17ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein#!/usr/bin/env python 27ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 37ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinimport sys 47ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinfrom scipy.stats import mannwhitneyu 57ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 67ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinSIGNIFICANCE_THRESHOLD = 0.0001 77ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 87ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleina,b = {},{} 97ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinfor (path, d) in [(sys.argv[1], a), (sys.argv[2], b)]: 107ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein for line in open(path): 117ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein try: 127ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein tokens = line.split() 137ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein samples = tokens[:-1] 147ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein label = tokens[-1] 157ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein d[label] = map(float, samples) 167ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein except: 177ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein pass 187ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 197ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleincommon = set(a.keys()).intersection(b.keys()) 207ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 217ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinps = [] 227ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinfor key in common: 237ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein _, p = mannwhitneyu(a[key], b[key]) # Non-parametric t-test. Doesn't assume normal dist. 247ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein am, bm = min(a[key]), min(b[key]) 257ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein ps.append((bm/am, p, key, am, bm)) 267ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinps.sort(reverse=True) 277ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 287ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleindef humanize(ns): 297ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein for threshold, suffix in [(1e9, 's'), (1e6, 'ms'), (1e3, 'us'), (1e0, 'ns')]: 307ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein if ns > threshold: 317ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein return "%.3g%s" % (ns/threshold, suffix) 327ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 337ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinmaxlen = max(map(len, common)) 347ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein 357ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein# We print only signficant changes in benchmark timing distribution. 367ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinbonferroni = SIGNIFICANCE_THRESHOLD / len(ps) # Adjust for the fact we've run multiple tests. 377ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtkleinfor ratio, p, key, am, bm in ps: 387ba39cb9a6c97f07eb392a1cf99ce65c1f23ded0mtklein if p < bonferroni: 398a84db909a65fae4e801999fb45c538aaad805a8Mike Klein str_ratio = ('%.2gx' if ratio < 1 else '%.3gx') % ratio 408a84db909a65fae4e801999fb45c538aaad805a8Mike Klein print '%*s\t%6s -> %6s\t%s' % (maxlen, key, humanize(am), humanize(bm), str_ratio) 41