def main():
args = parse_command_line_arguments()
poscar = Poscar()
poscar.read_from( args.poscar )
theta = math.pi * args.degrees / 180.0
poscar.cell.rotate( args.axis, theta )
poscar.output()
def main():
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
poscar.output_as_cif( args.symprec )
def main():
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from(args.poscar)
poscar.output_as_pimaim()
def main():
args = parse_command_line_arguments()
coordinate_types = { 'd' : 'Direct',
'direct' : 'Direct',
'c' : 'Cartesian',
'cartesian' : 'Cartesian' }
coordinate_type = coordinate_types[ args.coordinate_type ]
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
if args.scale:
poscar.cell.matrix *= poscar.scaling
poscar.scaling = 1.0
if args.supercell: # generate supercell
if args.group:
# check that if grouping is switched on, we are asking for a supercell that allows a "3D-chequerboard" pattern.
for (i,axis) in zip( args.supercell, range(3) ):
if i%2 == 1 and i > 1:
raise Exception( "odd supercell expansions != 1 are incompatible with automatic grouping" )
poscar = poscar.replicate( *args.supercell, group=args.group )
if args.bohr:
poscar = poscar.in_bohr()
# output to stdout
output_opts = { 'label' : args.label,
'numbered' : args.number_atoms,
'coordinates_only' : args.coordinates_only,
'selective': args.selective }
poscar.output( coordinate_type=coordinate_type, opts=output_opts )
def main():
args = parse_command_line_arguments()
poscar = Poscar()
poscar.read_from(args.poscar)
theta = math.pi * args.degrees / 180.0
poscar.cell.rotate(args.axis, theta)
poscar.output()
def main():
args = parse_command_line_arguments()
coordinate_types = {
'd': 'Direct',
'direct': 'Direct',
'c': 'Cartesian',
'cartesian': 'Cartesian'
}
coordinate_type = coordinate_types[args.coordinate_type]
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from(args.poscar)
if args.scale:
poscar.cell.matrix *= poscar.scaling
poscar.scaling = 1.0
if args.supercell: # generate supercell
if args.group:
# check that if grouping is switched on, we are asking for a supercell that allows a "3D-chequerboard" pattern.
for (i, axis) in zip(args.supercell, range(3)):
if i % 2 == 1 and i > 1:
raise Exception(
"odd supercell expansions != 1 are incompatible with automatic grouping"
)
poscar = poscar.replicate(*args.supercell, group=args.group)
if args.bohr:
poscar = poscar.in_bohr()
# output to stdout
output_opts = {
'label': args.label,
'numbered': args.number_atoms,
'coordinates_only': args.coordinates_only,
'selective': args.selective
}
poscar.output(coordinate_type=coordinate_type, opts=output_opts)
def main():
args = parse_command_line_arguments()
# initialise
poscar = Poscar() # this doesn't really need vasppy. Could just use pymatgen to read the POSCAR
# read POSCAR file
poscar.read_from( args.poscar )
structure = poscar.to_pymatgen_structure()
symmetry_analyzer = SpacegroupAnalyzer( structure, symprec = args.symprec )
print( symmetry_analyzer.get_space_group_symbol() )
def main():
args = parse_command_line_arguments()
# initialise
poscar = Poscar() # this doesn't really need vasppy. Could just use pymatgen to read the POSCAR
# read POSCAR file
poscar.read_from( args.poscar )
structure = poscar.to_pymatgen_structure()
symmetry_analyzer = SpacegroupAnalyzer( structure, symprec = args.symprec )
print( symmetry_analyzer.get_space_group_symbol() )
def main():
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
# construct new Poscar instance with sorted atom types
sorted_poscar = copy.deepcopy( poscar )
sorted_poscar.atoms = []
sorted_poscar.atom_numbers = []
coordinate_list = []
atoms = poscar.to_configuration().atoms
for label in args.labels:
if label in poscar.atoms:
sorted_poscar.atoms.append( label )
matched_atoms = [ atom for atom in atoms if atom.label == label ]
sorted_poscar.atom_numbers.append( len( matched_atoms ) )
coordinate_list.extend( [ atom.r for atom in matched_atoms ] )
else:
raise( ValueError( "'{}' atom label not found in {}".format( label, args.poscar ) ) )
sorted_poscar.coordinates = np.array( coordinate_list )
sorted_poscar.output( coordinate_type = poscar.coordinate_type )
def main():
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from(args.poscar)
# construct new Poscar instance with sorted atom types
sorted_poscar = copy.deepcopy(poscar)
sorted_poscar.atoms = []
sorted_poscar.atom_numbers = []
coordinate_list = []
atoms = poscar.to_configuration().atoms
for label in args.labels:
if label in poscar.atoms:
sorted_poscar.atoms.append(label)
matched_atoms = [atom for atom in atoms if atom.label == label]
sorted_poscar.atom_numbers.append(len(matched_atoms))
coordinate_list.extend([atom.r for atom in matched_atoms])
else:
raise (ValueError("'{}' atom label not found in {}".format(
label, args.poscar)))
sorted_poscar.coordinates = np.array(coordinate_list)
sorted_poscar.output(coordinate_type=poscar.coordinate_type)
parser.add_argument( '-b', '--bohr', action='store_true', help='assumes the input file is in Angstrom, and converts everything to bohr')
parser.add_argument( '-n', '--number-atoms', action='store_true', help='label coordinates with atom number' )
args = parser.parse_args()
return( args )
if __name__ == "__main__":
args = parse_command_line_arguments()
coordinate_types = { 'd' : 'Direct',
'direct' : 'Direct',
'c' : 'Cartesian',
'cartesian' : 'Cartesian' }
coordinate_type = coordinate_types[ args.coordinate_type ]
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
if args.supercell: # generate supercell
if args.group:
# check that if grouping is switched on, we are asking for a supercell that allows a "3D-chequerboard" pattern.
for (i,axis) in zip( args.supercell, range(3) ):
if i%2 == 1 and i > 1:
raise Exception( "odd supercell expansions != 1 are incompatible with automatic grouping" )
poscar = poscar.replicate( *args.supercell, group=args.group )
if args.bohr:
poscar = poscar.in_bohr()
# output to stdout
output_opts = { 'label' : args.label,
'numbered' : args.number_atoms,
'coordinates_only' : args.coordinates_only }
poscar.output( coordinate_type = coordinate_type, opts = output_opts )
parser.add_argument( '-n', '--number-atoms', action='store_true', help='label coordinates with atom number' )
parser.add_argument( '--scale', action='store_true', help='scale the lattice parameters by the scaling factor' )
args = parser.parse_args()
return( args )
if __name__ == "__main__":
args = parse_command_line_arguments()
coordinate_types = { 'd' : 'Direct',
'direct' : 'Direct',
'c' : 'Cartesian',
'cartesian' : 'Cartesian' }
coordinate_type = coordinate_types[ args.coordinate_type ]
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
if args.scale:
poscar.cell.matrix *= poscar.scaling
poscar.scaling = 1.0
if args.supercell: # generate supercell
if args.group:
# check that if grouping is switched on, we are asking for a supercell that allows a "3D-chequerboard" pattern.
for (i,axis) in zip( args.supercell, range(3) ):
if i%2 == 1 and i > 1:
raise Exception( "odd supercell expansions != 1 are incompatible with automatic grouping" )
poscar = poscar.replicate( *args.supercell, group=args.group )
if args.bohr:
poscar = poscar.in_bohr()
# output to stdout
output_opts = { 'label' : args.label,
'numbered' : args.number_atoms,