def testBasics(self):
bbox = lsst.geom.Box2I(lsst.geom.Point2I(256, 100), lsst.geom.Extent2I(128, 127))
minCounts = 2000
maxCounts = 20000
starSigma = 1.5
numX = 4
numY = 4
coordList = self.makeCoordList(
bbox=bbox,
numX=numX,
numY=numY,
minCounts=minCounts,
maxCounts=maxCounts,
sigma=starSigma,
)
kwid = 11
sky = 2000
addPoissonNoise = True
exposure = plantSources(bbox=bbox, kwid=kwid, sky=sky, coordList=coordList,
addPoissonNoise=addPoissonNoise)
if display:
disp = afwDisplay.Display(frame=1)
disp.mtv(exposure, title=self._testMethodName + ": image with -ve sources")
schema = afwTable.SourceTable.makeMinimalSchema()
config = SourceDetectionTask.ConfigClass()
config.reEstimateBackground = False
config.thresholdPolarity = 'both'
detection = SourceDetectionTask(config=config, schema=schema)
algMetadata = dafBase.PropertyList()
measurement = SourceMeasurementTask(schema=schema, algMetadata=algMetadata)
table = afwTable.SourceTable.make(schema)
detections = detection.makeSourceCatalog(table, exposure)
sources = detections.sources
fpSets = detections.fpSets
self.assertEqual(len(sources), numX*numY)
self.assertEqual(fpSets.numPos, numX*numY/2)
self.assertEqual(fpSets.numNeg, numX*numY/2)
measurement.run(sources, exposure)
nGoodCent = 0
nGoodShape = 0
for s in sources:
cent = s.getCentroid()
shape = s.getShape()
if cent[0] == cent[0] and cent[1] == cent[1]:
nGoodCent += 1
if (shape.getIxx() == shape.getIxx() and
shape.getIyy() == shape.getIyy() and
shape.getIxy() == shape.getIxy()):
nGoodShape += 1
if display:
xy = cent[0], cent[1]
disp.dot('+', *xy)
disp.dot(shape, *xy, ctype=afwDisplay.RED)
self.assertEqual(nGoodCent, numX*numY)
self.assertEqual(nGoodShape, numX*numY)
def testBasics(self):
bbox = afwGeom.Box2I(afwGeom.Point2I(256, 100),
afwGeom.Extent2I(128, 127))
minCounts = 2000
maxCounts = 20000
starSigma = 1.5
numX = 4
numY = 4
coordList = self.makeCoordList(
bbox=bbox,
numX=numX,
numY=numY,
minCounts=minCounts,
maxCounts=maxCounts,
sigma=starSigma,
)
kwid = 11
sky = 2000
addPoissonNoise = True
exposure = plantSources(bbox=bbox,
kwid=kwid,
sky=sky,
coordList=coordList,
addPoissonNoise=addPoissonNoise)
if display:
ds9.mtv(exposure)
schema = afwTable.SourceTable.makeMinimalSchema()
config = SourceDetectionTask.ConfigClass()
config.reEstimateBackground = False
config.thresholdPolarity = 'both'
detection = SourceDetectionTask(config=config, schema=schema)
algMetadata = dafBase.PropertyList()
measurement = SourceMeasurementTask(schema=schema,
algMetadata=algMetadata)
table = afwTable.SourceTable.make(schema)
detections = detection.makeSourceCatalog(table, exposure)
sources = detections.sources
fpSets = detections.fpSets
self.assertEqual(len(sources), numX * numY)
self.assertEqual(fpSets.numPos, numX * numY / 2)
self.assertEqual(fpSets.numNeg, numX * numY / 2)
measurement.run(sources, exposure)
nGoodCent = 0
nGoodShape = 0
for s in sources:
cent = s.getCentroid()
shape = s.getShape()
if cent[0] == cent[0] and cent[1] == cent[1]:
nGoodCent += 1
if (shape.getIxx() == shape.getIxx()
and shape.getIyy() == shape.getIyy()
and shape.getIxy() == shape.getIxy()):
nGoodShape += 1
if display:
xy = cent[0] - exposure.getX0(), cent[1] - exposure.getY0()
ds9.dot('+', *xy)
ds9.dot(shape, *xy, ctype=ds9.RED)
self.assertEqual(nGoodCent, numX * numY)
self.assertEqual(nGoodShape, numX * numY)
detections = {}
exposures = {}
for filter_ in filter_names:
print 'detecting in ', filter_
lsst_image = lsst_images[filter_]
exposure = afwImage.ExposureF(lsst_image.getBBox(afwImage.PARENT))
exposure.getMaskedImage().getImage().getArray(
)[:, :] = lsst_image.getArray()
exposure.getMaskedImage().getVariance().set(noise_sigma**2)
exposure.setPsf(kernelPsf)
exposure.setWcs(wcs)
exposure.setCalib(calib)
exposures[filter_] = exposure
result = detectTask.makeSourceCatalog(table, exposure)
detections[filter_] = result.sources
result.sources.writeFits('%s/det_%s.fits' % (args.output_dir, filter_))
# merge detection lists together
merged = afwDet.FootprintMergeList(schema,
[filter_ for filter_ in filter_names])
id_factory = afwTable.IdFactory.makeSource(0, 32)
merged_sources = merged.getMergedSourceCatalog(
[detections[filter_] for filter_ in filter_names],
[filter_ for filter_ in filter_names], 6, schema, id_factory, 1.8)
for record in merged_sources:
record.getFootprint().sortPeaks()
print 'Total merged objects', len(merged_sources)
