def test_transforms_from_pqs_4dims():
random_state = np.random.RandomState(0)
P = random_state.randn(2, 3, 4, 5, 7)
P[..., 3:] = norm_vectors(P[..., 3:])
H = transforms_from_pqs(P)
P2 = pqs_from_transforms(H)
assert_array_almost_equal(P[..., :3], H[..., :3, 3])
assert_array_almost_equal(P[..., :3], P2[..., :3])
def test_transforms_from_pqs_1dim():
P = np.empty((10, 7))
random_state = np.random.RandomState(0)
P[:, :3] = random_state.randn(len(P), 3)
P[:, 3:] = norm_vectors(random_state.randn(len(P), 4))
H = transforms_from_pqs(P)
P2 = pqs_from_transforms(H)
assert_array_almost_equal(P[:, :3], H[:, :3, 3])
assert_array_almost_equal(P[:, :3], P2[:, :3])
for t in range(len(P)):
assert_quaternion_equal(P[t, 3:], quaternion_from_matrix(H[t, :3, :3]))
assert_quaternion_equal(P[t, 3:], P2[t, 3:])
def test_norm_vectors_0dims():
random_state = np.random.RandomState(8380)
V = random_state.randn(3)
V_unit = pbr.norm_vectors(V)
assert_almost_equal(np.linalg.norm(V_unit), 1.0)
def test_norm_vectors_zero():
V = np.zeros((3, 8, 1, 2))
V_unit = pbr.norm_vectors(V)
assert_array_almost_equal(V_unit, V)
def test_norm_vectors_3dims():
random_state = np.random.RandomState(8382)
V = random_state.randn(8, 2, 8, 3)
V_unit = pbr.norm_vectors(V)
assert_array_almost_equal(
np.linalg.norm(V_unit, axis=-1), np.ones(V_unit.shape[:-1]))
def test_norm_vectors_1dim_output_variable():
random_state = np.random.RandomState(8381)
V = random_state.randn(100, 3)
pbr.norm_vectors(V, out=V)
assert_array_almost_equal(
np.linalg.norm(V, axis=1), np.ones(len(V)))
def test_norm_vectors_1dim():
random_state = np.random.RandomState(8381)
V = random_state.randn(100, 3)
V_unit = pbr.norm_vectors(V)
assert_array_almost_equal(
np.linalg.norm(V_unit, axis=1), np.ones(len(V)))
