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#!/usr/bin/env python
# graph_latency.py - graph media latency
#
# This Source Code Form is subject to the terms of the Mozilla Public
# License, v. 2.0. If a copy of the MPL was not distributed with this
# file, You can obtain one at http://mozilla.org/MPL/2.0/.
# needs matplotlib (sudo aptitude install python-matplotlib)
import matplotlib.pyplot as plt
from matplotlib import rc
import sys
from pprint import pprint
import re
# FIX! needs to be sum of a single mediastreamtrack and any output overhead for it
# So there is one sum per MST
def compute_sum(data):
'Compute the sum for each timestamp. This expects the output of parse_data.'
last_values = {}
out = ([],[])
for i in data:
if i[0] not in last_values.keys():
last_values[i[0]] = 0
last_values[i[0]] = float(i[3])
print last_values
out[0].append(i[2])
out[1].append(sum(last_values.values()))
return out
def clean_data(raw_data):
'''
Remove the PR_LOG cruft at the beginning of each line and returns a list of
tuple.
'''
out = []
for line in raw_data:
match = re.match(r'(.*)#(.*)', line)
if match:
continue
else:
out.append(line.split(": ")[1])
return out
# returns a list of tuples
def parse_data(raw_lines):
'''
Split each line by , and put every bit in a tuple.
'''
out = []
for line in raw_lines:
out.append(line.split(','))
return out
if len(sys.argv) == 3:
name = sys.argv[1]
channels = int(sys.argv[2])
else:
print sys.argv[0] + "latency_log"
try:
f = open(sys.argv[1])
except:
print "cannot open " + name
raw_lines = f.readlines()
lines = clean_data(raw_lines)
data = parse_data(lines)
final_data = {}
for tupl in data:
name = tupl[0]
if tupl[1] != 0:
name = name+tupl[1]
if name not in final_data.keys():
final_data[name] = ([], [])
# sanity-check values
if float(tupl[3]) < 10*1000:
final_data[name][0].append(float(tupl[2]))
final_data[name][1].append(float(tupl[3]))
#overall = compute_sum(data)
#final_data["overall"] = overall
pprint(final_data)
fig = plt.figure()
for i in final_data.keys():
plt.plot(final_data[i][0], final_data[i][1], label=i)
plt.legend()
plt.suptitle("Latency in ms (y-axis) against time in ms (x-axis).")
size = fig.get_size_inches()
# make it gigantic so we can see things. sometimes, if the graph is too big,
# this errors. reduce the factor so it stays under 2**15.
fig.set_size_inches((size[0]*10, size[1]*2))
name = sys.argv[1][:-4] + ".pdf"
fig.savefig(name)
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