BraineryBytes_GeometricStiffness_plotModeShapes.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Frame Buckling Analysis in OpenSeesPy</h1>\n",
    "<h3>Authors: Luigi Caglio and Michael H. Scott</h3>\n",
    "<p>\n",
    "    June 2021\n",
    "    <p>\n",
    "    This notebook describes the elastic frame buckling computations developed by Luigi Caglio.<br>\n",
    "    The original idea was posted as a reply to a post in the OpenSees Facebook group and the steps were then summarized in this <A HREF=\"https://portwooddigital.com/2021/05/29/right-under-your-nose/\">blog post</A>.\n",
    "</p>\n",
    "\n",
    "<h2>Computational Procedure</h2>\n",
    "<p>As described in the blog post, the following steps are required in order to compute buckling loads.</p>\n",
    "<h3>1. Define the model</h3>\n",
    "<p>Define a frame model with geometric nonlinearity. This can be either a corotational mesh of elastic elements (either elasticBeamColumn or disp/forceBeamColumn with elastic sections) or elements with geometric nonlinearity \"inside the basic system\" (forceBeamColumnCBDI, dispBeamColumnNL, mixedBeamColumn, etc. with elastic sections).</p>\n",
    "<h3>2. Obtain the material stiffness matrix</h3>\n",
    "<p>Before applying any loads to the model, use printA to get the stiffness matrix.</p>\n",
    "<h3>3. Obtain the geometric stiffness matrix</h3>\n",
    "<p>Now apply reference axial loads to the model, use printA again to get the geometric stiffness matrix.</p>\n",
    "<h3>4. Eigenvalue analysis</h3>\n",
    "<p>Solve the generalized eigenvalue problem using numpy.slin.eig(). The returned eigenvalues give the critical buckling loads and the eigenvectors give the buckled shapes.</p>\n",
    "\n",
    "### Example Frame Structure\n",
    "\n",
    "The computational steps will be demonstrated for the frame shown below.\n",
    "\n",
    "<img src=\"https://portwoodhome.files.wordpress.com/2021/05/framebuckling-1.png?w=605\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "import opensees.openseespy as ops\n",
    "import openseespy.preprocessing.DiscretizeMember as dm\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import openseespy.postprocessing.ops_vis as opsv\n",
    "\n",
    "import numpy as np\n",
    "import scipy.linalg as slin\n",
    "\n",
    "#plt.rc('text',usetex=True)\n",
    "#plt.rc('font',family='serif')\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Units and Material Properties</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "inch = 1\n",
    "kip = 1\n",
    "\n",
    "ft = 12*inch\n",
    "ksi = kip/inch**2\n",
    "\n",
    "E = 29000*ksi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Main OpenSees code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
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       "        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",
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       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
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       "\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",
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       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
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       "            fig.request_resize(ui.size.width, ui.size.height);\n",
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       "\n",
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       "    this._resize_canvas(600, 600);\n",
       "\n",
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       "\n",
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       "\n",
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       "        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",
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       "}\n",
       "\n",
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       "    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",
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       "    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",
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       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
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       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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CIs1et0SYL+Oq02fPh3HH3/81gRhVJQEluTUuXubl5dn6e+Ug3CMIVHmzm+y3cSnQYMG1nFykmIeA08W/p07yekKy09w3ExEBDgT9NQ2TAQyfeeno2umY2RTXHFLgBVTUs+wXIgpTzzxxNacGMxpwVrzEiGQ6wiIAOfoDOAOq98EuCCUbsdgYqN33nkHvHdJkpPLBJgZhVm2qDBZu3atlRmaQjJ63nnnWX/mEXenDY86MXMxPyiQ5DnCJFH33nuvVScwmag5BJh3Y3lHtijxSoD9Slhy9NFHW/oxwRczWLZo0cJKSOUId89Lly5t/ZVEl2SyoHzzzTdWGSXuZHN3l3hS+FGBO+c8fu4IPxSRUFN/flwIQ0SAw0BZYwSBgNt3vhcd3I6RTXElEwKsmFL4bMv2mMKrObyiQ2FyS5JhiRAQAoAIcI7OgnQWEdwtZJ24t956C7NmzbKIBWut8l5kOol+0hnDgZ/BmfdRnBI5JDi5RoCTj6ux5A5LEhUmRR2B5vMvvviildWRO8iFCWv5su+CBDjdI9DHHnssSCDd7gD7UbLizz//3FrDmLvU3K0uKKwLzHrJxRHg5DbcTWdNYJZlmjRpkvVhgQnGeFeZwt1hZt/mIppJvMIQEeAwUNYYQSCQzjtfccU78m4JsGJK8Vhne0xJ3vkV+fX+e6eW2YmACHB2+jWlVakWKtz14u7ab7/9Zh0L5bFkHqEm8eBdx/vvv9/KVlycpBrDact+WRaH5INkg8d1c5EAE490kmDx/it3dwsmweLuL3eB6Rf6p6DwTjWTW/3+++/bEODkJFgk2MyiXFBYXog7okw05ZYAsy+WHWISNpJL7vKzxFIqYVki52gzd375tZ5C4soTDAWFNYo7dOiQNgF22id/VGAmaafG8lVXXYWnn37aqofMxRLvAgctIsBBI6z+g0Ig1TtfcSUz5N0SYMWUbfHOlZiSTH4Zx7gTLBECQiCBgAhwjs6GVAsVJ8PiTTfdZB2ZdVLlkzyRaHGXjGV6WCKmKEk1htPu+uuvt3aak4+s5ioBZoZmHrUtqgwSd0+IOesEn3baadZRXkeYqZjkrahETE72aD5fcAeYpJYfOpYsWVIkueUuaZ8+fazhvBBgJudq3ry5leTruOOOs+ruFpfBmgm8eJSbz1EmT568tSwUM5k3atQo39RjIhN+QCCZpSTPJ9ZCJpEuqkZv8s5xcimjn376yeqTHw9SZXhmIi4ep86UJIsA5+hLOQvMTvXOV1zJzMleCLBiSgLzXIkpyeSXx58ff/zxzCaeWguBLERABDgLnZqOScUtVLjo51HnJk2aWMdd+WyyMJs0j0CnerGmWgyxT5JoEhnWpGWmTkeyjQAzEUtxwuPl3GUkiatfv75FcHmU9/nnn7eONJO48YguSRh3QrlLzt1UPusI769eeuml1l979eqFHj16WMmhmPyJu5g85swxFi1atA0BZhsmxmAbSrdu3cD7wrvuuiu489u/f3/cddddFmFlf14IMPt96qmnrHlDQlmjRg1rt/r000/femyZJJLHpVlyiLbTTo5HYRvOC2ap5okB7vbyZAKFJxN4xIvH5mlfQQLMDza8V84M40x4xXq+zl1h1kSkvbwTTbzYf/K9YmLiJA1p3bo1brvtNgt3zm+See5mk6QzwzRLVzFTththeankLNYsR0Uf87518n0tfhRxU/LKjQ56Vgj4gYDiih8oFt1HMgFWTLFxUkzJP1+IB2OhE8dZxk8iBITAtgiIAOforChuocLkQtz5ZfZN/r+gkGDw+GqqjMGpCDDJA8kvSQsLsicfic02ApxqmpFQ8cMDhYSK96G5K0nh0XASQRJRCo/+8j4qyViykESR5HGnlUL8SXhJsHjsi8SPHzYKS4LF5/kMjw+/8sorVnuSbhIujktfkZBxbBJPrwSY/fIDCo9wJ5dDoo1MQkWyS6JLIUFlIE/OWMnSR2effTa4o0txShjxGD3/TCLKep+U5B1gEuB99913K1xMDEbbuKPOe3IUYjxkyJBtcKXtLB+RvJCgviTLxNbRhX3wg5FzTDuVz52fOzu+qZ73I8N0qjH0cyGQCQKKK5mgl7ptMgFO9bRiSm7GFMZtJ4Y6uSyKmiusIMGP2xIhkIsIiADnote3kKOiskA79x5TQcP7pDNmzCjysVQE2KlLV1jN21wmwASUxIqE67333rOO9JLcckf4hBNOsMhYYXd02Y53Y5mx+LXXXrOOqZMU1qlTxyKsLPPDnWHW/yuOTJEAc8eYO84MpmzPBFtszx3UTAmwoydJ/IgRI6xTANzNoI0777yzdcyZ989ZOol1iQsKd3t5FJtZnEl8eS+ZxJ9Hx2vXrr31xEIyAWbfTAzGf2N7HoVbuHChRbI513g0m7vATn3lwib1xIkTrfrDo0aNstrzuDP1PeCAAyy/8FRE8o58qt8fEeB0EdJzpiBQ3DtfcSVzL3olwIopuRNTCp7YK27WZfIhO/PZrB6EQLQIiABHi39koxe3UHFK4jDj73777Vekjtyxffjhhz0TYO58jR49Ghyn4Et73LhxFsFgWR7uzHHX0u3R0sjA1cBCQAgIgRxEQHElB50uk4WAEBACBiIgAmyg0/xQubiFCskm73/yaMy1117rebhUO8DpHv2kAsmJiTwrpIZCQAgIASEQGAKKK4FBq46FgBAQAkLARwREgH0E06SuiluocPeVO688FvrFF194NisVAS6u42w4Au0ZODUUAkJACBiIgOKKgU6TykJACAiBHERABDgHnU6TU5FTJhL6/PPP0b17d/Tu3TtfaRcmS/rss8+s+6XFHUtONYYIcI5OPpktBIRAViKQ6p2vuJKVbpdRQkAICAHjEBABNs5l3hQePny4RWQdYR1VLlaSa6ny2DMzBVPy8vKser8sEcOSMA0aNEDlypWtzMTTpk2zkhYxOy8JsiNuxxAB9uZLtRICQkAIxAEBt+98xZU4eE06CAEhIASEgAhwjswB1thlBt/iZNCgQVYZHEdWr15tZb1944038Ntvv1nlYnbffXcr6y1rlZ533nn5Shd5GaMofXQEOkcmpswUAkLAWAS8vPMVV4x1txQXAkJACGQNAiLAWeNKGSIEhIAQEAJCQAgIASEgBISAEBACxSEgAqz5IQSEgBAQAkJACAgBISAEhIAQEAI5gYAIcE64WUYKASEgBISAEBACQkAICAEhIASEgAiw5oAQEAJCQAgIASEgBISAEBACQkAI5AQCIsA54WYZKQSEgBAQAkJACAgBISAEhIAQEAIiwFk8B6pVq4aVK1eiRo0aWWylTBMCQkAIBIfA3LlzUb58eSxYsCC4QQzqWXHFIGdJVSEgBGKJgOJK9G4RAY7eB4FpUKFCBaxduxa1atUKbAx1HA8E+KGDwoW6JLsRkK/D9e+sWbNQpkwZLF++PNyBYzqa4kpMHROAWum8a1avBmbPtgcvWRKoUycARVx0uX49MGNGosGBB7ponMOPpuPrOMIzbx6wdKmtWeXK9n8miOJK9F4SAY7eB4FpcNBBB1k7wHPmzAlsDHUcDwS++OILS5EWLVrEQyFpERgC8nVg0BbaMd+jlMmTJ4c7cExHU1yJqWMCUCudd8377wNnnmkPTvI7ZUoAirjo8o8/gH32STTYtAkoUcJFBzn6aDq+jiM0nHucg5R+/YDu3eOo5bY6Ka5E7ycR4Oh9EJgGWqgEBm3sOjY1eMUOSAMUkq/DdZIWKvnxVlwJd/5FOVo675rnngO6drW1bN4c2PItNjK1RYC9QZ+Or731HGwrzrmvvrLHGDAA6Nw52PH86l1xxS8kvfcjAuwdu9i31EIl9i7yTUFTg5dvAORQR/J1uM7WQkUEONwZF5/R0nnX3H03cM89ts7t2gFDhkSrvwiwN/zT8bW3noNtdfjhwA8/2GO8+SbQpk2w4/nVu+KKX0h670cE2Dt2sW8pAhx7F/mmoKnByzcAcqgj+TpcZ2uhIgIc7oyLz2jpvGsuu8zeeaPceCPw4IPR6i8C7A3/dHztredgWx1wQOLO98iRwEknBTueX70rrviFpPd+RIC9Yxf7liLAsXeRbwqaGrx8AyCHOpKvw3W2FioiwOHOuPiMls675pRTABIPSv/+wLXXRqu/CLA3/NPxtbeeg21VrRqQl2eP8e23QJMmwY7nV++KK34h6b0fEWDv2MW+pQhw7F3km4KmBi/fAMihjuTrcJ2thYoIcLgzLj6jpfOuqVcP+PVXW+e33wbOOSda/UWAveGfjq+99RxsKxa+WLXKHmPSJODgg4Mdz6/eFVf8QtJ7PyLA3rGLfUsR4Ni7yDcFTQ1evgGQQx3J1+E6WwsVEeBwZ1x8RkvnXbPzzsB//9k6jx8PNGoUrf4iwN7wT8fX3noOrtWGDUCZMon+6fsaNYIbz8+eFVf8RNNbXyLA3nAzopUIsBFu8kVJE4OXL4bnYCfydbhO10JFBDjcGRef0VK9a1asACpUSOjLmqzVq0ervwiwN/xT+dpbr8G2WrIE2GWXxBiLFwP8IGOCKK5E7yUR4Oh9EJgGIsCBQRu7jk0MXmGCuHnzZvC/bJCvttR8aNasWTaYE6oNJUqUAP9zI1qoiAC7mS/Z9GyquDJtml37l1KqFLB2rf3/KEUE2Bv6qXztrddgW82dC+y9d2KM9euB0qWDHdOv3hVX/ELSez8iwN6xi31LEeDYu8g3BU0MXr4ZX0RHGzduxKJFi7B8+XKsW7cu6OFC63/ZsmXWWBUrVgxtzGwaqGzZsqhQoQJ23XVXlEpjta6FighwNs1/N7akiius+Xv88XaPe+0FkJBELSLA3jyQytfeeg22Fe+e8w46ZfvtE3eBgx3Vn94VV/zBMZNeRIAzQS/mbUWAY+4gH9UzMXj5aP42XZH8zp07F2vWrAlymEj6pm2UdMhbJAoaMmi5cuVQo0aNlDhqoSICbMiU9l3NVHFl8GCgfXt72MaNgTFjfFfBdYciwK4hsxqk8rW3XoNtxfl29NH2GFWrAgsWBDuen70rrviJpre+RIC94WZEKxFgI9zki5ImBi9fDC+ik4ULF1q7vySJVatWRfny5VGyZMkghwytb+0Ae4d606ZNWLlyJfLy8sAPCdwFrlKlSrEdaqEiAux9xpndMlVcue8+4LbbbBtbtwbeeit6e0WAvfkgla+99Rpsq48/Bk4+2R6jVi1g+vRgx/Ozd8UVP9H01pcIsDfcjGglAmyEm3xR0sTg5YvhRXQya9Ys69hz9erVUalSpSCHCr1vEeDMIV+6dCnmz58PHoeuWbOmCLALSBVXXIBl+KOp4sqVVwLPPGMb2b070K9f9AaLAHvzQSpfe+s12Fb84HLeefYYhx0G/PBDsOP52bsIsJ9oeutLBNgbbhm3WrVqFT755BN88MEH+O677zBnzhxrR2L//ffHueeeix49emDHHXfMaBwtVDKCz6jGJgavoABmsqupU6da3deqVQulTcmKkSYgIsBpAlXMYxs2bMCMGTOsJ+rUqVNsYixTFiphxBTipbiS+fwzpYdUceWMM4APPrCtefhh4Prro7dMBNibD1L52luvwbYaOBC49FJ7DOaE/PLLYMfzs3dT4oqfNsetLxHgiDwyYMAAXHbZZdbo/EU48MADwYXtmDFjrKQ9XJSNGjUq5fG84tTXQiUi50YwrInBKyiYeMx1GtOTAqhdu3bWHH128BIBznzmuJkjpixUwogpIsCZzz2TekgVV7jrNnGibdHrrwPnnx+9dSLA3nyQytfeeg221WOPAdddZ4/BjzHDhgU7np+9mxJX/LQ5bn2JAEfkkcGDB2PcuHG47rrrrF0qR/7++2+0atUKEydORNu2bTF06FDPGooAe4bOuIYmBq+gQHZDboLSIch+RYAzR9fNHDFloRJGTBEBznzumdRDqrjCxEMLF9oWffNNIiFRlDaKAHtDP5WvvfUabKtevYC77rLHuPBC4NVXgx3Pz95NiSt+2hy3vkSA4+YRAGPHjkWTJk2w3XbbWbvCvKfmRUSAvWeWI0oAACAASURBVKBmZhsTg1dQSLshN0HpEGS/IsCZo+tmjmTDQsWvmCICnPncM6mH4uIKa/6WK5ewZs6c/DVZo7JTBNgb8iauIW64AXjkEdverl0T99G9IRBuq2yIK+Ei5v9oIsD+Y5pxj7zLxay1FCZq2X333T31KQLsCTYjG5kYvIIC2g25CUqHIPsVAc4cXTdzJBsWKn7FFBHgzOeeST0UF1dmzwb228+2pkQJgBXnPH6r9xUSEWBvcJq4hujSBXjhBdvem28G+vb1ZnsUrbIhrkSBm59jigD7iaZPff3666+oV68eypQpY90H5k6wF+Ev2Pz567Bw4QyUKeOlB7UxBQETg1dQ2LohN0HpEGS/XglwCa5Sk4TJwZghmx/YGjZsiNNPPx1nnnlmkUnD2H7vvfe2EvaZLm7mSDYsVPyKKQ4BXrBgHRYtspOISbIXgeLiyqhRduIhSrVqwN9/xwMHEWBvfjBxDcE752++advLklw9e3qzPYpW2RBXosDNzzFFgP1E06e+mByLCU24IH3//fc998pfsN9+A95+ezLOOcdzN2poAAImBq+gYHVDboLSIch+MyXA7du3t9QjTiwHNH36dCtpGLNnMwv9kCFD0KhRo21MiCsB9qKXmzmSDQsVv2KKQ4AZV6ZPn2zV3pRkLwLFxZXBg4EtrxIceSQwblw8cBAB9uYHE9cQrAHMWsCUp54CWJbLFMmGuGIK1kXpKQIcMw9+9NFHOO2006xdGJZHql+/fkoNnV+kgg+yFuratTXRsOHXePDBn1L2owfMRWDlypWW8s7ReXMt8Udz4sD/9txzz6zLAk3yRilZsqQrsJx6yCS9BeX3339Hr1698O6772KHHXbAxx9/jEMOOSTfYyTKfC/t55x7dDV6cA/Trho1amDSpElpD0IM//rrL/D3xvndKapxp06drLk0efLktPuP04NeYgr1TxVXzjvvI1x++aw4mSpdfEaguLgyePA+ePll+wx0s2Z5uOOOePx+5OWVQ7t2TbYi8dlnX1hHtCXFI2DiGuLqqxtiypRKlmG33DIZJ5yQZ4ybTY8rxgBdjKIiwDHy4pQpU3D00UdjyZIleOyxx9CtW7e0tEu1UAEmY/Dgsdhjj9Vp9aeHzEPAxOAVJMoiwNuiWxwBdp6++uqr8corr1jk9+uvvw7SRb71LQJcNJReY0o6BLhixYl4440xKFvW/iAjyT4EiosrDz1UByNHVreMPv/8P9ClSzw+hogAe5uHJq4hOnVqhD/+2NEyuHfvn9GkySJvxkfQSgQ4AtALDCkCHL0PLA24G0HyO3fuXPTo0QOPOKntMtDPOQJNAnzjjcCDD2bQmZrGGgETjy8FBaib461B6RBkv5kegeZR56KEu8N77LGHtStKAnzMMcdsfbSwo8ZfffUVmjdvDh6r7tu3L26//XaMHDkSCxYswMMPP4zu3btb7Xlv+P7777d2llnqrWLFimjatCnuvPPObXaanQGZubhfv3745ptvsGjRIuy22244+OCDcfHFF+Oiiy7CSy+9hI4dOxZqCvumbkWJmzli6lG1IGIK8UyOKyw7wvIjkuxEoLi40rIl8Pnntt1xOn6qI9De5qKJa4g99wTmzbPt5Z30447zZnsUrUyNK1FgFdSYIsBBIeui33///RfHHnsspk6dai3oBg4ciIIJa1x0t/XR5IXKrrvaLwqP+bS8DK82ISJgYvAKCh435CYoHYLsN0gCTL3btGmD//3vf9aR6DvuuGOrKcUR4FNPPRW//PILNmzYYJHmNWvWWDkMunTpYhFY1jan3nwn1a1bF/PmzbPqoJcrVw7Dhw+3SHSy8AQMPwSSrB9xxBGoWbMmFi5caI3B3X0SavbLXAkvv/yy9W+tW7fe2kWdOnVwyy23FOkGN3PExIVKUDGlIAHm9xFDDgoE+SuZtX0XF1d4/3vmTNv0Dz8EWrWKBwwiwN78YOIaokIFYMUK296ffgLSuDHoDZwAWpkYVwKAIdIuRYAjhR9WlucWLVrg+++/xznnnIM333wTpUqV8kUr/oJNmQJs3mzfzRkyBGjXzpeu1UnMEDAxeAUFoRtyE5QOQfYbNAHu06ePtZPbtm1bDB06NC0CzIfOPvts63mSWkeoa+3ata0dXP4smaR+9tlnFjGuXLkyeAfZqXc+evRoNGvWDBUqVMCwYcOsPzuybt06fPnllzjppJOK1SsV/m7miGkLlSBjCnFN/rDKv//6K/8tFeL6uYkIFBVXmIZg++2Bdetsq+I0B0SAvc0009YQGzcCpUsnbP39d2Dffb3ZHkUr0+JKFBgFPaYIcNAIF9P/2rVrccopp2xd0DHjs7MI9EMt/oLNnbsBK1ZMs7o79lhg9Gg/elYfcUPAtOAVJH6pyA1PABeSBypIlXzpu1Ilu95m0AT4ueeeQ9euXXHyySdjxIgRxRJN5wg0S7Ux6R6PTycLd3Kvu+469OzZE/exTkUB4c/4zNtvv219AKRwN5nj8gj19ddfnxI7ZYFOQBR0TOFIjCszZ27CunVTrIGvuQZ4/PGUbtIDBiJQVFyZPx9I/lVfvhzY0b6KGbmIAHtzgWlriP/+A3beOWHrokXALrt4sz2KViLAUaCef0wR4Ih8sHHjRuuoIbOu8vgz780x+6qfwl+wxYtXY8GC37d2G6cvtX7amut9mRa8gvRXKgJcMHAGqYuffS9ZAuy0U/AE+Nlnn8UVV1xhfZxjBmFHijsC3bhxY4wZM2Ybc7nDyz7Gjx9faGklEl/uCvO4Mu8I873Ind/Vq1dbRJ9/TiUiwDZCYcQUjsO4kpe3FosW2edf+WGG12vKl0/lKf3cNASKiitjxwJNtiRaJukg+YiLiAB784Rpa4iCfl6/Pv+OsDcUwmslAhwe1kWNJAIckQ/69++/NUEMjw4yKUxhwl0QJn/xIvwFYzKbXXaZg4kT7R70td4LkvFvY1rwChJREeDC0XXyChSXBIst7733Xuvu74UXXohXmeVoixRHgM8//3y8/vrr2wxsH5f9LaW7L730UrzwwgvIy8tDtWrVUKVKFevP6YgIsI1SGDGF49CnK1aswpIls8GdP8rAgUCnTul4S8+YhEBRcYW/6m3b2pYceijw44/xsUoE2JsvTFtD/PJL4s4vP745d4G9WR9+KxHg8DEvOKIIcEQ+uPvuu3HPPfekHH327NnYZ599Uj5X2AMOAb711jm4/HL7CX2t9wRl7BuZFryCBFQEuHB00yXA3JHlzizvAt96661bO0uVBZpZmQsKk1FNmzbNOu1S3AkXJs4iCXYIcNWqVa1M0umICLCNUhgxheM4ceXUU+fgmWfssY84ApgwIR1v6RmTECgqrvTtC/TsaVty9tnAO+/ExyoRYG++MG0NweR7Ttbn6tUT2aC9WR9+KxHg8DEvOKIIcPQ+CEwDZ6EyadIc676OvtYHBnXkHZsWvIIELBUB1h3g9Mog8UgzjzY74oUAt2zZEp9//jl+/vnnIssdJc8FHYEO8jfDn76duDJs2Bw0aJDo84cfgMMO82cM9RIPBIqKK1dcATz7rK0jK5316xcPfamFCLA3X5i2hmDm8dNPt22tUwdWwleTRAQ4em+JAEfvg8A0cBYqLBly5ZXQ1/rAkI6+Y9OCV5CIpSLAQY4dRt9BJsHiLizLsLH00IQCW3peCDBrAzMBFk+7sOZvOuIkwWItdJZCSiVMHMgj06x7m664mSNaqORHNTmu8B4o74NSunQBnnsuXQ/oORMQKCqunHoq4OTHI/ndUu47FiaJAHtzg2lrCBYocGqQH3kkMG6cN7ujaqW4EhXyiXFFgKP3QWAaJC9Ufv4Z+b7Wf/890LBhYEOr45ARMC14BQmPG3ITpB5B9R0EAWYZIhJVlmFjTd2xY8eiXr16+UzwQoCXLFlilUGizs888ww6dOiQr8Y5cxTwuDVLwe25557WeKNGjbLqAleqVAnMjM8kgY6sX78enOvJZZB4RYR1hf/55x/sxCxhaYibOaKFStEEePBgoH17++e8h8fswEWks0jDK3okbggUFVcOPDCx48bjzzwGHRcRAfbmCdPWELx+wY0dyoknAh9/7M3uqFoprkSFfGJcEeDofRCYBskEmIMkf62/7DLg+ecDG1odh4yAacErSHjckJsg9Qiq70wJcPstjIU4sa/p06dj6tSpYHKsWrVqWfV6Dz/88G3U90KA2cm3336LM844A4sXL8bee++Ngw8+GCybNHfuXEyZMsVK1Ddx4kQ0SDpPy+R/N954o6VDo0aNULNmTSxcuNA6Sk2CzlMtjlx77bV44oknsO+++6JJkyZWHWKSbqd9YX5wM0e0UMmPYHJcWb3aLofDDOWUp58GeDxWkh0IFBZXeIWEJY9WrbJtZAIsJsKKi4gAe/OEaWuI5HvobdoAb77pze6oWimuRIV8YlwR4Oh9EJgGBQlw8td6Vlxi6Yo0N0wC01Ed+4OAacHLH6sL78UNuQlSj6D6zpQAO3qVLl3ayj5fvXp1NGzY0CKp/I//Xph4JcDsa/78+Xj00UcxfPhw/PHHHyhVqpQ17qGHHmrV/z3rrLO2qYHOneB+/fpZ5ZX+++8/65gzyfMll1yCdu3abVWRBJpllIYNG4a///4bGzZsQNOmTcEaxUWJmzmihUp+FAvGleuuAx57zH6mfn1YFQdYr1piPgKFxZV//wUqV07YFrf6qyLA3uadaWsIJmEjCaZceinwwgve7I6qleJKVMgnxhUBjt4HgWlQcKHCr/U8Zbh4sT3ko48CXLxIzEfAtOAVJOJuyE2QegTVt1cCHJQ+JvbrZo5ooVI8AZ46FahbN/EMy0En5U4zcXpI5y0IFBZXmOzMOSDCneBly+L1wUME2Nv0NW0NcdVV9okTClNFPPKIN7ujaqW4EhXyIsDRIx+CBgUJMIe8+WbgwQftwWvWBKZPB0qWDEEZDREoAqYFryDBcENugtQjqL5FgDNH1s0c0UKleALMnzZvDjgb7hddBLzySuY+Ug/RI1BYXOFR0/PPt3U75BCA+UXiJCLA3rxh2hqC75khQ2xbWVE0zRyL3sAJoJXiSgCguuxSO8AuATPp8cIIMIPDfvsBmzbZlgwfDjCjo8RsBEwLXkGi7YbcBKlHUH2LAGeOrJs5ooVKagL81lvAeefZz5UtC8ydC1Stmrmf1EO0CBQWV+67D7jtNluvuNUApk4iwN7mjGlrCJZAYikkCq9gdOvmze6oWimuRIV8YlwR4Oh9EJgGhRFgJ2i995497MknJ8oZBKaIOg4cAdOCV5CAuCE3QeoRVN8iwJkj62aOaKGSmgCvXw/ss4+dBZrSuzdw++2Z+0k9RItAYXGlc2fgxRdtvW64AXjooWh1LDi6CLA3f5i2hjjuOODrr21bBw0COnTwZndUrRRXokI+Ma4IcPQ+CEyDogjwF18Axx+fGJbHoGvVCkwNdRwCAqYFryAhcUNugtQjqL5FgDNH1s0c0UIlNQF2SK9zDJGZoWfPBsqUydxX6iE6BAqLK02bAqNH2zqxFE3XrtHpV9jIIsDe/GHaGoIJ9375xbY1bqW40vGA4ko6KAX7jAhwsPhG2ntRBJhlDA4+GPjtN1s9Hh1xsnhGqrAG94yAacHLs6FpNHRDbtLoLnaPiABn7hI3c0QLlfQI8IIFQI0aAHeDKTwW3bp15r5SD9EhUFhcYSJNVpCgfPop0LJldPqJAPuHvWlriH33BZxqeJ99ln9Txz9UgutJcSU4bNPtWQQ4XaQMfK4oAkxTkouIV6xoBzRmdJSYiYBpwStIlN2QmyD1CKpvEeDMkXUzR7RQSY8A86nkxDTcKSymElXmTlQPgSNQMK6wkgRLKDry++8AiUicRDvA3rxh2hpil10S9ce/+y6Rmdyb9eG3UlwJH/OCI4oAR++DwDQojgCvWGGXRFq61B6e6eSvuCIwVdRxwAiYFryChMMNuQlSj6D6FgHOHFk3c0QLlfQJ8Lhx+UsgMUMwMwVLzESgYFyZPNk+PUZhuXAS4iLKhkdmsAiwN+hNWkPwFCOvV2zcaNtq4jU+xRVv89TPViLAfqIZs76KI8BUlTWAnaPPBx4I/PprvOr5xQzOWKtjUvAKGkg35CZoXYLoXwQ4c1TdzBEtVNInwFyYHnEEwFqxlC5dgOeey9xf6iEaBArGlfffB84809aFeUNIPOImIsDePGLSGoIbOBUqJOzMywOqVPFmd1StFFeiQj4xrghw9D4ITINUBHjGDOCAAxLDm3iPIjDwDOvYpOAVNLRuyE3QugTRvwhw5qi6mSNaqKRPgPnkSy8BHTvabXhc9q+/gJ13ztxn6iF8BArGlX79gB49bD3iWkFCBNjbPDFpDcFs80y058iaNcB223mzO6pWiitRIS8CHD3yIWiQigBTBdYAHjHCVuass4B33w1BMQ3hOwImBS/fjS/QoRtyE7QuQfQvApw5qm7miBYq+fFOFVd4LHavvYBFi+x2jz5qnzaSmIdAwbhy1VX2dSkK//zkk/GzSQTYm09MWkNMmQLw1CKFdcfXrvVmc5StFFeiRN8eWzvA0fsgMA1SLVQ4MMkvSTClZElg1iy7nqPELARMCl5BI+uG3AStSxD9iwBnjqqbOaKFSn6804krPXsCffva7WrWtI/KMr5IzEKgYFzhru/HH9s2cDe4e/f42SMC7M0nJq0hknMNVK4MLFzozeYoWymuRIm+PbYIcPQ+CEyDdBYqmzYBtWsDM2faalx/PfDww4GppI4DQsCk4BUQBFu7dUNugtYliP5FgDNH1c0c0ULFPQEmCdlvP4DxhTJ8eOJDa+beUw9hIVAwruy/v/2RnML7wKefHpYm6Y8jApw+VslPmrSG4EcYfoyhcE7yOp9porgSvcdEgKP3QWAapEOAOfgTTwDXXmurwZJIf/5p/19iDgImBa+gUXVDboLWJYj+RYAzR9XNHNFCJT/e6caVs88G3nvPbnvKKcBHH2XuN/UQLgLJcWXDBmD77QH+n8KM0M4x1HC1Kn40EWBv3jBpDcEa4+edZ9vZsCHw/ffebI6yleJKlOjbY4sAR++DwDRId6FSsCRSXI82BQZUFnRsUvAKGm435CZoXYLoXwQ4c1TdzBEtVLwR4M8/B1q2TLSdNi1/0sXMvagegkYgOa6w5i+Ps1sLxxLAqlVAuXJBa+C+fxFg95ixhUlriAEDgMsus+1s3py6e7M5ylaKK1GiLwIcPfoBa5AuAaYaN90EPPSQrRDvAPNISdzq+wUMl9HdmxS8ggbaDbkJWpcg+vdKgEtw1ZpC2rdvj5eYxneL7LPPPvjjjz+wmfVtskjczBEtVPI7Pt24wilz0EEAE9ZQ4po0KYumte+mJMeV5GOne+5pnxSLo4gAe/OKSWuIRx4BbrjBttPU5K2KK97mqZ+ttAPsJ5ox6yvdhQrVZjDbd99EYXEeMWndOmYGSZ0iETApeAXtRjfkxg9d8vLyMGDAAIwaNQrLly9HhQoV0KxZM3Tu3BlVq1b1Y4h8fWRKgElyi5JjjjkGl1566dYfiwCTxB1k4TGZZz4lFh4rV67EnDlzUqLBGsBdu9qPqSRSSrhi90ByXOnfP5H06vjjAZZNjKOIAHvziklriDvvBHr3tu1kOEv6ZuvN+AhaKa5EAHqBIUWAo/dBYBq4WahQiXbtgNdes9Vp3BgYMyYw1dSxzwiYFLx8Nn2b7sIiwKtXr0a3bt2sHdP169dvo0eZMmXQsWNH9O/fH+V8PCuYKQF2s5s7a9Ysy7Y6deoE7bZQ+3czR7RQye8aN3GFx2RZEmnxYruPBx6wTxtJzEAgOa5ceSXwzDO23nHezRcB9ja3TFpDdOsGPP64bSfz1/DjjGmiuBK9x0SAo/dBYBq4WahQCSYSOOKIhDokwCTCkvgjYFLwChpNN+TGqy4kv6eccoq165tKmjZtihEjRmB7ZpDxQcIkwD6oG8su3MwRLVTyu9BtXLntNuC+++w+eHSWd0nLlInltJBSBRBIjistWgBffmk/wMSZV18dT7hEgL35xaQ1RMeOiV3fO+4AevXyZnOUrRRXokTfHlsEOHofBKaB24UKFTnuOODrr22V2rQB3nwzMPXUsY8ImBS8fDS70K7ckBuvunTp0gUvvPBC2s35/HM8D+qDhEmAizsC/eabb+Khhx7Cr7/+iooVK+LUU09F3759cfPNN+Pll1/Gl19+aR0FT5Z//vkHDzzwAD744APrbjE/Chx11FHo2bMnjuPLJ0m++uorNG/eHDyy/eijj+K2227De++9h8WLF6NWrVro0aMHOnXq5AlRN3NEC5X8ELuNK/Pn23klnEMSPGV0wQWe3KZGISOQHFeqVwf+/ttW4NNP8yc4C1mtYocTAfbmDZPWEOecA7z7rm0nc9c494G9WR5NK8WVaHBPHlUEOHofBKaB24UKFWHZCpavoJQsadf84+JFEm8ETApeQSPphtx40WXBggWoUaNGoceei+qPx6H//PNPX+4Ex4EAP/bYY7juuutQqlQpi+Tutttu+Oabb0A7DznkELz//vvbEOCpU6eiZcuWmDdvHmrWrGk9t2jRIowbNw4bNmzAK6+8gna8h7FFHAJ85plnYsqUKVi6dCkaNWqEFStWYPTo0di4caP1ESL5znK6/nQzR7RQyY+ql7hy8cXAq6/a/TRqBIwbZ2cSlsQbASeuNGzYAjvtlNCVOUO4mx9HEQH25hWT1hC8g+5kfn7++URGaG+WR9NKcSUa3JNHFQGO3geBaeBlobJxI1C7dqLY/XXXAY8+GpiK6tgnBEwKXj6ZXGQ3bsiNF1369OmD22+/3XVTtrv11ltdtyvYIGoC/Pvvv6Nu3booWbIkPvnkExx77LGWimvWrEHr1q0xfPhw6+/JO8Akqw0aNLB2i3kn+pprroGTlXrixIk44YQTrPbsu0qVKlZ7hwDzz+eee661q1y+fHnrZ8OGDcNZZ51lfYjgTrJbcTNHtFDJj66XuPLjj3a9Tke+/RZo0sSt1/R82Ag4cWXHHVvgyCPt0fkruHx5fD9giAB7myUmrSEOPxz44QfbzjfeSNQE9mZ5NK0UV6LBPXlUEeDofRCYBl4WKlTmySeBa66x1apQwc4QXalSYGqqYx8QMCl4+WBusV24ITdedDnxxBPxKc8AuhSSPBLGTCVTAlzc+O+++65FLB0p7Ag0yT/J/OWXX45nn302X3dMmnXAAQeAPkgmwDy6fPbZZ6Nt27YYOnToNiqQFHfv3h2PPPKIdbSZ4hBgHq+ePXs2dtlll3ztuIM8adIk62fU0424mSNaqORH1mtcadoUGD3a7osVBlhpQBJvBJy4Mm9eC1xyia0rP2QwX0hcRQTYm2dMWkMccIBdqpMyciRw0knebI6yleJKlOjbY4sAR++DwDTwulBZscLO3Pnff7ZqDz8MXH99YGqqYx8QMCl4+WBusV24ITdedGncuLF1bNet8K7r2LFj3Tbb5vlMCXBxZZCuvfZaHHbYYVvHLIwAt2jRwiK3n332GY7nWbQCcvjhh+OHH37IR4CvuuoqPP3003jjjTdw3nnnbdOGz7PdBRdcgNe2pKJ3CDDH+/zzz7dpw93mt99+G2PGjAF94kbczBEtVPIj6zWu6HqNmxkaj2eduPL55y22JjK78MLEcfZ4aJlfCxFgb14xaQ3B6oILF9p2mpqsVXHF2zz1s5UIsJ9oxqwvrwsVmnHLLXbJCgrJMO8CK3NnzBycpI5JwStoFN2QGy+6mL4D7KYMUmEEmCWRpk2bZv3H3d6Ccs4554A7yck7wK1atcJHH32UEm7eEXZ21x0CfMkll1jHnwtKhw4diky2lWogN3NECxV/CDCv13C6MAs0hRv9jzySylP6eZQIOHHlqada4J13bE2YcZeZd+MqIsDePGPKGmLzZoBVBdets+2cMgUwsUqf4oq3eepnKxFgP9GMWV+ZEOB584B9901k7uT60zkCFTMzpQ6YEOILCwfuluW6uCE3XrDK9TvADgGePn26lY25oPCoM488JxPgk08+GR9//LFVOsq541sY9uz7Fn59SzoCzR1r1louKCLAXmZv5m0yiSus3ckanpSKFYG//rKv2UjiiYATV665pgV++83WkZUhWCEiriIC7M0zpqwhVq8GdtghYSMzk1er5s3mKFuJAEeJvj22CHD0PghMg0wWKlSKFUYGDbLVO/BAYNIkOzO0JH4ImBK8wkAuaAKc61mgWZqIu7NujkAzU/PAgQOt5FVnnHFGWtMguQySCHBakIXyUCZxhcmTmD142TJb1X79gO7dQ1Fbg3hAgHFl48YSaNWq+dYyVr/8AtSr56GzkJqIAHsD2pQ1BAkvS3I5QkLMHWHTRAQ4eo+JAEfvg8A0yGShQqV4tOSggwAeOaG8/z5w+umBqauOM0DAlOCVgYlpNw2aAFORXK4DzHq89913H7p27Ypnnnkmn1+YxZm7wgWTYL3++utWAqyOHTvixRdfTMuXIsBpwRT6Q5nGFdbsdI4+16gBzJyp6zWhOzHNARlX/vpre7Rvb9+xZ+mqVaviTThEgNN0boHHTFlDcF3KDRnKdtux+oA3e6NuJQIctQe0Axy9BwLUINOFClVjTWAmL6EcfTTwzTcBKqyuPSNgSvDybKCLhmEQ4NWrV1vHeUeNGpVSs6ZNm2LkyJEo59Nn6kyTYGV6B3jmzJk48MADrRrATE7VZEs9G5YxYoKrDz74wMIk+Qg06/zWq1fPujd8//33W5meWTPYkXXr1uHDDz+0yDOfo4gAp5xakTyQaVxhVYH99gM2bLDVHzIESCr/HIlNGrRwBBhXxozZDXfccYj1AK9FOXe444qZCLA3z5iyhmAeSaeEGpNhLVjgzd6oW4kAR+0BEeDoPRCgBpkuVKgak90mJ1j9+mvgmGMCVFpde0LAlODlyTiXjcIgwFSJJJilewYNGoT169dvoyUJHnc8WeLHL/LLQTIlwMVlgWZdHYrEMQAAIABJREFU3V7McrNFCkuCxR89/PDDuPHGGy0SzCPRu+66K7799lurNnD9+vUtEsy/O+SYbaZOnYqTTjoJc+fOxe677w6WMWKJoz///NP62X///Wclz3LKMIkAu5z4IT3uR1xp3x4YPNhWuH59YOLE+NaVDQnWWA7DuDJkyN548cWaln48AcaTYHEWEWBv3jFlDTFiBHDqqbaNtWszrnizN+pWIsBRe0AEOHoPBKiBHwsVqtesGeBsdJ12GrBlgydAzdW1WwRMCV5u7fLyfFgE2NEtLy/Put9KwrZ8+XJUqFABzZo1Q+fOnVGVn6h9lkwJcHHqkLz+9NNPWx8pigDzAR5rfuihhzB58mSLyDLR1QMPPABmbeb9YJLa2lyhJMmSJUvw+OOPW0SXO8ncjSYZ5ruKybNY2mjHHXe0WogA+zxxfOrOj7jy66/575GaWsvTJ0hj2w3jSu/eB+Grr+z32K23An36xFZdSzERYG/+MWUNwSp5zomRI4+0N2lMFBHg6L2mO8AR+YB1L1nuY8KECRg/fjzmz5+P7bbbDjxG6Jf4sVChLslf3Ph3JsM6+GC/tFQ/fiBgSvDyw9ZUfYRNgFPp4/fPvRJgv/UorL+VK1eCpJm740uXLrV2iOMobuaISQsVk+IKP6YOH27PDiavL6TUcxynTk7pxLjSqVMj/PGH/VGK5OOCC+INgQiwN/+YsoZg2okrr7RtPOkkgB/PTBST4oqJ+KajswhwOigF8AyP+TEjarLElQAzCVaDBgCzP1IuvjhxfC0AaNSlBwRMCV4eTHPdxA25cd15DBrEgQAz2RWPPVeqVGkrIitWrMAVV1yBV199FZ06dbJ2xeMqbuaISQsVk+LK6NFA06aJGfLdd8Dhh8d1xuSmXiNHfonTTmuKjRvt8g/cuWdizDiLCLA375iyhrjvPuC222wbzz+fJ5G82Rt1K5PiStRYBTW+CHBQyKbol0cFV61ahSOOOML6r1q1arHdAaYpQ4cCF15oG8VNnVmzgL33jgg8DbsNAqYErzBc54bchKGP32PEgQD37dsXd999Nxo2bIg999wTPNo8ceJE/Pvvv9YO8Lhx4wI5/u0Xlm7miEkLFZPiCj+sMr/E+PG2V1lbljVmJfFB4IUXxqNLlyMthZizbuXK+GfsFgH2Nn9MWUPcdBPw0EO2jV27AgUKEXgzPoJWJsWVCOAJZUgR4FBgTj1IiRIlYk2AmbGzVi1gzhzblmuuAR5/PLVdeiIcBEwJXmGg4YbchKGP32PEgQB/9913eOSRRyyiu3DhQusuLxNonX766bj55ptRuXJlv832tT83c8TkhUrc48o77wDnnmu7ljXmp00D9t/fV1erswwQuPXWybj/fnvL95BDgJ9/zqCzkJqKAHsD2pQ1RJcuwAsv2Dbecgtw//3e7I26lclxJWrs/BpfBNgvJDPsJ+4LFZr31FPA1VfbhrKiC8lwADl+MkQyN5ubErzC8I4bchOGPn6PEQcC7LdNYffnZo6YvFCJe1zZuNGu6Tl9uj0DrrgCePrpsGeDxisKgbZt/8Drr9tHvZh4iCWr4i4iwN48ZMoa4rzzgLfesm3s2xe4+WZv9kbdyuS4EjV2fo0vAuwXkhn2E/eFCs1bvRrYZx9g4ULb2BtvBB58MEPD1dwXBEwJXr4Ym6ITN+QmDH38HkMEOHNE3cwRkxcqJsQV7uZwV4fCD6skMFWqZO5j9ZA5Akcd9S/Gj9/N6og7bdxxi7uIAHvzkClriBNPBD791Lbx2WeByy/3Zm/UrUyOK1Fj59f4IsB+IZlhPyYsVGjiww/bxJdSvry9C7ybHR8lESJgSvAKAyI35CYMffweQwQ4c0TdzBGTFyomxBUWPuCH1bw826+33w707p25j9VD5ghUrboGCxeWszr68EOgVavM+wy6BxFgbwibsoZo1AhgwjwKE2AxEZaJYnJcMRHvwnQWAY6JJzNZqDi/SAVNmTVrFqpUqYKXXnrJNytXry6Fdu0aY9myslaf7drNQefOv/vWvzryhgDLz1DK86uExMKB/zFBU0leLswiIXmjZJtdYbqIGP7111/g743zu1PU+MxozbnEesemiSlx5bXX9saAATUteCtUWI8hQ8agfPmNpsGdVfquWFEaZ5553Fabhg79FlWrro29jXl55dCuXZOten722RcoUSL2akeuoClriEsuOQrz5u1g4dW370844ojFkWPnRQGT44oXe+PYRgQ4Jl4xZaFCuIYO3RsDB9qLlR122IChQ8egQoUNMUEyN9UwJXiF5R2HAO+xxx6xrUXrFQsRYK/IJdpt3LgR8+bNEwEuBsowP6ySbLVt2wSrVpW2NLr00plo23Zu5o5WD54RmDSpErp3b2i1L19+PYYN+9oIIikC7M3lpqwhzj33GPz3n70B8+ST36Nu3WXeDI64lQhwxA4AIAIcvQ8sDTIhwEWZwAUMX2pznNTNPtm6bJl9ZG3JErvDu+4C7r7bp87VjScETDm+5Mk4D414+mHdunWoXr16vlq1HrqKXRMdgc7cJUuXLsX8+fNRtmxZ1Kxpf8wr7j3Kn+XaDnDYcaVnTzupDYVJxBm2drA3eiQRIPDkk3a1B8oxxwBffx2BEh6G1BFoD6ABMGENwdJp220HrF9v2zh1KlC7tjd7o26lI9BRe0AEOHoPbNHAJAJMlXv1sokvZaed7MVKpUqxgTPnFDEheIXpFJbmWbRokbX7W7VqVesIa7YcGRYB9j6TuHvOj4J5eXngLvCuu+5qXRMpTkxeqJgUV/75x64tz2SLlH79gO7dvftaLTNDoFMnYNAgu49rrwX698+sv7BaiwB7Q9qENQRveu24Y8K+BQvMrURiclzxNsPi10o7wDHxiUkLFUL233/2YoW7wZR77wVuuy0mYOagGiYErzDdQnIzd+5crGGGnSwT2kYhuZd4R6BcuXJW7eJUOJq8UDEtrvToYRNfSvXqwKxZdmZoSfgI1K8P/PKLPe7LLwOXXBK+Dl5GFAH2gpoZO8Dz5gF77pmwj+GdO8ImislxxUS8C9NZBDgmnjRtoULYmK2zTx8bwF12sXeBK1SICaA5poYI8LYOJ1HkLvDy5cut49DZItoBzsyTPPZcoUIFa/c3FfnlSCYvVEyLK/PnA/vtB6zdkmuJNYFZG1gSLgIkFtxp2/KtDZMmAQcfHK4OXkcTAfaGnAlrCOYhdObh9tsDq1Z5szUOrUyOK3HAzw8dRID9QNGHPkxbqNDkRYvsXeAtCYjxwAPATTf5AIa6cI2ACcHLtVE+Nti8eTP4XzbIV199ZZnRrFmzbDAnVBv4nuV/bsTkhYqJceWqqwASX0qNGsDMmUCZMm48pmczRWDCBODII+1etttuI1asKIXSdn6y2IsIsDcXmbCG+PZb+z46ZffdAX4wM1VMjiumYl5QbxHgiDw5fPhw9E4qdjh+/HhrYdaIRc62yB133IFWGRTeCyoJVjJkN98MPPig/S+sBzx7dv47GhHBm3PDmhC8cs4pARksXwcEbBHdmrRQyYa4MncuwLxkG7YUFhg4EOB9VEl4CDz7bGLnvW7dpfjtN3MSfIgAe5snJsSV4cOB006z7atbF/jtN2+2xqGVSXElDngFoYMIcBCoptEna/N27Nix2CcHDRqEDh06pNFb4Y+EQYAXLgT23TdxFIVHom+91bPKaugRAROCl0fT1KwAAvJ1uFPCpIVKtsSVSy8FSHwp++8PTJkCY3Ygw52dwYx22WXAgAF232ec8ReGDUu6eBnMkL71KgLsDUoT4sqQIcBFF9n2NW4MjBnjzdY4tDIprsQBryB0EAEOAtWY9BkGAaapyeUrmBGau8D8vyQ8BEwIXuGhkd0jydfh+lcLlfx4hxFXmPzqgAOATZvssV99FbjwwnD9nsujNWwI/PijjcANN0zBQw/VNQYOEWBvrjIhrjz1FHD11bZ9p5wCfPSRN1vj0EpxJXoviABH74PANAhjoULlFy+2d4GdjNB33GGXSZKEh4AJwSs8NLJ7JPk6XP9qoRI+AeaIF19sE18KjzsyEZMSnwc/95mAjMksnVqrzz03AV26JK5mBa9BZiOIAHvDz4S4whOGTL5KadsWGDrUm61xaKW4Er0XRICj90FgGoRFgGnAPfcAd99tm8LskdwF5p1gSTgImBC8wkEi+0eRr8P1sRYq0RBgHns+6CDAyV3HxS4XvZJgEeDOL3eAKWXKbMIHH4zCSSc1D3ZQH3sXAfYGpglx5cYbgYcftu1jdngnWZ43i6NtpbgSLf4cXQQ4eh8EpkGYBJi7v9wF5m4whS8qJzlWYAaq460ImBC85C5/EJCv/cEx3V60UImGAHPUCy4A3njDHp9HolkGxZRsxOnOr7g999xzQNeutla1ay/D009/jxYtWsRNzSL1EQH25ioT4kpybgBevbvvPm+2xqGV4kr0XhABjt4HgWkQJgGmESS8zApNYY023uNiqnpJ8AiYELyCRyE3RpCvw/WzFirREeCpU+1dYOcu8EsvAe3bh+v/XBuNeTdfftm2+swz/8K1104XAc6BSWBCXGndGnj7bdsZppfdVFyJ/pdKBDh6HwSmQdgEmPWAWb4iL8826ZprgMcfD8w8dZyEgAnBSw7zBwH52h8c0+1FC5XoCDBHvuQS4JVXbB322w8gKVZd4HRnr/vnatcGpk+32/XsORktW+aJALuH0bgWJsSVli2Bzz+3oeVJhS5djIN5q8KKK9H7TgQ4eh8EpkHYBJiGkPB262abVLYsMGMGUKNGYCaq4y0ImBC85Cx/EJCv/cEx3V60UImWAM+cCdSpA2zcaOvxwgsAj0JK/Edg0aL8uTteeWUsqldfLQLsP9Sx69GEuHL44cAPP9jQvfkm0KZN7GBMWyHFlbShCuxBEeDAoI2+4ygI8Jo1QK1awF9/2fZ37pyoJxg9ItmrgQnBK3vRD9cy+TpcvLVQiZYAc/Tku3/8oModyu22C3ce5MJoLCvTqpVtaeXKwGuvfYESJSACnAPONyGusCY4r9ZRPvkEOOEEcx2juBK970SAo/dBYBpEQYBpzPPPA5dfbpvFshW//mp/wZcEh4AJwSs463OrZ/k6XH9roRI9AWZiI35YdUrzsB7olVeGOw9yYbQ77wR697YtPeMMnub6wvqzkmBlv/dNiCusLMJTCpQJE4AjjjDXL4or0ftOBDh6HwSmQVQEmIsU1m10vtSddRbw7ruBmamOAZgQvOQofxCQr/3BMd1etFCJngBTAxLeZ56xdaleHeDRaCZblPiHAHfUPvvM7o8Zdo88UgTYP3Tj3VPc4wrLofHuv3MVgqdA+FHMVFFcid5zIsDR+yAwDaIiwDSI9zPOPz9h2jffAEcfHZipOd9x3INXzjvIRwDkax/BTKMrLVTiQYDnzbOTLK5da+vTrx/QvXsaDtQjaSFAYrHzzsDy5fbjX37J7NsiwGmBlwUPxT2urFgBVKiQAHrhQvuYvqmiuBK950SAo/dBYBpESYD5te7II4HvvrPNa9IEIAnmfSKJ/wjEPXj5b3Hu9ihfh+t7LVTiQYCpBQlv//62PjwOyVNGFSuGOx+ydTReVapXz7auZElg6VIeMxUBzlZ/F7Qr7nGFeWX22iuhNT+EMdGqqaK4Er3nRICj90FgGkRJgGnUV18BzZsnzOMxaB6HlviPQNyDl/8W526P8nW4vtdCJT4EmCX2WApp1SpbJ95ZveeecOdDto7GsjJdu9rWNWgATJxo5tUa3hffZ5+El1hDWh/eU8/auMeVSZOAQw6x7dhhB4BlN00WxZXovZc1BHj9+vWYNm0a/vnnHyxduhSVKlVC5cqVUbt2bZTJ0aKBURNgTu/TTgOGD7cnOusL8itz6dLRT/xs0yDuwSvb8I7SHvk6XPS1UIkPAXZIr5OoqXx5+y5wtWrhzolsHK1tW+D1123LrrnGLmlo4rtGBNjb7Iy7r7/+GjjuONs25gDglQiTRXEleu8ZTYBJdl966SUMHz4cEyZMwFrnclASruXKlUOjRo3QqlUrtG/f3iLFuSJxIMAkvPXr8y6RjfqzzyYyROeKH8KwM+7BKwwMcmUM+TpcT2uhEi8CvGyZfRf4339tva64Anj66XDnRLaNxitLe+wB/P23bdn//gece64IcLb5uTh74h5XPvjAzkxOOfBAYPJks72juBK9/4wkwDNmzMCdd96Jd999F+vWrbNQ3G233azd3l122QUVK1a0doGXLFmCqVOnYtGWvOlly5bFOeecg169emF/FhTLcokDASbEnToBgwbZYPNL/YwZwI47Zjn4IZsX9+AVMhxZPZx8Ha57tVCJFwGmNtyd7NbN1oul9n77DTjggHDnRTaNxoy6PKHliJNgyMR3jXaAvc3MuPv6lVeASy6xbWNOmW+/9WZnXFoprkTvCeMI8DXXXIPnn38eGzduRPPmzdGuXTs0a9YM++67b5Fo/v777/jyyy8xdOhQjBo1CqVKlUKXLl3wxBNPRO+BADWICwFm8gKmq1+zxjb27ruBu+4K0PAc7DruwSsHXRKYyfJ1YNAW2rEWKvEjwPzuzdrys2fburVpY1cekHhD4PnnEyezDj4Y4H1LionvGhFgb3Mg7r7mcv3aa23bWrUCPvzQm51xaaW4Er0njCPAO+ywg0Veb7rpJlTnRQCXMm/ePDz44IMYMGAAVpp+iz6F7XEhwFSzZ0+gb19bYSYw4BdnHrmS+INA3IOXP1aqF1MXpSZ7TguV/N6LS1x57TWgXbuEbuPHA40amTzTotP9wguBoUPt8a+6CnjySfvPJsYVEWBv8yjuvua9fya9o3C+vvqqNzvj0kpxJXpPGEeAFyxYgGo+ZLzwq5/oXVi0BnFZqFBDllTgLvA//9j6XnQRwCMtEn8QiHvw8sdK9WLqotRkz2mhEk8CzLwShx9uZyumNG1q165Vxl93v228/7vnnsD8+Xa7t94CWrcWAXaHovlPx30Ncf31wKOP2jgnf6QxFXnFleg9ZxwBzgQyHn9uyiiZIxInAkzIk49Z8e9jxwJHHZUjzgjYzLgHr4DNz6nu5etw3a2FSjwJMLX69FPgxBMT+g0blkiUE+4sMXc05uRIvj/NUlNVqogAm+tRb5rHPa4k55K59VagTx9vdsalleJK9J4wjgA/+uij6NGjh2vkRo4ciXPPPTfrjz0nAxM3ArxxI9CwIfDzz7aWRx4JjBkDlCzp2p1qUACBuAcvOcw/BORr/7BMpyctVOJLgKkZCTCJMIWnjFh5oGzZdDyrZ4hA8ofpgtl1TXzX6Ai0t3kdd1+ffTbw3nu2bQ8/DHBH2GRRXInee8YR4JIlS6JPnz7oyUulacqwYcNw/vnng7WCmTwrVyRuBJi4f/UV0Lx5wgM8Bs3j0JLMEIh78MrMOrVORkC+Dnc+aKESbwLMhE0NGiRK7T3yCODhG3m4kypGo7Hc0Tvv2ApdfTWQnBvUxHeNCLC3yRV3XzdrBowaZds2cKBdXcRkUVyJ3ntGEuASJUrg1ltvRW/eik8hr732Gjp06GCRX7YTAU6FWPA/Tw64TIQ1bRpQvnzw42bzCHEPXtmMfdi2ydfhIq6FSrwJMLW78krgmWdsPStVskvtVa4c7jwxcbT161lCEmBtZcrw4cCppyYsMfFdIwLsbSbG3deHHJLITv7uu8BZZ3mzMy6tFFei94SxBJjQXXfddXiYZyGKkBdffBGXX345Nm3ahM2bN4sARz/fLA1+/x2oWxfYUsIZd9wB9OoVE+UMVSPuwctQWGOptnwdrlu0UIk/AWZyRR5/ZrJFSteuCUIc7mwxa7SvvwaOO87WmcfGFy/O/zHaxHeNCLC3ORh3X++1F8CSmhSeJDQ9nY/iird56mcr4whw5cqVsXjx4q2E9oorrsCTTs7+JGT4b927d7fIL3d+SYDbtGmDN954w0/8Yt1XHI9AO4All0UqVw6YOhXYe+9Ywxlr5eIevGINnmHKydfhOkwLlfgTYGrYr1/i6DPzSjA7NHeNJEUjcPvtiWRCLVsm7lI7LUx814gAe5vxcfc1TwmuWmXb9ssvQL163uyMSyvFleg9YRwBnjx5Mlq2bImFCxduJcEdO3a06vo6wjq/vCPs7Pry/xdffDEGDRoE3iHOFYkzAV6+3M48uWCB7Y1zzgHefjtXPOO/nXEPXv5bnLs9ytfh+l4LFTMIME8UcVHMGvOU44+3CZ3KIhX9+8IyUj/8YP/8oYeAG27I/6yJ7xoRYG/vxzj7eu1agBsljvz5p126y2RRXInee8YRYEI2ffp0HH/88Zg/f/5Wktu2bVsMHjwY99xzD+6999585LdLly545plnrJ3gXJI4E2D64eWXgQ4dEh4peP8ol3yVqa1xDl6Z2qb25i9KTfahFipmEGBq+eGHwOmnJ/Rl1tgzzzR59gWn+8KFQNWqif6ZTOzgg81/14gAe5szcV5DcKNk990Tdq1cCeywgzc749JKcSV6TxhJgAnb7Nmz0aJFC8ydO3cr2a1VqxZmzJiRj/zyGDRLJ+WixJ0Ab9pk3+P45hvbO/vtZ5ew2H77XPRWZjbHOXhlZplaF0RAvg53TmihYg4B3rwZOPlk4JNPbJ332QeYPNn8xXIQM/7VV4GLL7Z7ZjJK7qoV3CMw8V0jAuxttsTZ11OmACzRReFd9TVrzD/ZobjibZ762cpYAkwQ/vzzT2sneObMmYViwmPQLJmUqxJ3Aky/8KvzoYcCTnWqO+8E7rknVz3m3e44By/vVqllYQjI1+HOCy1UzCHA1PS334D69YENG2y9b701cc813JkT79HatAH+9z9bx86dgaRbZFsVN/FdIwLsbd7F2dfffgscc4xtV7VqwN9/e7MxTq0UV6L3htEEmPAtWLDAuhM8hZ+IgK27v7169cJtt90WPcIRamACASY8vHfE2o2U7bazSTEzekrSRyDOwSt9K8x+kqVEZs8GVq8GSpWyj2zxP/7ZT5Gv/UQzdV9aqOTHyIS4csstwAMP2HqXKWMnzalTJ7Wvc+UJvqNYJopHSSkffACcdtq21pv4rhEB9jaL4+zr5KsNrCDCj1ymi+JK9B40jgDz2HNBWbRoESZNmrQ123P58uVxxBFHbPMc7wB//vnn0aMekgYmLFQIBRNi8aU2b54NzEknASNGmH/EJSQ3W8PEOXiFiUOYY7FkCBeOnKssJzJ//rajV6hgf7lmkre2bf2pdy1fh+llQAsV8wgwiR1jCo/1Urhs+OwzxRTHk8mEYscdAZaRSk4y5Dxn4rtGBNjb+zHOvh48GGjf3rbr6KMT1+a8WRqPVoor0fvBOALMLM6FJbNipmdHivo5/32jc9Y2euwD18AUAkwgeBSLR7IceestoHXrwCHKmgHiHLyyBuQthowfDzz9NPDmm/ZdpHSlYkXgppuA668vfLGZbj/ydbpI+fOcFirmEWBqzARYZ5+d0H3oUPsjlMQ+8vziizYSjLt8lxUmJr5rRIC9zfA4+7p/f6B7d9sunlTgh2fTRXEleg9mDQFOBaVTEkkEOBVS0fy8YPISJuXgMReSBklqBOIcvFJrb8YT338P3HEHMHJk0foygRvnLMs2/Pdf4c8x2RsX40ce6c1u+dobbl5baaGSHzlTPqwypjAjNKsLUHh3kPXmK1XyOhOyox33AIjFv//a9gwZArRrV7htJr5rRIC9zdM4+/quu4BevWy7LrnEriBiuiiuRO9BIwmwV9i0A+wVuXDazZhhl2FgPUfKVVcBTz4ZztimjxLn4GU6tiwXwl1bZk0tKLxHx10mZp5t2NCuTeiUGl+xAuBu8bvvAjzCxaP+jvBe4lNPAZdd5h4d+do9Zpm00EIlP3qmEGBq/fvvPMKeOKlx5ZX2710uy+jRdvUFCt9DPP5c1EcBE981IsDeZnecfX3NNYm1YLduwGOPebMxTq0UV6L3hnEE+A++3TKQvffeO4PWZjU1aaHiIMuvfPza5wjvVjrZ/8xCP1xt4xy8wkXCv9G4g/TCC8DNN2+7m3vUUfaRLJJflmVIJdwN5tx+/PFExnO2ue8+oGfPVK3z/1y+dodXpk9roZIfQdPiyr332ic3HCEBPPbYTGeFue35YZlXOCgnngh8/HHRtpj4rhEB9jY34+zriy6yTypQWCWE1UJMF8WV6D1oHAGOHjJzNDBtoUJkuft72GF27UZK7drATz9ldmfSHI951zTOwcu7VdG1zMsDOnTY9rhzgwZ2SZVTTvGWUIc1r887L38ZB55y4KI0XZGv00XKn+e0UMmPo2lxpWBMYYWBn3/OzXrz69cD1asnjj8PHAh06iQC7M+bwuxe4hxXTj3VTjZJ4Udk7gibLoor0XtQBDhiH6xZswb3338/XnvtNcydOxe77LILTj75ZLCM0548T5mBmLZQcUwdNw5o0oQlrex/YTUrfsWXZNdCJa7+5J3Bjh3to4GOMJszd2uvuCLzskbcoTjhBIBH/iklSgDvvAOcdVZ6iMR5oZKeBWY9ZdpCJciYQs+ZGFcmTAAaNwY2bbLnHpPROWWSzJqNmWnLd5tT7oglB/mhr7g70Sa+a7QD7G2OxNnX/N3lupDCq0gXXujNxji1Mi2uxAk7v3QxjgBPnToVdXwo6OdXP5k4gguV448/HmPGjMHuu++OY489FnPmzMGECRNQuXJljB07FjVr1vQ8hIkLFcdYHi9l5j9K6dI8ppWHsWMHYNSoUVi+fDkqVKiAZs2aoXPnzqhatapnjLKlYZyDlykYMzkMP7bYC+M8AAMAjMLOOy9HvXoVcNJJ/s23v/6yF+T8P4UEmycdmCArlRTm67y8PAwYoN+PVNh5+blJC5WgY4qpBJh6J9ebL1EiD127DsDMmbkVT5js6rXX7PfbQQcNQPXqxdtvYlwRAfbylot3KUWeBJw+3baLH3G4Ixw3cRuDTYorccPaL32MI8ClS5fG+eefj549e+JgZkxyKT/99BP69u0T9SynAAAgAElEQVSLt99+G+t5HihCufPOO9G7d280btwYn3zyCXZkQT4Ajz76KK6//nocd9xxFuHzKiYTYCYQonv/+GM1gG4oUeIlbN68rb/KlCmDjh07on///ihXWCFDr+AZ1s7EhUqcIF6yxC6R8vHH9nwDXgIQ7Hz79Ve7puGyZTYSjRrZ9Q2ZmKY4Sfb16tWr0a1bN7z00kuFvs/0+5H5LDNpoRJ0TDGZAK9axZiyGrNnh/P7nfnM87cHxtQqVVZj9er07TcxrogAe5s3cfZ1lSqJE1ljxwLMwREX8RqDTYorccHabz2MI8D33HMPHnnkEaxcuRL169fHhRdeiKZNm1p/5mKvoKxduxYTJ07El19+iaFDh+K3335D+fLlceONN+KO5MwYfiOboj+S7ypVquC///7Djz/+iEMPPTRfC9rzyy+/4Pvvv0dDppf1ICYTYJr7wQerccYZp1i7cKmEc2DEiBHYnnVoclDiHLzi7g7eNz/zTGDWLJLfcOfbG28AF1yQQIgJ4O6+Oz0CzA9np5xySlofyXL99yOTOWjKQiWMmGIyAeZCtXHjU/Dzz7kZTwYOXI1LL3X3fuMpNEqLFi0y+RUKta0IsDe447qG4FU4Lu15QovCUmbcEY6D8J3iNQabElfigHNQOhhHgAnEwoUL0adPHwwePBhLly4FyxuVLVsWzPC88847W8djly1bhsWLF4NZozds2ADWAa5UqZK1W8jdYx4xjlJIyBlUeMR55syZ26jCnWF+zb/rrrtwd6oVcRGGmE6Au3TpgheYhjdN4fPPPfdcmk9n12NxDV5xR5kZUFu3Brg7AnQBEP58u/RSgMloKLyXR0Je3M0Hx9evv/66fj9CmGCmLFTCiCkmE+Bcjye7794FCxa4e7/xtJ0IcAgvmRgMEdc1BMsHVqyYAIhlCSNevm9VJpN3iilxJQZTMzAVjCTADhr8+vLmm2/iww8/xLfffosFCxZsA1S1atWsu7WtWrXCeeedF5tjso899hiuu+46tGnTxrKhoAwfPhynnXYazjrrLLzLQqIexGQCTF/WqFHD1TF1ngD4888/c/JOcFyDl4dpG1qTQYPsOrz2l2W+O2oUeuy5KIX8mm88Al23LjB/vj0SM0zznhOTYxUm9DU/7rVr106/HyHMFlMWKmHEFFMJcK7Hk1GjFqBZM/fvN56aY2JO7QCH8KKJeIi4riEK7ugzq3uqa0JhQJnpO8WUuBIGllGNYTQBLgjaP//8Y+0Oc1eYu708Yhz1Tm9Rju3Rowf69etnkWDe+S0oP//8Mxo0aIDDDjsMP/zwg6f5YTIB5g7/7bff7tputrv11ltdtzO9QVyDVxxx5ZGq3r3z15suU6YP1q+Pbr4VPAr90Uc2ES6KAA8ZMgQvvviia3hz9ffDNVBJDUxZqIQRU0wlwLkeT5o06YOxY92/3zp16mRdMxMBzuQNYkbbuK4hmBzSuSHIZJFOzoyoUc30nWJKXIka5yDHzyoCHCRQfvftHJ247bbbcG8hNX54LLpWrVo44IADMG3atGKHd36RCj40a9Ys6yMAE+SYJjfddJMn4s/70g8++KBp5masL+/EU3i/XVI0Ahs2lMBjj9XGiBHVtz60885rUa1aU0yZMt41dH7NN5LyG29sgIkTd7F0qF17GZ566vtCd4Hpa16PYEI/t+KXvm7HNfl5kgD+Xk12ipPH1Bg/Y4pDdAsz1cS4ksvxZO3akjj99D7YuPEz1zOXH+FZktGkuJKXVw7t2jXZautnn31R5Gka14BkcYO4riEmTtwZN9xg58ipWnU1hg6176VHLZm+U0yJK1HjHOT4xhNgTqJjjjkG/H9xQhI4evRoT7smQTjgsssus8qWcJeT930LyowZMyzym6sE+Oqrr8aUKVNcQ1+3bl08+eSTrtuZ3iCuwStOuHIheM89B2P8+N22qrXXXitx//0/o0+fSyOfb1OnVsBVVx2xVbdevX7B0Uf/uw2E9DWT+KX6MFYY9rn6+5HJPDRloeJnTMk2ApzL8eTjj6vhwQc7A9hSSNXFL0Pt2rXx0EMPiQC7wMzUR+O6hhg9ujLuuaeeBev++y/Hc899FwuIM32nmBJXYgF2QEoYT4BLliyJDh06pCS2XBzwyOBGJ5VcQICm220Yx9VMPgJ94okn4tNPP00Xzq3PnXDCCVZJqVyTuB5fiosfmEjj9NOB5KpiTZoA778P7LorEJf5xmzU1IlyyCF2beCCd4Hpa69fn3P19yOTeWjKUbUwYopDjLlYZs16UyQuv99h48WTJfXrA5MmnQjAfTx1TozoCHTYngt/vLiuIZgHtQvzU1rZyIHPPw8fm8JGzPSdYkpciQfawWiRMwS4ffv2eO2117CON+hjIGEkLDGZAGd6vyIGLg5VhbgGr1BBKGKwxYvt+7QTJiQeOOssYOhQwKmaFZf59vPPQIMGCT35Dahly/yG0de6AxzezDJloRJGTDGVAMfl9zu8WWuPxCz3J5/MP/UBoDvAYeNv0nhxXUPwRtvNN9tInnsu8L//xQPVTN8ppsSVeKAdjBY5QYBZAumQQw6xMqfOmzcvGCRd9ppuyQre9WPtYy9iMgHONMOeF7xMbhPX4BU1pnl5wAkncAckockll9hlh0qXTvxbnObbqacCI0bYuvHPzAidLMoCHe6sMmWhEkZMMZUAx+n3O8zZy49n9o7ZApQoUQObN69Pe3hmuVcW6LThMv7BuK4hbrkFeOABG15WbXj++XhAnek7xZS4Eg+0g9HCSAKcfBznq6++Aksd1alTp1CEWAOYSTs4WS+++OLYJITiTjQTVDFj9Y8//ohDnTR3W6yoX78+fvnlF0yYMAFHHJG4F+hmGphMgGlnJjXW3OCUDc/GNXhFie3cufbu6YwZCS2uvBJ44gmgZMltNYvLfOOu74k8sbhFpk5lUqzE31UHONxZZcpCJYyYYioB9hJPLrigC157zdy68hMnAocdlvhdadWqC4YPVx3gcN8e5owW1zXE5ZcnSO9NNyXIcByQzWTNYEpciQPOQelgJAHmvV9HSpQoAe7wFif8knnyySdj4MCB2G23RAKcoEBNt18mwOIxiiZNmlj3Vp1MiyyLdP3111vJvb7++ut0u9vmOdMJMOs8n3LKKRiVfHGzCDT22YdZfEfGps6zZ6d5bBjX4OXRnIybzZwJHH88QBLsCI9R3X9/0fV13cy3pk2bYuTIYOYbX2f16gFO0uGrrgKS87o5vm7cuHHavx9B6puxs2LegUkLlaBjiskE2M3vN9AUdeqMxPjx5VCxYswnaBHqnX028N579g8PP5z5D1bj1FPTi6fO+2LMmDFWe90BNnMOuNE6rmuINm0Sx5779k0ch3ZjW1DPunmnFIzBJsWVoPCLul8jCfAfrIwNWMR3v/32Q+vWra1MhYVJ2bJlLdJLEhw3WbNmDZo1a4bx48dj9913x7HHHgvaxr/vuuuuGDduHPbff3/PaptOgGk4XzDdu3fHoEGDsH59Yce36NeOKFGiP0aPLodjjvEMl9EN4xq8ogD111/tY88LFiRGv+8+oGfP1Nqkmm98j3Ts2BH9+/cP9GNLcuKPnXYC/v4bKFfO1j/Z13HRNzWy5j5h0kIl6JhiMgFOJ56UKlUGGzd2BNAfQDmcdppNIkuVMmv+Mt/BkUcmdH77beCcc1LH04LvNxPjCpeH++yTsH3TpqI/eprl1WC1jauvE8f4geeeSyTEChaN9Hv3GoNNiivpo2HWk0YS4GSIeT+Wx4fPOOMMs5Dfoi1/ee6//37rrs2ff/6JnXfe2dqtZmmkvfbaKyObsoEAOwDk5eVZO/g88r58+XJUqFABRx3VDC+/3Blz51a1HiNczJq7i11KNackrsErbCf88IN9fJiJrxx5/HHgmmvcaVLYfOPHqs6dO6NqVXu+BSnMWl2tGrBqlT3K668D559v/7kwX0etb5BYRN23aQuVIGMKfZENcaW435f+/ataJ0Uciduxy3R+H/gB8LMtZX8bNgS++y4/CUz3fWFiXBEBTmeGbPtMXH3NY/w8zk956y2gdWtv9gXdKt3fKUcP0+JK0PhF0b/xBDgK0EwZMxsWKqmw5pfuo48GNmywn2TGyw8/NO+LfSo7U/08rsErld5+/nzsWNv/y5bZvfKmxIABQEdu6BgoHToAL/+fvTMBu2r6/vhKg5KQEoVEpfgpGUpIo4hkFvlHZZ4JGTKWIUPSzxgK8TNFkiJDSiqSMZlKSaG5SFIi/Z91jtu973zuuefcs8/Zn/08PdR79j5rfdZ+79rfu6fhruEq6vVEVy3EOr/BZKBSkHfS84rOGOps6ejRab/191APz4tDmTDB3f6RKvq5kXmmQDY+xPGzBgGcTYTTz5oa6113FUnduKZf6mT2bX+emlGLvBJ9HBIjgPWwq7Fjx8pHH30ky5cvlwMOOED0omktCxcudP5tzz33lAqZR79Gzz9UC5I+UEnBGzhQpE+fNMobbxTxeXB2qPEIs3FTk1eYPme2rdvEO3cWWbPG/Vf9NddrjnT/UFzLe++JtGnjWq93AevATlc52B7rfMeTgUpB4jbkFV2BofeE63aK1OeJfrF6+OH57n3ZvU93CemMWcru1q1F3n3X/xLgOH7WIICz6zOpp02N9dZbp7/U/vRTkULnxfpz1oBa5JXog5AIAayHJOkJz3rFke4L1oOx9N7fxx9/3CH89NNPS8+ePWXEiBFygl4kZkmxYaCiodRDgzSso0alAztmjDj7t2wppiavfPB/6y0Rvdd37Vr3bZUquYdmdOmSj7eH9w7t1w0bisyd675Djzm48koEcHjEi2+ZgYp9Alg91lmnFi1Eli1z/a9aVX/33H8ztQweLNK7d9o6XRXTsqV/a+OYVxDA/uJtYqx1ZV/m8T3z5hXc3+3PUzNqkVeij0PsBfDMmTOlZcuWsmHDBrngggvk4IMPlpNOOskRvCkB/Mcffzj79rp06eLstbWl2CKANZ667FVvi5o9242uHhz08cci9evbEW0Tk1c+yOsXHbonaP16921VqriH1vhd8pcPm7N5h65muOUWt4YOvD/8EAGcDb8gnmWgYqcAVq9172y7dumVJTVqiEydWvBasiD6WBBt6EF5el2azl5rOfNMdwtILiWOeQUB7C/iJsZ6+XKR7bZL+7NqlcT2VPbCUSGv+OunQdaKvQBWsTtq1CjnGqHUUf16TVKmAHYHjy2cw5O++eabIPkZ3ZZNAlgDodfG6MmXqWWwTZuK6DfgW2xhdJgCMc7E5BWIY6U0orO83bql93/rDM1rr6WXDYf9/ny0/8UXInvvnX6TzkrNnTvB+Yc4XU2SD1ZhvYOBir0CWD3Xe7l1e0XqEoIddxSZONFdnWFK0dUium85de1R9eois2YVFA9+bI1jXkEA+4m0mV+s6oSGfqmjRU9i199B3Q6UhEJeiT6KsRfAtWrVkt13312mTJmyiWZxAlivSnr77bdllX6FZEmxTQBrWF94QeSUU9IB1tlB/beMq6MTGf04DlRyCcQzz7iH0uiBNVr0rs5x49x9e0kqOrBt3Di9suGee0SaNUMA5zPGDFTsFsDqvZ7Cfuqp7nYbLbVruyI4NTjPZ38s7l1PPlnwsL+HHxY577zcrYpjXkEA+4u7ibHWFU+pJfw1a6a3I/jz0Kxa5JXo4xF7AVy5cmU55phj5AVVOf+W4gSwLn+eOHGi/P7779FTz5MFNgpgRXv55SL33puGfMMNIv375wl6RK8xMXmFhWLYMJGzz04PRvXaK90HrNd9JLFcd52I3mOsRQcDt92GAM5nnBmoIICVQObd3Pp3vaZM9wTvsUc+e2PRd82Z4x58lVr6rPem6snPQXzpG8e8ggD21x9NjLV+qX3kka4/uuIitcXNn4dm1SKvRB+P2AvgXXfd1bkT9gtdK1iKANbntthiC/lK18laUmwVwHpwgh6Albo2RsOtM4b6DX5Si4nJKwzWDz4octFF6ZZ1f5BejaDL3ZNa9A5EHeCmyogRU6RGjfUsgc5TwBmoIIBTBAp/+aZ7gl99NbqVJ7rd58ADRWbOdC3UE3P1//W0+CBKHPMKAthf5E2MtY7bund3/dHtbdOm+fPNxFrkleijEnsBfO6558rQoUPlpZdekuOOO84hWngG+Mknn3SuRLryyivlrrvuip56niywVQArXl3prgOD1JbvzTd3r4PI5UTMPIXN12tMTF6+HCmlki7/1VOQU0WXIb7zTvQzMEH7Wbg9XXZZr57IggXuT/r0+UY6dVqEAA4b/L/tM1ApCNrmvKIkdLmx3rCYWg5dubL7Bavuwc1n0e0fegbCiBHpt+r/B3n1WxzzCgLYXy80Mdb33Sdy6aWuPzoTrGd8JKWQV6KPZOwF8Pz586Vp06by559/Sp8+fZzl0HrgVdeuXeX666+XV155RW6//XapWrWq6InRO+i6JUuK7QMVvT5GvzVcscIN+Pbbu6fo7rJL8jqAickrKMo60NTTkG+9Nd1i3bqu+G3QIKi3mN3O+eeLDBni2ti69VK56aYvEcB5ChkDFQRw4a6me4J79EifPq8H8+hp7ddeG8zS47K6tn4mqjC4//70k336iAT9/X4c8woCuKzeU/zPTYz1TTelt6+ddprIU0/5883EWuSV6KMSewGsCPUALD0NesmSJc4dwJlF7wXebrvtnJOiD0raCTll9B/bBbDiee89Ed0TlTrBUw8t0WssdOlakoqJySsIvjrLcfHFIg89lG5tt93cvXdJ/CKjJGZ63dPRR7s/rVr1b3n55cly2GHtgkBMGx4+R/URm7bPlIaEvOLSmTTJvX/811/TtHSWSgfpYeYXFb96LsCAAen36rVvOjtWoUKwv85xzCsIYH99wMRY63Yn3fak5bLLCp7t4s9Lc2ohgKOPRSIEsGLUK46GDRsm48ePlx9++MG5F3innXaSQw89VHSZ9DZ6MaxlhYGKG/DHH3fvREwVXQat+0b12pykFBOTV65s9UsLnWV57rl0S//5j7u3W68isanoXj897Ct13/GgQZ9K794ZG4NtgpFnXxmoFAROXknz0C02ekXSvHnpf9P9t7pXuGPH4Duqnm+hM7+ZXwjuv7/7hWC1asG/L455BQHsrx+YGGtd4q+rLbToCovrr/fnm4m1yCvRRyUxAjh6lOZZwEAlHRM9BVqX06SKDlpGjRKpWNG8uPmxyMTk5cePVJ0//nD3sr3+eroVXc6uf1chaGM5/HD3tGstJ588X55/PoFr+Q0MLAMVBHBp3fKXX0R69nQPw8os+qXrnXcGNxu8fLm751e/vE2VvfZyxa8eBhhGiWNeQQD76wkmxlpXNug93Fr0Sx/dCpSUQl6JPpII4OhjEJoFCOA0Wl02dsEF6X2U+pNevdxv6pNwsbqJyctvx9YlhV266NaGdAu6jF2/sNhyS7+txr/ef//rLgPT0qDBavnuuxCmfOKPKXAPGKgggMvqVJpfBg4U6dtXRGdpU0VPZdZ/020cVaqU1UrJP3/5ZZELLxRZvDj9TD6+EIxjXkEA++tnJsZarzb89FPXH73ptGtXf76ZWIu8En1UYieA39NNnTmU1q1b51A7XlURwAXjtWGD+wGqg4lU6d1bRE8XjrsINjF5+fltWbRI5IgjRGbMSNc+4QT3lFU9ydvmoje46YyPlnLlNsry5eWsnQ3PZz9goFKQNnml5N6nn1v6xapeXZZZdIb23HNFzjvP+/YNFdU63Ln5ZvcGg8yieUy/vA37C8E45hUEsL9PRxNjrbcfaDy16MqHDh38+WZiLfJK9FGJnQDWK44KH3SVDUbdG2xLYaBSNNLr1onoUtLM71GuukrkjjviLYJNTF7Z/p59/bUrflPX/Wh9XUaopx8HfbhLtraZ8LwOiPUQ+6VLXWv0i5x/b34zwbzE2sBABQGcTefWswt0tYaeWq/X8WUW/aJVz+LUe+pbtBBp0sRdIr3ZZu61SsuWiXz5pcjEiSIvvigya1bB+nrl0u23uytB8vGlbRzzCgI4m96aftbEWOu+9t9/d23UL5WaNfPnm4m1yCvRRyV2Arhnz55FBPCKFStk7Nixzr/vs88+UlfvSBEdSC+Qzz//XPQk6M6dO0uNGjXkiSeeiJ56nixAABcPWpfY6pLaTz5J/1wPV9BDFuJaTExe2bDUGQ49UTVzwKjXeugeunwM9LKxNcpnTz45fe+nLqvUexIp4RJgoIIA9tPD9Pq9225zv8Bbu7bkFsqXd5dH65ezmcunC9fQ2a+HHxZp2NCPNf7qxDGvIICTEWs98DFz1Zd+Ma4HzCWlkFeij2TsBHBhZIsWLZKWLVtK48aN5f7775fdd9+9wCOzZ8+WSy+9VL7++muZNm2a1K5dO3rqebIAAVwy6JUrRdq3L7jUtl8/977ZOJY4DlRSnJ991l02mDrhWAXv4MEil1wSx0iEa7MOplMHgehy6Jkzw30frYswUEEA5/J7oLlm6FBXvP7wQ/YtqfDVfcSar/Jd4phXEMD+eolpsdbtUHXqpH3RmxC22MKfbybWIq9EH5XYC+AePXrIO++8I3PmzJHKuj6omLJ27Vpp2LChtG/fXp5K0k3aZfQfBHDpgHS5Wbt2er9n+jk9KVr/xG3W0bTk5eWjTZf86Qzvtdemn9ZfYRXELO0tnqAuiWzcOP0zXQ4d1gmwXmJowzMMVBDAQfRz/bzTA31Gjxb54AORjz8ueIdw6h3Vq4vo1UZ6jZKef6D3nkdV4phXEMD+eotpsdatALpFQIuOC0pbReHP42hrkVei5a9vj70A3mGHHaRdu3byXOZlocVw7datm+gv+JIlS6KnnicLEMBlg9bu0LatyLffpp/V/VWDBsVLBJuWvMoir8v99ECY4cPTT9asKTJmjIje00wpnoAOorfb7k9ZscI9EWzECPe6KEp4BBioIIDD6F36u6xbPjQH/fmnuwxar3jTPcGmlLjlFeWGAPbXe0yL9aRJ7thMy447ivz0kz+/TK1FXok+MrEXwFtssYUcfPDB8nbqsrASmHbs2FGmTp0qf+gFo5YUBLC3QOtSG11m9s036efPOEPk0UdFdH9WHIppyas0ZspbZ3g//DD9VIMGIuPG6fU+caAdrY0dOiyWCRN2cIzQZeJ64A4lPAIMVBDA4fUus1uOU15JkUQA++tTpsVaD3nUFRBamjYtuF3Nn4dm1SKvRB+P2AvgFi1aOAdd6TLoQw45pFiiU6ZMcWaJ9YCs6dOnR089TxYggL2D1uXQnTql75zTmieeKPK//8Xj+h3TkldJ5D/6yD3sauHC9BP6aztyJEt5vfbWSy6ZJfff38h5vHlzEYs+0rwiCvQ5BioI4EA7VIwai0teyUSKAPbXwUyL9WOPiZxzjuuLblWbMMGfX6bWIq9EH5nYC+CRI0fKSSed5Oz/1f3A+v96CrSeCD1//nx58cUXnX2/69atkxEjRsgJqa+UomcfugUI4OwQ63K0Ll1EJk9O12vVSuSVV8xallacV6Ylr+Js1C8TzjrLXe6XKno3pp5kXKlSdrGy+ekhQ6bL+ee3cBDo9VC//eYun6SEQ4CBCgI4nJ5lfqtxyCuFKSKA/fUr02KtV1OmzgfRyQi9FixJhbwSfTRjL4AV4QMPPCB9+vSRP//8s8gVSXoFUqVKleTOO+90ToO2qSCAs4+2rpDXD1tdjpsqeu3E66+bvTzXtOSVSV73++q+6kceSf+rCjcVvqkTjbOPlL013n57ohx9dGtZt85dn693Wpew+MVeSAF6zkAFARxgd4pVUybnlZJAIoD9dTHTYq3XIA4c6PqiX5TrDQhJKuSV6KOZCAGsGHW2d9iwYc4+34ULFzp3/9apU0datWolvXr1kl133TV62nm2AAHsD7hex6MHNGVeGa0Hk+hMsM4Im1hMS14pRnPmuIc0ff55mpqy1G9zdVkTJXsCGuvLL99HZsyo7lTWk7Svuir7dqjhjQADFQSwt56SvKdMzSulkUYA++uHpsVaz2FJjcH0GjC9UztJhbwSfTQTI4CjR2meBQhg/zHREzoHDBC57rp0GxUruqdDX3iheSdEm5a8lNpLL4loElu9Os1Qr/fQk4st/D7Kf2csVFNjPXTobvLcc/Wcn+ie6lGjAmuehgoRYKCCALb1l8LEvFJWLBDAZREq/uemxfqYY0RefdW19Z57RC6/3J9fptYir0QfGQRw9DEIzQIEcO5o9Xatnj1FdFY4Vbp3d5fzmnQpu0nJSwWvJquhQwvyv/hikbvvjsehYrn3nPBa0Fh/8EENuf76vZ2X1KolsnixeV/KhEcgvy0zUEEA57fHmfM2k/KKVyoIYK+kCj5nWqwPPljk/fddG598UqRHD39+mVqLvBJ9ZBDA0ccgNAsQwMGg/eADd19w5snFeiy/LuPdffdg3pFrK6YkrylTRE4/XWTevLRH1aqJDBvGfbW5xjhVX2O9alVFOf749Kn333/PrHpQfAu3w0AFARxW3zK9XVPySjacEMDZ0Eo/a1qsGzcWmTXLtW/MGJGjjvLnl6m1yCvRRwYBHH0MQrMAARwcWp1hO/lk98ChVNEZ4HvvFTn77Ohn36JOXnrQ1c03i9x1l4guH0+V/fYTef55sw8QC66X5KelVKzPPru9qPDVosvNLTrgPj+g/30LAxUEcF47nEEvizqv+EGBAPZDTa8Zcu8Zat++vb8GAq613XYiy5e7jepM8IEHBvyCiJsjr0QcABFBAEcfg9AsQAAHi/avv0SuucbdB5xZ9OokXe6rS1GjKlEmr4kT3UPDZs9Oe1++vLt/+vrrRXTvNCU4AqlYDxnSftPVEHpdxO23B/cOWkoTYKCCALb19yHKvOKXOQLYHzmTYv3PP+64Qf+rRWeCTVlt549u0VrklaBI+m8HAeyfnfE1EcDhhEgPHNL7bFeuTLev4lev9enaNZrZ4CiSl347e+WVIsOHF+Ss10Y9/bTIAbtfURkAACAASURBVAeEw9/2VlOxnj69/aZ7Eg87TOTNN20nE47/DFQQwOH0LPNbjSKv5EoFAeyPoEmx/uUXkW23TfuhYw29PSJJhbwSfTQRwNHHIDQLEMChoXX2A+sJx4VFxxFHiDz4YP73Y+Yzef39t8hjj4nccIPIihVpxpttJqIHXel1BVWrhsfe9pZTsd6wob2o8NWig4Nly6L58iXp8WCgggBOeh8vyb985pWgGCOA/ZE0KdZ6faJ+ka6lXDkRXX2nq8qSVMgr0UcTARx9DEKzAAEcGlqnYd3rqmJXL2zXPbCpUqWKiN5bpych5+uk6HwkL/X3tddcf7/9tiDbffd1T8bWa44o4RJIxXrvvdtLzZrpd+nAr27dcN9tY+sMVBDANvZ79TkfeSVotghgf0RNivWHH4q0bOn6oTPBmV+0+/POvFrklehjggCOPgahWYAADg1tgYbnzhU5/3yRt98u+L4dd3RnQ087TURnR8MsYSevyZPdQ67+PSdjkys603vrrSIXXSRSoUKYHtJ2ikBmrPU+5R9+cH/y8ssixx0Hp6AJMFBBAAfdp+LSXth5JQwOCGB/VE2K9euvi3Tu7PqhM8GZ54v48868WuSV6GOCAI4+BqFZgAAODW2RhnV2VO8M7t1bZOnSgj9u0sQ9DEpP6Q1rGU8YyUt9evddkf793f9mFl2W1KuXyC23iNSpkz/OvKngrIxezzVypEtFDx3TLyMowRJgoIIADrZHxae1MPJK2N4jgP0RNinWeoaIXqeoRWeC9SrKpBXySvQRRQBHH4PQLEAAh4a2xIZ//VVkwACRwYNF1q8v+FijRu4p0t26iWy+ebC2BZm8/vzTvVbn/vtFdClS4XLooSIDB4rsvXewPtCaNwKZsdaTn1X4aunUSWTcOG9t8JR3AgxUEMDee0uyngwyr+SLDALYH2mTYq3jJ51M0KIzwWPH+vPJ5FrkleijgwCOPgahWYAADg1tmQ3rslTdB6yzwoWL3m+nB2ide25wh2UFkbx0KfeTT4o8+mjRWWz14ZBDRG68UaRDBw5bKrMDhPhAZqz1EDYVvlpq1xbncDZKsAQYqCCAg+1R8WktiLySb28RwP6ImxRrPWAztZpJZ4IL3zThz0OzapFXoo8HAjiCGKxZs0ZefvllmT59unz44YcyY8YMWb9+vQwYMECu0SnCgAoCOCCQOTQzc6Z7P+uIEek77VLN6TLitm1FTj7ZXR6deaBRtq/0m7wWL3Zne595RmTatOLf2q6dyE03ibRpk61VPB8GgcxYq+DVveapksTrIsJgmE2bcRmokFeyiSrPeiHgN694aTusZxDA/siaFOsLLhB5+GHXD50JHjTIn08m14pLXjGZYa62IYBzJeij/ueffy777LNPkZoIYB8wY1JFD3G46y5XaGaeGJ0yX/cGq8Ds2NH9o90jm4OzvCYvXd788cfu9U160MQnnxQPUJdon3qqe7iVnvBMMYdAZqx1n7Z+cZK6k3riRPdLFUpwBOIyUCGvBBdzWnIJeM0rJvFCAPuLhkmx1kkBnTTQojPBqW0+/jwzs1Zc8oqZ9IKxCgEcDMesWpk7d64z29uiRQtp3ry5jBw5Um677TZmgLOiGM+HVajoch79dvO770r2oXp190ohFZ/6R/cP64m/W21VfJ3ikpfOBs6a5f758kv3IIlPPy26NzmzxT32EOnZ012incuMdDyjEw+rC8daBe+kSa7t993n3sVMCY5AXAYqpueVjRs3iv6hxIfAu/+eftg2wG/VypUrJ/onrIIA9kfWJAGs54y8847rh46VzjvPn08m14pLXjGZYa62IYBzJRhA/Ztvvln69euHAA6AZVya+Ocf94CpF14QefFF73s3VRjrqcsqhPWPXkOkbS1evFw2bNCBRQ3nFOply0TWrPFGY+edRbp2Ffm//xNp1oz9vd6oRfdU4YGKCt4HHnDtOesskccei862JL45rgMVE/LKhg0bZMWKFbJ69Wpnmw8lXgR+++03x+CtSvrm1ac7lSpVkmrVqkmNGjWkfMBXIyCA/QXFJAGsK+A+/9z1Q2eCTzrJn08m14prXjGZaba2IYCzJRbC8yYMVEJwiyY9ElABq7Ozb70lMn68K4w3bPBY2cdjlSu7VwsceaT7Z889Eb0+MEZWpfBARQ8t0wPVtBxwQMl7uSMzOOYvjutAJeq8ouJ3wYIFsq64PR8x7xO2mK8x1BK0SE3xq1y5stStWzfQ9hHA/nqnSQK4bl2RH390/dCZ4Pbt/flkcq245hWTmWZrGwI4W2IhPB/1QCUEl2gyBwKrVrn7dHV/ri5Z1m9C9VRp3b+bbdlmG5HGjd0l1PvtJ3Lgge71RRUrZtsSz5tCoPBARb88Oegg1zpdEaCTNtnsHzfFL1PtiOtAJeq8snTpUmf2V8XT9ttvL1WrVpXN6JimdvNi7QpjBviff/4RPbBtyZIlogJbZ4Fr1aoVGBcEsD+UJglgzWN//OH6MWOGSNOm/nwyuVZc84rJTLO1DQGcLbEQno96oBKCSzQZMAGdJV6yxBXCurdXRY7+0WXOuoLs++9nS/nyG6VFi0aiYwm9akmvxdH/hrjdKmAvac4LgcIDldWrC+4N1+usdtvNS0s844VAXAcqUecV3ZOsy57r1KkjW2+9tRfUPGMYgTAEcMrFVatWycKFC0WXQ9evXz8wzxHA/lCaIoB1wUiVKmkffvqp4E0H/rwzr1Zc84p5JP1bhAD2zy6wmrkOVFK/SIUN0gGIfrP6pF7uSkk0Af1GXYvOslCSTaC4WHfvfqAsWuSOGvr3/0IOPnh5siHk0bszzjjD+b366quv8vjW3F8VdV5RZvpnxx13DHSJa+5kaMErAZ2t1RLGzL3O/v7888/ObHDqM82rXaU9t2RJZTn11H+XxIhuK5rAl8AewJoyhli2bHM55ZSDN1k8bty7UqmS2w+TVOKaV5IUAwSwj2ieeOKJ8qUeq5tFeeqpp5xTn4srUQ9UsnCDRw0lYEryMhRPoswqLtY33NBE3n9/O8fPXr2+l+7df0iUz1E6k6+BStLySkoA77TTTqEIqCj7hC3vDlMAa9s//fQTAtiQzmTKGOK777aU885zx8pVqvwtY8e+ZwihYM3IV14J1upktYYA9hHP/fffXz4p6QLVEtqbOHGilHSVQK4CuCQXdGZYP9R+0HWzlEQTMGX5UqIhG+JccbHu21dkwADXQD3N+3//M8TYBJiRr6VqScorKm5m6f1roucPNEIAx/T3IMwl0GH1EZZA++tspowh3n5b5LDDXB/06sfvv/fnj+m18pVXTOcQpX0I4Cjp//tuBLABQYi5CaYkr5hjjIX5xcX6qadEevRwzdd7o7P8fi4WfkdlZFwHKlHmlbDETVR9wNb3IoDtibwpY4hnn3W/xNXSvLnI9OnJjEFc80qSooEANiCaUQ5UDHAfEwIgYEryCsAVmiiDQHGx1kGCXoGkZYstRPRgLA7cDaYrxXWgEmVeQQAH0/eibgUBHHUE8vd+U8YQ990ncumlrt96TeNrr+WPQT7fFNe8kk9GYb8LARw2YQ/tRzlQ8WAej8SAgCnJKwaoYm9icbHWq7P0yqtUWbBAZOedY++qEQ7EdaASZV5BAJfcdcsVOpa/QoUKzinZtWvXlv3220+6dOkixxxzjOi/F1e0/i677JKXrU0IYCM+gvJihCljiBtuELn1VtdlXdWU1DNc45pX8tIZ8/QSBHCeQJf2migHKga4jwkBEDAleQXgCk2UQaCkWNepI7JokVv5rbdEOnYEZRAE4jpQiTKvIIDLFsA9/t2zoKz0SqDZs2c7+6Y3btwoDRo0kGeeeabYgzNNFcDZ2hVWH2EPsL9PPVPGEOefLzJkiOvDFVeIDBzozx/Ta8U1r5jONRv7EMDZ0Arw2eOOO04W/Tta1ZMQ9TqAnXfe2bkzUYt+Gzxq1Kic3sghWDnhi1VlU5JXrKDF1NiSYt2hg8iECa5Tuozs4otj6qBhZsdpoGJKXglL3BjWNXyZk5oBVqFbuOjVhX379pURI0bIFltsIVOnTpVmzZoVeOzbb7+VihUrBnp3bkmOZDMDjAD21R2MqWTKGOLEE0VGjnSx3HGHyNVXG4MoUEPilFcCddygxhDAEQWjXr16Ml+/qiyhBLHECQEcUXAjeK0pySsC1617ZUmxvvBCkYcecnFccIHIgw9ahyYUh+M0UDElryCAS+6KpQngVK2zzjpLhg0bJvvss498+umnofRrL40igL1QSsYzpowh2rQRee/fm4+GDhU588xk8C3sRZzySjIjIIIATmpkRQQBnODgFnLNlORlD/HoPC0p1vffL3LJJa5d7dqlZ4OjszQZb2agUjCOXvIKAjg3AaxLonfccUfnGsPJkydLq1atNjVY3Ezru+++K+3atRNdVn3HHXfI9ddfL2+88YYsXrxYBg4cKJdddplTX69EHDBggLz55pvOCrStttpK2rRpIzfeeKM0bdq0iNEqgKdPny6PPvqoTJkyRVasWCE1a9aUvfbaS0477TTp3r27PPnkk9KrV69iHda21bbiSlh9hCXQ/j53TRlD/Oc/Il9/7fowerTI0Uf788f0WuSV6COEAI4+BqFZ4GWgEtrLaTivBExJXnl12tKXlRTrzPsTa9cWWbjQUkABu81ABQEcZJfyMgOs7zvppJPkpZdekv79+8sNejLQv6U0AXzkkUfKF198IX///bcjmtetW+ccqnXOOec4ArZz586iolb79B577OFsvZo2bZpUrlxZXnvtNUdEZxYV07okW5drN2/e3Fl2vXTpUucdVatWdQS1tjt06FAZPny4828n6hrWf0vjxo3lmmuuQQAH2YFCasuUMUStWiLLlrlOTp0qctBBITkccbPklYgDIMwARx+BEC1AAIcI17CmTUlehmFJpDklxfrHH0Xq1k27/OuvIltvnUgEeXWKgQoCOMgO51UA33bbbc5Mbrdu3eRZvRzVgwDWR3QfuD6vojZVVPQ2atTImcHVn2WK1PHjxzvCeLvttpPvv/9eKlWq5FR77733pG3btlKtWjUZPXq08/+psn79epk4caIcfvjhpdpVGjdmgIPsVbm3ZcIY4p9/RCpWFNH/apk9W6Rhw9x9M7EF8kr0UWEGOPoYhGYBAjg0tMY1bELyMg5KQg0qKdZ6pk61aiJr1riOf/ihSIsWCYWQR7cYqBSE7SWveBE32l/1+q44Ff1CqdAtRlmb71UAP/LII3LeeedJp06dZNy4caUKzdQS6M0331z0IC1dPp1ZBg8eLL1795Zrr71Wbr/99iI268/0mZEjR8rxxx/v/Fxnk/W9t956q1x33XVl+skhWGUiMvoBE8YQK1aI1KyZxrRypUj16kZj820cecU3usAqIoADQ2leQ14GKuZZjUV+CJiQvPzYTZ3sCZQWaz0wdsYMt02dNOrWLfv2qVFU8Om/fPXVV6DxeLaEFwGsKxTiNrj95ZeC92376RBeBfCQIUPk/PPPlyOOOEJef/11TwL4wAMPlPfff7+IWTrDq218+OGHxV6tpMJXZ4V1ubLuEd6wYYMz87t27VrRWyoKC+ri/EYA++kN5tQxYQwxa5ZI48Yuk/LlRf76K/cvnMwhTF4xLRYIYNMiEqA9COAAYRrelAnJy3BEiTGvtFhnXiHRv79IxtbBxPifb0f4pr7owE0PZ9L9nyUVBHDJvdSrANaZV937+3//93/yv//9z5MAPvnkk+X5558v8nLtw1+nThYq5RdIT59+7LHHZMmSJbLDDjs4y6LnzJnjHJZVVkEAl0XI7J+bMIaYMkXkkENcTttvL7J4sdnMcrGOvJILvWDqIoCD4WhkKwhgI8MSilEmJK9QHKPRIgRKi7WeN3PnnW6V008XGT4cgLkSYKCCAE4RyOcMsM7I6sys7gXWg6hSpaxToPVU5sJFD6OaNWuWc7CW3i9cUtGDs1QEpwRwrVq15LvvvkMA5/ohEoP6JowhXnlF97C7sPbaS2TmzBiA82kiecUnuACrIYADhGlaUwhg0yISnj0mJK/wvKPlTAKlxVrvTTz7bPfpgw8W0W/UKbkRYKASjgBmD/DGEjtm5jVIuqRZlzbnIoAPPfRQeeedd2TGjBnFXndU2BCWQOf2mRHH2iaMIR57TOScc1x6Sb/Kj7wS/W8JAjj6GIRmAQI4NLTGNWxC8jIOSkINKi3WeuVm6iaTpC8hy1d4GaiEI4DzFT/T3uNlCbTOwg4bNsy5ekjv4c0sfmaA9TojPQCrX79+zp2/XkrqEKzCM9Al1dXTo3XGWPcMeylelsl7aafwM9wD7Iea3hs/wanYvn17fw0EUGvAAJHUYoeTThIZMSKARg1tgrwSfWAQwNHHIDQLEMChoTWuYROSl3FQEmpQabHWsefOO6cd/+0392Roin8CDFQQwP57T9GapQlgvYZIheqIESOcO3U/+OADadKkSc4C+JdffnGuQdLrkB5++GHp2bOnpOzQxnVPty63VvGz0047Oe+bNGmScy+w7v8dM2aMHJLanCl6ONFfjmDKvAapXr16zr3Cy5Ytk2222aZMZAjgMhHl9QETxhCXXy5y772u2xdcIPLgg3lFkNeXkVfyirvYlyGAo49BaBYggENDa1zDJiQv46Ak1KDSYq33J+oWvz//dJ3/7DMRPRma4p8AAxUEsP/eU7IA7tGjh/NDFYIqTGfPni3ffvutbNy4URo2bOjc17v//vsXacDPDLA2MnXqVDn66KNl5cqVsssuu8hee+0lem3SggUL5JtvvnFE8GeffSbNMj4wUgdxaf0WLVpI/fr1ZenSpc5SahXomQehXXLJJXL//ffLrrvuKgcddJBzD7GK7j59+hSLDwEcZK/KvS0TxhB6bsXTT7u+6EKFfv1y98vUFsgr0UcGARx9DEKzAAEcGlrjGjYheRkHJaEGlRXr//xHJHXg60sviZxwQkJB5MktBioI4CC7WubMq7ZboUIFZ5a1Tp06st9++zkiVf/ovxdX/ApgbWvhwoUyaNAgee2112T+/PlSvnx557377LOPc//vscceK7qUOVVUmE+ZMkUeffRR53qlX3/91VnmrOL59NNPl1NPPXXTsyqg9Rql0aNHy6JFi+Tvv/+WNm3aiN5RXFxBAAfZq3Jvq6y8kvsbym7hiCNE3njDfe7++0UuuqjsOnF9grwSfeQQwNHHIDQLEMChoTWuYROSl3FQEmpQWbE+5hiRV191nb/jDpGrr04oiDy5xUAFAZynrmbca1QAa/FyDVK2xiOAsyUW7vNl5ZVw3+623ry5yMcfu///3HMip5ySj7dG8w7ySjTcM9+KAI4+BqFZgAAODa1xDZuQvIyDklCDyor1FVeIDBrkOn/WWSJ6sibFPwEGKghg/70n3jURwPGOXzbWl5VXsmnL77P16onoIWZaxo8X6dDBb0vm1yOvRB8jBHD0MQjNAgRwaGiNa9iE5GUclIQaVFasH37YPUBES9u2IhMnJhREntxioIIAzlNXM+41CGDjQhKaQWXlldBenNHwllvqgWzuP3z+ucjee+fjrdG8g7wSDffMtyKAo49BaBYggENDa1zDJiQv46Ak1KCyYv3WWyKHH+46rydCL1iQUBB5couBCgI4T13NuNcggI0LSWgGlZVXQnvxvw2vXese4JgqP/8sUqdO2G+Nrn3ySnTsU29GAEcfg9AsQACHhta4hqNOXsYBSbBBZcV6zhyRhg1dAJttJqIDi4xzbRJMJhzXGKgggMPpWea3igA2P0ZBWVhWXgnqPSW1o1/U7rJL+qfr1olsvnnYb42uffJKdOwRwNGzD90CBHDoiI15QdTJyxgQFhhSVqz1CqQqVUQ2bnRhzJ0rsttuFoAJyUUGKgjgkLqW8c0igI0PUWAGlpVXAntRCQ19+qnIfvu5P9xqK5FVq8J+Y7Ttk1ei5a9vZwY4+hiEZgECODS0xjUcdfIyDkiCDfIS6512EtElZFreeUekffsEAwnZNQYqCOCQu5ixzSOAjQ1N4IZ5ySuBvzSjwTffFOnUyf2H+vVFdCVTkgt5JfroIoCjj0FoFiCAQ0NrXMNRJy/jgCTYIC+xbtVKZOpUF8KwYSJnnJFgICG7xkAFARxyFzO2eQSwsaEJ3DAveSXwl2Y0+MwzIt27u/9wwAEi06aF+bbo2yavRB8DBHD0MQjNAgRwaGiNazjq5GUckAQb5CXWOpDQAYWWG24Q6d8/wUBCdo2BCgI45C5mbPMIYGNDE7hhXvJK4C/NaHDwYJHevd1/OOookTFjwnxb9G2TV6KPAQI4+hiEZgECODS0xjUcdfIyDkiCDfIS6+uvF7ntNhfCaaeJPPVUgoGE7BoDFQRwyF3M2OYRwMaGJnDDvOSVwF+a0WBmzurZU+SJJ8J8W/Rtk1eijwECOPoYhGYBAjg0tMY1HHXyMg5Igg3yEuuhQ0XOPtuFcMghIu+9l2AgIbvGQAUBHHIXM7Z5BLCxoQncMC95JfCXZjR47rkijz7q/kOfPiJ33RXm26Jvm7wSfQwQwNHHIDQLEMChoTWu4aiTl3FAEmyQl1iPHy/SsaMLgbuAc+sMDFQQwLn1oPjWRgDHN3bZWu4lr2TbZjbPn3CCyMsvuzXuvFPkqquyqR2/Z8kr0ccMARx9DEKzAAEcGlrjGo46eRkHJMEGeYk1dwEH1wEYqCCAg+tN8WoJARyveOVirZe8kkv7ZdVt3Vpk8mT3qccfF+nVq6wa8f45eSX6+CGAo49BaBYggENDa1zDUScv44Ak2CAvseYu4OA6AAMVBHBwvSleLSGA4xWvXKz1kldyab+suo0bi8ya5T41dqxI585l1Yj3z8kr0ccPARx9DEKzAAEcGlrjGo46eRkHJMEGeY01dwEH0wkYqCCAg+lJ8WsFARy/mPm12Gte8dt+WfW23Vbkl1/cp6ZPF2nevKwa8f45eSX6+CGAo49BaBYggENDa1zDUScv44Ak2CCvseYu4GA6AQMVBHAwPcltpVy5cmU216NHD3nyySc3PVevXj2ZP3++bNy4scy6QT6AAA6Sptltec0rYXixfr3I5punW/7hB5FddgnjTea0SV6JPhYI4OhjEJoFCODQ0BrXcJTJyzgYCTfIa6wz7wLWKyZuuSXhYEJyj4GK+QJ4yZIlMnToUJk0aZKsXr1aqlWrJm3btpUzzzxTtt9++5B6hr9mUwJYRW5JpVWrVnLWWWchgH0gnj9fpF69dMV//tEvHXw0ZFkVr3klDCw//yyiK5ZS5Y8/RKpUCeNN5rRJXok+Fgjg6GMQmgUI4NDQGtdwlMnLOBgJN8hrrK+7TuT2210Yp58uMnx4wsGE5B4DFXMF8Nq1a+XSSy91Zkv/+uuvIj2gYsWK0qtXL/nvf/8rlStXDqmHZNdsSgBnM5s7d+5cx7/GulEyj4UZ4DzCjvhVXvNKGGZ+9pnIvvu6LVerJvLbb2G8xaw2ySvRxwMBHH0MQrMAARwaWuMajjJ5GQcj4QZ5jfWQISLnn+/CaNdOZMKEhIMJyT0GKmYKYBW/RxxxhDPrW1Zp06aNjBs3TqoYMK3kRwCX5V9YP0cAh0XWvHa95pUwLH/zTZFOndyW69cX0VsMkl7IK9FHGAEcfQxCswABHBpa4xqOMnkZByPhBnmNtZ6k2aWLC6NhQ5HZsxMOJiT3GKiYKYDPOecceeyxxzxHXZ9/5JFHPD8f1oN+BHBpe4BHjBghd999t3z55Zey1VZbyZFHHil33HGHXH311TJ8+HCZOHGisxw8syxbtkzuvPNOGTNmjLO3WL8YaNmypVx77bXSWu+j+beoAJ48ebIcddRRoku2Bw0aJNddd5288sorsnLlSmnYsKFcfvnlcsYZZ2SN659//pFZ/x7726hRI9lss82ybqO4CiyB9ofRa17x13rptZ5+2l2lpOXAA0Xefz+Mt5jVJnkl+ngggKOPQWgWIIBDQ2tcw1EmL+NgJNwgr7GeMUOkWTMXhq7+1H1V7IXLvnMwUDFPAC9evFjq1q1b7LLnkiKsy6F//PHHyPcEBymABw8eLL1795by5cs7IrdmzZoyZcoUUV+bNm0qr776ahEB/O2338qhhx4qP//8s9SvX995bsWKFTJt2jT5+++/5emnn5ZTTz3VwZgpgI855hj55ptvZNWqVdKiRQv5/fff5b333pMNGzY4X0Rk7ln28luGAPZCKX/PeM0rYVh0zz0iV17ptnzMMSKvvBLGW8xqk7wSfTwQwNHHIDQLEMChoTWu4SiTl3EwEm6Q11ivXClSo0YaxvLlBf+ecEyBucdAxTwBfNttt8n1erJblkXr9e3bN8tawT4elAD+/vvvZY899nBmTt966y055JBDHEPXrVsnJ554orz22mvO3zNngFWsNmvWzJkt1n3RF1988aZTqT/77DPp2LGjU1/brlWrVgEBrG2dcMIJzqxy1apVnbZHjx4txx57rPNlhM4kZ1MQwNnQCv9Zr3klDEuuukrk7rvdls85R8SAhRphuFmgTfJK6IjLfAECuExE8X0AARzf2GVreZTJK1tbeT43Al5jrTem6Dh17Vr3fXrQSGpGODcL7KrNQKVgvL3klbDETcqSww47TN5+++2sO6IKPBWLURYv1yCNGjXKEZapUtwSaP0CQAX9ueeeK0N0w39G0UOzdt99d9E4ZApgXbp83HHHSbdu3eTZZ58tgkFF8WWXXSb33HOPs7Q5cwZYl1fPmzdPttULWzOKziDPnDnT+Zna6bWE1UdYAu01AgWf85pX/LVeeq2ePdOHNNpyYwF5JYyelF2bCODseMXqaS8DlVg5hLElEogyeRGW/BLIJtaNGqX3/r76anpPcH4tjvfbGKiYJ4APPPBAZ8lutkX3uX7wwQfZVgv0eS/XIF1yySWyb+pYXNFrfYreA9y+fXtH3I4fP146dOhQxMb9999fPvnkkwIC+MILL5SHHnpIXnjhBenatWuRAFLHsAAAIABJREFUOvq81jvllFPkueeeKyCA9X3vvPNOkTo62zxy5Eh5//33RePitSCAvZLKz3PZ5JWgLTrySJFx49xW77tP5OKLg36Dee2RV6KPCQI4ghjoHhxdOqTfRH/33XeidxhWr15dDjroIGc/T2opU66mIYBzJRif+lEmr/hQSoal2cT60ENFUmPWhx5KnwqdDBL58SIuAxWT8kpY4iYV8STMAGdzDVJxAlivRNJDpPSPzvYWLscff7zoTHLmDHDnzp3l9ddfL/MXR/cI6wx75gzw6aef7ix/Llx69uxZ4mFbpb0orD7CDHCZ4S32gWzyir83lFxr//1FPvnE/fnzz4ucfHLQbzCvvbjkFfPIBWcRAjg4lp5b2mmnnZwDKHRJ0QEHHOCI36+//trZl6PfDutJi7oMKdeCAM6VYHzqR5m84kMpGZZmE+vMpWXXXpu+FzgZJPLjRVwGKibllbDETSri7AEW505gFb+zZ892TmMuXHSpsy55zhTAnTp1kjfffNO5Pkr3+JZUtO1rrrmmgADWU6D1vmUEcH4+d/L9lmzyStC21a0r8uOPbqt6XZ9e25f0Epe8kuQ4IIAjiK5+e92rVy/nQIlKlSptskCvaDjvvPOcEx2/+OIL2XPPPXOyDgGcE75YVY4yecUKVAKMzSbWN9wgcuutrtOnnSby1FMJAJBnF+IyUDEpr4QtgDkFWkVCO3n33XezWgKtJzUPGzbMWYF29NFHl/mbVPgaJARwmchi+0A2eSVIJ/WsCr2lYP16t9UvvxT5z3+CfIOZbcUlr5hJLxirEMDBcAyslcMPP9xZGn3zzTfLTTfdlFO7COCc8MWqclTJK1aQEmJsNrF+9FGRc891HderQCdOTAiEPLqRhIFKvvNK2AJYw2/7PcB6H+/tt9/ufGn+8MMPF/iN0FOcdVa48CFYzz//vHMAln4B//jjj5f5W4QALhNRYh7IJq8E6fSqVSLbbJNucdkykZo1g3yDmW0lIa+YSda7VQhg76zy8uRVV13lXGqvyV1nhHMpCOBc6MWrblTJK16UkmFtNrHW7X6dO7t+168vMmdOMhjk04skDFTynVfyIYDXrl3rLOWdNGlSmd2hTZs28sYbb0hlnWqKuAR1DdKcOXOcVWK6YkwPp9IzRLToNUZ6wNWYMWOcv2cugdZ7fps0aeIsnR4wYIBz0rPeGZwq69evl7FjxzriWZ9DAEfcWfL4+mzySpBmffedSGoL+2abifz1l4j+N+klCXkl7jFCABsWwdSJijfeeKP069cvJ+sQwDnhi1XlqJJXrCAlxNhsYj1zpkjTpq7jm2/uXolUrlxCQOTJjSQMVPKdV/IhgDX8KoL1vIwnnnhC/tKRc6Gi4k5nO/V6HxPEr5rn5RRovVe3f//+m7wp7hAs/eHAgQOlT58+jgjWJdE1atSQqVOnOncD77333o4I1r+nxLHW0cPSdEXAggULpHbt2qLXGOl5JD/++KPzs19//dU5PEuvYUIA5+lDxoDXZJNXgjR36lSRVq3cFrffXmTx4iBbN7etJOQVc+l6swwB7I1TXp7Su/v0l+LPP/+Ujz/+WPbbb7+c3osAzglfrCpHlbxiBSkhxmYT619/FalePe340qUi222XEBB5ciPuA5Uo8kq+BHCqC+hNCrq3VffErl69WqpVqyZt27aVM888U7bXUbVBxcs9wCpeP//88zIFsD6gy5p11dhXX33lCFk96OrOO+8UPbVZr0hSUdtI70PLKL/88ovcd999jtDVmWQ9kVrFsPZ1PTxLvzDZcsstEcAG9ZuwTckmrwRpy6hRIscf77bYpInIF18E2bq5bcU9r5hL1rtlCGDvrEJ9Upcm6Te4U6ZMkZNPPtlJal5L6hep8PM68NGTHos7uMJr2zwXDwJr1qxxDK1atWo8DMZK3wSyibUeMHLUUa1l3boKzvuGDJkuDRv+7vvdNlY844wznN8rFRhxK1HmFWWmf/R0ap2RpOSPgH5G6BJmXQ6tM7s6Q+yn6BcZWsKIn7b9008/idqa+kzzY2PhOkuWVJZTT3WXg2sZP34Cq148gM0mr3hozvMjY8bUkcGDGzvP77vvSrn77vQXP54bieGDcc4rMcRdrMkIYB+R1G9H9cqibMpTTz0lLVq0KLHK+eefL0OGDJHddttNPvroI9l22209N48A9owqsQ9GlbwSC9Rgx7KNda9eB8iCBe4XI7fcMkMOOmiFwd6ZZ1q+BipJyysI4PD78rx585yxwtZbb73pZb///ruzt/eFF16Q7t27y4MPPujbEASwb3Sxq5htXgnKwaeeqifDh+/mNNehw2Lp2/froJo2up185RWjIURsHALYRwD2339/+SR1a7fH+pkHURSuont99MRnXaqlM8ANGjTw2Grpj7EEOhCMsWgkquVLsYCTMCOzjXWHDu7dilr0XL1zzkkYkJDdyddStSTllXwvgQ65Cxjb/B133OHcGKHbpXSmXZc2f/bZZ7J8+XLRfcPTpk3LaQm47gHWokurgy5h9ZH580Xq1Utbq5PYnHtQdvSyzStlt+jtiYsuEkl9R3PZZSL33uutXtyfyldeiTunMO1HAIdJ10Pb+u3sRRdd5HyDq/uXmjVr5qGWt0cQwN44JeGpqJJXEtjFzYdsY929u8gzz7he6s1qN98cN4+jtTeOA5Wo80pY4ibanmDe23W12D333OMI3aVLlzp7efUArS5dusjVV18t2+W44R8BbF7Mw7Io27wSlB1du4q8+KLb2u23i1x7bVAtm91OHPOK2USztw4BnD2zwGo888wzctppp0mVKlWcu38PPvjgwNrWhhDAgeI0urGokpfRUBJqXLaxvuoqkbvvdmGcfbaI3g1M8U4gbgMVE/IKAth7/zL5SQSwydEJ1rZs80pQb9f76VM3mQ0dKnLmmUG1bHY7ccsrZtP0Zx0C2B+3nGu9/vrrcswxxziHS+hVBYcddljObRZuAAEcOFJjG4wqeRkLJMGGZRtrXVJ2+eUuEL0TeOzYBMMJwbU4DVRMySsI4BA6YgRNIoAjgB7RK7PNK0GZucceejWX29qrr4p06RJUy2a3E6e8YjZJ/9YhgP2z811T7+Xr2LGjc2/hiy++6Ny3F0ZBAIdB1cw2o0peZtJItlXZxvqFF0ROOcVlsu++IlkeX5BsmB68i8tAxaS8ggD20LFi8AgCOAZBCsjEbPNKQK+VGjVEVq50W5s2TeSAA4Jq2ex24pJXzKaYm3UI4Nz4+apdvXp157L5XXfdVVq3bl1sG61atZKzzjrLV/upSgjgnPDFqnJUyStWkBJibLaxnjxZJPUxs8MOIosWJQREntyIy0DFpLyCAM5T5wz5NQjgkAEb1Hy2eSUI0//6S6RSpXRL8+YVPMAsiHeY2kZc8oqp/IKwCwEcBMUs2yjn4UjCHj165Hx/LwI4y8DE+PEokleMccXa9GxjPWeOSMOGrsv60bN+vUgF91pgigcCcRmomJRX9DCmb/9d19iwYUOpQIfz0NPMeyRMAax3VH/33XeO040bNxYv/dcLIU6B9kKp6DPZ5hV/bylYS7+MrVMn/W+//y5S1b2xL/ElLnklyYFAACc4ugjgBAe3kGtRJC976JrlabaxXrNGZMst0z78/HPBQYdZ3plnDQOVgjHxmlfmzp0r69evlzp16hS4p9a8CGNRSQTCFMCrVq2ShQsXSqVKlaR+/fqBBQEB7A9ltnnF31sK1poxQyR18YkKXxXAthTySvSRRgBHH4PQLPA6UAnNABrOG4EoklfenONFBQj4ifU224isWuU289FHIvvvD1SvBBio+BPAei3PihUrpHz58s5dtFWrVnUOfaTEh0AYAliXx69Zs0aWLFkiGzZskBo1akitWrUCg4IA9ofST17x96Z0rbfeEjn8cPfvu+4q8v33ubYYn/rklehjhQCOPgahWYAADg2tcQ1HkbyMg2CJQX5inXnS5ujRIkcfbQmsANxkoOJPAKu4WbBggaxbty6AKNBEFAQ0hlr0S4wwSuXKlZ17i4NsHwHsL1J+8oq/N6Vr/e9/Iqed5v5dD7/SQ7BsKeSV6CONAI4+BqFZgAAODa1xDUeRvIyDYIlBfmLdoYPIhAkuoCFDRM491xJYAbjJQMWfANZaKqB0Fnj16tXOcmhKvAiEMQOsBHTZc7Vq1ZzZ3yDFr7aNAPbXx/zkFX9vStcaNEjkiivcv+uXsvrlrC2FvBJ9pBHA0ccgNAsQwKGhNa7hKJKXcRAsMchPrLt3F3nmGRfQjTeK9OtnCawA3GSg4l8AZ9bUg7H0DyU+BN59913H2LZt2wZmtB52FdSBV8UZhQD2Fyo/ecXfm9K1rrlG5M473b/rpSePPZZri/GpT16JPlYI4OhjEJoFCODQ0BrXcBTJyzgIlhjkJ9ZXXSVy9912DjRy7RYMVIIRwLnGgfr5J+Dnsyb/VhZ8IwLYXwSiiPUZZ4g88YRrb9++Irfd5s/2ONYir0QfNQRw9DEIzQIEcGhojWs4iuRlHARLDPIT68GDRXr3dgF17iwydqwlsAJwk4EKAjiAbhTLJvx81kTtKALYXwSiiPVRR4m89pprr+aoSy/1Z3sca5FXoo8aAjj6GIRmAQI4NLTGNRxF8jIOgiUG+Yn1Cy+InHKKC2iffUQ+/dQSWAG4yUAFARxAN4plE34+a6J2FAHsLwJRxLp5c5GPP3btffZZkW7d/Nkex1rkleijhgCOPgahWYAADg2tcQ1HkbyMg2CJQX5iPXmySOvWLqDttxdZvNgSWAG4yUAFARxAN4plE34+a6J2FAHsLwJRxHrnnUV++sm1Vw9pbNfOn+1xrEVeiT5qCODoYxCaBQjg0NAa13AUycs4CJYY5CfWc+aINGzoAipXTuSvv/RqE0uA5egmAxUEcI5dKLbV/XzWRO0sAthfBPId63/+Ealc2c1FWr7+WkSv67OlkFeijzQCOPoYhGYBAjg0tMY1nO/kZRwAiwzyE+vVq0W22ioNSWeAdSaYUjYBBioI4LJ7STKf8PNZEzUJBLC/COQ71itWiNSsmbZ15UqR6tX92R7HWuSV6KOGAI4+BqFZgAAODa1xDec7eRkHwCKD/MRab5+pWlVk7VoX1IwZIk2bWgQtB1cZqCCAc+g+sa7q57MmaocRwP4ikO9Yf/WVyF57ubZWqiSybp27OsmWQl6JPtII4OhjEJoFetH8n3/+KQ1Tax9DexMNR01gzZo1jglVVeVQEk3Ab6y/+y693GyXXVxBTCmbwNy5c6VixYqyWqfRKUJesacT+P2siZKQLqnVz7pU2XPPKK2Jz7vzHWsdsuiXFVoqVkxv0YkPsdwsJa/kxi+I2gjgICga2kaFChVk48aN0rhxY0MtxKygCOiHqZb69esH1STtGEqAWOc3MAsWLHC+WFrMyWEOePJKfvtflG/jsyZK+vl9N7HOL2/ySn55F/c2BHD0MQjNApZYhIbWuIaJtXEhCc0gYh0aWhr2QID+5wFSQh4h1gkJpAc3iLUHSDySKAII4ESFs6AzfKAlOLiFXCPWxNoeAngaJQE+a6Kkn993E+v88o7ybcQ6Svq8OwoCCOAoqOfpnXyg5Qm0Aa8h1gYEIU8mEOs8geY1xRKg/9nTMYg1sbaHAJ7aRgABnOCIk7wSHFxmgO0JLrG2NtYmOk5eMTEq4dhErMPhamKrxNrEqGBTmAQQwGHSjbhtPtAiDkAeX0+s8wg74lcR64gDYPnr6X/2dABiTaztIYCnthFAACc44iSvBAeXWUF7gkusrY21iY6TV0yMSjg2EetwuJrYKrE2MSrYFCYBBHCYdGkbAhCAAAQgAAEIQAACEIAABIwhgAA2JhQYAgEIQAACEIAABCAAAQhAAAJhEkAAh0mXtiEAAQhAAAIQgAAEIAABCEDAGAIIYGNCgSEQgAAEIAABCEAAAhCAAAQgECYBBHCYdGkbAhCAAAQgAAEIQAACEIAABIwhgAA2JhQYAgEIQAACEIAABCAAAQhAAAJhEkAAh0mXtiEAAQhAAAIQgAAEIAABCEDAGAIIYGNCgSEQgAAEIAABCEAAAhCAAAQgECYBBHCYdCNqe926dTJgwAB57rnnZMGCBbLttttKp06dpH///rLTTjtFZFXyX/vHH3/IW2+9JWPGjJGPPvpIfvjhB9mwYYM0aNBATjjhBLn88stlyy23LBbEU089JQ888IB8/fXXUqlSJWnZsqVcf/31ctBBB5UI7v3335dbb71Vpk2bJuvXr5c999xTLrzwQunRo0eJdX766Se58cYb5Y033pCVK1dK3bp15ZRTTpG+fftK5cqVi61Hf/LWd5Vn48aNZdmyZdKoUSP59ttvS6xIvL0x5SlzCPA5EE0syCvRcDflreQVUyKBHUkjgABOWER1kNKhQwdRcVS7dm055JBDHCE2ffp02W677eSDDz6Q+vXrJ8xrM9wZOnSonH322Y4x//nPfxxB+ttvvzmxWL16tSOOJk2aJLVq1SpgsArje++9V6pUqSKHHXaYaAzfeecd2bhxo7z44oty3HHHFXFw1KhRctJJJ8k///wjrVu3lpo1azp1fv31V+ndu7cMGjSoSJ25c+fKgQce6Ai0vfbay7Hv448/lu+//97594kTJ8rmm29eoB79yXvf6tmzp6iw1biVJoCJt3emPGkGAT4HoosDeSU69ia8mbxiQhSwIYkEEMAJi6rO7t1yyy2OoNHZyNSMowqiK664whFLKsIowRNQ8aOzsSpAGzZsuOkFixYtks6dO8tnn30m3bp1k2effXbTzyZMmOB8YVGjRg3ny4lUPf3/tm3bOqJ43rx5Ur169U11fvnlF9l1111l1apVMnLkSDn++OOdny1ZskRatWolc+bMEW23Xbt2BZxs06aNvPfee3LJJZfIf//7X+dnf//9t3Tt2lVUUGvf6devX4E69Cdv/US/fDj00EPlnHPOkUcffbREAUy8vfHkKbMI8DkQXTzIK9Gxj/rN5JWoI8D7k0wAAZyg6P7111/O7KLOAn766aeyzz77FPBu7733li+++MKZ9dtvv/0S5Ln5rqig1eXMOsOqs8K6zFmLCuPXX3/dmQG+7LLLCjhy6aWXyn333ScDBw50vrxIlbvvvluuuuoqOeaYY+SVV14pUEeFrArio446ylmKnSq6JLtFixZO/9Bl8ZkzvSqcd955Z+fLEv3/ihUrOtXoT9761dq1a6Vp06ZOTDUeu+++e4kCmHh7Y8pT5hDgc8CcWBS2hLxibmxytYy8kitB6kOgdAII4AT1EF3C2r59e2eJs84CFi46M6zf5N90001y8803J8hz813RfVxVq1Z1DF24cKGzPF2XFW6zzTby559/yo8//lhkf/bkyZOdGXuduX333Xc3OZmayX366aele/fuBZzXvcBbb7218286U5za16sx1z3gZ555puiSusJFZ6F1dlL7kM48a6E/eetX11xzjdx1111OjHRPtc7OF7cEmnh748lTZhHgc8CseGRaQ14xNza5WkZeyZUg9SGAALamDwwePNhZfqt7Q0eMGFHE79dee82ZGTz22GOdJa+U/BH48ssvpUmTJs7squ4H1hnYzz//3Jml173ZS5cuLWLMmjVrnFlZXf6sB2Gkiv5dZ/m/+uorZx9v4dK8eXNnll/b11l/LRrz0aNHy4MPPigXXHBBkTp9+vRxZpq1D+nMsxb6U9n9Q1dU6GqK008/XYYNG+bsty9JABPvsnnyhHkE+BwwLyYpi8gr5sYmF8vIK7nQoy4EvBFgBtgbp1g8lTpcp6RDkGbMmCHNmjWTfffdVz755JNY+JQUI/VwLJ157dKli7z66quOW/pfXcasIliXrBdXUmJXl01Xq1bNWT6dmuHVPcBbbbVVkWp6aJYuxdX29X1aNOa6B1lF8NFHH12kju4J1iXY2ofuuece5+f0p9J7nx5Apnvt9RAxPfFZ93GXJoCJd1J+m+3yg88Bc+NNXjE3Nn4tI6/4JUc9CGRHAAGcHS+jn9YDeB577DG57rrrnOtxChddFq2HLOkexVmzZhntS5KM0z2+OvNeoUIF53qk1KysHob1f//3f3LwwQfLlClTinVZr636+eefNy2b1uXTO+64o/Os7s3TNgsXXRb9zDPPOIdt6aFbWjTm3333nbz99tvOYU2FS+qkUe1DjzzyiPNj+lPpvTD1pcETTzwhelKnltIEMPFO0m+1Pb7wOWBmrMkrZsYlV6vIK7kSpD4EvBFAAHvjFIunUt8G6/2xut+3cFEBpEIIAZy/cH7zzTeOwNX9uJnLi9UCFakqVvXkZt3vW1xRsauiN7VvWMVw6i7nkgSwimoVW5kCWL/40C9Axo8f75w6XbjoFyc60M0UwPSnkvuJ7tnW5ee6/Dlzf3ZpAph45+/3jjcFR4DPgeBYBtUSeSUokma1Q15hYsasHplsaxDACYovS9XMCuZPP/3kiF89dTlzaXHKSpbEmhWvbKzRpeV6zZju691jjz02VWUJdDYUeTYOBMgrZkWJvGJWPIK0hrzC1rwg+xNtlU4AAZygHsJhJeYEc/ny5XLIIYc4e0N79erlHJBUrly5AgZ6PRRJT4rWGeRU0b/r/l8OwYou3hpLjUNqOXvKEj3p+cMPP3Tub9Zrp7SMHTvWOcyMeEcXL97snwB5xT+7oGuSV4ImalZ75BUOZzWrRybbGgRwguLr9boKvQqpX79+CfLcLFf0lGe9jkpPYtY7efVE7vLlyxcxUu/500OuyroGSa9CmjRp0qb6pV2DpMui9WCsjRs3OidFZ3sNkl6F1K5dO+dd9KeS+1XhLzNK64H65YWKZeJt1u8p1ngjwOeAN05hP0VeCZtw9O2TVxiXRt8L7bEAAZygWOsdsLVq1XJmB/VUYT1dOLPobJUerz99+nTRq3IowRNQMXvEEUc44vHwww93TmKuVKlSiS868sgjZdy4cXLvvfc6pzBnFr2O6L777nPumNVrilJF/3711Vc7J0jrac+ZRa+3UtGt7eq1V6miMT/ggAOc/qFLsvUaplRZsmSJ7LzzzrLFFlvIsmXLnKuatNCfsu8fpS2B1taId/ZMqREtAT4HouWvbyevRB+DKC0gr0RJn3cnlQACOGGR1QOwbrvtNjnooIOcPYpVq1Z1PBw0aJBcccUVpR64lDAUeXdnw4YNzh3MKkJ1+fMbb7zhiMrSih5K1bFjR+cKnQ8++MA5pVuL/r/OxKpQnTdvnmy77babmtE7gfWuWb0SaeTIkY7g1aJ3Ceue45IOu9LDtqZOnerc86vLGrX8/fffcvLJJ8vLL78sxR2eRn/KrhuVNVAh3tnx5GkzCPA5EF0cyCvRsTflzeQVUyKBHUkigABOUjRFRPcgtm3b1tmHWLt2bUeIzZ8/3/m7iqxp06ZJgwYNEua1Ge6kri9Qa/Qu3uLu6NWfDRw4UGrWrLnJaJ351boqllUM64yLXlek9wHq8ukTTjihiIMqfLt27eosddYl0dqeiitd9nzJJZc47RUuegq43lu7YsUKadKkiXOKsV7LpPfY6uywnmacWjKdqkt/yq5vlTVQ0daId3ZMeTp6AnwORBcD8kp07E15M3nFlEhgR5IIIICTFM1/fdG9hgMGDHCuwdFj9XWfaadOnZyrkXSpKyUcAjfffLOnvdU6o1uvXr0CRjz55JPywAMPiF5voUuQW7Zs6czI6qxtSUVnc/W+Z/1SQ0WznkZ84YUXOodulVS0P+gecJ2d1plk7Q96V3Dfvn2dg5uKK/Qn7/3Fy0BFWyPe3pnypBkE+ByIJg7klWi4m/RW8opJ0cCWpBBAACclkvgBAQhAAAIQgAAEIAABCEAAAqUSQADTQSAAAQhAAAIQgAAEIAABCEDACgIIYCvCjJMQgAAEIAABCEAAAhCAAAQggACmD0AAAhCAAAQgAAEIQAACEICAFQQQwFaEGSchAAEIQAACEIAABCAAAQhAAAFMH4AABCAAAQhAAAIQgAAEIAABKwgggK0IM05CAAIQgAAEIAABCEAAAhCAAAKYPgABCEAAAhCAAAQgAAEIQAACVhBAAFsRZpyEAAQgAAEIQAACEIAABCAAAQQwfQACEIAABCAAAQhAAAIQgAAErCCAALYizDgJAQhAAAIQgAAEIAABCEAAAghg+gAEIAABCEAAAhCAAAQgAAEIWEEAAWxFmHESAhCAAAQgAAEIQAACEIAABBDA9AEIQAACEIAABCAAAQhAAAIQsIIAAtiKMOMkBLwRuOiii+TBBx8s8HCFChVk5513lmOPPVZuvvlm2Wqrrbw1JiL9+vWT/v37y8yZM2XPPfd06v3www+y6667Sps2beTdd9/11Fa5cuVkl112cermUhYtWiS77babnHHGGUX8zKVd6kIAAhCAQPEEyCv0DAhAwDQCCGDTIoI9EIiQwCGHHCJTpkyRzp07S82aNR1LFi9eLBMmTJC//vpLmjdvLh988IGUL1++TCuXLFkiDRo0cNp6/vnnNz0fpQBWIy699FJ56KGH5Msvv5RGjRqV6QcPQAACEICAfwLkFf/sqAkBCIRDAAEcDldahUDsCGzcuFG22WYb+e2332ThwoVSu3btTT58+OGH0qpVK/n7779lzJgxctRRR5XpnwrN++67Tz7//HPZe++9cxLA3377rVSsWFHq169f5nvLeuDnn3+WunXryoknnigvvPBCWY/zcwhAAAIQ8EmAvOITHNUgAIFQCSCAQ8VL4xCID4Hvv//eEZjbbrutrFixoojhHTp0cGaCdUnzDTfcUKpjf/zxh9SpU8dZtjxjxowCz/qZAQ6a4qGHHirvvfee/Pjjj7L99tsH3TztQQACEICAiJBX6AYQgICJBBDAJkYFmyAQAYFRo0bJ8ccfL61bt5ZJkyYVseDoo492Zn+9CODhw4dLz5495c4775SrrrrKswDWPcH6Hi36Lt0nrKW4PcCZQvrVV191RPnLL78sy5aW4QX1AAAgAElEQVQtc/YYn3POOc5y580226yIL48//riceeaZcscdd8jVV18dAW1eCQEIQCD5BMgryY8xHkIgjgQQwHGMGjZDIAQCesCVHlp1wQUXFHtA1B577CG6FPnpp5+W7t27l2rBSSedJC+99JLo0ukWLVp4EsCjR4+WU045RapVqybjxo2T/fbbb1O90gRwy5Ytnf3Jc+fOlfbt28v69evlnXfekbVr1zoi/Iknnihia2pWQvem6UwwBQIQgAAEgidAXgmeKS1CAAK5E0AA586QFiCQCALHHXecvPLKK84BUeeff34Bn958803p1KmTVKlSRebPny/bbbddqT7r/uGVK1c6+4k333zzMgXwk08+KWeddZazbPrtt98ucjhVaQJYG2/atKkjelMHd6kY1pls3cuswjo1q5xpiPqwevVqWbVqVREbExFQnIAABCAQMQHySsQB4PUQgECxBBDAdAwIQMAhoMuGdVmxzojqzKgeXqJ7ZF9//XW59tpr5ddff5UBAwbINddcUyqxpUuXOvtqGzZsKLNnzy7ybOE9wIMGDZIrr7xSdt99d0f86pVLhUtZAvitt96Sjh07Fqg2ZMgQR8gfdthhogK+cNFDvaZOnersUVYBTYEABCAAgWAJkFeC5UlrEIBAMAQQwMFwpBUIxJqAztRuvfXWJfqgM7+6lK3wft7iKuj1Qk2aNHGWPusS6MIlUwAffPDBcvvtt8u+++4rb7zxRokzy6UJ4JIO7Ur5tOWWWzoz0dpGZkntaR4/frzoAV8UCEAAAhAIjgB5hbwSXG+iJQgESwABHCxPWoNALAlMnjzZWTKsy4KPPPJIxwe967d69erO7Khee6RC00vRWVWdXVVRqeKyJAFcoUIF51qlHXbYQWbNmiVbbbVVic2XJoD32Wcf+fTTT4utq/brzLX+KSzwdR/zM888IyNHjnQO/6JAAAIQgEBwBMgr5JXgehMtQSBYAgjgYHnSGgRiSeCBBx6Qiy++WLp16ybPPvtsTj6kZoCbN28u06dPL1EAp5Ydf/HFF3LZZZfJvffeG7gA1nuNdY9vcQK4S5cuMnbsWEekMwOcU8ipDAEIQKAIAfIKM8D8WkDAVAIIYFMjg10QyCMBPYBq2LBhxV5blK0ZqT3AeqfwnDlzShTAesWRnhTdrl07UdF8xRVXyMCBA4t9XWkzwDVq1JDly5cXqZdafle1alXnsKvCS6DZA5xtZHkeAhCAgHcC5BXOlvDeW3gSAvklgADOL2/eBgEjCehs7ccff+wcFqWHRuVa9BRoFaUqQnX/cGYpfAiWCma9vuirr75y7uTVu3kLl7IOwdLDsw499NAC1R555BE577zznMOx9JCswkVPjF6zZo0zO1z4pOpc/ac+BCAAAdsJkFcK3oBge3/AfwiYRAABbFI0sAUCERDYsGGDc/eu3pu7ePFi5wTnXEvXrl3lxRdfdE5ZPuigg0oVwPpDFcFt27aVb775Rq677jq59dZbC9QpSwA3a9bMWcqss8Fa5s2b55xk/fPPP8uoUaPk2GOPLdCeXpPUoEEDZ9/zpEmTcnWX+hCAAAQgkEGAvEJe4RcCAiYTQACbHB1sg0AeCKjo3HPPPZ3DqBYtWhTIG4cPHy49e/Z0hKwK2sxSeAY49TMV3yqC9UCsG2+8Ufr167epWmkCuGXLlrJ+/XpH9OpMsv6/3gn8xx9/iB509fTTTxfxSZd76/I8nW3WWWcKBCAAAQgER4C8Ql4JrjfREgSCJ4AADp4pLUIgVgSef/555/CrTp06ybhx4wKxXWeTdRn0jjvu6Cxt9iKA9RkV4CqC9f7g/v37yw033OBULU0A617i0aNHS9++feWVV15xll7r3ZNnn322c7iWnmZduOihV3pCqd5zHMSMdyDQaAQCEIBAQgiQV3JfSZWQroAbEDCSAALYyLBgFATiT6B3794yePBg+eSTT5x7foMuJc0kl/Wen376SXbZZRc58cQT5YUXXijrcX4OAQhAAAKGECCvGBIIzIBAzAkggGMeQMyHgKkEdF+vngR9xBFHyIgRIwI3068AvvTSS+Whhx5yTp5u1KhR4HbRIAQgAAEIhEOAvBIOV1qFgG0EEMC2RRx/IZBHArqMWffyzpw509lnHGTxI4B1ifVuu+0mvXr1ckQwBQIQgAAE4kWAvBKveGEtBEwkgAA2MSrYBAEIlEnAjwAus1EegAAEIAABawmQV6wNPY5bRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6/IQABCEAAAhCAAAQgAAEIWEYAAWxZwHEXAhCAAAQgAAEIQAACEICArQQQwLZGHr8hAAEIQAACEIAABCAAAQhYRgABbFnAcRcCEIAABCAAAQhAAAIQgICtBBDAtkYevyEAAQhAAAIQgAAEIAABCFhGAAFsWcBxFwIQgAAEIAABCEAAAhCAgK0EEMC2Rh6//7/9OiYAAABgENS/tUEkwtglAQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+b63IFjMAAAGoSURBVDcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKCODr83YTIECAAAECBAgQIEBgJiCAZ4ebS4AAAQIECBAgQIAAgauAAL4+bzcBAgQIECBAgAABAgRmAgJ4dri5BAgQIECAAAECBAgQuAoI4OvzdhMgQIAAAQIECBAgQGAmIIBnh5tLgAABAgQIECBAgACBq4AAvj5vNwECBAgQIECAAAECBGYCAnh2uLkECBAgQIAAAQIECBC4Cgjg6/N2EyBAgAABAgQIECBAYCYggGeHm0uAAAECBAgQIECAAIGrgAC+Pm83AQIECBAgQIAAAQIEZgICeHa4uQQIECBAgAABAgQIELgKBPBMMBHhc3TAAAAAAElFTkSuQmCC\" 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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\numpy\\core\\_asarray.py:85: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return array(a, dtype, copy=False, order=order)\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\numpy\\core\\_asarray.py:85: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return array(a, dtype, copy=False, order=order)\n"
     ]
    }
   ],
   "source": [
    "# Creating a figure\n",
    "plt.figure()\n",
    "\n",
    "# Loop through two load cases\n",
    "for lc in [1,2]:\n",
    "\n",
    "    ops.wipe()\n",
    "    ops.model('basic','-ndm',2,'-ndf',3)\n",
    "\n",
    "    L = 12*ft\n",
    "    H = 30*ft\n",
    "    Lc = L\n",
    "    Lg = H\n",
    "    \n",
    "    ops.node(1,0,0); ops.fix(1,1,1,1)\n",
    "    ops.node(2,0,L)\n",
    "    ops.node(3,H,L)\n",
    "    ops.node(4,H,0); ops.fix(4,1,1,1)\n",
    "\n",
    "    # W14x90\n",
    "    A = 26.5\n",
    "    Ic = 999\n",
    "    ops.section('Elastic',1,E,A,Ic)\n",
    "    ops.beamIntegration('Legendre',1,1,2)\n",
    "\n",
    "    # W18x76\n",
    "    A = 22.3\n",
    "    Ig = 1330\n",
    "    ops.section('Elastic',2,E,A,Ig)\n",
    "    ops.beamIntegration('Legendre',2,2,2)\n",
    "\n",
    "    # Corotational transformation\n",
    "    ops.geomTransf('Corotational',1)\n",
    "\n",
    "    # Number of elements/member\n",
    "    Nele = 8\n",
    "\n",
    "    # Columns\n",
    "    dm.DiscretizeMember(1,2,Nele,'dispBeamColumn',1,1,10,10)\n",
    "    dm.DiscretizeMember(3,4,Nele,'dispBeamColumn',1,1,30,30)\n",
    "\n",
    "    # Beam\n",
    "    dm.DiscretizeMember(2,3,Nele,'dispBeamColumn',2,1,20,20)\n",
    "\n",
    "    ops.numberer('RCM')\n",
    "    ops.system('FullGeneral')\n",
    "    ops.constraints('Plain')\n",
    "    ops.integrator('LoadControl',0)\n",
    "    ops.test('NormUnbalance',1e-8,10,0)\n",
    "    ops.algorithm('Newton')\n",
    "    ops.analysis('Static')\n",
    "\n",
    "    \n",
    "    # Analyze with no loads\n",
    "    ops.analyze(1)\n",
    "\n",
    "    # Get number of equations\n",
    "    N = ops.systemSize()\n",
    "\n",
    "    # Get material stiffness\n",
    "    Kmat = ops.printA('-ret')\n",
    "    Kmat = np.array(Kmat)\n",
    "    Kmat.shape = (N,N)\n",
    "\n",
    "    # Apply reference loads\n",
    "    ops.timeSeries('Constant',1)\n",
    "    ops.pattern('Plain',1,1)\n",
    "    if lc == 1:\n",
    "        ops.load(2,0,-1.0,0)\n",
    "        ops.load(3,0,-1.0,0)\n",
    "    if lc == 2:\n",
    "        ops.load(2,0,-2.0,0)\n",
    "\n",
    "    # Analyze for reference loads\n",
    "    ops.analyze(1)\n",
    "\n",
    "    # Get geometric stiffness\n",
    "    Kgeo = ops.printA('-ret')\n",
    "    Kgeo = np.array(Kgeo)\n",
    "    Kgeo.shape = (N,N)\n",
    "    Kgeo = Kmat-Kgeo\n",
    "\n",
    "    # Eigenvalue analysis, and sorting\n",
    "    lam, x = slin.eig(Kmat,Kgeo)\n",
    "    lamSort = np.sort(lam[lam>0])\n",
    "\n",
    "    # for plotting mode shapes later in the notebook\n",
    "    if lc == 1:\n",
    "        x_lc1 = x\n",
    "        lam_lc1 = lam\n",
    "    if lc == 2:\n",
    "        x_lc2 = x\n",
    "        lam_lc2 = lam \n",
    "        \n",
    "        \n",
    "    #    \n",
    "    # Now get \"exact\" solution for this load case\n",
    "    # We are using direct assembly with exact stability functions for the columns\n",
    "    #    \n",
    "    Kmat = np.zeros((3,3))\n",
    "    \n",
    "    if lc == 1:\n",
    "        l1 = 1\n",
    "        l3 = 1\n",
    "    if lc == 2:\n",
    "        l1 = 2\n",
    "        l3 = 0\n",
    "        \n",
    "            \n",
    "    Pplot = []\n",
    "    Kplot = []\n",
    "    \n",
    "    Pmax = 55000*kip\n",
    "    Nsteps = 1000\n",
    "    dP = Pmax/Nsteps\n",
    "\n",
    "    # Axial load\n",
    "    P = 0\n",
    "    while P <= Pmax:\n",
    "\n",
    "        # Element 1\n",
    "        psi = Lc*(l1*P/(E*Ic))**0.5\n",
    "        if psi > 0:\n",
    "            B1 = (psi*np.sin(psi)-psi**2*np.cos(psi))/(2*(1-np.cos(psi))-psi*np.sin(psi))\n",
    "            C1 = (psi**2-psi*np.sin(psi))/(2*(1-np.cos(psi))-psi*np.sin(psi))\n",
    "        else: \n",
    "            # Regular 4EI/L and 2EI/L from linear structural analysis\n",
    "            B1 = 4\n",
    "            C1 = 2\n",
    "\n",
    "        # Element 3\n",
    "        psi = Lc*(l3*P/(E*Ic))**0.5\n",
    "        if psi > 0:\n",
    "            B3 = (psi*np.sin(psi)-psi**2*np.cos(psi))/(2*(1-np.cos(psi))-psi*np.sin(psi))\n",
    "            C3 = (psi**2-psi*np.sin(psi))/(2*(1-np.cos(psi))-psi*np.sin(psi))\n",
    "        else:\n",
    "            # Regular 4EI/L and 2EI/L from linear structural analysis\n",
    "            B3 = 4\n",
    "            C3 = 2\n",
    "\n",
    "        # Direct assembly of stiffness matrix for this level of axial loads\n",
    "        Kmat[0,0] = 2*(B1+C1)*E*Ic/Lc**3 + 2*(B3+C3)*E*Ic/Lc**3 - l1*P/Lc - l3*P/Lc\n",
    "        Kmat[1,0] = (B1+C1)*E*Ic/Lc**2\n",
    "        Kmat[2,0] = (B3+C3)*E*Ic/Lc**2\n",
    "\n",
    "        Kmat[0,1] = Kmat[1,0]\n",
    "        Kmat[1,1] = B1*E*Ic/Lc + 4*E*Ig/Lg\n",
    "        Kmat[2,1] = 2*E*Ig/Lg\n",
    "\n",
    "        Kmat[0,2] = Kmat[2,0]\n",
    "        Kmat[1,2] = Kmat[2,1]\n",
    "        Kmat[2,2] = B3*E*Ic/Lc + 4*E*Ig/Lg\n",
    "\n",
    "        Pplot.append(P)\n",
    "        Kplot.append(np.linalg.det(Kmat)) # When determinant is zero, we know the value of P is critical\n",
    "\n",
    "        P += dP\n",
    "\n",
    "    plt.subplot(2,2,lc)\n",
    "    plt.plot(Pplot,Kplot,'b-',markersize=1,label='Direct')\n",
    "    Nmodes = 3\n",
    "    plt.plot(lamSort[:Nmodes],[0]*Nmodes,'ko',label='Eigen')   \n",
    "    plt.grid()\n",
    "    plt.xlim([0,Pmax])\n",
    "    plt.xlabel('$P$ (kip)')\n",
    "    plt.ylim(-1.2*Kplot[0],1.2*Kplot[0])\n",
    "    if lc == 1:\n",
    "        plt.ylabel('$\\det({\\\\bf K})$')\n",
    "    plt.title(f'Load Case {lc}')\n",
    "    plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# draw model:\n",
    "import eSEESminiPy\n",
    "eSEESminiPy.drawModel()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sort mode shapes for plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to sort lambda and modeshape vectors accordingly\n",
    "    \n",
    "def sortModes(lam,x):\n",
    "    \n",
    "    #sort lambda and x\n",
    "    lambda_sorted = np.sort(lam)\n",
    "    lambda_inds = lam.argsort()\n",
    "    x_Sort = np.zeros_like(x)\n",
    "    \n",
    "    for count, index in enumerate(lambda_inds):\n",
    "        x_Sort[:,count]=x[:,index]\n",
    "\n",
    "    \n",
    "    #only modes with positive lambda\n",
    "    index = 0\n",
    "    while index<len(lambda_sorted) and lambda_sorted[index]<0:\n",
    "        index+=1\n",
    "    lamSort = lambda_sorted[index:]\n",
    "    x_Sort  = x_Sort[:,index:]\n",
    "    \n",
    "    return lamSort,x_Sort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "lam_lc1, x_lc1 = sortModes(lam_lc1,x_lc1) \n",
    "lam_lc2, x_lc2 = sortModes(lam_lc2,x_lc2) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Function to plot mode shapes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "# function to plot the mode shapes\n",
    "# from https://github.com/zhuminjie/OpenSeesPyDoc/blob/master/src/ops_vis/ops_vis.py\n",
    "\n",
    "# default settings\n",
    "\n",
    "# fmt: format string setting color, marker and linestyle\n",
    "# check documentation on matplotlib's plot\n",
    "\n",
    "# continuous interpolated shape line\n",
    "fmt_interp = 'b-'  # blue solid line, no markers\n",
    "\n",
    "# element end nodes\n",
    "fmt_nodes = 'rs'  # red square markers, no line\n",
    "\n",
    "# deformed model\n",
    "fmt_defo = 'b-'  # green dashed line, no markers\n",
    "\n",
    "# undeformed model\n",
    "fmt_undefo = 'g:'  # green dotted line, no markers\n",
    "\n",
    "# section forces\n",
    "fmt_secforce = 'b-'  # blue solid line\n",
    "\n",
    "# figure left right bottom top offsets\n",
    "fig_lbrt = (.04, .04, .96, .96)\n",
    "\n",
    "# azimuth and elevation in degrees\n",
    "az_el = (-60., 30.)\n",
    "\n",
    "# figure width and height in centimeters\n",
    "fig_wi_he = (16., 10.)\n",
    "\n",
    "#sfac=False\n",
    "\n",
    "nep=17\n",
    "unDefoFlag=1\n",
    "fmt_undefo='g:'\n",
    "interpFlag=1\n",
    "endDispFlag=0\n",
    "fmt_interp='b-'\n",
    "fmt_nodes='rs'\n",
    "Eo=0,\n",
    "az_el=(-60.0, 30.0)\n",
    "fig_wi_he=(16.0, 10.0)\n",
    "fig_lbrt=(0.04, 0.04, 0.96, 0.96)\n",
    "\n",
    "def plot_buckling_mode(mode,lambda_,vec,scalefac=10):  # modified from   _plot_defo_mode_2d    function\n",
    "    sfac=scalefac\n",
    "    \n",
    "    ele_tags = ops.getEleTags()\n",
    "    #plt.figure()\n",
    "    for ele_tag in ele_tags:\n",
    "        nd1, nd2 = ops.eleNodes(ele_tag)\n",
    "        \n",
    "        DOFs_nd1 = ops.nodeDOFs(nd1)\n",
    "        DOFs_nd2 = ops.nodeDOFs(nd2)\n",
    "        # element x, y coordinates\n",
    "        ex = np.array([ops.nodeCoord(nd1)[0],\n",
    "                       ops.nodeCoord(nd2)[0]])\n",
    "        ey = np.array([ops.nodeCoord(nd1)[1],\n",
    "                       ops.nodeCoord(nd2)[1]])\n",
    "    \n",
    "        #if modeNo:\n",
    "        if DOFs_nd1[0] != -1:\n",
    "            ed1 = -vec[DOFs_nd1[0],mode]\n",
    "        else:\n",
    "            ed1 = 0  \n",
    "        if DOFs_nd1[1] != -1:\n",
    "            ed2 = -vec[DOFs_nd1[1],mode]\n",
    "        else:\n",
    "            ed2 = 0  \n",
    "        if DOFs_nd1[2] != -1:\n",
    "            ed3 = -vec[DOFs_nd1[2],mode]\n",
    "        else:\n",
    "            ed3 = 0  \n",
    "        if DOFs_nd2[0] != -1:\n",
    "            ed4 = -vec[DOFs_nd2[0],mode]\n",
    "        else:\n",
    "            ed4 = 0  \n",
    "        if DOFs_nd2[1] != -1:\n",
    "            ed5 = -vec[DOFs_nd2[1],mode]\n",
    "        else:\n",
    "            ed5 = 0  \n",
    "        if DOFs_nd2[2] != -1:\n",
    "            ed6 = -vec[DOFs_nd2[2],mode]\n",
    "        else:\n",
    "            ed6 = 0  \n",
    "        \n",
    "        ed = np.array([ed1,\n",
    "                       ed2,\n",
    "                       ed3,\n",
    "                       ed4,\n",
    "                       ed5,\n",
    "                       ed6])\n",
    "    \n",
    "        if unDefoFlag:\n",
    "            plt.plot(ex, ey, fmt_undefo)\n",
    "    \n",
    "        # interpolated displacement field\n",
    "        if interpFlag:\n",
    "            xcdi, ycdi = opsv.beam_defo_interp_2d(ex, ey, ed, sfac, nep)\n",
    "            plt.plot(xcdi, ycdi, fmt_interp)\n",
    "    \n",
    "        # translations of ends\n",
    "        if endDispFlag:\n",
    "            xdi, ydi = opsv.beam_disp_ends(ex, ey, ed, sfac)\n",
    "            plt.plot(xdi, ydi, fmt_nodes)\n",
    "    \n",
    "    plt.axis('equal')\n",
    "    plt.title(\"Mode \"+str(mode+1)+'; lambda = '+str(int(np.real(lambda_[mode]))), x=0.5, y=0.8)\n",
    "    #plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot mode shapes for load case 1\n",
    "\n",
    "Notice the symmetry of the buckled shapes resulting from the symmetry of the loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scale_factor = 50\n",
    "lam = lam_lc1; x = x_lc1\n",
    "plt.figure()\n",
    "plt.subplot(2, 2, 1)\n",
    "plot_buckling_mode(0,lam,x,scale_factor)   #mode 1\n",
    "plt.subplot(2, 2, 2)\n",
    "plot_buckling_mode(1,lam,x,scale_factor)   #mode 2\n",
    "plt.subplot(2, 2, 3)\n",
    "plot_buckling_mode(2,lam,x,scale_factor)   #mode 3\n",
    "plt.subplot(2, 2, 4)\n",
    "plot_buckling_mode(3,lam,x,scale_factor)   #mode 4\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot mode shapes for load case 2\n",
    "\n",
    "Notice the asymmetry of the buckled shapes resulting from the asymmetric loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scale_factor = 50\n",
    "lam = lam_lc2; x = x_lc2\n",
    "plt.figure()\n",
    "plt.subplot(2, 2, 1)\n",
    "plot_buckling_mode(0,lam,x,scale_factor)   #mode 1\n",
    "plt.subplot(2, 2, 2)\n",
    "plot_buckling_mode(1,lam,x,scale_factor)   #mode 2\n",
    "plt.subplot(2, 2, 3)\n",
    "plot_buckling_mode(2,lam,x,scale_factor)   #mode 3\n",
    "plt.subplot(2, 2, 4)\n",
    "plot_buckling_mode(3,lam,x,scale_factor*4)   #mode 4\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}