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try_env.py
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try_env.py
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import logging
import gymnasium as gym
import numpy as np
import sinergym
from sinergym.utils.logger import TerminalLogger
from sinergym.utils.wrappers import (CSVLogger, LoggerWrapper, NormalizeAction,
NormalizeObservation)
# Logger
terminal_logger = TerminalLogger()
logger = terminal_logger.getLogger(
name='MAIN',
level=logging.INFO
)
# Create environment and apply wrappers for normalization and logging
env = gym.make('Eplus-5zone-hot-continuous-stochastic-v1')
env = NormalizeAction(env)
env = NormalizeObservation(env)
env = LoggerWrapper(env)
env = CSVLogger(env)
# Execute 3 episodes
for i in range(3):
# Reset the environment to start a new episode
obs, info = env.reset()
rewards = []
truncated = terminated = False
current_month = 0
while not (terminated or truncated):
# Random action selection
a = env.action_space.sample()
# Perform action and receive env information
obs, reward, terminated, truncated, info = env.step(a)
rewards.append(reward)
# Display results every simulated month
if info['month'] != current_month:
current_month = info['month']
logger.info('Reward: {}'.format(sum(rewards)))
logger.info('Info: {}'.format(info))
logger.info('Episode {} - Mean reward: {} - Cumulative Reward: {}'.format(i,
np.mean(rewards), sum(rewards)))
env.close()