import numpy as np
from . import convert_box

COLOR_RED_LIST = ["full", "R", "G", "B"]
GRAYSCALE_WEIGHTS = np.array([0.299, 0.587, 0.114], dtype=np.float32)


def check_param(space, color_reduction):
    assert isinstance(
        color_reduction, str
    ), "color_reduction must be str. It is {}".format(color_reduction)
    assert color_reduction in COLOR_RED_LIST, "color_reduction must be in {}".format(
        COLOR_RED_LIST
    )
    assert (
        len(space.low.shape) == 3 and space.low.shape[2] == 3
    ), "To apply color_reduction, shape must be a 3d image with last dimention of size 3. Shape is {}".format(
        (space.low.shape)
    )


def change_obs_space(obs_space, param):
    return convert_box(lambda obs: change_observation(obs, obs_space, param), obs_space)


def change_observation(obs, obs_space, color_reduction):
    if color_reduction == "R":
        obs = obs[:, :, 0]
    if color_reduction == "G":
        obs = obs[:, :, 1]
    if color_reduction == "B":
        obs = obs[:, :, 2]
    if color_reduction == "full":
        obs = (obs.astype(np.float32) @ GRAYSCALE_WEIGHTS).astype(np.uint8)
    return obs
