Add some statistics to the monsoon profile run

tools/perf/metrics/statistics_unittest.py

 # Copyright 2013 The Chromium Authors. All rights reserved.

[tonyg, 2014/03/12 15:28:38]

This file needs to move along with statistics.py.

Also, please add some basic tests for the new methods you've added. Be sure to
include the edge cases like 0, empty, etc.

 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 import unittest
 import random
 
-from metrics import statistics
+from telemetry.util import statistics
 
 
 def Relax(samples, iterations=10):
   """Lloyd relaxation in 1D.
 
   Keeps the position of the first and last sample.
   """
   for _ in xrange(0, iterations):
     voronoi_boundaries = []
     for i in xrange(1, len(samples)):
@@ skipping 132 matching lines @@
     # When the given percentage is very low, the lowest value is given.
     self.assertEquals(1, statistics.Percentile([2, 1, 5, 4, 3], 5))
     # When the given percentage is very high, the highest value is given.
     self.assertEquals(5, statistics.Percentile([5, 2, 4, 1, 3], 95))
     # Linear interpolation between closest ranks is used. Using the example
     # from <http://en.wikipedia.org/wiki/Percentile>:
     self.assertEquals(27.5, statistics.Percentile([15, 20, 35, 40, 50], 40))
 
   def testArithmeticMean(self):
     # The ArithmeticMean function computes the simple average.
-    self.assertAlmostEquals(40/3.0, statistics.ArithmeticMean([10, 10, 20], 3))
-    self.assertAlmostEquals(15.0, statistics.ArithmeticMean([10, 20], 2))
-    # Both lists of values or single values can be given for either argument.
-    self.assertAlmostEquals(40/3.0, statistics.ArithmeticMean(40, [1, 1, 1]))
+    self.assertAlmostEquals(40/3.0, statistics.ArithmeticMean([10, 10, 20]))
+    self.assertAlmostEquals(15.0, statistics.ArithmeticMean([10, 20]))
     # If the 'count' is zero, then zero is returned.
-    self.assertEquals(0, statistics.ArithmeticMean(4.0, 0))
-    self.assertEquals(0, statistics.ArithmeticMean(4.0, []))
+    self.assertEquals(0, statistics.ArithmeticMean([]))
 
   def testDurationsDiscrepancy(self):
     durations = []
     d = statistics.DurationsDiscrepancy(durations)
     self.assertEquals(d, 1.0)
 
     durations = [4]
     d = statistics.DurationsDiscrepancy(durations)
     self.assertEquals(d, 1.0)
 
     durations_a = [1, 1, 1, 1, 1]
     durations_b = [1, 1, 2, 1, 1]
     durations_c = [1, 2, 1, 2, 1]
 
     d_a = statistics.DurationsDiscrepancy(durations_a)
     d_b = statistics.DurationsDiscrepancy(durations_b)
     d_c = statistics.DurationsDiscrepancy(durations_c)
 
     self.assertTrue(d_a < d_b < d_c)