def save_env_info(env, env_info, episode, env_hist_path):
"""
Saves the environment info dictionary to a csv
args
env (energ_py environment)
env_info (dict) the info dict returned from env.step()
episode (int)
"""
if hasattr(env.observation_space, 'info') and hasattr(
env.state_space, 'info'):
logging.debug('saving env history')
state_info = env.state_space.info
observation_info = env.observation_space.info
output = []
for key, info in env_info.items():
if isinstance(info[0], np.ndarray):
df = pd.DataFrame(np.array(info).reshape(len(info), -1))
# there must be a better way! TODO
if key == 'observation' and observation_info:
df.columns = [
'{}_{}'.format(key, o) for o in observation_info
]
elif key == 'next_observation' and observation_info:
df.columns = [
'{}_{}'.format(key, o) for o in observation_info
]
elif key == 'state' and state_info:
df.columns = ['{}_{}'.format(key, s) for s in state_info]
elif key == 'next_state' and state_info:
df.columns = ['{}_{}'.format(key, s) for s in state_info]
else:
df.columns = [
'{}_{}'.format(key, n) for n in range(df.shape[1])
]
else:
df = pd.DataFrame(info, columns=[key])
output.append(df)
output = pd.concat(output, axis=1)
output.index = env.state_space.episode.index[:-1]
csv_path = os.path.join(env_hist_path, 'ep_{}'.format(episode),
'info.csv')
ensure_dir(csv_path)
output.to_csv(csv_path)
else:
logging.debug('Not saving env history')
def make_paths(experiments_dir, expt_name, run_name):
"""
Creates a dictionary of paths for use with experiments
args
experiments_dir (str) usually energy_py/energy_py/experiments
expt_name (str)
run_name (str)
returns
paths (dict) {name: path}
Folder structure
experiments/configs/expt_name/expt.ini
runs.ini
experiments/results/expt_name/run_name/tensorboard/run_name/rl
/act
/learn
env_histories/ep_1/info.csv
ep_2/info.csv
e..
expt.ini
runs.ini
agent_args.txt
env_args.txt
info.log
debug.log
"""
# rename the join function to make code below eaiser to read
join = os.path.join
config_dir = join(experiments_dir, 'configs', expt_name)
results_dir = join(experiments_dir, 'results', expt_name)
paths = {
# config files
'expt_config': join(config_dir, 'expt.ini'),
'run_configs': join(config_dir, 'runs.ini'),
# tensorboard runs are all in the tensoboard folder
# this is for easy comparision of runs
'tb_rl': join(results_dir, 'tensorboard', run_name, 'rl'),
'tb_act': join(results_dir, 'tensorboard', run_name, 'act'),
'tb_learn': join(results_dir, 'tensorboard', run_name, 'learn'),
# run specific folders are in another folder
'env_histories': join(results_dir, run_name, 'env_histories'),
'debug_log': join(results_dir, run_name, 'debug.log'),
'info_log': join(results_dir, run_name, 'info.log'),
'env_args': join(results_dir, run_name, 'env_args.txt'),
'agent_args': join(results_dir, run_name, 'agent_args.txt'),
'ep_rewards': join(results_dir, run_name, 'ep_rewards.csv')
}
# check that all our paths exist
for key, path in paths.items():
ensure_dir(path)
# copy config files into results directory
copyfile(paths['expt_config'], join(results_dir, run_name, 'expt.ini'))
copyfile(paths['run_configs'], join(results_dir, run_name, 'runs.ini'))
return paths
def make_paths(expt_path, run_name=None):
"""
Creates a dictionary of paths for use with experiments
args
expt_path (str)
run_name (str) optional name for run. Timestamp used if not given
returns
paths (dict) {name: path}
Folder structure
experiments/results/expt_name/run_name/tensoboard/run_name/rl
/act
/learn
env_histories/ep_1/hist.csv
ep_2/hist.csv
e..
common.ini
run_configs.ini
agent_args.txt
env_args.txt
info.log
debug.log
"""
# use a timestamp if no run_name is supplied
if run_name is None:
run_name = str(datetime.datetime.now().strftime('%Y-%m-%d_%H-%M-%S'))
# rename the join function to make code below eaiser to read
join = os.path.join
# run_path is the folder where output from this run will be saved in
run_path = join(expt_path, run_name)
paths = {
'run_path': run_path,
# config files
'common_config': join(expt_path, 'common.ini'),
'run_configs': join(expt_path, 'run_configs.ini'),
# tensorboard runs are all in the tensoboard folder
# this is for easy comparision of run
'tb_rl': join(expt_path, 'tensorboard', run_name, 'rl'),
'tb_act': join(expt_path, 'tensorboard', run_name, 'act'),
'tb_learn': join(expt_path, 'tensorboard', run_name, 'learn'),
'env_histories': join(run_path, 'env_histories'),
# run specific folders are in another folder
'debug_log': join(run_path, 'debug.log'),
'info_log': join(run_path, 'info.log'),
'env_args': join(run_path, 'env_args.txt'),
'agent_args': join(run_path, 'agent_args.txt'),
'ep_rewards': join(run_path, 'ep_rewards.csv')
}
# check that all our paths exist
for key, path in paths.items():
ensure_dir(path)
return paths