Source code for pm4py.algo.organizational_mining.roles.algorithm

from pm4py.algo.organizational_mining.roles.variants import pandas
from pm4py.algo.organizational_mining.roles.variants import log
from pm4py.util import exec_utils, pandas_utils
from enum import Enum
from typing import Optional, Dict, Any, Union, List
from pm4py.objects.log.obj import EventLog, EventStream
import pandas as pd


[docs] class Variants(Enum): LOG = log PANDAS = pandas
[docs] def apply( log: Union[EventLog, EventStream, pd.DataFrame], variant=None, parameters: Optional[Dict[Any, Any]] = None, ) -> List[Any]: """ Gets the roles (group of different activities done by similar resources) out of the log. The roles detection is introduced by Burattin, Andrea, Alessandro Sperduti, and Marco Veluscek. "Business models enhancement through discovery of roles." 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, 2013. Parameters ------------- log Log object (also Pandas dataframe) variant Variant of the algorithm to apply. Possible values: - Variants.LOG - Variants.PANDAS parameters Possible parameters of the algorithm Returns ------------ roles List of different roles inside the log, including: roles_threshold_parameter => threshold to use with the algorithm """ if parameters is None: parameters = {} if variant is None: if pandas_utils.check_is_pandas_dataframe(log): variant = Variants.PANDAS if variant is None: variant = Variants.LOG return exec_utils.get_variant(variant).apply(log, parameters=parameters)