sinergym.utils.wrappers.PreviousObservationWrapper

class sinergym.utils.wrappers.PreviousObservationWrapper(env: Any, previous_variables: List[str])

Wrapper to add observation values from previous timestep to current environment observation

__init__(env: Any, previous_variables: List[str])

Constructor for the observation wrapper.

Parameters:

env – Environment to be wrapped.

Methods

__init__(env, previous_variables)

Constructor for the observation wrapper.

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.

observation(obs)

Add previous observation to the current one

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().

set_wrapper_attr(name, value)

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

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.

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.

observation(obs: ndarray) ndarray

Add previous observation to the current one

Parameters:

obs (np.ndarray) – Original observation.

Returns:

observation with

Return type:

np.ndarray