def test_align_no_mask():
""" Test that alignment of images with no masks works """
reference = camera()
image = ndi.shift(camera(), shift=(-7, 12))
aligned = align(image, reference=reference)
assert np.allclose(reference[7::, 0:-12], aligned[7::, 0:-12])
def test_align_with_mask():
""" Test that alignment of images with no masks works """
reference = camera()
image = ndi.shift(camera(), shift=(-7, 12))
mask = np.ones_like(reference, dtype=bool)
mask[75:100, 50:100] = False
aligned = align(image, reference=reference, mask=mask)
assert np.allclose(reference[7::, 0:-12], aligned[7::, 0:-12])
def test_misaligned_canned_images(self):
""" shift images from skimage.data by entire pixels.
We don't expect perfect alignment."""
original = TEST_IMAGE
misaligned = ndi.shift(original, (randint(-4, 4), randint(-4, 4)))
aligned = align(misaligned, reference=original)
# edge will be filled with zeros, we ignore
diff = np.abs(original[5:-5, 5:-5] - aligned[5:-5, 5:-5])
# Want less than 1% difference
percent_diff = np.sum(diff) / (diff.size *
(original.max() - original.min()))
self.assertLess(percent_diff, 1)
def test_no_side_effects(self):
""" Test that aligned images are not modified in-place """
im = np.array(TEST_IMAGE[0:64, 0:64])
im.setflags(write=False)
aligned = align(im, reference=im, fill_value=np.nan)
self.assertEqual(im.dtype, TEST_IMAGE.dtype)
def test_align_no_side_effects():
""" Test that aligned images are not modified in-place """
im = np.array(camera()[0:64, 0:64])
im.setflags(write=False)
aligned = align(im, reference=im, fill_value=np.nan)
assert im.dtype == camera().dtype