How to use the emukit.core.loop.user_function.MultiSourceFunctionWrapper function in emukit

:param low_noise_std_deviation: Standard deviation of Gaussian observation noise on low fidelity observations.
                                     Defaults to zero.
    :return: Tuple of user function object and parameter space
    """
    parameter_space = ParameterSpace([
        ContinuousParameter('borehole_radius', 0.05, 0.15),
        ContinuousParameter('radius_of_influence', 100, 50000),
        ContinuousParameter('upper_aquifer_transmissivity', 63070, 115600),
        ContinuousParameter('upper_aquifer_head', 990, 1110),
        ContinuousParameter('lower_aquifer_transmissivity', 63.1, 116),
        ContinuousParameter('lower_aquifer_head', 700, 820),
        ContinuousParameter('borehole_length', 1120, 1680),
        ContinuousParameter('hydraulic_conductivity', 9855, 12045),
        InformationSourceParameter(2)])

    user_function = MultiSourceFunctionWrapper([
        lambda x: _borehole_low(x, low_noise_std_deviation),
        lambda x: _borehole_high(x, high_noise_std_deviation)])

    return user_function, parameter_space

x1 = x[:, 0]
        x2 = x[:, 1]
        result = (10.0 * np.sqrt(_branin(x - 2.0)[:, 0]) + 2.0 * (x1 - 0.5) - 3.0 * (
                    3.0 * x2 - 1.0) - 1.0) / 100.
        return result[:, None]

    def branin_low_fidelity(x):
        x2 = x[:, 1]
        result = (branin_medium_fidelity(1.2 * (x + 2.0))[:, 0] * 100. - 3.0 * x2 + 1.0) / 100.
        return result[:, None]

    parameter_space = ParameterSpace([ContinuousParameter('x1', -5, 10), ContinuousParameter('x2', 0, 15),
                                      InformationSourceParameter(3)])

    branin_high = lambda x: _branin(x)/100
    return MultiSourceFunctionWrapper([branin_low_fidelity, branin_medium_fidelity, branin_high]), parameter_space

function_input = np.array([1, 0])
        msfw = MultiSourceFunctionWrapper(functions)
        msfw.evaluate(function_input)

    # invalid function output
    with pytest.raises(ValueError):
        functions = [lambda x: np.array([2])]
        function_input = np.array([[1, 0]])
        msfw = MultiSourceFunctionWrapper(functions)
        msfw.evaluate(function_input)

    # invalid function output type
    with pytest.raises(ValueError):
        functions = [lambda x: [2]]
        function_input = np.array([[1, 0]])
        msfw = MultiSourceFunctionWrapper(functions)
        msfw.evaluate(function_input)

def test_multi_source_function_wrapper_evaluation_with_multiple_extra_arguments():
    functions = [lambda x: (2 * x, np.array([[1]] * x.shape[0]), np.array([[1]] * x.shape[0])),
                 lambda x: (4 * x, np.array([[2]] * x.shape[0]), np.array([[1]] * x.shape[0]))]
    function_input = np.array([[1, 0], [2, 1], [3, 0], [4, 0], [5, 1]])
    source_index = -1
    msfw = MultiSourceFunctionWrapper(functions, source_index, extra_output_names=['cost', 'constraint'])

    output = msfw.evaluate(function_input)

    assert len(output) == function_input.shape[0]
    for i, record in enumerate(output):
        assert_array_equal(output[i].X, function_input[i])
        this_function = functions[function_input[i, source_index]]
        this_function_input = np.delete(function_input[i], source_index)
        assert_array_equal(output[i].Y, this_function(this_function_input)[0])
        assert_array_equal(output[i].cost, this_function(this_function_input)[1][0])
        assert_array_equal(output[i].constraint, this_function(this_function_input)[2][0])

def test_multi_source_function_wrapper_too_many_outputs_outputs_fails():
    functions = [lambda x: (2 * x, np.array([[1]] * x.shape[0]), np.array([[1]] * x.shape[0])),
                 lambda x: (4 * x, np.array([[2]] * x.shape[0]), np.array([[1]] * x.shape[0]))]
    function_input = np.array([[1, 0], [2, 1], [3, 0], [4, 0], [5, 1]])
    source_index = -1
    msfw = MultiSourceFunctionWrapper(functions, source_index)

    with pytest.raises(ValueError):
        msfw.evaluate(function_input)

def test_multi_source_function_wrapper_too_few_outputs_outputs_fails():
    functions = [lambda x: 2 * x,
                 lambda x: 4 * x]
    function_input = np.array([[1, 0], [2, 1], [3, 0], [4, 0], [5, 1]])
    source_index = -1
    msfw = MultiSourceFunctionWrapper(functions, source_index, extra_output_names=['cost'])

    with pytest.raises(ValueError):
        msfw.evaluate(function_input)

def test_multi_source_function_wrapper_evaluation_single_output():
    functions = [lambda x: 2 * x, lambda x: 4 * x]
    function_input = np.array([[1, 0], [2, 1], [3, 0], [4, 0], [5, 1]])
    source_index = -1
    msfw = MultiSourceFunctionWrapper(functions, source_index)

    output = msfw.evaluate(function_input)

    assert len(output) == function_input.shape[0]
    for i, record in enumerate(output):
        assert_array_equal(output[i].X, function_input[i])
        this_function = functions[function_input[i, source_index]]
        this_function_input = np.delete(function_input[i], source_index)
        assert_array_equal(output[i].Y, this_function(this_function_input))

def test_multi_source_function_wrapper_evaluation_with_cost():
    functions = [lambda x: (2 * x, np.array([[1]] * x.shape[0])),
                 lambda x: (4 * x, np.array([[2]] * x.shape[0]))]
    function_input = np.array([[1, 0], [2, 1], [3, 0], [4, 0], [5, 1]])
    source_index = -1
    msfw = MultiSourceFunctionWrapper(functions, source_index, extra_output_names=['cost'])

    output = msfw.evaluate(function_input)

    assert len(output) == function_input.shape[0]
    for i, record in enumerate(output):
        assert_array_equal(output[i].X, function_input[i])
        this_function = functions[function_input[i, source_index]]
        this_function_input = np.delete(function_input[i], source_index)
        assert_array_equal(output[i].Y, this_function(this_function_input)[0])
        assert_array_equal(output[i].cost, this_function(this_function_input)[1][0])