# 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__)

    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)

        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

    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

        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

    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)

        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

    class OxidationStateRemovalTransformation(AbstractTransformation):
        """
        This transformation removes oxidation states from a structure.
        """

        def __init__(self):
            """
            No arg needed.
            """
            pass

        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

    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

        @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]])

        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

    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)

        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

    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

        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

    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

        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

    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

        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"]

    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

        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

    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

        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

    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

        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

    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()

        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

    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

        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

    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

        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

    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

        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