import gym
import numpy as np
import pytest
from gym import spaces

from stable_baselines3.common.vec_env import DummyVecEnv, VecCheckNan


class NanAndInfEnv(gym.Env):
    """Custom Environment that raised NaNs and Infs"""

    metadata = {"render.modes": ["human"]}

    def __init__(self):
        super(NanAndInfEnv, self).__init__()
        self.action_space = spaces.Box(low=-np.inf, high=np.inf, shape=(1,), dtype=np.float64)
        self.observation_space = spaces.Box(low=-np.inf, high=np.inf, shape=(1,), dtype=np.float64)

    @staticmethod
    def step(action):
        if np.all(np.array(action) > 0):
            obs = float("NaN")
        elif np.all(np.array(action) < 0):
            obs = float("inf")
        else:
            obs = 0
        return [obs], 0.0, False, {}

    @staticmethod
    def reset():
        return [0.0]

    def render(self, mode="human", close=False):
        pass


def test_check_nan():
    """Test VecCheckNan Object"""

    env = DummyVecEnv([NanAndInfEnv])
    env = VecCheckNan(env, raise_exception=True)

    env.step([[0]])

    with pytest.raises(ValueError):
        env.step([[float("NaN")]])

    with pytest.raises(ValueError):
        env.step([[float("inf")]])

    with pytest.raises(ValueError):
        env.step([[-1]])

    with pytest.raises(ValueError):
        env.step([[1]])

    env.step(np.array([[0, 1], [0, 1]]))

    env.reset()