0D-velocity-example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0-D Reactors"
   ]
  },
  {
   "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: http://cantera.org/docs/sphinx/html/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-block 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": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import cantera as ct\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "%matplotlib notebook"
   ]
  },
  {
   "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": [
    {
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       "        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",
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       "        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",
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       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
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       "\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",
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       "\n",
       "    canvas_div.resizable({\n",
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       "            pass_mouse_events = false;\n",
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       "        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",
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       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
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       "\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",
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       "\n",
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       "    this.rubberband = rubberband;\n",
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       "        // 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",
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       "\n",
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       "    this._resize_canvas(600, 600);\n",
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       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
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       "\n",
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       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
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       "\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",
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       "        return fig.toolbar_button_onclick(event['data']);\n",
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       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
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       "        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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.loadtxt('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": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gas = ct.Solution('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})"
   ]
  },
  {
   "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`, and after creating the reactor, we add it to a `ReactorNet`. The reactor network would also contain any flow controllers, if those were present."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "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` method of the `ReactorNet` and the `step` method. 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 `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 `list`s."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "temperature = []\n",
    "pressure = []\n",
    "volume = []\n",
    "time = []\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",
    "    time.append(netw.time)\n",
    "    temperature.append(reac.T)\n",
    "    pressure.append(reac.thermo.P)\n",
    "    volume.append(reac.volume)\n",
    "    netw.step()\n",
    "\n",
    "# It is more convenient to work with the data in NumPy arrays than Python lists, so convert\n",
    "temperature = np.array(temperature)\n",
    "pressure = np.array(pressure)\n",
    "volume = np.array(volume)\n",
    "time = np.array(time)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "/* 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",
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       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
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       "        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",
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       "    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",
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       "                // Full images could contain transparency (where diff images\n",
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       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
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       "\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",
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       "\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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('Simulated Temperature')\n",
    "plt.plot(time, temperature)\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",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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')\n",
    "plt.plot(expt_time, expt_pres, label='Experimental')\n",
    "plt.plot(time + 0.032, pressure/1.0E5, label='Simulation')\n",
    "plt.legend()\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Pressure [bar]');"
   ]
  },
  {
   "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 in the experiment. The volume of the reactor can be changed by considering it as a piston-cylinder assembly. The area of the piston is constant, and the rate of change of the volume is the velocity of the piston. It is this velocity that must be specified to the reactor to change its volume. First, we will define a class with the special `__call__` that returns the velocity at a point in time. The time is passed as the argument to the `__call__` function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "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": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "gas = ct.Solution('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": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "vol_data = np.loadtxt('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": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-38.6576215208\n",
      "0.388953308755\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": 13,
   "metadata": {
    "collapsed": true
   },
   "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_temperature = []\n",
    "vol_pressure = []\n",
    "vol_volume = []\n",
    "vol_time = []\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",
    "    vol_time.append(netw.time)\n",
    "    vol_temperature.append(reac.T)\n",
    "    vol_pressure.append(reac.thermo.P)\n",
    "    vol_volume.append(reac.volume)\n",
    "    netw.step()\n",
    "\n",
    "# It is more convenient to work with the data in NumPy arrays than Python lists, so convert\n",
    "vol_temperature = np.array(vol_temperature)\n",
    "vol_pressure = np.array(vol_pressure)\n",
    "vol_volume = np.array(vol_volume)\n",
    "vol_time = np.array(vol_time)"
   ]
  },
  {
   "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": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
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\" width=\"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_time, vol_volume, label='Simulated Volume')\n",
    "plt.ylabel('Volume [m**3]')\n",
    "plt.xlabel('Time, [s]')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"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(time + 0.032, pressure/1.0E5, label='Constant Volume Simulation')\n",
    "plt.plot(vol_time, vol_pressure/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. Another example where they are very useful is to construct a perfectly stirred reactor model with fixed residence time, rather than fixed mass flow rate (https://groups.google.com/d/msg/cantera-users/dMUhi5kVVDk/bDFYWMQsgbAJ)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "gas = ct.Solution('h2o2.xml')\n",
    "\n",
    "gas.TPX = 300, ct.one_atm, 'H2:1.0, O2:2.0, AR:4.0'\n",
    "upstream = ct.Reservoir(gas)\n",
    "downstream = ct.Reservoir(gas)\n",
    "\n",
    "gas.equilibrate('HP')\n",
    "r1 = ct.IdealGasReactor(gas)\n",
    "\n",
    "residence_time = 1e-4\n",
    "\n",
    "def mdot_out(t):\n",
    "    return r1.mass / residence_time\n",
    "\n",
    "inlet = ct.Valve(upstream, r1, K=100)\n",
    "outlet = ct.MassFlowController(r1, downstream)\n",
    "outlet.set_mass_flow_rate(mdot_out)\n",
    "\n",
    "net = ct.ReactorNet([r1])\n",
    "\n",
    "t = np.linspace(0, 5*residence_time, 200)\n",
    "T = np.zeros(t.shape)\n",
    "mdot = np.zeros(t.shape)\n",
    "for i,ti in enumerate(t):\n",
    "    if ti:\n",
    "        net.advance(ti)\n",
    "    T[i] = r1.T\n",
    "    mdot[i] = outlet.mdot(ti)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure('PSR Time vs. Temperature')\n",
    "plt.plot(t, T)\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Temperature [K]');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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('PSR Time vs. Mass Flow Rate')\n",
    "plt.plot(t, mdot)\n",
    "plt.xlabel('Time [s]')\n",
    "plt.ylabel('Mass Flow Rate [kg/s]');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}