tools/auto_bisect/math_utils_test.py

   1 # Copyright 2014 The Chromium Authors. All rights reserved.
   2 # Use of this source code is governed by a BSD-style license that can be
   3 # found in the LICENSE file.
   4
   5 import math
   6 import unittest
   7
   8 import math_utils
   9
  10
  11 class MathUtilsTest(unittest.TestCase):
  12   """Tests for mathematical utility functions."""
  13
  14   def testTruncatedMean_EmptyList(self):
  15     # TruncatedMean raises an error when passed an empty list.
  16     self.assertRaises(TypeError, math_utils.TruncatedMean, [], 0)
  17
  18   def testTruncatedMean_TruncateTooMuch(self):
  19     # An exception is raised if 50% or more is truncated from both sides.
  20     self.assertRaises(TypeError, math_utils.TruncatedMean, [1, 2, 3], 1.0)
  21     self.assertRaises(
  22         ZeroDivisionError, math_utils.TruncatedMean, [1, 2, 3], 0.5)
  23
  24   def testTruncatedMean_AlwaysKeepsAtLeastTwoValues(self):
  25     # If the length of the input is 1 or 2, nothing is truncated and
  26     # the average is returned.
  27     self.assertEqual(5.0, math_utils.TruncatedMean([5.0], 0.0))
  28     self.assertEqual(5.0, math_utils.TruncatedMean([5.0], 0.25))
  29     self.assertEqual(5.0, math_utils.TruncatedMean([5.0], 0.5))
  30     self.assertEqual(5.5, math_utils.TruncatedMean([5.0, 6.0], 0.0))
  31     self.assertEqual(5.5, math_utils.TruncatedMean([5.0, 6.0], 0.25))
  32     self.assertEqual(5.5, math_utils.TruncatedMean([5.0, 6.0], 0.5))
  33
  34   def testTruncatedMean_Interquartile_NumValuesDivisibleByFour(self):
  35     self.assertEqual(5.0, math_utils.TruncatedMean([1, 4, 6, 100], 0.25))
  36     self.assertEqual(
  37         6.5, math_utils.TruncatedMean([1, 2, 5, 6, 7, 8, 40, 50], 0.25))
  38
  39   def testTruncatedMean_Weighting(self):
  40     # In the list [0, 1, 4, 5, 20, 100], when 25% of the list at the start
  41     # and end are discarded, the part that's left is [1, 4, 5, 20], but
  42     # first and last values are weighted so that they only count for half
  43     # as much. So the truncated mean is (1/2 + 4 + 5 + 20/2) / 5.0.
  44     self.assertEqual(6.5, (0.5 + 4 + 5 + 10) / 3.0)
  45     self.assertEqual(6.5, math_utils.TruncatedMean([0, 1, 4, 5, 20, 100], 0.25))
  46
  47   def testMean_OneValue(self):
  48     self.assertEqual(3.0, math_utils.Mean([3]))
  49
  50   def testMean_ShortList(self):
  51     self.assertEqual(0.5, math_utils.Mean([-3, 0, 1, 4]))
  52
  53   def testMean_CompareAlternateImplementation(self):
  54     """Tests Mean by comparing against an alternate implementation."""
  55     def AlternateMean(values):
  56       return sum(values) / float(len(values))
  57     test_value_lists = [
  58         [1],
  59         [5, 6.5, 1.2, 3],
  60         [-3, 0, 1, 4],
  61         [-3, -1, 0.12, 0.752, 3.33, 8, 16, 32, 439],
  62     ]
  63     for value_list in test_value_lists:
  64       self.assertEqual(AlternateMean(value_list), math_utils.Mean(value_list))
  65
  66   def testRelativeChange_NonZero(self):
  67     # The change is relative to the first value, regardless of which is bigger.
  68     self.assertEqual(0.5, math_utils.RelativeChange(1.0, 1.5))
  69     self.assertEqual(0.5, math_utils.RelativeChange(2.0, 1.0))
  70
  71   def testRelativeChange_FromZero(self):
  72     # If the first number is zero, then the result is not a number.
  73     self.assertEqual(0, math_utils.RelativeChange(0, 0))
  74     self.assertTrue(math.isnan(math_utils.RelativeChange(0, 1)))
  75     self.assertTrue(math.isnan(math_utils.RelativeChange(0, -1)))
  76
  77   def testRelativeChange_Negative(self):
  78     # Note that the return value of RelativeChange is always positive.
  79     self.assertEqual(3.0, math_utils.RelativeChange(-1, 2))
  80     self.assertEqual(3.0, math_utils.RelativeChange(1, -2))
  81     self.assertEqual(1.0, math_utils.RelativeChange(-1, -2))
  82
  83   def testVariance_EmptyList(self):
  84     self.assertRaises(TypeError, math_utils.Variance, [])
  85
  86   def testVariance_OneValue(self):
  87     self.assertEqual(0, math_utils.Variance([0]))
  88     self.assertEqual(0, math_utils.Variance([4.3]))
  89
  90   def testVariance_ShortList(self):
  91     # Population variance is the average of squared deviations from the mean.
  92     # The deviations from the mean in this example are [3.5, 0.5, -0.5, -3.5],
  93     # and the squared deviations are [12.25, 0.25, 0.25, 12.25].
  94     # With sample variance, however, 1 is subtracted from the sample size.
  95     # So the sample variance is sum([12.25, 0.25, 0.25, 12.25]) / 3.0.
  96     self.assertAlmostEqual(8.333333334, sum([12.25, 0.25, 0.25, 12.25]) / 3.0)
  97     self.assertAlmostEqual(8.333333334, math_utils.Variance([-3, 0, 1, 4]))
  98
  99   def testStandardDeviation(self):
 100     # Standard deviation is the square root of variance.
 101     self.assertRaises(TypeError, math_utils.StandardDeviation, [])
 102     self.assertEqual(0.0, math_utils.StandardDeviation([4.3]))
 103     self.assertAlmostEqual(2.88675135, math.sqrt(8.33333333333333))
 104     self.assertAlmostEqual(2.88675135,
 105                            math_utils.StandardDeviation([-3, 0, 1, 4]))
 106
 107   def testStandardError(self):
 108     # Standard error is std. dev. divided by square root of sample size.
 109     self.assertEqual(0.0, math_utils.StandardError([]))
 110     self.assertEqual(0.0, math_utils.StandardError([4.3]))
 111     self.assertAlmostEqual(1.44337567, 2.88675135 / math.sqrt(4))
 112     self.assertAlmostEqual(1.44337567, math_utils.StandardError([-3, 0, 1, 4]))
 113
 114 if __name__ == '__main__':
 115   unittest.main()