def O_Task(self): # Get a new knowledgeability table knowledgeability = Task.NKnowledgeability_Task(self.hypo_table, self.num_hypo, self.num_feature, self.num_label, self.knowledge) # knowledgeability = [self.delta_g_h] for n in range(len(knowledgeability)): print(knowledgeability[n]) p, s = Task.Probability_Task(self.hypo_table, self.num_hypo, self.num_feature, self.num_label, copy.deepcopy(knowledgeability[n]), 1000) print(p, s, sep="\n") Report.Plot_P(Task.Average_Hypo(p, self.num_hypo), self.num_feature, n) # If reaches the identitly matrix, the loop will be ended if numpy.array_equal(knowledgeability[n], numpy.eye(self.num_hypo)): break mtp.legend() mtp.show() return