{
 "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": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/users/kieffer/.venv/py37/bin/python3\n"
     ]
    }
   ],
   "source": [
    "import os, sys\n",
    "print(sys.executable)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using pyFAI version: 0.19.0-beta0\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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"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 with 120 reflections 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.tar.bz2__content/gonio_ID28/det130_g0_0001p.cbf angle: 0.0\n",
      "filename /tmp/thick_testdata_kieffer/gonio_ID28.tar.bz2__content/gonio_ID28/det130_g17_0001p.cbf angle: 17.0\n",
      "filename /tmp/thick_testdata_kieffer/gonio_ID28.tar.bz2__content/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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"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": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.DEPRECATION:Function _integrate1d_legacy is deprecated since pyFAI version 0.19.\n",
      "  File \"/users/kieffer/.venv/py37/lib/python3.7/site-packages/pyFAI/multi_geometry.py\", line 149, in integrate1d\n",
      "    mask=mask, flat=flat)\n"
     ]
    },
    {
     "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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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25acnAxBEPDnn3+WOwACxd8CfjYAenp6Qq1Wi/osXbpUFACnTJmC6dOni/qcPn0aNWrUQHZ2NmJjYyEIAsLDw3WfP3jwAAqFAgEBAWX+TUiMAdAwBkAJWEBEJGdyD4CzZs0SbWvatCnWrFmj+2etVgtBEBAUFFRhAXDEiBGYNGmSqE9QUJAoAHbp0gWWlpawtrbWNaVSCUEQoNFoEBQUhJo1ayI/P1+0n44dO2L58uVl/k1IjAHQMAZACVhARCRncr8F7OHhIdqmUqnw1VdfibYJgoCDBw9i586dsLW1FX0WEBBQKQHQxcUFH3zwAa5du6bXcnNzGQArCAOgYQyAErCAiEjO5P4QSHkCYEhICMzMzEQPXixZssRgAJw2bRqGDBki2l9xt4DbtWsn6vPxxx+LAuCYMWPg5uZW4rkYugW8f/9+g78DlYwB0DAGQAlYQEQkZ6YUAFNSUmBtbY05c+YgLi4Oe/bsQZMmTQwGwFWrVqFp06aIjo7G/fv3kZeXV+JDIAsXLkRMTAz27dsHR0dHCIKA1NRUAMClS5egUCjg7u6OiIgIxMbG4tChQ3B3d9cda/jw4WjTpg1Onz6NixcvYtCgQXwIRCIGQMMYACVgARGRnJlSAAQK/+avRYsWUCgUGDJkCLZt22YwAN67dw/9+/eHjY1NuZaB2bx5MwRBEP2uZ8+e1e3L2toa7du3x6pVq3SfFy0DY2dnB4VCgYEDB3IZGIkYAA1jAJSABUREcibnAFiVffrpp3B0dDT2MEweA6BhDIASsICISM4YAF+MjRs34uzZs4iPj8euXbtgZ2eHpUuXGntYJo8B0DAGQAlYQEQkZwyAL8bcuXPRuHFjWFlZoWXLllixYgXfFVwFMAAaxgAoAQuIiOSMAZCqMwZAwxgAJWABEZGcMQBSdcYAaBgDoAQsICKSMwZAqs4YAA1jAJSABUREcsYASNUZA6BhDIASsICISM4YAKk6YwA0jAFQAhYQEckZAyBVZwyAhjEASsACIiI5YwCk6owB0DAGQAlYQEQkZ9UtABb3ejgyXQyAhjEASsACIiI5M+UA6OPjAzs7O73tgYGB6N+/P+rVq6f3zt8i06dPR/PmzVGrVi3Y29tj2LBhiIqKEvVJSkrCG2+8AYVCAQcHByxYsOCFLw4dEBAAZ2dnWFlZQa1W4/Dhw2X+rlarxbJly9CoUSPUqlULbm5ueu8eTklJwZgxY1C7dm3Y2dlh8uTJSE9PF/W5dOkSevfuDSsrKzg6OuLzzz8XfR4ZGYm33noLKpUKgiDovau5IjEAGsYAKAELiIjkjAFQPwDu2rULy5cvx3fffVdiANy6dStOnTqFhIQEXLhwAUOHDsXLL7+M/Px8AEB+fj7UajX69euHiIgIhISEwN7eHosXL5Z2gk8JDw+Hubk51qxZA41Gg48//hgWFha4cuVKmb7/2Wefwc7ODocOHcKlS5cwbNgwNGvWTFQLgwYNQocOHfDXX3/h9OnTaNGiBUaPHq37PC0tDQ0bNsTYsWMRGRkJf39/KBQKbN26Vdfn7NmzWLBgAfz9/dGoUSMGwCqEAVACFhARyZmcA2BGRgbGjx8Pa2trNGrUCOvWrRMFwJycHMyfPx9NmjSBUqlE165dERoaCgAIDQ2FIAii5u3tLdp/QkJCiQHwWZcuXYIgCIiLiwMAhISEoEaNGrhz546uz+bNm2Fra4vc3Nwynd/KlSvh4OAAGxsbTJkyBZ6enujQoYPu81GjRuHNN98Ufadbt254//33S923VqtFo0aNsHbtWt221NRUWFlZwd/fHwCg0WggCALOnTun6/PLL7/AzMwMt27dAgBs2rQJdevWFZ2Tp6cnnJ2diz2uSqUqNgC6urrC3d0d7u7usLW1Rf369fHxxx9Dq9WWei6GMAAaxgAoAQuIiOTMYADMzSi55WWXo29W2fqW08yZM9G0aVMcP34cly9fxpAhQ1C7dm1dAJw6dSp69uyJsLAwxMXFYe3atbCyskJsbCxyc3Oxfv162NraIjk5GcnJyXq3NssaADMyMjB37lw0a9ZMF4SWLVsmCmsAcP36dQiCgL///rvUc/Pz80OtWrWwY8cOxMTEYPny5bC1tRXt8+WXX9YLU15eXmjfvn2p+4+Pjy/23P71r39hzpw5AIDvv/8ederUEX3+5MkTmJub48CBAwCA8ePHY/jw4aI+v/32GwRBwMOHD/WOaygA2tjYwMPDA9HR0fDz84NSqcS2bdtKPRdDGAANYwCUgAVERHJmMAB625bc/P5P3PfTRiX33fGGuO/nzYrvVw7p6emwtLREQECAbltKSgoUCgU8PDyQlJQEc3Nz3ZWqIm5ubrrbsCXdAi5SWgDcuHEjrK2tIQgCnJ2ddVf/AGDatGkYMGCAqH9mZiYEQUBISEip59etWze4u7uLtvXq1UsUAC0sLPDDDz/ojalBgwal7j88PByCIOD27dui7W+//TZGjRoFAFi1ahVatWql910HBwds2rQJANC/f39Mnz5d9PnVq1chCAI0Go3edw0FwNatW4uu+Hl6eqJ169alnoshDICGMQBKwAIiIjmTawC8ePEiBEFAUlKSaHvHjh3h4eGB4OBgCIIAa2trUatZs6Yu4EgNgKmpqYiNjcWpU6cwdOhQdO7cWfc7Sg2AderUwc6dO0Xb5s2bV60D4KRJk0TbDh06hJo1a+r+rvJ5MAAaxgAoAQuIiORMrreASwuAe/fuhbm5OaKjo3Ht2jVRS05OBiA9AIpOKTcXSqVSF8ik3gIuSwCsbreAGQArHwOgBCwgIpIzuT4Ekp6eDgsLC9Et4IcPH0KpVMLDwwMxMTEQBAFhYWEl7mPPnj2wsbEp8fPyBMCcnBwoFAr4+PgA+N9DIHfv3tX12bp1K2xtbZGTk1Pq/rp164bZs2eLtvXu3VvvIZAhQ4aI+vTo0aNcD4GsW7dOty0tLa3Yh0DOnz+v63P06NFiHwLJy8vT9Vm8ePFzPQTSpk0b0bZFixbxFnAFYwCUgAVERHIm1wAIADNmzIBKpcKJEydw5coVDBs2TPcgAQCMHTsWTk5OCAwMxPXr13HmzBmsXr0awcHBAP53G/T48eO4f/8+MjMzART+LWFERAQOHz4MQRCwd+9eRERE6K4cxsfHY/Xq1Th//jySkpIQHh6OoUOHol69errAV7QMzIABA3Dx4kUcOXIEDg4OZV4Gxs/PDwqFAr6+voiNjcXKlStha2uLjh076vqEh4ejZs2aWLduHaKiouDt7V3uZWDq1KmDoKAgXL58GcOHDy92GZhOnTrhzJkz+P3339GyZUvRMjCpqalo2LAhxo8fj8jISOzduxdKpVK0DExubi4iIiIQERGBxo0bY8GCBYiIiMC1a9d0fYoeApk3bx6io6Pxww8/wNraGlu2bCnTuZSEAdAwBkAJWEBEJGdyDoDp6ekYN24clEolGjZsiDVr1oiWgcnLy4OXlxecnJxgYWGBxo0bY+TIkbh8+bJuHzNmzED9+vVFy8D4+PjoLRHz9Oe3bt3C4MGD0aBBA1hYWMDR0RFjxoxBdHS0aHyJiYkYPHgwFAoF7O3tMX/+/HItBL1ixQrY29vDxsYGkydPxpw5c9C9e3dRn4CAALRq1QqWlpZo27btcy0E3bBhQ1hZWcHNzQ0xMTGiPikpKRg9ejRsbGxga2uLSZMmGVwI+qWXXsJnn30m+rzoSuqzzdXVVdfH1dUVs2bNwowZM2Bra4u6detiyZIlXAamgjEASsACIiI5k3MANDX9+vXDuHHjjD2MClFRr/BjADSMAVACFhARyRkDYNWUmZmJL774ApGRkYiKioKXlxcEQcCxY8eMPbQKwQBoHAyAErCAiEjOGACNo02bNnpL1BQ1Pz8/ZGVlwc3NDfXq1YNSqUSnTp0QGBhY5v2HhYWVuH9ra+sKPLPnwwBoHAyAErCAiEjOGACNIzExUW95mqL2+PFjyfvPysoqcf9PP3xR3TEAGsYAKAELiIjkjAGQqjMGQMMYACVgARGRnDEAUnXGAGgYA6AELCAikjMGQKrOGAANYwCUgAVERHLGAEjVGQOgYQyAErCAiEjOGACpOmMANIwBUAIWEBHJGQMgVWcMgIYxAErAAiIiOatuAbCi1pMjeWIANIwBUAIWEBHJmSkHQB8fH9jZ2eltDwwMRP/+/VGvXj0IgoCIiAi9PtOnT0fz5s1Rq1Yt2NvbY9iwYYiKihL1SUpKwhtvvAGFQgEHBwcsWLCgXO8CLk1kZCTeeustqFQqCIKAr776Sq9P0WfPtlmzZpXpGNnZ2Zg1axbq1asHa2trvPXWW7hz546oT1nOMzQ0FJ06dYKlpSVeeeUV+Pj4iD4/deoUhgwZgsaNG0MQBBw8eLB8P4aB8TMAlowBUAIWEBHJGQOgfgDctWsXli9fju+++67EALh161acOnUKCQkJuHDhAoYOHYqXX34Z+fn5AID8/Hyo1Wr069cPERERCAkJgb29PRYvXiztBJ9y9uxZLFiwAP7+/mjUqFGxAfDevXtITk7WtWPHjkEQBISGhpbpGDNmzMDLL7+MEydO4Pz58+jevTt69uyp+7ws53n9+nUolUp8+OGH0Gg0+Pbbb2Fubo4jR47o+oSEhGDp0qU4cOAAA2AlYgCUgAVERHIm5wCYkZGB8ePHw9raGo0aNcK6detEATAnJwfz589HkyZNoFQq0bVrV13wCQ0N1bsq5u3tLdp/QkJCiQHwWZcuXYIgCIiLiwNQGGhq1Kghulq2efNm2NraIjc3t0znt3LlSjg4OMDGxgZTpkyBp6cnOnToUGxflUpVbAB8loeHB1555RVotdpS+6ampsLCwgL79+/XbYuKioIgCPjzzz8BlO08Fy5ciLZt24r2/c4772DgwIHFHrekAKhSqbBixQq8++67UCqVaNKkCTZs2GDwHBgADWMAlIAFRERyZmiCzMzLLLHl5OeUuW/2k+wy9S2vmTNnomnTpjh+/DguX76MIUOGoHbt2roAOHXqVPTs2RNhYWGIi4vD2rVrYWVlhdjYWOTm5mL9+vWwtbXVXR1LT08X7b+sATAjIwNz585Fs2bNdKFn2bJlemHt+vXrEAQBf//9d6nn5ufnh1q1amHHjh2IiYnB8uXLYWtrKykA5ubmon79+li1alWpxweAEydOQBAEPHr0SLS9adOm+PLLLwGU7Tz79Omjd1V2x44dsLW1Lfa4hgJg7dq18Z///AcxMTH45ptvYG5ujl9//bXEc2AANIwBUAIWEBHJmaEJUu2rLrHNPDZT1Pc1v9dK7Dvxl4mivn38+xTbrzzS09NhaWmJgIAA3baUlBQoFAp4eHggKSkJ5ubmuHXrluh7bm5uutuTJd0CLlJaANy4cSOsra0hCAKcnZ11V/8AYNq0aRgwYICof2ZmJgRBQEhISKnn161bN7i7u4u29erVS1IA3LdvX7G/SUn27NkDS0tLve2vvfYaFi5cCKBs59myZUusXr1a1Ofw4cMQBAFZWVl6+zcUAAcNGiTa9s4772Dw4MElngMDoGEMgBKwgIhIzuQaAC9evAhBEJCUlCTa3rFjR3h4eCA4OBiCIMDa2lrUatasiVGjRgGQHgBTU1MRGxuLU6dOYejQoejcubPud5QaAOvUqYOdO3eKts2bN09SABwwYACGDBlS6rGLVMUAuHz5ctG29evXw8nJqcRzYAA0jAFQAhYQEcmZXG8BlxYA9+7dC3Nzc0RHR+PatWuilpycDEB6AHxabm4ulEolfvjhBwDSbwG/6ACYmJiIGjVq4NChQ6Ueu0hVvAXMAPhiMQBKwAIiIjmT60Mg6enpsLCwEN0CfvjwIZRKJTw8PBATEwNBEBAWFlbiPvbs2QMbG5sSPy9PAMzJyYFCodAtb1L0cMTdu3d1fbZu3QpbW1vk5OSUsJf/6datG2bPni3a1rt37+cOgN7e3mjUqFG5lqEpegjkxx9/1G2Ljo4u9iEQQ+e5cOFCqNXiK7yjR49+rodAnr3d++677/IWsAQMgETNL0gAACAASURBVBKwgIhIzuQaAIHCJUpUKhVOnDiBK1euYNiwYbCxsdFdbRo7diycnJwQGBiI69ev48yZM1i9ejWCg4MBAOHh4RAEAcePH8f9+/eRmVl4FTIlJQURERG625R79+5FRESE7sphfHw8Vq9ejfPnzyMpKQnh4eEYOnQo6tWrpwtCRcujDBgwABcvXsSRI0fg4OBQ5mVg/Pz8oFAo4Ovri9jYWKxcuRK2trbo2LGjrk9ubi4iIiIQERGBxo0bY8GCBYiIiMC1a9dE+yooKEDTpk3h6en5XL9x06ZN8dtvv+H8+fPo0aMHevToofu8LOdZtAzMRx99hKioKGzcuFFvGZj09HTduQiCgC+//BIRERGiK7wqlQq2trb4/PPPERMTgw0bNujt51kMgIYxAErAAiIiOZNzAExPT8e4ceOgVCrRsGFDrFmzRrQMTF5eHry8vODk5AQLCws0btwYI0eOxOXLl3X7mDFjBurXry9aBsbHx6fYxZOLPr916xYGDx6MBg0awMLCAo6OjhgzZgyio6NF40tMTMTgwYOhUChgb2+P+fPnl+sK3IoVK2Bvbw8bGxtMnjwZc+bMQffu3XWfF12hfLa5urqK9nP06FEIgoCYmJhy/LqFihaCrlu3LpRKJUaOHKkLwuU5z9DQUHTs2BGWlpZo3ry53kLQxS3LIwgCJkyYoOtTdAv47bffhlKpRKNGjfD111+XOn4GwJIxAErAAiIiOZNzADQ1/fr1w7hx44w9DKMp61qHT2MANIwBUAIWEBHJGQNg1ZSZmYkvvvgCkZGRiIqKgpeXFwRBwLFjx4w9NKNhAHzxGAAlYAERkZwxABpHmzZt9JaoKWp+fn7IysqCm5sb6tWrB6VSiU6dOiEwMPCFjsHPz6/EMbRp0+aFHutFYAB88RgAJWABEZGcMQAaR2Jiot7yNEXt8ePHlTKGx48flziGxMTEShlDRWMANIwB8L/+85//QBCEMr9IHGABEZG8MQBSdcYAaBgDIICzZ8/CyckJ7du3ZwAkIpPBAEjVGQOgYSYfANPT09GyZUscO3ZMtIRAWbCAiEjOGACpOmMANMzkA+B7772HuXPnAgADIBGZFAZAqs4YAA0z6QDo7+8PtVqtK47SAmBOTg7S0tJ07caNGyZfQEQkXwyAVJ0xABpmsgHwn3/+QYMGDXDp0iXdttICoLe3d7GrlZtyARGRfDEAUnXGAGiYyQbAgwcPQhAEmJub65ogCDAzM4O5uTny8/P1vsMrgERUnVS3AFjeP+Oh6o0B0DCTDYCPHz/GlStXRK1Lly4YN24crly5UqZ9sICISM5MOQD6+PjAzs5Ob3tgYCD69++PevXqQRAERERE6PWZPn06mjdvjlq1asHe3h7Dhg1DVFSUqE9SUhLeeOMNKBQKODg4YMGCBeV6F3B5+Pv7QxAEDB8+XLR9woQJenesBg4cWOb9pqSkYMyYMahduzbs7OwwefJkpKeni/pcunQJvXv3hpWVFRwdHfH555/r7ScgIADOzs6wsrKCWq3G4cOHRZ+X5Td/HgyAhplsACwOHwIhIlPCAKgfAHft2oXly5fju+++KzGMbN26FadOnUJCQgIuXLiAoUOH4uWXX9bdOcrPz4darUa/fv0QERGBkJAQ2NvbY/HixdJOsBgJCQl46aWX0KdPn2ID4KBBg5CcnKxrDx8+LPO+Bw0ahA4dOuCvv/7C6dOn0aJFC4wePVr3eVpaGho2bIixY8ciMjIS/v7+UCgU2Lp1q65PeHg4zM3NsWbNGmg0Gnz88cewsLAQXWgpy2/+PBgADWMAfAoDIBGZEjkHwIyMDIwfPx7W1tZo1KgR1q1bJ/p3eE5ODubPn48mTZpAqVSia9euCA0NBQCEhobqXRnz9vYW7T8hIaHMYeTSpUsQBAFxcXEAgJCQENSoUQN37tzR9dm8eTNsbW2Rm5tbpvNbuXIlHBwcYGNjgylTpsDT0xMdOnQQ9cnPz0fPnj2xfft2TJgwodgA+Oy2stJoNBAEAefOndNt++WXX2BmZoZbt24BADZt2oS6deuKzsnT0xPOzs66fx41ahTefPNN0b67deuG999/X++Yhn5zQRCwadMmDBo0CLVq1UKzZs2wf/9+g+fAAGgYA6AELCAikjNDE2RBZmbJLSen7H2f2XdJ/cpr5syZaNq0KY4fP47Lly9jyJAhqF27ti4ATp06FT179kRYWBji4uKwdu1aWFlZITY2Frm5uVi/fj1sbW11V8aevbVZ1gCYkZGBuXPnolmzZrogtGzZMr2wdv36dQiCgL///rvUc/Pz80OtWrWwY8cOxMTEYPny5bC1tdXbp5eXF0aMGAGg+LA3YcIE2NnZwcHBAa1atcKMGTPw4MGDUo8PAN9//z3q1Kkj2vbkyROYm5vjwIEDAIDx48frHfO3336DIAi6K40vv/yy3jt8vby80L59e71jlhYA69evj++++w4xMTH4+OOPYW5uDo1GU+I5MAAaxgAoAQuIiOTM0ASpcXYpsSVNny7qG9WxU4l9E8eNF/WN6d6j2H7lkZ6eDktLSwQEBOi2paSkQKFQwMPDA0lJSTA3N9ddqSri5uamuw1b0i3gIqUFwI0bN8La2hqCIMDZ2Vl39Q8Apk2bhgEDBoj6Z2ZmQhAEhISElHp+3bp1g7u7u2hbr169RAHw9OnTeOmll3D//n0AxQdAf39/BAUF4fLlyzh48CBat26N1157rdiHHJ+1atUqtGrVSm+7g4MDNm3aBADo378/pj9TC1evXoUgCLpgZmFhgR9++EHUZ+PGjWjQoIHevksLgDNmzBBt69atG2bOnFniOTAAGsYAKAELiIjkTK4B8OLFixAEAUlJSaLtHTt2hIeHB4KDgyEIAqytrUWtZs2aGDVqFADpATA1NRWxsbE4deoUhg4dis6dO+t+R6kBsE6dOti5c6do27x583QB8PHjx3BychLtqyy3e+Pj4yEIAo4fP17qGKpiAHz2N5k7dy769u1b4jkwABrGACgBC4iI5Eyut4BLC4B79+6Fubk5oqOjce3aNVFLTk4GID0APi03NxdKpVIXdKTeAi4tAEZEROgtY2ZmZqZbxuzpq5HPsre3x5YtW0odQ1W8BcwA+GIxAErAAiIiOZPrQyDp6emwsLAQ3QJ++PAhlEolPDw8EBMTA0EQEBYWVuI+9uzZAxsbmxI/L08AzMnJgUKhgI+PD4D/PQRy9+5dXZ+tW7fC1tYWOc+E5+J069YNs2fPFm3r3bu3LgBmZ2frLWM2fPhwvP7667hy5UqJD5rcuHEDZmZmCAoKKnUMRQ+BnD9/Xrft6NGjxT4EkpeXp+uzePFivYdAhgwZItp3jx49nushkGdv93bv3p23gCVgAJSABUREcibXAAgAM2bMgEqlwokTJ3DlyhUMGzYMNjY2uodAxo4dCycnJwQGBuL69es4c+YMVq9ejeDgYACFy5MU3Q69f/8+Mv97FTIlJQURERE4fPgwBEHA3r17ERERobtyGB8fj9WrV+P8+fNISkpCeHg4hg4dinr16ukCX9EyMAMGDMDFixdx5MgRODg4lHkZGD8/PygUCvj6+iI2NhYrV66Era0tOnbsWOJ3nr0FnJ6ejgULFuDPP/9EQkICjh8/js6dO6Nly5ZlCqFA4TIwnTp1wpkzZ/D777+jZcuWomVgUlNT0bBhQ4wfPx6RkZHYu3cvlEql3jIwNWvWxLp16xAVFQVvb2+9ZWBK+82BwgBob2+P77//HjExMfDy8kKNGjVw9erVEsfPAGgYA6AELCAikjM5B8D09HSMGzcOSqUSDRs2xJo1a0TLwOTl5cHLywtOTk6wsLBA48aNMXLkSFy+fFm3jxkzZqB+/fqiZWB8fHyKfeVn0ee3bt3C4MGD0aBBA1hYWMDR0RFjxoxBdHS0aHyJiYkYPHgwFAoF7O3tMX/+/HItBL1ixQrY29vDxsYGkydPxpw5c9C9e/cS+z8bALOysjBgwAA4ODjAwsICKpUK06ZNEy1NU5qUlBSMHj0aNjY2sLW1xaRJkwwuBP3SSy/hs88+09tPQEAAWrVqBUtLS7Rt21ZvIejSfnOgMABu3LgR/fv3h5WVFZycnLBv3z6D42cANIwBUAIWEBHJmZwDoKnp168fxo0bZ+xhGI0gCDh48GC5vsMAaBgDoAQsICKSMwbAqikzMxNffPEFIiMjERUVBS8vLwiCgGPHjhl7aEbDAPjiMQBKwAIiIjljADSONm3a6C1RU9T8/PyQlZUFNzc31KtXD0qlEp06dUJgYOALHcOqVatKHMOgQYNe6LFeBAbAF48BUAIWEBHJGQOgcSQmJuotT1PUHj9+XCljSElJKXEMN2/erJQxVDQGQMMYACVgARGRnDEAUnXGAGgYA6AELCAikjMGQKrOGAANYwCUgAVERHJWNEFmZWUZeyhEL1xWVhYDoAEMgBKwgIhIzvLz86HRaPDgwQNjD4XohXvw4AE0Gg3y8/P1PuP8zQAoCQuIiOTu9u3buhCYlZWF7OxsNjZZt6ysLF34u337drF1z/mbAVASFhARyZ1Wq9WFQDa26tRu374NrVZbbN1z/mYAlIQFRETVRX5+vtGv3LCxvahW3G3fp3H+ZgCUhAVEREQkP5y/GQAlYQERERHJD+dvBkBJWEBERETyw/mbAVASFhAREZH8cP5mAJSEBURERCQ/nL8ZACVhAREREckP528GQElYQERERPLD+ZsBUBIWEBERkfxw/mYAlIQFREREJD+cvxkAJWEBERERyQ/nbwZASVhARERE8sP5mwFQEhYQERGR/HD+ZgCUhAVEREQkP5y/GQAlYQERERHJD+dvBkBJWEBERETyw/mbAVASFhAREZH8cP5mAJSEBURERCQ/nL8ZACVhAREREckP528GQElYQERERPLD+ZsBUBIWEBERkfxw/mYAlIQFREREJD+cvxkAJWEBERERyQ/nbwZASVhARERE8sP5mwFQEhYQERGR/HD+ZgCUhAVEREQkP5y/GQAlYQERERHJD+dvBkBJWEBERETyw/mbAVASFhAREZH8cP5mAJSEBURERCQ/nL8ZACVhAREREckP528GQElYQERERPLD+ZsBUBIWEBERkfxw/mYAlIQFREREJD+cvxkAJWEBERERyQ/nbwZASVhARERE8sP5mwFQEhYQERGR/HD+ZgCUhAVEREQkP5y/GQAlYQERERHJD+dvBkBJWEBERETyw/mbAVASFhAREZH8cP5mAJSEBURERCQ/nL8ZACVhAREREckP528GQElYQERERPLD+ZsBUBIWEBERkfxw/mYAlIQFREREJD+cvxkAJWEBERERyQ/nbxMPgJs2bUK7du1Qu3Zt1K5dG927d0dISEiZv88CIiIikh/O3yYeAH/66SccPnwYsbGxiImJwZIlS2BhYYHIyMgyfZ8FREREJD+cv008ABanbt262L59e5n6soCIiIjkh/M3A6BOfn4+/P39YWlpiatXrxbbJycnB2lpabp248YNky8gIiIiuWEAZADE5cuXYW1tDXNzc9jZ2eHw4cMl9vX29oYgCHrNlAuIiIhIbhgAGQCRm5uLa9eu4fz581i0aBHs7e15BZCIiKgaYwBkANTj5uaG6dOnl6kvC4iIiEh+OH8zAOr597//jQkTJpSpLwuIiIhIfjh/m3gAXLRoEU6dOoWEhARcvnwZixYtgpmZGX799dcyfZ8FREREJD+cv008AE6ePBkqlQqWlpZwcHCAm5tbmcMfwAIiIiKSI87fJh4ApWIBERERyQ/nbwZASVhARERE8sP5mwFQEhYQERGR/HD+ZgCUhAVEREQkP5y/GQAlYQERERHJD+dvmQbA9957D6dOnTL2MFhAREREMsT5W6YBcPjw4bCwsECLFi2watUq3Lx50yjjYAERERHJD+dvmQZAALh37x6++OILtG/fHjVr1sSgQYOwf/9+5OXlVdoYWEBERETyw/lbxgHwaRcuXMDs2bNRq1Yt2NvbY+7cuYiNja3w47KAiIiI5IfzdzUIgLdv38Znn30GZ2dnWFtb47333oObmxtq1qyJL7/8skKPzQIiIiKSH87fMg2AeXl5+PHHH/Hmm2/CwsICr776KjZv3iz6P/LAgQOoU6dOhY6DBURERCQ/nL9lGgDr16+PunXrYtasWYiIiCi2z6NHj+Dk5FSh42ABERERyQ/nb5kGwF27diE7O9vYw2ABERERyRDnb5kGwEmTJuHx48d62zMyMjBp0qRKGwcLiIiISH44f8s0ANaoUQN3797V237//n2Ym5tX2jhYQERERPLD+VtmATAtLQ2pqakwMzNDXFwc0tLSdO3hw4fYuXMnGjduXKnjMfUCIiIikhvO3zILgGZmZqhRo0aJzdzcHJ9++mmljYcFREREJD+cv2UWAE+ePInQ0FCYmZnhwIEDOHnypK798ccfuHXrVqWOhwVEREQkP5y/ZRYAiyQmJkKr1Rp7GCwgIiIiGeL8LaMAeOnSJRQUFOj+t6FWWVhARERE8sP5W0YB0MzMTPfkb9HfApqZmem1GjVqVNqYWEBERETyw/lbRgHw6du+iYmJBltlYQERERHJD+dvGQXAqogFREREJD+cv2UaAH19fREcHKz7548++gh2dnbo0aMHrwASERGRQZy/ZRoAW7VqhRMnTgAA/vjjDygUCmzduhVDhw7FyJEjK20cLCAiIiL54fwt0wCoUCiQlJQEAFi4cCHGjx8PAIiMjIS9vX2ljYMFREREJD+cv2UaAB0cHPD3338DADp27Ihdu3YBAOLi4mBtbV1p42ABERERyQ/nb5kGwDFjxqBz586YMmUKlEolHjx4AAAICgpC27ZtK20cLCAiMgVarRZ3Mu4AAFIz86rEQvxEUnD+lmkAfPToEdzd3TFs2DD88ssvuu1eXl58FzAR0Qt24c4FtN/ZHkP2Tkcz7y0Y8s1pHNfcYRAk2eL8LdMAWFWwgIjIFGz8eyPUvmpdc9k4DM1XfIE3vwljECRZ4vwt4wD46NEjHD16FLt378bOnTt1rejvASsDC4iIqqsTSSeQlpuGvPwCzN0bgWZe2+D89Xi09+2gC4Ktt7jhldWfYMi3J3EiikGQ5IPzt0wD4E8//YTatWvDzMwMdnZ2qFOnjq7VrVu30sbBAiKi6ui3pN/Qfmd7DD84AhN9T0HlGYzeH/jilwOhuH0/AWvPrkVXv25Q+6rR9jtXqDx/gsozGEO/Pc0gSLLA+VumAbBly5bw8PBAZmamUcfBAiKi6ubivYvosrsL1L5q9Pl+JlSeP2Po+xtxtU1baJxdcGvhQgBAWm4adkRsw9FvlmLzpoPovPAAVIsOoeW6OXhjQxB+i7rLIEhVFudvmQZApVKJ+Ph4Yw+DBURE1UpiWiL6+PeB2leNrtvfhcozCJ0XHcQV19ehcXZBVLv2uL91m65/Tnw8NM4uuna2S2fsG9AaX45ug7lTB2DCivUMglQlcf6WaQAcOXIk9u3bZ+xhsICIqNp4kPUAgwMHQ+2rRqftb0C1KBDtPzmKK/M8oXF2Qey//438x4+hffJE953s6GgkTZqE2H+5ioJgUftkShu4bBiBfpu2IjTsMm4tWYqM8HAjniVRIc7fMg2A27dvR9OmTeHt7Y0ff/wRQUFBolZZWEBEVB1k5mXi3Z/fhdpXjfbfu8JpiT+6fHoMUYGHdWEu48+/DO4j//FjZF28iEeBB3B1hSdC/t+/MG7Z/54cHrewNzTOLrjaug0y/7uQP5GxcP6WaQA0MzMrsdWoUaPSxsECIqLqICktCX33ukH9fTc4LfNBr89OIOHaDcT07AWNswvu/Oez59rvzfSb8P59FTr6vop+n76BnX2GQ+Psgst93VCQkfGCz4Ko7Dh/yzQAVhUsICKqDq7cTEWnVQFo5r0Fr68Lxe3ULOTduYvECRMRP2QICnJyJO0/NScVEbfj8OGO0zjVsRs0zi5IXLrsBY2eqPw4f1eDAJidnW20Y7OAiEjOkjOScTYhBWqvI1B5BuPNb8LwIP1/YU9bUIAn9+69sONl5eZj6rz1utvK6SdPvrB9E5UH52+ZBsD8/HysWLECTZo0gbm5ue6J4I8//hjbt2+vtHGwgIhIrg5eO4iOOzvB5bPVUHkG4+3NfyAtOw/a3NwKPe6oQxOxdlxraJxdENmtJ548fFihxyMqDudvmQbA5cuXo3nz5vDz84NCodAFwL1796J79+6VNg4WEBHJUfjNcN0bPVqum433vj+DrNx8aAsKkDj+Pdz29kZBBa2zev7OeXT6ri2O9nLB6Vdfw6OLlyvkOESGcP6WaQB85ZVXcPz4cQCAjY2NLgBGRUWhTp06lTYOFhARyY3mgQadd70Gta8azl+Pw8zd55D7pAAA8OD7HYXr/XXqjNykpAobg+eppej3ZVu8uv51eAVdqrDjEJWE87dMA2CtWrWQmJgIQBwAr169Cmtr60obBwuIiOTkZvpNdNtduNCzy8YRWBBwAfkFhYs0Z8fEIErdDhpnFzzcW7HrrD7Mfohufj0Lr0B+7olzCSlcLJoqFedvmQbAzp07Y/fu3QDEAXD58uXo3bt3pY2DBUREcpGak4qB+9+E2leN1lv6YVnQOV3oKsjNRfzwEdA4u+Cf6e9XShgLjA0sfJfw952weNpiJEx/H9qCggo/LhHA+RuQaQA8dOgQ7Ozs8Nlnn0GpVGLt2rWYOnUqLC0t8euvv1baOFhARCQX2y5tg9pXjTbf9cKkXb+KQt7ddV9A4+yCmG7dX+hTv4YUaAsw+uex6PNtW1xo2wYaZxc8+H5HpRybiPO3TAMgAISFhaFfv35wcHCAQqFAr169cPTo0UodAwuIiORCczsVLdd6oJnXdkQnP9Ztzzx/HprWhQEsrZL/HRrzMAYTfvLA+6M/KnxLiLodsqNjKnUMZJo4f8s4AFYFLCAiqsq0Wi0KtIW3Vd33XIDKMxgz/c6L+qSfPImYrt1wa6GnMYYIAJi95wJ2uL4FjbML4oYOQ0EFL0VDxPlbpgGwWbNmePDggd72R48eoVmzZpU2DhYQEVVlvpG++DD0Q1y9fR9Oi4Kh8gzG1Vv6/77Ku3sX+Y8fF7OHyvEgPQeui3/En+06QePsgrvr1hltLGQaOH/LNACamZnh7t27etvv3LkDS0vLShsHC4iIqqrQf0Kh9lVD7avGO34boPIMxrSd53SfV6UHLnLyc/DOwfcxcbG68C0hLq2Ree5c6V8kek6cv2UWAIOCghAUFAQzMzPs2rVL989BQUE4cOAA3N3d0apVq0obDwuIiKoirVaLEYdGQO2rxke/eaHZop+h8gzGlZupAIAnKSmIHzIUj48dM/JIC2m1Wrgfd4faV41vR3ZFpEtr3OMDIVSBOH/LLACamZnBzMwMNWrU0P3vomZpaYlWrVrh559/rrTxsICIqCr6/ebvUPuq0dWvK2bv/R0qz2BM8T0LoDBs3Zg9GxpnF8QPGQLtkydGHm2hm+k38eruV/Ha1rZ40+MDbDkZZ+whUTXG+VtmAbCIk5MT7t+/b+xhsICIqEqaenQq1L5qLDn1KZovPgyVZzAu3XgEAHh04GDhbVZ1O2RfvWrkkYptv7y9cKma7d3QatmPiL+XbuwhUTXF+VumAbCqYAERUVUTlRIFta8aHXZ2gPu+Y1B5BmPijjMAgNwbNxHd+VVonF1wf8tWI49UX15+HoYfHA61rxqtvpqC91cFImnqNDypAv/BT9UL528ZB8Djx49j8eLFmDJlCiZNmiRqlYUFRERVzdLTS6H2VcP913l45b9X/y4kPYS2oACJ48ZD4+yChHdHQ5ufb+yhFutc8rnCh1d82iKwZ9/Ct5O8P4OviqMXivO3TAPgJ598gho1aqBr164YPnw4RowYIWqVhQVERFVNak4qtl3ahpkBQVB5BmPc9r8AAA++3wGNswuiOnVGblKSkUdp2NLTS9HT73X8e54XLrVuW/h+4oAAYw+LqhHO3zINgI0aNcKuXbuMPQwWEBFVSTceZqLFksKrf+cTUwAAyStWFgapvfuMPLrSpeWmIT0nA29v+QPz3lrw3+DaqcoHV5IPzt8yDYD16tVDXJzxnxBjARFRVZFf8L9buksOXIbKMxhjvvtT1Cfz779ldSv1+v0MOC8Jxt6eb1T5W9ckL5y/ZRoAFy5ciBUrVhh7GCwgIqoyfCN9Me7wOATHntRd/fsrXv+NSXJSoC3ABz9vRK8VY3C+bYcq+/AKyQ/nb5kGwDlz5qBOnTr417/+hdmzZ2PevHmiVllYQERUFeQV5KHf/n5Q+6rx3r5voPIMxqgtf0BbUIB7X3+NnOvXjT3E5xKfGo8OOztA7avG1InvF14FHD2GVwFJMs7fMg2Affv2NdgqCwuIiKqC4PhgqH3V6OP/L7T8uPDhj/C4+3gcGgqNswuiX+uKgpwcYw/zuaw9u7ZwbcCtffDeuE9w6FyisYdE1QDnb5kGwKqCBURExqbVavH2T28XvvN330qoPIPxf5vDodVqkfjeBGicXXDn8zXGHuZzy8zLhFuAG9S+arRc9wFe+/QYcp7wCiBJw/lbZgFw5MiRpba33nqr0sbDAiIiY/vr9l9Q+6rx6u5X0WrZfqg8gxEWew9ZVyIL3/jRVo2827eNPUxJjice/+/agB3QbNkOBPx+DY9+DIS2oMDYQyOZ4vwtswA4ceLEMrXKwgIiImObcWwG1L5qjPCfD5VnMEZu/B1arRY3P5wPjbMLbn70kbGHKJlWq8Ws47Og9lWj9Yah+K2rKzTOLkg7ctTYQyOZ4vwtswBY1bCAiMiY4h7FQe2rRjvfdnD+ZDdUnsEIjb6LvJs3oWlTuIBytkZj7GG+EDce38Cru7tA7dMOy956DxpnF1wf+ZaslrWhqoPzt4kHwNWrV6NLly6wsbGBg4MDhg8fjujo6DJ/nwVERMb0pOAJfkn4Be8EeEHlGYxhzKas5wAAIABJREFU356GVqvFndX/gcbZBYmVeEekMvwU9xMW/hSMdnP34WLb9tA4uyA97LSxh0UyxPnbxAPgwIED4ePjg8jISFy8eBFvvPEGmjZtioyMjDJ9nwVERMaWkpGL1st+gcozGCei7gAA7m/Ziuiu3ZAeFmbk0b14dx9no+WSEKx8Y3rhsjBjxxp7SCRDnL9NPAA+6969exAEAadOnSpTfxYQERlL0a3Pz3+JgsozGG9+Eya6HVqQmVltb48uCryEVz/cjMtt1NA4uyDz3DljD4lkhvM3A6DItWvXIAgCrly5UuznOTk5SEtL07UbN26YfAERUeXLzMvEiEMjsOHCNrRZ9jNUnsE4Gpls7GFVmjV/bkJbn/b4avjr0Di7IGnqNGMPiWSGAZABUKegoABvvvkmevXqVWIfb29vCIKg10y5gIio8vlp/KD2VaPn7v5Qef6EQesLr/5l/PEH0sPCqu2VvyIn/zkJta8a//6iMyJbt8U/7u4oyM019rBIRhgAGQB1ZsyYAZVKhRs3bpTYh1cAicjYnhQ8wcAfBxaui7e28OGPX67chlarRfzwEdA4u+DhDz8Ye5gVqkBbALd9hb9BD6/5SE7NNvaQSGYYABkAAQDu7u5wdHTE9XK+L5MFRESV7UjCEah91eiyqydUiw5gwJenUFCgRUZ4ODTOLojq1Bn5jx4Ze5gVbo9mz39fEdcXq4IjjT0ckhnO3yYeALVaLdzd3dGkSRPExsaW+/ssICKqTFqtFu/+/G7h1b+v5kHlGYzgS4Vv+UiaMhUaZxckf7rKyKOsHBl5GeiyuyvUvmq0/c9XeBCXiNRDh4w9LJIJzt8mHgBnzpwJOzs7nDx5EsnJybqWlZVVpu+zgIioMp2/cx5qXzU6+HaG05K96PfFSRQUaJEdHV342rfWbZBr4M9YqpvPz6yB2leNPquHILJ1W2jatEXujZvGHhbJAOdvEw+AxT3QIQgCfHx8yvR9FhARVabZJ2YXXv37dipUnsE4FFEYdm55LoLG2QU35s418ggr143HN9DOtz3a7uiMfX2HFF4BXb7c2MMiGeD8beIBUCoWEBFVpqsPrmJkwCw4LfPBv9eFIr9Ai7w7d6BRt4PG2QVZly8be4iV7pfrv6Lbf37CkMnrC/8Gsl175N29a+xhURXH+ZsBUBIWEBFVptwnBejy6TGoPIMReKHwVm/W5SuIHzLUpN+I8V1YPFQLf8bP/3oDGmcX3FmzxthDoiqO8zcDoCQsICKqTAf/vgmVZzBe+/QYcp8U6LZrtVo8efjQiCMzrvScJ1B7H8Hbk1ZA4+yCaBN5EpqeH+dvBkBJWEBEVBm2XdoG73BvDN4YCJVnML45Xv5VC6qzm+k30XfPSLTZ1hPHe/WDxtkF977dYOxhURXG+ZsBUBIWEBFVtKwnWejt3xtqXzVe+XQ1Wi4Jwf30HGifPMHDfftQkJlp7CEaXW5+Lvr4/wtqXzUmTJ2Gqx074f7mLcYeFlVhnL8ZACVhARFRRdsXva9w4Wfff0PlGYT5ARcBAGmHD0Pj7IK4QYOr/avfymLTxU2FawJuGIyZm0ONPRyq4jh/MwBKwgIiooqUX5CPNw+8CbWvGq0+XwKVZzCu3EyFVqvF9f97m7c6n3I/6z467uoEta8azbw3IebOY2MPiaowzt8MgJKwgIioIh1POg61rxqdd3aHalEg3t78BwAg8+zZwiVP2nfAk5QUI4+y6lh6einUvmo4fz0W8/dFIOOvM3j822/GHhZVQZy/GQAlYQERUUUaHzIeal812n89FyrPYBy+XPjat39mzITG2QW3vbyNO8AqJiolqvA2sE97TJq4GBpnF1x73Q3avDxjD42qGM7fDICSsICIqKJcvHex8LVvOzvCaekP6LH6OJ7kFyAnPr7wtW8urZETf93Yw6xyJv4ysTAErvbA3692g8bZBY8OHjT2sKiK4fzNACgJC4iIKsrD7IfY8PcG9NhaePVvU2gcAOD2x8ugcXbBP7PcjTzCqun8nfP4KjwQKs+fsOTtBYUPygx+A9qCgtK/TCaD8zcDoCQsICKqSGcTUqDyDIbzxyF4mJELrVaLm/M+hMalNTLPnzf28KosrVaLAV+eQusPf8Sljq9C4+yCtCNHjT0sqkI4fzMASsICIqKKNNPvPFSewVgUeEm0PffGTS79Uoofz9+A6v+3d59hUZxdA8fXN48aNYmaxCt58iRuYjS7yGAHu8Se2FBTjKZg7yUmKvYullhiLyisir0j9t67WFcE7FHs0vvu//2wcSMKBF1kgD2/65oPzM4O52YOnMPszD0e6/H8thdGnZ4rzZrJz0xYSf2WBtAmkkBCiIz2JPYJnbZ3Ys2lbRQb4I/Ww59LofI35mX5nF+I04IqlBnoyXmn0hh1eiL371c7LJFFSP2WBtAmkkBCiIw29+xcFINCdd/GaD020nLeEQCiT54k/tYtlaPLPjyPeqIYFPQzvmH6N90IrlefyL171Q5LZBFSv6UBtIkkkBAiIyUkJVBzRU0Ug4LTRE+0Hv5suxCKOSmJ4Hr1MDqUlCYmna6HX8fJ4GSZF3DAXLac+UvtkEQWIvVbGkCbSAIJITLS5qubUQwKFRdXR+uxnmrjd5FkMhO+fTtGnZ5Al4qYoqLUDjPb6L6zu+UpKpM74DbjoFwDKKykfksDaBNJICFERvpp008oBoXKs/qh9fDHa/8VAK61bIVRp+fe5CkqR5i9HL1z1DInoHdZtANWcizwDo+XLSf20iW1QxMqk/otDaBNJIGEEBnl4sOLlqd+LCzNp4OW4jBkC2ExCUSfPm157JviRMK9e2qHma2YzWaarm+KYlAoPr4fS1p2w6jTc6tHT7VDEyqT+i0NoE0kgYQQGeXpc2xdDe3QevgzeN15AG716IlRp+f2gIEqR5g9rQlag2JQKOlVjepd5v3zFJWQELVDEyqS+i0NoE0kgYQQGWXTlU00XfctxYbPROvhT/C9SOJv3MCod8Co0xMXFKR2iNlSbGIso46M4qdFa9B6+LOl2c+Whrqfh9qhCRVJ/ZYG0CaSQEKIjDTS7wJaj438vOAYABE7dhBYvgI32ndQObLs78iVh2g9/GnUba7lLGBJRxJCQ9UOS6hE6rc0gDaRBBJCZJSouESUYVvReviz+9I/1/olRUYSf0umMLGV2Wym1sQ9aD02cqzxtxh1eh7On692WEIlUr+lAbSJJJAQwlaHbh9i8cXFeB24gNbDny//2IPJJNOVZLQb4TdosaYXX0xpy/AOoyyPh2vipnZYQiVSv6UBtIkkkBDCVq23tEYxKLjM+h2thz8+B69iiosj6shRmbcuA527f84yJYxPaZQ+3lwsVZobbdrKvIp2Suq3NIA2kQQSQtgi8FGgZeoXQyk+HbQEx6FbiYhN4PHKlRh1em527aZ2iDnK03kWS/zRi36GQ2qHI1Qk9VsaQJtIAgkhbDHs0DDLc3993NF6+DPc7wJmk4mQrxtYrlHz9lE7xBxly7Utlilh5lekxOANPI6KVzskoRKp39IA2kQSSAjxqsLiwqiwuAKKQaHY8Gl82t+faw+iiNi92/LYt/IVSIqMVDvMHCXRlEidlXVQDAqfew7Ha/8VEu7eJeEvucnG3kj9lgbQJpJAQohX5XPeB8WgUHVxA7QeG2nrcxyA6z9Z5qm7O2GCyhHmTAvOL0AxKDjMqcuonwdg1DtwZ/BgtcMSmUzqtzSANpEEEkK8iiRTEvVX17d8HDlhOFoPf/YH3Sfm3HnLHHWOisxR95qExYVR/u8zr25d+1nOtlZwxhQXp3ZoIhNJ/ZYG0CaSQEKIV/Ek9gm99/TGeVFVtP3XUnvSXsxmM3/1/u3vp1T0UzvEHG366el8u2wEnw1YxjHnKhh1esK3bVM7LJGJpH5LA2gTSSAhxKsymcxUn7AFrYc/i49cxxQfz5VGjTDq9MReuqR2eDnexdvhaD38Gdm4C0adnlvdu6sdkshEUr+lAbSJJJAQ4lXtNN5F6+GP07CtRMcnAmA2mYg+dUrlyOxHs5kHce3shVGn55LiRNKTJ2qHJDKJ1G9pAG0iCSSEeFnbr2/nevh1fpp/FK2HP2M2GdUOyS6ZzCZG7V6OfsY3bKtUE6NOz+PlK9QOS2QSqd/SANpEEkgI8TIi4yNx8XVBMSh8NnQun/X35+ajaGKNRkyxsWqHZ1dMZhON1jZGMSj0+7EZRp2e661bqx2WyCRSv6UBtIkkkBDiZfgafVEMCpUW1UfrsZGOi05gjo8nqFp1LleuQmxgoNoh2pU1QWtQDArVJldiYu/xJEVEqB2SyCRSv6UBtIkkkBAivUxmEw3XNrTMQTdhCFoPfw6HPOTJ2nUYdXqCqtfAHC9PpshM8UnxVF/mimJQKO45gluPo9UOSWQSqd/SANpEEkgIkV4H/jqAYlAot9AFbf811J+yD5PJxJVGjS2PffPyUjtEu+R1zuvviaFr88dWufvaXkj9lgbQJpJAQoj06rqzK4pBocyMrmg9/Fl54iaR+w9YJiIuW44k+TuiivD4cMotckYxKPRp25Erzb8h1ig35uR0Ur+lAbSJJJAQIj1uht/EyeCEYlD4dLCBCqN3EJeYxI02bSyPffMcq3aIdm3s0fEoBoX5DStYjsd4eQxfTif1WxpAm0gCCSHSY8/NPVRZWoUKXi3QevgzfVcQsUaj5bFvJR1J+OsvtUO0a6FRoXy5pBk/duz0z/WYSUlqhyVeI6nf0gDaRBJICJFeey7f4tNBvugGb+ZxVDwP5y/AqNPz12+/qx2aAG4+iqZ43/UcU8pi1OmJOnJE7ZDEayT1WxpAm0gCCSHSq43PcbQe/gxed966Li4oiPhr19QLSiTTxuc4E+u3tjyPecBAtcMRr5HUb2kAbSIJJIRIi9ls5tTdUwTdtTx39tP+/lx7EKV2WCIV/uev0KR3O8uj4cpXkMm5czCp39IA2kQSSAiRlqN3jlomGl7khtZjIx0WniApMoqEO3fUDk2k4Mjtozj5OLLX2QGjTk/4li1qhyReE6nf0gDaRBJICJGWnrt6WuaY+7MDWg9/jl97xMMF3hgdFe5Pnap2eOI5ZrOZL5e4Max9SZY0qkn0qdNqhyReE6nf0gDaRBJICJGa25G3KbWwlOW5v0O8aTL9AKb4eIJcv8So0/Nk9Wq1QxQpWHHRD8WgUHJ+Rc78dU/tcMRrIvVbGkCbSAIJIVIz6eQkFIOC0+zmaD388TtzmzA/P4w6PZerVsMkj33LkhJNiZQ31EQxKPy4YpLa4YjXROq3NIA2kQQSQqQkNjGWqsuqohgUPh81nipjd5GQmMSVps0w6vQ8mD1b7RBFGkbtm4diUKg9oSp3fJeoHY54DaR+SwNoE0kgIURK1gStQTEolFpQA62HH177rxB1+LDl7tIyZUl8/FjtEEUaouKjqTLDmQt6PUadnvhbt9QOSWQwqd/SANpEEkgIkZLf9vyGYlAoPr4vytCtRMQmcKN9B4w6PaEjR6kdnkiH9us9WVrbWc7Y5lBSv6UBtIkkkBAiJWazmUbzFqAdsJIxm4wkPnpEYNlyGB1KEn/jhtrhiXR4GBlHpx+HY9TpuVi3PmazWe2QRAaS+i0NoE0kgYQQKTn/VxhaD38+H7CJ209iAEgKCyN82zaVIxMvo6/hEAEOCkadnpjzF9QOR2Qgqd/SANpEEkgI8ayI+AhiEmPotew0Wg9/ei6TeeSysxPXHjG7TlOMOj3nBvdVOxyRgaR+SwNoE0kgIcSzpp6aSuUlVfhi3FC0Hv6cuxVGQmiofHyYTZnNZtr3a4xRp+dYhVKYExPVDklkEKnf0gDaRBJICPFUXFIcNZbXsEz9Mnos3885TFJkFIHOLlz7vgWJ9++rHaJ4BeO3b+JoGT0nS+m5deaQ2uGIDCL1WxpAm0gCCSGe2hCyAcWgoMyvitZjAzsu3uXRwoUYdXpC6n+F2WRSO0TxCsJjE2g4vD5lvRz5fedotcMRGUTqtzSANpEEEkKA5aPCFhtboBgUSkz4nZoT95AUn0BwzVoYdXoeL1uudojCBm1WLEQxKJQ2VCAiPkLtcEQGkPotDaBNJIGEEADHQ49bzv75lOXTgcvxPXqdsI3+lse+VaqMKTZW7RCFDc7efILDnNooPo7M3D9N7XBEBpD6LQ2gTSSBhBAAnXd0RjEofDGlPWVHbicmNp6Qrxtg1Om5P3Om2uGJDNBp8O/sqKxnaYNSxCfJc5yzO6nf0gDaRBJICHEn8g6lFpZC8XHi08EGJm2/TJifH0adnkCXiiRFRqodosgAu3ccwajTc17vwI1rV9UOR9hI6rc0gDaRBBJCAGy8eJbiY4dSYtBm7kfEcbNLV8sjxObMVTs0kUHMZjPbqtfHqNOzcuAktcMRNpL6LQ2gTSSBhBAAHRedQOvhT79VZwEwJyUR5u9PUmSUypGJjHRo3HSMOj3rK9cnLDpB7XCEDaR+SwNoE0kgIexbRHwE1x9G8Wl/f7Qe/gTdlTtEc7L4u/e4oHfAqNPTeU53tcMRNpD6becN4L59+2jUqBH//e9/0Wg0rFu37qXeLwkkhP0Kiwuj8pLK1F/SHu2A1bh7HyP28mW54zeHO/pdC4w6PcPbleTwrZNqhyNekdRvO28AN2/ezKBBg1i7dq00gEKIlzLv7DwUg4Lj3LpoPTZy0HiH4Jq1CKpWndiLF9UOT7wmj9etx6jTs7OSnsYr2qkdjnhFUr/tvAF8ljSAQoj0SvbYtzGj+OrP/Txevtwy71+1aphiYtQOUbwmpqgodrVrR8thJVG8FS49DFE7JPEKpH5LA2iVngYwLi6O8PBw63Lr1i27TyAh7NGKwBUoBgWn+dXRemxg7dErBH1ZE6NOz6OFC9UOT7xmiUkmys61PPnlhzW/qx2OeAXSAEoDaJWeBnDYsGFoNJoXFntOICHsTZIpiQZrGqAYFIqP64/LmB3cX+yLUacnqHoNuQbQTozfs+nvp7+U4a/we2qHI16SNIDSAFrJGUAhRHpsv77dcvbP2wVt/zXM2W4kqHoNy9k/X1+1wxOZJPz8Rf5oVZFfBpWkg98otcMRL0kaQGkAreQaQCFEerTf1h7FoFBiYk8chmzhrwUGy9k/1y8xxcsjwuzF/WmWOQE3VXOiwqSJxCea1A5JvASp39IAWkkDKIRIj6iEKOp7j+TTgcsZtuECd4YOw6jT83jZMrVDE5ko6ckTLpUth1Gn5/tfxrPs2A21QxIvQeq3nTeAkZGRBAQEEBAQgEajYfLkyQQEBHDjRvp+kSWBhLA/Z24+Qevhz2f9/bnxMBqAmAsXMMvZP7tzb+JEjDo96yrWpfq4XSQmyVnA7ELqt503gHv27Enxpg53d/d0vV8SSAj7EZ0QjdlsprX3MbQe/vReEaB2SEJliQ8fcql0GYw6Pd/1dGfwDh+1QxLpJPXbzhtAW0kCCWE/Bh4YSIPVzSg2fAbFBmwiZPNOEu7cUTssobK7np4YdXpW19Hj5F2RRzFP1A5JpIPUb2kAbSIJJIR9CI0KpczCMigGhc+GzcZj8VEuV6rMJcWJmAA5E2jPEu7exag4Wc4CjnSk7UYPtUMS6SD1WxpAm0gCCWEfJhyfgGJQ0M9sQrEBmwieMgOjTk9wvXqYExPVDk+o7O6ECazo0onKsxxRfJw4f/+C2iGJfyH1WxpAm0gCCZHzhcWF4eLrgmJQKDZyEgMXH+ayS0WMOj1h69erHZ7IIsJiElCm/4xiUGiw6ltMZrkhJCuT+i0NoE0kgYTI+eadnYdiUHCYU4fPB/gTMnEqRp2ekK++lrN/IpkRmw7juKA8ikFhzeU1aocj0iD1WxpAm0gCCZGzxSXFUWN5DRSDwudjRjHY9wiBzi6Ws38b/dUOT2QxoXsOsOLLajQe50jVJa4kJCWoHZJIhdRvaQBtIgkkRM628cpGFINCSa+qfD7Aj5AJUyxn/xo2xJyUpHZ4Iov56/c+GHV6FnxVlQazVmM2m9UOSaRC6rc0gDaRBBIiZzOZTTT0msPno8fSf805Hsyew6UyZQnfskXt0EQWFBccjFGnx6jTU73LfA4GP1A7JJEKqd/SANpEEkiInO3olYdoPfwpPnATfz2JASDx0SPMJrnAX6TsVo+eGHV6ZtZuyfdzDhP8OFhuCMmCpH5LA2gTSSAhciaz2UxsYiwt5h5G6+HPwLXn1A5JZBOxFy9i1Ok5r3PAdWhrnAxOrA1aq3ZY4jlSv6UBtIkkkBA504nQE1TyrUqJ8X0pMXAz1xYvI/r4cbXDEtnEzU6dMer0TGtUF8WgUGN5DcLiwtQOSzxD6rc0gDaRBBIiZ+q6oyuKQeGLKe0Ytfggl8qWw6jTE33ihNqhiWwgJiAAo07POX1Jakyw3EU+5ugYtcMSz5D6LQ2gTSSBhMh5gh4HoRgUHH2cKDFsEVdGWZ71erX5N3JXp0i3O0OGMnvAVEoMm4RiUCi1sBSXHl1SOyzxN6nf0gDaRBJIiJxnwP4BKAYF3bSWjFl8gEuly2DU6Yncu1ft0EQ2c/VBFJ/190c3rRWKQeHnzT/LDSFZhNRvaQBtIgkkRM4SGhVKqYWlLR//jpzLleGjLGf/vv9ezv6JV9Jz2Wk+HehLKYPlCSHrg+XxgVmB1G9pAG0iCSREzjLh+AQUg4J+ZhPGLtrPpVKlLWf/9h9QOzSRDZmTkrg0x5utFWpQYUQPKi2pjF+In9phCaR+gzSANpEEEiLniEmMocLiipaPf8dM5uqQ4Rh1eq790FLO/olXYjabufrd9xh1eoY36kRrw261QxJ/k/otDaBNJIGEyDnMZjMNZq2ixMQeDN9wgTA/P4Jr1yHq8GG1QxPZWMSu3Rh1ek46lsax90o2nr2tdkgCqd8gDaBNJIGEyDn2BN5D6+GPbvBm7kXEAmBOSJCzf8ImZrOZK25NMer0DGrSg9IjtrIucCse+z0kt1Qk9VsaQJtIAgmRM8QnxtNkxkG0Hv54rjmtdjgihwnfstVyFtCpHCX7GihlKIdiUOR6QBVJ/ZYG0CaSQEJkf0mmJOqsaIhu6k/U6/UnlypWJmzDBrXDEjmI2WQipEFDjDo9Hs1/o8SEPigGBdflrkTER6gdnl2S+i0NoE0kgYTI/nZc34FiUCg3uwJHq9fCqNNzs1Nn+XhOZKgwPz+MOj1nyrtQvM8qFK+aKAaFccfGqR2aXZL6LQ2gTSSBhMjezGYzDVd9i2JQmOZWG6NOT1D1GiQ+fqx2aCKHMScmcmfwYMJPnqLB1P0UGzkZxaBQemFpLj++rHZ4dkfqtzSANpEEEiJ7W3BuAYpBoUMfJ4w6PUa9A1FHjqodlsjhLoWGU3zgJnTTWqAYFH7Z/Iuccc5kUr+lAbSJJJAQ2dfJuycpZShFrSmOnFQUjDo996dOVTssYSdm7gjk00G+KN5lUQwKx+4cUzskuyL1WxpAm0gCCZE9PYx5SK0VtSi9wJH11ctbJnxu9SPmxES1QxM5XFJEBKFjxhD81dc0/XMPxccOpZnPfDkDmMmkfksDaBNJICGyp6DHQVRfWhtlVk3GuHXikktFEm7LBL3i9TPFxRFUrTpGnZ5L8xdRYuBmtB7+rDp5S+3Q7IrUb2kAbSIJJET2ZDKZqTd1C58OXsiErZdIevJE7ZCEHXlkMGDU6QmuU5fZOy+j9fBHGbaVi3dvcTPiptrh2QWp39IA2kQSSIjsJS4pDoDNhy5TrO8GHIdu5Ul0vMpRCXtjio7mcuUqGHV6Hq1dh9uMgxQbNZFSPs603tJaPg7OBFK/pQG0iSSQENlHaFQotVbWYtbxxSyv0YS1leoxa+k+tcMSdurB3HkYdXpCvm5A0J0wSgzzxfHvG0KWX1qudng5ntRvaQBtIgkkRPaQkJRAq02tUAwKQ9pXskzI61iKiECZf02oIykykkCXihh1eh7Mm8fcfSGUGN8XxaBQylCK3Td2qx1ijib1WxpAm0gCCZE9jDs2DsWg0Hx0Oc7rHSxP+1i8TO2whJ17vGyZ5VrAmrVIiIyi6cwDfPFnaxSDQvnF5Tl9T55L/bpI/ZYG0CaSQEJkfduubUMxKLjMcWR3uQqWCZ+79JDrrESW8NDHh8T79wG4cj+SLwZtRD/d8nSayksrE/w4WOUIcyap39IA2kQSSIis7Xr4dSouqYji44jX1zUw6vScq1GTpIgItUMTIkVee4PR9l+L45yGKAaFoYeGqh1SjiT1WxpAm0gCCZF1xSbG0nxDcxSDQveulnnXLjg4EnP2rNqhCZGiMD8/rv7QkpbTdqMduIKaCzyIS5S71F8Hqd/SANpEEkiIrMtkNjH64FSU+ZWp0nM6+2t+zQMvL7XDEiJFSRER1qlhAjt2QT/IH62HP4uOXAfAbDaTkJSgcpQ5h9RvaQBtIgkkRNb1KCqeauN3oR2wmu/mHCYuOhazyaR2WEKkKvrkSS4pThh1enb0HorWwx+HIVu49jCC4YeH021nNxJN8rjCjCD1WxpAm0gCCZH13Iq4RXhsNN/NPkyVbj5UH7+bR1HyMZrIHsLWr7fcqKTTM6bnH2g9/HGbt4ryi8tbpjE6OERuYMoAUr+lAbSJJJAQWUtkfCQN1zak8sIG/Nh6IBd0DlzynKh2WEK8lHtTpliaQEeF5p1noPXwZ/C25ZRaWArFoDD11FS1Q8z2pH5LA2gTSSAhsg6z2czve39HMSi4TqzEcaUMRp2eexMnqR2aEC/FbDJxq2cvjDo9Z8u7ULbnEvSDtzD12GIUg4JiUPA1+qodZrYm9VsaQJtIAgmRdSwxLrE8RWG+E2uqfolRp+fa9y0wJ8iF8yL7McXEcPWbb7k35U9azTuE1sOfkkO24LFzIopBwcngxJZrW9QOM9uS+i0NoE0kgYTIGs7eP0vphWVw8nbkz0b1LXdSlq9A/K1baocmxCszxVuuXQ2PTaCV1xG0Hv4UG+CP+wYPFIOCs68zD2Meqhxl9iQDhTu4AAAgAElEQVT1WxpAm0gCCaG+J7FPqLWiDmXmO+LVwPKcX6NDScK3blM7NCEyTGxkNLM8/kTbbyNaDz/cVnRlz809aoeVbUn9lgbQJpJAQqivz95+KAaFlgP/bv4UJ8K3bFU7LCEyjDkxkWstfsCo07Nq4ES0HpY5AnuvCCA+UaY2ehVSv6UBtIkkkBDqMpvNdF62A/3MJihjvLk8ewGRBw+qHZYQGe7h/AXWs9sb562m2IBNaD38+dHrKBcfXKHTjk7ycfBLkPotDaBNJIGEUJfX2qOU6bWUYgM2cSDogdrhCPHamM1mbg8aZLm+tVx59m87gsOQLWg9NlJ2fmMUg8L3G78nKiFK7VCzBanf0gDaRBJIiMxnNpvZeX0ns1bNYU+Zymx0rsWSnRfUDkuI184cH8/1n3/BqNMTXLMW589fpcLoHXw6xAdlQUUUg0KHbR3kkXHpIPVbGkCbSAIJkbmMD424b25No3GOHClreVrC0ao1Sbh9W+3QhMgUSU+eEFLPcqf7tRY/cDP0MbUn7eWzYbNRvMuhGBT67euHySzXBqZF6rc0gDaRBBIic9yPvs/gg4NxMjjx3UhHTjpZmr/dNeoSe+++2uEJkanirl4l0KUilytWIvbyZcKiE/h+zmGKjZyMo4/laSETjk9QO8wsTeq3NIA2kQQS4vWKTYxlzpk5OC92RjEouA8qSUBJB4w6PcebfEdCmPzuCfsUffIk8TduWL+OS0yi+9LTfD5mlPVpITJNTOqkfksDaBNJICFer4i4CCouroZiUGj9myvn9ZbmL6RDZ0yxsWqHJ0SW8WTVKuJu/cXYzZcoPt6Dkl6V6bPqBAlJlo+CE02JKkeYtUj9lgbQJpJAQmS8wEeBmM1mgu5G8P2cw3w+egyfjxnNdyPWcKFqDW7388CcKMVMiKdiAy9j1DtwyakUdz3HsnTbGT4buAKthz+/LDhGWEwc3/l9x6gjowiNClU73CxB6rc0gDaRBBIi49yJvEPffX1RDAqd183n87/nOdMN3sysPSHEJ5pIuHsPs0kubhfiWbGXL3P9p58t8wTq9ASWLcexoWMp67EOrYc/NWfMtX4sXG5ROcYeG8v9aPu+dlbqtzSANpEEEsJ20QnRTD01lfKLy1uKlI8TJSb24NN+fixp1YOrazeqHaIQWZ7ZbCZy/wGuNmtubQQvulRiUKsBFO+zHsVzBl/6fmttBMsvLs+E4xN4EGOf82dK/ZYG0CaSQEK8uiRTEmuD1vLlii+tRUk/swmfDZ1LtVFbOdG2K0adnkulSpNw757a4QqRLZhNJsK3bCGk/leWRtClIk3Gb/378XEbKTbiT5y93ay/c86+zlwLu6Z22JlO6rc0gDaRBBLi1Q3YP8BahBy9XPl81Hg+H+DP+HWnudqm3T/P9d20Se1Qhch2zImJPF65kier12Aymdl3+T4dDMf5ps0ktP38KDZyMk5zG1BzSXP+ehxtfZ+93Cwi9VsaQJtIAgmRfrcjb/NX5F8API6K58+Dm3Dydqb4+H5o+6/n29mHuHT6kvWh95fKlCVy/wGVoxYi5wjfvh2jTs+ROg1p3XUa2n5+aAeu4LP+/rQznGDzxavUXVWX6aenEx6fs+ua1G9pAG0iCSREysxmM1fDrrLq8ir67+9PnZV1UAwKTZf3psHU/Xza39/ykdSA1ZQZsY0VJ25ye+Cgfy5id6lI9OnTag9DiBzl8fIVBJYtZ/09O9X8B34f5vv3x8P+FB/3z1n5SksqMevMLCLiI9QO+7WQ+i0NoE0kgYRILj4pnt/2/IbrcldrIbF+zOtTCmVSK5q0ncLQxl3ZUq0+k3338zgqHoCHPj4YSzpy/cefiL18WeWRCJEzJT56xF1PTy4pTtZG8FK7jkyeuxll2GY+Hz0Whzm1rb+3FX0rM+zQMFZdXkV8Urza4WcYqd/SANpEEkjYq0RTIucfnMfnvA+zAmaRZDJz7lYYs/eGUM6npqXh8y6Dw4xG1PdoTd8W7qyq2YRzjv8UHaNOz5M1a637TIqIICkyUsVRCWE/Em7f5vbAgRgdSmLU6fnr9z5Exyey/PgNGv65mx86d6HqxBooPo4oBoXShvKsPHGdC7fDiEtMYn3wetYGrSXocVC2vG5Q6rc0gDaRBBL24kHMA06EnmDu2bm03dKeCn8/ms1SGCrgNHzLPx8jjRhPseEzKDdqM5MHz07W8Bl1eoKqVed2v348WbeOxAf2OQWFEFlFXEgIt3r05KGPj3VdbHCw9ff1SOkyLKlVhdHf1+WXH0dRtas3xftvpPSC2s/MLViBFn4/MvbYWPxC/LgadlW9AaWT1G9pAG0iCSSyM7PZzOPYxwQ+CmT/rf2sCVrDnydn8NuuwbTc0JElR68xaftl+qw8Q1Xv1v80fAscaTzWkV8GlKFHp9oMadGESfV/ZnHNbzhcsTpbPTwJDI3AbDaT+PgxgeUrcLNzFx4tXERccDBms1ntoQshnvPs72X06dNcadQIY0nHF/6BM+r0DHDrSYmJ3dDPbEKFWeVw83Sk7HxH69+IKou+ZvnxG5y5+YSY+CQO/XWIG+E3MJmzziTuUr+lAbSJJJDIap7EPuFq2FUC7p5jx9WDrLiwhRnHlzFkzzQ6bRrMsmPX8Np/hUnbL/P1ko7/XKPn40j16Y40GeuI+6CS/NqrJIOadmRSPXd8ajSj3y8NKelVDd20lpQd/nuKReHpct29dbKYzElJKv00hBC2MMXGEnPuHI+Xr+DOsGFc+74Fl0qX4caGzey+dI+Ze4L5Y+g8jDo95/UObK1UjmV1yjLv62r8Ub8NQxt348suc1B8ylquJ5yt0OiPCtSf+SW1Fzah4Yqf6bV5Etsv3uX4tUcE34tg2cX17Li2m4B7AVwJu8LDmIckmBIyfGxSv6UBtIkkkH0wm80kmhKJT4wnOj6GiLhIHsaEcT/qMdHxiUTEJvAkIoaQ+7e5cPc6p2+HcOz6RQ6ePcyeU3vZfnQ7mw5s4sKpS5w7dpGAw2dZe2Arc45vYPqR1fy5dzFzDOOZ4TWKqbOGMHlaf9bPWcHa6ctYNXkRQ2eNpOmKnjRY2oGvvVsy+NeaDOpejcFdXRjSuRwz23kw/ae+TP2uBx1+bfLPBK9zHPFt4MDKeg6sq6VnUw0928pXZU+ZShwqVYFJzWqhGBRKzq9Emem102zqjvzUgUPBD7hyP5LouESCa9Xm6jffcrNzF+4MHcb96TN4vGIFkQcOYoqKUvuQCSFeE3NSEuaEfxqysA0buFypcqp/O1q2HorD7K9x9C5Dp74lk70W4KjnQDknNjl/yYoqDXBrM9H696vheEfGujswsq0DQzuUZFCnUozo2oCZvcYyq88kRs3eQl3f1ny9tD0/LGhHP88f8fijDQP+7MygmT2Z6DOOrX4H2LnlCLuOBzPuwGImHlzCjH1L8dm2iHkbF9p9/bb7BnDGjBlotVry5s2Li4sLx44dS/d7nzaA3y8aiOfQtszr/I1l6dScpV07s6HnEDb0GMKabn35cflgWq4awg8rhzBySGvmtXf7e2mCb8e2rO/Sn/Vd+rOm0++0WtyPb1cM4NsVAxgy9GfmtWloWVo3xLftT6xv34f17fuwtt2vtPDuiduyPrgt68OAoT/i9XN95v9Un/k/1WPxz9+x3r0n6917svaX7vwwtzMNlvSkwZIe9Bn6Pd4/1LIsLWrh26IJ61t2Zv0PnVj/QydaTHen7uJO1F3UiV5DvmHhNzVY+E11FjavztLm9dnwTRs2NG/NhmbutJz0I64LW+NqcKfr4CYsaVyZJY0rsbRRJVY0+pKNDVuyscEPbGzQgh/Hfk8Vnx+o7PMDHQZ/zar6FVhVrwKr65Vnbd3KbKrdlM213dhcqwnuw5tSYYEbFRY0wX1ILTbULI3fl6XZ6Foa/xrl2VatPtuq1mN71bq069+QMvPrUmZBHVoOrcb2KgrbqyjsqOzIzkpO7HGuzt4K1dhbvhpdfq2DsqAyyoJKfDOiPAfLO3CwnAOHyzlwpIwDR0uV55hTOY4pZendqYb1D5KbpyMBjnrOlNRztqSecw56LugcrH/MBrtXT/bHK62GalTLf/Zbd1La20749p9tq09Pe9upbl/iuKACJb2qUn7al2luu61Fa6bvvsSK4zfZfykUY0lHLlevYWnsunS1NHYzLI1d9CmZkkUIkTKz2UxCaCiR+w8Q5ufHo0WLuT99BqGjx3DnrJGT1x+z3XibjZNnElDemQsOJVP8m9S2gyf6Gc1wmP0VHXq7pPn3q03LYda/i+6DUt7f06XL9wNx9LachWw5zLLt8eIlpAFUOwA1LV++nDx58uDt7c3Fixfp0KEDhQoV4l46Hzv1tAF0mO2ATxOHNBPw2esj5jRPe9tKs/7ZduoPaW/rOu2fbcf/nPa29Sb9s+2oNmlv23jsP9sO6pT2L9e3I0pZt+3bLe1tfxxYzrptj95pb9umzz83GnTsl/a2nXtVSvcfg187V7Fu+8PwtLft166addtmY9Juvob8XANH7zI4epflq3Flresv6C3N4pmSTpx2LMVJpQyePzeijFcjynq5UWdSY/Y5O7GnYil2VS7D9mpl2eNanz21GrK7rhszenWlxfJRuK+aSI9lk9n0TRM2t/iWrT+1YnvrNhzs9CvHenkQMGA4F5as4eajaMKiE0iMT+DJ6jWEbfQnYscOIvcfIOrYMWLOniU28DIJd5PnudmUda7PEULkXGazmaTISOJv/UXMhQtEHTpE+ObNJNy9h8lk5kl0PFcOnODcwBGc6N2fQ117srdde/b+0oaDP7bnwPfuLJq9mo7rZtB69WQGevZkV41K7KnqzP5K5TlUoQxHypfleFkXTpSuwPBu43H2akV5r2/5eVBdzjnoOSoNoH03gC4uLnTr1s36tclk4qOPPmLs2LHpev/TBrD+/C6M+v1b5v9U7++zb/VZ4v4j69v0Zn3b3qxu041mvr/RdFkfmi7ry/D+LfFyb2BZWjdkSdufWd+hLxs69mVNh19pubgv364YwHcrBjJ0mDvz2jVmXrsmzGvXhMUdW7Oh60A2dB3Ium4etF7Un5arhtFq1TCGjOnIvE7NmdfJciZyUbf2+PUaht+vw9nw61A6LxyM+9rRtF47hiETezK3+w/M7dGSuT1asujXzmz08MTfYywb+4+jl+8IOm6YSCe/iQyb0Z95v7dm7u+tmdu3DQv792TTsMlsHj6FzSP+ZNDSCfy6eQa9N89k5IKReA3ugteQrngN7caiER5sGz+H7RPmsn3iPMaumsmgHd4M3uHDhKVT8Pbsi/fYfniP88B34gh2z/Jl9+wl7JmzlFkbFjJh/0r+OLCaGRu98Z0xhiUzPFkyy5NVc6ZwyHc9h5Zs4PDSjSzZvo75J7bjfXIHvns2sG7xbNb7zsVvqRebVywkYNMezmzZx7lt+9l5dD+bAk+y5XIAO84eYd+2DRzY5sfhXZs5tncHV4+f5fqpC9w4Y+RSyGUC798h+OFdrobe5qbxIrcvXyb0SggPr10n4vZdou7eJ+bhIxJjYq25YTabLR+VyA0PQgiR5cglXHbcAMbHx/PGG2+wbt26ZOt/+eUXmjRpkuJ74uLiCA8Pty43b95Eo9Fw69atZOtlkUUWWWSRRZasu9y6dQuNRkNYWFhmtBxZkt02gLdv30aj0XD48OFk6/v27YuLi0uK7xk2bBgajUYWWWSRRRZZZMkBy5UrVzKj5ciSpAF8iQbw+TOAN27cQKPRcPPmTdX/m1HjPyd7O/Mp45Zx28Mi45Zx28Py9BO8J0+eZEbLkSXZbQP4Kh8BPy883D6vIZBxy7jtgYxbxm0PZNz2Ne5n2W0DCJabQLp372792mQy8b///e+lbwKxtwSSccu47YGMW8ZtD2Tc9jXuZ9l1A7h8+XLy5s2LwWDAaDTSsWNHChUqxN27d9P1fntNIBm3jNseyLhl3PZAxm1f436WXTeAANOnT6do0aLkyZMHFxcXjh49mu73xsXFMWzYMOLi4l5jhFmPjFvGbQ9k3DJueyDjtq9xP8vuG0AhhBBCCHsjDaAQQgghhJ2RBlAIIYQQws5IAyiEEEIIYWekARRCCCGEsDN20QB6enpSoUIF3nrrLYoUKYKbmxuBgYHJtgkJCaFp06a8//77vP3223z33Xfpmg5mxowZaLVa8ubNi4uLC8eOHUv2emxsLF27duXdd9+lQIECNG/e/IX93rhxgwYNGpAvXz6KFClCnz59SExMzLbjfvToEd27d+eLL77gzTff5JNPPqFHjx4vPHMxpcfyLFu2LNuOG8DV1fWFMXXq1CnZNjnteF+7di3VxyytXLnSul12O9779u2jUaNG/Pe//0Wj0bwwaTyA2WxmyJAhfPjhh7z55pvUrl2boKCgZNs8evSIVq1a8fbbb1OwYEHatm1LZGRkth13QkIC/fr1Q1EU8ufPz3//+19+/vlnbt++nWw7rVb7wvFO7xyrWXHcAO7u7i+MqX79+sm2yWnHG1L+3dVoNEyYMMG6TXY73unZr5r1OzPYRQNYv359fHx8uHDhAmfOnKFBgwYULVqUqKgoAKKioihWrBjNmjXj3LlznDt3Djc3N5ydnTGZTKnud/ny5eTJkwdvb28uXrxIhw4dKFSoEPfu3bNu07lzZz755BN27drFyZMnqVSpElWqVLG+npSUhKIo1KlTh4CAADZv3sz777/PgAEDsu24z58/T/PmzfHz8yMkJIRdu3ZRokQJvvnmm2T70Wg0+Pj4EBoaal1iY2Oz7bjB0gB26NAh2ZienWcqJx7vpKSkZOMNDQ1lxIgRvPXWW8kKX3Y73ps3b2bQoEGsXbs21cI4btw4ChYsyPr16zl79ixNmjThs88+Szaur776itKlS3P06FEOHDhA8eLFadmyZbYdd1hYGHXq1GHFihUEBgZy5MgRXFxcKF++fLLttFotI0eOTHa8n8aWHccNlgbwq6++Sjamx48fJ9smpx1v4IXfb29vb3LlypXsObrZ7Xj/235B3fqdGeyiAXze/fv30Wg07Nu3D4Bt27bxf//3f8kKdVhYGLly5WLHjh2p7sfFxYVu3bpZvzaZTHz00UfW/3rCwsLInTs3q1atsm5z6dIlNBoNR44cASy/fP/3f/+X7L+K2bNn88477xAfH58xA/5bZo07JStXriRPnjzJ/jNK7Y9NRsvMcbu6utKrV69U92Evx7tMmTK0bds22brsdryflVLsZrOZDz/8kD/++CPZfvPmzWs9s2k0GtFoNJw4ccK6zZYtW8iVK9cLZ8xslVnjTsnx48fRaDTcuHHDuk6r1TJlypSXHMXLy8xxu7u74+bmlur77OV4u7m5UatWrWTrsvPxTmm/Wa1+vw522QAGBwej0Wg4f/48AH5+frzxxhvJJoSMi4vjjTfeYNiwYSnuIz3PEt61a1eKD5suWrQokydPBmDIkCGULl062etXr15Fo9Fw+vRpm8b5vMwad0q8vLx4//33k63TaDR89NFHvPfeezg7O7NgwQLMZvMrji51mTluV1dX3n//fd577z0cHR3p378/0dHR1tft4XifPHkSjUbDoUOHkq3PTsf7eSkVxitXrqDRaAgICEi2vkaNGvTs2ROABQsWUKhQoWSvJyYm8sYbb7B27dqXHVqaMmvcKdmxYwe5cuVKVoS1Wi0ffPAB7777LmXKlGHChAmv5aOxzBy3u7s7BQsWpEiRInzxxRd07tyZhw8fWl+3h+N99+5d/vOf/7BkyZJk67Pz8U5pv1mtfr8OdtcAmkwmGjZsSNWqVa3r7t+/zzvvvEOvXr2Ijo4mKiqK7t27o9Fo6NixY4r7uX37NhqNhsOHDydb37dvX1xcXABYsmQJefLkeeG9zs7O9OvXD4AOHTpQr169ZK9HR0ej0WjYvHmzTWN9VmaO+3kPHjygaNGiDBw4MNn6kSNHcvDgQU6fPs24cePImzcvU6dOtXGkyWX2uOfOncvWrVs5d+4cvr6+/O9//6NZs2bW1+3heHfp0gUHB4cX1men4/28lArjoUOH0Gg03LlzJ9n67777ju+//x6AMWPG8MUXX7ywvyJFijBr1qyXHV6qMnPcz4uNjaVcuXK0atUq2fpJkyaxZ88ezp49y+zZsylUqBC9e/d++cGlIbPHvWzZMjZs2MC5c+dYt24dDg4OODs7k5SUBNjH8R4/fjyFCxd+4fKN7Hy8U9pvVqrfr4vdNYCdO3dGq9Vy69atZOu3bdtGsWLFyJUrF2+88QY//fQT5cqVo3PnzinuJ7s1gJk57meFh4fj4uLCV199RUJCQpoxDhkyhI8//vglR5Y2tcb91NP/IkNCQoCcf7xjYmIoWLAgEydO/NcYs/Lxfl5WbwAzc9zPSkhIoHHjxpQtW/Zfn6m6YMEC/vOf/2Too7fUGvdTT88C79y5E8j5xxtAp9PRvXv3f91XdjreKe03K9Xv18WuGsBu3brx8ccfc/Xq1VS3efDggfWU7wcffJDsLqdnZaePgDN73E9FRERQuXJlateuna6L/f39/dFoNBn2B0OtcT8rKioKjUbD1q1bgZx9vAEWLVpE7ty5uX///r/GmZWP9/Oy8kfAmT3upxISEmjatCmlSpVK9jFoai5cuIBGo3nhTstXpda4n/f+++8zZ84cIGcfb4D9+/ej0Wg4c+bMv+4ruxzv1PabVer362QXDaDZbKZbt2589NFHL0zRkJpdu3aRK1euNJPXxcUl2X9CJpOJ//3vfy/cBLJ69WrrNoGBgSleRPrsnaRz587lnXfesbkwqjVusJz5q1SpEq6ursmugUvL6NGjKVy4cLq2TYua437ewYMH0Wg0nD17Fsi5x/spV1fXF+72Tk1WP97PSusmkGfPdoaHh6d4E8jJkyet22zbti1DbgpQa9zwT/Pn6OiYrmYfwNfXl//7v/974a7Zl6XmuJ9369YtcuXKxYYNG4Cce7yfcnd3f+Fu79Rk9eP9b/tVu35nBrtoALt06ULBggXZu3dvslvUY2JirNt4e3tz5MgRQkJCWLx4Me+++y6//fZbsv3UqlWL6dOnW79evnw5efPmxWAwYDQa6dixI4UKFUp2R1Dnzp0pWrQou3fv5uTJk1SuXJnKlStbX396G3m9evU4c+YMW7dupUiRIhlyG7la4w4PD6dixYo4OTkREhKS7Hs/vVbGz88PLy8vzp8/T3BwMLNmzSJ//vwMHTo02447JCSEkSNHcvLkSa5du8aGDRsoVqwYNWrUsO4jJx7vp4KDg8mVKxdbtmx5IbbseLwjIyMJCAggICAAjUbD5MmTCQgISHan67hx4yhUqJD1ujA3N7cUp4EpW7Ysx44d4+DBg5QoUSJDpgVRa9wJCQk0adKEjz/+mDNnziT73k/vfDx8+DBTpkzhzJkzXLlyBV9fX4oUKcIvv/ySbccdGRlJnz59OHLkCNeuXWPnzp2UK1eOEiVKJCv2Oe14PxUeHk7+/PmZPXv2C7Flx+Odnv2qWb8zg100gKlNYunj42PdxsPDgw8++IDcuXNTokQJJk2a9MIdilqt9oW7iqZPn07RokXJkycPLi4uHD16NNnrTyeSLFy4MPnz56dZs2aEhoYm2+b69et8/fXX5MuXj/fff5/ff/89Q+6eUmvce/bsSfV7X7t2DbBMjVCmTBneeustChQoQOnSpZkzZ06a8zZl9XHfvHmTGjVq8O6775I3b16KFy9O3759X7g2Kqcd76cGDBjAJ598kuIxzI7HO7U8dnd3t27zdCLoDz74gLx581K7dm0uX76cbL+PHj2iZcuWvPXWW7zzzju0adMmQyYGVmvcaU38vWfPHgBOnTpFxYoVKViwIG+++SYODg54enpmyFkRtcYdExNDvXr1KFKkCLlz50ar1dKhQ4cX/hHKacf7qblz55IvX74XJvSH7Hm807NfNet3ZrCLBlAIIYQQQvxDGkAhhBBCCDsjDaAQQgghhJ2RBlAIIYQQws5IAyiEEEIIYWekARRCCCGEsDPSAAohhBBC2BlpAIUQQggh7Iw0gEIIIYQQdkYaQCFEtuLq6kqvXr3UDiPDZNZ4zGYzkyZN4tNPPyVfvny4ubml+FSHZz18+JAiRYpYn+ADcPbsWapVq0apUqVo2rSp9WkPLVq0SPZcZCFE1iYNoBB24v79+3Tu3JlPPvmEPHny8MEHH1CvXj0OHjyYIftPrZHJ6Abn0aNHREREZNj+1Gbrz8fT05MKFSrw1ltvUaRIEdzc3AgMDHxhu99//53ixYuzb98+Tp48yccff8yvv/6a5r579+5N+/btrV/Hxsbi4OBg3X/Xrl1ZsGABAOfPn6dw4cL/2lQKIbIGaQCFsBPVq1enYsWK7N69m+vXr3Ps2DE8PT3ZsGFDhuz/dTeA8fHxNu8jK7L151O/fn18fHy4cOECZ86coUGDBhQtWpSoqCjrNkePHiVXrlycOnXKum7EiBF88cUXqe43Ojqad955hyNHjljXLVu2jN9++8369bRp0xg3bpz16woVKjBjxoxXHosQIvNIAyiEHXjy5AkajYa9e/emuo3JZGL8+PF8/vnn5MmTh08++YTRo0dbX9+yZQtVq1alYMGCvPvuuzRs2JCQkBAA3N3dX3io+rVr11JdbzKZ8PT05NNPP+XNN9+kVKlSrFq1Klk8rq6udOvWjV69evHee+/x5ZdfWtc/bZhcXV3p0aMHffv2pXDhwnzwwQfJHvgOEBERQatWrcifPz8ffvghkydP/temK62xPhtfRnzvZ79Oz8/l39y/fx+NRsO+ffus67799lvq1KmTbLs5c+bw7rvvprqfVatWUaRIkWTrhg4dyvz5861fd+rUCT8/P+vXI0aMoFq1ai8VrxBCHdIACmEHEhMTeeutt/j111+t12w9r1+/fhQuXBiDwUBISAgHDhzAy8vL+vrq1atZs2YNwcHBBAQE0LhxY5ycnN49YcUAAAYKSURBVDCZTISFhVG5cmU6dOhAaGgooaGhJCUlpbp+9OjR6PV6tm7dypUrV/Dx8SFv3rzJGlRXV1feeust+vbtS2BgoPVjx+cbwHfeeYfhw4cTFBTEwoULyZUrF9u3b7fup3379mi1Wnbu3Mn58+dp1qwZb7/9dpoNYFpjfTa+jPjez44nPT+XfxMcHIxGo+H8+fMAxMXFkS9fPmbOnJlsuz///JPPPvss1f307NmTr776Ktm62bNn06dPHwACAgJwcnIiMTHR+vqWLVvIkydPqjkmhMg6pAEUwk6sXr2awoUL8+abb1KlShUGDBjA2bNnAcuZqrx58yZr+P7NgwcPkjUa6f0IOC4ujvz583P48OFk27Vr146WLVsme1/ZsmXT3J+rq+sLZ5ycnZ3x8PCwjit37tzJzqKFhYWRP3/+l/rY9fmxZuT3fjqe9P5c0mIymWjYsCFVq1a1rjt8+DAajYY333yTAgUKWJc8efJQv379VPfl5uZG27Ztk62LioqiQYMGODo6UrVqVYxGY7LXz549i0aj4fr16+mKVwihHmkAhbAjsbGxbN++nZEjR1K5cmXeeOMNfHx8OHbsGBqNhqtXr6b63qCgIH744Qc+++wz3n77bQoUKIBGo2HTpk1A+hvACxcuoNFokjUjBQoUIHfu3Li4uCR737M3IKS0P1dXV7p27Zrs9SZNmtCmTRsAzpw5g0aj4caNG8m2KVu2bJoN4L+NNSO/99PxpPfnkpbOnTuj1Wq5deuWdZ3BYKBAgQIEBwcnW7744gtGjhyZ6r7q1av3wvj+TVBQEBqN5oXGUAiR9UgDKIQda9euHUWLFuXcuXP/2gDqdDrq1avHzp07MRqN1oZl3bp1QPobwKNHj1qvR3y+Kbl582aq70tpfUrbuLm54e7uDrx6A/hvY83I7/10P+n9uaSmW7dufPzxxy8cw2nTpqHVapOtu379Orly5eLixYup7q9Vq1bpPvP41NMxPHjw4KXeJ4TIfNIACmHHJk2axHvvvUdsbCz58uVL9SPghw8fotFo2L9/v3XdgQMHkjVFdevWpXv37i+89/n1Tz9uXrRoUZqxZUQD+PRj2NWrV1tfDwsLo0CBAqk2gOkZa0Z+76f7Se/P5Xlms5lu3brx0UcfERQU9MLrS5cupVChQpjNZuu6Dh060LBhwzT3+8cff1C6dOmXimX+/Pl8/PHHL/UeIYQ6pAEUwg48fPiQmjVrsnjxYs6ePcvVq1dZuXIlH3zwgfU6r+HDh1O4cGEWLlxISEgIR44csd7xaTKZeO+99/jpp58IDg5m165dODs7J2uKOnTogLOzM9euXePBgwfWGyZSWj9o0CDee+896w0np06dYtq0aRgMBmvMGdEAguVGjM8++4zdu3dz4cIFvvnmG95+++1U58BLz1gz8ns/u5/0/Fye16VLFwoWLMjevXutN9qEhoYSExMDwN27d3nzzTfx9PTk6tWrjBo1ig8//PBfzyqeO3eO//znPzx+/DjN7Z7l7u7+wnWDQoisSRpAIexAXFwc/fv3p1y5chQsWJD8+fOj0+kYPHiwtVEwmUyMHj0arVZL7ty5KVq0KJ6entZ97NixAwcHB/LmzUupUqXYu3dvsqbo8uXLVKpUiXz58lmne0ltvdls5s8//0Sn05E7d26KFClC/fr1k01dklENYEpTsbi4uNC/f/9Uf17/NtaM/N7P7ic9P5fnPT/NztPFx8fHus3y5cv55JNPyJcvX4pT2qTGxcWFOXPmpGvb2NhYChYsmGzeQCFE1iUNoBDCrkRFRVGwYMFk89nZw/d+Ff7+/jg4OCSb/iY1s2bNom7dupkQlRAiI0gDKITI0U6fPs3SpUutH6m6ublRsGDBTLlRQc3vnVGmTJmSrptQvLy8UnwEnRAia5IGUAiRo50+fZpy5cpRoEABChcuTJ06dTh37lyO/95CCJEWaQCFEEIIIeyMNIBCCCGEEHZGGkAhhBBCCDsjDaAQQgghhJ2RBlAIIYQQws5IAyiEEEIIYWekARRCCCGEsDPSAAohhBBC2BlpAIUQQggh7Mz/A62hof5AbXaiAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.DEPRECATION:Function _integrate1d_legacy is deprecated since pyFAI version 0.19.\n",
      "  File \"<ipython-input-14-d90507300a41>\", line 19, in <module>\n",
      "    res = ai.integrate1d(img, 5000, unit=\"2th_deg\", method=\"splitpixel\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f539ecd2780>"
      ]
     },
     "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 v2\",\n",
      "  \"detector\": \"Pilatus 1M\",\n",
      "  \"detector_config\": {},\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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.DEPRECATION:Function _integrate1d_legacy is deprecated since pyFAI version 0.19.\n",
      "  File \"<ipython-input-17-ae89462c1e23>\", line 51, in <module>\n",
      "    res = ai.integrate1d(img, 5000, unit=\"2th_deg\", method=\"splitpixel\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f539ec4f3c8>"
      ]
     },
     "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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