def test_robust_to_ordering(self, axial_slices):
'''
The DICOM slices should be able to be passed in in any order, and they
should be recombined appropriately.
'''
assert np.array_equal(
_merge_slice_pixel_arrays([axial_slices[0], axial_slices[1], axial_slices[2]]),
_merge_slice_pixel_arrays([axial_slices[1], axial_slices[0], axial_slices[2]])
)
assert np.array_equal(
_merge_slice_pixel_arrays([axial_slices[0], axial_slices[1], axial_slices[2]]),
_merge_slice_pixel_arrays([axial_slices[2], axial_slices[0], axial_slices[1]])
)
def test_no_rescale_if_forced_false(self):
slice_datasets = [
MockSlice(np.ones((10, 20), dtype=np.uint8),
0,
RescaleSlope=2,
RescaleIntercept=3)
]
voxels = _merge_slice_pixel_arrays(slice_datasets, rescale=False)
assert voxels.dtype == np.uint8
def test_robust_to_ordering(self, axial_slices):
"""
The DICOM slices should be able to be passed in in any order, and they
should be recombined appropriately using the sort function.
"""
assert np.array_equal(
_merge_slice_pixel_arrays(
sort_by_slice_position(
[axial_slices[0], axial_slices[1], axial_slices[2]])),
_merge_slice_pixel_arrays(
sort_by_slice_position(
[axial_slices[1], axial_slices[0], axial_slices[2]])))
assert np.array_equal(
_merge_slice_pixel_arrays(
sort_by_instance_number(
[axial_slices[0], axial_slices[1], axial_slices[2]])),
_merge_slice_pixel_arrays(
sort_by_instance_number(
[axial_slices[2], axial_slices[0], axial_slices[1]])))
def test_casting_rescale_slope_and_intercept(self):
'''
Some DICOM modules contain the `RescaleSlope` and `RescaleIntercept` DICOM attributes.
'''
slices = [
MockSlice(np.ones((10, 20), dtype=np.uint8), 0, RescaleSlope=2, RescaleIntercept=3),
MockSlice(np.ones((10, 20), dtype=np.uint8), 1, RescaleSlope=2, RescaleIntercept=3),
]
voxels = _merge_slice_pixel_arrays(slices)
assert voxels.dtype == np.dtype('float32')
assert voxels[0, 0, 0] == 5.0
def test_casting_if_only_rescale_slope(self):
'''
If the `RescaleSlope` DICOM attribute is present, the
`RescaleIntercept` attribute should also be present, however, we handle
this case anyway.
'''
slices = [
MockSlice(np.ones((10, 20), dtype=np.uint8), 0, RescaleSlope=2),
MockSlice(np.ones((10, 20), dtype=np.uint8), 1, RescaleSlope=2),
]
voxels = _merge_slice_pixel_arrays(slices)
assert voxels.dtype == np.dtype('float32')
assert voxels[0, 0, 0] == 2.0
def test_rescales_if_forced_true(self):
slice_datasets = [MockSlice(np.ones((10, 20), dtype=np.uint8), 0)]
voxels = _merge_slice_pixel_arrays(slice_datasets, rescale=True)
assert voxels.dtype == np.float32
