Add wrappers to website

docs/_scripts/gen_envs_display.py

@@ -10,7 +10,7 @@
 def create_grid_cell(env_id):
     env_name = env_id.split("-")[-2]
     return f"""
-    <a href="{env_name.lower()}">
+    <a href="environments/{env_name.lower()}">
         <div class="env-grid__cell">
             <div class="cell__image-container">
                 <img src="/_static/environments/{env_name.lower()}.jpg">

docs/conf.py

@@ -16,11 +16,12 @@
 
 # -- Project information -----------------------------------------------------
 import os
+import time
 
 import miniworld
 
 project = "Miniworld"
-copyright = "2023 Farama Foundation"
+copyright = f"{time.localtime().tm_year} Farama Foundation"
 author = "Farama Foundation"
 
 # The full version, including alpha/beta/rc tags
@@ -34,7 +35,6 @@
 # ones.
 extensions = [
     "sphinx.ext.napoleon",
-    "sphinx.ext.doctest",
     "sphinx.ext.autodoc",
     "sphinx.ext.githubpages",
     "sphinx.ext.viewcode",

docs/content/wrappers.md

@@ -0,0 +1,9 @@
+# Wrapper
+
+Miniworld include several built in wrapper available to researchers in `miniworld.wrappers`
+
+```{eval-rst}
+.. autoclass:: miniworld.wrappers.PyTorchObsWrapper
+.. autoclass:: miniworld.wrappers.GreyscaleWrapper
+.. autoclass:: miniworld.wrappers.StochasticActionWrapper
+```

docs/index.md

@@ -10,6 +10,7 @@ lastpage:
 
 content/design
 environments
+content/wrappers
 content/create_env
 content/troubleshooting
 content/installation

miniworld/envs/collecthealth.py

@@ -30,21 +30,20 @@ class CollectHealth(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +2 for each time step
     -100 for dying
 
     ## Arguments
 
+    * `size`: size of the room
+
     ```python
-    CollectHealth(size=16)
+    env = gymnasium.make("Miniworld-CollectHealth-v0", size=16)
     ```
-
-    `size`: size of the room
-
     """
 
     def __init__(self, size=16, **kwargs):

miniworld/envs/fourrooms.py

@@ -22,16 +22,16 @@ class FourRooms(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when red box reached and zero otherwise.
 
     ## Arguments
 
     ```python
-    env = gym.make("MiniWorld-FourRooms-v0")
+    env = gymnasium.make("MiniWorld-FourRooms-v0")
     ```
 
     """

miniworld/envs/hallway.py

@@ -24,19 +24,21 @@ class Hallway(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when red box reached
 
     ## Arguments
 
+    * `length`: length of the entire space
+
     ```python
-    Hallway(length=12)
+    env = gymnasium.make("Miniworld-Hallway-v0", length=12)
     ```
 
-    `length`: length of the entire space
+
 
     """
 

miniworld/envs/maze.py

@@ -26,24 +26,23 @@ class Maze(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when red box reached and zero otherwise.
 
     ## Arguments
 
     ```python
-    env = gym.make("MiniWorld-Maze-v0")
+    env = gymnasium.make("MiniWorld-Maze-v0")
     # or
-    env = gym.make("MiniWorld-MazeS2-v0")
+    env = gymnasium.make("MiniWorld-MazeS2-v0")
     # or
-    env = gym.make("MiniWorld-MazeS3-v0")
+    env = gymnasium.make("MiniWorld-MazeS3-v0")
     # or
-    env = gym.make("MiniWorld-MazeS3Fast-v0")
+    env = gymnasium.make("MiniWorld-MazeS3Fast-v0")
     ```
-
     """
 
     def __init__(

miniworld/envs/oneroom.py

@@ -26,22 +26,21 @@ class OneRoom(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when red box reached and zero otherwise.
 
     ## Arguments
 
     ```python
-    env = gym.make("MiniWorld-OneRoom-v0")
+    env = gymnasium.make("MiniWorld-OneRoom-v0")
     # or
-    env = gym.make("MiniWorld-OneRoomS6-v0")
+    env = gymnasium.make("MiniWorld-OneRoomS6-v0")
     # or
-    env = gym.make("MiniWorld-OneRoomS6Fast-v0")
+    env = gymnasium.make("MiniWorld-OneRoomS6Fast-v0")
     ```
-
     """
 
     def __init__(self, size=10, max_episode_steps=180, **kwargs):

miniworld/envs/pickupobjects.py

@@ -24,22 +24,20 @@ class PickupObjects(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +1 when agent picked up object
 
     ## Arguments
 
+    * `size`: size of world
+    * `num_objs`: number of objects
+
     ```python
-    PickupObjects(size=12, num_objs=5)
+    env = gymnasium.make("Miniworld-PickupObjects-v0", size=12, num_objs=5)
     ```
-
-    `size`: size of world
-
-    `num_objs`: number of objects
-
     """
 
     def __init__(self, size=12, num_objs=5, **kwargs):

miniworld/envs/putnext.py

@@ -28,19 +28,21 @@ class PutNext(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when red box is next to yellow box
 
     ## Arguments
 
+    * `size`: size of world
+
     ```python
-    PutNext(size=12)
+    env = gymnasium.make("Miniworld-PutNext-v0", size=12)
     ```
 
-    `size`: size of world
+
 
     """
 

miniworld/envs/roomobjects.py

@@ -30,20 +30,19 @@ class RoomObjects(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     None
 
     ## Arguments
 
+    * `size`: size of world
+
     ```python
-    RoomObjects(size=16)
+    env = gymnasium.make("Miniworld-RoomObjects-v0", size=16)
     ```
-
-    `size`: size of world
-
     """
 
     def __init__(self, size=10, **kwargs):

miniworld/envs/sidewalk.py

@@ -25,18 +25,17 @@ class Sidewalk(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when object reached
 
     ## Arguments
 
     ```python
-    env = gym.make("MiniWorld-Sidewalk-v0")
+    env = gymnasium.make("MiniWorld-Sidewalk-v0")
     ```
-
     """
 
     def __init__(self, **kwargs):

miniworld/envs/sign.py

@@ -52,27 +52,23 @@ class Sign(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +1 for touching the object where the color matches the sign and the shape matches the goal
     -1 for touching any other object
 
     ## Arguments
 
+    * `size`:  size of the square room.
+    * `max_episode_steps`: number of steps before the episode ends.
+    * `color_index`: specifies whether the sign says blue (0), green (1), or red (2).
+    * `goal`: specifies box (0) or key (1).
+
     ```python
-    Sign(size=10, max_episode_steps=20, color_index=0, goal=0)
+    env = gymnasium.make("Miniworld-Sign-v0", size=10, max_episode_steps=20, color_index=0, goal=0)
     ```
-
-    `size`:  size of the square room.
-
-    `max_episode_steps`: number of steps before the episode ends.
-
-    `color_index`: specifies whether the sign says blue (0), green (1), or red (2).
-
-    `goal`: specifies box (0) or key (1).
-
     """
 
     def __init__(self, size=10, max_episode_steps=20, color_index=0, goal=0, **kwargs):

miniworld/envs/threerooms.py

@@ -25,18 +25,17 @@ class ThreeRooms(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     None
 
     ## Arguments
 
     ```python
-    env = gym.make("MiniWorld-ThreeRooms-v0")
+    env = gymnasium.make("MiniWorld-ThreeRooms-v0")
     ```
-
     """
 
     def __init__(self, **kwargs):

miniworld/envs/tmaze.py

@@ -27,18 +27,18 @@ class TMaze(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when box reached and zero otherwise.
 
     ## Arguments
 
     ```python
-    env = gym.make("MiniWorld-TMazeLeft-v0")
+    env = gymnasium.make("MiniWorld-TMazeLeft-v0")
     # or
-    env = gym.make("MiniWorld-TMazeRight-v0")
+    env = gymnasium.make("MiniWorld-TMazeRight-v0")
     ```
     """
 

miniworld/envs/wallgap.py

@@ -25,16 +25,16 @@ class WallGap(MiniWorldEnv, utils.EzPickle):
     ## Observation Space
 
     The observation space is an `ndarray` with shape `(obs_height, obs_width, 3)`
-    representing a RGB image of what the agents sees.
+    representing an RGB image of what the agents see.
 
-    ## Rewards:
+    ## Rewards
 
     +(1 - 0.2 * (step_count / max_episode_steps)) when box reached
 
     ## Arguments
 
     ```python
-    env = gym.make("MiniWorld-WallGap-v0")
+    env = gymnasium.make("MiniWorld-WallGap-v0")
     ```
     """