Source code for

This module contains functionality for reading and writing an ASE
Atoms object in VASP POSCAR format.

import re
from pathlib import Path
from typing import List, Optional, TextIO, Tuple

import numpy as np

from ase import Atoms
from ase.constraints import FixAtoms, FixedLine, FixedPlane, FixScaled
from import ParseError
from import string2index
from import ImageIterator
from ase.symbols import Symbols
from ase.utils import reader, writer

from .vasp_parsers import vasp_outcar_parsers as vop

__all__ = [
    'read_vasp', 'read_vasp_out', 'iread_vasp_out', 'read_vasp_xdatcar',
    'read_vasp_xml', 'write_vasp', 'write_vasp_xdatcar'

def get_atomtypes(fname):
    """Given a file name, get the atomic symbols.

    The function can get this information from OUTCAR and POTCAR
    format files.  The files can also be compressed with gzip or

    fpath = Path(fname)

    atomtypes = []
    atomtypes_alt = []
    if fpath.suffix == '.gz':
        import gzip
        opener =
    elif fpath.suffix == '.bz2':
        import bz2
        opener = bz2.BZ2File
        opener = open
    with opener(fpath) as fd:
        for line in fd:
            if 'TITEL' in line:
            elif 'POTCAR:' in line:

    if len(atomtypes) == 0 and len(atomtypes_alt) > 0:
        # old VASP doesn't echo TITEL, but all versions print out species
        # lines preceded by "POTCAR:", twice
        if len(atomtypes_alt) % 2 != 0:
            raise ParseError(
                f'Tried to get atom types from {len(atomtypes_alt)}'
                '"POTCAR": lines in OUTCAR, but expected an even number'
        atomtypes = atomtypes_alt[0:len(atomtypes_alt) // 2]

    return atomtypes

def atomtypes_outpot(posfname, numsyms):
    """Try to retrieve chemical symbols from OUTCAR or POTCAR

    If getting atomtypes from the first line in POSCAR/CONTCAR fails, it might
    be possible to find the data in OUTCAR or POTCAR, if these files exist.

    posfname -- The filename of the POSCAR/CONTCAR file we're trying to read

    numsyms -- The number of symbols we must find

    posfpath = Path(posfname)

    # Check files with exactly same path except POTCAR/OUTCAR instead
    fnames = [posfpath.with_name('POTCAR'),
    # Try the same but with compressed files
    fsc = []
    for fnpath in fnames:
        fsc.append(fnpath.parent / ( + '.gz'))
        fsc.append(fnpath.parent / ( + '.bz2'))
    for f in fsc:
    # Code used to try anything with POTCAR or OUTCAR in the name
    # but this is no longer supported

    tried = []
    for fn in fnames:
        if fn in posfpath.parent.iterdir():
            at = get_atomtypes(fn)
            if len(at) == numsyms:
                return at

    raise ParseError('Could not determine chemical symbols. Tried files ' +

def get_atomtypes_from_formula(formula):
    """Return atom types from chemical formula (optionally prepended
    with and underscore).
    from ase.symbols import string2symbols
    symbols = string2symbols(formula.split('_')[0])
    atomtypes = [symbols[0]]
    for s in symbols[1:]:
        if s != atomtypes[-1]:
    return atomtypes

[docs]@reader def read_vasp(filename='CONTCAR'): """Import POSCAR/CONTCAR type file. Reads unitcell, atom positions and constraints from the POSCAR/CONTCAR file and tries to read atom types from POSCAR/CONTCAR header, if this fails the atom types are read from OUTCAR or POTCAR file. """ from import chemical_symbols fd = filename # The first line is in principle a comment line, however in VASP # 4.x a common convention is to have it contain the atom symbols, # eg. "Ag Ge" in the same order as later in the file (and POTCAR # for the full vasp run). In the VASP 5.x format this information # is found on the fifth line. Thus we save the first line and use # it in case we later detect that we're reading a VASP 4.x format # file. line1 = fd.readline() # Scaling factor # This can also be one negative number or three positive numbers. # scale = np.array(fd.readline().split()[:3], dtype=float) if len(scale) not in [1, 3]: raise RuntimeError('The number of scaling factors must be 1 or 3.') if len(scale) == 3 and np.any(scale < 0.0): raise RuntimeError('All three scaling factors must be positive.') # Now the lattice vectors cell = np.array([fd.readline().split()[:3] for _ in range(3)], dtype=float) # Negative scaling factor corresponds to the cell volume. if scale[0] < 0.0: scale = np.cbrt(-1.0 * scale / np.linalg.det(cell)) cell *= scale # Number of atoms. Again this must be in the same order as # in the first line # or in the POTCAR or OUTCAR file atom_symbols = [] numofatoms = fd.readline().split() # Check whether we have a VASP 4.x or 5.x format file. If the # format is 5.x, use the fifth line to provide information about # the atomic symbols. vasp5 = False try: int(numofatoms[0]) except ValueError: vasp5 = True atomtypes = numofatoms numofatoms = fd.readline().split() # check for comments in numofatoms line and get rid of them if necessary commentcheck = np.array(['!' in s for s in numofatoms]) if commentcheck.any(): # only keep the elements up to the first including a '!': numofatoms = numofatoms[:np.arange(len(numofatoms))[commentcheck][0]] if not vasp5: # Split the comment line (first in the file) into words and # try to compose a list of chemical symbols from ase.formula import Formula atomtypes = [] for word in line1.split(): word_without_delims = re.sub(r"-|_|,|\.|=|[0-9]|^", "", word) if len(word_without_delims) < 1: continue try: atomtypes.extend(list(Formula(word_without_delims))) except ValueError: # print(atomtype, e, 'is comment') pass # Now the list of chemical symbols atomtypes must be formed. # For example: atomtypes = ['Pd', 'C', 'O'] numsyms = len(numofatoms) if len(atomtypes) < numsyms: # First line in POSCAR/CONTCAR didn't contain enough symbols. # Sometimes the first line in POSCAR/CONTCAR is of the form # "CoP3_In-3.pos". Check for this case and extract atom types if len(atomtypes) == 1 and '_' in atomtypes[0]: atomtypes = get_atomtypes_from_formula(atomtypes[0]) else: atomtypes = atomtypes_outpot(, numsyms) else: try: for atype in atomtypes[:numsyms]: if atype not in chemical_symbols: raise KeyError except KeyError: atomtypes = atomtypes_outpot(, numsyms) for i, num in enumerate(numofatoms): numofatoms[i] = int(num) atom_symbols.extend(numofatoms[i] * [atomtypes[i]]) # Check if Selective dynamics is switched on sdyn = fd.readline() selective_dynamics = sdyn[0].lower() == 's' # Check if atom coordinates are cartesian or direct if selective_dynamics: ac_type = fd.readline() else: ac_type = sdyn cartesian = ac_type[0].lower() in ['c', 'k'] tot_natoms = sum(numofatoms) atoms_pos = np.empty((tot_natoms, 3)) if selective_dynamics: selective_flags = np.empty((tot_natoms, 3), dtype=bool) for atom in range(tot_natoms): ac = fd.readline().split() atoms_pos[atom] = [float(_) for _ in ac[0:3]] if selective_dynamics: selective_flags[atom] = [_ == 'F' for _ in ac[3:6]] atoms = Atoms(symbols=atom_symbols, cell=cell, pbc=True) if cartesian: atoms_pos *= scale atoms.set_positions(atoms_pos) else: atoms.set_scaled_positions(atoms_pos) if selective_dynamics: set_constraints(atoms, selective_flags) return atoms
def set_constraints(atoms: Atoms, selective_flags: np.ndarray): """Set constraints based on selective_flags""" from ase.constraints import FixAtoms, FixConstraint, FixScaled constraints: List[FixConstraint] = [] indices = [] for ind, sflags in enumerate(selective_flags): if sflags.any() and not sflags.all(): constraints.append(FixScaled(ind, sflags, atoms.get_cell())) elif sflags.all(): indices.append(ind) if indices: constraints.append(FixAtoms(indices)) if constraints: atoms.set_constraint(constraints) def iread_vasp_out(filename, index=-1): """Import OUTCAR type file, as a generator.""" it = ImageIterator(vop.outcarchunks) return it(filename, index=index)
[docs]@reader def read_vasp_out(filename='OUTCAR', index=-1): """Import OUTCAR type file. Reads unitcell, atom positions, energies, and forces from the OUTCAR file and attempts to read constraints (if any) from CONTCAR/POSCAR, if present. """ # "filename" is actually a file-descriptor thanks to @reader g = iread_vasp_out(filename, index=index) # Code borrowed from if isinstance(index, (slice, str)): # Return list of atoms return list(g) else: # Return single atoms object return next(g)
[docs]@reader def read_vasp_xdatcar(filename='XDATCAR', index=-1): """Import XDATCAR file. Parameters ---------- index : int or slice or str Which frame(s) to read. The default is -1 (last frame). See :func:`` for details. Notes ----- Constraints ARE NOT stored in the XDATCAR, and as such, Atoms objects retrieved from the XDATCAR will not have constraints. """ fd = filename # @reader decorator ensures this is a file descriptor images = [] cell = np.eye(3) atomic_formula = '' while True: comment_line = fd.readline() if "Direct configuration=" not in comment_line: try: lattice_constant = float(fd.readline()) except Exception: # XXX: When would this happen? break xx = [float(x) for x in fd.readline().split()] yy = [float(y) for y in fd.readline().split()] zz = [float(z) for z in fd.readline().split()] cell = np.array([xx, yy, zz]) * lattice_constant symbols = fd.readline().split() numbers = [int(n) for n in fd.readline().split()] total = sum(numbers) atomic_formula = ''.join(f'{sym:s}{numbers[n]:d}' for n, sym in enumerate(symbols)) fd.readline() coords = [np.array(fd.readline().split(), float) for _ in range(total)] image = Atoms(atomic_formula, cell=cell, pbc=True) image.set_scaled_positions(np.array(coords)) images.append(image) if index is None: index = -1 if isinstance(index, str): index = string2index(index) return images[index]
def __get_xml_parameter(par): """An auxiliary function that enables convenient extraction of parameter values from a vasprun.xml file with proper type handling. """ def to_bool(b): if b == 'T': return True else: return False to_type = {'int': int, 'logical': to_bool, 'string': str, 'float': float} text = par.text if text is None: text = '' # Float parameters do not have a 'type' attrib var_type = to_type[par.attrib.get('type', 'float')] try: if par.tag == 'v': return list(map(var_type, text.split())) else: return var_type(text.strip()) except ValueError: # Vasp can sometimes write "*****" due to overflow return None
[docs]def read_vasp_xml(filename='vasprun.xml', index=-1): """Parse vasprun.xml file. Reads unit cell, atom positions, energies, forces, and constraints from vasprun.xml file Examples: >>> import >>>"out.traj","vasprun.xml", index=":")) """ import xml.etree.ElementTree as ET from collections import OrderedDict from ase.calculators.singlepoint import (SinglePointDFTCalculator, SinglePointKPoint) from ase.constraints import FixAtoms, FixScaled from ase.units import GPa tree = ET.iterparse(filename, events=['start', 'end']) atoms_init = None calculation = [] ibz_kpts = None kpt_weights = None parameters = OrderedDict() try: for event, elem in tree: if event == 'end': if elem.tag == 'kpoints': for subelem in elem.iter(tag='generation'): kpts_params = OrderedDict() parameters['kpoints_generation'] = kpts_params for par in subelem.iter(): if par.tag in ['v', 'i']: parname = par.attrib['name'].lower() kpts_params[parname] = __get_xml_parameter(par) kpts = elem.findall("varray[@name='kpointlist']/v") ibz_kpts = np.zeros((len(kpts), 3)) for i, kpt in enumerate(kpts): ibz_kpts[i] = [float(val) for val in kpt.text.split()] kpt_weights = elem.findall('varray[@name="weights"]/v') kpt_weights = [float(val.text) for val in kpt_weights] elif elem.tag == 'parameters': for par in elem.iter(): if par.tag in ['v', 'i']: parname = par.attrib['name'].lower() parameters[parname] = __get_xml_parameter(par) elif elem.tag == 'atominfo': species = [] for entry in elem.find("array[@name='atoms']/set"): species.append(entry[0].text.strip()) natoms = len(species) elif (elem.tag == 'structure' and elem.attrib.get('name') == 'initialpos'): cell_init = np.zeros((3, 3), dtype=float) for i, v in enumerate( elem.find("crystal/varray[@name='basis']")): cell_init[i] = np.array( [float(val) for val in v.text.split()]) scpos_init = np.zeros((natoms, 3), dtype=float) for i, v in enumerate( elem.find("varray[@name='positions']")): scpos_init[i] = np.array( [float(val) for val in v.text.split()]) constraints = [] fixed_indices = [] for i, entry in enumerate( elem.findall("varray[@name='selective']/v")): flags = (np.array( entry.text.split() == np.array(['F', 'F', 'F']))) if flags.all(): fixed_indices.append(i) elif flags.any(): constraints.append(FixScaled(cell_init, i, flags)) if fixed_indices: constraints.append(FixAtoms(fixed_indices)) atoms_init = Atoms(species, cell=cell_init, scaled_positions=scpos_init, constraint=constraints, pbc=True) elif elem.tag == 'dipole': dblock = elem.find('v[@name="dipole"]') if dblock is not None: dipole = np.array( [float(val) for val in dblock.text.split()]) elif event == 'start' and elem.tag == 'calculation': calculation.append(elem) except ET.ParseError as parse_error: if atoms_init is None: raise parse_error if calculation and calculation[-1].find("energy") is None: calculation = calculation[:-1] if not calculation: yield atoms_init if calculation: if isinstance(index, int): steps = [calculation[index]] else: steps = calculation[index] else: steps = [] for step in steps: # Workaround for VASP bug, e_0_energy contains the wrong value # in calculation/energy, but calculation/scstep/energy does not # include classical VDW corrections. So, first calculate # e_0_energy - e_fr_energy from calculation/scstep/energy, then # apply that correction to e_fr_energy from calculation/energy. lastscf = step.findall('scstep/energy')[-1] dipoles = step.findall('scstep/dipole') if dipoles: lastdipole = dipoles[-1] else: lastdipole = None de = (float(lastscf.find('i[@name="e_0_energy"]').text) - float(lastscf.find('i[@name="e_fr_energy"]').text)) free_energy = float(step.find('energy/i[@name="e_fr_energy"]').text) energy = free_energy + de cell = np.zeros((3, 3), dtype=float) for i, vector in enumerate( step.find('structure/crystal/varray[@name="basis"]')): cell[i] = np.array([float(val) for val in vector.text.split()]) scpos = np.zeros((natoms, 3), dtype=float) for i, vector in enumerate( step.find('structure/varray[@name="positions"]')): scpos[i] = np.array([float(val) for val in vector.text.split()]) forces = None fblocks = step.find('varray[@name="forces"]') if fblocks is not None: forces = np.zeros((natoms, 3), dtype=float) for i, vector in enumerate(fblocks): forces[i] = np.array( [float(val) for val in vector.text.split()]) stress = None sblocks = step.find('varray[@name="stress"]') if sblocks is not None: stress = np.zeros((3, 3), dtype=float) for i, vector in enumerate(sblocks): stress[i] = np.array( [float(val) for val in vector.text.split()]) stress *= -0.1 * GPa stress = stress.reshape(9)[[0, 4, 8, 5, 2, 1]] dipole = None if lastdipole is not None: dblock = lastdipole.find('v[@name="dipole"]') if dblock is not None: dipole = np.zeros((1, 3), dtype=float) dipole = np.array([float(val) for val in dblock.text.split()]) dblock = step.find('dipole/v[@name="dipole"]') if dblock is not None: dipole = np.zeros((1, 3), dtype=float) dipole = np.array([float(val) for val in dblock.text.split()]) efermi = step.find('dos/i[@name="efermi"]') if efermi is not None: efermi = float(efermi.text) kpoints = [] for ikpt in range(1, len(ibz_kpts) + 1): kblocks = step.findall( 'eigenvalues/array/set/set/set[@comment="kpoint %d"]' % ikpt) if kblocks is not None: for spin, kpoint in enumerate(kblocks): eigenvals = kpoint.findall('r') eps_n = np.zeros(len(eigenvals)) f_n = np.zeros(len(eigenvals)) for j, val in enumerate(eigenvals): val = val.text.split() eps_n[j] = float(val[0]) f_n[j] = float(val[1]) if len(kblocks) == 1: f_n *= 2 kpoints.append( SinglePointKPoint(kpt_weights[ikpt - 1], spin, ikpt, eps_n, f_n)) if len(kpoints) == 0: kpoints = None # DFPT properties # dielectric tensor dielectric_tensor = None sblocks = step.find('varray[@name="dielectric_dft"]') if sblocks is not None: dielectric_tensor = np.zeros((3, 3), dtype=float) for ii, vector in enumerate(sblocks): dielectric_tensor[ii] = np.fromstring(vector.text, sep=' ') # Born effective charges born_charges = None fblocks = step.find('array[@name="born_charges"]') if fblocks is not None: born_charges = np.zeros((natoms, 3, 3), dtype=float) for ii, block in enumerate(fblocks[1:]): # 1. element = dimension for jj, vector in enumerate(block): born_charges[ii, jj] = np.fromstring(vector.text, sep=' ') atoms = atoms_init.copy() atoms.set_cell(cell) atoms.set_scaled_positions(scpos) atoms.calc = SinglePointDFTCalculator( atoms, energy=energy, forces=forces, stress=stress, free_energy=free_energy, ibzkpts=ibz_kpts, efermi=efermi, dipole=dipole, dielectric_tensor=dielectric_tensor, born_effective_charges=born_charges ) = 'vasp' atoms.calc.kpts = kpoints atoms.calc.parameters = parameters yield atoms
[docs]@writer def write_vasp_xdatcar(fd, images, label=None): """Write VASP MD trajectory (XDATCAR) file Only Vasp 5 format is supported (for consistency with read_vasp_xdatcar) Args: fd (str, fp): Output file images (iterable of Atoms): Atoms images to write. These must have consistent atom order and lattice vectors - this will not be checked. label (str): Text for first line of file. If empty, default to list of elements. """ images = iter(images) image = next(images) if not isinstance(image, Atoms): raise TypeError("images should be a sequence of Atoms objects.") symbol_count = _symbol_count_from_symbols(image.get_chemical_symbols()) if label is None: label = ' '.join([s for s, _ in symbol_count]) fd.write(label + '\n') # Not using lattice constants, set it to 1 fd.write(' 1\n') # Lattice vectors; use first image float_string = '{:11.6f}' for row_i in range(3): fd.write(' ') fd.write(' '.join(float_string.format(x) for x in image.cell[row_i])) fd.write('\n') fd.write(_symbol_count_string(symbol_count, vasp5=True)) _write_xdatcar_config(fd, image, index=1) for i, image in enumerate(images): # Index is off by 2: 1-indexed file vs 0-indexed Python; # and we already wrote the first block. _write_xdatcar_config(fd, image, i + 2)
def _write_xdatcar_config(fd, atoms, index): """Write a block of positions for XDATCAR file Args: fd (fd): writeable Python file descriptor atoms (ase.Atoms): Atoms to write index (int): configuration number written to block header """ fd.write(f"Direct configuration={index:6d}\n") float_string = '{:11.8f}' scaled_positions = atoms.get_scaled_positions() for row in scaled_positions: fd.write(' ') fd.write(' '.join([float_string.format(x) for x in row])) fd.write('\n') def _symbol_count_from_symbols(symbols: Symbols) -> List[Tuple[str, int]]: """Reduce list of chemical symbols into compact VASP notation Args: symbols (iterable of str) Returns: list of pairs [(el1, c1), (el2, c2), ...] Example: >>> s = Atoms('Ar3NeHe2ArNe').symbols >>> _symbols_count_from_symbols(s) [('Ar', 3), ('Ne', 1), ('He', 2), ('Ar', 1), ('Ne', 1)] """ sc = [] psym = str(symbols[0]) # we cast to str to appease mypy count = 0 for sym in symbols: if sym != psym: sc.append((psym, count)) psym = sym count = 1 else: count += 1 sc.append((psym, count)) return sc
[docs]@writer def write_vasp( fd: TextIO, atoms: Atoms, direct: bool = False, sort: bool = False, symbol_count: Optional[List[Tuple[str, int]]] = None, vasp5: bool = True, vasp6: bool = False, ignore_constraints: bool = False, potential_mapping: Optional[dict] = None ) -> None: """Method to write VASP position (POSCAR/CONTCAR) files. Writes label, scalefactor, unitcell, # of various kinds of atoms, positions in cartesian or scaled coordinates (Direct), and constraints to file. Cartesian coordinates is default and default label is the atomic species, e.g. 'C N H Cu'. Args: fd (TextIO): writeable Python file descriptor atoms (ase.Atoms): Atoms to write direct (bool): Write scaled coordinates instead of cartesian sort (bool): Sort the atomic indices alphabetically by element symbol_count (list of tuples of str and int, optional): Use the given combination of symbols and counts instead of automatically compute them vasp5 (bool): Write to the VASP 5+ format, where the symbols are written to file vasp6 (bool): Write symbols in VASP 6 format (which allows for potential type and hash) ignore_constraints (bool): Ignore all constraints on `atoms` potential_mapping (dict, optional): Map of symbols to potential file (and hash). Only works if `vasp6=True`. See `_symbol_string_count` Raises: RuntimeError: raised if any of these are true: 1. `atoms` is not a single `ase.Atoms` object. 2. The cell dimensionality is lower than 3 (0D-2D) 3. One FixedPlane normal is not parallel to a unit cell vector 4. One FixedLine direction is not parallel to a unit cell vector """ if isinstance(atoms, (list, tuple)): if len(atoms) > 1: raise RuntimeError( 'Only one atomic structure can be saved to VASP ' 'POSCAR/CONTCAR. Several were given.' ) else: atoms = atoms[0] # Check lattice vectors are finite if atoms.cell.rank < 3: raise RuntimeError( 'Lattice vectors must be finite and non-parallel. At least ' 'one lattice length or angle is zero.' ) # Write atomic positions in scaled or cartesian coordinates if direct: coord = atoms.get_scaled_positions(wrap=False) else: coord = atoms.positions # Convert ASE constraints to VASP POSCAR constraints constraints_present = atoms.constraints and not ignore_constraints if constraints_present: sflags = _handle_ase_constraints(atoms) # Conditionally sort ordering of `atoms` alphabetically by symbols if sort: ind = np.argsort(atoms.symbols) symbols = atoms.symbols[ind] coord = coord[ind] if constraints_present: sflags = sflags[ind] else: symbols = atoms.symbols # Set or create a list of (symbol, count) pairs sc = symbol_count or _symbol_count_from_symbols(symbols) # Write header as atomic species in `symbol_count` order label = ' '.join(f'{sym:2s}' for sym, _ in sc) fd.write(label + '\n') # For simplicity, we write the unitcell in real coordinates, so the # scaling factor is always set to 1.0. fd.write(f'{1.0:19.16f}\n') for vec in atoms.cell: fd.write(' ' + ' '.join([f'{el:21.16f}' for el in vec]) + '\n') # Write version-dependent species-and-count section sc_str = _symbol_count_string(sc, vasp5, vasp6, potential_mapping) fd.write(sc_str) # Write POSCAR switches if constraints_present: fd.write('Selective dynamics\n') fd.write('Direct\n' if direct else 'Cartesian\n') # Write atomic positions and, if any, the cartesian constraints for iatom, atom in enumerate(coord): for dcoord in atom: fd.write(f' {dcoord:19.16f}') if constraints_present: flags = ['F' if flag else 'T' for flag in sflags[iatom]] fd.write(''.join([f'{f:>4s}' for f in flags])) fd.write('\n')
def _handle_ase_constraints(atoms: Atoms) -> np.ndarray: """Convert the ASE constraints on `atoms` to VASP constraints Returns a boolean array with dimensions Nx3, where N is the number of atoms. A value of `True` indicates that movement along the given lattice vector is disallowed for that atom. Args: atoms (Atoms) Returns: boolean numpy array with dimensions Nx3 Raises: RuntimeError: If there is a FixedPlane or FixedLine constraint, that is not parallel to a cell vector. """ sflags = np.zeros((len(atoms), 3), dtype=bool) for constr in atoms.constraints: if isinstance(constr, FixScaled): sflags[constr.index] = constr.mask elif isinstance(constr, FixAtoms): sflags[constr.index] = 3 * [True] elif isinstance(constr, FixedPlane): # Calculate if the plane normal is parallel to a cell vector mask = np.all( np.abs(np.cross(constr.dir, atoms.cell)) < 1e-5, axis=1 ) if sum(mask) != 1: raise RuntimeError( 'VASP requires that the direction of FixedPlane ' 'constraints is parallel with one of the cell axis' ) sflags[constr.index] = mask elif isinstance(constr, FixedLine): # Calculate if line is parallel to a cell vector mask = np.all( np.abs(np.cross(constr.dir, atoms.cell)) < 1e-5, axis=1 ) if sum(mask) != 1: raise RuntimeError( 'VASP requires that the direction of FixedLine ' 'constraints is parallel with one of the cell axis' ) sflags[constr.index] = ~mask return sflags def _symbol_count_string( symbol_count: List[Tuple[str, int]], vasp5: bool = True, vasp6: bool = True, symbol_mapping: Optional[dict] = None ) -> str: """Create the symbols-and-counts block for POSCAR or XDATCAR Args: symbol_count (list of 2-tuple): list of paired elements and counts vasp5 (bool): if False, omit symbols and only write counts vasp6 (bool): if True, write symbols in VASP 6 format (allows for potential type and hash) symbol_mapping (dict): mapping of symbols to VASP 6 symbols e.g. if sc is [(Sn, 4), (S, 6)] then write for vasp 5: Sn S 4 6 and for vasp 6 with mapping {'Sn': 'Sn_d_GW', 'S': 'S_GW/357d'}: Sn_d_GW S_GW/357d 4 6 """ symbol_mapping = symbol_mapping or {} out_str = ' ' # Allow for VASP 6 format, i.e., specifying the pseudopotential used if vasp6: out_str += ' '.join([ f"{symbol_mapping.get(s, s)[:14]:16s}" for s, _ in symbol_count ]) + "\n " out_str += ' '.join([f"{c:16d}" for _, c in symbol_count]) + '\n' return out_str # Write the species for VASP 5+ if vasp5: out_str += ' '.join([f"{s:3s}" for s, _ in symbol_count]) + "\n " # Write counts line out_str += ' '.join([f"{c:3d}" for _, c in symbol_count]) + '\n' return out_str