{
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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",
      "2018-06-24 19:45:22.869853\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_20180216.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[:10].show_in_notebook()"
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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(\"$('#table140403920007800-672407').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",
       "    $('#table140403920007800-672407').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
}