Visualization.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
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   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import yaml\n",
    "import seaborn as sns\n",
    "from ipywidgets import interact\n",
    "import seaborn as sns\n",
    "from ipywidgets import interact\n",
    "import pandas as pd\n",
    "from country import County, Party\n",
    "from voting import Nation\n",
    "import copy\n",
    "import numpy as np\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
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  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
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     0
    ]
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   "outputs": [],
   "source": [
    "def mandates2017(st_lagues=1.4, area_importance=1.8):\n",
    "    df = pd.read_excel('tabell.xlsx', skiprows=[0, 1, 2])\n",
    "    df = df.iloc[:, :4]\n",
    "\n",
    "    st_lagues = st_lagues\n",
    "\n",
    "    counties = []\n",
    "    for k, row in df.iterrows():\n",
    "        counties.append(County(name=row[0], population=row[1], area=row[3]))\n",
    "    County.set_parameters({'st_lagues_factor': st_lagues})\n",
    "    County.set_parameters({'area_importance': area_importance})\n",
    "    Party.set_parameters({'st_lagues_factor': st_lagues})\n",
    "\n",
    "    norway = Nation(counties=copy.deepcopy(counties))\n",
    "    norway.calc_representatives(method='normal')\n",
    "\n",
    "    # Read in the votes in each county\n",
    "\n",
    "    votes_raw = pd.read_excel('tabell.xlsx', sheet_name='stemmer', index=1)\n",
    "    votes = votes_raw.iloc[:,\n",
    "            1:-1]  # fylker er kolonner, parti er index, stemmer er verdier\n",
    "    votes.index = votes_raw.iloc[:, 0]\n",
    "    votes = votes.fillna(value=0, axis=0)\n",
    "\n",
    "    parties = votes.index\n",
    "\n",
    "    for county in norway.counties:\n",
    "        county_votes = votes[county._name]\n",
    "        county.add_parties([Party(name=county_votes.index[k], votes=p_votes)\n",
    "                            for k, p_votes in enumerate(county_votes)])\n",
    "\n",
    "    norway.calc_rep_distribution(method='modified')\n",
    "\n",
    "    #print(norway.represented_parties())\n",
    "\n",
    "    return norway.national_mandates_count().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {
    "code_folding": [
     18
    ]
   },
   "outputs": [],
   "source": [
    "def vary_parameters(area_max=10,st_lagues_max=10):\n",
    "    res = {}\n",
    "    st_lagues = np.linspace(1,st_lagues_max,11)\n",
    "    st_lagues[1] = 1.4 #Used today\n",
    "    area_importance = np.linspace(1,area_max,11)\n",
    "    area_importance[1] = 1.8 #Used today\n",
    "    for area in area_importance:\n",
    "        ll  = [] \n",
    "        for st_lague in st_lagues:\n",
    "            ll.append(mandates2017(st_lagues=st_lague,\n",
    "                                  area_importance=area))    \n",
    "\n",
    "        partier = ll[0].index\n",
    "        df = pd.DataFrame(index=partier)\n",
    "\n",
    "        for k,dist in enumerate(ll):\n",
    "            df[st_lagues[k]] = dist \n",
    "\n",
    "        mappings = {'Arbeiderpartiet':'AP','Fremskrittspartiet':'FRP',\n",
    "                    'Høyre':'H','Kristelig Folkeparti': 'KRF',\n",
    "                   'Miljøpartiet De Grønne':'MDG','Rødt':'R',\n",
    "                   'Senterpartiet':'SP', 'Sosialistisk Venstreparti':'SV',\n",
    "                   'Venstre':'V'}\n",
    "\n",
    "        df.index = [mappings[p] for p in df.index]\n",
    "\n",
    "        df = df.fillna(value=0)\n",
    "        res[area] = df\n",
    "    return res, st_lagues, area_importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "res, st_lagues, area_importance = vary_parameters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
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       "        }\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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Zztq8FgDx1q7XWu4WwSg6qunudTyk3rRU92RrgFvPVmo7oTX5uMaUG2Oen5+DVxrD0CVrQFilal/t7kjfNoEoM69nq5TsyP1dKFaKlWyVM/KP+5NwDUg37wJuIShBo/1VJxvWgbm23k4SQCqbIlWLeWqmZzafFzH5relnh5UA+rPTVLLfkoU6v0L9djTmnWoGYorKwD1ebW8p56Cs3m7b9VZea4N4vWM/O2nHtXf6pxrAF7vVqgBep1XLS8rkahHsda7EjZHjwBsNnWfrU/v/v4eJwBVR/XNRy05rlmKevRpyURx3H2b8oqvoKIIIDArAQIwa+a1GwEE9p1Ay+B839vo/BFAAAEEzgEBAnAOoKoSAQQQOA8ECMB5gOwjEEAAgUMkQAAOMavahAACMxAgADNkWRsRQACBc0CAAJwDqKpEAAEEzgMBAnAeIPsIBBBA4BAJEIBDzKo2IYAAAggggAACCCBwDAECoGsggAACCCCAAAIIIDARAQIwUbI1FQEEEEAAAQQQQAABAqAPIIAAAggggAACCCAwEQECMFGyNRUBBBBAAAEEEEAAAQJwYfvANZY3YdZbJ//mwp6KT0cAAQQQQAABBPaOwPskuX6Sn0ry53t39hfohAnABQK/fOxnJnnhhT0Fn44AAggggAACCOw9gc9K8v1734rz1AACcJ5AH/Mxt0nyyhe84AW56KKLLuyZ+HQEEEAAAQQQQGDPCLz+9a/P3e52tzrr2yb55T07/Qt2ugTggqH/hw++ZZJLL7300tzylvU/HQgggAACCCCAAAKtBF7zmtfkVre6VRWv/3hNa9zs5QjAhe0BBODC8vfpCCCAAAIIILDHBAhAX/IIQB+3UVEEYBRJ9SCAAAIIIIDAdAQIQF/KCUAft1FRBGAUSfUggAACCCCAwHQECEBfyglAH7dRUQRgFEn1IIAAAggggMB0BAhAX8oJQHKXJD9xDL47JPmFrb99YpKvS/KRSd6R5AeTfGWSP+zDbxNwJzdhCCCAAAIIIIBACEBfJyAAlwvAVx0hApcm+YsF7Z2T/HiSH0ry5CTXSfL4JH+a5KOS/HVHCswAdEATggACCCCAAAIIFAEC0NcPCMDlAnD3JM8/C8aXJXm/5e7/ZUu5OyZ5aZIvTfLUjhQQgA5oQhBAAAEEEEAAAQLQ3wcIQJsAfHCS303yiCSP28H9G0l+J8knd6SBAHRAE4IAAggggAACCBCA/j5AAC4XgFrH/wHL2v6fX9b6/+yC9lOSvCjJv07ywzu4n5fkTkmu15EGAtABTQgCCCCAAAIIIEAA+vsAAUhuk+QLkvxkkj9OclGShya56TLgf3GSz0vyPUl2NwUX+acl+cIk73tCGmrPwLV3ytwkyQu9Cbi/A4tEAAEEEEAAgXkJ2APQl3sCcDS390/y6iR/sqz53wjA7ZP84k5ICUAJxFVPSMHFSR51VBkC0Nd5RSGAAAIIIIDA3AQIQF/+CcDx3GpT7/2TXC3Jxw9YAmQGoK+PikIAAQQQQAABBI4kQAD6OgYBOJ7btya5X5J/suwNqE3AD18e/bkd9dokb7IJuK8DikIAAQQQQAABBHoJEIA+cgTgaG7XXJYAvTVn9gjUUUt/ajbg1kn+bvl3tSSoNgw/IEkJw9rDJuC1xJRHAAEEEEAAAQQWAgSgrysQgORZyx38X0ryR0k+LMmDk9QG3U9bXv5VdOuNwT+W5AeSPGV5EVg9EvTPvQisr/OJQgABBBBAAAEErgwBAtBHjwCcWdbzuUlulOTqy8bfevznNyR5+Q7WT0ry6GUW4B1JfnB5YlA9QrTnMAPQQ00MAggggAACCCDgTcDdfYAAdKMbEkgAhmBUCQIIIIAAAgjMSMAMQF/WCUAft1FRBGAUSfUggAACCCCAwHQECEBfyglAH7dRUWcVgNs99BmjPufU1POKS+5zas7FiSCAAAIIIIDAfhMgAH35IwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJNWDAAIIIIAAAtMRIAB9KScAfdxGRRGAUSTVgwACCCCAAALTESAAfSknAH3cRkURgFEk1YMAAggggAAC0xEgAH0pJwB93EZFEYBRJCeo505PutPBtfKlD3rpwbVJgxBAAAEEzh8BAtDHmgD0cRsVRQBGkZygHgIwQZI1EQEEEEBgFQECsArXuwsTgD5uo6IIwCiSE9RDACZIsiYigAACCKwiQABW4SIAfbiGRxGA4UgPt0ICcLi51TIEEEAAgT4CBKCPmxmAPm6jogjAKJIT1EMAJkiyJiKAAAIIrCJAAFbhMgPQh2t4FAEYjvRwKyQAh5tbLUMAAQQQ6CNAAPq4mQHo4zYqigCMIjlBPQRggiRrIgIIIIDAKgIEYBUuMwB9uIZHEYDhSA+3QgJwuLnVMgQQQACBPgIEoI+bGYA+bqOiCMAokhPUQwAmSLImIoAAAgisIkAAVuEyA9CHa3gUARiO9HArJACHm1stQwABBBDoI0AA+riZAejjNiqKAIwiOUE9BGCCJGsiAggggMAqAgRgFS4zAH24hkcRgOFID7dCAnC4udUyBBBAAIE+AgSgj5sZgD5uo6IIwCiSE9RDACZIsiYigAACCKwiQABW4TID0IdreBQBGI70cCskAIebWy1DAAEEEOgjQAD6uJkB6OM2KooAjCI5QT0EYIIkayICCCCAwCoCBGAVLjMAfbiGRxGA4UgPt0ICcLi51TIEEEAAgT4CBKCPmxmAPm6jogjAKJIT1EMAJkiyJiKAAAIIrCJAAFbhMgPQh2t4FAEYjvRwKyQAh5tbLUMAAQQQ6CNAAPq4mQHo4zYqigCMIjlBPQRggiRrIgIIIIDAKgIEYBUuMwB9uIZHEYDhSA+3QgJwuLnVMgQQQACBPgIEoI+bGYCjud03ybcn+cskV98pctskT0hy+ySXJXlJkockeWNHCghAB7RZQwjArJnXbgQQQACB4wgQgL6+QQCuyO2Dk7xmGfxfY0cAbp7kZUleleRxSa6a5NFJrpnk1kneujINBGAlsJmLE4CZs6/tCCCAAAJHESAAff2CAFyR2w8keVeSP0nyOTsC8Nwkd01ykyRvW0JvmOR1SZ6Y5GEr00AAVgKbuTgBmDn72o4AAgggQADG9QEC8J4s753kKUlukeQxOwJwlWXQ/4wk999JwYuT3CjJTVemhgCsBDZzcQIwc/a1HQEEEECAAIzrAwTgcpbXSfJrSR65SMB37wjAzZK8NskDl79vZ+GSJA9OcrUk71yRHgKwAtbsRQnA7D1A+xFAAAEEdglYAtTXJwjA5dyen+S6ST5uWQK0KwB3TPLSJPdK8uwd3I9I8tgk10vy5mNSUYJx7Z2/1VKiF1566aW55S3LBd7zuN1Da7LhsI5XXHKfw2rQeWwNATiPsH0UAggggMBeECAAfWkiAGe4fXaSZyW5zTILUP/uOAG4Z5LnHCMAJRBvOSYVFyd51FF/IwB9nXe2KAIwW8a1FwEEEEDgJAIE4CRCR/+dAJx5zOfrkzxzWfe/IVV7AT4zyYck+dvlv6/MEiAzAEnMAPR9USuKAPSzE4kAAgggcJgECEBfXglA8qFJfusEfC9c9gPUk3+enuQBO+VflOTGNgGf3AkJwMmMjitBAPrZiUQAAQQQOEwCBKAvrwTgzLP866Veu8fDk9w5yacl+aMkly5Lf+6S5KIkb18CbrD1GNCKWXPYBLyG1uRlCcDkHUDzEUAAAQSuQIAA9HUKAnA8t909AFWyXgT28iSv3HkR2LW8CKytA5oBaON0VCkC0M9OJAIIIIDAYRIgAH15JQDrBKBK3y7J45PcIcllSV6S5CFJ3tCRAjMAHdBmDSEAs2ZeuxFAAAEEjiNAAPr6BgHo4zYqigCMIjlBPQRggiRrIgIIIIDAKgIEYBWudxcmAH3cRkURgFEkJ6iHAEyQZE1EAAEEEFhFgACswkUA+nANjyIAw5EeboUE4HBzq2UIIIAAAn0ECEAfNzMAfdxGRRGAUSQnqIcATJBkTUQAAQQQWEWAAKzCZQagD9fwKAIwHOnhVkgADje3WoYAAggg0EeAAPRxMwPQx21UFAEYRXKCegjABEnWRAQQQACBVQQIwCpcZgD6cA2PIgDDkR5uhQTgcHOrZQgggAACfQQIQB83MwB93EZFEYBRJCeohwBMkGRNRAABBBBYRYAArMJlBqAP1/AoAjAc6eFWSAAON7dahgACCCDQR4AA9HEzA9DHbVQUARhFcoJ6CMAESdZEBBBAAIFVBAjAKlxmAPpwDY8iAMORHm6FBOBwc6tlCCCAAAJ9BAhAHzczAH3cRkURgFEkJ6iHAEyQZE1EAAEEEFhFgACswmUGoA/X8CgCMBzp4VZIAA43t1qGAAIIINBHgAD0cTMD0MdtVBQBGEVygnoIwARJ1kQEEEAAgVUECMAqXGYA+nANjyIAw5Eebl2W4N4AACAASURBVIUE4HBzq2UIIIAAAn0ECEAfNzMAfdxGRRGAUSQnqIcATJBkTUQAAQQQWEWAAKzCZQagD9fwKAIwHOnhVkgADje3WoYAAggg0EeAAPRxMwPQx21UFAEYRXKCegjABEnWRAQQQACBVQQIwCpcZgD6cA2PIgDDkR5uhQTgcHOrZQgggAACfQQIQB83MwB93EZFEYBRJCeohwBMkGRNRAABBBBYRYAArMJlBqAP1/AoAjAc6eFWSAAON7dahgACCCDQR4AA9HEzA9DHbVQUARhFcoJ6CMAESdZEBBBAAIFVBAjAKlxmAPpwDY8iAMORHm6FBOBwc6tlCCCAAAJ9BAhAHzczAH3cRkURgFEkJ6iHAEyQZE1EAAEEEFhFgACswmUGoA/X8CgCMBzp4VZIAA43t1qGAAIIINBHgAD0cTMD0MdtVBQBGEVygnoIwARJ1kQEEEAAgVUECMAqXGYA+nANjyIAw5EeboUE4HBzq2UIIIAAAn0ECEAfNzMAfdxGRRGAUSQnqIcATJBkTUQAAQQQWEWAAKzCZQagD9fwKAIwHOnhVkgADje3WoYAAggg0EeAAPRxMwPQx21UFAEYRXKCegjABEnWRAQQQACBVQQIwCpcZgD6cA2PIgDDkR5uhQTgcHOrZQgggAACfQQIQB83MwB93EZFEYBRJCeohwBMkGRNRAABBBBYRYAArMJlBqAP1/AoAjAc6eFWSAAON7dahgACCCDQR4AA9HEzA9DHbVQUARhFcoJ6CMAESdZEBBBAAIFVBAjAKlxmAPpwDY8iAMORHm6FBOBwc6tlCCCAAAJ9BAhAHzczAH3cRkURgFEkJ6iHAEyQZE1EAAEEEFhFgACswmUGoA/X8CgCMBzp4VZIAA43t1qGAAIIINBHgAD0cTMD0MdtVBQBGEVygnoIwARJ1kQEEEAAgVUECMAqXGYA+nANjyIAw5EeboUE4HBzq2UIIIAAAn0ECEAfNzMAfdxGRRGAUSQnqIcATJBkTUQAAQQQWEWAAKzCZQagD9fwKAIwHOnhVkgADje3WoYAAggg0EeAAPRxMwPQx21UFAEYRXKCegjABEnWRAQQQACBVQQIwCpcZgD6cA2PIgDDkR5uhQTgcHOrZQgggAACfQQIQB83MwB93EZFEYBRJCeohwBMkGRNRAABBBBYRYAArMJlBqAP1/AoAjAc6eFWSAAON7dahgACCCDQR4AA9HEzA9DHbVQUARhFcoJ6CMAESdZEBBBAAIFVBAjAKlxmAPpwDY8iAMORHm6FBOBwc6tlCCCAAAJ9BAhAHzczAH3cRkURgFEkJ6iHAEyQZE1EAAEEEFhFgACswmUGoA/X8CgCMBzp4VZIAA43t1qGAAIIINBHgAD0cTMD0MdtVBQBGEVygnoIwARJ1kQEEEAAgVUECMAqXGYA+nANjyIAw5EeboUE4HBzq2UIIIAAAn0ECEAfNzMAfdxGRRGAUSQnqIcATJBkTUQAAQQQWEWAAKzCZQagD9fwKAIwHOnhVkgADje3WoYAAggg0EeAAPRxMwPQx21UFAEYRXKCegjABEnWRAQQQACBVQQIwCpcZgD6cA2PIgDDkR5uhQTgcHOrZQgggAACfQQIQB83MwB93EZFEYBRJCeohwBMkGRNRAABBBBYRYAArMJlBqAP1/AoAjAc6eFWSAAON7dahgACCCDQR4AA9HEzA9DHbVQUARhFcoJ6CMAESdZEBBBAAIFVBAjAKlxmAPpwDY8iAMORHm6FBOBwc6tlCCCAAAJ9BAhAHzczAH3cRkURgFEkJ6iHAEyQZE1EAAEEEFhFgACswmUGoA/X8CgCMBzp4VZIAA43t1qGAAIIINBHgAD0cTMD0MdtVBQBGEVygnoIwARJ1kQEEEAAgVUECMAqXGYA+nANjyIAw5EeboUE4HBzq2UIIIAAAn0ECEAfNzMAfdxGRRGAUSQnqIcATJBkTUQAAQQQWEWAAKzCZQagD9fwKAIwHOnhVkgADje3WoYAAggg0EeAAPRxMwPQx21UFAEYRXKCegjABEnWRAQQQACBVQQIwCpcZgD6cA2PIgDDkR5uhQTgcHOrZQgggAACfQQIQB83MwB93EZFEYBRJCeohwBMkGRNRAABBBBYRYAArMJlBqAP1/AoAjAc6eFWSAAON7dahgACCCDQR4AA9HEzA9DHbVQUARhFcoJ6CMAESdZEBBBAAIFVBAjAKlxmAPpwDY8iAMORHm6FBOBwc6tlCCCAAAJ9BAhAHzczAH3cRkURgFEkJ6iHAEyQZE1EAAEEEFhFgACswmUGoA/X8CgCMBzp4VZIAA43t1qGAAIIINBHgAD0cTMD0MdtVBQBGEVygnoIwARJ1kQEEEAAgVUECMAqXGYAtnDdOsnXJ/mIJNdO8ldJfiPJk5M8cwfrbZM8Icntk1yW5CVJHpLkjX34QwA6wc0YRgBmzLo2I4AAAgicjQAB6OsfZgCSuyS5Z5KfTfJ7Sd4vyecv/+5rkjxmQXvzJC9L8qokj0ty1SSPTnLNJCURb+1IAQHogDZrCAGYNfPajQACCCBwHAEC0Nc3CMDx3H4hyfWS3GAp8twkd01ykyRvW/7dDZO8LskTkzysIwUEoAParCEEYNbMazcCCCCAAAEY2wcIwPE8fzDJLZLcOMlVlkH/M5LcfyfkxUlulOSmHakhAB3QZg0hALNmXrsRQAABBAjA2D5AAC7n+V5J6p9a0nP3JN+c5MuSPC3JzZK8NskDkzxlJwWXJHlwkqsleefK9BCAlcBmLk4AZs6+tiOAAAIIHEXAEqC+fkEALuf2rUnut/zfv0ny5Umeuvz/OyZ5aZJ7JXn2DupHJHnsslzozWdJw3WWTcbbRWo50QsvvfTS3PKW5QLvedzuoTXhcFjHKy65z2E16Dy2hgCcR9g+CgEEEEBgLwgQgL40EYDLudVa/xqk1z+fkeRLlnX935hkIwC1Wfg5xwjAdZO85SxpuDjJo476OwHo67yzRRGA2TKuvQgggAACJxEgACcROvrvBOB4bnX3/77Lnf1rDVgCZAYgiRmAvi9qRRGAfnYiEUAAAQQOkwAB6MsrATie2xcl+a7lmf+vWDYBPz3JA3ZCXrRsFLYJuKEPEoAGSMcUIQD97EQigAACCBwmAQLQl1cCcDy3WoBf7wP4oOUZ/7X0p94ZcFGSty9htWxo8xjQh3ekwCbgDmizhhCAWTOv3QgggAACxxEgAH19gwAk37bc3a+XfP1Bkg9cngL0uUnqCT9fuaCtF4G9PMkrd14EVsuDvAissf+ZAWgEdUQxAtDPTiQCCCCAwGESIAB9eSUASS31qX8+PMn7J/mLJL+S5DuSPHMH6+2SPD7JHZJcluQlSR6S5A19+GMGoBPcjGEEYMasazMCCCCAwNkIEIC+/kEA+riNiiIAo0hOUA8BmCDJmogAAgggsIoAAViF692FCUAft1FRBGAUyQnqIQATJFkTEUAAAQRWESAAq3ARgD5cw6MIwHCkh1shATjc3GoZAggggEAfAQLQx80MQB+3UVEEYBTJCeohABMkWRMRQAABBFYRIACrcJkB6MM1PIoADEd6uBUSgMPNrZYhgAACCPQRIAB93MwA9HEbFUUARpGcoB4CMEGSNREBBBBAYBUBArAKlxmAPlzDowjAcKSHWyEBONzcahkCCCCAQB8BAtDHzQxAH7dRUQRgFMkJ6iEAEyRZExFAAAEEVhEgAKtwmQHowzU8igAMR3q4FRKAw82tliGAAAII9BEgAH3czAD0cRsVRQBGkZygHgIwQZI1EQEEEEBgFQECsAqXGYA+XMOjCMBwpIdbIQE43NxqGQIIIIBAHwEC0MfNDEAft1FRBGAUyQnqIQATJFkTEUAAAQRWESAAq3CZAejDNTyKAAxHergVEoDDza2WIYAAAgj0ESAAfdzMAPRxGxVFAEaRnKAeAjBBkjURAQQQQGAVAQKwCpcZgD5cw6MIwHCkh1shATjc3GoZAggggEAfAQLQx80MQB+3UVEEYBTJCeohABMkWRMRQAABBFYRIACrcJkB6MM1PIoADEd6uBUSgMPNrZYhgAACCPQRIAB93MwA9HEbFUUARpGcoB4CMEGSNREBBBBAYBUBArAKlxmAPlzDowjAcKSHWyEBONzcahkCCCCAQB8BAtDHzQxAH7dRUQRgFMkJ6iEAEyRZExFAAAEEVhEgAKtwmQHowzU8igA0IH3Toz+iodR+FbnBI1+9+oQJwGpkAhBAAAEEDpwAAehL8KHMAFw1yWOTfEuSN/ahuCBRBKABOwE4A4kANHQWRRBAAAEEpiJAAPrSfSgCcI0kf5LkLkl+pg/FBYkiAA3YCQABaOgmiiCAAAIITEiAAPQlfZ8E4FfP0sT3SnKLJL+V5C+TvCvJR/YhOa9RBKABNwEgAA3dRBEEEEAAgQkJEIC+pO+TAPx9krck+Y0jmnqVWiGR5FeS/Nny97v2ITmvUQSgATcBIAAN3UQRBBBAAIEJCRCAvqTvkwA8JsmDk3xrkq9O8o6tJr//1hKgn+5DcUGiCEADdgJAABq6iSIIIIAAAhMSIAB9Sd8nAagW3jrJdyW5ZpL7J3nx0uzaA/Cnyx4AAtDXF85L1Csuuc/qzyEABGB1pxGAAAIIIDAFAQLQl+Z9E4Bq5XsnecQyC/D8JF+e5DIC0NcBzncUAThD3GNAz3B46YNeer67oM9DAAEEEDggAgSgL5n7KACbltam35oNuEmSr03yzUlq3b8ZgL6+cF6iCAAB2O5oBOC8fO18CAIIIHCwBAhAX2r3WQCqxXX+tS+gBKDeBUAA+vrBeYsiAASAAJy3r5sPQgABBA6eAAHoS/G+C8Cm1ddPcuMkv5zkbX0oLkiUTcAN2O0BOAPJi8AaOosiCCCAAAJTESAAfek+FAHoa/2FjyIADTkgAASgoZsoggACCCAwIQEC0Jf0QxSAmg2odr2pD8l5jSIADbgJAAFo6CaKIIAAAghMSIAA9CX9EAXgbxcBqJeDnfaDADRkiAAQgIZuoggCCCCAwIQECEBf0g9RAL4zyXsl+aI+JOc1igA04CYABKChmyiCAAIIIDAhAQLQl/RDFIA+EhcmigA0cCcABKChmyiCAAIIIDAhAQLQl/RDFIB6HOh17AHo6xDnOspjQM8Q9iKwMxy8B+Bcf+PUjwACCBw2AQLQl99DFIDPTvLc5Y3BfVTOX5QZgAbWZgDMADR0E0UQQAABBCYkQAD6kk4A+riNiiIADSQJAAFo6CaKIIAAAghMSIAA9CV9nwTgkY1NvEWSu5sBaKR1notZAnQGuCVAZzhYAnSev4A+DgEEEDgwAgSgL6H7JAB/n+RdyyM+T2ptlXvvkwqdgr+bAWhIghkAMwAN3UQRBBBAAIEJCRCAvqTvkwD8YZLvS/JVJzT1M5N8BwHo6xDnOsoMgBmA7T5mBuBcf+PUjwACCBw2AQLQl999EoAXJ3mfJHc9oak2Aff1hfMSRQAIAAE4L181H4IAAghMQYAA9KV5nwTgCUnum+RaJzT1U5M8NcmN+pCc1yhLgBpwWwJ0BtKdnnSnBlr7VcQMwH7ly9kigAACp40AAejLyD4JwNWTfECS3+lr6qmMIgANaSEABKChmyiCAAIIIDAhAQLQl/R9EoC+Fp7uKALQkB8CQAAauokiCCCAAAITEiAAfUknAH3cRkURgAaSBIAANHQTRRBAAAEEJiRAAPqSTgD6uI2KIgANJAkAAWjoJooggAACCExIgAD0JZ0A9HEbFUUAGkgSAALQ0E0UQQABBBCYkAAB6Es6AejjNiqKADSQJAAEoKGbKIIAAgggMCEBAtCXdALQx21UFAFoIEkACEBDN1EEAQQQQGBCAgSgL+kEoI/bqCgC0ECSABCAhm6iCAIIIIDAhAQIQF/SCUAft1FRBKCBJAEgAA3dRBEEEEAAgQkJEIC+pBOAPm6joghAA0kCQAAauokiCCCAAAITEiAAfUknAH3cRkURgAaSBIAANHQTRRBAAAEEJiRAAPqSTgD6uI2KIgANJAkAAWjoJooggAACCExIgAD0JZ0A9HEbFUUAGkgSAALQ0E0UQQABBBCYkAAB6Es6AejjNiqKADSQJAAEoKGbKIIAAgggMCEBAtCXdALQx21UFAFoIEkACEBDN1EEAQQQQGBCAgSgL+kEoI/bqCgC0ECSABCAhm6iCAIIIIDAhAQIQF/SCUAft1FRBKCBJAEgAA3dRBEEEEAAgQkJEIC+pBOAPm6joghAA0kCQAAauokiCCCAAAITEiAAfUknAH3cRkURgAaSBIAANHQTRRBAAAEEJiRAAPqSTgD6uI2KIgANJAkAAWjoJooggAACCExIgAD0JZ0A9HEbFUUAGkgSAALQ0E0UQQABBBCYkAAB6Es6AejjNiqKADSQJAAEoKGbKIIAAgggMCEBAtCXdALQx21UFAFoIEkACEBDN1EEAQQQQGBCAgSgL+kEoI/bqCgC0ECSABCAhm6iCAIIIIDAhAQIQF/SCUAft1FRBKCBJAEgAA3dRBEEEEAAgQkJEIC+pBOAPm6joghAA0kCQAAauokiCCCAAAITEiAAfUknAH3cRkURgAaSBIAANHQTRRBAAAEEJiRAAPqSTgD6uI2KIgANJAkAAWjoJooggAACCExIgAD0JZ0A9HEbFUUAGkgSAALQ0E0UQQABBBCYkAAB6Es6AejjNiqKADSQJAAEoKGbKIIAAgggMCEBAtCXdAKQfEKSeye5Y5LrJ/mzJL+U5NFJXrGD9bZJnpDk9kkuS/KSJA9J8sY+/CEADeAIAAFo6CaKIIAAAghMSIAA9CWdACTPS/IBOfPfv5bk2kkenOSjknzKMsgvujdP8rIkr0ryuCRXXSThmkluneStHSkgAA3QCAABaOgmiiCAAAIITEiAAPQlnQAk10nyhzv4rp7k9UkuTfKJy9+em+SuSW6S5G3Lv7thktcleWKSh3WkgAA0QCMABKChmyiCAAIIIDAhAQLQl3QCcDy3Wt7zwUluluQqy6D/GUnuvxPy4iQ3SnLTjhQQgAZoBIAANHQTRRBAAAEEJiRAAPqSTgCO5naNJL+zLP/5d4sEvDbJA5M8ZSfkkmXJ0NWSvHNlGghAAzACQAAauokiCCCAAAITEiAAfUknAEdze2aSz102+9ZG4Nog/NIk90ry7J2QRyR5bJLrJXnzWdJQS41qf8H2UcuJXnjppZfmlrcsF3jP43YPrQmHwzpeccl9VjeIABCA1Z1GAAIIIIDAFAQIQF+aCcAVuX1dkv+a5EFJvmX580YA7pnkOccIwHWTvOUsabg4yaOO+jsBOHvnJQAEoO/yJgoBBBBA4NAJEIC+DBOA9+RWA/QaqH/1cld/89faB3BllwCZAajnqpoB+Ic+dYNHvnr1N/ZOT7rT6pjTHvDSB9XEmgMBBBBAAIE+AgSgjxsBuJzbZvBfAvC1Ozg3m4CfnuQBO397UZIb2wTc1gEJwBlOBOAMBwLQ9r1RCgEEEEDgaAIEoK9nEIAz3L5meab/Y5b/fRTNWvpzlyQXJXn7UuAGW48BfXhHCmwCboBmCdAZSGYAGjqLIggggAACUxEgAH3pJgBnXvr1jUnqTv7unf+i+gsL2noR2MuTvHLnRWDX8iKw9s5nBuAMKzMAZziYAWj/7iiJAAIIIHBFAgSgr1cQgOQnk9z5LPi2Gd0uyeOT3CHJZctjQh+S5A19+GMGoAGcGQAzAA3dRBEEEEAAgQkJEIC+pBOAPm6joghAA0kCQAAauokiCCCAAAITEiAAfUknAH3cRkURgAaSBIAANHQTRRBAAAEEJiRAAPqSTgD6uI2KIgANJAkAAWjoJooggAACCExIgAD0JZ0A9HEbFUUAGkgSAALQ0E0UQQABBBCYkAAB6Es6AejjNiqKADSQJAAEoKGbKIIAAgggMCEBAtCXdALQx21UFAFoIEkACEBDN1EEAQQQQGBCAgSgL+kEoI/bqCgC0ECSABCAhm6iCAIIIIDAhAQIQF/SCUAft1FRBKCBJAEgAA3dRBEEEEAAgQkJEIC+pBOAPm6joghAA0kCQAAauokiCCCAAAITEiAAfUknAH3cRkURgAaSBIAANHQTRRBAAAEEJiRAAPqSTgD6uI2KIgANJAkAAWjoJooggAACCExIgAD0JZ0A9HEbFUUAGkgSAALQ0E0UQQABBBCYkAAB6Es6AejjNiqKADSQJAAEoKGbKIIAAgggMCEBAtCXdALQx21UFAFoIEkACEBDN1EEAQQQQGBCAgSgL+kEoI/bqCgC0ECSABCAhm6iCAIIIIDAhAQIQF/SCUAft1FRBKCBJAEgAA3dRBEEEEAAgQkJEIC+pBOAPm6joghAA0kCQAAauokiCCCAAAITEiAAfUknAH3cRkURgAaSBIAANHQTRRBAAAEEJiRAAPqSTgD6uI2KIgANJAkAAWjoJooggAACCExIgAD0JZ0A9HEbFUUAGkgSAALQ0E0UQQABBBCYkAAB6Es6AejjNiqKADSQJAAEoKGbKILA1AR+/etfcnDt//Cv/oSDa5MGjSdAAPqYEoA+bqOiCEADSQJAABq6iSIITE2AAEyd/qkbTwD60k8A+riNiiIADSQJAAFo6CaKIDA1AQIwdfqnbjwB6Es/AejjNiqKADSQJAAEoKGbKILA1AQIwNTpn7rxBKAv/QSgj9uoKALQQJIAEICGbqIIAlMTIABTp3/qxhOAvvQTgD5uo6IIQANJAkAAGrqJIghMTYAATJ3+qRtPAPrSTwD6uI2KIgANJAkAAWjoJoogMDUBAjB1+qduPAHoSz8B6OM2KooANJAkAASgoZsogsDUBAjA1OmfuvEEoC/9BKCP26goAtBAkgAQgIZuoggCUxMgAFOnf+rGE4C+9BOAPm6joghAA0kCQAAauokiCExNgABMnf6pG08A+tJPAPq4jYoiAA0kCQABaOgmiiAwNQECMHX6p248AehLPwHo4zYqigA0kCQABKChmyiCwNQECMDU6Z+68QSgL/0EoI/bqCgC0ECSABCAhm6iCAJTEyAAU6d/6sYTgL70E4A+bqOiCEADSQJAABq6iSIITE2AAEyd/qkbTwD60k8A+riNiiIADSQJAAFo6CaKIDA1AQIwdfqnbjwB6Es/AejjNiqKADSQJAAEoKGbKILA1AQIwNTpn7rxBKAv/QSgj9uoKALQQJIAEICGbqIIAlMTIABTp3/qxhOAvvQTgD5uo6IIQANJAkAAGrqJIghMTYAATJ3+qRtPAPrSTwD6uI2KIgANJAkAAWjoJoogMDUBAjB1+qduPAHoSz8B6OM2KooANJAkAASgoZsogsDUBAjA1OmfuvEEoC/9BKCP26goAtBAkgAQgIZuoggCUxMgAFOnf+rGE4C+9BOAPm6joghAA0kCQAAauokiCExNgABMnf6pG08A+tJPAPq4jYoiAA0kCQABaOgmiiAwNQECMHX6p248AehLPwHo4zYqigA0kCQABKChmyiCwNQECMDU6Z+68QSgL/0EoI/bqCgC0ECSABCAhm6iCAJTEyAAU6d/6sYTgL70E4A+bqOiCEADSQJAABq6iSIITE2AAEyd/qkbTwD60k8A+riNiiIADSQJAAFo6CaKIDA1AQIwdfqnbjwB6Es/AejjNiqKADSQJAAEoKGbKILA1AQIwNTpn7rxBKAv/QSgj9uoKALQQJIAEICGbqIIAlMTIABTp3/qxhOAvvQTgD5uo6IIQANJAkAAGrqJIghMTYAATJ3+qRtPAPrSTwD6uI2KIgANJAkAAWjoJoogMDUBAjB1+qduPAHoSz8B6OM2KooANJAkAASgoZsogsDUBAjA1OmfuvEEoC/9BKCP26goAtBAkgAQgIZuoggCUxMgAFOnf+rGE4C+9BOAPm6joghAA0kCQAAauokiCExNgABMnf6pG08A+tJPAPq4jYoiAA0kCQABaOgmiiAwNQECMHX6p248AehLPwHo4zYqigA0kCQABKChmyiCwNQECMDU6Z+68QSgL/0EoI/bqCgC0ECSABCAhm6iCAJTEyAAU6d/6sYTgL70E4A+bqOiCEADSQJAABq6iSIITE2AAEyd/qkbTwD60k8A+riNiiIADSQJAAFo6CaKIDA1AQIwdfqnbjwB6Es/AejjNiqKADSQJAAEoKGbKILA1AQIwNTpn7rxBKAv/QSgj9uoKALQQJIAEICGbqIIAlMTIABTp3/qxhOAvvQTgD5uo6IIQANJAkAAGrqJIghMTYAATJ3+qRtPAPrSTwD6uI2KIgANJAkAAWjoJoogMDUBAjB1+qduPAHoSz8B6OM2KooANJAkAASgoZsogsDUBAjA1OmfuvEEoC/9BKCP26goAtBAkgAQgIZuoggCUxMgAFOnf+rGE4C+9BOAPm6joghAA0kCQAAauokiCExNgABMnf6pG08A+tJPAPq4jYoiAA0kCQABaOgmiiAwNQECMHX6p248AehLPwHo4zYqigA0kCQABKChmyiCwNQECMDU6Z+68QSgL/0EoI/bqCgC0ECSABCAhm6iCAJTEyAAU6d/6sYTgL70E4A+bqOiCEADSQJAABq6iSIITE2AAEyd/qkbTwD60k8A+riNiiIADSQJAAFo6CaKIDA1AQIwdfqnbjwB6Es/AejjNiqKADSQJAAEoKGbKILA1AQIwNTpn7rxBKAv/QSgj9uoKALQQJIAEICGbqIIAlMTIABTp3/qxhOAvvQTgD5uo6IIQANJAkAAGrqJIghMTYAATJ3+qRtPAPrSTwDOcPunSb4mya2T3CbJByb52iQXH4H1tkmekOT2SS5L8pIkD0nyxo4UEIAGaASAADR0E0UQmJoAAZg6/VM3ngD0pZ8AnOH2oUleleRXkvxmkvseIwA3T/Kypezjklw1yaOTXHORh7euTAMBaABGAAhAQzdRBIGpCRCAqdM/deMJQF/6CcAZbhsO71ru/tdA/qgZiwUkDgAAHwpJREFUgOcmuWuSmyR524L8hklel+SJSR62Mg0EoAEYASAADd1EEQSmJkAApk7/1I0nAH3pJwBX5FbLf44SgKssg/5nJLn/TtiLk9woyU1XpoEANAAjAASgoZsogsDUBAjA1OmfuvEEoC/9BKBdAG6W5LVJHpjkKTthlyR5cJKrJXnnilQQgAZYBIAANHQTRRCYmgABmDr9UzeeAPSlnwC0C8Adk7w0yb2SPHsn7BFJHpvkeknefEwqrpPk2jt/q6VEL7z00ktzy1uWC7zncbuH1mTDYR2vuOQ+qxtEAAjA6k4jAIHJCBCAyRKuue8mQAD6OgMBWC8A90zynGME4LpJ3nJMKuqJQo866m8E4OydlwAQgL7LmygE5iFAAObJtZa+JwEC0NcjCEC7AFzZJUBmAJKYATjT4W7wyFev/sbe6Ul3Wh1z2gNe+qCaVHMggMCVJUAArixB8ftKgAD0ZY4AtAvAZhPw05M8YCfsRUlubBPwyZ2QABCA7V5CAE7+ziiBQAsBAtBCSZlDJEAA+rJKANoFoErW0p+7JLkoyduX0BtsPQb04SvTYBNwAzBLgM5AMgPQ0FkUQWBSAgRg0sRrdghAXycgAJdz+7Qk77e8Ffi7kjwvST33v44fTvKOJPUisJcneWWS7ReBXcuLwNo6oBkAMwBmANq+K0ohsIYAAVhDS9lDIkAA+rJJAC7n9ttJ6qVeRx31jP/6ex23S/L4JHdIclmSlyR5SJI3dKTADEADNDMAZyCZAWjoLIogMCkBAjBp4jXbDEBnHyAAneAGhRGABpAEgAA0dBNFEJiaAAGYOv1TN94MQF/6CUAft1FRBKCBJAEgAA3dRBEEpiZAAKZO/9SNJwB96ScAfdxGRRGABpIEgAA0dBNFEJiaAAGYOv1TN54A9KWfAPRxGxVFABpIEgAC0NBNFEFgagIEYOr0T914AtCXfgLQx21UFAFoIEkACEBDN1EEgakJEICp0z914wlAX/oJQB+3UVEEoIEkASAADd1EEQSmJkAApk7/1I0nAH3pJwB93EZFEYAGkgSAADR0E0UQmJoAAZg6/VM3ngD0pZ8A9HEbFUUAGkgSAALQ0E0UQWBqAgRg6vRP3XgC0Jd+AtDHbVQUAWggSQAIQEM3UQSBqQkQgKnTP3XjCUBf+glAH7dRUQSggSQBIAAN3UQRBKYmQACmTv/UjScAfeknAH3cRkURgAaSBIAANHQTRRCYmgABmDr9UzeeAPSlnwD0cRsVRQAaSBIAAtDQTRRBYGoCBGDq9E/deALQl34C0MdtVBQBaCBJAAhAQzdRBIGpCRCAqdM/deMJQF/6CUAft1FRBKCBJAEgAA3dRBEEpiZAAKZO/9SNJwB96ScAfdxGRRGABpIEgAA0dBNFEJiaAAGYOv1TN54A9KWfAPRxGxVFABpIEgAC0NBNFEFgagIEYOr0T914AtCXfgLQx21UFAFoIEkACEBDN1EEgakJEICp0z914wlAX/oJQB+3UVEEoIEkASAADd1EEQSmJkAApk7/1I0nAH3pJwB93EZFEYAGkgSAADR0E0UQmJoAAZg6/VM3ngD0pZ8A9HEbFUUAGkgSAALQ0E0UQWBqAgRg6vRP3XgC0Jd+AtDHbVQUAWggSQAIQEM3UQSBqQkQgKnTP3XjCUBf+glAH7dRUQSggSQBIAAN3UQRBKYmQACmTv/UjScAfeknAH3cRkURgAaSBIAANHQTRRCYmgABmDr9UzeeAPSlnwD0cRsVRQAaSBIAAtDQTRRBYGoCBGDq9E/deALQl34C0MdtVBQBaCBJAAhAQzdRBIGpCRCAqdM/deMJQF/6CUAft1FRBKCBJAEgAA3dRBEEpiZAAKZO/9SNJwB96ScAfdxGRRGABpIEgAA0dBNFEJiaAAGYOv1TN54A9KWfAPRxGxVFABpIEgAC0NBNFEFgagIEYOr0T914AtCXfgLQx21UFAFoIEkACEBDN1EEgakJEICp0z914wlAX/oJQB+3UVEEoIEkASAADd1EEQSmJkAApk7/1I0nAH3pJwB93EZFEYAGkgSAADR0E0UQmJoAAZg6/VM3ngD0pZ8A9HEbFUUAGkgSAALQ0E0UQWBqAgRg6vRP3XgC0Jd+AtDHbVQUAWggSQAIQEM3UQSBqQkQgKnTP3XjCUBf+glAH7dRUQSggSQBIAAN3UQRBKYmQACmTv/UjScAfeknAH3cRkURgAaSBIAANHQTRRCYmgABmDr9UzeeAPSlnwD0cRsVRQAaSBIAAtDQTRRBYGoCBGDq9E/deALQl34C0MdtVBQBaCBJAAhAQzdRBIGpCRCAqdM/deMJQF/6CUAft1FRBKCBJAEgAA3dRBEEpiZAAKZO/9SNJwB96ScAfdxGRRGABpIEgAA0dBNFEJiaAAG4PP0XX3zxQfWFQ2vP6OQQgD6iBKCP26goAtBAkgAQgIZuoggCUxMgAARg1i8AAejLPAHo4zYqigA0kCQABKChmyiCwNQECAABmPULQAD6Mk8A+riNiiIADSQJAAFo6CaKIDA1AQJAAGb9AhCAvswTgD5uo6IIQANJAkAAGrqJIghMTYAAEIBZvwAEoC/zBKCP26goAtBAkgAQgIZuoggCUxMgAARg1i8AAejLPAHo4zYqigA0kCQABKChmyiCwNQECAABmPULQAD6Mk8A+riNiiIADSQJAAFo6CaKIDA1AQJAAGb9AhCAvswTgD5uo6IIQANJAkAAGrqJIghMTYAAEIDdL8Bzn/cxB/eduMfdX3aFNhGAvjQTgD5uo6IIQANJAkAAGrqJIghMTYAAEAACkFslec3UF4IVjScAK2Cdg6IEoAEqASAADd1EEQSmJkAACAABIABrLoIEYA2t8WUJQANTAkAAGrqJIghMTYAAEAACQADWXAQJwBpa48sSgAamBIAANHQTRRCYmgABIAAEgACsuQgSgDW0xpclAA1MCQABaOgmiiAwNQECQAAIAAFYcxEkAGtojS9LABqYEgAC0NBNFEFgagIEgAAQAAKw5iJIANbQGl+WADQwJQAEoKGbKILA1AQIAAEgAARgzUWQAKyhNb4sAWhgSgAIQEM3UQSBqQkQAAJAAAjAmosgAVhDa3xZAtDAlAAQgO1u8lMff+eGXrNfRe780z+1XyfsbE8dAQJAAAgAAVhzYSIAa2iNL0sAGpgSAAJAABq+KIpMTYAAEAACQADWXAQJwBpa48sSgAamBIAAEICGL4oiUxMgAASAABCANRdBArCG1viyBKCBKQEgAASg4YuiyNQECAABIAAEYM1FkACsoTW+LAFoYEoACAABaPiiKDI1AQJAAAgAAVhzESQAa2iNL0sAGpgSAAJAABq+KIpMTYAAEAACQADWXAQJwBpa48sSgAamBIAAEICGL4oiUxMgAASAABCANRdBArCG1viyBKCBKQEgAASg4YuiyNQECAABIAAEYM1FkACsoTW+LAFoYEoACAABaPiiKDI1AQJAAAgAAVhzESQAa2iNL0sAGpgSAAJAABq+KIpMTYAAEAACQADWXAQJwBpa48sSgAamBIAAEICGL4oiUxMgAASAABCANRdBArCG1viyBKCBKQEgAASg4YuiyNQECAABIAAEYM1FkACsoTW+LAFoYEoACAABaPiiKDI1AQJAAAgAAVhzESQAa2iNL0sAGpgSAAJAABq+KIpMTYAAEAACQADWXAQJwBpa48sSgAamBIAAEICGL4oiUxMgAASAABCANRdBArCG1viyBKCBKQEgAASg4YuiyNQECAABIAAEYM1FkACsoTW+LAFoYEoACAABaPiiKDI1AQJAAAgAAVhzESQAa2iNL0sAGpgSAAJAAK74RfmWB/9Aw7dnv4p82Td9xuoT/vp7f87qmNMe8NXPfP7qUyQABIAAEIA1Fw4CsIbW+LIEoIEpASAABIAAHHepIABnyBAAAkAACEDDkOrdRQjAGlrjyxKABqYEgAAQAAJAAM5+sSQABIAAEICGIRUBWANpp+zVkzwmyT2SXCvJa5M8LsmzO+okAA3QCAABIAAEgAAQgIafi38ocvHFF7cW3Ytyve157vM+Zi/at+Yk73H3l12h+Gte85rc6la3qn9f//GaNfXNXNYMwPrs/2iSj07y8CS/meTzktw3yecnedbK6ghAAzACQAAIAAEgAASg4eeCAGxBIgCtPWbOcgRgXd4/PckPLYP+790KLSmowfwNkvzdiioJQAMsAkAACAABIAAEoOHnggAQADMAjV8UAtAIain27UnumeSaSS7bCr3Xcvf/Tkl+bkWVBKABFgEgAASAABAAAtDwc0EACAABaPyiEIBGUEuxn0/y3kl2F9b9w0A+yf2SfNuKKglAAywCQAAIAAEgAASg4eeCABAAAtD4RSEAjaCWYrXm/41JPnUn7LpJfj/JVyX5hmOqvE6Sa+/87eZJnv+CF7wgF1100RXC7v6NL1x3dntQ+nkP+azVZ/nmp95tdcxpD7juA16w+hTv/T33Xh1z2gOe+fnPXH2KL7/PF6yOOe0BH/2Mp68+xWc94SdXx5z2gM/7yrusPsWnPewrVsec9oD7Pf6Jq0/xDU/7xdUxpz3gJvf72K5TfPKTn9wVd1qDHvjAB3ad2oteXAsWDuv41E+54vNWXv/61+dud/uHccJtk/zyYbX43LWGAKxjWwLwhiSfthO2EYBHLE8EOqrWeizBo9Z9nNIIIIAAAggggAACDQTqDuP3N5RTJAkBWNcNrswSoKNmAOqRojddlg/9zbpTGVb6JklqqqG+OCU3sx44nMk8DjjsXgP0CX1iu0/oD/rDaesP75Pk+kl+KsmfzzqIWdtuArCOWK3vrw2/u5uAa56tngq0dhPwuk8/N6U3+xdmf34uDmf6Fw447F5p9Al9YrtP6A/6g/5wbsZj57VWArAOdy39+eHlSUDP2Qr9kST/ouMxoOs+/dyUdjF3MXcxv+J3y/ficiZYuEa4RrhGHDcCcX04N2Ozc14rAViPuJ75/1FJHpbk9cuMwBcnqR2a37O+ugse4cvrx92Pux/3s12IXCNcI1wjXCMIwAUfro09AQKwnmet2//6JPdIcq0kr12e/HPFrenr674QEX7c/bj7cffjTgBOvvq6VrpWula6Vp58pdiTEgRgTxJ1Dk+zNid/aZKnJPnDc/g5p71qHM5kCAccdr+r+oQ+sd0n9Af9QX847SOahvMjAA2QFEEAAQQQQAABBBBA4FAIEIBDyaR2IIAAAggggAACCCDQQIAANEBSBAEEEEAAAQQQQACBQyFAAA4lk9qBAAIIIIAAAggggEADAQLQAOlAivynJN+c5DVJ6qVfu8e7dv7F25L8cpJLkvzQnjH4wiT/85hz/qYkD0ny20luuFXmHUl+I8l3JXlykm0ed0nyE1tl/z7JHyX56SSPTPLre8Zn93Q3vD46yS8d0ZYfXPrMh+5pO49r3wcmeVGSmyf5t8uL/B611cbLkrw5yYuTfE2St+y0f7cPbf/5nyb5iwvMa/t7cNckP7lzPnX9f93y9ud6g2b18zq2+3719boWvCnJLyzfq/rvo45/nuQ/J/n0JDdOctXlwQIvS/Ldy3Xk7y4wk7Ufv3stqfN/6/LG0eoTxe8Qj49N8vAkt0tSef2zJG9M8nNJHrw0uPrTnbca/84kv7n0kf+RpPrOPh9nY/C4JL+X5P8s7wU6qp3/bLlm/HiSz9xnEDvn/n1JPjXJdZd+cVTT6pHo9aTED0nyBwfU9oNqCgE4qHSetTGvSvKRS4nbJ/nFndL1o//8JDVAfq/lB/y/Jrlpks/YMwnY/Gh/0fKY1u2m/v4ymKnB2+8uMlB/v16S/7IMAr86yWO3gjYC8FWLCNRrx+tdEDX4rx+5j1h+DPa1N80oAPXD9GPL4KYGrDWovThJCUD9uNXr5OuRv5+8DHjqcb+3TvK3W0ne7UPb+a9B74UeAG3y+vYkL0zy73c66KZf199fuSMAm2tB/UbUQKZuGtxneeFhDe5qoL991DXl+5NU+acuPEuAbrBcPz47yf2SfOeefUl2ryUlNfXG97pGFLeSxz/dszaddLr/esllDfC/fZHgGuzVNa/eel/fnTrq79dP8vnL/6+nA90/Sb0w8wnLu3JO+qzT+vcWBvUd+TfLQPioPvAlSZ6W5G7L9++0tnXteVWbfyDJA5enB+7GX2PrxkndWHGcUgIE4JQmZvBp1YX75csgvi5sdVGvi9P2UQJQd76/bOtf3mR52Vndwfikwed0Lqs7aUBbn12Dt0uXC/jmXGqgU3c6a/C3PTuwGSjdfZGkTfn/sAxoSpTq3RD7epzE69BmAD4sSfXpf5zkU5K8ekncRgCuvczwbPJZs0Ilk5+wMxN0VB86TX1gk9fvWAZpH7Tczd+c4/9a7v5Xv68Zre0ZgN1rQcW8d5JvS1L9vh4dXAP9Ot5/Ee2aRavBcc2a7B71pvQP2OF3mlgddy7HfTdK/r92YXHcbOM+tO+oc6zZoA9e5KZmwbaPujm0EdsSgJpF255Rru9UyXL1teoX28K8TzxaGJTo/HCSByX5liMaVzcVata0hGmX4z6x2D3Xug7U72R9z2tssXuUBNa1oW4c1m+H45QSIACnNDGDT6u+jPWlrDvVdUei/rsu0PWDvTmOEoD6W70boKZ/ayZgX46TBrTVjuMGb3XntgYrdadvcxwnALdYllQdJVT7wqrO8yRehyQA9UNcS3rq7nRJbS1r2BzHCUANdmtAfK8k2y/82xcB+FfLD/FXLN//au/mLl0tDfzyRgGouH+y/PjX3e9a5lPHQ5c7vruCvE/fgePO9bjvRs0a1dLIRySp5SCHdNSNkfp+1KzO2Y6jBKDKPzdJ9YWSiJpx3cejhUHJ0O8sv5G1VGr7+PAkv7Ysof3KfQRwwjnXDHn1/fqt3NxA2YTU6oKaGap/9m3J3wGm6vgmEYDDT3f9YJep19rMj0nyH5PUHcH6YXv6VvOPEoBrLgODupNRd/b25dj8aNcP2Ct2TnpzJ+aowdtVkvy/ZY1vXdg2x3ECUOs6a2lFXQxrScC+HmfjVW2qNtZbUPd9D0ANgGuQXzmupT27d6qPE4DaB1P7RupHvpbKbI7qQ7Wn5rN2El93SC/08p86pe3Baw30b5ak1jXXUTcEvnFZvvDzKwSgYr93WQpSP/C1jO5Hl9mRmknYvqmwr9+H7fM+TgBq+UPd9a2lTbUO/JCOuqFx3yRPSlJruavPH3Un/zgBqGtuXT+rP/zVnoJpZfB1SWoGuJYH/spWW2sJVIlxiUDNiBzacdEypqh9hXVd3Rybm2IlxSUIjlNMgACc4uQMOrVa9/uM5Qe/7v7XuuYa+NQG34/f+owSgHobcK3trX5Ry3/+27Ke87i1foNOcXg1Z9sEXFPUJQG7g7faA1AX8oqtdYvbG583AvC5y4991VFTn7U05EZJbpvkV4e34vxVeDZem7OoO137LgDVllreVUuAaiPn7rERgJod++Plu1KzBLXEo9a3f95OwHGbgGs5WPWlC31sD17re18b2Wu5RklLzXTVf9fSprrb2bIEaNOe+nF/2CITVU9tgq/lHrVOfPuoO6T1z+Y4LWK0Ji+7crzZA1CbmuumSs2uHNLyjmJTS7VekOTjFlA1+K8lpLXuu6Rns7l9IwA1+K2jls6VaNbm4ectm0DXsD5NZVsZ1PX/DYssbfbFbG4k1b/fMDxNbRt1LpX/ujFUv50bQaybCrVJvFYMHOoG+VH8Lng9BOCCp+Ccn0B9SevOf/041+Cnjs2a5u0v6e5TgKpcla9NwXWXY5+OzY92bVrcfULP5ik3xw3e6s5oidL2sfsUoM3ffmvZOFw/lvt8nI1XteuJy3TuvgtADeJr1uZZy4bW3enpjQDs5rKe9vSJR9wFrT5Uswnbd8AqtpY9nIalD9sCUHdl6we5ZnNq8FrCWjcAfqZDAB6fpJY11GzC2QTgv+9sFi6prg2E+3QcJ8d1XbnjWZ6Csk9tPO5c6yZHCU79d10Da71/9fl6WlgJ4+5TgKqeGgjWEqC6abT5vdlnFicxqLb93+UBGzUQ/ptl7Xtda2q2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   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "@interact(st_lagues = st_lagues, area_importance=area_importance)\n",
    "def plot_numerical(st_lagues, area_importance):\n",
    "    ax.clear()\n",
    "    plt.title('Area importance: {0:.1f}'.format(area_importance))\n",
    "    plt.ylabel('St Lagües modified factor: {0}'.format(st_lagues))\n",
    "    sns.barplot(x=df.index, y=st_lagues, data=res[area_importance])"
   ]
  }
 ],
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   "hotkeys": {
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