def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.output, 'output')
# check if the group is already present (and not empty) in the output file
if check_output(fn_h5, grp_name, args.overwrite):
return
# Load the system
sys = System.from_file(args.wfn)
# Define a list of optional arguments for the WPartClass:
WPartClass = wpart_schemes[args.scheme]
kwargs = dict((key, val) for key, val in vars(args).iteritems() if key in WPartClass.options)
# Load the proatomdb
if args.atoms is not None:
proatomdb = ProAtomDB.from_file(args.atoms)
proatomdb.normalize()
kwargs['proatomdb'] = proatomdb
else:
proatomdb = None
# Run the partitioning
agspec = AtomicGridSpec(args.grid)
molgrid = BeckeMolGrid(sys, agspec, mode='only')
sys.update_grid(molgrid) # for the grid to be written to the output
wpart = wpart_schemes[args.scheme](sys, molgrid, **kwargs)
names = wpart.do_all()
write_part_output(fn_h5, grp_name, wpart, names, args)
def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.output, 'output')
# check if the group is already present (and not empty) in the output file
if check_output(fn_h5, grp_name, args.overwrite):
return
# Load the system
sys = System.from_file(args.cube)
ugrid = sys.grid
if not isinstance(ugrid, UniformGrid):
raise TypeError(
'The specified file does not contain data on a rectangular grid.')
ugrid.pbc[:] = parse_pbc(args.pbc)
moldens = sys.extra['cube_data']
# Reduce the grid if required
if args.stride > 1 or args.chop > 0:
moldens, ugrid = reduce_data(moldens, ugrid, args.stride, args.chop)
# Load the proatomdb and make pro-atoms more compact if that is requested
proatomdb = ProAtomDB.from_file(args.atoms)
if args.compact is not None:
proatomdb.compact(args.compact)
proatomdb.normalize()
# Select the partitioning scheme
CPartClass = cpart_schemes[args.scheme]
# List of element numbers for which weight corrections are needed:
wcor_numbers = list(iter_elements(args.wcor))
# Run the partitioning
kwargs = dict((key, val) for key, val in vars(args).iteritems()
if key in CPartClass.options)
cpart = cpart_schemes[args.scheme](sys, ugrid, True, moldens, proatomdb,
wcor_numbers, args.wcor_rcut_max,
args.wcor_rcond, **kwargs)
names = cpart.do_all()
# Do a symmetry analysis if requested.
if args.symmetry is not None:
sys_sym = System.from_file(args.symmetry)
sym = sys_sym.extra.get('symmetry')
if sym is None:
raise ValueError('No symmetry information found in %s.' %
args.symmetry)
sys_results = dict((name, cpart[name]) for name in names)
sym_results = symmetry_analysis(sys, sym, sys_results)
cpart.cache.dump('symmetry', sym_results)
names.append('symmetry')
sys.extra['symmetry'] = sym
write_part_output(fn_h5, grp_name, cpart, names, args)
def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.output, 'output')
# check if the group is already present (and not empty) in the output file
if check_output(fn_h5, grp_name, args.overwrite):
return
# Load the system
sys = System.from_file(args.cube)
ugrid = sys.grid
if not isinstance(ugrid, UniformGrid):
raise TypeError('The specified file does not contain data on a rectangular grid.')
ugrid.pbc[:] = parse_pbc(args.pbc)
moldens = sys.extra['cube_data']
# Reduce the grid if required
if args.stride > 1 or args.chop > 0:
moldens, ugrid = reduce_data(moldens, ugrid, args.stride, args.chop)
# Load the proatomdb and make pro-atoms more compact if that is requested
proatomdb = ProAtomDB.from_file(args.atoms)
if args.compact is not None:
proatomdb.compact(args.compact)
proatomdb.normalize()
# Select the partitioning scheme
CPartClass = cpart_schemes[args.scheme]
# List of element numbers for which weight corrections are needed:
wcor_numbers = list(iter_elements(args.wcor))
# Run the partitioning
kwargs = dict((key, val) for key, val in vars(args).iteritems() if key in CPartClass.options)
cpart = cpart_schemes[args.scheme](
sys, ugrid, True, moldens, proatomdb, wcor_numbers,
args.wcor_rcut_max, args.wcor_rcond, **kwargs)
names = cpart.do_all()
# Do a symmetry analysis if requested.
if args.symmetry is not None:
sys_sym = System.from_file(args.symmetry)
sym = sys_sym.extra.get('symmetry')
if sym is None:
raise ValueError('No symmetry information found in %s.' % args.symmetry)
sys_results = dict((name, cpart[name]) for name in names)
sym_results = symmetry_analysis(sys, sym, sys_results)
cpart.cache.dump('symmetry', sym_results)
names.append('symmetry')
sys.extra['symmetry'] = sym
write_part_output(fn_h5, grp_name, cpart, names, args)
def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.output, 'output')
# check if the group is already present (and not empty) in the output file
if check_output(fn_h5, grp_name, args.overwrite):
return
# Load the system
mol = IOData.from_file(args.wfn)
# Define a list of optional arguments for the WPartClass:
WPartClass = wpart_schemes[args.scheme]
kwargs = dict((key, val) for key, val in vars(args).iteritems()
if key in WPartClass.options)
# Load the proatomdb
if args.atoms is not None:
proatomdb = ProAtomDB.from_file(args.atoms)
proatomdb.normalize()
kwargs['proatomdb'] = proatomdb
else:
proatomdb = None
# Run the partitioning
agspec = AtomicGridSpec(args.grid)
grid = BeckeMolGrid(mol.coordinates,
mol.numbers,
mol.pseudo_numbers,
agspec,
mode='only')
dm_full = mol.get_dm_full()
moldens = mol.obasis.compute_grid_density_dm(dm_full,
grid.points,
epsilon=args.epsilon)
dm_spin = mol.get_dm_spin()
if dm_spin is not None:
kwargs['spindens'] = mol.obasis.compute_grid_density_dm(
dm_spin, grid.points, epsilon=args.epsilon)
wpart = wpart_schemes[args.scheme](mol.coordinates, mol.numbers,
mol.pseudo_numbers, grid, moldens,
**kwargs)
keys = wpart.do_all()
if args.slow:
# ugly hack for the slow analysis involving the AIM overlap operators.
wpart_slow_analysis(wpart, mol)
keys = list(wpart.cache.iterkeys(tags='o'))
write_part_output(fn_h5, grp_name, wpart, keys, args)
def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.output, 'output')
# check if the group is already present (and not empty) in the output file
if check_output(fn_h5, grp_name, args.overwrite):
return
# Load the system
mol = IOData.from_file(args.wfn)
# Define a list of optional arguments for the WPartClass:
WPartClass = wpart_schemes[args.scheme]
kwargs = dict((key, val) for key, val in vars(args).iteritems() if key in WPartClass.options)
# Load the proatomdb
if args.atoms is not None:
proatomdb = ProAtomDB.from_file(args.atoms)
proatomdb.normalize()
kwargs['proatomdb'] = proatomdb
else:
proatomdb = None
# Run the partitioning
agspec = AtomicGridSpec(args.grid)
grid = BeckeMolGrid(mol.coordinates, mol.numbers, mol.pseudo_numbers, agspec, mode='only')
dm_full = mol.get_dm_full()
moldens = mol.obasis.compute_grid_density_dm(dm_full, grid.points, epsilon=args.epsilon)
dm_spin = mol.get_dm_spin()
if dm_spin is not None:
kwargs['spindens'] = mol.obasis.compute_grid_density_dm(dm_spin, grid.points, epsilon=args.epsilon)
wpart = wpart_schemes[args.scheme](mol.coordinates, mol.numbers, mol.pseudo_numbers,grid, moldens, **kwargs)
keys = wpart.do_all()
if args.slow:
# ugly hack for the slow analysis involving the AIM overlap operators.
wpart_slow_analysis(wpart, mol)
keys = list(wpart.cache.iterkeys(tags='o'))
write_part_output(fn_h5, grp_name, wpart, keys, args)
def main():
args = parse_args()
fn_h5, grp_name = parse_h5(args.output, 'output')
# check if the group is already present (and not empty) in the output file
if check_output(fn_h5, grp_name, args.overwrite):
return
# Load the IOData
mol = IOData.from_file(args.cube)
ugrid = mol.grid
if not isinstance(ugrid, UniformGrid):
raise TypeError('The density cube file does not contain data on a rectangular grid.')
ugrid.pbc[:] = parse_pbc(args.pbc)
moldens = mol.cube_data
# Reduce the grid if required
if args.stride > 1 or args.chop > 0:
moldens, ugrid = reduce_data(moldens, ugrid, args.stride, args.chop)
# Load the spin density (optional)
if args.spindens is not None:
molspin = IOData.from_file(args.spindens)
if not isinstance(molspin.grid, UniformGrid):
raise TypeError('The spin cube file does not contain data on a rectangular grid.')
spindens = molspin.cube_data
if args.stride > 1 or args.chop > 0:
spindens = reduce_data(spindens, molspin.grid, args.stride, args.chop)[0]
if spindens.shape != moldens.shape:
raise TypeError('The shape of the spin cube does not match the shape of the density cube.')
else:
spindens = None
# Load the proatomdb and make pro-atoms more compact if that is requested
proatomdb = ProAtomDB.from_file(args.atoms)
if args.compact is not None:
proatomdb.compact(args.compact)
proatomdb.normalize()
# Select the partitioning scheme
CPartClass = cpart_schemes[args.scheme]
# List of element numbers for which weight corrections are needed:
if args.wcor == '0':
wcor_numbers = []
else:
wcor_numbers = list(iter_elements(args.wcor))
# Run the partitioning
kwargs = dict((key, val) for key, val in vars(args).iteritems() if key in CPartClass.options)
cpart = cpart_schemes[args.scheme](
mol.coordinates, mol.numbers, mol.pseudo_numbers, ugrid, moldens,
proatomdb, spindens=spindens, local=True, wcor_numbers=wcor_numbers,
wcor_rcut_max=args.wcor_rcut_max, wcor_rcond=args.wcor_rcond, **kwargs)
keys = cpart.do_all()
# Do a symmetry analysis if requested.
if args.symmetry is not None:
mol_sym = IOData.from_file(args.symmetry)
if not hasattr(mol_sym, 'symmetry'):
raise ValueError('No symmetry information found in %s.' % args.symmetry)
aim_results = dict((key, cpart[key]) for key in keys)
sym_results = symmetry_analysis(mol.coordinates, ugrid.get_cell(), mol_sym.symmetry, aim_results)
cpart.cache.dump('symmetry', sym_results)
keys.append('symmetry')
write_part_output(fn_h5, grp_name, cpart, keys, args)