# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
from __future__ import division, unicode_literals, print_function
import abc
import re
import os
import glob
import shutil
import warnings
from itertools import chain
from copy import deepcopy
import six
import numpy as np
from monty.serialization import loadfn
from monty.io import zopen
from pymatgen.core.structure import Structure
from pymatgen.io.vasp.inputs import Incar, Poscar, Potcar, Kpoints
from pymatgen.io.vasp.outputs import Vasprun, Outcar
from monty.json import MSONable
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
from pymatgen.symmetry.bandstructure import HighSymmKpath
from pymatgen.analysis.structure_matcher import StructureMatcher
from pymatgen.core.sites import PeriodicSite
"""
This module defines the VaspInputSet abstract base class and a concrete
implementation for the parameters developed and tested by the core team
of pymatgen, including the Materials Virtual Lab, Materials Project and the MIT
high throughput project. The basic concept behind an input set is to specify
a scheme to generate a consistent set of VASP inputs from a structure
without further user intervention. This ensures comparability across
runs.
Read the following carefully before implementing new input sets:
1. 99% of what needs to be done can be done by specifying user_incar_settings
to override some of the defaults of various input sets. Unless there is an
extremely good reason to add a new set, DO NOT add one. E.g., if you want
to turn the hubbard U off, just set "LDAU": False as a user_incar_setting.
2. All derivative input sets should inherit from one of the usual MPRelaxSet or
MITRelaxSet, and proper superclass delegation should be used where possible.
In particular, you are not supposed to implement your own as_dict or
from_dict for derivative sets unless you know what you are doing.
Improper overriding the as_dict and from_dict protocols is the major
cause of implementation headaches. If you need an example, look at how the
MPStaticSet or MPNonSCFSets are constructed.
The above are recommendations. The following are UNBREAKABLE rules:
1. All input sets must take in a structure or list of structures as the first
argument.
2. user_incar_settings and user_kpoints_settings are absolute. Any new sets you
implement must obey this. If a user wants to override your settings,
you assume he knows what he is doing. Do not magically override user
supplied settings. You can issue a warning if you think the user is wrong.
3. All input sets must save all supplied args and kwargs as instance variables.
E.g., self.my_arg = my_arg and self.kwargs = kwargs in the __init__. This
ensures the as_dict and from_dict work correctly.
"""
__author__ = "Shyue Ping Ong, Wei Chen, Will Richards, Geoffroy Hautier, Anubhav Jain"
__copyright__ = "Copyright 2011, The Materials Project"
__version__ = "1.0"
__maintainer__ = "Shyue Ping Ong"
__email__ = "shyuep@gmail.com"
__date__ = "May 28 2016"
MODULE_DIR = os.path.dirname(os.path.abspath(__file__))
def _load_yaml_config(fname):
config = loadfn(os.path.join(MODULE_DIR, "%s.yaml" % fname))
config["INCAR"].update(loadfn(os.path.join(MODULE_DIR,
"VASPIncarBase.yaml")))
return config
[docs]class DictSet(VaspInputSet):
"""
Concrete implementation of VaspInputSet that is initialized from a dict
settings. This allows arbitrary settings to be input. In general,
this is rarely used directly unless there is a source of settings in yaml
format (e.g., from a REST interface). It is typically used by other
VaspInputSets for initialization.
Special consideration should be paid to the way the MAGMOM initialization
for the INCAR is done. The initialization differs depending on the type of
structure and the configuration settings. The order in which the magmom is
determined is as follows:
1. If the site itself has a magmom setting, that is used.
2. If the species on the site has a spin setting, that is used.
3. If the species itself has a particular setting in the config file, that
is used, e.g., Mn3+ may have a different magmom than Mn4+.
4. Lastly, the element symbol itself is checked in the config file. If
there are no settings, VASP's default of 0.6 is used.
Args:
structure (Structure): The Structure to create inputs for.
config_dict (dict): The config dictionary to use.
files_to_transfer (dict): A dictionary of {filename: filepath}. This
allows the transfer of files from a previous calculation.
user_incar_settings (dict): User INCAR settings. This allows a user
to override INCAR settings, e.g., setting a different MAGMOM for
various elements or species. Note that in the new scheme,
ediff_per_atom and hubbard_u are no longer args. Instead, the
config_dict supports EDIFF_PER_ATOM and EDIFF keys. The former
scales with # of atoms, the latter does not. If both are
present, EDIFF is preferred. To force such settings, just supply
user_incar_settings={"EDIFF": 1e-5, "LDAU": False} for example.
The keys 'LDAUU', 'LDAUJ', 'LDAUL' are special cases since
pymatgen defines different values depending on what anions are
present in the structure, so these keys can be defined in one
of two ways, e.g. either {"LDAUU":{"O":{"Fe":5}}} to set LDAUU
for Fe to 5 in an oxide, or {"LDAUU":{"Fe":5}} to set LDAUU to
5 regardless of the input structure.
user_kpoints_settings (dict or Kpoints): Allow user to override kpoints
setting by supplying a dict E.g., {"reciprocal_density": 1000}.
User can also supply Kpoints object. Default is None.
user_potcar_settings (dict: Allow user to override POTCARs. E.g.,
{"Gd": "Gd_3"}. This is generally not recommended. Default is None.
constrain_total_magmom (bool): Whether to constrain the total magmom
(NUPDOWN in INCAR) to be the sum of the expected MAGMOM for all
species. Defaults to False.
sort_structure (bool): Whether to sort the structure (using the
default sort order of electronegativity) before generating input
files. Defaults to True, the behavior you would want most of the
time. This ensures that similar atomic species are grouped
together.
potcar_functional (str): Functional to use. Default (None) is to use
the functional in Potcar.DEFAULT_FUNCTIONAL. Valid values:
"PBE", "LDA", "PW91", "LDA_US"
force_gamma (bool): Force gamma centered kpoint generation. Default
(False) is to use the Automatic Density kpoint scheme, which
will use the Gamma centered generation scheme for hexagonal
cells, and Monkhorst-Pack otherwise.
reduce_structure (None/str): Before generating the input files,
generate the reduced structure. Default (None), does not
alter the structure. Valid values: None, "niggli", "LLL".
vdw: Adds default parameters for van-der-Waals functionals supported
by VASP to INCAR. Supported functionals are: DFT-D2, undamped
DFT-D3, DFT-D3 with Becke-Jonson damping, Tkatchenko-Scheffler,
Tkatchenko-Scheffler with iterative Hirshfeld partitioning,
MBD@rSC, dDsC, Dion's vdW-DF and DF2, optPBE, optB88, and optB86b.
"""
def __init__(self, structure, config_dict,
files_to_transfer=None, user_incar_settings=None,
user_kpoints_settings=None, user_potcar_settings=None,
constrain_total_magmom=False, sort_structure=True,
potcar_functional="PBE", force_gamma=False,
reduce_structure=None, vdw=None):
if reduce_structure:
structure = structure.get_reduced_structure(reduce_structure)
if sort_structure:
structure = structure.get_sorted_structure()
self.structure = structure
self._config_dict = deepcopy(config_dict)
self.files_to_transfer = files_to_transfer or {}
self.constrain_total_magmom = constrain_total_magmom
self.sort_structure = sort_structure
self.potcar_functional = potcar_functional
self.force_gamma = force_gamma
self.reduce_structure = reduce_structure
self.user_incar_settings = user_incar_settings or {}
self.user_kpoints_settings = user_kpoints_settings
self.user_potcar_settings = user_potcar_settings
self.vdw = vdw.lower() if vdw is not None else None
if self.vdw:
vdw_par = loadfn(os.path.join(MODULE_DIR, "vdW_parameters.yaml"))
try:
self._config_dict["INCAR"].update(vdw_par[self.vdw])
except KeyError:
raise KeyError("Invalid or unsupported van-der-Waals "
"functional. Supported functionals are "
"%s." % vdw_par.keys())
if self.user_potcar_settings:
warnings.warn(
"Overriding POTCARs is generally not recommended as it "
"significantly affect the results of calculations and "
"compatibility with other calculations done with the same "
"input set. In many instances, it is better to write a "
"subclass of a desired input set and override the POTCAR in "
"the subclass to be explicit on the differences.")
for k, v in self.user_potcar_settings.items():
self._config_dict["POTCAR"][k] = v
@property
def incar(self):
settings = dict(self._config_dict["INCAR"])
settings.update(self.user_incar_settings)
structure = self.structure
incar = Incar()
comp = structure.composition
elements = sorted([el for el in comp.elements if comp[el] > 0],
key=lambda e: e.X)
most_electroneg = elements[-1].symbol
poscar = Poscar(structure)
hubbard_u = settings.get("LDAU", False)
for k, v in settings.items():
if k == "MAGMOM":
mag = []
for site in structure:
if hasattr(site, 'magmom'):
mag.append(site.magmom)
elif hasattr(site.specie, 'spin'):
mag.append(site.specie.spin)
elif str(site.specie) in v:
mag.append(v.get(str(site.specie)))
else:
mag.append(v.get(site.specie.symbol, 0.6))
incar[k] = mag
elif k in ('LDAUU', 'LDAUJ', 'LDAUL'):
if hubbard_u:
if hasattr(structure[0], k.lower()):
m = dict([(site.specie.symbol, getattr(site, k.lower()))
for site in structure])
incar[k] = [m[sym] for sym in poscar.site_symbols]
# lookup specific LDAU if specified for most_electroneg atom
elif most_electroneg in v.keys() and \
isinstance(v[most_electroneg], dict):
incar[k] = [v[most_electroneg].get(sym, 0)
for sym in poscar.site_symbols]
# else, use fallback LDAU value if it exists
else:
incar[k] = [v.get(sym, 0) for sym in poscar.site_symbols]
elif k.startswith("EDIFF") and k != "EDIFFG":
if "EDIFF" not in settings and k == "EDIFF_PER_ATOM":
incar["EDIFF"] = float(v) * structure.num_sites
else:
incar["EDIFF"] = float(settings["EDIFF"])
else:
incar[k] = v
has_u = hubbard_u and sum(incar['LDAUU']) > 0
if has_u:
# modify LMAXMIX if LSDA+U and you have d or f electrons
# note that if the user explicitly sets LMAXMIX in settings it will
# override this logic.
if 'LMAXMIX' not in settings.keys():
# contains f-electrons
if any([el.Z > 56 for el in structure.composition]):
incar['LMAXMIX'] = 6
# contains d-electrons
elif any([el.Z > 20 for el in structure.composition]):
incar['LMAXMIX'] = 4
else:
for key in list(incar.keys()):
if key.startswith('LDAU'):
del incar[key]
if self.constrain_total_magmom:
nupdown = sum([mag if abs(mag) > 0.6 else 0
for mag in incar['MAGMOM']])
incar['NUPDOWN'] = nupdown
return incar
@property
def poscar(self):
return Poscar(self.structure)
@property
def nelect(self):
"""
Gets the default number of electrons for a given structure.
"""
return int(round(
sum([self.structure.composition.element_composition[ps.element]
* ps.ZVAL
for ps in self.potcar])))
@property
def kpoints(self):
"""
Writes out a KPOINTS file using the fully automated grid method. Uses
Gamma centered meshes for hexagonal cells and Monk grids otherwise.
Algorithm:
Uses a simple approach scaling the number of divisions along each
reciprocal lattice vector proportional to its length.
"""
settings = self.user_kpoints_settings or self._config_dict["KPOINTS"]
if isinstance(settings, Kpoints):
return settings
# If grid_density is in the kpoints_settings use
# Kpoints.automatic_density
if settings.get('grid_density'):
return Kpoints.automatic_density(
self.structure, int(settings['grid_density']),
self.force_gamma)
# If reciprocal_density is in the kpoints_settings use
# Kpoints.automatic_density_by_vol
elif settings.get('reciprocal_density'):
return Kpoints.automatic_density_by_vol(
self.structure, int(settings['reciprocal_density']),
self.force_gamma)
# If length is in the kpoints_settings use Kpoints.automatic
elif settings.get('length'):
return Kpoints.automatic(settings['length'])
# Raise error. Unsure of which kpoint generation to use
else:
raise ValueError(
"Invalid KPoint Generation algo : Supported Keys are "
"grid_density: for Kpoints.automatic_density generation, "
"reciprocal_density: for KPoints.automatic_density_by_vol "
"generation, and length : for Kpoints.automatic generation")
def __str__(self):
return self.__class__.__name__
def __repr__(self):
return self.__class__.__name__
[docs]class MITRelaxSet(DictSet):
"""
Standard implementation of VaspInputSet utilizing parameters in the MIT
High-throughput project.
The parameters are chosen specifically for a high-throughput project,
which means in general pseudopotentials with fewer electrons were chosen.
Please refer::
A Jain, G. Hautier, C. Moore, S. P. Ong, C. Fischer, T. Mueller,
K. A. Persson, G. Ceder. A high-throughput infrastructure for density
functional theory calculations. Computational Materials Science,
2011, 50(8), 2295-2310. doi:10.1016/j.commatsci.2011.02.023
"""
CONFIG = _load_yaml_config("MITRelaxSet")
def __init__(self, structure, **kwargs):
super(MITRelaxSet, self).__init__(
structure, MITRelaxSet.CONFIG, **kwargs)
self.kwargs = kwargs
[docs]class MPRelaxSet(DictSet):
"""
Implementation of VaspInputSet utilizing parameters in the public
Materials Project. Typically, the pseudopotentials chosen contain more
electrons than the MIT parameters, and the k-point grid is ~50% more dense.
The LDAUU parameters are also different due to the different psps used,
which result in different fitted values.
"""
CONFIG = CONFIG = _load_yaml_config("MPRelaxSet")
def __init__(self, structure, **kwargs):
super(MPRelaxSet, self).__init__(
structure, MPRelaxSet.CONFIG, **kwargs)
self.kwargs = kwargs
[docs]class MPHSERelaxSet(DictSet):
"""
Same as the MPRelaxSet, but with HSE parameters.
"""
CONFIG = _load_yaml_config("MPHSERelaxSet")
def __init__(self, structure, **kwargs):
super(MPHSERelaxSet, self).__init__(
structure, MPHSERelaxSet.CONFIG, **kwargs)
self.kwargs = kwargs
[docs]class MPStaticSet(MPRelaxSet):
def __init__(self, structure, prev_incar=None, prev_kpoints=None,
lepsilon=False, lcalcpol=False, reciprocal_density=100,
**kwargs):
"""
Run a static calculation.
Args:
structure (Structure): Structure from previous run.
prev_incar (Incar): Incar file from previous run.
prev_kpoints (Kpoints): Kpoints from previous run.
lepsilon (bool): Whether to add static dielectric calculation
reciprocal_density (int): For static calculations,
we usually set the reciprocal density by volume. This is a
convenience arg to change that, rather than using
user_kpoints_settings. Defaults to 100, which is ~50% more than
that of standard relaxation calculations.
\\*\\*kwargs: kwargs supported by MPRelaxSet.
"""
super(MPStaticSet, self).__init__(structure, **kwargs)
if isinstance(prev_incar, six.string_types):
prev_incar = Incar.from_file(prev_incar)
if isinstance(prev_kpoints, six.string_types):
prev_kpoints = Kpoints.from_file(prev_kpoints)
self.prev_incar = prev_incar
self.prev_kpoints = prev_kpoints
self.reciprocal_density = reciprocal_density
self.structure = structure
self.kwargs = kwargs
self.lepsilon = lepsilon
self.lcalcpol = lcalcpol
@property
def incar(self):
parent_incar = super(MPStaticSet, self).incar
incar = Incar(self.prev_incar) if self.prev_incar is not None else \
Incar(parent_incar)
incar.update(
{"IBRION": -1, "ISMEAR": -5, "LAECHG": True, "LCHARG": True,
"LORBIT": 11, "LVHAR": True, "LWAVE": False, "NSW": 0,
"ICHARG": 0, "ALGO": "Normal"})
if self.lepsilon:
incar["IBRION"] = 8
incar["LEPSILON"] = True
# LPEAD=T: numerical evaluation of overlap integral prevents
# LRF_COMMUTATOR errors and can lead to better expt. agreement
# but produces slightly different results
incar["LPEAD"] = True
# Note that DFPT calculations MUST unset NSW. NSW = 0 will fail
# to output ionic.
incar.pop("NSW", None)
incar.pop("NPAR", None)
if self.lcalcpol:
incar["LCALCPOL"] = True
for k in ["MAGMOM", "NUPDOWN"] + list(self.kwargs.get(
"user_incar_settings", {}).keys()):
# For these parameters as well as user specified settings, override
# the incar settings.
if parent_incar.get(k, None) is not None:
incar[k] = parent_incar[k]
else:
incar.pop(k, None)
# use new LDAUU when possible b/c the Poscar might have changed
# representation
if incar.get('LDAU'):
u = incar.get('LDAUU', [])
j = incar.get('LDAUJ', [])
if sum([u[x] - j[x] for x, y in enumerate(u)]) > 0:
for tag in ('LDAUU', 'LDAUL', 'LDAUJ'):
incar.update({tag: parent_incar[tag]})
# ensure to have LMAXMIX for GGA+U static run
if "LMAXMIX" not in incar:
incar.update({"LMAXMIX": parent_incar["LMAXMIX"]})
# Compare ediff between previous and staticinputset values,
# choose the tighter ediff
incar["EDIFF"] = min(incar.get("EDIFF", 1), parent_incar["EDIFF"])
return incar
@property
def kpoints(self):
self._config_dict["KPOINTS"]["reciprocal_density"] = \
self.reciprocal_density
kpoints = super(MPStaticSet, self).kpoints
# Prefer to use k-point scheme from previous run
if self.prev_kpoints and self.prev_kpoints.style != kpoints.style:
if self.prev_kpoints.style == Kpoints.supported_modes.Monkhorst:
k_div = [kp + 1 if kp % 2 == 1 else kp
for kp in kpoints.kpts[0]]
kpoints = Kpoints.monkhorst_automatic(k_div)
else:
kpoints = Kpoints.gamma_automatic(kpoints.kpts[0])
return kpoints
[docs] @classmethod
def from_prev_calc(cls, prev_calc_dir, standardize=False, sym_prec=0.1,
international_monoclinic=True, reciprocal_density=100,
small_gap_multiply=None, **kwargs):
"""
Generate a set of Vasp input files for static calculations from a
directory of previous Vasp run.
Args:
prev_calc_dir (str): Directory containing the outputs(
vasprun.xml and OUTCAR) of previous vasp run.
standardize (float): Whether to standardize to a primitive
standard cell. Defaults to False.
sym_prec (float): Tolerance for symmetry finding. If not 0,
the final structure from the previous run will be symmetrized
to get a primitive standard cell. Set to 0 if you don't want
that.
international_monoclinic (bool): Whether to use international
convention (vs Curtarolo) for monoclinic. Defaults True.
reciprocal_density (int): density of k-mesh by reciprocal
volume (defaults to 100)
small_gap_multiply ([float, float]): If the gap is less than
1st index, multiply the default reciprocal_density by the 2nd
index.
\\*\\*kwargs: All kwargs supported by MPStaticSet,
other than prev_incar and prev_structure and prev_kpoints which
are determined from the prev_calc_dir.
"""
vasprun, outcar = get_vasprun_outcar(prev_calc_dir)
prev_incar = vasprun.incar
prev_kpoints = vasprun.kpoints
# We will make a standard structure for the given symprec.
prev_structure = get_structure_from_prev_run(
vasprun, outcar, sym_prec=standardize and sym_prec,
international_monoclinic=international_monoclinic)
# multiply the reciprocal density if needed:
if small_gap_multiply:
gap = vasprun.eigenvalue_band_properties[0]
if gap <= small_gap_multiply[0]:
reciprocal_density = reciprocal_density * small_gap_multiply[1]
return MPStaticSet(
structure=prev_structure, prev_incar=prev_incar,
prev_kpoints=prev_kpoints,
reciprocal_density=reciprocal_density, **kwargs)
[docs]class MPHSEBSSet(MPHSERelaxSet):
def __init__(self, structure, user_incar_settings=None, added_kpoints=None,
mode="Uniform", reciprocal_density=None,
kpoints_line_density=20, **kwargs):
"""
Implementation of a VaspInputSet for HSE band structure computations.
Remember that HSE band structures must be self-consistent in VASP. A
band structure along symmetry lines for instance needs BOTH a uniform
grid with appropriate weights AND a path along the lines with weight 0.
Thus, the "Uniform" mode is just like regular static SCF but allows
adding custom kpoints (e.g., corresponding to known VBM/CBM) to the
uniform grid that have zero weight (e.g., for better gap estimate).
The "Line" mode is just like Uniform mode, but additionally adds
k-points along symmetry lines with zero weight.
Args:
structure (Structure): Structure to compute
user_incar_settings (dict): A dict specifying additional incar
settings
added_kpoints (list): a list of kpoints (list of 3 number list)
added to the run. The k-points are in fractional coordinates
mode (str): "Line" - generate k-points along symmetry lines for
bandstructure. "Uniform" - generate uniform k-points grid
reciprocal_density (int): k-point density to use for uniform mesh
kpoints_line_density (int): k-point density for high symmetry lines
**kwargs (dict): Any other parameters to pass into DictVaspInputSet
"""
super(MPHSEBSSet, self).__init__(structure, **kwargs)
self.structure = structure
self.user_incar_settings = user_incar_settings or {}
self._config_dict["INCAR"].update({
"NSW": 0,
"ISMEAR": 0,
"SIGMA": 0.05,
"ISYM": 3,
"LCHARG": False,
"NELMIN": 5
})
self.added_kpoints = added_kpoints if added_kpoints is not None else []
self.mode = mode
self.reciprocal_density = reciprocal_density or \
self.kpoints_settings['reciprocal_density']
self.kpoints_line_density = kpoints_line_density
@property
def kpoints(self):
kpts = []
weights = []
all_labels = []
# for both modes, include the Uniform mesh w/standard weights
grid = Kpoints.automatic_density_by_vol(self.structure,
self.reciprocal_density).kpts
ir_kpts = SpacegroupAnalyzer(self.structure, symprec=0.1)\
.get_ir_reciprocal_mesh(grid[0])
for k in ir_kpts:
kpts.append(k[0])
weights.append(int(k[1]))
all_labels.append(None)
# for both modes, include any user-added kpoints w/zero weight
for k in self.added_kpoints:
kpts.append(k)
weights.append(0.0)
all_labels.append("user-defined")
# for line mode only, add the symmetry lines w/zero weight
if self.mode.lower() == "line":
kpath = HighSymmKpath(self.structure)
frac_k_points, labels = kpath.get_kpoints(
line_density=self.kpoints_line_density,
coords_are_cartesian=False)
for k in range(len(frac_k_points)):
kpts.append(frac_k_points[k])
weights.append(0.0)
all_labels.append(labels[k])
comment = ("HSE run along symmetry lines"
if self.mode.lower() == "line"
else "HSE run on uniform grid")
return Kpoints(comment=comment,
style=Kpoints.supported_modes.Reciprocal,
num_kpts=len(kpts), kpts=kpts, kpts_weights=weights,
labels=all_labels)
[docs] @classmethod
def from_prev_calc(cls, prev_calc_dir, mode="gap",
reciprocal_density=50, copy_chgcar=True, **kwargs):
"""
Generate a set of Vasp input files for HSE calculations from a
directory of previous Vasp run. if mode=="gap", it explicitly adds VBM
and CBM of the prev run to the k-point list of this run.
Args:
prev_calc_dir (str): Directory containing the outputs
(vasprun.xml and OUTCAR) of previous vasp run.
mode (str): Either "uniform", "gap" or "line"
reciprocal_density (int): density of k-mesh
copy_chgcar (bool): whether to copy CHGCAR of previous run
\\*\\*kwargs: All kwargs supported by MPHSEBSStaticSet,
other than prev_structure which is determined from the previous
calc dir.
"""
vasprun, outcar = get_vasprun_outcar(prev_calc_dir)
# note: don't standardize the cell because we want to retain k-points
prev_structure = get_structure_from_prev_run(vasprun, outcar,
sym_prec=0)
added_kpoints = []
if mode.lower() == "gap":
bs = vasprun.get_band_structure()
vbm, cbm = bs.get_vbm()["kpoint"], bs.get_cbm()["kpoint"]
if vbm:
added_kpoints.append(vbm.frac_coords)
if cbm:
added_kpoints.append(cbm.frac_coords)
files_to_transfer = {}
if copy_chgcar:
chgcars = sorted(glob.glob(os.path.join(prev_calc_dir, "CHGCAR*")))
if chgcars:
files_to_transfer["CHGCAR"] = str(chgcars[-1])
return MPHSEBSSet(
structure=prev_structure,
added_kpoints=added_kpoints, reciprocal_density=reciprocal_density,
mode=mode, files_to_transfer=files_to_transfer, **kwargs)
[docs]class MPNonSCFSet(MPRelaxSet):
def __init__(self, structure, prev_incar=None,
mode="line", nedos=601, reciprocal_density=100, sym_prec=0.1,
kpoints_line_density=20, optics=False, **kwargs):
"""
Init a MPNonSCFSet. Typically, you would use the classmethod
from_prev_calc to initialize from a previous SCF run.
Args:
structure (Structure): Structure to compute
prev_incar (Incar/string): Incar file from previous run.
mode (str): Line or Uniform mode supported.
nedos (int): nedos parameter. Default to 601.
reciprocal_density (int): density of k-mesh by reciprocal
volume (defaults to 100)
sym_prec (float): Symmetry precision (for Uniform mode).
kpoints_line_density (int): Line density for Line mode.
optics (bool): whether to add dielectric function
\\*\\*kwargs: kwargs supported by MPVaspInputSet.
"""
super(MPNonSCFSet, self).__init__(structure, **kwargs)
if isinstance(prev_incar, six.string_types):
prev_incar = Incar.from_file(prev_incar)
self.prev_incar = prev_incar
self.kwargs = kwargs
self.nedos = nedos
self.reciprocal_density = reciprocal_density
self.sym_prec = sym_prec
self.kpoints_line_density = kpoints_line_density
self.optics = optics
self.mode = mode.lower()
if self.mode.lower() not in ["line", "uniform"]:
raise ValueError("Supported modes for NonSCF runs are 'Line' and "
"'Uniform'!")
if (self.mode.lower() != "uniform" or nedos < 2000) and optics:
warnings.warn("It is recommended to use Uniform mode with a high "
"NEDOS for optics calculations.")
@property
def incar(self):
incar = super(MPNonSCFSet, self).incar
if self.prev_incar is not None:
incar.update({k: v for k, v in self.prev_incar.items()})
# Overwrite necessary INCAR parameters from previous runs
incar.update({"IBRION": -1, "ISMEAR": 0, "SIGMA": 0.001,
"LCHARG": False, "LORBIT": 11, "LWAVE": False,
"NSW": 0, "ISYM": 0, "ICHARG": 11})
incar.update(self.kwargs.get("user_incar_settings", {}))
if self.mode.lower() == "uniform":
# Set smaller steps for DOS output
incar["NEDOS"] = self.nedos
if self.optics:
incar["LOPTICS"] = True
incar.pop("MAGMOM", None)
return incar
@property
def kpoints(self):
if self.mode == "line":
kpath = HighSymmKpath(self.structure)
frac_k_points, k_points_labels = kpath.get_kpoints(
line_density=self.kpoints_line_density,
coords_are_cartesian=False)
kpoints = Kpoints(
comment="Non SCF run along symmetry lines",
style=Kpoints.supported_modes.Reciprocal,
num_kpts=len(frac_k_points),
kpts=frac_k_points, labels=k_points_labels,
kpts_weights=[1] * len(frac_k_points))
else:
kpoints = Kpoints.automatic_density_by_vol(self.structure,
self.reciprocal_density)
mesh = kpoints.kpts[0]
ir_kpts = SpacegroupAnalyzer(
self.structure,
symprec=self.sym_prec).get_ir_reciprocal_mesh(mesh)
kpts = []
weights = []
for k in ir_kpts:
kpts.append(k[0])
weights.append(int(k[1]))
kpoints = Kpoints(comment="Non SCF run on uniform grid",
style=Kpoints.supported_modes.Reciprocal,
num_kpts=len(ir_kpts),
kpts=kpts, kpts_weights=weights)
return kpoints
[docs] @classmethod
def from_prev_calc(cls, prev_calc_dir, copy_chgcar=True,
nbands_factor=1.2, standardize=False, sym_prec=0.1,
international_monoclinic=True, reciprocal_density=100,
kpoints_line_density=20, small_gap_multiply=None,
**kwargs):
"""
Generate a set of Vasp input files for NonSCF calculations from a
directory of previous static Vasp run.
Args:
prev_calc_dir (str): The directory contains the outputs(
vasprun.xml and OUTCAR) of previous vasp run.
copy_chgcar: Whether to copy the old CHGCAR. Defaults to True.
nbands_factor (float): Multiplicative factor for NBANDS. Choose a
higher number if you are doing an LOPTICS calculation.
standardize (float): Whether to standardize to a primitive
standard cell. Defaults to False.
sym_prec (float): Tolerance for symmetry finding. If not 0,
the final structure from the previous run will be symmetrized
to get a primitive standard cell. Set to 0 if you don't want
that.
international_monoclinic (bool): Whether to use international
convention (vs Curtarolo) for monoclinic. Defaults True.
reciprocal_density (int): density of k-mesh by reciprocal
volume in uniform mode (defaults to 100)
kpoints_line_density (int): density of k-mesh in line mode
(defaults to 20)
small_gap_multiply ([float, float]): If the gap is less than
1st index, multiply the default reciprocal_density by the 2nd
index.
\\*\\*kwargs: All kwargs supported by MPNonSCFSet,
other than structure, prev_incar and prev_chgcar which
are determined from the prev_calc_dir.
"""
vasprun, outcar = get_vasprun_outcar(prev_calc_dir)
incar = vasprun.incar
# Get a Magmom-decorated structure
structure = get_structure_from_prev_run(
vasprun, outcar, sym_prec=standardize and sym_prec,
international_monoclinic=international_monoclinic)
# Turn off spin when magmom for every site is smaller than 0.02.
if outcar and outcar.magnetization:
site_magmom = np.array([i['tot'] for i in outcar.magnetization])
ispin = 2 if np.any(site_magmom[np.abs(site_magmom) > 0.02]) else 1
elif vasprun.is_spin:
ispin = 2
else:
ispin = 1
nbands = int(np.ceil(vasprun.parameters["NBANDS"] * nbands_factor))
incar.update({"ISPIN": ispin, "NBANDS": nbands})
files_to_transfer = {}
if copy_chgcar:
chgcars = sorted(glob.glob(os.path.join(prev_calc_dir, "CHGCAR*")))
if chgcars:
files_to_transfer["CHGCAR"] = str(chgcars[-1])
# multiply the reciprocal density if needed:
if small_gap_multiply:
gap = vasprun.eigenvalue_band_properties[0]
if gap <= small_gap_multiply[0]:
reciprocal_density = reciprocal_density * small_gap_multiply[1]
kpoints_line_density = kpoints_line_density * \
small_gap_multiply[1]
return MPNonSCFSet(structure=structure, prev_incar=incar,
reciprocal_density=reciprocal_density,
kpoints_line_density=kpoints_line_density,
files_to_transfer=files_to_transfer, **kwargs)
[docs]class MPSOCSet(MPStaticSet):
def __init__(self, structure, saxis=(0, 0, 1), prev_incar=None,
reciprocal_density=100, **kwargs):
"""
Init a MPSOCSet.
Args:
structure (Structure): the structure must have the 'magmom' site
property and each magnetic moment value must have 3
components. eg:- magmom = [[0,0,2], ...]
saxis (tuple): magnetic moment orientation
prev_incar (Incar): Incar file from previous run.
reciprocal_density (int): density of k-mesh by reciprocal
volume (defaults to 100)
\\*\\*kwargs: kwargs supported by MPVaspInputSet.
"""
if not hasattr(structure[0], "magmom") and \
not isinstance(structure[0].magmom, list):
raise ValueError(
"The structure must have the 'magmom' site "
"property and each magnetic moment value must have 3 "
"components. eg:- magmom = [0,0,2]")
self.saxis = saxis
super(MPSOCSet, self).__init__(
structure, prev_incar=prev_incar,
reciprocal_density=reciprocal_density, **kwargs)
@property
def incar(self):
incar = super(MPSOCSet, self).incar
if self.prev_incar is not None:
incar.update({k: v for k, v in self.prev_incar.items()})
# Overwrite necessary INCAR parameters from previous runs
incar.update({"ISYM": -1, "LSORBIT": "T", "ICHARG": 11,
"SAXIS": list(self.saxis)})
incar.update(self.kwargs.get("user_incar_settings", {}))
return incar
[docs] @classmethod
def from_prev_calc(cls, prev_calc_dir, copy_chgcar=True,
nbands_factor=1.2, standardize=False, sym_prec=0.1,
international_monoclinic=True, reciprocal_density=100,
small_gap_multiply=None, **kwargs):
"""
Generate a set of Vasp input files for SOC calculations from a
directory of previous static Vasp run. SOC calc requires all 3
components for MAGMOM for each atom in the structure.
Args:
prev_calc_dir (str): The directory contains the outputs(
vasprun.xml and OUTCAR) of previous vasp run.
copy_chgcar: Whether to copy the old CHGCAR. Defaults to True.
nbands_factor (float): Multiplicative factor for NBANDS. Choose a
higher number if you are doing an LOPTICS calculation.
standardize (float): Whether to standardize to a primitive
standard cell. Defaults to False.
sym_prec (float): Tolerance for symmetry finding. If not 0,
the final structure from the previous run will be symmetrized
to get a primitive standard cell. Set to 0 if you don't want
that.
international_monoclinic (bool): Whether to use international
convention (vs Curtarolo) for monoclinic. Defaults True.
reciprocal_density (int): density of k-mesh by reciprocal
volume (defaults to 100)
small_gap_multiply ([float, float]): If the gap is less than
1st index, multiply the default reciprocal_density by the 2nd
index.
\\*\\*kwargs: All kwargs supported by MPSOCSet,
other than structure, prev_incar and prev_chgcar which
are determined from the prev_calc_dir.
"""
vasprun, outcar = get_vasprun_outcar(prev_calc_dir)
incar = vasprun.incar
# Get a magmom-decorated structure
structure = get_structure_from_prev_run(
vasprun, outcar, sym_prec=standardize and sym_prec,
international_monoclinic=international_monoclinic)
# override magmom if provided
if kwargs.get("magmom", None):
structure = structure.copy(
site_properties={"magmom": kwargs["magmom"]})
kwargs.pop("magmom", None)
# magmom has to be 3D for SOC calculation.
if hasattr(structure[0], "magmom"):
if not isinstance(structure[0].magmom, list):
structure = structure.copy(site_properties={
"magmom": [[0, 0, site.magmom] for site in structure]})
else:
raise ValueError("Neither the previous structure has mamgom "
"property nor magmom provided")
nbands = int(np.ceil(vasprun.parameters["NBANDS"] * nbands_factor))
incar.update({"NBANDS": nbands})
files_to_transfer = {}
if copy_chgcar:
chgcars = sorted(glob.glob(os.path.join(prev_calc_dir, "CHGCAR*")))
if chgcars:
files_to_transfer["CHGCAR"] = str(chgcars[-1])
# multiply the reciprocal density if needed:
if small_gap_multiply:
gap = vasprun.eigenvalue_band_properties[0]
if gap <= small_gap_multiply[0]:
reciprocal_density = reciprocal_density * small_gap_multiply[1]
return MPSOCSet(structure, prev_incar=incar,
files_to_transfer=files_to_transfer,
reciprocal_density=reciprocal_density, **kwargs)
[docs]class MVLElasticSet(MPRelaxSet):
"""
MVL denotes VASP input sets that are implemented by the Materials Virtual
Lab (http://www.materialsvirtuallab.org) for various research.
This input set is used to calculate elastic constants in VASP. It is used
in the following work::
Z. Deng, Z. Wang, I.-H. Chu, J. Luo, S. P. Ong.
“Elastic Properties of Alkali Superionic Conductor Electrolytes
from First Principles Calculations”, J. Electrochem. Soc.
2016, 163(2), A67-A74. doi: 10.1149/2.0061602jes
To read the elastic constants, you may use the Outcar class which parses the
elastic constants.
Args:
scale (float): POTIM parameter. The default of 0.015 is usually fine,
but some structures may require a smaller step.
user_incar_settings (dict): A dict specifying additional incar
settings.
"""
def __init__(self, structure, potim=0.015, **kwargs):
super(MVLElasticSet, self).__init__(structure, **kwargs)
self._config_dict["INCAR"].update({"IBRION": 6, "NFREE": 2,
"POTIM": potim})
self._config_dict["INCAR"].pop("NPAR", None)
[docs]class MVLGWSet(DictSet):
"""
MVL denotes VASP input sets that are implemented by the Materials Virtual
Lab (http://www.materialsvirtuallab.org) for various research. This is a
flexible input set for GW calculations.
Note that unlike all other input sets in this module, the PBE_54 series of
functional is set as the default. These have much improved performance for
GW calculations.
"""
CONFIG = _load_yaml_config("MVLGWSet")
SUPPORTED_MODES = ("DIAG", "GW", "STATIC", "BSE")
def __init__(self, structure, prev_incar=None, nbands=None,
potcar_functional="PBE_54",
reciprocal_density=100, mode="STATIC", **kwargs):
"""
A typical sequence is mode="STATIC" -> mode="DIAG" -> mode="GW" ->
mode="BSE". For all steps other than the first one (static), the
recommendation is to use from_prev_calculation on the preceding run in
the series.
Args:
structure (Structure): Input structure.
prev_incar (Incar/string): Incar file from previous run.
mode (str): Supported modes are "STATIC" (default), "DIAG", "GW",
and "BSE".
nbands (int): For subsequent calculations, it is generally
recommended to perform NBANDS convergence starting from the
NBANDS of the previous run for DIAG, and to use the exact same
NBANDS for GW and BSE. This parameter is used by
from_previous_calculation to set nband.
potcar_functional (str): Defaults to "PBE_54".
\\*\\*kwargs: All kwargs supported by DictSet. Typically,
user_incar_settings is a commonly used option.
"""
super(MVLGWSet, self).__init__(
structure, MVLGWSet.CONFIG, **kwargs)
self.prev_incar = prev_incar
self.nbands = nbands
self.potcar_functional = potcar_functional
self.reciprocal_density = reciprocal_density
self.mode = mode.upper()
if self.mode not in MVLGWSet.SUPPORTED_MODES:
raise ValueError("%s not one of the support modes : %s" %
(self.mode, MVLGWSet.SUPPORTED_MODES))
self.kwargs = kwargs
@property
def kpoints(self):
"""
Generate gamma center k-points mesh grid for GW calc,
which is requested by GW calculation.
"""
return Kpoints.automatic_density_by_vol(self.structure,
self.reciprocal_density,
force_gamma=True)
@property
def incar(self):
parent_incar = super(MVLGWSet, self).incar
incar = Incar(self.prev_incar) if self.prev_incar is not None else \
Incar(parent_incar)
if self.mode == "DIAG":
# Default parameters for diagonalization calculation.
incar.update({
"ALGO": "Exact",
"NELM":1,
"LOPTICS": True,
"LPEAD": True
})
elif self.mode == "GW":
# Default parameters for GW calculation.
incar.update({
"ALGO": "GW0",
"NELM": 1,
"NOMEGA": 80,
"ENCUTGW": 250
})
incar.pop("EDIFF", None)
incar.pop("LOPTICS", None)
incar.pop("LPEAD", None)
elif self.mode == "BSE":
# Default parameters for BSE calculation.
incar.update({
"ALGO": "BSE",
"ANTIRES": 0,
"NBANDSO": 20,
"NBANDSV": 20
})
if self.nbands:
incar["NBANDS"] = self.nbands
# Respect user set INCAR.
incar.update(self.kwargs.get("user_incar_settings", {}))
return incar
[docs] @classmethod
def from_prev_calc(cls, prev_calc_dir, copy_wavecar=True, mode="DIAG",
nbands_factor=5, ncores=16, **kwargs):
"""
Generate a set of Vasp input files for GW or BSE calculations from a
directory of previous Exact Diag Vasp run.
Args:
prev_calc_dir (str): The directory contains the outputs(
vasprun.xml of previous vasp run.
copy_wavecar: Whether to copy the old WAVECAR, WAVEDER and
associated files. Defaults to True.
mode (str): Supported modes are "STATIC", "DIAG" (default), "GW",
and "BSE".
nbands_factor (int): Multiplicative factor for NBANDS. Only applies
if mode=="DIAG". Need to be tested for convergence.
ncores (int): numbers of cores you do calculations. VASP will alter
NBANDS if it was not dividable by ncores. Only applies
if mode=="DIAG".
\\*\\*kwargs: All kwargs supported by MVLGWSet,
other than structure, prev_incar and mode, which
are determined from the prev_calc_dir.
"""
vasprun, outcar = get_vasprun_outcar(prev_calc_dir)
prev_incar = vasprun.incar
structure = vasprun.final_structure
nbands = int(vasprun.parameters["NBANDS"])
if mode.upper() == "DIAG":
nbands = int(np.ceil(nbands * nbands_factor / ncores) * ncores)
# copy WAVECAR, WAVEDER (derivatives)
files_to_transfer = {}
if copy_wavecar:
for fname in ("WAVECAR", "WAVEDER", "WFULL"):
w = sorted(glob.glob(os.path.join(prev_calc_dir, fname + "*")))
if w:
if fname == "WFULL":
for f in w:
fname = os.path.basename(f)
fname = fname.split(".")[0]
files_to_transfer[fname] = f
else:
files_to_transfer[fname] = str(w[-1])
return MVLGWSet(structure=structure, prev_incar=prev_incar,
nbands=nbands, mode=mode,
files_to_transfer=files_to_transfer, **kwargs)
[docs]class MVLSlabSet(MPRelaxSet):
"""
Class for writing a set of slab vasp runs,
including both slabs (along the c direction) and orient unit cells (bulk),
to ensure the same KPOINTS, POTCAR and INCAR criterion.
Args:
k_product: default to 50, kpoint number * length for a & b directions,
also for c direction in bulk calculations
bulk (bool): Set to True for bulk calculation. Defaults to False.
**kwargs:
Other kwargs supported by :class:`DictSet`.
"""
def __init__(self, slab, k_product=50, bulk=False,
auto_dipole=False, **kwargs):
super(MVLSlabSet, self).__init__(slab, **kwargs)
self.structure = slab
self.slab = slab
self.k_product = k_product
self.bulk = bulk
self.auto_dipole = auto_dipole
self.kwargs = kwargs
slab_incar = {"EDIFF": 1e-6, "EDIFFG": -0.01, "ENCUT": 400,
"ISMEAR": 0, "SIGMA": 0.05, "ISIF": 3}
if not self.bulk:
slab_incar["ISIF"] = 2
slab_incar["AMIN"] = 0.01
slab_incar["AMIX"] = 0.2
slab_incar["BMIX"] = 0.001
slab_incar["NELMIN"] = 8
if self.auto_dipole:
slab_incar["IDIPOL"] = 3
slab_incar["LDIPOL"] = True
slab_incar["DIPOL"] = slab.center_of_mass
self._config_dict["INCAR"].update(slab_incar)
@property
def kpoints(self):
"""
k_product, default to 50, is kpoint number * length for a & b
directions, also for c direction in bulk calculations
Automatic mesh & Gamma is the default setting.
"""
# To get input sets, the input structure has to has the same number
# of required parameters as a Structure object (ie. 4). Slab
# attributes aren't going to affect the VASP inputs anyways so
# converting the slab into a structure should not matter
kpt = super(MVLSlabSet, self).kpoints
kpt.comment = "Automatic mesh"
kpt.style = 'Gamma'
# use k_product to calculate kpoints, k_product = kpts[0][0] * a
abc = self.structure.lattice.abc
kpt_calc = [int(self.k_product/abc[0]+0.5),
int(self.k_product/abc[1]+0.5), 1]
self.kpt_calc = kpt_calc
# calculate kpts (c direction) for bulk. (for slab, set to 1)
if self.bulk:
kpt_calc[2] = int(self.k_product/abc[2]+0.5)
kpt.kpts[0] = kpt_calc
return kpt
[docs]class MVLGBSet(MPRelaxSet):
"""
Class for writing a vasp input files for grain boundary calculations, slab
or bulk.
Args:
structure(Structure): provide the structure
k_product: Kpoint number * length for a & b directions, also for c
direction in bulk calculations. Default to 40.
slab_mode (bool): Defaults to False. Use default (False) for a
bulk supercell. Use True if you are performing calculations on a
slab-like (i.e., surface) of the GB, for example, when you are
calculating the work of separation.
is_metal (bool): Defaults to True. This determines whether an ISMEAR of
1 is used (for metals) or not (for insulators and semiconductors)
by default. Note that it does *not* override user_incar_settings,
which can be set by the user to be anything desired.
**kwargs:
Other kwargs supported by :class:`DictVaspInputSet`.
"""
def __init__(self, structure, k_product=40, slab_mode=False, is_metal=True,
**kwargs):
super(MVLGBSet, self).__init__(structure, **kwargs)
self.structure = structure
self.k_product = k_product
self.slab_mode = slab_mode
self.is_metal = is_metal
@property
def kpoints(self):
"""
k_product, default to 40, is kpoint number * length for a & b
directions, also for c direction in bulk calculations
Automatic mesh & Gamma is the default setting.
"""
# To get input sets, the input structure has to has the same number
# of required parameters as a Structure object.
kpt = super(MVLGBSet, self).kpoints
kpt.comment = "Generated by pymatgen's MVLGBSet"
kpt.style = 'Gamma'
# use k_product to calculate kpoints, k_product = kpts[0][0] * a
lengths = self.structure.lattice.abc
kpt_calc = [int(self.k_product / lengths[0] + 0.5),
int(self.k_product / lengths[1] + 0.5),
int(self.k_product / lengths[2] + 0.5)]
if self.slab_mode:
kpt_calc[2] = 1
kpt.kpts[0] = kpt_calc
return kpt
@property
def incar(self):
incar = super(MVLGBSet, self).incar
# The default incar setting is used for metallic system, for
# insulator or semiconductor, ISMEAR need to be changed.
incar.update({
"LCHARG": False,
"NELM": 60,
"PREC": "Normal",
"EDIFFG": -0.02,
"ICHARG": 0,
"NSW": 200,
"EDIFF": 0.0001
})
if self.is_metal:
incar["ISMEAR"] = 1
incar["LDAU"] = False
if self.slab_mode:
# for clean grain boundary and bulk relaxation, full optimization
# relaxation (ISIF=3) is used. For slab relaxation (ISIF=2) is used.
incar["ISIF"] = 2
incar["NELMIN"] = 8
incar.update(self.user_incar_settings)
return incar
[docs]class MITNEBSet(MITRelaxSet):
"""
Class for writing NEB inputs. Note that EDIFF is not on a per atom
basis for this input set.
Args:
unset_encut (bool): Whether to unset ENCUT.
\\*\\*kwargs: Other kwargs supported by :class:`DictSet`.
"""
def __init__(self, structures, unset_encut=False, **kwargs):
if len(structures) < 3:
raise ValueError("You need at least 3 structures for an NEB.")
kwargs["sort_structure"] = False
super(MITNEBSet, self).__init__(structures[0], **kwargs)
self.structures = self._process_structures(structures)
self.unset_encut = False
if unset_encut:
self._config_dict["INCAR"].pop("ENCUT", None)
if "EDIFF" not in self._config_dict["INCAR"]:
self._config_dict["INCAR"]["EDIFF"] = self._config_dict[
"INCAR"].pop("EDIFF_PER_ATOM")
# NEB specific defaults
defaults = {'IMAGES': len(structures) - 2, 'IBRION': 1, 'ISYM': 0,
'LCHARG': False, "LDAU": False}
self._config_dict["INCAR"].update(defaults)
@property
def poscar(self):
return Poscar(self.structures[0])
@property
def poscars(self):
return [Poscar(s) for s in self.structures]
def _process_structures(self, structures):
"""
Remove any atom jumps across the cell
"""
input_structures = structures
structures = [input_structures[0]]
for s in input_structures[1:]:
prev = structures[-1]
for i in range(len(s)):
t = np.round(prev[i].frac_coords - s[i].frac_coords)
if np.any(np.abs(t) > 0.5):
s.translate_sites([i], t, to_unit_cell=False)
structures.append(s)
return structures
[docs]class MITMDSet(MITRelaxSet):
"""
Class for writing a vasp md run. This DOES NOT do multiple stage
runs.
Args:
start_temp (int): Starting temperature.
end_temp (int): Final temperature.
nsteps (int): Number of time steps for simulations. The NSW parameter.
time_step (int): The time step for the simulation. The POTIM
parameter. Defaults to 2fs.
spin_polarized (bool): Whether to do spin polarized calculations.
The ISPIN parameter. Defaults to False.
sort_structure (bool): Whether to sort structure. Defaults to False
(different behavior from standard input sets).
\\*\\*kwargs: Other kwargs supported by :class:`DictSet`.
"""
def __init__(self, structure, start_temp, end_temp, nsteps, time_step=2,
spin_polarized=False, **kwargs):
# MD default settings
defaults = {'TEBEG': start_temp, 'TEEND': end_temp, 'NSW': nsteps,
'EDIFF_PER_ATOM': 0.000001, 'LSCALU': False,
'LCHARG': False,
'LPLANE': False, 'LWAVE': True, 'ISMEAR': 0,
'NELMIN': 4, 'LREAL': True, 'BMIX': 1,
'MAXMIX': 20, 'NELM': 500, 'NSIM': 4, 'ISYM': 0,
'ISIF': 0, 'IBRION': 0, 'NBLOCK': 1, 'KBLOCK': 100,
'SMASS': 0, 'POTIM': time_step, 'PREC': 'Normal',
'ISPIN': 2 if spin_polarized else 1,
"LDAU": False}
super(MITMDSet, self).__init__(structure, **kwargs)
self.start_temp = start_temp
self.end_temp = end_temp
self.nsteps = nsteps
self.time_step = time_step
self.spin_polarized = spin_polarized
self.kwargs = kwargs
# use VASP default ENCUT
self._config_dict["INCAR"].pop('ENCUT', None)
if defaults['ISPIN'] == 1:
self._config_dict["INCAR"].pop('MAGMOM', None)
self._config_dict["INCAR"].update(defaults)
@property
def kpoints(self):
return Kpoints.gamma_automatic()
[docs]def get_vasprun_outcar(path, parse_dos=True, parse_eigen=True):
vruns = list(glob.glob(os.path.join(path, "vasprun.xml*")))
outcars = list(glob.glob(os.path.join(path, "OUTCAR*")))
if len(vruns) == 0 or len(outcars) == 0:
raise ValueError(
"Unable to get vasprun.xml/OUTCAR from prev calculation in %s" %
path)
vsfile_fullpath = os.path.join(path, "vasprun.xml")
outcarfile_fullpath = os.path.join(path, "OUTCAR")
vsfile = vsfile_fullpath if vsfile_fullpath in vruns else sorted(vruns)[-1]
outcarfile = outcarfile_fullpath if outcarfile_fullpath in outcars else sorted(outcars)[-1]
return Vasprun(str(vsfile), parse_dos=parse_dos, parse_eigen=parse_eigen), \
Outcar(str(outcarfile))
[docs]def get_structure_from_prev_run(vasprun, outcar=None, sym_prec=0.1,
international_monoclinic=True):
"""
Process structure from previous run.
Args:
vasprun (Vasprun): Vasprun that contains the final structure
from previous run.
outcar (Outcar): Outcar that contains the magnetization info from
previous run.
sym_prec (float): Tolerance for symmetry finding for standardization. If
no standardization is desired, set to 0 or a False.
international_monoclinic (bool): Whether to use international
convention (vs Curtarolo) for monoclinic. Defaults True.
Returns:
Returns the magmom-decorated structure that can be passed to get
Vasp input files, e.g. get_kpoints.
"""
structure = vasprun.final_structure
site_properties = {}
# magmom
if vasprun.is_spin:
if outcar and outcar.magnetization:
site_properties.update({"magmom": [i['tot']
for i in outcar.magnetization]})
else:
site_properties.update({"magmom": vasprun.parameters['MAGMOM']})
# ldau
if vasprun.parameters.get("LDAU", False):
for k in ("LDAUU", "LDAUJ", "LDAUL"):
vals = vasprun.incar[k]
m = {}
l = []
s = 0
for site in structure:
if site.specie.symbol not in m:
m[site.specie.symbol] = vals[s]
s += 1
l.append(m[site.specie.symbol])
if len(l) == len(structure):
site_properties.update({k.lower(): l})
else:
raise ValueError("length of list {} not the same as"
"structure".format(l))
structure = structure.copy(site_properties=site_properties)
if sym_prec:
sym_finder = SpacegroupAnalyzer(structure, symprec=sym_prec)
new_structure = sym_finder.get_primitive_standard_structure(
international_monoclinic=international_monoclinic)
# the primitive structure finding has had several bugs in the past
# defend through validation
vpa_old = structure.volume / structure.num_sites
vpa_new = new_structure.volume / new_structure.num_sites
if abs(vpa_old - vpa_new) / vpa_old > 0.02:
raise ValueError(
"Standardizing cell failed! VPA old: {}, VPA new: {}".format(
vpa_old, vpa_new))
sm = StructureMatcher()
if not sm.fit(structure, new_structure):
raise ValueError(
"Standardizing cell failed! Old structure doesn't match new.")
structure = new_structure
return structure