{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CSCS530 Winter 2015\n",
    "#### Complex Systems 530 - Computer Modeling of Complex Systems (Winter 2015)\n",
    "\n",
    "  * Course ID: CMPLXSYS 530\n",
    "  * Course Title: Computer Modeling of Complex Systems\n",
    "  * Term: Winter 2015\n",
    "  * Schedule: Wednesdays and Friday, 1:00-2:30PM ET\n",
    "  * Location: 120 West Hall (http://www.lsa.umich.edu/cscs/research/computerlab)\n",
    "  * Teachers: [Mike Bommarito](https://www.linkedin.com/in/bommarito) and [Sarah Cherng](https://www.linkedin.com/pub/sarah-cherng/35/1b7/316)\n",
    "\n",
    "#### [View this repository on NBViewer](http://nbviewer.ipython.org/github/mjbommar/cscs-530-w2015/tree/master/)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
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       "gg==\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110620c90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn; seaborn.set()\n",
    "\n",
    "# Import widget methods\n",
    "from IPython.html.widgets import *\n",
    "\n",
    "#initialNumPeople = 10 #inital number of people\n",
    "#barCapacity = 80\n",
    "#maxExitRatePerTimeStep = 5\n",
    "\n",
    "#Our goal is to measure how many people are in the bar across timesteps\n",
    "\n",
    "#create model that counts/changes number of people in the bar\n",
    "#condition to stop when we reach max timestep\n",
    "#Can simulate random number of people entering bar at some probability that changes over time\n",
    "#based on amount over/under capacity, change probability of going to bar the next timestep\n",
    "def run_simulation(initialNumPeople = 10, barCapacity=80, maxExitRatePerTimeStep = 5):\n",
    "    peopleList = []\n",
    "    minExitRatePerTimeStep = 0\n",
    "    maxTimeStep = 100\n",
    "    currentTime = 0\n",
    "    while currentTime < maxTimeStep:\n",
    "        if initialNumPeople >= barCapacity:\n",
    "            enteringPeeps = 0 #no one enters the bar if it is at full capacity\n",
    "        else:\n",
    "            enteringPeeps = int(numpy.random.normal(5,1))\n",
    "        exitingPeeps = int(numpy.random.uniform(minExitRatePerTimeStep, maxExitRatePerTimeStep))\n",
    "        if exitingPeeps > initialNumPeople+enteringPeeps:\n",
    "            exitingPeeps = 0\n",
    "        initialNumPeople = initialNumPeople + enteringPeeps - exitingPeeps        \n",
    "        peopleList.append(initialNumPeople)\n",
    "        currentTime +=1\n",
    "    \n",
    "\n",
    "    %matplotlib inline\n",
    "    f = plt.figure()\n",
    "    plt.plot(peopleList)\n",
    "    plt.xlabel('TimeStep')\n",
    "    plt.ylabel('Number of People in the Bar')\n",
    "    plt.title('Rockstar CSCS530 1st Program Yay')\n",
    "\n",
    "# Call the ipython interact() method to allow us to explore the parameters and sampling\n",
    "interact(run_simulation, initialNumPeople=(1, 200),\n",
    "         barCapacity = (1, 200),\n",
    "         maxExitRatePerTimeStep = (0, 50))\n",
    "print peopleList"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "IPython (Python 2)",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.3"
  },
  "signature": "sha256:58efcef0f1ab5736ec424cdc996381b6d1cee69647b2ef8e2d16547d59d72e62"
 },
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}