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

'''
    PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or any later version.

This program 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 Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License
along with this program.  If not, see this software project's root or
visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions
Contact: info@processintelligence.solutions
'''
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




class Variants(Enum):
    CLASSIC = classic



CLASSIC = Variants.CLASSIC
DEFAULT_VARIANT = CLASSIC

VERSIONS = {CLASSIC}




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, parameters=parameters)





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
    )