Source code for pm4py.algo.discovery.inductive.base_case.single_activity

'''
    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.base_case.abc import BaseCase
from pm4py.algo.discovery.inductive.dtypes.im_ds import (
    IMDataStructureUVCL,
    IMDataStructureDFG,
)
from pm4py.objects.process_tree.obj import ProcessTree, Operator
from typing import Optional, Dict, Any




class SingleActivityBaseCaseUVCL(BaseCase[IMDataStructureUVCL]):


    @classmethod
    def holds(
        cls,
        obj=IMDataStructureUVCL,
        parameters: Optional[Dict[str, Any]] = None,
    ) -> bool:
        if len(obj.data_structure.keys()) != 1:
            return False
        if len(list(obj.data_structure.keys())[0]) > 1:
            return False
        return True




    @classmethod
    def leaf(
        cls,
        obj=IMDataStructureUVCL,
        parameters: Optional[Dict[str, Any]] = None,
    ) -> ProcessTree:
        for t in obj.data_structure:
            if t:
                return ProcessTree(label=t[0])
            else:
                return ProcessTree()






class SingleActivityBaseCaseDFG(BaseCase[IMDataStructureDFG]):



    @classmethod
    def holds(
        cls,
        obj=IMDataStructureDFG,
        parameters: Optional[Dict[str, Any]] = None,
    ) -> bool:
        return (
            len(obj.dfg.graph) == 0
            and len(
                set(obj.dfg.start_activities).union(obj.dfg.end_activities)
            )
            == 1
        )




    @classmethod
    def leaf(
        cls,
        obj=IMDataStructureDFG,
        parameters: Optional[Dict[str, Any]] = None,
    ) -> ProcessTree:
        leaf = ProcessTree(label=list(obj.dfg.start_activities)[0])
        return leaf