exercise_41_1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def net_distance(G1, G2):\n",
    "   avgdeg1 = 2 * len(G1.edges) / len(G1.nodes)\n",
    "   avgdeg2 = 2 * len(G2.edges) / len(G2.nodes)\n",
    "   avgcc1 = nx.average_clustering(G1)\n",
    "   avgcc2 = nx.average_clustering(G2)\n",
    "   dens1 = nx.density(G1)\n",
    "   dens2 = nx.density(G2)\n",
    "   return (abs(avgdeg1 - avgdeg2) + abs(avgcc1 - avgcc2) + abs(dens1 - dens2)) / 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "G1 = nx.read_edgelist(\"data1.txt\", delimiter = \"\\t\", nodetype = int)\n",
    "G2 = nx.read_edgelist(\"data2.txt\", delimiter = \"\\t\", nodetype = int)\n",
    "G3 = nx.read_edgelist(\"data3.txt\", delimiter = \"\\t\", nodetype = int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "G1-G2 difference: 0.18333850648545705\n",
      "G1-G3 difference: 0.21621126045625028\n",
      "G2-G3 difference: 0.03287275397079319\n"
     ]
    }
   ],
   "source": [
    "print(\"G1-G2 difference: %s\" % net_distance(G1, G2))\n",
    "print(\"G1-G3 difference: %s\" % net_distance(G1, G3))\n",
    "print(\"G2-G3 difference: %s\" % net_distance(G2, G3))"
   ]
  }
 ],
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