Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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44 lines
1.0 KiB
44 lines
1.0 KiB
"""
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==============
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Directed Graph
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==============
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Draw a graph with directed edges using a colormap and different node sizes.
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Edges have different colors and alphas (opacity). Drawn using matplotlib.
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"""
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import matplotlib as mpl
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import matplotlib.pyplot as plt
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import networkx as nx
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G = nx.generators.directed.random_k_out_graph(10, 3, 0.5)
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pos = nx.layout.spring_layout(G)
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node_sizes = [3 + 10 * i for i in range(len(G))]
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M = G.number_of_edges()
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edge_colors = range(2, M + 2)
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edge_alphas = [(5 + i) / (M + 4) for i in range(M)]
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nodes = nx.draw_networkx_nodes(G, pos, node_size=node_sizes, node_color="blue")
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edges = nx.draw_networkx_edges(
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G,
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pos,
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node_size=node_sizes,
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arrowstyle="->",
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arrowsize=10,
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edge_color=edge_colors,
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edge_cmap=plt.cm.Blues,
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width=2,
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)
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# set alpha value for each edge
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for i in range(M):
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edges[i].set_alpha(edge_alphas[i])
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pc = mpl.collections.PatchCollection(edges, cmap=plt.cm.Blues)
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pc.set_array(edge_colors)
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plt.colorbar(pc)
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ax = plt.gca()
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ax.set_axis_off()
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plt.show()
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