def create_t_values(): if not os.path.exists(t_values_directory): os.makedirs(t_values_directory) with open("base.txt", "r") as base: benign = base.readlines() with open("input.txt", "r") as tar: target = tar.readlines() loopcount = 0 for b in benign: for t in target: loopcount += 1 sys.stdout.write('\r') sys.stdout.write("[%-20s] %d%%" % ('*'*int((20*loopcount)/(len(benign)*len(target))), ((100*loopcount)/(len(benign)*len(target))))) sys.stdout.flush() b_name = b.split("/")[-1].split(".")[0] t_name = t.split("/")[-1].split(".")[0] data1 = com.load_matrix(b.strip()) data2 = com.load_matrix(t.strip()) for c in range(num_hpc): for r in range(num_indicator): dis1 = select_column(data1, c + r) dis2 = select_column(data2, c + r) m1, v1 = mean_var(dis1) m2, v2 = mean_var(dis2) t_val = (m1 - m2) / float((math.sqrt((v1 + v2)/float(len(dis1))))) Matrix[r][c] = t_val com.save_matrix(t_values_directory+b_name+"_"+t_name+".txt", Matrix)
def execute_matrix_generator(self): print('Gen matrix...') self.matrix_a = self._gen_matrix() self.matrix_b = self._gen_matrix() remove_file(self.file_name) print('Saving to file...') save_matrix(self.file_name, self.matrix_a) save_matrix(self.file_name, self.matrix_b) return self.file_name
def proccess_matrix_summary(self): print('Read matrix...') file_name = self.file_loader.get_file() res = self._read_matrix(file_name) if not res: return print('Sum matrix') matrix_a, matrix_b = res file_name = get_files_directory() + 'F1.txt' new_matrix = self._sum_matrix(matrix_a, matrix_b) print('Saving to file...') remove_file(file_name) save_matrix(file_name, new_matrix) return new_matrix
def calculate_single(t): if not os.path.exists(bin_directory): os.makedirs(bin_directory) with open("base.txt", "r") as base: benign = base.readlines() for b in benign: b_name = b.split("/")[-1].split(".")[0] t_name = t.split("/")[-1].split(".")[0] data = com.load_matrix(t_stat.t_values_directory + b_name + "_" + t_name + ".txt") for r in range(t_stat.num_indicator): for c in range(t_stat.num_hpc): Matrix[r][c] = 0 if abs(data[r][c]) >= t_stat.t_critical: Matrix[r][c] = 1 com.save_matrix(bin_directory + b_name + "_" + t_name + ".txt", Matrix)
def create_t_values_single_file(t): if not os.path.exists(t_values_directory): os.makedirs(t_values_directory) with open("base.txt", "r") as base: benign = base.readlines() for b in benign: b_name = b.split("/")[-1].split(".")[0] t_name = t.split("/")[-1].split(".")[0] data1 = com.load_matrix(b.strip()) data2 = com.load_matrix(t.strip()) for c in range(num_hpc): for r in range(num_indicator): dis1 = select_column(data1, c + r) dis2 = select_column(data2, c + r) m1, v1 = mean_var(dis1) m2, v2 = mean_var(dis2) t_val = (m1 - m2) / float((math.sqrt((v1 + v2)/float(len(dis1))))) Matrix[r][c] = t_val com.save_matrix(t_values_directory+b_name+"_"+t_name+".txt", Matrix)