PAL Trending: Data in txt table in Mpps

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

diff --git a/resources/tools/presentation/generator_CPTA.py b/resources/tools/presentation/generator_CPTA.py
index 8ae0662..2e9abde 100644 (file)
--- a/resources/tools/presentation/generator_CPTA.py
+++ b/resources/tools/presentation/generator_CPTA.py
@@ -291,19 +291,21 @@ def _generate_trending_traces(in_data, period, moving_win_size=10,
             "color": anomalies_res,
             "colorscale": color_scale,
             "showscale": True,
-
+            "line": {
+                "width": 2
+            },
             "colorbar": {
                 "y": 0.5,
                 "len": 0.8,
-                "title": "Results Clasification",
+                "title": "Circles Marking Data Classification",
                 "titleside": 'right',
                 "titlefont": {
                     "size": 14
                 },
                 "tickmode": 'array',
                 "tickvals": [0.125, 0.375, 0.625, 0.875],
-                "ticktext": ["Outlier", "Regress", "Normal", "Progress"],
-                "ticks": 'outside',
+                "ticktext": ["Outlier", "Regression", "Normal", "Progression"],
+                "ticks": "",
                 "ticklen": 0,
                 "tickangle": -90,
                 "thickness": 10
@@ -314,7 +316,7 @@ def _generate_trending_traces(in_data, period, moving_win_size=10,
 
     if show_moving_median:
         data_mean_y = pd.Series(data_y).rolling(
-            window=moving_win_size).median()
+            window=moving_win_size, min_periods=2).median()
         trace_median = plgo.Scatter(
             x=data_x,
             y=data_mean_y,
@@ -324,7 +326,7 @@ def _generate_trending_traces(in_data, period, moving_win_size=10,
                 "width": 1,
                 "color": color,
             },
-            name='{name}-trend'.format(name=name, size=moving_win_size)
+            name='{name}-trend'.format(name=name)
         )
         traces.append(trace_median)
 
@@ -388,7 +390,7 @@ def _generate_all_charts(spec, input_data):
                         chart_data[test_name][int(idx)] = \
                             test["result"]["throughput"]
                     except (KeyError, TypeError):
-                        chart_data[test_name][int(idx)] = None
+                        pass
 
         # Add items to the csv table:
         for tst_name, tst_data in chart_data.items():
@@ -441,15 +443,23 @@ def _generate_all_charts(spec, input_data):
         file_handler.writelines(csv_table)
 
     txt_table = None
-    with open("{0}.csv".format(file_name), 'rb') as csv_file:
+    with open("{0}.csv".format("cpta-trending"), 'rb') as csv_file:
         csv_content = csv.reader(csv_file, delimiter=',', quotechar='"')
+        header = True
         for row in csv_content:
             if txt_table is None:
                 txt_table = prettytable.PrettyTable(row)
+                header = False
             else:
+                if not header:
+                    for idx, item in enumerate(row):
+                        try:
+                            row[idx] = str(round(float(item) / 1000000, 2))
+                        except ValueError:
+                            pass
                 txt_table.add_row(row)
         txt_table.align["Build Number:"] = "l"
-    with open("{0}.txt".format(file_name), "w") as txt_file:
+    with open("{0}.txt".format("cpta-trending"), "w") as txt_file:
         txt_file.write(str(txt_table))
 
     # Evaluate result:
@@ -462,9 +472,8 @@ def _generate_all_charts(spec, input_data):
             result = "PASS"
         elif item == 0.33 or item == 0.0:
             result = "FAIL"
-    print(results)
-    print(result)
-    if result == "FAIL":
-        return 1
-    else:
-        return 0
+
+    logging.info("Partial results: {0}".format(results))
+    logging.info("Result: {0}".format(result))
+
+    return result