import os
import copy
import subprocess
from math import pi, sqrt
import pathlib
from typing import Union, Optional, List, Set, Dict, Any
import warnings
import numpy as np
from ase.cell import Cell
from ase.outputs import Properties, all_outputs
from ase.utils import jsonable
from ase.calculators.abc import GetPropertiesMixin
class CalculatorError(RuntimeError):
"""Base class of error types related to ASE calculators."""
class CalculatorSetupError(CalculatorError):
"""Calculation cannot be performed with the given parameters.
Reasons to raise this errors are:
* The calculator is not properly configured
(missing executable, environment variables, ...)
* The given atoms object is not supported
* Calculator parameters are unsupported
Typically raised before a calculation."""
class EnvironmentError(CalculatorSetupError):
"""Raised if calculator is not properly set up with ASE.
May be missing an executable or environment variables."""
class InputError(CalculatorSetupError):
"""Raised if inputs given to the calculator were incorrect.
Bad input keywords or values, or missing pseudopotentials.
This may be raised before or during calculation, depending on
when the problem is detected."""
class CalculationFailed(CalculatorError):
"""Calculation failed unexpectedly.
Reasons to raise this error are:
* Calculation did not converge
* Calculation ran out of memory
* Segmentation fault or other abnormal termination
* Arithmetic trouble (singular matrices, NaN, ...)
Typically raised during calculation."""
class SCFError(CalculationFailed):
"""SCF loop did not converge."""
class ReadError(CalculatorError):
"""Unexpected irrecoverable error while reading calculation results."""
class PropertyNotImplementedError(NotImplementedError):
"""Raised if a calculator does not implement the requested property."""
class PropertyNotPresent(CalculatorError):
"""Requested property is missing.
Maybe it was never calculated, or for some reason was not extracted
with the rest of the results, without being a fatal ReadError."""
def compare_atoms(atoms1, atoms2, tol=1e-15, excluded_properties=None):
"""Check for system changes since last calculation. Properties in
``excluded_properties`` are not checked."""
if atoms1 is None:
system_changes = all_changes[:]
else:
system_changes = []
properties_to_check = set(all_changes)
if excluded_properties:
properties_to_check -= set(excluded_properties)
# Check properties that aren't in Atoms.arrays but are attributes of
# Atoms objects
for prop in ['cell', 'pbc']:
if prop in properties_to_check:
properties_to_check.remove(prop)
if not equal(getattr(atoms1, prop), getattr(atoms2, prop),
atol=tol):
system_changes.append(prop)
arrays1 = set(atoms1.arrays)
arrays2 = set(atoms2.arrays)
# Add any properties that are only in atoms1.arrays or only in
# atoms2.arrays (and aren't excluded). Note that if, e.g. arrays1 has
# `initial_charges` which is merely zeros and arrays2 does not have
# this array, we'll still assume that the system has changed. However,
# this should only occur rarely.
system_changes += properties_to_check & (arrays1 ^ arrays2)
# Finally, check all of the non-excluded properties shared by the atoms
# arrays.
for prop in properties_to_check & arrays1 & arrays2:
if not equal(atoms1.arrays[prop], atoms2.arrays[prop], atol=tol):
system_changes.append(prop)
return system_changes
all_properties = ['energy', 'forces', 'stress', 'stresses', 'dipole',
'charges', 'magmom', 'magmoms', 'free_energy', 'energies']
all_changes = ['positions', 'numbers', 'cell', 'pbc',
'initial_charges', 'initial_magmoms']
# Recognized names of calculators sorted alphabetically:
names = ['abinit', 'ace', 'aims', 'amber', 'asap', 'castep', 'cp2k',
'crystal', 'demon', 'demonnano', 'dftb', 'dftd3', 'dmol', 'eam',
'elk', 'emt', 'espresso', 'exciting', 'ff', 'fleur', 'gamess_us',
'gaussian', 'gpaw', 'gromacs', 'gulp', 'hotbit', 'kim',
'lammpslib', 'lammpsrun', 'lj', 'mopac', 'morse', 'nwchem',
'octopus', 'onetep', 'openmx', 'orca', 'psi4', 'qchem', 'siesta',
'tip3p', 'tip4p', 'turbomole', 'vasp']
special = {'cp2k': 'CP2K',
'demonnano': 'DemonNano',
'dftd3': 'DFTD3',
'dmol': 'DMol3',
'eam': 'EAM',
'elk': 'ELK',
'emt': 'EMT',
'crystal': 'CRYSTAL',
'ff': 'ForceField',
'fleur': 'FLEUR',
'gamess_us': 'GAMESSUS',
'gulp': 'GULP',
'kim': 'KIM',
'lammpsrun': 'LAMMPS',
'lammpslib': 'LAMMPSlib',
'lj': 'LennardJones',
'mopac': 'MOPAC',
'morse': 'MorsePotential',
'nwchem': 'NWChem',
'openmx': 'OpenMX',
'orca': 'ORCA',
'qchem': 'QChem',
'tip3p': 'TIP3P',
'tip4p': 'TIP4P'}
external_calculators = {}
def register_calculator_class(name, cls):
""" Add the class into the database. """
assert name not in external_calculators
external_calculators[name] = cls
names.append(name)
names.sort()
def get_calculator_class(name):
"""Return calculator class."""
if name == 'asap':
from asap3 import EMT as Calculator
elif name == 'gpaw':
from gpaw import GPAW as Calculator
elif name == 'hotbit':
from hotbit import Calculator
elif name == 'vasp2':
from ase.calculators.vasp import Vasp2 as Calculator
elif name == 'ace':
from ase.calculators.acemolecule import ACE as Calculator
elif name == 'Psi4':
from ase.calculators.psi4 import Psi4 as Calculator
elif name in external_calculators:
Calculator = external_calculators[name]
else:
classname = special.get(name, name.title())
module = __import__('ase.calculators.' + name, {}, None, [classname])
Calculator = getattr(module, classname)
return Calculator
def equal(a, b, tol=None, rtol=None, atol=None):
"""ndarray-enabled comparison function."""
# XXX Known bugs:
# * Comparing cell objects (pbc not part of array representation)
# * Infinite recursion for cyclic dicts
# * Can of worms is open
if tol is not None:
msg = 'Use `equal(a, b, rtol=..., atol=...)` instead of `tol=...`'
warnings.warn(msg, DeprecationWarning)
assert rtol is None and atol is None, \
'Do not use deprecated `tol` with `atol` and/or `rtol`'
rtol = tol
atol = tol
a_is_dict = isinstance(a, dict)
b_is_dict = isinstance(b, dict)
if a_is_dict or b_is_dict:
# Check that both a and b are dicts
if not (a_is_dict and b_is_dict):
return False
if a.keys() != b.keys():
return False
return all(equal(a[key], b[key], rtol=rtol, atol=atol) for key in a)
if np.shape(a) != np.shape(b):
return False
if rtol is None and atol is None:
return np.array_equal(a, b)
if rtol is None:
rtol = 0
if atol is None:
atol = 0
return np.allclose(a, b, rtol=rtol, atol=atol)
def kptdensity2monkhorstpack(atoms, kptdensity=3.5, even=True):
"""Convert k-point density to Monkhorst-Pack grid size.
atoms: Atoms object
Contains unit cell and information about boundary conditions.
kptdensity: float
Required k-point density. Default value is 3.5 point per Ang^-1.
even: bool
Round up to even numbers.
"""
recipcell = atoms.cell.reciprocal()
kpts = []
for i in range(3):
if atoms.pbc[i]:
k = 2 * pi * sqrt((recipcell[i]**2).sum()) * kptdensity
if even:
kpts.append(2 * int(np.ceil(k / 2)))
else:
kpts.append(int(np.ceil(k)))
else:
kpts.append(1)
return np.array(kpts)
def kpts2mp(atoms, kpts, even=False):
if kpts is None:
return np.array([1, 1, 1])
if isinstance(kpts, (float, int)):
return kptdensity2monkhorstpack(atoms, kpts, even)
else:
return kpts
def kpts2sizeandoffsets(size=None, density=None, gamma=None, even=None,
atoms=None):
"""Helper function for selecting k-points.
Use either size or density.
size: 3 ints
Number of k-points.
density: float
K-point density in units of k-points per Ang^-1.
gamma: None or bool
Should the Gamma-point be included? Yes / no / don't care:
True / False / None.
even: None or bool
Should the number of k-points be even? Yes / no / don't care:
True / False / None.
atoms: Atoms object
Needed for calculating k-point density.
"""
if size is not None and density is not None:
raise ValueError('Cannot specify k-point mesh size and '
'density simultaneously')
elif density is not None and atoms is None:
raise ValueError('Cannot set k-points from "density" unless '
'Atoms are provided (need BZ dimensions).')
if size is None:
if density is None:
size = [1, 1, 1]
else:
size = kptdensity2monkhorstpack(atoms, density, None)
# Not using the rounding from kptdensity2monkhorstpack as it doesn't do
# rounding to odd numbers
if even is not None:
size = np.array(size)
remainder = size % 2
if even:
size += remainder
else: # Round up to odd numbers
size += (1 - remainder)
offsets = [0, 0, 0]
if atoms is None:
pbc = [True, True, True]
else:
pbc = atoms.pbc
if gamma is not None:
for i, s in enumerate(size):
if pbc[i] and s % 2 != bool(gamma):
offsets[i] = 0.5 / s
return size, offsets
@jsonable('kpoints')
class KPoints:
def __init__(self, kpts=None):
if kpts is None:
kpts = np.zeros((1, 3))
self.kpts = kpts
def todict(self):
return vars(self)
def kpts2kpts(kpts, atoms=None):
from ase.dft.kpoints import monkhorst_pack
if kpts is None:
return KPoints()
if hasattr(kpts, 'kpts'):
return kpts
if isinstance(kpts, dict):
if 'kpts' in kpts:
return KPoints(kpts['kpts'])
if 'path' in kpts:
cell = Cell.ascell(atoms.cell)
return cell.bandpath(pbc=atoms.pbc, **kpts)
size, offsets = kpts2sizeandoffsets(atoms=atoms, **kpts)
return KPoints(monkhorst_pack(size) + offsets)
if isinstance(kpts[0], int):
return KPoints(monkhorst_pack(kpts))
return KPoints(np.array(kpts))
def kpts2ndarray(kpts, atoms=None):
"""Convert kpts keyword to 2-d ndarray of scaled k-points."""
return kpts2kpts(kpts, atoms=atoms).kpts
class EigenvalOccupationMixin:
"""Define 'eigenvalues' and 'occupations' properties on class.
eigenvalues and occupations will be arrays of shape (spin, kpts, nbands).
Classes must implement the old-fashioned get_eigenvalues and
get_occupations methods."""
@property
def eigenvalues(self):
return self.build_eig_occ_array(self.get_eigenvalues)
@property
def occupations(self):
return self.build_eig_occ_array(self.get_occupation_numbers)
def build_eig_occ_array(self, getter):
nspins = self.get_number_of_spins()
nkpts = len(self.get_ibz_k_points())
nbands = self.get_number_of_bands()
arr = np.zeros((nspins, nkpts, nbands))
for s in range(nspins):
for k in range(nkpts):
arr[s, k, :] = getter(spin=s, kpt=k)
return arr
class Parameters(dict):
"""Dictionary for parameters.
Special feature: If param is a Parameters instance, then param.xc
is a shorthand for param['xc'].
"""
def __getattr__(self, key):
if key not in self:
return dict.__getattribute__(self, key)
return self[key]
def __setattr__(self, key, value):
self[key] = value
@classmethod
def read(cls, filename):
"""Read parameters from file."""
# We use ast to evaluate literals, avoiding eval()
# for security reasons.
import ast
with open(filename) as fd:
txt = fd.read().strip()
assert txt.startswith('dict(')
assert txt.endswith(')')
txt = txt[5:-1]
# The tostring() representation "dict(...)" is not actually
# a literal, so we manually parse that along with the other
# formatting that we did manually:
dct = {}
for line in txt.splitlines():
key, val = line.split('=', 1)
key = key.strip()
val = val.strip()
if val[-1] == ',':
val = val[:-1]
dct[key] = ast.literal_eval(val)
parameters = cls(dct)
return parameters
def tostring(self):
keys = sorted(self)
return 'dict(' + ',\n '.join(
'{}={!r}'.format(key, self[key]) for key in keys) + ')\n'
def write(self, filename):
pathlib.Path(filename).write_text(self.tostring())
[docs]class Calculator(GetPropertiesMixin):
"""Base-class for all ASE calculators.
A calculator must raise PropertyNotImplementedError if asked for a
property that it can't calculate. So, if calculation of the
stress tensor has not been implemented, get_stress(atoms) should
raise PropertyNotImplementedError. This can be achieved simply by not
including the string 'stress' in the list implemented_properties
which is a class member. These are the names of the standard
properties: 'energy', 'forces', 'stress', 'dipole', 'charges',
'magmom' and 'magmoms'.
"""
implemented_properties: List[str] = []
'Properties calculator can handle (energy, forces, ...)'
default_parameters: Dict[str, Any] = {}
'Default parameters'
ignored_changes: Set[str] = set()
'Properties of Atoms which we ignore for the purposes of cache '
'invalidation with check_state().'
discard_results_on_any_change = False
'Whether we purge the results following any change in the set() method. '
'Most (file I/O) calculators will probably want this.'
_deprecated = object()
def __init__(self, restart=None, ignore_bad_restart_file=_deprecated,
label=None, atoms=None, directory='.',
**kwargs):
"""Basic calculator implementation.
restart: str
Prefix for restart file. May contain a directory. Default
is None: don't restart.
ignore_bad_restart_file: bool
Deprecated, please do not use.
Passing more than one positional argument to Calculator()
is deprecated and will stop working in the future.
Ignore broken or missing restart file. By default, it is an
error if the restart file is missing or broken.
directory: str or PurePath
Working directory in which to read and write files and
perform calculations.
label: str
Name used for all files. Not supported by all calculators.
May contain a directory, but please use the directory parameter
for that instead.
atoms: Atoms object
Optional Atoms object to which the calculator will be
attached. When restarting, atoms will get its positions and
unit-cell updated from file.
"""
self.atoms = None # copy of atoms object from last calculation
self.results = {} # calculated properties (energy, forces, ...)
self.parameters = None # calculational parameters
self._directory = None # Initialize
if ignore_bad_restart_file is self._deprecated:
ignore_bad_restart_file = False
else:
warnings.warn(FutureWarning(
'The keyword "ignore_bad_restart_file" is deprecated and '
'will be removed in a future version of ASE. Passing more '
'than one positional argument to Calculator is also '
'deprecated and will stop functioning in the future. '
'Please pass arguments by keyword (key=value) except '
'optionally the "restart" keyword.'
))
if restart is not None:
try:
self.read(restart) # read parameters, atoms and results
except ReadError:
if ignore_bad_restart_file:
self.reset()
else:
raise
self.directory = directory
self.prefix = None
if label is not None:
if self.directory == '.' and '/' in label:
# We specified directory in label, and nothing in the diretory key
self.label = label
elif '/' not in label:
# We specified our directory in the directory keyword
# or not at all
self.label = '/'.join((self.directory, label))
else:
raise ValueError('Directory redundantly specified though '
'directory="{}" and label="{}". '
'Please omit "/" in label.'
.format(self.directory, label))
if self.parameters is None:
# Use default parameters if they were not read from file:
self.parameters = self.get_default_parameters()
if atoms is not None:
atoms.calc = self
if self.atoms is not None:
# Atoms were read from file. Update atoms:
if not (equal(atoms.numbers, self.atoms.numbers) and
(atoms.pbc == self.atoms.pbc).all()):
raise CalculatorError('Atoms not compatible with file')
atoms.positions = self.atoms.positions
atoms.cell = self.atoms.cell
self.set(**kwargs)
if not hasattr(self, 'name'):
self.name = self.__class__.__name__.lower()
if not hasattr(self, 'get_spin_polarized'):
self.get_spin_polarized = self._deprecated_get_spin_polarized
@property
def directory(self) -> str:
return self._directory
@directory.setter
def directory(self, directory: Union[str, pathlib.PurePath]):
self._directory = str(pathlib.Path(directory)) # Normalize path.
@property
def label(self):
if self.directory == '.':
return self.prefix
# Generally, label ~ directory/prefix
#
# We use '/' rather than os.pathsep because
# 1) directory/prefix does not represent any actual path
# 2) We want the same string to work the same on all platforms
if self.prefix is None:
return self.directory + '/'
return '{}/{}'.format(self.directory, self.prefix)
@label.setter
def label(self, label):
if label is None:
self.directory = '.'
self.prefix = None
return
tokens = label.rsplit('/', 1)
if len(tokens) == 2:
directory, prefix = tokens
else:
assert len(tokens) == 1
directory = '.'
prefix = tokens[0]
if prefix == '':
prefix = None
self.directory = directory
self.prefix = prefix
[docs] def set_label(self, label):
"""Set label and convert label to directory and prefix.
Examples:
* label='abc': (directory='.', prefix='abc')
* label='dir1/abc': (directory='dir1', prefix='abc')
* label=None: (directory='.', prefix=None)
"""
self.label = label
def get_default_parameters(self):
return Parameters(copy.deepcopy(self.default_parameters))
def todict(self, skip_default=True):
defaults = self.get_default_parameters()
dct = {}
for key, value in self.parameters.items():
if hasattr(value, 'todict'):
value = value.todict()
if skip_default:
default = defaults.get(key, '_no_default_')
if default != '_no_default_' and equal(value, default):
continue
dct[key] = value
return dct
[docs] def reset(self):
"""Clear all information from old calculation."""
self.atoms = None
self.results = {}
[docs] def read(self, label):
"""Read atoms, parameters and calculated properties from output file.
Read result from self.label file. Raise ReadError if the file
is not there. If the file is corrupted or contains an error
message from the calculation, a ReadError should also be
raised. In case of succes, these attributes must set:
atoms: Atoms object
The state of the atoms from last calculation.
parameters: Parameters object
The parameter dictionary.
results: dict
Calculated properties like energy and forces.
The FileIOCalculator.read() method will typically read atoms
and parameters and get the results dict by calling the
read_results() method."""
self.set_label(label)
def get_atoms(self):
if self.atoms is None:
raise ValueError('Calculator has no atoms')
atoms = self.atoms.copy()
atoms.calc = self
return atoms
@classmethod
def read_atoms(cls, restart, **kwargs):
return cls(restart=restart, label=restart, **kwargs).get_atoms()
[docs] def set(self, **kwargs):
"""Set parameters like set(key1=value1, key2=value2, ...).
A dictionary containing the parameters that have been changed
is returned.
Subclasses must implement a set() method that will look at the
chaneged parameters and decide if a call to reset() is needed.
If the changed parameters are harmless, like a change in
verbosity, then there is no need to call reset().
The special keyword 'parameters' can be used to read
parameters from a file."""
if 'parameters' in kwargs:
filename = kwargs.pop('parameters')
parameters = Parameters.read(filename)
parameters.update(kwargs)
kwargs = parameters
changed_parameters = {}
for key, value in kwargs.items():
oldvalue = self.parameters.get(key)
if key not in self.parameters or not equal(value, oldvalue):
changed_parameters[key] = value
self.parameters[key] = value
if self.discard_results_on_any_change and changed_parameters:
self.reset()
return changed_parameters
[docs] def check_state(self, atoms, tol=1e-15):
"""Check for any system changes since last calculation."""
return compare_atoms(self.atoms, atoms, tol=tol,
excluded_properties=set(self.ignored_changes))
def get_potential_energy(self, atoms=None, force_consistent=False):
energy = self.get_property('energy', atoms)
if force_consistent:
if 'free_energy' not in self.results:
name = self.__class__.__name__
# XXX but we don't know why the energy is not there.
# We should raise PropertyNotPresent. Discuss
raise PropertyNotImplementedError(
'Force consistent/free energy ("free_energy") '
'not provided by {0} calculator'.format(name))
return self.results['free_energy']
else:
return energy
[docs] def get_property(self, name, atoms=None, allow_calculation=True):
if name not in self.implemented_properties:
raise PropertyNotImplementedError('{} property not implemented'
.format(name))
if atoms is None:
atoms = self.atoms
system_changes = []
else:
system_changes = self.check_state(atoms)
if system_changes:
self.reset()
if name not in self.results:
if not allow_calculation:
return None
self.calculate(atoms, [name], system_changes)
if name not in self.results:
# For some reason the calculator was not able to do what we want,
# and that is OK.
raise PropertyNotImplementedError('{} not present in this '
'calculation'.format(name))
result = self.results[name]
if isinstance(result, np.ndarray):
result = result.copy()
return result
def calculation_required(self, atoms, properties):
assert not isinstance(properties, str)
system_changes = self.check_state(atoms)
if system_changes:
return True
for name in properties:
if name not in self.results:
return True
return False
[docs] def calculate(self, atoms=None, properties=['energy'],
system_changes=all_changes):
"""Do the calculation.
properties: list of str
List of what needs to be calculated. Can be any combination
of 'energy', 'forces', 'stress', 'dipole', 'charges', 'magmom'
and 'magmoms'.
system_changes: list of str
List of what has changed since last calculation. Can be
any combination of these six: 'positions', 'numbers', 'cell',
'pbc', 'initial_charges' and 'initial_magmoms'.
Subclasses need to implement this, but can ignore properties
and system_changes if they want. Calculated properties should
be inserted into results dictionary like shown in this dummy
example::
self.results = {'energy': 0.0,
'forces': np.zeros((len(atoms), 3)),
'stress': np.zeros(6),
'dipole': np.zeros(3),
'charges': np.zeros(len(atoms)),
'magmom': 0.0,
'magmoms': np.zeros(len(atoms))}
The subclass implementation should first call this
implementation to set the atoms attribute and create any missing
directories.
"""
if atoms is not None:
self.atoms = atoms.copy()
if not os.path.isdir(self._directory):
os.makedirs(self._directory)
[docs] def calculate_numerical_forces(self, atoms, d=0.001):
"""Calculate numerical forces using finite difference.
All atoms will be displaced by +d and -d in all directions."""
from ase.calculators.test import numeric_force
return np.array([[numeric_force(atoms, a, i, d)
for i in range(3)] for a in range(len(atoms))])
[docs] def calculate_numerical_stress(self, atoms, d=1e-6, voigt=True):
"""Calculate numerical stress using finite difference."""
stress = np.zeros((3, 3), dtype=float)
cell = atoms.cell.copy()
V = atoms.get_volume()
for i in range(3):
x = np.eye(3)
x[i, i] += d
atoms.set_cell(np.dot(cell, x), scale_atoms=True)
eplus = atoms.get_potential_energy(force_consistent=True)
x[i, i] -= 2 * d
atoms.set_cell(np.dot(cell, x), scale_atoms=True)
eminus = atoms.get_potential_energy(force_consistent=True)
stress[i, i] = (eplus - eminus) / (2 * d * V)
x[i, i] += d
j = i - 2
x[i, j] = d
x[j, i] = d
atoms.set_cell(np.dot(cell, x), scale_atoms=True)
eplus = atoms.get_potential_energy(force_consistent=True)
x[i, j] = -d
x[j, i] = -d
atoms.set_cell(np.dot(cell, x), scale_atoms=True)
eminus = atoms.get_potential_energy(force_consistent=True)
stress[i, j] = (eplus - eminus) / (4 * d * V)
stress[j, i] = stress[i, j]
atoms.set_cell(cell, scale_atoms=True)
if voigt:
return stress.flat[[0, 4, 8, 5, 2, 1]]
else:
return stress
def _deprecated_get_spin_polarized(self):
msg = ('This calculator does not implement get_spin_polarized(). '
'In the future, calc.get_spin_polarized() will work only on '
'calculator classes that explicitly implement this method or '
'inherit the method via specialized subclasses.')
warnings.warn(msg, FutureWarning)
return False
[docs] def band_structure(self):
"""Create band-structure object for plotting."""
from ase.spectrum.band_structure import get_band_structure
# XXX This calculator is supposed to just have done a band structure
# calculation, but the calculator may not have the correct Fermi level
# if it updated the Fermi level after changing k-points.
# This will be a problem with some calculators (currently GPAW), and
# the user would have to override this by providing the Fermi level
# from the selfconsistent calculation.
return get_band_structure(calc=self)
[docs] def calculate_properties(self, atoms, properties):
"""This method is experimental; currently for internal use."""
for name in properties:
if name not in all_outputs:
raise ValueError(f'No such property: {name}')
# We ignore system changes for now.
self.calculate(atoms, properties, system_changes=all_changes)
props = self.export_properties()
for name in properties:
if name not in props:
raise PropertyNotPresent(name)
return props
def export_properties(self):
return Properties(self.results)
[docs]class FileIOCalculator(Calculator):
"""Base class for calculators that write/read input/output files."""
command: Optional[str] = None
'Command used to start calculation'
def __init__(self, restart=None,
ignore_bad_restart_file=Calculator._deprecated,
label=None, atoms=None, command=None, **kwargs):
"""File-IO calculator.
command: str
Command used to start calculation.
"""
Calculator.__init__(self, restart, ignore_bad_restart_file, label,
atoms, **kwargs)
if command is not None:
self.command = command
else:
name = 'ASE_' + self.name.upper() + '_COMMAND'
self.command = os.environ.get(name, self.command)
[docs] def calculate(self, atoms=None, properties=['energy'],
system_changes=all_changes):
Calculator.calculate(self, atoms, properties, system_changes)
self.write_input(self.atoms, properties, system_changes)
if self.command is None:
raise CalculatorSetupError(
'Please set ${} environment variable '
.format('ASE_' + self.name.upper() + '_COMMAND') +
'or supply the command keyword')
command = self.command
if 'PREFIX' in command:
command = command.replace('PREFIX', self.prefix)
try:
proc = subprocess.Popen(command, shell=True, cwd=self.directory)
except OSError as err:
# Actually this may never happen with shell=True, since
# probably the shell launches successfully. But we soon want
# to allow calling the subprocess directly, and then this
# distinction (failed to launch vs failed to run) is useful.
msg = 'Failed to execute "{}"'.format(command)
raise EnvironmentError(msg) from err
errorcode = proc.wait()
if errorcode:
path = os.path.abspath(self.directory)
msg = ('Calculator "{}" failed with command "{}" failed in '
'{} with error code {}'.format(self.name, command,
path, errorcode))
raise CalculationFailed(msg)
self.read_results()
[docs] def read_results(self):
"""Read energy, forces, ... from output file(s)."""
pass