Howto Documentation draft #188

fhswf · Dec 6, 2021 · 0c72f70 · 0c72f70
1 parent fbc943b
commit 0c72f70
Show file tree

Hide file tree

Showing 4 changed files with 159 additions and 19 deletions.
diff --git a/doc/rtd/content/append1/howto.bf.rst b/doc/rtd/content/append1/howto.bf.rst
@@ -3,9 +3,38 @@ Basic Functions
 
 We provide some examples of `MLPro <https://github.com/fhswf/MLPro.git>`_'s basic funcionalities implementation, which is available on our GitHub file.
 
-- File 01: `(Various) Log and Timer <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2001%20-%20(Various)%20Log%20and%20timer.py>`_
-- File 02: `(Math) Spaces, subspaces and elements <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2002%20-%20(Math)%20Spaces%2C%20subspaces%20and%20elements.py>`_ 
-- File 03: `(Various) Store, plot, and save variables <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2003%20-%20(Various)%20Store%2C%20plot%2C%20and%20save%20variables.py>`_ 
-- File 04: `(ML) Hyperparameters setup <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2004%20-%20(ML)%20Hyperparameters%20setup.py>`_ 
+`(Various) Logging <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2001%20-%20(Various)%20Logging.py>`_
+-----------------
 
-Moreover, you can find the UML diagram of MLPro's basic funcionalities `here <https://github.com/fhswf/MLPro/tree/main/doc/bf>`_.
+.. literalinclude:: ../../../../examples/bf/Howto 01 - (Various) Logging.py
+    :language: python
+
+`(Various) Timer <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2002%20-%20(Various)%20Timer.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/bf/Howto 02 - (Various) Timer.py
+    :language: python
+
+`(Math) Spaces, subspaces and elements <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2003%20-%20(Math)%20Spaces%2C%20subspaces%20and%20elements.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/bf/Howto 03 - (Math) Spaces, subspaces and elements.py
+    :language: python
+
+`(Data) Store, plot, and save variables <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2004%20-%20(Data)%20Store%2C%20plot%2C%20and%20save%20variables.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/bf/Howto 04 - (Data) Store, plot, and save variables.py
+    :language: python
+
+`(ML) Hyperparameters setup <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2005%20-%20(ML)%20Hyperparameters%20setup.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/bf/Howto 05 - (ML) Hyperparameters setup.py
+    :language: python
+
+`(Data) Buffer <https://github.com/fhswf/MLPro/blob/main/examples/bf/Howto%2006%20-%20(Data)%20Buffer.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/bf/Howto 06 - (Data) Buffer.py
+    :language: python
diff --git a/doc/rtd/content/append1/howto.gt.rst b/doc/rtd/content/append1/howto.gt.rst
@@ -3,7 +3,15 @@ Game Theory
 
 We provide some examples of `MLPro <https://github.com/fhswf/MLPro.git>`_'s GT implementation, which is available on our GitHub file.
 
-- File 06: `(GT) Run multi-player with own policy in multicartpole game board <https://github.com/fhswf/MLPro/blob/main/examples/gt/Howto%2006%20-%20(GT)%20Run%20multi-player%20with%20own%20policy%20in%20multicartpole%20game%20board.py>`_
-- File 07: `(GT) Train own multi-player with multicartpole game board <https://github.com/fhswf/MLPro/blob/main/examples/gt/Howto%2007%20-%20(GT)%20Train%20own%20multi-player%20with%20multicartpole%20game%20board.py>`_
+`Run multi-player with own policy in multicartpole game board <https://github.com/fhswf/MLPro/blob/main/examples/gt/Howto%2006%20-%20(GT)%20Run%20multi-player%20with%20own%20policy%20in%20multicartpole%20game%20board.py>`_
+-----------------
 
-Moreover, you can find the UML diagram of MLPro's GT funcionalities `here <https://github.com/fhswf/MLPro/tree/main/doc/gt>`_.
+.. literalinclude:: ../../../../examples/gt/Howto 06 - (GT) Run multi-player with own policy in multicartpole game board.py
+    :language: python
+
+
+`Train own multi-player with multicartpole game board <https://github.com/fhswf/MLPro/blob/main/examples/gt/Howto%2007%20-%20(GT)%20Train%20own%20multi-player%20with%20multicartpole%20game%20board.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/gt/Howto 07 - (GT) Train own multi-player with multicartpole game board.py
+    :language: python
diff --git a/doc/rtd/content/append1/howto.rl.rst b/doc/rtd/content/append1/howto.rl.rst
@@ -3,12 +3,106 @@ Reinforcement Learning
 
 We provide some examples of `MLPro <https://github.com/fhswf/MLPro.git>`_'s RL funcionalities implementation, which is available on our GitHub file.
 
-- File 01: `(RL) Types of reward <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2001%20-%20(RL)%20Types%20of%20reward.py>`_
-- File 02: `(RL) Run agent with own policy with gym environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2002%20-%20(RL)%20Run%20agent%20with%20own%20policy%20with%20gym%20environment.py>`_
-- File 03: `(RL) Train agent with own policy on gym environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2003%20-%20(RL)%20Train%20agent%20with%20own%20policy%20on%20%20gym%20environment.py>`_
-- File 04: `(RL) Run multi-agent with own policy in multicartpole environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2004%20-%20(RL)%20Run%20multi-agent%20with%20own%20policy%20in%20multicartpole%20environment.py>`_
-- File 05: `(RL) Train multi-agent with own policy on multicartpole environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2005%20-%20(RL)%20Train%20multi-agent%20with%20own%20policy%20on%20multicartpole%20environment.py>`_
-- File 06: `(RL) A2C Implementation <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2006%20-%20(RL)%20A2C%20Implementation.py>`_
-- File 08: `(RL) Run own agents with petting zoo environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2008%20-%20(RL)%20Run%20own%20agents%20with%20petting%20zoo%20environment.py>`_
-
-Moreover, you can find the UML diagram of MLPro's RL funcionalities `here <https://github.com/fhswf/MLPro/tree/main/doc/rl>`_.
+`Types of reward <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2001%20-%20(RL)%20Types%20of%20reward.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 01 - (RL) Types of reward.py
+    :language: python
+
+
+`Run agent with own policy with gym environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2002%20-%20(RL)%20Run%20agent%20with%20own%20policy%20with%20gym%20environment.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 02 - (RL) Run agent with own policy with gym environment.py
+    :language: python
+
+
+`Train agent with own policy on gym environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2003%20-%20(RL)%20Train%20agent%20with%20own%20policy%20on%20gym%20environment.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 03 - (RL) Train agent with own policy on gym environment.py
+    :language: python
+
+
+`Run multi-agent with own policy in multicartpole environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2004%20-%20(RL)%20Run%20multi-agent%20with%20own%20policy%20in%20multicartpole%20environment.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 04 - (RL) Run multi-agent with own policy in multicartpole environment.py
+    :language: python
+
+
+`Train multi-agent with own policy on multicartpole environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2005%20-%20(RL)%20Train%20multi-agent%20with%20own%20policy%20on%20multicartpole%20environment.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 05 - (RL) Train multi-agent with own policy on multicartpole environment.py
+    :language: python
+
+
+`A2C Implementation <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2006%20-%20(RL)%20A2C%20Implementation.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 06 - (RL) A2C Implementation.py
+    :language: python
+
+
+`Train UR5 Robot environment with A2C Algorithm <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2007%20-%20(RL)%20Train%20UR5%20Robot%20environment%20with%20A2C%20Algorithm.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 07 - (RL) Train UR5 Robot environment with A2C Algorithm.py
+    :language: python
+
+
+`Run own agents with petting zoo environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2008%20-%20(RL)%20Run%20own%20agents%20with%20petting%20zoo%20environment.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 08 - (RL) Run own agents with petting zoo environment.py
+    :language: python
+
+
+`SAC Implementation <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2009%20-%20(RL)%20SAC%20Implementation.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 09 - (RL) SAC Implementation.py
+    :language: python
+
+
+`Train using SB3 Wrapper <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2010%20-%20(RL)%20Train%20using%20SB3%20Wrapper.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 10 - (RL) Train using SB3 Wrapper.py
+    :language: python
+
+
+`Wrap mlpro Environment class to gym environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2011%20-%20(RL)%20Wrap%20mlpro%20Environment%20class%20to%20gym%20environment.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 11 - (RL) Wrap mlpro Environment class to gym environment.py
+    :language: python
+
+
+`Wrap mlpro Environment class to petting zoo environment <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2012%20-%20(RL)%20Wrap%20mlpro%20Environment%20class%20to%20petting%20zoo%20environment.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 12 - (RL) Wrap mlpro Environment class to petting zoo environment.py
+    :language: python
+
+
+`Comparison Native and Wrapper SB3 Policy <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2013%20-%20(RL)%20Comparison%20Native%20and%20Wrapper%20SB3%20Policy.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 13 - (RL) Comparison Native and Wrapper SB3 Policy.py
+    :language: python
+
+
+`Train UR5 with SB3 wrapper <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2014%20-%20(RL)%20Train%20UR5%20with%20SB3%20wrapper.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 14 - (RL) Train UR5 with SB3 wrapper.py
+    :language: python
+
+
+`Train Robothtm with SB3 Wrapper <https://github.com/fhswf/MLPro/blob/main/examples/rl/Howto%2015%20-%20(RL)%20Train%20Robothtm%20with%20SB3%20Wrapper.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/rl/Howto 15 - (RL) Train Robothtm with SB3 Wrapper.py
+    :language: python
diff --git a/doc/rtd/content/append1/howto.ui.rst b/doc/rtd/content/append1/howto.ui.rst
@@ -3,6 +3,15 @@ User Interface
 
 We provide some examples of `MLPro <https://github.com/fhswf/MLPro.git>`_'s SciUI funcionalities implementation, which is available on our GitHub file.
 
-- File 01: `(SciUI) - Reuse of interactive 2D,3D input space <https://github.com/fhswf/MLPro/blob/main/examples/sciui/Howto%2001%20(SciUI)%20-%20Reuse%20of%20interactive%202D%2C3D%20input%20space.py>`_
+`Reuse of interactive 2D,3D input space <https://github.com/fhswf/MLPro/blob/main/examples/sciui/Howto%2001%20(SciUI)%20-%20Reuse%20of%20interactive%202D%2C3D%20input%20space.py>`_
+-----------------
 
-Moreover, you can find the UML diagram of MLPro's UI funcionalities `here <https://github.com/fhswf/MLPro/tree/main/doc/sciui>`_.
+.. literalinclude:: ../../../../examples/sciui/Howto 01 (SciUI) - Reuse of interactive 2D,3D input space.py
+    :language: python
+
+
+`Reinforcement learning cockpit <https://github.com/fhswf/MLPro/blob/main/examples/sciui/Howto%2002%20(SciUI)%20-%20Reinforcement%20learning%20cockpit.py>`_
+-----------------
+
+.. literalinclude:: ../../../../examples/sciui/Howto 02 (SciUI) - Reinforcement learning cockpit.py
+    :language: python