{
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  {
   "cell_type": "markdown",
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    "deletable": true,
    "editable": true
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   "source": [
    "# GAMA-12 Selection Functions\n",
    "## Depth maps and selection functions\n",
    "\n",
    "The simplest selection function available is the field MOC which specifies the area for which there is Herschel data. Each pristine catalogue also has a MOC defining the area for which that data is available.\n",
    "\n",
    "The next stage is to provide mean flux standard deviations which act as a proxy for the catalogue's 5$\\sigma$ depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This notebook was run with herschelhelp_internal version: \n",
      "017bb1e (Mon Jun 18 14:58:59 2018 +0100)\n",
      "This notebook was executed on: \n",
      "2019-01-29 12:07:42.907451\n"
     ]
    }
   ],
   "source": [
    "from herschelhelp_internal import git_version\n",
    "print(\"This notebook was run with herschelhelp_internal version: \\n{}\".format(git_version()))\n",
    "import datetime\n",
    "print(\"This notebook was executed on: \\n{}\".format(datetime.datetime.now()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "#%config InlineBackend.figure_format = 'svg'\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rc('figure', figsize=(10, 6))\n",
    "\n",
    "import os\n",
    "import time\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.table import Column, Table, join\n",
    "import numpy as np\n",
    "from pymoc import MOC\n",
    "import healpy as hp\n",
    "#import pandas as pd #Astropy has group_by function so apandas isn't required.\n",
    "import seaborn as sns\n",
    "\n",
    "import warnings\n",
    "#We ignore warnings - this is a little dangerous but a huge number of warnings are generated by empty cells later\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from herschelhelp_internal.utils import inMoc, coords_to_hpidx, flux_to_mag\n",
    "from herschelhelp_internal.masterlist import find_last_ml_suffix, nb_ccplots\n",
    "\n",
    "from astropy.io.votable import parse_single_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "FIELD = 'GAMA-12'\n",
    "#FILTERS_DIR = \"/Users/rs548/GitHub/herschelhelp_python/database_builder/filters/\"\n",
    "FILTERS_DIR = \"/opt/herschelhelp_python/database_builder/filters/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth maps produced using: master_catalogue_gama-12_20190128.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."
   ]
  },
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   "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",
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       "<thead><tr><th>idx</th><th>hp_idx_O_13</th><th>hp_idx_O_10</th><th>ferr_ap_decam_g_mean</th><th>f_ap_decam_g_p90</th><th>ferr_decam_g_mean</th><th>f_decam_g_p90</th><th>ferr_ap_decam_r_mean</th><th>f_ap_decam_r_p90</th><th>ferr_decam_r_mean</th><th>f_decam_r_p90</th><th>ferr_ap_decam_z_mean</th><th>f_ap_decam_z_p90</th><th>ferr_decam_z_mean</th><th>f_decam_z_p90</th><th>ferr_ap_suprime_g_mean</th><th>f_ap_suprime_g_p90</th><th>ferr_suprime_g_mean</th><th>f_suprime_g_p90</th><th>ferr_ap_suprime_r_mean</th><th>f_ap_suprime_r_p90</th><th>ferr_suprime_r_mean</th><th>f_suprime_r_p90</th><th>ferr_ap_suprime_i_mean</th><th>f_ap_suprime_i_p90</th><th>ferr_suprime_i_mean</th><th>f_suprime_i_p90</th><th>ferr_ap_suprime_z_mean</th><th>f_ap_suprime_z_p90</th><th>ferr_suprime_z_mean</th><th>f_suprime_z_p90</th><th>ferr_ap_suprime_y_mean</th><th>f_ap_suprime_y_p90</th><th>ferr_suprime_y_mean</th><th>f_suprime_y_p90</th><th>ferr_ap_omegacam_u_mean</th><th>f_ap_omegacam_u_p90</th><th>ferr_omegacam_u_mean</th><th>f_omegacam_u_p90</th><th>ferr_ap_omegacam_g_mean</th><th>f_ap_omegacam_g_p90</th><th>ferr_omegacam_g_mean</th><th>f_omegacam_g_p90</th><th>ferr_ap_omegacam_r_mean</th><th>f_ap_omegacam_r_p90</th><th>ferr_omegacam_r_mean</th><th>f_omegacam_r_p90</th><th>ferr_ap_omegacam_i_mean</th><th>f_ap_omegacam_i_p90</th><th>ferr_omegacam_i_mean</th><th>f_omegacam_i_p90</th><th>ferr_ap_gpc1_g_mean</th><th>f_ap_gpc1_g_p90</th><th>ferr_gpc1_g_mean</th><th>f_gpc1_g_p90</th><th>ferr_ap_gpc1_r_mean</th><th>f_ap_gpc1_r_p90</th><th>ferr_gpc1_r_mean</th><th>f_gpc1_r_p90</th><th>ferr_ap_gpc1_i_mean</th><th>f_ap_gpc1_i_p90</th><th>ferr_gpc1_i_mean</th><th>f_gpc1_i_p90</th><th>ferr_ap_gpc1_z_mean</th><th>f_ap_gpc1_z_p90</th><th>ferr_gpc1_z_mean</th><th>f_gpc1_z_p90</th><th>ferr_ap_gpc1_y_mean</th><th>f_ap_gpc1_y_p90</th><th>ferr_gpc1_y_mean</th><th>f_gpc1_y_p90</th><th>ferr_ap_ukidss_y_mean</th><th>f_ap_ukidss_y_p90</th><th>ferr_ukidss_y_mean</th><th>f_ukidss_y_p90</th><th>ferr_ap_ukidss_j_mean</th><th>f_ap_ukidss_j_p90</th><th>ferr_ukidss_j_mean</th><th>f_ukidss_j_p90</th><th>ferr_ap_ukidss_h_mean</th><th>f_ap_ukidss_h_p90</th><th>ferr_ukidss_h_mean</th><th>f_ukidss_h_p90</th><th>ferr_ap_ukidss_k_mean</th><th>f_ap_ukidss_k_p90</th><th>ferr_ukidss_k_mean</th><th>f_ukidss_k_p90</th><th>ferr_ap_vista_z_mean</th><th>f_ap_vista_z_p90</th><th>ferr_vista_z_mean</th><th>f_vista_z_p90</th><th>ferr_ap_vista_y_mean</th><th>f_ap_vista_y_p90</th><th>ferr_vista_y_mean</th><th>f_vista_y_p90</th><th>ferr_ap_vista_j_mean</th><th>f_ap_vista_j_p90</th><th>ferr_vista_j_mean</th><th>f_vista_j_p90</th><th>ferr_ap_vista_h_mean</th><th>f_ap_vista_h_p90</th><th>ferr_vista_h_mean</th><th>f_vista_h_p90</th><th>ferr_ap_vista_ks_mean</th><th>f_ap_vista_ks_p90</th><th>ferr_vista_ks_mean</th><th>f_vista_ks_p90</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>uJy</th><th>uJy</th><th></th><th></th><th>uJy</th><th>uJy</th><th></th><th></th><th>uJy</th><th>uJy</th><th></th><th></th><th>uJy</th><th>uJy</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<tr><td>0</td><td>418870903</td><td>6544857</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7244428</td><td>30.47033271789551</td><td>0.4332496</td><td>28.859434127807617</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7203741106424314</td><td>4.226689706733889</td><td>nan</td><td>nan</td><td>1.1277800512051432</td><td>11.068269939586912</td><td>1.0566371170798494</td><td>8.590130989694243</td><td>0.7268498549820356</td><td>18.548420327446713</td><td>0.9587195792798897</td><td>17.716335385735455</td><td>2.0276057668759533</td><td>27.395108281794997</td><td>1.7860161967029509</td><td>27.712195945478307</td><td>3.72421861066248</td><td>34.196446882499274</td><td>2.617814829925206</td><td>34.50906586788093</td><td>3.7342746</td><td>28.607540130615234</td><td>nan</td><td>nan</td><td>4.5572295</td><td>53.862796783447266</td><td>6.021867</td><td>46.81786346435547</td><td>4.149413</td><td>54.5397689819336</td><td>7.6806154</td><td>52.189874267578126</td><td>5.8566217</td><td>61.47573318481445</td><td>9.801786</td><td>71.39154052734376</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418870910</td><td>6544857</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7244428</td><td>30.47033271789551</td><td>0.4332496</td><td>28.859434127807617</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7203741106424314</td><td>4.226689706733889</td><td>nan</td><td>nan</td><td>1.1277800512051432</td><td>11.068269939586912</td><td>1.0566371170798494</td><td>8.590130989694243</td><td>0.7268498549820356</td><td>18.548420327446713</td><td>0.9587195792798897</td><td>17.716335385735455</td><td>2.0276057668759533</td><td>27.395108281794997</td><td>1.7860161967029509</td><td>27.712195945478307</td><td>3.72421861066248</td><td>34.196446882499274</td><td>2.617814829925206</td><td>34.50906586788093</td><td>3.7342746</td><td>28.607540130615234</td><td>nan</td><td>nan</td><td>4.5572295</td><td>53.862796783447266</td><td>6.021867</td><td>46.81786346435547</td><td>4.149413</td><td>54.5397689819336</td><td>7.6806154</td><td>52.189874267578126</td><td>5.8566217</td><td>61.47573318481445</td><td>9.801786</td><td>71.39154052734376</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418870911</td><td>6544857</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7244428</td><td>30.47033271789551</td><td>0.4332496</td><td>28.859434127807617</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7203741106424314</td><td>4.226689706733889</td><td>nan</td><td>nan</td><td>1.1277800512051432</td><td>11.068269939586912</td><td>1.0566371170798494</td><td>8.590130989694243</td><td>0.7268498549820356</td><td>18.548420327446713</td><td>0.9587195792798897</td><td>17.716335385735455</td><td>2.0276057668759533</td><td>27.395108281794997</td><td>1.7860161967029509</td><td>27.712195945478307</td><td>3.72421861066248</td><td>34.196446882499274</td><td>2.617814829925206</td><td>34.50906586788093</td><td>3.7342746</td><td>28.607540130615234</td><td>nan</td><td>nan</td><td>4.5572295</td><td>53.862796783447266</td><td>6.021867</td><td>46.81786346435547</td><td>4.149413</td><td>54.5397689819336</td><td>7.6806154</td><td>52.189874267578126</td><td>5.8566217</td><td>61.47573318481445</td><td>9.801786</td><td>71.39154052734376</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418870908</td><td>6544857</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7244428</td><td>30.47033271789551</td><td>0.4332496</td><td>28.859434127807617</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7203741106424314</td><td>4.226689706733889</td><td>nan</td><td>nan</td><td>1.1277800512051432</td><td>11.068269939586912</td><td>1.0566371170798494</td><td>8.590130989694243</td><td>0.7268498549820356</td><td>18.548420327446713</td><td>0.9587195792798897</td><td>17.716335385735455</td><td>2.0276057668759533</td><td>27.395108281794997</td><td>1.7860161967029509</td><td>27.712195945478307</td><td>3.72421861066248</td><td>34.196446882499274</td><td>2.617814829925206</td><td>34.50906586788093</td><td>3.7342746</td><td>28.607540130615234</td><td>nan</td><td>nan</td><td>4.5572295</td><td>53.862796783447266</td><td>6.021867</td><td>46.81786346435547</td><td>4.149413</td><td>54.5397689819336</td><td>7.6806154</td><td>52.189874267578126</td><td>5.8566217</td><td>61.47573318481445</td><td>9.801786</td><td>71.39154052734376</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418870909</td><td>6544857</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7244428</td><td>30.47033271789551</td><td>0.4332496</td><td>28.859434127807617</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.7203741106424314</td><td>4.226689706733889</td><td>nan</td><td>nan</td><td>1.1277800512051432</td><td>11.068269939586912</td><td>1.0566371170798494</td><td>8.590130989694243</td><td>0.7268498549820356</td><td>18.548420327446713</td><td>0.9587195792798897</td><td>17.716335385735455</td><td>2.0276057668759533</td><td>27.395108281794997</td><td>1.7860161967029509</td><td>27.712195945478307</td><td>3.72421861066248</td><td>34.196446882499274</td><td>2.617814829925206</td><td>34.50906586788093</td><td>3.7342746</td><td>28.607540130615234</td><td>nan</td><td>nan</td><td>4.5572295</td><td>53.862796783447266</td><td>6.021867</td><td>46.81786346435547</td><td>4.149413</td><td>54.5397689819336</td><td>7.6806154</td><td>52.189874267578126</td><td>5.8566217</td><td>61.47573318481445</td><td>9.801786</td><td>71.39154052734376</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418871039</td><td>6544859</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.58127826</td><td>42.178996658325204</td><td>0.38195536</td><td>41.49726905822755</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.965313650885829</td><td>204.6775232916318</td><td>0.9180944352568156</td><td>196.14299226029826</td><td>1.2154834403367296</td><td>231.43105297570565</td><td>0.9883821441085165</td><td>188.4516842092352</td><td>1.221231126672516</td><td>106.82202041567238</td><td>1.1621429315006848</td><td>132.09023775713752</td><td>1.6808787587821974</td><td>159.82678210301603</td><td>1.6364865378707154</td><td>148.13890108927257</td><td>3.3308147611707035</td><td>312.5404086544643</td><td>3.177393952033732</td><td>289.40897637321706</td><td>4.0133185</td><td>406.45132141113277</td><td>6.634674</td><td>405.5004608154296</td><td>4.7049756</td><td>400.8567993164063</td><td>5.837565</td><td>388.8366516113282</td><td>4.291269</td><td>324.14100418090834</td><td>8.771494</td><td>351.38515319824216</td><td>5.9828053</td><td>234.35469970703127</td><td>11.26616</td><td>256.0556884765625</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418871038</td><td>6544859</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.58127826</td><td>42.178996658325204</td><td>0.38195536</td><td>41.49726905822755</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.965313650885829</td><td>204.6775232916318</td><td>0.9180944352568156</td><td>196.14299226029826</td><td>1.2154834403367296</td><td>231.43105297570565</td><td>0.9883821441085165</td><td>188.4516842092352</td><td>1.221231126672516</td><td>106.82202041567238</td><td>1.1621429315006848</td><td>132.09023775713752</td><td>1.6808787587821974</td><td>159.82678210301603</td><td>1.6364865378707154</td><td>148.13890108927257</td><td>3.3308147611707035</td><td>312.5404086544643</td><td>3.177393952033732</td><td>289.40897637321706</td><td>4.0133185</td><td>406.45132141113277</td><td>6.634674</td><td>405.5004608154296</td><td>4.7049756</td><td>400.8567993164063</td><td>5.837565</td><td>388.8366516113282</td><td>4.291269</td><td>324.14100418090834</td><td>8.771494</td><td>351.38515319824216</td><td>5.9828053</td><td>234.35469970703127</td><td>11.26616</td><td>256.0556884765625</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418871037</td><td>6544859</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.58127826</td><td>42.178996658325204</td><td>0.38195536</td><td>41.49726905822755</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.965313650885829</td><td>204.6775232916318</td><td>0.9180944352568156</td><td>196.14299226029826</td><td>1.2154834403367296</td><td>231.43105297570565</td><td>0.9883821441085165</td><td>188.4516842092352</td><td>1.221231126672516</td><td>106.82202041567238</td><td>1.1621429315006848</td><td>132.09023775713752</td><td>1.6808787587821974</td><td>159.82678210301603</td><td>1.6364865378707154</td><td>148.13890108927257</td><td>3.3308147611707035</td><td>312.5404086544643</td><td>3.177393952033732</td><td>289.40897637321706</td><td>4.0133185</td><td>406.45132141113277</td><td>6.634674</td><td>405.5004608154296</td><td>4.7049756</td><td>400.8567993164063</td><td>5.837565</td><td>388.8366516113282</td><td>4.291269</td><td>324.14100418090834</td><td>8.771494</td><td>351.38515319824216</td><td>5.9828053</td><td>234.35469970703127</td><td>11.26616</td><td>256.0556884765625</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418871007</td><td>6544859</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.58127826</td><td>42.178996658325204</td><td>0.38195536</td><td>41.49726905822755</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.965313650885829</td><td>204.6775232916318</td><td>0.9180944352568156</td><td>196.14299226029826</td><td>1.2154834403367296</td><td>231.43105297570565</td><td>0.9883821441085165</td><td>188.4516842092352</td><td>1.221231126672516</td><td>106.82202041567238</td><td>1.1621429315006848</td><td>132.09023775713752</td><td>1.6808787587821974</td><td>159.82678210301603</td><td>1.6364865378707154</td><td>148.13890108927257</td><td>3.3308147611707035</td><td>312.5404086544643</td><td>3.177393952033732</td><td>289.40897637321706</td><td>4.0133185</td><td>406.45132141113277</td><td>6.634674</td><td>405.5004608154296</td><td>4.7049756</td><td>400.8567993164063</td><td>5.837565</td><td>388.8366516113282</td><td>4.291269</td><td>324.14100418090834</td><td>8.771494</td><td>351.38515319824216</td><td>5.9828053</td><td>234.35469970703127</td><td>11.26616</td><td>256.0556884765625</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>418871031</td><td>6544859</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.58127826</td><td>42.178996658325204</td><td>0.38195536</td><td>41.49726905822755</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.965313650885829</td><td>204.6775232916318</td><td>0.9180944352568156</td><td>196.14299226029826</td><td>1.2154834403367296</td><td>231.43105297570565</td><td>0.9883821441085165</td><td>188.4516842092352</td><td>1.221231126672516</td><td>106.82202041567238</td><td>1.1621429315006848</td><td>132.09023775713752</td><td>1.6808787587821974</td><td>159.82678210301603</td><td>1.6364865378707154</td><td>148.13890108927257</td><td>3.3308147611707035</td><td>312.5404086544643</td><td>3.177393952033732</td><td>289.40897637321706</td><td>4.0133185</td><td>406.45132141113277</td><td>6.634674</td><td>405.5004608154296</td><td>4.7049756</td><td>400.8567993164063</td><td>5.837565</td><td>388.8366516113282</td><td>4.291269</td><td>324.14100418090834</td><td>8.771494</td><td>351.38515319824216</td><td>5.9828053</td><td>234.35469970703127</td><td>11.26616</td><td>256.0556884765625</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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(\"$('#table140624717102664-837247').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",
       "    $('#table140624717102664-837247').dataTable({\n",
       "        order: [],\n",
       "        pageLength: 50,\n",
       "        lengthMenu: [[10, 25, 50, 100, 500, 1000, -1], [10, 25, 50, 100, 500, 1000, 'All']],\n",
       "        pagingType: \"full_numbers\",\n",
       "        columnDefs: [{targets: [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106], type: \"optionalnum\"}]\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for col in master_catalogue.colnames:\n",
    "    if col.startswith(\"f_\"):\n",
    "        errcol = \"ferr{}\".format(col[1:])\n",
    "        depths = join(depths, \n",
    "                      group[\"hp_idx_O_{}\".format(str(ORDER)), errcol].groups.aggregate(np.nanmean),\n",
    "                     join_type='left')\n",
    "        depths[errcol].name = errcol + \"_mean\"\n",
    "        depths = join(depths, \n",
    "                      group[\"hp_idx_O_{}\".format(str(ORDER)), col].groups.aggregate(lambda x: np.nanpercentile(x, 90.)),\n",
    "                     join_type='left')\n",
    "        depths[col].name = col + \"_p90\"\n",
    "\n",
    "depths[:10].show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## III - Save the depth map table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "depths.write(\"{}/depths_{}_{}.fits\".format(OUT_DIR, FIELD.lower(), SUFFIX), overwrite=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## IV - Overview plots\n",
    "\n",
    "### IV.a - Filters\n",
    "First we simply plot all the filters available on this field to give an overview of coverage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'decam_g',\n",
       " 'decam_r',\n",
       " 'decam_z',\n",
       " 'gpc1_g',\n",
       " 'gpc1_i',\n",
       " 'gpc1_r',\n",
       " 'gpc1_y',\n",
       " 'gpc1_z',\n",
       " 'omegacam_g',\n",
       " 'omegacam_i',\n",
       " 'omegacam_r',\n",
       " 'omegacam_u',\n",
       " 'suprime_g',\n",
       " 'suprime_i',\n",
       " 'suprime_r',\n",
       " 'suprime_y',\n",
       " 'suprime_z',\n",
       " 'ukidss_h',\n",
       " 'ukidss_j',\n",
       " 'ukidss_k',\n",
       " 'ukidss_y',\n",
       " 'vista_h',\n",
       " 'vista_j',\n",
       " 'vista_ks',\n",
       " 'vista_y',\n",
       " 'vista_z'}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tot_bands = [column[2:] for column in master_catalogue.colnames \n",
    "             if (column.startswith('f_') & ~column.startswith('f_ap_'))]\n",
    "ap_bands = [column[5:] for column in master_catalogue.colnames \n",
    "            if column.startswith('f_ap_') ]\n",
    "bands = set(tot_bands) | set(ap_bands)\n",
    "bands"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Passbands on GAMA-12')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for b in bands:\n",
    "    plt.plot(Table(data = parse_single_table(FILTERS_DIR + b + '.xml').array.data)['Wavelength']\n",
    "            ,Table(data = parse_single_table(FILTERS_DIR + b + '.xml').array.data)['Transmission']\n",
    "            , label=b)\n",
    "plt.xlabel('Wavelength ($\\AA$)')\n",
    "plt.ylabel('Transmission')\n",
    "plt.xscale('log')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.title('Passbands on {}'.format(FIELD))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### IV.a - Depth overview\n",
    "Then we plot the mean depths available across the area a given band is available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "decam_g: mean flux error: 0.31319212913513184, 3sigma in AB mag (Aperture): 23.96766976514582\n",
      "decam_r: mean flux error: 0.49817511439323425, 3sigma in AB mag (Aperture): 23.463741790203805\n",
      "decam_z: mean flux error: 0.566842257976532, 3sigma in AB mag (Aperture): 23.323541314828965\n",
      "suprime_g: mean flux error: 0.02346797101199627, 3sigma in AB mag (Aperture): 26.781008005457572\n",
      "suprime_r: mean flux error: 0.03223560005426407, 3sigma in AB mag (Aperture): 26.436357466050474\n",
      "suprime_i: mean flux error: 0.03589833527803421, 3sigma in AB mag (Aperture): 26.319511089688667\n",
      "suprime_z: mean flux error: 0.07204469293355942, 3sigma in AB mag (Aperture): 25.563191876542312\n",
      "suprime_y: mean flux error: 0.17221812903881073, 3sigma in AB mag (Aperture): 24.616999696232845\n",
      "omegacam_u: mean flux error: 0.25683921575546265, 3sigma in AB mag (Aperture): 24.18304352532092\n",
      "omegacam_g: mean flux error: 0.0991758331656456, 3sigma in AB mag (Aperture): 25.21618221914246\n",
      "omegacam_r: mean flux error: 0.10521373152732849, 3sigma in AB mag (Aperture): 25.1520158041181\n",
      "omegacam_i: mean flux error: 0.38767945766448975, 3sigma in AB mag (Aperture): 23.736014890082593\n",
      "gpc1_g: mean flux error: 2340.1041022111876, 3sigma in AB mag (Aperture): 14.284108918382508\n",
      "gpc1_r: mean flux error: 620.6933806808139, 3sigma in AB mag (Aperture): 15.72500407839501\n",
      "gpc1_i: mean flux error: 35.59435070222106, 3sigma in AB mag (Aperture): 18.828744175399272\n",
      "gpc1_z: mean flux error: 4.436678454889803, 3sigma in AB mag (Aperture): 21.0895519765161\n",
      "gpc1_y: mean flux error: 368.38374830112036, 3sigma in AB mag (Aperture): 16.29144570691073\n",
      "ukidss_y: mean flux error: 4.142264366149902, 3sigma in AB mag (Aperture): 21.164102331119032\n",
      "ukidss_j: mean flux error: 5.497151851654053, 3sigma in AB mag (Aperture): 20.85685252832493\n",
      "ukidss_h: mean flux error: 5.658304214477539, 3sigma in AB mag (Aperture): 20.825481130037325\n",
      "ukidss_k: mean flux error: 6.462373733520508, 3sigma in AB mag (Aperture): 20.68121668662902\n",
      "vista_z: mean flux error: 0.7918038368225098, 3sigma in AB mag (Aperture): 22.960652858524973\n",
      "vista_y: mean flux error: 1.6924923658370972, 3sigma in AB mag (Aperture): 22.13588006712296\n",
      "vista_j: mean flux error: 1.7619426250457764, 3sigma in AB mag (Aperture): 22.09221745776633\n",
      "vista_h: mean flux error: 2.965503692626953, 3sigma in AB mag (Aperture): 21.526950690324576\n",
      "vista_ks: mean flux error: 3.0620462894439697, 3sigma in AB mag (Aperture): 21.49216748392316\n",
      "decam_g: mean flux error: 5.940648555755615, 3sigma in AB mag (Total): 20.772612211686273\n",
      "decam_r: mean flux error: 2.843416213989258, 3sigma in AB mag (Total): 21.57259577429081\n",
      "decam_z: mean flux error: 0.5780910849571228, 3sigma in AB mag (Total): 23.30220618333589\n",
      "suprime_g: mean flux error: nan, 3sigma in AB mag (Total): nan\n",
      "suprime_r: mean flux error: 0.049323439598083496, 3sigma in AB mag (Total): 25.97456347632039\n",
      "suprime_i: mean flux error: 0.05512996390461922, 3sigma in AB mag (Total): 25.853727592869255\n",
      "suprime_z: mean flux error: 0.10940670222043991, 3sigma in AB mag (Total): 25.10958704430886\n",
      "suprime_y: mean flux error: 0.27911773324012756, 3sigma in AB mag (Total): 24.092728289502737\n",
      "omegacam_u: mean flux error: 0.44394752383232117, 3sigma in AB mag (Total): 23.588867768189836\n",
      "omegacam_g: mean flux error: 0.13682326674461365, 3sigma in AB mag (Total): 24.866796975010963\n",
      "omegacam_r: mean flux error: 0.1392875760793686, 3sigma in AB mag (Total): 24.847415911351312\n",
      "omegacam_i: mean flux error: 0.5982900857925415, 3sigma in AB mag (Total): 23.264917347576862\n",
      "gpc1_g: mean flux error: 2871.5784942368, 3sigma in AB mag (Total): 14.061895132789708\n",
      "gpc1_r: mean flux error: 1554.7747531125422, 3sigma in AB mag (Total): 14.728028163661868\n",
      "gpc1_i: mean flux error: 42.361289768808916, 3sigma in AB mag (Total): 18.639773926836646\n",
      "gpc1_z: mean flux error: 6.287417537115276, 3sigma in AB mag (Total): 20.711016107965598\n",
      "gpc1_y: mean flux error: 258.2831490542425, 3sigma in AB mag (Total): 16.676956681212012\n",
      "ukidss_y: mean flux error: 7.324713230133057, 3sigma in AB mag (Total): 20.54522029746439\n",
      "ukidss_j: mean flux error: 7.508972644805908, 3sigma in AB mag (Total): 20.518245557711886\n",
      "ukidss_h: mean flux error: 11.174776077270508, 3sigma in AB mag (Total): 20.08659978970436\n",
      "ukidss_k: mean flux error: 12.963382720947266, 3sigma in AB mag (Total): 19.925401005709254\n",
      "vista_z: mean flux error: 2.0196564197540283, 3sigma in AB mag (Total): 21.944003127327214\n",
      "vista_y: mean flux error: 4.0979905128479, 3sigma in AB mag (Total): 21.17576949159487\n",
      "vista_j: mean flux error: 4.591563701629639, 3sigma in AB mag (Total): 21.05229532836764\n",
      "vista_h: mean flux error: 7.914881706237793, 3sigma in AB mag (Total): 20.461085792214412\n",
      "vista_ks: mean flux error: 8.422895431518555, 3sigma in AB mag (Total): 20.393543340575754\n"
     ]
    }
   ],
   "source": [
    "average_depths = []\n",
    "for b in ap_bands:\n",
    "    \n",
    "    mean_err = np.nanmean(depths['ferr_ap_{}_mean'.format(b)])\n",
    "    print(\"{}: mean flux error: {}, 3sigma in AB mag (Aperture): {}\".format(b, mean_err, flux_to_mag(3.0*mean_err*1.e-6)[0]))\n",
    "    average_depths += [('ap_' + b, flux_to_mag(1.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(3.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(5.0*mean_err*1.e-6)[0])]\n",
    "    \n",
    "for b in tot_bands:\n",
    "    \n",
    "    mean_err = np.nanmean(depths['ferr_{}_mean'.format(b)])\n",
    "    print(\"{}: mean flux error: {}, 3sigma in AB mag (Total): {}\".format(b, mean_err, flux_to_mag(3.0*mean_err*1.e-6)[0]))\n",
    "    average_depths += [(b, flux_to_mag(1.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(3.0*mean_err*1.e-6)[0], \n",
    "                        flux_to_mag(5.0*mean_err*1.e-6)[0])]\n",
    "    \n",
    "average_depths = np.array(average_depths,  dtype=[('band', \"<U16\"), ('1s', float), ('3s', float), ('5s', float)])\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "def FWHM(X,Y):\n",
    "    \n",
    "    half_max = max(Y) / 2.\n",
    "    #find when function crosses line half_max (when sign of diff flips)\n",
    "    #take the 'derivative' of signum(half_max - Y[])\n",
    "    d = half_max - Y\n",
    "    #plot(X,d) #if you are interested\n",
    "    #find the left and right most indexes\n",
    "    low_end = X[np.where(d < 0)[0][0]]\n",
    "    high_end = X[np.where(d < 0)[0][-1]]\n",
    "    return low_end, high_end, (high_end - low_end)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "data = []\n",
    "\n",
    "for b in ap_bands:\n",
    "    data += [['ap_' + b, Table(data = parse_single_table(FILTERS_DIR + b +'.xml').array.data)]]\n",
    "    \n",
    "for b in tot_bands:\n",
    "    data += [[b, Table(data = parse_single_table(FILTERS_DIR + b +'.xml').array.data)]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ap_decam_g (4180.0, 5470.0, 1290.0)\n",
      "ap_decam_r (5680.0, 7150.0, 1470.0)\n",
      "ap_decam_z (8490.0, 9960.0, 1470.0)\n",
      "ap_suprime_g (4090.0, 5460.0, 1370.0)\n",
      "ap_suprime_r (5440.0, 6960.0, 1520.0)\n",
      "ap_suprime_i (6980.0, 8420.0, 1440.0)\n",
      "ap_suprime_z (8540.0, 9280.0, 740.0)\n",
      "ap_suprime_y (9360.0, 10120.0, 760.0)\n",
      "ap_omegacam_u (3296.7, 3807.9, 511.19995)\n",
      "ap_omegacam_g (4077.9, 5369.7, 1291.8003)\n",
      "ap_omegacam_r (5640.7, 6962.8, 1322.0996)\n",
      "ap_omegacam_i (6841.5, 8373.8, 1532.2998)\n",
      "ap_gpc1_g (4260.0, 5500.0, 1240.0)\n",
      "ap_gpc1_r (5500.0, 6900.0, 1400.0)\n",
      "ap_gpc1_i (6910.0, 8190.0, 1280.0)\n",
      "ap_gpc1_z (8190.0, 9210.0, 1020.0)\n",
      "ap_gpc1_y (9200.0, 9820.0, 620.0)\n",
      "ap_ukidss_y (9790.0, 10820.0, 1030.0)\n",
      "ap_ukidss_j (11695.0, 13280.0, 1585.0)\n",
      "ap_ukidss_h (14925.0, 17840.0, 2915.0)\n",
      "ap_ukidss_k (20290.0, 23820.0, 3530.0)\n",
      "ap_vista_z (8300.0, 9260.0, 960.0)\n",
      "ap_vista_y (9740.0, 10660.0, 920.0)\n",
      "ap_vista_j (11670.0, 13380.0, 1710.0)\n",
      "ap_vista_h (15000.0, 17900.0, 2900.0)\n",
      "ap_vista_ks (19930.0, 23010.0, 3080.0)\n",
      "decam_g (4180.0, 5470.0, 1290.0)\n",
      "decam_r (5680.0, 7150.0, 1470.0)\n",
      "decam_z (8490.0, 9960.0, 1470.0)\n",
      "suprime_g (4090.0, 5460.0, 1370.0)\n",
      "suprime_r (5440.0, 6960.0, 1520.0)\n",
      "suprime_i (6980.0, 8420.0, 1440.0)\n",
      "suprime_z (8540.0, 9280.0, 740.0)\n",
      "suprime_y (9360.0, 10120.0, 760.0)\n",
      "omegacam_u (3296.7, 3807.9, 511.19995)\n",
      "omegacam_g (4077.9, 5369.7, 1291.8003)\n",
      "omegacam_r (5640.7, 6962.8, 1322.0996)\n",
      "omegacam_i (6841.5, 8373.8, 1532.2998)\n",
      "gpc1_g (4260.0, 5500.0, 1240.0)\n",
      "gpc1_r (5500.0, 6900.0, 1400.0)\n",
      "gpc1_i (6910.0, 8190.0, 1280.0)\n",
      "gpc1_z (8190.0, 9210.0, 1020.0)\n",
      "gpc1_y (9200.0, 9820.0, 620.0)\n",
      "ukidss_y (9790.0, 10820.0, 1030.0)\n",
      "ukidss_j (11695.0, 13280.0, 1585.0)\n",
      "ukidss_h (14925.0, 17840.0, 2915.0)\n",
      "ukidss_k (20290.0, 23820.0, 3530.0)\n",
      "vista_z (8300.0, 9260.0, 960.0)\n",
      "vista_y (9740.0, 10660.0, 920.0)\n",
      "vista_j (11670.0, 13380.0, 1710.0)\n",
      "vista_h (15000.0, 17900.0, 2900.0)\n",
      "vista_ks (19930.0, 23010.0, 3080.0)\n"
     ]
    }
   ],
   "source": [
    "wav_range = []\n",
    "for dat in data:\n",
    "    print(dat[0], FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission'])))\n",
    "    wav_range += [[dat[0], FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission']))]]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Depths on GAMA-12')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for dat in data:\n",
    "    wav_deets = FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission']))\n",
    "    depth = average_depths['5s'][average_depths['band'] == dat[0]]\n",
    "    #print(depth)\n",
    "    plt.plot([wav_deets[0],wav_deets[1]], [depth,depth], label=dat[0])\n",
    "    \n",
    "plt.xlabel('Wavelength ($\\AA$)')\n",
    "plt.ylabel('Depth')\n",
    "plt.xscale('log')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.title('Depths on {}'.format(FIELD))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "### IV.c - Depth vs coverage comparison\n",
    "\n",
    "How best to do this? Colour/intensity plot over area? Percentage coverage vs mean depth?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Depths (5 $\\\\sigma$) vs coverage on GAMA-12')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for dat in data:\n",
    "    wav_deets = FWHM(np.array(dat[1]['Wavelength']), np.array(dat[1]['Transmission']))\n",
    "    depth = average_depths['5s'][average_depths['band'] == dat[0]]\n",
    "    #print(depth)\n",
    "    coverage = np.sum(~np.isnan(depths['ferr_{}_mean'.format(dat[0])]))/len(depths)\n",
    "    plt.plot(coverage, depth, 'x', label=dat[0])\n",
    "    \n",
    "plt.xlabel('Coverage')\n",
    "plt.ylabel('Depth')\n",
    "#plt.xscale('log')\n",
    "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)\n",
    "plt.title('Depths (5 $\\sigma$) vs coverage on {}'.format(FIELD))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (herschelhelp_internal)",
   "language": "python",
   "name": "helpint"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}