{
  "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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