Report: Add historical data to performance changes table 83/12183/1
authorTibor Frank <tifrank@cisco.com>
Thu, 26 Apr 2018 12:11:11 +0000 (14:11 +0200)
committerTibor Frank <tifrank@cisco.com>
Thu, 26 Apr 2018 12:12:19 +0000 (14:12 +0200)
Change-Id: If7bce2c86b2fb352368c433c5db81a4a4bc976ed
Signed-off-by: Tibor Frank <tifrank@cisco.com>
resources/tools/presentation/generator_tables.py
resources/tools/presentation/utils.py

index 96930cd..92f0cee 100644 (file)
@@ -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"])
index 88baf95..df543c1 100644 (file)
@@ -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