"""
This module provides the :class:`ClusterSpace` class.
"""
import os
import copy
import itertools
import pickle
import tarfile
import tempfile
from collections.abc import Iterable
from math import log10, floor
from typing import Dict, List, Union, Tuple
import numpy as np
import spglib
from _icet import ClusterSpace as _ClusterSpace
from ase import Atoms
from ase.io import read as ase_read
from ase.io import write as ase_write
from icet.core.orbit_list import OrbitList
from icet.core.structure import Structure
from icet.core.sublattices import Sublattices
from icet.tools.geometry import (ase_atoms_to_spglib_cell,
get_occupied_primitive_structure)
from pandas import DataFrame
[docs]
class ClusterSpace(_ClusterSpace):
"""This class provides functionality for generating and maintaining
cluster spaces.
Note
----
In :program:`icet` all :class:`Atoms <ase.Atoms>` objects must have
periodic boundary conditions. When constructing cluster expansions
for surfaces and nanoparticles it is therefore recommended to
surround the structure with vacuum and use periodic boundary
conditions. This can be achieved by using :func:`Atoms.center <ase.Atoms.center>`.
Parameters
----------
structure
Atomic structure.
cutoffs
Cutoff radii per order that define the cluster space.
Cutoffs are specified in units of Ångstrom and refer to the
longest distance between two atoms in the cluster. The first
element refers to pairs, the second to triplets, the third
to quadruplets, and so on. :attr:`cutoffs=[7.0, 4.5]` thus implies
that all pairs distanced 7 Å or less will be included,
as well as all triplets among which the longest distance is no
longer than 4.5 Å.
chemical_symbols
List of chemical symbols, each of which must map to an element
of the periodic table.
If a list of chemical symbols is provided, all sites on the
lattice will have the same allowed occupations as the input
list.
If a list of list of chemical symbols is provided then the
outer list must be the same length as the :attr:`structure` object and
:attr:`chemical_symbols[i]` will correspond to the allowed species
on lattice site ``i``.
symprec
Tolerance imposed when analyzing the symmetry using spglib.
position_tolerance
Tolerance applied when comparing positions in Cartesian coordinates.
Examples
--------
The following snippets illustrate several common situations::
>>> from ase.build import bulk
>>> from ase.io import read
>>> from icet import ClusterSpace
>>> # AgPd alloy with pairs up to 7.0 A and triplets up to 4.5 A
>>> prim = bulk('Ag')
>>> cs = ClusterSpace(structure=prim, cutoffs=[7.0, 4.5],
... chemical_symbols=[['Ag', 'Pd']])
>>> print(cs)
>>> # (Mg,Zn)O alloy on rocksalt lattice with pairs up to 8.0 A
>>> prim = bulk('MgO', crystalstructure='rocksalt', a=6.0)
>>> cs = ClusterSpace(structure=prim, cutoffs=[8.0],
... chemical_symbols=[['Mg', 'Zn'], ['O']])
>>> print(cs)
>>> # (Ga,Al)(As,Sb) alloy with pairs, triplets, and quadruplets
>>> prim = bulk('GaAs', crystalstructure='zincblende', a=6.5)
>>> cs = ClusterSpace(structure=prim, cutoffs=[7.0, 6.0, 5.0],
... chemical_symbols=[['Ga', 'Al'], ['As', 'Sb']])
>>> print(cs)
>>> # PdCuAu alloy with pairs and triplets
>>> prim = bulk('Pd')
>>> cs = ClusterSpace(structure=prim, cutoffs=[7.0, 5.0],
... chemical_symbols=[['Au', 'Cu', 'Pd']])
>>> print(cs)
"""
def __init__(self,
structure: Atoms,
cutoffs: List[float],
chemical_symbols: Union[List[str], List[List[str]]],
symprec: float = 1e-5,
position_tolerance: float = None) -> None:
if not isinstance(structure, Atoms):
raise TypeError('Input configuration must be an ASE Atoms object'
f', not type {type(structure)}.')
if not all(structure.pbc):
raise ValueError('Input structure must be periodic.')
if symprec <= 0:
raise ValueError('symprec must be a positive number.')
self._config = {'symprec': symprec}
self._cutoffs = cutoffs.copy()
self._input_structure = structure.copy()
self._input_chemical_symbols = copy.deepcopy(chemical_symbols)
chemical_symbols = self._get_chemical_symbols()
self._pruning_history: List[tuple] = []
# set up primitive
occupied_primitive, primitive_chemical_symbols = get_occupied_primitive_structure(
self._input_structure, chemical_symbols, symprec=self.symprec)
self._primitive_chemical_symbols = primitive_chemical_symbols
assert len(occupied_primitive) == len(primitive_chemical_symbols)
# derived tolerances
if position_tolerance is None:
self._config['position_tolerance'] = symprec
else:
if position_tolerance <= 0:
raise ValueError('position_tolerance must be a positive number')
self._config['position_tolerance'] = position_tolerance
effective_box_size = abs(np.linalg.det(occupied_primitive.cell)) ** (1 / 3)
tol = self.position_tolerance / effective_box_size
tol = min(tol, self._config['position_tolerance'] / 5)
self._config['fractional_position_tolerance'] = round(tol, -int(floor(log10(abs(tol)))))
# set up orbit list
self._orbit_list = OrbitList(
structure=occupied_primitive,
cutoffs=self._cutoffs,
chemical_symbols=self._primitive_chemical_symbols,
symprec=self.symprec,
position_tolerance=self.position_tolerance,
fractional_position_tolerance=self.fractional_position_tolerance)
self._orbit_list.remove_orbits_with_inactive_sites()
# call (base) C++ constructor
_ClusterSpace.__init__(self,
orbit_list=self._orbit_list,
position_tolerance=self.position_tolerance,
fractional_position_tolerance=self.fractional_position_tolerance)
def _get_chemical_symbols(self):
""" Returns chemical symbols using input structure and
chemical symbols. Carries out multiple sanity checks. """
# setup chemical symbols as List[List[str]]
if all(isinstance(i, str) for i in self._input_chemical_symbols):
chemical_symbols = [self._input_chemical_symbols] * len(self._input_structure)
# also accept tuples and other iterables but not, e.g., List[List, str]
# (need to check for str explicitly here because str is an Iterable)
elif not all(isinstance(i, Iterable) and not isinstance(i, str)
for i in self._input_chemical_symbols):
raise TypeError('chemical_symbols must be List[str] or List[List[str]], not {}'.format(
type(self._input_chemical_symbols)))
elif len(self._input_chemical_symbols) != len(self._input_structure):
msg = 'chemical_symbols must have same length as structure. '
msg += 'len(chemical_symbols) = {}, len(structure)= {}'.format(
len(self._input_chemical_symbols), len(self._input_structure))
raise ValueError(msg)
else:
chemical_symbols = copy.deepcopy(self._input_chemical_symbols)
for i, symbols in enumerate(chemical_symbols):
if len(symbols) != len(set(symbols)):
raise ValueError(
'Found duplicates of allowed chemical symbols on site {}.'
' allowed species on site {}= {}'.format(i, i, symbols))
if len([tuple(sorted(s)) for s in chemical_symbols if len(s) > 1]) == 0:
raise ValueError('No active sites found')
return chemical_symbols
def _get_chemical_symbol_representation(self):
"""Returns a str version of the chemical symbols that is
easier on the eyes.
"""
sublattices = self.get_sublattices(self.primitive_structure)
nice_str = []
for sublattice in sublattices.active_sublattices:
sublattice_symbol = sublattice.symbol
nice_str.append('{} (sublattice {})'.format(
list(sublattice.chemical_symbols), sublattice_symbol))
return ', '.join(nice_str)
def _get_string_representation(self,
print_threshold: int = None,
print_minimum: int = 10) -> str:
"""
String representation of the cluster space that provides an overview of
the orbits (order, radius, multiplicity etc) that constitute the space.
Parameters
----------
print_threshold
if the number of orbits exceeds this number print dots
print_minimum
number of lines printed from the top and the bottom of the orbit
list if `print_threshold` is exceeded
Returns
-------
multi-line string
string representation of the cluster space.
"""
def repr_orbit(orbit, header=False):
formats = {'order': '{:2}',
'radius': '{:8.4f}',
'multiplicity': '{:4}',
'index': '{:4}',
'orbit_index': '{:4}',
'multicomponent_vector': '{:}',
'sublattices': '{:}'}
s = []
for name, value in orbit.items():
if name == 'sublattices':
str_repr = formats[name].format('-'.join(value))
else:
str_repr = formats[name].format(value)
n = max(len(name), len(str_repr))
if header:
s += ['{s:^{n}}'.format(s=name, n=n)]
else:
s += ['{s:^{n}}'.format(s=str_repr, n=n)]
return ' | '.join(s)
# basic information
# (use largest orbit to obtain maximum line length)
prototype_orbit = self.as_list[-1]
width = len(repr_orbit(prototype_orbit))
s = []
s += ['{s:=^{n}}'.format(s=' Cluster Space ', n=width)]
s += [' {:38} : {}'.format('space group', self.space_group)]
s += [' {:38} : {}'
.format('chemical species', self._get_chemical_symbol_representation())]
s += [' {:38} : {}'.format('cutoffs',
' '.join(['{:.4f}'.format(c) for c in self.cutoffs]))]
s += [' {:38} : {}'.format('total number of parameters', len(self))]
t = ['{}= {}'.format(k, c)
for k, c in self.number_of_orbits_by_order.items()]
s += [' {:38} : {}'.format('number of parameters by order', ' '.join(t))]
for key, value in sorted(self._config.items()):
s += [' {:38} : {}'.format(key, value)]
# table header
s += [''.center(width, '-')]
s += [repr_orbit(prototype_orbit, header=True)]
s += [''.center(width, '-')]
# table body
index = 0
orbit_list_info = self.as_list
while index < len(orbit_list_info):
if (print_threshold is not None and
len(self) > print_threshold and
index >= print_minimum and
index <= len(self) - print_minimum):
index = len(self) - print_minimum
s += [' ...']
s += [repr_orbit(orbit_list_info[index])]
index += 1
s += [''.center(width, '=')]
return '\n'.join(s)
def __str__(self) -> str:
""" String representation. """
return self._get_string_representation(print_threshold=50)
def _repr_html_(self) -> str:
""" HTML representation. Used, e.g., in jupyter notebooks. """
s = ['<h4>Cluster Space</h4>']
s += ['<table border="1" class="dataframe">']
s += ['<thead><tr><th style="text-align: left;">Field</th><th>Value</th></tr></thead>']
s += ['<tbody>']
s += [f'<tr><td style="text-align: left;">Space group</td><td>{self.space_group}</td></tr>']
for sl in self.get_sublattices(self.primitive_structure).active_sublattices:
s += [f'<tr><td style="text-align: left;">Sublattice {sl.symbol}</td>'
f'<td>{sl.chemical_symbols}</td></tr>']
s += [f'<tr><td style="text-align: left;">Cutoffs</td><td>{self.cutoffs}</td></tr>']
s += ['<tr><td style="text-align: left;">Total number of parameters</td>'
f'<td>{len(self)}</td></tr>']
for k, n in self.number_of_orbits_by_order.items():
s += [f'<tr><td style="text-align: left;">Number of parameters of order {k}</td>'
f'<td>{n}</td></tr>']
for key, value in sorted(self._config.items()):
s += [f'<tr><td style="text-align: left;">{key}</td><td>{value}</td></tr>']
s += ['</tbody>']
s += ['</table>']
return ''.join(s)
def __repr__(self) -> str:
""" Representation. """
s = type(self).__name__ + '('
s += f'structure={self.primitive_structure.__repr__()}'
s += f', cutoffs={self._cutoffs.__repr__()}'
s += f', chemical_symbols={self._input_chemical_symbols.__repr__()}'
s += f', position_tolerance={self._config["position_tolerance"]}'
s += ')'
return s
@property
def symprec(self) -> float:
""" Tolerance imposed when analyzing the symmetry using spglib. """
return self._config['symprec']
@property
def position_tolerance(self) -> float:
""" Tolerance applied when comparing positions in Cartesian coordinates. """
return self._config['position_tolerance']
@property
def fractional_position_tolerance(self) -> float:
""" Tolerance applied when comparing positions in fractional coordinates. """
return self._config['fractional_position_tolerance']
@property
def space_group(self) -> str:
""" Space group of the primitive structure in international notion (via spglib). """
structure_as_tuple = ase_atoms_to_spglib_cell(self.primitive_structure)
return spglib.get_spacegroup(structure_as_tuple, symprec=self._config['symprec'])
@property
def as_list(self) -> List[dict]:
"""Representation of cluster space as list with information regarding
order, radius, multiplicity etc.
"""
data = []
zerolet = dict(
index=0,
order=0,
radius=0,
multiplicity=1,
orbit_index=-1,
multicomponent_vector='.',
sublattices='.',
)
data.append(zerolet)
sublattices = self.get_sublattices(self.primitive_structure)
index = 0
for orbit_index in range(len(self.orbit_list)):
orbit = self.orbit_list.get_orbit(orbit_index)
representative_cluster = orbit.representative_cluster
orbit_sublattices = [
sublattices[sublattices.get_sublattice_index_from_site_index(ls.index)].symbol
for ls in representative_cluster.lattice_sites]
for cv_element in orbit.cluster_vector_elements:
index += 1
data.append(dict(
index=index,
order=representative_cluster.order,
radius=representative_cluster.radius,
multiplicity=cv_element['multiplicity'],
orbit_index=orbit_index,
multicomponent_vector=cv_element['multicomponent_vector'],
sublattices=orbit_sublattices
))
return data
[docs]
def to_dataframe(self) -> DataFrame:
""" Returns a representation of the cluster space as a DataFrame. """
df = DataFrame.from_dict(self.as_list)
del df['index']
return df
@property
def number_of_orbits_by_order(self) -> dict:
""" Number of orbits by order in the form of a dictionary
where keys and values represent order and number of orbits,
respectively.
"""
count_orbits: Dict[int, int] = {}
for orbit in self.as_list:
k = orbit['order']
count_orbits[k] = count_orbits.get(k, 0) + 1
return dict(sorted(count_orbits.items()))
[docs]
def get_cluster_vector(self, structure: Atoms) -> np.ndarray:
"""
Returns the cluster vector for a structure.
Parameters
----------
structure
Atomic configuration.
"""
if not isinstance(structure, Atoms):
raise TypeError('Input structure must be an ASE Atoms object')
try:
cv = _ClusterSpace.get_cluster_vector(
self,
structure=Structure.from_atoms(structure),
fractional_position_tolerance=self.fractional_position_tolerance)
except Exception as e:
self.assert_structure_compatibility(structure)
raise Exception(str(e))
return cv
[docs]
def get_coordinates_of_representative_cluster(self, orbit_index: int) -> List[Tuple[float]]:
"""
Returns the positions of the sites in the representative cluster of the selected orbit.
Parameters
----------
orbit_index
Index of the orbit for which to return the positions of the sites.
"""
# Raise exception if chosen orbit index not in current list of orbit indices
if orbit_index not in range(len(self._orbit_list)):
raise ValueError('The input orbit index is not in the list of possible values.')
return self._orbit_list.get_orbit(orbit_index).representative_cluster.positions
def _remove_orbits(self, indices: List[int]) -> None:
"""
Removes orbits.
Parameters
----------
indices
Indices to all orbits to be removed.
"""
size_before = len(self._orbit_list)
# Since we remove orbits, orbit indices will change,
# so we run over the orbits in reverse order.
for ind in reversed(sorted(indices)):
self._orbit_list.remove_orbit(ind)
size_after = len(self._orbit_list)
assert size_before - len(indices) == size_after
def _prune_orbit_list(self, indices: List[int]) -> None:
"""
Prunes the internal orbit list and maintains the history.
Parameters
----------
indices
Indices to all orbits to be removed.
"""
self._remove_orbits(indices)
self._pruning_history.append(('prune', indices))
@property
def primitive_structure(self) -> Atoms:
""" Primitive structure on which cluster space is based. """
structure = self._get_primitive_structure().to_atoms()
# Decorate with the "real" symbols (instead of H, He, Li etc)
for atom, symbols in zip(structure, self._primitive_chemical_symbols):
atom.symbol = min(symbols)
return structure
@property
def chemical_symbols(self) -> List[List[str]]:
""" Species identified by their chemical symbols. """
return self._primitive_chemical_symbols.copy()
@property
def cutoffs(self) -> List[float]:
"""
Cutoffs for different n-body clusters. The cutoff radius (in
Ångstroms) defines the largest interatomic distance in a
cluster.
"""
return self._cutoffs
@property
def orbit_list(self):
""" Orbit list that defines the cluster in the cluster space. """
return self._orbit_list
[docs]
def get_possible_orbit_occupations(self, orbit_index: int) -> List[List[str]]:
""" Returns possible occupations of the orbit.
Parameters
----------
orbit_index
Index of orbit of interest.
"""
orbit = self.orbit_list.orbits[orbit_index]
indices = [ls.index for ls in orbit.representative_cluster.lattice_sites]
allowed_species = [self.chemical_symbols[index] for index in indices]
return list(itertools.product(*allowed_species))
[docs]
def get_sublattices(self, structure: Atoms) -> Sublattices:
""" Returns the sublattices of the input structure.
Parameters
----------
structure
Atomic structure the sublattices are based on.
"""
sl = Sublattices(self.chemical_symbols,
self.primitive_structure,
structure,
fractional_position_tolerance=self.fractional_position_tolerance)
return sl
[docs]
def assert_structure_compatibility(self, structure: Atoms, vol_tol: float = 1e-5) -> None:
""" Raises error if structure is not compatible with this cluster space.
Parameters
----------
structure
Structure to check for compatibility with cluster space.
vol_tol
Tolerance imposed when comparing volumes.
"""
# check volume
vol1 = self.primitive_structure.get_volume() / len(self.primitive_structure)
vol2 = structure.get_volume() / len(structure)
if abs(vol1 - vol2) > vol_tol:
raise ValueError(f'Volume per atom of structure ({vol1}) does not match the volume of'
f' the primitive structure ({vol2}; vol_tol= {vol_tol}).')
# check occupations
sublattices = self.get_sublattices(structure)
sublattices.assert_occupation_is_allowed(structure.get_chemical_symbols())
# check pbc
if not all(structure.pbc):
raise ValueError('Input structure must be periodic.')
[docs]
def merge_orbits(self,
equivalent_orbits: Dict[int, List[int]],
ignore_permutations: bool = False) -> None:
""" Combines several orbits into one. This allows one to make custom
cluster spaces by manually declaring the clusters in two or more
orbits to be equivalent. This is a powerful approach for simplifying
the cluster spaces of low-dimensional structures such as
surfaces or nanoparticles.
The procedure works in principle for any number of components. Note,
however, that in the case of more than two components the outcome of
the merging procedure inherits the treatment of the multi-component
vectors of the orbit chosen as the representative one.
Parameters
----------
equivalent_orbits
The keys of this dictionary denote the indices of the orbit into
which to merge. The values are the indices of the orbits that are
supposed to be merged into the orbit denoted by the key.
ignore_permutations
If ``True`` orbits will be merged even if their multi-component
vectors and/or site permutations differ. While the object will
still be functional, the cluster space may not be properly spanned
by the resulting cluster vectors.
Note
----
The orbit index should not be confused with the index shown when
printing the cluster space.
Examples
--------
The following snippet illustrates the use of this method to create a
cluster space for a (111) FCC surface, in which only the singlets for
the first and second layer are distinct as well as the in-plane pair
interaction in the topmost layer. All other singlets and pairs are
respectively merged into one orbit. After merging there aree only 3
singlets and 2 pairs left with correspondingly higher multiplicities.
>>> from icet import ClusterSpace
>>> from ase.build import fcc111
>>>
>>> # Create primitive surface unit cell
>>> structure = fcc111('Au', size=(1, 1, 8), a=4.1, vacuum=10, periodic=True)
>>>
>>> # Set up initial cluster space
>>> cs = ClusterSpace(structure=structure, cutoffs=[3.8], chemical_symbols=['Au', 'Ag'])
>>>
>>> # At this point, one can inspect the orbits in the cluster space by printing the
>>> # ClusterSpace object and accessing the individial orbits.
>>> # There will be 4 singlets and 8 pairs.
>>>
>>> # Merge singlets for the third and fourth layers as well as all pairs except for
>>> # the one corresponding to the in-plane interaction in the topmost surface
>>> # layer.
>>> cs.merge_orbits({2: [3], 4: [6, 7, 8, 9, 10, 11]})
"""
self._pruning_history.append(('merge', equivalent_orbits))
orbits_to_delete = []
for k1, orbit_indices in equivalent_orbits.items():
orbit1 = self.orbit_list.get_orbit(k1)
for k2 in orbit_indices:
# sanity checks
if k1 == k2:
raise ValueError(f'Cannot merge orbit {k1} with itself.')
if k2 in orbits_to_delete:
raise ValueError(f'Orbit {k2} cannot be merged into orbit {k1}'
' since it was already merged with another orbit.')
orbit2 = self.orbit_list.get_orbit(k2)
if orbit1.order != orbit2.order:
raise ValueError(f'The order of orbit {k1} ({orbit1.order}) does not'
f' match the order of orbit {k2} ({orbit2.order}).')
if not ignore_permutations:
# compare site permutations
permutations1 = [el['site_permutations']
for el in orbit1.cluster_vector_elements]
permutations2 = [el['site_permutations']
for el in orbit2.cluster_vector_elements]
for vec_group1, vec_group2 in zip(permutations1, permutations2):
if len(vec_group1) != len(vec_group2) or \
not np.allclose(np.array(vec_group1), np.array(vec_group2)):
raise ValueError(f'Orbit {k1} and orbit {k2} have different '
'site permutations.')
# compare multi-component vectors (maybe this is redundant because
# site permutations always differ if multi-component vectors differ?)
mc_vectors1 = [el['multicomponent_vector']
for el in orbit1.cluster_vector_elements]
mc_vectors2 = [el['multicomponent_vector']
for el in orbit2.cluster_vector_elements]
if not all(np.allclose(vec1, vec2)
for vec1, vec2 in zip(mc_vectors1, mc_vectors2)):
raise ValueError(f'Orbit {k1} and orbit {k2} have different '
'multi-component vectors.')
# merge
self._merge_orbit(k1, k2)
orbits_to_delete.append(k2)
# update merge/prune history
self._remove_orbits(orbits_to_delete)
[docs]
def is_supercell_self_interacting(self, structure: Atoms) -> bool:
"""
Checks whether a structure has self-interactions via periodic
boundary conditions.
Returns ``True`` if the structure contains self-interactions via periodic
boundary conditions, otherwise ``False``.
Parameters
----------
structure
Structure to be tested.
"""
ol = self.orbit_list.get_supercell_orbit_list(
structure=structure,
fractional_position_tolerance=self.fractional_position_tolerance)
orbit_indices = set()
for orbit in ol.orbits:
for cluster in orbit.clusters:
indices = tuple(sorted([site.index for site in cluster.lattice_sites]))
if indices in orbit_indices:
return True
else:
orbit_indices.add(indices)
return False
[docs]
def write(self, filename: str) -> None:
"""
Saves cluster space to a file.
Parameters
---------
filename
Name of file to which to write.
"""
with tarfile.open(name=filename, mode='w') as tar_file:
# write items
items = dict(cutoffs=self._cutoffs,
chemical_symbols=self._input_chemical_symbols,
pruning_history=self._pruning_history,
symprec=self.symprec,
position_tolerance=self.position_tolerance)
temp_file = tempfile.TemporaryFile()
pickle.dump(items, temp_file)
temp_file.seek(0)
tar_info = tar_file.gettarinfo(arcname='items', fileobj=temp_file)
tar_file.addfile(tar_info, temp_file)
temp_file.close()
# write structure
temp_file = tempfile.NamedTemporaryFile(delete=False)
temp_file.close()
ase_write(temp_file.name, self._input_structure, format='json')
with open(temp_file.name, 'rb') as tt:
tar_info = tar_file.gettarinfo(arcname='atoms', fileobj=tt)
tar_file.addfile(tar_info, tt)
os.remove(temp_file.name)
[docs]
@staticmethod
def read(filename: str):
"""
Reads cluster space from file and returns :attr:`ClusterSpace` object.
Parameters
---------
filename
Name of file from which to read cluster space.
"""
if isinstance(filename, str):
tar_file = tarfile.open(mode='r', name=filename)
else:
tar_file = tarfile.open(mode='r', fileobj=filename)
# read items
items = pickle.load(tar_file.extractfile('items'))
# read structure
temp_file = tempfile.NamedTemporaryFile(delete=False)
temp_file.write(tar_file.extractfile('atoms').read())
temp_file.close()
structure = ase_read(temp_file.name, format='json')
os.remove(temp_file.name)
tar_file.close()
# ensure backward compatibility
if 'symprec' not in items: # pragma: no cover
items['symprec'] = 1e-5
if 'position_tolerance' not in items: # pragma: no cover
items['position_tolerance'] = items['symprec']
cs = ClusterSpace(structure=structure,
cutoffs=items['cutoffs'],
chemical_symbols=items['chemical_symbols'],
symprec=items['symprec'],
position_tolerance=items['position_tolerance'])
if len(items['pruning_history']) > 0:
if isinstance(items['pruning_history'][0], tuple):
for key, value in items['pruning_history']:
if key == 'prune':
cs._prune_orbit_list(value)
elif key == 'merge':
# It is safe to ignore permutations here because otherwise
# the orbits could not have been merged in the first place.
cs.merge_orbits(value, ignore_permutations=True)
else: # for backwards compatibility
for value in items['pruning_history']:
cs._prune_orbit_list(value)
return cs
[docs]
def copy(self):
""" Returns copy of :class:`ClusterSpace` instance. """
cs_copy = ClusterSpace(structure=self._input_structure,
cutoffs=self.cutoffs,
chemical_symbols=self._input_chemical_symbols,
symprec=self.symprec,
position_tolerance=self.position_tolerance)
for key, value in self._pruning_history:
if key == 'prune':
cs_copy._prune_orbit_list(value)
elif key == 'merge':
# It is safe to ignore permutations here because otherwise
# the orbits could not have been merged in the first place.
cs_copy.merge_orbits(value, ignore_permutations=True)
return cs_copy