sinergym.utils.wrappers.NormalizeObservation

class sinergym.utils.wrappers.NormalizeObservation(env: Any, ranges: Dict[str, Sequence[Any]], variables: List[str] | None = None)
__init__(env: Any, ranges: Dict[str, Sequence[Any]], variables: List[str] | None = None)

Observations normalized to range [0, 1].

Parameters:
  • env (Any) – Original Sinergym environment.

  • ranges (Dict[str, Sequence[Any]]) – Observation variables ranges to apply normalization (rely on environment).

  • variables (Optional[List[str]]) – List of variables you want to normalize. If it is None, all environment variables are included.

Methods

__init__(env, ranges[, variables])

Observations normalized to range [0, 1].

class_name()

Returns the class name of the wrapper.

close()

Closes the wrapper and env.

get_unwrapped_obs()

Get last environment observation without normalization.

get_wrapper_attr(name)

Gets an attribute from the wrapper and lower environments if name doesn't exist in this object.

observation(obs)

Applies normalization to observation.

render()

Uses the render() of the env that can be overwritten to change the returned data.

reset(*[, seed, options])

Modifies the env after calling reset(), returning a modified observation using self.observation().

step(action)

Modifies the env after calling step() using self.observation() on the returned observations.

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.

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.

get_unwrapped_obs() ndarray | None

Get last environment observation without normalization.

Returns:

Last original observation. If it is the first observation, this value is None.

Return type:

Optional[np.ndarray]

observation(obs: ndarray) ndarray

Applies normalization to observation.

Parameters:

obs (np.ndarray) – Original observation.

Returns:

Normalized observation.

Return type:

np.ndarray