Project.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Potrebne biblioteke:\n",
    "- numpy\n",
    "- scipy\n",
    "- sounddevice\n",
    "- matplotlib\n",
    "- rtttl (koristi se za parsiranje jezika za specifikaciju melodija)\n",
    "\n",
    "rtttl biblioteku instalirati komandom: `pip install rtttl`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Izvrsiti kod koji sadrzi potrebne importe i pomocne funkcije\n",
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import scipy.signal as signal\n",
    "import scipy.io.wavfile as wavfile\n",
    "import matplotlib.pyplot as pyplot\n",
    "import numpy.random as random\n",
    "import sounddevice as sd\n",
    "import math\n",
    "import rtttl\n",
    "\n",
    "# Kod za plot dtft-a koristen na vjezbama\n",
    "def plot_dtft(x, fs):\n",
    "    from scipy.fftpack import rfft, rfftfreq\n",
    "    \n",
    "    L = np.int(2**np.ceil(np.log2(len(x))))\n",
    "    X = rfft(x, L)\n",
    "    X /= L\n",
    "    F = rfftfreq(L, 1/fs)\n",
    "    \n",
    "    pyplot.figure()\n",
    "    pyplot.plot(F, 20*np.log10(np.abs(X)))\n",
    "    pyplot.xlabel('F [Hz]')\n",
    "    pyplot.ylabel('|X(F)| [dB]')\n",
    "\n",
    "def normalizeFloat(sound):\n",
    "    return sound / np.amax(np.abs(sound))\n",
    "\n",
    "def delaySound(sound, fs, delay):\n",
    "    padSamples = round(fs * delay)\n",
    "    return np.pad(sound, (padSamples, 0), mode = \"constant\", constant_values = 0)\n",
    "\n",
    "def padSound(sound, samples):\n",
    "    if sound.size >= samples:\n",
    "        return sound\n",
    "    return np.pad(sound, (0, samples - sound.size), mode = \"constant\", constant_values = 0)\n",
    "    \n",
    "def generateSilence(s, fs):\n",
    "    samples = round(s * fs)\n",
    "    return np.zeros(samples)\n",
    "\n",
    "# Prosiruje prvi ili drugi signal i sumira ih\n",
    "def padAndSum(sound1, sound2):\n",
    "    padding = max(sound1.size, sound2.size)\n",
    "    return padSound(sound1, padding) + padSound(sound2, padding)\n",
    "\n",
    "cMajor = [261.6256, 293.6648, 329.6276, 349.2282, 391.9954, 440.0000, 493.8833, 523.2511]\n",
    "\n",
    "def plotTime(time, synth):\n",
    "    pyplot.figure();\n",
    "    pyplot.xlabel(\"t[s]\");\n",
    "    pyplot.plot(time, synth);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Odredjivanje funkcije prenosa\n",
    "<img src=\"image/ks1.jpg\" />\n",
    "\n",
    "Primjecujemo sa slike da vazi:\n",
    "$$Y(Z) = A(Z)Z^{-N}$$\n",
    "$$A(Z) = X(Z) + Y(Z)H_d(Z)$$\n",
    "Uvrstavanjem druge jednacine u prvu i izrazavanjem $Y(Z)$ dobijamo:\n",
    "$$ Y(Z) = \\frac{X(Z)Z^{-N}}{1 - H_d(Z)Z^{-N}}$$ \n",
    "Djeljenjem jednacine sa $X(Z)$ dobijamo:\n",
    "$$ H(Z) = \\frac{Z^{-N}}{1 - H_d(Z)Z^{-N}}$$\n",
    "Uvrstavanjem $H_d(Z) = \\frac{1 + Z^{-N}}{2}$ dobijamo funkciju prenosa za dati sistem sa slike:\n",
    "$$H(Z) = \\frac{2Z^{-N}}{2 - Z^{-N} - Z^{-N - 1}}$$\n",
    "Odgovarajuca jednacina diferencija:\n",
    "$$ 2y(n) - y(n - N) - y(n - N - 1) = 2x(n - N) $$\n",
    "Iz jednacine diferencija dobijamo koeficijente koje koristimo za implementaciju filtra\n",
    "$$b_N =2, a_0 = 2, a_N = -1, a_{N+1} = -1 $$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2 Tacka\n",
    "\n",
    "f = 440\n",
    "FS = 48000\n",
    "N = round(FS / f - 0.5)\n",
    "b = np.zeros(N + 1)\n",
    "a = np.zeros(N + 2)\n",
    "\n",
    "# Koeficijenti dobijeni iz jednacine diferencija\n",
    "(b[N], a[0], a[N], a[N + 1]) = (2, 2, -1, -1)\n",
    "\n",
    "(w, H) = signal.freqz(b, a, FS * 2, True, fs = FS)\n",
    "\n",
    "# Amplitudni spektar\n",
    "pyplot.figure()\n",
    "pyplot.xlabel(\"f[Hz]\")\n",
    "pyplot.ylabel(\"|H(f)|\")\n",
    "ampSpectrum = np.abs(H)\n",
    "# Trazenje maksimalne vrijednosti i uzimanje iste za referentnu\n",
    "ampSpectrum = np.where(np.isinf(ampSpectrum), 0, ampSpectrum)\n",
    "pyplot.plot(w, 20 * np.log10(np.abs(H) / np.amax(ampSpectrum)))\n",
    "\n",
    "#Fazni spektar\n",
    "pyplot.figure()\n",
    "pyplot.xlabel(\"f[Hz]\")\n",
    "pyplot.ylabel(\"arg H(f)\")\n",
    "pyplot.plot(w, np.angle(H))\n",
    "\n",
    "# Amplitudski spektar bijelog suma\n",
    "noise = random.normal(0, 1, N)\n",
    "plot_dtft(noise, 48000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "U idealnom slucaju amplitudski spektar bijelog suma je konstantan(proizilazi iz cinjenice da je spektralna gustina snage bijelog suma konstanta funkcija). To govori da u idealnom slucaju svi harmonici imaju istu snagu te odgovarajucim filtrom je dovoljno izdvojiti frekvencije \"koje nam trebaju\". "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tacka 3\n",
    "\n",
    "# Rezultat funkcije je trojka(vremenska osa, dobijena frekvencija, sintetizovan zvuk)\n",
    "def karplusStrong(f, fs, l):\n",
    "    N = round(fs / f - 0.5)\n",
    "    actualFreq = FS / (N + 0.5)\n",
    "    (b, a) = (np.zeros(N + 1), np.zeros(N + 2))\n",
    "    (b[N], a[0], a[N], a[N + 1]) = (2, 2, -1, -1)\n",
    "    totalSamples = round(l * fs)\n",
    "    \n",
    "    #Generisanje bijelog suma\n",
    "    noise = random.normal(0, 1, N)\n",
    "\n",
    "    # Dodavanje nula na kraj generisanog ulaza (s ciljem da se dobije ton zeljenog trajanja)\n",
    "    inputNoise = padSound(noise, totalSamples)\n",
    "    result = signal.lfilter(b, a, inputNoise)\n",
    "    \n",
    "    # Normalizacija odmjeraka na opseg (-1, 1)\n",
    "    normalized = normalizeFloat(result)\n",
    "    time = np.linspace(0, l, totalSamples)\n",
    "    return time, actualFreq, normalized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Tacka 4\n",
    "# Generisanje A tona duzine 1s\n",
    "l = 1\n",
    "FS = 48000\n",
    "f = 440\n",
    "(time, actualFreq, synth) = karplusStrong(f, FS, l)\n",
    "sd.play(synth, FS)\n",
    "\n",
    "# Signal u vremenu\n",
    "plotTime(time, synth)\n",
    "\n",
    "# Amplitudni spektar\n",
    "plot_dtft(synth, FS)\n",
    "wavfile.write(f\"{f}.wav\", FS, synth.astype(np.float32))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mozemo primjetiti da je harmonik frekvencije 440 znatno vece amplitude u odnosu na ostale."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "C dur frekvencije:  [261.6256, 293.6648, 329.6276, 349.2282, 391.9954, 440.0, 493.8833, 523.2511]\n",
      "Dobijene frekvencije:  [261.58038147138967, 293.57798165137615, 329.89690721649487, 349.09090909090907, 391.83673469387753, 438.35616438356163, 492.3076923076923, 524.5901639344262]\n",
      "Razlika:  [0.04521853 0.08681835 0.26930722 0.13729091 0.15866531 1.64383562\n",
      " 1.57560769 1.33906393]\n"
     ]
    }
   ],
   "source": [
    "# Tacka 5\n",
    "# Generisanje c-dur ljestvice\n",
    "cMajorActualFreq = []\n",
    "FS = 48000\n",
    "l = 0.8\n",
    "result = np.array([])\n",
    "# U svakoj iteraciji generisemo ton frekvencije iz c-dur ljestvice\n",
    "for i, freq in enumerate(cMajor):\n",
    "    time, actualFreq, synth = karplusStrong(freq, FS, l)\n",
    "    cMajorActualFreq.append(actualFreq)\n",
    "    result = np.concatenate((result, synth))\n",
    "sd.play(result, FS)\n",
    "\n",
    "wavfile.write(\"c major.wav\", FS, result.astype(np.float32))\n",
    "print(\"C dur frekvencije: \", cMajor)\n",
    "print(\"Dobijene frekvencije: \", cMajorActualFreq)\n",
    "print(\"Razlika: \", np.abs(np.array(cMajor) - np.array(cMajorActualFreq)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Funkcija prenosa filtra sa kontrolom trajanja tona\n",
    "\n",
    "Jedina razlika u odnosu na prethodni sistem jeste filtar u povratnoj grani.\n",
    "$$H_d(Z) = \\rho(1 - S) + \\rho S Z^{-1}$$\n",
    "Uvrstavanjem $H_d(Z)$ u prethodno izvedenu funkciju prenosa za proizvoljan filtar u povratnoj grani dobijamo:\n",
    "$$ H(Z) = \\frac{Z^{-N}}{1 - Z^{-N}(\\rho(1 - S) + \\rho SZ^{-1})} $$\n",
    "Sredjivanjem dobijamo:\n",
    "$$ H(Z) = \\frac{Z^{-N}}{1 - \\rho(1 - S)Z^{-N} - \\rho SZ^{-N - 1}} $$\n",
    "Jednacina diferencija:\n",
    "$$ y(n) - \\rho(1 - S)y(n - N) - \\rho Sy(n - N - 1) = x(n - N) $$\n",
    "Koeficijenti:\n",
    "$$ b_N = 1, a_0 = 1, a_N = -\\rho(1 - S), a_{N + 1} = -\\rho S $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tacka 6\n",
    "# Implementacija filtra\n",
    "def karplusStrong2(f, fs, l, S, t60):\n",
    "    N = round(fs / f - 0.5)\n",
    "    actualFreq = FS / (N + 0.5)\n",
    "    b = np.zeros(N + 1)\n",
    "    a = np.zeros(N + 2)\n",
    "    ro = 0.001 ** (1 / (f * t60))\n",
    "    (b[N], a[0], a[N], a[N + 1]) = (1, 1, -ro * (1 - S), -ro * S)\n",
    "    totalSamples = round(l * fs)\n",
    "    noise = random.normal(0, 1, N)\n",
    "    inputNoise = np.concatenate((noise, np.zeros(totalSamples - N)))\n",
    "    result = signal.lfilter(b, a, inputNoise)\n",
    "    normalized = normalizeFloat(result)\n",
    "    time = np.linspace(0, l, totalSamples)\n",
    "    return time, actualFreq, normalized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "S = 0.1, t60 = 1\n",
      "S = 0.2, t60 = 1\n",
      "S = 0.4, t60 = 1\n",
      "S = 0.5, t60 = 1\n",
      "S = 0.8, t60 = 1\n",
      "S = 0.9, t60 = 1\n",
      "S = 0.5, t60 = 0.5\n",
      "S = 0.5, t60 = 1\n",
      "S = 0.5, t60 = 1.5\n",
      "S = 0.5, t60 = 2\n"
     ]
    }
   ],
   "source": [
    "# Demonstracija uticaja razlicitih parametara na ton frekvencije 440 herca\n",
    "f = 440\n",
    "FS = 48000\n",
    "l = 3\n",
    "params = [(0.1, 1,), (0.2, 1), (0.4, 1), (0.5, 1), \n",
    "          (0.8, 1), (0.9, 1), (0.5, 0.5), (0.5, 1), (0.5, 1.5), (0.5, 2)]\n",
    "\n",
    "for param in params:\n",
    "    synth = karplusStrong2(f, FS, l, param[0], param[1])[2]\n",
    "    print(f\"S = {param[0]}, t60 = {param[1]}\")\n",
    "    sd.play(synth, FS)\n",
    "    sd.wait()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mozemo potvrditi da ton najduze traje u slucajevima kada je parametar S blize 0 ili 1, i sto je parametar t60 veci"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "S = 0.1, t60 = 1\n",
      "S = 0.2, t60 = 1\n",
      "S = 0.4, t60 = 1\n",
      "S = 0.5, t60 = 1\n",
      "S = 0.8, t60 = 1\n",
      "S = 0.9, t60 = 1\n",
      "S = 0.5, t60 = 0.5\n",
      "S = 0.5, t60 = 1\n",
      "S = 0.5, t60 = 1.5\n",
      "S = 0.5, t60 = 2\n"
     ]
    }
   ],
   "source": [
    "# Tacka 7\n",
    "# Uticaj parametara na c-dur ljestvicu\n",
    "FS = 48000\n",
    "l = 0.8\n",
    "S = 0.5\n",
    "t60 = 2\n",
    "params = [(0.1, 1,), (0.5, 1), (0.9, 1), (0.5, 0.5), (0.5, 1), (0.5, 1.5), (0.5, 2)]\n",
    "\n",
    "def generateCMajor(FS, l, S, t60):\n",
    "    result = np.array([])\n",
    "    for freq in cMajor:\n",
    "        synth = karplusStrong2(freq, FS, l, S, t60)[2]\n",
    "        result = np.concatenate((result, synth))\n",
    "    return result\n",
    "\n",
    "for param in params:\n",
    "    print(f\"S = {param[0]}, t60 = {param[1]}\")\n",
    "    cMajorSynth = generateCMajor(FS, l, param[0], param[1])\n",
    "    sd.play(cMajorSynth, FS)\n",
    "    wavfile.write(f\"c major_S={S}_t60={t60}.wav\", FS, cMajorSynth.astype(np.float32))\n",
    "    sd.wait()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Filtar sa kontrolom polozaja trzalice\n",
    "<img src=\"image/ksb.jpg\"/>\n",
    "Funkcija prenosa zeljenog filtra se dobije mnozenjem $H_b(Z)$ i funkcije prenosa filtra iz prethodne tacke (oznaceno sa $H'(Z)$).\n",
    "$$ H_b(Z) = 1 - Z^{-\\lfloor \\beta N \\rfloor} $$\n",
    "$$ H(Z) = H_b(Z)H'(Z) $$\n",
    "\n",
    "$$ H(Z) = \\frac{Z^{-N} - Z^{-N - \\lfloor \\beta N \\rfloor}}{1 - \\rho(1 - S)Z^{-N} - \\rho SZ^{-N - 1}} $$\n",
    "\n",
    "Jednacina diferencija:\n",
    "$$ y(n) - \\rho(1 - S)y(n - N) - \\rho Sy(n - N - 1) = x(n - N) - x(n - N - \\lfloor \\beta N \\rfloor) $$\n",
    "\n",
    "Koeficijenti:\n",
    "$$ b_N = 1, b_{N + \\lfloor \\beta N \\rfloor} = -1, a_0 = 1, a_N = -\\rho(1 - S), a_{N + 1} = -\\rho S $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tacka 8\n",
    "# Implementacija filtra\n",
    "def karplusStrongFilter(f, fs, l, S, t60, beta):\n",
    "    N = round(FS / f - 0.5)\n",
    "    actualFreq = FS / (N + 0.5)\n",
    "    betaN = math.floor(beta * N)\n",
    "    b = np.zeros(N + betaN + 1)\n",
    "    a = np.zeros(N + 2)\n",
    "    ro = 0.001 ** (1 / (f * t60))\n",
    "    (b[N], b[N + betaN], a[0], a[N], a[N + 1]) = (1, -1, 1, -ro * (1 - S), -ro * S)\n",
    "    totalSamples = round(l * fs)\n",
    "    noise = random.normal(0, 1, N)\n",
    "    inputNoise = np.concatenate((noise, np.zeros(totalSamples - N)))\n",
    "    result = signal.lfilter(b, a, inputNoise)\n",
    "    normalized = normalizeFloat(result)\n",
    "    time = np.linspace(0, l, totalSamples)\n",
    "    return time, actualFreq, normalized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "beta = 0.01\n",
      "beta = 0.1\n",
      "beta = 0.5\n",
      "beta = 0.6\n",
      "beta = 0.7\n",
      "beta = 0.8\n",
      "beta = 0.9\n"
     ]
    }
   ],
   "source": [
    "# Demonstracija uticaja beta parametra na ton frekvencije 440 herca\n",
    "f = 440\n",
    "FS = 48000\n",
    "l = 3\n",
    "S = 0.5\n",
    "t60 = 1\n",
    "\n",
    "params = [0.01, 0.1, 0.5, 0.9]\n",
    "\n",
    "for param in params:\n",
    "    synth = karplusStrongFilter(f, FS, l, S, t60, param)[2]\n",
    "    print(f\"beta = {param}\")\n",
    "    sd.play(synth, FS)\n",
    "    sd.wait()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "beta = 0.01\n",
      "beta = 0.1\n",
      "beta = 0.5\n",
      "beta = 0.9\n"
     ]
    }
   ],
   "source": [
    "# Tacka 9\n",
    "# Demonstracija uticaja beta parametra na tonove c-dur ljestvice\n",
    "FS = 48000\n",
    "l = 1\n",
    "S = 0.5\n",
    "t60 = 3\n",
    "params = [0.01, 0.1, 0.5, 0.9]\n",
    "\n",
    "def generateCMajor(FS, l, S, t60, beta):\n",
    "    result = np.array([])\n",
    "    for freq in cMajor:\n",
    "        synth = karplusStrongFilter(freq, FS, l, S, t60, beta)[2]\n",
    "        result = np.concatenate((result, synth))\n",
    "    return result\n",
    "\n",
    "for param in params:\n",
    "    print(f\"beta = {param}\")\n",
    "    cMajorSynth = generateCMajor(FS, l, S, t60, param)\n",
    "    sd.play(cMajorSynth, FS)\n",
    "    wavfile.write(f\"c major_S={S}_t60={t60}_beta={param}.wav\", FS, cMajorSynth.astype(np.float32))\n",
    "    sd.wait()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Za $\\beta$ vrijednosti blize 0 ili 1 tonovi su \"cistiji\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tacka 10\n",
    "# Implementacija filtra\n",
    "\n",
    "\n",
    "def overdriveFilter(sample):\n",
    "    if sample >= 1:\n",
    "        return 2 / 3\n",
    "    elif sample <= -1:\n",
    "        return -2 / 3\n",
    "    else:\n",
    "        return sample - (sample ** 3) / 3\n",
    "    \n",
    "def karplusStrongOD(f, fs, l, S, t60, beta, g):\n",
    "    N = round(FS / f - 0.5)\n",
    "    actualFreq = FS / (N + 0.5)\n",
    "    betaN = math.floor(beta * N)\n",
    "    b = np.zeros(N + betaN + 1)\n",
    "    a = np.zeros(N + 2)\n",
    "    ro = 0.001 ** (1 / (f * t60))\n",
    "    (b[N], b[N + betaN], a[0], a[N], a[N + 1]) = (1, -1, 1, -ro * (1 - S), -ro * S)\n",
    "    totalSamples = round(l * fs)\n",
    "    noise = random.normal(0, 1, N)\n",
    "    inputNoise = np.concatenate((noise, np.zeros(totalSamples - N)))\n",
    "    result = signal.lfilter(b, a, inputNoise)\n",
    "    result *= g\n",
    "    overdrive = np.vectorize(overdriveFilter)\n",
    "    normalized = overdrive(result)\n",
    "    time = np.linspace(0, l, totalSamples)\n",
    "    return time, actualFreq, normalized\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Tacka 11\n",
    "# Demonstracija uticaja g parametra na tonove C-dur ljestvice.\n",
    "FS = 48000\n",
    "l = 1\n",
    "S = 0.5\n",
    "t60 = 3\n",
    "g = 1000\n",
    "beta = 0.5\n",
    "\n",
    "def generateCMajor(FS, l, S, t60, beta, g):\n",
    "    result = np.array([])\n",
    "    for freq in cMajor:\n",
    "        synth = karplusStrongOD(freq, FS, l, S, t60, beta, g)[2]\n",
    "        result = np.concatenate((result, synth))\n",
    "    return result\n",
    "\n",
    "cMajorSynth = generateCMajor(FS, l, S, t60, beta, g)\n",
    "\n",
    "# Utisacemo da ne bi izgubili sluh \n",
    "sd.play(0.01 * cMajorSynth, FS)\n",
    "wavfile.write(f\"c major_S={S}_t60={t60}_beta={param}_g={g}.wav\", FS, cMajorSynth.astype(np.float32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tacka 12\n",
    "# Funkcija za generisanje akorda\n",
    "# Prvi argument je niz frekvencija, drugi argument frekvecija odmjeravanja, treci argument duzina generisanog akorda.\n",
    "# Ukoliko elemenat u prvom nizu je par(tuple) onda je prvi elemenat u paru frekvencija, a drugi kasnjenje tona u sekundama.\n",
    "# Koristen je filtar sa kontrolom trajanja tona\n",
    "def generateChord(freqs, fs, l):\n",
    "    result = None\n",
    "    \n",
    "    for freq in freqs:\n",
    "        synth = None\n",
    "        delay = None\n",
    "        genFreq = None\n",
    "        \n",
    "        if isinstance(freq, tuple):\n",
    "            genFreq = freq[0]\n",
    "            delay = freq[1]\n",
    "        else:\n",
    "            genFreq = freq\n",
    "            \n",
    "        synth = karplusStrong2(genFreq, FS, l, 0.5, 2)[2]\n",
    "        \n",
    "        if delay is not None:\n",
    "            synth = delaySound(synth, fs, delay)\n",
    "            \n",
    "        if result is None:\n",
    "            result = synth\n",
    "        else:\n",
    "            result = padAndSum(result, synth)\n",
    "    \n",
    "    return normalizeFloat(result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [],
   "source": [
    "FS = 48000\n",
    "l = 5\n",
    "# C akord\n",
    "# Ton sa frekvencijom 329 herca je zakasnjen za 50ms , a ton frekvencije 392 herca za 100ms\n",
    "result = generateChord([261.6256, (329.6276, 0.05), (391.9954, 0.1)], FS, l)\n",
    "sd.play(result, FS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Tacka 13\n",
    "# Super mario brothers\n",
    "# Koristena rtttl biblioteka za parsiranje nokia RTTTL formata za prenos tonova\n",
    "parsedRtttl = None\n",
    "with open(\"smb.txt\") as file:\n",
    "     parsedRtttl = rtttl.parse_rtttl(file.read())\n",
    "    \n",
    "FS = 48000\n",
    "result = np.array([])\n",
    "for tone in parsedRtttl[\"notes\"]:\n",
    "    \n",
    "    # tone[\"duration\"] u ms\n",
    "    (freq, duration) = (tone[\"frequency\"], tone[\"duration\"] / 1000)\n",
    "    if freq == 0:\n",
    "        synth = generateSilence(duration, FS)\n",
    "    else:\n",
    "        synth = karplusStrong2(freq, FS, duration, 0.1, 2)[2]\n",
    "    result = np.concatenate((result, synth))\n",
    "\n",
    "sd.play(result, FS)"
   ]
  },
  {
   "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
}