Source code for pm4py.algo.conformance.footprints.variants.log_extensive

'''
    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




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"





class ConfOutputs(Enum):
    FOOTPRINTS = "footprints"
    START_ACTIVITIES = "start_activities"
    END_ACTIVITIES = "end_activities"
    MIN_LENGTH_FIT = "min_length_fit"
    IS_FOOTPRINTS_FIT = "is_footprints_fit"





def apply(
    log_footprints: Dict[str, Any],
    model_footprints: Dict[str, Any],
    parameters: Optional[Dict[Any, Any]] = None,
) -> Dict[str, Any]:
    """
    Apply footprints conformance between a log footprints object
    and a model footprints object

    Parameters
    -----------------
    log_footprints
        Footprints of the log (entire log)
    model_footprints
        Footprints of the model
    parameters
        Parameters of the algorithm

    Returns
    ------------------
    violations
        Dictionary containing all the violations
    """
    if parameters is None:
        parameters = {}

    if type(log_footprints) is list:
        raise Exception(
            "it is possible to apply this variant only on overall log footprints, not trace-by-trace footprints!"
        )

    log_configurations = log_footprints[Outputs.SEQUENCE.value].union(
        log_footprints[Outputs.PARALLEL.value]
    )
    model_configurations = model_footprints[Outputs.SEQUENCE.value].union(
        model_footprints[Outputs.PARALLEL.value]
    )

    ret = {}
    ret[ConfOutputs.FOOTPRINTS.value] = set(
        x for x in log_configurations if x not in model_configurations
    )
    ret[ConfOutputs.START_ACTIVITIES.value] = (
        set(
            x
            for x in log_footprints[Outputs.START_ACTIVITIES.value]
            if x not in model_footprints[Outputs.START_ACTIVITIES.value]
        )
        if Outputs.START_ACTIVITIES.value in model_footprints
        else set()
    )
    ret[ConfOutputs.END_ACTIVITIES.value] = (
        set(
            x
            for x in log_footprints[Outputs.END_ACTIVITIES.value]
            if x not in model_footprints[Outputs.END_ACTIVITIES.value]
        )
        if Outputs.END_ACTIVITIES.value in model_footprints
        else set()
    )
    ret[ConfOutputs.MIN_LENGTH_FIT.value] = (
        log_footprints[Outputs.MIN_TRACE_LENGTH.value]
        >= model_footprints[Outputs.MIN_TRACE_LENGTH.value]
        if Outputs.MIN_TRACE_LENGTH.value in log_footprints
        and Outputs.MIN_TRACE_LENGTH.value in model_footprints
        else True
    )
    ret[ConfOutputs.IS_FOOTPRINTS_FIT.value] = (
        len(ret[ConfOutputs.FOOTPRINTS.value]) == 0
        and len(ret[ConfOutputs.START_ACTIVITIES.value]) == 0
        and len(ret[ConfOutputs.END_ACTIVITIES.value]) == 0
        and ret[ConfOutputs.MIN_LENGTH_FIT.value]
    )

    return ret