def test_median(self): # Returns 2.5 (between 2 and 3). v = metrics.median([1,2,3,4]) self.assertEqual(v, 2.5) # Returns 3 (middle of list). v = metrics.median([1,2,3,4,5]) self.assertEqual(v, 3) # Raises ValueError (empty list). self.assertRaises(ValueError, metrics.median, [])
def test_median(self): # Assert 2.5 (between 2 and 3). v = metrics.median([1,2,3,4]) self.assertEqual(v, 2.5) # Assert 3 (middle of list). v = metrics.median([1,2,3,4,5]) self.assertEqual(v, 3) # Assert that empty list raises ValueError. self.assertRaises(ValueError, metrics.median, []) print("pattern.metrics.median()")
def test_median(self): # Assert 2.5 (between 2 and 3). v = metrics.median([1, 2, 3, 4]) self.assertEqual(v, 2.5) # Assert 3 (middle of list). v = metrics.median([1, 2, 3, 4, 5]) self.assertEqual(v, 3) # Assert that empty list raises ValueError. self.assertRaises(ValueError, metrics.median, []) print("pattern.metrics.median()")
def test_boxplot(self): # Different a,b,c,d quantile parameters produce different results. # By approximation, should return (53, 79.5, 84.5, 92, 98) a = [79,53,82,91,87,98,80,93] v = metrics.boxplot(a) self.assertEqual(v[0], min(a)) self.assertTrue(abs(v[1] - 79.5) <= 0.5) self.assertTrue(abs(v[2] - metrics.median(a)) <= 0.5) self.assertTrue(abs(v[3] - 92.0) <= 0.5) self.assertEqual(v[4], max(a))