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Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍 https://github.com/madlabunimib/PyCTBN
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PyCTBN/venv/share/doc/networkx-2.5/examples/jit/plot_rgraph.py

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"""
======
Rgraph
======
An example showing how to use the JavaScript InfoVis Toolkit (JIT)
JSON export
See the JIT documentation and examples at http://thejit.org
"""
import json
import matplotlib.pyplot as plt
import networkx as nx
from networkx.readwrite.json_graph import jit_data, jit_graph
# add some nodes to a graph
G = nx.Graph()
G.add_node("one", type="normal")
G.add_node("two", type="special")
G.add_node("solo")
# add edges
G.add_edge("one", "two")
G.add_edge("two", 3, type="extra special")
# convert to JIT JSON
jit_json = jit_data(G, indent=4)
print(jit_json)
X = jit_graph(json.loads(jit_json))
print(f"Nodes: {list(X.nodes(data=True))}")
print(f"Edges: {list(X.edges(data=True))}")
nx.draw(G, with_labels=True)
plt.show()