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Updates the Env, Wrapper and Vector API documentation (#48)

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Mark Towers
2022-10-12 15:58:01 +01:00
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docs/api/spaces.md
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@@ -1,3 +1,8 @@
---
title: Spaces
---
# Spaces
```{toctree}
@@ -5,37 +10,38 @@
spaces/fundamental
spaces/composite
spaces/utils
spaces/vector_utils
```
```{eval-rst}
.. autoclass:: gymnasium.spaces.Space
```
## General Functions
## Attributes
```{eval-rst}
.. autoproperty:: gymnasium.spaces.space.Space.shape
.. property:: Space.dtype
Return the data type of this space.
```
## Methods
Each space implements the following functions:
```{eval-rst}
.. autofunction:: gymnasium.spaces.Space.sample
.. autofunction:: gymnasium.spaces.Space.contains
.. autoproperty:: gymnasium.spaces.Space.shape
.. property:: gymnasium.spaces.Space.dtype
Return the data type of this space.
.. autofunction:: gymnasium.spaces.Space.seed
.. autofunction:: gymnasium.spaces.Space.to_jsonable
.. autofunction:: gymnasium.spaces.Space.from_jsonable
.. autofunction:: gymnasium.spaces.space.Space.sample
.. autofunction:: gymnasium.spaces.space.Space.contains
.. autofunction:: gymnasium.spaces.space.Space.seed
.. autofunction:: gymnasium.spaces.space.Space.to_jsonable
.. autofunction:: gymnasium.spaces.space.Space.from_jsonable
```
## Fundamental Spaces
Gymnasium has a number of fundamental spaces that are used as building boxes for more complex spaces.
```{eval-rst}
.. currentmodule:: gymnasium.spaces
@@ -48,6 +54,8 @@ Each space implements the following functions:
## Composite Spaces
Often environment spaces require joining fundamental spaces together for vectorised environments, separate agents or readability of the space.
```{eval-rst}
* :py:class:`Dict` - Supports a dictionary of keys and subspaces, used for a fixed number of unordered spaces
* :py:class:`Tuple` - Supports a tuple of subspaces, used for multiple for a fixed number of ordered spaces
@@ -57,9 +65,29 @@ Each space implements the following functions:
## Utils
Gymnasium contains a number of helpful utility functions for flattening and unflattening spaces.
This can be important for passing information to neural networks.
```{eval-rst}
* :py:class:`utils.flatdim` - The number of dimensions the flattened space will contain
* :py:class:`utils.flatten_space` - Flattens a space for which the `flattened` space instances will contain
* :py:class:`utils.flatten` - Flattens an instance of a space that is contained within the flattened version of the space
* :py:class:`utils.unflatten` - The reverse of the `flatten_space` function
```
## Vector Utils
When vectorizing environments, it is necessary to modify the observation and action spaces for new batched spaces sizes.
Therefore, Gymnasium provides a number of additional functions used when using a space with a Vector environment.
```{eval-rst}
.. currentmodule:: gymnasium
* :py:class:`vector.utils.batch_space`
* :py:class:`vector.utils.concatenate`
* :py:class:`vector.utils.iterate`
* :py:class:`vector.utils.create_empty_array`
* :py:class:`vector.utils.create_shared_memory`
* :py:class:`vector.utils.read_from_shared_memory`
* :py:class:`vector.utils.write_to_shared_memory`
```