def aposteriori_spawning(fin, fout, pin, pout, save_canonical=False):
"""
:param f: An ``IOManager`` instance providing the simulation data.
:param datablock: The data block where the results are.
"""
# Number of time steps we saved
timesteps = fin.load_wavepacket_timegrid()
nrtimesteps = timesteps.shape[0]
params = fin.load_wavepacket_parameters()
coeffs = fin.load_wavepacket_coefficients()
# A data transformation needed by API specification
coeffs = [ [ coeffs[i,j,:] for j in xrange(pin["ncomponents"]) ] for i in xrange(nrtimesteps) ]
# The potential
Potential = PotentialFactory().create_potential(pin)
# Initialize a mother Hagedorn wavepacket with the data from another simulation
HAWP = HagedornWavepacket(pin)
HAWP.set_quadrature(None)
# Initialize an empty wavepacket for spawning
SWP = HagedornWavepacket(pout)
SWP.set_quadrature(None)
# Initialize a Spawner
NAS = NonAdiabaticSpawnerKF(pout)
# Try spawning for these components, if none is given, try it for all.
if not "spawn_components" in parametersout:
components = range(pin["ncomponents"])
else:
components = parametersout["spawn_components"]
# Iterate over all timesteps and spawn
for i, step in enumerate(timesteps):
print(" Try spawning at timestep "+str(step))
# Configure the wave packet and project to the eigenbasis.
HAWP.set_parameters(params[i])
HAWP.set_coefficients(coeffs[i])
# Project to the eigenbasis as the parameter estimation
# has to happen there because of coupling.
T = HAWP.clone()
T.project_to_eigen(Potential)
# Try spawning a new packet for each component
estps = [ NAS.estimate_parameters(T, component=acomp) for acomp in components ]
# The quadrature
quadrature = InhomogeneousQuadrature()
# Quadrature, assume same quadrature order for both packets
# Assure the "right" quadrature is choosen if mother and child have
# different basis sizes
if max(HAWP.get_basis_size()) > max(SWP.get_basis_size()):
quadrature.set_qr(HAWP.get_quadrature().get_qr())
else:
quadrature.set_qr(SWP.get_quadrature().get_qr())
for index, ps in enumerate(estps):
if ps is not None:
# One choice of the sign
U = SWP.clone()
U.set_parameters(ps)
# Project the coefficients to the spawned packet
tmp = T.clone()
NAS.project_coefficients(tmp, U, component=components[index])
# Other choice of the sign
V = SWP.clone()
# Transform parameters
psm = list(ps)
B = ps[0]
Bm = -np.real(B)+1.0j*np.imag(B)
psm[0] = Bm
V.set_parameters(psm)
# Project the coefficients to the spawned packet
tmp = T.clone()
NAS.project_coefficients(tmp, V, component=components[index])
# Compute some inner products to finally determine which parameter set we use
ou = abs(quadrature.quadrature(T,U, component=components[index]))
ov = abs(quadrature.quadrature(T,V, component=components[index]))
# Choose the packet which maximizes the inner product. This is the main point!
if ou >= ov:
U = U
else:
U = V
# Finally do the spawning, this is essentially to get the remainder T right
# The packet U is already ok by now.
NAS.project_coefficients(T, U, component=components[index])
# Transform back
if save_canonical is True:
T.project_to_canonical(Potential)
U.project_to_canonical(Potential)
# Save the mother packet rest
fout.save_wavepacket_parameters(T.get_parameters(), timestep=step, blockid=2*index)
fout.save_wavepacket_coefficients(T.get_coefficients(), timestep=step, blockid=2*index)
# Save the spawned packet
fout.save_wavepacket_parameters(U.get_parameters(), timestep=step, blockid=2*index+1)
fout.save_wavepacket_coefficients(U.get_coefficients(), timestep=step, blockid=2*index+1)
quads1 = []
quads2 = []
quads12 = []
for index, pos in enumerate(positions):
print(pos)
# Moving Gaussian
WP2.set_parameters((1.0j, 1.0, 0.0, 0.0, pos))
# Transform the nodes
nodes1 = squeeze(HQ1.transform_nodes(WP1.get_parameters(), WP1.eps))
nodes2 = squeeze(HQ2.transform_nodes(WP2.get_parameters(), WP2.eps))
nodes12 = squeeze(IHQ.transform_nodes(Pibra, WP2.get_parameters(), WP1.eps))
# Compute inner products
Q1 = IHQ.quadrature(WP1, WP1, summed=True)
Q2 = IHQ.quadrature(WP2, WP2, summed=True)
Q12 = IHQ.quadrature(WP1, WP2, summed=True)
quads1.append(Q1)
quads2.append(Q2)
quads12.append(Q12)
# Evaluate the packets
y = WP1.evaluate_at(x, prefactor=True, component=0)
z = WP2.evaluate_at(x, prefactor=True, component=0)
figure()
plot(x, conj(y) * y, "b")
plot(x, conj(z) * z, "g")
plot(x, conj(y) * z, "r")