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