def testReferenceFilter(self):
"""Test sub-selecting reference objects by flux."""
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
# Apply source selector to sourceCat, using the astrometry config defaults
tempConfig = measAstrom.AstrometryTask.ConfigClass()
tempSolver = measAstrom.AstrometryTask(config=tempConfig, refObjLoader=None)
sourceSelection = tempSolver.sourceSelector.run(sourceCat)
distortedCat = distort.distortList(sourceSelection.sourceCat, distort.linearXDistort)
matchPessConfig = measAstrom.MatchPessimisticBTask.ConfigClass()
matchPessConfig.maxRefObjects = 150
matchPessConfig.minMatchDistPixels = 5.0
matchPess = measAstrom.MatchPessimisticBTask(config=matchPessConfig)
trimmedRefCat = matchPess._filterRefCat(refCat, 'r_flux')
self.assertEqual(len(trimmedRefCat), matchPessConfig.maxRefObjects)
matchRes = matchPess.matchObjectsToSources(
refCat=refCat,
sourceCat=distortedCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
)
self.assertEqual(len(matchRes.matches), matchPessConfig.maxRefObjects - 3)
def singleTestInstance(self, filename, distortFunc):
cat = self.loadCatalogue(self.filename)
img = distort.distortList(cat, distortFunc)
bbox = afwGeom.Box2I(afwGeom.Point2I(0, 0),
afwGeom.Extent2I(1000, 1000))
res = self.astrom.determineWcs2(img, bbox=bbox)
imgWcs = res.getWcs()
# Create a wcs with sip
cat = cat.cast(SimpleCatalog, False)
matchList = self.matchSrcAndCatalogue(cat, img, imgWcs)
print("*** num matches =", len(matchList))
return
sipObject = sip.makeCreateWcsWithSip(matchList, imgWcs, 3)
imgWcs = sipObject.getNewWcs()
print('number of matches:', len(matchList), sipObject.getNPoints())
scatter = sipObject.getScatterOnSky().asArcseconds()
print("Scatter in arcsec is %g" % (scatter))
self.assertLess(scatter, self.tolArcsec,
"Scatter exceeds tolerance in arcsec")
if False:
scatter = sipObject.getScatterInPixels()
self.assertLess(
scatter, self.tolPixel,
"Scatter exceeds tolerance in pixels: %g" % (scatter, ))
def testReferenceFilter(self):
"""Test sub-selecting reference objects by flux."""
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
# Apply source selector to sourceCat, using the astrometry config defaults
tempConfig = measAstrom.AstrometryTask.ConfigClass()
tempSolver = measAstrom.AstrometryTask(config=tempConfig,
refObjLoader=None)
sourceSelection = tempSolver.sourceSelector.run(sourceCat)
distortedCat = distort.distortList(sourceSelection.sourceCat,
distort.linearXDistort)
matchPessConfig = measAstrom.MatchPessimisticBTask.ConfigClass()
matchPessConfig.maxRefObjects = 150
matchPessConfig.minMatchDistPixels = 5.0
matchPess = measAstrom.MatchPessimisticBTask(config=matchPessConfig)
trimmedRefCat = matchPess._filterRefCat(refCat, 'r_flux')
self.assertEqual(len(trimmedRefCat), matchPessConfig.maxRefObjects)
matchRes = matchPess.matchObjectsToSources(
refCat=refCat,
sourceCat=distortedCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
)
self.assertEqual(len(matchRes.matches),
matchPessConfig.maxRefObjects - 3)
def testPassingMatcherState(self):
"""Test that results of the matcher can be propagated to to in
subsequent iterations.
"""
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
# Apply source selector to sourceCat, using the astrometry config defaults
tempConfig = measAstrom.AstrometryTask.ConfigClass()
tempSolver = measAstrom.AstrometryTask(config=tempConfig,
refObjLoader=None)
sourceSelection = tempSolver.sourceSelector.run(sourceCat)
distortedCat = distort.distortList(sourceSelection.sourceCat,
distort.linearXDistort)
sourceCat = distortedCat
matchRes = self.MatchPessimisticB.matchObjectsToSources(
refCat=refCat,
sourceCat=sourceCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
)
maxShift = matchRes.match_tolerance.maxShift * 300
# Force the matcher to use a different pattern thatn the previous
# "iteration".
matchTol = measAstrom.MatchTolerancePessimistic(
maxMatchDist=matchRes.match_tolerance.maxMatchDist,
autoMaxMatchDist=matchRes.match_tolerance.autoMaxMatchDist,
maxShift=maxShift,
lastMatchedPattern=0,
failedPatternList=[0],
PPMbObj=matchRes.match_tolerance.PPMbObj,
)
matchRes = self.MatchPessimisticB.matchObjectsToSources(
refCat=refCat,
sourceCat=sourceCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
match_tolerance=matchTol,
)
self.assertEqual(len(matchRes.matches), self.expectedMatches)
self.assertLess(matchRes.match_tolerance.maxShift, maxShift)
self.assertEqual(matchRes.match_tolerance.lastMatchedPattern, 1)
self.assertIsNotNone(matchRes.match_tolerance.maxMatchDist)
self.assertIsNotNone(matchRes.match_tolerance.autoMaxMatchDist)
self.assertIsNotNone(matchRes.match_tolerance.lastMatchedPattern)
self.assertIsNotNone(matchRes.match_tolerance.failedPatternList)
self.assertIsNotNone(matchRes.match_tolerance.PPMbObj)
def singleTestInstance(self, filename, distortFunc, doPlot=False):
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
distortedCat = distort.distortList(sourceCat, distortFunc)
if doPlot:
import matplotlib.pyplot as plt
undistorted = [self.wcs.skyToPixel(self.distortedWcs.pixelToSky(ss.getCentroid())) for
ss in distortedCat]
refs = [self.wcs.skyToPixel(ss.getCoord()) for ss in refCat]
def plot(catalog, symbol):
plt.plot([ss.getX() for ss in catalog], [ss.getY() for ss in catalog], symbol)
#plot(sourceCat, 'k+') # Original positions: black +
plot(distortedCat, 'b+') # Distorted positions: blue +
plot(undistorted, 'g+') # Undistorted positions: green +
plot(refs, 'rx') # Reference catalog: red x
# The green + should overlap with the red x, because that's how matchOptimisticB does it.
# The black + happens to overlap with those also, but that's beside the point.
plt.show()
sourceCat = distortedCat
matchRes = self.matchOptimisticB.matchObjectsToSources(
refCat = refCat,
sourceCat = sourceCat,
wcs = self.distortedWcs,
refFluxField = "r_flux",
)
matches = matchRes.matches
if doPlot:
measAstrom.plotAstrometry(matches=matches, refCat=refCat, sourceCat=sourceCat)
self.assertEqual(len(matches), 183)
refCoordKey = afwTable.CoordKey(refCat.schema["coord"])
srcCoordKey = afwTable.CoordKey(sourceCat.schema["coord"])
refCentroidKey = afwTable.Point2DKey(refCat.getSchema()["centroid"])
maxDistErr = afwGeom.Angle(0)
for refObj, source, distRad in matches:
sourceCoord = source.get(srcCoordKey)
refCoord = refObj.get(refCoordKey)
predDist = sourceCoord.angularSeparation(refCoord)
distErr = abs(predDist - distRad*afwGeom.radians)
maxDistErr = max(distErr, maxDistErr)
if refObj.getId() != source.getId():
refCentroid = refObj.get(refCentroidKey)
sourceCentroid = source.getCentroid()
radius = math.hypot(*(refCentroid - sourceCentroid))
self.fail("ID mismatch: %s at %s != %s at %s; error = %0.1f pix" %
(refObj.getId(), refCentroid, source.getId(), sourceCentroid, radius))
self.assertLess(maxDistErr.asArcseconds(), 1e-7)
def testPassingMatcherState(self):
"""Test that results of the matcher can be propagated to to in
subsequent iterations.
"""
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
# Apply source selector to sourceCat, using the astrometry config defaults
tempConfig = measAstrom.AstrometryTask.ConfigClass()
tempSolver = measAstrom.AstrometryTask(config=tempConfig, refObjLoader=None)
sourceSelection = tempSolver.sourceSelector.run(sourceCat)
distortedCat = distort.distortList(sourceSelection.sourceCat, distort.linearXDistort)
sourceCat = distortedCat
matchRes = self.MatchPessimisticB.matchObjectsToSources(
refCat=refCat,
sourceCat=sourceCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
)
maxShift = matchRes.match_tolerance.maxShift * 300
# Force the matcher to use a different pattern thatn the previous
# "iteration".
matchTol = measAstrom.MatchTolerancePessimistic(
maxMatchDist=matchRes.match_tolerance.maxMatchDist,
autoMaxMatchDist=matchRes.match_tolerance.autoMaxMatchDist,
maxShift=maxShift,
lastMatchedPattern=0,
failedPatternList=[0],
PPMbObj=matchRes.match_tolerance.PPMbObj,
)
matchRes = self.MatchPessimisticB.matchObjectsToSources(
refCat=refCat,
sourceCat=sourceCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
match_tolerance=matchTol,
)
self.assertEqual(len(matchRes.matches), self.expectedMatches)
self.assertLess(matchRes.match_tolerance.maxShift, maxShift)
self.assertEqual(matchRes.match_tolerance.lastMatchedPattern, 1)
self.assertIsNotNone(matchRes.match_tolerance.maxMatchDist)
self.assertIsNotNone(matchRes.match_tolerance.autoMaxMatchDist)
self.assertIsNotNone(matchRes.match_tolerance.lastMatchedPattern)
self.assertIsNotNone(matchRes.match_tolerance.failedPatternList)
self.assertIsNotNone(matchRes.match_tolerance.PPMbObj)
def singleTestInstance(self, filename, distortFunc):
cat = self.loadCatalogue(self.filename)
img = distort.distortList(cat, distortFunc)
bbox = afwGeom.Box2I(afwGeom.Point2I(0, 0),
afwGeom.Extent2I(1000, 1000))
res = self.astrom.determineWcs2(img, bbox=bbox)
imgWcs = res.getWcs()
def printWcs(wcs):
print("WCS metadata:")
md = wcs.getFitsMetadata()
for name in md.names():
print("%s: %r" % (name, md.get(name)))
printWcs(imgWcs)
# Create a wcs with sip
cat = cat.cast(SimpleCatalog, False)
matchList = self.matchSrcAndCatalogue(cat, img, imgWcs)
print("*** num matches =", len(matchList))
return
sipObject = sip.makeCreateWcsWithSip(matchList, imgWcs, 3)
# print 'Put in TAN Wcs:'
# print imgWcs.getFitsMetadata().toString()
imgWcs = sipObject.getNewWcs()
# print 'Got SIP Wcs:'
# print imgWcs.getFitsMetadata().toString()
# Write out the SIP header
# afwImage.fits_write_imageF('createWcsWithSip.sip', afwImage.ImageF(0,0),
# imgWcs.getFitsMetadata())
print('number of matches:', len(matchList), sipObject.getNPoints())
scatter = sipObject.getScatterOnSky().asArcseconds()
print("Scatter in arcsec is %g" % (scatter))
self.assertLess(scatter, self.tolArcsec,
"Scatter exceeds tolerance in arcsec")
if False:
scatter = sipObject.getScatterInPixels()
self.assertLess(
scatter, self.tolPixel,
"Scatter exceeds tolerance in pixels: %g" % (scatter, ))
def singleTestInstance(self, filename, distortFunc):
cat = self.loadCatalogue(self.filename)
img = distort.distortList(cat, distortFunc)
bbox = afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(1000, 1000))
res = self.astrom.determineWcs2(img, bbox=bbox)
imgWcs = res.getWcs()
def printWcs(wcs):
print "WCS metadata:"
md = wcs.getFitsMetadata()
for name in md.names():
print "%s: %r" % (name, md.get(name))
printWcs(imgWcs)
#Create a wcs with sip
cat = cat.cast(afwTable.SimpleCatalog, False)
matchList = self.matchSrcAndCatalogue(cat, img, imgWcs)
print "*** num matches =", len(matchList)
return
sipObject = sip.makeCreateWcsWithSip(matchList, imgWcs, 3)
#print 'Put in TAN Wcs:'
#print imgWcs.getFitsMetadata().toString()
imgWcs = sipObject.getNewWcs()
#print 'Got SIP Wcs:'
#print imgWcs.getFitsMetadata().toString()
# Write out the SIP header
#afwImage.fits_write_imageF('createWcsWithSip.sip', afwImage.ImageF(0,0),
#imgWcs.getFitsMetadata())
print 'number of matches:', len(matchList), sipObject.getNPoints()
scatter = sipObject.getScatterOnSky().asArcseconds()
print "Scatter in arcsec is %g" % (scatter)
self.assertLess(scatter, self.tolArcsec, "Scatter exceeds tolerance in arcsec")
if False:
scatter = sipObject.getScatterInPixels()
self.assertLess(scatter, self.tolPixel, "Scatter exceeds tolerance in pixels: %g" %(scatter))
def singleTestInstance(self, filename, distortFunc, doPlot=False):
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
distortedCat = distort.distortList(sourceCat, distortFunc)
if doPlot:
import matplotlib.pyplot as plt
undistorted = [
self.wcs.skyToPixel(
self.distortedWcs.pixelToSky(ss.getCentroid()))
for ss in distortedCat
]
refs = [self.wcs.skyToPixel(ss.getCoord()) for ss in refCat]
def plot(catalog, symbol):
plt.plot([ss.getX() for ss in catalog],
[ss.getY() for ss in catalog], symbol)
plot(distortedCat, 'b+') # Distorted positions: blue +
plot(undistorted, 'g+') # Undistorted positions: green +
plot(refs, 'rx') # Reference catalog: red x
# The green + should overlap with the red x, because that's how
# MatchPessimisticB does it.
plt.show()
sourceCat = distortedCat
matchRes = self.MatchPessimisticB.matchObjectsToSources(
refCat=refCat,
sourceCat=sourceCat,
wcs=self.distortedWcs,
refFluxField="r_flux",
)
matches = matchRes.matches
if doPlot:
measAstrom.plotAstrometry(matches=matches,
refCat=refCat,
sourceCat=sourceCat)
self.assertEqual(len(matches), 183)
refCoordKey = afwTable.CoordKey(refCat.schema["coord"])
srcCoordKey = afwTable.CoordKey(sourceCat.schema["coord"])
refCentroidKey = afwTable.Point2DKey(refCat.getSchema()["centroid"])
maxDistErr = afwGeom.Angle(0)
for refObj, source, distRad in matches:
sourceCoord = source.get(srcCoordKey)
refCoord = refObj.get(refCoordKey)
predDist = sourceCoord.angularSeparation(refCoord)
distErr = abs(predDist - distRad * afwGeom.radians)
maxDistErr = max(distErr, maxDistErr)
if refObj.getId() != source.getId():
refCentroid = refObj.get(refCentroidKey)
sourceCentroid = source.getCentroid()
radius = math.hypot(*(refCentroid - sourceCentroid))
self.fail(
"ID mismatch: %s at %s != %s at %s; error = %0.1f pix" %
(refObj.getId(), refCentroid, source.getId(),
sourceCentroid, radius))
self.assertLess(maxDistErr.asArcseconds(), 1e-7)
def singleTestInstance(self, filename, distortFunc, doPlot=False):
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
# Apply source selector to sourceCat, using the astrometry config defaults
tempConfig = measAstrom.AstrometryTask.ConfigClass()
tempConfig.matcher.retarget(measAstrom.MatchOptimisticBTask)
tempConfig.sourceSelector["matcher"].excludePixelFlags = False
tempSolver = measAstrom.AstrometryTask(config=tempConfig,
refObjLoader=None)
sourceSelection = tempSolver.sourceSelector.run(sourceCat)
distortedCat = distort.distortList(sourceSelection.sourceCat,
distortFunc)
if doPlot:
import matplotlib.pyplot as plt
undistorted = [
self.wcs.skyToPixel(
self.distortedWcs.pixelToSky(ss.getCentroid()))
for ss in distortedCat
]
refs = [self.wcs.skyToPixel(ss.getCoord()) for ss in refCat]
def plot(catalog, symbol):
plt.plot([ss.getX() for ss in catalog],
[ss.getY() for ss in catalog], symbol)
# plot(sourceCat, 'k+') # Original positions: black +
plot(distortedCat, 'b+') # Distorted positions: blue +
plot(undistorted, 'g+') # Undistorted positions: green +
plot(refs, 'rx') # Reference catalog: red x
# The green + should overlap with the red x, because that's how matchOptimisticB does it.
# The black + happens to overlap with those also, but that's beside the point.
plt.show()
sourceCat = distortedCat
matchRes = self.matchOptimisticB.matchObjectsToSources(
refCat=refCat,
sourceCat=sourceCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
)
matches = matchRes.matches
if doPlot:
measAstrom.plotAstrometry(matches=matches,
refCat=refCat,
sourceCat=sourceCat)
self.assertEqual(len(matches), 183)
refCoordKey = afwTable.CoordKey(refCat.schema["coord"])
srcCoordKey = afwTable.CoordKey(sourceCat.schema["coord"])
refCentroidKey = afwTable.Point2DKey(refCat.getSchema()["centroid"])
maxDistErr = 0 * lsst.geom.radians
for refObj, source, distRad in matches:
sourceCoord = source.get(srcCoordKey)
refCoord = refObj.get(refCoordKey)
predDist = sourceCoord.separation(refCoord)
distErr = abs(predDist - distRad * lsst.geom.radians)
maxDistErr = max(distErr, maxDistErr)
if refObj.getId() != source.getId():
refCentroid = refObj.get(refCentroidKey)
sourceCentroid = source.getCentroid()
radius = math.hypot(*(refCentroid - sourceCentroid))
self.fail(
"ID mismatch: %s at %s != %s at %s; error = %0.1f pix" %
(refObj.getId(), refCentroid, source.getId(),
sourceCentroid, radius))
self.assertLess(maxDistErr.asArcseconds(), 1e-7)
def singleTestInstance(self, filename, distortFunc, doPlot=False):
sourceCat = self.loadSourceCatalog(self.filename)
refCat = self.computePosRefCatalog(sourceCat)
# Apply source selector to sourceCat, using the astrometry config defaults
tempConfig = measAstrom.AstrometryTask.ConfigClass()
tempSolver = measAstrom.AstrometryTask(config=tempConfig, refObjLoader=None)
sourceSelection = tempSolver.sourceSelector.run(sourceCat)
distortedCat = distort.distortList(sourceSelection.sourceCat, distortFunc)
if doPlot:
import matplotlib.pyplot as plt
undistorted = [self.wcs.skyToPixel(self.distortedWcs.pixelToSky(ss.getCentroid()))
for ss in distortedCat]
refs = [self.wcs.skyToPixel(ss.getCoord()) for ss in refCat]
def plot(catalog, symbol):
plt.plot([ss.getX() for ss in catalog],
[ss.getY() for ss in catalog], symbol)
plot(distortedCat, 'b+') # Distorted positions: blue +
plot(undistorted, 'g+') # Undistorted positions: green +
plot(refs, 'rx') # Reference catalog: red x
# The green + should overlap with the red x, because that's how
# MatchPessimisticB does it.
plt.show()
sourceCat = distortedCat
matchRes = self.MatchPessimisticB.matchObjectsToSources(
refCat=refCat,
sourceCat=sourceCat,
wcs=self.distortedWcs,
sourceFluxField='slot_ApFlux_instFlux',
refFluxField="r_flux",
)
matches = matchRes.matches
if doPlot:
measAstrom.plotAstrometry(matches=matches, refCat=refCat,
sourceCat=sourceCat)
self.assertEqual(len(matches), self.expectedMatches)
refCoordKey = afwTable.CoordKey(refCat.schema["coord"])
srcCoordKey = afwTable.CoordKey(sourceCat.schema["coord"])
refCentroidKey = afwTable.Point2DKey(refCat.getSchema()["centroid"])
maxDistErr = 0*lsst.geom.radians
for refObj, source, distRad in matches:
sourceCoord = source.get(srcCoordKey)
refCoord = refObj.get(refCoordKey)
predDist = sourceCoord.separation(refCoord)
distErr = abs(predDist - distRad*lsst.geom.radians)
maxDistErr = max(distErr, maxDistErr)
if refObj.getId() != source.getId():
refCentroid = refObj.get(refCentroidKey)
sourceCentroid = source.getCentroid()
radius = math.hypot(*(refCentroid - sourceCentroid))
self.fail(
"ID mismatch: %s at %s != %s at %s; error = %0.1f pix" %
(refObj.getId(), refCentroid, source.getId(),
sourceCentroid, radius))
self.assertLess(maxDistErr.asArcseconds(), 1e-7)