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 theenv
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 wrapperaction_space
is used.metadata
Returns the
Env
metadata
.np_random
Returns the
Env
np_random
attribute.observation_space
Return the
Env
observation_space
unless overwritten then the wrapperobservation_space
is used.render_mode
Returns the
Env
render_mode
.reward_range
Return the
Env
reward_range
unless overwritten then the wrapperreward_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]]