triaxis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fine Structure Constant according to Atiyah's work"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note to the reader:\n",
    "---------------------------\n",
    "\n",
    "In this tutorial we'll be using the following list of Symbols\n",
    "\n",
    "### Basic Math Symbols\n",
    "\n",
    "≠ ± ∓ ÷ × ∙ – √ ‰ ⊗ ⊕ ⊖ ⊘ ⊙ ≤ ≥ ≦ ≧ ≨ ≩ ≺ ≻ ≼ ≽ ⊏ ⊐ ⊑ ⊒ ² ³ °\n",
    "\n",
    "### Geometry Symbols\n",
    "\n",
    "∠ ∟ ° ≅ ~ ‖ ⟂ ⫛\n",
    "\n",
    "### Algebra Symbols\n",
    "\n",
    "≡ ≜ ≈ ∝ ∞ ≪ ≫ ⌊⌋ ⌈⌉ ∘∏ ∐ ∑ ⋀ ⋁ ⋂ ⋃ ⨀ ⨁ ⨂ 𝖕 𝖖 𝖗\n",
    "\n",
    "### Set Theory Symbols\n",
    "\n",
    "∅ ∖ ∁ ↦ ↣ ∩ ∪ ⊆ ⊂ ⊄ ⊊ ⊇ ⊃ ⊅ ⊋ ⊖ ∈ ∉ ∋ ∌ ℕ ℤ ℚ ℝ ℂ ℵ ℶ ℷ ℸ 𝓟\n",
    "\n",
    "### Logic Symbols\n",
    "\n",
    "¬ ∨ ∧ ⊕ → ← ⇒ ⇐ ↔ ⇔ ∀ ∃ ∄ ∴ ∵ ⊤ ⊥ ⊢ ⊨ ⫤ ⊣\n",
    "\n",
    "### Calculus and Analysis Symbols\n",
    "\n",
    "∫ ∬ ∭ ∮ ∯ ∰ ∇ ∆ δ ∂ ℱ ℒ ℓ\n",
    "\n",
    "### Greek Letters\n",
    "\n",
    "𝛢𝛼 𝛣𝛽 𝛤𝛾 𝛥𝛿 𝛦𝜀𝜖 𝛧𝜁 𝛨𝜂 𝛩𝜃𝜗 𝛪𝜄 𝛫𝜅 𝛬𝜆 𝛭𝜇 𝛮𝜈 𝛯𝜉 𝛰𝜊 𝛱𝜋 𝛲𝜌 𝛴𝜎 𝛵𝜏 𝛶𝜐 𝛷𝜙𝜑 𝛸𝜒 𝛹𝜓 𝛺𝜔"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reduced Electron Compton Wavelength is given by :\n",
    "\n",
    "ƛ$_{e}\\,=\\hbar/c\\cdot m_{e}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/latex": [
       "$\\displaystyle 3.8615926754860414e-13$"
      ],
      "text/plain": [
       "3.8615926754860414e-13"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reduced Electron Compton Wavelength is given by :\n",
    "scipy.constants.hbar / (scipy.constants.c * scipy.constants.m_e)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples of multi axis 3D plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Geo Dim GC couple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#import IPython\n",
    "%matplotlib notebook\n",
    "#%matplotlib inline\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from itertools import product, combinations\n",
    "\n",
    "#plt.figure(figsize=(w, h), dpi=d)\n",
    "#figsize=(15,7.5), dpi= 80\n",
    "\n",
    "fig = plt.figure(figsize=(15,7.5))\n",
    "#plt.figure(figsize=(15,7.5), dpi=80)\n",
    "ax = fig.gca(projection='3d')\n",
    "ax.set_aspect(\"equal\")\n",
    "\n",
    "# draw cube\n",
    "r = [-1, 1]\n",
    "t = [-1, 2]\n",
    "u = [-1, 1]\n",
    "for s, e in combinations(np.array(list(product(r, t, u))), 2):\n",
    "    if np.sum(np.abs(s-e)) == r[1]-r[0]:\n",
    "        ax.plot3D(*zip(s, e), color=\"b\")\n",
    "for s, e in combinations(np.array(list(product(r, t, u))), 2):\n",
    "    if np.sum(np.abs(s-e)) == t[1]-t[0]:\n",
    "        ax.plot3D(*zip(s, e), color=\"b\")\n",
    "\n",
    "# draw sphere\n",
    "#u, v = np.mgrid[0:2*np.pi:20j, 0:np.pi:10j]\n",
    "#x = np.cos(u)*np.sin(v)\n",
    "#y = np.sin(u)*np.sin(v)\n",
    "#z = np.cos(v)\n",
    "#ax.plot_wireframe(x, y, z, color=\"r\")\n",
    "\n",
    "# draw a point\n",
    "ax.scatter([-1], [2], [-1], color=\"g\", s=100)\n",
    "\n",
    "# draw a vector\n",
    "from matplotlib.patches import FancyArrowPatch\n",
    "from mpl_toolkits.mplot3d import proj3d\n",
    "\n",
    "\n",
    "class Arrow3D(FancyArrowPatch):\n",
    "\n",
    "    def __init__(self, xs, ys, zs, *args, **kwargs):\n",
    "        FancyArrowPatch.__init__(self, (0, 0), (0, 0), *args, **kwargs)\n",
    "        self._verts3d = xs, ys, zs\n",
    "\n",
    "    def draw(self, renderer):\n",
    "        xs3d, ys3d, zs3d = self._verts3d\n",
    "        xs, ys, zs = proj3d.proj_transform(xs3d, ys3d, zs3d, renderer.M)\n",
    "        self.set_positions((xs[0], ys[0]), (xs[1], ys[1]))\n",
    "        FancyArrowPatch.draw(self, renderer)\n",
    "\n",
    "a = Arrow3D([-1.10, 1], [2.10, -1], [-1.1, 1], mutation_scale=20,\n",
    "            lw=1, arrowstyle=\"-|>\", color=\"k\")\n",
    "# Demo 2: color\n",
    "ax.text(-0.3, -1.2, 0, \"$R_{GC}/\\lambdabar_{e}$\", fontsize=24, color='green')\n",
    "ax.text(-1.5, -2, -1, \"$R/\\lambdabar_{e}$\", fontsize=24, color='black')\n",
    "ax.text(-1.5, 0.8, 1, \"$M^\\prime/m_{e}$\", fontsize=24, color='green')\n",
    "ax.text(1.1, 1, -1, \"$t/t_{e}$\", fontsize=24, color='black')\n",
    "#plt.axis('off')\n",
    "ax.set_xlabel('Log T', fontsize=14, color='black')\n",
    "ax.set_ylabel('Log L', fontsize=14, color='black')\n",
    "ax.set_zlabel('Log M', fontsize=14, color='black')\n",
    "\n",
    "#ax.text2D(0.05, 0.95, \"Geo Dimensional Couple\", transform=ax.transAxes)\n",
    "#ax.text2D(0.05, 0.95, \"$M^\\prime/m_{e}$\", transform=ax.transAxes)\n",
    "#ax.text2D(0.95, 0.05, \"$t/t_{e}$\", transform=ax.transAxes)\n",
    "#ax.text2D(0.02, 0.05, \"$R/\\lambdabar_{e}$\", transform=ax.transAxes)\n",
    "#plt.tick_params(\n",
    "#    axis='x',      # changes apply to the x-axis\n",
    "#    which='both',      # both major and minor ticks are affected\n",
    "#    bottom=False,      # ticks along the bottom edge are off\n",
    "#    top=False,         # ticks along the top edge are off\n",
    "#    labelbottom=False) # labels along the bottom edge are off\n",
    "#ax.yaxis.set_ticks_position('none') \n",
    "#plt.xticks([], [])\n",
    "#plt.yticks([], [])\n",
    "#plt.zticks([], [])\n",
    "plt.setp( ax.get_xticklabels(), visible=False)\n",
    "plt.setp( ax.get_yticklabels(), visible=False)\n",
    "plt.setp( ax.get_zticklabels(), visible=False)\n",
    "ax.add_artist(a)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples of multi axis multi scale plot for a slope of ln(2)/4\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### I) Example of multi axis multi scale plot\n",
    "Work to be continued"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### II) Example of multi axis multi scale plot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### III) Example of multi axis multi scale plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: Cannot change to a different GUI toolkit: qt. Using notebook instead.\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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\" width=\"864\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "%matplotlib qt\n",
    "#%matplotlib inline\n",
    "import pylab\n",
    "import numpy as np\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from mpl_toolkits.mplot3d import proj3d\n",
    "fig = pylab.figure(figsize=(12, 9))\n",
    "ax = fig.add_subplot(111, projection = '3d')\n",
    "x = [0, 10, 10, 14, 14, 14.56, 18, 22, 22, 23.3, 25.17, 26, 30, 30, 31.556]\n",
    "y = [0, 1, 2, 3, 3, 3.14, 4, 5, 5, 5.33, 5.78, 6, 7, 7, 7.38]\n",
    "z = [0, np.log(np.log(274.072)), np.log(np.log(268.6)), np.log(np.log(83432)), np.log(np.log(83782)), np.log(np.log(245901)), np.log(np.log(6.842e9)), np.log(np.log(1.3011e19)), np.log(np.log(1.834e19)), np.log(np.log(7.52e24)), np.log(np.log(2.46e36)), np.log(np.log(2.126e39)), np.log(np.log(9.656e82)), np.log(np.log(4.258e78)), np.log(np.log(2.350e99))]\n",
    "sc = ax.scatter(x,y,z)\n",
    "# now try to get the display coordinates of the first point\n",
    "\n",
    "x2, y2, _ = proj3d.proj_transform(10,2,1.72, ax.get_proj())\n",
    "x3, y3, _ = proj3d.proj_transform(30,7,5, ax.get_proj())\n",
    "x4, y4, _ = proj3d.proj_transform(14.56,3.14,2.51, ax.get_proj())\n",
    "x5, y5, _ = proj3d.proj_transform(14,3,2.427, ax.get_proj())\n",
    "x6, y6, _ = proj3d.proj_transform(23.3,5.3,4.078, ax.get_proj())\n",
    "x7, y7, _ = proj3d.proj_transform(26,6,4.506, ax.get_proj())\n",
    "\n",
    "label = pylab.annotate(\n",
    "    \"Mean Pion\", \n",
    "    xy = (x2, y2), xytext = (-20, 20),\n",
    "    textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "    bbox = dict(boxstyle = 'round,pad=0.5', fc = 'white', alpha = 0.5),\n",
    "    arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))\n",
    "\n",
    "label = pylab.annotate(\n",
    "    \"Rydberg Wavelength\", \n",
    "    xy = (x5, y5), xytext = (-20, 20),\n",
    "    textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "    bbox = dict(boxstyle = 'round,pad=0.5', fc = 'red', alpha = 0.5),\n",
    "    arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))\n",
    "\n",
    "label = pylab.annotate(\n",
    "    \"Higgs Boson\", \n",
    "    xy = (x4, y4), xytext = (-20, 20),\n",
    "    textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "    bbox = dict(boxstyle = 'round,pad=0.5', fc = 'green', alpha = 0.5),\n",
    "    arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))\n",
    "\n",
    "label = pylab.annotate(\n",
    "    \"Kotov Cycle * 2pi.a\", \n",
    "    xy = (x6, y6), xytext = (-20, 20),\n",
    "    textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "    bbox = dict(boxstyle = 'round,pad=0.5', fc = 'red', alpha = 0.5),\n",
    "    arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))\n",
    "\n",
    "label = pylab.annotate(\n",
    "    \"Hubble Diameter * 2 pi\", \n",
    "    xy = (x7, y7), xytext = (-20, 20),\n",
    "    textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "    bbox = dict(boxstyle = 'round,pad=0.5', fc = 'red', alpha = 0.5),\n",
    "    arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))\n",
    "\n",
    "label = pylab.annotate(\n",
    "    \"Super Cycle\", \n",
    "    xy = (x3, y3), xytext = (-20, 20),\n",
    "    textcoords = 'offset points', ha = 'right', va = 'bottom',\n",
    "    bbox = dict(boxstyle = 'round,pad=0.5', fc = 'green', alpha = 0.5),\n",
    "    arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))\n",
    "\n",
    "\n",
    "def update_position(e):\n",
    "    x2, y2, _ = proj3d.proj_transform(10,2,1.72, ax.get_proj())\n",
    "    label.xy = x2,y2\n",
    "    label.update_positions(fig.canvas.renderer)\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "def update_position(e):\n",
    "    x3, y3, _ = proj3d.proj_transform(30,7,5, ax.get_proj())\n",
    "    label.xy = x3,y3\n",
    "    label.update_positions(fig.canvas.renderer)\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "def update_position(e):\n",
    "    x4, y4, _ = proj3d.proj_transform(14.56, 3.14, 2.51, ax.get_proj())\n",
    "    label.xy = x4,y4\n",
    "    label.update_positions(fig.canvas.renderer)\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "def update_position(e):\n",
    "    x5, y5, _ = proj3d.proj_transform(14, 3, 2.427, ax.get_proj())\n",
    "    label.xy = x5,y5\n",
    "    label.update_positions(fig.canvas.renderer)\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "def update_position(e):\n",
    "    x6, y6, _ = proj3d.proj_transform(23.3,5.3,4.078, ax.get_proj())\n",
    "    label.xy = x6,y6\n",
    "    label.update_positions(fig.canvas.renderer)\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "def update_position(e):\n",
    "    x7, y7, _ = proj3d.proj_transform(23.3,5.3,4.078, ax.get_proj())\n",
    "    label.xy = x7,y7\n",
    "    label.update_positions(fig.canvas.renderer)\n",
    "    fig.canvas.draw()\n",
    "    \n",
    "fig.canvas.mpl_connect('button_release_event', update_position)\n",
    "pylab.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
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