#/usr/bin/env python # -*- coding: utf-8 -*- from modeling import get_model from modeling import testdata from gp_calc import monte_carlo import random print '##make model##' model = get_model.transition_model(data = testdata.amazlet(), goal = '__mode=showcode', max_state = 5) print "##model done##" target = '__mode=showcode' print "target URL:", target print "##simulation start##" sim = monte_carlo.mc_sim(data = model) gp = sim.get_gp() print '## show model data ##' print sim.model print '## end ##' print '## show gp list ##' for k, v in sorted(gp.items(), key = lambda x:x[1], reverse = True): print k, ":", int(v)
#/usr/bin/env python # -*- coding: utf-8 -*- from modeling import get_model from modeling import testdata from gp_calc import monte_carlo import random print '##make model##' #疑似データ #model = get_model.transition_model(data = testdata.pseudo_shingakunet(), # goal = 'https://shingakunet.com/net2/shiryoSeikyu/entry/complete', # max_state = 5) #本データ model = get_model.transition_model(data = testdata.shingakunet(num = 1), goal = '/shiryoSeikyu/entry/complete', max_state = 5) print "##model done##" target = '/shiryoSeikyu/entry/complete' print "target URL:", target print "##simulation start##" sim = monte_carlo.mc_sim(data = model) gp = sim.get_gp() print '## show model data ##' print sim.model
#/usr/bin/env python # -*- coding: utf-8 -*- from modeling import get_model from modeling import testdata from gp_calc import monte_carlo import random print '##make model##' model = get_model.transition_model(data = testdata.amazlet(), upper_limit_of_lower_dic = 5) i = 0 cv = random.randint(0, len(model)) print "##model done##" for k, v in model.items(): if i == cv: print "CV: ", k model[k]["CV_flag"] = 1 i += 1 print k print "##simulation start##" sim = monte_carlo.mc_sim(data = model) gp = sim.get_gp() print gp