Don't suppress nanobench output table in verbose mode

bin/compare

 #!/usr/bin/env python
 
 import sys
 from scipy.stats import mannwhitneyu
 
 SIGNIFICANCE_THRESHOLD = 0.0001
 
 a,b = {},{}
 for (path, d) in [(sys.argv[1], a), (sys.argv[2], b)]:
     for line in open(path):
         try:
-            tokens  = line.split()
-            samples = tokens[:-1]
-            label   = tokens[-1]
+            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.
     am, bm = min(a[key]), min(b[key])
     ps.append((bm/am, p, key, am, bm))
 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 in ps:
     if p < bonferroni:
         str_ratio = ('%.2gx' if ratio < 1 else '%.3gx') % ratio
         print '%*s\t%6s -> %6s\t%s' % (maxlen, key, humanize(am), humanize(bm), str_ratio)