0D_velocity_example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0-D Reactors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using Cantera version 2.4.0\n"
     ]
    }
   ],
   "source": [
    "import cantera as ct\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "print(f\"Using Cantera version {ct.__version__}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cantera can solve the coupled energy and species equations for zero-dimensional reactors. For further details of the actual equations that are solved, see the documentation: https://cantera.org/science/reactors.html The 0-D reactors have a number of options that enable them to model a wide range of systems, including user-controlled varying volume, heat transfer into or out of the environment, mass flow into and out of the system, and surface kinetics.\n",
    "\n",
    "Effectively, there are two major choices the user must make in desiging the model of the basic system. The first is whether the reactor solves the general energy equation (solved in terms of the mixture enthalpy) or the ideal gas energy equation (solved in terms of the temperature). In general, the two methods will give the same solution to the problem; however, if the system can be modeled as an ideal gas, the ideal gas equation tends to be more robust and faster.\n",
    "\n",
    "The second choice the user must make is whether the system will be modeled as constant pressure or constant volume.\n",
    "\n",
    "For each of these choices, there is a specific reactor type:\n",
    "\n",
    "* `Reactor`: Constant volume, general energy equation\n",
    "* `IdealGasReactor`: Constant volume, ideal gas energy equation\n",
    "* `ConstantPressureReactor`: Constant pressure, general energy equation\n",
    "* `ConstantPressureIdealGasReactor`: Constant pressure, ideal gas energy equation\n",
    "\n",
    "<div class=\"alert alert-info\">\n",
    "\n",
    "Old examples recommended that constant pressure reactors be approximated by allowing the volume of the reactor to expand very quickly as the reaction proceeded. This is no longer recommended because it creates extra stiffness in the solution and the `ConstantPressure*` reactors are a better solution\n",
    "\n",
    "</div>\n",
    "\n",
    "In the following example, we will solve a constant volume, adiabatic reactor problem, followed by a variable-volume reactor where the volume is controlled by a user-defined function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## RCM Experimental Information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following experimental data comes from the work of Dames et al., *Combustion and Flame*, 168, 310-330, https://doi.org/10.1016/j.combustflame.2016.02.021 The experiment is a 50%-50% by mole mixture of propane and dimethyl ether. The experiment is a rapid compression machine experiment, where a compression process brings the reactant mixture to the end of compression (EOC) conditions. In this particular experiment, the EOC pressure is 30.11 bar and the EOC temperature is 682 K, and the ignition delay is 19.58 ms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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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     },
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     "output_type": "display_data"
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\" 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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.loadtxt('input-files/0d_example/Tc_682K_P0_1.5137_T0_323K_pressure.txt')\n",
    "expt_time = data[:, 0]\n",
    "expt_pres = data[:, 1]\n",
    "plt.figure('Experimental Pressure')\n",
    "plt.plot(expt_time, expt_pres)\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Pressure [bar]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Constant Volume Simulation Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'C3H8': 0.024950099800399205,\n",
       " 'CH3OCH3': 0.024950099800399205,\n",
       " 'N2': 0.7504990019960079,\n",
       " 'O2': 0.1996007984031936}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gas = ct.Solution('input-files/0d_example/mech.cti')\n",
    "gas.TP = 682, 30.11E5\n",
    "gas.set_equivalence_ratio(1.0, {'ch3och3': 1, 'c3h8': 1}, {'o2': 1, 'n2': 3.76})\n",
    "gas.mole_fraction_dict()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The experiment can be modeled as an ideal gas mixture, and the reactor can be modeled as constant volume for simplicity, with no mass transfer to/from the environment. The reactor is an [`IdealGasReactor`](https://cantera.org/documentation/docs-2.4/sphinx/html/cython/zerodim.html#idealgasreactor), and after creating the reactor, we add it to a [`ReactorNet`](https://cantera.org/documentation/docs-2.4/sphinx/html/cython/zerodim.html#cantera.ReactorNet). The reactor network would also contain any flow controllers, if those were present."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "reac = ct.IdealGasReactor(gas)\n",
    "netw = ct.ReactorNet([reac])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next step is to run the integrator. There are two options for this, the [`advance`](https://cantera.org/documentation/docs-2.4/sphinx/html/cython/zerodim.html#cantera.ReactorNet.advance) and [`step`](https://cantera.org/documentation/docs-2.4/sphinx/html/cython/zerodim.html#cantera.ReactorNet.step) methods of the `ReactorNet`. The `advance` method is useful when there is a desired end time for the integration, or you would like to have fixed step sizes in the output. The only argument to the `advance` method is the desired end time, and the solver will take as many internal, variable-sized, time steps as necessary to get to that end tim. By contrast, the `step` method takes one variable sized time step, with the size determined by the integrator. It is useful when you want as much detail (in terms of time history) as possible. The easiest way to store the data is to append to a [`SolutionArray`](https://cantera.org/documentation/docs-2.4/sphinx/html/cython/importing.html#cantera.SolutionArray)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "sol = ct.SolutionArray(gas, extra=[\"time\", \"volume\"])\n",
    "\n",
    "# End the simulation when the temperature exceeds 2500 K or the time reaches 0.1 s\n",
    "while reac.T < 2500 and netw.time < 0.1:\n",
    "    sol.append(time=netw.time, T=reac.T, P=reac.thermo.P, X=reac.thermo.X, volume=reac.volume)\n",
    "    netw.step()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('Simulated Temperature')\n",
    "plt.plot(sol.time, sol.T)\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Temperature [K]');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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"
    },
    {
     "data": {
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('Experimental Pressure vs. Simulated Pressure')\n",
    "plt.plot(expt_time, expt_pres, label='Experimental')\n",
    "plt.plot(sol.time + 0.032, sol.P/1.0E5, label='Simulation')\n",
    "plt.legend()\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Pressure [bar]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Variable-Volume Simulation Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The agreement between the experiment and the model is quite good, although it is clear there is some experimental detail that is missing. We can account for this detail (the compression stroke and post-compression heat-loss) by changing the volume of the `IdealGasReactor` to model the processes occurring in the experiment. In Cantera, the volume of a `Reactor` is changed by specifying the velocity of a `Wall` attached to the reactor.\n",
    "\n",
    "The basic RCM experiment is a piston-cylinder assembly. The area of the piston is constant, and thus the velocity of the piston is equal to the rate of change of the volume of the cylinder.\n",
    "\n",
    "$$\\begin{aligned}\n",
    "V &= A h \\\\\n",
    "\\frac{dV}{dt} &= A \\frac{dh}{dt}\n",
    "\\end{aligned}$$\n",
    "\n",
    "Since we are not interested in any quantities such as the total heat release that would depend on the actual `Reactor` volume, it is sufficient to assume the piston has unit area. Therefore, if we can find the rate of change of the volume of the cylinder in the experiment, we can specify that as the velocity of the wall and create the appropriate volume change in the `Reactor`. \n",
    "\n",
    "From the experiment, we are able to compute a \"volume trace,\" in this case, by assuming isentropic compression and \"expansion\" and using the measured pressure data to calculate the volume as a function of time. This could also be done by directly measuring the position of the piston. Rather than computing the derivative of the volume on every time step, we would like to compute it once and store that result for speed. To do so, we will define a Python `class` that computes $dV/dt$ when initialized and returns the appropriate value when passed the time in the simulation. This latter part is done with the special `__call__` method of the class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class VolumeProfile(object):\n",
    "    \"\"\"\n",
    "    Set the velocity of the piston by using a user specified volume\n",
    "    profile. The initialization and calling of this class are handled\n",
    "    by the `cantera.Func1` interface of Cantera.\n",
    "    The velocity is calculated by assuming a unit area and using the\n",
    "    forward difference, calculated by `numpy.diff`. This function is\n",
    "    only called once when the class is initialized at the beginning of\n",
    "    a problem so it is efficient.\n",
    "    Parameters\n",
    "    ----------\n",
    "    time: `numpy.ndarray`\n",
    "        Array or list of time values\n",
    "    volume: `numpy.ndarray`\n",
    "        Array or list of volume values\n",
    "    Attributes\n",
    "    ----------\n",
    "    time: `numpy.ndarray`\n",
    "        Array of time values\n",
    "    volume: `numpy.ndarray`\n",
    "        Array of volume values\n",
    "    velocity: `numpy.ndarray`\n",
    "        Array of velocity values\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, time, volume):\n",
    "        # The time and volume are stored as lists in the keywords\n",
    "        # dictionary. The volume is normalized by the first volume\n",
    "        # element so that a unit area can be used to calculate the\n",
    "        # velocity.\n",
    "        self.time = np.array(time)\n",
    "        self.volume = np.array(volume)/volume[0]\n",
    "\n",
    "        # The velocity is calculated by the forward difference.\n",
    "        # numpy.diff returns an array one element smaller than the\n",
    "        # input array, so we append a zero to match the length of the\n",
    "        # self.time array.\n",
    "        self.velocity = np.diff(self.volume)/np.diff(self.time)\n",
    "        self.velocity = np.append(self.velocity, 0)\n",
    "\n",
    "    def __call__(self, t):\n",
    "        \"\"\"Return the velocity when called during a time step.\n",
    "        Parameters\n",
    "        ----------\n",
    "        t : `float`\n",
    "            Current simulation time.\n",
    "        \"\"\"\n",
    "\n",
    "        if t <= self.time[-1] and t >= self.time[0]:\n",
    "            # prev_time_point is the previous value in the time array\n",
    "            # after the current simulation time\n",
    "            prev_time_point = self.time[self.time <= t][-1]\n",
    "            # index is the index of the time array where\n",
    "            # prev_time_point occurs\n",
    "            index = np.where(self.time == prev_time_point)[0][0]\n",
    "            return self.velocity[index]\n",
    "        else:\n",
    "            return 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we need to define a `Solution` just like before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "gas = ct.Solution('input-files/0d_example/mech.cti')\n",
    "gas.TP = 323, 1.5137E5\n",
    "gas.set_equivalence_ratio(1.0, {'ch3och3': 1, 'c3h8': 1}, {'o2': 1, 'n2': 3.76})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The volume of the cylinder from the experiment is used to compute the velocity in the `VolumeProfile` class, so we need to load the volume trace from the file on the disk."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "vol_data = np.loadtxt('input-files/0d_example/Tc_682K_P0_1.5137_T0_323K_volume.csv', delimiter=',')\n",
    "inp_time = vol_data[:, 0]\n",
    "inp_vol = vol_data[:, 1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can calculate a few values of velocity using the `VolumeProfile` class, just to demonstrate the operation. First, an instance of the class is initialized with the volume and time read from the input file. Then we can call the instance, passing time points, and the velocity is returned. If the time that is passed is greater than the maximum time present in the input file (0.4 s), the velocity returned is zero."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-38.65762152078938\n",
      "0.38895330875536716\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "vpro = VolumeProfile(inp_time, inp_vol)\n",
    "print(vpro(0.01))\n",
    "print(vpro(0.35))\n",
    "print(vpro(0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To effect the volume change, instances of `Wall`s can be installed between two Cantera reactors. In this case, we only care about reactions and changes in the reactor representing the RCM reaction chamber, so we install a `Wall` between the `IdealGasReactor` and a `Reservoir`, which represents the environment. Then we specify the `VolumeProfile` class as the means to calculate the velocity. Other options would be a constant value, or a function that takes a single argument (the simulation time). With the velocity defined and the `Wall` installed, the simulation can proceed as before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "reac = ct.IdealGasReactor(gas)\n",
    "env = ct.Reservoir(ct.Solution('air.xml'))\n",
    "wall = ct.Wall(reac, env, A=1.0, velocity=vpro)\n",
    "netw = ct.ReactorNet([reac])\n",
    "netw.set_max_time_step(inp_time[1])\n",
    "\n",
    "vol_sol = ct.SolutionArray(gas, extra=[\"time\", \"volume\"])\n",
    "# End the simulation when the temperature exceeds 2500 K or the time reaches 0.1 s\n",
    "while reac.T < 2500 and netw.time < 0.1:\n",
    "    vol_sol.append(time=netw.time, T=reac.T, P=reac.thermo.P, X=reac.thermo.X, volume=reac.volume)\n",
    "    netw.step()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can compare a number of parameters between the simulation and experiment. First, we can compare the volume that is read from the input file to the simulated volume of the reactor as a function of time. Remember that we did not specify the volume of the reactor directly, instead we specified it through the velocity. The two volume traces agree exactly (although the simulated volume is somewhat shorter than the input volume because of the conditions we placed on the integration)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
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       "\n",
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       "\tthis.context.oBackingStorePixelRatio ||\n",
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       "\n",
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       "    );\n",
       "\n",
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       "    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"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('Volume Trace Comparison')\n",
    "plt.plot(inp_time, inp_vol, label='Input Volume')\n",
    "plt.plot(vol_sol.time, vol_sol.volume, label='Simulated Volume')\n",
    "plt.ylabel('Volume [m**3]')\n",
    "plt.xlabel('Time, [s]')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('Experimental Pressure vs. Simulated Pressure 2')\n",
    "plt.plot(expt_time, expt_pres, label='Experimental')\n",
    "plt.plot(sol.time + 0.032, sol.P/1.0E5, label='Constant Volume Simulation')\n",
    "plt.plot(vol_sol.time, vol_sol.P/1.0E5, label='Variable Volume Simulation')\n",
    "plt.legend()\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Pressure [bar]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Then, comparing all three pressure traces, we can see that the green variable volume simulation very closely approximates the behavior of the experimental pressure trace, including the compression stroke and post-compression behavior. User defined functions and classes, such as the one used to compute the velocity of the wall in this example, are very powerful in Cantera."
   ]
  }
 ],
 "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
}