def test_transform_points_transpose_equivalence() -> None:
input_points = np.random.rand(10, 3)
input_points_t = input_points.transpose(1, 0)
# Generate some random transformation matrix
tf = np.identity(4)
tf[:3, :3] = transforms3d.euler.euler2mat(np.random.rand(),
np.random.rand(),
np.random.rand())
tf[3, :3] = np.random.rand(3)
output_points = transform_points(input_points, tf)
output_points_t = transform_points_transposed(input_points_t, tf)
np.testing.assert_array_equal(output_points.transpose(1, 0),
output_points_t)
tf_inv = np.linalg.inv(tf)
input_points_recovered = transform_points(output_points, tf_inv)
input_points_t_recovered = transform_points_transposed(
output_points_t, tf_inv)
np.testing.assert_almost_equal(input_points_recovered,
input_points,
decimal=10)
np.testing.assert_almost_equal(input_points_t_recovered,
input_points_t,
decimal=10)
def test_wrong_input_shape(self) -> None:
tf = np.eye(4)
with self.assertRaises(ValueError):
points = np.zeros((3, 10))
transform_points(points, tf)
with self.assertRaises(ValueError):
points = np.zeros((10, 3))
transform_points_transposed(points, tf)