Source code for pm4py.algo.discovery.inductive.cuts.abc

from abc import ABC, abstractmethod
from typing import (
    Optional,
    List,
    Collection,
    Any,
    Tuple,
    Generic,
    TypeVar,
    Dict,
)

from pm4py.algo.discovery.inductive.dtypes.im_ds import IMDataStructure
from pm4py.objects.process_tree.obj import ProcessTree

T = TypeVar("T", bound=IMDataStructure)




[docs]
class Cut(ABC, Generic[T]):



[docs]
    @classmethod
    @abstractmethod
    def operator(
        cls, parameters: Optional[Dict[str, Any]] = None
    ) -> ProcessTree:
        pass





[docs]
    @classmethod
    @abstractmethod
    def holds(
        cls, obj: T, parameters: Optional[Dict[str, Any]] = None
    ) -> Optional[List[Collection[Any]]]:
        pass





[docs]
    @classmethod
    def apply(
        cls, obj: T, parameters: Optional[Dict[str, Any]] = None
    ) -> Optional[Tuple[ProcessTree, List[T]]]:
        g = cls.holds(obj, parameters)
        return (
            (cls.operator(), cls.project(obj, g, parameters))
            if g is not None
            else g
        )





[docs]
    @classmethod
    @abstractmethod
    def project(
        cls,
        obj: T,
        groups: List[Collection[Any]],
        parameters: Optional[Dict[str, Any]] = None,
    ) -> List[T]:
        """
        Projection of the given data object (Generic type T).
        Returns a corresponding process tree and the projected sub logs according to the identified groups.
        A precondition of the project function is that it holds on the object for the given Object
        """
        pass