New rtc dump analyzing tool in Python
R=henrik.lundin@webrtc.org, ivoc@webrtc.org, kwiberg@webrtc.org, peah@webrtc.org, phoglund@webrtc.org Review-Url: https://codereview.webrtc.org/1999113002 Cr-Commit-Position: refs/heads/master@{#13218}
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aleloi
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webrtc/tools/py_event_log_analyzer/rtp_analyzer.py
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webrtc/tools/py_event_log_analyzer/rtp_analyzer.py
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# Copyright (c) 2016 The WebRTC project authors. All Rights Reserved.
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#
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# Use of this source code is governed by a BSD-style license
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# that can be found in the LICENSE file in the root of the source
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# tree. An additional intellectual property rights grant can be found
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# in the file PATENTS. All contributing project authors may
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# be found in the AUTHORS file in the root of the source tree.
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"""Displays statistics and plots graphs from RTC protobuf dump."""
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from __future__ import division
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from __future__ import print_function
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import collections
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import sys
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import matplotlib.pyplot as plt
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import numpy
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import misc
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import pb_parse
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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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def __init__(self, data_points):
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"""Initializes object with data_points and computes simple statistics.
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Computes percentages of number of packets and packet sizes by
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SSRC.
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Args:
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data_points: list of pb_parse.DataPoints on which statistics are
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calculated.
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"""
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self.data_points = data_points
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self.ssrc_frequencies = misc.normalize_counter(
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collections.Counter([pt.ssrc for pt in self.data_points]))
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self.ssrc_size_table = misc.ssrc_normalized_size_table(self.data_points)
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self.bandwidth_kbps = None
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self.smooth_bw_kbps = None
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def print_ssrc_info(self, ssrc_id, ssrc):
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"""Prints packet and size statistics for a given SSRC.
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Args:
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ssrc_id: textual identifier of SSRC printed beside statistics for it.
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ssrc: SSRC by which to filter data and display statistics
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"""
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filtered_ssrc = [point for point in self.data_points if point.ssrc
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== ssrc]
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payloads = misc.normalize_counter(
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collections.Counter([point.payload_type for point in
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filtered_ssrc]))
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payload_info = "payload type(s): {}".format(
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", ".join(str(payload) for payload in payloads))
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print("{} 0x{:x} {}, {:.2f}% packets, {:.2f}% data".format(
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ssrc_id, ssrc, payload_info, self.ssrc_frequencies[ssrc] * 100,
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self.ssrc_size_table[ssrc] * 100))
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print(" packet sizes:")
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(bin_counts, bin_bounds) = numpy.histogram([point.size for point in
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filtered_ssrc], bins=5,
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density=False)
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bin_proportions = bin_counts / sum(bin_counts)
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print("\n".join([
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" {:.1f} - {:.1f}: {:.2f}%".format(bin_bounds[i], bin_bounds[i + 1],
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bin_proportions[i] * 100)
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for i in range(len(bin_proportions))
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]))
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def choose_ssrc(self):
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"""Queries user for SSRC."""
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if len(self.ssrc_frequencies) == 1:
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chosen_ssrc = self.ssrc_frequencies[0][-1]
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self.print_ssrc_info("", chosen_ssrc)
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return chosen_ssrc
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for (i, ssrc) in enumerate(self.ssrc_frequencies):
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self.print_ssrc_info(i, ssrc)
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while True:
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chosen_index = int(misc.get_input("choose one> "))
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if 0 <= chosen_index < len(self.ssrc_frequencies):
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return list(self.ssrc_frequencies)[chosen_index]
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else:
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print("Invalid index!")
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def filter_ssrc(self, chosen_ssrc):
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"""Filters and wraps data points.
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Removes data points with `ssrc != chosen_ssrc`. Unwraps sequence
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numbers and timestamps for the chosen selection.
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"""
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self.data_points = [point for point in self.data_points if
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point.ssrc == chosen_ssrc]
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unwrapped_sequence_numbers = misc.unwrap(
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[point.sequence_number for point in self.data_points], 2**16 - 1)
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for (data_point, sequence_number) in zip(self.data_points,
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unwrapped_sequence_numbers):
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data_point.sequence_number = sequence_number
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unwrapped_timestamps = misc.unwrap([point.timestamp for point in
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self.data_points], 2**32 - 1)
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for (data_point, timestamp) in zip(self.data_points,
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unwrapped_timestamps):
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data_point.timestamp = timestamp
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def print_sequence_number_statistics(self):
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seq_no_set = set(point.sequence_number for point in
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self.data_points)
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print("Missing sequence numbers: {} out of {}".format(
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max(seq_no_set) - min(seq_no_set) + 1 - len(seq_no_set),
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len(seq_no_set)
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))
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print("Duplicated packets: {}".format(len(self.data_points) -
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len(seq_no_set)))
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print("Reordered packets: {}".format(
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misc.count_reordered([point.sequence_number for point in
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self.data_points])))
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def estimate_frequency(self):
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"""Estimates frequency and updates data.
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Guesses the most probable frequency by looking at changes in
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timestamps (RFC 3550 section 5.1), calculates clock drifts and
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sending time of packets. Updates `self.data_points` with changes
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in delay and send time.
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"""
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delta_timestamp = (self.data_points[-1].timestamp -
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self.data_points[0].timestamp)
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delta_arr_timestamp = float((self.data_points[-1].arrival_timestamp_ms -
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self.data_points[0].arrival_timestamp_ms))
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freq_est = delta_timestamp / delta_arr_timestamp
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freq_vec = [8, 16, 32, 48, 90]
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freq = None
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for f in freq_vec:
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if abs((freq_est - f) / f) < 0.05:
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freq = f
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print("Estimated frequency: {}kHz".format(freq_est))
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if freq is None:
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freq = int(misc.get_input(
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"Frequency could not be guessed. Input frequency (in kHz)> "))
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else:
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print("Guessed frequency: {}kHz".format(freq))
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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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def print_duration_statistics(self):
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"""Prints delay, clock drift and bitrate statistics."""
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min_delay = min(point.delay for point in self.data_points)
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for point in self.data_points:
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point.absdelay = point.delay - min_delay
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stream_duration_sender = self.data_points[-1].real_send_time_ms / 1000
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print("Stream duration at sender: {:.1f} seconds".format(
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stream_duration_sender
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))
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arrival_timestamps_ms = [point.arrival_timestamp_ms for point in
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self.data_points]
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stream_duration_receiver = (max(arrival_timestamps_ms) -
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min(arrival_timestamps_ms)) / 1000
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print("Stream duration at receiver: {:.1f} seconds".format(
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stream_duration_receiver
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))
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print("Clock drift: {:.2f}%".format(
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100 * (stream_duration_receiver / stream_duration_sender - 1)
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))
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total_size = sum(point.size for point in self.data_points) * 8 / 1000
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print("Send average bitrate: {:.2f} kbps".format(
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total_size / stream_duration_sender))
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print("Receive average bitrate: {:.2f} kbps".format(
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total_size / stream_duration_receiver))
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def remove_reordered(self):
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last = self.data_points[0]
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data_points_ordered = [last]
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for point in self.data_points[1:]:
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if point.sequence_number > last.sequence_number and (
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point.real_send_time_ms > last.real_send_time_ms):
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data_points_ordered.append(point)
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last = point
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self.data_points = data_points_ordered
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def compute_bandwidth(self):
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"""Computes bandwidth averaged over several consecutive packets.
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The number of consecutive packets used in the average is
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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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)
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correlate_filter = (numpy.ones(
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RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE) /
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RTPStatistics.BANDWIDTH_SMOOTHING_WINDOW_SIZE)
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self.smooth_bw_kbps = numpy.correlate(self.bandwidth_kbps, correlate_filter)
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def plot_statistics(self):
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"""Plots changes in delay and average bandwidth."""
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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.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.xlabel("Send time [s]")
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plt.ylabel("Bandwidth [kbps]")
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plt.show()
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def main():
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if len(sys.argv) < 2:
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print("Usage: python rtp_analyzer.py <filename of rtc event log>")
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sys.exit(0)
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data_points = pb_parse.parse_protobuf(sys.argv[1])
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rtp_stats = RTPStatistics(data_points)
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chosen_ssrc = rtp_stats.choose_ssrc()
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print("Chosen SSRC: 0X{:X}".format(chosen_ssrc))
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rtp_stats.filter_ssrc(chosen_ssrc)
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print("Statistics:")
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rtp_stats.print_sequence_number_statistics()
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rtp_stats.estimate_frequency()
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rtp_stats.print_duration_statistics()
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rtp_stats.remove_reordered()
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rtp_stats.compute_bandwidth()
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rtp_stats.plot_statistics()
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if __name__ == "__main__":
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main()
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