Source code for pm4py.algo.evaluation.precision.algorithm

'''
    PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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'''
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


[docs] 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}
[docs] 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 )