def test_rotate_y_torch_scalar(self):
"""
Test rotation about Y axis. With a right hand coordinate system this
should result in a vector pointing along the x-axis being rotated to
point along the negative z axis.
"""
angle = torch.tensor(90.0)
t = RotateAxisAngle(angle=angle, axis="Y")
# fmt: off
matrix = torch.tensor(
[[
[0.0, 0.0, -1.0, 0.0], # noqa: E241, E201
[0.0, 1.0, 0.0, 0.0], # noqa: E241, E201
[1.0, 0.0, 0.0, 0.0], # noqa: E241, E201
[0.0, 0.0, 0.0, 1.0], # noqa: E241, E201
]],
dtype=torch.float32,
)
# fmt: on
points = torch.tensor([1.0, 0.0, 0.0])[None, None, :] # (1, 1, 3)
transformed_points = t.transform_points(points)
expected_points = torch.tensor([0.0, 0.0, -1.0])
self.assertTrue(
torch.allclose(transformed_points.squeeze(),
expected_points,
atol=1e-7))
self.assertTrue(torch.allclose(t._matrix, matrix, atol=1e-7))
def test_rotate_z_python_scalar(self):
t = RotateAxisAngle(angle=90, axis="Z")
# fmt: off
matrix = torch.tensor(
[[
[0.0, 1.0, 0.0, 0.0], # noqa: E241, E201
[-1.0, 0.0, 0.0, 0.0], # noqa: E241, E201
[0.0, 0.0, 1.0, 0.0], # noqa: E241, E201
[0.0, 0.0, 0.0, 1.0], # noqa: E241, E201
]],
dtype=torch.float32,
)
# fmt: on
points = torch.tensor([1.0, 0.0, 0.0])[None, None, :] # (1, 1, 3)
transformed_points = t.transform_points(points)
expected_points = torch.tensor([0.0, 1.0, 0.0])
self.assertTrue(
torch.allclose(transformed_points.squeeze(),
expected_points,
atol=1e-7))
self.assertTrue(torch.allclose(t._matrix, matrix, atol=1e-7))