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Issue 703713002: Add nanobench stats scripts to Skia repo. (Closed) Base URL: https://skia.googlesource.com/skia.git@master
Patch Set: ac Created 6 years, 1 month ago
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1 #!/usr/bin/env python
2
3 import sys
4 from scipy.stats import mannwhitneyu
5
6 SIGNIFICANCE_THRESHOLD = 0.0001
7
8 a,b = {},{}
9 for (path, d) in [(sys.argv[1], a), (sys.argv[2], b)]:
10 for line in open(path):
11 try:
12 tokens = line.split()
13 samples = tokens[:-1]
14 label = tokens[-1]
15 d[label] = map(float, samples)
16 except:
17 pass
18
19 common = set(a.keys()).intersection(b.keys())
20
21 ps = []
22 for key in common:
23 _, p = mannwhitneyu(a[key], b[key]) # Non-parametric t-test. Doesn't ass ume normal dist.
24 am, bm = min(a[key]), min(b[key])
25 ps.append((bm/am, p, key, am, bm))
26 ps.sort(reverse=True)
27
28 def humanize(ns):
29 for threshold, suffix in [(1e9, 's'), (1e6, 'ms'), (1e3, 'us'), (1e0, 'ns')] :
30 if ns > threshold:
31 return "%.3g%s" % (ns/threshold, suffix)
32
33 maxlen = max(map(len, common))
34
35 # We print only signficant changes in benchmark timing distribution.
36 bonferroni = SIGNIFICANCE_THRESHOLD / len(ps) # Adjust for the fact we've run m ultiple tests.
37 for ratio, p, key, am, bm in ps:
38 if p < bonferroni:
39 print '%*s\t%6s -> %6s\t%.2gx' % (maxlen, key, humanize(am), humanize(bm ), ratio)
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