spin_entropy_fitting.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib as mpl\n",
    "mpl.style.use('paper.rc')\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import peakutils\n",
    "import os, glob\n",
    "from lmfit import Model, Parameter\n",
    "import data_tools as dt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Directories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_dir = os.path.join('./raw_data')\n",
    "analysis_dir = os.path.join('./analysis')\n",
    "fig_dir = os.path.join('./figures')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Constants\n",
    "\n",
    "Determined in `characterize_dot.ipynb`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "MU_B = 5.7883818012e-5 # eV/T\n",
    "K_B = 8.6173303e-5 # eV/K\n",
    "\n",
    "ALPHA1_CLSD = 0.0469\n",
    "ALPHA1_OPN = 0.0295\n",
    "G1_OPN = 0.417\n",
    "ALPHA2_CLSD = 0.0442\n",
    "ALPHA2_OPN = 0.0333\n",
    "G2_OPN = 0.400\n",
    "ALPHA3_CLSD = 0.0415\n",
    "ALPHA3_OPN = 0.0265"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calibrate Heater\n",
    "\n",
    "Find conversion between applied power and dT using dataset 944. Here, a DC current ($I^{DC}_{Heat}$) was used to heat the reservoir."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
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       "    } 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",
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       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
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       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
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       "\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",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
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       "\n",
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       "            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",
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       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
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       "\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",
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       "    canvas_div.append(rubberband);\n",
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       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
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       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
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       "        // 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",
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       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
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       "        return false;\n",
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       "\n",
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       "        canvas_div.focus();\n",
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       "\n",
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       "\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",
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       "        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",
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       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
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       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "T_{base} (mK) = 113.7\n",
      "\\Theta (mV) = 0.2089*\\sqrt{0.4988*P(pW) + 1}\n"
     ]
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1,1)\n",
    "\n",
    "dat = 944\n",
    "xmult = [0.5, 1e-3*2e-8] # plunger in mV, I_AC in Amps\n",
    "avgs = 5\n",
    "\n",
    "### import i_sense ###\n",
    "swp = dt.open_hdf5(dat, path=data_dir) # load sweep data\n",
    "x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['i_sense_dc2d'][:], \n",
    "                        avgs, axis=1) # rolling mean of sensor data\n",
    "z = z*1e9 # i_sense (nA)\n",
    "y = swp['y_array'][:]*xmult[1]*1e9 # I_AC (nA)\n",
    "\n",
    "### fit i_sense curves ###\n",
    "span = 5.0\n",
    "xlim = (-490, -482)\n",
    "centers = -486*np.ones(len(z))\n",
    "widths = 0.6*np.ones(len(z))\n",
    "\n",
    "i_results = dt.i_sense_fit_simultaneous(x, z, centers, \n",
    "                                        widths, xlim, constrain = None, span = span)\n",
    "i_results['i_heat'] = y\n",
    "\n",
    "### calculate DC power ###\n",
    "v = swp['vdc_heat2d'][:].mean(axis=1)\n",
    "v = v-v[20] # subtract offset voltage\n",
    "p = (i_results['i_heat'].values*1e-9)*v*1e12 # pW\n",
    "i_results['p_heat'] = p\n",
    "\n",
    "### fit theta vs current ###\n",
    "def theta_fit(x, a, b):\n",
    "    return a*np.sqrt(b*x + 1)\n",
    "\n",
    "idx = i_results['p_heat']<5.0\n",
    "popt, _ = dt.curve_fit(theta_fit, i_results['p_heat'][idx], i_results['theta'][idx])\n",
    "theta_calc = theta_fit(i_results['p_heat'], *popt)\n",
    "t_calc = ALPHA1_CLSD*theta_calc/(K_B)\n",
    "i_results['T_electron'] = t_calc\n",
    "\n",
    "ax.scatter(i_results['i_heat'], i_results['theta'], s=20)\n",
    "ax.plot(i_results['i_heat'], theta_calc, c='C3')\n",
    "ax.set_xlabel(r'$I^{DC}_{Heat}$ (nA)')\n",
    "ax.set_ylabel(r'$\\Theta$ (mV)')\n",
    "\n",
    "print(r'T_{{base}} (mK) = {0:.1f}'.format(ALPHA1_CLSD*popt[0]/(K_B)))\n",
    "print(r'\\Theta (mV) = {0:.4f}*\\sqrt{{{1:.4f}*P(pW) + 1}}'.format(*popt))\n",
    "\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat944_theta_calc.csv\"), theta_calc, delimiter=\",\")\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat944_PtoTheta_fit.csv\"), popt, delimiter=\",\")\n",
    "i_results.to_csv(os.path.join(analysis_dir,'dat944_i_results.csv'), index=False) # save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def power_to_theta(p):\n",
    "    ''' P (pW) to \\theta (mV) '''\n",
    "    return 0.2089*np.sqrt(0.4988*p + 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fit 0-1 peak data\n",
    "\n",
    "Fit dI curves to fit for dS at the 0-1 electron transition. \n",
    "\n",
    "dataset 945 -- di vs plunger vs AC power  \n",
    "dataset 1011 -- di vs plunger vs parallel field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "        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",
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       "        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",
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       "\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",
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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",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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CR8zkwAJkAAJWBCBzNhYRI0ajZSICFQePgw+gwbBzt7egmpouKowftMAalITBaQJHzOTAAmQAAlYCIFbP/6ojniRmzzkbD/Z8KHnxPhNA6hJ3xSQJnzMTAIkQAIkYGYCasp36VtIWL4c7o8/rm71cKxY0cy1Mv7rGb9pADWpjALShI+ZSYAESIAEzEggMzoakaNGI/W331B55Aj4vPaabqd8i2Jm/KYB1PTRo4A04WNmEiABEiABMxG4+d13iB4/AXblyiFw0SKUa9TQTDUxz2sZv2kANSmPAtKEj5lJgARIgARMTCA3IwNx4Utw7aOPUL5dO/jPmQ1Hb28T18L8r2P8pgHUpEIKSBM+ZiYBEiABEjAhgYwrkYgcFYK0EyfhO2oUKvZ7BXZ2diasgeW8ivGbBlCTGikgTfiYmQRIgARIwEQEbu7ejaiJk+BQvjwCwxfDrUEDE73ZMl/D+E0DqEmZFJAmfMxMAiRAAiRgZAI5MuW7cCGuf7Ia5Z98AgGzZ8PB09PIb7X84hm/bcgApqamIjs7u5gq3dzc4HCPdxtSQJb/IWcNSYAESMBWCWRcvozIkcFIO3MGVcaMgfdLfW12yreoBhi/dWIAU1JSMHnyZHz22We4evUqAgMD0b17d0yZMgWet/+l89BDD+HUqVPFvgd27dqFJ598Uv1eBDF69Ghs3rwZycnJaNasGebPn4/GjRuX+P1BAdnq1yrbTQIkQAKWTeDG9h2InjwZDt7eCFy8GG7161l2hU1cO8ZvnRjAl19+GWvXrsWoUaPw6KOP4vjx45g3bx46deqETZs2IScnB+XKlcOsWbPQvMiF1vXr1883iU899RSOHj2K6dOno0qVKli2bBkOHjyoflezZs1i8qSATPyJ5etIgARIgAT+kUBOejriwsJwfd16VOjYEf4zZ8ChQgVSK0KA8VsHBlBG/Pz8/DBx4kTMmDEjv4vl/4eFhalRvWvXrqF69er4448/8OCDD5b4QdizZ48aCdy2bRueeeYZ9UxaWhruu+8+dO7cGR9++CENIL9CSIAESIAELJZAxsWLuBIcgoxz51Blwnh49erFKd9SeosGUAcGUKZ1BwwYoKZqH3vssfyunjt3rjKFCQkJOHbsmDJ3MlXs6OioRgTlfwumESNGYMOGDYiJiSn0genbty9kmjg2NpYG0GK/9lgxEiABErBtAknbtiFmylQ4Vq6MwCXhcH3oIdsGcofW0wDqwAAW7OPMzEy1du/IkSOQaWFZu7dlyxasXLlSre1r3bo1vv32W7UZRNb3LVy4MN80yt+cnZ2xe/fuQrKRqeQJEybg+vXr8PLyKvQ3CojfLyRAAiRAAuYkkJOWhtg5c5H42Wfw6NwZfqGhcCjvbs4qWcW7Gb91ZgC/+OIL9OzZU4nPx8dHmbmgoCA1EigjgjKaJz/x8fHq/58/fx4//fSTMooPP/wwZD3gp59+Wki8sg5w8ODBuHjxopoOLpjyBHT58mV4eHjk/8nFxQXyw0QCJEACJEACxiKQfv682uWbcekSqkyeBK/nnuOUbymw09PTIT95SeJ3tWrVkJSUVCh+G6uvLLFcu9zc3FxLrNi91Emme2XDxtmzZxEeHo6oqChERESoaWBZK/ivf/0rv1gxgbIe8PHHH1cbRR544AE0atSomAFcvnw5Bg0ahLi4OFSuXLlEA1i0rtOmTVMbSZhIgARIgARIwBgEkjZvRnToDDj5+SEwPByudWob4zW6KVNicmhoaLH20ADqpov/bsiff/6pRuxk9G/27NkltrBr1644ceIE/ve//6ndw97e3tixY0ehZxcsWIDx48cjIyOj2HmBHAHUoXDYJBIgARKwYAI5qamImTkLSV99Bc+uXeE3dQrs3Tnle6cu4whgcUJWPwK4ePFitQHkt99+U0e3FEyyZq93795o1aqVmt595JFHCv1djomRzR0ySti/f39s374d0dHRhZ559dVX1d9lZLFo4hqCO33k+HcSIAESIAFDEUg/exZXgoORGRkFvylT4NWju6GKtrlyGL91sAZQDm3u1q0bVq1apTZ+5KVffvkFTZo0UWf5ySieHA79/fff5/9d1u3JtK/s/pXjYmQaWA6PlnWDTzzxhHpOhoZr1aqFoUOHljh0TAHZ3HcGG0wCJEACJicgK7WSvtqImJkz4VytqprydalVy+T10NMLGb91YADlSBfZxHH69GmMGzdOjfSdO3dO7fCVNXs///wzPvnkE7WRo0ePHnjxxRfVqJ+YQrkeTo6IkeekHNkJLHllrYBs6pDRxStXrqhp4ooVK3IEUE+ffraFBEiABKyAQE5yMmJmzEDS5q/h+dyz8Js0CfZublZQc8uuIg2gDgygSEw2e4wdO1at30tMTFQHQ3fp0kXd/JFn3MQELlmyRF0HJ7eCtG/fXu0ELnjDhxz1EhISoq6Cy8rKUhtEJI+MFJaUKCDL/oCzdiRAAiRgzQTSTp9GZHAIMmNi4B86HZ5dulhzcyyq7ozfOjGA5lIVBWQu8nwvCZAACeiXgEz5Jn72OWLnzIHz//3fX1O+Ne7Xb4PN0DLGbxpATbKjgDThY2YSIAESIIEiBLJv3ULM1Gm48c038Or1AqqMHw97V1dyMjABxm8aQE2SooA04WNmEiABEiCBAgTSTp5UU75ZV6/Cf+YMeNy+l56QDE+A8ZsGUJOqKCBN+JiZBEiABEgAgEz5Xl+/HnFz58H5gVqoGh4O5yI3TxGUYQkwftMAalIUBaQJHzOTAAmQgM0TyL55E9GTp+Dmjh3wfvFF+I4bC3tnZ5vnYmwAjN80gJo0RgFpwsfMJEACJGDTBFKP/47IkBBkJybCf9YseDzdwaZ5mLLxjN80gJr0RgFpwsfMJEACJGCTBNSU7+rViF2wEK4PPojAxYvgXK2aTbIwV6MZv2kANWmPAtKEj5lJgARIwOYIZCclIWrSJNzavQcVX3kZvqNGwY5TvibXAeM3DaAm0VFAmvAxMwmQAAnYFIHU335Tu3zlqJeAuXNQ4fa1ozYFwUIay/hNA6hJihSQJnzMTAIkQAI2QUCmfK999DHiFi+GW926asrXKTDQJtpuqY1k/KYB1KRNCkgTPmYmARIgAd0TyLp+HdETJuLW99+j4muvwnfkSNg5Oem+3ZbeQMZvGkBNGqWANOFjZhIgARLQNYGUiAhEjhqN3NRU+M+biwpt2+q6vdbUOMZvGkBNeqWANOFjZhIgARLQJYHcnBwkrFiJ+KVL4RYUhMBFC+Hk56fLtlproxi/aQA1aZcC0oSPmUmABEhAdwSyrl1D1LjxSP7xR/gMGoTKw4fBztFRd+209gYxftMAatIwBaQJHzOTAAmQgK4IpPz8819TvllZCAgLQ/nHW+mqfXpqDOM3DaAmPVNAmvAxMwmQAAnogkBudjYSPvgA8W//B+WaNEHAggVwquKri7bptRGM3zSAmrRNAWnCx8wkQAIkYPUEsq5eRdTYsUg+cBCVhgxBpTeGws7BwerbpfcGMH7TAGrSOAWkCR8zkwAJkIBVE0g+eBCRY8YAuUDggvlwb9HCqttjS5Vn/KYB1KR3CkgTPmYmARIgAaskIFO+V999D1fffRflmjdD4Pz5cKxc2SrbYquVZvymAdSkfQpIEz5mJgESIAGrI5AZF4eoMWMhGz4qvfkGKr3+Oqd8ra4XAcZvGkBNsqWANOFjZhIgARKwKgK39u9H1NhxsLO3R8DChXBv9qhV1Z+V/ZsA4zcNoKbPAwWkCR8zkwAJkIBVEJBjXeL/8x8kLPsA7o89hoD5YXD08bGKurOSJRNg/KYB1PTZoIA04WNmEiABErB4ApkxMYgcPRqpvx5F5REj4DPgNTUCyGTdBBi/aQA1KZgC0oSPmUmABEjAognc2rdP3eph5+qqrnMr17ixRdeXlSs7AcZvGsCyq6WEJykgTfiYmQRIgAQskkBuZibilizBtZUfonybNvCfNxeO3t4WWVdW6t4IMH7TAN6bcm7nooA04WNmEiABErA4AplRUYgMGYXU33+Hb3AwKvbvxylfi+sl7RVi/KYB1KQiCkgTPmYmARIgAYsicHPvXkRNmAh793Koungx3IKCLKp+rIzhCDB+0wBqUhMFpAkfM5MACZCARRDIzchA3KLFuLZqFcq3b4+AObPh4OVlEXVjJYxDgPGbBlCTsiggTfiYmQRIgATMTiDjyhU15Zv2xx+oMmY0vF96CXZ2dmavFytgXAKM3zSAmhRGAWnCx8wkQAIkYFYCN3buRPSkyXDw9ERg+GK41a9v1vrw5aYjwPitEwOYkpKCyZMn47PPPsPVq1cRGBiI7t27Y8qUKfD09FSKOnXqFIKDg7F//344OzvjmWeewaJFi1C5wP2NIojRo0dj8+bNSE5ORrNmzTB//nw0LmXrPwVkug8r30QCJEAChiKQI1O+YfNxfe1aVOjQAf6zZsLBw8NQxbMcKyDA+K0TA/jyyy9j7dq1GDVqFB599FEcP34c8+bNQ6dOnbBp0yZlCh955BH4+fkpg5eRkYHZs2fD3d0dhw8fVoZQ0lNPPYWjR49i+vTpqFKlCpYtW4aDBw+q39WsWbOYpCkgK/iUs4okQAIkUIBAxqVLiAwOQfrZs/AdPw7effpwytcGFcL4rQMDKOZOjN3EiRMxY8aMfBnL/w8LC1MXPosZDA8Px4ULF/JH/H799Vc0atQIq1atghjIPXv24Mknn8S2bdvU6KCktLQ03HfffejcuTM+/PBDGkAb/JJgk0mABPRD4Ma33yJ68hQ4+Pj8NeVbt65+GseW3BUBGkAdGECZ2h0wYICaqn3sscfyBTB37lxlChMSEtCuXTvUqVNHTREXTFWrVkXLli3x6aefYsSIEdiwYQNiYmIK/Wuwb9++2LVrF2JjY2kA7+rjxYdJgARIwDII5KSnI3buXCRu+BQez3SC34wZcChf3jIqx1qYhQANoA4MYEHlZGZmqrV7R44cUaN6snZv48aNaopXRgdlnWDB1LFjR2X4ZIq3devW6rndu3cXekZGDydMmIDr16/Dq8ixABSQWT63fCkJkAAJlJlA+oULaso34/x5VJk0CV7P9+SUb5np6fdBxm+dGcAvvvgCPXv2VIr18fFRZi4gIECt53v33XcxZMiQQmru3bu3WuMnU8MPP/ww6tevr0YDCyZZBzh48GBcvHhRTQcXTHkCunz5MjwKLCB2cXGB/DCRAAmQAAmYj0DSlq2ImTYNjr6+CFy6BK516pivMnyzWQmkp6dDfvKSxO9q1aohKSmpUPw2ayVN/HK73NzcXBO/02ivk+leGc07e/asWvMXFRWFrVu3om3btiUawBdffFE9f+LECTzwwANqTWBRA7h8+XIMGjQIcXFxhXYMSyPyDGDRBk2bNk1tJGEiARIgARIwPYGc1FTEzpmDxM+/gEeXLvCfPg327u6mrwjfaDEEJCaHhoYWqw8NoMV0keEq8ueff6oRu5EjR2LJkiWYM2eOmsotmGRzx61bt7Bv3z61e9jb2xs7duwo9MyCBQswfvx4tXPYwcGh0N84Ami4/mJJJEACJGAIAunnziFyZDAyLl+G35TJ8OzRg1O+hgBr5WVwBLB4B1r9CODixYvVBpDffvtNTfUWTLJmT6Z5t2/frs70k00eBVONGjXw73//WxnE/v37q+eio6MLPfPqq68iIiJCjRQWTVxDYOXfCKw+CZCArggkbtyEmBkz4BQQgKpLwuHywAO6ah8bYzgCjN86WAMohzZ369Yt/ziXPHn88ssvaNKkiTrL7+TJk/joo4/UOj4Z5ZMkB0K3atUKe/fuVbuE5bxAOTxa1g0+8cQT6hkZGq5VqxaGDh1a4tAxBWS4DyNLIgESIIF7JZCTkoKYGTORtGkTPLt3VyN/9uXK3WtxzGcDBBi/dWAAc3Jy1G7f06dPY9y4cWojx7lz57Bw4UK1Zu/nn39WO3jlIGgZ8ZPDoq9du6YMXYMGDfKnfKUc2QkseWWtgGzqkNHFK1euqDWCFStW5AigDXwpsL+CElUAACAASURBVIkkQALWRSDtzBm1yzczKgp+06bCq1s362oAa2sWAjSAOjCAohzZ7DF27Fhl5hITE9XB0F26dMGsWbPyjdvvv/+u1gMeOHBA3QDy7LPPKpMo/52XxCiGhISoq+CysrLw+OOPq+lh2SBSUqKAzPK55UtJgARIALJ/MenLLxEzcxacq1dXu3xdatQgGRIoEwHGb50YwDL1thEeooCMAJVFkgAJkMAdCGTfSkZMaChubNkCr549UWXSRNi7upIbCZSZAOM3DWCZxcIRQE2omJkESIAEDEIg7dQptcs3Ky4OfqGh8OzyL4OUy0JsiwANIA2gJsVTQJrwMTMJkAAJlJmATPkmfvopYufMhXONGuouX5f77y9zfj5IAgUJMH7TAGr6RFBAmvAxMwmQAAmUiUD2rVuInjIFN7/dDq/evVBl/HjY87alMrHjQyUTYPymAdT02aCANOFjZhIgARK4I4HUEyfULt/shAT4z5oJj06d7piHD5DAnQgwftMA3kkj//h3CkgTPmYmARIggVIJyJTv9bXrEBcWBpfatdWUr+z2ZSIBQxBg/KYB1KQjCkgTPmYmARIggRIJZN+4gehJk3Fz1y549+0L37FjYO/sTFokYDACjN80gJrERAFpwsfMJEACJFCMQOqxY39N+d64Af/Zs+DRoQMpkYDBCTB+0wBqEhUFpAkfM5MACZBAPgGZ8r22ahXiFi2G60MPIXDxIjhXrUpCJGAUAozfNICahEUBacLHzCRAAiSgCGQnJiJq4iTc2rsXFfv1g29IMOw45Ut1GJEA4zcNoCZ5UUCa8DEzCZAACSDl118ROWoUcpJTEDB3Liq0b0cqJGB0AozfNICaREYBacLHzCRAAjZMIDcnB9c++ghx4UvgVq+emvJ1CgiwYSJsuikJMH7TAGrSGwWkCR8zkwAJ2CiBrOvXETV+PJL3/QCfAa+h8ogRsHNyslEabLY5CDB+0wBq0h0FpAkfM5MACdgggZQjRxA5ajRy09MREDYP5du0sUEKbLK5CTB+0wBq0iAFpAkfM5MACdgQAZnyTfhgOeLffhtuDYMQuHAhnPz8bIgAm2pJBBi/aQA16ZEC0oSPmUmABGyEQFZCAqLGjkPyf/8Ln9cHofKbb8LO0dFGWs9mWiIBxm8aQE26pIA04WNmEiABGyCQfOgwokaPRm52NgIWzEf5li1toNVsoqUTYPymAdSkUQpIEz5mJgES0DEBMXxX338fV995F+WaNlXmz8nXV8ctZtOsiQDjNw2gJr1SQJrwMTMJkIBOCWTFxyNyzFikHDqESkOHotLQIbBzcNBpa9ksayTA+E0DqEm3FJAmfMxMAiSgQwKyzk/MH+ztELhgAdybN9dhK9kkayfA+E0DqEnDFJAmfMxMAiSgIwK5WVmIf+cdJLy/DO4tmiNg/nw4VqqkoxayKXoiwPhNA6hJzxSQJnzMTAIkoBMCmbGxiBo1GikREag8fBh8Bg2Cnb29TlrHZuiRAOM3DaAmXVNAmvAxMwmQgA4I3PrxR3XEi9zkEbhoodrwwUQClk6A8ZsGUJNGKSBN+JiZBEjAignkZmYi/q23kbB8Odwff1zd6uFYsaIVt4hVtyUCjN80gJr0TgFpwsfMJEACVkogMzoakSGjkHrsGCqPHAGf117jlK+V9qWtVpvxmwZQk/YpIE34mJkESMAKCdz87jtEj58AOzc3BC5ehHKNGllhK1hlWyfA+E0DqOkzQAFpwsfMJEACVkQgNyMDcYvDce3jj1G+bVv4z50DR29vK2oBq0oCfxNg/KYB1PR5oIA04WNmEiABKyGQcSUSkaNCkHbiJHxHjULFfq/Azs7OSmrPapJAcQKM3zSAmj4XFJAmfMxMAiRgBQRu7t6NqImT4FC+vJrydQsKsoJas4ok8M8EGL9tyACmpKQgJyenmCLc3d3v+V+yFBC/YkiABPRKIEemfBcsxPXVq1H+yScQMHs2HDw99dpctsvGCDB+68QAZmdnY9GiRVi5ciUuXrwIT09PdOrUCQsXLkTlypWRm5sLMXqpqanFJH727FnUqlVL/T4qKgrBwcHYtWuXMott2rRBeHg4atSoUeJHgwKysW8MNpcEbIRAxuXLiBwZjLQzZ1BlzBh4v9T3nv+hbCPI2EwrI8D4rRMDOGHCBISFhWH48OFo27YtTp48iblz56J+/frYv38/oqOjERgYiDVr1uC+++4rJNMmTZrA1dUVGRkZaNiwoTKJkydPhpubmzKVMTExOHbsGCqWcL4VBWRln3hWlwRI4I4EbmzfgejJk+Hg7Y3AxYvhVr/eHfPwARKwNgKM3zowgGLYfH198cILL2DFihX5GpT/HjhwILZv345y5cqp0bzk5GRl7EpKMnoozx8/fhx169ZVj8TGxqJatWrKEE6dOrVYNgrI2j7yrC8JkEBpBHLS0xEXFobr69ajwtNPw3/WTDhUqEBgJKBLAozfOjCAMjrXoEEDfP7553juuefyhXrixAnUq1dPTQP7+PhgypQpuHz5MmS6WHav2Re5p7Jr165qpPDw4cOFxN6qVStkZmbi0KFDNIC6/Bpgo0iABDIuXsSV4BBknDuHKhPGw6tXL075Uha6JkADqAMDmJiYiCNHjqBRo0aFpmllRG/AgAH49NNP1ajeunXrUL16dfzwww/K/LVv3x5LlizBQw89pEQuf+vQoUOhUUT5/eDBg7FhwwbIe4omCkjX3w9sHAnYBIGkbdsQM2UqHCtXRuCScLje/k60icazkTZLgPFbBwawJPXu3r1bjQZ6e3vj999/V1O769evx8iRI/HMM8/gwoULmDVrFmRncEREhDJ/Mk08bNgwtZawYMpbX5g3cljwb3kCkpFFDw+P/D+5uLhAfphIgARIwFIJ5KSlIXbOXCR+9hk8OneGX2goHMq7W2p1WS8S0EQgPT0d8pOXJH7LEq+kpKRC8VvTS6wss12ubJHVSYqPj4cYtg8//FBt9ti8eTMeeeQRiCF0dHRUG0Ty0qlTp9Tfhg4dqkYCnZycEBISUswATpo0Sf1d1g+WNgJY9PfTpk3D9OnTdUKVzSABEtAbgfTz59Uu34xLl1Bl0kR49ezJKV+9dTLbU4iAxOTQ0NBiVGgAdSAUmaYVM3fz5k28+eabmDlzJsqXL/+PLZO1g3JMjBhE2UjSvXt3LFu2rFCeN954A1u3bsWlS5dKNYAcAdSBgNgEErARAkmbNyM6dAac/PwQGB4O1zq1baTlbKYtE+AIYPHeN+oIoJzJt3HjRrXuTkbc4uLiIMOuXl5eyng98MADat2d/Mh/32sS0yZr9Zo1a6ZG/x5++OH8osQQykhgixYtULNmzUKvkPV/8vPVV1+hXbt26giYgwcPFnpG1grK9O6mTZtKNYC2/C+Ie+0z5iMBEjAtgZyUFMTMmo2kr76CZ9eu8Js6BfbunPI1bS/wbZZCgGsAjbQGUHbMytEpe/fuVYcwOzs7K8MnZ+mJmbp165baVCHHrKSlpampBzFgMnX6+OOP35U+xOD5+/ujcePG6gBneVfBJDt4xXDKmsBVq1bl/0l2+4phfPfddzFkyBA1zTt69Gh1hmDt2n/9i1jWCtapU0eNCvbv358G8K56hg+TAAlYCoH0s2dxJTgYmVci4Td1Krx6dLeUqrEeJGAWAjSABjaAcmjymDFj1I5bMWTPP/88WrZsqf67qDGTHpeNFXKMixzWLJs0Dhw4gH//+99YvHhxqbdvFFXKl19+qczdvHnz1HEwRZPc8iE7guXvshkkbxPInDlz1LTvL7/8og6CljV+QUFByoyKeZWbQGbPnq3+JhtFZI1g0UQBmeVzy5eSAAmUkYD8Azzpq42ImTkTztWqqilfl9s3H5WxCD5GArokwPhtYAMoI20dO3ZUI2lyw8bdJjFacm7fli1b1Fq+siR5XkxnaUlGFeUMwLfffhsffPABzp8/r3YHixEUE1ilSpX8rLKWT24T2bNnDxwcHFRbli5dqoxiSYkCKksP8RkSIAFzEMhJTkbMjBlI2vw1PJ/tAb/Jk2FfykH45qgf30kC5iTA+G1gA3j69Gk1Zao1ydTr/fffr7UYo+engIyOmC8gARK4BwJpp0+rXb6ZsbHwnz4Nnv/+9z2UwiwkoF8CjN8GNoAzZsxAr1698tfQ6Vc6f7WMAtJ7D7N9JGBdBGTKN/GzzxE7Zw6c/+///pryrWH5/5i2LsqsrR4IMH4b2ADKDRuyhq5+/frKCMoawBo1auhBKyW2gQLSbdeyYSRgdQSyb91CzLTpuLFtG7xeeEFd6Wbv6mp17WCFScAUBBi/DWwA5eo1OTNPjnsRIyhJNoC88MIL6Nmzp7pxQ0+JAtJTb7ItJGC9BNJOnlS7fLOvJsBvRig8O3e23saw5iRgAgKM3wY2gNJnMgUhZ+nJuXly/t6ZM2dUV4ohbN68uTKDsms3ICDABF1s3FdQQMbly9JJgAT+mYB8315fvx5xc+fB+YFaqBoeDuf77iM2EiCBOxBg/DaCASzKXDaG5JlBOXtPjleRqeJWrVopM/jss8+WusvW0hVMAVl6D7F+JKBfAtk3byJ68hTc3LED3i++CN+xY2DPO8j12+FsmUEJMH6bwAAW7DGZGv7666/VyKActSJXs4gZbNOmjbqOzdoSBWRtPcb6koA+CKQe/x2RMuWblAT/WbPg8XQHfTSMrSABExFg/DaxASzYr3L487Bhw3D06FE1PSyHQltbooCsrcdYXxKwbgJqynf1asQuWAjXBx9E4OJFcK5WTTUqOycXhy9cQ9zNNPhWcMWj91eEg/1fa7G1JmOVbaxyjcmDdS6sJmPxMFa5ebVn/DahAZQvrp9++klNB8uP3BMsv5Mr4mQaWK5ks7ZEAVlbj7G+JGC9BGS0L2rSJNzavQcVX3kZvqNGwe721Zfbf49G6JaTiE5Ky2+gv6crpnV5GB3r+WtqtLHKNla50lhjlW2sclnnwhI1JmcawL9Z2+WKCzNSysjIwM6dO5Xhk9s9rl69qkyf3Anco0cPdUxM+/bt1TSwNSYaQGvsNdaZBKyPQOpvvyEyOARy1EvA3Dmo8MQT+Y2QYDlkTQSKfpHnjf2917fRPZtAY5VtrHLzjJQxeLDOxU2atXEu2ALGbyOMAApUOQpm48aN2LFjh7pjV0yfXBPXrVs3ZfqefPJJODo6Wt+3cJEaU0BW34VsAAlYNAH57rz20ceIW7wYbnXrqilfp8DA/DrLNFmrsL2FRv4KNkhMoJ+nK34a1/6up4ONVbaxypV2G6tsY5XLOhf++BmTc9EPOuO3gQ1ghw4dsG/fPmRlZSnTV6FCBXTt2lWZvqeffhpOTk4W/WV7t5WjgO6WGJ8nARIoK4Gs69cRPWEibn3/PSq+9ip8R46EXZHv0APnEtB7+cE7Frl+YHO0qOlzx+cKPmCsso1VrtTdWGUbq1zWubAkjcmZBrD4x9+gU8Aylevu7o4uXboo09epUye46PhYAhrAu4onfJgESKCMBFIiIhAZMgq5aWnwnzcXFdq2LTHn5qORGLHh6B1LXdorCF2D/h45vGMGAMYq21jlSpuMVbaxymWdCyvRmJxpAI1sAL/44gt07twZbm5uZfl+sfpnaACtvgvZABKwKAK5OTlIWLES8UuXwi0oCIGLFsLJz6/UOhpzxMRYZRurXI6mmW40zVh9aKxyS/oAMX4beAr4Xr5JL126hOPHj+Nf//rXvWQ3ax4KyKz4+XISsEoCpR1vkXXtGqLGjUfyjz/CZ9AgVB4+DHZ3WCudt2YqJimt2CYQgWOINYCGLpt1LixbY/EwVrlSe2OVbaxyaQBL/qo06BRwSa/4888/S/2SlltB3nrrLXUETFra38cXWMu3Og2gtfQU60kClkGgtOMt5tTMRNX/zEVuVhYCwsJQ/vFWZa5w3u5UyVBwJ7AhdwEbumzWuXD3GouHscqV2hurbGOVW/QDxfhtghFAWRcoBz3/U6pfv746ENraEgVkbT3G+pKA+QiUdIyIfW4OXjizFy/+sQOZdRug3rtL4VTF964racxz04xVtrHKzTMnxjgXkXUublytjXNeCxi/TWAA+/XrV6IBTEhIUAdDy8jfzz//jLp16971l565M1BA5u4Bvp8ErINAScdbeKXdxJhf1iEo/n9YX+dJ7H20C36c8ORdH9eSR8CYNycYq2xjlStMjFW2scplnQt/lo3JWd7E+G0CA/hPX883b95E69at0bhxY6xYscI6vskL1JICsrouY4VJwCwEii5ubxB/FmOPrFN1WdCkD45WfkD9970c12KWBvGlJGDlBBi/zWwART9Lly7F9OnTcf36dauTEwVkdV3GCpOAWQjkHW8hU769T+1Cn9O78VvlWljQuDeuu3rk1+lejmsxS4P4UhKwcgKM3xZgAN977z1MnDiRBtDKP0ysPgmQQOkEZARw6Ns7Me7IWtS7eh5rH+yAT+s8gRy7wtdgcgSQKiIB0xCgATSzAZTbQtq1a4cHH3wQ77//vml63YBvoYAMCJNFkYCOCdz48Sf8MSwYmbBHWJMXcbxSzUKt1XJci46xsWkkYDQCjN8mMIAzZswosQNlE4jcFXzu3DkMGTIE5cuXz39Odg3Pnj3baB1vqIIpIEORZDkkoE8CcqxL/Nv/QcIHHyC1QRO86v8MklwqGPy4Fn3SY6tIwHgEGL9NYADlGJi7TWIAs7Oz7zabyZ+ngEyOnC8kAashkBkTg8jRo5H661FUHjECPgNew46TsTDGsRlWA4UVJQELIcD4bQIDuG/fvnvq7jZt2txTPlNmooBMSZvvIgHrIXBr3z51q4edq6u6zq1c48b5lTf28RbWQ4k1JQHzEWD8NoEBNF/3Gv/NFJDxGfMNJGBNBHIzMxG3ZAmurfwQ5du0gf+8uXD09ramJrCuJGATBBi/aQA1CZ0C0oSPmUlAVwQyo6IQGTIKqb//Dt/gYFTs3w9297AERldQ2BgSsFACjN8GNoBynt/IkSPh5eV1z10um0MWLVqEOXPm3HMZpspIAZmKNN9DApZN4ObevYiaMBH27uVQdfFiuAUFWXaFWTsSsHECjN8GNoAdOnTAgQMH0L9/fwwdOlQd71LWdOLECbzzzjv45JNP0KlTJ3z++edlzWq25yggs6Hni0nAIgjkZmQgbtFiXFu1CuWfeAIBs2fBQcM/gC2iUawECdgAAcZvAxtA0czXX3+N8ePH4/Tp03jkkUfQsmVLPProo6hataoaGZTjXuQKuGvXruHy5cvKMMqdwGfOnFGGUW4GefLJJ61CfhSQVXQTK0kCRiGQceWKmvJN++MPVBkzGt4vvVTivedGeTkLJQES0ESA8dsIBlB6JCcnB+vWrVOHOx86dEgd6SJHuxRNchC0o6Ojug94wIAB6NmzJxwcHO66U6V8mTZeuXIlLl68CE9PTzWKuHDhQlSuXFmVd/DgQYwZMwYRERHw8PBQ75o7dy7c3d3z3xcVFYXg4GDs2rVLtUF2IoeHh6NGjRol1okCuuuuYgYS0AWBGzt3InrSZDh4eiIwfDHc6tfXRbvYCBKwFQKM30YygAUFlJSUhO+++w5nz57F1atX1ZVv5cqVg7+/P+rVq6dGCLWsGZR3TZgwAWFhYRg+fDjatm2LkydPKnNXv3597N+/X41GNm3aVI1EyqHT8fHx6v7hxo0b45tvvlHVzcjIQMOGDZGamorJkyfDzc1NmcqYmBgcO3YMFStWLPa5oIBs5auC7bQ1AqUd1ZIjU75h83F97VpU6NAB/rNmwsHj77t8bY0T20sC1kqA8dsEBtDY4hDD5uvrixdeeAErVqzIf53898CBA7F9+3asWbMGP/zwgzKCrq6u6pmNGzeiR48ekHMKZQRSRg/l+ePHj6Nu3brqmdjYWFSrVk0ZwqlTp9IAGrszWT4JWACB7b9Hl3hY88ymnqj53jyknzkD3/Hj4N2nD6d8LaC/WAUSuBcCNIA6MIAyOtegQQO1aeS5557L14FsKpERRpkGlmvlZIp5/vz5+X9PSUmBt7e32rUso4ddu3ZFdHQ0Dh8+XEhLrVq1QmZmpprKLpoooHv52DEPCVguATF/Q9ZEFLqqTWrbOvIoRvz6OZwq+eCBd96C2+1/JFpuS1gzEiCBfyLA+K0DA5iYmIgjR46gUaNGhaZpZURPTJ+Yu3HjxmH16tXo27dvIT3IphP52bRpE6pXrw7ZxVxwFFEeHjx4MDZs2AB5Dw0gv1BIQL8EZNq3VdheRCel5TfSKTsTrx//Gp0vHsC+wCB82vpF7J7SGQ72xdc065cMW0YC+iNAA6gDA1iSLHfv3q1GA2WE7+OPP1brAmWtn2wMKZhatGihpoRljaKsSxw2bJgyjAVT3vrCkjay5AlIdjPLxpK85OLiAvlhIgESsB4CB84loPfyg/kVDrwVjwmHV6ParTi8/0g3fHtfM8DODusHNkeLmj7W0zDWlARIAOnp6eonL0n8liVesk+hYPy2JVR2ubIVVydJNneIYfvwww9x3333YfPmzerIGZnGLckA5m1A2bZtG5ycnBASElLMAE6aNAlLlixBcnJyqSOARf8wbdo0tcmEiQRIwHoIbD4aiREbjqoKt70cgWG/fYlrrh6Y3fQlXPQMyG/I0l5B6BoUaD0NY01JgARUTA4NDS1GggZQB+KQaVo5fFoM35tvvomZM2eqMwdlR7Bs6pBjaXr37l2opfL7Jk2aYNWqVWojSffu3bFs2bJCz7zxxhvYunUrLl26VKoB5AigDgTEJtg8ARkB7PfeD3j9+GZ0unQIe6o2wn+CnkWaY+HRfI4A2rxUCMAKCXAEsHinWcQI4IwZM0rcZSubNsaOHXtHqYlpk7V6zZo1U6N/Dz/8cH4e6XQ5ZmbEiBGYN29e/u/l2Bc5L1COi5GNIO3atVNHwMh5gQVT+/bt1fCwrBMsmriG4I5dwwdIwGoIpJz9H/a/NAiVbl7Fe490x87qTdWUb16S//LzdMVP49pzDaDV9CorSgIlE2D8NvMaQBmVk/TSSy+po1oKzkbLeYGjR49Wpuyfkoz4yZmCcqafHODs7Oxc7PFu3bqp413++OOP/L+vXbtWvVfOJ6xZs6aa5pX3yYhh7dq1VRkXLlxAnTp11KigXG9HA8ivEhLQJ4HETZsQEzoD6T6+GF67J/708Cu0EzjPBr7XtxE61vPXJwS2igRsiAANoJkN4P3336/kJtOrsmavYJIbQmQjh4zQ/VP68ssv1XMyuifHwRRNtWrVghz5IodAy2YQOetPjJ2sBejTp0/+lK+s8QsKClLnesm5f3ITiBwfI5tE5PYQWSNIA2hD3w5sqk0QyElJQczMWUjauBGePXrAb/Ik7DyfVOI5gNO6PEzzZxOqYCNtgQANoJkNYJ7IHnroITU6dy9JzvmTK95KS3kbMuQgaDkO5ujRo/Dx8cErr7yiTKAYzbwka/nkNpE9e/aoK+k6duyo7iaW9YElJQroXnqMeUjAMgiknTmDyOAQZEZFwX/6NHh27ZpfsdJuArGMmrMWJEACWgkwfluIASytI+WWDrmP11ITBWSpPcN6kUDpBGSpSdKXXyJm1mw4V6uGwKVL4FLKfd/kSAIkoE8CjN8WYgBlQ8Ynn3yCuLi4fKXJ2j+5i1emby01UUCW2jOsFwmUTCD7VjJiQkNxY8sWePXsiSqTJsL+9vWQZEYCJGA7BBi/LcQADhkyRJ3ZJ4cxS3J3d1f39r711lsYNGiQxSqSArLYrmHFSKAYgbRTpxA5MhhZcXHwCw2FZ5d/kRIJkICNEmD8thADGBAQoNbdyZ27splDdgfL/2ZlZakNGZaaKCBL7RnWiwT+JiBTvomffobYOXPgXKMGAsMXw+X2BjRyIgESsE0CjN8WYgBl5E9O405LS1Nr/mTXrdy9+8gjj+DPP/+0WHVSQBbbNawYCSgC2bduIWbqVNz45lt49e6FKuPHw57XNFIdJGDzBBi/LcQAyhl+cg3biy++CDka5tdff4V0jtzUIef8WWqigCy1Z1gvEgBST5xQu3yzr12D/8wZ8ChyFzgZkQAJ2C4Bxm8jGEAZuZObNyRdvXpVnZ8nN278U9q+fTt69uyJvXv3Yv369ZCz/WTaRu7wzTss2hJlSgFZYq+wTrZCoLSjWuS74/radYgLC4NL7dpqyte5enVbwcJ2kgAJlIEA47cBDaCs15MNG8eOHcORI0cU/s8++wwvv/yyOsw5ODj4H7skOztbmT57e3usXr0asjNYzuor6WaPMvStSR6hgEyCmS8hgWIEtv8eXeJhzdPbV0fdtf/BzZ074d23L3zHjoF9CbcDESkJkIBtE2D8NqABlAOT33nnHTVi16RJE6UsuU3jm2++Udeovf322+jVq5euFEcB6ao72RgrISDmb8iaiEJXtUnVa1//E+N/XgNfuwxUnzcHHk89ZSUtYjVJgARMTYDx24AGUK5Rk2NbWrduXawfv/jiC8iNHQcPHiyxj2Xkb/78+Wr6NyYmBnIAtBhJucVDRgQtNVFAltozrJdeCci0b6uwvYhOSvu7ibm56HbuR7x6YhvOewVgRfsB2DyzJxzs827w1SsNtosESOBeCTB+G9AAenh4qIOc5e7cokl2+MpRL3Lfbklp1qxZatpXrmqTu3qlnKeeegpPP/30He8CvtfON0Q+CsgQFFkGCZSdwIFzCei9/O9/SJbPSEFwxKd4LOYEvqzZGh/XfQZZ9o5YP7A5WtT0KXvBfJIESMCmCDB+G9AAent747fffkP1EhZbX7lyBQ0bNkR8fHyJApM8W7duVce+yB28sh5Q7gYWEyh5LTVRQJbaM6yXXglsPhqJERuOquY9eO2imvItl5WORY164ZB/3fxmL+0VhK5BgXrFwHaRAAloJMD4bUADKKN1jz/+eIkHN8uVbrIWUA57Lin5+Pio8/7kBpA8AyhXwFWpUoXHwGgUObOTgJ4IyAhgnw/+KnLnBgAAIABJREFUix7/24d+J7/Fae/qCGvyIuLLeRdqJkcA9dTrbAsJGJ4ADaABDeB3332HZ555BqNGjVK7d2VULzY2FmvWrIFM8W7ZsgVPPPFEib3YvXt3NUI4derUfAO4cuVKrF27Vh0NY6mJArLUnmG99EogI+Eavnp+EBpEnsDnD7TFqoc6IdveIb+5surPz9MVP41rzzWAehUB20UCBiDA+G1AAyj9IYZt2LBh6laPvFS+fHm1AUTW9pWWZPRPpnvlKJkLFy6gQYMGyjzu2LED9evXN0BXG6cICsg4XFkqCZREIOWXXxAZMgrpqWkIrfscjlR5qNBO4LwtH+/1bYSO9fwJkQRIgARKJcD4bWADKKRlo8f+/fvVIdC+vr547LHHIFe93SnJuX/btm3DuXPnEBgYqEYT73SA9J3KNPbfKSBjE2b5JADk5uQgYfkKxL/1FtwaBiFw0SLsic8p8RzAaV0epvmjaEiABO5IgPHbCAawKHU5C1Cmf1esWKH+t2CSa9/s7P75qIbz58/fsSPN9QAFZC7yfK+tEMhKSEDU2HFI/u9/4fP6IFR+803YOTqq5pd2E4itsGE7SYAE7p0A47cRDaAYNzF9q1atUqOBsknk66+/LtRb06dPzzeAchbgjBkz1Nl/BVPR/3/v3W34nBSQ4ZmyRBLII5B86DCiRo9WI4AB88NQvmVLwiEBEiABgxBg/DawAczMzFT3+C5fvhzff/+96iRZ/9evXz/IMTF3Snk7gO/0nKX8nQKylJ5gPfREIDc7G1fffx9X33kX5Zo2RcCC+XDy9dVTE9kWEiABMxNg/DagARw5cqTaBCJTvn379sVrr72mdv3K2YByCHRZEg1gWSjxGRLQL4Gs+HhEjhmLlEOHUGnoUFQaOgR2Dn/v8tVvy9kyEiABUxKgATSgAZQr2x599FE1AiibOCRVrlyZBtCUiua7SMCKCcg6PzF/sLdD4IIFcG/e3Ipbw6qTAAlYMgEaQAMaQLnv9/3338eBAwfQs2dPDBkyBF26dMHRo0c5AmjJnwLWjQTMTCA3Kwvx77yDhPeXwb1FC7Xez7FSJTPXiq8nARLQMwEaQAMawDyhnDlzBsuWLVObP65duwbZ6DFgwIASTaBs+iiYQkND1fOyISQvyeHQlpooIEvtGdbLWghkxsYiatRopEREoPLwYfAZNAh29vbWUn3WkwRIwEoJMH4bwQDmaSE9PR0bNmxQZvDnn39G27ZtsWvXrkJSkWNg/inJETE8BsZKP12sNgncJlDacS23fvxRHfFi5+SEwEUL1YYPJhIgARIwBQEaQCMawIIdKNPAYgTfe+89U/Sryd5BAZkMNV9kpQS2/x5d7MDmqhWcsPDmAXhu2gD3xx9HQNg8OFasaKUtZLVJgASskQDjt4ENoEzpvvDCC6hTp4416uGu60wB3TUyZrAhAmL+hqyJKHRdW6WUREw4sgZ1rv+JG31eQ4tJIznla0OaYFNJwFIIMH4b2ADKTmCZtpX7e3v16oXnn38eNWrUsJT+Nng9KCCDI2WBOiEg076twvYiOiktv0WPxpzEqF82IN3RCWFN+uJajYfw07j2cLD/59uAdIKEzSABErAgAozfBjaAstlj69atiIuLy7/ho3HjxmpUUHYGV69e3YK6X3tVKCDtDFmCPgkcOJeA3ssPqsY55mSh38lv8ez/9uFQlYewqHEv3HR2V39bP7A5WtT00ScEtooESMBiCTB+G9gASk/LDt6DBw9i06ZN2Lx5M2RXsCQZGWzevLkyg88991yZj4axWPUAoIAsuXdYN3MS2Hw0EiM2HIVv8jU15Vsr8Qo+evgZfFWrjXwZ5Fdtaa8gdA3669xQJhIgARIwFQHGbyMYwKKdd/r06XwzePjwYXVTiEwVt2rVSpnBZ599Fr5Wes0TBWSqjyrfY20EZATwrdAVCP71U6Q4umJu0744XfG+Ys3gCKC19SzrSwL6IMD4bQIDWFAqMjX89ddfq5HBPXv2QI6KETPYpk0b7N6926iqSklJUeazaHJ3d8+frr7bClBAd0uMz9sCgZyMDMTOX4DENWvwX/96CG/4PG45lyvUdBkD9PN05RpAWxAE20gCFkiA8dvEBrCgBvbv349hw4apm0Jkejg7O9sgEpHjZmbOnIkrV67klyfT0mL0UlNTi73j7NmzqFWrlvp9VFQUgoOD1XmFYhbFmIaHh5e6kYUCMkiXsRAdEcj4809EBocg7cwZXOv7Ovpeu09N+f59tDuQNwH8Xt9G6FjPX0etZ1NIgASshQDjtwkNoJiwn376SU0Hy8/FixfVekG5L1imgd99913NuhHT1759e8hoX0EDKMZO7ides2YN7ruv8DRUkyZN4OrqioyMDDRs2FCZxMmTJ8PNzQ2LFi1CTEwMjh07hoolnFNGAWnuMhagIwI3tm9H9OQpcPD2RuDixXCrXw8lnQPo7+mKaV0epvnTUd+zKSRgbQQYv41sAMVU7dy5Uxm+LVu24OrVq8r0iZnq0aOHOiZGDJtMA2tJ3333HUaMGIGTJ0+qkUQxewUN4I8//qhG85KTk5WxKymtXLkSAwcOxPHjx1G3bl31SGxsLKpVq6YMYUlX0lFAWnqNefVCICc9HXFhYbi+bj0qdOwI/5kz4FChQn7zSrsJRC/tZztIgASsjwDjtxEMoECVo2A2btyIHTt2KNMlps/LywvdunVTpu/JJ5+Eo6OjwRRz4sQJZTAlff7558q4FTSAH3/8MaZMmYLLly8rgyhTzkVNZ9euXREdHQ3ZqFIwyWaVzMxMHDp0qFh9KSCDdSELslICGRcv4kpwCDLOnUOVCePh1avXPa+ptVIErDYJkIAVEmD8NrAB7NChA/bt24esrCxl+ipUqAAxVmL6nn76aTg5ORldJv369VMbSgoaQDF/69atU+cQ/vDDD8r8ycjjkiVL8NBDD6k6yd+k/itWrChUx8GDB6s7jRMTE2kAjd57fIE1EUjaug0xU6fCsXJlBC4Jh+vtz5I1tYF1JQESsE0CNIAGNoBirGSzRZcuXZTp69SpE1xcXEyqrpIMYJ8+fbB+/XqMHDkSzzzzDC5cuIBZs2aptYIRERHK/JUrV05tSgkLCytU3wkTJqjf5Y0cFvxjnoBkZNHDwyP/T9JmU7fbpJD5MpsmkJOWhtjZc5D4+efw6NwZfqGhcCj/18HOTCRAAiRgiQTk1BH5yUsSv2WJV1JSUqH4bYl1N1ad7HJlqM5A6YsvvkDnzp1LXWdnoNf8YzElGUAZEZQp57Zt2+bnPXXqFB555BEMHTpUjQTK6GRISEgxAzhp0iT1d5nKLpryDGDR30+bNg3Tp083RXP5DhIwKYH08+cROTIYGZcuocrkSfB67jlO+Zq0B/gyEiCBeyEgMTk0NLRYVhrAe6FpoXlKMoClVbVBgwZqF7IYRDmMunv37pBjZAqmN954Q61pvHTpUqkGkCOAFioGVsugBJI2b0Z06Aw4+fkhMDwcrnVqG7R8FkYCJEACxiLAEcDiZA06AmisjrubcosawJs3b6qDp1u0aIGaNWsWKkrW/8nPV199hXbt2qkjYOQau4JJ1grK9K7sZC6auIbgbnqGz1orgZyUFMTMmo2kr76CZ9eu8Js6BfbunPK11v5kvUmABHiVq2hA9wZQdvDKDmS5f3jVqlX5upfdvs2aNVPnDw4ZMkRN844ePVodJVO79l8jG7JWsE6dOmpUsH///jSA/NbQLYHSjmpJP3sWV4KDkRkZBb8pU+DVo7tuGbBhJEACtkOAAzg2YABFzrKRY968eeqcv7xNIHPmzFHTvr/88os6CFrW+AUFBan1THLun9wEMnv2bPU32ShS0g5mCsh2viz03NISD2v2cMH88n+i8odvw7laVTXl63L7xhw9s2DbSIAEbIMA47eNGEDZwfv222/jgw8+wPnz5+Ht7a2MoJjAKlWq5Ktd1vINHz5c3VPs4OCAjh07YunSpcoolpQoINv4otBzK8X8DVkTUeiqNtesdAw7+iXaX4nAzSeeQZOFs2BfygHqembDtpEACeiXAOO3Dg2gKeVKAZmSNt9laAIy7dsqbC+ik9Lyi/6/pChM/Hk1KqUm4e2g53Cq3mP4aVx7ONjn3eBr6FqwPBIgARIwPQHGbxpATaqjgDThY2YzEzhwLgG9l9/e9JSbi06XDuH1Y5sQWb4y5jR9CZEV/hr5Xj+wOVrU9DFzbfl6EiABEjAcAcZvGkBNaqKANOFjZjMT2Hw0EiM2HEW5zDQMO/oF2kYexbb/a44P6ndFhsPft/Ys7RWErkGBZq4tX08CJEAChiPA+E0DqElNFJAmfMxsZgIyAjh5wZeY8PNqeKffxNKgnvihalCxWnEE0MwdxdeTAAkYnADjNw2gJlFRQJrwMbMZCcgFQNfWrUfk7Lm4VKGKmvKNLl+pUI1k1Z+fpyvXAJqxn/hqEiAB4xBg/KYB1KQsCkgTPmY2E4HsmzcRPXkKbu7YgRuduuElx2bIdHAqtBM4b8vHe30boWM9fzPVlK8lARIgAeMQYPymAdSkLApIEz5mNgOB1OO/IzI4GNlJSfCfNQseT3dAiecAerpiWpeHaf7M0Ed8JQmQgPEJMH7TAGpSGQWkCR8zm5CATPleX70asQsWwvXBBxG4eBGcq1XLr0FpN4GYsIp8FQmQAAmYjADjNw2gJrFRQJrwMbOJCMhoX9SkSbi1ew8qvvIyfEeNgp2zs4nezteQAAmQgOURYPymAdSkSgpIEz5mNgGB1N9+Q2RwCLJv3ULA3Dmo8MQTJngrX0ECJEAClk2A8ZsGUJNCKSBN+JjZiARyc3Jw7eNViFu8GG5166opX6dAnuVnROQsmgRIwIoIMH7TAGqSKwWkCR8zG4lA1vXriB4/Abf27UPF116F78iRsHP6+2BnI72WxZIACZCA1RBg/KYB1CRWCkgTPmY2AoGUiAhEhoxCbloa/OfNRYW2bY3wFhZJAiRAAtZNgPGbBlCTgikgTfiY2YAEZMo3YcVKxC9dCrcGDf6a8vXzM+AbWBQJkAAJ6IcA4zcNoCY1U0Ca8DHzPRAo6biW3MTriBo3Hsk//gifQYNQefgw2Dk63kPpzEICJEACtkGA8ZsGUJPSKSBN+Jj5LgmUdGBzm9QrGP3zarggFwFhYSj/eKu7LJWPkwAJkIDtEWD8pgHUpHoKSBM+Zr4LAmL+hqyJyL+uzT43B8+f2Yu+f+zACZ/7UXHuPDzVuv5dlMhHSYAESMB2CTB+0wBqUj8FpAkfM5eRgEz7tgrbi+ikNJXDK+0mxvyyDkHx/8P6Ok+qH19vd/w0rj0c7PNu8S1j4XyMBEiABGyQAOM3DaAm2VNAmvAxcxkJHDiXgN7LD6qnG8Sfxdgj69R/L2jSB0crP5BfyvqBzdGipk8ZS+VjJEACJGC7BBi/aQA1qZ8C0oSPmctIYPPRSASvj0CfU7vQ+/RuHKtUE/Ob9MF1V49CJSztFYSuQTzsuYxY+RgJkIANE2D8pgHUJH8KSBM+Zi4jgYOHT+NiyCjUu3oeax/sgE/rPIEcO/tiuTkCWEagfIwESMDmCTB+0wBq+hBQQJrwMXMZCNz6aT+ixo5FQmoW5jbqg2OVaxXLJav+/DxduQawDDz5CAmQAAkIAcZvGkBNnwQKSBM+Zv4HArlZWYh/+z9I+OADuD/2GE69GoLXt1xQOXIL5Mvb8vFe30boWM+fTEmABEiABMpAgPGbBrAMMin9EQpIEz5mLoVAZkwMIkePRuqvR1F5+HD4DBwAO3t7lHQOoL+nK6Z1eZjmj2oiARIggbsgwPhNA3gXcin+KAWkCR8zl0Dg1r596lYPOxcXdZ1bucaNCz1V0k0gPPqFUiIBEiCBuyPA+E0DeHeKKfI0BaQJHzMXIJCbmYm4JUtwbeWHKN+mDfznzYWjtzcZkQAJkAAJGIEA4zcNoCZZUUCa8DHzbQKZUVGIDBmF1N9/h29wMCr276emfJlIgARIgASMQ4DxmwZQk7IoIE34mBnAzb17ETVhIuzdyyFw0SKUa9iQXEiABEiABIxMgPGbBlCTxCggTfhsOnNuRgbiFi3GtVWrUL59ewTMmQ0HLy+bZsLGkwAJkICpCDB+0wBq0hoFpAmfzWbOuHJFTfmm/fEHqoweBe+XX4adHe/wtVlBsOEkQAImJ8D4rUMDuGzZMsycORNXrlwpJKiDBw9izJgxiIiIgIeHB3r27Im5c+fC3d09/7moqCgEBwdj165dyMnJQZs2bRAeHo4aNWqUKE4KyOSfWat44T/t1L2xcyeiJ02Gg6cnAsMXw61+fatoEytJAiRAAnoiwPitMwMopq99+/ZISUkpZABPnTqFpk2b4tFHH8WQIUMQHx+P6dOno3Hjxvjmm2+UpjMyMtCwYUOkpqZi8uTJcHNzw6JFixATE4Njx46hYsWKxbRPAenp68AwbSn1rL6OtRC0dTWur12LCh06wH/WTDh4FL7L1zA1YCkkQAIkQAJ3IsD4rRMD+N1332HEiBE4efIksrOzERgYWMgAvvTSS/jhhx9w+vRpuLq6Kl1s3LgRPXr0wL59+9C6dWusXLkSAwcOxPHjx1G3bl31TGxsLKpVq6YM4dSpU2kA7/SJsvG/i/kbsiai0E0dgiTg1lWM/3k1aiXHwW/COHj36cMpXxvXCptPAiRgXgI0gDoxgCdOnMCWLVuUmj7//HNl3PKmgGUqt1KlShgwYADmz5+frzgZJfT29sbIkSMRFhaGrl27Ijo6GocPHy6kylatWiEzMxOHDh2iATTv59Wi3y7Tvq3C9iI6Ka1QPR+PPIqRv36ORJfy+KDdAKyb/wp4cLNFdyUrRwIkYAMEaAB1YgALarVfv37YvXt3vgE8f/48atasidWrV6Nv376FZP3ggw9CfjZt2oTq1aujQ4cOWLFiRaFnBg8ejA0bNiAxMZEG0Aa+FO61iQfOJaD38oP52Z2yM/H68a/R+eIB7AsMwltBzyHFyRXrBzZHi5o+9/oa5iMBEiABEjAAARpAGzCAMqLXrFkztdavU6dOhWTTokULNSUsU8jlypXDsGHD1GhgwTRhwgT1O5laLrpTM09Aly9fVhtL8pKLiwvkh8l2CGw+GokRG46qBgfeiseEw6tR7VYc3q/fFd/+X3Pg9i7fpb2C0DUo0HbAsKUkQAIkYAEE0tPTIT95SeK3LPFKSkoqFL8toKomq4Jdbm5ursneZoIXFR0B3L9/P2QatyQD2LJlS3h5eWHbtm1wcnJCSEhIMQM4adIkLFmyBMnJycVqn2cAi/5h2rRpapMJk+0QyBsBbHs5AsN++xLXXD0wp+lLuOAZUAgCRwBtRxNsKQmQgOUQkJgcGhparEI0gJbTR5prUtQAysYQ2dSxbt069O7du1D58vsmTZpg1apV8PX1Rffu3SHHyBRMb7zxBrZu3YpLly6VagA5Aqi526y+gMzkFKzsNQxtzv4Xe6o2wn+CnkWa49+jwHLKn5+nK34a155rAK2+t9kAEiABayPAEcDiPab7EUDpdBnlk13C8+bNyycgx754enqqswBlI0i7du3UETByXmDBJMfKyPSurBMsmriGwNq+AoxT3/Rz5xA5Mhipl/7E0rpdsat6U+QWONg574jn9/o2Qsd6/sapBEslARIgARIoMwHGbxtYAyhq6Natmzre5Y8//oCzs7MSyNq1ayHHw5w9e1ZtEpFp3tGjR6ujZGrXrq2euXDhAurUqaNGBfv3708DWOaPlu08mLhxE2JmzIBTQIA62Pn7jAoI3XKy0G5gf09XTOvyMM2f7ciCLSUBErBwAjSANmIA5SBnOQS6bdu26qw/MXayFqBPnz75U76yxi8oKEht9JBz/+T4mNmzZ6tNInJ7iKwR5AighX+iTVi9nJQUxMyYiaRNm+DZvTv8pkyGfblyqgb/dBOICavIV5EACZAACZRCgAbQRgyg9L8cBD1u3DgcPXoUPj4+eOWVV5QJdHR0zJeHrOUbPnw49uzZAwcHB3Ts2BFLly5V6wNLShSQbX63pJ05g8jgEGRGRcFv2lR4detmmyDYahIgARKwUgKM3zo0gKbUIgVkStrmf5dsmE/68kvEzJoN52rVELh0CVxKuSfa/LVlDUiABEiABEojwPhNA6jp00EBacJnVZmzbyUjJjQUN7ZsgVfPnqgyaSLsb18raFUNYWVJgARIgATA+E0DqOljQAFpwmc1mdNOnVK7fLPi4uAXGgrPLv+ymrqzoiRAAiRAAsUJMH7TAGr6XFBAmvBZfGaZ8k389DPEzpkD5xo11C5fl/vvt/h6s4IkQAIkQAL/TIDxmwZQ02eEAtKEz6IzZ9+6hegpU3Dz2+3w6t0LVcaPhz2v97PoPmPlSIAESKCsBBi/aQDLqpUSn6OANOEze+bSjmtJPXFC7fLNvnYN/jNnwKPIHdJmrzgrQAIkQAIkoIkA4zcNIAWkiYD1Zt7+e3TxA5s9XLDQ6Qx8PnkfLrVrqylf5+rVrbeRrDkJkAAJkAAHcErRgO6ugjOl1vkvCFPSNty7xPwNWROB3AJFumekIvjXz9Ay+jhuPNMDTedNg/3tW2MM92aWRAIkQAIkYAkEGL85AqhJhxSQJnxmySzTvq3C9ha6qq329T8x/uc1KJ+ZiiUNn8eFh5rip3Ht4WCfd4uvWarKl5IACZAACRiJAOM3DaAmaVFAmvCZJfOBcwnovfzgX+/OzUW3cz/i1RPbcM4rAHObvIQ494rqT+sHNkeLmj5mqSNfSgIkQAIkYFwCjN80gJoURgFpwmeWzJuPRmLEhqMon5GCkIhP0SLmBL6s2Rof130GWfZ/Xwu4tFcQugYFmqWOfCkJkAAJkIBxCTB+0wBqUhgFpAmfWTLLCGBo2AY15euWlYHFjV7AIf+6xerCEUCzdA9fSgIkQAImIcD4TQOoSWgUkCZ8Js+cm5ODqys/RMzicJzxro55TV5EfDnvQvWQVX9+nq5cA2jy3uELSYAESMB0BBi/aQA1qY0C0oTPpJmzrl9H1PjxSN73A5K69ULfnIbItncotBM4b8vHe30boWM9f5PWjy8jARIgARIwHQHGbxpATWqjgDThM1nmlCNHEDlqNHIzMhAQNg/lW7dGiecAerpiWpeHaf5M1jN8EQmQAAmYhwDjNw2gJuVRQJrwGT2zTPkmfLAc8W+/DbeGQQhctAhOVarkv7e0m0CMXjG+gARIgARIwKwEGL9pADUJkALShM+ombMSEhA1dhyS//tf+Ax+HZXfeAN2jn/v8jXqy1k4CZAACZCARRNg/KYB1CRQCkgTPqNlTj50GFGjR0NGAAPmh6F8y5ZGexcLJgESIAESsD4CjN80gJpUSwFpwmfwzLnZ2bj6/vu4+s67KNe0KQIWzIeTr6/B38MCSYAESIAErJsA4zcNoCYFU0Ca8Bk0c1Z8PCLHjEXKoUOo9MYbqDRkMOwcHAz6DhZGAiRAAiSgDwKM3zSAmpT8/+2dCbiN1f7Hv8d4zDOHg+pSEeVcQxFJVOhWmiiijJXbQMSRZIjMY0UhyjXm3pL6qxSKm3DpOCESKsMxndDJkPn8n++6vefus4czvXuf/e69v+t5znO79rvWu9Zn/d53fd/f+q21ZEC28PktM+P8KP6QJwqx48ajSMOb/Fa2ChIBERABEQg/Ahq/JQBtWbUMyBY+25lTL15E8tSpOPbWdBRp1MjE++UrW9Z2uSpABERABEQgvAlo/JYAtGXhMiBb+LKU2ddWLReOHMHBvi/gTEICyj33LMo88QSi8uTJUpm6SAREQAREILIJaPyWALT1BMiAbOHLNLOvzZpHVT6FStPGICp/fsROGG8WfCiJgAiIgAiIQFYJaPyWAMyqrXi9TgZkC1+GmSn+es5LSHdUW97Ll/DYjuVot2sV/oi7ETdMm4R8pUsHrhIqWQREQAREICwJaPyWALRl2DIgW/h8Zua0b5Mxq3Ao5WzaNWXP/IYBm+ahxol9mFOzFdbWb4V/D7gdefNYJ/gGpi4qVQREQAREIPwIaPyWALRl1TIgW/h8Zl635xjaz1yf9vuNh7ej77eLcDZfAYyu3xE7ylxpflvYoyEaVSsTmEqoVBEQAREQgbAloPFbAtCWccuAbOHzmXlpYhJ6LUpEvssX0Xn7p3hw92psqFATE+o9gpMFiqTlm/JIHNrExQamEipVBERABEQgbAlo/JYAtGXcMiBb+DL0APaa/Ale3DQP1X87gNm1/oYl1ZoCUemne+UBDAx/lSoCIiAC4U5A43cECcDU1FScPn3aw6bz5MmDwoUL58jWZUA5wpZpppTPv8CuF+JxKm80RjXoiJ2lr0iXhzIwpkQ0vo5vrhjATGnqAhEQAREQAXcCGr8jSABu2LABDRs29HgKYmNjceDAAfPv69evR79+/ZCQkIDixYujbdu2GDVqFIoU+d+0o2sBMiD/vlQunz+Po+PH48Q/5uLMjY3RuWxLnCpQON1KYMsH+GbHumhVu6J/K6DSREAEREAEIoKAxu8IEoALFizAM888g48++iidcRcsWBANGjTADz/8YP73xhtvRM+ePZGcnIyhQ4eiXr16+OSTT7w+EDIg/70nzu/fj6Tez+Pcjz+ifP/+KNXxUSz//jCGfbw93WrgiiWiMeSe6yT+/IdeJYmACIhAxBHQ+B1BAnD48OFYtmyZ8fJ5S506dcKaNWuwc+dOREdHm0uWLFmCBx54AKtXr0bTpk09ssmA/PPO+P2z5Tg0aBDyliqF2EmTUKh2rbSCfZ0E4p87qxQREAEREIFIJKDxO4IEYOfOnXHp0iXMnTsXFy5cQP78+dNs/vLlyyhbtiy6d++OsWPHpv37mTNnUKpUKfTu3RtjxoyRAPTzW+LyuXM4OmYMTixYiGKtWqHi8FeQt1gxP99FxYmACIiACIhAegISgBEkAG+55RZERUXhyJEj+PHHH1G0aFE8/PDDmDBhAo4dO4Zq1arBm0PBAAAgAElEQVQZcdixY8d0VlKjRg3w78MPP5QA9OMb5Pwvv+BAnz44v3sPKrw4ACUfecT0j5IIiIAIiIAIBJqABGAECcBKlSrh1KlTGDFiBGrWrIlvvvnGePXq1KmDyZMnmwUijPVr3bp1Ortr1KiRmRL+8ssvfQrA/fv3m0UjVmJcIf+UvBNIWbYMh18ejHzlyiF28iRE16wpVCIgAiIgAiIQMALnzp0D/6xEAVilShWkpKSkG78DVgEHFhyVyv1RIiDNnz8fdevWNeLPSrNmzTLTvhSFgwYN8ioAGzdujJIlS5r4QfdkfUG4//uQIUPMAhKl9AQunz2LIyNH4bfFi1H87rsRM3Qo8hb1vsJa7ERABERABETAXwQ4Jg8bNsyjOAlAfxEOsXJOnDiB0qVLG6OgaONK4fbt26drRa1atVC/fn3MmTPHpwCUBzDzjj/3009mle/5vXtRYdBLKPnQQ5ryzRybrhABERABEfADAXkAPSFGhAdw9+7dZvXvfffdZ2L/rMR4wJiYGDMFPGDAAPTq1QujR49O+/38+fMoUaKE2QuQC0F8eQAj+QsiK89lytKlODTsFeSPiTGrfKOvvSYr2XSNCIiACIiACASEgGIAIyQGcO3atWjSpAlmz56NLl26pBnTuHHj0L9/f3z//fcYOHAgtm7dih07dqBAgQLmGk4bc3uYXbt2mUUiEoC+n0Nv27VEnTuLw8NHIOWDD1CiTRvEDH4ZeXxsqh2QJ1yFioAIiIAIiIAXAhKAESIAL168iNtuuw2bNm3C4MGDzapeegS5Avjxxx8HYwG3bNliNoFu1qwZevTogZ9//tlMDXfo0AHTp0/3+gDJgP6L5bNthzw2bK53+QQGJ8xDwWNHEfPyyyj5wP16CYmACIiACIiAIwho/I4QAUhrO378uBF03NyZU79Vq1Y13j16/vLly2cMkhtBx8fHIzExEWXKlDHikHms3+UB9HxuKf56zkv433Ftqam4Y99G/H3LEhwuXBoFXhmFFq0bOeKBVyVEQAREQAREgAQkACNIAAbC5CPdgDjt22TMqrSj2qIvnsPT332A2/d/i8+uuBHTr78PpcoUx9fxzZE3j/b4C4QNqkwREAEREIHsE4j08ZvEImIRSPZNI2s5It2A1u05hvYz/3u03pUpB/Hixnko98dveD3uIXxZpW4axIU9GqJRtTJZg6qrREAEREAERCDABCJ9/JYAtGlgkW5ASxOT0GvhZrTeuwFPbvkQSUXLYWSDTkgqVj4d2SmPxKFNXKxN2souAiIgAiIgAv4hEOnjtwSgTTuKdANat3UfEnvHo1lSIpZd2Qgzrr8X5/P+74xlC688gDYNTdlFQAREQAT8SiDSx28JQJvmFMkGdHb7dhzo/Tx+P3QUU+o8hNWV4zxoMuovpkS0YgBt2pmyi4AIiIAI+JdAJI/fFknFANqwqUg0IJ4ceGLhQhwdNRoFr74ae3q+iB4rjxiKrmcKWks+3uxYF61qV7RBWVlFQAREQAREwL8EInH8dicoAWjDpiLNgC6dPIlDg17GyeXLUerRR1E+vj/yFCjgdR/AiiWiMeSe6yT+bNiXsoqACIiACASGQKSN394oSgDasK1IMqA/tm5D0vPP41JKCiqOGIHiLe9MR87bSSDa+sWGcSmrCIiACIhAwAhE0vjtC6IEoA3zigQDMlO+c+fiyLjxiK5RA7ETJ6BAlSo2qCmrCIiACIiACASXQCSM35kRlgDMjFAGv4e7AdHbd/Cll3BqxUqUfvwxlO/bF1F/npNsA5uyioAIiIAIiEBQCYT7+J0VuBKAWaHk45pwNqA/vvsOSc/3waVTp1Bp1EgUa9HCBillFQEREAEREAHnEAjn8TurlCUAs0rKy3XhaECc8j3+zrs4OnEiCtWqZaZ888dqE2cbZqKsIiACIiACDiMQjuN3dhFLAGaXmMv14WZAF0+cwKEXB+LUV1+hdLeuKN+7N6Lye27sbAOZsoqACIiACIhA0AmE2/idE6ASgDmh9meecDKgMwkJSOrTF6lnz6Li6FEo1qyZDTLKKgIiIAIiIALOJRBO43dOKUsA5pQcgFAzIG9bteRBKo69PQvJU6agUFwcYieMR/6YGBtUlFUEREAEREAEnE0g1MbvQNCUALRBNZQM6LNthzDs4+04lHI2rcXXFLyA0TuXoFDif1DmiSdQ7rlnEZUvnw0iyioCIiACIiACzicQSuN3oGhKANogGyoGRPHXc15CuqPaav+6B/Gb5iPf5Us4138wmnW81wYJZRUBERABERCB0CEQKuN3IIlKANqgGwoGxGnfJmNWpXn+8qReRrsfV6HjjuXYVvYvGFevAwrEVMDX8c2hkztsGIOyioAIiIAIhAyBUBi/Aw1TAtAG4VAwoHV7jqH9zPWmlSXPnkS/bxcgLnk3Fl57OxbUuAOXo/KY3xb2aIhG1crYoKGsIiACIiACIhAaBEJh/A40SQlAG4RDwYCWJiah16JE1Enehf6bFpjWjqvfAYnlrk7X8imPxKFNnPb7s2EOyioCIiACIhAiBEJh/A40SglAG4RDwYDW/XgUy/qNQPudK/BdueoYV689TkQX92i1PIA2DEFZRUAEREAEQopAKIzfgQYqAWiDsNMN6MKRo0jq1w+nN27E/GvvxKJrW6RN+VrNjgIQUyJaMYA27EBZRUAEREAEQouA08fv3KApAWiDspMN6NTXa3Gwf39E5c2LA88MRNfNl0xLU13aS/HH9GbHumhVu6INEsoqAiIgAiIgAqFDwMnjd25RlAC0QdqJBpR68SKSX38Dx2bMQJHGjVFpzGjkK1MG3vYBrFgiGkPuuU7iz4YNKKsIiIAIiEDoEXDi+J3bFCUAbRB3mgFdOHwYSX1fwB+JiSjXqxfKdO+GqDz/XeXL5O0kEG39YsMAlFUEREAERCAkCTht/A4GRAlAG9SdZECnVq/GwfgBiIqONse5Fa5Xz0bLlFUEREAEREAEwpeAk8bvYFGWALRB3gkGlHrhAo5Onozjs2aj6K23ouLoUchXqpSNVimrCIiACIiACIQ3ASeM38EmLAFooweCbUAXDh5EUp+++GPbNpR//nmU7tI53ZSvjaYpqwiIgAiIgAiELYFgj99OACsBaKMXgmlAJ1etwsEXByJvkSKInTgBheLibLREWUVABERABEQgcggEc/x2CmUJQBs9EQwDSj1/HkcnTMTxOXNQtEULVBr5KvKWKGGjFcoqAiIgAiIgApFFIBjjt9MISwC69cicOXMwevRo/PLLL6hatSqeeeYZPPvss177LVAG5Gu17vkDB8yU79kdO1Ch3wso1akToqKs3fycZlqqjwiIgAiIgAg4k0Cgxm9nttZ7rSQAXbjMmzcPnTp1wlNPPYWWLVsiISEBI0eOxKuvvor4+HgPgoEwIF/79Y0u9ytipk8w3r7YSRNR6PrrQ8nOVFcREAEREAERcAyBQIzfjmlcFisiAfgnqMuXL+Oqq67CTTfdhMWLF6fh69WrF9555x0cOnQIRYoUSYfV3wZE8ddzXkK60zryX7qI7ts+xr0/r8Xphk3x19fGIW9xz7N8s9jfukwEREAEREAEIp6Av8fvUAQqAfhnr23evBl169bFsmXLcNddd6X15YoVK3DHHXfgk08+QevWrQMmADnt22TMKhxKOZt2j4qnfsWLG+fiypOHMbP2vdgU1xxfD2gBbd4cio+a6iwCIiACIuAUAhKAgATgn9Y4e/ZsdOvWDfv370flypXTbPTw4cOoWLEiJk2ahN69ewdMAK7bcwztZ65PK/+WpET03vxPnChYDKMadMKekrHmt4U9GqJRtTJOeYZUDxEQAREQAREIOQISgBKAaUY7duxYE+d35swZFCpUKO3fz507h+joaAwdOhRDhgzxKgApGou7TMsWLFgQ/MtOWpqYhF6LEk2WkmdPYvYXo7Ah5jq8HvcQzuSPTitqyiNxaBP3XzGoJAIiIAIiIAIikDkBjuX8sxIFYJUqVZCSkpJu/M68pPC5Qh7AP/uSCz0GDRrkIQAvXLiAAgUKgAKxX79+XgWguzlQKFIwZie5ewArnUrGwSJlAbdVvvIAZoeqrhUBERABERABmDF52LBhHigkAGUdmDZtGp5++mkcPHjQTPlaKTk5GeXLlweniLt06eJVAPrDA2jFAB5OOZtuEYh1Q272ElMiGl/HN1cMoOxVBERABERABLJBQB5AT1jyAP7JZPXq1WjWrBk+/fRTtGrVKo3UmjVrcOutt4KLROLcTtvwdwyBtQqYN0916Strp783O9ZFq9r/E6fZsH1dKgIiIAIiIAIi8CcBf4/foQhWAvDPXjt//rxZ/MH9/+bOnZvWlz169MDnn3+OvXv3evRvIAzI1z6AQ+65TuIvFJ8w1VkEREAERMBxBAIxfjuukZlUSALQBdCMGTPw5JNPgnv/0Ru4cuVKTJ06FfPnz0f79u1zRQDyJr5OAgk141J9RUAEREAERMCJBCQAtQrYwy6nT5+OCRMmYN++fahWrRoGDhyIRx991Kv9yoCc+FirTiIgAiIgAiKQMQGN3xKAtp4RGZAtfMosAiIgAiIgAkEhoPFbAtCW4cmAbOFTZhEQAREQAREICgGN3xKAtgxPBmQLnzKLgAiIgAiIQFAIaPyWALRleDIgW/iUWQREQAREQASCQkDjtwSgLcOTAdnCp8wiIAIiIAIiEBQCGr8lAG0ZXiANiLuWjxo1Ci+++GK2zxW21ahcyqz25RLoAN5GfRhAuLlQdLj3HxGGexvVvpw/KIEcv3Neq9zNqX0AbfAOpAEFsmwbTfZbVrXPbyiDVpD6MGjo/XLjcO8/Qgr3Nqp9OX8Uwp1dVshIAGaFko9rAmlAgSzbRpP9llXt8xvKoBWkPgwaer/cONz7TwLQL2YS1EICaaOBLDuo0LJxcwnAbMByvzSQBhTIsm002W9Z1T6/oQxaQerDoKH3y43Dvf8kAP1iJkEtJJA2GsiygwotGzeXAMwGLPdLU1JSULJkSezfvx/Fixe3UZJnVhpnlSpVAlK2Xyuaw8LUvhyCc1A29aGDOiMHVQn3/rMEoN6jOTAOh2QJpI1aZf/2228oUaKEQ1qcu9WQALTB+8CBA0akKYmACIiACIiACIQeATpwKleuHHoV90ONJQBtQLx8+TIOHjyIYsWKISoqykZJyioCIiACIiACIpBbBFJTU3Hy5ElUqlQJefLkya3bOuo+EoCO6g5VRgREQAREQAREQAQCT0ACMPCMdQcREAEREAEREAERcBQBCUBHdUfkVubSpUv4448/PADkzZsXhQoVchQYTh2cPn3ao06cRihcuLCj6pqblQmlPsxNLqF+r1OnTnltQtGiRR3VtDNnzoBhOe6pSJEiER2iEyr95yhjipDKSAAGqaPnzJmD0aNH45dffkHVqlXxzDPP4Nlnn82wNuPHj8e0adNw6NAhXHPNNRgwYADat28fpBb4vi2FwIQJEzBr1izTPq6wat26NVj/cuXKec343nvv4ZFHHvH4rXHjxvj6668d1cYNGzagYcOGHnWKjY0FFwb5SqHSfxcvXsTZs2d9tsOXKA+FPpw+fTqGDx/u0U/r169Hv379kJCQYFb0t23b1pzEQ/GQUVq2bBkGDx6MHTt2GNvu3LkzXn75ZeTLly9oNuurjUuXLsXIkSOxbds2E/NEGx4zZgzq1q3rs65HjhxBTEyM198vXLgQlHZ6ax8/ythX3j4id+3aherVq/tso9P60L19vj44XRvkS4w7qf+yMi6E03MYtBdANm4sAZgNWP66dN68eejUqROeeuoptGzZ0gw6fDG/+uqriI+P93ob/jZkyBDze4MGDbBy5Uq88cYbWLRoER5++GF/Vc0v5fD4Og4szz33HJo1a4bt27ebwfT666/H2rVrvX6Ns/3kMmPGjHR1oHhkPielBQsWGMH+0UcfpatWwYIFTd94S6HUf++++y66dOniE/mtt96Kr776yuN3p/chxXnz5s1BT5GrUP/hhx9Mv914443o2bMnkpOTMXToUNSrVw+ffPKJTw6rV6/G7bffjvvuuw8dOnTAnj17TD4+22+++WZQTNZXGz/77DPcddddaNWqlelbbn3BZ/TXX3/Fzp07UaFCBa/1/eabb8CPsBUrVngcSdmkSZNcb6Ov9nExHj/A+A654oor0tWrfv36iI6O9lpXp/Wht/bxI/qqq67KkDVForfkpP7LbFygHYbLc5jrD0YObygBmENwOc3GKQo+zDfddBMWL16cVkyvXr3wzjvvGO+eu9eB+w1ymToHp7Fjx6bladOmjfma58DjlMQv8PLlyxtR+vbbb6dVi//do0cPcCCi6HVP3bp1M9OqFLROT/Qg0WvAr9WspFDqP7bn6NGj+PHHHz2a9v333+Pvf/876L3u2LFjyPThl19+CT5f/BChF8LdU0vBtmbNGiOELKGwZMkSPPDAA6BAaNq0qdduvuWWW0Av2Lp169I+aiZNmoQXXnjBPJNXXnllVszDL9dk1sYWLVogKSkJ7EN6cJl2796Nq6++2swk8APNW5o7d67xjB4+fNgv9cxpIZm179///jf4YcJ3SHZCRpzShxm1j+f9bty40QMd28oPD9rpzJkzHd1/WRkXKN5D/TnMqX0HK58EYC6T37x5s5lyoYDgF7mV+IV9xx13GI8Dp0tdkzUY8eV93XXXeYgqDmw1a9bM5ZZ4v92WLVtQp04d/POf/8RDDz2UdhHrXrt2bTMN3LdvX4/M9BTyZUxxdf78eRQoUMAR7fFWCU7zUUhwcKQAyJ8/f4Z1DaX+89UQilh6Uv72t79h8uTJXi9zah/S9j7++GNTZ9olp8UsDyA/yMqWLYvu3bun+7iil7BUqVLo3bu38ZS5p+PHj5t89MJTFFvJElUM1eAHW26ljNrIOpQuXdqIBdbXNXHamlPBFh/3+tKjydkGCiyGBlA8BmPLq8zaR681p965pxufTdYxs609nNSHmbXPmx3xI/vnn382ITK+3pdO6b+sjAucJQn15zC3nnd/3UcC0F8ks1jO7NmzQW+X++aT/MKuWLEi6EHgoOOaGGPEeEHGZbm+1OiBatSoESgwOA3lhMSppU2bNhmRy0HHSowH5MPNOLF27dp5VJUbateqVct4KDg4My85jRgxwnFikEKVAwyFBD1ljL/hy5hxj952lA+l/vNlQ/TefvHFFybWzZeHJRT6kOKdH1uWAPzpp59QrVo1I+bdvZo1atQA/z788EMPLKtWrQK9ahRG7lOh9CIyvMOXUA70c+reRt6PIo4eSbbVXaxSqFKwekv0jvKZpL0zVIVtu/vuuzFlyhSzf1owkrf2UfwxNIPx1PQi8T3J6X72ga+PY6f2obf2uXOeP38+Hn/8cSQmJpoPa1/JKf2X2bjAjyyGN4XTcxiMZyO795QAzC4xm9dzCpeGTg+D60BKNz9frvxiY6yfa6KH4f333zeCwzVxyooDFL9++TJwauKAS28gPSqcsnaf4qaw5epZxiFR8HG6e/ny5Xjttddw//33G6+NkxIHPq6sY105uDDOhi8wej75NW5NsVl1DvX+4zQovXv/+te/8OCDD3rtilDpQ/fB9T//+Y8Jx/DmeefHFZ9JTs+5J4ZvUPR7877zQ46xdgzpCEbKioCg8OVHIwU9P9hou97SzTffbH6nwCKPrVu3Gi89n2WKD26Cn9vJW/vo3Vy4cKH5eObMCj1jfD75nqVwpTAMlT7MrP/oueQiQC4AfP311zPE78T+syrsOi5wDOM7Jpyew9x+LnJyPwnAnFCzkYdu7kGDBnkIQE4l0o1PgciYG9dE7wsXHLgLQK5u44uAgxFXLTotMZiegb/0ejIwm6sQb7jhBo9q8iX9wQcfmFgr1xc1Bx2+xDltHhcX55jm8eubHk5Xz4Ll4fTmjQ3V/rOAc3EEvZz0mPhKodKH7oMrFyXRg+dt4OHiB571zXAN90QboMfQmwBkjCHF1dSpU4NisxkJCL5nOMvwyiuvgAsHaLfeVt9bFeczyw8e18VN9CZy8Yu32YrcaLC39lFMcOU1RYSVuLiH7xt+gHnzxjq1DzMTgBwf+E5luAGFeEbJif3nbVzgiRzh9hzmxrNg9x4SgHYJZjM/p1qefvppc4QcPQVW4kPBxRN8sN1XYPbv3994w9y35mBgMAdnDsy33XZbNmsS2Mu5mIMvXj7YXDFLr0F29w2z4iW9TQsEtvbZL/3EiRNm2prtpMB3TaHYf1b9P/30U+NR4fQvB/3sJqf1ofvgSgHH0ANOH7pvqcR/Z9wjF724JwpGxkPS+0vPmGuih5sLQYYNG5ZdXH653peAYF88+uijxuvHPmU8YGarS31ViKEO/Oh0Xejll8pnoZDMBJJrEfRsMs6RAjFU+jCj9h07dsycP9+nTx/zcZzTFKz+8zUuhONzmNO+yc18EoC5SRswqwr5lcqBldNEVmLcClexefN2cQDiS4Evbk75Wukf//gHunbtajyDZcqUyeWW+L4d97FiDBSn1ihoXReueMv13XffmalhTuO4Bphb++3xK/bee+91RPv41c3YS3p4XAWttd8WY6O4/Y1rCrX+c607hQLjHNnujFKo9KH74MrQC3r5uEqYcbZW4kIkDpJcHesek8tr9u7da2LquN0Lbd1K+/btM97uYMblehMQnAalh51teuutt3DPPfdk+jwxLtlanOa6TQw9h7T9J598EhMnTsy0HH9f4N4+fmTyHUEh7hrjyPvSS88/zjC4J6f2YUYCkDNEXLVt7R+bEVun9V9G40I4Pof+tvtAlCcBGAiqGZTJgYUxbtwKhZ4tK3Ga8PPPPzcDi3uiuODUKD1J9DBZ6c477wQfHIpKpyS+jOnZ5B5q9BplZTWvNRXj7smkp5QCkttXuC4oCWZbrSlDd0/tuHHjTP+4r9RmXUOp/1zZco84bgLMKSdf24RY14dKH3obXCnmGdvGDyzLXtkeBtAzzMJdVFhtZlgCN43mx5uVGOLBP3r0M9tEOlB27K2NFH8U8vyoct8nz1c9+NzxXcVFTK7eTMbkciGXt2nzQLXJtVz39nFamyKeccau3lorvjOjFdlO7MOMBCA9moyX5tZDmSUn9V9WxoVwew4z6x8n/C4BGIRe4GbH/Hqm14HeQMbUMF6Igw6nofjgckDiBsiMJ2IaOHAgKDI4vci4Fsb9MSifoomrUp2SuFiFL2J6U7wFlnNHfi5+cW3f77//bmKMKDg40FB0UDySE2OVGAvolMStMDjdzsB4Doz0yNIjyBXAXIjDmKpQ7j9XzvQws01cBOEaW8Vr3NsYKn3obXDlFhUMpWAb+SHGBQS0Q3qk6bVg4j5m/NDi82htTG5trszruDiG3nvaPfMy9jVYyb2NfK4YXsJ3C0Wte+LHFdvvrY3Mw3cNPwK4XQw99fwYoLeNz2gwtoTx1ofkTfbsP2sRCDcmZ7u//fZbs5gnVPrQlwC0vMtcJMjFgu7Jyf2XlXGBccTh9BwG6/nPzn0lALNDy4/XcmChaOBDTQ8DBR7jc5iskxi4ipAvAybuV8YXL/PRu8D4JHoavG2q7MdqZrso7vPnvojFtRC+vDh1xjhH1/ZxWxwKPa7+ZTwdhSKn1hg/6LTEVXgc5DnNZ3n3OLCyDxmIHsr958qa/ClouQeg+xnH3toYCn3oa3ClF4+r87myleEUFL7sY+tIN+s0Bv47224lTi1yMKZ3jeKQxzl6mzLOTRt2byM/VnydUMN6WSe7eGsjRQWFFTfp5dY5nArmBx4/zLIb0+svBt76kHv/cUUsPxq5wpmLIygEKQKt6etQ6UNfNsr4OQpyzhRxz1j35OT+y8q4wOconJ5Df9l7IMuRAAwkXZUtAiIgAiIgAiIgAg4kIAHowE5RlURABERABERABEQgkAQkAANJV2WLgAiIgAiIgAiIgAMJSAA6sFNUJREQAREQAREQAREIJAEJwEDSVdkiIAIiIAIiIAIi4EACEoAO7BRVSQREQAREQAREQAQCSUACMJB0VbYIiIAIiIAIiIAIOJCABKADO0VVEgEREAEREAEREIFAEpAADCRdlS0CIiACIiACIiACDiQgAejATlGVREAE0hPgsYdt27Y1J2289tprHnh4XB1PyuH5rzyu7y9/+Qu6du0KniedP39+4RQBERABEXAjIAEokxABEXAEAesoK+toMtdKtWjRAjxQfs+ePTh48CAKFiyY9jPP0O7WrZs5f5dHtfH8VwpBngvbpEkTc+Sgv9Odd95pzsblkWh2Eo9/XLBgAWrWrInt27d7FPXDDz/gpptuwo4dO1CpUiU7t1JeERABEUhHQAJQBiECIuAIAr4EIM/ZrVOnjjlvl//7xhtvoEOHDqbOp06dQpUqVcy50fQAuqaNGzfiySefxIoVK1C6dGm/tfGjjz4yZ7LyHG+eG5zTdObMGSNWT58+bYrYsmULrr/+eo/i2rVrhwIFCpjzeJVEQAREwF8EJAD9RVLliIAI2CLgSwD26dMHycnJmDt3Lp577jls3boVnPJlWr58OVq1agV6yq699lpb989K5kuXLqF27dpo3rw5pk6dmpUsPq9ZtGiREZIsb9u2bRg0aBCGDx/ucT2FLL2Aa9euRaNGjWzdU5lFQAREwCIgAShbEAERcAQBbwLw7NmziI2Nxf/93/8Z8UMvWVxcnPEGVq9eHZz+7dixI+hNK1SoUMDbQS9cp06djGCrVauWrfvde++9+Pjjj7FhwwbTNrZn586dXsts0KABihcvjpUrV9q6pzKLgAiIgASgbEAERMBRBLwJwDlz5qBz587pplqPHTuG+Ph4jB49Gl988QUYj/fzzz/jyiuvTNceeuu4eOS2224zU63+SI0bNzbTzt99911acc2aNUNiYiJY/4EDB+L999/H77//bqarJ0yYAOZxTydOnEBMTAz++te/Yv369eaab775Bps3bzYC1z2NGxru5NEAAAZ1SURBVDcO/fv3NzGQXOCiJAIiIAJ2CcgDaJeg8ouACPiFgDcBSM8YBR4XdFhp8eLFoCDav38/zp07h4oVKxpxxClU10Sv4QMPPIAjR46gVKlStuv422+/oWzZsnjiiScwbdq0dAKQ07TXXHMNUlJSzPQw78n7lyxZErt37/aIFZw5c6YpZ/z48ejbt69pD9swYMAAj1hG3ojikCLRut52Y1SACIhAxBOQAIx4ExAAEXAGAXcBSK9avXr1sHfvXlSuXDmtksePHzfes/feew/3338/ZsyYYWIDR4wYgYcffhjFihUzCz+4MISC6oUXXvBLA5csWWIEJVcV0ytpJXoAV69ejVtuucXEJFpT0VyAwrpxmtpatGLloVfyq6++Mm2rWrUqdu3aZQRktWrVjGB0TxS6nAJmvOPSpUv90h4VIgIiENkEJAAju//VehFwDAF3AUgBx1i/VatWedTx7rvvRmpqKpYtW2Z+41QwVwFzapbxgFxN26tXL3CbFX+lsWPHmqln3uv222/3EIDr1q0zW8NYiULtvvvuw8iRI80WNVbiNjZcucy4Pk7/WokxhdwKZtOmTUb4uieK4CJFiviME/RXO1WOCIhAZBCQAIyMflYrRcDxBDLaB9AJlecULadqOd1bv359DwHIfQqLFi2a9u/08NHT5766d+LEiWbal/GBXOFsJV736quvol+/fqDYdE833HCDmfZm/KCSCIiACNglIAFol6Dyi4AI+IWA0wUg4xDffvttsylzjRo1PATghQsXkC9fPg8B+NJLL5npaSvR80cvn6/ExSxc1OKeuKk1vYxc3KIkAiIgAnYJSADaJaj8IiACfiHgdAHIKWUeQ8dTRijirGTFAGZFAFqxfldddZVZLOKeGLvIuEBODXPvP9fE1cH0AHIVtJIIiIAI2CUgAWiXoPKLgAj4hYDTBSC3nWEs32effYaWLVvmSAAOGzYMQ4cONUKS5xq7pzFjxpiFK5wa5hSxa6JnMDo62mx6rSQCIiACdglIANolqPwiIAJ+IeBNAFL0cMUtRZNr4v9/9913zd57dhPvwSlabiidUeK2Lvfccw+4hUv37t1zJAA5dcxVvklJSahQoYLH7SwPIReJ0BMYFRVlrrl48aJZ3czFJ9w8WkkEREAE7BKQALRLUPlFQAT8QsDpApCLL7ih9GOPPYZZs2ZlWwAmJCSY1b0tWrQw29T4SlzBzJNGePTbzTffbC6z8k6ZMsVseaMkAiIgAnYJSADaJaj8IiACfiFgRwDu27fPCKM1a9agcOHC4B58XHyRJ08eM2XLEzq4eKNEiRJma5bJkyeb6VR65Kzj14YMGeLhaXRvGMXbgQMH0m3FktUYQK7u5UbO7h5E93uwHq+88orZxob1ZHrjjTfMlHFunXnslw5VISIgAo4mIAHo6O5R5UQgsglkZQqYmyTTa9a+fXuzvcpPP/2Etm3bomvXrmZLFZ7GwZM72rVrZ36jiGMsHk/iYMrqFDCvXbhwodnUmWcS8565legJLFiwIL788svcuqXuIwIiEOYEJADDvIPVPBEIZQIUZ4yF85auuOIKEwP4wQcfGOHnunUKp2i50ILbrXD6lCtqeT4vr+fpIV26dEk7Oi47ApCxeNyPr2nTpnjrrbdyBa01/UvxR2+jkgiIgAj4g4AEoD8oqgwREIGAEMiKB9A6R9e9Ajy39/Dhw8YLSJFITyCnfLmNC72D1tnB2RGAvAdPAmnTpo0RpuXKlQtIu10LpceRm0xr8UfAUesGIhBRBCQAI6q71VgRCC0CWRGAPGuXJ2fwGDgr/frrr0hOTjZij0KP5wqXKVPG/EwPHqeDcyoAWcaDDz6Iq6++GtwaJpCJU9acamb9eT8lERABEfAXAQlAf5FUOSIgAn4nkBUByNW5NWvWNFu5MA6QC0LoNeN5wdxOhQsquKKWC0A4bTt48GDjFRw+fLhZJFK9enWz4MLbvnx+b5AKFAEREAGHEJAAdEhHqBoiIAKeBLIiAJmL3r/evXubc3qLFy9u9vQbOXKkOTaN+why+pRTwFz4wa1ceO2nn35qzurlxsuTJk0yC0P430oiIAIiEAkEJAAjoZfVRhEQAREQAREQARFwISABKHMQAREQAREQAREQgQgjIAEYYR2u5oqACIiACIiACIiABKBsQAREQAREQAREQAQijIAEYIR1uJorAiIgAiIgAiIgAv8Pxv4+t+Fa2QwAAAAASUVORK5CYII=\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# calculate applied AC power\n",
    "# lock in measuring v_heat overloaded, so I need to clean up the data\n",
    "dat = 945\n",
    "xmult = [0.5, 2e-8] # plunger in mV, I_ac in Amps\n",
    "\n",
    "swp = dt.open_hdf5(dat, path=data_dir) # load sweep data\n",
    "v = swp['vac_heat2d'][:].mean(axis=1)*1e6\n",
    "y = swp['y_array'][:]*xmult[1]*1e9\n",
    "\n",
    "fig, ax = plt.subplots(1,1)\n",
    "\n",
    "ax.scatter(y, v)\n",
    "ax.set_xlabel('I$^{AC}_{Heat}$ (nA)')\n",
    "ax.set_ylabel('V$^{AC}_{Heat}$ ($\\mu V$)')\n",
    "\n",
    "popt = np.polyfit(y[:12], v[:12], deg=1)\n",
    "v_corrected = dt.line(y, *popt)\n",
    "ax.plot(y, v_corrected, c='C3')\n",
    "\n",
    "p = v_corrected*y*1e-3\n",
    "t_calc = ALPHA1_CLSD*power_to_theta(p)/(K_B)\n",
    "\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat945_voltage_fit.csv\"), popt, delimiter=\",\")\n",
    "di_results = pd.DataFrame({'i_heat':y, 'v_heat':v_corrected, \n",
    "                           'p_heat':p, 't_calc':t_calc, 'dT':t_calc-t_calc[0]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fit dataset 945 twice\n",
    "#    first with delta=0, second with delta as a free parameter\n",
    "\n",
    "avgs = 5\n",
    "span = 5.0\n",
    "\n",
    "x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['g5x2d'][:], avgs, axis=1)\n",
    "z = z*(1e-8)*(1e9)  # convert from dV to dI (nA)\n",
    "\n",
    "xlim = (-490, -486)\n",
    "centers = -488*np.ones(len(z))\n",
    "widths = 0.3*np.ones(len(z))\n",
    "\n",
    "di_zero_params = dt.di_fit_simultaneous(x, z, centers, widths, xlim, \n",
    "                                          constrain = None, span = span, fix=['epsilon','di2'])\n",
    "di_free_params, err = dt.di_fit_simultaneous(x, z, centers, widths, xlim, \n",
    "                                             constrain = None, span = span, \n",
    "                                             nboot=500, bootstat='bounds')\n",
    "\n",
    "pd.concat([di_results, di_zero_params], axis=1).to_csv(\n",
    "    os.path.join(analysis_dir,'dat945_di_zero_fits.csv'), index=False)\n",
    "pd.concat([di_results, di_free_params], axis=1).to_csv(\n",
    "    os.path.join(analysis_dir,'dat945_di_free_fits.csv'), index=False)\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat945_di_free_eps-err.csv\"), err, \n",
    "           delimiter=\",\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# equation for change in entropy at 0-1 electron transition\n",
    "\n",
    "def dS01(fields, a, b, g, de, temp):\n",
    "        return dt.gibbs_entropy(fields, a, b, temp, g, de)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "dat = 1011\n",
    "xmult = [0.5, 1.0] # mV, mT\n",
    "swp = dt.open_hdf5(dat, path=data_dir) # load sweep data\n",
    "\n",
    "avgs = 5\n",
    "span = 5.0\n",
    "\n",
    "### get centers from g_sense ###\n",
    "x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['g_sense_dc2d'][:], avgs, axis=1)\n",
    "y = swp['y_array'][:]\n",
    "dz = dt.dfdx(z, x, axis = 1)\n",
    "argmins = np.argmin(dz, axis=1)\n",
    "realmins = x[argmins]\n",
    "centers_fit = np.polyfit(y, realmins, deg=2)\n",
    "centers = dt.parabola(y,*centers_fit)\n",
    "\n",
    "x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['g5x2d'][:], avgs, axis=1)\n",
    "z = z*(1e-8)*(1e9) # nA\n",
    "\n",
    "results = dt.di_fit_simultaneous(x, z, centers, 0.65*np.ones(len(z)), \n",
    "                                 (-495,-485), constrain = None, span=span)\n",
    "results['field'] = y/1000.0\n",
    "\n",
    "results.to_csv(os.path.join(analysis_dir,'dat1011_di_free_fits.csv'), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "temp = 161.4 (mK, fixed)\n",
      "peak height = 0.938 +/- 0.032\n",
      "g = 0.4846 +/- 0.021\n",
      "de = 0.002 +/- 0.001\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create model and parameters\n",
    "smodel = Model(dS01)\n",
    "\n",
    "params = smodel.make_params()\n",
    "params['a'] = Parameter(name='a', value=1.0, min=0.2, max=1.8)\n",
    "params['b'] = Parameter(name='b', value=0.0, min=-0.1, max=0.1, vary=False)\n",
    "params['g'] = Parameter(name='g', value=0.4, min=0.1, max=1.0)\n",
    "params['de'] = Parameter(name='de', value=0.0, min=-0.1, max=0.1)\n",
    "\n",
    "# calculate temp based on calibration above\n",
    "pwr = power_to_theta(p)\n",
    "current = 0.5*2e-8\n",
    "volts = swp['vac_heat2d'][:].mean()\n",
    "theta = power_to_theta(current*volts*1e12)\n",
    "temp = theta*ALPHA1_CLSD/K_B\n",
    "\n",
    "params['temp'] = Parameter(name='temp', value=temp, vary=False)\n",
    "\n",
    "sresult = smodel.fit(-1.0*results['epsilon'].values, params, \n",
    "                  fields = 1000*results['field'].values)\n",
    "\n",
    "N = 500\n",
    "sfit = sresult.best_fit\n",
    "resid = sresult.residual\n",
    "boot_params = np.zeros((500,len(sresult.values)))\n",
    "for k in range(500):\n",
    "    stest = sfit + np.random.choice(resid.flatten(), size=sfit.shape)\n",
    "    out = smodel.fit(stest, params, \n",
    "                      fields = 1000*results['field'].values)\n",
    "    boot_params[k] = [v for k, v in out.values.items()]\n",
    "\n",
    "### print info for paper ###\n",
    "print('temp = {0:.1f} (mK, fixed)'.format(temp))\n",
    "\n",
    "peak_err = np.abs(np.percentile(boot_params[:,0], [2.5,97.5]) - sresult.values['a']).mean()\n",
    "print('peak height = {0:.3f} +/- {1:.3f}'.format(sresult.values['a'], peak_err))\n",
    "\n",
    "g_err = np.abs(np.percentile(boot_params[:,2], [2.5,97.5]) - sresult.values['g']).mean()\n",
    "print('g = {0:.4f} +/- {1:.3f}'.format(sresult.values['g'], g_err))\n",
    "\n",
    "de_err = np.abs(np.percentile(boot_params[:,3], [2.5,97.5]) - sresult.values['de']).mean()\n",
    "print('de = {0:.3f} +/- {1:.3f}'.format(sresult.values['de'], de_err))\n",
    "\n",
    "### plot results ###\n",
    "fig, ax = plt.subplots(1,1)\n",
    "\n",
    "bs = np.linspace(-5, 5, 500)\n",
    "ax.scatter(results['field'], -1.0*results['epsilon'])\n",
    "ax.plot(bs, smodel.eval(sresult.params, fields=1000*bs), c='C3')\n",
    "ax.set_xlabel('field (T)');\n",
    "ax.set_ylabel(r'dS$_{01}$/k$_{B}$');\n",
    "\n",
    "### save data ###\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat1011_field.csv\"), bs, delimiter=\",\")\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat1011_dS01_fit.csv\"), \n",
    "           smodel.eval(sresult.params, fields=1000*bs), delimiter=\",\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fit 2-3 peak data\n",
    "\n",
    "Fit dI curves to fit for dS at the 2-3 electron transition. Here, the entropy of the ST states is ignored because the field is not high enough for those states to contribute to dS\n",
    "\n",
    "dataset 1442 -- di vs plunger vs parallel field"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# equation for change in entropy at 0-1 electron transition\n",
    "\n",
    "def dS23(fields, a, b, g, de, temp):\n",
    "    return dt.gibbs_entropy(fields, a, b, temp, g, de)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "dat = 1442\n",
    "xmult = [0.5, 1.0] # mV, mT\n",
    "n=-10\n",
    "swp = dt.open_hdf5(dat, path=data_dir) # load sweep data\n",
    "\n",
    "avgs = 5\n",
    "span = 5.0\n",
    "\n",
    "### get centers from g_sense ###\n",
    "x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['g_sense_dc2d'][:n], avgs, axis=1)\n",
    "y = swp['y_array'][:n]\n",
    "dz = dt.dfdx(z, x, axis = 1)\n",
    "argmins = np.argmin(dz, axis=1)\n",
    "realmins = x[argmins]\n",
    "centers_fit = np.polyfit(y, realmins, deg=2)\n",
    "centers = dt.parabola(y,*centers_fit)\n",
    "\n",
    "x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['g5x2d'][:n], avgs, axis=1)\n",
    "z = z*(1e-8)*(1e9) # nA\n",
    "\n",
    "results = dt.di_fit_simultaneous(x, -1*z, centers, 0.32*np.ones(len(z)), \n",
    "                                 (-325,-315), constrain = None, span=span)\n",
    "results['field'] = y/1000.0\n",
    "\n",
    "### save data ###\n",
    "results.to_csv(os.path.join(analysis_dir,'dat1442_di_free_fits.csv'), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "temp = 144.0 (mK, fixed)\n",
      "peak height = 0.982 +/- 0.017\n",
      "g = 0.438 +/- 0.009\n",
      "de = 0.000 +/- 0.000\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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Goo8iZJGAad98Bl2F329jYx+4gigVZqZNyUBGsA0NOCQlJRk+P1G2ZhIgAbQRFC8jARUQkCs3g2uWw/uTXxRYNSoVKOSzwjWX9mrf7EwgfndnQE44M6TGPidXI4iT+9IcwETHRx1l3q6ZcWJ4Q2QLcu/v1MJCoZBApomwP6bI4CKHgAKSBE+ZiYBixN4vPl/iBwxAj47tiNbsWKp7t8n5ve1X3wizfgGNyiNGXv+xtsPb2H6odkYVbUHThcokywft4RJEyMvIAGLE2D/TQOoSHQUkCJ8zEwCFiUgXnaEfNoGTp6eKLJ4EUyZ35dWgGJ+n3MWRwT8ehnDfp2Mx8454F+tV7Js3BImLYr8nAQsT4D9Nw2gItVRQIrwMTMJWJTAywsXENK2HQrPn4ejb72DL1afRVrz+9IKUJ7f9yo+EUN7jkOvk+vRo+Ew3HHLk8IEckuYtGjycxKwHAH23zSAitRGASnCx8wkYFECEUOHQRz95h20HdWmHMDD56+M3t9wfp+xSdLiGn1DJ14Zd5t/EKt3jEVg8epY/l5To2VzQYhFm5w3I4FUCbD/pgFU9HhQQIrwMTMJWIxAwrNnuPZRTTxs2RH9Hf+Dh8/j0ry3PL9PXKhvAo290t16PlzaEqbPH1tQJ+wcOvmOQoJjyqPluCVMmth5AQlYhAD7bxpARUKjgBThY2YSsBiBx7/8ggi/kejS6Hvcd81l0n118/tS2QfQt6yXrhx50Ujx6AjM2z8N/lV74JTBYhBxMUcATULPi0gg0wmw/6YBVCQyCkgRPmYmAYsRCOnUGWfCn+LbKr1Nvqds1lI7CUS/IHnbmKjoGMzZNxVhOd7CxMpddJcYvjI2OQheSAIkkCkE2H/TACoSFgWkCB8zk4BFCLwKC8P1Bg0x5cP22O/9YZr3zKhZkzeObnntALr+tQMdfP3xPJsruAo4TeS8gAQsToD9Nw2gItFRQIrwMTMJWITAvblzcXfxErRq4IfYLGLz5jcnYdjmd6oA/Ve8aeWRPxcmcMbPx/HjRj/MKd8aO4pVBfcBNJUeryMByxFg/00DqEhtFJAifMxMAplKQH5169qnI6ILl0DXAs3SvF8et2wY37JshsyfXLi47+VO3RD3MgavfpyHysU94eQojwOmGQIvIAESsAAB9t80gIpkRgEpwsfMJJBpBORNnrPeDpHO6RWLMs54lUHiGw6+NOexbY9/2YxIPz+UPHgAWfOlft5wpgFgwSRAAm8kwP6bBlDRI0IBKcLHzCSQKQTkuXjC63X6ayeaXz+MDk1GI84pi9H7ZcYcvYTHj/H3RzWRf8RweHbokCn1ZKEkQAIZJ8D+mwYw4+oBQAEpwsfMJGB2AvJq3MjoGCApCQv3/oCruYtg2oftdPcSb2P1RwIza45eaK/eSHr1CkVXrjB7PVkgCZCAMgLsv2kAFSmIAlKEj5lJwCwE9LdpufskFuOD/pLKLRYdifn7p2JU1Z44XeDdZPca2exd5M3pjHw5XTJtjt7jTZsQOcof0Su34E6W7Jl6L7OAZCEkoCEC7L9pABXJnQJShI+ZSUAxAXmunzTiZ5A6XNmFVsGH0K7paMQ7Jn/9a44TOdLaH3DX8Sso2KM15v+nhXQ8nEiZNdqoGCQLIAGNEWD/TQOoSPIUkCJ8zEwCigjoz/UzVtDMAzMQ6ZYXkyp1SvGx0hM5jBlPfXMnxzb+6EIkODhiZPXXG1BnxnxDRRCZmQQ0SoD9Nw2gIulTQIrwMTMJZJhAsrl+RkrJ8zIaq3eOxeQPO+CAdwXdFRnd5Fn/FqkZT9ncze3wAcYG/gUxKikWoPS8vA1tmwTgZVYXnQks4OGCI0PrcXuYDCuAGUlAGQH233ZuAFesWIFJkyYhJCQERYoUQf/+/TFgwIA3qmb//v0YOXIkzp8/jyxZsqBWrVqYNWsWihUrliIfBaTsAWRuEsgoAfns3dTyN7l5HP3++B/aNRmNZ9myJzOAGd3kWRSSlvEUJjC3W1Y8fB4n3bPA8wdYtnsixlbuimMFyyULd03PKqhRKm9GETAfCZCAAgLsv+3YAK5evRqdO3dG37590bhxY5w9exYTJkzA+PHjMXToUKOyOXLkCOrXr49GjRqhW7duiIyMxLhx41C4cGGcOnUKjo6OyfJRQAqePmYlAQUEtp4Px8D151MtIeD4T3BOiMOwj77QXZMre1ZMalVO0SbPaRlPYwEt+Gcl8vQKbZN9nMs1Kya1VhaPAoTMSgKaJsD+204NYGJiIooXL44qVapgw4YNOpEPHDgQy5Ytk4ydm5tbCvFXq1ZN+t3Ro0d1Zi8wMBA9e/bE4cOHUapUKRpATX9lsPJqIfAmI+YcH4sNQf5YVqYptpSspQvZHCNuaRlPY3y6Xw5Ew9DT6Og7CkkOyf+IVHLsnFragnGQgC0SoAG0UwN47tw5VKhQAcK8NW3aVKfNPXv2oGHDhggKCkKTJk2SaTYsLAze3t5YtWoVOnXqhISEBDg5Ob1R1xSQLT72jNkeCMivYqOiY2B4uEe1iEsYdWo5ejQcJi0CMce8P5mZqSOAnm7Z8Oj5Kym2Mg9uYurhuRhcawCueBZNht+csdlDu7IOJGApAuy/7dQALl26VBq1u337tvT6Vk5RUVHw8vLC9OnTMWjQoGQ627hxIz777DPJAC5evBjidbC7uzs+/vhj/Pjjj8ifP38KXVJAlnpUeR8SSElAXowhPtE3gYPObsC7j0LQp/53Zl91+ybjKeKQDd3IZmXQb+1ZKS7HpESs3T4a24tVw4oyyf/wlGuldFUy9UECJJA+Auy/7dQATpkyRZrn9+LFC7i6uupUERsbCxcXF4wePRr+/v7J1CIWeohXxDlz5kT37t3h6+uL4OBg+Pn5oWDBgrhw4QKyZcuWLI8sIGE0hVmUk7OzM8QPEwmQQOYSMNyOxSEpEWt2jMHuIpWw7L1mmbLvXmrG03CLF3HdsF8u4vHLOHzz+zr4REfgy3rfGAVijn0JM5c0SycB2yYg+n/xIyfRf4u3ftHR0cn6b9uuZfqid0hKSnrD8ejpK0wtV4uFHsK4GRrAuLg4ycQJgzhkyJBk4YrFHmL1r1g0Mn/+fN1nYkSwS5cu2Lx5M1q2bGnUABrWW5hLYTKZSIAEMp+A/obM+cNvwOObz3HbfzpyVq6Uaad8pLUPoFzro8H30fGnk/go/AK+P70KXRuNwN3snimgcAQw83XCO2ibgOiTAwICUkCgAbQzXcybNw/9+vVDRESE9MpXTvfu3UO+fPkgXhGLUT79NHXqVHz77bfYsmULmjdvrvvowYMHyJs3LyZOnIhhw4YZNYAcAbQzAbE6Nkvg/oIFePDTEpQ+fgwOWbNmaj3SOglE3Fx+ZRx9/zE2BI3C3P+0xPbirxebicQ5gJnaRCycBHQEOAKYUgx2OQJ48OBB1KlTB9u3b5de5crp0KFDqF27NsQikfLlyyejIUb4WrduLa0abtOmje4zed7gzJkz8dVXXxk1gFr+C4LfLySgJgIhnTrBKVcueM+Zo5qw5FfGUw7PxeNsOTC+Sled+RP/ULIvoWoqyUBIwMYIcA6gnc4BfPXqlbT4Q+z/J17hyql3797YtWsXbt26lUKqYqSvUKFC+OSTTyAWhMhJvA7+8ssvcfHiRZQtW5YG0MYecoarHQIJz57h76rVUMDve+Ru105VFRcm8Oy4qWh4aS/aNg1AoqNTpsxPVFWlGQwJqJgADaCdGkChuUWLFqFPnz7Swg4xGrh3717MnTsXa9asQfv27REeHi6ZunLlyknGT6SxY8di1KhR0jYwwgiKRSDidx06dMCSJUtSSJkCUvHTzdA0R+Dp3r0I69cfPrt3IZu3t+rq/+zcedxu3x6hY2bB/cMKmTY/UXUVZ0AkoEIC7L/t2AAKvS1cuBBibl9oaCh8fHwwYsQIdOzYUZLi8uXLpXmAYmNoceqHnIRxnDZtGm7cuCHNH+zatatkCsWxcIaJAlLhU82QNEsgMiAAz48dQ8mdO1XJICkhAX9Xqw7PLl3wVv9+qoyRQZGAVgiw/7ZzA5jZQqaAMpswyycB0wkEN2yEHDU/QoFRo0zPZOErwwYOQvzduyi2bq2F78zbkQAJ6BNg/00DqOiJoIAU4WNmEjAbgVehobjeqDEKz5uLnPXqma1ccxf0aMMGRAWMkVYpO+ntHWru+7A8EiCBNxNg/00DqOgZoYAU4WNmEjAbgYdr1+LOhIkofeI4nHLkMFu55i7oVVg4rjdogEKzZ8G9YUNzF8/ySIAETCTA/psG0ESpGL+MAlKEj5lJwGwEbvfrj8ToaBRd/e+qf7MVbuaCrvs2QfaqVeDFzeLNTJbFkYDpBNh/0wCarhYjV1JAivAxMwmYhUBSfLy0/Ytnj+5468svzVJmZhYSNXYcnh08iJJ7dmfmbVg2CZDAGwiw/6YBVPSAUECK8DEzCZiFwMuLFxHS5jMUXbsG2StUMEuZmVnI0z17ENZ/AHz27EG2wq+3oGIiARKwLAH23zSAihRHASnCx8wkYBYCD376CffmzsPbJ0/AIVs2s5SZmYUkREdLI5Ze48YhV+tWmXkrlk0CJJAKAfbfNICKHg4KSBE+ZiYBsxAI7f05kJiIIkt+Mkt5lijkRqtWcClVCgUnT7bE7XgPEiABAwLsv2kAFT0UFJAifMxMAooJJMXF4WqVqsjbty/yft5bcXmWKuDOpMl4snMnSu7bCwcHB0vdlvchARL4hwD7bxpARQ8DBaQIHzOTQIYJJCQm4dTNh3jy+1kUGfUVvNetQ44Pyme4PEtnfLp/P8K++BI+u3YiW5Eilr4970cCmifA/psGUNFDQAEpwsfMJJAhAjsuRSLgtz8RGR2Ddlf3oM21/fiq/RSMbF4OvmW9MlSmpTMlPH2Kv6tURYGA0cjdpo2lb8/7kYDmCbD/pgFU9BBQQIrwMTMJpJuAMH9frD6LpH9yTji6EK8csyCgWk/pN/M7VbAZE3jz0zbIVqwYCv34Q7o5MAMJkIAyAuy/aQAVKYgCUoSPmUkgXQTEa9+PJu+TRv5EypoQj42Bflj5ri82l6oDMZOugIcLjgytBydHdc+rE3X5Y+Q4ZNm3E89WbUHlEnlUH3O6GosXk4DKCbD/pgFUJFEKSBE+ZiaBdBE4fv0B2i8+octT9v51/HBkPvrXGYTruQrrfr+ud1VU88mTrrItebH8CrvQ3+cw9vgS9GowFImFvOH/SRmbGb20JC/eiwQygwD7bxpARbqigBThY2YSSBeBrefDMXD9eV2eDld2ocX1w2jXNACJDo66389sVx7Ny6tzg2X9V9iucTHYGDQKc//TEjuKV5Pit6VX2OlqPF5MAiojwP6bBlCRJCkgRfiYmQTSRcBwBHDK4Xl4mi07xlbplqwctY4AGr7CFkFPOzgbd7PnxqRKnWzqFXa6Go4Xk4AKCbD/pgFUJEsKSBE+ZiaBdBGQDVRUdAyyJsRhU6AffnrvY/zqU1MqR+1zAA0NrIi52+UgNAw9jY6+o4B/9gNUq4FNV2PxYhJQOQH23zSAiiRKASnCx8wkkG4C8ivU9+9dw8SjC/FF3W8Q4uElmT+R1PwK1fAVtoi3wt2rGH9sMfrU+xah7gWkOqj5FXa6G4wZSEClBNh/0wAqkiYFpAgfM5NAhggIE3h+7A+o++dBtGs6GkkOjvDycFH9IgpjI4DO8bHYGDgKC8v9F4Elakg8OAKYIVkwEwmkiwD7bxrAdAnG8GIKSBE+ZiaBDBMI6doNT5AVNwePRr6cLqhc3FP126jov8KW9zEUAH48NAcPXNwxqXIXm9nGJsMNx4wkoBIC7L9pABVJkQJShI+ZSSBDBKTzfytXwVv9+yFPz9cbQNtKkl9hi3hlE9j9ciAahJ5BJ99RmN/5Q24FYyuNyThtmgD7bxpARQKmgBThY2YSyBCBlxcvIaRNGxRdtxbZP/ggQ2VYM5P+UXYijkpRf2LMiaUIn7MKDRpUtGZovDcJaIYA+28aQEVip4AU4WNmEsgQgYcrVuDutHOWmzUAACAASURBVOkoffoUHLNly1AZ1s4kXgefuvkQd5/GIL9DHDzaNYXX+PHI1aqltUPj/UlAEwTYf9MAKhI6BaQIHzOTQJoE9I2SPNcvctAgxD98gGKrV6eZ3xYuEHX8q9kneFa0FJKG+NnEfEZb4MoYSeBNBNh/0wAqekIoIEX4mJkE3kjA8FWpuNjL3RmLfx2FfJ+1Qb6vB9s8QbmOLQ6tRYW7f6N3w2E2saLZ5sGzAponwP6bBlDRQ0ABKcLHzCSQKgH9I9P0Lyr47D6W7JmEOyMmoE4X235dql/HWmHnMfzManTwHYXHLu5SldW8pyGlSwK2ToD9Nw2gIg1TQIrwMTMJGCVg7Mg0+cIGoacx+OwGfNVuMnaN+lj1W7+k1sSGdfR8GY01O8difKXOOFLofdWfakLpkoCtE2D/TQOoSMMUkCJ8zEwCRgkY2zBZvvCrcxvxzqNQfFnvG5veMNlYHZfumoiTBd7Fwv+00HHhptB8SEggcwiw/6YBVKQsCkgRPmYmAaMEjB2ZJl+4cM8UXMzrgznlW9v0kWnG6vj17+tR/EkkBtT9d24jj4XjQ0ICmUOA/TcNoCJlUUCK8DEzCaRrBNAj9hnWbx+NKR92wH7vCljTswpqlMprkxSNjQA2CjmJr85vwmfNxuJFVhepXhwBtMnmZdA2QID9Nw1gMpkmJCTg5cuXKaTr5OQEV1fXFL+ngGzgKWeINkcgtSPTqkZegv/J5ejaaATuZvdEAXcXjP5vGZs8OcNYHQs9u4ef9kyGX7VeOJv/HR4LZ3PKZcC2RID9t50bwBUrVmDSpEkICQlBkSJF0L9/fwwYMCBVjf78889o165dis9r1KiBI0eO0ADa0tPNWG2agLEj03pc2oY64efQpZEf4OAgLZQQyVZXy6aoY1IS1u4IwM6iVbCyTBObrZdNC4/Ba4YADaAdG8DVq1ejc+fO6Nu3Lxo3boyzZ89iwoQJGD9+PIYOHWpU5OJzkW/RokXJPvfw8EC5cuVoADXz1cCKqoGAMEijf72MqCexUjhTD83GXdfcmFypky48YQILeLjgyNB6Nrki2HCvw+9PrcBb8S/gMm+xTY5sqkE3jIEETCFAA2inBjAxMRHFixdHlSpVsGHDBp0WBg4ciGXLliEyMhJubm4pNNKzZ088f/4c69evN0U/oIBMwsSLSCDDBI4G30fHn04iW0IcNm3zw+Jyn+C3Eh+lKM+W58rpn3ZSeN+vcFu+AKXPnLbZY+4y3NjMSAIWJMD+204N4Llz51ChQgUEBgaiadOmOknt2bMHDRs2RFBQEJo0aZJCanXq1EHNmjUxduxYvHr1CtnSOGeUArLg08pbaZKAvFq27P3r+OHIfPSrMxg3chVKwcJeVss+v3QZoZ9+itDR0+FeqRKPhdOk6llpSxBg/22nBnDp0qUQo3m3b99G4cKFdVqKioqCl5cXpk+fjkGDBqXQmLe3N9577z1cvnwZYWFh8PT0lMoZN26cUTNIAVniMeU9tExAXi3b9upefHZtH9o0G4tEB0e7GgGUKyNeB4/Zegmz1w3Bz6XrYUPp+jwWTsviZ90zlQD7bzs1gFOmTJHm+b148SLZ6t3Y2Fi4uLhg9OjR8Pf3TyaumJgYZM+eHfnz55cMnzCOO3fuxKxZs9CyZUts3LgxhRhlAQmj6e7++vgmkZydnaUfJhIgAWUE5NWyfXfMgWNSEkZW752sQFufA6hv/r5YfRZJAMYeW4wkBweMqtbL5he6KGt95iYB8xEQ/b/4kZPov8WgT3R0dLL+23x3VH9JDklJSeI7x66SWOjh5+eXwgDGxcVJI3nCIA4ZMiRZnYVZ3Lx5M2rVqiWtGJbTyJEjJUMoXiuXL18+WR7ZABrCE+ZSmEwmEiAB5QR2/BGOPB0+xuZSdbDu7Qa6Am19FbBcEcNj4dpd3YNPrx3AZ83GSKOd9mJylSuBJZBAxgmIPjkgICBFATSAGWeqypzz5s1Dv379EBERIb3yldO9e/eQL18+iFfE3bt3Nyl2eT7hqlWr0KnTv6sPRWaOAJqEkBeRgCICMVf/xs3mzTG58Vc44PrvH2deHi7w/8Q29wHUB2K4KbQ83/HLul/jpkdB3aW2vNBFkQCYmQTMQIAjgCkh2uUI4MGDByEWdGzfvh2+vr66Wh86dAi1a9c2Opp34cIFXLp0CR06dICDgzy2AJw8eRJVq1bF1q1b8d///tfoCKCW/4Iww3PJIkjgjQQerVuHqPETUPLkSZyJeom7T2OQL6eL3SyQMDwWTl7xvKjcf7GtRA0dG3tZ6EK5k4AaCHAOoJ3OARQreMUcPrH/nxi5k1Pv3r2xa9cu3Lp1K4X+1qxZI43w7du3D3Xr1tV9LkYSxYhheHi4tChEP1FAaniMGYO9Ewj/dghehYai+Iaf7bKqxo6FM7bnIUcA7bL5WSkrEWD/bacGUOhJbObcp08fiL3/xGjg3r17MXfuXAij1759e8nQXbx4UdrguVChQtLr3EqVKuH+/fvSPIECBQpg9+7dUjljxoyBmAtomCggKz25vK2mCATXq4+cjRoh/zDjG7jbOgxjx8KJU0/qhp1D58Z+0hsJW97s2tbbh/HbJwH233ZsAIVkFy5ciKlTpyI0NBQ+Pj4YMWIEOnbsKKl5+fLl0jxAsTF0t27dpN+J1bzC6InVv48ePULJkiWlk0TEEXLGEgVkn18MrJV6CMRFRiK4bj0Umj0L7g0bqicwM0dieCxclcjLGH1yGbr9c+6xrR53Z2ZMLI4EzEaA/bedG0CzKSWVgiigzCbM8rVOIDowEBHffItSR48gS548do1D/1g499jn+Hm7PxbV7IrGA7vyWDi7bnlWzhoE2H/TACrSHQWkCB8zk4BRAvpHoxVdPQ85Lv6Okjt3aIKWft19hvSCZ/UqKBjALaU00fispEUJsP+mAVQkOApIET5mJoEUBPRHwcSHc/ZNQ0S+IigyaYLmRsEiR47Ey/MXUOK3X6kUEiABMxNg/00DqEhSFJAifMxMAskIyPPg5J3ps8e9xIbAUZj1QRvsLloZWpsH9/h/WxA5YgRKnzgOJw8PqoUESMCMBNh/0wAqkhMFpAgfM5OAjoDhaRjigwp3rmL88cXo1WAoInK8pbmVsGLrm+uNGsN74QLkqF2baiEBEjAjAfbfNICK5EQBKcLHzCSgI2BsL7zOf+5A05DjaN9kNPDP5uxa2gtPnNJ5rVYt5GrZCvm+Hky1kAAJmJEA+28aQEVyooAU4WNmEtARMDwNQ3ww6ch8PM/qirFVXm/TJJLWTsMIGzgI8Q/uo9jq1VQLCZCAGQmw/6YBVCQnCkgRPmYmgVRHAJ0SE7Ap0A+r3mmMzaXq6K7T0gigeC1+fsYCuCybjycbd6Jy6QJwcvz3mErKhwRIIOME2H/TAGZcPYB0eoiHhwd4FrAijMxMAjA8DaP0o1DMPDgLg2oNwFXPohC2R0unYcirod1uBWP2gRn4umZ/PC7xDvw/KaO51dB8PEggMwiw/6YBVKQrCkgRPmYmgWQE9E/DaBF8EF3+2oE2zcYiwTGLdJ1WVgHrr4Z2lEZCR2LtOw3xS6nXZ5TP7fABcrs54+7TGOTL6YLKxT05MshniQTSSYD9Nw1gOiWT/HIKSBE+ZiaBFATkka+euxYgR9xLDPvoC3h5uGhm5MvYaujxRxfilVNWBFTtIfESb4ET5b1yAE3x4SNDAuYiwP6bBlCRliggRfiYmQSMEohPSMTV6jXwqF4zOPX6QlMjXMZWQ3e4sgvNrx9Bu6ajkeTgmIKZPCtQKyOkfGxIwBwE2H/TACrSEQWkCB8zk4BRArE3b+JGk6bwXrwIOWrW1BQlY6uhy9/9GxOPLUKfet8i1L2AUR5amyOpKVGwsplCgP03DaAiYVFAivAxMwkYJfD4l82I9PND6VMn4ZQzp6YoGRsBdI2LwcagUZjzfivsKFb1jTy0tEpaU8JgZc1OgP03DaAiUVFAivAxMwnoCIi5b6duPpQWNhRdMh3uocEosXWL5ggZroaWAcw8MAOhOfNj6oft38hEa/skak4grLDZCLD/pgFUJCYKSBE+ZiYBiYC88CMyOkb6/8V7JuNqoXdRcvxoTW55or8aWl7r0eePragS9Sd6NBrOEUA+NyRgBgLsv2kAFcmIAlKEj5lJQDJ/X6w+C9noeMQ+xfrtAZhUsSMOFf5AM1u/GErB0BR/FH4B359ehY6NR+Khq0cK5XAOIB8mEkgfAfbfNIDpU4zB1RSQInzMrHECxrY8qR5xESNPrUDnRn54kD2XpjZ/NpSD/mvx/HHP4NG5BSZU6owjhd7XGWaRh6uANf4gsfoZIsD+mwYwQ8KRM1FAivAxs8YJGFvw0OvSbxCjXd0a++nocGHDaxTBjRrjQdmKGPRWPcivy8XvtbRPosYfGVbfjATYf9MAKpITBaQIHzNrnICxLU+mH5yFSLc8mFKxo44OFza8RhExbDhi//4bRTZt0i2Y4UkgGn+IWP0ME2D/TQOYYfGIjBSQInzMrHEChiOAzvGvsCnQDwv+0wKBxatzBNBAH482bkSU/2iUPnUKTjncNK4eVp8ElBFg/00DqEhBFJAifMyscQKGW56UuxeMKUcX4Iu63yDEw0ua21bAwwVHhtbT/Fm3gtWZQ+fg3rcjno2bjgqtGmueicYfH1ZfIQH23zSAiiREASnCx8wkoFsFLFC0vboHra8dwGfNxgD/HHnG4830tsl5/BLrt/tjW/Ea2Fu1uWbOR+ZjQgKZQYD9Nw2gIl1RQIrwMTMJSATkLU++2D4bcHDAqGq9uLDhH20YbpMz6sQyuCS8wvc1+khX0CDzISKBjBFg/00DmDHl/JOLAlKEj5lJQEcgPi4ef1epigeftEWWLj1Qubin5l9xGtsmp/W1/eh4ZTfaNBuLREcnviLnM0QCGSTA/psGMIPSeZ2NAlKEj5lJQEcg5soV3GzREkVXrUT2SpVIBoCxbXLeeRiC6Yfm4KvaA3Ett7fEidvkUC4kkH4C7L9pANOvGr0cFJAifMxMAjoCD9eswZ1Jk/H26VNwdHEhGQDGtsnJmhCPjYF+WF6mKbaUrCVx4jY5lAsJpJ8A+28awPSrhgZQETNmJgFjBMK//gZxEREotn4dAf1DwNgIoPhoyuF5iHZ2w/jKXTkCSLWQQAYJ0ADSAGZQOq+zUUCK8DEzCegIXKtbD+5NmiD/d0NI5R8ChtvkyGC6/rkdjW6dQiffUSiQy5Xb5FAxJJABAuy/aQAzIJt/s1BAivAxMwlIBOLCwxFcvwEKz52DnPXrk4oeAXkVsPhV0j+/r3jnL4w9vgQ9GwzDqL6N4FvWi8xIgATSSYD9Nw1gOiWT/HIKSBE+ZiYBiUD0b78hYsh3KHX8GLLkzk0qBgTkbXLk83/dXr3EhqBReNhvCGoO6E5eJEACGSDA/psGMAOy4QigImjMTAIGBCL9R+PFmTPwCdxGNqkQEK+DT918iLtPYyDO/833dU+4liuLguPGkRkJkEAGCNAA2rkBXLFiBSZNmoSQkBAUKVIE/fv3x4ABA0yWStOmTfHHH38gLCzMaB4KyGSUvJAEUhCQTY1rn45A2fdRbtokze/9Z6pMosaMwfPjJ+CzPcjULLyOBEhAjwD7bzs2gKtXr0bnzp3Rt29fNG7cGGfPnsWECRMwfvx4DB06NM0HYdGiRejTpw8KFSpEA5gmLV5AAukjIL/WfHbvATYE+eOHCu3xV7kaPN7MRIzRv21DxJAhKHXsKLJ4epqYi5eRAAnIBGgA7dQAJiYmonjx4qhSpQo2bNigU/zAgQOxbNkyREZGws3NLdUn4ebNm3j//ffh6emJ+Ph4GkB+Z5CAGQnoH29WJfIyRp9chq4NR+Ce22sjw+PN0oYttswJrlefC2fSRsUrSMAoARpAOzWA586dQ4UKFRAYGAjxGldOe/bsQcOGDREUFIQmTZoYFUVSUhLq1q2LokWLwsHBASIPXwHzG4QEzEPA8HizHpe2oU74OXRp5CedA+wA8HgzE1Fz6xwTQfEyEjBCgAbQTg3g0qVL0bNnT9y+fRuFCxfWNX1UVBS8vLwwffp0DBo0yOhDIT778ccfcfnyZekaGkB+d5CA+QgYbm487eBs3MmeG5MrdUp2Ex5vljbz8G++RVxYGIr9vD7ti3kFCZBAMgI0gCo1gOIV7uPHj6VXsCKdOHECx48fR+3ataWRvbTSlClTpHl+L168gKurq+7y2NhYuLi4YPTo0fD3909RzJUrV/DBBx9g48aN+Pjjj9GtWzeTDKAwmu7u7rrynJ2dIX6YSIAEkhPQP97MOf4VNgX6YUG55ggsUSPZhTzeLG3lPFy7FncmTsLbp07CUe97Lu2cvIIEtEdA9P/iR07CAHp7eyM6OjpZ/60lMg5J4p2nipJ4fStez967d08yfGLV7qeffopcuXJJDbVp0ya0aNHijRGLhR5+fn4pDGBcXByyZcsGYRCHDEl+4oCY61e9enWUKVMGy5cvl8o31QAaBiPMpTCZTCRAAskJ6I8AlrsXjClHF+CLut8gxCP5ZsYcAUxbOTFXr+Jm8xYosnIF3CpXTjsDryABDRMQfXJAQEAKAjSAKhJFzZo1kS9fPnTt2hVLlizBrl27pFe2YjXvtGnTsGbNGvz+++9vjHjevHno168fIiIipFe+chKmUpQtXhF37558A9WJEydixowZUtnCbIok7rl//35cvXpVMo7iRz/JQ8gcAVSRgBiKqgnoH2/W7sputLx+CG2bBiDJwVGKm3MATW++pIQE/F21GvL07IG8ffuanpFXkoAGCXAEMGWjq24E0MPDA9evX0fevHlx584dycA9ffpUWrUrnHqBAgXw8uXLN8r34MGDqFOnDrZv3w5fX1/dtYcOHZJGFcUoY/ny5ZOVIUYVt27dmmq5YgWxMIjGDKCW/4LQ4PcIq6yQgLwKeOyxRYh3cMLoaj115k/8g6uATQcc+vnn0hlxRRYvMj0TryQBEgDnAKpwDqCTkxMSEhJ08kzr/43p+NWrV9LiD7H/36pVq3SX9O7dWxpRvHXrVopsf/31Fx48eJDs92LfwDNnzmDz5s3SfoBiaxkaQH5zkIByAjsuhCF/x4+xtnR9bCxdTyrQy8OF+wCmE+39BQvx4KefUPrkCTg4OaUzNy8nAe0SoAG0UwMoJC1v5CxG7sRo4N69ezF37lzpFXL79u0RHh6Oixcvoly5cpK5M5ZMnQPIEUDtfomw5ukjIJ/+EX3hDxQd8SWeTJmLqCJvS8ebVS7uyZNA0ocTL06fxq3OXVB8y//g8s476czNy0lAuwRoAFVqAI8cOQJ5bYqYE2j4//ojhG+S78KFCzF16lSEhobCx8cHI0aMQMeOHaUsYqGHmAcoNoYWRo8GULtfBKy5ZQjIp39ERseg+fXD6HE5EP07/IDvW7wP37LJF4FYJiLbv0tiTAyuVqqM/MOHwbNDB9uvEGtAAhYiQAOoQgPo6Ph6MnhqSWzObKoBzGwdUUCZTZjl2wsB/dM/RJ2+P7UCHrHPMLRmP6mKnPeX8ZYOadsOWQsXRqGpP2a8EOYkAY0RYP9tZQMojmTTX6Wbmv5WrlyJLl26qE6eFJDqmoQBqZCA4ekfSErCmh1jsKtoZawo04QrfxW22Z0pP+DJ9u0otX+fwpKYnQS0Q4D9t5UNoHgtu2/fPunYNWPp0qVL0nYuR48elc7kVVuigNTWIoxHjQQMT/8o+OweluyZjJHVeuJM/nd1IXPvv4y13tO9exHWrz9K7tuLrAULZqwQ5iIBjRFg/21lA5g9e3Zpu5fdu3fj7bff1slPbPsycuRIiP38hPGrWLEiTp06pTp5UkCqaxIGpEIC+qd/iPAa3jqFQec2ok2zMXiR9d+Tenj6R8YaL/7hQ1yrXgMFf/gBHp98nLFCmIsENEaA/beVDeDhw4elI9fEcW07d+7E+++/L23bIo5xk8/tFVuxiE2h1ZgoIDW2CmNSG4GjwffR8aeTurAGn/0ZPtHh6F/362ShcgQw4y13vWkzZK9SGV5GjrjMeKnMSQL2S4D9t5UNoJCWOHlDbNYsFna8++670pm/4rzer7/+GsOHD5c2gFZrooDU2jKMSy0ExOKP0b9eRtSTf8/g/Gn3JPye723Mf7+lFCZP/1DeWpEjR+LlhT9Q4tfUN7NXfheWQAL2Q4D9twoMoJCT2IS5YcOG0tFtlStXxoYNG1CkSBHVK40CUn0TMUArEjBc+StCyR3zBGt3jMGESp1wuFB5yfyJxFXAyhrq8f+2IHLECJQ+cRxOHh7KCmNuEtAAAfbfKjGAQmshISFo0KCBZAK3bNmCRo0aqV6CFJDqm4gBWolAipW//8TxUfgFfH96FTo2HomHrh48/cNM7fMqNBTXGzWG98IFyFG7tplKZTEkYL8E2H9b2ACWKFHijWoSiz/EcWzZsmVDQb3VbGLvP3E+sNoSBaS2FmE8aiFguPJXjqvvH1tQOeov9Gg0XPrVmp5VUKNUXrWEbbNxiI3zr9WqhVwtWyHf14Ntth4MnAQsRYD9t4UNoDiSTZi5jKT9+/dnJFum5qGAMhUvC7dhAoYrf+WqzNs3FVdze2PmB59Jv+LKX2WNLB+td/dpDIrNHgeHx49wc+RUHq2nDCtza4AA+28LG0B70xQFZG8tyvqYi4CxEUD32Of4ebs/pnzYHvu9P5RuxZW/GSeuf7SeKKVF8CF0+zMIbZqNQ5xTFr5ezzha5tQAAfbfFjaAYrXvJ598Im39ktrmz7akOwrIllqLsVqSgDwHMCo6Bkn/3Lh6xEWMPLUCnRv54UH2XCjg4YIjQ+vByTFjbwUsWR+13cvYAptSj25j1sGZGFyrP654FuMCG7U1GuNRFQH23xY2gGJhx6FDhxAXFydt+dKsWTPJDNaoUQNpnQGsKuX8EwwFpMZWYUxqISCbFBGPMIHy/L+e/8z/48rfjLVUagtsHBMTsClwJNa+0xCbStWVCucWOxljzFz2T4D9t4UNoJDU8+fPsWvXLgQFBUk/4jxgT09PNG7cWDKDYpQwd+7cNqE+CsgmmolBWpGA/mvKufum4loub/xctwv8PykD37JeVozMdm+d2gIbUaPxRxch3tER/tV6JasgX7Xbbnsz8swhwP7bCgbQsCnFRtDbtm2TzOCZM2fg5OSEqlWrSq+KmzZtivfeey9zWt8MpVJAZoDIIuyegBixOn3hJjzaN8Pzb/zwQc8OfO2roNVTW2Ajivzs771o+/c+tGk6BomOTrq7cLGNAuDMapcE2H+rwADqK+vu3bsIDAyUfsT5wM+ePZPmCoqRwVmzZqlOhBSQ6pqEAamUwJPduxE+4CuU3LcXWfW2eFJpuKoO600jgO88vIXph2ZjUK0BuOpZVFcPjgCqukkZnBUIsP9WmQHU10B8fDwOHDggmUExOnj16lUrSOTNt6SAVNckDEilBKLGT8Cz/ftRcs9ulUZoO2EZW2AjR++UmIANQaOwvnR9bCxdT/q1p1tWnBjeANmyONpOJRkpCWQyAfbfKjaAmdz2ZimeAjILRhaiAQI3mreAy3vvoeCE8RqobeZX0XCBjf4dxxxbDEckwa/657pfe3m4cN5l5jcL72BDBNh/q9QArly5EufPn4fYOFqcDdy6dWv8/fff+O9//4s5c+bA1dVVFTKjgFTRDAxC5QTiHz3CtWrV4TVpInK1aKHyaG0nPMN9AOXIP722Hx2v7EKbZmMR75hF+jXPXLaddmWkliHA/luFBnDMmDGYPXs2atWqhcOHD6NYsWIoUKAAevXqhRkzZqBixYqYMmWKZRSSxl0oIFU0A4NQOQHd/L+9e5C1UCGVR2tb4emfBOLpmg0DN5xH3rBgzDw4C9/U7Ic/8xTXVYhbwthW2zLazCXA/luFBlCcF7x27VppJfCpU6dQrVo1BAcHo3jx4tIooNgm5saNG5mrDBNLp4BMBMXLNE2A8/8s0/zy4hCxH+CGIH9sKlUH699ukOLmXBBimfbgXdRNgP23Cg2geL1779495MiRA4mJiciSJQsSEhKkM4RjYmKQJ08eaS9BNSQKSA2twBjUToDz/yzTQvrbw4w+vgTOCXEY/lHfFDfnljCWaQ/eRd0E2H+r0ACKff++/vpr9OzZU1LPgwcPJNMn0r59+9C3b19pJFANiQJSQyswBjUTSHj8GH+L+X8TJiBXS87/y8y20t8epmXwQXT9c7vuXGD9+3IEMDNbgWXbCgH23yo0gL/++ivatWuHd955BydOnEC2bNkkPY0fPx7Tp0/HiBEjJIOohkQBqaEVGIOaCTzdswdh/QfAZ88eZCvM+X+Z2Vb628OUeByOOQemY8hHX+BSXh/ptpwDmJn0WbatEWD/rUIDKER0+/ZtaSPorl27SieDiDRp0iRpQYgwh2pJFJBaWoJxqJVA1IQJeLZ3H0ru3aPWEO0qLnl7GIekRKwP8scWn5pY+04jrgK2q1ZmZcxBgP23Sg2gaNzo6Gh4eHiYo50zrQwKKNPQsmA7IXCjRUu4vPsuCk6cYCc1Un815O1heu1agByvXmBozS/BfQDV326M0LIE2H+r0ABGRESgbdu2OHbsGHLnzo2ffvoJLfT2DhMjgmJRiBoSBaSGVmAMaiUg7f9XvQbn/1mhgcTr4PMzFsBl6Xw82bADld/x4vnLVmgH3lK9BNh/q9AAtmnTBvfv38c333yDI0eOSGcAnzt3Dm+//bakJEdHR2l1sBoSBaSGVmAMaiXwZPt2hA/+GiUP7EfWAgXUGqbdxhVz9SpuNm+BIsuXwa1qVbutJytGAhkhwP5bhQYwf/78OHv2LAr9s2Fsnz59EB4ejm3btkltzBHAjEideUjA8gQiR/njxZkz8AkKtPzNeUckJSZKI7C52rdDvoEDSYQESECPAA2gCg2g2P/v5s2beOutt6SmEqOBJUuWxJYtW6Sj4TgCyGeYBGyDQHDDRshR+vJ8iQAAIABJREFUqxYKjPSzjYDtMMqwrwYi/v59FFu7xg5rxyqRQMYJ0ACq0AA2atQIRYoUwbRp0+Du7i617o8//oi5c+di7969KFWqFOcAZlzzzEkCFiHw6vZtXG/YCIXnzEbOBilPo7BIELwJHq5ZgzsTJ+Htkyfg6OZGIiRAAv8QoAFUoQG8cuUKPv74Y2kU8MyZM/jggw+QlJSE9u3b43//+x/i4+NpAPkIk4DKCTz4eQPuBATg+uLNyFsgLyoX9+QiBCu0WeyNG7jRtBmejf4BEe98gHw5XdgWVmgH3lJ9BGgAVWgAhUyE4fvzzz+lff/c9P5qPXTokGQKTdkIesWKFdLegSEhIdKIYv/+/TFgwIBUVShOHBkyZIg01/DZs2dSnk6dOuG7777TbUZtmJkCUt9DzYisT0BsQxL17bfwiL6PwbW/kgLiNiTWaZcdFyOQo9unOFSgLBaVa862sE4z8K4qJMD+W6UGUKlWVq9ejc6dO0vHxjVu3FhaVDJhwgTpNJGhQ4caLb5WrVqSuRw+fDjKlCmDw4cPY+bMmRg4cCBmzJhhNA8FpLSlmN+eCIitR+bsC8aM3VewbnsAgopVxcoyTaQqilMoRJrfqQJ8y3rZU7VVWxd5U+iBZzfg7Ue38EX9IWwL1bYWA7M0AfbfVjKAv//+OwIDA1G1alWIOX9yEvP85syZI43a5c2bFy1btsTYsWPTtSG02CKmePHiqFKlCjZs2KArWxi5ZcuWITIyMtmoorjg/Pnz0qvmJUuWoEePHro8HTp0kM4fjoqKogG09NPJ+9kUAWE2Rv96GVFPYiGOIZt7YDq+q9EXF98qqasHjyKzXJPKx8JFRsegdtg5DDuzBh0bj8RD19eb67MtLNcWvJM6CdAAWsEA+vv7Y9y4cZIihLkTZ/uKJIzfV199BQcHB2mhh5jrd+PGDckkiv0AxepfU5LYM7BChQqSwWzatKkuy549e9CwYUMEBQWhSZPXoxJy2r9/P0aOHImVK1eiRIkSut+LLWjWrVsHIRRjiQIypUV4jb0TkEeakv6paOtrB9Dpyk581nQs4pyypKj+ut5VUc0nj71jsWr9jl9/gPaLT0gxeMQ+w/rto/FjhXbYW6RisrjYFlZtJt7cigTYf1vYAB48eBB169aVtnUJCAiQRv/y5Mkjbezs5eUlbfmydOlS6QxgkSZOnAg/Pz+I+XxiPp4pSeTv2bOndJ5w4cKFdVnEKJ64x/Tp0zFo0KBUi3r16pU0B1CsOBbliFhmz55NA2gKfF6jOQL6I01y5cceWwwHJMGv+udGecxsVx7NyxfSHCtLVnjr+XAMXH9ed8vZ+6fjVs78+LFih2RhsC0s2Sq8l5oI0ABa2ACKUz62b9+Oq1ev6jZ6FoI4evQoatasiffeew8XL17UaUQsBhELQcScPJHPlDRlyhRpnt+LFy/g6uqqyxIbGwsXFxeMHj0aYhQytSS2nBGLQUQSo4HCCIoYjCVZQMJsylvWiOucnZ2lHyYSsHcC+iNNoq5ZE+KxIWgkVr/TCL+Uqmu0+hx1ynxVGLZLj8vbUD/0d3T0HQU4yDMyAbZF5rcF76AOAsIDiB85if7b29sb0dHRyfpvdURrmSgckoTLslASp3tUrFgRW7duTXZHsThDvIIVCzDEv/VTx44dIV7f3rlzx6QoRX4xamhoAOPi4qTVvMIgygbPWIHi1BGxAvnSpUvS/oMCz+XLl6VziQ2TbAANfy8MpjCaTCRg7wQMR5rK3b+OKUfmo3+dwbieK/koH+edWU4N8shsVHQMxBd8+bt/Y+KxRfii7tcI8SjIOYCWawreSSUERJ8s3jwaJhpACzWQMGCff/65NN9PP/n6+mL37t3SKJ/+ohBxjdi6ZeHChRCvZk1J8+bNQ79+/RARESG98pXTvXv3kC9fPukVc/fu3U0pSloJLFYHL1q0CL17907VAHIE0CScvMgOCRiONHX+cweahRxD+yajkeSQfN6uMIBcBWw5EchzM8UdsyTEYWPgSKx81xf/K1VHCoJtYbm24J2sT4AjgCnbwKIjgJ6entJCjJ9//lkXiRiZE7+PiYnBw4cPkTNnzmRRig2gd+7cKX1mShLzDMWRccJMCmMpJ7GHYO3atSEWiZQvXz5ZUYMHD5Y2mRabT4tFKHJ6/PixNPIn9hM0tn0M5xCY0iK8xp4JGI40zTgwE1FueTCpUvI5u9wH0DoqECYw4Lc/IVYDjz+6CIkODpjXZAD8PynD7Xis0yS8q0oIsP+28BzA+vXrQ5z0ERwcrJuft2PHDmm1buXKlXHixOtVa3ISjr1o0aJ49913IVbqmpLESKFY/CH2/1u1apUuixjB27VrF27dupWiGLHfn1gYIsyjGPGT0y+//IJPP/1UMqCGI5PiGgrIlBbhNfZOQB5pco99hrXbAzC9wmfYU6SSrtqDG5RC/3qleBKIlYQgTPqpmw8Rt3YF8m5aiVInTiCrq4uVouFtSUAdBNh/W9gACkMlFoIIMzVq1Ci8fPkSYqsVMfI2derUZKtzExIS8OWXX+Knn37C4sWLk+3Pl5Z8xCtbUa7Y+0+MBoqFHGKPwTVr1khHyol5fmKxSbly5aTFKGLVb+nSpaXXzMOGDZMWf/zxxx/SecTCmIrX0/ojg/L9KaC0WoKfa4WAMIE7Z67A54dXoIPvKDxycefpHypr/JgrV3CzRUsUWb4MblWrqiw6hkMCliXA/tvCBlA0r1joMXnyZJ2hEoss3n//fRw/flxapStS69atpdFAsWmzGMkzdQWwvnzEvEFhKkNDQ+Hj4yPtNygWlIi0fPlyaR6g2Bi6W7du0u/EyKR4zStGAcUCErE6qG3bttLiFP3VxPr3oIAs+8DybuomEDbkOzy6fAU3JsznmbMqbKqkxERcq1kLuVq1RL5vvlFhhAyJBCxHgP23FQygaF5x5NrmzZuleX3i9W6vXr2Snc6RJUsW6SQQ8XsxUigWj6gxUUBqbBXGZA0Ckrn4qCZytW6NfN98bY0QeE8TCIQP+Q6xwcEo8b/NJlzNS0jAfgmw/7aSAUxLUmJDaGEA1Z4oILW3EOOzFIGXFy8hpE0bFF21Etkr/Tv/z1L3531MIxD92zZEDBmCkgcPIGv+/KZl4lUkYIcE2H9b2ACOGTMmQzIS8+/Eq1i1JQpIbS3CeKxF4P78+Xjw0xKUPnEcDlmzWisM3jcNAvGPHuFa9RrwGjsGuT79lLxIQLME2H9b2AAaO89XXlxhbD9q8Zn4vfivWBSitkQBqa1FGI+1CIR06IgseTxROJVjE60VF++bnIBYEfxnq8/w0j0XEvwnoXJxT67Opkg0SYD9t4UNoOEWLI8ePZJWBTs5OUknZ1StWlWaCygWf4hNmMVJHOJ4uPXr1yNHjhyqEykFpLomYUBWIJAQHY2/q1VHAX9/5G77mRUi4C1NISDvCVj71Da0ubYfnzUdg3y53bgnoCnweI3dEWD/bWEDaKggschj27ZtuHDhAvIbmY8i5gKKrVq6dOkirRxWW6KA1NYijMcaBJ7s2IHwQYNRct9eZC1Y0Boh8J5pEJD3ahTHwvk8DsOcAzPwXY2+uPRWSSknTwWhhLRGgP23lQ3gW2+9JW0CvWLFilS1J46OCwoKQlhYmOr0SQGprkkYkBUIRHz/PV5euACfbduscHfeMi0C8mkt4jQQkRySErF6x1js9f4QS8t+zHOB0wLIz+2SAPtvKxtA8VpXGMANGzakKrB27drh119/lfbmU1uigNTWIozH0gTEHN3g2nXg3rQp8g8baunb834mEDA8r1lkGXz2Z5R+FIov6g/RlbCud1VU88ljQom8hARsnwD7bysbQHE276lTpyDO6a1kZOsIcRpH9erVpbN7jxw5ojrFUUCqaxIGZGECL/66glstWyJs+CTk+OgjLiqwMH9Tbrf1fDgGrj+f7NKPwi/g+9Or0LXRCNzN7il9NrNdeTQvX8iUInkNCdg8AfbfVjaAR48ehTgfWIwidOrUCTVr1pTmAt67dw8HDhyQFn+I1b/iKDb9M3rVojwKSC0twTisQUDMK/t9/DT4XtyNdk0CEOeUhce/WaMh0rinsRHA7HEvsSHIH/P+0wJBxatLJXAEUIWNx5AyjQD7bysbQNGyx44dk878FaN9+uftClNYuHBh6RxgcRycGhMFpMZWYUyWICAvKph2cCbuuebGhMpdpNs6/HNzLiqwRCuYdg95DmBUdAzEIhA5TT48D8+zumJs1e4o4OGCI0PrcUsY05DyKjsgwP5bBQZQ1tG5c+ek18EPHjxA9uzZpdW/derUkbaIUWuigNTaMowrMwnIhiLmzl2s3TEGP1Zoh71FKupuKUwgDUVmtkD6y5YNu8gpm8BPr+1Hxyu78FnTsZjdtTJ8y3qlv2DmIAEbJcD+W0UG0BY1RAHZYqsxZqUE5FeKjUNOYsD5TejQZDSeOLulKJavFJWSNm9+eR9AeTVw0SeRWLBvKg738kO5lr6cv2le3CxN5QTYf9MAKpIoBaQIHzPbKAF5UYH/iaVwi3uJ72r2M1oTLipQXwOL0dtTNx9i959R2HIuHFO3jMbp/O9i3vutOH9Tfc3FiDKRAPtvGkBF8qKAFOFjZhslIEYAu80/hJ+DRmHVu774pVQdozXhCKA6G1h/U+jPL25FzfA/0KXx94CDoxQw52+qs90YlXkJsP+mAVSkKApIET5mtlECYhSpf78Z+Gr/IvSq/x3Cc+ZLVhPOAVRvwxpuCl3u/nVMOTIfA2t/hb9zF+Gm0OptOkZmZgLsv2kAFUmKAlKEj5ltmMCpft8g+uRpfN5gaLKVpVwFrO5GNdwSxjExAeu2ByCoeDWsKNNEFzxHb9XdjoxOOQH23zSAilREASnCx8w2SiApMRHXatXGw+r1MDh3LciLCkR1vDxc4P9JGa4oVWnbGtsU+uvf16PU49vJTgXh/E2VNiDDMhsB9t80gIrERAEpwsfMNkpAnPsb0rYdiq5eBecKH0qLCu4+jUG+nC5cSaryNjW2KXS1iEsYdWo5ejYYiogcb0k14AigyhuS4SkmwP6bBlCRiCggRfiY2UYJ3J0xA4/XrUepo0fgkCWLjdZCm2Eb2xTaOT4WPwf5Swt6Npeqwz0ctSkNzdWa/TcNoCLRU0CK8DGzjRK48cl/4VLmXRScPNlGa6DtsI1tCj3qxDK4v3qOIbX6cxWwtuWhmdqz/6YBVCR2CkgRPma2QQKxN27gRtNmKDx3DnLWr2+DNWDIgoDhptANb53CoHMbEb5kExrVKENIJGD3BNh/0wAqEjkFpAgfM9sggfsLFuDBosUodewoHF1cbLAGDFkmIG8KLeZv5k98CY9OzeE1JgC5Pv2UkEjA7gmw/6YBVCRyCkgRPma2QQI3WrSEc4kSKDRtqg1Gz5DfRCCkUyc45cgJ7wXzCYoE7J4A+28aQEUip4AU4WNmGyPwKiQE132boNDMmXBv3MjGome4aRF4sHw57k2dhlLHj8EpR460LufnJGDTBNh/0wAqEjAFpAgfM9sYgfuLFuP+/PkoLV7/urraWPQMNy0CcZGRCK5bDwUnT4JH8+ZpXc7PScCmCbD/pgFUJGAKSBE+ZrYxAjdbf4qs3t4oPGO6jUXOcE0lENK+A5w8PPga2FRgvM5mCbD/pgFUJF4KSBE+ZrYhAq9u38b1ho1QaPo0uDf598gwG6oCQzWBwMOVq3Dnhx9Q+shhyQgykYC9EmD/TQOoSNsUkCJ8zGxDBB4sWYJ7s2a/fv3r5mZDkTNUUwjIK4If3ApDiX7t8XzgMERUrc/TXUyBx2tskgD7bxpARcKlgBThY2YbInDzs7bImj8fCs+ebUNRM1RTCBjuCTjl8DzEOGXFqOq9pew839kUirzG1giw/6YBVKRZCkgRPma2EQJx4eEIrt8ABX/4AR6ffGwjUTNMUwjIp4Ik6V3c7MZR9L24FR2a+ONpNjc4/PPZ/E4V4FvWy5RieQ0JqJ4A+287N4ArVqzApEmTEBISgiJFiqB///4YMGBAqsKMiYnB6NGjsX79ekRGRiJv3rxo3bq1VEb27NlT5KOAVP+MM0AzEHiwdBnuzZghbf7M7UHMAFQlRcjnAkdGxySLKFfMU6zeMQazy3+KncWqSJ8JE1jAwwVHhtaDk6NsCVVSEYZBAhkgwP7bjg3g6tWr0blzZ/Tt2xeNGzfG2bNnMWHCBIwfPx5Dhw41Kpf27dtj8+bNGD58ON5//32cOnUKU6dORatWrSRTaJgooAw8dcxicwRutGqFbIUKo/DsWTYXOwNOncDx6w/QfvEJoxdMPLIAiQ6O+L7G58k+X9e7Kqr55CFWErB5Auy/7dQAJiYmonjx4qhSpQo2bNigE+rAgQOxbNkyaXTPzWAie2hoKIoVK4YxY8bAz89Pl0f8W5jGK1eu4O23304megrI5r8DWIE0CMRev44bzT5GoVkz4d6Imz/bk2C2ng/HwPXnjVapyc3j6PfH/9DRdxSinf/dFHpmu/JoXr6QPWFgXTRKgP23nRrAc+fOoUKFCggMDETTpk118t6zZw8aNmyIoKAgNDHYyuLXX39F8+bNcfr0aVSsWFGXR5Tx8ccfY9OmTdLrYP1EAWn0m0ND1b47YwYerVmLUkcOw9HZWUM1t/+qvmkE0CP2GdbsGIN5/2mBoOLVdTA4Amj/utBKDdl/26kBXLp0KXr27Inbt2+jcOHCOj1HRUXBy8sL06dPx6BBg5LpXHx26dIlVK9ePdl8v5EjR2LcuHE4efIkKleuTAOolW8H1hNJSUnS3n/Zq1ZBwXHjSMTOCMhzAKOiY6C/CESu5phji5E9Phbf1urPOYB21vasDkADaKcGcMqUKdI8vxcvXsBV78iq2NhYuLi4SAs9/P3903wG1qxZgx49ekijiUePHoWjo6NRAyiMpru7u+4zZ2dniB8mErBlAi/OncOt9h1QZPlyuFV9vRiAyb4IyKuARa0MTWDtsHMYdmYNejQchii3vOAqYPtqe63VRvT/4kdOwgB6e3sjOjo6Wf+tJS4OSeLPfDtLYs6emLtnaADj4uKQLVs2CIM4ZMiQVGstVg2LEcKtW7eifPny0n/FKmLDJP8FYfh7YS6FyWQiAVsmEDVmLJ7u3YuS+/fBweCPH1uuF2NPTsBwH0D5U+f4V1i7IwC73quPD0Z+yy1gKBybJiD65ICAgBR1oAG06WZNGfy8efPQr18/RERESK985XTv3j3ky5cP4hVx9+7djdZ6xowZGDFiBBwcHKT/fvfdd8iaNavRa2UDyBFAOxMQq4OkuDhcq1UbHi1bIv93qf+xRFT2QUA+CeTu0xjkdXOW9n25/ywWRZdMQ44rF+Gza6f0nchEArZKgCOAKVvOLkcADx48iDp16mD79u3w9fXV1frQoUOoXbs2xCIRMbJnmMT2L2LPP7FwZMGCBdLw8JsS5xDY6lcB406LwNN9+xH25Zd4OmsZIvN580iwtIDZ6efPT5xEaLduKLp2LbJX+MBOa8lqaZEA+287nQP46tUrafGH2P9v1apVOm337t0bu3btwq1bt1LoPTg4WNrmpW3bthBz/0z5a5cC0uLXhn3XWR4Jev7d14iLCMcXtQfrKswjwey77Y3VLj4+AVfr1sOT9ysDg4ehcnFPbgStPRnYZY3Zf9upARRqXbRoEfr06QOx958YDdy7dy/mzp0rmTux4XN4eDguXryIcuXKoVChQtKGz99++620T2CBAgVSCF6+Tv8DCsguvxc0Wyl5LtiLu/ewesdYLC77X/zq85GOh/wCcG6HD5DbzRnidWG+nC40BXaqGFkPjY5vRrObx6U9AfN65oT/J2U4H9BO21xL1WL/bccGUAh54cKFkrETmzz7+PhIc/o6duwoaXz58uXSPEBh+Lp16yYdEycMYmpJvo4GUEtfEdqpq/6ZsC2CD6HHn4FShy/OgjVM4iSwRL2lYxwZtD+d6Ouh8NO7WLx3CiZW7ITDhV9PneGKYPtrc63ViAbQzg1gZguaAspswizfEgSSnQmblIR5+6ciLEc+TKjcxaTbyyODNAUm4VL9RcbOCP7x0BzEOmWTjobjucCqb0IGaAIB9t80gCbIJPVLKCBF+JhZJQT0T4Qo9eg2Zh2ciZHVeuJM/ndNjpCmwGRUqr/Q2AkhDW6dxjfnfka3hsNxx+31WcA8FUT1TckA30CA/TcNoKIHhAJShI+ZVUJA/0zYLy9sRrXIS+ja2A+JDsk3PjclXJoCUyip+xpjZwQ7x8dizY6x2FriI6wq83pnhf51fVAqf07OA1V3czK6VAiw/6YBVPRwUECK8DGzSgjIIz6ikxeLPwKLV8fy9/49Qzs9Yc5sVx7NyxdKTxZeqzICqZ0R3P/8L6gS9Se6NhqBREenZFFzHqjKGpHhpEmA/TcNYJoiedMFFJAifMysEgLynK9yfxzCwHMbpaO/5Nd86Q2RI4DpJaa+61M7I7jk4zDMPjADo6r2wOkCZZIFznmg6mtHRvRmAuy/aQAVPSMUkCJ8zKwiAmLVZ2yvLoh2zoFR1XqlOzLOAUw3MlVnMHpGcFIS5hyYjjuuuTG2asqTlKgBVTcpgzMgwP6bBlDRQ0EBKcLHzCoi8PLiJYS0aYOZ9fpgh3spXWQ5nJ3wLDbhjZFy9EdFDWnGUIydEdzs5jF88ccWdGs4Avez5zJ6N44Cm7ERWFSmEWD/TQOoSFwUkCJ8zKwiAhF+fnh+9BiK79qF06HR0ibP4kzYbzZeQNSTmDdGyvlfKmpIM4ciXgfP2ReM6Xv+lkp2jYvB6p2vF4OsLNPE6N04D9TMjcDiMoUA+28aQEXCooAU4WNmlRB49TgawbXr4EHzdsjStZfuZI/UFgMYhr2mZxXUKJVXJbVhGOYkYGxPwL5/bEGt8PPo2sgPcU5ZUtyOI4DmbAGWlVkE2H/TACrSFgWkCB8zq4CAeM13ZMo8tD29GV0a++GRizvkEb3Y+EQMXH8+zSg54pMmIpu9wNgfAfLJIFM+7ID93hV0deMcQJttZk0Gzv6bBlCR8CkgRfiY2coEhPn7ctUZLNwzBddzFcKkSp2liOQ5fYMalML0PdfSjJIjPmkistkLjO0JKCoz/uhCuMa/wte1ByQzgDwNxmabWnOBs/+mAVQkegpIET5mtiIB+dWe99WzCDixFINrDcAVz6LJOvP87s6SHbzzJAZ6R/9yxMeK7WbpW6c2DaBq5CX4n1yOr2oPxLXc3sjjlg3jW5aFb1kvS4fI+5FAhgiw/6YBzJBw5EwUkCJ8zGxFAkeD76PjTycx8cgCOCfEJRvJ0Q9rcIPSmPHPAgB9E8iVv1ZsPAveOrU9AR2TErF010RczFsCy2p1wYnhDZAtS/pPjrFgVXgrEkhGgP03DaCiR4ICUoSPma1EQLz6HfbLReSOuoV5+6dhYsVOOFS4vNFoxPw+5yyOCPjtT0RG/7samCt/rdR4Vrit0T0BAbQKPojulwMRtWDd/9s7E/AoivSNv7kTcpEACfcNCoKEqLCCiiAIeOMBIvoXRFcQFFg88OJcFA9EWWBFReTwAHRFXGBFQEFQLgPIoYDcBhKIkJBA7sz/+VomTJKZdPd0z2SOt58nTiRV1VW/+qbr7a+qvkKPLldWQc14SxJwngDHbwpA560HAA3IED5mrgIC1sFcvHmjUhYh6fQBDOrxfIWjvaxVs67vE0/QlsNnlPAwCdHhpTuFq6AJvGUVELAXE7BJhAUzvhqPWg/cj4Snn66CWvGWJOA8AY7fFIDOWw8FoCF2zOx+ArYhParnZWP+qn9ifqte+LxF1wqV4Y5O9/ePp9/R3ktAxtQ3kbloMZp//x2CoqI8vQmsHwmUEqAApAA09HWgARnCx8xuJmC7oP/hvStxx6ENePjmF5ETWs2uAOSOTjd3kBferjA9Hb/f1B0Jo0ejxqCBXtgCVtlfCXD8pgA0ZPs0IEP4mNnNBKwhPaoV5mL+N5OxsnFHzGlze4VaVK8Wgil3t+WOTjf3j7fe7sRzY3B+yxY0X/UNAkJCvLUZrLefEeD4TQFoyORpQIbwMbObCVg9gH33r8GDv61SvH8S+Ln8xZM93NwxXn67vH37cPjOu1Bnyquoftddpa3hulEv71gfrz7HbwpAQyZOAzKEj5lNJKBlsJU03Sb/D1OWvIyNda/EjKR7ytSA6/5M7BA/K+r40CdQcOQImv73awQEBcHephHuHPczo/Dw5nL8pgA0ZKI0IEP4mNkkAnoG241vzELsnBl4rMcYnIysUVoDxvUzqTP8tJjcXbtw5L6+qDv1TfzUKBlDF6ZUCB5OG/NT4/DQZnP8pgA0ZJo0IEP4mNkEArZhXWyLszfYlhQU4GDPXshsfgWeanoX4/qZwJ9FXCJw7LG/o/DECTzUeQROnCuwi4ZeZlqMpxDg+E0BaMgWaUCG8DGzQQK2YV3sFVV+sP3z40+QPnkyjr7xPmJatlQO/c3IyWdcP4P94O/ZrcsPzv2cgoZjn8Lkax7ChnrtKsXCdab+bjVV336O3xSAhqyQBmQIHzMbJODonNbyxUow53OZ2Yh5tB9+rtEcb179gJKEa7IMdgCzV1jrN3njbFTPz8HwrqNgCXB8NFz1iBBMuYc7zWlCVUeA4zcFoCHrowEZwsfMBglYw7qoFfNI58Y4O28+Bu/5Lx676VmcjKqpZOGaLDVy/HtlBOwtP7jiz8N484eZlR4vaC1T7I+xJmljVUWA4zcFoCHbowEZwsfMBglo9QDWCbXgraXjsanOFXinfd8yd+WaLIOd4KfZK1t+MP6nOaifcxqP3/QMigODHBKi7fmp8XhIszl+UwAaMkUakCF8zGyQgHUQTsvKq7Dj0urhk6DOPXb8Dw/+ugqP9ngOp6rF272r9cxfg1Vidj8hUNnLR+OsE5j53TTMbNcHK5p0UiVC21NFxAQuIMDxmwLQkFnRgAzhY2YTCFin4aQoi0154l2R/698OHoMAAAgAElEQVRdkosZKyZjTYOr8O92fRze8Z37k3BnUj0TasQi/IGA2vKDp7d9gvanD+CRHs8jPzi0UiS0PX+wGM9rI8dvCkBDVkkDMoSPmU0iYC8OoHj+Mi8UYujO/+Cm4ykY3GMMssKiHN6RXhiTOsNPilFbflD7/J94b/XrWNjqZixueVOlVGh7fmI0HtZMjt8UgIZMkgZkCB8zm0jA9iSQmpFhGL1kJ4JSj2H22jfxUeve+LxFV7t34zosEzvBj4pSW34gKIb8shQ9jm3F4O5jkBkeXYEObc+PDMYDm8rxmwLQkFnSgAzhY2YXEbB6Z8ZumoumWSfwWPdnURgU4lAAciemizrCx4t1FITc2uyogguY8+0U/Fi3jd3NR5KOtufjRuLBzeP4TQFoyDxpQIbwMbOLCMj6rDn/+hyvbXwXU64egHX129u9k0wTT7mbsdhc1A1+UayIwPHL9iDtXL7d9t52aCOG/rIUo24cgf3V65emYQxKvzAPj24kx28fF4Dz5s3DlClTcOTIETRs2BDDhw/Hk08+qckon3/+efzwww/YsGGDw/Q0IE0omcjNBDb+lobsh+5HTkgEnr5+GBBgjfhXtiI8jcHNHeOjt5Pp4Blrf8e01fsrtDCopBgzvnsLtevWQt7Uf+MUT57xUSvwvmZx/PZhAbhw4UI89NBDGDJkCHr27ImUlBS88sormDx5Mp577rlKrXX37t3o2rUrLrvsMgpA7/te+3WNxSOz6ZV3cG/KMjzZdRQOx9atwINrr/zaRFzWeHubkcTT92qjPCROfBp133wTsbfd6rL7s2AS0EOAAtBHBWBJSQmaNGmCjh07YvHixaU2MWLECMydOxcnT55EZGRkBVv59NNPMXHiRPz222/K3zp37kwBqOcbxbRVSkAG4JffW4vZa17HN406YvaVd9oVf/KPXHtVpV3lsze33YyUEB2ODk3iERQYgD+eGoELKSlotvy/CIqN9dn2s2HeQ4AC0EcF4Pbt25GcnIzly5fjlltuKbXI1atXo0ePHlixYgV69+5dwVJ//PFHrF+/Xvn39957D3Xr1qUA9J7vs8/W1NGgattg667MR76djdZ/HlE2flwIiajAhGuvfNZMPLphhenpOHTLrYi59VbUmTjBo+vKyvkHAQpAHxWAH374IQYPHozjx4+jfv1LC4/T0tJQp04dTJs2DSNHjqzUym+88UYUFRVRAPrHs8DjWmkVfd/uTcPSHSdw5nxBaR3tiTjZ+fv2xDkYv3kuXrvqAXzfINlum7juz+O62m8qdOaTT5A+cRIafbwQ1a66qtJ2a3np8RtwbKhLCFAA+qgAfP3115V1fhcuXEBExCUvSH5+PsLDwzF+/HiMGzfONAEoQjMmJqa0vLCwMMgPLxJwhoC9tVS25Vi3dNhO43694TfEDX8YB2PrYtzfBjvc+MFTF5zpEeYxg4ClpARH+z+A4pwcNPnyPwgMtX9CiKO1hONub41ebeqYURWW4YcEZPyXH+slArBBgwbIysoqM377E5oAi8Vie4KUT7RdNnq89NJLFQRgYWEhQkNDIQLxmWeeMU0Ali9IxKWITF4koJeAWmw12/LiI0Ow6fnuCA0OxM5h/0Dhuu8w5KankRFR3eFteeqC3h5hejMJ5O3bj8P33osagwYh4R+jUN7Td/Z8AYZ9klLhbGt7Lz1m1otl+T4BGZMnTKi4/IAC0Mf6ftasWRg2bBhOnDihTPlar9OnTyMhIQEyRTxo0CDTBCA9gD5mQFXUHOs6vpNZeZprEB8ZircanUfiK89jbqcHsCQhucLgKYVx569mpEzoYgIZ787G6enTcXLSO3hxfwBs7T0wAChx4JKgDbu4Y3y8eHoAK3awT3oA161bB1nDt3LlSvTq1au01bLBo0uXLpBNIklJSaYJQH9+g/DxZ4Zbm6d2vqq9ykQXnMestVOBxk2RPWEqhn26XUlmO4bSe+LWbuTNVAhYioqw8+5+yEg9hWFdRyE/WN9yGXqxaWJmEOAaQB9dA1hQUKBs/pD4fwsWLCi1lcceewyrVq3C0aNHVe2Hm0BUETGByQTkBI8Rn+3QXqrFgpe3zEObjEN4ottohCQm4s6kOli282QZrwp3/mpHypSuJyCe7nte+BTjvp6CVQ2vwb/b3a3rplzHqgsXEzsgQAHoowJQ+lvCuDz++OOQ2H8i5tasWYOZM2fi448/Rv/+/ZGamopdu3ahbdu2qFevXgUToQDkc8PdBPR6AHsf/glP7fwCEzsMxE912yjVFW/fzAfaIy4yDKey82Abi83d7eH9SMAeAaudyzFxw375soz9aiH28q2tUDM6jLatBRbTOCRAAejDAlB6ffbs2Zg6dSqOHTuGZs2a4YUXXsCAAQMUg/joo4+UdYASGHrgwIEUgHxQVDkB6xrAtKw8u+v4bCvY8Fwa3ln3DtY0uBozku4p/RPXSVV5N7ICKgS+3J6KUYt2ABYLXtoyD1dmHMTwG0fhVGS8KrvyawTp3VZFxgT0ADq0AZ9cA+gui+cbhLtI+899rLuApcWOtudHFObh7XXTYQkIwIguI5AfXDGcBtdJ+Y/NeFNLxb5f+HIXzpwvVKodWZCLGd+/hcywaDxz/RMoCgzW1Ryub9WFi4ltCHD89nEPoKutnQbkasL+Wb69OGgBAYrDRPnPi1vnI/nUfjzVZQRSoxPsQuI6Kf+0HU9utaMQRy3PHsOb62dieZNOdo8vlDap7Q5OjAnD1L5JyMjJ59SwJxuBB9WN4zcFoCFzpAEZwsfMlRBwFB/tngPfYfCe5ZjU4WH8WLetwxLoAaR5eRIBtRBH1vWAb7Xvi28bdShT9XuT6+HzlFRdzbFODfdoXRtbDp/helhd9PwjMcdvCkBDlk4DMoSPmXUS+H7BV6j1yvNY3KIr5rW+dMa1bTFcA6gTKpO7hYDqBieLBU/t+Bzdj2/Ds9cNxW/xjZV6iT3HRoQgM/evKWOtl+QTh3n1aiHIvHApL9cMaiXo++k4flMAGrJyGpAhfMwMVDgJoUOTeATJfFe5K2/fPhx9YAAirr4aX94zEtPWHqyQhuuhaFKeSkBLiKPgkiK8unE26uZkKGtbM6o5PtHG2XbyO+IsOd/Lx/GbAtCQVdOADOHzmcx6D663pv92bxqW7jiBM+cLSlnI8W59kuqhe+vasIrBwvRTONKvH4Li49B4wQIERkaC56X6jPn4RUNUPYAXKcTmZ+Od76cjLzgUT18/DDmh1ZS/VI8IQVZuoerueC0w6SXXQsn303D8pgA0ZOU0IEP4fCKzXiFmL70jEDJdNb5bQ7R47TkUnzmLxosWISTx0qYPvcLTJ4CzEV5JQE+Io3rZpzD1hxk4Fp2IFzv9HYVBIXBmHaAaKK6TVSPk23/n+E0BaMjCaUCG8HlsZq3CytGuRkfTTI7SOwIRXlSAST+9j1Z5p9H8k4UIv+wyj2XGipGAGgEtIY6sZVx+5ihe3fgutiVcjtc6PIiigCC14nX/nTvldSPzqQwcvykADRk0DcgQPo/MXJlHz3ZHYc3IMIxeshNp5/LstqP8NJPaLsjyhch6qLGb5qLNn4fx1s3DMW/qo3bXBnokRFaKBBwQsPf9sm7UsG7csGbtkLYXL2/+COvrJWHqVfejJCCwTKmRoUE4X1DsNGt6AJ1G5xMZOX5TABoyZBqQIXwel7kyj569HYVaGmAdZLSugZIyRfyN2boQHdJ/xdi/DcaOhJbgYKWFNtN4AwF7HnZZDzvh671lzrCWvVCd/tiJMds+xpoGyXi7fV9YyolAZ9rrjjWAWmcRnKk/85hDgOM3BaAhS6IBGcLnUZn1eui0Vt46zaRlF6SUGVJciBe3zEfy6f34Z4eHsaV2a+VWnK7SSpzpvJWArWjKyM7HpOW/Kk3p8sd2PLPtE6xpeDXeaX9fBU+gvfY68iq6Yxew3nXB3tpf3l5vjt8UgIZsmAZkCJ9HZdbjodNTcT0ewLCifIzdPA+tzxzGpI4DkZJwac0fPYB6qDOttxMo/8LU9XgKRqd8hh/rtMEbVz2AwqDKj4z7eHBHZOcXVvAq2osDaKa3Tu+64KroJzPbWxX1N+ueHL8pAA3ZEg3IED6PyqzVQ6en0hLSZdPz3REaHKjE+7vutbVIy8qzG8oiNj8H4zfNQaNz6Rj3t0ewq1Zz5VbumK7S0yamJQF3ELD3Qtbx5B68sHUBdtdoikkdH0ZecJjDqlg95mpix0xvndosgid8l81srzvswJX34PhNAWjIvmhAhvDpyqz2INdVmJ3ErvIA2h5JNWPt75i2en+Fu9fJycCknz5ARFE+xl07GL9Xr18q/uSXfz+YjF5t6hhtIvOTgNcQcPTC1Pb07xi/eS5ORtbA+I6POAwWrcVjbra3TuszREvdXNFRZrfXFXV0Z5kcvykADdkbDcgQPtXMlQVMNvtIJzUPnWplHSRwdCSVNbkMaC9tW4DCyBhMuv7v2BcQXVqS2W10tg3MRwJVQcBR2JjGWScwftOHCCkpxsSOA7EvvlFp9eT7lhgThql9k5CRk4+E6PDSgOq2L5F6d/Frab/WWYSqWM/rDd5JLYzNTMPxmwLQkD3RgAzhqzSzWsBkZxdzV+ZJ1BOnzHDLLRb0Obgej+5djqgOHVBv2lsIiK3Og+sNg2UBvkTAUdgYnDmDl7fMQ/PMP/BWcj+sq99eWS7h6PzfO9rVwbKdJ8vsMtbCSY+3zpM9gJ5cNy394Io0HL8pAA3ZFQ3IED6HmbUGTNa7pkbL+hdJM37ZHqSdy3dN4wDIZo+R25fgxtQdWNGmO0Z88haCQ0Ncdj8WTALeTMBR2JjJS3ei77qF6H78Z3zdpBOWdLgbp03+2k7r2w59kv9akqF2qc0i6H1eqd1Pz9892Tuppx1mpuX4TQFoyJ5oQIbw2c2sNlVhL5OWt3Q96182/p6BAR9sNr9xgOKxkJAWtXIzFc/FhnrtGOPPJaRZqK8TUIThoT+R/58lSFjwLo5H1cKk5AH4I/rScYlGGcRHhuKVPm1gGwTedlq5fPmOZhGcnbEwWn9rfnoAK5Lk+E0BaOj7RQMyhM9uZq0PKtvMamtq1ERl+TdzrW/LelofWFKMvge+w4DfVuFwTB28cfUDOB6dqBShVn8992FaEvBHAptXb0bmmGeRkHsW77a9C9806gAEWGWX80Qqm1Yed3tru5uztMw0OF8j53J6snfSuRYZz8XxmwLQkBXRgAzhs5vZGfGl5gHUKir1xOyTyr98ayvUjA6DdUF5+jn7IV7qZ5/CyO2LIeebLm7ZDZ9c3gNFgZfimKnV33zKLJEEfIuAPDeeXbgZQ3Z9hV5Ht2B7rRaYnnQv0iJruKShah49V0ctcKZRnuqddKYtZuTh+E0BaMiOfNmAquoBplWsScfZO293y+EzOJWdV2b3n1ZRaRs7rLKYffbW8th7uIYVFeD+/Wtwz4HvcbpadUxNvh97azQptbmqXBNkyPCZmQQ8jIDtcyM5fR+e2vE5YgtyML9VL3zV9DqUBAaZXmOtzx/Tb2ygQE/0ThpojqGsvjx+awUTYLFYZOMULycI+KoBVeVDQm2qwtpN5d/AK6tzbEQo+r+/SbWHbT1xzrwtl9YhMxcd0/ZiyK6lqJF3DotbdFM8fwVBlzZ6qHkQVCvLBCRAAqUEyj83wovy8fDelbjj0EYci07A+23vKHOyju1zJCYiGFm5RU7TlOdGVm6BplNHbG9SVS/ZVXVfpwG7KKOvjt96cFEA6qFVLq0vGpCezRKuepBoCcdiGyNPbdfwiJuaY9HWP+BoitaRJ84ZIXzu5+1YPepltDp1ECm1WmJmuz44EVWrgpUxxp+BLx6zkoAdAvaeG7Lp6u+7vkLbPw9jc2IrfNDm9tJNItaXsJHdW2Da6gNOM32kc2PM3Xikwgk/lb3kOfNscbqCzGiXgC+O33q7mgJQLzGb9L5mQHo2S3y7N033G68e1PYekHK0Wp+keujeunaZ4K4yXXsyK6/S4qtHhCAzt7A0VpgjT2L5QrSK3PwDB3B6+r+Q/e23yiaPua1vwdbEyx0uRJezSju3qKkHCdOSAAmoELArrGLCMCTgKJp8MRfxOWfwff32+PSy7sitXU95nnS7PBGjl+x0+IKoBl12Cp85X2A3WWXLRcpPvXFWQI20uX/3tfHbGToUgM5Qu5jH1wxI6/q7Ud1b4u3V+3W98TqDWYv40lpn6/2jwoKRk39pusf2qDZ76wfV6p27Ywcy3nsfOWvXIrhuHRy/6yE8mloTJQGBlWblzl81svw7CThHwNFzozA3D7+8Nx/4ZB7Cz53F9/XaY1HLbjgWUxvVq4Ug80LFF8TKaiCCLS4yBGfOF6pW1Lq8RM9LdlCg8V3MqhXz4wS+Nn4705UUgM5Q81EBqHWzhNWbZg+dOzY22D7gD6TnYMZ3v+vqxbhqIbi7/SVPol5vpqWwENlrv8PZBQtwYds2hDZtihqPPorY227FpuPZutcb6qo8E5MACThNQDyET83bjB5Ht6DfgbWolZulLNVY2ux6bEu8DLGRYYoQtF6OhKFVmsn075yNR1TrY33h0/rCysgAqkgNJ6AA5C5gQ0bkawak9eGkBZqrHmBqR8RpqZukkQf4vx9MVpIPXZiiyZtZmJ6OzCWfI3PxYhSdOoWIpCTEPzII0d27IyDwL4+f2iYWdwhkrQyYjgT8iUB571twSRGuS/1FOZKxZeYfSI2siR8v64TuIwbhdFh0aSSByl4Q9W4w0/qS7UkzBFpmYrzRjnxt/HamD+gBdIaaj3oAtYiX2Itr6dSwqT3AnHmoqG32UKuT7d+th8aLFEw7Z3/9oKRpElGCz1vnI3v5clzYvBkBERGIvf12xPW/H+GXX273ls7sINZTd6YlARLQT8DhC67FglZnjuL2wxvR6cQuhKIEUZ07o/rdfRDVrRsCw8KUFzt7S0S0PDNrx4Zjw3PdIFO6Wl+yXfUCrZeaL29WoQCkB1Dv96FMencbkDOiSW8D1Xbg3ptcD5+npKoWW9kDzJmHitraGdUK6UgQXXAeV6f/hk4ndqND+q8IsRQjsmNHxN5+G6JvvhlB0dGqpTnTRtVCmYAESMBpAlq8b9UKczGr7hk03vodZH1vYLVqiOxyg+Llj+rSBUFRURXur+eFT69gdLqxJmTUExHChNu5vQh3j99ub6CGG9IDqAGSoyTuNCCjgkKPeFSbZpUTlhxFj6xsilPqMGPt75i2en8FpGo74LS+OTvVnRYLGmWnKaJP4ve1/vMIgmDB/ur1sa5eEm4a9iBu7dZOd9F6mOsunBlIgAR0EdD6DLG+vOYfPozsb1YpO/vz9uxBQEgIqnW6FlGdr0Nk507K2t8SCxTPoEwTL91xosxuYEehnvQIRl0NNDGx2gu3Lyxlcef4bWLXmFoUBaABnO4yIKNvYpWJR0eHnFcm1hwhU4t7NX7ZHqSdy3dIvLKHipa3d81dabGgYXY6rsw4qPy0zTiI6gXnkRcUgh21WmBz7dbYktgKZyJilSI9ZTpGc/uYkARIoAIBI963wtRUZK9Zg+w1a5GbkgLZCFYUXxOb4pphc2xj/BrfWFlDGB8VWiFUlb2uMPpC7+ru1SuWXV0fV5TvrvHbFXU3q0wKQAMk3WFARt/EKhOPEofKusvNisE2LIqW+Hq2+NTeeLUeOWM9YzchOrw03p/WB5K1PtZD3OX/4/LOoeXZ42iR+QdaZB7HZWePI7bgPIoCg3CoRiOkxDXBzprNlId4fnBoaZN84S3XgHkzKwn4HAEzvG8lublY//kqbFi0Eu1P7UfTcycVTlmh1bAvrhF+jW+EXvd1x3W9OyE4Lq7S9YPOhJ5yplP0zkZofeFWW+vtTF3dlccd47e72uLsfXxaAM6bNw9TpkzBkSNH0LBhQwwfPhxPPvlkpazefPNNzJo1CydPnkTLli0xZswY9O/f324edxiQVuFjz0ulJh4rA6F1rZ+1DAnSvOn57ggNLhv/zkgdpOzygjQtK6/Cjl1rHSILctEgJx0Nz6UrHr4OgecQcfwQauadu/iAjsT+uAY4UL0+dtdoiiFP3AlLeISyC1guW4GqNiXt7BeO+UiABKqWgFHvW/lnmjx3Ljt7DK3OHEGrs0dx+ZljiCz6a2NZUXwN7I1IxG/VEnEoti7+iEpAcd36GHN3e/RqU8d0EPaEnt4wV1IpI+OO6Y1yUYHuGL9dVHXTivVZAbhw4UI89NBDGDJkCHr27ImUlBS88sormDx5Mp577jm7AOVv48aNU/5+zTXXYM2aNZgxYwY+++wz9OvXr0IeVxmQM3Hu7L2Jaf0Sm2VN9kSo0TrYCjEUF2PsnO+RcOEMEi+cRaLNZ/2c08q5u3KVyM7eyHjEXNYCxY2aYsHZatgSmojTEdWVkznKeyqNDghm8WM5JEAC7iGgxSPmKI3aMy3AUoJ6ORkY3tCCXzemoEnWCTQ5dxIJuZmljTsTFo1qTRsjsXULhDZqjNCGDRCcmIiQOnUQXKsWAoKCdIOw9xwrP8NjLdT6XJ35QHvERYbhVHZeadgb2a1sZLpcd8WrKIOrxu8qao5Tt/VJAVhSUoImTZqgY8eOWLx4cSmYESNGYO7cuYp3LzIysgywrKws1K9fH0OHDsXrr79e+rc777wTu3fvxsGDB90iANU2YDjqZXvTplrd+E5Zjp1M9kSoah0sFlQrykdUwQXE52ejen424vKyEZefjfiLn/JvtQpyUCsvCyi6dIqHPERPVYtDerU4pEbWwrGYRByLTkRqVC0UBIWUrt0z8rA3iw3LIQES8B4Clb0U5haWYNSiHaqNKR8wX55x9XJOo+75DEUgNs8/gxsi81B49ChKcnIulRcUpIjAkNq1EVy7NkISExEUH4/gGvHKZ1BcHILls0YNBEZGIiAgAM6GyJLDRmQji/Wyd8a6/M0XZ0coAH00DMz27duRnJyM5cuX45Zbbik17tWrV6NHjx5YsWIFevfuXeYL/OWXX+Luu+/Gnj170Lp169K/ffDBB3jsscewd+9etGrVqkwesw3I7C+x1iClqk+y8gksFoSWFCG8qADhxfkXPwswuWdzXB4XjJILF2DJzUXJhVwcSf0TX/10ANEFuYgqlJ8LiLL9vTAPQZaSMncoRgCywqJwNjwaIvLk82xYDG6/ORmXJbUEEuug+8f7kOZgPwnX7unuUWYgARK4SEBt3XRkWBDO5xebwkvOBO/UvAZKsrIggeYLT55EUVo6CtOsn2koSk9H8ZkzKM7KqnBP2ZkcGBeHo/mBOBcUhgvB4TgfEl76eT4kAheCw3Dh4r/lBYciPzBEWeucHxRi8xOqvDRbLh5hafUM6tndbAoQNxZi9vjtxqqbdiuf9AB++OGHGDx4MI4fP6549axXWloa6tSpg2nTpmHkyJFlII4dO1ZZL5iXl4fAi6c6SIJNmzbh2muvhQjEu+66y2UCsPy6kuRT+xRhFWgpUQTSpU+L8vtfP9bfLeXS/PW3W69IwMb9p5CbVwiZlgi6mN5aXkhJEUJKiiER8eX34JJi5dP678pncTGCLfJpm7YYgQ5X4l1CFBAWpsTRSi8IQFZwOLJDIpATUg05ofJZ9vfs0GqlYi87NNLuWbq2HkYzFnNr8Qya9k1jQSRAAh5PwOiaZWmgvIBqDZgvXsIp97TVtB6wqKAQ23YextmT6ahZlIsWYUXYs/cIvt+yH4HnL6BaUS4iC/OUn2pFZT/lhV3LVRAYXCoKCwNDUBgYpGyWQ3AwYqMjEBtTDTFREQgIDVHC4gQEX/xUfg/+69+Un2AgMAgBQYHKJwIDECCfQYF2Pv9KY01b9lP+FojITp0RFFV21k5LeypLQwHoox5AmcKVdXwXLlxAREREqQ3k5+cjPDwc48ePV9b62V5PPPEEvvjiC6Snp5f593379uHyyy/HRx99hIcfftiuABShGRMTU/q3sLAwyI+eq/y6ko+++ScSbdaMlC+rOCAQJQEB+OszUFn3pnwGWD8DlS9bbGQ4Tp0vLPPv1ryFgcH46yfor8+gYBQFBCmf8v/yxbf9tE2bHxQKeZtU3iiDQvGPO5NwfdsGykkZgdUiERgRXrqOxVXBpY2s3TOSV0+/Mi0JkID3EFBb36fWEuvaupHdW2Da6gNqyZW/W4+lrGxTiL3nVVRYEHI0eiLlBV5EYVhxAUKLi5TP8OJChBYXKr+HyWdRAcJK5P8v/R5UUqI4BoIt4igoRqdGsagTGQxLUaESCgeF8lmk/K78FF36XdZsW0pKoHxK4Fjb/7/47ygpKU1TGaymK1cgrEkTTTwdJZLxX36slwjABg0aQJZ/2Y7fhm7iZZl90gMomzleeumlCgKwsLAQoaGhyhq/Z555pkxXyTTvsmXLKgjAAwcOKLuBZS3hfffdZ1cAlu9zEZciMvVc5dfKyXoRuWwFnVXwWd30WsqXjRlZuQUY88UuZOZeOuRcS17bNLLGMDUzV3Ow0/Llq8UilJAzjnb4qgWX1htKwWhcRb3smJ4ESMA7CKiuWVZpRo3IUEzu0wYSX7WyZ5ptMWrPN0fB891N1NVLa0rFolU0yuLEkmJYiosRFBPj1MYYW0YyJk+YMKECNgpAd1uSi+8nYVyGDRuGEydOKFO+1uv06dNISEiATBEPGjSoTC2effZZTJ8+XZkCtr22bt2KDh06YO3atejatatdAegKD6BZiKzTpht/z8CADzbrLrb8l17vtKlt+pqRYcrrbkZOfpkdZ1IpM6Z0tTRObYrH1Q85LXVkGhIggaohYNQDOK1vO/RJ/mvZkd413eWjKEh+teD5VUHJWwPj0wNY0Vp80gO4bt063HjjjVi5ciV69epV2ur169ejS5cukE0iSUlJZWhIzMCBAwfi119/VaZ8rdf8+fPxyCOPKJ7BGjVq2BWAZrxBqG27d/aLbv2yOlO+0Vh4eqdZ9aZ3honWB7y3PuScYcI8JEACfxFw5jlpy86eiMnHiY0AABXFSURBVNM6+2JvjbPW4Plq/Vc+HEz53b9q+W3/7s3Bn23bwTWAProGsKCgQNn8IfH/FixYUNrnMs27atUqHD16tIK9i8CTYNHiCZw0aVLp32+++WZl3YCIyvKX2Qak942xsi+tPU9WZV62yk4FcSZgqbPTrHo9jHoeXJJW6xSPrzzk9PJhehLwdwJqa5bt8als5kDr7Is1lJfMlIxeshNp58rORjnTL7ZT0rZLZc6eL8CwTyoGwNdyD195OTZ7/NbCztPS+KQHUCC/9957ePzxxyGx/8QbKEGdZ86ciY8//lg52SM1NRW7du1C27ZtUa9ePaVfXnjhBbzxxhvK+sErr7xSWff3+eefK9O/119/vcsFoNzA2TiA5SvnaGGx2lo8vevp7Bm0J0+z0gPoaY8g1ocEPI9AZUGVbY+ZlJqrzZRo8Soa8cg5oufodCZrer1jja8tj6EA9FEPoNXAZ8+ejalTp+LYsWNo1qyZIvAGDBig/Fl29co6QAkMLVO/ckkA6VdffRWST9YLXnHFFcrJIeJJtHe5yoCsXjB7MZi0PChsj0+zJ+hc7WXTK7JcXR/bvlN7GPvaQ87zhlbWiAS8g4BZx6pZX+ztHTnpKhJadhbLvaWNWjaZqIlcV7XDleW6avx2ZZ3NLttnPYBmg3KnACwvWPS47kd1b4Hh3VrAmfMfjTBz9vi6sOBATPh6L05mXZruKH9Um5F62cvrrg0nZteb5ZEACVQ9AWdfWO153LS80OttsZ7np9psjfXeesrUW9+qSk8B6OMeQFcbVlUZkNpmCWfX3znLS+9UgvU+o7q3xNur91cIKe2Ot001hs6yYD4SIAEScETAVjxmZOdj0vJfTYVldQDIeb5aLq2zNXJiSecWNbUU6TVpqmr89iRA9AAa6I2qNCBHb6Fqb3RmT3E6s3FF6pAYI4GyAxwudDa7nva62dk3eQMmw6wkQAIkoBDQuiHNHq6osGDk5F863cNZD53WOvjipriqHL895StAAWigJzzRgLS+0Zmxk0tNbNpDqzdSvhn1NNDFzEoCJEACLiGg9Vlte3O19d16K6q1Dr74HPbE8Vtv/xlNTwFogKAnGpA73+i0PjzsPcDyi0ow4rMdqvR98c1TtdFMQAIk4PMEtGxIk5mSqX2T7AbPNwOQljrUjg3Hhue6Qeu0shn1ckcZnjh+u6PdtvegADRA3BMNSGvMKTPe6LSKTSti27AEWsWjGfU00MXMSgIkQAIuI+AJG9I8oQ4uA1xJwZ44frubAwWgAeKeZkBajg4yc22dVhFni1jrySRm1tNAFzMrCZAACbiUgL0NafKy3CepHrq3ro0OTeJd7n3zx01xnjZ+u9TIHBROAWiAuicZkJbNGGbvrlWbPrCH1t5xR5LO9sgjs+tpoIuZlQRIgARcTqCy2K/ObvDQW2l/2xTnSeO33r4yKz0FoAGSnmJAWjdjuOJBokV42vMAWv/NH988DZgcs5IACfgoAbPDd/mboNNrFp4yfuutt5npKQAN0PQUA9I6FeuqWE5Gp575oDJghMxKAiTg9QTUXuL1Lonhi7W6SXjK+K1eU9eloAA0wNZTDEjrZgxX7qit7EghTukaMDJmJQES8HkCWl/itWyKM9uT6KvwPWX8rkq+FIAG6HuKAZn58DCAQ8nKN0+jBJmfBEjA3wiY9RJvtifRl/vBU8bvqmRMAWiAvqcYkNpmDL3TBwaQKFk5pWuUIPOTAAn4EwGzXuLNKscf2HvK+F2VrCkADdD3JAPy11hOBrqPWUmABEjAIwiY9RJvlifRI6C4uBKeNH67uKkOi6cANEDe0wyI068GOpNZSYAESKAKCZjxEk8PoPYO9LTxW3vNzUtJAWiApScaEKdfDXQos5IACZBAFRIw+hJvliexChG47daeOH67rfEXb0QBaIA4DcgAPGYlARIgARKoQMDoS7wZnkR/6BaO3wAFoAFLpwEZgMesJEACJEACLiFg1JPokkp5WKEcvykADZkkDcgQPmYmARIgARJwEQGjnkQXVctjiuX4TQFoyBhpQIbwMTMJkAAJkAAJVAkBjt8UgIYMjwZkCB8zkwAJkAAJkECVEOD4TQFoyPBoQIbwMTMJkAAJkAAJVAkBjt8UgIYMjwZkCB8zkwAJkAAJkECVEOD4TQFoyPBoQIbwMTMJkAAJkAAJVAkBjt8UgIYMjwZkCB8zkwAJkAAJkECVEOD4TQFoyPBoQIbwMTMJkAAJkAAJVAkBjt8UgIYMjwZkCB8zkwAJkAAJkECVEOD4TQFoyPBoQIbwMTMJkAAJkAAJVAkBjt8UgIYMjwZUFl9+fj5effVVPP/88wgLCzPElpkdEyBn91gHOZOzewi45y6057KcOX5TABr65tGA+IUyZEBOZqbdOQlOZzZy1gnMyeTk7CQ4ndnImeNVeZMJsFgsFp12xOQXCfALxS9UVXwZaHfuoU7O5OweAu65C+2Z4xUFoInfNX6h+IUy0Zw0F0W704zKUEJyNoRPc2Zy1ozKUEJy5nhFAWjoK1Q2c1ZWFqpXr47jx48jJibGxJK9syh5wDRo0IA8XNx95OxiwDYeftqz61nTnl3PWO5AzhUFoHy/MzMzERsb655O8LC7cArYQIf88ccfiuDhRQIkQAIkQAIk4H0ExIFTv35976u4CTWmADQAsaSkBCdOnEB0dDQCAgIMlMSsJEACJEACJEAC7iIg2x+ys7NRt25dBAYGuuu2HnUfCkCP6g5WhgRIgARIgARIgARcT4AC0PWMeQcSIAESIAESIAES8CgCFIAe1R2sDAmQAAmQAAmQAAm4ngAFoOsZ+/UdCgoKcM011yjrJDds2ODXLMxu/NmzZ5VTV5YtW4Y///xTWcvyf//3fxg7diyCgoLMvp1flTdv3jxMmTIFR44cQcOGDTF8+HA8+eSTfsXA1Y0tLi7G1KlTMWfOHIWz7MTs3bs33nzzTdSqVcvVt/fb8ocOHYp3330XhYWFCA4O9lsObDhPAqENuJjACy+8oBwP17lzZwpAE1nLAmZhunfvXrz88sto0qQJvv32W8yePRvPPvusIl54OUdg4cKFeOihhzBkyBD07NkTKSkpeOWVVzB58mQ899xzzhXKXBUIyMvLa6+9hqeeego33nijYsvyrGjbti02btzIjXUusJlVq1YpNi0XBaALAHtZkfQAelmHeVN1N2/erDzY4+PjFYFCD6B5vffDDz/ghhtuwIIFC/Dggw+WFiy/L1myBBkZGYrXlZc+ArKzX2y1Y8eOWLx4cWnmESNGYO7cuTh58iQiIyP1FcrUFQjk5uYiISEB/fr1wwcffFD6d/n9sccew//+979SoUJ85hCQeHcirmV24OjRoxSA5mD16lIoAL26+zy38vKAT0pKwv33349169ahqKiIAtDE7po+fTpElJw+fRo1a9YsLXnmzJnKdOW2bdtw1VVXmXhH/yhq+/btSE5OxvLly3HLLbeUNnr16tXo0aMHVqxYoUxT8jJG4JdffkG7du2Ul5V77723tLA9e/agTZs2yjTw6NGjjd2EucsQEK+2xLzr0qULJk6cSAFI+wAFII3AJQREnIjw27p1qzJwUgCai/nw4cM4ePAgbrrppjJTZfKQlynM9PR0xcPCSx+BDz/8EIMHD1YGStvgsGlpaahTpw6mTZuGkSNH6iuUqSsQEG+UvKSI2JYZAusl6wEfffRRLFq0CH379iU5kwh8+eWXyrIGEd7z58/HhAkTKABNYuvNxVAAenPveWjdv/vuO/Tq1QsyBSxeQJkGpgB0bWfJmkBZUP/MM8/gvvvuKzN96do7+1bpr7/+urLO78KFC4iIiChtXH5+PsLDwzF+/HiMGzfOtxrtIa0RL6t4A+Pi4rB7925OtZvULzJLcMUVVyh2O2zYMMWGKQBNguvlxVAAenkHelr1JbK6rDMZOHCg8qCRiwLQtb0kb/Uy7SvrAsUjKNNqMojy0k9ANnq89NJLFQSgLJgPDQ2FCEQR2bzMIyACRTaEiPe1UaNG+Oqrr3DllVeadwM/L+nuu++GRAxYu3atMltAAejnBmHTfApA2oJmAt9//z26du1aafpu3bopC+VlF19ISIiSVtZMScgH2YEWFhZW+u+ab+xnCbVwFrF37bXXKmLljTfeUEJoiHh5/PHHuXvSgL3MmjVL8ZLIEY8y5Wu9RKTIlLqIlEGDBhm4A7PaEvjss8/wxBNPKEdyyUvMpEmTEBUVRUgmEfj000+VJQ0yGyObm+SSHe2y21qm4eV5LJ5tXv5JgALQP/vdqVbLOijZnVfZJR6SX3/91WESrqFSR6+Fs2xQkLVo8oB/+OGH8dZbb5VZS6V+F6awR0DWrYrHeuXKlcoyBuu1fv16ZfG8bBKRZQ28jBOQkEUSakd2XIuwbt26tfFCWUIZAvKMeOeddxxSufPOO7F06VJS81MCFIB+2vGuavaOHTuQk5NTpngJoCseQPGuNG3aVAlYzMsYAZnOkeneMWPGKG/zvMwhIIHLZfOHxEqTEDvWS0KTiAdbwmfwMk5APH7iYZWd6hK/UqbXeZlPQDaLpaamlilYxLaENJKZBvFqt2rVyvwbs0SvIEAB6BXd5N2V5BpA8/tPRPV7772nbPaQaZzyV4cOHegRdBK7cJWpdNnJLra7Zs0aSHidjz/+GP3793eyVGazJfDFF18oGz4kYLmEgyl/NW/eHPLDy3wCXANoPlNvLZEC0Ft7zovqTQFofmfddtttSqw6R5fsxBbuvJwjINOTsqv62LFjaNasGeREmwEDBjhXGHNVICBx/irbTCM7Vq2byIjPXAIUgOby9ObSKAC9ufdYdxIgARIgARIgARJwggAFoBPQmIUESIAESIAESIAEvJkABaA39x7rTgIkQAIkQAIkQAJOEKAAdAIas5AACZAACZAACZCANxOgAPTm3mPdSYAESIAESIAESMAJAhSATkBjFhIgARIgARIgARLwZgIUgN7ce6w7Cfg4gZKSEiVcyMKFC5GRkYFDhw5BgtvKkYQvvvgi/vnPf+oicOTIEeVILAnpImVWdlnT6glJIgGj8/PzMXHixNKjt7RUUML2SPzB2rVrK6e68CIBEiABVxOgAHQ1YZZPAiTgNAHrucj16tWDHFslZ8WeOXMGM2bMwM033ww5Ek/P5UoBKMfEXXPNNfjll18UISci0Pbau3evcuqFHH32t7/9rczf5BxcEY7JycmQ03R4OoOeXmVaEiABZwhQADpDjXlIgATcQmD+/PnKWcdvvPEGnn76acP3dKUA7NGjh3KkmaMA3R999BEGDRqEyjyKt956q3JsotqZ24ZBsAASIAG/J0AB6PcmQAAk4LkErKJJpkdletXo5SoBuGHDBlx//fWK+HPkldQiACW/nPKyfv16pTxeJEACJOAqAhSAriLLckmABAwRkKPs1q1bV6YMWf8nIs7eGsCjR49i7Nixivfs3LlzaN26NYYOHYrBgwcjICBAKceRANy4caNy3Nu2bdsQERGhTDfLtKxMyWpZAyhrCleuXInTp08jKCjIbru1CEDx/sXFxaFPnz6YN2+eIX7MTAIkQAKVEaAApH2QAAl4JAFZ57ds2TJl3Vz37t1xxRVXKAJP1tiVF4D79u1TPGZnz55F7969UbduXfzwww+QdXe2Gz7sCcAff/xRKU+u22+/XRGA33zzDWJiYnDw4EFVAWixWJCQkKCs/1uxYoVDlloEoGSWtY1bt25VxGRwcLBH9g0rRQIk4P0EKAC9vw/ZAhLwWQJW0fT+++/j0UcfVdpp3Rhiuwu4U6dO+Pnnn5W/XXvttUo62UEs4u+zzz5TvHO9evWy6wFMSkrCnj17FMFo3Zxx8uRJiAdy//79qgJQNn9o8RRqFYDjx4/HhAkTkJKSgvbt2/ts37JhJEACVUuAArBq+fPuJEAClRDQIgBl16wIJRGIIhRtrwMHDqBly5Z4/PHH8e6771YQgCKyrrrqKmWjidzL9vr000/xwAMPqArAxYsXo1+/fsq9rSLVXpO0CsAPPvhAWe/4ySefoH///rQPEiABEnAJAQpAl2BloSRAAmYQ0CIARdjJWr/rrrtOEXPlr3/961+44YYbILH2yk8BW/POmTMHjzzySJmsst6wadOmqgJw1qxZGDZsGJYsWYJ7773XYbO1CsD//Oc/uOeee/D2229jxIgRZmBkGSRAAiRQgQAFII2CBEjAYwloEYCTJ0/GSy+9VGkbRBjKBo/yAtCa97///S8kBIvtderUKSQmJqoKQGsZ1mlmRxXRKgBXr14NCSkj08Cy5pEXCZAACbiCAAWgK6iyTBIgAVMIaBGA4ikbNWqUJo9ZeQE4bdo0/OMf/8DcuXMxcODAMnXeuXMnZH2g2i5gaxkyFXzfffcZ9gAuXbpU2QU8ffp0PPnkk6ZwZCEkQAIkUJ4ABSBtggRIwGMJaBGAa9euxU033aQIOBFytld6ejpGjx6Nbt26KVO85QWg1dtmbw3gzJkzlVAwagJQNpnIWj2ZTpa1hkY9gNY2yxrE+++/32P7hhUjARLwbgIUgN7df6w9Cfg0AS0CsKioCM2aNYNM2f7000+K104uOVpNhN2iRYsc7gKWvHI2sIRc2bx5M9q1a6fklXOHr776akhsQTUBuHv3brRt21b1bGKtU8ByvvHLL7+sTFnbW9Po0x3OxpEACbiNAAWg21DzRiRAAnoJaBGAUqZs8JATOCTgs6yfi4+PV07TOHToUJkdvvbiAErgaIn/J8e4ySkcEv/v66+/VkK7yLo+NQEo4Wbk7F8RgWvWrDHsAbzjjjsgsQlF0AYGBupFxvQkQAIkoIkABaAmTExEAiRQFQS0CkCpm4R0kU0TIvwkOLOEf5GwLEOGDFE9CUTiB8pJIFKGiEdr+BcRg2oCUO4tp42IpzEzM9Nh8GYtHkCrmJTA1xIGhhcJkAAJuIoABaCryLJcEiABvyEgU88SjFpOLhFvorPXqlWr0LNnTyWgdZcuXZwthvlIgARIQJUABaAqIiYgARIgAXUCMvUs5wDLlLKzl5xBnJWVpQhAXiRAAiTgSgIUgK6ky7JJgAT8hoCcOywbUORIOlkPqPeS84zlvGPxJsq5wrxIgARIwJUEKABdSZdlkwAJ+BUBCTmTmpqqnD+s9xo0aJCSpXwoG73lMD0JkAAJaCFAAaiFEtOQAAmQAAmQAAmQgA8RoAD0oc5kU0iABEiABEiABEhACwEKQC2UmIYESIAESIAESIAEfIgABaAPdSabQgIkQAIkQAIkQAJaCFAAaqHENCRAAiRAAiRAAiTgQwQoAH2oM9kUEiABEiABEiABEtBCgAJQCyWmIQESIAESIAESIAEfIkAB6EOdyaaQAAmQAAmQAAmQgBYCFIBaKDENCZAACZAACZAACfgQAQpAH+pMNoUESIAESIAESIAEtBCgANRCiWlIgARIgARIgARIwIcI/D8o3+cvTympHAAAAABJRU5ErkJggg==\" 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     "metadata": {},
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    }
   ],
   "source": [
    "### create model and parameters\n",
    "smodel = Model(dS23)\n",
    "\n",
    "params = smodel.make_params()\n",
    "params['a'] = Parameter(name='a', value=1.0, min=0.2, max=1.8)\n",
    "params['b'] = Parameter(name='b', value=0.0, min=-0.1, max=0.1, vary=False)\n",
    "params['g'] = Parameter(name='g', value=0.4, min=0.1, max=1.0)\n",
    "params['de'] = Parameter(name='de', value=0.0, min=-0.1, max=0.1)\n",
    "\n",
    "# calculate temp based on calibration above\n",
    "current = 0.5*2e-8\n",
    "volts = swp['vac_heat2d'][:n].mean()\n",
    "theta = power_to_theta(current*volts*1e12)\n",
    "temp = theta*ALPHA3_CLSD/K_B\n",
    "\n",
    "params['temp'] = Parameter(name='temp', value=temp, vary=False)\n",
    "\n",
    "sresult = smodel.fit(-1.0*results['epsilon'].values, params, \n",
    "                  fields = 1000*results['field'].values)\n",
    "\n",
    "N = 500\n",
    "sfit = sresult.best_fit\n",
    "resid = sresult.residual\n",
    "boot_params = np.zeros((500,len(sresult.values)))\n",
    "for k in range(500):\n",
    "    stest = sfit + np.random.choice(resid.flatten(), size=sfit.shape)\n",
    "    out = smodel.fit(stest, params, \n",
    "                      fields = 1000*results['field'].values)\n",
    "    boot_params[k] = [v for k, v in out.values.items()]\n",
    "    \n",
    "### print info for paper ###\n",
    "print('temp = {0:.1f} (mK, fixed)'.format(temp))\n",
    "\n",
    "peak_err = np.abs(np.percentile(boot_params[:,0], [2.5,97.5]) - sresult.values['a']).mean()\n",
    "print('peak height = {0:.3f} +/- {1:.3f}'.format(sresult.values['a'], peak_err))\n",
    "\n",
    "g_err = np.abs(np.percentile(boot_params[:,2], [2.5,97.5]) - sresult.values['g']).mean()\n",
    "print('g = {0:.3f} +/- {1:.3f}'.format(sresult.values['g'], g_err))\n",
    "\n",
    "de_err = np.abs(np.percentile(boot_params[:,3], [2.5,97.5]) - sresult.values['de']).mean()\n",
    "print('de = {0:.3f} +/- {1:.3f}'.format(sresult.values['de'], de_err))\n",
    "\n",
    "### plot results ###\n",
    "fig, ax = plt.subplots(1,1)\n",
    "\n",
    "bs = np.linspace(-5, 5, 500)\n",
    "ax.scatter(results['field'], -1.0*results['epsilon'])\n",
    "ax.plot(bs, smodel.eval(sresult.params, fields=1000*bs), c='C3')\n",
    "ax.set_xlabel('field (T)');\n",
    "ax.set_ylabel(r'dS$_{23}$/k$_{B}$');\n",
    "\n",
    "### save data ###\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat1442_field.csv\"), bs, delimiter=\",\")\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat1442_dS23_fit.csv\"), \n",
    "           smodel.eval(sresult.params, fields=1000*bs), delimiter=\",\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fit 1-2 peak data\n",
    "\n",
    "Fit dI curves to fit for dS at the 1-2 electron transition.\n",
    "\n",
    "dataset 1284,1285,1286,1288,1290 -- di vs plunger vs parallel field (field increases with dataset number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dS12(fields, temp, alow, ahigh, b, glow, ghigh, est, de):\n",
    "    return - dt.gibbs_entropy(fields, alow, 0.0, temp, glow, de) + \\\n",
    "             dt.gibbs_entropy(fields, ahigh, 0.0, temp, ghigh, est) + b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "xmult = [0.5, 1.0] # mV, mT\n",
    "avgs = 5\n",
    "span = 5.0\n",
    "\n",
    "#############\n",
    "dats = [1284, 1285, 1286, 1288, 1290]\n",
    "ns = [None, None, 25, None, None]\n",
    "\n",
    "columns = ['x0', 'theta', 'di0', 'di2', 'epsilon', 'field']\n",
    "results = pd.DataFrame(columns=columns)\n",
    "\n",
    "vac = []\n",
    "for n, dat in zip(ns,dats):\n",
    "    swp = dt.open_hdf5(dat, path=data_dir) # load sweep data\n",
    "    vac.append(swp['vac_heat2d'][:])\n",
    "    \n",
    "    ### get centers from g_sense ###\n",
    "    x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['g_sense_dc2d'][:n], avgs, axis=1)\n",
    "    y = swp['y_array'][:n]\n",
    "    dz = dt.dfdx(z, x, axis = 1)\n",
    "    argmins = np.argmin(dz, axis=1)\n",
    "    realmins = x[argmins]\n",
    "    centers_fit = np.polyfit(y, realmins, deg=2)\n",
    "    centers = dt.parabola(y,*centers_fit)\n",
    "\n",
    "    x, z = dt.moving_avg(swp['x_array'][:]*xmult[0], swp['g5x2d'][:n], avgs, axis=1)\n",
    "    z = z*(1e-8)*(1e9) # nA\n",
    "\n",
    "    _results = dt.di_fit_simultaneous(x, -1*z, centers, 0.32*np.ones(len(z)), \n",
    "                                            (-305,-265), constrain = None, span=span)\n",
    "    _results['field'] = y/1000.0\n",
    "    results = pd.concat([results, _results], ignore_index=True)\n",
    "\n",
    "### save data ###\n",
    "results.to_csv(os.path.join(analysis_dir,'dat1284-1290_di_free_fits.csv'), index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "temp = 153.9 (mK, fixed)\n",
      "peak height (B=0) = 1.008+/-0.031\n",
      "g(B=0) = 0.467+/-0.019\n",
      "peak height (B=9T) = 1.043+/-0.040\n",
      "g(B=9T) = 0.693+/-0.035\n",
      "de = 0.000 +/- 0.001\n"
     ]
    },
    {
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       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
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       "\n",
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       "\n",
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       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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8AFWr16Nt99+26gANDQCIS6FyORFAiRAAiRAAnIJCPH38ZIovHf6b7xxaQ/ebT4G8PKC3OlbEULm4uAv8NL9aHzcQH+M062DJx4VJ8bkMWPGZOoKCkC51ukm6WbNmoXevXvj5s2b0pSv9rpz5w7CwsIgpoiFl0/3mjJlCj7//HP88ccfePPNNzM+unfvHvLmzYsJEyZgyJAhRgUgPYBuYhisJgmQAAm4KAHt7l+xcePL/81FqpcPRr/WLaO2cqZvhQdw/ojv8VnUL2jXfCye+Gcz2lp6AAF6AFU6Bbxjxw7Uq1cPGzZskKZytdfOnTtRt25diE0iFSpU0HswhIevTZs20q7hdu3aZXymXTc4bdo0fPLJJ0YFoCd/g3DRdymrRQIkQAJuRUAb/89Lk45f1400Gf/PnHgTIvLtL37B17+Pwcjq3XAg/0t6DOSISLeCpqCyXAOoUgGYnJwsbf4Q8f/EFK726t69OzZt2oQrV65kMhvh6StYsCBatWoFsSFEe4np4F69euH48eMoW7YsBaCCB45ZSYAESIAEjBPQngBS9FEMftg2BYNr9sSxfCUyJbY0fbvx+E3k6PQWNhetgp/KPI+CIXca2VP6hwJQpQJQGPDcuXPRo0cPaWOH8AZu3boVM2fOxNKlS9GhQwfcuHFDEnXlypWThJ+4xo0bh5EjR0phYIQQFJtAxN/ee+89zJ8/P9NzQQPylFcF20kCJEACjiWg9QA2jd6HPkd+Q9uWXyLRN/NmQjnTtwc//AjXo2PQ/7WeGZVmHED9/uP4rWIBKLp6zpw5EGv7rl69iuLFi2PYsGHo2LGjZAU//fSTtA5QBIYWp35oLyEcv/32W1y6dElaP/jhhx9KolAcC2d40YAc+0Jk6SRAAiTgKQS0awDbb1+E4nE30Of1AXpNt2b69t6ChbgzfToerNyI2/GpPAnEiBFx/Fa5AHT0i4MG5GjCLJ8ESIAEPIeA2AXs1bk9juUrjpnl22Q03Nrp2/gDB3Dl/Q8QuWYNAkuX8hyAVrSU4zcFoBXmkjkpDUgRPmYmARIgARLQIZD25CnOVa6MH2t2wm/5nm9UtHb6ViqnShWEf/klcrVpTcb0ABq1AVXGAXSWtVMAOos070MCJEAC6icQHxWFK+91RNHff8dR/3y4/TjR5unbiy1aIrhaNeQfOUL94GxoIcdvegBtMJvnWWhAivAxMwmQAAmQgA6Be0uW4tbEr3H+pz8RljsHqkaG2nxk241Bg5B85Qoif/mFjOkBpAfQ3k8BBaC9ibI8EiABEvBMAmL9X/TQ4Sh0OzpjA4i1U7+65O7//DNuT56C0ocOwsvPzzOhmmk1x296ABU9FDQgRfiYmQRIgARIAID2CLjv/vkO0SH5MbVSe4mLtZs/dGFqp5Mjf1+NwJf0A0IT+rOTQHLmzMmzgGkMthGgAdnGjblIgARIgASeERDhX2pO3IbbD5/i97VfYMHLLbCmeO0MPNaEf9Flmh4fj7OVqyB87BjkatuWuA0IcPymB1DRQ0EDUoSPmUmABEjAowkI8Td41TGsirqOIo9iMWfbZAyq9TGO5y2eiYucANCGmS61aoWgV19F+OjRHs3ZWOM5flMAKnooaECK8DEzCZAACXgsATHtO2T1cTyMT5EY1LsWhcGHlqFt83F46h+UiYulI+CMgbwxZCjunzyDS+Nm2LybWK0dxPGbAlCRbdOAFOFjZhIgARLwSAJC/PVcEqXX9q4n1qL2zaPo0vgLo0ys9QCKe+yaNBvvHlyN1i3HI9XbF0o2laitozh+UwAqsmkakCJ8zEwCJEACHkdAe+RbTFyiXtvH75mLRF9/jKv2/GhSbQIh3HYPri87JIx2U0np+9GYunMG+tTrj4u5CinaVKK2juL4TQGoyKZpQIrwMTMJkAAJeByBvRfvocO8ffrt1miwfMNorI2sgaUvNcnE5IdOldC0bLgsVroCMyA1CavXDsd3Fdthc9GqUn5bN5XIurkbJeL4TQGoyFxpQIrwMTMJkAAJeByBNUduoN+KI3rtDk2Iw9K/x2Fs1c7YW6Cs3mefNiyFfg1LyuZkKDDnbZ6Igy+8hDmvvKlXhrVTyrIr4CYJOX5TACoyVRqQInzMTAIkQAIeR8CYB7BK7GmM3TcfHzYahtvBoRlM8ocEYM+QBrKnfkVGQ4E5bP/PCEl+iiG1PtZjbcumEjV1FsdvCkBF9kwDUoSPmUmABEjA4whop2hj4xKh+a/175zbinbntqNdi3GA17Pwz+K/s62Y+tWCNBSY7c9uQesLO/BO87EZZYu09AAyELSXRqPR2qDHPYhKG0wBqJQg85MACZCA5xHQbtIQLRcD8JADi5E78TEG1+4lwcidzQ8TWpeTve5Pl6ChwKwWcxKj/12IDxp/gTvZcnMN4H+wOH7TA6jozUMDUoSPmUmABEjAYwkIETjmr1MQu4HnbfkaB8NexC/V2qJLzQj0qV/SqmlfQ4i6AjNP/EMs3vQlRlfrgv3hL0tJbfEsqq2jOH5TACqyaRqQInzMTAIkQAIeTUB46/afuo6c7Zogod9QVPiokyLhpwszQ2A+TMDK9SOxukRd7KjaEqNalbHJs6i2juL4TQGoyKZpQIrwMTMJkAAJeDyB+MOHcaXDe4hc/RsCy5SxKw9JYF6+D/+BveGbOzfKzptlN4Fp14pmQWEcvykAFZkdDUgRPmYmARIgAY8n8GD5csSO/wqlow7B29/fITxiv/oKT3bsQIm//3ZI+e5YKMdvCkBFdksDUoSPmUmABEjA4wnEjByFhKNHUWzNHw5j8fC31YgZPhylDx6Ad3Cww+7jTgVz/KYAVGSvNCBF+JiZBEiABDyewOV330VARCQKfD3RYSwSTp5EdJu2KLp8GbJVrOiw+7hTwRy/KQAV2SsNSBE+ZiYBEiABjyagSUvD2VcrI1//fsjTOfMZwPaCk56UJN0n//AvkLt9e3sV69blcPymAFRkwDQgRfiYmQRIgAQ8mkDSpUu41LwFivz0E4KrV3Moi0ut3kDQq5UQPnq0Q+/jLoVz/KYAVGSrNCBF+JiZBEiABDyaQNy6dbj52ecotW8vfHLlciiLGwMHIeXaNUSsWO7Q+7hL4Ry/KQAV2SoNSBE+ZiYBEiABjyZwe8oUxK1dh5Lbtzmcw73583Fn5ixpI4iXt7fD7+fqN+D4TQGoyEZpQIrwMTMJkAAJeDSBq//XHV5+fig8e5bDOTzZvQfX/u//UHzjBvhHRDj8fq5+A47fFICKbJQGpAgfM5MACZCARxM4V6s2cr/TDvk++cThHFLv3sX5WrVR8LvvENK0icPv5+o34PhNAajIRmlAivAxMwmQAAl4LIHUO3dwvnYdFJw+DSGNGzuFgxCcudq1RVi/fk65nyvfhOM3BaAi+6QBKcLHzCRAAiTgsQSe7NqNa927o/jmTfAvXNgpHJw55eyUBim4CcdvCkAF5gPQgBThY2YSIAES8FgCd+fNw705c1Fq/79O25Rxe/JkxK1b75RNJ67esRy/KQAV2SgNSBE+ZiYBEiABjyVwY8BnSLl9CxFLljiNQdxfa3Fz4ECnhJ1xWqNsvBHHb5ULwEWLFmHixImIjo5GkSJF0KdPH/Tt21e2uTRv3hzHjh3D9evXjeahAclGyYQkQAIkQAL/EUhL1+B042Z49HIFeH0yEFUjQ+Hj7eVwPkkXLuBSy1YosmgRgqtVdfj9XPkGHL9VLACXLFmC999/Hz179kSTJk0QFRWFr776CuPHj8fgwYMt2uXcuXPRo0cPFCxYkALQIi0mIAESIAESkENg44kYTFh9GLOWfY5pFdpiU0Q1hOcMxKhWZdC0bLicImxOo0lNxdlKryLs888Q+sEHNpejhowUgCoVgOnp6YiMjES1atWwcuXKDFvt168fFi5ciJiYGAQHB5u04cuXL6N8+fIIDQ1FamoqBaAanna2gQRIgASymIAQfx8viUKp+1fw3c7v0bdef1zIVQha39/sTpUcLgIvt2mLgFKlUGDCV1lMI2tvTwGoUgF4+PBhVKpUCevWrYOYxtVeW7ZsQaNGjbB+/Xo0a9bMqPVpNBq8/vrrKFq0KLy8vCDycAo4ax9U3p0ESIAE3J2AmPat9fU2xMQloln0PvQ+uhpvtxyPFB8/qWlCBObPGYjdg+s7dDr45hdfIPH0aRRbvdrdkSqqPwWgSgXgggUL0K1bN1y7dg2FChXKMJLY2FiEh4dj6tSp6N+/v1HjEZ9NnjwZJ0+elNJQACp6xpiZBEiABEgAwN6L99Bh3j6JRe+jv+Hle5fRq/7nmdgs714drxXP4zBm9xcvwe1Jk1A66pB0ComnXhSAKhWAkyZNktb5xcfHIygoKMO+k5KSEBgYiNGjR2PUqFGZ7P7MmTOoWLEifv31V7Rs2RKdO3eWJQCF0AwJCckoLyAgAOKHFwmQAAmQAAkIAuP+Oon5e6IlGFN2fo+YbHkwufJ7meBMa18Bb1Yo6DBo8QcO4Mr7HyDyzzUILFXKYfdxtYLF+C9+tJcQgIULF0ZcXJze+O1q9XZkfbw0Ys5TZZfY6DF8+PBMAjAlJQX+/v4QAnHgwIF6rRZr/WrUqIEyZcrgp59+kj6TKwAN8QlxKUQmLxIgARIgARIQa/96LomSQHhr0rFq7XAsebExVpeslwmOoz2AaY8e4VzVaigw6WvkfOMNj+kcMSaPGTMmU3spAFVmArNmzULv3r1x8+ZNacpXe925cwdhYWEQU8RdunTRa/WECRPw3Xff4dChQ8iVK5f0mdhBvH37dpw9e1YSjuJH99K6kOkBVJkBsTkkQAIkYCcCumv/RJEFn9zBj1u+xtAaH+FI2HMPnDPWAIq67L98H8EftkFanfp45csRDl1vaCeEdimGHsDMGFXpAdyxYwfq1auHDRs2oGnTphmt3rlzJ+rWrQuxSaRChQp6NN566y2sWbPGpKGJHcRCIBoTgJ78DcIuTyYLIQESIAGVEtBd+yeaWPvGEQw7sATtm41GXEB2vVb/4MBdwMILOeavU9ImlBH7FiIwLQUzmn/ilPAzrti1XAOo0jWAycnJ0uYPEf9v8eLFGbbXvXt3bNq0CVeuXMlkj6dPn8a9e/f0/i7iBh48eBCrV6+W4gGK0DIUgK74KLNOJEACJOCaBNYcuYF+K45kVO7DU+vR8OohvN90hF6Fu9aMwMhWLzukEeuPxaDXsmdT0OLqdPpvtLj8P7zXbDTg5QVnhJ9xSMMUFEoBqFIBKGxCG8hZeO6EN3Dr1q2YOXMmli5dig4dOuDGjRs4fvw4ypUrJ4k7Y5fcNYD0ACp4CpmVBEiABFRMwNADOGbvj9DAC6Nf66bXaket/Vt/7Cb6LD+MdJ3V/jVuHseI/YvwXtOReBgY4pTwM67WxRSAKhaAwtjmzJmDKVOm4OrVqyhevDiGDRuGjh07SnYoNnqIdYAiMLQQehSArvZ4sj4kQAIk4P4EtGsAY+MSITTY4o1jsblIFfxc5lksWkeu/dPdfKJLMv/Te1i4eQKGv/Z/OPTCi9JHjhKgrtqDFIAqF4CONjwakKMJs3wSIAEScH8C2hNAciY9xvINYzC+yvvYXbC8Q08AMdx8okvRS+xEXjcCK0o1wK+l6ksfOTr8jKv1IsdvCkBFNkkDUoSPmUmABEjAYwgIEfjrnN/w+eaZ6NpwCGKy53XoGcCGU8+GoCfvnIE7QbnwdZVO9ADqxPH1GIMU3mc1xgF0VgdSADqLNO9DAiRAAu5P4M68H3Fn1iycn78GYTmzoWpkqMPCsPwedR2frjxqElqvo6tR/u4F9GgwSBKijj6CztV6j+M3BaAim6QBKcLHzCRAAiTgUQRuDPgMKbduIWLpEoe3e/6uSxi37rTJ+zSN3oc+R35D61ZfYfqH1dC07POYuQ6vnAvcgOM3BaAiM6QBKcLHzCRAAiTgUQQuNm2G4Fq1kH/4Fw5v9++Hb+DTX56HnzG8YakHVzFtx3Qs7zoGrzauibAcgQ71SDq8wVbegOM3BaCVJqOfnAakCOKkIekAACAASURBVB8zkwAJkIBHEJBO4Dh5HTnfaYKEfkNR4aNODpv61QK1tAYwIDUZv639At9XaIu/I6pJ2cRU8KhWZTzCG8jxmwJQ0cuHBqQIHzOTAAmQgOoJaE/gCL10GpN3zcTHrw9AUpFiDhda5nYBa6HP3fI1Ducrhdnl35b+JELSiMsTAkNz/KYAVPTyoQEpwsfMJEACJKBaAkKAzdh2AVO3nJPa+MbFXeh2ch1atxyPdG8fpwgtbfgZcTOdONAZzIccWILQxDgMqt0742+OjEvoSp3N8ZsCUJE90oAU4WNmEiABElAlASG8Rv95ErGPkjLa92nUCkQ8ikW/ev0zvG35nbD7VvcMYEPY75zbinfObUfbFuOkI+F0L7UHhub4TQGo6OVDA1KEj5lJgARIQHUEtF43Q4/bzG1TcDZ3EUyv2M7pQktag3j5Pm4/TsT5W08wY/sFqQ6Vb53GuL3z0bXREMQE59Wrl9oDQ3P8pgBU9PKhASnCx8wkQAIkoCoCptbd+aWl4Pe1X2DWK29hfWSNLBVauptDxMkkKzaMwVdVOmFXwQpOF6ZZ2fkcvykAFdkfDUgRPmYmARIgAVURMLXztuSDa5i+Yxr61+mLs6FFs1RorT92E32WH0b6fy7KRX9/iR2FKmDByy2lenENoKpM0mxjeBKIgr6mAFQAj1lJgARIQGUE1hy5gX4rMsfeaxa9D72PrpY2gCT7+GWZ0DI2PT38358QnJKIobV6ZtSLu4BVZpgmmkMBqKCfKQAVwGNWEiABElAZAVMewD5HVqHM/Wj0qv95RouFp82ZQsvU9PS7Z7ei7fnteKfFWMDLG/0alETfBiUdHqcwq7ue4zengBXZIA1IET5mJgESIAFVEdCKrNi4RL2wK1N3TMP17GGY8moHqb1ZEXDZlDitdPssxv9vHro1HIyb2fNlWf2cbQgcvykAFdkcDUgRPmYmARIgAdURMIy955OehtVrv8DCMs3xR4k66N+gBPo2KOV0D5up6ekcyU+xcv0oTKzcETsKVcyYBhb/cKaH0tmGwPGbAlCRzdGAFOFjZhIgARJQJQHd2HsRcTGYvX0KBtX6GMfzFs8S75+AbO5ouIWbxmNPgVfwY9lWelPUzohTmFUGwPGbAlCR7dGAFOFjZhIgARJQLYH1x2LQa1kUGl3Zj/6Hf0W7FuMQ7xeYZcetmZqeFh0wbP/PyJn0BINr98rUH2oNCM3xmwJQ0cuHBqQIHzOTAAmQgCoJ6G64EBtAyt67jJ4NBma5d83U0XDtzm1D+3NbpRNBNF7een3StWYERrZ6WXX9xPGbAlCRUdOAFOFjZhIgARJQJQHd6dbvt0/FpZwFMLXSuy7hXTN2NFyFO+cxYc8cdG8wCNdzhGWq5w+dKqFp2XBV9RXHbwpARQZNA1KEj5lJgARIQJUEtBsu/NNSpA0gxk4AEQ3PquPWhIdy38V76L0sCg8TUpA9OR6/rh+JSa92wPbCr+r1iVoDQ3P8pgBU9PKhASnCx8wkQAIkoEoCWg/gS/ei8e2uGehTrz8u5irkEh5A3UoIb2DPJVHSn+ZvnoB/85fB3HJvGu0Tta0F5PhNAajo5UMDUoSPmUmABEhAlQS0awCrH9qED0+tR5uW45Hm7ZPRVlfyqo376yTm74nGkANLkCcxDgNr9zbaJ1nlrXSUgXD8pgBUZFs0IEX4mJkESIAEVEtAeNcu9xuAsISH+KxOHz3xJ/7HVWLsab2Vrc//g/fP/I22Lb7UE6vaitMDqD5T5VFwCvqUAlABPGYlARIgAZUTOFa3PraHvoippVtktDQrTgExh1nrrcx96Qym7JqBvvX644LOdLUreSvtaS4cv+kBVGRPNCBF+JiZBEiABFRLIPXBA5x/rQbyf/MNzpR5DbcfJyIsRyCqRoY6/RQQS5CFt/KTRf9i1drhmFeuFf4qVkvKIsSfK3krLbXDms85flMAWmMvmdLSgBThY2YSIAESUC2BJzt34tpHPVB88yb4Fy7s8u0UIjDl4664FpAbkyp3lOrrat5Ke0Lk+E0BqMieaECK8DEzCZAACaiWwJ3p3+PBsmUoufd/8PLS+tJcu7kxEybi3sZNuDhtsct6K+1FkOM3BaAiW6IBKcLHzCRAAiSgWgJXunSBd1A2FJ41023a+GjjRtzo/ylK7NwBv7DMAaHdpiEyKsrxmwJQhpmYTkIDUoSPmUmABEhAlQQ0KSk4W6068vXuhTzdurlNG1NiY3Gh3usoOH0aQho3dpt621JRjt8UgLbYTUYeGpAifMxMAiRAAqokkHD8BKLbtUPR5cuQrWJFt2rj+dfrI6RZM7ww6PnZxW7VAJmV5fhNASjTVIwnowEpwsfMJEACJKBKAvcXLcLtb6ei1IH98Pb3d6s23hgwACkxsYhYvsyt6m1tZTl+q1wALlq0CBMnTkR0dDSKFCmCPn36oG/fvibtJDExEaNHj8aKFSsQExODvHnzok2bNlIZ2bJly5SPBmTtI8f0JEACJKB+Atc/6Ye0+/dRdMlit2vs/Z9/xu3JU/Bg5UbcTkxX7WYQjt8qFoBLlizB+++/j549e6JJkyaIiorCV199hfHjx2Pw4MFGH8oOHTpg9erVGDp0KMqXL4/9+/djypQpaN26tSQKDS8akNu921hhEiABEnAoAY1Gg/O16yBXmzYI+7S/Q+/liMK3/bEd4UN64bPavXEqT6R0CzWGg+H4rVIBmJ6ejsjISFSrVg0rV67MeEb69euHhQsXSt694OBgvWfn6tWriIiIwNixYzF8+PCMz8S/hWg8c+YMSpcurZeHBuSI1w/LJAESIAH3JZBwORrRzZrh+uCvkL1OHZcM/GyKrogF2PvnA1i5fiRWlqyPX0o3kJKqMSA0x2+VCsDDhw+jUqVKWLduHZo3b55h61u2bEGjRo2wfv16NGvWTO8Z+PPPP/Hmm2/iwIEDqFy5csZnooyWLVti1apV0nSw7kUDct+XNGtOAiRAAvYmIATUlqkL0GXPUrzTfCye+ge5jfdMeyRcTFwixuz9Eb7p6fii5kcZiNR2JBzHb5UKwAULFqBbt264du0aChUqlGHAsbGxCA8Px9SpU9G/v75rXnx24sQJ1KhRQ2+934gRI/Dll1/i33//RdWqVSkA7f3GZHkkQAIkoAICQvx9vCQK/aJWouTDa+hd/zO38p7tvXgPHebtk+rc5vw/6HTmb7RrMQ6p3r56vbO8e3W8VjyP2/cYBaBKBeCkSZOkdX7x8fEICgrKMNSkpCQEBgZKGz1GjRpl0YCXLl2Krl27St7EPXv2wNvb26gAFEIzJCQk47OAgACIH14kQAIkQALqJiA8Z/su3kPvZVF4mJCC+Zsn4GBYacwu39qtvGdrjtxAvxVHpDqXfHAN03dM01sHqG3MtPYV8GaFgm7XqWL8Fz/aSwjAwoULIy4uTm/8druGKaiwl0asWFXZJdbsibV7hgIwJSUF/v7+EAJx4EDTMY7ErmHhIVyzZg0qVKgg/Ra7iA0v7TcIw78LcSlEJi8SIAESIAH1EhBevzF/nYKYNhVX2NP7WLT5K4yt2hl7C5TN1HBX9p7pegC909Owcv0orCpZDytKN9Rrhyu3wZyliTF5zJgxmZJQAKrs+Zw1axZ69+6NmzdvSlO+2uvOnTsICwuDmCLu0qWL0VZ/9913GDZsmHR2o/g9aNAg+Pn5GU2rFYD0AKrMgNgcEiABErBAQDvlq+tBaRz9Lz45sgrv/rf+z7AIV/aeadcAxsYlQrRp9N758EtPxRc1e0jNcPc1gPQAZjZoVXoAd+zYgXr16mHDhg1o2rRpRqt37tyJunXrQmwSEZ49w0uEfxEx/8TGkR9++EFyD5u7uIaAYwQJkAAJeB4B3Q0Tuq0ffGAJ8sffw6d1+xmF4ureM62oFZVv/d86wHeaj0Oqz7N1gLM7VULTss+dKu7c8xy/VboGMDk5Wdr8IeL/LV78PBBn9+7dsWnTJly5ciWT3V64cEEK8/Luu+9CrP0THkBLFw3IEiF+TgIkQALqI6A7XaptnZcmHcs2jMHGiGpYVOZ59Al3855pp7WDr1zA9/98h89r98b9Yi9hVKsyqhF/ok84fqtUAIrOnTt3Lnr06AER+094A7du3YqZM2dK4k4EfL5x4waOHz+OcuXKoWDBglLA588//1yKE5g/f/5MbyxtOt0PaEDqe7GzRSRAAiRgiYDuhglt2oi4m5i9/VsMqdkDR/OVzCjCHWPoCQ/n/gt3kKN9C9xs8AaevtcV+UMC3SqmoaU+5PitYgEoOn/OnDmSsBNBnosXLy6t6evYsaNkFz/99JO0DlAIvs6dO0vHxAmBaOrSpqMAtPRY8XMSIAESUDcBYx7Aty7sROdT66XQKSk+z9eNu+spGsITePuzz5Dj0d2MKW13bYsxa6QAVLkAdPQriAbkaMIsnwRIgARcj4DhhglRw2fBk9MyNk3kCvLDzI6VUL1YHvh4W15S5Eqt1K4FbHhlP/of/hXvNRuFuIDsGVX8QQVrATl+UwAqeuZoQIrwMTMJkAAJuC0B3Q0TPumpWLluJJaXbohVpepLbXLXDRO6G1xyJz7Cso1jMenV97C9cKWMvsqVzQ+HhjdyO2HLGTz9x02Vu4Cd9UahAHQWad6HBEiABFyPgHbDxAvnj2HC/+ai1+sDkFikmFtvmDCc3p6x/VtE58iPyZXf0+uATxuWQr+Gz9c6ul7vmK8Rx296ABXZLA1IET5mJgESIAG3JyA8ZseHjoL3rn/w9OfVqOqGU766nWC4weXDU+vRNPpfaRpY4/X8NKycQb6IGtHYbb2AHL8pABW9fGhAivAxMwmQAAm4PQFxmNbFxk0QXLMGwlVwApShB/Dlu5cwefcs9Kv7Cc7l1j8Ry529gBy/KQAVvXxoQIrwMTMJkAAJuD2BpEuXcKl5CxT6YTZy1Kvn9u0RHs1Xx22WzjUWlzgW7pf1o/B7iTpY9mLjTO1z1w0hHL8pABU9rDQgRfiYmQRIgATcnsC9+Qtw5/vvUWrfXngHBrp9e0QDpm05h6lbzme0ZciBxQh/eg/96vXP1D4RGmb34PpuNxXM8ZsCUNHDSgNShI+ZSYAESMDtCUR36gSf7DlQYNYs7L98H7cfJyIsh3sHTZa8gF9uxsP4Z17AutcPY8jBpfiw8TDczhaaqc9c/Yg7Y0bG8ZsCUNHLhwakCB8zkwAJkIBLE5BOxDAj6lJu38aFuvVwt9dADHpSBDFxiRntcfegyWKHc88lUVJ7glIS8cuGUVhQpgX+KFEnU59Na18Bb1Yo6NJ9aVg5jt8UgIoMlgakCB8zkwAJkIDLEtCGeDEn6u4vXYrYrybg3Saj8Ng/m15b3PEIOMPO0J0KHr13PoJTEzGwdm96AF3Waq2rGOMAWsdLLzUFoAJ4zEoCJEACTiBgyYtnrAraIM8agw8NRV30+x9g/82nGFSlq9GWiPT53XSNnGiQYFdz4jbEPkpEo/9OBenUdAQeBIZI7XXn9nH8pgdQ0euHBqQIHzOTAAmQgEMJyPHiGVZA9yQMY5XTip5/ur2Ci3Xr4rvybbEpoprZdrjjGjltg7RiOEfyUyzdMAZzyr2JtcVqSuJPXO564gnHbwpARS8fGpAifMxMAiRAAg4jINeLZ1gBwzh4pir4W/gNBM2ZhnebiunfYLPtcMc1croN0grpHhtnIiQ5HgPq9oW7r3Hk+E0BqOjlQwNShI+ZSYAESMAhBOR68YyFLzE8CcNUBVcf/xG+eULxRoHWFtvgzh5AbeME08M/rUTwpNF4NG8FKtd8xe1Cv+h2FMdvCkCLD665BDQgRfiYmQRIgAQcQkCuF8+YMDOMgWesgoUe38a8rZMQPnUqmh3xQ2xcIgzXC4p87rxGzli70xMScL5WbYR26YJ8fTJvBnFIZzqoUI7fFICKTIsGpAgfM5MACZCAQwjI9eIZTs3qhj4xVTEh6npd3IQ3ruxDyV07sen8fXz8X7gUXRHo7mvkTLX/5tBhiI86hOIbN8LLS9tKh3SjQwvl+E0BqMjAaECK8DEzCXgsAVt2pnosLBsabq0HUPTHvov30HtZVMYRaKZu66NJxx+7v0HeRvUzzv61ZbOJDc1yiSxP9/2Lq507o+jin5GtShWXqJMtleD4TQFoi91k5KEBKcLHzCTgkQQ8SSxkVQdr1wCampoV9QoN9sO+oQ2x7cwtjPnrlF4QZ3P1Hh/+CJVmj0XELysQVL58RlJPEfUajQaXmjZDYLlyKDj5m6zqYsX35fjtZAGYnp6Ohw8fIjT02VEy+/btw969e1G3bl1UqlRJcYc6uwAakLOJ834k4N4EbN2Z6t6tzpraa1mLuxtbnyf+niubX8ZxZ3Jr+euVlcib9AQRv61y6ylQue01lu7egoW4M3UqSuzcAd/cuZUUlWV5OX47UQAePnwYzZo1w507dyTB17dvX7Rt2xa5cuVCXFwcVq1ahbfeeivLjMGWG9OAbKHGPCTgmQSU7Ez1TGLKW23M26qk1PxP72HBlokoMG4scrVtq6Qot86b+uABLtSpi3z9+yNPN+NBsF29gRy/nSgAa9eujbCwMHz44YeYP38+Nm3ahKlTp6Jnz5749ttvsXTpUhw6dMjVbUavfjQgt+ouVpYEspSAtevSsrSyKrp5cmo6qk/YivtPkxW1Smx36Ht+I1pc24+SO/6Bd1CQovLcPfONQYOQEHUYxTdugJevr9s1h+O3EwVgzpw5cfHiReTNmxe3bt1CeHg4Hj9+jODgYMkDmD9/fiQkJLiVEdGA3Kq7WFkSyFICtu5MzdJKq+DmcoW3uaYK8ReUkoiV/0xEvnZt8cKQwSogo6wJCSdPIrpNWxSc+i1CmjVTVlgW5Ob47UQB6OPjg7S0tIxutvT/WWAPVt+SBmQ1MmYgAY8lIFeIqCFosCt1slzhba7O4tSLyZoTCF0+HyU2b4Jf/vyu1MQsq8uVzl2Q/uQJIn5d6XbrITl+UwAqenBoQIrwMTMJeBQBSztT1RY02FU6V67wNlbfXEF+mNmxEioXyI4LjRrhcblXoRk4AlUjn21k3H/5Pm4/TkRYjkDpbz7e7hsXz5b+erJrF651/whFFi1CcLWqthSRZXk4fjtZAO7evRtiC7m4xJpAw//X9RBmmVVYcWMakBWwmJQESACmdqaqNWiwK3S5JeFtrI66/SE+3z5lHj7YuwI9G3yOazleQPYAH/j6eOvtIHb3s3Ft6Ssxnl9u3QY+2bOjyM+L3MoLyPHbiQLQ29vbrH2JiOIUgLY8gsxDAiTgTgQYB9D5vWVOeAuXhGE4GK2YEzXtt+hfzNsyEadCIzCxyvsmK++pIv7x9u24/nEvFJ7/I7LXrOn8zrXxjhSADhKAMTEx0iYPS9fPP/+MDz74wFIyl/2cBuSyXcOKkYBLE/CUoMGu1AnmhHejMvkzTeeKutf6ehtqHNyIzqfWo0eDgbiZPZ95RwaA/DkDsXtwfY+ZDhZewOj27aVgiyI4trscD8fx20ECsHjx4ti2bRuKFi1q9GE5ceIEevfujT179iA1NdWV3hFW1YUGZBUuJiYBEiABiYAjBLCcMi2l0f387uMkfPt7FBZsnoBdBctjRoU2snvP0zbyPN27F1e7dEXBb6cgpHlz2ZyyMiHHbwcJwGzZsknhXjZv3ozSpUtn9LEI+zJixAjMmjVLEn6VK1fG/v37s9IGFN2bBqQIHzOTAAk4kIAlsePAW5st2hFT4LaWqcso+m48lu+/ithHiRn1//joajS8dgj/13AwHgSGyEY2rX0FvFmhoOz0akh4rXcfJJ48ieLr18E7WzaXbxLHbwcJwF27dqFly5YICgrC33//jfLly2Px4sUYPHgwYmNjpenhr776SgoK7c4XDcide491JwH1ErBVEDmaiK1H4ZkTs7aWaemUkOIPr2PaP9PwY9lW+KNEHavQeJoHUMBJvnYNl1q0RGiXLgj7tL9VvLIiMcdvBwlA0ZniVI+mTZtKGzteeukl6czfwMBADBgwAEOHDpUCQLv7RQNy9x5k/UlAfQRsFUSOJmHrUXiW1u6JdXoxcc+9drrtMBVaxxQjbV7v9DR8u3MG/NNT0adef6R7+8jGIzaQeNIaQF0wd6Z/j7vz5iHy15UIfPFF2cyyIiHHbwcKQNGhp0+fRqNGjXDz5k1UrVoVK1euRJEiRbKirx1yTxqQdVhddUrKulYwNQm4LgFbRZYzWiQ3Hp+u98ySmO3fsCSmbjlvsfq6ZVpiJArrcGYzOp7ZhM/r9MGZUONr2U3d9IdOldC0rOVNkBYr7YYJ0pOTpdNB4OuLSLEhxN/fZVvB8dvBAlD0fHR0NBo2bCiJwD/++AONGzd2mkEsWrQIEydOlOoghGefPn3Qt29fs/efPHmytEZR7GQuVaoUhgwZgg4dOhjNQwOS35WuOiUlvwVMSQKOJ2D4JenVorlx6MoD2cGGbRFZjm/VszvIPZFDu37OklCTjmfz90F88vMTpky1RXdNniVGJR9cw7c7v8fKUvWx+KWmVuH5tGEp9GtY0qo8akssHRH3zrvI060bwgZ86rLN4/htJwFYrFgxs50sNn/cu3cP/v7+KFCgQEZasV1cnA/siGvJkiV4//330bNnTzRp0gRRUVHSusPx48dLaxGNXeKzUaNGSZ9XqVIFW7duxYwZM7BixQq8++67mbLQgOT1nKVv8bM9+BuzPIJM5QkEjH1JEgdLpD+LnS9dloINWyuynMFVK2p/3nsZG07csnhLrbfOklCzWJBOAl0PoDlGOZKfSuv+Hvtnw4A6fZGmM/UrBKdOV2S6ff6QAOwZ0sBjwr+Y43937jzc+fZbFPphNnLUq2dNVzktLcdvOwnAevXq2Rz7Z/v27Xbv8PT0dERGRqJatWrStLP26tevHxYuXCh59wzXIMbFxaFQoUL4+OOPMWnSpIw8b775JkTYGmNClQZkuevkfIv3tLhZlqkxhZoIyFn6YGlNmpaHpWDDckWTszYpWNpoodvPhuv15IpZS7aiPc6terE8kjgzxchbk46xe39EiYfX8Um9/rid7dlxb9p6DWv+EvouP5zpdpb6xFL91Pi5Jj0d13v3QXxUFCJX/gJ/EyHhsrLtHL/tJACzshON3fvw4cOoVKkS1q1bh+Y6MYm2bNkirUlcv349mjVrppf1999/R+vWrXHy5EmUKVMm47Mff/wR3bt3x6lTp6TNLLoXDchyz7vagGS5xkxBAvYjIGfpg6UvSYa1MXdmsJxjzwwFkf1aq1+SXFGrK251ZwPkvjvk1j802A9vVyiI7IF++H7beT3PKjQa9Dm6Gk2j92F4je44ElYqQ/yJf2jrJac/5dZH7enS4uIQ3b4DNOlpiFi+HL6hzwS1q1wcv+0kAMVu31atWkmhX0wFf3Zmpy9YsADdunXDtWvXJK+e9tKGoJk6dSr699ffpj5y5EhpvWBiYiJ0j63bt28fXnvtNQiB+NZbb1EAWtmRcr/Fe2LcLCtRMrmbEZC79MFWoWPKi2fq2DNDfJamky3hNufZtFbUinsZrp+TI2Yt1VHu5x1P/41OZzdjaoV22BRRLSObMUZyPLpy76v2dMnXryP63fbwK1AAReb/CJ8Q+bEUHc2GAtBOAlBs7Ni5cydSUlIkL1mLFi0kMVizZk09MeXoDtWWL6ZwxTq++Ph4KRah9kpKSpJC0YwePVpa66d79erVC7/99htu3dJfo3L27Fm8+OKL+OmnnzLFLdQakBCaITqGHRAQAPHDCyanWwzZOGtKin1CArYQsHbQlyOAtGvG1h67iX4rjlhdLXNfmuRMvSqZurTkCbNF1Bprz/pjMei1LMpqNrIzaDTofGoD3j2/DQvKNMeqUvXRr0FJROYLRliOQFSNDOWaPtkwjScUm0Kudu0G/4IFpfOCfXPnVliibdnF+C9+tJcYvwsXLgyx/Et3/LatdPfM5aURB/nZ4Xr69Ck2bdokTa+KH7HOLjQ0VNqAIcSg8BLmdlLHi80cw4cPzyQAhUAVG1GEQBw4cKBeq8U0759//plJAJ4/f17aDSzWErZr104vj1YAGuIT4lKITF7PjnwScbpi4xKNLqA2N51FfiTgCgQsiR1jdZQrgITYCAn0xbh1p61uqqUvTeLZ23fxHnovi8LDhBSj5dvy/MnxbCalplstag3bY07ECvGcmJqOuPgUsxszzEEVa/56Hf0dLaL3Ym7ZVvi9RF0puSWuVncUMyDx7FnpqDjfPHlQeM4PkkfQ2ZcYk8eMGZPpthSADugJEQh67dq1khg8ePAgfHx8UL16dWmqWKzLe/nllx1w12dFijAu4qxhEXpGnDqive7cuYOwsDCIKeIuXbro3X/QoEGYPn26NAWsex04cECKYSjONn799deNCkBP9gDK8YyYmpJS4oFwmPGwYBLQISBH7BiL+SZ36YMtsLWibcfA142GiDE8z1aOuJQreix5NrV1m9yuPDr++K/s5hmuS7S0fnDWexWl7Rm2egdzJj3G4IPL8MqdC5hesR02Fa2aUVcuR5HdbVYlTLp4Ede6f4T0hAQU/O47BFd7ztyqgmxMTA9gZnB28wCa65Pbt29LGzLEjzgf+MmTJ9JaQeEZFKLL3teOHTsgdiZv2LBB8jxqLzFNXbduXYhNIhUqVNC7rYgZ2LlzZyl4tZjy1V4///wzunbtKnkG8+TJY1QAeuo3CGs8I9aktbc9sDwSsIWAXLFj7NQHuR5Aa+ul/dL0UZ1I/Hk0Ru8EDLFe7Y3y4Zn+LuceurH39l++bzLuoNx2Le1WDZ+vOmrS82+qTqINI1q8JHlETZ3uIfJmD/CBj7c34kx4Ns21udydCxh0aDl8NGmYWLkTjuUroZdcrhiWw5Vp9AmkPniAGwMGIH7/AeTt3Qt5u3eHl59flmDiGkA7rQG0pvdSU1Pxzz//SGJQeAfFGjt7X8nJydLmDzH9LM4g1l5imldMU1+5+AFOSQAAIABJREFUciXTLYXAE8GihSdw3LhxGZ+L9Y3im4MQlYaXJxuQOc+IWFPwacOSiMirv45GjrfQ3rbA8tRJwBm2JFfsGAoGOVOvcnvFMA6gmPqsHBGKtcdi5BYhK51oQ1xCMsb8dSqTqBzVqkzGyRZyPZtCUAb4eqPnEuvW71mKtSerMSYSZU+OR7eTa9H0yn4cz1MMX1fuiHtBOTNS2zIdrqQ+nppXk5qKOzNn4t7ceQgoVQrhY8ciqFxZp+Pw5PFbC9spHkDdnhXespw5nz90jur1uXPnokePHhCx/4Q3UAR1njlzJpYuXSqd7HHjxg0cP34c5cqVQ8GCBaVqDBs2DN988420fvCVV16R1v2tWrVKmv6tXbs2BeB/BMQAV3PiNsQ+Mn7+piEopbsNHWUjLNc9CTjLm2yN2HmzwrN3iJzNF3KpC0/Y+69FZEzzRt+Nx7J/r+DW4+cL2eWWZSqdVvSMaFFGWitoakF4t5oRaFgmP9I1GllTu1pRPG3LOVlHtSlth7n8AanJeOPSbrQ7vx3eGg3mv9wCGyOqQePlrSf+xP8wKL0je0K/bLE5JGbYF0g6exYhLVogX79P4O/Eo2IpAJ3oARTr8cRpGv/73/+kzSAivp5uWBWxRjAtzfKRPtaY55w5czBlyhRcvXoVxYsXlwRex44dpSLErl6xDlAEhhZTv+ISAaQnTJgAkU+sFxTrFMWGEuFJNHapzYDkelWsfalzrZ81Vsu05gjYuibPFqrWegAtrVuztg66a9HsXbZuXcR6OktTrtr0OQN98CgxzezGC931fLbucLaWlbH0eRMeotnlfWh2ZR9yJMdjQ0R1LC/dEA8CM4ci4ZdUexC3vgzhDXz4+++4+/0MpN67hxyNGyHPhx8isHx5mw+XkFsLtY3fctutm85pHkCxg/bu3bv47LPPsHv3bmntn1iLV7p0aak+IvaeEGDudKnJgOR6VUQ6a6d1RJ/KmV6RK0DdyUZYV/sRULImz5ZaWLODXZQvdrubW7dmbR3aViqE2qXyIm9wAD779ahsj7s19+laMwKNyuRHh3n7rMkmK60QVe2rFHaqBzA4OQHVYk+h1s1jqHrrNJJ8/LCl8KvSDt/Y4OdruMVUeoeqRTItU5HVMCayOwGxMeTh6tW4//PPSLlyFf7FiiFnq5aSZ9BRXkE1jd+2dojTBOALL7wgncernW4V07NiGlbsFBaXIzyAtkKRm08tBmTJu/DDf2f1WhqA5XAzF7zW0vojOeUzjXoJWOuR05JQ8sVC7g52uXVztd4Rz+Ptx4lWh2yR0w7ter5c2fxsDtdiaU2gX1oKXnxwFeXuXpR+Xr4XDT9NGk6FFsW2QpWwrfCrSPALzFRdsUmlZsm8cprBNE4koElLw9M9exD311o83roVmvh4BJQsgYLTpiOgWKRda6KW8VsJFKcJwOzZs+Py5cvIly+fVF/hDSxRogT++OMPaY0ePYBKutH2vHLW84kX+KHhjSB2Byr1FBgLseDMaT3bSTFnVhOw15o8a6f7LHnHxTM0dfM5zNh+IasRWXV/cTTavqENpTWGSp9rczfO5u+D+OQ0aRZAbtBZ4aEb2fJljF17ErGPkiA8e2EJD/BC/H0UeXwLEY9iERl3E4We3IGvJh2P/YJwIk8xHMlXEnsKlNPb3GGsbgz1YpWpZEni9Ph4PNm5C0927UT+ESPgHZhZyCupGAWgE9cAit20Ypftt99+mxF1e/LkydLGDLFBo2TJknZfA6jEOOTkVYMByV3PJ45pisibTbGnwNiOSXNTZ3KmjuX0FdO4PwG5Xjatjdnzi4UpL6I9N31kRQ/phl0xFaxdcb00GvinpyIoLRl+qSkISEtGQJr4/fzfwSmJCEl+ihwp8dJ6vTxpCaiYyxt+jx4g6fpNBKc+33D21DcQl3OGIzokP6JDwnEqNEL6t+6mDkt1ZqgXS4TU/7kaxm+lveQ0D+CZM2ekuH/CCygCQ1esWBHiEBKxI1ecsyvCw9h7E4hSOJbyO8qAUm7dxq0vvxTz4vDy9tb/7eMNePvAy8Rv+HjDy9sHer99/eDl7wfvgAB4iR8/f3gF+OPQzSf4Zns0Unx8keztixQfP+l3vG8gEvwCkK6zS054AWe+V0nWDkBT3LSeRB8R2+K/y9pB3VKf8HP1ErDnmjxLwZTlULS0dEJOGfhPHAWmJiMwNQmBackISk2SxJFvehr80lOl376aZ//2E//W/s3gc7HD1UujgTjhQvz4iP+HBj6adHhJfxOfPftc+3dtnsjQQFy/+0T6uzaNyJdRVvqz/CJ2nuHnz9I9u8+z++r+fvZ3OVeSty8e+wfjkX82PPbPhkf+wQgvGo4dj3xxOyg3bmfLjVvZcuNBQA7A6/k7RFt27mx+GP9WWYxde9rkekl+oZTTE56RxlHjtzvRc5oAFFCE4Dt16hQiIiIQHBycwUkEaBaicMCAAe7EDo4yoJTYWMSMGAmkpUEjNsaY/Z0mzluDJt34bylvaio0ycnQpBg/DsoU9AQff8T7BSLeN0AShXnCcuPc43TpBf0wIAceBmTP+BEv5biA7IjzDzb6chb3MDzsXfzNlmk9tzISVtauBOy9Ji802B/3nyZn1FHu9LCx9bBCmIUmPkKehEfIkxiHXElPJG9WSHI8sv/n2RL/Fl4uIfIkoZeaDB/ZE6PPqpni7YMU8YXN2wep3r5I9fJBmthE5yV+vJDm5Q0h/cT/5w0JQljOIJyIfYxkjReE9BNpnqV9ll6k9fP3RenwXDh16wniUzVSGdp0z/7t/d/fxG8vpHv/9//wzri3uTzJPn7ShowkH39kDwnGrG414BUYiHcWRuF6ggYJvgFI8vXXsxUh1nIH++H+U8vvLbFh5uu2r0jn9sq1EbsaJgtzOwKOGr/dCYRTBaA7gZFTV3czICEmhQjUJCXhwLlb+OTnffBLE16FVGmKxj8tBf5pqciWmigNTtnET0qi9P/af4upmBzJT5E78QlyJT1GQHqqHqpEHz/pm3pstlDp51a2UMQE58X9Fwph3YT28PX1yUgvBtGf9lyWdQ4qp2zkWKRnpLG0Js+aLxaGxMyFLBJfYNMePEBydDRO7z+JP9fvQ8EndxH+9J4k+HInPdErLsXLR/JkJQQGI1veUJx+6oUnwrvlFyR9sUr08ZeET6KvPxJ9nv1OkP7tDyGYnok8X6RKgu+Z2BMiy5j3y1TPi+dGXHLW+IkvaH3ql5DW+m4+FYsFe6KtWrdnjfVZUy8h0h88TTYpk8V6wT1DGkjiT3vJsRFr6su06iPgbuO3I3qAAlABVXc2ILmeN7N4NBpJKOZKfoJciU+QO+kxwuKfLdTOH3//2e+n96W1P+LyCgpCQPHiUvT3S6GFMf1WEA565Ua6mLI2cxmbOlbQbcyqAgKWdvbKXdtqDIV2mnD7By8h+dRJJJ46hcST4vdppN29m5HldlAu3MieDzHBeXA3MKe08eDZ7xDcC8yJJ35BkqD6tNGzUFdiravD1tkZNER3qtOaWHzaHf+iOEeubxSbMMTVb8URi9YoQtUs3BMtpdPdRGIpvqglG7F4YyZQNQF3Hr/t1TEUgApIurMByV17pwDPs6waDQZXzYf386ci6dx5JJ07h9tHT8Dn8kVp956YXj6buwiO5i2Bgy+8iIs5Cxj1cOgOTIrrxAJUTcDWWJWhCXGocOcCXrl7Ea/cvYDw+PsSJ5+8eRH4chncyFcUS+/644RXLkn0GU5ZGoMqTvPImyMAYTkCJS+WOG3DUMjI6QzdHbSWdtMaCiNrnnUxBa57trEQUTO2XcDCPZfx0IZzd021zRoPoNxj6uRwZBoS0BJw5/HbXr3oNAHYqFEji5G9xTm97nS5swFZWlBvz36Y+k555M8ZJMUb0wa1vf/gMUo+uIaXHlzBy/cuS4OumGa+H5ADB18ojT0FXsGhsNJIExteAOQ3GJjsWT+WpR4CcsIa6ba2yKNYvBZzEq/FnEDph9ekjy6HhONo3uKo+lZD1HnrdfiFhWWsK5MbxkSUY3iOrxBXb5QPx59HY6wOGK1dmyjKNYyXaew+uuf3Whu/U3e5hV02uugA132WxZ/NeUUNn3t69NTznLpCS9x5/LYXP6cJwCVLlqB///4oVqwYWrRoYbT+o0aNsle7nFKOuxuQqcXS9oZnuNDeWPliAX2Ze9Gocuu0FMG/yOPbiPPPhl0Fy2NL4cqSl3BEyzIZ3pSqkaF6a37sXWeW534EhEAYvOoYVkVdN1v57MnxeP16FBpfOYAScTcgNjsJ7/Pe8LKICislbWYSlxBCws72Xbwnee6UesC0nrmZ71VE7uAA6QuR1jM4bt0pPVFo7qQKQyH0atHcGecFi/KMPRvWeEW1MfKsFY6WLMbYlK2ld5D2DGI+75bo8nNrCbj7+G1te42ld5oAFDcfO3YsYmNjMWvWLHvUPcvLUIMBGVvnkzubL5JTNXiabN+zmWV3mEaDiEcxqH89CvWuH0a+hDiczVUYa4rXxq6Cr0iL4XmUk2yaHpFQ2PGQ1cfxMN70jlEROLj1hR2oc+OoFK5kf/4y2FyksuRpFiGQdC9tIGJDYSYHprkpWlPebEveLUufi3pZSiN3XaTWA2jN1LEcLqZ2WBt7B1nyasq5H9OQgDkCahi/lfawUwXgrl27pPN/P/nkE6X1don8ajEgw4EjXaNRFO/Pnp0j4pdVvnUGb13cjUp3zklTxL+WfB3rIl/TG7Tlhu+wZ91YlmsQsOTdEksMOpzdjFdvn8OtoFz4q1hNbC1cGQ8Dc5hsgPb0Cke10Jpd7XJ2tMpJY2l63FCcKtkoJsp6ISQAU96pgLtPkiRPpzkvnvYdpN19bMjd0oYPR/UTy1UvAbWM30p6yKkCUElFXTGvWg3Imhe/qXVN4pgpOfG7rOlXsV6rzYUdaHDtkBQMdtmLjfB30apSjDLdAUIcbi9CWWin2Dh9ZA1l90prbppS2EuXU+tRPfYULoYUwKqS9aQlBWJdaVZfco8ik3OaiWjLx0uiMoVJsWbK1VhaWz2Atoo1S1POXAuc1Varrvurdfy2ppcoAK2hZZBWrQZkzYt/1nsV0fyVApmmn2IfJeLTXyyHeLAFf8End9DxzCa8fv0wzucsiJnlW+NsaFFJBObM5odAXx+9kwDoHbSFsuvnMRVHUsSu/OD0RrS8tAe3s4ViUZmm2FmwvFVHhTm69XI8gHIEkfCyAV5WnXwh11toae2jvZ83ue8dOewc3X8s3/0JqHX8tqZn7CoADx06hHXr1qF69eoQZ/9qL3He74wZMxAdHY28efPi7bffxrhx45AzZ05r6upyadVqQJYGHm1HmPtGLvdlrqRTX7x/Bb2PrkaxuJvYEFEdP5ZtiURfMSDqX7Z6JJTUjXkdQ0B3qvCPIzf1TvEQd6wecwK9j/4unbyx+MUm+LN4LWnNqKtc1nix7PkMGTuD25SXXE78P3MedzmbUoz1x7i/TmL+f/H+zPWXXO+pq/Q56+GaBNQ6fltD224CUOzg/VKcXwtI4m7YsGHSv4XwE2v+vLy8ULJkSenM30uXLkkicffu3fAWZ9266aVmA7K0rkq3y4x9I3dWmBmxmL/lpf+hy6l1UhDebyq/h3O5ixgVgQwl46YP2n/VNidMAlKT8PGxNWhydT/+feElzCr/tuT9c6XL2i8i1izFsNROS6LJ0ho8w/Kt2dAhxwOv9H1jqf38nAQMCah5/Jbb23YRgDt27MDrr7+OEiVKYMyYMZL3L0+ePEhPT0d4eDju3r2LBQsW4MMPP5TqNWHCBAwfPhyLFi1Cp06d5NbV5dKp2YDEgNBnWRQ2nIi1yN3U4GIpxINuwdac+2msQmJaeNDBpZI3cFGZZlhVop7RgNK6gXm5NtBi17pMAnPx6Io+isHQA0ukk2dmv/I2NhWpYtVxabY00lIwZmNlyhFCuvkc6QHUvY8cj582fa4gP8zsWAnVi+XJFIZJznrFpmXDM6Gxx4yDLX3IPJ5NQM3jt9yetYsAbNeuHTZs2ICzZ8+iYMGCGffes2cPateujZdffhnHjx/P+Ls4UzMiIgJlypSR8rnrpVYDsmZAEH1nak2O3FMEdOOjjVt32ubjsnzS06S1X++c347thSpiWoV2Zk9rsHZAdlc7dfd6mxMIYsp38MGl0skcEyt3wtWQ/JmamzubH9q+WhA/7oo2eZ6stYzE2lcRyy82LkE6y9rcWbXmRJO5+1ryomt32oo1gLceJRptm6UpZ1sCPZvz+MfEJRptkr2Wi/BEIGstlelNEVDr+G1Nj9tFAArRV7lyZaxZs0bv3uPHj8eIESMwdOhQiH/rXh07dsSWLVtw69Yta+rrUmnVaEDWDAjmXurGRKQYCGuVzIuD0Q/0Fq3rxvSLvhuP77ack/rZmlMXdA2j1o2j+CxqBa7meAEjX+uGuADj4T5MBealZ9ClHjMY9YRpNHjr4i50P/EX9hQohymV2mcS+8H+PvioTjGUDMshBXK21Z4MaXzasBT6NSyZ8WdTnm5rp3yNUZdTtsgndgEbPjOW7i/X82ZYL2Mef7neSmPiUe5UtzgTeGSrl13LOFkbtyWgxvHb2s6wiwD09/fHRx99JK33072aNm2KzZs3S14+3U0hIk3fvn0xZ84cJCcnW1tnl0mvNgOyZkAwN7hYmgrSPQlBCL7l+6/qCcJc2fyQnJqOeAWBqIs9vIFxe3+Uzhr+osZHuB1sej2YYdBZEcLmyzfLSrubeTmHgLkgxoYCQcSG/Oj4n3jr0m78WrIeFpZpbnSHr/hisXNQfdT9ZrvVR6+ZarUoc8+QBkanPw2PaLOXh1nOrl05aQzbJFe0GeZTIuLsLR6dY528ixoJqG38tqWP7CIAQ0NDIc76/eWXXzLqkJKSAvH3xMRE3L9/Hzly6HthOnTogL///lv6zF0vtRmQNQOCqcHNkojU9RqKoK/G4pfZyx7yP72Hr/bMhV96KobU6okb2fNZVXSPOpEY2ryMVXmY2HoCxsSLrlf47uMkaZpVXEL89Tm6Gk2j/8XM8m9jfWQNszcUaz61eeXUTBsA2nCNn7EvPLYcySanDsbSWDrlQ+SRk0a3bLmeN20ee0zj2rJhzNI0tq1Mmc+zCaht/LalN+0iABs0aIAzZ87gwoULCAoKkuqxceNGNG/eHFWrVsW+ffv06paUlISiRYvipZdewvbt222pt0vkUZsByR0Q+rxeHJ82Km30LF65InJpt2r4fNVRu3lmTBlE7sRHmLjnBwSlJmFgrV64FZzHKtuZ9V4lNH8l88J1qwphYpME5C45EF5aTXo6+h75DU2u7MfUiu9gS9EqFsl+8FpR/Lz3isV0krgEMLtTJSmtJW+eLR43WZVwYiK5z6qWjfgt+JjbyBEbp2wtoriH7lS9pWlsJ+LirVRGQG3jty3dYxcB+Ntvv0FsBBHTvCNHjkRCQgJ69OiBy5cvY8qUKejfv39G3dLS0tCrVy/8+OOPmDdvHrp27WpLvV0ij9oMSO6AYC4QqzUicsb2i07pRyECv9k1Szr/dVDtXrgblEv2ffME+2P/Fw2Nil3ZhTChUQKWvMWGmbqd+AutL+yU1vttK/KqLKpyPYCin8e/XTZD3Jjzplla4mBKJMmqsBMTWdpkolsVOdPZctYrGhOP2vuoQVQ7sft4K4UE1DZ+24LDLgJQ3Fhs9Pj666+leH/StziNBuXLl8fevXsRGBgo/a1NmzaSNzAmJgZNmjRx6x3Aoj1qMyBLA4KcqRi5IrLP6yUwY/sFW2zWpjz54h/gm10z8dQvCJ/X7o0Ev2c2KefiyQNyKFmfRq6tiJLfvrADH534C7PLvSUFd7Z0aW11x8DXpTWApjxTohyx5nPf0Ibw9/W2OI1qSbTKeUYs1d2Zn1sK1dStZgQalslv9hxf3foqFXHWTmM7kxXvpS4Cahu/bekduwlAcfODBw9i9erV0ro+Mb37f//3fwgODs6ol6+vr3QSiPi78BSKzSPufKnRgJR+i5crIie3K4+OP/7r1O4XZ8N+u3MGTuWJwOhqXZAu80xYS0F0ndoIFd1MrrdY7Or+4sBirChVH4vKNM9EwNJ6Pbk2LUe8yBWt7vSlQU67rTE7ijhraDFtVhFQ4/htLUu7CkBLNxcBoYUAVMulVgNSOiDIGXAblcmPWl9vsxjzz5aAu+bsq+Ltc9Lu4LWRNTDnlbdkhQZxp8HcnZ4tOWIqIi4GU3dOx778L+Pryh31AjxbcxatJZuWO60rV7S625cGijZ3enJYV3sQUOv4bQ0buwjAsWPHWnPPjLRiuljECXTXS80GpHRAsDTgij63JBQ/qhOJP4/G6G0UMQzZkjPIF3EJqVaZUItLe9Dn2O+49ckX6Hw1t9m84n4zOnAjiFWAZSa25C3OnhyP6f9Mk0L5fFanj8mg3mJDkbe3F24/TkRYjkCT05WmbNqaaV1xfm6Hefqb2ow1l18aZBoBk5FAFhFQ8/gtF6ldBKCx83x11wIaVkZ8JtYIit9iU4i7XjQg8z0nR0RaEoqWQm2kazTWTyVrNBh0aBnq3j2Nbf2+xpSzKWYbot0dam4Bu7vacFbX2+QaNI0Go/ctwEv3r+CTev3M7t5W6m2T44kUnISoE0HCzXmu3W0NoJxnNKtthPcnAUcQ4PgtwmoJJabwunJFP8zCgwcPpF3BPj4+GD16NKpXry6tBRSbP3bt2oXJkydLx8OtWLEC2bNnV3j3rMtOA7IPeyWDkCUvkqkairAw3+/6Hi/kDMLvH43DwoOxJqeD3W1Qt0+vOK8UY18CWl7ag97Hfseo6l2xP7/5WIxKvW3WTuta8ly7yy5gS1++nGcBvBMJOJ8Ax287CUDDrhObPNauXYujR4/ihRdeyNSzYi1guXLl8MEHH0g7h931ogG5Rs9Z2sloqpZiU8j3/3wnrQecV+4Ni41RKjQs3sCDE+ieG53z1lVp6ndj0WqYXf5ts1REeJLdg+srCtNjjQfwteLP4ki6u3iSu+bRg02STVc5AY7fDhKA+fLlk4JAL1q0yKQJiaPj1q9fj+vXr7utmdGAXKfrjA3IcmrX+vw/6HZynXRSyPG8xc1mUTrVKKc+nppGK0h80lMx7Z9p8IIG/ev2Q7KPn0kk9pqat+RFNuUBVuK5zsp+tmbNo49YBMuLBFRIgOO3gwSgmNYVAnDlypUmzaZ9+/b4888/ER8fb3fTEsfQic0lS5YskULSiHiEYqOKOK7O3CXE6KBBg6Tzi4VxREZGonfv3tK5xcYuGpDdu05RgboDsu7xYeYKFcGhJ+6ejXwJD9Hr9c/MxgekB1BR95jMrCtI2p/dgk5nNqFf3X64mKugyTy5s/lhQutyRk+lsKWWapnWldN2WzyecsplGhJwJwIcvx0kAOvWrYv9+/dj586dqFIl83FNx44dQ40aNVChQgXs3r3b7jbTvXt3LFu2DKNGjULJkiWlM4pXrVol1Ufc19j19OlTSSiKU0yGDx8uhasReYSInT17Nnr27JkpGw3I7l1ntwIteXV0byTODJ69bTLWR7xmdCqYawDt1i1GC9IKkkKPb2PW9ilYXbwufno5c7w/kTlXkB+61IxAn/olFU37GquIu0/ryu0la9c8yi2X6UjAnQhw/HaQANyzZw/E+cBif0mnTp1Qu3ZtaS3gnTt38M8//0ibP8TuX+Fpq1Onjl1t5vz583jxxRfx/fffS0fOiUvUo2LFiggNDcW2bduM3m/x4sXSmkSxSaVWrecnDYi6izOOxQYWw4sGZNeus3th1qwNbHduGz48vRF96/XH5ZwFMurCs0jt3i2ZTtuIfZSIASuiMGn3bORKfIze9T8zOvVr7gxqe9XSXad1rWk/PYDW0GJatRLg+O0gASgM5n//+58kwIS3TxsSRivGChUqJJ0DLI6Ds/c1depUDBw4EGInco4cOTKKF169iRMn4uHDh0Z3Hg8YMECq0+PHj/WqJMoSu5bFxpU8eZ4tANdeNCB79579y5O7NtA3PRUztk/FU79A6ag4jZe3VBk5Z6Dav9bqLdFYf4ij2Cqe3ovPo1ZgUM2eOJ6vhFEAnIK3j11Y8o7T420fzizFtQlw/HagANR2/eHDh6Xp4Hv37iFbtmzS7t969epJIWIccQkvnhCfwmunewmvY4cOHSDqI6aeDa/Tp09LIk94/HQv8f8ijzAWw3iHNCBH9KD9yxQD3k97LmPcutNmCy979yK+2T0bc6u1R61PuuFhfDJCswcgf4jp4ML2r616SzS18zQoJRHztk7CiTzFMLFKp0wAKEjsbxOetObR/vRYohoIcPx2ggB0tqGIzSdCbP77r/45s3///TeaNm0qTUGLNYqWLrGRRGwI+e677ySP4qRJkzJl0RrQ/7d3HtBRFd8f/ybU0IsgVYgSBKS3H00QCFVBVKQqgoC0KE2qlIQmRekoTYqEroL03qRIjyAqLQEhEBACAZEEQvI/d/zvurvZTTZ5KfvefuccztHsm/fmfua+ne/emblz7do15MiRw/x5pkyZIP9YXIeAs+ueBp9YjpoRIejfYiSu/PNfikxGArX1ZXw7Tz/4bQveunQA3X2H4E6W3Fb5GDkFr417fLXdZc1jyhHknfVEICoqCvLPVGT8Llq0KCIiIqzGbz3ZpLWtyZIIWmsjkrO+7PSVjrUVgLLesHHjxioaaW9jimUbZLOIn58fzp49q6KGixcvtivoTALQtv2y+UQSYLO4DgFn1z21fyE92s3+FGt86mN56f+WKFCIaOtLR/xlA8783ZOxxqcBAks3QZ6sGRH+6In5YRTe2rgnVNsd1jwmxICfuwcBGZMDAgLiGEsBqJP+l+hd/fr1422tfB4aGorz589bXbd27Vq0adMGwcHBKr2LvSIpaUT4ieCTdYoS/XvnnXccPo8RQJ04DqA2HsR3hJdY8nz2jPDw8ETzI9+hRfAhfNhoGO5l/i+yy6nIpPe3owjsoBOAQIrXAAAgAElEQVQrUOHOJXT1HYKo9JmQM3N6fFjHG8Wfyxrvub5JbwlrkgAJuCMBRgDj9rquIoBhYWHYtm1bvL4rx9KNGzdObQKxPGZO8gDOmDEDt2/ftrv+MDo6Gg0aNFBpaT799FMVwZM1i/EVriHQ19dIQuue+vn6YNqui8j65DG+2fU5Dhcsh5mV3o1jJDcjJL7f7UUAiz24ia/2TMWcCm9hi/d/6ZmSK8Fz4lvJGiRAAu5CgOO3AdcABgUFqZQvCxcuRNeuXZUvy3o+2fhRtWpVh6eTLFq0SF0/d+5c9OjRw6l3gA7kFCaXuii+dU9R0THouypItfetS/vx4bnNal1aWFbr3d88ESTxXWovAjvy6BJ4R9zAR76DEe2Z3nxTRloTz5c1SIAEEkeA47cBBaC4QIcOHbBx40Y131+sWDHMmzdP7QwWcViixL8pJmR9n0wVy4YQLy8vtGjRQq0b/Pbbb+16kek6yw/pQIl74VzlakfrniyjVJmin2DRzs9xrEBpzKjUxqrpjAAmrSctdwGXvPcnZuyfiSmV22PPC1Xs3pCck8aZtUiABBImwPHboAIwMjISw4cPV6eBSF4/ifxJLj/LzR+dO3dW0cCQkBAUL14cZcuWxblz5xx6jek6CsCEXyy9XmEbpWp16QC6nttkjgIyMpW4nrUntHf+FoYBa37BkP3zUOCfcPRq8Cli/j/nou3dGWlNHG9eTQIk4DwBCkCDCkDnXUDblXQgbfxcsbblOsGMFlHAmf8fBfz6vcrJdv6sK9qfXG1yNNU+8vXSmL94Gz7fOgWTq3TA3qKVHT6SEcDk6g3ehwRIwJYAx28KQE1vBR1IEz6XrWwpXmQtYNdzmzHkbX983L4OxZ8TveYo4bNEUCWz4tDjgZAp4G6+QxDjaT8hfN6sGXHsM99kP+/XiebzEhIgATcgwPGbAlCTm9OBNOFz6cqm6cu//rqHl/q0R97W76DAsKFxzrGt7p2HIsWiJ+NL+CyXFfz7DhbsmoSvK7yFzRY7f22d4cPaxTGqxSsu7SNsHAmQgH4JcPymANTkvXQgTfh0U/n21GkIDwzEbv+FWHD6L9x//NTcdiYqtu7GhBJuf3J6Lf4X9hs6Nx6Op+kycPpXN28BG0oCxiLA8ZsCUJNH04E04dNFZYlozV93DLVHdsXS0k3xvY91InKeEGLdjWM3nsM3h67Y7ducUQ+xbPs4LCvVBGtLNnDY/yKqDw5pwMiqLt4QNpIE9EmA4zcFoCbPpQNpwufylWUt29AfzuL+P0/R79QaVLl9Hl0aD7PKWSdGcHfwv10pvHoGnnLYr+3O70LbC7vxfpOR+Dtj3CTrFNMu/0qwgSRgGAIcvykANTkzHUgTPpeubCtmXngQhnl7voh356o771pNaO1fuphnWLpjPI4WKINZFVvb7XtOp7v0K8HGkYChCHD8pgDU5NB0IE34XLayIzHz+cG5yBATjU/r+tltuzvnrUto7V+966cx9MRy9GwwEFdzFLTil8srA+Z0rIwaL+bltK/LvhVsGAkYiwDHbwpATR5NB9KEz2UrOxIztW6cxchjS9Hntf4IzlU4TvvdOQL4Y1Co+Rg9ex07df8sRKbPiOG17R+z6M7sXPZFYMNIwMAEOH5TAGpybzqQJnwuW9mRmPFU05gT1PFwttOYnh7A7PaV0by8dXTLZY1M5obFFwF86f51zN43HQH/64yfC5Zl9DSZ2fN2JEACiSfA8ZsCMPFeY1GDDqQJn8tWjk/MtP9jJ9pc3IP3mozCo4xeVjbIJgZ3PSnE9hg9SzB9fvkeNW7+hg8aD3eY+JkRQJd9HdgwEjAkAY7fFICaHJsOpAmfy1aOT8zkjnyAb7ePw4KyLbDhpVfjCMACbpzCxPIYPTnxQ0qm6Cgs3zYWP75YB8vKNI3T59xB7bKvARtGAoYmwPGbAlCTg9OBNOFz6cr2xIypwZ8dXYqCj+7Cr8EAuza4czTL9gxg3z+Po/+pNejSaBj+yppHHQVnKkz74tKvABtHAoYmwPGbAlCTg9OBNOFz+cq2YsbU4OphvyHg50Xwe60/LtvZDOLOu4GFkekYvdsPI/HimP7InjM7fuw4FIsPhfAUFZf3ejaQBNyDAMdvCkBNnk4H0oRPF5Utxcydh1EYu/l3yGYQOdHiQOEKmFe+VRw73DkCaAkj6vJlBL/+Br6u9yE25C5j/kjSvnSpXRx+DXyY9kUXbwEbSQLGI8DxmwJQk1fTgTTh011ly7WBXX7dhMZ/HsN7TUeZTwbhejbrLv150Chg+2a832QUnqZLz6lf3Xk8G0wCxiXA8ZsCUJN304E04dNlZdPawKL/fzLIuGqdcKhweXUcnBR33QVs25nRUU9w8n+1satwZSwo1zJOX1Ms69L92WgSMAwBjt8UgJqcmQ6kCZ9uK5vWBg7eMAkRGbPBv2ZX8Bgz6+48vnIjsgUMRu/6AxCSs5DDvuZ0uW5fAzacBHRNgOM3BaAmB6YDacKn68oyHRw0ZxG8vpqKB9/+gGpVSrr9ejbL9ZJZJwfg6cUL6NXgU8DDFB+N2+XuvmFG1y8BG08COibA8ZsCUJP70oE04dN95WcPHuBinVeRr39/5O3SWff2aDHAcsd05ugorNzqj5Uv+2JNyYbx3pYRQC3UWZcESCCpBDh+UwAm1XdUPTqQJnyGqHz944/xNOwWvNeuMYQ9STHCtC7SlOOv/rWTGHxyJT5oNBy3s+axe0uuAUwKadYhARJILgIcvykANfkSHUgTPkNUfrB1K0L7D0DxbdsQ9CwbJPdd/uyZUd07j1tMCZt2Rt+MiDT355jDC5AlOgqf1vVzKP7kA26YMcQrQCNIQJcEOH5TAGpyXDqQJnyGqBzz+DF+r1kL60o3wsJi9cw2ucumENtzk3NGPVRHv31dvhU2e9ey28fuwsYQDk4jSMCgBDh+UwBqcm06kCZ8hqgs05/B/Qai+IMw9G4w0GyTu6SFWXc6FP1XB5ntbnn5ILr/ugEdm47Gg0xZzX/3q/8SfJ7P7lbRUUM4OI0gAYMS4PhNAajJtelAmvDpvrJp+vOFP07C/+hi9GjwKf7MUcBKBBbImRkHhzQw5HSwiN/h684i/NFTs81fHpiFhxmyqNQ4loWbPXTv7jSABAxFgOM3BaAmh6YDacKn+8qm6c8Mz6KxfFsANnrXxrIyTePYZUTxY7vxQ4x+7vF9dUTelMrtseeFKooDN3vo3s1pAAkYkgDHbwpATY5NB9KET/eVfwwKRd9V/05/9ju1BmXvBqOb75A4ee+MluvO3sYPYdDy8k/o9usmtG/mj0cZvXg6iu49nAaQgHEJcPymANTk3XQgTfh0X9lyA0Sl2xcw4fB8+L3WD5dzFTH09Kftxg+TsZN/moPH6TNhdM1u6k95s2bE+LfKomnZgrrvaxpAAiRgLAIcvykANXk0HUgTPt1XNkXCwiIi4RnzTCU/tpwGNur0p2Xk09SJuSMfIHDbWMyo9C52FKuu/jytTQW8VdlaDOu+02kACZCAIQhw/KYA1OTIdCBN+AxR2bQWTozpf3IVSt6/hp4NBxl6+tNeBPD1kMPodWY92jcbjYcZ/939a8S1j4ZwWhpBAiTAgxxkjXZsbKwpgT9dIpEEKAATCcygl5uOQSv2xwmMProE3RoORkyRFzC6RRlDTn9aRj5NXx4TDs2D/PdntXtw44dB/ZxmkYCRCHD8pgDU5M90IE34DFFZxNCxkHCERTzG/XsPUX1AB0S1+wAVhvQ1ZOoXU6dtOXMTvVecUv+bM+pvLN82BnPKv4Vt3jXV33jKhyHcm0aQgGEJcPw2qAB8+vQpRo4cicDAQISHh6NChQoYM2YMGjVq5LQz37t3D2XLlkX9+vXVfewVOpDTOA15oSnyZ3kMWsDJZXgJj3B+1AzkyZYJBXIY71g4W7ubXDmKT4K+Q8emo+D1fD7DRj4N6cQ0igTclADHb4MKwO7du2PFihUYPXo0fHx8sHr1anz33Xc4cOAAatWyfzyV7TvQoUMHrFy5Eh07dqQAdNMviPjMtpcHT66vf+0UBp9cgfebjMAdr1zqFkY6+sye3f5HvkGW6EgMfrUPvupQCc3LF6LHkAAJkIBLE6AANKAAvHjxIkqVKoVZs2ahd+/eygFlmWOlSpWQJ08e7NmzJ0GnFLHYrVs3eHh44PXXX6cATJCYe13gKA+eUMj65LHaDbygXAtsfLGOGYzsCNb7tKg9uzNFR2HNltFYWrop1vm8BiOffOJeXk5rScDYBCgADSgAp02bhkGDBkGmcLNnz2724BEjRmDixIm4f/8+smXL5tCzb926paZ+J0+ejICAANSpU4cC0NjfA4m2zlEePNONxh5egPQx0RhWp5eVANS7OLJnd42bv/678cV3CEKz5VP2Lu/6P9T2eS7RXFmBBEiABFKLAAWgAQVgp06dcPjwYVy6dMnKj1atWoX27dvj9OnTqFixokMfe/PNNyFrCLds2YLixYtTAKbW26ij59jLg2fZ/GYhR9DnzDq0a+aPvzNmsbJMz6lR7NktJ6CUCQ/BR3ICyv+XXF4ZMPGdcobcAa0jN2VTSYAE4iFAAWhAAdi8eXPcvXsXR48eter67du3o2nTpti3bx/q1atn1y2WLFmCfv364dy5cyhcuLDTAvDatWvIkSOH+Z6ZMmWC/GMxJoGEIoB5H0cgcPtYTKzaEfuLVLKCoOdj4Wzt9oiNUcmf9xStjG/KtrCy0whT3sb0XlpFAu5JICoqCvLPVEQAFi1aFBEREVbjtzvRMVweQNnpKx1rKwB37tyJxo0b49ixY6hWrVqcPhYRV65cOUyfPh2dO3dWnzsbAbS9mWw+8ff3dyc/citb7eXBswUwa+80XMueH5OrdrT6qL9vSfT19dElL1u7Xw6/iukHZuHTOr1x7rkX4whAvU9567KT2GgSIAG7BGRMlmVdtoUCUCcOI9E7ScsSX5HPQ0NDcf78eavL1q5dizZt2iA4OBje3t5xbtGkSRM8e/YM69evN3/2yiuvoGbNmli4cCG8vLyQLl06q3qmEDIjgDpxoGRspqNdwKZHvP/7NrQIPqSmgWM8//MbvUfGLPP/ffDbVjQPOaJO/7C00RKznqe8k9FdeCsSIIE0JsAIYNwO0FUEMCwsDNu2bYvXja5evYpx48apTSCWmz0kD+CMGTNw+/btOEJObpgrVy4VCnZU1q1bh1atWtkVgO78CyKN3+k0fby9PICmBpW89ydm7J8ZJzqm5/OBbe39as+XuJyzEL6s0t5hP+h5yjtNnYsPJwESSFECXANowDWAQUFBKuWLRO26du2qHEg2dcjGj6pVq2Lp0qV2nernn39GdHS01Wfvvvsuypcvr5JKlylTRqWRsSx0oBR9P3Vxc9NJIDt/C8P6oBsIf/REtVvWx8npGLteqIpFr7wRxxa9RcZsI575H4Vj6c4JGF/tfRwsXMFhX+nNTl04HRtJAiSgmQDHbwMKQPEKSeK8ceNGNd9frFgxzJs3T+0MFnFYokQJ5Thnz55VU8WyIUSmd+0VZ9cAMgKo+V00xA1EDE7beQGz9/67A73/qdV4+d6f6NlwUBz79BQZs5f/r+Xlg+j260a0ax6AfzJkjmOfniOdhnBGGkECJBAvAQpAgwrAyMhIDB8+XJ0G8vDhQxX5++KLL6w2f8hGD4kGhoSEqM0eFID8tkgOApY7ZWvdOIuRx5aiS6NhCMua1+r2eoqM2dv1PP7QfGXPZ7U/siv+5I96T3ydHP7Ae5AACbgmAQpAgwrA1HI3OlBqkdbPcyx3ymZ+GonVW0ZjYdkW2PDSv6eC6DEyZpv/z8uOXZY9ZKSj7/TjeWwpCZBAYghw/KYATIy/xLmWDqQJn2Erm9bLiYHjDs1HrAcwotZHSvzpMTJmGwE0nf7xYaOhuJn1vxM//OqXQO0Sz6G6dx6k8zRZa9hupmEkQAI6JsDxmwJQk/vSgTThM3Rl047Zaqd2otu5TWjbLAC5nsuF0S3K6O6EDNv8f35B36PiXxfRrdFQ3UY1De18NI4ESCBBAhy/KQATdJL4LqADacJn+MoinE4cPosc3dri0fDxqPTeW7qNjJmjmrGxWLxjAn4u+Armlm+l26im4Z2PBpIACcRLgOM3BaCmV4QOpAmf21S+3Kw5slStioJjx+jWZhGzs/dcwvatP+PLzRMwqkZXHC9QGlzvp9suZcNJwK0JcPymANT0AtCBNOFzm8phEybg4c5dKLFnNzw89Lc2zjIBdKtLB9Dlty3o/s7n6FivJPwa+Og2quk2DkhDSYAE4hDg+E0BqOm1oANpwuc2lR/sP4DQHj1w5ctvkKvUy7raJGGbAHrc4X/Tv4ys9W/6F6Z6cRs3pqEkYCgCHL8pADU5NB1IEz63qCwCasK6IMxcORhLyjTH+hJ1dTNtapsAOlP0E6zZMgqL/98OPaa0cQuno5EkQAIJEuD4TQGYoJPEdwEdSBM+w1e2jJ6ZImd6Sgdjm/6lWtjvGPPzN+jecDCuZ89v7j89JbU2vNPRQBIgAacIcPymAHTKURxdRAfShM/QlW2jZ6a1c22aj0FU+oy6SAg9duM5fHPoirmfep5Zjxo3z6Fz4+GAxVpGPR1rZ2ino3EkQAJOE+D4TQHotLPYu5AOpAmfoSvbRs+KPryF+bunYGTNrjjxfGmXj55J9LJn4CmrPlq4cyKC8pXA7Iqtrf7OCKChXZnGkYAhCXD8pgDU5Nh0IE34DF3Z9vg0xMZiyY7xOFKwLOaVb2W23RWjZ7bRS2lswb/vYNGuiQj4X2f8XLCsaj/XABrahWkcCRiaAMdvCkBNDk4H0oTP0JVtI4Bi7MdB36H8ncvo7jvEbPvI10ujc21vl0qlYq/tLYIPovvZjWjbPACPM2Q2t3/ue5V1d7KJoR2PxpEACThFgOM3BaBTjuLoIjqQJnyGrmx7fJoYW+vGWYw8thRdGg1DWNa8ZvtdLZlynOglAP8j3yDTsycYVqeXud0f1i6OUS1eMXQ/0jgSIAFjEuD4TQGoybPpQJrwGb6y+fg0ALEAsjx9jNVbRqsj1DZ71zLbb0oN7So59WwjgBmePVXpX5aXaozvfOqb2821f4Z3YRpIAoYlwPGbAlCTc9OBNOFzi8qWp2iIwZN/+gp/Z/DCmBpdrOx3pfV0ttHLSrcvYMLh+ehVfwCu5CzEtX9u4bk0kgSMTYDjNwWgJg+nA2nC5zaVRVAtORSCsZt/R5sLu9H2wh61li7aM30cBq4SVbOMXnY9uwH1QoPwfpOR5qPsXCVa6TZORENJgASSlQDHbwpATQ5FB9KEz60qm9bVvXQ/FLP3TcPg2j1xNl+JOAzSalewiNRjIeG4/TAS+bNnRpViufH1vstYfCgEkzaNx++5i2N65Ta6OcXErZyLxpIACSSaAMdvCsBEO41lBTqQJnxuVXnGrguYtusiPGJjELhtLHa9UBWLX3ndJSKAttPU0ihPDyAmFsj/TziW7piA6bU7o0z7t+DXwMeldiy7lRPRWBIggWQjwPGbAlCTM9GBNOFzm8q2SZUHnlwJ74ib8GswwMwgrdYAWh5XZ69DmoUcQZ8z69CuWQAeZfQCp37dxm1pKAkYmgDHbwpATQ5OB9KEzy0q20uqXO/6aQw9sRwdm4xEuFdOxUEEYGqLK3tts+2UkUeXIGfU3/i0rh83f7iFx9JIEnAPAhy/KQA1eTodSBM+t6hsL6lyjqhHWLnVH9MrvYudxaorDv19S6Kvr0+qMrHXNssGpI+JVmlr1vrUx6qXfc0fucpGlVSFxYeRAAkYigDHbwpATQ5NB9KEzy0q20uqLIZP2z8Dt7LkwcRq7ysOabH5w1HbTB1T7s5lTD74NT5+rR8u5Spi7q+0aKtbOAuNJAESSDUCHL8pADU5Gx1IEz63qOwoyvbe79vRMvgg2jXzR4xnOqRFVC2hCGDnc1vQ5OpRdGg2GrEenowAuoXH0kgScA8CHL8pADV5Oh1IEz63qGzvSDgxvFT4VUw7MAsDX/XDvRdL4eCQBqm+u9ZR20wdM3vvVFzJXgBfVO2g/pRWG1XcwlFoJAmQQKoS4PhNAajJ4ehAmvC5TWXbI+HEcM/YGKzc4q+OhKs1YTiali2YJjzstU0akjvyAVZsG4PJVTpgb9HKSvxJSe2NKmkChQ8lARIwPAGO3xSAmpycDqQJn1tVtpdrzz9oJSp6PkTFLT+mKQt7bWv053H0O7VGTf9GZMrGBNBp2kN8OAmQQHIT4PhNAajJp+hAmvC5XWXb0zZKnfkJYcOGwefQQaTPmzdNeZjaFhbxGOGPnuCVRVOQ7kYork/8GgVyZEZ17zypPkWdpkD4cBIgAUMT4PhNAajJwelAmvC5feXoO3dwsc6rKDRpInK++Waa8zBFAm/d/0dNT2/yroVdNVthdIsyaTZFneZQ2AASIAFDEuD4TQGoybHpQJrwuX1libr91qIV/nm+MGI+G5umUTbLE0FeDr+K6QdmYcCrfvgjb3HVT1z75/buSgAkYCgCHL8pADU5NB1IEz63rmyKtjU6sg7NrxxBh2b+yJElE7rULp7q5+3angjS4Y8daHX5J3OKGu7+dWtXpfEkYEgCHL8pADU5Nh1IEz63rWwZbStzNwRf/jQH/ep+jPN5iikmubJkwMS3y6XatKttPsCp+2fhL6+c+Lx6J6s+SotchW7rJDScBEggRQlw/KYA1ORgdCBN+Nyysm20zTPmGVZt9cePL9bB8tJNzExS82xgyxNBsj95pNb/zaz0Lnb8/zF1pkbxBBC3dFkaTQKGJMDx26AC8OnTpxg5ciQCAwMRHh6OChUqYMyYMWjUqFGCjjx37lzMmDEDwcHByJs3L95++21MmTIFXl5ecerSgRLEyQtsCNg7fWPYsW+R//E99K/X1+rqgjkzp0qCaMs21b0ehGEnAvFek5G465WTEUB6MAmQgCEJcPw2qADs3r07VqxYgdGjR8PHxwerV6/Gd999hwMHDqBWrVoOnVmE3tChQ9G3b1+8+uqrOHnyJCZPngw/Pz9MnTqVAtCQXwOpa5S983cbXT2GfqfXon0zfzzIlDXVRZfliSD9Tq2Cz/1Q9G4w0CoaWSCVxGjq9gafRgIk4K4EKAANKAAvXryIUqVKYdasWejdu7fy7djYWFSqVAl58uTBnj177Pr73bt3UaxYMfTp0weTJk0yX/PZZ59hw4YNOHv2LAWgu35TJKPd9iKAplM3JlXpgH1FK1s9LbWmXdW6xGUnEbhtDHYXrYJFZd9Q7eAJIMnY+bwVCZCAyxCgADSgAJw2bRoGDRqEe/fuIXv27GZnGzFiBCZOnIj79+8jW7ZscZxw2bJl6NSpE65du4YiRYogOjoa6dOnj9dZ6UAu8y7rpiG2awBNDZ+9Zyqu5Pjv3F3T3/s29EH/RiVTxb7dGw6g0OAeGFq7B37J56OeKdPQzAOYKvj5EBIggVQkwPHbgAJQRNzhw4dx6dIlK1datWoV2rdvj9OnT6NixYpx3EwifyIC5Z8ISIkkFipUCD169FDTwhkzZmQEMBVfTiM/SqJtPQNPWZnY+dwWNLl6VB29Fuvhaf7M0wOY3b4ympdP+bOC/5ozB+GLlyA8cCNuRz5D/uw8AcTIfkjbSMCdCVAAGlAANm/eHDKde/ToUSvf3r59O5o2bYp9+/ahXr16cfxeNnts3boVWbNmxbBhw1CmTBns3bsXX3zxBTp37oxFixY5FIASNcyRI4f580yZMkH+sZCAIwIiAgeu/QWPop6pS8reuYwpB7/GJ/X64mLuonGqzX2vcoqnhQlp/S4yFC2CItOmseNIgARIwFAEoqKiIP9MRQRg0aJFERERYTV+G8roBIzxiJUFcgYqstNXOtZWAO7cuRONGzfGsWPHUK1atTgW+/r6Yvfu3ZBIYdu2bc2fd+3aFUuWLMHt27fVrmDLYvoFYXsz2Xzi7+9vIKo0JSUIrDsdiv6rg9St08U8w+oto/FDibpYUapxnMel9I7gp7du41K9eig0eRJytmyZEubyniRAAiSQZgRkTA4ICIjzfArANOuSxD1Yonf169ePt5J8HhoaivPnz1tdt3btWrRp00ald/H29o5zjxYtWmDTpk1qjWDOnP+lv/j+++/RunVrHDlyBDVq1LArABkBTFw/8up/CdhuCBl6fBkKPrqLvq/1s4soJRMx31uzBmH+AfA5dBDpc+dmF5EACZCAoQgwAhi3O3UVAQwLC8O2bdvidcqrV69i3LhxahOI5WYPyQMo+f0kkpcuXbo49/jkk0/UzmH5PF++fObPTWsHf/nlF5QvX96uAHTnXxCG+oZIZWNsN4S8du0UhpxcgfebjMAdr1xxWtOs7PNqGjgl1uZd690Hzx5EoHhgYCpT4ONIgARIIPUJcA2gAdcABgUFqZQvCxcuhEzfSpHE0LLxo2rVqli6dKldT5Pon0QBZ8+erVLBmIpMB0v+wOvXr8cRjnSg1H9pjfZEyw0hWZ88xqqtozG33JvY/GLteE1Njt25IkCPhYTjr7sRKNH9beTz80O+7t2Mhpj2kAAJkEAcAhy/DSgApZc7dOiAjRs3qvl+ye03b948tTNYxGGJEiWUI0heP5kqlg0hcspHTEwMmjRposTe4MGD1ekhO3bswIIFC5RolN3FtoUOxG+V5CCw5cwN+K08jZhYYPyheSr73me1P4r31lrz84nwDNj4G25GRKJa2G8Y8/MifPbmCHz0foMU32ySHMx4DxIgARLQQoDjt0EFYGRkJIYPH65OA3n48KGK/MluXsvNH7KzV4RdSEgIihcvrvzo8ePH6gi55cuXqyPkJKG0pICR9DH2Ch1Iy+vHupYEtpy5id4rTqFF8EF0P7sR7Zr7458McY8ftKwjIjApJ3SopM+Bp2Da/eUX9B0q/XUR3XyHAh4e+DoVdhyz90mABEggLQlw/DaoAEwtp6IDpRZp93jO2I3nsGHnaQP0gOYAAB/uSURBVHy7YzwmVu2I/UUqOWV4YjaH2K479IiNwbfbx+OnwuUxv9yb6uSPpIhKpxrKi0iABEjARQhw/KYA1OSKdCBN+FjZhoBpV/DMvdMQmi0fJlV7zylGiTkuznbncanwq5h2YBYG1+mFs8+9ZH5eYkSlU43kRSRAAiTgQgQ4flMAanJHOpAmfKxsQ8AUnat/dAPevnRATQNHe8Z/HKHcIjFi7cegUPRd9W/uQSndzm5A/eun8X7TkYixOIEkMaKSHUkCJEACeiPA8ZsCUJPP0oE04WNlOwRkfd7kOZswZ+9UfFazO049/7JDTkmZrrWKAMbGYsmO8TheoDTmVHjH6jmJEZXsSBIgARLQGwGO3xSAmnyWDqQJHys7ILDt7A1k/rAdgnJ7Y3rlNnavSuouYMsdxyXv/YkZ+2diSO2eOJPv393xUlL61BF2PAmQAAmkNQGO3xSAmnyQDqQJHyvHQ+DW9Bm4uywQl+auQUhENFYe+xNhDyKtRNroFmUSlbLFdvfvh79uQqM/j6Nj01GI8fwvOXqPut4Y1rwM+4cESIAEDEuA4zcFoCbnpgNpwsfK8RCIunQJwW+0QJGv5iB7gwYwJW2+/TAySSeB2O7+RWwsFu+cgJP5X8bsiq2tWiLRRaaCoXuSAAkYmQDHbwpATf5NB9KEj5UTIBDc8k1kKlEChad+qZmV7e5f0/Tv8Fof4XT+knEEIFPBaEbOG5AACbgwAY7fFICa3JMOpAkfKydA4M68+bgzdy5KHjoIzyxZNPGy3f3b48x61A39RZ07bDn9a/kQbgTRhJyVSYAEXJgAx28KQE3uSQfShI+VEyDw5No1XG7UWEUAczRvbvdqZ6eGLSOA6WKeYfm2Mdj1QlUsLNvCYSuYCoYuSgIkYFQCHL8pADX5Nh1IEz5WdoLAlbbt4JkrJ16YJ2cEWxfL83xNn8gOXnubQ0xrAMMiIlH95jn4H12MXvUH4ErOQg5bwQigEx3ES0iABHRJgOM3BaAmx6UDacLHyk4QuLdmDcL8A1Bi9y5kKFjQXMN2R6/pg/jSw5jqDDv2LQr9fQd+DQbYbUFS8gs6YQovIQESIAGXIcDxmwJQkzPSgTThY2UnCDz7+xEu1q2LvF0/RL4+fVSNODt6be4Tn4Dbceg3FOjeFovLNMO6EvXitCCp+QWdMIWXkAAJkIDLEOD4TQGoyRnpQJrwsbKTBG6MGIFHhw+jxM6d8EiXDrY7eh3dxt4UrtpY8tVXuL90HXZc+wfrg24g/NET8y0cTSE72VReRgIkQAK6IMDxmwJQk6PSgTThY2UnCEi07+TWA8g+sCf+Hj0Zldu+gU1nblid5+voNrabOGKfPcOlRo2QtUZNFJow3hxNPBYSjqTmF3TCBF5CAiRAAi5HgOM3BaAmp6QDacLHygkQMG/yuP8YM/bPwD/pM2Pm6/3QrlpRTNt1MUF+thHAh3v24HrvPii+di28ypVNsD4vIAESIAGjEuD4TQGoybfpQJrwsXI8BGw3ebwaGoThxwPx8Wv9cClXEeTKkgER/zxFrJ17OFoDePW99xHz9Am8V68mexIgARJwawIcvykANb0AdCBN+FjZAQF7mzw8Y57hm10T8Xue4phctSOyZEyHf548g4g9SxHoaBPHo2PH8GenD8xHyxE+CZAACbgzAY7fFICa/J8OpAkfKzsg4GiTR4vgg+hx5kf0avgprmV/XtX29ABiLBSg5SYOyyTR3p8PQbbIv+G9fh08PEwykV1AAiRAAu5JgOM3BaAmz6cDacLHyg4I2B7bZrosw7NozNs9GVdzFEBAjQ+tanetXRy+ZQqguncepPP0gGWS6LJ3LmPKwa8x+7VuaOHXAU3L/pdPkJ1AAiRAAu5IgOM3BaAmv6cDacLHyomMAMrlda8HYdiJQAyp3RNn8pVQd7Bd82e5ftAzNgYz907H03TpMLDux4j18MTX71WmCKT3kQAJuDUBjt8UgJpeADqQJnys7ICA5bFtcTZ5xMZi6oHZyBr9GB+/1h9P0mUw38WvfgnUfDEvBq79BWEPItXfW106gB6/bkDfep/gQu4X1N8K5MiEQ0MbqkghCwmQAAm4IwGO3xSAmvyeDqQJHyvHQ8AUxZNLbEXgCw/CMGvfdGwpXgPzyrdyeJfiETcwY/9Mu9f19y2Jvr4+7AMSIAEScEsCHL8pADU5Ph1IEz5WToCA5To+20tbXj6IXmfXY2aFd7DVu2acO+V9HIEvD8zCowxe6FfvEzy1iBSaLp7LqWD6IAmQgJsS4PhNAajJ9elAmvCxshMEZDr458t30WfFKdx//PS/GrGx6HVmPVqGHMLS0k2x1qc+nnmmU5/73LuG4ce/hWdsLAbW9cMdr1x2n8SpYCc6gJeQAAkYkgDHbwpATY5NB9KEj5UTQcA2MbSqGhuLDud34v0/duCWV26cy+uNvJERqHDnMi7kKoLx1TvhdpY88T6FU8GJ6AReSgIkYBgCHL8pADU5Mx1IEz5WTiSBLWduwG/laau8f3KL4hE30SLkEIo9CMPDjFlwuGBZ7C1aGdGe6Z16AqeCncLEi0iABAxEgOM3BaAmd6YDacLHyokk4ChBdCJvE+dySR59cEgD7grWCpL1SYAEdEOA4zcFoCZnpQNpwsfKiSTgKEG0o9vYnhIS3+NWdq+Bmi/lTWSLeDkJkAAJ6JMAx28KQE2eSwfShI+VE0kgMRFAyfD3UV1vzDsQ4tRTZrSriDcrFnbqWl5EAiRAAnonwPGbAlCTD9OBNOFj5UQSiDdBtMW9ZHdv++ovoPhzWfHThTv47tT1BJ/ECGCCiHgBCZCAgQhw/KYA1OTOdCBN+Fg5CQTiSxAtt3ujfEGcuHLPfBKI/C2+qWDbY+SS0CRWIQESIAHdEeD4bVAB+PTpU4wcORKBgYEIDw9HhQoVMGbMGDRq1CheJ71y5QoGDx6MgwcP4tGjRyhbtiwCAgLg6+trtx4dSHfvvCEabC9BtGzkaFmhIOYfCIlzcogjo00HwfFsYEO4BY0gARJIBAGO3wYVgN27d8eKFSswevRo+Pj4YPXq1fjuu+9w4MAB1KpVy6GYK1euHLJmzapEYObMmbFw4ULs27cPe/bsQd26dePUowMl4m3jpclKQKaDj4WE4/bDSOTPnhlViuVG3cl7rSJ/tg+0jQSKaBzdogyali2YrG3jzUiABEjA1Qlw/DagALx48SJKlSqFWbNmoXfv3soHY2NjUalSJeTJk0eJOXtl2bJl6NSpE86cOQMRglKioqJQvHhxNGzYUEUTbQsdyNVfcfdp34xdFzBt18UEDR75emk8lz2TEo3VvfMw9UuCxHgBCZCAEQlw/DagAJw2bRoGDRqEe/fuIXv27Ga/HTFiBCZOnIj79+8jW7ZscfxZ6g0YMABhYWF4/vnnzZ+XKFFCTSF///33FIBG/BYwgE0yJdwz8JRTlnC3r1OYeBEJkIDBCVAAGlAAShTv8OHDuHTpkpX7rlq1Cu3bt8fp06dRsWLFOK4tkcPy5cujcePGmDRpkhKPs2fPVqJRxN/bb79NAWjwLwQ9mmfaGXwzItKp5nO3r1OYeBEJkIDBCVAAGlAANm/eHHfv3sXRo0et3Hf79u1o2rSpWtNXr149u65tmga2/LB169ZYu3at3etNDnTt2jXkyJHDfE2mTJkg/1hIIKUJJCY3IE/8SOne4P1JgARclYAs6ZJ/piLjd9GiRREREWE1frtq+1OiXR6xskDOQEV2+krH2grAnTt3qujesWPHUK1atTgWHzp0SK31k+lemQqWaeIff/wRCxYsUDuBR40a5TACaPuBbD7x9/c3EFWa4qoEEnM6CM/8ddVeZLtIgARSmoCMyTKW2xYKwJQmn0z3l+hd/fr1472bfB4aGorz589bXSdRvDZt2iA4OBje3t5x7iHRQRGNkgomZ86c5s/btWuHDRs24OHDh0iXLp1VPUYAk6ljeZskE3A2AtjftyT6+vok+TmsSAIkQAJ6JsAIYNze01UEUDZobNu2LV4fvHr1KsaNG6c2gVhu9pA8gDNmzMDt27fjCDm54csvv6zCwMePH7e6v9Tp168fbt68iQIFCtgVgO78C0LPXwhGaLszp4PIySCHhjbkjl8jdDhtIAESSBYCXANowDWAQUFBKuWL5PDr2rWrchRJDC0bP6pWrYqlS5fadR6JAMo0cEhICJ577jnzNbKpZMuWLbh165bDCCAFYLK8j7xJEgk4Oh2EiZ6TCJTVSIAEDE+AAtCAAlC8tkOHDti4caOa7y9WrBjmzZundgaLOJS0LlLOnj2rpoplQ4iXlxf27t2r1ghKJLBv374qZ+COHTswf/58TJ8+Xf3NttCBDP8doRsDHZ0OwkTPuulCNpQESCAVCXD8NqgAjIyMxPDhw9VpILJ2TyJ/X3zxhdXmj86dO6tooET8JNmzlJMnT2Ls2LFqLaAcIWcSg6ZIIgVgKr6dfFSiCdieDsJEz4lGyAokQAJuQoAC0KACMLX8lw6UWqT5HBIgARIgARJIPgIcvykANXkTHUgTPlYmARIgARIggTQhwPGbAlCT49GBNOFjZRIgARIgARJIEwIcvykANTkeHUgTPlYmARIgARIggTQhwPGbAlCT49GBNOFjZRIgARIgARJIEwIcvykANTkeHUgTPlYmARIgARIggTQhwPGbAlCT49GBNOFjZRIgARIgARJIEwIcvykANTmekRxIzkn8/PPPMWzYMGTKlEkTF1esTPtcsVcS1yb2YeJ4ueLV7ENX7BXn22Sk/jPS+O18D1pfqauzgJNqZErVM5IDGckWe/1N+1LqLUi9+7IPU491Sj2JfZhSZFPnvkbqPyPZktTepwBMKjkARnIgI9lCAZhDg1e7blX6qOv2jbMtYx86S8o1rzNS/xnJlqR6CwVgUslRAGogl/pVjf6yG90+8Rij22h0+9iHqf+9l9xPNJKPGsmWpPYzBWBSyQGIiIhArly5cO3aNeTIoe+oi7wMRYsWNYQtjiKAtE+Ds7tAVfqoC3SCxiawDzUCTOPqRuo/ky33799Hzpw505hs2jyeAlAD9+vXryvRxEICJEACJEACJKA/AhLAKVKkiP4angwtpgDUADEmJgY3btxA9uzZ4eHhoeFOrEoCJEACJEACJJBaBGJjY/Hw4UMUKlQInp6eqfVYl3oOBaBLdQcbQwIkQAIkQAIkQAIpT4ACMOUZ8wkkQAIkQAIkQAIk4FIEKABdqjvYGBIgARIgARIgARJIeQIUgCnPWLdPePLkCapVq6bWOB48eFC3dlg2/N69e+q0kw0bNuDu3btq/UenTp0watQopEuXTpc2Ll26FBMnTsSVK1fwwgsvwM/PDx9//LEubbHX6GfPnuHLL7/EN998o2yUHXvNmjXDF198gXz58hnGTpMhvXr1wty5c/H06VOkT5/eMPYFBQVh6NCh+PnnnyF9Kt8tU6dORcWKFXVvo/SV+Ki8i3/++ScKFy6M9957D0OGDNH9yUrz5s3D2LFjIZseLYv046BBg3Dq1CmVBePdd99Vp0llzZpV9/3pLgZQALpLTyfBzuHDh6sXunbt2oYQgLLoV2z57bffMHLkSHh7e2Pnzp2QL7jBgwcrEaW3EhgYiPfffx89e/ZEkyZN1JfxhAkTMH78eDX4GKGIYJ80aRI++eQTvPbaa6r/xC/LlSuHQ4cOGWoD1o4dO1Q/SjGSALxw4QL+97//oUyZMurHyaNHj9T7FhkZiT/++EP3oqF///74+uuv1Y9L8cvjx4+rHyidO3fGggULdPsaiuhr0KAB/vnnHysBKH0mAr569eqQHyx//fUX/P39UaVKFWzZskW39rpbwykA3a3HnbT36NGjarDNkyePEkpGiAD+9NNPqFu3LpYtW6Z+nZuK/PfatWtx584dFe3US5Fd6NI3MrCuWbPG3Oy+ffti8eLFuHnzpu4H1sePHyN//vxo27YtFi5caLZR/rt79+7Ytm2bWTDppd8ctVPykYl4kEj01atXDSUA27dvjyNHjuD333+Hl5eXQnDmzBk0btwYK1asUCJDryU6OhrZsmVDnz59VBTQVAYMGIBZs2apBOYmm/Vi4969eyHfI/JjS6K1EtG0jADKj84DBw7g/PnzyJw5szJr3bp1ePvtt7F//371Pcvi+gQoAF2/j1K9hTLoyrRMu3bt1MssX3BGEIAzZ85UX2rya/W5554zc50zZ46aNj1x4oT6BauXcvr0aVSuXBmbN29G8+bNzc3etWsXGjVqpH6Jy1SpnouIhAoVKiiB3rp1a7Mp586dQ9myZVWUZeDAgXo20dx2GVQlJ1m9evUwZswYwwhAWUoiCfNlRmHEiBGQHy6SNssoqbNkWYn8UJaIpmXUfdy4cWqmQQSgnn5YikPK+7Vx40blm/Lu3bp1yywApf/k+7Nbt26YPHmy2X8lSpg7d27069dPRexZXJ8ABaDr91Gqt1BEkgg/mcYQIWEUARgSEoLLly+jYcOGVoOPDLwylSpfchJt0ktZtGgRunbtqkSDZSLTsLAwFCxYENOmTVNfxnouEhUTYS5CVwZZU5H1gDIArV69Gm3atNGzieboifihCN5vv/0WAQEBhhGA8j0iU4XyA0yWXGzdulWti5Oon/joSy+9pPv+8/X1xa+//oolS5aoH5His9KfsuTkxx9/1LV9Mo0tPypNEcDg4GDVZ7YzKWJkqVKl1L/169fr2mZ3aTwFoLv0tJN2Sui/adOmkClgiQLKNLBRBKAtAlkTKFM2spBZFjBbTqM6iStNL5Nf3xJxkF/ellNMUVFRalpG1uSMHj06TduYEg+XwUiigRJtkEFX74vOJSL9yiuvqL6SaUTpNyMJQNlw9eabb6p+euuttyDTwfIjRaJj8t0i0SbLiHxK+ExK31OWW4jItZwmzZs3r1qTKxuz9FxsBeCxY8fUshN7Mww1a9ZU3z0yjrC4PgEKQNfvo1RroWRFlzVI8sLLICTFqAJQIi0y7SvrAiUiKNMcIij0VGSjh0yp2QpA2TyQMWNGNT0j4tYoRYSSLLKXyGexYsVUZKV8+fK6N0/WTck04p49e1Rk2mgC0LRRSX5YSvTPVExrcmUnsGyi0GuRH1wS6bt06ZJ6H8UnZa2jTAGLsJXdzxLx1GuxFYCy8apOnTp2BaBwkOl+WZbC4voEKABdv4+SpYX79u1D/fr1472XTMnIL1l5wTNkyKCulTVksghYdifKl5jp78nSqGS8iTP2yYAjv1DlS3rKlCkqnYiIqB49euhyPdJXX32lIkZyHKFM+ZqKCCWZyhah1KVLl2SknHa3WrVqFXr37q2ObhLhLmkpZOG93svKlSvVNL5E3GVDjxTZxS27nGX6W9450yJ7vdr6/fffq4jt9OnT1RpcyyLpQzp06KDS3ui1iG9KVFNSwEhKKVORDUry/bl8+XJlo16LrQCUjSESsZbNO2K3ZZG/V61aVbFgcX0CFICu30fJ0kKZcpEvpPiKRIzkl6uj4sprypyxTzZKyJo4GXQ/+OADlYPMcl1ZsoBOxZvIOk2J0EpURaIrpiK782QjgWwSMUKONUnTI2luZNpJRK2kEjFKEX+cMWOGQ3Nk6lTv66lkGlTWxdlGpGUJRpYsWVQaEXkX9VpErMsGF1mOIALIVCIiIlQ0TD6X/Id6LbYCUCKeYpeIecvUWbLZR35Ui716X3us175KbLspABNLzMDXy1TF33//bWWh5OySCKBEm1588UWVOFmvRabYZLpXvozlS0rvRb5wZfOH5I2TBdmmIulRJGIrqUT0XiTiJ9FNERCygUCmto1UZGNSaGiolUkiciWNj0S1JZJbunRpXZss6/yKFi2q/kmk07T7V364yI+yTZs24fXXX9etjaYIoEQxZTbBVEzfNyLgRcjrtdgKQLGjVatWOHv2rAoYmN5JiXTKxpeLFy8aYmOPXvsrMe2mAEwMLTe81khrAEXMzp8/X232sLcmRxZx6y0iKPbIoCO/xqWvdu/eDUlrI1/GttMzenRf0/ShRBokHYxtKVGiBOSfkYrR1gBK38jOZom6y5SoiARZpiAbXSpVqqSEvZ5Twkgya5n2FDEvKYnEJvlviXiK6JUTM/R6ypD0nT0BKGuo5ftSvnPkB6fYK/0pU90SsWfRBwEKQH30U5q10kgC8I033oh3cbLsXBN79VbkC1d2M8sRVJKeQaajOnbsqDcz7LZX8vzFt5FFds6aNiwZwmDAcJtATP3yww8/qLWbsoZMfmjJukCJxBthLaes1xTBJz9YJPIuG8patmyppkj1trnM9j2yJwDlGllqIlkIZOZIdjyLwBcRaKTjC43yneLIDgpAo/cw7SMBEiABEiABEiABGwIUgHQJEiABEiABEiABEnAzAhSAbtbhNJcESIAESIAESIAEKADpAyRAAiRAAiRAAiTgZgQoAN2sw2kuCZAACZAACZAACVAA0gdIgARIgARIgARIwM0IUAC6WYfTXBLQE4GYmBiVBkbOk71z5w6Cg4NVzjE51vCzzz5T560mply5ckUduSZpcuSe8RXTtYlJNSM50eSkhDFjxpiPdnOmfZKCSHI6FihQQNenYjhjK68hARJwDQIUgK7RD2wFCZCAHQKmM54LFy6sTlOQPHLh4eGYPXs2GjdurE6SSExJSQEoR+9Vq1YNkiRXhJyIQMsi+e8k6bEcaVejRg2rz+R8YxGOlStXVnnV9H76R2L6hNeSAAmkDQEKwLThzqeSAAk4QcB0gsSUKVPw6aefOlEj/ktSUgA2atRIHYu1efNmu41YsmQJunTpgvgiinIkmhy9mNC53ZpB8AYkQAJuT4AC0O1dgABIwHUJmESTTI/K9KrWklIC8ODBg3j11VeV+HMUlXRGAEp9ObFGTlmQ+7GQAAmQQEoRoABMKbK8LwmQgCYCcizf/v37re4h6/9ExNlbAyhHcI0aNUpFzx48eIAyZcqgV69e6Nq1q/msWUcC8NChQ+oIvRMnTsDLy0tNN8u0rEzJOrMGUNYUbt26VZ1x6+jcV2cEoET/5Oiwt956C0uXLtXEj5VJgARIID4CFID0DxIgAZckIOv8NmzYoNbN+fr64pVXXlECT9bY2QrA8+fPq4jZvXv30KxZMxQqVAg//fSTOnfWcsOHPQF4+PBhdT8pLVq0UAJw+/btyJEjBy5fvpygAIyNjUX+/PnV+r8tW7Y4ZOmMAJTKsrbx+PHjSkzyXFWXdE02igQMQYAC0BDdSCNIwJgETKJpwYIF6NatmzLStDHEchdwrVq1cPLkSfVZzZo11XWyg1jE36pVq1R0rmnTpip6aLsLuGLFijh37pwSjKbNGTdv3oREIC9cuJCgAJTNH85ECp0VgP7+/ggICMCpU6dQqVIlY3YsrSIBEkhzAhSAad4FbAAJkIAjAs4IQNk1K0JJBKIIRcty8eJFlCxZEj169MDcuXPjCEARWVWqVMEHH3wAeZZlWblyJTp06JCgAFyzZg3atm2rnm0SqfbscVYALly4UK13XLFiBdq3b0/nIAESIIEUIUABmCJYeVMSIIHkIOCMABRhJ2v96tSpo8ScbZk1axbq1q0LybVnGwE01f3mm2/w4YcfWlWV9YYvvvhiggLwq6++Qp8+fbB27Vq0bt3aodnOCsAffvgB77zzDqZPn46+ffsmB0begwRIgATiEKAApFOQAAm4LAFnBOD48eMxYsSIeG0QYSgbPGwFoKnupk2bIClYLMvt27fx/PPPJygATfcwTTM7aoizAnDXrl2QlDIyDSxrHllIgARIICUIUACmBFXekwRIIFkIOCMAJVLWv39/pyJmtgJw2rRpGDBgABYvXozOnTtbtfmXX36BrA9MaBew6R4yFfzuu+9qjgCuX79e7QKeOXMmPv7442ThyJuQAAmQgC0BCkD6BAmQgMsScEYA7tmzBw0bNlQCToScZbl16xYGDhyIBg0aqCleWwFoirbZWwM4Z84clQomIQEom0xkrZ5MJ8taQ60RQJPNsgaxXbt2Lts3bBgJkIC+CVAA6rv/2HoSMDQBZwRgdHQ0XnrpJciU7ZEjR1TUToocrSbCbvXq1Q53AUtd2RUsKVeOHj2KChUqqLpy7nDVqlUhuQUTEoC//vorypUrl+DZxM5OAcv5xiNHjlRT1vbWNBq6w2kcCZBAqhGgAEw11HwQCZBAYgk4IwDlnrLBQ07g8PDwUOvn8uTJo07TCA4Ottrhay8NjCSOlvx/coybnMIh+f82btyoUrvIur6EBKCkm5Gzf0UE7t69W3MEsGXLlpDchCJoPT09E4uM15MACZCAUwQoAJ3CxItIgATSgoCzAlDaJildZNOECD9JzizpXyQtS8+ePRM8CUTyB8pJIHIPEY+m9C8iBhMSgPJsOW1EIo337993mLzZmQigSUxK4mtJA8NCAiRAAilFgAIwpcjyviRAAm5DQKaeJRm1nFwi0cSklh07dqBJkyYqoXW9evWSehvWIwESIIEECVAAJoiIF5AACZBAwgRk6lnOAZYp5aQWOYM4IiJCCUAWEiABEkhJAhSAKUmX9yYBEnAbAnLusGxAkSPpZD1gYoucZyznHUs0Uc4VZiEBEiCBlCRAAZiSdHlvEiABtyIgKWdCQ0PV+cOJLV26dFFVbFPZJPY+vJ4ESIAEnCFAAegMJV5DAiRAAiRAAiRAAgYiQAFooM6kKSRAAiRAAiRAAiTgDAEKQGco8RoSIAESIAESIAESMBABCkADdSZNIQESIAESIAESIAFnCFAAOkOJ15AACZAACZAACZCAgQhQABqoM2kKCZAACZAACZAACThDgALQGUq8hgRIgARIgARIgAQMRIAC0ECdSVNIgARIgARIgARIwBkCFIDOUOI1JEACJEACJEACJGAgAhSABupMmkICJEACJEACJEACzhCgAHSGEq8hARIgARIgARIgAQMR+D/60p+J4SN33wAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create model and parameters\n",
    "smodel = Model(dS12)\n",
    "\n",
    "params = smodel.make_params()\n",
    "params['alow'] = Parameter(name='alow', value=1.0, min=0.2, max=1.8)\n",
    "params['ahigh'] = Parameter(name='ahigh', value=1.0, min=0.2, max=1.8)\n",
    "params['glow'] = Parameter(name='glow', value=0.4, min=0.1, max=1.0)\n",
    "params['ghigh'] = Parameter(name='ghigh', value=0.4, min=0.1, max=1.0)\n",
    "params['est'] = Parameter(name='est', value=0.25, min=0.1, max=0.5)\n",
    "params['de'] = Parameter(name='de', value=0.0, min=-0.1, max=0.1)\n",
    "params['b'] = Parameter(name='b', value=0.0, min=-0.3, max=0.3)\n",
    "\n",
    "# calculate temp based on calibration above\n",
    "current = 0.5*2e-8\n",
    "volts = np.nanmean(np.concatenate(vac).flatten())\n",
    "theta = power_to_theta(current*volts*1e12)\n",
    "temp = theta*ALPHA2_CLSD/K_B\n",
    "\n",
    "params['temp'] = Parameter(name='temp', value=temp, vary=False)\n",
    "\n",
    "sresult = smodel.fit(-1.0*results['epsilon'].values, params, \n",
    "                     fields = 1000*results['field'].values)\n",
    "\n",
    "N = 500\n",
    "sfit = sresult.best_fit\n",
    "resid = sresult.residual\n",
    "boot_params = np.zeros((500,len(sresult.values)))\n",
    "for k in range(500):\n",
    "    stest = sfit + np.random.choice(resid.flatten(), size=sfit.shape)\n",
    "    out = smodel.fit(stest, params, \n",
    "                     fields = 1000*results['field'].values)\n",
    "    boot_params[k] = [v for k, v in out.values.items()]\n",
    "\n",
    "### print info for paper ###\n",
    "# temp, alow, ahigh, b, glow, ghigh, est, de\n",
    "print('temp = {0:.1f} (mK, fixed)'.format(temp))\n",
    "\n",
    "alow_err = np.abs(np.percentile(boot_params[:,1], [2.5,97.5]) - sresult.values['alow']).mean()\n",
    "print('peak height (B=0) = {0:.3f}+/-{1:.3f}'.format(sresult.values['alow'], alow_err))\n",
    "\n",
    "glow_err = np.abs(np.percentile(boot_params[:,4], [2.5,97.5]) - sresult.values['glow']).mean()\n",
    "print('g(B=0) = {0:.3f}+/-{1:.3f}'.format(sresult.values['glow'], glow_err))\n",
    "\n",
    "ahigh_err = np.abs(np.percentile(boot_params[:,2], [2.5,97.5]) - sresult.values['ahigh']).mean()\n",
    "print('peak height (B=9T) = {0:.3f}+/-{1:.3f}'.format(sresult.values['ahigh'], ahigh_err))\n",
    "\n",
    "ghigh_err = np.abs(np.percentile(boot_params[:,5], [2.5,97.5]) - sresult.values['ghigh']).mean()\n",
    "print('g(B=9T) = {0:.3f}+/-{1:.3f}'.format(sresult.values['ghigh'], ghigh_err))\n",
    "\n",
    "de_err = np.abs(np.percentile(boot_params[:,7], [2.5,97.5]) - sresult.values['de']).mean()\n",
    "print('de = {0:.3f} +/- {1:.3f}'.format(sresult.values['de'], de_err))\n",
    "\n",
    "### plot results ###\n",
    "fig, ax = plt.subplots(1,1)\n",
    "\n",
    "bs = np.linspace(-5, 11, 800)\n",
    "ax.scatter(results['field'], -1.0*results['epsilon'])\n",
    "ax.plot(bs, smodel.eval(sresult.params, fields=1000*bs), c='C3')\n",
    "ax.set_xlabel('field (T)');\n",
    "ax.set_ylabel(r'dS$_{12}$/k$_{B}$');\n",
    "\n",
    "### save data ###\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat1284-1290_field.csv\"), bs, delimiter=\",\")\n",
    "np.savetxt(os.path.join(analysis_dir, \"dat1284-1290_dS12_fit.csv\"), \n",
    "           smodel.eval(sresult.params, fields=1000*bs), delimiter=\",\")"
   ]
  }
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