"""
Classic cart-pole system implemented by Rich Sutton et al.
Copied from http://incompleteideas.net/sutton/book/code/pole.c
permalink: https://perma.cc/C9ZM-652R

Originally from OpenAI's gym environment
continuous version adapted by Edan Meyer
"""

import math
import gym
from gym import spaces, logger
from gym.utils import seeding
import numpy as np

class CartPoleEnv(gym.Env):
    metadata = {
        'render.modes': ['human', 'rgb_array'],
        'video.frames_per_second' : 50
    }

    def __init__(self):
        self.min_action = -1.0
        self.max_action = 1.0
        self.gravity = 9.8
        self.masscart = 1.0
        self.masspole = 0.1
        self.total_mass = (self.masspole + self.masscart)
        self.length = 0.5 # actually half the pole's length
        self.polemass_length = (self.masspole * self.length)
        self.force_mag = 10.0
        self.tau = 0.02  # seconds between state updates
        self.kinematics_integrator = 'euler'

        # Angle at which to fail the episode
        self.theta_threshold_radians = 12 * 2 * math.pi / 360
        self.x_threshold = 2.4

        # Angle limit set to 2 * theta_threshold_radians so failing observation is still within bounds
        high = np.array([
            self.x_threshold * 2,
            np.finfo(np.float32).max,
            self.theta_threshold_radians * 2,
            np.finfo(np.float32).max])
        
        self.action_space = spaces.Box(low=self.min_action, high=self.max_action,
                                       shape=(1,), dtype=np.float32)
        self.observation_space = spaces.Box(-high, high, dtype=np.float32)

        self.seed()
        self.viewer = None
        self.state = None

        self.steps_beyond_done = None

    def seed(self, seed=None):
        self.np_random, seed = seeding.np_random(seed)
        return [seed]

    def step(self, action):
        state = self.state
        x, x_dot, theta, theta_dot = state
        force = self.force_mag * action
        costheta = math.cos(theta)
        sintheta = math.sin(theta)
        temp = (force + self.polemass_length * theta_dot * theta_dot * sintheta) / self.total_mass
        thetaacc = (self.gravity * sintheta - costheta* temp) / (self.length * (4.0/3.0 - self.masspole * costheta * costheta / self.total_mass))
        xacc  = temp - self.polemass_length * thetaacc * costheta / self.total_mass
        if self.kinematics_integrator == 'euler':
            x  = x + self.tau * x_dot
            x_dot = x_dot + self.tau * xacc
            theta = theta + self.tau * theta_dot
            theta_dot = theta_dot + self.tau * thetaacc
        else: # semi-implicit euler
            x_dot = x_dot + self.tau * xacc
            x  = x + self.tau * x_dot
            theta_dot = theta_dot + self.tau * thetaacc
            theta = theta + self.tau * theta_dot
        self.state = (x,x_dot,theta,theta_dot)
        done =  x < -self.x_threshold \
                or x > self.x_threshold \
                or theta < -self.theta_threshold_radians \
                or theta > self.theta_threshold_radians
        done = bool(done)

        if not done:
            reward = 1.0
        elif self.steps_beyond_done is None:
            # Pole just fell!
            self.steps_beyond_done = 0
            reward = 1.0
        else:
            if self.steps_beyond_done == 0:
                logger.warn("You are calling 'step()' even though this environment has already returned done = True. You should always call 'reset()' once you receive 'done = True' -- any further steps are undefined behavior.")
            self.steps_beyond_done += 1
            reward = 0.0

        return np.array(self.state), reward, done, {}

    def reset(self):
        self.state = self.np_random.uniform(low=-0.05, high=0.05, size=(4,))
        self.steps_beyond_done = None
        return np.array(self.state)

    def render(self, mode='human'):
        screen_width = 600
        screen_height = 400

        world_width = self.x_threshold*2
        scale = screen_width/world_width
        carty = 100 # TOP OF CART
        polewidth = 10.0
        polelen = scale * (2 * self.length)
        cartwidth = 50.0
        cartheight = 30.0

        if self.viewer is None:
            from gym.envs.classic_control import rendering
            self.viewer = rendering.Viewer(screen_width, screen_height)
            l,r,t,b = -cartwidth/2, cartwidth/2, cartheight/2, -cartheight/2
            axleoffset =cartheight/4.0
            cart = rendering.FilledPolygon([(l,b), (l,t), (r,t), (r,b)])
            self.carttrans = rendering.Transform()
            cart.add_attr(self.carttrans)
            self.viewer.add_geom(cart)
            l,r,t,b = -polewidth/2,polewidth/2,polelen-polewidth/2,-polewidth/2
            pole = rendering.FilledPolygon([(l,b), (l,t), (r,t), (r,b)])
            pole.set_color(.8,.6,.4)
            self.poletrans = rendering.Transform(translation=(0, axleoffset))
            pole.add_attr(self.poletrans)
            pole.add_attr(self.carttrans)
            self.viewer.add_geom(pole)
            self.axle = rendering.make_circle(polewidth/2)
            self.axle.add_attr(self.poletrans)
            self.axle.add_attr(self.carttrans)
            self.axle.set_color(.5,.5,.8)
            self.viewer.add_geom(self.axle)
            self.track = rendering.Line((0,carty), (screen_width,carty))
            self.track.set_color(0,0,0)
            self.viewer.add_geom(self.track)

            self._pole_geom = pole

        if self.state is None: return None

        # Edit the pole polygon vertex
        pole = self._pole_geom
        l,r,t,b = -polewidth/2,polewidth/2,polelen-polewidth/2,-polewidth/2
        pole.v = [(l,b), (l,t), (r,t), (r,b)]

        x = self.state
        cartx = x[0]*scale+screen_width/2.0 # MIDDLE OF CART
        self.carttrans.set_translation(cartx, carty)
        self.poletrans.set_rotation(-x[2])

        return self.viewer.render(return_rgb_array = mode=='rgb_array')

    def close(self):
        if self.viewer:
            self.viewer.close()
            self.viewer = None
