def METHOD_NAME(self):
    x = np.array([[0.0], [2.0], [3.0], [4.0], [6.0]])
    y = np.array([[branin_1d(case)] for case in x])
    surrogate = KrigingSurrogate(eval_rmse=True)
    surrogate.train(x, y)
    new_x = np.array([3.5])
    mu, sigma = surrogate.predict(new_x)
    assert_near_equal(mu, [[branin_1d(new_x)]], 1e-1)
    assert_near_equal(sigma, [[0.07101449]], 1e-2)