| #!/usr/bin/env python |
| |
| import argparse |
| import numpy |
| import sys |
| from scipy.stats import mannwhitneyu |
| from scipy.stats import sem |
| |
| 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()) |
| |
| ps = [] |
| for key in common: |
| _, p = mannwhitneyu(a[key], b[key]) # Non-parametric t-test. Doesn't assume normal dist. |
| if args.use_means: |
| am, bm = numpy.mean(a[key]), numpy.mean(b[key]) |
| asem, bsem = sem(a[key]), sem(b[key]) |
| else: |
| am, bm = min(a[key]), min(b[key]) |
| asem, bsem = 0, 0 |
| 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) |