{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Event Handling and Interactive Plots"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following sections of this IPython Notebook we be looking at the following:\n",
    "\n",
    "* matplotlib's event loop support\n",
    "* Basic Event Handling\n",
    "  * List of supported events\n",
    "  * Mouse events\n",
    "  * Limitations of the IPython Notebook backend\n",
    "  * Keyboard events\n",
    "  * Axes and Figures events\n",
    "  * Object picking\n",
    "* Compound Event Handling\n",
    "  * Toolbar\n",
    "  * Interactive panning and zooming of figures\n",
    "\n",
    "Warm-up proceedures:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "matplotlib.use('nbagg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that we've left out the following line from our usual notebook prelude:\n",
    "\n",
    "```\n",
    "%matplotlib inline\n",
    "```\n",
    "\n",
    "We've disabled inline so that we get access to the interactive mode. More on that later :-)\n",
    "\n",
    "Let's continue with the necessary imports:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import random\n",
    "import sys\n",
    "import time\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from IPython.display import Image\n",
    "from typecheck import typecheck\n",
    "\n",
    "sys.path.append(\"../lib\")\n",
    "import topo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's set up our colors for this notebook:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "pallete_name = \"husl\"\n",
    "colors = sns.color_palette(pallete_name, 8)\n",
    "colors.reverse()\n",
    "cmap = mpl.colors.LinearSegmentedColormap.from_list(pallete_name, colors) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Event Loop Basics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we look at matplotlib's event loop support, let's do a quick survey of event loops and get a refresher on how they work. Here's a pretty simple \"event\" loop:\n",
    "\n",
    "```python\n",
    "while True:\n",
    "    pass\n",
    "```\n",
    "\n",
    "That loop is not going be worth our while to execute in this notebook :-) So let's do another one, almost as simple, that has a good chance of exiting in under a minute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x = True\n",
    "while x:\n",
    "    time.sleep(1)\n",
    "    if random.random() < 0.15:\n",
    "        x = False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This loop only handles one \"event\": the change of a value from ``True`` to ``False``. That loop will continue to run until the condition for a false value of ``x`` is met (a random float under a particular threshold).\n",
    "\n",
    "So what relation do these simple loops have with the loops that power toolkits like GTK and Qt or frameworks like Twisted and Tornado? Usually event systems have something like the following:\n",
    " * a way to start the event loop\n",
    " * a way to stop the event loop\n",
    " * providing a means for registering events\n",
    " * providing a means for responding to events\n",
    "\n",
    "During each run, a loop will usually check a data structure to see if there are any new events that have occurred since the last time it looped. In a network event system, each loop might check to see if any file descriptors are ready for reading or writing. In a GUI toolkit, each look might check to see if any clicks or button presses had occurred.\n",
    "\n",
    "Given the simple criteria above, let's try building a minimally demonstrative, if not useful, event loop. To keep this small, we're not going to integrate with socket or GUI events. The event that our loop will respond to will be quite minimal indeed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class EventLoop:\n",
    "    def __init__(self):\n",
    "        self.command = None\n",
    "        self.status = None\n",
    "        self.handlers = {\"interrupt\": self.handle_interrupt}\n",
    "        self.resolution = 0.1\n",
    "\n",
    "    def loop(self):\n",
    "        self.command = \"loop\"\n",
    "        while self.command != \"stop\":\n",
    "            self.status = \"running\"\n",
    "            time.sleep(self.resolution)\n",
    "            \n",
    "    def start(self):\n",
    "        self.command = \"run\"\n",
    "        try:\n",
    "            self.loop()\n",
    "        except KeyboardInterrupt:\n",
    "            self.handle_event(\"interrupt\")\n",
    "            \n",
    "    def stop(self):\n",
    "        self.command = \"stop\"\n",
    "\n",
    "    @typecheck\n",
    "    def add_handler(self, fn: callable, event: str):\n",
    "        self.handlers[event] = fn\n",
    "\n",
    "    @typecheck\n",
    "    def handle_event(self, event: str):\n",
    "        self.handlers[event]()\n",
    "        \n",
    "    def handle_interrupt(self):\n",
    "        print(\"Stopping event loop ...\")\n",
    "        self.stop()            "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here's what we did:\n",
    "\n",
    "* Created a class that maintains a data structure for event handlers\n",
    "* We also added a default handler for the \"interrupt\" event\n",
    "* Created a loop method\n",
    "* Created methods for starting and stopping the loop (via an attribute change)\n",
    "* In our ``start`` method, we check for an interrupt signal, and fire off an interrupt handler for said signal\n",
    "* Created a method for adding event handlers to the handler data structure (should we want to add more)\n",
    "\n",
    "Let's creat an instance and start it up:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stopping event loop ...\n"
     ]
    }
   ],
   "source": [
    "el = EventLoop()\n",
    "el.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When you evaluate that cell, IPython will display the usual indicator that a cell is continuing to run:\n",
    "\n",
    "```\n",
    "In [*]:\n",
    "```\n",
    "\n",
    "As soon as you're satisfied that the loop is merrily looping, go up to the IPython Notebook menu and select \"Kernel\" -> \"Interrupt\". The cell with the loop in it should finish, with not only an ``In`` number instead of an asterisk, but our interrupt handler should have printed out a status message as well.\n",
    "\n",
    "Though this event loop is fairly different from those that power networking libraries or GUI toolkits, it's *very* close (both in nature and code) to the default event loops matplotlib provides for its canvas objects. As such, this is a perfect starting place for your deeper understanding of matplotlib. To continue in this vein, reading the matplotlib backend source code would serve you well."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standard Event Handling in matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With some event loop knowledge under our belts, we're ready to start working with matplotlib events.\n",
    "\n",
    "Below is the list of supported events in matplotlib as of version 1.4:\n",
    "\n",
    "\n",
    "| Event name              | Class and description                                |\n",
    "|-------------------------|------------------------------------------------------|\n",
    "|``button_press_event``   | ``MouseEvent`` - mouse button is pressed             |\n",
    "|``button_release_event`` | ``MouseEvent`` - mouse button is released            |\n",
    "|``draw_event``\t          | ``DrawEvent`` - canvas draw                          |\n",
    "|``key_press_event``      | ``KeyEvent`` - key is pressed                        |\n",
    "|``key_release_event``    | ``KeyEvent`` - key is released                       |\n",
    "|``motion_notify_event``  | ``MouseEvent`` - mouse motion                        |\n",
    "|``pick_event``           | ``PickEvent`` - an object in the canvas is selected  |\n",
    "|``resize_event``\t      | ``ResizeEvent`` - figure canvas is resized           |\n",
    "|``scroll_event``\t      | ``MouseEvent`` - mouse scroll wheel is rolled        |\n",
    "|``figure_enter_event``   | ``LocationEvent`` - mouse enters a new figure        |\n",
    "|``figure_leave_event``   | ``LocationEvent`` - mouse leaves a figure            |\n",
    "|``axes_enter_event``\t  | ``LocationEvent`` - mouse enters a new axes          |\n",
    "|``axes_leave_event``\t  | ``LocationEvent`` - mouse leaves an axes             |\n",
    "\n",
    "\n",
    "We'll discuss some of these below in more detail. With that information in hand, you should be able to tackle problems with any of the supported events in matplotlib."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mouse Events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the next cell, we will define a couple of callback functions, and then connet these to specific canvas events.\n",
    "\n",
    "Go ahead and render the cell then click on the display plot a couple of times:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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.focus_on_mousover = false;\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this.root.attr('style', 'display: inline-block');\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",
       "            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",
       "            fig.waiting = false;\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",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "    canvas_div.resizable({ resize: mpl.debounce_resize(\n",
       "        function(event, ui) { fig.request_resize(ui.size.width, ui.size.height); }\n",
       "        , 50)});\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both;');\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;\")\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "    function mouse_event_fn(event) {\n",
       "        return fig.mouse_event(event, event['data']);\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",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keydown('key_release', canvas_keyboard_event);\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);\n",
       "        canvas.attr('height', height);\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",
       "\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",
       "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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (this.focus_on_mouseover && name === 'motion_notify')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button});\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 = function(event, name) {\n",
       "    /* Don't fire events just when a modifier is changed.  Modifiers are\n",
       "       sent along with other keys. */\n",
       "    if (event.keyCode >= 16 && event.keyCode <= 20) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    value = '';\n",
       "    if (event.ctrlKey) {\n",
       "        value += \"ctrl+\";\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        value += \"alt+\";\n",
       "    }\n",
       "    value += String.fromCharCode(event.keyCode).toLowerCase();\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        var format_dropdown = this.format_dropdown;\n",
       "        var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "        this.ondownload(this, format);\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",
       "\n",
       "mpl.debounce_event = function(func, time){\n",
       "    var timer;\n",
       "    return function(event){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event); }, time);\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.debounce_resize = function(func, time){\n",
       "    var timer;\n",
       "    return function(event, ui){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event, ui); }, time);\n",
       "    };\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\"], [\"\", \"\", \"\", \"\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pgf\", \"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",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           function() { },\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(fig.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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 (cell.output_area.outputs[j]['text/html'] == html_output) {\n",
       "                    var output = cell.output_area.outputs[j];\n",
       "                    return [cell, output, 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 at 0x10bf6df60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML at 0x10bf6dfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def press_callback(event):\n",
    "    event.canvas.figure.text(event.xdata, event.ydata, '<- clicked here')\n",
    "    \n",
    "def release_callback(event):\n",
    "    event.canvas.figure.show()\n",
    "    \n",
    "(figure, axes) = plt.subplots()\n",
    "press_conn_id = figure.canvas.mpl_connect('button_press_event', press_callback)\n",
    "release_conn_id = figure.canvas.mpl_connect('button_release_event', release_callback)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our callbacks display a little note close to each $(x, y)$ coordinate where we clicked (the location is not exact due to font-sizing, etc.) If we use a graphical indication as opposed to a textual one, we can get much better precision:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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.focus_on_mousover = false;\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this.root.attr('style', 'display: inline-block');\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",
       "            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",
       "            fig.waiting = false;\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",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "    canvas_div.resizable({ resize: mpl.debounce_resize(\n",
       "        function(event, ui) { fig.request_resize(ui.size.width, ui.size.height); }\n",
       "        , 50)});\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both;');\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;\")\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "    function mouse_event_fn(event) {\n",
       "        return fig.mouse_event(event, event['data']);\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",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keydown('key_release', canvas_keyboard_event);\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);\n",
       "        canvas.attr('height', height);\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",
       "\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",
       "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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (this.focus_on_mouseover && name === 'motion_notify')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button});\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 = function(event, name) {\n",
       "    /* Don't fire events just when a modifier is changed.  Modifiers are\n",
       "       sent along with other keys. */\n",
       "    if (event.keyCode >= 16 && event.keyCode <= 20) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    value = '';\n",
       "    if (event.ctrlKey) {\n",
       "        value += \"ctrl+\";\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        value += \"alt+\";\n",
       "    }\n",
       "    value += String.fromCharCode(event.keyCode).toLowerCase();\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        var format_dropdown = this.format_dropdown;\n",
       "        var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "        this.ondownload(this, format);\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",
       "\n",
       "mpl.debounce_event = function(func, time){\n",
       "    var timer;\n",
       "    return function(event){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event); }, time);\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.debounce_resize = function(func, time){\n",
       "    var timer;\n",
       "    return function(event, ui){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event, ui); }, time);\n",
       "    };\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\"], [\"\", \"\", \"\", \"\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pgf\", \"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",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           function() { },\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(fig.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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 (cell.output_area.outputs[j]['text/html'] == html_output) {\n",
       "                    var output = cell.output_area.outputs[j];\n",
       "                    return [cell, output, 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 at 0x10c20d400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML at 0x10bf93320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class Callbacks:\n",
    "    def __init__(self):\n",
    "        (figure, axes) = plt.subplots()\n",
    "        axes.set_aspect(1)\n",
    "        figure.canvas.mpl_connect('button_press_event', self.press)\n",
    "        figure.canvas.mpl_connect('button_release_event', self.release)\n",
    "\n",
    "    def start(self):\n",
    "        plt.show()\n",
    "\n",
    "    def press(self, event):\n",
    "        self.start_time = time.time()\n",
    "\n",
    "    def release(self, event):\n",
    "        self.end_time = time.time()\n",
    "        self.draw_click(event)\n",
    "        \n",
    "    def draw_click(self, event):\n",
    "        size = 4 * (self.end_time - self.start_time) ** 2\n",
    "        c1 = plt.Circle([event.xdata, event.ydata], 0.002,)\n",
    "        c2 = plt.Circle([event.xdata, event.ydata], 0.02 * size, alpha=0.2)\n",
    "        event.canvas.figure.gca().add_artist(c1)\n",
    "        event.canvas.figure.gca().add_artist(c2)\n",
    "        event.canvas.figure.show()\n",
    "\n",
    "cbs = Callbacks()\n",
    "cbs.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, we changed the callback to display a cicle instead of text. If you choose to press and hold, and then release a bit later, you will see that a second, transparent circle is displayed. The longer you hold, the larger the second transpent circle will be.\n",
    "\n",
    "Let's try something a little more involved, adapted from the [line-drawing example](http://matplotlib.org/users/event_handling.html#event-attributes) in the \"Event handling and picking\" chapter of the matplotlib [Advanced Guide](http://matplotlib.org/users/developer.html):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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.focus_on_mousover = false;\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this.root.attr('style', 'display: inline-block');\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",
       "            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",
       "            fig.waiting = false;\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",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "    canvas_div.resizable({ resize: mpl.debounce_resize(\n",
       "        function(event, ui) { fig.request_resize(ui.size.width, ui.size.height); }\n",
       "        , 50)});\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both;');\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;\")\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "    function mouse_event_fn(event) {\n",
       "        return fig.mouse_event(event, event['data']);\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",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keydown('key_release', canvas_keyboard_event);\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);\n",
       "        canvas.attr('height', height);\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",
       "\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",
       "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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (this.focus_on_mouseover && name === 'motion_notify')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button});\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 = function(event, name) {\n",
       "    /* Don't fire events just when a modifier is changed.  Modifiers are\n",
       "       sent along with other keys. */\n",
       "    if (event.keyCode >= 16 && event.keyCode <= 20) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    value = '';\n",
       "    if (event.ctrlKey) {\n",
       "        value += \"ctrl+\";\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        value += \"alt+\";\n",
       "    }\n",
       "    value += String.fromCharCode(event.keyCode).toLowerCase();\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        var format_dropdown = this.format_dropdown;\n",
       "        var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "        this.ondownload(this, format);\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",
       "\n",
       "mpl.debounce_event = function(func, time){\n",
       "    var timer;\n",
       "    return function(event){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event); }, time);\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.debounce_resize = function(func, time){\n",
       "    var timer;\n",
       "    return function(event, ui){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event, ui); }, time);\n",
       "    };\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\"], [\"\", \"\", \"\", \"\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pgf\", \"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",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           function() { },\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(fig.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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 (cell.output_area.outputs[j]['text/html'] == html_output) {\n",
       "                    var output = cell.output_area.outputs[j];\n",
       "                    return [cell, output, 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 at 0x10c5255f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML at 0x10c525630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "class LineBuilder:\n",
    "    def __init__(self, event_name='button_press_event'):\n",
    "        (self.figure, self.axes) = plt.subplots()\n",
    "        plt.xlim([0, 10])\n",
    "        plt.ylim([0, 10])\n",
    "        (self.xs, self.ys) = ([5], [5])\n",
    "        (self.line,) = self.axes.plot(self.xs, self.ys)\n",
    "        self.axes.set_title('Click the canvas to build line segments...')\n",
    "        self.canvas = self.figure.canvas\n",
    "        self.conn_id = self.canvas.mpl_connect(event_name, self.callback)\n",
    "\n",
    "    def start(self):\n",
    "        plt.show()\n",
    "\n",
    "    def update_line(self, event):\n",
    "        self.xs.append(event.xdata)\n",
    "        self.ys.append(event.ydata)\n",
    "        self.line.set_data(self.xs, self.ys)\n",
    "\n",
    "    def callback(self, event):\n",
    "        if event.inaxes != self.line.axes:\n",
    "            return\n",
    "        self.update_line(event)\n",
    "        self.canvas.draw()\n",
    "\n",
    "lb = LineBuilder()\n",
    "lb.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For dessert, here's the [slider demo](http://matplotlib.org/users/screenshots.html#slider-demo) from matplotlib: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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.focus_on_mousover = false;\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this.root.attr('style', 'display: inline-block');\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",
       "            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",
       "            fig.waiting = false;\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",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "    canvas_div.resizable({ resize: mpl.debounce_resize(\n",
       "        function(event, ui) { fig.request_resize(ui.size.width, ui.size.height); }\n",
       "        , 50)});\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both;');\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;\")\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "    function mouse_event_fn(event) {\n",
       "        return fig.mouse_event(event, event['data']);\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",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keydown('key_release', canvas_keyboard_event);\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);\n",
       "        canvas.attr('height', height);\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",
       "\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",
       "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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (this.focus_on_mouseover && name === 'motion_notify')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button});\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 = function(event, name) {\n",
       "    /* Don't fire events just when a modifier is changed.  Modifiers are\n",
       "       sent along with other keys. */\n",
       "    if (event.keyCode >= 16 && event.keyCode <= 20) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    value = '';\n",
       "    if (event.ctrlKey) {\n",
       "        value += \"ctrl+\";\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        value += \"alt+\";\n",
       "    }\n",
       "    value += String.fromCharCode(event.keyCode).toLowerCase();\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        var format_dropdown = this.format_dropdown;\n",
       "        var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "        this.ondownload(this, format);\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",
       "\n",
       "mpl.debounce_event = function(func, time){\n",
       "    var timer;\n",
       "    return function(event){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event); }, time);\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.debounce_resize = function(func, time){\n",
       "    var timer;\n",
       "    return function(event, ui){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event, ui); }, time);\n",
       "    };\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\"], [\"\", \"\", \"\", \"\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pgf\", \"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",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           function() { },\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(fig.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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 (cell.output_area.outputs[j]['text/html'] == html_output) {\n",
       "                    var output = cell.output_area.outputs[j];\n",
       "                    return [cell, output, 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 at 0x10c9573c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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      ],
      "text/plain": [
       "<IPython.core.display.HTML at 0x10c957470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import widgets\n",
    "from matplotlib.backend_bases import MouseEvent\n",
    "\n",
    "def get_sine_data(amplitude=5, frequency=3, time=None):\n",
    "    return amplitude * np.sin(2 * np.pi * frequency * time)\n",
    "\n",
    "class SineSliders:\n",
    "    def __init__(self, amplitude=5, frequency=3):\n",
    "        (self.figure, _) = plt.subplots()\n",
    "        self.configure()\n",
    "        self.a0 = amplitude\n",
    "        self.f0 = frequency\n",
    "        self.time = np.arange(0.0, 1.0, 0.001)\n",
    "        self.data = get_sine_data(\n",
    "            amplitude=self.a0, frequency=self.f0, time=self.time)\n",
    "        (self.line,) = plt.plot(self.time, self.data, lw=2, color='red')\n",
    "        self.axes_amp  = plt.axes([0.25, 0.15, 0.65, 0.03])\n",
    "        self.axes_freq = plt.axes([0.25, 0.1, 0.65, 0.03])\n",
    "        self.setup_sliders()\n",
    "        self.setup_reset_button()\n",
    "        self.setup_color_selector()\n",
    "\n",
    "    def start(self):\n",
    "        plt.show()\n",
    "\n",
    "    def configure(self):\n",
    "        plt.subplots_adjust(left=0.25, bottom=0.25)\n",
    "        plt.axis([0, 1, -10, 10])\n",
    "\n",
    "    def setup_sliders(self):\n",
    "        self.slider_amp = widgets.Slider(\n",
    "            self.axes_amp, 'Amp', 0.1, 10.0, valinit=self.a0)\n",
    "        self.slider_freq = widgets.Slider(\n",
    "            self.axes_freq, 'Freq', 0.1, 30.0, valinit=self.f0)\n",
    "        self.slider_freq.on_changed(self.update)\n",
    "        self.slider_amp.on_changed(self.update)\n",
    "        \n",
    "    def setup_reset_button(self):\n",
    "        reset_axes = plt.axes([0.8, 0.025, 0.1, 0.04])\n",
    "        reset_button = widgets.Button(reset_axes, 'Reset', hovercolor='0.975')\n",
    "        reset_button.on_clicked(self.reset)\n",
    "        \n",
    "    def setup_color_selector(self):\n",
    "        radio_axes = plt.axes([0.025, 0.5, 0.15, 0.15], aspect=1)\n",
    "        radio_select = widgets.RadioButtons(\n",
    "            radio_axes, ('red', 'blue', 'green',), active=0)\n",
    "        radio_select.on_clicked(self.switchcolor)\n",
    "        \n",
    "    def update(self, val):\n",
    "        self.data = get_sine_data(self.slider_amp.val,\n",
    "                                  self.slider_freq.val,\n",
    "                                  self.time)\n",
    "        self.line.set_ydata(self.data)\n",
    "        self.figure.canvas.draw()\n",
    "\n",
    "    def reset(self, event):\n",
    "        self.slider_freq.reset()\n",
    "        self.slider_amp.reset()\n",
    "\n",
    "    def switchcolor(self, label):\n",
    "        self.line.set_color(label)\n",
    "        self.figure.canvas.draw()\n",
    "\n",
    "sldrs = SineSliders(amplitude=0.5, frequency=20)\n",
    "sldrs.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Limitations of *nbagg*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The IPython Notebook AGG backend currently doesn't provide support for the following matplotlib events:\n",
    " * ``key_press``\n",
    " * ``scroll_event`` (mouse scrolling)\n",
    " * mouse right click\n",
    " * mouse doubleclick\n",
    " \n",
    "Also, mouse movement events can be a little inconsistent (this can be especially true if your browser or other application is running at a significant CPU%, causing events to be missed in matplotlib running in an IPython notebook).\n",
    " \n",
    "However, we can still use IPython while switching to a new backend for matplotlib. To see which backends are available to you:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['CocoaAgg',\n",
       " 'GTK',\n",
       " 'GTK3Agg',\n",
       " 'GTK3Cairo',\n",
       " 'GTKAgg',\n",
       " 'GTKCairo',\n",
       " 'MacOSX',\n",
       " 'Qt4Agg',\n",
       " 'Qt5Agg',\n",
       " 'TkAgg',\n",
       " 'WX',\n",
       " 'WXAgg',\n",
       " 'WebAgg',\n",
       " 'agg',\n",
       " 'cairo',\n",
       " 'emf',\n",
       " 'gdk',\n",
       " 'nbAgg',\n",
       " 'pdf',\n",
       " 'pgf',\n",
       " 'ps',\n",
       " 'svg',\n",
       " 'template']"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(set(mpl.rcsetup.interactive_bk + mpl.rcsetup.non_interactive_bk + mpl.rcsetup.all_backends))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Currently keyboard events aren't supported by IPython and the matplotlib *nbagg* backend. So, for this section, we'll switch over to your default platform's GUI toolkit in matplotlib.\n",
    "\n",
    "You have two options for the remainder of this notebook:\n",
    "\n",
    "1. Use IPython from a terminal, or\n",
    "1. Switch backends in this notebook.\n",
    "\n",
    "For terminal use, change directory to where you cloned this notebook's git repo and then fire up IPython:\n",
    "\n",
    "```bash\n",
    "$ cd interaction\n",
    "$ make repl\n",
    "```\n",
    "\n",
    "The ``repl`` target is a convenience that uses a Python virtual environment and the downloaded dependencies for this notebook. Once you're at the IPython prompt, you may start entering code with automatically-configured access to the libraries needed by this notebook.\n",
    "\n",
    "If you would like to continue using this notebook instead of switching to the terminal, you'll need to change your backend for the remaining examples. For instance:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.switch_backend('MacOSX')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Keyboard Events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's prepare for our key event explorations by defining some support functions ahead of time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def make_data(n, c):\n",
    "    r = 4 * c * np.random.rand(n) ** 2\n",
    "    theta = 2 * np.pi * np.random.rand(n)\n",
    "    area = 200 * r**2 * np.random.rand(n)\n",
    "    return (r, area, theta)\n",
    "\n",
    "def generate_data(n, c):\n",
    "    while True:\n",
    "        yield make_data(n, c)\n",
    "                 \n",
    "def make_plot(radius, area, theta, axes=None):\n",
    "    scatter = axes.scatter(\n",
    "        theta, radius, c=theta, s=area, cmap=cmap)\n",
    "    scatter.set_alpha(0.75)\n",
    "\n",
    "def update_plot(radius, area, theta, event):\n",
    "    figure = event.canvas.figure\n",
    "    axes = figure.gca()\n",
    "    make_plot(radius, area, theta, axes)\n",
    "    event.canvas.draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's make a class which will:\n",
    "\n",
    "* dispatch based upon keys pressed and\n",
    "* navigate through our endless data set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class Carousel:\n",
    "    def __init__(self, data):\n",
    "        (self.left, self.right) = ([], [])\n",
    "        self.gen = data\n",
    "        self.last_key = None\n",
    "\n",
    "    def start(self, axes):\n",
    "        make_plot(*self.next(), axes=axes)\n",
    "\n",
    "    def prev(self):\n",
    "        if not self.left:\n",
    "            return []\n",
    "        data = self.left.pop()\n",
    "        self.right.insert(0, data)\n",
    "        return data\n",
    "\n",
    "    def next(self):\n",
    "        if self.right:\n",
    "            data = self.right.pop(0)\n",
    "        else:\n",
    "            data = next(self.gen)\n",
    "        self.left.append(data)\n",
    "        return data\n",
    "\n",
    "    def reset(self):\n",
    "        self.right = self.left + self.right\n",
    "        self.left = []\n",
    "        \n",
    "    def dispatch(self, event):\n",
    "        if event.key == \"right\":\n",
    "            self.handle_right(event)\n",
    "        elif event.key == \"left\":\n",
    "            self.handle_left(event)\n",
    "        elif event.key == \"r\":\n",
    "            self.handle_reset(event)\n",
    "\n",
    "    def handle_right(self, event):\n",
    "        print(\"Got right key ...\")\n",
    "        if self.last_key == \"left\":\n",
    "            self.next()\n",
    "        update_plot(*self.next(), event=event)\n",
    "        self.last_key = event.key\n",
    "    def handle_left(self, event):\n",
    "        print(\"Got left key ...\")\n",
    "        if self.last_key == \"right\":\n",
    "            self.prev()\n",
    "        data = self.prev()\n",
    "        if data:\n",
    "            update_plot(*data, event=event)\n",
    "        self.last_key = event.key\n",
    "\n",
    "    def handle_reset(self, event):\n",
    "        print(\"Got reset key ...\")\n",
    "        self.reset()\n",
    "        update_plot(*self.next(), event=event)\n",
    "        self.last_key = event.key"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One more class, to help keep things clean:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class CarouselManager:\n",
    "    def __init__(self, density=300, multiplier=1):\n",
    "        (figure, self.axes) = plt.subplots(\n",
    "            figsize=(12,12), subplot_kw={\"polar\": \"True\"})\n",
    "        self.axes.hold(False)\n",
    "        data = generate_data(density, multiplier)\n",
    "        self.carousel = Carousel(data)\n",
    "        _ = figure.canvas.mpl_connect(\n",
    "            'key_press_event', self.carousel.dispatch)\n",
    "    def start(self):\n",
    "        self.carousel.start(self.axes)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can take it for a spin:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Got right key ...\n",
      "Got right key ...\n",
      "Got right key ...\n",
      "Got right key ...\n",
      "Got left key ...\n",
      "Got left key ...\n",
      "Got left key ...\n",
      "Got reset key ...\n",
      "Got right key ...\n",
      "Got right key ...\n"
     ]
    }
   ],
   "source": [
    "cm = CarouselManager(multiplier=2)\n",
    "cm.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the GUI canvas, you should see something that looks a bit like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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xYINVVR1pWkSaFhFx5a7G7e3OkbPYytmoPvEJltdwmEWWFXH+fH/2/A4Am05s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\nSYkAQACQgPblPl2VoKlASpWgqxIminmsnJrEpo0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oFtOQZQmVis2Vb0QLeOzZZ3BqxWZo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U8YsUnmvTfeJ9nHSCaF0Lm3Z/ilCofGKhnc+SPPoyD+1cy+aNd5btdSqRfD6P55ZOOJ9uYtH5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\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r25m/7MYMprlcutCIaswh3gM+/3U7MyklzS2dCNJ4jNEFoJraNZw4uYfFDbcP+q6qsoGt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\nag6aIyeOQ80XrilZjscF5vIw2utr2fv5UebOmj2l7Qgh6O3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TG/7he0Te2cLT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\n90Hu4+OkYuEsDry5iZTLgerI/IL2vSJJROUU0XgMu7X/fYgHQ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TsJ6JBQ4DARNE3jH174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\nfYI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6ahGcHA4dl8skFIpXtC/F8z//LrfNGB9r1WKwpI0Y5sZc5zLp7emgbdos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LOqhkwmhVTO+cxdIRDCwLbDJGJhDKNwu6WUoq21nWsuGy/+TTCVs5lAEIsWHE41VREcJ4+h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Hrmd4eIinH/s70qeOsCWRoaspijHDtVB9QzOjIxpjqSHqnPmPE64XcKovw6kBn1g0wS3X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\nJJm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+LlsjtcJCrbBUp+2r1fBkWWd/KFsUpfrDRJu9kfqRUT+ylJWB3PCQ3OAC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\nqe6fXQWBI8exVRSlkiRTvx8TMAH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      "text/plain": [
       "<IPython.core.display.Image at 0x10c99a6d8>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(\"figure_1.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The plot shoudl have the focus automatically. Press the right and left arrow keys to navigate through your data sets. You can return to the beginning of the data set by typing \"r\", the \"reset\" key. Play with it a bit, to convince yourself that it's really doing what we intended :-)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Axes and Figure Events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def enter_axes(event):\n",
    "    print('enter_axes', event.inaxes)\n",
    "    event.inaxes.patch.set_facecolor('yellow')\n",
    "    event.canvas.draw()\n",
    "\n",
    "def leave_axes(event):\n",
    "    print('leave_axes', event.inaxes)\n",
    "    event.inaxes.patch.set_facecolor('white')\n",
    "    event.canvas.draw()\n",
    "\n",
    "def enter_figure(event):\n",
    "    print('enter_figure', event.canvas.figure)\n",
    "    event.canvas.figure.patch.set_facecolor('red')\n",
    "    event.canvas.draw()\n",
    "\n",
    "def leave_figure(event):\n",
    "    print('leave_figure', event.canvas.figure)\n",
    "    event.canvas.figure.patch.set_facecolor('grey')\n",
    "    event.canvas.draw()\n",
    "\n",
    "class FigureAndAxesFocus:\n",
    "    def __init__(self):\n",
    "        (self.figure, (self.axes1, self.axes2)) = plt.subplots(2, 1)\n",
    "        title = \"Hover mouse over figure or its axes to trigger events\"\n",
    "        self.figure.suptitle(title)\n",
    "        self.setup_figure_events()\n",
    "        self.setup_axes_events()\n",
    "\n",
    "    def start(self):\n",
    "        plt.show()\n",
    "        \n",
    "    def setup_figure_events(self):\n",
    "        self.figure.canvas.mpl_connect(\n",
    "            \"figure_enter_event\", enter_figure)\n",
    "        self.figure.canvas.mpl_connect(\n",
    "            \"figure_leave_event\", leave_figure)\n",
    "\n",
    "    def setup_axes_events(self):\n",
    "        self.figure.canvas.mpl_connect(\n",
    "            \"axes_enter_event\", enter_axes)\n",
    "        self.figure.canvas.mpl_connect(\n",
    "            \"axes_leave_event\", leave_axes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try it out:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enter_figure Figure(640x440)\n",
      "enter_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "leave_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "enter_axes Axes(0.125,0.1;0.775x0.363636)\n",
      "leave_axes Axes(0.125,0.1;0.775x0.363636)\n",
      "enter_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "leave_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "enter_axes Axes(0.125,0.1;0.775x0.363636)\n",
      "leave_axes Axes(0.125,0.1;0.775x0.363636)\n",
      "leave_figure Figure(640x440)\n",
      "enter_figure Figure(640x440)\n",
      "leave_figure Figure(640x440)\n",
      "enter_figure Figure(640x440)\n",
      "enter_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "leave_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "enter_axes Axes(0.125,0.1;0.775x0.363636)\n",
      "leave_axes Axes(0.125,0.1;0.775x0.363636)\n",
      "enter_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "leave_axes Axes(0.125,0.536364;0.775x0.363636)\n",
      "leave_figure Figure(640x440)\n"
     ]
    }
   ],
   "source": [
    "faaf = FigureAndAxesFocus()\n",
    "faaf.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Object Picking"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next event we will mention is a special one: the event of an object being \"picked\". Every ``Artist`` instance (naturally including any subclassess of ``Artist``) has an attribute ``picker``. Setting this attribute is what enables object picking in matplotlib.\n",
    "\n",
    "The definition of *picked* can vary, depending upon context. For instance, setting ``Artist.picked`` has the following results:\n",
    " * If ``True``, picking is enabled for the artist object and a ``pick_event`` will fire any time a mouse event occurs over the artist object in the figure.\n",
    " * If a number (e.g., ``float`` or ``int``), the value is interpreted as a \"tolerance\"; if the event's data (such as $x$ and $y$ values) is within the value of that tolerance, the ``pick_event`` will fire.\n",
    " * If a callable, then the provided function or method returns a boolean value which determines if the ``pick_event`` is fired.\n",
    " * If ``None``, picking is disabled.\n",
    " \n",
    "The example below is adapted from the matplotlib project's [picking exercise](http://matplotlib.org/users/event_handling.html#picking-exercise) in the [Advanced User's Guide](http://matplotlib.org/users/developer.html). In it, we create a data set of 100 arrays, each containing 1000 random numbers. The sample mean and standard deviation of each is determined, and a plot is made of the 100 means vs the 100 standard deviations. We then connect the line created by the plot command to the pick event, and plot the original (randomly generated) time series data corresponding to the \"picked\" points. If more than one point is within the tolerance of the clicked on point, we display multiple subplots for the time series which fall into our tolerance (in this case, 10 pixels)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class DataPicker:\n",
    "    def __init__(self, range):\n",
    "        self.range = range\n",
    "        self.figure = self.axes = self.line = None\n",
    "        self.xs = np.random.rand(*self.range)\n",
    "        self.means = np.mean(self.xs, axis=1)\n",
    "        self.stddev = np.std(self.xs, axis=1)\n",
    "\n",
    "    def start(self):\n",
    "        self.create_main_plot()\n",
    "        self.figure.canvas.mpl_connect('pick_event', self.handle_pick)\n",
    "        plt.show()\n",
    "\n",
    "    def create_main_plot(self):\n",
    "        (self.figure, self.axes) = plt.subplots()\n",
    "        self.axes.set_title('click on point to plot time series')\n",
    "        (self.line,) = self.axes.plot(self.means, self.stddev, 'o', picker=10)\n",
    "\n",
    "    def create_popup_plot(self, n, event):\n",
    "        popup_figure = plt.figure()\n",
    "        for subplotnum, i in enumerate(event.ind):\n",
    "            popup_axes = popup_figure.add_subplot(n, 1, subplotnum + 1)\n",
    "            popup_axes.plot(self.xs[i])\n",
    "            text_data = (self.means[i], self.stddev[i])\n",
    "            popup_axes.text(\n",
    "                0.05, 0.9,\n",
    "                '$\\mu$=%1.3f\\n$\\sigma$=%1.3f' % text_data,\n",
    "                transform=popup_axes.transAxes, va='top')\n",
    "            popup_axes.set_ylim(-0.5, 1.5)\n",
    "        popup_figure.show()\n",
    "\n",
    "    def handle_pick(self, event):\n",
    "        if event.artist != self.line:\n",
    "            return\n",
    "        n = len(event.ind)\n",
    "        if not n:\n",
    "            return\n",
    "        self.create_popup_plot(n, event)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dp = DataPicker(range=(100,1000))\n",
    "dp.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Compound Event Handling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This section discusses the combination of multiple events or other sources of data in order to provide a more highly customized user experience, whether that be for visual plot updates, preparation of data, setting object properties, or updating widgets. This is what we will refer to as \"compound events\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Navigation Toolbar"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "matplotlib backends come with a feature we haven't discussed yet: a widget for [interactive navigation](http://matplotlib.org/users/navigation_toolbar.html). This widget is available for all the backends (including the ``nbagg`` backend for IPython, when not in \"inline\" mode). In brief, the functionality associated with the buttons in the widget is as follows:\n",
    " * *Home*: returns the figure to its originally rendered state\n",
    " * *Previous*: return to the previous view in the plot's history\n",
    " * *Next*: move to the next view in the plot's history\n",
    " * *Pan/Zoom*: pan across the plot by clicking and holding the left mouse button; zoom by clicking and holding the right mouse button (behavior differs between Cartesian and Polar plots)\n",
    " * *Zoom-to-Rectangle*: zoom in on a selected portion of the plot\n",
    " * *Subplot Configuration*: configure the display of subplots via a pop-up widget with various parameters\n",
    " * *Save*: save the plot, in its currently displayed state, to a file\n",
    " \n",
    "When a toolbar action is engaged, the ``NavigationToolbar`` instance sets the current mode. For instance, when the *Zoom-to-Rectangle* button is clicked, the mode will be set to ``zoom rect``. When in *Pan/Zoom*, the mode will be set to ``pan/zoom``. These can be used in conjunction with the supported events to fire callbacks in response to toolbar activity.\n",
    "\n",
    "In point of fact, the toolbar class, ``matplotlib.backend_bases.NavigationToolbar2`` is an excellent place to look for examples of \"compound events\". Let's examine the *Pan/Zoom* button. The class tracks the following via attributes that get set:\n",
    " * The connection id for a \"press\" event\n",
    " * The connection id for a \"release\" event\n",
    " * The connection id for a \"mouse move\" event (correlated to a mouse drag later)\n",
    " * Whether the toolbar is \"active\"\n",
    " * What the toolbar mode is\n",
    " * What the zoom mode is\n",
    "\n",
    "During toolbar setup, toolbar button events are connected to callbacks. When these buttons are pressed, and the callbacks are fired, old events are disconnected and new ones connected. In this way, chains of events may be set up with a particular sequence of events firing only a particular set of callbacks and in a particular order."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Specialized Events"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code in ``matplotlib.backend_bases.NavigationToolbar2`` is a great place to go to get some ideas about how you might combine events in your own projects. You might have a workflow that requires responses to plot updates, but only if a series of other events has taken place first. You can accomplish these by connecting events to and disconnecting them from various callbacks."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interactive Panning and Zooming"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's go back to the toolbar for a practical example of creating a compound event.\n",
    "\n",
    "The problem we want to address is this: when a user pans or zooms out of the range of previously computed data in a plotted area, they are presented with parts of an empty grid with no visualization. It would be nice if we could put our new-found event callback skills to use in order to solve this issue.\n",
    "\n",
    "Let's look at an example where it would be useful to have the plot figure refreshed when it is moved: a topographic map. Geophysicsist Joe Kington has provided some nice answers on Stackoverflow regarding matplotlib in the context of terrain gradients. In [one particular example](http://stackoverflow.com/a/16531438), he showed how to view the flow of water from random wells on a topographic map. We're going to do a couple of things with this example:\n",
    "\n",
    "* add a color map to give it the look of a physical map\n",
    "* give altitude in meters, and most importantly,\n",
    "* create a class that can update the map via a method call\n",
    "\n",
    "Our custom color map and Joe's equations for generating a topographical map have been saved to ``./lib/topo.py``. We'll need to import those. Then we can define ``TopoFlowMap``, our wrapper class that will be used to update the plot when we pan:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class TopoFlowMap:\n",
    "    def __init__(self, xrange=None, yrange=None, seed=1):\n",
    "        self.xrange = xrange or (0,1)\n",
    "        self.yrange = yrange or (0,1)\n",
    "        self.seed = seed\n",
    "        (self.figure, self.axes) = plt.subplots(figsize=(12,8))\n",
    "        self.axes.set_aspect(1)\n",
    "        self.colorbar = None\n",
    "        self.update()\n",
    "\n",
    "    def get_ranges(self, xrange, yrange):\n",
    "        if xrange:\n",
    "            self.xrange = xrange\n",
    "        if yrange:\n",
    "            self.yrange = yrange\n",
    "        return (xrange, yrange)\n",
    "\n",
    "    def get_colorbar_axes(self):\n",
    "        colorbar_axes = None\n",
    "        if self.colorbar:\n",
    "            colorbar_axes = self.colorbar.ax\n",
    "            colorbar_axes.clear()\n",
    "        return colorbar_axes\n",
    "    \n",
    "    def get_filled_contours(self, coords):\n",
    "        return self.axes.contourf(cmap=topo.land_cmap, *coords.values())\n",
    "\n",
    "    def update_contour_lines(self, filled_contours):\n",
    "        contours = self.axes.contour(filled_contours, colors=\"black\", linewidths=2)\n",
    "        self.axes.clabel(contours, fmt=\"%d\", colors=\"#330000\")\n",
    "\n",
    "    def update_water_flow(self, coords, gradient):\n",
    "        self.axes.streamplot(\n",
    "            coords.get(\"x\")[:,0],\n",
    "            coords.get(\"y\")[0,:],\n",
    "            gradient.get(\"dx\"),\n",
    "            gradient.get(\"dy\"),\n",
    "            color=\"0.6\",\n",
    "            density=1,\n",
    "            arrowsize=2)\n",
    "        \n",
    "    def update_labels(self):\n",
    "        self.colorbar.set_label(\"Altitude (m)\")\n",
    "        self.axes.set_title(\"Water Flow across Land Gradients\", fontsize=20)\n",
    "        self.axes.set_xlabel(\"$x$ (km)\")\n",
    "        self.axes.set_ylabel(\"$y$ (km)\")\n",
    "\n",
    "    def update(self, xrange=None, yrange=None):\n",
    "        (xrange, yrange) = self.get_ranges(xrange, yrange)\n",
    "        (coords, grad) = topo.make_land_map(self.xrange, self.yrange, self.seed)\n",
    "        self.axes.clear()\n",
    "        colorbar_axes = self.get_colorbar_axes()\n",
    "        filled_contours = self.get_filled_contours(coords)\n",
    "        self.update_contour_lines(filled_contours)\n",
    "        self.update_water_flow(coords, grad)\n",
    "        self.colorbar = self.figure.colorbar(filled_contours, cax=colorbar_axes)\n",
    "        self.update_labels()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's switch back to the IPython Notebook backend, so we have a reference image saved in the notebook:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.switch_backend('nbAgg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's draw the topographical map next, without any ability to update when panning:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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.focus_on_mousover = false;\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this.root.attr('style', 'display: inline-block');\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",
       "            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",
       "            fig.waiting = false;\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",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "    canvas_div.resizable({ resize: mpl.debounce_resize(\n",
       "        function(event, ui) { fig.request_resize(ui.size.width, ui.size.height); }\n",
       "        , 50)});\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both;');\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;\")\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "    function mouse_event_fn(event) {\n",
       "        return fig.mouse_event(event, event['data']);\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",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keydown('key_release', canvas_keyboard_event);\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);\n",
       "        canvas.attr('height', height);\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",
       "\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",
       "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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (this.focus_on_mouseover && name === 'motion_notify')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button});\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 = function(event, name) {\n",
       "    /* Don't fire events just when a modifier is changed.  Modifiers are\n",
       "       sent along with other keys. */\n",
       "    if (event.keyCode >= 16 && event.keyCode <= 20) {\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    value = '';\n",
       "    if (event.ctrlKey) {\n",
       "        value += \"ctrl+\";\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        value += \"alt+\";\n",
       "    }\n",
       "    value += String.fromCharCode(event.keyCode).toLowerCase();\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        var format_dropdown = this.format_dropdown;\n",
       "        var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "        this.ondownload(this, format);\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",
       "\n",
       "mpl.debounce_event = function(func, time){\n",
       "    var timer;\n",
       "    return function(event){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event); }, time);\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.debounce_resize = function(func, time){\n",
       "    var timer;\n",
       "    return function(event, ui){\n",
       "        clearTimeout(timer);\n",
       "        timer = setTimeout(function(){ func(event, ui); }, time);\n",
       "    };\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\"], [\"\", \"\", \"\", \"\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pgf\", \"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",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           function() { },\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(fig.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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 (cell.output_area.outputs[j]['text/html'] == html_output) {\n",
       "                    var output = cell.output_area.outputs[j];\n",
       "                    return [cell, output, 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 at 0x11026aeb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      ],
      "text/plain": [
       "<IPython.core.display.HTML at 0x11026ad30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tfm = TopoFlowMap(xrange=(0,1.5), yrange=(0,1.5), seed=1732)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you click the \"pan/zoom\" button on the navigation toolbar, and then click+hold on the figure, you can move it about. Note that, when you do so, nothing gets redrawn.\n",
    "\n",
    "Since we do want to redraw, and there is no \"pan event\" to connect to, what are our options? Well, two come to mind:\n",
    " * piggy back on the ``draw_event``, which fires each time the canvas is moved, or\n",
    " * use the ``button_release_event`` which will fire when the panning is complete\n",
    " \n",
    "If our figure was easy to draw with simple equations, the first option would probably be fine. However, we're doing some multivariate calculus on our simulated topography; as you might have noticed, our plot does not render immediately. So let's go with the second option.\n",
    "\n",
    "There's an added bonus, though, that will make our lives easier: the ``NavigationTool2`` keeps track of the mode it is in on it's ``mode`` attribute. Let's use that to save some coding!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "class TopoFlowMapManager:\n",
    "    def __init__(self, xrange=None, yrange=None, seed=1):\n",
    "        self.map = TopoFlowMap(xrange, yrange, seed)\n",
    "        _ = self.map.figure.canvas.mpl_connect(\n",
    "            'button_release_event', self.handle_pan_zoom_release)\n",
    "\n",
    "    def start(self):\n",
    "        plt.show()\n",
    "        \n",
    "    def handle_pan_zoom_release(self, event):\n",
    "        if event.canvas.toolbar.mode != \"pan/zoom\":\n",
    "            return\n",
    "        self.map.update(event.inaxes.get_xlim(),\n",
    "                        event.inaxes.get_ylim())\n",
    "        event.canvas.draw()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's switch back to the native backend (in my case, that's ``MacOSX``; you may need ``Qt5Agg``, ``WXAgg``, or ``GTK3Agg``):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.switch_backend('MacOSX')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the next bit of code, and then start panning around and releasing; you should see the new data displayed after the callbacks fires off the recalculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tfmm = TopoFlowMapManager(xrange=(0,1.5), yrange=(0,1.5), seed=1732)\n",
    "tfmm.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is not a perfect topographical model, so sometimes you will see colors get shifted as the range of altitudes decreases or increases in a given view. Certainly close enough to demonstrate this use case, though :-)\n",
    "\n",
    "Another thing you could do is add support for ``zoom rect`` such that the contour lines don't get angled (due to sparse data sample spacing), but stay smoothly curved no matter how far you zoom in. Given the example above, that should be fairly easy to implement, and we leave it as a fun exercise for the motivated reader :-)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.2"
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 },
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}