Source code for pymatgen.transformations.standard_transformations

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

from __future__ import division, unicode_literals

import logging

from fractions import Fraction

from pymatgen.analysis.bond_valence import BVAnalyzer
from pymatgen.analysis.ewald import EwaldSummation, EwaldMinimizer
from pymatgen.analysis.elasticity.strain import Deformation
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
from pymatgen.transformations.site_transformations import \
    PartialRemoveSitesTransformation
from pymatgen.transformations.transformation_abc import AbstractTransformation

"""
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.
"""


__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. 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. """ def __init__(self, axis, angle, angle_in_radians=False): """ """ 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): 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): return RotationTransformation(self.axis, -self.angle, self.angle_in_radians) @property def is_one_to_many(self): return False
[docs]class OxidationStateDecorationTransformation(AbstractTransformation): """ This transformation decorates a structure with oxidation states. Args: oxidation_states (dict): Oxidation states supplied as a dict, e.g., {"Li":1, "O":-2} """ def __init__(self, oxidation_states): self.oxidation_states = oxidation_states
[docs] def apply_transformation(self, structure): s = structure.copy() s.add_oxidation_state_by_element(self.oxidation_states) return s
@property def inverse(self): return None @property def is_one_to_many(self): return False
[docs]class AutoOxiStateDecorationTransformation(AbstractTransformation): """ This transformation automatically decorates a structure with oxidation states using a bond valence approach. 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. """ def __init__(self, symm_tol=0.1, max_radius=4, max_permutations=100000, distance_scale_factor=1.015): 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): return self.analyzer.get_oxi_state_decorated_structure(structure)
@property def inverse(self): return None @property def is_one_to_many(self): return False
[docs]class OxidationStateRemovalTransformation(AbstractTransformation): """ This transformation removes oxidation states from a structure. """ def __init__(self): pass
[docs] def apply_transformation(self, structure): s = structure.copy() s.remove_oxidation_states() return s
@property def inverse(self): return None @property def is_one_to_many(self): return False
[docs]class SupercellTransformation(AbstractTransformation): """ The RotationTransformation applies a rotation to a structure. 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. """ def __init__(self, scaling_matrix=((1, 0, 0), (0, 1, 0), (0, 0, 1))): 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): 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): raise NotImplementedError() @property def is_one_to_many(self): return False
[docs]class SubstitutionTransformation(AbstractTransformation): """ This transformation substitutes species for one another. 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. """ def __init__(self, species_map): 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): 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): inverse_map = {v: k for k, v in self._species_map.items()} return SubstitutionTransformation(inverse_map) @property def is_one_to_many(self): return False
[docs]class RemoveSpeciesTransformation(AbstractTransformation): """ Remove all occurrences of some species from a structure. Args: species_to_remove: List of species to remove. E.g., ["Li", "Mn"] """ def __init__(self, species_to_remove): self.species_to_remove = species_to_remove
[docs] def apply_transformation(self, structure): 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): return None @property def is_one_to_many(self): 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`. 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. """ 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): """ """ 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_and_occu == 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): 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): 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. 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. """ ALGO_FAST = 0 ALGO_COMPLETE = 1 ALGO_BEST_FIRST = 2 def __init__(self, algo=ALGO_FAST, symmetrized_structures=False): self.algo = algo self._all_structures = [] 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) 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_and_occu if not site.species_and_occu.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_and_occu 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) 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 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): return None @property def is_one_to_many(self): return True @property def lowest_energy_structure(self): 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 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. """ def __init__(self, tolerance=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): return None @property def is_one_to_many(self): return False
[docs]class PerturbStructureTransformation(AbstractTransformation): """ This transformation perturbs a structure by a specified distance in random directions. Used for breaking symmetries. Args: amplitude (float): Amplitude of perturbation in angstroms. All sites will be perturbed by exactly that amplitude in a random direction. """ def __init__(self, amplitude=0.01): self.amplitude = amplitude
[docs] def apply_transformation(self, structure): s = structure.copy() s.perturb(self.amplitude) return s
def __str__(self): return "PerturbStructureTransformation : " + \ "Amplitude = {}".format(self.amplitude) def __repr__(self): return self.__str__() @property def inverse(self): return None @property def is_one_to_many(self): return False
[docs]class DeformStructureTransformation(AbstractTransformation): """ This transformation deforms a structure by a deformation gradient matrix Args: deformation (array): deformation gradient for the transformation """ def __init__(self, deformation): self.deformation = Deformation(deformation)
[docs] def apply_transformation(self, structure): return self.deformation.apply_to_structure(structure)
def __str__(self): return "DeformStructureTransformation : " + \ "Deformation = {}".format(str(self.deformation.tolist())) def __repr__(self): return self.__str__() @property def inverse(self): return DeformStructureTransformation(self.deformation.inv()) @property def is_one_to_many(self): 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. 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. The maximum allowed difference is calculated as 1/max_denominator * 0.5 * tol. A tol of 1.0 indicates to try to accept all discretizations. """ def __init__(self, max_denominator=5, tol=0.25): self.max_denominator = max_denominator self.tol = tol
[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 round(abs(old_occ - new_occ), 6) > ( 1 / self.max_denominator / 2) * 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): return None @property def is_one_to_many(self): return False