Python _univariate_feature_screening Beispiele

Beispiel #1

Datei: test_space_net.py Projekt: spanlab/spantoolbox

def test_univariate_feature_screening(dim=(11, 12, 13), n_samples=10):
    rng = np.random.RandomState(42)
    mask = rng.rand(*dim) > 100. / np.prod(dim)
    assert_true(mask.sum() >= 100.)
    mask[dim[0] // 2, dim[1] // 3:, -dim[2] // 2:] = 1  # put spatial structure
    n_features = mask.sum()
    X = rng.randn(n_samples, n_features)
    w = rng.randn(n_features)
    w[rng.rand(n_features) > .8] = 0.
    y = X.dot(w)
    for is_classif in [True, False]:
        X_, mask_, support_ = _univariate_feature_screening(
            X, y, mask, is_classif, 20.)
        n_features_ = support_.sum()
        assert_equal(X_.shape[1], n_features_)
        assert_equal(mask_.sum(), n_features_)
        assert_true(n_features_ <= n_features)

Beispiel #2

Datei: test_space_net.py Projekt: CandyPythonFlow/nilearn

def test_univariate_feature_screening(dim=(11, 12, 13), n_samples=10):
    rng = np.random.RandomState(42)
    mask = rng.rand(*dim) > 100. / np.prod(dim)
    assert_true(mask.sum() >= 100.)
    mask[dim[0] // 2, dim[1] // 3:, -dim[2] // 2:] = 1  # put spatial structure
    n_features = mask.sum()
    X = rng.randn(n_samples, n_features)
    w = rng.randn(n_features)
    w[rng.rand(n_features) > .8] = 0.
    y = X.dot(w)
    for is_classif in [True, False]:
        X_, mask_, support_ = _univariate_feature_screening(
            X, y, mask, is_classif, 20.)
        n_features_ = support_.sum()
        assert_equal(X_.shape[1], n_features_)
        assert_equal(mask_.sum(), n_features_)
        assert_true(n_features_ <= n_features)