flame_debugging.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Debugging 1D solver failures\n",
    "\n",
    "This notebook shows an example where the 1D solver fails, and demonstrates the use of callbacks to diagnose the failure modes.\n",
    "This example is adapted from the bug report at https://github.com/Cantera/cantera/issues/384."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running Cantera version 2.4.0\n"
     ]
    }
   ],
   "source": [
    "import cantera as ct\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['figure.constrained_layout.use'] = True\n",
    "\n",
    "print(f\"Running Cantera version {ct.__version__}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### parameter values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "p = 50 * ct.one_atm  # pressure\n",
    "tburner = 300.0  # burner temperature\n",
    "mdot = 0.22  # kg/m^2/s\n",
    "width = 0.05  # m"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set up the problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "gas = ct.Solution('h2o2.cti')\n",
    "\n",
    "# set state to that of the unburned gas at the burner\n",
    "gas.set_equivalence_ratio(0.4, 'H2', 'O2:1.0, AR:4')\n",
    "gas.TP = tburner, p\n",
    "\n",
    "sim = ct.BurnerFlame(gas=gas, width=width)\n",
    "sim.burner.mdot = mdot\n",
    "sim.set_refine_criteria(ratio=3, slope=0.1, curve=0.2, prune=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Try to solve it..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     6.007e-06      3.742\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002309      3.011\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [7] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 \n",
      "    to resolve AR H2 H2O H2O2 HO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     7.594e-05      3.711\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [10] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 6 \n",
      "    to resolve AR H2 H2O H2O2 HO2 O O2 OH T point 6 u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001139      4.053\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [15] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 4 5 \n",
      "    to resolve AR H2 H2O H2O2 HO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001139      4.397\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.002919       3.95\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [21] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 4 5 6 7 8 9 \n",
      "    to resolve AR H2 H2O H2O2 HO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001709      4.802\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.00146      4.529\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.007389      3.828\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.001559      4.483\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.002219      4.429\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.002809      4.309\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0005925      5.096\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.004499      4.234\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002669      5.612\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.002027      4.539\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002706      5.408\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0004566      5.321\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps        0.0026      4.662\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001828       5.56\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0009256      4.844\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002471      5.426\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002085      5.811\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0007037      4.912\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002969      5.726\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0006679      5.318\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.002254      4.495\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001783      6.073\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0006018      5.327\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0006771      4.698\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.003428       4.35\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001525      5.977\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.001158      5.253\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.002606      4.497\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.008795      3.973\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01484      3.563\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02226      3.256\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.07513       2.89\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps        0.3804      2.157\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [27] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 \n",
      "    to resolve AR H2 H2O H2O2 HO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0002563      4.065\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.001946      4.364\n",
      "Attempt Newton solution of steady-state problem...    success.\n",
      "\n",
      "Problem solved on [31] point grid(s).\n",
      "\n",
      "..............................................................................\n",
      "##############################################################################\n",
      "Refining grid in flame.\n",
      "    New points inserted after grid points 0 1 2 3 4 \n",
      "    to resolve AR H2 H2O H2O2 HO2 O O2 OH T u \n",
      "##############################################################################\n",
      "\n",
      "..............................................................................\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps     0.0001709      5.071\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.001946      4.134\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps      0.006568      3.779\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.05611      2.753\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.05326      2.696\n",
      "Attempt Newton solution of steady-state problem...    failure. \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Take 10 timesteps       0.02247      2.965\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03792      2.764\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04799      2.789\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04555      2.765\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01441      2.553\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03648      2.753\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03463      2.334\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04383      2.197\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01387      2.045\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02633      2.838\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04998      2.483\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01581      3.057\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02252      2.448\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02533       2.73\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02137      3.281\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03043      2.887\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03852      2.938\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03656      2.901\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02314      2.832\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02196      2.505\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps        0.0139      2.281\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02638      3.088\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03339      2.971\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02113      2.999\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03566      2.793\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02539      2.858\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04819       2.69\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04575      2.297\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps        0.0386      2.385\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03664      2.844\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01739      2.734\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01651      2.931\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03133      3.136\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01983      3.259\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01412      2.835\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps        0.0402      2.769\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.01908      3.038\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03622      2.959\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03438      2.454\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04895      2.219\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.04647      2.952\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.03921       2.45\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps       0.02481      2.075\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps        0.0471      2.156\n",
      "Attempt Newton solution of steady-state problem...    failure. \n",
      "Take 10 timesteps   "
     ]
    },
    {
     "ename": "CanteraError",
     "evalue": "\n***********************************************************************\nCanteraError thrown by OneDim::timeStep:\nTook maximum number of timesteps allowed (500) without reaching steady-state solution.\n***********************************************************************\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mCanteraError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-47562cfe2005>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msim\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msolve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloglevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mauto\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m~/miniconda3/envs/cantera-workshop/lib/python3.7/site-packages/cantera/onedim.py\u001b[0m in \u001b[0;36msolve\u001b[0;34m(self, loglevel, refine_grid, auto)\u001b[0m\n\u001b[1;32m    741\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    742\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 743\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mBurnerFlame\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msolve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloglevel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrefine_grid\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mauto\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    744\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mFlameBlowoff\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    745\u001b[0m             \u001b[0;31m# The eventual solution for a blown off flame is the non-reacting\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32minterfaces/cython/cantera/onedim.pyx\u001b[0m in \u001b[0;36mcantera._cantera.Sim1D.solve\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mCanteraError\u001b[0m: \n***********************************************************************\nCanteraError thrown by OneDim::timeStep:\nTook maximum number of timesteps allowed (500) without reaching steady-state solution.\n***********************************************************************\n"
     ]
    }
   ],
   "source": [
    "sim.solve(loglevel=1, auto=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### That didn't work...what went wrong?\n",
    "* We can see that the solver failed because it was taking too many timesteps without those timesteps increasing in size, as would normally be expected.\n",
    "* Add a callback function to collect data after each timestep\n",
    "* We are only interested in the timesteps leading up to the final, failed solution attempt, but we don't know when that will occur.\n",
    "* Use the `time_step` callback to collect data after each timestep, no matter what.\n",
    "* Use the `steady` callback to clear data after a successful solve "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# variables used to capture data within the callback functions\n",
    "grid = []\n",
    "TT = []\n",
    "YY = []\n",
    "UU = []\n",
    "\n",
    "# Callback function must take one argument, even if we don't use it\n",
    "def time_step_callback(_):\n",
    "    grid[:] = sim.grid\n",
    "    TT.append(sim.T)\n",
    "    YY.append(sim.Y[gas.species_index('O2')])\n",
    "    UU.append(sim.u)\n",
    "    return 0  # Callback function must return a number\n",
    "\n",
    "def steady_callback(_):\n",
    "    TT.clear()\n",
    "    YY.clear()\n",
    "    UU.clear()\n",
    "    return 0\n",
    "\n",
    "# Recreate the flame object and attach the callback functions\n",
    "gas.set_equivalence_ratio(0.4, 'H2', 'O2:1.0, AR:4')\n",
    "gas.TP = tburner, p\n",
    "sim = ct.BurnerFlame(gas=gas, width=width)\n",
    "sim.burner.mdot = mdot\n",
    "sim.set_refine_criteria(ratio=3, slope=0.1, curve=0.2, prune=0)\n",
    "\n",
    "sim.set_time_step_callback(time_step_callback)\n",
    "sim.set_steady_callback(steady_callback)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Attempt to solve the flame again\n",
    "Wrap the call to `solve` in a `try`/`except` block, since we are expecting it to fail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "***********************************************************************\n",
      "CanteraError thrown by OneDim::timeStep:\n",
      "Took maximum number of timesteps allowed (500) without reaching steady-state solution.\n",
      "***********************************************************************\n",
      "\n",
      "\n",
      "Statistics:\n",
      "\n",
      " Grid   Timesteps  Functions      Time  Jacobians      Time\n",
      "    9          20        304    0.0055         14    0.0089\n",
      "   12          10        299    0.0068          9    0.0096\n",
      "   17          10        267    0.0087          7    0.0106\n",
      "   23          20        466    0.0198         13    0.0261\n",
      "   29         330      13157    0.7048        426    1.1215\n",
      "   33          20        436    0.0276         16    0.0500\n",
      "   38         500      19320    1.3206        673    2.2968\n"
     ]
    }
   ],
   "source": [
    "try:\n",
    "    sim.solve(loglevel=0, auto=False)\n",
    "except ct.CanteraError as e:\n",
    "    print(e)\n",
    "    sim.show_stats()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert saved data to 2D arrays"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = np.array(TT)\n",
    "Y = np.array(YY)\n",
    "U = np.array(UU)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot profiles\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax = plt.subplots(1, 1, figsize=(5,4))\n",
    "# Plot the last N profiles\n",
    "N = 50  \n",
    "# Use a sequential color map so we can tell which lines belong to which timestep\n",
    "C = plt.cm.viridis(np.linspace(0, 1, N))\n",
    "for i in range(N):\n",
    "    ax.plot(grid, T[len(T)-N+i], '.-', color=C[i])\n",
    "ax.set_xlim(0, 0.002);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's look at what's happening as a function of time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f,ax = plt.subplots(1, 3, figsize=(9, 3.5))\n",
    "ax[0].plot(T[:,1])\n",
    "ax[1].plot(Y[:,1])\n",
    "ax[2].plot(U[:,1])\n",
    "ax[0].set_title('Temperature at $j=1$')\n",
    "ax[1].set_title('$Y_{O_2}$ at $j=1$')\n",
    "ax[2].set_title('velocity at $j=1$');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}