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Unified Diff: tools/auto_bisect/math_utils_test.py

Issue 736573002: Add unit tests for functions in math_utils.py (Closed) Base URL: https://chromium.googlesource.com/chromium/src.git@master
Patch Set: Updated an incorrect comment. Created 6 years, 1 month ago
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Index: tools/auto_bisect/math_utils_test.py
diff --git a/tools/auto_bisect/math_utils_test.py b/tools/auto_bisect/math_utils_test.py
index 4d19881f55887d1b41ef531e0f7cb7e49d128b3b..ab85b0be6bbf027a1c6574cd334d0d533ae25e7b 100644
--- a/tools/auto_bisect/math_utils_test.py
+++ b/tools/auto_bisect/math_utils_test.py
@@ -11,52 +11,105 @@ import math_utils
class MathUtilsTest(unittest.TestCase):
"""Tests for mathematical utility functions."""
- def testTruncatedMeanRaisesError(self):
- """TruncatedMean should raise an error when passed an empty list."""
- with self.assertRaises(TypeError):
- math_utils.TruncatedMean([], 0)
+ def testTruncatedMean_EmptyList(self):
+ # TruncatedMean raises an error when passed an empty list.
+ self.assertRaises(TypeError, math_utils.TruncatedMean, [], 0)
- def testMeanSingleNum(self):
- """Tests the Mean function with a single number."""
+ def testTruncatedMean_TruncateTooMuch(self):
+ # An exception is raised if 50% or more is truncated from both sides.
+ self.assertRaises(TypeError, math_utils.TruncatedMean, [1, 2, 3], 1.0)
+ self.assertRaises(
+ ZeroDivisionError, math_utils.TruncatedMean, [1, 2, 3], 0.5)
+
+ def testTruncatedMean_AlwaysKeepsAtLeastTwoValues(self):
+ # If the length of the input is 1 or 2, nothing is truncated and
+ # the average is returned.
+ self.assertEqual(5.0, math_utils.TruncatedMean([5.0], 0.0))
+ self.assertEqual(5.0, math_utils.TruncatedMean([5.0], 0.25))
+ self.assertEqual(5.0, math_utils.TruncatedMean([5.0], 0.5))
+ self.assertEqual(5.5, math_utils.TruncatedMean([5.0, 6.0], 0.0))
+ self.assertEqual(5.5, math_utils.TruncatedMean([5.0, 6.0], 0.25))
+ self.assertEqual(5.5, math_utils.TruncatedMean([5.0, 6.0], 0.5))
+
+ def testTruncatedMean_Interquartile_NumValuesDivisibleByFour(self):
+ self.assertEqual(5.0, math_utils.TruncatedMean([1, 4, 6, 100], 0.25))
+ self.assertEqual(
+ 6.5, math_utils.TruncatedMean([1, 2, 5, 6, 7, 8, 40, 50], 0.25))
+
+ def testTruncatedMean_Weighting(self):
+ # In the list [0, 1, 4, 5, 20, 100], when 25% of the list at the start
+ # and end are discarded, the part that's left is [1, 4, 5, 20], but
+ # first and last values are weighted so that they only count for half
+ # as much. So the truncated mean is (1/2 + 4 + 5 + 20/2) / 5.0.
+ self.assertEqual(6.5, (0.5 + 4 + 5 + 10) / 3.0)
+ self.assertEqual(6.5, math_utils.TruncatedMean([0, 1, 4, 5, 20, 100], 0.25))
+
+ def testMean_OneValue(self):
self.assertEqual(3.0, math_utils.Mean([3]))
- def testMeanShortList(self):
- """Tests the Mean function with a short list."""
+ def testMean_ShortList(self):
self.assertEqual(0.5, math_utils.Mean([-3, 0, 1, 4]))
- def testMeanCompareAlternateImplementation(self):
+ def testMean_CompareAlternateImplementation(self):
"""Tests Mean by comparing against an alternate implementation."""
- def AlternateMeanFunction(values):
- """Simple arithmetic mean function."""
+ def AlternateMean(values):
return sum(values) / float(len(values))
- test_values_lists = [[1], [5, 6.5, 1.2, 3], [-3, 0, 1, 4],
- [-3, -1, 0.12, 0.752, 3.33, 8, 16, 32, 439]]
- for values in test_values_lists:
- self.assertEqual(
- AlternateMeanFunction(values),
- math_utils.Mean(values))
-
- def testRelativeChange(self):
- """Tests the common cases for calculating relative change."""
+ test_value_lists = [
+ [1],
+ [5, 6.5, 1.2, 3],
+ [-3, 0, 1, 4],
+ [-3, -1, 0.12, 0.752, 3.33, 8, 16, 32, 439],
+ ]
+ for value_list in test_value_lists:
+ self.assertEqual(AlternateMean(value_list), math_utils.Mean(value_list))
+
+ def testRelativeChange_NonZero(self):
# The change is relative to the first value, regardless of which is bigger.
self.assertEqual(0.5, math_utils.RelativeChange(1.0, 1.5))
self.assertEqual(0.5, math_utils.RelativeChange(2.0, 1.0))
- def testRelativeChangeFromZero(self):
- """Tests what happens when relative change from zero is calculated."""
+ def testRelativeChange_FromZero(self):
# If the first number is zero, then the result is not a number.
self.assertEqual(0, math_utils.RelativeChange(0, 0))
- self.assertTrue(
- math.isnan(math_utils.RelativeChange(0, 1)))
- self.assertTrue(
- math.isnan(math_utils.RelativeChange(0, -1)))
+ self.assertTrue(math.isnan(math_utils.RelativeChange(0, 1)))
+ self.assertTrue(math.isnan(math_utils.RelativeChange(0, -1)))
- def testRelativeChangeWithNegatives(self):
- """Tests that relative change given is always positive."""
+ def testRelativeChange_Negative(self):
+ # Note that the return value of RelativeChange is always positive.
self.assertEqual(3.0, math_utils.RelativeChange(-1, 2))
self.assertEqual(3.0, math_utils.RelativeChange(1, -2))
self.assertEqual(1.0, math_utils.RelativeChange(-1, -2))
+ def testVariance_EmptyList(self):
+ self.assertRaises(TypeError, math_utils.Variance, [])
+
+ def testVariance_OneValue(self):
+ self.assertEqual(0, math_utils.Variance([0]))
+ self.assertEqual(0, math_utils.Variance([4.3]))
+
+ def testVariance_ShortList(self):
+ # Population variance is the average of squared deviations from the mean.
+ # The deviations from the mean in this example are [3.5, 0.5, -0.5, -3.5],
+ # and the squared deviations are [12.25, 0.25, 0.25, 12.25].
+ # With sample variance, however, 1 is subtracted from the sample size.
+ # So the sample variance is sum([12.25, 0.25, 0.25, 12.25]) / 3.0.
+ self.assertAlmostEqual(8.333333334, sum([12.25, 0.25, 0.25, 12.25]) / 3.0)
+ self.assertAlmostEqual(8.333333334, math_utils.Variance([-3, 0, 1, 4]))
+
+ def testStandardDeviation(self):
+ # Standard deviation is the square root of variance.
+ self.assertRaises(TypeError, math_utils.StandardDeviation, [])
+ self.assertEqual(0.0, math_utils.StandardDeviation([4.3]))
+ self.assertAlmostEqual(2.88675135, math.sqrt(8.33333333333333))
+ self.assertAlmostEqual(2.88675135,
+ math_utils.StandardDeviation([-3, 0, 1, 4]))
+
+ def testStandardError(self):
+ # Standard error is std. dev. divided by square root of sample size.
+ self.assertEqual(0.0, math_utils.StandardError([]))
+ self.assertEqual(0.0, math_utils.StandardError([4.3]))
+ self.assertAlmostEqual(1.44337567, 2.88675135 / math.sqrt(4))
+ self.assertAlmostEqual(1.44337567, math_utils.StandardError([-3, 0, 1, 4]))
if __name__ == '__main__':
unittest.main()
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