def test_ica_simple(method):
"""Test that ICA recovers the unmixing matrix in a simple case."""
_skip_check_picard(method)
n_components = 3
n_samples = 1000
rng = np.random.RandomState(0)
S = rng.laplace(size=(n_components, n_samples))
A = rng.randn(n_components, n_components)
data = np.dot(A, S)
ica = ICA(n_components=n_components, method=method, random_state=0)
ica._fit(data, n_components, 0)
transform = np.dot(np.dot(ica.unmixing_matrix_, ica.pca_components_), A)
amari_distance = np.mean(np.sum(np.abs(transform), axis=1) /
np.max(np.abs(transform), axis=1) - 1.)
assert amari_distance < 0.1
def test_ica_simple(method):
"""Test that ICA recovers the unmixing matrix in a simple case."""
_skip_check_picard(method)
n_components = 3
n_samples = 1000
rng = np.random.RandomState(0)
S = rng.laplace(size=(n_components, n_samples))
A = rng.randn(n_components, n_components)
data = np.dot(A, S)
ica = ICA(n_components=n_components, method=method, random_state=0)
ica._fit(data, n_components, 0)
transform = np.dot(np.dot(ica.unmixing_matrix_, ica.pca_components_), A)
amari_distance = np.mean(np.sum(np.abs(transform), axis=1) /
np.max(np.abs(transform), axis=1) - 1.)
assert amari_distance < 0.1
def test_ica_simple(method):
"""Test that ICA recovers the unmixing matrix in a simple case."""
if method == "fastica":
try:
import sklearn # noqa: F401
except ImportError:
raise SkipTest("scikit-learn not installed")
_skip_check_picard(method)
n_components = 3
n_samples = 1000
rng = np.random.RandomState(0)
S = rng.laplace(size=(n_components, n_samples))
A = rng.randn(n_components, n_components)
data = np.dot(A, S)
ica = ICA(n_components=n_components, method=method, random_state=0)
ica._fit(data, n_components, 0)
transform = np.dot(np.dot(ica.unmixing_matrix_, ica.pca_components_), A)
amari_distance = np.mean(np.sum(np.abs(transform), axis=1) /
np.max(np.abs(transform), axis=1) - 1.)
assert amari_distance < 0.1
