Source code for pm4py.statistics.overlap.cases.log.get

from enum import Enum
from typing import Dict, Optional, Any, List

from pm4py.objects.log.obj import EventLog
from pm4py.statistics.overlap.utils import compute
from pm4py.util import exec_utils, constants, xes_constants
from pm4py.objects.conversion.log import converter


[docs]class Parameters(Enum): TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY START_TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY
[docs]def apply(log: EventLog, parameters: Optional[Dict[str, Any]] = None) -> List[int]: """ Computes the case overlap statistic from an interval event log Parameters ----------------- log Interval event log parameters Parameters of the algorithm, including: - Parameters.TIMESTAMP_KEY => attribute representing the completion timestamp - Parameters.START_TIMESTAMP_KEY => attribute representing the start timestamp Returns ---------------- case overlap List associating to each case the number of open cases during the life of a case """ if parameters is None: parameters = {} log = converter.apply(log, parameters=parameters) 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) points = [] for trace in log: case_points = [] for event in trace: case_points.append((event[start_timestamp_key].timestamp(), event[timestamp_key].timestamp())) points.append((min(x[0] for x in case_points), max(x[1] for x in case_points))) return compute.apply(points, parameters=parameters)