def test_homogenous_coordinates_violation_warning(self):
affine = np.ones((4, 4))
array = np.arange(4 * 5 * 6 * 3).reshape(4, 5, 6, 3)
expected_warning = RuntimeWarning
match = "affine is not in homogenous coordinates.\naffine\[-1] should be zeros with a 1 on the right."
with pytest.warns(expected_warning, match=match):
_multiply_coords_by_affine(affine, array)
def test_non_square_affine(self):
affine = np.eye(4)[:3]
array = np.arange(4 * 5 * 6 * 3).reshape(4, 5, 6, 3)
expected_exception = ValueError
match = "affine must be a square matrix."
with pytest.raises(expected_exception, match=match):
_multiply_coords_by_affine(affine, array)
def test_incompatible_affine_and_array(self):
affine = np.eye(4)
array = np.arange(4 * 5 * 6 * 2).reshape(4, 5, 6, 2)
expected_exception = ValueError
match = "array is incompatible with affine. The length of the last dimension of array should be 1 less than the length of affine."
with pytest.raises(expected_exception, match=match):
_multiply_coords_by_affine(affine, array)
def test_3D_affine_array(self):
affine = np.eye(4)[None]
array = np.arange(4 * 5 * 6 * 3).reshape(4, 5, 6, 3)
expected_exception = ValueError
match = "affine must be a 2-dimensional matrix."
with pytest.raises(expected_exception, match=match):
_multiply_coords_by_affine(affine, array)
def test_rotational_affine_identity_velocity_fields(self, deform_to):
num_timesteps = 10
template_shape = (3, 4, 5)
template_resolution = 1
target_shape = (2, 4, 6)
target_resolution = 1
velocity_fields = np.zeros(
(*template_shape, num_timesteps, len(template_shape)))
velocity_field_resolution = 1
# Indicates a 90 degree rotation to the right.
affine = np.array([
[0, 1, 0, 0],
[-1, 0, 0, 0],
[0, 0, 1, 0],
[0, 0, 0, 1],
])
if deform_to == "template":
expected_output = _lddmm_utilities._multiply_coords_by_affine(
affine,
_lddmm_utilities._compute_coords(template_shape,
template_resolution),
)
elif deform_to == "target":
expected_output = _lddmm_utilities._multiply_coords_by_affine(
inv(affine),
_lddmm_utilities._compute_coords(target_shape,
target_resolution),
)
position_field = generate_position_field(
affine=affine,
velocity_fields=velocity_fields,
velocity_field_resolution=velocity_field_resolution,
template_shape=template_shape,
template_resolution=template_resolution,
target_shape=target_shape,
target_resolution=target_resolution,
deform_to=deform_to,
)
assert np.allclose(position_field, expected_output)
def test_identity_affine_3D(self):
affine = (
np.eye(4)
+ np.append(np.arange(3 * 4).reshape(3, 4), np.zeros((1, 4)), 0) ** 2
)
array = _compute_coords((3, 4, 5), 1)
result = _multiply_coords_by_affine(affine, array)
arrays = []
for dim in range(3):
arrays.append(np.sum(affine[dim, :-1] * array, axis=-1) + affine[dim, -1])
expected = np.stack(arrays=arrays, axis=-1)
assert np.array_equal(result, expected)
def test_rotational_position_field(self):
# Note: applying an affine indicating a clockwise-rotation to a position_field produces a position _ield rotated counter-clockwise.
# The corresponding effect on the deformed_subject is a counter-clockwise rotation.
subject = np.array([
[0, 1, 0, 0],
[0, 1, 0, 0],
[0, 1, 0, 0],
[0, 1, 1, 1],
])
subject_resolution = 1
output_resolution = 1
output_shape = None
position_field_resolution = subject_resolution
# Indicates a 90 degree rotation to the right.
affine = np.array([
[0, 1, 0],
[-1, 0, 0],
[0, 0, 1],
])
position_field = _lddmm_utilities._multiply_coords_by_affine(
affine,
_lddmm_utilities._compute_coords(subject.shape,
position_field_resolution),
)
deformed_subject = _transform_image(
subject=subject,
subject_resolution=subject_resolution,
output_resolution=output_resolution,
output_shape=output_shape,
position_field=position_field,
position_field_resolution=position_field_resolution,
)
expected_output = np.array([
[0, 0, 0, 1],
[0, 0, 0, 1],
[1, 1, 1, 1],
[0, 0, 0, 0],
])
assert np.allclose(deformed_subject, expected_output)
def test_rotational_position_field(self):
# Note: applying an affine indicating a clockwise-rotation to a position_field produces a position _ield rotated counter-clockwise.
# The corresponding effect on a deformed image is a counter-clockwise rotation.
subject = np.array([
[0, 1, 0],
[0, 1, 0],
[0, 1, 1],
])
subject_resolution = 1
position_field_resolution = subject_resolution
# Indicates a 90 degree rotation to the right.
affine = np.array([
[0, 1, 0],
[-1, 0, 0],
[0, 0, 1],
])
position_field = _lddmm_utilities._multiply_coords_by_affine(
affine,
_lddmm_utilities._compute_coords(subject.shape,
position_field_resolution),
)
# The middle column.
points = np.array([
[-1, 0],
[0, 0],
[1, 0],
])
transformed_points = _transform_points(
points=points,
position_field=position_field,
position_field_resolution=position_field_resolution,
)
# The middle row.
expected_output = np.array([
[0, 1],
[0, 0],
[0, -1],
])
assert np.array_equal(transformed_points, expected_output)