
| Current Path : /proc/thread-self/root/usr/local/share/doc/networkx-2.5/examples/algorithms/ |
Linux ift1.ift-informatik.de 5.4.0-216-generic #236-Ubuntu SMP Fri Apr 11 19:53:21 UTC 2025 x86_64 |
| Current File : //proc/thread-self/root/usr/local/share/doc/networkx-2.5/examples/algorithms/plot_decomposition.py |
"""
=============
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()