Source code for pm4py.algo.transformation.log_to_target.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 enum import Enum
from pm4py.algo.transformation.log_to_target.variants import (
    next_activity,
    next_time,
    remaining_time,
)
from pm4py.objects.log.obj import EventLog, EventStream
import pandas as pd
from typing import Union, Dict, Optional, Any, Tuple, List
from pm4py.util import exec_utils




class Variants(Enum):
    NEXT_ACTIVITY = next_activity
    NEXT_TIME = next_time
    REMAINING_TIME = remaining_time





def apply(
    log: Union[EventLog, EventStream, pd.DataFrame],
    variant=None,
    parameters: Optional[Dict[Any, Any]] = None,
) -> Tuple[Any, List[str]]:
    """
    Extracts from the event log
    the target vector for a specific ML use case

    Parameters
    ---------------
    log
        Event log / Event stream / Pandas dataframe
    variant
        Specification of the target vector:
        - Variants.NEXT_ACTIVITY => encodes the next activity
        - Variants.NEXT_TIME => encodes the next timestamp
        - Variants.REMAINING_TIME => encodes the remaining time

    Returns
    --------------
    vector
        Target vector for the specified ML use case
    classes
        Classes (for every column of the target vector)
    """
    if variant is None:
        raise Exception(
            "please provide the variant between: Variants.NEXT_ACTIVITY, Variants.NEXT_TIME, Variants.REMAINING_TIME"
        )
    return exec_utils.get_variant(variant).apply(log, parameters=parameters)