pm4py.algo.transformation.log_to_target.variants.next_activity module#

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class pm4py.algo.transformation.log_to_target.variants.next_activity.Parameters(*values)[source]#

Bases: Enum

ACTIVITIES = 'activities'#
ACTIVITY_KEY = 'pm4py:param:activity_key'#
ENABLE_PADDING = 'enable_padding'#
PAD_SIZE = 'pad_size'#
pm4py.algo.transformation.log_to_target.variants.next_activity.apply(log: EventLog | EventStream | DataFrame, parameters: Dict[Any, Any] | None = None) → Tuple[List[List[List[int]]], List[str]][source]#

Returns a list of matrixes (one for every case). Every matrix contains as many rows as many events are contained in the case (an automatic padding option is also available), and as many columns as many distinct activities are in the log.

The corresponding activity to the given event is assigned to the value 1; the remaining activities are assigned to the value 0.

Parameters:

  • log – Event log / Event stream / Pandas dataframe

  • parameters – Parameters of the algorithm, including: - Parameters.ACTIVITIES => list of activities to consider - Parameters.ACTIVITY_KEY => attribute that should be used as activity - Parameters.ENABLE_PADDING => enables the padding (the length of cases is normalized) - Parameters.PAD_SIZE => the size of the padding

Returns:

  • target – The aforementioned list of matrixes.

  • activities – The considered list of activities