The Tor Browser / file comparison
comparison: content/media/test/graph_latency.py
content/media/test/graph_latency.py
- branch
- TOR_BUG_9701
- changeset 8
- 97036ab72558
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| -1:000000000000 | 0:a955d1f522d2 |
|---|---|
| 1 #!/usr/bin/env python | |
| 2 # graph_latency.py - graph media latency | |
| 3 # | |
| 4 # This Source Code Form is subject to the terms of the Mozilla Public | |
| 5 # License, v. 2.0. If a copy of the MPL was not distributed with this | |
| 6 # file, You can obtain one at http://mozilla.org/MPL/2.0/. | |
| 7 | |
| 8 # needs matplotlib (sudo aptitude install python-matplotlib) | |
| 9 | |
| 10 import matplotlib.pyplot as plt | |
| 11 from matplotlib import rc | |
| 12 import sys | |
| 13 from pprint import pprint | |
| 14 import re | |
| 15 | |
| 16 | |
| 17 # FIX! needs to be sum of a single mediastreamtrack and any output overhead for it | |
| 18 # So there is one sum per MST | |
| 19 def compute_sum(data): | |
| 20 'Compute the sum for each timestamp. This expects the output of parse_data.' | |
| 21 last_values = {} | |
| 22 out = ([],[]) | |
| 23 | |
| 24 for i in data: | |
| 25 if i[0] not in last_values.keys(): | |
| 26 last_values[i[0]] = 0 | |
| 27 last_values[i[0]] = float(i[3]) | |
| 28 print last_values | |
| 29 out[0].append(i[2]) | |
| 30 out[1].append(sum(last_values.values())) | |
| 31 return out | |
| 32 | |
| 33 | |
| 34 def clean_data(raw_data): | |
| 35 ''' | |
| 36 Remove the PR_LOG cruft at the beginning of each line and returns a list of | |
| 37 tuple. | |
| 38 ''' | |
| 39 out = [] | |
| 40 for line in raw_data: | |
| 41 match = re.match(r'(.*)#(.*)', line) | |
| 42 if match: | |
| 43 continue | |
| 44 else: | |
| 45 out.append(line.split(": ")[1]) | |
| 46 return out | |
| 47 | |
| 48 # returns a list of tuples | |
| 49 def parse_data(raw_lines): | |
| 50 ''' | |
| 51 Split each line by , and put every bit in a tuple. | |
| 52 ''' | |
| 53 out = [] | |
| 54 for line in raw_lines: | |
| 55 out.append(line.split(',')) | |
| 56 return out | |
| 57 | |
| 58 if len(sys.argv) == 3: | |
| 59 name = sys.argv[1] | |
| 60 channels = int(sys.argv[2]) | |
| 61 else: | |
| 62 print sys.argv[0] + "latency_log" | |
| 63 | |
| 64 try: | |
| 65 f = open(sys.argv[1]) | |
| 66 except: | |
| 67 print "cannot open " + name | |
| 68 | |
| 69 raw_lines = f.readlines() | |
| 70 lines = clean_data(raw_lines) | |
| 71 data = parse_data(lines) | |
| 72 | |
| 73 final_data = {} | |
| 74 | |
| 75 for tupl in data: | |
| 76 name = tupl[0] | |
| 77 if tupl[1] != 0: | |
| 78 name = name+tupl[1] | |
| 79 if name not in final_data.keys(): | |
| 80 final_data[name] = ([], []) | |
| 81 # sanity-check values | |
| 82 if float(tupl[3]) < 10*1000: | |
| 83 final_data[name][0].append(float(tupl[2])) | |
| 84 final_data[name][1].append(float(tupl[3])) | |
| 85 | |
| 86 #overall = compute_sum(data) | |
| 87 #final_data["overall"] = overall | |
| 88 | |
| 89 pprint(final_data) | |
| 90 | |
| 91 fig = plt.figure() | |
| 92 for i in final_data.keys(): | |
| 93 plt.plot(final_data[i][0], final_data[i][1], label=i) | |
| 94 | |
| 95 plt.legend() | |
| 96 plt.suptitle("Latency in ms (y-axis) against time in ms (x-axis).") | |
| 97 | |
| 98 size = fig.get_size_inches() | |
| 99 # make it gigantic so we can see things. sometimes, if the graph is too big, | |
| 100 # this errors. reduce the factor so it stays under 2**15. | |
| 101 fig.set_size_inches((size[0]*10, size[1]*2)) | |
| 102 name = sys.argv[1][:-4] + ".pdf" | |
| 103 fig.savefig(name) | |
| 104 |
