fix #18: inverse the coding and shebang line

examples/reinforcement/baselines/acrobot_gym.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Acrobot' OpenAI Gym environments in PRL using the `stable_baselines` library.
 """
 

examples/reinforcement/baselines/acrobot_prl.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the PRL 'Acrobot' environment using the `stable_baselines` library.
 """
 

examples/reinforcement/baselines/cartpole_gym.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PRL using the `stable_baselines` library.
 """
 

examples/reinforcement/baselines/pendulum_gym.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Pendulum' OpenAI Gym environments in PRL using the `stable_baselines` library.
 """
 

examples/reinforcement/baselines/pendulum_prl.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the PRL 'Acrobot' environment using the `stable_baselines` library.
 """
 

examples/reinforcement/gym/cartpole/linear_bo.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PyRoboLearn using a linear policy trained with
 the Bayesian Optimization algorithm.
 """

examples/reinforcement/gym/cartpole/linear_cem.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PyRoboLearn using a linear policy trained with
 the Cross-Entropy Method algorithm.
 """

examples/reinforcement/gym/cartpole/linear_cmaes.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PyRoboLearn using a linear policy trained with
 the CMA-ES algorithm.
 """

examples/reinforcement/gym/cartpole/linear_fd.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PyRoboLearn using a linear policy trained with
 the finite difference algorithm.
 """

examples/reinforcement/gym/cartpole/linear_power.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PyRoboLearn using a linear policy trained with
 the PoWER RL algorithm.
 """

examples/reinforcement/gym/cartpole/neat_neat.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PyRoboLearn using NEAT.
 """
 

examples/reinforcement/gym/cartpole/random_none.py

@@ -1,5 +1,5 @@
-# -*- coding: utf-8 -*-
 #!/usr/bin/env python
+# -*- coding: utf-8 -*-
 """Example on how to use the 'Cartpole' OpenAI Gym environments in PyRoboLearn using a random policy
 """