''' 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.evaluation.precision.variants import etconformance_token from pm4py.algo.evaluation.precision.variants import align_etconformance from pm4py.objects.petri_net.utils.check_soundness import check_easy_soundness_net_in_fin_marking from enum import Enum from pm4py.util import exec_utils from typing import Optional, Dict, Any, Union from pm4py.objects.log.obj import EventLog, EventStream from pm4py.objects.petri_net.obj import PetriNet, Marking import pandas as pd class Variants(Enum): ETCONFORMANCE_TOKEN = etconformance_token ALIGN_ETCONFORMANCE = align_etconformance ETCONFORMANCE_TOKEN = Variants.ETCONFORMANCE_TOKEN ALIGN_ETCONFORMANCE = Variants.ALIGN_ETCONFORMANCE VERSIONS = {ETCONFORMANCE_TOKEN, ALIGN_ETCONFORMANCE} def apply(log: Union[EventLog, EventStream, pd.DataFrame], net: PetriNet, marking: Marking, final_marking: Marking, parameters: Optional[Dict[Any, Any]] = None, variant=None) -> float: """ Method to apply ET Conformance Parameters ----------- log Trace log net Petri net marking Initial marking final_marking Final marking parameters Parameters of the algorithm, including: pm4py.util.constants.PARAMETER_CONSTANT_ACTIVITY_KEY -> Activity key variant Variant of the algorithm that should be applied: - Variants.ETCONFORMANCE_TOKEN - Variants.ALIGN_ETCONFORMANCE """ if parameters is None: parameters = {} # execute the following part of code when the variant is not specified by the user if variant is None: if not (check_easy_soundness_net_in_fin_marking( net, marking, final_marking)): # in the case the net is not a easy sound workflow net, we must apply token-based replay variant = ETCONFORMANCE_TOKEN else: # otherwise, use the align-etconformance approach (safer, in the case the model contains duplicates) variant = ALIGN_ETCONFORMANCE return exec_utils.get_variant(variant).apply(log, net, marking, final_marking, parameters=parameters)