def testUnityConvolution(self):
"""Verify that convolution with a centered delta function reproduces the original.
"""
# create a delta function kernel that has 1,1 in the center
kFunc = afwMath.IntegerDeltaFunction2D(0.0, 0.0)
kernel = afwMath.AnalyticKernel(3, 3, kFunc)
doNormalize = False
doCopyEdge = False
afwMath.convolve(self.cnvImage, self.maskedImage.getImage(), kernel,
doNormalize, doCopyEdge)
afwMath.convolve(self.cnvMaskedImage, self.maskedImage, kernel,
doNormalize, doCopyEdge)
cnvImMaskVarArr = self.cnvMaskedImage.getArrays()
skipMaskArr = numpy.array(numpy.isnan(cnvImMaskVarArr[0]),
dtype=numpy.uint16)
kernelDescr = "Centered DeltaFunctionKernel (testing unity convolution)"
self.assertImagesAlmostEqual(self.cnvImage,
self.maskedImage.getImage(),
skipMask=skipMaskArr,
msg=kernelDescr)
self.assertMaskedImagesAlmostEqual(self.cnvMaskedImage,
self.maskedImage,
skipMask=skipMaskArr,
msg=kernelDescr)
def testIntegerDeltaFunction2D(self):
def basicDelta(x, xo):
return (x == xo)
errMsg = "{} = {} != {} for x={}, y={}, xo={}, yo={}"
for xo in np.arange(-5.0, 5.0, 1.0):
for yo in np.arange(-5.0, 5.0, 1.0):
f = afwMath.IntegerDeltaFunction2D(xo, yo)
g = f.clone()
for x in np.arange(-5.0, 5.0, 1.0):
for y in np.arange(-5.0, 5.0, 1.0):
predVal = basicDelta(x, xo) * basicDelta(y, yo)
msg = errMsg.format(
type(f).__name__, f(x, y), predVal, x, y, xo, yo)
self.assertFloatsAlmostEqual(f(x, y),
predVal,
msg=msg,
atol=self.atol,
rtol=None)
msg = errMsg.format(
type(g).__name__, g(x, y), predVal, x, y, xo,
yo) + "; clone"
self.assertFloatsAlmostEqual(g(x, y),
predVal,
msg=msg,
atol=self.atol,
rtol=None)
def testUnityConvolution(self):
"""Verify that convolution with a centered delta function reproduces the original.
"""
# create a delta function kernel that has 1,1 in the center
kFunc = afwMath.IntegerDeltaFunction2D(0.0, 0.0)
kernel = afwMath.AnalyticKernel(3, 3, kFunc)
doNormalize = False
doCopyEdge = False
afwMath.convolve(self.cnvImage, self.maskedImage.getImage(), kernel, doNormalize, doCopyEdge)
cnvImArr = self.cnvImage.getArray()
afwMath.convolve(self.cnvMaskedImage, self.maskedImage, kernel, doNormalize, doCopyEdge)
cnvImMaskVarArr = self.cnvMaskedImage.getArrays()
refCnvImMaskVarArr = self.maskedImage.getArrays()
skipMaskArr = numpy.isnan(cnvImMaskVarArr[0])
kernelDescr = "Centered DeltaFunctionKernel (testing unity convolution)"
errStr = imTestUtils.imagesDiffer(cnvImArr, refCnvImMaskVarArr[0], skipMaskArr=skipMaskArr)
if errStr:
self.fail("convolve(Image, kernel=%s, doNormalize=%s, doCopyEdge=%s) failed:\n%s" % \
(kernelDescr, doNormalize, doCopyEdge, errStr))
errStr = imTestUtils.maskedImagesDiffer(cnvImMaskVarArr, refCnvImMaskVarArr, skipMaskArr=skipMaskArr)
if errStr:
self.fail("convolve(MaskedImage, kernel=%s, doNormalize=%s, doCopyEdge=%s) failed:\n%s" % \
(kernelDescr, doNormalize, doCopyEdge, errStr))
self.assert_(sameMaskPlaneDicts(self.cnvMaskedImage, self.maskedImage),
"convolve(MaskedImage, kernel=%s, doNormalize=%s, doCopyEdge=%s) failed:\n%s" % \
(kernelDescr, doNormalize, doCopyEdge, "convolved mask dictionary does not match input"))
def testIntegerDeltaFunction2D(self):
"""A test for IntegerDeltaFunction2D"""
def basicDelta(x, xo):
return (x == xo)
for xo in numpy.arange(-5.0, 5.0, 1.0):
for yo in numpy.arange(-5.0, 5.0, 1.0):
f = afwMath.IntegerDeltaFunction2D(xo, yo)
g = f.clone()
for x in numpy.arange(-5.0, 5.0, 1.0):
for y in numpy.arange(-5.0, 5.0, 1.0):
predVal = basicDelta(x, xo) * basicDelta(y, yo)
if predVal != f(x, y):
self.fail("%s = %s != %s for x=%s, y=%s, xo=%s, yo=%s" % \
(type(f).__name__, f(x, y), predVal, x, y, xo, yo))
if predVal != g(x, y):
self.fail("%s = %s != %s for x=%s, y=%s, xo=%s, yo=%s; clone" % \
(type(g).__name__, g(x, y), predVal, x, y, xo, yo))