def test_double_index(subset_func, subset_func2):
    adata = gen_adata((10, 10))
    obs_subset = subset_func(adata.obs_names)
    var_subset = subset_func2(adata.var_names)
    v1 = adata[obs_subset, var_subset]
    v2 = adata[obs_subset, :][:, var_subset]

    assert np.all(asarray(v1.X) == asarray(v2.X))
    assert np.all(v1.obs == v2.obs)
    assert np.all(v1.var == v2.var)
def compute_svm_cv(K, y, C=100.0, n_folds=5,
                   scoring=balanced_accuracy_scoring):
    """Compute cross-validated score of SVM with given precomputed kernel.
    """
    cv = StratifiedKFold(y, n_folds=n_folds)
    clf = SVC(C=C, kernel='precomputed', class_weight='auto')
    scores = cross_val_score(clf, K, y,
                             scoring=scoring, cv=cv)
    return scores.mean()