{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pilatus on a goniometer at ID28\n",
    "\n",
    "Nguyen Thanh Tra who was post-doc at ESRF-ID28 enquired about a potential bug in pyFAI in October 2016: he calibrated 3 images taken with a Pilatus-1M detector at various detector angles: 0, 17 and 45 degrees. \n",
    "While everything looked correct, in first approximation, one peak did not overlap properly with itself depending on the detector angle. This peak correspond to the peak in the angle of the detector, at 23.6° ...\n",
    "\n",
    "This notebook will guide you through the calibration of the goniometer setup.\n",
    "\n",
    "Let's first retrieve the images and initialize the environment:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab nbagg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "#Nota: comment out when running from outside ESRF\n",
    "os.environ[\"http_proxy\"] = \"http://proxy.esrf.fr:3128\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mntdirect/_scisoft/users/jupyter/jupy35/lib/python3.5/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using pyFAI version: 0.15.0-beta4\n",
      "gonio_ID28\n",
      "det130_g45_0001p.npt\n",
      "det130_g0_0001p.cbf\n",
      "det130_g17_0001p.npt\n",
      "det130_g0_0001p.npt\n",
      "det130_g45_0001p.cbf\n",
      "det130_g17_0001p.cbf\n"
     ]
    }
   ],
   "source": [
    "import fabio, pyFAI, os\n",
    "print(\"Using pyFAI version:\", pyFAI.version)\n",
    "from os.path import basename\n",
    "from pyFAI.gui import jupyter\n",
    "from pyFAI.calibrant import get_calibrant\n",
    "from silx.resources import ExternalResources\n",
    "\n",
    "downloader = ExternalResources(\"thick\", \"http://www.silx.org/pub/pyFAI/testimages\")\n",
    "all_files = downloader.getdir(\"gonio_ID28.tar.bz2\")\n",
    "for afile in all_files:\n",
    "    print(basename(afile))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are 3 images stored as CBF files and the associated control points as npt files. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "images = [i for i in all_files if i.endswith(\"cbf\")]\n",
    "images.sort()\n",
    "mask = None\n",
    "fig, ax = subplots(1,3, figsize=(9,3))\n",
    "for i, cbf in enumerate(images):\n",
    "    fimg = fabio.open(cbf)\n",
    "    jupyter.display(fimg.data, label=basename(cbf), ax=ax[i])\n",
    "    if mask is None:\n",
    "        mask = fimg.data<0\n",
    "    else:\n",
    "        mask |= fimg.data<0\n",
    "\n",
    "numpy.save(\"mask.npy\", mask)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To be able to calibrate the detector position, the calibrant used is LaB6 and the wavelength was 0.69681e-10m "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LaB6 Calibrant at wavelength 6.968e-11\n"
     ]
    }
   ],
   "source": [
    "wavelength=0.6968e-10\n",
    "calibrant = get_calibrant(\"LaB6\")\n",
    "calibrant.wavelength = wavelength\n",
    "print(calibrant)\n",
    "\n",
    "detector =  pyFAI.detector_factory(\"Pilatus1M\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "filename /tmp/thick_testdata_kieffer/gonio_ID28/det130_g0_0001p.cbf angle: 0.0\n",
      "filename /tmp/thick_testdata_kieffer/gonio_ID28/det130_g17_0001p.cbf angle: 17.0\n",
      "filename /tmp/thick_testdata_kieffer/gonio_ID28/det130_g45_0001p.cbf angle: 45.0\n"
     ]
    }
   ],
   "source": [
    "# Define the function that extracts the angle from the filename:\n",
    "\n",
    "def get_angle(basename):\n",
    "    \"\"\"Takes the basename (like det130_g45_0001.cbf ) and returns the angle of the detector\"\"\"\n",
    "    return float(os.path.basename((basename.split(\"_\")[-2][1:])))\n",
    "\n",
    "for afile in images:\n",
    "    print('filename', afile, \"angle:\",get_angle(afile))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Define the transformation of the geometry as function of the goniometrer position. \n",
    "# by default scale1 = pi/180 (convert deg to rad) and scale2 = 0.\n",
    "\n",
    "from pyFAI.goniometer import GeometryTransformation, GoniometerRefinement, Goniometer\n",
    "\n",
    "goniotrans2d = GeometryTransformation(param_names = [\"dist\", \"poni1\", \"poni2\",\n",
    "                                                    \"rot1\", \"rot2\",\n",
    "                                                     \"scale1\", \"scale2\"],\n",
    "                                     dist_expr=\"dist\",\n",
    "                                     poni1_expr=\"poni1\",\n",
    "                                     poni2_expr=\"poni2\",\n",
    "                                     rot1_expr=\"scale1 * pos + rot1\",\n",
    "                                     rot2_expr=\"scale2 * pos + rot2\",\n",
    "                                     rot3_expr=\"0.0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Definition of the parameters start values and the bounds\n",
    "\n",
    "param = {\"dist\":0.30,\n",
    "         \"poni1\":0.08,\n",
    "         \"poni2\":0.08,\n",
    "         \"rot1\":0,\n",
    "         \"rot2\":0,\n",
    "         \"scale1\": numpy.pi/180., # rot2 is in radians, while the motor position is in degrees\n",
    "         \"scale2\": 0\n",
    "        }\n",
    "#Defines the bounds for some variables. We start with very strict bounds\n",
    "bounds = {\"dist\": (0.25, 0.31),\n",
    "          \"poni1\": (0.07, 0.1),\n",
    "          \"poni2\": (0.07, 0.1),\n",
    "          \"rot1\": (-0.01, 0.01),\n",
    "          \"rot2\": (-0.01, 0.01),\n",
    "          \"scale1\": (numpy.pi/180., numpy.pi/180.), #strict bounds on the scale: we expect the gonio to be precise\n",
    "          \"scale2\": (0, 0) #strictly bound to 0\n",
    "         }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty goniometer refinement object:\n",
      "GoniometerRefinement with 0 geometries labeled: .\n"
     ]
    }
   ],
   "source": [
    "gonioref2d = GoniometerRefinement(param, #initial guess\n",
    "                                  bounds=bounds,\n",
    "                                  pos_function=get_angle,\n",
    "                                  trans_function=goniotrans2d,\n",
    "                                  detector=detector, \n",
    "                                  wavelength=wavelength)\n",
    "print(\"Empty goniometer refinement object:\")\n",
    "print(gonioref2d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "det130_g0_0001p Angle: 0.0\n",
      "det130_g17_0001p Angle: 17.0\n",
      "det130_g45_0001p Angle: 45.0\n",
      "Filled refinement object:\n",
      "GoniometerRefinement with 3 geometries labeled: det130_g0_0001p, det130_g17_0001p, det130_g45_0001p.\n"
     ]
    }
   ],
   "source": [
    "# Populate with the images and the control points\n",
    "for fn in images:\n",
    "    base = os.path.splitext(fn)[0]\n",
    "    bname = os.path.basename(base)\n",
    "    fimg = fabio.open(fn)\n",
    "    sg =gonioref2d.new_geometry(bname, image=fimg.data, metadata=bname, \n",
    "                                control_points=base+\".npt\",\n",
    "                                calibrant=calibrant)\n",
    "    print(sg.label, \"Angle:\", sg.get_position())\n",
    "\n",
    "\n",
    "print(\"Filled refinement object:\")\n",
    "print(gonioref2d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 0.0007718180621418161\n",
      "[0.3        0.08       0.08       0.         0.         0.01745329\n",
      " 0.        ]\n",
      "     fun: 4.4188913962221164e-08\n",
      "     jac: array([ 8.45390424e-09,  8.92671967e-08,  3.37939728e-07, -9.31373960e-08,\n",
      "        3.55469623e-08, -3.52535668e-03,  9.75932426e-04])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 191\n",
      "     nit: 21\n",
      "    njev: 21\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([0.28456254, 0.08940175, 0.08892749, 0.00442128, 0.0029766 ,\n",
      "       0.01745329, 0.        ])\n",
      "Cost function after refinement: 4.4188913962221164e-08\n",
      "GonioParam(dist=0.28456254071696413, poni1=0.08940174752967277, poni2=0.08892749449109176, rot1=0.004421281197936293, rot2=0.0029766044781369553, scale1=0.017453292519943295, scale2=0.0)\n",
      "maxdelta on: dist (0) 0.3 --> 0.28456254071696413\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0.28456254, 0.08940175, 0.08892749, 0.00442128, 0.0029766 ,\n",
       "       0.01745329, 0.        ])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Initial refinement of the goniometer model with 5 dof\n",
    "\n",
    "gonioref2d.refine2()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cost function before refinement: 4.4188913962221164e-08\n",
      "[0.28456254 0.08940175 0.08892749 0.00442128 0.0029766  0.01745329\n",
      " 0.        ]\n",
      "     fun: 1.872456502089939e-08\n",
      "     jac: array([-1.85415310e-08, -5.84912461e-08, -3.53206487e-07, -4.17128709e-07,\n",
      "        2.09677793e-07,  2.08230218e-06,  1.22462904e-07])\n",
      " message: 'Optimization terminated successfully.'\n",
      "    nfev: 124\n",
      "     nit: 13\n",
      "    njev: 13\n",
      "  status: 0\n",
      " success: True\n",
      "       x: array([ 2.84547605e-01,  8.86540301e-02,  8.93070277e-02,  5.48717450e-03,\n",
      "        5.54901577e-03,  1.74619285e-02, -2.09889821e-05])\n",
      "Cost function after refinement: 1.872456502089939e-08\n",
      "GonioParam(dist=0.2845476046521533, poni1=0.0886540301310109, poni2=0.08930702773696293, rot1=0.005487174500206645, rot2=0.005549015769013916, scale1=0.017461928498376328, scale2=-2.0988982115318873e-05)\n",
      "maxdelta on: rot2 (4) 0.0029766044781369553 --> 0.005549015769013916\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([ 2.84547605e-01,  8.86540301e-02,  8.93070277e-02,  5.48717450e-03,\n",
       "        5.54901577e-03,  1.74619285e-02, -2.09889821e-05])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove constrains on the refinement:\n",
    "gonioref2d.bounds=None\n",
    "gonioref2d.refine2()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n",
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    }
   ],
   "source": [
    "# Check the calibration on all 3 images\n",
    "\n",
    "fig, ax = subplots(1, 3, figsize=(9, 3) )\n",
    "for idx,lbl in enumerate(gonioref2d.single_geometries):\n",
    "    sg = gonioref2d.single_geometries[lbl]\n",
    "    if sg.control_points.get_labels():\n",
    "        sg.geometry_refinement.set_param(gonioref2d.get_ai(sg.get_position()).param)\n",
    "    jupyter.display(sg=sg, ax=ax[idx])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MultiGeometry integrator with 3 geometries on (0, 63) radial range (2th_deg) and (-180, 180) azimuthal range (deg)\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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.legend.Legend at 0x7fea7c3a8908>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Create a MultiGeometry integrator from the refined geometry:\n",
    "\n",
    "angles = []\n",
    "images = []\n",
    "for sg in gonioref2d.single_geometries.values():\n",
    "    angles.append(sg.get_position())\n",
    "    images.append(sg.image)\n",
    "\n",
    "multigeo = gonioref2d.get_mg(angles)\n",
    "multigeo.radial_range=(0, 63)\n",
    "print(multigeo)\n",
    "# Integrate the whole set of images in a single run:\n",
    "\n",
    "res_mg = multigeo.integrate1d(images, 10000)\n",
    "ax = jupyter.plot1d(res_mg, label=\"multigeo\")\n",
    "for lbl, sg in gonioref2d.single_geometries.items():\n",
    "    ai = gonioref2d.get_ai(sg.get_position())\n",
    "    img = sg.image * ai.dist * ai.dist / ai.pixel1 / ai.pixel2\n",
    "    res = ai.integrate1d(img, 5000, unit=\"2th_deg\", method=\"splitpixel\")\n",
    "    ax.plot(*res, \"--\", label=lbl)\n",
    "ax.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 500000000000.0)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Let's focus on the inner most ring on the image taken at 45°:\n",
    "#ax.set_xlim(21.5, 21.7)\n",
    "ax.set_xlim(29.0, 29.2)\n",
    "ax.set_ylim(0, 5e11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On all three imges, the rings on the outer side of the detector are shifted in compatison with the average signal comming from the other two images. \n",
    "This phenomenon could be related to volumetric absorption of the photon in the thickness of the detector.\n",
    "\n",
    "To be able to investigate this phenomenon further, the goniometer geometry is saved in a JSON file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"content\": \"Goniometer calibration v1.1\",\n",
      "  \"detector\": \"Pilatus 1M\",\n",
      "  \"pixel1\": 0.000172,\n",
      "  \"pixel2\": 0.000172,\n",
      "  \"wavelength\": 6.968e-11,\n",
      "  \"param\": [\n",
      "    0.2845476046521533,\n",
      "    0.0886540301310109,\n",
      "    0.08930702773696293,\n",
      "    0.005487174500206645,\n",
      "    0.005549015769013916,\n",
      "    0.017461928498376328,\n",
      "    -2.0988982115318873e-05\n",
      "  ],\n",
      "  \"param_names\": [\n",
      "    \"dist\",\n",
      "    \"poni1\",\n",
      "    \"poni2\",\n",
      "    \"rot1\",\n",
      "    \"rot2\",\n",
      "    \"scale1\",\n",
      "    \"scale2\"\n",
      "  ],\n",
      "  \"pos_names\": [\n",
      "    \"pos\"\n",
      "  ],\n",
      "  \"trans_function\": {\n",
      "    \"content\": \"GeometryTransformation\",\n",
      "    \"param_names\": [\n",
      "      \"dist\",\n",
      "      \"poni1\",\n",
      "      \"poni2\",\n",
      "      \"rot1\",\n",
      "      \"rot2\",\n",
      "      \"scale1\",\n",
      "      \"scale2\"\n",
      "    ],\n",
      "    \"pos_names\": [\n",
      "      \"pos\"\n",
      "    ],\n",
      "    \"dist_expr\": \"dist\",\n",
      "    \"poni1_expr\": \"poni1\",\n",
      "    \"poni2_expr\": \"poni2\",\n",
      "    \"rot1_expr\": \"scale1 * pos + rot1\",\n",
      "    \"rot2_expr\": \"scale2 * pos + rot2\",\n",
      "    \"rot3_expr\": \"0.0\",\n",
      "    \"constants\": {\n",
      "      \"pi\": 3.141592653589793\n",
      "    }\n",
      "  }\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "gonioref2d.save(\"id28.json\")\n",
    "\n",
    "with open(\"id28.json\") as f:\n",
    "    print(f.read())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Peak profile\n",
    "\n",
    "Let's plot the full-width at half maximum for every peak in the different intergated profiles:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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.legend.Legend at 0x7fea7c361390>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Peak profile\n",
    "\n",
    "from scipy.interpolate import interp1d\n",
    "from scipy.optimize import bisect\n",
    "\n",
    "def calc_fwhm(integrate_result, calibrant):\n",
    "    \"calculate the tth position and FWHM for each peak\"\n",
    "    delta = integrate_result.intensity[1:] - integrate_result.intensity[:-1]\n",
    "    maxima = numpy.where(numpy.logical_and(delta[:-1]>0, delta[1:]<0))[0]\n",
    "    minima = numpy.where(numpy.logical_and(delta[:-1]<0, delta[1:]>0))[0]\n",
    "    maxima += 1\n",
    "    minima += 1\n",
    "    tth = []\n",
    "    FWHM = []\n",
    "    for tth_rad in calibrant.get_2th():\n",
    "        tth_deg = tth_rad*integrate_result.unit.scale\n",
    "        if (tth_deg<=integrate_result.radial[0]) or (tth_deg>=integrate_result.radial[-1]):\n",
    "            continue\n",
    "        idx_theo = abs(integrate_result.radial-tth_deg).argmin()\n",
    "        id0_max = abs(maxima-idx_theo).argmin()\n",
    "        id0_min = abs(minima-idx_theo).argmin()\n",
    "        I_max = integrate_result.intensity[maxima[id0_max]]\n",
    "        I_min = integrate_result.intensity[minima[id0_min]]\n",
    "        tth_maxi = integrate_result.radial[maxima[id0_max]]\n",
    "        I_thres = (I_max + I_min)/2.0\n",
    "        if minima[id0_min]>maxima[id0_max]:\n",
    "            if id0_min == 0:\n",
    "                min_lo = integrate_result.radial[0]\n",
    "            else:\n",
    "                min_lo = integrate_result.radial[minima[id0_min-1]]\n",
    "            min_hi = integrate_result.radial[minima[id0_min]]\n",
    "        else:\n",
    "            if id0_min == len(minima) -1:\n",
    "                min_hi = integrate_result.radial[-1]\n",
    "            else:\n",
    "                min_hi = integrate_result.radial[minima[id0_min+1]]\n",
    "            min_lo = integrate_result.radial[minima[id0_min]]\n",
    "            \n",
    "        f = interp1d(integrate_result.radial, integrate_result.intensity-I_thres)\n",
    "        tth_lo = bisect(f, min_lo, tth_maxi)\n",
    "        tth_hi = bisect(f, tth_maxi, min_hi)\n",
    "        FWHM.append(tth_hi-tth_lo)\n",
    "        tth.append(tth_deg)\n",
    "    return tth, FWHM\n",
    "    \n",
    "fig, ax = subplots()\n",
    "ax.plot(*calc_fwhm(res_mg, calibrant), \"o\", label=\"multi\")\n",
    "for lbl, sg in gonioref2d.single_geometries.items():\n",
    "    ai = gonioref2d.get_ai(sg.get_position())\n",
    "    img = sg.image * ai.dist * ai.dist / ai.pixel1 / ai.pixel2\n",
    "    res = ai.integrate1d(img, 5000, unit=\"2th_deg\", method=\"splitpixel\")\n",
    "    t,w = calc_fwhm(res, calibrant=calibrant)\n",
    "    ax.plot(t, w,\"-o\", label=lbl)\n",
    "ax.set_title(\"Peak shape as function of the angle\")\n",
    "ax.set_xlabel(res_mg.unit.label)\n",
    "ax.legend()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion:\n",
    "Can the FWHM and peak position be corrected using raytracing and deconvolution ?"
   ]
  }
 ],
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