from datetime import timedelta
from utils import mean, stdev, relative_change, classify_anomalies, \
- convert_csv_to_pretty_txt
+ convert_csv_to_pretty_txt, relative_change_stdev
REGEX_NIC = re.compile(r'\d*ge\dp\d\D*\d*')
item.append(round(data_r_stdev / 1000000, 2))
else:
data_r_mean = None
+ data_r_stdev = None
item.extend([None, None])
data_c = tbl_dict[tst_name]["cmp-data"]
if data_c:
item.append(round(data_c_stdev / 1000000, 2))
else:
data_c_mean = None
+ data_c_stdev = None
item.extend([None, None])
- if data_r_mean and data_c_mean is not None:
- item.append(round(relative_change(data_r_mean, data_c_mean), 2))
+ if data_r_mean and data_c_mean:
delta, d_stdev = relative_change_stdev(
data_r_mean, data_c_mean, data_r_stdev, data_c_stdev)
item.append(round(delta, 2))