How to use the tellurium.tellurium function in tellurium

def spark_work(model_with_parameters):
        import tellurium as te
        if(antimony == "antimony"):
            model_roadrunner = te.loada(model_with_parameters[0])
        else:
            model_roadrunner = te.loadSBMLModel(model_with_parameters[0])
        parameter_scan_initilisation = te.ParameterScan(model_roadrunner,**model_with_parameters[1])
        simulator = getattr(parameter_scan_initilisation, function_name)
        return(simulator())

def spark_sensitivity_analysis(model_with_parameters):
        import tellurium as te

        sa_model = model_with_parameters[0]

        parameters = model_with_parameters[1]
        class_name = importlib.import_module(sa_model.filename)

        user_defined_simulator = getattr(class_name, dir(class_name)[0])
        sa_model.simulation = user_defined_simulator()

        if(sa_model.sbml):
            model_roadrunner = te.loadAntimonyModel(te.sbmlToAntimony(sa_model.model))
        else:
            model_roadrunner = te.loadAntimonyModel(sa_model.model)

        model_roadrunner.conservedMoietyAnalysis = sa_model.conservedMoietyAnalysis


        #Running PreSimulation
        model_roadrunner = sa_model.simulation.presimulator(model_roadrunner)

        #Running Analysis
        computations = {}
        model_roadrunner = sa_model.simulation.simulator(model_roadrunner,computations)

        _analysis = [None,None]

        #Setting the Parameter Variables

def stochastic_work(model_object):
        import tellurium as te
        if model_type == "antimony":
            model_roadrunner = te.loada(model_object.model)
        else:
            model_roadrunner = te.loadSBMLModel(model_object.model)
        model_roadrunner.integrator = model_object.integrator
        # seed the randint method with the current time
        random.seed()
        # it is now safe to use random.randint
        model_roadrunner.setSeed(random.randint(1000, 99999))
        model_roadrunner.integrator.variable_step_size = model_object.variable_step_size
        model_roadrunner.reset()
        simulated_data = model_roadrunner.simulate(model_object.from_time, model_object.to_time, model_object.step_points)
        return([simulated_data.colnames,np.array(simulated_data)])

def spark_work(model_with_parameters):
        import tellurium as te
        if(antimony == "antimony"):
            model_roadrunner = te.loada(model_with_parameters[0])
        else:
            model_roadrunner = te.loadSBMLModel(model_with_parameters[0])
        parameter_scan_initilisation = te.ParameterScan(model_roadrunner,**model_with_parameters[1])
        simulator = getattr(parameter_scan_initilisation, function_name)
        return(simulator())

def spark_work(model_with_parameters):
        import tellurium as te
        if(antimony == "antimony"):
            model_roadrunner = te.loada(model_with_parameters[0])
        else:
            model_roadrunner = te.loadSBMLModel(model_with_parameters[0])
        parameter_scan_initilisation = te.ParameterScan(model_roadrunner,**model_with_parameters[1])
        simulator = getattr(parameter_scan_initilisation, function_name)
        return(simulator())

def stochastic_work(model_object):
        import tellurium as te
        if model_type == "antimony":
            model_roadrunner = te.loada(model_object.model)
        else:
            model_roadrunner = te.loadSBMLModel(model_object.model)
        model_roadrunner.integrator = model_object.integrator
        # seed the randint method with the current time
        random.seed()
        # it is now safe to use random.randint
        model_roadrunner.setSeed(random.randint(1000, 99999))
        model_roadrunner.integrator.variable_step_size = model_object.variable_step_size
        model_roadrunner.reset()
        simulated_data = model_roadrunner.simulate(model_object.from_time, model_object.to_time, model_object.step_points)
        return([simulated_data.colnames,np.array(simulated_data)])

def spark_sensitivity_analysis(model_with_parameters):
        import tellurium as te

        sa_model = model_with_parameters[0]

        parameters = model_with_parameters[1]
        class_name = importlib.import_module(sa_model.filename)

        user_defined_simulator = getattr(class_name, dir(class_name)[0])
        sa_model.simulation = user_defined_simulator()

        if(sa_model.sbml):
            model_roadrunner = te.loadAntimonyModel(te.sbmlToAntimony(sa_model.model))
        else:
            model_roadrunner = te.loadAntimonyModel(sa_model.model)

        model_roadrunner.conservedMoietyAnalysis = sa_model.conservedMoietyAnalysis


        #Running PreSimulation
        model_roadrunner = sa_model.simulation.presimulator(model_roadrunner)

        #Running Analysis
        computations = {}
        model_roadrunner = sa_model.simulation.simulator(model_roadrunner,computations)

        _analysis = [None,None]

        #Setting the Parameter Variables
        _analysis[0] = {}
        for i_param,param_names in enumerate(sa_model.bounds.keys()):