Source code for pm4py.statistics.concurrent_activities.log.get

from enum import Enum

from pm4py.objects.conversion.log import converter
from pm4py.objects.log.util import sorting
from pm4py.util import exec_utils, constants, xes_constants
from typing import Optional, Dict, Any, Union, Tuple
from pm4py.objects.log.obj import EventLog




class Parameters(Enum):
    ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
    TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY
    START_TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY
    STRICT = "strict"





def apply(
    interval_log: EventLog,
    parameters: Optional[Dict[Union[str, Parameters], Any]] = None,
) -> Dict[Tuple[str, str], int]:
    """
    Gets the number of times for which two activities have been concurrent in the log

    Parameters
    --------------
    interval_log
        Interval event log
    parameters
        Parameters of the algorithm, including:
        - Parameters.ACTIVITY_KEY => activity key
        - Parameters.START_TIMESTAMP_KEY => start timestamp
        - Parameters.TIMESTAMP_KEY => complete timestamp
        - Parameters.STRICT => Determine if only entries that are strictly concurrent
            (i.e. the length of the intersection as real interval is > 0) should be obtained. Default: False

    Returns
    --------------
    ret_dict
        Dictionaries associating to a couple of activities (tuple) the number of times for which they have been
        executed in parallel in the log
    """
    if parameters is None:
        parameters = {}

    interval_log = converter.apply(
        interval_log,
        variant=converter.Variants.TO_EVENT_LOG,
        parameters=parameters,
    )

    activity_key = exec_utils.get_param_value(
        Parameters.ACTIVITY_KEY, parameters, xes_constants.DEFAULT_NAME_KEY
    )
    timestamp_key = exec_utils.get_param_value(
        Parameters.TIMESTAMP_KEY,
        parameters,
        xes_constants.DEFAULT_TIMESTAMP_KEY,
    )
    start_timestamp_key = exec_utils.get_param_value(
        Parameters.START_TIMESTAMP_KEY,
        parameters,
        xes_constants.DEFAULT_TIMESTAMP_KEY,
    )
    strict = exec_utils.get_param_value(Parameters.STRICT, parameters, False)

    ret_dict = {}
    for trace in interval_log:
        sorted_trace = sorting.sort_timestamp_trace(trace, start_timestamp_key)
        i = 0
        while i < len(sorted_trace):
            act1 = sorted_trace[i][activity_key]
            ts1 = sorted_trace[i][start_timestamp_key]
            tc1 = sorted_trace[i][timestamp_key]
            j = i + 1
            while j < len(sorted_trace):
                ts2 = sorted_trace[j][start_timestamp_key]
                tc2 = sorted_trace[j][timestamp_key]
                act2 = sorted_trace[j][activity_key]
                if max(ts1, ts2) <= min(tc1, tc2):
                    if not strict or max(ts1, ts2) < min(tc1, tc2):
                        # avoid getting two entries for the same set of
                        # concurrent activities
                        tup = tuple(sorted((act1, act2)))
                        if tup not in ret_dict:
                            ret_dict[tup] = 0
                        ret_dict[tup] = ret_dict[tup] + 1
                else:
                    break
                j = j + 1
            i = i + 1

    return ret_dict