pm4py.algo.discovery.minimum_self_distance.variants.pandas module#

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class pm4py.algo.discovery.minimum_self_distance.variants.pandas.Parameters(*values)[source]#

Bases: Enum

ACTIVITY_KEY = 'pm4py:param:activity_key'#
CASE_ID_KEY = 'pm4py:param:case_id_key'#
pm4py.algo.discovery.minimum_self_distance.variants.pandas.apply(df, parameters=None)[source]#

This algorithm computes the minimum self-distance for each activity observed in an event log. The self distance of a in <a> is infinity, of a in <a,a> is 0, in <a,b,a> is 1, etc. The minimum self distance is the minimal observed self distance value in the event log. The activity key needs to be specified in the parameters input object (if None, default value ‘concept:name’ is used).

Parameters:

  • df – Pandas dataframe

  • parameters – parameters object;

Return type:

dict mapping an activity to its self-distance, if it exists, otherwise it is not part of the dict.