sinergym.utils.wrappers.CSVLogger
- class sinergym.utils.wrappers.CSVLogger(*args, **kwargs)
- __init__(*args, **kwargs)
Wraps an environment to allow a modular transformation of the
step()andreset()methods.- Parameters:
env – The environment to wrap
Methods
__init__(*args, **kwargs)Wraps an environment to allow a modular transformation of the
step()andreset()methods.class_name()Returns the class name of the wrapper.
close()Recording last episode summary and close env.
Dump all logger data into CSV files.
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 theenvthat can be overwritten to change the returned data.reset([seed, options])Reset the environment.
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 theenvthat can be overwritten to change the returned data.wrapper_spec(**kwargs)Generates a WrapperSpec for the wrappers.
Attributes
action_spaceReturn the
Envaction_spaceunless overwritten then the wrapperaction_spaceis used.metadataReturns the
Envmetadata.np_randomReturns the
Envnp_randomattribute.np_random_seedReturns the base environment's
np_random_seed.observation_spaceReturn the
Envobservation_spaceunless overwritten then the wrapperobservation_spaceis used.render_modeReturns the
Envrender_mode.specReturns the
Envspecattribute with the WrapperSpec if the wrapper inherits from EzPickle.unwrappedReturns the base environment of the wrapper.
- close() None
Recording last episode summary and close env.
- dump_log_files() None
Dump all logger data into CSV files.
- logger = <Logger WRAPPER CSVLogger (INFO)>
- reset(seed: int | None = None, options: Dict[str, Any] | None = None) Tuple[ndarray, Dict[str, Any]]
Reset the environment. Saving current logger episode summary and interaction in CSV files.
Args: seed (Optional[int]): The seed that is used to initialize the environment’s episode (np_random). If value is None, a seed will be chosen from some source of entropy. Defaults to None. options (Optional[Dict[str, Any]]): Additional information to specify how the environment is reset. Defaults to None.
Returns: Tuple[np.ndarray, Dict[str, Any]]: Current observation and info context with additional information.