non_ideal_gas_models.ipynb

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   "cell_type": "markdown",
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    "# Non-ideal gas models in Cantera\n",
    "\n",
    "In this example, we will demonstrate Cantera's ability to handle non-ideal gas equations of state.  This particular example will use a multi-component Redlich-Kwong Equation of state:\n",
    "$$p = \\frac{RT}{v - b} - \\frac{a}{v\\sqrt{T}\\left(v+b\\right)}$$\n",
    "and will compare results to an ideal gas approximation:\n",
    "$$pv = RT$$\n",
    "We will compare various properties of a mixture CO$_2$, H$_2$O, H$_2$, and CO.\n",
    "\n",
    "First, import the necessary python modules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cantera as ct\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['axes.labelsize'] = 16\n",
    "plt.rcParams['xtick.labelsize'] = 12\n",
    "plt.rcParams['ytick.labelsize'] = 12\n",
    "plt.rcParams['figure.autolayout'] = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Non-Ideal Shock Tube Example\n",
    "## Ignition delay time computations in a high-pressure reflected shock tube reactor\n",
    " \n",
    "In this example we will illustrate how to setup and use a constant volume, adiabatic reactor to simulate reflected shock tube experiments. This reactor will then be used to compute the ignition delay of a gas at any temperature and pressure.  \n",
    " \n",
    "The example here demonstrates the calculations carried out by G. Kogekar, et al., \"Impact of non-ideal behavior on ignition delay and chemical kinetics in high-pressure shock tube reactors,\" Combust. Flame., 2017.\n",
    "\n",
    "The reflected shock tube reactor is modeled as a constant-volume, adiabatic reactor.  The heat transfer and the work rates are therefore both zero.  With no mass inlets or exits, the 1st law energy balance reduces to:\n",
    "\n",
    "\\begin{equation*}\n",
    "\\frac{dU}{dt} = \\dot{Q} - \\dot{W} = 0.\n",
    "\\end{equation*}\n",
    " \n",
    "Because of the constant-mass and constant-volume assumptions, the density is also therefore constant:\n",
    "\n",
    "\\begin{equation*}\n",
    "\\frac{d\\rho}{dt} = 0.\n",
    "\\end{equation*}\n",
    "\n",
    "Along with the evolving gas composition, then, the thermodynamic state of the gas is defined by the initial total internal energy $U = mu = m\\sum_k\\left(Y_ku_k\\right)$, where $u_k$ and $Y_k$ are the specific internal energy (kJ/kg) and mass fraction of species $k$, respectively. \n",
    "\n",
    "The species mass fractions evolve according to the nety chemical production rates due to homogeneous gas-phase reactions:\n",
    "\n",
    "\\begin{equation*}\n",
    "\\frac{dY_k}{dt} = \\frac{W_k}{\\rho}\\dot{\\omega}_k,\n",
    "\\end{equation*}\n",
    "\n",
    "where $W_k$ is the molecular weight of species $k$ $\\left({\\rm kg}\\,{\\rm kmol}^{-3}\\right)$, $\\rho$ is the (constant) gas-phase density $\\left({\\rm kg}\\,{\\rm m^{-3}}\\right)$, and $\\dot{\\omega}_k$ is the net production rate of species $k$ $\\left({\\rm kmol}\\,{\\rm m^{-3}}\\,{\\rm s^{-1}}\\right)$."
   ]
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   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Runnning Cantera version: 2.4.0\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "import time\n",
    "\n",
    "print('Runnning Cantera version: ' + ct.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define Ignition Delay:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ignitionDelay(df, species):\n",
    "    \"\"\"\n",
    "    This function computes the ignition delay from the occurence of the\n",
    "    peak in species' concentration.\n",
    "    \"\"\"\n",
    "    return df[species].idxmax()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define the gas\n",
    "\n",
    "In this example we will choose a stoichiometric mixture of n-dodecane and air as the gas. For a representative kinetic model, we use that developed by Wang, Ra, Jia, and Reitz (https://www.erc.wisc.edu/chem_mech/nC12-PAH_mech.zip) by [H.Wang, Y.Ra, M.Jia, R.Reitz, Development of a reduced n-dodecane-PAH mechanism and its application for n-dodecane soot predictions, $Fuel$ 136 (2014) 25–36].\n",
    "\n",
    "To run a different model or use a different EoS, simply replace this cti file with a different mechanism file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "gas = ct.Solution('input-files/WangMechanismRK.cti','WangmechanismRK')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Illustration : NTC behavior\n",
    "\n",
    "In the paper by Kogekar, et al., the reactor model is used to demonstrate the impacts of non-ideal behavior on IDTs in the Negative Temperature Coefficient region, where observed IDTs, counter to intuition, increase with increasing temperature.\n",
    "\n",
    "### Define the temperatures for which we will run the simulations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a list of all the temperatures we would like to run simulations at\n",
    "T = [1800, 1600, 1400, 1200, 1100, 1075, 1050, 1025, 1000, 975, 950, 925, 900, 850, 825, 800,\n",
    "     750, 700]\n",
    "\n",
    "# Create an array of max simulation times:\n",
    "estimatedIgnitionDelayTimes = 0.005*np.ones(len(T))\n",
    "\n",
    "# Now create a dataFrame out of these\n",
    "ignitionDelays = pd.DataFrame(data={'T':T})\n",
    "ignitionDelays['ignDelay'] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the code above for each temperature, and save the IDT for each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computed Ignition Delay: 3.203e-07 seconds for T=1800K. Took 2.85s to compute\n",
      "Computed Ignition Delay: 8.500e-07 seconds for T=1600K. Took 3.31s to compute\n",
      "Computed Ignition Delay: 3.193e-06 seconds for T=1400K. Took 3.72s to compute\n",
      "Computed Ignition Delay: 1.979e-05 seconds for T=1200K. Took 4.05s to compute\n",
      "Computed Ignition Delay: 6.126e-05 seconds for T=1100K. Took 4.31s to compute\n",
      "Computed Ignition Delay: 7.908e-05 seconds for T=1075K. Took 4.43s to compute\n",
      "Computed Ignition Delay: 9.548e-05 seconds for T=1050K. Took 4.58s to compute\n",
      "Computed Ignition Delay: 1.027e-04 seconds for T=1025K. Took 5.53s to compute\n",
      "Computed Ignition Delay: 9.720e-05 seconds for T=1000K. Took 4.75s to compute\n",
      "Computed Ignition Delay: 8.595e-05 seconds for T=975K. Took 4.62s to compute\n",
      "Computed Ignition Delay: 7.828e-05 seconds for T=950K. Took 4.71s to compute\n",
      "Computed Ignition Delay: 7.608e-05 seconds for T=925K. Took 5.03s to compute\n",
      "Computed Ignition Delay: 7.639e-05 seconds for T=900K. Took 5.19s to compute\n",
      "Computed Ignition Delay: 7.998e-05 seconds for T=850K. Took 4.96s to compute\n",
      "Computed Ignition Delay: 9.117e-05 seconds for T=825K. Took 5.32s to compute\n",
      "Computed Ignition Delay: 1.180e-04 seconds for T=800K. Took 5.89s to compute\n",
      "Computed Ignition Delay: 2.855e-04 seconds for T=750K. Took 7.14s to compute\n",
      "Computed Ignition Delay: 1.017e-03 seconds for T=700K. Took 8.16s to compute\n"
     ]
    }
   ],
   "source": [
    "for i, temperature in enumerate(T):\n",
    "    # Set up the gas and reactor\n",
    "    reactorTemperature = temperature\n",
    "    reactorPressure = 100.0*101325.0\n",
    "    gas.TP = reactorTemperature, reactorPressure\n",
    "    gas.set_equivalence_ratio(phi=1.0, fuel='c12h26', oxidizer={'o2':1.0, 'n2':3.76})\n",
    "    r = ct.Reactor(contents=gas)\n",
    "    reactorNetwork = ct.ReactorNet([r])\n",
    "\n",
    "    \n",
    "    # Now compile a list of all variables for which we will store data\n",
    "    stateVariableNames = [r.component_name(item) for item in range(r.n_vars)]\n",
    "    # Create an empty data frame\n",
    "    timeHistory = pd.DataFrame(columns=stateVariableNames)\n",
    "\n",
    "    t0 = time.time()\n",
    "\n",
    "    t = 0\n",
    "    counter = 0\n",
    "    while t < estimatedIgnitionDelayTimes[i]:\n",
    "        t = reactorNetwork.step()\n",
    "        if not counter % 20:\n",
    "            timeHistory.loc[t] = r.get_state()\n",
    "        counter += 1\n",
    "\n",
    "    tau = ignitionDelay(timeHistory, 'oh')\n",
    "    t1 = time.time()\n",
    "\n",
    "    print('Computed Ignition Delay: {:.3e} seconds for T={}K. Took {:3.2f}s to compute'.format(tau, temperature, t1-t0))\n",
    "\n",
    "    ignitionDelays.at[i, 'ignDelay'] = tau"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure: ignition delay ($\\tau$) vs. the inverse of temperature ($\\frac{1000}{T}$). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
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       "\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"
    },
    {
     "data": {
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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.semilogy(1000/ignitionDelays['T'], ignitionDelays['ignDelay'],'o-',color='b')\n",
    "ax.set_ylabel('Ignition Delay (s)',fontname='Times New Roman',fontsize=16)\n",
    "ax.set_xlabel(r'$\\mathdefault{1000/T\\, (K^{-1})}$', fontsize=16,fontname='Times New Roman')\n",
    "\n",
    "# Add a second axis on top to plot the temperature for better readability\n",
    "ax2 = ax.twiny()\n",
    "ticks = ax.get_xticks()\n",
    "ax2.set_xticks(ticks)\n",
    "ax2.set_xticklabels((1000/ticks).round(1))\n",
    "ax2.set_xlim(ax.get_xlim())\n",
    "ax2.set_xlabel('Temperature (K)',fontname='Times New Roman',fontsize=16);\n",
    "\n",
    "for tick in ax.xaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')\n",
    "for tick in ax.yaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')\n",
    "for tick in ax2.xaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Repeat for an ideal gas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "gas = ct.Solution('input-files/WangMechanismRK.cti','WangmechanismIG')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a list of all the temperatures we would like to run simulations at\n",
    "T = [1800, 1600, 1400, 1200, 1100, 1075, 1050, 1025, 1000, 975, 950, 925, 900, 850, 825, 800,\n",
    "     750, 700]\n",
    "\n",
    "# Create an array of max simulation times:\n",
    "estimatedIgnitionDelayTimes = 0.005*np.ones(len(T))\n",
    "\n",
    "# Now create a dataFrame out of these\n",
    "ignitionDelays_IG = pd.DataFrame(data={'T':T})\n",
    "ignitionDelays_IG['ignDelay'] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computed Ignition Delay: 3.469e-07 seconds for T=1800K. Took 0.95s to compute\n",
      "Computed Ignition Delay: 9.380e-07 seconds for T=1600K. Took 1.13s to compute\n",
      "Computed Ignition Delay: 3.563e-06 seconds for T=1400K. Took 1.05s to compute\n",
      "Computed Ignition Delay: 2.222e-05 seconds for T=1200K. Took 1.17s to compute\n",
      "Computed Ignition Delay: 6.911e-05 seconds for T=1100K. Took 1.21s to compute\n",
      "Computed Ignition Delay: 8.975e-05 seconds for T=1075K. Took 1.31s to compute\n",
      "Computed Ignition Delay: 1.096e-04 seconds for T=1050K. Took 1.44s to compute\n",
      "Computed Ignition Delay: 1.198e-04 seconds for T=1025K. Took 1.51s to compute\n",
      "Computed Ignition Delay: 1.150e-04 seconds for T=1000K. Took 1.53s to compute\n",
      "Computed Ignition Delay: 1.026e-04 seconds for T=975K. Took 1.49s to compute\n",
      "Computed Ignition Delay: 9.370e-05 seconds for T=950K. Took 1.39s to compute\n",
      "Computed Ignition Delay: 9.118e-05 seconds for T=925K. Took 1.49s to compute\n",
      "Computed Ignition Delay: 9.201e-05 seconds for T=900K. Took 1.82s to compute\n",
      "Computed Ignition Delay: 9.813e-05 seconds for T=850K. Took 1.66s to compute\n",
      "Computed Ignition Delay: 1.118e-04 seconds for T=825K. Took 1.83s to compute\n",
      "Computed Ignition Delay: 1.433e-04 seconds for T=800K. Took 1.72s to compute\n",
      "Computed Ignition Delay: 3.363e-04 seconds for T=750K. Took 1.73s to compute\n",
      "Computed Ignition Delay: 1.153e-03 seconds for T=700K. Took 2.06s to compute\n"
     ]
    }
   ],
   "source": [
    "for i, temperature in enumerate(T):\n",
    "    # Set up the gas and reactor\n",
    "    reactorTemperature = temperature\n",
    "    reactorPressure = 100.0*101325.0\n",
    "    gas.TP = reactorTemperature, reactorPressure\n",
    "    gas.set_equivalence_ratio(phi=1.0, fuel='c12h26', oxidizer={'o2':1.0, 'n2':3.76})\n",
    "    r = ct.Reactor(contents=gas)\n",
    "    reactorNetwork = ct.ReactorNet([r])\n",
    "\n",
    "    \n",
    "    # Now compile a list of all variables for which we will store data\n",
    "    stateVariableNames = [r.component_name(item) for item in range(r.n_vars)]\n",
    "    # Create an empty data frame\n",
    "    timeHistory = pd.DataFrame(columns=stateVariableNames)\n",
    "\n",
    "    t0 = time.time()\n",
    "\n",
    "    t = 0\n",
    "    counter = 0\n",
    "    while t < estimatedIgnitionDelayTimes[i]:\n",
    "        t = reactorNetwork.step()\n",
    "        if not counter % 20:\n",
    "            timeHistory.loc[t] = r.get_state()\n",
    "        counter += 1\n",
    "\n",
    "    tau = ignitionDelay(timeHistory, 'oh')\n",
    "    t1 = time.time()\n",
    "\n",
    "    print('Computed Ignition Delay: {:.3e} seconds for T={}K. Took {:3.2f}s to compute'.format(tau, temperature, t1-t0))\n",
    "\n",
    "    ignitionDelays_IG.at[i, 'ignDelay'] = tau"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "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>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "ax.semilogy(1000/ignitionDelays['T'], ignitionDelays['ignDelay'],'o-',color='b')\n",
    "ax.semilogy(1000/ignitionDelays_IG['T'], ignitionDelays_IG['ignDelay'],'-',color='k')\n",
    "ax.set_ylabel('Ignition Delay (s)',fontname='Times New Roman',fontsize=16)\n",
    "ax.set_xlabel(r'$\\mathdefault{1000/T\\, (K^{-1})}$', fontsize=16,fontname='Times New Roman')\n",
    "ax.legend(['Redlich-Kwong','Ideal Gas'])\n",
    "\n",
    "# Add a second axis on top to plot the temperature for better readability\n",
    "ax2 = ax.twiny()\n",
    "ticks = ax.get_xticks()\n",
    "ax2.set_xticks(ticks)\n",
    "ax2.set_xticklabels((1000/ticks).round(1))\n",
    "ax2.set_xlim(ax.get_xlim())\n",
    "ax2.set_xlabel('Temperature (K)',fontname='Times New Roman',fontsize=16);\n",
    "\n",
    "for tick in ax.xaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')\n",
    "for tick in ax.yaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')\n",
    "for tick in ax2.xaxis.get_major_ticks():\n",
    "    tick.label1.set_fontsize(12)\n",
    "    tick.label1.set_fontname('Times New Roman')"
   ]
  },
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   "metadata": {},
   "source": [
    "## Extension - looking at non-ideal impacts on NTC.\n",
    "\n",
    "Using Cantera's object-oriented nature, and branching functions in Git, it is possible to explore the impacts of non-ideal effects on NTC behavior.  \n",
    "\n",
    "As published in _Combust. Flame_ in 2017 (see above for reference), we created three different thermodynamic models to explore NTC of n-dodecane:\n",
    "\n",
    "- 'Ideal gas': An ideal gas model.\n",
    "- 'R-K $\\left(\\left[X_k\\right]\\right)$': A model which (incorrectly) used used the Redlich-Kwong model for the equation of state (EoS - phase density and species concentrations) but uses the ideal gas model for chemical kinetics (i.e. activity coefficients \n",
    "$\\gamma_k = 1$ and $\\dot{q} = k_{\\rm fwd}\\prod\\left[X_k\\right]^{\\nu^\\prime_k} - k_{\\rm rev}\\prod\\left[X_k\\right]^{\\nu^{\\prime\\prime}_k}$).\n",
    "- 'R-K $\\left(\\gamma_k\\right)$':A model which (correctly) used the Redlich-Kwong model for both EoS and activity coefficient calculations, such that $\\dot{q} = k_{\\rm fwd}\\prod\\left(\\gamma_k\\left[X_k\\right]\\right)^{\\nu^\\prime_k} - k_{\\rm rev}\\prod\\left(\\gamma_k\\left[X_k\\right]\\right)^{\\nu^{\\prime\\prime}_k}$\n",
    "\n",
    "### \"Low\" pressure (40 atm)\n",
    "<img src=\"images/IDT_40atm.png\"  width=\"500\">\n",
    "\n"
   ]
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   "outputs": [],
   "source": []
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