Trending: NDRPDR dashboard

[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 ac0a5c6..a308f64 100644 (file)
--- a/resources/tools/presentation/generator_cpta.py
+++ b/resources/tools/presentation/generator_cpta.py
@@ -146,7 +146,7 @@ def generate_cpta(spec, data):
 
 
 def _generate_trending_traces(in_data, job_name, build_info,
-                              show_trend_line=True, name=u"", color=u""):
+                              name=u"", color=u""):
     """Generate the trending traces:
      - samples,
      - outliers, regress, progress
@@ -155,13 +155,11 @@ def _generate_trending_traces(in_data, job_name, build_info,
     :param in_data: Full data set.
     :param job_name: The name of job which generated the data.
     :param build_info: Information about the builds.
-    :param show_trend_line: Show moving median (trending plot).
     :param name: Name of the plot
     :param color: Name of the color for the plot.
     :type in_data: OrderedDict
     :type job_name: str
     :type build_info: dict
-    :type show_trend_line: bool
     :type name: str
     :type color: str
     :returns: Generated traces (list) and the evaluated result.
@@ -169,8 +167,13 @@ def _generate_trending_traces(in_data, job_name, build_info,
     """
 
     data_x = list(in_data.keys())
-    data_y_pps = list(in_data.values())
-    data_y_mpps = [float(item) / 1e6 for item in data_y_pps]
+    data_y_pps = list()
+    data_y_mpps = list()
+    data_y_stdev = list()
+    for item in in_data.values():
+        data_y_pps.append(float(item[u"receive-rate"]))
+        data_y_stdev.append(float(item[u"receive-stdev"]) / 1e6)
+        data_y_mpps.append(float(item[u"receive-rate"]) / 1e6)
 
     hover_text = list()
     xaxis = list()
@@ -178,7 +181,8 @@ def _generate_trending_traces(in_data, job_name, build_info,
         str_key = str(key)
         date = build_info[job_name][str_key][0]
         hover_str = (u"date: {date}<br>"
-                     u"value [Mpps]: {value:.3f}<br>"
+                     u"average [Mpps]: {value:.3f}<br>"
+                     u"stdev [Mpps]: {stdev:.3f}<br>"
                      u"{sut}-ref: {build}<br>"
                      u"csit-ref: mrr-{period}-build-{build_nr}<br>"
                      u"testbed: {testbed}")
@@ -186,6 +190,7 @@ def _generate_trending_traces(in_data, job_name, build_info,
             hover_text.append(hover_str.format(
                 date=date,
                 value=data_y_mpps[index],
+                stdev=data_y_stdev[index],
                 sut=u"dpdk",
                 build=build_info[job_name][str_key][1].rsplit(u'~', 1)[0],
                 period=u"weekly",
@@ -195,6 +200,7 @@ def _generate_trending_traces(in_data, job_name, build_info,
             hover_text.append(hover_str.format(
                 date=date,
                 value=data_y_mpps[index],
+                stdev=data_y_stdev[index],
                 sut=u"vpp",
                 build=build_info[job_name][str_key][1].rsplit(u'~', 1)[0],
                 period=u"daily",
@@ -208,8 +214,9 @@ def _generate_trending_traces(in_data, job_name, build_info,
     for key, value in zip(xaxis, data_y_pps):
         data_pd[key] = value
 
-    anomaly_classification, avgs_pps = classify_anomalies(data_pd)
+    anomaly_classification, avgs_pps, stdevs_pps = classify_anomalies(data_pd)
     avgs_mpps = [avg_pps / 1e6 for avg_pps in avgs_pps]
+    stdevs_mpps = [stdev_pps / 1e6 for stdev_pps in stdevs_pps]
 
     anomalies = OrderedDict()
     anomalies_colors = list()
@@ -221,8 +228,7 @@ def _generate_trending_traces(in_data, job_name, build_info,
     }
     if anomaly_classification:
         for index, (key, value) in enumerate(data_pd.items()):
-            if anomaly_classification[index] in \
-                    (u"outlier", u"regression", u"progression"):
+            if anomaly_classification[index] in (u"regression", u"progression"):
                 anomalies[key] = value / 1e6
                 anomalies_colors.append(
                     anomaly_color[anomaly_classification[index]])
@@ -251,23 +257,30 @@ def _generate_trending_traces(in_data, job_name, build_info,
     )
     traces = [trace_samples, ]
 
-    if show_trend_line:
-        trace_trend = plgo.Scatter(
-            x=xaxis,
-            y=avgs_mpps,
-            mode=u"lines",
-            line={
-                u"shape": u"linear",
-                u"width": 1,
-                u"color": color,
-            },
-            showlegend=False,
-            legendgroup=name,
-            name=f"{name}",
-            text=[f"trend [Mpps]: {avg:.3f}" for avg in avgs_mpps],
-            hoverinfo=u"text+name"
+    trend_hover_text = list()
+    for idx in range(len(data_x)):
+        trend_hover_str = (
+            f"trend [Mpps]: {avgs_mpps[idx]:.3f}<br>"
+            f"stdev [Mpps]: {stdevs_mpps[idx]:.3f}"
         )
-        traces.append(trace_trend)
+        trend_hover_text.append(trend_hover_str)
+
+    trace_trend = plgo.Scatter(
+        x=xaxis,
+        y=avgs_mpps,
+        mode=u"lines",
+        line={
+            u"shape": u"linear",
+            u"width": 1,
+            u"color": color,
+        },
+        showlegend=False,
+        legendgroup=name,
+        name=f"{name}",
+        text=trend_hover_text,
+        hoverinfo=u"text+name"
+    )
+    traces.append(trace_trend)
 
     trace_anomalies = plgo.Scatter(
         x=list(anomalies.keys()),
@@ -347,8 +360,8 @@ def _generate_all_charts(spec, input_data):
 
         # Transform the data
         logging.info(
-             f"    Creating the data set for the {graph.get(u'type', u'')} "
-             f"{graph.get(u'title', u'')}."
+            f"    Creating the data set for the {graph.get(u'type', u'')} "
+            f"{graph.get(u'title', u'')}."
         )
 
         if graph.get(u"include", None):
@@ -377,8 +390,10 @@ def _generate_all_charts(spec, input_data):
                     if chart_data.get(test_name, None) is None:
                         chart_data[test_name] = OrderedDict()
                     try:
-                        chart_data[test_name][int(index)] = \
-                            test[u"result"][u"receive-rate"]
+                        chart_data[test_name][int(index)] = {
+                            u"receive-rate": test[u"result"][u"receive-rate"],
+                            u"receive-stdev": test[u"result"][u"receive-stdev"]
+                        }
                         chart_tags[test_name] = test.get(u"tags", None)
                     except (KeyError, TypeError):
                         pass
@@ -387,9 +402,12 @@ def _generate_all_charts(spec, input_data):
         for tst_name, tst_data in chart_data.items():
             tst_lst = list()
             for bld in builds_dict[job_name]:
-                itm = tst_data.get(int(bld), u'')
+                itm = tst_data.get(int(bld), dict())
                 # CSIT-1180: Itm will be list, compute stats.
-                tst_lst.append(str(itm))
+                try:
+                    tst_lst.append(str(itm.get(u"receive-rate", u"")))
+                except AttributeError:
+                    tst_lst.append(u"")
             csv_tbl.append(f"{tst_name}," + u",".join(tst_lst) + u'\n')
 
         # Generate traces: