def testNoiseCoadd(self):
"""Build a coadd from noise images and compare the histogram to a chi
squared distribution
"""
numImages = 4
imShape = (150, 150)
imSigma = 1.0
imVariance = 1.0
numBins = 200
maxStdDevErr = 0.2
maxMeanErr = 1.0e-12
badMaskPlanes = ["EDGE"]
np.random.seed(0)
coadd = None
for imInd in range(numImages):
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=imShape, sigma=imSigma, variance=imVariance)
exposure = afwImage.ExposureF(maskedImage)
if not coadd:
coadd = coaddChiSq.Coadd(bbox=exposure.getBBox(),
wcs=exposure.getWcs(),
badMaskPlanes=badMaskPlanes)
coadd.addExposure(exposure)
coadd.getWeightMap()
coaddExposure = coadd.getCoadd()
histX, histY, chiSqY = makeHistogram(coaddExposure.getMaskedImage(),
numBins=numBins,
numImages=numImages)
if doPlot:
pyplot.plot(histX, histY, drawstyle="steps")
pyplot.plot(histX, chiSqY)
pyplot.ylabel('frequency')
pyplot.xlabel('sum of (counts/noise)^2')
pyplot.show()
errArr = (histY - chiSqY) * numBins # crude scaling
# print "Mean error =", errArr.mean()
# print "Std dev error = ", errArr.std()
if errArr.std() > maxStdDevErr:
self.fail("Standard deviation of error = %s > %s limit" %
(errArr.std(), maxStdDevErr))
if errArr.mean() > maxMeanErr:
self.fail("Mean of error = %s > %s limit" %
(errArr.mean(), maxMeanErr))
def testNoiseCoadd(self):
"""Build a coadd from noise images and compare the histogram to a chi squared distribution
"""
numImages = 4
imShape = (150, 150)
imSigma = 1.0
imVariance = 1.0
numBins = 200
maxStdDevErr = 0.2
maxMeanErr = 1.0e-12
badMaskPlanes = ["EDGE"]
np.random.seed(0)
coadd = None
for imInd in range(numImages):
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=imShape, sigma=imSigma, variance=imVariance)
exposure = afwImage.ExposureF(maskedImage)
if not coadd:
coadd = coaddChiSq.Coadd(
bbox=exposure.getBBox(),
wcs=exposure.getWcs(),
badMaskPlanes=badMaskPlanes)
coadd.addExposure(exposure)
coadd.getWeightMap()
coaddExposure = coadd.getCoadd()
histX, histY, chiSqY = makeHistogram(
coaddExposure.getMaskedImage(), numBins=numBins, numImages=numImages)
if doPlot:
pyplot.plot(histX, histY, drawstyle="steps")
pyplot.plot(histX, chiSqY)
pyplot.ylabel('frequency')
pyplot.xlabel('sum of (counts/noise)^2')
pyplot.show()
errArr = (histY - chiSqY) * numBins # crude scaling
# print "Mean error =", errArr.mean()
# print "Std dev error = ", errArr.std()
if errArr.std() > maxStdDevErr:
self.fail("Standard deviation of error = %s > %s limit" % (errArr.std(), maxStdDevErr))
if errArr.mean() > maxMeanErr:
self.fail("Mean of error = %s > %s limit" % (errArr.mean(), maxMeanErr))
def testFilters(self):
"""Test that the coadd filter is set correctly
"""
filterPolicyFile = pexPolicy.DefaultPolicyFile("afw",
"SdssFilters.paf",
"tests")
filterPolicy = pexPolicy.Policy.createPolicy(
filterPolicyFile, filterPolicyFile.getRepositoryPath(), True)
imageUtils.defineFiltersFromPolicy(filterPolicy, reset=True)
unkFilter = afwImage.Filter()
gFilter = afwImage.Filter("g")
rFilter = afwImage.Filter("r")
imShape = (150, 150)
imSigma = 1.0
imVariance = 1.0
badMaskPlanes = ["EDGE"]
np.random.seed(0)
coadd = None
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=imShape, sigma=imSigma, variance=imVariance)
inExp = afwImage.ExposureF(maskedImage)
coadd = coaddChiSq.Coadd(
bbox=inExp.getBBox(),
wcs=inExp.getWcs(),
badMaskPlanes=badMaskPlanes,
)
inExp.setFilter(gFilter)
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), gFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter, ))
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), gFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter, ))
inExp.setFilter(rFilter)
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), unkFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter, rFilter))
def testFilters(self):
"""Test that the coadd filter is set correctly
"""
filterPolicyFile = pexPolicy.DefaultPolicyFile("afw", "SdssFilters.paf", "tests")
filterPolicy = pexPolicy.Policy.createPolicy(
filterPolicyFile, filterPolicyFile.getRepositoryPath(), True)
imageUtils.defineFiltersFromPolicy(filterPolicy, reset=True)
unkFilter = afwImage.Filter()
gFilter = afwImage.Filter("g")
rFilter = afwImage.Filter("r")
imShape = (150, 150)
imSigma = 1.0
imVariance = 1.0
badMaskPlanes = ["EDGE"]
np.random.seed(0)
coadd = None
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=imShape, sigma=imSigma, variance=imVariance)
inExp = afwImage.ExposureF(maskedImage)
coadd = coaddChiSq.Coadd(
bbox=inExp.getBBox(),
wcs=inExp.getWcs(),
badMaskPlanes=badMaskPlanes,
)
inExp.setFilter(gFilter)
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), gFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter,))
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), gFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter,))
inExp.setFilter(rFilter)
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), unkFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter, rFilter))
def testFilters(self):
"""Test that the coadd filter is set correctly
"""
imageUtils.defineFilter("g", 468.6)
imageUtils.defineFilter("r", 616.5)
unkFilter = afwImage.Filter()
gFilter = afwImage.Filter("g")
rFilter = afwImage.Filter("r")
imShape = (150, 150)
imSigma = 1.0
imVariance = 1.0
badMaskPlanes = ["EDGE"]
np.random.seed(0)
coadd = None
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=imShape, sigma=imSigma, variance=imVariance)
inExp = afwImage.ExposureF(maskedImage)
coadd = coaddChiSq.Coadd(
bbox=inExp.getBBox(),
wcs=inExp.getWcs(),
badMaskPlanes=badMaskPlanes,
)
inExp.setFilter(gFilter)
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), gFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter, ))
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), gFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter, ))
inExp.setFilter(rFilter)
coadd.addExposure(inExp)
self.assertEqualFilters(coadd.getCoadd().getFilter(), unkFilter)
self.assertEqualFilterSets(coadd.getFilters(), (gFilter, rFilter))
config = NoiseCoaddConfig()
sys.stderr.write("""
coaddPath = %s
numImages = %d
imageShape = %s
imageSigma = %0.1f
variance = %0.1f
""" % (coaddPath, numImages, config.imageShape, config.imageSigma, config.variance))
numpy.random.seed(0)
coadd = None
for imInd in range(numImages):
print >> sys.stderr, "Create exposure %d" % (imInd,)
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=config.imageShape, sigma=config.imageSigma, variance=config.variance)
# the WCS doesn't matter; the default will do
wcs = afwImage.Wcs()
exposure = afwImage.ExposureF(maskedImage, wcs)
if not coadd:
print >> sys.stderr, "Create coadd"
coadd = coaddChiSq.Coadd.fromConfig(
bbox = exposure.getBBox(),
wcs = exposure.getWcs(),
config = config.coadd)
print >> sys.stderr, "badPixelMask=", coadd.getBadPixelMask()
coadd.addExposure(exposure)
print >> sys.stderr, "Save weight map as %s" % (weightPath,)
for lineNum, line in enumerate(infile):
line = line.strip()
if not line or line.startswith("#"):
continue
exposurePath = line
expNum += 1
try:
print("Processing exposure %s" % (exposurePath, ),
file=sys.stderr)
inputExposure = afwImage.ExposureF(exposurePath)
print("Create Gaussian noise exposure", file=sys.stderr)
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=inputExposure.getDimensions(),
sigma=config.imageSigma,
variance=config.variance,
)
exposure = afwImage.ExposureF(maskedImage,
inputExposure.getWcs())
if config.saveDebugImages:
exposure.writeFits("exposure%d.fits" % (expNum, ))
if not coadd:
print(
"Create warper and coadd with size and WCS matching the first exposure",
file=sys.stderr)
warper = afwMath.Warper.fromConfig(config.warp)
coadd = coaddChiSq.Coadd.fromConfig(
bbox=exposure.getBBox(),
config = NoiseCoaddConfig()
sys.stderr.write("""
coaddPath = %s
numImages = %d
imageShape = %s
imageSigma = %0.1f
variance = %0.1f
""" % (coaddPath, numImages, config.imageShape, config.imageSigma, config.variance))
np.random.seed(0)
coadd = None
for imInd in range(numImages):
print("Create exposure %d" % (imInd,), file=sys.stderr)
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=config.imageShape, sigma=config.imageSigma, variance=config.variance)
exposure = afwImage.ExposureF(maskedImage)
if not coadd:
print("Create coadd", file=sys.stderr)
coadd = coaddChiSq.Coadd.fromConfig(
bbox=exposure.getBBox(),
wcs=exposure.getWcs(),
config=config.coadd)
print("badPixelMask=", coadd.getBadPixelMask(), file=sys.stderr)
coadd.addExposure(exposure)
print("Save weight map as %s" % (weightPath,), file=sys.stderr)
weightMap = coadd.getWeightMap()
weightMap.writeFits(weightPath)
with file(indata, "rU") as infile:
for lineNum, line in enumerate(infile):
line = line.strip()
if not line or line.startswith("#"):
continue
exposurePath = line
expNum += 1
try:
print("Processing exposure %s" % (exposurePath,), file=sys.stderr)
inputExposure = afwImage.ExposureF(exposurePath)
print("Create Gaussian noise exposure", file=sys.stderr)
maskedImage = afwTestUtils.makeGaussianNoiseMaskedImage(
dimensions=inputExposure.getDimensions(),
sigma=config.imageSigma,
variance=config.variance,
)
exposure = afwImage.ExposureF(maskedImage, inputExposure.getWcs())
if config.saveDebugImages:
exposure.writeFits("exposure%d.fits" % (expNum,))
if not coadd:
print("Create warper and coadd with size and WCS matching the first exposure",
file=sys.stderr)
warper = afwMath.Warper.fromConfig(config.warp)
coadd = coaddChiSq.Coadd.fromConfig(
bbox=exposure.getBBox(),
wcs=exposure.getWcs(),
config=config.coadd,