def test_calc_Lambda_b(expected_scatter_matrices, expected_W,
expected_Lambda_b):
S_b = expected_scatter_matrices['S_b']
W = expected_W
actual_Lambda_b = calc_Lambda_b(S_b, W)
assert_allclose(actual_Lambda_b, expected_Lambda_b, rtol=1e-8)
assert_diagonal(actual_Lambda_b, atol=1e-6)
def test_calc_Lambda_w(expected_scatter_matrices, expected_W,
expected_Lambda_w):
S_w = expected_scatter_matrices['S_w']
W = expected_W
dim = W.shape[0]
actual_Lambda_w = calc_Lambda_b(S_w, W)
assert_allclose(actual_Lambda_w, expected_Lambda_w, rtol=1e-8)
assert_diagonal(actual_Lambda_w, atol=1e-6)
assert_allclose(np.eye(dim), actual_Lambda_w, atol=1e-6)
def test_calc_Psi():
np.random.seed(1234)
N = 1234
K = 34
n_avg = N / K
dim = 5
Lambda_b = np.diag(np.random.randint(1, 100, dim))
Lambda_w = np.eye(dim)
expected_Psi = (n_avg - 1) / n_avg * Lambda_b.diagonal() - (1 / n_avg)
expected_Psi[expected_Psi < 0] = 0
expected_Psi = np.diag(expected_Psi)
actual_Psi = calc_Psi(Lambda_w, Lambda_b, n_avg)
assert_diagonal(actual_Psi)
assert_allclose(actual_Psi, expected_Psi)
assert_allclose(actual_Psi.diagonal(), expected_Psi.diagonal())