def METHOD_NAME():
    # Check that MCD returns a ValueError with informative message when the
    # covariance of the support data is equal to 0.
    X_1 = np.array([0.5, 0.1, 0.1, 0.1, 0.957, 0.1, 0.1, 0.1, 0.4285, 0.1])
    X_1 = X_1.reshape(-1, 1)
    X_2 = np.array([0.5, 0.3, 0.3, 0.3, 0.957, 0.3, 0.3, 0.3, 0.4285, 0.3])
    X_2 = X_2.reshape(-1, 1)
    msg = (
        "The covariance matrix of the support data is equal to 0, try to "
        "increase support_fraction"
    )
    for X in [X_1, X_2]:
        with pytest.raises(ValueError, match=msg):
            MinCovDet().fit(X)