pm4py.algo.simulation.montecarlo.algorithm module#

class pm4py.algo.simulation.montecarlo.algorithm.Variants(*values)[source]#

Bases: Enum

PETRI_SEMAPH_FIFO = <module 'pm4py.algo.simulation.montecarlo.variants.petri_semaph_fifo' from '/Users/chris/Desktop/PIS/pm4py2/pm4py/pm4py/algo/simulation/montecarlo/variants/petri_semaph_fifo.py'>#
pm4py.algo.simulation.montecarlo.algorithm.apply(log: EventLog | DataFrame, net: PetriNet, im: Marking, fm: Marking, variant=Variants.PETRI_SEMAPH_FIFO, parameters: Dict[Any, Any] | None = None) → Tuple[EventLog, Dict[str, Any]][source]#

Performs a Monte Carlo simulation of an accepting Petri net without duplicate transitions and where the preset is always distinct from the postset

Parameters:

  • log – Event log

  • net – Accepting Petri net without duplicate transitions and where the preset is always distinct from the postset

  • im – Initial marking

  • fm – Final marking

  • variant – Variant of the algorithm to use: - Variants.PETRI_SEMAPH_FIFO

  • parameters –

    Parameters of the algorithm:

    Parameters.PARAM_NUM_SIMULATIONS => (default: 100) Parameters.PARAM_FORCE_DISTRIBUTION => Force a particular stochastic distribution (e.g. normal) when the stochastic map is discovered from the log (default: None; no distribution is forced) Parameters.PARAM_ENABLE_DIAGNOSTICS => Enable the printing of diagnostics (default: True) Parameters.PARAM_DIAGN_INTERVAL => Interval of time in which diagnostics of the simulation are printed (default: 32) Parameters.PARAM_CASE_ARRIVAL_RATIO => Case arrival of new cases (default: None; inferred from the log) Parameters.PARAM_PROVIDED_SMAP => Stochastic map that is used in the simulation (default: None; inferred from the log) Parameters.PARAM_MAP_RESOURCES_PER_PLACE => Specification of the number of resources available per place (default: None; each place gets the default number of resources) Parameters.PARAM_DEFAULT_NUM_RESOURCES_PER_PLACE => Default number of resources per place when not specified (default: 1; each place gets 1 resource and has to wait for the resource to finish) Parameters.PARAM_SMALL_SCALE_FACTOR => Scale factor for the sleeping time of the actual simulation (default: 864000.0, 10gg) Parameters.PARAM_MAX_THREAD_EXECUTION_TIME => Maximum execution time per thread (default: 60.0, 1 minute)

Returns:

  • simulated_log – Simulated event log

  • simulation_result –

    Result of the simulation:

    Outputs.OUTPUT_PLACES_INTERVAL_TREES => inteval trees that associate to each place the times in which it was occupied. Outputs.OUTPUT_TRANSITIONS_INTERVAL_TREES => interval trees that associate to each transition the intervals of time in which it could not fire because some token was in the output. Outputs.OUTPUT_CASES_EX_TIME => Throughput time of the cases included in the simulated log Outputs.OUTPUT_MEDIAN_CASES_EX_TIME => Median of the throughput times Outputs.OUTPUT_CASE_ARRIVAL_RATIO => Case arrival ratio that was specified in the simulation Outputs.OUTPUT_TOTAL_CASES_TIME => Total time occupied by cases of the simulated log