Report: Add historical data to performance changes table

[csit.git] / resources / tools / presentation / generator_tables.py

diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 6948b45..92f0cee 100644 (file)
--- 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"])
@@ -806,9 +805,9 @@ def table_performance_trending_dashboard(table, input_data):
                         or isnan(stdev_t[build_nr]) \
                         or isnan(value):
                     classification_lst.append("outlier")
-                elif value < (median_t[build_nr] - 3 * stdev_t[build_nr]):
+                elif value < (median_t[build_nr] - 2 * stdev_t[build_nr]):
                     classification_lst.append("regression")
-                elif value > (median_t[build_nr] + 3 * stdev_t[build_nr]):
+                elif value > (median_t[build_nr] + 2 * stdev_t[build_nr]):
                     classification_lst.append("progression")
                 else:
                     classification_lst.append("normal")
@@ -846,7 +845,8 @@ def table_performance_trending_dashboard(table, input_data):
         for nrp in range(table["window"], -1, -1):
             tbl_pro = [item for item in tbl_reg if item[5] == nrp]
             for nro in range(table["window"], -1, -1):
-                tbl_out = [item for item in tbl_pro if item[5] == nro]
+                tbl_out = [item for item in tbl_pro if item[6] == nro]
+                tbl_out.sort(key=lambda rel: rel[2])
                 tbl_sorted.extend(tbl_out)
 
     file_name = "{0}{1}".format(table["output-file"], table["output-file-ext"])