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iPADS / TwoDimEnv.py

YvesP

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3c74b8c about 1 year ago

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	import gymnasium as gym
	from params import *


	class TwoDimEnv(gym.Env):
	"""
	Custom 2D-Environment that follows gym interface.
	This is a simple 2D-env where the agent must go to the 0,0 point,
	it can go right or straight in a continuous action space, but cannot change speed
	"""
	def __init__(self):
	super(TwoDimEnv, self).__init__()

	# agent cannot be further away from target than space_limits
	self.space_limits = SPACE_LIMITS

	# Initialize the agent position
	rho_init = np.random.random() * SPACE_LIMITS
	theta_init = np.random.random() * 2 * PI - PI
	self.rho_init, self.theta_init, self.z_init = rho_init, theta_init, Z_INIT
	self.agent_pos = rho_init * np.exp(1j * theta_init)
	self.agent_z = Z_INIT

	# agent abs speed is constant, may change of direction on the plane, but doesnt change in the z-axis
	self.agent_speed = SPEED_RHO * np.exp(1j*SPEED_ANGLE)
	self.agent_speed_z = SPEED_Z
	self.agent_max_angle = MAX_ANGLE

	#
	self.agent_previous_pos = self.agent_pos


	def reset(self, training=True, rho_init=RHO_INIT, theta_init=THETA_INIT, z_init=Z_INIT):
	"""
	:input: TwoDimEnv
	:return: TwoDimEnv
	"""
	# Initialize the agent position and speed
	self.agent_pos = rho_init * np.exp(1j * theta_init)
	self.agent_speed = SPEED_RHO * np.exp(1j * SPEED_ANGLE)
	self.agent_z = z_init

	# init step index
	self.step_index = 0

	return self.get_obs()

	def step(self, action):
	'''
	the Gym step
	:param action:
	:return:
	'''

	self.step_index += 1

	# Agent changes of direction according to its action: action[0] in [-1; 1]
	self.agent_speed = np.exp(1j self.agent_max_angle * action[0], dtype=complex)
	self.agent_previous_pos = self.agent_pos
	self.agent_pos += self.agent_speed
	self.agent_z -= self.agent_speed_z

	# Are we done?
	done = bool(self.agent_z <= 0)

	# get normalized obs
	obs = self.get_obs()

	return obs, 0., done, {}

	def render(self, **kwargs):
	pass

	def close(self):
	pass

	# calculates normalized obs
	def get_obs(self):
	'''
	normalises the observation
	:return: normalised observation
	'''
	agent_dist = np.abs(self.agent_pos) / self.space_limits
	agent_angle = np.angle(self.agent_pos) / (2 * PI)
	if agent_angle < 0:
	agent_angle += 1
	agent_speed = np.angle(self.agent_speed) / (2 * PI)
	if agent_speed < 0:
	agent_speed += 1
	agent_z = (Z_INIT-self.agent_z) / Z_INIT
	obs = np.array([agent_dist, agent_angle, agent_speed, agent_z]).astype(np.float32)
	return obs