Project 2nice.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project 2\n",
    "\n",
    "Copyright 2017 Eamon and Lydia\n",
    "\n",
    "Git ass\n",
    "\n",
    "License: [Creative Commons Attribution 4.0 International](https://creativecommons.org/licenses/by/4.0)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from modsim import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "init = State(temp=82)\n",
    "#ideal_temp = 57"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "coffee = System(init=init,\n",
    "                volume=300,\n",
    "                r=0.01,\n",
    "                T_env=22,\n",
    "                T_fridge=1.6,\n",
    "                T_freezer=-18,\n",
    "                t0=0,\n",
    "                t_f_in=10,\n",
    "                t_end=30,\n",
    "                dt=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def update_air(state, system):\n",
    "    \"\"\"update_air the thermal transfer model.\n",
    "    \n",
    "    state: State (temp)\n",
    "    system: System object\n",
    "    \n",
    "    returns: State (temp)\n",
    "    \"\"\"\n",
    "    unpack(system)\n",
    "    T = state.temp\n",
    "    T += -r * (T - T_env) * dt\n",
    "\n",
    "    return State(temp=T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def update_fridge(state, system):\n",
    "    \"\"\"update_air the thermal transfer model.\n",
    "    \n",
    "    state: State (temp)\n",
    "    system: System object\n",
    "    \n",
    "    returns: State (temp)\n",
    "    \"\"\"\n",
    "    unpack(system)\n",
    "    T = state.temp\n",
    "    T += -r * (T - T_fridge) * dt\n",
    "\n",
    "    return State(temp=T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def update_freezer(state, system):\n",
    "    \"\"\"update_air the thermal transfer model.\n",
    "    \n",
    "    state: State (temp)\n",
    "    system: System object\n",
    "    \n",
    "    returns: State (temp)\n",
    "    \"\"\"\n",
    "    unpack(system)\n",
    "    T = state.temp\n",
    "    T += -r * (T - T_freezer) * dt\n",
    "\n",
    "    return State(temp=T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def run_simulation(system, update1, update2, t_f_out):\n",
    "    \"\"\"Runs a simulation of the system.\n",
    "    \n",
    "    Add a TimeFrame to the System: results\n",
    "    \n",
    "    system: System object\n",
    "    update_air_func: function that update_airs state\n",
    "    \"\"\"\n",
    "    unpack(system)\n",
    "    \n",
    "    frame = TimeFrame(columns=init.index)\n",
    "    frame.loc[t0] = init\n",
    "    ts = linrange(t0, t_end-dt, dt)\n",
    "    \n",
    "    for t in ts:\n",
    "        if t < t_f_in:\n",
    "            frame.loc[t+dt] = update1(frame.loc[t], system)\n",
    "        else:\n",
    "            if t < t_f_out:\n",
    "                frame.loc[t+dt] = update2(frame.loc[t], system)\n",
    "            else:\n",
    "                frame.loc[t+dt] = update1(frame.loc[t], system)\n",
    "    \n",
    "    results = frame\n",
    "    return results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def final_temp(system):\n",
    "    \"\"\"Final temperature.\n",
    "    \n",
    "    If system has no results, return initial temp.\n",
    "    \n",
    "    system: System object.\n",
    "    \n",
    "    returns: temperature (degC)\n",
    "    \"\"\"    \n",
    "    if hasattr(system, 'results'):\n",
    "        return system.results.temp[system.t_end]\n",
    "    else:\n",
    "        return 'No results'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    " def sweep_simulation(system, update1, update2):\n",
    "        sweep = SweepSeries()\n",
    "        unpack(system)\n",
    "        t_f_out_array = linrange(t_f_in, t_end, dt)\n",
    "        \n",
    "        for time in t_f_out_array:\n",
    "            sim = run_simulation(system=system, update1=update1, update2=update2, t_f_out=time)\n",
    "            sweep[time] = sim.temp[t_end]\n",
    "        return sweep"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's how we use it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "sim = run_simulation(coffee, update_air, update_freezer, 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
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2wCKKchK9Y+drO9jzYS1jY+M+rEwk8N3OVMwmoNFaWzZ50BhzzBjz4ynPXQs0XCfwRbyc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\nFOwiIkHm/wMG2X7iU8zblAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x25f951f5588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(sim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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sTmpSsItIyImNjmD94kmsXjCRyAjPSU0uF5+creTtvcXcamjxc4WDS8EuIiHJ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\n/1dq96QPL/bTAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x25f954072e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sweep1 = sweep_simulation(coffee, update_air, update_fridge)\n",
    "plot(sweep1)"
   ]
  },
  {
   "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": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}