Coverage for python/lsst/meas/algorithms/astrometrySourceSelector.py : 36%

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# # LSST Data Management System # # Copyright 2008-2017 AURA/LSST. # # 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 <https://www.lsstcorp.org/LegalNotices/>. #
Such sources have good signal-to-noise, are well centroided, not blended, and not flagged with a handful of "bad" flags. """
doc="List of flags which cause a source to be rejected as bad", dtype=str, default=[ "base_PixelFlags_flag_edge", "base_PixelFlags_flag_interpolatedCenter", "base_PixelFlags_flag_saturatedCenter", "base_PixelFlags_flag_crCenter", "base_PixelFlags_flag_bad", ], ) doc="Type of source flux; typically one of Ap or Psf", dtype=str, default="Ap", ) dtype=float, doc="Minimum allowed signal-to-noise ratio for sources used for matching " "(in the flux specified by sourceFluxType); <= 0 for no limit", default=10, )
"""Select sources that are useful for astrometry.
Good astrometry sources have high signal/noise, are non-blended, and did not have certain "bad" flags set during source extraction. They need not be PSF sources, just have reliable centroids. """
BaseSourceSelectorTask.__init__(self, *args, **kwargs)
"""Return a selection of sources that are useful for astrometry.
Parameters: ----------- sourceCat : `lsst.afw.table.SourceCatalog` Catalog of sources to select from. This catalog must be contiguous in memory. matches : `list` of `lsst.afw.table.ReferenceMatch` or None Ignored in this SourceSelector. exposure : `lsst.afw.image.Exposure` or None The exposure the catalog was built from; used for debug display.
Return ------ struct : `lsst.pipe.base.Struct` The struct contains the following data:
- selected : `array` of `bool`` Boolean array of sources that were selected, same length as sourceCat. """ self._getSchemaKeys(sourceCat.schema)
bad = reduce(lambda x, y: np.logical_or(x, sourceCat.get(y)), self.config.badFlags, False) good = self._isGood(sourceCat) return Struct(selected=good & ~bad)
"""Extract and save the necessary keys from schema with asKey.""" self.parentKey = schema["parent"].asKey() self.nChildKey = schema["deblend_nChild"].asKey() self.centroidXKey = schema["slot_Centroid_x"].asKey() self.centroidYKey = schema["slot_Centroid_y"].asKey() self.centroidXErrKey = schema["slot_Centroid_xErr"].asKey() self.centroidYErrKey = schema["slot_Centroid_yErr"].asKey() self.centroidFlagKey = schema["slot_Centroid_flag"].asKey()
self.edgeKey = schema["base_PixelFlags_flag_edge"].asKey() self.interpolatedCenterKey = schema["base_PixelFlags_flag_interpolatedCenter"].asKey() self.saturatedKey = schema["base_PixelFlags_flag_saturated"].asKey()
fluxPrefix = "slot_%sFlux_" % (self.config.sourceFluxType,) self.instFluxKey = schema[fluxPrefix + "instFlux"].asKey() self.fluxFlagKey = schema[fluxPrefix + "flag"].asKey() self.instFluxErrKey = schema[fluxPrefix + "instFluxErr"].asKey()
"""Return True for each source that is likely multiple sources.""" test = (sourceCat.get(self.parentKey) != 0) | (sourceCat.get(self.nChildKey) != 0) # have to currently manage footprints on a source-by-source basis. for i, cat in enumerate(sourceCat): footprint = cat.getFootprint() test[i] |= (footprint is not None) and (len(footprint.getPeaks()) > 1) return test
"""Return True for each source that has a valid centroid""" def checkNonfiniteCentroid(): """Return True for sources with non-finite centroids.""" return ~np.isfinite(sourceCat.get(self.centroidXKey)) | \ ~np.isfinite(sourceCat.get(self.centroidYKey)) assert ~checkNonfiniteCentroid().any(), \ "Centroids not finite for %d unflagged sources." % (checkNonfiniteCentroid().sum()) return np.isfinite(sourceCat.get(self.centroidXErrKey)) \ & np.isfinite(sourceCat.get(self.centroidYErrKey)) \ & ~sourceCat.get(self.centroidFlagKey)
"""Return True for each source that has Signal/Noise > config.minSnr.""" if self.config.minSnr <= 0: return True else: with np.errstate(invalid="ignore"): # suppress NAN warnings return sourceCat.get(self.instFluxKey)/sourceCat.get(self.instFluxErrKey) > self.config.minSnr
""" Return True for each source that is usable for matching, even if it may have a poor centroid.
For a source to be usable it must: - have a valid centroid - not be deblended - have a valid flux (of the type specified in this object's constructor) - have adequate signal-to-noise """
return self._hasCentroid(sourceCat) \ & ~self._isMultiple(sourceCat) \ & self._goodSN(sourceCat) \ & ~sourceCat.get(self.fluxFlagKey)
""" Return True for each source that is usable for matching and likely has a good centroid.
The additional tests for a good centroid, beyond isUsable, are: - not interpolated in the center - not saturated - not near the edge """
return self._isUsable(sourceCat) \ & ~sourceCat.get(self.saturatedKey) \ & ~sourceCat.get(self.interpolatedCenterKey) \ & ~sourceCat.get(self.edgeKey)
"""Return True if any of config.badFlags are set for this source.""" return any(source.get(flag) for flag in self.config.badFlags) |