def transform_inhawp_to_eigen(iomin, iomout, blockidin=0, blockidout=0):
"""Compute the transformation to the eigenbasis for a wavepacket.
Save the result back to a file.
:param iomin: An :py:class:`IOManager: instance providing the simulation data.
:param iomout: An :py:class:`IOManager: instance for saving the transformed data.
:param blockidin: The data block from which the values are read. Default is `0`.
:param blockidout: The data block to which the values are written. Default is `0`.
"""
parameters = iomin.load_parameters()
# Number of time steps we saved
timesteps = iomin.load_inhomogwavepacket_timegrid(blockid=blockidin)
nrtimesteps = timesteps.shape[0]
# The potential used
Potential = BlockFactory().create_potential(parameters)
# Basis transformator
BT = BasisTransformationHAWP(Potential)
# Initialize a Hagedorn wavepacket with the data
descr = iomin.load_inhomogwavepacket_description(blockid=blockidin)
HAWP = BlockFactory().create_wavepacket(descr)
iomout.add_inhomogwavepacket(descr, timeslots=nrtimesteps, blockid=blockidout)
iomout.save_inhomogwavepacket_description(HAWP.get_description(), blockid=blockidout)
BT.set_matrix_builder(HAWP.get_quadrature())
# Basis shapes
BS_descr = iomin.load_inhomogwavepacket_basisshapes()
BS = {}
for ahash, descr in BS_descr.iteritems():
BS[ahash] = BlockFactory().create_basis_shape(descr)
# Iterate over all timesteps
for i, step in enumerate(timesteps):
print(" Compute eigentransform at timestep # " + str(step))
# Retrieve simulation data
params = iomin.load_inhomogwavepacket_parameters(timestep=step, blockid=blockidin)
hashes, coeffs = iomin.load_inhomogwavepacket_coefficients(timestep=step, get_hashes=True, blockid=blockidin)
# Configure the wavepacket
HAWP.set_parameters(params)
HAWP.set_basis_shape([ BS[int(ha)] for ha in hashes ])
HAWP.set_coefficients(coeffs)
# Transform to the eigenbasis.
BT.transform_to_eigen(HAWP)
# Save the transformed packet
# Pi
iomout.save_inhomogwavepacket_parameters(HAWP.get_parameters(), timestep=step, blockid=blockidout)
# Basis shapes (in case they changed!)
for shape in HAWP.get_basis_shape():
iomout.save_inhomogwavepacket_basisshapes(shape, blockid=blockidout)
# Coefficients
iomout.save_inhomogwavepacket_coefficients(HAWP.get_coefficients(), HAWP.get_basis_shape(), timestep=step, blockid=blockidout)
def read_data_inhomogeneous(iom, blockid=0):
r"""
:param iom: An :py:class:`IOManager` instance providing the simulation data.
:param blockid: The data block from which the values are read.
"""
parameters = iom.load_parameters()
timegrid = iom.load_inhomogwavepacket_timegrid(blockid=blockid)
time = timegrid * parameters["dt"]
# The potential used
Potential = BlockFactory().create_potential(parameters)
# Basis transformator
BT = BasisTransformationHAWP(Potential)
# Basis shapes
BS_descr = iom.load_wavepacket_basisshapes(blockid=blockid)
BS = {}
for ahash, descr in BS_descr.iteritems():
BS[ahash] = BlockFactory().create_basis_shape(descr)
# Initialize a Hagedorn wavepacket with the data
descr = iom.load_inhomogwavepacket_description(blockid=blockid)
HAWP = BlockFactory().create_wavepacket(descr)
BT.set_matrix_builder(HAWP.get_quadrature())
# Store the resulting coefficients here
CI = [ [] for i in xrange(HAWP.get_number_components()) ]
# Iterate over all timesteps, this is an *expensive* transformation
for i, step in enumerate(timegrid):
print(" Computing eigentransformation at timestep "+str(step))
# Retrieve simulation data
params = iom.load_inhomogwavepacket_parameters(timestep=step, blockid=blockid)
hashes, coeffs = iom.load_inhomogwavepacket_coefficients(timestep=step, get_hashes=True, blockid=blockid)
# Configure the wavepacket
HAWP.set_parameters(params)
HAWP.set_basis_shapes([ BS[int(ha)] for ha in hashes ])
HAWP.set_coefficients(coeffs)
# Transform to the eigenbasis.
BT.transform_to_eigen(HAWP)
for index, item in enumerate(HAWP.get_coefficients()):
CI[index].append(item)
CI = [ transpose(hstack(item)) for item in CI ]
return time, CI
def read_data_inhomogeneous(iom, blockid=0):
r"""
:param iom: An :py:class:`IOManager` instance providing the simulation data.
:param blockid: The data block from which the values are read.
"""
parameters = iom.load_parameters()
timegrid = iom.load_inhomogwavepacket_timegrid(blockid=blockid)
dt = parameters["dt"] if "dt" in parameters else 1.0
time = timegrid * dt
# The potential used
Potential = BlockFactory().create_potential(parameters)
# Basis transformator
BT = BasisTransformationHAWP(Potential)
# Initialize a Hagedorn wavepacket with the data
descr = iom.load_inhomogwavepacket_description(blockid=blockid)
HAWP = BlockFactory().create_wavepacket(descr)
BT.set_matrix_builder(HAWP.get_quadrature())
# Store the resulting coefficients here
CI = [[] for i in range(HAWP.get_number_components())]
# Iterate over all timesteps, this is an *expensive* transformation
for i, step in enumerate(timegrid):
print(" Computing eigentransformation at timestep {}".format(step))
# Retrieve simulation data
HAWP = iom.load_inhomogwavepacket(timestep=step, blockid=blockid)
# Transform to the eigenbasis.
BT.transform_to_eigen(HAWP)
for index, item in enumerate(HAWP.get_coefficients()):
CI[index].append(item)
CI = [transpose(hstack(item)) for item in CI]
return time, CI
def transform_inhawp_to_eigen(iomin, iomout, blockidin=0, blockidout=0):
"""Compute the transformation to the eigenbasis for a wavepacket.
Save the result back to a file.
:param iomin: An :py:class:`IOManager: instance providing the simulation data.
:param iomout: An :py:class:`IOManager: instance for saving the transformed data.
:param blockidin: The data block from which the values are read. Default is `0`.
:param blockidout: The data block to which the values are written. Default is `0`.
"""
parameters = iomin.load_parameters()
KEY = ("q", "p", "Q", "P", "S", "adQ")
# Number of time steps we saved
timesteps = iomin.load_inhomogwavepacket_timegrid(blockid=blockidin)
nrtimesteps = timesteps.shape[0]
# The potential used
Potential = BlockFactory().create_potential(parameters)
# Basis transformator
BT = BasisTransformationHAWP(Potential)
# Initialize a Hagedorn wavepacket with the data
descr = iomin.load_inhomogwavepacket_description(blockid=blockidin)
HAWP = BlockFactory().create_wavepacket(descr)
iomout.add_inhomogwavepacket(descr, timeslots=nrtimesteps, blockid=blockidout, key=KEY)
iomout.save_inhomogwavepacket_description(HAWP.get_description(), blockid=blockidout)
BT.set_matrix_builder(HAWP.get_innerproduct())
# Basis shapes
BS_descr = iomin.load_inhomogwavepacket_basisshapes(blockid=blockidin)
BS = {}
for ahash, descr in BS_descr.items():
BS[ahash] = BlockFactory().create_basis_shape(descr)
# Iterate over all timesteps
for i, step in enumerate(timesteps):
print(" Compute eigentransform at timestep %d" % step)
# Retrieve simulation data
params = iomin.load_inhomogwavepacket_parameters(timestep=step, blockid=blockidin, key=KEY)
hashes, coeffs = iomin.load_inhomogwavepacket_coefficients(timestep=step, get_hashes=True, blockid=blockidin)
# Configure the wavepacket
HAWP.set_parameters(params, key=KEY)
HAWP.set_basis_shapes([BS[int(ha)] for ha in hashes])
HAWP.set_coefficients(coeffs)
# Transform to the eigenbasis.
BT.transform_to_eigen(HAWP)
# Save the transformed packet
# Pi
iomout.save_inhomogwavepacket_parameters(HAWP.get_parameters(key=KEY), timestep=step, blockid=blockidout, key=KEY)
# Basis shapes (in case they changed!)
for shape in HAWP.get_basis_shapes():
iomout.save_inhomogwavepacket_basisshapes(shape, blockid=blockidout)
# Coefficients
iomout.save_inhomogwavepacket_coefficients(HAWP.get_coefficients(), HAWP.get_basis_shapes(), timestep=step, blockid=blockidout)