def load_wavepacket(self, timestep, blockid=0, key=("q", "p", "Q", "P", "S", "adQ")): r"""Load a wavepacket at a given timestep and return a fully configured instance. This method just calls some other :py:class:`IOManager` methods in the correct order. It is included only for convenience and is not particularly efficient. :param timestep: The timestep :math:`n` at which we load the wavepacket. :param key: Specify which parameters to load. All are independent. :type key: Tuple of valid identifier strings that are ``q``, ``p``, ``Q``, ``P``, ``S`` and ``adQ``. Default is ``("q", "p", "Q", "P", "S", "adQ")``. :param blockid: The ID of the data block to operate on. :return: A :py:class:`HagedornWavepacket` instance. """ from WaveBlocksND.BlockFactory import BlockFactory BF = BlockFactory() descr = self.load_wavepacket_description(blockid=blockid) HAWP = BF.create_wavepacket(descr) # Parameters and coefficients Pi = self.load_wavepacket_parameters(timestep=timestep, blockid=blockid, key=key) hashes, coeffs = self.load_wavepacket_coefficients(timestep=timestep, get_hashes=True, blockid=blockid) # Basis shapes Ks = [] for ahash in hashes: K_descr = self.load_wavepacket_basisshapes(the_hash=ahash, blockid=blockid) Ks.append(BF.create_basis_shape(K_descr)) # Configure the wavepacket HAWP.set_parameters(Pi, key=key) HAWP.set_basis_shapes(Ks) HAWP.set_coefficients(coeffs) return HAWP
def prepare_simulation(self): r"""Set up a Hagedorn propagator for the simulation loop. Set the potential and initial values according to the configuration. :raise: :py:class:`ValueError` For invalid or missing input data. """ BF = BlockFactory() # The potential instance potential = BF.create_potential(self.parameters) # Project the initial values to the canonical basis BT = BasisTransformationHAWP(potential) # Finally create and initialize the propagator instance # TODO: Attach the "leading_component to the hawp as codata self.propagator = BF.create_propagator(self.parameters, potential) # Create suitable wavepackets for packet_descr in self.parameters["initvals"]: packet = BF.create_wavepacket(packet_descr) # Transform to canonical basis BT.set_matrix_builder(packet.get_innerproduct()) BT.transform_to_canonical(packet) # And hand over self.propagator.add_wavepacket((packet, )) # Add storage for each packet npackets = len(self.parameters["initvals"]) slots = self._tm.compute_number_events() key = ("q", "p", "Q", "P", "S", "adQ") for i in range(npackets): bid = self.IOManager.create_block( dt=self.parameters.get("dt", 0.0)) self.IOManager.add_inhomogwavepacket(self.parameters, timeslots=slots, blockid=bid, key=key) # Write some initial values to disk for packet in self.propagator.get_wavepackets(): self.IOManager.save_inhomogwavepacket_description( packet.get_description()) if self._tm.is_event(0): for packet in self.propagator.get_wavepackets(): # Pi self.IOManager.save_inhomogwavepacket_parameters( packet.get_parameters(key=key), timestep=0, key=key) # Basis shapes for shape in packet.get_basis_shapes(): self.IOManager.save_inhomogwavepacket_basisshapes(shape) # Coefficients self.IOManager.save_inhomogwavepacket_coefficients( packet.get_coefficients(), packet.get_basis_shapes(), timestep=0)
def prepare_simulation(self): r"""Set up a Hagedorn propagator for the simulation loop. Set the potential and initial values according to the configuration. :raise: :py:class:`ValueError` For invalid or missing input data. """ BF = BlockFactory() # The potential instance potential = BF.create_potential(self.parameters) # Project the initial values to the canonical basis BT = BasisTransformationHAWP(potential) # Finally create and initialize the propagator instance # TODO: Attach the "leading_component to the hawp as codata self.propagator = BF.create_propagator(self.parameters, potential) # Create suitable wavepackets chi = self.parameters["leading_component"] for packet_descr in self.parameters["initvals"]: packet = BF.create_wavepacket(packet_descr) # Transform to canonical basis BT.set_matrix_builder(packet.get_innerproduct()) BT.transform_to_canonical(packet) # And hand over self.propagator.add_wavepacket((packet, chi)) # Add storage for each packet npackets = len(self.parameters["initvals"]) slots = self._tm.compute_number_events() key = ("q", "p", "Q", "P", "S", "adQ") for i in range(npackets): bid = self.IOManager.create_block(dt=self.parameters.get("dt", 0.0)) self.IOManager.add_wavepacket(self.parameters, timeslots=slots, blockid=bid, key=key) # Write some initial values to disk for packet in self.propagator.get_wavepackets(): self.IOManager.save_wavepacket_description(packet.get_description()) if self._tm.is_event(0): for packet in self.propagator.get_wavepackets(): # Pi self.IOManager.save_wavepacket_parameters(packet.get_parameters(key=key), timestep=0, key=key) # Basis shapes for shape in packet.get_basis_shapes(): self.IOManager.save_wavepacket_basisshapes(shape) # Coefficients self.IOManager.save_wavepacket_coefficients(packet.get_coefficients(), packet.get_basis_shapes(), timestep=0)
def load_wavepacket_inhomogeneous(iom, timestep, blockid=0): r"""Utility function to load an inhomogeneous wavepacket from an :py:class:`IOManager` instance. :param iom: The :py:class:`IOManager` instance from which to load data. :param timestep: Load the data corresponding to the given `timestep`. :param blockid: The `datablock` from which to read the data. Default is the block with `blockid=0`. Note: This function is a pure utility function and is not efficient. It is built for interactive use only and should not be use in scripts. """ if not iom.has_inhomogwavepacket(blockid=blockid): print("There is no (inhomogeneous) wavepacket to load in block {}". format(blockid)) return BF = BlockFactory() wpd = iom.load_inhomogwavepacket_description(blockid=blockid) HAWP = BF.create_wavepacket(wpd) # Basis shapes BS_descr = iom.load_inhomogwavepacket_basisshapes(blockid=blockid) BS = {} for ahash, descr in BS_descr.items(): BS[ahash] = BF.create_basis_shape(descr) KEY = ("q", "p", "Q", "P", "S", "adQ") # Retrieve simulation data params = iom.load_inhomogwavepacket_parameters(timestep=timestep, blockid=blockid, key=KEY) hashes, coeffs = iom.load_inhomogwavepacket_coefficients(timestep=timestep, get_hashes=True, blockid=blockid) # Configure the wavepacket HAWP.set_parameters(params, key=KEY) HAWP.set_basis_shapes([BS[int(ha)] for ha in hashes]) HAWP.set_coefficients(coeffs) return HAWP
def load_wavepacket_inhomogeneous(iom, timestep, blockid=0): r"""Utility function to load an inhomogeneous wavepacket from an :py:class:`IOManager` instance. :param iom: The :py:class:`IOManager` instance from which to load data. :param timestep: Load the data corresponding to the given `timestep`. :param blockid: The `datablock` from which to read the data. Default is the block with `blockid=0`. Note: This function is a pure utility function and is not efficient. It is built for interactive use only and should not be use in scripts. """ if not iom.has_inhomogwavepacket(blockid=blockid): print("There is no (inhomogeneous) wavepacket to load in block {}".format(blockid)) return BF = BlockFactory() wpd = iom.load_inhomogwavepacket_description(blockid=blockid) HAWP = BF.create_wavepacket(wpd) # Basis shapes BS_descr = iom.load_inhomogwavepacket_basisshapes(blockid=blockid) BS = {} for ahash, descr in BS_descr.items(): BS[ahash] = BF.create_basis_shape(descr) KEY = ("q", "p", "Q", "P", "S", "adQ") # Retrieve simulation data params = iom.load_inhomogwavepacket_parameters(timestep=timestep, blockid=blockid, key=KEY) hashes, coeffs = iom.load_inhomogwavepacket_coefficients(timestep=timestep, get_hashes=True, blockid=blockid) # Configure the wavepacket HAWP.set_parameters(params, key=KEY) HAWP.set_basis_shapes([BS[int(ha)] for ha in hashes]) HAWP.set_coefficients(coeffs) return HAWP