pm4py.algo.conformance.tokenreplay.algorithm module#

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class pm4py.algo.conformance.tokenreplay.algorithm.Variants(*values)[source]#

Bases: Enum

TOKEN_REPLAY = <module 'pm4py.algo.conformance.tokenreplay.variants.token_replay' from '/home/javert/ALE/pm4py/pm4py/algo/conformance/tokenreplay/variants/token_replay.py'>#
BACKWARDS = <module 'pm4py.algo.conformance.tokenreplay.variants.backwards' from '/home/javert/ALE/pm4py/pm4py/algo/conformance/tokenreplay/variants/backwards.py'>#
pm4py.algo.conformance.tokenreplay.algorithm.apply(log: EventLog | EventStream | DataFrame, net: PetriNet, initial_marking: Marking, final_marking: Marking, parameters: Dict[Any, Any] | None = None, variant=Variants.TOKEN_REPLAY) → List[Dict[str, Any]][source]#

Method to apply token-based replay

Parameters:

  • log – Log

  • net – Petri net

  • initial_marking – Initial marking

  • final_marking – Final marking

  • parameters –

    Parameters of the algorithm, including:

    Parameters.ACTIVITY_KEY -> Activity key

  • variant –

    Variant of the algorithm to use:

    • Variants.TOKEN_REPLAY

    • Variants.BACKWARDS

pm4py.algo.conformance.tokenreplay.algorithm.get_diagnostics_dataframe(log: EventLog | EventStream | DataFrame, tbr_output: List[Dict[str, Any]], variant=Variants.TOKEN_REPLAY, parameters: Dict[Any, Any] | None = None) → DataFrame[source]#

Gets the results of token-based replay in a dataframe

Parameters:

  • log – Event log

  • tbr_output – Output of the token-based replay technique

  • variant –

    Variant of the algorithm to use:

    • Variants.TOKEN_REPLAY

    • Variants.BACKWARDS

Returns:

Diagnostics dataframe

Return type:

dataframe