def test_crosscorr_volume(self):
random.seed(42)
ref = random.randn(25, 25, 3)
im = shift(ref, [2, -2, 0], mode='constant', order=0)
imin = ImagesLoader(self.sc).fromArrays(im)
paramout = Register('crosscorr').estimate(imin, ref)[0][1]
imout = Register('crosscorr').transform(imin, ref).first()[1]
assert (allclose(paramout, [[2, -2], [2, -2], [2, -2]]))
assert (allclose(ref[:-2, 2:, :], imout[:-2, 2:, :]))
def test_reference_3d(self):
random.seed(42)
im0 = random.randn(25, 25, 3).astype('uint16')
im1 = random.randn(25, 25, 3).astype('uint16')
imin = ImagesLoader(self.sc).fromArrays([im0, im1])
ref = Register.reference(imin)
assert(allclose(ref, (im0 + im1) / 2))
def test_reference_2d(self):
random.seed(42)
im0 = random.randn(25, 25).astype('uint16')
im1 = random.randn(25, 25).astype('uint16')
im2 = random.randn(25, 25).astype('uint16')
imin = ImagesLoader(self.sc).fromArrays([im0, im1, im2])
ref = Register.reference(imin)
assert(allclose(ref, (im0 + im1 + im2) / 3))
print(imin.keys().collect())
ref = Register.reference(imin, startidx=0, stopidx=2)
assert(allclose(ref, (im0 + im1) / 2))
ref = Register.reference(imin, startidx=1, stopidx=2)
assert(allclose(ref, im1))
def test_reference_3d(self):
random.seed(42)
im0 = random.randn(25, 25, 3).astype('uint16')
im1 = random.randn(25, 25, 3).astype('uint16')
imin = ImagesLoader(self.sc).fromArrays([im0, im1])
ref = Register.reference(imin)
assert (allclose(ref, (im0 + im1) / 2))
def test_reference_2d(self):
random.seed(42)
im0 = random.randn(25, 25).astype('uint16')
im1 = random.randn(25, 25).astype('uint16')
im2 = random.randn(25, 25).astype('uint16')
imin = ImagesLoader(self.sc).fromArrays([im0, im1, im2])
ref = Register.reference(imin)
assert (allclose(ref, (im0 + im1 + im2) / 3))
print(imin.keys().collect())
ref = Register.reference(imin, startidx=0, stopidx=2)
assert (allclose(ref, (im0 + im1) / 2))
ref = Register.reference(imin, startidx=1, stopidx=2)
assert (allclose(ref, im1))
def test_reference_2d(self):
random.seed(42)
im0 = random.random_integers(0, high=127,
size=(25, 25)).astype('uint16')
im1 = random.random_integers(0, high=127,
size=(25, 25)).astype('uint16')
im2 = random.random_integers(0, high=127,
size=(25, 25)).astype('uint16')
imgIn = ImagesLoader(self.sc).fromArrays([im0, im1, im2])
ref = Register.reference(imgIn)
assert (allclose(ref, (im0 + im1 + im2) / 3))
ref = Register.reference(imgIn, startIdx=0, stopIdx=2)
assert (allclose(ref, (im0 + im1) / 2))
ref = Register.reference(imgIn, startIdx=1, stopIdx=2)
assert (allclose(ref, im1))
def test_reference_3d(self):
random.seed(42)
im0 = random.random_integers(0, high=127,
size=(25, 25, 3)).astype('uint16')
im1 = random.random_integers(0, high=127,
size=(25, 25, 3)).astype('uint16')
imgIn = ImagesLoader(self.sc).fromArrays([im0, im1])
ref = Register.reference(imgIn)
assert (allclose(ref, (im0 + im1) / 2))
def test_crosscorr_image(self):
random.seed(42)
ref = random.randn(25, 25)
reg = Register('crosscorr')
im = shift(ref, [2, 0], mode='constant', order=0)
imin = ImagesLoader(self.sc).fromArrays(im)
paramout = reg.estimate(imin, ref).collect()[0][1]
imout = reg.transform(imin, ref).first()[1]
assert(allclose(ref[:-2, :], imout[:-2, :]))
assert(allclose(paramout, [2, 0]))
im = shift(ref, [0, 2], mode='constant', order=0)
imin = ImagesLoader(self.sc).fromArrays(im)
paramout = reg.estimate(imin, ref).collect()[0][1]
imout = reg.transform(imin, ref).first()[1]
assert(allclose(ref[:, :-2], imout[:, :-2]))
assert(allclose(paramout, [0, 2]))
im = shift(ref, [2, -2], mode='constant', order=0)
imin = ImagesLoader(self.sc).fromArrays(im)
paramout = reg.estimate(imin, ref).collect()[0][1]
imout = reg.transform(imin, ref).first()[1]
assert(allclose(ref[:-2, 2:], imout[:-2, 2:]))
assert(allclose(paramout, [2, -2]))
im = shift(ref, [-2, 2], mode='constant', order=0)
imin = ImagesLoader(self.sc).fromArrays(im)
paramout = reg.estimate(imin, ref).collect()[0][1]
imout = reg.transform(imin, ref).first()[1]
assert(allclose(ref[2:, :-2], imout[2:, :-2]))
assert(allclose(paramout, [-2, 2]))
# just that that applying a filter during registration runs
# TODO add a check that shows this helps compensate for noisy pixels
reg = Register('crosscorr').setFilter('median', 2)
im = shift(ref, [-2, 2], mode='constant', order=0)
imin = ImagesLoader(self.sc).fromArrays(im)
paramout = reg.estimate(imin, ref).collect()[0][1]
imout = reg.transform(imin, ref).first()[1]
def test_crosscorr_image(self):
random.seed(42)
ref = random.randn(25, 25)
reg = Register('crosscorr')
im = shift(ref, [2, 0], mode='constant', order=0)
imgIn = ImagesLoader(self.sc).fromArrays(im)
paramOut = reg.estimate(imgIn, ref).collect()[0][1]
imgOut = reg.transform(imgIn, ref).first()[1]
assert (allclose(ref[:-2, :], imgOut[:-2, :]))
assert (allclose(paramOut, [2, 0]))
im = shift(ref, [0, 2], mode='constant', order=0)
imgIn = ImagesLoader(self.sc).fromArrays(im)
paramOut = reg.estimate(imgIn, ref).collect()[0][1]
imgOut = reg.transform(imgIn, ref).first()[1]
assert (allclose(ref[:, :-2], imgOut[:, :-2]))
assert (allclose(paramOut, [0, 2]))
im = shift(ref, [2, -2], mode='constant', order=0)
imgIn = ImagesLoader(self.sc).fromArrays(im)
paramOut = reg.estimate(imgIn, ref).collect()[0][1]
imgOut = reg.transform(imgIn, ref).first()[1]
assert (allclose(ref[:-2, 2:], imgOut[:-2, 2:]))
assert (allclose(paramOut, [2, -2]))
im = shift(ref, [-2, 2], mode='constant', order=0)
imgIn = ImagesLoader(self.sc).fromArrays(im)
paramOut = reg.estimate(imgIn, ref).collect()[0][1]
imgOut = reg.transform(imgIn, ref).first()[1]
assert (allclose(ref[2:, :-2], imgOut[2:, :-2]))
assert (allclose(paramOut, [-2, 2]))
# just that that applying a filter during registration runs
# TODO add a check that shows this helps compensate for noisy pixels
reg = Register('crosscorr').setFilter('median', 2)
im = shift(ref, [-2, 2], mode='constant', order=0)
imgIn = ImagesLoader(self.sc).fromArrays(im)
paramOut = reg.estimate(imgIn, ref).collect()[0][1]
imgOut = reg.transform(imgIn, ref).first()[1]