Source code for pm4py.visualization.dfg.visualizer

'''
    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.visualization.common import gview
from pm4py.visualization.common import save as gsave
from pm4py.visualization.dfg.variants import frequency, performance, cost
from enum import Enum
from pm4py.util import exec_utils
from copy import deepcopy
from pm4py.visualization.common.gview import serialize, serialize_dot
from typing import Optional, Dict, Any, Tuple
import graphviz
from pm4py.objects.log.obj import EventLog




class Variants(Enum):
    FREQUENCY = frequency
    PERFORMANCE = performance
    COST = cost



DEFAULT_VARIANT = Variants.FREQUENCY




def apply(
    dfg0: Dict[Tuple[str, str], float],
    log: EventLog = None,
    activities_count: Dict[str, int] = None,
    serv_time: Dict[str, float] = None,
    parameters: Optional[Dict[Any, Any]] = None,
    variant=DEFAULT_VARIANT,
) -> graphviz.Digraph:
    """
    Visualize a frequency/performance directly-follows graph

    Parameters
    -----------------
    dfg0
        Directly-follows graph
    log
        (if provided) Event log for the calculation of statistics
    activities_count
        (if provided) Dictionary associating to each activity the number of occurrences in the log.
    serv_time
        (if provided) Dictionary associating to each activity the average service time
    parameters
        Variant-specific parameters
    variant
        Variant:
        - Frequency DFG representation
        - Performance DFG representation

    Returns
    -----------------
    gviz
        Graphviz digraph
    """
    dfg = deepcopy(dfg0)
    return exec_utils.get_variant(variant).apply(
        dfg,
        log=log,
        activities_count=activities_count,
        serv_time=serv_time,
        parameters=parameters,
    )





def save(gviz, output_file_path, parameters=None):
    """
    Save the diagram

    Parameters
    -----------
    gviz
        GraphViz diagram
    output_file_path
        Path where the GraphViz output should be saved
    """
    gsave.save(gviz, output_file_path, parameters=parameters)
    return ""





def view(gviz, parameters=None):
    """
    View the diagram

    Parameters
    -----------
    gviz
        GraphViz diagram
    """
    return gview.view(gviz, parameters=parameters)





def matplotlib_view(gviz, parameters=None):
    """
    Views the diagram using Matplotlib

    Parameters
    ---------------
    gviz
        Graphviz
    """

    return gview.matplotlib_view(gviz, parameters=parameters)