livibetter

#!/usr/bin/env python

 

from matplotlib import pyplot

from matplotlib.ticker import IndexLocator

from numpy import *

 

results = [

    ('2.6.31-gentoo-r4', [0.15673866271972656, 0.22011380195617675, 0.31147456169128418, 0.31806101799011233, 0.45194501876831056, 0.49375133514404296, 0.61773824691772461, 0.63911833763122561, 0.75951099395751953, 0.78272194862365718, 0.88353796005249019, 0.94253153800964351, 1.0565287590026855, 1.0960891723632813, 1.2079774379730224, 1.2763566017150878, 1.3607078075408936, 1.4153385639190674, 1.5076858043670653, 1.6175025463104249, 1.6524959564208985, 1.7378323554992676, 1.7971437931060792, 1.8734035968780518, 1.9591879844665527, 2.0440726280212402, 2.094032573699951, 2.1864066123962402, 2.2562743663787841, 2.3418245792388914, 2.4131356239318849, 2.5000920772552488]),

    ('2.6.31-gentoo-r4-bfs', [0.15105123519897462, 0.15202860832214354, 0.23054533004760741, 0.31636881828308105, 0.37918915748596194, 0.46293921470642091, 0.53474774360656741, 0.61435899734497068, 0.68547730445861821, 0.76638255119323728, 0.83417096138000491, 0.91335644721984866, 0.99857978820800786, 1.062566375732422, 1.1367023468017579, 1.2150913715362548, 1.2890355587005615, 1.3727387905120849, 1.4421934127807616, 1.5104918003082275, 1.592773151397705, 1.6809540271759034, 1.7389869689941406, 1.8142241477966308, 1.8861724376678466, 1.9673441886901855, 2.0324893951416017, 2.1128292083740234, 2.1875843524932863, 2.2638030529022215, 2.3384195804595946, 2.4296010017395018]),

    ('2.6.32-rc5', [0.15692081451416015, 0.15577034950256347, 0.23881216049194337, 0.30775957107543944, 0.39050402641296389, 0.46690564155578612, 0.54277920722961426, 0.61949896812438965, 0.69837198257446287, 0.77543320655822756, 0.85235204696655276, 0.93067021369934078, 1.0140983581542968, 1.0921456336975097, 1.1726108551025392, 1.2533286571502686, 1.3232304096221923, 1.4089258670806886, 1.4863292217254638, 1.5622700214385987, 1.6449746131896972, 1.7351542472839356, 1.8334334373474122, 1.880321741104126, 1.9584332466125489, 2.0412515163421632, 2.1100759983062742, 2.1974469661712646, 2.2678318023681641, 2.3443553924560545, 2.4461697578430175, 2.5226269721984864]),

    ]

 

left, width = 0.1, 0.8

rect1 = [left, 0.3, width, 0.6]

rect2 = [left, 0.1, width, 0.2]

 

fig = pyplot.figure()

ax1 = fig.add_axes(rect1)

ax2 = fig.add_axes(rect2, sharex=ax1)

 

ax1.hold(True)

x = range(1, len(results[0][1]) + 1)

for result in results:

  ax1.semilogy(x, result[1], label=result[0])

ax1.legend(loc=0)

ax1.xaxis.set_minor_locator(IndexLocator(1, 0))

ax1.grid(which='major', linestyle='-')

ax1.grid(which='minor')

ax1.set_xlabel('', visible=False)

ax1.set_ylabel('Elapsed time (second, log)')

 

for lbl in ax1.get_xticklabels():

  lbl.set_visible(False)

ax1.get_yticklabels()[0].set_visible(False)

 

base = array(results[0][1])

comp = array(results[1][1])

perf = -1 * (comp - base) / base * 100

ymin = []

ymax = []

for r in perf:

  if r < 0:

    ymin.append(r)

    ymax.append(0)

  else:

    ymin.append(0)

    ymax.append(r)

 

ax2.vlines(x, ymin, ymax, linewidth='10', color='blue')

ax2.xaxis.set_minor_locator(IndexLocator(1, 0))

ax2.grid(which='major', linestyle='-')

ax2.grid(which='minor')

ax2.set_ylabel('Improvement (%)')

ax2.set_xlabel('Concurrent processes')

 

ax2.get_yticklabels()[-1].set_visible(False)

 

for i in range(len(results[0][1])):

  print '%3d %9f(%9f) %9f(%9f) %9f(%9f) %6.2f%%' % (i + 1,

      results[0][1][i], results[0][1][i]/(i+1),

      results[1][1][i], results[1][1][i]/(i+1),

      results[2][1][i], results[2][1][i]/(i+1),

      perf[i])

pyplot.show()