.7009519094501205</td><td>3936.969748207869</td><td>6.529729527654593</td><td>3703.752487511755</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>6</td><td>163569013</td><td>2555765</td><td>7.743878</td><td>639.3397979736328</td><td>15.4039</td><td>845.4422363281251</td><td>6.003914</td><td>433.57851257324194</td><td>6.6958</td><td>471.21519775390607</td><td>7.843617</td><td>711.2130737304688</td><td>10.631635</td><td>860.280200195312</td><td>14.274835</td><td>1482.4726440429686</td><td>15.761008</td><td>1564.0201660156247</td><td>55.95911</td><td>3023.656726074219</td><td>57.43031595193315</td><td>3052.4401733398445</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>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>0.4865763419523362</td><td>2487.089826246271</td><td>1.410005143138388</td><td>2379.8752657275786</td><td>0.5890315507773657</td><td>3485.2645337402255</td><td>1.5075894652359496</td><td>3317.0906407542493</td><td>0.46708482608697993</td><td>3980.968874119753</td><td>1.1719755225165434</td><td>3766.03227538404</td><td>0.7499965271015302</td><td>3759.9013502505577</td><td>3.1876323072982173</td><td>3694.9212251452213</td><td>0.7009519094501205</td><td>3936.969748207869</td><td>6.529729527654593</td><td>3703.752487511755</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>7</td><td>163569113</td><td>2555767</td><td>0.46507087</td><td>18.494094848632812</td><td>0.53582704</td><td>23.931727600097677</td><td>0.4854082</td><td>13.731683254241943</td><td>0.5991355</td><td>18.382286071777344</td><td>1.0392536</td><td>34.10355758666992</td><td>1.2994108</td><td>53.77048797607428</td><td>1.7264436</td><td>95.60541076660157</td><td>2.0580883</td><td>90.65150604248046</td><td>5.719912</td><td>204.465466308594</td><td>6.513234275084519</td><td>282.53305664062543</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>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>0.08680726164811882</td><td>91.10388415594878</td><td>0.6723587788258806</td><td>116.76293399440722</td><td>0.1160328770004235</td><td>143.96863687144267</td><td>0.7100629514721215</td><td>202.31100505312656</td><td>0.0988246861362748</td><td>172.04163363045566</td><td>0.6051517374171178</td><td>238.98746755002387</td><td>0.18363072473326186</td><td>214.9412616280489</td><td>1.4446663079620115</td><td>331.20329555258877</td><td>0.1916976978882056</td><td>306.97166978746304</td><td>3.996872201219117</td><td>751.3773025085177</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>8</td><td>163569143</td><td>2555767</td><td>0.46507087</td><td>18.494094848632812</td><td>0.53582704</td><td>23.931727600097677</td><td>0.4854082</td><td>13.731683254241943</td><td>0.5991355</td><td>18.382286071777344</td><td>1.0392536</td><td>34.10355758666992</td><td>1.2994108</td><td>53.77048797607428</td><td>1.7264436</td><td>95.60541076660157</td><td>2.0580883</td><td>90.65150604248046</td><td>5.719912</td><td>204.465466308594</td><td>6.513234275084519</td><td>282.53305664062543</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>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>0.08680726164811882</td><td>91.10388415594878</td><td>0.6723587788258806</td><td>116.76293399440722</td><td>0.1160328770004235</td><td>143.96863687144267</td><td>0.7100629514721215</td><td>202.31100505312656</td><td>0.0988246861362748</td><td>172.04163363045566</td><td>0.6051517374171178</td><td>238.98746755002387</td><td>0.18363072473326186</td><td>214.9412616280489</td><td>1.4446663079620115</td><td>331.20329555258877</td><td>0.1916976978882056</td><td>306.97166978746304</td><td>3.996872201219117</td><td>751.3773025085177</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>nan</td><td>nan</td><td>nan</td><td>nan</td></tr>\n",
       "<tr><td>9</td><td>163569139</td><td>2555767</td><td>0.46507087</td><td>18.494094848632812</td><td>0.53582704</td><td>23.931727600097677</td><td>0.4854082</td><td>13.731683254241943</td><td>0.5991355</td><td>18.382286071777344</td><td>1.0392536</td><td>34.10355758666992</td><td>1.2994108</td><td>53.77048797607428</td><td>1.7264436</td><td>95.60541076660157</td><td>2.0580883</td><td>90.65150604248046</td><td>5.719912</td><td>204.465466308594</td><td>6.513234275084519</td><td>282.53305664062543</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>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>0.08680726164811882</td><td>91.10388415594878</td><td>0.6723587788258806</td><td>116.76293399440722</td><td>0.1160328770004235</td><td>143.96863687144267</td><td>0.7100629514721215</td><td>202.31100505312656</td><td>0.0988246861362748</td><td>172.04163363045566</td><td>0.6051517374171178</td><td>238.98746755002387</td><td>0.18363072473326186</td><td>214.9412616280489</td><td>1.4446663079620115</td><td>331.20329555258877</td><td>0.1916976978882056</td><td>306.97166978746304</td><td>3.996872201219117</td><td>751.3773025085177</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>nan</td><td>nan</td><td>nan</td><td>nan</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(\"$('#table139899167917952-759791').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",
       "    $('#table139899167917952-759791').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": [
       "{'gpc1_g',\n",
       " 'gpc1_i',\n",
       " 'gpc1_r',\n",
       " 'gpc1_y',\n",
       " 'gpc1_z',\n",
       " 'irac_i1',\n",
       " 'irac_i2',\n",
       " 'irac_i3',\n",
       " 'irac_i4',\n",
       " 'megacam_g',\n",
       " 'megacam_r',\n",
       " 'megacam_u',\n",
       " 'megacam_z',\n",
       " 'suprime_g',\n",
       " 'suprime_i',\n",
       " 'suprime_n921',\n",
       " 'suprime_r',\n",
       " 'suprime_y',\n",
       " 'suprime_z',\n",
       " 'ukidss_j',\n",
       " 'ukidss_k',\n",
       " 'wfc_g',\n",
       " 'wfc_i',\n",
       " 'wfc_r',\n",
       " 'wfc_u',\n",
       " 'wfc_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,'Passbands on ELAIS-N1')"
      ]
     },
     "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": {},
     "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": [
      "wfc_u: mean flux error: 4.338520526885986, 3sigma in AB mag (Aperture): 21.11384272176445\n",
      "wfc_g: mean flux error: 1.281677484512329, 3sigma in AB mag (Aperture): 22.437749975590997\n",
      "wfc_r: mean flux error: 1.5445971488952637, 3sigma in AB mag (Aperture): 22.235158791056385\n",
      "wfc_i: mean flux error: 3.2868664264678955, 3sigma in AB mag (Aperture): 21.415241724860657\n",
      "wfc_z: mean flux error: 9.724007606506348, 3sigma in AB mag (Aperture): 20.237583638466127\n",
      "megacam_u: mean flux error: 0.015514050610363483, 3sigma in AB mag (Aperture): 27.230383853506076\n",
      "megacam_g: mean flux error: 0.010639035142958164, 3sigma in AB mag (Aperture): 27.639941254555517\n",
      "megacam_r: mean flux error: 0.020171120762825012, 3sigma in AB mag (Aperture): 26.9453717895098\n",
      "megacam_z: mean flux error: 0.04639334976673126, 3sigma in AB mag (Aperture): 26.04105753501424\n",
      "suprime_g: mean flux error: 0.017642125487327576, 3sigma in AB mag (Aperture): 27.09081959604557\n",
      "suprime_r: mean flux error: 0.03673762083053589, 3sigma in AB mag (Aperture): 26.294419294492123\n",
      "suprime_i: mean flux error: 0.0400569848716259, 3sigma in AB mag (Aperture): 26.2005012221559\n",
      "suprime_z: mean flux error: 0.10882171243429184, 3sigma in AB mag (Aperture): 25.11540797383889\n",
      "suprime_y: mean flux error: 0.20747078955173492, 3sigma in AB mag (Aperture): 24.414804463948023\n",
      "suprime_n921: mean flux error: 0.08915248513221741, 3sigma in AB mag (Aperture): 25.331863229022353\n",
      "gpc1_g: mean flux error: 0.49417333358880866, 3sigma in AB mag (Aperture): 23.47249859707805\n",
      "gpc1_r: mean flux error: 0.7111272150862947, 3sigma in AB mag (Aperture): 23.07732861430221\n",
      "gpc1_i: mean flux error: 0.7608708224089503, 3sigma in AB mag (Aperture): 23.003919537558964\n",
      "gpc1_z: mean flux error: 0.6404433251641901, 3sigma in AB mag (Aperture): 23.19099510394556\n",
      "gpc1_y: mean flux error: 1.190484217844742, 3sigma in AB mag (Aperture): 22.517887757272312\n",
      "ukidss_j: mean flux error: 0.5760568380355835, 3sigma in AB mag (Aperture): 23.306033522579433\n",
      "ukidss_k: mean flux error: 0.7020628452301025, 3sigma in AB mag (Aperture): 23.091256888734485\n",
      "irac_i3: mean flux error: 5.451919405581034, 3sigma in AB mag (Aperture): 20.865823295353927\n",
      "irac_i4: mean flux error: 5.145973917282828, 3sigma in AB mag (Aperture): 20.928527911628528\n",
      "irac_i1: mean flux error: 0.8135667514426842, 3sigma in AB mag (Aperture): 22.93121388398942\n",
      "irac_i2: mean flux error: 1.0381956883724712, 3sigma in AB mag (Aperture): 22.666498810897743\n",
      "wfc_u: mean flux error: 8.41977310180664, 3sigma in AB mag (Total): 20.3939458927537\n",
      "wfc_g: mean flux error: 4.339249610900879, 3sigma in AB mag (Total): 21.113660280215406\n",
      "wfc_r: mean flux error: 4.6165571212768555, 3sigma in AB mag (Total): 21.046401329417286\n",
      "wfc_i: mean flux error: 8.161396026611328, 3sigma in AB mag (Total): 20.427785732615966\n",
      "wfc_z: mean flux error: 22.611180546943984, 3sigma in AB mag (Total): 19.321388768744036\n",
      "megacam_u: mean flux error: 0.019857371225953102, 3sigma in AB mag (Total): 26.96239247606875\n",
      "megacam_g: mean flux error: 0.01311870850622654, 3sigma in AB mag (Total): 27.41246915750478\n",
      "megacam_r: mean flux error: 0.02594779245555401, 3sigma in AB mag (Total): 26.671945824324688\n",
      "megacam_z: mean flux error: 0.06112588942050934, 3sigma in AB mag (Total): 25.74163388460544\n",
      "suprime_g: mean flux error: 0.029757732525467873, 3sigma in AB mag (Total): 26.523197273603124\n",
      "suprime_r: mean flux error: 0.062232933938503265, 3sigma in AB mag (Total): 25.722146173078322\n",
      "suprime_i: mean flux error: 0.06631475687026978, 3sigma in AB mag (Total): 25.653171408923278\n",
      "suprime_z: mean flux error: 0.178494393825531, 3sigma in AB mag (Total): 24.578135412484677\n",
      "suprime_y: mean flux error: 0.360311359167099, 3sigma in AB mag (Total): 23.815501978461818\n",
      "suprime_n921: mean flux error: 0.14952917397022247, 3sigma in AB mag (Total): 24.77038202773368\n",
      "gpc1_g: mean flux error: 0.6702953789321207, 3sigma in AB mag (Total): 23.141531299839606\n",
      "gpc1_r: mean flux error: 0.6491015107146099, 3sigma in AB mag (Total): 23.176415313434752\n",
      "gpc1_i: mean flux error: 0.6314110441623573, 3sigma in AB mag (Total): 23.20641642827129\n",
      "gpc1_z: mean flux error: 1.5213217066631834, 3sigma in AB mag (Total): 22.251644208319668\n",
      "gpc1_y: mean flux error: 3.631297300544963, 3sigma in AB mag (Total): 21.307042346192283\n",
      "ukidss_j: mean flux error: 0.7455479502677917, 3sigma in AB mag (Total): 23.02600791184694\n",
      "ukidss_k: mean flux error: 0.9726672172546387, 3sigma in AB mag (Total): 22.737286166514444\n",
      "irac_i3: mean flux error: 5.467139847306324, 3sigma in AB mag (Total): 20.862796405407813\n",
      "irac_i4: mean flux error: 5.575424935601417, 3sigma in AB mag (Total): 20.841501930468077\n",
      "irac_i1: mean flux error: 0.9211400756453788, 3sigma in AB mag (Total): 22.796382669754983\n",
      "irac_i2: mean flux error: 1.1858054591697822, 3sigma in AB mag (Total): 22.522163249692532\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_wfc_u (3355.0, 3925.0, 570.0)\n",
      "ap_wfc_g (4260.0, 5485.0, 1225.0)\n",
      "ap_wfc_r (5575.0, 6910.0, 1335.0)\n",
      "ap_wfc_i (6970.0, 8485.0, 1515.0)\n",
      "ap_wfc_z (8500.0, 9000.0, 500.0)\n",
      "ap_megacam_u (3500.0, 4100.0, 600.0)\n",
      "ap_megacam_g (4180.0, 5580.0, 1400.0)\n",
      "ap_megacam_r (5680.0, 6880.0, 1200.0)\n",
      "ap_megacam_z (8280.0, 9160.0, 880.0)\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_suprime_n921 (9146.5, 9279.0, 132.5)\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_j (11695.0, 13280.0, 1585.0)\n",
      "ap_ukidss_k (20290.0, 23820.0, 3530.0)\n",
      "ap_irac_i3 (50246.3, 64096.7, 13850.398)\n",
      "ap_irac_i4 (64415.2, 92596.8, 28181.598)\n",
      "ap_irac_i1 (31754.0, 39164.8, 7410.801)\n",
      "ap_irac_i2 (39980.1, 50052.3, 10072.199)\n",
      "wfc_u (3355.0, 3925.0, 570.0)\n",
      "wfc_g (4260.0, 5485.0, 1225.0)\n",
      "wfc_r (5575.0, 6910.0, 1335.0)\n",
      "wfc_i (6970.0, 8485.0, 1515.0)\n",
      "wfc_z (8500.0, 9000.0, 500.0)\n",
      "megacam_u (3500.0, 4100.0, 600.0)\n",
      "megacam_g (4180.0, 5580.0, 1400.0)\n",
      "megacam_r (5680.0, 6880.0, 1200.0)\n",
      "megacam_z (8280.0, 9160.0, 880.0)\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",
      "suprime_n921 (9146.5, 9279.0, 132.5)\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_j (11695.0, 13280.0, 1585.0)\n",
      "ukidss_k (20290.0, 23820.0, 3530.0)\n",
      "irac_i3 (50246.3, 64096.7, 13850.398)\n",
      "irac_i4 (64415.2, 92596.8, 28181.598)\n",
      "irac_i1 (31754.0, 39164.8, 7410.801)\n",
      "irac_i2 (39980.1, 50052.3, 10072.199)\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,'Depths on ELAIS-N1')"
      ]
     },
     "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": {},
     "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,'Depths (5 $\\\\sigma$) vs coverage on ELAIS-N1')"
      ]
     },
     "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": {},
     "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}