{
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{
"cell_type": "markdown",
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"source": [
"\n# DAG - Topological Layout\n\nThis example combines the `topological_generations` generator with\n`multipartite_layout` to show how to visualize a DAG in topologically-sorted\norder.\n"
]
},
{
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"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import networkx as nx\nimport matplotlib.pyplot as plt\n\n\nG = nx.DiGraph(\n [\n (\"f\", \"a\"),\n (\"a\", \"b\"),\n (\"a\", \"e\"),\n (\"b\", \"c\"),\n (\"b\", \"d\"),\n (\"d\", \"e\"),\n (\"f\", \"c\"),\n (\"f\", \"g\"),\n (\"h\", \"f\"),\n ]\n)\n\nfor layer, nodes in enumerate(nx.topological_generations(G)):\n # `multipartite_layout` expects the layer as a node attribute, so add the\n # numeric layer value as a node attribute\n for node in nodes:\n G.nodes[node][\"layer\"] = layer\n\n# Compute the multipartite_layout using the \"layer\" node attribute\npos = nx.multipartite_layout(G, subset_key=\"layer\")\n\nfig, ax = plt.subplots()\nnx.draw_networkx(G, pos=pos, ax=ax)\nax.set_title(\"DAG layout in topological order\")\nfig.tight_layout()\nplt.show()"
]
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