Improvements to bandwidth plot. See Monorail issue for comparison.
NOTRY=true BUG=webrtc:6070 Review-Url: https://codereview.webrtc.org/2178973005 Cr-Commit-Position: refs/heads/master@{#13606}
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@ -26,6 +26,7 @@ class RTPStatistics(object):
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"""Has methods for calculating and plotting RTP stream statistics."""
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BANDWIDTH_SMOOTHING_WINDOW_SIZE = 10
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PLOT_RESOLUTION_MS = 50
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def __init__(self, data_points):
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"""Initializes object with data_points and computes simple statistics.
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@ -170,7 +171,7 @@ class RTPStatistics(object):
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for point in self.data_points:
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point.real_send_time_ms = (point.timestamp -
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self.data_points[0].timestamp) / freq
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point.delay = point.arrival_timestamp_ms -point.real_send_time_ms
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point.delay = point.arrival_timestamp_ms - point.real_send_time_ms
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def print_duration_statistics(self):
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"""Prints delay, clock drift and bitrate statistics."""
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@ -221,12 +222,14 @@ class RTPStatistics(object):
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BANDWIDTH_SMOOTHING_WINDOW_SIZE. Averaging is done with
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numpy.correlate.
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"""
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self.bandwidth_kbps = []
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for i in range(len(self.data_points) - 1):
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self.bandwidth_kbps.append(self.data_points[i].size * 8 /
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(self.data_points[i +
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1].real_send_time_ms -
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self.data_points[i].real_send_time_ms)
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start_ms = self.data_points[0].real_send_time_ms
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stop_ms = self.data_points[-1].real_send_time_ms
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(self.bandwidth_kbps, _) = numpy.histogram(
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[point.real_send_time_ms for point in self.data_points],
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bins=numpy.arange(start_ms, stop_ms,
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RTPStatistics.PLOT_RESOLUTION_MS),
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weights=[point.size * 8 / RTPStatistics.PLOT_RESOLUTION_MS
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for point in self.data_points]
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)
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correlate_filter = (numpy.ones(
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RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE) /
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@ -235,22 +238,48 @@ class RTPStatistics(object):
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def plot_statistics(self):
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"""Plots changes in delay and average bandwidth."""
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start_ms = self.data_points[0].real_send_time_ms
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stop_ms = self.data_points[-1].real_send_time_ms
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time_axis = numpy.arange(start_ms / 1000, stop_ms / 1000,
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RTPStatistics.PLOT_RESOLUTION_MS / 1000)
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delay = calculate_delay(start_ms, stop_ms,
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RTPStatistics.PLOT_RESOLUTION_MS,
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self.data_points)
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plt.figure(1)
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plt.plot([f.real_send_time_ms / 1000 for f in self.data_points],
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[f.absdelay for f in self.data_points])
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plt.plot(time_axis, delay)
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plt.xlabel("Send time [s]")
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plt.ylabel("Relative transport delay [ms]")
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plt.figure(2)
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plt.plot([f.real_send_time_ms / 1000 for f in
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self.data_points][:len(self.smooth_bw_kbps)],
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self.smooth_bw_kbps[:len(self.data_points)])
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plt.plot(time_axis[:len(self.smooth_bw_kbps)], self.smooth_bw_kbps)
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plt.xlabel("Send time [s]")
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plt.ylabel("Bandwidth [kbps]")
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plt.show()
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def calculate_delay(start, stop, step, points):
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"""Quantizes the time coordinates for the delay.
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Quantizes points by rounding the timestamps downwards to the nearest
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point in the time sequence start, start+step, start+2*step... Takes
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the average of the delays of points rounded to the same. Returns
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masked array, in which time points with no value are masked.
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"""
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grouped_delays = [[] for _ in numpy.arange(start, stop, step)]
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rounded_value_index = lambda x: int((x - start) / step)
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for point in points:
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grouped_delays[rounded_value_index(point.real_send_time_ms)
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].append(point.absdelay)
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regularized_delays = [numpy.average(arr) if arr else None for arr in
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grouped_delays]
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return numpy.ma.masked_values(regularized_delays, None)
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def main():
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usage = "Usage: %prog [options] <filename of rtc event log>"
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parser = optparse.OptionParser(usage=usage)
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