mirror of
https://github.com/mollyim/webrtc.git
synced 2025-05-12 21:30:45 +01:00
83e34eed87
python-modernize, format and some manual lint fixes No-Try: True Bug: None Change-Id: I89d9f97f238be887962c67e18cc6480a8f6f3ac4 Reviewed-on: https://webrtc-review.googlesource.com/c/src/+/264551 Commit-Queue: Mirko Bonadei <mbonadei@webrtc.org> Reviewed-by: Mirko Bonadei <mbonadei@webrtc.org> Reviewed-by: Tomas Gunnarsson <tommi@webrtc.org> Cr-Commit-Position: refs/heads/main@{#37071}
340 lines
12 KiB
Python
340 lines
12 KiB
Python
#!/usr/bin/env python3
|
|
# Copyright (c) 2016 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.
|
|
"""Displays statistics and plots graphs from RTC protobuf dump."""
|
|
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
from __future__ import absolute_import
|
|
import collections
|
|
import optparse
|
|
import os
|
|
import sys
|
|
from six.moves import range
|
|
from six.moves import zip
|
|
|
|
import matplotlib.pyplot as plt
|
|
import numpy
|
|
|
|
import misc
|
|
import pb_parse
|
|
|
|
|
|
class RTPStatistics:
|
|
"""Has methods for calculating and plotting RTP stream statistics."""
|
|
|
|
BANDWIDTH_SMOOTHING_WINDOW_SIZE = 10
|
|
PLOT_RESOLUTION_MS = 50
|
|
|
|
def __init__(self, data_points):
|
|
"""Initializes object with data_points and computes simple statistics.
|
|
|
|
Computes percentages of number of packets and packet sizes by
|
|
SSRC.
|
|
|
|
Args:
|
|
data_points: list of pb_parse.DataPoints on which statistics are
|
|
calculated.
|
|
|
|
"""
|
|
|
|
self.data_points = data_points
|
|
self.ssrc_frequencies = misc.NormalizeCounter(
|
|
collections.Counter([pt.ssrc for pt in self.data_points]))
|
|
self.ssrc_size_table = misc.SsrcNormalizedSizeTable(self.data_points)
|
|
self.bandwidth_kbps = None
|
|
self.smooth_bw_kbps = None
|
|
|
|
def PrintHeaderStatistics(self):
|
|
print("{:>6}{:>14}{:>14}{:>6}{:>6}{:>3}{:>11}".format(
|
|
"SeqNo", "TimeStamp", "SendTime", "Size", "PT", "M", "SSRC"))
|
|
for point in self.data_points:
|
|
print("{:>6}{:>14}{:>14}{:>6}{:>6}{:>3}{:>11}".format(
|
|
point.sequence_number, point.timestamp,
|
|
int(point.arrival_timestamp_ms), point.size, point.payload_type,
|
|
point.marker_bit, "0x{:x}".format(point.ssrc)))
|
|
|
|
def PrintSsrcInfo(self, ssrc_id, ssrc):
|
|
"""Prints packet and size statistics for a given SSRC.
|
|
|
|
Args:
|
|
ssrc_id: textual identifier of SSRC printed beside statistics for it.
|
|
ssrc: SSRC by which to filter data and display statistics
|
|
"""
|
|
filtered_ssrc = [point for point in self.data_points if point.ssrc == ssrc]
|
|
payloads = misc.NormalizeCounter(
|
|
collections.Counter([point.payload_type for point in filtered_ssrc]))
|
|
|
|
payload_info = "payload type(s): {}".format(", ".join(
|
|
str(payload) for payload in payloads))
|
|
print("{} 0x{:x} {}, {:.2f}% packets, {:.2f}% data".format(
|
|
ssrc_id, ssrc, payload_info, self.ssrc_frequencies[ssrc] * 100,
|
|
self.ssrc_size_table[ssrc] * 100))
|
|
print(" packet sizes:")
|
|
(bin_counts,
|
|
bin_bounds) = numpy.histogram([point.size for point in filtered_ssrc],
|
|
bins=5,
|
|
density=False)
|
|
bin_proportions = bin_counts / sum(bin_counts)
|
|
print("\n".join([
|
|
" {:.1f} - {:.1f}: {:.2f}%".format(bin_bounds[i], bin_bounds[i + 1],
|
|
bin_proportions[i] * 100)
|
|
for i in range(len(bin_proportions))
|
|
]))
|
|
|
|
def ChooseSsrc(self):
|
|
"""Queries user for SSRC."""
|
|
|
|
if len(self.ssrc_frequencies) == 1:
|
|
chosen_ssrc = list(self.ssrc_frequencies.keys())[0]
|
|
self.PrintSsrcInfo("", chosen_ssrc)
|
|
return chosen_ssrc
|
|
|
|
ssrc_is_incoming = misc.SsrcDirections(self.data_points)
|
|
incoming = [ssrc for ssrc in ssrc_is_incoming if ssrc_is_incoming[ssrc]]
|
|
outgoing = [ssrc for ssrc in ssrc_is_incoming if not ssrc_is_incoming[ssrc]]
|
|
|
|
print("\nIncoming:\n")
|
|
for (i, ssrc) in enumerate(incoming):
|
|
self.PrintSsrcInfo(i, ssrc)
|
|
|
|
print("\nOutgoing:\n")
|
|
for (i, ssrc) in enumerate(outgoing):
|
|
self.PrintSsrcInfo(i + len(incoming), ssrc)
|
|
|
|
while True:
|
|
chosen_index = int(misc.get_input("choose one> "))
|
|
if 0 <= chosen_index < len(self.ssrc_frequencies):
|
|
return (incoming + outgoing)[chosen_index]
|
|
print("Invalid index!")
|
|
|
|
def FilterSsrc(self, chosen_ssrc):
|
|
"""Filters and wraps data points.
|
|
|
|
Removes data points with `ssrc != chosen_ssrc`. Unwraps sequence
|
|
numbers and timestamps for the chosen selection.
|
|
"""
|
|
self.data_points = [
|
|
point for point in self.data_points if point.ssrc == chosen_ssrc
|
|
]
|
|
unwrapped_sequence_numbers = misc.Unwrap(
|
|
[point.sequence_number for point in self.data_points], 2**16 - 1)
|
|
for (data_point, sequence_number) in zip(self.data_points,
|
|
unwrapped_sequence_numbers):
|
|
data_point.sequence_number = sequence_number
|
|
|
|
unwrapped_timestamps = misc.Unwrap(
|
|
[point.timestamp for point in self.data_points], 2**32 - 1)
|
|
|
|
for (data_point, timestamp) in zip(self.data_points, unwrapped_timestamps):
|
|
data_point.timestamp = timestamp
|
|
|
|
def PrintSequenceNumberStatistics(self):
|
|
seq_no_set = set(point.sequence_number for point in self.data_points)
|
|
missing_sequence_numbers = max(seq_no_set) - min(seq_no_set) + (
|
|
1 - len(seq_no_set))
|
|
print("Missing sequence numbers: {} out of {} ({:.2f}%)".format(
|
|
missing_sequence_numbers, len(seq_no_set),
|
|
100 * missing_sequence_numbers / len(seq_no_set)))
|
|
print("Duplicated packets: {}".format(
|
|
len(self.data_points) - len(seq_no_set)))
|
|
print("Reordered packets: {}".format(
|
|
misc.CountReordered(
|
|
[point.sequence_number for point in self.data_points])))
|
|
|
|
def EstimateFrequency(self, always_query_sample_rate):
|
|
"""Estimates frequency and updates data.
|
|
|
|
Guesses the most probable frequency by looking at changes in
|
|
timestamps (RFC 3550 section 5.1), calculates clock drifts and
|
|
sending time of packets. Updates `self.data_points` with changes
|
|
in delay and send time.
|
|
"""
|
|
delta_timestamp = (self.data_points[-1].timestamp -
|
|
self.data_points[0].timestamp)
|
|
delta_arr_timestamp = float((self.data_points[-1].arrival_timestamp_ms -
|
|
self.data_points[0].arrival_timestamp_ms))
|
|
freq_est = delta_timestamp / delta_arr_timestamp
|
|
|
|
freq_vec = [8, 16, 32, 48, 90]
|
|
freq = None
|
|
for f in freq_vec:
|
|
if abs((freq_est - f) / f) < 0.05:
|
|
freq = f
|
|
|
|
print("Estimated frequency: {:.3f}kHz".format(freq_est))
|
|
if freq is None or always_query_sample_rate:
|
|
if not always_query_sample_rate:
|
|
print("Frequency could not be guessed.", end=" ")
|
|
freq = int(misc.get_input("Input frequency (in kHz)> "))
|
|
else:
|
|
print("Guessed frequency: {}kHz".format(freq))
|
|
|
|
for point in self.data_points:
|
|
point.real_send_time_ms = (point.timestamp -
|
|
self.data_points[0].timestamp) / freq
|
|
point.delay = point.arrival_timestamp_ms - point.real_send_time_ms
|
|
|
|
def PrintDurationStatistics(self):
|
|
"""Prints delay, clock drift and bitrate statistics."""
|
|
|
|
min_delay = min(point.delay for point in self.data_points)
|
|
|
|
for point in self.data_points:
|
|
point.absdelay = point.delay - min_delay
|
|
|
|
stream_duration_sender = self.data_points[-1].real_send_time_ms / 1000
|
|
print("Stream duration at sender: {:.1f} seconds".format(
|
|
stream_duration_sender))
|
|
|
|
arrival_timestamps_ms = [
|
|
point.arrival_timestamp_ms for point in self.data_points
|
|
]
|
|
stream_duration_receiver = (max(arrival_timestamps_ms) -
|
|
min(arrival_timestamps_ms)) / 1000
|
|
print("Stream duration at receiver: {:.1f} seconds".format(
|
|
stream_duration_receiver))
|
|
|
|
print("Clock drift: {:.2f}%".format(
|
|
100 * (stream_duration_receiver / stream_duration_sender - 1)))
|
|
|
|
total_size = sum(point.size for point in self.data_points) * 8 / 1000
|
|
print("Send average bitrate: {:.2f} kbps".format(total_size /
|
|
stream_duration_sender))
|
|
|
|
print("Receive average bitrate: {:.2f} kbps".format(
|
|
total_size / stream_duration_receiver))
|
|
|
|
def RemoveReordered(self):
|
|
last = self.data_points[0]
|
|
data_points_ordered = [last]
|
|
for point in self.data_points[1:]:
|
|
if point.sequence_number > last.sequence_number and (
|
|
point.real_send_time_ms > last.real_send_time_ms):
|
|
data_points_ordered.append(point)
|
|
last = point
|
|
self.data_points = data_points_ordered
|
|
|
|
def ComputeBandwidth(self):
|
|
"""Computes bandwidth averaged over several consecutive packets.
|
|
|
|
The number of consecutive packets used in the average is
|
|
BANDWIDTH_SMOOTHING_WINDOW_SIZE. Averaging is done with
|
|
numpy.correlate.
|
|
"""
|
|
start_ms = self.data_points[0].real_send_time_ms
|
|
stop_ms = self.data_points[-1].real_send_time_ms
|
|
(self.bandwidth_kbps, _) = numpy.histogram(
|
|
[point.real_send_time_ms for point in self.data_points],
|
|
bins=numpy.arange(start_ms, stop_ms, RTPStatistics.PLOT_RESOLUTION_MS),
|
|
weights=[
|
|
point.size * 8 / RTPStatistics.PLOT_RESOLUTION_MS
|
|
for point in self.data_points
|
|
])
|
|
correlate_filter = (
|
|
numpy.ones(RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE) /
|
|
RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE)
|
|
self.smooth_bw_kbps = numpy.correlate(self.bandwidth_kbps, correlate_filter)
|
|
|
|
def PlotStatistics(self):
|
|
"""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 = CalculateDelay(start_ms, stop_ms, RTPStatistics.PLOT_RESOLUTION_MS,
|
|
self.data_points)
|
|
|
|
plt.figure(1)
|
|
plt.plot(time_axis, delay[:len(time_axis)])
|
|
plt.xlabel("Send time [s]")
|
|
plt.ylabel("Relative transport delay [ms]")
|
|
|
|
plt.figure(2)
|
|
plt.plot(time_axis[:len(self.smooth_bw_kbps)], self.smooth_bw_kbps)
|
|
plt.xlabel("Send time [s]")
|
|
plt.ylabel("Bandwidth [kbps]")
|
|
|
|
plt.show()
|
|
|
|
|
|
def CalculateDelay(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, 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 -1 for arr in grouped_delays
|
|
]
|
|
return numpy.ma.masked_values(regularized_delays, -1)
|
|
|
|
|
|
def main():
|
|
usage = "Usage: %prog [options] <filename of rtc event log>"
|
|
parser = optparse.OptionParser(usage=usage)
|
|
parser.add_option("--dump_header_to_stdout",
|
|
default=False,
|
|
action="store_true",
|
|
help="print header info to stdout; similar to rtp_analyze")
|
|
parser.add_option("--query_sample_rate",
|
|
default=False,
|
|
action="store_true",
|
|
help="always query user for real sample rate")
|
|
|
|
parser.add_option("--working_directory",
|
|
default=None,
|
|
action="store",
|
|
help="directory in which to search for relative paths")
|
|
|
|
(options, args) = parser.parse_args()
|
|
|
|
if len(args) < 1:
|
|
parser.print_help()
|
|
sys.exit(0)
|
|
|
|
input_file = args[0]
|
|
|
|
if options.working_directory and not os.path.isabs(input_file):
|
|
input_file = os.path.join(options.working_directory, input_file)
|
|
|
|
data_points = pb_parse.ParseProtobuf(input_file)
|
|
rtp_stats = RTPStatistics(data_points)
|
|
|
|
if options.dump_header_to_stdout:
|
|
print("Printing header info to stdout.", file=sys.stderr)
|
|
rtp_stats.PrintHeaderStatistics()
|
|
sys.exit(0)
|
|
|
|
chosen_ssrc = rtp_stats.ChooseSsrc()
|
|
print("Chosen SSRC: 0X{:X}".format(chosen_ssrc))
|
|
|
|
rtp_stats.FilterSsrc(chosen_ssrc)
|
|
|
|
print("Statistics:")
|
|
rtp_stats.PrintSequenceNumberStatistics()
|
|
rtp_stats.EstimateFrequency(options.query_sample_rate)
|
|
rtp_stats.PrintDurationStatistics()
|
|
rtp_stats.RemoveReordered()
|
|
rtp_stats.ComputeBandwidth()
|
|
rtp_stats.PlotStatistics()
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|