look_at_data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from astropy.table import Table\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import lsst.afw.display as afwDisplay\n",
    "from lsst.daf.persistence import Butler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from deepcoadd_afw_to_astropy import read_cats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Turn off interactive plotting by default.\n",
    "# Call plt.show() to display an interactive plot\n",
    "# Then if you want to create a new interactive plot, call\n",
    "#\n",
    "# plt.close()\n",
    "# <...new plotting commands...>\n",
    "# plt.show()\n",
    "#\n",
    "# This will result in the desired behavior that you can run the entire\n",
    "# notebook and generate each figure as an interactive figure.\n",
    "# Otherwise, if you just kept one figure interactive all plots would go to that figure.\n",
    "\n",
    "plt.ioff()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "repo = os.path.join(os.getenv('DR1BASE'), 'repo', 'test_dr1')\n",
    "rerun = os.path.join(repo, 'rerun', 'coaddPhotTest')\n",
    "\n",
    "field, tract = 'LSQ13cwp', 0\n",
    "# field = 'PTF11mty'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "J_cat, H_cat, ref_table = read_cats(field, tract=0, repo=rerun)\n",
    "\n",
    "snr_threshold = 5\n",
    "good_color = (J_cat['J_SNR'] > snr_threshold) & (H_cat['H_SNR'] > snr_threshold)\n",
    "\n",
    "J_cat = J_cat[good_color]\n",
    "H_cat = H_cat[good_color]\n",
    "ref_table = ref_table[good_color]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "butler = Butler(rerun)\n",
    "\n",
    "dId = {'field': field, 'filter': 'H', 'tract': 0, 'patch': '0,0'}\n",
    "calexp = butler.get('deepCoadd', dataId=dId)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "display = afwDisplay.getDisplay(backend='ds9')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "display.mtv(calexp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "display.setMaskTransparency(80)\n",
    "display.scale(\"asinh\", -2, 25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = calexp.getMask()\n",
    "for maskName, maskBit in mask.getMaskPlaneDict().items():\n",
    "    print('{}: {}'.format(maskName, display.getMaskPlaneColor(maskName)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "H_src = butler.get('deepCoadd_forced_src', dataId=dId )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "print([name for name in H_cat.colnames if name[:4] == 'slot'])\n",
    "X = 'slot_Centroid_x'\n",
    "Y = 'slot_Centroid_y'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "display.erase()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with display.Buffering():\n",
    "    for s in H_cat:\n",
    "        display.dot(\"o\", s[X], s[Y], size=10, ctype='orange')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_ds9_region_file(cat, galaxies, out_file='ra_dec.reg'):\n",
    "    header = \"\"\"# coord_ra, coord_dec\n",
    "global point=circle\n",
    "fk5\n",
    "\"\"\"\n",
    "    lines = [header]\n",
    "    for row, gal in zip(cat, galaxies):\n",
    "        line = \"point({ra:0.8f}, {dec:0.8f})\".format(\n",
    "            ra=np.rad2deg(row['coord_ra']), dec=np.rad2deg(row['coord_dec']))\n",
    "        if gal:\n",
    "            line += \" # point=box\"\n",
    "            \n",
    "        line += \"\\n\"\n",
    "        lines.append(line) \n",
    "    \n",
    "    with open(out_file, mode='w') as out:\n",
    "        out.writelines(lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "extendedName = \"base_ClassificationExtendedness_value\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "plt.hist(ref_table[extendedName], bins=np.linspace(-0.05, 1.05, 12), range=(-0.5, 1.5))\n",
    "plt.xlabel('ClassificationExtendness')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "extendedness_threshold = 0.95  # [2018-04-04]  It's actually currently just 0 or 1.\n",
    "stars = ref_table[extendedName] > extendedness_threshold\n",
    "gal = ref_table[extendedName] < extendedness_threshold\n",
    "# There are also NaNs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "make_ds9_region_file(H_cat, gal, out_file=\"%s.reg\" % field)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "cat = H_cat\n",
    "plt.scatter(cat[stars][\"slot_PsfShape_xx\"], cat[stars][\"slot_PsfShape_yy\"], label='Stars')\n",
    "plt.scatter(cat[gal][\"slot_PsfShape_xx\"], cat[gal][\"slot_PsfShape_yy\"], label='Galaxies')\n",
    "plt.xlabel('PsfShape xx')\n",
    "plt.ylabel('PsfShape yy')\n",
    "plt.plot([0, 25], [0, 25], linestyle='--', color='grey')\n",
    "plt.xlim(0, 25)\n",
    "plt.ylim(0, 20)\n",
    "plt.legend()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.scatter(J_cat[stars]['J_mag']-H_cat[stars]['H_mag'], J_cat[stars]['J_mag'], label='Stars')\n",
    "plt.scatter(J_cat[gal]['J_mag']-H_cat[gal]['H_mag'], J_cat[gal]['J_mag'], marker='+', label='Galaxies')\n",
    "plt.xlabel('J-H [AB mag]')\n",
    "plt.ylabel('J [AB mag]')\n",
    "plt.ylim(24, 13)\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "plt.close()\n",
    "plt.scatter(J_cat[stars]['J_mag'], H_cat[stars]['H_mag'], label='Stars')\n",
    "plt.scatter(J_cat[gal]['J_mag'], H_cat[gal]['H_mag'], marker='+', label='Galaxies')\n",
    "plt.xlabel('J [AB mag]')\n",
    "plt.ylabel('H [AB mag]')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "plt.close()\n",
    "plt.scatter(J_cat[stars]['J_mag'], J_cat[stars]['J_mag_err'], label='J stars', color='blue')\n",
    "plt.scatter(J_cat[gal]['J_mag'], J_cat[gal]['J_mag_err'], label='J galaxies', marker='+', color='blue')\n",
    "plt.scatter(H_cat[stars]['H_mag'], H_cat[stars]['H_mag_err'], label='H stars', color='green')\n",
    "plt.scatter(H_cat[gal]['H_mag'], H_cat[gal]['H_mag_err'], label='H galaxies', marker='+', color='green')\n",
    "\n",
    "plt.xlabel('AB mag')\n",
    "plt.ylabel('mag uncertainty')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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