Source code for pm4py.algo.discovery.log_skeleton.algorithm

'''
    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.objects.conversion.log import converter as log_conversion
from pm4py.algo.discovery.log_skeleton.variants import classic
from enum import Enum
from pm4py.util import exec_utils
from typing import Optional, Dict, Any, Union, Tuple, List
from pm4py.objects.log.obj import EventLog, EventStream
import pandas as pd


[docs]class Variants(Enum): CLASSIC = classic
CLASSIC = Variants.CLASSIC DEFAULT_VARIANT = CLASSIC VERSIONS = {CLASSIC}
[docs]def apply(log: Union[EventLog, EventStream, pd.DataFrame], variant=DEFAULT_VARIANT, parameters: Optional[Dict[Any, Any]] = None) -> Dict[str, Any]: """ Discover a log skeleton from an event log Parameters ------------- log Event log variant Variant of the algorithm, possible values: - Variants.CLASSIC parameters Parameters of the algorithm, including: - the activity key (Parameters.ACTIVITY_KEY) - the noise threshold (Parameters.NOISE_THRESHOLD) Returns ------------- model Log skeleton model """ return exec_utils.get_variant(variant).apply(log_conversion.apply(log, variant=log_conversion.Variants.TO_EVENT_LOG, parameters=parameters), parameters=parameters)
[docs]def apply_from_variants_list(var_list: List[Tuple[str, int]], variant=DEFAULT_VARIANT, parameters: Optional[Dict[Any, Any]] = None) -> Dict[str, Any]: """ Discovers the log skeleton from the variants list Parameters --------------- var_list Variants list variant Variant of the algorithm, possible values: - Variants.CLASSIC parameters Parameters Returns ------------- model Log skeleton model """ return exec_utils.get_variant(variant).apply_from_variants_list(var_list, parameters=parameters)