def test_transform_geometric_centers_3d():
# Create arbitrary image-to-space transforms
axis = np.array([.5, 2.0, 1.5])
t = 0.15 # translation factor
for theta in [-1 * np.pi / 6.0, 0.0, np.pi / 5.0]: # rotation angle
for s in [0.83, 1.3, 2.07]: # scale
m_shapes = [(256, 256, 128), (255, 255, 127), (64, 127, 142)]
for shape_moving in m_shapes:
s_shapes = [(256, 256, 128), (255, 255, 127), (64, 127, 142)]
for shape_static in s_shapes:
moving = np.ndarray(shape=shape_moving)
static = np.ndarray(shape=shape_static)
trans = np.array([[1, 0, 0, -t * shape_static[0]],
[0, 1, 0, -t * shape_static[1]],
[0, 0, 1, -t * shape_static[2]],
[0, 0, 0, 1]])
trans_inv = npl.inv(trans)
rot = np.zeros(shape=(4, 4))
rot[:3, :3] = geometry.rodrigues_axis_rotation(axis, theta)
rot[3, 3] = 1.0
scale = np.array([[1 * s, 0, 0, 0],
[0, 1 * s, 0, 0],
[0, 0, 1 * s, 0],
[0, 0, 0, 1]])
static_grid2world = trans_inv.dot(
scale.dot(rot.dot(trans)))
moving_grid2world = npl.inv(static_grid2world)
# Expected translation
c_static = np.array(shape_static, dtype=np.float64) * 0.5
c_static = tuple(c_static)
c_static = static_grid2world.dot(c_static + (1,))[:3]
c_moving = np.array(shape_moving, dtype=np.float64) * 0.5
c_moving = tuple(c_moving)
c_moving = moving_grid2world.dot(c_moving + (1,))[:3]
expected = np.eye(4)
expected[:3, 3] = c_moving - c_static
# Implementation under test
actual = imaffine.transform_geometric_centers(
static, static_grid2world, moving, moving_grid2world)
assert_array_almost_equal(actual.affine, expected)
def test_transform_geometric_centers_3d():
# Create arbitrary image-to-space transforms
axis = np.array([.5, 2.0, 1.5])
t = 0.15 # translation factor
for theta in [-1 * np.pi / 6.0, 0.0, np.pi / 5.0]: # rotation angle
for s in [0.83, 1.3, 2.07]: # scale
m_shapes = [(256, 256, 128), (255, 255, 127), (64, 127, 142)]
for shape_moving in m_shapes:
s_shapes = [(256, 256, 128), (255, 255, 127), (64, 127, 142)]
for shape_static in s_shapes:
moving = np.ndarray(shape=shape_moving)
static = np.ndarray(shape=shape_static)
trans = np.array([[1, 0, 0, -t * shape_static[0]],
[0, 1, 0, -t * shape_static[1]],
[0, 0, 1, -t * shape_static[2]],
[0, 0, 0, 1]])
trans_inv = npl.inv(trans)
rot = np.zeros(shape=(4, 4))
rot[:3, :3] = geometry.rodrigues_axis_rotation(axis, theta)
rot[3, 3] = 1.0
scale = np.array([[1 * s, 0, 0, 0],
[0, 1 * s, 0, 0],
[0, 0, 1 * s, 0],
[0, 0, 0, 1]])
static_grid2world = trans_inv.dot(
scale.dot(rot.dot(trans)))
moving_grid2world = npl.inv(static_grid2world)
# Expected translation
c_static = np.array(shape_static, dtype=np.float64) * 0.5
c_static = tuple(c_static)
c_static = static_grid2world.dot(c_static + (1,))[:3]
c_moving = np.array(shape_moving, dtype=np.float64) * 0.5
c_moving = tuple(c_moving)
c_moving = moving_grid2world.dot(c_moving + (1,))[:3]
expected = np.eye(4)
expected[:3, 3] = c_moving - c_static
# Implementation under test
actual = imaffine.transform_geometric_centers(
static, static_grid2world, moving, moving_grid2world)
assert_array_almost_equal(actual.affine, expected)