X-Git-Url: https://gerrit.fd.io/r/gitweb?p=csit.git;a=blobdiff_plain;f=resources%2Ftools%2Fpresentation%2Fgenerator_cpta.py;h=401767042716a4baae8d7fc3d0ccde4b976aa6c6;hp=f63caa40afeeaec4478f507fab197d1e49539024;hb=b55e324d526e5b05baef015c3614b9743c955992;hpb=ba15109cf5b9972be50821ef500e8a637cdac4f9
diff --git a/resources/tools/presentation/generator_cpta.py b/resources/tools/presentation/generator_cpta.py
index f63caa40af..4017670427 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 = list(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}
"
- u"value: {value:,}
"
+ u"value [Mpps]: {value:.3f}
"
u"{sut}-ref: {build}
"
u"csit-ref: mrr-{period}-build-{build_nr}
"
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)
@@ -556,18 +559,18 @@ def _generate_all_charts(spec, input_data):
anomaly_classifications = dict()
- # Create the header:
+ # Create the table header:
csv_tables = dict()
for job_name in builds_dict:
if csv_tables.get(job_name, None) is None:
csv_tables[job_name] = list()
- header = u"Build Number:," + u",".join(builds_dict[job_name]) + u'\n'
+ header = f"Build Number:,{u','.join(builds_dict[job_name])}\n"
csv_tables[job_name].append(header)
build_dates = [x[0] for x in build_info[job_name].values()]
- header = u"Build Date:," + u",".join(build_dates) + u'\n'
+ header = f"Build Date:,{u','.join(build_dates)}\n"
csv_tables[job_name].append(header)
versions = [x[1] for x in build_info[job_name].values()]
- header = u"Version:," + u",".join(versions) + u'\n'
+ header = f"Version:,{u','.join(versions)}\n"
csv_tables[job_name].append(header)
for chart in spec.cpta[u"plots"]:
@@ -583,8 +586,8 @@ def _generate_all_charts(spec, input_data):
# Write the tables:
for job_name, csv_table in csv_tables.items():
- file_name = spec.cpta[u"output-file"] + u"-" + job_name + u"-trending"
- with open(f"{file_name}.csv", u"w") as file_handler:
+ file_name = f"{spec.cpta[u'output-file']}/{job_name}-trending"
+ with open(f"{file_name}.csv", u"wt") as file_handler:
file_handler.writelines(csv_table)
txt_table = None
@@ -610,7 +613,7 @@ def _generate_all_charts(spec, input_data):
)
line_nr += 1
txt_table.align[u"Build Number:"] = u"l"
- with open(f"{file_name}.txt", u"w") as txt_file:
+ with open(f"{file_name}.txt", u"wt") as txt_file:
txt_file.write(str(txt_table))
# Evaluate result: