def setUp(self):
##Load sample input from disk
path = os.path.join(eups.productDir("meas_pipeline"), "tests")
srcSet = readSourceSet(os.path.join(path, "v695833-e0-c000.xy.txt"))
#Make a copy, with different fluxes.
#The exact choice doesn't matter ,we just want to make sure the code returns an answer
#Also need to specify that each source is a star
catSet = []
flags = malgUtil.getDetectionFlags()
goodFlag = flags['BINNED1'] | flags['STAR']
for s in srcSet:
s1 = afwDet.Source(s)
s1.setPsfFlux(s1.getPsfFlux() * .281)
catSet.append(s1)
s.setFlagForDetection(goodFlag)
#Make a SourceMatch object
maxDist = 1 / 3600. #matches must be this close together
srcMatchSet = afwDet.matchXy(catSet, srcSet, maxDist)
#Put them on the clipboard
filename = pexPolicy.DefaultPolicyFile("meas_pipeline",
"PhotoCalStageDictionary.paf",
"policy")
self.policy = pexPolicy.Policy.createPolicy(filename)
self.clipboard = pexClipboard.Clipboard()
self.clipboard.put(self.policy.get("sourceMatchSetKey"), srcMatchSet)
self.clipboard.put(self.policy.get("inputExposureKey"),
afwImage.ExposureF(afwGeom.Extent2I(10, 10)))
def setUp(self):
##Load sample input from disk
path = os.path.join(eups.productDir("meas_pipeline"), "tests")
srcSet = readSourceSet(os.path.join(path, "v695833-e0-c000.xy.txt"))
#Make a copy, with different fluxes.
#The exact choice doesn't matter ,we just want to make sure the code returns an answer
#Also need to specify that each source is a star
catSet = []
flags = malgUtil.getDetectionFlags()
goodFlag = flags['BINNED1'] | flags['STAR']
for s in srcSet:
s1 = afwDet.Source(s)
s1.setPsfFlux(s1.getPsfFlux()*.281)
catSet.append(s1)
s.setFlagForDetection(goodFlag)
#Make a SourceMatch object
maxDist = 1/3600. #matches must be this close together
srcMatchSet = afwDet.matchXy(catSet, srcSet, maxDist)
#Put them on the clipboard
filename = pexPolicy.DefaultPolicyFile("meas_pipeline",
"PhotoCalStageDictionary.paf", "policy")
self.policy = pexPolicy.Policy.createPolicy(filename)
self.clipboard = pexClipboard.Clipboard()
self.clipboard.put(self.policy.get("sourceMatchSetKey"), srcMatchSet)
self.clipboard.put(self.policy.get("inputExposureKey"), afwImage.ExposureF(afwGeom.Extent2I(10, 10)))
def getCalibObjects(butler, filterName, dataId):
"""
A version of getCalibObjectsImpl that isn't a class method, for use by other code
@param useOutputSrc # use fluxes from the "src", not "icSrc"
"""
#################################
# color calibration
#
# this stuff stolen from pipette.
# - numbers from suprimecam.paf, method in Calibrate.py
#####################
primaryLookup = {
#"B" : "g",
#"V" : "g",
#"R" : "r",
#"I" : "i",
"g" : "g",
"g" : "g",
"r" : "r",
"i" : "i",
}
# The below colour terms are from the last page of
# http://www.naoj.org/staff/nakata/suprime/illustration/colorterm_report_ver3.pdf
secondaryLookup = {
"g" : ["r", [-0.00569, -0.0427]],
"r" : ["g", [0.00261, 0.0304]],
"i" : ["r", [0.00586, 0.0827, -0.0118]],
"z" : ['i', [0.000329, 0.0608, 0.0219]],
"y" : ['i', [0.000329, 0.0608, 0.0219]],
}
# figure out which filters we need for the color term
primaryFilter = primaryLookup[filterName] # Primary band for correction
secondaryFilter = secondaryLookup[primaryFilter][0] # Secondary band for correction
log = pexLog.Log.getDefaultLog()
psources = butler.get('icSrc', dataId)
pmatches = butler.get('icMatch', dataId)
calexp_md = butler.get('calexp_md', dataId)
wcs = afwImage.makeWcs(calexp_md)
W, H = calexp_md.get("NAXIS1"), calexp_md.get("NAXIS2")
calib = afwImage.Calib(calexp_md)
matches = pmatches.getSourceMatches()
setMatchListBlobsNone(matches)
sources = psources.getSources() ## fails
setSourceSetBlobsNone(sources)
anid = pmatches.getSourceMatchMetadata().getInt('ANINDID')
del psources; del pmatches; del calexp_md # cleanup
useOutputSrc = False
if useOutputSrc:
srcs = butler.get('src', dataId).getSources()
setSourceSetBlobsNone(srcs)
import lsst.afw.detection as afwDetect
pmMatch = afwDetect.matchXy(sources, srcs, 1.0, True)
for icSrc, src, d in pmMatch:
icSrc.setPsfFlux(src.getPsfFlux())
# ref sources
xc, yc = 0.5*W, 0.5*H
radec = wcs.pixelToSky(xc, yc)
ra = radec.getLongitude(afwCoord.DEGREES)
dec = radec.getLatitude(afwCoord.DEGREES)
radius = wcs.pixelScale().asDegrees()*math.hypot(xc, yc)*1.1
pol = pexPolicy.Policy()
pol.set('matchThreshold', 30)
solver = measAstrom.createSolver(pol, log)
idName = 'id'
X = solver.getCatalogue(ra, dec, radius, primaryFilter, idName, anid)
refsources = X.refsources
setSourceSetBlobsNone(refsources)
inds = X.inds
referrs, stargal = None, None
cols = solver.getTagAlongColumns(anid)
colnames = [c.name for c in cols]
col = 'starnotgal'
if col in colnames:
stargal1 = solver.getTagAlongBool(anid, col, inds)
stargal = []
for i in range(len(stargal1)):
stargal.append(stargal1[i])
fdict = maUtils.getDetectionFlags()
# get the data for the secondary
XX = solver.getCatalogue(ra, dec, radius, secondaryFilter, idName, anid)
secondaryRefsources = XX.refsources
setSourceSetBlobsNone(secondaryRefsources)
polyData = secondaryLookup[primaryFilter][1] # Polynomial correction
polyData.reverse() # Numpy wants decreasing powers
polynomial = numpy.poly1d(polyData)
# We already have the 'primary' magnitudes in the matches
secondariesDict = dict()
for s in secondaryRefsources:
secondariesDict[s.getId()] = (s.getPsfFlux(), s.getPsfFluxErr())
del secondaryRefsources
keepref = []
keepi = []
for i in xrange(len(refsources)):
ra, dec = refsources[i].getRa(), refsources[i].getDec() # ra,dec in Rads
x, y = wcs.skyToPixel(afwCoord.Coord(afwGeom.PointD(numpy.degrees(ra), numpy.degrees(dec))))
if x < 0 or y < 0 or x > W or y > H:
continue
refsources[i].setXAstrom(x)
refsources[i].setYAstrom(y)
if stargal[i]:
refsources[i].setFlagForDetection(refsources[i].getFlagForDetection() | fdict["STAR"])
# color term
primaryMag = -2.5*numpy.log10(refsources[i].getPsfFlux())
secondaryMag = -2.5*numpy.log10(secondariesDict[refsources[i].getId()][0])
diff = polynomial(primaryMag - secondaryMag)
refsources[i].setPsfFlux(10.0**(-0.4*(primaryMag+diff)))
keepref.append(refsources[i])
keepi.append(i)
refsources = keepref
if referrs is not None:
referrs = [referrs[i] for i in keepi]
if stargal is not None:
stargal = [stargal[i] for i in keepi]
measAstrom.joinMatchList(matches, refsources, first=True, log=log)
measAstrom.joinMatchList(matches, sources, first=False, log=log)
return matches, calib, refsources
def plotsForField(inButler, keys, fixup, plots=None, prefix=''):
if plots is None:
plots = ['photom', 'matches', 'corr', 'distortion']
filters = inButler.queryMetadata('raw', 'filter', **keys)
print('Filters:', filters)
filterName = filters[0]
try:
psources = inButler.get('icSrc', **keys)
print('Got sources', psources)
except Exception:
print('"icSrc" not found. Trying "src" instead.')
psources = inButler.get('src', **keys)
print('Got sources', psources)
pmatches = inButler.get('icMatch', **keys)
sources = psources.getSources()
calexp = inButler.get('calexp', **keys)
wcs = calexp.getWcs()
photocal = calexp.getCalib()
zp = photocal.getMagnitude(1.)
print('Zeropoint is', zp)
# ref sources
W, H = calexp.getWidth(), calexp.getHeight()
log = Log.getDefaultLogger()
log.setLevel(Log.DEBUG)
kwargs = {}
if fixup:
# ugh, mask and offset req'd because source ids are assigned at write-time
# and match list code made a deep copy before that.
# (see svn+ssh://svn.lsstcorp.org/DMS/meas/astrom/tickets/1491-b r18027)
kwargs['sourceIdMask'] = 0xffff
kwargs['sourceIdOffset'] = -1
(matches, ref) = measAstrom.generateMatchesFromMatchList(
pmatches, sources, wcs, W, H, returnRefs=True, log=log, **kwargs)
print('Got', len(ref), 'reference catalog sources')
# pull 'stargal' and 'referrs' arrays out of the reference sources
fdict = maUtils.getDetectionFlags()
starflag = int(fdict["STAR"])
stargal = [bool((r.getFlagForDetection() & starflag) > 0)
for r in ref]
referrs = [float(r.getPsfInstFluxErr() / r.getPsfInstFlux() * 2.5 / -np.log(10))
for r in ref]
nstars = sum([1 for s in stargal if s])
print('Number of sources with STAR set:', nstars)
visit = keys['visit']
raft = keys['raft']
sensor = keys['sensor']
prefix += 'imsim-v%i-r%s-s%s' % (visit, raft.replace(',', ''), sensor.replace(',', ''))
if 'photom' in plots:
print('photometry plots...')
tt = 'LSST ImSim v%i r%s s%s' % (visit, raft.replace(',', ''), sensor.replace(',', ''))
wcsPlots.plotPhotometry(sources, ref, matches, prefix, band=filterName,
zp=zp, referrs=referrs, refstargal=stargal, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix, band=filterName, zp=zp,
delta=True, referrs=referrs, refstargal=stargal, title=tt)
# test w/ and w/o referrs and stargal.
if False:
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'A', band=filterName, zp=zp, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'B',
band=filterName, zp=zp, referrs=referrs, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'C',
band=filterName, zp=zp, refstargal=stargal, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'A',
band=filterName, zp=zp, delta=True, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'B', band=filterName,
zp=zp, delta=True, referrs=referrs, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'C', band=filterName,
zp=zp, delta=True, refstargal=stargal, title=tt)
if 'matches' in plots:
print('matches...')
wcsPlots.plotMatches(sources, ref, matches, wcs, W, H, prefix)
if 'distortion' in plots:
print('distortion...')
wcsPlots.plotDistortion(wcs, W, H, 400, prefix,
'SIP Distortion (exaggerated x 10)', exaggerate=10.)
print('distortion...')
wcsPlots.plotDistortion(wcs, W, H, 400, prefix,
'SIP Distortion (exaggerated x 100)', exaggerate=100.,
suffix='-distort2.')
def plotsForField(inButler, keys, fixup, plots=None, prefix=''):
if plots is None:
plots = ['photom', 'matches', 'corr', 'distortion']
filters = inButler.queryMetadata('raw', 'filter', **keys)
print('Filters:', filters)
filterName = filters[0]
psources = inButler.get('icSrc', **keys)
# since the butler does lazy evaluation, we don't know if it fails until...
try:
print('Got sources', psources)
except:
print('"icSrc" not found. Trying "src" instead.')
psources = inButler.get('src', **keys)
print('Got sources', psources)
pmatches = inButler.get('icMatch', **keys)
sources = psources.getSources()
calexp = inButler.get('calexp', **keys)
wcs = calexp.getWcs()
photocal = calexp.getCalib()
zp = photocal.getMagnitude(1.)
print('Zeropoint is', zp)
# ref sources
W, H = calexp.getWidth(), calexp.getHeight()
log = Log.getDefaultLogger()
log.setLevel(Log.DEBUG)
kwargs = {}
if fixup:
# ugh, mask and offset req'd because source ids are assigned at write-time
# and match list code made a deep copy before that.
# (see svn+ssh://svn.lsstcorp.org/DMS/meas/astrom/tickets/1491-b r18027)
kwargs['sourceIdMask'] = 0xffff
kwargs['sourceIdOffset'] = -1
(matches, ref) = measAstrom.generateMatchesFromMatchList(
pmatches, sources, wcs, W, H, returnRefs=True, log=log, **kwargs)
print('Got', len(ref), 'reference catalog sources')
# pull 'stargal' and 'referrs' arrays out of the reference sources
fdict = maUtils.getDetectionFlags()
starflag = int(fdict["STAR"])
stargal = [bool((r.getFlagForDetection() & starflag) > 0)
for r in ref]
referrs = [float(r.getPsfFluxErr() / r.getPsfFlux() * 2.5 / -np.log(10))
for r in ref]
nstars = sum([1 for s in stargal if s])
print('Number of sources with STAR set:', nstars)
visit = keys['visit']
raft = keys['raft']
sensor = keys['sensor']
prefix += 'imsim-v%i-r%s-s%s' % (visit, raft.replace(',', ''), sensor.replace(',', ''))
if 'photom' in plots:
print('photometry plots...')
tt = 'LSST ImSim v%i r%s s%s' % (visit, raft.replace(',', ''), sensor.replace(',', ''))
wcsPlots.plotPhotometry(sources, ref, matches, prefix, band=filterName,
zp=zp, referrs=referrs, refstargal=stargal, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix, band=filterName, zp=zp,
delta=True, referrs=referrs, refstargal=stargal, title=tt)
# test w/ and w/o referrs and stargal.
if False:
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'A', band=filterName, zp=zp, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'B',
band=filterName, zp=zp, referrs=referrs, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'C',
band=filterName, zp=zp, refstargal=stargal, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'A',
band=filterName, zp=zp, delta=True, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'B', band=filterName,
zp=zp, delta=True, referrs=referrs, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'C', band=filterName,
zp=zp, delta=True, refstargal=stargal, title=tt)
if 'matches' in plots:
print('matches...')
wcsPlots.plotMatches(sources, ref, matches, wcs, W, H, prefix)
if 'distortion' in plots:
print('distortion...')
wcsPlots.plotDistortion(wcs, W, H, 400, prefix,
'SIP Distortion (exaggerated x 10)', exaggerate=10.)
print('distortion...')
wcsPlots.plotDistortion(wcs, W, H, 400, prefix,
'SIP Distortion (exaggerated x 100)', exaggerate=100.,
suffix='-distort2.')
def getCalibObjects(butler, filterName, dataId):
"""
A version of getCalibObjectsImpl that isn't a class method, for use by other code
@param useOutputSrc # use fluxes from the "src", not "icSrc"
"""
#################################
# color calibration
#
# this stuff stolen from pipette.
# - numbers from suprimecam.paf, method in Calibrate.py
#####################
primaryLookup = {
#"B" : "g",
#"V" : "g",
#"R" : "r",
#"I" : "i",
"g": "g",
"g": "g",
"r": "r",
"i": "i",
}
# The below colour terms are from the last page of
# http://www.naoj.org/staff/nakata/suprime/illustration/colorterm_report_ver3.pdf
secondaryLookup = {
"g": ["r", [-0.00569, -0.0427]],
"r": ["g", [0.00261, 0.0304]],
"i": ["r", [0.00586, 0.0827, -0.0118]],
"z": ['i', [0.000329, 0.0608, 0.0219]],
"y": ['i', [0.000329, 0.0608, 0.0219]],
}
# figure out which filters we need for the color term
primaryFilter = primaryLookup[filterName] # Primary band for correction
secondaryFilter = secondaryLookup[primaryFilter][
0] # Secondary band for correction
log = pexLog.Log.getDefaultLog()
psources = butler.get('icSrc', dataId)
pmatches = butler.get('icMatch', dataId)
calexp_md = butler.get('calexp_md', dataId)
wcs = afwImage.makeWcs(calexp_md)
W, H = calexp_md.get("NAXIS1"), calexp_md.get("NAXIS2")
calib = afwImage.Calib(calexp_md)
matches = pmatches.getSourceMatches()
setMatchListBlobsNone(matches)
sources = psources.getSources() ## fails
setSourceSetBlobsNone(sources)
anid = pmatches.getSourceMatchMetadata().getInt('ANINDID')
del psources
del pmatches
del calexp_md # cleanup
useOutputSrc = False
if useOutputSrc:
srcs = butler.get('src', dataId).getSources()
setSourceSetBlobsNone(srcs)
import lsst.afw.detection as afwDetect
pmMatch = afwDetect.matchXy(sources, srcs, 1.0, True)
for icSrc, src, d in pmMatch:
icSrc.setPsfFlux(src.getPsfFlux())
# ref sources
xc, yc = 0.5 * W, 0.5 * H
radec = wcs.pixelToSky(xc, yc)
ra = radec.getLongitude(afwCoord.DEGREES)
dec = radec.getLatitude(afwCoord.DEGREES)
radius = wcs.pixelScale().asDegrees() * math.hypot(xc, yc) * 1.1
pol = pexPolicy.Policy()
pol.set('matchThreshold', 30)
solver = measAstrom.createSolver(pol, log)
idName = 'id'
X = solver.getCatalogue(ra, dec, radius, primaryFilter, idName, anid)
refsources = X.refsources
setSourceSetBlobsNone(refsources)
inds = X.inds
referrs, stargal = None, None
cols = solver.getTagAlongColumns(anid)
colnames = [c.name for c in cols]
col = 'starnotgal'
if col in colnames:
stargal1 = solver.getTagAlongBool(anid, col, inds)
stargal = []
for i in range(len(stargal1)):
stargal.append(stargal1[i])
fdict = maUtils.getDetectionFlags()
# get the data for the secondary
XX = solver.getCatalogue(ra, dec, radius, secondaryFilter, idName, anid)
secondaryRefsources = XX.refsources
setSourceSetBlobsNone(secondaryRefsources)
polyData = secondaryLookup[primaryFilter][1] # Polynomial correction
polyData.reverse() # Numpy wants decreasing powers
polynomial = numpy.poly1d(polyData)
# We already have the 'primary' magnitudes in the matches
secondariesDict = dict()
for s in secondaryRefsources:
secondariesDict[s.getId()] = (s.getPsfFlux(), s.getPsfFluxErr())
del secondaryRefsources
keepref = []
keepi = []
for i in xrange(len(refsources)):
ra, dec = refsources[i].getRa(), refsources[i].getDec(
) # ra,dec in Rads
x, y = wcs.skyToPixel(
afwCoord.Coord(
afwGeom.PointD(numpy.degrees(ra), numpy.degrees(dec))))
if x < 0 or y < 0 or x > W or y > H:
continue
refsources[i].setXAstrom(x)
refsources[i].setYAstrom(y)
if stargal[i]:
refsources[i].setFlagForDetection(
refsources[i].getFlagForDetection() | fdict["STAR"])
# color term
primaryMag = -2.5 * numpy.log10(refsources[i].getPsfFlux())
secondaryMag = -2.5 * numpy.log10(
secondariesDict[refsources[i].getId()][0])
diff = polynomial(primaryMag - secondaryMag)
refsources[i].setPsfFlux(10.0**(-0.4 * (primaryMag + diff)))
keepref.append(refsources[i])
keepi.append(i)
refsources = keepref
if referrs is not None:
referrs = [referrs[i] for i in keepi]
if stargal is not None:
stargal = [stargal[i] for i in keepi]
measAstrom.joinMatchList(matches, refsources, first=True, log=log)
measAstrom.joinMatchList(matches, sources, first=False, log=log)
return matches, calib, refsources
def plotsForField(inButler, keys, fixup, plots=None, prefix=''):
if plots is None:
plots = ['photom','matches','corr','distortion']
filters = inButler.queryMetadata('raw', 'filter', **keys)
print 'Filters:', filters
filterName = filters[0]
psources = inButler.get('icSrc', **keys)
# since the butler does lazy evaluation, we don't know if it fails until...
try:
print 'Got sources', psources
except:
print '"icSrc" not found. Trying "src" instead.'
psources = inButler.get('src', **keys)
print 'Got sources', psources
pmatches = inButler.get('icMatch', **keys)
#print 'Got matches', pmatches
#matchmeta = pmatches.getSourceMatchMetadata()
#matches = pmatches.getSourceMatches()
#print 'Match metadata:', matchmeta
sources = psources.getSources()
calexp = inButler.get('calexp', **keys)
#print 'Got calexp', calexp
wcs = calexp.getWcs()
#print 'Got wcs', wcs
#print wcs.getFitsMetadata().toString()
wcs = afwImage.cast_TanWcs(wcs)
#print 'After cast:', wcs
photocal = calexp.getCalib()
zp = photocal.getMagnitude(1.)
print 'Zeropoint is', zp
# ref sources
W,H = calexp.getWidth(), calexp.getHeight()
log = Log.getDefaultLog()
log.setThreshold(Log.DEBUG);
kwargs = {}
if fixup:
# ugh, mask and offset req'd because source ids are assigned at write-time
# and match list code made a deep copy before that.
# (see svn+ssh://svn.lsstcorp.org/DMS/meas/astrom/tickets/1491-b r18027)
kwargs['sourceIdMask'] = 0xffff
kwargs['sourceIdOffset'] = -1
(matches,ref) = measAstrom.generateMatchesFromMatchList(
pmatches, sources, wcs, W, H, returnRefs=True, log=log, **kwargs)
print 'Got', len(ref), 'reference catalog sources'
# pull 'stargal' and 'referrs' arrays out of the reference sources
fdict = maUtils.getDetectionFlags()
starflag = int(fdict["STAR"])
stargal = [bool((r.getFlagForDetection() & starflag) > 0)
for r in ref]
referrs = [float(r.getPsfFluxErr() / r.getPsfFlux() * 2.5 / -np.log(10))
for r in ref]
nstars = sum([1 for s in stargal if s])
print 'Number of sources with STAR set:', nstars
visit = keys['visit']
raft = keys['raft']
sensor = keys['sensor']
prefix += 'imsim-v%i-r%s-s%s' % (visit, raft.replace(',',''), sensor.replace(',',''))
if 'photom' in plots:
print 'photometry plots...'
tt = 'LSST ImSim v%i r%s s%s' % (visit, raft.replace(',',''), sensor.replace(',',''))
wcsPlots.plotPhotometry(sources, ref, matches, prefix, band=filterName, zp=zp, referrs=referrs, refstargal=stargal, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix, band=filterName, zp=zp, delta=True, referrs=referrs, refstargal=stargal, title=tt)
# test w/ and w/o referrs and stargal.
if False:
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'A', band=filterName, zp=zp, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'B', band=filterName, zp=zp, referrs=referrs, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'C', band=filterName, zp=zp, refstargal=stargal, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'A', band=filterName, zp=zp, delta=True, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'B', band=filterName, zp=zp, delta=True, referrs=referrs, title=tt)
wcsPlots.plotPhotometry(sources, ref, matches, prefix + 'C', band=filterName, zp=zp, delta=True,refstargal=stargal, title=tt)
if 'matches' in plots:
print 'matches...'
wcsPlots.plotMatches(sources, ref, matches, wcs, W, H, prefix)
if 'corr' in plots:
#print 'corr...'
# requires astrometry.libkd (not available in 0.30)
#wcsPlots.plotCorrespondences2(sources, ref, matches, wcs, W, H, prefix)
#print 'corr...'
#wcsPlots.plotCorrespondences(sources, ref, matches, wcs, W, H, prefix)
pass
if 'distortion' in plots:
print 'distortion...'
wcsPlots.plotDistortion(wcs, W, H, 400, prefix,
'SIP Distortion (exaggerated x 10)', exaggerate=10.)
print 'distortion...'
wcsPlots.plotDistortion(wcs, W, H, 400, prefix,
'SIP Distortion (exaggerated x 100)', exaggerate=100.,
suffix='-distort2.')