Source code for WaveBlocksND.SimulationLoopFourier

"""The WaveBlocks Project

This file contains the main simulation loop
for the Fourier propagator.

@author: R. Bourquin
@copyright: Copyright (C) 2010, 2011, 2012, 2013, 2015, 2016 R. Bourquin
@license: Modified BSD License
"""

from WaveBlocksND.BlockFactory import BlockFactory
from WaveBlocksND.Initializer import Initializer
from WaveBlocksND.BasisTransformationWF import BasisTransformationWF
from WaveBlocksND.SimulationLoop import SimulationLoop
from WaveBlocksND.IOManager import IOManager

__all__ = ["SimulationLoopFourier"]


class SimulationLoopFourier(SimulationLoop):
    """This class acts as the main simulation loop. It owns a propagator that
    propagates a set of initial values during a time evolution.
    """

    def __init__(self, parameters, resultsfile):
        """Create a new simulation loop instance for a simulation
        using the Fourier propagation method.

        :param parameters: The simulation parameters.
        :type parameters: A :py:class:`ParameterProvider` instance.
        :param resultsfile: Path and filename of the hdf5 output file.
        """
        # Keep a reference to the simulation parameters
        self.parameters = parameters

        # The time propagator instance driving the simulation.
        self.propagator = None

        # An `IOManager` instance for saving simulation results.
        self.IOManager = None

        # Which data do we want to save
        self._tm = self.parameters.get_timemanager()

        # Set up serialization of simulation data
        self.IOManager = IOManager()
        self.IOManager.create_file(resultsfile)
        self.IOManager.create_block(dt=self.parameters.get("dt", 0.0))

        # Save the simulation parameters
        self.IOManager.add_parameters()
        self.IOManager.save_parameters(parameters)


    def prepare_simulation(self):
        r"""Set up a Fourier 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)

        # Compute the position space grid points
        grid = BF.create_grid(self.parameters)

        # Construct initial values
        I = Initializer(self.parameters)
        initialvalues = I.initialize_for_fourier(grid)

        # Transform the initial values to the canonical basis
        BT = BasisTransformationWF(potential)
        BT.set_grid(grid)
        BT.transform_to_canonical(initialvalues)

        # Finally create and initialize the propagator instance
        self.propagator = BF.create_propagator(self.parameters, potential, initialvalues)

        # Write some initial values to disk
        slots = self._tm.compute_number_events()

        self.IOManager.add_grid(self.parameters, blockid="global")
        self.IOManager.add_fourieroperators(self.parameters)
        self.IOManager.add_wavefunction(self.parameters, timeslots=slots)

        self.IOManager.save_grid(grid.get_nodes(flat=True), blockid="global")
        self.IOManager.save_fourieroperators(self.propagator.get_operators())
        if self._tm.is_event(0):
            self.IOManager.save_wavefunction(initialvalues.get_values(), timestep=0)


    def run_simulation(self):
        r"""Run the simulation loop for a number of time steps.
        """
        # The number of time steps we will perform.
        nsteps = self._tm.compute_number_timesteps()

        # Run the prepropagate step
        self.propagator.pre_propagate()
        # Note: We do not save any data here

        # Run the simulation for a given number of timesteps
        for i in range(1, nsteps + 1):
            print(" doing timestep {}".format(i))

            self.propagator.propagate()

            # Save some simulation data
            if self._tm.is_event(i):
                # Run the postpropagate step
                self.propagator.post_propagate()
                self.IOManager.save_wavefunction(self.propagator.get_wavefunction().get_values(), timestep=i)
                # Run the prepropagate step
                self.propagator.pre_propagate()

        # Run the postpropagate step
        self.propagator.post_propagate()
        # Note: We do not save any data here


    def end_simulation(self):
        """Do the necessary cleanup after a simulation. For example request the
        :py:class:`IOManager` to write the data and close the output files.
        """
        self.IOManager.finalize()