sinergym.utils.wrappers.DiscretizeEnv

class sinergym.utils.wrappers.DiscretizeEnv(env: EplusEnv, discrete_space: Discrete | MultiDiscrete | MultiBinary, action_mapping: Callable[[int | List[int]], float | List[float]])

Wrapper to discretize an action space.

__init__(env: EplusEnv, discrete_space: Discrete | MultiDiscrete | MultiBinary, action_mapping: Callable[[int | List[int]], float | List[float]])

Wrapper for Discretize action space.

Parameters:

env (EplusEnv) – Original environment.
discrete_space (Union[gym.spaces.Discrete, gym.spaces.MultiDiscrete, gym.spaces.MultiBinary]) – Discrete Space.
action_mapping (Callable[[Union[int, List[int]]], Union[float, List[float]]]) – Function with action as argument, its output must match with original env action space, otherwise an error will be raised.

Methods

`__init__`(env, discrete_space, action_mapping)	Wrapper for Discretize action space.
`action`(action)	Returns a modified action before `env.step()` is called.
`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.
`render`()	Uses the `render()` of the `env` that can be overwritten to change the returned data.
`reset`(*[, seed, options])	Uses the `reset()` of the `env` that can be overwritten to change the returned data.
`step`(action)	Runs the `env` `env.step()` using the modified `action` from `self.action()`.
`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.
`is_discrete`
`logger`
`metadata`	Returns the `Env` `metadata`.
`np_random`	Returns the `Env` `np_random` attribute.
`observation_space`	Return the `Env` `observation_space` unless overwritten then the wrapper `observation_space` is used.
`render_mode`	Returns the `Env` `render_mode`.
`reward_range`	Return the `Env` `reward_range` unless overwritten then the wrapper `reward_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.

action(action: int | List[int]) → List[int]

Returns a modified action before env.step() is called.

Parameters:: action – The original step() actions
Returns:: The modified actions

property is_discrete: bool

logger = <Logger WRAPPER DiscretizeEnv (INFO)>