X-Git-Url: https://gerrit.fd.io/r/gitweb?a=blobdiff_plain;ds=sidebyside;f=resources%2Ftools%2Fpresentation%2Fgenerator_tables.py;h=36933cc0e5df9d14955433a804ba70c1c8d99e3e;hb=3acc992d8774e1b65c1e6d8c7147a204c1af6436;hp=57ca6caad1313902b11a1cdc1b5cd60a76559574;hpb=eb6840a319390feb18b2ca32854edf1a6ad15e95;p=csit.git diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index 57ca6caad1..36933cc0e5 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -730,13 +730,13 @@ def table_performance_trending_dashboard(table, input_data): data = input_data.filter_data(table, continue_on_error=True) # Prepare the header of the tables - header = ["Test Case", + header = [" Test Case", "Trend [Mpps]", - "Short-Term Change [%]", - "Long-Term Change [%]", - "Regressions [#]", - "Progressions [#]", - "Outliers [#]" + " Short-Term Change [%]", + " Long-Term Change [%]", + " Regressions [#]", + " Progressions [#]", + " Outliers [#]" ] header_str = ",".join(header) + "\n" @@ -745,6 +745,8 @@ def table_performance_trending_dashboard(table, input_data): for job, builds in table["data"].items(): for build in builds: for tst_name, tst_data in data[job][str(build)].iteritems(): + if tst_name.lower() in table["ignore-list"]: + continue if tbl_dict.get(tst_name, None) is None: name = "{0}-{1}".format(tst_data["parent"].split("-")[0], "-".join(tst_data["name"]. @@ -775,8 +777,9 @@ def table_performance_trending_dashboard(table, input_data): stdev_t = data_t.rolling(window=win_size, min_periods=2).std() median_first_idx = pd_data.size - long_win_size try: - max_median = max([x for x in median_t.values[median_first_idx:] - if not isnan(x)]) + max_median = max( + [x for x in median_t.values[median_first_idx:-win_size] + if not isnan(x)]) except ValueError: max_median = nan try: @@ -791,14 +794,6 @@ def table_performance_trending_dashboard(table, input_data): # Test name: name = tbl_dict[tst_name]["name"] - logging.info("{}".format(name)) - logging.info("pd_data : {}".format(pd_data)) - logging.info("data_t : {}".format(data_t)) - logging.info("median_t : {}".format(median_t)) - logging.info("last_median_t : {}".format(last_median_t)) - logging.info("median_t_14 : {}".format(median_t_14)) - logging.info("max_median : {}".format(max_median)) - # Classification list: classification_lst = list() for build_nr, value in pd_data.iteritems():