Notebooks/Interp/Interp.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interpolation and Curve Fitting\n",
    "### by [Richard W. Evans](https://sites.google.com/site/rickecon/), February 2020\n",
    "The code in this Jupyter notebook was written using Python 3.7. This data file and image file are stored along with the Jupyter notebook file `Interp.ipynb` in the public GitHub repository [https://github.com/rickecon/Notebooks/blob/master/Interp/](https://github.com/rickecon/Notebooks/blob/master/Interp/).\n",
    "\n",
    "For teaching and learning purposes, it is best to clear all cell output by selecting `Cell` then `All Output` then `Clear` from the menu across the top of this notebook. However, this notebook comes with all the cells' output displayed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Introduction\n",
    "The general broad definition of interpolation \"a method of constructing new data points within the range of a discrete set of known data points\" (*Wikipedia*, \"[Interpolation](https://en.wikipedia.org/wiki/Interpolation)\"). Interpolation is a nonparametric method of inferring unknown data from known data. Examples include estimating a linear regression and using that regression to predict $\\hat{y}_i$ values from $X_i$ values that were not in the data. It also includes curve-fitting in which the curve is required to pass through all the data points.\n",
    "\n",
    "1. We will define as **regression interpolation** the type of interpolation in which the estimated function need not or cannot pass through all the data points.\n",
    "2. We will define as **spline interpolation** the type of interpolation in which the estimated function necessarily passes through all the data points.\n",
    "\n",
    "You should look at the documentation for [`scipy.interpolate`](https://docs.scipy.org/doc/scipy/reference/tutorial/interpolate.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Types of interpolants"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1. Curve fitting or regression interpolation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.1.1. Piecewise constant curve fit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.1.2. Polynomial curve fit\n",
    "High order polynomials, orthogonal polynomials (Chebyshev polynomials), pitfalls of high order polynomials."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.1.3. Kernel density estimator curve fit\n",
    "Non-parametric density estimator."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2. Splines"
   ]
  },
  {
   "attachments": {
    "Screen%20Shot%202020-02-24%20at%2010.14.19%20AM.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.1. Piecewise constant interpolation\n",
    "Divide the range of the data into bins, one bin per data point. You can choose the bin edges to be anywhere between data points. The interpolated value of the function is the data point value of that bin. This can be called nearest neighbor interpolation. You can see how this is related to a $K$ nearest neighbor (KNN) classifier. A $K=1$ KNN classifier would choose the bin edges as the midpoints between the data points.\n",
    "![Screen%20Shot%202020-02-24%20at%2010.14.19%20AM.png](attachment:Screen%20Shot%202020-02-24%20at%2010.14.19%20AM.png)"
   ]
  },
  {
   "attachments": {
    "Screen%20Shot%202020-02-24%20at%2010.30.02%20AM.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.2. Linear spline\n",
    "A practical definition of a linear spline is to connect each of the data points with a line. Let each data point be labeled $x_i\\in\\{x_1,x_2,...x_N\\}$. Let the linear function between points $x_i$ and $x_{i+1}$ be defined as the following line,\n",
    "\\begin{equation*}\n",
    "  f_{i}(x) = a_i x + b_i\n",
    "\\end{equation*}\n",
    "The solution for $a_i$ and $b_i$ is just the two-point equation for a line.\n",
    "\\begin{equation*}\n",
    "  a_i = \\frac{f(x_{i+1}) - f(x_i)}{x_{i+1} - x_i} \\quad b_i = f(x_i) - a_i x_i\n",
    "\\end{equation*}\n",
    "![Screen%20Shot%202020-02-24%20at%2010.30.02%20AM.png](attachment:Screen%20Shot%202020-02-24%20at%2010.30.02%20AM.png)"
   ]
  },
  {
   "attachments": {
    "Screen%20Shot%202020-02-24%20at%2010.36.55%20AM.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.2.3. Cubic spline\n",
    "A cubic spline fits a cubic polynomial between points $x_i$ and $x_{i+1}$. Let the cubic polynomial between $x_i$ and $x_{i+1}$ defined as the following,\n",
    "\\begin{equation*}\n",
    "  f_{i}(x) = a_i x^3 + b_i x^2 + c_i x + d_i\n",
    "\\end{equation*}\n",
    "The cubic polynomial must satisfy four conditions to pin down the four parameters $a_i$, $b_i$, $c_i$, and $d_i$. The polynomial must pass through both end points (two conditions) and the second derivatives must be zero at the end points (two conditions).\n",
    "![Screen%20Shot%202020-02-24%20at%2010.36.55%20AM.png](attachment:Screen%20Shot%202020-02-24%20at%2010.36.55%20AM.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Examples\n",
    "\n",
    "### 3.1. Fertility rates\n",
    "The U.S. National Vital Statistics Reports, Volume 64, Number 1,    January 15, 2015, Table 3, final 2013 data [http://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_01.pdf](http://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_01.pdf) shows number of births per 1,000 females by age group"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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=\"639.4444613839378\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Fertility rate $f_{s}$')"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import MultipleLocator\n",
    "%matplotlib notebook\n",
    "\n",
    "# Hard code input births data by age group\n",
    "# Add two zeros on the end of each vector\n",
    "# Age bins are 9, 10, 10-14, 15-17, 18-19, 20-24, 25-29, 30-34, 35-39,\n",
    "# 40-44, 45-49, 55, 56. First two and last two are not data\n",
    "\n",
    "fert_data = (np.array([0.0, 0.0, 0.3, 12.3, 47.1, 80.7, 105.5, 98.0,\n",
    "                       49.3, 10.4, 0.8, 0.0, 0.0]) / 2000)\n",
    "age_midp = np.array([9, 10, 12, 16, 18.5, 22, 27, 32, 37, 42, 47,\n",
    "                     55, 56])\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(age_midp, fert_data, s=40, c='blue', marker='o',\n",
    "            label='Data')\n",
    "# for the minor ticks, use no labels; default NullFormatter\n",
    "minorLocator = MultipleLocator(1)\n",
    "ax.xaxis.set_minor_locator(minorLocator)\n",
    "plt.grid(b=True, which='major', color='0.65', linestyle='-')\n",
    "plt.xlabel(r'Age $s$')\n",
    "plt.ylabel(r'Fertility rate $f_{s}$')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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=\"639.4444613839378\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xb19101d90>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import scipy.interpolate as si\n",
    "\n",
    "fert_func = si.interp1d(age_midp, fert_data, kind='cubic')\n",
    "\n",
    "age_fine = np.linspace(age_midp.min(), age_midp.max(), 100)\n",
    "fert_fine = fert_func(age_fine)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "plt.scatter(age_midp, fert_data, s=40, c='blue', marker='o',\n",
    "            label='Data')\n",
    "plt.scatter(age_fine, fert_fine, s=20, c='red', marker='o',\n",
    "            alpha=0.5, label='Cubic spline points')\n",
    "plt.plot(age_fine, fert_fine, label='Cubic spline')\n",
    "# for the minor ticks, use no labels; default NullFormatter\n",
    "minorLocator = MultipleLocator(1)\n",
    "ax.xaxis.set_minor_locator(minorLocator)\n",
    "plt.grid(b=True, which='major', color='0.65', linestyle='-')\n",
    "plt.title('Fitted fertility rate function by age ($f_{s}$)',\n",
    "          fontsize=20)\n",
    "plt.xlabel(r'Age $s$')\n",
    "plt.ylabel(r'Fertility rate $f_{s}$')\n",
    "plt.xlim((age_midp.min() - 1, age_midp.max() + 1))\n",
    "plt.ylim((-0.15 * (fert_fine.max()),\n",
    "          1.15 * (fert_fine.max())))\n",
    "plt.legend(loc='upper right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2. Interpolation through lots of points (regression)\n",
    "This is what I have you doing in your problem set.\n",
    "Good functions are ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}