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 cost function from the HDF5 file
cost, used_volume = load_cost(args.cost)
# Find the optimal charges
results = {}
results['x'] = cost.solve(args.qtot, args.ridge)
results['charges'] = results['x'][:cost.natom]
# Related properties
results['cost'] = cost.value(results['x'])
if results['cost'] < 0:
results['rmsd'] = 0.0
else:
results['rmsd'] = (results['cost'] / used_volume)**0.5
# Worst case stuff
results['cost_worst'] = cost.worst(0.0)
if results['cost_worst'] < 0:
results['rmsd_worst'] = 0.0
else:
results['rmsd_worst'] = (results['cost_worst'] / used_volume)**0.5
# Write some things on screen
if log.do_medium:
log('Important parameters:')
log.hline()
log('RMSD charges: %10.5e' % np.sqrt(
(results['charges']**2).mean()))
log('RMSD ESP: %10.5e' % results['rmsd'])
log('Worst RMSD ESP: %10.5e' % results['rmsd_worst'])
log.hline()
# Perform a symmetry analysis if requested
if args.symmetry is not None:
mol_pot = IOData.from_file(args.symmetry[0])
mol_sym = IOData.from_file(args.symmetry[1])
if not hasattr(mol_sym, 'symmetry'):
raise ValueError('No symmetry information found in %s.' %
args.symmetry[1])
aim_results = {'charges': results['charges']}
sym_results = symmetry_analysis(mol_pot.coordinates, mol_pot.cell,
mol_sym.symmetry, aim_results)
results['symmetry'] = sym_results
# Store the results in an HDF5 file
write_script_output(fn_h5, grp_name, results, 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 cost function from the HDF5 file
cost, used_volume = load_cost(args.cost)
# Find the optimal charges
results = {}
results['x'] = cost.solve(args.qtot, args.ridge)
results['charges'] = results['x'][:cost.natom]
# Related properties
results['cost'] = cost.value(results['x'])
if results['cost'] < 0:
results['rmsd'] = 0.0
else:
results['rmsd'] = (results['cost']/used_volume)**0.5
# Worst case stuff
results['cost_worst'] = cost.worst(0.0)
if results['cost_worst'] < 0:
results['rmsd_worst'] = 0.0
else:
results['rmsd_worst'] = (results['cost_worst']/used_volume)**0.5
# Write some things on screen
if log.do_medium:
log('Important parameters:')
log.hline()
log('RMSD charges: %10.5e' % np.sqrt((results['charges']**2).mean()))
log('RMSD ESP: %10.5e' % results['rmsd'])
log('Worst RMSD ESP: %10.5e' % results['rmsd_worst'])
log.hline()
# Perform a symmetry analysis if requested
if args.symmetry is not None:
sys = System.from_file(args.symmetry[0])
sys_sym = System.from_file(args.symmetry[1])
sym = sys_sym.extra.get('symmetry')
if sym is None:
raise ValueError('No symmetry information found in %s.' % args.symmetry[1])
sys_results = {'charges': results['charges']}
sym_results = symmetry_analysis(sys, sym, sys_results)
results['symmetry'] = sym_results
sys.extra['symmetry'] = sym
# Store the results in an HDF5 file
write_script_output(fn_h5, grp_name, results, 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 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)
