Demo analysis of KONECT's Internet topology network dataset ... (dataset from 2005, updated by me, IPv4 only!) http://irl.cs.ucla.edu/topology/

notebook2-topology-2005.ipynb

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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import pandas as pd\n",
      "from scipy import stats, integrate\n",
      "import matplotlib.pyplot as plt\n",
      "from operator import mul\n",
      "import requests\n",
      "import re\n",
      "\n",
      "from graph_tool.all import *"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Load Dataset"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "NETWORK_NAME = 'topology' # arenas-pgp, topology, as20000102"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# g = graph_tool.collection.konect_data[NETWORK_NAME] \n",
      "g = graph_tool.collection.load_koblenz_dir('topology2') \n",
      "# print g.gp.readme"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "g"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<Graph object, undirected, with 20277 vertices and 57238 edges at 0x7fc68aa2d190>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "r = requests.get('http://konect.uni-koblenz.de/networks/' + NETWORK_NAME).text\n",
      "print re.search('description\">(.*)</div></div>', r).group(1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "This is the network of connections between autonomous systems of the Internet. The nodes are autonomous systems (AS), i.e. collections of connected IP routing prefixes controlled by independent network operators. Edges are connections between autonomous systems. Multiple edges may connect two nodes, each representing an individual connection in time. Edges are annotated with the timepoint of the connection.\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Helper Functions"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def plot_hist(data, xlog=False, ylog=True, label=''):\n",
      "    plt.bar(range(len(data[0])), data[0], log=ylog)\n",
      "    if xlog:\n",
      "        plt.xscale('log')\n",
      "    plt.title(label + ' Histogram')\n",
      "    plt.xlabel(label)\n",
      "    plt.ylabel('Frequency')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def avg_from_hist(data):\n",
      "    ammount = data[0]\n",
      "    label = data[1][:-1]\n",
      "    return sum(map(mul, ammount, label)) / sum(ammount)\n",
      "\n",
      "# for degrees, this is equal to vertex_average(g, 'total')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Shortest-distance\n",
      "the shortest-distance for each vertex pair in the graph."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "distance_hist = distance_histogram(g)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_hist(distance_hist, label='Shortest Distance')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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RMTnt+zrwUER8PR2Ebh4RnyuznqMxxHt7B3B1RKyRdCbASO+tk1ZSvzA1NiKe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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fb7db3dc1d0>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Average Shortest-distance"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "avg_from_hist(distance_hist)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "3.6676403855683604"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Degree\n",
      "the vertex degree."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "degree_hist = vertex_hist(g, \"total\")\n",
      "# degree_hist"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_hist(degree_hist, label='Degree')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7fb7bb27e810>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_hist(degree_hist, xlog=True, label='Degree')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7fb7bac1ed50>"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Average Degree"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "avg_from_hist(degree_hist)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 14,
       "text": [
        "5.6251674739771209"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "vertex_average(g, 'total')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "(5.625167473977121, 0.27574733192371698)"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    }
   ],
   "metadata": {}
  }
 ]
}