sinergym.utils.wrappers.BaseLoggerWrapper

class sinergym.utils.wrappers.BaseLoggerWrapper(*args, **kwargs)

__init__(*args, **kwargs)

Wraps an environment to allow a modular transformation of the step() and reset() methods.

Parameters:: env – The environment to wrap

Methods

`__init__`(args, *kwargs)	Wraps an environment to allow a modular transformation of the `step()` and `reset()` methods.
`calculate_custom_metrics`(obs, action, ...)	Calculate custom metrics from current interaction (or passed using self.data_logger attributes)
`class_name`()	Returns the class name of the wrapper.
`close`()	Close the environment and save normalization calibration.
`get_episode_summary`()	Return data summary for the logger. This method should be implemented in the child classes.
`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])	Reset the environment and the information logged.
`set_wrapper_attr`(name, value, *[, force])	Sets an attribute on this wrapper or lower environment if name is already defined.
`step`(action)	Uses the `step()` of the `env` that can be overwritten to change the returned data.
`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.

abstractmethod calculate_custom_metrics(obs: ndarray, action: ndarray, reward: SupportsFloat, info: Dict[str, Any], terminated: bool, truncated: bool)

Calculate custom metrics from current interaction (or passed using self.data_logger attributes)

Parameters:

obs (np.ndarray) – Observation from environment.
action (np.ndarray) – Action taken in environment.
reward (float) – Reward received from environment.
info (Dict[str, Any]) – Information from environment.
terminated (bool) – Flag to indicate if episode is terminated.
truncated (bool) – Flag to indicate if episode is truncated.

close(): Close the environment and save normalization calibration.

abstractmethod get_episode_summary() → Dict[str, float]

Return data summary for the logger. This method should be implemented in the child classes.: This method determines the data summary of episodes in Sinergym environments.

Returns:: Data summary.
Return type:: Dict[str, float]

reset(seed: int | None = None, options: Dict[str, Any] | None = None) → Tuple[ndarray, Dict[str, Any]]: Reset the environment and the information logged.

step(action: ndarray) → Tuple[ndarray, SupportsFloat, bool, bool, Dict[str, Any]]: Uses the step() of the env that can be overwritten to change the returned data.