def psf(self, exposure, sources):
"""Measure the PSF
@param exposure Exposure to process
@param sources Measured sources on exposure
"""
assert exposure, "No exposure provided"
assert sources, "No sources provided"
psfPolicy = self.config['psf']
selName = psfPolicy['selectName']
selPolicy = psfPolicy['select'].getPolicy()
algName = psfPolicy['algorithmName']
algPolicy = psfPolicy['algorithm'].getPolicy()
self.log.log(self.log.INFO, "Measuring PSF")
#
# Run an extra detection step to mask out faint stars
#
if False:
print "RHL is cleaning faint sources"
import lsst.afw.math as afwMath
sigma = 1.0
gaussFunc = afwMath.GaussianFunction1D(sigma)
gaussKernel = afwMath.SeparableKernel(15, 15, gaussFunc, gaussFunc)
im = exposure.getMaskedImage().getImage()
convolvedImage = im.Factory(im.getDimensions())
afwMath.convolve(convolvedImage, im, gaussKernel)
del im
fs = afwDet.makeFootprintSet(convolvedImage,
afwDet.createThreshold(4, "stdev"))
fs = afwDet.makeFootprintSet(fs, 3, True)
fs.setMask(exposure.getMaskedImage().getMask(), "DETECTED")
starSelector = measAlg.makeStarSelector(selName, selPolicy)
psfCandidateList = starSelector.selectStars(exposure, sources)
psfDeterminer = measAlg.makePsfDeterminer(algName, algPolicy)
psf, cellSet = psfDeterminer.determinePsf(exposure, psfCandidateList)
# The PSF candidates contain a copy of the source, and so we need to explicitly propagate new flags
for cand in psfCandidateList:
cand = measAlg.cast_PsfCandidateF(cand)
src = cand.getSource()
if src.getFlagForDetection() & measAlg.Flags.PSFSTAR:
ident = src.getId()
src = sources[ident]
assert src.getId() == ident
src.setFlagForDetection(src.getFlagForDetection()
| measAlg.Flags.PSFSTAR)
exposure.setPsf(psf)
return psf, cellSet
def showPsfSpatialCells(exposure, cellSet, showBadCandidates, frame=1):
maUtils.showPsfSpatialCells(exposure, cellSet,
symb="o", ctype=ds9.CYAN, ctypeUnused=ds9.YELLOW,
size=4, frame=frame)
for cell in cellSet.getCellList():
for cand in cell.begin(not showBadCandidates): # maybe include bad candidates
cand = measAlg.cast_PsfCandidateF(cand)
status = cand.getStatus()
ds9.dot('+', *cand.getSource().getCentroid(), frame=frame,
ctype=ds9.GREEN if status == afwMath.SpatialCellCandidate.GOOD else
ds9.YELLOW if status == afwMath.SpatialCellCandidate.UNKNOWN else ds9.RED)
def plotPsfCandidates(cellSet, showBadCandidates=False, frame=1):
import lsst.afw.display.utils as displayUtils
stamps = []
for cell in cellSet.getCellList():
for cand in cell.begin(not showBadCandidates): # maybe include bad candidates
cand = measAlg.cast_PsfCandidateF(cand)
try:
im = cand.getMaskedImage()
chi2 = cand.getChi2()
if chi2 < 1e100:
chi2 = "%.1f" % chi2
else:
chi2 = numpy.nan
stamps.append((im, "%d%s" %
(maUtils.splitId(cand.getSource().getId(), True)["objId"], chi2),
cand.getStatus()))
except Exception, e:
continue
def plotPsfCandidates(cellSet, showBadCandidates=False, frame=1):
import lsst.afw.display.utils as displayUtils
stamps = []
for cell in cellSet.getCellList():
for cand in cell.begin(not showBadCandidates): # maybe include bad candidates
cand = measAlg.cast_PsfCandidateF(cand)
try:
im = cand.getMaskedImage()
chi2 = cand.getChi2()
if chi2 < 1e100:
chi2 = "%.1f" % chi2
else:
chi2 = float("nan")
stamps.append((im, "%d%s" %
(maUtils.splitId(cand.getSource().getId(), True)["objId"], chi2),
cand.getStatus()))
except Exception:
continue
mos = displayUtils.Mosaic()
for im, label, status in stamps:
im = type(im)(im, True)
try:
im /= afwMath.makeStatistics(im, afwMath.MAX).getValue()
except NotImplementedError:
pass
mos.append(im, label,
ds9.GREEN if status == afwMath.SpatialCellCandidate.GOOD else
ds9.YELLOW if status == afwMath.SpatialCellCandidate.UNKNOWN else ds9.RED)
if mos.images:
mos.makeMosaic(frame=frame, title="Psf Candidates")
def testGetPcaKernel(self):
"""Convert our cellSet to a LinearCombinationKernel"""
nEigenComponents = 2
spatialOrder = 1
kernelSize = 21
nStarPerCell = 2
nStarPerCellSpatialFit = 2
tolerance = 1e-5
if display:
ds9.mtv(self.mi, frame=0)
#
# Show the candidates we're using
#
for cell in self.cellSet.getCellList():
i = 0
for cand in cell:
i += 1
source = algorithms.cast_PsfCandidateF(cand).getSource()
xc, yc = source.getXAstrom() - self.mi.getX0(), source.getYAstrom() - self.mi.getY0()
if i <= nStarPerCell:
ds9.dot("o", xc, yc, ctype=ds9.GREEN)
else:
ds9.dot("o", xc, yc, ctype=ds9.YELLOW)
pair = algorithms.createKernelFromPsfCandidates(self.cellSet, self.exposure.getDimensions(),
self.exposure.getXY0(), nEigenComponents, spatialOrder,
kernelSize, nStarPerCell)
kernel, eigenValues = pair[0], pair[1]; del pair
print "lambda", " ".join(["%g" % l for l in eigenValues])
pair = algorithms.fitSpatialKernelFromPsfCandidates(kernel, self.cellSet, nStarPerCellSpatialFit, tolerance)
status, chi2 = pair[0], pair[1]; del pair
print "Spatial fit: %s chi^2 = %.2g" % (status, chi2)
psf = algorithms.PcaPsf.swigConvert(roundTripPsf(5, algorithms.PcaPsf(kernel))) # Hurrah!
self.assertTrue(afwMath.cast_AnalyticKernel(psf.getKernel()) is None)
self.assertTrue(afwMath.cast_LinearCombinationKernel(psf.getKernel()) is not None)
self.checkTablePersistence(psf)
if display:
#print psf.getKernel().toString()
eImages = []
for k in afwMath.cast_LinearCombinationKernel(psf.getKernel()).getKernelList():
im = afwImage.ImageD(k.getDimensions())
k.computeImage(im, False)
eImages.append(im)
mos = displayUtils.Mosaic()
frame = 3
ds9.mtv(mos.makeMosaic(eImages), frame=frame)
ds9.dot("Eigen Images", 0, 0, frame=frame)
#
# Make a mosaic of PSF candidates
#
stamps = []
stampInfo = []
for cell in self.cellSet.getCellList():
for cand in cell:
#
# Swig doesn't know that we inherited from SpatialCellMaskedImageCandidate; all
# it knows is that we have a SpatialCellCandidate, and SpatialCellCandidates
# don't know about getMaskedImage; so cast the pointer to PsfCandidate
#
cand = algorithms.cast_PsfCandidateF(cand)
s = cand.getSource()
im = cand.getMaskedImage()
stamps.append(im)
stampInfo.append("[%d 0x%x]" % (s.getId(), s.getFlagForDetection()))
mos = displayUtils.Mosaic()
frame = 1
ds9.mtv(mos.makeMosaic(stamps), frame=frame, lowOrderBits=True)
for i in range(len(stampInfo)):
ds9.dot(stampInfo[i], mos.getBBox(i).getX0(), mos.getBBox(i).getY0(), frame=frame, ctype=ds9.RED)
psfImages = []
labels = []
if False:
nx, ny = 3, 4
for iy in range(ny):
for ix in range(nx):
x = int((ix + 0.5)*self.mi.getWidth()/nx)
y = int((iy + 0.5)*self.mi.getHeight()/ny)
im = psf.getImage(x, y)
psfImages.append(im.Factory(im, True))
labels.append("PSF(%d,%d)" % (int(x), int(y)))
if True:
print x, y, "PSF parameters:", psf.getKernel().getKernelParameters()
else:
nx, ny = 2, 2
for x, y in [(20, 20), (60, 20),
(60, 210), (20, 210)]:
im = psf.computeImage(afwGeom.PointD(x, y))
psfImages.append(im.Factory(im, True))
labels.append("PSF(%d,%d)" % (int(x), int(y)))
if True:
print x, y, "PSF parameters:", psf.getKernel().getKernelParameters()
frame = 2
mos.makeMosaic(psfImages, frame=frame, mode=nx)
mos.drawLabels(labels, frame=frame)
if display:
ds9.mtv(self.mi, frame=0)
psfImages = []
labels = []
if False:
nx, ny = 3, 4
for iy in range(ny):
for ix in range(nx):
x = int((ix + 0.5)*self.mi.getWidth()/nx)
y = int((iy + 0.5)*self.mi.getHeight()/ny)
algorithms.subtractPsf(psf, self.mi, x, y)
else:
nx, ny = 2, 2
for x, y in [(20, 20), (60, 20),
(60, 210), (20, 210)]:
if False: # Test subtraction with non-centered psfs
x += 0.5; y -= 0.5
#algorithms.subtractPsf(psf, self.mi, x, y)
ds9.mtv(self.mi, frame=1)
def testGetPcaKernel(self):
"""Convert our cellSet to a LinearCombinationKernel"""
nEigenComponents = 2
spatialOrder = 1
kernelSize = 21
nStarPerCell = 2
nStarPerCellSpatialFit = 2
tolerance = 1e-5
if display:
ds9.mtv(self.mi, frame=0)
#
# Show the candidates we're using
#
for cell in self.cellSet.getCellList():
i = 0
for cand in cell:
i += 1
source = algorithms.cast_PsfCandidateF(cand).getSource()
xc, yc = source.getXAstrom() - self.mi.getX0(
), source.getYAstrom() - self.mi.getY0()
if i <= nStarPerCell:
ds9.dot("o", xc, yc, ctype=ds9.GREEN)
else:
ds9.dot("o", xc, yc, ctype=ds9.YELLOW)
pair = algorithms.createKernelFromPsfCandidates(
self.cellSet, self.exposure.getDimensions(),
self.exposure.getXY0(), nEigenComponents, spatialOrder, kernelSize,
nStarPerCell)
kernel, eigenValues = pair[0], pair[1]
del pair
print "lambda", " ".join(["%g" % l for l in eigenValues])
pair = algorithms.fitSpatialKernelFromPsfCandidates(
kernel, self.cellSet, nStarPerCellSpatialFit, tolerance)
status, chi2 = pair[0], pair[1]
del pair
print "Spatial fit: %s chi^2 = %.2g" % (status, chi2)
psf = algorithms.PcaPsf.swigConvert(
roundTripPsf(5, algorithms.PcaPsf(kernel))) # Hurrah!
self.assertTrue(afwMath.cast_AnalyticKernel(psf.getKernel()) is None)
self.assertTrue(
afwMath.cast_LinearCombinationKernel(psf.getKernel()) is not None)
self.checkTablePersistence(psf)
if display:
#print psf.getKernel().toString()
eImages = []
for k in afwMath.cast_LinearCombinationKernel(
psf.getKernel()).getKernelList():
im = afwImage.ImageD(k.getDimensions())
k.computeImage(im, False)
eImages.append(im)
mos = displayUtils.Mosaic()
frame = 3
ds9.mtv(mos.makeMosaic(eImages), frame=frame)
ds9.dot("Eigen Images", 0, 0, frame=frame)
#
# Make a mosaic of PSF candidates
#
stamps = []
stampInfo = []
for cell in self.cellSet.getCellList():
for cand in cell:
#
# Swig doesn't know that we inherited from SpatialCellMaskedImageCandidate; all
# it knows is that we have a SpatialCellCandidate, and SpatialCellCandidates
# don't know about getMaskedImage; so cast the pointer to PsfCandidate
#
cand = algorithms.cast_PsfCandidateF(cand)
s = cand.getSource()
im = cand.getMaskedImage()
stamps.append(im)
stampInfo.append("[%d 0x%x]" %
(s.getId(), s.getFlagForDetection()))
mos = displayUtils.Mosaic()
frame = 1
ds9.mtv(mos.makeMosaic(stamps), frame=frame, lowOrderBits=True)
for i in range(len(stampInfo)):
ds9.dot(stampInfo[i],
mos.getBBox(i).getX0(),
mos.getBBox(i).getY0(),
frame=frame,
ctype=ds9.RED)
psfImages = []
labels = []
if False:
nx, ny = 3, 4
for iy in range(ny):
for ix in range(nx):
x = int((ix + 0.5) * self.mi.getWidth() / nx)
y = int((iy + 0.5) * self.mi.getHeight() / ny)
im = psf.getImage(x, y)
psfImages.append(im.Factory(im, True))
labels.append("PSF(%d,%d)" % (int(x), int(y)))
if True:
print x, y, "PSF parameters:", psf.getKernel(
).getKernelParameters()
else:
nx, ny = 2, 2
for x, y in [(20, 20), (60, 20), (60, 210), (20, 210)]:
im = psf.computeImage(afwGeom.PointD(x, y))
psfImages.append(im.Factory(im, True))
labels.append("PSF(%d,%d)" % (int(x), int(y)))
if True:
print x, y, "PSF parameters:", psf.getKernel(
).getKernelParameters()
frame = 2
mos.makeMosaic(psfImages, frame=frame, mode=nx)
mos.drawLabels(labels, frame=frame)
if display:
ds9.mtv(self.mi, frame=0)
psfImages = []
labels = []
if False:
nx, ny = 3, 4
for iy in range(ny):
for ix in range(nx):
x = int((ix + 0.5) * self.mi.getWidth() / nx)
y = int((iy + 0.5) * self.mi.getHeight() / ny)
algorithms.subtractPsf(psf, self.mi, x, y)
else:
nx, ny = 2, 2
for x, y in [(20, 20), (60, 20), (60, 210), (20, 210)]:
if False: # Test subtraction with non-centered psfs
x += 0.5
y -= 0.5
#algorithms.subtractPsf(psf, self.mi, x, y)
ds9.mtv(self.mi, frame=1)
algPolicy.add('kernelSizeMax', 45)
algPolicy.add('spatialOrder', 2)
algPolicy.add('nStarPerCell', 0)
algPolicy.add('nStarPerCellSpatialFit', 10)
algPolicy.add('tolerance', 1e-2)
algPolicy.add('spatialReject', 3.)
starSelector = measAlg.makeStarSelector(selName, selPolicy)
psfCandidateList = starSelector.selectStars(exposure, sources)
psfDeterminer = measAlg.makePsfDeterminer(algName, algPolicy)
psf, cellSet = psfDeterminer.determinePsf(exposure, psfCandidateList)
# The PSF candidates contain a copy of the source, and so we need to explicitly propagate new flags
for cand in psfCandidateList:
cand = measAlg.cast_PsfCandidateF(cand)
src = cand.getSource()
if src.getFlagForDetection() & measAlg.Flags.PSFSTAR:
ident = src.getId()
src = sources[ident]
assert src.getId() == ident
src.setFlagForDetection(src.getFlagForDetection()
| measAlg.Flags.PSFSTAR)
exposure.setPsf(psf)
print 'Got PSF', psf
# Target cluster
#x,y = 726., 4355.
psfimg = psf.computeImage(afwGeom.Point2D(x, y))
psfimg.writeFits(psffn)
algPolicy.add('kernelSizeMax', 45)
algPolicy.add('spatialOrder', 2)
algPolicy.add('nStarPerCell', 0)
algPolicy.add('nStarPerCellSpatialFit', 10)
algPolicy.add('tolerance', 1e-2)
algPolicy.add('spatialReject', 3.)
starSelector = measAlg.makeStarSelector(selName, selPolicy)
psfCandidateList = starSelector.selectStars(exposure, sources)
psfDeterminer = measAlg.makePsfDeterminer(algName, algPolicy)
psf, cellSet = psfDeterminer.determinePsf(exposure, psfCandidateList)
# The PSF candidates contain a copy of the source, and so we need to explicitly propagate new flags
for cand in psfCandidateList:
cand = measAlg.cast_PsfCandidateF(cand)
src = cand.getSource()
if src.getFlagForDetection() & measAlg.Flags.PSFSTAR:
ident = src.getId()
src = sources[ident]
assert src.getId() == ident
src.setFlagForDetection(src.getFlagForDetection() | measAlg.Flags.PSFSTAR)
exposure.setPsf(psf)
print 'Got PSF', psf
# Target cluster
#x,y = 726., 4355.
psfimg = psf.computeImage(afwGeom.Point2D(x,y))
psfimg.writeFits(psffn)