import brain_state_calculate_c as bsc import cpp_file_tools_c as cft import pstats, cProfile file=["F:/data/r617/0620healthyOutput_1.txt","F:/data/r617/0620healthyOutput_2.txt","F:/data/r617/0620healthyOutput_3.txt"] my_bsc = bsc.brain_state_calculate(32) my_cft = cft.cpp_file_tools(32, 1) # cProfile.runctx('my_bsc.init_networks(file, my_cft)', globals(), locals(), "Profile.prof") # s = pstats.Stats("Profile.prof") # s.strip_dirs().sort_stats("time").print_stats() my_bsc.init_networks(file, my_cft) print "END kohonen" #my_bsc.train_one_file(file[1], my_cft, is_healthy=False, new_day=True, obs_to_add=0, with_RL=True, train_mod_chan=False, on_stim=False, autosave=False) cProfile.runctx('my_bsc.train_one_file(file[1], my_cft, is_healthy=False, new_day=True, obs_to_add=0, with_RL=True, train_mod_chan=False, on_stim=False, autosave=False)', globals(), locals(), "Profile.prof") s = pstats.Stats("Profile.prof") s.strip_dirs().sort_stats("time").print_stats() print 'END'
def init_classifier(self): my_bsc = bsc.brain_state_calculate(self.input_count_classifier, 'koho', self.ext_img, self.save_img, self.show) self.classifier = my_bsc