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CSIT-1208: Add new data to 1807 report
[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
d4ac06d
..
7279ea3
100644
(file)
--- a/
resources/tools/presentation/generator_CPTA.py
+++ b/
resources/tools/presentation/generator_CPTA.py
@@
-22,7
+22,6
@@
import prettytable
import plotly.offline as ploff
import plotly.graph_objs as plgo
import plotly.exceptions as plerr
import plotly.offline as ploff
import plotly.graph_objs as plgo
import plotly.exceptions as plerr
-import pandas as pd
from collections import OrderedDict
from datetime import datetime
from collections import OrderedDict
from datetime import datetime
@@
-116,23
+115,40
@@
def _generate_trending_traces(in_data, job_name, build_info,
hover_text = list()
xaxis = list()
for idx in data_x:
hover_text = list()
xaxis = list()
for idx in data_x:
+ date = build_info[job_name][str(idx)][0]
+ hover_str = ("date: {0}<br>"
+ "value: {1:,}<br>"
+ "{2}-ref: {3}<br>"
+ "csit-ref: mrr-{4}-build-{5}")
if "dpdk" in job_name:
if "dpdk" in job_name:
- hover_text.append("dpdk-ref: {0}<br>csit-ref: mrr-weekly-build-{1}".
- format(build_info[job_name][str(idx)][1].
- rsplit('~', 1)[0], idx))
+ hover_text.append(hover_str.format(
+ date,
+ int(in_data[idx].avg),
+ "dpdk",
+ build_info[job_name][str(idx)][1].
+ rsplit('~', 1)[0],
+ "weekly",
+ idx))
elif "vpp" in job_name:
elif "vpp" in job_name:
- hover_text.append("vpp-ref: {0}<br>csit-ref: mrr-daily-build-{1}".
- format(build_info[job_name][str(idx)][1].
- rsplit('~', 1)[0], idx))
- date = build_info[job_name][str(idx)][0]
+ hover_text.append(hover_str.format(
+ date,
+ int(in_data[idx].avg),
+ "vpp",
+ build_info[job_name][str(idx)][1].
+ rsplit('~', 1)[0],
+ "daily",
+ idx))
+
xaxis.append(datetime(int(date[0:4]), int(date[4:6]), int(date[6:8]),
int(date[9:11]), int(date[12:])))
xaxis.append(datetime(int(date[0:4]), int(date[4:6]), int(date[6:8]),
int(date[9:11]), int(date[12:])))
- data_pd = pd.Series(data_y, index=xaxis)
+ data_pd = OrderedDict()
+ for key, value in zip(xaxis, data_y):
+ data_pd[key] = value
anomaly_classification, avgs = classify_anomalies(data_pd)
anomaly_classification, avgs = classify_anomalies(data_pd)
- anomalies =
pd.Series
()
+ anomalies =
OrderedDict
()
anomalies_colors = list()
anomalies_avgs = list()
anomaly_color = {
anomalies_colors = list()
anomalies_avgs = list()
anomaly_color = {
@@
-141,11
+157,10
@@
def _generate_trending_traces(in_data, job_name, build_info,
"progression": 1.0
}
if anomaly_classification:
"progression": 1.0
}
if anomaly_classification:
- for idx,
item in enumerate(data_pd.
items()):
+ for idx,
(key, value) in enumerate(data_pd.iter
items()):
if anomaly_classification[idx] in \
("outlier", "regression", "progression"):
if anomaly_classification[idx] in \
("outlier", "regression", "progression"):
- anomalies = anomalies.append(pd.Series([item[1], ],
- index=[item[0], ]))
+ anomalies[key] = value
anomalies_colors.append(
anomaly_color[anomaly_classification[idx]])
anomalies_avgs.append(avgs[idx])
anomalies_colors.append(
anomaly_color[anomaly_classification[idx]])
anomalies_avgs.append(avgs[idx])
@@
-155,7
+170,7
@@
def _generate_trending_traces(in_data, job_name, build_info,
trace_samples = plgo.Scatter(
x=xaxis,
trace_samples = plgo.Scatter(
x=xaxis,
- y=
data_y
,
+ y=
[y.avg for y in data_y]
,
mode='markers',
line={
"width": 1
mode='markers',
line={
"width": 1
@@
-169,7
+184,7
@@
def _generate_trending_traces(in_data, job_name, build_info,
"symbol": "circle",
},
text=hover_text,
"symbol": "circle",
},
text=hover_text,
- hoverinfo="
x+y+text+name
"
+ hoverinfo="
text
"
)
traces = [trace_samples, ]
)
traces = [trace_samples, ]
@@
-185,7
+200,9
@@
def _generate_trending_traces(in_data, job_name, build_info,
},
showlegend=False,
legendgroup=name,
},
showlegend=False,
legendgroup=name,
- name='{name}-trend'.format(name=name)
+ name='{name}'.format(name=name),
+ text=["trend: {0:,}".format(int(avg)) for avg in avgs],
+ hoverinfo="text+name"
)
traces.append(trace_trend)
)
traces.append(trace_trend)
@@
-280,7
+297,7
@@
def _generate_all_charts(spec, input_data):
chart_data[test_name] = OrderedDict()
try:
chart_data[test_name][int(index)] = \
chart_data[test_name] = OrderedDict()
try:
chart_data[test_name][int(index)] = \
- test["result"]["
throughput
"]
+ test["result"]["
receive-rate
"]
except (KeyError, TypeError):
pass
except (KeyError, TypeError):
pass
@@
-289,11
+306,12
@@
def _generate_all_charts(spec, input_data):
tst_lst = list()
for bld in builds_dict[job_name]:
itm = tst_data.get(int(bld), '')
tst_lst = list()
for bld in builds_dict[job_name]:
itm = tst_data.get(int(bld), '')
+ if not isinstance(itm, str):
+ itm = itm.avg
tst_lst.append(str(itm))
csv_tbl.append("{0},".format(tst_name) + ",".join(tst_lst) + '\n')
# Generate traces:
traces = list()
tst_lst.append(str(itm))
csv_tbl.append("{0},".format(tst_name) + ",".join(tst_lst) + '\n')
# Generate traces:
traces = list()
- win_size = 14
index = 0
for test_name, test_data in chart_data.items():
if not test_data:
index = 0
for test_name, test_data in chart_data.items():
if not test_data:
@@
-305,7
+323,7
@@
def _generate_all_charts(spec, input_data):
test_data,
job_name=job_name,
build_info=build_info,
test_data,
job_name=job_name,
build_info=build_info,
- name='-'.join(test_name.split('-')[
3
:-1]),
+ name='-'.join(test_name.split('-')[
2
:-1]),
color=COLORS[index])
traces.extend(trace)
res.append(rslt)
color=COLORS[index])
traces.extend(trace)
res.append(rslt)