def BO_dipole_couplings(self, m_list, q_list, E_lim):
"""
BO_dipole_couplings(m_list, q_list, E_lim)
Parallel program that calculates the dipole couplings for a
z-polarized laser in lenght gauge. An eigenstate basis is used, of
states whose quantum numbers are in <m_list> and <q_list>, that have
energies below <E_lim>. The couplings are stored to an HDF5 file.
Parameters
----------
m_list : list of integers, containing the m values wanted in
the basis.
q_list : list of integers, containing the q values wanted in
the basis.
E_lim : float, the upper limit of the energies wanted in
the basis, for R ~ 2.0.
Notes
-----
I sometimes observe unnatural spikes in the couplings
(as a function of R), which should be removed before the couplings
are used. I don't know why they are there.
Example
-------
>>> filename = "el_states_m_0_nu_70_mu_25_beta_1_00_theta_0_00.h5"
>>> tdse = tdse_electron.TDSE_length_z(filename = filename)
>>> m = [0]
>>> q = [0,1,2,3]
>>> E_lim = 5.0
>>> tdse.BO_dipole_couplings(m, q, E_lim)
"""
#Name of the HDF5 file where the couplings will be saved.
self.coupling_file = name_gen.electronic_eig_couplings_R(self,
m_list, q_list, E_lim)
#Parallel stuff
#--------------
#Get processor 'name'.
my_id = pypar.rank()
#Get total number of processors.
nr_procs = pypar.size()
#Size of eigenstate basis. (Buffer for broadcast.)
basis_size_buffer = r_[0]
#Get number of tasks.
f = tables.openFile(self.eigenstate_file)
try:
R_grid = f.root.R_grid[:]
finally:
f.close()
nr_tasks = len(R_grid)
#Get a list of the indices of this processors share of R_grid.
my_tasks = nice_stuff.distribute_work(nr_procs, nr_tasks, my_id)
#The processors will be writing to the same file.
#In order to avoid problems, the procs will do a relay race of writing to
#file. This is handeled by blocking send() and receive().
#Hopefully there will not be to much waiting.
#ID of the processor that will start writing.
starter = 0
#ID of the processor that will be the last to write.
ender = (nr_tasks - 1) % nr_procs
#Buffer for the baton, i.e. the permission slip for file writing.
baton = r_[0]
#The processor one is to receive the baton from.
receive_from = (my_id - 1) % nr_procs
#The processor one is to send the baton to.
send_to = (my_id + 1) % nr_procs
#-------------------------------
#Initializing the HDF5 file
#--------------------------
if my_id == 0:
#Initialize index list.
index_array = []
#Find the index of the R closest to 2.0.
R_index = argmin(abs(R_grid - 2.0))
#Choose basis functions.
f = tables.openFile(self.eigenstate_file)
try:
for m in m_list:
m_group = name_gen.m_name(m)
for q in q_list:
q_group = name_gen.q_name(q)
for i in range(self.config.nu_max + 1):
if eval("f.root.%s.%s.E[%i,%i]"%(m_group, q_group,
i, R_index)) > E_lim:
break
else:
#Collect indices of the basis functions.
index_array.append(r_[m, q, i])
finally:
f.close()
#Cast index list as an array.
index_array = array(index_array)
#Number of eigenstates in the basis.
basis_size = len(index_array)
print basis_size, "is the basis size"
basis_size_buffer[0] = basis_size
f = tables.openFile(self.coupling_file, 'w')
try:
f.createArray("/", "R_grid", R_grid)
#Saving the index array.
f.createArray("/", "index_array", index_array)
#Initializing the arrays for the couplings and energies.
f.createCArray('/', 'E',
tables.atom.FloatAtom(),
(basis_size, nr_tasks),
chunkshape=(basis_size, 1))
f.createCArray('/', 'couplings',
tables.atom.ComplexAtom(16),
(basis_size, basis_size, nr_tasks),
chunkshape=(basis_size, basis_size, 1))
finally:
f.close()
#Save config instance.
self.config.save_config(self.coupling_file)
#----------------------------------
#Calculating the dipole couplings
#--------------------------------
#Broadcasting the basis size from processor 0.
pypar.broadcast(basis_size_buffer, 0)
#Initializing the index array.
if my_id != 0:
index_array = zeros([basis_size_buffer[0], 3], dtype=int)
#Broadcasting the index array from proc. 0.
pypar.broadcast(index_array, 0)
#Looping over the tasks of this processor.
for i in my_tasks:
#Calculate the dipole couplings for one value of R.
couplings, E = self.calculate_dipole_eig_R(index_array, R_grid[i])
#First file write. (Send, but not receive baton.)
if starter == my_id:
#Write to file.
self.save_dipole_eig_R(couplings, E, R_grid[i])
#Avoiding this statement 2nd time around.
starter = -1
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Last file write. (Receive, but not send baton.)
elif i == my_tasks[-1] and ender == my_id :
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
self.save_dipole_eig_R(couplings, E, R_grid[i])
#The rest of the file writes.
else:
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
self.save_dipole_eig_R(couplings, E, R_grid[i])
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Showing the progress of the work.
if my_id == 0:
nice_stuff.status_bar("Electronic dipole couplings:",
i, len(my_tasks))
#----------------------------
#Letting everyone catch up.
pypar.barrier()
def save_all_eigenstates(filename_el, nr_kept, xmin, xmax, xsize, order):
"""
save_all_eigenstates(filename_el, nr_kept, xmin, xmax, xsize, order)
This program solves the vibrational TISE for a set of energy curves,
and stores them in an HDF5 file.
This program must be run in parallel.
Example
-------
To run this program on 5 processors:
$ mpirun -n 5 python -c "execfile('vibrational_BO.py');save_eigenstates()"
"""
#Retrieve the electronic energy curves.
f = tables.openFile(filename_el)
try:
r_grid = f.root.R_grid[:]
energy_curves = f.root.E[:]
finally:
f.close()
#Initialize the B-spline_basis.
spline_basis = vibrational_methods.Bspline_basis(xmin, xmax, xsize, order)
spline_basis.setup_kinetic_hamiltonian()
spline_basis.setup_overlap_matrix()
#Generate a filename.
filename = name_gen.vibrational_eigenstates(filename_el, spline_basis)
#Parallel stuff
#--------------
#Get processor 'name'.
my_id = pypar.rank()
#Get total number of processors.
nr_procs = pypar.size()
#Get number of tasks.
nr_tasks = len(energy_curves)
#Get a list of the indices of this processors share of R_grid.
my_tasks = nice_stuff.distribute_work(nr_procs, nr_tasks, my_id)
#The processors will be writing to the same file.
#In order to avoid problems, the procs will do a relay race of writing to
#file. This is handeled by blocking send() and receive().
#Hopefully there will not be to much waiting.
#ID of the processor that will start writing.
starter = 0
#ID of the processor that will be the last to write.
ender = (nr_tasks - 1) % nr_procs
#Buffer for the baton, i.e. the permission slip for file writing.
baton = r_[0]
#The processor one is to receive the baton from.
receive_from = (my_id - 1) % nr_procs
#The processor one is to send the baton to.
send_to = (my_id + 1) % nr_procs
#-------------------------------
#Initializing the HDF5 file
#--------------------------
if my_id == 0:
f = tables.openFile(filename, 'w')
try:
f.createArray("/", "electronicFilename", [filename_el])
f.createArray("/", "R_grid", r_grid)
f.createArray("/", "overlap", spline_basis.overlap_matrix)
#Initializing the arrays for the eigenvalues and states.
f.createCArray('/','E',
tables.atom.FloatAtom(),
(nr_kept, nr_tasks),
chunkshape=(nr_kept, 1))
f.createCArray('/','V',
tables.atom.FloatAtom(),
(spline_basis.nr_splines, nr_kept, nr_tasks),
chunkshape=(spline_basis.nr_splines, nr_kept, 1))
f.createCArray('/','hamiltonian',
tables.atom.FloatAtom(),
(spline_basis.nr_splines, spline_basis.nr_splines, nr_tasks),
chunkshape=(spline_basis.nr_splines, spline_basis.nr_splines,
1))
finally:
f.close()
#Save spline info.
spline_basis.bsplines.save_spline_info(filename)
#----------------------------------
#Solving the TISE
#----------------
#Looping over the tasks of this processor.
for i in my_tasks:
#TODO REMOVE?
#remove_spikes removes points where the diagonalization has failed.
#potential_hamiltonian = spline_basis.setup_potential_matrix(
# r_grid, remove_spikes(energy_curves[i,:]) + 1/r_grid)
####
#Setup potential matrix.
potential_hamiltonian = spline_basis.setup_potential_matrix(
r_grid, energy_curves[i,:] + 1/r_grid)
#The total hamiltonian.
hamiltonian_matrix = (spline_basis.kinetic_hamiltonian +
potential_hamiltonian)
#Diagonalizing the hamiltonian.
E, V = spline_basis.solve(hamiltonian_matrix, nr_kept)
#First file write. (Send, but not receive baton.)
if starter == my_id:
#Write to file.
spline_basis.save_eigenstates(filename, E, V,
hamiltonian_matrix, i)
#Avoiding this statement 2nd time around.
starter = -1
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Last file write. (Receive, but not send baton.)
elif i == my_tasks[-1] and ender == my_id :
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
spline_basis.save_eigenstates(filename, E, V,
hamiltonian_matrix, i)
#The rest of the file writes.
else:
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
spline_basis.save_eigenstates(filename, E, V,
hamiltonian_matrix, i)
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Showing the progress of the work.
if my_id == 0:
nice_stuff.status_bar("Vibrational BO calculations",
i, len(my_tasks))
#----------------------------
#Letting everyone catch up.
pypar.barrier()
def save_eigenfunction_couplings(filename_el, nr_kept, xmin, xmax, xsize, order):
"""
save_eigenfunction_couplings(filename_el, nr_kept, xmin, xmax, xsize, order)
This program sets up the laser interaction hamiltonian for the
eigenfunction basis, and stores it in an HDF5 file.
This program must be run in parallel.
Example
-------
To run this program on 5 processors:
$ mpirun -n 5 python -c "execfile('vibrational_BO.py');save_eigenstates()"
"""
#Retrieve the electronic energy curves.
f = tables.openFile(filename_el)
try:
r_grid = f.root.R_grid[:]
#Get number of tasks.
el_basis_size = f.root.couplings.shape[0]
finally:
f.close()
#Filter function, describing what index pairs should be included in the
#calculations.
def no_filter(index_pair):
"""
All couplings included.
"""
return True
def symmetry_filter(index_pair):
"""
Only include the upper/lower triangular, since the hermeticity means
that they are the same.
"""
i = index_pair[0]
j = index_pair[1]
if i >= j:
return True
else:
return False
#Make a list of the coupling indices that should be included.
index_table = create_index_table(el_basis_size, no_filter)
nr_tasks = len(index_table)
#Initialize the B-spline_basis.
spline_basis = vibrational_methods.Bspline_basis(xmin, xmax, xsize, order)
vib_basis_size = spline_basis.nr_splines
#Generate a filename.
filename = name_gen.eigenfunction_couplings(filename_el, spline_basis)
#Name of vib states.
filename_vib = name_gen.vibrational_eigenstates(filename_el, spline_basis)
#Parallel stuff
#--------------
#Get processor 'name'.
my_id = pypar.rank()
#Get total number of processors.
nr_procs = pypar.size()
#Get a list of the indices of this processors share of R_grid.
my_tasks = nice_stuff.distribute_work(nr_procs, nr_tasks, my_id)
#The processors will be writing to the same file.
#In order to avoid problems, the procs will do a relay race of writing to
#file. This is handeled by blocking send() and receive().
#Hopefully there will not be to much waiting.
#ID of the processor that will start writing.
starter = 0
#ID of the processor that will be the last to write.
ender = (nr_tasks - 1) % nr_procs
#Buffer for the baton, i.e. the permission slip for file writing.
baton = r_[0]
#The processor one is to receive the baton from.
receive_from = (my_id - 1) % nr_procs
#The processor one is to send the baton to.
send_to = (my_id + 1) % nr_procs
#-------------------------------
#Initializing the HDF5 file
#--------------------------
if my_id == 0:
f = tables.openFile(filename, 'w')
g = tables.openFile(filename_vib)
try:
f.createArray("/", "electronicFilename", [filename_el])
#Initializing the arrays for the time dependent couplings of H.
f.createCArray('/','couplings',
tables.atom.FloatAtom(),
(nr_kept * el_basis_size,
nr_kept * el_basis_size),
chunkshape=(nr_kept,nr_kept))
#Energy diagonal. Time independent part of H.
energy_diagonal = zeros(nr_kept * el_basis_size)
for i in range(el_basis_size):
energy_diagonal[nr_kept * i:
nr_kept * (i + 1)] = g.root.E[:nr_kept,i]
f.createArray("/", "energyDiagonal", energy_diagonal)
finally:
f.close()
g.close()
#Save spline info.
spline_basis.bsplines.save_spline_info(filename)
#----------------------------------
#Setting up the hamiltonian
#--------------------------
#Looping over the tasks of this processor.
for i in my_tasks:
#Retrieve indices.
row_index, column_index = index_table[i]
#Retrieve electronic couplings.
f = tables.openFile(filename_el)
try:
el_coupling = f.root.couplings[row_index, column_index,:]
finally:
f.close()
# #TODO REMOVE?
# #Remove errors from the coupling. (A hack, unfortunately.)
# r_grid_2, el_coupling_2 = remove_spikes(r_grid, el_coupling)
#
# #Setup potential matrix.
# couplings = spline_basis.setup_potential_matrix(
# r_grid_2, el_coupling_2)
#
#Setup potential matrix. Aij = <Bi | f(R) | Bj>
bfb_matrix = spline_basis.setup_potential_matrix(
r_grid, el_coupling)
couplings = zeros([nr_kept, nr_kept])
#Retrieve eigensvectors.
g = tables.openFile(filename_vib)
try:
Vr = g.root.V[:,:,row_index]
Vc = g.root.V[:,:,column_index]
finally:
g.close()
#Calculate couplings.
for r_index in range(nr_kept):
for c_index in range(nr_kept):
couplings[r_index, c_index] = dot(Vr[:,r_index],
dot(Vc[:,c_index]))
#First file write. (Send, but not receive baton.)
if starter == my_id:
#Write to file.
spline_basis.save_couplings(filename, couplings,
row_index, column_index)
#Avoiding this statement 2nd time around.
starter = -1
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Last file write. (Receive, but not send baton.)
elif i == my_tasks[-1] and ender == my_id :
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
spline_basis.save_couplings(filename, couplings,
row_index, column_index)
#The rest of the file writes.
else:
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
spline_basis.save_couplings(filename, couplings,
row_index, column_index)
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Showing the progress of the work.
if my_id == 0:
nice_stuff.status_bar("Calculating couplings:",
i, len(my_tasks))
#----------------------------
#Letting everyone catch up.
pypar.barrier()
def save_electronic_eigenstates(m_max, nu_max, mu_max, R_grid, beta, theta):
"""
save_electronic_eigenstates(m_max, nu_max, mu_max, R_grid, beta, theta)
This program solves the electronic TISE for a range of internuclear
distances, given in <R_grid>, and stores them in an HDF5 file.
This program must be run in parallel.
Example
-------
To run this program on 5 processors:
$ mpirun -n 5 python electronic_BO.py
"""
#Parallel stuff
#--------------
#Get processor 'name'.
my_id = pypar.rank()
#Get total number of processors.
nr_procs = pypar.size()
#Get number of tasks.
nr_tasks = len(R_grid)
#Get a list of the indices of this processors share of R_grid.
my_tasks = nice_stuff.distribute_work(nr_procs, nr_tasks, my_id)
#The processors will be writing to the same file.
#In order to avoid problems, the procs will do a relay race of writing to
#file. This is handeled by blocking send() and receive().
#Hopefully there will not be to much waiting.
#ID of the processor that will start writing.
starter = 0
#ID of the processor that will be the last to write.
ender = (nr_tasks - 1) % nr_procs
#Buffer for the baton, i.e. the permission slip for file writing.
baton = r_[0]
#The processor one is to receive the baton from.
receive_from = (my_id - 1) % nr_procs
#The processor one is to send the baton to.
send_to = (my_id + 1) % nr_procs
#-------------------------------
#Initializing the HDF5 file
#--------------------------
if my_id == 0:
#Creates a config instance.
my_config = config.Config(m = m_max, nu = nu_max, mu = mu_max,
R = R_grid[0], beta = beta, theta = theta)
#Number of basis functions.
basis_size = (2 * m_max + 1) * (nu_max + 1) * (mu_max + 1)
#Generate a filename.
filename = name_gen.electronic_eigenstates_R(my_config)
f = tables.openFile(filename, 'w')
try:
f.createArray("/", "R_grid", R_grid)
#Looping over the m values.
for m in range(-1 * m_max, m_max + 1):
#Creating an m group in the file.
m_group = name_gen.m_name(m)
f.createGroup("/", m_group)
#Looping over th q values.
for q in range(mu_max + 1):
#Creating a q group in the m group in the file.
q_group = name_gen.q_name(q)
f.createGroup("/%s/"%m_group, q_group)
#Initializing the arrays for the eigenvalues and states.
f.createCArray('/%s/%s/'%(m_group, q_group),'E',
tables.atom.FloatAtom(),
(basis_size/(mu_max + 1), nr_tasks),
chunkshape=(basis_size/(mu_max + 1), 1))
f.createCArray('/%s/%s/'%(m_group, q_group),'V',
tables.atom.ComplexAtom(16),
(basis_size, basis_size/(mu_max + 1), nr_tasks),
chunkshape=(basis_size, basis_size/(mu_max + 1), 1))
finally:
f.close()
#Save config instance.
my_config.save_config(filename)
#----------------------------------
#Solving the TISE
#----------------
#Looping over the tasks of this processor.
for i in my_tasks:
#Creating TISE instance.
tise = tise_electron.TISE_electron(m = m_max, nu = nu_max,
mu = mu_max, R = R_grid[i], beta = beta, theta = theta)
#Diagonalizing the hamiltonian.
E,V = tise.solve()
#First file write. (Send, but not receive baton.)
if starter == my_id:
#Write to file.
tise.save_eigenfunctions_R(E, V, R_grid[i])
#Avoiding this statement 2nd time around.
starter = -1
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Last file write. (Receive, but not send baton.)
elif i == my_tasks[-1] and ender == my_id :
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
tise.save_eigenfunctions_R(E, V, R_grid[i])
#The rest of the file writes.
else:
#Receiving the baton from the previous writer.
pypar.receive(receive_from, buffer = baton)
#Write to file.
tise.save_eigenfunctions_R(E, V, R_grid[i])
#Sending the baton to the next writer.
pypar.send(baton, send_to, use_buffer = True)
#Showing the progress of the work.
if my_id == 0:
nice_stuff.status_bar("Electronic BO calculations",
i, len(my_tasks))
#----------------------------
#Letting everyone catch up.
pypar.barrier()
#Since the sign of the eigenfunctions are completely arbitrary, one must
#make sure they do not change sign from one R to another.
if my_id == 0:
tise.align_all_phases()
#Letting 0 catch up.
pypar.barrier()
