| #!/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) |