blob: 3b746ad8ee5aab9310b57a9374aec61e381eaef0 [file] [log] [blame]
#!/usr/bin/env python
# Copyright (c) 2019 The WebRTC project authors. All Rights Reserved.
#
# Use of this source code is governed by a BSD-style license
# that can be found in the LICENSE file in the root of the source
# tree. An additional intellectual property rights grant can be found
# in the file PATENTS. All contributing project authors may
# be found in the AUTHORS file in the root of the source tree.
"""Plots metrics from stdin.
Expected format:
PLOTTABLE_DATA: <json data>
Where json data has the following format:
{
"graph_name": "<graph name>",
"trace_name": "<test suite name>",
"units": "<units>",
"mean": <mean value>,
"std": <standard deviation value>,
"samples": [
{ "time": <sample time in us>, "value": <sample value> },
...
]
}
"""
import argparse
import fileinput
import json
import matplotlib.pyplot as plt
LINE_PREFIX = 'PLOTTABLE_DATA: '
GRAPH_NAME = 'graph_name'
TRACE_NAME = 'trace_name'
UNITS = 'units'
MICROSECONDS_IN_SECOND = 1e6
def main():
parser = argparse.ArgumentParser(
description='Plots metrics exported from WebRTC perf tests')
parser.add_argument(
'-m',
'--metrics',
type=str,
nargs='*',
help=
'Metrics to plot. If nothing specified then will plot all available')
args = parser.parse_args()
metrics_to_plot = set()
if args.metrics:
for metric in args.metrics:
metrics_to_plot.add(metric)
metrics = []
for line in fileinput.input('-'):
line = line.strip()
if line.startswith(LINE_PREFIX):
line = line.replace(LINE_PREFIX, '')
metrics.append(json.loads(line))
else:
print line
for metric in metrics:
if len(metrics_to_plot
) > 0 and metric[GRAPH_NAME] not in metrics_to_plot:
continue
figure = plt.figure()
figure.canvas.set_window_title(metric[TRACE_NAME])
x_values = []
y_values = []
start_x = None
samples = metric['samples']
samples.sort(key=lambda x: x['time'])
for sample in samples:
if start_x is None:
start_x = sample['time']
# Time is us, we want to show it in seconds.
x_values.append(
(sample['time'] - start_x) / MICROSECONDS_IN_SECOND)
y_values.append(sample['value'])
plt.ylabel('%s (%s)' % (metric[GRAPH_NAME], metric[UNITS]))
plt.xlabel('time (s)')
plt.title(metric[GRAPH_NAME])
plt.plot(x_values, y_values)
plt.show()
if __name__ == '__main__':
main()