[CalendarServer-changes] [6100] CalendarServer/trunk/contrib/performance

[source_changes at macosforge.org]

Revision: 6100
          http://trac.macosforge.org/projects/calendarserver/changeset/6100
Author:   exarkun at twistedmatrix.com
Date:     2010-08-17 17:35:07 -0700 (Tue, 17 Aug 2010)
Log Message:
-----------
simple student's t test, applicable to the urlopen times at least

Added Paths:
-----------
    CalendarServer/trunk/contrib/performance/compare
    CalendarServer/trunk/contrib/performance/compare.py

Added: CalendarServer/trunk/contrib/performance/compare
===================================================================
--- CalendarServer/trunk/contrib/performance/compare	                        (rev 0)
+++ CalendarServer/trunk/contrib/performance/compare	2010-08-18 00:35:07 UTC (rev 6100)
@@ -0,0 +1,3 @@
+#!/usr/bin/python
+from compare import main
+main()


Property changes on: CalendarServer/trunk/contrib/performance/compare
___________________________________________________________________
Added: svn:executable
   + *

Added: CalendarServer/trunk/contrib/performance/compare.py
===================================================================
--- CalendarServer/trunk/contrib/performance/compare.py	                        (rev 0)
+++ CalendarServer/trunk/contrib/performance/compare.py	2010-08-18 00:35:07 UTC (rev 6100)
@@ -0,0 +1,41 @@
+import sys, pickle
+
+import stats
+
+try:
+    from scipy.stats import ttest_1samp
+except ImportError:
+    from math import pi
+    from ctypes import CDLL, c_double
+    libc = CDLL('libc.dylib')
+    gamma = libc.gamma
+    gamma.argtypes = [c_double]
+    gamma.restype = c_double
+    def ttest_1samp(a, popmean):
+        t = (stats.mean(a) - popmean) / (stats.stddev(a) / len(a) ** 0.5)
+        v = len(a) - 1.0
+        p = gamma((v + 1) / 2) / ((v * pi) ** 0.5 * gamma(v / 2)) * (1 + t ** 2 / v) ** (-(v + 1) / 2)
+        return (
+            [t, None], 
+            [p, None])
+
+
+def select(statistics, benchmark, parameter, statistic):
+    for stat, samples in statistics[benchmark][int(parameter)].iteritems():
+        if stat.name == statistic:
+            return (stat, samples)
+    raise ValueError("Unknown statistic %r" % (statistic,))
+
+
+def main():
+    first = pickle.load(file(sys.argv[1]))
+    second = pickle.load(file(sys.argv[2]))
+
+    stat, first = select(first, *sys.argv[3:])
+    stat, second = select(second, *sys.argv[3:])
+
+    if ttest_1samp(second, stats.mean(first))[1][0] < 0.05:
+        print 'same' # failed to reject the null hypothesis
+    else:
+        print 'different' # rejected the null hypothesis
+
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