def setUp(self):
"""
Load the test model.
"""
self._bounce = load_fmu('bouncingBall.fmu', path_to_fmus_me1)
self._dq = load_fmu('dq.fmu', path_to_fmus_me1)
self._bounce.initialize()
self._dq.initialize()
self._bounceSim = FMIODE(self._bounce)
self._dqSim = FMIODE(self._dq)
def __init__(self, start_time, final_time, input, model, options):
"""
Create a simulation algorithm using Assimulo.
Parameters::
model --
fmi.FMUModel object representation of the model.
options --
The options that should be used in the algorithm. For details on
the options, see:
* model.simulate_options('AssimuloFMIAlgOptions')
or look at the docstring with help:
* help(pyfmi.fmi_algorithm_drivers.AssimuloFMIAlgOptions)
Valid values are:
- A dict that overrides some or all of the default values
provided by AssimuloFMIAlgOptions. An empty dict will thus
give all options with default values.
- AssimuloFMIAlgOptions object.
"""
self.model = model
if not assimulo_present:
raise Exception(
'Could not find Assimulo package. Check pyfmi.check_packages()'
)
# set start time, final time and input trajectory
self.start_time = start_time
self.final_time = final_time
self.input = input
self.model.time = start_time #Also set start time into the model
# handle options argument
if isinstance(options, dict) and not \
isinstance(options, AssimuloFMIAlgOptions):
# user has passed dict with options or empty dict = default
self.options = AssimuloFMIAlgOptions(options)
elif isinstance(options, AssimuloFMIAlgOptions):
# user has passed AssimuloFMIAlgOptions instance
self.options = options
else:
raise InvalidAlgorithmOptionException(options)
# set options
self._set_options()
input_traj = None
if self.input:
if hasattr(self.input[1], "__call__"):
input_traj = (self.input[0],
TrajectoryUserFunction(self.input[1]))
else:
input_traj = (self.input[0],
TrajectoryLinearInterpolation(
self.input[1][:, 0], self.input[1][:, 1:]))
#Sets the inputs, if any
self.model.set(input_traj[0],
input_traj[1].eval(self.start_time)[0, :])
# Initialize?
if self.options['initialize']:
try:
self.model.initialize(
relativeTolerance=self.solver_options['rtol'])
except KeyError:
rtol, atol = self.model.get_tolerances()
self.model.initialize(relativeTolerance=rtol)
# Sensitivities?
if self.options["sensitivities"]:
if self.options["solver"] != "CVode":
raise Exception(
"Sensitivity simulations currently only supported using the solver CVode."
)
#Checks to see if all the sensitivities are inside the model
#else there will be an exception
self.model.get(self.options["sensitivities"])
if not self.input:
if self.options["sensitivities"]:
self.probl = FMIODESENS(
self.model,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
parameters=self.options["sensitivities"],
logging=self.options["logging"])
else:
self.probl = FMIODE(self.model,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
logging=self.options["logging"])
else:
if self.options["sensitivities"]:
self.probl = FMIODESENS(
self.model,
input_traj,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
parameters=self.options["sensitivities"],
logging=self.options["logging"])
else:
self.probl = FMIODE(self.model,
input_traj,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
logging=self.options["logging"])
# instantiate solver and set options
self.simulator = self.solver(self.probl)
self._set_solver_options()
def __init__(self, start_time, final_time, input, model, options):
"""
Create a simulation algorithm using Assimulo.
Parameters::
model --
fmi.FMUModel object representation of the model.
options --
The options that should be used in the algorithm. For details on
the options, see:
* model.simulate_options('AssimuloFMIAlgOptions')
or look at the docstring with help:
* help(pyfmi.fmi_algorithm_drivers.AssimuloFMIAlgOptions)
Valid values are:
- A dict that overrides some or all of the default values
provided by AssimuloFMIAlgOptions. An empty dict will thus
give all options with default values.
- AssimuloFMIAlgOptions object.
"""
self.model = model
if not assimulo_present:
raise Exception(
'Could not find Assimulo package. Check pyfmi.check_packages()'
)
# set start time, final time and input trajectory
self.start_time = start_time
self.final_time = final_time
self.input = input
# handle options argument
if isinstance(options, dict) and not \
isinstance(options, AssimuloFMIAlgOptions):
# user has passed dict with options or empty dict = default
self.options = AssimuloFMIAlgOptions(options)
elif isinstance(options, AssimuloFMIAlgOptions):
# user has passed AssimuloFMIAlgOptions instance
self.options = options
else:
raise InvalidAlgorithmOptionException(options)
# set options
self._set_options()
input_traj = None
if self.input:
if hasattr(self.input[1], "__call__"):
input_traj = (self.input[0],
TrajectoryUserFunction(self.input[1]))
else:
input_traj = (self.input[0],
TrajectoryLinearInterpolation(
self.input[1][:, 0], self.input[1][:, 1:]))
#Sets the inputs, if any
self.model.set(input_traj[0],
input_traj[1].eval(self.start_time)[0, :])
if self.options["result_handling"] == "file":
self.result_handler = ResultHandlerFile(self.model)
elif self.options["result_handling"] == "memory":
self.result_handler = ResultHandlerMemory(self.model)
elif self.options["result_handling"] == "custom":
self.result_handler = self.options["result_handler"]
if self.result_handler == None:
raise Exception(
"The result handler needs to be specified when using a custom result handling."
)
if not isinstance(self.result_handler, ResultHandler):
raise Exception(
"The result handler needs to be a subclass of ResultHandler."
)
elif self.options[
"result_handling"] == "none": #No result handling (for performance)
self.result_handler = ResultHandlerDummy(self.model)
else:
raise Exception("Unknown option to result_handling.")
self.result_handler.set_options(self.options)
# Initialize?
if self.options['initialize']:
try:
rtol = self.solver_options['rtol']
except KeyError:
rtol, atol = self.model.get_tolerances()
if isinstance(self.model, fmi.FMUModelME1):
self.model.time = start_time #Set start time before initialization
self.model.initialize(relativeTolerance=rtol)
elif isinstance(self.model, fmi.FMUModelME2):
self.model.setup_experiment(tolerance=rtol,
start_time=self.start_time,
stop_time=self.final_time)
self.model.initialize()
self.model.event_update()
self.model.enter_continuous_time_mode()
else:
raise Exception("Unknown model.")
self.result_handler.initialize_complete()
elif self.model.time == None and isinstance(self.model,
fmi.FMUModelME2):
raise Exception(
"Setup Experiment has not been called, this has to be called prior to the initialization call."
)
#See if there is an time event at start time
if isinstance(self.model, fmi.FMUModelME1):
event_info = self.model.get_event_info()
if event_info.upcomingTimeEvent and event_info.nextEventTime == model.time:
self.model.event_update()
self.result_handler.simulation_start()
# Sensitivities?
if self.options["sensitivities"]:
if self.model.get_generation_tool() != "JModelica.org":
raise Exception(
"Sensitivity calculations only possible with JModelica.org generated FMUs"
)
if self.options["solver"] != "CVode":
raise Exception(
"Sensitivity simulations currently only supported using the solver CVode."
)
#Checks to see if all the sensitivities are inside the model
#else there will be an exception
self.model.get(self.options["sensitivities"])
if not self.input and isinstance(self.model, fmi.FMUModelME2):
if self.options["sensitivities"]:
self.probl = FMIODESENS2(
self.model,
result_file_name=self.result_file_name,
start_time=self.start_time,
parameters=self.options["sensitivities"],
logging=self.options["logging"],
result_handler=self.result_handler)
else:
self.probl = FMIODE2(self.model,
result_file_name=self.result_file_name,
start_time=self.start_time,
logging=self.options["logging"],
result_handler=self.result_handler)
elif isinstance(self.model, fmi.FMUModelME2):
if self.options["sensitivities"]:
self.probl = FMIODESENS2(
self.model,
input_traj,
result_file_name=self.result_file_name,
start_time=self.start_time,
parameters=self.options["sensitivities"],
logging=self.options["logging"],
result_handler=self.result_handler)
else:
self.probl = FMIODE2(self.model,
input_traj,
result_file_name=self.result_file_name,
start_time=self.start_time,
logging=self.options["logging"],
result_handler=self.result_handler)
elif not self.input:
if self.options["sensitivities"]:
self.probl = FMIODESENS(
self.model,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
parameters=self.options["sensitivities"],
logging=self.options["logging"],
result_handler=self.result_handler)
else:
self.probl = FMIODE(self.model,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
logging=self.options["logging"],
result_handler=self.result_handler)
else:
if self.options["sensitivities"]:
self.probl = FMIODESENS(
self.model,
input_traj,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
parameters=self.options["sensitivities"],
logging=self.options["logging"],
result_handler=self.result_handler)
else:
self.probl = FMIODE(self.model,
input_traj,
result_file_name=self.result_file_name,
with_jacobian=self.with_jacobian,
start_time=self.start_time,
logging=self.options["logging"],
result_handler=self.result_handler)
# instantiate solver and set options
self.simulator = self.solver(self.probl)
self._set_solver_options()
def __init__(self,
start_time,
final_time,
input,
model,
options):
"""
Create a simulation algorithm using Assimulo.
Parameters::
model --
fmi.FMUModel object representation of the model.
options --
The options that should be used in the algorithm. For details on
the options, see:
* model.simulate_options('AssimuloFMIAlgOptions')
or look at the docstring with help:
* help(pyfmi.fmi_algorithm_drivers.AssimuloFMIAlgOptions)
Valid values are:
- A dict that overrides some or all of the default values
provided by AssimuloFMIAlgOptions. An empty dict will thus
give all options with default values.
- AssimuloFMIAlgOptions object.
"""
self.model = model
self.timings = {}
self.time_start_total = timer()
try:
import assimulo
except:
raise fmi.FMUException(
'Could not find Assimulo package. Check pyfmi.check_packages()')
# import Assimulo dependent classes
from pyfmi.simulation.assimulo_interface import FMIODE, FMIODESENS, FMIODE2, FMIODESENS2
# set start time, final time and input trajectory
self.start_time = start_time
self.final_time = final_time
self.input = input
# handle options argument
if isinstance(options, dict) and not \
isinstance(options, AssimuloFMIAlgOptions):
# user has passed dict with options or empty dict = default
self.options = AssimuloFMIAlgOptions(options)
elif isinstance(options, AssimuloFMIAlgOptions):
# user has passed AssimuloFMIAlgOptions instance
self.options = options
else:
raise InvalidAlgorithmOptionException(options)
# set options
self._set_options()
#time_start = timer()
input_traj = None
if self.input:
if hasattr(self.input[1],"__call__"):
input_traj=(self.input[0],
TrajectoryUserFunction(self.input[1]))
else:
input_traj=(self.input[0],
TrajectoryLinearInterpolation(self.input[1][:,0],
self.input[1][:,1:]))
#Sets the inputs, if any
input_names = [input_traj[0]] if isinstance(input_traj[0],str) else input_traj[0]
input_values = input_traj[1].eval(self.start_time)[0,:]
if len(input_names) != len(input_values):
raise fmi.FMUException("The number of input variables is not equal to the number of input values, please verify the input object.")
self.model.set(input_names, input_values)
if self.options["result_handling"] == "file":
self.result_handler = ResultHandlerFile(self.model)
elif self.options["result_handling"] == "binary":
if self.options["sensitivities"]:
logging.warning('The binary result file do not currently support storing of sensitivity results. Switching to textual result format.')
self.result_handler = ResultHandlerFile(self.model)
else:
self.result_handler = ResultHandlerBinaryFile(self.model)
elif self.options["result_handling"] == "memory":
self.result_handler = ResultHandlerMemory(self.model)
elif self.options["result_handling"] == "csv":
self.result_handler = ResultHandlerCSV(self.model, delimiter=",")
elif self.options["result_handling"] == "custom":
self.result_handler = self.options["result_handler"]
if self.result_handler is None:
raise fmi.FMUException("The result handler needs to be specified when using a custom result handling.")
if not isinstance(self.result_handler, ResultHandler):
raise fmi.FMUException("The result handler needs to be a subclass of ResultHandler.")
elif self.options["result_handling"] == "none": #No result handling (for performance)
self.result_handler = ResultHandlerDummy(self.model)
else:
raise fmi.FMUException("Unknown option to result_handling.")
self.result_handler.set_options(self.options)
time_end = timer()
#self.timings["creating_result_object"] = time_end - time_start
time_start = time_end
time_res_init = 0.0
# Initialize?
if self.options['initialize']:
try:
rtol = self.solver_options['rtol']
except KeyError:
rtol, atol = self.model.get_tolerances()
if isinstance(self.model, fmi.FMUModelME1):
self.model.time = start_time #Set start time before initialization
self.model.initialize(tolerance=rtol)
elif isinstance(self.model, fmi.FMUModelME2) or isinstance(self.model, fmi_coupled.CoupledFMUModelME2):
self.model.setup_experiment(tolerance=rtol, start_time=self.start_time, stop_time=self.final_time)
self.model.initialize()
self.model.event_update()
self.model.enter_continuous_time_mode()
else:
raise fmi.FMUException("Unknown model.")
time_res_init = timer()
self.result_handler.initialize_complete()
time_res_init = timer() - time_res_init
elif self.model.time is None and isinstance(self.model, fmi.FMUModelME2):
raise fmi.FMUException("Setup Experiment has not been called, this has to be called prior to the initialization call.")
elif self.model.time is None:
raise fmi.FMUException("The model need to be initialized prior to calling the simulate method if the option 'initialize' is set to False")
#See if there is an time event at start time
if isinstance(self.model, fmi.FMUModelME1):
event_info = self.model.get_event_info()
if event_info.upcomingTimeEvent and event_info.nextEventTime == model.time:
self.model.event_update()
if abs(start_time - model.time) > 1e-14:
logging.warning('The simulation start time (%f) and the current time in the model (%f) is different. Is the simulation start time correctly set?'%(start_time, model.time))
time_end = timer()
self.timings["initializing_fmu"] = time_end - time_start - time_res_init
time_start = time_end
self.result_handler.simulation_start()
self.timings["initializing_result"] = timer() - time_start + time_res_init
# Sensitivities?
if self.options["sensitivities"]:
if self.model.get_generation_tool() != "JModelica.org" and \
self.model.get_generation_tool() != "Optimica Compiler Toolkit":
if isinstance(self.model, fmi.FMUModelME2):
for var in self.options["sensitivities"]:
causality = self.model.get_variable_causality(var)
if causality != fmi.FMI2_INPUT:
raise fmi.FMUException("The sensitivity parameter is not specified as an input which is required.")
else:
raise fmi.FMUException("Sensitivity calculations only possible with JModelica.org generated FMUs")
if self.options["solver"] != "CVode":
raise fmi.FMUException("Sensitivity simulations currently only supported using the solver CVode.")
#Checks to see if all the sensitivities are inside the model
#else there will be an exception
self.model.get(self.options["sensitivities"])
if not self.input and (isinstance(self.model, fmi.FMUModelME2) or isinstance(self.model, fmi_coupled.CoupledFMUModelME2)):
if self.options["sensitivities"]:
self.probl = FMIODESENS2(self.model, result_file_name=self.result_file_name, with_jacobian=self.with_jacobian, start_time=self.start_time, parameters=self.options["sensitivities"],logging=self.options["logging"], result_handler=self.result_handler)
else:
self.probl = FMIODE2(self.model, result_file_name=self.result_file_name, with_jacobian=self.with_jacobian, start_time=self.start_time,logging=self.options["logging"], result_handler=self.result_handler,extra_equations=self.options["extra_equations"])
elif isinstance(self.model, fmi.FMUModelME2) or isinstance(self.model, fmi_coupled.CoupledFMUModelME2):
if self.options["sensitivities"]:
self.probl = FMIODESENS2(
self.model, input_traj, result_file_name=self.result_file_name, with_jacobian=self.with_jacobian, start_time=self.start_time,parameters=self.options["sensitivities"],logging=self.options["logging"], result_handler=self.result_handler)
else:
self.probl = FMIODE2(
self.model, input_traj, result_file_name=self.result_file_name, with_jacobian=self.with_jacobian, start_time=self.start_time,logging=self.options["logging"], result_handler=self.result_handler, extra_equations=self.options["extra_equations"])
elif not self.input:
if self.options["sensitivities"]:
self.probl = FMIODESENS(self.model, result_file_name=self.result_file_name,with_jacobian=self.with_jacobian,start_time=self.start_time,parameters=self.options["sensitivities"],logging=self.options["logging"], result_handler=self.result_handler)
else:
self.probl = FMIODE(self.model, result_file_name=self.result_file_name,with_jacobian=self.with_jacobian,start_time=self.start_time,logging=self.options["logging"], result_handler=self.result_handler)
else:
if self.options["sensitivities"]:
self.probl = FMIODESENS(
self.model, input_traj, result_file_name=self.result_file_name,with_jacobian=self.with_jacobian,start_time=self.start_time,parameters=self.options["sensitivities"],logging=self.options["logging"], result_handler=self.result_handler)
else:
self.probl = FMIODE(
self.model, input_traj, result_file_name=self.result_file_name,with_jacobian=self.with_jacobian,start_time=self.start_time,logging=self.options["logging"], result_handler=self.result_handler)
# instantiate solver and set options
self.simulator = self.solver(self.probl)
self._set_solver_options()
