Developed by @MohammadRaziei
- gym_prescan : That's the main folder and provided as the environment.
- gym_prescan/envs : There is some codes writhen with python and registered in OpenAI-gym:
- gym_prescan/envs/prescan_env.py: about
prescan-v0
- gym_prescan/envs/prescan_env2.py: about
prescan-without-matlabengine-v0
- gym_prescan/envs/prescan_env.py: about
- gym_prescan/envs/PreScan: It's the PreScan folder.
- gym_prescan/envs : There is some codes writhen with python and registered in OpenAI-gym:
- test : There's some RL-algorithms using stable-baseline
import gym, gym_prescan
env_dict = {
'id': 'prescan-without-matlabengine-v0',
'host': '172.21.217.140',
'verbose': True,
'nget': 152
}
env = gym.make(**env_dict)
for i_episode in range(20):
observation = env.reset()
for t in range(100):
env.render()
print(observation)
action = env.action_space.sample()
observation, reward, done, info = env.step(action)
if done:
print("Episode finished after {} timesteps".format(t+1))
break
env.close()
- 'id' must be 'prescan-v0' or 'prescan-without-matlabengine-v0'
- 'host' can be ignored if you have local run ('host' takes 'localhost' as default.)
- if 'verbose' took True as value, logs are allowed to be printed in terminal.