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A series of Python3 script to lower the barrier of computing and simulating molecular and material systems.
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CMMDE/lib/cmmde_atoms.py

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# Copyright 2008, 2009 CAMd
# (see accompanying license files for details).
"""Definition of the Atoms class.
This module defines the central object in the ASE package: the Atoms
object.
"""
import copy
import numbers
from math import cos, sin, pi
import numpy as np
import cmmde_units as units
from cmmde_unit import Atom
from cmmde_cell import Cell
from cmmde_stress import voigt_6_to_full_3x3_stress, full_3x3_to_voigt_6_stress
from ase.data import atomic_masses, atomic_masses_common
from ase.geometry import (wrap_positions, find_mic, get_angles, get_distances,
get_dihedrals)
from ase.symbols import Symbols, symbols2numbers
from ase.utils import deprecated
class Atoms:
"""Atoms object.
The Atoms object can represent an isolated molecule, or a
periodically repeated structure. It has a unit cell and
there may be periodic boundary conditions along any of the three
unit cell axes.
Information about the atoms (atomic numbers and position) is
stored in ndarrays. Optionally, there can be information about
tags, momenta, masses, magnetic moments and charges.
In order to calculate energies, forces and stresses, a calculator
object has to attached to the atoms object.
Parameters:
symbols: str (formula) or list of str
Can be a string formula, a list of symbols or a list of
Atom objects. Examples: 'H2O', 'COPt12', ['H', 'H', 'O'],
[Atom('Ne', (x, y, z)), ...].
positions: list of xyz-positions
Atomic positions. Anything that can be converted to an
ndarray of shape (n, 3) will do: [(x1,y1,z1), (x2,y2,z2),
...].
scaled_positions: list of scaled-positions
Like positions, but given in units of the unit cell.
Can not be set at the same time as positions.
numbers: list of int
Atomic numbers (use only one of symbols/numbers).
tags: list of int
Special purpose tags.
momenta: list of xyz-momenta
Momenta for all atoms.
masses: list of float
Atomic masses in atomic units.
magmoms: list of float or list of xyz-values
Magnetic moments. Can be either a single value for each atom
for collinear calculations or three numbers for each atom for
non-collinear calculations.
charges: list of float
Initial atomic charges.
cell: 3x3 matrix or length 3 or 6 vector
Unit cell vectors. Can also be given as just three
numbers for orthorhombic cells, or 6 numbers, where
first three are lengths of unit cell vectors, and the
other three are angles between them (in degrees), in following order:
[len(a), len(b), len(c), angle(b,c), angle(a,c), angle(a,b)].
First vector will lie in x-direction, second in xy-plane,
and the third one in z-positive subspace.
Default value: [0, 0, 0].
celldisp: Vector
Unit cell displacement vector. To visualize a displaced cell
around the center of mass of a Systems of atoms. Default value
= (0,0,0)
pbc: one or three bool
Periodic boundary conditions flags. Examples: True,
False, 0, 1, (1, 1, 0), (True, False, False). Default
value: False.
constraint: constraint object(s)
Used for applying one or more constraints during structure
optimization.
calculator: calculator object
Used to attach a calculator for calculating energies and atomic
forces.
info: dict of key-value pairs
Dictionary of key-value pairs with additional information
about the system. The following keys may be used by ase:
- spacegroup: Spacegroup instance
- unit_cell: 'conventional' | 'primitive' | int | 3 ints
- adsorbate_info: Information about special adsorption sites
Items in the info attribute survives copy and slicing and can
be stored in and retrieved from trajectory files given that the
key is a string, the value is JSON-compatible and, if the value is a
user-defined object, its base class is importable. One should
not make any assumptions about the existence of keys.
Examples:
These three are equivalent:
>>> d = 1.104 # N2 bondlength
>>> a = Atoms('N2', [(0, 0, 0), (0, 0, d)])
>>> a = Atoms(numbers=[7, 7], positions=[(0, 0, 0), (0, 0, d)])
>>> a = Atoms([Atom('N', (0, 0, 0)), Atom('N', (0, 0, d))])
FCC gold:
>>> a = 4.05 # Gold lattice constant
>>> b = a / 2
>>> fcc = Atoms('Au',
... cell=[(0, b, b), (b, 0, b), (b, b, 0)],
... pbc=True)
Hydrogen wire:
>>> d = 0.9 # H-H distance
>>> h = Atoms('H', positions=[(0, 0, 0)],
... cell=(d, 0, 0),
... pbc=(1, 0, 0))
"""
ase_objtype = 'atoms' # For JSONability
def __init__(self, symbols=None,
positions=None, numbers=None,
tags=None, momenta=None, masses=None,
magmoms=None, charges=None,
scaled_positions=None,
cell=None, pbc=None, celldisp=None,
constraint=None,
calculator=None,
info=None,
velocities=None):
self._cellobj = Cell.new()
self._pbc = np.zeros(3, bool)
atoms = None
if hasattr(symbols, 'get_positions'):
atoms = symbols
symbols = None
elif (isinstance(symbols, (list, tuple)) and
len(symbols) > 0 and isinstance(symbols[0], Atom)):
# Get data from a list or tuple of Atom objects:
data = [[atom.get_raw(name) for atom in symbols]
for name in
['position', 'number', 'tag', 'momentum',
'mass', 'magmom', 'charge']]
atoms = self.__class__(None, *data)
symbols = None
if atoms is not None:
# Get data from another Atoms object:
if scaled_positions is not None:
raise NotImplementedError
if symbols is None and numbers is None:
numbers = atoms.get_atomic_numbers()
if positions is None:
positions = atoms.get_positions()
if tags is None and atoms.has('tags'):
tags = atoms.get_tags()
if momenta is None and atoms.has('momenta'):
momenta = atoms.get_momenta()
if magmoms is None and atoms.has('initial_magmoms'):
magmoms = atoms.get_initial_magnetic_moments()
if masses is None and atoms.has('masses'):
masses = atoms.get_masses()
if charges is None and atoms.has('initial_charges'):
charges = atoms.get_initial_charges()
if cell is None:
cell = atoms.get_cell()
if celldisp is None:
celldisp = atoms.get_celldisp()
if pbc is None:
pbc = atoms.get_pbc()
if constraint is None:
constraint = [c.copy() for c in atoms.constraints]
if calculator is None:
calculator = atoms.calc
if info is None:
info = copy.deepcopy(atoms.info)
self.arrays = {}
if symbols is None:
if numbers is None:
if positions is not None:
natoms = len(positions)
elif scaled_positions is not None:
natoms = len(scaled_positions)
else:
natoms = 0
numbers = np.zeros(natoms, int)
self.new_array('numbers', numbers, int)
else:
if numbers is not None:
raise TypeError(
'Use only one of "symbols" and "numbers".')
else:
self.new_array('numbers', symbols2numbers(symbols), int)
if self.numbers.ndim != 1:
raise ValueError('"numbers" must be 1-dimensional.')
if cell is None:
cell = np.zeros((3, 3))
self.set_cell(cell)
if celldisp is None:
celldisp = np.zeros(shape=(3, 1))
self.set_celldisp(celldisp)
if positions is None:
if scaled_positions is None:
positions = np.zeros((len(self.arrays['numbers']), 3))
else:
assert self.cell.rank == 3
positions = np.dot(scaled_positions, self.cell)
else:
if scaled_positions is not None:
raise TypeError(
'Use only one of "symbols" and "numbers".')
self.new_array('positions', positions, float, (3,))
self.set_constraint(constraint)
self.set_tags(default(tags, 0))
self.set_masses(default(masses, None))
self.set_initial_magnetic_moments(default(magmoms, 0.0))
self.set_initial_charges(default(charges, 0.0))
if pbc is None:
pbc = False
self.set_pbc(pbc)
self.set_momenta(default(momenta, (0.0, 0.0, 0.0)),
apply_constraint=False)
if velocities is not None:
if momenta is None:
self.set_velocities(velocities)
else:
raise TypeError(
'Use only one of "momenta" and "velocities".')
if info is None:
self.info = {}
else:
self.info = dict(info)
self.calc = calculator
@property
def symbols(self):
"""Get chemical symbols as a :class:`ase.symbols.Symbols` object.
The object works like ``atoms.numbers`` except its values
are strings. It supports in-place editing."""
return Symbols(self.numbers)
@symbols.setter
def symbols(self, obj):
new_symbols = Symbols.fromsymbols(obj)
self.numbers[:] = new_symbols.numbers
@deprecated(DeprecationWarning('Please use atoms.calc = calc'))
def set_calculator(self, calc=None):
"""Attach calculator object.
Please use the equivalent atoms.calc = calc instead of this
method."""
self.calc = calc
@deprecated(DeprecationWarning('Please use atoms.calc'))
def get_calculator(self):
"""Get currently attached calculator object.
Please use the equivalent atoms.calc instead of
atoms.get_calculator()."""
return self.calc
@property
def calc(self):
"""Calculator object."""
return self._calc
@calc.setter
def calc(self, calc):
self._calc = calc
if hasattr(calc, 'set_atoms'):
calc.set_atoms(self)
@calc.deleter # type: ignore
@deprecated(DeprecationWarning('Please use atoms.calc = None'))
def calc(self):
self._calc = None
@property # type: ignore
@deprecated('Please use atoms.cell.rank instead')
def number_of_lattice_vectors(self):
"""Number of (non-zero) lattice vectors."""
return self.cell.rank
def set_constraint(self, constraint=None):
"""Apply one or more constrains.
The *constraint* argument must be one constraint object or a
list of constraint objects."""
if constraint is None:
self._constraints = []
else:
if isinstance(constraint, list):
self._constraints = constraint
elif isinstance(constraint, tuple):
self._constraints = list(constraint)
else:
self._constraints = [constraint]
def _get_constraints(self):
return self._constraints
def _del_constraints(self):
self._constraints = []
constraints = property(_get_constraints, set_constraint, _del_constraints,
'Constraints of the atoms.')
def set_cell(self, cell, scale_atoms=False, apply_constraint=True):
"""Set unit cell vectors.
Parameters:
cell: 3x3 matrix or length 3 or 6 vector
Unit cell. A 3x3 matrix (the three unit cell vectors) or
just three numbers for an orthorhombic cell. Another option is
6 numbers, which describes unit cell with lengths of unit cell
vectors and with angles between them (in degrees), in following
order: [len(a), len(b), len(c), angle(b,c), angle(a,c),
angle(a,b)]. First vector will lie in x-direction, second in
xy-plane, and the third one in z-positive subspace.
scale_atoms: bool
Fix atomic positions or move atoms with the unit cell?
Default behavior is to *not* move the atoms (scale_atoms=False).
apply_constraint: bool
Whether to apply constraints to the given cell.
Examples:
Two equivalent ways to define an orthorhombic cell:
>>> atoms = Atoms('He')
>>> a, b, c = 7, 7.5, 8
>>> atoms.set_cell([a, b, c])
>>> atoms.set_cell([(a, 0, 0), (0, b, 0), (0, 0, c)])
FCC unit cell:
>>> atoms.set_cell([(0, b, b), (b, 0, b), (b, b, 0)])
Hexagonal unit cell:
>>> atoms.set_cell([a, a, c, 90, 90, 120])
Rhombohedral unit cell:
>>> alpha = 77
>>> atoms.set_cell([a, a, a, alpha, alpha, alpha])
"""
# Override pbcs if and only if given a Cell object:
cell = Cell.new(cell)
# XXX not working well during initialize due to missing _constraints
if apply_constraint and hasattr(self, '_constraints'):
for constraint in self.constraints:
if hasattr(constraint, 'adjust_cell'):
constraint.adjust_cell(self, cell)
if scale_atoms:
M = np.linalg.solve(self.cell.complete(), cell.complete())
self.positions[:] = np.dot(self.positions, M)
self.cell[:] = cell
def set_celldisp(self, celldisp):
"""Set the unit cell displacement vectors."""
celldisp = np.array(celldisp, float)
self._celldisp = celldisp
def get_celldisp(self):
"""Get the unit cell displacement vectors."""
return self._celldisp.copy()
def get_cell(self, complete=False):
"""Get the three unit cell vectors as a `class`:ase.cell.Cell` object.
The Cell object resembles a 3x3 ndarray, and cell[i, j]
is the jth Cartesian coordinate of the ith cell vector."""
if complete:
cell = self.cell.complete()
else:
cell = self.cell.copy()
return cell
@deprecated('Please use atoms.cell.cellpar() instead')
def get_cell_lengths_and_angles(self):
"""Get unit cell parameters. Sequence of 6 numbers.
First three are unit cell vector lengths and second three
are angles between them::
[len(a), len(b), len(c), angle(b,c), angle(a,c), angle(a,b)]
in degrees.
"""
return self.cell.cellpar()
@deprecated('Please use atoms.cell.reciprocal()')
def get_reciprocal_cell(self):
"""Get the three reciprocal lattice vectors as a 3x3 ndarray.
Note that the commonly used factor of 2 pi for Fourier
transforms is not included here."""
return self.cell.reciprocal()
@property
def pbc(self):
"""Reference to pbc-flags for in-place manipulations."""
return self._pbc
@pbc.setter
def pbc(self, pbc):
self._pbc[:] = pbc
def set_pbc(self, pbc):
"""Set periodic boundary condition flags."""
self.pbc = pbc
def get_pbc(self):
"""Get periodic boundary condition flags."""
return self.pbc.copy()
def new_array(self, name, a, dtype=None, shape=None):
"""Add new array.
If *shape* is not *None*, the shape of *a* will be checked."""
if dtype is not None:
a = np.array(a, dtype, order='C')
if len(a) == 0 and shape is not None:
a.shape = (-1,) + shape
else:
if not a.flags['C_CONTIGUOUS']:
a = np.ascontiguousarray(a)
else:
a = a.copy()
if name in self.arrays:
raise RuntimeError('Array {} already present'.format(name))
for b in self.arrays.values():
if len(a) != len(b):
raise ValueError('Array "%s" has wrong length: %d != %d.' %
(name, len(a), len(b)))
break
if shape is not None and a.shape[1:] != shape:
raise ValueError('Array "%s" has wrong shape %s != %s.' %
(name, a.shape, (a.shape[0:1] + shape)))
self.arrays[name] = a
def get_array(self, name, copy=True):
"""Get an array.
Returns a copy unless the optional argument copy is false.
"""
if copy:
return self.arrays[name].copy()
else:
return self.arrays[name]
def set_array(self, name, a, dtype=None, shape=None):
"""Update array.
If *shape* is not *None*, the shape of *a* will be checked.
If *a* is *None*, then the array is deleted."""
b = self.arrays.get(name)
if b is None:
if a is not None:
self.new_array(name, a, dtype, shape)
else:
if a is None:
del self.arrays[name]
else:
a = np.asarray(a)
if a.shape != b.shape:
raise ValueError('Array "%s" has wrong shape %s != %s.' %
(name, a.shape, b.shape))
b[:] = a
def has(self, name):
"""Check for existence of array.
name must be one of: 'tags', 'momenta', 'masses', 'initial_magmoms',
'initial_charges'."""
# XXX extend has to calculator properties
return name in self.arrays
def set_atomic_numbers(self, numbers):
"""Set atomic numbers."""
self.set_array('numbers', numbers, int, ())
def get_atomic_numbers(self):
"""Get integer array of atomic numbers."""
return self.arrays['numbers'].copy()
def get_chemical_symbols(self):
"""Get list of chemical symbol strings.
Equivalent to ``list(atoms.symbols)``."""
return list(self.symbols)
def set_chemical_symbols(self, symbols):
"""Set chemical symbols."""
self.set_array('numbers', symbols2numbers(symbols), int, ())
def get_chemical_formula(self, mode='hill', empirical=False):
"""Get the chemical formula as a string based on the chemical symbols.
Parameters:
mode: str
There are four different modes available:
'all': The list of chemical symbols are contracted to a string,
e.g. ['C', 'H', 'H', 'H', 'O', 'H'] becomes 'CHHHOH'.
'reduce': The same as 'all' where repeated elements are contracted
to a single symbol and a number, e.g. 'CHHHOCHHH' is reduced to
'CH3OCH3'.
'hill': The list of chemical symbols are contracted to a string
following the Hill notation (alphabetical order with C and H
first), e.g. 'CHHHOCHHH' is reduced to 'C2H6O' and 'SOOHOHO' to
'H2O4S'. This is default.
'metal': The list of chemical symbols (alphabetical metals,
and alphabetical non-metals)
empirical, bool (optional, default=False)
Divide the symbol counts by their greatest common divisor to yield
an empirical formula. Only for mode `metal` and `hill`.
"""
return self.symbols.get_chemical_formula(mode, empirical)
def set_tags(self, tags):
"""Set tags for all atoms. If only one tag is supplied, it is
applied to all atoms."""
if isinstance(tags, int):
tags = [tags] * len(self)
self.set_array('tags', tags, int, ())
def get_tags(self):
"""Get integer array of tags."""
if 'tags' in self.arrays:
return self.arrays['tags'].copy()
else:
return np.zeros(len(self), int)
def set_momenta(self, momenta, apply_constraint=True):
"""Set momenta."""
if (apply_constraint and len(self.constraints) > 0 and
momenta is not None):
momenta = np.array(momenta) # modify a copy
for constraint in self.constraints:
if hasattr(constraint, 'adjust_momenta'):
constraint.adjust_momenta(self, momenta)
self.set_array('momenta', momenta, float, (3,))
def set_velocities(self, velocities):
"""Set the momenta by specifying the velocities."""
self.set_momenta(self.get_masses()[:, np.newaxis] * velocities)
def get_momenta(self):
"""Get array of momenta."""
if 'momenta' in self.arrays:
return self.arrays['momenta'].copy()
else:
return np.zeros((len(self), 3))
def set_masses(self, masses='defaults'):
"""Set atomic masses in atomic mass units.
The array masses should contain a list of masses. In case
the masses argument is not given or for those elements of the
masses list that are None, standard values are set."""
if isinstance(masses, str):
if masses == 'defaults':
masses = atomic_masses[self.arrays['numbers']]
elif masses == 'most_common':
masses = atomic_masses_common[self.arrays['numbers']]
elif masses is None:
pass
elif not isinstance(masses, np.ndarray):
masses = list(masses)
for i, mass in enumerate(masses):
if mass is None:
masses[i] = atomic_masses[self.numbers[i]]
self.set_array('masses', masses, float, ())
def get_masses(self):
"""Get array of masses in atomic mass units."""
if 'masses' in self.arrays:
return self.arrays['masses'].copy()
else:
return atomic_masses[self.arrays['numbers']]
def set_initial_magnetic_moments(self, magmoms=None):
"""Set the initial magnetic moments.
Use either one or three numbers for every atom (collinear
or non-collinear spins)."""
if magmoms is None:
self.set_array('initial_magmoms', None)
else:
magmoms = np.asarray(magmoms)
self.set_array('initial_magmoms', magmoms, float,
magmoms.shape[1:])
def get_initial_magnetic_moments(self):
"""Get array of initial magnetic moments."""
if 'initial_magmoms' in self.arrays:
return self.arrays['initial_magmoms'].copy()
else:
return np.zeros(len(self))
def get_magnetic_moments(self):
"""Get calculated local magnetic moments."""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
return self._calc.get_magnetic_moments(self)
def get_magnetic_moment(self):
"""Get calculated total magnetic moment."""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
return self._calc.get_magnetic_moment(self)
def set_initial_charges(self, charges=None):
"""Set the initial charges."""
if charges is None:
self.set_array('initial_charges', None)
else:
self.set_array('initial_charges', charges, float, ())
def get_initial_charges(self):
"""Get array of initial charges."""
if 'initial_charges' in self.arrays:
return self.arrays['initial_charges'].copy()
else:
return np.zeros(len(self))
def get_charges(self):
"""Get calculated charges."""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
try:
return self._calc.get_charges(self)
except AttributeError:
from ase.calculators.calculator import PropertyNotImplementedError
raise PropertyNotImplementedError
def set_positions(self, newpositions, apply_constraint=True):
"""Set positions, honoring any constraints. To ignore constraints,
use *apply_constraint=False*."""
if self.constraints and apply_constraint:
newpositions = np.array(newpositions, float)
for constraint in self.constraints:
constraint.adjust_positions(self, newpositions)
self.set_array('positions', newpositions, shape=(3,))
def get_positions(self, wrap=False, **wrap_kw):
"""Get array of positions.
Parameters:
wrap: bool
wrap atoms back to the cell before returning positions
wrap_kw: (keyword=value) pairs
optional keywords `pbc`, `center`, `pretty_translation`, `eps`,
see :func:`ase.geometry.wrap_positions`
"""
if wrap:
if 'pbc' not in wrap_kw:
wrap_kw['pbc'] = self.pbc
return wrap_positions(self.positions, self.cell, **wrap_kw)
else:
return self.arrays['positions'].copy()
def get_potential_energy(self, force_consistent=False,
apply_constraint=True):
"""Calculate potential energy.
Ask the attached calculator to calculate the potential energy and
apply constraints. Use *apply_constraint=False* to get the raw
forces.
When supported by the calculator, either the energy extrapolated
to zero Kelvin or the energy consistent with the forces (the free
energy) can be returned.
"""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
if force_consistent:
energy = self._calc.get_potential_energy(
self, force_consistent=force_consistent)
else:
energy = self._calc.get_potential_energy(self)
if apply_constraint:
for constraint in self.constraints:
if hasattr(constraint, 'adjust_potential_energy'):
energy += constraint.adjust_potential_energy(self)
return energy
def get_properties(self, properties):
"""This method is experimental; currently for internal use."""
# XXX Something about constraints.
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
return self._calc.calculate_properties(self, properties)
def get_potential_energies(self):
"""Calculate the potential energies of all the atoms.
Only available with calculators supporting per-atom energies
(e.g. classical potentials).
"""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
return self._calc.get_potential_energies(self)
def get_kinetic_energy(self):
"""Get the kinetic energy."""
momenta = self.arrays.get('momenta')
if momenta is None:
return 0.0
return 0.5 * np.vdot(momenta, self.get_velocities())
def get_velocities(self):
"""Get array of velocities."""
momenta = self.get_momenta()
masses = self.get_masses()
return momenta / masses[:, np.newaxis]
def get_total_energy(self):
"""Get the total energy - potential plus kinetic energy."""
return self.get_potential_energy() + self.get_kinetic_energy()
def get_forces(self, apply_constraint=True, md=False):
"""Calculate atomic forces.
Ask the attached calculator to calculate the forces and apply
constraints. Use *apply_constraint=False* to get the raw
forces.
For molecular dynamics (md=True) we don't apply the constraint
to the forces but to the momenta. When holonomic constraints for
rigid linear triatomic molecules are present, ask the constraints
to redistribute the forces within each triple defined in the
constraints (required for molecular dynamics with this type of
constraints)."""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
forces = self._calc.get_forces(self)
if apply_constraint:
# We need a special md flag here because for MD we want
# to skip real constraints but include special "constraints"
# Like Hookean.
for constraint in self.constraints:
if md and hasattr(constraint, 'redistribute_forces_md'):
constraint.redistribute_forces_md(self, forces)
if not md or hasattr(constraint, 'adjust_potential_energy'):
constraint.adjust_forces(self, forces)
return forces
# Informs calculators (e.g. Asap) that ideal gas contribution is added here.
_ase_handles_dynamic_stress = True
def get_stress(self, voigt=True, apply_constraint=True,
include_ideal_gas=False):
"""Calculate stress tensor.
Returns an array of the six independent components of the
symmetric stress tensor, in the traditional Voigt order
(xx, yy, zz, yz, xz, xy) or as a 3x3 matrix. Default is Voigt
order.
The ideal gas contribution to the stresses is added if the
atoms have momenta and ``include_ideal_gas`` is set to True.
"""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
stress = self._calc.get_stress(self)
shape = stress.shape
if shape == (3, 3):
# Convert to the Voigt form before possibly applying
# constraints and adding the dynamic part of the stress
# (the "ideal gas contribution").
stress = full_3x3_to_voigt_6_stress(stress)
else:
assert shape == (6,)
if apply_constraint:
for constraint in self.constraints:
if hasattr(constraint, 'adjust_stress'):
constraint.adjust_stress(self, stress)
# Add ideal gas contribution, if applicable
if include_ideal_gas and self.has('momenta'):
stresscomp = np.array([[0, 5, 4], [5, 1, 3], [4, 3, 2]])
p = self.get_momenta()
masses = self.get_masses()
invmass = 1.0 / masses
invvol = 1.0 / self.get_volume()
for alpha in range(3):
for beta in range(alpha, 3):
stress[stresscomp[alpha, beta]] -= (
p[:, alpha] * p[:, beta] * invmass).sum() * invvol
if voigt:
return stress
else:
return voigt_6_to_full_3x3_stress(stress)
def get_stresses(self, include_ideal_gas=False, voigt=True):
"""Calculate the stress-tensor of all the atoms.
Only available with calculators supporting per-atom energies and
stresses (e.g. classical potentials). Even for such calculators
there is a certain arbitrariness in defining per-atom stresses.
The ideal gas contribution to the stresses is added if the
atoms have momenta and ``include_ideal_gas`` is set to True.
"""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
stresses = self._calc.get_stresses(self)
# make sure `stresses` are in voigt form
if np.shape(stresses)[1:] == (3, 3):
stresses_voigt = [full_3x3_to_voigt_6_stress(s) for s in stresses]
stresses = np.array(stresses_voigt)
# REMARK: The ideal gas contribution is intensive, i.e., the volume
# is divided out. We currently don't check if `stresses` are intensive
# as well, i.e., if `a.get_stresses.sum(axis=0) == a.get_stress()`.
# It might be good to check this here, but adds computational overhead.
if include_ideal_gas and self.has('momenta'):
stresscomp = np.array([[0, 5, 4], [5, 1, 3], [4, 3, 2]])
if hasattr(self._calc, 'get_atomic_volumes'):
invvol = 1.0 / self._calc.get_atomic_volumes()
else:
invvol = self.get_global_number_of_atoms() / self.get_volume()
p = self.get_momenta()
invmass = 1.0 / self.get_masses()
for alpha in range(3):
for beta in range(alpha, 3):
stresses[:, stresscomp[alpha, beta]] -= (
p[:, alpha] * p[:, beta] * invmass * invvol)
if voigt:
return stresses
else:
stresses_3x3 = [voigt_6_to_full_3x3_stress(s) for s in stresses]
return np.array(stresses_3x3)
def get_dipole_moment(self):
"""Calculate the electric dipole moment for the atoms object.
Only available for calculators which has a get_dipole_moment()
method."""
if self._calc is None:
raise RuntimeError('Atoms object has no calculator.')
return self._calc.get_dipole_moment(self)
def copy(self):
"""Return a copy."""
atoms = self.__class__(cell=self.cell, pbc=self.pbc, info=self.info,
celldisp=self._celldisp.copy())
atoms.arrays = {}
for name, a in self.arrays.items():
atoms.arrays[name] = a.copy()
atoms.constraints = copy.deepcopy(self.constraints)
return atoms
def todict(self):
"""For basic JSON (non-database) support."""
d = dict(self.arrays)
d['cell'] = np.asarray(self.cell)
d['pbc'] = self.pbc
if self._celldisp.any():
d['celldisp'] = self._celldisp
if self.constraints:
d['constraints'] = self.constraints
if self.info:
d['info'] = self.info
# Calculator... trouble.
return d
@classmethod
def fromdict(cls, dct):
"""Rebuild atoms object from dictionary representation (todict)."""
dct = dct.copy()
kw = {}
for name in ['numbers', 'positions', 'cell', 'pbc']:
kw[name] = dct.pop(name)
constraints = dct.pop('constraints', None)
if constraints:
from ase.constraints import dict2constraint
constraints = [dict2constraint(d) for d in constraints]
info = dct.pop('info', None)
atoms = cls(constraint=constraints,
celldisp=dct.pop('celldisp', None),
info=info, **kw)
natoms = len(atoms)
# Some arrays are named differently from the atoms __init__ keywords.
# Also, there may be custom arrays. Hence we set them directly:
for name, arr in dct.items():
assert len(arr) == natoms, name
assert isinstance(arr, np.ndarray)
atoms.arrays[name] = arr
return atoms
def __len__(self):
return len(self.arrays['positions'])
def get_number_of_atoms(self):
"""Deprecated, please do not use.
You probably want len(atoms). Or if your atoms are distributed,
use (and see) get_global_number_of_atoms()."""
import warnings
warnings.warn('Use get_global_number_of_atoms() instead',
np.VisibleDeprecationWarning)
return len(self)
def get_global_number_of_atoms(self):
"""Returns the global number of atoms in a distributed-atoms parallel
simulation.
DO NOT USE UNLESS YOU KNOW WHAT YOU ARE DOING!
Equivalent to len(atoms) in the standard ASE Atoms class. You should
normally use len(atoms) instead. This function's only purpose is to
make compatibility between ASE and Asap easier to maintain by having a
few places in ASE use this function instead. It is typically only
when counting the global number of degrees of freedom or in similar
situations.
"""
return len(self)
def __repr__(self):
tokens = []
N = len(self)
if N <= 60:
symbols = self.get_chemical_formula('reduce')
else:
symbols = self.get_chemical_formula('hill')
tokens.append("symbols='{0}'".format(symbols))
if self.pbc.any() and not self.pbc.all():
tokens.append('pbc={0}'.format(self.pbc.tolist()))
else:
tokens.append('pbc={0}'.format(self.pbc[0]))
cell = self.cell
if cell:
if cell.orthorhombic:
cell = cell.lengths().tolist()
else:
cell = cell.tolist()
tokens.append('cell={0}'.format(cell))
for name in sorted(self.arrays):
if name in ['numbers', 'positions']:
continue
tokens.append('{0}=...'.format(name))
if self.constraints:
if len(self.constraints) == 1:
constraint = self.constraints[0]
else:
constraint = self.constraints
tokens.append('constraint={0}'.format(repr(constraint)))
if self._calc is not None:
tokens.append('calculator={0}(...)'
.format(self._calc.__class__.__name__))
return '{0}({1})'.format(self.__class__.__name__, ', '.join(tokens))
def __add__(self, other):
atoms = self.copy()
atoms += other
return atoms
def extend(self, other):
"""Extend atoms object by appending atoms from *other*."""
if isinstance(other, Atom):
other = self.__class__([other])
n1 = len(self)
n2 = len(other)
for name, a1 in self.arrays.items():
a = np.zeros((n1 + n2,) + a1.shape[1:], a1.dtype)
a[:n1] = a1
if name == 'masses':
a2 = other.get_masses()
else:
a2 = other.arrays.get(name)
if a2 is not None:
a[n1:] = a2
self.arrays[name] = a
for name, a2 in other.arrays.items():
if name in self.arrays:
continue
a = np.empty((n1 + n2,) + a2.shape[1:], a2.dtype)
a[n1:] = a2
if name == 'masses':
a[:n1] = self.get_masses()[:n1]
else:
a[:n1] = 0
self.set_array(name, a)
def __iadd__(self, other):
self.extend(other)
return self
def append(self, atom):
"""Append atom to end."""
self.extend(self.__class__([atom]))
def __iter__(self):
for i in range(len(self)):
yield self[i]
def __getitem__(self, i):
"""Return a subset of the atoms.
i -- scalar integer, list of integers, or slice object
describing which atoms to return.
If i is a scalar, return an Atom object. If i is a list or a
slice, return an Atoms object with the same cell, pbc, and
other associated info as the original Atoms object. The
indices of the constraints will be shuffled so that they match
the indexing in the subset returned.
"""
if isinstance(i, numbers.Integral):
natoms = len(self)
if i < -natoms or i >= natoms:
raise IndexError('Index out of range.')
return Atom(atoms=self, index=i)
elif not isinstance(i, slice):
i = np.array(i)
# if i is a mask
if i.dtype == bool:
if len(i) != len(self):
raise IndexError('Length of mask {} must equal '
'number of atoms {}'
.format(len(i), len(self)))
i = np.arange(len(self))[i]
import copy
conadd = []
# Constraints need to be deepcopied, but only the relevant ones.
for con in copy.deepcopy(self.constraints):
try:
con.index_shuffle(self, i)
except (IndexError, NotImplementedError):
pass
else:
conadd.append(con)
atoms = self.__class__(cell=self.cell, pbc=self.pbc, info=self.info,
# should be communicated to the slice as well
celldisp=self._celldisp)
# TODO: Do we need to shuffle indices in adsorbate_info too?
atoms.arrays = {}
for name, a in self.arrays.items():
atoms.arrays[name] = a[i].copy()
atoms.constraints = conadd
return atoms
def __delitem__(self, i):
from ase.constraints import FixAtoms
for c in self._constraints:
if not isinstance(c, FixAtoms):
raise RuntimeError('Remove constraint using set_constraint() '
'before deleting atoms.')
if isinstance(i, list) and len(i) > 0:
# Make sure a list of booleans will work correctly and not be
# interpreted at 0 and 1 indices.
i = np.array(i)
if len(self._constraints) > 0:
n = len(self)
i = np.arange(n)[i]
if isinstance(i, int):
i = [i]
constraints = []
for c in self._constraints:
c = c.delete_atoms(i, n)
if c is not None:
constraints.append(c)
self.constraints = constraints
mask = np.ones(len(self), bool)
mask[i] = False
for name, a in self.arrays.items():
self.arrays[name] = a[mask]
def pop(self, i=-1):
"""Remove and return atom at index *i* (default last)."""
atom = self[i]
atom.cut_reference_to_atoms()
del self[i]
return atom
def __imul__(self, m):
"""In-place repeat of atoms."""
if isinstance(m, int):
m = (m, m, m)
for x, vec in zip(m, self.cell):
if x != 1 and not vec.any():
raise ValueError('Cannot repeat along undefined lattice '
'vector')
M = np.product(m)
n = len(self)
for name, a in self.arrays.items():
self.arrays[name] = np.tile(a, (M,) + (1,) * (len(a.shape) - 1))
positions = self.arrays['positions']
i0 = 0
for m0 in range(m[0]):
for m1 in range(m[1]):
for m2 in range(m[2]):
i1 = i0 + n
positions[i0:i1] += np.dot((m0, m1, m2), self.cell)
i0 = i1
if self.constraints is not None:
self.constraints = [c.repeat(m, n) for c in self.constraints]
self.cell = np.array([m[c] * self.cell[c] for c in range(3)])
return self
def repeat(self, rep):
"""Create new repeated atoms object.
The *rep* argument should be a sequence of three positive
integers like *(2,3,1)* or a single integer (*r*) equivalent
to *(r,r,r)*."""
atoms = self.copy()
atoms *= rep
return atoms
def __mul__(self, rep):
return self.repeat(rep)
def translate(self, displacement):
"""Translate atomic positions.
The displacement argument can be a float an xyz vector or an
nx3 array (where n is the number of atoms)."""
self.arrays['positions'] += np.array(displacement)
def center(self, vacuum=None, axis=(0, 1, 2), about=None):
"""Center atoms in unit cell.
Centers the atoms in the unit cell, so there is the same
amount of vacuum on all sides.
vacuum: float (default: None)
If specified adjust the amount of vacuum when centering.
If vacuum=10.0 there will thus be 10 Angstrom of vacuum
on each side.
axis: int or sequence of ints
Axis or axes to act on. Default: Act on all axes.
about: float or array (default: None)
If specified, center the atoms about <about>.
I.e., about=(0., 0., 0.) (or just "about=0.", interpreted
identically), to center about the origin.
"""
# Find the orientations of the faces of the unit cell
cell = self.cell.complete()
dirs = np.zeros_like(cell)
lengths = cell.lengths()
for i in range(3):
dirs[i] = np.cross(cell[i - 1], cell[i - 2])
dirs[i] /= np.linalg.norm(dirs[i])
if dirs[i] @ cell[i] < 0.0:
dirs[i] *= -1
if isinstance(axis, int):
axes = (axis,)
else:
axes = axis
# Now, decide how much each basis vector should be made longer
pos = self.positions
longer = np.zeros(3)
shift = np.zeros(3)
for i in axes:
if len(pos):
scalarprod = pos @ dirs[i]
p0 = scalarprod.min()
p1 = scalarprod.max()
else:
p0 = 0
p1 = 0
height = cell[i] @ dirs[i]
if vacuum is not None:
lng = (p1 - p0 + 2 * vacuum) - height
else:
lng = 0.0 # Do not change unit cell size!
top = lng + height - p1
shf = 0.5 * (top - p0)
cosphi = cell[i] @ dirs[i] / lengths[i]
longer[i] = lng / cosphi
shift[i] = shf / cosphi
# Now, do it!
translation = np.zeros(3)
for i in axes:
nowlen = lengths[i]
if vacuum is not None:
self.cell[i] = cell[i] * (1 + longer[i] / nowlen)
translation += shift[i] * cell[i] / nowlen
# We calculated translations using the completed cell,
# so directions without cell vectors will have been centered
# along a "fake" vector of length 1.
# Therefore, we adjust by -0.5:
if not any(self.cell[i]):
translation[i] -= 0.5
# Optionally, translate to center about a point in space.
if about is not None:
for vector in self.cell:
translation -= vector / 2.0
translation += about
self.positions += translation
def get_center_of_mass(self, scaled=False):
"""Get the center of mass.
If scaled=True the center of mass in scaled coordinates
is returned."""
masses = self.get_masses()
com = masses @ self.positions / masses.sum()
if scaled:
return self.cell.scaled_positions(com)
else:
return com
def set_center_of_mass(self, com, scaled=False):
"""Set the center of mass.
If scaled=True the center of mass is expected in scaled coordinates.
Constraints are considered for scaled=False.
"""
old_com = self.get_center_of_mass(scaled=scaled)
difference = old_com - com
if scaled:
self.set_scaled_positions(self.get_scaled_positions() + difference)
else:
self.set_positions(self.get_positions() + difference)
def get_moments_of_inertia(self, vectors=False):
"""Get the moments of inertia along the principal axes.
The three principal moments of inertia are computed from the
eigenvalues of the symmetric inertial tensor. Periodic boundary
conditions are ignored. Units of the moments of inertia are
amu*angstrom**2.
"""
com = self.get_center_of_mass()
positions = self.get_positions()
positions -= com # translate center of mass to origin
masses = self.get_masses()
# Initialize elements of the inertial tensor
I11 = I22 = I33 = I12 = I13 = I23 = 0.0
for i in range(len(self)):
x, y, z = positions[i]
m = masses[i]
I11 += m * (y ** 2 + z ** 2)
I22 += m * (x ** 2 + z ** 2)
I33 += m * (x ** 2 + y ** 2)
I12 += -m * x * y
I13 += -m * x * z
I23 += -m * y * z
I = np.array([[I11, I12, I13],
[I12, I22, I23],
[I13, I23, I33]])
evals, evecs = np.linalg.eigh(I)
if vectors:
return evals, evecs.transpose()
else:
return evals
def get_angular_momentum(self):
"""Get total angular momentum with respect to the center of mass."""
com = self.get_center_of_mass()
positions = self.get_positions()
positions -= com # translate center of mass to origin
return np.cross(positions, self.get_momenta()).sum(0)
def rotate(self, a, v, center=(0, 0, 0), rotate_cell=False):
"""Rotate atoms based on a vector and an angle, or two vectors.
Parameters:
a = None:
Angle that the atoms is rotated around the vector 'v'. 'a'
can also be a vector and then 'a' is rotated
into 'v'.
v:
Vector to rotate the atoms around. Vectors can be given as
strings: 'x', '-x', 'y', ... .
center = (0, 0, 0):
The center is kept fixed under the rotation. Use 'COM' to fix
the center of mass, 'COP' to fix the center of positions or
'COU' to fix the center of cell.
rotate_cell = False:
If true the cell is also rotated.
Examples:
Rotate 90 degrees around the z-axis, so that the x-axis is
rotated into the y-axis:
>>> atoms = Atoms()
>>> atoms.rotate(90, 'z')
>>> atoms.rotate(90, (0, 0, 1))
>>> atoms.rotate(-90, '-z')
>>> atoms.rotate('x', 'y')
>>> atoms.rotate((1, 0, 0), (0, 1, 0))
"""
if not isinstance(a, numbers.Real):
a, v = v, a
norm = np.linalg.norm
v = string2vector(v)
normv = norm(v)
if normv == 0.0:
raise ZeroDivisionError('Cannot rotate: norm(v) == 0')
if isinstance(a, numbers.Real):
a *= pi / 180
v /= normv
c = cos(a)
s = sin(a)
else:
v2 = string2vector(a)
v /= normv
normv2 = np.linalg.norm(v2)
if normv2 == 0:
raise ZeroDivisionError('Cannot rotate: norm(a) == 0')
v2 /= norm(v2)
c = np.dot(v, v2)
v = np.cross(v, v2)
s = norm(v)
# In case *v* and *a* are parallel, np.cross(v, v2) vanish
# and can't be used as a rotation axis. However, in this
# case any rotation axis perpendicular to v2 will do.
eps = 1e-7
if s < eps:
v = np.cross((0, 0, 1), v2)
if norm(v) < eps:
v = np.cross((1, 0, 0), v2)
assert norm(v) >= eps
elif s > 0:
v /= s
center = self._centering_as_array(center)
p = self.arrays['positions'] - center
self.arrays['positions'][:] = (c * p -
np.cross(p, s * v) +
np.outer(np.dot(p, v), (1.0 - c) * v) +
center)
if rotate_cell:
rotcell = self.get_cell()
rotcell[:] = (c * rotcell -
np.cross(rotcell, s * v) +
np.outer(np.dot(rotcell, v), (1.0 - c) * v))
self.set_cell(rotcell)
def _centering_as_array(self, center):
if isinstance(center, str):
if center.lower() == 'com':
center = self.get_center_of_mass()
elif center.lower() == 'cop':
center = self.get_positions().mean(axis=0)
elif center.lower() == 'cou':
center = self.get_cell().sum(axis=0) / 2
else:
raise ValueError('Cannot interpret center')
else:
center = np.array(center, float)
return center
def euler_rotate(self, phi=0.0, theta=0.0, psi=0.0, center=(0, 0, 0)):
"""Rotate atoms via Euler angles (in degrees).
See e.g http://mathworld.wolfram.com/EulerAngles.html for explanation.
Parameters:
center :
The point to rotate about. A sequence of length 3 with the
coordinates, or 'COM' to select the center of mass, 'COP' to
select center of positions or 'COU' to select center of cell.
phi :
The 1st rotation angle around the z axis.
theta :
Rotation around the x axis.
psi :
2nd rotation around the z axis.
"""
center = self._centering_as_array(center)
phi *= pi / 180
theta *= pi / 180
psi *= pi / 180
# First move the molecule to the origin In contrast to MATLAB,
# numpy broadcasts the smaller array to the larger row-wise,
# so there is no need to play with the Kronecker product.
rcoords = self.positions - center
# First Euler rotation about z in matrix form
D = np.array(((cos(phi), sin(phi), 0.),
(-sin(phi), cos(phi), 0.),
(0., 0., 1.)))
# Second Euler rotation about x:
C = np.array(((1., 0., 0.),
(0., cos(theta), sin(theta)),
(0., -sin(theta), cos(theta))))
# Third Euler rotation, 2nd rotation about z:
B = np.array(((cos(psi), sin(psi), 0.),
(-sin(psi), cos(psi), 0.),
(0., 0., 1.)))
# Total Euler rotation
A = np.dot(B, np.dot(C, D))
# Do the rotation
rcoords = np.dot(A, np.transpose(rcoords))
# Move back to the rotation point
self.positions = np.transpose(rcoords) + center
def get_dihedral(self, a0, a1, a2, a3, mic=False):
"""Calculate dihedral angle.
Calculate dihedral angle (in degrees) between the vectors a0->a1
and a2->a3.
Use mic=True to use the Minimum Image Convention and calculate the
angle across periodic boundaries.
"""
return self.get_dihedrals([[a0, a1, a2, a3]], mic=mic)[0]
def get_dihedrals(self, indices, mic=False):
"""Calculate dihedral angles.
Calculate dihedral angles (in degrees) between the list of vectors
a0->a1 and a2->a3, where a0, a1, a2 and a3 are in each row of indices.
Use mic=True to use the Minimum Image Convention and calculate the
angles across periodic boundaries.
"""
indices = np.array(indices)
assert indices.shape[1] == 4
a0s = self.positions[indices[:, 0]]
a1s = self.positions[indices[:, 1]]
a2s = self.positions[indices[:, 2]]
a3s = self.positions[indices[:, 3]]
# vectors 0->1, 1->2, 2->3
v0 = a1s - a0s
v1 = a2s - a1s
v2 = a3s - a2s
cell = None
pbc = None
if mic:
cell = self.cell
pbc = self.pbc
return get_dihedrals(v0, v1, v2, cell=cell, pbc=pbc)
def _masked_rotate(self, center, axis, diff, mask):
# do rotation of subgroup by copying it to temporary atoms object
# and then rotating that
#
# recursive object definition might not be the most elegant thing,
# more generally useful might be a rotation function with a mask?
group = self.__class__()
for i in range(len(self)):
if mask[i]:
group += self[i]
group.translate(-center)
group.rotate(diff * 180 / pi, axis)
group.translate(center)
# set positions in original atoms object
j = 0
for i in range(len(self)):
if mask[i]:
self.positions[i] = group[j].position
j += 1
def set_dihedral(self, a1, a2, a3, a4, angle,
mask=None, indices=None):
"""Set the dihedral angle (degrees) between vectors a1->a2 and
a3->a4 by changing the atom indexed by a4.
If mask is not None, all the atoms described in mask
(read: the entire subgroup) are moved. Alternatively to the mask,
the indices of the atoms to be rotated can be supplied. If both
*mask* and *indices* are given, *indices* overwrites *mask*.
**Important**: If *mask* or *indices* is given and does not contain
*a4*, *a4* will NOT be moved. In most cases you therefore want
to include *a4* in *mask*/*indices*.
Example: the following defines a very crude
ethane-like molecule and twists one half of it by 30 degrees.
>>> atoms = Atoms('HHCCHH', [[-1, 1, 0], [-1, -1, 0], [0, 0, 0],
... [1, 0, 0], [2, 1, 0], [2, -1, 0]])
>>> atoms.set_dihedral(1, 2, 3, 4, 210, mask=[0, 0, 0, 1, 1, 1])
"""
angle *= pi / 180
# if not provided, set mask to the last atom in the
# dihedral description
if mask is None and indices is None:
mask = np.zeros(len(self))
mask[a4] = 1
elif indices is not None:
mask = [index in indices for index in range(len(self))]
# compute necessary in dihedral change, from current value
current = self.get_dihedral(a1, a2, a3, a4) * pi / 180
diff = angle - current
axis = self.positions[a3] - self.positions[a2]
center = self.positions[a3]
self._masked_rotate(center, axis, diff, mask)
def rotate_dihedral(self, a1, a2, a3, a4,
angle=None, mask=None, indices=None):
"""Rotate dihedral angle.
Same usage as in :meth:`ase.Atoms.set_dihedral`: Rotate a group by a
predefined dihedral angle, starting from its current configuration.
"""
start = self.get_dihedral(a1, a2, a3, a4)
self.set_dihedral(a1, a2, a3, a4, angle + start, mask, indices)
def get_angle(self, a1, a2, a3, mic=False):
"""Get angle formed by three atoms.
Calculate angle in degrees between the vectors a2->a1 and
a2->a3.
Use mic=True to use the Minimum Image Convention and calculate the
angle across periodic boundaries.
"""
return self.get_angles([[a1, a2, a3]], mic=mic)[0]
def get_angles(self, indices, mic=False):
"""Get angle formed by three atoms for multiple groupings.
Calculate angle in degrees between vectors between atoms a2->a1
and a2->a3, where a1, a2, and a3 are in each row of indices.
Use mic=True to use the Minimum Image Convention and calculate
the angle across periodic boundaries.
"""
indices = np.array(indices)
assert indices.shape[1] == 3
a1s = self.positions[indices[:, 0]]
a2s = self.positions[indices[:, 1]]
a3s = self.positions[indices[:, 2]]
v12 = a1s - a2s
v32 = a3s - a2s
cell = None
pbc = None
if mic:
cell = self.cell
pbc = self.pbc
return get_angles(v12, v32, cell=cell, pbc=pbc)
def set_angle(self, a1, a2=None, a3=None, angle=None, mask=None,
indices=None, add=False):
"""Set angle (in degrees) formed by three atoms.
Sets the angle between vectors *a2*->*a1* and *a2*->*a3*.
If *add* is `True`, the angle will be changed by the value given.
Same usage as in :meth:`ase.Atoms.set_dihedral`.
If *mask* and *indices*
are given, *indices* overwrites *mask*. If *mask* and *indices*
are not set, only *a3* is moved."""
if any(a is None for a in [a2, a3, angle]):
raise ValueError('a2, a3, and angle must not be None')
# If not provided, set mask to the last atom in the angle description
if mask is None and indices is None:
mask = np.zeros(len(self))
mask[a3] = 1
elif indices is not None:
mask = [index in indices for index in range(len(self))]
if add:
diff = angle
else:
# Compute necessary in angle change, from current value
diff = angle - self.get_angle(a1, a2, a3)
diff *= pi / 180
# Do rotation of subgroup by copying it to temporary atoms object and
# then rotating that
v10 = self.positions[a1] - self.positions[a2]
v12 = self.positions[a3] - self.positions[a2]
v10 /= np.linalg.norm(v10)
v12 /= np.linalg.norm(v12)
axis = np.cross(v10, v12)
center = self.positions[a2]
self._masked_rotate(center, axis, diff, mask)
def rattle(self, stdev=0.001, seed=None, rng=None):
"""Randomly displace atoms.
This method adds random displacements to the atomic positions,
taking a possible constraint into account. The random numbers are
drawn from a normal distribution of standard deviation stdev.
For a parallel calculation, it is important to use the same
seed on all processors! """
if seed is not None and rng is not None:
raise ValueError('Please do not provide both seed and rng.')
if rng is None:
if seed is None:
seed = 42
rng = np.random.RandomState(seed)
positions = self.arrays['positions']
self.set_positions(positions +
rng.normal(scale=stdev, size=positions.shape))
def get_distance(self, a0, a1, mic=False, vector=False):
"""Return distance between two atoms.
Use mic=True to use the Minimum Image Convention.
vector=True gives the distance vector (from a0 to a1).
"""
return self.get_distances(a0, [a1], mic=mic, vector=vector)[0]
def get_distances(self, a, indices, mic=False, vector=False):
"""Return distances of atom No.i with a list of atoms.
Use mic=True to use the Minimum Image Convention.
vector=True gives the distance vector (from a to self[indices]).
"""
R = self.arrays['positions']
p1 = [R[a]]
p2 = R[indices]
cell = None
pbc = None
if mic:
cell = self.cell
pbc = self.pbc
D, D_len = get_distances(p1, p2, cell=cell, pbc=pbc)
if vector:
D.shape = (-1, 3)
return D
else:
D_len.shape = (-1,)
return D_len
def get_all_distances(self, mic=False, vector=False):
"""Return distances of all of the atoms with all of the atoms.
Use mic=True to use the Minimum Image Convention.
"""
R = self.arrays['positions']
cell = None
pbc = None
if mic:
cell = self.cell
pbc = self.pbc
D, D_len = get_distances(R, cell=cell, pbc=pbc)
if vector:
return D
else:
return D_len
def set_distance(self, a0, a1, distance, fix=0.5, mic=False,
mask=None, indices=None, add=False, factor=False):
"""Set the distance between two atoms.
Set the distance between atoms *a0* and *a1* to *distance*.
By default, the center of the two atoms will be fixed. Use
*fix=0* to fix the first atom, *fix=1* to fix the second
atom and *fix=0.5* (default) to fix the center of the bond.
If *mask* or *indices* are set (*mask* overwrites *indices*),
only the atoms defined there are moved
(see :meth:`ase.Atoms.set_dihedral`).
When *add* is true, the distance is changed by the value given.
In combination
with *factor* True, the value given is a factor scaling the distance.
It is assumed that the atoms in *mask*/*indices* move together
with *a1*. If *fix=1*, only *a0* will therefore be moved."""
if a0 % len(self) == a1 % len(self):
raise ValueError('a0 and a1 must not be the same')
if add:
oldDist = self.get_distance(a0, a1, mic=mic)
if factor:
newDist = oldDist * distance
else:
newDist = oldDist + distance
self.set_distance(a0, a1, newDist, fix=fix, mic=mic,
mask=mask, indices=indices, add=False,
factor=False)
return
R = self.arrays['positions']
D = np.array([R[a1] - R[a0]])
if mic:
D, D_len = find_mic(D, self.cell, self.pbc)
else:
D_len = np.array([np.sqrt((D**2).sum())])
x = 1.0 - distance / D_len[0]
if mask is None and indices is None:
indices = [a0, a1]
elif mask:
indices = [i for i in range(len(self)) if mask[i]]
for i in indices:
if i == a0:
R[a0] += (x * fix) * D[0]
else:
R[i] -= (x * (1.0 - fix)) * D[0]
def get_scaled_positions(self, wrap=True):
"""Get positions relative to unit cell.
If wrap is True, atoms outside the unit cell will be wrapped into
the cell in those directions with periodic boundary conditions
so that the scaled coordinates are between zero and one.
If any cell vectors are zero, the corresponding coordinates
are evaluated as if the cell were completed using
``cell.complete()``. This means coordinates will be Cartesian
as long as the non-zero cell vectors span a Cartesian axis or
plane."""
fractional = self.cell.scaled_positions(self.positions)
if wrap:
for i, periodic in enumerate(self.pbc):
if periodic:
# Yes, we need to do it twice.
# See the scaled_positions.py test.
fractional[:, i] %= 1.0
fractional[:, i] %= 1.0
return fractional
def set_scaled_positions(self, scaled):
"""Set positions relative to unit cell."""
self.positions[:] = self.cell.cartesian_positions(scaled)
def wrap(self, **wrap_kw):
"""Wrap positions to unit cell.
Parameters:
wrap_kw: (keyword=value) pairs
optional keywords `pbc`, `center`, `pretty_translation`, `eps`,
see :func:`ase.geometry.wrap_positions`
"""
if 'pbc' not in wrap_kw:
wrap_kw['pbc'] = self.pbc
self.positions[:] = self.get_positions(wrap=True, **wrap_kw)
def get_temperature(self):
"""Get the temperature in Kelvin."""
dof = len(self) * 3
for constraint in self._constraints:
dof -= constraint.get_removed_dof(self)
ekin = self.get_kinetic_energy()
return 2 * ekin / (dof * units.kB)
def __eq__(self, other):
"""Check for identity of two atoms objects.
Identity means: same positions, atomic numbers, unit cell and
periodic boundary conditions."""
if not isinstance(other, Atoms):
return False
a = self.arrays
b = other.arrays
return (len(self) == len(other) and
(a['positions'] == b['positions']).all() and
(a['numbers'] == b['numbers']).all() and
(self.cell == other.cell).all() and
(self.pbc == other.pbc).all())
def __ne__(self, other):
"""Check if two atoms objects are not equal.
Any differences in positions, atomic numbers, unit cell or
periodic boundary condtions make atoms objects not equal.
"""
eq = self.__eq__(other)
if eq is NotImplemented:
return eq
else:
return not eq
# @deprecated('Please use atoms.cell.volume')
# We kind of want to deprecate this, but the ValueError behaviour
# might be desirable. Should we do this?
def get_volume(self):
"""Get volume of unit cell."""
if self.cell.rank != 3:
raise ValueError(
'You have {0} lattice vectors: volume not defined'
.format(self.cell.rank))
return self.cell.volume
def _get_positions(self):
"""Return reference to positions-array for in-place manipulations."""
return self.arrays['positions']
def _set_positions(self, pos):
"""Set positions directly, bypassing constraints."""
self.arrays['positions'][:] = pos
positions = property(_get_positions, _set_positions,
doc='Attribute for direct ' +
'manipulation of the positions.')
def _get_atomic_numbers(self):
"""Return reference to atomic numbers for in-place
manipulations."""
return self.arrays['numbers']
numbers = property(_get_atomic_numbers, set_atomic_numbers,
doc='Attribute for direct ' +
'manipulation of the atomic numbers.')
@property
def cell(self):
"""The :class:`ase.cell.Cell` for direct manipulation."""
return self._cellobj
@cell.setter
def cell(self, cell):
cell = Cell.ascell(cell)
self._cellobj[:] = cell
def write(self, filename, format=None, **kwargs):
"""Write atoms object to a file.
see ase.io.write for formats.
kwargs are passed to ase.io.write.
"""
from ase.io import write
write(filename, self, format, **kwargs)
def iterimages(self):
yield self
def edit(self):
"""Modify atoms interactively through ASE's GUI viewer.
Conflicts leading to undesirable behaviour might arise
when matplotlib has been pre-imported with certain
incompatible backends and while trying to use the
plot feature inside the interactive GUI. To circumvent,
please set matplotlib.use('gtk') before calling this
method.
"""
from ase.gui.images import Images
from ase.gui.gui import GUI
images = Images([self])
gui = GUI(images)
gui.run()
def string2vector(v):
if isinstance(v, str):
if v[0] == '-':
return -string2vector(v[1:])
w = np.zeros(3)
w['xyz'.index(v)] = 1.0
return w
return np.array(v, float)
def default(data, dflt):
"""Helper function for setting default values."""
if data is None:
return None
elif isinstance(data, (list, tuple)):
newdata = []
allnone = True
for x in data:
if x is None:
newdata.append(dflt)
else:
newdata.append(x)
allnone = False
if allnone:
return None
return newdata
else:
return data