Reformat the docs and add myst-nb as a doc dep

code/docs/api_docs.rst

@@ -0,0 +1,14 @@
+API Docs
+========
+
+MCMC : Markov Chain Monte Carlo Routines
+---------------------------------------------
+
+.. automodule:: MCFF.mcmc
+   :members:
+
+Ising_Model : Ising Model Routines
+---------------------------------------------
+
+.. automodule:: MCFF.ising_model
+   :members:

code/docs/conf.py

@@ -34,8 +34,12 @@ release = "1.0"
 extensions = [
     "sphinx.ext.autodoc",
     "sphinx.ext.napoleon",
+    "myst_nb",
 ]
 
+# Tell myst_nb not to execute the notebooks
+nb_execution_mode = "off"
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]
 

code/docs/index.rst

@@ -7,54 +7,14 @@ You can find the source code and main landing page for this project on `GitHub <
 
 There is a `Jupyter notebook <https://github.com/TomHodson/ReCoDE_MCMCFF>`_ detailing how this page was generated in there.
 
-
-
-Quickstart
-----------
-
-.. code-block:: python
-
-   from MCFF.mcmc import mcmc_generator
-   from MCFF.ising_model import show_state
-
-   ### Simulation Inputs ###
-   N = 500  # Use an NxN system
-
-   initial_state = np.random.choice(
-      np.array([-1, 1], dtype=np.int8), size=(N, N)
-   )  # the intial state to use
-
-   ### Simulation Code ###
-   critical_states = [
-      s for s in mcmc_generator(initial_state, steps=5, stepsize=5*N**2, T= 3.5)
-   ]
-
-   fig, axes = plt.subplots(
-      ncols=len(critical_states), figsize=(5 * len(critical_states), 5)
-   )
-
-   for s, ax in zip(critical_states, axes):
-      show_state(s, ax=ax)
-
-.. image:: _static/states.png
-  :width: 100%
-  :alt: 5 grids showing black and white Ising Model states
-
 .. toctree::
-   :maxdepth: 2
-   :caption: Contents:
+   :maxdepth: 1
+   :glob:
+   :caption: Table of Contents:
 
-mcmc : Markov Chain Monte Carlo Routines
----------------------------------------------
-
-.. automodule:: MCFF.mcmc
-   :members:
-
-ising_model : Ising Model Routines
----------------------------------------------
-
-.. automodule:: MCFF.ising_model
-   :members:
+   quickstart
+   api_docs
+   learning/*
 
 
 

code/docs/quickstart.rst

@@ -0,0 +1,30 @@
+Quickstart
+----------
+
+.. code-block:: python
+
+   from MCFF.mcmc import mcmc_generator
+   from MCFF.ising_model import show_state
+
+   ### Simulation Inputs ###
+   N = 500  # Use an NxN system
+
+   initial_state = np.random.choice(
+      np.array([-1, 1], dtype=np.int8), size=(N, N)
+   )  # the intial state to use
+
+   ### Simulation Code ###
+   critical_states = [
+      s for s in mcmc_generator(initial_state, steps=5, stepsize=5*N**2, T= 3.5)
+   ]
+
+   fig, axes = plt.subplots(
+      ncols=len(critical_states), figsize=(5 * len(critical_states), 5)
+   )
+
+   for s, ax in zip(critical_states, axes):
+      show_state(s, ax=ax)
+
+.. image:: _static/states.png
+  :width: 100%
+  :alt: 5 grids showing black and white Ising Model states

code/docs/requirements.txt

@@ -0,0 +1,2 @@
+sphinx
+myst-nb

readthedocs.yaml

@@ -23,5 +23,6 @@ sphinx:
 python:
    install:
    - requirements: requirements.txt
+   - requirements: code/docs/requirements.txt
    - method: pip
      path: code/