Source code for pymatgen.transformations.standard_transformations

# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.

"""
This module defines standard transformations which transforms a structure into
another structure. Standard transformations operate in a structure-wide manner,
rather than site-specific manner.
All transformations should inherit the AbstractTransformation ABC.
"""

import logging

from fractions import Fraction
from typing import Optional, Union

from numpy import around

from pymatgen.analysis.bond_valence import BVAnalyzer
from pymatgen.analysis.structure_matcher import StructureMatcher
from pymatgen.analysis.ewald import EwaldSummation, EwaldMinimizer
from pymatgen.analysis.elasticity.strain import Deformation
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
from pymatgen.core.composition import Composition
from pymatgen.core.operations import SymmOp
from pymatgen.core.periodic_table import get_el_sp
from pymatgen.core.structure import Structure, Lattice
from pymatgen.transformations.site_transformations import \
    PartialRemoveSitesTransformation
from pymatgen.transformations.transformation_abc import AbstractTransformation

__author__ = "Shyue Ping Ong, Will Richards"
__copyright__ = "Copyright 2011, The Materials Project"
__version__ = "1.2"
__maintainer__ = "Shyue Ping Ong"
__email__ = "shyuep@gmail.com"
__date__ = "Sep 23, 2011"

logger = logging.getLogger(__name__)


[docs]class RotationTransformation(AbstractTransformation): """ The RotationTransformation applies a rotation to a structure. """ def __init__(self, axis, angle, angle_in_radians=False): """ Args: axis (3x1 array): Axis of rotation, e.g., [1, 0, 0] angle (float): Angle to rotate angle_in_radians (bool): Set to True if angle is supplied in radians. Else degrees are assumed. """ self.axis = axis self.angle = angle self.angle_in_radians = angle_in_radians self._symmop = SymmOp.from_axis_angle_and_translation( self.axis, self.angle, self.angle_in_radians)
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Rotated Structure. """ s = structure.copy() s.apply_operation(self._symmop) return s
def __str__(self): return "Rotation Transformation about axis " + \ "{} with angle = {:.4f} {}".format( self.axis, self.angle, "radians" if self.angle_in_radians else "degrees") def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: Inverse Transformation. """ return RotationTransformation(self.axis, -self.angle, self.angle_in_radians) @property def is_one_to_many(self): """Returns: False""" return False
[docs]class OxidationStateDecorationTransformation(AbstractTransformation): """ This transformation decorates a structure with oxidation states. """ def __init__(self, oxidation_states): """ Args: oxidation_states (dict): Oxidation states supplied as a dict, e.g., {"Li":1, "O":-2} """ self.oxidation_states = oxidation_states
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Oxidation state decorated Structure. """ s = structure.copy() s.add_oxidation_state_by_element(self.oxidation_states) return s
@property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class AutoOxiStateDecorationTransformation(AbstractTransformation): """ This transformation automatically decorates a structure with oxidation states using a bond valence approach. """ def __init__(self, symm_tol=0.1, max_radius=4, max_permutations=100000, distance_scale_factor=1.015): """ Args: symm_tol (float): Symmetry tolerance used to determine which sites are symmetrically equivalent. Set to 0 to turn off symmetry. max_radius (float): Maximum radius in Angstrom used to find nearest neighbors. max_permutations (int): Maximum number of permutations of oxidation states to test. distance_scale_factor (float): A scale factor to be applied. This is useful for scaling distances, esp in the case of calculation-relaxed structures, which may tend to under (GGA) or over bind (LDA). The default of 1.015 works for GGA. For experimental structure, set this to 1. """ self.symm_tol = symm_tol self.max_radius = max_radius self.max_permutations = max_permutations self.distance_scale_factor = distance_scale_factor self.analyzer = BVAnalyzer(symm_tol, max_radius, max_permutations, distance_scale_factor)
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Oxidation state decorated Structure. """ return self.analyzer.get_oxi_state_decorated_structure(structure)
@property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class OxidationStateRemovalTransformation(AbstractTransformation): """ This transformation removes oxidation states from a structure. """ def __init__(self): """ No arg needed. """ pass
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Non-oxidation state decorated Structure. """ s = structure.copy() s.remove_oxidation_states() return s
@property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class SupercellTransformation(AbstractTransformation): """ The RotationTransformation applies a rotation to a structure. """ def __init__(self, scaling_matrix=((1, 0, 0), (0, 1, 0), (0, 0, 1))): """ Args: scaling_matrix: A matrix of transforming the lattice vectors. Defaults to the identity matrix. Has to be all integers. e.g., [[2,1,0],[0,3,0],[0,0,1]] generates a new structure with lattice vectors a" = 2a + b, b" = 3b, c" = c where a, b, and c are the lattice vectors of the original structure. """ self.scaling_matrix = scaling_matrix
[docs] @staticmethod def from_scaling_factors(scale_a=1, scale_b=1, scale_c=1): """ Convenience method to get a SupercellTransformation from a simple series of three numbers for scaling each lattice vector. Equivalent to calling the normal with [[scale_a, 0, 0], [0, scale_b, 0], [0, 0, scale_c]] Args: scale_a: Scaling factor for lattice direction a. Defaults to 1. scale_b: Scaling factor for lattice direction b. Defaults to 1. scale_c: Scaling factor for lattice direction c. Defaults to 1. Returns: SupercellTransformation. """ return SupercellTransformation([[scale_a, 0, 0], [0, scale_b, 0], [0, 0, scale_c]])
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Supercell Structure. """ return structure * self.scaling_matrix
def __str__(self): return "Supercell Transformation with scaling matrix " + \ "{}".format(self.scaling_matrix) def __repr__(self): return self.__str__() @property def inverse(self): """ Raises: NotImplementedError """ raise NotImplementedError() @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class SubstitutionTransformation(AbstractTransformation): """ This transformation substitutes species for one another. """ def __init__(self, species_map): """ Args: species_map: A dict or list of tuples containing the species mapping in string-string pairs. E.g., {"Li":"Na"} or [("Fe2+","Mn2+")]. Multiple substitutions can be done. Overloaded to accept sp_and_occu dictionary E.g. {"Si: {"Ge":0.75, "C":0.25}}, which substitutes a single species with multiple species to generate a disordered structure. """ self.species_map = species_map self._species_map = dict(species_map) for k, v in self._species_map.items(): if isinstance(v, (tuple, list)): self._species_map[k] = dict(v)
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Substituted Structure. """ species_map = {} for k, v in self._species_map.items(): if isinstance(v, dict): value = {get_el_sp(x): y for x, y in v.items()} else: value = get_el_sp(v) species_map[get_el_sp(k)] = value s = structure.copy() s.replace_species(species_map) return s
def __str__(self): return "Substitution Transformation :" + \ ", ".join([str(k) + "->" + str(v) for k, v in self._species_map.items()]) def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: Inverse Transformation. """ inverse_map = {v: k for k, v in self._species_map.items()} return SubstitutionTransformation(inverse_map) @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class RemoveSpeciesTransformation(AbstractTransformation): """ Remove all occurrences of some species from a structure. """ def __init__(self, species_to_remove): """ Args: species_to_remove: List of species to remove. E.g., ["Li", "Mn"] """ self.species_to_remove = species_to_remove
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Structure with species removed. """ s = structure.copy() for sp in self.species_to_remove: s.remove_species([get_el_sp(sp)]) return s
def __str__(self): return "Remove Species Transformation :" + \ ", ".join(self.species_to_remove) def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class PartialRemoveSpecieTransformation(AbstractTransformation): """ Remove fraction of specie from a structure. Requires an oxidation state decorated structure for ewald sum to be computed. Given that the solution to selecting the right removals is NP-hard, there are several algorithms provided with varying degrees of accuracy and speed. Please see :class:`pymatgen.transformations.site_transformations.PartialRemoveSitesTransformation`. """ ALGO_FAST = 0 ALGO_COMPLETE = 1 ALGO_BEST_FIRST = 2 ALGO_ENUMERATE = 3 def __init__(self, specie_to_remove, fraction_to_remove, algo=ALGO_FAST): """ Args: specie_to_remove: Specie to remove. Must have oxidation state E.g., "Li+" fraction_to_remove: Fraction of specie to remove. E.g., 0.5 algo: This parameter allows you to choose the algorithm to perform ordering. Use one of PartialRemoveSpecieTransformation.ALGO_* variables to set the algo. """ self.specie_to_remove = specie_to_remove self.fraction_to_remove = fraction_to_remove self.algo = algo
[docs] def apply_transformation(self, structure, return_ranked_list=False): """ Apply the transformation. Args: structure: input structure return_ranked_list (bool/int): Boolean stating whether or not multiple structures are returned. If return_ranked_list is an int, that number of structures is returned. Returns: Depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {"structure" = .... , "other_arguments"} the key "transformation" is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class. """ sp = get_el_sp(self.specie_to_remove) specie_indices = [i for i in range(len(structure)) if structure[i].species == Composition({sp: 1})] trans = PartialRemoveSitesTransformation([specie_indices], [self.fraction_to_remove], algo=self.algo) return trans.apply_transformation(structure, return_ranked_list)
@property def is_one_to_many(self): """ Returns: True """ return True def __str__(self): spec_str = ["Species = {}".format(self.specie_to_remove), "Fraction to remove = {}".format(self.fraction_to_remove), "ALGO = {}".format(self.algo)] return "PartialRemoveSpecieTransformation : " + ", ".join(spec_str) def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None
[docs]class OrderDisorderedStructureTransformation(AbstractTransformation): """ Order a disordered structure. The disordered structure must be oxidation state decorated for ewald sum to be computed. No attempt is made to perform symmetry determination to reduce the number of combinations. Hence, attempting to performing ordering on a large number of disordered sites may be extremely expensive. The time scales approximately with the number of possible combinations. The algorithm can currently compute approximately 5,000,000 permutations per minute. Also, simple rounding of the occupancies are performed, with no attempt made to achieve a target composition. This is usually not a problem for most ordering problems, but there can be times where rounding errors may result in structures that do not have the desired composition. This second step will be implemented in the next iteration of the code. If multiple fractions for a single species are found for different sites, these will be treated separately if the difference is above a threshold tolerance. currently this is .1 For example, if a fraction of .25 Li is on sites 0,1,2,3 and .5 on sites 4, 5, 6, 7 then 1 site from [0,1,2,3] will be filled and 2 sites from [4,5,6,7] will be filled, even though a lower energy combination might be found by putting all lithium in sites [4,5,6,7]. USE WITH CARE. """ ALGO_FAST = 0 ALGO_COMPLETE = 1 ALGO_BEST_FIRST = 2 def __init__(self, algo=ALGO_FAST, symmetrized_structures=False, no_oxi_states=False): """ Args: algo (int): Algorithm to use. symmetrized_structures (bool): Whether the input structures are instances of SymmetrizedStructure, and that their symmetry should be used for the grouping of sites. no_oxi_states (bool): Whether to remove oxidation states prior to ordering. """ self.algo = algo self._all_structures = [] self.no_oxi_states = no_oxi_states self.symmetrized_structures = symmetrized_structures
[docs] def apply_transformation(self, structure, return_ranked_list=False): """ For this transformation, the apply_transformation method will return only the ordered structure with the lowest Ewald energy, to be consistent with the method signature of the other transformations. However, all structures are stored in the all_structures attribute in the transformation object for easy access. Args: structure: Oxidation state decorated disordered structure to order return_ranked_list (bool): Whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned. Returns: Depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {"structure" = .... , "other_arguments"} the key "transformation" is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class. """ try: num_to_return = int(return_ranked_list) except ValueError: num_to_return = 1 num_to_return = max(1, num_to_return) if self.no_oxi_states: structure = Structure.from_sites(structure) for i, site in enumerate(structure): structure[i] = {"%s0+" % k.symbol: v for k, v in site.species.items()} equivalent_sites = [] exemplars = [] # generate list of equivalent sites to order # equivalency is determined by sp_and_occu and symmetry # if symmetrized structure is true for i, site in enumerate(structure): if site.is_ordered: continue for j, ex in enumerate(exemplars): sp = ex.species if not site.species.almost_equals(sp): continue if self.symmetrized_structures: sym_equiv = structure.find_equivalent_sites(ex) sym_test = site in sym_equiv else: sym_test = True if sym_test: equivalent_sites[j].append(i) break else: equivalent_sites.append([i]) exemplars.append(site) # generate the list of manipulations and input structure s = Structure.from_sites(structure) m_list = [] for g in equivalent_sites: total_occupancy = sum([structure[i].species for i in g], Composition()) total_occupancy = dict(total_occupancy.items()) # round total occupancy to possible values for k, v in total_occupancy.items(): if abs(v - round(v)) > 0.25: raise ValueError("Occupancy fractions not consistent " "with size of unit cell") total_occupancy[k] = int(round(v)) # start with an ordered structure initial_sp = max(total_occupancy.keys(), key=lambda x: abs(x.oxi_state)) for i in g: s[i] = initial_sp # determine the manipulations for k, v in total_occupancy.items(): if k == initial_sp: continue m = [k.oxi_state / initial_sp.oxi_state if initial_sp.oxi_state else 0, v, list(g), k] m_list.append(m) # determine the number of empty sites empty = len(g) - sum(total_occupancy.values()) if empty > 0.5: m_list.append([0, empty, list(g), None]) matrix = EwaldSummation(s).total_energy_matrix ewald_m = EwaldMinimizer(matrix, m_list, num_to_return, self.algo) self._all_structures = [] lowest_energy = ewald_m.output_lists[0][0] num_atoms = sum(structure.composition.values()) for output in ewald_m.output_lists: s_copy = s.copy() # do deletions afterwards because they screw up the indices of the # structure del_indices = [] for manipulation in output[1]: if manipulation[1] is None: del_indices.append(manipulation[0]) else: s_copy[manipulation[0]] = manipulation[1] s_copy.remove_sites(del_indices) if self.no_oxi_states: s_copy.remove_oxidation_states() self._all_structures.append( {"energy": output[0], "energy_above_minimum": (output[0] - lowest_energy) / num_atoms, "structure": s_copy.get_sorted_structure()}) if return_ranked_list: return self._all_structures[:num_to_return] else: return self._all_structures[0]["structure"]
def __str__(self): return "Order disordered structure transformation" def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: True """ return True @property def lowest_energy_structure(self): """ :return: Lowest energy structure found. """ return self._all_structures[0]["structure"]
[docs]class PrimitiveCellTransformation(AbstractTransformation): """ This class finds the primitive cell of the input structure. It returns a structure that is not necessarily orthogonalized Author: Will Richards """ def __init__(self, tolerance=0.5): """ Args: tolerance (float): Tolerance for each coordinate of a particular site. For example, [0.5, 0, 0.5] in cartesian coordinates will be considered to be on the same coordinates as [0, 0, 0] for a tolerance of 0.5. Defaults to 0.5. """ self.tolerance = tolerance
[docs] def apply_transformation(self, structure): """ Returns most primitive cell for structure. Args: structure: A structure Returns: The most primitive structure found. The returned structure is guaranteed to have len(new structure) <= len(structure). """ return structure.get_primitive_structure(tolerance=self.tolerance)
def __str__(self): return "Primitive cell transformation" def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class ConventionalCellTransformation(AbstractTransformation): """ This class finds the conventional cell of the input structure. """ def __init__(self, symprec=0.01, angle_tolerance=5, international_monoclinic=True): """ Args: symprec (float): tolerance as in SpacegroupAnalyzer angle_tolerance (float): angle tolerance as in SpacegroupAnalyzer international_monoclinic (bool): whether to use beta (True) or alpha (False) as the non-right-angle in the unit cell """ self.symprec = symprec self.angle_tolerance = angle_tolerance self.international_monoclinic = international_monoclinic
[docs] def apply_transformation(self, structure): """ Returns most primitive cell for structure. Args: structure: A structure Returns: The same structure in a conventional standard setting """ sga = SpacegroupAnalyzer(structure, symprec=self.symprec, angle_tolerance=self.angle_tolerance) return sga.get_conventional_standard_structure(international_monoclinic=self.international_monoclinic)
def __str__(self): return "Conventional cell transformation" def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class PerturbStructureTransformation(AbstractTransformation): """ This transformation perturbs a structure by a specified distance in random directions. Used for breaking symmetries. """ def __init__( self, distance: float = 0.01, min_distance: Optional[Union[int, float]] = None, ): """ Args: distance: Distance of perturbation in angstroms. All sites will be perturbed by exactly that distance in a random direction. min_distance: if None, all displacements will be equidistant. If int or float, perturb each site a distance drawn from the uniform distribution between 'min_distance' and 'distance'. """ self.distance = distance self.min_distance = min_distance
[docs] def apply_transformation(self, structure: Structure) -> Structure: """ Apply the transformation. Args: structure: Input Structure Returns: Structure with sites perturbed. """ s = structure.copy() s.perturb(self.distance, min_distance=self.min_distance) return s
def __str__(self): return "PerturbStructureTransformation : " + \ "Amplitude = {}".format(self.amplitude) def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class DeformStructureTransformation(AbstractTransformation): """ This transformation deforms a structure by a deformation gradient matrix """ def __init__(self, deformation=((1, 0, 0), (0, 1, 0), (0, 0, 1))): """ Args: deformation (array): deformation gradient for the transformation """ self._deform = Deformation(deformation) self.deformation = self._deform.tolist()
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Deformed Structure. """ return self._deform.apply_to_structure(structure)
def __str__(self): return "DeformStructureTransformation : " + \ "Deformation = {}".format(str(self.deformation)) def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: Inverse Transformation. """ return DeformStructureTransformation(self._deform.inv()) @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class DiscretizeOccupanciesTransformation(AbstractTransformation): """ Discretizes the site occupancies in a disordered structure; useful for grouping similar structures or as a pre-processing step for order-disorder transformations. """ def __init__(self, max_denominator=5, tol=None, fix_denominator=False): """ Args: max_denominator: An integer maximum denominator for discretization. A higher denominator allows for finer resolution in the site occupancies. tol: A float that sets the maximum difference between the original and discretized occupancies before throwing an error. If None, it is set to 1 / (4 * max_denominator). fix_denominator(bool): If True, will enforce a common denominator for all species. This prevents a mix of denominators (for example, 1/3, 1/4) that might require large cell sizes to perform an enumeration. 'tol' needs to be > 1.0 in some cases. """ self.max_denominator = max_denominator self.tol = tol if tol is not None else 1 / (4 * max_denominator) self.fix_denominator = fix_denominator
[docs] def apply_transformation(self, structure): """ Discretizes the site occupancies in the structure. Args: structure: disordered Structure to discretize occupancies Returns: A new disordered Structure with occupancies discretized """ if structure.is_ordered: return structure species = [dict(sp) for sp in structure.species_and_occu] for sp in species: for k, v in sp.items(): old_occ = sp[k] new_occ = float( Fraction(old_occ).limit_denominator(self.max_denominator)) if self.fix_denominator: new_occ = around(old_occ * self.max_denominator) \ / self.max_denominator if round(abs(old_occ - new_occ), 6) > self.tol: raise RuntimeError( "Cannot discretize structure within tolerance!") sp[k] = new_occ return Structure(structure.lattice, species, structure.frac_coords)
def __str__(self): return "DiscretizeOccupanciesTransformation" def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class ChargedCellTransformation(AbstractTransformation): """ The ChargedCellTransformation applies a charge to a structure (or defect object). """ def __init__(self, charge=0): """ Args: charge: A integer charge to apply to the structure. Defaults to zero. Has to be a single integer. e.g. 2 """ self.charge = charge
[docs] def apply_transformation(self, structure): """ Apply the transformation. Args: structure (Structure): Input Structure Returns: Charged Structure. """ s = structure.copy() s.set_charge(self.charge) return s
def __str__(self): return "Structure with charge " + \ "{}".format(self.charge) def __repr__(self): return self.__str__() @property def inverse(self): """ Raises: NotImplementedError """ raise NotImplementedError() @property def is_one_to_many(self): """ Returns: False """ return False
[docs]class ScaleToRelaxedTransformation(AbstractTransformation): """ Takes the unrelaxed and relaxed structure and applies its site and volume relaxation to a structurally similar structures (e.g. bulk: NaCl and PbTe (rock-salt), slab: Sc(10-10) and Mg(10-10) (hcp), GB: Mo(001) sigma 5 GB, Fe(001) sigma 5). Useful for finding an initial guess of a set of similar structures closer to its most relaxed state. """ def __init__(self, unrelaxed_structure, relaxed_structure, species_map=None): """ Args: unrelaxed_structure (Structure): Initial, unrelaxed structure relaxed_structure (Structure): Relaxed structure species_map (dict): A dict or list of tuples containing the species mapping in string-string pairs. The first species corresponds to the relaxed structure while the second corresponds to the species in the structure to be scaled. E.g., {"Li":"Na"} or [("Fe2+","Mn2+")]. Multiple substitutions can be done. Overloaded to accept sp_and_occu dictionary E.g. {"Si: {"Ge":0.75, "C":0.25}}, which substitutes a single species with multiple species to generate a disordered structure. """ # Get the ratio matrix for lattice relaxation which can be # applied to any similar structure to simulate volumetric relaxation relax_params = list(relaxed_structure.lattice.abc) relax_params.extend(relaxed_structure.lattice.angles) unrelax_params = list(unrelaxed_structure.lattice.abc) unrelax_params.extend(unrelaxed_structure.lattice.angles) self.params_percent_change = [] for i, p in enumerate(relax_params): self.params_percent_change.append(relax_params[i] / unrelax_params[i]) self.unrelaxed_structure = unrelaxed_structure self.relaxed_structure = relaxed_structure self.species_map = species_map
[docs] def apply_transformation(self, structure): """ Returns a copy of structure with lattice parameters and sites scaled to the same degree as the relaxed_structure. Arg: structure (Structure): A structurally similar structure in regards to crystal and site positions. """ if self.species_map is None: match = StructureMatcher() s_map = \ match.get_best_electronegativity_anonymous_mapping(self.unrelaxed_structure, structure) else: s_map = self.species_map params = list(structure.lattice.abc) params.extend(structure.lattice.angles) new_lattice = Lattice.from_parameters(*[p * self.params_percent_change[i] for i, p in enumerate(params)]) species, frac_coords = [], [] for site in self.relaxed_structure: species.append(s_map[site.specie]) frac_coords.append(site.frac_coords) return Structure(new_lattice, species, frac_coords)
def __str__(self): return "ScaleToRelaxedTransformation" def __repr__(self): return self.__str__() @property def inverse(self): """ Returns: None """ return None @property def is_one_to_many(self): """ Returns: False """ return False