diff options
Diffstat (limited to 'resources')
| -rw-r--r-- | resources/tools/presentation/generator_cpta.py | 47 |
1 files changed, 25 insertions, 22 deletions
diff --git a/resources/tools/presentation/generator_cpta.py b/resources/tools/presentation/generator_cpta.py index 29eed8cf75..a11d1da25f 100644 --- a/resources/tools/presentation/generator_cpta.py +++ b/resources/tools/presentation/generator_cpta.py @@ -169,44 +169,47 @@ def _generate_trending_traces(in_data, job_name, build_info, """ data_x = list(in_data.keys()) - data_y = [float(item) / 1e6 for item in in_data.values()] + data_y_pps = list(in_data.values()) + data_y_mpps = [float(item) / 1e6 for item in data_y_pps] hover_text = list() xaxis = list() - for idx in data_x: - date = build_info[job_name][str(idx)][0] + for index, key in enumerate(data_x): + str_key = str(key) + date = build_info[job_name][str_key][0] hover_str = (u"date: {date}<br>" - u"value: {value:,}<br>" + u"value [Mpps]: {value:.3f}<br>" u"{sut}-ref: {build}<br>" u"csit-ref: mrr-{period}-build-{build_nr}<br>" u"testbed: {testbed}") if u"dpdk" in job_name: hover_text.append(hover_str.format( date=date, - value=int(in_data[idx]), + value=data_y_mpps[index], sut=u"dpdk", - build=build_info[job_name][str(idx)][1].rsplit(u'~', 1)[0], + build=build_info[job_name][str_key][1].rsplit(u'~', 1)[0], period=u"weekly", - build_nr=idx, - testbed=build_info[job_name][str(idx)][2])) + build_nr=str_key, + testbed=build_info[job_name][str_key][2])) elif u"vpp" in job_name: hover_text.append(hover_str.format( date=date, - value=int(in_data[idx]), + value=data_y_mpps[index], sut=u"vpp", - build=build_info[job_name][str(idx)][1].rsplit(u'~', 1)[0], + build=build_info[job_name][str_key][1].rsplit(u'~', 1)[0], period=u"daily", - build_nr=idx, - testbed=build_info[job_name][str(idx)][2])) + build_nr=str_key, + testbed=build_info[job_name][str_key][2])) xaxis.append(datetime(int(date[0:4]), int(date[4:6]), int(date[6:8]), int(date[9:11]), int(date[12:]))) data_pd = OrderedDict() - for key, value in zip(xaxis, data_y): + for key, value in zip(xaxis, data_y_pps): data_pd[key] = value - anomaly_classification, avgs = classify_anomalies(data_pd) + anomaly_classification, avgs_pps = classify_anomalies(data_pd) + avgs_mpps = [avg_pps / 1e6 for avg_pps in avgs_pps] anomalies = OrderedDict() anomalies_colors = list() @@ -217,20 +220,20 @@ def _generate_trending_traces(in_data, job_name, build_info, u"progression": 1.0 } if anomaly_classification: - for idx, (key, value) in enumerate(data_pd.items()): - if anomaly_classification[idx] in \ + for index, (key, value) in enumerate(data_pd.items()): + if anomaly_classification[index] in \ (u"outlier", u"regression", u"progression"): - anomalies[key] = value + anomalies[key] = value / 1e6 anomalies_colors.append( - anomaly_color[anomaly_classification[idx]]) - anomalies_avgs.append(avgs[idx]) + anomaly_color[anomaly_classification[index]]) + anomalies_avgs.append(avgs_mpps[index]) anomalies_colors.extend([0.0, 0.5, 1.0]) # Create traces trace_samples = plgo.Scatter( x=xaxis, - y=data_y, + y=data_y_mpps, mode=u"markers", line={ u"width": 1 @@ -251,7 +254,7 @@ def _generate_trending_traces(in_data, job_name, build_info, if show_trend_line: trace_trend = plgo.Scatter( x=xaxis, - y=avgs, + y=avgs_mpps, mode=u"lines", line={ u"shape": u"linear", @@ -261,7 +264,7 @@ def _generate_trending_traces(in_data, job_name, build_info, showlegend=False, legendgroup=name, name=f"{name}", - text=[f"trend: {int(avg):,}" for avg in avgs], + text=[f"trend [Mpps]: {avg:.3f}" for avg in avgs_mpps], hoverinfo=u"text+name" ) traces.append(trace_trend) |