Adding upstream version 1:115.7.0.upstream/1%115.7.0upstream

Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>

1 files changed, 340 insertions, 0 deletions

diff --git a/third_party/libwebrtc/rtc_tools/py_event_log_analyzer/rtp_analyzer.py b/third_party/libwebrtc/rtc_tools/py_event_log_analyzer/rtp_analyzer.py
new file mode 100644
index 0000000000..5844997877
--- /dev/null
+++ b/third_party/libwebrtc/rtc_tools/py_event_log_analyzer/rtp_analyzer.py
@@ -0,0 +1,340 @@
+#!/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()