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
.wy-nav-content {
max-width: 1200px !important;
}
+.rst-content blockquote {
+ margin-left: 0px;
+ line-height: 18px;
+ margin-bottom: 0px;
+}
+.wy-menu-vertical a {
+ display: inline-block;
+ line-height: 18px;
+ padding: 0 2em;
+ display: block;
+ position: relative;
+ font-size: 90%;
+ color: #d9d9d9
+}
+.wy-menu-vertical li.current a {
+ color: gray;
+ border-right: solid 1px #c9c9c9;
+ padding: 0 3em;
+}
+.wy-menu-vertical li.toctree-l2.current > a {
+ background: #c9c9c9;
+ padding: 0 3em;
+}
+.wy-menu-vertical li.toctree-l2.current li.toctree-l3 > a {
+ display: block;
+ background: #c9c9c9;
+ padding: 0 4em;
+}
+.wy-menu-vertical li.toctree-l3.current li.toctree-l4 > a {
+ display: block;
+ background: #bdbdbd;
+ padding: 0 5em;
+}
+.wy-menu-vertical li.on a, .wy-menu-vertical li.current > a {
+ color: #404040;
+ padding: 0 2em;
+ font-weight: bold;
+ position: relative;
+ background: #fcfcfc;
+ border: none;
+ border-top-width: medium;
+ border-bottom-width: medium;
+ border-top-style: none;
+ border-bottom-style: none;
+ border-top-color: currentcolor;
+ border-bottom-color: currentcolor;
+ padding-left: 2em -4px;
+}
"""
COLORS = ["SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
"Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
- "Violet", "Blue", "Yellow"]
+ "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
+ "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
+ "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
+ "MediumSeaGreen", "SeaGreen", "LightSlateGrey",
+ "SkyBlue", "Olive", "Purple", "Coral", "Indigo", "Pink",
+ "Chocolate", "Brown", "Magenta", "Cyan", "Orange", "Black",
+ "Violet", "Blue", "Yellow", "BurlyWood", "CadetBlue", "Crimson",
+ "DarkBlue", "DarkCyan", "DarkGreen", "Green", "GoldenRod",
+ "LightGreen", "LightSeaGreen", "LightSkyBlue", "Maroon",
+ "MediumSeaGreen", "SeaGreen", "LightSlateGrey"
+ ]
def generate_cpta(spec, data):
ret_code = _generate_all_charts(spec, data)
cmd = HTML_BUILDER.format(
- date=datetime.utcnow().strftime('%m/%d/%Y %H:%M UTC'),
+ date=datetime.utcnow().strftime('%Y-%m-%dT%H:%MZ'),
working_dir=spec.environment["paths"]["DIR[WORKING,SRC]"],
build_dir=spec.environment["paths"]["DIR[BUILD,HTML]"])
execute_command(cmd)
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:
- 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:
- 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:])))
- 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)
- anomalies = pd.Series()
+ anomalies = OrderedDict()
anomalies_colors = list()
anomalies_avgs = list()
anomaly_color = {
"progression": 1.0
}
if anomaly_classification:
- for idx, item in enumerate(data_pd.items()):
+ for idx, (key, value) in enumerate(data_pd.iteritems()):
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])
trace_samples = plgo.Scatter(
x=xaxis,
- y=data_y,
+ y=[y.avg for y in data_y],
mode='markers',
line={
"width": 1
"symbol": "circle",
},
text=hover_text,
- hoverinfo="x+y+text+name"
+ hoverinfo="text"
)
traces = [trace_samples, ]
},
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)
chart_data[test_name] = OrderedDict()
try:
chart_data[test_name][int(index)] = \
- test["result"]["throughput"]
+ test["result"]["receive-rate"]
except (KeyError, TypeError):
pass
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()
- win_size = 14
index = 0
for test_name, test_data in chart_data.items():
if not test_data:
logs.append(("WARNING", "No data for the test '{0}'".
format(test_name)))
continue
+ message = "index: {index}, test: {test}".format(
+ index=index, test=test_name)
test_name = test_name.split('.')[-1]
- trace, rslt = _generate_trending_traces(
- test_data,
- job_name=job_name,
- build_info=build_info,
- name='-'.join(test_name.split('-')[3:-1]),
- color=COLORS[index])
+ try:
+ trace, rslt = _generate_trending_traces(
+ test_data,
+ job_name=job_name,
+ build_info=build_info,
+ name='-'.join(test_name.split('-')[2:-1]),
+ color=COLORS[index])
+ except IndexError:
+ message = "Out of colors: {}".format(message)
+ logs.append(("ERROR", message))
+ logging.error(message)
+ index += 1
+ continue
traces.extend(trace)
res.append(rslt)
index += 1
Code Review / csit.git / blobdiff