data-visualization/0001-matplotlib-animation/matplotlib-animation-notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Matplotlib animation in Jupyter Notebook\n",
    "\n",
    "This is a notebook for the medium article [Matplotlib Animations in Jupyter Notebook](https://bindichen.medium.com/matplotlib-animations-in-jupyter-notebook-4422e4f0e389)\n",
    "\n",
    "Please check out article for instructions\n",
    "\n",
    "**License**: [BSD 2-Clause](https://opensource.org/licenses/BSD-2-Clause)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 248,
       "width": 386
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 2*np.pi, 100)\n",
    "y = np.sin(x)\n",
    "\n",
    "plt.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Animations with interactive plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Enable interactive plot\n",
    "%matplotlib notebook\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.animation import FuncAnimation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"432\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "line, = ax.plot([])\n",
    "\n",
    "ax.set_xlim(0, 2*np.pi)\n",
    "ax.set_ylim(-1.1, 1.1)\n",
    "\n",
    "def animate(frame_num):\n",
    "    y = np.sin(x + 2*np.pi * frame_num/100)\n",
    "    line.set_data((x, y))\n",
    "    return line\n",
    "\n",
    "anim = FuncAnimation(fig, animate, frames=100, interval=5)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Animations with embedded HTML5 video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.animation import FuncAnimation\n",
    "from IPython import display\n",
    "\n",
    "# Turn off matplotlib plot in Notebook\n",
    "plt.ioff()\n",
    "# Pass the ffmpeg path\n",
    "plt.rcParams['animation.ffmpeg_path'] = '/Users/chen5/Downloads/ffmpeg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<video width=\"432\" height=\"288\" controls autoplay loop>\n",
       "  <source type=\"video/mp4\" src=\"data:video/mp4;base64,AAAAIGZ0eXBNNFYgAAACAE00ViBpc29taXNvMmF2YzEAAAAIZnJlZQAAYTptZGF0AAACrgYF//+q\n",
       "3EXpvebZSLeWLNgg2SPu73gyNjQgLSBjb3JlIDE2MyByMzA1OSBiNjg0ZWJlIC0gSC4yNjQvTVBF\n",
       "Ry00IEFWQyBjb2RlYyAtIENvcHlsZWZ0IDIwMDMtMjAyMSAtIGh0dHA6Ly93d3cudmlkZW9sYW4u\n",
       "b3JnL3gyNjQuaHRtbCAtIG9wdGlvbnM6IGNhYmFjPTEgcmVmPTMgZGVibG9jaz0xOjA6MCBhbmFs\n",
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       "\">\n",
       "  Your browser does not support the video tag.\n",
       "</video>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "line, = ax.plot([])\n",
    "\n",
    "ax.set_xlim(0, 2*np.pi)\n",
    "ax.set_ylim(-1.1, 1.1)\n",
    "\n",
    "\n",
    "def animate(frame_num):\n",
    "    y = np.sin(x + 2*np.pi * frame_num/100)\n",
    "    line.set_data((x, y))\n",
    "    return line\n",
    "\n",
    "anim = FuncAnimation(fig, animate, frames=100, interval=20)\n",
    "\n",
    "video = anim.to_html5_video()\n",
    "html = display.HTML(video)\n",
    "display.display(html)\n",
    "plt.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Thanks for reading"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a notebook for the medium article [Matplotlib Animations in Jupyter Notebook](https://bindichen.medium.com/matplotlib-animations-in-jupyter-notebook-4422e4f0e389)\n",
    "\n",
    "Please check out article for instructions\n",
    "\n",
    "**License**: [BSD 2-Clause](https://opensource.org/licenses/BSD-2-Clause)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "data-visualization",
   "language": "python",
   "name": "data-visualization"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}