junction_tree for #1012 (#4004)

* Initial commit.

* Fixed PEP 8 issues.

* Fixed more PEP 8 issues.

* Added type to sepset-nodes.

* Moved file to networkx/algorithms/tree, changed name of module to avoid namespace collision, added entry to doc system, changed deepcopy to list, removed check for None, shifted to G.is_directed(), added example.

* Removed example code.

* Removed unused import statement.

* Moved notes section.

* Fixed PEP 8 issues and removed old file.

* Fixed PEP 8 issues.

* Formatting with Black, added docstring to example and removed license information.

* Added name to name of contributors.

* Ran black

i.e.,
black networkx/algorithms/tree/tests/test_junction_tree_algorithm.py

* Updated explanation of junction trees, removed 'Graph' from unsupported classes.

* DOC: tweaks to docstring.

* Changed naming and updated docstring/code according to suggestions.

* Removed old files.

* Updated doc and init.

* Minor tweaks in docs and import structure

* Improve example

Co-authored-by: Jarrod Millman <jarrod.millman@gmail.com>
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
Co-authored-by: Dan Schult <dschult@colgate.edu>

1 files changed, 40 insertions, 0 deletions

diff --git a/examples/algorithms/plot_decomposition.py b/examples/algorithms/plot_decomposition.py
new file mode 100644
index 00000000..7b83a718
--- /dev/null
+++ b/examples/algorithms/plot_decomposition.py
@@ -0,0 +1,40 @@
+"""
+=============
+Decomposition
+=============
+
+Example of creating a junction tree from a directed graph.
+"""
+
+import networkx as nx
+from networkx.algorithms import moral
+from networkx.algorithms.tree.decomposition import junction_tree
+from networkx.drawing.nx_agraph import graphviz_layout as layout
+import matplotlib.pyplot as plt
+
+B = nx.DiGraph()
+B.add_nodes_from(["A", "B", "C", "D", "E", "F"])
+B.add_edges_from(
+    [("A", "B"), ("A", "C"), ("B", "D"), ("B", "F"), ("C", "E"), ("E", "F")]
+)
+
+options = {"with_labels": True, "node_color": "white", "edgecolors": "blue"}
+
+bayes_pos = layout(B, prog="neato")
+ax1 = plt.subplot(1, 3, 1)
+plt.title("Bayesian Network")
+nx.draw_networkx(B, pos=bayes_pos, **options)
+
+mg = moral.moral_graph(B)
+plt.subplot(1, 3, 2, sharex=ax1, sharey=ax1)
+plt.title("Moralized Graph")
+nx.draw_networkx(mg, pos=bayes_pos, **options)
+
+jt = junction_tree(B)
+plt.subplot(1, 3, 3)
+plt.title("Junction Tree")
+nsize = [2000 * len(n) for n in list(jt.nodes())]
+nx.draw_networkx(jt, pos=layout(jt, prog="neato"), node_size=nsize, **options)
+
+plt.tight_layout()
+plt.show()