import numpy as np import pytest import gymnasium as gym from gymnasium.spaces import Box, Dict, Discrete, MultiBinary, Tuple from gymnasium.utils.env_checker import data_equivalence def test_sequence_inheritance(): """The gymnasium Tuple space inherits from abc.Sequences, this test checks all functions work""" spaces = [Discrete(5), Discrete(10), Discrete(5)] tuple_space = Tuple(spaces) assert len(tuple_space) == len(spaces) # Test indexing for i in range(len(tuple_space)): assert tuple_space[i] == spaces[i] # Test iterable for space in tuple_space: assert space in spaces # Test count assert tuple_space.count(Discrete(5)) == 2 assert tuple_space.count(Discrete(6)) == 0 assert tuple_space.count(MultiBinary(2)) == 0 # Test index assert tuple_space.index(Discrete(5)) == 0 assert tuple_space.index(Discrete(5), 1) == 2 # Test errors with pytest.raises(ValueError): tuple_space.index(Discrete(10), 0, 1) with pytest.raises(IndexError): assert tuple_space[4] @pytest.mark.parametrize( "space, seed", [ (Tuple([Discrete(5), Discrete(4)]), None), (Tuple([Discrete(5), Discrete(4)]), 123), (Tuple([Discrete(5), Discrete(4)]), (123, 456)), ( Tuple( (Discrete(5), Tuple((Box(low=0.0, high=1.0, shape=(3,)), Discrete(2)))) ), (123, (456, 789)), ), ( Tuple( ( Discrete(3), Dict(position=Box(low=0.0, high=1.0), velocity=Discrete(2)), ) ), (123, {"position": 456, "velocity": 789}), ), ], ) def test_seeds(space, seed): seeds1 = space.seed(seed) assert isinstance(seeds1, tuple) assert len(seeds1) == len(space) sample1 = space.sample() seeds2 = space.seed(seeds1) sample2 = space.sample() assert data_equivalence(seeds1, seeds2) assert data_equivalence(sample1, sample2) @pytest.mark.parametrize( "space_fn", [ lambda: Tuple(["abc"]), lambda: Tuple([gym.spaces.Box(0, 1), "abc"]), lambda: Tuple("abc"), ], ) def test_bad_space_calls(space_fn): with pytest.raises(AssertionError): space_fn() def test_contains_promotion(): space = gym.spaces.Tuple((gym.spaces.Box(0, 1), gym.spaces.Box(-1, 0, (2,)))) assert ( np.array([0.0], dtype=np.float32), np.array([0.0, 0.0], dtype=np.float32), ) in space space = gym.spaces.Tuple((gym.spaces.Box(0, 1), gym.spaces.Box(-1, 0, (1,)))) assert np.array([[0.0], [0.0]], dtype=np.float32) in space def test_bad_seed(): space = gym.spaces.Tuple((gym.spaces.Box(0, 1), gym.spaces.Box(0, 1))) with pytest.raises( TypeError, match="Expected seed type: list, tuple, int or None, actual type: ", ): space.seed(0.0)