import json  # note: ujson fails this test due to float equality
from copy import copy

import numpy as np
import pytest

from gym.spaces import Tuple, Box, Discrete, MultiDiscrete, MultiBinary, Dict


@pytest.mark.parametrize("space", [
    Discrete(3),
    Tuple([Discrete(5), Discrete(10)]),
    Tuple([Discrete(5), Box(low=np.array([0, 0]), high=np.array([1, 5]), dtype=np.float32)]),
    Tuple((Discrete(5), Discrete(2), Discrete(2))),
    MultiDiscrete([2, 2, 100]),
    Dict({"position": Discrete(5),
          "velocity": Box(low=np.array([0, 0]), high=np.array([1, 5]), dtype=np.float32)}),
])
def test_roundtripping(space):
    sample_1 = space.sample()
    sample_2 = space.sample()
    assert space.contains(sample_1)
    assert space.contains(sample_2)
    json_rep = space.to_jsonable([sample_1, sample_2])

    json_roundtripped = json.loads(json.dumps(json_rep))

    samples_after_roundtrip = space.from_jsonable(json_roundtripped)
    sample_1_prime, sample_2_prime = samples_after_roundtrip

    s1 = space.to_jsonable([sample_1])
    s1p = space.to_jsonable([sample_1_prime])
    s2 = space.to_jsonable([sample_2])
    s2p = space.to_jsonable([sample_2_prime])
    assert s1 == s1p, "Expected {} to equal {}".format(s1, s1p)
    assert s2 == s2p, "Expected {} to equal {}".format(s2, s2p)


@pytest.mark.parametrize("space", [
    Discrete(3),
    Box(low=np.array([-10, 0]), high=np.array([10, 10]), dtype=np.float32),
    Tuple([Discrete(5), Discrete(10)]),
    Tuple([Discrete(5), Box(low=np.array([0, 0]), high=np.array([1, 5]), dtype=np.float32)]),
    Tuple((Discrete(5), Discrete(2), Discrete(2))),
    MultiDiscrete([2, 2, 100]),
    MultiBinary(6),
    Dict({"position": Discrete(5),
          "velocity": Box(low=np.array([0, 0]), high=np.array([1, 5]), dtype=np.float32)}),
])
def test_equality(space):
    space1 = space
    space2 = copy(space)
    assert space1 == space2, "Expected {} to equal {}".format(space1, space2)


@pytest.mark.parametrize("spaces", [
    (Discrete(3), Discrete(4)),
    (MultiDiscrete([2, 2, 100]), MultiDiscrete([2, 2, 8])),
    (MultiBinary(8), MultiBinary(7)),
    (Box(low=np.array([-10, 0]), high=np.array([10, 10]), dtype=np.float32),
     Box(low=np.array([-10, 0]), high=np.array([10, 9]), dtype=np.float32)),
    (Tuple([Discrete(5), Discrete(10)]), Tuple([Discrete(1), Discrete(10)])),
    (Dict({"position": Discrete(5)}), Dict({"position": Discrete(4)})),
    (Dict({"position": Discrete(5)}), Dict({"speed": Discrete(5)})),
])
def test_inequality(spaces):
    space1, space2 = spaces
    assert space1 != space2, "Expected {} != {}".format(space1, space2)


@pytest.mark.parametrize("space", [
    Discrete(5),
    Box(low=0, high=255, shape=(2,), dtype='uint8'),
])
def test_sample(space):
    space.seed(0)
    n_trials = 100
    samples = np.array([space.sample() for _ in range(n_trials)])
    if isinstance(space, Box):
        expected_mean = (space.high + space.low) / 2
    elif isinstance(space, Discrete):
        expected_mean = space.n / 2
    else:
        raise NotImplementedError
    np.testing.assert_allclose(expected_mean, samples.mean(), atol=3.0 * samples.std())