def test_train_test_split_ratios():
n_class1 = 4
n_class2 = 8
transform_type = "Train/Test Split"
time_series = [TimeSeries(*sample_values(), target='class1')
for i in range(n_class1)]
time_series += [TimeSeries(*sample_values(), target='class2')
for i in range(n_class2)]
outputs = transformation.train_test_split(
time_series, test_size=0.5, train_size=0.5)
npt.assert_equal(len(outputs[1]), len(time_series) / 2)
npt.assert_equal(len(outputs[0]), len(time_series) / 2)
def test_train_test_split_basecase():
npt.assert_equal(transformation.train_test_split([]), ([], []))
