X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_tables.py;h=9b9f09f4be2f4c4335fef44039297cde3829a532;hb=4f5872c1bb23873b3a93cb471aae8700d5ca029d;hp=f73357db304422d1efa20d6e84923f0bcdc9c35a;hpb=bb81ef05b86154d000128ef15bd3ecffe997ef9a;p=csit.git diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index f73357db30..9b9f09f4be 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -25,7 +25,7 @@ from math import isnan from xml.etree import ElementTree as ET from errors import PresentationError -from utils import mean, stdev, relative_change, remove_outliers, find_outliers +from utils import mean, stdev, relative_change, remove_outliers, split_outliers def generate_tables(spec, data): @@ -405,14 +405,16 @@ def table_performance_comparison(table, input_data): item = [tbl_dict[tst_name]["name"], ] if tbl_dict[tst_name]["ref-data"]: data_t = remove_outliers(tbl_dict[tst_name]["ref-data"], - table["outlier-const"]) + outlier_constant=table["outlier-const"]) + # TODO: Specify window size. 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"]: data_t = remove_outliers(tbl_dict[tst_name]["cmp-data"], - table["outlier-const"]) + outlier_constant=table["outlier-const"]) + # TODO: Specify window size. item.append(round(mean(data_t) / 1000000, 2)) item.append(round(stdev(data_t) / 1000000, 2)) else: @@ -594,14 +596,16 @@ def table_performance_comparison_mrr(table, input_data): item = [tbl_dict[tst_name]["name"], ] if tbl_dict[tst_name]["ref-data"]: data_t = remove_outliers(tbl_dict[tst_name]["ref-data"], - table["outlier-const"]) + outlier_const=table["outlier-const"]) + # TODO: Specify window size. 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"]: data_t = remove_outliers(tbl_dict[tst_name]["cmp-data"], - table["outlier-const"]) + outlier_const=table["outlier-const"]) + # TODO: Specify window size. item.append(round(mean(data_t) / 1000000, 2)) item.append(round(stdev(data_t) / 1000000, 2)) else: @@ -708,7 +712,8 @@ def table_performance_trending_dashboard(table, input_data): name = tbl_dict[tst_name]["name"] median = pd_data.rolling(window=win_size, min_periods=2).median() - trimmed_data, _ = find_outliers(pd_data, outlier_const=1.5) + trimmed_data, _ = split_outliers(pd_data, outlier_const=1.5, + window=win_size) stdev_t = pd_data.rolling(window=win_size, min_periods=2).std() rel_change_lst = [None, ] @@ -937,7 +942,8 @@ def table_performance_trending_dashboard_html(table, input_data): file_name = "ip6.html" elif "l2xcbase" in item or "l2xcscale" in item \ - or "l2bdbasemaclrn" in item or "l2bdscale" in item: + or "l2bdbasemaclrn" in item or "l2bdscale" in item \ + or "l2dbbasemaclrn" in item or "l2dbscale" in item: file_name = "l2.html" if "iacl" in item: feature = "-features"