def __init__(self, nb_chan, group_by):
self.ext_img = '.png'
self.save_img = True
self.show = False
self.img_save_path = 'benchmark_img/'
self.ground_truth = ['gnd_truth']
self.my_cft = cpp_file_tools(nb_chan, group_by, self.ext_img, self.save_img, self.show,ion=False)
def __init__(self, nb_chan, group_by):
#general option
self.save_obj = False
self.ext_img = '.png'
self.save_img = True
self.show = False
self.img_save_path = 'benchmark_img/'
self.my_cft = cpp_file_tools(nb_chan, group_by, self.ext_img, self.save_img, self.show, ion=False)
self.res_dict={}
#simulated benchmark option
self.simulated_dir_name = '../data/RT_classifier/BMIOutputs/0423_r600/'
simulated_iteration = 5
self.simulated_files = [2, 3, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14]
self.simulated_date = 't_0423'
self.simulated_rat = 'r0'
self.simulated_corename = 'healthyOutput_'
self.simulated_change_every = len(self.simulated_files)
self.simulated_first_train = 3
tmp=[]
for i in range(simulated_iteration):
tmp += self.simulated_files
self.simulated_files = tmp
#SCI benchmark option
self.SCI_dir_name = '../data/RT_classifier/BMIOutputs/BMISCIOutputs/'
self.SCI_corename = 'SCIOutput_'
self.SCI_first_train = 5
self.SCI_min_obs = 10
self.SCI_files = {'r31': OrderedDict([
('03', range(1, 25)+range(52, 58)),
('04', range(1, 45)),
('06', range(78, 113)),
('07', range(27, 51)),
('10', range(6, 31)),
('11', range(1, 16)),
('12', range(1, 27)),
('13', range(63, 89)),
('14', range(1, 23))]),
'r32': OrderedDict([
('03', range(25, 52)),
('04', range(45, 83)),
('06', range(42, 78)),
('07', range(51, 82)),
('10', range(31, 69)),
('11', range(1, 36)),
('12', range(27, 54)),
('13', range(32, 63))]),
'r34': OrderedDict([
('06', range(1, 42)),
('07', range(1, 27)),
('11', range(1, 31)),
('12', range(54, 87)),
('13', range(1, 32)),
('14', range(23, 48))])
}
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 change_chan_group_by(self, nb_chan, group_by):
self.my_cft = cpp_file_tools(nb_chan, group_by, self.ext_img, self.save_img, self.show, ion=False)
