def test_pham_pos_weight(get_covmats):
# Test that weight must be strictly positive
n_trials, n_channels, w_val = 5, 3, 2
covmats = get_covmats(n_trials, n_channels)
w = w_val * np.ones(n_trials)
with pytest.raises(ValueError): # not strictly positive weight
w[0] = 0
ajd_pham(covmats, sample_weight=w)
def test_pham(get_covmats):
"""Test pham's ajd"""
n_trials, n_channels, w_val = 5, 3, 2
covmats = get_covmats(n_trials, n_channels)
V, D = ajd_pham(covmats)
assert V.shape == (n_channels, n_channels)
assert D.shape == (n_trials, n_channels, n_channels)
Vw, Dw = ajd_pham(covmats, sample_weight=w_val * np.ones(n_trials))
assert_array_equal(V, Vw) # same result as ajd_pham without weight
assert_array_equal(D, Dw)
def test_pham_zero_weight(get_covmats):
# now test that setting one weight to almost zero it's almost
# like not passing the matrix
n_trials, n_channels, w_val = 5, 3, 2
covmats = get_covmats(n_trials, n_channels)
w = w_val * np.ones(n_trials)
V, D = ajd_pham(covmats[1:], sample_weight=w[1:])
w[0] = 1e-12
Vw, Dw = ajd_pham(covmats, sample_weight=w)
assert V == approx(Vw, rel=1e-4, abs=1e-8)
assert D == approx(Dw[1:], rel=1e-4, abs=1e-8)
def test_pham():
"""Test pham's ajd"""
Nt = 100
covmats, diags, A = generate_cov(Nt, 3)
V, D = ajd_pham(covmats)
w = 5 * np.ones(Nt)
Vw, Dw = ajd_pham(covmats, sample_weight=w)
assert_array_equal(V, Vw) # same result as ajd_pham without weight
assert_array_equal(D, Dw)
# Test that weight must be strictly positive
with pytest.raises(ValueError): # not strictly positive weight
w[0] = 0
ajd_pham(covmats, sample_weight=w)
# now test that setting one weight to almost zero it's almost
# like not passing the matrix
V, D = ajd_pham(covmats[1:])
w[0] = 1e-12
Vw, Dw = ajd_pham(covmats, sample_weight=w)
assert_allclose(V, Vw, rtol=1e-4, atol=1e-8)
assert_allclose(D, Dw[1:], rtol=1e-4, atol=1e-8)
def test_pham():
"""Test pham's ajd"""
covmats, diags, A = generate_cov(100, 3)
V, D = ajd_pham(covmats)