def KRY_Regularizer(ls_graph, ls_lb_tr, int_iter, str_file, ls_lb_tl): ls_lb_nu = src.copy_list(ls_lb_tr) ls_lb_tlnu = src.copy_list(ls_lb_tl) flo_timestart = time() mtx_lb_pr = src.KrylovRegularizer(ls_graph, ls_lb_nu, int_iter) flo_timefinal = time() - flo_timestart # Getting Results ls_lb_pr = src.convert_to_list(mtx_lb_pr) ls_lb_prflo = src.float_list_normalization(ls_lb_pr) ls_temp_lb = ls_lb_prflo np.savetxt("Pr" + str_file, (tuple(ls_temp_lb) + tuple(ls_lb_tlnu))) ls_lb_alpha = src.generalizeAlphaCut(np.array(ls_lb_pr), 0.5, 0, 1) ls_lb_alphaint = src.int_list_normalization(ls_lb_alpha) flo_acc = src.accuracyTest(ls_lb_alphaint, ls_lb_tlnu) flo_TP, flo_TN, flo_FP, flo_FN = src.confussionMatrix( ls_lb_alphaint, ls_lb_tlnu) np.savetxt("Rs" + str_file, (flo_TP, flo_TN, flo_FP, flo_FN, flo_acc, flo_timefinal)) print str_file + " done!" return ls_lb_pr
string_nome_temp = string_nome + str_graph_type + str( floint_graph_hyper) + str_reg_type + "L" + str(int_per) + "%.txt" # Saving Performance metrics and other results np.savetxt(string_nome_temp, (TP, TN, FP, FN, acc, timefinal_gc, timefinal_gr)) print acc #----- (end) SMOOTH OPERATOR REGULARIZATION (end) -----# #----- (begin) KRYLOV REGULARIZATION (begin) -----# print "< < Krylov > >" # Checking Regularization str_reg_type = "Kry" timestart = time() respK = src.KrylovRegularizer(Gr_K, label_proc, 100) # --------------------> Regulating timefinal_gr = time() - timestart respK = src.convert_to_list(respK) # Converting to list, the result of the regulation dataK = src.float_list_normalization(respK) # Mapping results as floats temp_respK = dataK string_nome_data_temp = string_nome_data + str_graph_type + str( floint_graph_hyper) + str_reg_type + "L" + str(int_per) + "%.txt" # Saving results of data np.savetxt(string_nome_data_temp, (temp_respK)) repK = src.generalizeAlphaCut(np.array(respK), 0.5, 0, 1)