def initialize_for_fourier(self, grid):
# NOTE: This code is only temporary until we get the
# more versatile initial value specifications.
# TODO: Make a specification of the IV setup in configurations
Psi = []
for packet_descr in self._parameters["initvals"]:
packet = BlockFactory().create_wavepacket(packet_descr)
# Evaluate the
X = grid.get_nodes(flat=True)
values = packet.evaluate_at(X, prefactor=True)
# Reshape values into hypercubic shape
values = [val.reshape(grid.get_number_nodes()) for val in values]
Psi.append(values)
# TODO: Maybe sum up immediately instead of at the end to reduce memory usage
Psi = reduce(add, Psi)
# Pack the values in a WaveFunction instance
WF = WaveFunction(self._parameters)
WF.set_grid(grid)
WF.set_values(Psi)
return WF
def initialize_for_fourier(self, grid):
# NOTE: This code is only temporary until we get the
# more versatile initial value specifications.
# TODO: Make a specification of the IV setup in configurations
Psi = []
for packet_descr in self._parameters["initvals"]:
packet = BlockFactory().create_wavepacket(packet_descr)
# Evaluate the
X = grid.get_nodes(flat=True)
values = packet.evaluate_at(X, prefactor=True)
# Reshape values into hypercubic shape
values = [val.reshape(grid.get_number_nodes()) for val in values]
Psi.append(values)
# TODO: Maybe sum up immediately instead of at the end to reduce memory usage
Psi = reduce(add, Psi)
# Pack the values in a WaveFunction instance
WF = WaveFunction(self._parameters)
WF.set_grid(grid)
WF.set_values(Psi)
return WF
