03_fitting_power_laws_01.ipynb

03_fitting_power_laws_02.ipynb

03_networkx_transitivi.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Reading the data \n",
    "dataset = \"protein\" #Try with other datasets\n",
    "g = nx.read_edgelist(\"data/%s.txt\" %(dataset), delimiter=\"\\t\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Return the density, clustering coefficient, average clustering coefficient (average of local clustering coefficient of all nodes)\n",
    "\n",
    "density = nx.density(g)\n",
    "global_cc = nx.transitivity(g)\n",
    "avg_cc = nx.average_clustering(g)\n",
    "print(\"density = %s , CC = %s , Average CC = %s\" % (density,global_cc,avg_cc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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