advanced tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from mesa import Agent, Model\n",
    "from mesa.time import RandomActivation\n",
    "import random\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from mesa.space import MultiGrid\n",
    "import numpy as np\n",
    "from mesa.datacollection import DataCollector\n",
    "from mesa.batchrunner import BatchRunner\n",
    "from mesa.visualization.modules import CanvasGrid\n",
    "from mesa.visualization.ModularVisualization import ModularServer\n",
    "from mesa.visualization.modules import ChartModule\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def compute_gini(model):\n",
    "    agent_wealths = [agent.wealth for agent in model.schedule.agents]\n",
    "    x = sorted(agent_wealths)\n",
    "    N = model.num_agents\n",
    "    B = sum( xi * (N-i) for i,xi in enumerate(x) ) / (N*sum(x))\n",
    "    return (1 + (1/N) - 2*B)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class MoneyAgent(Agent):\n",
    "    \"\"\"An agent with fixed initial wealth.\"\"\"\n",
    "    def __init__(self, unique_id, model):\n",
    "        super().__init__(unique_id, model)\n",
    "        self.wealth = 1\n",
    "        \n",
    "    # agent move to cell based on moore neighborhood\n",
    "    def move(self):\n",
    "        possible_steps = self.model.grid.get_neighborhood(\n",
    "            self.pos,\n",
    "            moore=True,\n",
    "            include_center=False)\n",
    "        new_position = random.choice(possible_steps)\n",
    "        self.model.grid.move_agent(self, new_position) \n",
    "    \n",
    "    # interact with agents in grid\n",
    "    def give_money(self):\n",
    "        cellmates = self.model.grid.get_cell_list_contents([self.pos])\n",
    "        if len(cellmates) > 1:\n",
    "            other = random.choice(cellmates)\n",
    "            other.wealth += 1\n",
    "            self.wealth -= 1\n",
    "    \n",
    "    # Agent steps  \n",
    "    def step(self):\n",
    "        self.move()\n",
    "        if self.wealth > 0:\n",
    "            self.give_money()\n",
    "    \n",
    "    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class MoneyModel(Model):\n",
    "    \"\"\"A model with some number of agents.\"\"\"\n",
    "    def __init__(self, N, width, height):\n",
    "        self.num_agents = N\n",
    "        self.grid = MultiGrid(width, height, True)\n",
    "        self.schedule = RandomActivation(self)\n",
    "        self.running = True\n",
    "        \n",
    "        # Create agents\n",
    "        for i in range(self.num_agents):\n",
    "            a = MoneyAgent(i, self)\n",
    "            self.schedule.add(a)\n",
    "            \n",
    "            # Add the agent to a random grid cell\n",
    "            x = random.randrange(self.grid.width)\n",
    "            y = random.randrange(self.grid.height)\n",
    "            self.grid.place_agent(a, (x, y))\n",
    "    \n",
    "        self.datacollector = DataCollector(\n",
    "            model_reporters={\"Gini\": compute_gini},\n",
    "            agent_reporters={\"Wealth\": lambda a: a.wealth})\n",
    "        \n",
    "    def step(self):\n",
    "        self.datacollector.collect(self)\n",
    "        '''Advance the model by one step.'''\n",
    "        self.schedule.step()\n",
    "        \n",
    "        \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = MoneyModel(50, 10, 10)\n",
    "for i in range(20):\n",
    "    model.step()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x220a548d828>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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7NJLUSU4GkCS1anyGzkw0ktRJ9mgkSa2yRyNJatX49GicdSZJapU9GknqJIfO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\nJLXKRCNJapWJRpLUKhONJKlV/x9oy2t2pQ4/2gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x220a539e550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "agent_counts = np.zeros((model.grid.width, model.grid.height))\n",
    "for cell in model.grid.coord_iter():\n",
    "    cell_content, x, y = cell\n",
    "    agent_count = len(cell_content)\n",
    "    agent_counts[x][y] = agent_count\n",
    "plt.imshow(agent_counts, interpolation='nearest')\n",
    "plt.colorbar()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "model = MoneyModel(50, 10, 10)\n",
    "for i in range(100):\n",
    "    model.step()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def agent_portrayal(agent):\n",
    "    portrayal = {\"Shape\": \"circle\",\n",
    "                 \"Color\": \"red\",\n",
    "                 \"Filled\": \"true\",\n",
    "                 \"Layer\": 0,\n",
    "                 \"r\": 0.5}\n",
    "    \n",
    "    \n",
    "    if agent.wealth > 0:\n",
    "        portrayal[\"Color\"] = \"red\"\n",
    "        portrayal[\"Layer\"] = 0\n",
    "    else:\n",
    "        portrayal[\"Color\"] = \"grey\"\n",
    "        portrayal[\"Layer\"] = 1\n",
    "        portrayal[\"r\"] = 0.2\n",
    "    return portrayal\n",
    "    \n",
    "    \n",
    "    return portrayal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "grid = CanvasGrid(agent_portrayal, 10, 10, 500, 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Interface starting at http://127.0.0.1:8889\n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "IOLoop is already running",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-b57517a62713>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      9\u001b[0m                        100, 10, 10)\n\u001b[1;32m     10\u001b[0m \u001b[0mserver\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mport\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m8889\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mserver\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32mC:\\Users\\Tom\\Anaconda3\\lib\\site-packages\\mesa\\visualization\\ModularVisualization.py\u001b[0m in \u001b[0;36mlaunch\u001b[0;34m(self, port)\u001b[0m\n\u001b[1;32m    282\u001b[0m         \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Interface starting at http://127.0.0.1:{PORT}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mPORT\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mport\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    283\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlisten\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mport\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 284\u001b[0;31m         \u001b[0mtornado\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mioloop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mIOLoop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32mC:\\Users\\Tom\\Anaconda3\\lib\\site-packages\\zmq\\eventloop\\ioloop.py\u001b[0m in \u001b[0;36mstart\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    160\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mstart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    161\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 162\u001b[0;31m             \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mZMQIOLoop\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    163\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mZMQError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    164\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0merrno\u001b[0m \u001b[1;33m==\u001b[0m \u001b[0mETERM\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\Tom\\Anaconda3\\lib\\site-packages\\tornado\\ioloop.py\u001b[0m in \u001b[0;36mstart\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    750\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mstart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    751\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_running\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m--> 752\u001b[0;31m             \u001b[1;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"IOLoop is already running\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    753\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_setup_logging\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m    754\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_stopped\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mRuntimeError\u001b[0m: IOLoop is already running"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Socket opened!\n",
      "{\"type\":\"reset\"}\n",
      "{\"type\":\"get_step\",\"step\":1}\n",
      "{\"type\":\"get_step\",\"step\":2}\n",
      "{\"type\":\"get_step\",\"step\":3}\n",
      "{\"type\":\"get_step\",\"step\":4}\n",
      "{\"type\":\"get_step\",\"step\":5}\n",
      "{\"type\":\"get_step\",\"step\":6}\n",
      "{\"type\":\"get_step\",\"step\":7}\n",
      "{\"type\":\"get_step\",\"step\":8}\n",
      "{\"type\":\"get_step\",\"step\":9}\n",
      "{\"type\":\"get_step\",\"step\":10}\n",
      "{\"type\":\"get_step\",\"step\":11}\n",
      "{\"type\":\"get_step\",\"step\":12}\n",
      "{\"type\":\"get_step\",\"step\":13}\n",
      "{\"type\":\"get_step\",\"step\":14}\n",
      "{\"type\":\"get_step\",\"step\":15}\n",
      "{\"type\":\"get_step\",\"step\":16}\n",
      "{\"type\":\"get_step\",\"step\":17}\n",
      "{\"type\":\"get_step\",\"step\":18}\n",
      "{\"type\":\"get_step\",\"step\":19}\n",
      "{\"type\":\"get_step\",\"step\":20}\n",
      "{\"type\":\"get_step\",\"step\":21}\n",
      "{\"type\":\"get_step\",\"step\":22}\n",
      "{\"type\":\"get_step\",\"step\":23}\n",
      "{\"type\":\"get_step\",\"step\":24}\n",
      "{\"type\":\"get_step\",\"step\":25}\n"
     ]
    }
   ],
   "source": [
    "\n",
    "chart = ChartModule([{\"Label\": \"Gini\",\n",
    "                      \"Color\": \"Black\"}],\n",
    "                    data_collector_name='datacollector')\n",
    "\n",
    "server = ModularServer(MoneyModel,\n",
    "                       [grid],\n",
    "                       \"Money Model\",\n",
    "                       100, 10, 10)\n",
    "server.port = 8889\n",
    "server.launch()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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