{
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   "cell_type": "markdown",
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    "deletable": true,
    "editable": true
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   "source": [
    "# ELAIS-N2 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",
      "0246c5d (Thu Jan 25 17:01:47 2018 +0000) [with local modifications]\n",
      "This notebook was executed on: \n",
      "2018-02-27 20:46:38.136501\n"
     ]
    }
   ],
   "source": [
    "from herschelhelp_internal import git_version\n",
    "print(\"This notebook was run with herschelhelp_internal version: \\n{}\".format(git_version()))\n",
    "import datetime\n",
    "print(\"This notebook was executed on: \\n{}\".format(datetime.datetime.now()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "#%config InlineBackend.figure_format = 'svg'\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rc('figure', figsize=(10, 6))\n",
    "\n",
    "import os\n",
    "import time\n",
    "\n",
    "from astropy import units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.table import Column, Table, join\n",
    "import numpy as np\n",
    "from pymoc import MOC\n",
    "import healpy as hp\n",
    "#import pandas as pd #Astropy has group_by function so apandas isn't required.\n",
    "import seaborn as sns\n",
    "\n",
    "import warnings\n",
    "#We ignore warnings - this is a little dangerous but a huge number of warnings are generated by empty cells later\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from herschelhelp_internal.utils import inMoc, coords_to_hpidx, flux_to_mag\n",
    "from herschelhelp_internal.masterlist import find_last_ml_suffix, nb_ccplots\n",
    "\n",
    "from astropy.io.votable import parse_single_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "FIELD = 'ELAIS-N2'\n",
    "#FILTERS_DIR = \"/Users/rs548/GitHub/herschelhelp_python/database_builder/filters/\"\n",
    "FILTERS_DIR = \"/opt/herschelhelp_python/database_builder/filters/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Depth maps produced using: master_catalogue_elais-n2_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": null,
   "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": 5,
   "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": 6,
   "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": 7,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "#Downgrade the groups from order=ORDER to order=13 and then fill out the appropriate cells\n",
    "#hp.pixelfunc.ud_grade([2599293, 2599294], nside_out=hp.order2nside(13))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## II Create a table of all Order=13 healpix cells in the field and populate it\n",
    "We create a table with every order=13 healpix cell in the field MOC. We then calculate the healpix cell at lower order that the order=13 cell is in. We then fill in the depth at every order=13 cell as calculated for the lower order cell that that the order=13 cell is inside."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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": 9,
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    "depths[:10].show_in_notebook()"
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    "depths.add_column(Column(data=hp.pixelfunc.ang2pix(2**ORDER,\n",
    "                     hp.pixelfunc.pix2ang(2**13, depths['hp_idx_O_13'], nest=True)[0],\n",
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       "<thead><tr><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th>uJy</th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<tr><td>0</td><td>155039231</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039223</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039215</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039225</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039219</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039221</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039222</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039226</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039228</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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>155039229</td><td>2422487</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.824555558086</td><td>20.4518767084</td><td>1.17799665239</td><td>19.9950880879</td><td>0.993341818025</td><td>31.2425249234</td><td>1.00539012625</td><td>28.8953144064</td><td>1.168141704</td><td>61.2187612844</td><td>1.48782667998</td><td>57.1027277396</td><td>1.97889178959</td><td>106.706590925</td><td>2.54136389696</td><td>98.8802632738</td><td>4.34504931018</td><td>151.032118827</td><td>4.98429221574</td><td>134.159890995</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>0.0337288339551</td><td>2.14004225731</td><td>nan</td><td>nan</td><td>0.0389683742498</td><td>4.13383560181</td><td>nan</td><td>nan</td><td>0.194294410673</td><td>12.4583120346</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><td>nan</td><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(\"$('#table140376547795128-879303').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",
       "    $('#table140376547795128-879303').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], type: \"optionalnum\"}]\n",
       "    });\n",
       "});\n",
       "</script>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 12,
     "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": 13,
   "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": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'gpc1_g',\n",
       " 'gpc1_i',\n",
       " 'gpc1_r',\n",
       " 'gpc1_y',\n",
       " 'gpc1_z',\n",
       " 'irac_i1',\n",
       " 'irac_i2',\n",
       " 'irac_i3',\n",
       " 'irac_i4',\n",
       " 'megacam_g',\n",
       " 'megacam_i',\n",
       " 'megacam_r',\n",
       " 'megacam_u',\n",
       " 'megacam_y',\n",
       " 'megacam_z',\n",
       " 'wfc_g',\n",
       " 'wfc_i',\n",
       " 'wfc_r',\n",
       " 'wfc_u',\n",
       " 'wfc_z'}"
      ]
     },
     "execution_count": 14,
     "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": 15,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7fab7e543ba8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LB2zbti0gICDAEhYWVj969GjD999/75uQkGA4ePCg1mazsbVr156fMmWKoaam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PAAAg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\nIYQQQhTB/wfR2U4S4IEYSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fabf6442358>"
      ]
     },
     "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": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "wfc_u: mean flux error: 2.707310199737549, 3sigma in AB mag (Aperture): 21.625851814542862\n",
      "wfc_g: mean flux error: 0.8930113911628723, 3sigma in AB mag (Aperture): 22.830054366350062\n",
      "wfc_r: mean flux error: 1.1431512832641602, 3sigma in AB mag (Aperture): 22.561937592682433\n",
      "wfc_i: mean flux error: 1.8998199701309204, 3sigma in AB mag (Aperture): 22.010415741980758\n",
      "wfc_z: mean flux error: 9.140722235701249, 3sigma in AB mag (Aperture): 20.304745583224125\n",
      "gpc1_g: mean flux error: 445.76862986796755, 3sigma in AB mag (Aperture): 16.084423106802866\n",
      "gpc1_r: mean flux error: 26.65651684368098, 3sigma in AB mag (Aperture): 19.142688362321373\n",
      "gpc1_i: mean flux error: 412.04631114782217, 3sigma in AB mag (Aperture): 16.16983178704006\n",
      "gpc1_z: mean flux error: 5.721158636530188, 3sigma in AB mag (Aperture): 20.813486888029594\n",
      "gpc1_y: mean flux error: 696.8996115385006, 3sigma in AB mag (Aperture): 15.599271307105333\n",
      "megacam_u: mean flux error: 0.014376260340213776, 3sigma in AB mag (Aperture): 27.31308204113467\n",
      "megacam_g: mean flux error: 0.012265769764780998, 3sigma in AB mag (Aperture): 27.48545984199435\n",
      "megacam_r: mean flux error: 0.01957886293530464, 3sigma in AB mag (Aperture): 26.977728198064987\n",
      "megacam_z: mean flux error: 0.045153290033340454, 3sigma in AB mag (Aperture): 26.070473362996275\n",
      "irac_i1: mean flux error: 0.9869013923953526, 3sigma in AB mag (Aperture): 22.72151245892784\n",
      "irac_i2: mean flux error: 6.440256551173726, 3sigma in AB mag (Aperture): 20.68493894303895\n",
      "irac_i3: mean flux error: 5.399856515339477, 3sigma in AB mag (Aperture): 20.876241313376845\n",
      "irac_i4: mean flux error: 5.091050562440103, 3sigma in AB mag (Aperture): 20.940178337421635\n",
      "wfc_u: mean flux error: 3.8052480220794678, 3sigma in AB mag (Total): 21.25623944097965\n",
      "wfc_g: mean flux error: 2.3747789809039648, 3sigma in AB mag (Total): 21.76813887234116\n",
      "wfc_r: mean flux error: 2.972396526059261, 3sigma in AB mag (Total): 21.524430000553217\n",
      "wfc_i: mean flux error: 4.253242793789795, 3sigma in AB mag (Total): 21.135396426052814\n",
      "wfc_z: mean flux error: 18.230205535888672, 3sigma in AB mag (Total): 19.555217950395125\n",
      "gpc1_g: mean flux error: 148.4476318213597, 3sigma in AB mag (Total): 17.27826367893517\n",
      "gpc1_r: mean flux error: 17.264502802496242, 3sigma in AB mag (Total): 19.614311673970725\n",
      "gpc1_i: mean flux error: 153.745154178122, 3sigma in AB mag (Total): 17.24019327235647\n",
      "gpc1_z: mean flux error: 5.406278613566402, 3sigma in AB mag (Total): 20.874950804736493\n",
      "gpc1_y: mean flux error: 128.07595480699501, 3sigma in AB mag (Total): 17.438527857629943\n",
      "megacam_u: mean flux error: 0.01715118996798992, 3sigma in AB mag (Total): 27.12146122009596\n",
      "megacam_g: mean flux error: 0.022457983897224542, 3sigma in AB mag (Total): 26.82876994794764\n",
      "megacam_r: mean flux error: 0.029622873498061517, 3sigma in AB mag (Total): 26.52812890330987\n",
      "megacam_z: mean flux error: 0.11214411338828534, 3sigma in AB mag (Total): 25.082755658819814\n",
      "irac_i1: mean flux error: 1.204303589179223, 3sigma in AB mag (Total): 22.505356911499653\n",
      "irac_i2: mean flux error: 9.547149566373069, 3sigma in AB mag (Total): 20.25751254742918\n",
      "irac_i3: mean flux error: 5.73690816315948, 3sigma in AB mag (Total): 20.810502118899272\n",
      "irac_i4: mean flux error: 5.786097583852566, 3sigma in AB mag (Total): 20.801232478578335\n",
      "megacam_i: mean flux error: 0.07988616824150085, 3sigma in AB mag (Total): 25.451017886643093\n",
      "megacam_y: mean flux error: nan, 3sigma in AB mag (Total): nan\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": 17,
   "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": 18,
   "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": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ap_wfc_u (3355.0, 3925.0, 570.0)\n",
      "ap_wfc_g (4260.0, 5485.0, 1225.0)\n",
      "ap_wfc_r (5575.0, 6910.0, 1335.0)\n",
      "ap_wfc_i (6970.0, 8485.0, 1515.0)\n",
      "ap_wfc_z (8500.0, 9000.0, 500.0)\n",
      "ap_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_megacam_u (3500.0, 4100.0, 600.0)\n",
      "ap_megacam_g (4180.0, 5580.0, 1400.0)\n",
      "ap_megacam_r (5680.0, 6880.0, 1200.0)\n",
      "ap_megacam_z (8280.0, 9160.0, 880.0)\n",
      "ap_irac_i1 (31754.0, 39164.801, 7410.8008)\n",
      "ap_irac_i2 (39980.102, 50052.301, 10072.199)\n",
      "ap_irac_i3 (50246.301, 64096.699, 13850.398)\n",
      "ap_irac_i4 (64415.199, 92596.797, 28181.598)\n",
      "wfc_u (3355.0, 3925.0, 570.0)\n",
      "wfc_g (4260.0, 5485.0, 1225.0)\n",
      "wfc_r (5575.0, 6910.0, 1335.0)\n",
      "wfc_i (6970.0, 8485.0, 1515.0)\n",
      "wfc_z (8500.0, 9000.0, 500.0)\n",
      "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",
      "megacam_u (3500.0, 4100.0, 600.0)\n",
      "megacam_g (4180.0, 5580.0, 1400.0)\n",
      "megacam_r (5680.0, 6880.0, 1200.0)\n",
      "megacam_z (8280.0, 9160.0, 880.0)\n",
      "irac_i1 (31754.0, 39164.801, 7410.8008)\n",
      "irac_i2 (39980.102, 50052.301, 10072.199)\n",
      "irac_i3 (50246.301, 64096.699, 13850.398)\n",
      "irac_i4 (64415.199, 92596.797, 28181.598)\n",
      "megacam_i (6831.7305, 8388.5557, 1556.8252)\n",
      "megacam_y (7040.0, 8360.0, 1320.0)\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": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7fab7c887e80>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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ramq6vNadscJO/YJVbiIioh+muXPnXs7MzAyMiIiIj4iIuKLT6eoBwNvb21lYWOizadMm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\npryUrZYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fab7e7256a0>"
      ]
     },
     "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": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7fab7c619cc0>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Dq9VeklKKpKQkOwAkJiY2VFRUeAYGBl5X7hISEnIlPT29bO7cuREOhwNqtfrykSNHTnU0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fab7c738b38>"
      ]
     },
     "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
}