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