def test_perturb():
C = SO2.exp(torch.Tensor([np.pi / 4]))
C_copy = copy.deepcopy(C)
phi = torch.Tensor([0.1])
C.perturb(phi)
assert utils.allclose(
C.as_matrix(), (SO2.exp(phi).dot(C_copy)).as_matrix())
def test_perturb_batch():
C = SO2.exp(torch.Tensor([-1., 0., 1.]))
C_copy1 = copy.deepcopy(C)
C_copy2 = copy.deepcopy(C)
phi = torch.Tensor([0.1])
C_copy1.perturb(phi)
assert utils.allclose(C_copy1.as_matrix(),
(SO2.exp(phi).dot(C)).as_matrix())
phis = torch.Tensor([0.1, 0.2, 0.3])
C_copy2.perturb(phis)
assert utils.allclose(C_copy2.as_matrix(),
(SO2.exp(phis).dot(C)).as_matrix())
def test_exp_log():
C_big = SO2.exp(torch.Tensor([np.pi / 4]))
torch.testing.assert_close(torch.tensor([
[0.7071, -0.7071],
[0.7071, 0.7071],
]),
C_big.mat,
rtol=1e-5,
atol=1e-3)
C_small = SO2.exp(torch.Tensor([0]))
torch.testing.assert_close(torch.tensor([
[1, -0],
[0, 1],
],
dtype=torch.float32),
C_small.mat,
rtol=1e-5,
atol=1e-3)
def test_normalize_batch():
C = SO2.exp(torch.Tensor([-1., 0., 1.]))
assert SO2.is_valid_matrix(C.mat).all()
C.mat.add_(0.1)
assert (SO2.is_valid_matrix(C.mat) == torch.ByteTensor([0, 0, 0])).all()
C.normalize(inds=[0, 2])
assert (SO2.is_valid_matrix(C.mat) == torch.ByteTensor([1, 0, 1])).all()
C.normalize()
assert SO2.is_valid_matrix(C.mat).all()
def test_adjoint_batch():
C = SO2.exp(torch.Tensor([-1., 0., 1.]))
assert (C.adjoint() == torch.ones(C.mat.shape[0])).all()
def test_adjoint():
C = SO2.exp(torch.Tensor([np.pi / 4]))
assert (C.adjoint() == torch.Tensor([1.])).all()
def test_inv_batch():
C = SO2.exp(torch.Tensor([-1., 0., 1.]))
assert utils.allclose(C.dot(C.inv()).mat, SO2.identity(C.mat.shape[0]).mat)
def test_inv():
C = SO2.exp(torch.Tensor([np.pi / 4]))
assert utils.allclose(C.dot(C.inv()).mat, SO2.identity().mat)
def test_normalize():
C = SO2.exp(torch.Tensor([np.pi / 4]))
C.mat.add_(0.1)
C.normalize()
assert SO2.is_valid_matrix(C.mat).all()
def test_exp_log_batch():
C = SO2.exp(torch.Tensor([-1., 0., 1.]))
assert utils.allclose(SO2.exp(SO2.log(C)).mat, C.mat)
def test_exp_log():
C_big = SO2.exp(torch.Tensor([np.pi / 4]))
assert utils.allclose(SO2.exp(SO2.log(C_big)).mat, C_big.mat)
C_small = SO2.exp(torch.Tensor([0]))
assert utils.allclose(SO2.exp(SO2.log(C_small)).mat, C_small.mat)