def testGood(self):
ti = afwImage.MaskedImageF(geom.Extent2I(100, 100))
ti.getVariance().set(0.1)
ti[50, 50, afwImage.LOCAL] = (1., 0x0, 1.)
sKernel = self.makeSpatialKernel(2)
si = afwImage.MaskedImageF(ti.getDimensions())
convolutionControl = afwMath.ConvolutionControl()
convolutionControl.setDoNormalize(True)
afwMath.convolve(si, ti, sKernel, convolutionControl)
bbox = geom.Box2I(geom.Point2I(25, 25),
geom.Point2I(75, 75))
si = afwImage.MaskedImageF(si, bbox, origin=afwImage.LOCAL)
ti = afwImage.MaskedImageF(ti, bbox, origin=afwImage.LOCAL)
kc = ipDiffim.KernelCandidateF(50., 50., ti, si, self.ps)
sBg = afwMath.PolynomialFunction2D(1)
bgCoeffs = [0., 0., 0.]
sBg.setParameters(bgCoeffs)
# must be initialized
bskv = ipDiffim.BuildSingleKernelVisitorF(self.kList, self.ps)
bskv.processCandidate(kc)
self.assertEqual(kc.isInitialized(), True)
askv = ipDiffim.AssessSpatialKernelVisitorF(sKernel, sBg, self.ps)
askv.processCandidate(kc)
self.assertEqual(askv.getNProcessed(), 1)
self.assertEqual(askv.getNRejected(), 0)
self.assertEqual(kc.getStatus(), afwMath.SpatialCellCandidate.GOOD)
def testGood(self):
ti = afwImage.MaskedImageF(afwGeom.Extent2I(100, 100))
ti.getVariance().set(0.1)
ti.set(50, 50, (1., 0x0, 1.))
sKernel = self.makeSpatialKernel(2)
si = afwImage.MaskedImageF(ti.getDimensions())
afwMath.convolve(si, ti, sKernel, True)
bbox = afwGeom.Box2I(afwGeom.Point2I(25, 25),
afwGeom.Point2I(75, 75))
si = afwImage.MaskedImageF(si, bbox, origin=afwImage.LOCAL)
ti = afwImage.MaskedImageF(ti, bbox, origin=afwImage.LOCAL)
kc = ipDiffim.KernelCandidateF(50., 50., ti, si, self.policy)
sBg = afwMath.PolynomialFunction2D(1)
bgCoeffs = [0., 0., 0.]
sBg.setParameters(bgCoeffs)
# must be initialized
bskv = ipDiffim.BuildSingleKernelVisitorF(self.kList, self.policy)
bskv.processCandidate(kc)
self.assertEqual(kc.isInitialized(), True)
#ds9.mtv(kc.getTemplateMaskedImage(), frame=1)
#ds9.mtv(kc.getScienceMaskedImage(), frame=2)
#ds9.mtv(kc.getKernelImage(ipDiffim.KernelCandidateF.RECENT), frame=3)
#ds9.mtv(kc.getDifferenceImage(ipDiffim.KernelCandidateF.RECENT), frame=4)
askv = ipDiffim.AssessSpatialKernelVisitorF(sKernel, sBg, self.policy)
askv.processCandidate(kc)
self.assertEqual(askv.getNProcessed(), 1)
self.assertEqual(askv.getNRejected(), 0)
self.assertEqual(kc.getStatus(), afwMath.SpatialCellCandidate.GOOD)
def testBad(self):
ti = afwImage.MaskedImageF(geom.Extent2I(100, 100))
ti.getVariance().set(0.1)
ti[50, 50, afwImage.LOCAL] = (1., 0x0, 1.)
sKernel = self.makeSpatialKernel(2)
si = afwImage.MaskedImageF(ti.getDimensions())
convolutionControl = afwMath.ConvolutionControl()
convolutionControl.setDoNormalize(True)
afwMath.convolve(si, ti, sKernel, convolutionControl)
bbox = geom.Box2I(geom.Point2I(25, 25), geom.Point2I(75, 75))
si = afwImage.MaskedImageF(si, bbox, origin=afwImage.LOCAL)
ti = afwImage.MaskedImageF(ti, bbox, origin=afwImage.LOCAL)
kc = ipDiffim.KernelCandidateF(50., 50., ti, si, self.ps)
badGaussian = afwMath.GaussianFunction2D(1., 1., 0.)
badKernel = afwMath.AnalyticKernel(self.ksize, self.ksize, badGaussian)
basisList = []
basisList.append(badKernel)
badSpatialKernelFunction = afwMath.PolynomialFunction2D(0)
badSpatialKernel = afwMath.LinearCombinationKernel(
basisList, badSpatialKernelFunction)
badSpatialKernel.setSpatialParameters([[
1,
]])
sBg = afwMath.PolynomialFunction2D(1)
bgCoeffs = [10., 10., 10.]
sBg.setParameters(bgCoeffs)
# must be initialized
bskv = ipDiffim.BuildSingleKernelVisitorF(self.kList, self.ps)
bskv.processCandidate(kc)
self.assertEqual(kc.isInitialized(), True)
askv = ipDiffim.AssessSpatialKernelVisitorF(badSpatialKernel, sBg,
self.ps)
askv.processCandidate(kc)
self.assertEqual(askv.getNProcessed(), 1)
self.assertEqual(askv.getNRejected(), 1)
self.assertEqual(kc.getStatus(), afwMath.SpatialCellCandidate.BAD)