Source code for pm4py.algo.discovery.footprints.dfg.variants.dfg

'''
    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.objects.dfg import utils
from enum import Enum
from typing import Optional, Dict, Any, Tuple




class Outputs(Enum):
    DFG = "dfg"
    SEQUENCE = "sequence"
    PARALLEL = "parallel"
    START_ACTIVITIES = "start_activities"
    END_ACTIVITIES = "end_activities"
    ACTIVITIES = "activities"
    SKIPPABLE = "skippable"
    ACTIVITIES_ALWAYS_HAPPENING = "activities_always_happening"
    MIN_TRACE_LENGTH = "min_trace_length"
    TRACE = "trace"





def apply(
    dfg: Dict[Tuple[str, str], int],
    parameters: Optional[Dict[Any, Any]] = None,
) -> Dict[str, Any]:
    """
    Discovers a footprint object from a DFG

    Parameters
    --------------
    dfg
        DFG
    parameters
        Parameters of the algorithm

    Returns
    --------------
    footprints_obj
        Footprints object
    """
    if parameters is None:
        parameters = {}

    parallel = {(x, y) for (x, y) in dfg if (y, x) in dfg}
    sequence = {(x, y) for (x, y) in dfg if not (y, x) in dfg}
    # replace this if needed
    start_activities = set(utils.dfg_utils.infer_start_activities(dfg))
    # replace this if needed
    end_activities = set(utils.dfg_utils.infer_end_activities(dfg))
    activities = set(utils.dfg_utils.get_activities_from_dfg(dfg))

    return {
        Outputs.SEQUENCE.value: sequence,
        Outputs.PARALLEL.value: parallel,
        Outputs.START_ACTIVITIES.value: start_activities,
        Outputs.END_ACTIVITIES.value: end_activities,
        Outputs.ACTIVITIES.value: activities,
    }