sinergym.utils.wrappers.LoggerWrapper
- class sinergym.utils.wrappers.LoggerWrapper(env: ~typing.Any, logger_class: ~typing.Callable = <class 'sinergym.utils.logger.CSVLogger'>, monitor_header: ~typing.List[str] | None = None, progress_header: ~typing.List[str] | None = None, flag: bool = True)
- __init__(env: ~typing.Any, logger_class: ~typing.Callable = <class 'sinergym.utils.logger.CSVLogger'>, monitor_header: ~typing.List[str] | None = None, progress_header: ~typing.List[str] | None = None, flag: bool = True)
CSVLogger to log interactions with environment.
- Parameters:
env (Any) – Original Gym environment.
logger_class (CSVLogger) – CSV Logger class to use to log all information.
monitor_header – Header for monitor.csv in each episode. Default is None (default format).
progress_header – Header for progress.csv in whole simulation. Default is None (default format).
flag (bool, optional) – State of logger (activate or deactivate). Defaults to True.
Methods
__init__
(env[, logger_class, ...])CSVLogger to log interactions with environment.
Activate logger if its flag False.
class_name
()Returns the class name of the wrapper.
close
()Recording last episode summary and close env.
Deactivate logger if its flag True.
get_wrapper_attr
(name)Gets an attribute from the wrapper and lower environments if name doesn't exist in this object.
render
()Uses the
render()
of theenv
that can be overwritten to change the returned data.reset
([seed, options])Reset the environment.
step
(action)Sends action to the environment.
wrapper_spec
(**kwargs)Generates a WrapperSpec for the wrappers.
Attributes
action_space
Return the
Env
action_space
unless overwritten then the wrapperaction_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 wrapperobservation_space
is used.render_mode
Returns the
Env
render_mode
.reward_range
Return the
Env
reward_range
unless overwritten then the wrapperreward_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.
- activate_logger() None
Activate logger if its flag False.
- close() None
Recording last episode summary and close env.
- deactivate_logger() None
Deactivate logger if its flag True.
- reset(seed: int | None = None, options: Dict[str, Any] | None = None) Tuple[ndarray, Dict[str, Any]]
Reset the environment. Recording episode summary in logger
- Parameters:
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:
Current observation and info context with additional information.
- Return type:
Tuple[np.ndarray,Dict[str,Any]]
- step(action: int | ndarray) Tuple[ndarray, float, bool, bool, Dict[str, Any]]
Sends action to the environment. Logging new information in monitor.csv.
- Parameters:
action (Union[int, float, np.integer, np.ndarray, List[Any], Tuple[Any]]) – Action selected by the agent.
- Returns:
Observation for next timestep, reward obtained, Whether the episode has ended or not, Whether episode has been truncated or not, and a dictionary with extra information
- Return type:
Tuple[np.ndarray, float, bool, Dict[str, Any]]