def _testing_original_file(self, test_dir, type_data):
dnn_predict_dir = (
"/home/danglab/3P/Net_Space/unnormal/"
+ self.hidden_layer
+ "100ms/"
+ self.artic
+ type_data
+ "test_"
+ str(self.test_number)
+ "/"
)
if not os.path.exists(dnn_predict_dir):
os.makedirs(dnn_predict_dir)
for afile in self.missing_filename_list:
test_arr, factors = read_file_test(
test_dir + afile + "_in.txt", self.n_input_f, "factors"
) # read a missing_feature
energy = test_arr[:, 0] # ko cho energy vao DNN
test_arr = test_arr[:, 1 : self.n_input_f]
factors = 1
self._write_predict_2_file(
dnn_predict_dir + afile + ".txt", energy, self.predict(test_arr), factors
) # write result to file
def _testing_noise_space(self, test_dir, type_data):
for type_test in sorted(os.listdir(test_dir)):
if (not type_test.endswith("zip")) and "output" not in type_test:
type_test_dir = test_dir + type_test + "/"
print type_test_dir
dnn_predict_dir = (
"/home/danglab/3P/Net_Space/unnormal/"
+ self.hidden_layer
+ "100ms/"
+ self.artic
+ type_data
+ "test_"
+ str(self.test_number)
+ "/"
+ type_test
+ "/"
)
if not os.path.exists(dnn_predict_dir):
os.makedirs(dnn_predict_dir)
print type_test
duration = type_test.split("_")[1] # 50ms, 100ms
# listtest = sorted(os.listdir(type_test_dir))
# for afile in listtest:
for prefix_file in self.missing_filename_list:
afile = prefix_file + "_" + duration + "_in.txt"
test_arr, factors = read_file_test(
type_test_dir + afile, self.n_input_f, "factors"
) # read a missing_feature
find_ = [m.start() for m in re.finditer("_", afile)]
energy = test_arr[:, 0] # ko cho energy vao DNN
test_arr = test_arr[:, 1 : self.n_input_f]
factors = 1
self._write_predict_2_file(
dnn_predict_dir + afile.replace(afile[find_[4] : len(afile) - 4], ""),
energy,
self.predict(test_arr),
factors,
) # write result to file