Source code for pm4py.algo.organizational_mining.roles.variants.pandas

'''
    This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

    PM4Py is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    PM4Py is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with PM4Py.  If not, see <https://www.gnu.org/licenses/>.
'''
from pm4py.algo.organizational_mining.roles.common import algorithm
from pm4py.util import xes_constants as xes
from collections import Counter
from pm4py.util import exec_utils

from enum import Enum
from pm4py.util import constants
from typing import Optional, Dict, Any, Union, Tuple, List
from pm4py.objects.log.obj import EventLog, EventStream
import pandas as pd


[docs]class Parameters(Enum): ROLES_THRESHOLD_PARAMETER = "roles_threshold_parameter" RESOURCE_KEY = constants.PARAMETER_CONSTANT_RESOURCE_KEY ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
[docs]def apply(df: pd.DataFrame, parameters: Optional[Dict[Union[str, Parameters], Any]] = None) -> List[Any]: """ Gets the roles (group of different activities done by similar resources) out of the log Parameters ------------- df Pandas dataframe parameters Possible parameters of the algorithm Returns ------------ roles List of different roles inside the log """ if parameters is None: parameters = {} resource_key = exec_utils.get_param_value(Parameters.RESOURCE_KEY, parameters, xes.DEFAULT_RESOURCE_KEY) activity_key = exec_utils.get_param_value(Parameters.ACTIVITY_KEY, parameters, xes.DEFAULT_NAME_KEY) activity_resource_couples = Counter(dict(df.groupby([resource_key, activity_key]).size())) return algorithm.apply(activity_resource_couples, parameters=parameters)