From: Tibor Frank Date: Thu, 26 Apr 2018 12:11:11 +0000 (+0200) Subject: Report: Add historical data to performance changes table X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=commitdiff_plain;h=52cb667958d954d6233d0865a59d90cca82db026;hp=0740688e5798f7ab7162fd7f4bc5eb8455164a7c Report: Add historical data to performance changes table Change-Id: If7bce2c86b2fb352368c433c5db81a4a4bc976ed Signed-off-by: Tibor Frank --- diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index 96930cddb6..92f0ceed45 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -432,18 +432,17 @@ def table_performance_comparison(table, input_data): for tst_name in tbl_dict.keys(): item = [tbl_dict[tst_name]["name"], ] if history: - for hist_list in tbl_dict[tst_name]["history"].values(): - for hist_data in hist_list: - if hist_data: - data_t = remove_outliers( - hist_data, outlier_const=table["outlier-const"]) - if data_t: - item.append(round(mean(data_t) / 1000000, 2)) - item.append(round(stdev(data_t) / 1000000, 2)) - else: - item.extend([None, None]) + for hist_data in tbl_dict[tst_name]["history"].values(): + if hist_data: + data_t = remove_outliers( + hist_data, outlier_const=table["outlier-const"]) + if data_t: + item.append(round(mean(data_t) / 1000000, 2)) + item.append(round(stdev(data_t) / 1000000, 2)) else: item.extend([None, None]) + else: + item.extend([None, None]) if tbl_dict[tst_name]["ref-data"]: data_t = remove_outliers(tbl_dict[tst_name]["ref-data"], outlier_const=table["outlier-const"]) diff --git a/resources/tools/presentation/utils.py b/resources/tools/presentation/utils.py index 88baf95928..df543c17ea 100644 --- a/resources/tools/presentation/utils.py +++ b/resources/tools/presentation/utils.py @@ -87,7 +87,7 @@ def remove_outliers(input_list, outlier_const=1.5, window=14): iqr = (upper_quartile - lower_quartile) * outlier_const quartile_set = (lower_quartile - iqr, upper_quartile + iqr) result_lst = list() - for y in data.tolist(): + for y in input_list: if quartile_set[0] <= y <= quartile_set[1]: result_lst.append(y) return result_lst