def METHOD_NAME(ddof):
    c1 = stats.Cov(ddof=ddof)
    c2 = stats.Cov(ddof=ddof)
    X = [random.random() for _ in range(30)]
    Y = [random.random() for _ in range(30)]
    W = [random.random() for _ in range(30)]
    Z = [random.random() for _ in range(30)]
    for i, (x, y, w, z) in enumerate(zip(X, Y, W, Z)):
        c1.update(x, y)
        c2.update(w, z)
        if i >= c1.ddof:
            assert math.isclose(
                c1.get(),
                np.cov(X[: i + 1], Y[: i + 1], ddof=ddof)[0, 1],
                abs_tol=1e-10,
            )
            assert math.isclose(
                c2.get(),
                np.cov(W[: i + 1], Z[: i + 1], ddof=ddof)[0, 1],
                abs_tol=1e-10,
            )
            assert math.isclose(
                (c1 + c2).get(),
                np.cov(X[: i + 1] + W[: i + 1], Y[: i + 1] + Z[: i + 1], ddof=ddof)[0, 1],
                abs_tol=1e-10,
            )
    c1 += c2
    assert math.isclose(c1.get(), np.cov(X + W, Y + Z, ddof=ddof)[0, 1], abs_tol=1e-10)