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)
