|  | #!/usr/bin/env python | 
|  |  | 
|  | import argparse | 
|  | import sys | 
|  |  | 
|  | have_scipy = True | 
|  | try: | 
|  | import scipy.stats | 
|  | except: | 
|  | have_scipy = False | 
|  |  | 
|  | SIGNIFICANCE_THRESHOLD = 0.0001 | 
|  |  | 
|  | parser = argparse.ArgumentParser( | 
|  | formatter_class=argparse.RawDescriptionHelpFormatter, | 
|  | description='Compare performance of two runs from nanobench.') | 
|  | parser.add_argument('--use_means', action='store_true', default=False, | 
|  | help='Use means to calculate performance ratios.') | 
|  | parser.add_argument('baseline', help='Baseline file.') | 
|  | parser.add_argument('experiment', help='Experiment file.') | 
|  | args = parser.parse_args() | 
|  |  | 
|  | a,b = {},{} | 
|  | for (path, d) in [(args.baseline, a), (args.experiment, b)]: | 
|  | for line in open(path): | 
|  | try: | 
|  | tokens = line.split() | 
|  | if tokens[0] != "Samples:": | 
|  | continue | 
|  | samples  = tokens[1:-1] | 
|  | label    = tokens[-1] | 
|  | d[label] = map(float, samples) | 
|  | except: | 
|  | pass | 
|  |  | 
|  | common = set(a.keys()).intersection(b.keys()) | 
|  |  | 
|  | def mean(xs): | 
|  | return sum(xs) / len(xs) | 
|  |  | 
|  | ps = [] | 
|  | for key in common: | 
|  | p, asem, bsem = 0, 0, 0 | 
|  | m = mean if args.use_means else min | 
|  | am, bm = m(a[key]), m(b[key]) | 
|  | if have_scipy: | 
|  | _, p = scipy.stats.mannwhitneyu(a[key], b[key]) | 
|  | asem, bsem = scipy.stats.sem(a[key]), scipy.stats.sem(b[key]) | 
|  | ps.append((bm/am, p, key, am, bm, asem, bsem)) | 
|  | ps.sort(reverse=True) | 
|  |  | 
|  | def humanize(ns): | 
|  | for threshold, suffix in [(1e9, 's'), (1e6, 'ms'), (1e3, 'us'), (1e0, 'ns')]: | 
|  | if ns > threshold: | 
|  | return "%.3g%s" % (ns/threshold, suffix) | 
|  |  | 
|  | maxlen = max(map(len, common)) | 
|  |  | 
|  | # We print only signficant changes in benchmark timing distribution. | 
|  | bonferroni = SIGNIFICANCE_THRESHOLD / len(ps)  # Adjust for the fact we've run multiple tests. | 
|  | for ratio, p, key, am, bm, asem, bsem in ps: | 
|  | if p < bonferroni: | 
|  | str_ratio = ('%.2gx' if ratio < 1 else '%.3gx') % ratio | 
|  | if args.use_means: | 
|  | print '%*s\t%6s(%6s) -> %6s(%6s)\t%s' % (maxlen, key, humanize(am), humanize(asem), | 
|  | humanize(bm), humanize(bsem), str_ratio) | 
|  | else: | 
|  | print '%*s\t%6s -> %6s\t%s' % (maxlen, key, humanize(am), humanize(bm), str_ratio) |