Source code for pm4py.algo.discovery.inductive.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 typing import Optional, Dict, Any, Union

import pandas as pd

from pm4py import util as pmutil
from pm4py.algo.discovery.inductive.dtypes.im_dfg import InductiveDFG
from pm4py.algo.discovery.inductive.dtypes.im_ds import (
    IMDataStructureUVCL,
    IMDataStructureDFG,
)
from pm4py.algo.discovery.inductive.variants.im import IMUVCL
from pm4py.algo.discovery.inductive.variants.imf import IMFUVCL
from pm4py.algo.discovery.inductive.variants.imd import IMD
from pm4py.algo.discovery.inductive.variants.instances import IMInstance
from pm4py.objects.dfg.obj import DFG
from pm4py.objects.log.obj import EventLog
from pm4py.objects.process_tree.obj import ProcessTree
from pm4py.objects.process_tree.utils import generic as pt_util
from pm4py.objects.process_tree.utils.generic import tree_sort
from pm4py.util import constants
import warnings
from pm4py.util import exec_utils
from pm4py.util import xes_constants as xes_util
from pm4py.util.compression import util as comut
from pm4py.util.compression.dtypes import UVCL




class Parameters(Enum):
    ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
    TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY
    CASE_ID_KEY = constants.PARAMETER_CONSTANT_CASEID_KEY





class Variants(Enum):
    IM = IMInstance.IM
    IMf = IMInstance.IMf
    IMd = IMInstance.IMd





def apply(
    obj: Union[EventLog, pd.DataFrame, DFG, UVCL],
    parameters: Optional[Dict[Any, Any]] = None,
    variant=Variants.IM,
) -> ProcessTree:
    if parameters is None:
        parameters = {}
    ack = exec_utils.get_param_value(
        Parameters.ACTIVITY_KEY, parameters, xes_util.DEFAULT_NAME_KEY
    )
    tk = exec_utils.get_param_value(
        Parameters.TIMESTAMP_KEY, parameters, xes_util.DEFAULT_TIMESTAMP_KEY
    )
    cidk = exec_utils.get_param_value(
        Parameters.CASE_ID_KEY, parameters, pmutil.constants.CASE_CONCEPT_NAME
    )

    process_tree = ProcessTree()
    if type(obj) is DFG:
        if variant is not Variants.IMd:
            if constants.SHOW_INTERNAL_WARNINGS:
                warnings.warn(
                    "Inductive Miner Variant requested for DFG artefact is not IMD, resorting back to IMD"
                )
        imd = IMD(parameters)
        idfg = InductiveDFG(dfg=obj, skip=False)
        process_tree = imd.apply(IMDataStructureDFG(idfg), parameters)
    else:
        if type(obj) in [UVCL]:
            uvcl = obj
        else:
            uvcl = comut.get_variants(
                comut.project_univariate(
                    obj, key=ack, df_glue=cidk, df_sorting_criterion_key=tk
                )
            )

        if variant is Variants.IM:
            im = IMUVCL(parameters)
            process_tree = im.apply(IMDataStructureUVCL(uvcl), parameters)
        if variant is Variants.IMf:
            imf = IMFUVCL(parameters)
            process_tree = imf.apply(IMDataStructureUVCL(uvcl), parameters)
        if variant is Variants.IMd:
            imd = IMD(parameters)
            idfg = InductiveDFG(
                dfg=comut.discover_dfg_uvcl(uvcl), skip=() in uvcl
            )
            process_tree = imd.apply(IMDataStructureDFG(idfg), parameters)

    process_tree = pt_util.fold(process_tree)
    tree_sort(process_tree)

    return process_tree