Source code for pm4py.statistics.traces.cycle_time.log.get

'''
    PM4Py – A Process Mining Library for Python
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This program is free software: you can redistribute it and/or modify
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published by the Free Software Foundation, either version 3 of the
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
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'''
from pm4py.objects.log.obj import EventLog, Trace
from pm4py.util import exec_utils, constants, xes_constants
from enum import Enum
from pm4py.objects.conversion.log import converter
from pm4py.statistics.traces.cycle_time.util import compute
from typing import Union, Dict, Optional, Any


[docs] class Parameters(Enum): TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY START_TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY
[docs] def apply( log_or_trace: Union[Trace, EventLog], parameters: Optional[Dict[Union[str, Parameters], Any]] = None, ) -> float: """ Computes the cycle time starting from an event log or a trace object The definition that has been followed is the one proposed in: https://www.presentationeze.com/presentations/lean-manufacturing-just-in-time/lean-manufacturing-just-in-time-full-details/process-cycle-time-analysis/calculate-cycle-time/#:~:text=Cycle%20time%20%3D%20Average%20time%20between,is%2024%20minutes%20on%20average. So: Cycle time = Average time between completion of units. Example taken from the website: Consider a manufacturing facility, which is producing 100 units of product per 40 hour week. The average throughput rate is 1 unit per 0.4 hours, which is one unit every 24 minutes. Therefore the cycle time is 24 minutes on average. Parameters ------------------ log_or_trace Log or trace parameters Parameters of the algorithm, including: - Parameters.START_TIMESTAMP_KEY => the attribute acting as start timestamp - Parameters.TIMESTAMP_KEY => the attribute acting as timestamp Returns ------------------ cycle_time Cycle time """ if parameters is None: parameters = {} start_timestamp_key = exec_utils.get_param_value( Parameters.START_TIMESTAMP_KEY, parameters, xes_constants.DEFAULT_TIMESTAMP_KEY, ) timestamp_key = exec_utils.get_param_value( Parameters.TIMESTAMP_KEY, parameters, xes_constants.DEFAULT_TIMESTAMP_KEY, ) if type(log_or_trace) is Trace: log = EventLog() log.append(log_or_trace) else: log = converter.apply( log_or_trace, variant=converter.Variants.TO_EVENT_LOG, parameters=parameters, ) events = [ (x[start_timestamp_key].timestamp(), x[timestamp_key].timestamp()) for trace in log for x in trace ] return compute.cycle_time(events, len(log))