verifyWcs.py

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#
# LSST Data Management System
# Copyright 2008, 2009, 2010 LSST Corporation.
#
# This product includes software developed by the
# LSST Project (http://www.lsst.org/).
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the LSST License Statement and
# the GNU General Public License along with this program.  If not,
# see <http://www.lsstcorp.org/LegalNotices/>.
#
 
__all__ = ["checkMatches"]
 
 
import numpy as np
import logging
 
import lsst.geom
import lsst.afw.detection as afwDetection
import lsst.afw.math as afwMath
import lsst.meas.algorithms as measAlg
 
_LOG = logging.getLogger(__name__)
 
 
def checkMatches(srcMatchSet, exposure, log=None):
    """Check astrometric matches and assess Wcs quality by computing statics
    over spacial cells in the image.
 
    Parameters
    ----------
    srcMatchSet : `list` of `lsst.afw.table.ReferenceMatch`
        List of matched sources to a reference catalog.
    exposure : `lsst.afw.image.Exposure`
        Image the sources in srcMatchSet were detected/measured in.
    log : `lsst.log.Log` or `logging.Logger`
        Logger object.
 
    Returns
    -------
    values : `dict`
        Result dictionary with fields:
 
        - ``minObjectsPerCell`` : (`int`)
        - ``maxObjectsPerCell`` : (`int`)
        - ``meanObjectsPerCell`` : (`float`)
        - ``stdObjectsPerCell`` : (`float`)
    """
    if not exposure:
        return {}
 
    if log is None:
        log = _LOG
 
    im = exposure.getMaskedImage().getImage()
    width, height = im.getWidth(), im.getHeight()
    nx, ny = 3, 3
    w, h = width//nx, height//ny
 
    if w == 0:
        w = 1
    while nx*w < width:
        w += 1
 
    if h == 0:
        h = 1
    while ny*h < height:
        h += 1
 
    cellSet = afwMath.SpatialCellSet(
        lsst.geom.Box2I(lsst.geom.Point2I(0, 0), lsst.geom.Extent2I(width, height)), w, h)
    #
    # Populate cellSet
    #
    i = -1
    for m in srcMatchSet:
        i += 1
 
        src = m.second
        csrc = afwDetection.Source()
        csrc.setId(i)
        csrc.setXAstrom(src.getXAstrom())
        csrc.setYAstrom(src.getYAstrom())
 
        try:
            cellSet.insertCandidate(measAlg.PsfCandidateF(csrc, exposure.getMaskedImage()))
        except Exception as e:
            log.warning("%s", e)
 
    ncell = len(cellSet.getCellList())
    nobj = np.ndarray(ncell, dtype='i')
 
    for i in range(ncell):
        cell = cellSet.getCellList()[i]
 
        nobj[i] = cell.size()
 
        dx = np.ndarray(cell.size())
        dy = np.ndarray(cell.size())
 
        j = 0
        for cand in cell:
            #
            # Swig doesn't know that we're a SpatialCellImageCandidate;  all it knows is that we have
            # a SpatialCellCandidate so we need an explicit (dynamic) cast
            #
            mid = cand.getSource().getId()
            dx[j] = srcMatchSet[mid].first.getXAstrom() - srcMatchSet[mid].second.getXAstrom()
            dy[j] = srcMatchSet[mid].first.getYAstrom() - srcMatchSet[mid].second.getYAstrom()
 
            j += 1
 
        log.debug("%s %-30s  %8s  dx,dy = %5.2f,%5.2f  rms_x,y = %5.2f,%5.2f",
                  cell.getLabel(), cell.getBBox(), ("nobj=%d" % cell.size()),
                  dx.mean(), dy.mean(), dx.std(), dy.std())
 
    nobj.sort()
 
    values = {}
    values["minObjectsPerCell"] = int(nobj[0])  # otherwise it's a numpy integral type
    values["maxObjectsPerCell"] = int(nobj[-1])
    values["meanObjectsPerCell"] = nobj.mean()
    values["stdObjectsPerCell"] = nobj.std()
 
    return values
def checkMatches(srcMatchSet, exposure, log=None): …