{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n# Visibility Graph\n\nVisibility Graph constructed from a time series\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from matplotlib import pyplot as plt\n\nimport networkx as nx\n\ntime_series = [0, 2, 1, 3, 2, 1, 3, 2, 1, 3, 2, 1, 3, 4, 0]\n# or\n# import random\n# time_series = [random.randint(1, 10) for i in range(10)]\n\nG = nx.visibility_graph(time_series)\n\nlabels = nx.get_node_attributes(G, \"value\")\n\nfig, all_axes = plt.subplots(2, 1, num=\"Visibility Graph\", figsize=(8, 12))\naxs = all_axes.flat\n\nlayouts_params = {\n # a layout emphasizing the line-of-sight connectivity\n \"Line-of-Sight Connectivity\": {\n \"pos\": {x: (x, 0) for x in range(len(time_series))},\n \"connectionstyle\": \"arc3,rad=-1.57079632679\",\n },\n # a layout showcasing the time series values\n \"Time Series values with Connectivity\": {\n \"pos\": {i: (i, v) for i, v in enumerate(time_series)}\n },\n}\n\nfor i, (name, params) in enumerate(layouts_params.items()):\n axs[i].title.set_text(name)\n axs[i].title.set_size(11)\n axs[i].set_xlabel(\"Time\", size=10)\n axs[i].margins(0.10)\n nx.draw_networkx_nodes(G, params.get(\"pos\"), ax=axs[i], alpha=0.5)\n nx.draw_networkx_labels(G, params.get(\"pos\"), ax=axs[i], labels=labels)\n nx.draw_networkx_edges(\n G, **params, ax=axs[i], arrows=True, arrowstyle=\"<->\", arrowsize=10\n )\n\naxs[1].set_ylabel(\"Value\", size=10)\n\nfig.suptitle(\"Visibility Graph\")\nfig.tight_layout()\nplt.show()"
]
}
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