sinergym.utils.wrappers.LoggerWrapper

class sinergym.utils.wrappers.LoggerWrapper(env: Any, flag: bool = True)

__init__(env: Any, flag: bool = True)

CSVLogger to log interactions with environment.

Parameters

• env (Any) – Original Gym environment.

• flag (bool, optional) – State of logger (activate or deactivate). Defaults to True.

Methods

__init__(env[, flag])	CSVLogger to log interactions with environment.
activate_logger()	Activate logger if its flag False.
class_name()
close()	Close env.
compute_reward(achieved_goal, desired_goal, info)
deactivate_logger()	Deactivate logger if its flag True.
render([mode])	Renders the environment.
reset()	Resets the environment.
seed([seed])	Sets the seed for this env's random number generator(s).
step(action)	Step the environment.

Attributes

action_space
metadata
observation_space
reward_range
spec
unwrapped	Completely unwrap this env.

activate_logger() → None

Activate logger if its flag False.

close() → None

Close env. Recording last episode summary.

deactivate_logger() → None

Deactivate logger if its flag True.

reset() → numpy.ndarray

Resets the environment. Recording episode summary in logger

Returns

First observation given

Return type

np.ndarray

step(action: Union[int, numpy.ndarray]) → Tuple[numpy.ndarray, float, bool, Dict[str, Any]]

Step the environment. Logging new information

Parameters

action (Union[int, np.ndarray]) – Action executed in step

Returns

Tuple with next observation, reward, bool for terminated episode and dict with extra information.

Return type

Tuple[np.ndarray, float, bool, Dict[str, Any]]