lluang · December 20, 2015 03:59
diff --git a/Community Volunteer Retention.ipynb b/Community Volunteer Retention.ipynb
 {
 "metadata": {
  "name": "Volunteer retention simulation"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Disaster Reponse Volunteer Retention\n",
      "\n",
      "- Overview, Design concept, and Details protocol\n",
      "- Louis Luangkesorn\n",
      "\n",
      "## Problem        \n",
      "        \n",
      "-  Much of community disaster response is based on the use of community volunteers who provide additional capability when the standing emergency response capacity is overwhelmed.\n",
      "\n",
      "-  Community volunteer recruitment and retention is often influenced by the frequency and level of activity.\n",
      "\n",
      "-  Objective: Explore the effect of the number of teams on the ability of response teams to recruit and retain volunteers.          \n",
      "\n",
      "--\n",
      "\n",
      "## Model formulation                  \n",
      "                \n",
      "-  A given region has a random number of disasters per year that require a random number of response teams (one lead, and random number of support teams)\n",
      "-  Actual responses (lead or support) lead to improved publicity in the community and improved recruitment.\n",
      "-  Too many responses lead to burnout.\n",
      "-  Teams can respond as a lead or support.\n",
      "-  Only teams of a minimum size can be a lead team.\n",
      "\n",
      "##  Purpose\n",
      "\n",
      "-  To evaluate the effect of the number and concentration of teams on team recruitment and retention.\n",
      "\n",
      "-  Project is motivated on the experiences of Community Evacuation Center Teams associated with the Western Pennsylvania Red Cross\n",
      "\n",
      "--\n",
      "\n",
      "##  Entities, State Variables, and Scales\n",
      "\n",
      "-  Entities\n",
      "\t-  Potential volunteers\n",
      "\t-  Teams\n",
      "\t-  Coordinator\n",
      "-  State variables\n",
      "\t-  Historical responses\n",
      "-  Scale\n",
      "\t-  Annual\n",
      "\n",
      "--\n",
      "\n",
      "##  Process Overview and Scheduling\n",
      "\n",
      "-  Teams recruit a random number of volunteers. Influenced by historical activity.\n",
      "-  Team members drop out of the team.\n",
      "-  Incidents occur during the year.\n",
      "\t-  Coordinator chooses a lead team and responding teams.\n",
      "\t-  For each incident a lead team is chosen from the teams of a minimum size.\n",
      "\t-  Each incident is of random size which determines how the size of the required volunteer base.\n",
      "\t-  Support teams can be chosen from any other teams until the volunteer base is reached.\n",
      "\t-  Teams can refuse a call.  Usually based on number of responders and if team feels it has been too busy.\n"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from random import randint, random\n",
      "import numpy as np\n",
      "import matplotlib.pyplot as plt\n",
      "import matplotlib.cm as cm\n",
      "import scipy"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def teamsrequired(numyears, avgincidentsperyear = 2.5, avgresponse = 20):\n",
      "    ''' Generate the sequence of teams needed per year\n",
      "        \n",
      "        Input:\n",
      "            -  Number of years\n",
      "            -  Average number of incidents per year\n",
      "            -  Average number of people required per incident (must be greater than 1)\n",
      "        Output:\n",
      "            -  List of years where each year has the number of teams requried for each incident.\n",
      "    '''\n",
      "    annualdisasters = scipy.random.poisson(float(avgincidentsperyear), numyears)\n",
      "    teamscalled = [scipy.random.poisson(avgresponse-1, annualdisasters[year])+1 for year in range(len(annualdisasters))]\n",
      "    return annualdisasters, teamscalled"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "numberyears = 25\n",
      "disasters, teams = teamsrequired(numberyears)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "disasters"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "array([3, 4, 3, 5, 3, 0, 2, 3, 1, 4, 3, 1, 1, 3, 5, 2, 2, 0, 4, 1, 5, 2, 1,\n",
        "       3, 3])"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "teams"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "[array([28, 22, 18]),\n",
        " array([27, 19, 20, 18]),\n",
        " array([19, 22, 19]),\n",
        " array([26, 14, 18, 17, 18]),\n",
        " array([19, 23, 20]),\n",
        " array([], dtype=int64),\n",
        " array([19, 11]),\n",
        " array([21, 15, 18]),\n",
        " array([14]),\n",
        " array([24, 21, 19, 20]),\n",
        " array([23, 21, 19]),\n",
        " array([20]),\n",
        " array([26]),\n",
        " array([21, 17, 16]),\n",
        " array([17, 16, 18, 13, 27]),\n",
        " array([17, 27]),\n",
        " array([26, 19]),\n",
        " array([], dtype=int64),\n",
        " array([16, 26, 25, 18]),\n",
        " array([25]),\n",
        " array([27, 20, 22, 15, 29]),\n",
        " array([26, 14]),\n",
        " array([21]),\n",
        " array([22, 16, 27]),\n",
        " array([22, 19, 23])]"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Team retention and recruitment\n",
      "\n",
      "Each team can draw from a fixed population.  Each team starts with a certain number of members.\n",
      "Each year, members randomly enter and leave the system.\n",
      "\n",
      "**To add**: $p_{retain}$ and $p_{recruit}$ should be functions of the size of the team and incidents called"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "numberteams = 20\n",
      "sourcepopulation = 50\n",
      "minsizelead = 6\n",
      "avginitial = 8.5\n",
      "pretain = 0.8\n",
      "precruit = 0.05\n",
      "fractioninitial = float(avginitial)/float(sourcepopulation)\n",
      "neighborhood = scipy.random.binomial(1, fractioninitial, [1, int(numberteams), int(sourcepopulation)])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def individualchoice(current, pretain, precruit):\n",
      "    '''  Model the individual person decision to remain on a team or leave\n",
      "    '''\n",
      "    if current == 1:\n",
      "        next = scipy.random.binomial(1, pretain)\n",
      "    else:\n",
      "        next = scipy.random.binomial(1, precruit)\n",
      "    return next\n",
      "\n",
      "def updateteams(neighborhood, pretain, precruit):\n",
      "    '''  For each team, model the decisions of people within the team to leave within.\n",
      "    '''\n",
      "    \n",
      "    newneighborhood = scipy.zeros(shape(neighborhood))\n",
      "    for team in range(len(neighborhood)):\n",
      "        nextyear = [individualchoice(neighborhood[team][i], pretain, precruit) for i in range(len(neighborhood[team]))]\n",
      "        newneighborhood[team] = nextyear\n",
      "        #print nextyear\n",
      "    #print sum(newneighborhood), newneighborhood\n",
      "    return [newneighborhood]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nextround = updateteams(neighborhood[0], pretain, precruit)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "for i in range(numberyears):\n",
      "    nextround = updateteams(nextround[0], pretain, precruit)\n",
      "    neighborhood= vstack((neighborhood, nextround))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Assignment of teams to incidents\n",
      "\n",
      "Each incident has a minimum size.  Add teams until the sum of members of teams reaches that size"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "timeindex = len(neighborhood)\n",
      "timeindex\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "26"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "currentteamsize = [[int(sum(neighborhood[yearindex][i])) for i in range(len(neighborhood[0]))] for yearindex in range(timeindex)]\n",
      "currentteamsize"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "[[14, 5, 10, 11, 8, 12, 8, 8, 9, 4, 9, 10, 8, 10, 5, 5, 12, 7, 6, 8],\n",
        " [13, 10, 11, 9, 13, 7, 5, 8, 9, 10, 9, 10, 9, 11, 5, 6, 11, 12, 12, 9],\n",
        " [13, 11, 9, 10, 17, 8, 7, 12, 8, 7, 10, 8, 10, 14, 7, 4, 10, 13, 10, 7],\n",
        " [13, 12, 12, 6, 14, 8, 4, 11, 10, 8, 10, 9, 11, 15, 8, 6, 10, 10, 10, 6],\n",
        " [12, 8, 10, 4, 11, 9, 6, 7, 9, 8, 7, 9, 11, 13, 10, 7, 12, 7, 11, 6],\n",
        " [13, 8, 11, 5, 12, 9, 9, 7, 6, 6, 7, 11, 8, 10, 12, 9, 14, 8, 11, 9],\n",
        " [12, 7, 13, 7, 16, 7, 7, 8, 7, 11, 6, 13, 12, 7, 12, 9, 10, 8, 9, 10],\n",
        " [14, 8, 15, 8, 16, 7, 6, 7, 6, 11, 8, 12, 13, 8, 12, 8, 8, 8, 9, 11],\n",
        " [14, 9, 18, 9, 15, 8, 7, 6, 7, 11, 7, 9, 12, 10, 11, 8, 7, 7, 10, 11],\n",
        " [12, 7, 16, 10, 14, 5, 8, 5, 9, 10, 8, 9, 12, 13, 12, 9, 6, 8, 8, 12],\n",
        " [9, 7, 15, 11, 13, 4, 9, 8, 7, 10, 7, 7, 11, 14, 11, 8, 8, 9, 7, 12],\n",
        " [8, 7, 11, 8, 14, 4, 5, 3, 4, 11, 8, 8, 9, 15, 9, 8, 7, 13, 6, 10],\n",
        " [7, 8, 12, 9, 14, 7, 9, 6, 9, 12, 6, 7, 10, 14, 7, 8, 6, 12, 5, 8],\n",
        " [5, 11, 12, 10, 17, 6, 10, 6, 8, 10, 6, 6, 9, 10, 7, 7, 6, 11, 5, 8],\n",
        " [7, 11, 12, 12, 13, 5, 10, 9, 7, 9, 7, 5, 9, 11, 8, 9, 6, 6, 5, 6],\n",
        " [6, 8, 13, 11, 12, 5, 12, 7, 9, 9, 7, 7, 6, 8, 13, 9, 8, 5, 4, 6],\n",
        " [9, 12, 12, 12, 11, 8, 11, 6, 9, 11, 6, 7, 8, 7, 13, 10, 8, 5, 3, 8],\n",
        " [7, 9, 14, 11, 12, 9, 12, 6, 9, 9, 6, 11, 5, 9, 11, 9, 9, 4, 6, 6],\n",
        " [9, 10, 13, 9, 9, 13, 14, 5, 6, 9, 7, 11, 7, 10, 12, 10, 9, 5, 7, 7],\n",
        " [11, 12, 15, 11, 11, 11, 10, 4, 8, 11, 7, 12, 5, 9, 12, 11, 7, 9, 6, 7],\n",
        " [11, 12, 12, 9, 6, 15, 11, 6, 8, 13, 5, 9, 6, 9, 9, 13, 7, 12, 8, 6],\n",
        " [13, 10, 12, 8, 7, 12, 9, 8, 5, 10, 8, 7, 7, 11, 12, 11, 6, 9, 12, 6],\n",
        " [13, 8, 13, 5, 4, 14, 12, 7, 8, 9, 9, 7, 9, 10, 11, 13, 6, 8, 11, 9],\n",
        " [12, 6, 12, 8, 3, 14, 12, 10, 8, 6, 10, 6, 8, 9, 10, 16, 5, 7, 7, 10],\n",
        " [12, 7, 15, 7, 7, 14, 13, 10, 5, 5, 9, 6, 6, 8, 8, 13, 5, 8, 7, 8],\n",
        " [14, 15, 14, 9, 7, 11, 13, 12, 7, 5, 9, 7, 6, 8, 6, 13, 6, 5, 9, 11]]"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#  Data visualization\n",
      "\n",
      "Use a grid that shows how many members are in each team over time"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# From the Matplotlib gallery http://matplotlib.org/examples/api/image_zcoord.html\n",
      "def format_coord(x, y):\n",
      "    col = int(x+0.5)\n",
      "    row = int(y+0.5)\n",
      "    if col>=0 and col<numcols and row>=0 and row<numrows:\n",
      "        z = X[row,col]\n",
      "        return 'x=%1.4f, y=%1.4f, z=%1.4f'%(x, y, z)\n",
      "    else:\n",
      "        return 'x=%1.4f, y=%1.4f'%(x, y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "X = currentteamsize\n",
      "\n",
      "fig = plt.figure()\n",
      "ax = fig.add_subplot(111)\n",
      "ax.imshow(X, cmap=cm.jet, interpolation='nearest')\n",
      "numrows, numcols = shape(X)\n",
      "ax.format_coord = format_coord\n",
      "plt.xlabel('Team')\n",
      "plt.ylabel('Year')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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      }
     ],
     "prompt_number": 13
    }
   ],
   "metadata": {}
  }
 ]
 }
	{
	"metadata": {
	"name": "Volunteer retention simulation"
	},
	"nbformat": 3,
	"nbformat_minor": 0,
	"worksheets": [
	{
	"cells": [
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"# Disaster Reponse Volunteer Retention\n",
	"\n",
	"- Overview, Design concept, and Details protocol\n",
	"- Louis Luangkesorn\n",
	"\n",
	"## Problem \n",
	" \n",
	"- Much of community disaster response is based on the use of community volunteers who provide additional capability when the standing emergency response capacity is overwhelmed.\n",
	"\n",
	"- Community volunteer recruitment and retention is often influenced by the frequency and level of activity.\n",
	"\n",
	"- Objective: Explore the effect of the number of teams on the ability of response teams to recruit and retain volunteers. \n",
	"\n",
	"--\n",
	"\n",
	"## Model formulation \n",
	" \n",
	"- A given region has a random number of disasters per year that require a random number of response teams (one lead, and random number of support teams)\n",
	"- Actual responses (lead or support) lead to improved publicity in the community and improved recruitment.\n",
	"- Too many responses lead to burnout.\n",
	"- Teams can respond as a lead or support.\n",
	"- Only teams of a minimum size can be a lead team.\n",
	"\n",
	"## Purpose\n",
	"\n",
	"- To evaluate the effect of the number and concentration of teams on team recruitment and retention.\n",
	"\n",
	"- Project is motivated on the experiences of Community Evacuation Center Teams associated with the Western Pennsylvania Red Cross\n",
	"\n",
	"--\n",
	"\n",
	"## Entities, State Variables, and Scales\n",
	"\n",
	"- Entities\n",
	"\t- Potential volunteers\n",
	"\t- Teams\n",
	"\t- Coordinator\n",
	"- State variables\n",
	"\t- Historical responses\n",
	"- Scale\n",
	"\t- Annual\n",
	"\n",
	"--\n",
	"\n",
	"## Process Overview and Scheduling\n",
	"\n",
	"- Teams recruit a random number of volunteers. Influenced by historical activity.\n",
	"- Team members drop out of the team.\n",
	"- Incidents occur during the year.\n",
	"\t- Coordinator chooses a lead team and responding teams.\n",
	"\t- For each incident a lead team is chosen from the teams of a minimum size.\n",
	"\t- Each incident is of random size which determines how the size of the required volunteer base.\n",
	"\t- Support teams can be chosen from any other teams until the volunteer base is reached.\n",
	"\t- Teams can refuse a call. Usually based on number of responders and if team feels it has been too busy.\n"
	]
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"from random import randint, random\n",
	"import numpy as np\n",
	"import matplotlib.pyplot as plt\n",
	"import matplotlib.cm as cm\n",
	"import scipy"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 1
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"def teamsrequired(numyears, avgincidentsperyear = 2.5, avgresponse = 20):\n",
	" ''' Generate the sequence of teams needed per year\n",
	" \n",
	" Input:\n",
	" - Number of years\n",
	" - Average number of incidents per year\n",
	" - Average number of people required per incident (must be greater than 1)\n",
	" Output:\n",
	" - List of years where each year has the number of teams requried for each incident.\n",
	" '''\n",
	" annualdisasters = scipy.random.poisson(float(avgincidentsperyear), numyears)\n",
	" teamscalled = [scipy.random.poisson(avgresponse-1, annualdisasters[year])+1 for year in range(len(annualdisasters))]\n",
	" return annualdisasters, teamscalled"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 2
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"numberyears = 25\n",
	"disasters, teams = teamsrequired(numberyears)"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 3
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"disasters"
	],
	"language": "python",
	"metadata": {},
	"outputs": [
	{
	"output_type": "pyout",
	"prompt_number": 4,
	"text": [
	"array([3, 4, 3, 5, 3, 0, 2, 3, 1, 4, 3, 1, 1, 3, 5, 2, 2, 0, 4, 1, 5, 2, 1,\n",
	" 3, 3])"
	]
	}
	],
	"prompt_number": 4
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"teams"
	],
	"language": "python",
	"metadata": {},
	"outputs": [
	{
	"output_type": "pyout",
	"prompt_number": 5,
	"text": [
	"[array([28, 22, 18]),\n",
	" array([27, 19, 20, 18]),\n",
	" array([19, 22, 19]),\n",
	" array([26, 14, 18, 17, 18]),\n",
	" array([19, 23, 20]),\n",
	" array([], dtype=int64),\n",
	" array([19, 11]),\n",
	" array([21, 15, 18]),\n",
	" array([14]),\n",
	" array([24, 21, 19, 20]),\n",
	" array([23, 21, 19]),\n",
	" array([20]),\n",
	" array([26]),\n",
	" array([21, 17, 16]),\n",
	" array([17, 16, 18, 13, 27]),\n",
	" array([17, 27]),\n",
	" array([26, 19]),\n",
	" array([], dtype=int64),\n",
	" array([16, 26, 25, 18]),\n",
	" array([25]),\n",
	" array([27, 20, 22, 15, 29]),\n",
	" array([26, 14]),\n",
	" array([21]),\n",
	" array([22, 16, 27]),\n",
	" array([22, 19, 23])]"
	]
	}
	],
	"prompt_number": 5
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"# Team retention and recruitment\n",
	"\n",
	"Each team can draw from a fixed population. Each team starts with a certain number of members.\n",
	"Each year, members randomly enter and leave the system.\n",
	"\n",
	"To add: $p_{retain}$ and $p_{recruit}$ should be functions of the size of the team and incidents called"
	]
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"numberteams = 20\n",
	"sourcepopulation = 50\n",
	"minsizelead = 6\n",
	"avginitial = 8.5\n",
	"pretain = 0.8\n",
	"precruit = 0.05\n",
	"fractioninitial = float(avginitial)/float(sourcepopulation)\n",
	"neighborhood = scipy.random.binomial(1, fractioninitial, [1, int(numberteams), int(sourcepopulation)])"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 6
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"def individualchoice(current, pretain, precruit):\n",
	" ''' Model the individual person decision to remain on a team or leave\n",
	" '''\n",
	" if current == 1:\n",
	" next = scipy.random.binomial(1, pretain)\n",
	" else:\n",
	" next = scipy.random.binomial(1, precruit)\n",
	" return next\n",
	"\n",
	"def updateteams(neighborhood, pretain, precruit):\n",
	" ''' For each team, model the decisions of people within the team to leave within.\n",
	" '''\n",
	" \n",
	" newneighborhood = scipy.zeros(shape(neighborhood))\n",
	" for team in range(len(neighborhood)):\n",
	" nextyear = [individualchoice(neighborhood[team][i], pretain, precruit) for i in range(len(neighborhood[team]))]\n",
	" newneighborhood[team] = nextyear\n",
	" #print nextyear\n",
	" #print sum(newneighborhood), newneighborhood\n",
	" return [newneighborhood]"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 7
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"nextround = updateteams(neighborhood[0], pretain, precruit)"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 8
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"for i in range(numberyears):\n",
	" nextround = updateteams(nextround[0], pretain, precruit)\n",
	" neighborhood= vstack((neighborhood, nextround))"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 9
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"# Assignment of teams to incidents\n",
	"\n",
	"Each incident has a minimum size. Add teams until the sum of members of teams reaches that size"
	]
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"timeindex = len(neighborhood)\n",
	"timeindex\n"
	],
	"language": "python",
	"metadata": {},
	"outputs": [
	{
	"output_type": "pyout",
	"prompt_number": 10,
	"text": [
	"26"
	]
	}
	],
	"prompt_number": 10
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"currentteamsize = [[int(sum(neighborhood[yearindex][i])) for i in range(len(neighborhood[0]))] for yearindex in range(timeindex)]\n",
	"currentteamsize"
	],
	"language": "python",
	"metadata": {},
	"outputs": [
	{
	"output_type": "pyout",
	"prompt_number": 11,
	"text": [
	"[[14, 5, 10, 11, 8, 12, 8, 8, 9, 4, 9, 10, 8, 10, 5, 5, 12, 7, 6, 8],\n",
	" [13, 10, 11, 9, 13, 7, 5, 8, 9, 10, 9, 10, 9, 11, 5, 6, 11, 12, 12, 9],\n",
	" [13, 11, 9, 10, 17, 8, 7, 12, 8, 7, 10, 8, 10, 14, 7, 4, 10, 13, 10, 7],\n",
	" [13, 12, 12, 6, 14, 8, 4, 11, 10, 8, 10, 9, 11, 15, 8, 6, 10, 10, 10, 6],\n",
	" [12, 8, 10, 4, 11, 9, 6, 7, 9, 8, 7, 9, 11, 13, 10, 7, 12, 7, 11, 6],\n",
	" [13, 8, 11, 5, 12, 9, 9, 7, 6, 6, 7, 11, 8, 10, 12, 9, 14, 8, 11, 9],\n",
	" [12, 7, 13, 7, 16, 7, 7, 8, 7, 11, 6, 13, 12, 7, 12, 9, 10, 8, 9, 10],\n",
	" [14, 8, 15, 8, 16, 7, 6, 7, 6, 11, 8, 12, 13, 8, 12, 8, 8, 8, 9, 11],\n",
	" [14, 9, 18, 9, 15, 8, 7, 6, 7, 11, 7, 9, 12, 10, 11, 8, 7, 7, 10, 11],\n",
	" [12, 7, 16, 10, 14, 5, 8, 5, 9, 10, 8, 9, 12, 13, 12, 9, 6, 8, 8, 12],\n",
	" [9, 7, 15, 11, 13, 4, 9, 8, 7, 10, 7, 7, 11, 14, 11, 8, 8, 9, 7, 12],\n",
	" [8, 7, 11, 8, 14, 4, 5, 3, 4, 11, 8, 8, 9, 15, 9, 8, 7, 13, 6, 10],\n",
	" [7, 8, 12, 9, 14, 7, 9, 6, 9, 12, 6, 7, 10, 14, 7, 8, 6, 12, 5, 8],\n",
	" [5, 11, 12, 10, 17, 6, 10, 6, 8, 10, 6, 6, 9, 10, 7, 7, 6, 11, 5, 8],\n",
	" [7, 11, 12, 12, 13, 5, 10, 9, 7, 9, 7, 5, 9, 11, 8, 9, 6, 6, 5, 6],\n",
	" [6, 8, 13, 11, 12, 5, 12, 7, 9, 9, 7, 7, 6, 8, 13, 9, 8, 5, 4, 6],\n",
	" [9, 12, 12, 12, 11, 8, 11, 6, 9, 11, 6, 7, 8, 7, 13, 10, 8, 5, 3, 8],\n",
	" [7, 9, 14, 11, 12, 9, 12, 6, 9, 9, 6, 11, 5, 9, 11, 9, 9, 4, 6, 6],\n",
	" [9, 10, 13, 9, 9, 13, 14, 5, 6, 9, 7, 11, 7, 10, 12, 10, 9, 5, 7, 7],\n",
	" [11, 12, 15, 11, 11, 11, 10, 4, 8, 11, 7, 12, 5, 9, 12, 11, 7, 9, 6, 7],\n",
	" [11, 12, 12, 9, 6, 15, 11, 6, 8, 13, 5, 9, 6, 9, 9, 13, 7, 12, 8, 6],\n",
	" [13, 10, 12, 8, 7, 12, 9, 8, 5, 10, 8, 7, 7, 11, 12, 11, 6, 9, 12, 6],\n",
	" [13, 8, 13, 5, 4, 14, 12, 7, 8, 9, 9, 7, 9, 10, 11, 13, 6, 8, 11, 9],\n",
	" [12, 6, 12, 8, 3, 14, 12, 10, 8, 6, 10, 6, 8, 9, 10, 16, 5, 7, 7, 10],\n",
	" [12, 7, 15, 7, 7, 14, 13, 10, 5, 5, 9, 6, 6, 8, 8, 13, 5, 8, 7, 8],\n",
	" [14, 15, 14, 9, 7, 11, 13, 12, 7, 5, 9, 7, 6, 8, 6, 13, 6, 5, 9, 11]]"
	]
	}
	],
	"prompt_number": 11
	},
	{
	"cell_type": "markdown",
	"metadata": {},
	"source": [
	"# Data visualization\n",
	"\n",
	"Use a grid that shows how many members are in each team over time"
	]
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"# From the Matplotlib gallery http://matplotlib.org/examples/api/image_zcoord.html\n",
	"def format_coord(x, y):\n",
	" col = int(x+0.5)\n",
	" row = int(y+0.5)\n",
	" if col>=0 and col<numcols and row>=0 and row<numrows:\n",
	" z = X[row,col]\n",
	" return 'x=%1.4f, y=%1.4f, z=%1.4f'%(x, y, z)\n",
	" else:\n",
	" return 'x=%1.4f, y=%1.4f'%(x, y)"
	],
	"language": "python",
	"metadata": {},
	"outputs": [],
	"prompt_number": 12
	},
	{
	"cell_type": "code",
	"collapsed": false,
	"input": [
	"X = currentteamsize\n",
	"\n",
	"fig = plt.figure()\n",
	"ax = fig.add_subplot(111)\n",
	"ax.imshow(X, cmap=cm.jet, interpolation='nearest')\n",
	"numrows, numcols = shape(X)\n",
	"ax.format_coord = format_coord\n",
	"plt.xlabel('Team')\n",
	"plt.ylabel('Year')\n",
	"plt.show()"
	],
	"language": "python",
	"metadata": {},
	"outputs": [
	{
	"output_type": "display_data",
	"png": 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	}
	],
	"prompt_number": 13
	}
	],
	"metadata": {}
	}
	]
	}