Plotting of runtime of tests from http://lemire.me/blog/archives/2012/07/23/is-cc-worth-it/#comments ( c++ code - https://gist.github.com/4578190 )

plot-run-time.py

#!/usr/bin/env python

import pylab as pl
import numpy as np
import random
import sys


stat = {}

#each measure should be prefixed by character ':'
for l in sys.stdin:
    if l[0:1] == ':':
        words = l[1:].split()
        num = float(words[-1])
        label = ' '.join(words[:-1])
        stat.setdefault(label, []).append(num)
        
stat = list(sorted(stat.items(), key = lambda (label, vals): (np.median(vals), label))) #sort by median value

def error_pair(vals):
    a, b = np.percentile(vals, [10, 90])
    val = np.median(vals)
    return (val, val-a, b-val)

pl.xlabel('secods of run time')
pl.title('performance of different cum-sum funtions')
pl.subplots_adjust(bottom=0, left=.4, right=.99, top=.90, hspace=.35) #too long labels spans left right without adjust
pl.grid(True)

ypos = np.arange(len(stat))+.5 #vertical positions

val, err_low, err_hi = zip(*[error_pair(time_values) for label, time_values in stat])
    
pl.barh(
    ypos,
    val, 
    xerr=[err_low, err_hi],
    ecolor='r', align='center'
    )

#green dots to plot every measurement    
xdots = []
ydots = []
for y, (labels, xs) in zip(ypos, stat):
    for x in xs:
        xdots.append(x)
        ydots.append(y + random.uniform(-0.3, + 0.3)) #random vertical jitter
pl.plot(xdots, ydots, 'gx', alpha=0.3)

pl.yticks(ypos, [label for label, time_values in stat]) #label for each bar

pl.show()