refactor: auto format comments (#262)

.github/dependabot.yml

@@ -5,7 +5,7 @@
 
 version: 2
 updates:
-  # Maintain dependencies for GitHub Actions
+  # Maintain dependencies for GitHub Actions.
   - package-ecosystem: "github-actions"
     directory: "/"
     schedule:
@@ -14,15 +14,15 @@ updates:
       - dependency-name: "*"
         update-types: ["version-update:semver-patch"]
 
-  # Maintain dependencies for npm
+  # Maintain dependencies for npm.
   - package-ecosystem: "npm"
     directory: "/"
     schedule:
       interval: "weekly"
     ignore:
       - dependency-name: "*"
         update-types: ["version-update:semver-patch"]
-  # Maintain dependencies for npm
+  # Maintain dependencies for npm.
   - package-ecosystem: "pip"
     directory: "/"
     schedule:

.github/workflows/stable_learning_control.yml

@@ -7,7 +7,7 @@ on:
     tags-ignore:
       - v*.*.*
 jobs:
-  markdown-lint: # Lints the markdown code
+  markdown-lint: # Lints the markdown code.
     name: runner / remark-lint
     runs-on: ubuntu-latest
     steps:
@@ -18,7 +18,7 @@ jobs:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           reporter: github-check
           level: warning
-  black: # Check python code format
+  black: # Check python code format.
     name: runner / black
     runs-on: ubuntu-latest
     steps:
@@ -28,7 +28,7 @@ jobs:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           reporter: github-check
           level: warning
-  flake8: # Lints python code
+  flake8: # Lints python code.
     name: runner / flake8
     runs-on: ubuntu-latest
     steps:
@@ -54,9 +54,9 @@ jobs:
     name: python-tests (Testing)
     runs-on: ubuntu-latest
     strategy:
-      fail-fast: false # Run all matrix jobs
+      fail-fast: false # Run all matrix jobs.
       matrix:
-        python-version: [3.8, 3.9, "3.10"] # Supported python versions
+        python-version: [3.8, 3.9, "3.10"] # Supported python versions.
     steps:
       - name: Checkout stable-learning-control repository
         uses: actions/checkout@v3

.github/workflows/test.yml

@@ -15,7 +15,7 @@ jobs:
           level: warning
           exclude: |
             ./CHANGELOG.md
-  alex: # Checks docs for inconsiderate writing
+  alex: # Checks docs for inconsiderate writing.
     name: runner / alex
     runs-on: ubuntu-latest
     steps:
@@ -25,7 +25,7 @@ jobs:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           reporter: github-check
           level: warning
-  markdown-lint: # Lints the markdown code
+  markdown-lint: # Lints the markdown code.
     name: runner / remark-lint
     runs-on: ubuntu-latest
     steps:
@@ -36,7 +36,7 @@ jobs:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           reporter: github-check
           level: warning
-  black: # Check python code format
+  black: # Check python code format.
     name: runner / black
     runs-on: ubuntu-latest
     steps:
@@ -46,7 +46,7 @@ jobs:
           github_token: ${{ secrets.GITHUB_TOKEN }}
           reporter: github-check
           level: warning
-  flake8: # Lints python code
+  flake8: # Lints python code.
     name: runner / flake8
     runs-on: ubuntu-latest
     steps:
@@ -72,9 +72,9 @@ jobs:
     name: python-tests (Testing)
     runs-on: ubuntu-latest
     strategy:
-      fail-fast: false # Run all matrix jobs
+      fail-fast: false # Run all matrix jobs.
       matrix:
-        python-version: [3.8, 3.9, "3.10"] # Supported python versions
+        python-version: [3.8, 3.9, "3.10"] # Supported python versions.
     steps:
       - name: Checkout stable-learning-control repository
         uses: actions/checkout@v3

docs/Makefile

@@ -1,6 +1,6 @@
 # Makefile for Stable Learning Control Sphinx documentation
 
-# You can set these variables from the command line.
+# You can set these variables from the command line
 SPHINXOPTS    =
 SPHINXBUILD   = sphinx-build
 SPHINXPROJ    = Stable Learning Control

docs/source/conf.py

@@ -68,12 +68,12 @@ def __getattr__(cls, name):
     "myst_parser",
 ]
 
-# Extension settings
+# Extension settings.
 autosummary_generate = True
 autosummary_generate_overwrite = True
 autodoc_member_order = "bysource"
 
-# imgmath settings
+# imgmath settings.
 imgmath_image_format = "svg"
 imgmath_font_size = 14
 
@@ -110,7 +110,7 @@ def __getattr__(cls, name):
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.
-# This patterns also effect to html_static_path and html_extra_path
+# This patterns also effect to html_static_path and html_extra_path.
 exclude_patterns = ["_build", "Thumbs.db", ".DS_Store", "TODO.*", "README.*"]
 
 # The name of the Pygments (syntax highlighting) style to use.

docs/source/control/eval_robustness.rst

@@ -99,23 +99,23 @@ under several Impulse disturbances.
 
     if __name__ == "__main__":
 
-        # Parse input arguments
+        # Parse input arguments.
         parser = argparse.ArgumentParser()
         parser.add_argument("fpath", type=str, help="The path where the policy is stored")
         args = parser.parse_args()
 
-        # Retrieve dataframe
+        # Retrieve dataframe.
         robustness_eval_df = pd.read_csv(Path(args.fpath).absolute())
 
-        # Retrieve observation and reference data from the dataframe
+        # Retrieve observation and reference data from the dataframe.
         o_disturbances_df = robustness_eval_df.query("variable == 'observation'").dropna(
             axis=1, how="all"
         )
         ref_disturbance_df = robustness_eval_df.query("variable == 'reference'").dropna(
             axis=1, how="all"
         )
 
-        # Merge observations and references into one dataframe
+        # Merge observations and references into one dataframe.
         obs_df_tmp = o_disturbances_df.query("observation == 3")
         obs_df_tmp["signal"] = "obs_" + (obs_df_tmp["observation"] + 1).astype(str)
         obs_df_tmp.insert(len(obs_df_tmp.columns), "type", "observation")
@@ -190,14 +190,14 @@ class to add all the required methods and attributes to make it compatible with
     import numpy as np
     from stable_learning_control.simzoo.simzoo.common.disturber import Disturber
 
-    # Disturber config used to overwrite the default config
+    # Disturber config used to overwrite the default config.
     DISTURBER_CFG = {
-        # Disturbance applied to environment variables
+        # Disturbance applied to environment variables.
         "env": {
             "description": "Pole length disturbance",
-            # The env variable which you want to disturb
+            # The env variable which you want to disturb.
             "variable": "length",
-            # The range of values you want to use for each disturbance iteration
+            # The range of values you want to use for each disturbance iteration.
             "variable_range": np.linspace(0.5, 2.0, num=5, dtype=np.float32),
             # Label used in robustness plots.
             "label": "r: %s",
@@ -271,10 +271,10 @@ When editing the ``DISTURBANCE_CFG`` config in the :class:`~stable_learning_cont
     :linenos:
     :emphasize-lines: 5
 
-    # A random noise that is applied at every timestep
+    # A random noise that is applied at every timestep.
     "noise": {
         "description": "Random noise disturbance",
-        # The means and standards deviations of the random noise disturbance
+        # The means and standards deviations of the random noise disturbance.
         "noise_range": {
             "mean": np.linspace(80, 155, num=3, dtype=np.int16),
             "std": np.linspace(1.0, 5.0, num=3, dtype=np.int16),
@@ -292,14 +292,14 @@ When editing the ``DISTURBANCE_CFG`` config in the :class:`~stable_learning_cont
 
     # Disturbance applied to the *OUTPUT* of the environment step function
     "output": {
-        # The disturbance variant used when no variant is given
+        # The disturbance variant used when no variant is given.
         "default_variant": "impulse",
-        # A random noise that is applied at every timestep
+        # A random noise that is applied at every timestep.
         "noise": {
             "description": "Random noise disturbance",
-            # The means and standards deviations of the random noise disturbance
+            # The means and standards deviations of the random noise disturbance.
             "noise_range": {
-                # "mean": np.linspace(80, 155, num=3, dtype=np.int16),  # All obs
+                # "mean": np.linspace(80, 155, num=3, dtype=np.int16),  # All obs.
                 "mean": np.vstack(
                     (
                         np.linspace(80, 155, num=3, dtype=np.int16),  # Obs 1
@@ -308,7 +308,7 @@ When editing the ``DISTURBANCE_CFG`` config in the :class:`~stable_learning_cont
                         np.linspace(80, 155, num=3, dtype=np.int16),  # Obs 4
                     )
                 ).T,
-                # "std": np.linspace(1.0, 5.0, num=3, dtype=np.int16),  # All Obs
+                # "std": np.linspace(1.0, 5.0, num=3, dtype=np.int16),  # All Obs.
                 "std": np.vstack(
                     (
                         np.linspace(1.0, 5.0, num=3, dtype=np.int16),  # Obs 1
@@ -332,20 +332,20 @@ When editing the ``DISTURBANCE_CFG`` config in the :class:`~stable_learning_cont
     :linenos:
     :emphasize-lines: 4, 12
 
-    # Input and output noise disturbance
+    # Input and output noise disturbance.
     "noise": {
         "description": "Random input and output noise disturbance",
         "input_noise": {
             # The means and standards deviations of the random input noise
-            # disturbance
+            # disturbance.
             "noise_range": {
                 "mean": np.linspace(80, 155, num=3, dtype=np.int16),
                 "std": np.linspace(1.0, 5.0, num=3, dtype=np.int16),
             },
         },
         "output_noise": {
             # The means and standards deviations of the random output noise
-            # disturbance
+            # disturbance.
             "noise_range": {
                 "mean": np.linspace(80, 155, num=3, dtype=np.int16),
                 "std": np.linspace(1.0, 5.0, num=3, dtype=np.int16),

docs/source/control/saving_and_loading.rst

@@ -189,23 +189,23 @@ the :torch:`PyTorch documentation <tutorials/beginner/saving_loading_models.html
     MODEL_LOAD_FOLDER = "./data/lac/oscillator-v1/runs/run_1614680001"
     MODEL_PATH = osp.join(MODEL_LOAD_FOLDER, "torch_save/model_state.pt")
 
-    # Restore the model
+    # Restore the model.
     config = EpochLogger.load_config(
         MODEL_LOAD_FOLDER
-    )  # Retrieve the experiment configuration
+    )  # Retrieve the experiment configuration.
     env = EpochLogger.load_env(MODEL_LOAD_FOLDER)
     model = LAC(env=env, ac_kwargs=config["ac_kwargs"])
     restored_model_state_dict = torch.load(MODEL_PATH, map_location="cpu")
     model.load_state_dict(
         restored_model_state_dict,
     )
 
-    # Create dummy observations and retrieve the best action
+    # Create dummy observations and retrieve the best action.
     obs = torch.rand(env.observation_space.shape)
     a = model.get_action(obs)
     L_value = model.ac.L(obs, torch.from_numpy(a))
 
-    # Print results
+    # Print results.
     print(f"The LAC agent thinks it is a good idea to take action {a}.")
     print(f"It assigns a Lyapunov Value of {L_value} to this action.")
 
@@ -237,23 +237,23 @@ Load Tensorflow Policy
     MODEL_LOAD_FOLDER = "./data/lac/oscillator-v1/runs/run_1614673367"
     MODEL_PATH = osp.join(MODEL_LOAD_FOLDER, "tf2_save")
 
-    # Restore the model
+    # Restore the model.
     config = EpochLogger.load_config(
         MODEL_LOAD_FOLDER
-    )  # Retrieve the experiment configuration
+    )  # Retrieve the experiment configuration.
     env = EpochLogger.load_env(MODEL_LOAD_FOLDER)
     model = LAC(env=env, ac_kwargs=config["ac_kwargs"])
     weights_checkpoint = tf.train.latest_checkpoint(MODEL_PATH)
     model.load_weights(
         weights_checkpoint,
     )
 
-    # Create dummy observations and retrieve the best action
+    # Create dummy observations and retrieve the best action.
     obs = tf.random.uniform((1, env.observation_space.shape[0]))
     a = model.get_action(obs)
     L_value = model.ac.L([obs, tf.expand_dims(a, axis=0)])
 
-    # Print results
+    # Print results.
     print(f"The LAC agent thinks it is a good idea to take action {a}.")
     print(f"It assigns a Lyapunov Value of {L_value} to this action.")
 

docs/source/hardware/hardware.rst

@@ -36,11 +36,11 @@ then be loaded onto the hardware using the :obj:`tf.saved_model.load` method.
 
     model_path = "./data/lac/oscillator-v1/runs/run_1614673367/tf2_save"
 
-    # Load model and environment
+    # Load model and environment.
     loaded_model = tf.saved_model.load(model_path)
     loaded_env = EpochLogger.load_env(os.path.dirname(model_path))
 
-    # Get action for dummy observation
+    # Get action for dummy observation.
     obs = tf.random.uniform((1, loaded_env.observation_space.shape[0]))
     a = loaded_model.get_action(obs)
     print(f"\nThe model thinks it is a good idea to take action: {a.numpy()}")

docs/source/simzoo/simzoo.rst

@@ -70,7 +70,7 @@ being printed to the console.
     print("Taking 1000 steps in the Oscillator-v1 environment...")
     for ii in range(1000):
         env.render()  # Does not work with the Oscillator-v1 environment.
-        obs, cost, done, info_doc = env.step(env.action_space.sample())  # take a random action
+        obs, cost, done, info_doc = env.step(env.action_space.sample())  # take a random action.
         if ii % 100 == 0:
             print(f"Randoms step {ii}: {obs}")
     env.close()