def test_modify_view_component(matrix_type, mapping_name):
    adata = ad.AnnData(
        np.zeros((10, 10)),
        **{mapping_name: dict(m=matrix_type(asarray(sparse.random(10, 10))))},
    )
    init_hash = joblib.hash(adata)

    subset = adata[:5, :][:, :5]
    assert subset.is_view
    m = getattr(subset, mapping_name)["m"]
    m[0, 0] = 100
    assert not subset.is_view
    assert getattr(subset, mapping_name)["m"][0, 0] == 100

    assert init_hash == joblib.hash(adata)
def balanced_accuracy_scoring(clf, X, y):
    """Scoring function that computes the balanced accuracy to be used
    internally in the cross-validation procedure.
    """
    y_pred = clf.predict(X)
    conf_mat = confusion_matrix(y, y_pred)
    bal_acc = 0.
    for i in range(len(conf_mat)):
        bal_acc += (float(conf_mat[i, i])) / np.sum(conf_mat[i])

    bal_acc /= len(conf_mat)
    return bal_acc