Gymnasium/gym/wrappers/test_transform_observation.py

import pytest

import numpy as np

import gym
from gym.wrappers import TransformObservation


@pytest.mark.parametrize("env_id", ["CartPole-v1", "Pendulum-v0"])
def test_transform_observation(env_id):
    affine_transform = lambda x: 3 * x + 2
    env = gym.make(env_id)
    wrapped_env = TransformObservation(gym.make(env_id), lambda obs: affine_transform(obs))

    env.seed(0)
    wrapped_env.seed(0)

    obs = env.reset()
    wrapped_obs = wrapped_env.reset()
    assert np.allclose(wrapped_obs, affine_transform(obs))

    action = env.action_space.sample()
    obs, reward, done, _ = env.step(action)
    wrapped_obs, wrapped_reward, wrapped_done, _ = wrapped_env.step(action)
    assert np.allclose(wrapped_obs, affine_transform(obs))
    assert np.allclose(wrapped_reward, reward)
    assert wrapped_done == done