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Unified Diff: tools/py_event_log_analyzer/rtp_analyzer.py

Issue 1999113002: New rtc dump analyzing tool in Python (Closed) Base URL: https://chromium.googlesource.com/external/webrtc.git@master
Patch Set: Updated README to reflect changes in code. Created 4 years, 7 months ago
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Index: tools/py_event_log_analyzer/rtp_analyzer.py
diff --git a/tools/py_event_log_analyzer/rtp_analyzer.py b/tools/py_event_log_analyzer/rtp_analyzer.py
new file mode 100644
index 0000000000000000000000000000000000000000..efa86ffd935e8031e4d3d7d405012aa6f7da0565
--- /dev/null
+++ b/tools/py_event_log_analyzer/rtp_analyzer.py
@@ -0,0 +1,266 @@
+# 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
+
+import collections
+import sys
+import builtins
+import matplotlib.pyplot as plt
+import misc
+import numpy
+import pb_parse
+
+
+
+class RTPStatistics(object):
+ """Has methods for calculating and plotting statistics for RPT
hlundin-webrtc 2016/05/25 12:54:23 RPT -> RTP
+ packets.
+ """
+
+ BANDWIDTH_SMOOTHING_WINDOW_SIZE = 10
+
+ def __init__(self, data_points):
+ """Initializes object with data_points computes simple statistics:
kwiberg-webrtc 2016/05/25 12:42:42 and
aleloi2 2016/05/30 14:57:56 Done.
+ percentages 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.percent_table([x.ssrc for x in
+ self.data_points])
+ self.ssrc_size_table = misc.ssrc_size_table(self.data_points)
+ self.bandwidth_kbps = None
+ self.smooth_bw_kbps = None
+
+ def print_ssrc_info(self, ssrc_id, ssrc):
+ """Prints packet and size statistics for given SSRC.
peah-webrtc 2016/05/26 06:44:18 Maybe "the" or "a" should be added between "for" a
aleloi2 2016/05/30 14:57:56 Done.
+
+ Args:
+ ssrc_id: textual identifier of SSRC printed beside statistics for it.
+ ssrc: SSRC by which to filter data and display statistics
+
+ Raises:
+ Exception: when different payload types are present in data
hlundin-webrtc 2016/05/25 12:54:23 This will happen, and can be legit. When comfort n
aleloi2 2016/05/30 14:57:55 Now it prints the different payload types instead
+ for same SSRC
+ """
+ filtered_ssrc = [x for x in self.data_points if x.ssrc == ssrc]
+ payloads = misc.percent_table([x.payload_type for x in filtered_ssrc])
+
+ if len(payloads) == 1:
+ payload_info = "payload type {}".format(*list(payloads))
+ else:
+ raise Exception(
+ "This tool cannot yet handle changes in codec sample rate")
+ print("{} 0X{:X} {}, {:.2f}% packets, {:.2f}% data".format(
kwiberg-webrtc 2016/05/25 12:42:42 Consider using lowercase hexadecimal. It causes le
aleloi2 2016/05/30 14:57:56 Ok.
+ ssrc_id, ssrc, payload_info, self.ssrc_frequencies[ssrc]*100,
+ self.ssrc_size_table[ssrc]*100))
kwiberg-webrtc 2016/05/25 12:42:41 You still have some binary operators not surrounde
aleloi2 2016/05/30 14:57:56 Done.
+ print(" packet sizes:")
+ bin_counts, bin_bounds = numpy.histogram([x.size for x 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 builtins.range(len(bin_proportions))
+ ]))
+
+ def choose_ssrc(self):
+ """Queries user for SSRC."""
+ ssrc_frequencies_lst = list(enumerate(self.ssrc_frequencies))
kwiberg-webrtc 2016/05/25 12:42:42 Eliminate this variable. You don't use it for anyt
aleloi2 2016/05/30 14:57:56 It was used to pair ssrc with an integer counter,
+
+ if len(self.ssrc_frequencies) == 1:
+ chosen_ssrc = self.ssrc_frequencies[0][-1]
+ self.print_ssrc_info("", chosen_ssrc)
+ return chosen_ssrc
+
+ for i, ssrc in enumerate(self.ssrc_frequencies):
+ self.print_ssrc_info(i, ssrc)
+
+ while True:
+ chosen_index = int(builtins.input("choose one> "))
+ if 0 <= chosen_index < len(ssrc_frequencies_lst):
+ return ssrc_frequencies_lst[chosen_index][-1]
+ else:
+ print("Invalid index!")
+
+ def filter_ssrc(self, chosen_ssrc):
+ """Filters and wraps data points.
+
+ Removes data points with `ssrc != chosen_ssrc`. Unwraps sequence
+ numbers and time stamps for the chosen selection.
hlundin-webrtc 2016/05/25 12:54:23 Nit: 'timestamps' is typically written as one word
aleloi2 2016/05/30 14:57:56 Done.
+ """
+ self.data_points = [x for x in self.data_points if x.ssrc ==
+ chosen_ssrc]
+ unwrapped_sequence_numbers = misc.unwrap([x.sequence_number for x 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([x.timestamp for x in self.data_points],
+ 2**32-1)
+
+ for (data_point, timestamp) in zip(self.data_points,
+ unwrapped_timestamps):
+ data_point.timestamp = timestamp
+
+ def print_sequence_number_statistics(self):
+ seq_no_set = set(x.sequence_number for x in self.data_points)
+ print("Missing sequence numbers: {} out of {}".format(
+ max(seq_no_set) - min(seq_no_set) + 1 - len(seq_no_set),
+ len(seq_no_set)
+ ))
+ packet_counter = collections.Counter(x.sequence_number for x in
+ self.data_points)
+ print("Duplicated packets: {}".format(sum(packet_counter.values())
+ - len(packet_counter)
+ ))
kwiberg-webrtc 2016/05/25 12:42:41 Unless I'm mistaken, it's simpler and more efficie
aleloi2 2016/05/30 14:57:56 I agree. Changed.
+ print("Reordered packets: {}".format(
+ misc.count_reordered([x.sequence_number for x in self.data_points])))
+
+ def print_frequency_duration_statistics(self):
peah-webrtc 2016/05/26 06:44:19 Suggestion: This is a fairly long method which doe
aleloi2 2016/05/30 14:57:56 I agree. I divided it into a frequency related and
+ """Estimates frequency and prints related statistics.
+
+ 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))
+ fs_est = delta_timestamp / delta_arr_timestamp
+
+ fs_vec = [8, 16, 32, 48, 90] # TODO(aleloi) 90 is a hack for video
hlundin-webrtc 2016/05/25 12:54:23 Not really a "hack"; https://tools.ietf.org/html/r
peah-webrtc 2016/05/26 06:44:18 The python style guide actually has an example whe
+ fs = None
+ for f in fs_vec:
+ if abs((fs_est - f)/float(f)) < 0.05:
kwiberg-webrtc 2016/05/25 12:42:42 No need for float, since you import division from
aleloi2 2016/05/30 14:57:56 OK.
+ fs = f
+
+ print("Estimated frequency: {}".format(fs_est))
+ if fs is None:
+ fs = int(builtins.input(
+ "Frequency could not be guessed. Input frequency> "))
+
+ print("Guessed frequency: {}".format(fs))
kwiberg-webrtc 2016/05/25 12:42:41 Don't print this if the user entered a frequency.
aleloi2 2016/05/30 14:57:56 Done.
+
+ for f in self.data_points:
+ f.real_send_time_ms = (f.timestamp -
+ self.data_points[0].timestamp) / fs
+ f.delay = f.arrival_timestamp_ms - f.real_send_time_ms
+
+ min_delay = min(f.delay for f in self.data_points)
+
+ for f in self.data_points:
hlundin-webrtc 2016/05/25 12:54:23 Oh. Python cannot do "vector +/- scalar" without e
kwiberg-webrtc 2016/05/25 13:00:31 No. list + list returns a new list that's a concat
ivoc 2016/05/25 13:17:37 It could do it if it was a numpy array instead of
kwiberg-webrtc 2016/05/25 13:29:04 Right, I'd forgotten about numpy, because I never
+ f.absdelay = f.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 = [pt.arrival_timestamp_ms for pt 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)
+ ))
+
+ print("Send average bitrate: {:.2f} kbps".format(
+ sum(x.size for x
+ in self.data_points) * 8 / stream_duration_sender / 1000))
+
+ print("Receive average bitrate: {:.2f} kbps".format(
+ sum(x.size
+ for x in self.data_points) * 8 / stream_duration_receiver /
+ 1000))
+
+ def remove_reordered(self):
+ last = self.data_points[0]
+ data_points_ordered = [last]
+ for x in self.data_points[1:]:
+ if x.sequence_number > last.sequence_number and (x.real_send_time_ms >
+ last.real_send_time_ms):
+ data_points_ordered.append(x)
+ last = x
+ self.data_points = data_points_ordered
+
+ def compute_bandwidth(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.
+ """
+ self.bandwidth_kbps = []
+ for i in range(len(self.data_points)-1):
+ self.bandwidth_kbps.append(
+ self.data_points[i].size*8 / (self.data_points[i+1].real_send_time_ms
+ - self.data_points[i].real_send_time_ms)
+ )
+ 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 plot_statistics(self):
+ """Plots changes in delay and average bandwidth."""
+ plt.figure(1)
+ plt.plot([f.real_send_time_ms/1000 for f in self.data_points],
+ [f.absdelay for f in self.data_points])
+ plt.xlabel("Send time [s]")
+ plt.ylabel("Relative transport delay [ms]")
+
+ plt.figure(2)
+ plt.plot([f.real_send_time_ms / 1000 for f in
+ self.data_points][:len(self.smooth_bw_kbps)],
+ self.smooth_bw_kbps[:len(self.data_points)])
+ plt.xlabel("Send time [s]")
+ plt.ylabel("Bandwidth [kbps]")
+
+ plt.show()
+
+
+def main():
+
+ if len(sys.argv) < 2:
+ print("Usage: python rtp_analyzer.py <filename of rtc event log>")
+ sys.exit(0)
+
+ data_points = pb_parse.parse_protobuf(sys.argv[1])
+ rtp_stats = RTPStatistics(data_points)
+ chosen_ssrc = rtp_stats.choose_ssrc()
+ print("Chosen SSRC: 0X{:X}".format(chosen_ssrc))
+
+ rtp_stats.filter_ssrc(chosen_ssrc)
+ print("Statistics:")
+ rtp_stats.print_sequence_number_statistics()
+ rtp_stats.print_frequency_duration_statistics()
+ rtp_stats.remove_reordered()
+ rtp_stats.compute_bandwidth()
+ rtp_stats.plot_statistics()
+
+if __name__ == "__main__":
+ main()
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