07_Curl.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Chapter 7 of [a guided tour of mathematical methods for the physical sciences](http://www.cambridge.org/nz/academic/subjects/physics/mathematical-methods/guided-tour-mathematical-methods-physical-sciences-3rd-edition#KUoGXYx5FTwytcUg.97) introduces the curl of a vector field. As with the previosuu topic of divergence, perhaps the most intuitive example is fluid flow. This flow represents a vector field, in which you could insert imaginary paddle wheels to describe the presence of \"curl\" or rotation in the field. These paddle wheels would capture well the physical interpretation of the curl operator, as established in our book:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"The component of the curl of a vector field ${\\bf v}$ in a certain direction is the closed line integral of ${\\bf v}$ along a closed path perpendicular to this direction, per unit surface area.\" Captured in mathematics, this is \n",
    "\n",
    "$$ \\frac{\\oint {\\bf v} \\cdot d{\\bf S}}{d{\\bf S}}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us set up a grid for fluid flow, where the curl of this particular vector field is also called [*vorticity*](https://en.wikipedia.org/wiki/Vorticity):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "\n",
    "# set up a normalized grid:\n",
    "dim= 10\n",
    "xarray= np.arange(-dim,dim)\n",
    "yarray= np.arange(-dim,dim)\n",
    "\n",
    "x,y = np.meshgrid(xarray,yarray)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rigid rotation \n",
    "In our book, we derived how fluid flow with a rigid rotation requires that the veloity increases with radius, and:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ff0083bc780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vx = -y\n",
    "vy = x\n",
    "\n",
    "# plot the flow lines:\n",
    "plt.figure()\n",
    "plt.quiver(x,y, vx, vy, pivot='mid')\n",
    "plt.xlabel(\"$x$-axis\")\n",
    "plt.ylabel(\"$y$-axis\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now numerically approximate the vertical component of the curl of this vector field by computing the line integral as the sum of a small square in our grid:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "xmin=3\n",
    "xmax=4\n",
    "ymin=3\n",
    "ymax=4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The closed line integral is reduced to a sum:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "bottom = -np.sum(vy[ymin,xmin:xmax])\n",
    "right = np.sum(vx[ymin:ymax,xmax])\n",
    "top = np.sum(vy[ymax,xmax:xmin:-1])\n",
    "left = -np.sum(vx[ymax:ymin:-1,xmin])\n",
    "area = (xmax-xmin)*(ymax-ymin)\n",
    "total = (top+bottom+left+right)/area"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's plot the flow and box, with the vertical component of the curl in its title: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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",
       "        this.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\", \"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 overriden (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": {
      "text/html": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('The line intregral of the red box is {:.3}'.format(total))\n",
    "plt.quiver(x,y, vx, vy, pivot='mid')\n",
    "\n",
    "# bottom, top, left and right side of the box, respectively:\n",
    "plt.plot(x[ymin,xmin:xmax+1],y[ymin,xmin:xmax+1],'r',alpha=0.5) # bottom\n",
    "plt.plot(x[ymax,xmax:xmin-1:-1],y[ymax,xmax:xmin-1:-1],'r',alpha=0.5) # top\n",
    "plt.plot(x[ymax:ymin-1:-1,xmin],y[ymax:ymin-1:-1,xmin],'r',alpha=0.5) # left\n",
    "plt.plot(x[ymin:ymax+1,xmax],y[ymin:ymax+1,xmax],'r',alpha=0.5) # right\n",
    "plt.xlabel(\"$x$-axis\")\n",
    "plt.ylabel(\"$y$-axis\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Varying the location of the box, you will find that what we derived in the book: the vorticity equals 2 everywhere! 1 for the rotation of the paddle wheel around the source, and 1 more for the shear introduced by the fluid flow that increases as a function of the radius."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A model for hurricane winds or the Biot Savart Law\n",
    "Let's now define a different fluid flow pattern where a rotational field decreases in amplitude radially away from the source. This model is equivalent to winds in a hurricane, or the magnetic field around a long vertical wire:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kvan637/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py:2: RuntimeWarning: invalid value encountered in true_divide\n",
      "  from ipykernel import kernelapp as app\n",
      "/home/kvan637/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py:3: RuntimeWarning: invalid value encountered in true_divide\n",
      "  app.launch_new_instance()\n"
     ]
    }
   ],
   "source": [
    "r= np.sqrt(x**2+y**2)\n",
    "vx = -y/r**2\n",
    "vy = x/r**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Apologies for the \"pesky\" warning, but can you figure out what invalid value python is complaining about? Where do you think these values are occurring? Maybe if we *plot* the fluid flow, things become more clear:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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",
       "        this.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\", \"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 overriden (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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.quiver(x,y, vx, vy, pivot='mid')\n",
    "plt.xlabel(\"$x$-axis\")\n",
    "plt.ylabel(\"$y$-axis\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Near the origin, the values of the flow get really big, so let us mask the singularity at the source:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kvan637/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py:2: RuntimeWarning: invalid value encountered in greater\n",
      "  from ipykernel import kernelapp as app\n",
      "/home/kvan637/anaconda3/lib/python3.5/site-packages/ipykernel/__main__.py:3: RuntimeWarning: invalid value encountered in greater\n",
      "  app.launch_new_instance()\n"
     ]
    }
   ],
   "source": [
    "threshold = 0.33\n",
    "Mx = np.abs(vx) > threshold\n",
    "My = np.abs(vy) > threshold\n",
    "vx = np.ma.masked_array(vx, mask=Mx)\n",
    "vy = np.ma.masked_array(vy, mask=My)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's define a box in this 2D flow, and compute the z-component of the vorticity:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "xmin=3\n",
    "xmax=4\n",
    "ymin=3\n",
    "ymax=4\n",
    "\n",
    "# closed line \"integral\".\n",
    "bottom = -np.sum(vy[ymin,xmin:xmax])\n",
    "right = np.sum(vx[ymin:ymax,xmax])\n",
    "top = np.sum(vy[ymax,xmax:xmin:-1])\n",
    "left = -np.sum(vx[ymax:ymin:-1,xmin])\n",
    "\n",
    "area = (xmax-xmin)*(ymax-ymin)\n",
    "\n",
    "total = (top+bottom+left+right)/area"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "plot the flow, the box, and the vorticity (in the title):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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",
       "        this.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\", \"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 overriden (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"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.title('The line intregral of the red box is {:.3}'.format(total))\n",
    "plt.quiver(x,y, vx, vy, pivot='mid')\n",
    "\n",
    "# bottom, top, left and right side of the box, respectively:\n",
    "plt.plot(x[ymin,xmin:xmax+1],y[ymin,xmin:xmax+1],'r',alpha=0.5) # bottom\n",
    "plt.plot(x[ymax,xmax:xmin-1:-1],y[ymax,xmax:xmin-1:-1],'r',alpha=0.5) # top\n",
    "plt.plot(x[ymax:ymin-1:-1,xmin],y[ymax:ymin-1:-1,xmin],'r',alpha=0.5) # left\n",
    "plt.plot(x[ymin:ymax+1,xmax],y[ymin:ymax+1,xmax],'r',alpha=0.5) # right\n",
    "plt.xlabel(\"$x$-axis\")\n",
    "plt.ylabel(\"$y$-axis\")\n",
    "plt.axis('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Despite the radial motion in the fluid flow, the decay of this motion away from the origin leads to a shear that counteracts the pure rotational movement. In other words, a paddle wheel at the location of the red box -- or anywhere else in the grid for that matter -- would not spin around its axis (and rigidly move with the flow). \n",
    "\n",
    "Move the box around the grid, and you will find that the the vorticity is zero everywhere in the grid! In Chapter 7 of our book we showed this can be easily verified analytically. The chapter concludes by deriving the curl of a vector field in cylindrical and spherical coordinate systems. With the knowledge of the curl, grad and div operators, we are ready for the physics that involves these. Let's get back to the [overview of jupyter notebooks](https://pal.blogs.auckland.ac.nz/2017/12/02/jupyter-notebooks-for-mathematical-methods-in-the-physical-sciences/)!"
   ]
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