From c43656826722f78cec550e467b1a7a4bfcd9c1b8 Mon Sep 17 00:00:00 2001
From: Ralf Toenjes <toenjes@cluster.stat.physik.uni-potsdam.de>
Date: Thu, 24 Jan 2019 11:27:09 +0100
Subject: [PATCH] Uebung 09 bewertet

---
 .../Uebung09-checkpoint.ipynb                 | 1913 +++++++++++++++++
 Uebung9/Uebung09.ipynb                        |  174 +-
 2 files changed, 2006 insertions(+), 81 deletions(-)
 create mode 100644 Uebung9/.ipynb_checkpoints/Uebung09-checkpoint.ipynb

diff --git a/Uebung9/.ipynb_checkpoints/Uebung09-checkpoint.ipynb b/Uebung9/.ipynb_checkpoints/Uebung09-checkpoint.ipynb
new file mode 100644
index 0000000..ccd9552
--- /dev/null
+++ b/Uebung9/.ipynb_checkpoints/Uebung09-checkpoint.ipynb
@@ -0,0 +1,1913 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulation und Modellierung WS 18/19 Uebung 09 \n",
+    "### Abgabe zum 21.01.2019"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Aufgabe 1 : einfache Flaechen in 3d\n",
+    "Plotten Sie die Oberflaeche eines <a href=\"https://de.wikipedia.org/wiki/Torus\">Torus</a> und ein <a href=\"https://de.wikipedia.org/wiki/M%C3%B6biusband\">Moebiusband</a> in Zylinderkoordinaten."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from pylab import *\n",
+    "from mpl_toolkits.mplot3d import Axes3D\n",
+    "#from scipy.spatial import Delaunay"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "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": [
+       "<img 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\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "theta = np.linspace(0, 2.*pi, 200)\n",
+    "phi = np.linspace(0, 2.*pi, 200)\n",
+    "TH, PH = np.meshgrid(theta, phi)\n",
+    "a, i = 4, 1\n",
+    "x = (a + i*cos(TH)) * cos(PH)\n",
+    "y = (a + i*cos(TH)) * sin(PH)\n",
+    "z = i * sin(TH)\n",
+    "\n",
+    "fig = figure('3D-Plot')\n",
+    "ax = fig.add_subplot(121, projection='3d')\n",
+    "ax.set_zlim(-3,3)\n",
+    "ax.plot_surface(x, y, z, cmap=\"rainbow\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib notebook"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "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"
+    }
+   ],
+   "source": [
+    "phi = np.linspace(0,2*np.pi, 100)\n",
+    "a = np.linspace(-1,1, 100)\n",
+    "PH, A = np.meshgrid(phi,a)\n",
+    "\n",
+    "\n",
+    "x = cos(PH)*(1+(A/2)*(cos(PH/2)))\n",
+    "y = sin(PH)*(1+(A/2)*(cos(PH/2)))\n",
+    "z = (A/2)*sin((PH/2))\n",
+    "\n",
+    "fig = figure('3D-Plot')\n",
+    "ax = fig.add_subplot(121, projection='3d')\n",
+    "ax.set_zlim(-3,3)\n",
+    "ax.plot_surface(x, y, z, cmap=\"Reds\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Aufgabe 2 : choose your weapon\n",
+    "Der Angriffswert eines $k$-Magierstabes ergebe sich aus dem Produkt der Augenzahlen von $k$ 4er Wuerfeln $\\left(W4^k\\right)$. Der Angriffswert einer $k$-Kriegeraxt ergebe sich aus der Summe von $k$ 8er Wuerfeln $\\left(k W8\\right)$.\n",
+    "\n",
+    "Bestimmen Sie den **Wertebereich** der jeweiligen Angriffe und erzeugen Sie durch Simulation von Wuerfen fuer die beiden Waffen und verschiedene $k$-Werte Histogramme, die die **Wahrscheinlichkeiten** der Angriffswerte darstellen.\n",
+    "\n",
+    "*Hinweise :* Es ist moeglich, mehrere Histogramme semitransparent oder gestaffelt in einem Diagram abzubilden und so die Wahrscheinlichkeitsverteilungen besser zu vergleichen. Verwenden Sie zum wuerfeln `np.random.randint` oder `np.random.random_integer`.\n",
+    "\n",
+    "Bestimmen und vergleichen Sie ausserdem Mittelwerte, Standardabweichungen und Maxima der Verteilungen (z.B. in Form einer Tabelle) bzw. markieren diese in geeigneter Weise in den Diagrammen."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 213,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def Magierstab(k):\n",
+    "    Angriffswert = 1\n",
+    "    for i in range(k):\n",
+    "        Angriffswert *= np.random.randint(1,4) # achtung hier wird 1,2,3 ohne 4 erzeugt\n",
+    "    return Angriffswert\n",
+    "def Axt(k):\n",
+    "    Angriffswert = 0\n",
+    "    for i in range(k):\n",
+    "        Angriffswert += np.random.randint(1,8) # hier werden 1...7 ohne 8 erzeugt\n",
+    "    return Angriffswert\n",
+    "\n",
+    "k = 3\n",
+    "Angriffswert_Magierstab = []\n",
+    "Angriffswert_Axt = []\n",
+    "for n in range(10000):\n",
+    "    Angriffswert_Magierstab.append(Magierstab(k))\n",
+    "    Angriffswert_Axt.append(Axt(k))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Gute Loesung, die Wuerfe mit Hilfe von Funktionen zu simulieren. Dann aber vielleicht auch List Comprehension statt Schleife."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 214,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 227,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[]"
+      ]
+     },
+     "execution_count": 227,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "Magierstab = hist(Angriffswert_Magierstab, alpha=0.4)\n",
+    "mu_Magierstab = plt.axvline(mean(Angriffswert_Magierstab), color = 'b')\n",
+    "sig_Magierstab = plt.axvline(std(Angriffswert_Magierstab), linestyle = 'dotted', color = 'g')\n",
+    "max_Magierstab = plt.axvline(argmax(Angriffswert_Magierstab),linestyle = 'dotted', color = 'r')\n",
+    "\n",
+    "Axt=hist(Angriffswert_Axt, color = 'k', alpha=0.4)\n",
+    "mu_Axt = plt.axvline(mean(Angriffswert_Axt), color = 'k')\n",
+    "sig_Axt = plt.axvline(std(Angriffswert_Axt),  color = 'g')\n",
+    "max_Axt = plt.axvline(argmax(Angriffswert_Axt), color = 'r')\n",
+    "\n",
+    "plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dieses Histogamm zeigt keine Wahrscheinlichkeiten. Definieren Sie die Bins als `arange` ueber den Wertebereich und verwenden Sie `normed=True` oder `density=True` zur Normierung."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 216,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "7.9618\n",
+      "12.0441\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(mean(Angriffswert_Magierstab))\n",
+    "print(mean(Angriffswert_Axt))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 217,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "6.0803734062966885\n",
+      "3.477176324260822\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(std(Angriffswert_Magierstab))\n",
+    "print(std(Angriffswert_Axt))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 218,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "35\n",
+      "4\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(argmax(Angriffswert_Magierstab))  # argmax liefert nicht das maximum !!\n",
+    "print(argmax(Angriffswert_Axt))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Bemerkung : \n",
+    "-15%"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Zusatzaufgabe : Kugelflaechenfunktionen (+20P)\n",
+    "\n",
+    "So wie sich periodische Funktionen ueber rechteckigem Definitionsbereich in Fourierkomponenten zerlegen lassen, so koennen Funktionen auf einer Kugeloberflaeche in <a href=\"https://de.wikipedia.org/wiki/Kugelfl%C3%A4chenfunktionen\">Kugelflaechenfunktionen</a> $Y^{m}_l(\\vartheta,\\varphi)$ zerlegt werden. Insbesondere in der Atomphysik gibt $\\left|Y^m_l(\\vartheta,\\varphi)\\right|^2$ die Wahrscheinlichkeitsdichte an, ein Elektron mit einem bestimmten Drehimpuls, der durch die Quantenzahlen $(l,m)$ gegeben ist, in einer Richtung $\\vec{e}_r = \\left(\\cos\\varphi\\cos\\vartheta,\\sin\\varphi\\cos\\vartheta,\\sin\\vartheta\\right)$ zu finden.\n",
+    "\n",
+    "Plotten Sie diese Wahrscheinlichkeitsdichte als Flaeche in Kugelkoordinaten, wobei der Abstand $r$ vom Koordinaten Ursprung die Wahrscheinlichkeitsdichte in Richtung $\\vec{e}_r$ repraesentiert."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Stellen Sie die Wahrscheinlichkeitsdichten fuer die folgenden Kugelflaechenfunktionen dar :\n",
+    "\n",
+    "$$\n",
+    "    Y_{0}^{0}(\\vartheta,\\varphi)={1\\over 2}\\sqrt{1\\over \\pi}\n",
+    "$$\n",
+    "$$\n",
+    "    Y_{1}^{ 0}(\\vartheta,\\varphi) =  {1\\over 2}\\sqrt{3\\over  \\pi}\\cdot \\cos\\vartheta\n",
+    "$$\n",
+    "$$\n",
+    "    Y_{1}^{ 1}(\\vartheta,\\varphi) = -{1\\over 2}\\sqrt{3\\over 2\\pi}\\cdot e^{i\\varphi}\\cdot \\sin\\vartheta\n",
+    "$$\n",
+    "$$\n",
+    "    Y_{2}^{ 0}(\\vartheta,\\varphi)= {1\\over 4}\\sqrt{ 5\\over  \\pi}\\cdot (3\\cos^{2}\\vartheta-1)\n",
+    "$$\n",
+    "$$\n",
+    "    Y_{2}^{ 1}(\\vartheta,\\varphi)=-{1\\over 2}\\sqrt{15\\over 2\\pi}\\cdot e^{  i\\varphi}\\cdot\\sin    \\vartheta\\cdot  \\cos\\vartheta\n",
+    "$$\n",
+    "$$\n",
+    "    Y_{2}^{ 2}(\\vartheta,\\varphi)= {1\\over 4}\\sqrt{15\\over 2\\pi}\\cdot e^{ 2i\\varphi}\\cdot\\sin^{2}\\vartheta\n",
+    "$$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "*Hinweise :* Sie koennen den Realteil oder das Vorzeichen des Realteils der <a href=\"https://de.wikipedia.org/wiki/Kugelfl%C3%A4chenfunktionen\">Kugelflaechenfunktionen</a> zusammen mit einer geeigneten Colormap (`cmap`) als Farbe der Flaechenelemente definieren, und so gegenphasige Schwingungen repraesentieren. Sie koennen ausserdem Transparenz einsetzen. Die Funktion `np.exp` akzeptiert auch komplexe Argumente."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.4.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Uebung9/Uebung09.ipynb b/Uebung9/Uebung09.ipynb
index c559dda..ccd9552 100644
--- a/Uebung9/Uebung09.ipynb
+++ b/Uebung9/Uebung09.ipynb
@@ -18,19 +18,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "metadata": {},
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [],
    "source": [
     "from pylab import *\n",
     "from mpl_toolkits.mplot3d import Axes3D\n",
-    "from scipy.spatial import Delaunay"
+    "#from scipy.spatial import Delaunay"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
-   "metadata": {},
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "%matplotlib notebook"
@@ -38,8 +42,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
-   "metadata": {},
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {
@@ -47,7 +54,6 @@
        "/* 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",
@@ -106,9 +112,6 @@
        "    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",
@@ -123,7 +126,7 @@
        "        };\n",
        "\n",
        "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
+       "        this.ws.close();\n",
        "    }\n",
        "\n",
        "    this.ws.onmessage = this._make_on_message_function(this);\n",
@@ -178,15 +181,6 @@
        "    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",
@@ -243,9 +237,8 @@
        "        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",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
        "\n",
        "        rubberband.attr('width', width);\n",
        "        rubberband.attr('height', height);\n",
@@ -378,10 +371,10 @@
        "}\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",
+       "    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",
@@ -537,8 +530,8 @@
        "        this.canvas_div.focus();\n",
        "    }\n",
        "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\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",
@@ -600,7 +593,7 @@
        "};\n",
        "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
        "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+       "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",
@@ -618,7 +611,7 @@
        "    // Register the callback with on_msg.\n",
        "    comm.on_msg(function(msg) {\n",
        "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
        "        ws.onmessage(msg['content']['data'])\n",
        "    });\n",
        "    return ws;\n",
@@ -659,7 +652,6 @@
        "};\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",
@@ -668,7 +660,7 @@
        "    // 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.parent_element).html('<img src=\"' + dataURL + '\">');\n",
        "    fig.close_ws(fig, msg);\n",
        "}\n",
        "\n",
@@ -679,9 +671,8 @@
        "\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",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
        "}\n",
        "\n",
        "mpl.figure.prototype.updated_canvas_event = function() {\n",
@@ -824,7 +815,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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\" 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T08P9u7da/U/1xRWrwGEEELKEKuDX6no7e1NzecNh8N5y99IBVD9fHUGLRqNlvR5xooAqteQSazGmgBmywaqVjRqlFxvb++YyAZavQYQQggpQ6wOfqWgr68PkUgkJSft7e15y18pBFCdk8slfweCAKot3HybR5dSAFWGtdDHmXsc+ny+VBsd89nA/v5+S//9Wr0GEEIIKUMsjXwlwCx/arRZPjKWLmaFjmgzTxPxeDyIRCKjIppjRQDTBc4sVpFIZNhsoFUCaM4Ger1eeL3elLQqCbQ6G2j1GkAIIaQMsSTilQglf5FIBLFYDIFAILU9WYhkFTrXNx6Pp2QzX/kbiQCqKSJjSQDVlat5tPny+/2WCqB6D36/f8jEEyWCiUTCkmyg1WsAIYSQMmS/R7sSsXfvXkSj0ZR8qW1YdQZwtAVQNUsuRDaLEUCV0fR4PAgEAggEAmNKAJVAhUKhIc2j0wUwFosV/fzRaLTo964utY1tltaxkA20eg0ghBBShuy3KFdCMsmfysSpKuDRFEC19WkuAhkNATRvaasiE6/XW1QrltEUwPTnMM/oHUsCaH4P5okn5i1sK7KBVq8BhBBCypD9EuFKSH9/P2KxWEr+VOZJ/bm9vX1Ut4CV/CnpLFQACxFNtaUdCARSo+BUK5Z4PF6Q/OwPAUwkEqmpIaodzlgVQHV1dnamekWqLez9nQ20eg0ghBBShoxqZCsxSv5Uhi9d/uLxeKrSs1ABzDXXV11qnnAwGExl50ZLAJVEKdk0F4FkmngxVgRQXfH4vgKW7u7uEQvgSM4/DiehVmcDrV4DCCGElCGjFtVKjFn+1H/VYX6zOI2WACr5CwQCqRFz6sxbqQXQLLbZqoALbcWyvwUwkdg3o1e15Sk0a7m/BDD9M/L7/fs1G2j1GkAIIaQMKXk0GwX6+/tTApVL/ooVwGxzfdWlRsopgVC3jYYApr83JZ2Z2sAU0oplpAJYbBWveSpHIBAoqHn0/hZA9XozFbSMZjbQ6jWAEEJIGVLSSDYKDAwMoKOjIyV/SniySZ7P50MwGCyZAGabJ1yMAA531jDTe8slgOpS59jMmav0Kx6Pj1gAR7KFq7KAhTSPNl/hcDjVxLnYy+fz5Z2FzJYNDAQCiEQiJc0GWr0GEEIIKUNKEsFGiULlLx6Pw+/3l0wA1TzhdPlTVykF0NxY2nx7PgJozlylF1+YBbDQUWqlFED1GRbSPNpKAcz0mSoBjEaj6O7uLlkm0Oo1gBBCSBlSkgg2CgwMDKCzs3OI/A0ndyMRwPQM33DzhEslgObzhenfy1cAzaJnLr4YKwJoPgOYqfJ2fwigmglc6OPMfw9KZBOJBDOAhBBCxi8liWAlZmBgANFoNFXxaq6+HU6ySiGAauqEyvxke1wpBDDT+cKRCGAiMbj4QgnPWBBAs3zl0zzafIVCIcsEUH2mqvWPqr4uFVavAYQQQsqQkkWxEjEwMICuri74fL5U4YG5+jYfAcyUSct1pbd0UU2Xh5O7kQpgtvOFIxVAJVhKbFUWdSwJoLo6OjpS7zFXg+tQKIRwOGyZAJp/hnq93AImhBAybilJBCsRAwMD6O7uRjgcTs1tLUT+SiGAqv9ePmJXyBzgdAHMZ4t5JAKoLjX2TBVgjDUBNGfXcjW4LoUAer3eogpQzJf5LCO3gAkhhIxbShLBSoBZ/tQWrMfjybo1mu1S83KLEUDzSLl8HlesAKr3N5z8lUIAE4l91av5brfubwFUl2pwnX5+cSwJoHofe/bsKdm/favXAEIIIWVIyaLYCBgYGEhNY1BNltXc20Lkb6QCWKjQFSOAqh9evlnGUghgIrGvDUw+263ZMl/ZsnOllC81NSRdGIPBICKRyIjkzePx5F10QgEkhBByQFOyKDYC0uVPiYqSjkIF0O/3F/QYVYxQaANpr9dblADmK39K2swCWOw83Hg8WQSiCkQKnSe8vwQwkRh6frGnp2fMCKB6HxRAQggh45qSRbEiSSQSg+RP9d1TLTdGWwCVlBVa0FGMAKpt2EIeowQwFAohGo2OWACVYKmsZ77zhPenAKpLFQOpgqCRCGBPTw88Hk/BmU8KICGEkAOSkkWxIlDyF41GhxRFhEKhogQwGAzmLYDmxtKjLYBqxNtwM4f3hwBmEqzh5MwKAVTiZt46L3aUXKkEUGURe3t7S/Z7YPUaQAghpAwpWRQrkN7e3kHyl14UMdoCmN5bcDQF0NzEuhgBDAaDoyKASoyUnOYqEBmpAHo8nhEVYPh8Pni93pzj7kZbANXPoAASQggZ95QsihVAb28vIpHIIPlLPxcXCoVS0yMKFcDhxDFTb8FiBTAcDg/7XEr+cs0ctkoA1WWefZtJkkohgCM5f6dm8BbSPNp8dXd3w+PxFJ1BTJdICiAhhJBxTcmiWJ709fUNkr9sFbGjJYDZJm8UejYvHwFMH/E2lgVQSVK2fnxWC6C5DY367AupZqYAEkIIISZKFsXywCx/8XjuiRvhcLgoAcy1dZxr8kapBTCTaI51AVSXasNjLhAZSwI4nKxmurq6ukYsgGaJpAASQggZ15Qsig3D3r17EYlEUpKlzsNl23YttQCaK4yzzdwtVADb29szCmA20RwvAqiESZ3L7OzsHPEYtVILYCKxr5pZneXMJXdKAIt9fgogIYSQA4qSRbEc7N27F9FoNCVY6hxXLuEKh8OD5uaORADzGbtWKgHM9VzjSQCVYJl7FxabASxFAUauDGS25tGlFkDzz+jr6yvZ74fVawAhhJAypGRRLAvFyF88PnhubqECaM4c5jt2rRQCONxzjTcBVFdnZyc8Hg98Pp9lFbjDbUFnah6d/h68Xi8FkBBCCBEZXQHs7+8f1JZFtRsZrnJ2JAJo3jrOVWSSSQDzeV25BHC451KCUsh4u7EggIlEIlV0ocbzjTUBNEtapt6GpRBA88+gABJCCBnXlCyKpREKhfDDH/4wNcWhEPlTAlhotixdAFWRQL4zd0cigPk813gWQLW9qj6rYDCYt9CVQgDV32m+z6f+vUUiEfT09KTa3FAACSGEEBk9AXzttddw+umnIxAIoL29vSD5K4UA5rvVnC2bl+9jQqFQ3s91IAhgIpFIzRPOtzBEFU+MVAALLUJRxSuqgGSkAmiWSAogIYSQcU3Jolga//jHP3DKKafA7/enxq0VIlfFnJdTAqhGrhU6c7cYAVTzffN5bLECGAgEEAgExowAqixbrjN3mQRwJC1Yiq1C7unpSQm61+sd0WswC+DevXtL9rti9RpACCGkDClZFEvjrbfewqZNm/DNb36zqLN8xchSPL6vvcxIz/Pl+5hC5DYWixX8nrxeL7xeLzweD/x+P/x+vyUC6PV6MwpYZ2dn6sxdtgKRUghgtufP91L/Y1BI8+hcnyEFkBBCyLimZFEsjd27d6O+vh4333xzUTN9ixFAtW1cTOawUAFUry+fucPFCqC6vxIXJZzFVOKWQgCzzfI1Z9kyjWgrlQCOZJaw+jtWhSzxeOEtbSiAhBBCDhhKFsVMvPHGG5g0aRJmzJiRczJHKWVJyZ85wBcqgPlm8tSINzUtY7Tek8pm+v1+hEIhRCKRlATGYrGChGo0BVBdHR0dGUe0jQUBVC16zM2jzZNOCvkZFEBCCCHjnpJFMRNXXnklrr76aixZsqTomb6FyJISsmAwWHTxiM/ny0vmzCPeCpHGQt+T+dxaIBAYVASiRKuQSlzVoHq0BUwViJi3bEvRhLlUAqj+bJ50ku/WMgWQEELIAUN6MLrlllswe/Zs1NXVoaWlBevXr8cf/vCHggJab28v+vv7sXDhwqJHuilZGq6Fi5K/QCAwKBM4GgKYPuItX2ksVADNLXPUtmV6FXChlbjpAjSaAmYuEAmFQqlG0iMRwJGOkotGo0PefyGFLOpnqM+/v7+fAkgIIWT8kh6M/vGPfyAajQIA+vr6cNddd6G1tRUDAwMFB7bRFkC1lafafCghHA0BzDTizefzIRgMllQAlcCq15JNANMFRvW7GwsCaM6yqc9sLAhgtgpqcyFLrvdIASSEEHLAkCswJRIJfO5zn4Ou6wgGgwUHNiWAxZzJi8fjOQXQvBVrFqrREMBsI95KLYDmrWx1Wy4BNAuM+iyySZIVAqgkNVeBSL4/YzQFUD1HevPo9PtEIhEEg0EKICGEkPFPpoD0/PPPo76+HpqmwWaz4brrrisqsC1cuLDokW65BFBl49RWbLpEFdM+JpfMZRvxVkoBVNnMQCAw6Pv5CKBZtLJVuFolgEpQPR5P6r0U2oalFJNEzPKW61K9/jLJdDgcpgASQgg5MMgVmCKRCO6++248/fTTRQW2UghgejPnTFuxoymAqhI3k4j6/f6iBDD9Z6WfLTR/L10Ah5O4eDyescJ1pAI4kgycGqHW3d2dGpmXSVLHggCq51Myba62DofDCIVCFEBCCCHjn+GC08DAAOrq6vDHP/6x4MCmBLCYLVklMmYBzLYVm2+WLdeVSeaGG/FWCgEcTmjNApivxJkrXFXWbiwIoFlGC2nDUgoBNMtbvpf6N6iylmrsHwWQEELIuGe44NTX14eqqip861vfKjiwHXzwwakM2kgFMBaLZd2KHQ0BNFfiFiKNhQig+T1le73FCKCSJvUeotFoXtnD/SWA2SQ121WKPoLFCKB6bvV35Pf7EQ6HkUgkiiqKyobVawAhhJAyJD0Y3XPPPfD5fAAAv9+Pbdu2oaGhAe3t7QUHtuXLl+Odd94pSsiUACoBU1uHw7WFybd9TC6ZS6/EHS0BzOc9+Xy+ogRQXepMmzozOVYEUEmq+qxzVTFbKYDqdaq/O5/Ph56eHgogIYSQ8U16MNq4cSMmTpwIt9uNyZMnY9OmTfjd735XVGA74ogj8K9//atoAVTj2VQWMdtWbKkEMBAIpM4Q5iN26jGFPI96bcNtL+cSwLfeegtPP/00PvWpT2H79u0466yzsHHjRqxfvx4bNmzA/Pnzce655+K6667Dfffdh5/+9Kf473//C4/HU/Q83ZEIoJLQXIKYq4q5FAIYCoVS2btiL9V3sb29Hb29vSMWP4XVawAhhJAypGRRLAPr1q3DX//61xEJYCAQyFv+0iWrUAH0+/2DmkqPlgAq+ctn9vCLL76IK664Aocdcggmu6tRpWkQEThFMFUES0VwrAg2imCzCNaKQESwTATzRdAgAk0ENhHU22yY1dqKE088Effcc09B2cTRFECVZTMXXpi/pyaJjAUBDIfDiMViPANICCFkfFOyKJaBU045BX/4wx+KErJ4PLkFnK8olUIA1dzdfGW1WAHMtb3s9/tx66234pBFB6HKEL1WEZxnCN5RIlgigpkiaBFBjQgqRGAXgW7InyaCKhHUi2CSCOaJYLkIThTBu0VwkghqjcdMrq3F5s2bsXv3bksFUF3q7z0YDKaErxSj5NSYwJEKYDQaRSLBM4CEEELGOSWLYhk4/fTT8etf/7ooIVNnw/x+f8HiWOjzqarUXMUYma5AIFCQAKrt5UyPefjhh7Fk4UK4DHF7twi2GkJnM+SuysjsXSyCO0XwhAheEsHvRPBXEbwugi8Yj/mlCL4ngi+J4EYRnCqCGSY5nCmCdSK4TARuETiM28866yy88cYbQ7Jz+0sAE4nklq95Tu9YEUC/358SwFJi8RJACCGkHClpJEvj3HPPxc9+9rOChUzJn2oVUowA5rtlrNqwqCrPQp6nEAFUkml+bX6/H5dddhmaKirgFMG5IrhIBAuMrF6NCKqN6+8iGBABhrkeN4Qu2/c7RfBjEXzM2D7WTRnED4jgIEMGD547F88+++wgASy2DUs8Hi9IANVzms9jjhUBVNvTpcTqNYAQQkgZUtJIlsZFF12EXbt2FSRk5nFow83nzXal9w/MJWUq01TMdm6+Amhu9Ky2gM85+2y4dR0TRfBhY1vWbVxXiGC3CPaK4FcicImgPw/5gwgeFEFjnveF8TxiSKcugmki2G5kH+0imNnaiqeeemrEAlhsBbIqEBnpKDjz9hXHFW4AACAASURBVG2xl2rUTQEkhBAy7ilpJEvjyiuvxPPPP5+3kCn5U1JV6Ki1QgXQ3FcwEAiMSgbQ3Og5EongmmuuQY3Nhqki+JQIVkvynN+hIvi6CBJpgtZtbNu+Yvw5JoKnRfA/kjwTeLiRtZutCWZqybN9DhEcIoLjRHChCO4ytokzSeSVxuMhgjdEcK2xFdxgiOClhgjOnTYNL7/88n4XwEQiuYWsxNk8mcMKAYzH49izZ09Jf0+sXgMIIYSUISWNZGns2LED3/rWt/ISMrVFai7CKLTPXiECmD7iLRgMFiWAuR5jzjB+4QtfgMuQq+NFcIIhfkeL4Gc5MnT/MDJ0bhHUa8aWrSaY69BxYpUD2+oqcGNjJT7VXIVPN1dheYUNIoIPNLhwVo0Th7vsaLVp0IzHTdKSz/+gCPaIYJEIdqQ9Z1wEnxZBnQiaRPAJEZxmiOWmU09FPJ7/GLdSCaAaH2eezFHIzzBv3xZ7tbe3UwAJIYQcGJQ0kqXxoQ99CE888cSghs65tkjTK3BHIoC5ni9TD77REMBgMIi3334bm049FQ5Jnu9bZIhUowh+lEX6/iSCM0TQrCWzfyKCel3wzUlu/GtWPQbmNgLzmjJeH2usxEy7PuT2zjmN+NW0WtzTUoWN1Q64taQQOiVZILInw+uIi+AmQ1Tni+ARSbaeaaiowPe+9739KoDqDKF5MkchPQ1LJYAdHR0UQEIIIeOfkkayNG6++WY8+uijqYbOueRPna8yf6+Yc3nxeDzn82Ub8VZqAQyFQvjpT3+K1poatBrbu/NFUCnJoo6D0mSrXwR3i2C6cRZveYUNX5xQjf+2NeCqeheWVdiySp/5urGxEnMcQwUw/do7txEvTKmBGIJZpSWrgv+SQQT/Lckzii4RvMt4DxUiqHG788rEjXQOcXoVsblAJBwO57UlrLZvRyKASjopgIQQQsY9JY1kadx2223YuXNnViEzn4/L1H6l0DYrwwlgrhFvxQhgtseEw2F89rOfRYWxdbrTkL61InhLBH+WZGuXvxji9xERNGiCak1wXYMLb8ysHyRrn2muwixnfgJ4Xb0LC/K877OT3HBqgj1zG/GdyTU4ssoBuySrg3+XJoEDxllCp3Em8MvGFnGV3T5shW+pBVBdXV1dqRF3w80TLpUAdnZ2UgAJIYSMf0oaydL43Oc+h3vuuQft7e1DpMt8Pi5b771SCuBwI95U1fFIBTASieCiCy+EXQSfEcElxpbvJ2VwEcZySVbeNmmCOl3Dp5ur0DEn89buU5PcaLZreUndjvoKHJynAF5f78L8tPu+Or0OG91O2EVwhAi8ptd8uAimiOBgSRaJfE+STamrdR2vvvrqqAlgPJ59C7mnpyeV1Y1Go1mzgaUQQFWJXMoxcAAFkBBCiAWUNJKlsXPnTtxxxx1D2rnEYrFBFbi5tliLFUDz86VXF4+WAEajUaxdswYuQ45WG5m/F9Oyaf8RQbOxlXpjUyXiWcRPXb+YVosqTfKSuu11FVia53bxSVUObK5xZvzer6fVYpnLjioteQ7wb0bm77ci6BHB+cbrf0yS1cguEezatWu/C2B6ljBbgYg6v0cBJIQQQmR0BfDRRx/FJz7xiSECGAwGh5U/JYDFTAIxC2C2ApP0KxQKjUgAY7EYFs6ZgxoR/MLI7k02xMksf3cZ5+0WOpPVun+ZUTesqP17Vj00EcRnN+BX02rxpQnV2FHvwvoqBxY5bZhs01Cva3BrkjrTN8uh43CXHefUOPHxpkp8a5Ibb6YVkCyssOHDjZVZn7d/biMebq1GtVF9vCxtS/hWY0v485JsJ1Mhkmoebb6i0eioC2AikSwQUf+20rN9IxVAczNsCiAhhJBxT0kjWRpPPPEEbrrppkH9/NLbrxS6xZrPpYQzV4FJKQUwFoth1vTpqBXBqyKYbVz/NQlTnwiOEYFTE3xxQjUG5jZivtOGq+sqsgrYwNxG/H56HT7SWJkSuwpNMLHChiVNldjU1oBrlk7CnUdOxyMnzMYT6+fiiMlu1DptuPnwqbjwoBYcPbkGs2ucqLfr0ETQqGs40+3E4xPdaLFpeKi1elgBfWdWPXRJViR/I01ov2Rscd8tyR6CFSL47ne/O0QAA4FA0fJVaAZRtRQKhUKpLWF1fo8CSAghhMjoCuC3v/1tXH/99al2Lpnar4yWAKot3VxnDEshgB6PB7W1tRBjK3SBCGaJwGeSJK8IpuqCaXYd/2fK+L2/wYWDMpzXe2dWPW5prMRUuw67CKa7nRARfHTlFPRfswrYsSbrdf6CFhwxuSbj9wKXLcdda2fiiEk1aLDrqNQEq112fGdyDfpytJZ5ZpIbdhH8T4MLDkmOjDNL4MOGBH5ZBFcZ28E//elPLRPARCJZIKLOmHZ2do5YALu7u+HxeNDT00MBJIQQMv4paSRL4/nnn8c111wDv98Pv9+fsf3KcIJVqJSpLWB15SN/SgBVo99CRNOm63CI4DxJbpO6jHNy5p5+dZrgyEo7wrMbBovV5BrU6fuKO16dXofNbidsIpjksuMDh01C6IoVwI41mOx24jNrZ+SUP+xYg3PmN+OoKbXD3q//mlUQESxuqkS1rqHFpuGulip0ZjiPeEKlHRvcybOC351cgwot2Q4mfWvbJcnehmcYX//zn/+0TABV1k5Vfns8nhFtAZsFsK+vr6S/J1avAYQQQsqQkkayNF566SVcdtllqVmuhchfsVm5eDzZCDrfbeaRCOD0adPgEMETkpymYRfBROPsX78Ifi8CtyY43e3EngwZtva2BogIfjS1NlV5e0hzFX68ZdEQYVvSUo1rlk4aVuzOnNuE46YNL4B/e89SiAg6rzoce65eheuXTUaj04ZaXcPdLVWDXu8Em4YHJuzbKv71tFrU6BrWpUngdkOCa40CEYcIXnvttREL4Egf39nZCY/HA5/PV/Q84a6uLgogIYSQA4eSRrI0fvGLX+CSSy7Bb37zm6JEbiTbsoVWD4fD4YIE8MEHH4RLBO8TwfOG7DwrgogIJojgZBHUaIJzapzYm2V7tXNOI6qNwo2DGyvx+/OWZBW242bU46x5TcOK3RlzGnHC9Lph7/fNk+eh0q4PyQrefPhU1No0zHDoeGlqLQJtDdBFhvQm/OOMOtTqGjaYBPAo45yiU5KVz/XGn19//XUEg0HLBDCRSKT+TXi93qImgigBTCQSFEBCCCHjn5JGsjS++c1vor6+HnfeeWdR7VwKzcqpM4bmopPREMC///3vyWydCIKSbIhsPhf3iJEJW1dpyyp/P59Wiyl2HS5NsKK1elhh2zq/GevyyOy9q60BG2bWD3u/W1dPw7Saiozf67l6FTbPboBDE0zSNTTZtIzj516dXocqTXCp8f6rRPBjQ/wuFMFLhhjbNLFUAM0FHCpDHAwG85ogYs4ier1eCiAhhJADg5JGMhNvvvkmWltbsXTp0qLbuRQigOYRb8WMkMtXAEOhEJwOBypE8LoI1khyrJuapdsvglm6BhHBSZX2jK1VPt5cCYcINrU14MMrpmBuQ+WwwvbepZOwbMLwonhaWwNOmdUw7P22HTwByydmLhZR18+2LIJNBA26hj9maVfz4tRa2Iys31PGZ/B9Q/x+aWyNu0Swffv2ogUuEomMSCDNAphIJM/zqQKRfM8FUgAJIYQcUJQ0kpk4+eSTce6552LDhg1FV/PmK2XpI95GSwCj0ShO3bgRLqPtydOG6PyfKft3mggm2DTsnFCNKk2wZ07DoC3fk91OVNs0PLF+LrBjDZ46eR6aKh3DCttHD5+KBY37RDF65Ur87twleObUBXjo+Nn43FEzceeRM7CgsRJLmqvw+Pq5ePH0g/D6hYeh75rVQ37eyTPrcdqcxmGfd0qNEy5dQ4Um+PYkd0YJbLUlhdc8NeTdxlnILhFMNbaC//73v48JAVS3FTJP2DyOjgJICCFk3FPSSGYiGAziP//5D44//viiq3nzlbL0EW/FTBAJh8OpBsLZnufJJ5+EJslWL72SnOZh3vp9zBDCl6fVom9uIxp1DZ9oSjZaDsxuwGKXHS0uO16/8NCUYL327kNg17Wc7V3637caN6yYgoYKG06YXocmlz3ZE9CmoaHSgYl1LkxrrsbMCW5UO21wO21odjtR47RB1wR2TTCvwYVLFk3A19bPhe+y5VjZ6sZli1uHFcAqh46fbFmEDy2fDIcm+HxL1SD5e31mXTJLqAmO1ZINomFsjbslOed4l/G5tDY2WiKA5greTJk9NU84V4GIWQD37t1b0t8Vq9cAQgghZUimgPShD30IixcvRm1tLSZPnoxzzjkHb7/9dsGBze/348gjjxyRAA4nZZlGvBUjgJFIJOtzxWIxvPPOO6hyOuAQwW4R3Gic/YsZwhMTQa2m4WOmyRrXNrjQZtfR3taAOU4bZridiF25csh5O00Er5yzeNDtA+9bjV9uXYxtB7eiocIGh66hymnDhjUzcOc1a/F/X383OnZfNeQ6bsU0bDpmdurPoRcvxzN3nYrtW5bg0HktaKhyQJekFG6e3Yjg5Suyyp+qFI4ar/mh42fDqQk+1bxPAk+ucmCly443Z9ahSgQPmIT4XhHUSHJ03EmSrJK+9tprCxa4cDiMUCg0KgKosoHq/GgsFst4v3h83zQSCiAhhJBxT6aAdOONN+LVV19FX18fYrEYzj33XCxdurTgwBaPx7F8+fKi27kMJ2XZRrwVc+Yw23PFYjH4fD5s2bIFNkNk+gz5u8ckO8eLYL5DR6+pWOK30+vgEMEMu4622gr0XJ05y9dSacfdR88EdqxB4upVePD42Zhd54LTpmHBjAbceuVqfOnD69BUX5lR+szXscum4vRj5+S8zy8f3ooqlwNVdh12TcNZ85vxh/MOGfK67lo7ExOqBm9PP7lhHio0wT0tVeif04AaXcOTxtbwLU2VqDJtBfca28DbRPAXEdiMreC//OUvBRVgjFQAzS1cct0vHo+n/ocifZ4wBZAQQsgBRT4B6g9/+AN0XUc0Gi0osO3ZswdLliwpqsfecFKWa8RbqQRQNSD+9a9/DTEyWL83tjUbjMwWRPAb43u/nFY7aHs0MacRFZqg0qaha/vKrJm2Fa1uXLCwBfcf14bmSgdqXXacu34+/v3di1PS9u1Pb0Stu2JYATz6sCnYcvzcYe/X0lSNB25ch6duOxkHzWqEXdewflYj/nT+0tTrOnNuE46eOrTy+KHjZ8OhCc6rcaJKE/SYmkdPt2l4t0mMH5JkX8A+EZxpbAUvO2RJQVW4pRLAfLOFql2MuUDE3IyaAkgIIWTck0+AuuOOOzBr1qyCA9vAwAAWLFgwIgH0eDwZM3K5pnwUU3SSSQCDwSC8Xi+WHbIEYlSz1hkVr3ONil+IYL4ITq9xDimOuKTOBZcmOKgxd5XvlrlNEBG4K2y4eushiPzoyiHC9sMvbEZ1pWNYsVu7dDK25iGA9bUufOO2k1N/fvmRrVg8pxl2TcNli1sRvXIlljRX4X1Zmk/fsGIKdBGcWzt4lvGPp9TALskJKBBBwpDlj4ngNVMW8LnnnkuNaRtOykKh0IgEUDWCzvf+mQpEKICEEEIOKIYLTrt27YLb7cYLL7xQVHBbuHBhwU2WswmgCsLDjXgrVgDNz6XOhP3oRz9KFlyI4GoR3GAITIUI5ongBUNq/pHWKPnxiW5UaIKbD5+Kugp7RonqvOpwXLp4Iuy6hkqXHb4XtmUVtp8/tBUVDtuwYnfkIZNx9onzhr1fdaUDP7h385Dbv3XnRrTUudBc6UC1Xcf9x7VlFVddkvONO9LGxy2usA0aFfcREUzVkl8fYXx+C2bNTH3mkUgkZzYwFAohHA6PSABVC5dCM4eqQCQcDqd6Efb39xf1u5ANi5cAQggh5UiuwPS9730P9fX1ePbZZ4sObkoAcxVzZLtUFsa8tev1eocd8TZSAVQ9BSORCNzV1RBJjnjrF8FqEWwSgUcEc4xs4Blp2b//zKpHpSa4aeUUBC9fAU0Efzp/8Bm7P5+/FLPqXGiqqcBlmxdjQnN1TmF79WvnwaZrw4rdmiWTcO76+cPez+nQ8ctHzsr4vdhPrsQ5J81DlV3HxYsmZGwj8+LpB0ETQZPThgvrXYObXBu9Ad8wPrMtRvZUJNksWozrxRdfRGdnZ+osZ/q5O6sFUGUD1b+H9vZ29PT0UAAJIYSMf7IFpccffxz19fXYtWvXiILbwoULcxZz5COAsVgsNeItn/m+xVQdq+dSIhgOh/HSSy+hQkvKy0cNmakWwXeNzNZfDZFZb2r4PDC3EeuqnZhf70rJ0qzaCnxo+eTUn7932gK4bDpWHTwRoRcvT57vq3bmFLa/PX0BRCTj9rD5Wr14Et69YUHO+8R+ciU0TfDak+dnvU/oxcshIqi061g7tQ6RKwafYTx7XjMOn+jGz7cuglNLzjM2S+BMhw1XimCmCJqMz2mNJOcmV4hAE8HihQtSkqW22+PxeMkF0NzCpdjLPGKwt7d3RL8T6Vi6ABBCCClPMgWke++9F/X19fj5z38+4uBWCgFU27GRSCSvxxVTdayey9xT0OVyYaZdg00EfxPBk4a8qOKPh4yMVoUm+NvM5KSMZybXwKXJoF5/Fy6agJUT3fsKKHQN27cs3nf+7tGz4HToOaXtze9dAhEZVBjSsfsqxH+6HZ4fbMPfv3UBXnvyfBw6vwVnnTAP4R9dkfVn/ee55M/6V9rPMl8/eWALNBH8+anzMamxCnMaKuHZtjz1nmbWufDx1dOAHWuwqa0Bs+yDK6A/3VQJpwgWisBvVEy3Gp/bhca2uV0E//73v1OSFYvF4PV6EQqFBm0JB4NBRCIRSwUwEokgEAik+hGWEouXAEIIIeVIpoCkaRqcTidqampQU1MDt9uNmpqaooRQbQGnF3Pkc8VisZSUhcPhvB9XjACqzJ/qH/jOO++gUhOsctkxwxCXk4xLnW1bo2t4V7UDx1c7cZjLjr65jZhu13HOvKZB2bIH1rVhorsCO49rg1PXcOc1awfJ1hvPXAQRwdvPX5JVyHwvXAYRwafftxY7zj0Ua5dNw6QWNxx2PbWlqmn7tldFBO4qJ+bPbMQZ6+bhtquPwEs7z0D4R1fglcfOgYjAv+vyrM9397VHo6HWhY7dVyGw63LMnlKH6TUV+O+ly9F/zSpU2XX8+IxFwI416Nq+Em5dwxcnVKcE8D01TlSK4HHjs/qnJOcj+0TwnAgqje3z+fPnZz13pwpERiqA8fi+Fi7FXuZKZG4BE0IIGfeUNJJlYPHixQgEAkUJoBJHNeJttARQtZUxbzGvWrUKlVqyt981hsRMFMHnZd+kC10Ev5lWi99Pr4NdBB9trIRb14b0+3vlnCVw6hrsmuDua48eIluRH10JTQQvfvH0jGf/brxoJebOaICuCdzuCkyZPwkrT1+OrZ/YguuefT8++9c78eX4g3g88SjmrGzDmnNW49aXb8blD12Kk64+AQvWzkfz5AY4HTa4nDasWNQKEYHvhcuyCuDVWw/BwramQa9xztQ6tNW78MLmhdBF0HnV4an3+IHDJqFJ15CY04g/zaiDUxM06oKLjOKPARG0iOA2SY6Hs4vg9GoHKjUZcvbPfO4uGo0iEAiMKQEcGBgo6e+I1WsAIYSQMqSkkSwDK1aswNtvv12wAJq3ZPM595cugPlWHZvbyqjzhvF4HDYRvKe2AnVa8sxfnyR72P3OEMCvi6BB11IZr6Mq7dBEcMHC5qwFE5dsWpRVuNyVDjx00wkp2Xr05hNxyPwJsOkaWqY24rhtx0BE8OEf/g8eTzya9Zqzsg3HXnJ0xu99ufNBXPHINkw5aDIqnDa4Kuy4eNPBePVr5w15Pacd1YbjVkwbdFtg1+WY3FQFEcFs0xlH7FiDvmtWodam46HWahzitOEktxN3NFWiSfaNhztDBMcaX6/QBKe7ndBFcOmll2bduvV6vfB6vZYLoPkcIgWQEELIuKekkSwDRx55JN54441BcpWP/KmJDMUIYL5tZ8xtZcwFJ2+//TZcmuCBCckK4IAIXjSyVr2GwFysCZZV2FIC+HBrNao1QeCy5YPE6L+XLkd9hQ0igpsuWZlVACdPcOPmy1Zh5w3HYWJTNaoqHThs46G468+3pwTO5rDhumd25BTA2SvbcNylx+S8z/avXI6K6gpcev9FmNiWlMyNR88eJIIrF7Xigo0HDXmdr3/nQogIjptWN0R0z1/QgkY9+Tn9cUYdIm0NyRY5xmd2lwimGl9/UAQLHDoON+YaZxOv7u7ulASaGzMXcpl7+FEACSGEEBl9ATz++OPxl7/8JW8BTB/xNpoCaG4ro54rFoth2bJlcIrgU02VqcKFG0UwW9t3/q9NE1xvan9yem0FdBHcceT0lBD1v2811kyqQdvkOhy7Yho2HjkrqwAumNmYrLqtdOC4S47BI9EHhoibs9KJ9z15VW4BXDEL6y47Nud9Lr7vArgb3ak/3/yTD2Pqgsmw2zRcfvpi/Pf72zBvRiM+eMHyzNnKaiccuobnNi0YJIC+y5ZDE8FxVY7U59Kia/iK8Zn9UJKzgSGCb4qgURN8tqUKldrgYpD0y+/3p/5nQDVm3t8CaD6HSAEkhBAy7ilpJMvAxo0b8fvf/z4vAcw04m20BFBVFqufbRZAEcHRlXac4XbgOENYThPByboGGFXAuuwb/dY5pxEOESxvdWNBU1VKiL5w7CxUOXT849sX4L1nLcXCWY0Zizsu2nQw7DYdtRNq8SX/fVnFzeV24covXzZiATzvznNQ11o35PYPPH0N6hqr0VxfCXelA3dec2RmAaxyYMVBrWhw2RE2tYfpuXoVHCJ4r0mMl5jOUL5hfG57JNlCxyaCV6fXwi6CE044IacAxmIxdHZ2wufzwe/3o6urK295U+cIKYCEEEKIQUkjWQbOOOMM/OpXvxpW5LKNeCuk/YtZAHO1nTE3ejY/v8fjwRtvvAGXJrituQqHOG14nyEvh4ngvcbXrxnbwf1zGoB5Tfj2JDdqbDp+umURXHYde65eBc+25XDZdHz8itXo2H0V7rn2aLQ2uweJ1CtfPQczJ9ehtqEak+ZNwtINS3KKW1VdFbY9cHHO+7Qtn4XjLz8u53223nIGmqY1ZfzeV7sfxpqzV6PK5cA5J80f0nfwv/+7DZom+MtT56O1zoVLF7emBPATq6dBRDDJrmPAaAlzttuJtcbntseoTv698bUmgpen1cKtJb8eTgATiWSBSCgUgtfrTd22PwQwEAggGo1SAAkhhBwYlDSSZeC8887D7t27cwpgrhFvqgCgVAJobvSc/ho8Hg8uvfRSuDTBj6fWYpquYYkIJmkaNEP6VovgiyKo12TfzN96Fw5tqUbfNatR7dDx0PGz8Z6DWjDNNN3jO585FTWmZs/funMjXBV2zD18Nh6JPoAjzl2DBUfOyylu1Y3VuPi+C4YVwBOuyC2Amz+8CS2zJuS8j2gCl9OGIw+dgnf+99LU637qtpPhsOuI/WQ7nrnrVNg1DX86fymwYw3mNVbi4kUTYBPBP43ReJ9qqkyd+4Mk+yZ+w/i6SQRfnFCFYyqT5wCzzQU2C6C61L+NYDA47JZwqQWw1Fi9BhBCCClDSh7N0rj44ouxa9eunAKYa8RbMQKYrfG0KvRQjZ4zCWBddWWyR15bPRwicIvgThFMl+Ts37WSbAbtkn0COMNhww0rpgA71uDU2Y1Y2lwFmyb47mdPS4nTbx87FzZdQ+wnV+L+G9bBYddx4vbjU8J1/BXrMGvZzJxSVtNcgwvufveIBfC0/zkFE+dOzHmfiuoKXPP17WhorcPcGQ1445mL0LH7KnzowuWYPqk29b4ObmvCyTPr0XP1KlTYNPx868FoqbDj4dbqVHbUZRLAFhHca3y90DhHeVNjJRwiuPbaazPKl2rpk357d3d36n8cssljIpFs4qwaOBd7mSW01Fi9BhBCCClDSh7N0ti+fTuee+65rFu5w41483q9BTWBziaA5sribI977bXXICJo1DUsceqoFsG3DVk5StdwvtHS5DyjJczzk2sQm90AEcFr5yVn/X7x2DZU2XXMnlI/aOvU+4NtEBHceNEKOOw6zrlt6yDh2njtBkw7eFpOKattqcGZHz8D//O9D+DsT23F2vesxbw189A6ZyLqJtbD3eSGbtPhqnFh2uLpOGT9UmzYsR7bHrgYn/zNLfhq18N4PPEoTvnAekyal1sA7U47PvmbW/BQeCdaZ7ZgxuQ6/OvZi7D52Dk4atm+9jC7v7QFdk3woeVTUOPQsfea1VgxoRrbjHOAv5teBxHBdSKYYIizUwQrDKG+sNaJr090w60JamvcBQmg2hJWWd1IJJIxG1hKAdyzZ0/Jf0esXQEIIYSUJSWPZmm8//3vx9NPP50xk5fPiLf29vaiBNDcdzC9sjjb46699tp9UzS05LSKnxkCeKQIzje+vsnYDq6xafj+lBq4NC11Du635yyBXdPw6M0nDCmeqHAm28Gcd+c5Q7dlbzwNk+ZNGnL7Yz2P4JaffQSnXHsybI7k4yvclXBPn4imVUsw/ez1WHDdhVhy+w4c+vkPwTV1AuqWzsecK8/CpJPXou6g2aie0ACbwwZnpROLT1yC6UumY/LCKTkFUNM13PXnO/B44lF8Of4gWmc0Y8GsJiyZ24yLThvcz3DOlKTkvWt2I7BjDS5fPAFLK5OVwH+dXgunCGqNNjAuEbxfBOs0DRUiOMxpwyvT61ChCarsesECqC417i0QCAxpLG1u4lzspV4DBZAQQsgBQcmjWRo33HADvva1rw0RQFWIMZzcjVQAVXGJubI423XI4oOTgqUJHp/oRpUIXjak73hJNjJWLWEWOm1YXGFHgyZocdpSAnjP0bNQadfxyEcHC+DPHtwKu03DvCPmZhSuMz92Oia07TuXd7/nXpz9yTPRMKURNocNNW1TISKYf/1F2NL96wuYOAAAIABJREFUStarYdlBmH35mUNuPz36C6x46Ba0rjscNqcNmq7hkJMOwQefuw6P9Twy6LU8En0AIoJ7//XZ1G0PBXeivrkGFQ4dH7308EHv7d7rj0G1XccD69pS847rdA39cxow1a5BRPB347OrNqR6QASrDNl+aqI7Jd4vv/zyEPlSFd3DSVp3dzeCwWAq+0sBJIQQQrJQ8miWxi233IJHHnlk0FauErR8Rry1t7cXPArO3NQ5W3FJpqvJXQlNBEucNgzMbUzJCkSwVdNwvPH1zSKY77Tht8YIuOaKfQK4uCXZPPrsE+elBOmt5y/BhMYqaJoMOvdnvs7+5JlomTkB9711D0686gTYnXZUNddhzvazcJrnJWzpfgUVLY045LPXFyWA5mvuNefBXlONplVL4HA5MHHuJFzz9atSIviFNz8HEcH9nnsHvcbP/vVOuCrsuHrrIYMEsP2Hl6LaruPJDfOAHWvw+/OWQESw2e2AyxC7DuOzc4rg/4yvT9KTxTX1tqQkVtk1XH311RkFMN8m0D09PanznKpnYCgUGrEAqtdAASSEEHJAUPJolsbtt9+OnTt3pjJ5uQoxSi2AuYpL0q+33noLIpJqAYN5TajVBC8YsrJDBEuNrz8tgpmO5BSQk6occOjJLWDPtmQj5E3HtOGg2fvm6J52VBsaJ9ZhwVELcPiWlRkF8Nzbz4Kz0gFHhQPVk1uw/MGPDRG3iuYGLP3c/wwrgG2XbcktgDvejdqFs7Gl+xWc9s6LmLJ5HRyVTkxfMh23/Pwj+Oxf74SI4KHgzqHVwSJw2HX86P4zUu/vwZuOhyaCM+e3ADvWoGv7SoixTX5Xc1Kq+w0JFBH81/gcj9AE59Y40WZsjR/U4MKyQ5eOSADV1dXVlcr8BgKB1BQPCiAhhBAioy+Ad999N+6+++6UyA1XiJF++Xy+ogWwkCbSDz74YDILpQnubUkKYJO2r2XJXSKYbjSCflQEE7TkHOCLaisgInjzosPwlRPnoLG6AjtvOA4tjckWMF//5AY4HTZ86jcfx8rNy3HwukVDpOoTv7wZLTObYauw45BPfyCruDkb63DYF27ILYDLF6Ft2xk57zP/2gtQM2/moNs2vvlDNB95KHS7juWblkFE8Ej0S0Neq7PSiSkLJmHm5DqEXroCHbuvwlknzINN11BXYcPA+1YDO9bAIYItbie+0loNt/EZ/liSjaD3qipgEVxX78IPptTAKYK1k9xorRtaCFKMAKpsoDpq4Pf7C54gYr68Xi86OzvR29tb8t8Ri5cAQggh5UjJo1ka999/P26//fbUPNfhCjFKIYCqsriQs4MXXXQRKu06qjXB/ROSLUym6ILPG7LyrAjqtaQA7hJjpNm8Jry71gURwZY5TbhwUSuWLZiAH91/BiqcNvh3XY4JjVU46vwj8HjiURx36TGYvbJtUIHHOZ/aCpvDBntVBVxTJ+YUN0ddDZbf/9ERC+CCD16M6rZpGb93xLfvhq3SCRHBHb+/dYgA6jYdn/z1Lah2V6SaXB/U1oiLNy2CTRP87T2H4sdbFsEhgt9Or8OHGlyYY3yGnxLBFNnXEqZZkrI9MLcRzTYNTS4bKmxaVvkqVt78fn8q65xeIEIBJIQQUpaUPJql8eUvfxm33norPB5P3mfx0gUw3+3ieHzf+cJ8Zw+ra86c2dA1QZNDx05DAA926LjOkJV/SnJ0WZcI/m1ksrrmNODiOheq7BoaKx2Y11iF9551CN5+/lKICK7augTumgp8ufNBo/3KBkxbPDVZaBF5ACvetQKOygoc9sWbsPiT16B65tSc4marrsTKR2/NeZ/GFYvQdunpOe+z6OYrUTV9UtbvH7f7K9BtGhyVDlz3zI5BhSAigi+8eTfOuW0rXBU2/Oe5S9BSX4mdNxyHxuoKfG39XBw2oRq6CP4xsx4nVzlwsuwbp3eS8XWf8Rn+bGoNMK8JE41zgCKCN954o6QCGAwGEQ6HEQgEis4mejwedHV1UQAJIYQcGJQ8mqXx2GOP4aijjsLjjz9e0Navuvx+f94CaD5fWKgAighm11VgeqUddxtbwJuqHTjJ2Pbtl2RbmCeMrytE8O1Jblzb4ML8ehd0LSkvT99xCjp2X4XqSkcyM3jz5sGtXuZPxpd896Ft+Wy4Gmtxwm+/gS3dr+DgW7ZnzcqpS69wYvU3Po1N3h/jmBcfxLKdH8HCG7dh1sWnY+rmEzD55KMhItCdDsx933lYctv7sPqJO3Diq0/hjI5fpX7Oktt3wDWxOevznPCbr0NE0LbtDNgcttT4ubv+fHvybGDofjyeeBQNzW5cf/4yuJw2vLTzDMybVo8dh06CzfgsvG0NmOOw4aOG9M0SwcdNQq2LYI8xTq/JJICPPfZYSQUwEAikegSqfyPZegZm20qmABJCCDmgKHk0MzEwMIB169Zh1qxZ+Nvf/lZQJq9QATQ3elZVoIUIoEPXcN2hkzCnpgIfb6oE5jXh1qZKTNb2bVkeKYItxteHahourHXituYqzKpxYdWkmmSBw/9uS/bGm5rsjffV7of3tXq55Qw0z2jBtMXTUTWxCRvf2pWSroNuugzuuTMyCtm7Arux+ut3QnQNYksWTNgqXbA3tcA2bTa0BYdBO+xoaIefALE7IJoOrW0R7BOnwV5XD81mg17hQNPKJVj0se2Y94Hz4WyozSqAJ/3xW8m+foHdWHL7DtgcNlxy34W45WcfGfSezrltK3Q9KW3/ee4SHLdiGpy6Brsx27d3biNqNQ3flX0tYFRRzXfUlroxTcWlCZY0VsKmCU499dSM2beRCKAa45ZIJNDZ2ZnqC5nPlrASwO7ubgogIYSQA4OSRzMTH/zgBzFhwgRcdNFFBWXy0gVwuMxheqNnJYD5FoBEo1G4HTq+tWEeDmuuwnvrK4B5TfjTjDpoIohIciJIldHGxGVkAOuNfoHNTjs+s3YGKu06OnZfhfhPt2Naqxu1rbVDWr04XA5UtTbhtPYfDy7MuO4C1CxsS/35jK7fYO3z92HKacdBc9hhc1dDdB3a+nPheOjnqNjlz3hpi1ZCP+ncQbc5nn8H9o8+Av3oTbC1ToGIQLPpWPSx7dj4r+8PEcCT3/hfiAhO+2+y/cwhn70eNocNJ79/PXSbnno/X+1+OFk5XWFDx+6rcMEpB8Gpa1jaXIUGm4a/GJ9fQAQvGVvonYYAfkQEc53JSuo9cxshIrh77Qy4bBoaGhpGVQCV1GXqGUgBJIQQUhaUPJoZ9Pf349prr8VXvvIVbNu2LS+RK0YAszV6LkQA77vvPlTZdbz0roU4ZWY9Tql2pDJTbk1whCRHv601tihfEMEFhgRuqrLDpQl+8K6FqLbr8L2wzWj6rGPG0umDCj6WnXYYbE77oMyfumZfsRX1hy3E6fGXseLhW1A9ayr0Cie0+Uth/+gjcD77r2QLlq++klX+Knb5oR18OPQTtua8j+2WrybbtDS3QrPbMG3rBpz0f0/vyziGfwYRwSlv7JPDhTcmzzXanfZBUtswpQFTWpIVzzvOORROXcMxU2uxrNKBq+sqMFfT8B8RbBTBalMByGpNw9luJzCvCW/Oqocmgthly+HQk1vBpRRA8xzf9CsWi8Hr9SIUCmXdEu7u7obH40FPTw/6+vpK/rti5e8/IYSQMiVXYHryySexdu1a1NbWQtd19Pf3FxzcfvnLX+KCCy5AIBAoSgBzPS5Xo+dCBHDhwoWotOv4xZZF+MDSiVhgZKYwrwk1WrKf3Q8lOb2iVZKj4BJGJlCM6/YjpqPaoeOBG9fh2ncvg9OhY6JptNsF95wPe4UdFc2NGbddp599MlyTW1A1fTJsVVXQjz8Tju/8IyVtzieTc4odz/4rtwAuWQ193Zk57+N4cDdEBM7n34L9k1+HbfpcaDYbZpx3Cja++UNs6X4FoutY/6fvDHqNdUvmQbfp2PnO51Pva8HaedA0wb++ezHWrZiKaruOpU1VuKKuAnbj3KQYn1WlCJ43PjuHCJ6Z5AbmNeHHU2vh1jXgvatweKt7kACas2+jIYCJRLJnoN/vh8/ny3jWkAJICCHkgCNXYHrhhRfw5JNP4pFHHilaAH/3u9/hrLPOGhUBzNXouRABFBG4bBp+deYifHP9HLg0wcDcRvxqWi1EBNNNmavrRDDT+HqLpiW3hDXB6oluVDt0vOuY2ZgzrQET50xA49RmPJ54FLe/eitsDhsaVy5G1cwpQ+TvlDe+D/ec6ckCjrWnwvG9N4dK26MvQ3RbTrGr2OWHtvRI6Mduzi2Az7yeFMCn/pS6zX7bU9BbJ8FW5cKy+z4MvcKJdb98fNDrPPyJO2B32rF0w9LU1JAFa+ejymXHQzcdj5aGSkyvcaLRrqNakuL8RRF835DALYb4bTG20/uNApD7J1RjossOvHcVTp5RDxHBa6+9VjIBzGeWsLlnYDQaHZQN7OrqgsfjQSKRoAASQgg5MMgnQP3kJz8pWgD//Oc/Y/PmzQgEAvD7/UUJYKbHqUrfbJKnKj3zeQ6nQ0elTcfPz1iE2OXLoYvg37PqMcWu44QqO3QR/MuQvr8aZ9n+JoIfGFmtQ506bCKosuuYPjEpjZs/vAm1LXX4atfDmLZ4GhqXL8JBH7kc7tnTB0nVmm98BnZ3FXSnA7L21OzSdu8PIE7XoNucP/DA+cQf4Nj5EhyfeQaOO74JmTQTWtsiOB7+BZzf+SecL/gy/jyx2eF46GdDbtfPvx66ywVblQtrn/vCkB6BIgKHy4GrH7sCjycexdSDpkDTBOdtWAgRweRqBzRD+NqMrOnRIjjB6KH4NaP6d6IuqSzrFfUuHNZSBbx3FU6cliyeueuuu/arAKqro6MD7e3tCAQCqeekABJCCDngyCdAjUQAX3/9dWzYsAHBYLAoAcz0OJWpySV4Xq83bwGsrrSj2q7jhU0LgPeuQoNdxxa3Ey5N4G9rwCSbDbeZsoCrJNnPbq8IJorgmEo7Ko3WJ9WVdlRXOfH+b74X1Q1uXHLfhXBWVeC0d17E/OsuRM2CZKHHGZ2/xrz3XwDN4YC+eRu01unQz78+qwDab/kqxFUF24U3QF++DlrTJIimJ7egHRXQXG5olbUQmz156clqYamohDbzINjWvxv26z4P52O/TQqgqxqOzzyTWTa/+gp0pwMVLQ1Y94vHUgJ41P9+EZpNR9tlW+BurMZDwZ1omdGM1jmtmDWlLrUdrrZ+75Xk+DeXsfULEfSYts1DbckM4GKXHVcubgXeuwpHGNXUmzdvHrL9uj8EUD2nyi53dHSgs7MTXq+XAkgI+X/2zjs6yjL74/ft0yczk94TkkAoCRBIEelFQ5FiaAGRKkTAhgWwgB0VVwWxghWxsLZlLdiIYsHV1d21/nRRXDF10gvjKn5/f8y8LzPJTDKZkOWc8HzOec6BJJNkHjJ5Ptz73HsZjN5DMAdUdwTw6NGjGD9+/EkTQLXRc2dTPoIVwPr6esgSD5PEY29hOrA2HwNseug4wka7DshwoMSqIMkTzQIR/uKRmjpyj4gL86SCybMcMWFY/8rl0Jl0MIQZkHHJee5Cj5I5CBvSDzNr30fM5NEQDAaIN+3xCJkB4sYHfCN8f/0J4jUPg887y/25ZQWyNRlhSYVIyLsB/We8heEr6lCw+ldt2ZImw5Y8GQWrf8WQRf9G+sQnEDVwFQyRORCMEe4WMRHxIL0RwgWbAgonOWJBZit4RcaIF+5GUesnGH/wcRARZjV+BL3djFnXzkBYTBjGLB2lPXeFIySJPAxEaPQUyySRu3ciiLCJCDaewwBFxCi9iNY0OwQivD0zE1ibj/52PYgIMTExJ00AQ2n+7N0zUI02u1wu/P77711+DXTGKXz5MxgMBuN0JZgDqjsCWF1djREjRsDpdGqRmK4KoPo49UAOZjRcsAL4wQcfgIgQYZZx35hkzz00KwQiVHoiVDWpNshEeNcjMceJkE6EWZ4Il5kIYbw7NUxEiEgJx7Vvb4Csl6EPM2NW88coav0ECXPPhuOMbISPyIFgsUJ67CO36O074k6tetq7yE9+CmHGBSDFANKZYI4dCWvCRCimVB/Z87fsqTNgTZgQ8P055/+ImMGXgiQdiBfAJw+AuP4+yK/94nuXMCEdQvGl4GddAE4Skf/UFhR+8xcQEaZXHEDWbZdC1sswOUxY8dBSd2sZT3rcTIT15J6aYiTC417R01iex0a7Hh8lWCAR4f4IAww8h+Orc4G1+YgyuBtocxx3SgVQXWrPQLUSmQkgg8FgMHoFwRxQ3RHApqYm5OTkoKamJiQBVB/n3eg5mMeVl5cHNQt406ZN4DlCRrwFVw+LA9bmI92qgCNCmUcAkeHAMEXEZOI0kXnZEwX8mQh3eP4sqhHARAc2v3cNJJ2kRf+KWj9B5Pg8dxNnqw3S0/86kXLdedB9J++JTyCMmw3iBcjWZCSPvAd5JcdQsPpXRGYuhSkq10fmhi+vQva8zzFg5lvoN+VF9C18Dnp7f0iGaAwseh9Dz/sOeaua/YqgKSoXtuTpsPWZBU5nBNkiIF52F+TXy9wCmD0C/OgZnnuBl4OTRBQ8czuICJO/+ytmNX8Mvd0MxaTg4mdWaxFA8hR41BJhNrkLZn7z7NlbHkE8mhIGZDgw1iiDJ0KGRQHW5uP4mjyIPIfB6eFaJbB6/647AtjdSSJqX8ny8nK0tLR0+TXQGafu1c9gMBiM05aODqbjx4/D5XJh//794Hle68X2xx9/BH24/fe//8WgQYO6JYAVFRU+jZ6DeVxFRUVQAjh37lwYdCLGDYvHrHQHfi3JhV7gYeAID3hmAiPDgUMJFq34A550cB4Rcj332qK9BCgsJgwXP7MaskHGrPoPtMbO5owkd6Tvqc997/dtehSkM4BECUpYGjLPebWdsBnCB0Nv64eogRfAGJ4NXnK3SyFOBC8awIsmCJIZHC+DE3TgBB2IOBDxkA2xCEs8Cwl5N2DAzLeQt6oJEZmLYYwYioLVvyJvZROiBq4CpxjBxaZCuvNl8FMWgUvLOlEcMmuVuy+hJGLCx3s8vQtnQzEqWPfiJe6qYo8IbyXCd+Tuk7jPK/rXnwhzzYq2p2/HWyBzhEuy3Pf/flkyFESEdQuGQJF4HDt2zKcA41QJYGNjo/aze+zYsW4LX1tO5eufwWAwGKcpHR1Mjz32GDiOA8/z4Hle+/O7774b9OH2xx9/oF+/fprIhZICLisra9fo+WQJ4MiRI2EzK1g7OwsZdj12jE6GWeIxNTkMBQZZkxVkONBP4lHkFQX8F7nbmuwlwu1eAqgzKRhcmA3iSIv+Db7zCrdAzVjuW3Bx1z6QLRIkykib8KiP9A0u/ifihm2EztrH87kFEPE+0TZ1cSSAJ8nv+7SPERT34hVIxjhwnIjhy6tORBRX1MCadLa7iCQ2FWQw+1YI5453Vwe/sgNFrZ/gnIoDbgF84WItBZxKhP8SoS9xmECcdm/yoCf691WSVdvPvydaIRHhgv4RwNp8vD0jEyZZwIPrx8KolzTpOtUCqDYbZ3cAGQwGg9FrOOmnmR8yMzNRW1vbZQFUR7x1da5vVwQwKysLDqsOL9w2GSLPYVikEfMzHPj73IHgifCzJ12JDAc+TLBAJMJnXlGtEV6pX84T9SIiCJK7Creo9ROM/3A3OEl0V8je+pz7nt/+CgiLrnLLFsfBmjDJHY1b1YS0CY/A4MgCcQI4QfF8bhESb0RsVDImTJiAyy67DI8//jg+/fRT1NbW+ghLa2srjhw5gv3792Pr1q1YuHAhsgcNhtUYDY4ELyHUgxMURGQuRva8zzUR7D/jLXCKu6pX2vbaCVndXwFelhAxZjjObfkbilo/gSAJGH/BWPfHEuEjItzkiQQe8dqnVCLMNet8hHqtTQ+ZCPFmdwr4rpFJiHMY8PimiTDqJa3au7sC2N1JImrDcZfLFdI1iM44Va99BoPBYJzGnPTTzA+hCqDaikOd19pVAQymWCQjIwM2s4LaN1ZA4jkYRR7PnJUGrM1HjF7GZofeR1rydSKGeyJbOz3SQ0QYSoQyIjg0AeQhGA2YWfcBjKnx4DKy3ZL04neQ//ID+GETwClGpE18AoJkRvLIu5Ay6m6IunDwgl6TtOjwREycOBE7duzQnlcoElNbW4uamhrU1tZi+/btOKNgxAkR5CUQJyAsYRKy5vxNSwsTz4MkGeK1u05UB9uiwCsyht670T0xhAiCcCLKuNQjwTu95O9BT3r4Jy+ZPpZmh5nncEl2NASOUL50KGan2XFmdgweuXYCjHoJLpdLq/p2Op0h3wPsrgDW19czAWQwGAxG7+Kkn2Z+UAWwKyKnpn6dTmdIqeNgBLC+vh4JCQkw6kQ0l5bAondH6aqW5wBr83Ht8DjYBQ6/pts1cSlPtUFPhOs8Ua4/EeFrj/RcS4T3vKSQNxkw4LpVEEwmiLc8DVIMkPd+DS45E4IxAkMWfouB574Ljpcg6MLBCzoQEcx6BxYvXozvv/9ea4StFr90VwDbvn3r1q3IGTLcc59QAHEiHH1mI2fxj9BZMyAZY0GiBPHCm93FIf2GgiwOCHodpv74OkjgIRMhzUv+FCJUe+SvhQgWjnB9G5F+NMoIs8Dj+OpcxJsVXDk0BtEGCZuW5eL+q8bCqBfR3NyM5uZmlJWVaSP/uprKPRmNpOvr61FdXc0EkMFgMBi9h5N+mvkhMzMTdXV1QQugd6PnroqjuiorKzsUwIaGBpSXl8Nut0PgOTQdWIXwMB3iTTKwNh9Ym4/fVufCxHN4LMroIy8b7XoIRDiTTvQGfNYT5XqJCNu8UsG8LEFYexvEtVvAWcLBxSRDsiZg+IoaDD3/Bxgjh7kjcESIjUrCrl272kVBe1IA1VVRUYHi4gUg4sDxMnhBB72tPxRLMlLHPgCSZAjLrgU/YQ64fkMhRMYi9pxx4IkQSYQKIgzx/Lk/cYgnDseJMI4IfSTeR6KPp9uRKvEoznAAa/OxJjsayWYZHBH+b+95uG3NCOgVET/++COamppQXl6OY8eOadHAtqPaeloA6+rqmAAyGAwGo3dx0k8zP3QlAti20XNXxDFYAVTvFlZWVsJsdk+eKHtlGSJsehhFHr+vztMkcHG/cCRKAn7zEpjHo4wgItjpRIsTeCKABiJ8QoTVngghGS1Q3qyCMGm+OwVsTULeygZknP0MeNEIjpegSHo888wzAdPglZWVmgCqEylOtgB6R7sWLFh4ouiEEzFo9kdIn/gESJTB5YwBGS0Qb31Oa/nyLyJMJ4KFCIfJ3QImighZnmjo3xOtPgL9YqwZOo5D3YphwNp8/GVqXxhEHg6jhObSElx5Xg5EgcOnn36qjWZTvz9VCL1HtXW0TkYfwbq6OjidTiaADAaDweg9nPTTzA9ZWVmorKxEWVlZpynZto2euyOATqfTr/yp6cSGhgZIkgSB5/DZE/MQadNDETi8N6u/JoAtK4fByPN4xCsKGCfyWGZRECfymOAlgH8QYRERTB4pmueRQGHzo6CIWBARhi93IiZrjRb1yxma0+Hz+F8LoLp+/PFH9M0YAOJEiIodA889iNQxO05UFRvMUIjwPhEWe57n39rc+xOIcJHFt5L693Q70iQB56batD2uXTEMHBFy+kWgubQExWf3BRHh7bffbieAqtRVV1cHlRI+GQLovXdMABkMBoPRKzjpp5kfcnNz8Z///KdDAQzU6FmNCJ4sAVQLS9SqYkmSYNCJePmOqdArAuxmBRdmRWtygrX5WJMVBYfAoTnNjgNxZq2Z8eeJVshE2OwlPr8ToYjc0zA+IcJ8NRIoCMgofB6W+LHgBB1iY+Lxww8/dPo8TpUAqmvz5s1aWjjjrD2IGLgaHLln/b5HhPM86e5Srz04RoRoz5ziM3SCjwDujDLCyHNoWDlM29+GlcMgcIQZo1LRXFqC3AHRICI8++yzfgXQ5XL5pITr6uoCCt7JFsCu9MAMllP7G4DBYDAYpyUn/TTzw6hRo/Dvf/87YDsXNSXrr9FzqAJYVVXVTgBramq0O2Tq24gIBkXEugVDQETYcP4whCkCfvNKAx9fnQu7JOJKux4FOgFTjSeiWk9HmyB77gCqAvQbERZ40qOvEuEiz/1AUR8NTlCwcuXKoJ+HGulS+yD+rwXQ5XLhz3/+s5YSlnkFVo/cTvKI4Ltez/04EQYRIVUS8HKsGTIRqj0TVer62GDhOVw+xFewHxmfCoPIY+TgWDSXliDC5q6C3r59uybzgb43dVRboJTwyWgkXVNTwwSQwWAwGL2Lk36a+WHixIn48ssv/Qqg2mQ3UKNnNS3cXQH0Lizx/jh3g2tCapwFVpO7HYxB4vHylAwfSXnmrDQIRNBzhH2xZp+o1o0OPXQc4UAbEbrCEx3bSoRLPKlTk9GIw4cPd0kAy8vLUVZWpvVE/F8LYF1dHd544w3oiNCXCF8QIYPcLW8+93rOIMJ4Ith5Dj+mhOGPdDv6SAKWedLAiy0KonSSNvdXXTkRRlhNMuKjLah4dbmWZr7ttts6FUA1yqfuU9uZvydLANVei0wAGQwGg9ErOOmnmR+mTZuGzz77rJ0Atr2PFyg1HEojaO/K2baFJd5LkiUYbQYQEbLS3XfQRmbHYkyc2UdSsDYfCUYRPBFa0uw+AvhHuh1rrQoMnHvihbcQPUIneuSNIkK4RwrffffdoJ+HOglF/XNbyelJAWxtbcWgQYNAnjuN+4lg80T5jrZ5rlOJYOI4/NNr2sddEQZECgL2x5khEeHguZk+e/qv+VkQOMI9l46C2Sjjze0zoFMEcDyHu+66KygBdLncKWH1Z6W2tlZL+TY3N4ccNVWX0+lEXV0dE0AGg8Fg9B5O+mnmh6KiInz00Uft0q9q1Mb7bSdbANW7hf7uAzY2NsJgNGLA2H4gIswYm4bm0hIc2jkHAkf4ekF2m0iVATqOcJXN4COAqgSutCrQc4TX29yHM3gEMMojUEWelPB0MdGOAAAgAElEQVS8uXM7nFaiiqua4mxsbNQmY3R07+1kCeDBgwchE8FI7opnhdxTT5Z7npd3tHO8R/4+bVPxW5ZqA0fuKSnnedq+eK9F/SKRHmfFV08vAMcRNi3PRXi0BcQRHn30UZ8pHMEsNSVcVVWF1tZWJoAMBoPBYPjjpJ9mfli4cCFKS0t9BFBt9NyR/KlRwlAEUO2fpxaWBHp8REQEJqwcA4HnsK54CJpLS9BcWoL0+DCtT526bIqElQMjIRHh9TizXwm8PEwHhQgPe+ToPCIkkLsx8iKP+M0mwvNEiCZCmCThlltu8Su+5eXlqKysREVFBZxOp9ZKp7N7b90VwMOHD2PUGWdAJMJccvc2jPJIbHKbqN8xTzTQxvtG/ryrfqMFDjLHtUv9Hl0yFCJH2HtrIRreXglB4JAca8HA8f1BRHjnnXe6LIBqNNDpdKK8vFyrIu+OAKr/kXC5XD3y+jjFvwIYDAaDcTrSIydaG5YtW4Y33nhDE75A9/FOpgCq8hfobqG6MjMzUTAnF5LI48rzcjQBfHnrVIgc4fvzBgNr8/H1gixw5J4SsnJABIwc4d/JYe2EBxkO3BNhgESEFeRuCfOklzDtJ0IcEaxEuMWz9ESINBmxefNm1NfX+xTFqCnyuro61NTUoLy8HK2trV1qhRKsAH711VcYN2YMFHKPtvuLJ20teuT1BXL39fvB81x+IEIUR0iVePyQ4n8vrrLpoOMI4TqpXfRv1aBoJIQbtT2PjXD3V1x4x1wQEX755ZeQBFBd6s9Od6uAmQAyGAwGo9fRIydaG1avXo19+/Zpo90C3cfrSAA7ixS2fYw6Q7gzcZw6dSr6j3b3nRuQatdkpLm0BOlxVszsYwfW5uPyIdFItehOpIPDDUgSBdT0sfkVn9c87WI4IlT5iZqp4hdFhC1E2ETu1jFWUcTUKVPw4Ycfoq6uTrv3p8pfVVUV6uvr0dLS4nPvrbPpGIEEsLW1FQ888AD6p6ZCJEIuEXYTYQq529fkEOEjr+89lwiFRHicCEaOMMkgoT7AHjzuqZC+7YxESDyHFq/WL/9eNBgiz2HPDWdp+z08MxJEhC2fXg9e4OFy+Y5h644EVlZWhjwPWK1OZwLIYDAYjF5Dj5xobbjsssuwd+9eLRrT2Yze7gpgdXW1duh39rEXX3wxYjKiwYvuauB/P79IE5J3758Fkefw0ewByIkwYkX/KE1gfi3JRYJeRo4ioblNUYi6EiR3Lzwz59smRl1OIlzlEUE7EVYSYTu5q2v1njV37ly8/fbbKCsr04S2oaFBi562trZq0zGcTmdACfQWwNraWsybNw8ZaWkw8zz0RFhChB1EGO5JU2cRYR+dGHWnric87+eJcHO4AcfT/T/31zxFH7cVJOL4mjwYRR47x6Vo+zc1OQwZ8VYf4T5nZAqII1z9+hWQDfJJEcDGxhNzodWG4qEK4K+//tojr49T/TuAwWAwGKchPXKitWHjxo147rnnUFZWhqqqqi6lctXCh2AFUO31p94B7Ozj7733XujMOkg6CUa9hK0XnekjJaOHxKK/XY9wnYxHJ6T6pDBrVgxDuCRipF5EaxsJbEqzQeYI7ydYcLVdB4kII4lQ40cE64nwJyLEk7vQQiJ3tfBNRMj2RBEtPI+0+HhMnToVt956Kw4ePKjdbVRTwmq62DvSVVZWhr179+LCCy9Efl4eYs1uMVM8Eb5biVBMhAhyT+44h9x9/dqKH4jwDBGsnPsu4IYwnV/xQ4YD78RbIHOEi7JOCPOEBCumJocBa/PxxvR+kHkOh3bO0fa56cAqRNj0kHQiVj60BIpROWkCqFYRNza6G2nX1NR0KSWs/keCCSCDwWAweg09cqK1YdOmTRgyZAjefvvtLkX/uiqA3ncLnU5nUAJ48OBBEBF4gceAMf0wINXhI4BH9y2BQeQhcoQvi7Pa3WP7ZclQ2CUeZ+plNHlJ4J3hBtgETouQfZZoxSBFgJEjXE7uytm2gnXck34lj4wpROhD7vYrG4mwgQhjiRDpkUKBCEaOg10UYeI4WHkeUTodwmUZVkFwTyDxROz6knsqyY1EWEOE0R4BJCIMJMKdRCj38z2BCN8SIZtzi+lVNh3OMkgYpRf9yt/+ODNkjrC8f4TPPt1SkIAksw4tq4Yj1ihrUz/UtX/bdMgiD0eiAzOumgJBEuBy+c7h7a4AulzuvoBq38lgU8JMABkMBoPR6+iRE80Ll8uF9PR0FBQU4Oeffw767l9bAeysYERtmaIKZrAC+H//938QZQFEhOveugoCz+HjR+b4yMnyc9xVqf4EEGvzUb50KCJlEVmygCrP1Is8RUCxRWlXEftQpBE2noOd53CrHxG8xCN9v5G7p+BGIgwhdyGG7InU9Sf3FI4iIpzvSR1L5L6ft5YIJURYRu5pJNOJcAa5q3etHnG0EWGG520pAaQPRDhChDGezz3JKOFbT9HLY1FGOES+nfw9HW2CRIQLB0a226M3p2fCKPEoGRQNu9HdcNt7j+dMyIAk8bDF2pA1aSCI6KQIoL8ikmPHjmn/WWhoaOg0GlhRUYGmpiYmgAwGg8HoPfTIiebh+PHjmDNnDhITE7FlyxZUVFSEJIBqO49A7/fX68/pdAZ1B/DIkSOQdBKICPcd+RNi+0Th/Cn9feTkornZEDhCf7sergtz/Upgw8phSDJKiBV5fJ1khZ3n8ES0yW+UrCnNjpvDDTBxBBvnjsi1eKRroEfi2sqYiwifEuFRIlxJ7qbLWUSIJXelsdQmcmgjQioRRngkcQu57/T97JXefYEIYX6+1vt04i5ggV7Ee/EWn+//aEoYOCL85BHCP9LtuMGhh0SE63Pj/O6Pc3mO1hB739ZpPvv708tLIAo8xi0bDXO4GZZIC4jjekwAvaODnd2dZALIYDAYjF5Jj5xoHlpbW7Fq1SrccccduPXWW7XL+CdTAAPNEa6pqQlKAGtrazUxeeDo3Vjz+ArIIo+fXl6iCcqYoXE4Kz8JVr2IlQOi/AoO1ubjt9W5GBFtAkfuIokjAVqjqKs5zY57IgyIE3noOUIeuZsu+ysY6WwZyLdaN5h11BMRrCb33cRLiRDHcxCIMMUo4YMES8DvPVbkcb1Dj4Y+Nkw3yTDwhGfOSgu4Nz8tHgKeIwzPjPCRv+bSElyzJBe2cDPW/Xkt9Bb3HGCbzQaXy12w0h0B7OwOoffdyUDtdNTei//973975HVyin8FMBgMBuN0JJgD6rrrrkNsbCxMJhNGjx6NL7/8sksH3OOPP47rr78elZWVIQugv8hhR3OEgxXAxsZGHwHc49oFW7gZ6xed6AnYJy4MGxcPw+v3TIcicHhkfGpA0cHafIyLs0AkQolVaVcc4m8dT7djf5wZU4zuSKSBc6dt7/OKDHa2dJ4IYVcE8EvP8zZ7IojxHqn7uRNxRYYD8y0K0kQeCSKPSJ2Irxf4T49jbT5aVg3HILsRIk+YPS7NR/4qX1sOi1HG7Otn4qp9l0IxyFAMMvLy8jQBDHWGcTACqKaE1SsE/trpMAFkMBgMRq+js8Pp9ttvR2JiIr766iu4XC5s2LABcXFxaGlpCfqAe+aZZ7Bx48aQBdBf6rizOcJdEkCBB8dxuOurW7HHtQuLts6DXhHx876laC4tQUSYATs3jkdzaQluWpkPiedQOqt/QOGZmhyGFIuMMIlHisTj4w4iad7rzzEmEBH2RJsw26zAzHOQiBDNuSuIryT3mLljfmROJsI/O5C9I0R4kNwVv/3IXc3LeQQwQeDw90Qr/gjQ0qXt+jXdjrkmGXqOMDHegl9L/KfFsTYfx9fkYXqKDQ6jgkWF/ZCdHu4jgDetyofZosfu1odx9WuXQzHI4AUes2bNOikCWFdXF3QVsdpOp+2ElbKyMrS0tDABZDAYDEbvobPDKSUlBdu3b9f+/vvvvyMiIgK7d+8O+oB76aWXcNlll6GysjLgTN6uCqA66itQdXBNTQ0qKiqC+vwGhw2KQcayexdhj2uXJwpowkVzBqO5tAQGRcSb22do0lI8MR0Gkce/5vuPeqVaFFyfF49jJbmYEH8iGlgXoGGyui4KUzBAEXwig/9IsuLeSCMWWBSkSTxET9rWxBEiOEI8R0jzpJzjyT2WrR8RUjhCjOeOoeIRPSvPoUAv4gqbDi/GmlHdx4bzrQpG6PxX9Ppb78Zb0EcWoPO0g2k73s17/bEmD6sHRcMoCfj08Xm446IzERNu0Pbx531LYdSJmH39TOxx7cI1+939/4gIl1xyCVwuF2pqarotgF1JIXtPWGlqamICyGAwGIzeSUcHU0NDAziOw6FDh3zePmnSJKxbty7oA+61117DmjVrUFVVdVIEUO3111FhSFcEMCY5CUSEAWMyNQFc8/gKSCKPTx+fC44jfPvceT6RqzFD4mBTBHy7MLud+FhlAS9NydD+/uq0vohUBFh4DvdFGvHfAJG2sXoR89pUDrddv6fbcSQlDAfiLXgq2oRtEQbc4HDfm5tpknGFTYdr7HpsCTfgoUgjXow149NEa0D5vCXcgDRZ6FT8vk8Ow3SzDIkIk5OsqF4+FBwR/j53YEAB3DgsDjqRx6t3nYPm0hI8v2UyLEZZ28OSWVmwhZuxu/Vh7HHt0iKAnCRg586dmgDW1tb+zwRQTQmrE1bU1HBraysTQAaDwWD0Hjo6mH7++WdwHIdvv/3W5+1z587FihUrgj7gDhw4gOXLl3dLANXUsdq+o7Nq4tra2qAFMC8vT+sF+HDFdk0C4zNikJHornite+sCHwFsfGclcjOjYFdEfL3ghAS2rBwGniMcXjTYNxW6OhcbcmJhFnjEijweiTLi1zYimCa57+AFG43zXjwRvg8wm7ijtSfahAg/LV3UdTg5DEusOohE6Bemw+fzBmnPKdYk45aCBL+Rvw05sdAJHJ69+Wxtzz5+ZA5EgUfjOys9f+Zw2d412n4XXTdDq8hWrxx0VwC7k0Jubm5GRUUFysrK0NzcjN9++y00w+uEU/07gMFgMBinIR0dTCcrAvjRRx9h0aJFqKqqQnV1dZcFUL072LbX38kSwGXLlkEw6CAbZKy473xNSLb+6yZ3kYRBale5qkpgwcBoWGQBf5vjjoS9MrUvJJ7D8TV5fqNix0pysaJ/JMwCj3CBw5ZwA6o90bkIgcOTAVrHdLaICD8GUbzRdr2fYIGBI5+3/ZFux8EEC2aYFQhESLMoeHVa33bPZWKyDTNSbe3u/JUMioJe5LH31kKf/frlr0tBRPjXU8XITg9H+rBUba+fOrYTjgS7W8QVWSvEOJUC6HK5G0erY/i6cu+1K5za3wAMBoPBOC3p7HDydwcwMjKyS3cAP/vsM8yZMwfV1dUhC6B65y/Yx9fW1mqzXztbTz75JESTHqbUeCRlJ2pSsse1C0nZCdDJAn548Xy/EthcWoKpI5KhCBxenpKBjcNikWpROqwSVmcJrx8ai3BZgEiEmRYFeo7a9dwLZh1Ps4GI8FMIAviTp6ffsTQbfk4Jwx3hBqRIPGSOkBNhxMFzMwM+h8uHxmCAQ+9T7TslOQxGWcAb26a326emA6sgSzzOGZkCg17Sqq73uHZhc+kGCJIAXq/A6LBpkzqcTifq6upCFrju3iFsbW3VqoPr6+tDM7xOONW/AxgMBoNxGtLZ4XTHHXcgKSkJX375JVpbW7Fx40bEx8d3KRry9ddfY8aMGSELYEVFBcrLy9v1+jtZAlhVVQXBoMOA9UvAizy2fLJZE5OxS0dClnhMGJaIpgOrAkrgRXOyIPEc9AKPwiRrpwLovV6Z2he5EQYoHMHIEeZZFTwTY9Iig52tXz0CeLSLAng83Y6PEywgIkTw7kKSKJ2IlQMiUb1saKff98PjUhFtkIC1+Thy/hBk2vWwG2X848n5Afcpyu6+r7h0+3k+op1flAtBFiEYdcjKzkZNTY32b95dAexOBFGNAB47doylgBkMBoPRewjmgNq0aROio6NhNBpD6gN4+PBhnH322aiurg5qPJv3amhoQHl5OcrLy4OWv8ZG92i4YAWwtrYWnChgwFWLEdYvGWcWF2hikjszB8mDE6HXSbilpCCg2DSXluDRa8eDI8LgcAOcy3O6JIGHZg9wTyMZnYyCKCNsEg+OCKkSjyUWBQ9GGnEowYIGP1LY5BHA8tTAwng83Y4fU8KwL9aMGx16TDBKMPIcJM7dQzA/yogvigd16Xt+Z2YmTBKPfVP7wijxGJBsQ8WrywLuT9kryxBmUmCJNPvI344f7wQv8og/ZxR4nYyrr74aLpd7ikdZWRmqqqo6HdfW0wLocrmYADIYDAaj99AjJ1obfvnlF4wbNy7o+bze8ldVVYWysrIuRw6DFUD1XiHHcYgtHIFRL2wFL/K49/BW7HHtwsDx/ZE3aziW33c+JJHHK56K1kDLZtFB5jk4dCL2T+8XtEw9PC4FYYrg87Yvi7Nw5dAYDI80Ilonaq1XLDyHfrKAcQYJ880yVprdhROXhOmw0a7H5TYdVlgUTDdJyNWJiBNPtI+xChxSTDLOSbHhkfGpaFk5DKlWHTYN9z/CraP17cJsberJBdP7d7gvje+swqS8RCiSgLyi4T4COPWys2GMsSPz0gUgnsOPP/6oCVhVVZUWCWxpaemywHU3hdzc3Izy8nImgAwGg8HoXfTIidYGp9OJM844o8sCqN77q6ysDEkAy8rKOvwY7xnC4eHhEAw6zGt+H6b4CExcORZ7XLuQnt8HYxePwh7XLoxaUACTXsI/dxcHFB2rScazN5+NeRPTIfEczusXgZoVwzqVqSuHxqCvTd/px323MBuPTUjFFUNiUNTHjjFxFmTZdeCIkGFV0N+mQ7ZDj4JoEwqTwrAkMwK3FCTg1Wl90bTS//dREGvG4szwLsnfm9MzEWuUoBc43HXpyA7lr7m0BJfNHwq9TkJGQTqyJg7U5O/BX+6BpIgYvv0qJM4aDyLyEbDq6mrU1dVpKeHGxsZTJoC///57j7w+TvXvAAaDwWCchvTIidaG5uZmDB06FE6nM+jpHN69/kKpHu5MANUZwtXV1WhoaMDixYvBKzLG79+BEXtuhiAK2Pbd7UgenIjCtRM1YekzJBlxESYcfsF/UYgs8fjg4SI0l5bgze0zEGXVwSwLeGhsCn5f7b8yGGvzMT/dgTEJXbs7qK7ypUNBRKgNQjT9rZlpDpydGNzX/mnxEMxMc0DmOUwflQKrScY9l43qUP62rRsNWRJw+QtrMWbxSKTn99H2s3DtJBiibCh2HYJtSF+/AlhfX++TEq6trQ06Jez9+FBWU1MTKioqmAAyGAwGo3fRIydaG3777TcMHDgw6PFsqrypvf5CKR5RG/kGkr+2M4Q//vhjcKKItOUzUOw6BGufeOTNGoaEgXGYetnZmrA80fwgohMj0DcpTBsVp66j+5aAiHzksPGdlbh0/mAYJQHpNj3+MrUv/vDTImZsnAXFfbsWhVPXz0uGgIhQf0FoArh6UBSGRxo7/Bjn8hxcNiQGMs+hT6wF7z/kltx+KXasmZ0VUP4e3zQRksjj/LuKsce1C5MvnoSkrATsce3C3d9sgSAJGPHkjSgqfwOcwEOn0/kImFr4430nr7KyElVVVT7j2pgAMhgMBoPRBXrkRPNDZmZmUNM5VHHz7vV3MgWwoxnCRATRbMC8pvcx6b2dECQB5nATzrliss+dtUecO+CItmBAqsNHAt/cPgMcR2h4e2X7Aoi/LsO0kcnQiTwGOAz4c2G6T0Qwy6HH5UNiQhK4I+cPBhGhceXwkB6/KTcO/Ww6v+/7ZclQrBsaA0XgEG3TY9fV432e19jhiZg+OtWv/D2xeRIkkUfRddO1vZt+5RTE9YvDHtcuDD47C9aMRBS7DiF3x3oIBh1Gjx7doQC6XO5JHer1gM5Swt0VwMZGdxsiJoAMBoPB6FX0yInmh2AEUL2T11b2QqkeVgWwreR1NEOYJAWCTsHIZ25FsesQYibkgRd4TL9yio8A7nHtws6q7QiPDkN6gk2L+D2wfqzPqDN/64cXz8fUM5NhkATEGGXcPiIRVctzkBKmx5Yz2k/VCGb9+zy3ADaFKIB3j0xCgknW/v7HmjwcPLc/ZmeEQ+QIsQ4Dtq3zn+Y9b3Im8gZGtXv7QxvGQRJ5zLp6ms++FV07HTFpMVj3/FqIsojJn+1BsesQwrLSQUR48MEHOxVAdQWTEu7o8UwAGQwGg3Ha0iMnmh8yMzM7nM6h3snz1+uvq8UjgQRQHSMXaIawJEkgjkP4Gdkodh3CnNpScDyHcUtHtRPAPa5deKT2PkQnhSM23IjPn5yPa5YMQ1K0udOCiObSElS9vhwl5w5CuEmGwBFMEo+LsqNDkrjvFmaDiNCyKjQBfHxCH0QaZXyzIBub8+KRYJIhCxyy08Lxwm2TO3wely8cir5JNp9mz5tX5EESeSy4dU67PZuzeSbCExwwO0xIOW8Kil2HUPi3J8GJAkiSUVVV5SNg6pWBjoo01J8bfynh7gqgGjF2uVw4fvx4j7w2TvXvAAaDwWCchvTIieYHVQD9tWZR7+T5S8uGKoBqdEj9fG3vFfpbM2fOBBGBE3gtMiXbLRBEATe+f41fCXyi+UGkDUuGUS/hzOwYZKdHBCWA3mvf1mnQywKMkgCR5zA2wYp7RiXhi+KsgCPlvNfXC7JARGgtye2S+DWsHIZXp/XFrD52GEUeAkeIDzei5NxBOLpvSVDf+5bVZyAhyi29NW9cgPmT+kGRRax5cqXf/Zpz/SxIighDlA3zWj9EsesQkuedBU4SQILYTsA6E8C2KeGmpqYuP54JIIPBYDBOO3rkRPNDRwJYXV3dYaPnrlQP+xNA73YvHT3m8OHDIFEE7whH0uyJKHYdgj0nExzHwR5rw86qe/1KzR7XLoxedCaICEP7RqDxncATQwItk0HGvjunYu+thTg7PxHRNj1EjmCUeIyMNWNDTiyempSGv88dhLo2xR5fFA9yV89e6F8Af1udhyPnD8Gb0zNxz6gkLMqMQFqYHhwRTLKAhEgTdLKAw88HHncXaD24fiwibXp88+xCDOrjgNmixw0Hrw64T+dcMRmiLKLw4ydQ7DqEGf/+izv6ZwmDoighCaAqgf5Swt0VwPr6elRXVzMBZDAYDEbvokdOND8EEsCO7uSpK9jqYX8CWF9fHzC17O8xJCuQRheCEwRM+2ovIkYMRvK8Qhgj7RhSmIWnju0MKDex/WKgyALG5MQHbBMTaOlkAQcfLGqXJn5g/VjMHNMHGfFhCDcpUAQORARF4BBrlDHAYUB2uAFEhIkJVkxKtGJsvAU5kUb0sepgU0RwnibQZkVEbJgeuf2jcNHcbLx7/yw0l5bg/YeKoMhCl+WvubQEz958Now6EUadhIR+MXioYnvA/dny6fUQZRGCTkGx6xCKXYeQvuJcCNExIEnC+eef307A1CsDwQpb25QwE0AGg8FgMPzQIyeaH7Kzs1FRUeFTmdvZnbyTIYAVFRU+7V46e0xsbCz4pDSISalInDkesYUjED95FKZ+sReSXsa510wPKDhpuakYNm0IIhMcMBskPLF5Uofzg70Xz3EdNpj2Xl89vQBP33Q2blqZjwuLBqGwIAlEhKkjkjFtZAqKxvXB0mmZuGLhUGxbNwpvbp+BqteXB/x8/9g9HzzPdVn+ft63FFPPTIZeEXH2mgkB92WPaxceOHo3wqKt4HgO1n4pKHYdwjnfvABOFKCctwYkyX7v6lVUVLRL6wYTDVT/Y+EvLdyVVVdXB6fTyQSQwWAwGL2LHjnR/JCXl4effvpJE8Bg7uR1RwDVIpCuzBBuaGjAK6+8AuJ56K+/D5woIGLEYEQWDEGx65C7QbQk4MJHV/iVnIRB8Zhy6VnY3fowJl04DookYPzwBHz19IIORarsr8va9Q/synrvgXNB5L/9TDDr388vAhF1KIneq+nAKuzcOB5WkwyjUQYRdSh/j9Xdj5QhyTAnRiFj9RzYBmeg2HUI8dPHQExIgTytGCQIfgUsFAFUJVD9GXA6nSHPEvYWwD/++KNHXhun9jcAg8FgME5LeuRE88Po0aPx/fffa2lZ9WAORsyC6R/o795gsILZNmpIsgJlyaUQs/Pcs3czkrWUZdb1KyFIAq7ad2n7FHBGDGZuONH2ZOu/bkJceiQkkce6BUNR/uoy/xG4J+eDiFD5WnAC1na9e/8sdxuYIKON7QT0FbeAdiaqzaUlOHDfLGSnh0OniCi8aCJu/8eN4EU+oPw90fQgsicOhN5mwayy/UhdNBXhBVmY8Ob94CQRxgf/AtIZUFBQcFIFUF1qFDjYxtFtV21tLWpqapgAMhgMBqN30SMnmh8mTZqEL774QovKdaWxc0ftYwJ9fFlZmSabXRXAKVOmgAtzwLLvnyAiyHarJoDFrkNIX1UEURZxzf4rfGQnqk8k5lw/q50ErXx4Kax2I8wGGTevKmgnem9unwGuGwJ34D63AIby2ObSEtS/tRJEhPceODfgx3z48GxMzE+CKPLoW5CG+47ciT2uXdj23e0gIuxufbjd836y+SHkzsyBYjbgnG+eR7HrEOImj0TMpHwYk2MhFoyHYfMOkKLDL7/84lfAysvL0dzcHLIAqingQFXCTAAZDAaDcVrSIyeaH8455xx89tlnKCsrC/pOXigC6J1aDuZ+YdulRoxIVmDc8gjEs84F8Tymf/eSjwSmLpoKURGx8dV1mvBEJDlQfOtsv5Gw3a0Po+i66bBY9TAZJFy1KEdL+e69tRCyFFoRRnNpCd7eMbNbAthcWgJB4LBv67R2qd59d07DqKHxEAUOydmJuOXjTT7P6/7/3AUialf88UTTgxg+PQeKSYfCT3dr+xaeOwiSxQTBbILlnX9DyBjUbv7vyRTAsrIytLS0+KSE6+rqgk4J19TUoLa2lgkgg8FgMHoXPXKi+WH27NnYunUrjh492qWonCqA/trH+Lv357Ox39QAACAASURBVN3upby8PCQBrK+vh6woEPpmwfLGt+AkEeH5WZjX8oGPBKatmAlRFnDJ0yXY49oFR4IdC2+f2+F9uN2tD2PeTUVwRFkh8BymnZmCNbOzYDJIIcubGkHsjgDqFAG7b5iE5lL3tJJbLzwDiTEWKJKAvmek4bZPr/f7fB6u2A4iwvbDd5xokF1zHwaO7Q/FYtD6KarLlBILIoLhpodgevivIEHEtm3belwA1b+rVcLV1dVBpYSZADIYDAajV9IjJ5ofxo4di6SkJHz99dddFsC6urpOBdDfJJHuCODTTz8NEkWY7n8RJIgQdDKyNq30kZli1yEMWL8EgiSg+NbZcMTbcd7WeR0KoPda/8pl6JOTDFHgwfMcLpg5EK/edQ7q3rqgS/L2xrbp4LjuCaDFKGPexAycMTgOPMchzG7EuGWjOmzrosoeEeHOL27BHtcu7PhhK+L7x0HvsOCc/3vRZ6+Kyt+AoFPAJfZB2IdlEPPGgHj/xR+BBK4r69ixY34f39raqvWe7Cwl7HQ6UVdXxwSQwWAwGL2LHjnR2nDfffdBURQ89thjXb6XF4wAqpNE2qaWQxVA9THEcRAG5oCzhUMcNw2cKGLcq9vbSWD+zusg6STIegmL7pwftACqa+6Ns6AYFcT1jYFOEaFXREzMT8Lta0fg4INFqH2zYyEMRQB/ePF8PHdLIS6aOxhpiTZwHEGvlzH47Cxsemd90N/7Y/UPgIhwxz9uwg3vXQ2T3QRrnwQUVb3ls0fzWz9E9IQ88IoEw87XYHrkdZAgYPz48T0ugP4ifcGmhL0FsKc41b8DGAwGg3Ea0mOnmocjR47AbDbj3HPPxcsvvxyyAHr3D2y7Ak0SKS8v71IVcFsBnDRpEkiUQGYr5LkrIE2ZB9Gkx7Sv9raTwLM+egyiIiE6PQp3fnlLlwTw3GvOQURyhPvuXPODKNm5DFkTB8IRbYUk8hAEDhlJdhSNz8B1y3LxyLUTsH/bdPxj93z85y9L8Nc7p4H3EsCmA6tQ+dpyfP/nRfho52y8cNtk3HPZKFw0Jxujh8bBYdWBiGAyuaVz4sqxMDqMmH9LUZfl9fEGtwAWrp0IQRIQP3WkNuLNe/W/fBF4nbtljOW9/0DIygXxvNZi5X8tgMGmhKurq1FfX88EkMFgMBi9ix471bwoLy/HunXr8Nxzz4VUmNGRAHY0SSQUAfSOGn7xxRcgIhARhAE57rRlvywYEqIx6+jr7STHEB8NXuAhKiKW71jU4dQQ7zXt8kJEZ0T7b6PS/CDWv3IZCi+aiH4jMxCdEoEwuxEGvQSe57Tvj4ggCByENm+TJQFmsw6OaCsSB8Yjd2YOFt4+F/f8320+Xyc8KRyzN83osgBu//4O99fiCMPuvrzdnhS7DiHvwWvAyxLk4lUgoxnG2x8DSTJSU9M7lLtgBK6j1drairKysk4LPtSUsL+WM6oA/vrrrz32+jhlL34Gg8FgnL6EcmD985//RGFhIWJiYsBxHN5+++1OH3P11VfjySefDCktq6bq2r69s0rfioqKkAVQvVOYkpruFhxFB+v7R2EpPQIhOhZhg9Ixu/ptH9ExpyYi+/pVyL6+BJJOQr8zM3D3N1s6lajCiyYibkB8l+Vrd+vDuP8/d2HFg4tBRNjw6jpseHUdNpduwJ1f3IJHau8L+nNFpUVhxvqpQX/8U8d2YtXDS6EYFYiyiHFv3OdX/kb9+XZwkgjdRZuhW3MtuIhocI5IEBH27t2rzWs+lQLYUUpYvVPKBJDBYDAYvYpQDqxvvvkGO3fuxKeffgqe54MSwBtvvBE7d+7slgB6p3jVqGBNTU3Ax4UqgLW1tdqdwmeffdYtgIII06P7EfZhGSz7v4HgCEf48IGYU3NAkx1L3xQMWL8Exa5DmP79SwjLTIYoCyi6bgYeq7s/oExNWjUOidmJXRZAdV392uXghcDNmINZMf1iMW1dYVAfu+WTzUjL7QNJLyNj9VwQEWYc/ks7+Rvzl7vckb+FqxH2YRnk8TPceykrsIfHwuVyaXteU1PTTtT+lwIYKCXMBJDBYDAYvZLuHl7BRgBvv/127NixI6S0bFsBbNvupSMB7EgQAwlgZWWlJqpOpxOR0YkgUYSQORjWgz+7JfDVLyDaHHDkDMDsKnckMCwrHX0vmucjQcN3rIcuzARLpAWrHl6K3S3tGyZPuGAskocknVIBjBsQj8kXT+o03XvmghHgRR6OYf0x48d9mPWfV0FEKKp4wzfy9/wdbvkrWoqwD8sQ9mEZuKg4LTV9zz33oLGxEa2trWhpadGE2zslHIrAea+WlhaUlZWFJI5qSljtP8kEkMFgMBi9iu4eXsEK4LZt2/CnP/0ppKicOqGjoaHBb7uXkymA3hNEnE4nampqsHv3bi1ypbvgKk1oLK9+ATE8EpZ+KZh55BWEF2QhddG0dpGwec3vI23FTMhGHcITw7Fq5zI80fSgJlbjlo1CytBTK4AJAxNw9poJft939zdbMHbpaAiiAHNyLMa9dq/23KZ/9xKIyKfwI3/ndeAkEfL8VSf26pUT9yltjhg0NTWhvr4eDQ0NaG1txbFjx1BTU6NVe59KAVSjj2qUWS1U6SlO7W8ABoPBYJyWeB9EixcvBsdx4HkeHMe1W2PHjm13eAUrgA899BBuueWWbglgfX09KisrUVFREdQkkcrKyi4JoHqnsLq6WhsBpoqKzRahpYKN9/75hNi89R3EuGToohywDemHuCmj/N6FK3YdQpHzHaScNwWKSQeTw4S5N8zC/T/9CeOWjULqsNRTLIDxOGv1eO3vTx3biWvfuBI504aCF3hYkmMx8tkt7Z7TlH88DU4UtFYvAzYsAS9L0K2+Rtsj6we/QCwYB5IUECfg/vvvR319vba39fX1WuRP/beura3VBC5UAWxubkZ5eXlIj1VXeXm5Fm1mfQAZDAaD0WvwPohaWlpQU1MTcDU2NrY7vIIVwCeeeAKbN28OKSqnSkFVVZXfdi8nQwDVNLN62Hs/rqysDAcOHAAn6iHow8EZzbA8/7cTEvj+UYhDCkBEcAzrH1AA1TWn8T1kXr4Ihsgw8AIPIkJcZiweq38gJHnb8Oq6bgtg4qBETLpwHO7+ZgvmXD8L9ng7REWEIycTE956IOBzmXRwFwS9gtlVbyNu8pkQ9DoYbtml7U3Yh2XQLbsCJCsg4tAnrZ+212oKv6GhAXV1dWhqakJra6t2D6+qquqUC6D3CMKe4lT/DmAwGAzGaUh3D69gBfDZZ5/Fhg0buhyV8xbArvYQrKys7PSeoPr5y8vLtXtfVVVVWoRKLVBoaWlBeHgEeMUGObwv+IQ+sL7xrY/o8JmDwUkiMkpmY27De52KYLHrEMa9ug1KRBgknQRJJyFn2lCU7FqGHT/e+T8RwN0tD+OG966GPc4GIgLHczDFRiDjwtnt7vX5W2P/eg9Eow6GhGgIDgdMT7/nsyeGGx8AiaKW/v3888/R0tKipegrKyvR1NSEpqYmrThITQmrAtjZtI5AS/33624EsLm5Gf/973+7+1IJyCn+FcBgMBiM05FQDy31nhTHcXj99dfhcrnw+++/B/z4l19+GZdeemnQUuYvNdtVcQzma3lPEVEnjqhSUllZierqajQ3N2uFCpygQ8SQCyGaoyAOyoX1wA+a7Og3/sndj89ihiUjCYWfPBmUBKavPBdhWRkoeGQzIs8cAr3dAuIIjgQHRi44A8vuXYQb378Gj9T4b+sSrAA+dWwntn9/B6546WIUXTsdmaMzIetliLIISRFh6Zfkt8l1oDWv5QNkXDgHglEPcegZsJQe8ZE/4/a9IFGCJWkCOEGHxYuXoKWlRVvNzc0+Tby9U8JqJNBb/LsaCWxqakJFRUW3BLCsrIwJIIPBYDB6H6EcWEeOHNHuCnqv66+/PuBjXn/9daxevbrLAqhexA9lgkhVVVWnX0uN+qkVv2pj6fLyclRUVGjyp65ly5aBeBGp0/aAN9gg5o2F9V23+Jgeec096eK1ryBmDQcniRhw1RLMrX+3Q5Hqu2Yuwgam+7xt2ld7MWD9EjiG94cxyp2OJSKY7CYkD0nB8Bk5KLxoIuZsnokJK8eC4zlc8MBirLh/MZZsW4jiW2djxvqpGLNkFAaOG4CoPlHuz8ERdBY9LClxiJ8+GgWPbcacxvdg7d8H/S6eH7T8Ff7tSYQNTIegk0GKzkf8wj4sg+mhfSBFB8fA86GPHAwiQlNTk89eqhKo/hurd0PVlLAa+VUjeU6ns0sSeLIEsKWlhQkgg8FgMHoXPXaqtaG0tBTLli0LSsq87+WpB38oE0Q6+1reU0TUe39NTU2oqanRpLOxsbGdtNjtDgg6OzKL3went0DMGwNr6Y+wlB4BcTzMz33gjghu2g7RYoE+NhKj9t6O+cc+8itTmesWwtI3peNoW+uHKPx0N4bdfTn6LJ2O6Al5sGWnw9InHoZIOyS9BFOUHaZoB0yxEbAkx8LaNxmOvEFImDEG/a88HyP33h4wrWvpm4LMdQs7Fb+i8jeQsbIInChAHDQMctEy8EnpvvL3wEtuKexbhIQxW8EJCvbv399uH72XmoavqqpCc3MzGhsbtX+H1tZWrSefKuXByJsaBQ5V/tQ+hEwAGQwGg9Hr6LFTrQ2HDh3Ceeedh6qqKlRXVwd1L8+73UsoDaQ7EkDvKSJqkYuaglRbzqgColapqqupqQmibIAxJhcDlv4LvMEKISsX1je/A2cww/inPScKREqPQJo4A7wiwzFsICa+82A7qRp49TKYUuKDjr75u0fICULIjy92HYIpNUFrYu23cKXmALJvWg3BoIPoiIDhjscR9mEZpIkzIQzOP5H2/dNTIEmGrd9c9J37JjheQm5ubofy572vquSpqXn1z+q9QPXfLdD0kJ4QwNbWVvz222899to41b8DGAwGg3Ea0mOnWhs+//xzzJ49OygBbHv4NzY2hiyA/r6WKnk1NTWaAKrvayt83h/rnQ7+4YcfwAk6OPovRNbKHyGYIsEn9gEXFg79xTe0S4laXvwEYnYeOElEeEEWxr26XYsIDr5pNfSxEaEL4Gv3dlsADYkxGLTpgvYRv4o3kX1DCSSLCaLFCl3JBp/nJWYOhTRlnjviuf4OkCgiYsiFGLj0K/CSCYqiC0r+vFPCqnirPQHbtopRfx78TQ/xXurPUagCqPYhZALIYDAYjF5Hj51qbfjmm28wffp0VFdXdyqA3oUB6ttCmSDi72t5V/yqqV/vil+1/5z3amxs1KKR3hL41ltvgRMUxORvxJC1tVAcGSAiyIWz2wmglh599n0Ig/PAKzLM6UkYvv0qDNmyFrLD2k0B5LslgPqYcAy57WLt74V/exJ9lswAL0sQbQ4oy9bB8v7Rds+HszqgW7sJ8qwlIElGwpityF51BJIpFrJi6JL8eaeD1RS8WoSj3gtsbOx4ekhbAayqquq2AB47dowJIIPBYDB6Fz12qrXhhx9+wFlnnYXq6mpUVVUFlDbvtKv320NpIN1WANW0slrx63Q6UVdXh+bm5nYVv/4iU2p60vte4B133AGOlxE/+jYMvbQVkjkJJIjQrbkOVj/C5D1FRDqrCKLVCiICL0sY/eKdmNt48JQIoGy3YNB1KzDktotg6ZvivuOX2Af6a+8J+Bysb33vbh0TEQtOb0bf2fuRXXIUii0NHC+hoaGhy/KnirjaF1CNBKutYjqbHnIyBdC7ETUTQAaDwWD0KnrsVGtDWVkZxo4dC6fTGVAAve/ltX1fdwVQlQHvil/181VXV6OysjKg/HlLoFqQ4p0mXrp0KTheQvyoW5C54APP2DgdxMFnwPLy3wMKlLqkpZeBeA6CQQ9BJyNu8kjk7liPaV/9OWDhiPcav38HOL7rAji3/l2M378DA648H5ynIbUUHglpyhxYXur4+7Z+8Av0l98KkmTIjgxklxxFdsl/oNjSwfEyKioquix//kS87Z6r/QIDTQ/xTgnX19ejurq62wLocrmYADIYDAajd9Fjp1obampqUFBQEFAAve/a+ZO5UAVQ/VreFb/eRR9qBMlfi5JAy7ttiSoqU6dOBcfLiM69HLxkRuL4bZDtaSBFD/2Vt3cYDTTtPuBuH/POYXfl8LARkOwOEM9DtpkRPSEPg65dgTOfvgWT//4U5tSWthNA6kAA57d+iJlHXsGEtx5A7r3rkbZiJqz9U8EJAgS9DmJ8MogIumvu7lRWwz4sg+WlTyHlTwBJMoh4DFvnwqDl30K2JILjJXz//fchpX6dTqff1jvee67+fLSdHtLS0qKl6VtbW0+KAKp9CF2ujntcdpdT/TuAwWAwGKchPXaqtaGlpQVDhw6F0+lEZWVlO/lT7+UFkrlQRsipstlZxa93SjfYpd5L9I5WFRYWghMUEPGw952DYetciCm4BpxigJA+EKadr/gXqre+cwvgvn/4vv31r6C/5EaIZ06CmJACKcwKThRARBCNehgTo2Eb3Bem1Dj3OLmpoxA3ZSSiJ+TBkTcIln4pUCLt2mMEgx5SRCSEvoMgzzwfxm3PwvL+UVjf+8ndY/CxNzqO+pX+CN2qjSBZgWxPgzEmD+b4UehX/B4EJQzEifjyyy9Dkr9g/i3Un4OOpoeooq++z+l0dksA1UkiTAAZDAaD0avosVOtDb///jsGDBiAmpoaHwFs2+4lkMyFMkJOlU01Wudd8aumDdu2eOnqfTXvO2otLS2YO3eeZ6SajEEr/g/D1rmQVfIfGOPPBAkipFGTYX7mYDu5IkGE+anSzqNv7x+F6cl3oN+0HcryKyDPWAQ+50y3FBaMh1gwHtKoQkiTZ0OetxL6S26A8U9PwfL6V4E/52tfugX0r//yL37v/QeGa7eBs0eC11uRMGYrci5tAS+bYU2dDI6XQcThq6++CmkfGxvbV193lCbuaHrIsWPHNJlUq8BDFUDvRtJMABkMBoPRq+ixU80PmZmZPgLofS+vI/kLVQCrq6tRVlamVfrW1NR0WvEbyr01NeqkFj1ceeWV4HgJvGxG2syXMGydC8PWudCv+CAURz+QIEAeew7Mj795QgD1Rph2PB9UCrZdCvn+l0HEhfTYsA/LYH7uQxDHtavytZb+CP2GreAj40CKAY5BSzH04kYMW+dCRtEr7mgn555Q8sMPP4S8fxUVFXA6nV16jBrVbTs9RG0SrUbvysvLtZQwE0AGg8FgMDz02KnmB1UA1Upaf+1eOhLAroyQU9u9qBWlXan4DWV5C0lTUxNKSko8kUAJ4YOWYMhapyaCfee+CV3EAJAgQhyQA8OND4Cz2GC44f7QBPDhfSCikAXQtPNVkHxinJv5z4egnLcWnNEMTm+GY+BiDFlbe+L7n/cOJGMMiOMRFRGDw4cPw+l0hrSfwRbg+Fv+pod4p4TVn7WuTA/xXurPHRNABoPBYPQ6euxU80NmZiZqa2u1+3xdme/blRFyamRRnecbSsVvKEtNK6t3A2+++WYQ8eAEHURDxP+3d+fhUVX3/8DvJCRsM2GAoCwiRGlJAmFLZBUkVIOlFnAXtJVaKV/9umCVCjwKVKuCuICA+w8p+LQVNRL5KhaUtiqIIhJQWyxLMCGZ7MlsIZrl/fsjnvFmmJncmbl3Tsh9v57nPq1Icm9mJud8POd8Ph8MmfWGL4jKurcew+Ydhi1lOixdrFASOyM+bTS6r3sdPT4sDDOAeweKoqDHnuKIAsDuT2yB0s2KrotWolPqaChxcUjoMRD9L34YY+6p8z3vqP8tRXJGSy9kRbFgypRLfGfxRE2+cJNpwk3A8b/U3UNcLpfv7J/o5CICf63dQ4IFgE1NTYb9XsgeA4iIyIQMm9UCEAGgw+FotX2ndwAotmTFCqNYlYsk4zfc7czy8nKUlJT4zgVWVVVh/NiJvnOBtoFTMezmA60CwTH31KFTt75Q4uOhJHaB0qUbOk25HF0Xr4btbx+1GdhZN/69JQD8qEhz0Ndj9zF0X/c6Ov9mISz23lA6d0G8NRn2n1yJ9F9/3vr5Frpx/qXrEJdogyW+CxRFwezZs8/42dUrum29VuLcXyS1AgO97uI/KERmcG1tre8zI7ZzRV/pUN1DgtURZABIREQdimGzWgCpqam+mm7hnufT2kNYnfErgjFxPizSjF+tl7oosQiGxP2eeeYZxFsSW87MWTqh59BrMfw3h31BVs+h18I2YDLG3OPBoMuehXXgFMTbkqHExUHp1h3xI8a2JHUsfRLWDW/C9von6PGPEy0B4KadLQHgh9+2DvI+PoWkHV/Btvl9dF/1Crrc8SAScq5C3MALoFgsUDp3RWLPCxDfpTc6de/fKujLurcemfd4kPLzjUi0ngdLp5bAL+2nw4Oe9/N4PAFL5AT6e2IVWM/XX2STi/9QEOc/xZZwXV0dysvLQ3YPYQBIRESmYNisFsCYMWPwyCOPoLi4OKzgT2sAqA4+xLk/EQRGm/GrJfhQB5jqRIWamhp4vV4UFxfj4klTfGcDFUs8eqT8HEOvfx8Ds59EfJdeZwRho/63FINyXkDPodegS/IwxCedC0uXbi0BnKJASUiAEt+SiGHp2QeW5HNbVvS6doNiaSnurHRKgKV7DyTYB6H7gIk4J/NuDJ3zT9/2bu/UObAOuPjHe95RhoHZTyChe1/fil/nBBueeeYZTa+Fut2efxAoVkn92+rpdYnEDdFGLtzuIepLXUeQASAREXUohs1qfurr63HhhRfiiiuuwKlTp8IOANvqIaxe/RHBnzhfKAJAEYjpfYl7BAowRWCoTpJ4//33Mei8C1uCM0s8LHGJ6NT1HCiKBWk37T0jCAx0jbnHg/Sbv8CQ2bnoP2kFFEVB/0krcN7kRzFw2tO44BdbMPT6XRix4GSb36tr7+HoM/J3+Om176FX6g2wxCXC0qlrS+1AS2fMnTs37NdOXSJHveoqjgAYtQ3v9Xp9RwBCdQ9xuX7sLx1sS5gBIBERdViGzWoqzc3NmDt3LqxWK44cOeJbKdMrAFTXEvTP+C0tLUVFRYVvdTDSbNW2VpxCbWe6XC7f86nv/be//Q0DB/wQCCoKLPFdoSgWdDtnFM6b8ijSf/05Mn9/us0Abvhv/wNFUTD6zgpNwaO4Rt9ZgQtnva66f2colpai0Qnx3TBz5iwUFxdH/Nqoz+aJVTi9zv0Fu0TALYK+trqHlJWVteoeor7UhaQZABIRUYdi2Kym8sEHH2Dw4MGYOHEi/vvf/0YcAAZqIed0On0rTergT2wbqzN+gwVi0QQ4IoDQ0kdYna2q/nfvv/8+sjLH+gKxTpZu6JTQA4qlE+ISk5A0OAcDLn4IP7nqbYyYfxSZv69rFciNWFAARVEw6n9Lgwd7d1Uj/VefIuXn/w99Rt2GLr3TWzKUO3VtWYVUOkNRLEjq3ge33347KioqdA/KxPa8UcGf2+0+YyVW/Z5r6R4SLABsbm427PdD8hBARERmZNis5sfpdGL69Ok4fPiwbxUonAAwWA9hkWwhJuu2Mn5DBWLhXqF612pZEfP/96WlpcjMzIQ96RzEWRKQYOmB7p3OR9f4vuiccA7iE5KgKBZY4hKQYB2A7n2z0OOCGbD/5CooioLe6Tfi3My70GfE/JakkoFT0aV3Wkubth/OHSYk9kaXTuegW6f+6NZpACxKPBTFggnjJyIvL8+QwEwEyursaKPuEaigtHjPtXQPqamp8W0JV1dXo6qqigEgERF1PJFOWps3b8akSZPQq1cvJCcnIzs7G3v27An5NbNmzcLnn3+uWwCoDqbUPX7byvgN1L0j3CuaGnYi2KiqqgoaPDocDixbtgwjR4yGtUsyFCUOCXFW9OqcgeQumejVeRTsielISvwprJ1SWhI14pNhTRgMa0IKkhJ/gh6JQ9Gz83Akd8lEcpcsWDsNhqLEoVNcF/TtMwhXXnklNm7caPiZPFGQ2e12h1UqJpxLtP0LlXmspXuIODJQV1fHAJCIiDquSCetZ599Fjt37oTH40FjYyPWrFkDm82G4uLioF9z3XXXYc+ePREHgOoewv4Zv5H0+FV/j3CCDT3OsokkhGDbx/73KC4uxgsvvICbbroJWVkXYcC5KbB1OwedO/VAfFwXxFla+vFalHjEWRKRENcd3RJ7oVdSfwy5MBU5OTm4//77sXv3bt/2uEiUiHYlVEuwGyo7Wq97aAli/TOUxWdJbAnX1dWhoqLCFwhWV1czACQioo5Hz4nMbrdj27ZtQf/9r3/9a+zevTuiAFDdQzhQxq/Y2gu3x68ICLQmh+jZR1idKasOXsQ9jMpaFgGo0dnRoX6OUKViwr1HuCV+/DOUA5WKEf9xUF5ejtOnTzMAJCKijkWvSWzfvn1ISEhAQUFB0L8zf/587NixI6wWcP4BoMj4raioQG1tra/ci3r7LtyAQmTyttXKTNxDz0xi/+1o9T2MCv7U9whUpkbve7QViIXbQk59j2Dn/rR8baDuIepSMaKGZGVlJbOAiYioY/GfjObNmweLxYK4uDhYLJYzruzs7DMmsMLCQgwePBjLli0LOdHdeeed2LZtW8QBoAjSysrK2sz4jSQgENuigbZERaszo/oIixUn8TMacY9gP4d/pqwe92nrTJ76eUQAHG6hbq33CHX5B8DiXKBIMKqurmYASEREHY//ZOT1en0JFYEul8vV6u8fPXoUKSkpWLx4cZsT3X333YfXXnvNt+oSbgBYUlISNONXj+zSUFm6RvcRFgGN2HY0KgAMlrzSVgCsxz3a+pq2EmMCBW56vB8iABYrkWI1UPyHRn19vX7RXgCyxwAiIjKhaCauQ4cOoV+/fnjkkUc0/f0HHngAmzdvjigAFNtx4Wb8RnL5Z+n6JzIYcamTV6LZFtVyj2DJK/7bopEGU5G23WsrMUaPewS7xMqo2IoXr1VVVRXq6uqi+TVpk+wxgIiITCjSSWvPnj3o1asX1q5dq/lr/vSnP+Gll17yreJpDf5EfqYhYgAAIABJREFU1qj4ukgyfqMJRozuI+yfLOEfjOh5Dy3JK5GeCxTn/kJ1RdHynKHqNBp9RlL8B4V4751OJ9auXYuDBw9G+qvSJtljABERmVCkk1Z2djbi4+Nhs9lgtVphtVphs9nw2GOPBf2a1atXY/369b5AREvwJ4IRsT0ZTcZvJEGgCAaM2voNFtDoWS5FJEuEkyDjvy2q5R6iW0u029ehViL1OPfX1iW24p966im8++67GDVqFLxeb6S/Km2SPQYQEZEJGTarBbBu3To8+eSTKC0t1RQAqkuFqAMCI7JxAwUh5eXlvsuI4sVaEkvCLVMTLKAJp2OJ//NpORdYXV2te6DsvxKp57m/YJdYVa6srMRll12GXr164a9//auhvxeyxwAiIjIhQ2c2Py+99BIeffRRTQGg6PErDuKLQERkq8ZiFUgETUYULw4naNJapiZUEBXp+UUtP7sehbGDXWIlsrS0NGZb8SK56LrrrsOsWbPQrVs3vPLKK4b9XsgeA4iIyIQMm9UC2LJlC5YvX+47JxYqABTdGNQZv+JcnlHBhriCZbFqaeGm9Qo3aIokS1fPZAl18W31zx6LrXhR7NnI91294uvxePDcc8/hqquuQlNTE3bv3o3c3FzDfi9kjwFERGRChs1qAWzduhWLFy9GWVlZyABQXReusrLyjIxfo/rJagnM1DXzIg0CI+30EapMTaC/G21CRqDnVq9E+gdNRgWAYjVW/OzV1dW630+9GvvFF18gPT0dVVVVMfm9kD0GEBGRCcVkhvvB22+/jYULF4YMANXbjdXV1UEzfkUwqOeWrNbVrGAt3LQGcdFmsba1EmlkYKY+FyhWaY0M/vzP/enVQk59iZVSp9OJqqoqjBkzBh9++GHMfi9kjwFERGRCMZvlAOzcuRO33367r31XsIzfqqoqX7mXUBm/eiRI+AdmWgML/xZu4QRPepxfDLUSaURCRqCfQ7xXRgV/wbaw/Xv56vG+i2D6f/7nf/Dwww8b2vvXn+wxgIiITChmsxyAf/3rX7jllltQXl5+RgCoXtkJ1OM3WJCnx5ZsNIFZOCuRegdmYqVPHQgZmZChDsBE4K1XAB4sMAu2UioC8GjPOKrf99deew3Tpk1DY2NjLH8tGAASEVHsxXKi+/TTT3HTTTedEQA6nU7f2bJIevyqA6FIgqto27xpWYk0KjBTB0IiwNRzWzzQ/URNQREMRpqhHOrSWu8v3BZy/l8r3vdvvvkGQ4cOxalTp2L5KwGAASAREUkQy4kuPz8f11xzDcrLy1FRUeEL/kTwFk2P30i2ZL3e6MukiEsEQuXl5Wc8b6RJH+Fc4uxkLMvjqF97PRNzwq33p14FDudrxOqh0+nElClT8Pbbb8fy18FH9hhAREQmFMuJ7siRI5g5cyYqKip8AWBbGb/hBmbh1OsTQYBegVmgLVmjW5f5B2YiS9qIIFC8J4GCLL1qJUZauiacMjn+xwqWLl2KhQsXxvTcn5rsMYCIiEwolhNdQUEBcnJyfAFgoIxft9sd9Xaplnp9YsVO7yQG/zZmeiV9tBWYia3MaDKU9QjMosnSjTZYDtVCTn2pVzHfe+89jB07FvX19bH8VWhF9hhAREQmFMuJzuFwYOrUqb6gSJxbExm/LpdLt8LCoZJDYlG/TqyW6bG9rCUwUwfLkW6HtxWYaQ2WRRAa7rlAvfr8BitaLf6deE8KCwuRlpaGb775Jpa/BmeQPQYQEZEJxXKiq66uxvjx430lRESmb6CMXz2Co2CrYZH2xg03CBEBoFFbsiJYDhaYiSA0msLJkWZIh3suMNT2cjTvvToIVZ/FdLvduOKKK7B58+ZY/goEJHsMICIiE4rlRFdXV4esrCwcOXLENxGLjF+jVuXUgYjL5fJtlxq5KucfaESyGqbl59LyekVbODma0jXqc4GhglA9W9YFe+9ra2tbZS8/8cQT+NWvfiXt3J+a7DGAiIhMKJYTXWNjIyZMmICrr77at9InMn6NXJVTByJG18gLtIrpH4TqcR+RIa3l9Yo0CNWrdE2oINToJBmPx+NbXRSB7N69e5GRkQGXyxXLj39QsscAIiIyoVhOdH/605/QvXt3fP31176tS5HxG4tVOREARlIzTmuwEWy7NJw+vm1dkZSuCXdLVq+zmOrvFygI1evcX6hLBLJvvPEGZs6ciczMTOzfvz+WH/2QZI8BRERkQrGa5N58803YbDakpKT4zgA6nc6YdK5QFy82opesuLRsl2rJUA51RVO6RmupllhsxzudTt3P/QW61IHsiRMnkJGRgb59++LIkSOx+ui3SfYYQEREJhSrSe7IkSN47733kJqa6lv1cTgcvvNhRgZ//qtyRpzLE4GdlkDW5XLB4XCEHWDptV0qnjVY5xLRGSUWGdJGdy1RB7IbN27EjBkzsGjRIiQlJeHYsWOx+viHJHsMICIiE4pm4srLy8OIESPQs2dP9OzZE5mZmXjjjTeC/v3m5mYkJSXh4MGDKC4uxjfffGP46l+wNm96nssTAV04wUy49fqi6Vcc7JkDdc8QK7JGbseLQNbIDGmvt/WK7OHDh5Gamory8nIAwL59+9pFAgjAAJCIiCSIZuISqzjChx9+iK5du+Lw4cNBv2bHjh1ITU3FJZdcgptvvlmX7hHBrrbOyulxLi+aVblw6vVFk40b6v7qziWxaFnn9f547s/lchlStNrrbV0fsbq6GmPHjsUHH3wQzcfdMLLHACIiMiG9JrHm5mZ89NFH6Nq1K958882Qf/fWW2+F3W7H888/D6/3x1UnPZMzwjkrF2m9PD1W5bScyzPynKQ6CC4tLTV0RU79WouAT++i1eJ7isLVHo8Hd999Nx544IF2s+LnT/YYQEREJhTt5OV0OmG325GYmAiLxYIpU6aEbKv1yiuvoFevXjhw4AB+9rOf4cEHH4TH4/Fto+oRgITbuUIEWeHeX89VOXF//3N5emfjBrvKy8tDngvU4wpV70+PotXiUgflubm5mDx5MhoaGqL9qBtG9hhAREQmFGhCmjdvHiwWC+Li4mCxWM64srOzz/ia7777Drm5uVi5cmXIlZavvvoKH374IQDg+++/xy233IIbb7zRVw8w2uSMaDJYRX9gLfePpBSLlgBJ3b5Onb0ci64looWaES3ytGyV65Ghre6LfPz4cQwdOhQnT57UKVRrbe/evZg2bRpsNhvsdjsmTZoU0feRPQYQEZEJBZqQvN6W5IlgV6gCujNmzMD69es1T37Nzc149NFHMWXKFBQVFUWdnBFtQWn/c3HBAjWjzsqp719RUWF4yzr/VTl1coqewa3Wen/hJscE+1lcLhemTZsWMikpGnv37oXdbseWLVtQX1+PpqYmfPbZZxF9L9ljABERmZDO8yIuu+wy3HnnnWF/3WuvvYYRI0bg8OHDrc6lhXMuTK+C0qHub3TnCnGPsrKymJTICfSz6H0uL9x6f+r7a03O8f9Z/vjHP+K2224z7Nzf5MmTcd999+nyvWSPAUREZELRTFybN2/Gf//7XzQ1NeH06dN47rnn0KlTJ+zYsSOi7/fJJ58gLS0Nu3btahU4aFlpMyJRQn0uTQQZ5eXlhneuECtZlZWVup2LC3S1lcCix7m8aPr8hnN/9Qrj7t27MWbMGNTV1UXz8Q6qrq4O8fHx+MMf/oCxY8eid+/eyMrKajP5KRjZYwAREZlQNBPh8uXLkZKSAqvViuTkZEycOBGvv/56NN8SJ06cwKhRo7Bx40ZfYBcoOUJ9GZkoob5/sJqCel7+CSxGdS5Rn5XT8vNHcn89Vku1JAepz2OeOnUK6enp+Prrr6P6HIZy6tQpWCwW9O3bFwcOHEBTUxNyc3ORmJiIffv2hf39ZI8BRERkQgbMj1GrqanBpZdeigceeMCXIaxOjvAPMoxOlBABZixa1gVKYAknOUVrUBXOzxJpco5efX5DnUtU1y50u9246qqr8OKLLxr6+XQ6nbBYLFiyZEmrP58+fToWL14c9veTPQYQEZEJ6TUp6u3777/Hb3/7W8ydOzdohrDe3THaCphKS0sNKVosrqqqqqBJH3p1LomkRI7//bUEjlpXGMO5v/+5QHXw7/V6sW7dOlx//fVoamoy/PM5ZMgQBoBERHT20mtCNEJzczNWrlyJKVOmoLCw8IwgyIjuGMECJrEFrXfRYnFpKSsTbeeSaErkiK/X0rklmnN/WgJLUTRcHTDv378fw4YNQ01NTUw+m2vXrkW/fv2Qn5+P5uZm5OXloWvXrti/f3/Y30v2GEBERCZkwNyou9dffx0jRozAoUOHWgVBsehZGyjpQ+/2deG2YBPBYridU/QKmEOdy4xFlrQIMMU2dkVFBUaPHo29e/fG9HO5cuVKDBw4EElJScjMzMT27dsj+j6yxwAiIjIhnedEw+zbtw9paWnYuXMnPv/8c+zdu9fwMimhkj5E1nG0nTMiDZjC7Zyid5Z0sHOJep37a+veDocD33zzDcaPH49bb70VK1eulP0RjZjsMYCIiExI9uQXjoKCAmRkZGDQoEFYvHixpgzhSC8tW7KhklO0Bn/RnGHUmpxhVJa0/5a83uf+gt1TbGPX1NTgxhtvRGJiIrZt2yb74xkx2WMAERGZkOzJLxwNDQ3Izs7GeeedhyVLlrSZIRzpJbYYtWzJRtO5Qo8t2baSM4zOkvbfkjfi3F+w1+zf//43UlNT8dxzz6F79+7YsmWL7I9oRGSPAUREZEKyJ79wrFixAunp6aisrMStt96KOXPm+IoERxqEBQpowt2SDTdD1uvVd0s2VHJGqMxiPYNAUSYn3HOJ4Vzq8jW1tbWYOHGir+j4oUOHUF5eLvkTGhnZYwAREZmQ7MkvHA6HAydOnADQkiG8atUqTJ48OWCGcKSBTKSdPrRmyHq9xm3J+ieHaNnG1uMS5/6cTqfuq7Hq11eUr/F4PFi0aBEWLVpkWKu3WJI9BhARkQnJnvyi9frrryMjI+OMDOFItiL16PTRVoau0VuyYktc9BLWK1M52OV/7k8E0YGKNkdzqc9KvvPOO5gwYQK+++472R8/XcgeA4iIyIRkT356+PTTT5GWloa///3vvqAk3AxhPVfLQmXoVlZWGr4l63a7fWfyjEzICFbvL9pAPFSQWVBQgNTUVBw7dkz2x043sscAIiIyIdmTn15OnjyJ0aNH4+WXX4bXq62HsH8go+dqWaAMXRGYxmJLtrS0NOxzieFcWs5Kqos2RxrwqoNMt9uN6dOn4y9/+Yvhn6fZs2fDYrHggw8+MPxesscAIiIyIcNntxiqra3FZZddhqVLl8Lj8fhq1YU6k2Zk4WL1uUQRDBmdJeu/JRvJaqjWIFPLWclw6xWGem8ee+wx3HLLLYaf+/vzn/+MnJwcxMXFMQAkIqKOyfDZLca+//57/O53v8MNN9zgyxAWZ9L8t0OjbY2mNYiprKxESUkJysvLDQ3+gm3J6l0vMdx6f5GWylEHmR999BFGjhwJt9tt6OenqKgIgwYNQlFREVcAiYio4zJ8dpOgubkZq1evxsUXX4xvv/02aIawHkkfWgJAEYCKlTij6vGJLNlgQVigzh16BZlani+cPsrqM5kOhwPDhw9Hfn6+4Z+dnJwcvPzyywDAAJCIiDouw2c3id58801kZGQgPz+/VZmW2tramJVIUQeZ0WyHthVcaekoEm2Grh7b5eot6WDPqu6N7PF4cMMNN2DdunWGf142bNiAnJwc3z8zACQiog7L8NlNss8++wxpaWl47733Wq0sxaJESqAgU2v7tnCucDqKRJOhq1efX7ElHSgQVpfJ8Xq9eOGFFzB79mw0NTUZ+jk5fvw4+vXrh8LCQt+fMQAkIqIOy6hJbe/evZg2bRpsNhvsdjsmTZpk1K3aJDKEX3zxRTgcDmzfvh0lJSWG9BAOtIoVKAjTq1ZepB1FtKzE+f99PbfLgwXC6s4lBw8eRFpaGiorKw3/jGzatAmdO3dGnz59kJycjOTkZFgsFtjtdixYsMDQe8seA4iIyISMmND27t0Lu92OLVu2oL6+Hk1NTfjss8+MuJVmIkN40qRJuPTSSw3pIey/ihVqq1SPWnnRdhTRuiUd6bk/La+TulSNCGZdLheqqqqQmZmJf/3rXzH5fJw+fRrFxcWtLovFgq1bt6KmpsbQe8seA4iIyISMmNAmT56M++67z4hvHZUVK1agR48emDNnjq82XbAM4WguLefx1CtrkZRp0SuDua0taSPL5IjvL85mqlckb7/9dvzxj3+U2uqNZWCIiKjD0nsyq6urQ3x8PP7whz9g7Nix6N27N7KysvDmm2/qfauw7Nq1C1arFfn5+Vi9ejUmTZrkyxAOJztVS0AX7lZpJGVa1Fuleq7E+W9J63Xur637l5aWori4GE888QT++te/YurUqWhoaJD6mYkV2WMAERGZkN6T2alTp2CxWNC3b18cOHAATU1NyM3NRWJiIvbt26f37TRzu9346KOPfP+cm5uLjIwMHDx48IwM4UgDmUjP44mVOK1b0kZkMKtfA3FuUe9zf8EukcRy7NgxDB06FOeffz4OHz4s7bMSa7LHACIiMiG9JzOn0wmLxYIlS5a0+vPp06dj8eLFet8uKvv370daWhp27NjRKrCKpFZftOfxRBDWVnJIqOQSPS7xGlRUVMSkc4k4XyjOAE6bNg3jxo3DBRdcYJogUPYYQEREJmTEhDZkyJCzIgAEgG+//RZjxozBiy++6AtIwq3VJ5I+9EgoCbUl7V8ixahLrGQ6HI6YbP2K85gPPPAA7rrrLjQ2NmLFihXIzc2V/fGICdljABERmZARE9ratWvRr18/5Ofno7m5GXl5eejatSv2799vxO2i5nQ6MX36dNx///2teghrPfum53k8cYnkEPVKX2Vlpe73CXSJ+4jLqC1gdbLMzp07cdFFF6G+vl72xyHmZI8BRERkQkZNaitXrsTAgQORlJSEzMxMbN++3ahb6aKhoQELFizAtddeG1aGsJEdRdTJISIgNLpzifrcn94JMsHuU1hYiLS0NBw5ckT2x0AK2WMAERGZkOzJrz1pbm7GE088gYkTJ+LkyZNtBkBG1cfzv4fD4YhJ55JgP49/coie93G73fjlL3+JTZs2yX77pZE9BhARkQnJnvzao9zcXAwfPhxffPFF0ADI6Pp4/vdxOByGbse29fNEUqpGy32eeuop3HTTTbrX+1u8eDEyMjKQlJSE/v37Y86cOSgqKtL1HnqRPQYQEZEJyZ782qvPP/8caWlpePfdd+H1/rjVW1VVBbfbHVax52iCJXEft9tt2Has16uteLUe3VPUdQX37duHjIwMOJ1O3d+/pUuX4osvvkBDQwOcTifmzp2LUaNG6X4fPcgeA4iIyIRkT37tmcgQfv75530BkFiJi0V9vEB1+PTejg12n1BBaaR9jNXnJcvKyjBixIiYtQjMz89HXFwcamtrY3K/cMgeA4iIyIRkT36hzJ49GxaLJSbtuIJxOp24/PLLsWjRIrjdbhw7dgwlJSWGbseKYDNYUWn1amS0K5CRnGOMpI+xun6hx+PBzTffjCeffDJm7+OqVauQkpISs/uFQ/YYQEREJiR78gvmz3/+M3JycmLWjzWUhoYG3HbbbZgzZw6Sk5OxY8eOiFfBtAZYDocDVVVVIQO3aLdjoz3HqO5jHOoZ/OsXvvLKK5gxYwaamppi8v6JNoA7d+6Myf3CJXsMICIiE5I9+QVSVFSEQYMGoaioSPoKoHD69GkMHjwYY8aMQUFBgWElUsQWq5bAzu12o6yszHdGMNx76XGOUSSHhCqcra6T+OWXXyI1NRVlZWUxed+2b98Ou92OvLy8mNwvErLHACIiMiHZk18gOTk5ePnllwGg3QSAt912G8aMGYPXXnutzQzhaC7RFzecLiQVFRVwOBxhrUbq2ec3VCAquoq4XC7U1NRg3LhxeP/992Pynr366quw2+3YtWtXTO4XKdljABERmZDsyc/fhg0bkJOT4/vn9hAANjU1YcmSJSgoKADwY4bwO++8A69XvzN56mAp3FVDEYhqOZNnRP3CQIGouj+yx+PBPffcg6VLl+pe8iWQdevWwW634+OPPzb8XtGSPQYQEZEJyZ781I4fP45+/fqhsLDQ92ftIQAMpLCwEJmZmXjuued8QVW4PYT9V9FEkkSkQZiWQNTI+oXq5JCamppWW9l5eXmYNGkSvv/++5i8PxaLBYmJibDZbLDZbLBarbDZbO0yIJQ9BhARkQnJnvzUNm3ahM6dO6NPnz5ITk5GcnIyLBYL7HY7FixYIPvxzuByuXD55Zfjvvvug9vtjvhMnjpJQo+s3lCBaCzqF4pAtKSkBG63G8ePH8fQoUN9K6jUmuwxgIiITEj25Kd2+vRpFBcXt7osFgu2bt2Kmpoa2Y8XUENDA26//XZcffXVvi4Z4WYIV1ZW+pIk9AjAggWiep77aysILSkpwe7du3HNNdcgJycHW7dulf1WtVuyxwAiIjIh2ZNfW9pDGZi2NDc34+mnn8aECRN8GcJVVVWaMoTVxZH13o5Vn8mLRd9icd/S0lJUVVXhxIkTGDVqFM4999xW2/rUmuwxgIiITEj25NeRbNu2DcOGDcOBAwd8K26hMoSNDsrUZ/JEH1+jgz/1FvM//vEPjBo1CvPmzUPfvn3x5Zdfyn6L2iXZYwAREZmQ7Mmvozlw4ADS0tLwf//3f/B6f8zs9U/MMDIZw/8qKyvTrXNIqEu9xVxcXIxhw4bhyy+/RHNzMzZt2mRIz9+OQPYYQEREJiR78uuIioqKkJmZiWeffda30uefmBGLZAx1UCb+V49Ek0CXejXT7Xbj6quvxvPPPy/7rTgryB4DiIjIhGRPfh2Vy+XCjBkzAmYIi2LPsUrGEFvMbrcbpaWlEXcOCXb5r2Zu2LAB1157bcxavZ3tZI8BRERkQrInPz0tXrwYGRkZSEpKQv/+/TFnzhwUFRVJe56GhgbccccduOqqq1plCIv+uUYGf8G2mCPJUm7rqqys9K1m7t+/H8OGDUN1dbW01/1sI3sMICIiE5I9+elp6dKl+OKLL9DQ0ACn04m5c+di1KhRsh8La9aswYQJE3Do0CHMnz8fBQUFKCkp0bWHsP8VaotZzz7GIovZ7XajsrISo0ePxp49ewx7LZctW4b+/fvDarXikksuwVdffWXYvWJF9hhAREQmJHvyM1J+fj7i4uJQW1sr+1GQl5eHn/70p5gyZYqvL66ePYTVl9Z6f+IZIl2NVHcv8Xg8mD9/Ph599FHDXsPHH38c559/Pr7++mvU19djyZIlGDBgALxer2H3jAXZYwAREZmQ7MnPSKtWrUJKSorsxwAAPPXUU+jbty/S09Oxfft2eL0tGcKiPIteiRnhlpaJ9BnU3Uu8Xi/+8pe/4NJLL0VjY6Nhr2FKSgrWrVvn++fGxkb06dMHr776qmH3jAXZYwAREZmQ7MnPKLt27YLVasXOnTtlPwqKi4thtVrxySefoKioCFlZWdiwYYMvYCstLfX1zI0m+FMXYQ53JS/cZ6iqqvJ1L/nPf/6D1NRUlJSUGPYaOp1OWCwW7Nu3r9Wf5+Tk4N577zXsvrEgewwgIiITkj35GWH79u2w2+3Iy8uT/Sg+p06d8v1/t9uNX/ziF7j33nuj6iHsf0VTWkadHNLWM4jahi6XC7W1tbj44ovx7rvvGvr6FRUVwWKx4MiRI63+/Prrr8f8+fMNvbfRZI8BRERkQrInP729+uqrsNvt2LVrl+xHCamxsRF33nknrrzySt/2q7p1W7gBnB59frUkh4hzf9XV1fB4PLj//vtx7733orm52dDXiyuAREREOpI9+elp3bp1sNvt+Pjjj2U/imZr167F+PHjceLEiVat28JpD6d3S7nq6uqACSpilVBsFe/YsQPjx4/Hd999F5PXKtAZwHPOOYdnAImIiMIle/LTk8ViQWJiImw2G2w2G6xWK2w2W7sPCLdv345hw4Zh//79vtU8rdm5kZ77a+sS5V3U7eNEAWuPx4OTJ08iNTUVR48ejdnrtHr1agwaNAhfffUV6urqsHTpUpx33nnwepkFTEREFBbZkx+1OHjwINLT0/H222/7ztlpyc41sqWcOkFFnPtzOp1wu934+c9/LmXlbfny5ejbty+6d+/OOoBERESRkj350Y9OnTqFiy66COvXrz8jAAsU4Olx7q+tS2QIl5SU+LqKrFq1CvPmzTP83J9ZyB4DiIjIhGRPftSayBD+/e9/D7fb7au355+dq/e5v1BbzOXl5XA4HJg/fz42bdqEkSNHwu12y36pOgzZYwAREZmQ7MmPziQyhGfPno2KioozMoSNOvcX6BKrjE6nEytWrEDnzp2xcuVK2S9RhyJ7DCAiIhOSPflRcM888wzGjx+P48ePt8oQFjUDjTj3538GUKwyejwezJ07FwsWLIDNZsNDDz0k++XpMGSPAUREZEKyJ7/2ZtmyZejfvz+sVmu7SDLwzxAW5/GMXv0Tq4zi3N9LL72EmTNnoqmpCYcPH8aGDRukvi4diewxgIiITEj25NeePP744zj//PPx9ddfo76+HkuWLMGAAQPg9cotM5Kfn4/09HS8/PLLuPDCC1FQUKB7D2H/q7Ky0rfKmJ+fj7S0NFRUVEh9HToq2WMAERGZkOzJrz0JVGi4T58+7aLQ8NGjR9GzZ0/ccMMNrbJz9egh7H+JGoButxvV1dXIysrCP//5T9kvQYclewwgIiITkj35tRftvdXYLbfcggkTJmDGjBlYuHChL0NYa/9erZdo9VZTUwOPx4M77rgDy5cvZ8kXA8keA4iIyIRkT37tRVFRESwWC44cOdLqz6+//nrMnz9f0lO1KCsrQ0ZGBoqKitDY2Ii7774bM2fODJghHO25v7KyMlRUVMDr9eKNN97AJZdcgoaGhpj8nJs3b8akSZPQq1cvJCcnIzs7G3vQj5GkAAAG9klEQVT27InJvWWSPQYQEZEJyZ782ov2vgLY1NTU6p/Xr1+PcePG+TKERf/eaOoCVlVVobS0FB6PB0ePHsXQoUPx7bffxuxnfPbZZ7Fz5054PB40NjZizZo1sNlsKC4ujtkzyCB7DCAiIhOSPfm1J4HOAJ5zzjnt4gxgIO+88w6GDRuGzz77rNXZverq6rDPBYpWby6XC06nE1OnTsVbb70l+0eE3W7Htm3bZD+GoWSPAUREZEKyJ7/2ZPXq1Rg0aBC++uor1NXVYenSpTjvvPOkZwGHIjKEt23b5gvkws0QFuf+ROC4bNky3HHHHdLP/e3btw8JCQkoKCiQ+hxGkz0GEBGRCcme/Nqb5cuXo2/fvujevXu7qAOoRXFxMS666CI888wzYWcIi0QS8Xd37dqFrKwsnD59WrfnmzdvHiwWC+Li4mCxWM64srOzz/iawsJCDB48GMuWLdPtOdor2WMAERGZkOzJj/Th8Xjwy1/+EnfffXdYGcLV1dVwOBzweDwoKipCWloa/v3vf+v6bOJ8YbDL5XK1+vtHjx5FSkoKFi9erOtztFeyxwAiIjIh2ZMf6aexsRELFy5slSFcWVnp6+Ub7Nyf0+mE2+3GrFmzsHHjRqk/w6FDh9CvXz888sgjUp8jlmSPAUREZEKyJz/S34YNGzBu3DgcO3YsaIawaPUmWsqtWbMGc+fOlXrub8+ePejVqxfWrl0r7RlkkD0GEBGRCcme/MgY77zzDtLT0/Hpp5+ekSHsdrtRUVHhO/f36aefYvjw4aitrZX6zNnZ2YiPj4fNZoPVaoXVaoXNZsNjjz0m9bmMJnsMICIiE5I9+XVU7aGo8aFDh5Ceno633noLXq8XLpcLDocDZWVlcDgccLvdKC8vx8iRI8+of0ixI3sMICIiE5I9+XVU7aWocUlJCcaOHYs1a9bA6/WivLwcJSUl+PLLL1FYWIjf/OY3WL16dUyfiVqTPQYQEZEJyZ78zERWUWOPx4NZs2bhrrvuQkZGBt544w3Mnz8fF1xwAbKzs8/oMkKxJXsMICIiE5I9+ZmF7KLGjY2NyMrKwpAhQ3Dq1CkcOnQIQ4YMQe/evU3Rb7c9kz0GEBGRCcme/M42Z2tR49zcXPTo0QMPPfQQsrKyMGbMGOzcuRPr16/HueeeC7fbLe3ZzE72GEBERCYke/I725ytRY2vvvpqbN26FUDL+cQrrrjCV/KlqqpK5qOZnuwxgIiITEj25NeRtaeixrL7+lJwsscAIiIyIdmTX0dl1qLGFD7ZYwAREZmQ7MmvozJrUeNgnn76aVgsFjz44IOyH6XdkT0GEBGRCcme/KjjO3LkCC644AKMHDmSAWAAsscAIiIyIdmTH3VsTU1NGDduHPLy8jB16lQGgAHIHgOIiMiEZE9+1LE9/PDDuOmmmwCAAWAQsscAIiIyIdmTH519tNZCzM/Px6BBg1BTUwOAAWAwsscAIiIyIdmTH519tNRCbGhowIgRI/DWW2/5vo4BYGCyxwAiIjIh2ZMfaXO2ZdGePHkScXFx6NOnD5KTk5GcnIyEhAR069YNw4cPl/147YrsMYCIiExI9uRHbTsbs2ibm5tRXFzc6powYQIWLlyI0tJS2Y/XrsgeA4iIyIRkT34UWkfKos3Ozj6rn98osscAIiIyIdmTH4XGLNqOT/YYQEREJiR78jMjZtGSmuwxgIiITEj25GdGzKIlNdljABERmZDsyY8CYxatecgeA4iIyIRkT34UGLNozUP2GEBERETt225FUR6S/RBEREREREREREREREREREREREREdNYZoCjKq4qiVCqK4lIU5bCiKMOlPhERERERGaanoigFiqI8riiK/Yc/u1BRlGRpT0REREREAem1avewoij7dXwuIiIiIjKAnqt2nyiK8jdFUXIVRalSFOU/iqI8oChKXPSPSURERER60bJq94qiKM2KojT98L/+1+4f/t5RRVEaFUWZoyhKvKIoIxRFKVQUZZHuT01EREREEdOyatdNUZReIS7bD3/vwA/fT21xgD8jIiIiIgPIWLV7SVGUvX5/xgCQiIiIKEZkrNqNURSlXlGU65SWFcRhiqKcVBRlYQTfi4iIiIgMoveq3S+Ulixit9Kyusjzf0RERETtDFftiIiIiEyIq3ZEREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREREZLz/Dx3Jy3waMthAAAAAAElFTkSuQmCC\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -853,7 +844,9 @@
   {
    "cell_type": "code",
    "execution_count": 81,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "%matplotlib notebook"
@@ -861,8 +854,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
-   "metadata": {},
+   "execution_count": 6,
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "data": {
@@ -870,7 +865,6 @@
        "/* 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",
@@ -929,9 +923,6 @@
        "    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",
@@ -946,7 +937,7 @@
        "        };\n",
        "\n",
        "    this.imageObj.onunload = function() {\n",
-       "        fig.ws.close();\n",
+       "        this.ws.close();\n",
        "    }\n",
        "\n",
        "    this.ws.onmessage = this._make_on_message_function(this);\n",
@@ -1001,15 +992,6 @@
        "    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",
@@ -1066,9 +1048,8 @@
        "        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",
+       "        canvas.attr('width', width);\n",
+       "        canvas.attr('height', height);\n",
        "\n",
        "        rubberband.attr('width', width);\n",
        "        rubberband.attr('height', height);\n",
@@ -1201,10 +1182,10 @@
        "}\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",
+       "    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",
@@ -1360,8 +1341,8 @@
        "        this.canvas_div.focus();\n",
        "    }\n",
        "\n",
-       "    var x = canvas_pos.x * mpl.ratio;\n",
-       "    var y = canvas_pos.y * mpl.ratio;\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",
@@ -1423,7 +1404,7 @@
        "};\n",
        "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
        "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
+       "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",
@@ -1441,7 +1422,7 @@
        "    // Register the callback with on_msg.\n",
        "    comm.on_msg(function(msg) {\n",
        "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
+       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
        "        ws.onmessage(msg['content']['data'])\n",
        "    });\n",
        "    return ws;\n",
@@ -1482,7 +1463,6 @@
        "};\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",
@@ -1491,7 +1471,7 @@
        "    // 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.parent_element).html('<img src=\"' + dataURL + '\">');\n",
        "    fig.close_ws(fig, msg);\n",
        "}\n",
        "\n",
@@ -1502,9 +1482,8 @@
        "\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",
+       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
        "}\n",
        "\n",
        "mpl.figure.prototype.updated_canvas_event = function() {\n",
@@ -1647,7 +1626,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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\" 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\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -1658,8 +1637,8 @@
     }
    ],
    "source": [
-    "phi = np.linspace(0,2*np.pi, 24)\n",
-    "a = np.linspace(-1,1, 8)\n",
+    "phi = np.linspace(0,2*np.pi, 100)\n",
+    "a = np.linspace(-1,1, 100)\n",
     "PH, A = np.meshgrid(phi,a)\n",
     "\n",
     "\n",
@@ -1691,18 +1670,20 @@
   {
    "cell_type": "code",
    "execution_count": 213,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "def Magierstab(k):\n",
     "    Angriffswert = 1\n",
     "    for i in range(k):\n",
-    "        Angriffswert *= np.random.randint(1,4)\n",
+    "        Angriffswert *= np.random.randint(1,4) # achtung hier wird 1,2,3 ohne 4 erzeugt\n",
     "    return Angriffswert\n",
     "def Axt(k):\n",
     "    Angriffswert = 0\n",
     "    for i in range(k):\n",
-    "        Angriffswert += np.random.randint(1,8)\n",
+    "        Angriffswert += np.random.randint(1,8) # hier werden 1...7 ohne 8 erzeugt\n",
     "    return Angriffswert\n",
     "\n",
     "k = 3\n",
@@ -1713,10 +1694,19 @@
     "    Angriffswert_Axt.append(Axt(k))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Gute Loesung, die Wuerfe mit Hilfe von Funktionen zu simulieren. Dann aber vielleicht auch List Comprehension statt Schleife."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 214,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "%matplotlib inline"
@@ -1726,6 +1716,7 @@
    "cell_type": "code",
    "execution_count": 227,
    "metadata": {
+    "collapsed": false,
     "scrolled": false
    },
    "outputs": [
@@ -1766,10 +1757,19 @@
     "plot()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Dieses Histogamm zeigt keine Wahrscheinlichkeiten. Definieren Sie die Bins als `arange` ueber den Wertebereich und verwenden Sie `normed=True` oder `density=True` zur Normierung."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 216,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1788,7 +1788,9 @@
   {
    "cell_type": "code",
    "execution_count": 217,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1807,7 +1809,9 @@
   {
    "cell_type": "code",
    "execution_count": 218,
-   "metadata": {},
+   "metadata": {
+    "collapsed": false
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1819,10 +1823,18 @@
     }
    ],
    "source": [
-    "print(argmax(Angriffswert_Magierstab))\n",
+    "print(argmax(Angriffswert_Magierstab))  # argmax liefert nicht das maximum !!\n",
     "print(argmax(Angriffswert_Axt))"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Bemerkung : \n",
+    "-15%"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -1893,7 +1905,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.0"
+   "version": "3.4.6"
   }
  },
  "nbformat": 4,
-- 
GitLab