def testFailures(self):
"""Test deblender failure flagging (#2871)
We create a good source which is expected to pass and a bad source
which is expected to fail because its footprint goes off the image.
This latter case may not happen in practise, but it is useful for
checking the plumbing of the deblender.
"""
import lsst.meas.deblender as measDeb
self.checkDeblender()
xGood, yGood = 57, 86
# Required to be in image so we can evaluate the PSF; will put neighbour just outside
xBad, yBad = 0, 0
flux = 100.0
dims = geom.Extent2I(128, 128)
mi = afwImage.MaskedImageF(dims)
mi.getVariance().set(1.0)
image = mi.getImage()
image.set(0)
image[xGood, yGood, afwImage.LOCAL] = flux
exposure = afwImage.makeExposure(mi)
psf = algorithms.DoubleGaussianPsf(21, 21, 3.)
exposure.setPsf(psf)
schema = afwTable.SourceTable.makeMinimalSchema()
config = measDeb.SourceDeblendConfig()
config.catchFailures = True
task = measDeb.SourceDeblendTask(schema, config=config)
catalog = afwTable.SourceCatalog(schema)
def makeSource(x, y, offset=-2, size=3.0):
"""Make a source in the catalog
Two peaks are created: one at the specified
position, and one offset in x,y.
The footprint is of the nominated size.
"""
src = catalog.addNew()
spans = afwGeom.SpanSet.fromShape(int(size), offset=(x, y))
foot = afwDetection.Footprint(spans)
foot.addPeak(x, y, flux)
foot.addPeak(x + offset, y + offset, flux)
src.setFootprint(foot)
return src
good = makeSource(xGood, yGood)
bad = makeSource(xBad, yBad)
task.run(exposure, catalog)
self.assertFalse(good.get('deblend_failed'))
self.assertTrue(bad.get('deblend_failed'))
def testInclude(self):
schema = afwTable.SourceTable.makeMinimalSchema()
# Create the detection task
config = SourceDetectionTask.ConfigClass()
config.reEstimateBackground = False # Turn off so that background does not change from orig
detectionTask = SourceDetectionTask(config=config, schema=schema)
# Create the deblender Task
debConfig = measDeb.SourceDeblendConfig()
debTask = measDeb.SourceDeblendTask(schema, config=debConfig)
# Create the measurement Task
config = SingleFrameMeasurementTask.ConfigClass()
measureTask = SingleFrameMeasurementTask(schema, config=config)
# Create the output table
tab = afwTable.SourceTable.make(schema)
# Process the data
result = detectionTask.run(tab, self.calexp)
sources = result.sources
# Run the deblender
debTask.run(self.calexp, sources)
# Run the measurement task: this where the replace-with-noise occurs
measureTask.run(sources, self.calexp)
plotOnFailure = False
if display:
plotOnFailure = True
# The relative differences ranged from 0.02 to ~2. This rtol is somewhat
# random, but will certainly catch the pathology if it occurs.
self.assertFloatsAlmostEqual(
self.calexpOrig.getMaskedImage().getImage().getArray(),
self.calexp.getMaskedImage().getImage().getArray(),
rtol=1E-3,
printFailures=False,
plotOnFailure=plotOnFailure)