def test_omp_path():
path = orthogonal_mp(X, y, n_nonzero_coefs=5, return_path=True)
last = orthogonal_mp(X, y, n_nonzero_coefs=5, return_path=False)
assert path.shape == (n_features, n_targets, 5)
assert_array_almost_equal(path[:, :, -1], last)
path = orthogonal_mp_gram(G, Xy, n_nonzero_coefs=5, return_path=True)
last = orthogonal_mp_gram(G, Xy, n_nonzero_coefs=5, return_path=False)
assert path.shape == (n_features, n_targets, 5)
assert_array_almost_equal(path[:, :, -1], last)
def test_unreachable_accuracy():
assert_array_almost_equal(orthogonal_mp(X, y, tol=0),
orthogonal_mp(X, y, n_nonzero_coefs=n_features))
assert_array_almost_equal(
assert_warns(RuntimeWarning,
orthogonal_mp,
X,
y,
tol=0,
precompute=True),
orthogonal_mp(X, y, precompute=True, n_nonzero_coefs=n_features))
def test_omp_return_path_prop_with_gram():
path = orthogonal_mp(X,
y,
n_nonzero_coefs=5,
return_path=True,
precompute=True)
last = orthogonal_mp(X,
y,
n_nonzero_coefs=5,
return_path=False,
precompute=True)
assert path.shape == (n_features, n_targets, 5)
assert_array_almost_equal(path[:, :, -1], last)
def test_perfect_signal_recovery():
idx, = gamma[:, 0].nonzero()
gamma_rec = orthogonal_mp(X, y[:, 0], 5)
gamma_gram = orthogonal_mp_gram(G, Xy[:, 0], 5)
assert_array_equal(idx, np.flatnonzero(gamma_rec))
assert_array_equal(idx, np.flatnonzero(gamma_gram))
assert_array_almost_equal(gamma[:, 0], gamma_rec, decimal=2)
assert_array_almost_equal(gamma[:, 0], gamma_gram, decimal=2)
def test_swapped_regressors():
gamma = np.zeros(n_features)
# X[:, 21] should be selected first, then X[:, 0] selected second,
# which will take X[:, 21]'s place in case the algorithm does
# column swapping for optimization (which is the case at the moment)
gamma[21] = 1.0
gamma[0] = 0.5
new_y = np.dot(X, gamma)
new_Xy = np.dot(X.T, new_y)
gamma_hat = orthogonal_mp(X, new_y, 2)
gamma_hat_gram = orthogonal_mp_gram(G, new_Xy, 2)
assert_array_equal(np.flatnonzero(gamma_hat), [0, 21])
assert_array_equal(np.flatnonzero(gamma_hat_gram), [0, 21])
def test_with_without_gram_tol():
assert_array_almost_equal(orthogonal_mp(X, y, tol=1.),
orthogonal_mp(X, y, tol=1., precompute=True))
def test_with_without_gram():
assert_array_almost_equal(
orthogonal_mp(X, y, n_nonzero_coefs=5),
orthogonal_mp(X, y, n_nonzero_coefs=5, precompute=True))
def test_tol():
tol = 0.5
gamma = orthogonal_mp(X, y[:, 0], tol=tol)
gamma_gram = orthogonal_mp(X, y[:, 0], tol=tol, precompute=True)
assert np.sum((y[:, 0] - np.dot(X, gamma))**2) <= tol
assert np.sum((y[:, 0] - np.dot(X, gamma_gram))**2) <= tol
def test_n_nonzero_coefs():
assert np.count_nonzero(orthogonal_mp(X, y[:, 0], n_nonzero_coefs=5)) <= 5
assert np.count_nonzero(
orthogonal_mp(X, y[:, 0], n_nonzero_coefs=5, precompute=True)) <= 5
def test_correct_shapes():
assert (orthogonal_mp(X, y[:, 0],
n_nonzero_coefs=5).shape == (n_features, ))
assert (orthogonal_mp(X, y, n_nonzero_coefs=5).shape == (n_features, 3))