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diff --git a/_downloads/d8d3d37031dc95f0d814575af4ac51f7/plot_igraph.ipynb b/_downloads/d8d3d37031dc95f0d814575af4ac51f7/plot_igraph.ipynb new file mode 100644 index 00000000..07200afe --- /dev/null +++ b/_downloads/d8d3d37031dc95f0d814575af4ac51f7/plot_igraph.ipynb @@ -0,0 +1,90 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n# igraph\n\nigraph (https://igraph.org/) is a popular network analysis package that\nprovides (among many other things) functions to convert to/from NetworkX.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\nimport networkx as nx\nimport igraph as ig" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## NetworkX to igraph\n\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "G = nx.dense_gnm_random_graph(30, 40, seed=42)\n\n# largest connected component\ncomponents = nx.connected_components(G)\nlargest_component = max(components, key=len)\nH = G.subgraph(largest_component)\n\n# convert to igraph\nh = ig.Graph.from_networkx(H)\n\n\n# Plot the same network with NetworkX and igraph\nfig, (ax0, ax1) = plt.subplots(nrows=1, ncols=2, figsize=(12, 6))\n\n# NetworkX draw\nax0.set_title(\"Plot with NetworkX draw\")\nnx.draw_kamada_kawai(H, node_size=50, ax=ax0)\n\n# igraph draw\nax1.set_title(\"Plot with igraph plot\")\nlayout = h.layout_kamada_kawai()\nig.plot(h, layout=layout, target=ax1)\nplt.axis(\"off\")\nplt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## igraph to NetworkX\n\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "g = ig.Graph.GRG(30, 0.2)\nG = g.to_networkx()\nnx.draw(G, node_size=50)\nplt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.15" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +}
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