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test: add xfail for 3d transform on 4d data #282

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test: add xfail for 3d transform on 4d data #282

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24 changes: 24 additions & 0 deletions nitransforms/tests/test_resampling.py
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Original file line number Diff line number Diff line change
Expand Up @@ -330,6 +330,30 @@ def test_apply_transformchain(tmp_path, testdata_path):
assert (np.abs(diff) > 1e-3).sum() / diff.size < RMSE_TOL_LINEAR


@pytest.mark.xfail(reason="gh-281: applying a single 3D transform to 4D data")
def test_apply_single_3d_on_4d():
"""Apply one 3D transform across all timepoints of a 4D dataset."""
nvols = 5
data = np.zeros((10, 5, 5, nvols), dtype=np.float32)
for i in range(nvols):
data[i + 1, 2, 2, i] = i + 1

img = nb.Nifti1Image(data, np.eye(4))

mat = np.eye(4)
mat[0, 3] = -1.0
ref = nb.Nifti1Image(np.zeros((10, 5, 5), dtype=np.uint8), np.eye(4))
xfm = nitl.Affine(mat, reference=ref)

moved = apply(xfm, img, order=0)
moved_data = np.asanyarray(moved.dataobj)

assert moved_data.shape == data.shape
for i in range(nvols):
assert moved_data[i + 2, 2, 2, i] == i + 1
assert moved_data[i + 1, 2, 2, i] == 0
Comment on lines +333 to +354
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At present, this could fail because checking the values after applying the transform is wrong. I think a much simpler test is:

Suggested change
@pytest.mark.xfail(reason="gh-281: applying a single 3D transform to 4D data")
def test_apply_single_3d_on_4d():
"""Apply one 3D transform across all timepoints of a 4D dataset."""
nvols = 5
data = np.zeros((10, 5, 5, nvols), dtype=np.float32)
for i in range(nvols):
data[i + 1, 2, 2, i] = i + 1
img = nb.Nifti1Image(data, np.eye(4))
mat = np.eye(4)
mat[0, 3] = -1.0
ref = nb.Nifti1Image(np.zeros((10, 5, 5), dtype=np.uint8), np.eye(4))
xfm = nitl.Affine(mat, reference=ref)
moved = apply(xfm, img, order=0)
moved_data = np.asanyarray(moved.dataobj)
assert moved_data.shape == data.shape
for i in range(nvols):
assert moved_data[i + 2, 2, 2, i] == i + 1
assert moved_data[i + 1, 2, 2, i] == 0
@pytest.mark.xfail(reason="gh-281: applying a single 3D transform to 4D data", strict=True)
def test_apply_single_3d_on_4d():
"""Apply one 3D transform across all timepoints of a 4D dataset."""
img4d = nb.Nifti1Image(np.zeros((2, 3, 4, 5), np.eye(4))
ref3d = img4d.slicer[..., 0]
xfm = nitl.Affine(np.eye(4))
# Just a smoke test. When this passes, we should validate the values.
apply(xfm, img, reference=ref3d)

I'm adding strict=True so that the test doesn't just sit around XPASSing when we should start validating values after that point.



@pytest.mark.parametrize("serialize_4d", [True, False])
def test_LinearTransformsMapping_apply(
tmp_path, data_path, testdata_path, serialize_4d
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