Add EnvFactory.ClassicControl typings, Improve README (#2)

* add classic control factory

* build in all branches

* remove regex

* add readme data

Author: cric96

.github/workflows/build.yml

@@ -2,7 +2,6 @@ name: Build
 
 on:
   push:
-    branches: [ main ]
 jobs:
   Build:
     runs-on: ubuntu-latest

README.md

@@ -1,14 +1,105 @@
 # ScalaPy Gym Facade
-A ScalaPy Facade for OpenAI Gym!
+A [ScalaPy](https://scalapy.dev/) Facade for OpenAI Gym!
 ## Quality
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 ## CI status
-![Build](https://github.com/cric96/scalapy-gym/actions/workflows/build.yml/badge.svg)
+| Main  | Develop  |
+|---|---|
+| ![Build](https://github.com/cric96/scalapy-gym/actions/workflows/build.yml/badge.svg)  |  ![Build](https://github.com/cric96/scalapy-gym/actions/workflows/build.yml/badge.svg?branch=develop) |
 ## Links
 [![Scala Doc](https://img.shields.io/badge/-Scala%20doc-red?logo=scala)](https://cric96.github.io/scalapy-gym/latest/api/)
-[![Maven Central](https://maven-badges.herokuapp.com/maven-central/io.github.cric96/scalapy-gym_2.13/badge.svg)](https://maven-badges.herokuapp.com/maven-central/io.github.cric96/scalapy-gym_2.13/badge.svg)
+
+## What this project supports
+The main aim of this facade consist in using the basic environment describe in [OpenAI Gym](http://gym.openai.com/envs/#classic_control).
+
+Currently, there is no interesting in creating environment Scala side. The workflow idea is:
+- develop your reinforcement learning in Scala,
+- create a functional facade to interact with ScalaPy Gym
+- test your algorithms in Open AI baselines and share your results!
+
+## Installation
+First of all, you should setup your ScalaPy project correctly, please refer to [this](https://scalapy.dev/docs/) documentation:
+
+Then, you should add this library as dependecy in your sbt file:
+```
+libraryDependencies += "io.github.cric96" %% "scalapy-gym" % "<x.y.z>"
+```
+The latest version is: [![Maven Central](https://maven-badges.herokuapp.com/maven-central/io.github.cric96/scalapy-gym_2.13/badge.svg)](https://maven-badges.herokuapp.com/maven-central/io.github.cric96/scalapy-gym_2.13/badge.svg)
+
+Then you should install OpenAI dependencies. I suggest you to use `pyenv`. BTW, the main dependencies are:
+- gym
+- scipy
+
+Look to [requirements.txt](/requirements.txt).
+
+To use other environment (`box2d` or `MuJuCo` and `Atari`), please refer to [OpenAI Documentation](http://gym.openai.com/docs/).
+
+## How to use
+
+This library try to make environments type safe. So you add to define:
+- action type
+- observation type
+- action space type
+- observation space type
+
+For example, for [FrozenLake](http://gym.openai.com/envs/FrozenLake-v0/) you should write:
+```scala
+val env = Gym.make[Int, Int, Discrete, Discrete]("FrozenLake-v0")
+```
+
+If you do not care about the action and observation type, you can type:
+```scala
+val env = Gym.unsafe("FrozenLake-v0")
+```
+
+A simple loop that advance in the simulation could be:
+```scala
+import io.github.cric96.gym.Gym
+val env = Gym.unsafe("FrozenLake-v0") // or EnvFactory.ToyText.frozenLakeV0
+env.reset()
+val observations = (0 to 1000)
+        .tapEach(_ => env.render)
+        .map(env.step(env.actionSpace.sample()))
+env.close()
+```
+
+The python counterpart is:
+```python
+
+val env = Gym.unsafe("FrozenLake-v0")
+env.reset()
+for _ in range(1000):
+  env.render()
+  env.step(env.action_space.sample()) # take a random action
+env.close()
+```
+
+As you can see, the experience is very similar :)
+
+Some environments, has already the correct typing (Looks to [EnvFactory](/src/main/scala/gym/envs/EnvFactory.scala))
+
+### Typings
+- ToyTest
+    - [x] FrozenLake
+    - [x] FrozenLake
+    - [x] GuessingGame
+    - [x] HotterColder
+    - [x] nChain
+    - [x] Roulette
+- ClassicControl
+    - [x] Acrobot
+    - [x] CartPole
+    - [x] MountainCar
+    - [x] MountainCarContinuous
+    - [x] Pendulum
+- [ ] Atari
+- [ ] Box2D
+- [ ] MuJoCo
+- [ ] Robotics
+- [ ] Algorithms
+
 
 ## Example
 - [Basic Q-Learning implementation](https://github.com/cric96/scala-rl-examples/blob/main/qlearning.ipynb)

src/main/scala/gym/envs/EnvFactory.scala

@@ -1,12 +1,12 @@
 package io.github.cric96
 package gym.envs
 
-import gym.Gym
+import gym.{ExternalType, Gym}
 import gym.core.Env
 import gym.spaces.{Box, Discrete, Tuple}
 
 /** a facade for some of the standard open ai environments */
-object EnvFactory {
+object EnvFactory extends App {
 
   object ToyText {
 
@@ -22,5 +22,21 @@ object EnvFactory {
     def rouletteV0(): Env[Int, Int, Discrete, Discrete] = Gym.make[Int, Int, Discrete, Discrete]("Roulette-v0")
   }
 
-  object ClassicControl
+  object ClassicControl {
+
+    def acrobotV1(): Env[Int, ExternalType.NumpyArray, Discrete, Box] =
+      Gym.make[Int, ExternalType.NumpyArray, Discrete, Box]("Acrobot-v1")
+
+    def cartPoleV1(): Env[Int, ExternalType.NumpyArray, Discrete, Box] =
+      Gym.make[Int, ExternalType.NumpyArray, Discrete, Box]("CartPole-v1")
+
+    def mountainCarV0(): Env[Int, ExternalType.NumpyArray, Discrete, Box] =
+      Gym.make[Int, ExternalType.NumpyArray, Discrete, Box]("MountainCar-v0")
+
+    def mountainCarContinuousV0(): Env[ExternalType.NumpyArray, ExternalType.NumpyArray, Box, Box] =
+      Gym.make[ExternalType.NumpyArray, ExternalType.NumpyArray, Box, Box]("MountainCarContinuous-v0")
+
+    def pendulumV0(): Env[ExternalType.NumpyArray, ExternalType.NumpyArray, Box, Box] =
+      Gym.make[ExternalType.NumpyArray, ExternalType.NumpyArray, Box, Box]("Pendulum-v0")
+  }
 }

src/test/scala/gym/envs/EnvFactoryTest.scala

@@ -1,8 +1,9 @@
 package io.github.cric96
 package gym.envs
 
+import gym.ExternalType
 import gym.core.Env
-import gym.envs.EnvFactory.ToyText
+import gym.envs.EnvFactory.{ClassicControl, ToyText}
 import gym.spaces.{Box, Discrete, Space, Tuple}
 
 import me.shadaj.scalapy.readwrite.{Reader, Writer}
@@ -58,6 +59,29 @@ object EnvFactoryTest extends TestSuite {
           assert(checkEnv[Int, Int, Discrete, Discrete](ToyText.rouletteV0()))
         }
       }
+
+      test("ClassicControl") {
+        test("acrobotV1 should be correctly typed") {
+          assert(checkEnv[Int, ExternalType.NumpyArray, Discrete, Box](ClassicControl.acrobotV1()))
+        }
+        test("cartPoleV1 should be correctly typed") {
+          assert(checkEnv[Int, ExternalType.NumpyArray, Discrete, Box](ClassicControl.cartPoleV1()))
+        }
+        test("mountainCarV0 should be correctly typed") {
+          assert(checkEnv[Int, ExternalType.NumpyArray, Discrete, Box](ClassicControl.mountainCarV0()))
+        }
+
+        test("mountainCarContinuousV0 should be correctly typed") {
+          assert(
+            checkEnv[ExternalType.NumpyArray, ExternalType.NumpyArray, Box, Box](
+              ClassicControl.mountainCarContinuousV0()
+            )
+          )
+        }
+        test("pendulumV0 should be correctly typed") {
+          assert(checkEnv[ExternalType.NumpyArray, ExternalType.NumpyArray, Box, Box](ClassicControl.pendulumV0()))
+        }
+      }
     }
   }
 }