bf2eb63dc6d14a30dc80f121ea335298b60954d4,nilearn/tests/test_param_validation.py,,test_feature_screening,#,69

Before Change

                    screening_percentile, MNI152_BRAIN_VOLUME, is_classif),
                    BaseEstimator))
            else:
                assert_warns(UserWarning, check_feature_screening,
                             screening_percentile, MNI152_BRAIN_VOLUME * 2,
                             is_classif)


def test_get_mask_volume():
    // Test that hard-coded standard mask volume can be corrected computed

After Change

def test_feature_screening():
    // dummy
    mask_img_data = np.zeros((182, 218, 182))
    mask_img_data[30:-30, 30:-30, 30:-30] = 1
    affine = np.eye(4)
    mask_img = nibabel.Nifti1Image(mask_img_data, affine=affine)

    for is_classif in [True, False]:
        for screening_percentile in [100, None, 20, 101, -1, 10]:

Instances