{
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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": {
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    "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",
      "2018-06-25 13:16:47.114108\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_20180218.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>7.244427e-07</td><td>3.047033242182806e-05</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>7.244427e-07</td><td>3.047033242182806e-05</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>7.244427e-07</td><td>3.047033242182806e-05</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>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>7.244427e-07</td><td>3.047033242182806e-05</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>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>7.244427e-07</td><td>3.047033242182806e-05</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>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>5.812783e-07</td><td>4.217899695504457e-05</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>418871036</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>5.812783e-07</td><td>4.217899695504457e-05</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>418871001</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>5.812783e-07</td><td>4.217899695504457e-05</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>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>5.812783e-07</td><td>4.217899695504457e-05</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>418870998</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>5.812783e-07</td><td>4.217899695504457e-05</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(\"$('#table139639990186952-987701').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",
       "    $('#table139639990186952-987701').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,'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": {},
     "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: 3.1319208915192576e-07, 3sigma in AB mag (Aperture): 38.967669903754704\n",
      "decam_r: mean flux error: 4.981751544619328e-07, 3sigma in AB mag (Aperture): 38.46374170287702\n",
      "decam_z: mean flux error: 5.668424591931398e-07, 3sigma in AB mag (Aperture): 38.32354092941642\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: 13680.875, 3sigma in AB mag (Total): 12.366912176115015\n",
      "decam_r: mean flux error: 39934.17578125, 3sigma in AB mag (Total): 11.20383505002814\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,'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": {},
     "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 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": {},
     "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
}