def test_dim(self):
a = np.array([0, 0, 0, 1])
with self.assertRaises(ValueError) as context:
onehot_reverse(a)
msg = context.exception
self.assertEqual(str(msg), "Input array must have 2 dimensions\n"
"Got predictions.ndim: 1")
def test_dim(self):
a = np.array([0, 0, 0, 1])
with self.assertRaises(ValueError) as context:
onehot_reverse(a)
msg = context.exception
self.assertEqual(
str(msg), "Input array must have 2 dimensions\n"
"Got predictions.ndim: 1")
def test_proba(self):
a = np.array([[0.66, 0.24, 0.10],
[0.66, 0.24, 0.10],
[0.66, 0.24, 0.10],
[0.24, 0.66, 0.10]])
got = onehot_reverse(a)
expect = np.array([0, 0, 0, 1], dtype=np.int32)
self.assertTrue(np.array_equal(got, expect))
def test_defaults(self):
a = np.array([[1., 0., 0., 0.],
[0., 1., 0., 0.],
[0., 0., 0., 1.],
[0., 0., 0., 1.]])
got = onehot_reverse(a)
expect = np.array([0, 1, 3, 3], dtype=np.int32)
self.assertTrue(np.array_equal(got, expect))
def test_proba(self):
a = np.array([[0.66, 0.24, 0.10], [0.66, 0.24, 0.10],
[0.66, 0.24, 0.10], [0.24, 0.66, 0.10]])
got = onehot_reverse(a)
expect = np.array([0, 0, 0, 1], dtype=np.int32)
self.assertTrue(np.array_equal(got, expect))
def test_defaults(self):
a = np.array([[1., 0., 0., 0.], [0., 1., 0., 0.], [0., 0., 0., 1.],
[0., 0., 0., 1.]])
got = onehot_reverse(a)
expect = np.array([0, 1, 3, 3], dtype=np.int32)
self.assertTrue(np.array_equal(got, expect))