def test_normalize():
# can you pass a Space instance to the Space constructor?
space = Space([(0.0, 1.0), (-5, 5), ("a", "b", "c"),
(1.0, 5.0, "log-uniform"), ("e", "f")])
space.set_transformer("normalize")
X = [[0.0, -5, "a", 1.0, "e"]]
Xt = np.zeros((1, 5))
assert_array_equal(space.transform(X), Xt)
assert_array_equal(space.inverse_transform(Xt), X)
assert_array_equal(space.inverse_transform(space.transform(X)), X)
def test_normalize_types():
# can you pass a Space instance to the Space constructor?
space = Space([(0.0, 1.0), Integer(-5, 5, dtype=int), (True, False)])
space.set_transformer("normalize")
X = [[0.0, -5, False]]
Xt = np.zeros((1, 3))
assert_array_equal(space.transform(X), Xt)
assert_array_equal(space.inverse_transform(Xt), X)
assert_array_equal(space.inverse_transform(space.transform(X)), X)
assert isinstance(space.inverse_transform(Xt)[0][0], float)
assert isinstance(space.inverse_transform(Xt)[0][1], int)
assert isinstance(space.inverse_transform(Xt)[0][2], (np.bool_, bool))
def test_set_get_transformer():
# can you pass a Space instance to the Space constructor?
space = Space([(0.0, 1.0), (-5, 5), ("a", "b", "c"),
(1.0, 5.0, "log-uniform"), ("e", "f")])
transformer = space.get_transformer()
assert_array_equal(
["identity", "identity", "onehot", "identity", "onehot"], transformer)
space.set_transformer("normalize")
transformer = space.get_transformer()
assert_array_equal(["normalize"] * 5, transformer)
space.set_transformer(transformer)
assert_array_equal(transformer, space.get_transformer())
space.set_transformer_by_type("label", Categorical)
assert space.dimensions[2].transform(["a"]) == [0]