''' This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de). PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. PM4Py is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with PM4Py. If not, see . ''' from pm4py.algo.conformance.alignments.decomposed.variants import recompos_maximal from enum import Enum from pm4py.util import exec_utils from typing import Optional, Dict, Any, Union from pm4py.objects.log.obj import EventLog from pm4py.objects.petri_net.obj import PetriNet, Marking from pm4py.util import typing import pandas as pd class Variants(Enum): RECOMPOS_MAXIMAL = recompos_maximal VERSIONS = {Variants.RECOMPOS_MAXIMAL} def apply(log: Union[EventLog, pd.DataFrame], net: PetriNet, im: Marking, fm: Marking, variant=Variants.RECOMPOS_MAXIMAL, parameters: Optional[Dict[Any, Any]] = None) -> typing.ListAlignments: """ Apply the recomposition alignment approach to a log and a Petri net performing decomposition Parameters -------------- log Event log net Petri net im Initial marking fm Final marking variant Variant of the algorithm, possible values: - Variants.RECOMPOS_MAXIMAL parameters Parameters of the algorithm Returns -------------- aligned_traces For each trace, return its alignment """ return exec_utils.get_variant(variant).apply(log, net, im, fm, parameters=parameters)