def calc_ao(qc,
drv=None,
otype=None,
ofid=None,
numproc=None,
slice_length=None):
'''Computes and saves all atomic orbital or a derivative thereof.
**Parameters:**
qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec :
See :ref:`Central Variables` for details.
drv : string or list of strings {None,'x','y', 'z', 'xx', 'xy', ...}, optional
If not None, a derivative calculation of the atomic orbitals
is requested.
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`.
numproc : int, optional
Specifies number of subprocesses for multiprocessing.
If None, uses the value from :mod:`options.numproc`.
slice_length : int, optional
Specifies the number of points per subprocess.
If None, uses the value from :mod:`options.slice_length`.
**Returns:**
ao_list : numpy.ndarray, shape=((NAO,) + N)
Contains the computed NAO atomic orbitals on a grid.
'''
slice_length = options.slice_length if slice_length is None else slice_length
numproc = options.numproc if numproc is None else numproc
datalabels = qc.ao_spec.get_labels()
ao_list = core.rho_compute(qc,
calc_ao=True,
drv=drv,
slice_length=options.slice_length,
numproc=options.numproc)
if otype is None:
return ao_list
if ofid is None:
ofid = '%s_AO' % (options.outputname)
if not options.no_output:
output_written = main_output(ao_list,
qc,
outputname=ofid,
datalabels=qc.ao_spec.get_labels(),
otype=otype,
drv=drv)
return ao_list
def get_ao(x):
ao_list = core.ao_creator(global_args['geo_spec'],
[global_args['ao_spec'][int(x)]],
drv=global_args['drv'])
if global_args['otype'] is not None:
drv = global_args['drv']
comments = '%03d.lxlylz=%s,at=%d' %(x,
global_args['ao_spec'][x]['exp_list'][0],
global_args['ao_spec'][x]['atom'])
output.main_output(ao_list[0] if drv is None else ao_list,
global_args['geo_info'],
global_args['geo_spec'],
comments=comments,
outputname='%s_AO_%03d' % (global_args['ofid'],x),
otype=global_args['otype'],
omit=['h5','vmd','mayavi'],
drv = None if drv is None else [drv])
return ao_list
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_jmo(qc,
ij,
drv=['x', 'y', 'z'],
numproc=1,
otype=None,
ofid='',
**kwargs):
'''Calculate one component (e.g. drv='x') of the
transition electoronic flux density between the
molecular orbitals i and j.
.. math::
moTEFD_{i,j}(r) = <mo_i|\delta(r-r')\\nabla_x|mo_j>
**Parameters:**
i: int
index of the first mo (Bra)
j: int
index of the second mo (Ket)
drv: {0,1,2,'x','y','z'}
The desired component of the vector field of the
transition electoronic flux density
**Returns:**
mo_tefd : numpy.ndarray
'''
ij = numpy.asarray(ij)
if ij.ndim == 1 and len(ij) == 2:
ij.shape = (1, 2)
assert ij.ndim == 2
assert ij.shape[1] == 2
u, indices = numpy.unique(ij, return_inverse=True)
indices.shape = (-1, 2)
mo_spec = qc.mo_spec[u]
qc_select = qc.copy()
qc_select.mo_spec = mo_spec
labels = mo_spec.get_labels(format='short')
mo_matrix = core.calc_mo_matrix(qc_select,
drv=drv,
numproc=numproc,
**kwargs)
jmo = numpy.zeros((len(drv), len(indices)) + grid.get_shape())
datalabels = []
for n, (i, j) in enumerate(indices):
jmo[:, n] = -0.5 * (mo_matrix[:, i, j] - mo_matrix[:, j, i])
datalabels.append('j( %s , %s )' % (labels[i], labels[j]))
if not options.no_output:
output_written = main_output(jmo,
qc,
outputname=ofid,
datalabels=datalabels,
otype=otype,
drv=drv)
return jmo
def calc_mo(qc,
fid_mo_list,
drv=None,
otype=None,
ofid=None,
numproc=None,
slice_length=None):
'''Calculates and saves the selected molecular orbitals or the derivatives thereof.
**Parameters:**
qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec :
See :ref:`Central Variables` for details.
fid_mo_list : str
Specifies the filename of the molecular orbitals list or list of molecular
orbital labels (cf. :mod:`orbkit.read.mo_select` for details).
If fid_mo_list is 'all_mo', creates a list containing all molecular orbitals.
drv : string or list of strings {None,'x','y', 'z', 'xx', 'xy', ...}, optional
If not None, a derivative calculation of the molecular orbitals
is requested.
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`.
numproc : int, optional
Specifies number of subprocesses for multiprocessing.
If None, uses the value from :mod:`options.numproc`.
slice_length : int, optional
Specifies the number of points per subprocess.
If None, uses the value from :mod:`options.slice_length`.
**Returns:**
mo_list : numpy.ndarray, shape=((NMO,) + N)
Contains the NMO=len(qc.mo_spec) molecular orbitals on a grid.
'''
mo_spec = qc.mo_spec[fid_mo_list]
qc_select = qc.copy()
qc_select.mo_spec = mo_spec
slice_length = options.slice_length if slice_length is None else slice_length
numproc = options.numproc if numproc is None else numproc
# Calculate the AOs and MOs
mo_list = core.rho_compute(qc_select,
calc_mo=True,
drv=drv,
slice_length=slice_length,
numproc=numproc)
if otype is None:
return mo_list
if ofid is None:
if '@' in options.outputname:
outputname, group = options.outputname.split('@')
else:
outputname, group = options.outputname, ''
outputname, autootype = os.path.splitext(outputname)
ofid = '%s_MO%s@%s' % (outputname, autootype, group)
if not options.no_output:
output_written = main_output(mo_list,
qc_select,
outputname=ofid,
datalabels=qc_select.mo_spec.get_labels(),
otype=otype,
drv=drv)
return mo_list
def mo_set(qc,
fid_mo_list,
drv=None,
laplacian=None,
otype=None,
ofid=None,
return_all=True,
numproc=None,
slice_length=None):
'''Calculates and saves the density or the derivative thereof
using selected molecular orbitals.
**Parameters:**
qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec :
See :ref:`Central Variables` for details.
fid_mo_list : str
Specifies the filename of the molecular orbitals list or list of molecular
orbital labels (cf. :mod:`orbkit.orbitals.MOClass.select` 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 : string or list of strings {None,'x','y', 'z', 'xx', 'xy', ...}, optional
If not None, a derivative calculation is requested.
return_all : bool
If False, no data will be returned.
numproc : int, optional
Specifies number of subprocesses for multiprocessing.
If None, uses the value from :mod:`options.numproc`.
slice_length : int, optional
Specifies the number of points per subprocess.
If None, uses the value from :mod:`options.slice_length`.
**Returns:**
datasets : numpy.ndarray, shape=((NSET,) + N)
Contains the NSET molecular orbital sets on a grid.
delta_datasets : numpy.ndarray, shape=((NSET,NDRV) + N)
Contains the NDRV NSET molecular orbital set on a grid. This is only
present if derivatives are requested.
'''
#Can be an mo_spec or a list of mo_spec
# For later iteration we'll make it into a list here if it is not
mo_info_list = qc.mo_spec.select(fid_mo_list, flatten_input=False)
drv = options.drv if drv is None else drv
laplacian = options.laplacian if laplacian is None else laplacian
slice_length = options.slice_length if slice_length is None else slice_length
numproc = options.numproc if numproc is None else numproc
if ofid is None:
ofid = options.outputname
datasets = []
datalabels = []
delta_datasets = []
delta_datalabels = []
cube_files = []
for i_file, mo_info in enumerate(mo_info_list):
qc_select = qc.copy()
qc_select.mo_spec = mo_info
label = 'mo_set:' + mo_info.selection_string
display('\nStarting with the molecular orbital list \n\t' + label +
'\n\t(Only regarding existing and occupied mos.)\n')
data = core.rho_compute(qc_select,
drv=drv,
laplacian=laplacian,
slice_length=slice_length,
numproc=numproc)
if drv is None:
rho = data
delta_datasets = numpy.zeros((0, ) + rho.shape)
elif laplacian:
rho, delta_rho, laplacian_rho = data
delta_datasets.extend(delta_rho)
delta_datasets.append(laplacian_rho)
delta_datalabels.extend(
['d^2/d%s^2 %s' % (i, label) for i in 'xyz'])
delta_datalabels.append('laplacian_of_' + label)
else:
rho, delta_rho = data
delta_datasets.extend(delta_rho)
delta_datalabels.extend(['d/d%s %s' % (i, label) for i in drv])
datasets.append(rho)
datalabels.append(label)
datasets = numpy.array(datasets)
delta_datasets = numpy.array(delta_datasets)
delta_datalabels.append('mo_set')
data = numpy.append(datasets, delta_datasets, axis=0)
if not options.no_output:
output_written = main_output(data,
qc,
outputname=ofid,
datalabels=datalabels + delta_datalabels,
otype=otype,
drv=None)
return data
def calc_mo(qc, fid_mo_list, drv=None, otype=None, ofid=None,
numproc=None, slice_length=None):
'''Calculates and saves the selected molecular orbitals or the derivatives thereof.
**Parameters:**
qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec :
See :ref:`Central Variables` for details.
fid_mo_list : str
Specifies the filename of the molecular orbitals list or list of molecular
orbital labels (cf. :mod:`orbkit.read.mo_select` for details).
If fid_mo_list is 'all_mo', creates a list containing all molecular orbitals.
drv : int or string, {None, 'x', 'y', 'z', 0, 1, 2}, optional
If not None, a derivative calculation of the atomic orbitals
is requested.
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`.
numproc : int, optional
Specifies number of subprocesses for multiprocessing.
If None, uses the value from :mod:`options.numproc`.
slice_length : int, optional
Specifies the number of points per subprocess.
If None, uses the value from :mod:`options.slice_length`.
**Returns:**
mo_list : numpy.ndarray, shape=((NMO,) + N)
Contains the NMO=len(qc.mo_spec) molecular orbitals on a grid.
mo_info : dict
Contains information of the selected molecular orbitals and has following Members:
:mo: - List of molecular orbital labels.
:mo_ii: - List of molecular orbital indices.
:mo_spec: - Selected elements of mo_spec. See :ref:`Central Variables` for details.
:mo_in_file: - List of molecular orbital labels within the fid_mo_list file.
:sym_select: - If True, symmetry labels have been used.
'''
mo_info = mo_select(qc.mo_spec, fid_mo_list, strict=True)
qc_select = qc.todict()
qc_select['mo_spec'] = mo_info['mo_spec']
slice_length = options.slice_length if slice_length is None else slice_length
numproc = options.numproc if numproc is None else numproc
# Calculate the AOs and MOs
mo_list = core.rho_compute(qc_select,
calc_mo=True,
drv=drv,
slice_length=slice_length,
numproc=numproc)
if otype is None:
return mo_list, mo_info
if ofid is None:
ofid = '%s_MO' % (options.outputname)
if not options.no_output:
if 'h5' in otype:
output.main_output(mo_list,qc.geo_info,qc.geo_spec,data_id='MO',
outputname=ofid,
mo_spec=qc_select['mo_spec'],drv=drv,is_mo_output=True)
# Create Output
cube_files = []
for i,j in enumerate(qc_select['mo_spec']):
outputname = '%s_%s' % (ofid,mo_info['mo'][i])
comments = ('%s,Occ=%.1f,E=%+.4f' % (mo_info['mo'][i],
j['occ_num'],
j['energy']))
index = numpy.index_exp[:,i] if drv is not None else i
output_written = output.main_output(mo_list[index],
qc.geo_info,qc.geo_spec,
outputname=outputname,
comments=comments,
otype=otype,omit=['h5','vmd','mayavi'],
drv=drv)
for i in output_written:
if i.endswith('.cb'):
cube_files.append(i)
if 'vmd' in otype and cube_files != []:
display('\nCreating VMD network file...' +
'\n\t%(o)s.vmd' % {'o': ofid})
output.vmd_network_creator(ofid,cube_files=cube_files)
if 'mayavi' in otype:
datalabels = ['MO %(sym)s, Occ=%(occ_num).2f, E=%(energy)+.4f E_h' %
i for i in qc_select['mo_spec']]
if drv is not None:
tmp = []
for i in drv:
for j in datalabels:
tmp.append('d/d%s of %s' % (i,j))
datalabels = tmp
data = mo_list.reshape((-1,) + grid.get_shape())
output.main_output(data,qc.geo_info,qc.geo_spec,
otype='mayavi',datalabels=datalabels)
return mo_list, mo_info
def mo_set(qc, fid_mo_list, drv=None, laplacian=None,
otype=None, ofid=None, return_all=True,
numproc=None, slice_length=None):
'''Calculates and saves the density or the derivative thereof
using selected molecular orbitals.
**Parameters:**
qc.geo_spec, qc.geo_info, qc.ao_spec, qc.mo_spec :
See :ref:`Central Variables` for details.
fid_mo_list : str
Specifies the filename of the molecular orbitals list or list of molecular
orbital labels (cf. :mod:`orbkit.read.mo_select` 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', 0, 1, 2}, optional
If not None, a derivative calculation of the atomic orbitals
is requested.
return_all : bool
If False, no data will be returned.
numproc : int, optional
Specifies number of subprocesses for multiprocessing.
If None, uses the value from :mod:`options.numproc`.
slice_length : int, optional
Specifies the number of points per subprocess.
If None, uses the value from :mod:`options.slice_length`.
**Returns:**
datasets : numpy.ndarray, shape=((NSET,) + N)
Contains the NSET molecular orbital sets on a grid.
delta_datasets : numpy.ndarray, shape=((NSET,NDRV) + N)
Contains the NDRV NSET molecular orbital set on a grid. This is only
present if derivatives are requested.
mo_info : dict
Contains information of the selected molecular orbitals and has following Members:
:mo: - List of molecular orbital labels.
:mo_ii: - List of molecular orbital indices.
:mo_spec: - Selected elements of mo_spec. See :ref:`Central Variables` for details.
:mo_in_file: - List of molecular orbital labels within the fid_mo_list file.
:sym_select: - If True, symmetry labels have been used.
'''
mo_info = mo_select(qc.mo_spec, fid_mo_list, strict=False)
qc_select = qc.todict()
drv = options.drv if drv is None else drv
laplacian = options.laplacian if laplacian is None else laplacian
slice_length = options.slice_length if slice_length is None else slice_length
numproc = options.numproc if numproc is None else numproc
if ofid is None:
ofid = options.outputname
if 'h5' in otype and os.path.exists('%s.h5' % ofid):
raise IOError('%s.h5 already exists!' % ofid)
datasets = []
delta_datasets = []
cube_files = []
for i_file,j_file in enumerate(mo_info['mo_in_file']):
display('Starting with the %d. element of the molecular orbital list (%s)...\n\t' %
(i_file+1,fid_mo_list) + str(j_file) +
'\n\t(Only regarding existing and occupied mos.)\n')
qc_select['mo_spec'] = []
for i_mo,j_mo in enumerate(mo_info['mo']):
if j_mo in j_file:
if mo_info['sym_select']:
ii_mo = numpy.argwhere(mo_info['mo_ii'] == j_mo)
else:
ii_mo = i_mo
qc_select['mo_spec'].append(mo_info['mo_spec'][int(ii_mo)])
data = core.rho_compute(qc_select,
drv=drv,
laplacian=laplacian,
slice_length=slice_length,
numproc=numproc)
datasets.append(data)
if drv is None:
rho = data
elif laplacian:
rho, delta_rho, laplacian_rho = data
delta_datasets.extend(delta_rho)
delta_datasets.append(laplacian_rho)
else:
rho, delta_rho = data
delta_datasets.append(delta_rho)
if options.z_reduced_density:
if grid.is_vector:
display('\nSo far, reducing the density is not supported for vector grids.\n')
elif drv is not None:
display('\nSo far, reducing the density is not supported for the derivative of the density.\n')
else:
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')
if not options.no_output:
if 'h5' in otype:
display('Saving to Hierarchical Data Format file (HDF5)...')
group = '/mo_set:%03d' % (i_file+1)
display('\n\t%s.h5 in the group "%s"' % (ofid,group))
output.HDF5_creator(rho,ofid,qc.geo_info,qc.geo_spec,data_id='rho',
mode='w',group=group,mo_spec=qc_select['mo_spec'])
if drv is not None:
for i,j in enumerate(drv):
data_id = 'rho_d%s' % j
output.HDF5_creator(delta_rho[i],ofid,qc.geo_info,qc.geo_spec,
data_id=data_id,data_only=True,mode='a',
group=group,mo_spec=qc_select['mo_spec'])
if laplacian:
data_id = 'rho_laplacian'
output.HDF5_creator(laplacian_rho,ofid,qc.geo_info,qc.geo_spec,
data_id=data_id,data_only=True,mode='a',
group=group,mo_spec=qc_select['mo_spec'])
fid = '%s_%03d' % (ofid, i_file+1)
cube_files.append('%s.cb' % fid)
comments = ('mo_set:'+','.join(j_file))
output.main_output(rho,qc.geo_info,qc.geo_spec,outputname=fid,
otype=otype,omit=['h5','vmd','mayavi'],
comments=comments)
if drv is not None:
for i,j in enumerate(drv):
fid = '%s_%03d_d%s' % (ofid, i_file+1, j)
cube_files.append('%s.cb' % fid)
comments = ('d%s_of_mo_set:' % j + ','.join(j_file))
output.main_output(delta_rho[i],qc.geo_info,qc.geo_spec,outputname=fid,
otype=otype,omit=['h5','vmd','mayavi'],
comments=comments)
if laplacian:
fid = '%s_%03d_laplacian' % (ofid, i_file+1)
cube_files.append('%s.cb' % fid)
comments = ('laplacian_of_mo_set:' + ','.join(j_file))
output.main_output(laplacian_rho,qc.geo_info,qc.geo_spec,outputname=fid,
otype=otype,omit=['h5','vmd','mayavi'],
comments=comments)
if 'vmd' in otype and cube_files != []:
display('\nCreating VMD network file...' +
'\n\t%(o)s.vmd' % {'o': ofid})
output.vmd_network_creator(ofid,cube_files=cube_files)
datasets = numpy.array(datasets)
if drv is None:
if 'mayavi' in otype:
output.main_output(datasets,qc.geo_info,qc.geo_spec,
otype='mayavi',datalabels=mo_info['mo_in_file'])
return datasets, mo_info
else:
delta_datasets = numpy.array(delta_datasets)
if 'mayavi' in otype:
datalabels = []
for i in mo_info['mo_in_file']:
datalabels.extend(['d/d%s of %s' % (j,i) for j in drv])
if laplacian:
datalabels.append('laplacian of %s' % i)
output.main_output(delta_datasets.reshape((-1,) + grid.get_shape()),
qc.geo_info,qc.geo_spec,otype='mayavi',datalabels=datalabels)
return datasets, delta_datasets, mo_info
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))])
# Run orbkit
rho,delta_rho = core.rho_compute(qc,drv=['x','y','z'],numproc=4)
# Compute the reduced density gradient
from numpy import sqrt,pi
s = (1./(2*(3*pi**2)**(1/3.)) * sqrt((delta_rho**2).sum(axis=0))/(rho**(4/3.)))
# Apply a density cutoff, i.e., consider only values for rho < 0.05 a.u.
s[rho>0.05] = 1e3
# Write a cube file and vmd script for the reduced density gradient
output.main_output(s,
qc.geo_info, # atomic information
qc.geo_spec, # atomic coordinates
outputname='reduced_drho',
otype=['cb','vmd'],
iso=(-0.5,0.5) # isocontour value of s = 0.5 a.u.
)
'''
Classify the interaction types
using the second derivatives of the density
("the three eigenvalues of the electronic Hessian matrix")
'''
# Compute the second derivatives of the density
rho,delta2_rho = core.rho_compute(qc,drv=['xx','yy','zz'],numproc=4)
# Sort the three components of the derivatives
# The sign of the second value determines, if the interaction is bonding (negative)
# non-bonding (positive)
of the gross atomic density.
Hint: Use the VMD script file (ch2o.vmd) for depicting the results.
'''
from orbkit import read, grid, extras, output, atomic_populations, display
# Open molden file and read parameters
qc = read.main_read('ch2o.molden', itype='molden')
# Perform a Mulliken population analysis and write the output to a PDB file
pop = atomic_populations.mulliken(qc)
output.pdb_creator(qc.geo_info,
qc.geo_spec,
filename='ch2o',
charges=pop['charge'])
# Initialize the grid
display.display('\nSetting up the grid...')
grid.adjust_to_geo(qc, extend=5.0, step=0.1)
grid.grid_init()
display.display(grid.get_grid())
# Compute and save the gross atomic density of the C atom
rho_atom = extras.gross_atomic_density(1, qc)
output.main_output(rho_atom[0],
qc.geo_info,
qc.geo_spec,
outputname='ch2o',
otype='cb')
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
if 'native' in options.otype:
output.main_output(qc, outputname=options.outputname, otype='native', ftype=options.niotype)
options.otype.remove('native')
if not len(options.otype):
t.append(time.time()) # Final time
good_bye_message(t)
return
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:
rho_atom = extras.gross_atomic_density(options.gross_atomic_density,qc,
drv=options.drv)
if not options.no_output:
output_written = output.main_output(rho_atom,
qc,
outputname=options.outputname,
otype=options.otype)
t.append(time.time())
good_bye_message(t)
return rho_atom
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
t.append(time.time()) # A new time step
# Generate the output requested
if not options.no_output:
if not (options.drv is not None or options.laplacian):
plt_data = rho
datalabels = 'rho'
else:
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,outputname=options.outputname,
otype=options.otype,datalabels=datalabels)
t.append(time.time()) # Final time
good_bye_message(t)
# 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
'''
Partial Charges and Gross Atomic Density
Example for the orbkit's non-grid based capabilities and for the computation
of the gross atomic density.
Hint: Use the VMD script file (ch2o.vmd) for depicting the results.
'''
from orbkit import read, grid, extras, output, atomic_populations, display
# Open molden file and read parameters
qc = read.main_read('ch2o.molden', itype='molden')
# Perform a Mulliken population analysis and write the output to a PDB file
pop = atomic_populations.mulliken(qc)
output.pdb_creator(qc.geo_info,
qc.geo_spec,
filename='ch2o',
charges=pop['charge'])
# Initialize the grid
display.display('Setting up the grid...')
grid.adjust_to_geo(qc, extend=5.0, step=0.1)
grid.grid_init()
display.display(grid.get_grid())
# Compute and save the gross atomic density of the C atom
rho_atom = extras.gross_atomic_density(1, qc)
output.main_output(rho_atom[0], qc, outputname='ch2o', otype='cb')
display.display(grid.get_grid())
# Run orbkit
rho,delta_rho = core.rho_compute(qc,drv=['x','y','z'],numproc=4)
# Compute the reduced density gradient
from numpy import sqrt,pi
s = (1./(2*(3*pi**2)**(1/3.)) * sqrt((delta_rho**2).sum(axis=0))/(rho**(4/3.)))
# Apply a density cutoff, i.e., consider only values for rho < 0.05 a.u.
s[rho>0.05] = 1e3
# Write a cube file and vmd script for the reduced density gradient
output.main_output(s,
qc, # atomic information
outputname='reduced_drho',
otype=['cb','vmd'],
iso=(-0.5,0.5) # isocontour value of s = 0.5 a.u.
)
'''
Classify the interaction types
using the second derivatives of the density
("the three eigenvalues of the electronic Hessian matrix")
'''
# Compute the second derivatives of the density
rho,delta2_rho = core.rho_compute(qc,drv=['xx','yy','zz'],numproc=4)
# Sort the three components of the derivatives
# The sign of the second value determines, if the interaction is bonding (negative)
# non-bonding (positive)
delta2_rho.sort(axis=0)
