pm4py.conformance.fitness_footprints

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

Calculate 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 – Arguments where the first is an event log (or its footprints) and the others represent the process model (or its footprints).

Returns:

A dictionary containing fitness metrics based on footprints.

Return type:

Dict[str, float]

Example:

```python 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.