def prepare_simulation(self):
r"""
Set up a Spawning propagator for the simulation loop. Set the
potential and initial values according to the configuration.
:raise ValueError: For invalid or missing input data.
"""
potential = PotentialFactory().create_potential(self.parameters)
N = potential.get_number_components()
# Check for enough initial values
if self.parameters["leading_component"] > N:
raise ValueError("Leading component index out of range.")
if len(self.parameters["parameters"]) < N:
raise ValueError("Too few initial states given. Parameters are missing.")
if len(self.parameters["coefficients"]) < N:
raise ValueError("Too few initial states given. Coefficients are missing.")
# Create a suitable wave packet
packet = HagedornWavepacket(self.parameters)
packet.set_parameters(self.parameters["parameters"][self.parameters["leading_component"]])
packet.set_quadrature(None)
# Set the initial values
for component, data in enumerate(self.parameters["coefficients"]):
for index, value in data:
packet.set_coefficient(component, index, value)
# Project the initial values to the canonical basis
packet.project_to_canonical(potential)
# Finally create and initialize the propagator instace
inner = HagedornPropagator(potential, packet, self.parameters["leading_component"], self.parameters)
self.propagator = SpawnAdiabaticPropagator(inner, potential, packet, self.parameters["leading_component"], self.parameters)
# Write some initial values to disk
slots = self.tm.compute_number_saves()
for packet in self.propagator.get_wavepackets():
bid = self.iom.create_block(groupid=self.gid)
self.iom.add_wavepacket(self.parameters, timeslots=slots, blockid=bid)
self.iom.save_wavepacket_coefficients(packet.get_coefficients(), blockid=bid, timestep=0)
self.iom.save_wavepacket_parameters(packet.get_parameters(), blockid=bid, timestep=0)
class SimulationLoopSpawnAdiabatic(SimulationLoop):
r"""
This class acts as the main simulation loop. It owns a propagator that
propagates a set of initial values during a time evolution. All values are
read from the ``Parameters.py`` file.
"""
def __init__(self, parameters):
r"""
Create a new simulation loop instance.
"""
# Keep a reference to the simulation parameters
self.parameters = parameters
self.tm = TimeManager(parameters)
#: The time propagator instance driving the simulation.
self.propagator = None
#: A ``IOManager`` instance for saving simulation results.
self.iom = IOManager()
self.iom.create_file(parameters)
self.gid = self.iom.create_group()
def prepare_simulation(self):
r"""
Set up a Spawning propagator for the simulation loop. Set the
potential and initial values according to the configuration.
:raise ValueError: For invalid or missing input data.
"""
potential = PotentialFactory().create_potential(self.parameters)
N = potential.get_number_components()
# Check for enough initial values
if self.parameters["leading_component"] > N:
raise ValueError("Leading component index out of range.")
if len(self.parameters["parameters"]) < N:
raise ValueError("Too few initial states given. Parameters are missing.")
if len(self.parameters["coefficients"]) < N:
raise ValueError("Too few initial states given. Coefficients are missing.")
# Create a suitable wave packet
packet = HagedornWavepacket(self.parameters)
packet.set_parameters(self.parameters["parameters"][self.parameters["leading_component"]])
packet.set_quadrature(None)
# Set the initial values
for component, data in enumerate(self.parameters["coefficients"]):
for index, value in data:
packet.set_coefficient(component, index, value)
# Project the initial values to the canonical basis
packet.project_to_canonical(potential)
# Finally create and initialize the propagator instace
inner = HagedornPropagator(potential, packet, self.parameters["leading_component"], self.parameters)
self.propagator = SpawnAdiabaticPropagator(inner, potential, packet, self.parameters["leading_component"], self.parameters)
# Write some initial values to disk
slots = self.tm.compute_number_saves()
for packet in self.propagator.get_wavepackets():
bid = self.iom.create_block(groupid=self.gid)
self.iom.add_wavepacket(self.parameters, timeslots=slots, blockid=bid)
self.iom.save_wavepacket_coefficients(packet.get_coefficients(), blockid=bid, timestep=0)
self.iom.save_wavepacket_parameters(packet.get_parameters(), blockid=bid, timestep=0)
def run_simulation(self):
r"""
Run the simulation loop for a number of time steps. The number of steps is calculated in the ``initialize`` function.
"""
tm = self.tm
# Run the simulation for a given number of timesteps
for i in xrange(1, tm.get_nsteps()+1):
print(" doing timestep "+str(i))
self.propagator.propagate(tm.compute_time(i))
# Save some simulation data
if tm.must_save(i):
# Check if we need more data blocks for newly spawned packets
while self.iom.get_number_blocks(groupid=self.gid) < self.propagator.get_number_packets():
bid = self.iom.create_block(groupid=self.gid)
self.iom.add_wavepacket(self.parameters, blockid=bid)
for index, packet in enumerate(self.propagator.get_wavepackets()):
self.iom.save_wavepacket_coefficients(packet.get_coefficients(), timestep=i, blockid=index)
self.iom.save_wavepacket_parameters(packet.get_parameters(), timestep=i, blockid=index)
def end_simulation(self):
r"""
Do the necessary cleanup after a simulation. For example request the
IOManager to write the data and close the output files.
"""
self.iom.finalize()
