{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CCD calibration\n",
    "\n",
    "This tutorial presents how to calibrate the distortion from a CCD camera coupled with a taper of optic fibers.\n",
    "If your camera is already calibrated using Fit2D and you have access to the corresponding *spline* file, this tutorial is not for you: simply create your detector object like this ``pyFAI.detectors.Detector(splineFile=\"example.spline\")`` and you are done. This tutorial uses the image of a regular grid on the detector. \n",
    "\n",
    "It uses a procedure described in: \"Calibration and correction of spatial distortions in 2D detector systems\" from \n",
    "Hammersley, A. P.; Svensson, S. O.; Thompson, A. published in \n",
    "Nuclear Instruments and Methods in Physics Research Section A, Volume 346, Issue 1-2, p. 312-321.\n",
    "DOI:10.1016/0168-9002(94)90720-X\n",
    "\n",
    "The procedure is performed in 4 steps:\n",
    "1. peak picking\n",
    "2. grid assignment\n",
    "3. distortion fitting\n",
    "4. interpolation of the fitted data\n",
    "5. saving into a detector definition file\n",
    "\n",
    "The picture used is the one of a regular metallic grid of holes (spaced by 5mm), just in front of the detector. We will assume holes are circular what looks correct in first approximation. Parallax error will be ignored in a first time.\n",
    "\n",
    "The images used for this test can be downloaded from:\n",
    "http://www.silx.org/pub/pyFAI/detector_calibration/frelonID22_grid.edf\n",
    "\n",
    "## Peak picking\n",
    "\n",
    "\n",
    "Lets start with peak picking, for this, we will use the *FabIO* library able to read the image and *matplotlib* to display the image. The distortion is assumed to be minimal in the middle of the detector, so we first focus on one spot in the middle:\n",
    "\n",
    "First we initialize the matplotlib library to be used in the *Jupyter notebook* interface."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n",
      "Working with pyFAI version: 0.18.0\n"
     ]
    }
   ],
   "source": [
    "%pylab nbagg\n",
    "import time\n",
    "start_time = time.time()\n",
    "import pyFAI\n",
    "print(\"Working with pyFAI version: %s\"%pyFAI.version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/pyFAI_testdata_kieffer/frelonID22_grid.edf\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "#Nota: comment out when running from outside ESRF\n",
    "#os.environ[\"http_proxy\"] = \"http://proxy.esrf.fr:3128\"\n",
    "from silx.resources import ExternalResources\n",
    "downloader = ExternalResources(\"pyFAI\", \"http://www.silx.org/pub/pyFAI/detector_calibration\", \"PYFAI_DATA\")\n",
    "fname = downloader.getfile(\"frelonID22_grid.edf\")\n",
    "print(fname)\n",
    "\n",
    "#To test the corrections are good, once you have finished this tutorial:\n",
    "#fname = \"corrected.edf\"\n",
    "\n",
    "import fabio\n",
    "img = fabio.open(fname).data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Zoom one point in the center')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Display the image, and zoom on one spot\n",
    "fig,ax = subplots(1, 2, figsize=(10,5))\n",
    "ax[0].imshow(img, interpolation=\"nearest\", origin=\"lower\")\n",
    "#Zoom into a spot in the middle of the image, where the distortion is expected to be minimal\n",
    "ax[1].imshow(img[1060:1100,1040:1080], interpolation=\"nearest\", origin=\"lower\")\n",
    "ax[1].set_title(\"Zoom one point in the center\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7a6358c278>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Look at the profile of the peak to measure the width (it is expected to be a crenel)\n",
    "fig,ax = subplots()\n",
    "ax.plot(img[1060+25,1040:1060])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at one spot, in the center of the image: it is circular and is slightly larger than 10 pixels.\n",
    "We will define a convolution kernel of size 11x11 of circular shape with sharp borders as this is what a perfect spot is expected to look like. The kernel is normalized in such a way it does not modify the average intensity of the image\n",
    "\n",
    "Now convolve the image with this circular kernel using scipy.signal (in direct space: the kernel is small and performance does not really matter here). \n",
    "\n",
    "It is important to have an odd size for the kernel for convolution as an even shape would induce an offset of 1/2 pixel in the located peak-position."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f7a63544e10>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "size = 11 #Odd of course\n",
    "center = (size-1)//2\n",
    "y, x = numpy.ogrid[-center:center+1,-center:center+1]\n",
    "r2 = x*x + y*y\n",
    "kernel = (r2<=(center+0.5)**2).astype(float)\n",
    "kernel /= kernel.sum()\n",
    "\n",
    "fig,ax = subplots()\n",
    "ax.imshow(kernel, interpolation=\"nearest\", origin=\"lower\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import ndimage, signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "cnv = signal.convolve2d(img, kernel, mode=\"same\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2048, 2048)\n",
      "(2048, 2048)\n"
     ]
    }
   ],
   "source": [
    "#Check that size is unchanged.\n",
    "print(img.shape) \n",
    "print(cnv.shape) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Zoom one point in the center')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Check the image still looks the same. it is just supposed to be smoother.\n",
    "\n",
    "fig,ax = subplots(1,2, figsize=(10,5))\n",
    "ax[0].imshow(cnv, interpolation=\"nearest\", origin=\"lower\")\n",
    "#Zoom into a spot in the middle of the image, where the distortion is expected to be minimal\n",
    "ax[1].imshow(cnv[1060:1100,1040:1080], interpolation=\"nearest\", origin=\"lower\")\n",
    "ax[1].set_title(\"Zoom one point in the center\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f7a5b464b38>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Zoom into the very same spot to ensure it is smoother\n",
    "imshow(cnv[1060:1100,1040:1080], interpolation=\"nearest\", origin=\"lower\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAoAAAAHgCAYAAAA10dzkAAAgAElEQVR4nOzdaXzV5Z3+8cOgRhnXThVbbW8XlrYwUmo7LQ5jx7FWWq1YZ7CDllptqx3/01anrTdhrSIIiOAGFit1qQKiIuqdhLDvO4SQEPYlhB0CWQhZz7n+Dw4cTEG2X5L7LJ/363UemHMSLvQr34tzfktIAAAASCkh3wEAAADQtCiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCCAAAkGIogAAAACmGAggAAJBiKIAAAAAphgIIAACQYiiAAAAAKYYCGEA4HFZRUZFKSkpUWlrKgwcPHjx48EiAR0lJiYqKihQOh31XCW8ogAEUFRUpFArx4MGDBw8ePBLwUVRU5LtKeEMBDKCkpCQ2QL7/NsODBw8ePHjwOL3H0TdwSkpKfFcJbyiAAZSWlioUCqm0tNR3FAAAcJrY3xTAQBggAAASD/ubAhgIAwQAQOJhf1MAA2GAAABIPOxvCmAgDBAAAImH/U0BDIQBAgAg8bC/KYCBMEAAACQe9jcFMBAGCACAxMP+pgAGwgABAJB42N8UwEAYIAAAEg/7mwIYCAMEAEDiYX9TAANhgAAASDzsbwpgIAwQAACJh/1NAQyEAQJwMku3FCt94iq9Pm+zlhceUGVNne9IAMT+liiAgTBAAD5LbtFBfbVvlox1scf16Rm688W56jVxld5duk1rd5WpLhzxHRVIOexvCmAgDBCAE9m875C+8dQUGet018vz9PO/Lo79898/vto3S93+vEADMwr0Se4OlVXW+I4PJD32NwUwEAYIwN/bU1apzkOmy1inO16co/KqWklSJBLRtuIKudydGphRoG5/XnDcO4TGOn136AwdOvI9ABoH+5sCGAgDBODTyipr9IPn58hYp5uHztDesqqTvr4uHNHaXWV6d+k29Zq4KvYu4aDMgiZKDKQm9jcFMBAGCMBRVbV16v7qQhnrdOOAKdq6/9AZ/4xpBbtjxwqu213WCCkBSOxviQIYCAMEQIq+k/fo28tlrNPX+mYpb3vJWf+sX765VMY63fvnBYpEOEEEaAzsbwpgIAwQgEgkon6T8mSsU6teGZq7fl+gn1d0oEJt+2TKWKeJK4oaKCWAT2N/UwADYYAAvDxjg4x1uqan08crdzToz7xxwFSVHOasYKChsb8pgIEwQEBqe3fJttjZu3+dt7nBfm51bVj/MWymjHXqNymvwX4ugCj2NwUwEAYISF1TV+/WdekZMtZpcNaaBv/58zfsk7FO1/Z0gY4pBHA89jcFMBAGCEhNy7YWq03v6HF6v5+wstFO1vjN2BWxi0mHuWMI0GDY3xTAQBggIPWs312mG/6ULWOdHnx9iWrqwo32a+0prVS7fpNlrNM7iwob7dcBUg37mwIYCAMEpJaDFdXqNGiajHW6e+Q8Ha6ua/Rfc8zczTLW6YY/ZWt/+ckvLA3g9LC/KYCBMEBAajlaxm4eOkMHDlU3ya9ZWxdWlyN3F/njeyub5NcEkh37mwIYCAMEpJYfvTRXxjq9uWBLk/66y7YeiJ1tvHRLcZP+2kAyYn9TAANhgIDUsWFPuYx1ui49w8tHsU+8lytjnW4fMVu1jXjcIZAK2N8UwEAYICB1DMteGzvxw4fiQ9Xq8GT05JPX5jbcNQeBVMT+pgAGwgABqSESiajzkOky1umjBrrbx9kYu7hQxjq16zdZu0srveUAEh37mwIYCAMEpIZlW4tlrNPX+mY1yZm/nyUcjqjry/NkrNP/jl3hLQeQ6NjfFMBAGCAgNfT+cJWMdXr83RzfUZS3vUTX9oyeEDJvwz7fcYCExP6mAAbCAAHJr7o2HDv2bs76vb7jSJL6f5QvY51uGTZTVbX+3pEEEhX7mwIYCAMEJL+pq3fLWKdvPj1VdXFyO7bSyhrdOGCqjHV6fR4nhABniv1NAQyEAQKS36PvLJexTgM+We07Sj1/nRe9KPU9o+b7jgIkHPY3BTAQBghIbqWVNWrTO1PGOuVtL/Edp55dJZWxi0NzRjBwZtjfFMBAGCAgub27dJuMdbr1uVmKROLj499P+/HI6BnBbzXxnUmARMf+pgAGwgABya37qwtlrNPLMzb4jnJCo2dvlLFO3V9d6DsKkFDY3xTAQBggIHntKqnUNUcut7KtuMJ3nBMq3F8Ruz1d8aFq33GAhMH+9lAAZ8+erTvvvFNf+MIXFAqF9OGHH37max955BGFQiGNGDGi3teLi4t133336aKLLtIll1yihx56SOXl5fVek5ubq86dOystLU1XX321hgwZctzPnzBhgtq2bau0tDS1b99eGRkZZ/R7YYCA5HX03bX/eiW+T7L4wfNzZKzTu0u2+Y4CJAz2t4cCmJmZqd69e2vixIknLYATJ05Uhw4d9MUvfvG4AtilSxd16NBBixYt0ty5c9WqVSt179499nxpaalatmyp+++/X/n5+Ro3bpwuuOACjR49Ovaa+fPnq3nz5ho6dKgKCgrUp08fnXvuucrLyzvt3wsDBCSvLkeK1duLtvqOclIvTFvv9R7FQCJif3v+CPizCuD27dt11VVXKT8/X8aYegWwoKBAoVBIS5cujX0tKytLzZo1044d0Xt0jho1Spdddpmqq499JGKtVdu2bWP/fO+99+qOO+6o9+t++9vf1iOPPHLa+RkgIDmt2VUqY51a9crQwYr4/mh1/e4yGevUulemyiprfMcBEgL7Ow4LYDgc1i233KLnn39eko4rgGPGjNGll15a73tqa2vVvHlzTZw4UZLUo0cPde3atd5rZsyYoVAopAMHDkiSvvSlLx33zmK/fv10ww03fGbeqqoqlZaWxh5FRUUpP0BAMnomc42MdfrVm0tP/WLPIpGIbhk2U8Y6TcrZ7jsOkBAogHFYAAcNGqTbbrstdsmFvy+AAwcOVJs2bY77WZdffrlGjRolSbrtttv08MMP13t+9erVCoVCKigokCSde+65Gjt2bL3XjBw5UldcccVn5u3fv79CodBxj1QeICDZhMMRdRo0TcY6Zaza6TvOaRk6OVpYf/23Zb6jAAmBAhhnBXDZsmVq2bJl7KNcKb4KIO8AAslv4ab9Mtapfb/JqqxJjPvsrioqkbFOX+mTpcPViZEZ8IkCGGcFcMSIEWrWrJmaN28ee4RCIf3DP/yDjDGS/H4E/PcYICD52PdzZazTE+/l+o5y2iKRiG56ZrqMdcrK2+U7DhD32N9xVgD379+vvLy8eo8vfvGLstZq7dq1ko6dBLJs2bGPOrKzs094EkhNzbEDotPT0487CeTOO++sl6dTp06cBAKksMqaOrXvP1nGOi3YuN93nDPy1CerZazTY+NzfEcB4h7720MBLC8vV05OjnJychQKhTR8+HDl5OSosLDwhK//+4+ApehlYDp27KjFixdr3rx5at26db3LwJSUlKhly5bq0aOH8vPzNX78eLVo0eK4y8Ccc845GjZsmNasWaP+/ftzGRggxWWu2iljnb4zaJrC4fi79dvJLN1SHP3ouv9kVdeGfccB4hr720MBnDlz5glPpHjggQdO+PoTFcDi4mJ1795dF154oS6++GI9+OCDJ70Q9FVXXaXBgwcf97MnTJigNm3a6LzzzlO7du24EDSQ4h5+a6mMdRqUWeA7yhkLhyP65tNTZazTzLV7fMcB4hr7m1vBBcIAAcnjYEW1WvfKlLFOa3Yl5v/TvT9cJWOden6QOMcvAj6wvymAgTBAQPJ4Z1GhjHW6fcRs31HO2tz1+2Ss0zeemqK6BPsIG2hK7G8KYCAMEJA8ur2yQMY6vTJro+8oZ62mLqwOT2bLWKeFmxLrJBagKbG/KYCBMEBAcig6UCFjna7p6bTj4GHfcQL5/YSVMtap/0f5vqMAcYv9TQEMhAECksPLMzbIWKf/Hr3Qd5TAphXslrFO3x6YeGcyA02F/U0BDIQBAhJfJBLRrc/NkrFO7y7Z5jtOYJU1dfpa3ywZ67Si8IDvOEBcYn9TAANhgIDEl7c9ehu11r0zVVpZc+pvSAD/O3ZFwl7OBmgK7G8KYCAMEJD4Bhy5g8b/vL3s1C9OEC43ekHrm4fOUCTCx8DA32N/UwADYYCAxPbpe+hOzk+ee+geqqpVm97RaxoW7OTPJ+Dvsb8pgIEwQEBi27S3PPrxb69MVVTX+o7ToH75ZvSuJs9NWec7ChB32N8UwEAYICCxvblgi4x1+snoBb6jNLj3lxXJWKfvD0/cC1sDjYX9TQEMhAECEtvRd8lenrHBd5QGV1JRo+vTM2Ss06a95af+BiCFsL8pgIEwQEDiqqkLq12/yTLWKbfooO84jeKnry2SsU4jZyZfwQWCYH9TAANhgIDEtXRLsYx16vBkdtLeN/fo/Y1/9NJc31GAuML+pgAGwgABiWv4lHUy1unRt5f7jtJo9pZV6ZqeTsY6bU/wW9wBDYn9TQEMhAECEtc9o+bLWKexiwt9R2lU3f68QMY6vTZ3s+8oQNxgf1MAA2GAgMRUWlmj646cILGtuMJ3nEY1Zu5mGevU7ZXkO9MZOFvsbwpgIAwQkJgm5++SsU7//uxM31Ea3Y6Dh2Ws0zU9nfaWVfmOA8QF9jcFMBAGCEhMfT7Mk7FOfT7M8x2lSdz10lwZ6/T2oq2+owBxgf1NAQyEAQIS078/OzPpbv92MqNmbpSxTj99bZHvKEBcYH9TAANhgIDEs624QsY6XZeeodLKGt9xmsTmfYdkrNP1KfR7Bk6G/U0BDIQBAhLP2MXRa+PdM2q+7yhN6pYUe9cTOBn2NwUwEAYISDyPvr1cxjoNn7LOd5QmdfS4x76TUuO4R+Bk2N8UwEAYICCx1IUj6vBktox1Wrql2HecJnX0zOdbUuDMZ+BU2N8UwEAYICCx5BYdlLFO7ftNVk1d2HecJlVaWaNruSsIIIn9LVEAA2GAgMTy8owNMtbpl28u9R3Fi7tHzpOxTu8u2eY7CuAV+5sCGAgDBCSWn4yO3hbtzQVbfEfx4rnstTLW6X/HrvAdBfCK/U0BDIQBAhJHRXWtWvWK3v5t095y33G8WLy5WMY6feOpKQqHI77jAN6wvymAgTBAQOKYsXaPjHW66ZnpikRSs/xU14b11b5ZMtYpf0eJ7ziAN+xvCmAgDBCQOJ78eLWMdbLv5/qO4tWDry+RsU6jZ2/0HQXwhv1NAQyEAQISx23DZ8lYp09yd/iO4tVrczdzWzikPPY3BTAQBghIDLtLK2Ws0zU9nQ4cqvYdx6t1u8tkrFOb3pmqrKnzHQfwgv1NAQyEAQISw/vLimSs049emus7ineRSETfenqqjHWav2Gf7ziAF+xvCmAgDBCQGB4bnyNjnYZkrfEdJS48fuTfx2D+fSBFsb8pgIEwQED8i0QiunHAkXe8NvKOlyR9sJx3RJHa2N8UwEAYICD+FewslbFOX+mTpapajnmTOCYSYH9TAANhgID49+rsTTLW6YG/LvYdJa4cPSva5e70HQVocuxvCmAgDBAQ/3qMWSxjnf4yZ5PvKHHl6HURe36wyncUoMmxvymAgTBAQHyrrKlTm96ZMtZp7a4y33HiyvQ1u2WsU+ch031HAZoc+5sCGAgDBMS3eRv2yVinbz09NWVv//ZZDlXV6vr06L2RC/dX+I4DNCn2NwUwEAYIiG/PZK6RsU6Pv5vjO0pc6vbKAhnr9Pairb6jAE2K/e2hAM6ePVt33nmnvvCFLygUCunDDz+MPVdTU6MnnnhC7du3V4sWLfSFL3xBPXr00I4d9W/dVFxcrPvuu08XXXSRLrnkEj300EMqLy+v95rc3Fx17txZaWlpuvrqqzVkyJDjskyYMEFt27ZVWlqa2rdvr4yMjDP6vTBAQHy748U5MtZp4ooi31Hi0gvT1stYp1//bZnvKECTYn97KICZmZnq3bu3Jk6ceFwBLCkp0fe+9z29++67Wrt2rRYuXKh/+Zd/0Y033ljvZ3Tp0kUdOnTQokWLNHfuXLVq1Urdu3ePPV9aWqqWLVvq/vvvV35+vsaNG6cLLrhAo0ePjr1m/vz5at68uYYOHaqCggL16dNH5557rvLy8k7798IAAfFrf3mVjHUy1mlPWaXvOHFpeeEBGet0w5+yVRfmI3KkDva354+A/74AnsiSJUsUCoVUWFgoSSooKFAoFNLSpUtjr8nKylKzZs1i7xSOGjVKl112maqrj13fylqrtm3bxv753nvv1R133FHv1/r2t7+tRx555LTzM0BA/Ppo5Q4Z63T7iNm+o8St2rqw2vefLGOdVm476DsO0GTY3wlQAKdOnapmzZrF/iONGTNGl156ab3X1NbWqnnz5po4caIkqUePHuratWu918yYMUOhUEgHDhyQJH3pS1/SiBEj6r2mX79+uuGGG047PwMExK8/vrdSxjo97Vb7jhLXfvXmUhnr9PKMDb6jAE2G/R3nBbCyslLf+MY3dN9998W+NnDgQLVp0+a4115++eUaNWqUJOm2227Tww8/XO/51atXKxQKqaCgQJJ07rnnauzYsfVeM3LkSF1xxRWfmaeqqkqlpaWxR1FRUcoPEBCPIpGIOg2aJmOdZq3b6ztOXHtzwRYZ6/Tfoxf6jgI0GQpgHBfAmpoa/ehHP1LHjh3r/QfyWQD79++vUCh03COVBwiIRxv3lstYp9a9MnW4mtu/ncwm/l0hBVEA47QA1tTU6O6779YNN9yg/fv313vO50fAvAMIJIbX522WsU7dX+VdrVOJRCK66ZnpvFuKlEIBjMMCeLT8tWvXTnv3Hv+H0dGTQJYtO3bZguzs7BOeBFJTUxN7TXp6+nEngdx55531fnanTp04CQRIAr94Y4mMdRo1c6PvKAmB4yWRatjfHgpgeXm5cnJylJOTo1AopOHDhysnJ0eFhYWqqanRXXfdpauvvlorV67Url27Yo9Pn9HbpUsXdezYUYsXL9a8efPUunXrepeBKSkpUcuWLdWjRw/l5+dr/PjxatGixXGXgTnnnHM0bNgwrVmzRv379+cyMEASqKkLq12/6JmtedtLfMdJCEfPmO7y/BzfUYAmwf72UABnzpx5wuPoHnjgAW3ZsuWEz4VCIc2cOTP2M4qLi9W9e3ddeOGFuvjii/Xggw+e9ELQV111lQYPHnxclgkTJqhNmzY677zz1K5dOy4EDSSBJVuKZaxTx6emKMy17U7Lvk9dM3FvWZXvOECjY39zK7hAGCAg/oyYuk7GOj36znLfURLKD56P3jVlUs5231GARsf+pgAGwgAB8ecno7m/7dkYlFEgY53+MGGl7yhAo2N/UwADYYCA+FJZU6fWvTNlrNPGveWn/gbEzF63V8Y6fWfQNEUifHSO5Mb+pgAGwgAB8WX+xn0y1ulbT0+lxJwhyjNSCfubAhgIAwTEl+emRI//+83YFb6jJKTury6UsU5vzN/iOwrQqNjfFMBAGCAgvnR7JXr839jFhb6jJKSRMzfIWKdfvLHUdxSgUbG/KYCBMEBA/DhcXafWvaIfYW7Zd8h3nIS0qqhExjq16zdZtXVh33GARsP+pgAGwgAB8WPehujxf98eyEkMZ6suHFGHJ7NlrNOyrcW+4wCNhv1NAQyEAQLix7DstTLW6bHxOb6jJLRH314uY52en7redxSg0bC/KYCBMEBA/PjPUfNlrNP4JRz/F8Q7iwplrNN/vTLfdxSg0bC/KYCBMEBAfKiorlWrXhky1qlwf4XvOAltW3GFjHW6Pj1D5VW1vuMAjYL9TQEMhAEC4sOc9dGLGHfiIsYN4uahM2Ss07SC3b6jAI2C/U0BDIQBAuLDkKw1Mtbp8Xc5/q8hpE9cJWOd+n+U7zsK0CjY3xTAQBggID78eOQ8Ges0Yek231GSgsvdKWOdbh8x23cUoFGwvymAgTBAgH+Hqmp1fXr0+L9txRz/1xD2l1fJWCdjnfaXV/mOAzQ49jcFMBAGCPBv1rro8X//Oni67yhJ5fvDZ8tYp8xVO31HARoc+5sCGAgDBPj3TGb0+L/fT1jpO0pS6f9Rvox16jspz3cUoMGxvymAgTBAgH9dX44e//f+siLfUZJKVl70OMDvPTfLdxSgwbG/KYCBMECAX+VVtbruyPF/2w8e9h0nqRw4VK1rekaPA9xbxnGASC7sbwpgIAwQ4NeMNXtkrNO/DZnhO0pS6vL8HBnr9EnuDt9RgAbF/qYABsIAAX4NyiiQsU5/fI/j/xrDnz6OHgfYa+Iq31GABsX+pgAGwgABfv3opbky1mniCo7/awzZ+btkrNMtw2b6jgI0KPY3BTAQBgjwp7SyRtceOUZtZwnH/zWGkoqa2HGAe0orfccBGgz7mwIYCAME+DOtYLeMdfruUI7/a0x3vBg9DnBSznbfUYAGw/6mAAbCAAH+PO1Wy1innh/k+o6S1AZ8wr9nJB/2NwUwEAYI8Id3ppoG77QiGbG/KYCBMECAHyWHjx2btptj0xoVx1oiGbG/KYCBMECAH1NWR9+VuuXZmb6jpATOtkayYX9TAANhgAA/nvw4elxaOtenaxJcbxHJhv1NAQyEAQL8+MGRO1R8vJI7VDSFGWu54wqSC/ubAhgIAwQ0vYMVx+5Ru6eM4/+aAvdcRrJhf1MAA2GAgKY3+cjdKW59bpbvKCml68vzZKzTe8s4DhCJj/1NAQyEAQKaXv+Poven7f0hx/81pcFZa2Ss0/+9y3GASHzsbwpgIAwQ0PRuHzFbxjq53J2+o6SU2ev2ylinm56Z7jsKEBj7mwIYCAMENK3iQ9UyNnr8377yKt9xUsqhqlpdf+Q4wG3FFb7jAIGwvymAgTBAQNPKXLVTxjrdNpzj/3y4Z9R8Gev07pJtvqMAgbC/KYCBMEBA0+o3KU/GOvWdlOc7Skp6dvJaGev0+Pgc31GAQNjfFMBAGCCgad02fJaMdcpcxfF/Psxdv0/GOn1n0DRFIhHfcYCzxv6mAAbCAAFNZ195Vez4v+JD1b7jpKTD1XVq1St6HOCWfYd8xwHOGvubAhgIAwQ0HZcbPf7v9hGzfUdJad1eWSBjncYuLvQdBThr7G8KYCAMENB0+nwYPf6v/0f5vqOktOemrJOxTr8dt8J3FOCssb8pgIEwQEDTufW56PF/WXm7fEdJafM3Ro8D/NbTUzkOEAmL/e2hAM6ePVt33nmnvvCFLygUCunDDz+s93wkElHfvn115ZVX6vzzz9ett96q9evX13tNcXGx7rvvPl100UW65JJL9NBDD6m8vLzea3Jzc9W5c2elpaXp6quv1pAhQ47LMmHCBLVt21ZpaWlq3769MjIyzuj3wgABTWNvWfT4v2t6Oh2s4Pg/nypr6tS6d6aMddq4t/zU3wDEIfa3hwKYmZmp3r17a+LEiScsgIMHD9Yll1yiSZMmKTc3V3fddZeuvfZaVVYeu+l7ly5d1KFDBy1atEhz585Vq1at1L1799jzpaWlatmype6//37l5+dr3LhxuuCCCzR69OjYa+bPn6/mzZtr6NChKigoUJ8+fXTuuecqL+/0Ly/BAAFN4+OVO2SsU5fn5/iOAkk/GR09DvDtRVt9RwHOCvvb80fAf18AI5GIrrzySj377LOxr5WUlCgtLU3jxo2TJBUUFCgUCmnp0qWx12RlZalZs2basWOHJGnUqFG67LLLVF197J0Ca63atm0b++d7771Xd9xxR7083/72t/XII4+cdn4GCGga6RNXyVinJz9e7TsKJI2YGj0O8P+9s9x3FOCssL/jrABu2rRJoVBIOTn1LzJ6880367e//a0kacyYMbr00kvrPV9bW6vmzZtr4sSJkqQePXqoa9eu9V4zY8YMhUIhHThwQJL0pS99SSNGjKj3mn79+umGG2447fwMENA0bhk2U8Y6TVm923cUSFq0ab+MdbpxAMcBIjGxv+OsAM6fP1+hUEg7d9a/yGu3bt107733SpIGDhyoNm3aHPezLr/8co0aNUqSdNttt+nhhx+u9/zq1asVCoVUUFAgSTr33HM1duzYeq8ZOXKkrrjiis/MW1VVpdLS0tijqKgo5QcIaGy7Sytjx/+VVNT4jgNJVbV1anPkOMD1u8t8xwHOGAWQAljvNacqgP3791coFDrukcoDBDS2D1dsl7FOd74413cUfMp9f1koY53eWrDFdxTgjFEA46wAxvtHwLwDCDS9J97LlbFOAzMKfEfBp7w4bb2Mdfqft5f5jgKcMQpgnBXAoyeBDBs2LPa10tLSE54EsmzZsT90srOzT3gSSE3NsY+L0tPTjzsJ5M4776yXp1OnTpwEAsSZfxsyQ8Y6zVizx3cUfMrSLcUy1qnjU1MUDnMcIBIL+9tDASwvL1dOTo5ycnIUCoU0fPhw5eTkqLAweluhwYMH69JLL9VHH32kVatWqWvXrie8DEzHjh21ePFizZs3T61bt653GZiSkhK1bNlSPXr0UH5+vsaPH68WLVocdxmYc845R8OGDdOaNWvUv39/LgMDxJmiAxUy1um69AyVV9X6joNPqa4N6yt9smSs09pdHAeIxML+9lAAZ86cecLj6B544AFJxy4E3bJlS6WlpenWW2/VunXr6v2M4uJide/eXRdeeKEuvvhiPfjggye9EPRVV12lwYMHHwfCcnAAACAASURBVJdlwoQJatOmjc477zy1a9eOC0EDcWbC0m0y1unukfN8R8EJ/PS1RTLW6fV5m31HAc4I+5tbwQXCAAGN6/F3c2Ss05CsNb6j4ARenrFBxjo9/NbSU78YiCPsbwpgIAwQ0HgikYi+M2iajHWau36f7zg4geWFB2SsU4cnszkOEAmF/U0BDIQBAhrPln2HZKxTq14ZOlxd5zsOTqCmLqyv9Y0eB7h6B38OInGwvymAgTBAQOMZu7hQxjp1e2WB7yg4iZ+NWSxjnV6by3GASBzsbwpgIAwQ0Hj+d+wKGes0fMq6U78Y3rwya6OMdfrFGxwHiMTB/qYABsIAAY0jEonoxgFTZazTwk37fcfBSazcdlDGOv1z/8mq4zhAJAj2NwUwEAYIaBwb9pTJWKc2vTNVVcvxf/Gsti6s9v0my1invO0lvuMAp4X9TQEMhAECGsebC7bIWKf7/rLQdxSchgdfXyJjnV6dvcl3FOC0sL8pgIEwQEDj+PXflslYp5emr/cdBafh1dmbZKzTg68v8R0FOC3sbwpgIAwQ0PDC4Yi+/mS2jHVatrXYdxychrztJTLWqV2/yaqtC/uOA5wS+5sCGAgDBDS81TtKZazTV/tmqYYykRDqwhH9c//ocYA52w76jgOcEvubAhgIAwQ0vNfmbpaxTj8bs9h3FJyBX765VMY6jZq50XcU4JTY3xTAQBggoOH94o1okXhlFkUikYw5Utx7UNyRANjfFMBAGCCgYdWFI2p/5KPE3CI+SkwkfHSPRML+pgAGwgABDSu3KHpR4fZcVDjh1D9554DvOMBJsb8pgIEwQEDD+nPstmJcTiQRPfJW9PI9L8/Y4DsKcFLsbwpgIAwQ0LB+NmaxjHV6be5m31FwFt6YH72A9/1/WeQ7CnBS7G8KYCAMENBwaurC+mrfLBnrtHoH/08lonW7o7fwa9uHW/ghvrG/KYCBMEBAw1m29YCMdfr6k9kKc/xfQopEIrpxwBQZ67R4MxfxRvxif1MAA2GAgIbz0vT1Mtbp139b5jsKAnj0neUy1un5qdzGD/GL/U0BDIQBAhrOfX9ZKGOd3lywxXcUBPC3hVtlrNNPRi/wHQX4TOxvCmAgDBDQMKpq69Smd6aMdVq/u8x3HASwcW+5jHVq3TtTlTUcB4j4xP6mAAbCAAENY+Gm/TLW6cYBUxWJcPxfIotEIvrW01NlrNOCjft9xwFOiP1NAQyEAQIaxvAp62Ss0/+OXeE7ChrAb8aukLFOz01Z5zsKcELsbwpgIAwQ0DC6vbJAxjq9s6jQdxQ0gLGLC2WsU7dXOA4Q8Yn9TQEMhAECgjtcXadWvTJkrNOWfYd8x0ED2LLvkIx1atUrQ4erOQ4Q8Yf9TQEMhAECgpu7fp+MdfrOoGkc/5ckIpGIvjNomox1mrt+n+84wHHY3xTAQBggILghWWtkrNPj43N8R0EDenx8jox1Gjp5je8owHHY3xTAQBggILi7R86TsU4Tlm7zHQUN6N2l22Ss049HzvMdBTgO+5sCGAgDBARTXlWr69Kjx/8VHajwHQcNaFtxhYx1uj49Q4eqan3HAephf1MAA2GAgGBmrNkjY506D5nuOwoawb8Oni5jnWat2+s7ClAP+5sCGAgDBAQzMKNAxjo98V6u7yhoBH+YsFLGOj2TyXGAiC/sbwpgIAwQEMydL86VsU4frtjuOwoawfvLimSs010vcxwg4gv7mwIYCAMEnL2Sihpd09PJWKfdpZW+46AR7Dh4WMY6XZeeobLKGt9xgBj2NwUwEAYIOHvZ+btkrNMtw2b6joJGdPPQGTLWafqa3b6jADHsbwpgIAwQcPb+9HG+jHXqNXGV7yhoRPb9XBnr9LRb7TsKEMP+pgAGwgABZ+/2EbNlrNMnuTt8R0EjmpSzXcY63fHiHN9RgBj2NwUwEAYIODv7y6tkbPT4v33lVb7joBHtKa2UsU7X9HQqqeA4QMQH9jcFMBAGCDg7Gat2ylin7w+f7TsKmsAtw2bKWKcpqzkOEPGB/U0BDIQBAs5Or4mrZKxT/4/yfUdBEzj63/vJjzkOEPGB/U0BDIQBAs7Ovw2Jnhk6lXeEUsInuTtkrFOX5zkOEPGB/U0BDIQBAs7c1v2HYveILecesSlhb9mxYz4PHKr2HQdgfysOC2BdXZ369Omja665Rueff76uu+46PfXUU4pEIrHXRCIR9e3bV1deeaXOP/983XrrrVq/fn29n1NcXKz77rtPF110kS655BI99NBDKi8vr/ea3Nxcde7cWWlpabr66qs1ZMiQM8rKAAFn7m8Lt8pYp25/XuA7CprQ956bJWOdsvJ2+o4CsL8VhwVw4MCB+qd/+ic557Rlyxa99957uvDCC/XCCy/EXjN48GBdcsklmjRpknJzc3XXXXfp2muvVWXlsbsJdOnSRR06dNCiRYs0d+5ctWrVSt27d489X1paqpYtW+r+++9Xfn6+xo0bpwsuuECjR48+7awMEHDmHnlrmYx1enHa+lO/GEmj76Q8GevUb1Ke7ygA+1txWADvuOMOPfTQQ/W+ds899+j++++XFH3378orr9Szzz4be76kpERpaWkaN26cJKmgoEChUEhLly6NvSYrK0vNmjXTjh3Ra46NGjVKl112maqrj30cYa1V27ZtTzsrAwScmdq6sNr3nyxjnXK2HfQdB00o88iZ37cNn+U7CsD+VhwWwIEDB8oYo3Xr1kmSVq5cqSuuuEJvv/22JGnTpk0KhULKycmp930333yzfvvb30qSxowZo0svvbTe87W1tWrevLkmTpwoSerRo4e6du1a7zUzZsxQKBTSgQMHTpitqqpKpaWlsUdRUVHKDxBwJpYXHpCxTjf8KVt14cipvwFJo/hQNdd+RNygAMZhAQyHw7LWqlmzZjrnnHPUrFkzDRo0KPb8/PnzFQqFtHNn/eNIunXrpnvvvVdStES2adPmuJ99+eWXa9SoUZKk2267TQ8//HC951evXq1QKKSCgoITZuvfv79CodBxj1QeIOBMPD91vYx1+p+3l/mOAg+O3v3F5XIcIPyiAMZhARw3bpyuvvpqjRs3TqtWrdJbb72lz33uc3rjjTck+S2AvAMIBPOfo+bLWKd3FhX6jgIPjt7/ufeH3P8ZflEA47AAXn311Xr55ZfrfW3AgAGxY/N8fgT89xgg4PSVVdbouvQMGeu0rbjCdxx4kJ2/S8Y6/cewmb6jIMWxv+OwAH7uc5+LvUt31KBBg9S6dWtJx04CGTZsWOz50tLSE54EsmzZsY+ZsrOzT3gSSE3NsXtTpqencxII0EiOLv/vDp3hOwo8Kamo0TU9o8cB7imtPPU3AI2E/R2HBfCBBx7QVVddFbsMzMSJE/X5z39eTzzxROw1gwcP1qWXXqqPPvpIq1atUteuXU94GZiOHTtq8eLFmjdvnlq3bl3vMjAlJSVq2bKlevToofz8fI0fP14tWrTgMjBAIzl6GZA+H3IZkFR2x4tzZKzTpJztvqMghbG/47AAlpWV6Xe/+52+/OUvxy4E3bt373qXazl6IeiWLVsqLS1Nt956a+ys4aOKi4vVvXt3XXjhhbr44ov14IMPnvRC0FdddZUGDx58RlkZIOD0/fuzM2WsU3b+Lt9R4NGAT1bLWKeeH+T6joIUxv6OwwKYSBgg4PRsK66QsU7XpWeotLLm1N+ApDV9zW4Z69R5yPR6d3gCmhL7mwIYCAMEnJ6xiwtlrNN/jprvOwo8O1RVq1a9oicDbd53yHccpCj2NwUwEAYIOD2Pvr1cxjqNmLru1C9G0vvv0QtlrNMb87f4joIUxf6mAAbCAAGnVheO6IY/ZctYp2VbT+8SS0huo2ZulLFOv3hjie8oSFHsbwpgIAwQcGortx2UsU7t+09WbV3YdxzEgfwdJTLW6Wt9s1Rdy0yg6bG/KYCBMEDAqb00PXr7t4ffWuo7CuJEOBzRjQOmylinBRv3+46DFMT+pgAGwgABp3bvnxfIWKe3Fm71HQVx5PHxOTLWaXDWGt9RkILY3xTAQBgg4OQ+fcbn1v2c8YljJq4okrFOP3xhju8oSEHsbwpgIAwQcHKfvuYb8Gn7yqtkbPS2cHvLqnzHQYphf1MAA2GAgJPr/1G+jHVKn7jKdxTEoR++EL0t3MQVRb6jIMWwvymAgTBAwMnd+twsGeuUlbfTdxTEocFZa2Ss02Pjc3xHQYphf1MAA2GAgM+2s+SwjHW6tqdTyWFu/4bjLdi4X8Y63ThgqsJhbguHpsP+pgAGwgABn+3dpdtkrNPdI+f5joI4VV0b1tf6ZslYp/wdJb7jIIWwvymAgTBAwGf737ErZKzTc9lrfUdBHPvFG0tkrNOomRt9R0EKYX9TAANhgIATC4cj6vjUFBnrtGRLse84iGNvzN8iY53+e/RC31GQQtjfFMBAGCDgxPK2R2/11a7fZNVw+zecxOZ9h2SsU6teGTpUVes7DlIE+5sCGAgDBJzYyJkbZKzTL97g9m84uUgkos5DpstYp2kFu33HQYpgf1MAA2GAgBPr/upCGev0xvwtvqMgAfSauErGOvWblOc7ClIE+5sCGAgDBBzvcHWdWvfKlLFOm/aW+46DBDA5f5eMdfr3Z2f6joIUwf6mAAbCAAHHm7l2j4x1uumZ6YpEuLYbTq2sskbXp0fvGb2tuMJ3HKQA9jcFMBAGCDjeU5+slrFO9v1c31GQQLq9skDGOr29aKvvKEgB7G8KYCAMEHC87w+fLWOdXC63f8Ppe3Haehnr9PBbnDiExsf+pgAGwgAB9e0urZSxTtf0dDpwqNp3HCSQldsOylin9lw6CE2A/U0BDIQBAup7f1mRjHW666W5vqMgwdSFI/r6k9lcPBxNgv1NAQyEAQLq+9246O3fhk5e4zsKEtDR2wcO4/aBaGTsbwpgIAwQcEw4HNGNA6bKWKeFm/b7joMENGHpNt5BRpNgf1MAA2GAgGNW7yiVsU5f7Zul6lqO4cKZ4xhSNBX2NwUwEAYIOGb07I0y1unB15f4joIEdvuI6FnkH6/c4TsKkhj7mwIYCAMEHPPT1xbJWKcxczf7joIE9rSLXkfyDxNW+o6CJMb+pgAGwgABUZU1dWrTO3r7tw17ynzHQQKbs36vjHX6l4FTuZMMGg37mwIYCAMERE0r2M3t39AgKmvq1LZP9C8Ta3fxlwk0DvY3BTAQBgiI6vlBrox16jcpz3cUJIGfjVksY51enb3JdxQkKfY3BTAQBgiIXv7lW09HL/8ye91e33GQBF6bu1nGOv30tUW+oyBJsb8pgIEwQMCxW3i16zdZVbV1vuMgCWzYUyZjnVr3ztThamYKDY/9TQEMhAECpOey18pYp/95e5nvKEgSkUhEnQZNk7FOs3hXGY2A/U0BDIQBAqQuz8+RsU4fLC/yHQVJ5In3oseVPvXJat9RkITY3xTAQBggpLqiAxUy1ula7tyABuZyd8pYp+89N8t3FCQh9jcFMBAGCKnuzQVbZKxTt1cW+I6CJFNSUaNrezoZ67Tj4GHfcZBk2N8UwEAYIKS6o3f/GD17o+8oSEJ3j5wnY53GLyn0HQVJhv1NAQyEAUIqK6usUateGTLWadPect9xkISGT1knY50efXu57yhIMuxvCmAgDBBSWcaq6DFatzw703cUJKllWw/IWKcb/pStujB3mEHDYX9TAANhgJDKHh+fI2OdBmYU+I6CJFVbF9Y/958sY52WFx7wHQdJhP0dpwVw+/btuv/++/W5z31O559/vtq3b6+lS5fGno9EIurbt6+uvPJKnX/++br11lu1fv36ej+juLhY9913ny666CJdcskleuihh1ReXv9jqtzcXHXu3FlpaWm6+uqrNWTIkDPKyQAhVdXWhdXhyWwZ67Ro037fcZDEHn1nuYx1Gpy1xncUJBH2dxwWwAMHDsgYo5///OdavHixNm/erOzsbG3ceOwg88GDB+uSSy7RpEmTlJubq7vuukvXXnutKisrY6/p0qWLOnTooEWLFmnu3Llq1aqVunfvHnu+tLRULVu21P3336/8/HyNGzdOF1xwgUaPHn3aWRkgpKrFm4tlrFOHJ7NVWxf2HQdJ7KOVO6KHGgyb6TsKkgj7Ow4LoLVWnTt3/sznI5GIrrzySj377LOxr5WUlCgtLU3jxo2TJBUUFCgUCtV71zArK0vNmjXTjh07JEmjRo3SZZddpurqY9cus9aqbdu2p52VAUKqGphRIGOdHh+f4zsKklxZZY1a98qUsU4b9pT5joMkwf6OwwL41a9+VY899pj+67/+S5dffrm+/vWv69VXX409v2nTJoVCIeXk1F88N998s377299KksaMGaNLL7203vO1tbVq3ry5Jk6cKEnq0aOHunbtWu81M2bMUCgU0oEDJz7WpKqqSqWlpbFHUVFRyg8QUtMtz86UsU4ud6fvKEgBD/x1sYx1ennGBt9RkCQogHFYANPS0pSWlqb09HStWLFCo0eP1vnnn6833nhDkjR//nyFQiHt3Fl/8XTr1k333nuvJGngwIFq06bNcT/78ssv16hRoyRJt912mx5++OF6z69evVqhUEgFBSc+qL1///4KhULHPVJ5gJB6Nu4tl7FOrXplqKyyxnccpICxiwtlrNOPXprrOwqSBAUwDgvgueeeq06dOtX72m9+8xt95zvfkeS3APIOICCNnr1Rxjr99LVFvqMgRewrr9I1R+4Ksp27gqABUADjsAB++ctf1i9+8Yt6Xxs1apS++MUvSvL7EfDfY4CQirr9eYGMdXpj/hbfUZBCur0Snbu/ztvsOwqSAPs7Dgtg9+7djzsJ5LHHHou9K3j0JJBhw4bFni8tLT3hSSDLli2LvSY7O/uEJ4HU1Bz7CCs9PZ2TQICTOHCoOnZ/1qIDFb7jIIX8Zc4mGev0k9HcdxrBsb/jsAAuWbJE55xzjgYOHKgNGzbonXfeUYsWLfT222/HXjN48GBdeuml+uijj7Rq1Sp17dr1hJeB6dixoxYvXqx58+apdevW9S4DU1JSopYtW6pHjx7Kz8/X+PHj1aJFCy4DA5zEB8uLZKzT7SNm+46CFLOtuELGOl3b06n4UPWpvwE4CfZ3HBZASfrkk0/Uvn17paWl6Stf+Uq9s4ClYxeCbtmypdLS0nTrrbdq3bp19V5TXFys7t2768ILL9TFF1+sBx988KQXgr7qqqs0ePDgM8rJACHVPPp29KK8w7LX+o6CFPTDF+bIWKd3l2zzHQUJjv0dpwUwUTBASCVVtXVq1y96W66V2w76joMU9MK09TLW6aHXl/iOggTH/qYABsIAIZXMXrdXxjp98+mpCocjvuMgBa3dVSZjnVr3zlR5Va3vOEhg7G8KYCAMEFJJv0l5Mtap5we5vqMgRUUiEX136AwuQo7A2N8UwEAYIKSKSCSim56ZLmOdphXs9h0HKWzQkdsQ/mbsCt9RkMDY3xTAQBggpIrVO0plrFPbPpmqrKnzHQcpbHnhARnr1K7fZFXVMos4O+xvCmAgDBBSxYtHDr7/xRtLfUdBiguHI/rW01NlrNOMtXt8x0GCYn9TAANhgJAq7npprox1Gre40HcUQL0/XMXxqAiE/U0BDIQBQirYU1opY6N3/9hTVnnqbwAa2Zz10TPSbxwwRXWckY6zwP6mAAbCACEVjF1cKGOdur48z3cUQJJUUxfWP/ePXpNy8eZi33GQgNjfFMBAGCCkgodeXyJjnV6avt53FCDm8fE5MtbpqU9W+46CBMT+pgAGwgAh2R2urlOb3pky1mnNLuYc8SMrb5eMdfrXwdMVifAxMM4M+5sCGAgDhGQ3ZfVulizi0uHqOrXtE/3LSf6OEt9xkGDY3xTAQBggJLsn3suVsU79P8r3HQU4zq/eXCpjnZ6bss53FCQY9jcFMBAGCMksHI7oxgHR663NXb/PdxzgOB8sL5KxTt8fPtt3FCQY9jcFMBAGCMlsxZE7LrTvN1nVtWHfcYDjlFTU6Pr0DBnrtGXfId9xkEDY3xTAQBggJLMhWWtkrNOj7yz3HQX4TPf/ZZGMdfrzrI2+oyCBsL8pgIEwQEhW4XBE/zp4uox1mpSz3Xcc4DO9tWCLjHX68UiuU4nTx/6mAAbCACFZLd5cLGOd2vWbrMPVdb7jAJ9pV8mxO9XsLuVONTg97G8KYCAMEJKVfT969u8f31vpOwpwSnePnCdjnd5auNV3FCQI9jcFMBAGCMmosqZO7ftFb7O1cNN+33GAU3pl1kYZ6/TT1xb5joIEwf6mAAbCACEZfbxyh4x1uumZ6QqHufgz4t/mfYdkrNP16RkqqajxHQcJgP1NAQyEAUIy+vlfF8tYp2HZa31HAU7bbcNnyViniSuKfEdBAmB/UwADYYCQbPaUVeq6I9dV27S33Hcc4LQNy14rY50efmup7yhIAOxvCmAgDBCSzV/mbJKxTndzSQ0kmLztJTLWqW2fTM5cxymxvymAgTBASDY/eH5O9GzKBVt8RwHOSCQS0U3PRK9dOTl/l+84iHPsbwpgIAwQkknBzlIZ69SqV4YOHKr2HQc4Y09+vFrGOj3+bo7vKIhz7G8KYCAMEJLJwIwCjqFCQjt6AfP2XMAcp8D+pgAGwgAhWdTWhfXNp6fy8RkSWjgcUech0Y+BP1jO2cD4bOxvCmAgDBCSxax1e2WsU4cns1VdG/YdBzhrL0xbL2Od7v3zAt9REMfY3xTAQBggJIvfjlshY536TsrzHQUIZMfBw7q2Z/TewJv3HfIdB3GK/U0BDIQBQjIoq6xR2z6ZMtYpZ9tB33GAwB44cjHzwVlrfEdBnGJ/UwADYYCQDN5duk3GOt0ybKYiEW79hsSXuWqnjHX61tNTVVvHIQ04HvubAhgIA4Rk8JPRC2Ss08szNviOAjSI6tqwvvHUFBnrNHX1bt9xEIfY3xTAQBggJLqiAxUyNnq81PaDh33HARrMgE+i1wT85Ztc1gjHY39TAANhgJDoXp6xQcY6/ffohb6jAA1q/e4yGet0XXqG9pRV+o6DOMP+pgAGwgAhkUUiEd0ybKaMdZqwdJvvOECDu3vkPBnr9Mqsjb6jIM6wvymAgTBASGQ52w7KWKe2fTJVXlXrOw7Q4MYvKYye4PQsJzihPvY3BTAQBgiJrO+kPBnr9LtxK3xHARpFeVWtvto3S8Y6Ld5c7DsO4gj7mwIYCAOERFVdG1aHJ7NlrNPsdXt9xwEazR/fWyljnf7v3ZW+oyCOsL8pgIEwQEhUk/N3xa6TVhfmozEkr2Vbi2Ws01f6ZKmsssZ3HMQJ9jcFMBAGCInq4beWylingRkFvqMAjSoSieg/jpzs9M6iQt9xECfY3wlQAJ955hmFQiH97ne/i32tsrJSjz76qD73uc/pH//xH3XPPfdo9+76F/ssLCzUD3/4Q11wwQW6/PLL9Yc//EG1tfUPdJ85c6Y6duyo8847T9dff71ef/31M8rGACERHThUrVa9MmSs05pdzC6S3+jZG2Ws010vz/MdBXGC/R3nBXDJkiW65pprdMMNN9QrgL/+9a/1pS99SdOnT9eyZcv0ne98RzfddFPs+bq6OrVv317f+973lJOTo8zMTH3+859Xenp67DWbN29WixYt9H//938qKCjQSy+9pObNm2vy5MmnnY8BQiJ6a8EWGev0g+fn+I4CNIl95VW6Pp2/9OAY9nccF8Dy8nK1bt1aU6dO1Xe/+91YASwpKdG5556r9957L/baNWvWKBQKaeHC6MVsMzMz9Q//8A/13hV85ZVXdPHFF6u6ulqS9MQTT6hdu3b1fs2f/OQnuv322087IwOERNT15ei10f4yZ5PvKECTeeStZTLW6U8f5/uOgjjA/o7jAvizn/1Mjz32mCTVK4DTp09XKBTSwYMH673+y1/+soYPHy5J6tu3rzp06FDv+c2bNysUCmnFiuglL/7t3/6t3ruKkvTXv/5VF1988WlnZICQaDbuLefuCEhJM9bskbFOHZ7MVlVtne848Iz9HacFcNy4cWrfvr0qK6ML6tMF8J133tF555133Pd861vf0hNPPCFJ+tWvfqXvf//79Z6vqKhQKBRSZmamJKl169YaNGhQvddkZGQoFArp8OET3xO1qqpKpaWlsUdRUVHKDxASy7OT18pYp5//dbHvKECTqgtH9O2B02Ss0ye5O3zHgWcUwDgsgNu2bdMVV1yh3Nzc2NfipQD2799foVDouEcqDxASRzgc0U3PTJexTh+vZAEi9Rz9C9BPX1vkOwo8owDGYQH88MMPFQqF1Lx589gjFAqpWbNmat68uaZNm+btI2DeAUQim75mt4x1at9vsipr+AgMqadwf4WMdbqmp1PRgQrfceARBTAOC2BZWZny8vLqPb75zW/qpz/9qfLy8mIngbz//vux71m7du0JTwLZs2dP7DWjR4/WxRdfrKqqKknRk0Dat29f79fu3r07J4EgKUUiEd09MnryxyCu/YcU1v3VhTLWafiUdb6jwCP2dxwWwBP59EfAUvQyMF/+8pc1Y8YMLVu2TJ06dVKnTp1izx+9DMz3v/99rVy5UpMnT9bll19+wsvA/PGPf9SaNWs0cuRILgODpDV/wz4Z69S6dyYnfyClTcrZLmOdbnpmOnfBSWHs7wQtgEcvBH3ZZZepRYsW+vGPf6xdu3bV+56tW7fqBz/4gS644AJ9/vOf1+9///sTXgj661//us477zxdd911XAgaSevoux59J+X5jgJ4VVlTp3/uP5n7YKc49neCFMB4xQAhESzbekDGOl2fnqHtB098ghOQSvpOypOxTo++s9x3FHjC/qYABsIAIRE8+PoSGev0x/dW+o4CxIW87SXRQyJ6ZerAoWrfceAB+5sCGAgDhHh3dNFd29Np875DvuMAceOHL8yRsU5j5m72HQUesL8pgIEwQIh3//N29PZXvxm7wncUIK68eeSe2N8fPluRCCeDpBr2ialdaQAAF4xJREFUNwUwEAYI8WzDnjJd09PJWKe1u8p8xwHiSklFjdr0zpSxTisKD/iOgybG/qYABsIAIZ49/m6OjHX65ZtLfUcB4tLj43O4NWKKYn9TAANhgBCvCvdX6Lr0DBnrtHLbwVN/A5CCNu87pOuP/H8yf8M+33HQhNjfFMBAGCDEq/SJq7jnKXAa+h25JMwPX5ijMBeGThnsbwpgIAwQ4tGukkq17hU9tmnRpv2+4wBxbX95ldr3i14YeuKKIt9x0ETY3xTAQBggxKMnP14tY526vbLAdxQgIYycuSF2e7jKmjrfcdAE2N8UwEAYIMSb/eVVatsn+u7fLG5zBZyWypo6dRo0TcY6vTJro+84aALsbwpgIAwQ4s3QyWtkrNOdL87l2mbAGXh/WZGMdWrffzJ3B0kB7G8KYCAMEOJJyeGa2LFMk/N3+Y4DJJRwOKIfPB+9O8ifPs73HQeNjP1NAQyEAUI8eXHaehnrdNvwWZzNCJyFuev3yVin69MztIVbJyY19jcFMBAGCPHiUFWtOjyZLWOdJuVs9x0HSFg/G7NYxjr9z9vLfEdBI2J/UwADYYAQL16dvUnGOn136AzV1oV9xwES1ppdpbr2yC0Ul23lFnHJiv1NAQyEAUI8qKyp0zefnipjncYvKfQdB0h4T7yXK2Od7hk1n5OpkhT7mwIYCAOEePDWgi0y1qnToGmqruXdPyCo3aWV+kqfLBnrlJW303ccNAL2NwUwEAYIvtXUhXXTM9NlrNMb87f4jgMkjeey18pYp39/dqZqOKwi6bC/KYCBMEDwbcLSbTLW6cYBU7mDAdCAyqtqdeOAKfzlKkmxvymAgTBA8Clve4na95/M3QuARvK3hVtlrFPHp6aotLLGdxw0IPY3BTAQBgi+bNhTpo5PRd+d+M9R83n3D2gEtXVh/cewmTLWaXDWGt9x0IDY3xTAQBgg+FC4v0L/MnBq7JZvvDMBNJ4pq3fLWKc2vTO14+Bh33HQQNjfFMBAGCA0tV0lleo8JHrSx/eem6Vi7lkKNKpIJKJuf14gY50efzfHdxw0EPY3BTAQBghNaV95VezjqJuHztCe0krfkYCUsHLbQRnrdE1Pp/wdJb7joAGwvymAgTBAaColFTXqcuRG9Z0GTVPRgQrfkYCU8puxK2Ss03+9Ml+Hqmp9x0FA7G8KYCAMEJpCeVWt7h45L3a5l017y31HAlLOtuIKtemdKWOdbn1ultbvLvMdCQGwvymAgTBAaGyVNXX679ELZazTDX/K1ppdzBrgy5ItxbETsL7SJ0sTVxT5joSzxP6mAAbCAKExVdeG9eDrS2Ss09f6Ziln20HfkYCUt6+8Svf9JfqXMmOden6wisswJSD2NwUwEAYIjaW2LqxH314eu/zEwk37fUcCcERdOKLnpqzTNT2jJfCHL8zR1v2HfMfCGWB/UwADYYDQGMLhiH4/YaWMdWrVK0Mz1+7xHQnACcxetzd2Qfb2/ScrK2+X70g4TexvCmAgDBAaWlVtnfpOypOxTtelZygrb6fvSABOYmfJYd0zan7sI+EBn6xWTV3YdyycAvubAhgIA4SGsnZXmZ78eLW+/mR2bJF8sJwDzIFEUFMX1oBPVsf+371n1HztLOGuIfGM/U0BDIQBQhBllTUau7hQXV+eF1scxjp96+mplD8gAWXl7VL7fpNlrFPHp6Zo9rq9viPhM7C/KYCBMEA4U5FIREu2FOv3E1bqK32yYqXv+vQM/erNpZq+Zrdq+fgISFhb9x/SD1+YE7tzSPdXF+ovczZx/c44w/6mAAbCAOF07S2r0iuzNuqWI7dyO/q4ZdhM/XnWRu0tq/IdEUADqaypU88PVtX7f91Yp+8OnaEnP16tuev3qbqWv+j5xP6mAAbCAOHv1YUjKtxfoelrdmv07I3643sr9eOR83R9ekZsCXylT5b+MGGllm4pViQS8R0ZQCPZsu+QXpu7Wff/ZZFa9cqoVwa/1jdLj7y1TO8u2aY9ZdzXu6mxvymAgTBAqauqtk5rdpXqk9wdGjF1nf7fO8t1+4jZsVtFnehx98h5Gre4UOXcRxRIOeVVtcrK26k/vrdSNw6YetyfDz96aa6edqv1+rzNmpy/S6uKSrSvvIq/JDYS9jcFMBAGKHHVhSMqr6rVvvIqbSuu0IY9ZVpR+P/bu/eoKOt1D+CvsRgSFcSgvA5pUasjZXWAA3rS7cIDhiVb1ypW7ZasUwsbpZXtvCzK5WbXMbQ0tKCLJxOXO8KtLlF30CTXERQvE/c7CMJEXIXhJqAM3/MHMceBwRuDM/O+389azx++8y59Hn/v8H6ZeeedVqSWNOJ4tgbfZ1Th89Nl2HaiAO/8mI039p/HS19m4D8/TdFf5D1auW1NhP8eFdbH/orI02U4lVuHqmbeJJaIBul0A8jTtGFPUhlejsq47c+TxZ+lImjfObx3OAef/lyCQ1lXkFzcgOyaVlQ3d0HbfR06HYPi3eD5mwFwTMb7ABoYGMCNfh16rvejs/cGtN3X0dzZi4b2Hmhau3GlpQsVjZ0ore9AUV07iuraUVinRWGdFgW/jax8zWDladoMKrfWsHKGVXZNK9RXWnGp+irOX27BucoWnK1oRkZ5M1RlTUgrbURKSQOSihrwS2E9fimsR1JRA5KLG5BS0oDU0kaklTYivawJZ8qbkFHejLMVzThbOViqsiaklDRAWViPn/J+x4mc33BUrUHchRocOleN7zOqsE9ViejUCuxNKscuZSkiEorx91OF2Bqfjy1H8/DXwzkIjf0Vaw9dwn/HXMQb+8/jlW/PYWVUBvwiVXjh01R4bk+Ce7gSbh+O/ird3ZT735QIjM7ExiO5+Ca9EklFDahu7kI/fxAT0V1o7OjBPy/V4qNTRVD8Q42V0Znw3J6k/6aRO6l5HyTguY9PY+nuNKz++izeOngRG4/kYvtPRYhOrcChrCs4cqkWp3Lr8EthPVRlTbhQdRW5tW0ore/AlZYu1Gt70Nbdh57r/bjRrxP1q48MgAyAYzJeB9DepHKDa8ZY41tPbE3Ego9+wcIdKQj44gz+8t15rI/9FVvj87FLWYrvzlzGUbUGycUNUF+5isqmTrTwrRkiGmd9N3SovdqNC1VXcSLnN3ydVoltJwrw1sFLWPHlGSzckYKntv08rj8fHw0b/EaiJ7Ym4qltP8M9XIkFH/2Cf/+f0/DcngTviGQs2pmCP+1Kw7LP07F87xm8HJWBVV9l4pVvz+Ev351H8IELeOvgJSj+ocY7P2bj3bi7q/G4IT4DIAPgmIxnALzVE/KxDwafjPP/psQzfx98InpsT4LnH+X1yWD9xyfJ+vKOGCyfP2rhjpRb1qKdhrX4s1T8aVcalu4efJL7Rargv0eFF/eewYovB5/wgdGZ+PNXgxUYnYmVURl4OSoDK748g4AvzmD53jPw36OCX6QK/xWZjmWfp8P383T471HhpS8z8Oc/fmC8/l0W1nx/AW8dvIi3D6kRGvsr/no4B5uP5uLD4/kIP1mITxKK8ZmyBHuSyhCdWoH/VV1GTGYVfjh/Bf+8VIvj2Rr8K68OycUNyKxohvpKKwrrtLjc1Im6tmto7erDtb5+vm1CRFav90Y/Gtp7UFLfjnOVLUjM/x2x52sQnVqB7T8VYeORXKw9dAnBBy4gaN85BEZnYvneM1i6Kw0+Ecl4/uPT+LdtP1vsCw97kspM/n/GAGiBATAiIgIeHh6YPHkyXFxcEBgYiNLSUoN9enp6sH79ekybNg2TJk3C6tWr0dDQYLBPTU0NAgICMHHiRLi4uGDTpk24ccPw4vu0tDQ899xzkMlkeOyxxxATE3NXvY7XAdTecx0N7T1o7uyFtvs6OntvSOIleSIiMq8b/Tr9JUctnb1o7OhBvXbwsqOalm5cbupERWMHSus7UFg3eFlRdk0rLlZfHXFJz7/y6hCf/RuOXKrFjzdd0rP/LuvXmlaTz8kAaIEB0N/fHzExMSgsLERubi4CAgIgl8vR1fX/F9ErFArMmTMHKSkpUKvV8Pb2xsKFC/WP9/f3w93dHcuWLUNOTg4SExPh7OyMDz74QL9PVVUV7O3t8f7776O4uBhRUVGwsbGBUqm84155ABEREVkfnr8tMAAO19TUBEEQoFKpAABarRa2trY4evSofp+SkhIIgoCsrCwAQGJiIh544AGDVwW/+eYbODg4oK+vDwCwZcsWzJ8/3+DfCgoKgr+//x33xgOIiIjI+vD8bQUBsKKiAoIgoKCgAACQkpICQRDQ1tZmsJ9cLkdkZCQAYNu2bViwYIHB41VVVRAEAdnZ2QCAF154ARs2bDDY58CBA3BwcBi1l97eXrS3t+tLo9FI/gAiIiKyNgyAFh4AdTodVqxYgUWLFum3xcbGQiaTjdjX09MTW7ZsAQCEhITAz8/P4PHu7m4IgoDExEQAgJubGyIiIgz2SUhIgCAIuHbtmtF+wsPDIQjCiJLyAURERGRtGAAtPAAqFAq4urpCo9Hot5kzAPIVQCIiIuvHAGjBATA0NBSzZ89GVVWVwXZzvgU8HA8gIiIi68PztwUGwIGBAYSGhmLmzJkoLy8f8fjQh0COHTum31ZaWmr0QyCNjY36ffbt2wcHBwf09vYCGPwQiLu7u8Hf/dprr/FDIERERCLH87cFBsB169bB0dER6enpqK+v19fNb8sqFArI5XKkpqZCrVbDx8cHPj4++seHbgPj5+eH3NxcKJVKuLi4GL0NzObNm1FSUoKvvvqKt4EhIiKSAJ6/LTAAGvuQhSAIBjdpHroRtJOTE+zt7bFq1SrU19cb/D1XrlzBiy++iIkTJ8LZ2RkbN240eiPoZ599FjKZDPPmzbOYG0ETERHR+OH52wIDoDXhAURERGR9eP5mABwTHkBERETWh+dvBsAx4QFERERkfXj+ZgAcEx5ARERE1ofnbwbAMeEBREREZH14/mYAHBOtVgtBEKDRaAy+IYTFYrFYLJbl1tA3eWm1WnNHCbNhAByDoQOIxWKxWCyW9dXNXzUrNQyAY6DT6aDRaKDVasfttxMxv7oohRk5p/iKc4qnpDAj5zReWq0WGo0GOp3O3FHCbBgALVR7u/ivT5DCjADnFBvOKR5SmBHgnGQcA6CFksKBLIUZAc4pNpxTPKQwI8A5yTgGQAslhQNZCjMCnFNsOKd4SGFGgHOScQyAFqq3txfh4eHo7e01dyvjRgozApxTbDineEhhRoBzknEMgEREREQSwwBIREREJDEMgEREREQSwwBIREREJDEMgEREREQSwwBogaKjo+Hq6go7Ozt4eXnhwoUL5m7JpMLDw0d8Hc+TTz5p7rbGTKVS4aWXXsKMGTMgCALi4+MNHh8YGMC2bdswffp0PPjgg/D19UV5ebmZur13t5szODh4xPr6+/ubqdt7ExERAQ8PD0yePBkuLi4IDAxEaWmpwT49PT1Yv349pk2bhkmTJmH16tVoaGgwU8f35k7mXLJkyYj1fPvtt83U8b35+uuv8fTTT2PKlCmYMmUKvL29kZiYqH9cDGsJ3H5OMazlcDt27IAgCNiwYYN+m1jWc7wxAFqYw4cPQyaT4cCBAygqKkJISAimTp2KxsZGc7dmMuHh4Zg/fz7q6+v11dzcbO62xiwxMRFbt27F8ePHjQajnTt3wtHRESdOnEBeXh5WrlyJuXPnoqenx0wd35vbzRkcHIzly5cbrG9ra6uZur03/v7+iImJQWFhIXJzcxEQEAC5XI6uri79PgqFAnPmzEFKSgrUajW8vb2xcOFCM3Z99+5kziVLliAkJMRgPa3tPmunTp1CQkICysvLUVZWhg8//BC2trYoLCwEII61BG4/pxjW8mYXL17Eo48+imeeecYgAIplPccbA6CF8fLyQmhoqP7POp0OM2fOxI4dO8zYlWmFh4djwYIF5m5jXA0PRgMDA5g+fTp27dql36bVamFnZ4e4uDhztGgSowXAwMBAM3U0PpqamiAIAlQqFYDBtbO1tcXRo0f1+5SUlEAQBGRlZZmrzTEbPicwGBpuPrmKhZOTE/bv3y/atRwyNCcgrrXs7OyEm5sbkpKSDOYS+3qaEgOgBenr64ONjc2IE+qaNWuwcuVKM3VleuHh4bC3t8eMGTMwd+5cvP7666ipqTF3WyY1PBhdvnwZgiAgJyfHYL/Fixfj3Xffvd/tmcxoAdDR0REuLi544oknoFAo0NLSYqYOTaOiogKCIKCgoAAAkJKSAkEQ0NbWZrCfXC5HZGSkOVo0ieFzAoOhwdnZGQ899BDmz5+PsLAwdHd3m7HLsenv70dcXBxkMhmKiopEu5bD5wTEtZZr1qzBe++9B8Aw2Ip1PccDA6AFqaurgyAIOHfunMH2zZs3w8vLy0xdmV5iYiKOHDmCvLw8KJVK+Pj4QC6Xo6Ojw9ytmczwYHT27FkIgoDff//dYL9XXnkFr7766v1uz2SMBcC4uDicPHkS+fn5iI+Px1NPPQVPT0/09/ebqcux0el0WLFiBRYtWqTfFhsbC5lMNmJfT09PbNmy5X62ZzLG5gSAffv2QalUIj8/Hz/88ANmzZqFVatWmanLe5efn49JkybBxsYGjo6OSEhIACC+tRxtTkA8axkXFwd3d3f95TM3B0Cxred4YgC0IFIJgMO1tbXBwcFB/zaFGEg5AA439OpncnLyferKtBQKBVxdXaHRaPTbxHiSMTanMUOvsFRWVt6nzkyjr68PFRUVUKvVCAsLg7OzM4qKikS3lqPNaYw1rmVtbS0efvhh5OXl6bcxAN4bBkALIpW3gI3x8PBAWFiYudswGSm/BWyMs7Mzvv322/vQkWmFhoZi9uzZqKqqMtgutreZRpvTmK6uLgiCAKVSeR86Gz++vr5Yu3at6NZyuKE5jbHGtYyPj4cgCLCxsdGXIAiYMGECbGxskJycLOr1NCUGQAvj5eWFd955R/9nnU6HWbNmiepDIMN1dnbCyckJX3zxhblbMZnRPgSye/du/bb29nZRfghkOI1GgwkTJuDkyZP3qauxGxgYQGhoKGbOnGn0Vj1DF5ofO3ZMv620tNTqLjS/3ZzGZGZmQhAEg1dgrNHSpUsRHBwsmrUczdCcxljjWnZ0dKCgoMCgPDw88MYbb6CgoED062lKDIAW5vDhw7Czs8PBgwdRXFyMtWvXYurUqaK6h9HGjRuRnp6O6upqnD17FsuWLYOzszOamprM3dqYdHZ2IicnBzk5ORAEAZGRkcjJydF/wGXnzp2YOnWq/vq4wMBAq7wNzK3m7OzsxKZNm5CVlYXq6mokJyfj+eefh5ubG3p7e83d+h1bt24dHB0dkZ6ebnDLjGvXrun3USgUkMvlSE1NhVqtho+PD3x8fMzY9d273ZyVlZX4+OOPoVarUV1djZMnT2LevHlYvHixmTu/O2FhYVCpVKiurkZ+fj7CwsIwYcIEnD59GoA41hK49ZxiWUtjhn+6WSzrOd4YAC1QVFQU5HI5ZDIZvLy8cP78eXO3ZFJBQUGYMWMGZDIZZs2ahaCgIKu6BmU0aWlpI26yKgiC/rfvoRtBP/LII7Czs4Ovry/KysrM2/Q9uNWc165dg5+fH1xcXGBrawtXV1eEhIRY3S8wxuYTBAExMTH6fYZuNuvk5AR7e3usWrUK9fX15mv6HtxuztraWixevBjTpk2DnZ0dHn/8cWzevNnq7h335ptvwtXVFTKZDC4uLvD19dWHP0Acawncek6xrKUxwwOgWNZzvDEAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxDAAEhEREUkMAyARERGRxPwfAiHhwgq7L+AAAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f7a5a88f3c8>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# and here again the same profile:\n",
    "fig, ax = subplots() \n",
    "ax.plot(cnv[1060+25,1030:1070])\n",
    "# the peak got broader (2x) but much smoother on the top: this is what we are interrested in."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After convolution with a pattern of the same shape as the hole, the peak center is located with a sub-pixel resolution.\n",
    "The peak has a full size of 30 pixels in 1 dimension.\n",
    "\n",
    "All peak positions will be extracted using the pyFAI inverse watershed algorithm. \n",
    "Once all regions are segmented, the ones too small are sieved out and the remaining ones are classifies according to their peak intensity using an histogram. As intensity vary a lot, this histogram it is done on the log-scale of the intensity."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of points in the kernel: 97\n"
     ]
    }
   ],
   "source": [
    "mini = (kernel>0).sum()\n",
    "print(\"Number of points in the kernel: %s\"%mini)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of region segmented: 79513\n",
      "Number of large enough regions : 8443\n"
     ]
    }
   ],
   "source": [
    "try: #depends if the version of pyFAI you are using\n",
    "    from pyFAI.watershed import InverseWatershed\n",
    "except:\n",
    "    from pyFAI.ext.watershed import InverseWatershed\n",
    "    #Version of pyFAI newer than feb 2016\n",
    "iw = InverseWatershed(cnv)\n",
    "iw.init()\n",
    "iw.merge_singleton()\n",
    "all_regions = set(iw.regions.values())\n",
    "regions = [i for i in all_regions if i.size>mini]\n",
    "\n",
    "print(\"Number of region segmented: %s\"%len(all_regions))\n",
    "print(\"Number of large enough regions : %s\"%len(regions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(array([1.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00, 0.000e+00,\n",
       "        0.000e+00, 0.000e+00, 0.000e+00, 1.000e+00, 2.850e+02, 5.999e+03,\n",
       "        1.719e+03, 1.000e+00, 0.000e+00, 1.000e+00, 3.000e+00, 2.300e+01,\n",
       "        1.170e+02, 2.930e+02]),\n",
       " array([2.05537045, 2.1621182 , 2.26886594, 2.37561369, 2.48236143,\n",
       "        2.58910918, 2.69585692, 2.80260467, 2.90935241, 3.01610016,\n",
       "        3.1228479 , 3.22959565, 3.33634339, 3.44309114, 3.54983888,\n",
       "        3.65658663, 3.76333437, 3.87008212, 3.97682986, 4.08357761,\n",
       "        4.19032535]),\n",
       " <a list of 20 Patch objects>)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = [i.maxi for i in regions]\n",
    "\n",
    "fig, ax = subplots()\n",
    "ax.hist(numpy.log10(s), 20)\n",
    "#Look for the maximum value in each region to be able to segment accordingly"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are clearly 3 groups of very different intensity, well segregated:\n",
    "\n",
    "* around $10^{2.1}$ (~125), those are the peaks where no tapper brings light\n",
    "* around $10^{3.4}$ (~2500), those are segmented region in the background\n",
    "* above $10^{3.9}$ (~8000), those are actual peaks, we are looking for.\n",
    "\n",
    "We retain all peaks >$10^{3.5}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of remaining peaks: 438\n"
     ]
    }
   ],
   "source": [
    "peaks = [(i.index//img.shape[-1], i.index%img.shape[-1]) for i in regions if (i.maxi)>10**3.5]\n",
    "print(\"Number of remaining peaks: %s\"%len(peaks))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Raw peak coordinate:\n",
      "[(601, 446), (603, 347), (605, 249), (1273, 2027), (1274, 1933), (608, 153), (1275, 1838), (1845, 2021), (1276, 1742), (610, 58)]\n"
     ]
    }
   ],
   "source": [
    "fix, ax = subplots()\n",
    "ax.imshow(img, interpolation=\"nearest\", origin=\"lower\")\n",
    "peaks_raw = numpy.array(peaks)\n",
    "plot(peaks_raw[:,1], peaks_raw[:, 0], \"or\")\n",
    "xlim(0,2048)\n",
    "ylim(0,2048)\n",
    "title(\"Extracted peak position (raw)\")\n",
    "print(\"Raw peak coordinate:\")\n",
    "print(peaks[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Precise peak extraction is performed using a second order tailor expansion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    from pyFAI.bilinear import Bilinear\n",
    "except:\n",
    "    from pyFAI.ext.bilinear import Bilinear\n",
    "bl = Bilinear(cnv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Refined peak coordinate:\n",
      "[(600.8470064401627, 445.7594981044531), (603.185812458396, 347.425573438406), (605.352923810482, 249.39718168973923), (1272.9463423714042, 2026.5502902269363), (1274.126026943326, 1932.9975793703925), (607.8263006657362, 152.83770795166492), (1274.7215883433819, 1837.7138437330723), (1845.278432816267, 2020.8729793131351), (1276.1018461734056, 1742.0432641915977), (610.4052897691727, 57.652136385440826)]\n"
     ]
    }
   ],
   "source": [
    "ref_peaks = [bl.local_maxi(p) for p in peaks]\n",
    "fig, ax = subplots()\n",
    "ax.imshow(img, interpolation=\"nearest\", origin=\"lower\")\n",
    "peaks_ref = numpy.array(ref_peaks)\n",
    "ax.plot(peaks_raw[:,1], peaks_raw[:, 0], \"or\")\n",
    "ax.plot(peaks_ref[:,1],peaks_ref[:, 0], \"ob\")\n",
    "xlim(0,2048)\n",
    "ylim(0,2048)\n",
    "title(\"Extracted peak position (red: raw, blue: refined)\")\n",
    "print(\"Refined peak coordinate:\")\n",
    "print(ref_peaks[:10])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this stage, a visual inspection of the grid confirms all peaks have been properly segmented. If this is not the case, one can adapt:\n",
    "\n",
    "* the size of the kernel\n",
    "* the threshold coming out of the histogramming\n",
    "\n",
    "## Pair-wise distribution function\n",
    "\n",
    "We will now select the (4-) first neighbours for every single peak.\n",
    "For this we calculate the distance_matrix from any point to any other: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Nota, pyFAI uses **C-coordinates** so they come out as (y,x) and not the usual (x,y). \n",
    "# This notation helps us to remind the order\n",
    "yx = numpy.array(ref_peaks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pairwise distance calculation using scipy.spatial.distance_matrix\n",
    "from scipy.spatial import distance_matrix\n",
    "dist = distance_matrix(peaks_ref, peaks_ref)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's have a look at the pairwise distribution function for the first neighbors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Pair-wise distribution function')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = subplots()\n",
    "ax.hist(dist.ravel(), 200, range=(0,200))\n",
    "title(\"Pair-wise distribution function\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This histogram provides us:\n",
    "\n",
    "* At 0, the 438 peaks with 0-distance to themselves.\n",
    "* between 85 and 105 the first neighbours\n",
    "* between 125 and 150 the second neighbours.\n",
    "* ... and so on.\n",
    "\n",
    "We now focus on the first neighbours which are all located between 70 and 110 pixels apart."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 359 control point with exactly 4 first neigbours\n"
     ]
    }
   ],
   "source": [
    "#We define here a data-type for each peak (called center) with 4 neighbours (called north, east, south and west). \n",
    "point_type = np.dtype([('center_y', float), ('center_x', float),\n",
    "                        ('east_y', float), ('east_x', float),\n",
    "                        ('west_y', float), ('west_x', float),\n",
    "                        ('north_y', float), ('north_x', float),\n",
    "                        ('south_y', float), ('south_x', float)])\n",
    "\n",
    "neig = np.logical_and(dist>70.0, dist<110.0)\n",
    "valid = (neig.sum(axis=-1)==4).sum()\n",
    "print(\"There are %i control point with exactly 4 first neigbours\"%valid)\n",
    "# This initializes an empty structure to be populated\n",
    "point = numpy.zeros(valid, point_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Populate the structure: we use a loop as it loops only over 400 points \n",
    "h=-1\n",
    "for i, center in enumerate(peaks_ref):\n",
    "    if neig[i].sum()!=4: continue\n",
    "    h+=1\n",
    "    point[h][\"center_y\"],point[h][\"center_x\"] = center\n",
    "    for j in ((0,1),(0,-1),(1,0),(-1,0)):\n",
    "        tmp = []\n",
    "        for k in numpy.where(neig[i]):\n",
    "            curr = yx[k]\n",
    "            tmp.append(dot(curr-center,j))\n",
    "            l = argmax(tmp)\n",
    "            y, x = peaks_ref[numpy.where(neig[i])][l]\n",
    "            if j==(0,1):point[h][\"east_y\"], point[h][\"east_x\"] = y, x\n",
    "            elif j==(0,-1):point[h][\"west_y\"], point[h][\"west_x\"] = y, x\n",
    "            elif j==(1,0): point[h][\"north_y\"],point[h][\"north_x\"] = y, x\n",
    "            elif j==(-1,0):point[h][\"south_y\"],point[h][\"south_x\"] = y, x"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will need to define an *origin* but taking it on the border of the image is looking for trouble as this is where distortions are likely to be the most important. The center of the detector is an option but we prefer to take the peak the nearest to the centroid of all other peaks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The guessed center is at (734, 1181)\n",
      "The center is at (753.7035001516342, 1186.1879850327969)\n",
      "The X vector is is at (97.71973018262348, -0.7879771176533654)\n",
      "The Y vector is is at (1.382185794965657, 97.08269907579457)\n"
     ]
    }
   ],
   "source": [
    "#Select the initial guess for the center:\n",
    "\n",
    "#Most intense peak:\n",
    "#m = max([i for i in regions], key=lambda i:i.maxi)\n",
    "#Cx, Cy = m.index%img.shape[-1],m.index//img.shape[-1]\n",
    "#Cx, Cy = point[\"center_x\"].mean(), point[\"center_y\"].mean() #Centroid of all points\n",
    "Cx, Cy = 734, 1181 #beam center\n",
    "#Cx, Cy = tuple(i//2 for i in cnv.shape) #detector center\n",
    "print(\"The guessed center is at (%s, %s)\"%(Cx, Cy))\n",
    "\n",
    "#Get the nearest point from centroid:\n",
    "d2 = ((point[\"center_x\"]-Cx)**2+(point[\"center_y\"]-Cy)**2)\n",
    "best = d2.argmin()\n",
    "Op = point[best]\n",
    "Ox, Oy = Op[\"center_x\"], Op[\"center_y\"]\n",
    "\n",
    "print(\"The center is at (%s, %s)\"%(Ox, Oy))\n",
    "#Calculate the average vector along the 4 main axes \n",
    "Xx = (point[:][\"east_x\"] - point[:][\"center_x\"]).mean()\n",
    "Xy = (point[:][\"east_y\"] - point[:][\"center_y\"]).mean()\n",
    "Yx = (point[:][\"north_x\"] - point[:][\"center_x\"]).mean()\n",
    "Yy = (point[:][\"north_y\"] - point[:][\"center_y\"]).mean()\n",
    "\n",
    "print(\"The X vector is is at (%s, %s)\"%(Xx, Xy))\n",
    "print(\"The Y vector is is at (%s, %s)\"%(Yx, Yy))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X has an angle of -0.4620027563549718 deg\n",
      "Y has an angle of 89.18432364179688 deg\n",
      "The XY angle is 89.64632639815186 deg\n"
     ]
    }
   ],
   "source": [
    "print(\"X has an angle of %s deg\"%rad2deg(arctan2(Xy, Xx)))\n",
    "print(\"Y has an angle of %s deg\"%rad2deg(arctan2(Yy, Yx)))\n",
    "print(\"The XY angle is %s deg\"%rad2deg(arctan2(Yy, Yx)-arctan2(Xy, Xx)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = point[:][\"center_x\"] - Ox\n",
    "y = point[:][\"center_y\"] - Oy\n",
    "xy = numpy.vstack((x,y))\n",
    "R = numpy.array([[Xx,Yx],[Xy,Yy]])\n",
    "iR = numpy.linalg.inv(R)\n",
    "IJ = dot(iR,xy).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Xmin/max -6.073942128478845 12.06072105601781\n",
      "Ymin/max -11.08905457323414 7.040603636712159\n",
      "Maximum error versus integrer: 0.11721135467538701 * pitch size (5mm)\n"
     ]
    }
   ],
   "source": [
    "Xmin = IJ[:,0].min()\n",
    "Xmax = IJ[:,0].max()\n",
    "Ymin = IJ[:,1].min()\n",
    "Ymax = IJ[:,1].max()\n",
    "print(\"Xmin/max\",Xmin, Xmax)\n",
    "print(\"Ymin/max\",Ymin,Ymax)\n",
    "print(\"Maximum error versus integrer: %s * pitch size (5mm)\"%(abs(IJ-IJ.round()).max()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point it is important to check the correct rounding to integers: The maximum error should definitely be better than 0.2*pitch ! If not, try to change the origin (Cx and Cy). This criteria will be used for the optimization later on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Red: measured peaks, Green: Expected position')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = subplots()\n",
    "plot(IJ[:,0],IJ[:,1],\"or\")\n",
    "idx = numpy.round(IJ).astype(int)\n",
    "plot(idx[:,0],IJ[:,1],\"og\")\n",
    "xlim(floor(Xmin), ceil(Xmax))\n",
    "ylim(floor(Ymin), ceil(Ymax))\n",
    "title(\"Red: measured peaks, Green: Expected position\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Estimation of the pixel size:\n",
    "\n",
    "The pixel size is obtained from the pitch of the grid, in vectorial:\n",
    "\n",
    "$$pitch^2 = (Px \\cdot Xx)^2 + (Py \\cdot Xy)^2$$\n",
    "\n",
    "$$pitch^2 = (Px \\cdot Yx)^2 + (Py \\cdot Yy)^2$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Pixel size in average: x:51.165 micron, y: 51.497 microns\n"
     ]
    }
   ],
   "source": [
    "pitch = 5e-3 #mm distance between holes\n",
    "Py = pitch*sqrt((Yx**2-Xx**2)/((Xy*Yx)**2-(Xx*Yy)**2))\n",
    "Px = sqrt((pitch**2-(Xy*Py)**2)/Xx**2)\n",
    "print(\"Pixel size in average: x:%.3f micron, y: %.3f microns\"%(Px*1e6, Py*1e6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this stage, we have:\n",
    "\n",
    " * A list of control points placed on a regular grid with a sub-pixel precision\n",
    " * The center of the image, located on a control point\n",
    " * the average X and Y vector to go from one control point to another\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Optimization of the pixel position\n",
    "\n",
    "\n",
    "The optimization is obtained by minimizing the mis-placement of the control points on the regular grid. For a larger coverage we include now the peaks on the border with less than 4 neighbours."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total inital error  2.59957636070107 [753.7035001516342, 1186.1879850327969, 97.71973018262348, 1.382185794965657, -0.7879771176533654, 97.08269907579457]\n",
      "Maximum initial error versus integrer: 0.19983845643285036 * pitch size (5mm)\n",
      "      fun: 2.123772842174055\n",
      " hess_inv: array([[ 1.43805951e+01,  4.53195877e-01, -8.98140076e-01,\n",
      "         5.58786696e-01, -4.60715036e-03,  7.00463929e-02],\n",
      "       [ 4.53195877e-01,  1.44067578e+01, -1.13249351e-02,\n",
      "         2.28513422e-02, -8.73810864e-01,  5.64844125e-01],\n",
      "       [-8.98140076e-01, -1.13249351e-02,  3.01862537e-01,\n",
      "        -5.18119505e-03,  1.88182399e-03, -3.51293545e-03],\n",
      "       [ 5.58786696e-01,  2.28513422e-02, -5.18119505e-03,\n",
      "         3.00149915e-01, -5.45667603e-04,  5.59024177e-03],\n",
      "       [-4.60715036e-03, -8.73810864e-01,  1.88182399e-03,\n",
      "        -5.45667603e-04,  2.97476220e-01, -3.55561469e-03],\n",
      "       [ 7.00463929e-02,  5.64844125e-01, -3.51293545e-03,\n",
      "         5.59024177e-03, -3.55561469e-03,  2.94399849e-01]])\n",
      "      jac: array([-7.15255737e-07,  3.87430191e-07, -5.06639481e-07, -5.36441803e-07,\n",
      "        0.00000000e+00,  7.74860382e-07])\n",
      "  message: 'Optimization terminated successfully.'\n",
      "     nfev: 160\n",
      "      nit: 15\n",
      "     njev: 20\n",
      "   status: 0\n",
      "  success: True\n",
      "        x: array([ 7.53021122e+02,  1.18519693e+03,  9.81143532e+01,  1.47509387e+00,\n",
      "       -8.04478939e-01,  9.73166900e+01])\n",
      "total Final error  2.123772842174055 [ 7.53021122e+02  1.18519693e+03  9.81143532e+01  1.47509387e+00\n",
      " -8.04478939e-01  9.73166900e+01]\n",
      "Maximum final error versus integrer: 0.23464504285932897 * pitch size (5mm)\n"
     ]
    }
   ],
   "source": [
    "#Measured peaks (all!), needs to flip x<->y\n",
    "peaks_m = numpy.empty_like(peaks_ref)\n",
    "peaks_m[:,1] = peaks_ref[:,0]\n",
    "peaks_m[:,0] = peaks_ref[:,1]\n",
    "\n",
    "#parameter set for optimization:\n",
    "P0 = [Ox, Oy, Xx, Yx, Xy, Yy]\n",
    "\n",
    "P = numpy.array(P0)\n",
    "\n",
    "def to_hole(P, pixels):\n",
    "    \"Translate pixel -> hole\"\n",
    "    T = numpy.atleast_2d(P[:2])\n",
    "    R = P[2:].reshape((2,2))\n",
    "    #Transformation matrix from pixel to holes:\n",
    "    hole = dot(numpy.linalg.inv(R), (pixels - T).T).T\n",
    "    return hole\n",
    "\n",
    "def to_pix(P, holes):\n",
    "    \"Translate hole -> pixel\"\n",
    "    T = numpy.atleast_2d(P[:2])\n",
    "    R = P[2:].reshape((2,2))\n",
    "    #Transformation from index points (holes) to pixel coordinates: \n",
    "    pix = dot(R,holes.T).T + T\n",
    "    return pix\n",
    "\n",
    "def error(P):\n",
    "    \"Error function\"\n",
    "    hole_float = to_hole(P, peaks_m)\n",
    "    hole_int = hole_float.round()\n",
    "    delta = hole_float-hole_int\n",
    "    delta2 = (delta**2).sum()\n",
    "    return delta2\n",
    "\n",
    "print(\"Total inital error \", error(P), P0)\n",
    "holes = to_hole(P, peaks_m)\n",
    "print(\"Maximum initial error versus integrer: %s * pitch size (5mm)\"%(abs(holes-holes.round()).max()))\n",
    "from scipy.optimize import minimize\n",
    "res = minimize(error, P)\n",
    "print(res)\n",
    "print(\"total Final error \", error(res.x),res.x)\n",
    "holes = to_hole(res.x, peaks_m)\n",
    "print(\"Maximum final error versus integrer: %s * pitch size (5mm)\"%(abs(holes-holes.round()).max()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Peak position: measured (red) and expected (Green)')"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig,ax = subplots()\n",
    "peaks_c = to_pix(res.x,to_hole(res.x,peaks_m).round())\n",
    "ax.imshow(img, interpolation=\"nearest\", origin=\"lower\")\n",
    "ax.plot(peaks_m[:,0],peaks_m[:, 1], \"or\")\n",
    "ax.plot(peaks_c[:,0], peaks_c[:, 1], \"og\")\n",
    "xlim(0, 2048)\n",
    "ylim(0, 2048)\n",
    "ax.set_title(\"Peak position: measured (red) and expected (Green)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimized pixel size in average: x:50.959 micron, y: 51.373 microns\n"
     ]
    }
   ],
   "source": [
    "pitch = 5e-3 #mm distance between holes\n",
    "Ox, Oy, Xx, Yx, Xy, Yy = res.x\n",
    "Py = pitch*sqrt((Yx**2-Xx**2)/((Xy*Yx)**2-(Xx*Yy)**2))\n",
    "Px = sqrt((pitch**2-(Xy*Py)**2)/Xx**2)\n",
    "print(\"Optimized pixel size in average: x:%.3f micron, y: %.3f microns\"%(Px*1e6, Py*1e6))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Few comments:\n",
    "\n",
    "* The maximum error grow during optimization without explanations\n",
    "* The outer part of the detector is the most distorted\n",
    "\n",
    "## Interpolation of  the fitted data\n",
    "\n",
    "### Multivariate data interpolation (griddata)\n",
    "\n",
    "\n",
    "Correction arrays are built slightly larger (+1) to be able to manipulate corners instead of centers of pixels\n",
    "As coordinates are needed as y,x (and not x,y) we use p instead of peaks_m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f7a3f394d30>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from scipy.interpolate import griddata\n",
    "grid_x, grid_y = np.mgrid[0:img.shape[0]+1, 0:img.shape[1]+1]\n",
    "delta = peaks_c - peaks_m\n",
    "#we use peaks_res instead of peaks_m to be in y,x coordinates, not x,y\n",
    "delta_x = griddata(peaks_ref, delta[:,0], (grid_x, grid_y), method='cubic')\n",
    "delta_y = griddata(peaks_ref, delta[:,1], (grid_x, grid_y), method='cubic')\n",
    "\n",
    "fig, ax = subplots(1, 2, figsize=(10,5))\n",
    "im0 = ax[0].imshow(delta_x,origin=\"lower\", interpolation=\"nearest\")\n",
    "ax[0].set_title(r\"$\\delta$ x\")\n",
    "fig.colorbar(im0, ax=ax[0])\n",
    "\n",
    "im1=ax[1].imshow(delta_y, origin=\"lower\", interpolation=\"nearest\")\n",
    "ax[1].set_title(r\"$\\delta$ y\")\n",
    "fig.colorbar(im1, ax=ax[1])\n",
    "\n",
    "#Nota: the arrays are filled with \"NaN\" outside the convex Hull"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "#From http://stackoverflow.com/questions/3662361/fill-in-missing-values-with-nearest-neighbour-in-python-numpy-masked-arrays\n",
    "def fill(data, invalid=None):\n",
    "    \"\"\"\n",
    "    Replace the value of invalid 'data' cells (indicated by 'invalid') \n",
    "    by the value of the nearest valid data cell\n",
    "\n",
    "    Input:\n",
    "        data:    numpy array of any dimension\n",
    "        invalid: a binary array of same shape as 'data'. True cells set where data\n",
    "                 value should be replaced.\n",
    "                 If None (default), use: invalid  = np.isnan(data)\n",
    "\n",
    "    Output: \n",
    "        Return a filled array. \n",
    "    \"\"\"\n",
    "\n",
    "    if invalid is None: \n",
    "        invalid = numpy.isnan(data)\n",
    "\n",
    "    ind = ndimage.distance_transform_edt(invalid, return_distances=False, return_indices=True)\n",
    "    return data[tuple(ind)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f7a3f2d0550>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = subplots(1,2, figsize=(10,5))\n",
    "im0 = ax[0].imshow(fill(delta_x),origin=\"lower\", interpolation=\"nearest\")\n",
    "ax[0].set_title(r\"$\\delta$ x\")\n",
    "fig.colorbar(im0, ax=ax[0])\n",
    "\n",
    "im1 = imshow(fill(delta_y), origin=\"lower\", interpolation=\"nearest\")\n",
    "title(r\"$\\delta$ y\")\n",
    "fig.colorbar(im1, ax=ax[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is important to understand the extrapolation outside the convex hull has no justification, it is there just to prevent numerical bugs.\n",
    "\n",
    "## Saving the distortion correction arrays to a detector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mntdirect/_scisoft/users/kieffer/.jupy37/lib/python3.7/site-packages/pyFAI/io/__init__.py:999: H5pyDeprecationWarning: The default file mode will change to 'r' (read-only) in h5py 3.0. To suppress this warning, pass the mode you need to h5py.File(), or set the global default h5.get_config().default_file_mode, or set the environment variable H5PY_DEFAULT_READONLY=1. Available modes are: 'r', 'r+', 'w', 'w-'/'x', 'a'. See the docs for details.\n",
      "  self.h5 = h5py.File(self.filename)\n"
     ]
    }
   ],
   "source": [
    "from pyFAI.detectors import Detector\n",
    "detector = Detector(Py,Px)\n",
    "detector.max_shape = detector.shape = img.shape\n",
    "detector.set_dx(fill(delta_x))\n",
    "detector.set_dy(fill(delta_y))\n",
    "detector.mask = numpy.isnan(delta_x).astype(numpy.int8)[:img.shape[0], :img.shape[1]]\n",
    "detector.save(\"testdetector.h5\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Validation of the distortion correction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pyFAI.distortion import Distortion\n",
    "dis = Distortion(detector)\n",
    "cor = dis.correct(img)\n",
    "\n",
    "fig, ax = subplots(1, 2, figsize=(10,5))\n",
    "ax[0].imshow(img, interpolation=\"nearest\", origin=\"lower\")\n",
    "ax[0].set_title(\"Original\")\n",
    "\n",
    "ax[1].imshow(cor, origin=\"lower\", interpolation=\"nearest\")\n",
    "ax[1].set_title(\"Corrected\")\n",
    "\n",
    "# Save the corrected image\n",
    "fabio.edfimage.EdfImage(data=cor).save(\"corrected.edf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "This procedure describes how to measure the detector distortion and how to create a detector description file directly usable in pyFAI. Only the region inside the convex hull of the grid data-points is valid and the region of the detector which is not calibrated has been masked out to prevent accidental use of it.\n",
    "\n",
    "The distortion corrected image can now be used to check how \"good\" the calibration actually is. This file can be injected in the third cell, and follow the same procedure (left as exercise). This gives a maximum mis-placement of 0.003, the average error is then of 0.0006 and correction-map exhibit a displacement of pixels in the range +/- 0.2 pixels which is acceptable and validates the whole procedure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Execution time: 12.727s\n"
     ]
    }
   ],
   "source": [
    "print(\"Execution time: %.3fs\"%(time.time()-start_time))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7 local venv",
   "language": "python",
   "name": "python3.7"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
