| # 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 optparse |
| import os |
| import sys |
| |
| import matplotlib.pyplot as plt |
| import numpy |
| |
| import misc |
| import pb_parse |
| |
| |
| class RTPStatistics(object): |
| """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.normalize_counter( |
| collections.Counter([pt.ssrc for pt in self.data_points])) |
| self.ssrc_size_table = misc.ssrc_normalized_size_table(self.data_points) |
| self.bandwidth_kbps = None |
| self.smooth_bw_kbps = None |
| |
| def print_header_statistics(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 print_ssrc_info(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.normalize_counter( |
| 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 choose_ssrc(self): |
| """Queries user for SSRC.""" |
| |
| if len(self.ssrc_frequencies) == 1: |
| chosen_ssrc = self.ssrc_frequencies[0][-1] |
| self.print_ssrc_info("", chosen_ssrc) |
| return chosen_ssrc |
| |
| ssrc_is_incoming = misc.ssrc_directions(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.print_ssrc_info(i, ssrc) |
| |
| print("\nOutgoing:\n") |
| for (i, ssrc) in enumerate(outgoing): |
| self.print_ssrc_info(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] |
| 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 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 print_sequence_number_statistics(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.count_reordered([point.sequence_number for point in |
| self.data_points]))) |
| |
| def estimate_frequency(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 print_duration_statistics(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 remove_reordered(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 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. |
| """ |
| 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 plot_statistics(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 = calculate_delay(start_ms, stop_ms, |
| RTPStatistics.PLOT_RESOLUTION_MS, |
| self.data_points) |
| |
| plt.figure(1) |
| plt.plot(time_axis, delay) |
| 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 calculate_delay(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.parse_protobuf(input_file) |
| rtp_stats = RTPStatistics(data_points) |
| |
| if options.dump_header_to_stdout: |
| print("Printing header info to stdout.", file=sys.stderr) |
| rtp_stats.print_header_statistics() |
| sys.exit(0) |
| |
| 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.estimate_frequency(options.query_sample_rate) |
| rtp_stats.print_duration_statistics() |
| rtp_stats.remove_reordered() |
| rtp_stats.compute_bandwidth() |
| rtp_stats.plot_statistics() |
| |
| if __name__ == "__main__": |
| main() |
