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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from networks import *\n",
    "from simulation import *\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "g = gen_BA_graph(1000, 3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.161\n",
      "0.137\n",
      "0.143\n"
     ]
    }
   ],
   "source": [
    "print(run_SIS_simulation(g, 0.3, time_steps=500))\n",
    "print(run_SIS_simulation(g, 0.3, time_steps=1000))\n",
    "print(run_SIS_simulation(g, 0.3, time_steps=2000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.156\n",
      "0.138\n",
      "0.14\n",
      "0.134\n",
      "0.16\n"
     ]
    }
   ],
   "source": [
    "for lam in np.linspace(0, 1, 5):\n",
    "    print(run_SIS_simulation(g, 0.3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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