def test_combine_other_empty(self):
s1 = Statistics()
s2 = Statistics()
s1.add(1.0)
s3 = s1.combine(s2)
self.assertEqual(1, len(s3))
self.assertEqual(1.0, s3.mean)
def test_add_zero_once(self):
s = Statistics()
s.add(0.0)
self.assertEqual(1, len(s))
self.assertEqual(0.0, s.mean)
self.assertEqual(0.0, s.var)
self.assertEqual(0.0, s.std)
self.assertEqual(0.0, s.min)
self.assertEqual(0.0, s.max)
def test_add_multiple(self):
s = Statistics()
s.add(0.0)
s.add(1.0)
s.add(2.0)
self.assertEqual(3, len(s))
self.assertEqual(1.0, s.mean)
# note that np.var returns the variance, not sample variance
sample_variance = 3.0 / 2.0 * np.var([0.0, 1.0, 2.0])
self.assertEqual(1.0, sample_variance)
self.assertEqual(sample_variance, s.var)
self.assertEqual(np.sqrt(sample_variance), s.std)
self.assertEqual(0.0, s.min)
self.assertEqual(2.0, s.max)
def test_combine(self):
s1 = Statistics()
for x in np.arange(0, 11):
s1.add(x)
s2 = Statistics()
for x in np.arange(11, 21):
s2.add(x)
s3 = Statistics()
for x in np.arange(0, 21):
s3.add(x)
sc = s1.combine(s2)
self.assertEqual(len(s3), len(sc))
self.assertEqual(s3.mean, sc.mean)
self.assertEqual(s3.var, sc.var)
self.assertEqual(s3.std, sc.std)
self.assertEqual(s3.min, sc.min)
self.assertEqual(s3.max, sc.max)
def test_combine_both_empty(self):
s1 = Statistics()
s2 = Statistics()
s3 = s1.combine(s2)
self.assertEqual(0, len(s3))