graph tut.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['b', 'c', 'd']\n"
     ]
    }
   ],
   "source": [
    "import networkx as nx\n",
    "\n",
    "g = nx.DiGraph()\n",
    "g.add_edge('a','b',weight=0.1)\n",
    "g.add_edge('b','c',weight=1.5)\n",
    "g.add_edge('a','c',weight=1.0)\n",
    "g.add_edge('c','d',weight=2.2)\n",
    "print(nx.shortest_path(g,'b','d'))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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27dtFRyEBOBETaYlu3bohISEBhoaGsLa2xvHjx8v9vvT0dMyfPx9SqZQlrCRT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\niIgE+j9eAqGlhwC0mAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105a21cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "nx.draw(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x105af5630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw_random(G)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}