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)