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"], 2)) / 1000000, 2))
- item.append(round(stdev(remove_outliers(
- tbl_dict[tst_name]["ref-data"], 2)) / 1000000, 2))
+ data_t = remove_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"], 2)) / 1000000, 2))
- item.append(round(stdev(remove_outliers(
- tbl_dict[tst_name]["cmp-data"], 2)) / 1000000, 2))
+ data_t = remove_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: