def run(self, exposure):
table = SourceTable.make(self.schema)
background = None
detRes = self.detection.run(table=table, exposure=exposure)
sourceCat = detRes.sources
if background is None:
background = BackgroundList()
if detRes.fpSets.background:
background.append(detRes.fpSets.background)
if self.config.doDeblend:
self.deblend.run(exposure=exposure, sources=sourceCat)
self.measurement.run(
measCat=sourceCat,
exposure=exposure
)
#results2 = self.deblend.run(...)
#results3 = self.measurement.run(...)
return pipeBase.Struct(
exposure = exposure,
background = background,
sourceCat = sourceCat
)
def run(self, exposure, exposureIdInfo, background=None, allowApCorr=True):
"""!Detect, deblend and perform single-frame measurement on sources and refine the background model
@param[in,out] exposure exposure to process. Background must already be subtracted
to reasonable accuracy, else detection will fail.
The background model is refined and resubtracted.
apCorrMap is set if measuring aperture correction.
@param[in] exposureIdInfo ID info for exposure (an lsst.daf.butlerUtils.ExposureIdInfo)
@param[in,out] background background model to be modified (an lsst.afw.math.BackgroundList),
or None to create a new background model
@param[in] allowApCorr allow measuring and applying aperture correction?
@return pipe_base Struct containing these fields:
- exposure: input exposure (as modified in the course of runing)
- sourceCat: source catalog (an lsst.afw.table.SourceTable)
- background: background model (input as modified, or a new model if input is None);
an lsst.afw.math.BackgroundList
"""
if background is None:
background = BackgroundList()
sourceIdFactory = IdFactory.makeSource(exposureIdInfo.expId,
exposureIdInfo.unusedBits)
table = SourceTable.make(self.schema, sourceIdFactory)
table.setMetadata(self.algMetadata)
detRes = self.detection.run(table=table,
exposure=exposure,
doSmooth=True)
sourceCat = detRes.sources
if detRes.fpSets.background:
background.append(detRes.fpSets.background)
if self.config.doDeblend:
self.deblend.run(
exposure=exposure,
sources=sourceCat,
psf=exposure.getPsf(),
)
self.measure(
exposure=exposure,
exposureIdInfo=exposureIdInfo,
sourceCat=sourceCat,
allowApCorr=allowApCorr,
)
return pipeBase.Struct(
exposure=exposure,
sourceCat=sourceCat,
background=background,
)
def run(self, exposure, exposureIdInfo, background=None, allowApCorr=True):
"""!Detect, deblend and perform single-frame measurement on sources and refine the background model
@param[in,out] exposure exposure to process. Background must already be subtracted
to reasonable accuracy, else detection will fail.
The background model is refined and resubtracted.
apCorrMap is set if measuring aperture correction.
@param[in] exposureIdInfo ID info for exposure (an lsst.daf.butlerUtils.ExposureIdInfo)
@param[in,out] background background model to be modified (an lsst.afw.math.BackgroundList),
or None to create a new background model
@param[in] allowApCorr allow measuring and applying aperture correction?
@return pipe_base Struct containing these fields:
- exposure: input exposure (as modified in the course of runing)
- sourceCat: source catalog (an lsst.afw.table.SourceTable)
- background: background model (input as modified, or a new model if input is None);
an lsst.afw.math.BackgroundList
"""
if background is None:
background = BackgroundList()
sourceIdFactory = IdFactory.makeSource(exposureIdInfo.expId, exposureIdInfo.unusedBits)
table = SourceTable.make(self.schema, sourceIdFactory)
table.setMetadata(self.algMetadata)
detRes = self.detection.run(table=table, exposure=exposure, doSmooth=True)
sourceCat = detRes.sources
if detRes.fpSets.background:
background.append(detRes.fpSets.background)
if self.config.doDeblend:
self.deblend.run(
exposure = exposure,
sources = sourceCat,
psf = exposure.getPsf(),
)
self.measure(
exposure = exposure,
exposureIdInfo = exposureIdInfo,
sourceCat = sourceCat,
allowApCorr = allowApCorr,
)
return pipeBase.Struct(
exposure = exposure,
sourceCat = sourceCat,
background = background,
)
def detectMeasureAndEstimatePsf(self, exposure, exposureIdInfo,
background):
"""!Perform one iteration of detect, measure and estimate PSF
Performs the following operations:
- if config.doMeasurePsf or not exposure.hasPsf():
- install a simple PSF model (replacing the existing one, if need be)
- interpolate over cosmic rays with keepCRs=True
- estimate background and subtract it from the exposure
- detect, deblend and measure sources, and subtract a refined background model;
- if config.doMeasurePsf:
- measure PSF
@param[in,out] exposure exposure to characterize (an lsst.afw.image.ExposureF or similar)
The following changes are made:
- update or set psf
- update detection and cosmic ray mask planes
- subtract background
@param[in] exposureIdInfo ID info for exposure (an lsst.obs_base.ExposureIdInfo)
@param[in,out] background initial model of background already subtracted from exposure
(an lsst.afw.math.BackgroundList).
@return pipe_base Struct containing these fields, all from the final iteration
of detect sources, measure sources and estimate PSF:
- exposure characterized exposure; image is repaired by interpolating over cosmic rays,
mask is updated accordingly, and the PSF model is set
- sourceCat detected sources (an lsst.afw.table.SourceCatalog)
- background model of background subtracted from exposure (an lsst.afw.math.BackgroundList)
- psfCellSet spatial cells of PSF candidates (an lsst.afw.math.SpatialCellSet)
"""
# install a simple PSF model, if needed or wanted
if not exposure.hasPsf() or (self.config.doMeasurePsf
and self.config.useSimplePsf):
self.log.warn(
"Source catalog detected and measured with placeholder or default PSF"
)
self.installSimplePsf.run(exposure=exposure)
# run repair, but do not interpolate over cosmic rays (do that elsewhere, with the final PSF model)
self.repair.run(exposure=exposure, keepCRs=True)
self.display("repair_iter", exposure=exposure)
if background is None:
background = BackgroundList()
sourceIdFactory = IdFactory.makeSource(exposureIdInfo.expId,
exposureIdInfo.unusedBits)
table = SourceTable.make(self.schema, sourceIdFactory)
table.setMetadata(self.algMetadata)
detRes = self.detection.run(table=table,
exposure=exposure,
doSmooth=True)
sourceCat = detRes.sources
if detRes.fpSets.background:
for bg in detRes.fpSets.background:
background.append(bg)
if self.config.doDeblend:
self.deblend.run(exposure=exposure, sources=sourceCat)
self.measurement.run(measCat=sourceCat,
exposure=exposure,
exposureId=exposureIdInfo.expId)
measPsfRes = pipeBase.Struct(cellSet=None)
if self.config.doMeasurePsf:
if self.measurePsf.usesMatches:
matches = self.ref_match.loadAndMatch(
exposure=exposure, sourceCat=sourceCat).matches
else:
matches = None
measPsfRes = self.measurePsf.run(exposure=exposure,
sources=sourceCat,
matches=matches,
expId=exposureIdInfo.expId)
self.display("measure_iter", exposure=exposure, sourceCat=sourceCat)
return pipeBase.Struct(
exposure=exposure,
sourceCat=sourceCat,
background=background,
psfCellSet=measPsfRes.cellSet,
)
def characterize(self, exposure, exposureIdInfo, background=None):
"""!Characterize a science image
Peforms the following operations:
- Iterate the following config.psfIterations times, or once if config.doMeasurePsf false:
- detect and measure sources and estimate PSF (see detectMeasureAndEstimatePsf for details)
- interpolate over cosmic rays
- perform final measurement
@param[in,out] exposure exposure to characterize (an lsst.afw.image.ExposureF or similar).
The following changes are made:
- update or set psf
- set apCorrMap
- update detection and cosmic ray mask planes
- subtract background and interpolate over cosmic rays
@param[in] exposureIdInfo ID info for exposure (an lsst.daf.butlerUtils.ExposureIdInfo)
@param[in] background model of background model already subtracted from exposure
(an lsst.afw.math.BackgroundList). May be None if no background has been subtracted,
which is typical for image characterization.
@return pipe_base Struct containing these fields, all from the final iteration
of detectMeasureAndEstimatePsf:
- exposure: characterized exposure; image is repaired by interpolating over cosmic rays,
mask is updated accordingly, and the PSF model is set
- sourceCat: detected sources (an lsst.afw.table.SourceCatalog)
- background: model of background subtracted from exposure (an lsst.afw.math.BackgroundList)
- psfCellSet: spatial cells of PSF candidates (an lsst.afw.math.SpatialCellSet)
"""
self._frame = self._initialFrame # reset debug display frame
if not self.config.doMeasurePsf and not exposure.hasPsf():
raise RuntimeError("exposure has no PSF model and config.doMeasurePsf false")
if background is None:
background = BackgroundList()
# make a deep copy of the mask
originalMask = exposure.getMaskedImage().getMask().clone()
# subtract an initial estimate of background level
estBg = estimateBackground(
exposure = exposure,
backgroundConfig = self.config.background,
subtract = False, # this makes a deep copy, which we don't want
)[0]
image = exposure.getMaskedImage().getImage()
image -= estBg.getImageF()
background.append(estBg)
psfIterations = self.config.psfIterations if self.config.doMeasurePsf else 1
for i in range(psfIterations):
if i > 1:
# restore original mask so that detections and cosmic rays
# are only marked by the final iteration
exposure.getMaskedImage().getMask()[:] = originalMask
dmeRes = self.detectMeasureAndEstimatePsf(
exposure = exposure,
exposureIdInfo = exposureIdInfo,
background = background,
)
psf = dmeRes.exposure.getPsf()
psfSigma = psf.computeShape().getDeterminantRadius()
psfDimensions = psf.computeImage().getDimensions()
medBackground = np.median(dmeRes.background.getImage().getArray())
self.log.info("iter %s; PSF sigma=%0.2f, dimensions=%s; median background=%0.2f" % \
(i + 1, psfSigma, psfDimensions, medBackground))
self.display("psf", exposure=dmeRes.exposure, sourceCat=dmeRes.sourceCat)
# perform final repair with final PSF
self.repair.run(exposure=dmeRes.exposure)
self.display("repair", exposure=dmeRes.exposure, sourceCat=dmeRes.sourceCat)
# perform final measurement with final PSF, including measuring and applying aperture correction,
# if wanted
self.detectAndMeasure.measure(
exposure = dmeRes.exposure,
exposureIdInfo = exposureIdInfo,
sourceCat = dmeRes.sourceCat,
allowApCorr = True, # the default; listed for emphasis
)
self.display("measure", exposure=dmeRes.exposure, sourceCat=dmeRes.sourceCat)
return dmeRes
def run(self, exposure, exposureIdInfo=None, background=None,
icSourceCat=None):
"""!Calibrate an exposure (science image or coadd)
@param[in,out] exposure exposure to calibrate (an
lsst.afw.image.ExposureF or similar);
in:
- MaskedImage
- Psf
out:
- MaskedImage has background subtracted
- Wcs is replaced
- PhotoCalib is replaced
@param[in] exposureIdInfo ID info for exposure (an
lsst.obs.base.ExposureIdInfo) If not provided, returned
SourceCatalog IDs will not be globally unique.
@param[in,out] background background model already subtracted from
exposure (an lsst.afw.math.BackgroundList). May be None if no
background has been subtracted, though that is unusual for
calibration. A refined background model is output.
@param[in] icSourceCat A SourceCatalog from CharacterizeImageTask
from which we can copy some fields.
@return pipe_base Struct containing these fields:
- exposure calibrate science exposure with refined WCS and PhotoCalib
- background model of background subtracted from exposure (an
lsst.afw.math.BackgroundList)
- sourceCat catalog of measured sources
- astromMatches list of source/refObj matches from the astrometry
solver
"""
# detect, deblend and measure sources
if exposureIdInfo is None:
exposureIdInfo = ExposureIdInfo()
if background is None:
background = BackgroundList()
sourceIdFactory = IdFactory.makeSource(exposureIdInfo.expId,
exposureIdInfo.unusedBits)
table = SourceTable.make(self.schema, sourceIdFactory)
table.setMetadata(self.algMetadata)
detRes = self.detection.run(table=table, exposure=exposure,
doSmooth=True)
sourceCat = detRes.sources
if detRes.fpSets.background:
for bg in detRes.fpSets.background:
background.append(bg)
if self.config.doSkySources:
skySourceFootprints = self.skySources.run(mask=exposure.mask, seed=exposureIdInfo.expId)
if skySourceFootprints:
for foot in skySourceFootprints:
s = sourceCat.addNew()
s.setFootprint(foot)
s.set(self.skySourceKey, True)
if self.config.doDeblend:
self.deblend.run(exposure=exposure, sources=sourceCat)
self.measurement.run(
measCat=sourceCat,
exposure=exposure,
exposureId=exposureIdInfo.expId
)
if self.config.doApCorr:
self.applyApCorr.run(
catalog=sourceCat,
apCorrMap=exposure.getInfo().getApCorrMap()
)
self.catalogCalculation.run(sourceCat)
self.setPrimaryFlags.run(sourceCat, includeDeblend=self.config.doDeblend)
if icSourceCat is not None and \
len(self.config.icSourceFieldsToCopy) > 0:
self.copyIcSourceFields(icSourceCat=icSourceCat,
sourceCat=sourceCat)
# TODO DM-11568: this contiguous check-and-copy could go away if we
# reserve enough space during SourceDetection and/or SourceDeblend.
# NOTE: sourceSelectors require contiguous catalogs, so ensure
# contiguity now, so views are preserved from here on.
if not sourceCat.isContiguous():
sourceCat = sourceCat.copy(deep=True)
# perform astrometry calibration:
# fit an improved WCS and update the exposure's WCS in place
astromMatches = None
matchMeta = None
if self.config.doAstrometry:
try:
astromRes = self.astrometry.run(
exposure=exposure,
sourceCat=sourceCat,
)
astromMatches = astromRes.matches
matchMeta = astromRes.matchMeta
except Exception as e:
if self.config.requireAstrometry:
raise
self.log.warn("Unable to perform astrometric calibration "
"(%s): attempting to proceed" % e)
# compute photometric calibration
if self.config.doPhotoCal:
try:
photoRes = self.photoCal.run(exposure, sourceCat=sourceCat, expId=exposureIdInfo.expId)
exposure.setPhotoCalib(photoRes.photoCalib)
# TODO: reword this to phrase it in terms of the calibration factor?
self.log.info("Photometric zero-point: %f" %
photoRes.photoCalib.instFluxToMagnitude(1.0))
self.setMetadata(exposure=exposure, photoRes=photoRes)
except Exception as e:
if self.config.requirePhotoCal:
raise
self.log.warn("Unable to perform photometric calibration "
"(%s): attempting to proceed" % e)
self.setMetadata(exposure=exposure, photoRes=None)
if self.config.doInsertFakes:
self.insertFakes.run(exposure, background=background)
table = SourceTable.make(self.schema, sourceIdFactory)
table.setMetadata(self.algMetadata)
detRes = self.detection.run(table=table, exposure=exposure,
doSmooth=True)
sourceCat = detRes.sources
if detRes.fpSets.background:
for bg in detRes.fpSets.background:
background.append(bg)
if self.config.doDeblend:
self.deblend.run(exposure=exposure, sources=sourceCat)
self.measurement.run(
measCat=sourceCat,
exposure=exposure,
exposureId=exposureIdInfo.expId
)
if self.config.doApCorr:
self.applyApCorr.run(
catalog=sourceCat,
apCorrMap=exposure.getInfo().getApCorrMap()
)
self.catalogCalculation.run(sourceCat)
if icSourceCat is not None and len(self.config.icSourceFieldsToCopy) > 0:
self.copyIcSourceFields(icSourceCat=icSourceCat,
sourceCat=sourceCat)
frame = getDebugFrame(self._display, "calibrate")
if frame:
displayAstrometry(
sourceCat=sourceCat,
exposure=exposure,
matches=astromMatches,
frame=frame,
pause=False,
)
return pipeBase.Struct(
exposure=exposure,
background=background,
sourceCat=sourceCat,
astromMatches=astromMatches,
matchMeta=matchMeta,
# These are duplicate entries with different names for use with
# gen3 middleware
outputExposure=exposure,
outputCat=sourceCat,
outputBackground=background,
)
def calibrate(self,
exposure,
exposureIdInfo=None,
background=None,
icSourceCat=None):
"""!Calibrate an exposure (science image or coadd)
@param[in,out] exposure exposure to calibrate (an
lsst.afw.image.ExposureF or similar);
in:
- MaskedImage
- Psf
out:
- MaskedImage has background subtracted
- Wcs is replaced
- Calib zero-point is set
@param[in] exposureIdInfo ID info for exposure (an
lsst.obs.base.ExposureIdInfo) If not provided, returned
SourceCatalog IDs will not be globally unique.
@param[in,out] background background model already subtracted from
exposure (an lsst.afw.math.BackgroundList). May be None if no
background has been subtracted, though that is unusual for
calibration. A refined background model is output.
@param[in] icSourceCat A SourceCatalog from CharacterizeImageTask
from which we can copy some fields.
@return pipe_base Struct containing these fields:
- exposure calibrate science exposure with refined WCS and Calib
- background model of background subtracted from exposure (an
lsst.afw.math.BackgroundList)
- sourceCat catalog of measured sources
- astromMatches list of source/refObj matches from the astrometry
solver
"""
# detect, deblend and measure sources
if exposureIdInfo is None:
exposureIdInfo = ExposureIdInfo()
if background is None:
background = BackgroundList()
sourceIdFactory = IdFactory.makeSource(exposureIdInfo.expId,
exposureIdInfo.unusedBits)
table = SourceTable.make(self.schema, sourceIdFactory)
table.setMetadata(self.algMetadata)
if self.config.doInsertFakes:
self.insertFakes.run(exposure, background=background)
detRes = self.detection.run(table=table,
exposure=exposure,
doSmooth=True)
sourceCat = detRes.sources
if detRes.fpSets.background:
background.append(detRes.fpSets.background)
if self.config.doDeblend:
self.deblend.run(exposure=exposure, sources=sourceCat)
self.measurement.run(measCat=sourceCat,
exposure=exposure,
exposureId=exposureIdInfo.expId)
if self.config.doApCorr:
self.applyApCorr.run(catalog=sourceCat,
apCorrMap=exposure.getInfo().getApCorrMap())
self.catalogCalculation.run(sourceCat)
if icSourceCat is not None and \
len(self.config.icSourceFieldsToCopy) > 0:
self.copyIcSourceFields(icSourceCat=icSourceCat,
sourceCat=sourceCat)
# perform astrometry calibration:
# fit an improved WCS and update the exposure's WCS in place
astromMatches = None
if self.config.doAstrometry:
try:
astromRes = self.astrometry.run(
exposure=exposure,
sourceCat=sourceCat,
)
astromMatches = astromRes.matches
except Exception as e:
if self.config.requireAstrometry:
raise
self.log.warn("Unable to perform astrometric calibration "
"(%s): attempting to proceed" % e)
# compute photometric calibration
if self.config.doPhotoCal:
try:
photoRes = self.photoCal.run(exposure, sourceCat=sourceCat)
exposure.getCalib().setFluxMag0(photoRes.calib.getFluxMag0())
self.log.info("Photometric zero-point: %f" %
photoRes.calib.getMagnitude(1.0))
self.setMetadata(exposure=exposure, photoRes=photoRes)
except Exception as e:
if self.config.requirePhotoCal:
raise
self.log.warn("Unable to perform photometric calibration "
"(%s): attempting to proceed" % e)
self.setMetadata(exposure=exposure, photoRes=None)
frame = getDebugFrame(self._display, "calibrate")
if frame:
displayAstrometry(
sourceCat=sourceCat,
exposure=exposure,
matches=astromMatches,
frame=frame,
pause=False,
)
return pipeBase.Struct(
exposure=exposure,
background=background,
sourceCat=sourceCat,
astromMatches=astromMatches,
)
def characterize(self, exposure, exposureIdInfo, background=None):
"""!Characterize a science image
Peforms the following operations:
- Iterate the following config.psfIterations times, or once if config.doMeasurePsf false:
- detect and measure sources and estimate PSF (see detectMeasureAndEstimatePsf for details)
- interpolate over cosmic rays
- perform final measurement
@param[in,out] exposure exposure to characterize (an lsst.afw.image.ExposureF or similar).
The following changes are made:
- update or set psf
- set apCorrMap
- update detection and cosmic ray mask planes
- subtract background and interpolate over cosmic rays
@param[in] exposureIdInfo ID info for exposure (an lsst.daf.butlerUtils.ExposureIdInfo)
@param[in] background model of background model already subtracted from exposure
(an lsst.afw.math.BackgroundList). May be None if no background has been subtracted,
which is typical for image characterization.
@return pipe_base Struct containing these fields, all from the final iteration
of detectMeasureAndEstimatePsf:
- exposure: characterized exposure; image is repaired by interpolating over cosmic rays,
mask is updated accordingly, and the PSF model is set
- sourceCat: detected sources (an lsst.afw.table.SourceCatalog)
- background: model of background subtracted from exposure (an lsst.afw.math.BackgroundList)
- psfCellSet: spatial cells of PSF candidates (an lsst.afw.math.SpatialCellSet)
"""
self._frame = self._initialFrame # reset debug display frame
if not self.config.doMeasurePsf and not exposure.hasPsf():
raise RuntimeError(
"exposure has no PSF model and config.doMeasurePsf false")
if background is None:
background = BackgroundList()
# make a deep copy of the mask
originalMask = exposure.getMaskedImage().getMask().clone()
# subtract an initial estimate of background level
estBg = estimateBackground(
exposure=exposure,
backgroundConfig=self.config.background,
subtract=False, # this makes a deep copy, which we don't want
)[0]
image = exposure.getMaskedImage().getImage()
image -= estBg.getImageF()
background.append(estBg)
psfIterations = self.config.psfIterations if self.config.doMeasurePsf else 1
for i in range(psfIterations):
if i > 1:
# restore original mask so that detections and cosmic rays
# are only marked by the final iteration
exposure.getMaskedImage().getMask()[:] = originalMask
dmeRes = self.detectMeasureAndEstimatePsf(
exposure=exposure,
exposureIdInfo=exposureIdInfo,
background=background,
)
psf = dmeRes.exposure.getPsf()
psfSigma = psf.computeShape().getDeterminantRadius()
psfDimensions = psf.computeImage().getDimensions()
medBackground = np.median(dmeRes.background.getImage().getArray())
self.log.info("iter %s; PSF sigma=%0.2f, dimensions=%s; median background=%0.2f" % \
(i + 1, psfSigma, psfDimensions, medBackground))
self.display("psf",
exposure=dmeRes.exposure,
sourceCat=dmeRes.sourceCat)
# perform final repair with final PSF
self.repair.run(exposure=dmeRes.exposure)
self.display("repair",
exposure=dmeRes.exposure,
sourceCat=dmeRes.sourceCat)
# perform final measurement with final PSF, including measuring and applying aperture correction,
# if wanted
self.detectAndMeasure.measure(
exposure=dmeRes.exposure,
exposureIdInfo=exposureIdInfo,
sourceCat=dmeRes.sourceCat,
allowApCorr=True, # the default; listed for emphasis
)
self.display("measure",
exposure=dmeRes.exposure,
sourceCat=dmeRes.sourceCat)
return dmeRes
def detectMeasureAndEstimatePsf(self, exposure, exposureIdInfo, background):
"""!Perform one iteration of detect, measure and estimate PSF
Performs the following operations:
- if config.doMeasurePsf or not exposure.hasPsf():
- install a simple PSF model (replacing the existing one, if need be)
- interpolate over cosmic rays with keepCRs=True
- estimate background and subtract it from the exposure
- detect, deblend and measure sources, and subtract a refined background model;
- if config.doMeasurePsf:
- measure PSF
@param[in,out] exposure exposure to characterize (an lsst.afw.image.ExposureF or similar)
The following changes are made:
- update or set psf
- update detection and cosmic ray mask planes
- subtract background
@param[in] exposureIdInfo ID info for exposure (an lsst.obs_base.ExposureIdInfo)
@param[in,out] background initial model of background already subtracted from exposure
(an lsst.afw.math.BackgroundList).
@return pipe_base Struct containing these fields, all from the final iteration
of detect sources, measure sources and estimate PSF:
- exposure characterized exposure; image is repaired by interpolating over cosmic rays,
mask is updated accordingly, and the PSF model is set
- sourceCat detected sources (an lsst.afw.table.SourceCatalog)
- background model of background subtracted from exposure (an lsst.afw.math.BackgroundList)
- psfCellSet spatial cells of PSF candidates (an lsst.afw.math.SpatialCellSet)
"""
# install a simple PSF model, if needed or wanted
if not exposure.hasPsf() or (self.config.doMeasurePsf and self.config.useSimplePsf):
self.log.warn("Source catalog detected and measured with placeholder or default PSF")
self.installSimplePsf.run(exposure=exposure)
# run repair, but do not interpolate over cosmic rays (do that elsewhere, with the final PSF model)
self.repair.run(exposure=exposure, keepCRs=True)
self.display("repair_iter", exposure=exposure)
if background is None:
background = BackgroundList()
sourceIdFactory = IdFactory.makeSource(exposureIdInfo.expId, exposureIdInfo.unusedBits)
table = SourceTable.make(self.schema, sourceIdFactory)
table.setMetadata(self.algMetadata)
detRes = self.detection.run(table=table, exposure=exposure, doSmooth=True)
sourceCat = detRes.sources
if detRes.fpSets.background:
for bg in detRes.fpSets.background:
background.append(bg)
if self.config.doDeblend:
self.deblend.run(exposure=exposure, sources=sourceCat)
self.measurement.run(measCat=sourceCat, exposure=exposure, exposureId=exposureIdInfo.expId)
measPsfRes = pipeBase.Struct(cellSet=None)
if self.config.doMeasurePsf:
if self.measurePsf.usesMatches:
matches = self.ref_match.loadAndMatch(exposure=exposure, sourceCat=sourceCat).matches
else:
matches = None
measPsfRes = self.measurePsf.run(exposure=exposure, sources=sourceCat, matches=matches,
expId=exposureIdInfo.expId)
self.display("measure_iter", exposure=exposure, sourceCat=sourceCat)
return pipeBase.Struct(
exposure=exposure,
sourceCat=sourceCat,
background=background,
psfCellSet=measPsfRes.cellSet,
)