{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using the LSST Stack tools to do positional matching on coadd and src catalogs\n",
    "<br>Owner: **Jim Chiang** ([@jchiang87](https://github.com/LSSTDESC/DC2-analysis/issues/new?body=@jchiang87))\n",
    "<br>Updated by: **Javier Sánchez** ([@fjaviersanchez](https://github.com/LSSTDESC/DC2-analysis/issues/new?body=@fjaviersanchez))\n",
    "<br>Last Run: **2020-06-12**\n",
    "\n",
    "In this notebook, we use the data butler to retrieve catalogs from coadd and visit-level analyses of Run2.2i, and use the `lsst.afw.table.matchRaDec` function to do positional matching against galaxy truth info extracted from the cosmoDC2 v1.1.4 extragalactic catalog.  To enable this, we show how to create a `SourceCatalog` object from the galaxy truth info provided by the GCR interface.\n",
    "\n",
    "## Set Up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "from collections import namedtuple\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import lsst.afw.geom as afw_geom\n",
    "import lsst.afw.table as afw_table\n",
    "import lsst.daf.persistence as dp\n",
    "import GCRCatalogs\n",
    "import healpy as hp\n",
    "import lsst.geom"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## How To Create a Source Catalog\n",
    "\n",
    "In order to use the Stack's spatial matching code, we will need to reformat the extragalactic catalog galaxy position and magnitude information into an afw `SourceCatalog` object. These table objects are initialized by a \"schema\", which in turn is built from column definition \"Coldef\" objects.  The `mag_cols` function below shows how these Coldefs can be created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_SourceCatalog(new_cols):\n",
    "    \"\"\"\n",
    "    Make a SourceCatalog to contain id and coordinates for each object, plus any new\n",
    "    columns.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    new_cols: list of Coldefs\n",
    "        Column info for adding to an afw.table schema.\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    lsst.afw.table.SourceCatalog: An empty SourceCatalog with the desired schema.\n",
    "    \"\"\"\n",
    "    # The minimal schema just contains the `id`, `coord_ra`, and `coord_dec` fields.\n",
    "    schema = afw_table.SourceTable.makeMinimalSchema()\n",
    "    for coldef in new_cols:\n",
    "        schema.addField(coldef.name, type=coldef.type, doc=coldef.doc)\n",
    "    return afw_table.SourceCatalog(schema)\n",
    "\n",
    "\n",
    "def mag_cols(bands):\n",
    "    \"\"\"Return column information for adding magnitude columns to an afw.table schema.\"\"\"\n",
    "    Coldef = namedtuple('Coldef', 'name type doc'.split())\n",
    "    return [Coldef(f'mag_{x}', float, f'{x}-magnitude')\n",
    "            for x in bands]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Selecting Galaxies\n",
    "\n",
    "We are going to downselect cosmoDC2 to the sky region being considered. We'll make a general-purpose RegionSelector class, and then sub-class it for selecting objects in either CCDs or patches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class RegionSelector:\n",
    "    \"\"\"\n",
    "    Class to rotate the protoDC2 galaxies to the Run1.1p sky location and downselect those galaxies\n",
    "    based on a magnitude limit and on the coordinates of the subregion (i.e., patch or CCD) being\n",
    "    considered.\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self):\n",
    "        pass\n",
    "    \n",
    "    def _set_coord_range(self, bbox, wcs):\n",
    "        \"\"\"\n",
    "        Set the coordinate range of the region.\n",
    "        \n",
    "        Notes\n",
    "        -----\n",
    "        This method is used by the RegionSelector's subclasses.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        bbox: Calexp.BBox\n",
    "            Defines corners of region's bounding box\n",
    "        wcs: Calexp.Wcs\n",
    "            Defines pixel to world (sky) coordinate transformation\n",
    "        \"\"\"\n",
    "        region_box = lsst.geom.Box2D(bbox)\n",
    "        corners = region_box.getCorners()\n",
    "        ra_values, dec_values = [], []\n",
    "        for corner in corners:\n",
    "            ra, dec = wcs.pixelToSky(corner)\n",
    "            ra_values.append(ra.asDegrees())\n",
    "            dec_values.append(dec.asDegrees())\n",
    "        self.ra_range = min(ra_values), max(ra_values)\n",
    "        self.dec_range = min(dec_values), max(dec_values)\n",
    "\n",
    "    def __call__(self, gc, band, max_mag):\n",
    "        \"\"\"\n",
    "        Create a SourceCatalog object from the input galaxy catalog for the specified band, and\n",
    "        apply the region and magnitude cuts.\n",
    "\n",
    "        Parameters\n",
    "        ----------\n",
    "        gc: GCRCatalogs GalaxyCatalog\n",
    "            The galaxy catalog obtained via GCR.\n",
    "        band: str\n",
    "            The band, e.g., 'i', to use for the magnitude comparison with the values measured\n",
    "            from the simulated data.\n",
    "        max_mag: float\n",
    "            The magnitude limit to apply.\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        lsst.afw.table.SourceCatalog\n",
    "        \"\"\"\n",
    "        # Retrieve the healpix pixels corresponding to the catalog so we don't query the full catalog\n",
    "        vertices = hp.ang2vec(np.array([self.ra_range[0], self.ra_range[1],\n",
    "                                        self.ra_range[1], self.ra_range[0]]),\n",
    "                              np.array([self.dec_range[0], self.dec_range[0],\n",
    "                                        self.dec_range[1], self.dec_range[1]]), lonlat=True)\n",
    "        ipix = hp.query_polygon(32, vertices, inclusive=True)\n",
    "        # We are going to pass the healpixels that overlap with our catalog as native filters to speed up the process\n",
    "        native_filter = f'(healpix_pixel == {ipix[0]})'\n",
    "        for ipx in ipix:\n",
    "            native_filter=native_filter+f' | (healpix_pixel == {ipx})'\n",
    "        # Retrieve the desired columns and cut on the magnitude values.\n",
    "        bandname = f'mag_{band}'\n",
    "        filter_ = f'{bandname} < {max_mag}'\n",
    "        print(\"Applying magnitude filter:\", filter_)\n",
    "        gc_cols = gc.get_quantities(['galaxy_id', 'ra', 'dec',\n",
    "                                     bandname], filters=[filter_, \n",
    "                                                         f'ra > {self.ra_range[0]}',\n",
    "                                                         f'ra < {self.ra_range[1]}',\n",
    "                                                         f'dec > {self.dec_range[0]}',\n",
    "                                                         f'dec < {self.dec_range[1]}',\n",
    "                                                        ],\n",
    "                                    native_filters = native_filter)\n",
    "        print(\"Number of galaxies within region:\", len(gc_cols['ra']))\n",
    "\n",
    "        # Create a SourceCatalog with the galaxy_ids, coordinates, magnitudes\n",
    "        galaxy_catalog = make_SourceCatalog(mag_cols((band,)))\n",
    "        for id_, ra, dec, mag in zip(gc_cols['galaxy_id'], gc_cols['ra'], gc_cols['dec'], gc_cols[bandname]):\n",
    "            record = galaxy_catalog.addNew()\n",
    "            record.set('id', id_)\n",
    "            record.set('coord_ra', lsst.geom.Angle(ra, lsst.geom.degrees))\n",
    "            record.set('coord_dec', lsst.geom.Angle(dec, lsst.geom.degrees))\n",
    "            record.set(f'mag_{band}', mag)\n",
    "        return galaxy_catalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CcdSelector(RegionSelector):\n",
    "    \"\"\"RegionSelector to use with visit-level calexps, i.e., single CCD exposures.\"\"\"\n",
    "    def __init__(self, butler, visit, raft, sensor):\n",
    "        super(CcdSelector, self).__init__()\n",
    "        # Get the CCD boundaries\n",
    "        dataId = dict(visit=visit, raft=raft, sensor=sensor)\n",
    "        calexp = butler.get('calexp', dataId=dataId)\n",
    "        self._set_coord_range(calexp.getBBox(), calexp.getWcs())\n",
    "\n",
    "\n",
    "class PatchSelector(RegionSelector):\n",
    "    \"\"\"RegionSelector to use with skyMap patches, i.e., coadd data.\"\"\"\n",
    "    def __init__(self, butler, tract, patch):\n",
    "        super(PatchSelector, self).__init__()\n",
    "        # Get the patch boundaries.\n",
    "        skymap = butler.get('deepCoadd_skyMap')\n",
    "        tractInfo = skymap[tract]\n",
    "        patchInfo = tractInfo.getPatchInfo(eval(patch))\n",
    "        self._set_coord_range(patchInfo.getOuterBBox(), tractInfo.getWcs())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Matching Experiments\n",
    "\n",
    "Now we have the tools we need, let's read in the Run 2.2i-DR3 coadd catalog data and match it to the extragalactic catalog input. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a data butler for the repo.\n",
    "repo = '/global/cfs/cdirs/lsst/production/DC2_ImSim/Run2.2i/desc_dm_drp/v19.0.0-v1/rerun/run2.2i-coadd-wfd-dr3-v1'\n",
    "butler = dp.Butler(repo)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sources or Objects?\n",
    "\n",
    "We can consider visit-level src catalog data, in which case we would provide a `dataId` to the butler with (`visit`, `raft`, `sensor`) ids; or we can consider coadd object data, for which we would provid a `dataId` with (`filter`, `tract`, `patch`) ids.\n",
    "\n",
    "Somewhat different flux models are available in the Run2.2i data for src catalogs versus coadd catalogs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "mag_max = 24.5\n",
    "# we_are_matching = \"Sources\"\n",
    "we_are_matching = \"Objects\"\n",
    "\n",
    "if we_are_matching == \"Sources\":\n",
    "    # Get the src catalog for a selected visit, raft, and sensor:\n",
    "    visit = 219976\n",
    "    raft = '2,2'\n",
    "    sensor = '1,1'\n",
    "    title = f'Run2.2i-DR3, visit={visit}, raft={raft}, sensor={sensor}'\n",
    "    dataId = dict(visit=visit, raft=raft, sensor=sensor)\n",
    "    catalog = butler.get('src', dataId=dataId)\n",
    "    calexp = butler.get('calexp', dataId=dataId)\n",
    "    filter_ = calexp.getInfo().getFilter().getFilter()\n",
    "    calib = calexp.getPhotoCalib()\n",
    "    #flux_model = 'ext_photometryKron_KronFlux'\n",
    "    flux_model = 'modelfit_CModel'\n",
    "    region_selector = CcdSelector(butler, visit, raft, sensor)\n",
    "\n",
    "else:\n",
    "    # Get the coadd catalog for a selected filter, tract, and patch:\n",
    "    filter_ = 'r'\n",
    "    tract = 4638\n",
    "    patch = '2,2'\n",
    "    title = f'Run2.2i-DR3, filter={filter_}, tract={tract}, patch={patch}'\n",
    "    dataId = dict(tract=tract, patch=patch, filter=filter_)\n",
    "    catalog = butler.get('deepCoadd_meas', dataId=dataId)\n",
    "    calexp = butler.get('deepCoadd', dataId=dataId)\n",
    "    calib = calexp.getPhotoCalib()\n",
    "    flux_model = 'modelfit_CModel'\n",
    "    region_selector = PatchSelector(butler, tract, patch)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Focusing on Well-measured Galaxies\n",
    "\n",
    "Galaxies can be selected as extended objects (or sources) using the `base_ClassificationExtendedness_value`. We use the model flag and flux to ensure that a flux value could be measured, and then apply a selection to ensure that we get deblended objects. Finally, we apply a relatively bright magnitude cut, to avoid confusion when performing the positional match."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of observed objects in our DRP galaxy catalog 3658\n"
     ]
    }
   ],
   "source": [
    "# Extract columns to use in the selection:\n",
    "ext = catalog.get('base_ClassificationExtendedness_value')\n",
    "model_flag = catalog.get(flux_model + '_flag')\n",
    "model_flux = catalog.get(flux_model + '_instFlux')\n",
    "num_children = catalog.get('deblend_nChild')\n",
    "\n",
    "# Apply the extendedness, flag, and blendedness cuts using the subset method:\n",
    "cat_temp = catalog.subset((ext == 1) &\n",
    "                          (model_flag == False) &\n",
    "                          (model_flux > 0) &\n",
    "                          (num_children == 0))\n",
    "# Extract the magnitude and again use subset to apply the depth cut:\n",
    "_mag = calib.instFluxToMagnitude(cat_temp, flux_model) \n",
    "mag = _mag[:,0] #Magnitude\n",
    "magerr = _mag[:,1] #Magnitude Error\n",
    "#print(mag, len(mag))\n",
    "cat_temp = cat_temp.subset(mag < mag_max)\n",
    "\n",
    "# Repackage everything in a more minimal SourceCatalog and add a magnitude column for comparing\n",
    "# to the galaxy catalog truth values.\n",
    "drp_catalog = make_SourceCatalog(mag_cols((filter_,)))\n",
    "for record in cat_temp:\n",
    "    new_rec = drp_catalog.addNew()\n",
    "    for name in 'id coord_ra coord_dec parent'.split():\n",
    "        new_rec.set(name, record[name])\n",
    "    mag = calib.instFluxToMagnitude(record, flux_model)\n",
    "    new_rec.set(f'mag_{filter_}', mag.value)\n",
    "                \n",
    "print(\"Number of observed objects in our DRP galaxy catalog\", len(drp_catalog))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting the Truth Info\n",
    "\n",
    "We can now use our region_selector object to process the protoDC2 extragalactic catalog. Note that while we instantiated it with a butler, so that it could work on selecting galaxy observations from either a tract or a CCD, we can _call_ it as a function (via its `__call__` method) which takes a GCR catalog object as its first argument. The result will be a DM Stack SourceCatalog object, that we can match to our observed DRP catalog."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in the galaxy catalog data.\n",
    "with warnings.catch_warnings():\n",
    "    warnings.filterwarnings('ignore')\n",
    "    gc = GCRCatalogs.load_catalog('cosmoDC2_v1.1.4_image')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Applying magnitude filter: mag_r < 24.5\n",
      "Number of galaxies within region: 3784\n"
     ]
    }
   ],
   "source": [
    "# Create a SourceCatalog from the gc data, applying the region and magnitude selections.\n",
    "galaxy_catalog = region_selector(gc, band=filter_, max_mag=mag_max)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the number of galaxies within our region with th enumber of observed galaxies in the DRP catalog. Is this what you would expect?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Doing the Matching\n",
    "We can now carry out the spatial matching, and compute some quantities to plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find positional matches within 100 milliarcseconds:\n",
    "radius = lsst.geom.Angle(0.1, lsst.geom.arcseconds)\n",
    "matches = afw_table.matchRaDec(drp_catalog, galaxy_catalog, radius)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`matches` is a list of `match` objects, each one containing an observed-true matchd galaxy pair. The code below shows how to work with these, looping over the matches and extracting information to plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of matches: 2951\n"
     ]
    }
   ],
   "source": [
    "# Compare magnitudes for matched objects:\n",
    "drp_mag = np.zeros(len(matches), dtype=np.float)\n",
    "gc_mag = np.zeros(len(matches), dtype=np.float)\n",
    "sep = np.zeros(len(matches), dtype=np.float)\n",
    "# Arrays for a quiver plot.\n",
    "u = np.zeros(len(matches), dtype=np.float)\n",
    "v = np.zeros(len(matches), dtype=np.float)\n",
    "for i, match in enumerate(matches):\n",
    "    drp_mag[i] = match.first[f'mag_{filter_}']\n",
    "    gc_mag[i] = match.second[f'mag_{filter_}']\n",
    "    sep[i] = np.degrees(match.distance)*3600.*1000.\n",
    "    u[i] = match.first['coord_ra'] - match.second['coord_ra']\n",
    "    v[i] = match.first['coord_dec'] - match.second['coord_dec']\n",
    "print(\"Number of matches:\", len(matches))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x800 with 5 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 765,
       "width": 766
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Start a 2x2 panel figure:\n",
    "fig = plt.figure(figsize=(8, 8))\n",
    "frame_axes = fig.add_subplot(111, frameon=False)\n",
    "frame_axes.set_title(title)\n",
    "frame_axes.get_xaxis().set_ticks([])\n",
    "frame_axes.get_yaxis().set_ticks([])\n",
    "\n",
    "delta_mag = drp_mag - gc_mag  # Observed - True\n",
    "\n",
    "# Upper Left: Histogram of match separations.\n",
    "fig.add_subplot(2, 2, 1)\n",
    "plt.hist(sep, range=(0, 100), histtype='step', bins=40)\n",
    "plt.xlabel('separation (marcsec)')\n",
    "plt.ylabel('entries / bin')\n",
    "\n",
    "# Upper Right: Quiver plot of (DRP - galaxy_catalog) positions on the sky.\n",
    "fig.add_subplot(2, 2, 2)\n",
    "plt.quiver(np.degrees(drp_catalog['coord_ra']),\n",
    "           np.degrees(drp_catalog['coord_dec']),\n",
    "           u, v)\n",
    "plt.xlabel('RA (deg)')\n",
    "plt.ylabel('Dec (deg)')\n",
    "\n",
    "# Lower left: Difference in magnitudes vs true magnitude (mag_gc).\n",
    "fig.add_subplot(2, 2, 3)\n",
    "plt.errorbar(gc_mag, delta_mag, fmt='.', alpha=0.1)\n",
    "plt.xlabel(f'True mag {filter_}_gc'.format(filter_))\n",
    "plt.ylabel(f'Mag difference ({filter_}_gc - {filter_}_drp)')\n",
    "\n",
    "# Difference in magnitudes vs separation.\n",
    "fig.add_subplot(2, 2, 4)\n",
    "plt.errorbar(sep, delta_mag, fmt='.', alpha=0.1)\n",
    "plt.xlabel('separation (mas)')\n",
    "plt.ylabel(f'Mag difference ({filter_}_gc - {filter_}_drp)')\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Going Further\n",
    "\n",
    "The available columns in a `SourceCatalog` can be seen by printing the info from the schema that it carries around with it. The cells below show you what you have available. The drp_catalog and galaxy_catalog that we made to do the spatial matching only have positions and magnitudes in them - but the parent catalogs have many more quantities. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id:  unique ID\n",
      "coord_ra:  position in ra/dec\n",
      "coord_dec:  position in ra/dec\n",
      "parent:  unique ID of parent source\n",
      "mag_r:  r-magnitude\n"
     ]
    }
   ],
   "source": [
    "for item in drp_catalog.schema:\n",
    "    print(f\"{item.field.getName()}:  {item.field.getDoc()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id:  unique ID\n",
      "coord_ra:  position in ra/dec\n",
      "coord_dec:  position in ra/dec\n",
      "parent:  unique ID of parent source\n",
      "mag_r:  r-magnitude\n"
     ]
    }
   ],
   "source": [
    "for item in galaxy_catalog.schema:\n",
    "    print(f\"{item.field.getName()}:  {item.field.getDoc()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "id:  unique ID\n",
      "coord_ra:  position in ra/dec\n",
      "coord_dec:  position in ra/dec\n",
      "parent:  unique ID of parent source\n",
      "merge_footprint_i:  Detection footprint overlapped with a detection from filter i\n",
      "merge_footprint_r:  Detection footprint overlapped with a detection from filter r\n",
      "merge_footprint_z:  Detection footprint overlapped with a detection from filter z\n",
      "merge_footprint_y:  Detection footprint overlapped with a detection from filter y\n",
      "merge_footprint_g:  Detection footprint overlapped with a detection from filter g\n",
      "merge_footprint_u:  Detection footprint overlapped with a detection from filter u\n",
      "merge_footprint_sky:  Detection footprint overlapped with a detection from filter sky\n",
      "merge_peak_i:  Peak detected in filter i\n",
      "merge_peak_r:  Peak detected in filter r\n",
      "merge_peak_z:  Peak detected in filter z\n",
      "merge_peak_y:  Peak detected in filter y\n",
      "merge_peak_g:  Peak detected in filter g\n",
      "merge_peak_u:  Peak detected in filter u\n",
      "merge_peak_sky:  Peak detected in filter sky\n",
      "deblend_nChild:  Number of children this object has (defaults to 0)\n",
      "deblend_deblendedAsPsf:  Deblender thought this source looked like a PSF\n",
      "deblend_psfCenter_x:  If deblended-as-psf, the PSF centroid\n",
      "deblend_psfCenter_y:  If deblended-as-psf, the PSF centroid\n",
      "deblend_psf_instFlux:  If deblended-as-psf, the instrumental PSF flux\n",
      "deblend_tooManyPeaks:  Source had too many peaks; only the brightest were included\n",
      "deblend_parentTooBig:  Parent footprint covered too many pixels\n",
      "deblend_masked:  Parent footprint was predominantly masked\n",
      "deblend_skipped:  Deblender skipped this source\n",
      "deblend_rampedTemplate:  This source was near an image edge and the deblender used \"ramp\" edge-handling.\n",
      "deblend_patchedTemplate:  This source was near an image edge and the deblender used \"patched\" edge-handling.\n",
      "deblend_hasStrayFlux:  This source was assigned some stray flux\n",
      "base_NaiveCentroid_x:  centroid from Naive Centroid algorithm\n",
      "base_NaiveCentroid_y:  centroid from Naive Centroid algorithm\n",
      "base_NaiveCentroid_flag:  General Failure Flag\n",
      "base_NaiveCentroid_flag_noCounts:  Object to be centroided has no counts\n",
      "base_NaiveCentroid_flag_edge:  Object too close to edge\n",
      "base_NaiveCentroid_flag_resetToPeak:  set if CentroidChecker reset the centroid\n",
      "base_SdssCentroid_x:  centroid from Sdss Centroid algorithm\n",
      "base_SdssCentroid_y:  centroid from Sdss Centroid algorithm\n",
      "base_SdssCentroid_xErr:  1-sigma uncertainty on x position\n",
      "base_SdssCentroid_yErr:  1-sigma uncertainty on y position\n",
      "base_SdssCentroid_flag:  General Failure Flag\n",
      "base_SdssCentroid_flag_edge:  Object too close to edge\n",
      "base_SdssCentroid_flag_noSecondDerivative:  Vanishing second derivative\n",
      "base_SdssCentroid_flag_almostNoSecondDerivative:  Almost vanishing second derivative\n",
      "base_SdssCentroid_flag_notAtMaximum:  Object is not at a maximum\n",
      "base_SdssCentroid_flag_resetToPeak:  set if CentroidChecker reset the centroid\n",
      "base_SdssCentroid_flag_badError:  Error on x and/or y position is NaN\n",
      "base_Blendedness_old:  Blendedness from dot products: (child.dot(parent)/child.dot(child) - 1)\n",
      "base_Blendedness_raw:  Measure of how much the flux is affected by neighbors: (1 - child_instFlux/parent_instFlux).  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_raw_child_instFlux:  Instrumental flux of the child, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_raw_parent_instFlux:  Instrumental flux of the parent, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_abs:  Measure of how much the flux is affected by neighbors: (1 - child_instFlux/parent_instFlux).  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_abs_child_instFlux:  Instrumental flux of the child, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_abs_parent_instFlux:  Instrumental flux of the parent, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_raw_child_xx:  Shape of the child, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_raw_child_yy:  Shape of the child, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_raw_child_xy:  Shape of the child, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_raw_parent_xx:  Shape of the parent, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_raw_parent_yy:  Shape of the parent, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_raw_parent_xy:  Shape of the parent, measured with a Gaussian weight matched to the child.  Operates on the \"raw\" pixel values.\n",
      "base_Blendedness_abs_child_xx:  Shape of the child, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_abs_child_yy:  Shape of the child, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_abs_child_xy:  Shape of the child, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_abs_parent_xx:  Shape of the parent, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_abs_parent_yy:  Shape of the parent, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_abs_parent_xy:  Shape of the parent, measured with a Gaussian weight matched to the child.  Operates on the absolute value of the pixels to try to obtain a \"de-noised\" value.  See section 4.9.11 of Bosch et al. 2018, PASJ, 70, S5 for details.\n",
      "base_Blendedness_flag:  General Failure Flag\n",
      "base_Blendedness_flag_noCentroid:  Object has no centroid\n",
      "base_Blendedness_flag_noShape:  Object has no shape\n",
      "base_InputCount_flag:  Set for any fatal failure\n",
      "base_InputCount_value:  Number of images contributing at center, not including anyclipping\n",
      "base_InputCount_flag_noInputs:  No coadd inputs available\n",
      "base_SdssShape_xx:  elliptical Gaussian adaptive moments\n",
      "base_SdssShape_yy:  elliptical Gaussian adaptive moments\n",
      "base_SdssShape_xy:  elliptical Gaussian adaptive moments\n",
      "base_SdssShape_xxErr:  Standard deviation of xx moment\n",
      "base_SdssShape_yyErr:  Standard deviation of yy moment\n",
      "base_SdssShape_xyErr:  Standard deviation of xy moment\n",
      "base_SdssShape_x:  elliptical Gaussian adaptive moments\n",
      "base_SdssShape_y:  elliptical Gaussian adaptive moments\n",
      "base_SdssShape_instFlux:  elliptical Gaussian adaptive moments\n",
      "base_SdssShape_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_SdssShape_psf_xx:  adaptive moments of the PSF model at the object position\n",
      "base_SdssShape_psf_yy:  adaptive moments of the PSF model at the object position\n",
      "base_SdssShape_psf_xy:  adaptive moments of the PSF model at the object position\n",
      "base_SdssShape_instFlux_xx_Cov:  uncertainty covariance between base_SdssShape_instFlux and base_SdssShape_xx\n",
      "base_SdssShape_instFlux_yy_Cov:  uncertainty covariance between base_SdssShape_instFlux and base_SdssShape_yy\n",
      "base_SdssShape_instFlux_xy_Cov:  uncertainty covariance between base_SdssShape_instFlux and base_SdssShape_xy\n",
      "base_SdssShape_flag:  General Failure Flag\n",
      "base_SdssShape_flag_unweightedBad:  Both weighted and unweighted moments were invalid\n",
      "base_SdssShape_flag_unweighted:  Weighted moments converged to an invalid value; using unweighted moments\n",
      "base_SdssShape_flag_shift:  centroid shifted by more than the maximum allowed amount\n",
      "base_SdssShape_flag_maxIter:  Too many iterations in adaptive moments\n",
      "base_SdssShape_flag_psf:  Failure in measuring PSF model shape\n",
      "ext_shapeHSM_HsmPsfMoments_x:  HSM Centroid\n",
      "ext_shapeHSM_HsmPsfMoments_y:  HSM Centroid\n",
      "ext_shapeHSM_HsmPsfMoments_xx:  HSM moments\n",
      "ext_shapeHSM_HsmPsfMoments_yy:  HSM moments\n",
      "ext_shapeHSM_HsmPsfMoments_xy:  HSM moments\n",
      "ext_shapeHSM_HsmPsfMoments_flag:  general failure flag, set if anything went wrong\n",
      "ext_shapeHSM_HsmPsfMoments_flag_no_pixels:  no pixels to measure\n",
      "ext_shapeHSM_HsmPsfMoments_flag_not_contained:  center not contained in footprint bounding box\n",
      "ext_shapeHSM_HsmPsfMoments_flag_parent_source:  parent source, ignored\n",
      "ext_shapeHSM_HsmShapeRegauss_e1:  PSF-corrected shear using Hirata & Seljak (2003) ''regaussianization\n",
      "ext_shapeHSM_HsmShapeRegauss_e2:  PSF-corrected shear using Hirata & Seljak (2003) ''regaussianization\n",
      "ext_shapeHSM_HsmShapeRegauss_sigma:  PSF-corrected shear using Hirata & Seljak (2003) ''regaussianization\n",
      "ext_shapeHSM_HsmShapeRegauss_resolution:  resolution factor (0=unresolved, 1=resolved)\n",
      "ext_shapeHSM_HsmShapeRegauss_flag:  general failure flag, set if anything went wrong\n",
      "ext_shapeHSM_HsmShapeRegauss_flag_no_pixels:  no pixels to measure\n",
      "ext_shapeHSM_HsmShapeRegauss_flag_not_contained:  center not contained in footprint bounding box\n",
      "ext_shapeHSM_HsmShapeRegauss_flag_parent_source:  parent source, ignored\n",
      "ext_shapeHSM_HsmShapeRegauss_flag_galsim:  GalSim failure\n",
      "ext_shapeHSM_HsmSourceMoments_x:  HSM Centroid\n",
      "ext_shapeHSM_HsmSourceMoments_y:  HSM Centroid\n",
      "ext_shapeHSM_HsmSourceMoments_xx:  HSM moments\n",
      "ext_shapeHSM_HsmSourceMoments_yy:  HSM moments\n",
      "ext_shapeHSM_HsmSourceMoments_xy:  HSM moments\n",
      "ext_shapeHSM_HsmSourceMoments_flag:  general failure flag, set if anything went wrong\n",
      "ext_shapeHSM_HsmSourceMoments_flag_no_pixels:  no pixels to measure\n",
      "ext_shapeHSM_HsmSourceMoments_flag_not_contained:  center not contained in footprint bounding box\n",
      "ext_shapeHSM_HsmSourceMoments_flag_parent_source:  parent source, ignored\n",
      "ext_shapeHSM_HsmSourceMomentsRound_x:  HSM Centroid\n",
      "ext_shapeHSM_HsmSourceMomentsRound_y:  HSM Centroid\n",
      "ext_shapeHSM_HsmSourceMomentsRound_xx:  HSM moments\n",
      "ext_shapeHSM_HsmSourceMomentsRound_yy:  HSM moments\n",
      "ext_shapeHSM_HsmSourceMomentsRound_xy:  HSM moments\n",
      "ext_shapeHSM_HsmSourceMomentsRound_flag:  general failure flag, set if anything went wrong\n",
      "ext_shapeHSM_HsmSourceMomentsRound_flag_no_pixels:  no pixels to measure\n",
      "ext_shapeHSM_HsmSourceMomentsRound_flag_not_contained:  center not contained in footprint bounding box\n",
      "ext_shapeHSM_HsmSourceMomentsRound_flag_parent_source:  parent source, ignored\n",
      "ext_shapeHSM_HsmSourceMomentsRound_Flux:  HSM flux\n",
      "modelfit_DoubleShapeletPsfApprox_0_xx:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_yy:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_xy:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_x:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_y:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_0:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_1:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_2:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_3:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_4:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_0_5:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_xx:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_yy:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_xy:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_x:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_y:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_0:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_1:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_1_2:  Double-Shapelet approximation to the PSF model at the position of this source\n",
      "modelfit_DoubleShapeletPsfApprox_flag:  General Failure Flag\n",
      "modelfit_DoubleShapeletPsfApprox_flag_invalidPointForPsf:  PSF model could not be evaluated at the source position\n",
      "modelfit_DoubleShapeletPsfApprox_flag_invalidMoments:  Moments of the PSF model were not a valid ellipse\n",
      "modelfit_DoubleShapeletPsfApprox_flag_maxIterations:  optimizer exceeded the maximum number (inner or outer) iterations\n",
      "base_CircularApertureFlux_3_0_instFlux:  instFlux within 3.000000-pixel aperture\n",
      "base_CircularApertureFlux_3_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_3_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_3_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_3_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "base_CircularApertureFlux_4_5_instFlux:  instFlux within 4.500000-pixel aperture\n",
      "base_CircularApertureFlux_4_5_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_4_5_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_4_5_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_4_5_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "base_CircularApertureFlux_6_0_instFlux:  instFlux within 6.000000-pixel aperture\n",
      "base_CircularApertureFlux_6_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_6_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_6_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_6_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "base_CircularApertureFlux_9_0_instFlux:  instFlux within 9.000000-pixel aperture\n",
      "base_CircularApertureFlux_9_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_9_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_9_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_9_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "base_CircularApertureFlux_12_0_instFlux:  instFlux within 12.000000-pixel aperture\n",
      "base_CircularApertureFlux_12_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_12_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_12_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_12_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "base_CircularApertureFlux_17_0_instFlux:  instFlux within 17.000000-pixel aperture\n",
      "base_CircularApertureFlux_17_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_17_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_17_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_25_0_instFlux:  instFlux within 25.000000-pixel aperture\n",
      "base_CircularApertureFlux_25_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_25_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_25_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_35_0_instFlux:  instFlux within 35.000000-pixel aperture\n",
      "base_CircularApertureFlux_35_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_35_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_35_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_50_0_instFlux:  instFlux within 50.000000-pixel aperture\n",
      "base_CircularApertureFlux_50_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_50_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_50_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_CircularApertureFlux_70_0_instFlux:  instFlux within 70.000000-pixel aperture\n",
      "base_CircularApertureFlux_70_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_CircularApertureFlux_70_0_flag:  General Failure Flag\n",
      "base_CircularApertureFlux_70_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "base_GaussianFlux_instFlux:  instFlux from Gaussian Flux algorithm\n",
      "base_GaussianFlux_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_GaussianFlux_flag:  General Failure Flag\n",
      "base_LocalBackground_instFlux:  background in annulus around source\n",
      "base_LocalBackground_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_LocalBackground_flag:  General Failure Flag\n",
      "base_LocalBackground_flag_noGoodPixels:  no good pixels in the annulus\n",
      "base_LocalBackground_flag_noPsf:  no PSF provided\n",
      "base_PixelFlags_flag:  General failure flag, set if anything went wrong\n",
      "base_PixelFlags_flag_offimage:  Source center is off image\n",
      "base_PixelFlags_flag_edge:  Source is outside usable exposure region (masked EDGE or NO_DATA)\n",
      "base_PixelFlags_flag_interpolated:  Interpolated pixel in the Source footprint\n",
      "base_PixelFlags_flag_saturated:  Saturated pixel in the Source footprint\n",
      "base_PixelFlags_flag_cr:  Cosmic ray in the Source footprint\n",
      "base_PixelFlags_flag_bad:  Bad pixel in the Source footprint\n",
      "base_PixelFlags_flag_suspect:  Source''s footprint includes suspect pixels\n",
      "base_PixelFlags_flag_interpolatedCenter:  Interpolated pixel in the Source center\n",
      "base_PixelFlags_flag_saturatedCenter:  Saturated pixel in the Source center\n",
      "base_PixelFlags_flag_crCenter:  Cosmic ray in the Source center\n",
      "base_PixelFlags_flag_suspectCenter:  Source''s center is close to suspect pixels\n",
      "base_PixelFlags_flag_clippedCenter:  Source center is close to CLIPPED pixels\n",
      "base_PixelFlags_flag_sensor_edgeCenter:  Source center is close to SENSOR_EDGE pixels\n",
      "base_PixelFlags_flag_inexact_psfCenter:  Source center is close to INEXACT_PSF pixels\n",
      "base_PixelFlags_flag_bright_objectCenter:  Source center is close to BRIGHT_OBJECT pixels\n",
      "base_PixelFlags_flag_clipped:  Source footprint includes CLIPPED pixels\n",
      "base_PixelFlags_flag_sensor_edge:  Source footprint includes SENSOR_EDGE pixels\n",
      "base_PixelFlags_flag_inexact_psf:  Source footprint includes INEXACT_PSF pixels\n",
      "base_PixelFlags_flag_bright_object:  Source footprint includes BRIGHT_OBJECT pixels\n",
      "base_PsfFlux_instFlux:  instFlux derived from linear least-squares fit of PSF model\n",
      "base_PsfFlux_instFluxErr:  1-sigma instFlux uncertainty\n",
      "base_PsfFlux_area:  effective area of PSF\n",
      "base_PsfFlux_flag:  General Failure Flag\n",
      "base_PsfFlux_flag_noGoodPixels:  not enough non-rejected pixels in data to attempt the fit\n",
      "base_PsfFlux_flag_edge:  object was too close to the edge of the image to use the full PSF model\n",
      "base_Variance_flag:  Set for any fatal failure\n",
      "base_Variance_value:  Variance at object position\n",
      "base_Variance_flag_emptyFootprint:  Set to True when the footprint has no usable pixels\n",
      "ext_photometryKron_KronFlux_instFlux:  flux from Kron Flux algorithm\n",
      "ext_photometryKron_KronFlux_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_photometryKron_KronFlux_radius:  Kron radius (sqrt(a*b))\n",
      "ext_photometryKron_KronFlux_radius_for_radius:  radius used to estimate <radius> (sqrt(a*b))\n",
      "ext_photometryKron_KronFlux_psf_radius:  Radius of PSF\n",
      "ext_photometryKron_KronFlux_flag:  general failure flag, set if anything went wrong\n",
      "ext_photometryKron_KronFlux_flag_edge:  bad measurement due to image edge\n",
      "ext_photometryKron_KronFlux_flag_bad_shape_no_psf:  bad shape and no PSF\n",
      "ext_photometryKron_KronFlux_flag_no_minimum_radius:  minimum radius could not enforced: no minimum value or PSF\n",
      "ext_photometryKron_KronFlux_flag_no_fallback_radius:  no minimum radius and no PSF provided\n",
      "ext_photometryKron_KronFlux_flag_bad_radius:  bad Kron radius\n",
      "ext_photometryKron_KronFlux_flag_used_minimum_radius:  used the minimum radius for the Kron aperture\n",
      "ext_photometryKron_KronFlux_flag_used_psf_radius:  used the PSF Kron radius for the Kron aperture\n",
      "ext_photometryKron_KronFlux_flag_small_radius:  measured Kron radius was smaller than that of the PSF\n",
      "ext_photometryKron_KronFlux_flag_bad_shape:  shape for measuring Kron radius is bad; used PSF shape\n",
      "ext_convolved_ConvolvedFlux_seeing:  original seeing (Gaussian sigma) at position\n",
      "ext_convolved_ConvolvedFlux_0_deconv:  deconvolution required for seeing 3.500000; no measurement made\n",
      "ext_convolved_ConvolvedFlux_0_3_3_instFlux:  instFlux within 3.300000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_0_3_3_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_0_3_3_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_0_3_3_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_0_3_3_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_0_4_5_instFlux:  instFlux within 4.500000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_0_4_5_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_0_4_5_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_0_4_5_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_0_4_5_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_0_6_0_instFlux:  instFlux within 6.000000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_0_6_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_0_6_0_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_0_6_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_0_6_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_0_kron_instFlux:  convolved Kron flux: seeing 3.500000\n",
      "ext_convolved_ConvolvedFlux_0_kron_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_0_kron_flag:  convolved Kron flux failed: seeing 3.500000\n",
      "ext_convolved_ConvolvedFlux_1_deconv:  deconvolution required for seeing 5.000000; no measurement made\n",
      "ext_convolved_ConvolvedFlux_1_3_3_instFlux:  instFlux within 3.300000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_1_3_3_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_1_3_3_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_1_3_3_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_1_3_3_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_1_4_5_instFlux:  instFlux within 4.500000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_1_4_5_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_1_4_5_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_1_4_5_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_1_4_5_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_1_6_0_instFlux:  instFlux within 6.000000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_1_6_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_1_6_0_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_1_6_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_1_6_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_1_kron_instFlux:  convolved Kron flux: seeing 5.000000\n",
      "ext_convolved_ConvolvedFlux_1_kron_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_1_kron_flag:  convolved Kron flux failed: seeing 5.000000\n",
      "ext_convolved_ConvolvedFlux_2_deconv:  deconvolution required for seeing 6.500000; no measurement made\n",
      "ext_convolved_ConvolvedFlux_2_3_3_instFlux:  instFlux within 3.300000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_2_3_3_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_2_3_3_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_2_3_3_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_2_3_3_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_2_4_5_instFlux:  instFlux within 4.500000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_2_4_5_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_2_4_5_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_2_4_5_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_2_4_5_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_2_6_0_instFlux:  instFlux within 6.000000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_2_6_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_2_6_0_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_2_6_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_2_6_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_2_kron_instFlux:  convolved Kron flux: seeing 6.500000\n",
      "ext_convolved_ConvolvedFlux_2_kron_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_2_kron_flag:  convolved Kron flux failed: seeing 6.500000\n",
      "ext_convolved_ConvolvedFlux_3_deconv:  deconvolution required for seeing 8.000000; no measurement made\n",
      "ext_convolved_ConvolvedFlux_3_3_3_instFlux:  instFlux within 3.300000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_3_3_3_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_3_3_3_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_3_3_3_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_3_3_3_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_3_4_5_instFlux:  instFlux within 4.500000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_3_4_5_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_3_4_5_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_3_4_5_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_3_4_5_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_3_6_0_instFlux:  instFlux within 6.000000-pixel aperture\n",
      "ext_convolved_ConvolvedFlux_3_6_0_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_3_6_0_flag:  General Failure Flag\n",
      "ext_convolved_ConvolvedFlux_3_6_0_flag_apertureTruncated:  aperture did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_3_6_0_flag_sincCoeffsTruncated:  full sinc coefficient image did not fit within measurement image\n",
      "ext_convolved_ConvolvedFlux_3_kron_instFlux:  convolved Kron flux: seeing 8.000000\n",
      "ext_convolved_ConvolvedFlux_3_kron_instFluxErr:  1-sigma instFlux uncertainty\n",
      "ext_convolved_ConvolvedFlux_3_kron_flag:  convolved Kron flux failed: seeing 8.000000\n",
      "ext_convolved_ConvolvedFlux_flag:  error in running ConvolvedFluxPlugin\n",
      "modelfit_CModel_initial_instFlux:  flux from the initial fit\n",
      "modelfit_CModel_initial_instFluxErr:  flux uncertainty from the initial fit\n",
      "modelfit_CModel_initial_flag:  flag set when the flux for the initial flux failed\n",
      "modelfit_CModel_initial_instFlux_inner:  flux within the fit region, with no extrapolation\n",
      "modelfit_CModel_initial_ellipse_xx:  half-light ellipse of the initial fit\n",
      "modelfit_CModel_initial_ellipse_yy:  half-light ellipse of the initial fit\n",
      "modelfit_CModel_initial_ellipse_xy:  half-light ellipse of the initial fit\n",
      "modelfit_CModel_initial_objective:  -ln(likelihood*prior) at best-fit point for the initial fit\n",
      "modelfit_CModel_initial_nonlinear_0:  nonlinear parameters for the initial fit\n",
      "modelfit_CModel_initial_nonlinear_1:  nonlinear parameters for the initial fit\n",
      "modelfit_CModel_initial_nonlinear_2:  nonlinear parameters for the initial fit\n",
      "modelfit_CModel_initial_fixed_0:  fixed parameters for the initial fit\n",
      "modelfit_CModel_initial_fixed_1:  fixed parameters for the initial fit\n",
      "modelfit_CModel_initial_flag_trSmall:  the optimizer converged because the trust radius became too small; this is a less-secure result than when the gradient is below the threshold, but usually not a problem\n",
      "modelfit_CModel_initial_flag_maxIter:  the optimizer hit the maximum number of iterations and did not converge\n",
      "modelfit_CModel_initial_nIter:  Number of total iterations in stage\n",
      "modelfit_CModel_initial_time:  Time spent in stage\n",
      "modelfit_CModel_initial_flag_numericError:  numerical underflow or overflow in model evaluation; usually this means the prior was insufficient to regularize the fit, or all pixel values were zero.\n",
      "modelfit_CModel_exp_instFlux:  flux from the exponential fit\n",
      "modelfit_CModel_exp_instFluxErr:  flux uncertainty from the exponential fit\n",
      "modelfit_CModel_exp_flag:  flag set when the flux for the exponential flux failed\n",
      "modelfit_CModel_exp_instFlux_inner:  flux within the fit region, with no extrapolation\n",
      "modelfit_CModel_exp_ellipse_xx:  half-light ellipse of the exponential fit\n",
      "modelfit_CModel_exp_ellipse_yy:  half-light ellipse of the exponential fit\n",
      "modelfit_CModel_exp_ellipse_xy:  half-light ellipse of the exponential fit\n",
      "modelfit_CModel_exp_objective:  -ln(likelihood*prior) at best-fit point for the exponential fit\n",
      "modelfit_CModel_exp_nonlinear_0:  nonlinear parameters for the exponential fit\n",
      "modelfit_CModel_exp_nonlinear_1:  nonlinear parameters for the exponential fit\n",
      "modelfit_CModel_exp_nonlinear_2:  nonlinear parameters for the exponential fit\n",
      "modelfit_CModel_exp_fixed_0:  fixed parameters for the exponential fit\n",
      "modelfit_CModel_exp_fixed_1:  fixed parameters for the exponential fit\n",
      "modelfit_CModel_exp_flag_trSmall:  the optimizer converged because the trust radius became too small; this is a less-secure result than when the gradient is below the threshold, but usually not a problem\n",
      "modelfit_CModel_exp_flag_maxIter:  the optimizer hit the maximum number of iterations and did not converge\n",
      "modelfit_CModel_exp_nIter:  Number of total iterations in stage\n",
      "modelfit_CModel_exp_time:  Time spent in stage\n",
      "modelfit_CModel_exp_flag_numericError:  numerical underflow or overflow in model evaluation; usually this means the prior was insufficient to regularize the fit, or all pixel values were zero.\n",
      "modelfit_CModel_dev_instFlux:  flux from the de Vaucouleur fit\n",
      "modelfit_CModel_dev_instFluxErr:  flux uncertainty from the de Vaucouleur fit\n",
      "modelfit_CModel_dev_flag:  flag set when the flux for the de Vaucouleur flux failed\n",
      "modelfit_CModel_dev_instFlux_inner:  flux within the fit region, with no extrapolation\n",
      "modelfit_CModel_dev_ellipse_xx:  half-light ellipse of the de Vaucouleur fit\n",
      "modelfit_CModel_dev_ellipse_yy:  half-light ellipse of the de Vaucouleur fit\n",
      "modelfit_CModel_dev_ellipse_xy:  half-light ellipse of the de Vaucouleur fit\n",
      "modelfit_CModel_dev_objective:  -ln(likelihood*prior) at best-fit point for the de Vaucouleur fit\n",
      "modelfit_CModel_dev_nonlinear_0:  nonlinear parameters for the de Vaucouleur fit\n",
      "modelfit_CModel_dev_nonlinear_1:  nonlinear parameters for the de Vaucouleur fit\n",
      "modelfit_CModel_dev_nonlinear_2:  nonlinear parameters for the de Vaucouleur fit\n",
      "modelfit_CModel_dev_fixed_0:  fixed parameters for the de Vaucouleur fit\n",
      "modelfit_CModel_dev_fixed_1:  fixed parameters for the de Vaucouleur fit\n",
      "modelfit_CModel_dev_flag_trSmall:  the optimizer converged because the trust radius became too small; this is a less-secure result than when the gradient is below the threshold, but usually not a problem\n",
      "modelfit_CModel_dev_flag_maxIter:  the optimizer hit the maximum number of iterations and did not converge\n",
      "modelfit_CModel_dev_nIter:  Number of total iterations in stage\n",
      "modelfit_CModel_dev_time:  Time spent in stage\n",
      "modelfit_CModel_dev_flag_numericError:  numerical underflow or overflow in model evaluation; usually this means the prior was insufficient to regularize the fit, or all pixel values were zero.\n",
      "modelfit_CModel_instFlux:  flux from the final cmodel fit\n",
      "modelfit_CModel_instFluxErr:  flux uncertainty from the final cmodel fit\n",
      "modelfit_CModel_flag:  flag set if the final cmodel fit (or any previous fit) failed\n",
      "modelfit_CModel_instFlux_inner:  flux within the fit region, with no extrapolation\n",
      "modelfit_CModel_fracDev:  fraction of flux in de Vaucouleur component\n",
      "modelfit_CModel_objective:  -ln(likelihood) (chi^2) in cmodel fit\n",
      "modelfit_CModel_flag_region_maxArea:  number of pixels in fit region exceeded the region.maxArea value\n",
      "modelfit_CModel_flag_region_maxBadPixelFraction:  the fraction of bad/clipped pixels in the fit region exceeded region.maxBadPixelFraction\n",
      "modelfit_CModel_flags_region_usedFootprintArea:  the pixel region for the initial fit was defined by the area of the Footprint\n",
      "modelfit_CModel_flags_region_usedPsfArea:  the pixel region for the initial fit was set to a fixed factor of the PSF area\n",
      "modelfit_CModel_flags_region_usedInitialEllipseMin:  the pixel region for the final fit was set to the lower bound defined by the initial fit\n",
      "modelfit_CModel_flags_region_usedInitialEllipseMax:  the pixel region for the final fit was set to the upper bound defined by the initial fit\n",
      "modelfit_CModel_flag_noShape:  the shape slot needed to initialize the parameters failed or was not defined\n",
      "modelfit_CModel_flags_smallShape:  initial parameter guess resulted in negative radius; used minimum of 0.100000 pixels instead.\n",
      "modelfit_CModel_ellipse_xx:  fracDev-weighted average of exp.ellipse and dev.ellipse\n",
      "modelfit_CModel_ellipse_yy:  fracDev-weighted average of exp.ellipse and dev.ellipse\n",
      "modelfit_CModel_ellipse_xy:  fracDev-weighted average of exp.ellipse and dev.ellipse\n",
      "modelfit_CModel_region_initial_ellipse_xx:  ellipse used to set the pixel region for the initial fit (before applying bad pixel mask)\n",
      "modelfit_CModel_region_initial_ellipse_yy:  ellipse used to set the pixel region for the initial fit (before applying bad pixel mask)\n",
      "modelfit_CModel_region_initial_ellipse_xy:  ellipse used to set the pixel region for the initial fit (before applying bad pixel mask)\n",
      "modelfit_CModel_region_final_ellipse_xx:  ellipse used to set the pixel region for the final fit (before applying bad pixel mask)\n",
      "modelfit_CModel_region_final_ellipse_yy:  ellipse used to set the pixel region for the final fit (before applying bad pixel mask)\n",
      "modelfit_CModel_region_final_ellipse_xy:  ellipse used to set the pixel region for the final fit (before applying bad pixel mask)\n",
      "modelfit_CModel_flag_noShapeletPsf:  the multishapelet fit to the PSF model did not succeed\n",
      "modelfit_CModel_flag_badCentroid:  input centroid was not within the fit region (probably because it''s not within the Footprint)\n",
      "detect_isPatchInner:  true if source is in the inner region of a coadd patch\n",
      "detect_isTractInner:  true if source is in the inner region of a coadd tract\n",
      "detect_isPrimary:  true if source has no children and is in the inner region of a coadd patch and is in the inner region of a coadd tract and is not \"detected\" in a pseudo-filter (see config.pseudoFilterList)\n",
      "calib_psf_candidate:  Propagated from visits\n",
      "calib_psf_used:  Propagated from visits\n",
      "calib_psf_reserved:  Propagated from visits\n",
      "calib_astrometry_used:  Propagated from visits\n",
      "calib_photometry_used:  Propagated from visits\n",
      "calib_photometry_reserved:  Propagated from visits\n",
      "base_GaussianFlux_apCorr:  aperture correction applied to base_GaussianFlux\n",
      "base_GaussianFlux_apCorrErr:  standard deviation of aperture correction applied to base_GaussianFlux\n",
      "base_GaussianFlux_flag_apCorr:  set if unable to aperture correct base_GaussianFlux\n",
      "base_PsfFlux_apCorr:  aperture correction applied to base_PsfFlux\n",
      "base_PsfFlux_apCorrErr:  standard deviation of aperture correction applied to base_PsfFlux\n",
      "base_PsfFlux_flag_apCorr:  set if unable to aperture correct base_PsfFlux\n",
      "ext_convolved_ConvolvedFlux_0_3_3_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_0_3_3\n",
      "ext_convolved_ConvolvedFlux_0_3_3_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_0_3_3\n",
      "ext_convolved_ConvolvedFlux_0_3_3_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_0_3_3\n",
      "ext_convolved_ConvolvedFlux_0_4_5_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_0_4_5\n",
      "ext_convolved_ConvolvedFlux_0_4_5_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_0_4_5\n",
      "ext_convolved_ConvolvedFlux_0_4_5_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_0_4_5\n",
      "ext_convolved_ConvolvedFlux_0_6_0_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_0_6_0\n",
      "ext_convolved_ConvolvedFlux_0_6_0_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_0_6_0\n",
      "ext_convolved_ConvolvedFlux_0_6_0_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_0_6_0\n",
      "ext_convolved_ConvolvedFlux_0_kron_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_0_kron\n",
      "ext_convolved_ConvolvedFlux_0_kron_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_0_kron\n",
      "ext_convolved_ConvolvedFlux_0_kron_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_0_kron\n",
      "ext_convolved_ConvolvedFlux_1_3_3_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_1_3_3\n",
      "ext_convolved_ConvolvedFlux_1_3_3_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_1_3_3\n",
      "ext_convolved_ConvolvedFlux_1_3_3_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_1_3_3\n",
      "ext_convolved_ConvolvedFlux_1_4_5_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_1_4_5\n",
      "ext_convolved_ConvolvedFlux_1_4_5_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_1_4_5\n",
      "ext_convolved_ConvolvedFlux_1_4_5_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_1_4_5\n",
      "ext_convolved_ConvolvedFlux_1_6_0_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_1_6_0\n",
      "ext_convolved_ConvolvedFlux_1_6_0_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_1_6_0\n",
      "ext_convolved_ConvolvedFlux_1_6_0_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_1_6_0\n",
      "ext_convolved_ConvolvedFlux_1_kron_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_1_kron\n",
      "ext_convolved_ConvolvedFlux_1_kron_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_1_kron\n",
      "ext_convolved_ConvolvedFlux_1_kron_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_1_kron\n",
      "ext_convolved_ConvolvedFlux_2_3_3_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_2_3_3\n",
      "ext_convolved_ConvolvedFlux_2_3_3_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_2_3_3\n",
      "ext_convolved_ConvolvedFlux_2_3_3_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_2_3_3\n",
      "ext_convolved_ConvolvedFlux_2_4_5_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_2_4_5\n",
      "ext_convolved_ConvolvedFlux_2_4_5_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_2_4_5\n",
      "ext_convolved_ConvolvedFlux_2_4_5_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_2_4_5\n",
      "ext_convolved_ConvolvedFlux_2_6_0_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_2_6_0\n",
      "ext_convolved_ConvolvedFlux_2_6_0_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_2_6_0\n",
      "ext_convolved_ConvolvedFlux_2_6_0_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_2_6_0\n",
      "ext_convolved_ConvolvedFlux_2_kron_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_2_kron\n",
      "ext_convolved_ConvolvedFlux_2_kron_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_2_kron\n",
      "ext_convolved_ConvolvedFlux_2_kron_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_2_kron\n",
      "ext_convolved_ConvolvedFlux_3_3_3_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_3_3_3\n",
      "ext_convolved_ConvolvedFlux_3_3_3_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_3_3_3\n",
      "ext_convolved_ConvolvedFlux_3_3_3_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_3_3_3\n",
      "ext_convolved_ConvolvedFlux_3_4_5_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_3_4_5\n",
      "ext_convolved_ConvolvedFlux_3_4_5_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_3_4_5\n",
      "ext_convolved_ConvolvedFlux_3_4_5_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_3_4_5\n",
      "ext_convolved_ConvolvedFlux_3_6_0_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_3_6_0\n",
      "ext_convolved_ConvolvedFlux_3_6_0_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_3_6_0\n",
      "ext_convolved_ConvolvedFlux_3_6_0_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_3_6_0\n",
      "ext_convolved_ConvolvedFlux_3_kron_apCorr:  aperture correction applied to ext_convolved_ConvolvedFlux_3_kron\n",
      "ext_convolved_ConvolvedFlux_3_kron_apCorrErr:  standard deviation of aperture correction applied to ext_convolved_ConvolvedFlux_3_kron\n",
      "ext_convolved_ConvolvedFlux_3_kron_flag_apCorr:  set if unable to aperture correct ext_convolved_ConvolvedFlux_3_kron\n",
      "ext_photometryKron_KronFlux_apCorr:  aperture correction applied to ext_photometryKron_KronFlux\n",
      "ext_photometryKron_KronFlux_apCorrErr:  standard deviation of aperture correction applied to ext_photometryKron_KronFlux\n",
      "ext_photometryKron_KronFlux_flag_apCorr:  set if unable to aperture correct ext_photometryKron_KronFlux\n",
      "modelfit_CModel_apCorr:  aperture correction applied to modelfit_CModel\n",
      "modelfit_CModel_apCorrErr:  standard deviation of aperture correction applied to modelfit_CModel\n",
      "modelfit_CModel_flag_apCorr:  set if unable to aperture correct modelfit_CModel\n",
      "modelfit_CModel_dev_apCorr:  aperture correction applied to modelfit_CModel_dev\n",
      "modelfit_CModel_dev_apCorrErr:  standard deviation of aperture correction applied to modelfit_CModel_dev\n",
      "modelfit_CModel_dev_flag_apCorr:  set if unable to aperture correct modelfit_CModel_dev\n",
      "modelfit_CModel_exp_apCorr:  aperture correction applied to modelfit_CModel_exp\n",
      "modelfit_CModel_exp_apCorrErr:  standard deviation of aperture correction applied to modelfit_CModel_exp\n",
      "modelfit_CModel_exp_flag_apCorr:  set if unable to aperture correct modelfit_CModel_exp\n",
      "modelfit_CModel_initial_apCorr:  aperture correction applied to modelfit_CModel_initial\n",
      "modelfit_CModel_initial_apCorrErr:  standard deviation of aperture correction applied to modelfit_CModel_initial\n",
      "modelfit_CModel_initial_flag_apCorr:  set if unable to aperture correct modelfit_CModel_initial\n",
      "base_ClassificationExtendedness_value:  Set to 1 for extended sources, 0 for point sources.\n",
      "base_ClassificationExtendedness_flag:  Set to 1 for any fatal failure.\n",
      "base_FootprintArea_value:  Number of pixels in the source''s detection footprint.\n"
     ]
    }
   ],
   "source": [
    "# All the DRP measurements:\n",
    "for item in catalog.schema:\n",
    "    print(f\"{item.field.getName()}:  {item.field.getDoc()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['sed_9395_583_bulge',\n",
       " 'sed_7843_486',\n",
       " 'sed_8846_549_disk',\n",
       " 'sed_1246_306_no_host_extinction',\n",
       " 'sed_7843_486_disk',\n",
       " 'halo_mass',\n",
       " 'sed_4565_283_no_host_extinction',\n",
       " 'mag_r_lsst',\n",
       " 'ellipticity_bulge_true',\n",
       " 'sed_4565_283',\n",
       " 'mag_u_sdss',\n",
       " 'sed_6954_431_disk_no_host_extinction',\n",
       " 'sed_15143_2259_bulge_no_host_extinction',\n",
       " 'shear_2_treecorr',\n",
       " 'mag_g_lsst',\n",
       " 'position_y',\n",
       " 'mag_true_u',\n",
       " 'is_central',\n",
       " 'sed_6166_382',\n",
       " 'sed_2407_591_disk',\n",
       " 'sed_4048_251_no_host_extinction',\n",
       " 'sed_3184_197_bulge',\n",
       " 'dec',\n",
       " 'mag_true_z_sdss',\n",
       " 'Mag_true_z_sdss_z0_no_host_extinction',\n",
       " 'mag_true_u_lsst_no_host_extinction',\n",
       " 'sed_3590_222_no_host_extinction',\n",
       " 'sed_11467_1710_no_host_extinction',\n",
       " 'sed_4299_266_bulge',\n",
       " 'mag_z_sdss_no_host_extinction',\n",
       " 'sed_17402_2596_disk_no_host_extinction',\n",
       " 'sed_5806_360',\n",
       " 'sed_8329_517_bulge_no_host_extinction',\n",
       " 'mag_true_g_sdss_no_host_extinction',\n",
       " 'sed_2998_186_no_host_extinction',\n",
       " 'sed_5467_339_no_host_extinction',\n",
       " 'sed_8846_549_bulge',\n",
       " 'sed_6166_382_bulge_no_host_extinction',\n",
       " 'sed_3381_209_bulge_no_host_extinction',\n",
       " 'sed_8329_517',\n",
       " 'A_v',\n",
       " 'sed_1246_306',\n",
       " 'sed_7385_458_bulge',\n",
       " 'sed_13177_1966_disk',\n",
       " 'sed_15143_2259',\n",
       " 'sed_13177_1966_no_host_extinction',\n",
       " 'mag_true_i_sdss',\n",
       " 'sed_1552_381_bulge',\n",
       " 'sed_8329_517_bulge',\n",
       " 'velocity_y',\n",
       " 'sed_15143_2259_disk_no_host_extinction',\n",
       " 'sed_3381_209_bulge',\n",
       " 'sed_17402_2596_disk',\n",
       " 'stellar_mass_disk',\n",
       " 'sed_4048_251',\n",
       " 'mag_true_Y_lsst',\n",
       " 'sed_3812_236',\n",
       " 'sed_6166_382_disk_no_host_extinction',\n",
       " 'sed_4848_300_no_host_extinction',\n",
       " 'sed_9978_1489_no_host_extinction',\n",
       " 'shear_2',\n",
       " 'sed_1552_381_disk',\n",
       " 'ellipticity_true',\n",
       " 'sed_8846_549',\n",
       " 'ellipticity_1_true',\n",
       " 'sed_9395_583_no_host_extinction',\n",
       " 'sed_4565_283_disk_no_host_extinction',\n",
       " 'mag_true_i_sdss_no_host_extinction',\n",
       " 'sed_1000_246_no_host_extinction',\n",
       " 'stellar_mass',\n",
       " 'shear_2_phosim',\n",
       " 'mag_i_lsst_no_host_extinction',\n",
       " 'sed_8846_549_bulge_no_host_extinction',\n",
       " 'sed_1000_246_bulge',\n",
       " 'Mag_true_z_lsst_z0_no_host_extinction',\n",
       " 'sed_8329_517_disk_no_host_extinction',\n",
       " 'Mag_true_z_lsst_z0',\n",
       " 'sed_5806_360_bulge_no_host_extinction',\n",
       " 'sed_3184_197_no_host_extinction',\n",
       " 'Mag_true_g_lsst_z0_no_host_extinction',\n",
       " 'Mag_true_u_lsst_z0',\n",
       " 'mag_i_lsst',\n",
       " 'mag_true_i_lsst_no_host_extinction',\n",
       " 'Mag_true_y_lsst_z0_no_host_extinction',\n",
       " 'sed_2407_591_no_host_extinction',\n",
       " 'mag_r_lsst_no_host_extinction',\n",
       " 'mag_Y_lsst',\n",
       " 'Mag_true_r_lsst_z0',\n",
       " 'sed_5467_339_bulge',\n",
       " 'size_bulge_true',\n",
       " 'mag_true_y_lsst',\n",
       " 'mag_r_sdss_no_host_extinction',\n",
       " 'mag_true_z',\n",
       " 'mag_true_g',\n",
       " 'sed_4565_283_bulge',\n",
       " 'R_v_bulge',\n",
       " 'mag_z',\n",
       " 'sed_3381_209_disk',\n",
       " 'shear_1',\n",
       " 'sed_4048_251_disk',\n",
       " 'mag_Y_lsst_no_host_extinction',\n",
       " 'mag_y',\n",
       " 'mag_true_z_lsst',\n",
       " 'mag_true_u_sdss',\n",
       " 'sed_5467_339_disk_no_host_extinction',\n",
       " 'sed_3812_236_bulge',\n",
       " 'mag_z_sdss',\n",
       " 'mag_true_g_sdss',\n",
       " 'sed_3381_209',\n",
       " 'sed_3812_236_no_host_extinction',\n",
       " 'ellipticity_2_bulge_true',\n",
       " 'mag_true_r',\n",
       " 'sed_1000_246_disk_no_host_extinction',\n",
       " 'sed_6548_406_bulge',\n",
       " 'sed_17402_2596',\n",
       " 'sed_13177_1966_bulge',\n",
       " 'sed_17402_2596_bulge_no_host_extinction',\n",
       " 'sed_13177_1966_disk_no_host_extinction',\n",
       " 'sed_1000_246_bulge_no_host_extinction',\n",
       " 'sed_5148_319_no_host_extinction',\n",
       " 'mag_true_i',\n",
       " 'sed_1933_474_no_host_extinction',\n",
       " 'size_minor_bulge_true',\n",
       " 'position_angle_true',\n",
       " 'sed_1552_381_bulge_no_host_extinction',\n",
       " 'redshift_true',\n",
       " 'sed_3184_197_bulge_no_host_extinction',\n",
       " 'mag_true_r_lsst',\n",
       " 'sed_9978_1489_bulge_no_host_extinction',\n",
       " 'sed_2998_186',\n",
       " 'sed_2407_591',\n",
       " 'sed_7843_486_bulge_no_host_extinction',\n",
       " 'mag_z_lsst_no_host_extinction',\n",
       " 'sed_5467_339_disk',\n",
       " 'sed_5148_319_disk',\n",
       " 'ellipticity_2_disk_true',\n",
       " 'mag_true_z_sdss_no_host_extinction',\n",
       " 'mag_true_z_lsst_no_host_extinction',\n",
       " 'sersic_bulge',\n",
       " 'sed_8846_549_disk_no_host_extinction',\n",
       " 'sed_3812_236_bulge_no_host_extinction',\n",
       " 'size_minor_true',\n",
       " 'mag_g_lsst_no_host_extinction',\n",
       " 'sed_1933_474_disk_no_host_extinction',\n",
       " 'sed_1552_381_disk_no_host_extinction',\n",
       " 'Mag_true_i_sdss_z0_no_host_extinction',\n",
       " 'sed_13177_1966',\n",
       " 'sed_9395_583_bulge_no_host_extinction',\n",
       " 'sed_6548_406_no_host_extinction',\n",
       " 'sed_4299_266_no_host_extinction',\n",
       " 'Mag_true_Y_lsst_z0',\n",
       " 'sed_2407_591_disk_no_host_extinction',\n",
       " 'mag_true_Y_lsst_no_host_extinction',\n",
       " 'ra',\n",
       " 'sed_9978_1489_bulge',\n",
       " 'sed_11467_1710_bulge_no_host_extinction',\n",
       " 'mag_true_u_sdss_no_host_extinction',\n",
       " 'mag_r',\n",
       " 'sed_5148_319_disk_no_host_extinction',\n",
       " 'sed_7843_486_bulge',\n",
       " 'sed_4048_251_bulge',\n",
       " 'sed_3590_222_bulge',\n",
       " 'mag_true_u_lsst',\n",
       " 'mag_g_sdss_no_host_extinction',\n",
       " 'sed_2998_186_bulge',\n",
       " 'sed_7385_458_disk_no_host_extinction',\n",
       " 'sed_1933_474_disk',\n",
       " 'sed_7843_486_disk_no_host_extinction',\n",
       " 'sed_6166_382_bulge',\n",
       " 'size_disk_true',\n",
       " 'sed_9395_583_disk_no_host_extinction',\n",
       " 'mag_true_y',\n",
       " 'sed_3590_222_bulge_no_host_extinction',\n",
       " 'sed_4848_300_bulge',\n",
       " 'Mag_true_r_sdss_z0',\n",
       " 'sed_15143_2259_disk',\n",
       " 'sed_6548_406_bulge_no_host_extinction',\n",
       " 'sed_15143_2259_bulge',\n",
       " 'sed_4565_283_bulge_no_host_extinction',\n",
       " 'mag_y_lsst_no_host_extinction',\n",
       " 'sed_3590_222',\n",
       " 'position_z',\n",
       " 'sed_11467_1710_disk_no_host_extinction',\n",
       " 'sed_2998_186_disk_no_host_extinction',\n",
       " 'mag_u_lsst_no_host_extinction',\n",
       " 'sed_4048_251_bulge_no_host_extinction',\n",
       " 'size_minor_disk_true',\n",
       " 'ellipticity_1_disk_true',\n",
       " 'Mag_true_y_lsst_z0',\n",
       " 'dec_true',\n",
       " 'sed_7385_458_bulge_no_host_extinction',\n",
       " 'sed_4048_251_disk_no_host_extinction',\n",
       " 'sed_8329_517_no_host_extinction',\n",
       " 'sed_6954_431_bulge',\n",
       " 'Mag_true_z_sdss_z0',\n",
       " 'sed_3184_197_disk_no_host_extinction',\n",
       " 'sed_17402_2596_bulge',\n",
       " 'sed_6954_431',\n",
       " 'sed_5467_339_bulge_no_host_extinction',\n",
       " 'sed_5806_360_disk',\n",
       " 'redshift',\n",
       " 'sed_1246_306_disk',\n",
       " 'Mag_true_u_lsst_z0_no_host_extinction',\n",
       " 'sed_6954_431_bulge_no_host_extinction',\n",
       " 'sed_5806_360_disk_no_host_extinction',\n",
       " 'sed_1246_306_bulge_no_host_extinction',\n",
       " 'sed_6954_431_no_host_extinction',\n",
       " 'sed_1246_306_disk_no_host_extinction',\n",
       " 'sed_8329_517_disk',\n",
       " 'sed_6166_382_disk',\n",
       " 'velocity_x',\n",
       " 'sed_4565_283_disk',\n",
       " 'sed_6548_406_disk_no_host_extinction',\n",
       " 'sed_4299_266_disk_no_host_extinction',\n",
       " 'sed_1552_381',\n",
       " 'sed_2407_591_bulge_no_host_extinction',\n",
       " 'mag_z_lsst',\n",
       " 'mag_true_g_lsst_no_host_extinction',\n",
       " 'Mag_true_i_sdss_z0',\n",
       " 'sed_3812_236_disk_no_host_extinction',\n",
       " 'sersic_disk',\n",
       " 'Mag_true_r_lsst_z0_no_host_extinction',\n",
       " 'sed_6954_431_disk',\n",
       " 'mag_g',\n",
       " 'halo_id',\n",
       " 'mag_u',\n",
       " 'mag_true_y_lsst_no_host_extinction',\n",
       " 'sed_11467_1710',\n",
       " 'sed_4299_266_bulge_no_host_extinction',\n",
       " 'sed_1552_381_no_host_extinction',\n",
       " 'mag_g_sdss',\n",
       " 'sed_4299_266',\n",
       " 'sed_5806_360_no_host_extinction',\n",
       " 'mag_true_r_sdss',\n",
       " 'sed_9395_583_disk',\n",
       " 'R_v',\n",
       " 'Mag_true_g_sdss_z0_no_host_extinction',\n",
       " 'Mag_true_r_sdss_z0_no_host_extinction',\n",
       " 'ellipticity_1_bulge_true',\n",
       " 'Mag_true_i_lsst_z0',\n",
       " 'sed_15143_2259_no_host_extinction',\n",
       " 'sed_9395_583',\n",
       " 'A_v_disk',\n",
       " 'sed_4848_300_bulge_no_host_extinction',\n",
       " 'sed_8846_549_no_host_extinction',\n",
       " 'sed_4848_300_disk_no_host_extinction',\n",
       " 'Mag_true_g_lsst_z0',\n",
       " 'mag_i',\n",
       " 'mag_true_g_lsst',\n",
       " 'ellipticity_2_true',\n",
       " 'sed_5806_360_bulge',\n",
       " 'sed_2998_186_disk',\n",
       " 'sed_11467_1710_disk',\n",
       " 'sed_1933_474_bulge_no_host_extinction',\n",
       " 'Mag_true_i_lsst_z0_no_host_extinction',\n",
       " 'magnification',\n",
       " 'sed_6166_382_no_host_extinction',\n",
       " 'mag_true_r_sdss_no_host_extinction',\n",
       " 'mag_true_r_lsst_no_host_extinction',\n",
       " 'sed_1000_246_disk',\n",
       " 'mag_r_sdss',\n",
       " 'sed_2407_591_bulge',\n",
       " 'sed_3381_209_no_host_extinction',\n",
       " 'galaxy_id',\n",
       " 'mag_i_sdss',\n",
       " 'sed_5148_319',\n",
       " 'sed_9978_1489_disk',\n",
       " 'sed_13177_1966_bulge_no_host_extinction',\n",
       " 'sed_4848_300_disk',\n",
       " 'sed_6548_406_disk',\n",
       " 'mag_u_lsst',\n",
       " 'R_v_disk',\n",
       " 'velocity_z',\n",
       " 'sed_6548_406',\n",
       " 'sed_7385_458_disk',\n",
       " 'sed_9978_1489_disk_no_host_extinction',\n",
       " 'Mag_true_g_sdss_z0',\n",
       " 'bulge_to_total_ratio_i',\n",
       " 'Mag_true_Y_lsst_z0_no_host_extinction',\n",
       " 'ellipticity_disk_true',\n",
       " 'sed_1933_474_bulge',\n",
       " 'sed_3812_236_disk',\n",
       " 'Mag_true_u_sdss_z0',\n",
       " 'sed_7385_458',\n",
       " 'convergence',\n",
       " 'sed_1000_246',\n",
       " 'sed_4848_300',\n",
       " 'size_true',\n",
       " 'sed_7843_486_no_host_extinction',\n",
       " 'sed_9978_1489',\n",
       " 'sed_3590_222_disk',\n",
       " 'A_v_bulge',\n",
       " 'sed_3184_197_disk',\n",
       " 'sed_5467_339',\n",
       " 'mag_y_lsst',\n",
       " 'ra_true',\n",
       " 'sed_5148_319_bulge',\n",
       " 'sed_3381_209_disk_no_host_extinction',\n",
       " 'sed_11467_1710_bulge',\n",
       " 'sed_2998_186_bulge_no_host_extinction',\n",
       " 'position_x',\n",
       " 'sed_17402_2596_no_host_extinction',\n",
       " 'mag_u_sdss_no_host_extinction',\n",
       " 'sed_4299_266_disk',\n",
       " 'sed_7385_458_no_host_extinction',\n",
       " 'mag_i_sdss_no_host_extinction',\n",
       " 'stellar_mass_bulge',\n",
       " 'Mag_true_u_sdss_z0_no_host_extinction',\n",
       " 'sed_5148_319_bulge_no_host_extinction',\n",
       " 'sed_1246_306_bulge',\n",
       " 'mag_true_i_lsst',\n",
       " 'sed_3184_197',\n",
       " 'sed_1933_474',\n",
       " 'sed_3590_222_disk_no_host_extinction']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# All the cosmoDC2 parameters:\n",
    "# help(gc)\n",
    "gc.list_all_quantities()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "desc-stack",
   "language": "python",
   "name": "desc-stack"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}