"""Test suite for RescaleAction wrapper."""

import numpy as np

from gymnasium.spaces import Box
from gymnasium.wrappers import RescaleAction
from tests.testing_env import GenericTestEnv
from tests.wrappers.utils import record_action_step


def test_rescale_action_wrapper():
    """Test that the action is rescale within a min / max bound."""
    env = GenericTestEnv(
        step_func=record_action_step,
        action_space=Box(
            np.array([0, 1, -np.inf, 5, -np.inf], dtype=np.float32),
            np.array([1, 3, np.inf, np.inf, 7], dtype=np.float32),
        ),
    )
    wrapped_env = RescaleAction(
        env,
        min_action=np.array([-5, 0, -np.inf, -1, -np.inf], dtype=np.float32),
        max_action=np.array([5, 1.0, np.inf, np.inf, 4], dtype=np.float32),
    )
    assert wrapped_env.action_space == Box(
        np.array([-5, 0, -np.inf, -1, -np.inf], dtype=np.float32),
        np.array([5, 1, np.inf, np.inf, 4], dtype=np.float32),
    )

    for sample_action, expected_action in (
        (
            np.array([0.0, 0.5, 7.0, -1.0, -23.0], dtype=np.float32),
            np.array([0.5, 2.0, 7.0, 5.0, -20.0], dtype=np.float32),
        ),
        (
            np.array([-5.0, 0.0, -4.0, 0.0, -3.0], dtype=np.float32),
            np.array([0.0, 1.0, -4.0, 6.0, 0.0], dtype=np.float32),
        ),
        (
            np.array([5.0, 1.0, 0.0, 1.0, 4.0], dtype=np.float32),
            np.array([1.0, 3.0, 0.0, 7.0, 7.0], dtype=np.float32),
        ),
    ):
        assert sample_action in wrapped_env.action_space
        assert expected_action in env.action_space

        _, _, _, _, info = wrapped_env.step(sample_action)
        assert np.all(info["action"] == expected_action)