"""
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 ase.io import ParseError
from ase.io.formats import string2index
from ase.io.utils 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 parse_poscar_scaling_factor(line: str) -> np.ndarray:
"""Parse scaling factor(s) in the second line in POSCAR/CONTCAR.
This can also be one negative number or three positive numbers.
https://www.vasp.at/wiki/index.php/POSCAR#Full_format_specification
"""
scale = []
for _ in line.split()[:3]:
try:
scale.append(float(_))
except ValueError:
break
if len(scale) not in {1, 3}:
raise RuntimeError('The number of scaling factors must be 1 or 3.')
if len(scale) == 3 and any(_ < 0.0 for _ in scale):
raise RuntimeError('All three scaling factors must be positive.')
return np.array(scale)
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
bzip2.
"""
fpath = Path(fname)
atomtypes = []
atomtypes_alt = []
if fpath.suffix == '.gz':
import gzip
opener = gzip.open
elif fpath.suffix == '.bz2':
import bz2
opener = bz2.BZ2File
else:
opener = open
with opener(fpath) as fd:
for line in fd:
if 'TITEL' in line:
atomtypes.append(line.split()[3].split('_')[0].split('.')[0])
elif 'POTCAR:' in line:
atomtypes_alt.append(
line.split()[2].split('_')[0].split('.')[0])
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
# of POSCAR/CONTCAR.
fnames = [posfpath.with_name('POTCAR'),
posfpath.with_name('OUTCAR')]
# Try the same but with compressed files
fsc = []
for fnpath in fnames:
fsc.append(fnpath.parent / (fnpath.name + '.gz'))
fsc.append(fnpath.parent / (fnpath.name + '.bz2'))
for f in fsc:
fnames.append(f)
# 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():
tried.append(fn)
at = get_atomtypes(fn)
if len(at) == numsyms:
return at
raise ParseError('Could not determine chemical symbols. Tried files ' +
str(tried))
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]:
atomtypes.append(s)
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 ase.data 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()
scale = parse_poscar_scaling_factor(fd.readline())
# 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 # This works for both one and three scaling factors.
# 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(fd.name, numsyms)
else:
try:
for atype in atomtypes[:numsyms]:
if atype not in chemical_symbols:
raise KeyError
except KeyError:
atomtypes = atomtypes_outpot(fd.name, 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 formats.py:read
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:`ase.io.read` 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 ase.io
>>> ase.io.write("out.traj", ase.io.read("vasprun.xml", index=":"))
"""
import xml.etree.ElementTree as ET
from collections import OrderedDict
from ase.calculators.singlepoint import (
SinglePointDFTCalculator,
SinglePointKPoint,
)
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(i, flags, cell_init))
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
)
atoms.calc.name = '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