pm4py.algo.clustering.trace_attribute_driven.variants.sim_calc module

class pm4py.algo.clustering.trace_attribute_driven.variants.sim_calc.Parameters(*values)

Bases: Enum

ATTRIBUTE_KEY = 'pm4py:param:attribute_key'

ACTIVITY_KEY = 'pm4py:param:activity_key'

SINGLE = 'single'

BINARIZE = 'binarize'

POSITIVE = 'positive'

LOWER_PERCENT = 'lower_percent'

pm4py.algo.clustering.trace_attribute_driven.variants.sim_calc.inner_prod_calc(df)

pm4py.algo.clustering.trace_attribute_driven.variants.sim_calc.dist_calc(var_list_1, var_list_2, log1, log2, freq_thres, num, alpha, parameters=None)

this function compare the activity similarity between two sublogs via the two lists of variants. :param var_list_1: lists of variants in sublog 1 :param var_list_2: lists of variants in sublog 2 :param freq_thres: same as sublog2df() :param log1: input sublog1 of sublog2df(), which must correspond to var_list_1 :param log2: input sublog2 of sublog2df(), which must correspond to var_list_2 :param alpha: the weight parameter between activity similarity and succession similarity, which belongs to (0,1) :param parameters: state which linkage method to use :return: the similarity value between two sublogs