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))
