{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to the tutorials\n",
    "\n",
    "## The iPython/Jupyter notebook\n",
    "\n",
    "The document you are seeing it may be a PDF or a web page or another format, but what is important is how it has been made ...\n",
    "\n",
    "According to this article in [Nature](http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261) the Notebook, invented by iPython, and now part of the Jupyter project, is the revolution for data analysis which will allow reproducable science.\n",
    "\n",
    "This tutorial will introduce you to how to access to the notebook, how to use it and perform some basic data analysis with it and the pyFAI library.\n",
    "\n",
    "## Getting access to the notebook\n",
    "\n",
    "There are many cases ...\n",
    "\n",
    "### Inside ESRF\n",
    "The simplest case as the data analysis unit offers you a notebook server: just connect your web browser to http://scisoft12.esrf.fr:8000, http://scisoft13.esrf.fr:8000, http://scisoft14.esrf.fr:8000, http://kolla-vm006.esrf.fr:31227 and authenticate with your ESRF credentials.\n",
    "\n",
    "### Outside ESRF with an ESRF account.\n",
    "The JupyterHub server is not directly available on the internet, but you can [login into the firewall](http://www.esrf.eu/Infrastructure/Computing/Networks/InternetAndTheFirewall/UsersManual/SSH) to forward the web server:\n",
    "\n",
    "  ssh -XC  -p5022 -L8000:scisoft12:8000 user@firewall.esrf.fr\n",
    "\n",
    "Once logged in ESRF, keep the terminal opened and browse on your local computer to http://localhost:8000 to authenticate with your ESRF credentials. Do not worry about confidentiality as the connection from your computer to the ESRF firewall is encrypted by the SSH connection.\n",
    "\n",
    "### Other cases\n",
    "In the most general case you will need to install the notebook on your local computer in addition to silx, pyFAI and FabIO to follow the tutorial. WinPython provides it under windows. Please refer to the installation procedure of pyFAI to install locally pyFAI on your computer. Anaconda provides also pyFAI and FabIO as packages.\n",
    "\n",
    "## Getting trained in using the notebook\n",
    "\n",
    "There are plenty of good tutorials on how to use the notebook.\n",
    "[This one](https://github.com/jupyter/mozfest15-training/blob/master/00-python-intro.ipynb) presents a quick overview of the Python programming language and explains how to use the notebook. Reading it is strongly encouraged before proceeding to the pyFAI itself.\n",
    "\n",
    "Anyway, the most important information is to use **Control-Enter** to evaluate a cell.\n",
    "\n",
    "In addition to this, we will need to download some files from the internet. \n",
    "The following cell contains a piece of code to download files using the silx library. You may have to adjust the proxy settings to be able to connect to internet, especially at ESRF, see the commented out code."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Introduction to diffraction image analysis using the notebook\n",
    "\n",
    "All the tutorials in pyFAI are based on the notebook and if you wish to practice the exercises, you can download the notebook files (.ipynb) from [Github](https://github.com/silx-kit/pyFAI/tree/master/doc/source/usage/tutorial)\n",
    "\n",
    "### Load and display diffraction images\n",
    "\n",
    "First of all we will download an image and display it. Displaying it the right way is important as the orientation of the image imposes the azimuthal angle sign."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using pyFAI version 0.18.0\n"
     ]
    }
   ],
   "source": [
    "import os, time\n",
    "#Nota: May be used if you are behind a firewall and need to setup a proxy\n",
    "#os.environ[\"http_proxy\"] = \"http://proxy.company.fr:3128\"\n",
    "start_time = time.time()\n",
    "import pyFAI\n",
    "print(\"Using pyFAI version\", pyFAI.version)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from silx.resources import ExternalResources\n",
    "downloader = ExternalResources(\"pyFAI\", \"http://www.silx.org/pub/pyFAI/testimages/\", \"DATA\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/pyFAI_testdata_kieffer/moke.tif\n"
     ]
    }
   ],
   "source": [
    "moke = downloader.getfile(\"moke.tif\")\n",
    "print(moke)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The *moke.tif* image we just downloaded is not a real diffraction image but it is a test pattern used in the tests of pyFAI. \n",
    "\n",
    "Prior to displaying it, we will use the Fable Input/Output library to read the content of the file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "#initializes the visualization module to work with the jupyter notebook\n",
    "%pylab nbagg"
   ]
  },
  {
   "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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd52a1f0d68>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import fabio\n",
    "from pyFAI.gui import jupyter\n",
    "img = fabio.open(moke).data\n",
    "jupyter.display(img, label =\"Fake diffraction image\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the image looks like an archery target. The origin is at the **lower left** of the image. \n",
    "If you are familiar with matplotlib, it correspond to the option *origin=\"lower\"* of *imshow*.\n",
    "\n",
    "Displaying the image using imsho without this option ends with having the azimuthal angle (which angles are displayed in degrees on the image) to turn clockwise, so the inverse of the trigonometric order:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>"
      ]
     },
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     "output_type": "display_data"
    },
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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, 'Wrong orientation')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, ax = subplots(1,2, figsize=(10,5))\n",
    "ax[0].imshow(img, origin=\"lower\")\n",
    "ax[0].set_title(\"Proper orientation\")\n",
    "ax[1].imshow(img)\n",
    "ax[1].set_title(\"Wrong orientation\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Nota:** Displaying the image properly or not does not change the content of the image nor its representation in memory, it only changes its representation, which is important only for the user. **DO NOT USE** *numpy.flipud* or other array-manipulation which changes the memory representation of the image. This is likely to mess-up all your subsequent  calculation.\n",
    "\n",
    "### 1D azimuthal integration\n",
    "\n",
    "To perform an azimuthal integration of this image, we need to create an **AzimuthalIntegrator** object we will call *ai*. \n",
    "Fortunately, the geometry is explained on the image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.DEPRECATION:Function AzimuthalIntegrator is deprecated since pyFAI version 0.16. Use 'pyFAI.azimuthalIntegrator.AzimuthalIntegrator' instead.\n",
      "  File \"<ipython-input-7-403adc458771>\", line 3, in <module>\n",
      "    ai = pyFAI.AzimuthalIntegrator(dist=0.1, detector=detector)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Detector Detector\t Spline= None\t PixelSize= 1.000e-04, 1.000e-04 m\n",
      "SampleDetDist= 1.000000e-01m\tPONI= 0.000000e+00, 0.000000e+00m\trot1=0.000000  rot2= 0.000000  rot3= 0.000000 rad\n",
      "DirectBeamDist= 100.000mm\tCenter: x=0.000, y=0.000 pix\tTilt=0.000 deg  tiltPlanRotation= 0.000 deg\n"
     ]
    }
   ],
   "source": [
    "import pyFAI, pyFAI.detectors\n",
    "detector = pyFAI.detectors.Detector(pixel1=1e-4, pixel2=1e-4)\n",
    "ai = pyFAI.AzimuthalIntegrator(dist=0.1, detector=detector)\n",
    "# Short version ai = pyFAI.AzimuthalIntegrator(dist=0.1, pixel1=1e-4, pixel2=1e-4)\n",
    "print(ai)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Printing the *ai* object displays 3 lines:\n",
    "\n",
    " * The detector definition, here a simple detector with square, regular pixels with the right size\n",
    " * The detector position in space using the *pyFAI* coordinate system: dist, poni1, poni2, rot1, rot2, rot3\n",
    " * The detector position in space using the *FIT2D* coordinate system: direct_sample_detector_distance, center_X,\n",
    "center_Y, tilt and tilt_plan_rotation\n",
    "\n",
    "Right now, the geometry in the *ai* object is wrong. It may be easier to define it correctly using the *FIT2D* geometry which uses pixels for the center coordinates (but the sample-detector distance is in millimeters)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method setFit2D in module pyFAI.geometry:\n",
      "\n",
      "setFit2D(directDist, centerX, centerY, tilt=0.0, tiltPlanRotation=0.0, pixelX=None, pixelY=None, splineFile=None) method of pyFAI.azimuthalIntegrator.AzimuthalIntegrator instance\n",
      "    Set the Fit2D-like parameter set: For geometry description see\n",
      "    HPR 1996 (14) pp-240\n",
      "    \n",
      "    Warning: Fit2D flips automatically images depending on their file-format.\n",
      "    By reverse engineering we noticed this behavour for Tiff and Mar345 images (at least).\n",
      "    To obtaine correct result you will have to flip images using numpy.flipud.\n",
      "    \n",
      "    :param direct: direct distance from sample to detector along the incident beam (in millimeter as in fit2d)\n",
      "    :param tilt: tilt in degrees\n",
      "    :param tiltPlanRotation: Rotation (in degrees) of the tilt plan arround the Z-detector axis\n",
      "            * 0deg -> Y does not move, +X goes to Z<0\n",
      "            * 90deg -> X does not move, +Y goes to Z<0\n",
      "            * 180deg -> Y does not move, +X goes to Z>0\n",
      "            * 270deg -> X does not move, +Y goes to Z>0\n",
      "    \n",
      "    :param pixelX,pixelY: as in fit2d they ar given in micron, not in meter\n",
      "    :param centerX, centerY: pixel position of the beam center\n",
      "    :param splineFile: name of the file containing the spline\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(ai.setFit2D)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Detector Detector\t Spline= None\t PixelSize= 1.000e-04, 1.000e-04 m\n",
      "SampleDetDist= 1.000000e-01m\tPONI= 3.000000e-02, 3.000000e-02m\trot1=0.000000  rot2= 0.000000  rot3= 0.000000 rad\n",
      "DirectBeamDist= 100.000mm\tCenter: x=300.000, y=300.000 pix\tTilt=0.000 deg  tiltPlanRotation= 0.000 deg\n"
     ]
    }
   ],
   "source": [
    "ai.setFit2D(100, 300, 300)\n",
    "print(ai)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the *ai* object properly setup, we can perform the azimuthal integration using the *intergate1d* method.\n",
    "This methods takes only 2 mandatory parameters: the image to integrate and the number of bins. We will provide a few other to enforce the calculations to be performed in 2theta-space and in degrees:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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": {
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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, 'Display 1d powder diffraction data using pure matplotlib')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = ai.integrate1d(img, 300, unit=\"2th_deg\")\n",
    "\n",
    "#Display the integration result \n",
    "fig, ax = subplots(1,2, figsize=(10,5))\n",
    "jupyter.plot1d(res, label=\"moke\",ax=ax[0])\n",
    "\n",
    "#Example using pure matplotlib\n",
    "tth = res[0]\n",
    "I = res[1]\n",
    "ax[1].plot(tth, I, label=\"moke\")\n",
    "ax[1].set_title(\"Display 1d powder diffraction data using pure matplotlib\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the 9 rings gave 9 sharp peaks at 2theta position regularly ranging from 4 to 12 degrees as expected from the image annotation.\n",
    "\n",
    "**Nota:** the default radial unit is \"q_nm^1\", so the scattering vector length expressed in inverse nanometers. To be able to calculate *q*, one needs to specify the wavelength used (here we didn't). For example: ai.wavelength = 1e-10 \n",
    "\n",
    "To save the content of the integrated pattern into a 2 column ASCII file, one can either save the (tth, I) arrays, or directly ask pyFAI to do it by providing an output filename:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.io:Destination file moke.dat exists\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# == pyFAI calibration ==\n",
      "# Distance Sample to Detector: 0.1 m\n",
      "# PONI: 3.000e-02, 3.000e-02 m\n",
      "# Rotations: 0.000000 0.000000 0.000000 rad\n",
      "#\n",
      "# == Fit2d calibration ==\n",
      "# Distance Sample-beamCenter: 100.000 mm\n",
      "# Center: x=300.000, y=300.000 pix\n",
      "# Tilt: 0.000 deg  TiltPlanRot: 0.000 deg\n",
      "#\n",
      "# Detector Detector\t Spline= None\t PixelSize= 1.000e-04, 1.000e-04 m\n",
      "#    Detector has a mask: False\n",
      "#    Detector has a dark current: False\n",
      "#    detector has a flat field: False\n",
      "#\n",
      "# Mask applied: False\n",
      "# Dark current applied: False\n",
      "# Flat field applied: False\n",
      "# Polarization factor: None\n",
      "# Normalization factor: 1.0\n",
      "# --> moke.dat\n",
      "#       2th_deg             I\n",
      "3.831631e-01    6.384597e+00\n",
      "1.149489e+00    1.240657e+01\n",
      "1.915815e+00    1.222277e+01\n",
      "2.682142e+00    1.170348e+01\n",
      "3.448468e+00    9.964797e+00\n",
      "4.214794e+00    8.913503e+00\n",
      "4.981120e+00    9.104074e+00\n",
      "5.747446e+00    9.242975e+00\n",
      "6.513773e+00    6.136262e+00\n",
      "7.280099e+00    9.039030e+00\n",
      "8.046425e+00    9.203415e+00\n",
      "8.812751e+00    9.324570e+00\n",
      "9.579077e+00    6.470129e+00\n",
      "1.034540e+01    7.790758e+00\n",
      "1.111173e+01    9.410036e+00\n",
      "1.187806e+01    9.464832e+00\n",
      "1.264438e+01    7.749059e+00\n",
      "1.341071e+01    1.151200e+01\n",
      "1.417703e+01    1.324891e+01\n",
      "1.494336e+01    1.038730e+01\n",
      "1.570969e+01    1.069764e+01\n",
      "1.647601e+01    1.056094e+01\n",
      "1.724234e+01    1.286720e+01\n",
      "1.800867e+01    1.323240e+01\n",
      "1.877499e+01    1.548398e+01\n",
      "1.954132e+01    2.364553e+01\n",
      "2.030764e+01    2.537155e+01\n",
      "2.107397e+01    2.512984e+01\n",
      "2.184030e+01    2.191267e+01\n",
      "2.260662e+01    7.605135e+00\n"
     ]
    }
   ],
   "source": [
    "ai.integrate1d(img, 30, unit=\"2th_deg\", filename=\"moke.dat\")\n",
    "\n",
    "# now display the content of the file\n",
    "with open(\"moke.dat\") as fd:\n",
    "    for line in fd:\n",
    "        print(line.strip())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This \"moke.dat\" file contains in addition to the 2th/I value, a header commented with \"#\" with the geometry used to perform the calculation.\n",
    "\n",
    "**Nota: ** The *ai* object has initialized the geometry on the first call and re-uses it on subsequent calls. This is why it is important to re-use the geometry in performance critical applications.\n",
    "\n",
    "### 2D integration or Caking\n",
    "\n",
    "One can perform the 2D integration which is called caking in FIT2D by simply calling the *intrgate2d* method with 3 mandatroy parameters: the data to integrate, the number of radial bins and the number of azimuthal bins.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.azimuthalIntegrator:Method requested 'None' not available. Method 'IntegrationMethod(2d int, pseudo split, histogram, cython)' will be used\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Azimuthal angle chi (deg)')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res2d = ai.integrate2d(img, 300, 360, unit=\"2th_deg\")\n",
    "\n",
    "#Display the integration result \n",
    "fig, ax = subplots(1,2, figsize=(10,5))\n",
    "jupyter.plot2d(res2d, label=\"moke\",ax=ax[0])\n",
    "\n",
    "#Example using pure matplotlib\n",
    "I, tth, chi = res2d\n",
    "ax[1].imshow(I, origin=\"lower\", extent=[tth.min(), tth.max(), chi.min(), chi.max()], aspect=\"auto\")\n",
    "ax[1].set_xlabel(\"2 theta (deg)\")\n",
    "ax[1].set_ylabel(\"Azimuthal angle chi (deg)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The displayed images the \"caked\" image with the radial and azimuthal angles properly set on the axes. Search for the -180, -90, 360/0 and 180 mark on the transformed image.\n",
    "\n",
    "Like *integrate1d*, *integrate2d* offers the ability to save the intgrated image into an image file (EDF format by default) with again all metadata in the headers. \n",
    "\n",
    "### Radial integration\n",
    "\n",
    "Radial integration can directly be obtained from Caked images:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.azimuthalIntegrator:Method requested 'None' not available. Method 'IntegrationMethod(2d int, pseudo split, histogram, cython)' will be used\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Column number 34\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fd515b61f28>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "target = 8 #degrees\n",
    "#work on fewer radial bins in order to have an actual averaging:\n",
    "I, tth, chi = ai.integrate2d(img, 100, 90, unit=\"2th_deg\")\n",
    "column = argmin(abs(tth-target))\n",
    "print(\"Column number %s\"%column)\n",
    "\n",
    "fig, ax = subplots()\n",
    "ax.plot(chi, I[:,column], label=r\"$2\\theta=%.1f^{o}$\"%target)\n",
    "ax.set_xlabel(\"Azimuthal angle\")\n",
    "ax.set_ylabel(\"Intensity\")\n",
    "ax.set_title(\"Radial intgration\")\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Nota:** the pattern with higher noise along the diagonals is typical from the pixel splitting scheme employed. Here this scheme is a \"bounding box\" which makes digonal pixels look a bit larger (+40%) than the ones on the horizontal and vertical axis, explaining the variation of the noise.\n",
    "\n",
    "### Integration of a bunch of files using pyFAI\n",
    "\n",
    "Once the processing for one file is established, one can loop over a bunch of files.\n",
    "A convienient way to get the list of files matching a pattern is with the *glob* module.\n",
    "\n",
    "Most of the time, the azimuthal integrator is obtained by simply loading the *poni-file* into pyFAI and use it directly. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of EDF downloaded: 52\n"
     ]
    }
   ],
   "source": [
    "all_files = downloader.getdir(\"alumina.tar.bz2\")\n",
    "all_edf = [i for i in all_files if i.endswith(\"edf\")]\n",
    "all_edf.sort()\n",
    "print(\"Number of EDF downloaded: %s\"%len(all_edf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_00_max_51_frames.poni /tmp/pyFAI_testdata_kieffer/alumina/distorsion_2x2.spline\n",
      "Detector Detector\t Spline= /tmp/pyFAI_testdata_kieffer/alumina/distorsion_2x2.spline\t PixelSize= 1.034e-04, 1.025e-04 m\n",
      "Wavelength= 7.084811e-11m\n",
      "SampleDetDist= 1.168599e-01m\tPONI= 5.295653e-02, 5.473342e-02m\trot1=0.015821  rot2= 0.009404  rot3= 0.000000 rad\n",
      "DirectBeamDist= 116.880mm\tCenter: x=515.795, y=522.995 pix\tTilt=1.055 deg  tiltPlanRotation= 149.271 deg\n"
     ]
    }
   ],
   "source": [
    "ponifile = [i for i in all_files if i.endswith(\".poni\")][0]\n",
    "splinefile = [i for i in all_files if i.endswith(\".spline\")][0]\n",
    "print(ponifile, splinefile)\n",
    "\n",
    "#patch the poni-file with the proper path.\n",
    "with open(ponifile, \"a\") as f:\n",
    "    f.write(\"SplineFile: %s\\n\"%splinefile)\n",
    "\n",
    "ai = pyFAI.load(ponifile)\n",
    "print(ai)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0000.dat: 0.384s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0001.dat: 0.012s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0002.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0003.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0004.dat: 0.019s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0005.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0006.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0007.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0008.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0009.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0010.dat: 0.009s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0011.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0012.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0013.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0014.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0015.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0016.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0017.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0018.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0019.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0020.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0021.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0022.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0023.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0024.dat: 0.025s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0025.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0026.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0027.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0028.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0029.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0030.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0031.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0032.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0033.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0034.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0035.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0036.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0037.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0038.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0039.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0040.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0041.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0042.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0043.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0044.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0045.dat: 0.010s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0046.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0047.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0048.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0049.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/al2o3_0050.dat: 0.011s\n",
      "/tmp/pyFAI_testdata_kieffer/alumina/dark_0001.dat: 0.011s\n"
     ]
    }
   ],
   "source": [
    "fig, ax = subplots()\n",
    "\n",
    "for one_file in all_edf:\n",
    "    destination = os.path.splitext(one_file)[0]+\".dat\"\n",
    "    image = fabio.open(one_file).data\n",
    "    t0 = time.time()\n",
    "    res = ai.integrate1d(image, 1000, filename=destination)\n",
    "    print(\"%s: %.3fs\"%(destination, time.time()-t0))\n",
    "    jupyter.plot1d(res, ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This was a simple integration of 50 files, saving the result into 2 column ASCII files.\n",
    "\n",
    "**Nota:** the first frame took 40x longer than the other. This highlights go crucial it is to re-use *azimuthal intgrator* objects when performance matters.\n",
    "\n",
    "## Conclusion\n",
    "Using the notebook is rather simple as it allows to mix comments, code, and images for visualization of scientific data.\n",
    "\n",
    "The basic use pyFAI's AzimuthalIntgrator has also been presented and may be adapted to you specific needs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total execution time: 6.625s\n"
     ]
    }
   ],
   "source": [
    "print(\"Total execution time: %.3fs\"%(time.time()-start_time))"
   ]
  }
 ],
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