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Improvements to bandwidth plot. See Monorail issue for comparison.

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NOTRY=true

BUG=webrtc:6070

Review-Url: https://codereview.webrtc.org/2178973005
Cr-Commit-Position: refs/heads/master@{#13606}
This commit is contained in:
aleloi
2016-08-02 05:01:30 -07:00
committed by Commit bot
parent 5556dcb24c
commit b0dc30d282
1 changed files with 42 additions and 13 deletions
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53
webrtc/tools/py_event_log_analyzer/rtp_analyzer.py
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@ -26,6 +26,7 @@ class RTPStatistics(object):
"""Has methods for calculating and plotting RTP stream statistics.""" """Has methods for calculating and plotting RTP stream statistics."""
BANDWIDTH_SMOOTHING_WINDOW_SIZE = 10 BANDWIDTH_SMOOTHING_WINDOW_SIZE = 10
PLOT_RESOLUTION_MS = 50
def __init__(self, data_points): def __init__(self, data_points):
"""Initializes object with data_points and computes simple statistics. """Initializes object with data_points and computes simple statistics.
@ -170,7 +171,7 @@ class RTPStatistics(object):
for point in self.data_points: for point in self.data_points:
point.real_send_time_ms = (point.timestamp - point.real_send_time_ms = (point.timestamp -
self.data_points[0].timestamp) / freq self.data_points[0].timestamp) / freq
point.delay = point.arrival_timestamp_ms -point.real_send_time_ms point.delay = point.arrival_timestamp_ms - point.real_send_time_ms
def print_duration_statistics(self): def print_duration_statistics(self):
"""Prints delay, clock drift and bitrate statistics.""" """Prints delay, clock drift and bitrate statistics."""
@ -221,12 +222,14 @@ class RTPStatistics(object):
BANDWIDTH_SMOOTHING_WINDOW_SIZE. Averaging is done with BANDWIDTH_SMOOTHING_WINDOW_SIZE. Averaging is done with
numpy.correlate. numpy.correlate.
""" """
self.bandwidth_kbps = [] start_ms = self.data_points[0].real_send_time_ms
for i in range(len(self.data_points) - 1): stop_ms = self.data_points[-1].real_send_time_ms
self.bandwidth_kbps.append(self.data_points[i].size * 8 / (self.bandwidth_kbps, _) = numpy.histogram(
(self.data_points[i + [point.real_send_time_ms for point in self.data_points],
1].real_send_time_ms - bins=numpy.arange(start_ms, stop_ms,
self.data_points[i].real_send_time_ms) RTPStatistics.PLOT_RESOLUTION_MS),
weights=[point.size * 8 / RTPStatistics.PLOT_RESOLUTION_MS
for point in self.data_points]
) )
correlate_filter = (numpy.ones( correlate_filter = (numpy.ones(
RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE) / RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE) /
@ -235,22 +238,48 @@ class RTPStatistics(object):
def plot_statistics(self): def plot_statistics(self):
"""Plots changes in delay and average bandwidth.""" """Plots changes in delay and average bandwidth."""
start_ms = self.data_points[0].real_send_time_ms
stop_ms = self.data_points[-1].real_send_time_ms
time_axis = numpy.arange(start_ms / 1000, stop_ms / 1000,
RTPStatistics.PLOT_RESOLUTION_MS / 1000)
delay = calculate_delay(start_ms, stop_ms,
RTPStatistics.PLOT_RESOLUTION_MS,
self.data_points)
plt.figure(1) plt.figure(1)
plt.plot([f.real_send_time_ms / 1000 for f in self.data_points], plt.plot(time_axis, delay)
[f.absdelay for f in self.data_points])
plt.xlabel("Send time [s]") plt.xlabel("Send time [s]")
plt.ylabel("Relative transport delay [ms]") plt.ylabel("Relative transport delay [ms]")
plt.figure(2) plt.figure(2)
plt.plot([f.real_send_time_ms / 1000 for f in plt.plot(time_axis[:len(self.smooth_bw_kbps)], self.smooth_bw_kbps)
self.data_points][:len(self.smooth_bw_kbps)],
self.smooth_bw_kbps[:len(self.data_points)])
plt.xlabel("Send time [s]") plt.xlabel("Send time [s]")
plt.ylabel("Bandwidth [kbps]") plt.ylabel("Bandwidth [kbps]")
plt.show() plt.show()
def calculate_delay(start, stop, step, points):
"""Quantizes the time coordinates for the delay.
Quantizes points by rounding the timestamps downwards to the nearest
point in the time sequence start, start+step, start+2*step... Takes
the average of the delays of points rounded to the same. Returns
masked array, in which time points with no value are masked.
"""
grouped_delays = [[] for _ in numpy.arange(start, stop, step)]
rounded_value_index = lambda x: int((x - start) / step)
for point in points:
grouped_delays[rounded_value_index(point.real_send_time_ms)
].append(point.absdelay)
regularized_delays = [numpy.average(arr) if arr else None for arr in
grouped_delays]
return numpy.ma.masked_values(regularized_delays, None)
def main(): def main():
usage = "Usage: %prog [options] <filename of rtc event log>" usage = "Usage: %prog [options] <filename of rtc event log>"
parser = optparse.OptionParser(usage=usage) parser = optparse.OptionParser(usage=usage)