prml-figure-3.8.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PRML §3.3 Bayes linear regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "from scipy.stats import multivariate_normal\n",
    "from scipy.linalg import inv\n",
    "\n",
    "# cosmetics (change as you like)\n",
    "%matplotlib nbagg\n",
    "plt.style.use('seaborn-talk')\n",
    "plt.style.use('seaborn-darkgrid')\n",
    "plt.rcParams['image.cmap'] = 'viridis'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def gaussian(x, mu, beta):\n",
    "    \"\"\"1D Gaussian PDF N(x|mu,beta^-1).\"\"\"\n",
    "    return np.sqrt(beta/(2*np.pi)) * np.exp(-beta/2 * (x-mu)**2)\n",
    "\n",
    "def gaussian_basis(x, mu, sigma):\n",
    "    \"\"\"Gaussian basis function.\"\"\"\n",
    "    return np.exp(-(x-mu)**2 / (2*sigma))\n",
    "\n",
    "def Phi(x, mu=np.linspace(-1, 1, 11), sigma=0.04):\n",
    "    \"\"\"Calculate design matrix of Gaussian basis function.\"\"\"\n",
    "    return gaussian_basis(x[:,None], mu, sigma)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create model and data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 100\n",
    "M = 11\n",
    "\n",
    "alpha = 2\n",
    "beta = 25\n",
    "\n",
    "x_true = np.linspace(0, 1, N)\n",
    "y_true = np.sin(2*np.pi*x_true)\n",
    "\n",
    "np.random.seed(2018)\n",
    "x = np.random.uniform(0, 1, N)\n",
    "y = np.sin(2*np.pi*x) + np.random.normal(0, np.sqrt(1/beta), N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>"
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\" width=\"1800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x10bde45f8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(12, 4), dpi=150)\n",
    "fig.tight_layout(pad=3)\n",
    "\n",
    "ax.plot(x_true, y_true, label='True model')\n",
    "ax.plot(x, y, '.', c='gray', ms=10, label='Data')\n",
    "ax.set_xlim(0, 1)\n",
    "ax.set_ylim(-1.5, 1.5)\n",
    "ax.set_xlabel('$x$')\n",
    "ax.set_ylabel('$y$')\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate predictive distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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width=\"1800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m0 = np.zeros(M)\n",
    "S0 = alpha**-1 * np.identity(M)\n",
    "PhiN = Phi(x_true)\n",
    "\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12, 4), dpi=150)\n",
    "fig.tight_layout(pad=3)\n",
    "\n",
    "artists = []\n",
    "\n",
    "for n in range(1, N+1):\n",
    "    # calculate mn and Sn\n",
    "    Phin = Phi(x[:n])\n",
    "    Sn = inv(inv(S0) + beta * Phin.T@Phin)\n",
    "    mn = Sn @ (inv(S0)@m0 + beta * Phin.T@y[:n])\n",
    "    \n",
    "    mu = PhiN @ mn\n",
    "    sigma = (1/beta + (PhiN.T * (Sn@PhiN.T)).sum(0))**0.5\n",
    "    \n",
    "    ax.set_xlim(0, 1)\n",
    "    ax.set_ylim(-1.5, 1.5)\n",
    "    ax.set_xlabel('$x$')\n",
    "    ax.set_ylabel('$y$')\n",
    "    ax.set_title(f'$\\\\alpha={alpha}, \\\\beta={beta}$')\n",
    "    \n",
    "    im = []\n",
    "    im += ax.plot(x_true, y_true, '--', c='gray')\n",
    "    im += ax.plot(x[:n], y[:n], '.', c='gray', ms=10)\n",
    "    im += ax.plot(x_true, mu, c='#4878CF')\n",
    "    im += [ax.fill_between(x_true, mu+sigma, mu-sigma, color='#4878CF', alpha=0.25)]\n",
    "    im += [ax.text(0.04, -0.85, f'# of data = {n}', fontsize=15)]\n",
    "    \n",
    "    artists.append(im)\n",
    "\n",
    "ax.legend(['True model', 'Data', 'Predictive model ($\\pm 1 \\sigma$)'], loc=1)    \n",
    "ani = animation.ArtistAnimation(fig, artists, interval=250)\n",
    "ani.save(f'figure-3.8-alpha{alpha}.mp4')"
   ]
  },
  {
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}