Source code for pm4py.algo.discovery.powl.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.inductive.dtypes.im_ds import IMDataStructureUVCL
from pm4py.algo.discovery.powl.inductive.variants.im_dynamic_clustering_frequencies import (
    POWLInductiveMinerDynamicClusteringFrequency, )
from pm4py.algo.discovery.powl.inductive.variants.im_tree import IMBasePOWL
from pm4py.algo.discovery.powl.inductive.variants.im_brute_force import (
    POWLInductiveMinerBruteForce,
)
from pm4py.algo.discovery.powl.inductive.variants.im_maximal import (
    POWLInductiveMinerMaximalOrder,
)
from pm4py.algo.discovery.powl.inductive.variants.powl_discovery_varaints import (
    POWLDiscoveryVariant, )

from pm4py import util
from pm4py.algo.discovery.inductive.algorithm import Parameters
from pm4py.objects.powl.obj import POWL

from pm4py.util import xes_constants as xes_util
from pm4py.util.compression import util as comut
from pm4py.util.compression.dtypes import UVCL

from pm4py.util import exec_utils
from typing import Optional, Dict, Any, Union, Type
from pm4py.objects.log.obj import EventLog
import pandas as pd




def get_variant(variant: POWLDiscoveryVariant) -> Type[IMBasePOWL]:
    if variant == POWLDiscoveryVariant.TREE:
        return IMBasePOWL
    elif variant == POWLDiscoveryVariant.BRUTE_FORCE:
        return POWLInductiveMinerBruteForce
    elif variant == POWLDiscoveryVariant.MAXIMAL:
        return POWLInductiveMinerMaximalOrder
    elif variant == POWLDiscoveryVariant.DYNAMIC_CLUSTERING:
        return POWLInductiveMinerDynamicClusteringFrequency
    else:
        raise Exception("Invalid Variant!")





def apply(
    obj: Union[EventLog, pd.DataFrame, UVCL],
    parameters: Optional[Dict[Any, Any]] = None,
    variant=POWLDiscoveryVariant.MAXIMAL,
) -> POWL:
    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, util.constants.CASE_CONCEPT_NAME
    )
    if type(obj) in [EventLog, pd.DataFrame]:
        uvcl = comut.get_variants(
            comut.project_univariate(
                obj, key=ack, df_glue=cidk, df_sorting_criterion_key=tk
            )
        )
    else:
        uvcl = obj

    algorithm = get_variant(variant)
    im = algorithm(parameters)
    res = im.apply(IMDataStructureUVCL(uvcl), parameters)
    res = res.simplify()

    return res