def read_hdf5(fid,
variables=[
'geo_info', 'geo_spec_all', 'ao_spec', 'ao_spherical',
'mo_coeff_all', 'mo_energy_all', 'mo_occ_all', 'sym',
'index_list'
]):
'''Reads all variables specified in :literal:`variables` from an HDF5 file
created with :literal:`write_hdf5` and appends this data to the globals() of
this module.
'''
from orbkit.output import hdf5_open, hdf52dict
# Read HDF5 File
display('Reading Hierarchical Data Format file (HDF5) File from %s' % fid)
data_stored = []
for HDF5_file in hdf5_open(fid, mode='r'):
for i in variables:
try:
globals()[i] = hdf52dict(i, HDF5_file)
data_stored.append(i)
if i == 'sym':
s = dict(globals()[i])
globals()[i] = {}
for k, l in s.items():
globals()[i][k] = int(l)
except KeyError:
pass
if not data_stored:
raise IOError(
'Could not find any data in `%s` for the selected `variables`.' %
fid)
display('\tFound: ' + ', '.join(data_stored))
def save_hdf5(fid,
variables=[
'geo_info', 'geo_spec_all', 'ao_spec', 'ao_spherical',
'mo_coeff_all', 'mo_energy_all', 'mo_occ_all', 'sym',
'index_list'
],
hdf5mode='w',
**kwargs):
'''Writes all global variables specified in :literal:`variables` and all
additional :literal:`kwargs` to an HDF5 file.
'''
from orbkit.output import hdf5_open, hdf5_append
# Save HDF5 File
display('Saving Hierarchical Data Format file (HDF5) to %s...' % fid)
data_stored = []
for HDF5_file in hdf5_open(fid, mode=hdf5mode):
for i in variables:
if i in globals():
data = globals()[i]
if not (data == [] or data is None):
if i == 'sym':
data = numpy.array([[k, l] for k, l in data.items()])
hdf5_append(data, HDF5_file, name=i)
data_stored.append(i)
elif i not in kwargs:
raise ValueError(
'Variable `%s` is not in globals() or in **kwargs' % i)
for j in kwargs.keys():
hdf5_append(kwargs[j], HDF5_file, name=j)
data_stored.append(j)
display('\tContent: ' + ', '.join(data_stored))
def hdf5_save(self,fid='out.h5',group='/ci:0',mode='w'):
from orbkit.output import hdf5_open,hdf5_append
from copy import copy
for hdf5_file in hdf5_open(fid,mode=mode):
dct = copy(self.todict())
dct['info'] = numpy.array(dct['info'].items(),dtype=str)
hdf5_append(dct,hdf5_file,name=group)
def hdf5_read(self,fid='out.h5',group='/ci:0'):
from orbkit.output import hdf5_open,hdf52dict
for hdf5_file in hdf5_open(fid,mode='r'):
for key in self.__dict__.keys():
try:
self.__dict__[key] = hdf52dict('%s/%s' % (group,key),hdf5_file)
except KeyError:
self.__dict__[key] = hdf5_file['%s' % group].attrs[key]
self.__dict__['info'] = dict(self.__dict__['info'])
def run_orbkit(use_qc=None, check_options=True, standalone=False):
'''Controls the execution of all computational tasks.
**Parameters:**
use_qc : QCinfo, optional
If not None, the reading of a quantum chemistry output is omitted and
the given QCinfo class is used for all computational tasks.
(See :ref:`Central Variables` in the manual for details on QCinfo.)
check_options : bool, optional
If True, the specified options will be validated.
**Returns:**
data : type and shape depend on the options.
Contains orbkit's output.
See :ref:`High-Level Interface` in the manual for details.
'''
# Set some global variables
global qc
# Display program information
display(lgpl_short)
# Check for the correctness of orbkit.options
if check_options:
display('Checking orbkit.options...\n')
options.check_options(display=display,
interactive=False,
info=True,
check_io=(use_qc is None))
# Measurement of required execution time
t = [time.time()]
# Do we need to read out the info of all MOs?
if (options.mo_set or options.calc_mo) is not False:
options.all_mo = True
if use_qc is None:
# Read the input file
qc = read.main_read(options.filename,
itype=options.itype,
all_mo=options.all_mo,
spin=options.spin,
cclib_parser=options.cclib_parser)
else:
# Use a user defined QCinfo class.
qc = use_qc
display('\nSetting up the grid...')
if options.grid_file is not None:
# Read the grid from an external file
grid.read(options.grid_file)
elif options.adjust_grid is not None:
# Adjust the grid to geo_spec
extend, step = options.adjust_grid
grid.adjust_to_geo(qc, extend=extend, step=step)
elif options.random_grid:
# Create a randomized grid
grid.random_grid(qc.geo_spec)
# Initialize grid
grid.grid_init(is_vector=options.is_vector)
if options.is_vector:
grid.is_regular = False
display(grid.get_grid()) # Display the grid
if not grid.is_regular and options.center_grid is not None:
raise IOError(
'The option --center is only supported for regular grids.')
elif options.center_grid is not None:
atom = grid.check_atom_select(options.center_grid,
qc.geo_info,
qc.geo_spec,
interactive=True,
display=display)
# Center the grid to a specific atom and (0,0,0) if requested
grid.center_grid(qc.geo_spec[atom - 1], display=display)
if check_options or standalone:
options.check_grid_output_compatibilty()
t.append(time.time()) # A new time step
# The calculation of all AOs (--calc_ao)
if options.calc_ao != False:
data = extras.calc_ao(qc, drv=options.drv, otype=options.otype)
t.append(time.time()) # Final time
good_bye_message(t)
return data
# The calculation of selected MOs (--calc_mo) or
# the density formed by selected MOs (--mo_set)
if (options.mo_set or options.calc_mo) != False:
# What should the program do?
if options.calc_mo != False:
fid_mo_list = options.calc_mo
elif options.mo_set != False:
fid_mo_list = options.mo_set
# Call the function for actual calculation
if options.calc_mo != False:
data = extras.calc_mo(qc,
fid_mo_list,
drv=options.drv,
otype=options.otype)
elif options.mo_set != False:
data = extras.mo_set(qc,
fid_mo_list,
drv=options.drv,
laplacian=options.laplacian,
otype=options.otype)
t.append(time.time()) # Final time
good_bye_message(t)
return data
if options.gross_atomic_density is not None:
atom = options.gross_atomic_density
rho_atom = extras.numerical_mulliken_charges(atom, qc)
if not grid.is_vector:
mulliken_num = rho_atom[1]
rho_atom = rho_atom[0]
if not options.no_output:
fid = '%s.h5' % options.outputname
display('\nSaving to Hierarchical Data Format file (HDF5)...' +
'\n\t%(o)s' % {'o': fid})
output.hdf5_write(fid,
mode='w',
gname='',
atom=core.numpy.array(atom),
geo_info=qc.geo_info,
geo_spec=qc.geo_spec,
gross_atomic_density=rho_atom,
x=grid.x,
y=grid.y,
z=grid.z)
if not options.is_vector:
output.hdf5_write(
fid,
mode='a',
gname='/numerical_mulliken_population_analysis',
**mulliken_num)
t.append(time.time())
good_bye_message(t)
return rho_atom
if options.mo_tefd is not None:
mos = options.mo_tefd
ao_list = core.ao_creator(qc.geo_spec, qc.ao_spec)
mo_tefd = []
index = []
for i, j in mos:
mo_tefd.append([])
index.append([])
for ii_d in options.drv:
display('\nMO-TEFD: %s->%s %s-component' % (i, j, ii_d))
tefd = extras.mo_transition_flux_density(i,
j,
qc,
drv=ii_d,
ao_list=ao_list)
mo_tefd[-1].append(tefd)
index[-1].append('%s->%s:%s' % (i, j, ii_d))
if not options.no_output:
from numpy import array
fid = '%s.h5' % options.outputname
display('\nSaving to Hierarchical Data Format file (HDF5)...' +
'\n\t%(o)s' % {'o': fid})
HDF5_File = output.hdf5_open(fid, mode='w')
data = {
'geo_info': array(qc.geo_info),
'geo_spec': array(qc.geo_spec),
'mo_tefd:info': array(index),
'mo_tefd': array(mo_tefd),
'x': grid.x,
'y': grid.y,
'z': grid.z
}
output.hdf5_append(data, HDF5_File, name='')
HDF5_File.close()
t.append(time.time())
good_bye_message(t)
return mo_tefd
t.append(time.time()) # A new time step
# Compute the (derivative of the) electron density
if options.no_slice:
data = core.rho_compute_no_slice(qc,
drv=options.drv,
laplacian=options.laplacian,
return_components=False)
else:
data = core.rho_compute(qc,
drv=options.drv,
slice_length=options.slice_length,
laplacian=options.laplacian,
numproc=options.numproc)
if options.drv is None:
rho = data
elif options.laplacian:
rho, delta_rho, laplacian_rho = data
else:
rho, delta_rho = data
# Compute the reduced electron density if requested
if options.z_reduced_density:
if grid.is_vector:
display('\nSo far, reducing the density is not supported for ' +
'vector grids.\nSkipping the reduction...\n')
elif options.drv is not None:
display(
'\nSo far, reducing the density is not supported for ' +
'the derivative of the density.\nSkipping the reduction...\n')
else:
from scipy import integrate
display('\nReducing the density with respect to the z-axis.\n')
rho = integrate.simps(rho,
grid.x,
dx=grid.delta_[0],
axis=0,
even='avg')
rho = integrate.simps(rho,
grid.y,
dx=grid.delta_[1],
axis=0,
even='avg')
t.append(time.time()) # A new time step
# Generate the output requested
if not options.no_output:
output_written = output.main_output(rho,
qc.geo_info,
qc.geo_spec,
outputname=options.outputname,
otype=options.otype,
data_id='rho',
omit=['vmd', 'mayavi'],
mo_spec=qc.mo_spec)
if options.drv is not None:
output_written.extend(
output.main_output(delta_rho,
qc.geo_info,
qc.geo_spec,
outputname=options.outputname,
otype=options.otype,
data_id='delta_rho',
omit=['vmd', 'mayavi'],
mo_spec=qc.mo_spec,
drv=options.drv))
if options.laplacian:
output_written.extend(
output.main_output(laplacian_rho,
qc.geo_info,
qc.geo_spec,
outputname=options.outputname +
'_laplacian',
otype=options.otype,
data_id='laplacian_rho',
omit=['vmd', 'mayavi'],
mo_spec=qc.mo_spec))
if 'vmd' in options.otype:
# Create VMD network
display('\nCreating VMD network file...' +
'\n\t%(o)s.vmd' % {'o': options.outputname})
cube_files = []
for i in output_written:
if i.endswith('.cb'):
cube_files.append(i)
output.vmd_network_creator(options.outputname,
cube_files=cube_files)
t.append(time.time()) # Final time
good_bye_message(t)
if 'mayavi' in options.otype:
plt_data = [rho]
datalabels = ['rho']
if options.drv is not None:
plt_data.extend(delta_rho)
datalabels.extend(
['d/d%s of %s' % (ii_d, 'rho') for ii_d in options.drv])
if options.laplacian:
plt_data.append(laplacian_rho)
datalabels.append('laplacian of rho')
output.main_output(plt_data,
qc.geo_info,
qc.geo_spec,
otype='mayavi',
datalabels=datalabels)
# Return the computed data, i.e., rho for standard, and (rho,delta_rho)
# for derivative calculations. For laplacian (rho,delta_rho,laplacian_rho)
return data
def calc_ao(qc, drv=None, otype=None, ofid=None):
'''Computes and saves all atomic orbital or a derivative thereof.
**Parameters:**
qc.geo_spec, qc.geo_info, qc.ao_spec :
See :ref:`Central Variables` for details.
otype : str or list of str, optional
Specifies output file type. See :data:`otypes` for details.
ofid : str, optional
Specifies output file name. If None, the filename will be based on
:mod:`orbkit.options.outputname`.
drv : int or string, {None, 'x', 'y', 'z', 'xx', 'xy', ...}, optional
If not None, a derivative calculation of the atomic orbitals
is requested.
**Returns:**
ao_list : numpy.ndarray, shape=((NAO,) + N)
Contains the computed NAO atomic orbitals on a grid. Is only returned, if
otype is None.
'''
from omp_functions import run
if ofid is None:
ofid = options.outputname
dstr = '' if drv is None else '_d%s' % drv
ao_spec = []
lxlylz = []
datalabels = []
for sel_ao in range(len(qc.ao_spec)):
if 'exp_list' in qc.ao_spec[sel_ao].keys():
l = qc.ao_spec[sel_ao]['exp_list']
else:
l = core.exp[core.lquant[qc.ao_spec[sel_ao]['type']]]
lxlylz.extend(l)
for i in l:
ao_spec.append(qc.ao_spec[sel_ao].copy())
ao_spec[-1]['exp_list'] = [i]
datalabels.append('lxlylz=%s,atom=%d' %(i,ao_spec[-1]['atom']))
global_args = {'geo_spec':qc.geo_spec,
'geo_info':qc.geo_info,
'ao_spec':ao_spec,
'drv':drv,
'x':grid.x,
'y':grid.y,
'z':grid.z,
'is_vector':grid.is_vector,
'otype':otype,
'ofid':ofid}
display('Starting the computation of the %d atomic orbitals'%len(ao_spec)+
(' using %d subprocesses.' % options.numproc if options.numproc > 1
else '.' )
)
ao = run(get_ao,x=numpy.arange(len(ao_spec)).reshape((-1,1)),
numproc=options.numproc,display=display,
initializer=initializer,global_args=global_args)
if otype is None or 'h5' in otype or 'mayavi' in otype:
ao_list = []
for i in ao:
ao_list.extend(i)
ao_list = numpy.array(ao_list)
if otype is None or options.no_output:
return ao_list
if 'h5' in otype:
import h5py
fid = '%s_AO%s.h5' % (ofid,dstr)
display('Saving to Hierarchical Data Format file (HDF5)...\n\t%s' % fid)
output.hdf5_write(fid,mode='w',gname='general_info',
x=grid.x,y=grid.y,z=grid.z,
geo_info=qc.geo_info,geo_spec=qc.geo_spec,
lxlylz=numpy.array(lxlylz,dtype=numpy.int64),
aolabels=numpy.array(datalabels),
grid_info=numpy.array(grid.is_vector,dtype=int))
for f in output.hdf5_open(fid,mode='a'):
output.hdf5_append(ao_spec,f,name='ao_spec')
output.hdf5_append(ao_list,f,name='ao_list')
if 'mayavi' in otype:
output.main_output(ao_list,qc.geo_info,qc.geo_spec,
otype='mayavi',datalabels=datalabels)
if 'vmd' in otype and options.vector is None:
fid = '%s_AO%s' % (ofid,dstr)
display('\nCreating VMD network file...' +
'\n\t%(o)s.vmd' % {'o': fid})
output.vmd_network_creator(fid,
cube_files=['%s_AO%s_%03d.cb' % (ofid,
dstr,x) for x in range(len(ao_spec))])
