sinergym.utils.wrappers.MultiObsWrapper

class sinergym.utils.wrappers.MultiObsWrapper(env: Env, n: int = 5, flatten: bool = True)
__init__(env: Env, n: int = 5, flatten: bool = True) None

Stack of observations.

Parameters:
  • env (Env) – Original Gym environment.

  • n (int, optional) – Number of observations to be stacked. Defaults to 5.

  • flatten (bool, optional) – Whether or not flat the observation vector. Defaults to True.

Methods

__init__(env[, n, flatten])

Stack of observations.

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.

has_wrapper_attr(name)

Checks if the given attribute is within the wrapper or its environment.

render()

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

reset([seed, options])

Resets the environment.

set_wrapper_attr(name, value)

Sets an attribute on this wrapper or lower environment if name is already defined.

step(action)

Performs the action in the new 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.

np_random_seed

Returns the base environment's np_random_seed.

observation_space

Return the Env observation_space unless overwritten then the wrapper observation_space is used.

render_mode

Returns the Env render_mode.

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

Resets the environment.

Returns:

Stacked previous observations.

Return type:

np.ndarray

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

Performs the action in the new environment.

Parameters:

action (Union[int, np.ndarray]) – Action to be executed in environment.

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]]