How to use the fmpy.simulation.Input function in FMPy

def test_single_sample(self):
        t = np.array([0])
        y = np.array([2])

        # "interpolate" input with only one sample
        v = Input.interpolate(1, t, y)

        self.assertEqual(v,  2)

def test_input_continuous(self):

        t = np.array( [ 0, 1, 2, 3])
        y = np.array([[ 0, 0, 3, 3],
                      [-1, 0, 1, 2]])

        # extrapolate left (hold)
        v1, v2 = Input.interpolate(-1, t, y)
        self.assertEqual(v1,  0)
        self.assertEqual(v2, -1)

        # hit sample
        v1, v2 = Input.interpolate(1, t, y)
        self.assertEqual(v1, 0)
        self.assertEqual(v2, 0)

        # interpolate (linear)
        v1, v2 = Input.interpolate(1.5, t, y)
        self.assertAlmostEqual(v1, 1.5)
        self.assertAlmostEqual(v2, 0.5)

        # extrapolate right (hold)
        v1, v2 = Input.interpolate(4, t, y)
        self.assertEqual(v1, 3)
        self.assertEqual(v2, 2)

def simulateCS(model_description, fmu, start_time, stop_time, relative_tolerance, start_values, apply_default_start_values, input_signals, output, output_interval, timeout, step_finished):

    if output_interval is None:
        output_interval = auto_interval(stop_time - start_time)

    sim_start = current_time()

    is_fmi1 = model_description.fmiVersion == '1.0'
    is_fmi2 = model_description.fmiVersion == '2.0'

    if is_fmi2:
        fmu.setupExperiment(tolerance=relative_tolerance, startTime=start_time)

    input = Input(fmu=fmu, modelDescription=model_description, signals=input_signals)

    time = start_time

    apply_start_values(fmu, model_description, start_values, apply_default_start_values)

    # initialize the model
    if is_fmi1:
        input.apply(time)
        fmu.initialize(tStart=time, stopTime=stop_time)
    elif is_fmi2:
        fmu.enterInitializationMode()
        input.apply(time)
        fmu.exitInitializationMode()
    else:
        fmu.enterInitializationMode(tolerance=relative_tolerance, startTime=start_time)
        input.apply(time)

>>> import numpy as np
        >>> dtype = [('time', np.double), ('step', np.double), ('switch', np.bool_)]
        >>> signals = np.array([(0.0, 0.0, False), (0.5, 0.0, False), (0.5, 0.1, True), (1.0, 1.0, True)], dtype=dtype)
        """

        self.fmu = fmu

        if signals is None:
            self.t = None
            return

        # get the time grid
        self.t = signals[signals.dtype.names[0]]

        # find events
        self.t_events = Input.findEvents(signals, modelDescription)

        is_fmi1 = isinstance(fmu, _FMU1)
        is_fmi2 = isinstance(fmu, _FMU2)

        setters = dict()

        # get the setters
        if is_fmi1:
            setters['Real']    = (fmu.fmi1SetReal,    fmi1Real)
            setters['Integer'] = (fmu.fmi1SetInteger, fmi1Integer)
            setters['Boolean'] = (fmu.fmi1SetBoolean, c_int8)
        elif is_fmi2:
            setters['Real']    = (fmu.fmi2SetReal,    fmi2Real)
            setters['Integer'] = (fmu.fmi2SetInteger, fmi2Integer)
            setters['Boolean'] = (fmu.fmi2SetBoolean, fmi2Boolean)
        else:

step_size /= 2

    sim_start = current_time()

    time = start_time

    is_fmi1 = model_description.fmiVersion == '1.0'
    is_fmi2 = model_description.fmiVersion == '2.0'
    is_fmi3 = model_description.fmiVersion.startswith('3.0')

    if is_fmi1:
        fmu.setTime(time)
    elif is_fmi2:
        fmu.setupExperiment(startTime=start_time)

    input = Input(fmu, model_description, input_signals)

    apply_start_values(fmu, model_description, start_values, apply_default_start_values)

    # initialize
    if is_fmi1:

        input.apply(time)

        (iterationConverged,
         stateValueReferencesChanged,
         stateValuesChanged,
         terminateSimulation,
         nextEventTimeDefined,
         nextEventTime) = fmu.initialize()

        if terminateSimulation: