def run(
self,
refCatalogs: typing.List[afwTable.SimpleCatalog],
exposure: afwImage.Exposure,
) -> pipeBase.Struct:
refObjLoader = self.getRefObjLoader(refCatalogs)
detector = exposure.getDetector()
detectorWcs = exposure.getWcs()
try:
# Match detector layout to reference catalog
refSelection = self.runSelection(refObjLoader, detector,
detectorWcs, self.filterName)
# Except RuntimeError caused when no reference catalog
# available for the region covered by detector
except RuntimeError:
warnings.warn(
"No catalogs cover this detector. Returning empty catalog.",
RuntimeWarning,
)
refSelection = None
fieldObjects = self.donutCatalogToDataFrame(refSelection)
return pipeBase.Struct(donutCatalog=fieldObjects)
def run(
self,
exposure: afwImage.Exposure,
) -> pipeBase.Struct:
detectorName = exposure.getDetector().getName()
defocalType = DefocalType.Extra # we use one of the DefocalTypes,
# TODO: perhaps could make that as another configurable
camType = getCamType(self.instName)
pixelScale = exposure.getWcs().getPixelScale().asArcseconds()
# create a donut template
templateMaker = DonutTemplateFactory.createDonutTemplate(
DonutTemplateType.Model)
template = templateMaker.makeTemplate(
detectorName,
defocalType,
self.donutTemplateSize,
camType,
self.opticalModel,
pixelScale,
)
# given this template, detect donuts in one of the defocal images
detector = DonutDetector()
expArray = copy(exposure.getImage().getArray())
donutDf = detector.detectDonuts(
expArray,
template,
blendRadius=self.blendRadius,
peakThreshold=self.peakThreshold,
binaryChoice=self.binaryChoice,
)
# make a donut catalog :
# 1) remove the blends in donut catalog
if self.config.removeBlends:
donutDfCopy = donutDf[~donutDf["blended"]].copy()
else:
donutDfCopy = donutDf
# 2) update column names and content
donutCatUpd = self.updateDonutCatalog(donutDfCopy, exposure)
return pipeBase.Struct(donutCatalog=donutCatUpd)
def run(self, exposure: afwImage.Exposure,
inputCatalog: afwTable.SourceCatalog, msg: str) -> pipeBase.Struct:
self.log.info(f"Running aperture phot {msg}")
# Get the dimensions of the exposure
dimensions = exposure.getDimensions()
# Get indexes for each pixel
indy, indx = np.indices((dimensions.getY(), dimensions.getX()))
# Loop over each record in the catalog
for i, source in enumerate(inputCatalog):
if i % 100 == 0:
self.log.info(f"Processing record {i}")
# Create an aperture and measure the flux
center = source.getCentroid()
mask = ((indy - center.getY())**2 +
(indx - center.getX())**2)**0.5 < self.apRad
flux = np.sum(exposure.image.array * mask)
# Add a record to the output catalog
tmpRecord = self.outputCatalog.addNew()
tmpRecord.set(self.apKey, flux)
return pipeBase.Struct(outputCatalog=self.outputCatalog)
def testMultiPlaneFitsReaders(self):
"""Run tests for MaskedImageFitsReader and ExposureFitsReader.
"""
metadata = PropertyList()
metadata.add("FIVE", 5)
metadata.add("SIX", 6.0)
wcs = makeSkyWcs(Point2D(2.5, 3.75),
SpherePoint(40.0 * degrees, 50.0 * degrees),
np.array([[1E-5, 0.0], [0.0, -1E-5]]))
defineFilter("test_readers_filter", lambdaEff=470.0)
calib = PhotoCalib(2.5E4)
psf = GaussianPsf(21, 21, 8.0)
polygon = Polygon(Box2D(self.bbox))
apCorrMap = ApCorrMap()
visitInfo = VisitInfo(exposureTime=5.0)
transmissionCurve = TransmissionCurve.makeIdentity()
coaddInputs = CoaddInputs(ExposureTable.makeMinimalSchema(),
ExposureTable.makeMinimalSchema())
detector = DetectorWrapper().detector
record = coaddInputs.ccds.addNew()
record.setWcs(wcs)
record.setPhotoCalib(calib)
record.setPsf(psf)
record.setValidPolygon(polygon)
record.setApCorrMap(apCorrMap)
record.setVisitInfo(visitInfo)
record.setTransmissionCurve(transmissionCurve)
record.setDetector(detector)
for n, dtypeIn in enumerate(self.dtypes):
with self.subTest(dtypeIn=dtypeIn):
exposureIn = Exposure(self.bbox, dtype=dtypeIn)
shape = exposureIn.image.array.shape
exposureIn.image.array[:, :] = np.random.randint(low=1,
high=5,
size=shape)
exposureIn.mask.array[:, :] = np.random.randint(low=1,
high=5,
size=shape)
exposureIn.variance.array[:, :] = np.random.randint(low=1,
high=5,
size=shape)
exposureIn.setMetadata(metadata)
exposureIn.setWcs(wcs)
exposureIn.setFilter(Filter("test_readers_filter"))
exposureIn.setFilterLabel(
FilterLabel(physical="test_readers_filter"))
exposureIn.setPhotoCalib(calib)
exposureIn.setPsf(psf)
exposureIn.getInfo().setValidPolygon(polygon)
exposureIn.getInfo().setApCorrMap(apCorrMap)
exposureIn.getInfo().setVisitInfo(visitInfo)
exposureIn.getInfo().setTransmissionCurve(transmissionCurve)
exposureIn.getInfo().setCoaddInputs(coaddInputs)
exposureIn.setDetector(detector)
with lsst.utils.tests.getTempFilePath(".fits") as fileName:
exposureIn.writeFits(fileName)
self.checkMaskedImageFitsReader(exposureIn, fileName,
self.dtypes[n:])
self.checkExposureFitsReader(exposureIn, fileName,
self.dtypes[n:])
def testMultiPlaneFitsReaders(self):
"""Run tests for MaskedImageFitsReader and ExposureFitsReader.
"""
metadata = PropertyList()
metadata.add("FIVE", 5)
metadata.add("SIX", 6.0)
wcs = makeSkyWcs(Point2D(2.5, 3.75), SpherePoint(40.0*degrees, 50.0*degrees),
np.array([[1E-5, 0.0], [0.0, -1E-5]]))
defineFilter("test_readers_filter", lambdaEff=470.0)
calib = PhotoCalib(2.5E4)
psf = GaussianPsf(21, 21, 8.0)
polygon = Polygon(Box2D(self.bbox))
apCorrMap = ApCorrMap()
visitInfo = VisitInfo(exposureTime=5.0)
transmissionCurve = TransmissionCurve.makeIdentity()
coaddInputs = CoaddInputs(ExposureTable.makeMinimalSchema(), ExposureTable.makeMinimalSchema())
detector = DetectorWrapper().detector
record = coaddInputs.ccds.addNew()
record.setWcs(wcs)
record.setCalib(calib)
record.setPsf(psf)
record.setValidPolygon(polygon)
record.setApCorrMap(apCorrMap)
record.setVisitInfo(visitInfo)
record.setTransmissionCurve(transmissionCurve)
record.setDetector(detector)
for n, dtypeIn in enumerate(self.dtypes):
with self.subTest(dtypeIn=dtypeIn):
exposureIn = Exposure(self.bbox, dtype=dtypeIn)
shape = exposureIn.image.array.shape
exposureIn.image.array[:, :] = np.random.randint(low=1, high=5, size=shape)
exposureIn.mask.array[:, :] = np.random.randint(low=1, high=5, size=shape)
exposureIn.variance.array[:, :] = np.random.randint(low=1, high=5, size=shape)
exposureIn.setMetadata(metadata)
exposureIn.setWcs(wcs)
exposureIn.setFilter(Filter("test_readers_filter"))
exposureIn.setCalib(calib)
exposureIn.setPsf(psf)
exposureIn.getInfo().setValidPolygon(polygon)
exposureIn.getInfo().setApCorrMap(apCorrMap)
exposureIn.getInfo().setVisitInfo(visitInfo)
exposureIn.getInfo().setTransmissionCurve(transmissionCurve)
exposureIn.getInfo().setCoaddInputs(coaddInputs)
exposureIn.setDetector(detector)
with lsst.utils.tests.getTempFilePath(".fits") as fileName:
exposureIn.writeFits(fileName)
self.checkMaskedImageFitsReader(exposureIn, fileName, self.dtypes[n:])
self.checkExposureFitsReader(exposureIn, fileName, self.dtypes[n:])