exercise_41_4.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "G1 = nx.read_edgelist(\"1/data1.txt\", delimiter = \"\\t\", nodetype = int)\n",
    "G2 = nx.read_edgelist(\"1/data2.txt\", delimiter = \"\\t\", nodetype = int)\n",
    "G3 = nx.read_edgelist(\"1/data3.txt\", delimiter = \"\\t\", nodetype = int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "edges = []\n",
    "for n1 in range(len(G1.nodes) - 1):\n",
    "   for n2 in range(n1 + 1, len(G2.nodes)):\n",
    "      count = 0\n",
    "      if (n1, n2) in G1.edges or (n2, n1) in G1.edges:\n",
    "         count += 1\n",
    "      if (n1, n2) in G2.edges or (n2, n1) in G2.edges:\n",
    "         count += 1\n",
    "      if (n1, n2) in G3.edges or (n2, n1) in G3.edges:\n",
    "         count += 1\n",
    "      if count >= 2:\n",
    "         edges.append((n1, n2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "Gc = nx.Graph(edges)"
   ]
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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