pm4py.conformance.fitness_footprints

pm4py.conformance.fitness_footprints(*args) → Dict[str, float]

Calculates fitness using footprints. The output is a dictionary containing two keys: - perc_fit_traces => percentage of fit traces (over the log) - log_fitness => the fitness value over the log

Parameters:

args – provided arguments (the first argument is supposed to be an event log (or the footprints discovered from the event log); the other arguments are supposed to be the process model (or the footprints discovered from the process model).

Return type:

Dict[str, float]

import pm4py

net, im, fm = pm4py.discover_petri_net_inductive(dataframe, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')
fitness_fp = pm4py.fitness_footprints(dataframe, net, im, fm, activity_key='concept:name', case_id_key='case:concept:name', timestamp_key='time:timestamp')

Deprecated since version 2.3.0: This will be removed in 3.0.0. conformance checking using footprints will not be exposed in a future release