from string import replace
from errors import PresentationError
-from utils import mean, stdev, relative_change, remove_outliers
+from utils import mean, stdev, relative_change, find_outliers
def generate_tables(spec, data):
for tst_name in tbl_dict.keys():
item = [tbl_dict[tst_name]["name"], ]
if tbl_dict[tst_name]["ref-data"]:
- item.append(round(mean(remove_outliers(
- tbl_dict[tst_name]["ref-data"],
- table["outlier-const"])) / 1000000, 2))
- item.append(round(stdev(remove_outliers(
- tbl_dict[tst_name]["ref-data"],
- table["outlier-const"])) / 1000000, 2))
+ data_t, _ = find_outliers(tbl_dict[tst_name]["ref-data"],
+ table["outlier-const"])
+ item.append(round(mean(data_t) / 1000000, 2))
+ item.append(round(stdev(data_t) / 1000000, 2))
else:
item.extend([None, None])
if tbl_dict[tst_name]["cmp-data"]:
- item.append(round(mean(remove_outliers(
- tbl_dict[tst_name]["cmp-data"],
- table["outlier-const"])) / 1000000, 2))
- item.append(round(stdev(remove_outliers(
- tbl_dict[tst_name]["cmp-data"],
- table["outlier-const"])) / 1000000, 2))
+ data_t, _ = find_outliers(tbl_dict[tst_name]["cmp-data"],
+ table["outlier-const"])
+ item.append(round(mean(data_t) / 1000000, 2))
+ item.append(round(stdev(data_t) / 1000000, 2))
else:
item.extend([None, None])
if item[1] is not None and item[3] is not None: