Merge branch 'develop' of https://stash.pnnl.gov/scm/hyp/hypernetx in…

…to hotfix/grabprop
pnnl · Dec 5, 2024 · 3609c69 · 3609c69
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diff --git a/docs/source/algorithms/algorithms.rst b/docs/source/algorithms/algorithms.rst
@@ -44,6 +44,14 @@ algorithms.laplacians\_clustering module
    :undoc-members:
    :show-inheritance:
 
+algorithms.matching\_algorithms module
+--------------------------------------
+
+.. automodule:: algorithms.matching_algorithms
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 algorithms.s\_centrality\_measures module
 -----------------------------------------
 

diff --git a/docs/source/modularity.rst → .../hypergraph_modularity_and_clustering.rst b/docs/source/modularity.rst → .../hypergraph_modularity_and_clustering.rst
diff --git a/docs/source/algorithms/matching_algorithms.rst b/docs/source/algorithms/matching_algorithms.rst
@@ -35,24 +35,23 @@ These algorithms are crucial for applications that require scalable parallel pro
 
 Usage Example
 -------------
-Below is an example of how to use the matching algorithms module.
-
-```python
-from hypernetx.algorithms import matching_algorithms as ma
-
-# Example hypergraph data
-hypergraph = ... # Assume this is a d-uniform hypergraph
-
-# Compute a matching using the O(d²)-approximation algorithm
-matching = ma.matching_approximation_d_squared(hypergraph)
-
-# Compute a matching using the d-approximation algorithm
-matching_d = ma.matching_approximation_d(hypergraph)
-
-# Compute a matching using the d(d−1 + 1/d)²-approximation algorithm
-matching_d_squared = ma.matching_approximation_dd(hypergraph)
-
-print(matching, matching_d, matching_d_squared)
+Below is an example of how to use the matching algorithms module.::
+	
+	from hypernetx.algorithms import matching_algorithms as ma
+	
+	# Example hypergraph data
+	hypergraph = ... # Assume this is a d-uniform hypergraph
+	
+	# Compute a matching using the O(d²)-approximation algorithm
+	matching = ma.matching_approximation_d_squared(hypergraph)
+	
+	# Compute a matching using the d-approximation algorithm
+	matching_d = ma.matching_approximation_d(hypergraph)
+	
+	# Compute a matching using the d(d−1 + 1/d)²-approximation algorithm
+	matching_d_squared = ma.matching_approximation_dd(hypergraph)
+	
+	print(matching, matching_d, matching_d_squared)
 
 
 References

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -59,7 +59,7 @@ Contents
    A Gentle Introduction to Hypergraph Mathematics <hypergraph101>
    Hypergraph Constructors <hypconstructors>
    Visualization Widget <widget>
-   Algorithms: Modularity and Clustering <modularity>
+   Modules <modules>
    Publications <publications>
    Contributors Guide <contributions>
    license

diff --git a/docs/source/modules.rst b/docs/source/modules.rst
@@ -0,0 +1,18 @@
+.. _Modules:
+
+********************
+Modules
+********************
+
+This page provides additionally documentation for various contributions to HyperNetX through modules.
+We use the term module to describe an advanced method for studying hypergraphs. 
+Each module includes a descriptive document here as well as a notebook showcasing its functionality.
+Tutorial notebooks can be found for each module under the `advanced tutorials  <https://github.com/pnnl/HyperNetX/tree/master/tutorials/advanced>`_ folder in GitHub. 
+
+**Modules with additional documentation:**
+
+.. toctree::
+   :maxdepth: 1
+
+   Hypergraph Modularity and Clustering <algorithms/hypergraph_modularity_and_clustering>
+   Hypergraph Matching <algorithms/matching_algorithms>