Source code for pm4py.algo.discovery.temporal_profile.variants.log

'''
    This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

    PM4Py is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    PM4Py 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 General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with PM4Py.  If not, see <https://www.gnu.org/licenses/>.
'''
from enum import Enum
from statistics import mean, stdev
from typing import Optional, Dict, Any

from pm4py.objects.conversion.log import converter as log_converter
from pm4py.objects.log.obj import EventLog
from pm4py.util import exec_utils, constants, xes_constants
from pm4py.util import typing
from pm4py.util.business_hours import BusinessHours


[docs]class Parameters(Enum): ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY START_TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY BUSINESS_HOURS = "business_hours" WORKTIMING = "worktiming" WEEKENDS = "weekends" WORKCALENDAR = "workcalendar"
[docs]def apply(log: EventLog, parameters: Optional[Dict[Any, Any]] = None) -> typing.TemporalProfile: """ Gets the temporal profile from the log. Implements the approach described in: Stertz, Florian, J├╝rgen Mangler, and Stefanie Rinderle-Ma. "Temporal Conformance Checking at Runtime based on Time-infused Process Models." arXiv preprint arXiv:2008.07262 (2020). Parameters ---------- log Event log parameters Parameters, including: - Parameters.ACTIVITY_KEY => the attribute to use as activity - Parameters.START_TIMESTAMP_KEY => the attribute to use as start timestamp - Parameters.TIMESTAMP_KEY => the attribute to use as timestamp - Parameters.BUSINESS_HOURS => calculates the difference of time based on the business hours, not the total time. Default: False - Parameters.WORKTIMING => work schedule of the company (provided as a list where the first number is the start of the work time, and the second number is the end of the work time), if business hours are enabled Default: [7, 17] (work shift from 07:00 to 17:00) - Parameters.WEEKENDS => indexes of the days of the week that are weekend Default: [6, 7] (weekends are Saturday and Sunday) Returns ------- temporal_profile Temporal profile of the log """ if parameters is None: parameters = {} log = log_converter.apply(log, variant=log_converter.Variants.TO_EVENT_LOG, parameters=parameters) business_hours = exec_utils.get_param_value(Parameters.BUSINESS_HOURS, parameters, False) worktiming = exec_utils.get_param_value(Parameters.WORKTIMING, parameters, [7, 17]) weekends = exec_utils.get_param_value(Parameters.WEEKENDS, parameters, [6, 7]) workcalendar = exec_utils.get_param_value(Parameters.WORKCALENDAR, parameters, constants.DEFAULT_BUSINESS_HOURS_WORKCALENDAR) 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) diff_time_recordings = {} for trace in log: for i in range(len(trace) - 1): act_i = trace[i][activity_key] time_i = trace[i][timestamp_key].timestamp() for j in range(i + 1, len(trace)): time_j = trace[j][start_timestamp_key].timestamp() if time_j >= time_i: act_j = trace[j][activity_key] if not (act_i, act_j) in diff_time_recordings: diff_time_recordings[(act_i, act_j)] = [] if business_hours: bh = BusinessHours(trace[i][timestamp_key].replace(tzinfo=None), trace[j][start_timestamp_key].replace(tzinfo=None), worktiming=worktiming, weekends=weekends, workcalendar=workcalendar) diff_time_recordings[(act_i, act_j)].append(bh.getseconds()) else: diff_time_recordings[(act_i, act_j)].append(time_j - time_i) temporal_profile = {} for ac in diff_time_recordings: if len(diff_time_recordings[ac]) > 1: temporal_profile[ac] = (mean(diff_time_recordings[ac]), stdev(diff_time_recordings[ac])) else: temporal_profile[ac] = (diff_time_recordings[ac][0], 0) return temporal_profile