Source code for pm4py.statistics.passed_time.log.variants.post

from pm4py.algo.discovery.dfg.variants import native, performance
from typing import Optional, Dict, Any
from pm4py.objects.log.obj import EventLog
from pm4py.objects.conversion.log import converter as log_converter




def apply(
    log: EventLog, activity: str, parameters: Optional[Dict[Any, Any]] = None
) -> Dict[str, Any]:
    """
    Gets the time passed to each succeeding activity

    Parameters
    -------------
    log
        Log
    activity
        Activity that we are considering
    parameters
        Possible parameters of the algorithm

    Returns
    -------------
    dictio
        Dictionary containing a 'post' key with the
        list of aggregates times from the given activity to each succeeding activity
    """
    if parameters is None:
        parameters = {}

    log = log_converter.apply(
        log, variant=log_converter.Variants.TO_EVENT_LOG, parameters=parameters
    )

    dfg_frequency = native.native(log, parameters=parameters)
    dfg_performance = performance.performance(log, parameters=parameters)

    post = []
    sum_perf_post = 0.0
    sum_acti_post = 0.0

    for entry in dfg_performance.keys():
        if entry[0] == activity:
            post.append(
                [
                    entry[1],
                    float(dfg_performance[entry]),
                    int(dfg_frequency[entry]),
                ]
            )
            sum_perf_post = sum_perf_post + float(
                dfg_performance[entry]
            ) * float(dfg_frequency[entry])
            sum_acti_post = sum_acti_post + float(dfg_frequency[entry])

    perf_acti_post = 0.0
    if sum_acti_post > 0:
        perf_acti_post = sum_perf_post / sum_acti_post

    return {"post": post, "post_avg_perf": perf_acti_post}