Exemplo n.º 1
0
    def solve(self):
        """ 
        Runs the simulation. 
        """
        h = (self.final_time - self.start_time) / self.ncp
        grid = N.linspace(self.start_time, self.final_time, self.ncp + 1)[:-1]

        status = 0

        #For result writing
        result_write = ResultWriterDymola(self.model)
        result_write.write_header()

        for t in grid:
            status = self.model.do_step(t, h)

            if status != 0:
                result_write.write_finalize()
                raise Exception(
                    "The simulation failed. See the log for more information. Return flag %d"
                    % status)

            result_write.write_point()

        result_write.write_finalize()
Exemplo n.º 2
0
def write_data(simulator,write_scaled_result=False, result_file_name=''):
    """
    Writes simulation data to a file. Takes as input a simulated model.
    """
    #Determine the result file name
    if result_file_name == '':
        result_file_name=simulator.problem._model.get_name()+'_result.txt'

    model = simulator.problem._model

    t = N.array(simulator.problem._sol_time)
    r = N.array(simulator.problem._sol_real)
    data = N.c_[t,r]
    if len(simulator.problem._sol_int) > 0 and len(simulator.problem._sol_int[0]) > 0:
        i = N.array(simulator.problem._sol_int)
        data = N.c_[data,i]
    if len(simulator.problem._sol_bool) > 0 and len(simulator.problem._sol_bool[0]) > 0:
        #b = N.array(simulator.problem._sol_bool).reshape(
        #    -1,len(model._save_bool_variables_val))
        b = N.array(simulator.problem._sol_bool)
        data = N.c_[data,b]

    export = ResultWriterDymola(model)
    export.write_header(file_name=result_file_name)
    map(export.write_point,(row for row in data))
    export.write_finalize()
Exemplo n.º 3
0
    def solve(self):
        """ 
        Runs the simulation. 
        """
        h = (self.final_time - self.start_time) / self.ncp
        grid = N.linspace(self.start_time, self.final_time, self.ncp + 1)[:-1]

        status = 0

        # For result writing
        result_write = ResultWriterDymola(self.model)
        result_write.write_header()

        for t in grid:
            status = self.model.do_step(t, h)

            if status != 0:
                result_write.write_finalize()
                raise Exception("The simulation failed. See the log for more information. Return flag %d" % status)

            result_write.write_point()

        result_write.write_finalize()
Exemplo n.º 4
0
class FMIODE(Explicit_Problem):
    """
    An Assimulo Explicit Model extended to FMI interface.
    """
    def __init__(self,
                 model,
                 input=None,
                 result_file_name='',
                 with_jacobian=False,
                 start_time=0.0):
        """
        Initialize the problem.
        """
        self._model = model
        self.input = input
        self.input_names = []

        #Set start time to the model
        self._model.time = start_time

        self.t0 = start_time
        self.y0 = self._model.continuous_states
        self.problem_name = self._model.get_name()

        [f_nbr, g_nbr] = self._model.get_ode_sizes()

        self._f_nbr = f_nbr
        self._g_nbr = g_nbr

        if g_nbr > 0:
            self.state_events = self.g
        self.time_events = self.t

        #If there is no state in the model, add a dummy
        #state der(y)=0
        if f_nbr == 0:
            self.y0 = N.array([0.0])

        #Determine the result file name
        if result_file_name == '':
            self.result_file_name = model.get_name() + '_result.txt'
        else:
            self.result_file_name = result_file_name

        #Default values
        self.export = ResultWriterDymola(model)

        #Internal values
        self._sol_time = []
        self._sol_real = []
        self._sol_int = []
        self._sol_bool = []
        self._logg_step_event = []
        self._write_header = True

        #Stores the first time point
        #[r,i,b] = self._model.save_time_point()

        #self._sol_time += [self._model.t]
        #self._sol_real += [r]
        #self._sol_int  += [i]
        #self._sol_bool += b

        if with_jacobian:
            self.jac = self.j  #Activates the jacobian

    def rhs(self, t, y, sw=None):
        """
        The rhs (right-hand-side) for an ODE problem.
        """
        #Moving data to the model
        self._model.time = t
        #Check if there are any states
        if self._f_nbr != 0:
            self._model.continuous_states = y

        #Sets the inputs, if any
        if self.input != None:
            self._model.set(self.input[0], self.input[1].eval(t)[0, :])

        #Evaluating the rhs
        rhs = self._model.get_derivatives()

        #If there is no state, use the dummy
        if self._f_nbr == 0:
            rhs = N.array([0.0])

        return rhs

    def j(self, t, y, sw=None):
        """
        The jacobian function for an ODE problem.
        """
        #Moving data to the model
        self._model.time = t
        #Check if there are any states
        if self._f_nbr != 0:
            self._model.continuous_states = y

        #Sets the inputs, if any
        if self.input != None:
            self._model.set(self.input[0], self.input[1].eval(t)[0, :])

        #Evaluating the jacobian

        #-Evaluating
        Jac = N.zeros(len(y)**2)  #Matrix that holds the information

        #Compute Jac
        self._model.get_jacobian(1, 1, Jac)

        #-Vector manipulation
        Jac = Jac.reshape(len(y), len(y)).transpose()  #Reshape to a matrix

        return Jac

    def g(self, t, y, sw):
        """
        The event indicator function for a ODE problem.
        """
        #Moving data to the model
        self._model.time = t
        #Check if there are any states
        if self._f_nbr != 0:
            self._model.continuous_states = y

        #Sets the inputs, if any
        if self.input != None:
            self._model.set(self.input[0], self.input[1].eval(t)[0, :])

        #Evaluating the event indicators
        eventInd = self._model.get_event_indicators()

        return eventInd

    def t(self, t, y, sw):
        """
        Time event function.
        """
        eInfo = self._model.get_event_info()

        if eInfo.upcomingTimeEvent == True:
            return eInfo.nextEventTime
        else:
            return None

    def handle_result(self, solver, t, y):
        #
        #Post processing (stores the time points).
        #
        #Moving data to the model
        if t != self._model.time:
            #Moving data to the model
            self._model.time = t
            #Check if there are any states
            if self._f_nbr != 0:
                self._model.continuous_states = y

            #Sets the inputs, if any
            if self.input != None:
                self._model.set(self.input[0], self.input[1].eval(t)[0, :])

            #Evaluating the rhs (Have to evaluate the values in the model)
            rhs = self._model.get_derivatives()

        if solver.continuous_output:
            if self._write_header:
                self._write_header = False
                self.export.write_header(file_name=self.result_file_name)
            self.export.write_point()
        else:
            #Retrieves the time-point
            [r, i, b] = self._model.save_time_point()

            #Save the time-point
            self._sol_real += [r]
            self._sol_int += [i]
            self._sol_bool += b
            self._sol_time += [t]

    def handle_event(self, solver, event_info):
        """
        This method is called when Assimulo finds an event.
        """
        #Moving data to the model
        if solver.t != self._model.time:
            self._model.time = solver.t
            #Check if there are any states
            if self._f_nbr != 0:
                self._model.continuous_states = solver.y

            #Sets the inputs, if any
            if self.input != None:
                self._model.set(self.input[0],
                                self.input[1].eval(N.array([solver.t]))[0, :])

            #Evaluating the rhs (Have to evaluate the values in the model)
            rhs = self._model.get_derivatives()

        eInfo = self._model.get_event_info()
        eInfo.iterationConverged = False

        while eInfo.iterationConverged == False:
            self._model.event_update(intermediateResult=False)

            eInfo = self._model.get_event_info()
            #Retrieve solutions (if needed)
            #if eInfo.iterationConverged == False:
            #    pass

        #Check if the event affected the state values and if so sets them
        if eInfo.stateValuesChanged:
            solver.y = self._model.continuous_states

        #Get new nominal values.
        if eInfo.stateValueReferencesChanged:
            solver.atol = 0.01 * solver.rtol * self._model.nominal_continuous_states

        #Check if the simulation should be terminated
        if eInfo.terminateSimulation:
            raise TerminateSimulation  #Exception from Assimulo

    def step_events(self, solver):
        """
        Method which is called at each successful step.
        """
        #Moving data to the model
        if solver.t != self._model.time:
            self._model.time = solver.t
            #Check if there are any states
            if self._f_nbr != 0:
                self._model.continuous_states = solver.y

            #Sets the inputs, if any
            if self.input != None:
                self._model.set(self.input[0],
                                self.input[1].eval(N.array([solver.t]))[0, :])

            #Evaluating the rhs (Have to evaluate the values in the model)
            rhs = self._model.get_derivatives()

        if self._model.completed_integrator_step():
            self._logg_step_event += [solver.t]
            #Event have been detect, call event iteration.
            self.handle_event(solver, [0])
            return 1  #Tell to reinitiate the solver.
        else:
            return 0

    def print_step_info(self):
        """
        Prints the information about step events.
        """
        print '\nStep-event information:\n'
        for i in range(len(self._logg_step_event)):
            print 'Event at time: %e' % self._logg_step_event[i]
        print '\nNumber of events: ', len(self._logg_step_event)

    def finalize(self, solver):
        if solver.continuous_output:
            self.export.write_finalize()

    def _set_input(self, input):
        self.__input = input

    def _get_input(self):
        return self.__input

    input = property(_get_input,
                     _set_input,
                     doc="""
    Property for accessing the input. The input must be a 2-tuple with the first 
    object as a list of names of the input variables and with the other as a 
    subclass of the class Trajectory.
    """)