def main():
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
poscar.output_as_cif( args.symprec )
class PoscarTestCase( unittest.TestCase ):
def setUp( self ):
self.poscar = Poscar()
self.poscar.title = "Title"
self.poscar.scaling = 1.0
self.poscar.cell = Mock( spec=Cell )
self.poscar.cell.matrix = np.identity( 3 )
self.poscar.atoms = [ 'A' ]
self.poscar.atom_numbers = [ 1 ]
self.poscar.coordinate_type = 'Direct'
self.poscar.coordinates = np.array( [ [ 0.0, 0.0, 0.0 ] ] )
self.poscar.selective_dynamics = False
def test_stoichiometry( self ):
poscar = Poscar()
poscar.atoms = [ 'A', 'B', 'C' ]
poscar.atom_numbers = [ 1, 2, 3 ]
self.assertEqual( poscar.stoichiometry, Counter( { 'A': 1, 'B': 2, 'C': 3 } ) )
@patch('sys.stdout', new_callable=StringIO)
def test_output_header( self, mock_stdout ):
self.poscar.output_header()
expected_header_string = ("Title\n"
"1.0\n"
" 1.0000000000 0.0000000000 0.0000000000\n"
" 0.0000000000 1.0000000000 0.0000000000\n"
" 0.0000000000 0.0000000000 1.0000000000\n"
"A\n"
"1\n"
"Direct\n")
self.assertEqual( mock_stdout.getvalue(), expected_header_string )
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() # 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()
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 setUp( self ):
self.poscar = Poscar()
self.poscar.title = "Title"
self.poscar.scaling = 1.0
self.poscar.cell = Mock( spec=Cell )
self.poscar.cell.matrix = np.identity( 3 )
self.poscar.atoms = [ 'A' ]
self.poscar.atom_numbers = [ 1 ]
self.poscar.coordinate_type = 'Direct'
self.poscar.coordinates = np.array( [ [ 0.0, 0.0, 0.0 ] ] )
self.poscar.selective_dynamics = False
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 read_data( verbose=True ):
dir_list = find_vasp_calculations()
if not dir_list:
raise ValueError( 'Did not find any subdirectories containing vasprun.xml or vasprun.xml.gz files' )
data = []
for d in dir_list:
converged = True
try:
with warnings.catch_warnings(record=True) as w:
vasprun = read_vasprun( match_filename( d + 'vasprun.xml' ) )
for warning in w:
if isinstance( warning.message, UnconvergedVASPWarning ):
converged = False
else:
print( warning.message )
except:
continue
poscar = Poscar.from_file( d + 'POSCAR' )
data.append( [ poscar.scaling,
vasprun.final_structure.volume,
vasprun.final_energy,
converged ] )
column_titles = [ 'scaling', 'volume', 'energy', 'converged' ]
df = pd.DataFrame( data, columns=column_titles ).sort_values( by='scaling' )
df = df.reset_index( drop=True )
df['scaling_factor'] = df.volume / df.scaling**3
scaling_factor_round = 4
if verbose:
print( df.to_string(index=False) )
if len( set( df.scaling_factor.round( scaling_factor_round ) ) ) != 1:
raise ValueError( "POSCAR scaling factors and volumes are inconsistent" )
return df
def main():
filename = 'testout.rst'
restart_file = True
args = parse_command_line_arguments()
coordinates, velocities, dipoles, full_cell_matrix, cell_lengths = read_pimaim_restart( filename )
assert( sum( args.atom_numbers ) == len( coordinates ) )
poscar = Poscar()
full_cell_matrix = full_cell_matrix.transpose()
coordinates = get_cart_coords_from_pimaim_restart(coordinates, full_cell_matrix,cell_lengths)
poscar.cell = Cell( full_cell_matrix)
poscar.atoms = args.labels
poscar.atom_numbers = args.atom_numbers
poscar.coordinate_type = 'Cartesian'
poscar.coordinates = coordinates
poscar.output()
def main():
filename = 'testout.rst'
restart_file = True
args = parse_command_line_arguments()
coordinates, velocities, dipoles, full_cell_matrix = read_pimaim_restart(
filename)
assert (sum(args.atom_numbers) == len(coordinates))
poscar = Poscar()
poscar.cell = Cell(
full_cell_matrix) # TODO: possibly this needs transposing?
poscar.atoms = args.labels
poscar.atom_numbers = args.atom_numbers
poscar.coordinate_type = 'Cartesian'
poscar.coordinates = coordinates
poscar.output()
def main():
args = parse_command_line_arguments()
poscar = Poscar.from_file( args.poscar )
potcars = potcar_spec( args.potcar )
for i, ( species, potcar ) in enumerate( zip( poscar.atoms, potcars ), 1 ):
matching_potcar = potcar.startswith( species )
if not matching_potcar:
raise AttributeError( 'Species {} mismatch:\nPOSCAR contains {}\nPOTCAR contains {}'.format( i, species, potcar ) )
if args.ppset:
this_ppset = potcars[potcar]
if args.ppset != this_ppset:
raise AttributeError( 'Pseudopotential set mismatch: {}'.format( potcars.values() ) )
def __init__(self):
"""
Initialise a Xdatcar object.
Args:
None
Returns:
None
"""
self.poscar = []
self.poscar.append(Poscar())
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_pimaim()
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():
filename = 'testout.rst'
restart_file = True
args = parse_command_line_arguments()
coordinates, velocities, dipoles, full_cell_matrix, cell_lengths = read_pimaim_restart( filename )
assert( sum( args.atom_numbers ) == len( coordinates ) )
poscar = Poscar()
full_cell_matrix = full_cell_matrix.transpose()
coordinates = get_cart_coords_from_pimaim_restart(coordinates, full_cell_matrix,cell_lengths)
poscar.cell = Cell( full_cell_matrix)
poscar.atoms = args.labels
poscar.atom_numbers = args.atom_numbers
poscar.coordinate_type = 'Cartesian'
poscar.coordinates = coordinates
poscar.output()
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()
poscar = Poscar.from_file(args.poscar)
potcars = potcar_spec(args.potcar)
for i, (species, potcar) in enumerate(zip(poscar.atoms, potcars), 1):
matching_potcar = potcar.startswith(species)
if not matching_potcar:
raise AttributeError(
'Species {} mismatch:\nPOSCAR contains {}\nPOTCAR contains {}'.
format(i, species, potcar))
if args.ppset:
this_ppset = potcars[potcar]
if args.ppset != this_ppset:
raise AttributeError('Pseudopotential set mismatch: {}'.format(
potcars.values()))
def poscar_from_pimaim_restart(filename, atom_numbers, atom_labels):
number_of_atoms = sum(atom_numbers)
coordinates, velocities, dipoles, full_cell_matrix = read_restart_file(
filename, number_of_atoms)
poscar = Poscar()
poscar.cell = Cell(
full_cell_matrix) # TODO: possibly this needs transposing
poscar.atoms = atom_labels
poscar.atom_numbers = atom_numbers
poscar.coordinate_type = 'Direct'
poscar.coordinates = poscar.cell.cartesian_to_fractional_coordinates(
coordinates)
return poscar
def poscar_from_pimaim_restart(filename, atom_numbers, atom_labels):
number_of_atoms = sum(atom_numbers)
coordinates, velocities, dipoles, full_cell_matrix, cell_lengths = read_restart_file(
filename, number_of_atoms, cell_lengths)
poscar = Poscar()
full_cell_matrix = full_cell_matrix.transpose()
coordinates = get_cart_coords_from_pimaim_restart(coordinates,
full_cell_matrix,
cell_lengths)
poscar.cell = Cell(full_cell_matrix)
poscar.atoms = atom_labels
poscar.atom_numbers = atom_numbers
poscar.coordinate_type = 'Direct'
poscar.coordinates = poscar.cell.cartesian_to_fractional_coordinates(
coordinates)
return poscar
#! /usr/bin/env python3
from vasppy.poscar import Poscar
import math
import argparse
def parse_command_line_arguments():
parser = argparse.ArgumentParser( description='Rotates the cell lattice in VASP POSCAR files' )
parser.add_argument( 'poscar', help="filename of the VASP POSCAR to be processed" )
parser.add_argument( '-a', '--axis', nargs=3, type=float, help="vector for rotation axis", required=True )
parser.add_argument( '-d', '--degrees', type=int, help="rotation angle in degrees", required=True )
args = parser.parse_args()
return( args )
if __name__ == "__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()
# command line arguments
parser = argparse.ArgumentParser(
description='Reorders the atomic species in a VASP POSCAR file')
parser.add_argument('labels',
nargs='+',
help="atomic lables in the desired order")
parser.add_argument('poscar',
help="filename of the VASP POSCAR to be processed")
args = parser.parse_args()
return (args)
if __name__ == "__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:
parser.add_argument( '-g', '--group', help='group atoms within supercell', action='store_true' )
parser.add_argument( '-s', '--supercell', type=int, nargs=3, metavar=( 'h', 'k', 'l' ), help='construct supercell by replicating (h,k,l) times along [a b c]' )
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 }
#! /usr/bin/env python3
from vasppy.poscar import Poscar
import argparse
def parse_command_line_arguments():
# command line arguments
parser = argparse.ArgumentParser( description='Converts a VASP POSCAR file to the PIMAIM `restart.dat` format' )
parser.add_argument( 'poscar', help="filename of the VASP POSCAR to be processed" )
args = parser.parse_args()
return( args )
if __name__ == "__main__":
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
poscar.output_as_pimaim()
number_of_atomic_data_lines = next( index for index, d in enumerate( data_per_line[4:] ) if d == 1 )
number_of_atomic_data_types = sum( [ cr_dump_log, vel_dump_log, chg_dump_log ] )
number_of_atoms = int( number_of_atomic_data_lines / number_of_atomic_data_types )
# this assumes coordinates, velocities, and dipoles are all present.
# not sure what happens if atoms have qudrupoles, etc.
coordinates = lines_to_numpy_array( file_data[ 4 : 4 + number_of_atoms ] )
velocities = lines_to_numpy_array( file_data[ 4 + number_of_atoms : 4 + number_of_atoms * 2 ] )
dipoles = lines_to_numpy_array( file_data[ 4 + number_of_atoms * 2 : 4 + number_of_atoms * 3 ] )
cell_matrix = lines_to_numpy_array( file_data[ -6: -3 ] )
cell_lengths = lines_to_numpy_array( file_data[ -3: ] )
full_cell_matrix = cell_matrix * cell_lengths
# TODO! need to check this with a non-orthorhombic cell
return( coordinates, velocities, dipoles, full_cell_matrix )
if __name__ == '__main__':
filename = 'testout.rst'
restart_file = True
args = parse_command_line_arguments()
coordinates, velocities, dipoles, full_cell_matrix = read_pimaim_restart( filename )
assert( sum( args.atom_numbers ) == len( coordinates ) )
poscar = Poscar()
poscar.cell = Cell( full_cell_matrix ) # TODO: possibly this needs transposing?
poscar.atoms = args.labels
poscar.atom_numbers = args.atom_numbers
poscar.coordinate_type = 'Cartesian'
poscar.coordinates = coordinates
poscar.output()
#! /usr/bin/env python3
from vasppy.poscar import Poscar
import argparse
def parse_command_line_arguments():
# command line arguments
parser = argparse.ArgumentParser( description='Converts a VASP POSCAR file to the .xtl file format' )
parser.add_argument( 'poscar', help="filename of the VASP POSCAR to be processed" )
args = parser.parse_args()
return( args )
if __name__ == "__main__":
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from( args.poscar )
poscar.output_as_xtl()
parser.add_argument( '-s', '--supercell', type=int, nargs=3, metavar=( 'h', 'k', 'l' ), help='construct supercell by replicating (h,k,l) times along [a b c]' )
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' )
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
import argparse
def parse_command_line_arguments():
parser = argparse.ArgumentParser(
description='Rotates the cell lattice in VASP POSCAR files')
parser.add_argument('poscar',
help="filename of the VASP POSCAR to be processed")
parser.add_argument('-a',
'--axis',
nargs=3,
type=float,
help="vector for rotation axis",
required=True)
parser.add_argument('-d',
'--degrees',
type=int,
help="rotation angle in degrees",
required=True)
args = parser.parse_args()
return (args)
if __name__ == "__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()
import argparse
import copy
import numpy as np
def parse_command_line_arguments():
# command line arguments
parser = argparse.ArgumentParser( description='Reorders the atomic species in a VASP POSCAR file' )
parser.add_argument( 'labels', nargs='+', help="atomic lables in the desired order" )
parser.add_argument( 'poscar', help="filename of the VASP POSCAR to be processed" )
args = parser.parse_args()
return( args )
if __name__ == "__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:
def test_stoichiometry( self ):
poscar = Poscar()
poscar.atoms = [ 'A', 'B', 'C' ]
poscar.atom_numbers = [ 1, 2, 3 ]
self.assertEqual( poscar.stoichiometry, Counter( { 'A': 1, 'B': 2, 'C': 3 } ) )
#! /usr/bin/env python3
from vasppy.poscar import Poscar
import argparse
def parse_command_line_arguments():
# command line arguments
parser = argparse.ArgumentParser(
description='Converts a VASP POSCAR file to the .xtl file format')
parser.add_argument('poscar',
help="filename of the VASP POSCAR to be processed")
parser.add_argument(
'-s',
'--symprec',
type=float,
help="Symmetry precision for a symmetrised .cif output")
args = parser.parse_args()
return (args)
if __name__ == "__main__":
args = parse_command_line_arguments()
# initialise
poscar = Poscar()
# read POSCAR file
poscar.read_from(args.poscar)
poscar.output_as_cif(args.symprec)