From 7ee29c67ef9cecc51031d32107e7b9bbd9082106 Mon Sep 17 00:00:00 2001
From: Benjamin Frandsen <benfrandsen@gmail.com>
Date: Tue, 22 Nov 2016 11:31:02 -0800
Subject: [PATCH 1/4] updated mpdf tutorial with information about extracting
 ordered moment size

---
 cmi_scripts/mpdf/introTutorial.ipynb | 11212 +------------------------
 1 file changed, 81 insertions(+), 11131 deletions(-)

diff --git a/cmi_scripts/mpdf/introTutorial.ipynb b/cmi_scripts/mpdf/introTutorial.ipynb
index e04dd4d..cbe60b0 100644
--- a/cmi_scripts/mpdf/introTutorial.ipynb
+++ b/cmi_scripts/mpdf/introTutorial.ipynb
@@ -107,796 +107,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ben/anaconda/envs/mpdfdev/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
-      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Import the necessary libraries\n",
     "import numpy as np\n",
@@ -935,788 +150,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### make a copy of the magnetic structure\n",
     "mstr2 = mstr.copy()\n",
@@ -1768,35 +206,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[Mn2+ 0.000000 0.000000 0.000000 1.0000,\n",
-       " Mn2+ 0.000000 0.500000 0.500000 1.0000,\n",
-       " Mn2+ 0.500000 0.000000 0.500000 1.0000,\n",
-       " Mn2+ 0.500000 0.500000 0.000000 1.0000,\n",
-       " O2-  0.500000 0.500000 0.500000 1.0000,\n",
-       " O2-  0.500000 0.000000 0.000000 1.0000,\n",
-       " O2-  0.000000 0.500000 0.000000 1.0000,\n",
-       " O2-  0.000000 0.000000 0.500000 1.0000]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### First we have to import the loadStructure function from diffpy.Structure\n",
     "from diffpy.Structure import loadStructure\n",
     "\n",
     "### Now let's create a diffpy.Structure object from a CIF file for MnO. This has all the atomic information,\n",
-    "### but none of the magnetic information.\n",
+    "### but none of the magnetic information. Note that a .stru file generated from PDFgui or diffpy.Structure\n",
+    "### would also work just as well.\n",
     "mno = loadStructure('MnO_cubic.cif')\n",
     "\n",
     "### As a refresher, let's take a look at the mno structure object.\n",
@@ -1812,7 +233,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "collapsed": true
    },
@@ -1850,36 +271,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Coordinates of atoms and spins for Mn2+\n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ben/anaconda/envs/mpdfdev/lib/python2.7/site-packages/diffpy.Structure-1.3.2-py2.7.egg/diffpy/Structure/lattice.py:125: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n",
-      "  if [a, b, c, alpha, beta, gamma, base] == 7*[None]:\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Now we can create a MagStructure object and load mnoMag into it.\n",
     "mnoMagStruc = MagStructure()\n",
@@ -1898,788 +294,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Now we can create the mPDF calculator and load the magnetic structure\n",
     "mc = MPDFcalculator()\n",
@@ -2705,815 +324,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Coordinates of atoms and spins for \n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Running checks for  MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n",
-      "Since you are not using a diffpy Structure object,\n",
-      "the spins are generated from the makeAtoms() method.\n",
-      "Please call that method if you have not already.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ben/diffpy.mpdf/diffpy/mpdf/magstructure.py:158: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
-      "  ocoords = np.mgrid[-dim1:dim1+1, -dim2:dim2+1, -dim3:dim3+1].transpose().ravel().reshape((2*dim1+1)*(2*dim2+1)*(2*dim3+1), 3)\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Create the magnetic species and turn off the diffpy.structure option.\n",
     "mspec = MagSpecies(useDiffpyStruc=False)\n",
@@ -3545,788 +360,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Now we can set up the MPDFcalculator and plot the mPDF.\n",
     "mc = MPDFcalculator(mstruc)\n",
@@ -4349,842 +387,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Coordinates of atoms and spins for big\n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Running checks for big MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n",
-      "Coordinates of atoms and spins for small\n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Coordinates of atoms and spins for big\n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Running checks for small MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for big MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n",
-      "Since you are not using a diffpy Structure object,\n",
-      "the spins are generated from the makeAtoms() method.\n",
-      "Please call that method if you have not already.\n",
-      "Since you are not using a diffpy Structure object,\n",
-      "the spins are generated from the makeAtoms() method.\n",
-      "Please call that method if you have not already.\n",
-      "No magnetic form factor found for that element/ion.\n",
-      "Using generic magnetic form factor.\n",
-      "No magnetic form factor found for that element/ion.\n",
-      "Using generic magnetic form factor.\n",
-      "Running checks for small MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for big MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Create the first magnetic species and turn off the diffpy.structure option.\n",
     "mspec1 = MagSpecies(useDiffpyStruc=False)\n",
@@ -5217,796 +424,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'small': 0, 'big': 3287}\n",
-      "[0, 3287]\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Now we can set up the MPDFcalculator and plot the mPDF.\n",
     "mc = MPDFcalculator(mstruc)\n",
@@ -6040,801 +462,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Running checks for helix MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### We will load in a structure from a CIF file and modify it to simulate a 1-D material.\n",
     "astruc = loadStructure(\"MnO_cubic.cif\")\n",
@@ -6872,788 +504,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Now plot the mPDF.\n",
     "mc = MPDFcalculator(mstruc)\n",
@@ -7684,35 +539,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Coordinates of atoms and spins for Mn2+\n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n",
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Create the diffpy structure, MagSpecies, and MagStructure\n",
     "mno = loadStructure('MnO_cubic.cif')\n",
@@ -7735,788 +566,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Default mPDF calculator\n",
     "mc = MPDFcalculator(mnoMagStruc)\n",
@@ -8524,7 +578,7 @@
     "\n",
     "### Adjust qmin and qmax to simulate termination ripples\n",
     "mcQ = mc.copy()\n",
-    "mcQ.qmin, mcQ.qmax = 0.1,25\n",
+    "mcQ.qmin, mcQ.qmax = 0.1,25.0\n",
     "rq,frq = mcQ.calc()\n",
     "sclfactor = fr.max()/frq.max()\n",
     "frq *= sclfactor\n",
@@ -8534,7 +588,7 @@
     "\n",
     "ax.plot(r, fr, 'b-', label='Default')\n",
     "ax.plot(rq, frq, 'r-', label='With qmin/qmax')\n",
-    "ax.plot(r, frq-fr-7, 'g-', label='Difference')\n",
+    "ax.plot(r, frq-fr-35, 'g-', label='Difference')\n",
     "\n",
     "ax.set_xlabel(r'r ($\\AA$)')\n",
     "ax.set_ylabel(r'f ($\\AA^{-2}$)')\n",
@@ -8545,788 +599,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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3Kj0v3r1qiJuK1SogEmTJiFVqlT+zby9vRUGa9euxdevX1GuXDn06dMHJUqU4BGw1k8h+5MACZDAHxKgAKQA/MMt85/mFi0Ab926pXgAdUfAXbt2xY0bN3Dnzh1FWA0bNkz5kyFDBrRp00YRhyKsSpYsCWdnZ4wdOxbSR8Si9BPBJSLryJEj/qBFJMmdQhlDnrNt2zaIKNy1a5fibRT7/v27IgxFWImAFNEmwvLixYt4+vRpEAHYv39/TJ48Gd27d1f6y78PHDhQEWsnT56ElZWVMqbMM23atMiSJQscHR0hnsvevXsjWrRokHXLv4vNmTMHnTt3VtYnAtbLywsuLi7KXEQQxooVS2nXvHlzrFu3ThHFBQoUwL59+7B69Wo8efIEixYt4h1ArZ9E9icBEiCBPyBAAUgB+AfbJdimFisAAweB6MjIfcDNmzcjf/78ypdE/IkHcNq0aYp3Tmfv379HsmTJ0LRpUyxYsMD/6+LpE6Gk8yD+StzX11fxAor3z9bW1t+TOG/ePHTs2BGnT59GwYIFlW7SNleuXLh586a/AJSgCxGSMi8RfTo7deqUEsAic69Zs6a/AMyUKZMiTKNGjap8bcOGDWjQoIHiyRQx++nTJ+UOZP369SFz0Jk8R0SreAW7deumCGLxGo4ZM0bx+ulMhKMIVQpArR9D9icBEiCBPyNAAUgB+Gc75r+t9ScAfX0BLy+t8wm5vwRm+Hm4tDxId7dOBJMIIBFbz549wz///INLly7h2LFjiudMJwBFEKVMmdL/keK9E6+feMHKli3r/3Xx8NnY2MDJyUkRT2IXLlxQPGrnz5/H69evlWeJicdPxJmYeN/k/qFE+wY2EZ8yB10QyPz589GhQwfcu3cvSFCIjClH0O3atcPEiRP9BaAINFmTzkTIyXPFcydCcP/+/cpdR/l/8WrqTMYTESwCUgJlli5dqkRNS6CMeBV1dvToUZQuXZpHwFo2I/uSAAmQQDgIUABSAIZj2wTpoj8B6OkJxIundT4h9/fwAOLKlLWZTgD+GgQiEcBylCr3/FatWuUvAOX4VOdFkyeLp0/Snri6uiJbtmxBJiOeQfHwiWdQjkfFi5cjRw7lyFZSucgRrBwVyzHsgwcPlL7S/u3btzhz5kyQscS7JiJOJwDleFj6Bmdy9CtzEm+cmO4OoIhInf2atmXlypVo1qzZb8crVaoUDh48iPHjx2PAgAH4+PGjInB1JncQZf1MA6NtP7I3CZAACfwpAQpACsA/3TO/ttefADRDD+CvAlDgFC5cWBE6kgpG5wGUO3q6O3PSRjyA1apVU7x2ZcqU8Wf6qwdQd7QrQlCEoc7Ea/b48WN/Afg7D6Du+ToBqBOE4nm0s7P7z7sXL2CaNGnCLAD37NmDKlWqKB6+XwNDZBBJhSNewGXLlsHBwYEeQK2fNvYnARIgAT0RoACkANS6lfQnALXOxIj9f+cB/Pz5s+KlE6/doUOHfisAdXcAW7ZsqdyB05nOMyiBHuLVmz59Onr06IEXL14ogR1icgwrHkHxNOo8gLqjXbnLV6hQIaWdHMPmzJlT8RTqBKC0l6NpiQIO7g5jYIRh8QBKwIccbYt3UsTm70x3B1A8kH379vVvJhHKMhfeATTi5uWjSIAESICJoJU9oIY80sJLwGIFoAgoiWoVASRi6/nz55gxY4YSwStfr1Onzm8FoMCWIAyJApYgCRF7cp9P0rtIFLCkchGTr+XJk0e5JygpVOSeoUTRynGyBIPoBKB4GOUoVY6gR40ahcSJEyvRuXIf8dcoYHnu1KlTlaAUOaKNGTOm4k2Ue3xyB1C+JhYWASjtRMDJWOKFFG9gvHjxlGcKB/FuNmrUSBlPjpclBYzcZ5RAlb179yr/7e7uTgEY3k8f+5EACZBAOAnQA0gBGM6t49/NYgWgVNgIbOKhE4+bpFmRO4Bi4hWT0nByBzDwEbCun0QHi1D7NQ+gpJDRmQRRDBkyRAnwkAheEYlyhCwBFBJUoTP5d10eQEm90qRJE+VYVqKDf60EIp5GSSUj+Qnl7p94EyUvn8w9efLkypAiMuW+YGDPntwBlLQ3v3rsdu/erQStSMDKjx8/lMAYye8naWMkaERMxKmI2DVr1ig85HniDSxevDgFoNZPIfuTAAmQwB8SoACkAAxpyxQBMBKA5BX5CeA6gOK/dLBIAfiHnzM210CAtYA1wGNXEiABEvgNAQpACsDffThE/O0EIMnr1kuuYQCS3O4cBSC/nxiTAAWgMWnzWSRg2gSePweSJtVLNi/TXqgRZkcBSAH4u212FIDkFAnI2ht8S3oAjfBBteRHUABa8tvn2kkggMCnT4DcjpFKmrVrk4xWAhSAFIDB7SFJ1CYZmScBKA0gAwA3AGMAbKQHUOvHjv3/hAAF4J/QYlsSiLwErl4FcucGRo6UILrIu05jrYwCkAIwuL2WAoA7gJcAqgG4DKAWgNUApNxD4GzD9AAa69Nqoc+hALTQF89lk8AvBA4cACS+ztERCFSgiJzCSYACkAIwuK0jou4DgLEAnAM12A3gEoABgb5GARjODx+7hY0ABWDYOLEVCUR2AmvWAJJVql49YN26yL5aw6+PApAC8He77C4A+YiFSQA6OjrC2tpaGUtqw8ofMf7wNvyHOLI/gXsosr9hro8EwkZAvH5duwJSPOngwbD1YaugBKR6k/wRk3Rckg4MgNRg9bREVkwEHfxb7wagP4AqAK4CqBHoCPg8PYCW+FGJmDVTAEYMdz6VBEyNgIsLMH06kDEjcO7XfBSmNlkzmA89gPQAhrRN+wFw9PvtQDyCQwFs/6UDj4DN4INuzlOkADTnt8e5k4D+CHTuDJw+DXh7Azdv6m9cSx2JApACUOvepwDUSpD9QyRAAcgNQgIkIASaNAE+fgQuXgSePCETrQQoACkAte4hCkCtBNmfApB7gARIIFQCtWqpSaAlGOSDhCnSNBGgAKQA1LSBAFikAFyyZAlatWrlz87W1hZSCzhv3rxo3Lgx6tevr5WryfYvXbq0Utf4oJFuYdMDaLJbgRMjAaMSqFABKFIEGDUK+PGD1UC0wqcApADUuocsVgC2bt0a69evR4oUKfD161c8fvwYO3bswNq1a1GmTBls374dMWLE0MrX5PrL2qysrCgATe7NcEIkELkJFC0KNG0KdOkCSFUQW9vIvV5Dr44CkAJQ6x6zaAF49+5dpE+fPgjDTZs2oV69eujSpQumTZumla/J9acANLlXwgmRgEUQkCogQ4aoeQBfvgQSJ7aIZRtskRSAFIBaNxcF4C8CUIDWqVMHu3fvxrt37xAzZkwMHToU27Ztw71795R8iX/99RdGjx6NwoUL+/M/cuSI4jkUAblr1y6sW7cOPj4+cHBwwKRJk3DhwgX07NkTly5dQtq0aTF58mRUrFjRv7+0O3DggOKBdHJywrVr15A0aVL06tVLEaOB7eHDhxg4cCD27dun5GrMli0bXFxcUPuXApurV6/GsGHD4ObmhkyZMmHEiBGKqKUHUOvHhv1JgAT+lICkf/n3X6ByZTUKOIMUKaWFmwAFIAVguDePX0cKwGAE4Pz589GhQweIqCtevDjatWuHkiVLInXq1Pj06ROWL1+OjRs3KqIuR44cCkqdABRxJwKySpUqOHr0qCK6RMCJuOvbty+SJ0+ufE2E4KNHj5AgQQKlv9xJlDHt7OzQv39/ZMiQASLgFi9erPxp0aKF0u7JkyfIly+fIg4HDBgAe3t7rFmzBosWLcKWLVtQvXp1pd3+/fuVhN41atRQ1vL69WsMHjwY379/R9asWXkErPWTw/4kQAJ/RCBZMmDzZqBKFeDQIbUuMC38BCgAKQDDv3vUnhSAwQjAvXv3onLlyoqw+jUgRLx6vr6+ivATkTdlypQgArBNmzaYN2+e/3vJnz8/Ll++jOPHj6OI3IAGFO9e7ty5IcEozZs39xeAS5cuVURf4GeKl1COqsWLJybjy/3E27dvK2JRZ9LuzZs3uCg5FgAUK1YMHh4ecHV19W9z5swZZQ4SCMIgEK0fHfYnARL4EwLx4gHHjwPVqgGrVsn3qD/pzba/EqAApADU+qnQmwAUUeT1zUvrfELsH8c6jnJ8qdVEeEkQSHB3AGVsKbUj4k6OY+U+oHjT5Mj36tWryrGwmMxDPGw7d+4MIgDl6Ldu3br+U2zatKlyfCwfVp2JF04CTEaOHAlnZ7Van3gAV6xYAW9vb0SNGtW/7cKFCxUPpLu7u+I9TJkyJSpUqADxUupM2E+dOhX9+vVTRJ9ENdvY2CgeQjm+Dmxy51G8lBSAWncR+5MACYSVgK8vED06cOeOegQ8ezZQrlxYe7NdcAQoACkAtX4y9CYAPb96It5YKUloOPPo74G4MWTK2iw0Aag7ApYjXBFTf//9tyIIRTQmS5ZMEWjiiYsfP76/kNIdAYtYLFu2rP8ERdjJ8a9EGQc2ScUyaNAgDB8+3F8Aiph8KbejA5lEJtesWROnT59GwYIFlTuIP3/+VLyQv5qI0gcPHijiT46IpU5kp06dgjQTD6D8OwWgtj3E3iRAAmEn8PUrEDMm8OIFIOlgxoxRPYG08BOgAKQADP/uUXvqTQBGJg+gBFNIgMXbt2/9AyfkwyaiTWfiRRNvmk5I6UMAhsUDKAJU7iPKPcHgRGCuXLkUgUoPoNaPBvuTAAnoi4AcnCRMCHh5qZ6/vn2BQAcl+nqMRY1DAUgBqHXD600Aap2IMfuH5AHcsGEDGjRogB49emDixIlK5O6CBQvw/v17fwEooq98+fJB7tKJABTPnwjH8HoA5Q7gqlWrlOfrTI57JfpYdwdQPIriDZR7hSHlKZTglQ8fPvAOoDE3Fp9FAiQQLAEp/ZYqlZoAWg5I2rUDmjUjLC0EKAApALXsH716ALVOxJj9dZVA5L6e3Kn79u2bckQrwRXyNQmo2Lx5s3LcKgEhcvzbpEkT5Z6eBF/I3T3xsmXMmFGvHkCJApZj5T59+ihpW1auXIlly5YpwSLN/L5byl1AST8j85boYvFEijiVYA8Ribq7gXLsLHcUq1WrpkQBv3r1SrkPKPcPs2TJwiNgY244PosELJzA3btAzpyAHAVXqgRIsaW2bS0cisblUwBSAGrcQvo7AtY6EWP213kAdc+UXH+JEydW0qtI0IakcQlscpdO8va9ePECOXPmxJgxYxQRKHfuRGiJheQBFI+hpHwJbCIg5Q6g5OkT090VlMCTbt26KYIuSZIk6N27NxwdHYP0ffbsmSLmJN+gpHdJmDChMq+WLVsqQlVnEsUs7SRvoIhVmbMuD6Bu3obmzlJwhibM8UnA9AlIMgKpBCKxcFITWO4B/pLe1PQXYWIzpACkANS6JS3yCFgrNEP0/12wiCGeZcwxKQCNSZvPIgHTJHDhghr9+/o10KgRUKAA0Lu3ac7VXGZFAUgBqHWvUgBqJain/hSAegLJYUiABEyOwMmTgFxtlruADg5qFZDBg01ummY1IQpACkCtG5YCUCtBPfUXARjcUbGeho+wYegBjDD0fDAJmAwBqfwhd/7u3wc6dlQjgkeNMpnpmeVEKAApALVuXApArQTZP0QCFIDcICRAArt3Az17AjduAD16AJJRa9IkctFCgAKQAlDL/pG+FIBaCbI/BSD3AAmQQIgEtmwBpCjRpUvAgAGAhwcwaxahaSFAAUgBqGX/UABqpcf+oRKgBzBURGxAApGewNq1wOTJwOnTgCQ+kKQICxdG+mUbdIEUgBSAWjcYPYBaCbI/PYDcAyRAAiESWLYMkPLlR44A48cDly8DK1cSmhYCFIAUgFr2Dz2AWumxf6gE6AEMFREbkECkJyDiT7yAe/cC06cDhw8DGzdG+mUbdIEUgBSAWjcYPYBaCbI/PYDcAyRAAiESmDkT2LUL2L4d+PdfYNMm9b9p4SdAAUgBGP7do/YMkwCU8mNx40pTGgn8GQH5JpUqVSp4eHhwD/0ZOrYmgUhDYMoU4PhxYMMGYMkSYOlSwK+IUqRZo7EXQju8a6kAACAASURBVAFIAah1z4UoAL98+YJ06dIpJdBoJBBeAkmTJlXqFEvJPRoJkIDlERg7Frh6Vb33t2qVGgF87JjlcdDniikAKQC17qcQBaAMLiLw27dvWp/D/hZMwNramuLPgt8/l04CEvn78CGwaJHqBRw3Djh7lly0EKAApADUsn+kb6gCUOsD2J8ESIAESMCyCTg7A+/eAXPmqPcABw1SI4Fp4SdAAUgBGP7do/akANRKkP1JgARIgARCJNCrF/DjBzBtmhoJ7OQE3LxJaFoIUABSAGrZPxSAWumxPwmQAAmQQKgEunQBbG3VHICSAqZNG7UuMC38BCgAKQDDv3voAdTKjv1JgARIgATCQKBdOyBpUmDECODUKaBBA8DdPQwd2eS3BCgAKQC1fjx4BKyVIPuTAAmQAAmESKBFCyBzZvXu34ULQJUqwKtXhKaFAAUgBaCW/SN9KQC1EmR/EiABEiCBEAk0bAgUKAD06QNcuwaUKAF8+EBoWghQAFIAatk/FIBa6bE/CVgoAV9fwMrKQhfPZf8xgdq1gbJlgW7dgDt3gDx5gM+f/3gYdghEgAKQAlDrB4IeQK0E2Z8ELIxAq1aAm5t6mZ9GAmEhIEe+IgI7dFDzAWbIAPz8GZaebPM7AhSAFIBaPx0UgFoJsj8JWBgBnedPvIA0EggLAfH+yT1ABwfg2TMgRQo1LUzUqGHpzTbBEaAApADU+smgANRKkP1JwMII6ASgHOHZ2FjY4rnccBEoVgyQVDCNGwNv3wL29uoRMPdPuHAqnSgAKQDDv3vUnhSAWgmyPwlYEAFvbzWfm9jdu0DGjBa0eC413AQkAESqgdSpA3h5AXHjAu/fA3Z24R7S4jtSAFIAav0QUABqJcj+JGBBBHTHdwkSAHv2qJGdNBIIjUCuXMDYsUC1aoCUlo8RA3j5EkicOLSe/PffEaAApADU+umgANRKkP1JwIIIuLoCRYsCyZMDM2YAFSpY0OK51HATkByAs2YB5csDcnc0ShQ1EXTKlOEe0uI7UgBSAGr9EFAAaiXI/iRgQQSOHlUv80tVh5491YoONBIIjUCaNMDy5Wr+PzFra7UWsEQD08JHgAKQAjB8OyegFwWgVoLsTwIWRGDzZmD4cCBJkoC0Hha0fC41nATkF4atW4FChdQB4sQBzp4FsmUL54DsxiAQUABq/RhQAGolyP4kYEEEFi4EVq5U72799RfQv78FLZ5LDTeB+PHVvJG5c6tDJEwIHDigJoSmhY8APYAUgOHbOfQAauXG/iRgkQQmTQJOn1YFYOzYwLhxFomBi/5DAhI5fvEikDWr2jFZMmDLlgCP4B8Ox+ZMA6PsARYj0vZRoAdQGz/2JgGLIjB0KPD4sRoE8uoV8O+/FrV8LjacBCTh8717QLp06gBp06p3AosXD+eA7MYjYApAzZ8CCkDNCDkACVgOgb59gU+fgFSpgGvXgBUrLGftXGn4CEjJt2jRgKdP1V8cxCQqePZsoFy58I3JXkwETQ+g9k8BBaB2hhyBBCyGQNeuag43ieqUO1wSFEIjgZAISMWPWLGAN2/Uu39iOXMCEyYAUiOYFj4CvAPII+Cw7JxNAGoBKA/g4C8dKADDQpBtSIAEFAJt26r3t+QIb80aYO9egiGBkAlIxQ9JHC4VQOTeqFj+/MCQIUAt+clECxcBCkAKwNA2TgsATQBIulb5QwEYGjH+OwmQwG8JNG0K5MgBpE+vJoI+cYKwSCBkAi9eqL80SAWQ6NHVtkWKAD16MI+klr1DAUgBGNL+kRzrxwHINdvH9ABq+aixLwmQgBCQWq6SzFcS+Lq4AJcukQsJhEzg0SM1+EPuAlr5hW2WKgW0awc0a0Z64SVAAUgBGNLe2QNgLYAFAHwoAMP7MWM/EiABHQG5s1W7NpAxI9CpE3DnDtmQQMgEZI9I/j9v74B2FSsCjRoBrVuTXngJUABSAP5u73T2u/dXya8BBWB4P2XspzcCkghWSkBJLVmaeRIoXVr9oZ0pE1C/PvDkiXmug7M2HgGJFhev8YcPAc+sXh2oVk39JSKymBxpN28O5MtnnBVRAFIABrfT0vsd/RYG4E4BaJwPI58SOgE5/okZM6gnIPRebGFKBAoXBnr3BrJkAeQYTy7400ggJALnz6ti7+XLgFZ16wIlSwJOTpGDnaxNyt01aWK81EgUgBSAwX16WgKYK4nCA+VJlOB7DwBrAHQM1EmJAnZ0dIS1uGYAVKpUSflDIwF9Evj6VRV/Yr6++hyZYxmTgJR/Gz1areggwSDyXmkkEBIBCRRq3FhNIK4z+W/xlPXpEznYHT+uejnLlwf27TPcmvbs2QP5I/bt2zfMnDlT/hrP7+e94R5soiOzEsh/X4z8mE3wy5floKYhANmagRzxYBoYE93YkW1achFcUoeISSJhKQ1FMz8CcvQ7Zw6QPbua1Pf7dzXJL40Efkfg4EGgQwfg7t2AFi1bqtcIBg2KHNykPrYuQt7V1ThrogeQHsCw7rSfTAMTVlRsZwgCcgxUuTLw7h3w8CGQOrUhnsIxDU0gZUpg7VrV+2dnB3h4AHHl10gaCfyGwK5d6rWB69cDGrRvrx6ZDh8eObBJSqQxYwAfH0DS3hjDKAApALXuM3oAtRJk/zAR0P0QkG+O+/cDefOGqRsbmRgBqeQg708qOcitkWfP1BxvNBL4HQGpFiNC7+LFgBZduqjVQcaNixzcpEb2kSPAsWOqV1yX7saQq6MApADUur8oALUSZP8wEVi6FFi4UBUMs2apd2Vo5kdAju7lB7ncARQBePOmmhOQRgK/IyAVY6ZOBU6dCmjRs6d6F3jKlMjBTUokSqLrf/9VA6PEO25oowCkANS6xygAtRJk/zARmDQJOH1aTRsikX+SA4xmXgTkB3aUKOoRvtQCjh9f9XpIYAiNBH5HQPfLn6SB0tmAAYCnJ6DGMJi/yf0/8YqLJ1COuiVPpqGNApACUOseowDUSpD9w0Sgf3/1G767u3oX0NExTN3YyIQIfPkC2Nio6TwSJwZSpAA2bAD+/tuEJsmpmByBefOA9esBv+BVZX5SRebpU2D+fJObbrgmJN/TpErOsGHG+0xQAFIAhmuzBupEAaiVIPuHiUDnzkC8eMDz52odWSkETzMvAhLAI3cARcjHiQNkzgzMng2UK2de6+BsjUvgn3+AvXuBrVsDnjtqFHD7NiDewchgBQsC8kuueADlXmPVqoZfFQUgBaDWXUYBqJUg+4eJgIMDkCK9h3I/JgbiRZq7P2FafCRpJB4biQLWpX7JkwcYMQKoUSOSLJDLMAgB3fWPdesChp84EZDMAKtXG+SRRh9U98vQ4MHqFZeGknTNwEYBSAGodYtRAGolyP5hIiBlw7bljAN735yo+uyUclmaZl4E7t1T8//JZXexYsUAufzO+5zm9R6NPVtJHH7jBrB8ecCTp08HDh0CNm0y9mwM8zzJiSlrkZMN+V7Xtq1hnhN4VApACkCtu4wCUCtB9g8TgarVfLGrUBSlbePbvpDEqTTzIiA1XYsXV3P/iUkkt5S+ktrAtNAJiOdUSulJFLwl3ZuU+34S/LVgQQAjSSYuR8I7d4bOzRxaSC5MiXKWtcovRlIX2NBGAUgBqHWPUQBqJcj+YSJQtMJrnCqeWGlb9eIX7NgSI0z92Mh0CJw9C9SsGZDoVo5+GdAT9vdz4QJQoADQvXvkSX8SltXrAsBE+Ops0SIovwQasmxaWOamjzYSHR81KuDmpt4BTJfOOHecKQApALXuXwpArQTZP0wEslc8hacla8Hr5xv8ffoRTu5KFaZ+bGQ6BCTli9zllB90Yg0aAIUKqVUeaKETkCPQ5s2BatWA7dtDbx9ZWui8YYFz/q1YAcydCxw9av6r/PxZTWr95o0aBRwjBjBhguHXRQFIAah1l1EAaiXI/mEikKrSOsSqMBHPvtxHqsN7cX1/vjD1YyPTIbB7NyAJfI+dfwvvH94Y2DWlku9MLr7TQicggQ8DB6pl9AJXxQi9p3m3kJRPEjU+dmzAOiQgRBccYt6rU9MiSVk7SZMkFU/evlXrZRvaKAApALXuMQpArQTZP0wE7CvNRcbqW/DssxuwZyoeH6wUpn5sZDoE5JL7yJHAh5YZ8MzrGRyeeCvJoOWSPy10An36AAcPAq9eqfkwLcUkIEJyRop3TGdy/0+OSyODEL5/X62MI8FRkgJG7sqKh9PQRgFIAah1j1EAaiXI/mEiELvyGJSsdx3PPj2G++b2eHuoWZj6sZHpEJA7W3KP60QFK2VSTh7fYeUbjSl9wviKWrZUa8SuWqV6i4xRLzaMUzNoMzn2zpYNcHYOeIx4k3v1UqtmmLtduQKUKQNInkypbCIJrwPnPDTU+igAKQC17i0KQK0E2T9MBKyr9UGDJl/x/NMTnFpTAp8PGCFMLkwzY6OwEpAozhVrvuBQMRulS6dv9+HzNr1RjrvCOkdTbicBMxI5LZ7ADx/UxOiWYHJXVKKfRfDpTDyhHToAd++aP4ETJ4DGjYHHj9XE1hLgIiluDG0UgBSAWvcYBaBWguwfKgGlhuz/2sCpVUq8/PgCa5ckxM+9PDcMFZyJNZCKDhuO3sCZ3AVgF9MO1T9vwNd7RbBkiYlN1ESnkzevmiZEkgS7ugKZMpnoRPU8rVq1gAoVgC5dAgYW0SQphB490vPDImA48fhJoIvkOty4Ub3rKBHzhjYKQApArXuMAlArQfYPlYC3N2Db6n8Y2a40nn98hpn/fsLXTf/A2jrUrmxgQgQksnH7zX14ka8LbKPbIs+Hofh0oRbWrjWhSZrwVNKkUZMhi7dozRo1X5wlmHg+69YF2rULWO25c2pKISkNae4m9bBF9Mma5GhbouJF4BvaKAApALXuMQpArQTZP1QCkh4hUZ/SmO/YBo8+PMKImXfxbuESJYCAZj4EJMLxwMs1+J5vGuLEiAP7l/Xgebgdtm0znzVE5Ezt7dWauC1aqGlCqlSJyNkY79lyP65VK3XdOgt8b854MzHMk5YtA+bNU1PaSKokWeuDB4Z5VuBRKQApALXuMgpArQTZP1QCcjcmzZg82OI0Ag/eP0CPaYfxeMImpGIqwFDZmVKDAQOA419nIV6BnYhvEx+fHmWB5/ZB2L/flGZpunOxsQEuX1YFQrdullNCr2jR/9bHvXkTKFgQ+PjRdN9XWGcmZS3l6Fe8f+IFlATpL16EtXf421EAUgCGf/eoPSkAtRJk/1AJyDf7HHMz4oDTPLh9cEP7GStxrc9+JTKQZj4EpILFOZsRyFj4HhLZJoLrzW/wWjsdcp+LFjKBnz+BaNHU9C9yFPq//wHt21sGtfz51VyRtWsHrFc8ZLrUKeZOYdo04PBhtRawRDUXKQJ4ehp+VRSAFIBadxkFoFaC7B8qASmBVWhNMpxy2qIcATedOREnWp1RPAA08yEgguVK0h4oVsxKEYC7L7nCa/GKSJHLzdBvwcsLkHqxkiqkY0fV+2UpFVRy5vzvkbfUBpYTABHGUdQS4WZrcv/v6lW1tJ1UyZHgHqn7bOg0PxSAFIBaPzQUgFoJsn+oBORuTOk9cXHN6RTcPd1Rc2ZP7Kl5Q8mdRTMfApLPzTVTC9QtnRnxY8bH8tN78H7WVty6ZT5riKiZypFgsmTA16+AVMaQv8udSkswEURS9q1s2YDVSjLsJEnUfIhSOs2cTSK7RdBKmiRdVRB5z4YOcqMApADU+rmhANRKkP1DJbBrly+qnokKt+4P8NTzKcrMbIQNxd2VuzI08yFQrx5wI091dKlUFXGs42Dy4QV4N/lwpEjlYei3oKsWIZ4h8fzJ/8vRoSVY6tRq8utihb7j3I39yJurAj55RYOdnXpUKmXizNkkr6NkOpA0STpP7/v3UNZnSKMApADUur8oALUSZP9QCaxc542mN2zxqvcrvPj4AnlnlMCKXB+UfGg08yFQrRpwp1hJDK3eAbGtY6PfrmF4N+aiUtqMFjIBOSIsWVJNAC2ePzkqlITBlmCJEwO7dgHxJ1ZGhqx7sCCPCxpXHApbW+D1a0Cio83ZJL+hrGX8eODHDyB6dODpUyB5csOuigKQAlDrDqMA1EqQ/UMlMGvxGzg+SoTPzp/x8tNLpJuaAQtS/0Dr1mpJMZp5EJAjvPsV8mH6/1wQN0ZctNzQDu+H3VO8HrSQCZw6BYgHVYTB1KnAsWOA5I+zBJOKJ2c3uON697SoW98H7bwyY/a420pQjDGEkqEZt2kDpEwZUOtYjrQlGCRjRsM+mQKQAlDrDqMA1EqQ/UMlMGrmIwx6nQ4+Lj/xzvsd7CfYY1LCj+jZJVaofdnAdAhIdOPDGpmxvNFspRJIpWVV8GHgK8XrQQuZgKTK6dwZuHMHWLhQDRiwlPQ5IojcB87BnAfj4JLuIUo9s8bhOV8QNZoV5Gg8bVrz3j1S0eSvv4D+/dV1SH5TyQcoXzOkUQBSAGrdXxSAWgmyf6gE+k64jilef+P7cC98+/kNMUbGwGCb5xjeN2mofdnAdAjkyQM8rp8cu1puQgKbBMg1Oxe+Dv6Cb9/UYy/a7wls2aJ6iC5eVKuAiBdQvIKR3ZQykFEAr4Zt0DHzGTxOY4eXV07idtfbsM2dCZcuAVmymDcFSelTurSa61AsRQrVu/v334ZdFwUgBaDWHUYBqJUg+4dKoMPws1j6vSa8R6jZUaMOjYHOcMWMoRZSDDVUQubRQH5QP2keD2fbn4S9rT2STkoKjPgCj3cxlBQntN8TEI/f7Nnq0e/27YCzs5o6JLKbRPlKAuzv2f5ClTZWyJGjDBYenwHP3Kth166+wiNXLvOmUKmSWupOl9cxuKhnQ6yQApACUOu+ogDUSpD9QyXQZOAh7IjSFh4j7ittbVzs0eDrXiwZmy/UvmxgOgRSpfbFszbRcN/pPpLESgLb0XLz/TVePLBXUnrQfk9ASoWJV0iqRRw6BLRtC+X4M7KbhweQzO4zPkWJg7xTs8KpeG+03toaH30HIN2s0UpwiCSKNmeT4B4Rf82aqavInRsYNQqoXt2wq6IApADUusMoALUSZP9QCdTotR1nYg3Eq+FXlLZ2LulQxnMxNk0pFWpfNjAdAvZJvfG2ky1e93mNhDYJYT3SGj+n3saDC+nN/h6XoSkHDvw4exaoWdM45cIMva7Qxpe8eJWTXsLFeGWQYrAtNjTYgJILi+PWnUoofXQn1q5VK2eYs0lSb7n/J15AMVlPjx5AgwaGXRUFIAWg1h1GAaiVIPuHSqBs1zW4m3Aa3IeeVNomHfYXcr0ajX0zDfwrcqgzY4M/IRAr0Wt87pIY3gO9ETNaTCQcnxCf5xzAxR15WNYvFJDiEbp9G1i6VI0QlfthlhA9LXXAe6VZhzUFxiFGzSu43eU2SswuiHW746L5UzclebLcnzNnk0onkgKmalV1FeXKAZI03cHBsKuiAKQA1LrDKAC1EmT/UAkU6rgA71Osxt3B+5S2aUcURbLHTjg1j4kAQ4VnIg3kMn9UezdEccqE74O/w8rKCummpcP7hUtwcFFJ5ONpfohvSu78SXJguQf48CGQPr1aBs3Q5cIievtI1POyHGPQs8F5JMi8EV4DvPD3rHyYMPcBevt+xZTpUVGxYkTPUtvzM2QA5s+Hf2UjSXBfpYoa9W1IowCkANS6vygAtRJk/1AJ5Go7HVbpD+Kq82albbbRFWB9pzGuLG4dal82MA0CEukbI9U1xO1eAh4DPiiTyj0nN54tG4XN46ujWDHTmKepzkIiRCVSeuJENfmxJEf+/FkNkIjMdu0acCl/WxTtFwM5YszHl4FfUHxBMXSZfhoLvz+G04SUBr8rZ2i+kvB548aAqF9JcF+oENCrl2GfTAFIAah1h1EAaiXI/qESyOgwBolyXMepPsuVtvnG18bHa+VwZ1nXUPuygWkQkMv8djlPI5lTXTzr/VSZVIlFJXBvdUcs7d0UFSqYxjxNdRYS9CHpQSQVjAi/WLGAN2+AhAlNdcb6mde5c8D3YqUR858yqOwxE6/6vELVFVVRc8lpXHDfisoji/vfndPPE40/ipR8k3rnurx/rVqpHt7Bgw07FwpACkCtO4wCUCtB9g+VQMoWg5A1/2vsd5qrCocpTfHofE48XjEg1L5sYBoEXrwAkhXbj0zdHXGn621lUvKD/Nq62pjZur0S1ED7PYHGjYG8eYG+fQHlOD2qehQsdXIjsx0/DqQrnRp3N/ZG24fTca/bPTTZ0AS5N5/C1zMjkGlYMwgbczZJdO3qCkj6FzFHRyhpkcaMMeyqKAApALXuMApArQTZP1QCiZr1QLFiVtjcabLStsrMDrh4PBFerhoZal82MA0CDx4AmWpsRh6nEbjQ/oIyqfrr6uPcxiIYV7sn6zqH8ppEIEu+OBEHYrFjA+Idy5bNNN6voWaxf89PlK4cAzuPzMbQm7NxscNFdNreCXb7jyHT1kaI6jIILVsa6umGH1fucUpJO3d3tRycWJ8+UJKjT5tm2OdTAFIAat1hFIBaCbJ/qATiNWuHmmWTYlnrEapwmN8T+/b74sPqKaH2ZQPTICCRq/lbLUfhzvNwxOGIMqlWW1rh8OZ0cCk1xOARj6ZBIfyz+DUyVPIm7tgBFCgQ/jHNoef+pc9QvmUKLL+wCPOvLsZhh8Pov78/PI/tR82FefB48Hz/BMrmsJ5f5/jpkyrmAx/nu7gAz54BkvvRkEYBSAGodX9RAGolyP6hErBp1gStq/2FmY3VYpmtlw/G6u0v8Hm1gb9DhjozNggrgfPngTJ95qBku23Y0WSH0q3rzq7YudUGvXOPR6dOYR3JMttJ2hcJCqhfX12/3BFbtAgoFclTYR4cexa5B9fE6hODsef+HmxtvBVjj4/F1ZOb0HdCXBx32YcuXcx3T4jwS5QIECFoa6uuY9w4tcrLihWGXRcFIAWg1h1GAaiVIPuHSiB6i1roU6cCRtdWv9P3WD8OMzdcwbdVK0PtywamQUBKdtUcOxEVW53DmnprlEkN2D8Aa7d6wDHtLPTsaRrzNNVZSLkzEQa6XHG//repzlvrvI722IQk80Zi4656uP76OpbXWY7Z52Zj+4mFmO3ijfUurma9dyTPYZo0akofqXksNmMGcPAgsGmTVnoh96cApADUusMoALUSZP9QCURxKI8xTZqiX8VWStuhO//B8BX74LNiS6h92cA0COzdCzT5dxhqNn+EhbUWKpMadXQUFm69jdbxl2LgQNOYp6nO4leP368eQVOdt9Z5nWo6A75792Pbquzw+OqBWdVmYdW1VZh5eDx2936EGUPfYYAZx4JJcu88eQBv7wBSktxaKpzs2aOV3n/7iyf+3TsouRMpACkAte4wCkCtBNk/RALfvwPWnYpgbqseaF9MrY009fAi9Fi0HN/mH1Byo9FMn8CWLUC7dX3QqOlXTK8yXZnwtNPTMHXzETSNthEjGc8T4kuUvH87dwbc+TNWtYiI3lmXKvbD0zsfsWsmECdGHIwtPxY77+5E31094ep0GyMHemPQyJgRPc1wP//yZaBsWVWU6WzVKmDmTEAioPVtmTMDd++qHsePHz0RL148eYT8j6e+n2UO41mZwyRNeI4UgCb8ciLD1D58AOI758La9mNRP081ZUlLzq+Dw9xJ+DDxNNTvXzRTJ7B6NdB9Xye0bhIfo4sMAqytseDqEgzfuAb1vPdi0iRTX0HEzk/y/on3Rhf1+2tUcMTOznBPv5m/KS59zYFdI24im302OJdwxonHJ9BoQyM87P0CUzreQe+Z6Qw3AQOPfOoUUK8e8FRNjamY/LI0fDhwQQ2W15tJ+iAJOJE8km5uQIIEFIAUgNq2FwWgNn7sHQoBiYZLMT499nddiHIZ1KKf227tRM3p/fBs8DUkS0aE5kBAAhaczzVH11Lx4OywAChYEGtmdECvjTNR8/VJzJplDquImDn6+Kh5/x49Csj7FzgvYMTMyjhPfZy+NHYkaY3dThtQIX0FdCnUBddfXcffC/7G49F2WFljNRxXmm8ZGbnr1749cO9eAM99+4CuXYFbt/TLWBdwYm8PrF8veSUpACkAte0xCkBt/Ng7FAJyXJF5XhKc674DBZKrOS+OPDyC0tMccK+LG6SOJs30CYjAG37nf3D2uIVuscsD27djx+BGaOO+E1UeXlEiWmnBEwguVUjgyiCRmdvbhJmwqNAc7Gg0Eq3ytEKL3C3g7uGO1FNTw21OQRzM0wetd/mFRpshiO3bodxhlJJ3OjtxAkpyawkQ0afJM6TkotTdlmoj//sfBSAFoLYdRgGojR97h0LgyhUgz9rYuNH9HLIlUrPeXnh2AQWnVcHlpq/8yycRpGkTkCPeyc9KY8SRY2i90Q1YvhxHXLejTtaXqHDjPuSImBY8gVevAMn7J4ECMf2uuwWuDRyZuX2JGQ8Tax3HpnIOGFxyMGpnrY0PXz4g/rj4OLu2Gh7YVUTDE93MFsG6dcCECcDZswFLuHQJSmlE8djp0yQQSzyLRYoA6dIBPXpQAFIAatthFIDa+LF3KASOn/BBiX3R8KjHQ6SOp9a9uvXmFrJPzY+T1T9BoiFppk9AgjwWv82IUQ980XDLfcXlcb52QZRtGQ9lLrxU7j3Rgicg97UyZgR+/ACs/H5iOTsD798Ds2dHYmpfvyqKd0j7F1iVszjmVp+LsunK4ofPD0QfER3b9zeHlUdyVL061mwhLF0KSNTvETU3umISGSxl/+Sunj5tyRI1d2Tx4oD8UjFxIgUgBaC2HUYBqI0fe4dCYNueT6h5Ojbe9HmDhLYJlda6I6B9xX+ifDm/5FkkadIEJM3Lmk8JMC12BVQbuUYpaHsrcwLkafoFJU54Q+490YInIHViixYFPDx8scp1FapkrIJZk+MrQkEERKS1J0/gkyo1Bvf9hvmJUigJxHXXQGKNjoXZp9si3bX3KOFmvhD+/RfYuBHYvTvgLUpZOKnxHDg3oD7e8dixgJyoX7pxrgAAIABJREFUFC4MSF7ORYsoACkA/7uzpAS1hFumAfBRrlwB6AvgSTCbkAJQH59MjvFbAks3vEJL1yTwHuiNmNHU86/33u+RYHwCrM3jhfq1YpOeGRCQRM8bYI2lBYehVGM1cduT2mWQKu9hFN33AyeORzWDVUTMFM+cAWrXBrZdOI+C8wpiYImBsL86UvkhvmFDxMzJKE+9eBFeRSti8oA3GBvNBlc7XkWmhJmURyedmBTO19qi9O7T+OvlfqNMxxAPkXq/hw8HTfosKWESJgxaHUQfz5ZKMuJFlvKB8+cD27ZRAFIA/ndnjQKwHoBcS5XiNHLIkB1AXgpAfXwMOcafEJi21A3d72eCz9DvsPI7//r28xtijIyBORlfoEPTJH8yHNtGEIGerT9guX187Gq5D/lzlFdm8WFof8S3GofcOzxx+WycCJqZ6T9WFynabcV0OO12Qqk0pdD0+2FF/AX2HJn+Sv5whnv24EmDHlg+6DIGfI6BF71eIEls9fOeaUYmtLjfGg4LliGV140/HNh0motXTsq+rQxU1OjLF8DGBnj9GpCIXX1ZmzZAqlSqB7B3b+DUKQpACsDQd1duABcBJADg8UtzegBD58cWGggMn+OKEU+L4fuIoFsvikt0jEl5G/3apdcwOrsai8CECnvhUrgyLnW/iSz2WZTHft+2BdYXayPjlme4e5H5fH73LrZtAwYNAkqO6Ypzz87hiecTjE/6RLn/J17ASGvLlsG1+3zsHLYR/d7a47PzZ9hEt1GWm//f/Cj3pBmGjBmG2N8/mC0CFxfgyRP1HqDOJF+fpP15+DAg7Y8+FlinDlCypHqdQPJI3rlDAUgBGPrOkuPfjlJ/PJimFICh82MLDQR6Tj6N2e/qwHvksyCjRB9shz72RzHa6S8No7OrsQisyDUSzeoNxpMeT5Aibgr1sY8eIeb8tEi6xRUPr+Yw1lTC/ByJTLa1VX9YRqTJPKZPB+J0roQiKYtg2JFhWJ3rM8aNtMFF+dU8stqkSTgy7jTOjhoP5xeZ8W3QN/9TgNKLSyPHm3qY2aerGi0hLjMztL591en/80/QyUvCZkn8nTWr/hYlFUdatFBFoFQEefvWE3Z2rASiP8KRbyQ5q5GS1HUABHdNmwIw8r1zk1pR29EHsOZTR3iNugu8eAHEjav8VLYdlBKtY6/DP/2LmNR8OZngCexI1xDVHdbifb/3sItppzby8YH9gKhIvWU9Lt6qa1LoxAsTxS++SBIx66JvI2KS4h0SEfiwZibMqjoLtdfUxrQc5zChb3YlECTSWv/+2LDYE/fHd8C4F2Xxtu9b/6XWWFUD9u8qYV6X7ojmdg9Im9YsMUhaFkntI6lgApuU/tu1C8ifX3/Lkvx/4nEsXRqws5PfvzyRJg0FoP4IR66RqgNYBqAlgK2/WRoFYOR65ya3moZDtuLATxe8qTFbzWIqvxKfO4d4o/OiVrSZWDpUvU9GM20CJ5LlQvGOrooXJ3rUgALOafrGQNbNg7DnzmCTWsCNG0AOP6ekHNGl8HNaRsQkxfsn9wCPFImPIw5H0HB9Q7RPPQ2TOlVUjg8jrbVujdk7UsNzajnMedUCbk5u/ktturEprF7lwuRuM5D4yHo1uZ0ZmiT0Tp5cLf0W2ETPLlsGlCihv0VJ7r/Fi9Uxo0WTu4eeyJWLAlB/hCPPSE0BiFNaUqyHFGKlCEBHR0dYW1srq69UqZLyh0YC+iBQrd8qXLKeiWfHogGlSknompLGPvGrRSj2Ywg2jamtj8dwDEMS8PGBaxJb5Ovii28uX4M8KXt/O+TZVBMrb5tWKo/ly6GUpxOns0RMyvFZRNmYMcBV159YnTka3Hu4Q8RPJfv2mNC8qZILMNJajRoYeroyYsxOi9VvnHGl4xX/pXbc3hFvnyTAsJ57kH3FIClrYZYYmjYFcuZUq4EEtuzZgSlT5Oep/pYVPz4wevQe3L27BzNnCrJvWLNmpjxAVKCn/p5kPiPxDuB/31UXAPL7SA0AJ0J5lfQAms9eN8uZluoxHy9sl+L2+FPqT2PJGDxrFlJVtUXWTx2wb5L8rkIzaQJubjhbNBPKO9rBc1DQ8gYFh6RC0Q1pMfnqMeXiu6mYJK6WWqxv36p3ADt1iriZSQDI4zdvsSyZPT45f0KLTS2QxaYYJtTtgW/fIm5eBn9y4cLocLc3Ui74gb0fZuFYq4CIl777+uL2A2/06OWG0uOrAp07G3w6hnhA3bpqYuYePYKOLqlaJHemvnStXGMQr58kFU+TRg0umTfPE5Ur0wNoiPdqzmP6SIAeAN2v6iKSfQFUCUYQUgCa85s2g7kX7DoV0aMtwckLcYCjR9UU9smSIevA0kj4oSFOTG9vBquw8Cnu2IGVTo7o2RZ40f9hEBhlxv2FUqs90PvYI8jFd1Oxdu3U8muenkD06ICUsosoE3HwPspdrI6fS8mH6bjTEVF/xMM/tccoAlDmFyktfXpUe70I+ZffwoVPW5VE0DobcWQETty8j1Z9o6Fh92DOUM0ESNWq6i8YHSXMMpBJoEaHDoB4CPVhXl7q9WnJMSiewFy5gCFDPNGgAQWgPvha6hgUgJb65o207hydRiHjt7nYkr6D+iuxWJ48KFY+Bj59aojLs3saaSZ8TLgJTJiA4Yu3YHGrD3jQ2zXIMDVml0HJxafhsO0zEiU2nQMZqcXasKFaj/XaNWDFinCvXnPH9u2B70nOYI/d//Cs1zMMPTwU99+4Y3n9BcoRsFzoj5QWOzZyfzuLyuu34/H3S1hVd5X/MqeenopNl46iTr/scGr4UtxZZomgTBnAwQFoKTftA1mVKoCkbZFfRPRhcniSLBkg1fXktpZ4HR0cPNGuHQWgPvha6hgUgJb65o207gztBqDs22mY13Ov+l1LrGdP1Pq0A7d8m+H2v6YVPGAkLOb1mNat0fyiJy63csc1pzNB5t50TUPk+mctms14jZR59Jj1ViOhbNnUO1jyg1PKrUkQRkSZeIGiZ9+F8/H7wLWzK2adm4Wdd3dhR9NtShBIRAaoGIyJ5EaJFQv2eI1mW6bC2+o15taY6/+4hZcWYu7JVSjTvzbGlt6t3g02Q5Na5lIlp0EDqJtNsj/nygU5GhYvoJOTfhZ17x4g9wp1VwaqVQPKlfNEr14UgPohbJmjUABa5ns32qozOLRF7ecLMGnjR+UHgmKrV6P15m44EKs1Hi0w30LwRoMY0Q/6+28U+5EXPm3v4FTHA0Fm02FbB9hOXQ6nDoeQtkGhiJ6p//OlAsPeveqNA/kBLVHBEWVSBi5usRV4aD8XR1sdxfob6zHh5ARc6XJGqSIhOd0inT16BN/06RHV5zvabe6OuDYxMKFiQK6UddfXYcSBScjdvw+W5RirZAYwR8udG5D7pjUqfFGjQe7fVzZb89HZFMH2a3BIeNcoNYDF2yhHwGKNG0tCBU8MHUoBGF6m7AdQAHIXGJRAzmYVUd3rEsZueR3wnHv30McxC1Ykb49ni6RSIc1kCfj6wjdePKTM5ogcHW9gb6stQabaa08vPJ22EmNLTEbaAY1NYhk/f6r36h49Un9gBv7BGRETlONo+2rT4Z30IDY32owjD4+g1ZZW8Bj+APv3A3mDK9IZERPV5zPPn8fPKtUQ7c1LNN/ggIwJ02NIqSH+T9h9bze6bOuJlP3m43DiBmo5DTM0Ee8SbV7eYwPQv7+a6SBaNHTwnYNEiVRxqA87cQJo1Ahwd1dHkzuHsWJ5YvJkCkB98LXUMSgALfXNG2nd+ZvmRJXo1hi5OFDJA19fuFS0wdJkFeG29HcpKo00QT4mZAJPn8I3dWpYFx2K2p1vYV3joJfpXA654MSMFViQqBXSzPW74xnBTMXrJwEg3t6AhweQNKn6d0nYGxEmpbuSNxmKuKkeY2Gthbj5+iYKzCuAhHM+KTVkdTcjImJuBnvmzp341r0vYrm5ovry/6F0mtJw+jvgPPSk+0nUW90QMfsewf1oWWAll9t0mbsNNin9Dyy1eSXJd7G5LYCUKdV8Qy1bokf9J7CKYoXJk/XzTPFmy3HyzZvqeP36yS83npg/nwJQP4T1O0oMAM38KnAUBBAfgGR8Ou9XmUMSNH/R7yPDNRoFYLiwsVNYCRRpngSVk5aAy4T1QbqMrJsBy20T4NYy8zz6Cev6zb7dvn342b4ToqVvhNZdX2NB7YB7XLK2CScmYPXMxdj2rjCS715oEst1dVXzCkvkpHgD5dL8gwdq+oyIMDkmTN2hG7JktMbEihPx+tNrJJ6YGJnXemP65Jh6zRUXEesL9plLluDjrCVIcesgCswoh+Z/NYdDHgf/ptdeXkOxhcXxw/k5PiOWelYvLjMzM91Vg9wNM6Bf7zxoXLk38mcqhYltb+GeT3rMmaOfBW3cKDkA1fJyYvL3K1c8sXYtBaB+COtvFIkHGieVMgHsBnBVki37JWvMBaAyAKl7IzV6Izp7KgWg/t47RwqGQFEHG9TK0w39ustHIsDGtyuFpd/c4brkAbmZMoFp0/B5+wHEipoBPXpEweRKQfOpzD43G5PnzMXps3ZIeO2wSazk0CGgTRtV9IlJpYZNm4DChSNmehkzAml7NkPZXNnhbFsJP6JaIfqW/Mi19ymG9kquRItGOpswAW/3nkdO1zVIMawAnEs4o062gIU+/PAQGaZngI/LD/jEsYPVieNqbhMzM0l9dHHfWzxrYo8yDkC1TNWwfdJzbMjcH1ui11cCkPRhUlVESgoe9vuISe3hHTs8sXs3BaA++OpzDDnTGuQn/H437l8ARgCopc8Hh2MsCsBwQGOXMBLw9kbhbrZoVmkuutYLmu9v+uCWmP90G64u9LvVHMYh2czIBDp2xNufdkjy9i2cuybD8DJBa14tu7IM/f6djHtr3sD2jd8FJSNP8dfHrV2r5v074xewLHfshg4FakXQd1tJ35FuUFW0TFkAHRqMUwoT2w2xRsbjJ+DUOBeaN49gYIZ4fJ8+eHL/C0pfnYEoTpkxu9pslEtfzv9J77zfIeH4hMCoj/ieOh+izZoBVKxoiJkYbEypNy3JmZ+sOoYlS6pjToX4+PT9E17drY3z9xJgXIJxWB/04CPcc5k9G9i+XUSfOoQIwjlzPHHyJAVguKGyI4NAuAcMR8Dn8lXkmJcXzs22o3kRyUMeYAvmDse0i6NwdW7Q0mKGmw1HDheBkiXxqHwbZL69GyM650XfYnJwEWCbbm5C63lD8W7qNVhJ6o+IumgXaE5SJmvXLvUHppjoCknTIXVbI8IkgW+6UX9j0G0b1PfJpmSnTp9+GxLd3opWZUr9J4lwRMxR7890cMCdH+lR7+oQvGyRBNsbb0fBFHIbSrXvP7/DeqQ1rCY/w+dsjRGzc2ugRQu9T8OQA0pKlhgxgA8T5qHjw8FI/782GHtiLNztR8Pnn/1on3Yfdu7UzwwmTlQDpdesUcfbulXSqnrC1ZUCUD+ELXMUegAt870bZdVflq5F2svNsaj1QVTJWSzIM9ceWAuXTQ1xdYQXosc3oRISRiFjJg8RF0eiRLgyZif+Pj0CEztUhmMhxyCT33d/H/43rxs+TH6IaFcvSW6KCF+cePskAnjRInUqv6vXaoyJ6rxEqSdkxvwlz1Fu7j7g0ycU3FgZ0T+vQt2c9dCrlzFmYuRnVK2KiylrovPVjrhSw0apA5w5YdB8NzFHxoTVnKt4+dcQxC2dD+gb9JcLI8/4jx8nAUaSxPuLYy8UiL8Yo5otQp99fTA9VXsUbz0V1XK5+x/Z/vHgv3SQPf34MbDQ75rtkSOilz3x+DEFoFa2+uwv1TB/+g2oK8Gmz/H1PRYFoL6Jcjx/Ah/7jUBSq5E47HgWBVLlDkJm783jaDWvFG7XOI3YZQI8A8RnQgRevlRCaA9u8UL13dUxp0NrtMgd1Etzyv0Uys1pAPcFcZBwwQRAMtRGsDk6qiknx49XJ9K9uxpgqq+IzD9Z3pcvgI0NkGBkfOxf+BV5b3sCPj6o1N4GUaIMRZG0gzEkIDvKnwxt2m0LFsTBwgMw4lZ1HC4RA897PUfS2EmDzDnxhMT4umAX7hZYjsQS/yGZu83IdNU5flSqAruih3Cq43n02tsL9VJWRLsyvVEy30ccveCX+1Tjuvr0UauATJ+uDnT5sgQce+L9ewpAjWj11r0DgDYAPgKQytZSk3cGgEp6e4L+B6IA1D9TjuhHwKtmU9jlWYM73W8jQ4IMQbhceHoFZWYUwOOk82DXPSA6MLLDE69BPOV7thmYlM9o3Rpbpj1E48P5sbLDYNTOWjvIxK++vIqCM0vBdV1xZHKsBHTpEuELk+PeggUB+aEpNmoUcOuWem/K2Pb2LWCfyAdRXKLhwYUSSLP1iDKFJp2TwOdjcaRNvgFjI2Mu9DRpsK7Wcix+ng07cybCZ+fPsIluEwS/BIF4LJ2Pi4XPIvW7y8CqgFJxxn5P4XmemxsgAT5vsmZAggYP4NHfAz339ESy2EkxpOY/aJT0CDbcC/qLb3ieI306dVK9jWPGqCNIgFOmTJ7w8aEADC9TffcT0TcLgLXkafRL97JArqDo+0F6HI8CUI8wOVRQAu9z5kWC+pfxsvdLJI6VOMg/3nt3D9mmZMGrl70Q/18/V00kByj3diQQ4fhxoFjQE3HTXLmEGu7ahVXNdqD1pczY3jHoRX7lB9H7B8g4LQuO7+qEokWjmoQXRxI/S23Wcv9zh3VUa2xZmQSSRmO35GQwssmxXZosH4D+8eEJZ8RxGaXMoItLQXjd8UZce1fMEDdBZDI5944VCzPbXsJB72jYmjorvg36BiuroLWi88zJgxerhuNQkffIdnpRQIirmbCQ6jKFCvriZMKYKNkxBj44e2LY4WFw++CG6QNuwPltb/zzSmrEaTe5HpklS0A5deUXC3tPv+QiEBUo/2FxZjrVxwGJcZd0L7paSZLuRT7t+U34rVAAmvDLMeup+friVcLYSOL0GZ+cP8E2um2Q5Tz3eo7kk5PjzaGqSHjYL7TNrBcc+uT/9z9g82agc2dAAhVM3sTtECcOFmYdj073k+FY5y0olCJoubdXn14hycQkWHtsEurHOgJsCVopJCLWKBW5Ro75hoZX4iBV3FQYn/IuRo2ywoULxp+NJO7NX/4BvrfNgG+5N8DKL+eLy9zGuHdwD2LEeud/r8v4szPQEz9+VPbNoE5vcT/mI+xLWgFv+r75z8NKLiqJB2s7YFPxRCi4rJvqpjUju3gRaFLhNSbaJ8aAbtlxzfE6pMbximsrsHZVMsw7lhX9P0pCEO0m20ZqC8t1BrHv3yW/JQWgKQnAjADq+uUA1L3xegD0FAiufRMFMwIFoEGwclAp7fTwr9RI19UKPkN//Oe3f6+vXog7Ni6eL0mLpA/cIj0wcYpI0ljxTB09GpDQ1aQXLj9x2rTBP14t0f1VLFzreh7ZEmULMuXP3z8j1uhYmHBxBXrfHw1IFuYINqkCMnLpCfS8WBlffnzB8sK30KdtBuUSvbFNEvdWdjiNqFWL4GWbW6obB8C0nUNweOlI2Pz4gpXr5dAoEpmcjWbOjPYtv+JL8qM4nrA1Hjj9N99ntZXVcG1DdSwuUQxlXUqoZVvMyKQ826i6F1EncwmsbVcMe5vvhQRFOe50xAnXBtix8CUcvs/Ty4oqVQLq1w8ayR4zpie+fuURsF4A63kQCXe6o+cxDTEcBaAhqHJMSJHTs91aoWgdT/wY+d9v7D99fiLaiGhwn2KFlC9MI32IIV/bs2dqpahr14A8eZRAUKVChcmaTrHu2YMx+/PC+Ws0uPdwR8q4KYNM2dfXF1GGRYXjzb34Z1tNdWG/HPUZc40+PirXHhvH4OHXi3D3cEfdVF0wpHYzSJYaY09NojW79VuIbwXb4OaU72riOADLLy/FvzNaIde9K5h5JKcxERn+WZKAsXZtNCjxHLb5tuBK/KG41OHSf57beENjnNqYF1NKtcL/OiRW945t0JMCw082/E+QOs4bW25BymIdcaNROSyvsxy33tyCHG27R5mOywPXo7zPXr3sOSkXKMFNjQOV206UyBNv3lAAhv8NGq6nhMrpKQe44SYJMA+gQela8uAzZ2LLuhVoUPQRvo5+GiyJKENscG1hFOTYddosqwD8yeuVWp7yDfz2bTUq9Pp19QK5yZouxPHjR/Qe8wOTotvhQ78PiBfzvxEsMYfFRcW7h7B1xf/ZOwuorNani/8QAxUEEwULWzFQ7Gt3YneiWFgodiPYid3Yit3djd0oBgaiWAiCSH9r3oMK8oL09f9dZi3vWl7Pk+e858wzM3vvsiCerjAf/0um1EZBO8fOFM9eBElRBwZosqz5PJU0nCg3JKUJD9yCWdZ8Lb6Miwt9fw596Mkhhi1uTYdjqxn/MNxXPSknl1hjCQHj2LE0yHEHg4YbeK67mjPdI6vE9N7fm+O79ZlYxYbufdKAiwsYGcV6Vm/fwsePSf8K2b8f7vdbxDuzuaRs1oI59efgE+CDzjQdnhfchn+n8eT59kj1e4+vyaHR1haaNv3VU/783jx/nuwAxndvE6O9yMGtS4yOE7jP5AhgAm9ocndhOzBwIEvd3zKi0H2+TlNf25NqbFaOHctKzeGTFKbe/8e2fLlS/ycExUKVJ3QOf7XwwcmTSr7J1ZUeVm44ZMxF0PggNFMI01VE051sQKlHuzl3rpXCVPsvIlzEwZaPZdnFVelbti+e3z058vQoR7ru58mTOPkX8Xoqt2+HnSvN8C11g/2zfh2EnNycMFtSi+lrrTB3V4Ah/29MyOo2b6aS7wmKdFvEJ91j7OsgAlkRzfqoNbv2BDGylD197XKCSLhUrhyrbZBAtSjIyYFKWIuyRcSaxaqv2F4s0w2wGsHBbrsxaWzByCojVV2IA3iu6iYKV23P17e+6GePf6VawYIg75BatX7NslQpb+7eTXYAY3vfkuL65AhgUuxy8hh/7w7Urct4wwIsyXGNT9PCFMx/m23a0XlZc6cwHSpUhokT/961JMDMxo0Dj/ehjJ35EsuOeTEz4+9WgLC3h+PHVXIaLXo7c9CwLAETf0Wwwm+Jvl0hct1dyvV3NtCrF/+mtpkgrFVpsqG52NJqC1JrOvTYUDxtnVXqCeUjYlgS4M5G38XatXBqe2k0yoWybtLtnxc/+fSE4guLcWhOQ2p/jewcJfrEEnOAGTPgzh2K3d5MeeupBGdyZkOLyBw8gph12P0SK6M1WG0sC2PGEFthZAkaliypOIFSX5uULETr1kHOER2Y0v8qXc3G091EobMqvKgwi2rOpm5xM1yveGBUIf5eqQTVBV8V/vmtUsWbixeTHcDEfJTj2neyAxjXnUtu9/9jB3LnpmeTLhzWu4j71MjpH9VJeZQxk93KMiQ44H+OAyy2N0k+Tu/z2XMEKxp57cU4pdlPouLY9pUk18uE8+SByZOp1eUq1ws2w3vCW7VD551WhvTXJvJAd4/SRmQL/iWTKOsk2wDummnxqp8LfilCKL6sBAUdvzFjumaS81QL2vvyidxkq1KEudbHfu7KDy3c2zMLU8r3fwv9+sdbK9ImQUHob7Wn/qyR6GT2YXHjyLD3uZfnMn/nJSyz7GDUhSbQsKFSJxELW70a1q9X+Mel9HDnzlg0juely5ZB1TFVaDf8JTNbL6dRwUaqHmusrYG5iTmNywzj44bDFOlUNp4jgcgJXr4Mxsa/umrY0JsjR5IdwHhvbiJ0kJwCToRNTe7yf2QHpJhbW5sGg6fxROciz2z3q5145lEV6OldjZmXjivU9jE0qasaOhQVt1uxYjFs9C9fVrs2uNapQEhaDzL6ViT/ra0JJhSfKEsTLhVhUG7WDNM2J3Er1Q+PcepxbcVmVeP7hb48L/sMVZ5Vvsj/kq1aBev3uHClbFH8JocQXMaEdGb3KH/5Ob3b5aZ7EnOOixrJ9esZKNmgJeN6rP25KwKCSmWbisfzUlLwkx9oRk6t/0tbGP9hu3QhpHARUk8aS9sNfcmTNSPT6oQxGIfrfeWNldhs34GF1lEmvemlUp1RFbrFwoRSSVRfmjSBzp3h9etYNI7npSJc0mF8fkqM+cSR7icxNVAY3zru7EhJ/ZI0rr2dFGPHYDxByEHibpLmlsdDwNVyvvph7dp5s21bsgMY951NvJZyV/4XMO3JNYCJ9wz8d3sWgqw6dSjfdSR+ere5N0k9w7/B6FrUDqjHhiU2INxhMfwICjvJ+fNKuud/hUQ3f3FPXNtkZmvrrfTaPYD8uz24eSP+tUGJ8pCJAy8hBxHUzZmTws12E1jZjucj1RPplZvfiDcnm+PePj0sWQLCj/EvmUop4UgbVpXfyzOLe2BnR36D7eT22E8j47o/1UGSanoTJ4Ry/VlKGrcfi2XTyRGG1ZuamZMLPTF1egG5cyfVlBJ/nAYN8KnfCp2hvWixuS2V85RnWOVhkcZ1vO/I4K32dA+6xPRU40HQHOLBx8IaNADh1xS9Z1HYEQfQwCAWHcTjUnnWBkzURnfsN15avSSXbi5Vb1LbGBgSSLP2bmRvUwXjVUPjMQr4+Sng6A8fFIDTD+vZ05s1a5IdwHht7n+8cbID+B9/ABJl+Zs3w6JFGJepg3aOtziNVc+FlW9sU/IF1eXEXGsFHpsv3x+nI35ixoyq7pk6VfFR/naTE7xW4bNk7tWF50NcSD8lPXprX/LJNSKlyl+zjkuXlK+qIIE1NMjZeD2Zaq/h7lD1qfyaS9pw52AlPo+vrLSTD/m/ZHO73ELbuQKOPU052e+y6utZ2yoTeXy7kMVgRZKn3SdYfuSkf1YGWjrQ3jRi+NFoXkEmL/Sh4/JNaNYNV92fiHsnz6JEyzJlSkRpvDJlcOsxgYLDm1NpWS2VfvSP+rjwSxMkdNcNI+jsfZ/5hZaAhPYFQRwLK1RIIVWvWxdUBOB2KgaaJDHb0d/ovTA92YfD97HfSZMyjWrc2Zdm4/TGibaDDShukpKih+aqyYbaAAAgAElEQVTEaz7i+Am4RRxBLa1fXa1a5U2vXskOYLw29z/eONkB/I8/AImyfFG3d3PDKI0O+fOl5MRw9S/A4pM6kPZLaa4dWwuzZ0MjpYYmOhNetY49vmC79Qg9K7bm7ZuUqszR32wqapJGC6k/4ChHuhzAaF4BXixayrf7dROEIiLB1y5hVYErywcZyFh/McXMjnCxv/pUfjMHc45uNeL7hr4gLMz/Ip/bHcNG2NfxgpaFWdNsjWr+PWZVIdOZx3zK+h6HtUkbdZ3S5hYbspdlgdVh6uWPqApabkVF6tv7MdqiP+mH9E7w26iuQ/Htf4C0nz2L0Zkr9vPKlYvbox0xm14ZvdElmVp7Kk0KNYnUz/mX52ni0JkO716yrN4u5UQnzNkxtOBghVJJJNmEUknk0oRFxsYmhh3E87KpvV/QcF9+alrp8GXUl5+9bb63mSXXltBjRlOqZbhNgWvx0zh+8QLy51eVVUbgFPT29kZXERZPloKL571M6ubCAPY0qQdVM16yA/gX3IT/d1MQSpeyZdF//oCqxgXZMVC9HFKFqRZ4uxng/O6+8lWS4vE/2MqVYHPdkjcGS9G/vphVfSxVEY2/2aS8sYJtX4b002N6nemYbTHj0OI6PFwzSAQT/gqT+iJJnaWRIIYAQCQlGVaPlbbeNGq1u8/BnpvUzrW740DWrU5L8OEZpNALq1aXcExS24MHBJQ0pdYkM+pVK86E6hNUM7A5MY4ny2aS3f0Msy/FjmYkvkuYW2MfUyu25MigK5Q1iAgGaLSpEbrzfVlmWgHdZUmjhy1nM3EohDJFMBc/pMXiu86f7VXhbi2OzrnPGIeCvO1owK52u6iYs2KkIe68u0Ol5TVp6/qZtX0uQ+vW8EY9Z6i6+Um6N29eJTIm5N/z58OpU6jQ3klhM1s5UfhRQ0b0y8rjAY9/Dnna9TQ99/Vk6GYbmn1cRa5nZ+M1HRHXkdfj70IpyQ4gJO1xLurbWA6oE6YDfFXNZUL/Lq96wfDIm1Ek4sLheeL1fMSncbIDGJ/dS26rfgeEk2HKFHQPraZd2bqssBig9rr6c6xxdgniVRZt5YsUg/of6xEBLEybmW6m7dl16S7D9ZwYNervvhFCGNvxcF3mWbTDoowFI4+PZNlaL3b1WIaAQ/5tu3ZNoZcwN0fRpZUwikAc69dHVYDeYDhdzL+zrv1CtVMdcnA085d+wWvzUjJULaVCDgt4JMmtZ0/27tNg9IgnjKrXU5V6FFt3ex1LNoxh3Pr6NP2gRAWTypaXWkT/5oNwsXpKvowRSxy67O7C6wWf2Kuphe6JXUkyJZEUk1vz+bMSOZNqjQQ1b29VMd7SaV84ciUDh03T8LD/Qwpkisx6/tzzOQUXFKK1cyCO016AkN0FBECKFDGakmQD5KwiDq2Y/D0pgSDzau1HK7A/m8xzc6HHhZ9zfvzxMSbLTZh8cT89nPqR+dOTGK0nqosE3SyVFcKx/s7nnYpsWvYz2QH8exzAsYCweY4GpAy5PSCimYJRFEcvPyAwr3dhkT+hOw+H54nX8xGfxskOYHx2L7lt5B2QvIxULN+7h9Y8C4bV7I1d285qd6rDUjuO33ThY/V6sHRpjMAD1Ttd4XrhJjwZchfDOTnp+MqTTUoh9F9rsjTrV/k50HsltYxqsfb2WqzWOTCv5FmV0/Vv26BBILgd+fPh2gvSmxQET08Vklvk09J36Mmw3jmZ1Vh9bm36+ZmMtr/Fq3lbyDWsHZQpAyMVUtwkM6lXzJuXuplvcm9gIxzbr6N63uqq4c+8OEOnDR1xnvSNDH7vk1SDb03BIfTsPB/PkZ7oaelF2I7BhwdzcvlLnO4/J/3Tu0myVVJLJgcSKUsYMkQpvU1Qe/pUBc0fYunPd76yLKOu2rXLmB98P5BtdjYa3/rGAcmSynsjFmzODg4K4Pz0aWUFEiHT04P37yFr1gRdldrOlpqu4q3hLO53MlZFOX+Yt783utN1Gf/iMmM31iZNgE+8NAiFk71fP3j0OIT8C/Lz4ssL1Z6mCEiRnAJO/NscoxFEoEUcPSF02gPIF08cwqPAJeAe0BCwC+tN8OLqIXUxGi7BLkp2ABNsK5M7Uu2AFBYVLYp4DppWZbA3m8qAeupztAM3LMbh3BF8+k5Sqrjlq/QHsdbsLeaSp/pZnKz2km2KEVmuLOPh/vp/9eaPGhPEzNRaPLd6Sl69vFx6fYk6K9owMuWbv4L/WtLQc+cq6cCdTddSymkFSLEYyvc4++AWzB5QA+sqg9Xu86qbq+i7cDu3rY9SfMckha9CWHKT0saPhxs30L6wj+/DtHg26Bl59JQztqunK4UWFuKpTTbyHHZIUgmWdUbN6NFtP4ETg0ihETGyNfnsZFatusXz7cdI6Rc/JyEmWx0WnFP9zAIDFcW+L18UwHeCmZDVtWlD87JulKj2nGk+hQgcH4iGmt+1f5A/WlO0qObkwdlD2RR0l3hzIuUSA5N0tmSMhQvwh0ktoADRk0JlZ22hqThV2Exouyosa7Ls5xxEH1vUQCy8TzJ/RkVlk5VavTiZpLSFJ3/1oZvUXFeTXBlyMbrKaJrmbZrsAMZpR5Omkahad5GDDiDHgxFA0hR6xHx9yQ5gzPcq+cqY7MDBgzBiBMF3H5ByeG52ddpCC9N/1La027uZyYeXEDD7COjo/PH0HxICqduY07t9Lpa0mUzdFe24sMOEb0dH/8lvjMnME+2aFuau7MtbiIDx31VSaqJPqz9bn65uPqxbmT7Rxo1JxxLhE31c+ZBK0G7InW6UbpJT4QCUdMVTKDS1BusG96RLKXmdRbZdzrtov3gapztc45832xRAz1V1lTAxmVEcrpFF5M5NwAZH0nTMj+aQAnwf952UKaTyBgKDA1WOxsS5nRnTNh0pVyyNwyBxa7IxXxkGdnmCp83XSB0surqISWsP83HpIQVxLQCaRLRbtxQpMQnuihkaKvzrQquUYCZyFZMmUSrkFp1HXmWOuxnvhkniS72ltElNifMPuXWigOL4CYIjhuUDku6Vs+ZYyb+FWZs2SgB6tOTiEtl2GA5ma/NTFG3VHNtaEfkLCy4sSC3fpdiPa4bWvevKRONokqaXLILZ9FlceH2BktlK8tLrJYtqL0p2AOO4p0nZTLgeWgJSBDEoKQeOwVjJDmAMNin5kljswJw5qujR55U7yTw7A1d7X6ZcXvXlrqvOHqb39mGELHqgMJyKblbNmlEO9uoV5LGrwAbLIXQ2ac+4Y7ZMWf6I98s2JUnKJxa7EOFSkxYneVu2Lx5jlVogiRCks9XF5OZFLu8pEdduE6TdnTtQvbriFCxeFErbEXnItn+NisdRTNLC5R1KsnfgNBoXaqx2TEmx1lvckz01n9Eo1z1Fz1XCTX+I5ibIAqQTCfmsWIHrrlsUqHOOXIO68cIqrDAsbJDc83KTdf5QrvrNQPPdmxjXmcV3jpsLZmd011S8HB+ZoXjLvS1Yrl2M2+rnpD+8EypViu9w0bbfsQOmT/8FtBXQvShoxFJ8I/o5rlpFiON2tM4eZenJQ8y7N4L7lvejbJPBLjPZj53A5Vxphb9Ffv+D1Ueaf+9EHjPhAu3YPkThf1m6lA+a+szRn8X0G3X5/l0JRIs/mRhMAUcydWCWxV2aterDoAoRP+3VHKqR36sXdmMnY7hvGfEp9hXgmyic6Fm0p5R+KUrol2DE8RFc6XIl2QFM1F9MwnZeQVRipCQFEMfreMJ2H6fekh3AOG1bcqMod0CkFnLn5nGXCRTZnIrXVm7k1DVUe/mhu1dovL4lfnbuaHVooUDdhkUmjP3R+MSJUOqdycCdgZdUL8E9j/bQZslETre9Q5Uqf+89ydZwBbkb7OT6YKkIUazArDJ8PzoetxMt/tWJOzqCKBqcOOfD/e3vKNO5GKl9vyj1WPKSOg6NTuTk7IBtVM6lHkF71+MuZRZWZ4OxJx1a+ittpTI/l0KMm6gm3BgCHpg6lQu5OmA2YR0luzpwpntEzsKqDlW5u7Inn+8OQvPCuRinGeM195AQNpdMzcxuJbg9/Fakro4+PUqb1VY4b82EoZ2lwmaciCYSveLQyz0XE/CUOP7Ll/8a1N8fpLZOQAdxCkhOncqn8w8pcGUjc0+tZf3ddZzuFlakp2ZtOaYbkWLfOt5cqqYUJYrJAxkDkxT27t1QcctghbJoyRLen39MetuRfN+yB/PNdZGEhBxwpI4uoc8jV9LXoq/1K0a1taN9cSn7/2Xtd7RH830Zho06SOnFFvHSx5btEG71R7WKM83IgnJfM2DgbIFbfzcMs6rerck0MDF4Xv6WS6TsezaQ+S+YULID+BfchL9xCkLHJeU48k5OqWTSYmalS8O4cZzIUYO6x7PgM9qH9KnVpznvuT+m5BIT3g30Q3/VFBC+A8lJRWFTF79i3Id8+I3zVZGuPv38lEL2xizN5UMfi1Qxm18SXyUo2lQNR9GmixdbOv1KPTZY3ZZTG8vhf2p4gn+YYrNEke295n6VQ4YVsEhVgy5jgzHxOvezLmzrVuj0MB0PBt2kSJYiart283Yj17xcLM4WhGU/TVTcNsIlKJDTRDCZk4AXpOwvheMWJQfo4sK2XSkZuteGOm1cWdv8l+yaTKHzrs4c3VSUB2+cyNaqKkkiCfLuHcua5sDRogGn+xyOtBPX3a9TdVljruytR6k2hVW/m8S03r0VJQmh2xPbtEkhVJeyvR8m6hZjxkDHjsq/x9qsrLh5OwVjtObyz2hbnnx+wvoWUUsDFphTkk/bpuLp1ATs7ZWXjgg6/8FU4KT08HnbCTL2bAl37yqcMMCc4g50eTiK1sUfs/GAnir7euUKCDlBQtrjVMWpN96TNZ3XUztfRDj/kCNDePkqlB7WHjQZZxIvUJQENx8/CWRrgXQ8Xp0Oo9dfyWKjza42+6lRRGJKyQ5gQt7XpOirgQgWJcVAfxgj2QH8C27C3zYFCaoUMv6G60d31swuEHOkqlSWS0HZgwesc9ag+7WihNj4qy0AlzX/qIW708aPkq/PKvkc0ZKNwlqOPMzp1EPwtBWsFYieqtZkHbr63WD1jLjX2CTm/qtY/Pu3ZYp5ccYsuKxo2FlaMqyGJnOWfubj2uVk/hePgu3bw0PjtuQrGMBh5/2MXDqYRvvmUjGMtm3eIj+GfkqHxzAPsqXPpnarvgV+I/3U9IxP85HJozIrOTdJ5SU4yZwSWBT9Z1ENXL0qlLbTy4CFhSqPKZGS+S960L15LmxqRkQsjz05ljWO79nrX4ry7nuV0GYiW+Cla0wcVQOXvi3Z0XFDpNFUNCj2hTl4ZDQNirmFcfAk3qSEckgcu549lTHu3VOyzpKtF+YVOayIGI9Qqwgo6OPHOACmO3Vi5ZUSfLcaxb28vcmaLitTaiv1pOqszKIqOK/vj9/VDiD1g4J2iIEuuFDYVCgbjHeuYmgMHKi8O8Ls3dtQgmrVI2u90qSxn4nQkgotpYBGEtI+psiKkY0fl3pfVmUkwtusi7M4/vA6zQflxLJ3kOLcxtEkUvvG15UtWQrw/WxVUjZoRGWPqZi3mkXvf1QE4skRwDju7X+9WbID+F9/AtSsX1Ktjbc2ICDXMYyvXOT+4RiS58oXRQpzvLyYvuEW4x83JHDq+yh3WIrzU9ul5mBNdxoVS6VwNwhBmaAB1ZixxRxS5rvInTG/KBdy25Uj25PhXF/X9q+8k6oaulVlcfyWglYemZUoT6dOrOlfmT6P33FtwKmYgh4TZX2lTIJxaaXLFYsLWE4uT3p3K9o3m0mPHspww2zcmYMhAeMCSKWpPsoqNY2pbNJiEXiPZVMKKiEkgQ+Hh2cm0OyFm1qi05LW83HYzoRPgxWkSrp0quqBrWlqYdu6C+alI/LrrLyxknFbtjMj1UK6zyul5D5FRiIRzWf9Lvpt6odO//YsMYvsAHh990Jvhh6Lziyhf6gjnFEvtZdQU5QAmZTZ1lAFjRTKPTmvOTsrShNSDypVGHJoER5wUWWrIIVLsbDAmnXpf649o5/2xPJSQ5oVbkbfsn2j7KHGyoacW9Gc4Kt90LgbVpAqqNk/mMztXL8tzEw5RhX9JdVvz6aQW8oh5M0blmzSVQUVjx37U6+x+PegIPy0UpFOJIyt35JdO6Ic0ca7G1l4aQVVLZsxq+UVNHZsj0XnES8V//Zj+rNcDq3HiyLLVEieHlZGZO08kJmtF8jFyQ5gnHc34RveBsYDImoYqqZ7Ia82AyYBpRN++Fj1mOwAxmq7/hsXdx5+k23patCxeBfW7Xbjw4K9EUTIo9yFjRuVgvxLlxiy8AQr3ljiO90l2k1LMU6bpWWu0qdlMSX8IO1F4V2N6XXtRYMq2djae4oSrtDQoN5ic26czsWnHZP/ypuzZ08o7a7p4LRDE5NLz1GF+06d4lz/JtRrmoltVdwwk7fBv2CCqk6b5z4p+1bEu+VVbAeWZEvZVjQJdESwPGKdh95nW4ZKBEyKjGINP2XtiQbU99zNzgUVlIp18dRiEMmJ7bLFIRHQQtUKAQQXKYaB/SjSDbJQdSPRrcOF87K721pq5A3zcsIGOPbsGO3WDqTX90fMdMyjOKdCPZSI5jnJnta351B1cE8m1ZwYaSRxnFNOTkX/K5tY8HBEogpbi7Mn/q5EUNNn/kRqxx1ob9/LyhulyWY/jmbt06oAuFKFsX27ghaW/ZTgamzsi5EJY4Mms/i1GcZLjJlZZ2aU4CHpt9nGtuxbWh6/k8PQ8g8j8hPnXAj9orEF9qE0mVCafDP64m9hTmBIINqptSO2EG+2dWtu1xyiQjpLtxI5TggLcn/Pu6L65BqKiubmB+L8R98nn5+k9/4+lLeyZX35RaRyuhjnYYUr1CfnSjze9ObcpJcq73xGs8xc+acwe0aq8vfJDmCcdzfhGwrnhbjlguk/CQgEyivsJgkcUooFJCwisKG4PxUJM+9kBzBh9vH/VS85u4wnV6lnrO0+kaILSrHZ5CPtW/72clW34qFDUUHvliyhw9TNnPBazIcZ0T/iWqNzMSzvVuz6/KN8bUSlfmZktiThl07VuxpzqtVnyPKDCs1IgwaM62zK1L138V+/O1IQ4G+4KdPmf2KMVxa8Q0ehM0k44hVzb1wNw/LnmZPpG0MHJm4kKqp9ELq+Am0cqGzpwPmAjlw4spyGZd7wz2UPjhxWRJZqW5zidq7efJoYvXJldtviFHg+iwsODRVHRkJKX78maJRNJL+Es04CPkYHFvJ0+DJurL5Du05KkWrVGv5crJmWV0NekTODkC/8MlFnKL7YBLN739ipa6FEmwUSm4j2yXwYNQN20mfwMPqX7692pAy22ah8ZS1HDjdRfjuiaZYIJntWsiQ8evuKEgsKou8VzA2DSXyavo9AvawUdtmPSZkUqtJIwaL8AOLGNnP5Jb0B65vvxnKDqaos4H6/+xTMXDDKFXXfZcG6hYZ83GGjlELIf44eVUlJRmdzO1zDcldtgt66UG5LTdy/unO552WKZRXthTCTeuLJkwm6+5CMmTRUQArZg4Swr9cecbeZCU0Hp+fzyE+RunT+4EzZlWWpOPEgR7Kbk+q1a5yHlRS2Ru4epPZwZMMGX1U/e/vWZGzG+zyY/lH+muwAxnl3E6+h8FkI/Ys8yZmAz2Hkz5K/OpV4w8aq52QHMFbb9f//Yqn/S923KnYtezCmkTkZxuWnQehCtk1p9OfFS0GRhGc6d6b22Pm4hpzj+bToJa4yjTKlie441o9uAVLdL86f5E1/M3FWCi7NzMW9/lRoPVjRfLKx4ejHKzQy1uSh5TMKF/7zFJP6Css+O9iZoQ0eIz8oFfhhFnr4MNoXGtMx8DYrZybQVymWizt8GDpusqRHl7TMcXiDf9FC6GjMJPP2O7y9p2xm8Y4bCSixHJfR56PtveiMGgTf6IHLtq5KdFYcLIFgxjaHGM0oUj4pH0P3Wx5oFCvKmlobOa/TSIVaFdMv9pgvHUxUIKHfSZf9Av1INzUdxY+85V7foyraGJVHkIj2qW47TPJdYfbAmbQr3k7tSDmnFyXdmXm4nG6mhN8E0ZwIJvdazmd1hrfh/fHdvPmnJE1N2mFwpx91rEuScvwYDG16q1Q0JPgmvHOiGCLg2hhbSAiBmmm4vNaFHE2CKL60OL5jfCNFx8L3Z3VkCPbz4eWKeaq0M1WrgqBVuqjnnPzR9kjePioewyMzC7DTeSflDMrxzPMZhzqFm7CvL4j0yeXLVLEsqeq2q6IOGG/7uPciR6ybM8UqC84DnCP19+X7FzLOyEj5lTe4/L4SKfy/xxmGLHQ9qfOXpTh+2C18oBrr0exRmHycif8MVZIx2QGM9x39b3aQ7AD+N+97lKu+eTsI0x0ZuDfwOsX1i1F5ZnfcHxnyYk3UhdyqziR6IeGZsIKiEkNGo6XnybWJvxjy1Q1qNLYp+YIbcHJ6f0XDSbgdhBT3Ny2nnXve0vqOAV88+6A7P6zPoCDeNqyC4T9ObCnpQ7uW/y6psrr1DWzQiouFznBzwW9RguBgSgzWovTbsazfKdUgSW8Cmpj8rhxLOw+lfX1rlTBs5ScTuLy0O59P9lCVYmZtMZNitW9wdkAYd0gU06y1uCN3jpfg054wBl5J4zdtmqAkc0JjIrqoVbKXxk3Tl/rN72HeJY2KxNrHBzKYHqTIwJE4D1TPO5dlenb8HPbiczCLyoFUaYclYh2gl3Fl8tZ7zo6BmyKhRH9sY4l5/+CxfyDv30xUkNOJJGEhaN/Dh4NxMtFiV5queLRqwPjT4zlm5syw/LtZnnogXau4sv+oEoEUx0+igQ8UfyNG5vX8E7r5s/DxhQ8X/I6r+r/XT0SworYJpycwdZE79+xWKVzJffooWQCBI0dlPj746ubg5uzT9E7dhYnVJ1Izb01yz8/NA8sHEXWHBeWUPz/9Pk9R1TvOmhWjpfzxIvfl+3FY2p+jg/NyzvxcpOslvS8R0Pz7znPvalkFURNHtJfUu4aWyE7nHJXpPVY5UAceOYTWmcaEzFD9NdkB/OMdS75A3Q4kO4DJz0WEHbBZdgfbN1Xxt/FUqVZM2LuSKfs3EbD8TPT1MxJNadlScd40NMjZvwcm+XJxwFq9fuyPQcvb9uHbxyzctw9zMMuXh169lD/hbH2zdgwrtIv3dj6QJs3Pfwl9/Jgsa4rQV2MHU6a3+rvuZmgoQ+tkxblSMQ7bRf5I1LUqTL4H6Vl+PHLEMykWYtHHH4ccOrg0P0L+8g1UDtGYS7bYr37HoT5rVHVTqc2G0KEDrO8YPTeb+ebhbNrmR8CeRcrUBXIpsoBx4hJRv3rhCS6ScwIrte3Qz1EAs2JtWNRiikq1TgDoVYfbU6/3afa0V08jUnZ5BW4stObjmTZkLhkmgyFf10Qyvyy50Ov9hauDLlAqeym1o9RYbobTpvr4pT+goKf7Rg2YiM80hc4p9fu1LM5rjuewjwSk1yLLrCzc6H2DSf2KYLezCMFjJ1LUTuEiFMdPgreSxY8pf97Vdc4UNy9LuhBfhh8bjpe/Fyuaroh22rMvzWbckmtcsHJUsr6Scz51SkEER2Ehqx2418ued07bMDtago/DP6KTRoe229tipGfEjLqKV6QyYb+eOJEl/R+oIpoSCU0IezV5LTOP2fFukAk72u5Q26Xo9mqfXMW1Y81Ife2SAkWOg5mawtdqaVhYbiz1O4ZBmd+8IZ9tTlwVDsdkBzAO+5rcRCGk9vLy8iJDggpCJm/t/+oO1LBeybN0m3ltq5C33nvnTMlFptxo84UypaKpT5KjtTiBYRxeGfo1oWPZRizraRntVjSbZ8M1lxe4Lw3L4y1erDgNYVq0qsZ79rB8Sgdm1CnF82lXIvVnOiAH9V2MmHpM0a/9a+z2bTrZlEOn5UiWdfkhA/5rdt3ndCfV6U2s3BnRqU2q+ZdufI0nFevz1XA2GmvWwIULHHQ5SDuHIUzN4aLKsmfu047J/UwZX0uULKO2KSftGbfyDD6rd6v42VSIVkERSHguph5ENP2rKEqy+WDYMgstCjelcpuh1NtYjypX3lKrirYqbTnpmiUdW6dnVj31YR5xEA6tKsvJySOoMLedUhAWXkcsITc+KIiANKlJMyGU10NeR6pJ/DFUx60WbFlhQFChj2hm0FZb/5oQ0xKgUemUJlwu7sWxyUo9WgvHFpjmMMW63Di+jp9JtvunkNIE4dfMmsqIjLopYxW42tb/LNXWmpPd9zmll5dmeOXhdCzRMdrpr765mgHLt3K003FFkk7oeSwto6WD8i/7D8NudiDPuSCOvzjM0c4KwboALzrs7KCqAdVKqaWMK4jiLFlwcnxBq8E5cXNLiN0E14FzGfF0OVn612JpE/XSglXWVMH/Qj+OHphMpk2L4gw6Mi7kj2tbLW60Pk5RE0WhR8os6nZOxYnNwfK3ZAcwYW5rgvSiA0QPmUuQYRKkk2QH8LdtlA+NWAJ8sxLkBiV1J/oWvSlfIiP7Byun6JDQENKMz8owg4NMswwjh1M3KZEOE/mAMF2pVANMsas3lpFmUgYbtQ10WMnaqzv4ujRMJUNoYAQNLCd36VNSyhUrUrVxTVKUzs7Z4ZFTymYzu5D39GYWrHFTUsh/iX0fPwUT93kM7jmffpU7R5rVtKMrOLxpEKfb7UGzsXrkc2IuRafWEoq13IPTzZyK7MO0aXj6eZJpRmbau71juGU2FYXN1gGjaF2sdbRT2XZ/B+0WzuDZyGuq26cqCZAcsgjQFlFPIB2btUkwcWOZPtharcDN+g36Ojkos6IMxj4DeXOgBzlzwun8lZjRcgCdSqpX1Jh0ZhIrtj9nfPH19AteROj+A4wufUTlcyxYoFCgJJi9fo1H0dxkHw7fxnwjbSr1QJ+xxycydZEb3qWLovPASYHgJoJVLPIFQ5PMmLYbzJgWc1UjbLq7iekXpytpWtFZzJ8f233WTLg6Q+W4HeyxibNnoZT64GWkWS6rvZ1Gj5olvPcAACAASURBVObw+cYyKq+urKJH0dUS3yRq2/94P22WjWN3vTs0bIhyYJBiQMnpq0vPP3xIcGlTyuZwJ/uUjtTLV48hlRQFEUm7llpWCstylhGpZypXxrdjL7QHmkfHMhWrXX/ecRzmwduobdmZCdXVEwzKgePV5XJs3nmIfJO7KwSLcbAquc9xsWd1fEZ6k15L3AvF+nbWZ/kmFc1WsgMYh31NrCbeYVJv0v9BQL2AZmKNHrt+/5MOoDh5L974ceH+C248c8X5rSuuXq6893fla0pXQkM1KJ26Dadsh6ObIYF4A2J3X/6Vq1VI24EmzG0+Hqt6v9KpBcabkdmnOk7zrNXPS/JEUt/y6JHKeRMgSaqxWdjf9ihNJH8Rjc07eIDhR8YQtPDur6skDSQ8JFK1LqAQc3PSut/Hom5NFna0itSbSE6t3jSEW4bWpJ6cuGoKsbkxXmWqoV/vBhcHncPUIPI+HH9ymg6Lm/PiU0e0N6iPIsRmvNhc++kTZOnZA+s+OZg9aJuSepNqcyDvjBIEHp/M5A7N6fNCl5sDLlBSP3qgyuXXl6mysBXnm7urqCBVJjQrkrdNALHZAzY3eHaoEru6leKs5TVV94uvLmbNjQ08HHqF7/7BaNlk4HqfqxhnU689fcDlAOabR9Dw+UPWW98hoGJVCmf1pFVbTZXfJRzkCQbCvXSJ652aUbGLH0GTfaK8NcJP2HfhDl6W6UPOdVPgxo3Y3MYYXSt0P5ZpVrJrmCW7+53hn9yKp/vV/yv6s/VxsnBSERm7VDPGpM5TtrXfqUqnZtt7jZVTjGPMlrOoyCKaaB2lt7U/RbMUxb7hn8mPndycqLq4OZtN3wpjiwIg+oEELlcu8vqGDMHl0gcGZFrNxaqZVHMvnu1XanXbg20MOjxIpQSz8+FOjj0/RqcvuZny2JBc57dKmasSaYynPavXD7M8hxnSbxwWZdRz5Yhe75lLX7Ff60WlPiUV7b04mFm+KVxuP4kPUwMjtH7RsSVGW3bL/0t2AOOwr4nVRKq9Bc8keO3wzmBijReffv/fOoAhQcE8vHaH65fO4/L8Jm+8XXgf6sb7tJ9x0/XnvU4waQI1yOqjh1bKEmTLWJJC2YwwyW3Et4Dv2J63wSjAjAfzI1OSxGfD/+a2N+/7Yrpdl+dVdmA0bYEir1S0KP1rFmTDO0+8V6heNpFN0LuTJ4PQ8wMPn/hivFkbd6sP5ND9hXxV1/Tw7Zs02lIPf9uPvz6+8hEQB/DIEWjXjq/tLMgwKQ97uq2nWamI/G7S55NPTykyvyifVmdH7/WLhCP7is/N+vqVl7kzYTQ4BN+xPmojQK+9XpNnbl68lmZD590bRY4hiUwy7NUdS7C96yial+2sAHDCgDfmO/uydmV66qQdzgmTHNFGsH5MV9aSe14ethj7075NGCmvyEnIPYwvA29gIK8MKtCswxfMO1kxqIIwaIEgLQ3nGjLe8Dyv3QPZkqIhH4Z/UNWuqrO3X9+qrs+43Iuzh9KSr3QG7q+9QdkuRVXgW8EdCMo4QczRkR2zJmHe0I+vti+i7PLwk8OYLR7GtVIbMRlaSyGrS2ATVp5T5crTv/9tvozzIbXmr1IO0ayVurmptadSb6IRRXzSsnCuM623tebqweJMqzcpxhLFizJNIG2DS4wpc4/HAx6jpxU9l58s09XTlfz2BVmdNwDz7mHPvxxEBEQ0SLnPP02iyoaGLKq1i9O54JJhe9yHukdQGpIo4KgTo3C47UCjgo1oWbQllrt6YncsCEctT5o0SZDzCM/Lt6PKP2dYbbmWhgUldBnZHG45MOPoOmyXmNKmeaASZo6lyauwo3FbHpmd4pZC+fLTvLduRVcKdJMdwFjuauJeLgqKUln8HKgEhFNajDBwApxD4r2Q/2kHMCQ4BOdrdxUnz/Umr7we8VbjNe7pP/Fa7zs+aSCHlyY5vmZAP0Cf7GmMyJ2tKMa58lMuTy7yePuhIZxTwhclEkQjRvzM/Z64+4C6O0pzue1LKhb/e9KK8b7j0XQwcfV55jwx4+tCfzRGjUaVk7lwgQvLxtLALBT30d5kyKhGGFhe1iIvEHbCXbP/IRZO5Qi29YlSBu7HNDy+fiD73GzcauODSTH1KN4j5z7S8HRWPEd6qv2oyEs/7fjs7N0RSP3F20E0r/5tO3CALRP6YNk4A562kWkiZHqSXk81KR23V6eixK6TIACYJLLFK3wZ4J4Bt0pbMexlraQAw0xUDAZtXITn3nEYmA/lzajoybylWVBIEKknp2VYmsfMHC05YFAVXBkZwevXkD2iUkKsljlpEk72jvxj9ZQXQ1wj1NP1PdCXgOAADHQMcPnkwrY226LtOufcnKTYu573TrVwzlwFLdu2PKltwrHV//DURVPFRJQgNmcOcw/tYEblQDxsr0fZ5V2Pu5ReWJX9xq9o1FEvWiWcuM7rzG5P7k/NzJ7e/3CiV0Q6n1Oup2jp2JJ+Zfux7tpKnJenQtfVnTW3HRixxYGxOc6r9MD/ZBJlXJGqD4tG76FP03EMrDDwT01U/+4b4Iv2NG1mZP7AiAFhh0URvxVKnN9vhrynJ02iRvZH6DSfgF7eF2xoEVli7/eBHa+vY+iW7vT59oQ3IQVYrgAn4mWvCtWhcNtLOA28EmV0/IrbFRqub8bIeSMYVeNKnNL74vP2rGnK13rf2WcTEZLt7e2Nrq4qxZ4cAYzX3UzYxvKFlGB2gTBFkDDp7UiDRA+PTNg5RdXbX+8AipP3+OYDrl86x6OnN3jt9Qh3XvFWnLyM3/maBrJ7a2LgrUMO/+wYpM5PXv0SlChRkUq1qpElm3pZsQgbIrxzcuoULSn5E2bZrOtiqtuAwxOiSH0mzT1KslGaDBmBhsc89rffSXh5Cv/HD8iwsQRnL1en4u59oPOrDkUFF5Q0rxRpCTGXMJwvOsCaV6PwmamejiP8glRqCGMzM7/0SQa2US+M03/ucRw+9OXbtGdR7kXFWR3JceExu7OXJUHe8PHd9UGD6OZ6jXuVc3NzdNQUKvoTS2N1Ph2jq9RWoqhJZG2Gnedw+nb46A6Dc+d+gndk+Dfeb8hnn49iqRtSwTgHy6Iocv99qlknGWPyYQbHFzf59U+CshV0+A9m4diu79o1QqtXJ0+R4WTtdZQb/SKCgITgWWoBxQE91PFQlHQrP4btvb83AX5paJZqIdoXWtJK+wCa6dJjrFOFB+P38OmDZsIEYq2sGPr8PntKa/LcJqy+Vc3aP/t9JvPMzCzJ5U2/4XkVEESZMrHdpWivP95zK/O/9aViX2vGVxeRqogmqcpdzrtY22g5VUo0UdVtPs6igfGiUgz57s2s6X8mp5bSvQ0VazDD4ipvx37+BcKIwUpSTdSmf5qrzB8TRuJ8+rTC8ykHh/BR8erVCWnchIxThpPHtiLW1frRzeTPdXVy0Co8Ih2dQvpw9JK90ALG257mKkVBi7uqiHOWdOqzHD+k/jrMW84m43VoxIF3UthjLLvkIHu90iwYEpGUMdkBBIWu/u81gTZGFKX8u+b6VziA4uS53H7ItQvnePzsBq++POItr1SRPDc9P7y1QN9bE0NvHbL7Z8cwdT7yZitB8eIVqFirGtmyC4V8PE20I+VjJbkxExNVZ+3mLuT4y4N8tj8Sz87/B5r7+tKolwH5tUxYuOZspAlnH16ZQXc9GfMutSISmisXyLG/cWMFtCHo3TCrMW46rwNv8WxG9NxxP67PNLwSTbINYv1wVTojkpkMsiMo0z3uT4q6v7VX9tBvS3++bvhOSo93kbVBk/gWhBYpQp7yujSu15qlnYdHOXp9+/54XnrOVZd3CmAiiaxgt9loF7vArXvaCvmwRMDDWaddndh8bzNnup2het6YUaVUmN0Wj9umvNg48ldPUnQl+sePH8f+nkhtablyOJfrimn609h2bYB15ciHsTMvzqic1qjAH+HXden1JepvrM+wSsOYeW4qy+7kwmzTDRVq1W3zOO6s7aHw0cXXWrWireZ3npTQ49Z4SQqpN5WO8qT0DEl/g1nbuihRdFUxXMLZ1WJdaNBsN3v6HqJanj8knqpUUSnyhHbrRlqbjNR/e5q9y/+sWCq+zTI7Q1LUy8+6IZEpj6Jbje6EfDQKXMOWaeFEigWUJOUDP4jE5b3coAGuZ15SqGYIodb6vLR6iWEG5dD5J5s9rDK7Ur7irgBuvONfbXE1jwGVu38kcJJ/tFkOg9mGZFs4khsa89F8IUnB2JlI9/UfpUXtFv0Y2i4iFVOyA/j3O4Cxu9sJe7VEGKU6VZw8qSwWLaLfaT2TzAEUJ+/pvcdcPS+RvOu8/uLM29BXuKf7iFtGP7zEyfuaAkMvcfL0MUiVX3HyjMtTqXZ1suWIvpYsQbZOXr4XLoBIDmhosO/KfZrtr4DfBG+00vw/BoOEhhLarTvZszgysdZ+LJtE1khtNX8qZx5f4VNIDti3T+F5k70SZl5xngXxGWY5BnSibJ6i7B8eM0BGyfE9SPEtB7fnqCebTmdZg57lO7Cwe58ob/P3oO/o2uRk/d5Q2s3ekmiEujF6zl69IqhAPlJba3O+10n+yRc1EGbusS2M3DmTgNX30JC3vcBZk8C0urXEokFFFtmuBWFYFtLmcCb7+eLLC4pkiTmCd/COqSzeeRu/9dt+yfIJIkg8Kvlt9ewZ85XJ4aJVKxURXRcjBzYb5uPV0Bcx/uBHN9CUc1PY77KfKQX7ULuBJeIRONzfyIDNc1lU7J5gjuJv5ctTpbA+qUsacWp49LVfmccbUz1gJrtc1ykSaFKKklAWEsLVnJmp0vsb3uO8/hyZs7aGb99UUiD5plRG9/EAbq2PnspFpuroCOMupGZmlbG0aBdZ9zi65RhOrEiRL0M5aR+uALN7d4UQWupIpRBOykxMTNhUcgZjd64ie6NVXLGITAkV1Tgf1y7B0HUAoSuceXCucLwFV44WSEunjpn5ODl6XhlJrzstz8/rS4tI4fct1vQSD6/60GW1DmN7ONCyQvcIy0t2AJMdwKiedwk5DACkOlXyZvKLFBGcQsC3cI0S1AEMDQnh2f0nOJ07y6Mn4uQ9wj30JW/TfeS13je80kK2CE5ePoyyFsfYWInkZTfMllCvvbj1I9QDefMqb7PatQkIDCaNjQ77Gt+kaaWYfwjjNvi/2GrVKl5NHkWeHp/5OOwLmbXlsYhoZx8+pMZmU1z7fSDv4a1KfY6kfKdMieC0yLs65dCCzKo1n6FNYwaA77tqBRtvbcVncWSFROenvhRbn5FbPR9hkiestiyKrRq1ewFrzkxg/+PGVDgSddQl0Xd69WqOrFxIkzov8Z/8MUpQgszjtZcbueca4XKwHAUtuiYaEXD4NXt4hJJ9lgFHO62nXtkGSv1fWPo+Pntz/uVFqi9pzqWWHlSsEA7Qsns39OgB9+7FzMGVh0hKMXbvJujyNTJ1cyBfgwPctjoTn+lFbitOphAInj+PT9H8ZJyqT3ufy2yYnQDSfDlyUKBhKUxNq+LYf2y08za2bUGad9W4qeOhqJOIDltC2a1bzLSsxLa21bk+JOpU9M/htm1TNJJv3qSWfU8eXcuB+8bIHJa/T2/6/C+M9sqIR6PTZCsXGagV3XKK2zUj5eva3F4eDvQRFvFTMQsIiGjkSBUllLl1Jk7nqs3ABo3URoOjHOfePdpPKc1pzSEsaTlLdbaIswUE4FAhDdOaV8JlYvTco3Mvz8XW4QSeKw/Hqb7zzsZ71L5biqODr2JqGFEfOdkBTHYAo3qGJdYsZE9htPxI+ModGCr0T/FyAENDef7gKU7nzuH85BqvPB/iHvKKt+k+/HTysvqkIOcXbSWSl9KIvGFOXoUa1TDIHY9i8Dj/YmPRUCJb16//FMHUHlKenkWtse+tXsszFj3/nZfevg1VqjDY0pK1wefwmqP+VC2pKp0RJWmUyYpto6OO5Bx1ekmDgwV4b/2ZrLrhagWjWf2ZBw+puaUsrwZ8JFf2dBGu7DprCzs/TMZ3pnogRfiLg0OCaWRbnxu+p9F9NwX7rn1pUufPSER1U3v4MFTlGxgYxKHKpF07mmi48bpYXu5M+LMjqj+mMi2fZ2fpV39FPzeRbfMhVzpdKcy3xqdI29AMhBMmAYgvA4MD0ZlkQJPvgoCtpVqF4ECE2tF4fi80r11RatyiA4T4+yv1grIPp0+z5WYuulzPh2O3RbQybpHwOyPkf/36qWrOyk5vx5cnxXi6OnYRrEiTCggALS0y9f6HbpXNmde1R7TzbjJ/JDcfeuNuagK7doEA0xLIAmbZ88+dKTTqPAqbBvL6/4MJZDh/flXktf/OJTicvMg3h+j1vKXHLmMOcuFbE1xHv1M4JWNhdeYM4snjVLxcMSdiKzk0iCKIn5/qMBBQsz5ZS9zBv3MlXg99Sdb0WWM+SmAgJ4qno1kbXaxSuDNl8p/rGqPs/N07xnXKwbn65pwbsSbaOVx9c5UqyxrgNcuftDevQbGwOscYzvyKjSOVaM/7Ye8jrTfZAUx2ANU9RhK++RKGQHYKd4G8VUSY8RfKIRolkBfOz7ly5gzOLtd46enM25CXvE37gdcZv/ElbShZxMnz0ibH92zkECcvizHGxSpQoUZ1DPP+D6NmPTyU+jYXF1U0sOAwc3Kkz805m78BsxPDt0ZML5MvsyBPu3cn16f75NcrwpmJUevS9lvhwKpH0/GYdIdMGcKY9n8bq/bEadzzOc37OcdiOgsVgWu6EUXpnGsCKwf9SjcFBYWiM7QSZvlb4zg4/GMbddeh/v4cLKfH0KbFeBL6FNuiBxjXpWqM5yIXtrTZyO7vA9Dw1Wdp7W30aRZDJlxpHByMl0FWsnQPYXXTnXQVcMcfrP/aJay7vgivVc/Q/PQZRUoj8azrrE3sf78QT5OBSu1meNWVeA7ba9NEVl/cj1na6Vx/KYAtJ1Kk8yLV56Is83lI5/tOaMohq0uXCGUDiNMkArTybyL1t20bgTmNMOw+ktRFTvBq3DVSaCQCTY5oz0r5wvTpWG9ZyuLTu/i+4nj8dsHVVVVXmap/YabVmsWwZgq/YlQ2bNMallzYyLeWo/+oghHbibnXbk7eSoe4OfAWxfXV8yNG6FOir+LA7dvHkq+fGXhgKMH2j/44bLUBw8nhMRvHLYGQUg1TQDQ99Fgxn903z+K57DeaKYnQiqKMIMmNjNi4KYRe5+vQq1kJFsSAY/D3IUPKlCZHI3dyv17KtXXRE9RHu+AHD2gzyYQ0tW3Z2Dd6bj85lOpONmTdDk1azV+nkNvHwnb1HUGnzHP5ZhcYqdYw2QFMdgDVPUpSRCScDlLK/DjcBUJwILyEvcP9P1UKeKSlBR6+T3kb8kJx8vS+4ZkulCy+Ghh+UZw8A00j8oiTV7Q8FWpWJ6dRzIpvY/Gs/z2XClmUsNmOGUMtm8m8/PqMZ7PX/T3zS4iZSG2W0Lxoa/N+9Tr0Z+dkc/1TdKgeMc0Qfii/gACyjqxCNs2C3LRZgd5vjsqZe0+otakidqYbGdNGPTdWVFPvNH8x21/P59HwS+TLnlVFkVJvih1nvFfhMc6ZzBli4RQJ6rRsWbrr6bDBdSafJrqgp61eieH3+Ry/8YR6u0sxv+omjty7xom3jnjaOaOdNoYRg2vXMJ9ShQMFKvJ+1pk/0uDI+L7+fuiNL8iyS4H0HLEyAgI7IW71730YD+9POq3UXNPQUZCWDmEyfAkwmH+QP02W9cPJ4yxGOkVoXKoCBhkzc+DmVU6+2YvW17SYu2rSwPkNeXTzoq2XBS3fAEKePyVYNwPBvS0I7NSJiy5vmbB9E28y7OaG5QVKGSYEMkPNAhcuVCJuBw5w6sE9am+uxNexX9BOFzsnJkLPgqru3BmNjr5sb3KC1lWiB1FsPHeBrvvaEdz3HBrFiioRL80EqDkODWVrGV361NXhywy3GD2LqnUIjVL79pz/pzrVtpTAf4IfqVNF73wXsaxPB5cLTDwh9LexM7sd+7A9Px5/+ztRNnz4+i3lxluhU/A2T4ZdV2n/xtrMzbHWdmWJfyr84uPknz+PycY6NK25Edv2bf44jTpzB6B3cSc7ms9UDj6xsKXtmjBN34lXCz5EapXsACY7gOoepVhHADMXS4l2aHq0NTJQumgZmjVsTfnq1chdQPis/4MmfFO2tipF9N5LNrLt6Sq+zIuMjP2f3RlJswnNgiAzL16k18atbHi0hG/zbpIiRfQpTydnN2otbYdfhjvoBhZFSyMDGmjgF+LNlzR3KBMwlOvTp8U6o/g9IIh8wzrzLsMB9AKL4pPiDcEBqVjfaC+daiuo7Bjb6tWwZg3B5y6QblgJehSxZmmfmFX2m44fwGdfb1znrlfVgGqPKEHv4iNY1DNiAXZUc1k0uAOj0+7kaJenVDaO+e+n76KtbH7dgyefW6O/cn2MlxqXC7Wty2BecBQLT++E0qXjrFAQ27HFOZy97xBLzznyPuQ6ITpuBKcKAI0w/UXpMFQDQjThqyF5Nari2G8S5Qvmj+1QMb9eKEcE9fHiBUHBIaQal5E9zc/SrEIsn7nwI27axPcli0hb7wrXO7hjWij6jMir917kWZKRJz1fUSBvHpAIosihxdecnWlhUxyPvKO5NP3PdXw/h7OyUiH8P9nOJMv8tNw3d8c4d/Rr0B9cgFk3A+h6/hefZEynv+PcfdocrUSInXckJ/XTt08MPzyBtbcdyOHbgBs2y8iuE8da8fnzeXvyCAYlLnKw/XEalYxG2jK6ye/di+7lViyqfY0udf+MkF5+6CLDztXig954tEbFDBj3Y/hJLYzZlTUld1cozvHRo0dVf8QCAgJYrLAvJPMAxvRh+49cp64G8C0glJ7xqwH8L2ygr68iR3TnDgsfvWfIhU4EzYr9i+2v3CrhQBDNXgG8HDzIhzQpMbQtRdustmwcLjihP5ukZh0O3efi40d4f/eRrCd66dLTvFw5WtQ0+nMHUVwhGZ8lu+7g9MSFXJmyMbhVJfSzxDDyFr5Pd3flA/r+PbXnreGR/2nezPxzbZ1K93h0TsYU2YBNdyV1W3fCPO5+P4DHzJN/XNcbr3cUm5aLQW97YLsudmyzgYGhFOhThQp+N9m2yTf+PBVRzNbH3xedqbocaeBK/X5NFfoXeR6S2CTTKBxnHz+G8j0wkJDgFGiEapI+vYYqA54li6qMLvHtwwfIlk0BX2TIQNoB/zCoUj9mdIqs3RzjyUyfztNbFylY5BCeQwPQ040+mid7oTmoGAubTae/xSBYu1YhVo+nPV9kS1GPScwzfoJl++gBVBGGkgPUxo2EnjpNihHZ2dZqD20qRu0sSQlHmvFpOX2uJP+cuxrrWauAXpu0eTf0Pfo6v+r6BIVedU11vFxKUunbFA6sLvkLXR7rUVDAJAMGkNW0JTnL3uKWddxqLd+vnI+++xCut/LGtPifI5GfPoVSxCYT9pqV6Tjvz++h8Evr1yITdzJV59LqyCpMyRHA5AhgVD8DKZgSFLDAMMUZFLVqeaMVTkwUcFx+k39tGyGGrl2byw3aUXlbHnzH+JEuzZ+dERf3t7RcNoIngacJTPkZeUQ1QlKSIjQVqUNCSBMMqUNSkjI0DSEpMhKSMhOpU2iRKoUWaVJokVpTi1y6Bgxt0IaaRf58uoxq/74FfuPB+4d8/f6NUI0gJSLn6Uno6FEg7PETJ3HX4zM2x2cR4pkXj/l7SauVCDVW/9YNNjYGOzvWpi5Mjytl8ZvoSZqUaaKdzeVn96m8pgKvB3iSM4dyr7cde0G7iwX4OsYL7TTRp6Fb2Vvh77SAnROekaZI7B3hNZteMvR+XrZXXkHdpr0SZeccnc7Qfltn/GxfoZVFW9GeTRDiu0SZbtJ0KqCUPXugYkVy9utNifyZOTxsWtzH7t+fk3hRJ90JQma+i1E0PGP3HtSrlANHx8tKmjABuGjaDzHC+ZUOJ5ffVTnUMTahdZLykA8fSNW/ogo8MsYsahCcm7cbuebm5t3VVugf2h7jYX5cKGdSoXDab76RJsUVx1cAReVWlsP/6T/kvLuIQwc14uf8SadhAJcePdzYbFCUA123Uydf7GrypJuDUy3o9c6Rm2O+xljgpladBqQyvstRe8FixtBCQmjWORW+2qM4sSIyRVayA5jsAEb3JEk1vxCnyRFFtIj+VR7AGD7yf89lS5aopHv8j55Ayy4t59o+omrx6E/Rn32+YjC5DBl8TOlr2p88WbKSIvA72fcvJuuZjfhmyMRHfSN8U6Yk+Psn0no+5aNuNq4Wb4dbhtz4BfnhH/SdV75P+aS/g/Emy5jcOnY1I7KB1o6LmP9gBCEBacFfB1QOZzCGvCEALTw09AkNTUGoX0aK0ZrDkwaT2zBMv/XvuQPxm8nAgSpkq7edPbpTM3Oww1EalVIjLh9ulDGO65lzZgX+Sy/8/L+SLdcanVslLt+tmoJsVWeS3tSblIlt+zLT9G7cosUSCWrftCifCmpwYp6iq5zQ1m3VVHZfvoX3hNkK2lM431L/+WCT0PP4q/qTwvx27aBXLyoMno9XxjM8mrQn7lM0M2O1sT59vK8TtDhm5N6le67ii5EDri+KQo4cSglKHE0icvZO9tjstcZstwPrHsUssv9zOHkmtLXhzRt0xg6mfbWyrOweNTfh4Uen6LSsBW6+3Ui3MvZ6txL51+zYklGdKzGtiUKaPv3CdNZc38TLMTdwcU5Nnjxx3IzwzWSg9OnZa3ObQbf2k6nGJm70vhFrcNGEEdU55PqGS5uexvinY1V6HovMhvJxtHo5S7Wrc3enlK0hebV2sHdeZN6aZAcw2QGM768iQXkA4zuZv6q9nBYLFFCdglPalWZe9bUMbBq9IkLLudM57LqXz7MuKtE0odcQpQz5stvbK6z24ek2wghXVWk4qeXo9kvWyGLGIdZ4d+DN8Ofk0Iu50snmy6fotL85PdMeYGirqmTMqEHIWw+ytqrKt3LVeTN+/LS/hwAAIABJREFUOZqpUqhqzCXwEV7V7a/a//hORrjnxo9XaYqm71eP7uVbsti8b7S9VptmhZtbCM8XR/yIZe7dkVqlCrO9f9T0IHvuHqfH2hY89+yBnkPsP4I/Jra6y1z6GlnjMfoTmdJminK+rp6ufPn+hdI5YhclLmnXltA3ptxrURr694cnT+K70//77QcMUPLNs2fTetwezmDDR7uYOW5qF1+mDBOal2f265d8E/63GJjlyHcsS5uTNymHkcP5NWz6M32Qum633NuC7TlbPL99ZvcCD0618mDM/DjUzIk6zOLFGGw6TgnTbxwd9Evp5/dx7c+sZ/m64dwrYIXm2NExWG3kS9LXn0HZFpc423cvTz8/pdSyUtR/dxLdrxUTEqMEJUviMdAOw4H1MJxWBLtatnQpFbtDdpOhRnAjHwfO/rks5MdKZ9Q/xZrCDZjez5EWRWNWchF66RK6B6rQVuMOq6aUiLRpyQ5gsgMYpx9buEbJDmB0O1iihMqJ0L44jz6lhjCnRzim+t/ayak77YhCmOeeztKBrSAwEOrWVdKtQiwdXUHTqVOKEoPQYIgcncImgvagqnQs2Y7VfSSbHzPLOaYOWb7W5PbCMPJZ6ahePciaFUSWK7y2Zsy6/N+8SihuZM3u7hSaPIcsBj5cGrsk2rVkH1WdCmm6s9cmImCk4uCFfNQ7zFObiFqc4TtrscyKdIdXs6nvNiV9Fkd7cfMzLZdnwbLpTCyaqKe+8fDxoMTSEnz49oEHlg8oljXm3GKZxpakrqYdjtndFEk/eeb+6yaHM/kN7t3L8Lk3sfesS4Dtp7jvStasdB/Sgn1Pg/i8JnqeuB+DrFwJI5yrMbFAXqw2Po0TNc+qm6sYdWIUM+vOxOxlDr617Iv33ZcULx6HpUhdaLVqFL2TAq0iZ7g1KnIN2o9erXfN5PaW2ZxsPFNFKRUXK1zFGdd6pXk77A0tHFtQIlspHLstVGXmRZ0uwaxNG0LLlSfv4uG0mrKakz4LuNM3avTx7+NKnXDWcWlpvb8Xy+/+oNn98+yWDnLm4dMSBFlasLTJsj83EOLeDUvI+aw/41P6YjMuIj+qdJDsACY7gDF6kKK5KNkBjG4HRY3A05PsOp+omrMW24eFY6r/rd2Z+87U3Gr6i8zYzk5x/K5ciRmvm9BRzJsHDx/+dBYbTljMze878Zj5f+ydB1iO+xvHP6goJCqyycree4+s7E3KKJLILEKFJEQoK4coM3uvCNl7b9kZmZGipP/1ex4rrbflr3Pe+7rOda5z+v3u5/7d7/O87/3c4/uNzZARl9nPQl6Szy0vWxs9pF3jbzA9IrM4Z46E7P/vTffF8yFWqSIxCLS68p4rUet54pIwNqHqBG0mFNmLo3lMKBwr18Mse2dCmHP8pd38E0oza+tdepwKAY3YX9ZJeVBNDEvzpmIGds6Muwxs7++A194zRL7Ro2t7Tea3mauQeoFJpjYpK1PyX8YucKkE9otodfiviwiCxbN+/TpLVr9iwB1dPth9IJtatqR7RkC4aGjQzKU3t28V4tGyuOkNf1cs4O66TFyHequhXJ0fTY5HwUm6tuiZKzynMAuMFtDBoAN+TaeheuksjV5tSJKeH4sFdd+7d9T92oTHBdx45BA/7VqPZSNRX7+MZcN9k03BKFquH9RvwYtMZ8mdNTdzypzFpHtWnj1LHUScH+cSvNTPn9Mncgm6Bd4zTz03ly0vU1JbkGQlLmefnqXp/NqMWr8Ih9uKUxuu+ycENTctHIaU4bLV74yscV93r3M/zF9vZHTh9xI2+u+iDACVAWDid2zCK5QBYEL+2b9feqMt1aM1ubPpcmRi/F/mlou9WHnFhw8eh+DePRDZQwExIYCWFRGRqRM8oKamMEIMa4P3ruv0PV6NzxNDUFNJvEfPadN6Jh10JmLuRTnRJyYbRRlb4LwJbMP/mogf9Q8fsK3UHY+H5oRPi5+M/f3n9+SYloMd9V9j1CRm6XXj7ld0Oa1LyNgQNDPHpskLjwwn25RsnNhVhxpnjqTYy8M6TGVNSXteuESQIQ48uMKuBrxa60IWja9kaz2Zh3aKZTAC3wRSfE5p9jUMw3CxMVStmrq8syk++f9JgQB9F89rWBiHj2aksV82rg07S2ndZGAPipJ6uXKUcWiESmAnLnvFz1/962lFt4iO7leaL2rJrRt+FClXD+3sufFs44mORuITHP73/em9qTePhj/Bwz0jRUd3purgmhT0SCavsPjO8PGhfflJHMplSsjEB/F+OI08etF4/UYc55+V/ZgMMTcHrXyvKdtxG21LtWXqBB3p60sMJKeqrFgBixez3OwIIuuaeWATupXtxqBqCbeHfLdhSsAUTi2dSa1bKxh/MiZ/dkJ2njgejU4rdUqP+sJ7u/doqCb+kjhrVG18377Bou6tOGm0lQGgMgBM6bOhDAAT8uCnTxIheYtBpjxS/cKN6UviXV3FfjBfwtW5PHMWiG8zUQL2TiJ49IYNciYiMFB67f0Q+hXNKdps7+ZHmyrxAzR/N6qxy2juB4XyYN63EoOrq0yldORIqlB9pfRm++P7BZ3Y8OGsdT9Az5NFZUDbTHEPPJx9fInqCxrw0PIdhQrFxEIUdGYF5+px2HIzDfRrxzrGiccnaeXRgEvRMynsGn+WWNHzey78wLCnmlyus4KSrWLCkQS9D5ImLk2evSarVjgL1fMTYvcuzsD09+ttu7mT9vNsuDviOsV61YRRo6Bb/G0Nitqb7teJZ1VdHe7e5UZ4EcouLM0u69m0LN4y6UcTpWRzc3L3yUK5p7Pw91S8HaBUKZjhGkm0Q3Y+ODuy8u0himoVZZECJcMxfmN4GfaKz+uWCmhPboUXJPNaH2jcOOlnEDuEkq5dseh3iKWqFYh0DI8XSLrctIaM9g2g7/5XMnxWMkS0QYvnTAR8omVavLeKgki7dslQltCW06ell+EHp4MFWQu2OyfxIPQ2qzop1nNZz6se3ZdeJ0x7O2O21VXYOEEw9UFPn7pT3rLFdBe1C8b+HvldWV+r/Dx+WhmLnjvifEyVAaAyAFT4BoxnoTIATMyDrVszIm8W1uaI5Jnb9nhX5xhdky75h7O0c10oWVLCEER8oydFBDuHvr48MPINmy3rkAYMrG7G7F8GROJTqTemCTU1jNnqaCY3EYpvUREEdumSFCv+PWtFCiFXLu4cvE9JvxLcGnaVkjol4jzfokNbsPSdyJd5F2ORMIjhQRWzpkzp3pNxLc1j7XfZ4sLhDePZPOkJ6sXypdh/olrfbX4Bxqrkw9wzJq6az6UVDPjHg82tT0sfccfjupwYsovq+ROecBZGTfVbyPjlO/i8bCdqBfPA9u2KZ6hTfKq/XIF4VhYt4kX5ZuiNbsG8IZ2xqvkraZKC9nt7E73Mi8yNztH57SnWzFWAfu2batE+lz8/OG+vAM7OnK+Wn/rL6vN2zNt4X1y+W9XEuwllonqxcbw5Vw4Eo1M2zw9sQwUtj7lMgDTq6uIy8QnjKCDZoJUlbl7t/BOL47n6IW1uCVDvZHBnIxcpfHzkosnVq/JtKUxIYTdF7KNLqVYdqTJQtHw2+rlsx/fNWKmXNjERVYJc03Nxa44K27peZISnQWJbfvxdBLXHVepjP/EDnVqYM6RG4n3d5UdkQe+MDTYOTlIb9++iDACVAaDCN6AyAEymq9zdWbJrKcPLqBHqdiZOJV+iolCdmBXfxhfptvMfmV5r3brkXVBwDovgUZDCA0WtLSiqlxP/cdMS1ac2tiCO5VYzvnd92L1bzkQ+eEDKAbQSvfTfu6B6dT4PHkGW85NZ02c2ParFnZEZvGI23ocC+Pgr4Oq7d3I/ZpYsaPW2pEXDHPgOiP059LBrgNrFe/jsfpIqfhDQM3nbDKadpifLZ8dkhei2uh/rl+chdPM0RFahuEsdfIYMpXfFnoleu6+PPet3Peej11y5L1UoECDISpEHd9q1I8LMkszd+2BjXpwZRvZJ98zkyby5fx3tIr7YfAlhhlPsloH4lIp5EU9POKXXHpo0Idramryz8rKu6zoaFG4Qry1iAC3n9JxUueJPk9JVmFDHH6lmKBhFUiLa2qwbsJdeag25MjT+kng2R022rchGk3tJwLj7za5Tp+Q5uOBgGQFHwFOKAZBUFxGJaWpKvdkm08qiXewB8zOVINQuNFGc0N13djN01xDuDr/HYqcXDJyQtGdnt2Y3Ng4IRq1JGalXMyF5/fEVuq661PA6xtz1dSQACWUAGNsHyXvdSPW7Kt0qVGYAE/vobt3icKvyGHbJQ8SMx3GuvvLwMRW8ivDS8h065YrCxo0/pnkTUx/r72IIRPRmCYaCbNkwtJ/D7ciDPJy2NUFVog9NY6oGfi2f0qxmXhlIVpDcu7kl2YR/1QYbGykTovrlPuPa9WBSh7gbtw3dhnHzeiYeL3GTaLAQTfAzZ8o/FgsWYLA/iKwlT3NubGyg23qDclLsSUu8d6xJNdfpN9/D10pdeBBlAbNmSXrFD31ulyJk81/C/f2GiISxWndThpkUZ3YHgfWesDSeY8adcwV4Mr4niAEZwXiTzIxNYtdKd3+3tgYVFel5UTUaTfdeEaw0Tgacj7k5F/NmoAYbmKH9VnQgKCwiOSUgAJ/3HEEura9SJaDb+m5UyVuFsfXGxqvn6YenFHArQLa5YRzan4UqR93Bz0/O8KZE6tThSMUhNM9hzy6LJTQuGrucLPAvszhn4dTyKtS4fy7ZV5PAoHPIAaCgIh4zBoyNk60u4Y2iT3HaNGbeMOL4iWj8qmlyvP9xyudJuH/Rbr8dL17ex6uXL2t8IulpkjS+6A0FhnOj8XX8m0VysM/BBG1cc2wRLqssebIsjOMX1DGII9mozAAqM4ApfUKUAWBiHoyO5mq5glTsFMyXyZ/j7INZvO8wlnv7EFV9Gjg4yBy7KflhFSwWAsOuRw+s52/F64Ejoa4XE7T0xN3r1FlWnXe2oeRQj4Q8eWSIj9qJ95ok5oJ0/XfRBzhiBDnr1saoTnFWDog7q1NhShcyBtXh4sKR8mTstGkydZQYEDA2ZnDbQWwq7s/zyb/9yN24QYElZWj2ZTvL56beoI1x/xDWFMpF0ILM5L0UKEUGYoijpHtpej95h/cSuYk8V+eJVGv2gH2WyxP9mMpMbYVqYAcudS0sDxrduJHonv/MAjGFL4KmbdvIYTSd6m0vsn9QMgL65s3Z3rYkPR8dYUH5S9JMV1Jk8GAotNWD1mp+7BiwjS91nbj9+hYrO62MV83RR0fpurYn7xwfSwyPmSwHSq0P0j2cEunXj5thhaimt59/zIfQs3zsLPOjkEcUmV2Ei+s6UOG6XLVIroivvU6d5K4VEQiKd680EZFqbNmSfSWsJChMjVEVmdxoMu0N2id4uQbLGtBXpxld2s/iwsGQ74hdCpu4ptJ0orX8GNX2Gs9GCWbW+MVoQV1q7riE4+5QgWQlvRj8LsoAUBkAKnzzxbNQGQAq4MHHfftSqKg3b0eHoiVKZ7+J1T/LWHF5Be+vZ4AWLVI+WTl+PDx6BCtWsGjLBaxONyVqqqCVi1/m7NrO6N3j+OJxBcT0sugZFKXo/wruX3yu+dYHWLbPIHQMvnLYdmGcKws6NKBU6ED2O7SReYRFCV4wRAjZvp2zg7tRr68K4ZNjEtaHDrUgu85iXHK9YOzQpJWEEvo83d1hwpNKLH2Vma7q1SRQ3sXnFjNm1SpcSh5m0LehxTImi8lQdiPXxibOa6o3sSLlX03Br1yQPBwk2gSU8uMzRjx3ly9ToK0XOo1Xc3Hk/qR7p1Qp5o83xO7YQ9a02y7hwCdFBIrMFvMdNNo7lkqZrmI2czM7P05MEKvO55IP0/YtRX3tYal0St26YGkJvVPAZyyMdnHhxb5LFNf/wmTzuoyoLaMT/Cqng07TwqMx/kf7U/moR1KOGmvt5MkyNbUIggV6VZqJYAnKnJlH1jMpWhSMVnagSdFGDK8Vf7pWZN91XHXYVWoquTtMg3v3pb1JkdWtVlDq5kKq9T2RYE9lwMMAWnobcmtPGQqduCCR9YgZpd9FGQAqA8Ck3H9xrVUGgAp48JPvBjRudOWc6SMq6xeMtaOZsz3Pnt7i2j9b5KBLZN9SIgIUrEcPBAjWyStvqL1Zh5Ax79HMEj/xeD/POWy+eIh3C7fI9RNRQlYQhDYlpqaLvdWr06NkaS4UD+HWpLhL6VoTDGid0Z3V6ufkwCggIMbRThpPpHbJSbwyu4V2gW+YYQ8fcqFhKWoaq7Kp9nvatEm9jhQxuN3KfShmHd4x13wDXLtGj/Pj2LqkDEedHaQuASGNLbZzI994njteTvSjUHfUpdvnPXizXh4QWBh3MJyoon/jgsuXoX59CfuuXOcdvK8+gUcKwuv8cIfoL9PQwHZ5L+ZvzMyBkQsEvXDSRbSBVK/OGKtQbodcx69wTQmXMEM8VYVJhyax+fB9KgQux8c7GrS04PBhqFQp6df+dcemTXy0cyJ3hbpYDdSQAKZ/l223tjFyXh/WBtlQbdO4FF1PBDoCCEFkAQUTXZqJaIs5fpwo3w1Si6/JyhFk1/zK3Fbx42kGfwwmz8w8PMi7ipcWblT4fFZhGrjv51g3cD/111hS2fEDW3psoVaB2DeHuI5gQZnwuRZ9jqqSa/86RE9wXB+9MgBUBoApfUaUAaAiHgwJIZeLFt61d9K2fetYO0qONab+42csDcsBgoIspSKeeFHCOXGCUP3yZHfJxtE+Z6hbMn7Gh4bONgS9+MRddw+5h1BAfPTqlVJL/h37bWyYdv0CsyqF8NI57kEeNXtthmnuw3V2Wwkn7HfcxNOnomm+UR2/m2WpvvqwlEEQZaS1BlEYfwnnsvUpRAkrtUTEZ1p1fSlvOZ3LZyrwlWh0DXbz/p9NfLxR78ePj8mYs2zI0orwSS8TvPT3Xi179adMvjhKwqpjXMp+sFPrrH+FHsnhWvDmDQ2H3ORiqc6EOCQ81PDswzMcDjrg2MiRApoF5Jeu3LnptLIt2xY14vrSkRIgQJJFREJZsxKw7jnGYzV4YqrJa9v4qQH7bOnDpYPF6JjLAcf+j6FIEbm/MyH2IUWMunaNr9VroF5nLN2t7uDT0SfWLpGVXuZhh0e2WVSblzwWEEVMSdU1Irs/dSqcPSvRYbd0nEuQ2kEpKItPDj84jMlmEw6+dOTJLF8afk4YVD4uPdtnXKeZXXVaLa1On4p96Fc5JuOQ2COu8THiIxsD9HjxIRvld8+Qbqu4RBkAKgPAlD4XygBQQQ8WHKaOi/ogek+bHWtHrlENmH7iOgPGeqUecJWAxhclyJEjyTSiOAtaLcaieZN4rS0z3hStqJIct7GUJztF40hKM5EK+uavX7ZzJ3vsBtGx3VfCpwTFMlewKKhNUWNN+Gp6eI+UAcl+A2AWA7P5xtdgxYcweh17J7OqaGgwxr4VM3weErpihTRYm5pSuFwQT7oW4m3389xoXZ1mfTQoteslZ0/9BAW3nxHElPACREyIQDVT/GDhT94/oeDsgiwpFInZ8qbylGhSG9RS83B/oy4xNHXwIF0WZGNzvjJ8cYy75/e76Y4HHZkcMJkh1Yfg0dpDHl1t2ZLSjrm56TGdV8fbJBcWT2r6eue1iZyta6Plkgv/Pgfi5X0WUDGv9w1ktKEJ/fPulrAvpT7klMrnz0Srq5Orsgs1Rhxkb+89sTROPjyZy3NnMr7mBiqPiQOrJKU2pMV+gbMkcFVevZK+You1W8clDTdOmsfPduJ51pNNNzcxY08zgnefw/D12iRbdnjHBxq21WTQ+j5oaekxrVnMHs2H7x5SwqMEgdaBFDS25JZ+K9rstoqXrlsZACoDwCTfhL9tUAaACnqwyOCCjHuaj4FbTsXaoTWqIKv8QjE6F5x6kCuigfvMGWmiWH1IHUbUsWZqrx7xWptvTHNqZu/KZoOcIKBkrlxR8GT/gWUhIQQWzUmJoRmJdPxMpoyZYhxaZHLyueUj8Fhv9MvqyAi0v4mo7ql0N8a6uwGz1asKIk5o355WKwcQsMmAj7snpLojO3eGoxXL4NF5Ihe9pnLxzTsKZ3kQo3K73OcL/e6r8njEYzkLFY9cfnGZyu4N2Fr7HW2Gy5h3P3ocU93ydKpQlEwnTWJIQCPma2ol2KclTlhtcTWq56vOhhsbeDH6BRk3byHKeQoaHa4RMfcqX16UiIUpqbBnRB/f4MHoDDMm1/hKuLaaFO+QgggawtctYplDUwwvzZQqBxISQSpIVBF9qmTpS7T1Zi4PvhBL4+CdlmjM+Ye+g65RrnMScU9Twb5kqRA84QKw+v17+gzJTib9APxzmPJgePxsJzb7bAiLDMN0VnbePXpPi7tJp1AUM1d5yuRixQYzDkbeiZVxnHpkKsceH2Nnr51Shv54++lY7zUSico4RRkAKgPAZN3/v2xSBoAKerCQVV3GnD+PVcD7WEFeVjs1tj7rQbPlsUskCqqPvUw0gQmWhqdP0R7SEaMyTfCxip9lIrttRfoUdGLebT+5YURMESjlhweel65K3h7npR9qwTX6q1x6fonKcxsR6R5FpsP+MiVfHKLdxYFqTZ6wd7DXj78Wn14DTozi7pbuqe5tQSe9/oUzquU38+TtQxZ5vSXM/CG9bL7xPCMPKrc6nJML1oepkKdCvDaIElZTj74c7XKPWk2zytmq0smgOkv1U/5FCtu3lzBInEKGMjEqCzeHXqWEdtzA4V+jv5LdJTvH+h+TwJrFvyus8efeiV2UKnuQ7B5hvHmZOH1jvKc3MZGA5OvunkB4h3b0a2DI0JpD41yuNU2L8AUBXNpXAYNpfaFwYfklMBXka6vWdL1ammPWa3luEzt73snHiAYLd9Hun4/ol0uc3iwVTEq5CvE2JzBnjh3DdkV5gj7dZmPuCoSPj5/tpOfGnlTIXYGGlvf5mC03hienJNkOUcp9krsyQUvaMSp8LbeGxMzS1lpSC8tqlvSpaCpVGLbYncLDvywHDigDwPicnXpd10n+OP8VG5QBoIIfY+HhxvS/ugVHxz1ys/g3CX/2BI3FBTlX+SBV2jVSUJsCy8Q4oMBBuH2borNdKJEvD/vGOsW7UdVOj6kVtmIzy0qmkxNDJEr54YEXpjYUKTCX08POxcL78gvcT+c5przamR21wJvxQviUM/YhotwSbtvJAyJiMlBjck7qBx5in08KG+7j+Kx27IDR4z+gNqguhXIUZohpFBUH1CLvwp+YfyKOq7GqGAesl9KoSPz33+YbW+jkPplA8wPoV8uVMpaIf+t9NWyYVPqfp+/G6Od6BFhuo0b+uLm8H4c8psjcIoSNC6PTuk40K9qMEesfsztjIAN1b5Jlya14S3cKuU/AST15Qq9PXjwoPZS6NbPg2tw11taIqAgyT8kMM58SEpQXzSbV5CGwrl0Vukyii0aOxMnnFZOt1/DZ/jMZMwiS8Z9Sa3YF+nk9oPPB9xLBRroR0bA7cyazrrci4NR7tpXNkWDGV0DAmFcxp3irbUTVrEP9zSOTfFSB27lTtT1FJ1aiSgZnwsaH/WB4EdlFwUV+Z+gdikRll9hKFkz/wP6T2b5zAsS6njIDqMwAJvkm/G2DMgBU0IPlbIZR+ekBVuRqDAIz7JvcHjeK0qpuvBn1hRyaMUuLCqqOf5mAf7e2psqFG0RrvOTCZM8410Z9jUJlkhqba1+lQ9sKSL88ohFcKT88ELxsJzUudGSx9W6aF28awzNLTq3GbfFQzucZRpap8QMqt7c6yQHdjoROlDG8vk8GDg8LZfb0VG4ARG5FFMkcge0mUIHGldvGhvzWZBAMD9/GAgVtdPEZ1dkwzI7OZTrF+4nPP+7FEM/VhFjMQbNFbYkKSym/eUBMhx47xvK2G7G6YcCWgR4YFjOM000H7h1g4I6BUr/WrOOzOPjgIDs2ZWFq1TB2ZM7O13W+gmwi+bJ8OSxfzuhqhziRcToFa1xgbZfYfWcCBDq/W35UXCKICM1IBs3s0nADZeIfGEuSUYsXs3vEGlrbHopzEKXIlDzYLdWi781b0lxUuhHRA9itGyuzmLPIM5rzLbNy3uI8Bjpx07sVcy/G4jaL0azoTKZ+plRxT97Ai2dmazp0y0RRA0/ODTxHaV05C3/owSF6b+ottXJk+NajOMn6NQ8fxg/moAwAlQFgSp83ZQCooAfrTZjEpw9nOOt1WIZ6EROD799zolYRGreJJnz62xRhP8dphgDrjYigea5SEhvIg2lxTxi/CA1Gb1Ye7pTwo/goE3kAJCVA1Ar6JD0tC38eQtPxWvRtN4eB7YfFMN1+vTNXNtqz2ek2GUoUj/dY45xe4/JVh5CxIWhm1kQA8Bou6olbwccS7Fpqi6hU6enJ0Biif8jX5zMHLuvKEB+VK0uXk9qZhrXA3bILQ+sMiNeECbtm4bz8JFH9zMk4YhjcvJna5qZ/faJvzsWFjXZn6XO0JsvMR9O1bNyZtFWXV7Ho3CKO9DvClRdXqLW0Fq+2GmDcXQW+duHzQRsEBnmyRcAQmZjgNuwhq28sI0f9lRwwjV0LvPj8Ig2WNibb/Lc8DbgrB35iAlg1BeXnX40OCOBZE2P0Hd9wwfJcjABJZMCzTcrCtPkNGBLsl76+cgRTUuHC+NWdKIFBf7HSx6u9V5xZdHFOdWd1Lg66SKReDzRcJ1NsRLtkfbRTtWcxoNwJmvcKxKGBAx1Ld5T0TAmYwtXgq3KQL2hEZ85kaM3TEv7fjNjoO9IeZQCoDACTdRP+skkZACrowQ5T53H2jR9PLn5E4uWZNw+GDGFtYACmJSFibuI4bApe6uey9esluALTnmPY+cqD1zOOxani2J0r1POqR3jWCWQ5dzx1oGiSbOzfv6Fez9y00K+DvXNMuAer8S14dvUSm7Y+T/AQK1ZA/1u5OGW1X6Ln8rrgxdB/VrGx3QEx/JkmIrB8RRZQDHUKBivHa92Q8GYEYi4QFSVxGlDUAAAgAElEQVSGU3ph168iU43GxGvDQN8JLPd9SUSbmrBqFfE2FqXJKdKJUlFPb9GCvate0XlLC2abd2FA1biDapH1O/HkBBu6bZBaAfTd9Zmz+i1m7aFT1C7Cb9cROO7JF/GSWbgw63w+4bDOD9VWY7liGXuwyy/Qj37rh5Bz1S2uTNkqMwgJTMPUkm/QNnrOhfHt5U3DIg1/aP7w+QOa0zRxdRvE6JB0hikp/PT8OZeH/kODBlBmVh2sa1rTo1zs1pnXYa8lEOhn1u+JyFUWze2r0WpTL1keHlNsA2MyTMdqenGpp9Cuvp2kp+XKlhiVMJL7PJ2d4fp1ekStkhC9BJtlXKIMAJUBYLJuQmUAmHS3DXBfzYaHC3g7aBkSM7cosT5+zPAxI1n20J8QD7+kK01sR1CQxEph776NmY+GEz79Tpw7vAMO0m+TOVGPKpJBIM/a2iam+T/59ypdGtBY9T6z1sTkdO5jkpsH76pzeHvCKRuRlDH0rYW35XDph8LWbwxu899zddrCOLk6U8PJgrBDBIGiJVRkAUucWilPKUuUD7KodRxC725Z8eo5Pd5Ldlo6GL8dmnyoklWmt0tRdJIaJ/sLdbx6Bbq6nPALpemK/ky2qM7oOqPjNNTWz1bCa5tvJFNWjNxpjXeAB6rauvR49hyiMzJnTgrOKCJ7DQ1OL7tKu1nviO7ZRhpg+l1WX1nNxJ0LyLfnKIcMnSXAcFavTsGFf9saHU2Img41JuRlShfHGBnRO6/vUM7dALu5rkx8l/SeuNQzMhmaxBT81q08XrxbIv5pt1qwgTRmWK2Y1QGhWUzQixfs0x3fU6B0NrJePU2GsskrsVvXPsP0a0bM2GbFvXf38O7gjWjhyTUjF4f6HJKhfkR2slAhmh6dJD374j+VAWDcPlAOgSTj3v9lizIDqKD/7L33MPPKSMJnXkdqzBC8oa1b027Vcs4/vs4T9/i5OhW8RNzLChRgjbUTvUNGEOX8Ls41UzdvYaL/ZCI2PANfX6RXWqXE8kCxHiNp+HkOXrPv/eyRvHaNdlMrEPjFmWu+YxP02oMHoD/KBIchJZjY2IHW3h3Z7VmfsAMj46RqSo2P4OtXmdWvYEEZuxYBSCiIQUXtV7QhAFod7anX6jk7Bv4T7yUbzevJ9QOVCNZ7IE9AppQnNjUO97fpEDX37Nm56XOaiqvnYDM4N1OaxD3tKcCXC2UrhvZVB4mW7/2No7Rd1AALi384MMtMwtm2k5M7yZdSpXgwyoOyk0rxyUKfSPvIWEMYc0/OZcmBQ5S6sJkNqj1lgG9BaZeKcj1nXcwHhtOrc3+G1BjyQ/ORh0cwnteMDqtX4x7UORWv+AdUiQmrceMIPX5ZgvQ0XmdGMZ0CTGoce3p6X+A+hu4eyrwilzFsm0ViaJJ6M5Ihlp1esHCzHr7nvHE7P59T5qcQZXwxSf52zFtUMqrIQ4YWFlR07S0lA9vEQzGuzAAqM4DJuAVjbFEGgAp6cNG2Mww53oYv02K+hdecOIywUBWuzJyloKYkLuvShTMFSlIjpwtf7L/EwrAT2kZ4L8f75GLe/HNaxqfTSCdwDEl0RUqXl+4zj3wazhzQNIXp37Jl/fpRUWsXau/cObMsYSiXyEjIbOhEO7ObbDFZRYEZxfjo68nbc984g1NqoKL7S5SQYX5atZJ25O/qStF6Zzk6zDdeDZVmtSTkRGfuR2wHQ0MQfKhKie2BMmV4OtqNguv8GWwdLgM8xyGiZKf9siOrR1qwZAmY5d0l1+quXRNIMglmbhR2e8uWhDTugJa9KYzPykubl+hoxBy1neA/gZ2HgqnxYjGex8uDwA4ScDapKP765sxpfpZK3dsxufHkH5rXX1uHq3tP9I9eZO218ql4xT+g6sIFCfIn+vUbqV2y3xobsmT9FOfnvfbqWtxPuWP1bhPGo/MicbOpqSXLyKFDonHz1ODmEV/qHDTm3Zh3km6/e37sMt4l6xTB5ZYt5OtUS5oAjo9OUBkAKgPAZN2Ev2xSBoAKenDn8UDa7DHg66SIGJycxcf2oJBqFfyd0qjs6upK8MEj5Km5nVc2r9HWyBXLYtP5czl9YRU3z38BMUGmlDg9UG/gep7lnkjgnIdw9apM3dWwITqjdKjxxptd8xsn6jndujvR6DCKi0NOSGWbKvtfce6IdqL7UnWBqAnlzy//2AMle3miXmkrl2y//YDEcTF9lxpkvWTLlTsucoZIEK4qJbYHWrbkfbNO5Nj2kl7WN1nVJe5GvsqeldG66MihRR3o2RNW15kHe/fC9u1Si+bMmT/i8+R7efBgvmTJhursGWR1zs7pAacooxuz9Dhw+0DOHNaljcpEnNyyyn0Cgt8sFWVdzZnsL7yEDCYN8Wz7E4nAY78z+5dO4HPQR/YEpLOXzm+9jYSFoVtIne7zXHirepVVnVbF8tz80/PZfXc3LY7MYMCSmmSJTP4E/cSJMGBuWfKscCHXld7SEJH9QXvqF6qPTV0beTpfU5Pol6/InE9btAJSPJ65NGUAqAwAU/qYKwNABT14LfAd5Vbm5I1NCDk1hNtk0bVpTPPcfVll00dBTUlcFhBAVPfuqAx4xaUBt6hQUD+WgrYzJ/Pxki/+2RvCgqQj1CfRonS7vOOIw/hr9iHkZWsQJSDBuWpri9rHKZh8PsHSaYmT+dZsEszphnlY3Wk1QzaPx/D6PdYmnRUqZT4UKaeVK+HQIUlPZdPVfDBYwN1xR+PVm9upFCXvzOPoPhOp90nqY1VKbA8MHEiEVm4yH8pLC6s97OmzPU4v5ZuVD619G6lfpDZ79sDDziPliZy5cyWSif37fwxqJ9/LIoo8eRKNXRvQnqzPii6xp1Q7+nbknn8jRuQwpO+8ajJmUMaYWH3JN0De+U/7HTz/YM55i9ps7v4TiWD8clOe7dhE8KdQ6XFKVyLK/YIr+do1SrYuTmsHT25l2MJu492xjuF02Im7b+9SfvkAzA4akzPkYbKPKhDEqk/tSC3bBrTU3Uu9QvVwPe6Kv6k/VfNVBZGZbNKEl7fekDtPBmmgO76CjjIAVAaAyb4Rv21UBoAKejD041eyz1DlfN9AKhf9ibGnYVMG61JuTDNPozHQjx+JzpEDlZFabOu5F6PKVWNZXH/KKIqeX4NPexe5YUwpcXrAyvEmnlQh0v49GcSEdfbshLdoisZUDRzUg5lkq5uo50RTtn+JygRnuELpUEuMMnr8+XY6kb0UdSFR7s+YkQbmO7hbaDxPHS7Fa3+OSQWp92QVO5c2kkEFC8RPG5eoE/7NC6ZMIfrWbTJebkENS09ODZJBv38VwQKi5qSG7trbzJ+ij6DsizTqgIphYz4PGibFFQKJSbRqpkhE/c/ZmQIvzpFjdC0cDUfSrWy3GCrFcMKbvYNZoKNCo1MzZAzAVJZZwx6hd7AIC6xrcsz8xA/tZjPrk+3EE16o3v/zL0GpccaiRWHZMmrYNqK+xXqORs+UevJ+lxF7Rkj/S8+pMf0eOJI7KDYlnqLmiNmrjOPHYtz6HSss62K6xZRyuctxedBlubIkvpdmzOC85xmpU+P16/g1KwNAZQCo6H0X3zplAKigB8ULY8axumzqtIeONX8GYZnGaTO/5n4GtZdx2dJEKldGs8ELZrXzYUDT2P1mlez70eb4CqbMvypD1CglTg+4zHnDuBBtPth9IJtaNmnNo5BHFJ5dhH8KRmJuljiQt6ieHvvozUkdCyqfO0mfFpWkIYA/KqIZMVs2uYxdogRGVoc5rtuXtxPvx2uG+sRcmDxdw+IlrSRsSVRU/qjJ6eZiPj4S8q7629EU6jeOW8NjQ6p8hz/JOOMtd65oScyBT7QroOHmzKOKbSWAgFRx8aVL0kBAhcIhqJu1x7ROC6xqWMVwZal5pYjaNo+dOY9QSv2RBB6d2uI6I5rSS7QYPkCTuzY/J+iNHIpR7lp+XucMkPog052IYYtBg2jhY0y5tv5si7aQmDh+F9PNppTULonKwAL0ybSCvNfi4WZTwAHbtsE5Ky8mlVhJpN9enI8406ZkG6rl+0Y/KaY+rl1jW4/VEqKPuAXiE2UAqAwAFbjlElyiDACT4EGV4QbMaubOsDbNpV2RUZGoTVHjQOsgmlTPlwRNSVxqaUnR6C30N/TAvnOXWJvLj2yK8ZnjjD38MdXLP0m09K9e7rPiK33vZubOsJsUyyX3SZ19epba81qzoWawQr3zixeDwAvesyeaIkUy4O0NjVKRAVBhB1apIk0x0qULvUZdYHM2Q8InvYp3u8rELNg/XoHjLmt5ilEpcXtAlNX790dHywfV7sY8GxO73Bf0PogCswvApC+Eh2WiaZNoDl3QRPXMCU6HlaNdOwliLuUisH+yZqVLzce86upIw8r5Y02p5pqei6wb/Dmn7kTudrVlGshUFtFVoju3DmbGF3jvEP5De1WbHDR51IPIvJ4pg7xJZXsVVifoMitXptu5MRSodhFvmkpsJ79Lm9VtaF2iNaFtP2FS/AR5j65X+BK/LxQY7h49jrEhYzcQMF+/i7CpYkUW5LBj1y65UyU+UQaAygAw2Tfit43KADAJHsw6tB6Dqw/G1bSXtCvwZRDFFxTgycAI8udNJeT9uOxZvpzah0ZQreEMPPrFBqYtN9QA4zuZsNtzLQmn+e8t3b0b2h3OT4DVBmoXrC05YPed3bSbZ8PBrleppwC2q+jzF5SxZ87IVM3BwRJ03J8XMQgiyrhOTlhNCGSRSmmiJkbEaYdEFeikwpJ7izG75pkmZcI/74A0uuK9e1IWvWjF07xs35DQCSGxLnTj5Q2qelYni1uohMYzovdLZq/KLfXfbd2fVcLovngxlezT18cx72KOt/OnWNk3LGqz6Ifi7y+gOj5PePSlCeqec0kLRHKRFA2bYo2lsYfEfayuqi7ZkN8mE+2DFpJLf+D3eaRUOvQfUiOC5YgI+oe6k6PwI+ZShC8OX2JB7dRZKoNEP6t1FePmL8m9KW5KTkWsFvdF10YvuROSWx74EJn8X0Uwubi6MvqgkYT9OV+GmYxTlAGgMgBU5J5LaI0yAEyCB3WGdKBlqSasHGot7dp5/jxtfJvzZeorwSGfdnLjBt0cypGpnjNrhsXGqjOw0qHP20bYrd6Qdjb8CzSfOgX1VlZmg9VE2hvIUBneF73p7+7NNVt/harnon1OXx/27YPu3eVB4v+LCJRhf3/Yto0JLsE4R+Th0/hPZFaJTcj6/vN7iWh+x/VpGH06Lg+BKCVuDwiID3V16lc/ybHWtYhyiIox9S82nXpyitY+HdH1eSox6q0edopWnu3J+em5mAGRPpZUc7GREavetMSnxReylTnKxm4bf9j97MMz8rnlI9est7z6qE0GAVQpACNTWUQr4inbtczs3ZN7wx9QWKswX589RW1RfjrevULV8uUYmzCEZipblErqBKD6kSMMzb+JTOqhzM2anTe2b8ipnjPGBUSZ3aPlPAJLbqanRQ60Frok2wBB412ieDSRWjpkEG+Ton/gu3z6JGV8efAAo0EFJZSnIT9hF2NdUxkAKgPAZN+I3zYqA8AkeLDIMDNK6hVgn50MFjpn5y5G77Phy9w0zrx9/YpZB3VeVzBmyxSvWBbrD1NjkJojtq6pCwCbBNeki6V370LJyS1ZaN0Ji2oDJZudD7kyYf5Zghf4KpTJE72gIvFWoYI8RLg5bnrmtPfHwYMyRcCDB7i5f2LUW3WCRwejmzV2OvJ56HPyzsrL+XM2VM73HgQLglLi90C+fPTNvwzvNi1j9It+3yDo1/quG0rBrTfFkC6Xxq4haq4HVcKPM3y4vCpFLCC/WjZ6NMf3hzHJsA7hZRYT0O/nUIpgqGiwrAFF7Q5yLnsjMoa8SxMOcPGyM3XwE250LMh2s/3UMGjKy82ryH25N60vfKRVM40EA5W/9lYTnLuzZmHX5BTvQqJZmjczN6xu/GgP+W63rqsu69rt4YWBKx2cqpJlQjzcbAocVOLu1obIBk1QMekF5uY/dwkIryZN4O1b9Itl4J9/JKjCeEUZACoDQAVuuQSXKAPAJHiw4ugxqGiEcm6ynJcf7r2MJadXEDrfPwlakrfUvENRnucvyI75v00lvnhBnpl6jC25jxEDDJOn/D+y6+1byGVmiv3gkkxuNkE69aCNNngu/UTkNg+F5yJMTWUmNVGeGTz4/+Q80ccnsAA/fsRrTRbMH6rF6G381arAN4GUmFuaB0d6UaiRPjg4/J+MTieXrVmTKZHDsG9vzNORT8mbPeY478brGxm9ZTolD5+WoP8+jHVm2/TrtP+wCmNj+TdctAmkiixdykPnlfQ3HMvTCsOlAOW7HLh3gIHbB1FnuAPLaixC5VTcXOEpteP4cRCtaVqdszC18ijamDpzxbYP9dTXUO1oBCYm0LdvSq/yf9h/9CgCxNF50GOJa3tfBT2299xO9fzVfxgjJr5VnVTxa3uXr1UtaLq4OxnMzZJt7JcvSMDT7y1Gkz1jWEzYLjHA4+XFy40BEha0eMRz51YGgAk5W0kFl+xbUdqoDACT4L8m9q48ijzH3Wky8FuXOdM4eucSz+evSYKW5C3t36MpQVnvsXfpb5Oevr5kvtqTxTVv0qdNyeQp/4/sErRqmVqPpm//CJZ1c5dO3c6rL36+xQjfa6+wFwIDkd7OxZSeqNj8X0SkIgWl27FjrL9Znl4XtTkz9ACV9CrFMufKiytUcq9P8J4aaFt2i5l1+L8Y/5dftGtXfG7VxLyzA1esLlBKp1QMg70ueDFt52oqXd6PSCJFm5kze21eau93khI6gmWvbdtUOuOJE3xs0ZE2bXZxpVJzXtn+HPQRDBUzj7rT3bIuIweGkslzYSpdNKYaMYnauDFUsSxIr4/69J99iH3NijK0aQRaW59KBChdYs+mpYktqapUqseWwN31M4eOZOJm0zK4tXCjZfGfkF7vPr0j5/Sc+DUJIXfTxlTwnQAdO6bIDNH2d9NhNQU2e8CJn7A6WFpKZYWVVWdLGeTEEH2UGUBlBjBFN6IyAEya+7pP8+LQ69W8cN0vbaw3ZQQvX0Zza25KWN8Vs6GP1QiCQheyf3l4jDLPp0HmqOddyl7D5zSvk0cxZf/hVVkNXanb7Sz7Bsi0aTXdW3N/T3uCd1mkP6+I/qGxY9mdtQvtDxZhv5UPDQrH5oE++eQk9dw7E7IhJ1nnzZA4rJWSgAdGjWLfzkg691yHv3nMjJDYNefkHDz3HKHuk40y/EmTJswKNuFrn35SL5zoExXJ2VSRd+8gZ05aGF7Br24FIuwjZL5YwOOUB1uv7GfMwE8Yzu+AFECkgYgXntKloeu8FpRbdxg7220sc2jLSovavJh1SGI9aZlGMKhpcJyfKkXPnbo6q2c9Y/kePcJ6yEN+vcrLQ35C7r29R0mPkmytGknFjvoU8FsusQelRMS9scPtNpX7VpTKvVIviRDB4+zkRK/1HSX2j8k/WffivJwyAFQGgCm5D8VeZQYwCR4ctmAbXvcd+OAqj/gZjO+FdlR5jk1LKet74kaYTl3J7Xt9ODn0vAQT8F1eVNBHr/N9rvYIp2ypb18kiav7z67Qa+mNXovlXBxxUPJBsenVyHR8HLe3pkNqNFFvLFuWI/XH0XRDBTZbuWBU0ijWZytKhS08BvHJ6zUqh/2hUuws4X/2hojr4HPncnH2QZr2vc4604U01Y/ZiDX58GTW7r1Pq8/LRAsZAvhvSX1vHP0bIrLMAgRaYPqmloTnzMvg/GtY3rUxz0c9J082+UXP3t+eKw+fsch8F3oB66Fu3dS6ZAw9L17I9LRDdwwn0/YtzPZ8iJNDQ+5WLszh4d4SKY0iE/RpYlxKlerosHfkXibvrIr2kHYY6hsytOZPnmwBE9V6VWs8CgVjZJyDbBeOQvmU8R6LQV+3WdG0HFAQCUdKNPoJxGddXaKeviB3WV127oyfA/j7kZUBoDIATOntrwwAk+DBGWuOM+FidyKmy2CoemOaUi97bzZM6JcELclbOnzebrbe6c79vOOkrI8kN25wq2lFDMwy8mLopwT7RZJ31X/fLoO2u/lYZzSP7eTBnZxOBTG4uoYTvgpgwPxt7pg0Ce7d48Jwb2p41sXHagg9y/eMZeX2W9vp5D6eyAVXZIC6PMpMcYIf5ebNPLZwotqgDHj2sqeDQYcYy0fvG82uPZH00JqLw9gIKYt0e+99ShkWknrhli1L3RvldeWmzHnek7nWIzludlxijhAyaMcgwp5kwcdyLohMoWgJSAMRdGSibDlhrwuBby+wWncQFqFr0cmqi2d3Z/z8UoH2Lg3sVkhlxYqcbj+FAVvbUnlSX/Rz6uPQ8GeP7N67exm+dzijM13GzFINnjxJcXq3dm2kYaHuu/vKkbXoGVi9GqZP58SiS1L7gAi6E0OWUAaAygBQoXs8gUXKADAJHlzjd4teAZWIdpLBULOOKY1FoTm4WbVIgpbkLZ3ifRzXa0aE+Bf72RwyeTLHrvhTr8gNPk15QebYCCDJu9i/eFf9bue5UK45oQ6vkBq8J2em3cNbbPaKzbH817tBkBDPmcNtn5OUntqcxdbdMasSu0Fd9Ir1m+tK2LJLZBAUFanMFfvX+ympBp47x8f6LSg5ojwu3fphWtE0hoaB2wcSsDsPlqWcGNbylpyRDwvj4OGMAlcYLa2kXjDh9U97jGTfzgicnHezpO0SGhdtLG3ovK4zBW7nwXbyLvJHPEjdi/6iTWQ1BXHMDD8v9gStZr/pfoxWG9GmRBtG1LfkyhWplS59SqtW3C7dnlZbB9F+wUiio6OZ3XL2j7OsubKGeWfmYRK0hUEOuWX+cHUZBzG5IsrlnTrBQJ1NMnC3gCcQUV+tWkz6ai9BC61RoK1cGQAqA8Dk3oPf9ykDwCR48OTl19TerMPHcR/RUNUg03gtPKoEMLhzhSRoSd5Sz83XGHyuFlFzoiEgQP7RKVEC38G96PFoPdHut5Kn+D+2q3O/J2wqUpBI+0jehL8hz8w8DA0Jw90tZV/q/xc3fiOOf3r1DflHdWL2sCYMr/2zfPXdpiXnvBg9dyGv9j9H5elPKq//i83p4aIC3DF3boqMNmJ015YMqRETjK3Hhh6c3V6V8Y1s6Ke7Q87IC1q+NJJHzit47rgQ60VfGVn7Jx+wgIBpfrYwDdeEUP/NtjS6uqxWZABdt+5gwW07rlheoeKiikxsMIVOZdumDu9xmlqfgHJzc55G56XyDieGrHPi7tu7eHfw/rFh/un57AncQ4vjMxm4sBJqX34yoSTXZIEfKtp3bYZHyqCiYsJmwwYIDKRF37wSI5Ei6ALKAFAZACb3HlQGgMnwXPDLKPLMV+XmoAcU1NYh69SsHGgZTJOaaU8Fse3QE9ofLkjkaytUrt2ABg3Ax4fpbs5M2OtG5ILTyTjRf2+L9YgIPLQy82zUM16EvqDGgkY4ZH6L4PhNdxIaCtmz8yEwGE2b4Thalmdis9iIvLOOeuA234cHtzOiei422X26O3daGxwdTaSaBhUGGWLSrRbj6o+LcUXRE3ZtU3tmG1vQ6eFs+YUsDQEhn+y9Rs6WNeixsjEtS7T6wQdcen5pbPbkR+1aHXrfS2RiIIU+E5VKt1WXsThdl/dj36PjqsPmDvtpWKoy799Lt2H6FAcH3l0LosDepUz3l4M9AQXzXUS/pxgEqbrOApNtXdAKjYO+LYknHzhQhneZMgX53hFj1MOGEd2zl5Q9FhCfgukxMVEGgMoAMLF7JLG/KzOAiXnol79HRYGKnS7be+5GXy8nZReW5ungT+TVy5gELclbeuZyKDU2Z+e1xT1ydTKWer/YtInRD26wIGAtYYv8kqf4P7ZLfOk6ReTk9OBDPP3wlG5LRuNa9JrghE+fki8fUes2ojLDi+HmeZndLnYg4LBvGr6L13Ptc0FUtm9Jn+f8w1a/zVOK5m1K0rRnWaY1mxbj6nW96nJvzRBWju1J042D5fTYjBlpZuHLZ1/Ili87g7xaU6RIuR98wDozdNiwXIOjWouYcDxtJ7vFVKrHojBaH8vK7SG3KTmvJJeMX1KxhA4C2y6xfrU0c05KFXt6Er5mMxqH97Dy0hoWnJ3Hsf4/8RSH7xkuUcMVm92YzufHoxd8OaVXlOI9MYDs4RFTlcD9y5dP8SqzMgBUBoApvRmVAWASPagypBKurSeTXzsn3X2N+eL66I98+T1+HE2hJarcGXqH4jpFf1jd7x83tpw9zltPJQ2cIh+lILa3fVSKzQPm8fj9Y0Z4rWZJg/107arI7r9wjYCkMDMjk+95+vbJxNJuYiw1pozY5sCxJVs5mb8uGRcu+AsP8feZFFTGEJMKKpQ20We+UUxC1vILy/PYazp+C1pTfZwhdOsGA2JzdKfWqUSwcFG9Fr4zdPlcpiALjBbw5esX1JzUeOgWjUvLVyzw1U6ty8WpRwyOOznB4LsFGVpjKG4n3DjU5jlVq0pY5OlXtm/ny9jxqF6/zOYrexl3eATXra7/OI/JZhMMtA3Qsc1Hi1crKXL3QIrPKl5Cb9+WCjgxRCQDe/eWYYQUEWUAqAwAFblPElqjDACT6EHNQUYY1zAiX05tnPxmE7HgZBI1JG+54A3XdM5FgJk/9Uv8hPHoMMeRUzeDeLZIAJIpJTEP+PrCgOMNWGhmwf1395m+5DZb+/pI7A3pUszMpKnEzGe/0KHHW3xNY4MBm60bxZPlu9hbxxgmyAwoSknYA4GNzLDNfh+N/vlZ0XFFjMWF5xTm2bxVXN1Vj5KGhWUoj0aN0sylAvN7bqaRhA4+yaWG+VnfdT3feYCfeBRnavc7EitNWoqAebGyguVRLQh6HySxo7iU9sPISJ5YTbdy/jzRhoZkfPOaXZdO029fO56Pfv7jON+HXbKYfqBe1vOUOCuTAKREROZv//7YfNFLl8rDwAcUjDGVAaAyAEzJfSj2KgPAJHqw4GALyulro6epy+bzAbxb9GfIYBzJ58IAACAASURBVCUWi5FF8e21nG41fgKRNpo2jCePVbg7P3bmJ4lH+08sF1+8Hdd0YZJ5He6+ucuSBdm5MGO6gNNLn+LighjDzPauDA073WGn+c8G9u8H6r7CEhWf3azq6QD9+6fPc/5hq2/0mMSc4N08H5iHrT22xri6YIZ4N/swT0+UJG8xDRkaRNTu0lCMs26hSd0hrOhVnEN9D3H+2Xmae9Zj15rObOywQiCIpKm0aIGUJX9XZiY2fjaMqzcOw0zOIvksZhfSr3wDOdRUDWfzqSe02lGGzxM+k+EbkGPtpbUZXnM40a3OUsngEwZ+v9Vtk3Fykfnz8oJDh2JuFrNEAs1HUapuZQCoDACTcfvF2KIMAJPowSojJvNF8y5aGtkJuq9B4CLXJGpI/vJMVpWkHi/rFu1+KKkyuS9fX+tzca6S31URzwq+9bpThmJpocrFZ1c46NGN4D0DBAZr+pT166X+s1y5e1HB6BiHBsduBTBaYkqJlXuYM9YnnVI2/PmP5srIZaw76spRqzwc7CODhgsRMCEqTip8nR1IyK6PaBrWBJGeT03k5ziOWzH/K1yy6mIzpBTXrG+y684ubD27YH1yES9amEq0hGkpnTtD/frQtX8Q5tvNWWi0kGvHijBuHAiquHQr4s06c2Yqqd/C/YAWDXdp88HuA9nUsklHEiwgouQeVn0lJZrrU3pNyr9nt26FiRNBDPH/KoJOr1YtGRlGEVEGgMoAUJH7JKE1ygAwiR7s6LiaY5EeqGfKRrHwbvjPTLven99NyzKoITbNzHHqYvLjTyXsO5L3UyMCXFOLfT6JDklnyx8+hKJdF9Js6BauPr/O8wWribxb/4/0caaJqy5elMqPeetNo6DhNk4P2xXrMo0WdKb5yl2MW3gyBotMmtjzL1F6ye0AJ7168491fs4OPPvjVB8jPpLNJRtMf02EdwCqzhNBfAZpLCJDPS9Hebq3ekiw/XuWHprN2mUjKfDqBRUNc0vAwmkpffrIWH+/dhCIdgp3d4mOOn1LoUJ0CFuF7Y461NurysPhDymYo6B0JjFos89kH++L26NnZoSB++AUn1Vk/kQiXszx/So/AKK7K3YJZQCoDAAVu1PiX6UMAJPowcmLrjLpaS3UonIyINdK3EeljBcyKZfXtGhH79rNWdD3Jy5Z/nFNqJKpD9ud+iRF1X92rdRLWe4o2SxaERoZio7XS14+1Em//pAOpEkZowVkbOTL1dG/1ZWAGrObY77Kj4G7gyW6KaUk7oFLG+7w1LYsw0YU4fbQ2z82fO+9wymCr1PnkOHMaRBZ2DSWmjVhYtnxGBWaSqTDF6bN6sDNuycJfvBSKs2am6etAaL/T0C9CNKK7yJ61tatg7170/baaa69Vi2s74+gk293Op7KyaE+h6ioV1EGindSJdA6kLe63cg22YYSdimfFhPvC6Ln+M2bmCcTkICCRUZRqmFlAKgMAFP6bCgDwCR68NiJSOrtU5N2rav6hq5tciZRQ/KX61qY0KSCAb5WP0HrctlVoa2mA952Memqkn+Vf/dO0VCvlv0DX2w0yZYpJ0V830hMBula9PRoXnk4gQ03Ejj2TKyjVHCpwci15+l7QckCoujnfPVMOOEdNGg7TJfntsE/tt16dYtKiyqTaVoYob0Ggo4OTJ2qqNpkr2vWDExaBdI3tDjB9bcxaYkJGtXrcGzDLoYOhR49kq1aoY1jxsjTvvPm/Vw+dy4cPiyhUaVv6dyZGcfqUmH5SKxuF/vBtvI2/C25ZuSScA9fqVck03IvCpmmfNjnwQMoVgwJPud754D4XsqaFUSLioGBYu5UBoDKAPD3O0XUBi2A0sBXQPy0ibG/4/HcUsoAULFn7ccqCXvXpA9k/sDDGZsoVCiJClKwvLDlEAyKabB39E/MMQ27YljkXcJsa5keSimJeyBvXjCb58XHF3pc3tha4am7xDX/n1bUr08/tdrsa7KToPEyx/GvUmqSAWM2vKb/lZf/JwPT32UFO9eLWtoYDvtImP2nHwc4HXSa1ivakWHWc16WbQSiNtov7bnAO3aUCSMmvtXgwKJwnDtqU8d4DMstbRBzQGIaNy1FQMCIkuWvPMfOznDrVmw4k7S0I010Dx3KivWZybZwJlNfVWds3bF0LtOZwDeBGMw34NO4CMJUNPm4/yR6TVM+LSYGPXLmJAaA9rdEPm/fKk4lqAwAlQHg78+DJXD3W8AnvrVErdAJEO8UT+N4eJQBYDK+UYoWlR/e16+TsTkFW8oMGY9m3lecHO/5Q4vqeB0mFd/HuH4KQMen4Nr/pq3lyyP9aF67JrdvKcK7+Vefv18/HG7D/JYHeW0fmxO2sH1+xm/RZOCVG3/1Mf4m44KC4FLpihiNuizRBqpkVJHM239vP/03WoHHLR59zgPbtoGoz6axmJjImaGNOlWYUGoArne8GVZ7OOPa9UhS2TC5Zrq5wYkTMavddnby1OrC2MhDyb3M/2fftGnsn3WJ4Llr8P7agi6luzCg6gDOBJ2hzZo23O//EA1tdd7ceEEug9wptvE7t7LoRy4otxpy5w6UKycDRCs6T6QMAJUBoCI341ugLxATy0DeqQwAFfHgb2uCg+Hz558PbzJUJGtLzZGuhGY/y7VJvtJ+MZGYcaIaSyrewqyTfrJ0/hc3tWqFxLcpvnRFGUaUstK1ODuzZONRhrc/R6jjz3Ll9zPpjc/JhJ2VGXLRP10f808aL/qzduVtj8m4bbyxfUNOdbnVY9ONTdjtciHnwt2cDNSFkBCpBzOtRXDD5sgBtyt3pm7BujgfcWZf7320qlSV3buRAJnTUhYvltnuxLW+iyg9q6unKQlKWh7pp+4VK7hs/Q9nZwWwT7MHVfJWwbaurTRpLSBvjtXfg2aFwnx6H4lG9kypYpOgfBPAzxW+0cgfOSKDQIugUFFRBoDKADCxe0W8mh4R0+xA7NSAMgBMzH9/1d+b2y3mVsZNPHTeI9n1fSJxR4NXGDVOWyaAv8oRKTTGwgK0tWX8ssqVQeBvpWtZt469E6bQzvgenx1DYx0l53h17Pd1YeSZmIDG6frMaWx8eDgs1BjOaMe53B/+gMJahaUrLr+4nNn+K6i6wBGvz8bw+HEaWyKr/96Dl6XdaJ68f4LvNV+pNy23VnYJhqWk+IZPQxEAxSLTJwKV7yIq36Ia4pByZJQ0tFwB1QcO8KydBZtm3OVakcFoZtaU6P+8L3qz7OIy1ud1I0PL5uT88irV0AKKFJFL54LSXciGDXIgfToJlO7KAPC/EwAuA8SYZzRxn1mM/v3OZSCSywGAIJxxjOcxUGYAFfh++FuWdJvky6FPcwh2OSGZJLhs87vl52z7CKpWUv1bzPzr7RBUTKJ36cYNOfgT+FvpWs6f50bLJpQZ/J6vjlE/QGy/nymLfSYmHh7D2IC0H1ZI1378xXjRlD8y42yWTRjDkSHnKJ+nvPRX91PurDx6kC7zW2BbcgvskV/G0lpED57oS2w5eg29NvUiX/Z8PLQOQlUVRLk6jXGopUq3o2NM7DoxfVynDowYkdanT2P9N28SUa4y7i5hvKtqT/DHYBa3XczM4zM5FXQK94/mvO83jFLRN1PNEPHiOWkStPsG6SqGa/btkzsKFBVlAPjfCQA1gCwJ3BiRwIdf/l4c2AeIWqFdAvukANDKygo1NXmytUWLFtI/Svn7PDBo5h5Wvx7JexeZq/J68A3Kzq3Gg4EfKSwnKJSigAfEm/c//8DVq+DvL2cB07WEhPAqnxa6thA2Lgx1VfUfxxFQFpkmZ2LSicU47PlzmJXp2p/fjO+ptpEjI3ria3WQuoXqSv93SsAU9py+w6g5mnTspgqiOe4PyJw5cvbNY7n80tfRoCPLWm5ClBL/RBVaPCeDBskctt9FtFJ06pSmNMh/wLPIDd05cjBz3BsytlnG8cfH2dBtA2P8xhAaEYrdtTo8GreIOl9+SX+m0DIx0CMyqKamsiIB5P38ufy9lJDs3bsX8Y+QiIgI5sscgDnEKVJoUrrcniFdWp22RouuAvFaKgb2E3vlV2YA0/azSFXt4xedYNajLnyaGiTpPXDrJM0Wd+bNhCBpqkwpinlAwL587735Ez+eilmVslUvc+iSe+QrXtm8QlvjZzuA+AHL7pKdCdcP4OSbXgmPU+ab5O5umuMsz/vUYpb1DloWbympsfWz5cyFcGbPuE6laT3THoDvm/FLlsgDGOK33+eSD/UK1UPto740RCD6WDOlTmtavK46dQrEJPLTX0YJBTOI6E3s2TO5Hv579n1Sy45nnxNoDj7DyisrOWB6gP5b+1MoRyHMtmtxeV4ARp9TD+/m+1S3tbXsgwEDQE8PRKZXUVFmAP87GUBF74k6wHZgkqhWKLBJGQAq4KS/ZcmcVdcZdbMGUU5yn9fKk3swWTmSL3Ovp/kPwN/ig9SwIyoKVFSQymcREamh8f+v41GhOhQ2OyGxGIgfre/y4uV99BboM/bpI1w8v40c/v/NTRcWlMr3gVytNRnRfzHd6sjZ00E7BhF4RZt1k5aS8+BmEPQNf0DWrgUPj5isGzdvysMfAp8vrUVMzIujimTZdxGZ88mToW3btL562usPzlWKzY090HMOZ+LhiVywuECb1W1oVbwV7eYFcXjTG3qHLko1Q0T2T/QBirK6EFEKFoU3AbitqCgDQGUA+Pu9Isb8RFtp2C+9gqJvUGQCf8Fw/7FNGQAq+rT9BevW7gyi59kCP2ApZu31xXbTHKI85Z5ApSjuAUHGLkgx/g0/XuLU16r1oWqrNVwcdhkDnZ9IsvfPHaD4tmbYRkTh4pJRcQcpV0rUZ0UaqNO9qRXmvWZKHum5sSehF0uwdcoUMr57K4/m/gHZuZNYvLtnz8r4fy9epL0BEoViURAvT99hSoR/xHSwKGemdwks3IRjxUwouqw4xpuMeTTiETWX1GRU7VHUG7mL9Wf1GfY69aZdvvdNzp4te65GDbC1TVo/sjIAVAaAKX3ulAFgSj34B/cfOh5KY7/svLZ9TS71XIxdv5g5ezfxacmfaUT/g0dVXiqJHjjVxomW5ZzZb32Mqvl+YoJc3bKY2qcHYZPla/qf1kyiT1K6XLQJFKmdl0YlajNytFz+M1pthG5AUaat3Y/eu9QbCkjMVsG4IbJGv/LHCk5ZMzN5mj2tRWCeCtITkW3UEB3pyCXL7duhevW0vnra679csTd3MxlQ3q875RaW49P4TxRzL4ZXey/KdprK/OBu/K+9MwG3sWr/8C2FMiSVvmRIlKKSkrEiY8jQlySKJkNSKJIIUYYMZQqVJPQZUgmhSImKaBRfM6W+UkkqZYj/9Zy1T07nf7D3eY/3rL3377muc7mc8653Pet+13vOb6+1nufpvznr6u3ZyumXX+5PrG1nuKdPh4suin6sEoASgNHPloyvlAAMSjDE9hs27KPsjKP4ouunlDyuJDdPHsasFWvYPsnlBZQlL4FlHWZwbd62zOiyhItLXPw3iNVje9Hoq5H0OGFnygqDLHoClt+5aKVzOCdPHvoPcyX2Lp58MdXnF6b5R0dT8b/Tor9ZwCvXrgULurAcpKlm4suCByyZ+eE2y3uaJ49bbSwcyYWcLx+8/TacZXWn4txW1ezJ9m9+pfr64eQdlJct3bdw2ujTeOumtyha8Wr6H/0gD33cMMtGOXo0LFvmcitaxLmxtaA0W1WN1iQAJQCjnSsHuk4CMCjBENv/739QZFQhVt26lErFKnDF2F688e42vp8U76n4Q4SYoF0tun8NXb6rwuiuC6hfen8U/7K7W9Jqz0J6Ff+F1APnCYogy4dVsyYUvrAexbauZ8SkzSn3Lz+hPO2m5aZE7lY0Xto1y/s80A0tbZGdudthh3siZhVsLAh0xYrD74aJFDsza8nTbSvYqllY4MlXX4WfEP9wjPa15qPJs3Iplf83l0JDCzGnxRxqPVWLbT23keeEknQq8wqT1p6XZV1bJgIrq2ci0Mq/FSr0z9Jw0XQkASgBGM08Odg1EoBBCYbY3rZf8vU+jedveIKm5WtSY1gHvv74BL54/IEQvVBXPhKYP/Vn7nu9EL3aP8W/K1pJcGfz21alY6FN9Cv7bUqkoSx6Arbilu/CdhRc/xSPzfoDjjiCkqNKMnbcdr6/aC43PhHDfl303WZ4pUXfnnLKPyN+LWXInDmhpSJMSTljqWislGJKTfT8YBVTEiEDwZJbnqHY00Mp88vbnDv+XJqXbc6oVaP46bbNKXveLWp8z6xXg5eBS324lu/PEmjb6q0F85x/vttej7YMnN1HAlACMOCvFZWCCwowzPb2KfyIThWY2LI/7Ws05bwHWrD368p8MOHOMN1QXx4SsHzEA2cdxS1N7uXaZvsPq89qUJxupx/NkAs/xurJyqInYDnu9lYaSu73ezPznndTlM/xgwuyaMwOXu+0jTv6RA7DRX/LTF8ZSVWXUns3Ne4ko/q8me4gioZFi7pUNBYNbDnrTj7ZlcSMpJCN4g7+XrKo35tUHHIlJ+z8NiX6d/vO7fyx5w/erj2Tv04vw5WNdvL8C1kXRGVl4CwH4MaNbhXQznKmPd8ZDSkJQAnAaObJwa7RCmBQgiG3P6pdTfo1uZE+jdtQsl8dim1rxfJRN4bshbrzjYAFCdwzqSBtq11F+46RbLJ79zK5ah7urngBY2u+iVVukEVPoHVr+KPsRP7Y0puFZQaw75ZbyDXgSJ6dWpWNXVZgtXDDstTURZs3u5VAs/SBBIfblzPPdKlo6tZ1VUnKlXMCMBFs4YRN1LvlNHLu3knf1wcwcPlAWpRrwcx/3cb2xq1oV+8rZmbhUWvLRVq9utv2teCPCRP+WWYvGqYSgBKA0cwTCcCglDxqf8xNTWlXuw6jWt3GiX3O56K/+vLc4GYeeShXsoOAJertMqo4Lc88m659X3QubNrEuKtPo3f5Bky9fH7CpLwJi6+tymwr9h++y3E3K987n99nTiPf4HyMmD2AAl3v5easCwqNakgWffvuu1CmjLvcgnqsZrGJsjCsYkXo3dslhLaty9q1waKDE8EWzt1Fg2a5YfNm5v32Dk1mNGF43eHcubkYm+8cSe9abzFlStaN1IJpLIo69flZSp9YBaYEoARg0BmpFcCgBENuf9yNbbi86hlMbdeHfH1Kck2eKTzWJ1JRPGRf1J0/BD74ANoMPI8Whfdyz7gPnGNz5/Lg1I7cX6AGz7aaQZ06/vgbD5507gzf5V/AJyfdwQc9N/LN/Kcp+kZzmry4kRa3l8BWCMM0i75duNAlfza75RZ3/m7Qoeo9ZZGTNWq4ihXXXusCT2z8lh8wEcxK3ZWrV4STXpvNzsoVGbxiMF0qd+G4iVP4aMJyRtd4lokTs26ktqJrW+e27Wtl/sxScwJG24sEoARgtHPlQNdJAAYlGHL7Ijffxvnn5GF+l2Ecde+x9Cy8gvtvc4XqZclLwGq01r2rEdflXMn9c7Y5EPfdR7+tzzLix4osumVSTDnGkpfk/pF37w4b973OmmLXsXF1NdYt/Q/VOh7FGQt2pSRltjOCYVqpUjBpElh0spmd6bQULOZLGGZJpy1xutUEtjOnd94JViEkEezNNyFHzRpUmXgDXH/9/iF168brr+3lmYtHMWpU1o70pJNcHkU7y2mivkeP2O4vASgBGNuM+f9XSwAGJRhy+9Lt+/CvUltY1n0cue7PxbjTNtPpusihoJB9UXf+ELB0HKe370QnxvPQ1C2uzMkVV9Djwm2MW3s2y3uNwbbwZNETsBx767e+x7Litdja5VtWLJxI640jyff4JoYPd3n5wrTy5eGBB+Dyy12v6evJHm5frr7aJX02YfzMMzBsGNjRg0Qw21r/sGo72txZ2EFOtSZNmP1zHdZWv50hGdXSCjB4SzRuXRnH9u3dymosJgEoARjLfMnoWgnAoARDbl/h1uH89a/VLL1jHIWHF2ZupR00aXB0yF6oO98IWILgk67pTfuTH2Fiiyluqebkk+k0sAqTnj+TtUOHcPbZvnnttz/2x3nN518w79QzUsovLvh0Ab1f6c2vD76PlRJMXYkLaxQWNGCBJy1buh5tS79VK7gxpBgwOxNZrBj07w9PPgnTpsGSJWGN/vD2s2EDTC//IPc3WwOzZu3v7OyzGV1kCFurXZ4y7qw0C6Zp0QKGDnUl9WrViu3uEoASgLHNmP9/tQRgUIIht7+02xS+KPAkL98+kTIPn8uqxn+m1JGUJTeBX3+FAo0G0arqVKZvu8RVla9Wjeuf+jdTx5bmk8f6YluIsugJ2Nbcq6t/ZN5ZJ7Ljnh3M2TCHx955jE96vcbzz4NVCgnT6tcnJZI7NfikShW3DRtWdHeXLi4ZtK1+jh3rxJ9xSASzsmzdSz/HnHMHuEgbM8u7lTcvd9VeS6HqZ3H33Vk7UnuOVl7PzgBaVHAsVUDMEwlACcCgM1ICMCjBkNtf1WsxS47swrybJ3HxmBZ80uGbmH9xhOyyuguBwO7dkOuSh2l89fO8cN/70KxZSohh83//xZyHq7B59p1/pw8JwZ2E6OKRR2D+op0svCAP3935HbPXz+blL17mtY5zsTxutoUXpjVv7lKHdOvmerUVXds+DGsr2s4aWtWK8eNJ2Q610mW2CpgIZlWW6hZZx4d5q5DDPk1ZRuaU0ktFaNVsB5VqHE3XLC78YkLaKoLY+V1LAm2VVWIxCUAJwFjmS0bXSgAGJRhy+9vu/4CJuy5hUrNHaTN+BD8MXpXyKVKW3ARssSJnpUep0eF5lj0LLF4Ma9ZQ/8PevDSmCT8u6sjxxyc3o1hHb6W6LEfbipp5+PCWD5mxbgaf/fwZM66eEnPd1lj7zuh6i02wVVw7m2h26qkwdSpcvL/0c1Z0c8B7WLSxbZVan5YO5scfydLI2MPq/CFubsK2SKE/2JEjLzks2WKRIi4x3zXX0Kj85r+DX7LSx/nz3UkNK/H3zjux31kCUAIw9lnzzxYSgEEJhtx+yJgt9Np6Ej0rPsDQp9aye/ocjjwyZCfUnZcEcl84jfI3PM7q9ktcra6CBan+WE3eGHcjv61sY7tZshgIWK1d2+r8pNmJLGq9iKc/fJrdf+1hTKNRfP01WGWMMM3S0tgztDNjZiboly6F87KuRO1BhzN6tKta8dxzkN6XMDkcjr4sH5/lWdxTqgw5Rz8EDRuCLQHPm0ftXQtTIq7TBgdnhQ/ffOPmkJ3htOjuWE0CUAIw1jmT/noJwKAEQ24/c9ZeWn6Ui9pFm7B8flF2zR0dsgfqzlcC+Ss/S4lWQ1jXZfXfLp437kLeH3c3ez68MuYtJl/HGZZfdr5t4EDY1rYUjzd+nGkfTKPw0UUZUv++lNWvsFdU7Qya7U6OG+cI5M7t0rCULh0OEQt8MVH88ssuYtUqgfTqFU7fh7uXvXvdFuzvV7bhmHIlU1Io0aGD+xC1Yug/gm+y0hdjaXWAMzOXJAAlAIPORQnAoARDbm+7ErWeO53chbaQa1Vvts67K2QP1J2vBE6osogCzbvzRfd1f7t4+sPl+HLicPZsCDlnia+QYvDLdtHtvF3uLhW4r+Z9THl/ChUKXcS9dbulnNmyFaMwzaKSP/7YnRvbtcsJQDumZhUlwjALjrVkxZYzz1LR2CJZp05h9BxOH5aY+ZteYzlx9QKXcduUWc+eXPDg1fTtC02bhuNHtL1IAEoARjtXDnSdBGBQgiG3twPDZ917NXvLzuKs959j/bMqAxfyI/C2u1OqLWdf0+v5tucXf/t4yrBT+fmJp9ixQdViYn1wVl/5hhugWN8atDu/HZPenUTjYm25s/b1WCWHI46I9Y7BrrdExObTs8+683eW6jFMIbpggVvxs6ozF13kxJ+loUkUK1AA3p30DqVuvtQddrScN99+S7laJ6Uka7YobJ9MAlACMOh8lAAMSjDk9r/8AgUbDYW6d9Pk4++Y+/RJIXug7nwlUPqSNWy97HK23vPd3y4eN/hEmLaInz+K1A/z1XkP/Vq92q36VHn4CmqUqMGENRPocfZoOjeol1LDNWyzc2JWL/all1wJMasJbCuBFrAahtnug239Wvm3c85xZxFtFTBRzErtLVq4j/OvKuX2ZE3hr1qVEnhj299WCs8nkwCUAAw6HyUAgxIMub1Fex6dbxcX1PuEyiXPTvlkKhMBI3D2pev5olYVdty7/W8gRw/My3Gz1/DtB2cJUowEbKXL/ui3nt6Zo488molrJzKp+ko6NDuHrVtjvFkWXG7iz1YB33gD3nsPateGn37KghtHeQs7b2i5B+0coi2OmT/VqkXZOA4uK14cZsyAaptnuaVfK3fSoEFK+iRbdQ077+OhkEkASgAeao4c6ucSgIci5OHPLf/Y+vUuF5eVZZKJgBG4sO5G3rmoNHv67iZHjhzs3beXnANyUvL5TXzxbnFBipHAp5+6la7+S4aw8uuVzP9kPgtr/shNrY7HIjjDNtuCtUAQSxpsW8EWlWoJjMOy775LKS7Dn3+6BMZWBq5s2bB6P/z9WCLmiRMjFTnsk3ZkadUWA195BawUn08mASgBGHQ+SgAGJZgN7S0lgSVgtULiqXVBs8ENdekZgRoNt7C88kns7LOTXDlzsWP3DvIOykvZ+T/w0dtKFhnr47JUL7YqNOXdafRc2oOtf2zlxap/0qFDDj77LNa7Bb/ekk+3betEn737lg/QVgLDspRk47ncFnCJEmDp8mx1LFHsQNvaFuxjxUFsy90nkwCUAAw6HyUAgxLMhvYjRriVP6v/agfBZSJgBBo2+42FFfLzc8+fKZinID/8/kNKveiKi3bw9puqFx3rLEkNtFj031e5bMallDquFKNKffb3Klys9wt6vSULtkCEH35wCapttcpEYZh27LGuVO5ll8HOnU4QJopdeKELcvn3v/ePKCXBek4nuk30+mQSgBKAQeejBGBQgtnQfs8edwj8jDOyoXN16S2Bq1r8xTPliz4rEAAAHwhJREFUjmRzt82cUuAUNm3bRMlRJbl42V+89mpIkQLe0ondMculnT8/fLL5R854/MSUQJDO+V7lwQfBAkTCNssAYNuQFoBi5dhsS9iqSYRpp53mykzb8RMToolkVlHlllv+Gdmcmm7Htr9P8izeTgJQAjDo+ycBGJSg2ouAJwTatIH/lMrD+s4fcvrxp7P+h/WcP74SNd/4jUWLPHEyjtywVC9WZcfO+43dcA+Xlb6MTcsv4fHH3Rm8sO3bb92Wq23FWh1ZC1J5+ulwvbBVMqtBvGaNO4uYSFa3rhN/Fv+Ratu3g616WvYFSxPjk0kASgAGnY8SgEEJqr0IeEKgfXuYWqQQb3VcRvl/leftb96m9qTLqfXO91hVC1nsBGyL01LCWSoQs0cfdRGh2SGoLfrWRIjVrbVVSPvXVgLDNNsetWTUVirXqlgkktl56kaN3CpgqtkxG1v583G7WwJQAjDo+ycBGJSg2ouAJwS6dIEnChblpZtnU7VYVV7b+BpXPHU99dZ/mZLeQhY7ARNcVvnCyp6ZWRqWV1919XDDttRyZV995XLwpa0LHJYvPXs68Wn5AKdODavXcPpp3hyqV3fVX1LNWJ96KimJv8PKtxjtaCUAJQCjnSsHuk4CMChBtRcBTwjYH+eJuc5gzg3jqX1abV789EVuePouGm5cx+TJnjgZZ27Y6o+dtatY0TluZ9+yY+s1FdtxxzkBalvAZ54JvXuHC9S2v9u1c6VyrTxaIllG9Y3t3OV558GOHf6NVAJQAjDorJQADEpQ7UXAEwL9+sHYPefxZJuBNC7TmNkfzabLrGE03bI69K1CT5AEdsMiPy3lkgUImBljS39iVTmyw2wr2kTYww+DnVnr3DlcLywS+YILYMkSl4g6kezmm90ZSxO3qWZiv2ZNsiXx96HYSgBKAB5qjhzq5xKAhyKkn4tAnBAYPBhG/lKNsdd24eqzr2byu5PpN2caV/6+lIceipNBeOamrbKNGePEltldd7nVoLFjs8fRSpWcD9a/BStYXsCwzc5EGhfftkSDcjAxnS+fW+VNNUt2fcUVKSWBvTMJQAnAoJNSAjAoQbUXAU8I2KrQoG/qMLRVa26ocANjVo1h5PNLuCbHXAYN8sTJOHPDtv8GDIAmTZzjt90GefLAsGHZM5AGDaBZMydK7RygBS3IsoaA5Va1FFv2HqWaRXub0La0W76ZBKAEYNA5KQEYlKDai4AnBCZMgH7/bULfVvW5tdKtDH59MI+/8BFt809LuPNaYSGvWtUFBbRo4Xq0bUKLgDVRmB1m59Ss/Jqt6C5cuP9sYnb4kmh92nlKq61s71GqLV7snr+V3vTNJAAlAIPOSQnAoATVXgQ8IfDkk9Dz7ZZ0b3UBPar3oPfS3syc9xPti0xI2TaUxU7g0ktdzd3UrdbWrV0ePKsYkR1mkd629Tp6NFiEatGi2eFFYvY5cCB8/jnYe5Rqc+c6sb92rX9jlgCUAAw6KyUAgxJUexHwhICleunyyo10alWCfjX70WVhFxbMO4rbzxzO7bd74mScudGwITRtCh06OMctD94ll0DXrtkzkPvvd1HAS5f6mZsue6hkTa+2rW9CL23KpJkzndheuTJr+sjKu0gASgAGnU8SgEEJqr0IeELAVivaPdeZG1rnZWjdodw490aWzytOz8r9U1J3yGInkF7wpZ7BSxWEsd8xWAur/GHb0HYOcevWYPdS638SsHOVJqzTJk2fMgWeesp93zeTAJQADDonJQCDElR7EfCEgJ1XajX5Lq5ps4OxDcfSYnYL1r5Qif71unPddZ44GWdupN/ytZQgN94IVnYvO8xqEFeu7LahE60UW3bwTNvnY4+5Ki92tjLVJk6EF15wuSB9MwlACcCgc1ICMChBtRcBTwhYxGKzhwbS5PrPmNJsCg2nN2TD8014sEVHrrrKEyfjzI30ueFMfFm0aHbxtFW/4493OfgsF58s6wjYSp8lTF+2bP89LSL49ddhzpys6yer7iQBKAEYdC5JAAYlqPYi4AkBWx2q22cUtW96jWevfpZLJl/CxjkdGNehNY0be+JknLlhueGOOcaVPzM75xywfItWNza7zEqW3XQT2Ha0LOsIzJrloqut9F+qWU5AW2mdPj3r+smqO0kASgAGnUsSgEEJqr0IeELAqhZU7fQEVds/zZI2Szh/4vl8P7MfU+5pSp06njgZZ2706OGCLSwQwKx0abBtwUSrghFnj+WwuGtbvVbp5d1399++f3/4+uvsq/xysIFKAEoABn0RJACDElR7EfCEgNUtPbvFM1ToPIxVN6/ijDFn8Mv08cwZXpuLLvLEyThz49574bvvwM6HmVmpsNmzoVq1OBuI3D0kgZdeAkuzY5VOUu3uu+HXX2HcuEM2D/0CCUAJwKCTTgIwKEG1FwFPCFheuBK1FnNmt65suHUDRUYU4c8nn+OlyZWpWNETJ+PMDaugYoJg6lTneKFCLiK0QoU4G4jcPSSB5ctdvscvv9x/qaX7OfJIGD78kM1Dv0ACUAIw6KSTAAxKUO1FwBMCP/wAhc9/k1O6XcXmOzZTYHAB/nr0TVbNK5cSNSqLncDIkfDGG/DMM67t0Ue7LUKrhStLLAIZ1f3t2BFOOAEs/6JvJgEoARh0TkoABiWo9iLgCQHbqipQeh35u1bjl7t/IeeAnOQc8yX/XVWCUqU8cTLO3Bg/HubPd2lA9u6FnDlh40YoUSLOBiJ3D0ng/ffBKr+kza9oVWDs3GefPodsHvoFEoASgEEnnQRgUIJqLwKeENi9G3Kd+BU5up3K9l7byT84Pwz9kc2fHp9ydk0WOwFLCzJtmtv23bED8uYFW2m1VSFZYhH4+GO3tW/POdVatnT1li31j28mASgBGHROSgAGJaj2IuAJgX37IGe+n9l3VyHWd1pP2UfKwoDd/LjlyJTccbLYCVhZMIsAtm3glC32wk4g2FawLLEIbNoEJUvCX3+5estmVgawbl2wdEC+mQSgBGDQOSkBGJSg2ouARwTy5v+LP7ofxdyWc2nzXFu29drKb7+5lStZ7ASsvN5998E770BGAiH2O6qFrwS+/x7+9a9/1liuX98l/baE4L6ZBKAE4MHmZBfgIcCOr/Y9wIUSgL691fJHBAIQsK3Jv+48kV6X9GD86sfYeMen7Nnjzq7JYidg5fUsEtQigdevh0qVSBHUssQj8MsvULAg2L8F7C8jUKMGKXW0r73Wv/FKAEoAHmhWlgFeBH4FXpAA9O/llUcicDgIFC0KubqWo+bplXln83rWd3uLXbsOR0/Jcc+0qUHWrIGGDWHLluQYe7KN8s8/3da+Pd8TT3Sjt9J/lgzcqq/4ZhKAEoAZzckjgDeAQUA34HUJQN9eXfkjAoeHgEUs5utck6Pz7+SoPYV4r8cCtm8/PH0lw12tvF6TJi4ZtNVatqjQtHnikoFBsozRztAecQRYPs1ixdyoy5cHywXZqJF/FCQAJQAzmpUWsG4rgNcBVtZaAtC/d1ceicBhIWC1agu2u4p1fyyh+vFNWH3PFK1YBSBtdWCtioptCy5c6KJBP/oowA3V1GsCefK42r+nn+7cLFMGHnnEz9J/EoDJIwAnA22BfWQ85leBWsB5wPORf7dJAHr9u0bOiUCWE7jwQji+TScWbx1Py+LdeaP/sJTgBVnmCHz6KSlJtK0e8Jw5MHQo2KqgLDEJ2BnA118H+yBlZvken34aqlf3b7wSgMkjAI8B8hxkCu4G/gDWAv0iItAuj2oF8NZbbyVXrlwpt69fv37Kl0wERCD+CFx8MRS9eigzfrqb208bz6L7O2L5zWSZI7B5s9sOtECa6dPhiSfgVfu4LUtIAhYFPG8e2Acps5NOghdfhAsu8GO4ixcvxr7Mdu3axThXpPhYICkPekSy9fjxcLLZC8tN/wXwU5pVQpsYJg7t+5HPNP/wUlHA2fzQ1L0IZCUBy1lW/ooljPihLsPLrGLKoEp88EFW9pBc9/rxRxcQ8Pvv8NRTThxYVRBZYhKwFT8T+rbtb2bRwG++CeXK+TderQAmzwpgNLPPxPDJ6S60CpargCHA9xncRAIwGrK6RgTihIAFLNSvv4/yjVfyzZvVeeihHLz1Vpw476GbJvzy5QMTgk8+SQrL2bM9dFQuZQkBO/Nni2p16rjb2caYpQDysZSiBKAE4KEm/SvACkUBHwqTfi4CiUGgRQuXuuLOO2HKFPf1iv0WkGWKgFWFOPJIsK1g2/79/HMnBGWJScCifh94AC6/3FUESX32PpZSlACUAAz6FmoFMChBtRcBjwi0aeMiF3v3hvHjYf58bVkGfTy2CmRJoB9/nJSUOhYVKktMAmnz/qXWfrbVXx9LKUoASgAGfQslAIMSVHsR8IhAhw6uXu3AgTBypDu/pC3LYA+oUCG3imorgLlzw7Bhwe6n1v4SSFv5Y+tWJ/zsGMAxFobpmUkASgAGnZISgEEJqr0IeESgSxd3bslEyv33wyefuOAFWeYJnHqqY2jb6VZpxWoDyxKTQL16YMcorPbvt9+Cbf36WkpRAlACMOhbKAEYlKDai4BHBHr2dCsWY8e6beCffoIJEzxyMA5dsZxwQ4bAtGlQoQLcdVccDkIuR0XABVHBrbfCF1/AmWdaupWomoZ+kQSgBGDQSScBGJSg2ouARwT69YNvvnHn1bpZIUjgoYc8cjAOXbEkwLfdBv/5D1ianc6d43AQcjkqAmmDqOzcZ5Uq7tynjyYBKAEYdF5KAAYlqPYi4BEBW6lat86tVnXs6M4wWVSjLPMELrsMrrwSZsyAa6+FG27I/L3U0m8CaYOo1q6FBg3wtpSiBKAEYNC3SQIwKEG1FwGPCDz8sCtlZWXL0v4x88jFuHPlqqvcSpCVBOvTB664Iu6GIIejJNC+vav+YUFUK1fCNdfAV19F2TjkyyQAJQCDTjkJwKAE1V4EPCJg5/1Sq1U0bw7VqsEdd3jkYBy6ctNNrhycBYJYJHDNmnE4CLkcFQHb6s+TxwVRLVnizgL6WkpRAlACMKpJfZCLJACDElR7EfCIgCUpnjoVli6FRo2gcWO3FSzLPIGuXSFnzv11gC1ZsCwxCfToAX/+CWPGuA9S994L773n51glACUAg85MCcCgBNVeBDwiMHMmjB7ttq8uvRSuvx7atvXIwTh0pW9fF1gzeTJs3AjFi8fhIORyVARM8H3/PTz6KNi7ZEcqLJemjyYBKAEYdF5KAAYlqPYi4BGBuXNdnrp33nHn1qwknJ1hk2WegCXUXrDAJYP+5RcoYL81ZQlJwAKmbMvXtvvTrqb7OFgJQAnAoPNSAjAoQbUXAY8ILF7s0r9YCotzz4VBg1xdU1nmCVj0rzH94QfYvRty5Mj8vdTSbwIjRsCqVTBrliulaMLfyin6aBKAEoBB56UEYFCCai8CHhF47TWXpsSS2J5+OkycCLVqeeRgHLpiTC3ww1LqWF1YWeISGDcO7EPUCy/4X0pRAlACMOibKAEYlKDai4BHBFavhmbN9pexeuYZqFrVIwfj0JVPP4UzzoCzznIrq7LEJWAJ1G3176WX/C+lKAEoARj0TZQADEpQ7UXAIwIffABW0P7nn6FQIVi2DBS1GuwB/fYb5M8PlSvDW28Fu5da+03AEqhbAMjy5f6XUpQAlAAM+jZJAAYlqPYi4BGBTz5xgu+PP1w+sw8/dFvBsmAE7Nzfdde54ABZ4hKwFXPLAWjnAC1/5r59/pZSlACUAAz6JkoABiWo9iLgEQGrWlCiBOzZA0ceCV9/DUWLeuRgnLqyaZOrEGGiWpa4BCzgo3dveP99lz/TVtEtkMpHkwCUAAw6LyUAgxJUexHwiIBFqhYuDD/9tD9owYIXZCIgAocmkLb6h+XPLF3aJYP20SQAJQCDzksJwKAE1V4EPCLw668uT92GDS5oYedOyJXLIwfligh4TMDqaF97LdiKb4sW7tyn5dL00SQAJQCDzksJwKAE1V4EPCKwd6/b+rVUFk2bwo4dHjknV0TAcwJvv+3yZlo1EPu3YUPo1MlPpyUAJQCDzkwJwKAE1V4EPCNQsCAMH+62rv73P8+ckzsi4DEBC5q6+GLYtg1q13argZZX00eTAJQADDovJQCDElR7EfCMQMmS0Lo1zJnjtoJlIiAC0RGwnI/nnAN//gnVqsHtt0PLltG1DfsqCUAJwKBzTgIwKEG1FwHPCFSoAOXKwWefKW+dZ49G7nhOwKLmixcHO0ph79GAAdCkiZ9OSwBKAAadmRKAQQmqvQh4RuDSS13N2rx53VlAmQiIQHQEtmxx6X4sj6bl0xw7FurWja5t2FdJAEoABp1zEoBBCaq9CHhG4IorwA6zV68OM2d65pzcEQGPCWzfDsce6yrpnHsuPP00XHSRnw5LAEoABp2ZEoBBCaq9CHhG4MYbYfJkaNfOlbWSiYAIREdg1y7IndsFT9lZwEWL4IILomsb9lUSgBKAQeecBGBQgmovAp4RsLxlI0dCr17+VjHwDJncEYEUAlb6LWdO+PJLKFsW1qxx+TR9NAlACcCg81ICMChBtRcBzwg89JCrY/rII3DLLZ45J3dEwHMCdnZ29Wq3AmhC0Eor+mgSgBKAQeelBGBQgmovAp4RmDfPRS5aAEi9ep45J3dEwHMCRYrAk09C/fruLKDl1fTRJAAlAIPOSwnAoATVXgQ8I2ARjH36wAMPQJ48njknd0TAcwK25du9O9x8M+zZ47aEfTQJQAnAoPNSAjAoQbUXAREQARFIGAJVqrjVPztKYVHBvpoEoARg0LkpARiUoNqLgAiIgAgkDAETf7YNvGQJWGJoX00CUAIw6NyUAAxKUO1FQAREQAQShkCLFvDTT/D997Bunb/DkgCUAAw6OyUAgxJUexEQAREQgYQhYPkzX33VVQRZscLfYUkASgAGnZ0SgEEJqr0IiIAIiEDCELAAkDFjoE4dWLDA32FJAEoABp2dEoBBCaq9CIiACIhAwhAYOBD69oVrrnGl4Hw1CUAJwKBzUwIwKEG1FwEREAERSBgCjz0G7du7ZOojRvg7LAlACcCgs1MCMChBtRcBERABEUgYAlb/t0EDlwama1d/hyUBKAEYdHZKAAYlqPYiIAIiIAIJQ2DLFhcAsmwZ1Kzp77AkACUAg85OCcCgBNVeBERABEQgoQh8/jmUKuX3kCQAJQCDzlAJwKAE1V4EREAEREAEQiYgASgBGHTKSQAGJaj2IiACIiACIhAyAQlACcCgU04CMChBtRcBERABERCBkAlIAEoABp1yEoBBCaq9CIiACIiACIRMQAJQAjDolJMADEpQ7UVABERABEQgZAISgBKAQaecBGBQgmovAiIgAiIgAiETkACUAMxoyp0CDAUuA3IBm4BrgHUZXCwBGPJLq+5EQAREQAREICgBCUAJwPRz6DjgHWA2MAjYBlg2o1+AHyUAg75y8d9+8eLF1K9fP/4HohFERUDPOypMCXORnnfCPMpDDkQCUAIw/SQZCNhf90qHnD3uAq0ARgkqUS674447GDlyZKIMR+M4BAE97+SaInreyfO8JQAlANPP9jcjW7629VsD2AJMj6wG7tUKYPL8cjjQSPUHIrnmgJ63nndyEUie0UoAJo8AnAy0BfaR8ZhfBWoBnwIlgeuAWUA5YD4wBhh2IAH49ddfU6CALQbKEp3APffcw6BBdjpAlgwE9LyT4SnvH6Oed/I8bxOAxYoVswEfC2xPnpHvH2mOJBn0MUCeg4x1N/ArsBbYBVRNc+3dQNN030v9sQWMbE4ShhqmCIiACIiACCQagaLAN4k2qGjGkywCMBoWds1jkVW/alEKQONXJCIeo+1D14mACIiACIiACGQ/gfzAt5Hdwez3JmQPJAD/Cfx84A2gDfAMcBawAHg48hXy41F3IiACIiACIiACIpD1BCQA/z/TRsDgyFnA74BHD3D+L+ufhu4oAiIgAiIgAiIgAiEQkAAMAbK6EAEREAEREAEREAGfCEgABnsa9wE3R/IBWgDJrcBHwW6p1h4S6AfcC+yIRJFbNPk8oLWHvsql2AlcHXl3ywP5gKOAtGmfzo1kArggkhzezgrbuy+LTwKHet727P8E9qR53y0wUL/b4/N5246e7eyVAH4DXgPuShfAmZTvuARg5id0D6Az0AD4HDCRYGcHz4gIhczfWS19I2DPtjZwiW+OyZ8sIVAXKARYtoDH0wlAE4SfAE8AAyLv90JgODAqS3rXTcImcLDnbb6YALT3fVnYjqm/w0LggciZ/g8j7/h4oCxQIdJb0r7jEoCZn29fAFYSYmzkFjkj0UR3RJJHZ/7OaukbAQlA357I4fHHkr+/kk4AWv5Qqw1u0f6pq4K3A7cBpx8eN3TXkAhk9LxTBWCdyFwIyRV1EyIBW+m3kq/2oc/KvCbtOy4BmLlZZ1mfrU6wbQusSnOLxYB9yuieuduqlacETADaM7UtYPuySPHewEZP/ZVbmSOQkSCwD3mWDcBW+lPN3vsVkQSytqUki08CBxOAFgBoRwE2ARMiK8PxOUp5nZ6Abf92BE6L/CBp33EJwMy9HJY48qvIH4aP09xiRiSjePvM3VatPCVg2wWWKPxr4ORIVHgVwM6NmCCUJQaBjASBbQnnBa5JM8QzI+fBrIyA5RCTxSeBAwnASyMf8v4CbLvYyoH2AibG5zDldRoCtrL7HPBv4OXI95P2HZcAzNy7oRXAzHFLlFZWK9q2DhoDSxJlUBpHSv3v9FvASbs6kATz4UACMP3Q+wL1gIuSgEkiD/FyYGpky/eFNANN2ndcAjDz0z2jM4D/A7rpDGDmocZJy1QB2CTNp8g4cV1uHoRARoLAArseTHcGsEskAExnAON7OsUiAOsD1eN7uEntvWVssPP6V2XwoT1p33EJwMy/E3YmzKKALbzcxKB9SrwWKKNtwcxD9bSl/dKwlaGfgJMiW8C2GnAO8LunPsut6AkcETnvZYLAInytPJRt/1ldcNv+tWMeFgVs0YQm+qw60AhFAUcP2LMrD/a8z4ukfrGz3KnRwP+J/H4f59k45E50BOzvtEXw247NygyaWBRwUr7jEoDRTaADXdUf6BD5g7FGeQCDwfS49VzAzvyZGPgZWB7JC2jCXxb/BCwKcHKaeqD2e9FyPdpZMHvWZwOPAJYH0Lb+LY3EwPgfdtKO4GDP24732IqvnfO2PIAWBGLP3nI/yuKTgAn53cDOiPup77cFdqUKwqR8xyUA43NCy2sREAEREAEREAERyDQBCcBMo1NDERABERABERABEYhPAhKA8fnc5LUIiIAIiIAIiIAIZJqABGCm0amhCIiACIiACIiACMQnAQnA+Hxu8loEREAEREAEREAEMk1AAjDT6NRQBERABERABERABOKTgARgfD43eS0CIiACIiACIiACmSYgAZhpdGooAiIgAiIgAiIgAvFJQAIwPp+bvBYBERABERABERCBTBOQAMw0OjUUAREQAREQAREQgfgkIAEYn89NXouACIiACIiACIhApglIAGYanRqKgAgkIQErKH8u8BLwdhKOX0MWARFIEAISgAnyIDUMERCBUAjcDQwBegGDQ+lRnYiACIjAYSAgAXgYoOqWIiACCUugGXAWsBRYnbCj1MBEQAQSnoAEYMI/Yg1QBEQgRgLVgXHAeTG0ewGYA0yJoY0uFQEREIFsIyABmG3o1bEIiICnBNYC/YF5Gfh3LbAHmJHuZ6nnAksAOz0dl9wSAREQgb8JSABqMoiACCQrgVzArnSDvxSYChQD9qX72THABuBJoF8G0FYBjwKTkhWoxi0CIhA/BCQA4+dZyVMREIFgBJYB64ATgPqRVbxO6W45BigAtM2gqw7ABcBxwFUZ/Pw+oCLQKJibai0CIiACh5+ABODhZ6weREAE/CBgAtAEWnNgMZAH+DOda28CzwLD0n2/KFApIg7vAspmMKQrgfFAYT+GKy9EQARE4MAEJAA1O0RABJKFgAnAb4HWBxnwx8CIyFZu2stuB0ZHVgDfAPJGzgKmvaYOsBA4KlmAapwiIALxS0ACMH6fnTwXARGIjYAJwJVAn4M0y2gFsHJENG4G7NygBYhY0Mf6dPfRCmBsz0NXi4AIZCMBCcBshK+uRUAEQiVgAvB1oO9Beh0L5AOuT3NNT2Bomv+bEOwGzE53HxOGtk3cMNRRqTMREAERyAQBCcBMQFMTERCBuCQQjQCsFcnlVzwSBXxDZKXPInxT7VXgtQwigd+KRAA/Fpd05LQIiEBSEZAATKrHrcGKQFITeAVYcYgVQANkeQAHRPL5TQdaAi9HyFkUsAWJ/AY0BT6LfD81D+CpGQSWJDV0DV4ERMBPAhKAfj4XeSUCIpB9BKwSiG0FV4jBhbmRSiBPxdBGl4qACIhAthGQAMw29OpYBERABERABERABLKHgARg9nBXryIgAiIgAiIgAiKQbQQkALMNvToWAREQAREQAREQgewhIAGYPdzVqwiIgAiIgAiIgAhkGwEJwGxDr45FQAREQAREQAREIHsISABmD3f1KgIiIAIiIAIiIALZRkACMNvQq2MREAEREAEREAERyB4CEoDZw129ioAIiIAIiIAIiEC2EZAAzDb06lgEREAEREAEREAEsofA/wHhs74XDf9UTQAAAABJRU5ErkJggg==\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Change the intrinsic mPDF peak width to simulate thermal motion\n",
     "### and/or instrumental resolution effects.\n",
@@ -9355,788 +632,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Change the ordered scale factor relative to the paramagnetic scale factor, simulating\n",
     "### a reduction in the size of the ordered moment relative to the total local moment.\n",
@@ -10158,801 +658,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "### Change the r-range for the calculation from 20 Angstroms (default) to 40.\n",
     "mcL = mc.copy()\n",
@@ -10993,812 +703,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Coordinates of atoms and spins for Mn2+\n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n",
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "All MagSpecies() checks passed. No obvious problems found.\n",
-      "\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n",
-      "(array([ 3.75623147,  1.14768791]), 3)\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Create the structure from our cif file, update the lattice according to the PDFgui fit.\n",
     "structureFile = \"MnO_R-3m.cif\" # note we are not using the cubic structure now\n",
@@ -11874,9 +783,50 @@
     "In the plot above, the top set of curves gives the total experimental PDF (blue circles) with the refined structural PDF (red curve). The lower set of curves gives the structural PDF fit residual (blue circles), which contains the experimental mPDF, with the refined mPDF overlaid (red curve). The lower green curve gives the combined PDF+mPDF fit residual."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As an added bonus of collecting the nuclear and magnetic PDFs together, we can compare the overall scale factor for the nuclear PDF to the ordered scale factor for the mPDF to determine the size of the ordered moment. If we call $A$ the nuclear scale factor, $B$ the mPDF ordered scale factor, $n_s$ the fraction of atoms in the system that are magnetic, and $\\langle b \\rangle$ the average nuclear scattering length, then the magnitude of the refined moment $\\mathrm{S_{fit}}$ is related to the nominal magnitude of the spin vectors $\\mathrm{S_{nom}}$ used in the magnetic structure through the equation $\\mathrm{S_{fit}} = \\sqrt{\\frac{\\mathrm{B}\\langle b \\rangle ^2}{\\mathrm{A} n_s}} \\mathrm{S_{nom}}$. This is the spin quantum number, so the total magnitude of the magnetic moment is given by $g \\mu_{\\mathrm{B}} \\sqrt{\\mathrm{S_{fit}}(\\mathrm{S_{fit}}+1)}$. This is shown for the present case of MnO below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "nucScale = 0.968 ### refined nuclear scale factor taken from PDFgui\n",
+    "\n",
+    "### calculate the average nuclear scattering length\n",
+    "import periodictable as pt ### useful python package included in your installation of diffpy.mpdf\n",
+    "bMn = pt.Mn.neutron.b_c\n",
+    "bO = pt.O.neutron.b_c\n",
+    "bAvg = 0.5*bMn+0.5*bO\n",
+    "\n",
+    "### define the ratio of magnetic atoms to total atoms in MnO\n",
+    "ns = 0.5\n",
+    "\n",
+    "### determine the nominal spin quantum number from your structure\n",
+    "Snom = np.linalg.norm(mstr.spins[0])\n",
+    "\n",
+    "### calculate the refined value of the spin quantum number\n",
+    "Sfit = np.sqrt(mc.ordScale*bAvg**2/(nucScale*ns))*Snom\n",
+    "print Sfit"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We expect S = 2.5 for Mn<sup>2+</sup> with a fully quenched orbital moment. Our refined value is quite close to the ideal value. Not bad!"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {
     "collapsed": true
    },

From b743496760e083023972cd30c26b368b47cd021a Mon Sep 17 00:00:00 2001
From: Benjamin Frandsen <benfrandsen@gmail.com>
Date: Fri, 29 Sep 2017 12:50:13 -0700
Subject: [PATCH 2/4] updated mPDF tutorial materials

---
 cmi_scripts/mpdf/MnOpdfgui.ddp                |  Bin 0 -> 1155484 bytes
 cmi_scripts/mpdf/example_corefinement.ipynb   |  307 +++
 cmi_scripts/mpdf/example_corefinement1.py     |  163 --
 cmi_scripts/mpdf/example_fromPDFgui.py        |   64 -
 cmi_scripts/mpdf/example_fromSrfit.py         |  139 --
 cmi_scripts/mpdf/example_refineSpinDir.ipynb  | 1891 -----------------
 .../mpdf/example_refineSpinDirection.ipynb    |  261 +++
 cmi_scripts/mpdf/introTutorial.ipynb          |  550 ++++-
 8 files changed, 1006 insertions(+), 2369 deletions(-)
 create mode 100644 cmi_scripts/mpdf/MnOpdfgui.ddp
 create mode 100644 cmi_scripts/mpdf/example_corefinement.ipynb
 delete mode 100644 cmi_scripts/mpdf/example_corefinement1.py
 delete mode 100644 cmi_scripts/mpdf/example_fromPDFgui.py
 delete mode 100644 cmi_scripts/mpdf/example_fromSrfit.py
 delete mode 100644 cmi_scripts/mpdf/example_refineSpinDir.ipynb
 create mode 100644 cmi_scripts/mpdf/example_refineSpinDirection.ipynb

diff --git a/cmi_scripts/mpdf/MnOpdfgui.ddp b/cmi_scripts/mpdf/MnOpdfgui.ddp
new file mode 100644
index 0000000000000000000000000000000000000000..a25fa1d8e34d77dd5691590d1c95689bbe186218
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diff --git a/cmi_scripts/mpdf/example_corefinement.ipynb b/cmi_scripts/mpdf/example_corefinement.ipynb
new file mode 100644
index 0000000..88e0e19
--- /dev/null
+++ b/cmi_scripts/mpdf/example_corefinement.ipynb
@@ -0,0 +1,307 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Atomic and magnetic PDF co-refinement using SrFit"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This notebook provides an example of a simultaneous atomic + magnetic PDF refinement using SrFit. We will again use MnO as our test case."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Import necessary modules"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "### Import the necessary libraries\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from diffpy.mpdf import *\n",
+    "from diffpy.Structure import loadStructure\n",
+    "from scipy.optimize import least_squares\n",
+    "from diffpy.Structure.Parsers import getParser\n",
+    "from diffpy.srfit.pdf import PDFGenerator, PDFParser\n",
+    "from diffpy.srfit.fitbase import FitRecipe, FitResults\n",
+    "from diffpy.srfit.fitbase import Profile, FitContribution\n",
+    "\n",
+    "### Set all plots to be inline\n",
+    "%matplotlib notebook"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Set up nuclear/magnetic PDF structures and calculators"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Files containing our experimental data and structure file\n",
+    "dataFile = \"npdf_07334.gr\"\n",
+    "structureFile = \"MnO_R-3m.cif\"\n",
+    "\n",
+    "# load structure and space group from the CIF file\n",
+    "pcif = getParser('cif')\n",
+    "mno = pcif.parseFile(structureFile)\n",
+    "\n",
+    "# prepare profile object with experimental data\n",
+    "profile = Profile()\n",
+    "parser = PDFParser()\n",
+    "parser.parseFile(dataFile)\n",
+    "profile.loadParsedData(parser)\n",
+    "\n",
+    "# define range for pdf calculation\n",
+    "rmin = 0.01\n",
+    "rmax = 20\n",
+    "rstep = 0.01\n",
+    "\n",
+    "# setup calculation range for the PDF simulation\n",
+    "profile.setCalculationRange(xmin=rmin, xmax=rmax, dx=rstep)\n",
+    "\n",
+    "# prepare nucpdf function that simulates the nuclear PDF\n",
+    "nucpdf = PDFGenerator(\"nucpdf\")\n",
+    "nucpdf.setStructure(mno)\n",
+    "nucpdf.setProfile(profile)\n",
+    "\n",
+    "# prepare mpdf function that simulates the magnetic PDF\n",
+    "\n",
+    "# Create the Mn2+ magnetic species. Note that we are using a different\n",
+    "# setting for the unit cell, so the propagation vector is actually (0,0,3/2)\n",
+    "# instead of the (1/2,1/2,1/2) as it was for the pseudocubic setting.\n",
+    "mn2p = MagSpecies(struc=mno, label='Mn2+', magIdxs=[0,1,2],\n",
+    "                  basisvecs=np.array([1,0,0]), kvecs=np.array([0,0,1.5]),\n",
+    "                  ffparamkey='Mn2')\n",
+    "\n",
+    "\n",
+    "# Create and prep the magnetic structure\n",
+    "mstr = MagStructure()\n",
+    "mstr.loadSpecies(mn2p)\n",
+    "mstr.makeAll()\n",
+    "\n",
+    "# Set up the mPDF calculator.\n",
+    "\n",
+    "mc=MPDFcalculator(magstruc=mstr,rmin=rmin,rmax=rmax,rstep=rstep)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Create a \"total PDF\" calculator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "totpdf = FitContribution('totpdf')\n",
+    "totpdf.addProfileGenerator(nucpdf)\n",
+    "totpdf.setProfile(profile)\n",
+    "\n",
+    "# Define an mPDF function that will be added to the total PDF calculator\n",
+    "def mpdf(parascale, ordscale, damp):\n",
+    "    mc.paraScale, mc.ordScale, mc.dampRate = parascale, ordscale, damp\n",
+    "    mc.magstruc.makeAll()\n",
+    "    dr = mc.calc(both=True)[2]\n",
+    "    return dr\n",
+    "\n",
+    "#Add mPDF to the FitContribution\n",
+    "totpdf.registerFunction(mpdf)\n",
+    "totpdf.setEquation(\"nucscale * nucpdf + mpdf(parascale, ordscale, damp)\")\n",
+    "\n",
+    "# Make magnetic PDF depend on any changes to the atomic structure.\n",
+    "# A structure change will now trigger reevaluation of the mPDF.\n",
+    "nucpdf.phase.addObserver(totpdf.ordscale.notify)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Set up the fit recipe and add the parameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# The FitRecipe does the work of calculating the PDF with the fit variable\n",
+    "# that we give it.\n",
+    "mnofit = FitRecipe()\n",
+    "\n",
+    "# give the PDFContribution to the FitRecipe\n",
+    "mnofit.addContribution(totpdf)\n",
+    "\n",
+    "# Configure the fit variables and give them to the recipe.  We can use the\n",
+    "# srfit function constrainAsSpaceGroup to constrain the lattice and ADP\n",
+    "# parameters according to the CIF-loaded space group.\n",
+    "from diffpy.srfit.structure import constrainAsSpaceGroup\n",
+    "sgpars = constrainAsSpaceGroup(nucpdf.phase, pcif.spacegroup.short_name)\n",
+    "\n",
+    "# We can now cycle through the parameters and activate them as variables\n",
+    "for par in sgpars.latpars:\n",
+    "    mnofit.addVar(par)\n",
+    "# Set initial value for the ADP parameters, because CIF had no ADP data.\n",
+    "for par in sgpars.adppars:\n",
+    "    mnofit.addVar(par, value=0.003)\n",
+    "\n",
+    "# As usual, we add variables for the overall scale of the PDF and a delta2\n",
+    "# parameter for correlated motion of neighboring atoms.\n",
+    "mnofit.addVar(totpdf.nucscale, 1)\n",
+    "mnofit.addVar(nucpdf.delta2, 1.5)\n",
+    "\n",
+    "# We fix Qdamp based on prior information about our beamline.\n",
+    "mnofit.addVar(nucpdf.qdamp, 0.03, fixed=True)\n",
+    "\n",
+    "# add the mPDF variables\n",
+    "mnofit.addVar(totpdf.parascale, 4)\n",
+    "mnofit.addVar(totpdf.ordscale, 1.5)\n",
+    "mnofit.addVar(totpdf.damp, 0.01)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Perform the refinement"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Turn off printout of iteration number.\n",
+    "mnofit.clearFitHooks()\n",
+    "\n",
+    "# Initial structural fit\n",
+    "print \"Refine PDF using scipy's least-squares optimizer:\"\n",
+    "print \"  variables:\", mnofit.names\n",
+    "print \"  initial values:\", mnofit.values\n",
+    "least_squares(mnofit.residual, mnofit.values)\n",
+    "print \"  final values:\", mnofit.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot the result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "r = mnofit.totpdf.profile.x\n",
+    "gobs = mnofit.totpdf.profile.y\n",
+    "\n",
+    "# Get the calculated PDF and compute the difference between the calculated and\n",
+    "# measured PDF\n",
+    "gcalc = mnofit.totpdf.evaluate()\n",
+    "gnuc = mnofit.totpdf.evaluateEquation('nucscale * nucpdf')\n",
+    "gmag = mnofit.totpdf.evaluateEquation('mpdf')\n",
+    "\n",
+    "baseline = 1.1 * gobs.min()\n",
+    "gdiff = gobs - gcalc\n",
+    "baseline2 = 1.1 * (gdiff+baseline).min()\n",
+    "\n",
+    "# Plot the best-fit total PDF\n",
+    "ax=plt.figure().add_subplot(111)\n",
+    "ax.plot(r, gobs, 'bo', label=\"G(r) data\", markerfacecolor='none', markeredgecolor='b')\n",
+    "ax.plot(r, gcalc, 'r-', lw=2, label=\"G(r) fit\")\n",
+    "ax.plot(r, gdiff + baseline,'g-')\n",
+    "ax.plot(r, np.zeros_like(r) + baseline, 'k:')\n",
+    "ax.set_xlabel(r\"r ($\\AA$)\")\n",
+    "ax.set_ylabel(r\"G ($\\AA^{-2}$)\")\n",
+    "ax.set_xlim(xmax=mc.rmax)\n",
+    "plt.legend()\n",
+    "\n",
+    "plt.show()\n",
+    "\n",
+    "\n",
+    "# Plot just the mPDF\n",
+    "ax=plt.figure().add_subplot(111)\n",
+    "ax.plot(r, gobs-gnuc, 'bo', label=\"mPDF data\", markerfacecolor='none', markeredgecolor='b')\n",
+    "ax.plot(r, gmag, 'r-', lw=2, label=\"mPDF fit\")\n",
+    "ax.set_xlabel(r\"r ($\\AA$)\")\n",
+    "ax.set_ylabel(r\"D ($\\AA^{-2}$)\")\n",
+    "ax.set_xlim(xmax=mc.rmax)\n",
+    "plt.legend(loc=1)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/cmi_scripts/mpdf/example_corefinement1.py b/cmi_scripts/mpdf/example_corefinement1.py
deleted file mode 100644
index 8e5aa40..0000000
--- a/cmi_scripts/mpdf/example_corefinement1.py
+++ /dev/null
@@ -1,163 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-'''
-This example will show how to simultaneously refine the atomic and magnetic PDF
-of MnO using SrFit.
-'''
-
-# Import necessary functions
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.optimize.minpack import leastsq
-
-from diffpy.mpdf import *
-from diffpy.Structure.Parsers import getParser
-from diffpy.srfit.pdf import PDFGenerator, PDFParser
-from diffpy.srfit.fitbase import FitRecipe, FitResults
-from diffpy.srfit.fitbase import Profile, FitContribution
-
-# Files containing our experimental data and structure file
-dataFile = "npdf_07334.gr"
-structureFile = "MnO_R-3m.cif"
-
-# load structure and space group from the CIF file
-pcif = getParser('cif')
-mno = pcif.parseFile(structureFile)
-
-# prepare profile object with experimental data
-profile = Profile()
-parser = PDFParser()
-parser.parseFile(dataFile)
-profile.loadParsedData(parser)
-
-# define range for pdf calculation
-rmin = 0.01
-rmax = 20
-rstep = 0.01
-
-# setup calculation range for the PDF simulation
-profile.setCalculationRange(xmin=rmin, xmax=rmax, dx=rstep)
-
-# prepare nucpdf function that simulates the nuclear PDF
-nucpdf = PDFGenerator("nucpdf")
-nucpdf.setStructure(mno)
-nucpdf.setProfile(profile)
-
-# prepare mpdf function that simulates the magnetic PDF
-
-# Create the Mn2+ magnetic species
-mn2p = MagSpecies(struc=mno, label='Mn2+', magIdxs=[0,1,2],
-                  basisvecs=2.5*np.array([1,0,0]), kvecs=np.array([0,0,1.5]),
-                  ffparamkey='Mn2')
-
-# Create and prep the magnetic structure
-mstr = MagStructure()
-mstr.loadSpecies(mn2p)
-mstr.makeAll()
-
-# Set up the mPDF calculator.
-
-mc=MPDFcalculator(magstruc=mstr,rmin=rmin,rmax=rmax,
-                  rstep=rstep, gaussPeakWidth=0.2)
-
-def mpdf(parascale, ordscale):
-    mc.paraScale = parascale
-    mc.ordScale = ordscale
-    mc.magstruc.makeAtoms()
-    mc.magstruc.makeSpins()
-    rv = mc.calc(both=True)[2]
-    return rv
-
-totpdf = FitContribution('totpdf')
-totpdf.addProfileGenerator(nucpdf)
-totpdf.setProfile(profile)
-
-# Add mPDF to the FitContribution
-totpdf.registerFunction(mpdf)
-totpdf.setEquation("nucscale * nucpdf + mpdf(parascale, ordscale)")
-
-# Make magnetic PDF depend on any changes to the atomic structure.
-# Cover your eyes, but a structure change will now trigger the same
-# reevaluations as if ordscale were modified.
-nucpdf.phase.addObserver(totpdf.ordscale.notify)
-
-# The FitRecipe does the work of calculating the PDF with the fit variable
-# that we give it.
-mnofit = FitRecipe()
-
-# give the PDFContribution to the FitRecipe
-mnofit.addContribution(totpdf)
-
-# Configure the fit variables and give them to the recipe.  We can use the
-# srfit function constrainAsSpaceGroup to constrain the lattice and ADP
-# parameters according to the CIF-loaded space group.
-from diffpy.srfit.structure import constrainAsSpaceGroup
-sgpars = constrainAsSpaceGroup(nucpdf.phase, pcif.spacegroup.short_name)
-print "Space group parameters are:",
-print ', '.join([p.name for p in sgpars])
-print
-
-# We can now cycle through the parameters and activate them in the recipe as
-# variables
-for par in sgpars.latpars:
-    mnofit.addVar(par)
-# Set initial value for the ADP parameters, because CIF had no ADP data.
-for par in sgpars.adppars:
-    mnofit.addVar(par, value=0.003, fixed=True)
-
-# As usual, we add variables for the overall scale of the PDF and a delta2
-# parameter for correlated motion of neighboring atoms.
-mnofit.addVar(totpdf.nucscale, 1)
-mnofit.addVar(nucpdf.delta2, 1.5)
-
-# We fix Qdamp based on prior information about our beamline.
-mnofit.addVar(nucpdf.qdamp, 0.03, fixed=True)
-
-# add the mPDF variables
-mnofit.addVar(totpdf.parascale, 4)
-mnofit.addVar(totpdf.ordscale, 1.5)
-
-# Turn off printout of iteration number.
-mnofit.clearFitHooks()
-
-# Initial structural fit
-print "Refine PDF using scipy's least-squares optimizer:"
-print "  variables:", mnofit.names
-print "  initial values:", mnofit.values
-leastsq(mnofit.residual, mnofit.values)
-print "  final values:", mnofit.values
-print
-# Obtain and display the fit results.
-mnoresults = FitResults(mnofit)
-print "FIT RESULTS\n"
-print mnoresults
-
-
-# Get the experimental data from the recipe
-r = mnofit.totpdf.profile.x
-gobs = mnofit.totpdf.profile.y
-
-# Get the calculated PDF and compute the difference between the calculated and
-# measured PDF
-gcalc = mnofit.totpdf.evaluate()
-gnuc = mnofit.totpdf.evaluateEquation('nucscale * nucpdf')
-gmag = mnofit.totpdf.evaluateEquation('mpdf')
-
-baseline = 1.1 * gobs.min()
-gdiff = gobs - gcalc
-baseline2 = 1.1 * (gdiff+baseline).min()
-magfit=mc.calc(both=True)[2]
-
-# Plot!
-ax=plt.figure().add_subplot(111)
-ax.plot(r, gobs, 'bo', label="G(r) data", markerfacecolor='none', markeredgecolor='b')
-ax.plot(r, gcalc, 'r-', lw=1.5, label="G(r) fit")
-ax.plot(r, gdiff + baseline,'g-')
-ax.plot(r, np.zeros_like(r) + baseline, 'k:')
-ax.set_xlabel(r"r ($\AA$)")
-ax.set_ylabel(r"G ($\AA^{-2}$)")
-ax.set_xlim(xmax=mc.rmax)
-plt.legend()
-
-plt.show()
diff --git a/cmi_scripts/mpdf/example_fromPDFgui.py b/cmi_scripts/mpdf/example_fromPDFgui.py
deleted file mode 100644
index 7573135..0000000
--- a/cmi_scripts/mpdf/example_fromPDFgui.py
+++ /dev/null
@@ -1,64 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-'''
-This example will show how to perform mPDF refinements after having done the atomic
-PDF refinement in PDFgui. We use data from MnO at 15 K.
-'''
-
-# Import necessary functions
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.optimize import leastsq
-
-from diffpy.mpdf import *
-from diffpy.Structure import loadStructure
-
-# Create the structure from our cif file, update the lattice params
-structureFile = "MnO_R-3m.cif"
-mnostructure = loadStructure(structureFile)
-lat = mnostructure.lattice
-lat.a,lat.b,lat.c = 3.1505626,3.1505626,7.5936979 ## refined values from PDFgui
-
-# Create the Mn2+ magnetic species
-mn2p = MagSpecies(struc=mnostructure, label='Mn2+', magIdxs=[0,1,2],
-                 basisvecs=2.5*np.array([1,0,0]), kvecs=np.array([0,0,1.5]),
-                 ffparamkey='Mn2')
-
-# Create and prep the magnetic structure
-mstr = MagStructure()
-mstr.loadSpecies(mn2p)
-mstr.makeAtoms()
-mstr.makeSpins()
-mstr.makeFF()
-
-# Set up the mPDF calculator
-mc = MPDFcalculator(magstruc=mstr, gaussPeakWidth=0.2)
-
-# Load the data
-PDFfitFile = 'MnOfit_PDFgui.fgr'
-rexp,Drexp = getDiffData([PDFfitFile]) # this reads in the fit file
-mc.rmin = rexp.min()
-mc.rmax = rexp.max()
-
-# Do the refinement
-def residual(p, yexp, mcalc):
-    mcalc.paraScale, mcalc.ordScale = p
-    return yexp-mcalc.calc(both=True)[2]
-
-p0 = [5.0,3.0] # initial parameter values (paraScale, ordScale)
-pOpt = leastsq(residual, p0, args=(Drexp,mc))
-print pOpt
-
-fit=mc.calc(both=True)[2]
-
-# Plot the results
-fig = plt.figure()
-ax = fig.add_subplot(111)
-ax.plot(rexp, Drexp, marker='o', mfc='none', mec='b', linestyle='none')
-ax.plot(rexp, fit, 'r-', lw=2)
-ax.set_xlim(xmin=mc.rmin, xmax=mc.rmax)
-ax.set_xlabel('r ($\AA$)')
-ax.set_ylabel('d(r) ($\AA^{-2}$)')
-
-plt.show()
diff --git a/cmi_scripts/mpdf/example_fromSrfit.py b/cmi_scripts/mpdf/example_fromSrfit.py
deleted file mode 100644
index 96cc7e2..0000000
--- a/cmi_scripts/mpdf/example_fromSrfit.py
+++ /dev/null
@@ -1,139 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-'''
-This example will show how to perform mPDF refinements after performing the atomic
-PDF refinement in SrFit. We use data from MnO at 15 K.
-'''
-
-# Import necessary functions
-import numpy as np
-import matplotlib.pyplot as plt
-from scipy.optimize import leastsq
-
-from diffpy.mpdf import *
-from diffpy.Structure import loadStructure
-from diffpy.srfit.pdf import PDFContribution
-from diffpy.srfit.fitbase import FitRecipe, FitResults
-
-
-# Files containing our experimental data and structure file
-dataFile = "npdf_07334.gr"
-structureFile = "MnO_R-3m.cif"
-spaceGroup = "H-3m"
-mnostructure = loadStructure(structureFile)
-
-# Create the Mn2+ magnetic species
-mn2p = MagSpecies(struc=mnostructure, label='Mn2+', magIdxs=[0,1,2],
-                 basisvecs=2.5*np.array([[1,0,0]]), kvecs=np.array([[0,0,1.5]]),
-                 ffparamkey='Mn2')
-
-# Create and prep the magnetic structure
-mstr = MagStructure()
-mstr.loadSpecies(mn2p)
-mstr.makeAll()
-
-# Set up the mPDF calculator
-mc = MPDFcalculator(magstruc=mstr, gaussPeakWidth=0.2)
-
-### DO THE STRUCTURAL FIT USING SRFIT
-
-# Construct the atomic PDF contribution
-MnOPDF = PDFContribution("MnO")
-
-# Load the data and set the r-range over which we'll fit
-MnOPDF.loadData(dataFile)
-MnOPDF.setCalculationRange(xmin=0.01, xmax=20, dx=0.01)
-
-# Add the structure from our cif file to the contribution
-MnOPDF.addStructure("MnO", mnostructure)
-
-# The FitRecipe does the work of calculating the PDF with the fit variable
-# that we give it.
-MnOFit = FitRecipe()
-
-# give the PDFContribution to the FitRecipe
-MnOFit.addContribution(MnOPDF)
-
-# Configure the fit variables and give them to the recipe.  We can use the
-# srfit function constrainAsSpaceGroup to constrain the lattice and ADP
-# parameters according to the H-3m space group.
-from diffpy.srfit.structure import constrainAsSpaceGroup
-spaceGroupParams = constrainAsSpaceGroup(MnOPDF.MnO.phase, spaceGroup)
-print "Space group parameters are:",
-print ', '.join([p.name for p in spaceGroupParams])
-print
-
-# We can now cycle through the parameters and activate them in the recipe as
-# variables
-for par in spaceGroupParams.latpars:
-    MnOFit.addVar(par)
-# Set initial value for the ADP parameters, because CIF had no ADP data.
-for par in spaceGroupParams.adppars:
-    MnOFit.addVar(par, value=0.003,fixed=True)
-
-# As usual, we add variables for the overall scale of the PDF and a delta2
-# parameter for correlated motion of neighboring atoms.
-MnOFit.addVar(MnOPDF.scale, 1)
-MnOFit.addVar(MnOPDF.MnO.delta2, 1.5)
-
-# We fix Qdamp based on prior information about our beamline.
-MnOFit.addVar(MnOPDF.qdamp, 0.03, fixed=True)
-
-# Turn off printout of iteration number.
-MnOFit.clearFitHooks()
-
-# We can now execute the fit using scipy's least square optimizer.
-print "Refine PDF using scipy's least-squares optimizer:"
-print "  variables:", MnOFit.names
-print "  initial values:", MnOFit.values
-leastsq(MnOFit.residual, MnOFit.values)
-print "  final values:", MnOFit.values
-print
-
-# Obtain and display the fit results.
-MnOResults = FitResults(MnOFit)
-print "FIT RESULTS\n"
-print MnOResults
-
-# Get the experimental data from the recipe
-r = MnOFit.MnO.profile.x
-gobs = MnOFit.MnO.profile.y
-
-# Get the calculated PDF and compute the difference between the calculated and
-# measured PDF
-gcalc = MnOFit.MnO.evaluate()
-baseline = 1.1 * gobs.min()
-gdiff = gobs - gcalc
-baseline2 = 1.2 * (gdiff+baseline).min()
-
-### NOW DO THE MPDF REFINEMENT USING THE RESIDUAL FROM THE ATOMIC PDF
-mc.rmin = r.min()
-mc.rmax = r.max()
-def residual(p, yexp, mcalc):
-    mcalc.paraScale, mcalc.ordScale = p
-    return yexp - mcalc.calc(both=True)[2]
-
-p0 = [5.0, 3.0] # initial parameter values (parScale, ordScale)
-pOpt = leastsq(residual, p0, args=(gdiff,mc))
-print pOpt
-
-fit=mc.calc(both=True)[2]
-
-# Plot!
-ax=plt.figure().add_subplot(111)
-ax.plot(r, gobs, 'bo', label="Total PDF",markerfacecolor='b', markeredgecolor='b')
-ax.plot(r, gdiff + baseline,mfc='Indigo',mec='Indigo',marker='o',linestyle='none',label='mPDF')
-ax.plot(r, gcalc, 'r-', lw=2.5, label="Fit")
-ax.plot(r, fit+baseline,'r-',lw=2.5)
-ax.plot(r, gdiff - fit + baseline2, 'g-', label='Residual')
-ax.plot(r, np.zeros_like(r) + baseline2, 'k:')
-ax.set_xlabel('r ($\AA$)', fontsize=16)
-ax.set_ylabel('G, d ($\AA^{-2}$)', fontsize=16)
-ax.set_xlim(xmin=0, xmax=20)
-#ax.set_yticks([])
-#ax.set_yticklabels([])
-plt.legend()
-
-plt.tight_layout()
-plt.show()
diff --git a/cmi_scripts/mpdf/example_refineSpinDir.ipynb b/cmi_scripts/mpdf/example_refineSpinDir.ipynb
deleted file mode 100644
index 29f711d..0000000
--- a/cmi_scripts/mpdf/example_refineSpinDir.ipynb
+++ /dev/null
@@ -1,1891 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Refining the spin direction"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "This notebook provides examples of two methods for refining the spin direction: \n",
-    "   1. Updating the basis vector(s) and calling the makeSpins() function, which is a very general method and will work for magnetic structures of arbitrary complexity;\n",
-    "   2. Storing the locations of the \"up\" spins and \"down\" spins and updating them without calling makeSpins(), which is faster but best suited only for simple collinear magnetic structures."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ben/anaconda/envs/mpdfdev/lib/python2.7/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
-      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
-     ]
-    }
-   ],
-   "source": [
-    "### Import everything we need\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot as plt\n",
-    "from scipy.optimize import leastsq\n",
-    "\n",
-    "from diffpy.mpdf import *\n",
-    "from diffpy.Structure import loadStructure\n",
-    "\n",
-    "import time # we will be doing some speed testing\n",
-    "\n",
-    "%matplotlib notebook"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "lattice=Lattice(a=3.15056, b=3.15056, c=7.5937, alpha=90, beta=90, gamma=120)\n",
-      "Mn   0.000000 0.000000 0.000000 1.0000\n",
-      "Mn   0.333333 0.666667 0.666667 1.0000\n",
-      "Mn   0.666667 0.333333 0.333333 1.0000\n",
-      "O    0.000000 0.000000 0.500000 1.0000\n",
-      "O    0.333333 0.666667 0.166667 1.0000\n",
-      "O    0.666667 0.333333 0.833333 1.0000\n"
-     ]
-    }
-   ],
-   "source": [
-    "### Create the structure from our cif file, update the lattice params\n",
-    "structureFile = \"MnO_R-3m.cif\"\n",
-    "mnostructure = loadStructure(structureFile)\n",
-    "lat = mnostructure.lattice\n",
-    "lat.a, lat.b, lat.c = 3.1505626, 3.1505626, 7.5936979 # refined values from PDFgui\n",
-    "print mnostructure"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "### Set up the magSpecies\n",
-    "mn2p=MagSpecies(struc=mnostructure, label='Mn2+')\n",
-    "mn2p.magIdxs = [0,1,2]\n",
-    "mn2p.kvecs = np.array([0,0,1.5])\n",
-    "mn2p.ffparamkey = 'Mn2'\n",
-    "\n",
-    "# start with a randomly oriented spin basis vector\n",
-    "theta0 = np.arccos(np.random.uniform(-1,1))\n",
-    "phi0 = np.random.uniform(-np.pi,np.pi)\n",
-    "mn2p.basisvecs = 2.5*np.array([[np.sin(theta0)*np.cos(phi0),\n",
-    "                                np.sin(theta0)*np.sin(phi0), np.cos(theta0)]])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Coordinates of atoms and spins for Mn2+\n",
-      "have not been loaded because they have not yet been\n",
-      "generated and/or do not match in shape.\n",
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "kvecs and basisvecs must have the same dimensions.\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n",
-      "Running checks for Mn2+ MagSpecies object...\n",
-      "\n",
-      "kvecs and basisvecs must have the same dimensions.\n",
-      "Running checks for  MagStructure object...\n",
-      "\n",
-      "All MagStructure checks passed. No obvious problems found.\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/ben/anaconda/envs/mpdfdev/lib/python2.7/site-packages/diffpy.Structure-1.3.2-py2.7.egg/diffpy/Structure/lattice.py:125: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n",
-      "  if [a, b, c, alpha, beta, gamma, base] == 7*[None]:\n"
-     ]
-    }
-   ],
-   "source": [
-    "### Create and prep the magStructure\n",
-    "mstr = MagStructure()\n",
-    "mstr.loadSpecies(mn2p)\n",
-    "mstr.makeAll()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
-   "source": [
-    "### Set up the mPDF calculator\n",
-    "mc = MPDFcalculator(magstruc=mstr)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "### Load the data\n",
-    "PDFfitFile = 'MnOfit_PDFgui.fgr'\n",
-    "rexp,Drexp = getDiffData([PDFfitFile])\n",
-    "mc.rmin = rexp.min()\n",
-    "mc.rmax = rexp.max()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Method 1: Update the basis vector directly and call makeSpins() (slower)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Refined parameters:  [  3.75623138e+00   1.14768778e+00   1.57078652e+00  -8.42358774e+03]\n",
-      "Duration of refinement:  2.83608698845\n",
-      "Refined spin:  [ -1.39704933e+00   2.07322290e+00   2.45182236e-05]\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Do the refinement\n",
-    "def residual1(p,yexp):\n",
-    "    mc.paraScale, mc.ordScale, theta, phi = p\n",
-    "    mn2p.basisvecs = 2.5*np.array([np.sin(theta)*np.cos(phi),\n",
-    "                                   np.sin(theta)*np.sin(phi), np.cos(theta)])\n",
-    "    mstr.makeSpins()\n",
-    "    return yexp - mc.calc(both=True)[2]\n",
-    "\n",
-    "p0 = [5.0, 3.0, theta0, phi0] # initial parameter values\n",
-    "\n",
-    "start = time.time()\n",
-    "pOpt = leastsq(residual1, p0, args=(Drexp))\n",
-    "end = time.time()\n",
-    "\n",
-    "print 'Refined parameters: ', pOpt[0]\n",
-    "print 'Duration of refinement: ', end-start\n",
-    "thetaF, phiF = pOpt[0][2], pOpt[0][3]\n",
-    "Sfinal = 2.5*np.array([np.sin(thetaF)*np.cos(phiF),\n",
-    "                       np.sin(thetaF)*np.sin(phiF),np.cos(thetaF)])\n",
-    "print 'Refined spin: ', Sfinal\n",
-    "\n",
-    "fit=mc.calc(both=True)[2]\n",
-    "\n",
-    "# Plot the results\n",
-    "fig=plt.figure()\n",
-    "ax=fig.add_subplot(111)\n",
-    "ax.plot(rexp,Drexp,marker='o',mfc='none',mec='b',linestyle='none')\n",
-    "ax.plot(rexp,fit,'r-',lw=2)\n",
-    "ax.set_xlim(xmin=mc.rmin,xmax=mc.rmax)\n",
-    "ax.set_xlabel('r ($\\AA$)')\n",
-    "ax.set_ylabel('d(r) ($\\AA^{-2}$)')\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Method 2: Store the indices of the up and down spins and use these to update (faster)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Refined parameters:  [  3.75623138e+00   1.14768778e+00   1.57078652e+00  -8.42358774e+03]\n",
-      "Duration of refinement:  2.67924809456\n",
-      "Refined spin:  [ -1.39704933e+00   2.07322290e+00   2.45182236e-05]\n"
-     ]
-    },
-    {
-     "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "window.mpl = {};\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",
-       "            fig.send_message(\"refresh\", {});\n",
-       "        }\n",
-       "\n",
-       "    this.imageObj.onload = function() {\n",
-       "            if (fig.image_mode == 'full') {\n",
-       "                // Full images could contain transparency (where diff images\n",
-       "                // almost always do), so we need to clear the canvas so that\n",
-       "                // there is no ghosting.\n",
-       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "            }\n",
-       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "        };\n",
-       "\n",
-       "    this.imageObj.onunload = function() {\n",
-       "        this.ws.close();\n",
-       "    }\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function() {\n",
-       "    var titlebar = $(\n",
-       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
-       "        'ui-helper-clearfix\"/>');\n",
-       "    var titletext = $(\n",
-       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
-       "        'text-align: center; padding: 3px;\"/>');\n",
-       "    titlebar.append(titletext)\n",
-       "    this.root.append(titlebar);\n",
-       "    this.header = titletext[0];\n",
-       "}\n",
-       "\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = $('<div/>');\n",
-       "\n",
-       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
-       "\n",
-       "    function canvas_keyboard_event(event) {\n",
-       "        return fig.key_event(event, event['data']);\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
-       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
-       "    this.canvas_div = canvas_div\n",
-       "    this._canvas_extra_style(canvas_div)\n",
-       "    this.root.append(canvas_div);\n",
-       "\n",
-       "    var canvas = $('<canvas/>');\n",
-       "    canvas.addClass('mpl-canvas');\n",
-       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
-       "\n",
-       "    this.canvas = canvas[0];\n",
-       "    this.context = canvas[0].getContext(\"2d\");\n",
-       "\n",
-       "    var 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);\n",
-       "        canvas.attr('height', height);\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'];\n",
-       "    var y0 = fig.canvas.height - msg['y0'];\n",
-       "    var x1 = msg['x1'];\n",
-       "    var y1 = fig.canvas.height - msg['y1'];\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
-       "    var cursor = msg['cursor'];\n",
-       "    switch(cursor)\n",
-       "    {\n",
-       "    case 0:\n",
-       "        cursor = 'pointer';\n",
-       "        break;\n",
-       "    case 1:\n",
-       "        cursor = 'default';\n",
-       "        break;\n",
-       "    case 2:\n",
-       "        cursor = 'crosshair';\n",
-       "        break;\n",
-       "    case 3:\n",
-       "        cursor = 'move';\n",
-       "        break;\n",
-       "    }\n",
-       "    fig.rubberband_canvas.style.cursor = cursor;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message(\"ack\", {});\n",
-       "}\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            /* FIXME: We get \"Resource interpreted as Image but\n",
-       "             * transferred with MIME type text/plain:\" errors on\n",
-       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "             * to be part of the websocket stream */\n",
-       "            evt.data.type = \"image/png\";\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src);\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                evt.data);\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig[\"handle_\" + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "}\n",
-       "\n",
-       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function(e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e)\n",
-       "        e = window.event;\n",
-       "    if (e.target)\n",
-       "        targ = e.target;\n",
-       "    else if (e.srcElement)\n",
-       "        targ = e.srcElement;\n",
-       "    if (targ.nodeType == 3) // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "\n",
-       "    // jQuery normalizes the pageX and pageY\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    // offset() returns the position of the element relative to the document\n",
-       "    var x = e.pageX - $(targ).offset().left;\n",
-       "    var y = e.pageY - $(targ).offset().top;\n",
-       "\n",
-       "    return {\"x\": x, \"y\": y};\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * http://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys (original) {\n",
-       "  return Object.keys(original).reduce(function (obj, key) {\n",
-       "    if (typeof original[key] !== 'object')\n",
-       "        obj[key] = original[key]\n",
-       "    return obj;\n",
-       "  }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event)\n",
-       "\n",
-       "    if (name === 'button_press')\n",
-       "    {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x;\n",
-       "    var y = canvas_pos.y;\n",
-       "\n",
-       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
-       "                             step: event.step,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function(event, name) {\n",
-       "\n",
-       "    // Prevent repeat events\n",
-       "    if (name == 'key_press')\n",
-       "    {\n",
-       "        if (event.which === this._key)\n",
-       "            return;\n",
-       "        else\n",
-       "            this._key = event.which;\n",
-       "    }\n",
-       "    if (name == 'key_release')\n",
-       "        this._key = null;\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.which != 17)\n",
-       "        value += \"ctrl+\";\n",
-       "    if (event.altKey && event.which != 18)\n",
-       "        value += \"alt+\";\n",
-       "    if (event.shiftKey && event.which != 16)\n",
-       "        value += \"shift+\";\n",
-       "\n",
-       "    value += 'k';\n",
-       "    value += event.which.toString();\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, {key: value,\n",
-       "                             guiEvent: simpleKeys(event)});\n",
-       "    return false;\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
-       "    if (name == 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message(\"toolbar_button\", {name: name});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.close = function() {\n",
-       "        comm.close()\n",
-       "    };\n",
-       "    ws.send = function(m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function(msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
-       "        ws.onmessage(msg['content']['data'])\n",
-       "    });\n",
-       "    return ws;\n",
-       "}\n",
-       "\n",
-       "mpl.mpl_figure_comm = function(comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = $(\"#\" + id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm)\n",
-       "\n",
-       "    function ondownload(figure, format) {\n",
-       "        window.open(figure.imageObj.src);\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy,\n",
-       "                           ondownload,\n",
-       "                           element.get(0));\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element.get(0);\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "\n",
-       "    var output_index = fig.cell_info[2]\n",
-       "    var cell = fig.cell_info[0];\n",
-       "\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
-       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function() {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message(\"ack\", {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function() {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var nav_element = $('<div/>')\n",
-       "    nav_element.attr('style', 'width: 100%');\n",
-       "    this.root.append(nav_element);\n",
-       "\n",
-       "    // Define a callback function for later on.\n",
-       "    function toolbar_event(event) {\n",
-       "        return fig.toolbar_button_onclick(event['data']);\n",
-       "    }\n",
-       "    function toolbar_mouse_event(event) {\n",
-       "        return fig.toolbar_button_onmouseover(event['data']);\n",
-       "    }\n",
-       "\n",
-       "    for(var toolbar_ind in mpl.toolbar_items){\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) { continue; };\n",
-       "\n",
-       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
-       "        button.click(method_name, toolbar_event);\n",
-       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
-       "        nav_element.append(button);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
-       "    nav_element.append(status_bar);\n",
-       "    this.message = status_bar[0];\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
-       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
-       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
-       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
-       "    buttongrp.append(button);\n",
-       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
-       "    titlebar.prepend(buttongrp);\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function(el){\n",
-       "    var fig = this\n",
-       "    el.on(\"remove\", function(){\n",
-       "\tfig.close_ws(fig, {});\n",
-       "    });\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.attr('tabindex', 0)\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "    else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
-       "    var manager = IPython.notebook.keyboard_manager;\n",
-       "    if (!manager)\n",
-       "        manager = IPython.keyboard_manager;\n",
-       "\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which == 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        event.shiftKey = false;\n",
-       "        // Send a \"J\" for go to next cell\n",
-       "        event.which = 74;\n",
-       "        event.keyCode = 74;\n",
-       "        manager.command_mode();\n",
-       "        manager.handle_keydown(event);\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "}\n",
-       "\n",
-       "\n",
-       "mpl.find_output_cell = function(html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i=0; i<ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code'){\n",
-       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] == html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "}\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel != null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
-       "}\n"
-      ],
-      "text/plain": [
-       "<IPython.core.display.Javascript object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
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\">"
-      ],
-      "text/plain": [
-       "<IPython.core.display.HTML object>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "### Reset the magnetic structure to how it was originally\n",
-    "mn2p.basisvecs = 2.5*np.array([np.sin(theta0)*np.cos(phi0),\n",
-    "                               np.sin(theta0)*np.sin(phi0), np.cos(theta0)])\n",
-    "mstr.makeSpins()\n",
-    "\n",
-    "### Find the locations of the up and down spins (we are creating boolean masks)\n",
-    "upSpins = np.all(mstr.spins==mn2p.basisvecs, axis=1)\n",
-    "downSpins = np.all(mstr.spins==-1.0*mn2p.basisvecs, axis=1)\n",
-    "# Warning! If you define your basisvecs as a nested array, i.e. np.array([[x,y,z]]),\n",
-    "# you will want to use basisvecs[0] instead of basisvecs in the two preceding lines.\n",
-    "\n",
-    "### Modify the residual function\n",
-    "def residual2(p,yexp):\n",
-    "    mc.paraScale, mc.ordScale, theta, phi = p\n",
-    "    Svec = 2.5*np.array([np.sin(theta)*np.cos(phi),\n",
-    "                         np.sin(theta)*np.sin(phi), np.cos(theta)])\n",
-    "    mstr.spins[upSpins] = Svec\n",
-    "    mstr.spins[downSpins] = -Svec\n",
-    "    return yexp - mc.calc(both=True)[2]\n",
-    "\n",
-    "p0=[5.0, 3.0, theta0, phi0] # initial parameter values\n",
-    "\n",
-    "start = time.time()\n",
-    "pOpt = leastsq(residual2, p0, args=(Drexp))\n",
-    "end=time.time()\n",
-    "\n",
-    "print 'Refined parameters: ', pOpt[0]\n",
-    "print 'Duration of refinement: ', end-start\n",
-    "thetaF, phiF = pOpt[0][2], pOpt[0][3]\n",
-    "Sfinal = 2.5*np.array([np.sin(thetaF)*np.cos(phiF),\n",
-    "                       np.sin(thetaF)*np.sin(phiF), np.cos(thetaF)])\n",
-    "print 'Refined spin: ', Sfinal\n",
-    "\n",
-    "### Update the magnetic structure with the refined spin\n",
-    "#mn2p.basisvecs = np.array([Sfinal])\n",
-    "#mstr.makeSpins()\n",
-    "fit = mc.calc(both=True)[2]\n",
-    "\n",
-    "### Plot the results\n",
-    "fig = plt.figure()\n",
-    "ax = fig.add_subplot(111)\n",
-    "ax.plot(rexp, Drexp, marker='o', mfc='none', mec='b', linestyle='none')\n",
-    "ax.plot(rexp, fit, 'r-', lw=2)\n",
-    "ax.set_xlim(xmin=mc.rmin, xmax=mc.rmax)\n",
-    "ax.set_xlabel('r ($\\AA$)')\n",
-    "ax.set_ylabel('d(r) ($\\AA^{-2}$)')\n",
-    "\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "plt.close('all')"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 2",
-   "language": "python",
-   "name": "python2"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 2
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.11"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
diff --git a/cmi_scripts/mpdf/example_refineSpinDirection.ipynb b/cmi_scripts/mpdf/example_refineSpinDirection.ipynb
new file mode 100644
index 0000000..799e95b
--- /dev/null
+++ b/cmi_scripts/mpdf/example_refineSpinDirection.ipynb
@@ -0,0 +1,261 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Refining the spin direction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This notebook provides examples of two methods for refining the spin direction: \n",
+    "   1. Updating the basis vector(s) and calling the makeSpins() function, which is a very general method and will work for magnetic structures of arbitrary complexity;\n",
+    "   2. Storing the locations of the \"up\" spins and \"down\" spins and updating them without calling makeSpins(), which is faster and well suited for simple collinear magnetic structures."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "### Import the necessary libraries\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from diffpy.mpdf import *\n",
+    "from diffpy.Structure import loadStructure\n",
+    "from scipy.optimize import least_squares\n",
+    "\n",
+    "### Set all plots to be inline\n",
+    "%matplotlib notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "### Make the magnetic structure\n",
+    "PDFguiFile = 'MnOpdfgui.ddp'\n",
+    "struc = getStrucFromPDFgui(PDFguiFile,1)\n",
+    "\n",
+    "th0, phi0 = np.arccos(np.random.uniform(-1,1)),np.random.uniform(-np.pi,np.pi)\n",
+    "svec = np.array([np.sin(th0)*np.cos(phi0),np.sin(th0)*np.sin(phi0),np.cos(th0)])\n",
+    "msp = MagSpecies(struc,magIdxs=[0,1,2,3],ffparamkey='Mn2',rmaxAtoms=50,basisvecs=svec,\n",
+    "                kvecs=np.array([0.5,0.5,0.5]),label=str(0))\n",
+    "\n",
+    "mstr=MagStructure()\n",
+    "mstr.loadSpecies(msp)\n",
+    "mstr.makeAll()\n",
+    "\n",
+    "\n",
+    "### Get the data and make the calculator\n",
+    "r,d = getDiffData(PDFguiFile)\n",
+    "\n",
+    "mc = MPDFcalculator(mstr)\n",
+    "mc.rmin = r.min()\n",
+    "mc.rmax = r.max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Define a residual function that allows moment directions to vary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def residual(p,ydata):\n",
+    "    oscale,pscale,damp,th,phi = p\n",
+    "    newsvec = np.array([np.sin(th)*np.cos(phi),np.sin(th)*np.sin(phi),np.cos(th)])\n",
+    "    mstr.species['0'].basisvecs = newsvec\n",
+    "    mstr.makeSpins()\n",
+    "    mc.ordScale = oscale\n",
+    "    mc.paraScale = pscale\n",
+    "    mc.dampRate = damp\n",
+    "    return ydata - mc.calc(both=True)[2]\n",
+    "\n",
+    "p0 = [0.1,0.1,0.1,np.arccos(np.random.uniform(-1,1)),np.random.uniform(-np.pi,np.pi)]\n",
+    "optimized = least_squares(residual,p0,bounds=[[0,0,0,0,-np.pi],[10,10,10,np.pi,np.pi]],\n",
+    "                          args=(d,))\n",
+    "fit = mc.calc(both=True)[2]\n",
+    "\n",
+    "fig=plt.figure()\n",
+    "ax=fig.add_subplot(111)\n",
+    "ax.plot(r,d,'bo',linestyle='none')\n",
+    "ax.plot(r,fit,'r-',lw=2)\n",
+    "ax.set_xlabel('r ($\\AA$)')\n",
+    "ax.set_ylabel('D($\\AA^{-2}$)')\n",
+    "\n",
+    "plt.show()    "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visualize the refined magnetic structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "### Visualize the magnetic structure\n",
+    "uc = struc[:4].xyz\n",
+    "visatoms = uc.copy()\n",
+    "visatoms = np.concatenate((visatoms,visatoms+np.array([0,0,1]),visatoms+np.array([0,1,0]),visatoms+np.array([0,0,1])))\n",
+    "visatoms = struc.lattice.cartesian(visatoms)\n",
+    "visspins = mstr.spinsFromAtoms(visatoms,fractional=False)\n",
+    "mstr.visualize(visatoms,visspins)\n",
+    "\n",
+    "print mstr.spins[0], (mstr.spins[0]).sum()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The refined spin direction is nearly perfectly perpendicular to the (111) direction, as expected."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Faster method: Use masking to avoid having to regenerate spins each iteration"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "### Make the magnetic structure\n",
+    "PDFguiFile = 'MnOpdfgui.ddp'\n",
+    "struc = getStrucFromPDFgui(PDFguiFile,1)\n",
+    "\n",
+    "th0, phi0 = np.arccos(np.random.uniform(-1,1)),np.random.uniform(-np.pi,np.pi)\n",
+    "svec = np.array([np.sin(th0)*np.cos(phi0),np.sin(th0)*np.sin(phi0),np.cos(th0)])\n",
+    "msp = MagSpecies(struc,magIdxs=[0,1,2,3],ffparamkey='Mn2',rmaxAtoms=50,basisvecs=svec,\n",
+    "                kvecs=np.array([0.5,0.5,0.5]),label=str(0))\n",
+    "\n",
+    "mstr=MagStructure()\n",
+    "mstr.loadSpecies(msp)\n",
+    "mstr.makeAll()\n",
+    "\n",
+    "\n",
+    "### Get the data and make the calculator\n",
+    "r,d = getDiffData(PDFguiFile)\n",
+    "\n",
+    "mc = MPDFcalculator(mstr)\n",
+    "mc.rmin = r.min()\n",
+    "mc.rmax = r.max()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "### Make the masks\n",
+    "upMask = (np.apply_along_axis(np.linalg.norm,1,mstr.spins-svec)<0.1)\n",
+    "downMask = ~upMask\n",
+    "print mstr.spins[upMask][:4]\n",
+    "print mstr.spins[downMask][:4]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "def residual(p,ydata):\n",
+    "    oscale,pscale,damp,th,phi = p\n",
+    "    newsvec = np.array([np.sin(th)*np.cos(phi),np.sin(th)*np.sin(phi),np.cos(th)])\n",
+    "    mstr.spins[upMask]=newsvec\n",
+    "    mstr.spins[downMask]=-newsvec\n",
+    "    mc.ordScale = oscale\n",
+    "    mc.paraScale = pscale\n",
+    "    mc.dampRate = damp\n",
+    "    return ydata - mc.calc(both=True)[2]\n",
+    "\n",
+    "p0 = [0.1,0.1,0.1,np.arccos(np.random.uniform(-1,1)),np.random.uniform(-np.pi,np.pi)]\n",
+    "optimized = least_squares(residual,p0,bounds=[[0,0,0,0,-np.pi],[10,10,10,np.pi,np.pi]],\n",
+    "                          args=(d,))\n",
+    "fit = mc.calc(both=True)[2]\n",
+    "\n",
+    "fig=plt.figure()\n",
+    "ax=fig.add_subplot(111)\n",
+    "ax.plot(r,d,'bo',linestyle='none')\n",
+    "ax.plot(r,fit,'r-',lw=2)\n",
+    "ax.set_xlabel('r ($\\AA$)')\n",
+    "ax.set_ylabel('D($\\AA^{-2}$)')\n",
+    "\n",
+    "plt.show()    \n",
+    "\n",
+    "print mstr.spins[0],(mstr.spins[0]).sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/cmi_scripts/mpdf/introTutorial.ipynb b/cmi_scripts/mpdf/introTutorial.ipynb
index cbe60b0..c4131da 100644
--- a/cmi_scripts/mpdf/introTutorial.ipynb
+++ b/cmi_scripts/mpdf/introTutorial.ipynb
@@ -95,7 +95,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Simple example: Calculating the mPDF from a spin dimer"
+    "## Simple example: Calculating the mPDF from a pair of spins"
    ]
   },
   {
@@ -109,7 +109,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -117,22 +117,32 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "from diffpy.mpdf import *\n",
+    "from diffpy.Structure import loadStructure\n",
     "\n",
     "### Set all plots to be inline\n",
-    "%matplotlib notebook\n",
-    "\n",
+    "%matplotlib notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
     "### Create a MagStructure object\n",
-    "mstr = MagStructure()\n",
+    "mstruc = MagStructure()\n",
     "\n",
     "### Create two atoms in the structure\n",
-    "mstr.atoms = np.array([[0,0,0],[4,0,0]])\n",
+    "mstruc.atoms = np.array([[0,0,0],[4,0,0]])\n",
     "\n",
     "### Create two spin vectors corresponding to the atoms. Let's make them antiferromagnetic.\n",
     "S=np.array([0,0,1])\n",
-    "mstr.spins = np.array([S,-S])\n",
+    "mstruc.spins = np.array([S,-S])\n",
     "\n",
     "### Create the MPDFcalculator object and load the magnetic structure into it\n",
-    "mc = MPDFcalculator(mstr)\n",
+    "mc = MPDFcalculator(mstruc)\n",
     "\n",
     "### Calculate and plot the mPDF!\n",
     "r,fr = mc.calc() # Use calc() if you want to extract the numerical results of the calculation\n",
@@ -157,13 +167,13 @@
    "outputs": [],
    "source": [
     "### make a copy of the magnetic structure\n",
-    "mstr2 = mstr.copy()\n",
+    "mstruc2 = mstruc.copy()\n",
     "\n",
     "### Set the spins to be ferromagnetic\n",
-    "mstr2.spins = np.array([S,S])\n",
+    "mstruc2.spins = np.array([S,S])\n",
     "\n",
     "### Create another mPDF calculator\n",
-    "mc2 = MPDFcalculator(mstr2)\n",
+    "mc2 = MPDFcalculator(mstruc2)\n",
     "\n",
     "### Calculate the mPDF\n",
     "r2, fr2 = mc2.calc()\n",
@@ -183,11 +193,22 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Creating a magnetic structure from a CIF file using diffpy.Structure"
+    "## Creating a magnetic structure from a CIF file using diffpy.Structure"
    ]
   },
   {
@@ -212,16 +233,22 @@
    },
    "outputs": [],
    "source": [
-    "### First we have to import the loadStructure function from diffpy.Structure\n",
-    "from diffpy.Structure import loadStructure\n",
-    "\n",
     "### Now let's create a diffpy.Structure object from a CIF file for MnO. This has all the atomic information,\n",
     "### but none of the magnetic information. Note that a .stru file generated from PDFgui or diffpy.Structure\n",
     "### would also work just as well.\n",
-    "mno = loadStructure('MnO_cubic.cif')\n",
-    "\n",
+    "mno = loadStructure('MnO_cubic.cif')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
     "### As a refresher, let's take a look at the mno structure object.\n",
-    "mno"
+    "print mno"
    ]
   },
   {
@@ -240,26 +267,26 @@
    "outputs": [],
    "source": [
     "### We will now create a MagSpecies object to extend the mno structure object.\n",
-    "mnoMag = MagSpecies()\n",
+    "mspec = MagSpecies()\n",
     "\n",
     "### Load the mno structure and give the magnetic species a label\n",
-    "mnoMag.struc = mno\n",
-    "mnoMag.label = 'Mn2+'\n",
+    "mspec.struc = mno\n",
+    "mspec.label = 'Mn2+'\n",
     "\n",
     "### Now we need to tell it which atoms in MnO are magnetic. From the printed list in the previous cell,\n",
     "### the magnetic Mn ions are the first four positions in the structure, so we provide the corresponding indices.\n",
-    "mnoMag.magIdxs = [0,1,2,3]\n",
+    "mspec.magIdxs = [0,1,2,3]\n",
     "\n",
     "### Now we provide the magnetic propagation and basis vectors, which are known from previous neutron\n",
     "### diffraction studies of MnO.\n",
     "k = np.array([0.5,0.5,0.5])\n",
     "s = np.array([1,-1,0]) # we won't worry about the magnitude of the basis vector for now\n",
-    "mnoMag.kvecs = np.array([k])\n",
-    "mnoMag.basisvecs = np.array([s])\n",
+    "mspec.kvecs = np.array([k])\n",
+    "mspec.basisvecs = np.array([s])\n",
     "\n",
     "### Now we provide information about the magnetic form factor. We tell the MagSpecies object the type of magnetic\n",
     "### ion, and it looks up magnetic form factor in a table.\n",
-    "mnoMag.ffparamkey = 'Mn2'"
+    "mspec.ffparamkey = 'Mn2'"
    ]
   },
   {
@@ -278,18 +305,40 @@
    "outputs": [],
    "source": [
     "### Now we can create a MagStructure object and load mnoMag into it.\n",
-    "mnoMagStruc = MagStructure()\n",
-    "mnoMagStruc.loadSpecies(mnoMag)\n",
-    "\n",
+    "mstruc = MagStructure()\n",
+    "mstruc.loadSpecies(mspec)\n",
     "### Now we will generate the atomic positions and spins. It is important to do the atoms first, since the\n",
     "### spins are generated by applying the propagation and basis vectors to the atomic positions. These methods\n",
     "### use the information contained in the atomic and magnetic structures to generate arrays of atomic positions\n",
     "### and spin vectors.\n",
-    "mnoMagStruc.makeAtoms()\n",
-    "mnoMagStruc.makeSpins()\n",
+    "mstruc.makeAtoms()\n",
+    "mstruc.makeSpins()\n",
     "\n",
     "### And we make the magnetic form factor:\n",
-    "mnoMagStruc.makeFF()"
+    "mstruc.makeFF()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### View the magnetic structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "uc = mno[:4].xyz\n",
+    "visatoms = uc.copy()\n",
+    "visatoms = np.concatenate((visatoms,visatoms+np.array([0,0,1]),visatoms+np.array([0,1,0]),visatoms+np.array([0,0,1])))\n",
+    "visatoms = mno.lattice.cartesian(visatoms)\n",
+    "visspins = mstruc.spinsFromAtoms(visatoms,fractional=False)\n",
+    "mstruc.visualize(visatoms,visspins)"
    ]
   },
   {
@@ -302,12 +351,23 @@
    "source": [
     "### Now we can create the mPDF calculator and load the magnetic structure\n",
     "mc = MPDFcalculator()\n",
-    "mc.magstruc = mnoMagStruc\n",
+    "mc.magstruc = mstruc\n",
     "\n",
-    "### Plot the mPDf\n",
+    "### Plot the mPDF\n",
     "mc.plot()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -338,10 +398,11 @@
     "mspec.latVecs = np.array([[a,0,0], [0,a,0], [0,0,a]])\n",
     "\n",
     "### Define the positions of the magnetic atoms in the unit cell (in fractional coordinates). Let's make\n",
-    "### a body-centered structure.\n",
+    "### We'll make a body-centered structure.\n",
     "mspec.atomBasis = np.array([[0,0,0], [0.5,0.5,0.5]])\n",
     "\n",
-    "### Define the magnetic moments in the same order as the list of atoms. Let's make an antiferromagnet.\n",
+    "### Define the magnetic moments in the same order as the list of atoms.\n",
+    "### Let's make an antiferromagnet.\n",
     "mspec.spinBasis = np.array([[0,0,1], [0,0,-1]])\n",
     "\n",
     "\n",
@@ -371,6 +432,17 @@
     "mc.plot()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -385,6 +457,13 @@
     "We will create a ferrimagnetic structure to illustrate the use of multiple magnetic species within a single magnetic structure. Let's build another antiferromagnetic body-centered cubic structure but with two different spin species, one with a large moment and one with a small moment."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make a magnetic species with a large moment"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -403,13 +482,46 @@
     "### Define the atomic position and magnetic moment.\n",
     "mspec1.atomBasis = np.array([0,0,0])\n",
     "mspec1.spinBasis = np.array([0,0,1])\n",
-    "mspec1.label = 'big' ### it is necessary to define unique identifying labels when you have multiple species\n",
-    "\n",
+    "mspec1.label = 'big' ### it is necessary to define unique identifying labels when you have multiple species"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make a magnetic species with a small moment"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
     "### Now make the other species, starting with mspec1 as a template\n",
     "mspec2 = mspec1.copy()\n",
     "mspec2.atomBasis = np.array([0.5,0.5,0.5])\n",
-    "mspec2.spinBasis = np.array([0,0,-0.5])\n",
-    "mspec2.label = 'small'\n",
+    "mspec2.spinBasis = np.array([0,0,-0.25])\n",
+    "mspec2.label = 'small'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Create and view the magnetic structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
     "### Create the magnetic structure object and load the species.\n",
     "mstruc = MagStructure()\n",
     "mstruc.loadSpecies(mspec1)\n",
@@ -422,6 +534,13 @@
     "mstruc.visualize(visAtoms, visSpins, showcrystalaxes=True, axesorigin=np.array([-1,-1,-1]))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Calculate the mPDF"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -446,11 +565,22 @@
     "mc.plot()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Creating more complex magnetic structures: One-dimensional spin helix"
+    "## Creating more complex magnetic structures: One-dimensional spin helix"
    ]
   },
   {
@@ -517,19 +647,31 @@
     "mc.plot()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Exploring some of the additional parameters in the mPDF"
+    "## Exploring some of the additional parameters in the mPDF"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we will take a look at some of the other mPDF parameters that can be adjusted, including:\n",
-    "- Qmin and Qmax to simulate experimental conditions.\n",
+    "Now we will take a look at some of the other aspects of the mPDF that can be adjusted, including:\n",
+    "- Whether the normalized mPDF, unnormalized mPDF, or both are calculated (see Acta A REF)\n",
+    "- Qmax to simulate experimental conditions.\n",
     "- Parameters that dampen and/or broaden the mPDF, simulating the effects of thermal motion and instrumental resolution.\n",
     "- \"Ordered\" scale factor corresponding to the magnitude of the locally ordered moment, and \"paramagnetic\" scale factor which depends only on the magnitude and spatial extent of a single localized moment, not any correlations between moments.\n",
     "- The r-range for the calculation.\n",
@@ -537,6 +679,13 @@
     "For this, we will create the antiferromagnetic MnO structure again."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Create the MnO magnetic structure"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -548,20 +697,58 @@
     "### Create the diffpy structure, MagSpecies, and MagStructure\n",
     "mno = loadStructure('MnO_cubic.cif')\n",
     "\n",
-    "mnoMag = MagSpecies(mno, magIdxs=[0,1,2,3], label='Mn2+', ffparamkey='Mn2')\n",
-    "mnoMag.kvecs = np.array([0.5,0.5,0.5])\n",
-    "mnoMag.basisvecs = np.array([1,-1,0])\n",
+    "mspec = MagSpecies(mno, magIdxs=[0,1,2,3], label='Mn2+', ffparamkey='Mn2')\n",
+    "mspec.kvecs = np.array([0.5,0.5,0.5])\n",
+    "mspec.basisvecs = np.array([1,-1,0])\n",
+    "\n",
+    "mstruc = MagStructure()\n",
+    "mstruc.loadSpecies(mspec)\n",
+    "mstruc.makeAll()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Calculate the normalized and unnormalized mPDFs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "mc = MPDFcalculator(mstruc)\n",
+    "r, fr = mc.calc() ### by default, just the normalized mPDF is calculated\n",
+    "r, dr = mc.calc(normalized=False) ### setting the normalized arg to False calculates the unnormalized mPDF\n",
+    "\n",
+    "### Let's compare the two quantities\n",
+    "\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
     "\n",
-    "mnoMagStruc = MagStructure()\n",
-    "mnoMagStruc.loadSpecies(mnoMag)\n",
-    "mnoMagStruc.makeAll()"
+    "ax.plot(r, fr/fr.max(), 'b-', label='Normalized')\n",
+    "ax.plot(r, dr/dr.max(), 'r-', label='Unnormalized')\n",
+    "\n",
+    "ax.set_xlabel(r'r ($\\AA$)')\n",
+    "ax.set_ylabel(r'f ($\\AA^{-2}$)')\n",
+    "\n",
+    "plt.legend(loc='best')\n",
+    "plt.tight_layout()\n",
+    "plt.show()\n",
+    "\n",
+    "### Or you can calculate them both together:\n",
+    "r, fr, dr = mc.calc(both=True)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Now we'll make the mPDF calculator along with several slightly modified copies so that we can compare them."
+    "### Model the effect of finite Qmax"
    ]
   },
   {
@@ -573,21 +760,19 @@
    "outputs": [],
    "source": [
     "### Default mPDF calculator\n",
-    "mc = MPDFcalculator(mnoMagStruc)\n",
-    "r, fr, dr = mc.calc(both=True)\n",
+    "mc = MPDFcalculator(mstruc)\n",
+    "r, fr = mc.calc()\n",
     "\n",
-    "### Adjust qmin and qmax to simulate termination ripples\n",
+    "### Adjust qmax to simulate termination ripples\n",
     "mcQ = mc.copy()\n",
-    "mcQ.qmin, mcQ.qmax = 0.1,25.0\n",
+    "mcQ.qmax = 25.0\n",
     "rq,frq = mcQ.calc()\n",
-    "sclfactor = fr.max()/frq.max()\n",
-    "frq *= sclfactor\n",
     "\n",
     "fig = plt.figure()\n",
     "ax = fig.add_subplot(111)\n",
     "\n",
     "ax.plot(r, fr, 'b-', label='Default')\n",
-    "ax.plot(rq, frq, 'r-', label='With qmin/qmax')\n",
+    "ax.plot(rq, frq, 'r-', label='With qmax')\n",
     "ax.plot(r, frq-fr-35, 'g-', label='Difference')\n",
     "\n",
     "ax.set_xlabel(r'r ($\\AA$)')\n",
@@ -597,6 +782,13 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Change the intrinisic mPDF peak width"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -606,23 +798,50 @@
    "outputs": [],
    "source": [
     "### Change the intrinsic mPDF peak width to simulate thermal motion\n",
-    "### and/or instrumental resolution effects.\n",
+    "### and/or instrumental limitations.\n",
     "mcB = mc.copy()\n",
-    "mcB.gaussPeakWidth = 0.2 # in Angstroms; default is 0.1\n",
+    "mcB.gaussPeakWidth = 0.15 # in Angstroms; default is 0.1\n",
     "rB, frB = mcB.calc()\n",
     "\n",
+    "fig = plt.figure()\n",
+    "ax = fig.add_subplot(111)\n",
+    "\n",
+    "ax.plot(r, fr, 'b-', label='Default')\n",
+    "ax.plot(rB, frB, 'r-', label='Broadened')\n",
+    "ax.plot(r,frB - fr - 35, 'g-', label='Difference')\n",
+    "ax.set_xlabel(r'r ($\\AA$)')\n",
+    "ax.set_ylabel(r'f ($\\AA^{-2}$)')\n",
+    "\n",
+    "plt.legend(loc='best')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Introduce a damping envelope"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
     "### Include a damping factor to simulate a finite correlation length\n",
     "### and/or instrumental resolution effects.\n",
     "mcD = mc.copy()\n",
-    "mcD.dampRate = 0.1 # in inverse Angstroms\n",
+    "mcD.dampRate = 0.075 # in inverse Angstroms\n",
     "rD, frD = mcD.calc()\n",
     "\n",
     "fig = plt.figure()\n",
     "ax = fig.add_subplot(111)\n",
     "\n",
     "ax.plot(r, fr, 'b-', label='Default')\n",
-    "ax.plot(rB, frB, 'r-', label='Broadened')\n",
-    "ax.plot(rD, frD, 'g-', label='Damped')\n",
+    "ax.plot(rD, frD, 'r-', label='Damped')\n",
     "ax.set_xlabel(r'r ($\\AA$)')\n",
     "ax.set_ylabel(r'f ($\\AA^{-2}$)')\n",
     "\n",
@@ -630,6 +849,13 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Change the ordered scale factor"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -638,8 +864,7 @@
    },
    "outputs": [],
    "source": [
-    "### Change the ordered scale factor relative to the paramagnetic scale factor, simulating\n",
-    "### a reduction in the size of the ordered moment relative to the total local moment.\n",
+    "### Reduce the ordered scale factor, simulating a reduced ordered moment.\n",
     "mcS = mc.copy()\n",
     "mcS.ordScale = 0.5*mc.ordScale\n",
     "rS, frS, drS = mcS.calc(both=True) # both the normalized and unnormalized mPDF\n",
@@ -656,6 +881,13 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Change the calculation range"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -687,6 +919,17 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -701,6 +944,32 @@
     "Here, we will provide an example of doing a very basic mPDF fit to actual experimental data taken on MnO. The initial structural PDF was refined using PDFgui, and now we use the residual of that structural fit as the dataset against which the mPDF will be refined. To keep things simple, we will just refine the scale factors here."
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Extract the refined atomic structure from the PDFgui file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "PDFguiFile = 'MnOpdfgui.ddp'\n",
+    "struc = getStrucFromPDFgui(PDFguiFile,1)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make the magneitc structure"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -709,67 +978,124 @@
    },
    "outputs": [],
    "source": [
-    "# Create the structure from our cif file, update the lattice according to the PDFgui fit.\n",
-    "structureFile = \"MnO_R-3m.cif\" # note we are not using the cubic structure now\n",
-    "mnostructure = loadStructure(structureFile)\n",
-    "lat = mnostructure.lattice\n",
-    "lat.a, lat.b, lat.c = 3.1505626, 3.1505626, 7.5936979 # these are the refined values from PDFgui\n",
-    "\n",
-    "### Create the Mn2+ magnetic species.\n",
-    "msp = MagSpecies(struc=mnostructure, label='Mn2+', ffparamkey='Mn2')\n",
-    "msp.magIdxs = [0,1,2] # these indices correspond to the Mn atoms in the rhombohedral unit cell\n",
-    "msp.basisvecs = 2.5*np.array([1,0,0]) # spin direction in coordinate system of rhombohedral structure\n",
-    "msp.kvecs = np.array([0,0,1.5]) # propagation vector in the rhombohedral structure\n",
+    "svec = np.array([1.0,-1.0,0.0])\n",
+    "msp = MagSpecies(struc,magIdxs=[0,1,2,3],ffparamkey='Mn2',rmaxAtoms=50,basisvecs=svec,\n",
+    "                kvecs=np.array([0.5,0.5,0.5]),label=str(0))\n",
     "\n",
-    "### Create and prep the magnetic structure.\n",
-    "mstr = MagStructure()\n",
+    "mstr=MagStructure()\n",
     "mstr.loadSpecies(msp)\n",
     "mstr.makeAll()\n",
     "\n",
-    "### Set up the mPDF calculator.\n",
-    "mc = MPDFcalculator(magstruc=mstr)\n",
-    "\n",
+    "### Visualize the magnetic structure\n",
+    "uc = struc[:4].xyz\n",
+    "visatoms = uc.copy()\n",
+    "visatoms = np.concatenate((visatoms,visatoms+np.array([0,0,1]),visatoms+np.array([0,1,0]),visatoms+np.array([0,0,1])))\n",
+    "visatoms = struc.lattice.cartesian(visatoms)\n",
+    "visspins = mstr.spinsFromAtoms(visatoms,fractional=False)\n",
+    "mstr.visualize(visatoms,visspins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Extract the mPDF data and make the MPDFcalculator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "r,d = getDiffData(PDFguiFile) ### extract the fit residual from the atomic PDF fit done in PDFgui\n",
     "\n",
-    "# Load the data\n",
-    "PDFfitFile = 'MnOfit_PDFgui.fgr'\n",
-    "rexp, Drexp = getDiffData([PDFfitFile])\n",
-    "mc.rmin = rexp.min()\n",
-    "mc.rmax = rexp.max()\n",
+    "mc = MPDFcalculator(mstr)\n",
+    "mc.rmin = r.min()\n",
+    "mc.rmax = r.max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Refine the magnetic structure (just scale factor and damping rate for now)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from scipy.optimize import least_squares\n",
     "\n",
-    "# Do the refinement\n",
-    "from scipy.optimize import leastsq\n",
+    "def residual(p,ydata):\n",
+    "    oscale,pscale,damp = p\n",
+    "    mc.ordScale = oscale\n",
+    "    mc.paraScale = pscale\n",
+    "    mc.dampRate = damp\n",
+    "    return ydata - mc.calc(both=True)[2]\n",
     "\n",
-    "def residual(p,yexp,mcalc):\n",
-    "    mcalc.paraScale,mcalc.ordScale=p\n",
-    "    return yexp-mcalc.calc(both=True)[2]\n",
+    "p0 = [0.1,0.1,0.1]\n",
+    "optimized = least_squares(residual,p0,bounds=[[0,0,0],[10,10,10]],args=(d,))\n",
+    "fit = mc.calc(both=True)[2]\n",
     "\n",
-    "p0 = [5.0,3.0] # initial parameter values; paraScale, ordScale\n",
-    "pOpt = leastsq(residual, p0, args=(Drexp,mc))\n",
-    "print pOpt\n",
+    "fig=plt.figure()\n",
+    "ax=fig.add_subplot(111)\n",
+    "ax.plot(r,d,'bo',linestyle='none')\n",
+    "ax.plot(r,fit,'r-',lw=2)\n",
+    "ax.set_xlabel('r ($\\AA$)')\n",
+    "ax.set_ylabel('D($\\AA^{-2}$)')\n",
     "\n",
-    "fit = mc.calc(both=True)[2]\n",
-    "mdiff = Drexp - fit\n",
+    "plt.show()    \n",
     "\n",
-    "### Plot the results.\n",
+    "print optimized.x"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot the atomic refinement along with the magnetic refinement"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from diffpy.pdfgui import tui ### useful library to interact with PDFgui projects\n",
+    "prj = tui.LoadProject(PDFguiFile)\n",
+    "fitObj = prj.getFits()[0]\n",
+    "dataSet = fitObj.getDataSet(0)\n",
+    "gobs = np.array(dataSet.Gobs)\n",
+    "robs = np.array(dataSet.robs)\n",
+    "mask = np.logical_and(robs>r.min()-0.001,robs<r.max()+0.001)\n",
+    "gobs = gobs[mask]\n",
+    "gcalc = np.array(dataSet.Gcalc)\n",
+    "mdiff = fit - d\n",
     "\n",
-    "# Grab full structural PDF data for plotting.\n",
-    "PDFdata = np.loadtxt(PDFfitFile,unpack=True,skiprows=12)\n",
-    "r, grcalc, gdiff = PDFdata[0], PDFdata[1], PDFdata[3]\n",
-    "gobs = gdiff + grcalc\n",
     "offset1 = 1.2*gobs.min()\n",
     "offset2 = offset1 - 8*mdiff.max()\n",
     "\n",
     "# Make the figure.\n",
     "fig = plt.figure()\n",
     "ax = fig.add_subplot(111)\n",
-    "mask = (r <= mc.rmax)\n",
-    "ax.plot(r[mask],gobs[mask],marker='o',mfc='none',mec='b',linestyle='none')\n",
-    "ax.plot(r[mask],grcalc[mask],'r-',lw=3)\n",
-    "ax.plot(r[mask],gdiff[mask]+offset1,marker='o',mfc='none',mec='b',linestyle='none')\n",
-    "ax.plot(rexp,fit+offset1,'r-',lw=3)\n",
-    "ax.plot(rexp,np.zeros_like(rexp)+offset2,'k:')\n",
-    "ax.plot(rexp,mdiff+offset2,'g-')\n",
-    "ax.set_xlim(xmin=mc.rmin,xmax=mc.rmax)\n",
+    "ax.plot(r,gobs,marker='o',mfc='none',mec='b',linestyle='none') ### total observed PDF pattern \n",
+    "ax.plot(r,gcalc,'r-',lw=2) ### calculated atomic PDF\n",
+    "ax.plot(r,d+offset1,marker='o',mfc='none',mec='b',linestyle='none') ### residual from atomic PDF fit\n",
+    "ax.plot(r,fit+offset1,'r-',lw=2) ### calculated mPDF\n",
+    "ax.plot(r,np.zeros_like(r)+offset2,'k:')\n",
+    "ax.plot(r,mdiff+offset2,'g-') ### overall fit residual after including atomic and magnetic PDFs\n",
+    "ax.set_xlim(xmin=0,xmax=mc.rmax)\n",
     "ax.set_xlabel('r ($\\AA$)')\n",
     "ax.set_ylabel('G, d ($\\AA^{-2}$)')\n",
     "\n",
@@ -780,14 +1106,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "In the plot above, the top set of curves gives the total experimental PDF (blue circles) with the refined structural PDF (red curve). The lower set of curves gives the structural PDF fit residual (blue circles), which contains the experimental mPDF, with the refined mPDF overlaid (red curve). The lower green curve gives the combined PDF+mPDF fit residual."
+    "### Compare the magnetic and nuclear scale factors to determine the moment size"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As an added bonus of collecting the nuclear and magnetic PDFs together, we can compare the overall scale factor for the nuclear PDF to the ordered scale factor for the mPDF to determine the size of the ordered moment. If we call $A$ the nuclear scale factor, $B$ the mPDF ordered scale factor, $n_s$ the fraction of atoms in the system that are magnetic, and $\\langle b \\rangle$ the average nuclear scattering length, then the magnitude of the refined moment $\\mathrm{S_{fit}}$ is related to the nominal magnitude of the spin vectors $\\mathrm{S_{nom}}$ used in the magnetic structure through the equation $\\mathrm{S_{fit}} = \\sqrt{\\frac{\\mathrm{B}\\langle b \\rangle ^2}{\\mathrm{A} n_s}} \\mathrm{S_{nom}}$. This is the spin quantum number, so the total magnitude of the magnetic moment is given by $g \\mu_{\\mathrm{B}} \\sqrt{\\mathrm{S_{fit}}(\\mathrm{S_{fit}}+1)}$. This is shown for the present case of MnO below."
+    "If we call $A$ the nuclear scale factor, $B$ the mPDF ordered scale factor, $n_s$ the fraction of atoms in the system that are magnetic, and $\\langle b \\rangle$ the average nuclear scattering length, then the magnitude of the refined moment $\\mathrm{S_{fit}}$ is related to the nominal magnitude of the spin vectors $\\mathrm{S_{nom}}$ used in the magnetic structure through the equation $\\mathrm{S_{fit}} = \\sqrt{\\frac{\\mathrm{B}\\langle b \\rangle ^2}{\\mathrm{A} n_s}} \\mathrm{S_{nom}}$. When multiplied by the g factor (e.g. 2 for pure spins without any orbital contributions to the moment), this gives the ordered moment in Bohr magnetons."
    ]
   },
   {
@@ -798,7 +1124,7 @@
    },
    "outputs": [],
    "source": [
-    "nucScale = 0.968 ### refined nuclear scale factor taken from PDFgui\n",
+    "nucScale = 0.9518 ### refined nuclear scale factor taken from PDFgui\n",
     "\n",
     "### calculate the average nuclear scattering length\n",
     "import periodictable as pt ### useful python package included in your installation of diffpy.mpdf\n",
@@ -821,7 +1147,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We expect S = 2.5 for Mn<sup>2+</sup> with a fully quenched orbital moment. Our refined value is quite close to the ideal value. Not bad!"
+    "This is fairly consistent with our expectation of S = 5/2 for Mn2+."
    ]
   },
   {

From abe740751778b1dcc15bf13a92bea1d6f7ef282e Mon Sep 17 00:00:00 2001
From: Benjamin Frandsen <benfrandsen@gmail.com>
Date: Fri, 27 Oct 2017 15:19:03 -0700
Subject: [PATCH 3/4] updated fit numbers in some of the tutorial materials for
 mPDF

---
 cmi_scripts/mpdf/MnOpdfgui.ddp                | Bin 1155484 -> 589134 bytes
 cmi_scripts/mpdf/example_corefinement.ipynb   |   2 +-
 .../mpdf/example_refineSpinDirection.ipynb    |  15 ++++++++++++---
 cmi_scripts/mpdf/introTutorial.ipynb          |   6 +++---
 4 files changed, 16 insertions(+), 7 deletions(-)

diff --git a/cmi_scripts/mpdf/MnOpdfgui.ddp b/cmi_scripts/mpdf/MnOpdfgui.ddp
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diff --git a/cmi_scripts/mpdf/example_corefinement.ipynb b/cmi_scripts/mpdf/example_corefinement.ipynb
index 88e0e19..d25c9e8 100644
--- a/cmi_scripts/mpdf/example_corefinement.ipynb
+++ b/cmi_scripts/mpdf/example_corefinement.ipynb
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "collapsed": true
    },
diff --git a/cmi_scripts/mpdf/example_refineSpinDirection.ipynb b/cmi_scripts/mpdf/example_refineSpinDirection.ipynb
index 799e95b..390ba43 100644
--- a/cmi_scripts/mpdf/example_refineSpinDirection.ipynb
+++ b/cmi_scripts/mpdf/example_refineSpinDirection.ipynb
@@ -45,7 +45,7 @@
    "source": [
     "### Make the magnetic structure\n",
     "PDFguiFile = 'MnOpdfgui.ddp'\n",
-    "struc = getStrucFromPDFgui(PDFguiFile,1)\n",
+    "struc = getStrucFromPDFgui(PDFguiFile,0)\n",
     "\n",
     "th0, phi0 = np.arccos(np.random.uniform(-1,1)),np.random.uniform(-np.pi,np.pi)\n",
     "svec = np.array([np.sin(th0)*np.cos(phi0),np.sin(th0)*np.sin(phi0),np.cos(th0)])\n",
@@ -149,13 +149,13 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
     "### Make the magnetic structure\n",
     "PDFguiFile = 'MnOpdfgui.ddp'\n",
-    "struc = getStrucFromPDFgui(PDFguiFile,1)\n",
+    "struc = getStrucFromPDFgui(PDFguiFile,0)\n",
     "\n",
     "th0, phi0 = np.arccos(np.random.uniform(-1,1)),np.random.uniform(-np.pi,np.pi)\n",
     "svec = np.array([np.sin(th0)*np.cos(phi0),np.sin(th0)*np.sin(phi0),np.cos(th0)])\n",
@@ -235,6 +235,15 @@
    "source": [
     "plt.close('all')"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/cmi_scripts/mpdf/introTutorial.ipynb b/cmi_scripts/mpdf/introTutorial.ipynb
index c4131da..b7de586 100644
--- a/cmi_scripts/mpdf/introTutorial.ipynb
+++ b/cmi_scripts/mpdf/introTutorial.ipynb
@@ -955,12 +955,12 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": false
    },
    "outputs": [],
    "source": [
     "PDFguiFile = 'MnOpdfgui.ddp'\n",
-    "struc = getStrucFromPDFgui(PDFguiFile,1)"
+    "struc = getStrucFromPDFgui(PDFguiFile,0)"
    ]
   },
   {
@@ -1010,7 +1010,7 @@
    },
    "outputs": [],
    "source": [
-    "r,d = getDiffData(PDFguiFile) ### extract the fit residual from the atomic PDF fit done in PDFgui\n",
+    "r,d = getDiffData(PDFguiFile, 0) ### extract the fit residual from the atomic PDF fit done in PDFgui\n",
     "\n",
     "mc = MPDFcalculator(mstr)\n",
     "mc.rmin = r.min()\n",

From fb5d5b0f4386b069084031523656e10f628bf769 Mon Sep 17 00:00:00 2001
From: Benjamin Frandsen <benfrandsen@gmail.com>
Date: Tue, 18 Sep 2018 15:22:05 -0600
Subject: [PATCH 4/4] Updated introTutorial to use the SrFit infrastructure for
 the example fit

---
 cmi_scripts/mpdf/example_SrFit.ipynb      | 5577 +++++++++++++++++++++
 cmi_scripts/mpdf/example_corefinement2.py |   50 +-
 cmi_scripts/mpdf/introTutorial.ipynb      | 3693 +++++++++++++-
 3 files changed, 9196 insertions(+), 124 deletions(-)
 create mode 100644 cmi_scripts/mpdf/example_SrFit.ipynb

diff --git a/cmi_scripts/mpdf/example_SrFit.ipynb b/cmi_scripts/mpdf/example_SrFit.ipynb
new file mode 100644
index 0000000..1225f7b
--- /dev/null
+++ b/cmi_scripts/mpdf/example_SrFit.ipynb
@@ -0,0 +1,5577 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "### Import the necessary libraries\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "from diffpy.mpdf import *\n",
+    "from diffpy.Structure import loadStructure\n",
+    "\n",
+    "### Set all plots to be inline\n",
+    "%matplotlib notebook"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Perform a simple mPDF fit to MnO"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load the data into a Profile object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "PDFguiFile = 'MnOpdfgui.ddp'\n",
+    "r,d = getDiffData(PDFguiFile, 0) ### extract the fit residual from the atomic PDF fit done in PDFgui\n",
+    "\n",
+    "from diffpy.srfit.fitbase import Profile\n",
+    "\n",
+    "profile = Profile()\n",
+    "profile.setObservedProfile(r, d)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make the magnetic structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/ben/anaconda/envs/mpdfdev/lib/python2.7/site-packages/diffpy.Structure-1.3.2-py2.7.egg/diffpy/Structure/lattice.py:125: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n",
+      "  if [a, b, c, alpha, beta, gamma, base] == 7*[None]:\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",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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Aji051d9dEYA1SEecg8o0+b5/9dpwHV986699toiMAMzsGaDAC644IKFtlGzoQFcZ511iohjrYYGcObMmW7ttddu9Aipu+uTPCF7pEnBzw+ixxckBr85iNPrr79epIFBawshxHwPuUnVIE2U1EtJzsK+vfDCCw73g0mTJqXq9jvuA76Mg/RDyy23XPF3CyxRg3vI3dgI4JCb0rwDMgKYF+/B8rRO2jzxb2ID/sc//jFXW6bpm3f99dcXudiWXXZZVfgw90FoVlttNdXnXH755W78+PGqBPDee+91ELRYAkjdYMqrhRo9iB+yADGG5GEi978LqeManid5ACHTyAR/hxBSuxeSg5ZLvigVV7dpaOfKCCAl7TbZZJO63Yz6HHIHJsh4GFjiE0ILLImCs1UXGQFs1XSnH6wRwPSYDqY71tXmPfPMM+7BBx9U1Y4IjhDAMWPGzNWQaOGLJgat1VAmgJC0MpIH+YNglJE8yF+vKNaQAGI65V6SU/G1114riKB88TzIpE8I0SDGthzaueeff95BpDfeeOPYbtW6DrKMNhgZD5sFltSCtDUfMgLYmqnWGagRQB1c++muvjbPT4zsJ0eu6psHAWRz1HTCFwyp+Yr5t2yDTIkzpAWt1Oqrr57ytu+41xVXXFFo5hZffHGV5zCXmC7RuvEMtHhiwsVvD6Ilmjyf8KH9rBuI0IsAhgPFROwTQvpHX3xCCBnv1HIQQKqA3HfffeoEkOCjJZZYIvqA0y2wxNcSWoJqlderr25qBLCvpmPwdcYI4OCbs049rqvNq+Obh/kX85hmHjafABIAgolMs0EAMVmuscYamo9xqQggBB5NWpl/HiZdxoL/XajVa2J67SZ7vgkYLCGZK664YhSWEFOfEKKlRPPoE0IIqjS0c/g5appnn332WUd5wIkTJ0aNoe5FpB9aaqmlars4+IEl9EHM8BBA5lpyEVpgSd0Z6t/PGQHs37kZFD0zAjgopmluJ2Wx5z/8fGP8jMbn6aefLjZd0ehp+eahHWGT16zEIIOm5iv1eVdYYQXVySJ1CZtkDgK41lprFVqfmEYwRxnJg/wxvxKE4fvnPfHEEw4SGOsDGNOPbteEGkAJbIglgOG9IZP4maLpgxgSXAIBhNBKAu1HHnlEVTsHAcTN4f3vf39TeLp+npJ2aLhTBTl18iMEUw4FyIuQwroaX1VA7ObRCBgBjIbKLixDwAhgf8pFHW0eGyblsbbaaqvaprxYNNDA4Lu05ZZbxn6k9nVskJgy65KJ2AdjNmVDfN/73hf7kVrXXXnllW7NNdechwAy32VpVSB++M+hySnzzyPZctkmXjUIpNZAvA+lJoBhfyDBPiEkSTPjJspYtISdsKg7NrTcDz/8sJswYULdW0R9jgMOEcBaaY5kLUEmIH74ZXZKUN3L1zNqQHZRNgSMAGaDemg+yAjgwM1rSPLCHGHSs1htHpsi/nJbb721+qDQzGC6gmxqt1w1eiGANMiZVmMuMQGz4bMZY+qUoAxIDlqu0D+P3yGAVbQ1/UAAqaqipbXFB/X+++8vSBOyiOyDEWRQtISYkKtgFs45z3j00UfdRhttpCUOxX1vuummwr1BO9E58o1fpeRm9H2A6QdYiQ+h5CM0P0LVqW98cyOAjSFs9w2MAOrOf6d0Khp58yAS5MzbdtttdQflXKGNQXPxgQ98QP1ZqWv0zpg5y90xdZrbcIV5K3Hg08imiHm2acP86gdfiAkXsy3PgOiRG88ne2j4UuXKG2gCSGoTxqdFAEP/PPCGBGIuFkIImfEJIfhWIYS4Uzz22GPqBJBDG9pt/AA1W7fqLOHhUzSEEEBkki/wNEKoOUPV720EsDpm9gkPASOAacShkzaPTYkNnxxotFhtXp1eQTKuvvpqt91229X5eKXPMK4bbrjBbbPNNpU+V+dioiTBL1WN3t1Pudld//ALbs9NVnCHbP92xG+d8mmYbcv88/DHZMMM8+bxOyZtzMz4NWo1CCB9GzdunNYj5rlvaALOQQC7+efxzgkhhBRyYIHUiLkYLSFz0Y0QPvXUUw5fyg033FAVQ94jtHKa8sAAwtQ83QZlgSWqU57s5kYAk0HZzhsZAYyf9yraPInEw0xFygvZiKtoIOJ7NudKSAdJhqdMmVJJ01H1OVyfU9uYskQb2r9Jx17h/vnazGLYay69sPvV5zdyC80/sogqLauewVzih1eWPw+ShVmtzD+P/y+b76uuuqpINaOp8SF9iS93dea4ymfKCKAkN65yn9hr8c976KGHogM0IIRSpUSijZkbtJSiJYQQ+j5wTz75pONrgw02iO1WrevIc7nqqqtGBwXVeohzRV3julrZMLBE5DrUEFqkcd3Zqfc5I4D1cLNPvYWAEcB3ikJK3zzSSKAhovSXdmPDv/TSSwsNoLYzd05tIxsXDv6pSrS99sZMt/upt7jbHn+pmJIFR41wp+6xgVvglaeKtCpEY/paPX6GQNCHUKMH8auaVgUtLcmmjQDWfyOaBmjwjoeEkP/zCSHzjhl4/fXXr9/RiE9ed911xYFAszQg3eAgheYzRTqlsjWyU2CJ/H8EFHZJRQSMAFYEzC6fF4G2EsAYbZ5o8eQ7yPkanRhtHloKzE/rrbeeuuihjbrkkksKH0BO4poNokQww/bbb6/5mOLeqSt0kA6Dzf1/Ln3Q/frW5+f2/0PLv+mmLO8Kc7Ov0ZM0K6lIdRsIYEqyUSZgBGiQBiZVhC7vOBpePxch2mDeIwgTWkKCWjTeK/x2cQmAnGm2qgmnq/YFDCWwhMAtSC0HprISdjFrZ9Xnt/F6I4BtnPWEYx7qBLAsnQoLO5u5kEDg1PLNY5MiZ562GYkxMK6LLrqoiAKuqpWqKlKYRC+77LIs5uY6FTqYTzSiZf55/D/VMCB2D70y0v33VS+619+cXUCw1hIj3Rn7bO5GjRxeFZLo66+55prC5KcZ9TnQJuAcBFAzQhf54fCGphE5gRjyfkECxY8QbWEKQog8EHgk+Q2jBanihZAyZE67pjbdwhUF30kisYUUWmBJxQmLuNwIYARIdklnBIY6AWTRlgoFoMBCzua0xRZbVNbm1ZEjoggxI2mnkqBvLLQXXHBBkZqlWxmtOuMIP5PT3NwtQbMkwC7zz2PufbOtr9Xz686+9OoMt+vJN7kH/jG9GOZ73jXS/XqvjdyqSy6cAqp33KMtBLBTfdsUoOaI0H388ceLw9u6665bHBDxsZXE1KwjaNxDQlgnihuNMD7CEErNljrhdLe+cjgkgTYEUFpZmitIofkR1p91I4D1sbNPztF8zVF9DNFGeggIoDT8fnLlyuOZRBHypV1NgGcxleeff36RnNkvm6UxtWJuJgq4zqZXpU/kL2Ns5M4LffP4nU2EjabMP6+Khubff3mdO/e+l4uuDR/m3GEfep/bdcKYKl2NuhYCSESzVuJfOtEPGkBNApgjQpfDG4SvzH9XAoMk7QzfORQhg5KHEEIXo4knKIhnQCY1W658g2CDL/KkSZO6rkPdAkvKzMaa2AzWexsBHKwz1yf9HuoEEA2RTwBzRq8yxUQRapes8kUJAkh9Xv/krSFqGuZmNoQwrQoEj01YatuWpVVJVQGCtCIX3fOs+8FN/3RvvGUS3vp9S7of7jI+aVANPl+k/RjKBBB/M6q3jBmTnkAjz7kIIMRu/PjxUa8QbhE+IURj6BNCTLxlhJDKMPgIS6qoqIfVuChXvkHWXDSAm266aSVLhOgi/BKXFljSfaKNANZ4EewjbyPQNgKYM1UKKGOqIhKY03COduGFF7pNNtmk2Hg0G4SMZ5EI2jenxjxTzGll/nmQdbSXvrmWsnNoBDCTaTqPS8DOMqu8z+3ysxvdk9NeL4Yz+t3zu99+cYJbetEFYobX8xojgD0h6nlBjhQt+BiSS7BuLkU0gn5QCfKOXPvJqXl3CKbCR1j7nSXfIJrn2BrUPSehwwUcDhkTB9EYDWi35/iBJRKM51cskZrGbU1QbQSwrpTa5woE2kYAc/qugS9O5OSXmzx5chaJIwhk4sSJ6toE8TfsZm6GJBItXOafx2Lum219whealHNVtYAAsmGT9oPx7f+7v7nz7nqmmLeRw4e54z4xzm2/9mj3kysfcrc8Os2d+Ol6kd0QQOqxkm5Gqw20CVg74hQCiBZQM0ULmntcRuoSwHBu0W77hJD3gneAd4SgIDTCmr67pJsh/RCaWc3GIQ6tJn7WVVwwYvoU+hFCBsmyAG6Y3KWEXVvyERoBjJEau6YjAm0jgCxOF198cVHBQtt3DdBxIieKdfPNN88ihaSBIfpO26Fc/A1Z5MGxjOSxsbEQlyVJZuOLTauSi8w8/PDDhbnZJxW/v+UJ9+0/3e3esgi7Sass5q558IViLnffeHn3jQ+uUXle2Ygp/WUEsDJ0cz8wdepU9Rx9yANau7XXXrt+R7t8krUIQkieS94RnoU7g1+tJKUvLwePNdZYQz3fIIdsAls4HMa+43UBZh2SBNcS3dymwBIjgHUlxz7XCg2g+JXJdOeMlOWZEAq0ISyGORq+N0Qtps4pJk7vvtkWJ3lMPGxkUg0jJHudqmFUwYJqKpjuY32xqtzbv7ZTyp6Hn3vF7fqzm9wL0+cEE40aMczNeIsRHrnTmu4TGyxX6ZEQQGrkaqbjyEWaZeDIh0TbswFTv5nSZgTuaDQIILkANfNrohFG7lLUhu6GAYc23DZ4l3wNIdpH3h8hhHxv4u8KKYPMaqebATPIJtkINF02BFNf2xwGlnCNEMKhGFhiBFBjdWnRPYe6BjAkgL7misVUu2GeuPnmmwtfuRyN/FsQpbpVBSDIvtnWJ3yYdNHcCclDQ8Kz2Oib+vp0wyZXNRUI4LPPPlta+3Xmm7PcF395q7vmwbcTR8/ZXJw7/fMbufVXeE/09FL6i+TC2gSQoARt0jxQBJDIetwrNAkgQUFos9Zcc83oua16oUTMlgVM4EvH+iGkEH9EfAZ9Qsj7GEuyiDZGHrStA6wf+BvmOvR2y2841ANLjABWfePs+nkQaBsBZPDkyiMoQ9vpmmdximfDx+Sco+F7w4bVy9GbzaUsCIPFmw1Fql+AkUTestn4Pj25/A3ZiMERzaZmw+kfUoEJvVM7+eqH3bEX3O/83Ekkjb5ov0lu9CJxQSJtIYCUutMiuRBAyLqmTCB3+O1RpUOrScQsPsK9gqk4gIWEEPcLnxDy3nYihLmijXEH4dCLe0iOxrPQNMdG1XcLLPG1hIMhsMQIYA4JG8LPaCMBxAeQElLaebcQm5w1c3meX2ZMtJ+hfx6/o9lAayfkzjfdxpqZcuGYq5xebNLu0655xB174f3ujVlv08DFFpzPXXHAZlEVRCCApEfRMo8iB9pmc8iIHCCQJ778tCcQNHwctQign6RZa3lG88xBCb85rQaOaO3rRMzyWQ5GkpwacgiB8Qkh77cQQqnOoX3wRVOJWZYx5WiktyGoCktEneYHlvB5iTY+/vjjiwCgT37yk3Vum+UzRgCzwDx0H9JGAkiSUhz9tX1hkJocaWdYsNDcsSETcAKZkw2aDQxH8rL8eb00Dr2kHt8l0ldo41gWnNGrb3X+DqkgurRXfdmP/Pg69/en5ySM9tvKiy/oztu3d7ofzGOQv8FAAMuIHmQPeUP7JAcHqfkKIcFkyXfki00Zf1S+UroJMFekBypL0lxn7ss+A4lm/JoEUFKmECTWNCgNbWJICCF/QgghtMi2NgGEiFK/G7N2jsaBiijqXlaP2L4IIfzUpz5VWG6+9rWvxX40+3VGALNDPrQeONQJILOFtstvTf3kqkhAyrQz/mYM2fNNuPSJzZjnsdliDmGhx2zbdGPpNF6tgJPwebnqKUMqCC7oVbVl91Nudjc88oIrq6GzwmILuAv/vXvKHwggmjGtJMngV1UDiGyJphgSIbIlRE9cAfzvfoCP72sL6cAsJ9onNFTcT5IiS6WMJnLZrUpHlfez27UE0jCu1VdfPdUt33EfzZQpEELmVJJTk5Eg1BCSfDp1pEiqlU8AACAASURBVC7zTfWeXLlPtaKbd9ppp0L7t88++6jNf9MbGwFsimDLP99GAogzNKf6uiaDKiJTJ+2MXw1DNmU2ULSJvtYlNNuykOfQLsn4IdKYSLTzisX45lWZk07XVinbN2PmLPeL6x91v715qnv4uTk1hGlLLDyfu/rr3X2fMFlhHh0IAuj7forpVsy3yFYvotcJu5AA4pjPIURS3SDTEAP5IkAF8iFkEC1VlZxxEMAqVTrqyAf5JyGz5M7TauDCeqSdMkWCTfCZhNRLYAnEn6AQSU6NW0xTQgjRhDxvvPHGWrDNc1+tWspTpkxxe++9t9tzzz2zjKPOQ4wA1kHNPjMXgTYQQBZZiQZj4NRixWQwevRodUnoVDHDr4YRBmNIWpUy/7xeaVVykAsBjWz/pMhIZXrpNBmxvnlNJxPtH88ikXaV9vJrM93/XHK/O/OvT7qbDtmi5waaY44gL2jykHHfV49DhPh++mSPw0Qv2eqGSUgAb7nlloL8dcp1CAH0CSHvKORDzMWQkm5EhEMBpkbNKGcwpA9jx46tIg6VrpWcedopU8rKszFnyIaQQSm5yDz4hLAKMWfwBOcQQNNLk14JqC4XE9wCsU3t0w0p/4//+A+3yy67pOpq8vsYAUwOabtu2EYCmCMRr0iREECIkmj2xHzLokzARZl/Xl3zGKY3NJvkmdNuuTSpsb55TccLAYRYaGsuIIBox0gF07Sh0fM1efIzBAvyApEKtXr45sWmDontX1UC6N9Xckz6hJBx0XchhKGpsmmZtphxUcGH95DDolaTnHnaaaJigk3El9gnhBxGhRBCCqXaRjc8yM/I/Gy00UZasM1zX63gFg6CRx11lMMU3K/NCGC/zswg6VcbCaCGBoaFsiytCgs8CyubMJuYT/aqVMOIFSdMb2yaRMVpNz/iWPNZmGYhgVU1c1X7RAAIASck5dVsN910U6GZq0IAffnyCR9ED0IXavPQwnDg0NSQhSSO59Egl700gN3wFSIihBBCwmHJr6FLAAg4pCrTVtafe+65p9CWahJAzLEEMaAB1Gzia1gl2ESsFH5yajSWrGN+pHF4WKVEH+9st3RKKcdKUB9rA+tpqsbYyTF50kknuW233TbVbZPfxwhgckjbdcM2EsC6WjIWBRZA3y9Pfub/2Yh9vzz5GRNFrryDVGDglL7yyiurCzKmdIrLx+bfqtuhuqbZqs9j4yLlTA4CSI68Mi0tG3WZRk/kq8xHryyamyAQyIVmlGwvAkigSwrZ4L3zgxkghvwf5AwMOfB0y39XVQ7kegIZMIsj41qNQyMHUu2kyal8DTnQ+oSQ30NCyOFDu06zzIf4NrK+piybx33J/3jGGWdkS2dTR8aMANZBzT4zF4E2EEA2VTQI0nppyaQaRhhpyyaEKaXMbMsG1CmtSq58eYzv9ttvLzZDTa2F4JjLlJ5LM8emhe+SdvQiBxAqtaBFCckeRA/S4Sfglp+rpO0ZaAJYNTlvlSWZ9xP/PKmMASHBT03MxXyPzWXZ7bl33XVXcR/Nw1SupMloijmwpfY1RF4lDyHzwKFDfEnxnUTGq8htFTngWjFtxyTSrnJvCCBWlPPPP79nWqgq9019rRHA1Ii27H5tJIBCklZcccXCbBuabsNqGKFWr6pTdM68g+TfYgHWjFyUVyRHRQuelUsz9/TTTztypaUkgGhefJKHrLFhQmJ8oucTvhQbZq7yeb4mxjcBaxJAnunX6QVLyKCYjPkZ7aCYjIUQVl3aJaempjsFgTpo7bWTJufyNUQGOHwIKUfeWT99kzFyn6rVMW3HPBsCSAATWRWon9yvzQhgv87MIOlXGwggixCbgphrIRScHHE0Z6Pwy54J2UuhQRARyJl3kE2LMWnmLpNx5chnx7M0iFnZ64nzOukr6iSwDYmekD7+H9OUnzAZ/yhMwJqmxTYQQLRaZXV6pWSaaKZ49yEdvoYwhoTwLkHMOShqNfrGgRQNlmbLWZ/XD9BB/onWlrngvcBXzyeETUy3EkWdOo0OhwrkhfUghzWl7twbAayLnH2uQKANBBBNFSdS2YRlQ2Dz0IiIDEUrtj5vCpHEbwknfM36pdLPOsEMdcYIMcPkp71JUgeYyM9Oz/FL64VJk4XohT56yFxYAYMACXInahKLgSaAyAZBLlqpljDVs/mXEcBQxjjoCQmBiKB1g4QIIexkpkSbTgSsZkR9rqoZuUzNYE8gFYSTzAdhQ2Mn9YyZC/oFGfcDfCCEsVHqWppNDhcc0vA/7pTKqM5alvozRgBTI9qy+7WBAIZ5ANnk0RKULVAa058rWpa+5xwbZj5yAGoSGcbUi5ilmjOeQ+QnBLCTRo8NjA0Kx3dfqwfxi03dAwHEB1DTtNgGAsgc1TnoMIdSHcOvUuKTEEj7HXfcUQRUaRJA+oGvYUq3g7L3AdKL7zNRwNqtDjmX+ZASgv5cdLPGaAXRIBesa0Sbc1Do12YEsF9nZpD0qw0EEA0AhE8aan20B5opJPzpp1QRjuQpIiJ7iRWaMja4HH4rvYJpevU19u9EFbJJpt68/KhuNBFUMJByWWAowT5hipVYotdpfDlwG+oEkPExR3UIYDgvEEmfEKK9guCzbrD5E8zQdM47yQJEg0OHduR5LlMz42RuwK5ODWUx38t8+P6cQgrR3oqGUIvYEnhG/9EwNjFRx65xda8zAlgXOftcgUAbCWDuzTFXsATzWbUGbJPXIFfKGUgZ5rgttuheYq3TWEKi5wdlsFEJ0SO4hxM/+cvQ7mlt+m0hgGjOMKNptCYko1d/JLKVZ0BI+PKrlPBz1UCwTs9E3ji0aScfh1Dh01jHv7UXXuHfOWDTUgSigT0kUFLPYD726xnzjrLmpQ6iQYvJOsDhoGlpvKr4VbneCGAVtOzadyDQRgKIjwon7/XXXz+LRGgknu7UcRYuTsWURtJut912W+Ekr+0kzSaJo3yvXGlSUUL880Kih+agzEdPNvOmRDMWbwgg2gzN9CK5DzlhJRBkHhOaFgFk04cc1NEyxc4T8o2LA+b6sEpJSAjrkgRkjrFoJzmn//gHa5uawRY3FN4pjRJ6EvHt5yLk/5gn0RDyjsf6EHaSBbCiOgvks+7cxspZk+uMADZBzz7bSg0gUWr4e+XKVF838XQd8SQ9BqdksthrN0gZpEpjoff7zuaFtlGqJfhEL8yjBynoRfS6aWNiiGZTXHNoTttAANn4NaPdmScILAmtpfnl0oQU0o+wbF0sAWEd4p3VrpsL0UQzp61pBKccCbRlPnAPgXCOGTNmrpaQv/lRxmEZwZj3Fz/dj3/848U+ETuXMfdNfY0RwNSItux+bdQA5qotK6KUw+Qnz3rkkUcKP7YNNthAXZK1cw5KKSrSwKAlwYdSCB+brk/0MNmy0PN/dc1zbOhofXppGpsC2xYCSJALdak1GmQG+dAkgLy3RDH7BDAcC32Q3I6S6kQIiEQZd6tSQoQ77+yECRM0YJp7T4gShwJtTSMPxF+X91AzyEkGFhJoqRrjJ6fm/yDoQgrR3vbS6hG494UvfME99thjRgBVJbPZzYc1+7h9ug0EUHL+yWwT2o8WMMdpmGdCKiAnmnnfZGwsWBCmHIXY8SnCB6epGU6IXqjNY2OF6OGETVoG8PMTJvdaxKu+3aGmsernY6/PIQ/9oAHUJoDgncLPrNO81alnjCzjgiHaQbTxyKmflNoPYuBd5Z3Vfl8hSri+aBNNsORgyHqnnR2AZ/XCzyfoYjZmPwgJYXhovOSSS9wBBxxQaE1NAxi7suW/zghgQ8zbSABzJRaWqSGdBIEG2qZSnpdTu8lJn80tNhKzE9GD+PE3v+KKpFnh//g7Sae32WabhtLe/eNsEGh9xNSs9bBcBBDccviCglPoA8h84eOopQEkcIKNWZMApqhmwgEmJIQcmkQ7SBBSDneUXkQppayz3kF4yQOp3YjW5SvW4hGa8HnniSYXn076zZpz0UUXuSOOOKIgs/3czATcz7MzCPrWRgKYK6+cTH/O6hxoN9Eo5DD1kL6CBTVMxiuLbFgCLSR6fkAGWpFOGj02UOoOb7vttqpvFNoaNn2cvzVbjuAZNIBDnQAiL5qHKmQB37KUyawlqtXXEEJkcW8QLaFG2hGqH1GBJoffswTPLLfccpqvUXFvxsR6XtfnWQ6lfhqgz33uc4WGEGL4ox/9qIichiD2YzMC2I+zMoj61EYCmCvaU8QgZ3WOXHVzGRsEkJQZvm+eROCysELwwmTJ3Yhep9eGe1LIfrvttlN9s4j4I3p16623Vn2O1KLWjJ7OGQ3eSQOIyZ7oTI2G4z+aNE0MqWaimcpGNPYc2iTSWKqU+CbjFLWheQZawByZD2J8J1PJBIddyPQ666yT5JZobNEun3TSSe4vf/lLYbnBR5ND4QUXXJDkGSlvYgQwJZotvFcbCCAvNac5ablMffK8nNU5NMzb4Edy3LD8mWj0MNeG6VVYOFP56OELeNVVV7kpU6aovqEQwBymZiOAzacxBwHUTmUjGiwCNMRUj0nY10bxjnGI8svWhaUFY9BsqimLeYZck8J0Hvs8v+5w7GdirvvZz37mzj333IL0QTIJQtN2DYnpV3iNEcA6qNln5iLQRgKYS9MjIOesPNLEvO0TvdB8i5kq1OihSWXDSnX67vRaQj6vuOIKt/3226u+uWhfSNqt7WuYwyc0twYQ0yZEHW0VxB8c0c5paQDRPvMszcAqbT9G0QCS57LTO9SpSokQQkyVMQnL8Q3u9pyUL1YOzan0lxQ6VOtIXdYT0y+RwGeffXZKaErvBTk/6KCDCsLJWodbwymnnBIVGGQEUH16hvYD2kgAc5kURXJyRmRCyvA57FY2DaLHZs0XpIfvot0Tolem0Quj4XL5mREBfNlllxUaQM2IPDCgbJ+2r+FgJoDiM4XcgJd8R4b42/zzz1+YMyEbEECt8oc5cs1pk1jWB7RLaPzGjx8ftdFIlRLxIeR3NPA+ISxLg4SmDB/X2OdEdabDRTmIs7+2pioJ6A/nuOOOK9LZ/Pa3v20CRc/PSkECtIv77LNPETSFwoB3J8a9wQhgT4jtgm4ItJEAcmK8/PLL1QmFf0rNlZyZjReCQdk0IXphehVOmWhpQv88SF+3wuuhHOVKOi0EEB/AVGblsnci18Egdf7EU695xO2+8fLzYNNUA+iXzxOS5+dglLyLyIxEbIMp2nU2NTROyB9/h5xACvFrq5ujMZwvCCDBEprVVCCAaGMWX3xxtU2kqQmTtcw3GaMx9JNSS847/NiYxxz1z3PgJhOCaVYjITgRwPhTn3baaWpzz40PPvjgQtN45ZVX1nqOEcBasNmHBIE2EkBOzZdeemkRVKBJKARj8m9BzGJTFVSVTsxv4qOHPxFpESByQvTKyp9VIXqd+pOrpB6bGnm50MylIhBlY8rla5iSAB7xl3vcL65/3C29yPzut1+c4EYvskAxtCoEEHz9Q4IQPjQrkmzb9/OE/IXvTZgGBhIgiYCRfUgh7x3kBDLIF/esq9FFO4MMaxJAIs9JNE1ftRrvEHK39tprN36EaGf9snWsDRBv/gbWmJq11zy06KSGgvhrNwI2NKLBv/nNbxa5RwkG0WyYrrFscGBCKUHk9L/+67+6L37xi1GPNQIYBZNd1AmBNhBAf3MCB/zWyPNEtGcdh+qq0sQpn4z/TZO9ip9VmUYPYgTRwwQHCSTaj9/RktTdZHuNE60Cz9JOLSEEEN+8GH+nXv3u9HcIMydx7WCTlATwa7+/w51zx9PFkOYbMcx9/xPj3bZrLVVKAJF7Mfv75luIGXLjkzz5OZZwhwQQ8kSOPtGe+eRECCF9FtMlJKvKoSRHtQmIDEnONQmglg8b2PpJkPEzQ1sYJqVOUTc3fJ/QaKFphOxrNy1XgAMPPLCQx+OPP151CJLy52tf+5r75Cc/WWQh2G+//dyJJ57o9thjj57PNgLYEyK7oBsCbSSAmAyI7sLvgo1Pu7H48hVb77Mb0YMA+Ro9MeMK0csVyABmqYhtL/xzEXZxDdAONkmdF/KMmx53//nne9ys2XOQ3HmDZd1uqw8rTIMQMDkwQHA58IjZ1v/e9CDUiwCGcywVM4QM0leCOkQ7CDHslv4EDJF9zXJjpB4ix6WmJgtNLQQ8zKXZ652o+nf8ddHoomESDSGYczgUEs53v0pJ1WfI9RyiiGrOkTtP6yDwla98xS2zzDLu6KOPrgtD1OeQcRQDyJq0fffdtyCCHEB6NSOAvRCyv3dFoI0EkM3n/PPPL/zkOOVpN0yyaMvC0nMQvbLyZ2zUIdET0gdh7abRQ8PDCVw7Zx6Y5ao6Ak4XXnhhkYsrRU60TvOdyzc0FQH0AzLufuJ5d8C5U93LM+awwNHvmu2+vv4wt9Kyo+fR7PWSn7rvQhkBrGI+ZY7Flw1SyHvRzX8QDPm7Zrkx3iNMs5hQtRrEjANO03KKvfpXVju5W5USyUNYRSsrfSBiH3cX5ke7oU2HaJKvMWWjDjDm2cMOOyzlbd9xL+QX1xbSzkg74YQTiiokKA16NSOAvRCyvxsBnD3bYUb0G4Rik002ybJIkYSVhZ6UFT7hg3CIRiYMyKi7UefSYoElCxQkULvqSC6Nba5oY7QWmFZjN/2ygAyJ3gYbCcgYtcCC7vDLnnV/nfpKIeqjRjh38u4buvevpO+L1ZQAhosU7yuaqk7+gxyo2Pg1CSC5J4ma1TRlagUxhHjGlM5DlghWEw0hAT0cuHwNYUyVEiL2qTmMXGo3cmqiNaZiS8r2mc98xk2aNKlIz6LZdttttyIS3A8C2X///Ys0Sr5WsFMfjABqzk4L7t1GDSDTevHFFxeLVEozBSf5MH8eGzXEgsZCGgZksMCm9NHLRWIYTyfNZurXRjS2W265ZeHTqNVyBQd1I4B+QIYffVsWkIGfXllllROveMgdf/ED7i2LsNtn85Xcv289Vgu24r4hAUzpP1fmP4jGkLFj0qzqPxgLBASQoImUa0T4bDRzNM2axty/TuJsMPYJIfLI++cTwjKNPAF2WDtyWFduvfVWt9RSS7lll102dlqjrsMfb4cddnCYYzUbpl6I5uGHH+523nnnIhE9ASA/+clP3Kc//emejzYC2BMiu6AbAm0ggIyfzd1vLFIEStQx74RET0gf5IsFUTQyotVj82YBxuSs3XJFzDKOXGXncpnsc2EHAYT0s2mF+fSQUzZZOSj4gRmxARnMzbk33O0OPu8J99qbcyRu3TGLuJ/vuYFbYL6RKiKoSQDDDvMsyo0R0MDPvv+gpJxJ4SqAVoYas8yBVtOKYg37myJYoluVEjEZ47rC2kr93Bz+1bfcckvxHqXON7njjjsWBGzvvffWmvq59/3zn//sDjnkkCL/H1HtBIRYFHAc7MPiLrOrOiHQVgKInwr+Pd1yfEHcQo0evwvRC7V5/F628WBSoUA6GiztlitggnFQdg4TFou9dsNnc7PNNiu0PlpNgwD6uRiF7GHWZJ60AjLAh+jSp597wR194wx391MvF5C9e/4R7uef28ittUx6QlNGADVTgZDrEtKx/PLLu6r+g7HywxrBIVGTANbRzMX2379OI20O6yNrm/hu4n/MGsgaKWurZtQ+49OqOkLGAQJBPvvZz9aBO9tnTAOYDeqh+aC2EEA2dzYpaZh38MEi83pI9IT0SXqMsARaJ6LXSUIwo1AfkyAG7ZYrYIJxNCk7VxUHorYhmpp+RcgBrgF10s0gW5KLMayQgabK1+hBADkosEmmNP/7mPpJuo8671536rWPFn8eNsy5g7dbze05acWqU9D1+pAAakfQdvP96uU/GJt/kLxspDjSDGbIUdKOiSNYgnFr+kyyXpIWClKLFju2SkkTQcRkim916pKDHDa/8Y1vFKlZ+rkZAezn2RkEfWsTAWRBkjxoaK7YhNn0faIXplhJYUrKmZoll78cos1ij2mJxVK75QjaidGeSkCG758nP/M3X37EfBtGUoIZTTP1R1il5Yr7nnX/dvptbsabcw5Bm41d3J2427pu5IjhSaaunwigP6Am+QchgKTo0Dx05KhoAh5oTAlmSR0tGwoP5JvDNdYOIeISVMLv+FP6ZeuaJqXWStbNvFMODlNwPzcjgP08O4Ogb20hgESmoYnDL0XMFJwaiR7j96Z50LpNda4SY9KHHOZSnkXdYTQLOXwbSdxNtLGmOU4IoKSbKQvIgOxxHaboMHFyWUBGmVyg9YGY5CSA9OP5V2a4nX96o3vshVeLbi2+0Ch3xhc3cssvNsesfvUDz7mJKy1WixQKMUajyZe2BhCXCt5fgkCqtG75B0P/QdYMcndquh3kyGcIPlrRsiH2uMcw9+RY9bXbPhEXkzHvkV+2jvepKiHkWaRrqePL3Ulu6CvR36ecckoWq00V+Q2vNQLYBD37LBvR23bRIYyHmN2E6BF9RaLP1OkDyiDENIg/kXaCYXl2DnMpz8rp26gRtS14SYUMDgj4SkEEmLNUARmhTAwUAaQf+CQe/P/ucn+8/amiWyOGD3NHfXQt9+jz090PL3vIjVt2EXfml95feSUoI4CpN2a/U3UJYDgwiXRlfQjzD5KeAwKoaQLOYZplzETL4u5SlTBXFQTeG1KYQAC7NXGZ8MvW8X8STCIZE3q5SGhEatMPclj+4Q9/KCJ0+7kZAezn2RkEfWsLAQx9APHJY0HUNokgApKaJVft4RzaMsbFSZ5ozF6LfYrXgFrA+GM1yckmARmh+dbPx8iGxOIvG5CGZhgfKYgHBEmrhSbg8Dl/uu1Jd/BZd7k33yofsuJ73+UeeX6OZnCHcaPd9z85vlLXQgKonURZK/2H7z9ImiMIiNQvRiYwYfYiJVWAy2Wa5T0dPXp08nQp4VhxsSEwo6pVAPnBUhJWKfEJIab4EHuNpNP0heAiopm16rdXkZFu1xoBTIVkS+/TFgKIrx8EQBobCAu7ZjF5eVaT4II6YpmCLMU8F40Ziz01lbVblbQ9MQEZofkWX08+h/ZUO99gPxBA5uuJF151O//sRvfsy3OSpM8/crh7feacd+SrW67ivrLVKtHTmpsAahMaxiMEAFKTon5xGZiYZiGWEA7NxoEX7V/qdClhnzlcsbY29QtmrYYQgjsHTb5Ig+TnIMS3Fj/N1GZ65h7lAFpmItn7uRkB7OfZGQR9aysBZOHlRLnqqquqz1LOyFwGU4UsNRl8zuAW/LGoL+rXZQ0DMnzNXmxAhj/+XAE0uQggmyZpTLo1Ntov//o2d/l9z73jsuM+sbbbcfwyUSLCfdCeiQ8gGsBx48Y10th2ezAEEDKDG4dGYzzInJ/Pror/YGyfIBmkotJ2ReGgBslEC6jZOBSi1Zw8eXLSxzAfVCYRDSHP4dCGm8bYsWMLwpYq8TTrNesMWnTNWtMpADICmALFFt+jrQQQ3xsCQrQz8CNauYiFiDGnYpyYqZCg2TihU/GBWpbajc2YxRiCIWl6ygIyRLMXG5AR9vu8885TrxFN8l+0wqSB0WpsXjEEUJ7/i+sedf993r3uLYtw8d/Dhzn3my9McOuOWbRnN0MCqF1GjQTAkD9tAgiR6ZQJoJv/IO8e5steybtz+ebh88z7A1HSbMgcfrTavnOS+xECzTvPmsB67msI6yai5l4klybPKVVG+rkZAezn2RkEfWsrAWSRIuIsl4o/V2QuIkcFAyJMU+fGCsUZ0xgb/ZQpU5JJul9lxdfocdJnI8YHyzff4qDfa5Ot0rkc89SPBBCMdv3ZDe7OqS+7GW++7SoxasQwd+F+m7qlF+1egm8gCKBGBQiRFQgGBylMmbF+oN3yD0JMyqJctTWZMh4CM7B2aK8JmGyRb0rBaTfWCnwAN9988+JRYipGS8jawSFQCCFkPDalF9kNcA1Cy6hZBjAFPkYAU6DY4nu0hQCyWLCoS8thhvPFKkceO3men+RaU7QJnmCTrBPd3CsgI/TRw6xE0IT2BpaDAFLyCUKLiVSrPfzww4W5rJcJWJ5/2+PTihQxZW3h+Ue4Kw/czC04qnMZudwEUNunzScXdapZxOYfhABqElmZT/LlYe3oVvkohSySG/SBBx4oUjZpNz/nYJg+Bg27pJvhPZAqJT4h7DSvjz/+eLHWcI86c689bv/+RgBzoj0En9VWAphjE/bFRTONSSiW5MbitK/t7yPRzWgAO0VG+gEZvkaPBVkqZAjZk++c1MP75SK1OVLo5JC9qgTw9senuW/88S533zOvuLK8UIsuMNJdd9DmHfO0lRHAddZZR02DAgHEb05Lxtn80aSjXUpBAkL/QbRLaBbBjTFgno3VUNXZhrTzMkqfqA6E7E2YMKFONyt9plPOwbKbhEmpObyy3viEUCwJFAlAg8k1VfMSVhpAgouNACYAsc23aCsB5JSKrweBBTlarsAMxoJfHhuKln+U4IUWi3HhA8hCye9C8joFZPiavbBCRrd5IKgADYa2T04OTS0EkM0LP02tVpUASj9efm2m+7+XPehIE/P89Dfm6d5+W63k/nXLsaVdDgkg5Il3S8uEph3UINol0pmkdDEQ8MR/UFxRkAfcGSQZdYz/YBXZ0U7LI33Bbw4NGimbtBs5BykFV6fGOnhLHWPM1lKlBJ9M2ne+850i0X3KlD8aeBgB1EC1RfdsKwGsu0HWFQ2CGNCIaAdm0D/8fYj4w7Sk0aRCBiYW/H3YrCDTYYWMpgEZft9zaTUhgJz+NSuOoGFAu9CPBNDH/M6pL7n/c8F97pqHXnCjRg53d3yrcy3rgSCA5PDUOhB0My+mfKckOIOUVBLhCiHhMOXnH6xTJcPvp0bC5DIcyJ3IV478eaw5BAOJD2DdeUE7K4TwiCOOcOecc07h/wexJMcplYEwaWscBOr2WT5nBLApgi3/fFsJ4KOPPuowV+Q4qSJiOCvn8GHjWamqnHQLyKDYO2l0OCVLxQd+11ok0WrimK2dxyxHEu3BQgBlaYTcTZ8xH61MmAAAIABJREFUyy28wLw+gGLeR9tLig42UQ4D+Jnhc7beeuupEWntqFYIGFqzsKRZ6u0CDdYqq6wyj29rJ/9BsOUAyVcV7bmsP/iDah5seM4TTzxRrKvMvXZD5kjnlTrlDIf1ffbZxx166KGFhQNtMwfd2GAg7XH79zcCmBPtIfisthBATC4QGmmYKaZOnVokEc3ROIFTYUJLY+GPoWqVkzAgQ8y3UiEj9NGT2sl8Dp85Nsm6KRdisYdQrLjiiupm7Ry+mrgf4AOJRlirpdZwi9YX2ZAvNDDIAPLAF24AaIUZG6YzXBAg7JiBU/tSaRPAKv5lTeYQbT157LoFZ3TyH4QIhvWLO/WFYC0Ou5pl7Xg26yoaTE3ZljFqpZzBCnDIIYc4AgVp4K9lCv7P//xPd/jhh88zbWussYajXGRMMwIYg5Jd0xGBthJAzBSPPPJIlnQFgI8Jk5O+tgaLZ2EWYUOBMPmtTkBGN2KXM7+htllbcIIAbrTRRmoJjHlOPxNA/zDg+3NCiND6+ocBfkbrC7nzTcCQRTS2aKy4B38TzZVor5ouyWWas6b39D/P4YcxYP7TbDyDDb+Ka4iff1BSnvTyH0SrlbpiRhkuWFYwn2q6N8hztVLOnH322e6YY44pKoFoNwjg73//e4flQRpBR7HZDowAas/QEL9/WwkgzspsxNoJS0V8chEYnkdqCTZmtANoaXoFZLCRs7m//6jL3Jc2W9F9YbP4EmAkTsYHh5xbmo0Nn1JW2sXsc5TRyxGA1EsDWFZFReTEj85GNuSrmwks9AHE5QGTI8SE+7JZ4y6A2Q7zpRBCZLSO24A2ASTAgHdWu851iuhcP8LV9x8U7SDzBwHcZJNNklXL6PSuI3dogDWTnMuzSTnz4IMPJrfi/Pa3v3U//elPCzcG7QYBPOuss4ryeXWaEcA6qNln5iLQVgKInwpq9qY1K2NFKZVfXvg8Fn+f4PEzJ3A2eEigmOd6BWRseOSl7uUZc/IkLjjfcLf7xiu4r261ihs5YnjXIZI3Dx8cnqXZtPAL+5wjWptNi3nSjED3CSAaIzkI+CZcUp1A3H2Sx89V/cvAsIwAEggQmhxxw0BrJYQQXzvft43rY8xtMabTJvIIiUHm6kSYVnmuRsk8yKtgzHcauGOBwAWlzvzGjokKNGiLSUSv3Z555hmHxhGNfcr285//3P3ud78rSLN2gwAee+yxhcWBQzgk/aijjnIEOMU0I4AxKNk1HRFoKwFkAyK5MGkecrSqfnlhn3oFZPjpVZ566qliU8fnMLZtc/xV7rEXXpvncqpAfGSdZdyhH1zdLTR/eRLgHGlT6BSO2ORLI7pZs5XVHE79PC0CKMEDkLzHHnusIJmYkyAzaO8gVz7Z4/cUOe6qEMAQS8gK7yJfkBW0gb65uFNuPO3ExmCGzGmvD9rRucgEB0LcQiAZyASyUMV/sIr8o93mYJGjwhLrHEEnqQP5fvKTnzjWNawb2u3cc88tDme4AeCWhD8gY6JUaUzAjhFA7Rka4vdvCwFEQ8HCJA0HYkyl2iYeeR7PwiTTq7h43YAMX0zvvPPOYpGvQgB57oSjL3cvv/52tRS552X7T3bLvKe8FFiOqFn60ZRAx77GOQggWhI25SaRkshymVaPeRS/PDR/bMRsJPhyxmjWYnEKrws1gHWCDrgHuIh2kPHRdyGEEBgJJoEAIt9VfOeqjC1VipFezyRfoma0NM+XqiZYO8BPMI71H+w1Bv/v5LiEdFZZe6rc37+WID5ceWKr3cQ+5wc/+EGh/cU0m7uxL+G7/b3vfc/ttddePR9vBLAnRHZBNwTaSgA5CeNHtPXWW2cREHw8iIbEDEPzU2iw2chmjkakU4WM2Ejbu+++u9jsq57CH37uFbf9D66dpxLEuGXf7c78UueyTjmCJsALDQabfS8C3XQyIS44sGsRC/pXhQAWKVimT58beSsmXMxsyENovhXyhwkYIpUjHxtjSkEAw7nDvUG0g3yH0IpfGwFcmBm15gmcObQ1zTHXSx7xlSwzlff6XJW/S1WTsqTWMf6DVSK4SZfC9UQ2azetiOPvfve7jlRNp59+uvYQSu9PFZVtttmmMAX3akYAeyFkf++KQFsJICYe/G+22247VQmRJKOYmyFlbNpC+HgwG3ZY9xZfkCbaGnwbeW4dP5xTr3nEHXX+fXMxGeacO+pja7mPrVeeVDqHzxydidWgNp1MNmQc2DVrpkIAOemHmguppBJWU2FMofkWmelWOgyCRNDFQBJAfLNS+YYiz7w3oh0EP8a/5JJLzjVnpjJngzfBKkSBavsIc+BIiVOZ/EtOQ/wZe5E5op99kzz3q5J/kLUH6wOlKLWbVsQxZlgw+N///V/tIbzj/sg4bi70Yd999+35fCOAPSGyC7oh0FYCyELH4tutjm1VySkLyJAKGWxOkD/SwPQKyKj63PB6TuGc+utG4u128k3u5kdfnOe2B09ZzX1u0rxpZbggh8mU56BBxQRIMmjNliNhNz6ARDAS0ewHZSA/OOiHWj0CNaoeCIYaAQznnMMb+ImWkPdZKmegFQTDqpj5z9BKMhyOI0d6lro5DevkH6S0HTKs/Z6Co1bEMQmg0Tb/+Mc/1lxqinsfeOCB7sMf/nBh9sWkfdhhhxVrHThyuOnVjAD2Qsj+3hWBthBAFjM2C2n8TMoPNIC9TsUhgGUBGWzk3DPMlYbmBi0ISUV5TlWzbB3xbVpp4rU3ZrpJ373SvfJWVLD0Ye/JK7oDtl1tni7l0JjxQLQxYKmtWcAnizmKWXx7zY1of8PkyRwKICdoVsK8eqm0WANBADl0COmC2GDKSqUBDLEmfYpUoOFvvuYK7Q3vmh9MEus+Ic/BTw5H/E033bTXNDf6Oxp0Sg9CmrQa2OAz2dTfOSb/IBpA3tMwB6nG2DhIod2sY+no1p/999+/OEwcd9xxGt2e55677rprUSUKbT1rDhkVjjzyyOh1zgig+hQN7Qe0lQBC4ghgwAewU34z/Jp8/zz5mQUV85OY5fxUK502cBZG7sempd1SJBq+6eEX3KdPubno6nwjhrk33pxd/Pzx9Zd1//3Rt8cAYWIBjk1cWnfslHyCTGgTQKIyicirSgCRJ79ChvzM/4uZXzR7kAs0TKmjF31shzoB7JY+hfcMfMVczFzwjgohhHj3OvRpVZnw54gDAgSQXKQcHLWaVkqbMv9B1j98nfHVbVq/uBceHHQhpbyvKRtl4CCwELF+b0YA+32G+rx/bSWAfhkzyJw42pcFZIQ+emwmVTUKmGVZMMeNG6cuEVWCDLp15qjz7nV/+OtUd9Ju67qDz7rLPfL8q8XlH1hjCXfCbnNqfeYqcYcPJZvkaqvNq4FMDWav8fjBO75mTw4FZUEZYaLjHOQsxzN87CXK3tcAalaeqJI/T4iKEEJIuQSTQArLTOxEyBJMpZkoHszQlKJlrLqeVJH7XBHNvAMc1JABzM408R8E7zquDN3GyZrKs1KvCZ///OeLUnbf+ta3qsA8INcaARwQ2IfOQ9tEADEXsDAJycMsC5mD/NH8gAwhfU0DMkRSUmjlYqUuZQQom5SU+vrkT290f5v6z6Ib6y2/qDv98xsWpiW0cuTo02yY49gkUy/2YZ8hFjyDhLni0+kHZfAzzdf6CumL3cQhZ/gADnUNoCYBrJs/DwKPRkzIINpYLAAE/UhuPH7n76wPJObVamiv8EPG7NctoKfp85FZ/Mq0A1roJ8/h3aEONM+VhNSCc8r8g1oBJ7vttluR/xH/vH5vRgD7fYb6vH9tIYCc+qlaISY5NnAyyWM+wHzJ6bSXWajJVKbSysX0geg4Kp2kJhiQwS/+6jZ31f3PFd1YZYkF3aEbzHarrbqqeo1jchtiXkpt7mEcfu5FNhWIHOSPA4P4dPqavaayojU/vmzkIJn+8yQNjLxDmDYnTpyoViKwLgEM3x9IGOZeiXzlMIgJk3nn/9EANgkm6fa++vn5upXZi3nnu10D+UKDDtHUbqRrgvzx5bcY/8GqJQG1Ak7+5V/+xX30ox91//Zv/6YNV+P7GwFsDGG7b9AWAsgso3Vh85aFhhx2OKqz4Gu3lFq5Xn0lPxZZ5RmbRvv6mX9zf7r9qeLWiy0wzP3yU2u4sSuN0XjU3Huy2DcNovHr3/rmWzRC3BuSBwFAg0GEKYcEjY3ZCGBzUdFKoIyFADLI+wNx4tDhB5Ok9NWT/HzkGkwV/FOGbA5/Rnku1VNIY9LLIsAByyfeHLYIvPDrF/c6kEu1jNQBJzvssIPbc889oxIxN5fkZncwAtgMv9Z/uk0EkEXGb2gpyMLPoqPd2PTROKauW1nWb9IJUAoMDYxWwz/w1GsfLW6/yPwj3F++uolb8t16juz4Y9FiI/4kUjs03/aqf3vttdcWDuyhBiMljjlkoR80gJrRrVoEUOaZwyJuG0SE+8EkHCD9YJKqWitfjiBBaDJj8vM1kb8c5mzpHxU0eH+qBlGF+Qc5rAkZ7OQ/iL8hf0tdHpJo6QMOOMB96lOfagJ7ls8aAcwC89B9SJsIIAsuC4u0XClMeB5aOYgZflHaDe0FBIANWLOdeMVD7vsXP1A8YsFRI9xZX57oVlx8QZVHdoqi9uvf+lo9NHlo78KgDLR63TZtfBrRKGgSQMg5Jaw0DwM5tIz+RJeZgDUJoHYFDVwo0Nr7WnQOD+LTRtoOfveTJONDXMVcLAmaIRxVPlf1BaOvlGjTXg/o1/XXX19UAWmSSF3yD/byH8TfEKKJtj5lw+xPImZMwf3ejAD2+wz1ef/aTADrpvyoM6WQPzblHIsw5ALthWYEo2Dw3TOvdiffPic6eNSIYe70vTZy45ZbtA5EXT+DQz4EPkyeTEAP5MOvlCE/16l/ywaGRmHZZcsrn6QYGASQQvZaJnr6ONAEkBybBFBo5berU2u4ytyhrecQ1WmOJBrcr5rBgcM3F/dyH6iboLnKOLgWbSY583IcPtGg46ebskRfmf8gZBstP+4alNdsookN8aR6DvWAP/jBD1aFOvv1RgCzQz60HthmAkgyWRYPqnNoNzZ8FuEcpAztBYQpl9P3318e5b5zyVNu1mznRgwf5n72mfXcpFUXrw2pBGVIfWQ0e1ILtlv929oP9D4IARwzZkxyrYLfN20fzbYQQM0SahyiIOqxWlqfpCCryC6+xUII+Tn0aUuVoLmX3Pcis70+X+XvYYLuKp+NvVb8B1njaBDBqv6DnZ4FsSdX669+9asiErjfmxHAfp+hPu9fmwlgDm2PTD+LMHmrcpAyTvz4zOVI+yA1ep91i7o9TrvFzZw12w0b5tz3PzHOfXBcd2It1Vl806347LFZ+lo9HPK5ft1111V9o2644YZC+wcJ1GptIYCaCY61K41wYHviiSdqR9Jj3hXtIN851PjaQTSjuCkgb/gAaraqZLZJX1JFZ8f0AewoOcc6AcZiMo7xH+xGAElr9ec//1nVhzpmfDHXGAGMQcmu6YhAmwkgDsv4emlu9gI8pIxIViL+tBuLIWkfcpxg/Rq99z79T/eJn9zoXp85qxjit3ZY3X1m4grFz2hIfI2e/MxpHsf6sCRamDSWrP9smCRo1Ww5ZCKHP+hAmoBzVLjQrqELAcRtA3Ng0+bX1MUfjyolUvMZbT0HtZQmzLC/+ATzlWIsvbDAN3P99dcv3mfthr8uOTt9f8NO/oN+4u9uORf5PG4m5APVXmtS4GMEMAWKLb5HmwggTtucxKXdfPPNRQ7A1GkEysQJUkbUmvZpn2eTXgHNXNPanzGvRVii7fHnp7uPnHD93DrCnx23oNti6TeL5LukuigLyohJgYFPI6RRWwNIGgtSWKSOLPSxRLPEl6ZP1lAngNp5BjVJEyZLtFVo5rAMSF1o0RCi0UoZFAKR5VkQM+2Gb6amad7vP+ZmsgJ0y+LQyX9QsMZ07K8/EED+hgVFO+l8irkwApgCxRbfo80E0NdeaYtATlKGuRRy+4EPfEB1WGxkYMhmRX40Md9Oe/VNd9RtI9z0mc796MNj3LgVFi+IX52gDBlArkTaEEAcy1dYYY7mUqNB/tACaqbpyUkApfYuQQ1ExSIPEDTNEmfcXzPKOAdpQhN42223FWZmP5gEbaBvLm5aJQR5wwKhfXjiXdGeF/99xNw8fvz4wv8vtnXLP4jc8u7jE47/Zw7LUGy/O11nBLApgi3/fJsJYKi90hQFyBE+h9tss43mY4p7p36WlM/yTbg8Ayd2fPUgdmjNRLuHBuO1mbPcw8+96tZaJo0pCAIIidbWYkCcSS2hSQBz5GnUIoBSHg/yIr6byAWkBVmQOruYOiE2VTbnKi+GdpQxpAnzLHlCtVpZhQ7INP8vuQfBlvfK11j1SpAc9hcyg8ZR26SZw/Tvjy2FuVnyD4LPf/3XfxWl+Vi/yAO40047udVXXz2pNja1LBkBTI1oy+7XZgJIJnlO17zk2o2FHJPFdtttp/2owlRa91l+/Vt/g6fTflCGkD1889j8NUq0+UDlqqRCKSt8ijTdAgYDAZQ0J8iAT/bQ8on/GjJAdKtod5EdNlRJO4JGhWvBky+0g1XJS6eXBQKoGWSChhYSq6k140BDiUM0pZ0amPrBJJg0fX82fGV7NQ4DkEq0ZZoN8opvpnZtYxlD6kAgDi8XXHCB23vvvYvDC2soh0H8ATUPhE3mxAhgE/Tss0RWvp0ZeYjjEfoA4ufBJkW2f+1GAAMn1u233177UUWwBJUSpkyZ0vFZLNahRo/fiV70N3gJzuhU/zYXhloarRAgiWqmmoFWy5ETskq1Eama4hM9iB9Lg5B+IXrIQ1l+Oz8RtBABTNz4fkKk+BLyIoSwblm1k6951N1z3wPuiF0nFdpnjQYBhHhpas3QOvH+xKaGYj54R0U7CKlj/OCJhhBiWOZPy+GJeVh77bU1oJp7T6ltrF3aTh6oYW4m9yNzzl4B+Yb84UutGaTTZFKMADZBzz7bKgLIAsUmJI08UvxO3ifthuaEEysawFRakE59lmcJAeT3kOz59W/DwIyYoAx5dqcKHanxrEJomjw7BwHMUamlDC+/FrJP9pAFNOEiB0L2SLYbK6tlBNDXBAl5ETLI8zlUCBnEVBzzrDumvuQ+fcqtjlPr+GUXdqd+dj03auTwJlNe+lnMpmjoNLVmEDlSQ9VNDs965tfTRfsKjmIuZj454OI+wd+01zkpbUf2AW3CJIeM1H6m7AkQWNbLGHlMJXhHH320O+SQQ9x+++3njj/++OjbGgGMhsouLEOgTRrAkABSHgmN17hx49SFg8URsxU+gFUIVpWOiSYHzQILGRoBNDn8P5t5SPTQwDSNNuQ53F9bu5Ajdx5Y5wgMggCilaFShlZDk8FzMF0J2eM7mg2RBV+r1yRAhzH4BJBDFb5U3UyBUlbN1w5CXIQQdtLsvfzaTPfZn9/q7v/H9AK6hUaNcL/ccz03dsmFkkKZw2zK2HGhSBUM5NfThVxCYMCU+eBn7XUuV2k7Jlq0jaTQ6VVxpYpgEJTz4Q9/uNCyNl0bY59L6qmdd965cKdA22gEMBY554bFX2pXGgGcVwNIZQ4Ikqafj2DOgnXRRRcVkblNo/p8/yyJvOW71L/FbAcJ5MSPRqBX/dsmb0YuEp0jd54QQBZiKsRoNXLMoZVJRQAhU6GvHr/TmH+f6HEI0NDOVCWAPrZl2kFIqpDBsIrGjDdmusnHXe1efXPO8s+/39h+rNtlw3Tl+yDQYKhJmjRLtElkNkQGlwMOoKwDoh1M6Y8pc5mrsgnPQ+Zxc0mtbSS34B577FGkacpBANE0kp/xxz/+sTviiCOKoCMjgPErrxHAeKxKr2yzBhAtDERJO7JUNCQ4GJMHsIrvEwt3ma9eWP9WtHuQS/524YUXJiGbvcQrV4LmHIETjBUNABsl1QC0Wl0CCFFik/XNt/yMiR+Z8oMykBlkW7PesI9PGQGsq51hcxc/N7RkkptNNIRo0P9y0eXu548t4u55eo4mkLbF2MXcDz65dhLTXQ6/OaKMeY72HHFI4wAKfuAJthKtLYQwTLxeR/ZxJUCblSPXqZa2ETcdzLDkHc1BACGbzMH3v//9AjcjgNUkzwhgNbzecXWbCCCmEBY+abkCC+R55513XuFfUha5J/Vvw7JoLHSyuftpVrr5Z7Fhnn/++ZXJZh1RyqVFzeE3x/hzpAaKqQstlVNCsucTf1+zF2qV8WEj+W9sLds6c69FAEPtIO+EmIr5GdmH4I4bP9794vZp7tTrps79yOILzefO+Pz6bvQiCzQaUg6/OZJAswZpzxF+hpiAx44dW2AiaZ38YBLMqH4wSR2zKnNCFH2OakdYO0irlTrZPWv0YYcdVlRt0m6/+c1v3JFHHlmQZtZ4I4DVETcCWB2zeT7RZgKYoyKDDzYaQMx+LK6+6bZT/VshfHUWYxYyzCNE9Gq2XAma62rNqo6dEnpgJptl1c/HXA8xQ8Mg0Z+Q/JDooU1h3sPADLSTMc7pA0kAtfyzwBaNOKZTgo/ABzLz2IyF3P+58RX3VgVCN2KYc8d89H1uylpLxUxH6TXINZpVKk1otab1hmP7JVh10mpz2JBgEog2WmYOF6Id5OcYbRgyzAEqR71z3g+Stqcud3nWWWcV2jiIrGbj/YT4Y6mRSHMjgNURNwJYHTMjgG8hoK1VCuvfctrH/4oNUurf+oEZEI+YhTZmyiGbRMihLdFsufLzhaRJa0wQQE7jGmWg0N6huWDxR/aYe8i/Xw9ZtHp8bxKYMVQJIPMu/l+YmMET0nLfE8+6o65/1T33+ttbwsfWHe2+s+MatUQFzTbEXJMAapab8wdNqhlkKdavFeLr5x7kXn5lkk4uLDF5DWtNRsmHeG8I2EIGUrbTTz/dnXbaaUX6F80G0fzYxz42jz8u+wXrPwc8ZC/GV9eigDVnqQX3brMGEBMMPmyxebg6iYP4ZoXmWwnKEJKHxpENhaoZWpHA0kcCTogu1C7KnsuMzlzhy9QtaW6K15Xk4GyWTQmgBGaITKAdwUTGAs/9+TvPENlILQ/9QAC18sF1CgB45dXX3Df/eJe76IGX54rC6IWGuxM/tpJbYZmlKgVfoaHlOZo5QnOUmwMIkk1zEKyT25K1DdkVczHyzOHVDyYRosI1ZAVIFdzU7X0mByLvaur14JRTTnGQMzI2aDZwJNDIb5/73OcKeTvooIOig4+MAGrOUgvu3WYCiCmJ03GVUySbQhiUwcuMdqcs1YqvxcHBGHU/i6d2u/jiiwvncjRJmi0X0cBhns1F27zEZolpMbY6DBskGpPQhIsZjbkPI3CREcaiTWaZF0yM2gEGIlt+EIh2QuBe+ebOufNpd+gf/+5mvZXifuQw57685ky34fKLzI0slhx5nd4NDoZoZDQr3OQoN8f4IEqMN0V1Gz99D4SP34koZk1Dc0W0ft28hlXWKQKcMG2nJpsnnHBCkcLonHPOqdKdJNeaCbg6jGYCro7ZPJ9oEwFkk2LBksYChsmvzI9EzHWhVo/Nno09zKkXkzSXSiCkZlliiSUazlrvj5Mln+hmFmfNlis9Sx2yXmfcOH93Km2HTPjyIKQPosD8+2SPnzul+0GbiWO+JpkdSAIoGjotDaAQQDbMTv6QDz033e3589vc89Pfft93XWcxt9PKw+bmePPzDoZ+thBA5jv2IFBH1nJUG6FfrHGsA8svv3ydbnb8jKSjCs3FSy+99FwNYR3/5ZhOps6hKM/E/49MAGeeeWZMN5JeYwSwOpxGAKtjZgTwLQTwWaHyAyZgf2NHw8cXzY+89VOt1IH9qquuKjaUpZaq75we+9xc2sZc6VlY8NHOaUcYCgFceeWVSwMzIId+uhWIXmxghsxdDm3mUCaAkgKkGwEE6+kz3nRfO/NOd/WDL859bdZeemH3v59dx82Y/vLcyGICCphTyTvIzxBAWlNXgG7va45qIzwfQsPYxowZE7t81LoOjTM+wRxweV/BNQwmiQlginm4Vgqdo446qojM/uUvfxnTjQG/xkzAAz4Fg7sDbdIAYprCdCBkj5/xJaGF9W/ZBFLkxvKlg+LiOGJzQtZuaBupzsHCr9m0A2mk7920tU3GJykxRCYgtGiw0OohE35QBjKRonpKWwhg6iS9Ms9VcsAxv7+64Ql3zEUPzhWTBecb7n6xx3pu9dELu2MvfMA99vx0d/Bmi8/NkQfJxyeT+Udjr6XFgmigRdZMNs2gCZZYcskl3XLLLdfkVen5WQgg7w+JjWnMk/gOstaiUfWDSZpkKNCKoCYFDGvBT3/6057j7YcLjAD2wywM4j60iQCi8SO6y9fk4ey99dZbqwdlICJkmac017LLpqtY0En00Dbiv8TCr9lictqleD4bCJqMJklmOQD4QRmSfgeSgBYPsid1cakBmzowQ3CAAOK/VMX3tCqGuUrnSb98H0CtKg3yLNwwOEyRAy42av7Oqf90e/3qNvfKjFnFbTAdTR67mLvy/heK33fbaFl3yJSxBUnhUCgVbpAZ5EK0g8hJ7DN7zRlBAFgatMsoktJkmWWWKb40W7egFt4x3jchhBBfCKAQQspWxkS9Sv85eLL2pE7iTwAGWsof/vCHmlAlu7cRwGRQtvNGbSKAsknJAo6jPg6/U6ZMSbaod5OiG264oSB/2qYY+sAGSd4vIo41W67oXDHXxyR+lcCMkOwRlY1fXuirh6ZXTFMQM+QEzY9Wy+HPOJAEsFeQRlNchQBSVrFKm/bqG+5Lv77D3fnU21HC/uf/Y5tV3GcnzjGTSu48tGZSPQPyAkkRMgh5aXJIwFyKTGrKGmO5+eabC+2ftuUBmQOrmNKaYo0RQoi2UIJJwLUX0SaAhvco5llVZGTfffctTNjHHntslY8N2LVGAAcM+qHx4DYRQIgBm5M0fibcf9ttt610+qw78yQuxf8PLaB2u/baax1+bNqLfg5zJlihlWEjCzd9yJpEZfuRuGih2ET8YB0GMLuwAAAgAElEQVTJrdcNeyKNMf9qbspsXPgaavozDmUC2KTm7KzZs90PLn3InXzt46Vi8D+fWMt9YI0liuwAYe480Q5KVRLIG7WWhRASCFRFO5gj2TSDZN1hzdH2Pa7r0yhptCSYBG0/RNs3F5dVuuFQiKY+ZfvSl75U+H0efvjhKW+rdi8jgGrQtuPGbSaAnELJl4cJWMvPx5ciTDEsanXycVWVRsokEfWnbW7OQWYYO+QODSomHzR7QvYgf2jvQq0e5K+KSUnwJToX8qhplssR0NIPBLBXkEZVmZbrU5QBu+aB59xXf3eXm/HmW7li3rr58GHO/XrP9d3waY8X/p4cojo1NJFCBiEtaAN5v9EgYdLspR0k2TSHUM1cg/Sd94ZxaLuDYNLm3Wzq0yhEW7SDvOMc5IQQQrohmxrmc2rzUqHj0EMPrSueWT9nBDAr3EPvYW0mgCw0VMxgo+qU3T7ljOOMzeLVbVNJ9TzqS+Lzo21u1gjOkPQSPtFDA8hmyTyFgRkpK6hAAHlO002s2zwaAWwm5RBASE0Tf1B68PRLr7tdTr7ZPTf97frg/P+oEcPc8du8x41ZfOHod5W1BI2UEEK0lL20g/gfcwjVzDXIeDgM4g6inX5Kq34y76OQQb6DNdpZCDaa+rLa6nUlbJdddiksQvvvv3/dW2T9nBHArHAPvYe1mQAym+eff37hjJ9yEekkJdTJxEzUqSZnSunC7IP/X+rcX2EfmwZnYG4NffUksbZvvkVDSxqY7bbbLiVM77iXOP9rE0CS86auY+oPZiA1gLFpWupOJIE6HHCaEkB8Aid/79rSbiw40rlTPjbGrbX6KrW6CQH0tYPIr5iKRTuIrHHY0cw1SOcJPuMZ2gnoc2g0wQvNH9hxEEBbDxkEW8YXo3ntNqEf+chHHCTwy1/+cq15z/0hI4C5ER9iz2sTAWTq2Jz8RjFussljMtRuqcqMxfQTczOLYors/92e18k3L/wMCzfY+1o9fmYzZ3MMtXphYm2uI4JbmwCS/43NO7VvkY+HhtY0xHuoE0AOOE0J9GX3PluYgTu19yww3F2+/6SOyaZj3kOu4ZDjawcxHRPwgCYL7TXlIav4DsY+V64jIIxnQI40W47k2dJ/CCANawrYioYQbNG8irm4V8WXEA8CAvfee2+35557akKV7N5GAJNB2c4btZ0AUjINnw8WDe2G4z/+ato+P4wjl7kZXzy0MfhRSmNjg7CFZA9Tjl8uT0ifXy6v0xxw2r/yyiuLiG3NhlmOvlOyT6uxWaENbqrB6ta/3AQQcs/mC6GpkqevDsZogAgIakoAefYLr7zujjz/AXfx359zM6V2nNepRRYY4a4+YNM63ez4GWQZ7SB5AHknRIPFga1qOpSYjnFwQqOtvcbhPgGR1UyeLeMlWAsTcGhN4fDm5x5kvfWDScC6W0OmDj74YLfzzjvHQDvg1xgBHPApGNwdaDsBpGIGqQS0T8dISY4UIyKN5Mzj9Eviac2GCRhtDIu+X02FhTeMwEXL2ssxvlNfJWXP9ttvn2w4f3timhu33LzEPwcBbGo2jwFAq0SfaHIlCIfvfDE/NOYY7RbP1woCgQCi4U4ZRc24zrnzGfe9ix9y/3j57UwBjOn6r09yC44aGQN7pWtYDyTaFUJIQBWEEPzEXJzCv5WDE2ucdl3wTqSsEiiRFxOl3StIh4MosimEkPUJ+RRCCM5hZZKJEyc6qoHstNNOkT0Z2MuMAA4s/oP+6W0jgCywLPbSclXM4Hk5AgxkXNT/ZPMYO3ZsEhmVVA2+Vo/FFa0PjQhDv0Ra6ioqPAeynipn42Fn3+1+c9MTbu1l3u2+9aE13PrLz6mZjB8TY0ydX8yfhMFCAMNgHCF7osmFUIgWl40VfyzGRm5IyIz4vRF80DRnno8f80MJx5QE0L//M9NedXv9/Eb36EvOHfOx97nt19Ip3RimmpF3THwHMW2S/gT8IIQQljqR7axxRM/zfmq2stQ5Ws/DHxiZq+Ligtwin5LXkQAcDv7IppR0pIrJSSedVASCDIZmBHAwzFIf97HtBDBXxQxEAB8ZzD+a5kURNfwN2TzqOJjjs4SWxc+rx6bL//u59Vg00ejhZK5tmsWseOmllxY+gE3ric58c5Zb78hL3RteCpCNV17M/esWK7slZ79YjHu99dZTe2urJLWu24mqGkAx2wvJk+/8f1j7mN9DTa5fCUQSNUM6RLOFhhACI2SmSdAVsoiLg2YllRz1c3EJAYdOaaF434SwgCMERggLhDAWQ5Ld4+aC+4Vmg5TxjBxprjjgIk91g9ykBKRoB3/xi1+4P/3pT4WZfPfdd3df+cpXivv3ezMC2O8z1Of9azsBzJUwWbRL2uRCxI3NBW1BrxQTEKuQ6EH+0N6ICdfX8oTkK1c1ldRJu29/fJrb+ac3unmzwDm39lILuM+Pn9/tuPkEtTd3oAmgRF77ZI85x3/LD8YRrUgM4fYJIDLBe+Un7Ra/NzSDjB/ttJBBNt2YZ8iE0G8ImiYBzFE/t4oWS7SxvnYQE6iYirtpBzk4YdqMJYx1BZ9DJzKTI9E984/8pKpvzKGClGDf/OY3i4Mz/plg9qMf/Uj1MFgXa/mcEcCmCLb8820ngLkSJiNmlH7iRJ+6fmWZCONfxKZB9B+NDZpN2Cd7/AyxYmPwtTz8zOYSE5koptkUmrluryLmRQJ2ttlmm9p+hOH9f3Pj4+6wP98z979HDHNuxPBh7gfbvsdttcmGaitDDgJIqSy+kLVQq+dHXosZl+9NzPa9CKAPJqY3NC+QQQgNcipEhu+9krIzHoJoJk+erDZHmJhJo6SZSL0JYZJSakIIeT/QDvq+gwIO1Y7IdADp1mzMCeZU7dyjjIH5ocpRyvrGyCH3JKiN94EUYTvuuKN6NaUmc2IEsAl69lkW31AJMqRRYaFks5KWK2Eyz+NUSem0DTfUIxc8h80B7QKaGEy2bJhoeGihVq/MnFdFAFJr5jo9W6NqC6L/9TPvdGff8dTcx04cs6Dbd4P53UaKcxSbOqfKPPjBGcw3fnjMObIuybN9shcTeV3l+VUIoH9f+k1/xVQMOaWfaHf4KiOl4IcJUJMAEmQCuUhJMEI8m5ox5X6+ORNSDT6QPcmNh7Zs0003LaKNNVsOran0X6O+MTKMJpVAMO3guRNOOMHxhVKARuWhb3/72+6DH/xgpSkyAlgJLrs4RKDtBDBXvjxwT52ag4UfDVwYmAHxw/yLJoUNTMx6VWuVxrwtGpq5suditiRnI2bFsC5oTD87XfPK6zPdJ35yg3vw2elzL5m03Ch30ucnu1Ejhze5dcfPNiWAYg4UzZ7Mvx+cIaRgwoQJSfHqNKiQAOIXutVWW1XGT8qrQWTQlksQBGRQojbBD+0ZpEarsS6g/dOspa2lMfO1gxJZjGaOQC2+a2kCNbRyneaXgzu+hinL27FuovWdOnWqKvFnTGeffXaxRpM9gXf1tNNOc8cee2yh2axShtIIoNYK0JL7tp0A5sqXhzixsFDDEt+Sqo0N1g/MEFMuxEhy6/n1cCGb2vnsGIMWMQvxkbJ9kIrUmox7n37ZffKnN7jX3pjlhjlX+AVOHru4+8HO491C86dP/1GWO7EbsQrnnc/7wRn+vEtwhpiA3//+91cVtVrX+wQwRa1ekS1IoJiKITYQGLSCTz75pKoGUEPDFAKb2o+tbOI4oJEGhoTJYAl5Bj/RDpalQqklAM4VuRnxydMkzdI3XHfIcMA4UjXcEiCV4DQQASDINiRwr732ih6SEcBoqOzCMgTaTgBzlmd76qmnHPUy8cfp1tDkhL56kDlOjKGvHibestQQPIfFXjOalTFoEjMfI07J+ORo1W3+/S1PuG/88e6CAKL4e2OWc+sst4g76dPrufcuNCrp4tGJAEJw/LJ4IgMESPgpV2KCM4YCAQznHyIMGXz66acLf1ZwgACgHeQ9iPFZjZ1IclsSYYpGSKvl8DNkLSHTAQmOWSckVY/4DnKA830Hm9RERytHWpalltJJm+PPA0FGBLilLG/HAZ0k/QTGpbQy9JIf5uB3v/ud22OPPQoNIPWNY5sRwFik7LpSBNpOAPGVw1RaJ11KVZHCL4sSRmK6EjOdn0CZTZ8FCDNNSPaqJIXNFXCiTcx8jM8777wi95tGNCPjOPj/3eXOuu1Jt/EyI90904a5F6e/4VZeYkF38mfXd8u9J50DPXN8ww03vCNAA5LPxhNG4tYJzoAAogWuo22uKtdyEIBsQFZTaQA79QMNDVHuaLUkpxuaTyGDKapp5CAzOfwMu9Vllrq6QgaRS9EOgmXV6GxkGt85CLl206huQg5Q/LNFjrXHgA8oygDcHjjA/PrXv3Y77LBDpccaAawEl10cItA2AoiWhROXNJKXojnQLs/Gc9mQcTDGRCKBGSzCvPy+GQ/i1ysSspck5wo4oR9o5kjJoUHM/HFqP2f6jDfd7665x6254Ctu8ZXXdnv94hb35LTX3ehF5i9I4GpLVa8XHQZnMO9oZoXkh2QvVXDGQBNAyIBWqTtMdVSdEE06Wmgiq9EOis8bJFDSzNTRatF/CGZKH7Pwnc1hMpWcjLhO9NKQoh2UvHh8Z51EwyaRxb1cL/D75CCdUivXaZ3DrI11I2Vyaw4VZBng/aySlqjXWtzp7xBN1mme9/vf/9797Gc/c+RsNA1gPKJYbKw1QKDtBJCNhIWuykvXDe6yUllo+NCKoKVgs8JMItG4+O9pLDapA066jZn8WWg1tRPN8pxJkyYVhFmr+abTp6a95vb6xV/d/f94xS36rpHuxN3Wcxus0Dk5bBicIUEabKySQFuSZ5OmR7PawEASQDSZaNA0CSBVdTbeeON3iIHMgZBB5gC5FDII/r2IEDfNoc3CzEzOPE2TaV1tLDiybol2kJ/BUcggOIbr1jXXXFOkncpRVlMjuTUa2Y9//ONFpoYYGUm9BkE+qW1MJZLYZhrAWKTsulIE2k4Aqc5B9Nf48eMrS4gEZvhRuPzMhh8GZrBg8hx8POpER1btXE4fMKJz2YxTnsbLxstz0PpoEsAwUAcz8Jd/fav762PT3ALzDXfHf3K822qNJQsiL8EZfjSur9H1/fZ8P00+hw+TEcCqUj3nekgJrhRlBDC8I++ikBi+s7GLqbhbeTqNIIOwbxqRrOEzIOMQTXwAmzTBUTSEyLloB/mOdhBfQ9ZRTMfaTSO5NWblL3zhC0Wg3kAQQDIccCA49dRTo+EzAhgNlV1YhkDbCWBs7VfU9b6DPj+zkXMKDktldQrMqBL92VRaiZJ85JFHojbJps8iQTPpRrSLzV900UWFT5sm0YQAYpbxycU/X33d7XfG7e7qh6a54cOc+9zao9y6i8xJtSNzL2QvRqObgwA2iTivIw9+FHAq0tGpHxA5Dm5V/RvpI+a2mPJ0mDNJ0ZEyyjQcTw4tI7KGZitl3eRQO8i6xnvAvGMCJvWUJoHi+RDA1LkNWce+/vWvFzXbNfuPHBxyyCFFzj8IH3sJ/n/HHHNM4U5T5WBoBLDOamWfmYtA2wgg5l788aSFwRJiQgrJHr40+BKFZK9KYEaOjV/GRaQk/oaYTLUblQZwntY++bNAU9NU8zmc/pEJqhmIZq+IwB45nzvjoZHuysffKODcb4sV3D5brVZro8ghB0OZAGLeRbarEsDwPehWng7fYPyCNf3ZcmgZc5TN43CMZhDMRNPt+w6mjqhlDccEjN9xU19pXybOOeccd8QRRxQ5JrUbqV5Yzzios55RH/6ggw6qRP7ooxFA7Zka4vdvMwFkIUGTgM8HC5ak3UBTUBaY0XQhY8PBeXnKlCnqUhVGHGs+kNM4Dtnavj8piWaYRFvIHkSf0z9+WX6ABuSfzxx74f3u5KsfKeD8/KQV3Ne3Xc0NRy1YoUEoMTdRPk+rDSQBhOAS4NDU7NgJGwggmvuUOQ7D8nRSWg1tVkx5ujrzmCNoIkfSbBn7ZZddVlgCwNL3HeTQ7PsONtWuSW5DtJqS97IO/uFnzjzzzKL2L6b5wdKMAA6WmerTfraNAIr2AA2f5NZjQULjI9q9GDNenemUurkQwKaLYK/nM05O5JyStRsLPydYTW0JY6hLNP10O35dXAnO8Ikec4TpvJvmFAL43QvuK2Ddad2l3ZE7reXmGxFfNcQIYDOJ5MBGnsuUBNDvEfICQUeeIbMx5enqjAg/ULSMmgcnUuawDmhbAsQsy3P8qGu0g0IG0RKy7vm+g3UO1d1S29SZB/nML3/5S3f66ae7K664osltsn7WCGBWuIfew9pGAFmESMgsZI/f2fB7JWdOMfO56ubSVxZdTBlaWhgfDxZMyhdp+kvxvBii2S04w6+DLKQvTKIdazo/69ap7tA/3u3enDXbbbHa4u74nddxC44aESUmOTTBA60BTO135gMLAcRMj7ZJq/l55mLK09XpB1GzZB/QrDrB+tYpYrpOnzt9hveO97ObXx7XSN1n1ieIta8d5OeYgzHBdHVLDXYbM2lYzj33XEe2gcHSjAAOlpnq0362jQCGPoA5TaWYRghk2HrrrZP6rpSJFid/Sk1ppeLwn4lZG02GZs40noffz7hx4+YSTamc4Wv10NjUDc7gGVXk4fJ7n3X7/vb2ooTcemMWdSd+el232IK9q4YYAWy2GDJHHNo0CSARrWi1w8Am1o+y8nQSWVxFo5UjarZuwEzVGeJd5CBYxS8PTZ4k8hbtoJiK0RJ28u/TSjP0wx/+sIjO/9Of/lR1+AN2vRHAAYN+aDy4bQSQUyimP2k5TaW5yqYxNnx/8MMitYB2Q1tCxKRmPjO0pzyHfG5swpA+iBTpJ8JI3CqBOSE2aJfIDTl58uQo2P762IvuS7+61U17daZbdcmFioTRyyy6QNfPDnUCiHsF6Y5SRp76gEIAidQmIEircahZd911u0a2SyUNqVXMuEWjFVOeLuYZTcenbS6X/olfnpScq9rvMu2glPqDFPql/rTk67jjjivM5WeccUbV7g/Y9UYABwz6ofHgthNATp7UA86hKUNiNMuZ+RLJIkmUIclFtRumLBKYpqibKsEZvlaPsUhwBhFzaBrFhFunykM3PNgwSdJcxXfyvmdeLhJGP/3S627pReZ3/7v7BgUZ7NQwYaHN3H777dWmZiBNwFobtICFmZ5obU0CiDZr/fXXr5RySDRaseXp6jyjqsDkIMv0KbVfXoglWn20ghBrfoaoxR7SYjEjAhj3oNNOOy32IwN+nRHAAZ+Cwd2BthPAnJoyJCVHNQuekyPViEg+ZhPKZlHirkqT4AyJvhbShzmJQBw/kTI/Q2jJM6apaayrEZ76IlVDKB33mjttzw3dumM6J8PNRQDDfIZV5qbqtX4eQAjgrbfeWolEV3kemzSJzkk9pNUgZxtssEHtpOMx5ek4BDAGzcTmObBiDpBp1gENi4Ofv1F8B/EVZM0JtYNN5OEb3/hGUQf4xBNPbHKbrJ81ApgV7qH3sLYTwJyaMqQnRzJjnpPDzChvA8Rs+eWXd8suu2zHF4RF3M+tKKQPEhjmVuT3MDiDG6fUNHbqKBvMnXfeWct8+cL0Ge6Bf7ziNlpxsa4LRY5o8LKE1lqrl+TOxAxIPeihQABTlhrrVJ6OQxrBUxxoYoIf6swfeeb4gsxqNtYbzfrPft8ZD3kgORTij8la4fsO1k0Nc+CBBzrcR44//nhNqJLe2whgUjjbd7O2E8AcKTl8qUqZy66btOYgGfJ8Fv7llluu+KJ1C87wU67wc5WUOxDAVVZZpbKmscpbnSN6OsfcaBFAyAzaHt9EjxZdkqtLCURMj/gAahCbHKRGctpp1LeWsmp33XVXQV6oJhRTnq6KHMu1yAFzQZ5OzaZRcaRTf32/RtG0itkdIoqbiBBC5i9WBr/yla8UVUyOPvpoTaiS3tsIYFI423ezthFANjDU/NJybMa+VLGx4FyumfuL5+FDQ948kg2HRdtTSjlYkjiVkzPP8YMzQrLXJDiDPmNiWmmllYpFWqvl8AkVmdOcmxQE0Cd7kDzfRC+J0pljNlw2WsaFRgazIzgSoIPPFl/Ieyo5zEEANWrNhjLLYZD0U36aGcg1aWHeu/ji7pmZ73ITVlmykag//vjjRaQta45my1FxRPrfzQcU/PzIYiKJhQwig920g1TnIMvAt7/9bU2okt7bCGBSONt3s7YTwJy5+ZCuXDnz0DJQaoggkLomEf9tKAvOYNGHaLKxQwDwARS/PTb/1C3G1Nz0mTnS5+Qg51VrQQvZ84ke84tmL4yyLjPR+z6AQgYwb+JTicaG+4iWq2llDcgtJIAgDa0m5IxDi0brVM9WytOdfN0T7g/3vu4+tNIIt+eE0W6pJZcoiHZVEk2wDDJNShvNlrPiSOwBgGwBUvsZUijkWggh7gq+dvAzn/lMkTCbkmyDpRkBHCwz1af9bDsBzJmbDxEg99caa6yhnjOPxe/CCy8snLKr5Cajj35whmh98OsKgzNEw3fHHXcUm/uKK66oKuUQQCq2iKlZ42EvvvhikcJkq6220rh9cc+BJoDik8bc+oQPmfHJHoSD32NIR0gAiayXKE0/XQpkELcLieZGO1iVZGkTwE5VLVIKhCROBqPw/eT5R13wgDv9pqnFI9dZaj736VXecAvP5+Zqs2JJNIFAzDOaLc2Wq+IIYyAACDmqatYW7SBkkP6iHUT+kHEOsGgAd9xxR/fVr35VE6qk9zYCmBTO9t2s7QRQcvORBiZ1SpEyacoRyMBzY3MOSnCGBGVACPDn8YMzRKuH2a8sOAPChNmKqDzNhqkZ8y8kUKvlIIA5tM6iAZw4cWJBuHyfPX4WsgcR86OtY8heGfY+AUSGOBR0StOByVM0g+CNJobUPrIZ9/LZqksAYmWmk3Yu9vMx14E/gSbdEif/+W9Pu+/85T736huz3Oh3j3KHb7eCW3q+OSZOIdGiVQ21WdIHKqZwLdpYzUaf7rvvPrfxxhtrPqa4dwqtJvgje/SbzAyYfXEvQav8ne98pzik95JD9YFGPMAIYARIdklnBNpGAEUD4yNy/vnnFwsxi6h2o4QRmjJNPzbGwCbGuEjMKhoWNHi+Ro+fpXKGkAD5DhaxZICKI5yiCdDQbBBAzMxEHGu1HGmBtAigr7lFS4aWQ2Qh1OxB5mPnNwbrKgTQvx8yySYsyZTpk5DBTn6DEECu1/Jr66adi8Ei5hqpnEGgTDcXjfueecV97Q93uYefe9WNHD7MHbjNKm63jZYttMiCG/OMFlH8LTmMydxSMxnCveaaa8Z0q/Y1zMeDDz6oVp/Z7xhVYLBIpNRqUjaTIBDmhUTwZDQgGvgjH/lIbUxyfNAIYA6Uh/AzjAC6wlSKM7ZmPi4RoTBiVku0xMzIqZYNIAzO8AM0mgZnYO7DhEIyaM1GZRPIwQorrKD2GHCCaFKuT6sJAWzinylkL/TZE80tpAJ/MjQaqcleGS4hAWRDpS5slebnzhO/QUn+C7mR0mDagQ2inSszz1YZT7drq1TOeOX1me7b59zrLrj72eKWU9Zc0h3+odXcQvOPLH7vVJ4OzCBK4EqpRs2WK+E0Y4DUYs6ljnLKxnx/61vfcjvssENR13js2LFF3tF+bkYA+3l2BkHfjAA6lys1C+Jw0003FRUzUmmxxHmfhd4380EAaRKBqRmcgbkP8znl4DTbLbfcou5rmCMvZNUAHTZwMeMK4aOfzL2vuZVoXLQ/mIAx/3GwydFSEEC/n77fINolNNWMD3lGS8PvWoENderaVsW4auUM8PjVjVPdcRc/6GbOmu1WWvxd7vsfX8uNDSrOhOXpWBMgzrhNxJSnqzoOuT5XwmmeRw5A3qHUpJbKMt/73vfchz70obowRH3uqKOOcn/4wx+KikMcvgk8OeaYYwqzc9VmBLAqYnb9PAi0kQCigWGhlJYrNQvPg8Sg1UAzV7V1C85AyxNGa+JjNGHChK71TKv2oex6EiezyWiflvE1xCxYB7vYcQ40ARSyF2r28Edifn2fvW45FAeSAOJbhUxU1QB2myPxG4QMkmIGX1RIDRphcEnpryXauV7m2ViZKruO8eAPTLBRlb7f+vhL7oA/3OWe+ecM9675hrtv77Ca23Hc6I5dgWSgLUMjDG58F79B3qUyn94640LeIIGakdnSL3wNWQtTrjfcb/z48e6UU05RqWbiY0oJyF133bVYmzlsHHrooQ6NOXkhq+adNAJYR1rtM3MRMAKYLzULoFMii028V8AEZh20HGFNXO4REr1OwRnkMmNBxidIs0lC2zon2Cr9isWuyj3Da3OU0JPIczZ/NEEyx5A+CCiEoEyzV4UoDDUC6M8Tmk1MxPip4geHxtPPN9iU1FQxz9aVNUgZ/sB1os2ff2WGO+iP97jrHnqxePwuGyzj/mPbVd2okcPf0R382cADc2ZMebq649H2y/T75Y+pbn/Dz0EAsWCcddZZ2bTm0gdkmWowHNg5dFRpRgCroGXXvgMBI4DOXX311cXLr1ljVoAv85fzgzOEDGDy47Qekr0qme1zaTYpzE7TdjTPEWwCAUQzQ5LmlI3Nl3tD8tCQsWFCXHyyJ9q9KnPcqY8DSQC1U4KQ2gQc0diEpAbyVuY3WGUusRCQronMACkDZfw+NC2d9uas2e6EKx9xJ131aHHbccu82x338TXdsosuMM9Q0QCinQ/9czuVp4NIoyHkAFLlwJEiMjd2jlhvyDOaMugMPHDLYc3MocX0x3r//fcX+w+uNFUDW4wAxkqNXVeKgBHAORUm0MgRYardIDE0tHaSeoXNgAUtjMTFr67KIhz2PVfSaU7kaCxTO2WH48kRbALxZvOfMmVKbVHwU+tIrj00e2himGPmHhJDygxIX5M57tRJzHE4yw+ED2AOAliW266b3yDEJjbKv6p/Xh1BQc7wByZKv0m78v7n3SF/usdNe3WmW/RdI91RH3mf22zse+feEu08fma9LA5Snk2gWHcAACAASURBVA6NKl/IpJBBCHWvZPK58g0yMNwLOCSldAVBdnAnYH1O7VvYbX5ZK4g05lDIulO1GQGsiphdPw8CbSSALHa8eNI0Kkz4ZbT8AA02FxZTFlc//5pG5YxcSafvvffewilbO9cYJ2Q2M8xZWg0yfuWVV0YTQCF7vs+eT/Z8nz3J1dYkSXfsuIcyAYxNA+L7DUJKwV9Mxd00XHX982LnhutS1s6dOu0197Uz73J3PvmyG+ac23vyCm6fzVZ0I4YPq0WWkGmpoIHPpVTQEOzKEndjlufd0T4Egh3rAO9VymwAWGEguoxDO6G9Lyf77LOPO/fccwvyVye/qRHAKm+dXfsOBIwANo/MFcf9MBKXjV5qpooDP6Y5Ttfa5lImOpdpG6dsNk1McpoNR2mIsma0MZsdvjg4aoeN+fTnWJJmQ+hDn71uqXWMADaTkjrJjcvyDXbyG0QGsApQRUerIUf4tJJ/NEWbMXOW++6FD7gzbnmyuN0mK7/HHb3T+9zUh+4tZLMJWZLydJBBNFXItmgHpTwdOQA53OZY17AEQNbqEKZOWEPIyf1HicEcrkD0g7yDf/zjH/9/e+cBbVdVdf8VSoDQUZoJLfCnhBapoii9K1WlqDTxE0FBlCIKIp8iIn6ogEiRJoI06SCINEGQTgJJUHoTpLdAElL+47fDfO6c3HL6u/fdtcd447V7ztl77n3OnmeVuUJ50HYW2mb9dgJYxt3Tw+dwAjg9MzdtKbNmyRnK0oz19RqV0arLWsaSrsu1jSwDLq2qZDl0e9aRbSwCiEafYvYUl8nvMdmTdS+rjmLaKi1FHkv9YQGEAODmJtuUsICq3M95CGCMZau4QZ4DkEW8AnkSNNLOGWsqLpeX9rh2n4urhywy72Dbb7XBts6yC9u/p8xjf3v8dTt4k+GFQg7AhvmVcDeeDjDjuUisYR0EEDUApLQgbGU1xkNMIfPCc7vKBmaUm7v88stDzGGRF1ongFXOVA+c2wlg88xc3JpJq56SM2Kix89pA/cJ+IVkVG0tY+lW4dpudEvw9g9OVVVm0DWryjZm8xLJw1UIeYLQQ/ZiFy7znJXsNcLLCWCxB2uZQsCSViITU3qDWO0h+5TRSxs3mHVEWI/ziGWnuc7jr4y3g/40vXrIrIPMvrT6gnbxI2/ZhMlTbb9PL2Xf+Ew5NbvBjvsG3Kg8w/MSxYF25enSjKHVZxCEpx54mTHbJLEQwsIY2sU7Fu3/fvvtZxdccEGw/sXKCTxrstbFdgJYdDZ6/HgngBbexCmlxIMrll2BqJGIkczELZKcURdZYlnXVXWEDRnXUNXZc2T/QcyKBGljwYCsxjF7bPbMv4g8MWYqDVhFgkYd9acHsgWwTAKYfPwTygCZwcrI3KeNG8y6jVSdKJOsHjJisXls7Evvhm7+cKv/Z19YY/GsXW75eSy+qkIDIWxVnq7ohUmewaVdpquWF3OSsnjmV5X5rXE3e6agQbjnnntmgscJYCa4/MNJBHqRAEIAcGOI7PEzmzIP+2QmLsSgzMbGwsOxarJEn8uuOtIMBwgTmYNrrLFGmVDNdC4kLdhk0rqZGsnriOzFlj1+JraQB3NVdXrjwahOMzIjvExU0fqbABLqwIZaRas63ow1gpUJIWueDVgHy9YbrNpNDu6ss+Muv9sufHSSTZlmIUuYbOFZBpmdsNMI22SFj5Y2PUlplrg8HYSQ3yXPw4t2kecqL7a4a4lDLKuRWLLVVluFF9kqXvrK6mfyPE4Aq0K2R87biwQQ1wu1K0X2eBjzQKo6i5UlhVwCG8qaa65Z+QpjE+MhWXVWW11jaiU3I7IXW/Zw18fyOiJ9rUiXE8B8y5IXKMUAQpZIDKqSADJPRSzBrUbJCyJxZrEorzJjITPcv1xfrs48hKZqjDQ+ngFvzbaQHXPbf0L1EFzCkME5ZpvFTt9tVVtjifnzTXjiKMIzeIFuJM2SLE8HvnhVhB8u9yykCwFtqoBAKMtq1P/ebbfdQgnFLH0p6/p5z+MEMC9yflxAoBcJIGSBN1I1iAV/q4MAUsiehwxlgKpudZROYwx1jUkJNDz8Y1c9pE9aismYvawWtqx1evPMoSyAaMBljflJez0sgCTnrL3ueg0rRKQ9T9rPcT9BikgCqZrcVFULVmNtl6HbKG6Ql0l05NLqDUIkGQdxhlU2iA0vgI+/O5v98uan7NH/jO+73LxzzGq/32PkTPWE8/SHl2pIXZqXTV4UpDeo8nTKKk5Tng51A57VZVY4IhOX2Dy5/vNg0B/HOAHsD9QH0DWdAJrVmZhBfBEBx1U/+FmidVTO4DpUteBrnXXWKf3OgJCJ7HENYrQg6xA7WXBF+srQUlSZtk022SRkNVbVrr/++iACXCUB/Nmfx9lfnplqh26xnO229hKVEsEkAeSeqmqNQ5yYp6pKD2bN0IXQQOhUp5g5FRlspjeIFRGyUfWLIO5SJEZ+eNNLdscTb9gCc81mb74/uW9Zf3SewfbHvUbaYvMVC0XAhQoho5pGloZllZAYCCH48RIBCRQhbPQCh2YeigNgW1b7y1/+Yj/4wQ+MMJNuak4Au2m2OrCvTgDNiCnioT9y5MjKZ6jO2CySW3DLVCmcDGBlkVoe/rFlj5+x7LEJQPIgg7hnePiXQfYaTbYIIBpwReKU2i0kCCAuxqqyTB996nnb7pz/bmaLzTeHfWuj4bbd6ovb7LPOXDO2XX/b/b9OAgi55HpVEUAsyhCa9ddfv92wZ/p/LJMCoSGhAFcnhDC2bhGCQujEWmutlfkaWQ5ACWD4ssvaWQ++ZZc/9JKNn/Rfz4fOs/h8c9gl+6xh88+V/4WHl01IG9m5eVur8nScGwsj9z/WOuKNcR2X1a6++mo77rjjwktzNzUngN00Wx3Y114kgGwePKjVeBPHFVF1EgPX48FPfBQB5lW3OoSTGUMeUhuTPcXtkYGH9SRp2RMRq0NvsA6RZjC74YYb+jKNq1gHzMkx146zvzw744a/xIJz2f4bLmOfW3Uxm60EIqhNGysOP7NR83OV7k0IIJYjQgGqaCQCoDlZ9B5tFDeoRAiwYo6qjgVGCxSizHXfnTjZrhz9H7vg3hfs2TcmzADdQkNmt2u/sZbNM2c+EliFNp/K08myqvJ04AZxLlOv7+KLL7YzzjjDiC/spuYEsJtmqwP76gTQgksWBfiq38aZfh5mZMyVVQGg1ZKqSjcveU2wY8P/5Cc/2bA7kL04OYOfceVC9pIxe62sbnVI6NSh0VcXAWROzntmbrvln6+GeaFM2LQPZ+jgzZazr62/dKYnEqSFeWP+NJ98hzSzGbNh4w7FMsPncAFX4UbnBYq+VEUAq5BoUdygXMVYt4mXJGkC62BVluA777wzZM1jfVSbOm2aUUP4vHtesLuffrPv7z/bbgXbZpVFM60JfbgKbb64IzGZ5nkNGcTl3Ko8XZaBnHvuufanP/3JbrnlliyH9ftnnQD2+xR0dwecAFYbw5ZcHVgacS8VLQKfZtVBNGlpZVPSnLPRZ2KrJgRAblyRBMhALLEj0peVHKD/xjmrdNXXIdEiAoiLEQHxou1rf3jQthyxiO348Y/1ZTCKlK++5jq202n32FOvvRcug9FvoSGD7Zr917MFhrS29jCXSbIHyYPgaQ75DvkDNz7PXCMLRIwbf2OThuDwVZbbHgJIK1JBoRXmdUi04P4ldIKXIAgnYQ6QGXBqVac461ohXg7ReeapUXvilfF2+FWPBvfvGbutlvX0fZ+vQpuvUWcgglTPwHIqEWostjxflFUMflm1/E4//XS78cYbjdCMbmpOALtptjqwr04A87kw804lDyvcJVWWmVLfWsmm5O1/fJwIAlnNkEAIXUz2YuteVrLXqH91aCjWRQAJOsfFWJQAHnbZI3bFqJcCXCsvPq8dtsX/s3WXWShYtGWVffLV8YEEvvdh/Bc6cD/ediX7/Br/jdeSSz4mfMwl/WMe47nEcpVscQwgVi6stRAPyaZwXoiiyGARixfZ4FiAqiSAVeoYgh3kj3uGl5lk3KBcnRBCXLeN8E57/95+++2hQk+ZCRONrq1kE+a3ygZWxAASP6uKHc3K00EI+Urz7Pn1r38dtB8pz9ZNzQlgN81WB/a1Fwkgb5FYMtTqjMvjrRVpBrJMq25YSiBpq6yySuFLQQaSlj3ODUHAsoN0BuLWbPJpHrh5OlSX4HTVGbqMHQKIy7xoIPtF9z5vP7xmxszFTw5fyL4yckGbc/yLfW7568f8xw68+OEZYN/94wvZ1ksNCvOq+EuRPRG+ZmWxIMo0vnM/8QWJhLxgQWOu4qxw/icyyP8hgCKDWXXgIGdYeKpKbiIjtcosZnAjox08kuUTW8UNQgizJiZVkTDR6N4l2YT5gHBV2VhHWDURUW9k5YvL0zGPaIGyltuVpyMBhJcWSrR1U3MC2E2z1YF9dQJYb1weVQYIzN5ss80qXw15kibkyoMUxHF7IntYEmJrEASBDZ2MYx7KVba6BKerTtAAI9xN6623XmECyLl+ffMTdsptT80E/eoLz2JH7bCmfWzI1EDyTrr9ebv6MerDTrMp04gINNtm+XntsM2G24ILzN+UXMRkj5/1JQLId16osG6ryg5EhhcCNmlIYbxZY7Fhc1aFDV4YJJuCy7idEC+WbaxiVRHAOjT60M7kviGjvVlLxg2CLfef4t7SWI9xlyI1k+azRe5dnmkIc8exhkXO1+xYXkSJa8SD0m6dcA4+z3yy3nC187IqMsha07o8+uijw3ycddZZVXS7snM6AawM2t44sRNACw8G0v+rJjCsKGRNcMtsscUWlS+wdkkTCupPWvZ4y8YqE2fjYtlrZg0Cv4ceeqhyt3ZdyTrdRgCZx30vGGW3/uu/yR6BnJnZTstMtU2XnC2Q9iHzzGtH3fKajXpxvJEN/Nwb74c1uPlKC9svdlrF5ph91kDuYmIXEz79D3IHGeFLa0dyPawTviACWPl0DOeEtCXJoEqGQQbZqGmKhcP92cjKAwFkLS677LKV3EP0hXjTKnQt1WFeZnjBwk2etsV6g3HcIHgxv40IEUkNJOMUcbmn6R/izHgamsUapjlHms+wznA353lWNypPBwmEUPKyzPo85ZRT0nSjYz7jBLBjpqI7O+IE0MKDmPgPtN+qbryR8lYOAUzzBlukP3HMXJzBGWvtxWRPlr1WZK9Rf+rCr66KI2XF57WaOyyAlErLK2Wh8lqy0v771Tfth3eMt9cmTrfs0VZYYJCdt88nbL55hvSttZffmWiHXzHWjtx6BRv34tt2yGVj7IMp02zNJee3k3de1eabc7YZSBtkDzdavGb4HQKWtAYnkzw4ln6y8epn9Q1ipy/9Te5PCBhfWAqlocd3vYAg1ovVsCoCSEgILuwqRZo5PwQ6b3hGmrhBsIcAEmqQtSJO1udOXbGGeFAeeOCBGcr0Ze2rXnA4F2tp//33N8IKFl100fDzZz/72WCZrfr5nKffyWOcAJaBYg+fwwmghQcxMSybbrpp5SuhrlqzxHRhAcT1wds/GzibRmzZk4WvSJA5gNUV11hlxZF44st0zzZbUH/961+DZSYNAZTWXpygAea02Er70oTZbI8/PGKTpkztu+yBGw+3b3xmmb7fYysef7z7qTfsgEsesXcnTrFlPzrEfrn9cjbXtAl91j3uDTbCJNmDUGTdICF4IoP83IoM0k+uLcsg6xmrIq5ixRAOHz68kvu1DpFmXs4g0mWUn4zjBrGiYinEegppxlpKslFZGdjNAK8r1jBrlZa0C2SfffYJ80GMJS+A++67r/3iF79Ie3i/fc4JYL9BPzAu3IsEkM0FIqZWp1u27FJjjIXNMRmzx3V46PN/LCVs4JCNomSv0aqvK66xrIoj7e7cota5dufn/80IYCutvZiEYa1tlDxxyf0v2BFXjZtB82+3tYfa4VssN/1vH7p46QPWaEjW6Gdfs6NvecXemDjNFhg8zQ5ZZ4it9LEF+kgfLxBZyV47DGIyGMcUNrIMci42Z5FB1joElLJjEMKyrVtkUGNtrlKkGRcz9+2IESPaQZXp/3pZkBVVcYOKsawqFrCuWEPiTNE3baY5mgms6MN77bVXyMg+4ogjAoEGN1zrZTeI8vHHHx88TqgnkHW8/fbb576ME8Dc0PmBIOAEcPpGWJdbtojQsB7uyXJpkD3IXWwNghygmF9Vjd747mFzJgZo8803r/Sm4oGJ6wzXaZUti3Uubz9uuumm4GKEpMuyJ3durLUXu+WbaZvFcXtY2I64+p9BGmaOWafZxCnTXcKbLr+AHbbB4vb++Hf73LmxRfj9WeayI//6kj39+oTgBj5ll1VtjSUXyDu8TMdlJYPoaCrzGELAWo/lZYqSVd03VRJArPMQjSo1OllHuGaRy8FqmjZuMNPkffhhXM3cl1XVtlafGEcVEj277bZb0GY9+OCD8ww/9TF//vOfw7OStbXjjjs6AUyNXOMP/jfgpeCJevVwJ4AWrIE333xzyMytwkIWry3pzPGwafWwjN1+MeFT1YXYGgT5a0QOsJgRbF41YarLgpqn5Fye+1rkrGzttFhrD5kR4tj4W6y1J2HlZuswKb/y4UtcGKb+9877E+3L54yyJ1+fYIsPGWT/eW+qTbVBtuIC0+yANeayJRZfJLgHkxbhN9/7wPa7cLQ99PzbNsdss9jxO46wTVesVtctOT8ig4wljhtU8gjfidvCKkkVDUhOLC8jQeVFFlmkr3Zs1jXAiwZfVZaGJOkAAl5VPWPGLMkUnjWsJ54dEChlX/MZZRQX0RtUrGEdrmZpTJadoLPDDjsYX8QA1tVYy24BLIa2E8Bi+LkF0Cw8GHH7kQSSVWcrD/zJJAPJPcTZuLgg2ABjy57cuGlV7usiTHVZUNuVnMszF42O4WWAN/QiGY1s7nG5NH7G5aeKKMSZIZvxsY99rGl2dUz24mzcmOwpI5e1o6xcCPlbU+ewX46aav+z9kdt0QXntR/8+Wl7/4OpNnz+Weyry39gH1toXoMk8RW7Bd//YIod/Kcxdsu/XjMEo4/cennbec3/CkaXhXGa88jKp+8ihcS1cS8stdRSM7z4cB/H8jKQHmUUx5If7a7NixNrDRmbqlrV9YzpNxZGrE2NJFPAkjUpt7riBkUIszwHwf22224L5S2r0gDVPFQVn7nVVlvZ3nvvHb7qak4AiyPtBLAghr1oAdTDUdDJKoe0QNnxRMnp4Vq4GAlgl0WIzZu/i+zJ7YdrKy3Za7QM6hK4ZvPABYQLuEh/2y3lusaTlQCyAcYxmGysuMVZS3HJNEiLNtbkNWKyJ4LXiPQRbxnLr/A755T7X5Zh/jZx8hSbY7bpVTtGv/C27XvBaHvz/Q9sqYXmsp9utrjZe68HwgQBhAiSBcmamzx1qv3vtf+ySx98MRy732eWtv03WLr0OMB286341jj5RUkpuDUhK7FlMF57kEZcniI4/B7Ly7Sy9BM2wXFVlhysupwd2PLCgT5fO3WDOG4QCxsYq2oLmLWLAZWrOa7O0W5u8/6fl1oIetnWWUjyd7/7Xdt1113zdi3zcU4AM0M20wFOAAti6ARwOoBVaL/xYGWDTsbsQRjYaHG7aMNmEy6bPLGJ4S7jzbzKVpcLnfFg/aGGbpUNMov1B6tRssniFlv3mGMsHzHZ4+dmmZdymXENPpckeiKAkMiY7PEzxCVJ9rhOmrg3SsJ97fxR9uJbE22ReQfbGV9a3ZZecI7gQoVc852wBMggMXW/f+A1++3tzwQIvrDG4sEaONsss1QGvepIxwLkim+NxccVOpFWXia2drGGWK+xvEzSatWsSkeZA6+6mgl9zauZxzzwYsB6wGXM+lISSSO9wXbVOcrErSrrLKLsP/7xj4MbuK7mBLA40k4AC2LoBHA6gEUzP2O9NG1gbNi0pGWPwulYF6pWzechPmbMmMKaWe2WWNmZzc2ux4ZEBiCWhiobCUGU6IIAQu5isgeZh4QlyV4zWZSkZU/yJ4jPQvhFtjhn/KLA2uHYmOzxcztrTDtcXnp7gv3P+aPt8VfGz5TsAaECY9yffMeK+MDbc9vp979pU6eZbbT8R+0XO42wuWafuRZwu+sm/8+aSQqQq/ZwmvhWnS+r1qDCLUR4IdmSl8HaBdlJU6Uj63iTn69azJrrMTaeNcQA5m2N4gZFnhU3mLU6R96+cFwVc8OawKJ48skn25Zbblmke5mOdQKYCa6GH3YCWBDDXiWAvLXGkhhZ3H4iezExkGsKshdbKxpJdSAFgP5X1XUz66pwUlcMZZWENk66gTRDtLCg0OLs6lBRo4ksSryekkkM+h8PfSwszA1EizWkutQQLkgnRIRrVmEVZjy4gff/42h78MNkj19+fmXbcPkZJS8UTwdRunHcK3b2P80mTzVbdfG57dQvjbQFhwxO/eThfomJNMSP3yFb8b3CmIvGkGXNKGaOlURCv9QHxl9lDOC4cePC+KvSMmRyeCY9+OCDpb0wyZIqvFjHkGcwQ9amnas59YJp8UGS2pinvALajU7NuJDjOf/88wuR5azjcwKYFbGZP+8EsCCGTgCnAyirT9Iqp80rjvGKxXFjawUbdhpXHMXMyf7DrVJlg1ygmk98S5VN0jZVx1CWVXOYBz5Wi6T8ipJuICdLLrlkSNBoROCFZbOMXP7OOuA7lq7Yjcs6iusqi+gRr6WapRBM4vH4qkq3jWSP71w6xm577DWbddAg+9/PrWA7jFy84TIBl1vHPGeHXfOUjf9gmi02xOxHGy1sKy+9eCAAceiCiHTyfuEzjcSkq16XsZtY89VMa1Cl1ig5CDFk7iHjSpRJc2+nHQ+WbFzZyyzzX5HutMem/VxVosm6PhZGWYy5Z1SnmOdaUUt1szGWKaAd38cQ8euuu67S8n9cD5xIAKLxgnHCCSeE5zPWVJ45WZvrAGZFzD8/AwJOAKfDgVWOrEzeypOuuEaVENKSvUbLDfcf4sxs8FW2uip0KImmnbRN0bHmtWhC9kRImmntSVgZctDIQtuM7DEm/Q+ykYz5hNix0Sdduc3qKkMYiVPDOqgqLnGCRlEM4+M/mDLVjrpmumYg7bubLmtf/WTzTeixl8fb/5w/yv7zzkRbaK5ZbL+Vp9nic013U0vSBrILDsk4xaoIQVo8mlkGGyWRYGVCXxDcJZmCdVZag83q7qbtC5/DyswzBCmbqhpr/ZFHHgmVQKpssjQut9xyM8QNKqMYvMqKb65CP5H7d+jQoSFjmhJwVTYMDY1eyPfYYw8755xzMl/aCWBmyPyAGIFeJYBszLLM8KAkuJgHQaMg+7I3r3/84x9BwmLxxRtbXMpaoXVV6KC/VSTRJHFgU8al1cqiGWvtycInixsbkb5aVUWBAOIS4q1cBE+xezERTJI9lZJKujWzSGrEYxYZjBM0ZBnEOlVGYzz/99cn7Ky7ngun2/MTS9jBmy1rswya2blCfx574VU76IrH7c0Jk+2QkYNsvlkmBRkb4YNFkM2Uzb9qTc28428kL8O5RAYhgFgAVaYtjoPD4gWZUUZx0gKatk8QM0hyHqtP2mvwwoSrueyqGcnrc58hzq3kLOEFVnzRCHcBM+6pZi8/acZVhXwO9wD9Aiuyy7upOQHsptnqwL72KgFkk1eZJDZs5AV4G+eBXKarp9GU33PPPWGT5KvKlleg+Q93P2dDF5jTNlohvYsabUM2mrKISSNc2GgIat9kk03Cv9tp7YnssdE223SSSRr8jnQGFi0IOpsWx0LuZBlm3cQZuTHhq0pGiLHGCRpYFWM3cdE1e+adzwYiSNt2tUXt6G2Wtwnv/XfMsbTNLHPOY5NmHWKrL71wIDHgA27gA1nFegkRBzv62OlkkL5DWojFhNSTaMCYqNIhUqj1CHnkRUTyMhwXZxSnJb0QJuI9KWdXVauqakajF7Nm5dniuEHWL9Z4SLOsg1lrFFeRPa21yrxX/Uwue66dAJaNaI+dr1cJIOSIN3ltnHfffbcNGzaslgcAJIaNscqHP8sYKycCrVtssUVqUvvXcS/b/heODpUgzvzKx23tpRdMdUdUXT6NjZbqDGw0iy22WIjfa6e1l+x4s4zcZPIGlhOkQPiuBA3WihJ8RPggYUWJVypwEx9qRAZjN3HWPilu75J7n7Vf3P5SyPgdscA022fEIFtkoflnSIJJs2FzPogURBBCyDpULB3fiyZ65MGs0VoQqZelmD5D/CC1kP9YBghilySDjJMXAdXdhdxgSZJkSqtxjh49OnyWZ05VDcJFxZF11123qkuE82YhmoobpG+8MHBPiQymCatB1gpcCaEpqzH/PIvpU9WJeWX1WedxAlg2oj12vl4lgGzsclsx5XWRMq5FYgYPGtzAVbY8As3EhX3rotF2yz9ftXnmmNXO22tNG7H4fG27WWb5tGZae2zOzBsPf1n3Wmnt0WmRu0YuXP7H238ySSMut4f7ls+wybHBs7l3klUrlm6BiGCBjN3EjcigYiLjRA0lwPzr3cH2f3e9aROnTLORw+azU3ZdzRaYa/a289/qAxArWQYhAKx9VSGpiwxyLyTlfBhzMsNbcj555GV4qRQZZMwQSMUNJtfpqFGjAvGp0uJEX0iaoOZ0lS0r0Xzk3+/Y8I8OsdlsuuxQrDfYLm6wiuQZXlRw/bI2CffppuYEsJtmqwP76gRw+qTURcq41kMPPRQITJUZgFxHAs2bbrpppribCR9MsX3Oe9DufeZN+8jcg+2Cr65lS3+k9YMR8WS0tLKWT5O1KI3WHpYv3LNUHGlk0RHhi8leLL/SiOzxN9zWcdJCo9rKsVWLcAGOExmE0KR1/VX5CEjq+EE6VMkB4gzRBWfIUDzmOAGG/j343Fv2jT+OtrcnTLZlFx4SBKMXm2/OUroOSZJlkP7gDoSwgmUa62KaTjSqzCKNwTgsIEulnTiJJH5xbJZRrKxuSBiYy9IF8YVk8AzgZzLNq2pVAaMR4QAAIABJREFUlU1L9jcL0Xzujfdt5zMfsEXnm8NO2GmELfPhcyVt3GAVsZOQZHQ/uUc64T7Osh6cAGZByz/baOOc1ouwJC2APJAhAVXqcgln3D+4O8p0YzSawyICze9MmGy7n3O/jX3xnRAPeMHea9li8zcnAc1kdOJ+ydUYl/bCCkWTRIjcq40Sb3hDR0JHBJDzxZsxP0t+hQ1Flj0RH0iAMnJ1HTbmrEHpIoMQQcW7yQULGSwr4zHrfRlbTsEYFzZkj6bkJsgWLvR2lrfHXn43VA15+Z1Jtth8c9jvvry6Df/o3Fm71PLzkCRICl/0F4uZLINpYymZC9ZFvKbiyixp4kCzDiqr1iAvC9LOw5LM2mZ9Mg+8BGZ12aftL+uTUAbqWlfZuAeIn0tzHUoSHnjJWHt1/CSbe/Cs9r+fXd42X2nGWGPFkyrOMo4b5G/cY2WGzyDKjbg866a/7t288+MEMC9yflxAoFctgJAjHsJqBGVDDpAyqLrxFou1o+qMM+nzkTWbx7ry2ruTbLez7rOnX3vPllt4bvvD3ms2FQAm1nDVVVedIXO2ldZenJHbKvYnjtvDegQBJEMXi5He1qXVGLtyIQWMOak91474ZJ17xYGJDLKuRAaJ8apqQxHxiatpKDElWX8YgoukDBs1GyhubYgg/QSfZgTkhTepGjLKnnrtPVtyobnsmv3WqawUHGtF8jckWdAv4ajSb8yNXLkx4QOL+AVCZfiqIlbxGmlFBrl+Mm6Q9cFckMzA84f1KDcxBLjMPhMzy7qsUtAaLLgOX2nr877yzkQ75IpH7f5n3wpQfmWdoXbQxsvY7LM2LjMYxw0y77wcYDnFup0mbrDdPc3L/3bbbRfmpUz82123jP87ASwDxR4+hxPA6ZOPLhcP4+WXX77y1UAcC+QFMegqWxn6fC+8+b7tduZ99tLbE221ofPZ2XusYfPMMdtM3YYAEs+krD8e1Gx2uNlistfK7dYoI5e/xV9YGrBqYD0SqYU8MHeNauRWiW/y3LJciAyywUNisPTklQv58CWtj/jEGpWK24sJX7vElLjCB4QL3ES0GpHBN96bZAde/IgdsNFwW2upmWsjV4EvFjPFDGLFhLBCYvk7lnu5r7WuqqqYknVsIoOyTMfhB0o40wvB/fffH0gM+MvSxfVieZmi7kjuE85N2ckqGxJazFeW60yeOs1OvPUpO/uu50PXPj5sPjt+h5WCa7hVI1ab+WYdYE2VPiO45dUbJKxkr732ClZMJ4BVrpTyz+2VQApi6gRwOoBoQNGQfqi6kcnG5lDHtcrQ53vilfHBEvjmex/YesMXspO/MMLeH//ODOLKWGZ4M8fqlUZrrxXZE+nhO1a/2LKnKix684f8sRlgRYFosRFUZXXLsi5EhLG68QU5ENFqRwYZT2zZg0zHsYplER/6FFsGIVlKIInJIGOpemOUWz0W7MYlxwYP0Ye4QvqTVVKq7leWOY8/205rkJhjksBYE1rvWD7lKmYNxPIyWcMUOGcVdXMb4VHkOjf981U74up/2rsTp9hCc89uP99+RVu3hfIABBD3L+uUNcELggg0a0hJJFn0BglfOfDAA0PGdKeup2br0C2Aee9QP04Pnp6MAUy6gHHJ8NCV+GuVy6POa91444223nrr5dbnk9bevU++bIdd/2+bMHmarb7QVNtv5By2QCSsjFUT66k2tBi/JNlLZuTyWf4mEWdIgEifMnJjrb3Y7ZOMx2MOy7C6lTn/9JHNXWSQc8dWN8WwifxAeiHTsWUvT6xiljE0IoPqYxmVL5J9UXhAnInMZ2KXPdeNYwGTwtjKeKaf4NOpm7cyipWIw5gpN0cICC8ujeRlIL/KKGY9xPIyaYXFuQbrjtCMKhvC2byk5L3Os6+/b9/501j758vjbZZBZt/cYGn76ieXaChGjoYqcZPJMprJuEFeFsAsjd7gn//8Zzv66KODF6jbmhPAbpuxDuuvWwCnTwgK8zw08j7EskxrnddCnmWdddYJG2S71ih7Mtbae3L87HbUTf+xD6ZOs8+v8TH7ybbThXJplLcjgUbl7RrJr+hvfD7eDGXt4m+Qu5gEZMnUTLpg2XiV9FB2fFU7LBv9PyarbO5s7PwNiyXjxOIj617aTT5PP9odIzKoBA1ckbIM5iGDELeY6MWZyDHJbVV3OdlnZTzTR8U1KoEkTx/bYZL1/8xrMgaWlxrVROZ+xAUcu3mbZRTH8jKcg/FJazCOj0z28ZlnngkvUqusskrW7mf6fBn1eVEeOOb6x+2K0f8J195guYXsmG1XsPkTEkRUUYI4t9PrAzNZU1l7rC1hlowbvOKKK+yXv/xlUILotuYEsNtmrMP626sEkA2EjUntqaeeCm+xWeJY8k4l9Sx5MCM9UHW7+eabQ3ZeUp6lmdYeMUnxpqyAevXzxnEv2wEXjQ5iwft8aik7eLPpSTM8mGNxa7kN+R5n5IrssTnizot12FqVZ8uKk6xuisdjcxUZbJX4kPU6zT4vAhC7cvlZCQsaN8fjxoLIqI/0sxNIDH1jnRBrJekWCIssg41ItUhuMisXN26ckduqOkvWOZCEiJJc2vUx6/nTfD4muRq74hXjGNhkdjt950tWQl2rGRkk1EKWQax7EBvFDSaJDcQMIkTSVJWNZyf3cxkhLZc99GIggpOmTAvqAyfsuJKNWPy/L6+8aHIdwijSNjwLhDqAWzJukHV48cUX27nnnhtqAXdbcwLYbTPWYf11Ajh9Qnhb5iGRNpOtyDTyYGbTrzo7jz4S30KBc4hdUn6FjTLelOVya+ZKkwXv0gdesCOuejRAcNDGw4O7BjcQxBbLFcSADV8Zm3Jpxkka/Fx2Rm6zOWFzBW/IIESL64oMZrE6tZpzxe3FGMuiGRPqZgkLyT4S8yVXdh2ENc16jskgmykkBUsMViiNnxcbWlLWJ62sS5p+tPqM+ijrJWtZlsF2sZdpr819EEvPMOe4bGOSqznPksiRVV4GzGN5Ga6vjGLwh5hxD5ZBzFphQ+wcfVlxxRXTQtjyc0hPfeeycUYW+uBZB9n3t1jOdhy5WPA2oAKAlyb5Qpv2wsm4wW9+85vBEgtOvCyn8ZSkvVYdn3MCWAfKA/gaTgCnTy7xMlgQ1lprrcpnG7LEBppGNytrZ9icIFwiIoyLxsMzjdaerhfH7cVZuPyf38/5x3P2fzc9FT5+4CcXtvUXH9RXnk1afJBBrBOUu8r7wM46/nafZ5NVTV1IgmrqkkACOUvTYoumcCZ8INYYZLx5LZoiMRBW1omSM+hjf8a6xVYurE98yYoOGWTMlFDjqxMSccCRPiqjmHULQYIQZtFrxIKkeZZgOedOSs+USXKzkkFld7NeeJEFfyXQQJiqnI/HHnssPBPKVFB46/0PQnLIrY+9Hm7J7VZb1H6w5XJ2711/Dy/OZRA1MOYF+fTTTzdqwzPPG2+8sX35y1+2L33pS2keBf3+GSeA/T4F3d0BJ4DT5w8pA8hS1XUzuRZZc+hmFS3RxEMX4hFnTvJzLA8CiSBmBhLWzrLXivTRb4hlnKBx/sPv2o0vDDKiAA/51EK21jIfsb89O8H2/czw4NZiM2KcWN9EDth8+zO+Lb5b1UeIP6QQAijLoGKrktYexq+asUm9vSrGFSdnQGSk4QcZLMt62egJxnWTVi7FgyZfJFhXzLHcxLK6gSVWt05IzoizssER4srLCX2MK7koNEL3FARS2cdp5YzK3hGakUEljySTSGRNxjKnmudyE5MYkcUqmWYsJLVBMMvWUJ06bZqddddzdtKtT4eQk+UXmdt2GfaObf2ZtVO/rKXp/wknnGDowB577LF21VVXhWfXoYcemubQfv+ME8B+n4Lu7kCvEkAekrgt1CBKuEzImK265SWbquEaWyPYyHgbjjflOHGCuBYIYCw3ISuevsvCp3Erfi1ZI5e/61py5x5/6/N2yQMv2qyDzIYMns3emTjZfrHjCNt6lUX7YMS9AjkAYzZWNlwIDNaYPPIWVcwPawFiAGFl04dosampkkaj7NS6iY2sPIp1w+XXru5vGqzieMXYhc34WsWDNiOOyngGT1ocM1ilJSrNWLXmWYfKysbyI+sdZC8OjdD4qyD3afsbf66dvExMBiFmNNaI4gZZz7G8TBlhGMhacZ6qKhvd8/SbdsgV4+z18R/YnLNOs//d5v/ZVquWV0Lvpz/9aXgpP++88/JMSeZjfvOb39jxxx8fnofEgZ900kkhUS9PcwKYBzU/pg8BJ4DToWCzwpXxqU99qvLVkYZsyu0UW/fiGq5ptfYQOUU2gU2gkfwKm3+jGrkScY6TNBrFr02ZOs0OvmyM3TD2FZttlkGGwOsCc81uV31jHfvoPINnwlK1YCFabLaQQFyGWVxyZU2QZGfk1gNriCCB+mxo/J8+dqr1Uq5sNne5splnXgBaNUn7xGurmcByEZLL2ootg/yeVguxrDmOzxNnuYvock8x35A+CU2zFsERq1kZBKmKsXBOJY4kk0hEAnmexcRM1myRQSy6WGiVHZunWhD9QAKK9VdlbfOX35lo371snD30/PTSkXt+YpgduNEy4ZnDuChZ2E5Eutk8HHXUUSEp74wzzqhqqvrOe9FFF9nuu+9up556avA2/epXv7JLLrnEKEfXSEKrXYecALZDyP/fEgEngNPhYTPlQUZNyKpbkmw22pDldkq625pZzGKJFX4W2aPMEQ96SBZWN45P1shlE5T8ighflvi1SZOn2n4XjrY7n3wj6HjhrqG+56++0Fx+IpZEgRCDgdyvVbgNFbcXW7gUt5fU24tdZEnrJS40WS87hRwkXdmxWDIbMy5rkVy+x9I+sWWzbNdgfB+JDMbxeFWSwWQsrBI1mDOSlOLkp3jcYKUEEn5mvlmXkKROsQI2ej6JDHIfKSyESiDcS8gzJd3EnIPPiQzyMsBaEBlkDaVt6Ofx0oGwdZXt/YmT7NDz77RbX5xeMm7NJee347Zbwc7+x/N2zSMv2+93H2nDP5q+3+or7l7WxYknnlhl98O5IX2E/px88snhd+YNYetvfetb9r3vfS/z9Z0AZobMD0g8mHtSCDrpAsZSMWrUKNtwww0rXSBs1sQakjGLhaHZhswG1YpgxPF6sWWPvysJg79zfsXhyZ0JCWQTZHMQ4Svqih0/abLtc94oG/XC9Dd02gmfX9m2HDG90kGrpvgsiCBfkkOBtOZJeojj1yTDwmaucnEifIw9y6bOhilXNiQqdmVXSZ7a4af/i1Sz8fNCQ39p4AmOkBkRvrzWnrR9aTffsTC2LIMQwrz1k7FgxqER/NwoUYNxp7VqYq0WYeWliftFGcX9iV+MrV5swJMx813WXOaceyjWCmwlL6OMYp6FEEBlFLeLNSV+jucJRKbKhoWWLOAPFl3ZjrrucRs/aYotNGQ2W2DIYHvy1fds0XkH2x/2HGmLzTdnpm4ccMABYaw///nPMx2X9cP0H1wvvfRS23777fsO32OPPcK8XXnllVlPyVru6WpoPT34zKulwQFuAZwOCg9P6nOSBVZWi7X2ZIGBiEAW+B9v5mk25GZkj37G/4OUxLViVUpLJI+HD3GEvPUrFo8NgodfGQTm9fcm2Q6n3muvvDspQDj/XLPZtfutawvNPbMruBnGcQYsmy8bLRa3Zlm6il9LStzEWc8aP3FeZT0vwVoag3Jl112Krpn0jOov8x2LEJsLmaH8nkxyKWut5z0P8xfHDDL/rEf62YwM8hlZNTXvkDXWd1WJGsyxLINck+vQRwhhmdm/7YizxKVF+CCm0u6kTxAx1nt8P8dJJHpZ1IuBCGF8XdZMLC/D+UUGG+lT8uLMyxCJZlU2xo4O4EYbbWTPvP6+HfSnsfb4K+8Z9sAFhsxur7/3gS3zkbmCJZDf07avf/3rIU6aaiBVNmK/qZfOGOJYcyyQ1FK/++67M1/eCWBmyPyAGIFeJYCKfRMWPEgRM95ss81yLZBGWZOcE8ta0o3LgwzXLA+yZIsJHf+Taycme/wMAUnWyOWhH2vtScS5Eelhw4TAYB3EMshGBhlk081Lki687wX73+v+1ecGpp+brvhRO/GL+UpRqdqD5FCk5s+GG5cSU7xiUm8v7ziyLIDYlY11UKXoWhGYLOfXZ5OkBwIfu3LbxYTSL4g/WCKGi3VICSStqknk6WveY+JMXbBk/lmXCglgvetFSrIz8b2VxZqbt48cx/0iMoi1jD7InV0mlsmYRVn3mDvNN4Qvy4tNHnkZCZVDCsFdGcXSVeRZxvjR06uy8cyCJOm5+d6kKfaT6x+zqx+enmw0x2yz2MTJU221j81rZ3xpNRsyeNZU3SEmjySMww8/PNXn837ICWBe5Jof5xbAgpg6AZwOIA+X22+/3bbYYou2iDaKL2okgMtDmg0hSUTYvO+9994+a2M7+RVl/8q6x7U4JimsnKwy0HYgH1oQOR9EEHJAw5KVx/16279etaOu/WcIyI7b8TuOsG2irOA0/eIz8QYo3TllbrPZswGx6fC9DAtm2n41+xxzwhzJMshmK5KVJa6R8yTlfVRGLJmVm4f0KOMZkgUZZB2pn3VZs5phqDmX1RI8+RuN9Y2liTnPExpQdH4bHY9bT2QQLHlJERlMqyvJeWXJlmUPoivrXquYxSJjyiMvQ78UN8i8MB/0E/cv1q0qG1ZfvDQbbLBB32XA7Y/3/duO/+sTNnmq9b18fmr4gnbSF1e22WedHi/Yqu28887hxf+ggw5q99FC/3cXcCH4Gh7sBLAgpk4ApwMIyUIUFAIYE7ZGm3FSa09v48lSTPHUxCSPBxnZuQiaJstpYV2IiR4/xxm5IgDNKkoUWQ7SD4MMsqlBBkQG01o23pkw2f7vpifs4vv/3deVWWcZZDcfuJ4tPO8cTbuXjNtT0D4EJ6m3x2cbycqw8XYCEdSGzmaephSd4tfirFzJ+8Rjz0Pw260HERjwlF5jXa7NVokasSsXsoe1U/F4YCM3cX9kjzfDVFZW+onLXZnZrMtkHF1MdOPScbLuifRlse61m+tW/88iL6P1DfGDDBLTzFxKXqaq7GnuD9zNn/70p2cYyml3PGMX3v+iTZo8xd6eMP1lgbbVygvbz7Zb0WZpEya37bbbGiRw3333LQJhqmNJAsHaiPQLDdyXXHJJoyKJJ4GkgnCGDzkBzI7ZDEc4AZwOBxshpYB4uCQFcNtp7SWnoJEbVw9N3fSItEK0aCKOWCHjjFxt/mwedRObWMiZzYy+QAYhB2msTvc+/YYdevlY+8+H1sBNVviInbTzamG8ItWx/AoP92TcXisXtjCXKxuihdVM5dM6iRiIWKsUHW40aTWy1uJsZM15lizsgo+AvsO5B6SNB3nVnINpGUkPzRI1Ypcm12xFemRlVT9FBlXdo+77pBn2iqOTyDj3jO5j5pyvOCMZwtcfc96o/1nJIN4Mng16ZvCCyzwyJ5DBsqzKPC8eeeSRGaS6WA87nnF/iAWkSYpK49p5zcXtB1ss1zKsZfPNNw/kj2SMqhsyMFzntNNOC0QQGRhqEaOlyLM1a/MYwKyI+eedAH5IQmJ5DDY83mZpPKjj2KJWD2aRPRGbRjF7EBs2BK4XJ2mw8bMx8H82XywGuLf4KmPDLWupixhAWLMkj0z4YEqQh3nprYl2zheHzzD2JKkG71YW1HZjScrKKH6MjSmL+7XddbL8Pya6MdllvokNhRAx//QR91kWl2GWfuT5rORvIDD0HYJCP9NWcmmWqMEaT1r38opDiwzKMsg6jS2D/UUGWXtxRrJi9yB8rHvmnn5ynyc9AHnmqspjmmkNck3wZS1DAKkCwksXTYlmPE/BQbG7jLnIGsfFjl5eUqyf58xVD//Hfn/3CyE5JNn2WHeoHbzpsk1hQvqL+L8vfvGLVULZd24kYCQEPXLkyCA/k7cClRPAWqZs4F6kVy2APNiuvfba8HYqqwsPl/XXX7+lkG4a+RWREZVNk9RL7M5U/J6saclKFDxMy8zQLWsFt0seUb1YEV3G/v77E2zuuadnaIpYQ6rzbvztxqLM0tj9qkziKmPHYmFpEb7Ylavxy5WbphRdu7HW8X82dEiWKrlAqOUm1vpVUk6cjc38JuvlprEe5xkTc45LMq7uUQcZFMmPY/eUfa+sXL7rJZLnDhZ1xQ1CoiQt018vKmnxTpJBfud5gA7gCius0FDMnXsilpfheauM4qz3IufBc9KMLFE67tZ/vWbn3v28PfDcf+WoGN/WKy9sx22/UsOhYok77rjjDFdwtzUngN02Yx3W314lgEwDbphY/+6GG24IBFBvqWnkV3SemOxJ6iXWm2MjTOsKwTKoDF02VjZbyGAnbRDK2CT+hzd9fmczk1UrFtpl7P0lmpxVVibt7ZmU+JlOdN8PVtw8Fq5kli6YyeKWdt2k7XuRz8Vrk/sHQgcWcSZ2mpjYIn1od2wjMqi6v3wvYhnUC4409/jO30R049i9dv1UaEBcQ1mkVRm27c5R5/9jF74Ir5LRkFGR16KZ1iA4YcVTjKQsoYyZNdPuhZDnzNNPP52qhjp6pKfd8azd/vjrAaI91x1q321gBaT/lGOjCsimm25aJ5ylXMsJYCkw9u5JepkA8nYak7ybbropPFx4M+Xv0syK3bxsgMkaubhB4nq8bAaNsn+zrjK5uJShy8alpIx25b6yXqvd5xWwH1v2lJnK2CECsoDlSR5pd/0y/i+LG+QaawL9VlxjK5IVj10WrmYSP2VYuJSYQT/ZaLO6X8vASudIjp3+SFRbiQ3cE3yphBobelWE/6hrHrV/PPWGnfnlkTZswbnaDlXWeFkGeaESyWpHBpNJKhq7vAbxS0478tKuo1xLcisQJIUwKLax6PnbXT/5/3jsysCH8OsFhzXJl5LRssrLiPwqo5jrx/IyjUg69wMi52uuuWbq4Tz56ng7+87n7MfbrtjwGMaJ9ZJybLz8d1tzAthtM9Zh/e1VAogbhgeutKt4EKADyHesbQrITZI9Hswie3rrLxK7lnY5yHUEGeShyear8m5lkI5kP4gBi+PW+Fljb5WZmkweASPhWUU/0+KX/Jxc7mwqrAORLOZd1k1l5SoTO66L3EziJ29/mh1Xdyk6iUuz6Wv8sYVLpCeZqKEazxAtCKIsbpCtolVmhM3fH3/NvnbB6PAriZ27rT3U9v300vaRlELjjchg3E/Nexy/F6/5LNa9IutA/ZBlEPzpp5Iqilgwm/UrjluUdY+/JS2baWKTs5JBjVdkkDWojGK+a/2gowcmqCeU1bg2JexuvPFGW2uttco6bW3ncQJYG9QD80K9SgD/8Ic/2N577x1q/+62227B8ofGFJYL3C/Sm+OBhzhynJ1Z99t4I/LCgxAyyGZVNF4wjtsT6cNSovrAeceeN3mkzjuNTY6XATYXBetzfciq5l0xXP0972WXomskXh5beUT2ssZrcg5Z3CCGsfu1CBmcPGWqbXnyP+zfb03sWyJzzT6L7bnekrbXekvYPHPMlnrpMHaswMw7LwDcAzRl5vIMUGZuf8577M7GMsh9WRRPzhlXFImturLs6Z4vOnaRQXlU5E1RbeJkjWKRdJFB1g/3IS8SPE94PuGyLatxPbwA9913n40YMaKs09Z2HieAtUE9MC/UqwSQ0jvXX3+9XX311SGzjA0A689WW21lhxxySIjXw5LBRsaDh/9hLeTBWEeFibSrDVIAEeSLfqqiR7N4wTg7UxYeNmyIblJvr8hmnex/u+SRtOMt8rnYraWxy5WrsTPv9JUNSO5CNohOkpUBgzyl6GTVjS1crOU4ZpGfy7TU6h7iPmKtQl5UMi+PJevN9z+wz/7m7lD2K24LDpndvr7+UrbLWkNt8Gwzi/9yf2vcsnBxL8SlGJlvXgbUT+6lMi2YRdYux4ocKetZbnf1s5nbXfGqcuWCA88KvAiyamatKJJnLFnlZbiG7kWVr2SMWOyYl7TapK36Sp8YO8kllObstuYEsNtmrMP626sEkJq/bHZY/ogp4UFwxRVXBE0mNnusgrvuumtQuIcsyP3A5ohLM1lkvb+ntVm8oKyZsuwpbk8bX5paxGWOTRaNMiqPtOuXLAYaO9+ZZ+nOaeyN4jW12aqfHKc6up0k3aF+KuNZpehEXFQ+jbFDcFQnuD8SNSCD6meSXGchg4++9K7tfOZ99sGUaWEJDJ51kE368OdLv7aWrbTYPDNpeXJtxe6J9DSzbIq0QrQgIHFsY5kvRe3Wb7v/x+LY9BlLGWSQ8dFvEV2eX+AbZyXzcxbM2/Ul6/+bycs0swxy/scffzxYa5kDxoaHQhnFecNwwIkXEu5zvndbcwLYbTPWYf3tVQLYbBp4IFx55ZX2+9//3kgK+eQnPxnI4Pbbbx/eOHkT5WGBpQByBRHkodsJG4NKxrHZ495ig4Ag8KBXwgObRBUVJfIsa/pGVmCy8ggPYvqYpeHKjckOmx4WEs4TB+tndWfK8hJX9QBPZWYnKzxk6XNZnwVHxiotS75DfmmQHhEYcOiEdRrH4kEIY/0+LIRp3I5XP/ySHXb5uD4I559zVltz8Tls75VnD5a+2Lonwpcmfi05J0l3trCsqtpF1jURWwV5NkEE+RsYstZlHeyUe77R+NJoDTKeJ598Mgjlr7TSSiFEh2ccXzyLmVuRQV7s0nppeP4svfTSfXHAWfHv7887AezvGejy6zsBbDyBPESx+hErCBl89tlnAwn80pe+FJTocSnJ9aoKFKpLm/bhU2Tp8AAU4ZE7U1VEYlcuD0aRVsUL0s92GZBF+pbn2CzJI8nsTJWNg9zE7swq5GeUjANxAVdlPOchrXlw4hglasSuXCVqxLp7vBAoFo8NVBbMLBtk3j6mPS6OcQPTdmXe+Lwq9fzytufsusfft0E2zabZIJtv8CD7yeYfs7WXXTSQnzREMm0/+VxMBvm5jqznZP8kxRLrDvIZrXvILvc8ljKJePM/aQ2W4TbEFilyAAAgAElEQVTNglnWz7Yig88880xIRFtxxRkzevkbRI77EULIvIsMgkerdcAznvPx7Cwz9CHruPN+3glgXuT8uICAE8D2C4GHEkHC55xzjlHKhw10l112CZbBZZZZJrx18yBhA8M6hFUQkpXVitWsJ4rhibNS2YAgH7Erl59bWXiS8YKyYnWSSxMMkskjWFrZ0GnKypaFJyY8ddVN1Tw1k5WBDOaxNjWaf1l4YrKnuZdLDwxaVauR5IZK0bFGJIzdCRZMjVthDHGZN15UcO8xBq1/zf08881vR//tDRv94nsh7m/S5Kk21+yz2olfXMU+texC7W/sAp9Iul+rIIN60RHZ47uSdOLYvVZzCLGR6DSkkHUiEe+ynk8FYGx5KPcXfeZLYRw8V4kBbKY1yNqQJRxCyO+Sl8H7kXR7Y1Uk+xecyn5hqAqX+LxOAOtAeQBfwwlgtsnlQUHiyLnnnmsIR6Mij1Vwhx12CPFVvIFKqoUNWhIoaXXRmiUqKIYnJnx5SUajeEHFNRYp1ZQNycafTrpyefhDCGVVZQNTubz+jGFqZJmBuEi7D9IqIee0c885k4kakB5asqJG3rlX9it9lQVTlsH+nntZ95SswNxjxaSpTrTWqV50Xnl3on3+9PvslXcn2UJDZg/JIdSD/cm2K9q2q9UT05WUwIFoiGRlmfsypVga3V3cR8w5c4/FjOeVLIN164o26h9zHZNdXvawyikzmXsA0so60RfnaUYG9ZxTRjH3Viwvw9yMHTs2CEBDMJ0AlvEEr/ccg+q93MC7mhPAfHPKw4UH6QUXXBBcxI899ph97nOfsy9/+cu2wQYbBFcFZADLIG/tqv3JAyh2EcdxexJZTpuokK/nMx4lQgBplThyXbp9sTtP1h2JDCcribDhsyHUkTxSFFe5Xpl/+qzMV9ZATFpjq5YsfJLfiV3ZVVnpWKPMuYSxIYAig3W4CpOVJVgDYBKPnc2fjRp8lEDCuoG4qM7zqOfftt3PfdAmT51mKy8+j4158d0whdR/RR6mjpAMrZlmZJC5j12MjCFJeFRCLrbuVeHKpq+KoeMZRgwd8w2mzH9V6y2+r2TZFtnnu5KURPhaZSY30xpsJS/Dc1hkkJ/R/qMR8417uc51UvQZo+PdAlgWkj16HieAxSeeh9mDDz4YrIJ//OMfg/sPFzGWQUok8bCBCEJe+Kwy1tgseCvlgRtb9vi9P95G2RRifUGIC2SwrHjB2LoVk93YuqWSea0exmUmjxSf/dZnkFwL5IUNTm56sGDDryNuMc0Yib2TvAiEoOxSdM1c2RAPER6IX7u1z3mUkEN/aRCXu16ZzW576h37xU4r21l/fzbUg6Xtse4wO2Tz5WwWlKNrbtJt5J7iRQAyx3gh3qx/7jdlpMci03UTEeaeFwHw5DtEVRbMsuJFJcMTxy4ylwpj0PjzJCnlkZdhbk499dQQ0jNu3Dj7xCc+Ebw4fC233HI1r5T8l3MCmB87P9JjAEtfA7hZrrvuOjv77LPD96FDh9qwYcPCGyZJJOgMQu74HJsB/8el2WkByJBTJbmwUWWNF9QmJ8sWG14j65ZKSeWdiCzJI3mvkee4WHdOdWP5G/NMn2lYhVgbnRiDKTIYV0mBaKVdp6yZeLMHA1qyskTa8zWaAwgE/ZNlkPIgiy+2WLAMXj72bTv+r0+Ew7ZZZRE7ZtuVGuoD5pnbNMfoZUcWLta/rFOsA4Uy0NciGKTpS5bPSBid+cdaBiGTZTCLBqqsmxo/BJgY3WTsYtkvulnlZVB6OOigg+z73/++XX755UFqBl3Yukl4ljmKP+sEMC9yflxAwC2A5S4EalVC9EaNGtUXcA3JwdqzyiqrhMSRTTbZJFgCY2sbZEDWtrIfikVGSD/ZvCGD9JcNQSXoFDMWu3JF+LB84bpLZuXmecNP2//+qjwSx67F40/WjFWiRkxc2GhV4xkyUIf7LS2efC5NKbrYuifSxwtELMET143Ncv20n1Wii8qncQ89+v68dtK9b9qUqWafWGbBkBySpVpIlmuz3mOhZSxM0lwU6ZEUC/8TwYYYEi8qi1snkUFlvIsMQorUzzi7VuLysTs3FpqWS7dVve20WGf5XBp5GV7Sf/rTn9rDDz8cTg05r/IZFff/mGOOsWuvvdYeeuih8BIAflmbE8CsiPnnZ0DACWC5CwLLx6WXXmrrrrtuyBDmockGOWbMmJBFTMwg7Ytf/GKIF0TTKra28QYOEcAqCGHopDdRxQs+//zzIYichxYbLSSB1ihRob/6r8ojcr2qQgoB+kX7FAtMi/A1G3+71RXLyrDRYhVWhm6nZWnKpcnLgLJRwZK/V11RpB2O8f/BlPUJGbztny/bGePMJk4xW37huez0L4+0ReadM8vpZvpsKymW2J2dJgEkluqBDHK8SFbeRJ9Cg2tysAi2iCvPNNaqktZ4DsTu3HaKBFX0sdU5G5FB+n7mmWeG0B2SQepuRx11VJhvnqf0wwlg9hmoP7Ajex87+ggngPVOD2+YZA/z0CGbmPqTWAUhhFgCeAgQLygyoKzH/toMknWCITzSG+RNGTKk+qT0FUtmp1kwiySPSIInlmGB8GD9jK2bRV3ZrELIP/MOaY3j8CAE/TX/jF/WLWEAucaao/mXdp9K5nVSdjb9//u45+2Qa560tydOs4/OafbjTRe1jy83LNULVizFIutmVimWtE8Y7iMRLLDuBDIYJ6vIwqdkFc2/knJYp42kVtKOv+rPQdxHjx5td955p91111129913Bzc31Z6eeuqpqi/f9PwYBr797W87AcwxA04Ac4AWH+IEsCCABQ7HSnHhhRfaeeedZw888IBtueWWIXFk8803DySKzQBrC3FOZA+LYFW1wcauvDgrt12d4Ebxgp1YNzmZPMK45M6WvASbcEz2wKE/EjUg1iKDbLx5ZWWyLk9ZN+MyYpyjWb1grRlJ4LDJ8hIAGYQMdMrLwDOvv2f/c/4oe+6NCTbv4EG270pT7f99ZHDoZ5z5qheeOH4RYo5FK45fq9pVmySD4E8/q34Z0AtPsm4w3gi5cumL3LkKERFx1fxjcS8reSzrGubz9IsXv3vvvbeP8KHlyr1Mwgdi/uuvv36Q8ervKilOAPPM8PRjnADmxy4c6QSwIIAlHM7D6tFHHw1WwfPPPz9Y2HbeeedABlddddVgYVNCBhs0m0AZBEtkJxaYZjjJOsFpY3fieEGsWLjAZMHsNHemZHqI2YTwsTHQf232MeFpVCu4hGlPfQrmCTz5wvokWZmiG6xit0R42fQbWTfTxiWCH2tJSRmcX6QFAlvU9Z4asCYffPXdSbbvH0fZ2Bfftblmn8V+tOkwGzbb28HaykuVkrN4MahDiiXteJqRQUhW2nuz2bVid7ZILzjE409bN1ikS2RQngGVo6syto5r4znBsqcv4vpIsqKcJ18QvtVWW61fayA3mgcngGnvhJk/5wQwP3ZOAAtiV8XhEBAy0yCDV1xxRZAkwEUMIWTDZ4PlQYfFBSuECFY73TZZNqSoL1euAtVF+tJu9u3GzuavEnRIS3B+WdvSxEa1O3/W/zdKVMGVxQaqWEssmSrxVbW1NWv/9flYVoYXBenhpbG28fKQzMxls4+tW2z2ZcxPLNfCWu2EUnSsyRdffcMOvfJf9uCLE2yWQWa7LTvVNh4+d3Cxgw9rgntJxLUTBJLjtaLKHmDKXMoymIYMMieqGS0LX+zOloVPMlV516gscCqdByHk3pJANhbiomuM5yTZunLn/uMf/wjlOkm0g+zJwkfVkDpfPL73ve/Zcccd1xI6ZGficnZOAPOvNCeA+bFzAlgQu6oPh6RdfPHFwUXMAw7XMGQQKRnepiFYkEFcyVhYJODMA0/1UkX42NjkylWt4LoCtZPZuXVkPCcTNSQyHJMdaQ7G86hyecnkEfDtFHemNljFNkIGIDdKHmF+5ZqNCV/SuqfM3Ko3yP4qRQdZiitLyJ1PCbmzxnxgtz41Pkz9dzcZbnt/cslAFKSJB6a8uGC5Fhns70opyedNsswb61l95cVGQuMxBlj8dA/IyldHfGmydB5kUFVI2rnTFYdImIysezwPGf/aa68dyB5fEL/+llTimYxFuVUbPnz4DNI/TgDz76ROAPNj5wSwIHZ1Hc4DEH0qKo784Q9/CFbAL3zhC8FFvPrqq9sTTzxhuDIhKDzgaUnLTiOyU1f/4+vIgoVLm81W+oJZNMaS/W6XqKENL0uihtxZ3VB5hL5iZSGbkM2e3/nCrRlnpZZl3SuybuKsZzZLyIeIaxGCFbuzZd1SZQllp/Jd8V5Tp02zX9z4hJ3zj+fCcHZfd5gdmhCMZn2qdBpkEGugCFanhTTwwsNa5YWQlz3mHky0BuJyalXFEKddF8omZ80q85m54aUW5QTF6kLysPDxHfLHZ2J37pprrtlvyVFpx5rmc04A06DU+DNOAPNj5wSwIHb9cTgJIWeddVaQk0FrkI0IUkU9y5/85CfhgcgDVnFNWAWJF+y0DUsuQukLpo0XlDUgTtTAEiYZijh2r6ibSfPbLnmk7nWQJLwqo6XMZDZ4XG6sFdyZcr23CxOoexzJUnSsUZHBdn2NhaYZv4SWNf8QHoh/uzVw9l3P2vE3TheM3mrlRezY7RoLRnM9kUHuLcigEkja9bUKXJtlJ4OhysexBsAFHCTm3B99bTV+yeCgiHD44Yfb0ksvHQgs5JAqSnLl8n355ZfvKCt80XnFZY335qqrrrLjjz/ebr/99nBKwn7Shh64DmDRWejx47s1CSSPiCYPTbSXzjjjjGAp4aHy29/+NjxouqXxcOBtH53BkSNHBvLHG/Idd9xhG220UbAKbrPNNoEIYrXAIsB3Nka5iNttinVjISKgesRxX3HLKUlFpI/NWLGL2vDryuTrj8ojsStTLv2Y8DYjO7JgdZKsTLO11agUXZz1qpCGWIpFQtOycuaNX73m4f/Y968cF2oJr7v0AnbSzqu2FIxm/SnRgQ0cwqUaykWTMprhE7tzZeEEs9i6CQ5Jd6qyyelv3Ff6219kMJZj4dnFF6SajFzG8NxzzwVdPp5vv/71r4PVbyC2PffcM8R6J9stt9xiG264YaohOwFMBZN/qBkC3UoA84hoEpx77LHHhpsOV8ORRx4ZFOB52FT14C575emNPj4vxPbpp5/ucxFD+HbccccgNE2MDBsFJAAyyEYqUWSkZaqO/8oyflkFcWWyIcidjWuIGDxt9Fg0+tuNxbgU2wi2ELMypHpi657ITuzK1IaflfCKCECy6atiRssIyM8yx2k+iwUb6wgWN36msU4hWsSOCYN2sWNprqXP3PnE63bAJY/Ye5Om2IqLzWOn7bqaLTzvHG1PIVyJGcTiWlYNZSXsxKXkuA/kyhXpzxKXyjllxYQM1uHSVizqPffc0+fORZqFsfASS2ZuIzkW7n8sYxtssIERM+etMQJOAH1lFEKgWwmgBp02foIHEa7Q7373u3bwwQeHw9kIeRPmHLvsskshHDvlYAgE1kDiBalIAtnDKsj4kESAAEIEIQJsqsoiTutyKHOcrRI1pDWGG4tNC8tbGfGCZfY/Plfe5JFYd5DNPnZnx/F7ZUpoVCUrkwdbufRj3TnVjWUNsC4lVcLLDwQQ12sVxHXsi+/Y1y8YZa+N/8CGLjCnnfGl1W3pjwxJPaykdmNa7T5lqMfJGqx7XPqx9l5W0t+q40krZllkMCnHgnWPl2yevXF2bifKsaSe6A76oBPADpqMbuxKrxDAJ5980pZddll78MEHg2tBjTdMuRq6cf5a9RmyR4FzyOCtt95qn/70p0MW8bbbbhvcP1gBIIMQLDYAxYqVaVlR/2LLFhu5NOfierHa8JNWjWS8YBb5m7rntFXyiGpCx5m5rRIV6uh7nJQjEV/WQVVZzxB5CF4yM1VCw7LuNbLIK3kAiytxYtJDhAyWZRF+9vX37X8uGGUvvz3RzvrKSBu5xPy5pkEZurIOx1U9IPO6B4RDLDYt4l/FfdhoMI3iG1WOrl1iTjM5lpVXXrlPew8LX91yLLkmrQsPcgLYhZPWSV3uFQJINhkxfxAeNjg1SrBhCbvooos6aVpK7QukBLcqcjKQQax/O+ywQyCDvJXzEMeFBTZsTEVlWmTV0SaHpbWsRA3FC9JX3ESdHNsIYSE7m/griBZNsXtyZSr7sdQJz3GyWMQZ0kJTXFuRDG3FL8aVRWJXpiSJshI4aczRV3BW9RHc8FnPlYTrtfGT7LGXx9snllkwB5IzH8J9QFwb61V1s+kjJJt1AOFT4kYpFyxwkiQZhAASQoJrG6sd/b///vv75Fgop8ZLDKEmElvuBDmWAhB01aFOALtqujqvs51EAKsU0exlAhivOixxPLSJg0RjkE1o1113DWSQt/S4rBtkSy5iiSU3WsF8LhaYZrOvI1EDlxsEAEIrixD9xTKUJTaqjLtSQfpxVQ02Syyr2uDBCaur6vwqKacuS0/acUIGiWcDV8grhA23K/1tFSogKZbYuicLZ1xZoszKKoox65RSdLE7V25tCKqSliBUrFvwlUtb1rZOS87iHqZG7mmnnWa/+93vAlnV2sWboAxd5FhYw50UT5x2rXf755wAdvsM9nP/O4kAVimi2Ysu4HZLi42JQGvI4F//+tdQIxMiiHWQDYtNCksbJCCWExHhE9lRcfhYgqXuRA0sQiqXR/9EWOhHFRsTxCZ25cY1g+NklUaxe1Ukj7Sb67z/h9SRVATR5v6MpVqwYsWEl5+T2cl1WjhjK6bEsVUppapSdLoX4hhGMJMrW2uhEbmTS5u+YiGvMr4xzfzTb5LJ4uoaVNtAeYBnA255nqPEGKOccP3119vQoUPTnNo/UxECTgArArZXTttJBDAP5lmTQEgAIRGExqbNBjGQkkDyYMjGCXlCZBoXMZvAdtttF7KIedDzwIcQQgJxB9EgAljatMF1ShZ10npVRrxgMm4NogOJi6VowCGPZStv8kieeS5yjMiVMrTlyoTYQFzkyiyjjFiRfupYxY2qLjEvAdLtK+LSVtKOCB/EjTUWJ2vkceeyDtRXXqhwZcsyWGYCUIwtFj4SNGLCB9lfY401bL311gvZuVj5wC1+iWLMf/7zn+3zn/987Zb2MtbGQDqHE8CBNJv9MJZuJYBpRDSpt4jsCxYtGjIwP/vZz2aQgRk9enRXycBUuUQgdyTJXHLJJXbllVeG6iMqMQYZ/OpXvxpIDsQZwsgGIktbkU21qjElNfvSxAsmhaaVmau4tdjKWTTWLB53s+QR8K3KitkKd9ZC0rony5aSdSCBWAX5nKxXvFBVRVjyrpO8pejkXhbZk+C23Poifbz8lGllVtk0CCEhGSKDxDnmxVZjQYJFhO++++4LBA7rnty5aPF1ConPO9+9dJwTwF6a7QrG2q0EMI2IJg/ls88+2/gsTULQp59+enDf8YZ7yimnBIX5uBGn9a1vfctQp+cBudNOOwVB0lbxT436s8UWWwQ3Sbc0XL5kShPQzaZAbA9YkEnMOPgdSRk0BiElbPy4iHFhYQVB6oE4sU6xBsa4J+MFlejCJo7FJSY7il+MZVjyWPfyzrsqj8gihKi3MrSrqOjC9bBAgYHc2rEUi3BoZtmKs3MhL8rO5XuZJDkvnvFxrUrRgXOMAT+DTdKdm5eE5em/kl24xyCDYIplsF3ms6z6qp3L91iORQkbJHbUOZ48GPgxzRFwAuiroxAC3UoACw26zcFbbbVVsHAR/AwZ2GuvvQIpovxaswYB5CEN4VRjQyH2qJsaG0fSmsHfsPScf/75IZP40Ucftc997nOBDKJYz+f5P2QQwiiRYTaqTiIAsu7Frjb+prrJWFroe93xi63WRxWVR2KXtggf65xxx5Ul8hB5yDT48sU54xi8uhNz2t13kCtc2rHgtCy9rAWILy99ndJvsOUZw5cyn8eNGxcq//CCQrxeTPieeeYZW2WVVWbQ36PUWpnWynYY+/+rRcAJYLX4DvizOwGccYp5oI4YMcJwlay11lrhn1i/tt5667BZYOVq1CCAbKZXXHHFgF4zECZqEJM4AiEmBmznnXcOZHCFFVYIMhGqOkK8lMSbqwrCb0eeVEYuJjpYsiQ/wmYIaWVTlaUNa1t/lclqNZ5GySO4iCFZrYh2HLembG3mLbZsgUmZZL0qWZm8N1ecoRxXWJH+IN9xe8dZ2ipFl4cI5+1nmuPk0v773/9u3/nOd0KfWcf8HReuYvdw60JinfClQbU7P+MEsDvnrWN67QRwxqk466yzQpII7lA1NgY2AWLjFE+YnEAIIOQPVyhkZ+ONN7af/OQnIX5noDYsPASDQwavvfbaoBNGFjHB4WCAGxGrIIQQciEXcdVuTLnxsJhAdGJXbjPrXtLSxjEQQchVp8lzsJ6aJY9A6nAVxlmpsRSLsOgvlzYZ5eAJceWrqgo0imGMcQC3WI6mWYZysrybRJwhhP0h2aOQAKpqYOHj+wMPPBC0A0nWIIQFXEnWIonj+OOPt69//esD9bHj44oQcALoy6EQAk4AZ4Tvpz/9aSA0uFPiBhE4+uij7Rvf+EZDvC+88MKQGUuN4SeeeMK+//3vh82NB3aZlpVCk13hwWw8f/zjH4OLmMQaLKYkjmyyySZh/PwfMsj3NMkY7bqalKKB9EFIZd2LK0pktYBgxZQwNm5CxQtC5jvFHSh8ZHGFZEO45cKH6MqNWacUS7t5ayUrk9fqKtd+nKwB+eelLa6dy/2Ydy2Ab9Wl6IRdLMcC2eOLsAvkWBS7h3UPi3u8HsEBYsi4qcThbeAj4ARw4M9xpSPsFQKYVmT6sssuy0UAk5Mk3UH09SBBvdLYhMaOHRukdXARQ9SotgIZZFOCpMlFDLmCWGMZJIu02ebcKEkhad2T2HLZZJvrSF9QGdFYBvsjMzcWGZaVE2sfLx6MX32CCGERqjp5pOiaxkpHP1kPuDEhqpJqaWVpi8sKivRhtZM7typpoqpK0cVyLCJ8xCV+/OMfn4HwJeVYiuLvx3c/Ak4Au38O+3UEvUIA04pMo4WXxwXcaBKxHOEG7lV3DBv8X/7yl6AtiKwMsjzECkIIsU5BALEKQrAgf6o6ggUjGbunclSxDEvZ8hutbsRYXxDrINdWZm5ey1W7Gz92YypLORYZFhaNyJJc2pArrK6Qw06tPAIOyfjGWFYG7EV4Fb8nwelYf69s8t9qfvKWokvKsUD4iDdmPOuuu26I3+PL5Vja3R3+fxBwAujroBACvUIA04KkJBA0spA9oUFittxyy5ZJIMnzkzCy5JJLhrjAbbfdNu3lB+zniKmk3jIuYrBFIgcyuNlmm9m//vWv4DaHMGNloSkbk1jCqqx7ecGGXGG5grhiuVK8IDFieSU1ZOWMy6jFbky5tPNkpeZNHsmLT5HjRLSpnQu2Eh6H5EIKtR46RatOhC5Zio7+EwdMv1knys6F8BEiARnHnSv9PZdjKbJqevdYJ4C9O/eljNwJ4MwwIgPDA/3UU0/tk4EhIziWgYlFptmoiQ9ELxA3DWTm0EMPDTFZaG/hivM2HQEwwc2OXA41iWls8quvvrqdccYZIW4SwoLFFisgpBAXcSfG39F3xeCxyWeJF4RENspQLkOKpdVaU8UJ+ktyCC54yAjEqj/iG+XOjeP3YkkaLK30GStmLCvTKmSgv+41WSrvv//+IB3FOsYqydiQY4HsifC5HEt/zdLAuq4TwIE1n7WPxgngzJBjefjmN785gxD0iSeeOEPGYiwyzQa1/fbbhyoaPOwhLJtvvrn9+Mc/tksvvTRk5eGKg+ScdNJJwb3TrN16661B2mHMmDG2xBJL2BFHHNEnZF374qjgghtttFEgyGQvggMZoffcc0+wlA4fPtx23XVX22WXXQIxIb4tru8LUQFbYr06scXxgpABVUmhvxDFWGQY8hdnKNdt5VTlEdYlGNOUmVtlfCMkLiZ74ABJiiVpGmVqi1xJw7Gu/rZaZ/SJeSXxQhY+Xmp4HvDCSBlF+sv6xhJ4zDHHDKh7uRPvwV7rkxPAXpvxksfrBLBkQKPT4fLcfffdgyWR+J5f/epXQUqGDGMITrI99dRTwVKw77772j777GM33XSTffvb3w4SK7hMB0LDSob7LtkgAmBDvCCb6aabbhpcxFhjsaDiQlbVEZIeIIIQlk60rmLde+GFFwKxwuJJgywwbrkwIXx1xjC2IzK89JRdeYQxQ+Lj+D3mX0krIn1Z3bnJ0m51yMpoDlmHuHEppxbLseDOVYYuoSOsSyU1YeG+5ZZbQhwmzwFv5SDAPXbYYYcFKSrWGVnSeBak31rOVTr7LE4AO3t+Or53TgCrmyIe9lQQOfnkk8NF2Liw6lFmjqzkZONhBtl75JFH+v6FNQyLSTeVlCuCKKSBDGqkeEjIYezoCpJFTJF6MCT+DjLI/3ANQwb7s+wYrr5kCTElKbDpSxQZ8qAqKZ1YM5d5g7ziboW8Zk0eYW4g8rH2nty5sRxLmVp66q+SXSCXSnYpmpzDeKimodq5sRwLFmzcuZ/+9KdnkmMpsv792HQIcC+RJY1HAWkuQkUee+yxUMqSr15pTgB7ZaYrGqcTwGqAhRSwGeECxj2stscee4QNkqzYZPvMZz4TSA6WQjXeaLECQjB6rbEB/+1vfwtk8E9/+pMNHTo0WAUhxWzyxLBBVCCDEA25XLEsZdV7S4ttLMWihA2sD1ix4jJqjaxayXhBxd8Rz9Yf8XftxtwueYT/x0krcufGZK/sCiOt+pxXVkbnZA3x8hUTPsmxQPiUoetyLO1WTvX/5wWaSii333579Rfr4Cs4AezgyemGrjkBrGaWICUQFjYTNg81kkNuu+22vgSI+Ooo+hM8fvjhh/f9+brrrgu1PiEZRS0a1Yy0nrMSXwcJxEXMQ3+DDTYIZJCaxLhSIchyEWNhUtWRomW80kixQHiyVgvBNQx5xXKVjBesirwWmSnWHwovuzwAABjUSURBVJmtqvELYcX6JneuSB+/d0L/JeYdCzhDRrEUY4UVkUeCRYQvlmNRsgZW/Kwu6iI4+7HpEKBcJ2ExqC3wPOVZu99++9nXvva1dCcYIJ9yAjhAJrK/huEEsBrknQBWgysbN2455GT4wh284447BjLIZs3/sdqAP3FtbPaQwXb1cultLMUiy1ayogRWvjxSLM3QUJkvyCBjgeRLX7AoeS0yA8pSjt25/A0SBckTMeYadSSPFBmLyuZhTSccA/LACwPrCKwhe4rfI1Err5RPkT76sdkQ0L1BwtwXvvCFoKV44IEHhnhrvCy90pwA9spMVzROJ4DVAOsu4Gpwjc+KixjrDVbBiy++OMQBUYuYTGJiLeVyhQziLkanT5InWKlikqMYPglOxzVj60o0SeoL1hkvKHeuCF+jLGXiGZOlx5LJI3LDV1HvOcuKYm1QPk21c/n+9NNPh8xzxkC8GGOGPJCtz7rw1j0IYOUn2YP7X+2AAw4IRJC57pXmBLBXZrqicToBrAhYs2CRYsNB+oXGpoQ4NBIzzZJAcPmiHagGoWGT7ZUkkLyzgYsSKRniBcm4xKoDdsRfQkYgNCSXEDxOQ3oEAsBGEpO9JMnJ25+ix0FYJdHC2BQvSNJLURdrMo4R0oeVDFdnHL+HNTLttRolj8gyWGbSRyNck3IsKqcGbiRhybrHd0g1Y+IYPkf9auRZOlVaqOg66o/jf/SjHwVd1LhRtxhCXlZbaqmlgoj87373u75T/va3vw2Vl8gO7pXmBLBXZrqicToBrAhYs1D5AnfEaaedFoggyR1YqngQYo0i1o+HFRYsmmRg9t9/f9t7773t5ptvNt5qB5IMTHVoTz8zGzuYUov4zDPPDHF26LHxHfJ0yimnBIkOyB/uXVy6uIiLVPGoekyKF5Ren0rmpSUtkDOVkpOFLy4pJwKcNY6x2bjbJY8UxUvVQiTHgvYe4su45uPqGkk5lqLX9ePTIQABJPmNOuhquNWJvyyr8XJHTGqcBHLQQQeF2OrYKljW9Tr1PE4AO3VmuqRfTgCrnShijiQEPXLkSENQWlpge+65Z3BLIf6sxs88yMaOHWvDhg2zI488sqV47G9+85vUQtOcG9mEZINYYK0ZKA2rH+X7iBNaaaWVQoIGcYEQE+oQs3lQiYGsT6xsuIjRp8PKBhnsxCoTIrdYg5kvKtVI8oS5i+MFcX3HYssQSIlOy8IHeawj87hR5RH6myXzOZZjkXWPko3IfYjwuRxL59y9EECs8Q899FBlncLVy9xjaeSeRmybBJDTTz89xAP3SnMC2CszXdE4nQBWBGwNp80qNC0CiBA1rk41iE8dZKAGSMIlbrjhBsNFRFa1xgURufrqq4O1FXIICWej2GGHHYL7L7ay4SJU1ZFGotV1jaPVdSR5AhnErY27FpIH+cN9jDUsduf2t+h0q8ojSTLK2AiDkNgypI8EGV6g5M7Fxc8cpXVRd8Kc9UofIIC89GJdZ92hgnDssceG8Jcy2zXXXBO8KMRzLrPMMqGCkmcBl4lw559rUOd3sbN76ASws+enVe+yCk2LAEIYIAe92CAiWP3OP//8kEX8+OOP23bbbRfIIDqMEIrXXnstWNmwGkKkVHWkLBdpEdzlzo2zc7GQ4dbmf5AnkmGQxeh0SybzMGrUqGDFAXsIAy8nWHeYB8ImJLbscixFVk29x1KZg/AK4v64j5hfwjLQWEwbtlBvj7v3am4B7N6564ieOwHsiGnI3Ik8WcYigFjHsBRRdo63dTbZXmyQQeq4kjhCMgBWNESmIYOUlYJMKRGDJBKIFWSQWMK6LKZY82J3LhurEldk4YtlaZKWzLgecSfMsQi4aufiumNMjBNZFqxEuPSw5gyksIROwL6/+sD65Zlzwgkn2Fe/+tX+6saAvK4TwAE5rfUNyglgfViXeaU8OoNYVyCByCdAAMmgwwpG4DQVSHq5QahJtoEMYsEAD2IFd9ppp2AtJUYQawZfWNwgJ5DBMi0akCPIUEz4IEZcQ2QPK1kaQXD6qHhB3KeKF8RtWpesDeuJfrDuRPgkx7LyyivPEL9HTCb9pR401lkIIO55b9Uh8LOf/Sy4UNHPi6sPVXFFsrGp740r2Ft5CDgBLA/LnjyTE8DunPY8BLDRSKmogdUFIuhtehYxNXAvuOCCEC9IMs5nP/vZUIuYBBrkY5KJGHIRZyVWcZURCU8zByopp+zcosLEyXhBXMMQwTTi2FnWhORYHnzwwT7CR/ye5FhUTg2Ls+RYspzfP1seArjZsbQSC8y6rpIA8lKDLieuYFQNvJWHgBPA8rDsyTM5AezOac/jAm400kMOOcTuuOOOnhJPTTvjEJrRo0f3uYhx+7Jp4iImu1jCzZBxCByuYcggruKki5hzyZ0r0WnctQTJx8kauHOrTGyQvqDEseN6xFmvKzkWLMiy8MVyLErYwOIMOc56/rTz5J/LhgCEDAs3kkjo5pFcUyYBPPjgg0OJRty+rLOjjjoqZATzMsW94a08BJwAlodlT57JCWD3TntWoelGI0VMFRfjZZdd1r1A1NBzJGMQ48YqSDYx8ZO4iKkkAfEjy5jNDhcxn0VXEGLHzyJ8kHa5c2Xl669yb8rKVT1iZT5jGYSENmq4c5999tm+2rlY92I5FggfciwrrrhibTGSNUz9gLsE2qRYgX/5y1/ahhtuWDoBJI72b3/7W0imgvCtv/76QWwb2R5v5SLgBLBcPHvubE4Au3fKswpN85aPXALxV1iCiAGkSgmyKJtsskn3AlFzz9nYLrzwwuA2x7Kx5ZZbhng1CBKWMGKdIHaQLFzGkD2yctkM+b3TWjJekOxn4va+8pWvhAoqyLGopFosx4Irl83d5Vg6bUab94d1CxnDBcwarYIAdg8a3d9TJ4DdP4f9OgIngP0Kf+GLZxGa/vnPfx6EUpFkIClgtdVWsx/+8IcNxaHpGG/x6Hnh1sNSdPnll4fSaq0aSSYE8I8ZMybE/RxxxBEthawLA9BPJyA7GOJM4gil5yBNELzhw4fbvvvua1tttVVI1uDvYEfcIHFvuIjLjr0rAwKVhyMrlwoOJMIgkYNlEHf3tttuG9YJVueq3dRljMfPMTMCVM7AHX/jjTeGe5/mBLC7V4oTwO6ev37vvRPAfp+Cju0AJODvf/+7UVJrxx13bEsAVcoOArTPPvvYTTfdZN/+9rcHZCk7rK+40LCC8YVmHaSXEnRXXnllEKHGRbzzzjuHElhkXavqCNZXXMSQQdzE/REbF8ux4MrFwocmH/3SmHDZEQNJVi6u3/vuuy9ou3krHwHq2PJFZSAaVnpezniRKKtRnQNLdWyFJo6V9UfMKmu0Ey3UZY1/IJ7HCeBAnNUax+QEsEawu/hSbBLtLICHHXZYIHsIvqoRD0SCBPFzvdIYLwQRFzEWtS222CKQQVzFaPjhVlXsHRm+qu2LVbaqFsuxiPBB2EeMGNFH+HDnIsfSKIEFV/fqq6/usX0VTRBxpZAv6lZDzpEjwvpORjVksIxG0hFai3Hba6+9Qswm9y5xrd66CwEngN01Xx3XWyeAHTclHdmhNASQag5kF8YZhWeffXawApII0WuNjZwyVWzmWNHIviRpBEkZyBRNLmKkZ4gVxCqIFa6I9AvXJeEEkWvF7kH60DLEBRiXU3M5ls5dlSRqQAKrFE92F3Dnzn+anjkBTIOSf6YpAk4AfXGkQSANAcTtiUUBcVm16667zrbZZpugBZdGwDhNX7rxM7jaiI+EDJJxjaUNORlcxBA+soXlIoaoEScIGUxTzg3Ch9VRlj2+E7eJRRGyp2QNl2PpjpXDWkEQm2xdLIBYaatqTgCrQrae8zoBrAfnAXsVJ4ADdmpLHZgTwPLgxAV86aWXBkkZMmw33njjQAYhymRm4qpDUgZCKHkW6hBDGmlJORZ0+NBYIwFFhM/lWMqbr7rO9PDDDxti2cSIkmiDGPnWW29d1+X9Ol2IgBPALpy0TuqyE8BOmo3O7UsaAugu4Gzzh+WOODyIIPGCZAp//vOfD2QQax0NyRnitqhGgqUQl+3zzz8fXMcI+Kq6hsuxZMO+Ez+N255kG8IleEFApum2226r1ALYiTh4n9Ij4AQwPVb+yQYIOAH0ZZEGgTQEkEByXL5YMtRIfoDY9FISSBo8k5/Bqnf77bcHMsjmj6QMJfpoZN9iGSQZgJhCtPiwFiK3g6XP28BEAD1JMrFPO+20gTlAH1VhBJwAFoawt0/gBLC357/V6ElaQAuO9vGPf9xOOOGEoAVHXBrkhFg/NAUhLTTJwOy///62995728033xxqf5IZTCast3QIEAOIRfDYY48NCTSQPKx9SgxBpJlYQmLDSCjxVg0C4E+85qOPPhriV3GvH3fccbVJ4RAawH2GtJA3R6ARAk4AfV0UQsAJYCH4BvTBJC1A+JKN4HQ2pT333DPolvE5NX4+6KCDQkzasGHD7MgjjxyQQtADeuJ9cAEBZHuQMVp77bVt8uTJ9v3vfz9IHLG255577lJR4mUKzT8IHzGgxP9BNm+44QajXKM3R8AJ4MwIDPJlUQwBJ4DF8POjiyGQtdpIM1KKrt5iiy1WrDN+tCPQAgHiLsnOJi6PeNcyG1IvCKezjpEDolIHIRVO/spEeeCdyy2AA29Oax2RE8Ba4faLJRDIWm1EBBA36Hzzzdd3NjbmpICxg+0IlIkA4RAINRPj6qLJZSLr58qLgBPAvMj5cQEBJ4C+EDoFgTSJJiKAb7zxRiij5s0RqAMBknSoh4ze4h133FHHJf0ajkBbBJwAtoXIP9AKASeAvj46BYEsBHCppZYKtUuxxPzoRz8KYsfeHIGqEPjGN75hWKshf8S2enMEOgEBJ4CdMAtd3AcngF08eQOs62kIIK5frIDo5EEA0UojYxYxZMrQeRv4CGSNGy2KyDe/+U278sorjesus8wyRU/nxzsCpSHgBLA0KHvzRE4Ae3PeO3HUaQhgo35vsMEGIXsSIuht4COQNW40LyIIdX/rW9+yyy+/PLx0EP/nzRHoJAScAHbSbHRhX5wAduGkDdAu5yWAhxxySHDN3XXXXQMUGR9WMwTyrpk0iO63335BjgXr3worrNB3CFm6vVzXOg12/pl6EHACWA/OA/YqTgAH7NR23cDybuZIZcw777xBtNdbbyGQd82kQYlzN2pnn322a1umAdA/UzkCTgArh3hgX8AJ4MCe304fXdZqI7/61a9CHBZl0SZMmBBiAE866ST7y1/+YptsskmnD9f7VzICVRLAkrvqp3MESkfACWDpkPbWCZ0A9tZ8d9pos1Yb+fnPf26nn356KEE3ZMiQIJj7wx/+sGHFEo01b0kv+ka93TFjxtgSSyxhRxxxhFt+OmwBOQHssAnx7tSKgBPAWuEeeBdzAjjw5tRHNCMCeUp6qa7xvvvua/vss0+o0kBdXq9r3FmrywlgZ82H96ZeBJwA1ov3gLuaE8ABN6U+oDYIpCnpRRkuyB61X9WoC4sQ8PXXX+8YN0DgN7/5jR1//PH20ksv2eqrrx5c8+uss06lWDkBrBReP3mHI+AEsMMnqNO75wSw02fI+1c2AmlKelHrFV1BYg7VCP7HCvjWW2+V3aWuP99FF11ku+++u5166qm27rrrBtwuueQSQ7eRMn1ltnZxo2Vey8/lCHQyAk4AO3l2uqBvTgC7YJK8i6UhkLak1/LLL2977bWXHX744X3Xvu6662ybbbax9957z2VAEjMC6Vt77bXt5JNPDv8BZ+Im0dH73ve+V9r8caJ2caOlXsxP5gh0MAJOADt4crqha04Au2GWvI9lIZC2pJcTwPSIT5o0KSTkXHrppbb99tv3HbjHHnsElzk6et4cAUegfAScAJaPaU+d0QlgT013Tw82S0kvdwGnXyr//ve/bejQoXbnnXfaeuut13fgoYcearfddlso0+fNEXAEykfACWD5mPbUGZ0A9tR09+Rg85T0IgkEl+/DDz/ch9luu+1mr7/+uieBJFaRE8CevK180B2AgBPADpiEbu6CE8Bunj3vexoE0pT0ItYPbcHf//734ZSSgdl///1t7733tptvvtkOOOCArpaBOeaYY0L/H3roIRs8eHBwz5bR3AVcBop+DkcgOwJOALNj5kdECDgB9OUw0BFIU9Jrzz33tKeffjokGKjx80EHHWRjx461YcOG2ZFHHtnVQtBHHXWULbDAAvb888/bmWeeWRoBBC+SQJB8QfqFRhLIkksuabjdy04CGejr1cfnCKRFwAlgWqT8cw0RcALoC8MR6C0EzjnnnCBnU5YFEPSQgSHp47TTTgtEEBmYiy++2B599FFbdNFFewtgH60jUBMCTgBrAnqgXsYJ4ECdWR+XI9AYgSoIIFdCAkZC0CNHjrQTTzwxWAa9OQKOQDUIOAGsBteeOasTwJ6Zah+oIxAQqIoAOryOgCNQLwJOAOvFe8BdzQnggJtSH1APIUB83XHHHddyxOPGjbMVV1yx7zNOAHtogfhQBzQCTgAH9PRWPzgngNVj7FdwBKpCgLrGr732WsvTDx8+PGT9qjkBrGo2/LyOQL0IOAGsF+8BdzUngANuSn1AjkBLBJwA+gJxBAYGAk4AB8Y89tsonAD2G/R+YUegVgSeffbZIGR91VVXhWSN22+/PVx/ueWWs3nmmafWvvjFHAFHoDgCTgCLY9jTZ3AC2NPT74PvIQTQOjz33HNnGvEtt9xiG264YQ8h4UN1BAYGAk4AB8Y89tsonAD2G/R+YUfAEXAEHAFHIDcCTgBzQ+cHgoATQF8HjoAj4Ag4Ao5A9yHgBLD75qyjeuwEsKOmwzvjCDgCjoAj4AikQsAJYCqY/EPNEHAC6GvDEXAEHAFHwBHoPgScAHbfnHVUj50AdtR0eGccAUfAEXAEHIFUCDgBTAWTf8gtgL4GHAFHwBFwBByBgYOAE8CBM5f9MhK3APYL7H5RR8ARcAQcAUegEAJOAAvB5wc7Ao6AI+AIOAKOgCPgCHQbAoO6rcPeX0fAEXAEHAFHwBFwBByBYgg4ASyGnx/tCDgCjoAj4Ag4Ao5A1yHgBLDrpsw77Ag4Ao6AI+AIOAKOQDEEnAAWw8+PdgQcAUfAEXAEHAFHoOsQcALYdVPmHXYEHAFHwBFwBBwBR6AYAk4Ai+HnRzsCjoAj4Ag4Ao6AI9B1CDgB7Lop8w47Ao6AI+AIOAKOgCNQDAEngMXw86MdAUfAEXAEHAFHwBHoOgScAHbdlHmHHQFHwBFwBBwBR8ARKIaAE8Bi+PnRjoAj4Ag4Ao6AI+AIdB0CTgC7bsq8w46AI+AIOAKOgCPgCBRDwAlgMfz8aEfAEXAEHAFHwBFwBLoOASeAXTdl3mFHwBFwBBwBR8ARcASKIeAEsBh+frQj4Ag4Ao6AI+AIOAJdh4ATwK6bMu+wI+AIOAKOgCPgCDgCxRBwAlgMPz/aEXAEHAFHwBFwBByBrkPACWDXTZl32BFwBBwBR8ARcAQcgWIIOAEshp8f7Qg4Ao6AI+AIOAKOQNch4ASw66bMO+wIOAKOgCPgCDgCjkAxBJwAFsPPj3YEHAFHwBFwBBwBR6DrEHAC2HVT5h12BBwBR8ARcAQcAUegGAJOAIvh50c7Ao6AI+AIOAKOgCPQdQg4Aey6KfMOOwKOgCPgCDgCjoAjUAwBJ4DF8POjHQFHwBFwBBwBR8AR6DoEnAB23ZR5hx0BR8ARcAQcAUfAESiGgBPAYvj50Y6AI+AIOAKOgCPgCHQdAk4Au27KvMOOgCPgCDgCjoAj4AgUQ8AJYDH8/GhHwBFwBBwBR8ARcAS6DgEngF03Zd5hR8ARcAQcAUfAEXAEiiHgBLAYfn60I+AIOAKOgCPgCDgCXYeAE8CumzLvsCPgCDgCjoAj4Ag4AsUQcAJYDD8/2hFwBBwBR8ARcAQcga5DwAlg102Zd9gRcAQcAUfAEXAEHIFiCDgBLIafH+0IOAKOgCPgCDgCjkDXIeAEsOumzDvsCDgCjoAj4Ag4Ao5AMQScABbDz492BBwBR8ARcAQcAUeg6xBwAth1U+YddgQcAUfAEXAEHAFHoBgCTgCL4edHOwKOgCPgCDgCjoAj0HUIOAHsuinzDjsCjoAj4Ag4Ao6AI1AMASeAxfDzox0BR8ARcAQcAUfAEeg6BJwAdt2UeYcdAUfAEXAEHAFHwBEohoATwGL4+dGOgCPgCDgCjoAj4Ah0HQJOALtuyrzDjoAj4Ag4Ao6AI+AIFEPACWAx/PxoR8ARcAQcAUfAEXAEug4BJ4BdN2XeYUfAEXAEHAFHwBFwBIoh4ASwGH5+tCPgCDgCjoAj4Ag4Al2HgBPArpsy77Aj4Ag4Ao6AI+AIOALFEHACWAw/P9oRcAQcAUfAEXAEHIGuQ8AJYNdNmXfYEXAEHAFHwBFwBByBYgg4ASyGnx/tCDgCjoAj4Ag4Ao5A1yHgBLDrpsw77Ag4Ao6AI+AIOAKOQDEEnAAWw8+PdgQcAUfAEXAEHAFHoOsQ+P+wX+fHH/9qSgAAAABJRU5ErkJggg==\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "struc = getStrucFromPDFgui(PDFguiFile,0)\n",
+    "\n",
+    "svec = np.array([1.0,-1.0,0.0])\n",
+    "msp = MagSpecies(struc,magIdxs=[0,1,2,3],ffparamkey='Mn2',rmaxAtoms=50,basisvecs=svec,\n",
+    "                kvecs=np.array([0.5,0.5,0.5]),label=str(0))\n",
+    "\n",
+    "mstr=MagStructure()\n",
+    "mstr.loadSpecies(msp)\n",
+    "mstr.makeAll()\n",
+    "\n",
+    "### Visualize the magnetic structure\n",
+    "uc = struc[:4].xyz\n",
+    "visatoms = uc.copy()\n",
+    "visatoms = np.concatenate((visatoms,visatoms+np.array([0,0,1]),visatoms+np.array([0,1,0]),visatoms+np.array([0,0,1])))\n",
+    "visatoms = struc.lattice.cartesian(visatoms)\n",
+    "visspins = mstr.spinsFromAtoms(visatoms,fractional=False)\n",
+    "mstr.visualize(visatoms,visspins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make the MPDFcalculator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Warning: Your structure may not be big enough for your\n",
+      "desired calculation range.\n"
+     ]
+    }
+   ],
+   "source": [
+    "mc = MPDFcalculator(mstr,rmin=r.min(),rmax=r.max())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Set up and perform the fit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "### Make the FitContribution\n",
+    "\n",
+    "from diffpy.srfit.fitbase import FitContribution\n",
+    "mfit = FitContribution('mfit')\n",
+    "mfit.setProfile(profile)\n",
+    "\n",
+    "# Define the function that will calculate the mPDF\n",
+    "def mpdf(parascale, ordscale, damp):\n",
+    "    mc.paraScale, mc.ordScale, mc.dampRate = parascale, ordscale, damp\n",
+    "    dr = mc.calc(both=True)[2]\n",
+    "    return dr\n",
+    "\n",
+    "mfit.registerFunction(mpdf)\n",
+    "mfit.setEquation(\"mpdf(parascale, ordscale, damp)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<diffpy.srfit.fitbase.parameter.ParameterProxy at 0x7f6a58d02a90>"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Make the FitRecipe and add the relevant variables\n",
+    "from diffpy.srfit.fitbase import FitRecipe\n",
+    "recipe = FitRecipe()\n",
+    "\n",
+    "# give the PDFContribution to the FitRecipe\n",
+    "recipe.addContribution(mfit)\n",
+    "\n",
+    "# add the mPDF variables\n",
+    "recipe.addVar(mfit.parascale, 4)\n",
+    "recipe.addVar(mfit.ordscale, 0.5)\n",
+    "recipe.addVar(mfit.damp, 0.01)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Refine using scipy's least-squares optimizer:\n",
+      "  variables: ['parascale', 'ordscale', 'damp']\n",
+      "  initial values: [ 4.    0.5   0.01]\n",
+      "  final values: [ 2.8959563   1.23062246  0.00673758]\n"
+     ]
+    }
+   ],
+   "source": [
+    "### Run the refinement\n",
+    "\n",
+    "# Turn off printout of iteration number.\n",
+    "recipe.clearFitHooks()\n",
+    "\n",
+    "# Initial structural fit\n",
+    "print \"Refine using scipy's least-squares optimizer:\"\n",
+    "print \"  variables:\", recipe.names\n",
+    "print \"  initial values:\", recipe.values\n",
+    "\n",
+    "from scipy.optimize import least_squares\n",
+    "\n",
+    "least_squares(recipe.residual, recipe.values)\n",
+    "print \"  final values:\", recipe.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot the result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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e0QJQVOxkiLPO40dtBA0rYCmEPTxBGApBDABYMmmgoAgIAgkNQK+IICaBLrrAFJv+YMPfCsBw3MdOACcOgX06kUZmJhdwLlyAYULJ84CaApB08pGsWhm6rZuzboK0S2hMjC0ApoyMP3791cxeqbszPfff6+yg48dO6ayk1999VUVv2haLd966y1FRE+cOIEnn3xSycBQ27Bfv37Yu3evyiD+5JNPVDyjWAATd1cFKgFM3Gh9v5djBDApFed9D4scURAQBAQB/0DAVwSQo0mq57ImgJ4QZCIIE0LYmHxSsqR/4OyPvZAYwNivihBA72atIwSQ7oYXX7RWgbpxlTdqlO9Xmt4NX/YWBAQBQcC/EfAlAUyqkZ44YdUAjqsFBwP33XdnNZC49kspvwsBFALo5Fz3OQEk+WvbFkibFrhxI7rr+u+ZM4UEOnlB5diCgCDw30IgEAkgBaY3bLCuA+X3YisJV6oUkIklCaTdgYAQQCGATt4WPiWAvMlZYJyxHzG13LmBo0d9pzjvJDhybEFAEBAEkhuBQCSA1BbcsSMauWCEIzXCcQMMXXdtjEOMSpRNbqj97vxCAIUAOjkpfUoA//c/IKr8Yqx9XroUeOghJ4clxxYEBAFB4L+BQCASwDNngH37LPxDcANl8C+CcRsHUBinkMvlwjAGUCqRep6rQgCFADr5FPMpAaS8wLvvxt3dV14BKD8gTRAQBAQBQSB2BAKRAF68COyM0qwICzmCnDetqqa3gtLiarFyygt05Yo1biGAMV9/IYBCAJ18PvqUANarZ9WTZEuXjoWso7tu/k19zmXLnByWHFsQEAQEgf8GAoFOAEtgJ7IoqVqrbUR53Eaw/be4gIUAJvZOlSzgxCJn7edTAsiSPjrzl0W+WQxct5AQ4OZN6y9mBLNUkDRBQBAQBASB2BEIRAJouoDvwRakQ3RG4L+4G1cRXYdXkkCEACb2GSAEMLHIOUAAWdLnyJGoA2cGmOJ/lrVN3FqBAgCV4qUJAoKAICAI/PcIIF28/AdEoiI2IAhRwn8A9qAokC07zp2zxl2xIhAUJLPAEwLiAo59XggB9O6+8akFkDfyRha2i6PR5L93b1xb+f/vSSWq6v9ISA8FAUHAKQQCzQJIkectW4Bbt4DgyFu4D5tdoDmepiAO38prfycWwJhnjhBAIYBOPVd4XJ8SwA4dgO+/j7u71ARkADD1oQKx0bXdsiXArGfqXel2113ARx+JzmEgXlPpsyDgrwgEGgHUEjDZsgHXz11DWWx1gfYY8uIICiJDBus94G8xgJGRkejZsydmzJiBc+fOqfJuzz//vEspuKSaK0IAhQA6Odd8SgAHDQLeeSd+3Q1UKZhWrYA5c2Ifo4hdx28OyFaCgCAQNwKBRgB1/B81YS8fu4RSMAQBAZxJlQP7IovEaAHcv38/ipAVRrXs2bOrOr8jR45EhQoV1Lesn2vWAs6ZM6eqydu1a1e0adPGBVTWAnZvNWvWxKpVqzyCv3DhQrRs2RLLly9H0aJFwWNfvHgRadKkQaYoxeqwsDBFCvnPySYEUAigk/PLpwQwvjqAHNDrrwNvveXk0Hx/7PiQP56VmlaMfQxUC6fvkXP4iL//bq08GjQAHH4gOzwSObwgcAcCgUYATRHobDiHYtjjMqbzyILdKKGej/SgkNOZMYCaAC5duhRly5bF4cOH8dxzz2HPnj3YsWMHsmTJoghgyZIl8eabbyI8PFxtM3v2bHz00Ufo0qULJkyYYJ+TBHDy5Mlo1KiR/V1ISAhILD21sWPH4v3338cBs5ap24ZCAP3jRpUYQO+ug08JIGPiuECii9Qs+M0upkkTFRMSDISHA6+9Brz9tnedT8q9OabQ0Pif8ZdfgIcfjv/2smUiEaAPib53nW20cCFgPOgTeVTZTRDwGwQCjQCS1DEWnKSu99M1UaV4QaQOCsJX8+cjJE0avNGrH+5rNADvvfcMli2bgTx58mDcuDFo3LixwlwTQLpey5cvr75bvXo1atSogUWLFqFhw4aKAPK30aNHu1wnEr2nnnoKS5YsQf2oqgQkgCSHrbiCj6ORPH711Vf2VoULF1b9Mc9nWh/1hnQbO9HEAhg7qkIAvZt1PiWA7EqXLoC+f1IhAplwCReRxe5lrlxWqbgPPgD69/eu80m5d+/ewGefxf+MjIf89tv4by9bJhKBBQuApk2jd+7aFZg0KZEHk90EAf9DINAIoGkBfLZnDWzd8TcGduqExxo0wLQlSzB04kRUrfow6tRpjUqV6uDnnz/C3LnTcfDgQYSGhnokgCSDdPHOnTsXzZs3j5EARkREKJdt+/btMX78eHUxE0IAL1y4gE8++URZENetW4fUqVMjV65cLuc7e/Ys7rvvPvTo0QPdu3dX58ibNzqpxZczSAigEEBfzif3Y/mcAJL0dOt4HU9hEvrhE2xARTyB7+xSP1SIZ/vmG+CJJ5wcmm+PXbkysH696zHvuw9gBtv27cDff7v+VrMmEEOIiW87ltKP5h54WqwYsHt3SkdFxv8fQiBGEsCH0vHjST9Skp2//orxvKYGYL+e1ZE64jpWTpyotr99+zay1K2L2nUfwciRX6tiAVmyHEfJkvmUla9atWp3EMDz58/bVr3du3cri2FMFkCeg8ege3cBF4dRBDBdunSKzOn2zTffxGgRpFWR/2j50839fOICTvpp5+mMYgH07jr4nAAyDrBp/es4hELIhdO4hWAUxGGcRB4Xt3CgJYFUqgRs2BB/sB9/HPjuu/hvL1smEoEmTQC6faNaBFLhfz9dRr1moRKDmUhIZTf/QiBGAmgKryZll+MQctVl4FgMoMeT1VC+aCGMe/llRASlRlDEbRRu3hytHn0BPXoMVOFCJUpEImvWIMyZMwctWrSwCWD69OkRFBSEK1euqGSMMWPGoAnv96gkEE8uYP5WtWpVZQWcP3++TQA//fRT2yXML/Ply4cMTEP20IQAJuVk8u5cQgC9w88RAsjQi/cxAAPwoepda8zCT2gNszpIoBHAxx4Dpk93BZvxjs2aWYtwXQJPb/H++8CAAd5dHNk7bgQOZyqNgpddswzvwybsDr0PU6eKJE/cCMoW/o5AoFkANQFk+c9enauicsmiGN2/P64iPUJxDWEtWuCR9v3RvoMVA8SE35w5o+P0dAwg3b1lypRBjhw5kDVrVpfLFJMFkBZGumw7dOgAJnOwJcQFzO2FAPr7HRHdPyGA3l0rnxNAuoA7drRI3yy0Vb2bV3EIlj4wVHnmoqzyAecCfvVV4N134w/2118DnTrFf3vZMuEItG4Zge/nhrqUmeJRHsU0/IhH1QFFkifhuMoe/oVAoMUAmi7gF3rej0oliykCyOzfrLigCOCj7V/Eox2sFTLDaDJnvpMAmkkg7lckJgI4adIkdOvWDcuWLUNdFp13iAAyA5lagf0dDmSXGMDY70UhgN49q3xOAJmU9cILQM8aW/DZH/eq3k1BZ3TFFFUarl49YPFiSzA5kBQ7Ro1KWNJKoI3Pu2mU9HvTdVQ89IgSlHVvL+E9fICX1NesT82Fh0jyJP01kjP6BoFAI4BmEogmgB/174/TyKnCgkgA27d/Ho92HAgmz1IGJnXqhBPAmGRgnn76aTsBxCkC+PDDD4MuaiaapE2bVrmcnWhCAIUAOjGv9DF9TgC1BTATLtrZv8dK18HsZ39V1r+osIyAswDSnfjkk/G/FIGW5BL/kfnHlj17AlsnrMIqPKg69BcqoTKsLJ2P0Q/P42O7o3TP16njH/2WXggCCUUg0AigloGhFNjz3augYsni+LD/SziF3MiL44oAPt6+H9p2eEVBkVgLoCkETTcxxaIpAdO6dWsXiJ1wAa9Zs0ZZAKlLeOPGDYgMTEJntW+2Fwugdzj6nACaYtCX0mRDxlvnERFWFH9+t0dp9f78s9XhQIsB1JbN+MIdaOOL77j8YbuBAwHGWD6CH21X7zj0QV9Ysg+LM7dFw4sz7K4KGfeHqyZ9SCwCgUYATQvgvdiMENzCTaRRBLAAjigYdqM4rqXNihs3/K8UXGKvkxP7iQUwdlSFAHo36xwjgKVLA3N3l0GJ8G24hIzIjEsoXBgqEYSyKYFGkLQF0Exk8QQ9Y5XPnw+88Xk3jZJub03+eMa+GIuxeFad/GlMxAT0QBAisQZVUTNojV2n+cMPgRdfTLo+ypkEAV8iEGgEUMcAMuyi3O2NCMZtXEM6nERuFMZBBc0+hOFmppwgWSxUCMiTx5eI/XeOJQRQCKCTs9nnBPD77wGKILOtCKqNByNWqM+huAKkD1Vp/2yUSKFUSqC02CyAfNCxCorZAm18gXAdbt4E0qaN7ukwDMZgWPUEG2EhpqAL8uIETqYpgDy3DtsbBlrVmUC4FtLHpEMg0AjgiRPAoUPEJxKVsB600lxNFYoLafMg3/V9CriDKKSkwdiYBZwjR9LhGUhnEgIoBNDJ+epzArh8OcDkK8Z/zEjVDm0iLFdcYezH6dDCigAy8DfQ4rJ0bGNcFyN/fuDoUbEAxoVTYn4fORJ4xQobUu0z9ERPWDU/K2ADvkQ3VMRGhCM1QnATkQhSvwkBTAzaso+/IBBoBFBbAINT3Ub5yI0KxovIhBPIgxKwRNqPID+OIb/6XLKkVT9d2p0ICAEUAujkfeFzAkgrDfU1uaI71KIP0kz8VPX/uxfWodXwyihaFOADgiVcQ0KcHJpvj23GNrLE3QvpPkPBiIN46+ZAnEN0UXG6M7j6DTQXt2/RcuZo99wDbN0afezZaIVWmKO+KIDDmISn0BCL1d/Zcca+LoFWdtAZ9OSogYpAoBFAbQFMg1u4D5sV7OeRFceRB6VhaXby82EUEgIYx6QUAigE0Mnnls8JoLYAstPDg4diUPgw1f8mmI/l6ZvYLuBAswBqAqgKnEdEx579ijpol+NXpEnjWpVJXMC+n7YU3r582Tour8OqiOqojjXq7zS4icnoio6wCjCXwnbsRCn1WZJAfH8t5IhJh0CgEUBtAUyL6yiHfxRQZ5Adx5EXZfGv+vsUcuEACqvPge4CZtbz4cNQZe0ofs0CLXw++aIJARQC6It5FNMxfE4AdQwgXcD9gsdj9K2+6tydMQUzQjvbLuBAI0jUNmQcINt2lEIp7LQxLYGd2I0S6m9xATszXRljSZLN8AE2xl3uuF0MxbBXvVxy4gxG4QW8AOsiPYCV+B0PqM9ijXXmmshRkwYBTQJYf5bac/7e9u2zvDyM+y6Dbaq7J5FLuYBNQrgPRdVv9BaRBAZio8Yok/7cG5MBixf3fkTXrl2zS+OxnrHZLl68iCxZsvAr/uei92cLvCNIFrB318znBFBbyh54APi193QEP/GY6uGeXu/jrk8GKCHoVasC66VM8sHyl3RtPPfYcYyels8F9WdTjcUXafuqFWC5csCWLYE1Pu+mUNLsbVqW9RkvILPKLichvxvb8SrewTsYpH5uhdmYg1ZCAJPm8shZHESA5c127tyJ3Llzq7Jo/ty4QGPNdP4/Iy4ZLl+mZ+WxXcLnkBV7EM2QWGudRoNAajGRPz0GX5DAM2fO4OTJk6DodWo3NXshgFAJRtISj4CzBPC1JQhu8rDq3YGOg5B/0nCVIPL774FFkDT5yJYNqHfxJ8y47So0+iWewtP40uUqBJqFM/FTKGn2NLPLecbUCEc40qiTr0Y11MBqdMcETEBP9R0/f4Hu6rO4gJPmGslZnEPg2LFjOH/+vCKBoaGhqr6tPzaGaOzfb/UsIy4iLEr25QRy4zRyoGyURfAyMmA/os1+2bNb3pNAaXT7/mt5s2NtZcokzh1MYemrV68q8sc6yPnyuRodeFIhgEIA45p/cf3ucwJovqhrpv0Lq25UUX2gUO9L6ccFpAyMOSZTekSDuwEVUAkbVKk7WgsDMcs5romS3L+bSTjsSw6cxmnkUt1agMZoigXK6jcbbdR3r+FtjMBr6rOU5Uvuqyfn9xYBEoLjx48rEujP7fRpK8GPjS5gln5jO4tsuIRMtg7gDYTgOD7Z7/gAACAASURBVFxJzV13BY4VkC5uMx6Z3lnG/ZEY0hPE/7NlzOidxA3JX968eT0SfiGAQgC9fRb4nACaMjBlQnbjnxtWbNy36IAeod8GpAyM6daeersDwlZ/74I7V7OZcAkjRqRSZOPsWT/Mcp471yrD0qMHULmyt/Mmyfd3J4DFsNuOu+TcYvJHTUSXhvsIz+NFfKT62bgxVBlCaYJAoCNAd/CtW7f8dhjUgKULmK01ZmMEXlWfh2IIfsDjWI+KyICr2IkSaIF5LuP4+mvg/vv9dmguHWvUyLJ0ctHPBb+pA0tPLQ204eFWLfJFixI3pjRp0tzh9jWPJARQCGDiZlb0Xj4ngKYMzIENZ5C2gFUk+0zVxsj42wJVDSTQZGA0+bj7buDbXfejQvg6RCAVfkNt1MVyNb7cOKFKHenmV1nODEpkxXU+pXLlAhilTa2eAGruLuDKWId1sN4WY9EXz2KsyvzdjrvVd1PREU9iqj1ClpwKJNmhALo00lVBwEagfn2Az0u2XvgUn6KP+twFk/EVuij5lzw4if0ojCKI8hVH7R1IoRp581ox4erZn9uqE0+Js717ARLZkyet31jh5PhxZyaIEEAhgN7OLJ8TQDNYv0WTcMxZYMVpHQ+rhu73rLZrAfsVQYoDRZN8nEV2ZMM5nEh7F2beaIo+sHQOq2E1dmStprLZNm4Enn/ecj36RaN6MlWUdZs5E2hjuUoDpblbABtgMRajoer+cAzCGxiuSPgJ5FXfzUMzFwvDiBGuItKBMm7ppyAQSAiwutMPP1g9fhEf4kMMUJ8fxTRVt3s3rMz9U8iJ3DjlMrRAKtlYrRrw559W90nyNBnk3zRyHDhg/Va1KrDGUqryeRMCKATQ20nlcwKoydJzzwHjxgFnwq1MzW0ojXuDt6FvX+DjjwOrFJwmH2XzncU/x6wsvGWoiwVogg/wkvq7A75Fl186KMMaM6AZs0tBaLfELW+vV+L2f+ghYNmy6H379bMuQgA1U4eR8TV8oUxDezWC/vgAo9AfIbiBG7CkElbiAdTCSnuEdMXQ8ClNEBAEnEPg1VeBd9+1jj8IwzEcb6jPzTEXP6M5NuE+3Ie/VW3gUETVBY3qjj9X7KFna/x4YM8eoFgxK4lx/vw7cWSpSnobdGveHGD0jRNNCKAQQG/nlc8JoBkD2LQp8N3vhZHp3EFczZQHj9U+rm6aQEuS0OTjPmzCJlRQmDPz93z1Jui/+hH1N5MOsr//Gn77DVi/Hjh2zI/K3Zn+Cna2Vi2ojgZQc3cB98Dn+By91AiewpeYjKfU5ysIVS+WLbgH92KLPUIGaes61AE07MDtKuPU+C80NHDHID1PMAKjRgH9+1u70TI/CO+ozw9hKZbhIaxCTdTEH+q7YNzCbQTb5/BXAjhwoOXNYUxfQlvPnsBnnyV0r/htLwRQCGD8ZkrMW/mcAJoxgFRHD650H/D33yoAK/zydRQslCrgYgB1HeDGWIAFaKrQfBNvYCEaYzVqqL/H4Bn0wxj1mdZPv7FyMiPFTTvscmgu/Dn3JOrU8RMLZTxmsbsO4Mt4F+9GBZi3xiz8BEuahzVGWWX0MAqgEA7bR2aGHuemX1hk4zHegN6Ec46Ta8sWjCo6BqNvPQNmeHLxZ+nWJl1j2OvKldaCjFb5Bx+UOeAk+lOnWvFwbKYwew38rp6Vi9DQLteYBedxNTgLKK916hTgjyUbSf7ef9+K8+OUpofn0iVghlXiPs5Gj9fYsXFulqgNhAAKAUzUxDF28jkBNF/UNH9PPVQHWTZZ1qY691/Fb2stJftAigFkBRBWAumGL2xtOQY4L0IjW8tqBtqiW+YZqrA5LYD+YuV8vs4mjP7NslqajTIqqXPlUKvTQAgHNBcWxPbFky/jZbynhlQXy7AcddXnrSijqg9YmdlRdeOiBh5Ic87bGztZ93/nHWCQJcjN65ADZ3ATadXfdJ9RQDcp2qxZ1n178GD02UhEac0JhDmfFBj5+hz6WcnjfoZe6InP1SkqYIPynsxEG7TBbPVdr2aHMevPAor8sflbEoh+5jB5jG5dM9M3vrhNmQJ07hzfrRO2nRBAIYAJmzF3bu1zAqhddbyZ+fCdcKoVWmGOOnN+HEF4rvzqhg8koWS9qh2e9k0MujFEjaUF5uAXNLRjzv5Adeya8geeeMKqBekPmc6UVMi5LtpqaV7+KliLv2BpNAZCTogZWpAzJzD8VA/0wETV//LYiM0orz6bLibWB9Zi0f74gvH25vXX/demr4X7r0fHXz6IFViFB+3uJgUJJPlr2zZmhAJhzvvr9Y2tX/pZmTkz8OXtznjkytdqc12b+ys8aWfnl8QO7E5V0i7v6G8lG00ya2b60pLtHv/HRBA6Wuj1umgUZevaFZg0yZkrKQRQCKC3M8vnBFC/qJl1yZiOeTm7oumpKaqfG6ZuxXOfl1Gl4IYNAwYP9rb7SbO/fhCMR2/0hhXQQRmS9ais1O1z4Cz2IQwvtd2nVoqU22NLTouTJuKm1ZLSC2Gw0tMewY+YCSt+kQ+3o0f92zVmJhfRvT4d7dAOlh+mMPbjYFRh+Z/RVIlCs+XEKZyBJUPEJoLQzt8vF85HAtmyIotRmpTWch2vqXtAPWOn3MG01JCAXL0a83gZmsgXtYQE+HZOmKRpZlA7tImw7tG7cACHcJcqCKCVEypiPbanr2jH5vobAezd24rfy5QJYKUSndmbEMSousXwAyfmmRBAIYAJmYuetvU5AeTDlyt86iAx+XRusReQ6uPR6twRK1ah5Xs1VUIqV0y7djlzY3gLivv+elU7L6glmkVYKV20Zh5DfvyNcqrAOZXt0+E6goNTJXumM68B61BSqf4NvIk3YVktv0d7PA5Lo0Fnzuqx+tvD1/0amKEFzZoBA5c2wIPXl6rNMuMCLoFTGfgGT+AJfKc+F8cul3qj1Ofq1MnXs0OOZyLQtOIxzN/oWtNrNJ7DCxitxHHpvmejjMbq1c5gR+Fdin+7N8aaMRucMk1sCxcCFPSV5jsEdLw0j7ggqBkaR1ipsrlwUlXuGYmBGIj31Xeznv8Nk3bVsq1p/uYCbt0a+OknC5v06ROfROaUIUAIoBBAb+9cnxNAdujNN4EhQyw5lG9KvonCkywCMqD0PHy4vRkYIkTroFM3hreguO+vV7VrUQVV8JcSgQ7BTZXB9gsexsNYonbp0vwMzkRmT/ZMZ5MsfYpe6BUVh9MPH+MTPKf6+gmexXP4xB7q668Db73la+R8d7w7kouqVwH+sq5FatyGfhQwGecZjFMnNt3c/NtJd4zvRhq4R2LA/Lr3f8WvqOcyCGoytgme55JFSQvdhQvOjPXee1X+iRL+Ziku5qSYjZZHnpuixUusW1eajxAw9TqXBT2EuhGW/FQGXMb1oAx4PWIYhmGo+q4J5mNbWBNFwmlp8zcLfa9ewOdWCKNaUHDhSSLIpKLJk+MPmFPEVgigEMD4z0LPWzpCALW7jrFaj5/+xCYdT+AbLM39BCgV0LFj4MQBagsgM0sL4CiOIa/KNGUzY1o+6rENfT4pnezVTsxV+E9oiZawrJb340+sRVX1md+3RtTyFgBf3qZWtLcTy9f7mzGAfBBP21wa6Q/uwK3QzMiR+oLKzGN7C6/jdbytPlMseika2F0hIaBb0Al3jK/HG2jH09mSpjyPHsNfqKQWTmZjNqWuperLsdL6TS02TwH7VEOiFJAmnkzY2rHDl2eXY5kEcE2q6qgaaakgB3GRlioIL0S6ikOvC3tUZQHTKusUUUrsVdEuYNX/qDq/CTmWXmg4JXAtBFAIYELmo6dtHSGA5st6WLGv8cZuKw1qzwtj8cLuvipGzl+yZOMDYNmywLZ/I3ATIQjGbWxABVSCVfDyQ7xo15x9ACuxIf0DdkxLclk4zTicFXgQD2KV6mvL+lcwY2kWpEE4NqI8KiLKFxYFQsuW0S6P+OCSlNuYyUW0Vv6+35J7OYSCuDfrITCmjI2ubS3O3Q7TMQPtXLopbj/fXzVaZ0m62CiPxKosZjuKfGrhZLYCBayAeV830/rNlzZfvozBYuLZtm2uVRkYosLQB2m+Q8BcfO4ILY+SVzfjVlAIQiIsdWRzgfBb50l4bFFXu4pGcj0vYxq9KWqdEITcyaJT+oZCAIUAJmReetrWEQJouuuOfDoXqdu0tM49fDjCXx7kN1my8QGPFgMGjGfDWZyFVQWEWlaNYVX4fhXv4B1YkhetMBtLQlspAkiCm1yZzqYWFwWR78FWXEV6VYSdhKkgjqianPlwZ5FKfyWBZnIR3UVbDmRSMi//4m5Uy/SvbQE0k166Y4It26Ovtbz04zPrE7YNKz/wZcn2BbqhG6y0R8bFplWhEkFIixsuor+0ANIS52trrElAPI3CjEOkxZuWS2m+Q0AvPul6/+tyKZTCTpxDVmTHORUD2jXNN/jyphWIy5CUOXf1U/PgyhXrnz/V66aSEcOV2BhTXaqUJQdDWVtWI4pvEwIYX6QSvl2qhO8iexgIOEIAzVX4y9VX4N3VtdUpNz40AIPTv+8XWbLxnQXaDcCEgl0oqXb7Fh3QEd+qzyQZE9BTfX4x00S8c/JpNGgAlemcXIkVpgVQu60pkEzip+MY+VJmHGMEUqu+s1LG9esWKnSTMtbFnxpdevnzW8lFzZtGYO58q9+Xy9yP4mf+tK0IbTDTzm4eU2gknj8y0OVhTYkelugLlEY3KRNXdAkqknu+XP2psf71/v1WjxaiERrhF/WZkjwP4Hf1uQAO4ygKuHTbCYuPOffjwsjfXI5x9TcQfqcI/iefAMx+3XOrEDKdP4wzafMh5w3LAtwaszELVh1yirmPSf9ysntMYsKV1uMBAxLn/jWP6ZTAtVgAxQLo7TPBEQJoSnasHLsZ629bGm0T0B19gycke5ZsQkDjqm/nTqAq1mANqqtdzQQKVqGYBUtw7BWMwLSwVxSZ2r49+QigaQXRpdH+QVmVrTwHLdAC81R/8+EojiOfDUdwsFXuqEeP6ODnhGDl5LYkgKzkQFdeu0aXMH2RlfV7vvJDKLR9qR1PVh9LsAQPq99YisrdHVmmDLB1q5M99d2xqeO4bt2dx6tSBVi71nfn8fZI1D/TiRY6K/460uIbdMTT+FIdnmUU/8Z9LqdygoCZ1u+4xpVcC7S4+hWov/MepWv/xAlrBKeQEzlxBntQFMWxR333MH7BL7BSr4dhMN4LHZbsHpOY8NZklr/TMknPlm4Un6+N3/AD2mM77o71kjmlPiAEUAigt88KRwigGQPYpe4BTFoWpvq5u0I7vFBgerJnySYENG3dYMbafDRTuw7BUFtahSK3K2BZOOeW6I8eFz+wH4DJ5QLWgdhpcR3XYZnyGAtYGyvwOaIFlKnDtREV74DDH4PjTRfwT+OOYM3hgqrfs9Aa7YJm2VY+k6ivq94P3S5/rDJCdeveHZgwISEzIHm2jYn86d74EwksUSK6uofWxdyLIvgR7TxWa9FjcCLr07QAMhaLLSZ3nRBA385t0/PDBIijFzMgNPKqS11uxkmvRC114vV1+qPswg+S3WPiCQV3Mmtuw2fMKjyg4sFZ6aYstto6pJ6O5cQ853mEAAoB9PYOdoQAmjGAB/6+gLR5sqp+nq3cABlWLU72LNmEgFavniVX0wlf42tYySzPYAzG4Rn1+W78i39RVn2egs4YWniKcp8mpwVQE8C8OKa0Ctlo+WNFlqEYgiF4U31HUrsQTdRnxmLpzEkmvfzzT0JQcn5bbVVmtm/I3u0Iuc9adf9b+Um0u/oV/v3X6kMZbMVW3KM+T0JXOx5N99DJ0ky+QoFuX4rPujd3HTti4Q/u4P79oTL70+EariFUdXslHsA8NMd7eFn93RYzbEs5Y2oZZuCEZSQ2CyAx1dni7FNyLdB8NU/87Tja81ChArBpYyQiYDHw3dmroMTZtSqTtnzEeiWgz0Zh/ffDxie7x8QTjprM8rnIe4yLCD13qKfaHtPs3T7C83YioHksbTV0Yp7zPEIAhQB6+wxwhACaK8HQdBG4dD0YQYhU8Wd10q/125gPT2C2bw9MmwY8j4/wEV5Um3TAt/geHdRnCpyeRB71mVUong37OdkfaJosuZPTrpiCnvgMn6G36i8TJiah2x3D9kcrmWkBXP3JOsw5dr/q91j0xetZxtrSHoVw0F6N/4hH8Ch+dBmfU6txb29Ec39a9/5yVU1xOTxfSCSJ/pKw8/77VjJFEezFXhRTfZ2GR7EEDewkHE8JOU5ci4TEAIoF0JezFtDYM2563o/Xcei05X34DbVQB1Y9eJaE0y7TndU7o9beKcnuMfGEgn6G6t9Y3IBxuMG4hfPIqhLqdGMVqKLYa2uR6gWO/t2JeS4E0EJXkkC8u4cdIYD65mHWF+PhjlzLhmw4j50ogQqhO/025sMTlKztS0uBqS/XEIuwGA3V5qkRbtebPVGkKu67uibZH2iaLNXA7/gdD6h+6lVqS/yEn9Baffc63sLbeP2OYfujlcxMAnmt2jK8veYh1e8jnV5BjzMjsMCq/oasOIdzyK4+m9naepBOxJ15dwu67s1x0nKg3Zb33AOUL29llW/a5Bq/yPCEvXzvJHPT2ZLucbLLUce2+jHgX1sDnbwWZvyrmfHLc+oYV31+IYC+nTgm9o8+fA7TFlv34bqcjXD/6YXqs7lAYznHl8OmJ/uC2RMKphHj2WeBMWOsrVh33FPYjHvVIW6rq4eIBdC388w8mhBA77B1hABqFyQrgVBp/0aBIshydj+uZMyN1KdO+GXMR0wwtmkDzJ5tuSvc6wDrfc4gu5I52I1iqFdot8qmZbICleRZtzappQ1atADmzQOa4mf8jOaqm4MxDG9hsBKD/hPV1He0nj2LsXcM3akVqzdT1UwCGV75Jwz6yyKxB3u+jb5HXrMzy01C/geqoyb+cDmtv7/0TSFddwLDgaRJA9y6ZQ2pUqXYLYXe4J2Qfdu2BWbNcp1vLEG4Eg9iOeqqQ7EE2CsY6fi1MPGLawyB4AJmOM3YsVb1CbqwmRHOsBRfy+fEhVV8fjexL5buCHZfj47TbYtZ6hA5cFqVhGPbW6Yp8q//WVVk+f335Eua8zS2mGIATQ8K412Z5MLGIgff4QmPMDn1PBUXsFgA43NfxraNowSwdGlLWmT2/vIoj81KF6x04etIlz5VssbIxRc0PgRYzYQiw3RpaXciXV37UcQ+zA6UREnswnlkUZZOs9Hq8MILwHvvxfes3m1HdzXd1mwdMRVT8aT6rOMWzRX4TLTBI5h5xwm/+AJYv97KQGXcGWO8+JBOzpeO6QI++eFUjDodPa4FRZ5B3brAJEt+Tmkepsd1O/icRIoSMkeO+NdLxtOVfuMNJZdpt7vvtogeLYCbN7vGZlJ/72UrxC7ZGu8RlnVjTF9nTMEUdFV96YNxKlBeZ/5OxNPogYnqN0qEcIHkBBlPCAF0QobGlxeCbnVKkbgnsRBvliLj4tSfmol92bS78c+NEqp7rM/dCd+oz+lxFVeRQX1ehrpoln6ZHRLkb4T8xRet8nR8ftAKSHmbceiDPvhU9Z9ZzDqe2r20pnldnPI6CAEUAujt/e8IATTjJ3LnBv4IqYNih60YkMK5ruLgKSs2xN9ueHcwTTfAEtRHffxPbZIZF3AJlgwJGy1N1WGVPKIFSmvr8W9txXnpJedJoPky5rmfhWsZPq5QQ3ADN5DO7re7hSymCUV3Bh9kyfXSMZNA0k0aj+Dn+qqu/vL4FNSd0ln1rVtUOOPJVLmRK/IUToYWxoge+8F9tTSFv885U3w2rpvbKddSXOc1fzdf+i/CtczXH6iBwyikNme2trYC6f2duBaxCUGb1lMmJFCwPamt8/HFVpfWi237mTOT73701C8T+0ohW/DXzXvVZib5T4UI+/m4BlXxUOgaOyTInwh5TBZAs/Z7SezATpRSY1yO2qiL5R4vlxMLHZ5ICKAQwPg+T2LazhECqF8K1IQ6fhyYcbuVykBlK5T6KCLz5gsIa4z5QGP5twrYhFsIVgLK5tRbgMZ2ZZDsOGPHoJmgJ8ULx936MQjDMRxvqG40wzxbxsaU6iimgpfj35LrpWNaAPHeSLxy7hXVaQo/bwxro9xitADedRew4mgxFA7fC7rm6aIJC7NiUZMzMzu+CDOblhbX+DSnXEvxObfexiSs7+BVvIp31U/18D+sxf24DCud+X+oZy+g9L5OvPC7dgUYw+qpubvU43P+5BDiptuX85VW39gaLaksc5eclnmzf2YCTq20f+K3G1aoibt17EZwKELCr+Fy0XJI8+/ffqkKYS7+GzcGWEKSjZqGRbEvyttzDkdQQJWkPIlcyIOTHi+XEMCEPFEStq3EACYML/etHSWAPFmTJsCQfV1w/7av1Ll71foXn6+wJDycujG8gyR6b/OBdjDVXSgUechjCbXvUz2O9pE/qB1LBe/BzvCi6vMjjwArVljVK9icUoTXPXa3Hr2Ll20dtjr4Fb+hjtpUl4e7hnQIVdlsd95GprXExDO5XjpmEsi04oPw6G6rRtO2jxdj4JIGdgxgzZrAyssVkGrzJoQHpcGw126idm1gyBDgjz/8f86ZMiZcNJAExEQE/MECyJg0Wl/ZKPTeHV+oz/diM7agHG4jtVIAWIfKuB+WqjXrBvN6+rr0F+MQGY8Y3xaXBTK5hLh1BQo9DvfkFXN8/vQM1XOXLuqGaZdj+inP8Z+X0+dEhmtncDZbUTQrvQerV1sjig8hj++19XY79yxgHi8NbuIa0iM1IvAXKqEK/oLpGaIiBOMbKaNlis2LC9jbqxHz/kIAvcPWEQJoWs64kh1x/Xk8j49VT2uHrMaKm9bK0KkbwztIovfWDzS6P09dy6BS/7eijKqta7Yv0vZBtxtWXEjlVOuxPjJaXLlwYSveiTFSTM6YYxlCHWkdOwLEXjcmefTFeKtfWGfrby1GAzTAUvU9s2YvwNJpjKkxDpCWEJ18kBwvHTMJZG5YPzTfb6XlbZmwGq/NrWYTQH63PmMtVLy8Uv1OMeybSGsPLa6XviMXJgEHTYiMiT9YAFkDmLGIbHTztsZP6rMu/cY6sFlxAdtRCndjuwsSvnzhc36wXivnaXxbbOdPTiHuVq3i/5xwqs5sfDE0tzPnbvusi/D9+cbq52+LD0HH3UPtTQ/gLtyFQziGvMp6pmNC/eneNIsZ6AVYCey0Xb4/4DE8jh/wMfqhH6xnUS38Zotc8296JZYts+IIn38+MYjGvo+4gMUF7O2scoQAur/ETPHhRlholwJy6sbwFhS9vx6Hp4oa5jnexmt4DSPUVw9hKZbBkihhM1fvFStayRVONS1Zo49PYerO+Fr9Sf0tHa/yFZ7Ek5iqvqdWoHspI8ZFkfTpuDn3/ibHS8d0ARd7uyvaXbb8fBR+vl6kDB56CGDyCv//wv+aoiksXZicOIWQfDnBygR0AQ8bBgwe7NQV8P64scWwuR/dHyyAWgOQfaPeWy1YxJui0Iw1PYhCKKTqAOdDAVj1YJ95xsps9eULn2oDD1sVAOPVYgvJiEmI2/3ATglxs5Y4F1m6uZchM/vRoYProi9eg3doI3PB3OjGT5gVYWXqv4p38C5etZ+Fu9PcjWK3tuNWaGasXXwBr7xi1U73p3vTUwwg311aOJ/P/Nfxtouuai98is/Ry0a3eHGrQo5Thg4hgEIAvb2VHSGA7mr8pohye3yPabDSVP3hBRYbgHocpqTBbLRCG8x22e0lvOex4oH7sZs3B+bO9faSxby/aY3hVszy1X3VFhl+T0mOgXhfHYixWr+iXoI6RUsjsUnKZiaBhD75CIJmW9nLXww+iCcHFVIWVpJWviyX5GiPWscspf4P++7Ffa2KKJFaWnzy5AF27fKfuCl3DJmtzLguNlpnK2AjVqAWbiP4Drj9YQFlzjlax8tgGy4hIzLjkuova1CXxb/2d0WLAvv2WW5tX1oAn3wy4XMypvPHJcStLwTFgfmC93VjZrepGhBTOAbP+/jjFpH2h2Yu/LtnnoYJF63n/E+1R6HNihfsUIZjBSoh75ENiEgdjOWLb6kqMv54b1K9gWPSjcL5X6C7+rMHPsdE9FDPz/+hvvruPbxkh9yY18OX89w8rhBAIYDe3veOEED3QPYumIzJeEr11VwlFSoEHDzo7RCc218/0Mrhb1vOYmWJp/BG/i/xm5XUrNrTmKgeBmwxVdfgbz17Ap995lx/TWsMz2JmrJmZyyYhj02/KqaecsU+wjJ4JlkzLYA1hjVEreuL1blJkrKFZUWPHgAtk2zTs3RHuwtmLJqVjUhrCV+WTj2QvQXDtP6FYR/WoJoKLPeUQctz+cMCygw7OIHcyI1TsCoj7FNwrEY1VMOf6nPVyrfx++ogFCwInDnj2xjAhLhN9XXyZIGk5YeEK64EDH2MGzd8n0mckEQgfyKAZgxgtzRfY9QZq3QmJYG+y9LHrtbzR+oHUf32KvUb4+rCkcYv780337Rih3WjtuWbsL5ojrlKY5X36T5YMd8z0BbtMMPenqFDDJvxdayrPoEQQCGA3r5zHCGAlDxhwoNurTAbs2GJVr2CERgJK4OTzSk3irfAcH/9QGsY8isW3bSsZJ5WeY/gR/yIR9XvA/A+PsQAj6d3mji5WwB/Rw3UgBVhbcrTPIYf8AMeV9/3xwcYhXimnUaNKjn058wkkG1Zq6P0eUt2Z83KW3h7ZLCKAWTw+cWLwId40a7NWROrsC9fTTAjne53vth96Xr0xTzjMTg+xsuGh1tHNMfAv+nq3oYyLqfzBwsgSTWtsyHBEbgansYlQJ6dNRchE96/gHm/ZbbjNX1JxLm4mjDB89Uw61ybW3hyOSZER1A9D94D+LzzZUtIGADnDOVs/KGZFsDewRMxPjx6UTw1TTc7hpgVehrCWsCVynMemQtl8bt7k/cjLbw0UOjFwKfohV74XPW7Ev7CBlRSz9XrSIdg3AaVIiph4q7I1wAAIABJREFUwx2Xwpfz3Dy4EEAhgN7e944QQArXbjDugy5hv2LyfotAfZHzFXQ/HW0+8pd6pp6A1A80FrKfgXZqkx8rvYsPg1/Gn5ZRQ7X6WIIlsAKQhmMQ3oCh5GscmBp6lFFxqrkngfyNciiHf5Qwslm7ksHKOiP4A/THSzDYejw6lxxWBzMJZH+me1D40lZEhoZizdIreOcdKFLBOL8LF4AvCw3BU4feVCP5e+RClO3fSOkxMhuYsUbJkcQSF6zuxEPLTej9emO8XcNZf+dUbFFcfTV/13GnMZXgo1VE6/8VxCGcCC6Ivn2tCjm+JOLui5+4xkBSSMkg93AAdyHuuI5TvbqVXe7LllASSmtqdqvqWrI2k7i+kGYMRt3qp/pDQfrpaTraBPCfkq1RdqeVLHT70FGkyp/P7+5N7XGgEPu2bRasc9ACLTBPfc6HoziOfOozK0BRTusCMiOrKgRg5aYyAfDAASsBhIs1XzchgEIAvZ1TjhDAypWjkx34oC13O7p+IldR/YI/tS0d1GhjTJA/Nm0BfCbN5xhzywrupbv3Szzt0l1m2K7D/eq7mMqr8Tc+pCkJ45Rul7bG6M7tRREUwX7QNZcXJ+w+m9ls36IDOsJIHY7HhahRwyrdlJTNdAF3er0wCtw+aEvysCZu9+7RLuCxYR+g737LLLOq33SEt24HysOwWoi/lZzSGJoSPnTXu2dmT0JXdENUqZOonfyByGrixVqou1BS9cys/MB+d4WVsPP9G//iu413Y/5838cAJkRAm33hYoBhHO7WGU8EkC5hlrXkopYLDLMxppRap75sCSWAlB355x9f9iBxxzL7/UrwBxgRbt2D9JDMTfOITQCP1HkC+ZdbgYtrvtmNSo8W87t7U8ccP/VUdIWhtaiipF9uI0hpwWrBf1NVwdSB7dfPqh6SLx9w6JDvn/tCAIUAJu5Ojd7LEQLYu7drrFvDEnuxaFcxddYFmduj6cXv7R6ULAns2OHtMJzZX1sA6bYeASvAbGy9WZh6uTXWro0+ZzHsxm7cWfbIU6+ccgfwXA8+aFm4dKM4aS6cVuKlxbHH/j4jLtmVTFiO6SEsSxCAzLQ1sxQTtHMiNzaTQDLclR2pzp3DySzF8d3QXejTB2AsFl3AbAzQ1tl4T+FLFX+qC7Pzd19anhI5nDt2M623VbAWa1HVZZsVeBC1scLlO8YnDY1W1/BVVxJ0HB13Wg2rsRo11L6j8RxegBU9b8pkYM0ahFeq6kgMYELi5tgvhmMwlMF9LixeDDRsGH8IdInB+O8R95aeNOhi2ytjRiuUJrmbSQCHBL+NoeGvqy4xXm5xSHNQ4Jrty6DueCoiOkZ3d/p7/a4cnF5w6rhh9vswCqhMdjOjnd9/hp7oCSv+gMaAzcGVlYGjQgVrccCkLiee+0IAhQB6e887QgAZkxIaGt21bDiLs8ihvliIRmiCKFl1xswNAPgS0Y0PifHjgT17rBgMvtyTq1yTtgB+FDwAz4d/qLrorvXE78wC5/PRBM0wP8br4hT5oItUBx3rk1PoOR1uYDPuVbWYzcZMzYy4gm0orTI3E9JYa5gvqaRstgXwnUgMeC2NS8wNrchmEkgHfIdvowqzP4fR+ATPqfnIeenr7FNfYcAYxaOWSopLDWd9/CPIj4I44nK65BLlNjtBsXOGNbDSzDy0UD8xWF5XoHkLryu5DLY5zyzBF/vrOxIDmJC4OT5PGJzvaS7QUmy6dBnj1RfjEIxwjMGzuIUQl2tQvjywcaOvZoF1nIRaAHPkAE6f9m0fEnM08xp8V/wNPL7bCoUZ3/IXfH38YTtsZkzQc3gm4hP1GxcOW0Kr+d29yecpZVxIrOliD8Jt3ETIHTGuHMNAjLTj2h/FNDsenL8xTIOLOyee+0IAhQAm5j4193GEAPIE99wTrYbOhygzvdiYFagTE/i3WR2D9S+5kufNpxvdpSzKbcoieDvo+O6vLYCmG+v1Vv9g5dmyqsKHbsG4Zb8YmHjxAGL2jzqxEvT00jD7tAo18SAM0yCAnSiBEtgdVdKIcSvxb3SHrbTk3pKs6SSQiyev4Rqs1cXtmrWw7oPf8PbbVgxgzpzA+fNA+4zzMPW8RUZ+rvoWdrd/XRFESpD4OvvUFwC4L5hM0mQePz2u4jqsOtq6OTWf4jMus/Z0Z0zBFHRVu5nxiubLkWX75gW3cSQGMCGkiYsXxmW5zwX368CxmNb/MXjGFv3V+LgvYOODW1zbJGQsPNajjwLTLNWjZG36eUkLav3FAzEg0lrZc9H8e1Atu6rNH7VfRfXfLPXwGX3+hybv1/PLe9OsLJMHx+2Yv7lojpaI1vMykwDNJEcu0CglQ3UCJ+5TIYBCAL294R0jgO5agAyQpTbYv7hb6YLppqUsdPFzCrRGREQPS//NTLukJoF6DD8HtUDTCCv4Ny+O4QTy3oG7tqh5qhSiN3ayHrB77FJMQfm6L6ZorydiEdvEosuJRMupWEZP59ZJIDh1EieRR20S3qgZ1g2eZyeBsBIE+1Uby7EcrmWoTBewEw/jhNyI7lbuf/8FJk6MPsJ0tLPlJFhCjXFHbIyz24Pi6rO+L5IzEcQkKswm/wBWzFc7TLeTpij79Cn6qO//13EyRp/v4kgMoFl//IirofSOSxPTXKC34VOroI/dtI4hvziPLMiBM3bsF79zorxjQl3ArVsDJCvJ3UwL4Jyw59Biv2XlmzFgDT5cVZURAKoNTj0cw25H1yhflr6Z7QJO7nvTxNAkgBWwQWX9stHl2xvRel7340/8Cau61Xj0VtWXSIIZO8qFae7clnXf189LIYBCAL295x0jgO7VQHT5H8ZPFEx11E6tZ3YUH7x8KJP4mQ9nDk7/7SR5iglEPQZa0GrCSvX77OMb+PX3EEyf7rqXp4oHno7r1APOPQieGZeHcJf1AHbTp+J30/AoHsWP6vci2Iv9KJKgueTUOGLqhHYBj3txD/qMskjQd3gcT+A7uCeBVME6rHVLyjFdwE64Y+ILnicrt/u+dNnfiy24iTT4HD3xLMaqTShp8wdqumyenFIw7doBM6Jkz0bgFbyCkapvdbHMJuCd8DW+hqUHh3HjEN6jjyMxgCZp4guX8Ve//OL5qsQ0F8zkNe5phnboI5XGNuxAafvAzz3nKhYc33kQ23Z6rsf3WMmxIPPUN3NBMCtPL7Q+YUmmbJy0Ed3GlLdd5S+lHoX3blvSU3SZzg991HYBJ+e9aY5Ju4Aps8MKQmYVkGEYjKEYZm/OjOCjKKD+nodmKlOYcdJ8dwkBjO8sTtx2Ugs4cbjpvRwjgOZqkDfCn9eiJUlypr9qr/howWDJsf5RUnRNmwJNmkQTvwULoCwGbCySTndwUjVtAdwRVBolI3bgIjIhCy6q01NWxBSLjUlyxb2vTj3g3EWg+aLSunGT0QVPYbJLVxio/xysFXoN/G4H8McX26S2POkXfOO8G7HguFVr+XP0wJA8n2PMGKBRo+gkkI4V/8XUDWXVNmtKd8GanpPRqxfAElvJKQOjrdyxYZwKEbiCDEiP6yo+8yt0VmW02OhC1XqaadNaiS/JJQZtWkfYt4l4Gk/jS9XPe7EZW2CJb7PPM/GI+nyg73t49uBLmGcZ033qFtPko3Rp4Pp1YP/+aJQp90L3Lmtycx6QNHuaC+4EsDr+uINwP47vbA1NnsGJDE9aiDNksOKoqWsZn+YPGeH6GrD85cTwLuiCr1TX+Sw6nqW0nUH9d5/PUG58b/Xb4scno9akLsl+b7pjrEk4M8WZMU7B/G/QSW32LD7BWDxr78L4QGoBpkE4NuE+VMAm9ZsZm+zEglksgP9tCyDz+wwdcjWnmC+rl58kv1yGsDZNVkAFnvGu2hWfB0bUNo4RQHM1SEL3yaYHUeyoFYfWsuF1zP0lrfrMBxdf4HPmWEkfXHmZD2/eRDSdMykkqTUDtQVQZ9OaFQ7cXdXM0tRxdqwdfBPW+NybEw8CnsPdAlg99Vr8cdvKJPUUu/Qy3rWJBXUOZ6FtAqaNcwXOY+qEVuXvU24lxm2ppTY7+nh/9Lr8gVplMw5QVwKpV+wA/rcnTG1Dd+pjmK4exno1nxwvS77UeX4uGuiqppQOM+C5kKBUhI57LYz9tjX2J7TEHLS0q+h40gJMDgsg+0r5E8bQ6cZqJa1habvlxxEcQ3712bScDMFQfB02BMOH+z4wXj9vqNvGygtmhSF3IeiY5gL1LX/4IXpMZlyj/nYwhuEtDEaJEgBrBjuR4ZlQCyD7lhz1ud3vVbN02pKcj6P+aQvMRiX34ped0R6Gvpm+xthL0VVCFob1SdZ709Mzx1QdaNECuOfXT1QyGZun6kl8N4ThAM4gO3LCujE4z5yY67q/QgD/+wSQS2er0KDVWCdA53u9rOpsQ/lXqKT3FoByqmgAcD2mF6nb944TQGY3MhV+9u3maI6frRdE6hMIypsbjNXhy3jkSIDF3NlicgHzN67aKdOQVI1WzE4dI3ALVoWD9aiIylivTu9en9MUCWXAsI5TM/vqhLVAH98kgMxyrHlzGZbhIfUz3XOvwbV225P4Cl+hi/r9GYzBODwTL1hpmeALNiktT1qVnxqKA+9ZgKHrmlp9HToUEW8MUQuDZcssqwmtPKbr7kDZJhjTaL6q6sL92ZyywsYGoLuF1tzWnPMP4xf8gkbqZ1adWY46WABrvEMxBMMwVJFGXQEiKa+D7rOnJIWYFkAPYgVWoLY9nk/D3rMztn25GDJdwCSnrLv9haU04mKt79bNcsvR6+A+F9x1NN/Ga3fcN6Y1ne5fXwtas08JjQHkPuw7n1fJ1XiP8llPXLkYq/h2GzS6atVM54LgTEh+Wwamc4YZmHLFEtZf88j7aLVygMfrYY4lqdUhNAlfvdoSC9/75BAMgSUuz0WNvkd1H835H4orSJ0xVGkbcq45pTwgBPC/TwBbASjv4aam9Y+iEdQm0WUcsgBK7ZdvdWMdG+sjwTEC6P5Anp+9Eypt+0Z1pnqOnVhzxtLN48t482aLBLLRWsiEBmYRU9z0rbcAuoHZWCSd2l1J1fiie6T+OZyDJbNPwU9dwohuDl22i799jU7oBGt8FFrWuoBmX53IGNTH1zpozDyjZaZpxFzMRUv18yAMxzsY5AJbAyzGYliCZ2b1EnfLZkxYJ6XlyRSB3vTqNPwAq8j8tm4f4EyX/qAYMV27Tz5pEdNi+a5i97EMapvlqI26WA5eLxIDvehgjE5SNlqmGEvEVq4cQKsChcHpSjVFtele0pYG1pXejPvwF6qo/SiiPrrkpyrRRZPZpLwOGi9PostM7rob213CJLh9RazHelRWux5v0wfdb45zJC7KkwuY6gOj8CIexmJMx6OKPvOVQfLMesS7d7tWhalVyzW7/Qc8pqzHZvsVdVAPv4J1zA8fdublrsfCbHuSB3N+xFTWLjmq85i46HuUi1xWgpp8oglyrrPkvn6bdQYb9mdX4Tvsf8fsCzDllLWooVX4q8JD1MKf94cn63xyqEPoGEDeq9RXTTfwWTsWl0kfWvhfY0BB/Q6wtLFKYTsyVCiltGKdqHutzykE8L9PAJlWR+15WvRY1JUWv4OAqj5NZd8KQFTAgTUrfov627JVx90cI4CmS+bqVaD/gegbqGW+tdiZpYp9w1Nhnzc5GwO4SfqaNbNWTySD+mXnRN3N2CDiGHrU32NnXn6P9vZNTiubFjblMVgBhNlfbLpOpHlsSpDwYe5eeiruSxS/LcyYS2L4QZVp6DTfIkovYBRG4wWXA92DLXac1pd4yo7fit/ZLH0rlgFLiqYXEzznul5fYvRlqxILBZ8nogdIemn5oxuMZeGASNxGagQhEvtyVcHHHdYq3PVCIqldwKZGo/vCgaSU3+nMVXMePYCVOIDCdjLPTLTBI5ipXqKcf4xrSw4LoHvJQSLuKUyC35uxqCebdEG3oMmOEkDTBdwXY11itdrje0yLWjzoeavnAq9RtmyugspcPGjx7etIqzQ1dRjIlCnWgtQJWSGTAHJuz7YMabG2qlVhZ9nGta0Tv+t7VFtFl+IhW2C+aO7LCMqUQYXxEOOHQ5bjhxPRWfqfhY2M0QWcnOoQXJxR55KL4q9vRxM8Cv/vhVXYQLd38TJexnvqT5YGLdGrvlog8B3G5ktrtz6nEMD/NgFsDCBjVNwfiw4yHpCpRvdEuXoZ88dAm2PGPORyNRLAYzHc5AxMM4PTMlHg/MKFC8isyyj46OlgPsTonjvc5XUU+c4ShN3w7mI8O7eBElzlA5i/Wy/u2FtSx7mQVH3cMboqgy7zxocY4WKdR93ewat4FZZ50syC5N/MSBw3zor7cuJBwHOYbjmuph+95lmXTScPlCtwFn8fscS5TctmbFfAdHsnJYkyY6Imlh2Np7daZHZW22/xwdEOoJuGLZoAAu6yPKabNSnJK/tl9p/u27x5rdgxT20J6qM+/qd+yoWTuAo6lPgYADZkqYuRDZep4yWnBVDX/9X9Z+KKDpP4C5Vs2Rr+XggHcRCF1aaMx3ylyHS7bJ8v7wVPLuA+X1SwA/J5/pV4ALXgKmDJhRmJiae4OybhlMYONZf2oYjKzCYRTI9rqFYtlU24fDkO9lOPxT3RzH2+mNZ6bktxa19LjcTxSLZ/NvFjMs24zQ/g/luWHio1SW8j2N62Yba1WHTOik9eVf4ZtD06xmN4BhfYMalD6AW4k+oQOtGJmP58uxEawUorZ2GD88jmAo252OiKSUoTkws7J+pe6xMLAfxvE0D3e4+JHqQczINl6YbEEEBPiSVwggCaD2Q+EJrv+ACDL92pE0YXMHXQGCwbV3v9dcs6mFSta1fg+JSFWIgm6pTu6f9mP0zB2Jb4yXa/chu66Rh7RNLoVPyZqYNGctE94jN8pnKCGBMw2Y73i+5zJC4gi9JmpCh0KeyMF6ylSlml+5KSAOqsSFY8ONJnOFIPsTTEMHcuwhs3t90sI0YA1ItkO448yIOT2I/Cqh6ySQCT2m3qXqWCL4bGjQHKqGzZ4loJ51CqQigYeRiXQ7Ih000rmJwVCJhhuAEVUAkblEWCRD65LIC6/q+eMGaln0VoiMZYZM8lMx5zb5mmKLjxZ7tsny/vBXcXcMT+AzgAKxFItwikQh6cwGnkcvme1R6Ymcw4OrOdQ1ZkxQXsQnHsRxgaYKn6mRqbl1NnxTPPOBMDmJgkEPYrKe9J94eFeY9yYXzj3irIvPMvRKQKwtJFt5VYNesos3RejuNb8XcE7RgAvQ+9gr/0GJ5hlverWNFacJuJR7oPTqhDmC5gXuesDe/H/Vin6gCnwS1EIsgFghaYgzlgxBbwc5VhONhlMBYutBQsJAYwXq+WRG2U0mRg1vE+V6oLiXMBJ5kFUD/EaC3gC5DxTF+ohGVgQJYJmJ+vu3IBDxsGsPxS/ahUl5iEoJP6AaczHRudiU7/74ePMQb91MOKL2Az07APxtmJFJ1TfY2vIy3JADa66VhWyEkLoLsO2oQyH6Hlcksz54mg7/FdhOUONpvWm7uBEGXVcH+oxXZH+vLlHdedr+cSrRzTi76MR/ZYrpbZ/X7FpL117Iesru9Kor3lSlHcdXsfTiEncuMUKAXC2DnKaiS129RdEzOm8dLWp619ZsWcE8itxrAXRVAMe20RaB4nqcksz+me0MKY150opYb1DZ6wY2H5dzpEV25h/NxTYb86kgRiehyYUPZt8x/Qbenjd0DdCrPtF7X+kTFrFHRm0L5uZr9pOaQrviOsLAvGeEUUL6Ush0683E0yxTjRbTFUanQPJ0jqBbIJrnmPMsZSy35dQShypb9iy35xn6519mHSckYxARtKtscbxb/3GJ7RqpWlDsHnrU7a0eekFZ33MsOLqlSBS232uJ4n8fndTALh8Q+FFENYxF6cRg7kT3NaWVvNZgpF4+mnlbI7Y8QlBjA+aCd+m5REAOkHOhTlCh4TlQTCBBCrSC3AeD7mOfpFEoiZuVmvHvB2hRm4b7iV+bWzx/t48cgA5Q7lzf3330AmOqOjkkDcdQB17BZvdlpykqLpBwBJ38d4Xp1yeotvcLj2E3cE7vO3jpiKqXhSbUd3wHj0tbvJMTJonKtXp2IA3S0g7fePwAi8pvrQPt1PmHbdSggxm5m5bEp3xAdfX7u9YjunGV9U6pO+6B1pxVrqwuvazcLYNLp32dx1GU13WlKTJtMCqF3wnsZbHhuxEZbG4RR0RldMUZ93oCRKYhdokcqOcypeilp3bElNZnlO9yQQ1nNdjRqqP9SXfAGjjeFFx2NevrsKHi+21pEYQNNtSnwGX4sWpv4C3ewYV4ZqDIJrvAldfLQCMotca3uWDNmPHTct6ZIf8QgO4i70xyj1N0ubhTxUSyWpOREDaJIpktO/rEIwcbakDpExO2QuQPmM3nTNmrNnkQ2FQs8qoqZb4XQnsP+6VU2Jz6DH089x0YXVscUPPxytDsFn6I8/WtI769YBixbBDv3g+Xj9fOn+NmVgKLR9M2M2hFw5j10ogZIevCU5cQqnkFuNKfyhhlj31iLQI+GE5qXGUVzA/20XMMkdJVPp9mWsH1PYmBFMmZdTTIpVpSpdZWCovuoXMjCcpFq7jeKs955cimlnG6i5q7NO6XKhJYkvcMbIsbm/ICmGqh8eSfni1i/t4UGDMSjC8jub6f/ulkrTBfAq3rE19rgfYwbPnbPck06Vs3O3gGxqORjVFlv9HvXwIvRfbGX8aiLE7Lant/Sza5vGJQbduTPw1VfRgfKUgmEcTlI00yX2vwJPot6Rqeq03w3eju83lLIDrbUFkL/RglYNf6rtKNRqWjeTmjS5y6a4SwhpDB/DD7bIsDmH/oTlfqILMxjhSJc+yH5hOuH+iuuauhPAZpiHebBqL7+BNzEcUS76qANdTpURGSKv4GqRsnis7D+OEEBzjpAQzLoWHbPFrM21sGLOmJygXbnmOPlsoY6dbg+G/IkVN63yXtTRJAF8H1amGkvdrczTzrZK+XoxpMkHa1uf1qJfcV0Uh8rSxeO0ahP3mO/bhQoj3YmDuJE9L4KOH1Oal1rfNWfaSzh1g/YKgDGvLdMvseez+Yzn/azVIfguGT/ekhTz1Hx9DUwLYLXK4ZbuFy2Waauh0o2ooGNYiwY+C7+ZGom2T4YiXeR16HKgogMY39mT+O3+yxZASrlQ8ZaR+iR8VFGmlgezf9m0EHSPKCFo/s6im/EL5rKO4VgWMA9urgqZGavlLCaH9sX4MmOxfr214uZKj/p+jPFyj/FgFhwTRLp3h4q5oWh0UjTttjOzMqtgrRqDu+uF/amDX/Er6qmuuevu8UHOh4GTFkB3C8jQawMxENHF2FeqqWRlnGr5GmYHj4JVgsWTuKmJMzOLucpm3Bmbrx+4sV1TlxjAam2Qeo6VFvnH9MOo1KIAChe2sKX+GDMz2cwsxAy4jGupMtjWnaQiTbSCr1xpWTHik+REkWHq/LGZVT8YV6flhxh/diNdVtsCmBxWHzM2i31ljOlkPKX67UmsWsdjMoO2Xtg+R1zA5hzhQqVKy/zIfuOYctnlwimcRG7kwmkcQX4UxJ3FglmOkgRDN3NBRxmlQyhkl7SjVM/4oGfx7LPOxADqhTNlYCh7xWSEj0ZFoKgq2RjmklBhysIk9cLGvGfdCWBknjwIOXcS1/KGIfjgPpQta3k/uKDPkyMcew9ZhOp31ECHu373GJ7hPs9ie0b4OiTFjAGc+flppMlvxY2evr8JNr09Xz1nWN+XmPP9RWvfY2+UQJHw3WDde8aOSiUQ59/U/2UC6Dx6DhNA/VBgjN/Ip3ehZteSakzHHnoCORd+A7qGqd/Gwtms23nvvRbBY1Yn3R5MDuE/lm/67LOkjXfSZeAo/dIe01S/i2IP9ikFnjubqXc2Dn3wDKJMmhT0fQ/gw9zJGEB3C8jIa551q0wC2Bqz7AognrQC3UdJ62G/fs689GKb7KZLbEmqBngowgrGz4wLCE+fWZEhLiSohUYizPZzquZoGmlpMOTGCds9w79pWeAD28nGlzZ1z8xMcZ6PGLZubVm1mQVvlvoytcTK4h/8C6ucnalHF4Z9OJk+zCbiyUEA9b2h8euPD/ABrOwb1nb9EY+6QLsHRVEU+8BYxmphJxypjmDOfzN+jwTjAfwOU6i3eK4L2HPKskDpZnoh+B0lhj5HL/Xz05ioCKAW/6UHY3WT4SrI39cxgGboDLUqGQM3dtRNlHupodKzZJZ1fSzFBVX8yVXkOik9JO73jvsC9Og1K4FmO0qhYvrtLjGAvAeuRaZFWtzERpRHpVQbXWrDP29F3KjYcYZ1xKc5kQCjZWDKhezA5htWAS7qvfZK/7V65rAONkXoqX1IGaot2WvhnrNWlvnaX6/grQ9DHbF2azzEBfzfdgHHZ957u42jFkAzLi30yimsP2TFSPyMpng27Gdb+4nWJd5AtLLTtarjm7gt3Tmsecrvk9LtSCsRhZspkWJm//HB664ByNJe3WvvxHtzrED4hTk6oskZy03Jxpc0SYeTWcDuWXhn2nZH/vlWKYSO9/6Nb/9mkRjXgGozcDkuLUBtAdRkKyktgKYl+c9U1XB/pOXapdBvutDUdogACTZJFZtJ3Isoy0l0KSoKu65Y4e2tE/P+Wj4iLhkP9yMwy5d1RJlpGIqrdjnBz9ATPTFBbc44wW0h5W0NSiYv6Drazo3I9cjuSS20eL8CS8m9Hv5nW8L5N+/bi4XvQYZ9W3E7fQa0rn/ZkeoIugwZJZcyHtqGFacZCQOQVDN5YwK6ozus+0Fb8s1RTZoEZZmkS4/ZqmZWPxdKtLzp+Mw19/ZA5fWfOxLgb4qe87lRvTrwxPUv0WeDpX3J9ibesKtSJKe8kYmf+wL0zLX0qp41E81qhG52iQHkfXEmMhuy4fwdCgSmFdNTxZmY5rhTBLBtW6B2yGosvxkd4zoodLQaz8yZFgFkZjNlmf7P3ndAR1W07z8pkELnqhE/AAAgAElEQVTvIAgJHQEpgqD03kR6VURAKSK92RCkSZXeEQEFBaQXERBp0qQ3kd57b+nJ/zwzzN3Zy26STe7G7/z+O+d8n2T37q1zZ95536dse6UlKl6XyYKDS85i0II8ngDQzYOSJwOYuBvs1gBQn7hzZA7HldtSgvBm3vIo/mTHS8wu86XQG5hMWzKumEVktjCpmsI50f6tJA4hEj6C/s81h9mujudE+7eboFwjsMHvXTSIWWVM0mTnkdiSFBlADq4U0f4+7H1k2ihZi7Vzn8bv56XzisJUfvghsGLBEzyMlpkQnXXq6B4PHiyc1wyx3KQMxvXy0rb7ReB98gTCfAMxfcwzkR0mg5xuCcwoU1OSQces6A7ogLniUih6fT1dETFoczFBkgDB5FaCxtU9YwaHzE1m9lwJAIlTfIqUYtIk6YP6c6rpAZZZY/K/KPupDCAXNMyAjXtiC66K4TCOophx7osXA83HlZE0TS8vRIZFIcerXpaSJ3QbMvaDMvd/g099Kd2k8Ma9MQ7j0Fd81gYL8BNsLH1+pjKAfGaUHGl9uD96R0kIBeEd1AFUsjJnSzRDr+xL3CLyq4ueM6jlwng96thJ6zCj2rHqOeGWRDeT/0rgXB8n7BagF2OQPNAHXjExeFzwTfgd3ivgPRwz2Dh+ngnJjuy4jqvIjldx1diVDs+ILQDkO8ZAXXlou7MEvLz9Wvg2qi/O8UK7IcgxcyAYGJIENHu2HH9YUcg0ohc6PJEEKIq4H0lZXiQROG66Y8HsyQB6MoCO5mpXPnNrAGg2aD95OQVS4DmOoQjq5zpm2P/E54SJBaS+nTsmbUfHVwGgMvmm0wF15dh0Fib/ZtYgTbLnuPZQ2o8puyi1X5aKiC/igOEuFrA+cTDgHHOxqXCNYCub/Qr2Xsvh8Dar63uMVEgjTGccr6lUGV7txB0DmrN+oPejjadzIUfUZaHzlw03Bf5P2UjpJeBpvt3RJVICRstgj0ECUMdwR8aA+yaWlZAGVxvhBeeQV/xsORqhCZYbuxiAkQapiNjAtckaGzIU1Kpk9iopm54B5LuwKLQRGmGlOIXsuIrrQq9eNnry/nitCtIc3Cr+blr3OZatl1R+q/qQ2YZsbO5pIFucjeXb7/ER6sNmjUj7sSFCV9/WFAaQThYkpE2LtA9qzyM3ngjItMSX1vHd7BaRXz2Txnv3Wa8wlKqVHskjNBotgLw4I/rLf21xqO6gDtNoWDccy9fJxf7jYhXwfs7tBhtWYRYVs50s4Qy4bzyIN98E9soEv0ueyFa/z3YkkNMLALLg2KZMEasFwpS4oOdYSw1bqg+c/HA0hkdKELIZCmF1gCru7ePHSJOGDrDg/z2269D/n/zhyQAm7kEnSQBIFjBLhzsvylUfgdjlg66Jki8Dovg2qyaM+BxPAZAZGKXCU9AV4DWhv+0ssxMj3BB8EQVmDUvhgHEYlTFkyaBx4/gc3fVt9NIR8ZJTL9VDPUgT5RI57iBVcEZBSDC3NXgH72Cd+DgnLhm2Y87OgOfPEqc7BjRnx9Qzyfe8MiB9zH08ypgHQ9ueFQOv0gjTnUDMzix/Jatip93lLs003SaNZXMy3RkwxdX0AEX3ZubvOmM6pgt+Fyn/8wQZQcEQknphxHPQsVns2xtCKhoOG6l8Q/A00l+ca5cuEDi5yRdtfaxw5jv4bGxG4dtsVR8y25CNgo0AVQ2bsQXV8DqO4MgLW/W5aGdkh9VzYSmd2Ro2ZtAnXG2KPIflAopuJleRwxDkvvNqCbQvdtAtIr9mKMfxefvxRmfpBa23je/Nw8asbe36v1X3M66+6uh7fQH67RdPcPyyjeXbKXiTKJPqnsbE/hXHkRfOKi80jV7smFl69m+zg46S6OFmZia91QGgnQzM7PES0MvGL1q2FIQ4ZsBVAMivSKRTmeUemGB4evM7d1SwPAGgJwOYkHdV/41bA0CzPdOJZMWR4eoRRPkkQ6ZUYXjw0D5+p/AnJVNYKtDtrtQJJ+UAxzJXhw/CDRzWTpRDBUHEdl7au4f0QqfN7KzBsivZswQNuysAZClEYVE4gf10oxrSHNgizrdp7adYtiGFyJQpDJ+6p3p5sR7WYj2kSbu5UceQkhT/BQZQdzk5fy05kiNCgMdZmtczICQSsQ/xXpPUouRIKFOyDu+IS1LyPe4iT3CgJw6RmTFiQ22yFTEYhG/wIebhAN7AR5hjZyelZ/laYZEhB8Nz1jUm55eajLGhn4pssmpJuTDiMfXSHK/zQOhrYnH0FCmQyf+pgeGdNEkC5JO1aYEGoXSplIuMyGw5RTbfqvM225B9dvx9NAm1iTZTpDoNHhr3W5eCyZ5d+jCzjPruu1KJgB6uvrWqSTwByV+Znojy/PE7UpCb9M7IMxfcigFkKZr3tlnIfMPF5zfUNkrBk9ANPTBJME25HUX1HQVBionO+81nQfyrO6oo+gJ08dS7OHRVsma5wOyWa404z210qn/RSM55W9jbSyxvNHyM71QZWLeC45exaWhaPTeo6yFWONmQgSi7WVpVHRjxO4r3rykQDcwAcsypXVtCIYh//QPS0YDewMoaVF2Y1Tq2ngDQEwA6nKxd+NCtAaC5BDz7ck3UxCZxepSzUEw2R+fLAZD/i47+byY6DkJj+97ADSHBKAVLG2KV+LdZA1BhvVQ5VZUnlcMAgwKFGXFXCZgDvWKjMQBcdPFtpDouB9gG9SKxep0PmJEiZowDFoNFyhgw2FiE98R2sVnd8XsG9GTouUP8NrY+q/pRMtgCcuXrqk8KnAAZuFMGpCfGY7xwTaQx9i9YkayFXQbQXeQJPvODB1++GjpQrIAt/bsSDYyyqbi3Gtuc2apjoKSnbLQWXIlG4t8kJ4zCZ4YGIyfJpPY21gNA4YgTJgMj2u4VDrxoAP6p/cb+vjFHO1S/IkWtDy08iTq9C4msLYV9mzZ1YbRysqmeNWPw5lOrOry2SD/l/Fke4cwtDnM260Nau5XPfEaMLyp7rDI5/KxePWDu4ZLIdPUQIuCL5AgX0AjlDRyZIjUaV33kFpFfs6CyLuf0vtdC/BQj39XjacphYJWdwleaosjU2DMHgI6Y6IRMsLph9UJUX4C2rXYV8/54VZznvSpN8GGKXw28pHqEm72qo1qMfEYp8cRwwOHfDMTJfjZb4sUWAFq1mFDnp2N5dSkwis+fSV1K6BpyHFQYQP6uEE4azH2yhdtigV2PZUZclxpKbM/3BICeADCxfShJAkBVAh528T28h0XinGkfdRaSmBCfltSlLvqdrhl5HMch2bN62YgBIEsQLFUQs8IJn9p6ylrtOQLwdZ/nwl5KNYUZsXqgUvvXV+AzZwLLLkrySjiSoWBwuNBRZNZLTXSKMZsDV4yyrxm7aH4uOsvWXdfhqC+okmN63MM9ZBSbXHqtDibXWS8CPjLw2BgIccHA8qIu49Ee3wudOp297S7yBH2vqW/JVraszMzQgu4PVEVV/Gl3eeWwE7tQTnymFg+0ziIWMwq+xrYsY26GFFFfVfgLfOU13C4DmNTyH3oJ2AvRojRK6MNhn5LoUOyAXQBMB4dD5T5FtuVSFql3hb8xfkcp8D5ZpYup488YvM07UAQZbpxAZDJ/lC/xHHv3yUqDcocJhZ9gWecK8jayZwo+oDCAZyKDEIRLIPY3q9dt0A1iwxNb1ipvrgh8M9xXyJRYmX0yC7rfKFkPwf9IKAdL0dtRUXhbM9uaGo/tBM658FPOE4qJ7mxstRqOoi9AP6pyDrP/lHjWOzVbo33yhS8FgLoLkVmmiSQcvkMqGOZ4y6YnAxj4UluzfXu5IGfW30phemVDx+M6UxSgsD9Z58pDWs8yU+BaJTvUM3DF1cXZc9M/9wSAngAwPv0ktm3cGgDqq1mKIQ+81xPdYyaK89Env/hcBD2Dv/46Pltas02bNsDln7ZhGyqLHY5BX0NYWWd3cgL4/nsI+8eOP5YXmmOiMS3xQj2efyrMiJWThX6lOgaHBJbfLhVCIZwCMYyv53osRJJ5rjpmRf2eHrOcVELgjwy4hxAEOryJfIbEs1k96cX1xJQkT4n0l3DwfpDYfDGaC31GloAJGyBbkgE3y1tkT+p4HAr3TkE38Z1iDbojaOK+iclWbEd1XdQrvIuMSIZIu0slu5M4TZ1Bvg0VURlarQwAnSz2QrpSTER39MREcEHEBch/4W1M4sm8eZAEnNAH+OdWenFuv6MmavP/Xwi78zNO1L1u2jB5LbJuQ4upFUW22ipWvI4BJIHjemQmIfrMoDqv9wUjcLjyej3kOCqDqVnf3MAH/bMaDHIzBvDXzWngF/pYMLIbFvxXBPI6Xrbkq3fQrEtGsaiycjGkV01YMvzzknw3pbjwQ6zGu6gPqW/pCLPLoISMVMVEd/ZuEb92/7515WB9AfrH5JPYdF1qWHLhPCx4rrEAVeejB1XUtlQMa35P6RvCKMwZQP1a2K8IseBzYbPyGZC53lKzTme/VsEcg7zHgnMhxf252LaRvmIQ4iXdQC6kKIxBjY8LvLQaDzwBYFwjvevfe0ggrt8z/RduDQDVYMbBiIMN7a1GCDMTwJEpe2yXooDBibvc+P+aA+m5sTahZFV64x70TJISFeZg9bxKXdTFb/IgTG/wwl+0pMoA8nBkDy7ZHwz/GxcRni4zmpa/ZWQGiFlhloSxqXL1mImO6IjZ4kxbYyF+RmuHN4qDLoWgrZ704noqipFNcWSVkVW6hXpZiOfFbDMzgK0DVmBhiCy5qmeXM6fMxrkraHI2YenYIOrR1cRGkV1io4A4vUV/QSvx92j0wwCMtrslr+EETqCI+OxilXb4vcVcDBpkK1+6I5h19kwY5DKrx+5NKMGXLc6ifDuZyb9RtTU+DlgooHOqb/F+3+s2CLl/HCK2OfTtBrzer5YoE1uli6nf9wZ1I7ByvfQovBlUBnXT7cGhQ/JqZnp3QcfoGeLf1AI8EVDaOE9mhJlNEhjAS1Hw9ZcZ2P2+ZVA6co945+dEfIA2MVLfs1PlfzFra34BqyCUwipcnb5ozpY5Clfv+sE7OgrUiHwDB0X/6AdZWqiJ37EJNe0eFRena9fKd5yNC4UqVWyWZQyUuFhi41jAYN2Kpi9AF/U7hHU3pKf1NHTB6FzTjAWoOhbf3/b4QfxZyv84DoUXNgJ1CmCznK2XYYsXl3hasxUcPeS5uLZqYc1jcqHLfqsaxbd57ykFliYgAs9DbGGHvnDg9kr03Mxu5ncMKpVQvRX33JMB9GQAE9uPkiQAVCdJSYbZoHMd8DFmYQ4+jvf5c8KjnlJSNJX+d3S+Zhs4unwwWOTAsT51S9R/LoVA9/x8ARdigkSmIykwgGYclG+OrDJCyJkTkecuGYB1gt3Ng34FbMd2VBLnvQ+lURZ77EpL/JwTI0ua69bB8kkvrmeqAsCy2I3dsAmy9sIEOzwmA0BOeMwA1sBGbITUY1HCubp+ozuCJn3y1q9JxyOyHO2HMIPVuwyNEQp/AxqhWKv674O8L+NCdC7x0RI0Qwss4WN1azDr7JmYg1xK7OzBW2LzOYHdMC7nJCMrw8+YjfIaNRIDHn4utiGe8WhQA0vt4OyYs7uuwS+PlDy6W64BDn690sjQfOM7FF9HyjICrd7+CHxXBIAE8CsvYAZQLWvcw6KNEmrwu08d1I6SWcMJ6CGIF2x9y+3GuL/KWv4u6OL5qZ9ex96rUlJnNeqjAVajHeZiLjqIz7pjIqZ4dTdcNNQzK1YMOHJELvJYNlVZb37PQJUlU2qrUjaJgZMVTe8XvDdj/pLv6Y0WPdHp+XhjAaqORX9l5ZZkFuZWgRLPm+MO9f64sON/SWbRm/LitSoDaO7frC4ceCCzsLoUmDoH2pNSGUY1YpNVFSiFdwieR0tGPJvVAvSeANATACb23XVrAGi2jDL7a6psYHwugul+slCtWmk7O6aO/TDrr+kgfvV7nU16oUZHBG+WmTQdyJ+UMjBKCHr5n2nh+/QRQnIWQItipwz3BVUC1st0xHEdQTEUhaSWjkdP9MZ3Aviusp0MYjkYMrtgddYjruc/ZgzQvz9QHZuMjIdZKoX7YDBOcgtL1G/jL/yF8mLX49AbfTHOTsDbHcQJnRzBe/XggbwylsHaQZIgCCI/jiKgrtwrsJ/NHiINMuM2IiAzWKqlw33cF5bgAJmgzDK7O5h19kz0IJfl7jpRa/HzUymSq+vrMYvCvshs08zXJqLjSenvdWbIz+i9r6Wl/UjHAJZNfhC7wt4Qx6KDSk+/GaJUznasxxwUmSgXnf/2nomgER0NH2lqKTJzTAzghilncSpKZjXpJNLGa6HAAPZ6YvNqbpd5HfL3rGt5NlwvAee5/zfW3HpTnMd0dMYnmI63sMvAjTK71hU2A2NFTtP7Bt/VypVtGUBdXYFC0seOOXvSrn1u59e9cCt8qleROxgwAJHDRooFqCLc8GNdqqcSthoLUH733nsSz6ueqwry9DPiwpr9jyVgK+cGR/ZzLL+nxhM7KTB1LoSn6E48XKA1w6/ia3Np28rz5P49AaAnAHTtLX15a7cGgLRWIktKNX3w4mqaGRxXmlWrPGfHZDaAki2q6YMU3QAUHlD/va4nd7pBX+RfPU58TSV4FYAkhQyMWQj61EXptXkYxdA4+DCGDnWOAeT5chD+A9XgA0m7Hos+6Ac6IdjKHcHBMLA87n4W+j0mIWfkSED3LmZwPj3VABFkKD9dluOpys//0ZHiMEqI3Wwr1AnLa8xwu2uCM+eCv1FK6ELS4i0lniIUAaBO2AT0suuKMvAe/1L39EWEERQq9rMuRu6OYNbZO6JL8lA+Rc9I9QmchpleXQTmaeBAiY8iQWdK0Znoekz66p79Yi56HW1naQCoB6UNk6/HinBZ/ySr/Vu/b4wAsHvutZh4Xgar++oOxlDvQQY5QWUA+V2v8n/ju50y8CID9PviU3D4MPApJmMyuovPe2b8CaUnvGc5Hla/lrZpVmLeI8n+/gpDMRxfQSdCncxSGev6/CnebZZBVVN9g+8Gg0JzBpBZQWY9mdEnNMWKpgfhX5X+HUP21Zb3uc4gDPUZbGgmqmN9DVswXQfrsQF1jNOgVzaxc+peMKvPhcRrrwGFCkEQiIgfZXaZDGgr8Yxmm0P93VO+0upEOa6vXGlfUSFGtzukAD3nO5UdV7+xctz0BICeADCx765bA0AGDJQnUI3q9WeQX/y5CK2Msld8L8IqnIez45GmTxFl1ebAZidWFEcN/Jn+eyW9wEF2YsYh6P1QOgwc/XYdTuSqm2QlYDUA0y4v9Hk0qtWUulqPCpVFymO77XSriA9iloCTho5n1Cdz/pYBF+VHFM6OmCECtK3CbsX3uVesCCFiTQsviiCzfYKpRhlV7YeZAxIUGACWz3IGO27JvvYj3scH+NHtrgn65M1MNe8Ts4DEA9H3lGSbPDgvzonaZ5tQA1UgHTIojl4Ch3AH0i/b3EjQ8UeYCOjpF6xneawWwY3tuehBLkHtTU6PwOdPJK5X9Rf+W2GjOEnfHrsA392zPbffgj6xtASsM2f/aDsfyT/+UJzPliZTcKV+V9D2kO1N7/3YGy1FlZlR6+473XDz0DGAl+dsRPL6Ej4wFF9hkNdQUU5tEfETFsRIC7mZRSahy4luIpCyclLXA+zG16dgUkw3cbwP8YOhB3gLUnbnBrKKLLIZlsLsmCqV8v2mBBWDpv37pX8ts3VsxAqvXh3b047/dzoR5/LkVVge3VD8mLjvsb6fG/dZ7ZGLy9HoL/5sgl+xHE2MgxE6zYUD33niF9mYPdNxeebPrHoG5qoVGcq3kFWcw1rv+qgfbbthzApT1oWZY9X0qpH5uriNlXOYJwD0BIDxf0Mdb+nWAJADkQ7aJRtSaf85osnHdTFWveTOjmPWcFuBhob23yu4ZmgCqt/rnrIMwFZW0bI6LxTj1bbuJoEoHS6RCQh5jueQtnS7/Svj2o9/Cv0/3bvS2T3QXScom1EMR4wsoMLXJSUJhNfFlTYnrR6+UzEh8lNx6h9gPn6EHHlV6YtyDJTC4H+z4bphSXa+WCNMq77c7a4JenCkJuVUeGywBs0yO34IFcLQ6XEfC/ABrsGxXR+v8Q4yIiPu4SzyIB/O/mcBoF4i40Ji2NMeKL5N4uI6Fv4Ls09I7JeyVmN2clevpZh6p7n4nJ68K4J6C/ssq9jketm01c3xGPhA6j+2xM/YmqWlUXqsX/IaVh+U9/j86w3QI+dKIzOlYwDf9/0FCyIkKYfnq/QkKSi+Bu+Kz6OGDEP2qV9aromp96HFuT9H8/MjxfGIaVVSQGSKV4S09XGkp0ppKgoVx9VYoWGW1oqmY+dGllyCAQdbiN3+1XgcRob3fkkGhgu4qZDvMhd2i5O1sdPp5FhPzJxiM5MEwhKyGQNoNQnEnAEsiH/wD14T5zkPbQ0oh7pnTBpMn267gxyX5kOuOJgxVteotrByDvMEgJ4AMLHvrlsDQK4wiRmztRgBeGdpUgYXR2M9f11wmUEAS33uxAASP6YPMNtRwXD/4GQdDulvqZoqVfBvxnubWtsA2mJk5Qj7orlbBkbX/apT5j7W75WYsd3p6uDtB+tFqZROJMRDKd0qxzc/BntQFmUgZ5BSyY7gQIQUJWb2j4FsUmIA9QmxP0YJEWQ2Zpu2pWskroeMUjYGplWrygzgm/kfYu/pdOLzDaglHBTick1I7MtkLgGz/xaKtjGXHU0g8T3mjYBgZA25iJDUmTF3xC1hsUZCDltSloDVBEnpC17vj5EthRwPWwGfswiqlkf4IXftKj112e8Gl16Lr/fJ0uvlTsPw6fUvDUyqFROinnkdl2Igej+Trg3re/yODxfVNFivP86NwPvtX+Ary5RB5M49BjlKYQD5u+7JpmNihLTe0zNvOllqWe5+aHpesrWtuAbVD/QA+yefD/BelGQdkwmuAhFiGzthlvjckc81dfQciZGb+xrxzitWxLcHxr6djgG8MuJHJOsgF2ene0xFrlGfCKwly7hKy68dfsBctBfbdMIMzEInuwOwT5MMokgg/LJ8eRsRkKRA3VrOqmdgzgBSrmwnKohz+w690Edgo22NotUqi8r3vUb0BqOcrchnamur5zBPAOgJABP79ro1AHz6FOAKTW9K8PYuMgitrvi2AgVsmk/x/Y0r2+mZJvW7E7BZXNEP2NwUA5ifcwU8pcqv+BXN5GZkLihzUQZiL8zDrRqo9HPhuefNCxQtKssRY3tdw56rMtOxHI3QJnC5ALFTroLnyQCJwZBentc18rpgGqahq/j9IK8hGBIzUGThWI5JahYwsWTMFrGxHPcVhot/6xkRdS9YCmXj9VV6OwJbd8nJ/ly28ljTfwc6d5bfceJwR9nUEQu4LtYZNnTmCSG+/ZPriF4/FEXBiOOgUHRKPBPPjzIshCy4g9Hs7Nz0AKVuXWDikcrIe03qFjap+QTLN6YU/6ZOILUxOYFfm78ZPrWlkDW+/BKRg4dZaqOmM2e/uNYVbZ5IYgQJN9eyljKqEMS8bTmeCQFP7+JJupxoXe6SsUBVJWuOM+9dGoGBobKsTdbylpQNwLFMx5XO8uqEk91nYOJEa8t6egZKFw9n9eQJpL+uzipX3tD68+ICTYmjx9bHSAQjrMOKpmMAO/vOwbQISbbpgDn4OaCDYSHJcYj3sjkWYzGk2B6zrPPS9RZYRYXnZZ9m1o9jjiMhaMKLCPegNizHLi4CrRCCNmcAdY9u2kuaiYs1agCbpLmVaCVwEAchSUiL03ZCy4c2TBHJLGQyW5XE8ASAngAwse+uWwNAnhzlKq5csZ2mTpMPwHMBiI9PowzAP//EZ8uEbeNIw42WbllwG5eQ09Bt0/euM4A5eLXLvhELbkns0MU2A7G7zpAkwQCqc2eQyUku6vQ5+BSQSvy3qrXGmcELRTmFwSfPk0EQNf3Mmlrq2sheu4Dc4s+NqIFa2Cj+/V+QQJQEDCeBcdE9hQgyGyVhlDgy/1ar6yVLbBlOuqBQfPkASgoSho6bsxKLo+6boz6kB9OcDJWEhyu9NF8+4OfLb+ONMJt3as4gH8HKpsZdUmYA9Swn7+eBECk4TmeKzAFPDV09XR+t39t/YfQuycg+XLU3BgaOMwIvKxZEegn420ut0OD5L+JYuXEOjzPkFmVaNk68B6Nex+s4hjAkR0qfUHT91EsEccoJhNvpWnsVsQ07UFH8Xn8vtr3SElVu/Gw5BrBbN5usyCkUQAGcxhOkFCxU1WrjN/yGuuJPenl/gW9d6U7GtlaSJ/TFT69kU/BdhMQu0sd6ReD7RpZeqQ/U916H1dHSn3sghhi+3eodJWSFMAq9WkESCNnlhBaxGkECCP/HZkU/4n7MGUAG2PPQThyD7/IMdDHuH8ckSoCNGmW7/dlxFVchbfC4+G6C5XbPxqrz5E49AaAnAEzQi6/9yO0BoJlWryvAkxRyDjJQiaupEqbVHpbquC9nb2KExRUDCCXCaj5HPQAUg9DIPajyudRE01nO7paBUefOMjOPdXDBcZRuLy3sotu1x7OJ3xvEDX7mrARscziJwVXkQHZcF5MPCQxR8AE1BFmGSUoSCH1LlcyCTsopgmOGODKvqW1bmXXSMxEPYtIgDR7jJAqhME6KIFHpvlk5EKt+YTav5+c0hVfCzpSxUWbxcfV38/d/Jq+JyuEy1TBvwkN89m0aA9vmjmtxdn7mAPBqSHqkxwOBTXw94KwRAOrWarumHMS+KJkVmYpP0NN3qkEKsCIQ19/dLclroUq4XLB81fUBpi1Ka8jx0LZrVUhNvHpK3seWNe9jyaZ0IogrUwbYu1de9Wx8hI/wvfi3Tv7SGbjRderilYPrLMUA2tu3xeAJUolsLz2IX4Nt9asHosQpN0bC67hW9R2diLO1/jj4DOgr7t+JwUuR/4umIpPHzDuz8MxaU3VgKyTDg2oLYzKMEnaazJCx6RlA/q2wfnq/1CFCVvQjMfFINCYAACAASURBVG5PkDqiqjE7OQ7yWpi1XAqJZVXNLARdNH8Yjp6W2n97fMvhrcid4t+UrOG1WXWe3KcnAPQEgHadMQF/uD0ANOOiaKlGTTY2Z9Iqjq6DgPOTJ6W5vFUpdP045vOMD2GFGlC9Jd5ctE0TT6JGT2mB9AM+NJTu3S0DY/YBznBxP/ZDsh0XpOqKa59PMfTKVAZQZwo6ut8UKFYTiwrUOYgNGJC0TiD6inxj2uao8XCpON1cuIjLkOLI4joXALTv07FIZEl63bqFpxlzYf/SiyJrQCwSM0KUKrGiZKTfO0cZQDKQ38dCsRkB5f+ioMuvKclGy7yaoG6IzCYwy+CbM7uYUHgd7rgWZyepL+hS+4XhUZic7CiRUd3/L1HqY1MBIBcVnSuexLRt8r34p2w79M841yBfWBGA6MzZFddKozT2Ixpe8EUkvLy9DdwZs0W1Fn4g0zwAIo+cQI6ar9lh0/j5UjRFUywT29B/V2V0dEmQk+nKofADOblbcQ18L1m6pWMSm+4ruxnVUAMv8A0kPSEKT5ESAQh1qE3nSgezKiCxCwBrjoDP17KEfmz4ahTsV19gc6lQQD1PQmcqpdiPrc/kGEWpnW6Y8pK4ORequiuHEtSnHuyqVcCJE7YrteIZcG/mDCD1Rr/ECHEgRws4Zt85B+gl9wdIi7R4JGwEC+Jf8VuKbnOhYtV5cp+eANATALryrjvaNskDQF3/jOWBhXg/zmsgs5MTilXeoY4OaA4Ag3Ee55FHbPoLWqAVZFlJbyro4GccwCsEXcGuqznFJncqNsHmzr8mSQlYMYA5CPFejay3A4W7yLLVitx90Pj8WIO4oTCASlvL2c2nhtrXGCq+VrZ9LEUyAE9KEoi+Il8Hm9UeszEPYLPaUzg4PQi7GRCMLBpxggGAIiVZORCre6gyUbpXNEvoavJ2xNiMs/O/2EAnBOTDaVwLyGdk26y+FgbRkyZJjTNeS4MG0gKQAbP+PPL6XcGZMNnfuWD4IHCZUeojBJb6jcJabccF+OaXkAIi+yN//NktGEDu/lpgXrzy/Bye+qXHV53vYc8eW2aP8IhpgX1RYotcgH721jaM2i3fE71RoaA6/hAfpcQTPIPENbIRgxmIEBxDUXzf46hlGEDz+KPb//3k/QHaRM+3O8cjXsXwesxRRMAXgXiOSCSLb1cS2ymWulVYWL3vD/f5Gp9HyrGDdnU7A2oaGEAyvxk0OWLXmsXNWQ5XtoPsezxX4gKpZjBihHyX2T+ZELBqEWTOAFIuqDMkVZr4PqUtqm42z4kLMUrtqHYa+QRTn4Egs+N58gDnzlk/bnoCQE8A6NJL72BjtweA5tIqtZEUUUL3143tQviSUdrAnaVH83kSQP43pBgsy1bKtkg/Tx18z8CjQRWbzI3wW9MQ1u4mgTCjR5YdA8BR1TfhtZ7S5POXfF+h1ZmhRtCmY+T4PbNLZOYpbTB1fTpIW4GfVZksKQNAPeO006sCysXIrEtyhME3ILkRBCkcnK5H9vHEwqL0+xipRCmYkx7ZqVYD99U9c5QBpG4f2e7EnPmD6bGE2ZfP9umMj6LkREQywtnAYkY526osDvfNDA3LWiyLmhvxTopoxHexQsB+rL0lszh0pRj56jQxGRLIz+CPGoBs71e/iR83ZxP/VvIrVgbieh+5B1mSPoO8yI8zQr+PtmdsArMVPRIjIW3pmnv/ile6NRH9QW//pCyFgk8PINrbBz7R/LHtmd1NlhUZIm7hdkBOZA29ZBkGUGFd1XnoVobD8YVBflLfc1FKS0C2AjiF0yjw8gOL5RM+Pz4nqwJAve+P9R2APpGSIc1S7/7ASnZMfQZvOXAFVyAXD8y4NsdSMRapDDLf5+zZbTqA5kvRnUD4nVWLIHMGcDGai3NjM1cd+JnyU166VLKWOZbuRDmUwy7xm28Hh2HX/uSWCp+re+EJABM6mrr0qvyf3tjtAaB5Zat7h6rUf1x3mIMUy6hJmQHkyvV3SDV7sk9VNkw/Vx18z8Dj/dZRiII0kRf1xl1yEGBzpwyMuQRc9OJqrEYDcdyx6YYhot+XL5WAddavo/tPjN0xSPmXBWiDtlggiCPMBCWlDqDef86mLoE8jw8jwjs5+n4a5tDZQ8cA/pu6FPI9khP5jMmRhnSK1eK96v7pGEAC1glZuI5syIabuIIcyAmNDRVXp9e+p2XX4Wq94TNRuoQcnLILRTu+ZZTVrJrEGfwxcxdboyj39u1yi8a+q7EsUvaz38p+g3YXvjZwiSzHczKltdqPUx7hXlRasR0leer7brA0EFdZG5ZGI5AM3ojBXryJsthriJjz2HwmU0p8jyoLPxLnMrXodHQ73tku2M2fH9hwLi+Co86BwSS1F/V2NUUBZH92GjFp0yKb3wPL4AS8XxxPVNNF2b/OMBVD70lZGtUGYxAGYYj4k0xl9b670K3EplYtHhT0gkzXcVE90eGpjKo53t94tYwINpmlW7MGqFMHiMvekH2aFQ2FV+aCgrJCiiXMfRPOcemSvGKrroMZa1WG535Zfq+GLeIY5mwwP1NOUGrcIfO90YJGqBu+UvyGcA2/4OxucVDyBICeANDV9928fZIHgDpLag3ewbtYE+c18OWnZyUxH0mFAWyFRViE98S5UXZhIqSXqd70iVcNAJH+KeAT+hwoXFjWKl40d2YAzSSQU0OWoPAQKcQaPWYcnnXqbWRPmb0jC1g1BoIMiJQ+l/qcg52SnaDwbGVsEx6dND4n+9SqATeuh6/ju7ZdyyOcNJSEEDN6LBHRkkw9Cx0DeD1PBXjvkhnDbZvCUbZCsiTFANJjmUQiX0QZTOS4rpffM+Bj8KieCaVJTjT6Cj4jpQTO4bGbUbh7NQNYb0UAyPtGxxdXmi7my4Blvlc7kcUh0UZlAEUJuXYYVvwmsYLX8lZE54LbLMUAqqxNrlT3cfGJvWcys0jsH2zU+muXYbWsaRO2MXgIsk8faOdRy89vI5OQqDqH3MiLc3a3ZB8kxpC2fsQYcgqyIvuk7A7VwWj9NhRfiz8dBXgUuf4ZrcX3dJ8YjQF250kh9JI4iL+9yuB2TKaXHisX1JROsaLvcOd6BnBeQBe0DZHyJ9+1OYTRG4sb91iRJpIh3NBVpd5qJWx/SdycY5NyAnHUL3UcsxXPgNlrOo7ojQRAOu9QUcAPNJW2z+CrAFAfgwN7d4L3bKnTuH/WQZRoX0Lca6srWJ4A0BMAujJeO9rW7QGgubTKSfEZUiQIwMwSFAHE7mj6eXLS6hpj8/2kUv1PkBZQetMHT6XFd+BGNqQPu4nQLDmxYvylJMEA6jIwpUsDp7+cj0KjpBp99OSp2PvGJ0b2lELXalWtY9Uc3VMGWhlwHxeRC8GQnn5q0LViwI3Pc9Sfy12vjMgQcw+PMubG0LbnRIZJga9VQKpPRBu9a6FGtGSEktQTGZDabbg5HkOdq8IyZcBd3IWcfNejDuphfXwu2eE2X/uOwDeRElhPbbI/Auob12JFME5CkyZbGa/z1BnO1bAZW1DN+J0dBvBKDHz9Xqw0SpdG5K59lmIAVQYwD87iLPKJczhdqjVmVVoogj7a8bFxTfZz990o2km6lawO7o4GF0z1X9jY/0o+SL8ZOj4wFZ4IMoYV919nu/N4utgzLez+jpYsatWK4xAOoaT4Uyec8W+KF29AbcEgfog0qIytOILidr9XpXGrAkBVhqdU1NcX2+HDmHnieIVwEmd9C+HVV4ELF2wsYH4X4ZUMvjGRuJyhBMa9d9Auo89sKHF/zZtLnB8XqcwcUgWCbGkKoStmrVWQFGJEFRNc3SxKgDFzr2z3zC+Gun/6GPzmmoHwHiHFS4+M2oAifWoZVpxWjpueANATAMZroI5lI7cHgOYSMM+FLiBFcVysqghgNsqm8bgaelm6QwrGfJ6DMBiD8Y04I4r5Kt0t/RTN+mscmIo0yS+wRwoAzO3dLQOjgk8y5ogDrHVpJmaiszjVfhnmYmtwO1GqYvZU99eM63bvxxt4AwcRCR+BX+v0ia/wEqUlEzEvTZvGtYfEf2+I/BaIwdF/pSzPIRRHSRwSuoTMWp06Zctk6GD0VV4NUT96lTiJrLiBJ4FZ3YKbU1dpxgDqQH5XXECY1WT2g8LdbJwA+/hOwJgIqU/RAr9gbWALSyVt6ApBZqUrbSFaozV+Fj/Jj38Nn2/+rWMAiUtdvjEFkoU/x71sRfDhG8csJeOoDGAFv33YHlZGnI+Cl+iLHJb30t6zBYmrUrTC05mLhCWdaoF4ZpA+KMSsyCD8nqK/Y841RrHzUnalUemrWPl3dkuyaGbsGasj70BavbDvKj9a/TwfIzV8EG28D/yOZfB/UcAucynL4Xsc4k+tCF55XJ088XuG1qh5T/aL+YPO49cDwcbzZj8juYhOMr/8bs+WZUafbGE6yXBBMnmyJBEdOCCvmizgwYNlMNiihS2wtyoA5DitMIjqPlMGi4E0TQGKQKMdw57UoY/B9c5PxuD73cUuSHT8K+h9wWZWY7BVKhaeANATALoyXjva9j8JAH9FE0Mgk2KtSnQ4PhdjpXipfjxzADgJ3YQ0AZvZboklOlZ3zQ4MDABzNiklRIcZNCWDBJC7WwaG56jwWwweVlSagLeWyGChc+pFmPm4lRAsZfaUAxXvobJPi+2eU3qkcYyUHqH2WLK8QWKVTmN5qwczZ+fByYCTRe5sITh3I1BsthWVUAVbhWwE760eAOpyFNuyt4b3YjkR7Vl0Hm80DbYcN6eftyo/M3PB+0uZoz9RVWxCrbPPoCnGOrhgYiyZhWOQTcgAG4kLZGxfGTgLyT6Vdlmn+s9F8JB2lpazGdwoJ5X4vIfcRhd1Z+AUAvl82HQMILFbNyKllzHJGa/5nnELBpBZSOWXS+LEqFTDRX9XfZ2+slH3H+IhpEXgTv/q2PH1JoFpVY2e38qT2ZGQ71y0M/xg6wWfxPoLhSwJAM3sU1V6JMuXpccYeL/0WNRCmmNNajwW978plr6kVccfktR2AKWMfajA2KoMoApg2V+XRNvG9zI5rqHPuFdARi+z9UoHkCdyxz8HMoZew7O0r2D+8GtCZ1TZGyoZIfYdEreUg4j5JhBzN2eONSQQNU6rY5BoFgYJXWBfV/7L6ntzMkKNwR3T/IKZj6SX9J5m49Bwe2+xaLa6guUJAD0BYHzHamfbuT0AdGSPRfV6NRnWwgZshHTPiK0x00PfVzbFvIrrN658rzMJOYH/EG7LbjgTrNYzgGoFuOpJFbx+b6s49JIfniFzUKBYuVImgEGjOzCM+uqTGlktLtqYjp0yr8DBnA3tAjaWiffvj/vujENv9IYkHpDNt8+/ktDby5HDvYQcdWYMqDt1AnhNWXATNyGZpJeKvYuNXVeBNnEcWNlUJkMPALfn6wCvH+aK79eNPo6ANwqL35CbY9XEp99FcwZQZ1L3wVh8hz5x33RtC/ZDxc4eW/wn9DksYQjbmk3B2JCulmbRqFP2y8tKR7GeL6EBuXAZd5ARmXHHblsdA0gNz5935kDKh9fwNG12tCp/1VIMoHLPoD/0ckg9Dke4OEqITJ8WgzKV/OAVEYHzqYsJUpFixPJ3etaWwV4HyP7D1qEDMBE9kOL7SeJvtTC0Ioumjz8Mzm7FSByiMxciHl8XrGbZdxfexl6UwZv4W5wfGayKKezIx5bbWPUe0JaNQuxsevYyW7K7uBkhcZlsXboA06fLf19JUQA5np1GWEAazBnz0M7fWgWAn3wCTJPOfg6b+t6KZ2AeF5l5vYFXxHFXogEaQRI72OhFzGykavoYnPfyFvx8W8IhCJOYGTTSkwF0/ggT9U3CNBUSdcj/Uz92ewDoSBpDZ7h1wyRMgbQNctRYAhgyRLLHlO0PyQg6Y86KJ2JegZOtqCzQyFhTWQP9WI5IIPfKv4v0O18QW+i1xpScm72AzRjAK+0HIWiBZAhGrf0N+9LXtmNQ169v08OL7d7pKvgsOy5BC+FBS29els2sGHSdHd/eFUGWGJWIsmIlx1YC5n4XZ/oUze9MFYcwZ0Dcce7mxQ779iT0EMePr+alfj969pSlNTJpr01ejqXRMrjph9GY4NvP0iyamYQQ1zvlg0iEwl8QXK5lKYHcDw7aSQmNHCkZknx/ydSMypMPgdfOIiJ1ekTfvmdZ9pITL7FgZJh+gPmYD4l9pW3XHN8uwl1CNbKAmS0q0/gVeN+8gbv+2ZEp9KqBJaPdZKEHu7D8VjnxExU06YG4ro/ZIcfvmHu1piVBlF6BeLdWGFb9/sJNwvstVPXbZeA99efyMWZhFmRWmH1iH97ENlQWfxMmURVbcBcZRZmY2ULKEZkby/McWxPT+AxIDKPSAZuufamYs0p3UC0MSM5ZdU1CTJjlTI5w+Pp6GaQus8MGg2J6X+sYQB5LZTKtwNY1aiTL00Z/wQnDbUhfDLBUzGvVS7l2Y3DAcfgUl05MN2q3Q+a1cz0YwMR0sFh+6wkAE3dj3R4AmgcHni5XqztRQZw5hTY/wYslYSzXwjhKZXsoB0NbISub2bLub8hSLtl+LOU6KsHoAaCa/MNbvI9ki6Xzg0j35ZVWd+6UgdEZaCyVCLsOxZbZuhVPSlayY6CVLCk9ZNk4eTK7qsgUum7ae/jJIL9QwPtQhR6CJUcNN3dJqfCc2GdYrtMlH0pjH/ZB4rsm41P085ssspqcFOgwYAZjc5Hw+sL+NJkSv6mA7TiXrYK4XpaMv/lGGslb2dQkTrwPs5a6VAf9W5WskPmYegaK3zHIJgaK94AsSE5yA0tvwDf76oif/l13EIZ4D7Y0i2YmIcR1XwjdUDaOFIFWzhnqd7z/fKfYOGHuCZEevM8RgIwBzy0j4+iBU1//yRgTKrFX7LuKxa/OST0XXZvxu+Gh+OJLOY0UKgS8eXc95t2pJ/4mDngIBhkYXgY57R+MxVj0E9+38l2KXyKbWhoAMjDyv3EBZ6OlcDY18lr7LjUCI56DIrVQ/+8UContyNQnIUURjdT1E/+nMoKZcQt3kPmlR8vKSmJccczwGZ6LKpeS7auLVHNRwAUk265kFfFWxA7x7wE9QjH/Fz9jjGeloX17GVjyetVCgtCIq1elHNXDhxIeQdmWxApBO4LGcMzYjkri/OhgpcYSYp+Jgdab3Rj8/Lax8AfT32vXumX895SAPSXguMbpuL53ewDIE6DsCAcJ1XSbNaXXFdeJ6r6P3N8maedpWdMHMR7rbHSwYL46Km+pg+olYLUCvNmoC7KskBIIG4YfgP/bJVGhAtyyAlTnYc4A3mjWHTlWTBZfR/21B/u8ythlABlgMCvD62RwwcHPUdMxVSPwOfzHjRADL0vA7rJT43ko3B//rQJSM77rKwwXkxZFfhmMqower4XK+wxo5+QYhNZnZCZ0fqsNyN6+lsioMVvABYXV5XjVhzhZ8f5MRHd0h3wOZhypfr8pIMtSNxnaZFmzvzC7oEvaXP15O3yrysmIYKLIEaMtfQ5mEkJcL1YdrMd6yEBplPfn+Cxa2mWppsD+7F+UhvkzpAzKYJ+waEsVEIWQUC+75xbX8Zx9rwsof4HhGI6vxKZkSv+Vrr4IDFQZnRhLJuV1Jm+Dyo+weiuHQdmImZ3+WMo//VJ2AlrtkRlcNmoErqw7C4UmyKxbB8zBXHQAM7XEAyem6dnj+ml3YPVD6VCyLl9PtH803ligUcHGRtaJwSkURAGctjs0y8Z5cVYEXjrchiXylWj00mmOGiUxxAltLNcq0W/uYw9sz9oHHFxkgM3F4+LFEtPLYHvqhbqoEvqb+I7OPqlzpRfBNhdo5gwgYTjlvHbj15jGds4s6pwTmwF0RFak/I66X59jhCEg7qhsro/BZUtHyYGLAxPryvv2CUyv1Tq2ngDQEwAm9J1Vv0uSAJAdX4Ha1YHpk0i2bCj8QDkFZ1ZGxFmwHHhUq15wsOKgZWVTA4AKNCmfQPeIUyiAQjjl8FA6CURhQAaHDkDbmzYVfK4gGXC5gwWmTsrMAv7iUkd0xGzxde1sR3Av++t2GEBOZAx+2LiCprgvAc3mpotBswTyZMJcke2w0sXB0Y1leVllj1QA2BjLsAySdtwfozAG/UWQpIJXfQIgZIAYnbGZRqLPHen6oOzs+G/K4DBgTOykYT53cwmYpeo2kOq+Zpas/ltm+bZIrVm7psMnelY4gPE7JIj/ZpOu6Bg+xSjdWXEdZghEXO+WbunYFvOwAG3tfsIENN/T8uXltT0rVQlpj0oF6Ygnoahax88ucxvX8Zx9rwsoj8IA9If9u6f/juVOar19sqMlWmKx+EonobEE3PT2NAy931V8p65LX3zquM6Ntb9DrQ29RNB+5UriPMp1vcuK13/BohhJIuiLMZjo29fIABKH+P33tqsagoEYiBcptRcfd8Z0QwWA/X4FGotvnAnamyRLXX4U5gX+P/7FUTD0CMK9/VCiYKjQtGSjiwzHTG7Pez3ucjPUff6r+C4nLsEnKKdYLDAAVBhAfkd5n8MoLti41GYsjsN4ilR255lYSAexwSozyR3z/Bre/x7f3pai4R0xE7PRUZDOWJkwM3nVGMxr5FgakykTkj+6i5CsQfC9fMEtGHBPAOgJAF1+WU0/SJIAkC+F0kRWWJCfYRuEX8cRw3UiPhfEyYWMKiubPnnrpu80uS8PW71ZnwzMMjCc8JKPGYZhGChO7f681VgWXt8gK1jNAtOvX2cB7whqg3x7ZeDxdoZ/sftefjsGGrNNs6ROqYGhcXQvM+KOUTJSOnbutlPjeZA0o0xUFPlHx412wgyBfaI9IDOZ5mykepY6Bo/C3tuytRL2UpSV0LOGVvUjM95VB8Nnwm1DE9B8PGcTsLoO9rO5/f/BH9dfEz9lMD40aK6lWEwzBCKue0Lrty6Qme63sAt78JbxE2Z6aDlIN0QVAD4pVxvp//5dbBNx+wGqNEorYByJJSHo2EX9nOjbesynhLFAYD9i5mn1asAZw58l9z0NvkW+HyQt+NCglagzo4FRlmQ5ssyD3wxJqOG+gzA25WBRikxsEK5noOYUGocO//QV57Cx3SJMut3KYMdWrixFl1Vj5oxZQBJG2Cjd9DZ2IQLJxd8MrC4hSPzbmRalko+K65k7+56qCBTpZ0aecIbtdwuJRfMjpEZaPDJ+xn7OjK3SIf3Zvx1ahkrmyNJvTqLbtELGveYi9fSLxCYhH7oV50eYje8hAzOlyJDYfqQyybq4NINvLjTZmmEpfkVTgUF0tFjmNgq3zCzmwZCCKIh/hQ1l1oDHAvJgtYSZJwD0BIAJfWfV75IkAOQLz8mMqzshaXEFICtSYWkI2J6BLvG+Fq4Oh0tTBMuaGoC5wkv5/JahuxWbW4k+6KsVYNeoSeh7RZaNWmOhUOtPygwgsWejLzZDM8iVdblXLyM8y6t2GUAORrxOttjEoHUni7u5SmJJ/wNut1PjOVWrZsuIsVT0zz/SjWU8eotzpgvCYrQUJWwGcmY8onqWI/PMxoBzHcVvVtSbg9S9OohsJ7XGdNygVZ1IlWy5P5IPdE9QMxZKPyYDXp6PuekWf2unXsLOq3Iipw/s50G/oGNH62z5HJXAYrsvdG+oAHnSDEIeIL2xOfFRLM2riZ4T4sKQRgaLMrf/dVwIlYzuxGZuKDitypeLfd9D88hFYr/MGp1HHoeXMBBDBLaP7R2swTq8Y2yni1s3Tvcn/kpW2Si/MihZ2HUXSvWQJJHx6Ik+XuMTvZhgvyHeTWW9VwT1QsOLE8QxlvfcjrlnKhgBoO5sok66IP5BH4zDPWTAGPTDPWTUrjsGd5BJSPDcQmZ0bnATHTt5oW5d2yaUU1KWagl5F1QAyN/ynTwdLR176KiS1eu2YbXHAJC+y8wA8r0ecOVTtH0qSVrE+N7JVdooAevncR4SjqPaKryLhlgljkXxZitY/ToGVlUd9PJ5FWzBVlQR2Nzechh6qTEAJD6Q89ymEJsfcNqAMDwOTY5ff7VWw9YTAHoCwIS8r/pvkiQA1DFdFO1kie/q6gNYfFaWtBzpbcV2Ycp+J7EXr/9enwCpXn8ShcXXzgR8U6WS4GRVClCT9dkvf0Ce4e3Fb/d1mIHn73dKcgzgw/LvIMMeKSIbdeM29l3I9BL+JD7Cv7zGhykkYxKvvCI8tRjYuBsD6EiSxJEwt14C1gMJ9Sz7ZluIMTekyu+nmIyp+FQE46rMlNisgbn/mTOAFI99Df+AYrKp8YIi6aDTOstoc1HBjATFvVvXuIOFmySA/375+mibdrWlBvOuBIAUG6YIcQo8xwUEITcuGFelytm6JzPv95wQm6zSa/7ncSos2BIikZ4BXI36qI+14lzMGVeFy+R3LJFOh/TWZWZ5HtoZ5z/HtxM6RMr0ON02zA4aOiziXNWP8GH47EQtJhi8MvjQcbiUb2kOyTJgifqKb25DIJkLaPYHV9rvqImakKBp6hwqaRO1D2cQhPgegxhWYvvYGJRdis6BHLgm/K+DvK8YloYUb/74Y1sJuPv1z9DlscTyUDPzUlBl491Ux34Vl3EZuexO5SayIBtu2AlbJ3YhoWNgVZVnJmxQmmI4jKMoJmSwCDswN3MJ+FHld5Fxl6RXR1y+gSZds1ouA+YJAD0BYHzfUWfbJUkA6IjVyewSV6a0GiPeLhPu2OEAlXuGOnFdB5ABJYVrrWx6Caw8dmAHJAibWnh9Me6lQ7H8qNsGqXLd8x9/RUCbZmL7Q61G41HHfiIAdIcXpDqpl1jAOijnyRM8iUnp0IfSWRDIjJRiWZ9PVQzBT44iyjc5ZowPxYbfvdyOAWSWjo4letM1CaXmWTlw4mE22VxKVPdD14Xb1XAUlufp79A+zqp+ZMYAXkc2ZMNNXMarQi/PUWMGlu4DjliYfG8Yd5PQ0qT2M/y6gRRv4GGpamiTdbOlAaArJeDCOI7jkDIXZKmqYIV/K1iETmA5fx64UKU9Cu/7QfwmZP8JBNd7zRIikY4Bu5qbJwAAIABJREFUpEA4PWXZ/BCKSG+/lzyu+V1L31/xc6R8R38sOhofHLPhSdambIF6T5eI73YtvIDek4LEe07oA4PIgFsXDOH6NYEt0D/nL3ZC5K70JQXbMP9GzxzPnBCCNZv8jQxgrlyuZ+vGog/64DtxmOrYhD+gmYED+OwzexKHK9fAbYnH5j7YdA3Ds8iD/F5njQwgpYGYbVSZ4ZEphmLAM0nF//3TNWi79J2XfJmdCVuztH0FOY1TTWwJ3pEVom5YwED0Kl4V5JQ+DuQ87UggZbmy0IQRT5zA7keveUggrnaseGzvkYGJx02KZZMkCQB5fLOuGz9bhFZoBak+2y7jGsy7ayvF0PcxXz45OTKDwDKgYv66QwhaB8Hr7C8yC7+FZhXw4may/DZzpu3OqgHg53Yb0fIHKWxNgPYgDBFZJyvLdebnaWYBPy1WDmlO7BKbRYVGYN9BX6eDD8vBxCaSFML7zZIatbA4SFN/rsGkqqgS86fYVwo8RbhvCkv158zX4mixwG3moIMhyssszAkUEWo3DP7M5VyVzXo/w2/48Z6sdSlJD07kZABfu5Z4/Jn53A3buoJy/7ef+MMfYTiC11EcRxy+hrHhQvUS8KwZ0Th/yUfsYxfewvvBu0Q2hXCIxE5+3KcrJJDumIiJ6CnOZXGpMZjg2xd76DSmCQvr2VAu5saEdEVXSEXfcn77sStMetsm9txVBpALxN1hJVACh4XFpB/CRTaKz1uxgNUDoKg5y3lso9EPA14QR/j3Ru/aqBEtsYq71z9Au15p8e+/8pfsN6P738UHfaS/86bk9VAzXGYcXc1A8Zw4rhG+YG66wPaiCXfEuKccMt5662VCncOOpX1ItvIcfCw+UZlw/TeJHU91Jjb3S+wfM94nUQiF8YIBAtlXCb9QJeCWN8bj64eynkqd0b25WrxUAh7q+w2+ipSKywwo8+Kc+HcNbBSuL8SbPn2aeBkYYvtWSIc/o21BFeE4xKacbpwFyy8twhklMrXLtn07nhSv4HARHtezi+17TwbQkwFMTP/hb5MsAOTBGAQSP6HwJvWwFmtRX1zDnfINkXmn6Q10cnW0y2KgYmVTJQCuYNvFfG+AjEk4WJiikwhE9TKNWUBVlevy3NmN3ZBm8+Gf9MDBNhMEXpHMWas8K83XbWYBL7tkE1jNlytC4C5dsW7Ty3c7sjRFuZuSIrxg2GUs3fOqpfpz5mtxJBzObZhpUlpzajXOSZ8TqZnQoQKxithmCONuKDYAGyqPFIEuLafYrC4B62XUSm+GYOs+e+s6/VpZvua7oOQaHfVlfVJhEIXAAPiEh+JGlmI4ufAw3nhD6qS5Gnw4OpYrGUBd6JfB+L++RV4KqnVPZgY6Q0L6Gpn0an478Wd4uURj53gdOnaLAQKxZ3eRQZAinOFba7xyAhuvFxG34Qd8iPaQmUm23SiLstgr/k2x65SpfQTrk5lYBpO3LociFHwYwB6/SmgXvDVBGUAdu8hxgVlvYsT8k0fjUbg/kiMC1CtkQKsvWkjg0hee8RkDdd3VqfjEjlBhxXtgZtBS2YEBuPLsVudI6A5JLIoF3OjOLIy4Z5PU2RLU4aUSsJ4kYBVAZTK7YgqmQbK12RKzkHCUnOA+uXCjdiWvJwAhouTszITAvAi/1GkEcn//pTi3qGUrsC9bQ08GMD6d1cVtPBlAF2+YafMkDQDFyxAly3vUPHslUwQqtskJL4pzUaw3xUHsfFYiXlf0Ql4pXtvGZyM9A0JV/dEYIH7GEoSSH+HfCh9iZm6qcl3G2zb1+PA27XGgy/cYMcK9ASDPS2cB/+P9GtLd+AfhfimRM+0Tl30o9fLdtXod4TNXSsr8PfswXm9TzDIXB0fPRQ8c9OyIHnSkwUM8RhpDoNc8AahgRhePJvOzBybZ/cbM4o5PP4ltGz2IyobruI7sYvM1Pg3RLu0KEYSzcRKZOzdu8V19Url+HajSLAPSRd/HaeQT2m+KsZiYyU9djx686mLg+vUSttEEywyv2YsIwqSe57FwkZdBlHBkyccM1pF3B6LMJilXEr5uE6p9Wz1R2Dl1Xjp2iyQHWtKRNMBAUGfs69dBfOBtSIeedaiHd17gBvn3lZQFkePpvwj1S42qJR8Z8lUsXXJ/Fy/GIBzJkQyROJa8JJrnPpCgAFAx3RkcU7yd5C023X6MBLQP068RAaASaicG7YMPXOupJOkoYsgfqIrq0ERZE5C9NB9dYbxTpABSBMbg1h3pW0w9wJa59ohrox4jM418B1QJWNdc3NViIhpv7f5SCZhBJLPndAupjQ1G+Vq9z6oknlAtRo7bXCArcW392ohhJJbxGl4R/2UjPpl93NzMdpw1L840pHgGZJiDLcEdXFqEx+cJezKAngxgfPpJbNskeQD40slokdfFNMVQ6NFuscLmgHvZMWzK2IWVQaDyE+XOdSagYn+ZJxMyAlVpiL9Rk/XUAZfxySgJWl6CZsKLk5ZlVpbr4hp8/riYWwDzycIrG3xbYJcSkgHkcUb7fo5+kSPFIXkv9gZUsczFwVHHdJYBVI4GFBL2RaRwZqE1YNu2L8vAqC6lA/bpm0ptRB1bqus4JvZF4u8V7IfZvYJRNpycspGiLAony/geV59UKF1zy+9VYV0W/Up27Fl6VUhS0B2HrFuyDxPTdB06Ls6io+33Rkb7CHxhh2WkTMY49BX9m9lY6reprKpeDmf2vPVFm0jzR5lX46/09RMUOJmvUcduhUCW3FXmzNn9IIklAsngjRiYhegfBWRF6pBbAqwWee6SeHeUIw1LwEOHAh36pYP3o4c465Mf+aJkfdjVLCzv2UUbsdWQM6mcYh/+fCYdb5RLkhm2wFLlVEmejXfjWMCsKHGp2XFdYE55DhzDEpsJt1s8IBzh8BPn9ZdvRXR/fRsOHpSnyeOwqRJwuburMPtOQ/EZoTZzs3whSrpqXOVzortJAEKFHmtlbDX8wJWkTefOwIwZkiyVEC1GR+QnypaRpTxvaSACYkJwDEVEJpCNuGMuUh01fRH+U8NfUX2mxJkOTTkKXz/tbyfFFe8HF8uGngDQEwAmth/99wEgZwd6kxHkR1wNqqMBViEEL3RK4rhCWqwJ+7NENN1PlLvRTdbNGoUqEDRjAI1y3ZWHSPlqOnE2Z3LXwoLWG0TZw8pynflSzeWHyMzZ4Hf/JkIzv4pk1y+77EKiZ+E+8xmDEZFSC4vZ0PUBTUU53B06ejwGs48M0hiAsITHbBQ/O4O8Av9zH+kEcYhNWdqZZWBUVqhYynM4/FRa8f2E94QoMzMGXO1zUnfG6EtIV9ItD9lH3o62EYnGe/dG7+hxYtLltbiSeWRw17y5xJ9dSF4AAVdOIzJVOjSufF8IQZcq5Vpw7+zadAILMyIUTFbYOV2EW/2egVMlbEMY/MVijbJCegCo74/nvrLidyi7VKLnO6ZZjNmPmot/uxo4mc9f4c+SI0ycCxslakgGYXaNfdVRUwGRyhaqbcK8/ZE8Ogx3XymKdiWPGoQnXiMbF6V02siJK7jlkw2V811PUCCri+NTkoUahOwXOnFJ4Y9LlLBZN6pgjYESn1F8m27PpjLoiliX2ACwVy+JIWXLkPwJ7oZLZxVm7ZWfunrWLHczAKQ+5NDKf6DyMElIGY4vQHcfneyXA1cMosdKNEBjLEcIAkR5WXkbc7El1AoSqMVoxi+q++mPEGMOIrlIYQGduVCZYTjBl/7En6gqdjc99QDMzT/SpUV4fJ6rJwD0BIDx6SexbfPfB4A8uxMnEFm6LHxDnopzpWxBfawxxExjuwBaI+kG3gm5IeZVIL1NG0PiEbPjqlHK0/dNVq/AZb1oRhC2IxJlKyQTn+oi0laW68zX+BIAmcAwjogv0pSu+hDr2Zt373yPUfdsavibgjq6TUaF16VnADkpdu0qsy4M/NLhoQgE6SDDxklwyhQpK6QHEioDqJdhzxdrhGnVl9uxgOObiYtPnzL3IVqRrUYD8dOvMNSwKOPfrpRs1f2gjdn6m5LkEIbkKBQcJhiJ7FdWWEzpz5xd5wUqQ+DgziCfocPGEuI8fIilaGYEXErcXU3yLJOp/TGTwnelziWb9Er31POwMVtbS7JPagLPgLuG0PZa1BNyMLEFgMdRWBAUniIFUkGOO2QOK3wfg8hqvttRv74kBxADyACeWTtD3scrFd4s8DhBAWCXLjJzZW46waYNFhhe3Go7ffHA66OPb3zaLHyMjzFHbLpvyj70+aW0oT2Z0PIp98XAh9qEzEQT67x0+l0cuipJMnwOzQPWiqBOBWjMLqsSMO0RlYD4lUbd0frORDs9zLfxF/5CebEv2ir2xERBBGF5/wHSIj0eiO8U1jMhiwmdRa7uIxedmSOuCtYvmy5T5my+MS/CD/5wBKU/Li5+H93hI+ztMNuS91R/1p4A0BMAxufdj22b/40AkKvFb3aj7OBahl4aNZg6Q6PZOrkKMmwv2GTIEnQ/zKtAXU4iAM+NSUHt3NEgoK8At+0PRCBC8Dx3EUQfOSZs7Kws15kv0jz4eAX4wzsiDE9zv46A00dczgDqwcywN1bgywPSSmp3g28xPPIzg5GY2MyBo4elZ45UNoCloCj4is0vZX0TQTclSJ+N+EozE1ZlALP6P8SNUJmN/Q21URe/CRwX90v2s5UZQHMf+gDzMR8fimPrgHUGrcREma2knHVcdT84gdIiRWd3+/j5WmYyr565noHhOelELS7MiMNyNOyqBY65BMxMD+EVf308DxMfS709Eqvm+3USwUti+5AigQTjvCH8TOLAe1hkZFwd3Vud4Ul2+3OkQBbcNEqMF4u8g25Ba4wMIPehSsBtp72J5If/Fr7GyuvW1eDDmffyGNjIMgp+wmOryoO+aCEjWLGv4xr4BmCk4WVLO7v9wc1BWzkSMxJaPuUx1djDfbDK0a/1NVRsnUOczu3yjXFq+DJUqmQ7BvHf1B3kGjX4+QkcCJNkHMIkvsw6F1R/+OEFJ4eC7xTSZ6NxwHfoA31sToknCPFOKda5evY5rnuhf6/rSOqfU/fvMCQencFzJ0htSGdC0C8twq9eBV6VASQaNcKT+cs9LGBXHkw8t/WQQOJ5o5xs9j8TAHICGlR9JzahhsB8sOkDoLPLNGPxEnI7dO9ZriaPxhRBEZzAcwQIsVu9vfuubsZufzRVrrvlnRWZo28hOmcu7P3lojBKt7JcZ75Gu/LD7RhcvGwPwnaVBayTGaol347N4ZXEISmZMch/tFFWc6WUGd/n4ggDqGd3fvOqg7oxksbL0hjxQpyYye5VQZXKAOplQZbAKmObHTHAygygcrtR16l75SpHGH7HgMiscRjbvdGD+zJf1YDXHxJItWPdY7xdK5XLwb2zY+llPJ4jM45kpepiuO9iFdbg3VgfpQrozJqIgwr8gsH/Sn/bicET0POCdMtJTPaJv1fYXX3CnoFO6OY7Q4iWO2osGa5L1QIVrku9PwaPFxGM12AjcBFcGjlnniAIMPguUEAuGlgC3oxqqAZp3lwy/1McOp3C5UDWmfA2XV6IG2bLizM4BwlhUE1/58w4wtgeTDMswRK0EJtsrDoS3p8PEK4cxJYyK+dKVlo/jnrOlIzi/vRAfLl/KwwrtAiHDtmes54xnNjvKrqPkUESqy5k+esEJJ2Mx/P/Fc3wI97H+1gofkMHlNvpChoEjoQsJnQWubouzgFVYv4wCCcj8Dm+xAgxdrAPONLsfEkHULdbqlgRu0du82QAYx05EvalJwBM2H1Tv/qfCgCJr+iTYgbGPpO2cDtQHhWxQ7x4fCl1GRZ1AVZIwpgnbyXgSxYYsT6qccWtPGod3XY1CJzzyYfcUWcNvBon00mTpIOGFeU6R8dWAORcmUNw8bbET17PXwklH211mQWsM6J10V9q8akyEvdvZQClronPmN6kIuP1ouXHv/gXBcVfnAA+wI/i38oH9JtvgK+lnqzc5kfFlIxBFHwE2H8fSqMM9tmVBa3MACo8Io/PkuhXkYOEBiRbHazHBtQR/2bQqkDxjp6j+TM9uP/2xLuoHiLdBTLjFlIEZRb3yhWCj6Nj6pPysGGyrC5LwDG4jJx4FVdBgkUG3IsTm6syYepdYKaHOLyaISuxEo3E4Yen/BbR/T8Tzywx2Scdu1sB27EdcqHCLFp/xK4TxZJid0wW27MUuQ9loO/jcNXeGBg4zg4DKFnAAPFoDbBa/Pat4JvYcyGLZQGgLgJNHJrCNarnpgdqumd2XH2pFP7G33hTbKZXV1Tg5moGUx1PX7ARjxpw6RS23ykkvtYldvTzVosNZvCeCCUy4FK+aqjlvdmOWKd7AJfFbuxFWej2bBS1vlqguvGbhCxInWVimSWl3SRbb4wTNpSxaXaanUCoT1q+ViB8w0MQU7gIGuQ+5nECiauTJuB7TwCYgJum/eR/JgA0iAeIxjEUNQRE38ReY+BydKnObLRcuS32AWAMwuBnp8Ol9uVMAkB9r67hbtAbyHDxoJAuSI5wUTJjqZqTqxmv5sp5OttWDxLCbz3AkSvSl5Vlz67Bv7nMAtYHRR1HtwINDWwk929lAKWujdfCjB6DGmX19mXV3Ri2RWorKiwQ/61sscyTl76qpw1bSjwzmHw6Czg2X09XnwuDe4o/szFQGB9tCzDewm7sAe0BJF6K1SFXmgruV/q1QIMwmR1a9O0l9J6Q0+Xg3tFxzcEakxdsekmUWa8aeEHjjOXkVRbGHFQeH/c7fn5QW/xyMAZhdMBgO2wYiVKuNj2LxiB7PeqJXXyNbzAU2opA2zGlSvh8uj8ZhmEYKL4hXpN6pA2xAisg4Q4kYIzx/UIQFsg2Z1MkHj0LpbJ0rgZQznQXFcGEJJUsuG13S3jeJOaoTLeuJag2ZMBN3CUXGToBRpeCIdGubbZNoi8yA2gmUbnyHHTJKPZrr6NH4POGxL5dfacT3tg3A/fv2ws1G3CD5DF4Fu4LH0Tjb5TCm/jb7tB6oK0s7AinmIJuYjva+P3k286wyUvIgtSZAPonmCqsI9naYh6uVGmLLTLp67QpPUE1xtABiIunG8iGV3Ady5Z5vIBd6Vvx2dYTAMbnLjnf5n8mANQHc125fgJ6oBdeUMwcXAfxXwQfJ6bp3rP6qtSsmRWbBACPrybSP1FZlBvZnt4JwfGz/oYWYGIGW2fXaIcBzH4dPjml/hzFtdNvXeFymVAPoKiA/wySZm2+H1YGUOraHJWAdRzaIK9vMCTGfnI3l690PJ5ie55DbsEi1gNAK/qOOm8G+ErgnBP1vOg2gnXMVsjrFE7FFBD/JgtZl/+Iq9/qwf2Afz5E02fzxU8K4BTCgwpYkgE0l2spg8GS+luhW7AF1cTxxqMnemN8XKdrlwnTy8qfFt2GycdklPdTjgFoc3VkosD73E+TJlJcnk23DBvgMxajoxz4dWln/zFmYRZsIsRz0QHtYROA39pyBsY97WRkAPXSJOVZFD5Z+QUzs6/sE+O8SU6cV4h15eLTF1E4iBJ4Ay/0U17skAGoTvpg8EXMZvxaDMID0yLZ88e4ly4PDi89K+AI7I9cbFGnz1FpM65966Lx9eoBHxTch2ZjpYzNmqBuaHBp0ksBpi45dOyaJHcpbUv9eIdQAsVxWCyk/RGKaPhAd2malm0o1pX4yhB2T0gGUA/EddIQFxHfQDqQcPxp/VM9od8ZW2NfpBwT98NFFOWIiuGoIG0R1vTrMi+BBbeqeUggHhJIYvvS/0wAqMREOaD5hz3ELWQRdH+KcL6KK0L3zVEjiJks0cQ03To3Fy4KPBCb0vFT+65WzaZl5eh4ajW8zru+YRG1fPotpC+YGSwfJ3awdXaNdgDk2+eBPHnkpi9Slq6ygGmxZnOoiBGaaZyU9uMNlMZ+4zRY2iZ+yMpmDka4b51Q0d17CiZHSweANGnkxGWevPQA8JZ/TmQOvYKHgdkw6KPrOHvW5gRiZQBIiysGoqpRxPcdrBN/Zve9heuRmcW/CYCPK5Og3089uH/zh87wniWJUftnH0KJdsVdDu4dPSudAcxg4M4duRVtwyaju/j3R5htuOPE9rz1TJhOLHk9bJ8os7LNCeyOVHMnilKz2cYvvn2JgTHln1SWi1maeZAkk86Ybojw8m+zrzg/0wOJzzFCECR0zNmJwUuR97OmAgupwxF4zLkZ+qHZpbHiWCwb70QF8W+zMkBs1+IoA0jFAcU8XYV30RCr7HZBJrLKMqsvWrQAlsiksMOmB66HvYqjWIwUVWZA5Rfgk2hNTx0DSG3CspGaj7pXX1zpPkZgA/V+ob/jFxCEIFzCTWQRvtl6o6MLJZ+4DXVN2VgKVk5LFIP+LGCScQ0JwQDqiQfK8eTNK/tU673dUemIDSIwYnMZcPx31hyVgAt1rYosJ+Wg0LzOE+w/ldIOqxzfvu5sO08A6AkAE9uH/mcCQLOd0GrUF1IObCVxAIdQ0uG1JtbHkjslwPv0abl7HusASol/KyFWdeC4VvlqsqbmHFmIbHlwVrAT9UkooYBrZw/bLgMYeAI+xSSz7kbtdsi8dq7LQYIeEHM/95BeSC44WqVbocOoX5eeAVSTV0+MFxgctlZYhF8gyQSqme+nEgdmiXj7nYIoiH8N2Qji81gmY5DjzNg9IS9VhQoymFFNx3IlQzgiIaWB4soim49tF9wP1ATXdu8Gypa1hAWsT4K0OKTfKZ1H7jbvgi6QWiWU5FATb2z3R5+E9cAy252j2HKvmPgpMWgjg2YmSk7InCnWS3btfBZgXlQb4zSZkSF5Sw+U3sIu7EI5sY2qMpgF4HXRc25HHDLf477PbdkhHd9p1gaN7T45IoHowc0UdEU3TLHbhaP9O1owOTvuCq/GaBgj5a240L0bmEsET4nR9NSfA/vOx8Gb8e7kGuIYi/N+iZZnpfuL/o7q167s1ogxpXKCanrlQRG4+J1OMlmM5mgXsNiSAJDlcOJeFc58IVqjNaTiM8fwWZvzxBoAvkQC4Q+bNZNMKgAHll1EqSa5Eky2cfRMPQGgJwCMbYyJz3f/MwGgWUZDx3r0wneYgF4Orychqz59R3zhGRSoRpPxjagl/hyGLzEQcgBjiysDqAbjGeiMTi8kbErgoJAT4MThLgFlvUyY5eoBrL0pA1j6fo7JNdVlL2CWhvRyFsVyg3ERtNrKilt2z8EKHUbz86D7AkVuiddidm8ovhIisWw18Ts2oabdOZjxV3p25ahvCRSNPIwo3+QY0CPMTgcwISUjR51QF4FW3yutOF1njt+5mnW0ywCu+Bzeo6Ury+HvtqBo9youB/eOzl+/XyzjUYqD/TVfh4qogB3iJ2nxAI+QNs4xRX8f9eDkrQynseueLIOfKdsGFS4sMGy/XMXPcR/mDNrYTKPQ585nYv8UrlZYPv7NqgKlRZT+HD/jpH4W+cT2SjbGLAB/LvB1kdUzN5IC6IDC1hxLhCYiGwktDJzj0xwFgO/hJ0P3T8me6PtylGF05pzD35kt/S426YNcy74z+k/hT6sI/FxCs7DckRkD6LtxPcBORI3AwUOQffrAl0rM+rVTb7EC5MqJrP0IJBf/JsThFCSZ5N9S76HgfgmnoGTPU6QS/z6TvTJ6FvszUSVgvY9SpJq6gLlzA9VG10SBS5vEcdj3py9KKwoqzprZt5tM/+zDOiPfHzJj/2zHQaSsUCLRwuf68T0BoCcAjM9YE9s2/zMBoBnQrLNPHZVD1EUlZPLQbwhFpBtJcqJoLfCLkWEyB55xZW/UwDYnfX90uC9ZiBWxDTtQUZBAmIlIqF5VXA9aEQXqp9uJ1Q9kSepojd6oeXScy0QBXRaH+zmCYngdRwUTVF+l8zsrdBj1a3MUTM326oiPYqQfsZ4NpgQQM7fmRYA+wezyehtvxewWv6WocXJ/H6NsmNjFgzpvR5OwMya5q8fUg/tWZ4eg98NB4rB1sQ7/BNVNNAaQGaAaNWTAT9kyBjAyCxKDu8goSnC6F2pc/VAPqnUx6NSPrmDPdWmnQWhF/1xLRJCZ0PdBt4DjPof7fI0voiQWpBY2GIs4/k3oxbx5svxO2AAXFzrWVxFcKPjbCCvFPliOve+fXWSLzTAHHT9I3OAPaC9+w4CL9zM+Go+OMnc67oyElFWQNmlsztjjunMOA5g+fSD8iyl1w4CXJWJlZRc6ZjL8+smS/j8D5iHv0LbinvDZu9ovzX2f2VHGfV2yrUDd2RLo9kPBUejwb/+XMID6tetQiapFbmPbyUzCBUhfiCsZFoXR46KK8lwnUQjFfE8migRitixU+FzCXYjBjIQPkiECmzd7xSsDSMmvmTMlzpcJBMrHsP3cfhNaz63uyQDGNYC4+L2HBOLiDTNt/j8TALLsNGqU7exoPH8bmZFRGJmnR0bQLf3lx53QgUsdKXVqiDKaanopidizH2FzXo8re6MGEzo/KBbiph5rcSZ/PbFKXSchYQkebJ09aj1IKHBlM366JUswHIDmBg9zmQW8aRNA31rV9FV6oE8YQqLkKp0tXz5b+TxxXVH+Wg+mFOtShwME+13HxbBsYlvlF+0sAGRZZ/616qiGP8T2zB6E+6YQLGNiqRLbd9T1qmyU7oihfGlZ4qKZPRv7GhmR8QkQ9HupgvtvUo4RnqJsmzovQ5sVjV0O7vX9NmzoWNOSGZBGb9/C2J+yis3Nll6xPWedialProHP7uDAFYmD5KTfPWhNohZE5orBWPRBH8jsVnnsMBwk+Pft29JqTTlWyPOPwXMECnC+shXT7dIcCcDzV3zGzSIXYREkI4DOHQonyb/jC+9wlAGcjw8MiaOiOIrjKGrcamcM19gygObn1NR3JZZGytUux6jvAr4yyqcJXUibMYBNIm0L6D7e4xHVredLGED92nW4jK57qBNyJhWchh6npDQYhdQPPJRe50/9M6BF1buJygCqc2HVg+Me3VnOnQOGL8yF1A8u416yLMgYcTPOsYJjMDPAhJawFM7+WWLLOPgp2lOzAAAgAElEQVR9KTPFTCxszdxCLLBcff+dvW+eDKAnAxjbWByf7/5nAkAGHHwB9UbD7zrCeQDIiUuGL6S+TWImcXP5l/sdiCEYApllIftLSUvw77iOpQIB3c5JYdZ0DKBVpUd1H+wwgDfXwKeRFOu90H4ocs76yuUyIe8Lgy+uxNn0VXpG3ME9ZDQeAX1qFy+OT1eL3zZqQmE2g4QEngs1/Eg+iYK3kNUhG1Bv5slLzzD8ntxGyBnU5TZmLs+UqNKjo6swS0mk9AnBkyipxaj7iLZrB8ydG7/7oLbSg/u65ybjmwcyg8Ny4a6g9xKcAXQW/KnjVobNyzQuJr5+RXrf1p9DUManuHBXlu5O56yOCqGbRGDGlpDgw4wZdsTM5b515qzOSuZ3F5ELuXDZICAoezhHAvD6Nb6DNYYg9pcYhhH40vg6vtfiKADUcaPKnUTt2JnkkisYwLK++7E7srTYJcWy+wTOMDCA8Q1czb3XjAHsmW4+qv0oHXCmFZmGrsdl4OYMA0iYyieYLrbRs/uUClI6muZxeDfKoiykG1Bq/3A8CZX42rjGZ0dvnu57rti73E5lGdkniuJ4nH2U7ylJOuzTDACZLCh+ZB4CukhiEhMLyzJ/4gkAHT2ERHzmyQAm4ubx/QErIo8eITXTE/9hUxMSS4oqDa+n0M0lEXWq8R1wHV2ao9XzJK8e6BYzSWxOoLjyquTfdBaIbfWmAgHqU1FWgq0jZmI2OiIwULIE2RKiVxXbo7HDn6xbCp+WzcXmZ7uMRfDkPuK4fLyu3KuKFW2OFWZANEktqlEagZO+VW3IEGCQjL+NRkHuHLhmxxRU1ljcyDx56aXH0Zda4J3nkibJRUR4lpwii0AHkYRMGI6uU+km8h4z4Eh297rhH61rJyZEN9EOA3h0Drw7fSxO4VTfOcg3soPLwT1/q5sUOHtuOgaXJc85kMeNqzma6Jl5u3MjEmHRcqKmwHtV3x2JysQq1QBVFlwAm+xOPpw28H06ScwcdJkXFlQeYMVBZ506ul49OKYw8Rf41tgsvn3KUeB2A1kFxpb/fQX29HpnY4Z+TSSpMfDgOETmMoWZqQe4b588vQ3zb6FWW5nVPf9aPWT9e63AuyVGBuYlDODcWUAnKa8TNet7ZB/Y/qX96/hNlnc/h8S16s5P36M92kN6wpmzobo+YG6/a7gQ9orYLr73/v+xdxVQVlVt+5lgmAHp7kFCJKQbpIaWEBAFaZTuEEVBQBARQelQKQVBQkAJASnp7u7uhhkm//XsPfvefQ83zrkz/gs/Z6/1fTL3nntin3P2fvf7PqHfU30OUIt0CnCHQi7gFAHFU4Cs9qOXgPWFwqbqw1F57aemM8Se3jN+n5ABTMgAmnlO3G3z0gSAzix5GmORsP9hG4rBGIKhL1yLNy+92okzKQZd5JUOFKeRV2xOLM38+e67WwUC7ZMvxA+PZBD2W7nRuPhOP5DBR+smrhC9CQTcHVkffG6PmYMxd1qLzTmJrwzuKo5t9Mv19ODoHpl6dkWRWtTvWbrnoBcfjSxN9rPeCAWgNloiRGI/iqAY9jvYuTmzZ9LLOnP82iDnJqmdR+soOooov9u4PDv6OeoZQJaXx3c8iqbDJBN7bkBbtAiXaT9vAn8HFvCyuVJJnG3CBKBbN69YwDVrAgyg2PSytX5NemamPLbYGLPu7jMXOcSbqUWSUWJj+epE8IuOxKX0xdG5xB5b6c6b+6Dvm9niVUkaodgFyXDNgqu4hheDAhU0qmvQA4lgnLfJP21DWZTHNpeXWhx7sAcyk2Zk65q9FuNCRyc3MBOoiBHqJFxVDfR+MDJZjRcQGBCNh+GBQuSe0ISyQQfjLAOj6wAy8zUu9wTk/FZmqccU/Rn9D7z/AgZQH+s/xkiMxECxvb7Ip1h1SCx0o3Lh+9h00E5AojevciQqk3g/dj6XwtPeVFb0AJY6nsRPPjhyBQ27S4u6PxI3wttRiz3qJDojgURs3IrqQyuI/YR37Y3Ek8ZaWoS7e9f4XUIAmBAAenpGPH3/0gSAOphZnbRO+WcZsj6kDRabygCZHXCddYQzFXi97EwP2ntII35KAVZPQqlqf2Sq/gnpeqACV70E7E0g4O5G6uWHCYWmo9thuQI/O/BH9DrUTojZcpK0gj/RQfa6PAazH5t9KotBnS2+pFRo6cdjGhtLzrchsWO8N3UhfYAJOlfnYFyd69mVybBLmeycsg/95ha1ybXE1YdWnaueASRpIOvFLTZtuB+S90FfjBGBkTeBv0N5//Ji+DVtIu9tx68RPKm/5Qygsbzv6rli6boSNouvzTKAjROwvsDi838zNBmS4QlYVisVdMQWfHgzcRv3vTS0BmpAYkgyBT3AjdAU4t/6vrkI0hcr1JFTUiu0/lJeucqX1lXfUNj7WIxkqM5Ca7TFLNumZrLsvAeU6uT7GBEhf8os1yFImRxiAdtALlpUczXOGTOJJKJQc5T9vXu3xJyqxvHrRLhk9BNXnT3J3TjLwKjjs5+pydrogp0h3TX9QpQb2+QF9yNdZ7QzJmMypK4ntRznQC5eTyIv8uI0HiEZUuChA/5bVwWoH7Aav4dL1QZvxlWjkHWtWkCW2wfQcGhRsc/p6CAUHcxmABlAliwpqydP9xxH3f75xX5u1WmNDCtnedyPq2fO2ecJAWBCAGjleXG27UsTAPLkFNjdfqIxeITkYtI4g1zIgzMvXIOZAddVJ6mJWw/OdqKUsCSKho9gfxFvRlkMkjg8NTUp6RpjY9FbgNN1lXlvJjx3x9YByNPyj0OHY73E5qeGzEPfPc28CgD1CfZTnxEYHvOZ2Gd9LMMfPvVtwVd8XAuZi8wKOGv6xDgDbdEeL4LojM+Abm32+eO+6Bkpd04tuxs5y6F9ezlZxcWHVj9XfSHB+xwSZseIDfH/AkMjZd95M0HpGMCCl1Zi5i0psUGs6s/BgyxjAM2RBmJwG+lEOfS6T2Zkjon1uHPzEDKgoci2u365FJYO6XAHdGUpFHTWFgB60y+qzzt3lu/m3IvlbVm73DkiEFLLX7Ax9X0bccb9MBqjIUk1Y8BAXT4nzH52wySXV6sLNi9CY7wDqfXG5ilQ4DbqHrBkq7zFdRs6Z1Z2rgJAc/dTntvy5UCxnhWR5byUXQm7+xTVGySJkwyMXn0ggaL5xS9tmMgP0i1Drt71X6g+6KLpzTEXcyGz2j3xHcajpwNBh3JKBXHU4V7oAuV90szGjxGtvF5gGUkshPlUwzqsgyTSrSk5EDV3j/CYudPf0zt3JIyJft03IUvum1PUQ5vUyxOEoN2MId58lYAB9KbX7L95qQJAnpaOPePfio5PAkASPEM4pPeR8oEdOhTCVN6bpk/cqhTGQDMXzsUyj++K3ZqdoFQ5Rpew+QHtRblCDzLjkrV0dp36IIyvR+Hj+1IP7W0swcGcb+PDD62XgPXSEt03xkVL/82WmGPTKuPfcb2WPn1k/7pqug3cMAyyAcP17Y3noPvQXmz1GbLPkRqCM5uvRba2IYKVSA9UynuYmbA9PVt6sMzyZ/OoObZMRu9EE/FdhMxweBssq4VRo1QbsPh+VbGv/bU/Qe19X1pmARthD8xY3r/veIXpcAu3kEF8yFKcyqy56gdizZhtMjZjZnTzxezIjstCVqZ8jqviuN5mRtV1UB6FGLZll4oItjVtt/Jmfy6Y7/v3O/Z5vXqwWbvxXHXJJ+ISVdmVDNkRkEG7s5YcD22aiH+iBmrhT7EZs9LU+vRUKXCG/6Pu3zfoL/ZDgo9iGavju3p2+KynTevoVuLqvHmvJ963CxxXzXIS15Pl9VqKh8cxkh+mpP8cWWcME6cwuNRqfLGr5gvVB1oNHjkiz5KSPatRW/xbVUv0rD/9zMeGrBLjDBvH6UaRC7AA74m/h7wyGkOfSKat2XFa7x8jiYWL/fyH5qPyNCn6R81HitCbGSfUe0oYCN2p3qoRjkzBcr5iWX95/y2aw5LLx8v0FwkZQO8zgEQjMzQn0pPGR1qi3HT//y9s+NIFgFTs/91e6cU8n+ZoFiMV2YsHHsW+MJlSZ0nzyRMIIDl9S72h1hvLSATH30dKpMRDnEYe5IW0BzE7caugiWSDiwgWv6Va/XtY8I8GgDr+JMnXQ+D7hcRKHhq1CgX61vKKBKL7dVa9ag9oiCtckrGr6Hv+j4SNIdIy03J7MeP74i701T7JNcrui5ZcPD6bsyBUMT4nZhqBrtflZF4Py/EH6ol/9+yJF+QpLF9A7A+M5AKdBf4+5mIemrs8T0/H1DML2a5sx5Ib5cRP6M07PvhbyxlAo36es+O7YgATF0rZnx9/lFp6tM1ikMd74azpCyy+r0ci8iLd/dN4Gpgarya/a2MBx3Xi5hhwMiYPUtw6g7AkqRCc7J6N6a1P3CyN7thhP1M9U097NOJM2ehFrkhczq6LepLK2WW7TzmUi9lq28xMoKCeF/Ylxy42HapAR5CdKONwaHdQCyOms3t3YRIjMm+UNFGNi9DtFT9C4TVSo7Rxqr+wJHZB4W0lxSh/MjXlx8jys9Tz+qTMBny1o/ILAaAuNK/jKecm74yeiSYjx127GxNdYxaFTBPvuFpEkyyiPKpH+3yEzwNHiWyyNxCLF0gsNAWgp123buIauiefjanPWnnEAOrvKaVglC/4QyRHcjzG+cB8qJbpuNdzlbPnMCEAtBYAUoOAuWYuHUoJ4XH5e6KZrgi5K5b8ASdrWU/D9L/2+5cuAFS2bBRvvXQJGBRjt11q7LME65K9bRM2/fJL65kt/U7pEzdFTOvUiESXnpKpeCJlGbz+QAoIm81yqYAyFe7ZsINHstXC92+vcvCgNRtQmn2qHJiiSz6G72g5AB/4dgMKda9sGSfG3+pZitYplmLWQ6kftqjYCIwJGGibSJmJZSbNagDuDPPp7HpZQu+N78RXlbARm1Hphc2c9afqE4p5j0Vf8RvivLZkair04JgBJIbQzITt6T6UL28v5XHbzzHERljSrcLMPkf68RwwgIkOwK+ExCZdrd8JGZdMsXxvjfp5zq5N18JULHZuZxXvqUMseL/3RhVGYRwCZVaS+z0TmbK4Ttx0iyGre9vFzII5ewnZUCn4ksguGn2iKRyuAi5ej17K1fuBJUAVYLi690+RRIiiKw1BErzOnzfHtFfjjqpi8BjMJKpMa5HMt3DwWjqHQ7sjWxkXzfoPlfA1PyP5qcPz8bFlVoDl01XpWsUpA2hkv/a4YH9fG2fahhLdy75QAtZF//XFsvJe18vhRpkdXkdBHMZhvCEuM64kKyOJhYucYr8PReKRclVbFyuwEnU8jhP6e1qsGDB5stITDEby+xcRnio9Et+/6XE/nsYa/fuEANB8AEgjUYo1cT3E/BKJ8TTtoflgavFM0debRCQIgSHWu2LXZlZuyb9u25cuACxeXEoXcOBiBmF1W7uwKBljoyDLmywFUN2fpEhvV69GFfgnF+yEg/VBddE1xx+WBkeV8ahTPQIr1kqxZMXo4/kS+0ImojcZD3dPlr767HKyJ9o+ljI2pbEDN3OUtmwFx986lEaSbsDvT2XpcRQ+wscYJRwSVOnQmyDKGQHH2TVSRqUhlomvXGlBOutPtbLvHTQVXz+WWmR0P8g7orUI/LJmjZv8hTpXZ5Iq1M3rCXkP9GyON4G/Awv4ygngdUk+QOvW4gWgiLkViR8zAaArBrBVxrcxA7glsjTy3Nsl8LWZ0kXh1m2J4PHmfdAnbgY2N8JSIAUe4TjyoVjgcUHaMgb4eumRx/VFFEIRJFixeiMjWGXwxXa+EjNK5q5qtEVMj9ugTWK5DOdENtPsgsKoR8h9KuiJTnrQrdw4zjGgdtbUAoSZWFrPKk/qypUlyYRlTTb2U53nS7AEjcXfo1OOwIyMAy2Nccbj6yQQPlv9L3ZFV0wWm9XNuBfNvyn2whjNd5NYWfaX7vm7HlVQDeuFuPY4SByzEXLCzzLgBm5AisHr5EBvMoBGEguxezo5aPWQHag9pLTHOcbZfnh+e1FMKBdE+/nDLyoc8+b5uLWUc36HnX+aEACaDwBZQ6SpqyOa9MV+ZcGeyo3hgBO0uZW78+/Y9qULALt0AaZIXVARZOS4vx/7UUz8/ZNfG7SKktpQKkNodtB1djt0EVAOjjnC7P6TP/u2QquY2ZaM0vWScphvEBJHh+Fe1kKY/8khBycQbwIBT4+TKqfODuqIVqFMZAOLBx1A1+mFLePE+FsGlRkzAgQ0l8Ae7I6VvbhYtwsufzwJTZogToLKXbvKVbKnpjx1ie0iBtQoAs3fOxv4VYBAN5fZkMK0YWMnY3+ZzoIJqmAG3gSv+jlT8my67G5b0x0d6Gl6CtIDNy6BjmAXpr8Iv1wSWnCrclOkWbfAcgbQmdyS8R5sQGVUxib5DuIeHiCV+LdVzUc9A8iAbH20nVkc5BMGn8DEXmcA9Qx1UGAMHof5ww/RAjNcKckem+amvjik0xCDWL0dgMxKqhaORAhCqMNz1r8/MHy49KZmkMUMz5wtryJL+HnEpE2LqOu3TS8oliwBGsv4y9b8ESECUX9E2aSOjPfEnQuRXlJlOZyBKiVZyP7nuSsrOC5Cx76zHd1/kTCCH4K648NQuVDxdhGtLxSJsfwBHyD97z+KfXardBiTNkk5JON7psM/VDb1MAriDRyG7urCrP+NvJWE5aNqegl+B0qjLGRd3xuhdSOJhaVbekM3g9T8mtL3DLqMyeUxc2fMJPJ+FSwIRFUJQYo90okoGR7h9w3JwMA8PlpCAGg+AIyP/v5f3MdLFwAaMyr6CpGWZEqagoMaMTRxETE1ioAWDd1qs5Ca4N8bPWLZo2aDBL2kfC8gA1KF38LjtMGYM+Q8Vq36/7GC++R4KzR6KlMF1DGMzJnXshWcetCJ7SPJpnSKE9jxUGaeDhRuhS5JZgu9rHz5vPdyJcSGUBt3jYKsT/CKmNiVBqCz7Z0FVipA2NztV1ScKMUFFaCbYuOc0OOSPVbnQfV/o1esbl1HJqCSsfEmQ6Fnd2Nu3sKey5KcQX/sXsHLLGMAVVDmrt9vQbJ16WecRRRKZKO3LBc5ZpueAWQWbUV0LRthIpXPAzyIkVIt3gTGutbj+pVhSJQ8SOzrwRtvIumeTU49bpl54kJPb3qwzs+ZQcyP47ZNCEmhX7GRLDBzf2GkvXoIkYkC8XbNUBu5xN1YoePl9HN4FWdxFrnFRzqrWOlV8nN38AFVUmVJnceQXs6y6XJJvAc5os9BCbn/6tMUfTIviJMt4gsYurYtbcrwkcdOIWuVPC7HaLoILVwIXIQkBykBbJaCFbOaUmAXkPOFR+4O0gif6gu+OfFG0nO2TLhVq0UjiYVZzBKf1oD/eikplAIPEJg+hUcJLWd6ghwXqk1/F+k3SiH63H7ncexZsEeSkNn3KyEATAgAzT4rrrZ76QJAnqjRpkqVW4jvoXUTSznMAHKFy2Y2QDN2gvGlPTXmdxT6VNqoRX7+BbJO/cxSgKkTJzZezY3cOAsOVJxMufqObw9adT0OGMAxTeG7aKH4avv8iyjVJLvlLJHar7qeHH5XcCFKCqOqCYr4JTItOTl6g22bPRtoIxNzLpsOEDfqrek/cpcBXNjqdzSZI++pwhMxAPRGHNt4opw8WKZTeoTqezJKK0ASAxIh3EYY8CbQ4T5UtiRXukc4c1sGTVder44S99ZYzu7ynunacMZr0hmYRgawJy9s4770YJMlv1/C7OX8HIlv4NJzGcx6Exg7BIAL7yJRJmlPeLd0bST/e6WAW7AUanw2jcQjHSPK3xufM+UkYpQL2Rhpl50J9ItAp27+HklFzuzfeMzqWIM1kFp2CmKh96UnnK1eUuW2zDAxW0kMJM9fZQBZCi6Y8ym+nixZO4dTv4k37slMrzfvMH9n1NH79mpT5N4vx5921S5i1vrsLkvjqj+U0kOkjz8SxYRjO8oKqzdCBQIRhggB13dsDNTz4SQe4xVBslDN6nUYSSx8xkt1Lga/g/uhzid9eh+PAaAzRxGek07uodXd2A3FEjKAL9xN7z8wIwPDpSFxfkYxqwImSsLen9m/45cvZQDIrtODQN2yieUZDggMqFhGpKRHXMsXXCWTBNIz1RyE/CSFSKcUnIiuR7uaxvXwN3pZ6qB/MbwRuR9RfokwoFe4YBLfvCkfCm/P19Uj5YATa6ZpXRCYlC6dZZyYOo7aL4WA74tXCLhRpCaWdVot2L9xuR4zGMBOmIIp6CKOy4n6O/R22gXOyAlqYH/jtl3TK7z/p9jXaDhGjJCLB6vi2MaDu9JgU56y9BOlhqVq3gQ6egbw/q0InLkkJ0Nmw1sHb7aUASRzl4QJd01nWBo9gK1Ornq5mQzOH0PtpbW8ic7jdIQsZ5OZTDkgK02Hb+QOuIRTz3OIny9EE7QOWijkWBiYO3vXOHaoLBlt41SJnr9vgZ9sunT8W9k/GgOdSWdrIftxKf/yXs37+HVNSo9jhSv8pf6c66Qb1R+LFwONGrnvHTOMeqVFqpipp3zy4rWYk2LH3sJSjIHxosgGaIDlYp9Z/G7gnW4ZXI7RCjKzGjVRU3AwJeTgKAoIQo8xA633AJ9/JdvDSsFzBIqvidWkBIvZ5szCTWUkb/tlwA9f3DDlouTKU1i3Mw3BWrSfF5KAATR7c0xs5ykApGw+KYR3BOYXwtBSukgD+4T/9H+7vbQBIG8LV69UZtdLAgu/OovbyV61lVTjAwNISRCWI7tEauBj37lI0725pQBT96Cdea4SSj+XTgqJEYbMwYkF8NnbjJm7x1TPAJb+rDp8/pKiWX+veIRyNZPFOQP4Rr5wHDxh17PiwMsMLCd1b6/HmQ2f8Ro5mTfBYvFxCezGXpRw2g10FvhK2onamirt5L5lL+uHd+uDvc3HgOzx+AgAXV0DJ65MuCEYqcxYq2aVRcvfObCASwK+Af7wiY7Co9dKIOnR3ZburWLYc7/EUVXDX4iEP9aDBB85lPbCt0L3jK0dfsRMtBP/ZnmRntJW2N56wMPfTw1va3PNULZ83LfVzKLeL/x3kcTHsf+5lIdiBq9rklk2DKCz6gAlUnaqWYBkCPRDH4zFZryJmvjTpjVKiInCnr1Q6nyvCcDIjEHi+cvIWiarx2pBS3t1VPwuWTJpL3mnTT+0ui1tcHQGMq31mEX1FPyp54tBIINuVyVgVQ5WLhsMBCl5xeZtdtpYGjcGxgv+lCsOZ/dBLQLXZm6FkGsStlISu7BbiHQA7iz5WIlojCViu2y4hCuQFQqrz5IK3OidvGePfN8GfZUEAZGhiClQAE+2HzFFstIz0qVKSQJjdLSEnYyB1CmkCkHHdU1RrZq6Y3H7b0IJ2HMJ+IDQmgSYeykuXHaAL5mEoZYqAKmp8N9tL3UAqAbdcQH90eXZN/Iu8U2rWlWszOPK5DQOXoOjh6DkSqmhN6TUSgzdJelzZkvM+iCwMdlb8Fu1Qvx+2he30LpfOoSEAFu3el9ucfWY6lmiyYcroORzWX4kuDxrDn+vWMCqq3nOxPodOJEYiREOguaL4gBYRo1LQOuqHKaukav668gkJqh7SIV0uO2UAMLtq1e3e9uq36t7O6PbPrSdyFdflmPIUKRkhzfi2Mb+d5XFDEUgAvFc+K1SnFg1qyxa/s4hu8vKHVkIrO0VKCDUdM2ygPmMMPOl2o9oh3aQhKov8Qk+FcMimW/2IE0Pur3JEBkzXlN9O6Nj9FRxHN1TmgFObCxleiTWA7JLS/YgoLz05r3asCvSzp8oFiiu8MHOMqGv4LHAm+pTCoMCqhGwvUB2iGqL9CulBVyXyscwZaPEyLobK3R/bW6bLZvUU5z5qBEaQfoY6wxkVX423SlkL4bbJUjozsLzbydjeFHl4IK67qiKyHlFuoEE4RnCEORVGZ6/fyEwrlFVdgID40fPkDVPkMv7oBZQurXbAHxlU3pwB/vQ/cnfz7cH807Id/zrryXxxWxT95WEtxs3ZH88Q1Lx89sFKuHM9xtBxxZPc4AO/7mq1Rppb6e0S2l7t+G1zmLRHB8tIQD0HACS9ctSr2qsY/FNIy2Hki8JGUCOQQ8fIjm1JF6ypl5OXZfs77YzcKh4W6xeHb8YwCtXAP++PYHxkhUX+fd2ZG1SxuOqXu8yvQQ836853o2SAtYEed8IetVmfRXfJWAeQ5WADviXQOHIvYjx88MPUyIxaJAs1XJQ5OBopenXc9cnDVLH3ENkztyY+clp2365P2+ux1MA+B5+wS+xAsrOvFH162jQAFi61PHK1Lk/2XMCSUvIyXlHvjbY0XEmyDQnK9WKfIqzfnNGqGDgGir05QH66VbBRttP3Ul5uLovxgxgVJp0CHh4B6GZcyHg0hnTGUC9v41lz0j4IT+O4TTyOjjvJMNjcS3ObN7MPEdKdFr5dtNurQ+k7UvNZNuwOaKsKNUypmWwZSW7qJdkB5TeiJE7qoj97guRwsArVriXZaGItS6SbLwe4zUb5U76XrT7CDfItAtNR5f0SCpyxcBWTGSKURPiEgUZqXvzXhmvQz8mJbYYnIy/YSdZqIDTmzK8eMY3QhBuFIxm+rHyyHRumziNBnUj8ftKP48YwA8xHdMh/cuJO60OWcFwpgGoro+uQIOEsAdQP9Eq/B4hvdetLrJIQiEZhfhsMrQLp76MpK9nF/tilnFUiUViDvBkNuDM3YX7oPj8cjRwuB7CHZz5npt5p/RtEgJAzwEglyI0F7Tz/KUANDOB74gkyX+7vdQZQPVSTau/Ah2WvyXulLILim8MIGUT6CmZbrUsRXSucgLTNr7mEdejPz76YPi9b0e0j5L6IIVxAGeSFLYZr3taTVp9JPUM4NyDBZA34pgNHM1sF4H/ZgYx43H1kvaaUzmQNeqSjakX1xKwqwFTnYMujOtKAFpt62zyUvdi0kcX0eVrR1eW+CKBOMsAZsI1XEMWcWrUMFSZHf5ttTzF3xg9RjdfyIZsuCLs1CoEX+ySrWAAACAASURBVDWNAeRCgMxnNiPxgZ8xI9gdE/AAKYUunmLD8tmhFJA3TS+Rk5QwLGog+oSNFLuqir+wQZSeZbOKL9SxZ+cmrMDyaDk+0Ed3pP9gU/hgV0Ggs4DXiBXreOFjoYfJ9l6GDSjcs7JHrJhzyEAMHiMZXsFTnEZu5NXkZ632ibN7pLKw9L1WbHVd507pVHqTheXxjBjA7ZElUAJ7wUVFkH+k2/ugxhfdDo7ED1/hzcAJ+lcswjsCfsBMo966wy5orWsFWllk6e8WheE5B3zRaD8Kt5V5oTlBHdA6dJpgKlP2yl1zhQcujy3YIiSGpd90P4wxbRno6Z1LCAA9B4BZmcwhdt1JZ5YHYql6nnr65f6eRqNMetPajvUmilhT6NpMe6kDQPVSFcBRHBFa3cCZcq2w5v3Z8YoBZHmL4OHxF+qhHiS1uGT2m+j1ZXqPq3q9kx3KIc37w/9bWbbeP24z8nes6LYsZeZmudrGAQP4fi74nDuHsGRpsWP5bVSsCNNZIuP+daHs5WfzI0/EcVtgGV8lYN3STR2fgs/nkVNMBGfxKvLgNGIEhPfF5sp/VZFAcNvuaxtZux72DF4ebyQQZxO67gPNcmp7TU7U2wld9xg9GZMXKW6ddrA8M5Pd1cuxS2EH6qsepf5dG8yyedAqD2vi/oj19KYZJ0V67H4BadxdByuwCnVsu/UWvM8dfFXsVwzYJ6V+tr79Db6K6GtaIYAlWJZG6TqUPbuUalJlX/2ajWzRyZm+QLbv5bUMLfkHhuyu65FU5CzrTZmgm2LoBkiGqI3VtsN6+7zo560H/vycC+ePIkfYvI4bYKnIUBFvSLawlSws92eE0czaVwhprh1BREASNKrx1O19UO9PfhzF0djxXT/3ItiPgyji9NHTfZyVvBM3tJIB1MfNa9eAvn2B3BfWYi1qiGOOf2Ugej4Z4bH8y235fPA9ofC2apTxefX5MRyLLULORBsb7MLbjKveGQkBoOcA0Pjw8E1zFgx6M769DL/hqDcHQKdYcgvl05nZpPLsLRMn+FIHgCqgypbqCc7dppMfgDffBDZtilcMIIWBp04Ffr5ol+/InT0c7Tsl8riq1/tYHwx/fm0Y3j/5ufj6+DcrMGBTnXgTHzbeVx0nljRvZvhcv46nabJh96JLIgDkJO5NuVPP0u3zL4WikbsR4+ODH6ZGYdBgnzixgHW8JLOTx+3Sa9ADBXdlIPaDq3KKIoE8u/UYjyHhDZFVQrB7xNp4I4E4m9Ar4G/8jTfF8Sho2x9yEeBJysPVu2r0GF120W6nViD4mekMoF4KZFD9Ks6LYH4SutoyWfo5ELv0sEHrF0rrJsYU2yY8d4q5E6fI1g+jMRofiX+3SroYy/wa2SRKrGZH9cXW5WEzkaijBLqd6j0FOUZ2ivfFllEvbkLOsQieIC0GRxVbgI/3NfUqACTpYRdKi/0ojKrqwPgoATt7Rul1/IPgQwIdMdVWfvUm4DRKaUXlzoskV04jIlkqRN++5/Y+qGeSuDtmQan3qRoXJIQghMMg3Bi7ATPIfyFE9j8G4GNIFpgVDKA+bjJ44/h9d9J8NP2tmdhX6IixSPJpb9OleL7jKlvOhSk9mssE38DnU6VrCfVBFUOaKhe/Sdin1y0hALQeALIULE0E/zcauWz0LpbO1ZLpfBnABC6MTVziSx0A6gHVw0RpkTziLh6nyYE5Qy/ECwbQOKgvOFoASc4fQ1RQUjSs9sQyU1THCZ3r/i0G3ZdsSuLZdga/F2/iw8b7qpenOn2aGimj7+MU8uA1nBJkDW817/QS8A/nqqLccwnupjh3+hxJ4sQC1mUTmJXQV847UQqlYi25dYaf8bpLlpTZTWdN9clXwyMx4DPp76xs+eKLBKL6R89iOsP88NhmpDzcXYdwAikJPC1YGslPyIuOiojGrt0+pkDqvGbaXOnC6uznBliGi8ghCD6qsQzXJuQq5qyVE1dcWqtWkslKHGD/wAn46lkPsbv38bPINqrynpWJm7/X4Ra9/CdibAQLH9I6bHFQS5sMTHzBLYwl4BoXpmGaWHcDA9L+iJR92nlcLDqDPbwNuzXbJ/gSX+ETW3d7E5AZ7xXHOLKNKbDPxnetZuQf+AP1xN/0rR4GuVC1GoQb7wNJYcdDcwjmO0WdcwVdd3sfdFKMcvxR509twJLY4/LRK4RDOITC4nvCFz6AdB/xJgPIBMC0afL96IqJmCiKaMDv78xB/YUtTWUAuT0llphR1ht1QFUQq8Yf8fy/b9PL9vr1SggArQeAhwEU8rrHX64fEsv4DADRCToEnvhGcu8l8tR9e6kDQB1f0nZcERTGQXBlSHFQP39fUzgfd5dvLOss3pEZAXeu43n6rGhS6rLlAFCfJO5/8yNG3f1AHJ4g53XBH3odiHm6iXogqyzoogq+gd3fH4xTuVMvAU+4WB8hobTRBli2ShqcPk4sYD241z1PqTl4F2lE+fcQCjnYdOn9QDst+p66ag5Z0VSJ4BMZiUvpimHJwL3xRgJxsCMLkpOsbj1H8hJ1DHv1kjIb3rQXWMBU+d0kxXs5uz4OT+wxu0tZit1cJgophD3YE2vrpybOaeiADvjednr704ag6G3phBDXppee9cxTz6Q/YLZ/e9uEaTX40Pv+U/9RGB4pPd4YUK1J8rZTK7i4XIt+Hxi0/tV+Lmr/3ELsMnLseIR+0N3jfXCWjdOxbHx2fkIr22nGRwDInbFo8vff9qvXnwGyabtAem9adXrhb4zvwNlQKYFELb38SS66vQ8MgpjlZPsJLdACdpsZ4hSVn7az+5YR13EdmcVXembNyjU4cwEptnwIAkZKJQjCFPamr+NRBFqdH4kklF5VjSoVzAJOmJ0MQZFPcAyvowCOia/p3tJPqsN43RICQOsB4P9SBpBPPwnnNHbcrj1F5HpWAmLrCo6PF/Ppek6dddUrLzsLmOn0nenqouStleJqZo68gSVbM3hk+nl6s4yr+mMXghCEMBF4NMx5yLJUiB5Q6rikCz3GoPu5PpYDSk/nr763HzfGhpWLKl4KuybsjFO5Ux/cFwc2R6MwyWqeP+Iseo1/NU4lYL10NGuW3bC+PpZhmSDoA9+il401auwLTxIZ+r3tOjA5ksU8tg3AccmK6uehB8hkszKD0BPf2QSru6Weh0n3mlkmOOjHMLKAH5SrjTS7JE4s6s597DqV0m0G8MkTmQFSrQkWYiGaij8pufE1BoB2W3tRHKnwAM99EiPxri1ACeeai2afSbWdHgC29vsZs6Jaiq+6YQJ+DOwmMkRsVgNAB8mlioPgN1IyXA5+/Sfy96rh1ArO6rk7uw8qW1T4wlIsxdtik1EpRyL6o489ZgCdBYB0/vgIo8V+jMQYb6R3nF0jgyK+y6plxWVchmS6LvNpiIYxshbZrJk9IDPbV/o7QKjJ/kupkRqyAlE9+ymBLXSlFUrChrIWJOHjV0gcJ1tlbMAmuDbNpcSVcgjZjjIo77NdEPasXIMzF5Dis7ojYPpEcQ6lsBMX05cyHQBSjWC51MB2aBcgs6I3kEEEx2zeiMIb95sQACYEgFYDwCEi629oL2sAqAcJV9/qCL8fJat2z7S9KNS6WJxxPnrJdtjAMJy8JNHum/AmWufYJLJnVvxi9RXl4FKrbTqCl9t9ji63hvxjAaAKEr4eFob+g+U1KAmSuJQ79RLwoEsfotnTH8S+WX55nKOQ5RKwrlHGwZri2wzuixQB9lOVM7YkNQRyBa5YgC8OqZ4V//XBXfkyR+cIxq755+OUFdXPZc0aucKnHzB1Kbn6J0t9MKQVwYdZV+GHK7XiFAAaWcBjL7yNt2MT/qWyXkNMxkxuGd7168OGPeU56Qzg5phrk9rJgQuoxCd/QDm0/yqPsy736jMlBUN8VKW7i7EwWtIpiQcc599PYARv3wasimQ7BIDF+8BvnEyx7hu/BYU6lXdpBefVRcSC/Mmk5bmSLfp19bV4vackC8zP8xmanf7CIwbQWQl4LpqjOWR0Ru9uSvGo5q04s/Ea9QCQZcpKpcOw9E85Tuzwr4CykTI9aCV4UsfQg1qSaX5bmxSJwp/hbuaCaF30sFiksznLZuqLAwqTL0VDvIUVQouyvSjpuvZ5oArBkeup8Ur4fVxO9CqyR5wVxyHmebPU3/fYjAkALuDmwe5WM6XfWXT55lXTJWDjYkudwD4UFdqplPkJEFALH6+Ft/WLSggA/9sBoDcl4H9lBpAP/TD/YRgUKWNXZonWBdW34Vq8xfnoZchW1a9j9lpZUrj3ZgO0SbHUMmlDH1D2jNuKRTcqiP2R/j8p5xjLGUWPI1jsBrby1OUHeCVbKvHp9Tdq4uS41XEigeir+37XeqP9I5rqAGWxDTeCy1oqATtzKeC+OGlQHJs6cGxLYA9wqFd3Bs6DEU+sUT0YvxGUExlCLyA6XXrsXHYzTllRdU+oGdaxo6NESurUwObC3VFggz2DQFeDuIL5dRbwlhzNkXuXDBhKpT2H3XdyutV4fPVV4Px5+5Oka/G9iU02worawmomztMzqjOlmyVfgXmPpFzLgoJfoPvNz0RAxWY126VjSHXJJTJHTwUVcWsF5+mcnX1vLBd+WW8bCnWkkASwNGdvvH1+rMcA0FkGkAu1SpARS1I8sYkQ8+/4yBJxP8YMID97hGTCplDJ/fAzbwJA/f6SSPEo1B/+iBJ6km8G7bGN0c7ur7P+kILcWsrazc06gdcEzpnXkgKPxJYMcEnEMMNmNpb1J08Gao2tjnyXpQ7h4ysPkTxrckvvr8La6qdNbcMQIT0MJMcjQXiJj3ubEABaDwD/19w/SAIhIlyiViUJhN5TnIH+9SQQfZDv4D8DUyPai4ukovqcJJ1tunreTrAOsi1rjsG/cKxmeJs2iPx+pmWnEQdW2ZnD8Csq+UbX6n6ADMu+95qN62nCUoHnzqXXUaqhDGJvV2iI1Bt/EwMhCQRm1OyNx9EzFmOSDkKfp7LMtrLXGrT7pbrpErAnn1Keo7KvUgxV+uhysHQl/+IJH6UH440HSwkbNVHEJSvK62fwRwyis6ZjmWq9egp/nssTbxlABkuDL9odPKpnPooHmfO7zQDmzStFbFXTbRVZ+r2AnA6XEd8BoD7JV8V6/AXpgzUCAzHIZ4Qo27F5up/GvtYXb/N8W6BZtMSPcdFwLUket1Zwnt4nZ9/rzxMVA1JcPGiTKPnllQ9xYeB0r0rAZ5ALuXBOuN2kwT2HQ1vNirq6Lr3UqrZR79ltpEV6yCjcG2KCroUZFBCFZ+FSWncryqFGkq22++Asm8l3nsQRZs+9aX/DrtpAu01FtjCbEHCWAdSzdd+MCMfAT31MZwB5Dc60QRegKZpiobhEZtovIUdCBtCbG+7kN568gOPpMC/tbgiaIOmDMuoMBCkDQ4BPvlj7O08n/lKTQPQyz18f/YmA+lLtfWf1T1F4+XBhAbZli/XJQ3WKziTsX24rRm2VGbtr7/ZGp2djRcnWitewjtcqk/EChOcYgItl3sX5kfMFA48lCrMDlKebp75X2YnUD8/j+PNXxce/4D0MDP5FgI252jxyxLOavfF4egm45fVR+OSBHWi/P8fbpkrADLI5yLMf06cHyAplVurMGUmMUAEAj627aJChWtZnJ1h2o0aX3sw4RziQQCoVh8++fYj288fmdRFxyoqyr5npo2aas/YH6qIuJFa1bO7b2HEmreXgRt+vEQN4o3FXZFk2WWwStXMPdkUVdxvcU9uMchuqES9VJtYOPQDPbTgq9b1VNq6nZ1QPACsHbMOGcJk1YyZyUNAYW4bIagDI50rpEy6KtmeNC6e9ik8mZBbEG1dWcJ7O2dn3OlyE2WffC2dxFrnFpkuTNsfTaXM9wkVeLAHHIAyBgoHtjPBkhdHq7pqMFnTcVjHtyfhOhAhhs+jN8ZQbDlneAdF2F5ytiSrj8pwNoM86oRGuMl5GgoqVe7MYdgs94hpv+mcVwaTZbLIzEkipd7LD98pl3EucEWmeX/eY1TWer+oPjnl0G+L4ptvWlU28DzueF03IAFq50W62/a8HgOwaSsAoIWh6H1NnQbM6d9vT/4oAkF602R8dwZ/XJIGbHpHdX5klggNmN6xOHqpH9EF9fZ8/8OMtKY0wCMMwN+cgfPGFdQwg3QUKFQI+ePsu6rdLK/a3ErVFUMAJi4B8BjTuShRGP09al5F56KqpjNTrsIuOXqvZFk2fzBDlVeLsyJg1ayqvjqOXgN+5NQnD7km1oRb4CVuDW5gqATMAZQaQ1542LXCZIkWxTVmEqb/z4TiOI7/4k9gonRWoX/uCBdK+yV1zEMfuWwE+26Q/8qZ1EahQ2d9rcWyF++O+2K96AMvPmPkoF8vJIlCdtl7eZqi5P6NW2bXm/ZDt1zHiWqI2bcGzouXdsk+N9mOXkRVZcdUBkK73Y3xnAPUSYffy+zB+q/Rs3VKoM0Zmm4yVMlY2PWmrcx02DPg8Fs289ZUaKPdEspZrln6ANTtT2O5NfC229MUiMYCfd7yB4m9JmZwdGRqg3K2lHheLxpJnWtzGbaQX+1jjVwtv+a5ykEOy4mrh7l1Q76D+zK5AHdTBKvEznsddpLWkoaeO17YtQBIXWwo8wANICMoan5qoGWMXtXaFZ3QWnLp9sbUvp6IjOkLiwnVvabPYSWckkDLVksAnNBQXkhVEzseHLQeAegaQC16S9lueGIi3DkkHnBCsFfqFZs/RXV8klICtl4DNPlv/le1e6gBQXzGnS/QAtyLk4EJMRQ3YZSq8nWD1IKHE8Z/g305KMGxoNAHlf+kG2gNZLZ2qYEzXf3pQsALqpfxbZCs9BWMMljg46GURBkq9e0ugvLEpkgCDzh4V9iFkgJxglagsWXjMmHkKOp098Hr/90g+C+MetRWbbXl/Cpqs62SqBFyhgsT4sTEIVHpkzo5H2YUVkBgxGsQrMoW+Le+H2p+7l1QnT3x7pDoqhElcTzI8QtrgZKYFlI3H0PFUunyN2o6Yqnw4KcrNpfM9csmANDvAGMtU7S98hs8wQvy8RYa1KNAzxG3p0dGvOAbhCEAiRGI/iqAYYpk32slwQv7yS7Nn53k7NSGSLHN13XEcjpIBPoH+Hf1nCLIGg2orEyLvbcaMEutFq7rldx2Dbr8Af+HmwZK5t2OD8cqMgse7/nqMinWlwHh01RBkPrrWY8bRGAAWxGEcjpWlNbrGcL/xFYw7C7Lor90K0vaSC6+TyGc5A6gLfVNoPpPvTZx4IF1NlqE+GmKZqHq4y8opkpDnJ+nFLThGqHfh3RSrsTqmpsjMm8XXGd+tmxee2TCY2wMrY+PgDR7L+sazUu8bxzo+M+wjOpWMgdR8aZFoAeZGNDV9ju76JSEAjL8AMIWwbIXwnRnvzcP4L/3NSx0AqgGT6fSwsBg8wStIimcOwGX2u9mgwHiP9CDhrbPj8Pl9VtClSO3WHO8L9warHrqqrED3g3uhgQjEc9DsvVHOA2KF7a4cq7ByzjJLPC/KDCzVFR81QVzi/MpEbQUYcQE4UacPbvQfE6eys14CrnR7EabcocmMZHAuytHPVAlYDwCZOSHzr2BBWZZUGRx1X3QR1nb4ETMh3R1U43NApp0ZgDd/o/pzdUB91AyXGoY/fXMT/UenF8GrGQs14zPDcz96VH5KfT0KURN4zkmO50aphwy4JXTQauW7GOcA0JilmJRlBLJP+0wcf1jJ3/H57rfcZin0jIRDhgbVURNrXhi2KBpOUdz4anoGsF2V8/hxg4QonCrRDH0yzLOxRM2W7fhbHf9Hu62dz6U7ShgSI0VAmINvbHxnAHl8Tu7PQ6NEdpdth29ZlI3eJv7t7njGEnAVrMf6WEzkaL8B+CjKEbbtbWXDeO9atrSLDquxRScD0b1mKyqIEjYDGLPNGNBStJ34Nralid5Bi4Bf8fSp3JurfnHuj+z5DMgen5R3HJrtlGN21+Q/YfIjqctodjGhV4A4LkVftJ//yiSNcX/6Io9lfeOZ6u8bdQHZp3VuzkTVn+VY1glThIC42XN01xMJAaDnADAXACLXn8fi48g1JDCLgZ4K+PhfiiKxnMzH1RwFyfMz+m/Y4l8RAKqOdMb6Ut9561mqgoTRSYeg31MpP7K6+wq0+bWOV0GCmpyY7Sv5VnoEPLiN0Ew5EXD5nFtChsI0Rce6IamVs/EhMpY/HUqE2/6CX01pj3Tx/YHIOntEnIgnegm41L3VmH2rttj3EHyO2cFDTJWAyZSdPl0GbQyKt22TEzglFzjpqwmJuMCu5/rYdP+c6YBZcdPQg/vPj72Lt579Ks6dIGzf4BxeZwALFACOHZPXw3ull4B9EC0ybIoFqZwM4pKFcmdBRq3JT/a94zYA1DOAuXDGxqqm3MX7iFXh1R4yZ4uMuAxkepDQIuQGflony6b33myI1sl/s3nFWgl2jEHDaeRGbpzFXaRGWty1na639nvOrlcnpHEhwkz2M0jd0CM+hfAGDolnwd29NgZMTbEAC/CeOFxffIOxkNZybFbYrJ7uj8oAMlgmLo2NriNf4lPx74b4TWhvvv22JDiZbbrPMN/jXDGnbTI2JEOpDKO7a9GDebPH5bEoslz+8i82GaNhKcdiTHRvrzKAPG69esDwxvvxRpti4jRW5eiIOhenin9bWUSo940ZUWahCXnRtU2HJR6Bz58PTMgAmr3ZHrbzhAHcIeBEwEVRFQNeEUxsgIYtlOQ+AoDUUlo2kKetIZTi6Qxf7t281AGgcaD/C1VRFdKOLAUe4lGsxyv/9iZzoQcJXU72RNvHMvlLmZObOcuK8pLVDKCDc0PhXMC5cxL8Fqt3wSDImS+vKoUYcXHq8VGBkpEAoZcxTn9rxzHST3du8Gdxch/RMxZvpdyC3x9UFKezsUQ/vHtptE313t2kxzIWxXPNNF0CRrHl+Dv218yZ1jCMenm/1NS28J0tgUq7Zh1D8Rave40BDAkBOJGzKfaycgBIFXNXYKnEBIJa+DDLKly96j1GVfT1RghRYyVAXPvCZExGV3GMvmlnI22fVm7LVHpGogy2Y7vQjQfGoQd6YdwLt8VqFsjTfdUXEf5PHuDwFQnjYP90zrHKVBbZeAxj2fAapPvEJWQTgruqtW5tx6d5Ok9P3+uEtLVrpXd4+0/SIVnYHUTnfBWVspz1SEhT+1DPDcWwJwjItrSw+xlSJJtt4UKgiZRMjHMz9hcXMb1e+R4f7Owg9v0BvseP+EBARSjHZDbDruv4cT8FcARHYo22Zvq0Q7sYac9G7DEXb84ax2Dim9XC1+zFMgtbLnQd1qG6+Mlo/0/wUaTELpjNrjmoQFwB/DesBWpIbcfoTz5F5hnDPZb1jefrwIqOhbzo/uDMvPbDGNPn6K4/EjKAnjOA52IDPP6XSpGjYgNBCiirFhGbDZQeLf+t9lIHgMS8sUynmo5bIeHhBF63fUfyhS53YeY2OgQJk1rB92dZ/9g1+ziKv5/PqyDBgXzQuSh8DhxAlH8A/l77XLBPWTJ0hivk6luVd6mF9U7h02gxpqhIkbFUyoyianq2RM8QfVlskcgIsV3sNhrdLvSLk/i0mrCyZAEyXt+PPdFydUzwdXf/qWDg4ynA0bME7u5JsWLAjrAiSHTsoBBMpd1fvvx+QlaBODGzk5I6hh6IJ+nfBb5Tpd0VRcSLti/mdWbUnaQNhXyJpWL7LWkLNHoqnycr2S1jHxm1yja2noka82U5KXLSNIS27OCWBKIvonSfYi4QRkCWkvXmyWHFzHulb6MvIlIGhuF+mF2ovE7QRhsm1EqWlFACJTBMTObUX6TTi65px3OIiwWf8Tqdub6cRzCCcRG3fTPgzbw3PJb7jSXgL3wG47MYKRpeC6vwJ6TKAa/vd4lYiJfmrMzKrN9vaCT2/zFGYhQkw9/Ks6qTS/j+pji7D+sfOmKQuU9PzHKSJZQepLpgBoXMWHLB7KwxAMwTapfimeXXHm2jpFC9WTiBTuyhHmn3tL+gxqzmYh8/5B+LDsd7eyT2GM9N72sJXQLy4yiOoqDYdCbaoB1mmj5Hdw9AQgDoOQAkopzQ+TuCPEqnJhkIfkQYSmznJgSADx8iOdMsL1kz6lfNyfIJWl6VOJkjY9eg3OfVbQMEMSH3HGW0PF6Ng1TIe/Xgs+IP8Zuti2+gTIMMXgUJelZx0uE3Ueq5VNmn5EaW4ACXpUd1ralwD4cTl0CW5+dxNrga5jRfjYpV/NGjB3D8uLwkHRyuY8TGFPkJfQ5IIsu5vhPR82TXeAkAub8PK53C9E2viX2fLNUSfdPNcavyrzqf2ZLYRbXH+3ET6YUm2VW/7GhY9KLl7Kt+AD1zlnZkX3zwSGqhlMcWXAsu73VmlIzsKTKWfKFx31sgs6Tf+fRG7xh5TLMTkrN9GjOAZS7Yy15DU3+HgH493WYA9bJjW8zADFHwsGOR9GNyCOA7ZDXYdndj9Uk2MHEMnoVRqhTYgdKolmSHTcvTbJmNzzvhEfYWg0j4ww/R2O9XHBUD99hwZ7yeh6z1xEPTgzcufFhWrfdxAbwadgyP8QqSQ0YqZkrAVDW4cQMY+aATOkECLunPe9CvuCANWAnCzFyaszKrnpX6Bn3RX0yTnh129OPp5BIGZIVD7Rnm8b690DNaurN4kpcpX15CQ6y0OnWAYhmv4YsZWeTzlL4+yt5aJv5ttv/UPaVUDV2JOkXaM7JtfOcgZfeWGDfOGpFIf98U6S0DbuAGJPRBkWPMnqO7PkkIAD0HgMb+8xM6whBLXyalCfpiNpA4wIQMoJU38P9hWz0rxsMd7zoR+SZJzevhuWZi0Nk2trOISwaQ5bVqQyqg5HNJV1XBGsvKDLbMTk7qZFSWaG1AXYSES52LOWPv4KNRaVziClW28yOMsq3G+TuFz9GJIXqZTg8QHn7zPUbelWWd9vgBG3K2j5P7iL6abVX1Cmavzyb2faZIY/TKssgUgF8fEClKfOUKbOKwHX8nEgAAIABJREFU+iNEKyji53wRg5iSpbBj3E7LDGx9f3pgPD/3Z3j3jGTOHhu3FgPWhngdGHftCtAxwFnTsyoDfb7EyJhPxGZmS1LO9mkkgXxTYSle+1h60M7ONxJtTnzsFgOo97/+bDXGIiyBo5q1FYyl2ddfL7MRDRGQMgj+EWG4nbkwkp4+IDQhrej16cEMMyyZUobi3I0k4nRo4VgZm2ynxgyS8ho2e76uttMJUaw0kPSja+n5IUrAyN1N7GofCou3CI3RGBJ0902PS1i6N5tguMdHcGB8F7hA1rNpuuTSvESt8H4E5WStMY91cgmhKxWjN2Ijqoj9fO0zAANi5GLdE6xAzySauU+0XiSJyzcq3Cb+vB1l8U6WbR4rEvr+9WeJWdfB0UNQcqXEgQ8ptdJm5Wll/HcWAHI+eY5AsV+KV7+Jv+PlHicEgNYDQHX/UwssOyXNCCeTpJDDZh6+/7FtXuoSsBG70gB2A3ZjCYsgXmdG3O7ul14+vfhKAWR/cgwxSZNi57onXvvF6hnAQceaof6z+eIU6LqA4JwuM4Aq2KKFUnHss5326qwfoO617x0wMnoGUM9iBk4fD/++THIDq1rMRbUfmwvQtzPMoZnnWJfw2LfuHm5FpRE/o65hA/+VpiQ81n3+N64MI6O3LTajksvDZsR1XId0MYl5qx6ezFvu9XlzH/q9nfPaCLQ8KcudJ75ejv6b63kdALqTrSCW6nvIALxroulYmPJDUdoyK0vhrHOMJJBRVf9E/j6yVDgvz+d4//QQtwGgHsRPTtofnZ/KTI/RBo5ZEN7v+G76JMuMyJXQ1EiN+ziJvCgadNKynaOxnFmz+B2s3ptOnPb5/HVQ6tYKIQ/DRr9Yko3iozkqEsg9rkcVVMFG8e8keIpQJHEqXK6OTykn1ceUbVr24E3kvCwrBBRBD/cJ9Egk8fZaKMBOggIDNZIT/O7bNQipCdgoYIVgT3sq1+rH18klERFASPSftjL2MAzGl4mHivHHUwZQF4s3e32KYTt8cioEhj7AOb/cyBUlLW/MwglewAD26iZTgYRXbNuFrG+XtLQ44e/055NlZcofkQgy7NtXEBj5FMfwOgrgWJyqAqqPEgJA7wNA1YcUpWKeuigXLQB490PNPoT/A9u91AEgX1CullVjmWQPSoo/iUPrDMnSYqMYKUHfVpqeXbmTOLNQfo/OkhU7F1722i/WAVf4Ywf4/vC9OKXdPxxEsTZvuMQAcoKpF/JMEFvIIlWNzOfXccLhsnSclp4B5Oj98f0BYttGWIz9wY28LnUaB7MGtZ5j6Wq5ij2RsRLaBm/EDlKs3JU479xBVLZg+IU9FRIdeX3O4HJMVqe3iB6u+yExhmattdzda71fIr8ei8/uS4YlmZd7cjb1OjM6eDCEQLiz5oxZye3ikgE0WpDluLgJm1BZHH5q8o9w/+NRpkggBPhPeNIGbYRxkMQlnUucH9WqQYgxx+Uc3d0HI3v2TGhmZMZ1IZOTP8lFy3aORqut7LiIiwgWp0Cbu+Z+v9psBelAQSZwfLQXXTyADcnqofJjCRtJh1u4A3kwZwE/xxpiaZm5IiuWZAtdMzJdwCNQs5OfW8k4mb02I2FDz7gzk6ncYaxoD+oi48TxjSy7HO2WNRCnNDLpcAx8KlnGXDT16eP+TD3ZRVJAn/sYOhR4/XWIMv+lSxALibw4jUc+yVH6tYcecZj6WRgxgGOvvYc8+xaITT6ochYzNr5qGQOons/OnaX4vsI28nnPTrcSnwzIGHMjXt63hAAw7gGgeh4UVpDZQFms/2+0lzoA5C2g4wMZcWw6loKWW/UgB182b8om+uTaa2AQAmPCbJZM3vrFOrCAh/STox/b338LjT5XLGAGgINCtmEbpFWWalHwRVI8tZUQjNeqZ4h+zjsU759iYhs4MXYl+q+v7XWmi/vQyxnFi8Vg5z6JtdqFkigtnAc99L0hXTM25wQUmtYNmzdL1h9LqZzw2GpiNVZDyszMz/MZmp3+wrIKv95vDpnRmVPg36OL+HpNs5moPKuNV5lRdx7A3PdY9EZvyDQa8YA7/cqLYCQuGECjBVm6C7uwC6XFMWYm64GAKePcapUxszd+vLThO5a7HtJsk+9M3RI3sXJPehQtCuzfH7dzdHhgDX/o7Nn164HIHK8i6Pp5hKdMB59bt0QW2YqdozEDqLvfKIA9T4HZRkpDxVdzhqOj3eJ7kAFDMM7bAlH+bSyn679n9oqBVvsBaZA07B6uJH4V2Z4Tmg6RQWTGKD5xmNyvMQDkZ3eQRvgP0xeYMjpsVgJAXWKI/V0ndBEWQZLQPvEfja8ipfix2Qw4g0AGlXxnVCP0hXMA7zv7kCx8YihZ2md2dwvKozwkgPCNvGE4fCqx6bnAiAFcFRmCECEGAqT2e4hW3ZJbxgCq55Pv1YEDQJkywGuvAcNXFkWWWwcQjkRIjOfo2dMnzhn3hADQfABInT+7PoDzUSFRrK0aM4JElupM4fgaR162/bz0AaAehFBn7TkSCycDiisXxQHhy0rgujcBoBoA5s0IQ7N2kp2ocEQsH40YYc0Kjr/XM4Bl/hwKDJEBmUiz1K4NCjY7YwHzXP5ubpf40B+UwjiAQwKmKpseUOhZzF9zfYJ3zkrczdEJ6/Hxn1XiJQBk5oJsX7pbJMMTHEEBvJnqiCgZcSVOlrK6TIcH3ACYm4930SbxfJsWmb5ta8zCLEinkSkFJ6LLka5xCgD14P7ON7PwzV25786YjNXBnS1nRnX3CVcv8Ry0REv8LL5+DSdwCpI0E5eMjp6lIE7pi6aHUbjlG2K/f2b/ELUvT3eZpdCzTpxID6eqiAL3JJ1824bnaPRegM3NJS7n6G5Q0wPATZsA30KxQorJkiH6wSPQC9YK7k0fD0gGKRK5G7tRSpzCRHRFd0wU//ZmPHB3HUbyCQO0aVHt0R4zxM+KJjqCAxEFbLswEmpUYMCF5fnzADNwkeCUA+xNVBpVg3YIDbt/qhSvcHZk1/Ja+D+VgXyI5Egf8NByCdiYjW2OuZgrUFVAd4zHREi8tpXssjsbTCMRh5n4losbIvBPSf7Igiu4hiymS8B6UM5y7dRdRZH19gFE+iZCw1rPsWKlVJmz8m7o+2SpnVnd69eBdaiGalgv9keVh+SZXolzoJ8QAJoPAG9SnJzsblbjXLzozP69G+ulS4PB/4IjyEsfAOovPa23TkVI6QWuXrMH3fFKRkLdf/Wy6vizyLoNsOezpaIErKQYrAwACgNIjM9vFcfC7yNZejw6eAHyftYUjRsDR45IyRp9lc+J7WCIXQh5NWqiFv4Uv30Pv9gEY40Dqh7opP+yF9o9ltpu1Hy7lbOM16VO7kPvew5mpx5lQPqYW6D8xas4b3uNXAru1qoFsF4d2w6jIN4wQG2V7qFOUOiafiGy9mriFQFHHUsPjCmYPGAfX23gQo8x6H6uj+XA2Cji62wMobadumepcRf3kVqUIDkBeJvRMeKUfM6cht/recXhr4e0QJFDP4kFEANxo1+0ejaYVSJwfs7BN5A/8rAQMKajDj/nuf1TWSfjM0Sc7ryTxfHKqX2I8vVHxdIRYkHEZha3pUsTkUlbIcpOPBiFj/BN2lECAxjfASDPkf1LrJsiZE3w7YFu0RPE+ZfCTlsgqp4NHaqhB0vFiwNPz93E8fvSNu13vIX6kLovVoIlF/OY04/1DCCfSWpLDt9YAXlu2YlvEQiwlAE0Sp40C7OzzLslmoZJERIPG5cMuH4xOhFHlYCnoQM6QMJs3g7ej6UXipi+9+rdSppU4iK3XMqGbCKIzISy2a8JBjmP4+zdctX3+qJL34bwhHewSHykNE6tzCvOjpcQAJoPAIleJyCBAlphXHQBuBb7byqTEgvI5RvR90T4xFqUW3nF/pXbvvQBoIOMRCDwZ2hFVITMYqQNeop7YUks4zTUnVIDQNkUx7D5buzqvU0boTpMlh/V5q0wFNV+Vamwc6IfMDniQ/ExCQLzgj4QAasztiUHt6ch9W0TwUd+Y/B1lAweB+ArfA2J7WPTSyp6iRCdOuH9J1JWgpi6BzmKeJXFVMcxlr3OISdy4gIo15I/9U0R3Jw8Kbd2OpiR9quJMxIHyHJ2NEjGl40A8a++Yvm0D3oLOC4QtfFvPCtWId5IIENL/o7Bu+uLfV/qMBxdr31qOQA0o2e4D0VFVpo6hizzxMBX4FKJT/W26fegRAkg+tIV7L0l2dgL0QRNIfERzvpfL3FRzkLhkDjBFUx1TZAkWKaKT70843XqCxSW95bcroAKkEGHPyKQPJU/7t83n2XRFyUsa39ZfgXa/yb9o0clHYqPnw4W/zYbUFq5L7T+262lD77EJ/gEMuPeMNlfWPa4qsPudPar7hBBDGDgJbtm5K+BLfFBojkCHmK2XGrlvLmtHgCqAPY3NBR+vWyZcVWQsKyUgPVFEWVZWj+bgqYbJdRi7Buz0PeQBGXHVzDuTItxOD7Fp5AC0O2z/YkZl2uYPp5DWT59DK7cTyIY6vcyF0T+qMNeZ8cV7IJZYGapuUAjZr0jmFcC3sq8DyuuFY1zYJwQAJoPANX7wjpfXQA0TKVpIf8mZ4yu6ExV0Bnkv9Re+gDQaMJ+v3YzZNwgmbVbZpxC44/zuMyAeLqRagAoj63YIh4JILxrb+x9f6xwXvjjD2n1ZXWlxgCQKv7v+y/ATxHS6qk3xmJ6kt4iACQ4mOr4euPEVrh5fuTHcYQiEFWx3ubaMBmd0VUY2cjG1TvxVGz6IPZX1taoemWO+PzA/BMYPPc1r7KY6jhczRKvxCC4SBHglyMFkS/yqE33jLgfbsN79MIqn19wA6ZMtPZ6wFmcCJd+sHqbi+Zojl/ER1HHT2HX/TxxkoHRA4/D367D3FvSMYATxo/Bwy2XgJ1hqIzXoHyAdUcKTwzIFzrC8IExiGNmUbmNrE1cFwPy/yEwfM6COGPwuH6vc8Fkq8+3p3PWv9dZ8Xv3AjuTh6DkQ4mz2rbmCRq1TComWrPOF8YgoOSFX/GrKNwAI1J/g5/T97VEBLByLXSjaafZU3+KERgeK6ZNke0/UE/sTum/1a8PLJPxlcB7kQXMxqx3yegd2IGy4u/x6IGesa4s/1QGUGevK4Hi7/EBPoB06yiEQ8LFg3JUfe2OdG67x5iN7Rb1Hb6DvMgWvvOwMVMzS7Isnu6FsxJw0+vfIcXn8pj0cJ9Hg8N5QLNmnvZmZ+wSrxd29ymOXaJRGLABldE+5wZB1vEGH2ssjYtnEwMxENISKQTr8BeqxTnbmxAAWg8APT8V/60tXvoA0DiJtT3+Ebo8HS3uUlX8hQ2Qq25vJjE1oPzV+w9U/VYO3oMwDMMxCMTqEGPCVbzZAYW/10vASz5cBf/6dcR+z7cZgqzTP3dZAt74VxTKhiRBYoQLjF11rLXJolCm4S2scHgyKa/AkpQeIF978134LpSet0RIR2bJ4XUWUx2sbVt7BuvoK6WQ/8luRPv4onD+SBw5andifGHiIkWPKSZD0++Z/pWOkSmQ7RGSZEgWJyFoPTP6W7+tWHRDBvi0YpoYPAbDh1u7tzrj0dkQEYBwgU9l244yKAdZ23z/fRkce9v0Mi5Lh70+fIpqDeREda9oVRz57i9UquS8jOuweDoXhcRJpYLypSxlcGLGdlDHzVX52NvzdfY7BncE8nMxcSzXW0i9TT7L79e4jXlr0oKZTbOWi8YyYNVLMzFTFHaAgamm4LcMnf6xANAIA+gJe8CjwzTIWGU2Tw8AdcIEz1UnPdFbe6hQJfvnMoBGwgYXol9hAAYI8QugCtYLDT8rGUhjNnbGa6NQ92/pKNI2+WLMeiRXuVbGT3fPnbMSsI47HJn+Wwy81ct0BlBn7B5Yfgnbrsrxipn1/jkWErItLP+sBuWqr1kh4b9Jciq//RvU+kvaWn2Q/Ff8+OgdS33trF8SAsCEADCu4/RLHwAaMyAEF48Xhi5AjxSzseXVVi4zIJ46R02u3VL8hAkPpYMG/TkXZeiGCRNkCdgZYcPdfh1IIJFbIPzf2Lis/uYblySQ8DOXEJBHDkBL0QCNsAShCBIBoTPs3KhRAFlzeol8e/r6KH1TYolmjLyJ37amF2LN3mQx1TWqwYxlo/UxlW1Cu4kRhhTpEgtCB8Hrxomjbf6dmHm8zAtd1Qqz8RNkX+uNQS/1scJ8gxCc9ilu3vIRNoDUJfOm6f3So8I+fPe3tKi60agzOkRMtpzddWanpZ9XNlzCJVFUoMJ8IzQROvMyE8EJ0NumY4pISvphejTOXZQl9G0oi5CgbUIqyZl8iN4HGRPfx7Uwyp8CxJc2ClotmJRxeTbMXpMNa5sRGH/DjoUqlu4yPpmU1dJ7ZswCLa4yEeXnS7JBt+RzMOmR9NONr6BDv0ajl6+u+0jhdeWyon5DKRAlGq5n4BgYfJrrF/TcIW3HPkv6LUY87SX+bSUDZ7b/uZ2elVIl4H4YjdHCFAt4B78KBq+VYMeYjW1x4Qt8AVmCb5/hD2xLVTdeg3FnJeAQrMVaSP/eqWkGovPdEaYDQP2dLhOwD9vD5RjBcm3vwKk2EXGrGEa9r1W21ZkLT8OGwIIFL2J3zd7XhAAwIQA0+6y42u6lDwCNGZAvSyxBoSHSwSD6ixHYXmUg1VW8ArKrzMTAZOMx4rEMKk8P+Rl9974vSqdWMhOqgx1kYM4dAgrHsnc//BCYPt2lDMy+idtQrLuUgBmHHuiFcTiDXMiFc3iAFEiFWL2U2APR0J1kEj1Arju+BqrHrBVbJMdDhPonB4m4Vu2M9IdFH8zW+NdB9chV4utPO9/DD4tTgVprbPrE8eQJ8F6yP2wlMWLjigmUBYG4w/GlgOM6tttIi7S4C+IMi6U4hzx5zGeFnD3cevbr0p/HEVCEMF/gRs3WSLVslkhOOsN38ncTJ0rVHmZymCWjVImSoHD1IpWGvaQ3Ad3QA5IcQK9aTjRxabqAMG2zNu5IDP+ocBwLLIoCYftspARj0KMHS/kSn8fx57L0TjZ2+yTzbTIp/0SwpF+vOg8uEoI6tESTMJkSzYNTiAzOYykbawwCml6wO+d0Tr8YG1M3itegw9l1qM+aYZ4oObL1wDhMQA+H26wHc7poMvHFHaLsjP+2PrPwS0BrU6LJ3j5HaiHH8jSfcS4s2sCePe2RaAomRHSylJXSGd60fDxY/zOUXisdd8JXrEW1kSGWJH48XZuzEnDD4ANIV4MyvgBL2iSEmH2e9YwuKy5rYgNJlmsH+46wie9bxTDqgaUKtnUTg4EYgZEYKM6ZcADmBrxZ6CYEgAkBoKd3xtP3L30AqGdAKBdRLtFugGhsOkZ07IQG16Zgzx7JZrRSBtaxSXX3sAAjSzDPFq7A/kx1RKnWCjZJdbRDBjDDeQivK7b33hPRmisZmL97L0bF75qITZU5O22DFGCeTgHKTojbpEkDwXbUS+T7k1VEkceSIDPp23Cs/iuRyHSxWekb/aHRJ46fQpugcWxmKysu44ZfVlGGZjlJzwCWLAkU3GOfXH5EO5tcxhR0Qhc4mumSDEAGIhvLp+V9tovrYmnT2/PW++W1xBdw4nlOsf8FaIpWAQvEJGjsF2ZUmamhRqHeyBAkxo4itK7a21his1ajIPRXkDZwccUAch9qoiKgnMEDFwQp8EjIeFRKd1w8CydOvAi214Ol4AcHsOqGnCiZ4RiZfaqQqHD2O9dX6d03eiZyVbYOqHlJsjYP/nQIg34tZCkbaww6DjQYjDJrpDJ3+PLVqPZ1zXgNOvQrVtdhw/hhGZahodhEn9TVb2KVn8Sfum0aySvfpf8SzY7IhVDrFEsx56EUUPZkm+bdHXDMACoXjapPlqPONHlc5axkJQNoFPkeGtrf5ikcErAZ6yMqxquzibMSMMkrVyHF5de90gDVnyw1nQFcs0Y6dbC9i/mYDwkc7IMx+BZ25WqdzW2m//XAktleFoHC1mzGiifSCUn3Xlb786bakRAAJgSAZp5Hd9u89AEgT15lQIjJ+LzDdZR+W1qGbUn1Fire/11grKxi9fRALc0XvZBnpZRPKYttApxN2Yxr16wHIDoGcOkPd+CbIdaKoG5dRC//A0z7O5OBOd1zIvKMl6UsauLNQWvoXqF0PLgMylnKpmyuGMhwQmIpb2dMSZTEHlA8Olf2SHw92gc9enjHZFbH0TOAvwa2wjthP4mvvmp7Et+tzGtjyqmJQ+ml9cfXNuYyy+pKE8wo4M196YM4y99vY6nICn32mfelPH1yyux/C1ciMojzXo56aIDltn5U2QJPTgSeXjReo8oAqfvH31ix1nJ1DH1CobDs6gMZkSLsJh6lzoHmZS/YPJmNmQr9dx+X2YiRO6RP67UWH6Hjg1G2xYHVDIenvjB+74BTbdIDvpNkdpS2OJFFS1rCqRqDji9C+6IvxordVQv4GxsiKsRr0KFfi1Hig3jWvxAiNpmediD6PR/h4LfL51e5xhgzgCOj7MFSFd9N2J7ozf+XDCCZqSQ3EKLLsU4Jz09O1BNdI76zlAHUF1kcg74K7WHLfFdKvAObn0vBcm8XccbnyFkJWPfZ3RdUDsVDt5oOAMuWhc3NqAsmYRK6iUPq7y//tsKM5vYqsFTlX35G552jKCj2PwNtbQti/Ro7dQLol83qB3Ub2afuWkIAmBAAWh2Ljdv/KwJANdBw4Hr0IAphCBRi0PtRBLXS7xfZGb6kVgYanSQQ2LE1Gj+V7FmapD/IkE+8gPTPNFtO0DtWsYBpn/bbKmmfdi1XRXR8fbOYrJ2xgKM+/hR+o6ScQQ38KXAt0/y7oEOkzJaVwi7sjrXB49/vvgvMny8Ti8SRsBErWBBH8QRJhWAzmypBWOkb/Vp0+YqJUZ3R8qm036PMzP3sRQT2TMcAMnBmNnY0+qEfpAsKAeZ/oiYCEIGDeANFcNDhOSyGvdiLEuKzH/w64sOoqaKsT/C0t+etTxZXTjym9KrY/1qEoAZkmZyNItZ8djhYM4jmBEnNPkqTWGk6oL461mAdJOs4PjKARr21Y2FSjoes45yBN1xilfTfDSu+DIP2ymzV9npfYkT0J7bA0SrGyUq/cFs9UFiYawCanJXAziW9NmHmmTctZamNQcfY0E7oBCl9VC5wH7aHySynt8+Np2vTy/F62f879LS5wKh96IGD0TZtWYYPUeYwZWmBKqkPYuM9Ke5txjbN0zk6+96oQ0gXjdR3T9nEyn9CC7TCT5YwgEaFhrtNOiLzH1LqJHznfmSvX8QrGS1X12cknTCrygJL2z4pEfT8IU4hD17DKVNjttFmlOS/YfhcHPot/I4VkNJCbFaJXM4ko3St2WWob5PfcXcvGzQAllK92EVLCACtB4C+IPSBVql07wFiSNAEhEIjUxv8+7/U/hUBoC7qy1XbyuPBSPngIiJSpEGjincsa7rxBusTyY4MdvLE3hU3MHRqhjjJp3D/zCgxK/YkMrEgcjBYLeG7H++8IzFhRmHg67XbIdPqmeLZU5IMgzHUxg7UZSa4DQNUZgHJrlTtNHILSyeKZKcT6kYAxbOpxOJNIMvf6xPHd/590TNSZlvKYSsOBJWzCXHzWomdOysdpTALrdEaMqjm6ncl6ggBb2L90uO2wztWGyuxUqgzAUMxGEMwVAiz0uXFKJht9uVUASAxNj7RdtcFWkcpHUnuiwQKZhtZgnHVVBDN71OlAoKDpTyE3lhaVpp8uXEaZ5FbfG118nB2DkZZCRrK0x+aDg4p8dD2E2P5Tv2OZa7Ma2djRjSHPoDZju/9uwhsI7MVVsp+Zvtf307HqaYZ/zkGxQwTX3Ohs8G/hiWc6guyUPVaIuNaiSkMP3wS2UPyxmvQYbxefdwoiMM4DBm4/ejzAfom/16IB6umYwCNLNw5oU1sRKE8iS/hzHOp7WiFhWvlXhidSPhbB0khv1qoEbXKkhOJXtrnuDzpaRsUOSi9pjtXPo5pm/LFK8nIKDujLOMY+OXBGTzwSYlUMfdNZQB5b/R3ngF8z1jvh4p+27AlSkr0sFnF8TqTjEqEcIQ7UQnwdA8ZBHKBxmCXY2uuXJJZTG/vhADQWgBIzQpSJKnLwRTECSZIALwu5lxWhxAL6PB0V/53vv/XBIDMLJFwQDusuZcqIPkhKSbbuPYzLFkVZNk2zKEslasifLdJ7NymNc9R5s0AlyQBM7deZQBpLzRvXTokC7vj4LeZNi0wbZqjFuC1IrWR+eBqsfu0uC203jpgGqahk/iMjMMf8YHt8JwounWT2TfVriALsuAaLiOrMB7Xm7cZET2LNNJ/ED6OHC52S/bdtqAQWwA4fTqEtp5qlK6pA0kYSYdbWIqGNs9OMojVYMjvdYYcrdqmorP4nTPBbDP9z230bAH/pgcns8Z7UQwlhA68vXHyUo4U/JQEG2qDMSN48KAs2euNXqTEzultN0qI/bL8HoRQG6YxrixgHsMoIcJrIKlG+orGghmdBA/6vZv6+jh0PC6ZpnNqzsUCv+bCnZDt/ysDyEB65msj0fqEBMCv7LAUU641sMRU14MOvl/fXW6EXAd/E/trXe0KflqfJV6DDuPzpmeOcuIcziGX2GQemlGBzmFzPZgzBvHMRCvf2WR4hCdIJn77TwXjeuDKxRUXoA/uRSEcAcLfm89vKey2RKZT7xjHM+KRdW/kEmnOo/e4YMvQHHfvtw5p4L2n0RB9kz+cWQ65b0vZJZaEV60LQLVq7vYkbNmFBaFqv6dogbceSrbWe0VPYsF+6bbDZrUErDO+9bO4hXRiYX4BOUQGPy6N9pwHDjxCunQ0MAP/T5sJ4rLnf9dv7UJkns+bZqAEehH1usGwOcXkmGwlCECmLf4b7V8RAOqivtRl+uqi3YS9SpZTqNE1j+USsD4gqtLpUyTBK3gqsBfeSmToGECWkIu986qwTePLnwGxlNnYZ0sPcJ7kKoxXzh2ymYVzbaIzx4zsWWLLmGXUmzJ3ZyYwL07bvuKT15KcAAAgAElEQVTEy+sxWoWZecT1QXdm3pFoc0pO3t+/tQxLo+vbgojXXweOH7fvcRckHjEaPkiECMzHezYrpGCcx0WRgJeNpBfFimuExfgNjURJlmxiby3U9PvLYzBblhyPwexZySTHbAxYfkdQPAk/bDyebkZv/IyAbjKEje2Bb2qkiL6P20lzIP1T++BuNXvg7J4YNQiZxSyPbfJ8EWlzVjGWD/V7N8x/GAZFyhJXHazAxqA6tuD9/xMDeLX/d/DrF6uIPH8+Ihu/6xUGkG4LkyYBf0TWRE2sEdeV1u8+WnRLGSfWu6d3Qn+u0uMmbkLauRmxpfxMD+aMZfwtYcVRHPsQCT8kD4xAaJicyv6pYNyVRZli31/wyYmcMefEOZhdLA4bJiEUDKbo5pO7X0Nk2CGVr1ny7PllRsvjsrv+1/uQmpjEaBNuQtywwvUSTzz658wi8+6u0apTX9itRG3UhlyAp8Ed3APNw2Sz+n4YF2xqP4S/0ArzOQIQKAzJrIQvzq6GMV9CAOjpnVXfc5Sgf4L07nmxcWYjTSeWF2R2t//q7f4VAaCO1yOwussFO4C6WYb1eGtMFcsrTT1DpDJn/C+9IPWSn9XSqZogiF+jPdLmR4VRGIeEu0cShDo8LLphfEz69PC5fRuXfbIje8xFvPYakP3qdqx5Uk78Zjy6ixIFP6f9Ggc4o7wIA1ge4xAKiWPqzeygbnya9bLLO9fG4dsYmUWiBMYi/2YieLp6VZqeP3tm/7Uqy9xDKqTBPeglFpaPt0NeF9u36CVkb9j077w9Z+5HkVHUMcJSZkDiB7dwP0UO7F10QWCtVsvxXpRTGGyqRu1HssApkkwMztGjjr3C+6ZnXlP73MfdGKmxtx5VbKbv/Ntq9sDZaDJggKNMhC6anRRP8AxJxc+4IKA+pGp6ADjOrw96REmrvfLYggNJytvul9UJztk5uvtMD5omFpqKrodlhnddi1kY96C11xhAVgOmH6uATOdkKqdhnXAsW5lI/Dsuz467a9HHjSR4iqeQotx/oarI6OnPhp4BNNqmzd6SC2kfncOTwDR4t+od20Lqn7wXzizKyCTPh5N4hGQokvMRzp83F4Ty/WI5klUZZtvoeOJbt7btpXqv5n38/ndKMT54C+Mw3gcd0qBZjGM6PsSHkHjKwjiA4m0LY8YM908pz1m5KXHLXSiFkthtW7Aqu0pCaKhyYGUh6ko0XvcKNwaZVt8puX1CAGglhL4BoBZdslx0NtHDrFnJJd1/o/0rAkC97MNBf3yucQj+TgYiY4vMQb+DLS2XfRhInTolb7IKnHTBZWLDKHJsdUBWEwQDBzJ+N8PuXTxtQjiOnkokRKZVExIDVSJs6bkdKI2y2CG+rp3vPFaekDIyNBN/F7EuH0xjN7DbTMl9xSAKfvBFDJh9K41dDk+w1UBW/Vif8Pok+x5jHss67681fkCPg+1tmTNjAHgdGZERN4X/LLF/H8Gu19YEC7EYUvKGTS8d5cIZe1nNpKWTq1eVWUTeQwb0F32DkS3qovAx5nmxKVkVhZNU+1Gf07T9JjIgTDhGykbjeD47+/6PvSuBs7Fs39csjBnKErIbKlsIyZJEoaRIFMq+ZSmyJELIVtZsUZYSURSFFkuJ7FmyC9n3fV9mzPL/Xc9znvfc53Vm5szMOUfz/ef+/fq+cd7ted73eZ/3fu77uq+LquEOK4uN2AhNTTQVra2PEf+d2PHjri/Vq2sqGBrb+uf9L6HCBa2mkTP4HE5HZVV/86PG6xmTEZMleVrhueMaY/pR451YfelRv6WAJQbw6ngnFrE9JmFacPtkYQAji5fGff9uRUxwGty5Hpks6EZc40j+Lp3ZAMRY0ddtoeVRPf16lQo1JiOAdvza2egsyIJLYLS+WPB+ayHljfESVz/cSZRJqinqVzMl7EkaWmZluMjhvDzzxDPIuGWFHotP3sLytekUdVI/zQ2dbDPjmRkaZhy48GTk3lVmbRm2Z6uuIoPxOW32RZXhXL2ALIqP1Bjn8B80wsBjs5/bHEg6rFZwxXnLk5LpoSpWYFu6Cth5p/BdmYi7G5DqACbGASRYhlT9p+J4kuQWYUGI1nP6/2EpwgG0A7/3D5uP4v01GXTUgMHIM6lPooDfjPaQ5JcmaQTorFXBny5PPrETspkYn3tOA+x/DayFmjEaC0fQ9SXoSJGRcVMYseHHgbwaBL4hV11UOKlnnAxwVq+aCAOjU2vXAlQZmCTo9Dh5szqa5o1+mJsgubeqn52NcRd0boWKLIvyd1LpcuLhiJuTkTJWIqfHTSVrVwI7lU7n19AqDZTQMmou/DejZs9AfzjYZxNVSW4Uh9EHQ1RtCicY6Sj4wFXFp2cA+3TqbtxwfeEZce2ECdiLQngaf+IsNI0MLV8+TaNhTBLqSg6x5Kaxzfn5zIlRpCPLopZvop1qGvkCjuFYrOZBI5aRY8OYjJi0WfoaXo1lrRtA1ZLTwXn9VgQiF3AflZ6Dnlu0Pvbq+p9gWESXJGMAeX+33iqk4A6XkAm5Qy8lGbrh+vTj/hfnIlMxzmKgnYf1OHen1iPTuS4kxtlicPJ8GgTGxuDYg2VRNnajNU6TulDzpP2yop8LttOnXdOnhTKcxP7rOT0qRJGE94ykd+oEzD9d0Vq8FswfjUNHApNcfOauP3ZYh5lDu+ATi7eP0nDf4I0EI8D2KB3HDwuqTCWxuX5SqrJr1HBdiJlzDUJf9IUmyqYU4FKRbCSl0M94EekQoXDE7fEZpqJtAo811QFMjAMY7YjuuZYgOm8xZ/iTClbz/8dShANop34ofOtv/I0y6inNCGqJ5tE63u+pw1C7Nqy004M4jdPIqY53V56fWEyOwQAyEkBHU0a3iH07HRKuopWGiLh4cWDHF05y64nogK5pJ6rtJUvEYvPOtAiO1ZQ3Rk2DRLLEALbQRZ3KMuIyLiOz+nsJnkNNLHEZxYl1ZM3Bkk6l8oUfMfncK2pTT3yMueE91ceQDmCpUgQl66MCEY1oaN1Zo4tLKpjl0MjsYXgPveDMVRrnTNLXyPR4Ul9HRiVIu0PbBI25uoNgRUcjjWItLPYwVhAHrCpee3vpZBF4fvy4c//R6GpRgLA4xnDDeetjTryTiTjyvnx+qyka3XGqafyLR1RjypQBNov6FpcIYEBNPBerx0QmXMLtkEwqOkpL7BhP7POQC7gTExcgqL6mo8HQoYjq8X6SMIA8nIuP/bd04RPhG4XDjvtc3cTuhDCizKp2Ktg8EnjQhURcRr/kexR98Qr2nc2kbsFS1ED7AktVNbqvSbllBJBzCCtLW69tjaLr9Pxp2AcSGwFkQRtpZaj4UxpbFcZt5OAIxePp6ZzsyZji3MpFHRV8pLlbXCY0piVOjzjaKGjogNTx5r+TUpXNqCFT4naTXINcNH6lCEmIBIzBQRRUmRJjxE43wFyXTMndZ0x1ABPjAJLfn6EYx7R31+1k5I8p4lQH0JO30Y/72Mlfg29dxVUNfsWqwKdRJXZloshfc+Rwgv7J+7cHWiaM1CUtMd2lZ55MhvZbwSpgYshoEp9SKnA7tsWw4NxJz8LozpqeC3VOlwDV9AMxOuwDnDun0yrz1uZA2otncDwgL/LG6rATJ2/ivd5913llyTNlyJRluxKaEON6nDJy0SDTUsy5rCGym1/qhxc3fmilgAsUgMIP0ShDdwXODxxB+oXxD/5RBffkW9KcY8aYdmE6jGkY0jnQyPlIJzox2Bt7H379VeMw1TgRqipUHjEOKrcNHaqxesak3jR/48edknxxmazo5IKC0UKqofzlmoWP8/iENtSpA4uWiPt+jjeV5BWtdOA2bI3RVCSULty40Xk2iTtbn+YplL+jsXLvdYnEV7PTWFGnpC4OEmq32S6dpg/KL8XADXoMbXyhHwYGfZgoDKBUAiGGKyBzJgTfuIKbeQshzYG9eOYZXd3pqz7Zq8s5NljR6a7IixHCf//VY9i0m47egxFHrCKohSGv4dZXcxWFEnHDvmq3eu9mam5TKQcn+SufT/sHlkZW9cjpoTMmmRlIfVKueVEE7vsHN4LvR4aoK4lmZvBkPDVvrp0yGqPhVO0h76aJpg1GH3yAwQnyKUpnmCwFJsJPovo6AT+p7wktKfN/XFXAdfGDKnCjSeUY4p7X4Km7uk9HmgpVx5AX21X5SElFj0XT2YtUBzAxDqBOvidsrBb+/2IpIgJon/Q5SVao+yAyR57F5bBcqPXYCZUi83TyJL+cIfqVbPgsRugb9olLMQPBxC0TOSKMxjAHEWV/jFKBvfiB25kuWFr/c4A08ILuhR99pvNWni+GYthjkTvToSF9B1PH/BgZk5QUjDq+AbExiRMZzy1TwMUursb3ZyqrS5LoeWL4CCsCKNOouXEcx6FT2vPxCupjPkh1YZx2WSghU/Br8KQlfcdjkxs9kB9rRlpqQAPkJO2Gmox7ayfQGJn67QsB9ukkcrvMC3R6Dx+KwXlkVQ6swRfy2bmLACR1UmG6n9XvxmRBTTlssPCHhDVwXBunWSoSrLtdShFw30YIQnFb7UM8IavDEyt1ldh+SAzgtgl/4o9oLYk1HD3QJ3h4ojCA9rkgKDQNAqOjcO2R0ki3a4tKa/vSkZJONfvAgitCHIgjzpv5horcSziBGcOSQLpZ6R346m/ttC/K3hp1zk6NU885sfc6vv3tEcCqVYH6B4ejwaae6jCDzfXE6ZHcrFyo8h0q/3oBBB45jEtpsyNL5BmfOIBGUUX2k6T0JiPEBXc7TE6QgF2mw8um34PfT+kgwFdohv75v1LvkSS4T8xzsJNMm2P5rm5ABfVPZnrewkT1tyTNZ2SwClbeNf9wv35pP8agSP2stKU6gIlxABPzDP+/7JviHEAS8S5aBNBZeBKa+4nVeLcQ5rEDSACx4XEjJYZhfSfx8tCgfi7gW05uvJ6nZqdb6K/WcFpEtiZ+xRIVZHa13Q0GoOhcvU+/Mj9h0BZNikyTRSR2/jx5loSkhpKSyuD55Qf3t+FbEPLk4+qy2yp1QOHfJoIFCpJPi9tkVJUTagtoclji76hQ8g8KKyJjGjFsR2K1xJ1xFk2/kptCNZEncmZNPFEHdRQNKED6jnPIblX/vvqqVmcxZlJZ8v42wBx8B826bbBH/Hv1pB2o1EF/zBcG1sWzV35Q5/Wm2WklZNSmClbgT0VeoE06zVKRwIDcDRG3rHSXkmXebLc5l8QAdqm0EaNX64KZ7VU6oc994xKFAZTZgPtCInHltoZsM8L7fOgqCwOY3LET132wO4BMGVbABrU7oQ+xoNaA09gOkrVzDKqChSHA5vFrMe90JbUT4QMfhI1WY4qqOsld9MT3/NxFACUHZ+c0kzD+TnuPIoCyCMSkgE8iJ3LiNE4E5cOMQUe8SgFj+kX2A95TaZKOh3QuL+KXBMmbpTP8TNo1WB6pI3B8Hn3SjbbUdTxxht3dc3fSkrKdi/G8g3YmFv/iYZVhICVQdpzFNdyHmWiKRnBIPDkuQN7Ph3DAWlynOoDJJ9LxxXyXks6ZIhxAe9qFN5iOhUkjkpGfOosENtvB/O4eBqNnlFGjSfwIU39Gs9Ycx4lb4r0Serh2jBCLAkZB52pfw1x8j9fuOsWXIe3QIkJLKFEWjatZpndJP/Di5Jfxwh2tXZsTJy28ov0kj2MTNjmk4j5FR7yNT112kaoECfVBbpf3/rGQf7A1QqdxmS7vGDrd4pKTxzyBv/AXtA7oBLyliilodPwo1URHMKODt1RW0MpVMfdP7sdQUlUsztgQT5/WVdRv1jiEkd+HKyodphGJqyMgXlssruJ+S0rP/MpoVU9oCTNpJK6eiLfUT3zWdf7oBkZWvGn2MRXfokKm+qUiAWXjyEN5COGKl1JWbXuDqia+/koM4NGfdyBtWe0wn3yxLR6YNzlRlbvyXuRMdwknb+uiKn5Q64cttqL3yR07cfVH4iq5z+ZM1VDmMtnFgKzpruPCbU3JY4ztoDE1nTMnQDznhxUXo0yfF9TvB5v2w/E2H6JKFb2d+NLkwB7iew7uIoCVzi9A5+Uak2m4Rj1xeiQ1F8fZkSMAKZ8y4zIOBBfC+ul7E03N5ck7Q2eaGRaaWcQQQ3cTYaqAwhTjUHFprpM04a5Ty+f4atqF+C5SQ3D6YhA+CetrjaOkQmd4Lsp1urYhFleQUfGRGrhLSWzDNpRS1ya9k8lS8N+c00tiO1riS0u9iBrrI2Fki1IjgKkRQE/emrj3SREOoP0DyO5I7UZiKxY4RFw4wW7aFP9NadLEyaEn8V5NMBOz0MTlYBbnyorPhG633VmlgscUaOqU1piKL9D6rlOw+MREp4yTx4gAJdyW5G6FGg76Djq6+9IUV79L8mKesErgKqyIeVqdm2nnHhjpcp2kfuRl9OahtMewP0JH60hL0zJsrnIADV6GmCeCwVnRZgohPkIv9MZH6hhZ7WvSsNTdXIQ6avvoTAPR/fIH6m9vYAB5HkNW+0v2FnjhrI5Ebp29G/2+KaqwZ4zISPwfCyRMpTaLU5h+p5nCGlZ3s9jFVBcvvb8+alydr/ah49tt9hMqPe9NoyNLtQVGiGiSUodj/+fguuoZcD9ZtUi5QEYi+KG8FuusVq3x4A4l8UfllmvXdEFRfFJ4ye2Li3xayH7siNAqC8SCtgudaS0iPHHapDN5aNVxhBbSUIP9Jesh97p5ShuWRQJcCCaF+DyhvtrxXfLdNZFlnoNOHKvFyYFHJ4CE4OThGztWp1pNNPnD+0ZgwcPvKmlBaprT+fKVyQggC4CIn5P4s/FBXRRXpCfZAvlMWVSnUsDPhiHg1i0cur8kCl7VVVWePNPE9JcKPabYjMcZyiYjg2nkETkXGUyyu/PLSO6ggl+i78FWur2vTcSomx2s4jFPYUXurmFfLHAfo+LDYrQw3EQfDLEyRG9hgrWYlOcjNZYp9FqBKhZjQmoEMDUCmJh3x92+KcIBdIepYLm/cdbexQgrysZO8qMWVxrOThAs9XZfxE+WJq25WfxIMsXhqUmHiR9lRv3moqE6vDtGYjS633UqKSOWFpEWtxh3/CT4XXSJGqWOeRorsQraybMbq0+X4Tn1M+kG+mGQyy5JTfO5UPBsuYCQ3Jpz7kKFF5FhxU8qekNniH1lBIP8W1LBRIKdv0ZjSy6LRSH7UFhJ3BkHuS0mW9QH3qgCZjuNQz4jQwc0va6BdIyyXi5QBoyKEoPJaxmrkmkbVlzWK3JiAetgoeIFI69hLgeDVJ48Op0XfOcmzgdkQ1jsTdzJlA3pLp/C738EeT0CyLawqIjFRbQBWcai/0XNg9kjz2yMPO70OKWjz9Q21WZkVfZaVMQzaddaVeg8R1IXB24HopsfZdr2oZDj2H9bO23f4VW0CPvOWkR4kraV71eJtHuxLaKIOtcMNEX70Bk+p4Gx67xSAu516HQCq8cPQfN2qmfTQzvX0llioU7l/V9g9BW9EKTcoxn/3naW7I/CHQ9gIezFXuh7aIqzPIkAynmBGZLgoFjt9cbGIvaJcsh5dINPHHEuyN1lZOTikkVoNwLvV2M8rmiqcQDpQL4TNdKKqhHqsTJ7A6VDntyqbHf3W2qG07Gbj3oWab87nLF5hozcs0qYWNOMuOIoYkuNAKZGAD2dhd3vlyIcQHcRQJk6JMFmG0yzesiCWhIxuzNiCE0khdvjUqEwx1LdglVznpodAyijYSQsNTxQ8nxGiYQYGlJaSJMyaa9gPg6XegWFCt2d3qiNhVioVA5dK8zMuZK6kpX3vt4LtzDv1zB1yuOFnkGHQsutCk7ZZkZSZ6KZ+kmm1Un/8h5GqN9JC7MCz7hEctmHn1DbOpU3Poim/ccbdkfuOaPVuac0X42CTSspR42VuqzENiYjkky1EpD9rEM5UkZ4uL90dH/M2gYkyvaW6oF9vEnHg47yZLRTu7TCNMxK28py6Iwzx3FIx5bjVxbgsBjGSKeZayR1ceDpOyFxpMu+OY90ebOpQw8WexG5Nv+knHBPCzdkhL1iyBasjdCY1Eloj3fDJvmcBob39yMd0NZjKaAt2sRqFQpDo8K/yTSgaGr268gsi6QeeEA7L4HjxiCwu5bD29l7NqpNfV2pzvgqamna6k6ijIoU56Gfh8HPJSYCyOgydXlrVY9Ehy4aj7kzS2WUvPRnosn5PRlPpM2yK/PwOAkJehQ7sRuPxosJl0U5U7K+jzbntUBYm/DfMO1wNa8U5cgIIJ8/q5Z7XuuDPtAVZ10x2uIvlAIA7u6DXGhQ7WQ7HkstAvGCmJ4nY+5/eZ8U4QC6wwCG4iauI4NSviDHG3VnjTEqxVSk3TjJchKWRixbc4f8c1HstqhKuI+iaBGC4Z4OBDm5yAo1fqQ6YpKqvmQal8boTARCEIxolR4oC0HkBqBj0Of4NFpXCMeVQuY2rlznQBPscmIZA4feKoBs2XRkLinYIlnB+emEWNyJ1iB3TliVg9dbFZz8jR89YukkLk7yXZEA2rSL2MvZaAziFXlPaEyhGhwj/+1JRCihZ2J4GftG9EXrU5qE1XD1MU3E1Co/ygYDKLm6CJAnBqcrxrgcZ64pxw6LiYr3qKUiPr4wmXpsETQTX0ZrB5vt/TJdRwu0brCeMsVFWIGpYLYX2vAcSV0ceNpPyYEXcPMGdh/VVTLEPLUN/82qJPekHS5FSQNWI6S6rkrfXLU7Hv11pFWU5Mm5PG2/3K9dO2DyZCf+TC4gq4Wtw/KbusrTKPVIDCCdJRaVTcgxCPmmaHmMgeUWYcDGl3ziLNn7506ijPPPHaRxURAityehHfGZy7zwKRAa5azyXxZQAz93XuoTTWa+X1TasJskWTbFdoSRGLYHub9cpHOfYZedtEqcr/ekLaUwssktyrEXDLFK/+WoeZh5S6sgkeYlBNSn0Lyqw+GmY46Gy0BAQ3zryCqlRgBTI4BJmcWcx6QIB9D+Ipnmm6IC6uzeh2sWtxtTdART281Ig8nfJYbHcLhxOydrOmlJcZoM7oznobzPEYSrS9rl3PibrAwjB1Vt/OTS7Pr43iocIfZrXMh7Clw9zRnwVPs3x3RMh+aroQP2GbTeKo1pwHqafirRJlNuXOnPX5oeaSJv4kKu4mhRZodVwckT0/EmGJxAZTOZsf3zoUkRZTrcgJnnoR7qQSuf5MExnIBWtaB56yNOHFyaEUMwBH3VeS9OX4h5kbXBKlmmcumwE5tFTNSH6Gelz/khyYHT1n2VKXxyCVImjvQv1wLuw/Olz+H0pRCfRQBl9OaNNN9h1h1dkcw2TUzX3XIATfRGRgxlmm9VgWboEPaVFUXhh450F0kZ554OJrmAy5k9GifPapLw0w9VQqnrqy0uSU8cfklLVPbCEsw4q6vq+dy+zP+hpUzjrbFj7+NTT7kuCtdX64Pyv+uITp/yv2HoBk12Xr48sGGDs2KVGEAWFDDa2uGwMxLeKMcK1B5ZxScFE/a2xyVRxspwwhwk3yVhHVw4xmUyM0Cntt5TZ9Gyl1bL2fBgbVQ4owvXvBHFl22Ii2KFqfTPoRfKEkpCJ85w55nzyLYTS72zcH1k/VPjK+qWOYoFWzREIblFOe6+W5IiS/brEeyzcH7u7jmzP2YeJWxpELiASHUAUx1AT2dh9/ulaAeQDtVr0PwdpB4xWBY6KgT4S5Pyb/J3SbNCTro7SKs2k7CVHGmJNa4uCUQ3hSPpcR3XoXXn7FVe/I3h/K2gDDUwBW0sgl9zXamgMSKwJ74s/DH27HGSoJr9qKs6CR3VP2XUjY4fHcCk2l1Yn5zZNENzwYKI2ntAqTiQtJrOk7GB+ECRsdKewxILm1gJq7EaOmJDLjtG1iSdj7z/6n79pvVtk2MmAtg5ajS6Htf4S0Pp4i4CyErkDtBYQVbhxSIAW6DTjJLSRpLPxjRoiA1dvlURY29/8EzfJZ6IWFWTKmfVonFsua/Bb5lCJ0a881/YjM0oq05lKsRNBWXlysCfruqHybndbo+VThvTnPuPplVqLIx418+/OVFOm3Qmm6afjxk39OJi/SvDUHfte4lyJpPSUbsD+D6GYij6qFPVD16A+VG6oKlECWDHDj0eaKwCZuqYfI49jzjH2Is5t+CpTqV9Qpli75/UlOY24unoIG28pqvzTQEFt7GAhYu5uOyueeHkUb0CBBDz6mvItWquTzCApm32Bf4L+MXCb0sMdIUKWkZRmknNmoKSTfdVRZmrK9Uua5beQL0mYQrXzKIdvndJNXvmihkSzjmz1hdUlfjGiAEvB8Hg7uaCkuZrFt5AE8xKdQBTU8BJHZrWcSnCAXRXTcUekLZgMHTVaCN8Y6VA3RVu2NUUzB0gbUBx7FLg2gxwCsJ6kgZxd/fvxivGqhQvP3jkl6McmTRGmX6Flqug49QfA122S5oAdw6i2ZlpX1Ng4kwRJB/gb6/2m7sxHOlOH8G1DDnwfIlTd02ubI9Mi5Foez0qqmZSCs+A5E001CgpnMcDyIbzLn1PDgWDOZFp/8Eek1BghHaQ17f7ErcbtQCdHzsGUC4qGL09i+wKasAUPUl/H8N2dY6paI3W0BJa0d/Nw83n6ynMnSdRrKS8tTICKHGlRvnAnNNEACVfWptHVmLKfs1NY5fhY2SK75cvTaaAuajadvh+RYWxC8XwUviuJKWACd5vFOXEmrKC8vvsb3kFvB/fvTCV1ZwfmCF4K3osxkIX5BgdWv5N+ihWIRMDSJOqGV9GNkbWpZrM7s1n9mPKHw/7hDTZ3g/pvBoVDe6zGpVQCVpE2izCuJ2Lp7jMnhloWHofmgwqrHZfnrspqp+c4bO0NqOrdpUdMiRQKYMmFZ34ThrNb9MXs5giwTr5P38/p8m8mUkKwy2lE89CQk+KYeIbK3FlrmThIY8njvdL6CrkuIzP5RZCVap+A8o5uCdTI4CpEcDkzdwpwgF0h11ht6XzNB5vozPGq7tBtnip7MDfGM53cr3pm0Ys3qE7Ti3RvHAKvJIseizLQ3wAACAASURBVPfuxN9cd3hFVpDmwBkcQT4XvUeeXRKx2lO33J4XR3EUemXNqskGcJBg2ZrGalsTCaqDBfg5sI6KyiVFzFyeWvJ9MVW64pxWJjHRAqaJGAHkB4P/RUW5OkeGo5HnJJH1beiKGn50KmOV4u+iMsVOPKomYWlJ5S501/5bk6YjXQeHpMvEiQBnf0fFuKwC/gNVURU6GmAIxg0xNEXaWYEXibQ4jRw6/YsMeCLfWTRvH+rTKI58ByphDVY7pKNGoRt6BIyyqHjM85aKCfXS/qRS3jRGDEek7WsVjfTq5VrUkPgRn/AR8p2gjOGBa9mR4dY5XMhYAMVCDlqUOp44zwMGANTY5VhrG/OZBXVoE/QlpkW3QJEiya/ejK9HjHzR+WPVO4s8Xr81DdPQRh3SNf1kjLnR1jrcVAHbVTO+ulwHWVZrUvKmNU7j62UP+sUBlPRXso/uaKi4ne9yXNAAOwawaNR2R2ECMDWgLXZ2nuwTDCDbxTmHSQhpUn7ydzyL6vhdbWbRH7Hf0mRAgdmiOatyIf3VU7gYlhsvljyO9ev13sldgEoHkFhj0hNx3GTANfyKF5TqEbMKrfCFC/NDXOPPItpGLuTBidQIYGoEMOHJN4E9UoQDGBd2hS/9RWRBEGKwDSWV1BXNHa2F1P+V9+QmQpUDIqM73M6XlVQAiTV3Fct0bh7FbuUsMPIhTTpuks/Q7CMrOH9DdXQrsUy17aRrsbCifjEVxkxP/oYaXpnEJOM/7+vusLIocmMzYoKCsW7lHSW5xApOaZLqID8OWw4s92Gk7wFcVHijMtiCy8isDqWe7nNY5nIebzgnpv37Bs3BIx/oIhnpFTM9xNQtP+qMTplndTsoDKHROiLM4p320FxAVfGH4u/6BVqthemY0WVmYcsWrdHM5+ILPJ106HjfNjvS0nbybHPPpMP4esC3mB2rqWK64BOMD+xipeyTu0Dw5P0wH0JGxViMdDAmP/LjKPhByxd0UhUPnTiRcMqfjhTfSWIWaSNyjMK7pzXJet9CczFkn5Nk3RNn0pO2u9tHqjww2v4tnPeW0UAuKFipz/eUEcBVq5wpYFJKfXH4GYvLrWj+m2jWzreLB9OHZcsA8ljajSwKraCVUuWCrWJFLUfpzuwYwOZF/8KrIzT5+6LwTqhzeJz62xeQCHcOIK/FRSnn1314RKW0aaRCMsTRph/SMQtNF4tLt9OpYgx+QyqGbrMKYJILQYkrc6XbEavmkZtwJQ6Pb0wy8sdUcQwCEIIIBIXcQkSEEgfm/zjeiqSO6pR5XGoEMHnPLUU4gKSJ4MvozlgBzLQqXwrK6FxAVsXv1t1Gt0cMDictaTIitRJPW5EfAoPt0UJPb7MdA8jj4sIZchsjl0a1ozzWWwoa5npkuWeVHp3c+LAiUnP4KayyxMWTOwFLNQ3i8RZeeRoB/KIR63M7Ei+/mgbUnGVkhB8MOlSkk3gBi9U+WXDBIlbmv412KjVpy+EvK2og8XWm795ITxoMYOtsC9F3o6bJ2dZgMC516INKlTS/HrFajCgQJ0o93+w4h8PIjwLQpeTEVJoUDavximKPVTlOKhhDv+NLB1CmdKlduvGG1i79Ei2sjzf/be6ZTBmzenwqdGSKvIsmYsV/e0L54enYj2s/+cGlo731tsacUTkia8BFK3qZ0AdXnofVm50uD8RA9FeXZRX2b2lqWdX1yR33CfW5USNgzhxA0gb1xWD827CPSqkbaAHbQafXFIGwOGfeET1nUfrr4Xx3MGRogF+KQPguML1pr/CV9Exc4KyEU8omLhqsuzCA61YBT2uO0pjuPZDr6+E+wwBywWbH9fG6Bs6j9a5ZxhwApuypqiTNJTKX7jrO3dYYbXIJvhS63GsOoDsewITGVXzbZcEc4SnHkMnh+6U6gMm5r/+fj00RDmDdusCCBe4fEyW6jOqFwVK4A++6iyLmwCmcQi514h9QV1WjeionF9+gMR8Hs8+PeBkvQ1fF8ZpnkMM6/HvUR33oCjSme49DV6BJu4AsKt1ItvtCcICKbPu40KkEbMKm2McVGTZB3smNSJmqZmKIFkbWROa/lqirP/fEJSzbmAlt2gBTpwI1awKLF2tdVqY3aGkQiSiksVr7K2qiJvTxdKxM5fIA9MeHGKB+N+z+zz6rtYiTayRQnlj/NysqanBzTOHxY8iUYv/+/Fw4nW1JLSS1jUmkTGoY4kUZcXgQZxBB7FCY5tzzleNBB4JpN8IWct9xYim/QSO8gW+sW8RnRP9cfny64hOMRje1DyNW3wc2tCKAycU5efJs7JGQv1FKResN5sqcI6GUm9Q2Zgp4aExPS56vevAK/B6lNZG9pSITX99MCnR2m+V4faquVIp+730EDdMVwcSQGUwo4SdcgNKomjFnayGEHtuPqPsyoV7VS5bWuK/GjuwHo2GUU5MmlWVk1T73iUtRw44BbJN/GV7+VIcXv32kL974d5DPMIDE9PEZ2+1n1EIt/Kp+NowO7saUHI+FQo5gb4RmaSDEplm676ziv4TGY0Jj3x3vYkLHxLd9LDpbMCcquKxD8VQHMDk3NPVYpAgH0C6/JJ9bOWzABmjuLSPX5a5834C35bGysoqqDwT1J1cWi6tsprQkRkWmWHjNPdDRGxodiorQoBN7FazZxxRKnEU2pefqztj+lpiuNplreKvC03zsiGP5/LyTtiUXTiA6ey4VcW2maemU87Yp6jFVLKFX4q6l1PJeTEZbq+pZVi6b/iWVh9F+f+gAjq7vipt7F6OU00YH0CwYGK1kBJlGR9V8TJiuOYxwlbaUZngd5W++Sj1K/BY/bqeRU112Y+6X0TDtj5bsFR1E9ont4DOhE9IvYBC6X9G8c6wg3pX/RcWPxlSqPyKAdgzvOlRwgNi1020EnRKSXbSrcMjoecXgjVgfpSudk1v57vYFs/1oHKDtU/9CiTY69bn3+U441WucS3ERnTqOY0kEHZzXAUjOlw9RB46oSnpfytfZ+8N3VBZ4cOFsosLt8JlFMm6Oc0esb8cA1oxySjp+EDgY1zr18RkGkO1iUQ0jq9JkBT+/CxtRDr/8ArygZZctk4sjSSb+Gdqhe9hnFpl4chdH9nHPBTnfYzqwFCpIiGvR/twkvRaZDBakrYnIyNQUsCfva+o+7u9AinAAmW5gtEZSjTi7E4tDKKCKK5gGLhP6D7bdKnRXJMbIYsnbIGlJCKanU5BcWSx3GMAReFedm1YZf1pUKPw3U410LOJz7kwRQiTSIGuGCNy8FWBN4Kaaj5GgRpijrlEAB3EYBRQ+T6oWJPUlkKv9X7I2Rc1zX6tTbf52Pz6c9bAVweBv1GKeu1nTHJBfjOlUaRKrSLwdK7BpRhlE7su0J1fhyTGTAn457xaMWaXpXPZX74ATfSZaKeCNG3XKn/J0/6Co2sfIYplryxS7+c3JyO9soa+iONL5kYB3s+iR92jJEl3AxKId2signugerRmqq2AF/kpXxYpyJPcj58mzkfhF7i8LbdLhloqgGotPxlEu4ujETI5yLnokiXtyF3Ge9MmMq3Lpd2HOLkZiAKNIZOiF7BhAQwT9w7L0CLp9EzcLPIpGxXcqyioWB/hq7Nj7YxY+5ncWjRktdTIrGFobeZw9FWzHAL794Hd4fpoOLU4rOhJt9mgMjq/65K7ClmTKH+N9dV3qLc+DJlw2xTimPyYyx8XRSyHLMOucjlxSqenzvEOUg+aNxZEc9yarIe+poWLyZLxxn9cxW5Hn0zTZP+UEUx1AT+9f6n5334EU4QCy2RJ4be+GXBlxFUceNymsLmWxeCxTovxNyqeZiS+5slhmZUzyUUM/ILnCWmb+EdMvaSwaox+3kU5RxGzFYyiNrW7HqNS5NJWp9h3dpZm99SGUeJ+TtdshcOpkfflt2xBVrKQqfmBEadAgTVD91+FsitJFEsua9kqVENkH47TK3+jIuAOtJ+ZFNh+qv7/Zg1KvOyKvzZsD03W01BSB0JGuELPGwk6SyqYbPrEuRQLXPSiK+3Bd/SapJsxOPAdX9aT/8LbJDx4jxcZpkthVc01GGZiO5//TPg/qiDejtdoKdZD3hpWxohzJTXN50s+mTV0d+bWZXkDFyxoj+mTRS1i3x5nPI11TXHAP+UHlmFuSsQFK7ddV8SXuP4KdV/Opv7218Emob5yT5oxwEr3fqt0AX9eeYxGMG8dDVtL36xONA0c0ETYjoY0LrFPvDZ+Vr6LH9n4UKwbFJWpMLoRHoyu6Q0smSrNTa7lohB8BDn44E0U/0mmAO2MmIO9Hb/k0qikry80iWDpIdt116QTKCKAskOqGURgb2M1r8Ag57om95HNmsRNZE6gzbKqNExpnZns1OGEsH6EXeitnN9UB9PT+pe539x1IMQ4gm84Jl+lGrpalZcRlHEU+VQFGeZ0COKSwfUYBQ3485UqsGb7CV2ihTkVJLRIpJwRET2gQGYdDOoCSpZ60Lwb3lhXncA7Z1SmJX3kJP7s9PeW7XoEWN2ba1eAW5c6MBJkqWt6Pq8iY7GimOb9c7f9YoCtePqTZUXdMXoc+iypYEUCmW+iwBYSmQ+CdCKsy22DteIyMNpjz30GwqoiTWEGuzknfkFz8ovlQXN95GOmLF9CXJAiKCH4bDYwkk5WYRNNOStW1x2c4gdwYgj4ukSuzj68iHlyw8D5qCcFYRCPIku96Ks1fVvEDtzJl16kTlCwa7bfczVDtxEz19+Cme7HuQiGVGlPbvEC2ndA7IaOX/Fh/H+Mcz8TEng/KYUW04yvAkmlwRk9+inVivrLiPC5A6zx6I3KcUJ9MBPChjOfx2zYtmWGUfOKKADIaP2viFew4ph1evrPt8i8B5eWYefDV2LH3xS6JKSPfM9DUKnCSxxFWI5kHZFaAhT2Nb03BFLypDumQZio+j2rt06imu0wLcXFrHPRI49AJ70BXItPk4kxi86T0I9WUZqC5dUxy4RF2yIK8n4QJMcrIyKqnRq1prQGsqbbaKkc91QH09P6l7nf3HUhRDqCaNJfo6AY/FJzIjKYuV0S9MEz10KxijRNB7rDBWpjCxUiJ8YkDHE8i6UVhjZItiyV1Jk2In+mI76DTI0YCjX97SvLMSs8W+Eodv+qzXeg4oRh2ulLmua00Tm4629wsGcG41LEP3r6qge4kJD4U/qyqcCTvIosp+rx3B0GhOgSmuf5cOWJkn835Wb1XEjtcnk1y5OvkicyHYtPPZ/D4i47iGyLxF+qiHBMB5N9Tnv0GbZa/oX636yl7Onn4Morz/PNQFde060iP9LipKh/NvTOLG0Zr6OPSAST1yvgT9fCKQ26PC4hzwbnU++MJ9Yqn/Y5vP3u67puAN9AoVheu2CO//DDasV3m3LISmk7H0tuVrfF1f0gErkXoceeN6vGE+m3G1fo/bqH8M2Fq9zPFqmLPp3/chQEkFtcQQTevdhzTf9eFXheeqY8W6b9XKWBfVpC76wvxaFRlocmFKCv4X4RjdSAOpAPFqJ9ZkMkIHBcmrW+Nx3h0Vke0Svs1SHZN89X74A5rLWXWyG1YF66Vg4bySGLK+2EgPnRUkrOi+5cArctMSy4PqX3cSw34hMaXu+2yaHEhauNlEB+T6gAm5V6mHqPvQIpzAN0RLbMj1NQlUJ9FB1T1CMdhnEc25TCuXOlKDG1eRKn7+jwWI0O955Mlm2YGFf0LTurmOsT9/QldoUgsmalalkTWbMsAfOh2XEpljRrp12IdKqrJW0Yz/8ITeAKbQLLinFmjcO58QLJJoE1jJBdg8LAhePey1tRlCn1neG1VBczUeeHCQMiNi9h2XEdiXAsp9NmooXsN9yEdIqy+zsbraAytjEBjRS6ddm+YhdUqchVzFqvJUntGy5apVA8rzA0GsHPazzA2UhNEe8LO7659vozi0KE3mE7Dp8jK8IoP7FekvRbk4H0tRUZHiLYiTQ1UuaN5lPp0uoqpc+5LFPlycp8DnwEdNraRJguBHkuzG9vvaNwlTQRn77qsTAHzfOtu62piRv0zpYuwcI3+SAGbeeja1VikzxSMgJgYXChYFjumbVQOICM7pgqYfWIEjam/DlV2Y+LKR1XfztZqgdaBX94TB1BGwYIQpcjNXVUm7n7qMlos1V3Y1wZHR2AE3lMHtc/6PVZmra/SnL6MMBtScNPSQEQrSE0aRIGV5mXwt0snTDGLHEfjg7rg7eixaj+qFm0LrWgVZyR3HEkC8LjwfpzDSVbNsZGQce40UqWED3R6fAk2b051ABO6b6nb474DKc4BdBf6N92jvqwJ+5Ng+SP0xuuvA9R8ZPqYK1UCoAnOpjFN0AkT1N+sGntteDkFGE6OyQigOQ+FvvdByyTNCmiMJrG6siGh6jtzfH8MsJxDpikXw1bWJjiwbgSkR4ZYjVPzFr5LTmRTin2CNrs1pcj+Qd+i24aG6gNm0ryPZz2CTec1rYKRe+PfMg28HuVRHn9Zt7lH0GiMjHZULHix3eYCrAJuVP+O+sjRzjxcCd93Wa0oa37+GejWTXND900zDIPu9FL72OkwPBkTvsQA8voypXQMeZQawHHkBhVs5AeGjiIpdOjnUhlj1qGKKBOhK835sc9fIEhpXfv6Ay3vmUzfSsqix7EZW1DG2nXYMP2uujNZVcl7vS/mITyEg4pcPEfQeSuN7A9ya7koeqv3/bgv9hp2o6gifGcKmFFYk9ZlX4wW8IZxG/DDKc1aQFqPsQXGom1b/6aAeW07R50kaOc9dWcyoyCjW1TT+CBgMMr/pGU5B5T9CR9u0kTpvnQA3RWCGMYEckxmC7zoUjjoWPcpvKWRP5wV2BRvxOj5uBD24li6QtZCwhtQAs495Bq1mwkO8L2lHB3xgCxySsjMczqAgnhYObipDmBC9yx1e9x3IMU5gAZ8TKeEoXquoBgNIImv1JrdFlAKpWL/VpMxefk+/vjum/A1GluRp4exHw17P4whQ5I3XMyHgamSBx7QK/+D264qTJ6aEFENNaCjMZTlGgRNz8Fo2k/Qcl12ewdjMAbaQSLQ2SgPyP3+hfNjaDR1vTX58l6bFNb4EpPx9o526tL/9p6GrttbKQeQH2Q62g+c2oklJ0uo7aYq0t4fqeFsJt79KGTt5o68NXlPRTsVQ0akUdGBzSiDstisxg4pYJhuJsXNK5t6ozc+UpeqjmX4HQ4QXSIu7ssIoEldMbK0+erDeBgHQI7IrNArGqNhytRVqVLaAaSk4fx/S6DInZ2W3nW+fHoh5E8HUDqvsqJa85k9ad3h+GALMmrFd/7IbU3afQjheDT0kBW5SS52y5PHLRdFF0JyIkvEacTkyYu/vjuq5hCZ1p0710kE/Uu33zDrrFbpIR/l1PyD1f7+LALhtc29NAUUe1AERbDXMUa4gLxbY4Ft5HE0yaXHxV3vW04lohfTLsMvkfrd8dYi1N0zcZcNkhXmVFG6Dk3yTON3gMdIKIHkDmQq/GJAVisF7C0oAZ3A9u3vjvIx7T9pkqYtovH/f/gh/tFnntNV3IeMSro01QH05H1N3cf9HUhxDmB8EUB20cjl8O+H8C8O4iHrw2i/BfLlfwDn0b73A8l2AN2nqGNxHRkUZmsXilnUJ58FdEC72M9Usx7HJmxxyHvZ20lwsikciRwzEd3/7YAJE3SKychinUAu5MIpMDJUMfcxr+K7ZLTj1MhZGHtBl5d2wjj8FN5JORokgv70U6BdyXUIqqw/6IzIdoUuGJFGvr0NKK8cGHK5dU8z3qWIwRsrb3k9TsCkAboedD/Coq7hcs4imN13D379VX+oacQC3mjxFqrtnaj+zYKPTXgi0fOGrzBPbIj86O4OKoGi0TsRERyGZvVuKJWbsw6KSH50+WE3KeCjgeHIG3ME0dkexBdDTltVqjynL9srb54kcabj0wcaR8rKxuXQRMq0+KrwZdSKDuDF204Zxwqh2y0H0B/UNnJRdCLsEeS6+S9iM2fB+p8vKDysdACNFBz7N7TsfLy/SYeEjnb8GG8f6+lXImhzn+0RQEoxGv3cTLiEK0plwtVkStR+vCvV1SpLq9qXz8Ldt4DV+c0xQzVcytrx32ZekSngjUHlUTb6L0Uh1uOdO5g5O8hKxyY3BSzvHscL22vUqKpWBfifLHJzF9G0PwNW/T8NrcQUgjOIxIP8M1UKLtEzdeoBvAMpzgGMCwNoHielupj6pbH61lSmuXvckpCWqbGPhgXFmX7ydLjISalAAeDIEc1faCJ0MmIjqVty4qRF7mu/FjWCf4BeJo584CP8VLyXwjVKY8ojMy7jQNAjeDha62B66+Mui0D+7PoDPj+n20LerbnhPVGrFjBxIvDFF0DL3EsBVisASp+4Hwa5vXXkf8uFkziIgsiRI0BFcPkfjbi8hFbCnj4PgwEkJm7BhgcRQC8pf37g8GH1XJ54AkrHl4op519ogofWzVKnZjpIRiU9vZ4vI4DyA7ExoBzKxmpd0CBEIzQ0wEXCiu01KeA1+7IiS8wFNQYfwb/guPR3CpjFKxwWLD54P3owet/S6UISU1NX2aSw7dQ/pNUhLIOaunxejGqz/ccPRyEyVivMrMGTqBK0BoxsHjrk26iTGQdyUVSnXykUu7PNIj5n+2RaVxJBnxj6FYJaa+YBrpii3uzodyJoXtpEAA2OWDpOj2IndkPjFKVJWim7yoUk5W5ceCNm79Wk3L6MxjIbxIWAZIWQuG4ztkwfjEMn+SSJoeVClPMnNcpJ4cTz0rxFo+Xp3MG5is8jPpPKUbmxCyf1c0p1AD29yan7udyBFOcAJhQBpJ7uelRUnZyFN9AE+oPuzv6B1iS9jIzKeTIpguSMETtpdfnywPbtwPLISqgQrZXVqUEciRAYHWNqglLcOwZBbi9Nfc4/8Kza9jF64n3cnc+mrBYLK/akLYl6Bbd5Nb0nKR/6lluKgRu0g3e85QfoeH6gFcFQEcBs8xDUQBOwUmLKAMM9uacmHeVNDJdpOyN8FRqFa4+cuZczZ1ST2Oa334YqZKk3vQ5eiFqkfjdSUp602+zjLeqauK4pgffTDz2N8hEmEnAbOfOHKJylSevyHCYFvGWPHhuGa/JepICl80qOtpHQYNtFzb/Hx/vrY61+NVwKgOKTgHwk6yXsO59FHfNPeE1UufmrFQH1pRNuno1VBHINCHv+KQSu1dKHY0feQYdOwYiIuFsKjk7uxGIT0H5XJ7XvsmYzMe5iE4VD9ScRNK9tj+DJqCwL4pZCv+PSZESsRQvgK01MoGwK2qANpqm/ZeQtuZW08b1/7r4FEldNztHPoIu6aKYtUhTALJzdyWx6i0Uhvj7Yt1ExJj5qGKoPtcfn6rAPXlqBwT8p3eZUBzAxNzl1X+sOpDgH0N2qTz5PVkpdQmal1aoB8sfc4ll4DNU3iJcjhojKFcWLAztc2UgSPVTiclCpM/kq5qnzaSHvfAq/RY1fc/24LlYKf+NvB1B+SmA7vBPymRXtYQohJjrGch63pC2PxgXXe9UBdBF+n7MGwVWfUk2dl78bfnthFKgvysIaqoBUPTwdIy+0VNvtE3Bc/ZMFDN4upJAf6gxPFNUeEsFyjtw5I3+swqOtT1cF5W//qf62K1S4azuPIwG2sRo1nDQtiR44Hhwgo99LA59HjRjNCUPexzuhGa0xwcgvjSlgWTl4vshTmNdllXKyHP6v16LECTVftv3tgAkYH6udoCaYie9DmiiHiZYtm6aBIXA+LkJo7vdIyFHsi8ivjmGxUc/wuepZsDqe//mCjFv2UUYAn/zweTx92/kssoRndCkCYX/4LIg3TT/+IwyJ0RkKRvZ/Dq6Lt96CT2XT3D0buz6zJGiPqwLeYOIYqeIrJKXMqJxjFtvEUx8KfFhFbH3pRLnLBhG7uwxa2cO+WGY0kn3IkkW//sz6GO5RFqYZSU5zv5IrCpDQO+Fuu2GQiOtY6ahXxY9Yibp6CgCuJuV6Kf2Yu5GqKb1H/m1/inMAE4oA8vZJPEtcxMkk072DNAhGtFUU8OijuItfL7GPI64UtUyRsOJ4LwpbOJsVAVXxTOwfcV5KFrf8ENIQ9SK+ddmXJMo3kF79tiZNVTx1R5/LWylgec+fzbIVv18src5vVFdkY3rfNx5Drmk+sC4PzLTwgqTCoAAHK2737r27q8YJtMs2Jfb+2/d3iQB2LAP8/bfOszgIJFevhqLtoO0MLoVHozStiKSp8bQNlSoBPJ+vTEZiFwTURe0YzXNGfrBrYTnUB9lEkviRZgQwa9AlnIvWkTJDy8MAKD+C/iwCkWPo7dBpGH+rjWpTG0xROrTSmSZJNWEFNDqErKBlZITpXYOhkjreLDZ6O9005UT6K5Imi0DW5KiHJ09r9P7mhScwYHKuODGAcx7ugwb/avzjgk6/YeqhahYO1R+RSzM27fOoJGj/AAMxGDpFL81g6OxYNS6cp12pj3LH5qvd8+AYTiCP+tuXTpQ7zJxkXKA85hvQfJM04hFZHMXxRMsfdg6Hb8ZNxO+tIrq7bmQ8PxAGQ+c6LpPR8zFVp6PrCgUnSHUAE3OTU/e17kCKcwATwgCyZ8PwHt6Drqm340BMzzPgGq4pCKSzMtcbKWD7pGQcG1n5ypU/9Yu3oZS6/hdoidb4Is5hSVD2JeiP+BI8jwb3L1YrWIPfYVHFBWRV21eEvoAO+X/x6sfd3HNim4IPOSltjGqA6SMrSwekHYoel/uotrCfRmNUdo6pUmq+SuwOI5l0Dom78aa5YAAvVEKAyTXeuYOYwGA89ZQuAGEl5ht9CyA89nC8uszxtc3QTHiz/fJcMhJ74ulGCPpOq5msn30QpesVUNBGRmIZATPE3MUzHsOOK1oibXexV9Em43eqv6SH8acDKIl7G2MWvoYuJNrdfhwuNu6kinRMVLJaNYDvEcc3xwiPtZuEerDYqE/YGCt15q2FT3zPURaB/J67GZ51KK18/cFefLulkErrGnJn7ksHlqwAx199B8Gf/Vi1LwAAIABJREFUaoWKzZ+uR/HW5V2em68jl6ZP9igeJQI3Q+P23C3s+PvDD+v1E7koOb5oZg4igfQL0PJ+2YMuWIsOXzpR7hxAwmtuI1S1Yy0qohIc2AIHHpEZBlYzs90PRTm1vzmXdck8Q3FVcm7yNZwjvrFVrpzmJnVnVJL6QmkAAy3xCaZrdohUB9BXk+7/+HlTnAPoSQSQqh7fQLPgkmplCDRxsTSmYY9A89UxPdsA3ynS6ORqz8pJiSs5Vusy8rWyzUw8PVVrZVJlgg7gj3hF/VuuuA0Ojr8zXcGP2St1ojF/oVM/9Emsc+nLk/mOY81RrS4QU7ceqpyfpyJR3pp85T1nRNWs7uehnpXWNg2K6N4baUdpKpU24b9h2mFnhSejOi1bAufPA/36OWkRSNXDqKCvPn6mCnjzAzVQ+rym4Jk88ioWrbjPir6wcvaFJjol7w4P5G4ekIBxbmcqj8/bVyafw7I8LVH9uNYznt13N77ZWtTqC587FzO8z8WwG7scgP5jNVri8Adf4LXX/J8CZjsNcW+zDPPx1XVdCbusxnD0v97DxSnNkwc4ToYLOhPZdbUkHagDB4A/dYZe0fSYVN/hpn2Re9ogFdlZs8Z74z6+52ieBaNilWc7q/lLYwt2BpdWhNZ8dxnVo7FtXCh9GdgazaP1Yo9RzMOhxRTvnL8il7JPLIwyikLEvJ5GTrXZSNrF1X9Gj6nCJE3Srxj4hKHnSq6cY1ztiCsYcAo5kANnQGYEcmUaI7aY82tXB+WolI6za39znmJR272yuJxAWRDYFf0xRosHpDqA9+pBpfDrpjgHkCtXrqSN6oG7+y+1LVk19Rq+v2s30q4Ymo+J6IDOQRNVCim5k5WclOgAMrLUuTMw/OU16LFAY+eYDj6Ahyxuv6aYgfC+TcHIR8WK+qPHCB8xUGSvp13B/Urr+FC6IqhbaI8qLDFGzI2pWP01S2O8eOlr9UHxViSEkSdWjeqZ5jIuQ4Pm9uR/Ht2LLVZ0KsZWlOiEKju0FzTz7Q1oNqGcpYgiHwJX4EZeyh/VduQBrDyyDmrHOos8LgY/qLBmWhbYCQlgcQ5VVRJrBG+zEMNXZsYWsWRFxnVE+9hJ6lKM3uwILmNhyZh2M9KHz2b4C79fL6/2M/qoMt3qz7SjWRy9FPgLFsVoomCz+GGql+81o5IsUjl6FGgc+A1eil2IMbHvYAM0ebKxVzAf8+Fg2B02DDHvvocqVXQK3lsLn/ieo3kWdOrmFXgXrxwcpXb/oeuf+GJ/ZauwQ+Ixuf37oAaoH/2d2peL0Ath+fwauZR94lxDAmJaAGJwE2EK+iCpqjwZyyQ1Xn2nHMrBWZXOM77yCsDFl68sLtoUQzTPCvl0uG2pZzz0ENCzpybp5hw7r8VCPDVcT7AmUGCyGb6sXvb0fjAd3LSpXvhwsbl5M/A0VmIlVOEH5j/aGfV3qWhyqgPo6U1N3c/lDqRIB9CAeON6lpQEuor7Fe+eob6w78tKN6OoMRAfYGmlgV7Bb8UVoZQrbKZLSH/yNj5VzXoudBUajHtKOaBUpzDcdFyFfvmlbvkR5EM+HMPZwBx445lTKkVmooVSJJzVeCvemGJFHxg9Sa7JPqULjMStGO0N/onKqAJHSMZxkcU5W+D5U7o8cM2U3aj8ZlEr1cu2MNrHFCXPSfkjTriMgPgq+qcmSgcP4MocDVH51FzVtpkDD2HuX+EWiXX+B67j4DkNvvkdz1qcaHHdOxJjFyzoxPyxAGZT4n3GRD0aiQGcH94NdQ99oj8E3Vbjy32VLKdDOoD1Mi/HvEs6Cru68vt4L2qoirbRTMFFchc9nnbCOE2yqv2fV97HyueHuhSmPPYYkGXbcosf8HpIFiyfeggLV9yPabrQFM3wFb6CplP5t9tEdNvfQT1Lby584uuXcT4IIVhRdQCCBmsZx+3DfkXRrjWVEotxRvm7oeSZeLgWnrmtV0yEbtyXL4vfSblNv3if5UKSutLFsUthYIkrjouVQN4XEwU3x1Kj+j5oPidfL+zicgBZFGQW/QVxAIdQ8K5HyXlndMkv0WVbK7VtRoWJmIQOlkPsS/5CT98XuZ+p2m7/5HZMWvuY2jQOzfCO5jxMdQCTclNTj0l5PICepID5XDeirFJ7oDZuetxABNK5PG5WH86ETsmS0DhDr06WzmpyxgUjlFSVYHUpMVl0bjS2KVYVaoThFkg/cwo58QxWWB8Cg/FjZKxDB2D8eNdWbENJlMQOkO6F55BWAessNYUF4e/gjbNj8OCDmjvNGx93e6olEq6KGjlyAKdP6xbNC6iPerFOMPi1+/NYZNXu7qu3iz7s13DBAGZugYAZDu6K3bsRU7iohQHMrWTVNHB9Pl5BfSQudOGPSJrEAJ5s2QeBHzuAWL/9hqgq1Sw+OTpCNWtqnF+hfxZiAXSUY2+zITjbpreKKrNi1puay568M+aD3TB8A7497JRD64Kx6l0xNDaECtT9pS3aYqp12jcwC/PSvmFxtL2FCZgAZyXxsuxN0KWL/yTVJCVPszMj8P4lrV9HCcEt4fUVP52dkofb14c46XvGjYjA0hVpleNO80fkUj4nLsbIimRMcswZEn0uLqvhd/yIujiMAtai0xxjFqGUJiOTApkVHoRmJPdlBTDPb69kNm2SpNTPYDlWwFH1ITpPx7XznVEYEfuu+rUB5uCH4AbIm9d/XJKevDNmH9PX3DiO49Bwnz/z1UaVoyqjkeoAJuZmpu5r3YEUFwH0pAiEvZO0BHZGeG4nDm80uqsbQcxguVGNVBGCN4wpRWKwaMWKAbt3axzThBXF8ahjhX0LociEKzgblBMPRp9UBNT8CEp1CtOWChWA4esrozJ0ianhETTbm+b8DTNOaXmpGXl6o/nxIfjwQ42z84bZne5LyKTaTke2KP5xucQSPIfnsEz9Nn3MZfT6KKMF7pc7+qrow95flyrgrzoAn2nlFZVPKVNG3Sdi04pit0V++yVaoBUcodc4biDTXjQWExuwvzec7fiel3wOMwsPRpO9ulJzz4hF6PnnSxYfI7FO3btrGbinj8/GZ9caq/06YyzGo7OVkve3w2GlgAvswqJDxVWbpqK1cvTojBinqXBh4Ne9BVAAh63bYZcVlITvPQv/iOF7X0bZsroIxlsLn/iehZyHemSYhOHXO6rdv605He9saW5xEjIFTDoUFh6oYYcyKIO/wUVUCCJdHCpfyqa56wvv8z7NGa9sCJxSiLXwM87gQaXoEYrbiij5MWzD2bR5LSecx/CZcZF7EjmRE6dxFPmQH9qr9LUDaOcyNP14G+PVOKe1wJdWpNh+Dz4J7Y0utzRe+fNXl6Hfn9X9yiUZ3/iybzPvThhu4AYyqM2LUBl1tCpIqgOYmJuZuq91B1KcA+hpBFBW3b6K7zAPmpzY3WRHQHnzGdUV3sJb5o7EdjZex+twpXCJrFoDISuWKjJi4tGIy6F+MCM0rVo5gcgLURu1oXXLsuMMzkHTF9AkhcOQsCHoe7O31/B/PL/EAPLf5FfMjZM4ly4PqhY8phxcY6y8M3xa5NnKXyBIYbuY7u3USQlwgFicjh19m/Y17XHhAezXTXNB0Jifq1RJpQ3JvdUg33rMOaoJxBfk74xGZ8ZaovByTBDXREA/o2eGA9BfDqBUZDn89kj0uazJlF/DXGwKf03h/uhocCyZYpRu903BqGtvqv3GlpiKD4+3ttrtLYyop++MaX9+HFbRJNqtOg3x9UvfusjTZUt7BWcjXaXIjH6zu/d359jfUX3os2qhQU5KVhT72swHOXduoPrJGZge21xdsiM+xeSgjmBU/MQJHdVjZNIUW+xFIRTCfkt5QrbT32nHdu2AyZOdLSAWeQZ0P+hg18AyVMNyaweyK/QOHKYcWhqjfzT+m2T6GXEV1Kqtkm2Pet+9Seju7nna1UjMPtRVX+iIevfDh5beuv0cU4PaoXW0vgEs3rkcXtqvXJKJGaPOdHcsbiOdWjysRnFUxk6eJtUBTMzNTN3XugMpzgG0K23E9Szp9H2HBmozncGh0NQkxibDmWJ6DFvRbORjKmriTWN6k5OgoTvpgk/wCVzDjMMDe6FnjF6F0pgGMwSrBCwPG6Z/J01BU3yt/jYyZYaCoVXobEy7paM872AMxuEdVX3oDfwfz2l3uvfhESUpJmXtTPsNFigqJAyrF99QHHt//QVQDsubbfL0OblEABf1cfJXLFumgFlMtbNIp0m2JZh5rqY6LTGh/TFQpfJZSUuzV/ya30h9w3S/P/omyYdvjvgUAy++rdpGPNyq8GYW+TAVD959F6Bz0vDkJxgVq8dcQ3yL+cENFTzAOCcsPPKXmY9YxUfOY+3+bOqypuJUpoDJk2kv+ogICEH62OuIhq6Gn4C38Ba0bnNZbMSpXGVx8qR/ngOvKfFnjdLOwzeR2uvsgeEYl7aHFSVbtEgvMIydCsyFHDGncDptXuSOOmo5U9zu78IDzjMcv8Y4r+xFEfXP2wi5iwuTzmsRuJJ4cvHDhfOwT9IgKCYK24LLoFTUZnUOX0c0iTHkHGk3zudboblK7ZFjua+dnP9cunx+5ZJMzHsn093ngnMga9QZ7EQelIAql091ABNzM1P3te5AinMAPY0AMu27AyVVR5kOboaZLo/9B9RFXWgiXVKbtOydS1Xsets4yXKSZEVX4/A1+PqwrgQ2Zpdd4oTsTgqIFZydoKtr+YHciHLWOUimazSPGfEhya431RDsafe/UQql4NQ+lf05jPzIj6NQXoYDGGh4tfwdcWK7JAbwx3JDEPiBgxJo4ULEvFjb0gJmFG0uGqquXO03EnPydFcfFxPlmzoVCh/EqAOfJcH/TDkaJ9sffZPkw2NKfoF3tms+sIM9P8c7u960yIfZRoccMwYEDUL/aI0FICfm7yEvWqob9yoF/FihW9i6T3sepA95Fn+4pIBlgYccW0zT/4Oi6ifKPBqS3861/sXAWQ8pMml/PAd1/VnOtO4rYUsw/6ZePFCLdoCm5lDGaLGhguG/TTX/bhTFM9l3WylHbvOlbJq8j/Jv10xFLE4jh4Xhc3eMXSKRC9Y7t+5YlbZrAp/CUzFaotDX44uLl+XOAKXVXMmb+huqoQY09ZPdluMZC4ednoUrYenvWUV2XM/H/G7S3XyvRy8phmLYgxNIjzy4wV1SHcCEbmDqdrd3IMU5gJ5iAImTI61BIGJVQQgpCqStRiWLJDQtItCzb1oMGuT9USIJY+vUisLcjeEIOae5qS4FZEau2BMISh+quAIfeQRo3x6qgpCVmuQ+oyNHY1TqAwxWf9udxo9yjEGv05rc6g3Mxjd43asRKXu1nbx3TPPKakEjb6dYYwnGgu7LvYoA8vqmCnhK0dFovVuHefcN/Bbvbmxo4eY+yDEFA0/rVKlRp2CVLFNZtNatddSHKWxjjFoZEL0/IoByLI0oPRvv/q2jvofeGYPOB96xHEA6Es10fRM+Ri/0hA4js/p2VWBVK+rk6wiN/W1yvruxiEIwghCDs/nKYvhrG5VjfVbXDmAQ+qIv9GpsA8qhPP5SfzO19xN0OO1n1EItOKtpi1fOglWr/BcBHD1a4yw5RgqdW43V0HIyI9EdPTDS6rqM6KcPi8XVm0FqTvoLT1j9Mjv7GjNnfx7m39IJZMRM4l9ZfLYMNfAuNM2NJNZnJS0XRZeOXsVV5YMAf6Z7Du3Cl/iFZFxiGA0WUfcpFleQUdFmxcfpuT2gJErE7kB0mhCsWnILlZ4K8CuXZFzPw93vZsHB8bQ2sBJK3VirtN/0XU91ABNzL1P3dd6BFOcAulCSOADIcT1QUsA8hIO4hgy4X70uTuVAFjAUxj61ImdBg69WqzJt9/nnQLXDUzEVbVWTuwaOxfT7O6sUojE6FcTUHKOEscMY2Wh5aRRGQVesMZVnolX8d28Msciup9RegDcX1fFqJMTuAC5FDWtVnSnwKq7EGO2iWEQiLdIgChfDS2P7l1sIs1PYRmKg/AHOj2ss0Anc0nYSBl/UYH2Cw1eGt1CONwtBhmcfiR5nnZi67/Gaitwap4THEJ/J6tonntBKAYwQkniYz4eOor+KQKjEcGj0D/j8XD3VF+K15hbohbZtNfCeiwhT6yIlCJkqNWoPPM7fESeJm9t1QmPGGAl7FLuVMoNJTUsnhBWdxqEy8Aa23Y415SLEX1hMXr+PA03AdhePcmp1GxUNqW9txmQobuKmQ7KR0adXMy9XqhNUn6D5UjYtoY8eSefpoBfBHvyN0ir9ewfBqIoVKIiDFmPCuxhhzUM8J6ERmSOdJNKLAl/Gy7E/+oWOh9rbnLf5Ljqkva1ubkcJlMBORWkTiluIhQOwKG6EwTJfCMmFHYtPqLlK0vf4Ex6R0POR3z2DB091AOUXPaE7mLrd3R1IcQ6gpxhAdlZGCeyawCZSRSexWJp/Fe7OFx9wWYTAyXLiRGDL/MPYuIp0MEVVBIHOQ4sWmgiXURkjicUUo+GWkxJA7fAZJqOd9TyHB/dGjyiNI6yG3xR/mjcjUvaoq0yfU4f2DHKoa0sZppV4GlWxUmEaWSX4/fdAPe2v3BOjA7j2zekYeaGlun4HTMTi8A5g9IPpFRlhXfT2EqwMec4lKmVvNEH+HDMkJPeX4yHHUujKxQh66QXVrMPN+yPvtAEqfcWPIYtsSB5LY0VzC2jqG37cDcaL/+7VS8t6+cvkQuJ8SC48EHEK17PkxYxBR0H9X0OHImXFSPj8A/TAGYvOIGUMjcUGxKOZBRx/y5BB4zF98R7b79EHHzjJtiURuzu4iTm2QNgZHLyp3xV+xF/GQpfT+moR6snzff994OOP9Z6kfnkJP+FnvIjteEwRjZuFg122kg5w3qiDOIiH1LFzg15Hw+jZ6m9vzkHu+kDGBKMZbcjDzX6L8BJegubXkXOU8zyxIBMDHV06i49huzVX+YtL0pPnYvZh9J8LJFa5zwxohiaxM1MjgC4hncTczdR9zR1IcQ6gpxhAdnA0uqIrxqi+Sj6oYDgxK+tQAdVC17nF3XljmNgjgDKFKKvozLU4oWbK5Cw+ML9L5QNGfIahl9U8yhiZD2OtzOuw7FoFr2IA7RHAr9EYjaEnecMXxr+z4pxVnWzA/QbTOG/evXMATQr449Jz8N4Wzc9zuPModD7UzUoBT0vfGa1uaPJF6sz+hfIqKsX/6MAyxcSUPCdgaSxy8VfqURa0PHFjBYKqa36zo43eQ+6vh1nFNrJ9LqS4wUdxKEpziNG8oX2dmHdE4uaOpy+E3Df2IyIsM6YOv6joj4wDuAWlURpbFVUKo0+G90w6TUbuiwTp4Q7aEbbF106H6a98J3LiJE4it9pEDsk2mecrnKUdy0tS4gN4WO33R843UP3MLCsdT9Ug4k394by6e2YjRkBRUbkzST3C+VJKUXIOm9Z1J1qMKqEOjWreGnkWT7U0qX1J8G7XM5Zt/xQd0RFaKce8z3K77JPBoUr8tb/GUWLeHwoDTJ8OmPk+NQKYGgFMzPhxt2+KcwA9xQCys4yUfYYOqt+M+Ji/uSI8hVzqd35UGqZbaFXeJveG2o+XwP2XXtKpI1aWyspARi4YheJHQ0ZCJK5FqieQjqGXA9fF6y3I3hZ1zmrS3JLYjh0o4dUP4dKlzqICXkNWUJfENqvYpgCckYAjFRvh0NBv7nkK2KUIpNVCBL7i0NYbPBgx7/dR7aMc1nQ0R3PNqo9+Dfbgas4iiiPNyNxJPCD3Ydq3QAHtEBIH6I/iA9MXVifnObEBP5zSZMosEPokfJyqWmbkzxSucJuMpmXGRUvGj9uIOZU8cN4e+/bzSSD7x0tKoxS2qhQdozB0tJl+41gzzt1R5EU4DlsSZTvxqErrEeNlqDB2BD2GktFbrUv54znwYnwWdBiYkcgWchVnIzQai/CI57FU/S11vfW7uQ3bUEpt+xxvoj0+t9p9r7VnZQTQ3Tg4hjxKV5fPJhdOuexCaIEpSpsY1Alvx4zzm7YxF3eEmNjtPQyzFskkeTaMEGa/vDiKo8iv/mnkQrkAIfUW32lvFtF5670ytDf98SEGYEBqBDA1ApjsoZXiHMDERACrYIXFAj8G71jRQJnSIGbn4/yfuYD7k31XxQkkcJ8OIOk5xo1z1chkmpTk0XQqSPtipODMaUg6XOyOk9rA/vGQFZELRh9A3W4FveqQGLyTaY+MODYKX4c5DlUH+YFTgDQHydi9LAJxoYG5tgx47jndDXZq8GBFAk0MoExrM6JzGjldqF/ILceKw4sXnQ+XfI2nHN9Cf0UMGKVhtKZqlu3446KWhNpTuS2e2TdZQQdYe/Pvv842bgqrjMdvagLxUkUjsG1PWmsjyZcPHfLmaI//XDICuCNzZRS/pNvV7e1I7D2YRi1+KONIHCkLREyhBHGCJBy/iVCl6kN911twrSI2V/bXc+D1nn5aR3/ZZkNPswZPolrIGqvS2rSLqfniV9dgDTQLwCh0swor+G9/F+TYnxSpXNiGuIz9MpG/dLjloqwk9WlHBffEu1E6l+wvZ5xOIB03qQ9PnPS3eF21g9Q8I6HxvcYkVQwXtO0wWS2I+O4wBezPceTpG2gWUIboOjUC+L8bAWStoV6eOO19VdTntHyAinEzD0TxRQJ9uI8DUuzRsEpxDmBiMIAy0vcralpVgy9hERahjrpBJAoN+6ifwkP5wmQKmHgrO1jZfk3iyUqU0BWn1Jo9eFDvIclzmdZrCK1pS/sRL1t4orHvn0aXjx706gRm/zgMRh/0gZYhM5hD/l0JzmpIJatCEkRAAd35AfTXB0HeUxci6G1rNH8LrWtXYPRohXti9ENSQjA9ZByMuMYEMYD8b+tW3Tc6hr5O38kIYIaT+/DHycKqecSd9QufqSKAO3boSLIxu/KE7A8l4X780Rej3v05Zdp0aWBN1IhZonYkbUdkaCYVhZfv7ALUUVRNEsvL7YGIsVKudNzr4Qd1Hn89B9M7GTWjRCMjmVvxGKpl2apUff7+2/U+vHb/Esy9quliJmbth/cjP7Tmg3vtcCQUAfwGjdAIc1TbiXk0qWz+uyZ+xa+opbZFfzAAVZb3V8VR/sQ0svhJ4lmlPCY5Iw2Flnkiz+J3/I7q6p8foRd64yOlS05O0LFj781cldCbaCKArdLMxLQ7zVIjgP/DEUA6gJQ9nyIGxTVAk/4ACALAvAcVWLm0yam4gvX+vRMaSGJ7inMAExMBlHQAB1FAVQTT3sTn+Bzt1d+k/JgY0UZFe3xhxgF55x09scRnJmVkj+Kojxuu4Aq0OoJMM/Hfy1Ad1fG72pYB15A+ewZFiusth8QeARyTfSjeOauJtd8vtgCj9tdRkmjyQyCFZv8zEcDQbUApnYIzEUrK5ZH+ZxMex+PYoiof0yJSTS2GaNs8M1LZMN3EFNHChU51B4PZ9Nb9jmuMuGAAcxxDUAGuAYFzT9dHluXfu8UA7kMhPBKH8gQdc8IP/GXSAZwf+CpeiZmnLp0Hx3AhXR6FtaQiwxY8rn43kW5J+lwRpL+4H7ugpeRkUYK/noO5X1zfMKKvngGyIisugEVlJEmXVcB8r4nxez3tPEw65ySMnlegh1o4MN14r1OO8WEA2T/CTt7DCNVXOk9/4Flr2NTDPEtpKWbYcFRZ1EMJ7fjTAbTPUVIz1ywk5DiXvJ+mspnSiXv26L3utUPu7p00EUBS8ZAOKTUC+L8dAWT1gq5guNtY/kddMALZzjg206Mh4Rcp9vkF88RSnAMYlwB4XJ1lGukJbEIMAhCGmyp1QbLWftCkf10K/YIxe3U1pS8scQ6rawvkRyQAMbiDNCo1Zuc1XB9YEeVj1quDmY7Klj3Qqw6g/HCzTV0DxmBUjOYdpI7yHOjCCjmpGo4RUtqw0vZe0cC4YABHHUBgIQ3Cx+uvI+br2SheXE/65At7GAdwHg8gGxzyH+Jx0G9kHwxlh32s+OOD4RLNvH1ek9DRXnxR4QZMpFW27QRyKcwWMVz54OQWYvTSpK99Me7dnVO+uzMCW6BpjLM6+Ui6IsoBfAG/4Be8qA4fAI126gYnBdIbmIVjyItVeFrtY0+l+uM5mL7J/hgCdIORs+P/+N6MLPkVum1roQ6fW3UiZqTvoNLe/4WUo92Bsj+/tzABE9BJ/WzX122CmRZNzKTiE/DWrrf8QgMj22h3YDkPRiAEwYgGi4q4uJPWHpMwCZoSigwL0/m/X+hswH8dA1gjbA2W3nwq1QH8H48ApgNAyfmjhFOAxT/O9O5AJQELB6JYj2yKazLEVQaALflgDf0QxdbhNBK4Hb9y5QruZ/4kBZgUALdPsu6az/RYE8xSm6gOwsjBFLRBGxVgBaZ32YoWn2gslS+MDghTc5LrL6nXkdQ1jDIYI1lrSexQGKmxQ28qLjhvfghlIQuvKZVH2gZMxdRYrUjRCtMwDW3U32uafY6t5d7E4sW6uvNe0sCYKuDGNc5i5tIHVfsuPlUbLTIvtKqAzyKbcvwOoKByBGn2COCjjzoDiNu2OSOA3Ncf6W0XPGPx6zqsxDTAo8/inwm/q/ayKlma1GileoAxX+u0uhvj8t39FG+ho0PK7XFswt8BjyunQY4hfqQZqZcV8H0xCP+gCMjTSOuJjzEcTj0wfzwH0ze5MNodUAxFY/c4OEevuUg6cn9mAGLGf4pxMVq+j7q73wY3xVtv/TdSjpLWxt2zk7CZ/hiAgehv7dYWky1aqjaBX+BWo5bqffDmHJTQnElOTkrDSTNOOaOz2eFgdHfsILXiqaVOSFCxYnox+F9wyON7f4phl/qOpUYA/3cjgBTv5JKFkPMnFUyBlF6whGSpYE2M4PNioBAVzRQxwRiaIv9uGwCIN9exPSU5gImNAPKDMQhaCqs+vsd81HfBFA3ufBZ9xzoiKQnNMkncXr681sNNrhlia3uU6gAeUnQZFwKzIujCOZ9IYslqu9cxG7OhVSg6YyzGo7P6u1e6Mfjoto4Mch+CsOlWhC9AAAAgAElEQVSUEG5nn5yTey8Sezzb37vLTfxzLL06lJi/1uHL1Yd6z55YFS1Iizs4nLk0+tbaAruDZ78eFx8dOwITtDqfX9JdMprZrHE0Xm2kdXFJilwJa1VfeL8ZCdTmVNywR43vRdGBwTCxZd8V7IlXD+ov9vj6K7D4VhUVDZOk5i/jRyzEyygFJ9EySaI343FMxFvqWHs0yp9Oh3EAixQBvjlYDqUiN6pMQxCikT9/gHoe//zjHDlfFhmGFv9osPGvbedj4qlXrIIvf7bb3btjp3qy7yOLJqaiNdpCsw7QSNA9Bvq9H1b6W/T6u6HfuDFNGwwptGz3KjyFp7BG/UQS7tsItTaTU7IzNO0T8YLUnuY73anTf8Mhd/eMzLfP0A6lOoApywFkAYcb6WqXR02hSzFlWNvIXkunj4gdQryT6gCm+AigfaJiEIQ4LgLfuYrl6k3aq/jOogDgqm8o+iigNok/yTPW6o0IfD3LqRDi7sVL7m+GZT855+GHfV1UWZTFZkQhCGlwxwqAG9oMrniHtDkM6tb64oMycCAUtI8f5h/xiurO+xiKSRnfR5s2QNioQRjocLaXdV6E/YVfsvjd7mUEkO2kA9i9WywOHNFSXHSIXsu/UaVBAyNvua0qtUcA43t+/sI7SUc8IiAEaWMjce2hx1Ar51aFu5KWKeQWLkXoatkVqIIX0q1QaVaav9or22Pk0/jbwOCB+CBKR5Fq4Wf8nraWolSRyiVG8zojLlv0NXTcV6Ey+oNJEJ0yXgwN4fAXIbfpk6SkWhH4DKrErFCb6GwEhIZa1FJ0LJitP9mqLwI/cgiOL12KqGdqIE+e/0bKkYsLjve4LDvOWITvJFmug0XWrpwDOK/SBpVdgH6b6vj9WbhqGuumzcbreB3fqr8LYS/2o5DVZlnUQn7GQyiolH6IV6b5Yv6M++56tsV8+1iFzSK1VAcwZTmADDM9kMCjZgrXHX7vUUARYBUBsFdJwyYtBWy/fIrDAEpOOoLuOXHFZ2S1J5s9bQaaojm+UiDy+3BdAbb7v/GvEnb3pb35JjBFlvMk4WLEoI3Y6iz2uA9XcR06BXgV96n+7EIxFMcun02+5oO3buAyVOin6VQONe6L3F8MAnU5RwS8h1cPaaA4mK+sUkUR3d5LDCCbYlLApOGZ//v9CL55DbfyF0G1XHvUhE+Be9K+0DbnqYNPqixIMAJIah4WvhjzV+rR0Aoxynf8VhZkwSXswyOoWWCfirIytUtew9y5gciT53E2Vke3ScxdN+gnVbl84sS9cQAlzqxH0GgMj9a6zJKn7Tu8ilehi0Py4QiOQRe6XERmZMZlcJGzGDUtDj2mj03RiL+LQExKnvi+nwNewgsxWnkiG87iZlg25QCaBSn3+TG8C+oc0pVgOz5fiz4/VVQRwP9KyvHxx4EtrlA5a3xLeh4WTBFXbUxqNzfNsQzFOlf3OgwloSlTFuSYfT9GT/SEjjJLtgL+W1b9p8d1RASlVxXZZF74r2IAZcR56z+sOY9I1QJOaGD8j2xnvo1VvlkBXFILX10Ewq+WQ0IdVLLn1ze7I0roSddTnAMosSrkzWNEih80yqnxwydTLrwBXC3dQHoV9aGwfG0swlloHNhiPI9VvRdjiGNR7skNS8o+derAwpol5XgewyrlryNfw2v43vZxjEU0XAXmfRUJMR88fryKt6uk2vHPC12x+LnRKs27q0pHFFup2fexeTNQhnBUvapmBe29WFW7FIH8CATmzQ1VIZMnD2YOPYZmzXR0wEik6UWCJoSWxigOx5tdCcTs46+ImnkGjPaVrZsHIedPICJrLgSfPqGqvslpSG5D2uMPHMamC4QGA38Xboial761tI395bDKeygdQIkbm1xhGsZda4Vdu4DVqKTS2TRKC0Y6IMumSjsagfgFtVBbTX+6gvgE8liX8ecYY8SS6jCUcDzxdCMEfadpUtZ/cwilXwlXVDCcl7gIYso9uH0bNLyuscfEI98sUFxVoDdp4h8MaUJzz3UnrNTtrieREzlxGtTQzYvj1j7kWH0H49S/6+ZYj9dGlvd7n/gsQiS6HUB8hSskFacG9Q2EIYODXIMRQH5D/isOuf0hyIjzxZAcCIo4k+oAJjSoU+D2ikq9BviDFGrUoHcUgBDX19zRH0MDcxIABXwoMDkTUMCM/2kamPjAylLKRz73QwhXclEExNfCL1gL7bxQLqjIb5/C16Lf8a2sEzM+pQIHMTmMbJp0AM9DSaM1g/5QqXBffAiNM1UxbBtm775b0eCnzE3x4iUHmywlJsiseo95AF0KJyicwVAl25YpE8b0v6Qc1yfwl5J+o1FVw3zM5LPhx0Xy61GXk/ADQ7rsLwfQpRL4cUdfMma0qowYUaLKTK5cdDJ2YslJLdFF7NyQAtPUR5KLJH+1V95DE6Who9oYs/BVdBO1uRPGWRWmLMIpiENgwRNpVYzJyOBpPIgcDvKDtIjAHTg5nPzp2MoK/yV5W+O5Y1+o5n7TZydmb3vUhdCdDvvDfRvhwRXaSVzz9SFUaBRuUff44n1NzNxi9i1XDti40f2RhlOSVEkhiEAsAtWOX6AVWiqIOvBW1Z2YuIIJK9/MQfH1yZCkm31Y3LEAddU/yfdqsOD8tyn64reB4432X8cASk7ZV/sVRfY7/6Q6gEkZ5P/xYxg2mehI93JNw9FJ5260LbLHIhCGW6o6ij/IqUCE8f80EbTEABJ8zera02RDjMckkSwnAlPB1i/DaPS/3NVrfHlxNYFUI4xuJMb4TZfM9jz2/9o7E3ipxv+Pv2/d9j2paEcUlT1kS0oRWhBC8rOWrSxFdiKJkmTPn/oR+WkhoihbWcqWLJWUdpXSpu127//1fZ45c89Mc7sznTlz5jbf5/WKuTPnec5zPs93znzO9/l+P1+3FpdUOfmMU3HH5oje1Tf9JvDII/55FOQmO27Q/HA8zb/nWRFi+XF3V9MwwXWy3xiwBzCCMEkErcPGs7MZNWI73S7PojVTmILd0pbtLEciyL1esoUnHgIpJHLssVZ0uEeP/EzgVBEPN6E9rudRZH3/PTuLl+Dzj7abDOBnnrFitiImPvPpryl1qi0X9/3JN9F48lAkWD7VGm0Oju4ELvePsyR+DDDPrXnGW1+WLeSXfbO9H+N2bufxiK/QX1QPE0FHMimVRMqt8XngUzdzY571gknt2e+yjwtn+IqtSLjAmC1nczZ2m/ioOqvpN7gaI0cGJ5FU0P2oIBLovo9K3e+/zYYUuOtN5yz4k9ot6ga2jeomgW5NSVF+uCYkq1ucHFNtRnaFvuI4TsBKaB1/vPUASkulHcX7uxCxm7G6BZu++lIJYLzg6XExEShyW8DRkiSytdi5s92akzg7qbMb3YT0iZ6YNNFFq4U4TmH6Xe9zYn//NACdeUi92Rl2VyvuJoLDb9tQqHC7gwGhH0royDjzdNuQecwjvyJEN/Os4M8NzLkBNaq4nEmza5nzjKUT5zHWBJB/nNeKU3aK4xo+m7SZE9uUNYK4QcYA7uIBPPVU+OwzM8dhj23hpj6lcScKOaKw0QslYQJiX4tEoj3U3F7BVP1guKuBPPPTSRy7zWY5lmA7teuXMHhLeTf5f7sSH/P+dlvt4BHupH+ZR0wSiGxxpYqwunF0e8zcta0lVuveEo9SZke+2PlHnE4bPgp3l1reTuav8+aXHB8uTybvyRa9bLn6LcjtnN8dA/jGgf3o8ruINcCEmz7mpT9aGfkjd1LadxVbcuSGT80xrU7YwrQvS5t1CjpBKtrW5W/Hk+z+TLzI/wl5+hxJLflcqiy1w1Z1ubjtWt6cXCXQbVTZDr7hBhj74hrWGFlcG+5zJh+Y1+6YX6kF34F37DEfwOWXp28MoMzRiWf+Zt+zOHjVJCWAsYxX34sbgSJHAJ0vQawC4O6rlh9nkWEQD2EbJjM5QjEndKS4DmUvz+dWmMp+rNNLaTrRpJowIf/TaPHSafWu4JHOs+g65FhzkFRMuLfK00YGxI/KAs4P3jdT1nNsG1uVZEXTM5j71Ifmx+7CxyOzlGvWzDJZjhIOGNSP3C4xgOe0x+iNAG8MW83FN1bjSl7iJa4270lsmryW7SAhEk6ih5jJmDEgcVKyRSY/Fo63QBydS5emjng4Xo6pJdty2vbJZt6vPrmOvgMqm3rATrug5ATGbLdbYOJlG1q2H//+az9NFWF127ZbE/PoYt8zK9fGiEo97h48FxGLKfqdzsOMHOOuN+uMKVmel/A6DRpY0pvqUnARMYDXP0zxe++2U5swgZyzzjWJOKtWWZ3u7t3h4EuOodn2/Cz+smWzTCWWZFbtSdatzB1v5oz5MP1MyTRpck/9iDbmtVtuZf99dzBoSHbKYwCjr9t6m/P4l7KUYWs4QU6OcycGuiVtjjzSlnZM1xhA5xqFBBbrdgmtNr+uBDBZBp+h4xRJAihrJV+C666zT/yFNSmjto4qxuXvtLz99ydLskdS0GIFKBd2Wkeo1y1v4C5w3pvBRnvrNKYyldPNcOLluTvrEd9uYOHt1HU5lK8iGuWiUtmCsbdO5/zzYWHJg6m3bb7J2NzHSFjadvvtweoAOk/N8kM8ePlFNPzOxmG1PnAhHy+oH1Fp4sMrxzCl8gWIZp38eBfUJClH1lXaW29hrj8Vze0BfOjnzrTbYuvg7s8yStXfn6pVbSanENYlA1+nRHer1zj/hqHUffwmk5gQZJajPLjJerhrW79V7EK65L6BhDV8Ykqb2y1fJ4NT/naXQnRwlprU99A/AvZUElu3R/P5Q4dyzS+9zFwmd3+dYWsuDscADh9uNSPzGjUia+5ctpetxIz3/gkLd6dyzvHaaCxdQInVfIqbzRAiZP1fLjOvHVmtbVmlKZ23xYSgJFuMPt55O8c5ouNyT6q/fX5IoFuEU7JMRrBDXuWe6dQ1lwc+8Rymay1gNwa519/ApmeGKwFM1DD0+AgEiiwBlKuQH0O5Ccs/aS1bwrp1cIEtEhDRPuNkTsYllCa+/ldeSZk5XHih9SDF29xCvSIn0aEDZE35kA+xxeRH1b+HK5Y8yDk7xzGOzuY92SL+oe0dfPihP1t8EfFnrcqStWUL6+o05dAdsznmGHh7Rk1Krv2LDVXq8t7wPw0JGTLExj/On586D1ksjMVrJnN5Nie/CoyzjdW/2L3clWtLA57BhyYesH59TJ1WkYaQ5iZ87vFTTW7da9B82KUUe91qGH09ah7HXNyQ556zP2KytfhUkxe44adrzedTu77EkA1XhrclgyIdTiawW9vvQ84wW4hSVnA0Xc18pfzbkLDuvUVc5G7cFXAkDOKb/Tqa8nyyVnI/SOXWtjsGcMuwl3g+13qRpVLOq9lX0bq19RRLiTHJNs+pWYtSa5azrVotslcuNd5Y8Vqmcs7x3n9iEUB3qcfbeYzHTRl6TPUcSaTIq1aNc49fzdSp9gEkyO+8E28qoQSnM9XMszLrTD11t5C9iFg7pPass8KbA4F4yONdG3PcPfewoX9/JYAJgaYHRyNQpAlgQcsZyzt4Oa+Yeo/hNmUK5g6dohZrS2V3p47+gZYbcr/WXxvFemlOtmo3XuVVbH3RngwP17f04wfe7X16/7ua7Jv7l9Fla8Aik++xcFVZSuduIa9JE7J++snMKUgJGAdftwew/+ZeHD7NarE5FQDcVQEkgF8ygkuXJiyafMUVdsvUHf8n1/vUU7EfNvw0qYiklluvhRdEE16yPL43deqEbFx5JbRtC02nDGZQrtXaE+/x2OwLAy895mQCS23rHLLD8kzH8zW9GBImfU4lGTeWbpFoeV9iuRxJJ+c4P+y+oPV0xwAOPGI0t39vyesX5w1h4LZeYQ+giKRL1vUPiypRiQ38xiGcWf83RB80aE9ZQdcWXXFJiOoRGz/n07xdazA7GbVb92tAmwP/MElGIkckAv1BNYfAvswVXIF90Jet3zk0RXZPBmO/F115ndFcbF7LT4JI8gTpIY8bryeeYMNttykBjBswPTAWAnslAZQL3cU7eEoup03pR7HX/4spW+GIpaXILtzbRYWdUqoGSBKtO5hdbmg9Wu+a8HEDw8Kl2C7hv0yqcolvMYAybyf+7PfiB3PgzvlsLVuFMv+upWa1HFasyd8WZrpNTpB4xCC9HNExgPO63E2jt63woxPH9AqXh7X/GvGr0QR0SwqJN/aii+Dzz+267LefrbmbqmQDt71EeADfuIViQ6VEOHw3bDqH92gR9gDKe6MOfohL59lf4fd6TOS5Je0DLz3mLge3jspUZj1zOZhGzI3IcpfQBmc72Ll+SXiSMnAieu7EbrnrgQcaA/jcuxTvJOXZgf79yel7VzgGUN46u30e70zKJis3l02Njubig2aZtfBLs7Owe0xhnz/+uA3dcLeDyM/+f42u4RrrWyiNyBJLTfI2+/5ownKC9mo6BQOkMtE9WO++VJyZxFk8wS3cgv3enMxnfIEtoC0i0BJLmu4xgGayL7/MhiuvVAJYmCHr57tFYK8lgOm27hIvJl4lubmI7qAQuoKaeJzEk+Nu4vm5qetqVhudb1vZYWjriVz9V3+6/HSPee8c3mEi55jXfnhC3B7AEbMjA9oPqf4Pv62qas6d17YdWR/YctRBewDdhEnkWx6pNJB7Ntt6rJ0Ya0raueVrarKC9aVr0qpV/nZQEJp5BdmGew26zb+HG9fbGDghs7/XbxMRA7j8sr4Ue9xWQhCDyDmpZeClx5zYLJnSHzQw3mPxINVgFa/SLZz44RDxaBxkfRrxmykHt5NsJMFKYs4k9COoSiAyx7tOmEr/L20s7tJud9Jz3SMR4u+dz9zC25NsWb71R57KpbU+SWsCKJ4wd4UkqXzT/byNvPCG/GTYShqytZrNjrAO4zclT+S47TbMxo/7T0HfiVjvO3qxsh3/oqmRAJJE9zzX8SZd6MJb5r0G/MEirFi6tJtvLhoxgHz6qd0ClpsThgeGglUSQanoH+tvEdeij09hV6AEsDCEkvR5Ih5Ad/yfc3ohjO1a599sp9PCFDqP1gbcp9OpjBvnzxN4RAzgna3I+sRKvhxQYzMtD1vNy1Prm79XtexC9WlvpkUZOPeW6ddfw9jWwxnODWaeTiC7uyyUUzRevHtBlk3bndk5Xtj+5Qdw1yar+z65xzi6je0YzgKWGMB3615P+z9FUhTG3D6TUb8eE3gMoHtr8TuO5Eh+MDW5RVh4MmeEpV8kRnCD499I4DuYSuLh2JZ8X8fc9g0TVuaLiQ+p/xRSA1zIqcT/zp+xmm+X5D+83dRgIldfnb5bwJ06wfjxuwK/kfKmcsavNOJQfqUKa1kbqnAqcjDnl51kkqP8UCFIwAxwYk3b8kG4VrRkMd/Nw8i9swW26K+72ozEAEokhXj5U2lHiVyX+9gNGzZQSQRjlQDuKYQZ308JYIpMIJEYwFgeJyem5Z+sylTKy982e5brwnVRRfj0B440V+THDSwi/uzSjmGNmvdeWsGdV61mNs3MuT9vdBWzb3jRBMCLPExQEjAyFzdpffddWPpIfszkrWWeYfCWHkQTEckUdG8BB72d5TZRtwew/YKnuH+dzcrsymt8Wb9rWAfwxhvhmKe70y1P9OGhMb/we3bjwGMA3ckFbuJdls18Q3NTy1q2FMsiejWFP98HVZPZbVsDBsDUYT8zeXkTg7Xo5fWvP4LjjoM337Se5DMaLqR4wwPM53+1uohqk0endRJIOFYzK1LL0EnEWU9Fs31fh8UsRmoSgFRrcTxrftx/ErlVO9JbYve/YCuTONJCi6ljStm5hcTlc4mdHTHChngsWRJMiEci16gEMJ47RCKIZt6xSgBTtObRWXXRP1zuWKZYBNAhXxIvdTDzkfipUUPXcdKzXTnqt9HmKg5gAWsrHWCevv14Ao8QVX6mG0YrRdrcuQy/fzXXjz7J/CkxNrfxhJG5kFJrj4V2IVMEdcRp3DGAorm2bfTbvI3VbBm072P0WX17OItxNdWojtUVkmNFwzCosmkFYRURA/jTCIpdc5Vdgltf4KCBV0fEAH5R83xOXGnVxEf2X8xbX9UJPAbQ+R6IbbyZ05nO5MvY/MxhVOEffufAiGzf3dlN9Pcoldv1blH6/7RaxIipdivx79O70L3Mm2GsJSni+HI/UfxI+4C0vP1V1JjwYtqVgXPjLF480VGVOsbu9gmncipWSF1IewMW8jOW+ErCxZXY2JWgH5okflHiGMWj/y/lzJxEOPxkPmcrpclmJ1Jf+lhm7WJevXpZxYB0b0oAlQB6tVElgF4RjLN/LFkFp6uQDbnROiK9BW0BS9LyV9kncVyOTbCQOqjj6chZ2Hg7Kc+0Nquab0HMbjI1rvYNFH92uDnvi9fMZNwLq3mfs8zf3517P1+1vY9Jk4L3AMp8JAtY9OdkW7R1Xr4ouFP2bQ37GN1CN/G49VaQLeOgyqYVZFZuL2zZCaMpdqnNPP39+iE0GNrLCJ9XqwayM7T2uHYUm2wrNIhOSk6FKoHHALo94e7KEscwk1lYQXORbHJIRpxfr/BhqSaAUnNZ9CK7nrGG1ybbqhPrWrSnW9WJhgDKg50IDNdd9iVjV7Ywnw+hF0PrDUGSvSTjNEi5lN3hG11bV44dzUVchNXRPOOA39n+5wo+2WmTKAbTm1tNxdJgak27r8Vdf12UCuqx2Dw0H86PYY/leDrQifx9bgn7kHtcKm0oUft2H68EUAmgF/uRvkoAvSIYZ3/3D594P+RG4y4T5R5Gnj7lKdTdHAL5NvlekzpZS/lfXmeO4xtyyaIk2zm3U7ZvMYAyH4dMPZZ9J7fnPGqm2IqPqZG1mtF5F9kph1SshdQGWQbOwc+RgRECeHTuN0bmRZpUTrmRYeygxC4eAfEsib5cUGXTCjIrd0H4BUPe4cVVHcyhUuljdP1+RtnopZcs2f2+/MkcvtEG5U+fuo2BQ0oaUhJklqNjxxUqwP0b87MxRabJkTMSktEV69VOtKXS8+Rei1ee3cJvi22SxzRacmWDaeEYP3nvgspTGPOPrTf9Xfu7OWvWQyZeM9U6koniKdnvso3tNCF5vXnS/HkSn1OFdbyLzX6+m4d4GFsNJWgSJbqkUoFImuhMnsEU81pCJV7HiqM/zq271JdOh7nHu0ZKAJUAxmsrBR2nBNArgnH2350HUIZwb2XF8gA6wfPumL8LG37H0BUXUHPTgl2qb/gVg+OQqbuLD+DBHJuAIIK8+2ev5pkcm21niuaK1E4aZAG7vZY9esBNZ0VKWVzL82yigpnrx7SiNTY92y387BeWcZpOxGHubcd+x3/Mw19ZLctll/fjur8fDm87ihdw8hp3ksV2IzkyeLDVOkslUXJfgPt74K5t/SQ3i1/MHOqEEMSLj5Bd52FK5D/a2Aplvje3N7ZkiTxKlClOVl4eK+scQ9XfZxqPvtQnllJ1Z2way3OrzzNz6sujvNWgL/vsk94eQJmrc42nnGJLaIsA9GP0NdfRhTcpw5Ywcb+ep8P1moOyL2fR5bsuoujSRDP1Rp42r+Xh4mLeMK+v4flwhrDbWGLdf303pj04gRJAJYB7YDYRXZQAekUwzv6FxQC6h4n19OzIZ4xqcC+XLrS6VpLh9iYXmmDsP0s1pP62eYhnRSqH+BEDGLEF3Ho4xW+22bQiRv3cg6spe+9t5u/c0W9S7KIu5nXQOoDumDnZ1p07I79A/PuciRDAJdQ1cxXv6vnYmLmHH7ZCz+kmCitr4Gw73nrilzw+3W4rruhyM9f8+2SYAJ54Ikz5syFllv7OljJVOP2ItUaSJ+gyXe4s4O78H//Hf8z8v+BEk9UuLVYVEOf7Idt0kswzY4Z9R6r/CAEUaSVpjz4KfS0/8b25PYDPPw8/LqpIRTbyC41pX/+XsDdWSsFdV3Ykxa643Mxp3k1Pc+Dg69M6BtABzy12LckRpy3/b7gEnFTRyCLPlKSU5hbvTiURj7XQcg+URC5pIpDvZP5LgpHUBja2wzQ+peUu3SV2UO4V6d6UACoB9GqjSgC9Ihhn/2hl/d11i0UAnf7ylP00N5ruV2WN4KW8K83rGZzAiYR+FX3KAo5IApk/yta3AkSM+o7/rKb2yw+av2cPnESzPrZkXdA6gI4HQ6r+de8OxckhBytYLUHhPXg2nDn9PNeEM6rd2/Tp5AF0k45Ph81m0vLDzbW8wNUMqP+CiQGUfyecANMX7U+WaFrUrk3un0tMOcGgy3S5dQDdEh3uH2apWjKGC2N+RYTsnX023HknNGkCs2fb+E7ZTpUmxFfiNlPR3N5YmdPbX+5Hyb9Xsq1mXc4/5s8wGZf1qPTaM5gUbGlijJdfHvjDUTwYSTJIuXIYb6UkdE2+42M+xnqdH6Uv2ynJvSGh5XZMCpeqlMSvaCHpeM6XzGPOOQezBrJV/Tm2gom77cdyVrLfLu9rEkgyV8HfsQrXCfD3/EV9dCWAKVpB9w9fYafcXRKIux7nY9xOHwaZ4d7lbM7l3fDQfmzBRMjAfDzBBvhJNm3lhzmkyirOXWi38AafN52jbmhhfozlx3nOnOAC3R3CVKoUbNtm4REJC/HUSEmu6xke/kFzF4YXAigxgNL8wLIwGyjo84htxyULKHnoQebQ347qypJHX+MMG2ZmvGIbi1Wk3M6NbKrdiB9G/2pIU9BlutwPQs34kR85YpdLdVdniP5QMrOFeAmvdbdTT0W0cVNOAB1vrBDAMT9Yj+uOilXpfMrfEVnAJ3z+GMXutK7JOff/j8Z3n1ekPIAy7yOOgG0/5MuqjOQy1lMpvL3anK+ZSXNzjfKwEUtHcE/tfk/7iZbn+r+2sIGKlCD0hQaWUJu6LIk5rKzpsmV7esbU9VMPoHoAvVqbEkCvCMbZP9oD6JZ9iR5CNKxus7up4eZsIZ/KJ+ESWVIN5GzeM8f8H935D/9HnTpWw8qPIOyIqhqbplG8TStz7i9OuoM/vli2SxUHkZHYujVYHUAhCwx73zsAACAASURBVLVq5XuIZL5OVqDogN3EU7yJTV5xbz3KVqloGEpFOz+wjNNsdjnM7QEcO3wF3yzd3xwjGY1XVxvPmjW2S+VKeaxZn01xcsNyF5J1GnSZLncoRP2yq1j4b41drrE2S1hG7ZgQueP95AD5gZekKamrK+EGqfQ8RW8Bj1t0BEfwI1spRYOaW+nZ09bDPeQQ6LHyXm5enx+6Mbde27TPAhZ8nQcOqZAxbBhUyP2Hf6hi1mYKrVlFdS7hdfO3lOr7nYbm9WmnWW9zOrRDD4WXfz0eqTfttDFcwIWMiTk92TqWEJp0b0oAlQB6tVElgF4RjLN/dCUQ+SEUcjRzJnz4od0qdZpUDnjDximHm0Mg3cKmi4o1oH7uQnPMIG4LewPlbz9Ii1uEuOayb3l3xTHm3M/Qg7osDpPR6vxlStY5Yspvvw2dO8cJlA+HyXboV1/lD/w99odaKlD0Zkg4PkgyUUdi47Rky0sIU7rpALq3HS9ou4ExH5pKAPzTvA1nFpscvs7z2m3mfx+UN58tbHAal9ScGraxILe03QQwi1y2USrCMyNbweXYTB7FdrEEh/xJYoXYU7t2GMJ7331WikU+l++UJPCkorm9sSJ6XrfriTTfYcMwpERa7XrZ/PmnncnwUrfQc5sVlxt/2xdcN+rEIpEF7I4BbN5cpJHy+JeyJo5uDoexmLphGapDq6/h11X7mGsU6ZvvvkvFKhR+Drl3zrp0CEO4JXywZAOPxkooRbcaNWDlysLHDfoIJYBKAL3aoBJArwjG2V9+uKUWsLOt6O4mXgwJWl6/3r4rsU0//RQ5sGRvSmByrfLrWbqp8i5n7cNjDCK/ertfmWyONljzfRbw9d92+3FsyYvYb8efnJBnWewbI7dTs06JtNgCFtyrVoUNrkqZ7goUEsd0BwPNvM/mXd7j7F2wTactYHcSyLln5TDhfRvPuKFpCy6uM91UnRAitGn+CsoeZL2Da07sQIWPx1OvXvBJLdEVcZzKEg7oP9GEZkQZf+jDLl1gTGynjTki1ZIqbg9gv34wq1pbjlo92cxl5uR19H6gsvEgi7f/+dyruIoR5rOmzGZV9abUrZv+WcDuGEDxrl5+OWHh9LVUYWHWARyd9y07KWZkqHIpbq5RdPhm7aqxHOfdMrmHyTqdc9pGU2mmsakjfRJnlviYzTtiPylIApisZ7o3JYBKAL3aqBJArwgm0L9RI1M0wxBB8Y6tXRvZ2ZGFaNHCbj26m1PbUt6TG69UTHC3ixhttjLr14dFi+y2WLSWYAJTjXmo2wO49a/1/LTEElHZCmpQfAkH7ZzLxqyKlN2xHsnWlBZ0EkisGsxuLUV5fR5jzVyP50u+5vjwtTdsaGMX/fCm7ulaRG87/raoFKXYjng1z6r5fdhz0aTEXH7a0cicRkpgXVtmlPGOBakBKHNxewCFGL2d25GOTAjD8T/O4wL+FxMeeaj58UcrZSO26DSxtVtuSX3FGZnDgQda76NkIb9T6gKy3rZzz120mMZn1GHePDvLN+kSLpNWj0VGjDjojOx4bND9/XGkqoRAORnbf1PViKgvZz9qsTw8pMiwPGPLUAfeZJ1k7qXz/qURv/EDR8T0MDsTlVjhVHmRvYCjBFAJoBf7kb5KAL0imEB/pz5ldBfxUAlxc7ZMYsUxuQmgU7vWPc6JfMEMTjTeBhFg9sMDGBEDeEweWWVKUSxnhyEfh1dbRrE1q1lIff6cttDIc0gLWgYmVg3ml7gyXLLqR5pxOLPNXN0xTPK3kziSTgQwIgmkJORWqUrpf9exbt+GTHxinpOYzfHZs/gyx1bWGE5P+pQdHq40E6RHM1oOaWDxfvTZOSBsyn0YyCD6xPxWOQ814pUScrFggSVgEmsX1A/2gw/aLeiTToK3Kl1JzfdsKbSuzeYweratQSttEu1oh63KUpW1rKOKkWyS70eQ61HY7cuxN/EqS2LUjh3wOheHtfSc/tFl1UQDUWKA06XJw3X0A3esuUlVJlmTotCUACoB9GqnSgC9IphAf/nhEu+feGGik0CcvwuKY3KKs8vpxtIpooSRvOd4FZzp+BHnFZEFLOFlki63YgVLqUWt4ivJ2rmTbzmKea9/y8UX25mkowdQ4iWlVrG0fylDWbaY11VYGw5wdy9rOv1AR3sAP1tkC9svY3+OrrEsLIfy9YCpNL/TiuPNPP0Omk4cYHTpgk5qiSbkUkXGkRWRuR7NLL7j6JjfqpEj4bLLEvjCpeBQ53pEeLvfmvwqGScwg684ITwD0Tl0ZJokPnAn2eHP/PiuJuvSHcIuBFcSbUT56QHuDUu/OOdxqxCk0/avMz+xfbmWwpp4cuWBryg0JYBKAL3aqRJArwgm2D9WfU33EAXFMbmziKWEkVNzU/ruIJuy/BvWt5M6sCJg7GzDJjjFAg+P8AAeC1sObkb5PyLjtWQ7+LO7p5gtsXSQgZHtHwnqFjyc5q5m4LwnCSGl2RpzayidfqCjtefGzG5EmcVzySlXkZOarDf1i2Xdr6g6gRdXW5keKRP3er1+xiMTdFJL9Ja8JIJIPWuRMHqDC7nYlICz6l7uaizydzoK9LqTJF6qdR//WWq1MPsd9QEDvmsbtrnZNKUpc8wDR9VS/4YlieSBcNOm5H9Xk/WddxNAyex96CG4lFGMwmqAOs2toZlOHnNnflKX/CxbqtzEyBZUhlNiaM88M1no+TuOEkAlgF4tTAmgVwT3oL+QwETjmNw/nJLB9hqXRvy4ONuY8uZhh1ntvWQ3dwygZF+OWNSKVkyLOI3EOjnF4tNBBkYmJwLQr76aP81o/OQTkYZpwKJdIJMEnaVL0+cH2p0E0r49jPjpWGosnkVuVjGObpbDDz9a8tSzwiiGb7Q/0uNaDaPHzzeEvYNBejRl/hUrEt6ONj/I5FKDv1hJzTD5i2W7d9wBA/J3i5Nt3ns0njtJYmnvJ8i+w+o33VpnDIOXXBAec2nxetTauZj1ZWpw5hErwxnZsq0qsZnJfljbo4uJ0SlWCEXHml8xbmW+d1O6Da3+MG8e2M9cVzoSQLE7p0pSQdjI/Uq2f9N1LaLnrQRQCaDX77kSQK8I7mH/ROOY5AYmPxbSJFZtHoeEzyyCrJczMvy31Hx1KiPs4fQK7OZ4MMWrNqN2Fw749q2IY4dyU7ima7rIwLjjJ2Wybi1FZ/LRlVSc988/H96KvMRkQ5rQeM6DwCWXwJtvwgc5p3M6VnCtQtYmNuWVM6+vzxrO03n5pfpGZ3cznlARuA36B1q2CJ141915Y8TexQso8WTSpIbxqFEJweX7we4Hsx7ZL4brYV/JS7yMrdIjzUnckqznQwhlhoQ+SycPczRgzvWJ9I5k0st9SEIl1mLlXsLfk2JjGZvXyXjWgnzA2N2CSx1zEaYvqAUtV5WosSoBVAKYqM1EH68E0CuCKezveNQgj99KH8EhW23ywrX7v8sLy/PlS+RJ1y17kqwpuj2AIijc58+e9OTZiOH7l3+UBs/1NeLL6bAFLJOLJoDRBFqOeYvzw1ma7guS6hmSrZkuzR2ULx7AoUs6ccCP48302h+5nPe/t6Wtnqz5KDevvNO8HtHe/jjL9pa0oAlgtC6jG9vdEUKR5hCJjnRqbg9ZF96MKSou39ccIkW53deQroRJ5hhLSF3ej5bvacSv1D69kYmzS2dCKyRQStotXpy/AiKPJDsyQWqV7olNKwFUArgnduPuowTQK4Ip7C+Zwo6wbH0W8gD3GUmDIfSmZMksxKsoTW5oIgWT7BYdA7jkP/dRf6SNeXLaZYzkymmXhbOAg04CkXlJVnVfW4XLtLJsZjNWJNlpT3IzvXlyF8iuvRaeey7ZSO75eO6YLKm08Hf7btScYt1i4x6dS+c7DjavHy3Wj765dr/0dD7iyzKnG61JaX5kiCdyRQ0a5NunxKtKDJxb1qWgsYImrrHm5c5qllq4k7CBZvdzHw9w/y72JhqUjsfWGS+dCZPMUaqAPPWUna0kq0llk6E7etLmd/vwZyVglpl7kDz4iXRSOm+jiq19/rktJ7jffnDyyek934K+D0oAlQAmct+NdawSQK8IprD/o49i6rkW1iROSuKlkt3cWcDijZx/xwgaPX5VxGlaM4Xmd7Y2weLyIxC0DIxM7qKL7Hapu4l+WVXWhd/qyXCepecukEmN13fzSywnG9KEx3MIh2hKSuzYrYtu4AaGm3FaVZjJtI22OstT3BhRo3VWVvNw4LsfGpGJXIh4hmfMsNpsIlkUD/mTsIbly9Pvh3ryZGgbyvVowXSmc5KBYjC9w4laNVnBCvJL9nXCemylpbp6SSLr5BzriNC7+x7I73zOyVRnFVdlvcwrebaCzgMP2PJ32vxHQAmgEkCvVqYE0CuCKewvHj7Rpius+SVkGi1BUn/RNKZh6wE7TUrV/UZjI3T9yitQuzaIsHWQXo6mTXdNivmUUziFz8PzPo2p4RrL7us54gj4/vvCEE/d5+4tRyFFr9fvx+nfWE9f+9If8/5Wux6vcHk4LlS25xaWbBT2EActp+LWw5Rye6IZ+euvsROXHPHhdI3Pkm1pJzHlMOYwh6YG/5Elr+Ty7S+Z1wczl7lYUe7oeF15L8jvRjyWGx1C4fQpz0aTOb+GfcPDpPN2djzXWpSOUQKoBNCrvSoB9IpgivvvqYxMMqYZLUFyYPFFPDmhQXjoHIobOZod5JdYEqFe8fIEuS3keJzcGMiW782E9rWiNACFtErmr7TGjeGXX5KBXnLGcDyAstUmW1h9cgcwAFu3qgPjeYcO5rW72sn+LAt7oOSzoOVU3HqYhaEiYQ+igZmu8VmtWlkCJ61B8cX8sbOeeT2GC7gQW7fuGGYyk+bm9dNcH/bMOtee7qSpIAIYa+3ScZu+MBsrqp8rAVQC6NV2lQB6RTCA/kIC5UfcrWUlsTlSK1ji3fxqbgkS0dSa/H4OWylFcXLNKedyMIcVn8sBB1jC57TbbgPx+gTVYlVgac7X4bJv73EWZ/OeyZKV7FqJkZPyXtKEgCxcGNTMdz1vdCUN2boejs32lfjL/2KVkkWPsTVW+bYCG9hEhfBg6SCnUtiDjGy9iz2ne3yWyAQ5GfeV+cdU+JD2Q422HPnXB+a1W+z6Ee7kLiKzitKdNBVUwSjWtyLdryV9vsneZ6IEUAmgVytSAugVwYD6Jyojk4xpureAhWiuWxdZ4uplrgiXWHOfL2gtvYI8Tu2ZyKH8wvNcywYqhafszkSNVZc5GVju6RhuQXCH9I3Exl+54xi/pjnNmUkuWWSTEyFw3bUryDhBtz3Rwwx6ztHndxPAksV3sm2n1WqaU/EEmm6YYV53ZBzj6Gxe31tiAAOz7ghvx8t7H34IZ5yRbleWPx9JoIr3wTLdvZnpi3LiM1MCqAQwcauJ7KEE0CuCGdTfnQQilT6++QZO4VMm0IEtlOHc8tOYtakRUts4uu5m0HFOhXmc3MvoJoCx6jIHueTRAfmy7TueTmZKdzCAgdjsn19oTGN+YwMVqMSGiClLWawpU4K8ivxzB/Egk8wrP+ccmDgxf8SNlKc8m5nDYabyhzTxzEaTdNE4zMmx/cQ2Bw5M5qySO1a8ZdTkrOoBTC72uxtNCaASQK/WpgTQK4IZ1N/tAXRnI5dmCxUqZ7P6nxJhNJzgfeeNdPAMxPI47W750jFD0x2PJSTi3ApTeXudrfnr3l409ZlZztoytTjlgKX8/HP+lXboAOPzE1EzyIKTf6kiYSO6m06Tmsz7s4Il1KYuS8zb1/M0T3OjeS1l1JwqPg4JPOoo+Pbb5M8tWSPGiqEtaGwlgMlCvfBxlAAqASzcSnZ/hBJArwhmUH+JAZSkDomPq1sX5s4t+OKjBX2D9gA6M3V7nIQUOQH8sa6koLrMQS75PfdA//75M2hRYibTd9gEg2HcwE0MM6/F81eBTcYTeBiRWSySVHHLLUFexd51btHFmxcq7vErjWjEXNZTkcqsNxd6J4/wCHeZ1+cygQ9KnMuOHVaDThJ5pDLKrFnpi0kiHsCgNSbTF8Xkz0wJoBJAr1alBNArghnW/8EH4b774OCD83/0CoNApD7khy4dxWGLWhxadBKIW2LkVbrRnVfJZkc4E3s6LTiJ6RFL5JdMUGF2sLd+7l6TWLGXj9KXvtjsrJZM44dKLVlvuaFp110Hz0YW1EkrqC6+GN54I74pBa0xGd8s946jlAAqAfRqyUoAvSKYYf2dOMCKFeMvN3faaSBVK9K1FaU4NPHCli6dHz/WuNJyfllfy0A7lk6cx1j2ZRWrqGHem0h7ziE/SK15c/j663RdiaI5L7c248dZrWmVF5l9/QJXczVWE/BwfmA2h0dcqNQ6FmH1dG1SgznepKGXX4YrrkjXK9m75qUEUAmgV4tWAugVwQzr78QBJnLZ6ewBTOQ60uVY0cQbN87OphybwhIvH3E6bfgoQnh4FJfSDVsqTlq6JbWkC6Ze5uF4AEUzcvCizrTbYhenNkv4u3RtRm09n/N527xXh8UspU74dEUhHjMRHcB0q5zjZV3Tva8SQCWAXm1UCaBXBDOsv3jLypWzZbyc2rIOBCVLEiFv4YYmXWIA94blivxBziOHbKPFOJNjjPTLcXzFV5xgLlVKwrkFr6VyxcMP7w0opM81uOszTzvoKrJfGWEm14wfqXNWM/p80IpTc61atFTPcOpQS3LFF1+kz3UUNJPosIPdzVgEyh0R9fS/sqI9QyWASgC9WrASQK8IZlj/PfEACkTpkAW8tyyVJHGIuLbTVlONavzNAg7gIBbQjklM4izz8f3cx4NZ94dFw+++G1OnWVvyEHBvAT+e3Zdbc2y8n1Ne8DuO5Eh+YDslKMU2mjXLYvbsovOdkLADeeBzC8876LnlbOS9OnVg8eLkYasjFYyAEkAlgF6/H0oAvSKYYf0dIWLJBl6wIP6LVw9g/FgVduSoUdCtmz3qyCNhzI8Hc1DufNZRmaqs42Je53UuMZ/fzJM8XexmxDu7dWv6iw4Xdu3p+LnzUCSZ7/2KD6R/jtViPI//Mb7YefyRW496LGZD2Rpc0mplWDewKH0n2rSxGn+FtWuugeefL+wo/TwZCCgBVALo1Y6UAHpFMMP6P/kk9O4NIg0Rzw+CwFO5MqxZk55ZwEVx+Zw1cOY+gxM4ga/Mn5IBfB3PhXXnRrd7lV7fdQuXtlOdtuSvuBMWsc8+sOS+lyjR82pzkt5ln6f/qmvIq1CB8nmbyDukETvn/IrUmv77b9i8GUPMi0KTcI+yZXedqbwnDxZS71tauie0FAWs452jEkAlgPHaSkHHKQH0imCG9Y8uRVbQ5bt1AJUAJtdInDVwyMPY7e1pz/vmJNVYTQ+e5SHuNX+fwzt8XOaccLym6rQldy1kNHdYRP+jx3HXt7bsm1RmGbXvrSxbbVneH/u14Oajp/Pee3Y7tSh5AGX+HTvChAkF41cUElqSv/rBjagEUAmgV+tTAugVwQzrn0hAuBuaovZjl87LGh2HOSqrG5fm2UzfQ/iNa3meWxhi/j6Jz/mq+ElI6b7Jk0F12pK/sk4M4M03w+ynP2XqzpbmJIO4jUHcHiHJ0yl7ItdfD0OHFp0YQDdiBZFAJX/Jt6vCRlQCqASwMBsp7HMlgIUhpJ9HICAkom3bxEHRJJDEMSuohwTl16hhtxGlDaEXvRhqXp/ADK7lBbrzivm7X4efmZ1zqPE6SVMPYPLWwRnJHQPY4+Q5DP+sqfloBP9hRNU+zFjbyPw9s9FlPHjQyCIZA+hGTbaDpUrO/PnQsCEMGpTeOobJX/H0GFEJoBJAr5aoBNArghnWX2oAP/po4RedrqXgCp950Tji8sth5EgrCn0PD9Fvq93yPZt3uZoX6cA7lgB2X85Pa/YLkw6NAUz++rpjAP/8agWlGuxvTvJeiQ60fL8v5dq0MH8v7ngTNd4YSr16RS8GMPmo6YheEVACqATQqw0pAfSKYIb1l63ERKt6FCtmNQOLSsB7UVhStxZgT4YznBvMtLvxqokBdJJCSrCdqtVLULUq/PabTdyRNdSWPATcW/KVSm/jn62lzeCfcTKP0YeJnGP+vo/7GVTmPpM0URRjAJOHmI6UDASUACoB9GpHSgC9Iphh/Q87DH75JfGL1hjAxDHbXQ83AbyQN3iDi83hvRnMjQzjABbyN1VpVO1vk4HteGR1Kz656yCjOTGAgrF4ZFdtKU95NvMzhzKYWxjBVeak1/Eso8peZzJlpelaJH8tMmlEJYBKAL3auxJArwhmWP8GDWDRosQvWmPPEsdsdz0k7qpPH3tEGyYzGRuY2Z+76M0QyvEvv9CYw/jFyHeI9/Wff4pe5mlyUfNnNHclkClTYFP1BlTbuIi1xfahTL9bKNP/LnPi59qOpfv4TkZCafp09cb6sxqZM6oSQCWAXq1dCaBXBDOsv5SvmjEj8YvW7NPEMdtdD3cs5uH8wA8caQ4fzUVczBvm9TRack65afTtC/feC/vtB0uWqB5jclcCHALYqJHVxPvvohM5EfsleSHrGq7Je8G8lgSdFfVOoEwZ3Y5P9hpk4nhKAJUAerV7JYBeEcyw/o8/bjMAE22vvAKSuKAtOQhceCGMGWPHEu2/1VQ3r+dyMIcwz7x+gwu5sdobZgtYWq9eVgZGW3IRcJeCk+zsiWW7cMzCt8xJvuFYU59Z2n9a/sH7vzbgr7/s+XULOLnrkGmjKQFUAujV5pUAekUww/pLxmOpUolftGifPf104v20R2wEjjoKvv/eevN27sxjK6UpxfaIg5/kZnrzpFmvbdt0y9EvW3I8gI0b2+oevRfny/LkUJxsdppTl2UzO7LLGgmfZct0Pfxaj0wZVwmgEkCvtq4E0CuCGdj/+OPh668Tu/CePWH48MT66NEFI3DIITDPOvpM+4MGNCAyOLMPAxlEH+TYuXOVcPhlT9FbwOcvGmRwd7eNlKciG8NkXD7TjGy/ViQzxlUCqATQq6UrAfSKYAb2dycgxHv5GgMYL1LxHSeJBEI8nPY5J3ES0yM6X8AY/scF4fd0yzE+bBM9KnoL+MFDXuOazy6NGOYnmtCMnyLe08SoRJHW490IKAFUAuj1G6EE0CuCGdhfkgoeeyz+C8/OLlqF7+O/suCO/PBDaNcu//yvc3E4+cN592hm8R1Hs88+VnhYPU7+rJd7C1jiLQ9d/QmfcFrEySZwLh2JLKQr8bS33urPnHTUvR8BJYBKAL1auRJArwhmYP/TTgMRv423SdJIIoQx3nEz+TgpByfSLrm5FoW7eYiHsNVAnFaVv1lHVSpWhA0blAD6ZS/uLWAR267JClZgq4E4bTC9ub3Y4PB6yfv6vfBrRTJjXCWASgC9WroSQK8IZmB/RwtQKnyId08SQwpqt91ma4VqSz4CnTvDuHF23I6MYxydwydZSi0OLLk0Ym10Czj5ayAjureA7RnyWEM19mFt+IQ9eIbn6BExgaOPhlmz/JmTjrr3I6AEUAmgVytXAugVwQzsH52AINVBmjaFVavsD5p4m6RJtuPKlRkIUIou+YknQAi2tLr8yZ/UD595LJ04j7Hm7333hdWr1QPo17K4S8E555jKaZxGvpv8KL7le45SAujXImTguEoAlQB6NXslgF4RzMD+114LL1htW+MBzMmJDcI118Dzz2cgQCm65Ndeg0tduQafcCqn8pk5exfe5C26mNf77w/LlysB9GtZZDu+fHkrAu20XgxhCLeYP1dSg9osZSfZIdkee1SPHvDMM37NSsfd2xFQAqgE0KuNKwH0imAG9t+yBVNeTJpTY9aBwf231DyVqgfa/EHAiT1zRhcv4N30Zw5NeK7ETWzfkRVxYt0C9mcdZNQKFWDTpvzxRfPvXc6hCXO4gv/jfdrvcnL9fvi3HpkwshJAJYBe7VwJoFcEM7R/x44wITKpMQKJDh1g/PgMBSdFl+0QQCfLt6DT1qljS8BpFrB/CyMPRPJgFG876CCYPz/eo/U4RWBXBJQAKgH0+r1QAugVwQzuXxAJVPKXGqOITj6oWhXy8mDdusjz6xaw/+tRq5bdZo+3SfzmLXaHWJsisEcIKAFUArhHhuPqpATQK4IZ3l+8HiJnId6Mhg1txq9u+6bGKBwPoEPw3GetXdvGZrqTcHQL2L91efhhuPvu+McfORIuuyz+4/VIRSAaASWASgC9fiuUAHpFUPsrAgEh4BDAJk1gzhyoXt1uQ27cGDkh3QL2f4GiE3IKO6NWxikMIf28MASUACoBLMxGCvtcCWBhCOnnikCaIrCr/lzsieoWsP8LGEsKZndn1TJw/q/J3n4GJYBKAL3auBJArwhqf0UgIAR2RzpKl46UJZEp6hawfwslUjA1a4KUgotuIhGzbRvs2JH/ybRp0LKlf/PRkfd+BJQAKgH0auVKAL0iqP0VgYAQkAos5cpZDbp//oG6dUGkRaJJiAh3z52rWcB+L9P998MDD9izCAGXtZEazE5zNDOLF7frJKX8tCkCe4qAEkAlgHtqO04/JYBeEdT+ikBACER7AKXyiniZ1uZXIDMzE2K4eLESQL+XKVqXMfp8bo1M9QD6vRp7//hKAJUAerVyJYBeEdT+ikBACDgxgO3awQcfRE5C6jTLFuPUqfnv6xawvwsVb0ymzELXwt+1yITRlQAWTQJ4FxhZ+COA7UDlGMZaF3gWOA0QfflXgTsBd9GtZsBw4FhgNTAMeCxBw1cCmCBgergikC4IxPIAivSLe9tRPYCpWy33ekRXyClVysYBOk1FuVO3LnvrmZQAFk0CKFEi/wC1gStjEMDiwA+mhCTcDuwHjAReBPqFjFmI2zzgI2AA0BR4GegFhKq0xmX2SgDjgkkPUgTSD4HoGMDGjWHzZrvd624aA5iatZP1kNg/EeNu0QI6dYLp022ZuK5doVs3WC2P6nLj/ghOPz0189Kz7J0IKAEsmgTQscbuwJMxCOCZwESp4Q78FTr4OmAgsG/Ia9gD7fw4gQAAElZJREFUeBioGfpbDnsU6Ag0SsDclQAmAJYeqgikEwKxsoArVoT27S3REJLhbrrt6O/qJSIFo2vh71pkwuhKAPdOAvggcG5oi9ix4wbAH8BRwPchj6CQNyF8TpPtYon4qQpEFYMq8OugBDAT7hR6jXslAk7MmXiaxo0r+BL32w9WrFCvk99GkEgMoCaB+L0ae//4SgD3TgIoW7j1gLYuEy4LbAbOAiYBk4GFwLWuYw4Ffgbk/78WYP6lAPnntArA0vXr11NRXAfaFAFFoMggoFnA6bVU7ixgqcrSuzdMnAgSD3juuTB2LHz1FagMTHqtW1GdjRLA9CGAsv3atxBDagz85jqmoC1gPwng/cB90fNUAlhUbwE670xGwIkBLFsWNmywSFSqBFddBTfcAM2aRZaF021Hf61FZWD8xVdHj0RACWD6EECJzdunEAOVLVzJ+nVaQQTQzy1g9QDqXUQR2EsQiDfmTHUAU7Pg0VvAJUpEVv9wz0LJeGrWZG8+ixLA9CGAe2JnhSWBSPbvqtDA1wCDgOqAiAk4SSA1AKfA0CNAZ00C2ZOl0D6KQNFDIN6YM60FnJq1dXsAo2VfqlSBatVg/nw7F80CTs2a7M1nUQJYNAmgaPxJooYkeojMy8khI/09pPnnyMAsB/qEMn1HAS+5ZGAqAXNDsYCSHdwkJAPTW2Vg9uavvF6bIpCPgEM4HJkX+cTZAr7pJmjVChYsyD9evU7+Wo+bAMqarFoF61zpeFL6TbbtlQD6uw6ZMroSwKJJAF8BLo9hpJLF+0nofUkCESFoKRcuyR8iBH3HboSgpQS5CEELGUykaRZwImjpsYpAGiHgEI4mTWDOHKhTx8YCrl8fOUl5f8kS9Tr5vXS788hGbwcrGfd7Nfb+8ZUAFk0CmE6WqQQwnVZD56IIJIBAvFvABx8M8+YpAUwA2j06NN6YTPUA7hG82ikKASWASgC9fimUAHpFUPsrAgEhsDvC4d5udKanXid/F8pdCST6TFKbWdZk61b7icYA+rsWmTC6EkAlgF7tXAmgVwS1vyIQEAJCOEQCJjfXlh/r3h3eesuWg3O3ypXhn39AxYf9XahEPIBKxv1di0wYXQmgEkCvdq4E0CuC2l8RCAgBN+EQceGdOwueiFQDkThAOU6bPwiMGmXr/cbTlIzHg5IeszsElAAqAfT6DVEC6BVB7a8IBITA7mIAy5SxFSj+/ddOrlcvGDIkoIlmyGl79oRnJXUPu917/fXWMyvSL9OnWy+stAoVbHawkvEMMQyfLlMJoBJAr6alBNArgtpfEQgIAbcHUHTnZEtYCEesNnkytGkT0EQz5LRS7u3dd0Hi/WQdzj4b7rwTJEv7++/h1FMtEMccAzNnZggoepm+IaAEUAmgV+NSAugVQe2vCASEgGz5iriw41nad19LMjZtsh6mWbPyt4WfeAJuuSWgiWbIaYXYffttPslbtgxWrNj14o8+2q6NNkXACwJKAJUAerEf6asE0CuC2l8RCBCBtm1BvHuFtR494JlnCjtKP/eCQIcO8M47NjFHiPnixfmj1ahhNRq3bAHxFE6Y4OVM2lcREHvaQCVRfgf5T6gaeGYhk5VZl5v0q1UCmHRIdUBFIHUIdOoE48cXfr6OHWHcuMKP0yP2HIHBg+HWW23/6tXh0kvhgAPgjz/gv/+1lUGkqTd2zzHWnvkIKAFUD6DX74MSQK8Ian9FIEAErr0WXnjBTkBiz44/Ho44AtautZIwTmbwNdfA888HONEMOLXEYEryjcjySAKOOx7T+VvWSLyAkiSiTRHwgoASQCWAXuxH+ioB9Iqg9lcEAkTgnHNg4sR8r9NDD9nkA3nvnnvyvU7yniQoaPMXgT59YNCgXQmgED8hhrffDo895u8cdPTMQEAJoBJAr5auBNArgtpfEQgQAckw/flnyM62Hie3FqC8Jy0nBw47zNYL1uY/AkICZTvYvRYi+SJJOEr+/Mc/U86gBFAJoFdbVwLoFUHtrwgEiMAhh9g6v9Ik7kyygMuVs9VAPv003wMo9YDnzg1wohl2atkOlqSbBQvgwANBNAJ12zfDjMDny1UCqATQq4kpAfSKoPZXBAJEwIkBLMwDqDGAAS6SnloR8AEBJYBKAL2alRJArwhqf0UgQAQkoUBkR6SJDmDLlvkeQBGKXr3afiYVQSRBQZsioAjsHQgoAVQC6NWSlQB6RVD7KwIBIyASL7vTlRN9unikYgK+DD29IqAIJICAEkAlgAmYS8xDlQB6RVD7KwJpgEBBJFDJXxosjk5BEfABASWASgC9mpUSQK8Ian9FIE0QkO1gkRmZPx8aNrRyJLrtmyaLo9NQBJKMgBJAJYBeTUoJoFcEtb8ioAgoAoqAIpBiBJQAKgH0anJKAL0iqP0VAUVAEVAEFIEUI6AEUAmgV5NTAugVQe2vCCgCioAioAikGAElgEoAvZqcEkCvCGp/RUARUAQUAUUgxQgoAVQC6NXklAB6RVD7KwKKgCKgCCgCKUZACaASQK8mpwTQK4LaXxFQBBQBRUARSDECSgCVAHo1OSWAXhHU/oqAIqAIKAKKQIoRUAKoBNCrySkB9Iqg9lcEFAFFQBFQBFKMgBJAJYBeTU4JoFcEtb8ioAgoAoqAIpBiBJQAKgH0anJKAL0iqP0VAUVAEVAEFIEUI6AEUAmgV5MzBHDJkiVUrCgvtSkCioAioAgoAopAuiMgBLBOnToyzUrAhnSfrx/zy/Jj0AwasxawNIOuVy9VEVAEFAFFQBHYmxBoACzamy4o3mtRAhgvUrGPE/z2BzZ6G8b0rhAik7WTNF4SppQxQyj2wS614h8c/op9cNjrfT89sFcPYLDroGcHzHZyJrujA7QCxT5A8NX2AwVfbT9Q+PW+HyD8GW/76gEM0PqiTp3xxhjgUij2AYKvBDBQ8NX2A4VfCWCA8Ge87SsBDND6lACmDfgZfyMIeCUU/+AWQLEPDns5s+IfHP4Zj70SwOCML/rMpYA7gQHAtvSZVkbMRLEPdpkV/+DwV+yDw17OrPgHh3/GY68EMDjj0zMrAoqAIqAIKAKKgCIQCAJKAAOBXU+qCCgCioAioAgoAopAcAgoAQwOez2zIqAIKAKKgCKgCCgCgSCgBDAQ2PWkioAioAgoAoqAIqAIBIeAEsDgsNczKwKKgCKgCCgCioAiEAgCSgADgX2Xk14P3A7UBH4EbgS+SY+p7VWzOCWE89HAfkAnYLzrCuX78ABwNVAZmA70AObvVSgEczGS4d4ZaARsAWYAfYG5ir/vCyI2LP/qh870M/AgMCn0t9q970sQPsEdIaWHoUAvxd934O8H7os6i9xz5D4kLaNtXwmg7/ZX6AkuBEYC1wFfh24KFwCHAKsK7a0HJILAmcCJwLfA2BgEUAiJEJXLgYXAQ0BT4FBgayIn0mN3QeAD4A1gJpANPAI0CWG7OXS04u+P4ZwD7Aw9yMg9X+xbHjiPBIQMKu7+4B496rHAGGADMM1FABV///AXAng+0Np1ihxgjd5zLPvVFiwCQvrkR/GG0DSKAUuAYcCjwU5trz57XhQBlO/CcuAJ4PHQlUuNyL+A7iHyslcDkuKL2zf0gHMq8FnoSVzxT90irA2RwJfV7lMCenngO6AncDfwQ4gA6n3HX/iFAHYEjohxmozHXgmgv8ZX2OglgX9DTyjurchXQ1uQHQobQD/fYwSiCeABwIKQV0Ruzk77NHSzvnmPz6QdYyFwUMgjJR7WOYDinxo7KQ7IDoPcY8QDKJ5ttXv/sRe8hXT3Bj5xEUC1e3+xFwIo3u71IVv/MrTLs1jvOeoB9Nf0Ch99f2AZ0AIQw3TaY4B4Ro4rfAg9Yg8RiCaAsgYS8ydrssI1pmzZyLGyVa8tOQiIl/ud0EPOSaEhFf/kYFvQKEK05R5TGtgEdAXeD9171O79xf4i4C5AtoCFcLsJoNq9v9hL2I94XyXuT+K+JR6wVij8RL4TGW376gH01/gKG10JYGEI+fe5EkD/sC1s5GcBuTEL+VuqBLAwuJLyuew21AUkrEFioq4KPWQ6yU764JMUmHcZpA4wC2gDzA59qgTQH6zjGVXs/U/gFuBXJYDxQKbH+IWAbgH7hWzh4+oWcOEY+XHE04CENkhGtiTaOE23wvxAu+AxPwpt/Q7ULWBfgZf4s3GhJBznRLINL/ef3FCy3+8aeuLrGkQPLjH3Yv8vZrrtqwcwpXYX82SSBCKSLyL9Ik22xyQ+QX4oNQnEv/UpKAlEEkAkEURaxVCigiaBeF8HuddIYpNI77SMIa3jBGQr/t6xjmeEqaH7zBWhJBDFPR7UEj+mAlAvqtv/Ab8BQr4lC1uSnxT/xLHdkx6yHSxJlrIVLPejjMZeCeCemFBy+0hsmQQIXxsigqIN1SWkUyQZqNqSh4B8+SX5QNr3oW0AkWOQ4Gwh3SLHIDpdbhmYZioDk5QFeCYUdybeP7f2nwRniy6gNMU/KVDvMsiAkOaf2LgQEon/E6zbAlMUd39A382o7i1gtXt/4Rdi/W5o21fCHETnVTKCRdprdabbvhJAf40v3tFFAsYRgpYM1JtCmoDx9tfj4kNAPE9C+KKbEHDx8jmioNeEEhS+CMk2zItveD1qNwiIxzVWEw/UK6EPFH9/TGgEcHooCF4It8SiifdJyJ80xd0f3AsaNZoAKv7+4S/aoxJusk+I8Mk9XRJyJPM9421fCaB/hqcjKwKKgCKgCCgCioAikJYIKAFMy2XRSSkCioAioAgoAoqAIuAfAkoA/cNWR1YEFAFFQBFQBBQBRSAtEVACmJbLopNSBBQBRUARUAQUAUXAPwSUAPqHrY6sCCgCioAioAgoAopAWiKgBDAtl0UnpQgoAoqAIqAIKAKKgH8IKAH0D1sdWRFQBBQBRUARUAQUgbREQAlgWi6LTkoRUAQUAUVAEVAEFAH/EFAC6B+2OrIioAgoAoqAIqAIKAJpiYASwLRcFp2UIqAIKAKKgCKgCCgC/iGgBNA/bHVkRUAR2PsQODtURF7qiF4CzN/7LlGvSBFQBDIBASWAmbDKeo2KgCKQLATmAtcDhwEnABcla2AdRxFQBBSBVCKgBDCVaOu5FAFFoCggIIXjfwWaA4uiJjwD6AocDpwHdHN9LoXnZwJPFIWL1DkqAopAZiOgBDCz11+vXhFQBHZFYDBQAbg6Bjjy3nPAX0ATYK3rGPn7M6ABsF6BVQQUAUUgnRFQApjOq6NzUwQUAb8QKAlsjzF4WWAF0Bb4KurzbOAH4N3QNnAlIC/qGPEAvgIM92viOq4ioAgoAslAQAlgMlDUMRQBRSDdEfgEmAPkAJcCPwGnxZj0+cAzQPUYn90AnAH0BJYABwELoo67F2gDnJzugOj8FAFFILMRUAKY2euvV68IZAoCQgCPBp4FRoQuWhI6ottQ4GDgzKgPqobiAluG/v8PcCXwdtRx7YAJQEVgW6aAq9epCCgCRQ8BJYBFb810xoqAIpA4AkIAhZQdVUjX8cDfIXLnPnQYUAK4LvSmJIN8BIjHz92aAT8C9YE/E5+m9lAEFAFFIDUIKAFMDc56FkVAEQgWASGAotkXK7HDPbMPgd9DMX7O+4cC04HGwMrQmy8ANYFzoy6rITAPkD6SSaxNEVAEFIG0REAJYFoui05KEVAEkoyAEEBJ4OhVyLivAXJfFKkXpwkplNi/na73ioXiAOtFjXdcKHlkX2BNkq9Bh1MEFAFFIGkIKAFMGpQ6kCKgCKQxAvESwNtCSSJHhK5FKn9IVm/rUAKJc4nHAi8DEhu4znXdEhd4P1AnjbHQqSkCioAiYJ50tSkCioAisLcjEC8BbAp8F8oC3hTKHBaiNzAKoLqhGD/JJJaxnSZkUTyFQgS1KQKKgCKQtggoAUzbpdGJKQKKQBIRiJcAyim/Dnn3ygF9gQOAzVFzkXunEMS7gCdDn5UOxQhKJnC0hmASL0WHUgQUAUXAOwJKAL1jqCMoAorA3oVAe2BQqNJHbgKX1gPoFIoXTKCbHqoIKAKKQOoRUAKYesz1jIqAIpD+CEiyiGj8ieBzvO0q4HMglr5gvGPocYqAIqAIpAQBJYApgVlPoggoAoqAIqAIKAKKQPogoAQwfdZCZ6IIKAKKgCKgCCgCikBKEFACmBKY9SSKgCKgCCgCioAioAikDwJKANNnLXQmioAioAgoAoqAIqAIpAQBJYApgVlPoggoAoqAIqAIKAKKQPogoAQwfdZCZ6IIKAKKgCKgCCgCikBKEFACmBKY9SSKgCKgCCgCioAioAikDwL/D2k8v6ghNebSAAAAAElFTkSuQmCC\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gcalc = mfit.evaluateEquation(\"mpdf\")\n",
+    "\n",
+    "# Plot just the mPDF\n",
+    "ax=plt.figure().add_subplot(111)\n",
+    "ax.plot(r, d, 'bo', label=\"mPDF data\", markerfacecolor='none', markeredgecolor='b')\n",
+    "ax.plot(r, gcalc, 'r-', lw=2, label=\"mPDF fit\")\n",
+    "ax.set_xlabel(r\"r ($\\AA$)\")\n",
+    "ax.set_ylabel(r\"D ($\\AA^{-2}$)\")\n",
+    "ax.set_xlim(xmax=mc.rmax)\n",
+    "plt.legend(loc=1)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now refine spin direction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load the data into a Profile object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "PDFguiFile = 'MnOpdfgui.ddp'\n",
+    "r,d = getDiffData(PDFguiFile, 0) ### extract the fit residual from the atomic PDF fit done in PDFgui\n",
+    "\n",
+    "from diffpy.srfit.fitbase import Profile\n",
+    "\n",
+    "profile = Profile()\n",
+    "profile.setObservedProfile(r, d)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make the magnetic structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "struc = getStrucFromPDFgui(PDFguiFile,0)\n",
+    "\n",
+    "svec = np.array([1.0,-1.0,0.0])\n",
+    "msp = MagSpecies(struc,magIdxs=[0,1,2,3],ffparamkey='Mn2',rmaxAtoms=50,basisvecs=svec,\n",
+    "                kvecs=np.array([0.5,0.5,0.5]),label=str(0))\n",
+    "\n",
+    "mstr=MagStructure()\n",
+    "mstr.loadSpecies(msp)\n",
+    "mstr.makeAll()\n",
+    "\n",
+    "upMask = (np.apply_along_axis(np.linalg.norm,1,mstr.spins-svec)<0.01)\n",
+    "downMask = ~upMask\n",
+    "\n",
+    "### Visualize the magnetic structure\n",
+    "uc = struc[:4].xyz\n",
+    "visatoms = uc.copy()\n",
+    "visatoms = np.concatenate((visatoms,visatoms+np.array([0,0,1]),visatoms+np.array([0,1,0]),visatoms+np.array([0,0,1])))\n",
+    "visatoms = struc.lattice.cartesian(visatoms)\n",
+    "visspins = mstr.spinsFromAtoms(visatoms,fractional=False)\n",
+    "mstr.visualize(visatoms,visspins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make the MPDFcalculator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mc = MPDFcalculator(mstr)\n",
+    "mc.rmin = r.min()\n",
+    "mc.rmax = r.max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Set up and perform the fit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from diffpy.srfit.fitbase import FitContribution\n",
+    "mfit = FitContribution('mfit')\n",
+    "mfit.setProfile(profile)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Define an mPDF function that will be added to the total PDF calculator\n",
+    "def mpdf(parascale, ordscale, damp, th, phi):\n",
+    "    mc.paraScale, mc.ordScale, mc.dampRate = parascale, ordscale, damp\n",
+    "    newvec = np.array([np.sin(th)*np.cos(phi),np.sin(th)*np.sin(phi),np.cos(th)])\n",
+    "    mstr.spins[upMask] = newvec\n",
+    "    mstr.spins[downMask] = -newvec\n",
+    "    dr = mc.calc(both=True)[2]\n",
+    "    return dr\n",
+    "\n",
+    "mfit.registerFunction(mpdf)\n",
+    "mfit.setEquation(\"mpdf(parascale, ordscale, damp, th, phi)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from diffpy.srfit.fitbase import FitRecipe\n",
+    "recipe = FitRecipe()\n",
+    "\n",
+    "# give the PDFContribution to the FitRecipe\n",
+    "recipe.addContribution(mfit)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<diffpy.srfit.fitbase.parameter.ParameterProxy at 0x7f01e8787190>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# add the mPDF variables\n",
+    "recipe.addVar(mfit.parascale, 4)\n",
+    "recipe.addVar(mfit.ordscale, 0.5)\n",
+    "recipe.addVar(mfit.damp, 0.01)\n",
+    "recipe.addVar(mfit.th, 0.5)\n",
+    "recipe.addVar(mfit.phi, 0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Refine using scipy's least-squares optimizer:\n",
+      "  variables: ['parascale', 'ordscale', 'damp', 'th', 'phi']\n",
+      "  initial values: [ 4.    0.5   0.01  0.5   0.5 ]\n",
+      "  final values: [ 2.89532246  2.46122465  0.00673799  0.76372883 -1.60427272]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Turn off printout of iteration number.\n",
+    "recipe.clearFitHooks()\n",
+    "\n",
+    "# Initial structural fit\n",
+    "print \"Refine using scipy's least-squares optimizer:\"\n",
+    "print \"  variables:\", recipe.names\n",
+    "print \"  initial values:\", recipe.values\n",
+    "\n",
+    "from scipy.optimize import least_squares\n",
+    "\n",
+    "least_squares(recipe.residual, recipe.values, bounds=[[0,0,0,0,-np.pi],[5,5,1,np.pi,np.pi]])\n",
+    "print \"  final values:\", recipe.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot the result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gcalc = mfit.evaluateEquation(\"mpdf\")\n",
+    "\n",
+    "# Plot just the mPDF\n",
+    "ax=plt.figure().add_subplot(111)\n",
+    "ax.plot(r, d, 'bo', label=\"mPDF data\", markerfacecolor='none', markeredgecolor='b')\n",
+    "ax.plot(r, gcalc, 'r-', lw=2, label=\"mPDF fit\")\n",
+    "ax.set_xlabel(r\"r ($\\AA$)\")\n",
+    "ax.set_ylabel(r\"D ($\\AA^{-2}$)\")\n",
+    "ax.set_xlim(xmax=mc.rmax)\n",
+    "plt.legend(loc=1)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([-0.0231486 , -0.69123194,  0.72226211])"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "mstr.spins[0]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now using the fitRecipe restraint function to place bounds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load the data into a Profile object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "PDFguiFile = 'MnOpdfgui.ddp'\n",
+    "r,d = getDiffData(PDFguiFile, 0) ### extract the fit residual from the atomic PDF fit done in PDFgui\n",
+    "\n",
+    "from diffpy.srfit.fitbase import Profile\n",
+    "\n",
+    "profile = Profile()\n",
+    "profile.setObservedProfile(r, d)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make the magnetic structure"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/ben/anaconda/envs/mpdfdev/lib/python2.7/site-packages/diffpy.Structure-1.3.2-py2.7.egg/diffpy/Structure/lattice.py:125: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n",
+      "  if [a, b, c, alpha, beta, gamma, base] == 7*[None]:\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",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "struc = getStrucFromPDFgui(PDFguiFile,0)\n",
+    "\n",
+    "svec = np.array([1.0,-1.0,0.0])\n",
+    "msp = MagSpecies(struc,magIdxs=[0,1,2,3],ffparamkey='Mn2',rmaxAtoms=50,basisvecs=svec,\n",
+    "                kvecs=np.array([0.5,0.5,0.5]),label=str(0))\n",
+    "\n",
+    "mstr=MagStructure()\n",
+    "mstr.loadSpecies(msp)\n",
+    "mstr.makeAll()\n",
+    "\n",
+    "upMask = (np.apply_along_axis(np.linalg.norm,1,mstr.spins-svec)<0.01)\n",
+    "downMask = ~upMask\n",
+    "\n",
+    "### Visualize the magnetic structure\n",
+    "uc = struc[:4].xyz\n",
+    "visatoms = uc.copy()\n",
+    "visatoms = np.concatenate((visatoms,visatoms+np.array([0,0,1]),visatoms+np.array([0,1,0]),visatoms+np.array([0,0,1])))\n",
+    "visatoms = struc.lattice.cartesian(visatoms)\n",
+    "visspins = mstr.spinsFromAtoms(visatoms,fractional=False)\n",
+    "mstr.visualize(visatoms,visspins)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Make the MPDFcalculator"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "mc = MPDFcalculator(mstr)\n",
+    "mc.rmin = r.min()\n",
+    "mc.rmax = r.max()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Set up and perform the fit"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from diffpy.srfit.fitbase import FitContribution\n",
+    "mfit = FitContribution('mfit')\n",
+    "mfit.setProfile(profile)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "# Define an mPDF function that will be added to the total PDF calculator\n",
+    "def mpdf(parascale, ordscale, damp, th, phi):\n",
+    "    mc.paraScale, mc.ordScale, mc.dampRate = parascale, ordscale, damp\n",
+    "    newvec = np.array([np.sin(th)*np.cos(phi),np.sin(th)*np.sin(phi),np.cos(th)])\n",
+    "    mstr.spins[upMask] = newvec\n",
+    "    mstr.spins[downMask] = -newvec\n",
+    "    dr = mc.calc(both=True)[2]\n",
+    "    return dr\n",
+    "\n",
+    "mfit.registerFunction(mpdf)\n",
+    "mfit.setEquation(\"mpdf(parascale, ordscale, damp, th, phi)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from diffpy.srfit.fitbase import FitRecipe\n",
+    "recipe = FitRecipe()\n",
+    "\n",
+    "# give the PDFContribution to the FitRecipe\n",
+    "recipe.addContribution(mfit)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<diffpy.srfit.fitbase.parameter.ParameterProxy at 0x7f01eaee6c50>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# add the mPDF variables\n",
+    "recipe.addVar(mfit.parascale, 4)\n",
+    "recipe.addVar(mfit.ordscale, 0.5)\n",
+    "recipe.addVar(mfit.damp, 0.01)\n",
+    "recipe.addVar(mfit.th, 0.5)\n",
+    "recipe.addVar(mfit.phi, 0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "thrst = recipe.restrain(recipe.th, lb=0, ub=np.pi, sig=0.0001) \n",
+    "phirst = recipe.restrain(recipe.phi, lb=-np.pi, ub=np.pi, sig=0.0001) "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Refine using scipy's least-squares optimizer:\n",
+      "  variables: ['parascale', 'ordscale', 'damp', 'th', 'phi']\n",
+      "  initial values: [ 4.    0.5   0.01  0.5   0.5 ]\n",
+      "  final values: [  3.98934342e+00   1.61286874e+00  -6.71623536e-04  -2.28116068e-02\n",
+      "   4.48462494e-01]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Turn off printout of iteration number.\n",
+    "recipe.clearFitHooks()\n",
+    "\n",
+    "# Initial structural fit\n",
+    "print \"Refine using scipy's least-squares optimizer:\"\n",
+    "print \"  variables:\", recipe.names\n",
+    "print \"  initial values:\", recipe.values\n",
+    "\n",
+    "from scipy.optimize import least_squares\n",
+    "\n",
+    "least_squares(recipe.residual, recipe.values)\n",
+    "print \"  final values:\", recipe.values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Plot the result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "gcalc = mfit.evaluateEquation(\"mpdf\")\n",
+    "\n",
+    "# Plot just the mPDF\n",
+    "ax=plt.figure().add_subplot(111)\n",
+    "ax.plot(r, d, 'bo', label=\"mPDF data\", markerfacecolor='none', markeredgecolor='b')\n",
+    "ax.plot(r, gcalc, 'r-', lw=2, label=\"mPDF fit\")\n",
+    "ax.set_xlabel(r\"r ($\\AA$)\")\n",
+    "ax.set_ylabel(r\"D ($\\AA^{-2}$)\")\n",
+    "ax.set_xlim(xmax=mc.rmax)\n",
+    "plt.legend(loc=1)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The restraints do not work very well!!! Maybe discuss with Pavol?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/cmi_scripts/mpdf/example_corefinement2.py b/cmi_scripts/mpdf/example_corefinement2.py
index a4c820b..64b6546 100644
--- a/cmi_scripts/mpdf/example_corefinement2.py
+++ b/cmi_scripts/mpdf/example_corefinement2.py
@@ -14,7 +14,10 @@
 from scipy.optimize import leastsq
 
 from diffpy.mpdf import *
-from diffpy.Structure.Parsers import getParser
+try:
+    from diffpy.structure.parsers import getParser
+except:
+    from diffpy.Structure.Parsers import getParser
 from diffpy.srfit.pdf import PDFGenerator, PDFParser
 from diffpy.srfit.fitbase import FitRecipe, FitResults
 from diffpy.srfit.fitbase import Profile, FitContribution
@@ -65,9 +68,9 @@
 # parameters according to the CIF-loaded space group.
 from diffpy.srfit.structure import constrainAsSpaceGroup
 sgpars = constrainAsSpaceGroup(nucpdf.phase, pcif.spacegroup.short_name)
-print "Space group parameters are:",
-print ', '.join([p.name for p in sgpars])
-print
+print("Space group parameters are:",)
+print(', '.join([p.name for p in sgpars]))
+print()
 
 # We can now cycle through the parameters and activate them in the recipe as
 # variables
@@ -89,16 +92,19 @@
 mnofit.clearFitHooks()
 
 # Initial structural fit
-print "Refine PDF using scipy's least-squares optimizer:"
-print "  variables:", mnofit.names
-print "  initial values:", mnofit.values
+print("Refine PDF using scipy's least-squares optimizer:")
+print("  variables:")
+print(mnofit.names)
+print("  initial values:")
+print(mnofit.values)
 leastsq(mnofit.residual, mnofit.values)
-print "  final values:", mnofit.values
-print
+print("  final values:")
+print(mnofit.values)
+print()
 # Obtain and display the fit results.
 mnoresults = FitResults(mnofit)
-print "FIT RESULTS\n"
-print mnoresults
+print("FIT RESULTS\n")
+print(mnoresults)
 
 # Get the experimental data from the recipe
 r = mnofit.totpdf.profile.x
@@ -147,7 +153,7 @@ def magresidual(p, yexp, mcalc):
 
 p0=[5.0,3.0] # initial parameter values (paraScale, ordScale)
 pOpt=leastsq(magresidual, p0, args=(gdiff, mc))
-print pOpt
+print(pOpt)
 
 magfit = mc.calc(both=True)[2]
 magdiff = gdiff - magfit
@@ -189,15 +195,19 @@ def mpdf(parascale, ordscale):
 mnofit.addVar(totpdf.ordscale,value=mc.ordScale)
 
 # do the co-refinement
-print "Refine PDF using scipy's least-squares optimizer:"
-print "  variables:", mnofit.names
-print "  initial values:", mnofit.values
+print("Refine PDF using scipy's least-squares optimizer:")
+print("  variables:")
+print(mnofit.names)
+print("  initial values:")
+print(mnofit.values)
 leastsq(mnofit.residual, mnofit.values)
-print "  final values:", mnofit.values
-print
-mnoresults=FitResults(mnofit)
-print "FIT RESULTS\n"
-print mnoresults
+print("  final values:")
+print(mnofit.values)
+print()
+# Obtain and display the fit results.
+mnoresults = FitResults(mnofit)
+print("FIT RESULTS\n")
+print(mnoresults)
 
 # Get the calculated PDF and compute the difference between the calculated and
 # measured PDF
diff --git a/cmi_scripts/mpdf/introTutorial.ipynb b/cmi_scripts/mpdf/introTutorial.ipynb
index b7de586..403f4d7 100644
--- a/cmi_scripts/mpdf/introTutorial.ipynb
+++ b/cmi_scripts/mpdf/introTutorial.ipynb
@@ -107,7 +107,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {
     "collapsed": true
    },
@@ -117,7 +117,10 @@
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
     "from diffpy.mpdf import *\n",
-    "from diffpy.Structure import loadStructure\n",
+    "try:\n",
+    "    from diffpy.structure import loadStructure\n",
+    "except:\n",
+    "    from diffpy.Structure import loadStructure\n",
     "\n",
     "### Set all plots to be inline\n",
     "%matplotlib notebook"
@@ -125,11 +128,801 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Create a MagStructure object\n",
     "mstruc = MagStructure()\n",
@@ -160,11 +953,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e7620a58>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### make a copy of the magnetic structure\n",
     "mstruc2 = mstruc.copy()\n",
@@ -195,7 +999,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
     "collapsed": true
    },
@@ -227,9 +1031,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -241,14 +1045,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "lattice=Lattice(a=4.446, b=4.446, c=4.446, alpha=90, beta=90, gamma=90)\n",
+      "Mn2+ 0.000000 0.000000 0.000000 1.0000\n",
+      "Mn2+ 0.000000 0.500000 0.500000 1.0000\n",
+      "Mn2+ 0.500000 0.000000 0.500000 1.0000\n",
+      "Mn2+ 0.500000 0.500000 0.000000 1.0000\n",
+      "O2-  0.500000 0.500000 0.500000 1.0000\n",
+      "O2-  0.500000 0.000000 0.000000 1.0000\n",
+      "O2-  0.000000 0.500000 0.000000 1.0000\n",
+      "O2-  0.000000 0.000000 0.500000 1.0000\n"
+     ]
+    }
+   ],
    "source": [
     "### As a refresher, let's take a look at the mno structure object.\n",
-    "print mno"
+    "print(mno)"
    ]
   },
   {
@@ -260,7 +1080,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
     "collapsed": true
    },
@@ -298,9 +1118,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -327,11 +1147,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff81fbb2be0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "uc = mno[:4].xyz\n",
     "visatoms = uc.copy()\n",
@@ -343,11 +1174,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e777aeb8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Now we can create the mPDF calculator and load the magnetic structure\n",
     "mc = MPDFcalculator()\n",
@@ -359,7 +1201,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "metadata": {
     "collapsed": true
    },
@@ -384,11 +1226,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Since you are not using a diffpy Structure object,\n",
+      "the spins are generated from the makeAtoms() method.\n",
+      "Please call that method if you have not already.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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wvr6Orq4unD59Gnq9Hi+88ELdvrD5oFarkUqlsLi4CJ/Ph+HhYVmJODdT7yAhn6SYpml+NW97exsURSGTyUCv1/NyYVJd10rsUi9CJjvItQCVYmA1lP5akUhENsOtp59+Gt3d3Th16hSee+45WY4pBoWQS0Q+VZ3H48Hm5ib6+vpw7ty5rC8k2R+W40tKiL+SL2EqlUIgEMDW1hYmJiaqZmAPNJ5FZiXQ6XRoa2vbt0NN0zQWFhbAMExesQvZoZabxJqdkGmGRTLDwlIGIYdCIdkq5EuXLuEHP/gBfvSjHyGZTCISieB973sfvvGNb8hyfAKFkCVCTMxBeq67u7sFh1/lEPJGKIHNUAITXVa0CQYapNVQzpcwmUzC7XYjGAzCZDJhZGQEvb29JR+nFDRyy0IOqFQq6PV6GI1GHDp0iCeA3MQPj8ezL0OPtD8qEbs0OyFTqT0hlNVw97sj9XqSs2Xxmc98Bp/5zGcAAM899xwef/xx2ckYUAi5KMTEHKlUCm63G6FQCMPDw5iYmCj4pShHYfd//e+beMUTxn+7MIiPvXV637FKIfdEIgG3241wOIzR0VHMzMxgZWWlJkTZ7IRMIJa+nS/xg4gfYrFYlkpNzKCnGNnWk5Br8bqx9N73TmixWmigJ0Q4HK65R3ilUAg5D8TEHBRFwe12g6KokiKStFrtPqPvQkjRDO5s7Q0Onl3w4c8fmuJfpxRyj8fjcLvdiEQiGBsbyzpfOUUmhXAvEbKUayGf+IHIiUmPWih2yeekRv5dvYaJ9aqQ603IDzzwAB544AHZjwsohLwPxAg+Eomgo6NjX0TS6Ogo/3OpKLVC/sWSDwl6jyw9wQRe24jg2MDeo5cUIo3H43A6naAoCmNjY5ibm9t3vnISci4Z1WsPuZ6Qw8qUiF2EYFl2n5OaUOySTCYRDAZhs9lgMBhqRs61alnEXidkYQ9Z6muHQiEMDg5W7dyqAYWQsV/MQfaGNRoNXC4X1Gp1RRFJpRLy91/1os2sQzBOQ69R41+vbfCEXOhYFEXB6XQikUhgbGwMnZ2dBX0xcrX/5YAQbr7XUQi5MuRzUiNil1AoxItdhGkfuTvUcp9b7XrIe0+W1jJaFnJuWdQK9zQh5xNzRKNR7O7uguM4TE9PVxyRVAohB6g0/mPZj9882oPv3fDi+GALfnhzG3/x1ilYDFrRyjYWi8HpdCKZTGJ8fFxSBS8XURY7jkLI1QERu+h0OkxMTPA/J2kfsVgMfr8fa2trSKfTokGnxcQuhVCzCjn9esvCWHrLIhKJyLqHXAvck4RMVteIvzD5Im1vb2NlZYW/YI8dOybL65VCyGuBBLpserxtrhvfu+HFqaEWXF0J4se3tvE7J/uzjhWNRuF0OkHTdMlp03K1LBRC3kOj7JnnS/ugaZonaqHYhQQGCLc+pJAdwzA1cVBrNWlxfrQVLWUQsjLUa3CI7RBzHIeNjQ14PB60t7fjxIkT0Ov1uHLlimyvW8pQ7/hgC37+2EX4qT2hQZfVgAenOmHQ7lUjarUasVgMHo8HmUwG4+PjJRkUEchFyMWOU8gzo5nQKIScDzqdTlTsQgIDKIrC1tZWltgll6iFFTHDMDAajVU/7/vG2nHfWPb1nclkJFXn4XBYFkOhWuKeIOR8qjoSkXTo0CFeVSf8N3JBo9EglUpJ/vtqtQpG3d4Fl2ZY/D/vPQ5g7wLb2tqCWq3G/Px8RXf/alTIHMfB7/fD6XQinU7zX1itVovW1taGNpevFAf1KaBQYAAh6o2NDcTjcV7sYrVaEYvFoNPpaqrYI5B6M1AIucEgtkNMLCW3t7dFVXXVQDl7yEbdHnElaAbBYBBOpxNqtRqdnZ2w2WwVP4rJTciBQAAOhwNGoxGzs7PQ6XSgaZoXRKyuriIejwPY8ywmg6pqWGHWC81ysxEGBuS6qBGxSygUgs/nw9bWFliW5QMDciOZqgGpLQuKovallTQ6mpKQ84k5VldX4fP5ZDfQKYZyCFmnUUOjBlxrG1ixhzE1NQW73Q6Px1OTVoNUZDIZ3LhxAyaTiXezY1mWr5Dtdjv0ej2Gh4cB3PUsjsViWVaYuQ5rVqv1wKQ8AAe3Qi4FQrHLzs4OBgYGYLPZsgIDhJFMALKI2mq1yhIYIIWQye/joN0km4qQxcQcRKUWiUQwPDxckm+DXH3BUgiZVJtOpxN6tQrWljacOHGY/3O1Ws0b2VSCSgk5FArB4XAgkUhgbm4O3d3don8vd6gn9CA+dOgQ/3PisEaGTm63GzRN834QpKKuhh+EHKhHD7meNwGhUq9YYIBYyCkRu5TzlCS1QlapVAfuyaspCJlhGKRSKf7Dz41IGh0dFRVHFIKchkBShnrC/qvRaMTc3Bwsz78CFtnko9Fo6lohh8NhOBwOqNVqTE9Pw+Vy7RMzCCF1y0LMYU3YyySDTOIHkdv2qGVUkxjqQcj1TAuRotQrFHIqJTDAYrGIil2k9K0PqnH/gSZk8oWlaRrXrl3DuXPnEA6H4XK5wLIsxsbG0NbWVtYvhpCoHIRcqELmOA4+nw8ulwsmkwmHDx/mL2CjToMEnf3v5EqeLpWQI5EIHA4HOI7DxMQET5zVXHsr1MskbY9c9ZrFYkE6nUYgEOATQGqBehFyvUinkmGeUOwifEoiYpdYLCYaGED+S6fTRV87EolUrB+oBw40IQt9GdLpNF5++WVotVqMj49XvBBeqv9EIYiRKMdx2N3dhcvlgtVqxZEjR/ZVmiadGqlMNmnWal2NIBqNwuFwgGVZjI+P7xsmSll7q2amnrBVQhJAgsEg/H4/VldXs3ZthRW13G2PerUs6lUhV2O7Il+yizAwwO/3g6IoXL9+PUvsQn6vZO4QCoUO3A4ycMAJGQB2d3d5ccTJkydli0iqFiFzHIft7W243W7Y7XYcPXo07yO/QVu/CjkWi8HhcICmaUxMTORdH2ok4QdJANHpdJicnOR/Lmx7bGxsgKIo3gZTOESU4q6WD/day6KW7ze3nRUKhXDmzBnQNJ3Vn47FYshkMnjmmWewuLiIUCiEy5cvY25urqIMy2Qyifvvvx+pVAqZTAa/8zu/g09+8pNyvb0sHHhCZlkWx44dw/Xr12XNq9NqtbIQH7BHFJlMBl6vFysrK2hpacHx48dhMpkK/juTTo1kDiFXu0ImMux0Oi1JdHIQlHr5dm2F7mq7u7v8wElYdUkNPr3XCBmof/iATqdDa2vrvkp4aGgI3/nOd/Dss8/iH//xH3H79m18+tOfxsWLF8t6HYPBgJ///OewWq2gaRoXL17E2972Npw/f16Ot5GFA0/Ivb29fC9NzguUkGil4DiOT5EIhUI4ceKEZIWTUadBOJFtAFStClloTDQxMZHl4VvKcQiEA9Z6E7IYhDaYuZsBYsGn5PFYWFHXKqYpH+pNyPWAlGupp6cHo6OjeMMb3oC//uu/rvg1VSoVX+zRNA2apqt2MzrwhEw+GCJEMBgMshy30pYFy7Lwer1YXV1Fe3s7zGYzZmdnSzqGUafGdqQ6FTIhSmLVGY/HJRsTiR2n3D9vNKjVatE+Jnk8jsVi2N7ehtPpzFKukT+vpRrxoG4SVAKpNyG5A04ZhsGpU6fgcDjw4Q9/GOfOnZPt2EIceEImIARab0JmWRabm5tYXV1FZ2dnVtBpqdjbssgmX7kq5GQyiUQigddeew3j4+MFrToLodkIOR/EHo+Jci0Wi/E3XyKIqGTPVio4jqvLTjaxq60HpG4+hUKhrA2OSqHRaHDjxg2EQiG84x3vwM2bN3H48OHi/7BEHHhCzq2Q5YJWqy3Jf4J4Y3g8HnR3d+PMmTP7Vq5K7TOadBrZe8jJZBIulwvhcBharRbnzp2r2Fhd7MtJ3muzELIYhMo1g8GA+fl5APn3bOVWIzIMU7e0kHq1Skqx3pyampL99VtbW/Hggw/iJz/5iULIhSDnVkQpx2MYBuvr61hfX8ehQ4dw9uxZ0S9ZMSN3MRi0aiQz8lTIJOA0FArxcU4vvvhixV9oMTc3oUKqmQk5H/Lt2YqpEYmzmpCkpaoR67X2Vqv4JjFIXbeT01hod3eXf0JKJBL46U9/ij//8z+X5di5OPCEXM0KuRAhMwwDj8eD9fV19Pb2FjUpIscrRajwxqlOdFqz/36pBEoCWQOBAMbGxjAzMyNrVXWvtCzkQCE1Itn28Hg8oCgKHMcVVSM2e+K0GOrhhez1evF7v/d7vH/6u9/9bvzGb/yGLMfOxYEnZAKtVlsTQs5kMvB4PNjY2EBfXx/Onz8v6QIpp7J9w0QH3jAhbdshF+l0Gm63G36/HyMjI5ienq5axJBCyOVDqEYkmy1P3fDir3+8jAcnjPiLN1pE1YhWq1UWT5NycFAIWa4K+ejRo7h+/bosxyqGpiFknU7H75HKgVxCJradm5ub6O/vl0zEBHIN44ohnU5jZWUFPp8PIyMjmJqaqmqfMZ8B/b3QQ64W/vUVLxgWeHUzjq6uLlE1IpGNJxIJ+P3+mqgRhefQ6IR8EOObgCYgZGHLIhKJyHZcIgyhaRpra2vY2trCwMAALly4UNbFWG1CpmkaKysr2NnZwfDwMM6fP1+Tx9l8hHsv95ArwS1vFDe9MQDAbiyNhW0Ksz13BU9EjWi32/lth4GBgay2h5gaUdj2qPS6qCchSzX8ikajFanz6oUDT8gEcg/1WJZFLBbD1atXMTg4iPPnz1d0EVaLkDOZDFZWVrC9vV2yz7McYpp6eFk0M/7XlXWYdGokaBZqFfDjWztZhCyEcKin1+vR3t6+z4SJqBFjsViW/WXutkcpydT13rKQIqyq10pgpTjwhCz3UI888u/u7kKtVstmZC/3DUNYuQ8ODpZ1noRMK3l/Yi2LZDKJnZ0dPjBTIWRp8IaTeOb2Ln59tgs/vr2L+V4bfnx7F4+9aRRqEbJkWbZgtZhPjZjPVU2oRiwUeNroLYuDfL0deEImqJTwUqkU33sdHh7GhQsXcPnyZVml2HJUyJlMBjRN48qVKxVX7nKo/oQVsHCQ2NnZiVAohFgshng8jps3bzZlbJOc+OZLmwCAN0134Me3d3F+pBV//4IHN9YjODm4vx9a7s00n6uaUI24tbWFWCyWpUYkZC01ZLQakELIRMF4EK+vpiBklUpVdoUsXAsbGRkpKVGkFFRKyMI1O5VKhVOnThU1JyoGOQhZrVaDYRg4HA5sb2/znyHR+9M0jV/96lcYHR0VjW0iJE3+O4iPmXLhfWf7Mdtjhf31yPszwy34+tUN/PjWrqyEnA/F1IixWAx+vx+hUAjA3uCs2mrEXEi5GcRisQPphQw0CSEDxdevckGEEsFgEKOjo6JrYXIaFpVLyELhCVmze+211yo+H6D0z0zs3HZ3d7G7u4uJiQm+bSI8JvlMxWKbhBWZ1+tFLBbblwZitVrvmWq6x27Aw4e78R/LfgCAzajD373ncN4eci16uUI1YmdnJwBgdXUVer0eNput6mrEXEipkMPh8IEc6AFNQsilDI5Ixl44HMbo6GhBoUQ5Yo580Gg0Je2NCqXYPT09WcITUpVWinwra1LObWNjA2tra7DZbOjv78fQ0FDJx8lXkQnTQLxer2g1na+/2Qygmb1rWadR4XBffnFDvcyFSO+6FmrEXEjZspDbWKiWaLorOp88OR6Pw+VyIRqN8tLhYheznIQstcctJLtDhw6JKgDrlatHrERXVlbQ1dWFs2fPIhQKIRgM5v03pW5Z5EsDIV90IpIg/U3hWhcxma815B4i0a//TnSawtVvvaTThYZ6UtWIJBsx14SpWDailPd8UNNCgCYhZGGUU67OnqIouFwuUBSFsbExzM/PS64q5FxVK3YsoUtcd3d3Xk8MQL4KWSohk7gpp9OJ1tZWnDp1infVq9XaW74vunCta3t7G4lEAvF4HAsLC1lEXc1qWm5zemGFXAgHRTotpkYEwNu/Cm+0uWpE4VqeVMgpm641moKQCchgT6PR8KnTiUQCY2NjZdlLVjtXD8iuOjs7O0Vd4sSOVasK2e/3w+FwwGKxiKac1NMvDjOEAAAgAElEQVTLIt9a19WrV9Hb27vPu1ismpaDSOUnZFIhNwch54NKpeJnC/nUiLnZiMlkEpubmwXViAohNwi0Wi3C4TAWFxeRSqX4CKJyvyzVJGSO47C1tQW3242Ojg7eN7mcY5WLQoQcCoWwvLwMnU6XlYSdCymEXGuoVKqi1fTOzg7i8XhWNUb+y30y+eIv3Dg12II3TIjHWVWrQtYWIdt6EnI1X1eoRhQimUzi+vXrYBgmS41oMpn432E0GkUgEMgi+IOEpiBklUqFaDSKUCgEiqIwMzNTNAtOCqpByCTk1OVyob29PevxXyqqmasnTJmenp4uOq2W61yqjUIiCbEhFNm9tVqt+F+X1wGOy0vIcqPRWxb1st/UaDQwGo0YHBzkf0aGwOR3+JnPfAZXrlyBVqvFL3/5Sxw5cgQf/ehHyzpfj8eD97///dje3oZKpcKHPvQhPProo3K+pX1oCkImKc5tbW3o6emRhYwB+Qk5kUjg8uXLaG1txcmTJyVn64kdS+4KOR6Pw+FwIJlMYnJyUrJTVjEvi0aHWDWWu3vLsBy2t7bw8ssB0Wq6ei2L4hVyPT7nein1xFbehEPgrq4ufPWrX8Vf/uVf4q1vfSsGBgawsLBQ9rlqtVo88cQTOHnyJKLRKE6dOoVf+7Vfw9zcnBxvR/w1q3bkGuLQoUPo6Ojgqxu5UGpqiBiEA7FUKoX77ruvbCImkLNCTqVSuHXrFqLRKB9uKmem3kFE7u4thzUM9PfhxIlBvhLz+Xz89UacBre2tviVrkoqV6kVciNuWVQTUhWC4XAY3d3dOHbsGI4dO1b26/X29qK3txcAYLPZMDs7i42NDYWQi6GaJvUURZX1bzmOg8/ng9PphNVqxfHjx3H9+vWKyRjYq+oqfZ/pdBo+nw+JRALT09OYm5srO1OvkP3mQQe52ahVqrzVdDQa5ecWfr+fz9XLraalzghIhaxVN2bLAqjPE1A9vJAJVlZWcP369aqFmxI0FSHLUdEKodFoSq64OY6D3++H0+mE2WzG0aNHYTabZTsnoLIKWegOZ7PZ0NPTg56enorOpdkqZCFeL1aRj39UKhX0ej0MBgOGh4f5n7MsK7opQAQS5D+xappmOWjVxb0YmuWmJxVSrTfl3rKIxWJ417vehS9+8YtVVwA2BSETVKNCLqVXS4jYaDQW3EyoFOX0kBmGwdraGjY2Nnibzs3NTVnNhZoR5L1pClSrYsSoVqtFDXxIb5qiqH0p1TabDRaLBckUXbRdQXAvEbLUCjkajcqm1KNpGu9617vw3ve+F+985ztlOWYhNBUh1yvoNBAIwOl0Qq/XY25uDlaruPeAXCilQhYq/3p7e7MM9tVqdcWfVyFCboYKjmH33luht1HK+xQTSJCUamKHuePzQ8WxuH79+j65eL1aFI0AqYRczJZUKjiOwwc/+EHMzs7iT//0Tys+nhQ0BSHXK+g0GAzC4XBAp9NhZmZGksOUHCQlpUIWkznn7tfK5faWL3W6GSrn1/lY1I+YoNLfqTClGgBalliYfH7Mz8/zmx4k/BTYq6aJDWYqlSrJXL5S1PN3mslkikrjSYqKHLh06RK+/vWv48iRIzh+/DgA4NOf/jTe/va3y3J8MTQFIQOVWXDmQz5CDofDcDgcUKvVkokYuEukld69CxFpIZlzLso1F8o9RjMQbz7wLYsqEnIuMgwHnUYtmgIirKYZhsHCwgJvLk9aHtXM1Ku2KKTYa0s1p5fj93Hx4sWaX9tNQ8iA/C2LXOKLRCJYXl4GAExMTJTcp5KLkPNVyMVkzrmQ26C+1khn9mKOOBTf2S0XxYZ61cA7j/fgYh4RirCa9ng8/FpXOp3mh4hCFRuppsl/BoOhIrKqlygEkNayiMfjVZvd1AJNQ8jVSAggxxOq18ohYoJqSZ7D4TCWlpaKypyLHUeOcyGgKAo6nU4Wp7x8+B8/deA7r2zhncd78MmHp6ryGuUO9SrBCREz+mLQ6/XQ6/VZ614sy/JWpuFwGBsbG3w1ndublkqyjR7fFAqFDqz1JtBEhFwNRKNR3jlsYmKi4t1GuQiZHKdUmXMuqlEhR6NRLC0tgWEYsCyLTCaDRCIBl8slq6kPw3L4xVIAAHDZHazaAJH0kAsduR7DSylPJcSnQywYgPSmc6tp4e60WDBAoxPyQTYWApqUkCv9gsRiMTidTqTTaej1epw+fVqWL5xcLZVUKoVIJII7d+6UJHPOhVyEDOwZ/y8vLyOVSmFychJms5knjatXr8JqtYKiKN4ikxjO22y2snqel5wB7Mb2DP83wyksbFN5kzUqAdmyqOZQrxxUIgrR6XRoa2vLum6kBgPUk5ClvPZBNqcHmoiQyReikj4tRVFwOp1IJpMYHx9HR0cHLl++LFvfrNIKOZlMwul0IhKJQKvV4syZMxVP9ysl5HQ6jWQyiRs3bmBiYoK3OSXpKCqVCmq1Gl1dXfsM58mXn1RpHMdl9TxtNlvelse3Xt5Em0mLYCIDrVqFH7y2LSshhxM0nr65g/Mje9VWIe6rV4Us52sWCgYg1bTX60U4HEY6nUY6na55zJZCyAcQZNOiFEKOx+NwOp2Ix+M8EQvVf3Kl7JZLyMI057GxMczNzeHFF1+s+AtQCSEzDIPV1VV4vV6o1WqcP38+7/mQtobwz7Va7b74ptx93LW1NV7dRippq9WKnQRwyRXEu4734Ls3tnCkz4Yf3drBn755VLbh3kYoib95xolHHxzZew8APvPvDrxtvhvHB7JbQwetQi4Fub8nn8+HcDjM+00LjeVJNW2xWPiND7mDAYp9zkrLokGQu4ssJconkUjA6XQiFothfHxc1MSeEHKpFpliKJWQhTLnkZERTE1NyfrFL0f2LBSa9Pf34/z587hy5YpoQKxwBUlqz1O4jwtkx/9Eo1Hs7u4iGKXw3+b16DYlAADHe024vh7B1ZUQ/su4PE5/sz1WjHea8eyCDwCwFkjiWy9vYqrbck8Rci7I02ehmK1YLFY0Zqtan5dCyA0GKX1a4aP/+Ph4wVgnuS04pRyLYRh4PB6sr6/zMudqfPlKqZA5jsPOzg6cTic6OzsLRkzlopLVuHzxP/cxDC47tgGE0a1N4uPnjND6lvGruBmpVAo+n49veZRrmvQbR7rx5C9WAAAvrgTRZtbh4cP7jc/vNUIuNU9PLGZLePOVErMl9foJh8NZfskHDU1DyFLUeslkEi6XC+FwmH/0lxp0KgeKmR8VkjlXA1IJORgMYmlpCRaLpSwf52rsKms0Gther6SHhgZx/0Q7P5i6ceNG1pqXTqfL6ktLtcd8eP4uIS9tU/jD/zIEo27/7+NeI+RS2hCFggGE6S0ulwuZTCarmrZYLDCbzbyAScr7VSrkBoMYgaZSKbhcLgSDQcmJ04WOVy6k5OrlkzlXA8WUetFoFMvLy1CpVJifny/bo6Na4pHc3yAZTOl0OoyPj/M/Jy2PWCzGG/qQPLdC0U29LUYc6bPhV5tRqAC851Sv7O+hXNTTnF6u9p1YNS0MBtjZ2UEikeD9qWmaRjAYFP1dEUQiEYWQGwnCClk4DBsdHcXMzExDBZ2WInMWgxweCmKEnEgk4HA4kEgkKlqrI6i6mq/IscUkyAzDIB6P831pYjZPKjQyRLx/og2/2oxipseKLpv476ZeWxb1im+q1uvmBgMQMAwDn8+HZDKZN2aLkHQkElG2LBoBwpYFESf4fL6Kh2GlWnAWgpCQS5U554KQaSUtjdyhHk3TcLlc8Pv9mJiYQFdXlyxEU7UK+fVzK+fIGo1mnz2msN9JdnHntQk8+aAZNqsJm5ubfMtD+Lnfay2LWu8hkyw9m82Gqak9RWZuNb22toY//uM/BkVR+MQnPoHz58/jwoULZRvKf+ADH8DTTz+N7u5u3Lx5U863UxBNQ8jAHqFsbW1hd3cX09PTOH/+fMUXrUaj4XdqK4VWq0U8HsdLL71UssxZ7Lzk+nIQr+TNzU0MDw/Lvs1R7ZaFXIfO1+8UKtvW19cRi8UA3PUwpmlaIeQav25uNT0yMoJr167hjW98Ix577DEsLCxgcXGxbEL+/d//fXzkIx/B+9//frnegiQ0DSGzLIuXX34ZnZ2d6OzsxMDAgCzHlatlEY1GsbCwgGg0itOnT1ecPCCHqIOslF2+fBl9fX04f/582V+23Cox9/+uSsvi9ZeotrWRmLKN7EyT2PlEIgGfz5f1GG2z2aq24nWvEXIpXsjnzp3D+fPnK3q9+++/HysrKxUdoxw0DSFrNBpcuHABiUQCd+7cke24lRKyMM15eHgYHo9HlhiYSlR/pHdNfDAqHSKKCT/E/lxu1NP6PndnOpPJYGBgQHQolSs/tlqtFZNaPQm5Hq8rhZCbwQa2aQgZqK0ncjGQXWdhmjPDMLLddcutkIPBIJaXl2E2m3Hy5Em88sorFW90FCPcag/16v1FJDejfEMpIpggfelYLJZljUkGiKXsTNeLkOtlv0nSvaXgIKfUNBUhA/I5qhGUSshiMudcnw05UOqxYrEYlpeXwXEcZmdnJZvqS4EUQq4GKhnqyYliQ718ggkiEw+FQvB4PEin09DpdFky8Xw70/Vce6sXIRcbfCeTyZKH442GpiLkangiSyVkKTJnuWXPUirkZDIJh8MBiqIwNTUlezx6oXMRElVVWxZ1ZuRyVtDIHnSuNWY6nUY0GuXTqoU700Kibsa1t0KQIkgJhUJVT4WuNpqKkKuBYnJnInPe2NjA4OBg1WTOYudVqEKmaRputxs+n6+oPLzSta1iFXI5nhnSXlf2Q9Yder0eHR0dWTJxhmF4j4jt7W04nU4kEgkYDAakUqmaOq4B9WkJ1NoL+Xd/93fx3HPPwefzYWBgAJ/85CfxwQ9+UJZjF0JTETK5UEqRWhZDvmPkypwr2VAo97zEqlKWZbG6usqvsBVb/SNkWU1CrnoPuWpHlvj6Vd5D1mg0sNvtWdWf2+2GVquFwWDI8i8maSBCn+lmSKqWSshyiUK+/e1vy3KcUtFUhExA2gzViA8iMme3243u7u6ayZxzIab629zcxMrKSkk3CDluXmI3h1AohFQqxZNINQi5v9WI//l/zmO+d7+ku5ZijXop9UwmEzo7O7Mc18jOdDQazUqqFsrEbTZbXa7ZSiA1vukgy6YBhZAlI1fmfPr06bI0/XJV74QEOY6Dz+eDw+FAW1sbzpw5U9L7ljvGKRaLYXFxkd842NjYQDQaRTgcRnt7O1+5ybGfazVo8eBUR/G/WGXUS6kn9pr5dqZJy8Pv92NlZYWXHgv70tW0xawUUs3pFUJuIEhxfCsHmUwGV69eLVvmLASRYsuhIIzFYnjppZdgNBrLPi+5CDmVSmFlZQWxWAyTk5OwWq1Ip9PQaDRwOp2w2+3QarWIRqO8BWOzPF43upeFWq0WlYmTnWnh70S4M01M5gkR1mqz4x8vr6PLqsPDh+8OO6UUMQohNyh0Op0s6jqS5pzJZHDs2DFZ+lNkSFjJIyNFUfB4PMhkMjh+/HhFK2yVEjIZON26dQsTExOYnZ0Fy7J8RRONRhEKhdDZ2QmbzQa73Q6NRgOVSgWapnm129ra2r6NAkLU9cpwk4qD6GVRaGc6NwCVRGuZTCawLMtnTVYDv9qI4ImfuaAC8KbpTphE7E7zIRKJoKenpyrnVSs0FSELY5cqqZBz05wdDodsF2Alu8hEbBKLxXivhUr3icslZGHPWq1W4/Dhw7Db7WAYBiqVCplMhs8nnJ2d5f+M4zhwHMcTCqmM+/r6oFarwTAMEomEqIhCSNLVIoRycBAJOR/yRWslEgkEg0FkMhncvn2bJ+Vcn+lKP4e/++UqVNgb1P6nM4Bfm9m7zqUcV6mQGxTltiyEMmeh7WQtPJELIZPJwO12Y3d3lxeb+Hw+BAKBis+nHEL2+/1YWlrie9bLy8vweDzo6OiAxWLB9vY2v24njMUSEgh5TdIHJ1U1AN7g59ChQ3x/mriwCXugQqtMm80Gg8FQlx5oMxGyGNRqNSwWC1QqFUKhEA4fPgwAWS0Pn8/HexeXkgQixKsbEfynMwiDRgWoVHjmjg+/NtMl+fpUCLnBIKyQCyVz5EJM5pwbyFkPQmZZFmtra9jY2MDQ0FDWCptGo6m49wuURshkYKfRaHD06FEYjUawLIvR0VGEQiFsbm4iGAzymWukoiK9SOFnSt5HLqkICZr8LwAYDAbo9fosghdm7W1ubvLpIMlkEtvb27JVbcXQ7IRMkDtYE4vWIi0s0pd2Op1gGAYmkylrXiB28/zKf6yizaRFJJnBZLcZzy/7kaQZaMBKInWFkBsUOp2Ot0gshEIyZyGkZuFJgRRCFq7W9fT04Ny5c/suSLlk2FIIOZVKweFwIBaLYWpqCna7nSdLlUqFWCyGlZUVtLe34/Dhw9DpdLziLBKJYHd3F/F4PMuDmHwxc0lFeMMhyEfSwsdrtVrNt0quXbuGZDIJn8/Hv26+QdVBRSMQshjEdqZJtFYsFssbrRXI6HDJFcSfPDCC//ncCmZ7rFjYpnDJGcR9w9LSq8PhcFWUqLVEUxJysYq21DRnOU3qi52bz+fD8vIyWltbC66wybEdUew4xAxpe3ubj75iWZYn4ng8juXlZb5iFm55iCnOMpkMotEoP8SLxWL8Iy4Z+Nlstn1feikkTf7vTCYDjuPQ29sLrVbLkzTxjRAOqoRyZJvNVnZkfSOtvVUT5fpYkGit3JRqYbSWKhbEX503wJzxAgC69TRajBrcWA/hbL9B0u/moMc3AU1GyMXW3oRpzqXInGvRsiAbHQaDAceOHYPZbC7rOKVCjJA5jsPGxgZWV1fR39/Pm3yTgV06nYbL5UI8Hsfk5KTk7ROtVrtvR5aEXZIh3tLSEliWzdq0sNvt+7ZSckmaZVl4PB5sbm5ibGwMWq02q4ongZk9PT38eybDw93dXbhcLv7RWkjSUnbNG33tTS7IXZXnRmvNzQErPgr4z2uwG7V48tc7oKIjuHlzFxzHweVy8b8bMZl4Op0uOYC30dBUhAzcteAUEqiYzLmUaqjSrQ0hcok0Ho/zq3XT09OSzVGqVSGTCr29vR1nzpzJ6lUT0tve3sbo6GhJYbH5IBZ2SczfI5EIfD4f3G43aJqGyWTiq2jhEI/EYXV0dODs2bP7qjhS1ZNKmnz+ZO2ru7ubfx+pVIoXsqyvr/PbBMI2S66A4l7tIVcDcXrvWhs41IlT03vreLu7uwgEArDZbIjFYrxMnLTAGIaB3++X7fP4yU9+gkcffRQMw+AP/uAP8LGPfUyW40pB0xEycJdAOY7D1tYW3G53RWnOWq0WiURClnMjkVCpVApOpxORSASTk5NZj/ZSjyNnhUxyCLVabdbAjpDx1tYWVldX0dfXh7Nnz1aVDHLN34G7fUiy1+zxeJBIJEDTNHQ6HYaGhtDR0SF6Xmq1WvLwkCjdhINdYatFTNSSTqdr7slcj5tALQiZSu9d01bDXWoiTy5dXV2i0Vq3bt3CV77yFaytreH06dOYmZnBH/7hH+KBBx4o+fUZhsGHP/xh/PSnP8XAwADOnDmD3/qt38Lc3FzF700Kmo6QVSoV1Go1UqkULl++XFaacy7kbFkAe3f8ra2tiqpMuQiZtHFUKhUmJyf3DeyCwSAcDgdaWlpw+vTpunkgCPuQHR0dcLlcoGkaExMTUKvViEajWF5eRjwe5z2FSbtDzFO4lOGhWq3mq3gyPBS2WmKxGBYWFqDVamsqaqkHIVd7/zuW2rumLYa7n1s+Hwty87x48SJOnz6Nhx9+GJcuXcLi4mLZWZVXr17FxMQExsbGAADvec978P3vf18h5HIRCASwuLiITCaDs2fPymJYLQchk8f9lZUVmEymigNYK3VQI4PN9fV1dHV17RvYJRIJLC8vQ6VS4fDhw0V72rUA6W17PB4MDQ1hcnKSJ6XcyikSiSAajcLtdoOiKL7qJi0PMbIsZXgIgBe1RKNRDA4OwmQy8VX81tYWYrEYGIZpaFFLKahFhRxL7X3PhBVyJpMpev0RpzcSHlwuiI0uwcDAAK5cuVL28UpF0xFyKpXC/Pw8XnvtNdnSAypZeyNtE5fLhUOHDuHIkSPY3Nys+JG/3OpIOLAbGBjA+Pg4KIrifSeIjzLZyW6UNSISPUW2TwrNAHQ6neiGB6loSXI0x3FZJC22aZGPpMkx19bWQFEU/+/ERC2kL51P1FJLL+NKUIu+NUUqZH12hXwvGAsBTUjIfX19/DaAXBdQuWtvfr8fy8vLsNvtvDscqZrqAbGBXTweRzAYxCuvvIJUKgWGYdDV1YWJiQlZY57KBanUWZatqFLPJwkWmus4HA5kMpl9Gx65Fa1areYd9sieuNB9L7flQVYApYhahMrDWohaSkFNKuT0XuFjM2b3kIsN4SORiCxpIf39/fB4PPz/v76+jv7+/oqPKxVNR8gEZPWtkt4xQakti0gkgqWlJeh0Ohw9ejSLROTO/JOCaDSKxcVF6HQ6HDt2DAaDgW9PGI1GdHR0IBqNYmBgAO3t7aAoCltbWzwRWiyWrCqyFn1khmF40Q5RT8oNtVotKmIgGx6BQACrq6v8OpXdbofBYMD29jZ0Oh2OHz+etWZVrOUhHJKSnL22tjY+eowMD2OxGC9qIU5tjSBqqclQL8VAq1ZBr7l7I6qlFzKxAnC73ejv78c///M/41vf+lbFx5WKpiPk3F1kOQhZKokSoUQ6ncbU1JTofm4tCZnk6cXjcUxNTcFms2UN7MLhMJaXl2G1WnHy5Em+EmxtbeWrAuEK2s7ODi+FJX1RQtRy9UVJi2dlZYWfctdyvUuYddfb28ufE0VRcLlcWF9fh8lkQjqdxq1bt7I+A7GKtpThoUql4m8QZHhIqvhcUUsikYDH46lY1FIKatNDZmA1aLI+x1rGN2m1WnzpS1/CQw89BIZh8IEPfADz8/MVH1fy69fslWoMOTcjij02ptNpOJ1OhEIhTE5OZtkZVvO8APH1J6EZ0cTEBDo7O7MGdoSoGYbB7Oxs1npZLoQraH19ffxriu0JC0la7FG/GIg4xmaz1XWjQwhhMEF/fz8OHz7MkyzpDUejUezs7OyTh9vtdlGP51KHh0TU0tvby294XLt2DRqNpmJRSymozdpbBhZDNi3Vuof89re/HW9/+9tlOVapaDpCrpZJvRgymQxWV1f5FbaZmZmi5F1O4Oe11SA++8wy3nWiD+8+PcD/nAyNhMnOwoGdUGFHzndlZQWhUAgTExO8QqpU5KsiE4kEIpEIgsHgvkd9UkWKmcqQG0Q6nS56g6glKIrC4uIiDAYDTp06te8GQ8x1hDdgmqZ5kl5dXc2ShwvbPlI3PMj/Cgk7EolAq9Wiq6urYlFLKajFUC+WYmDV7xf2SCFksqp2kNF0hEwgdyUK3K1GWZbF+vo6PB4PBgYGqp40/c8vr+PGegThRCaLkEn7Q61WY3d3Fw6HQ1RhR4h6Y2MDw8PDWetickG4J0xMwoltZiQSQTgchsfjQSqVgsFggN1uh9VqRTgcRiAQ4Cv5RhhikSeMYDCIqampkiovnU6XJQcGsuXhm5ubvMczGR4Sos4nDyf/S9M0lpeXkUgkMDc3B41Gs0/U0t7eXpKopZSkltr0kDNZO8iANBGMsmXR4JC7Qibm6T6fDy6XC11dXaIubHIjRTP4xZIfAOD2x7Hij2Okw8yfUyQSgdvthl6v3zewA8CfLwlkreVASKVSZa2BAXdJen19HQsLC9Dr9VCpVFhbW0MoFOIJqh75bhzHYXt7G263G4ODg5iYmJDlHPLJw4lNJWmJkH1bYcvDYDDw7n+rq6sYGRkRFRPlGx4SUUtrays/PBTeIEgQqpSkllr4Z8RSDDqtpc8jmsFYCGhCQha2LOLxuGzH5TgOL730ElpaWipW/pWCZxd2EU3uVfpqFfCdaxv4v399kjdsX15exszMzL6BXSQSwfLyMsxmM06cOFGz8y0GItE2m8247777+DYAedyORCLY3t7mFXekeiSKu2qRtPC8atG/zpdzR9o+ufJwo9GI4eHhvEZOpQwPyf41sT8lJF1M1CKHd0ox/OF/GYJRd5f0pUrEiTDkoKPpCJlALkMg8kVNJpM4evSobOtXUi+0//3KJvpajNgMJzHWacFT1zfxG0McQgEfTCYTZmdnYTabeSIm3sU0TWN6erohdomBu57KyWRS9LzE+rGFPJVJX1pMFl0KaJrmwwlKMXeqBoRtn66uLl4ePj09DY7j+E2XRCLBy8OFGx5Sh4cA9sVpAXuiFqPRiEOHDvF71UJRSzKZxNWrV6sqannLTPZAXGrfuhm8kIEmJGS5hnpEkJBKpTA1NYW1tTXZqibS+y3W7oglM7izFcV7zw7g7553Y9CmhmOXxstbNN77hnNYWFiAy+VCW1sbLBYLdnd3EQwG+eikRgBJPSGDT+EQqhjEPJWFQzOhLFpI0lJ6oiQTcG1tDcPDw5ienm6I/jUAfh4wMDCAs2fPisrDyc2KtDyEO8uF2g5iSS1iw0NC2EJRSzAYxKlTp7JELcR5rVqiFikrb4BCyA0NlUpV9lCPeP0Gg8GsQVM1PJGLXWhWoxbP/+lFbO3s4u9/Cdh1HAbbjPBn9GBZFuPj43wCw/LyMrRaLQwGA3w+H1KplGRyqgbIuhiRjJNBY6UQG5oJB1dks6GQdwVZryMKykZYrwP2igASkXXy5MmCbaZ8AQCxWAyRSISXhwPIIspC8vB8jnhkrZM8iRHVY66oRZivJ5eoRSohJ5NJ2awS6ommJGSg9AqZpGOQSi63YqpHrl4kEuHXrswGLUw2O773f4zB+Ho0eigUgtPpRGdnJ+bn5/lzJI/5KysrfAUpXD2rNknHYjHebL8W/et8xveEpIXeFeRzHxsbQ3d3d0NEOQmfIqampspeRywkD49EItja2uL3z6UIe9RqNS8GGh4eRm9vb1abQzg8VKlU/MDWN9EAACAASURBVPEISecTtVgslqyWR6EbohRCJmukjfKEUwmalpClEqjQvL6/vz/vClstCTmZTGJ5eRnJZBJTU1N7+6PPvoBEmoFJr80ivFz5rhg5iZG0sBcrF0mTp4toNJpXqVgraDQanpw4juPXFPv6+qDVahEMBuHxeMCy7L4IqVqo3giCwSCWlpZ4v265b5T55OFkw8Pv92cFAAjN/91uN7RabdYONiE9KcNDYL+opVBSS26COCBNFEKgEHKDgngiFxJgcBzH3/07OzuLmtfLScj5jlVIYWfUahBPZXD79m0kk0neu1jq64mRNLGoFCPpUgZmZC97Y2MDIyMjDdWPDYVCWFpaQnt7O86dOyeaJkJRFL/dQSrIYjvClSKdTvMy+yNHjtTU3pQIVaxWa5awh+yMr6+vIxQKQa/Xw2QyYXV1tWBvuNThodFohMFgQHd3N/89zSdqIeEC8Xg87yqk1LbGQUBzvIsSQaoSi8WCkydPSsrhkjs1RFghC4Umg4OD+xR2LMtCxdHY8SfR3T0ni4BCq9WK9mJzfYSLkTRxPSMVXiO0AIC9rY7l5WXQNI35+fm8huX51s8ISefuCAtbP+X4dwg9nUnbpBFuXmT1bW1tDS0tLTh27Bg0Gk2WPJwIS6Q8XRUbHhKCJtd4PlHL6uoqEokEnE5nXlFLOByu63aMnGhKQs6Xd0ZW2NRqNebn50uS6FajZUEGX0JCy82483q9WFtbg1GngdFkyZq0y41CJE0EKISkjUYjYrEYH8raKAMVEgTg9Xr5bZNSCU9YQRII/TuIr3E6nc7K+SNCjnyIRqNYWFhAS0tLUU/nWoI46wUCAczMzGSRm1R5OBmiks9B6oYHUDipRa1Wo7OzEz09PaKiln/7t3/DU089BY7j8KUvfQknTpzAqVOnKg47/dd//Vd84hOfwJ07d3D16lWcPn26ouNJRWNcEVUCIT6apuFwOJBIJEqWwgqPJSchx2KxPaI1GnHixAno9fosA6BAIMBLoU+fPo0W5y3evLuWyCVp8lkGg0G0t7eDpmm8+uqr+yppi8VS88ovEAhgeXkZXV1dsm11EBTy7xDm/KVSKd6/g3weGo0GLpcLkUiEF/E0CoLBIBYXF9Hb24vTp09LalEVkodHIhFsbGzw8vDcDQ+x1o9Yy4NcZxRFob+/P6tIEYpaPvaxj+GBBx7Al7/8Zej1enzzm99EW1tbxZFLhw8fxlNPPYU/+qM/qug4paIpCZkQgVqtxuLiIiKRCMbHx9HV1VU2SZRrUp+LRCKBra0tZDIZHD16FFarNUthR1EUlpeXodFocPToUb7yNOo08FPVNUsqBOGj9vDw8D4jJVI1RSIRuFwuURFHtUg6mUxiaWkJHMdlfWbVhlDIkSsNF34WFEXxIZ3xeBxarbbuCSHEFyOVSsnyhFNMHi60bhVLDxciEAhgaWkJAwMDWddZPke8n//850gmk/jQhz5U0XsQYnZ2VrZjlYKmJGTyCBYOh9He3o65uTlZeq6VVMiZTAYulws+nw/t7e3Q6/WwWCw8ERPFWDwex+Tk5L4NBZNOjSRdn6QRUnkS46J8gZO5VVO1SZplWayurmJ7e7us5O5qgPh3kM0Om82GkydP8kq7SCQCr9eLRCLBO7EV8lOWG0K/jtHRUT5qqhoQ9udzrVuj0eg+V0CLxcJX1mI3idxKemdnB3/2Z38GtVqNJ598sirvodZoSkIOBAIAgN7eXrS3t8tywZVLyMKB3dDQEM6dO4dgMIjbt28jHo/DZrOBoigEAgGMjY3lTaE26jRI0tX3EhCCGO4DKGsToJokLYxQqsa6WLlgWRZutxs+nw9TU1NZmy25MfbpdJofogr9O3IHZnIRZiKR4A2d6iWIEbZ+hK6AXq8XTqcTNpsNKpUKN27cyLIOFX4WHMfhu9/9Lj73uc/hk5/8JN7xjneU9Rm95S1vwdbW1r6ff+pTn8Jv//ZvV/xey0FTEnJ3dzfa2tr4KbscKJWQCw3syFBndXUVTqeT9wj2eDwIhUJZGw3kQjNo1UhmalMhk/W7QCCAycnJsoUKYiiFpIV9WPJljMfjWFpagkaj2beDXW+QDMWenh5JSSd6vR6dnZ37BmaEpMX8O8rZGec4Dh6PB5ubmxUJT6oBmqaxtLTEp8QL2xe5Xia3b9/GE088AY1GA7PZjC9+8Yu4ePFi2TesZ599Vq63IRuakpAJdDqdbIO4UozliTQ338AuGAzC4XCgpaUF9913H1+pkC9jromM3W4Hm04iSTOSTYnKgdDmcXBwMMtHoZqQQtIURSGTyYBlWfT19aG3t7dhHOxSqRQWFxfBcVzFN4l8idnksxBuNQhtOsmQKxdks6OtrU32QWelIH3lfK0ToTycZVksLCxAp9Ph3e9+NywWC77xjW9gY2MD73//++v0DuRHUxIy+cXK5fgmFcSQiGTqEctCQsSkBaBSqUQTlMW+jOSxVs1FkcpweOHFF2ESpHDY7XZZqkQioGhpaWkIfwdC0m1tbfwu8MDAAGw2G2Kx2L5KuhqP+MVAKs+NjQ1MTExUbSWxkDQ8EonA4/HwvhXCx/vd3V1EIpGGSmEB9q7phYUFqFQq0SSWXGxtbeGjH/0o7HY7fvazn9VkVvC9730PjzzyCHZ3d/Hwww/j+PHj+Pd///eqv66qxDih0rKH6gRiiLK9vY1oNIqJiQlZjvvCCy/gvvvu2/dzmqbhcrmyki/InjEZ2BFJ8cTERFmuVP9waRVP/MyFa39xP1TM3Uo6Eonwq1YtLS0l59kRmXYmk8HU1FReAUU9IIxQmpycFH1Pwko6EonUjKTD4TAWFxfR3t6O0dHRhqg8yeqZ1+vF1tYWNBoN78JGPg+r1Vq3/WfhQHF8fBzd3d0F/z7LsvjOd76DL3zhC/jUpz6F3/zN32wIEU2ZkHTiTVkhE1Qzxgm4K0JYX1/no5E4juNfk+M4rK2twev1ViwpPjXUikceGIUKe9JTo9HIX9BC2atwci1Ultnt9qyql5gpCWXajQJhhNL09HRBT4xi7Q5hH1YOkib7sfF4HHNzcw1VeTIMA4/Hg0wmg/Pnz8NoNGaZC3m9XkSjUT4+Srh6Vu0nolQqhTt37kCn00l6AvN6vXjsscfQ3t6O559/vqH63tVEU1bIwN4FQHpuR44ckeWYV65cwalTp6DRaPj+V3d3N4aHh/cp7HZ2duB2u9HT04OhoaGaV1DC9IlwOIxoNMrLf1UqFcLhMAYGBjA0NNQwGwocx2FrawsrKysYHBxEf3+/bBWRcFgWiURAURS0Wm3WDavQ2pnw3EZGRnjlWCNAeG5SK0+yH0w+E+IAJxykykHSwrlEsUR2cm7f/va38bd/+7f49Kc/jYcffrhhPucKIelNNC0hp9Np/pH3xIkTshzz2rVrGBwcxMrKCsxmM8bHx/mBHQCe6JaXl2G1Wvk/bxSEQiHeb9dsNoOiKDAMk/VIK5aIXAtEo1EsLi7CYrFgYmKiJj3sXJLOraQJScfjcSwsLMBsNtfs3KSCnJvJZKro3IQOcOQzoWl6H0mXcj0nEgncuXMHJpMJk5OTRVslm5ubePTRR3Ho0CE88cQTTWE4L4BCyOl0GtevX8fZs2crPl4ikcCVK1f42CSr1corhlQqFRKJBO8UNjk52VCPsiQ+iaSfCM9N6HZGvogkc01I0tWqohspQomcj7A/HwqFwDAMOjs70dXVVfVsP6kgHsrb29uYnp6uSsCn8CmLEDXx7xCu4ZG1TeG/29jYwPr6uqQ1O5Zl8c1vfhNf/vKX8Td/8zd429veVvfPtwq4twmZpmkwDIMXX3xRdBBXynHIwE6v12NsbIwPFCVJCW63G6FQCBMTEw3V6yLuXdvb2xgbG5MsHWdZNmtQFovFeMMdu92OlpaWiv2TcyOUiF9uo4BsdvT19aGnpyercqQoKkvAIRdJh+I0Xl0PY7jDhJGO/MNVMlDs7OzEyMhITVtOwnkF+UzIUJmQs9frhd1ux+TkZNGnrY2NDfzJn/wJ+vv78fjjjzdFcnQeKITMsmzezYhiyB3Y9fX1weFwIBqNoqOjAzabDeFwGJubmw1HKML4JNLDrvRLK1yzIiQtND8vRQYtjFAaGxtrqBZAMpnE4uIiVCoVpqen8+4651bSuSq7ckj6c88s42uX1zFzyIqn/ujMvj/PZDL808Ts7GzDbMQQkiZe3iaTCQzDQK/XZz1lCf2MWZbF17/+dXzlK1/BZz/7WTz00EMN8/2pEpQti3IgNK7v7u7mFXYMw2B4eBjRaBSbm5twOBxQq9UwmUyIRqNQqVRoaWnJa6JdKxCLUSJKkUs8IUzgIBAKFsT2gnNJKZ1O8657jbYbK4xRkuKLIbYzLibs0Wq1kkg6STP43qt7Ml6njwKVysBiuPv1JKrPwcFBTE1NNRR5xeNx3L59G62trbh48SJfFZPBejQaxdbWFuLxOJ599lm43W44HA6Mj4/j+eefb7ZecUVoWkLO54lcCEQcYTabcfLkSeh0uixhB0VRfNjjfffdB4PBsO9LGI/Hodfrs3aCayHvJUGUFEVhamqqJr1YMcFCvs8D2PvijoyMYGZmpmE2O4C7w87Ozs6K1Gz5hD3kpkU+D7FK+qkbXoQSe+uSNMPhZ4s+/NbRHl4FCKBo8GmtQcyddnZ2MDMzs2890WAwZPl3sCyL69ev45e//CWOHTuGaDSKN73pTfiXf/kXTE1N1eMtNByatmWRyWTAMAyuXr2KEydOFHwsJv4IwoGccGCXTCbhcDhA0zQmJyeL+tmSyiAcDvM9NpPJlEXScj2mk9bK5uZm1d27ykEoFOI3FMxmM2KxGBKJBAwGg+xqw1JBYpRSqRRmZmZqFqMkJOlIJIJIjMJfXkrDZtRgJZRBm1mL2R4bPvlgF9bW1qqqAiwX0WgUd+7cQUdHB0ZHR4veYNfW1vDII49gfHwcn/vc52rqCc0wDE6fPo3+/n48/fTTNXvdHNzbLQtCSsTPQowAyYQ/GAzyj6kMw4BhGD6QkZjskPQJKcitDITTar/fzwc7kuX8lpaWstbNyOCJtFYaQS1GIIxQOnLkyL5+JxkMkQw3obE7+UyqtTIoHCjWI0ZJ6NEAAN9/dQv+5B3815Od+LsXtjDTArzoCuCVQ2FMDh5CJpMBRVENs93hdrvh9/sxOztblFhZlsXXvvY1fPWrX8UTTzyBN7/5zTV/D08++SRmZ2cRiURq+rrloGkJmYD4WQi9VUm/cGNjA8PDw5iamtqnsCNrO4ODg5KcuwpBaGQutBykKArhcBher5c3WBc+yuYzjCGp03q9vuEcz6RGKBVSG4ZCIaytrRVVG5YDYrZjt9sbJkbp7EgrHn1wFMf7bcALW5jrUONFrwo7piHc12Xf1+4QDspqSdKRSAR37txBd3e3pHSR1dVVfOQjH8HMzAwuXbpUl5nB+vo6fvjDH+LjH/84Pv/5z9f89UtF/a/GKkFYIRODIaKld7lcOHToEM6dO8fndBH4/X4+ibqaX1hhblt/fz+Au14E4XAYa2triMVivPViS0sLzGYzL3+dnJxsuBWhSiKUiLG7yWTKSt8QPlm43e59YaN2u13S74gEBITD4YaLUeptMeK/HmnFUy/cBgC88eQc+ofiuDjejo42U96etNBDuZokzTAMXC4XQqEQDh8+XHS7g2VZ/MM//AO+9rWv4Qtf+AIeeOCBulX2jz32GD772c8iGo3W5fVLRdMSMgHxsyCDG6vVmjWwI31iUnUaDIa6VZ1iMTjk3NfX1xEIBKDT6WA2m7G7u4t0Os0Ha9bzUbZaEUqFnixI1UhigfKpDcnWjMvlwuDgICYnJ+v+2C+EMO9xYGgEeHkRep0G7zndL/r3c9sdQH6je+FNq9ztHzID6Ovrw+nTp4sew+1245FHHsH8/DwuXbpU19W8p59+Gt3d3Th16hSee+65up1HKWh6QuY4Di6XC3q9HnNzc3xsEtmcSKVScDqdSCaTmJycrLtSLBfhcBhOpxMdHR04fPgwtFot0uk0PzAU9l/LcXurBPWIUBI+WZBYIKHakLR/WJaFyWQCRVH8CmAjtXaAu37AJKPwZ4s+AIBOUxpxihndV0rSDMPA4XAgFovh6NGjRQeeDMPgq1/9Kv7pn/4JX/ziF3H//ffX/cZ36dIl/OAHP8CPfvQjvh32vve9D9/4xjfqel6F0LRbFjRN4/bt29jZ2UFHRwfm5uayLDFZluXdzsqNi68myOaHWq3G5ORkwapT2H8lRE3TNCwWSxZJyzn0E0YoNZJBEXB38LS9vY2Ojg5kMpksv2C51IblgohPNBoNpqam+Jvnj2/t4M++ewvf/+OzmOyWv7IUkrRQzJJL0sFgkA8ZlWLw5HK58Mgjj+DYsWP41Kc+1TCCFSGee+45PP744/9/e+ceFFX9/vH3ARaUi6ySAgKCwu5yU4Fdyl8aUpNayWRmF7uMNnabJgEzU8vJ7PL1Uk6DWWbW9Ne3YrJv94ulTX0jlV0QkLZ2cdFWLslNgXZZ9nb2/P7w+zntCsoCu3uO8HnN+Ac4dp5D7HOe83ye5/2mUxZCQRY1pFIpurq6YLPZ+IRETtgTExNF5ccGeEpPymQyr4bmL9d/JVVjW1sbDAYDXC6XR0K63KHhlRCzhRLwj2NxbGws5s2b53F/7tuG7s4bI9k2HAnE+LS1tXXQNwoHe1GkargVsrdcqZImbxe9vb3gOA6xsbEICQlBf3//ZStplmVx4MABfPDBB3xVTBkdY7ZCJtViREQELw7vdDrhcDj4ld3o6GjRVMXuo1i+lp4kXKpRYTKZPBISOTi83IfPaDSiq6vL5z57vsBms/Gz5AqFwus+tvu2IZHlvNK24Ugxm83Q6XSQSqWYNWvWoG8r/6k9h+e/0uNwyf8hQRrYB11XVxcMBgOSk5MRExPjod1BlnuIAw7LspBIJCgtLYVSqcQrr7wSsBnuq5jxXSHr9Xo8/fTT6O3tRXx8PNrb23HrrbfioYce4kez9Ho9QkJC+Nf66OhoQSq+7u5uGAwGSKVSv9onBQUFDXpoSJIR2fSTSCQerQ6yGp2QkDDqEUBfQ6rOlpYWr7SAL2U424aXLrJ4k6RZluVn2Yea2yUVcqifKuRBr/k/k1GHw+GxCRgWFjZoJV1ZWYlXX30Vp0+fRmpqKiQSiU8lbsc7YzYhX3vttaioqEBJSQmOHj2KW2+9FR0dHbj//vsRFBSE3Nxc5OXlIS8vD9HR0TCZTGhtbR2wVRcdHe230TfiwedyuZCVlSVI7y0kJGSA4wb58HV1dUGn04HjOEyaNAkOhwMXLlwI2KHhUPz999+8gacvF2Ou5G1IXu0H2za8dNqFtE/i4+ORn58/ZAJ3sBdfQCXBgXngDWUy6k5oaCguXLiAN998E4WFhaioqIDJZMKJEyf8OstttVpRUFAAm80Gp9OJu+66Cy+++KLfric0Y7ZlQdBqtcjKyuJ/2TiOg9lsxokTJ1BZWYmqqiqcOnUK11xzDVQqFZRKJXJyciCRSPgPIBmrItXlSHqv7pCq6fz580hLSwvIdMJwuNRCadKkSR6bdb29vfyh4XDngX0B2bA0m81IT08XTKTI/WfiLkMZGRnJb4VlZmZ63T55/1gTdh85japNN3gIC/kau93Ou2Snp6cP+XB1Op3Yt28fDh48iL17945Kzna4kLOQyMhIOBwOLFiwAHv27MG8efMCFoOPGN8tC0J2drbH1wzDICoqCoWFhSgsLATwj82MRqNBZWUl3n33XXR0dCAtLQ1KpRJKpRIpKSlwOBxobm7me6/uVbQ3c57uVjuJiYmifP13t1BKS0vj72mwQ0OLxYLe3l50dHSgsbHR49DQH8L27vElJyePyqPQF1y6behyudDS0oKzZ88iKioKLMuirq7O621Dp8u/FfJwTUaBi62/kpISzJ8/H0ePHg14S4+MOQIXH8QOh0M05z7+YMxXyCOFZVk0NDRArVZDrVajtrYWDocDc+bMgVKpRF5eHhISEvhJBovFgrCwMI8k7V55EA3gqKgovvcmJnxhoUQMNcnoHRG2J5uGo5li6Ovr462KZDKZ6H5+/f390Ov1vEM2ic9925D8udy24Vv//RNv/dcI7fOFCPJx0rHZbNDr9QgODoZCoRjy5+d0OvHmm2/i008/xVtvvYXrrrvOp/EMB5ZloVQq0djYiCeffBK7du0SLJZRML4F6v2BxWJBbW0tNBoNNBoN/vjjD0RFRUGpVEKlUiEnJwcREREedjcTJkyAzWYDwzCDShQKjb8tlFiW9Wh1WCwWD3NRcpB6pQUFcigml8tFty7u7izujV0R+TeX2maxLIuvzjL48pQFFcW5PvM2HK7JKADodDoUFxdj4cKFeOGFF0Qz2tjT04Ply5dj7969A958rwJoQvY3HMfh/Pnz0Gg0UKvV0Gg0aG5uxowZM5CTk8OPsN19993gOI73qyMVI1lOEOIVTEgLJfcDst7eXlit1kHfLsjySXx8PJKSkkTV3gH+kaCcMmUKZs6cOaoE6nK5sOM7Pf5zsgMfLI+FyWQadQvIarVCp9MhLCwMcrl8yB6/0+nEnj178OWXX2Lfvn3Izx/oWiI0L730EsLDw7FhwwahQxkuNCELgcvlwv79+7Fr1y7I5XL09fWhr68PmZmZ/KHhzJkzYbFYPOzo3ZORv7Up3C2UUlNTBVc84zjOQ0O6p6eHF1aKj49HTExMQA8Nh8JdbMeXzifbDxnwZX0bKjfeAGDwFhCAIRUBh2syCgB//PEHiouLcdNNN2Hr1q2iEcLv7OyERCKBVCpFf38/Fi9ejE2bNqGoqEjo0IYLTchC8fnnn+P666/nD03sdjvq6+v5fvRvv/2G0NBQ5ObmQqVSITc312MY32q1+kXQ3t1CSaFQiMpCCRgo3RkeHs4nafJa7260GhkZGXAN6PPnz8NgMCAhIQGJiYk+fXC2dPfjfJ8dcxMv39YaytswNDQURqMRUVFRSEtLG/Ln43A4UFZWhm+++Qb79u2DSqXy2f34gvr6eqxevRosy8LlcuGee+7B1q1bhQ5rJNCELFY4jsPff/+NqqoqvtVx+vRpxMfH8/3o2bNnIyQkZNDRu+G+vrovTwghyO4N7jZKKSkpgyYSUjG6917JoaF7xeiPe7Pb7R6bgGLpqwL/LPc0NTWhu7sboaGhAxZZBts21Gq1KCkpweLFi7FlyxbRVMVjFJqQryZI0qysrOQPDclBFml1yGQyD4EYUhmRfvRgo3fEJ9AXfU5/4HA4YDAYYLVaoVAohr0cQypG8lrvvvpMHl6jMZ51PxQbySZgIOjr64NOp0N0dDS/ln05V2y9Xg+r1YozZ87g2LFj2L9/P/Ly8oS+hfEATchXO06nEzqdjl9gqa2tBcdxmDt3LlQqFfLy8hAXF8dXje6jdxMnTkRnZydcLhfkcrnoFLjcE52vvQBJMiJJ2n2rjiRpb6pBi8XCj9qNdBTQnxDnm/b2dq8meOx2Oz755BO8//776O7uhkQiwfTp0/H6668jMzMzQFGPW2hCHmuQcakTJ07wVXRDQwMmT57MtzqysrLw448/QiaT8YIvRIZzpN59vsZsNkOv1yMyMjJgM9mXbhpeyR7KPdEpFArRjdoB/4gVkTefodpXdrsdu3fvxpEjR7B//37k5OQAuKh8SFo9/qK5uRmrVq1Ce3s7GIbBY489htLSUr9dT6TQhDweII4YarUa5eXl+O677yCXyxEbG8sn6YyMDH4eWMjRO/fpBH/MPA8HsrBBqmjSpw8NDUVfXx9iYmJEuYBCdLy7urq8MhkFgJMnT6K0tBRFRUXYvHlzwHVIzp07h3PnziEvLw8mkwlKpRKff/75eKvKaUIeT3R0dKCkpAQ7d+7EjBkzYDAY+H50TU0NrFYrsrOz+SSdlJQU0NE7ImSTmJjo8+kEX+B0OtHY2Iienh5MmzYNVquV92ETg6g98I+Y0tSpU5GcnDxkHDabDa+99hp++uknvPPOO5gzZ06AIr0yy5Ytw9q1a7Fo0SKhQwkk4y8hHzx4ENu2bYNOp4NGoxHdCI+Q2Gw21NXV8f1orVaL8PBw5OXl8aN3RPXOl6N3ZKVYIpFAJpOJ8iS/s7MTjY2NmDFjBqZPn+7xsHAfM+vt7R2gl+ytjslocLlcOHPmDLq7u72ee66rq0NpaSnuuOMObNy4UTSVvtFoREFBAbRarejs0vzM+EvIOp0OQUFBePzxx7F7926akK8Ax3Ho7u5GVVUVn6SJ6JFKpYJKpUJ2djYYhhnR6J273563ywmBxmazoaGhAQCgUCi8flgMNsEQGhrq8fDy1Vhcb28v9Ho9b5U1VOK32WzYtWsXKioqsH//fsyePdsncfgCs9mMhQsXYsuWLbjzzjuFDifQjL+ETCgsLKQJeQSQJEoWWKqqqmAymZCens63OlJTU/kDssuN3hFPttjYWK9erQMN2WRrbm5GWloapk6dOur/ps1m8+hHE11t98mO4VSpLMvyGiMZGRleOXLU1NRg3bp1WLFiBTZs2CCaqhi4+BArKirCkiVLsH79eqHDEQKakGlCHj0OhwNarZbvR9fX1yM4OJgX+FcqlZg2bRpMJhPvrsEwDOLi4hATEzNA9U5oyMwuUd3z1zq2u8obSdROp9Nj0/ByEy/d3d1oaGjwehvQarVix44dOH78ON555x1kZWX55Z5GCsdxWL16NaZMmYKysjKhwxGKsZmQb775ZrS1tQ34/r/+9S8sW7YMAE3I/oSIJF0q8E+E/5977jksXLgQYWFhfLVot9v96oDtDe7TCQqFQhDVPZfL5aHyRkTsyaFhREQE2tra0N/fj4yMDK+E7aurq/HUU0/h3nvvxfr160Wj9+HOr7/+ihtuuAGzZ8/m35a2b9+O2267TeDIAsrYTMjeQBNy4LBarVi8eDEyMzNRUFCAkydPoqqqCp2dnZDJZLx2dEZGBt97DfTo8j+bzAAACGRJREFUHVnLjo2NxYwZM0TVQmFZFmazGX/99Rfa2toQEhIyYIllsLVnq9WK7du3Q61W48CBA8jIyBDoDiheQhOyPxPyoUOHUFpaCpZl8cgjj2Dz5s1+u5bYaW1tRUJCgsf3WJaFXq/ntTpqamrAsiwv8K9UKpGYmMhvGZrNZg9zVV+M3jkcDl5MKT09XZTOyO4mo+np6ZgwYQKvTUFaHeTQ0Gq1orGxEVOmTMGuXbtw//33Y926daKsiikDGH8J+bPPPkNxcTE6OzshlUqRk5OD77//3ufXYVkWcrkchw8f5q2YPvroo/E26D5sLBYLampq+C1DnU6HSZMm8QeGubm5HgL/oxm9a29vx5kzZwKu9TwcyLhdSkoK4uLirhijzWbDb7/9hu3bt0Or1SIiIgIKhQKrV6/GihUrAhg1ZYSMv4QcKI4fP45t27bxyX7Hjh0AgGeffVbIsK46OI5DV1eXh8B/S0sLkpOTeUGl7OxsXh3Pm9E7q9UKvV6PkJAQyOVyUR0oEoZrMgoAlZWV2LBhAx588EGUlpYiKCgIRqMRNpsN6enpfo13zZo1+PrrrzFt2jRotVq/XmsMQ01O/UVrayuSkpL4rxMTE6FWqwWM6OqEYRhMnToVS5cuxdKlSwFcPPg6ffo01Go1jhw5gp07d8JisXgI/MfHx8NisaClpcVj9I686svlcq+sioSAVO7eKsdZLBa8/PLLqKurQ3l5OeRyOf93M2fO9GeoPA899BDWrl2LVatWBeR64xmakCmiIigoCDKZDDKZDA8++CCAixXlyZMnoVar8d5770Gr1SIsLIwX+I+IiMAPP/yAW265BeHh4TAYDGhqavKYjxa6UnY3GVWpVF61Xo4dO4ZnnnkGq1evxuuvvy6YKFRBQQGMRqMg1x5v0IQ8AhISEtDc3Mx/3dLSMuBQi+I7QkNDkZ+fj/z8fKxduxYcx6G3txdHjx7Fa6+9Br1ej5SUFFRXVyMvLw/5+fmYM2cOQkJC0NPTg6amJsFG7ziOQ1tbG4xGo9cmo319fXjppZeg1Wrx8ccfQyaT+T1OijigCXkE5Ofnw2Aw4M8//0RCQgLKy8vx4Ycf+v26tJd3EYZhIJVKERwcjOXLl2Pt2rUICgpCU1MT1Go1jh8/jjfeeAPd3d0eAv/Tp0+HzWZDW1sbDAaD30fv3E1G8/Pzh5yG4DgOR48exaZNm7BmzRqUlZUJLpVKCSz0UG+EfPvtt1i3bh1YlsWaNWuwZcsWv1/zl19+QWRkJFatWjWuE7K3OJ1O/P777/waeG1tLRiG4QX+ST+aTHX4avTO3WRUJpMhJiZmyH/T19eHbdu2Qa/X48CBA0hNTR3pbfsFo9GIoqIi+ns3cuiUxViEfjBGDhH4r66uhkajQVVVFRoaGjBlyhSP0buJEyfyUx3DHb3r7++HTqdDeHg40tLSvKqKKyoqsHnzZjz66KN44oknRLW4QqC/d6OGJuSxCP1g+BaO49De3u4hqNTW1oZZs2bxSTozM5MX+L/c6B3DMGhubsZff/0FhUKByZMnD3lts9mMrVu3orGxEe+++27ApiaGy3333Yeff/4ZXV1diI2NxYsvvoiHH35Y6LCuNmhCHovQhOx/XC4XTp065SHwb7fbPQT+k5OTeV2Knp4e2Gw2hIeHIykpCVKpdNB1ZwLHcfjll1+wefNmPPHEE3jsscdEWRVTfApNyGMRmpCFwWq1egj8//777wgPD0dERAQuXLiAt99+G3FxcXw/mhjOuiu7TZgwASaTCc8//zyMRiMOHDiAlJQUoW+NEhhoQh6L0IQsDoxGI1auXInU1FTMmjULNTU1OHv2LJKSkniB/9mzZ/MC/+Xl5SgvL4fNZsP8+fNRXFwMlUolSn0Nil+gCXmsIVQvj7oGD8RkMuHMmTOYO3cu/z0i8UlaHdXV1TCZTJDL5ejo6MCECROwceNGtLS0QKPRYMmSJbj99tv9HisVwhIFNCFTfAN1DR45DocD9fX1+Oqrr7B169aA94qpEJZooFoWFN8QHx+P+Ph4ABfF1DMyMtDa2ko/1F4gkUh4uVEh0Gg0SEtLw6xZswAAK1euxBdffEH/34kUerRLGRZGoxG1tbW47rrrhA6F4gWDCWG1trYKGBHlStCETPEas9mMFStWoKysbLxZuFMoAYEmZIpXOBwOrFixAg888MB4tHC/aqFCWFcXNCFThoTjODz88MPIyMgIqIW71WrFtddei7lz5yIrKwsvvPBCwK49VnAXwrLb7SgvLw/IZAdlZNApC8qQCOUaTLQnIiMj4XA4sGDBAuzZswfz5s3z63XHGkIIYVEGQMfeKGMHi8WCBQsW4O2336YHipSrEa8SMm1ZUEQNy7LIycnBtGnTsGjRIpqMKWMampApoiY4OBh1dXX8dhtdGaeMZWhCplwVSKVS3HjjjTh06JDQoVAofoMmZIpo6ezsRE9PD4CLwu+HDx/2u+W9mDl48CCysrIQFBSE6upqocOh+AGakCmi5dy5c7jxxhsxZ84c5OfnY9GiRSgqKgpoDCzLIjc3N+DXHYzs7Gx8+umnKCgoEDoUip8Y7pQFhTKuYBhmPQAVgEkcxwmflQEwDPMzgA0cx9EyeYxBK2QK5TIwDJMIYCmA94SOhTI+oGpvFMrlKQOwEUBUoC7IMMwRAHGD/NUWjuO+CFQcFGGgCZlCGQSGYYoAdHAcd4JhmMJAXZfjuJsDdS2K+KAtCwplcOYDuJ1hGCOAcgA3MQzzb2FDoox16KEehTIE/6uQNwh9qMcwzHIAewFMBdADoI7juCVCxkTxLbRlQaFcJXAc9xmAz4SOg+I/aIVMoVAoIoH2kCkUCkUk0IRMoVAoIoEmZAqFQhEJ/w/fDDGMUVePKwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e592ccf8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Create the magnetic species and turn off the diffpy.structure option.\n",
     "mspec = MagSpecies(useDiffpyStruc=False)\n",
@@ -421,11 +1283,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e59f06a0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Now we can set up the MPDFcalculator and plot the mPDF.\n",
     "mc = MPDFcalculator(mstruc)\n",
@@ -434,7 +1307,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {
     "collapsed": true
    },
@@ -466,9 +1339,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -494,7 +1367,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {
     "collapsed": true
    },
@@ -516,11 +1389,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Since you are not using a diffpy Structure object,\n",
+      "the spins are generated from the makeAtoms() method.\n",
+      "Please call that method if you have not already.\n",
+      "Since you are not using a diffpy Structure object,\n",
+      "the spins are generated from the makeAtoms() method.\n",
+      "Please call that method if you have not already.\n",
+      "No magnetic form factor found for that element/ion.\n",
+      "Using generic magnetic form factor.\n",
+      "No magnetic form factor found for that element/ion.\n",
+      "Using generic magnetic form factor.\n",
+      "Please make sure your magnetic structure contains a\n",
+      "magnetic species with MagSpecies.struc set to a diffpy\n",
+      "structure or MagSpecies.latVecs provided and\n",
+      "MagSpecies.useDiffpyStruc set to False.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e58595f8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Create the magnetic structure object and load the species.\n",
     "mstruc = MagStructure()\n",
@@ -543,11 +1447,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'big': 0, 'small': 3287}\n",
+      "dict_values([0, 3287])\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e586c978>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Now we can set up the MPDFcalculator and plot the mPDF.\n",
     "mc = MPDFcalculator(mstruc)\n",
@@ -559,7 +1482,7 @@
     "### index of each species, use the getSpeciesIdxs method on the magnetic structure.\n",
     "\n",
     "mc.calcList = mstruc.getSpeciesIdxs().values()\n",
-    "print mc.calcList\n",
+    "print(mc.calcList)\n",
     "\n",
     "### Now we can plot.\n",
     "mc.plot()"
@@ -567,7 +1490,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {
     "collapsed": true
    },
@@ -592,11 +1515,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e590b438>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### We will load in a structure from a CIF file and modify it to simulate a 1-D material.\n",
     "astruc = loadStructure(\"MnO_cubic.cif\")\n",
@@ -634,11 +1568,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e58d5f98>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Now plot the mPDF.\n",
     "mc = MPDFcalculator(mstruc)\n",
@@ -649,7 +1594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {
     "collapsed": true
    },
@@ -688,9 +1633,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -715,11 +1660,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 26,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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C/A5a6//RWpdrrcuBHwHva633WHaZHnjd9+sc7VRVycS/W6Te9OlSXruxMbXtykQaGqCqii3dxnL//ZbtSsEpp/gClSiqqwGo69ofEHEqKHARqOHDYd26FDYu+8gogQImA2u01uu01g3A00C0yZKrgKeS0RDtr6HJWIL/TaCsPCed5LzjlClQXy/VS9s7GzdCczM//fMIvvc92LXL8lpFBaxd66+HSgTbt0N+PnWF3YAYAjV0KGze7PKiD2SeQPUDNlueVwe2RaCU6gDMAKx5bTTwtlJqgVLqRrcvUUrdqJSar5SaX1NTE/F6UVERu3fv9kUqA9Fas3v3boqKiuCTT6BrVzjmGOedTzhB7j/9NHUNzFQCI/U1SJBNYKAv+FVeE8e2bbJIt0FczkagIoIkAIYMCUb9+TiTzVF8FwAf2dx7p2ittyilegJvKaVWaq0/sL9Ra/0w8DBARUVFhAr179+f6upqnMTLJ/0UFRXRv39/saCmTJHUMU4MHAi9e4ubb+bM1DYy01i7Vu4CArV9u+W1wGJpFi2SqD6f1rN9O/TpExSkmBYUwPr14u7ziSDTBGoLMMDyvH9gmxNXYnPvaa23BO53KqVeQFyGEQIVi/z8fIYMGRLv23xSSV2dZIO2ZcEIQymxonwLCtatQxcVsb1esn2ECVSvXpJZYuHC9LTtaGL7dhg8OChQRUVRgiSMQPnzUK5kmotvHjBCKTVEKVWAiNDL9p2UUp2B04CXLNs6KqVKzWPgbGBZSlrtk3qWLZMoPjP6d+P44yVr9P79qWlXprJ2Lc2DhmICdyNq5U2YIBaUT9vYts27BdW3r7zoC5QrGSVQWusm4BbgDWAF8A+t9XKl1E1KqZssu14CvKm1rrNs6wV8qJRaDHwOvKa1npOqtvukGLPoNLD41xUTVr2snY9V1q2jvm9okXcggUeIiRNhxQo4dCi17TqaaGyU6JPevSMEynEOKidH5qF8gXIl01x8aK1nA7Nt2x6yPX8CeMK2bR1gW+Thc9RSWSmZOAcNir6fEajFi9t34tj16zl47LTg0wiBmjBBJuyXLg0Fl/jEx86dYtV7taBA3Hy+QLmSURaUj49nFi8W8XHJ+h6kf3/o0iVkcbVHDhyA2lrquoWmdx0tKPAj+dqCmdizWVCuc1DgW1Ax8AXKJ/toaRHBieXeAxGw8ePb91qoQGn3g536BjdFCNTAgSLkvkC1nm3b5D5eC2rfPodJQR/wBconG1m7VqL47Gl73Bg3TlxX7TVjd6Cs+/7S0JLCCIFSSgTfF6jWY7GgTPWZqHNQEB5q7hOBL1A+2YexhmwCtWaNS3md8eNF0NqrKyVgQe0rFguqWzcHgQIRqCVL/BIlrcVYUL16ceSIxEDk5XmwoCAl5+Z778FLL8XeL5PIuCAJH5+YrFgh98cdF9ykNYwYIfX3ItZXjx0r98uWtc8FkQELak+RCFRZWRSBOnRIlN4tO4ePO9u3i/oXFnLkiFhPEEOgzHrLFAjU6afLfUtL7KnbTMG3oHyyj5UrZc4kUBYeYPduud+1S8QqDFOvauXK1LQv09i6FTp3pralIyACVVvrsJ+Z0/PXQ7WOQJojIEygogZJdOoE3bsnXaCshbWzabrLFyif7GPVqpDoBLBaTRFrcjt1kkWRxvJqb2zZAv36cfiwPHW1oI47DvLz/Xmo1hJIcwR4t6AgJaHmVlHKptR/vkD5ZBdaiyVkc0HtsWRk3OKUHOu449q3BdW3b1CgevSQKbkICgpg9GhfoFqLiwUVNUgCUiJQ1kT1YWmuMhxfoHyyi23bZPhvs6CsAmV9HOTYY8WCao8Z6i0WVEEBdOxIUKwi8CP5WofWERZUUZG8FNOCGjRIym4kMcrUakEdOJC0r0k4vkD5ZBfGCrJZUGYOClwuwOOOk4kXE2nVXmhpkd8csKCKi2Xq7tAhF60uL4cdO7JrmJ0JHDggtcfinYMCEaiGhqQec6sF5QuUj0+yMAIVxYJyDAAw+7e3eajdu2WGvE+fMIFqbnYpNGwCJXwrKj4si3Qh0sXX1BTFQDLpujZuTFrzfIHy8UkFq1ZBSYkEPViwCpSrBQXtbx5q506579kzKFDFxbLJ0c1n1pZluEAdPCiV6j+Iu5hOkrAs0oVIgYIoVtTgwXKfRIHyXXw+PqnABEjYFnLs2ycBaOByAfbpA6Wl7c+CMuGNZWUcPizWk4nOd0xc3qWLdJgZLlDvvgsffQTf+U66WxIghgUFUQQqhRZUbq4vUD4+ycMhxByks+3ZU3TL8QJUqn1G8hmB6tmTQ4c8WFCQFYESX3wh9507p7cdQdpiQZWUyAJfxzQoieHAARGnXr18gfLxSQ6HDsko0yHLwaFDcp2XlrrMQYG8r70JlHHxBSwoMwcFUUo/lZdDVZVLLHpmYH7Wrl3pbUeQbdtEkbp0ASRewhokAR4CJZJoQR06JP97586+QPn4JIfVq+XewYKqq5Pw6U6dolyAI0ZIyHV7KspnLKju3eMTKK0lwW6GsmOH3GeMQG3fLtZTwPUclwUFSRco89936pRdxaV9gfLJHlxCzCE0QiwtjSFQ0L6SxtbUiPsoL89bkARkRSSfsaD278+QpW2BUu8GJ4GKulh38GARqCT9GDP/WFKS0YZxBL5A+WQPq1bJCNUIjQUjUCUlLml8IJQo1lhi7YGdO2VyDrxbUFlQG8q4cRsaCJa2SCvGggrQKguqrs5llXnbMfOPZg1ctpBxAqWUmqGUWqWUWqOUusPh9WlKqf1KqcrA7ede3+uT5axcKReyMQEsGIHq2DHKCNEI1Jo1yWtjplFTI8n3wLsFZWpDLVyYmja2Aut/nBEuqygWlOc5KEhaoIR9kXa2kFECpZTKBR4AzgVGAVcppUY57DpXa10euP0izvf6ZCsrVzrOP4FHgerSRRLRtXOBimlBAUyZIlnNM9QfVFcnUWkQvgg1LTQ0yIJomwVlTXVkdnMlyaHmxsVXXBxlYJKBZJRAAZOBNVrrdVrrBuBp4KIUvNcn02lpERefS50iTwIF4h5sTy6+1grU1KmS/uCzz5LfxlZQVxdaq512C8pEbLRlDirJAuW7+BJDP2Cz5Xl1YJudk5RSS5RSryulRsf5XpRSNyql5iul5tdEVLfzyUhM9J2LBVVX51Gghg9vPxZUc7OEufXsidZxuPgATjpJXH1z56akqfFSVwf9Ald32i0o2xqopiY59HHNQXXrJhOoSbSgfIFKDQuBgVrrccAs4MV4P0Br/bDWukJrXVEWGF36ZDirVsl9W1x8IAK1eXN2+Tlay549EhVWVkZDgzz0bEF16QLjxmWkQGktbc8YC8pkkbAs0oU456CUSmqouTWLiGui4Awk0wRqCzDA8rx/YFsQrfUBrfXBwOPZQL5SqoeX9/pkMVFCzBsb5daxo4cw2vYUam5LcwQiUIWF0h/G1OipU+GTT1yyyqaPw4elg+3VS567Rm2mCmNBWdIcQZwWFCRVoOxZRKK6GzOITBOoecAIpdQQpVQBcCXwsnUHpVRvpWQ1nFJqMvIbdnt5r08Ws2qVrDK0TEQbTEdrLKiGhih9anuK5LNkkTDWUnGxiFNxsQdXz+mny04ffpjUZsaLGYAEoufTH8dhBCrQoDYJVAqi+CB73HwZJVBa6ybgFuANYAXwD631cqXUTUqpmwK7fRlYppRaDNwPXKkFx/em/lf4JAWXJLEQutiMQIGHUPP2EChh0izYLCjwOBdx1lnSu77yStKa2BoyTqC2bZPo0IASuQlUTKtl0CBJO+6aq6v1eEoUnIHkpbsBdgJuu9m2bQ9ZHv8B+IPX96aV+no5O3MyahyQnaxaBdOmOb5kFShzqOvqgmnRwunaFbp3bx8WlFn02a0bhwOBBKaD8hRuXFIiVtQrr8Dvfuc4OEgHRpC6d5cmpb2zdVgDBZFzUDEFylp2Y8yYhDXPzNn5FpRPiFmzxCU1fHgo9bJP6zh4UAIbXELMTYflyYKC9hNqbsLbunZtnQUFcMklIubz5yelia3B/LclJfI7MsKCsq2BglYIVJJCzc33WuegfIFqz6xYAd/7noTqHjokF3m2zEpmIlVVch8lgg/iEKjhw9uHQO3dK0WyOnSIECjPCza/8hU5sI88krRmxov5bzt2zBCB2r49MRZUkgTKOkdrLKhsCWL1BSoZ3HOPnAnPPQdPPCEd7MMPp7tV2YsJMY+ySBfiEKhhw6C62sOsdZazd6/4OZVqvQXVuTNccQX8/e+hoAs7O3eKlZWi2GWrQMVcVpBstE6cQPXqJVMCCRYoa4CM7+Jr7zQ2wvPPw2WXycTpOefI3MlvfiMr+HziZ+VKmVwyAQ42zMVmOiyI0WkNHSodSxLLG2QE+/bJnBu0XqAA7rhD5lN/9rPw7atXi3egVy9xm556akrqX9gFKq2d7Z49MtCJIlCm0nNMgcrJgf79xZ2dQKz/vS9Q7Z3335eO4ZJL5LlScOutkgnhtdfS27ZsZdUqmUA2yc1sxG1BDRki90f7Wqi9e10FKq6cbMccI+fwww/DL38JixfDD38Io0fD22/DT38qXoN58+DKK5NuSWWUBWVbpAuh7OrmdFVKDCNPBvuAAWLdJxDrf9+WOaiFC+Hb305t9viMi+LLet54Q87Gs84KbTv/fMnL8uCDcJGfHjBuoiSJhXCBam6WxzEtKID16xPTvkxl715JoUMbLSiAX/9aLM6f/SxkSV13HfzqV6HOuUMHuPlmeOkluPjixPwGBzJqDsoIVBQLyjz2NA3dvz989FHi2kf49dEWC+qnP4XXX4cLLoAvfSlx7YuGb0Elmk8/hYkTQ0N5gLw8uOEGePNN2LQpfW3LRlpaZA4vikBZo/hKSsK3OdKnj/QYR7sFFcXFF3dW67w8+Mc/pPN88kkR98ceC184feONYunee29Cmu9GRllQtiwSkACB2rJFzvsE4eTia02QxLJlcp/K+CJfoBJJQ4OE4554YuRr3/iGuD7+/OfUtyubMXnzXAIkoBUuvpwc6UiPdoGyuPisE+XQyqShSklk6tVXh9bsWMnNFR/QBx8kdX6vrk6aUlSUAXNQibagBgyQeewEJrFO1ByUyc6SyqlbX6ASyZIl4qCdMiXytSFDYPp0iepL4OjoqCdGklhwjlKKmZ9t6NCj28WndSiKjwS4+Lzy5S/L/QsvJOHDhbo6ESalMsCC2rYtlAQyQJstKEhooIR1ANfaOaiWllD8S4KnyKLiC1QiWbxY7idNcn79uutk1J6BGaIzlihJYg2HDsm0X16eDOKLijx0WkOHHt0WVF2dTMhZXHz5+XKMIOTiS3g8w/DhkgXhpZcS/MEhjEBBhsxBWawnSJBAJVAFrIOT3Fy5VuIVqH37QkHIu3cnrGkx8QUqkSxfLmeBiRKzc9llUFoKjz+e2nZlMytXihVgEq85cOhQ+JSfp1H1kCFy1e3dm5h2Zhrmd1lcfMa6hNDjpERknXWWZEFP0uJ0q0Cl3YKyrYGCcIvFEJeLD5ImUKZd8QqUdQmcyaCVCnyBSiTLlsGoUe659zp0kJX5zz6blISQRyWmim6UPHD2ztdTp3W0R/IZgbK4+EwHBR6LFraWU0+FI0f49A/zefDBxH+8XaAaGtK4xNDBgjKdv3VVhGeBMklnk+TiM/fx/u9GoAYM8AUqe1m+XNaGROO66+SMefbZ1LQp24kRYg6harqGuATqaHXzWfLwQShZqCGpCzZPOQWAl37wATffnPgOzS5QkMZACVsePtOWDh3Cx1SeBSonR5akJNGC8lRqxYYpCjl8uO/iy0727oWtW2ML1IknikXgu/liU1srxzTK/BNEdr6eXXxw9AqUzcVnyi0YkipQPXrQNHQEFUiC2XnzEvvx9jkosy3l1NXJOepgQVmPNYhAec6sleDFukagjEXXmnk7E3Q0cKB8Xqpy+fkClShWrJD7UaOi76cUXHutFIFrDwlL24KHCD4I77DAo0B16iT1Go52gQq4+OwinlQXH7B30ATKqQQSX4PPyYJKi0A5hJiDu0B5npJLcLqjQ4dEnIwIggu2AAAgAElEQVRF15rQfKtAQercfL5AJYq1a+XelBSPxte/Lqb8E08ktUlZT4wksYZWCRQc3aHmNhdfSi0oYGO3coaxjk7sT3hYcsYIlMMiXYgM2oFWCFQCF+va5x9bE1hiBMoEGRqXX7LxBSpRrFsnQxSTMj8afftKEtk//zmUm8cnkpUrJS522LCou7VaoIYMObotKKUkGzkpDpIAqorLATity5KUCFRa5qAc8vCZttgtqIKCOARqwADxByYo8a59cNKxo4d1gjbM9WS0+MCBhDQtJr5AJYp162Ry0yWhaQTXXSejpLffTm67spmVK8XKsS4occA+Yi0picOC2rjx6Bwk7N0rbsxARKlbmHmyOvbl+SJQ0zovOnotKOOGM6HhARLi4rN+fhtJlAVVWChecWjHAqWUmqGUWqWUWqOUusPh9WuUUkuUUkuVUh8rpcZbXtsQ2F6plEptCdB162KO9MO48EIoK5Ms0D7OmBDzGDhZUJ5GiEOHSv6WLVta38ZMxZKHDyI7qWQL1LpDvdmT050xajlbtybuc7V2Fqh4LYKEUF0tBzIwz2dImEAlSNnt/73nAZyFgwflfZ06yfN2KVBKqVzgAeBcYBRwlVLKHnWwHjhNaz0W+C/AXglwuta6XGtdkfQGW1m3LhS67IXCQvjRj8SCevfd5LUrW2lujpkk1tAmFx8cnW4+Sx4+iOw0k+3iq9mlqO54DIMaqlzrHLaGhgY5Ncz/7Sk5cLLYvFmsJ9savTYLlLHIEmRBOUW5xivovkAJk4E1Wut1WusG4GkgrD6F1vpjrbVZ/v8p0D/FbYzk8GEJh45HoAD+7d8kLOa73/VLwtvZtEmOSQwLyoyo7T52T4s3j+a1UJY8fJB6C6qmBmq6jKTvgVXs3p24hbTWTOYQEqi0WVD9I7ufNgtUWZnkpUqSBWUGcPGkuTp4UN7X3gWqH2AdNlQHtrnxTeB1y3MNvK2UWqCUutHtTUqpG5VS85VS82sSkTXYRILFK1BFRfDQQ7LA96c/bXs7jiZMDr4YFtSRIxLsZLegwMOoesAACcI4GiP5bC6+VFtQu3bB3p7HUHpwGyX6QMIWd2aUQBkLyobdYoGQQHkShQQv1rUHSZSUSDviSXNVVyfvKy2V5+1VoDyjlJqOCNTtls2naK3LERfhTKXUqU7v1Vo/rLWu0FpXlJWVtb0xZgQer0ABnHsu3HSTzEU99FDb23K04DHE3Fru3eBZoPLzpYNJoQV1+LAUXU5y0dkwF19zs1iUqbKgtBYL6vBA+e9GUsWOHYn5bLtApS1IoqlJovgcLKgDB4LBk0EKC+W4eI7HGTAgqUESEN8xMy6+3Fx5f3sVqC2AdUjSP7AtDKXUOOBR4CKtdXBsprXeErjfCbyAuAyTj+ng4gmSsHL//XDeeeLy+/d/T92/n8msXCnVYHv0iLqbvcOyPvYcyZdCgfrud2HaNHjrrSR/kUOpDesoOj9fOptkCNSBAxJ70jR0JADHsCph81D2/zs3VzrflFtQ27aJ6W6zoBobpY1OAgVxuPn69iVR0SVuAhXPMTMCBeLmS1UXlWkl3+cBI5RSQxBhuhK42rqDUmog8DzwNa11lWV7RyBHa10beHw28IuUtHrjRjkDYnSmruTnS/2c738ffv97SYM0YwYcd5y4ARsbJaWKuR08KAsSTjtNSsh7DW3PJjwkiYUECdTLL7euja3g9YBD+tVX4eyzk/QlR45Ir+RSTdfQmqShXjDLd/KOHY5WihF6ddIECqTjTLlAGfebzYIyC1htgX1hAmVfxOtI375ykmgd8xqIRSItKGjHAqW1blJK3QK8AeQCj2mtlyulbgq8/hDwc6A78Eclf1xTIGKvF/BCYFse8Het9ZyUNLy62jGaJy4KCuAPf5D1UbNmwTvvwDPPhF4vLBQHcGmpnGHvvAMPPihC9eCDIlRHEytXivszBtZy74a4LsAhQyRVs/UKTBJ794Yi2r/4IolfZMsi4XSMzPNkWFBmWrd730J0774M3rYhaS4+SLNA2Swoc+ijCVQsGhth8+E+DDW5/kxkQiuxz4m1JvLRBElAOxYoAK31bGC2bdtDlsc3ADc4vG8dMN6+PSW4RPO0ikmTQimQjhwRp3V+vtystLSISN1+O1x8Mdx7L9x6a2LakG7275c0Mh7XQEEbLSiQhHFjxsTVzHgx6Rq7dQtNsSUFWx4+U9nF3s+ZooWJxghUjx6ghg5myPYNrDraLCgzP+RiQbXFxferX0HVQ315EsSV2EaBSoSLzwRJQGoFKtPmoLKTRAqUlcJCGebaxQkk0scUhrv0Upm7OlpKeHhMEgvuHZb1NTcaG0EPSV2ouRl0n322PE7axL4tk7npTEwEliFZFpRx8ZWVgRo8mKE5GxLu4rP+lrQJlMMi3URYUC+8ANsI5BRq4zyUCZBptYcB8TKmy8XXaoFSSnUMLKxt3zQ3y0nUL1o0fBIpLIS//13KeNxwQ0LT9KcNjyHmEN2CitZp7dghY4r/eCh1AmUG3acGYks3bkzSF9lcfMaCsgtUa+oCecFYUGVlwJAh9GmupmZbYhZCmf807RbUhg0weHCEW99NoLyG9be0yPhsK30BaNy0rU3NNKHkbXHxHT4sIpXRAqWUylFKXa2Uek0ptRNYCWxTSn2hlPofpdTw5DUzg9m5U0JOk2FBeaWwEP76VzEJvve99LUjUaxaBXl5nsL2zYVi9YJ4GSE+84z8dfc80R1dWpoygerYEcYHHNFJEyiPLr5kBUns3CkdYseOwODB5NGM2pKYgZMRIut0YaIESmv49rclmDYmLpljbIc+iNew/m3bRFRGnCoCtXVB2ywopwCZeF189mOekQIFvAcMA34E9NZaD9Ba9wROQTI6/EYp9dUktDGzcYnmSTnDhsEdd8Dzz8P81KYhTDgrV8rvcXJt2nDy+XsRqI8/No8UtWWpKbthYmkGD5bnia6TZGjeFe7ic7OgkhkkUVYWMC4CP7Z4x4aEfPbBg+LdtgauJkqgvvgCHn5YliMuWxZlR61dBcpU4OjVK3y7V7eaGSddeE0pdXRg7/K2WVDm/21LFJ9doP7t36SbSQXxCNSZWuv/0lov0VoHC5Vorfdorf+ptb4MeCbK+49OTFhWugUKJEiie3e48850t6RteEwSCyGBiteCqqqC44+Xxzs6pmYt1ObNcpr07i1Bm8mwoGpr4b7/FD+T7izDeLc5qGS5+HbuhJ49A08CAtVpz4aELE42cyFWz1qiBOpf/wo9/uCDKDvu2iVf6CBQW7fKJWhPwO/VgjJl5aZNV+zI6cuR9Ym3oOLNvmF3qx53nKzlSwWeBUpr3ZiIfY46MsWCAumlb70VZs+WHjgbaW6WSsMe5p9ABMqscDfk5koH4SZQWstXTJkiI/11OiBQSU7vYCyonBy5T4ZAvfIKtOzZyyGKWb1JesloFlSyoviCCVoGDKBF5dCvcX1CRMRpNUCiBGrBAhHWPn2sFrYDUTLHVFfLEiY78QhUTo6Ulavr3IecnW2zoJwWaRcUyM2rm85cR0leheFITIFSSp2llHpEKVUeeO6a465dUl0t/3ZrF+kmmhtukPmbbE2btGGDhB15tKCc0spA9Izm27dLhzZihIwGl9UNEce/8c8kgcZGmV8wy2YGDUqOi+/jj6Ere9lL16AVUFsrLjG7xzQlFlRBAYe79mUgmxISyecmUIcPt72s19q1MHIkVFTAwoVRdowiUFVVMNxhNt5rYcW1ayV/dEEB6D596Vy3tU2/zcmCUkqWOngt2+4075cqvFhQ1wM/BL6qlDodKE9uk7KM6mqJ4MvJkIj93r3hssskG0U2ZkiPI4IPxIKKV6BWr5b7ESNg1Cj4dGfyI/m2bhUDzRjagwYlx4JasQKGdt3HgdyufPKJbDtwwHkpTTIsKJOHz5risrGsH/3YklSBgraH7a9ZI1OfEyfKaWg+76OPbAurzXliyrUEqK8XgXE6dY0FE6uNa9eGMqZ1HNaHvmzl1lvlfP6v/4r/N7llEenaNRTQEYtMF6harfU+rfUPkPRBxye5TdlFstZAtYVvfEPiXd94I90tiZ+AQN0y65iwOQE39u937ny9CtSxx8KSuuQLlD3xwODBYlElegyxciX0KtxLc0kXFi+WbTU1zgZ+SYlYV23xbO7cCeefD3/8ozyvrZWOOmhBAbpfP/pTnZBsEvbaX5CYDNumYs6wYTBhghyTJUtkOvSUU+QW/K/WrZOBoC01x4cfSkDvKadEfn48Lj4jUAOn9KWEOv7+cC1HjsDdd8cvwsa9axeXo8mCes080FrfAfwlec3JQjJRoM48U87AZ7IwZmXVKg4W9+CBp7vz1a/KupBotNaCys8XK+bYY2Ejg9BKJVWgNm2Se6sFBQlLWA1IB711K3RXe8np3pVly6TDtFs0hu7dxXXUlo79f/9XpjxnzpQOz6kKev6g5FpQpqqIV4vACWu+5wkT5PGiRaFLaO9e+PzzwM6rVzsmhn7zTTmvTjst8vMLC8W1Fk2g9u+H3btDH50/UBbr/vctW3nhBRHIt9+O73cZcbHPP3brdpRYUFrrlwCUUj0Cz2clu1FZg9aZKVD5+eLme/nl5BX8SRarVrEKmX/asgUqK6PvvmuXs3VQWure8a5eLdMHeXkiUEcooq5Lv6SGmhuBMsJk7hM5D2UScJQ076OwT1eOHJE5ETeBMsfNZH5oDXPmhATi+edDv3PgwNA+RcP705kD7N3c9kiGaALl1SJwwkTPDR8u4tqtm8xD/fOfoenQoECtWCGTlzbeegtOOsk5GaxSsSs9RxRFCERb3HLZNs47Ty5r47b1ipsF1bWr9+PltBg+VcQzcfJY0lqRrezeLcOaTBMogCuukKv5zTfT3ZK4aFlVxeLDx3BDINviRx9F3z9sQt5CWVkoo4Gd1avFvQfSGRUXw44OyQ0137hROgUzkjUClch5KJPrr+jwXjoPlBDzxYvlGCVDoA4cgKVLpYTIwIHw2mvOApU3SLKsNG6IqJwTN04C1a2b3LfFglqzRu6HDRMxmTABnn5a3Hz/9m+y8HbtWuRg7doVIVA1NTKYOuss9++Ite7MiGRQoPqE0h0VFMDYsTGCNxxIpAVlTzacCuIRqLblfD8ayaQQczunnipXsqnvkA0cOEDOju1UMYJLLpHDGk2g6urk5iRQvXrhOOfR0iKdkRGonBwZIa8juQK1aVNIlEB+W05OYgVq5UooyG0mt3Y/XYd2JT9fOrQ9e5wFymxrrUB99pkcz5NPlnJmb70VSgJi+lYgmAZMb257NolkWlCdO4fEbsqUkOVwxRVica9fT2gUYBMoc56efrr7d8QSKKtIAqF49W0Saj5xooTCxzNnaCwou/XTrZu81uhhYdDBg9L2dMSBxfOVya4Bmn1kskAVFMhc1Ouvp6B8a4IIRC9UMZJJk8RdEm09irGQ3ARq377IIITNm8XraY1iP/ZYWFo3VHyK8dTBjoONG8MFKj9f+u1EuvhWroTyoeLXzO3RlVGjxAUHNsEI0FYL6qOPpNM64QQRqLo6qRgzalT4ujQjUA3rxYLav59Wz0cly4IywQlmAfC3vy2idOutcuyCdS2NQI0aFfb+5cvlftw49++I5eKrqpLvClo7nTqJeR9IGDthgojwljgMUVMmwy4uRtRN7sBYn2G3wFKFb0G1hUwWKJBeY9Mm1ryyghdflKryd94ZusYyjsDi4v09R9Krl+S/3bzZPaGz6eScBKp3b7m3W1FOleSPPRYW7QuEDCdhcZLW8rFWtxckPtR85UqYMDiU5qi8PJSyx2ltjrGgWrv86+OPxe3UqZNYDrm5MiKvqLDtGBColuotEgY/VI5FcE7HIw0N8vl2gSotle9uiwVltapBXL9r10oVG5D2bt6MxJt36BBRB+qLLyQyM9o8TSwLqqpK1mEFUUqsqIAFZXI4muhML9TWOouL+e+9DBRSUCrNlXgE6kdJa0W2Ul0tV4Y98VaKOXJEROfll+F3v4ObboIzzoAT7pKCfw9dNJtLLoEf/hB+8QtJ8WNCrTOKqipaUHQ7XnwcU6bI5k8/dd7dCJcRIyvmL7F3vk6VPCZPhrUkL9R8yxa5yO3z6okUqIYG+U/H9AtlKx1vqY7mtO65tFQi+VoTG9LcLP/LySfL844d4Zpr5LG5D9KhAw0lXenbUs2oUWKk5uTAL38Z33c6ZTIH6cfjWddjp7FRBhBOIm7o1Uss76bKpWI92UySqqrYa8tjCdSqVTaBgrDS76Zc2ZIl0b/HiptAmTG1lyhSt89IBfGkOoqWPrF9Ul0tNnmYPyM5NDTICPmVV2RUd/PNMiE7eLB4AUaNkqK6P/iBlIWqq4ORp/dnZ9lobhvzBp9/LiPMDRtk3uB3v0t6k+OmcXkVmxjI2MmyqnDCBPFUugmUEVmnjsWsoTQTz4bly2XC2zqmOOkk2KCSJ1BmkafNK8TgwXIKNSWgEkVVlXzOcX1CpTbMhP3QoRED/iDDhrXuJy9aJB2XESiQteGbNjnPw+QN7MfQAvFNPfGEuNDeeCM0R+KFaNFk8USl2dmwQQQ3mkCJla5RixZKUVEbW7bEdqR07OieksnEXkSIXJ8+QQuqc2c5Z+IRKDfrx5wPXgQqnRZUQirqKqW6aK09eDOPMhIcYt7QIBfL6tWh25o1cr9xY/iaoC5dxCVx8slw7bXyeMQIuciMTx6A754Of/oTfcobIT+frl3hS1+SiKtM4/CSKqoYyeTJ8rywUEQqmkD16BFZ2gDkOCgVWbl23jxxQVmTjXbuDP0n9eLwgmKK1q5LuC/buGScBKq5Wf5bh2U1cWHmQIZ3D7n4xoyRossme7oTQ4dKsEO8vPOO3FvFyOQYdCJnQD/OyN/CwsflP+3cGX7/e3HznXGGt+90q1YLcs7v3u29/VZMcEIsgRrKOnIP7IsQqKYmcSXHKgnXubN7ikzj7ozQvj59wgKdxo1LjIuvb1/5v7wKVFifkkJiCpRSahLwJeB+oAkYbbuNAToCDt1E/CilZgD3AbnAo1rrX9teV4HXzwMOAddqrRd6eW/Cqa4WJ3wcGHeCVXzMbePG8JxbnTuL6EyZAl/9akiERowQ14wnTjsNZs2SEhwnngjA1KliZW3e7N6hpBytKdi4miq+ylWWXCVTp8L998tkrl2IVq4MnzewUlQkHbN1vq22VkafP/xh5P7XXa9YO38onT9cT6IPydy54rqxR9KZbOoffdR2gVq2TAz5vsXhBYmiRZUBlJdLOPX27c6uUjfeeANGj47jPf36UbBkSXARrJmnmj8/foFyGpD06dN6t7URKLdzCUSgJrFAnthUZOdOGTw6JYm1Es0N+fHHIhgR83e9e8uJG0ihMW4cvPqquEmtJUfcOHjQeQbCRFqaZQGxPsM+f5oqvFhQ/wd8G9gE1ALLkWKFK4ArgXKtdUIKOgcq9D4AnAVUA/OUUi9rra2ZsM4FRgRuJwAPAid4fG9imTqVMEd/gKYmERsnS2j9+nARKi2VC+P44+Hqq0NW0IgRYh2otg7nTfnWf/0rKFCmY1y0KIMEqqaGovr97Ok+Mkx8v/xlCe544QW47rrQ9vp6sYaiFZebPFl+dkuLXPyvvy7/zYwZkft+85vw2U+G0jx/Hd+5GB580DnyzVBZKTUir7lGwn/dOHRI2nDllZGvjR0rI9M5c+DrX3f/DC8sWybnTH5deDXdWJx5ptw//LC4lyorxcK55BL3clxr18pviquqS//+ooJNTZCXR7duMoCItRDbiok4c7Kg+vXDU2osJ5YtE9FzCrYxGIFqzisg10wGBTBRdbEEqksX+Q1ah1/XWsv5fcopDq40cxJu3w7DhjFunJzPX3wR/bwz1Na6W4YDB3oXqEx28X2MJItdCHQAHtFa/wNAKfXDRIlTgMnAGq31usDnPw1cBFhF5iLgL1prDXyqlOqilOoDDPbw3oSy/sePUFUFax4IF6P168PnFUpKpPOYOFHWVFgtoWBht2RRViZD3X/9C34kcS5mpGhGjplA4/Iq8oEuk8NniSdPFtfY3XfDueeGRuxPPCEidd557p95/vmSqua112SU/pvfiCBb500MBQVw4tVDaX7kPd56U3PVVcq1w9u7Vz5vzx6Zd1mzxt0F8sQT0klEBA4gonnVVfDoo+4ZMbyybJlYQ+zdK8Njj8v+J0yQcYtdbPr3lwW406ZJlJ45R2tq4PbbZd7zW9+Ko4F9+oQyyQY63eHD45v/iubi699fOn+nXH2xWLRIrs1o12G3bnASH7Oj7wT6FhSEvWaCdbxYUM3NkWHbzz4rgvPIIw5vMgK1bRsMGxYcDy9Z4l2g3AIchgyJUVbE8hkZK1Ba6+8qpTporQ8ppboBP1VK/TvwCxK/NqofYPWKViNWUqx9+nl8b0I58cRQGHPHjnLBjR8vo36rJdSrV5JFKBbTpklP2SjzUN26yWgukwSq8h9VHA+MvSxcoJQSa+bss6UD6NlTLvJdu2TEGc2FdcUVImwXXigC1NAgnYFbTEveyKHkNRzk3l/u4ts/LaOyMtDp2/jb30LidN118Kc/ObsNd+2Cn/5UDr8xZO3cfDM88ADcd1/rslWDRJetXRsQwR175c/1eMLl5IgF9/bbElU4Zow8/t3v4D/+w/k9hYXy22N1yGGYkcX27cFOd+jQ+CqzGgvKycVn5n+2bHGIhItCU5Nkw5g5M/p+HdUhTuAzPu33few/OxDDENXihlC79+4Nicbbb0tu54oKuY/AetwQV3BxsTfLU2s5T90GT8OGiXu3oUGuDzfSuQ7KU5CE1vpQ4H4P8H2l1CDgl0AvpdR0rfV7SWxjwgnUtLoRYGAbnKuPPBKaJ+rdO80iFI3TTpNecMECmDIFpUQ87RFuhuZmWXD5zjviosrPDxU5KywMv+/RQ0Zy550X+/c3NoqFefiwDPJzc6WD2LULVv+9ivHkc+rXBkW879RTZWL4qadktJqXJ8f8W9+Kvrq9sFAqoz70kKTlueAC50SeQQKhf5dPWse3KWPOHGeBmjNHvv/aa0VYZs92Fqhf/1pG/X/4g/uxGTVKhPT3vw8VRI6XVaukMxo9Gli1z7N7z9CpE1x6aej5+efLbdUquZnIM63lfD/hBOfMFFGxdbQgArVrl3s5EDvRLCgjUNXV8QlUZaVY4g6BeWGoTz+hgEaWdT8N+1jDBGfE+u+sSW0HDpRz+ZJLpL2vv+7iUrVaUMg1M2mSN8vn0CFZguLWruHDxV24YYP7MXNbe5YqWhXFp7XeCHxNKfU74NdKqbu01tEufa9sgbA56v6BbV72yffwXgC01g8DDwNUVFS02gq84ILWvjPFmF75/feDi4v69nVfk/qTn4g77NhjQylRGhrkZLfe19eHErJ+//vRQ9fXrZP5Drc1N6/kV9E8aBgFBc7mzTHHwF13xf6pdnr2hJ//3OPOgQJ0XfeuY8SIE1wTc37+uYT0g7j67r9fjom1zHdjIzz2GFx+eUA4onDnnWLZPfBAHG21YAJBjj0W6f3iFCg3jjnGc93I2DgIlJn/3LrVm0Dt2yfH2Ck4wATTeplTsWJSVcYKJuG992gil0UdIv3De/fKGid7mXc79qzrv/61XEfPPx/Fvdu9u4zIjJkGTJ8unoFYwh5LOE1gjinU6EQ6M5lDHOugAtFzYWitK7XWM4C73PaJk3nACKXUEKVUARKE8bJtn5eBrythCrBfa73N43vbJz17Sk8zd25wU+/ezhkE9u4Vq+BrX5OO76OPJAx50SLxk69ZI9F/O3bIiPbQISnie++90Rd8fu978tmPPSYLip9/Hv7xD7mfMwfOHV5F8fg4hr7JwCyeWreOigpnN0pNjYz6zTx5RYWIkamzaPjoI/m9TsERdkaNknmxF16IfK2uTlxQ0VixQizJkSORL3XygaUbh5XTZpPXOlFupVVA/rqCAlthwRhoLVb55Mke1tq/+ipLO57ItrpIRdizx9uYwARhbN8ulsuzz8qSj6gRnDk50jjLcZs2Td7/4YfRv88IVDQXH0R39WeNQAHvKaW+o5QK84kFxCBHKfVnwMmL6hmtdRNwC/AGEiX4D631cqXUTUqpmwK7zQbWAWuAR4Cbo723Le05qpg6VXrNwGKq3r2ls7UvEn3nHbGMbrzR28cWF8s8i4lEcmLnTglUmDlT5mwuuEBcG5dfLvfnnNlM7ro18flmkkGHDnJg1q9nxAgRYnsuP/uiW7PKwC4iZl2L29yTnfPPF0G058W78kpZ+zJ7tvt7V66UDrqwEDEzEmRBJZTiYlEXS0drOmyvefmclhoY8vMlU0csMbfyxz9KcMlNN8XYccMGWLyYz/pc7Ji7zqvRal0c+/HHciguu8xDQy2LdUHmvgsKYkctxrKgevWSuXM3Vz9kl0DNAJqBp5RSW5VSXyil1gGrEWvl91rrJ9raIK31bK31SK31MK313YFtD2mtHwo81lrrmYHXx2qt50d7r0+AqVPlCg8kZ+vdW0TF3iH+619yMp4QR3jJoEHRc6t98ol8l1N4NxBSgnQLFASzgg4bFsqhZ8WkXzSJX0eOlHkBe37DBQskjNrrAsfACoCwY7h/v6x5ARnpu7Fpk6X6eAJdfAnHZrYn0oICEXKvWRZ+9jO45RYJvokZ4v/iiwAsHXqRq0B5+Z87dxaX3ObNUmeqoEAsqJj07h0mUMXFYrnHKkVjMmu4CZRSYkVFs6Dc6kmlinhSHdVrrf+otT4ZGAScAUzUWg/SWn9La70oaa30aTtTp8p9wM3nlqtu2TKxCtzWwLgxaZJ0yk58/rm40V0nos3y+gwTKIgMgzaCboIE8vNlZGwXsoXOGXFcqagQb441a4bJ8FBS4p5NAyRyrV8/RFEz1cUHEQLVvbt0komwoECO4datsUPXt2yB//5viXp89VUPmcr++lcoL6e+/3BHgfLq4gM5VzZuFNf22Wd7m3ujT5+ICyhhnaUAACAASURBVPXEE+V6s1v4VsxborkvowVLgXs9qVTRqgofWutGrfW2dpneKFsZPFh6sYBAOcxZo7UIVKxJfSfGjJGOwam+TFWV9PvFxS5vNikAMkWgNm+mX1kDEDZwBcQtmpsb3lEOGRI+/9bYKMfCoeiqKx07yjGcNy+07ZNPpAP/xjdEAJ1y9jU3Sxv79UMmBJuassaCys2V4ACvAhXLgjLWyP33R0/h8957ctx+8AMPA7HKShltfPObwYW2duIxWkeOlDnYTZs8uvdABGrnzrATYMoUEadoFuPmzRJQEi260ORitCYPsJJNLj6fbEYpsaLmzgWtHd0r+/aJ39qa6dsrgwbJ9JZTrZr16y0uKCeqquQKiCfXTrIYOhRaWujdIOFgdgtz1y654K3h7XaB2rxZjkXU3+zAhAkSjGL45BMZLEyYIH2TU4Tazp3SufTrRyg8LEsECkToTfh4LGJZUEOHyrzmfffJ+RjwzEXw8cdiuXjKUvb44+KLu/pqOneWoBX7ICwegTrppNBjzwJl/PGWEtFm8BMtvdPmzRLdGC10beBAiSR0y2NoonQz3oJSSv01cP+95DXHJ6lMnSo+kPXrHaupmr4jrgWYAcxyMqfyEZ4EauTIzFhIFgg1L6peQ2lp5PyIU8aHIUPk2B0+LM+Nu681ArVjh1hELS3i1jvxxND/4RR1abb17k1IoDLZxXfgQFjNic6dvQmUV+/lX/4Czz0n450//cl5n9WrZRAW07V35Iisyr7kEujWLeiOs2Ykb2gQ0fIqUNdfL1UIHnkkjk7fthYKgqdpVPecl1ybph+waF8Y6R7zxGNBTVJK9QWuV0p1VUp1s96S1UCfBGKZhyotlYGh9cQ0nXFryluZoAG7QB06JD56azXZCCIqtaURs/Bn1SrHsvE1NZGLVE22cPPbjTUVJlAPPyxX+dixrhUjTSLVRYskMm//fhGoaJ1I2ES48T9lsgUFYQe1c2dvVV0PHZLo0lgLhIuKxDL5ylfcF7Paqxu78tJLcoADSSCNm8sqUMbC8Dom6NZN1l7dcIO3/QFHgSouFqs5WoBDdXXiBCqaazWZxCNQDwHvAMcCC2y3+VHe55MpjB4tndfcuSglloCTBdUaT5tZyW8f5ZsT3DXK6ciR6EvZU01ZWbAuQu/e3iwouzivXy+j82AlljfflAJIo0eLT+6SSxwn60zWikWLCC4SPvHEUDh2NIHq1o30D3dj4TDx6dWCMuep10wbo0fLsbFHqba0yP8UrQRJkEcfFddAoLCWk0ClZI7GacIYaZpb+ffmZnktlkDFCvU3aZnyElKYKX7iieK7X2t9HPCY1nqo1nqI5TY0iW30SRQ5ObIiNBAo0aNHeKfXFoHq0EFGr/ZONFr+NEBmaFtaMkeglBIrKmBB2QW3psabQA0YELioW1pklfIxx0jitUcekfxBf/1rxFd36iST1kagunYNL9PhJFBhmpQNLj5olUCZORKvCXVNBm+7C6ymRtxyMTOcbdgAb70lPrnAhKOTQKUkDNscN1vETlmZu+WzfbuIVKxydV4sqHSOd+IOktBaRylw4JPxTJ0qLrUdOygrCx9h7tghUU2tOSGVcr5gotXwAUIh5tGK8aQai0BZLaiWFuko7W6mvn3FYjICtWGDxb338svir7vrLlHwCy4QN9/DDzt+9YQJEjT20UcSqZWTI+6cjh2dR7lhFlS2uPjaYEF5FShrlQor5hDFXLf0+ONyUltqvESzoJIaRFBYKA2OQ6DMer1YAmUs0qNGoHyyHDMP9eGHji6+tmRed7pgYlpQmSpQ1dX07VzH3r2h6N59+0Sk7J1kXp50BFYLKihQs2aJP+nLX5bnSsnK0M8+c5xAmDhR3r9yZahWE0S6Yw1798pcYnEx6Z8wiEVZmSiuRTW6dJFOPlbZe1eBqq+XCAobDtNdQMjiiSooWkv2/7PPDjO10ubiA8cISDPAdPj5ngUqL0+0L5qLzxcon9QxaZL0ZnPnRgjKjh2tC5Aw2C0yiF5kDhCBKivLrFF/IFBiWLOIp7FSzLFyGsUPGiQCVV8vA93Bg5FJgPfek7TnVie+iS+2lPI2XHhh6LE1GXHnzqEJeSumnIJSSG/SqZOH8LQ0kZsr/7XNggLn3/bGGyEXnWPanqefFoWrqIj4AGveOytmt6gLZOfNk5j+q68O25xWgbKlOwI5lI2NzhaomZuKJVDmc9wsqHgWIScDX6DaGwUFksdo7lx69CDMQoi37Lcd+5wWeLSgMmX+yRBoz8DDq4CQ6NqzSFgxAmVCzIcNQzpQrSM6OoYMkR3eeivic0aPloS6f/5zuFFZWhoa/VsJW7yaqXn4rNgsAVNc0BJ5DkgHO2OGxJOAHHulLD9v3z4JPOnXTxbT/uIXYe/PzxcxswuUJwvquefkA2zlCqLNQSV9nZCLBQXO4lJdLZ5BL0El3bq5R1Ju2xa7zlUy8QWqPTJ1KlRW0qejDCfN6LStFlS3biEvkyFaDR9AFqVkknsPpD1K0Wu/WFB2gXKzoLZskfgHCLj4nnkGjj/e+fedfbZYVw6+reuui8wP16mTs0AdPiwBKkD6/TFesHW0pu11deG7mRDxpUvltZ07pbMNGof/+IeYQ08/LRl1H344tBAtQM+eka6rmAtPtRaBOvPMiGOZERaUxZ9nBn1OFlR1tWi3F3e92zxgfb2cUq1ZF5kofIFqj0ydCi0tHLNHYpl37ZK5lR072mZBGTdUIGE6ICOzoiLnGj7U1spFl2kWVHExDBxI15pwCyqWi6+lJVTRZHjpDnEVXXyx83dMnSq923JvCfdLS53dYIcPW1JIZXIePoNHC8qaNWPZMhH/sI7y6aclnUJFhbhQa2ulbouFrl0jLQMj8q4uvqVLZRLQWsHR1larmKZUoOrrw5TE/Aan8yKYn9GJBQvEOrzjDmhsdE3h5LVScDLxBao9cuKJkJvLoE3Sm+7aJVZUc3PbBaqlJXyEuW9fFOvJBAlkmgUFcMwxlFSLQBkLM5YFBWIUdegAPeYHOsvzznP+/MmT5d4tBbwNNxff4cMW8c8mF1/AEnCzoKzBDUuW2Drc+noxsUwZ5+nTxXx/6aWwz3DqeGO65EwFw3PPjXgpP1/cZnYXn1IWKzZZOERAmt/gdF7s3OniDdm/X37bu+9KVdLbb3e1oIxA+RaUT2opKYGJE+mxUgSqpqZtWSQMRoisJ3vU/GmZlMXczjHHkL9+FaDDXHwdOjh3RkagFi6UNTjq9dky9Bw/3vnzhw6VTtWjQLm5+OrrbRZUNghUQ0PQF+xmQe3cKRP8paWweLFk6AoK1KefygLvadPkeV6ePLYVSHLqeA8cEDeha+Lit94Sy8zF/CgpiXTxlZSkIEuXQzaJaAJlgmcimDVLLvgPPpBCWPfdx7CW1Y4WlJlPjbXYN5n4AtVemTqVjss+o4Aj7NrVtkW6BieB2r8/ikCZTJdmVWUmMXo06uBBji3eFObic1uHY83WPml8k4SgmRG+E0qJFWVqasSgtFQ6Q6v7FLLUxQfBE87Ngtq5U3YdN048Ujt2WEby778vx++UU0JvmD5dolQsWXvdLKjSUpe/pb5eOu5A5ggn3AQq6TgIlJuLz+QtjBiraC3RN2ecIdG8d90FeXmcseReGhrk51tZsULEPJ2Xpy9Q7ZWpU1FHjlDBfHbtSpMFtXq1DJOT7h9pBYFU1yeVLAmzoNwEKi9PpkMAvjLoEzkIbu49Q0WFzEHZewYHzGjZ2jmCRaAaGsQMyQYLCoIC5WZB7dghQQ7jxonBpHUoQSoLF0q2V+uJZayp998PbjIWlHWd0IEDUeafPvpI/ouzz3Ztvl2gjOAlnThcfCbjeoQFtXixuNWvvFKe9+oF11zD2Mq/0IG6CDGfP19WXBQWJu5nxIsvUO2VwOjzrMK51NQkz4KKOgdVVZWZ808gxZmAiflLwyyoaMlK//QnuPtuOLP+NVEs60pbt+9oaZFVuTFw64yCc1CZnkXC4NGC2rNHovasHtJgGZjKykjX6ahRoh7zQ2lBu3SRjtoa3BdVUD74QBYSn3qqa/PTZkF17ix/tC1hbE5OpAXlmpLxnXfk3jpw+vrXyT9Sx5d4Ney6bWiQwzF9euJ+QmvIGIEKZEV/Sym1OnAfcaUppQYopd4LlJtfbi39oZS6Sym1RSlVGbjFGL62c3r0gOOO47TcuUELqrDQY4VPF8yA1joSi2lBZapAdeoEQ4YwusWbBQXyU378Y8h9Y7YMAGIdzIAIeonkc7M0gnNQmZ6Hz2DLQeT2uw4dktfGjQttGzMG+Z2bNkUKVE6OpOGwCRSED5iiWlCffy4L0aKYRE4ClRILSqmICEilnOcmw9JfWXn/fTlJrVEPU6dS370vV/P3sOt27lz5D6IYkykhYwQKuAN4R2s9AsmafofDPk3AbVrrUcAUYKZSapTl9Xu11uWB2+zkNznLmTqViiMfsXtnc3CRblsme+Oag9qzR8LjMjFAwjBuHCMOeRcoQBagLF3qGAUWwYgRYml5ECgzz2Rb6hNy8WWLBdWpk1gCMSyoQ4fkdx1/vBzK224LiJkpIWtSv1upqBA3ViBTvDkfrR2vqwWltQjUCSdEbX5JSbggpMyCAsdsEk7LDxwtqJYWMYmMK9SQm8ues67kXF6nbkvoQL36qgxYzzgjcc1vDZkkUBcBfw48/jMQsYAkUGZ+YeBxLbACcIv294nFqadS2ryf7psXtTmLBEQKVH293BwFygRIZKoFBTBuHL1rq6itqefIEemYYtUj4o035N6LQBUUiEDHIVBWS6O5WVwxRUVkfqkNg7EEAh1tQYFMxFt/l9ahBch5eTB7NtxzT+DFxYvl3ik6sqJCTrgvvgCc3aIHDrgI1Nq1Mmgy4f8ulJSEi2ltbXoFqmPHSHF3DKVfsyZUYMxG/QWXU0AjHd99Jbht7lwpfGAs3HSRSQLVS2ttjv52IOp0vVJqMDABsIZBfUcptUQp9ZiTi9DHxjnn0KJyOH7bywkRqOJi6VCMQEXNIpENAjV2LLm6mX61K9i6VTbFtKDmzBEXinHfxWLMGFmJGgMnC+rIEctrxq+T6QIFYa4qs4bI2sk2Nor4OsbOrFwpIx6nk9VEqQTcfE5RbrW1Li4+E03pwYJKi4sPHNMdFRc7W9XmtSCVlXLvYHkWTp3MZvrT68N/AmJsffFFuHs1XaRUoJRSbyulljncLrLup7XWgEOO3uDnlAD/BG7VWpvT70FgKFAObAN+F+X9Nyql5iul5te4ZUlsD/TowYZ+p3B67Uts3uwtsWQ0lApPaho1D9/q1TJvEAzNykACV+h4FgdTGEUVqKYmWUczY4Z3X+no0RIabR8G2zCdtbUzCuuIYlaGzCAcsklYLSjz2HGtksnd6HR8hw0TtVi4EAgJkdWCcnXxff65NGT06KhNT1uQBIgFtWdPaGSCs0CZoNAIgcrLk2ASG5275vA8l9J/+RyorWX9evlMr2OsZJJSgdJan6m1HuNwewnYoZTqAxC4d0wAr5TKR8TpSa3185bP3qG1btZatwCPAK62utb6Ya11hda6oiymz+boZsP4ixinl9Bl3/o2CxRIp2C3oBwFqqpKVremM4Y1FsOH01hcyvHMC1Zpj3q6fPaZ/OgZM7x/x7HHik/LXlnPhpMF5ShQWWZBgYivVaDM73K0oKIF1uTkiIWwaBEQEiIzYNI6hgU1aVLMTPBGTFta5PNSLlAQduw8W1CLF4s4OVxvHTvCCzlfJq/pCLz2WnjC4zSTSS6+l4FvBB5/A3jJvoNSSgF/AlZorf/X9po1Y9QlQGy/iQ+7TxHj9TL+mRCBisuCymT3HkBuLrXHTWYKnwYjwaNaUHPmSCcZK7zcijkGDrWhrDgJlBkpFxUhI+uOHSUfT6bTp49EnASCGezzKEasIgSqvh42b45+3kyYIIEUzc0RLj4jLBEWVEODiFoM9x6IGJk5svp6+byUCZTDWqhoFlRY/kun0PwASsEXXU5if4fe8M9/Bj8+nTn4DJkkUL8GzlJKrQbODDxHKdVXKWUi8k4Gvgac7hBO/lul1FKl1BJgOvDvKW5/VlI0ehifcgLX8gT9+7l6VT3TqVOkQEXMQWktApXJEXwBmiZNYTyLWbNEek1TZ8iROXOkDG48VowZppo5ORecgiQiLKhscO9BRDVBNwsqwsW3dq2cO9EEqrxc1G7NmoggCddaUIsXi0jFCJCA8IzmKUsUa3DIJuHJgqqpkVxRTpGPATp1zeXzfpfC7Nns2iijhbbOSSeCjBEorfVurfUZWusRAVfgnsD2rVrr8wKPP9RaK631OHs4udb6a1rrsYHXLrQEXPhEoW9feIzrGcNyypvmx35DDKwuPlcLaudO6S0y3YIC8k4+gTyayV28kIKCKPV1du6UnDznnBPfF3TqJKoXw4LyNAeVDe49iLAE7J2sqwXlJbBmwgS5X7SIwkKJEjTC5Joo1uRD9GhBQZoFyqOLL+jNM/5ph/knQ+fO8F63y+DQIbp8Oofi4ratiUwUGSNQPulh/Hh4uegrHFbFdHnu0TZ/ntXF5zoHZTqaLLCgSs6QTmv84U/o0ydK7MPLL8vo/qKLXHaIwvDhrXLxhQlUukufxoNHgYqwoLwI1KhR4uYMRK1ZLXpXC+qzz6RNHnzcaRWosjI5AWNYUPX1Ik45pnc3SZkDlaKd6NIFPso9FXr0YMSSf7Z5TWSi8AWqnZOXBx8u7UzT5VfDX/4SWYI0TuwWVG5uK0fCGUJB/55U5RzDdN6L7pN//nmJSGxNbO6IETFdfGY+wXUOKhtdfC4C5RoksXq1dNLRsmUUFEgkXiBQwpppIaoFdcIJnnrktApUXp5Y2x5cfGHiXlUlijVwoOtHd+kCu/fnwSWXUF79CgN7xs4PmQp8gfJh+HAovfsO8cP/zjU63xNmxKp1KM1RxHVfVSUXm6lRkeF8WnIW0/gXA3oecd5h/354+22pT96aYefw4VLwyJ7vx4JSIkSuczXZZEGZjMQWgXIKM3cUKC+DmgkTRKC0Dsu04ChQe/dKGWQP80/gLFApXcxqi4B0E6iwAImqKjnHokQoBjO/X3YZHZoPco56M7HtbiW+QPkIw4fD1VdLvZgY7qZodO4swVlHjkTJw7d6tQQH5OW1vr0pZHm/s+nAYc4u+dh5h5dflh99ySWt+wJTz2Dduqi7dehwlMxBFRaKtdcaF59XgaqpgW3bYrv45s2Tew/zT5BmCwoiskkUF8ui5kBAJGCrEQahtWNRCNbOOv109qquTN/7z8S2u5X4AuUT4je/ERfJzTdHFh7yiLn49++PkocvG0LMLRScPY0G8pl+8BXnHR5/HIYMcUwj4wkjUB4i+ZxcfMWqXl7IFhcfhKU78uTiq68XK9PLwm4TrbZoUWwX3+efi3lqslDEIBMFCiKPX1CgmptlwBlDoLp0kd9T15DPi/oiyje+JB6VNOMLlE+Ivn3ht7+VbAj//d+t+ggTUn7ggEupjZaWrAkxN9z+y1L2nHAeQ+c9LRe8lXXrpM779ddbZqXjxHS6lmJ7Trh25EeyaJGuweKq8hTFt3Gj3HsRKLPeZ9GiMBefowX12WeyWNq1Jkw4VoEya7dSKlC9e0t4fmAA6bY+Luji27hRzCsPAgVibD3Hlymq3y/LJtKML1A+4Xz72+Lq+9nP4BUXiyEK1sWRji6+jRvlajruuLa3NUWUlEDv265BbdsmYmTlvvvEVXntta3/gq5dZVhvOmEX7HM1QRdffRalOTJYBKpDBxmsG+13XAdlxHvIkNif3amTWKWVlWEuvtpaGUMEP9dkMPc4/wSh+aa0WlBNTVIJAA8WlIng8yhQK1fC/7d37lFW1dcd/+yZYbjDMDyGEWZAYECBBlAB0aZGXVqfmERMVkxwGaFpu4xNTGPTNqWaVW36immTrjQ1sdq4gm1WpFlRsRWLyDI1JhhLEAGlPETkNbzlOTM8d//4nXPn3Dv3NXMf55zr/qw16957zrn37vnNmfM9e//2b+8XuZGuEWPgkUdKaHj/MIEyUhGBxx93vXXuuKOnyGSBBEN8GQXKX5MRI4EC4GMfc2UkkmW1ca01Hn8c7rqruEKGItDeTrLGTBayzUElumLsQakmL6Z+yLKz0wlJfX3g+L4IFCRLHgVDfH4vqGQey3vvufVrBc4/gbvwizjvyReoijaETlusm02gkh5UPwTqDAM4dPs98OKLBTXTLCcmUEZvBg1yE//Dh7sLs1/KuwCCIb6Mc1BxFaiGBvjqV107jeefd7f7n/+82/e1rxX/+QUIVKY5qJoaqD0So0rmPq2tTomOH+91kfV7QaUkRL77rkuuKLS8wcyZsHUrLQOO0NnpnI5ehWL9CuZ98KBEegrGHj/u/lX6G9ntFxlS9KH3eZHiQQ0dmrdPjP9/6nd+qf2Du90dwne/WyLD+4cJlJGZ0aNd17IjR+DjH89bbdvH96AOHXL/wL1C+xs2uLUccQpH+dx7r5vfuP1210lv6VI3Z1eKiuzjx+cVqESix8uAnlCOHI5hiC9QFSH9Iuv3gkrh3XediBeqBl5FiYnHXP+o48czFIpdudINYB/XrgUFqqLhPSjYg0oRqEmT8i5/8Et4vfGGG+KWqSPhs5+FJ57o1YOqkphAGdm55BJ46ikX5vvsZ13MPg++IG3f7h4zelC/8RultbNSNDS4ieO5c90//L/8ixOtUtDe3jNxl4VsAhWrXlA+vifQ0dGrzmBnZxaBKjS8B8lMvrEH3ILdo0czNCtcudLdaPSxwG6oAlWgB5UM8W3ZUlDGrN8FfutWt0ytrg64/36XYPHNb5bG9n5gAmXk5qMfdSfos8/C4sV5D/cvAL4zkHLNVHUCFbfwXpDWVvjxj13dvbvvLt3ntre7xxxeVENDqkAlQzl+q40CM9EiQeBCmy3El0JfBaqtDUaNorWjR6BSQnzd3c5d6MfSgFAFqrHR/RKFeFCnTrl5tgL6ZjQ19dwU+GLFBRe4G9NHHy26wkx/MYEy8nPffa5Xzh//cd5Q38CB7sdfc5rSnmLfPncxjbNAlYsCBCqTB5UsczRsWN5eRpEih0D1CvEdPeq8xL4IFMDMmTTvcEk+x471JEkArqnh6dOu+nwf8QXqxImQWqIH1kL5nlKgh2HPefHeey4d3V9nlwORHmEaMyaw44EHnNCF5EWZQBn5qa116dS7d8Njj+U9fOjQHoFKqf4d1wSJSlCgQGW8U45TmSOf5mYXR8riQaUIVF8z+HxmzGDwe29Rz8neHtTKle4xbh4UpKTo+wKV0bP2m2AWIFDQM72V8u85aRLMn+9Szv24fQUxgTIK4yMfgWuvdWnWJ7PUpPMYNswt+gcTqIJpbna34330oGJX5sinpsZNdnR09Gol0qvYaX8FauZMas6eYRpvJeegkh7Uyy+7i69fF7AP+AJ15EhILSlyeFBnzzqHp6GBnpJlBbbG9YtpzJqVtuMv/9K5WA8+WJzd/cAEyiic++93XlSeuahg1e+UEN+GDe4iXIrWvdWGvxYqx2LdnHNQccrg8zn/fNi5M78H5bvj/RAogJm8kepBnT4NP/sZ3HBDv8z2BerQoZCGPYNA+eeFL1SJBM6DamwsWITvv98t6/vkJ9N2jBvnkoEWLYJ164q3vw+YQBmFc911bsFfnjCfH8uuq0u7w1y/3vXriUKjmSiSZy1UIuHW85w5414n5xriGOIDJ1A7dhQW4hsypO+/4wUXcG5EC9fws2R1oCFDcOufTpxw53M/aGx0Yhea49ramowx+k0JfYFKqcKxZYvzngr8f2tpgd///Sw1nP/8z93g3X9/0eb3BRMoo3BEXObaL37Rs6IvA75AtbQE/jdUXWttv06a0ZsCBApSL0YNDbiyN1lb/UaYsWOdQCXc8oWcIb4JE/p+Y1NTAzfexE0sY/dOV7uuqQl44QW375pr+mX28OFuNcCpUyEJVGANWaZzArxzZcuWguef8jJiBCxc6NZG/vznpfnMAjCBMvrGggVu3cgTT2Q9JChQSXbtcnf6JlDZaW93Vz6/42Ma6Rej7m4YNPCsG9c8lQIiydix0NnJoFNu7VfWdVB9TTEPUHPLzYxkPw1vrQJgSJO6EPV11/U7PucvaoUQQ3wAe/YwYIDT7eA5Ad55sXVrwfNPBfGHf+j+uf/szwpaE1kKIiNQItIsIstFZLP3mPHeRES2icg6EVkjIqv6+n6jSFpaYM4c90+epSWHvy4wZX3gm25Ff7IVgtEbv4Fjlnmo9Jp1XV3QXHPY/R1S7gZiwtixADQc2AFkWQel6rzKfgoUH/0oXSS4/O0fAjBuz+tubuYzn+m32UGBCi3EB9DRkWxk6c89+WM4vHOXc/FK5UGBu2t46CGXAfnMM6X73BxERqCAhcAKVZ0ErPBeZ+NaVZ2hqsEmLn15v1EM8+Y5j+jVVzPuvukmV57u4YcDG/2is/1pif5BIU+qeXrb964uaOGAexFjgRq4r0egzp3zPEPfg9q3zylWfwVq+HD+u+nT3Hzw32lhP1OX/J1LM7399n6bHbpA+SEKL1U2mN3pPza/37cU84L53OfgooucN+VX4S0jURKoucAi7/ki4LYKv98olFtvdVeQp57KuLu+Hv7qrzJ4UBMmhJSXGxPyeFCZ5htGaPwFSnbuSK7xSoaofIHqb4p5gB+P/SoDtZs1zGDEq0vgT/+0qPMwGE0ttHZtSWludqmE3o3MwIG956CGHehbinnB1NXBD34AX/96RRaBRUmgRqmqX5VwD5AtN1KBl0Tk1yISrDVT6PsRkbtFZJWIrNq/f3/Rhn/gaGx0BWR/8pPUXtO5sASJ/Jx3nott5fGgurtd5Ku7G4afjbFAtba6ReBeJl9XV4ZeUCUQqP0jpzGfJznMMI4v+KKrSl+k2T6lqBPcZ0TceHjp90EPyh+/pv3vuDvFcizpuOwy16CzAtm4FRUoEXlJRNZnmy2XEAAAEvhJREFU+JkbPE5VFSdEmbhSVWcAc4AvisjV6QfkeT+q+piqzlbV2efFcXI5CtxxBxw4ACtW5D/28GFXVbnXCkAjBRHnRRUwB3XqlBOpoae8G6w4ClRtrQtX7diR7HXVq5uuL1B++LMfDBkCi5nHdN5CHvnnLHnUhRNMmKxoL6ggEycmxyZTiK+xY4sTsTiVv8pAcX+pPqKq12fbJyJ7RaRNVTtEpA3Yl+UzdnmP+0TkGeBy4BWgoPcbJeLmm11No8WL3fNcvP66e+xHWZkPHDnabgTnoPw75aGnY+xBgQvzeYt1MwrU5s1OxIooeudH8+rqSicoa9dWLJEtMxMmwPLloEoiIb2SJBp2ljDFPESiFOJ7DljgPV8ALEk/QEQaRaTJfw7cCKwv9P1GCRk4EG67zWXz5Cl9xMqVzjvoQ2O4Dyw5qkkEQ3z+nfLgkwfcVTe0W/ki8ddCZQvxbdqUtxtsPvz6e8OHly4qddFFIef7TJjg1Hz//l4hvhrOUr9tY3zb2gSIkkB9A7hBRDYD13uvEZHRIrLUO2YU8KqIvAm8Djyvqv+d6/1GGZk3z63ZWbYs93GvvQbTplmCRCGMH+9CpxmqxgcFyr+QD+46EF/vCZKC3Jg4S2dnBg/Kb7hXBP5pF8dqUFnxJ7+2bk1Jkujuhna2UXOyuypqXlY0xJcLVT0I9Ko9oqq7gVu851uBjDPt2d5vlJHrrnMB+aeecpl9mTh3zpWW+dSnKmtbXAlm8k2dmrIrOAflC9SgzpgL1IUXwunTjK/Zwe6u9lQP6v33nVgX6UH5AhWsERl7/KSRd98lkfhwsiVYVxd8CK8oc9r5E0ei5EEZcWPAACc8S5Zk7xO1Zo270Fx5ZWVtiyt+MkCGMF+mOajEiSoQKGDC2S2956A2b3YvivSgfM3P08osXvjnydatvZIkkgJVBR6UCZRRHPPmuavK889n3u+H/268sXI2xRn/apohUSLTHFTieHUI1PgzOQSqSA9qzhw3HfO3f1vUx0SLxkbXWXDjxl6VJKbyNtra6hYkxxwTKKM4rrqqpw16JpYtc+ufQlnRGEPa2pxnmsODCob46o/sj2cdPp/RoyGRYGz3lt5JEps2uaKuRS42am52nV6uz5pDHFOmT4f163slSUyTDUgVeE9gAmUUS20t3Hkn/Od/ws6dqfsOHnSVz/OloRs91NS4/jt5PKiuLhjAKepOHI23B1VTAxdcwOiuDB7Uhg1ursXvKWGkMn06vP02iQFne/pBdZ3jQ/p2Vcw/gQmUUQq+8AWXDPHoo6nbFy92zYvmzQvHrriSJdW8psYVB/BLAo3goNsRZ4ECmDSJtqObegvU2rVWuzEX06fDyZOcf/KdpEA17d1ME8fg0kvDta1EmEAZxTNxoit99OijPa0iVF3NrunTrcRRX8mzWNf3oEax122Mc4gPYOpUzjuymbOdJ3tCfNrp5qBMoLIzbRoA446tTwrUmN1eg4fZs7O8KV6YQBml4cEHXV+iBx90r599Flavhvvusw66fWX8eNizJ7W/u0dQoFrZ4zbGPX/6kkuoPXeGC069zfHjzkus3fi288ovuihs66KL15163KE3OXnS3ROO27eKLmmoigw+iNA6KCPmzJrlQn3f+Y7L5336aXf3O39+2JbFDz+FePv2XhlsDQ3VKVAAl/Amhw7NdAkSfv8w86Cy09gIF1/M+F2/AFx9xkkHfsnGxlnMKLLeYFQwD8ooHd/+thOkf/1Xl53105+6jDSjb+RouxFsS9GGV7x/VNbC/fHgwgs5XT+IGazh4EEvg2/lSpd+V+p2EdXGVVcxZsdr1HGa7j3vM+nIKt5orp56BSZQRumor4dFi9wVdO3aqihWGQo5Ghemh/h0yJD41uHzqa3l4LhZ/BYrOXDAq533y1/CFVe4zBAjO9deS/2pE1zNK+iy5dRyjnWjbgjbqpJhf32j9CQSNu9UDGPGuPT9LB6UL1Dn13QgcQ/veeyfdg2X8ms69xylfeBul2L+kY+EbVb0mTOHU4km5vMkA3/0BPvqRvNua/V0DTCBMoyoUVfnGs3lEKjubmir2VM1C6Dfn/nb1HGW6R3LuanLa0Tw8Y+Ha1QcaGjg3at/hwU8ScMry3hy2JcYOCjePaCCVMdMmmFUG1lSzRsa3Prnri5o0w5orY71Lp2XXsVOxnDn8UcZX3sYpkypmsWm5Wbj/L9h5YtH+dhnBvP9X3yFqxvyvycumAdlGFEkS2fdYIjvvHN74p/B55EYXMd3+DI38BKTj6yChQstTFwgtcOa+Bw/ZOtX/pljJ+uTFUeqAfOgDCOKtLfDrl1w+nRKJqQvUOeOnWCwHq+aEF9DA3ybr6AIl3x4EHctWJD/TQbQuwRWg3lQhmGUlfZ2t1B1+/aUzb5ADT7s1T0cPbrytpWBhgY4Ry3f4k/438u+YN5TH0ivcl9NHpQJlGFEEb8Hkt9ywsNvjd50eIfbMG5chQ0rD8G7/sGDw7MjjviCdOKEK31pHpRhGOXFryCxaVPKZt+DGnbU86xMoD7w+ALld9U1gSoDItIsIstFZLP3ODzDMVNEZE3g56iI3Ofte0hEdgX23VL538IwSsTIkTB0KGzcmLLZF6jm49s5h7g1U1VA8KLa2BieHXHE70Zy+LB7tBBfeVgIrFDVScAK73UKqrpRVWeo6gzgUqATeCZwyD/6+1V1aUWsNoxyIOK8qAwCdeYMtHRu50hDm6veUQU0NfU8HzEiPDviiHlQlWEusMh7vgi4Lc/x1wHvqGrvXFzDqAamTOkV4vMvPud1b+f9IdUR3oNUna2SxMSK4QuUeVDlZZSqetUv2QPkq4A5D0jvM/4lEVkrIk9kChH6iMjdIrJKRFbt37+/CJMNo4xMngw7drjZbw//4nP+ue0cGzo2JMPKiwlU30gXKPOg+omIvCQi6zP8zA0ep6oKaI7PqQduBX4S2Px9YCIwA+gAvpXt/ar6mKrOVtXZ58W92ZtRvUyZ4h63bEluSiSgljO0s42j51VXpe+RI91jleR9VAx/DurQIfcY99rBQSq6UFdVr8+2T0T2ikibqnaISBuwL8dHzQFWq+rewGcnn4vI48B/lcJmwwgNP5Nv48Zkz6REAtrZRj2nOT56co43x4+f/9zViB0yJGxL4kVdnSv6fvCge11NSSZRCvE9B/jLxxcAS3Icewdp4T1P1Hw+AawvqXWGUWmmTHFVzdetS25qaIDJuHmprnFTwrKsLEyeDHPn5j/OSEXE3bj4AlVNHlSUBOobwA0ishm43nuNiIwWkWRGnog0AjcAT6e9/5sisk5E1gLXAn9UGbMNo0w0eK27V69Obmpqgim4zL5T7dXlQRn9J5HoCfFVkwcVmVp8qnoQl5mXvn03cEvg9QmgVyKqqt5VVgMNIwxmzYLly5Mvhw93HtRBmqlrbQnRMCNKJBKwe7d7Xk0CFSUPyjCMdGbNgo4O9wMMGwYXsY4NfMjmaowkfqIEWIjPMIxKMWuWe/TCfMMGn2Emb7CK2YzKtxDD+MAQXPtkHpRhGJXh0kvdKtaXXwZg+J4NNNLJKmYn07INwxeomppUbyrumEAZRpQZNAiuugqWLQNgwK9eBeB1LqfFpqAMDz+sN2hQdXUqMYEyjKhz002wfr3rsLt0Kbvr2+kcPSnYx9D4gDN0qHuspvAemEAZRvT59KfdeqgvfxleeIGRX/gUGzdV0W2yUTQmUIZhhMP48TB/PixZAvX11N13b9VdiIzi8AUqWBW+GojMOijDMHLwve/B5ZfDZZc5wTKMAL5AVVtpURMow4gDiQTcc0/YVhgRZdgw91htnrWF+AzDMGLOhRe6R79pYbVgAmUYhhFzLr7YPc6ZE64dpcZCfIZhGDFn8mTYuhXa28O2pLSYQBmGYVQBEyaEbUHpsRCfYRiGEUlMoAzDMIxIYgJlGIZhRBITKMMwDCOSmEAZhmEYkSQyAiUit4vIWyJyTkRm5zjuZhHZKCJbRGRhYHuziCwXkc3e4/DKWG4YhmGUg8gIFLAe+CTwSrYDRKQWeASYA0wF7hCRqd7uhcAKVZ0ErPBeG4ZhGDElMgKlqhtUdWOewy4HtqjqVlU9BTwFzPX2zQUWec8XAbeVx1LDMAyjEsRtoe4YYEfg9U7gN73no1S1w3u+BxiV7UNE5G7gbu/lcRHJJ4y5aAEOFPH+chNl+6JsG5h9xWL29Z8o2wbF21dQSf6KCpSIvAS0Ztj1gKouKdX3qKqKiObY/xjwWCm+S0RWqWrWObOwibJ9UbYNzL5iMfv6T5Rtg8rZV1GBUtXri/yIXcDYwOvzvW0Ae0WkTVU7RKQN2FfkdxmGYRghEpk5qAL5X2CSiEwQkXpgHvCct+85YIH3fAFQMo/MMAzDqDyRESgR+YSI7AR+C3heRJZ520eLyFIAVT0D3AssAzYA/6Gqb3kf8Q3gBhHZDFzvva4EJQkVlpEo2xdl28DsKxazr/9E2TaokH2imnWqxjAMwzBCIzIelGEYhmEEMYEyDMMwIokJVAFkK68U2C8i8k/e/rUiMquCto0VkZdF5G2vVNSXMxxzjYgcEZE13s9fVMo+7/u3icg677tXZdgf5vhNCYzLGhE5KiL3pR1T0fETkSdEZJ+IrA9sK6iUV75ztYz2/b2I/J/393tGRIZleW/Oc6GM9j0kIrsCf8Nbsry3rOOXxbbFAbu2iciaLO+txNhlvJ6Edv6pqv3k+AFqgXeAiUA98CYwNe2YW4AXAAE+DPyqgva1AbO8503Apgz2XQP8V4hjuA1oybE/tPHL8LfeA4wPc/yAq4FZwPrAtm8CC73nC4GHs9if81wto303AnXe84cz2VfIuVBG+x4C/qSAv39Zxy+TbWn7vwX8RYhjl/F6Etb5Zx5UfnKVV/KZCzypjteAYd5arLKjqh2qutp7fgyX3TimEt9dQkIbvzSuA95R1fdC+O4kqvoKcChtcyGlvAo5V8tin6q+qC7LFuA13BrFUMgyfoVQ9vHLZZuICPBp4Mel/M6+kON6Esr5ZwKVn0zlldIFoJBjyo6ItAMzgV9l2H2FF355QUSmVdQwUOAlEfm1uDJT6URi/HDr6rJdHMIcPyislFdUxvF3cR5xJvKdC+XkS97f8IksIaqwx+8qYK+qbs6yv6Jjl3Y9CeX8M4GqEkRkMPBT4D5VPZq2ezUwTlUvBr4LPFth865U1Rm4KvRfFJGrK/z9eRG38PtW4CcZdoc9fimoi6dEcn2IiDwAnAF+lOWQsM6F7+NCTzOADlwoLWrcQW7vqWJjl+t6UsnzzwQqP7nKK/XlmLIhIgNwJ9OPVPXp9P2qelRVj3vPlwIDRKSlUvap6i7vcR/wDC4UECTU8fOYA6xW1b3pO8IeP4+9fthTspfyCvs8/B3gY8Cd3kWsFwWcC2VBVfeq6llVPQc8nuV7Qxs/EanDtRtanO2YSo1dlutJKOefCVR+cpVX8nkOmO9lo30YOBJwh8uKF7f+AbBBVb+d5ZhW7zhE5HLc3/1ghexrFJEm/zluMn192mGhjV+ArHevYY5fgEJKeRVyrpYFEbkZ+Cpwq6p2ZjmmkHOhXPYF5zQ/keV7Qxs/XPWb/1PVnZl2VmrsclxPwjn/ypkRUi0/uCyzTbgMlQe8bfcA93jPBddI8R1gHTC7grZdiXO31wJrvJ9b0uy7F3gLl1XzGnBFBe2b6H3vm54NkRo/7/sbcYIzNLAttPHDCWUHcBoXx/89YASuEedm4CWg2Tt2NLA017laIfu24OYf/HPw0XT7sp0LFbLv37xzay3uotkWxvhlss3b/kP/fAscG8bYZbuehHL+WakjwzAMI5JYiM8wDMOIJCZQhmEYRiQxgTIMwzAiiQmUYRiGEUlMoAzDMIxIYgJlGIZhRBITKMMwDCOSmEAZRhUgIt8VkdUiclnYthhGqTCBMoyY45W+GQl8HlcLzzCqAhMow4gRItIgIv8jIrX+NlU9gWs09zPgn7zj6kXkFa8IqWHEEhMow4goXvHc9P/R3wWeVtWzgeNGAIOAY7hWF6hrGLcC+EyFzDWMkmMCZRgRQkTaRWSjiDyJq1Y9Nu2QO+ldSfprwD/giogGmyk+6x1vGLHEBMowosck4HuqOk0D7ee9FgYTVXVbYFs7cAWuj9AGUgVqPWBJE0ZsMYEyjOjxnqq+lmF7C3A4bdtfA19X15YgRaC8MOApv4+QYcQNm0A1jOhxIsv2LiDhvxCRGbgurFeKyCPevnVp7xkIdJfDSMMoN+ZBGUZMUNX3gVoR8UXqYVwH23ZVbQcuIeBBeckTB1T1dMWNNYwSYB6UYcSLF3Ee0zlgkKq+5O9Q1b0iMlhEmlX1EHAt8HxYhhpGsVhHXcOIESIyC/gjVb2rgGOfBhaq6qbyW2YYpcdCfIYRI1R1NfBycKFuJryMv2dNnIw4Yx6UYRiGEUnMgzIMwzAiiQmUYRiGEUlMoAzDMIxIYgJlGIZhRBITKMMwDCOSmEAZhmEYkeT/Ac1UluFnqIbwAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e5860f28>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "mc = MPDFcalculator(mstruc)\n",
     "r, fr = mc.calc() ### by default, just the normalized mPDF is calculated\n",
@@ -753,11 +1709,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 27,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e56995c0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Default mPDF calculator\n",
     "mc = MPDFcalculator(mstruc)\n",
@@ -791,11 +1758,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e59ec5c0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Change the intrinsic mPDF peak width to simulate thermal motion\n",
     "### and/or instrumental limitations.\n",
@@ -825,11 +1803,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 29,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e56cb358>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Include a damping factor to simulate a finite correlation length\n",
     "### and/or instrumental resolution effects.\n",
@@ -858,11 +1847,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e7565b38>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Reduce the ordered scale factor, simulating a reduced ordered moment.\n",
     "mcS = mc.copy()\n",
@@ -890,11 +1890,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7ff7e58455c0>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "### Change the r-range for the calculation from 20 Angstroms (default) to 40.\n",
     "mcL = mc.copy()\n",
@@ -921,7 +1932,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {
     "collapsed": true
    },
@@ -941,7 +1952,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here, we will provide an example of doing a very basic mPDF fit to actual experimental data taken on MnO. The initial structural PDF was refined using PDFgui, and now we use the residual of that structural fit as the dataset against which the mPDF will be refined. To keep things simple, we will just refine the scale factors here."
+    "Here, we will provide an example of doing a very basic mPDF fit to actual experimental data taken on MnO. The initial structural PDF was refined using PDFgui, and now we use the residual of that structural fit as the dataset against which the mPDF will be refined. To keep things simple, we will just refine the scale factors and an overall damping envelope here."
    ]
   },
   {
@@ -953,7 +1964,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
@@ -967,16 +1978,814 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Make the magneitc structure"
+    "### Make the magnetic structure"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/ben/anaconda/envs/mpdfdev/lib/python2.7/site-packages/diffpy.Structure-1.3.2-py2.7.egg/diffpy/Structure/lattice.py:125: FutureWarning: comparison to `None` will result in an elementwise object comparison in the future.\n",
+      "  if [a, b, c, alpha, beta, gamma, base] == 7*[None]:\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",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<img 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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "svec = np.array([1.0,-1.0,0.0])\n",
     "msp = MagSpecies(struc,magIdxs=[0,1,2,3],ffparamkey='Mn2',rmaxAtoms=50,basisvecs=svec,\n",
@@ -999,79 +2808,1747 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Extract the mPDF data and make the MPDFcalculator"
+    "### Extract the data, load it into a Profile object"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "collapsed": true
    },
    "outputs": [],
    "source": [
+    "PDFguiFile = 'MnOpdfgui.ddp'\n",
     "r,d = getDiffData(PDFguiFile, 0) ### extract the fit residual from the atomic PDF fit done in PDFgui\n",
     "\n",
-    "mc = MPDFcalculator(mstr)\n",
-    "mc.rmin = r.min()\n",
-    "mc.rmax = r.max()"
+    "from diffpy.srfit.fitbase import Profile\n",
+    "\n",
+    "profile = Profile()\n",
+    "profile.setObservedProfile(r, d)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Refine the magnetic structure (just scale factor and damping rate for now)"
+    "### Make the MPDFcalculator, set up the fit"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
-    "collapsed": false
+    "collapsed": true
    },
    "outputs": [],
    "source": [
-    "from scipy.optimize import least_squares\n",
+    "### Create the MPDFcalculator\n",
+    "mc = MPDFcalculator(mstr)\n",
+    "mc.rmin = profile.xobs.min()\n",
+    "mc.rmax = profile.xobs.max()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "### Make the FitContribution\n",
     "\n",
-    "def residual(p,ydata):\n",
-    "    oscale,pscale,damp = p\n",
-    "    mc.ordScale = oscale\n",
-    "    mc.paraScale = pscale\n",
-    "    mc.dampRate = damp\n",
-    "    return ydata - mc.calc(both=True)[2]\n",
-    "\n",
-    "p0 = [0.1,0.1,0.1]\n",
-    "optimized = least_squares(residual,p0,bounds=[[0,0,0],[10,10,10]],args=(d,))\n",
-    "fit = mc.calc(both=True)[2]\n",
-    "\n",
-    "fig=plt.figure()\n",
-    "ax=fig.add_subplot(111)\n",
-    "ax.plot(r,d,'bo',linestyle='none')\n",
-    "ax.plot(r,fit,'r-',lw=2)\n",
-    "ax.set_xlabel('r ($\\AA$)')\n",
-    "ax.set_ylabel('D($\\AA^{-2}$)')\n",
+    "from diffpy.srfit.fitbase import FitContribution\n",
+    "mfit = FitContribution('mfit')\n",
+    "mfit.setProfile(profile)\n",
+    "\n",
+    "# Define the function that will calculate the mPDF\n",
+    "def mpdf(parascale, ordscale, damp):\n",
+    "    mc.paraScale, mc.ordScale, mc.dampRate = parascale, ordscale, damp\n",
+    "    dr = mc.calc(both=True)[2]\n",
+    "    return dr\n",
+    "\n",
+    "mfit.registerFunction(mpdf)\n",
+    "mfit.setEquation(\"mpdf(parascale, ordscale, damp)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<diffpy.srfit.fitbase.parameter.ParameterProxy at 0x7fec5423e6d0>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "### Make the FitRecipe\n",
+    "### Make the FitRecipe and add the relevant variables\n",
+    "from diffpy.srfit.fitbase import FitRecipe\n",
+    "recipe = FitRecipe()\n",
     "\n",
-    "plt.show()    \n",
+    "# give the PDFContribution to the FitRecipe\n",
+    "recipe.addContribution(mfit)\n",
     "\n",
-    "print optimized.x"
+    "# add the mPDF variables\n",
+    "recipe.addVar(mfit.parascale, 4)\n",
+    "recipe.addVar(mfit.ordscale, 0.5)\n",
+    "recipe.addVar(mfit.damp, 0.01)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Plot the atomic refinement along with the magnetic refinement"
+    "### Run the refinement"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Refine using scipy's least-squares optimizer:\n",
+      "  variables: ['parascale', 'ordscale', 'damp']\n",
+      "  initial values: [ 2.8959563   1.23062246  0.00673758]\n",
+      "  final values: [ 2.8959563   1.23062245  0.00673758]\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",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "### Run the refinement\n",
+    "\n",
+    "# Turn off printout of iteration number.\n",
+    "recipe.clearFitHooks()\n",
+    "\n",
+    "# Initial structural fit\n",
+    "print \"Refine using scipy's least-squares optimizer:\"\n",
+    "print \"  variables:\", recipe.names\n",
+    "print \"  initial values:\", recipe.values\n",
+    "\n",
+    "from scipy.optimize import least_squares\n",
+    "\n",
+    "least_squares(recipe.residual, recipe.values)\n",
+    "print \"  final values:\", recipe.values\n",
+    "\n",
+    "### Plot the results\n",
+    "fit = mfit.evaluateEquation(\"mpdf\")\n",
+    "\n",
+    "ax=plt.figure().add_subplot(111)\n",
+    "ax.plot(r, d, 'bo', label=\"mPDF data\", markerfacecolor='none', markeredgecolor='b')\n",
+    "ax.plot(r, fit, 'r-', lw=2, label=\"mPDF fit\")\n",
+    "ax.set_xlabel(r\"r ($\\AA$)\")\n",
+    "ax.set_ylabel(r\"D ($\\AA^{-2}$)\")\n",
+    "ax.set_xlim(xmax=mc.rmax)\n",
+    "plt.legend(loc=1)\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": [
+       "/* Put everything inside the global mpl namespace */\n",
+       "window.mpl = {};\n",
+       "\n",
+       "\n",
+       "mpl.get_websocket_type = function() {\n",
+       "    if (typeof(WebSocket) !== 'undefined') {\n",
+       "        return WebSocket;\n",
+       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
+       "        return MozWebSocket;\n",
+       "    } else {\n",
+       "        alert('Your browser does not have WebSocket support.' +\n",
+       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
+       "              'Firefox 4 and 5 are also supported but you ' +\n",
+       "              'have to enable WebSockets in about:config.');\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
+       "    this.id = figure_id;\n",
+       "\n",
+       "    this.ws = websocket;\n",
+       "\n",
+       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
+       "\n",
+       "    if (!this.supports_binary) {\n",
+       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
+       "        if (warnings) {\n",
+       "            warnings.style.display = 'block';\n",
+       "            warnings.textContent = (\n",
+       "                \"This browser does not support binary websocket messages. \" +\n",
+       "                    \"Performance may be slow.\");\n",
+       "        }\n",
+       "    }\n",
+       "\n",
+       "    this.imageObj = new Image();\n",
+       "\n",
+       "    this.context = undefined;\n",
+       "    this.message = undefined;\n",
+       "    this.canvas = undefined;\n",
+       "    this.rubberband_canvas = undefined;\n",
+       "    this.rubberband_context = undefined;\n",
+       "    this.format_dropdown = undefined;\n",
+       "\n",
+       "    this.image_mode = 'full';\n",
+       "\n",
+       "    this.root = $('<div/>');\n",
+       "    this._root_extra_style(this.root)\n",
+       "    this.root.attr('style', 'display: inline-block');\n",
+       "\n",
+       "    $(parent_element).append(this.root);\n",
+       "\n",
+       "    this._init_header(this);\n",
+       "    this._init_canvas(this);\n",
+       "    this._init_toolbar(this);\n",
+       "\n",
+       "    var fig = this;\n",
+       "\n",
+       "    this.waiting = false;\n",
+       "\n",
+       "    this.ws.onopen =  function () {\n",
+       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
+       "            fig.send_message(\"send_image_mode\", {});\n",
+       "            if (mpl.ratio != 1) {\n",
+       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
+       "            }\n",
+       "            fig.send_message(\"refresh\", {});\n",
+       "        }\n",
+       "\n",
+       "    this.imageObj.onload = function() {\n",
+       "            if (fig.image_mode == 'full') {\n",
+       "                // Full images could contain transparency (where diff images\n",
+       "                // almost always do), so we need to clear the canvas so that\n",
+       "                // there is no ghosting.\n",
+       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "            }\n",
+       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
+       "        };\n",
+       "\n",
+       "    this.imageObj.onunload = function() {\n",
+       "        this.ws.close();\n",
+       "    }\n",
+       "\n",
+       "    this.ws.onmessage = this._make_on_message_function(this);\n",
+       "\n",
+       "    this.ondownload = ondownload;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_header = function() {\n",
+       "    var titlebar = $(\n",
+       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
+       "        'ui-helper-clearfix\"/>');\n",
+       "    var titletext = $(\n",
+       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
+       "        'text-align: center; padding: 3px;\"/>');\n",
+       "    titlebar.append(titletext)\n",
+       "    this.root.append(titlebar);\n",
+       "    this.header = titletext[0];\n",
+       "}\n",
+       "\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_canvas = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var canvas_div = $('<div/>');\n",
+       "\n",
+       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
+       "\n",
+       "    function canvas_keyboard_event(event) {\n",
+       "        return fig.key_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
+       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
+       "    this.canvas_div = canvas_div\n",
+       "    this._canvas_extra_style(canvas_div)\n",
+       "    this.root.append(canvas_div);\n",
+       "\n",
+       "    var canvas = $('<canvas/>');\n",
+       "    canvas.addClass('mpl-canvas');\n",
+       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
+       "\n",
+       "    this.canvas = canvas[0];\n",
+       "    this.context = canvas[0].getContext(\"2d\");\n",
+       "\n",
+       "    var backingStore = this.context.backingStorePixelRatio ||\n",
+       "\tthis.context.webkitBackingStorePixelRatio ||\n",
+       "\tthis.context.mozBackingStorePixelRatio ||\n",
+       "\tthis.context.msBackingStorePixelRatio ||\n",
+       "\tthis.context.oBackingStorePixelRatio ||\n",
+       "\tthis.context.backingStorePixelRatio || 1;\n",
+       "\n",
+       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
+       "\n",
+       "    var rubberband = $('<canvas/>');\n",
+       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
+       "\n",
+       "    var pass_mouse_events = true;\n",
+       "\n",
+       "    canvas_div.resizable({\n",
+       "        start: function(event, ui) {\n",
+       "            pass_mouse_events = false;\n",
+       "        },\n",
+       "        resize: function(event, ui) {\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "        stop: function(event, ui) {\n",
+       "            pass_mouse_events = true;\n",
+       "            fig.request_resize(ui.size.width, ui.size.height);\n",
+       "        },\n",
+       "    });\n",
+       "\n",
+       "    function mouse_event_fn(event) {\n",
+       "        if (pass_mouse_events)\n",
+       "            return fig.mouse_event(event, event['data']);\n",
+       "    }\n",
+       "\n",
+       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
+       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
+       "    // Throttle sequential mouse events to 1 every 20ms.\n",
+       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
+       "\n",
+       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
+       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
+       "\n",
+       "    canvas_div.on(\"wheel\", function (event) {\n",
+       "        event = event.originalEvent;\n",
+       "        event['data'] = 'scroll'\n",
+       "        if (event.deltaY < 0) {\n",
+       "            event.step = 1;\n",
+       "        } else {\n",
+       "            event.step = -1;\n",
+       "        }\n",
+       "        mouse_event_fn(event);\n",
+       "    });\n",
+       "\n",
+       "    canvas_div.append(canvas);\n",
+       "    canvas_div.append(rubberband);\n",
+       "\n",
+       "    this.rubberband = rubberband;\n",
+       "    this.rubberband_canvas = rubberband[0];\n",
+       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
+       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
+       "\n",
+       "    this._resize_canvas = function(width, height) {\n",
+       "        // Keep the size of the canvas, canvas container, and rubber band\n",
+       "        // canvas in synch.\n",
+       "        canvas_div.css('width', width)\n",
+       "        canvas_div.css('height', height)\n",
+       "\n",
+       "        canvas.attr('width', width * mpl.ratio);\n",
+       "        canvas.attr('height', height * mpl.ratio);\n",
+       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
+       "\n",
+       "        rubberband.attr('width', width);\n",
+       "        rubberband.attr('height', height);\n",
+       "    }\n",
+       "\n",
+       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
+       "    // upon first draw.\n",
+       "    this._resize_canvas(600, 600);\n",
+       "\n",
+       "    // Disable right mouse context menu.\n",
+       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
+       "        return false;\n",
+       "    });\n",
+       "\n",
+       "    function set_focus () {\n",
+       "        canvas.focus();\n",
+       "        canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    window.setTimeout(set_focus, 100);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) {\n",
+       "            // put a spacer in here.\n",
+       "            continue;\n",
+       "        }\n",
+       "        var button = $('<button/>');\n",
+       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
+       "                        'ui-button-icon-only');\n",
+       "        button.attr('role', 'button');\n",
+       "        button.attr('aria-disabled', 'false');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "\n",
+       "        var icon_img = $('<span/>');\n",
+       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
+       "        icon_img.addClass(image);\n",
+       "        icon_img.addClass('ui-corner-all');\n",
+       "\n",
+       "        var tooltip_span = $('<span/>');\n",
+       "        tooltip_span.addClass('ui-button-text');\n",
+       "        tooltip_span.html(tooltip);\n",
+       "\n",
+       "        button.append(icon_img);\n",
+       "        button.append(tooltip_span);\n",
+       "\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    var fmt_picker_span = $('<span/>');\n",
+       "\n",
+       "    var fmt_picker = $('<select/>');\n",
+       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
+       "    fmt_picker_span.append(fmt_picker);\n",
+       "    nav_element.append(fmt_picker_span);\n",
+       "    this.format_dropdown = fmt_picker[0];\n",
+       "\n",
+       "    for (var ind in mpl.extensions) {\n",
+       "        var fmt = mpl.extensions[ind];\n",
+       "        var option = $(\n",
+       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
+       "        fmt_picker.append(option)\n",
+       "    }\n",
+       "\n",
+       "    // Add hover states to the ui-buttons\n",
+       "    $( \".ui-button\" ).hover(\n",
+       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
+       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
+       "    );\n",
+       "\n",
+       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
+       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
+       "    // which will in turn request a refresh of the image.\n",
+       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_message = function(type, properties) {\n",
+       "    properties['type'] = type;\n",
+       "    properties['figure_id'] = this.id;\n",
+       "    this.ws.send(JSON.stringify(properties));\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.send_draw_message = function() {\n",
+       "    if (!this.waiting) {\n",
+       "        this.waiting = true;\n",
+       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    var format_dropdown = fig.format_dropdown;\n",
+       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
+       "    fig.ondownload(fig, format);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
+       "    var size = msg['size'];\n",
+       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
+       "        fig._resize_canvas(size[0], size[1]);\n",
+       "        fig.send_message(\"refresh\", {});\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
+       "    var x0 = msg['x0'] / mpl.ratio;\n",
+       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
+       "    var x1 = msg['x1'] / mpl.ratio;\n",
+       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
+       "    x0 = Math.floor(x0) + 0.5;\n",
+       "    y0 = Math.floor(y0) + 0.5;\n",
+       "    x1 = Math.floor(x1) + 0.5;\n",
+       "    y1 = Math.floor(y1) + 0.5;\n",
+       "    var min_x = Math.min(x0, x1);\n",
+       "    var min_y = Math.min(y0, y1);\n",
+       "    var width = Math.abs(x1 - x0);\n",
+       "    var height = Math.abs(y1 - y0);\n",
+       "\n",
+       "    fig.rubberband_context.clearRect(\n",
+       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
+       "\n",
+       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
+       "    // Updates the figure title.\n",
+       "    fig.header.textContent = msg['label'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
+       "    var cursor = msg['cursor'];\n",
+       "    switch(cursor)\n",
+       "    {\n",
+       "    case 0:\n",
+       "        cursor = 'pointer';\n",
+       "        break;\n",
+       "    case 1:\n",
+       "        cursor = 'default';\n",
+       "        break;\n",
+       "    case 2:\n",
+       "        cursor = 'crosshair';\n",
+       "        break;\n",
+       "    case 3:\n",
+       "        cursor = 'move';\n",
+       "        break;\n",
+       "    }\n",
+       "    fig.rubberband_canvas.style.cursor = cursor;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
+       "    fig.message.textContent = msg['message'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
+       "    // Request the server to send over a new figure.\n",
+       "    fig.send_draw_message();\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
+       "    fig.image_mode = msg['mode'];\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Called whenever the canvas gets updated.\n",
+       "    this.send_message(\"ack\", {});\n",
+       "}\n",
+       "\n",
+       "// A function to construct a web socket function for onmessage handling.\n",
+       "// Called in the figure constructor.\n",
+       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
+       "    return function socket_on_message(evt) {\n",
+       "        if (evt.data instanceof Blob) {\n",
+       "            /* FIXME: We get \"Resource interpreted as Image but\n",
+       "             * transferred with MIME type text/plain:\" errors on\n",
+       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
+       "             * to be part of the websocket stream */\n",
+       "            evt.data.type = \"image/png\";\n",
+       "\n",
+       "            /* Free the memory for the previous frames */\n",
+       "            if (fig.imageObj.src) {\n",
+       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
+       "                    fig.imageObj.src);\n",
+       "            }\n",
+       "\n",
+       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
+       "                evt.data);\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
+       "            fig.imageObj.src = evt.data;\n",
+       "            fig.updated_canvas_event();\n",
+       "            fig.waiting = false;\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        var msg = JSON.parse(evt.data);\n",
+       "        var msg_type = msg['type'];\n",
+       "\n",
+       "        // Call the  \"handle_{type}\" callback, which takes\n",
+       "        // the figure and JSON message as its only arguments.\n",
+       "        try {\n",
+       "            var callback = fig[\"handle_\" + msg_type];\n",
+       "        } catch (e) {\n",
+       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
+       "            return;\n",
+       "        }\n",
+       "\n",
+       "        if (callback) {\n",
+       "            try {\n",
+       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
+       "                callback(fig, msg);\n",
+       "            } catch (e) {\n",
+       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
+       "            }\n",
+       "        }\n",
+       "    };\n",
+       "}\n",
+       "\n",
+       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
+       "mpl.findpos = function(e) {\n",
+       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
+       "    var targ;\n",
+       "    if (!e)\n",
+       "        e = window.event;\n",
+       "    if (e.target)\n",
+       "        targ = e.target;\n",
+       "    else if (e.srcElement)\n",
+       "        targ = e.srcElement;\n",
+       "    if (targ.nodeType == 3) // defeat Safari bug\n",
+       "        targ = targ.parentNode;\n",
+       "\n",
+       "    // jQuery normalizes the pageX and pageY\n",
+       "    // pageX,Y are the mouse positions relative to the document\n",
+       "    // offset() returns the position of the element relative to the document\n",
+       "    var x = e.pageX - $(targ).offset().left;\n",
+       "    var y = e.pageY - $(targ).offset().top;\n",
+       "\n",
+       "    return {\"x\": x, \"y\": y};\n",
+       "};\n",
+       "\n",
+       "/*\n",
+       " * return a copy of an object with only non-object keys\n",
+       " * we need this to avoid circular references\n",
+       " * http://stackoverflow.com/a/24161582/3208463\n",
+       " */\n",
+       "function simpleKeys (original) {\n",
+       "  return Object.keys(original).reduce(function (obj, key) {\n",
+       "    if (typeof original[key] !== 'object')\n",
+       "        obj[key] = original[key]\n",
+       "    return obj;\n",
+       "  }, {});\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
+       "    var canvas_pos = mpl.findpos(event)\n",
+       "\n",
+       "    if (name === 'button_press')\n",
+       "    {\n",
+       "        this.canvas.focus();\n",
+       "        this.canvas_div.focus();\n",
+       "    }\n",
+       "\n",
+       "    var x = canvas_pos.x * mpl.ratio;\n",
+       "    var y = canvas_pos.y * mpl.ratio;\n",
+       "\n",
+       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
+       "                             step: event.step,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "\n",
+       "    /* This prevents the web browser from automatically changing to\n",
+       "     * the text insertion cursor when the button is pressed.  We want\n",
+       "     * to control all of the cursor setting manually through the\n",
+       "     * 'cursor' event from matplotlib */\n",
+       "    event.preventDefault();\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    // Handle any extra behaviour associated with a key event\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.key_event = function(event, name) {\n",
+       "\n",
+       "    // Prevent repeat events\n",
+       "    if (name == 'key_press')\n",
+       "    {\n",
+       "        if (event.which === this._key)\n",
+       "            return;\n",
+       "        else\n",
+       "            this._key = event.which;\n",
+       "    }\n",
+       "    if (name == 'key_release')\n",
+       "        this._key = null;\n",
+       "\n",
+       "    var value = '';\n",
+       "    if (event.ctrlKey && event.which != 17)\n",
+       "        value += \"ctrl+\";\n",
+       "    if (event.altKey && event.which != 18)\n",
+       "        value += \"alt+\";\n",
+       "    if (event.shiftKey && event.which != 16)\n",
+       "        value += \"shift+\";\n",
+       "\n",
+       "    value += 'k';\n",
+       "    value += event.which.toString();\n",
+       "\n",
+       "    this._key_event_extra(event, name);\n",
+       "\n",
+       "    this.send_message(name, {key: value,\n",
+       "                             guiEvent: simpleKeys(event)});\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
+       "    if (name == 'download') {\n",
+       "        this.handle_save(this, null);\n",
+       "    } else {\n",
+       "        this.send_message(\"toolbar_button\", {name: name});\n",
+       "    }\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
+       "    this.message.textContent = tooltip;\n",
+       "};\n",
+       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
+       "\n",
+       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
+       "\n",
+       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
+       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
+       "    // object with the appropriate methods. Currently this is a non binary\n",
+       "    // socket, so there is still some room for performance tuning.\n",
+       "    var ws = {};\n",
+       "\n",
+       "    ws.close = function() {\n",
+       "        comm.close()\n",
+       "    };\n",
+       "    ws.send = function(m) {\n",
+       "        //console.log('sending', m);\n",
+       "        comm.send(m);\n",
+       "    };\n",
+       "    // Register the callback with on_msg.\n",
+       "    comm.on_msg(function(msg) {\n",
+       "        //console.log('receiving', msg['content']['data'], msg);\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
+       "        ws.onmessage(msg['content']['data'])\n",
+       "    });\n",
+       "    return ws;\n",
+       "}\n",
+       "\n",
+       "mpl.mpl_figure_comm = function(comm, msg) {\n",
+       "    // This is the function which gets called when the mpl process\n",
+       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
+       "\n",
+       "    var id = msg.content.data.id;\n",
+       "    // Get hold of the div created by the display call when the Comm\n",
+       "    // socket was opened in Python.\n",
+       "    var element = $(\"#\" + id);\n",
+       "    var ws_proxy = comm_websocket_adapter(comm)\n",
+       "\n",
+       "    function ondownload(figure, format) {\n",
+       "        window.open(figure.imageObj.src);\n",
+       "    }\n",
+       "\n",
+       "    var fig = new mpl.figure(id, ws_proxy,\n",
+       "                           ondownload,\n",
+       "                           element.get(0));\n",
+       "\n",
+       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
+       "    // web socket which is closed, not our websocket->open comm proxy.\n",
+       "    ws_proxy.onopen();\n",
+       "\n",
+       "    fig.parent_element = element.get(0);\n",
+       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
+       "    if (!fig.cell_info) {\n",
+       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
+       "        return;\n",
+       "    }\n",
+       "\n",
+       "    var output_index = fig.cell_info[2]\n",
+       "    var cell = fig.cell_info[0];\n",
+       "\n",
+       "};\n",
+       "\n",
+       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
+       "    var width = fig.canvas.width/mpl.ratio\n",
+       "    fig.root.unbind('remove')\n",
+       "\n",
+       "    // Update the output cell to use the data from the current canvas.\n",
+       "    fig.push_to_output();\n",
+       "    var dataURL = fig.canvas.toDataURL();\n",
+       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
+       "    // the notebook keyboard shortcuts fail.\n",
+       "    IPython.keyboard_manager.enable()\n",
+       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
+       "    fig.close_ws(fig, msg);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
+       "    fig.send_message('closing', msg);\n",
+       "    // fig.ws.close()\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
+       "    // Turn the data on the canvas into data in the output cell.\n",
+       "    var width = this.canvas.width/mpl.ratio\n",
+       "    var dataURL = this.canvas.toDataURL();\n",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.updated_canvas_event = function() {\n",
+       "    // Tell IPython that the notebook contents must change.\n",
+       "    IPython.notebook.set_dirty(true);\n",
+       "    this.send_message(\"ack\", {});\n",
+       "    var fig = this;\n",
+       "    // Wait a second, then push the new image to the DOM so\n",
+       "    // that it is saved nicely (might be nice to debounce this).\n",
+       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._init_toolbar = function() {\n",
+       "    var fig = this;\n",
+       "\n",
+       "    var nav_element = $('<div/>')\n",
+       "    nav_element.attr('style', 'width: 100%');\n",
+       "    this.root.append(nav_element);\n",
+       "\n",
+       "    // Define a callback function for later on.\n",
+       "    function toolbar_event(event) {\n",
+       "        return fig.toolbar_button_onclick(event['data']);\n",
+       "    }\n",
+       "    function toolbar_mouse_event(event) {\n",
+       "        return fig.toolbar_button_onmouseover(event['data']);\n",
+       "    }\n",
+       "\n",
+       "    for(var toolbar_ind in mpl.toolbar_items){\n",
+       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
+       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
+       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
+       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
+       "\n",
+       "        if (!name) { continue; };\n",
+       "\n",
+       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
+       "        button.click(method_name, toolbar_event);\n",
+       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
+       "        nav_element.append(button);\n",
+       "    }\n",
+       "\n",
+       "    // Add the status bar.\n",
+       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
+       "    nav_element.append(status_bar);\n",
+       "    this.message = status_bar[0];\n",
+       "\n",
+       "    // Add the close button to the window.\n",
+       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
+       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
+       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
+       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
+       "    buttongrp.append(button);\n",
+       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
+       "    titlebar.prepend(buttongrp);\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._root_extra_style = function(el){\n",
+       "    var fig = this\n",
+       "    el.on(\"remove\", function(){\n",
+       "\tfig.close_ws(fig, {});\n",
+       "    });\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
+       "    // this is important to make the div 'focusable\n",
+       "    el.attr('tabindex', 0)\n",
+       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
+       "    // off when our div gets focus\n",
+       "\n",
+       "    // location in version 3\n",
+       "    if (IPython.notebook.keyboard_manager) {\n",
+       "        IPython.notebook.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "    else {\n",
+       "        // location in version 2\n",
+       "        IPython.keyboard_manager.register_events(el);\n",
+       "    }\n",
+       "\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
+       "    var manager = IPython.notebook.keyboard_manager;\n",
+       "    if (!manager)\n",
+       "        manager = IPython.keyboard_manager;\n",
+       "\n",
+       "    // Check for shift+enter\n",
+       "    if (event.shiftKey && event.which == 13) {\n",
+       "        this.canvas_div.blur();\n",
+       "        // select the cell after this one\n",
+       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
+       "        IPython.notebook.select(index + 1);\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
+       "    fig.ondownload(fig, null);\n",
+       "}\n",
+       "\n",
+       "\n",
+       "mpl.find_output_cell = function(html_output) {\n",
+       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
+       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
+       "    // IPython event is triggered only after the cells have been serialised, which for\n",
+       "    // our purposes (turning an active figure into a static one), is too late.\n",
+       "    var cells = IPython.notebook.get_cells();\n",
+       "    var ncells = cells.length;\n",
+       "    for (var i=0; i<ncells; i++) {\n",
+       "        var cell = cells[i];\n",
+       "        if (cell.cell_type === 'code'){\n",
+       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
+       "                var data = cell.output_area.outputs[j];\n",
+       "                if (data.data) {\n",
+       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
+       "                    data = data.data;\n",
+       "                }\n",
+       "                if (data['text/html'] == html_output) {\n",
+       "                    return [cell, data, j];\n",
+       "                }\n",
+       "            }\n",
+       "        }\n",
+       "    }\n",
+       "}\n",
+       "\n",
+       "// Register the function which deals with the matplotlib target/channel.\n",
+       "// The kernel may be null if the page has been refreshed.\n",
+       "if (IPython.notebook.kernel != null) {\n",
+       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
+       "}\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Javascript object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
+    "### Plot the total PDF (atomic + magnetic) with the total fit\n",
     "from diffpy.pdfgui import tui ### useful library to interact with PDFgui projects\n",
     "prj = tui.LoadProject(PDFguiFile)\n",
     "fitObj = prj.getFits()[0]\n",
@@ -1102,6 +4579,17 @@
     "plt.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "plt.close('all')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1118,11 +4606,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2.33669157881\n"
+     ]
+    }
+   ],
    "source": [
     "nucScale = 0.9518 ### refined nuclear scale factor taken from PDFgui\n",
     "\n",
@@ -1150,17 +4646,6 @@
     "This is fairly consistent with our expectation of S = 5/2 for Mn2+."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "plt.close('all')"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1189,5 +4674,5 @@
   }
  },
  "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
 }