text: # Copyright (c) Pymatgen Development Team.
  # Distributed under the terms of the MIT License.
  
  """
  This module defines filters for Transmuter object.
  """
  
  import abc
  from collections import defaultdict
  
  from monty.json import MSONable
  
  from pymatgen.analysis.structure_matcher import ElementComparator, StructureMatcher
  from pymatgen.core.periodic_table import get_el_sp
  from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
  
  
  class AbstractStructureFilter(MSONable, metaclass=abc.ABCMeta):
      """
      AbstractStructureFilter that defines an API to perform testing of
      Structures. Structures that return True to a test are retained during
      transmutation while those that return False are removed.
      """
  
      @abc.abstractmethod
      def test(self, structure):
          """
          Method to execute the test.
  
          Args:
              structure (Structure): Input structure to test
  
          Returns:
              (bool) Structures that return true are kept in the Transmuter
              object during filtering.
          """
          return
  
  
  class ContainsSpecieFilter(AbstractStructureFilter):
      """
      Filter for structures containing certain elements or species.
      By default compares by atomic number.
      """
  
      def __init__(self, species, strict_compare=False, AND=True, exclude=False):
          """
          Args:
              species ([Species/Element]): list of species to look for
              AND: whether all species must be present to pass (or fail) filter.
              strict_compare: if true, compares objects by specie or element
                  object if false, compares atomic number
              exclude: If true, returns false for any structures with the specie
                  (excludes them from the Transmuter)
          """
          self._species = list(map(get_el_sp, species))
          self._strict = strict_compare
          self._AND = AND
          self._exclude = exclude
  
      def test(self, structure):
          """
          Method to execute the test.
  
          Returns: True if structure do not contain specified species.
          """
          # set up lists to compare
          if not self._strict:
              # compare by atomic number
              filter_set = {sp.Z for sp in self._species}
              structure_set = {sp.Z for sp in structure.composition.elements}
          else:
              # compare by specie or element object
              filter_set = set(self._species)
              structure_set = set(structure.composition.elements)
  
          if self._AND and filter_set <= structure_set:
              # return true if we aren't excluding since all are in structure
              return not self._exclude
          if (not self._AND) and filter_set & structure_set:
              # return true if we aren't excluding since one is in structure
              return not self._exclude
          # return false if we aren't excluding otherwise
          return self._exclude
  
      def __repr__(self):
          return "\n".join(
              [
                  "ContainsSpecieFilter with parameters:",
                  f"species = {self._species}",
                  f"strict_compare = {self._strict}",
                  f"AND = {self._AND}",
                  f"exclude = {self._exclude}",
              ]
          )
  
      def as_dict(self):
          """
          Returns: MSONAble dict
          """
          return {
              "@module": self.__class__.__module__,
              "@class": self.__class__.__name__,
              "init_args": {
                  "species": [str(sp) for sp in self._species],
                  "strict_compare": self._strict,
                  "AND": self._AND,
                  "exclude": self._exclude,
              },
          }
  
      @classmethod
      def from_dict(cls, d):
          """
          Args:
              d (dict): Dict representation
  
          Returns:
              Filter
          """
          return cls(**d["init_args"])
  
  
  class SpecieProximityFilter(AbstractStructureFilter):
      """
      This filter removes structures that have certain species that are too close
      together.
      """
  
      def __init__(self, specie_and_min_dist_dict):
          """
          Args:
              specie_and_min_dist_dict (dict): A species string to float mapping. For
                  example, {"Na+": 1} means that all Na+ ions must be at least 1
                  Angstrom away from each other. Multiple species criteria can be
                  applied. Note that the testing is done based on the actual object
                  . If you have a structure with Element, you must use {"Na":1}
                  instead to filter based on Element and not Species.
          """
          self.specie_and_min_dist = {get_el_sp(k): v for k, v in specie_and_min_dist_dict.items()}
  
      def test(self, structure):
          """
          Method to execute the test.
  
          Args:
              structure (Structure): Input structure to test
  
          Returns: True if structure does not contain species within specified
              distances.
          """
          all_species = set(self.specie_and_min_dist.keys())
          for site in structure:
              species = site.species.keys()
              sp_to_test = set(species).intersection(all_species)
              if sp_to_test:
                  max_r = max(self.specie_and_min_dist[sp] for sp in sp_to_test)
                  nn = structure.get_neighbors(site, max_r)
                  for sp in sp_to_test:
                      for nnsite, dist, *_ in nn:
                          if sp in nnsite.species.keys():
                              if dist < self.specie_and_min_dist[sp]:
                                  return False
          return True
  
      def as_dict(self):
          """
          Returns: MSONable dict
          """
          return {
              "@module": self.__class__.__module__,
              "@class": self.__class__.__name__,
              "init_args": {"specie_and_min_dist_dict": {str(sp): v for sp, v in self.specie_and_min_dist.items()}},
          }
  
      @classmethod
      def from_dict(cls, d):
          """
          Args:
              d (dict): Dict representation
  
          Returns:
              Filter
          """
          return cls(**d["init_args"])
  
  
  class RemoveDuplicatesFilter(AbstractStructureFilter):
      """
      This filter removes exact duplicate structures from the transmuter.
      """
  
      def __init__(
          self,
          structure_matcher=StructureMatcher(comparator=ElementComparator()),
          symprec=None,
      ):
          """
          Remove duplicate structures based on the structure matcher
          and symmetry (if symprec is given).
  
          Args:
              structure_matcher: Provides a structure matcher to be used for
                  structure comparison.
              symprec: The precision in the symmetry finder algorithm if None (
                  default value), no symmetry check is performed and only the
                  structure matcher is used. A recommended value is 1e-5.
          """
          self.symprec = symprec
          self.structure_list = defaultdict(list)
          if isinstance(structure_matcher, dict):
              self.structure_matcher = StructureMatcher.from_dict(structure_matcher)
          else:
              self.structure_matcher = structure_matcher
  
      def test(self, structure):
          """
          Args:
              structure (Structure): Input structure to test
  
          Returns: True if structure is not in list.
          """
          h = self.structure_matcher._comparator.get_hash(structure.composition)
          if not self.structure_list[h]:
              self.structure_list[h].append(structure)
              return True
  
          def get_sg(s):
              finder = SpacegroupAnalyzer(s, symprec=self.symprec)
              return finder.get_space_group_number()
  
          for s in self.structure_list[h]:
              if self.symprec is None or get_sg(s) == get_sg(structure):
                  if self.structure_matcher.fit(s, structure):
                      return False
  
          self.structure_list[h].append(structure)
          return True
  
  
  class RemoveExistingFilter(AbstractStructureFilter):
      """
      This filter removes structures existing in a given list from the transmuter.
      """
  
      def __init__(
          self,
          existing_structures,
          structure_matcher=StructureMatcher(comparator=ElementComparator()),
          symprec=None,
      ):
          """
          Remove existing structures based on the structure matcher
          and symmetry (if symprec is given).
  
          Args:
              existing_structures: List of existing structures to compare with
              structure_matcher: Provides a structure matcher to be used for
                  structure comparison.
              symprec: The precision in the symmetry finder algorithm if None (
                  default value), no symmetry check is performed and only the
                  structure matcher is used. A recommended value is 1e-5.
          """
          self.symprec = symprec
          self.structure_list = []
          self.existing_structures = existing_structures
          if isinstance(structure_matcher, dict):
              self.structure_matcher = StructureMatcher.from_dict(structure_matcher)
          else:
              self.structure_matcher = structure_matcher
  
      def test(self, structure):
          """
          Method to execute the test.
  
          Args:
              structure (Structure): Input structure to test
  
          Returns: True if structure is not in existing list.
          """
  
          def get_sg(s):
              finder = SpacegroupAnalyzer(s, symprec=self.symprec)
              return finder.get_space_group_number()
  
          for s in self.existing_structures:
              if self.structure_matcher._comparator.get_hash(
                  structure.composition
              ) == self.structure_matcher._comparator.get_hash(s.composition):
                  if self.symprec is None or get_sg(s) == get_sg(structure):
                      if self.structure_matcher.fit(s, structure):
                          return False
  
          self.structure_list.append(structure)
          return True
  
      def as_dict(self):
          """
          Returns: MSONable dict
          """
          return {
              "@module": self.__class__.__module__,
              "@class": self.__class__.__name__,
              "init_args": {"structure_matcher": self.structure_matcher.as_dict()},
          }
  
  
  class ChargeBalanceFilter(AbstractStructureFilter):
      """
      This filter removes structures that are not charge balanced from the
      transmuter. This only works if the structure is oxidation state
      decorated, as structures with only elemental sites are automatically
      assumed to have net charge of 0.
      """
  
      def __init__(self):
          """
          No args required.
          """
  
      def test(self, structure):
          """
          Method to execute the test.
  
          Args:
              structure (Structure): Input structure to test
  
          Returns: True if structure is neutral.
          """
          return structure.charge == 0.0
  
  
  class SpeciesMaxDistFilter(AbstractStructureFilter):
      """
      This filter removes structures that do have two particular species that are
      not nearest neighbors by a predefined max_dist. For instance, if you are
      analyzing Li battery materials, you would expect that each Li+ would be
      nearest neighbor to lower oxidation state transition metal for
      electrostatic reasons. This only works if the structure is oxidation state
      decorated, as structures with only elemental sites are automatically
      assumed to have net charge of 0.
      """
  
      def __init__(self, sp1, sp2, max_dist):
          """
          Args:
              sp1 (Species): First specie
              sp2 (Species): Second specie
              max_dist (float): Maximum distance between species.
          """
          self.sp1 = get_el_sp(sp1)
          self.sp2 = get_el_sp(sp2)
          self.max_dist = max_dist
  
      def test(self, structure):
          """
          Method to execute the test.
  
          Args:
              structure (Structure): Input structure to test
  
          Returns: True if structure does not contain the two species are distances
              greater than max_dist.
          """
          sp1_indices = [i for i, site in enumerate(structure) if site.specie == self.sp1]
          sp2_indices = [i for i, site in enumerate(structure) if site.specie == self.sp2]
          fcoords = structure.frac_coords
          fcoords1 = fcoords[sp1_indices, :]
          fcoords2 = fcoords[sp2_indices, :]
          lattice = structure.lattice
          dists = lattice.get_all_distances(fcoords1, fcoords2)
          return all(any(row) for row in dists < self.max_dist)
  