sinergym.utils.wrappers.ReduceObservationWrapper

class sinergym.utils.wrappers.ReduceObservationWrapper(env: Env, obs_reduction: List[str])

__init__(env: Env, obs_reduction: List[str])

Wrapper to reduce the observation space of the environment. These variables removed from the space are included in the info dictionary. This way they are recordable but not used in DRL process.

Parameters:

• env (Env) – Original environment.

• obs_reduction (List[str]) – List of observation variables to be removed.

Methods

__init__(env, obs_reduction)	Wrapper to reduce the observation space of the environment.
class_name()	Returns the class name of the wrapper.
close()	Closes the wrapper and env.
get_wrapper_attr(name)	Gets an attribute from the wrapper and lower environments if name doesn't exist in this object.
render()	Uses the render() of the env that can be overwritten to change the returned data.
reset([seed, options])	Sends action to the environment.
step(action)	Sends action to the environment.
wrapper_spec(**kwargs)	Generates a WrapperSpec for the wrappers.

Attributes

action_space	Return the Env action_space unless overwritten then the wrapper action_space is used.
logger
metadata	Returns the Env metadata.
np_random	Returns the Env np_random attribute.
observation_space	Return the Env observation_space unless overwritten then the wrapper observation_space is used.
render_mode	Returns the Env render_mode.
reward_range	Return the Env reward_range unless overwritten then the wrapper reward_range is used.
spec	Returns the Env spec attribute with the WrapperSpec if the wrapper inherits from EzPickle.
unwrapped	Returns the base environment of the wrapper.

logger = <Logger WRAPPER ReduceObservationWrapper (INFO)>

reset(seed: int | None = None, options: Dict[str, Any] | None = None) → Tuple[ndarray, Dict[str, Any]]

Sends action to the environment. Separating removed variables from observation values and adding it to info dict

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

Sends action to the environment. Separating removed variables from observation values and adding it to info dict.

Parameters:

action (Union[int, float, np.integer, np.ndarray, List[Any], Tuple[Any]]) – Action selected by the agent.

Returns:

Observation for next timestep, reward obtained, Whether the episode has ended or not, Whether episode has been truncated or not, and a dictionary with extra information

Return type:

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