pm4py.algo.discovery.temporal_profile.variants package

Submodules

pm4py.algo.discovery.temporal_profile.variants.dataframe module

class pm4py.algo.discovery.temporal_profile.variants.dataframe.Parameters(value)[source]

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'
CASE_ID_KEY = 'case_id_glue'
START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'
pm4py.algo.discovery.temporal_profile.variants.dataframe.apply(df: pandas.core.frame.DataFrame, parameters: Optional[Dict[Any, Any]] = None) → Dict[Tuple[str, str], Tuple[float, float]][source]

Gets the temporal profile from a dataframe.

Implements the approach described in: Stertz, Florian, Jürgen Mangler, and Stefanie Rinderle-Ma. “Temporal Conformance Checking at Runtime based on Time-infused Process Models.” arXiv preprint arXiv:2008.07262 (2020).

Parameters
  • df – Dataframe

  • parameters – Parameters, including: - Parameters.ACTIVITY_KEY => the column to use as activity - Parameters.START_TIMESTAMP_KEY => the column to use as start timestamp - Parameters.TIMESTAMP_KEY => the column to use as timestamp - Parameters.CASE_ID_KEY => the column to use as case ID

Returns

Temporal profile of the dataframe

Return type

temporal_profile

pm4py.algo.discovery.temporal_profile.variants.log module

class pm4py.algo.discovery.temporal_profile.variants.log.Parameters(value)[source]

Bases: enum.Enum

An enumeration.

ACTIVITY_KEY = 'pm4py:param:activity_key'
BUSINESS_HOURS = 'business_hours'
START_TIMESTAMP_KEY = 'pm4py:param:start_timestamp_key'
TIMESTAMP_KEY = 'pm4py:param:timestamp_key'
WEEKENDS = 'weekends'
WORKTIMING = 'worktiming'
pm4py.algo.discovery.temporal_profile.variants.log.apply(log: pm4py.objects.log.obj.EventLog, parameters: Optional[Dict[Any, Any]] = None) → Dict[Tuple[str, str], Tuple[float, float]][source]

Gets the temporal profile from the log.

Implements the approach described in: Stertz, Florian, Jürgen 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 of the log

Return type

temporal_profile

Module contents