index.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import plotly\n",
    "import IPython\n",
    "import ipywidgets\n",
    "\n",
    "from euler_parametrization import EulerParametrization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\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",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\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",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var 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 = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "e = EulerParametrization(jupyter=True)\n",
    "\n",
    "roll_slider = ipywidgets.FloatSlider(\n",
    "    min=-90, max=90, step=1, value=0, continuous_update=False\n",
    ")\n",
    "pitch_slider = ipywidgets.FloatSlider(\n",
    "    min=-90, max=90, step=1, value=0, continuous_update=False\n",
    ")\n",
    "yaw_slider = ipywidgets.FloatSlider(\n",
    "    min=-90, max=90, step=1, value=0, continuous_update=False\n",
    ")\n",
    "\n",
    "@ipywidgets.interact(roll=roll_slider, pitch=pitch_slider, yaw=yaw_slider)\n",
    "def interactive_animation(roll, pitch, yaw):\n",
    "    e.interactive_plot(roll, pitch, yaw)\n",
    "    IPython.display.display(e._figure)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "  Your browser does not support the video tag.\n",
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      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Needs `ffmpeg` installed in the system\n",
    "IPython.display.HTML(e.animation().to_html5_video())"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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