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)
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.