X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_tables.py;h=a5a573ad9427ea7bd4644dcb171ae9e2e7a8a9ec;hp=59162444dcfd33664e8374f930fa0b111a46662b;hb=6f8266f81bb052e2c0e51b029e47f0eb4f04a7ed;hpb=7aff808942440ba9729bf60888738b920c024324

diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py
index 59162444dc..a5a573ad94 100644
--- a/resources/tools/presentation/generator_tables.py
+++ b/resources/tools/presentation/generator_tables.py
@@ -407,16 +407,22 @@ def table_performance_comparison(table, input_data):
             data_t = remove_outliers(tbl_dict[tst_name]["ref-data"],
                                      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))
+            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]["cmp-data"]:
             data_t = remove_outliers(tbl_dict[tst_name]["cmp-data"],
                                      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))
+            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 item[1] is not None and item[3] is not None:
@@ -598,16 +604,22 @@ def table_performance_comparison_mrr(table, input_data):
             data_t = remove_outliers(tbl_dict[tst_name]["ref-data"],
                                      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))
+            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]["cmp-data"]:
             data_t = remove_outliers(tbl_dict[tst_name]["cmp-data"],
                                      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))
+            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 item[1] is not None and item[3] is not None and item[1] != 0:
@@ -786,12 +798,15 @@ def table_performance_trending_dashboard(table, input_data):
                     else classification
                 for idx in range(first_idx, len(classification_lst)):
                     if classification_lst[idx] == tmp_classification:
-                        index = idx
-                        break
+                        if rel_change_lst[idx]:
+                            index = idx
+                            break
                 for idx in range(index+1, len(classification_lst)):
                     if classification_lst[idx] == tmp_classification:
-                        if rel_change_lst[idx] > rel_change_lst[index]:
-                            index = idx
+                        if rel_change_lst[idx]:
+                            if (abs(rel_change_lst[idx]) >
+                                    abs(rel_change_lst[index])):
+                                index = idx
 
             trend = round(float(median_lst[-1]) / 1000000, 2) \
                 if not isnan(median_lst[-1]) else '-'