def test_empty_test(self):
dataset = Dataset_Counts(state_shape=[2],
nb_actions=3,
count_param=0.2)
dataset.add(*transitions[0])
dataset.add(*transitions[1])
dataset_train, dataset_test = dataset.train_validation_split(
test_size=0.5)
s_train, a_train, p_train, r_train, s2_train, t_train, _, _, _ = dataset_train._get_transition(
0)
s_test, a_test, p_test, r_test, s2_test, t_test, _, _, _ = dataset_test._get_transition(
0)
if a_train == transitions[0].a:
trans_train = transitions[0]
trans_test = transitions[1]
else:
trans_train = transitions[1]
trans_test = transitions[0]
assert_sequence_almost_equal(self, s_train, trans_train.s)
self.assertEqual(a_train, trans_train.a)
assert_sequence_almost_equal(self, p_train, trans_train.p)
self.assertAlmostEqual(r_train, trans_train.r)
self.assertEqual(t_train, trans_train.t)
assert_sequence_almost_equal(self, s_test, trans_test.s)
self.assertEqual(a_test, trans_test.a)
assert_sequence_almost_equal(self, p_test, trans_test.p)
self.assertAlmostEqual(r_test, trans_test.r)
self.assertEqual(t_test, trans_test.t)
class TestSplittingDataset(TestCase):
def setUp(self):
self.dataset = Dataset_Counts(state_shape=[2],
nb_actions=3,
count_param=0.2)
self.dataset_size = 100
for i in np.random.randint(0, len(transitions), self.dataset_size):
self.dataset.add(*transitions[i])
def test_empty_test(self):
dataset_train, dataset_test = self.dataset.train_validation_split(
test_size=0)
self.assertEqual(dataset_test.size, 0)
self.assertEqual(dataset_train.size, self.dataset_size)
def test_default(self):
dataset_train, dataset_test = self.dataset.train_validation_split()
self.assertEqual(dataset_test.size, 20)
self.assertEqual(dataset_train.size, 80)
def test_empty_train(self):
dataset_train, dataset_test = self.dataset.train_validation_split(1)
self.assertEqual(dataset_test.size, self.dataset_size)
self.assertEqual(dataset_train.size, 0)
def test_original_data_set_does_not_change(self):
random_ind = np.random.randint(0, self.dataset_size)
s, a, p1, r, s2, t, c, p2, c1 = self.dataset._get_transition(
random_ind)
_, _ = self.dataset.train_validation_split(np.random.rand())
new_s, new_a, new_p1, new_r, new_s2, new_t, new_c, new_p2, new_c1 = self.dataset._get_transition(
random_ind)
assert_sequence_almost_equal(self, new_s, s)
self.assertEqual(new_a, a)
assert_sequence_almost_equal(self, new_p1, p1)
self.assertAlmostEqual(new_r, r)
assert_sequence_almost_equal(self, new_s2, s2)
self.assertEqual(new_t, t)
assert_sequence_almost_equal(self, new_c, c)
assert_sequence_almost_equal(self, new_p2, p2)
self.assertAlmostEqual(new_c1, c1)