def testAddTrimmedAmp(self):
"""Test that building a Ccd from trimmed Amps leads to a trimmed Ccd"""
dataSec = afwGeom.BoxI(afwGeom.PointI(1, 0), afwGeom.ExtentI(10, 20))
biasSec = afwGeom.BoxI(afwGeom.PointI(0, 0), afwGeom.ExtentI(1, 1))
allPixelsInAmp = afwGeom.BoxI(afwGeom.PointI(0, 0), afwGeom.ExtentI(11, 21))
eParams = cameraGeom.ElectronicParams(1.0, 1.0, 65000)
ccd = cameraGeom.Ccd(cameraGeom.Id(0))
self.assertFalse(ccd.isTrimmed())
for i in range(2):
amp = cameraGeom.Amp(cameraGeom.Id(i, "", i, 0),
allPixelsInAmp, biasSec, dataSec, eParams)
amp.setTrimmed(True)
if i%2 == 0: # check both APIs
ccd.addAmp(afwGeom.PointI(i, 0), amp)
else:
ccd.addAmp(amp)
self.assertTrue(ccd.isTrimmed())
# should fail to add non-trimmed Amp to a trimmed Ccd
i += 1
amp = cameraGeom.Amp(cameraGeom.Id(i, "", i, 0),
allPixelsInAmp, biasSec, dataSec, eParams)
self.assertFalse(amp.isTrimmed())
utilsTests.assertRaisesLsstCpp(self, pexExcept.InvalidParameterException, ccd.addAmp, amp)
# should fail to add trimmed Amp to a non-trimmed Ccd
ccd.setTrimmed(False)
amp.setTrimmed(True)
utilsTests.assertRaisesLsstCpp(self, pexExcept.InvalidParameterException, ccd.addAmp, amp)
def testSortedAmps(self):
"""Test if the Amps are sorted by ID after insertion into a Ccd"""
ccd = cameraGeom.Ccd(cameraGeom.Id())
Col = 0
for serial in [0, 1, 2, 3, 4, 5, 6, 7]:
gain, readNoise, saturationLevel = 0, 0, 0
width, height = 10, 10
allPixels = afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(width, height))
biasSec = afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(0, height))
dataSec = afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(width, height))
eParams = cameraGeom.ElectronicParams(gain, readNoise, saturationLevel)
amp = cameraGeom.Amp(cameraGeom.Id(serial, "", Col, 0), allPixels, biasSec, dataSec,
eParams)
ccd.addAmp(afwGeom.Point2I(Col, 0), amp); Col += 1
#
# Check that Amps are sorted by Id
#
serials = []
for a in ccd:
serials.append(a.getId().getSerial())
self.assertEqual(serials, sorted(serials))
def makeAmp(i):
height = 2048
width = 4096
allPixels = afwGeom.BoxI(
afwGeom.PointI(0, 0),
afwGeom.ExtentI(width + nExtended + nOverclock, height))
return cameraGeom.Amp(cameraGeom.Id(i), allPixels, None, None, None)
def setUp(self):
width, height = 110, 301
self.mi = afwImage.MaskedImageF(afwGeom.ExtentI(width, height))
self.mi.set(0)
sd = 3 # standard deviation of image
self.mi.getVariance().set(sd*sd)
self.mi.getMask().addMaskPlane("DETECTED")
self.FWHM = 5
self.ksize = 31 # size of desired kernel
sigma1 = 1.75
sigma2 = 2*sigma1
self.exposure = afwImage.makeExposure(self.mi)
self.exposure.setPsf(measAlg.DoubleGaussianPsf(self.ksize, self.ksize,
1.5*sigma1, 1, 0.1))
crval = afwCoord.makeCoord(afwCoord.ICRS, 0.0*afwGeom.degrees, 0.0*afwGeom.degrees)
wcs = afwImage.makeWcs(crval, afwGeom.PointD(0, 0), 1.0, 0, 0, 1.0)
self.exposure.setWcs(wcs)
ccd = cameraGeom.Ccd(cameraGeom.Id(1))
ccd.addAmp(cameraGeom.Amp(cameraGeom.Id(0),
afwGeom.BoxI(afwGeom.PointI(0,0), self.exposure.getDimensions()),
afwGeom.BoxI(afwGeom.PointI(0,0), afwGeom.ExtentI(0,0)),
afwGeom.BoxI(afwGeom.PointI(0,0), self.exposure.getDimensions()),
cameraGeom.ElectronicParams(1.0, 100.0, 65535)))
self.exposure.setDetector(ccd)
self.exposure.getDetector().setDistortion(None)
#
# Make a kernel with the exactly correct basis functions. Useful for debugging
#
basisKernelList = afwMath.KernelList()
for sigma in (sigma1, sigma2):
basisKernel = afwMath.AnalyticKernel(self.ksize, self.ksize,
afwMath.GaussianFunction2D(sigma, sigma))
basisImage = afwImage.ImageD(basisKernel.getDimensions())
basisKernel.computeImage(basisImage, True)
basisImage /= np.sum(basisImage.getArray())
if sigma == sigma1:
basisImage0 = basisImage
else:
basisImage -= basisImage0
basisKernelList.append(afwMath.FixedKernel(basisImage))
order = 1 # 1 => up to linear
spFunc = afwMath.PolynomialFunction2D(order)
exactKernel = afwMath.LinearCombinationKernel(basisKernelList, spFunc)
exactKernel.setSpatialParameters([[1.0, 0, 0],
[0.0, 0.5*1e-2, 0.2e-2]])
rand = afwMath.Random() # make these tests repeatable by setting seed
addNoise = True
if addNoise:
im = self.mi.getImage()
afwMath.randomGaussianImage(im, rand) # N(0, 1)
im *= sd # N(0, sd^2)
del im
xarr, yarr = [], []
for x, y in [(20, 20), (60, 20),
(30, 35),
(50, 50),
(20, 90), (70, 160), (25, 265), (75, 275), (85, 30),
(50, 120), (70, 80),
(60, 210), (20, 210),
]:
xarr.append(x)
yarr.append(y)
for x, y in zip(xarr, yarr):
dx = rand.uniform() - 0.5 # random (centered) offsets
dy = rand.uniform() - 0.5
k = exactKernel.getSpatialFunction(1)(x, y) # functional variation of Kernel ...
b = (k*sigma1**2/((1 - k)*sigma2**2)) # ... converted double Gaussian's "b"
#flux = 80000 - 20*x - 10*(y/float(height))**2
flux = 80000*(1 + 0.1*(rand.uniform() - 0.5))
I0 = flux*(1 + b)/(2*np.pi*(sigma1**2 + b*sigma2**2))
for iy in range(y - self.ksize//2, y + self.ksize//2 + 1):
if iy < 0 or iy >= self.mi.getHeight():
continue
for ix in range(x - self.ksize//2, x + self.ksize//2 + 1):
if ix < 0 or ix >= self.mi.getWidth():
continue
I = I0*psfVal(ix, iy, x + dx, y + dy, sigma1, sigma2, b)
Isample = rand.poisson(I) if addNoise else I
self.mi.getImage().set(ix, iy, self.mi.getImage().get(ix, iy) + Isample)
self.mi.getVariance().set(ix, iy, self.mi.getVariance().get(ix, iy) + I)
#
bbox = afwGeom.BoxI(afwGeom.PointI(0,0), afwGeom.ExtentI(width, height))
self.cellSet = afwMath.SpatialCellSet(bbox, 100)
self.footprintSet = afwDetection.FootprintSet(self.mi, afwDetection.Threshold(100), "DETECTED")
self.catalog = SpatialModelPsfTestCase.measure(self.footprintSet, self.exposure)
for source in self.catalog:
try:
cand = measAlg.makePsfCandidate(source, self.exposure)
self.cellSet.insertCandidate(cand)
except Exception, e:
print e
continue