pm4py.algo.filtering.log.cases.case_filter module#

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class pm4py.algo.filtering.log.cases.case_filter.Parameters(*values)[source]#

Bases: Enum

TIMESTAMP_KEY = 'pm4py:param:timestamp_key'#
pm4py.algo.filtering.log.cases.case_filter.filter_on_case_performance(log: EventLog, inf_perf: float, sup_perf: float, parameters: Dict[str | Parameters, Any] | None = None) → EventLog[source]#

Gets a filtered log keeping only traces that satisfy the given performance requirements

Parameters:

  • log – Log

  • inf_perf – Lower bound on the performance

  • sup_perf – Upper bound on the performance

  • parameters – Parameters

Returns:

Filtered log

Return type:

filtered_log

pm4py.algo.filtering.log.cases.case_filter.filter_on_ncases(log: EventLog, max_no_cases: int = 1000) → EventLog[source]#

Get only a specified number of traces from a log

Parameters:

  • log – Log

  • max_no_cases – Desidered number of traces from the log

Returns:

Filtered log

Return type:

filtered_log

pm4py.algo.filtering.log.cases.case_filter.filter_on_case_size(log: EventLog, min_case_size: int = 2, max_case_size=None) → EventLog[source]#

Get only traces in the log with a given size

Parameters:

  • log – Log

  • min_case_size – Minimum desidered size of traces

  • max_case_size – Maximum desidered size of traces

Returns:

Filtered log

Return type:

filtered_log

pm4py.algo.filtering.log.cases.case_filter.satisfy_perf(trace: Trace, inf_perf: float, sup_perf: float, timestamp_key: str) → bool[source]#

Checks if the trace satisfy the performance requirements

Parameters:

  • trace – Trace

  • inf_perf – Lower bound on the performance

  • sup_perf – Upper bound on the performance

  • timestamp_key – Timestamp key

Returns:

Boolean (is True if the trace satisfy the given performance requirements)

Return type:

boolean

pm4py.algo.filtering.log.cases.case_filter.filter_case_performance(log, inf_perf, sup_perf, parameters=None)[source]#
pm4py.algo.filtering.log.cases.case_filter.apply(df, parameters=None)[source]#
pm4py.algo.filtering.log.cases.case_filter.apply_auto_filter(df, parameters=None)[source]#