🏗️ Cleans up the respository structure

.gitmodules

@@ -1,3 +0,0 @@
-[submodule "simzoo/envs/ex3_ekf"]
-	path = simzoo/envs/ex3_ekf
-	url = ../ex3_ekf.git

README.md

@@ -3,7 +3,7 @@
 A python package containing the bayesian_learning_control Openai gym environments. It currently contains the following environments:
 
 -   [Oscillator:](https://github.com/rickstaa/oscillator) A gym environment for a synthetic oscillatory network of transcriptional regulators called a repressilator.
--   [Ex3_EKF:](https://github.com/rickstaa/ex3_ekf) A noisy master-slave environment that can be used to train a RL based stationary Kalman estimator.
+-   [Ex3EKF:](https://github.com/rickstaa/ex3_ekf) A noisy master-slave environment that can be used to train a RL based stationary Kalman estimator.
 
 ## Clone the repository
 

simzoo/__init__.py

@@ -13,8 +13,12 @@
     namespace_prefix = "bayesian_learning_control.simzoo."
 
 ENVS = {
-    "name": ["Oscillator-v1", "Ex3_EKF-v0", "CartPoleCustom-v0"],
-    "module": ["simzoo.envs.oscillator:Oscillator", "simzoo.envs.ex3_ekf:Ex3_EKF", "simzoo.envs.cart_pole.CartPole:CartPoleCustom"],
+    "name": ["Oscillator-v1", "Ex3EKF-v1", "CartPoleCost-v0"],
+    "module": [
+        "simzoo.envs.biological.oscillator:Oscillator",
+        "simzoo.envs.classic_control.ex3_ekf:Ex3EKF",
+        "simzoo.envs.classic_control.cart_pole_cost:CartPoleCost",
+    ],
     "max_step": [800, 800, 800],
 }
 

simzoo/envs/__init__.py

@@ -1,34 +1 @@
 """The Simzoo Gym environments."""
-import importlib
-import sys
-
-# Import simzoo stand-alone package or name_space package (mlc)
-if "simzoo" in sys.modules:
-    from simzoo.envs.oscillator.oscillator import Oscillator
-    from simzoo.envs.ex3_ekf.ex3_ekf import Ex3_EKF
-    from simzoo.envs.cart_pole.CartPole import CartPoleCustom
-elif importlib.util.find_spec("simzoo") is not None:
-    Oscillator = getattr(
-        importlib.import_module("simzoo.envs.oscillator.oscillator"), "Oscillator"
-    )
-    Ex3_EKF = getattr(importlib.import_module("simzoo.envs.ex3_ekf.ex3_ekf"), "Ex3_EKF")
-    CartPole = getattr(importlib.import_module("simzoo.envs.ex3_ekf.cart_pole"), "CartPoleCustom")
-else:
-    Oscillator = getattr(
-        importlib.import_module(
-            "bayesian_learning_control.simzoo.simzoo.envs.oscillator.oscillator"
-        ),
-        "Oscillator",
-    )
-    Ex3_EKF = getattr(
-        importlib.import_module(
-            "bayesian_learning_control.simzoo.simzoo.envs.ex3_ekf.ex3_ekf"
-        ),
-        "Ex3_EKF",
-    )
-    CartPole = getattr(
-        importlib.import_module(
-            "bayesian_learning_control.simzoo.simzoo.envs.cart_pole.CartPole"
-        ),
-        "CartPoleCustom",
-    )

simzoo/envs/biological/__init__.py

@@ -0,0 +1,21 @@
+"""Import biological environments onto namespace
+"""
+
+import sys
+import importlib
+
+# NOTE: Makes sure that it works both in the Simzoo stand-alone package and the name_space package (blc)
+if "simzoo" in sys.modules:
+    from simzoo.envs.biological.oscillator.oscillator import Oscillator
+elif importlib.util.find_spec("simzoo") is not None:
+    Oscillator = getattr(
+        importlib.import_module("simzoo.envs.biological.oscillator.oscillator"),
+        "Oscillator",
+    )
+else:
+    Oscillator = getattr(
+        importlib.import_module(
+            "bayesian_learning_control.simzoo.simzoo.envs.biological.oscillator.oscillator"
+        ),
+        "Oscillator",
+    )

simzoo/envs/classic_control/__init__.py

@@ -0,0 +1,34 @@
+"""Import classical_control environments onto namespace
+"""
+
+import sys
+import importlib
+
+# NOTE: Makes sure that it works both in the Simzoo stand-alone package and the name_space package (blc)
+if "simzoo" in sys.modules:
+    from simzoo.envs.classic_control.ex3_ekf.ex3_ekf import Ex3EKF
+    from simzoo.envs.classic_control.cart_pole_cost.cart_pole_cost import CartPoleCost
+elif importlib.util.find_spec("simzoo") is not None:
+    Ex3EKF = getattr(
+        importlib.import_module("simzoo.envs.classic_control.ex3_ekf.ex3_ekf"),
+        "Ex3EKF",
+    )
+    CartPoleCost = getattr(
+        importlib.import_module(
+            "simzoo.envs.classic_control.cart_pole_cost.cart_pole_cost"
+        ),
+        "CartPoleCost",
+    )
+else:
+    Ex3EKF = getattr(
+        importlib.import_module(
+            "bayesian_learning_control.simzoo.simzoo.envs.classic_control.ex3_ekf.ex3_ekf"
+        ),
+        "Ex3EKF",
+    )
+    CartPoleCost = getattr(
+        importlib.import_module(
+            "bayesian_learning_control.simzoo.simzoo.envs.classic_control.cart_pole_cost.cart_pole_cost"
+        ),
+        "CartPoleCost",
+    )

simzoo/envs/cart_pole/__init__.py → simzoo/envs/classic_control/cart_pole_cost/__init__.py

@@ -4,15 +4,15 @@
 
 # Import simzoo stand-alone package or name_space package (blc)
 if "simzoo" in sys.modules:
-    from simzoo.envs.cart_pole.CartPole import CartPoleCustom
+    from simzoo.envs.cart_pole.CartPole import CartPoleCost
 elif importlib.util.find_spec("simzoo") is not None:
     CartPole = getattr(
-        importlib.import_module("simzoo.envs.cart_pole.CartPole"), "CartPoleCustom"
+        importlib.import_module("simzoo.envs.cart_pole.CartPole"), "CartPoleCost"
     )
 else:
     CartPole = getattr(
         importlib.import_module(
             "bayesian_learning_control.simzoo.simzoo.envs.cart_pole.CartPole"
         ),
-        "CartPoleCustom",
+        "CartPoleCost",
     )

simzoo/envs/cart_pole/CartPole.py → simzoo/envs/classic_control/cart_pole_cost/cart_pole_cost.py

@@ -53,7 +53,7 @@
 # }
 
 
-class CartPoleCustom(gym.Env, Disturber):
+class CartPoleCost(gym.Env, Disturber):
     """
     Description:
         A pole is attached by an un-actuated joint to a cart, which moves along a
@@ -387,7 +387,7 @@ def COST_V2(r1, r2, e1, e2, x, x_dot, theta, theta_dot):
 if __name__ == "__main__":
 
     print("Settting up Cartpole environment.")
-    env = CartPoleCustom()
+    env = CartPoleCost()
 
     # Take T steps in the environment
     T = 60000

simzoo/envs/ex3-ekf/README.md → simzoo/envs/classic_control/ex3_ekf/README.md

@@ -1,4 +1,4 @@
-# Ex3_EKF gym environment
+# Ex3EKF gym environment
 
 A gym environment for a noisy master-slave system. This environment can be used to train a
 RL based stationary Kalman filter.
@@ -17,7 +17,7 @@ RL based stationary Kalman filter.
 
 ## Environment goal
 
-The goal of the agent in the Ex3_EKF environment is to act in such a way that
+The goal of the agent in the Ex3EKF environment is to act in such a way that
 estimator perfectly estimated the original noisy system. By doing this, it serves
 as an RL based stationary Kalman filter.
 

simzoo/envs/classic_control/ex3_ekf/__init__.py

@@ -0,0 +1,18 @@
+"""Noisy master slave system (Ex3EKF) gym environment."""
+import sys
+import importlib
+
+# Import simzoo stand-alone package or name_space package (blc)
+if "simzoo" in sys.modules:
+    from simzoo.envs.classic_control.ex3_ekf.ex3_ekf import Ex3EKF
+elif importlib.util.find_spec("simzoo") is not None:
+    Ex3EKF = getattr(
+        importlib.import_module("simzoo.envs.classic_control.ex3_ekf.ex3_ekf"), "Ex3EKF"
+    )
+else:
+    Ex3EKF = getattr(
+        importlib.import_module(
+            "bayesian_learning_control.simzoo.simzoo.envs.classic_control.ex3_ekf.ex3_ekf"
+        ),
+        "Ex3EKF",
+    )

simzoo/envs/ex3-ekf/ex3_ekf.py → simzoo/envs/classic_control/ex3_ekf/ex3_ekf.py

@@ -1,4 +1,4 @@
-"""Noisy master slave system (Ex3_EKF) gym environment.
+"""Noisy master slave system (Ex3EKF) gym environment.
 
 The dynamic system whose state is to be estimated:
 
@@ -21,7 +21,7 @@
     \\hat(x)(k+1)=A\\hat(x)(k)+u
     where u=[u1,u2,u3]', u=l(\\hat(x)(k),y(k)) come from the policy network l(.,.)
 """
-__VERSION__ = "0.6.3"  # Ex3_EKF version
+__VERSION__ = "0.6.3"  # Ex3EKF version
 
 import importlib
 import sys
@@ -68,9 +68,9 @@
 }
 
 
-class Ex3_EKF(gym.Env, Disturber):
+class Ex3EKF(gym.Env, Disturber):
     """Noisy master slave system
-    The goal of the agent in the Ex3_EKF environment is to act in such a way that
+    The goal of the agent in the Ex3EKF environment is to act in such a way that
     estimator perfectly estimated the original noisy system. By doing this it serves
     as a RL based stationary Kalman filter.
 
@@ -94,7 +94,7 @@ def __init__(self, seed=400):
         self.t = 0
         self.dt = 0.1
 
-        # Setup Ex3_EKF parameters
+        # Setup Ex3EKF parameters
         self.q1 = 0.01
         self.g = 9.81
         self.l_net = 1.0
@@ -248,21 +248,21 @@ def render(self, mode="human"):
             This currently is not yet implemented.
         """
         raise NotImplementedError(
-            "No render method was implemented yet for the Ex3_EKF environment."
+            "No render method was implemented yet for the Ex3EKF environment."
         )
 
 
 if __name__ == "__main__":
 
-    print("Settting up Ex3_EKF environment.")
-    env = Ex3_EKF()
+    print("Settting up Ex3EKF environment.")
+    env = Ex3EKF()
 
     # Take T steps in the environment
     T = 10
     path = []
     t1 = []
     s = env.reset()
-    print(f"Taking {T} steps in the Ex3_EKF environment.")
+    print(f"Taking {T} steps in the Ex3EKF environment.")
     for i in range(int(T / env.dt)):
         action = (
             env.np_random.uniform(