def getDcrModel(self, patchList, coaddRefs, visitInfo):
"""Build DCR-matched coadds from a list of exposure references.
Parameters
----------
patchList : `dict`
Dict of the patches containing valid data for each tract
coaddRefs : `list` of elements of type
`lsst.daf.butler.DeferredDatasetHandle` of
`lsst.afw.image.Exposure`
Data references to DcrModels that overlap the detector.
visitInfo : `lsst.afw.image.VisitInfo`
Metadata for the science image.
Returns
-------
`list` of elements of type `lsst.afw.image.Exposure`
Coadd exposures that overlap the detector.
"""
coaddExposureList = []
for tract in patchList:
for patch in set(patchList[tract]):
coaddRefList = [
coaddRef for coaddRef in coaddRefs
if _selectDataRef(coaddRef, tract, patch)
]
dcrModel = DcrModel.fromQuantum(
coaddRefList, self.config.effectiveWavelength,
self.config.bandwidth, self.config.numSubfilters)
coaddExposureList.append(
dcrModel.buildMatchedExposure(visitInfo=visitInfo))
return coaddExposureList
def run(self,
tractInfo,
patchList,
skyCorners,
availableCoaddRefs,
sensorRef=None,
visitInfo=None):
"""Gen2 and gen3 shared code: determination of exposure dimensions and
copying of pixels from overlapping patch regions.
Parameters
----------
skyMap : `lsst.skymap.BaseSkyMap`
SkyMap object that corresponds to the template coadd.
tractInfo : `lsst.skymap.TractInfo`
The selected tract.
patchList : iterable of `lsst.skymap.patchInfo.PatchInfo`
Patches to consider for making the template exposure.
skyCorners : list of `lsst.geom.SpherePoint`
Sky corner coordinates to be covered by the template exposure.
availableCoaddRefs : `dict` [`int`]
Dictionary of spatially relevant retrieved coadd patches,
indexed by their sequential patch number. In Gen3 mode, values are
`lsst.daf.butler.DeferredDatasetHandle` and ``.get()`` is called,
in Gen2 mode, ``sensorRef.get(**coaddef)`` is called to retrieve the coadd.
sensorRef : `lsst.daf.persistence.ButlerDataRef`, Gen2 only
Butler data reference to get coadd data.
Must be `None` for Gen3.
visitInfo : `lsst.afw.image.VisitInfo`, Gen2 only
VisitInfo to make dcr model.
Returns
-------
templateExposure: `lsst.afw.image.ExposureF`
The created template exposure.
"""
coaddWcs = tractInfo.getWcs()
# compute coadd bbox
coaddBBox = geom.Box2D()
for skyPos in skyCorners:
coaddBBox.include(coaddWcs.skyToPixel(skyPos))
coaddBBox = geom.Box2I(coaddBBox)
self.log.info("coadd dimensions=%s", coaddBBox.getDimensions())
coaddExposure = afwImage.ExposureF(coaddBBox, coaddWcs)
coaddExposure.maskedImage.set(np.nan,
afwImage.Mask.getPlaneBitMask("NO_DATA"),
np.nan)
nPatchesFound = 0
coaddFilterLabel = None
coaddPsf = None
coaddPhotoCalib = None
for patchInfo in patchList:
patchNumber = tractInfo.getSequentialPatchIndex(patchInfo)
patchSubBBox = patchInfo.getOuterBBox()
patchSubBBox.clip(coaddBBox)
if patchNumber not in availableCoaddRefs:
self.log.warning(
"skip patch=%d; patch does not exist for this coadd",
patchNumber)
continue
if patchSubBBox.isEmpty():
if isinstance(availableCoaddRefs[patchNumber],
DeferredDatasetHandle):
tract = availableCoaddRefs[patchNumber].dataId['tract']
else:
tract = availableCoaddRefs[patchNumber]['tract']
self.log.info("skip tract=%d patch=%d; no overlapping pixels",
tract, patchNumber)
continue
if self.config.coaddName == 'dcr':
patchInnerBBox = patchInfo.getInnerBBox()
patchInnerBBox.clip(coaddBBox)
if np.min(patchInnerBBox.getDimensions()
) <= 2 * self.config.templateBorderSize:
self.log.info(
"skip tract=%(tract)s, patch=%(patch)s; too few pixels.",
availableCoaddRefs[patchNumber])
continue
self.log.info("Constructing DCR-matched template for patch %s",
availableCoaddRefs[patchNumber])
dcrModel = DcrModel.fromQuantum(
availableCoaddRefs[patchNumber],
self.config.effectiveWavelength, self.config.bandwidth)
# The edge pixels of the DcrCoadd may contain artifacts due to missing data.
# Each patch has significant overlap, and the contaminated edge pixels in
# a new patch will overwrite good pixels in the overlap region from
# previous patches.
# Shrink the BBox to remove the contaminated pixels,
# but make sure it is only the overlap region that is reduced.
dcrBBox = geom.Box2I(patchSubBBox)
dcrBBox.grow(-self.config.templateBorderSize)
dcrBBox.include(patchInnerBBox)
coaddPatch = dcrModel.buildMatchedExposure(bbox=dcrBBox,
visitInfo=visitInfo)
else:
if sensorRef is None:
# Gen3
coaddPatch = availableCoaddRefs[patchNumber].get()
else:
# Gen2
coaddPatch = sensorRef.get(
**availableCoaddRefs[patchNumber])
nPatchesFound += 1
# Gen2 get() seems to clip based on bbox kwarg but we removed bbox
# calculation from caller code. Gen3 also does not do this.
overlapBox = coaddPatch.getBBox()
overlapBox.clip(coaddBBox)
coaddExposure.maskedImage.assign(
coaddPatch.maskedImage[overlapBox], overlapBox)
if coaddFilterLabel is None:
coaddFilterLabel = coaddPatch.getFilter()
# Retrieve the PSF for this coadd tract, if not already retrieved
if coaddPsf is None and coaddPatch.hasPsf():
coaddPsf = coaddPatch.getPsf()
# Retrieve the calibration for this coadd tract, if not already retrieved
if coaddPhotoCalib is None:
coaddPhotoCalib = coaddPatch.getPhotoCalib()
if coaddPhotoCalib is None:
raise RuntimeError("No coadd PhotoCalib found!")
if nPatchesFound == 0:
raise RuntimeError("No patches found!")
if coaddPsf is None:
raise RuntimeError("No coadd Psf found!")
coaddExposure.setPhotoCalib(coaddPhotoCalib)
coaddExposure.setPsf(coaddPsf)
coaddExposure.setFilter(coaddFilterLabel)
return coaddExposure