/
transformation_abc.py
85 lines (71 loc) · 2.72 KB
/
transformation_abc.py
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# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""
Defines an abstract base class contract for Transformation object.
"""
from __future__ import annotations
import abc
from monty.json import MSONable
from pymatgen.core import Structure
__author__ = "Shyue Ping Ong"
__copyright__ = "Copyright 2011, The Materials Project"
__version__ = "0.1"
__maintainer__ = "Shyue Ping Ong"
__email__ = "shyuep@gmail.com"
__date__ = "Sep 23, 2011"
class AbstractTransformation(MSONable, metaclass=abc.ABCMeta):
"""
Abstract transformation class.
"""
@abc.abstractmethod
def apply_transformation(self, structure: Structure):
"""
Applies the transformation to a structure. Depending on whether a
transformation is one-to-many, there may be an option to return a
ranked list of structures.
Args:
structure:
input structure
return_ranked_list:
Boolean stating 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.
"""
return
@property
@abc.abstractmethod
def inverse(self) -> AbstractTransformation | None:
"""
Returns the inverse transformation if available.
Otherwise, should return None.
"""
@property
@abc.abstractmethod
def is_one_to_many(self) -> bool:
"""
Determines if a Transformation is a one-to-many transformation. If a
Transformation is a one-to-many transformation, the
apply_transformation method should have a keyword arg
"return_ranked_list" which allows for the transformed structures to be
returned as a ranked list.
"""
return False
@property
def use_multiprocessing(self) -> bool:
"""
Indicates whether the transformation can be applied by a
subprocessing pool. This should be overridden to return True for
transformations that the transmuter can parallelize.
"""
return False