def test_projected_cov_calc(lorenz_dataset):
"""Test the project_cross_cov_mats function by also directly projecting
the data."""
rng = np.random.RandomState(20200226)
T, d, X, _, _ = lorenz_dataset
X = X[:, :3]
N = 3
d = 2
T = 6
V = init_coef(N, d, rng, 'random_ortho')
tV = torch.tensor(V)
ccms = calc_cross_cov_mats_from_data(X, T)
tccms = torch.tensor(ccms)
pccms = project_cross_cov_mats(ccms, V)
cov = calc_cov_from_cross_cov_mats(pccms)
XL = form_lag_matrix(X, T)
big_V = np.zeros((T * N, T * d))
for ii in range(T):
big_V[ii * N:(ii + 1) * N, ii * d:(ii + 1) * d] = V
Xp = XL.dot(big_V)
cov2 = np.cov(Xp, rowvar=False)
cov2 = toeplitzify(cov2, T, d)
assert_allclose(cov, cov2)
tpccms = project_cross_cov_mats(tccms, tV)
tcov = calc_cov_from_cross_cov_mats(tpccms)
assert torch.allclose(tcov, torch.tensor(cov2))
assert_allclose(tcov.numpy(), cov2)
def test_form_lag_matrix_copy():
"""Test whether stride_tricks returns a view if the original matrix
is C-contiguous and not otherwise. Also effectively tests whether different
paths are used for stride_tricks for True and False.
"""
X = np.ones((1001, 3), dtype=float, order='C')
# X should not be c-contiguous
X = X.T.copy().T
T = 5
X0 = form_lag_matrix(X, T, stride_tricks=False)
X0 *= 0.
assert not np.all(np.equal(X, 0.))
# X should be c-contiguous
X = np.ones((1001, 3), dtype=float, order='C')
X0 = form_lag_matrix(X, T, stride_tricks=True, writeable=True)
X0 *= 0.
assert_equal(X0, 0.)
def test_form_lag_matrix_errors():
"""Test whether form_lag_matrix raises the correct errors for invalid
T or stride values.
"""
X = np.random.randn(11, 3)
with pytest.raises(ValueError):
form_lag_matrix(X, 11)
form_lag_matrix(X, 3, stride=-1)
form_lag_matrix(X, 3, stride=.5)
def test_form_lag_matrix_stride_tricks():
"""Test whether stride_tricks gives the same answer as the
looping version.
"""
X = np.random.randn(1001, 3)
T = 1
X0 = form_lag_matrix(X, T, stride=1, stride_tricks=False)
assert_array_equal(X, X0)
X0 = form_lag_matrix(X, T, stride=1, stride_tricks=True)
assert_array_equal(X, X0)
T = 5
X0 = form_lag_matrix(X, T, stride=1, stride_tricks=False)
X1 = form_lag_matrix(X, T, stride=1, stride_tricks=True)
assert_array_equal(X0, X1)
T = 5
X0 = form_lag_matrix(X, T, stride=7, stride_tricks=False)
X1 = form_lag_matrix(X, T, stride=7, stride_tricks=True)
assert_array_equal(X0, X1)