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import pytest
import numpy as np
from dizoo.classic_control.acrobot.envs import AcroBotEnv
@pytest.mark.envtest
class TestAcrobotEnv:
def test_naive(self):
env = AcroBotEnv({})
env.seed(314, dynamic_seed=False)
assert env._seed == 314
obs = env.reset()
assert obs.shape == (6, )
for _ in range(5):
env.reset()
np.random.seed(314)
print('=' * 60)
for i in range(10):
# Both ``env.random_action()``, and utilizing ``np.random`` as well as action space,
# can generate legal random action.
if i < 5:
random_action = np.array([env.action_space.sample()])
else:
random_action = env.random_action()
timestep = env.step(random_action)
print(timestep)
assert isinstance(timestep.obs, np.ndarray)
assert isinstance(timestep.done, bool)
assert timestep.obs.shape == (6, )
assert timestep.reward.shape == (1, )
assert timestep.reward >= env.reward_space.low
assert timestep.reward <= env.reward_space.high
print(env.observation_space, env.action_space, env.reward_space)
env.close()
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