def test_theil_multiple_vectors(self):
sample = torch.Tensor(np.array([[0, 0, 0, 0], [1, 1, 1, 1]]))
self.assertTrue(torch.all(torch.eq(theil(sample), torch.Tensor([0., 0.]))))
def test_theil(self):
sample = torch.Tensor(np.array([[0, 0, 0, 0, 0, 1]]))
self.assertTrue(abs(theil(sample).item() - (1/2) * ((5/3) * np.log(5/3) + (1/3) * np.log(1/3))) < 1e-7)
def test_random_theil(self):
num_classes = 5
sample_size = 10
sample = torch.Tensor([np.random.choice(np.arange(num_classes), size=sample_size)])
self.assertGreaterEqual(theil(sample), 0.)
self.assertLessEqual(theil(sample), 1.)
def test_equal_mix_theil(self):
sample = torch.Tensor(np.array([[0, 0, 0, 1, 1, 1]]))
self.assertEqual(theil(sample), 0.)
def test_ones_theil(self):
sample = torch.Tensor(np.array([[1, 1, 1, 1, 1]]))
self.assertEqual(theil(sample), 0.)
def test_zeros_theil(self):
sample = torch.Tensor(np.array([[0, 0, 0, 0, 0]]))
self.assertEqual(theil(sample), 0.)