3D Bar Graphs for paper.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3D Bar Graphs for paper\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import gzip, pickle\n",
    "import os\n",
    "import sys\n",
    "from selectiontest import selectiontest\n",
    "import datetime\n",
    "\n",
    "%matplotlib notebook\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.backends.backend_pdf import PdfPages\n",
    "import seaborn as sns\n",
    "\n",
    "\n",
    "def create_3d_barplot(table, xticklabels, yticklabels, xlabel= None, ylabel=None, zlabel=None, pdfname=None,\\\n",
    "                      azim=None, elev=None, properties=dict(), lgnd=True):\n",
    "    with PdfPages(pdfname) as pdf:\n",
    "        fig = plt.figure()\n",
    "        ax1 = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "        num_elements = table.shape[1] \n",
    "        halflen = int(num_elements / 2)\n",
    "\n",
    "        mask = np.concatenate((np.ones(halflen), (np.zeros(halflen))))\n",
    "        palette = sns.color_palette(\"colorblind\", 2)\n",
    "        col0 = palette[0]\n",
    "        col1 = palette[1]\n",
    "        color = [col0] * halflen + [col1] * halflen \n",
    "        taj_proxy = plt.Rectangle((0, 0), 1, 1, fc=col0)\n",
    "        rho_proxy = plt.Rectangle((0, 0), 1, 1, fc=col1)\n",
    "        xpos = table[0] + 0.4 * mask\n",
    "        ypos = table[1] \n",
    "        zpos = np.zeros(num_elements)\n",
    "\n",
    "        xticks = np.arange(len(xticklabels))\n",
    "        plt.xticks([0, 1, 2, 3], xticklabels)\n",
    "        #ax1.ticklabel_format(axis='x', style='sci')\n",
    "        ax1.set_xlabel(xlabel, labelpad=5)\n",
    "\n",
    "        yticks = np.arange(len(yticklabels)) + 0.5\n",
    "        plt.yticks([0.5, 1.5, 2.5], yticklabels)\n",
    "        ax1.set_ylabel(ylabel, labelpad=5)\n",
    "\n",
    "        dx = np.ones(num_elements) / 4\n",
    "        dy = np.ones(num_elements) / 2\n",
    "        dz = table[2]\n",
    "\n",
    "        ax1.set_zlim([0, 1])\n",
    "        ax1.set_zlabel(zlabel, labelpad=5)\n",
    "        if azim is not None:\n",
    "            ax1.azim = azim\n",
    "        if elev is not None:\n",
    "            ax1.elev = elev\n",
    "        ax1.bar3d(xpos, ypos, zpos, dx, dy, dz, color=color)\n",
    "        if lgnd:\n",
    "            ax1.legend([rho_proxy, taj_proxy],[r'$\\rho $', 'Tajima\\'s D'])\n",
    "        d = pdf.infodict()\n",
    "        for key in properties:\n",
    "            d[key] = properties[key]\n",
    "        pdf.savefig(fig, bbox_inches='tight')\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Configure positive selection data produced by roc_simulation.py into a table and plot. \n",
    "To save, rotate to best position, then adjust azimuth and elevation parameters. Press button at top to \"stop interaction\". Right-click image and \"Open in new tab\". Can then save .png file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "taj_true\n",
      "8s30 0.3522 -1.73 1.73\n",
      "8s31 0.822 -1.73 1.81\n",
      "8s32 0.9613 -1.63 1.99\n",
      "8s20 0.1127 -1.73 1.73\n",
      "8s21 0.4253 -1.73 1.81\n",
      "8s22 0.7068 -1.63 1.99\n",
      "8s10 0.0107 -1.73 1.73\n",
      "8s11 0.0459 -1.73 1.81\n",
      "8s12 0.1146 -1.63 1.99\n",
      "8s00 0.0165 -1.73 1.73\n",
      "8s01 0.0346 -1.73 1.81\n",
      "8s02 0.0571 -1.63 1.99\n",
      "\n",
      " rho_true\n",
      "8s30 0.4593 0.71\n",
      "8s31 0.9549 0.76\n",
      "8s32 0.9941 0.46\n",
      "8s20 0.4914 0.71\n",
      "8s21 0.7866 0.76\n",
      "8s22 0.881 0.46\n",
      "8s10 0.1819 0.71\n",
      "8s11 0.2438 0.76\n",
      "8s12 0.2847 0.46\n",
      "8s00 0.0983 0.71\n",
      "8s01 0.1231 0.76\n",
      "8s02 0.1528 0.46\n"
     ]
    },
    {
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       "                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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = \"/Users/helmutsimon/Google Drive/Genetics/Software/msms/lib/data8\" \n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "\n",
    "job_no = '8s'\n",
    "table = list()\n",
    "\n",
    "key = 'taj_true'\n",
    "print(key)\n",
    "thresholds = np.array([[-1.73, -1.73, -1.63], [1.73, 1.81, 1.99]])\n",
    "for scene in [3, 2, 1, 0]:\n",
    "    for i in range(3):\n",
    "        lower = thresholds[0, i]\n",
    "        upper = thresholds[1, i]\n",
    "        job = job_no + str(scene) + str(i)\n",
    "        filename = 'roc_data_' + job + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        successes = [1 for x in sim_results[key] if not (lower < x < upper)]\n",
    "        success_rate = np.sum(successes) / len(sim_results[key])\n",
    "        print(job, success_rate, lower, upper)\n",
    "        table.append([3 - scene, i, success_rate])\n",
    "        \n",
    "key = 'rho_true'\n",
    "print('\\n', key)\n",
    "thresholds = np.array([0.71, 0.76, 0.46])\n",
    "for scene in [3, 2, 1, 0]:\n",
    "    for i in range(3):\n",
    "        threshold = thresholds[i]\n",
    "        job = job_no + str(scene) + str(i)\n",
    "        filename = 'roc_data_' + job + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        success_rate = np.sum(np.array(sim_results[key]) > threshold) / len(sim_results[key])\n",
    "        print(job, success_rate, threshold)\n",
    "        table.append([3 - scene, i, success_rate])        \n",
    "        \n",
    "        \n",
    "table = np.array(table).T\n",
    "table.shape\n",
    "path = \"/Users/helmutsimon/Google Drive/Genetics/Bayes SFS/Neutrality test/data\" \n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "pdfname = \"barplot3d_\" + job_no + \".pdf\"\n",
    "#xticklabels = ['$5x 10^{-3}$', '$10^{-3}$','$10^{-4}$', '$10^{-5}$']\n",
    "xticklabels = ['5e-3', '1e-3', '1e-4', '1e-5']\n",
    "yticklabels = [10, 20, 100]\n",
    "xlabel = \"Selection coefficient ($s$)\"\n",
    "ylabel = \"Sample size ($n$)\"\n",
    "zlabel = \"Power\"\n",
    "\n",
    "properties = dict()\n",
    "properties['Author'] = 'Helmut Simon'\n",
    "properties['Title'] = 'Positive selection: rho vs Tajima D'\n",
    "properties['Subject'] = 'Datafile: ' + filename\n",
    "properties['Keywords'] = 'Sn = 10, FPR=0.05'\n",
    "azim = -65\n",
    "elev = 6\n",
    "fig = create_3d_barplot(table, xticklabels, yticklabels, xlabel=xlabel, ylabel=ylabel, zlabel=zlabel, \n",
    "                        pdfname=pdfname, azim=azim, elev=elev, properties=properties)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following, we redo the same plot, but using a one-sided threshold of 0.05 for Tajima's D, taken from calibrate_tajD.py job 003. This is a fairer comparison if we are looking for evidence that there is a preponderance of low frequency alleles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "taj_true\n",
      "8s30 0.7482 -1.53 1.99\n",
      "8s31 0.9306 -1.52 1.99\n",
      "8s32 0.9889 -1.45 1.99\n",
      "8s20 0.4059 -1.53 1.99\n",
      "8s21 0.6419 -1.52 1.99\n",
      "8s22 0.8482 -1.45 1.99\n",
      "8s10 0.0725 -1.53 1.99\n",
      "8s11 0.11 -1.52 1.99\n",
      "8s12 0.2016 -1.45 1.99\n",
      "8s00 0.0541 -1.53 1.99\n",
      "8s01 0.066 -1.52 1.99\n",
      "8s02 0.1056 -1.45 1.99\n",
      "\n",
      " rho_true\n",
      "8s30 0.4593 0.71\n",
      "8s31 0.9549 0.76\n",
      "8s32 0.9941 0.46\n",
      "8s20 0.4914 0.71\n",
      "8s21 0.7866 0.76\n",
      "8s22 0.881 0.46\n",
      "8s10 0.1819 0.71\n",
      "8s11 0.2438 0.76\n",
      "8s12 0.2847 0.46\n",
      "8s00 0.0983 0.71\n",
      "8s01 0.1231 0.76\n",
      "8s02 0.1528 0.46\n"
     ]
    },
    {
     "data": {
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       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = \"/Users/helmutsimon/Google Drive/Genetics/Software/msms/lib/data8\" \n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "\n",
    "job_no = '8s'\n",
    "table = list()\n",
    "\n",
    "key = 'taj_true'\n",
    "print(key)\n",
    "thresholds = np.array([[-1.53, -1.52, -1.45], [1.45, 1.51, 1.62]])\n",
    "for scene in [3, 2, 1, 0]:\n",
    "    for i in range(3):\n",
    "        lower = thresholds[0, i]\n",
    "        job = job_no + str(scene) + str(i)\n",
    "        filename = 'roc_data_' + job + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        successes = [1 for x in sim_results[key] if x < lower]\n",
    "        success_rate = np.sum(successes) / len(sim_results[key])\n",
    "        print(job, success_rate, lower, upper)\n",
    "        table.append([3 - scene, i, success_rate])\n",
    "        \n",
    "key = 'rho_true'\n",
    "print('\\n', key)\n",
    "thresholds = np.array([0.71, 0.76, 0.46])\n",
    "for scene in [3, 2, 1, 0]:\n",
    "    for i in range(3):\n",
    "        threshold = thresholds[i]\n",
    "        job = job_no + str(scene) + str(i)\n",
    "        filename = 'roc_data_' + job + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        success_rate = np.sum(np.array(sim_results[key]) > threshold) / len(sim_results[key])\n",
    "        print(job, success_rate, threshold)\n",
    "        table.append([3 - scene, i, success_rate])        \n",
    "        \n",
    "        \n",
    "table = np.array(table).T\n",
    "table.shape\n",
    "path = \"/Users/helmutsimon/Google Drive/Genetics/Bayes SFS/Neutrality test/data\" \n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "pdfname = \"barplot3d_\" + job_no + \"a.pdf\"\n",
    "xticklabels = ['5e-3', '1e-3', '1e-4', '1e-5']\n",
    "yticklabels = [10, 20, 100]\n",
    "xlabel = \"Selection coefficient ($s$)\"\n",
    "ylabel = \"Sample size ($n$)\"\n",
    "zlabel = \"Power\"\n",
    "\n",
    "properties = dict()\n",
    "properties['Author'] = 'Helmut Simon'\n",
    "properties['Title'] = 'Positive selection: rho vs Tajima D'\n",
    "properties['Subject'] = 'Datafile: ' + filename\n",
    "properties['Keywords'] = 'Sn = 10, FPR=0.05'\n",
    "azim = -65\n",
    "elev = 6\n",
    "fig = create_3d_barplot(table, xticklabels, yticklabels, xlabel=xlabel, ylabel=ylabel, zlabel=zlabel, \n",
    "                        pdfname=pdfname, azim=azim, elev=elev, properties=properties, lgnd=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bar plot for negative selection data. This uses .05 threshold for rho .\n",
    "\n",
    "Thresholds for rho are from calibration_f103.csv and calibration_f104.csv.\n",
    "\n",
    "Thresholds for Tajima's D are from calibration_tajD_f006.csv and calibration_tajD_f007.csv which have a two-sided threshold of 0.05 (one-sided threshold of 0.025)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "taj_true\n",
      "t1-00 0.2929 -1.72 1.68\n",
      "t1-01 0.463 -1.72 1.67\n",
      "t1-02 0.5192 -1.73 1.67\n",
      "t1-10 0.1889 -1.73 1.69\n",
      "t1-11 0.2746 -1.73 1.67\n",
      "t1-12 0.3596 -1.72 1.67\n",
      "t1-20 0.09 -1.73 1.71\n",
      "t1-21 0.1202 -1.74 1.66\n",
      "t1-22 0.1818 -1.72 1.67\n",
      "\n",
      " rho_true\n",
      "t1-00 0.6928 -9.0\n",
      "t1-01 0.8064 -19.0\n",
      "t1-02 0.8373 -33.0\n",
      "t1-10 0.6199 -6.0\n",
      "t1-11 0.7286 -15.0\n",
      "t1-12 0.7711 -26.0\n",
      "t1-20 0.4363 -3.2\n",
      "t1-21 0.5883 -10.7\n",
      "t1-22 0.6426 -19.0\n"
     ]
    },
    {
     "data": {
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       "        return MozWebSocket;\n",
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       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
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       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
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       "\n",
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       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
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       "    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",
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       "    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",
       "    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",
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       "\n",
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       "            // 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",
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       "        var icon_img = $('<span/>');\n",
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       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
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       "\n",
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       "\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",
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       "    for (var ind in mpl.extensions) {\n",
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       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
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       "\n",
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       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
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       "\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",
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       "\n",
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       "\n",
       "\n",
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       "    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",
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       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
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       "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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = '/Users/helmutsimon/Google Drive/Genetics/Bayes SFS/Neutrality test/fwdpydata'\n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "\n",
    "job = 't1-'\n",
    "table = list()\n",
    "\n",
    "key = 'taj_true'\n",
    "print(key)\n",
    "lower_thrs = np.array([[-1.72, -1.72, -1.73], [-1.73, -1.73, -1.72], [-1.73, -1.74, -1.72]])\n",
    "upper_thrs = np.array([[1.68, 1.67, 1.67], [1.69, 1.67, 1.67], [1.71, 1.66, 1.67]])\n",
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        lower = lower_thrs[i, j]\n",
    "        upper = upper_thrs[i, j]\n",
    "        filename = 'fp_roc_data_' + job + str(i) + str(j) + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        successes = [1 for x in sim_results[key] if not (lower < x < upper)]\n",
    "        success_rate = np.sum(successes) / len(sim_results[key])\n",
    "        print(job + str(i) + str(j), success_rate, lower, upper)\n",
    "        table.append([i, j, success_rate])\n",
    "        \n",
    "key = 'rho_true'\n",
    "print('\\n', key)\n",
    "thresholds = np.array([[-9, -19, -33], [-6, -15, -26], [-3.2, -10.7, -19]])\n",
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        threshold = thresholds[i, j]\n",
    "        filename = 'fp_roc_data_' + job + str(i) + str(j) + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        success_rate = np.sum(np.array(sim_results[key]) > threshold) / len(sim_results[key])\n",
    "        print(job + str(i) + str(j), success_rate, threshold)\n",
    "        table.append([i, j, success_rate])  \n",
    "        \n",
    "        \n",
    "table = np.array(table).T\n",
    "path = \"/Users/helmutsimon/Google Drive/Genetics/Bayes SFS/Neutrality test/data\" \n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "pdfname = \"barplot3d_fwdpy.pdf\"\n",
    "xticklabels = ['-2e-2', '-1e-2', '-5e-3']\n",
    "yticklabels = [1, 2.5, 5]\n",
    "xlabel = \"Selection coefficient ($s$)\"\n",
    "ylabel = \"$\\lambda $\"\n",
    "zlabel = \"Power\"\n",
    "properties = dict()\n",
    "properties['Author'] = 'Helmut Simon'\n",
    "properties['Title'] = 'Negative selection: rho vs Tajima D'\n",
    "properties['Subject'] = 'Datafile: ' + filename\n",
    "properties['Keywords'] = 'n = 20'\n",
    "azim = -83\n",
    "elev = 4\n",
    "fig = create_3d_barplot(table, xticklabels, yticklabels, xlabel=xlabel, ylabel=ylabel, zlabel=zlabel,\n",
    "                        pdfname=pdfname, azim=azim, elev=elev, properties=properties)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bar plot for negative selection data. This uses .05 threshold for rho .\n",
    "\n",
    "Thresholds for rho are from calibration_f103.csv and calibration_f104.csv.\n",
    "\n",
    "Thresholds for Tajima's D are from calibration_tajD_f004.csv and calibration_tajD_f005.csv which have a two-sided threshold of 0.1 (one-sided threshold of 0.05)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.     0.     0.     1.     1.     1.     2.     2.     2.     0.\n",
      "  0.     0.     1.     1.     1.     2.     2.     2.    ]\n",
      " [0.     1.     2.     0.     1.     2.     0.     1.     2.     0.\n",
      "  1.     2.     0.     1.     2.     0.     1.     2.    ]\n",
      " [0.5012 0.6708 0.7264 0.3665 0.5042 0.5716 0.2058 0.2904 0.3604 0.6928\n",
      "  0.8064 0.8373 0.6199 0.7286 0.7711 0.4363 0.5883 0.6426]]\n"
     ]
    },
    {
     "data": {
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       "window.mpl = {};\n",
       "\n",
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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",
       "    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",
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       "    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",
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       "            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",
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       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
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       "\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",
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       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "path = '/Users/helmutsimon/Google Drive/Genetics/Bayes SFS/Neutrality test/fwdpydata'\n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "\n",
    "lgnd = False\n",
    "job = 't1-'\n",
    "table = list()\n",
    "\n",
    "key = 'taj_true'\n",
    "lower_thrs = np.array([[-1.49, -1.49, -1.48], [-1.49, -1.48, -1.49], [-1.48, -1.48, -1.49]])\n",
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        lower = lower_thrs[i, j]\n",
    "        filename = 'fp_roc_data_' + job + str(i) + str(j) + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        successes = [1 for x in sim_results[key] if x < lower]\n",
    "        success_rate = np.sum(successes) / len(sim_results[key])\n",
    "        table.append([i, j, success_rate])\n",
    "        \n",
    "key = 'rho_true'\n",
    "thresholds = np.array([[-9, -19, -33], [-6, -15, -26], [-3.2, -10.7, -19]])\n",
    "for i in range(3):\n",
    "    for j in range(3):\n",
    "        threshold = thresholds[i, j]\n",
    "        filename = 'fp_roc_data_' + job + str(i) + str(j) + '.pklz'\n",
    "        with gzip.open(filename, 'rb') as sim_results:\n",
    "            sim_results = pickle.load(sim_results)\n",
    "        success_rate = np.sum(np.array(sim_results[key]) > threshold) / len(sim_results[key])\n",
    "        table.append([i, j, success_rate])  \n",
    "        \n",
    "        \n",
    "table = np.array(table).T\n",
    "print(table)\n",
    "path = \"/Users/helmutsimon/Google Drive/Genetics/Bayes SFS/Neutrality test/data\" \n",
    "if not os.getcwd() == path:\n",
    "    os.chdir(path)\n",
    "pdfname = \"barplot3d_fwdpya.pdf\"\n",
    "xticklabels = ['-2e-2', '-1e-2', '-5e-3']\n",
    "yticklabels = [1, 2.5, 5]\n",
    "xlabel = \"Selection coefficient ($s$)\"\n",
    "ylabel = \"$\\lambda $\"\n",
    "zlabel = \"Power\"\n",
    "properties = dict()\n",
    "properties['Author'] = 'Helmut Simon'\n",
    "properties['Title'] = 'Negative selection: rho vs Tajima D'\n",
    "properties['Subject'] = 'Datafile: ' + filename\n",
    "properties['Keywords'] = 'n = 20'\n",
    "azim = -83\n",
    "elev = 4\n",
    "fig = create_3d_barplot(table, xticklabels, yticklabels, xlabel=xlabel, ylabel=ylabel, zlabel=zlabel, \n",
    "                        pdfname=pdfname, azim=azim, elev=elev, properties=properties, lgnd=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Do examples for expanding population"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "taj_true\n",
      "4d00 0.0295 -1.73 1.73\n",
      "4d01 0.1433 -1.73 1.73\n",
      "4d02 0.2981 -1.73 1.73\n",
      "4d03 0.2357 -1.73 1.73\n",
      "4d10 0.0125 -1.73 1.81\n",
      "4d11 0.0331 -1.73 1.81\n",
      "4d12 0.0468 -1.73 1.81\n",
      "4d13 0.0275 -1.73 1.81\n",
      "\n",
      " rho_true\n",
      "4d00 0.2409 0.71\n",
      "4d01 0.4929 0.71\n",
      "4d02 0.5685 0.71\n",
      "4d03 0.3188 0.71\n",
      "4d10 0.0533 0.76\n",
      "4d11 0.1177 0.76\n",
      "4d12 0.1127 0.76\n",
      "4d13 0.0386 0.76\n",
      "[[0.     0.     0.     0.     1.     1.     1.     1.     0.     0.\n",
      "  0.     0.     1.     1.     1.     1.    ]\n",
      " [0.     1.     2.     3.     0.     1.     2.     3.     0.     1.\n",
      "  2.     3.     0.     1.     2.     3.    ]\n",
      " [0.0295 0.1433 0.2981 0.2357 0.0125 0.0331 0.0468 0.0275 0.2409 0.4929\n",
      "  0.5685 0.3188 0.0533 0.1177 0.1127 0.0386]]\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 / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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 overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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XLJMBMC4hhEvogJUgApQgWRSgHCQTNaM3BfamACY/KOcPaQCVIAKUIGEFCAcJCSXJy+mjQmAnhy4bDQVoAJUgApYp4AGB3Xq1FGnZjAlnwI4cUQ7zSQrKyv5OmiwR5wCNiggs1MBKkAFqID3FEAMumXLlkm1atUiBiD2Xo/Y4nAFtm/frs4JbtiwoaSlpVGgMAUIgBwSVIAKUAEq4EsFNm3aJLt27VIQiFMpEGiYyfsK4ISQAwcOKPjDecXRTgrxfk+N9YAAaEw/5qYCVIAKUAGPKgBQyM3NVRDIlHwKAP6qV69OsI9iWgJg8o159ogKUAEqQAUSUADTwYcPH04gBy91uwKIdchp35KtRAB0+yhm+6gAFaACVIAKUAEqYLICBECTBWVxVIAKUAEqQAWoABVwuwIEQLdbiO2jAlSAClABKkAFqIDJChAATRaUxVEBKkAFqAAVoAJUwO0KEADdbiG2jwpQASpABagAFaACJitAADRZUBZHBagAFaACVIAKUAG3K0AAdLuF2D4qQAWoABWgAlSACpisAAHQZEFZHBWgAlSAClABKkAF3K4AAdDtFmL7qAAVoAJUgApQASpgsgIEQJMFZXFUgApQASpABagAFXC7AgRAt1uI7aMCLlIAZ6ci4af2O/5OSUk5ppXhf0e6xkXdYlOoABWgAr5TgADoO5Ozw1SgSIFQmIv2dyTg0/536NAhVU4k2AvXOPSa/Px8wats2bLH5I0GjaH/jwWa8YBnPNcYgdp49OAYpAJUgAo4rQAB0GkLsH4qYFCBUE9cSVAXDnOh+TQABLzg/9rPaCCEa/Ly8kqEv/DytW5u2bJF/vrrL2nduvUxIBpLhvDyQtsY2s5InslobdEDsCW1MxqsxgOx8eTV6o4FwtH6pSdfvMAcy358nwpQAXcpQAB0lz3YGp8rEA5w8XrmjMBcSd66aOYIBALKi5eampqwxXJzcxUAtm3bNuG8ZmUoCQi1OuK5JtQ+JbXNSFleAd1YcBn6PvTA2CkJjKM9fMQzXmO1xUjZZo1BlkMFnFaAAOi0BVh/0ipgdIpVE2bBggVSt25dKV26dLFnLl6vjBXTkYA/eP8OHjwoaWlpxV/kqCvSK9zAmzdvlg0bNjgKgEk76EI6ZgQ6I+kTT3nxXLNp0ybZunWrNG/evLgabZyW5L2Ndk0kz3As+8bzuYgGkfFCq3ZdLBiN57MczzVGoDYePWJpyve9pwAB0Hs2Y4ttVsCJKdbQLo4fP15Nl1aoUMH0nqNvhw8fVt487We037X3CwoKVDvCPVORGhcJCFFnYWGhZGVlqTI0T1D4tYn8P9K18f4vWhviyW+6QXxQILy/AMBWrVqZ0tt4oBMVxXNdPNfEW1ak69wOupdffrk8+OCD0rlzZ1Nsw0LcrQAB0N32YetMVkAPzB04cEDwqlSpUnFrQtfJhYJQrKf9SE/psbo4btw49WVZsWLFEi9FmwBnsQAu9H1AHRI8eRkZGVKqVKnin6G/a+9p/0tPT1d1AZJQL17wDGq/l/S/7du3C7yADRs2jOv6eMqNdE2i7YpWRkmiJwqw8UBlSWXGC6tm1GOVV8hsAIz1+UmW982E02hl4UHzzTfflNNOOy1ZZGM/SlCAAMjh4VkFzJpijQRzoV9+GzduVGvWOnTocJxWVn1Jal4ywNr06dPVFDDgK5KXLtSDp/UF18YLc7gOAJhIMrIGEPC3fv16adeuXSJVOnJtONCaAZXxAK0Z9USD8tD/x4LbeLyy8cKmBq94mMIO8qpVq0b1ACdapp52OjKgXFwpxgWm5YcPHy59+vRxcUvZNLMUIACapSTL0a2AHq+c9gUZWqlVXjkAIIClY8eOuvuIKc9EPHO4NrQ/2dnZaso0GtSF/h8wZxWYagIYAUDsAl63bp0nAFC3wT2SMVHQjAcqQ6E5Euzu3r1brR+tUqVKid7jRLzKyeS9NeLlDQXhRIcg9D711FNlxIgR0qtXr0Sz83oPKkAA9KDR3Nxks2Fu27ZtasNAy5YtVbetmGKNpScAEMDSqVMndakGP/GumQPMIQ9SItOsgDpMtU6YMEFatGhxzBR0rDZb/T4B0GqFk7d8fJ6xDED7TFvVU3pvj92UVZJXddCgQeoBFQ9nNWvWlBNOOEHdq3D/ueeee6R9+/ZWmYnlOqgAAdBB8b1eNdaAaWAT6pELX18Sa4pV0yGS1wo3pJUrV0qXLl0skQvtD98EEQ52e/fuVWsAAWS4ScKbh4SbY0nr5MKnYXFD1eOZAwBiaiZ0DaIlYiRQKAEwAbF46TEK2AWAyS57SZ7WaB7RaP///vvv1bT822+/Leeff77Url1b3Rdxj8ffWK8bT5o4caI899xzMnPmTMFu76+++koGDBhQYlZscrv77rtl4cKFCj4feughufrqq+OpjtcYVIAAaFBAP2fHDQM3FCu9cgDA5cuXS9euXWNKjRtiLJjTTqEI39GKadNo06uYrtqxY4c0a9bsGA+enhh4MTsR4QIAIOquXLmynuyW5CEAWiKrLwoFAOLzBK82k3sUwP2zfv36Mnr06OLZjkRb9+OPP8qUKVNUiKcLLrggJgCuXr1a3dtuuukmuf766+W3336TO++8UwCkZ5xxRqLV8/oEFSAAJigYLz+qACBK8wCarQtuRnj6RNDgVatWSZMmTY5ZQxctdAnaATBL1DNX0iYItAE3KqdCI+CpumnTpkkFgGvXruW0ktkfGo+Uh/W0O3fuJAC6zF6452KzGSAu0oa3RJsLx0AsD+B9992nYA+xTrV06aWXyq5du+Snn35KtEpen6ACBMAEBePliQNg6I7WRGLOaVPHqDEnJ0dBXTxgl+iO1lg2xa5VK6ehY9VPAIylEN/3kgIEQHdaC/dbTP3++uuvpmzQigcAe/ToIW3atJGhQ4cWi4JdyPACYrMQk7UKEACt1TepS8dT2v79++PyzGmewkRCk+BaeAqWLFki3bt3d0xLNwAgdudh16RbktEpYHoA3WJJ+9tBALRf83hqBABiDZ4WeD6ePCVdEw8AYm3hNddcI/fff39xUT/88IOcffbZat01oh8wWacAAdA6bZO+5FmzZqndfPHGnMOmiUQ3QWAX8KJFiwRPik4lrENcsWKFZRtRYvVr0qRJago8WQAQp0CsWbOGU8CxDJ+k7wMA8fAYehRcknbVU90CANaoUUMmT55syg5tAqD7zU8AdL+NXNtCK9cAap0GYGJ3mNMAGO9GFCuMRQC0QlWW6ZQCCKmE6T0CoFMWiFwvAPDEE0+U33//XW3MMJriAUBOARtV2Vh+AqAx/Xyd2w4AxG7B+fPnS8+ePR3TGh6rpUuXSrdu3RxpA57IGzVqpE5OcEsyMgVMD6BbrOhMOwiAzugeq1YAYLVq1QQzO1hyYjTFA4DYBIIpX9zjtXTZZZepXeLcBGLUArHzEwBja8QroihAALRnaCQjAGJXtRk7De2xAGsxUwEA4J49e0zxMpnZLr+XBQDEMhPAGB449aR9+/ap5TJIOFf4hRdekN69e6sYprVq1VJr/XCs5gcffKCu0cLA3HrrrXLttdfK2LFj5Y477mAYGD3i68hDANQhGrMUKWAHAGITyNy5cx09mogewONHvFEPIAHQv3cRbABCcHUzphn9q6L5PQcAVqxYUW26a9Cgga4KsIEEwBeerrrqKnnvvfdUgGes/8V1WsLvd911l1rrffLJJ8vgwYMZCFqX+olnIgAmrhlzHFHADgDEYvHZs2dHvKnYZQhsRFm8eLFjO5ERWBU3ZEzPuCURAN1iCe+1gwDoTpsBAMuXL69CXp1yyinubCRbZaoCBEBT5fRXYQjUrB2LZlXP3QCATm9ESTYABFAjuDengK361Li7XAKgO+2Dh7oKFSqoadk6deq4s5FslakKEABNldNfhdkBgNgtiHMl+/Tp45i4TgPg1KlT1RFNyeIBJAA6NpRdUTGmABE/FKfbMLlHAczo4LhJADrW6zElvwIEwOS3sWU99BMA4qgip3YiAwDr1asnJ5xwgmW2TLRgI1PABMBE1U6u6wmA7rRnXl6eijSATRonnXSSOxvJVpmqAAHQVDn9VZgdAIjdgn/88Yf07dvXMXGdDkWTjACIdUYdO3Z0zKas2DkFCIDOaV9SzfDKIg7gpk2bpHr16u5sJFtlqgIEQFPl9FdhdgAgdgsiMGm/fv0cE9fpncjTpk1Th7S76aZs1ANIAHRsODteMQHQcRNEbADutTgJBCcfuSnmqDvVSo5WEQCTw46O9IIAaI/sBEB7dGYt9iiATQYHDx40JdiwPS32Ry3YcIe1f1iigbWATMmvAAEw+W1sWQ/tAEAEFgUAnXbaaZb1I1bB8ADOmTPHsVA0yQaA2FSDYLGcAo418pLzfQKgO+2KpS7Y/Yv7HXYDMyW/AgTA5LexZT20CwCxBu7000+3rB+xCnY6FM306dOldu3aan2OW5KRKWACoFus6Ew7CIDO6B6rVnj+EP8PkRfKlSsX63K+nwQKEACTwIhOdcEOAMTCZMTBcxIAcUPE+ZiRItzboT0B0A6VWYddChAA7VI6sXqw9g/hpjDrkpOTk1hmXu1JBQiAnjSbOxptBwAeOHBAJk2aJGeccYZjnXY6FiE2wdSsWdNVoRnoAXRsOHq+YgQBR8iRJk2aeL4vydSB3NxcadiwoeCem52dnUxdY1+iKEAA5NDQrYCfAPDPP/90LBRNMgLg8uXLpVOnTrrHHjN6VwECoDtth/h/gHLAealSpdzZSLbKVAUIgKbK6a/C7ABA7BacMGGC9O/f3zFxnY5FSAB0zPSs2AIFCIAWiGpCkevXr1ens+C+npaWZkKJLMLtChAA3W4hF7fPDgA8dOiQjB8/Xk0Bp6SkOKIG4mPNmDHDMQ8g6kZ8LrzckoxMAWO34bJly+gBdIsxbW4HADA/P18aN25sc82sriQFEJ+xRYsW6nz31NRUiuUDBQiAPjCyVV30EwA6GYzarQCIs0P1QDkB0KpPpDfKRRBwjB0CoLvsBTBv27atgnMCoLtsY1VrCIBWKeuDcu0AQKxHGTdunNoF7NRNyelYhABAnM158sknu2ZUwQNIAHSNOTzVEAKgO82lxebErItT91p3KpO8rSIAJq9tLe8ZpgoAgVYmPI2OHTvW1wCIs5ARA5AAaOVIY9l2KQAAxH2jUaNGdlXJeuJQAMsyunXrJgi9RQCMQ7AkuIQAmARGdKoLdgIgTgJxamGy0x7AZATApUuXSufOnZ0auqzXQQXgacK9gwDooBEiVL1kyRLp1auXYM0zAdBdtrGqNQRAq5T1Qbl2ACCmGX/77Tfp16+fpKenO6Kq08GoAYDVq1dXsQDdkrRNIFgDmOg6QKwBJAC6xZL2t4MAaL/m8dS4cOFCdeQm4p4SAONRzPvXEAC9b0PHemAHAGKqaMyYMY4CoNPBqBGD8IQTTkgaAMRZo/A20APo2EfX0YoJgI7KH7Xy+fPny5lnnik4+jLRhzp39oitiqUAATCWQnw/qgJ2AmDfvn0lIyPDEWu4AQCrVasmtWrVcqT/kSo14gEkALrGjI40BACI8YNTJ5jco8CcOXPkvPPOE3joCYDusYuVLSEAWqlukpdtBwCijl9//VX69OnjWHR6pwFw5syZUrVq1aQCwMWLF0uXLl2S/BPC7kVSAKfABINBAqDLhgfOO7/wwgtl69atBECX2caq5hAArVLWB+X6BQCdPo3EaQCEnRGOB+Eh8MLv0AQ/4SnAeiHtpf0d+v/w/wGocepAs2bNVL6S8mjv0yORPDcUAqA7bYm1xpdeeqls3ryZAOhOE5neKgKg6ZL6p0A7ABBTRb/88ov07t1bMjMzHRHX6dNIAIBVqlSR2rVrm9p/eGGwySYU7jTAC/2pxfuD/llZWeqF3wFnKEN7wVb4HT+j/a7VifJRTvi1WlnhHQ2HxJIAM16oTARaY5WpZzOMqcb0UGEEQHcaC8Hur7jiCtm4cSMB0J0mMr1VBEDTJfVPgXYAIIDg559/VuEJAAxOJKcBEGYzLTMAACAASURBVFMzlStXTggAAVYa2IV770LhDtdhd7UGdaGAF/o7DocP9cIZXQNY0hSwBpHhP+MFzFgAGgk6S8oTWq/WpkjjMBKURgLHeK8LzRvt90RB2InPT3idAECkBg0auKE5bMMRBaZOnSrXXnutbNiwgQDok1FBAPSJoa3opt8A0KnTSACAlSpVkjp16igzYmd06HRs+O8APryQNK9duPcuFPj0hNcxAoDYZbho0SLPrgGMx+sZyxNakoc0HkCNVT7ej5TMhMpYXtFoda1du1Z5j0855ZTjpv851W/FnTq+MidPniw33nijrFu3jgAYn2Sev4oA6HkTOtcBOwAQvfvpp5+kZ8+ekp2d7Uhn7TqODl/aOPkkHOgwJaN9meI97bD2aN467f/w2lkVz8vPAOjIIEyw0ljT8pEAMhZURvKExvpfpPcxfqMBqjaVHs/0fCwAjeVp1ZM/maf6J06cKLfccousWbOGAJjg582rlxMAvWo5F7TbTgDs0aOHlC5d2pFem3EcXaSNFBroaVOyAE18MSLcTSjcIWxK2bJlpUaNGsX/h9fOSW8JAdCRoZgUleLIMcBXvXr1jlkragWUxgLUWNAbSfB4Ni0ZnbI34qnVC6njx4+XO+64Q1atWuXovSUpBrlHOkEA9Iih3NhMuwAQawC7d+/uOABGOo4u1kYKDe6ibaTQQC90Sjbcazd79mypUKGC1K1b1zXDwCgA4tSBrl27uqY/bIh9CmgAWL9+ffsq1VmTHoCMBZV6pv9LKjPWVH8sTyiCsn/00UcKxmEbxALEkhHMIODB89FHH9WpHrO5XQECoNst5OL22QWA2AUMWMjJybFVDW0jBc4Cxk5cBK6FNzB8U0WsjRTa+rvwjRTxdgYBWsuXL08AjFcwXudqBXAMIM719gIAulpIkZg78OPxqmLKd+zYsWr3L7yAV199tbrH4V6HmYbnn38+IRleffVVee655yQ3N1datmwpL7/8snTo0CFqGUOHDpXXX39drT1EtIOLLrpIhgwZ4timv4Q66/GLCYAeN6CTzfcyACa6kQI3RARjxjrEUG+dBnd6NlLEa7tkA0CcNbpgwQJ6AOMdAEl2HQHQnQbFTMvgwYMFO/T1ppEjR8qVV14pw4YNk44dOwrgbtSoUersb5xmFJ4+/vhjtfP43XffVZvC4IEEgCIe4QsvvKC3GcwXpwIEwDiF4mXHKwDPF6Y2rU44CQTnxpYpUyZmVdE2UoSGPilpI0XoblmAHrx26KeT5xEDAMuVK6d2TbolGZkCJgC6xYrOtAMwgAcmrAFkco8CP/zwgzz++OOC5Rl6E6Cvffv28sorr6gicJ+oWbOm3H777TJo0KDjir3tttsUcP7222/F791zzz2CmITYlcxkrQIEQGv1TerS7QTATp06qTWAkWLahe6ajbaRItKO2Xg3UsBbCAB06jziuXPnqrU4BMCk/jj5pnNYc4aNTgRAd5n8u+++k6eeekrmz5+vq2GYMsY9+vPPP5cBAwYUl3HVVVcJQj998803x5ULDyB2HmOZD6aJsQHl7LPPVgGpH3jgAV3tYKb4FSAAxq8VrwxTwCwAjLWRYtu2bcpjABDDguZIMe3CAxmbGf7E6fOICYD86CWTAgRAd1rz22+/lWeeeUZwv9GTsIYQkQoQUBozNlq69957ZcKECcqrFym99NJL8q9//UutZ8Q9/qabblJrApmsV4AAaL3GSVtDPAAY60QKbWq2pI0UmDJq2rSpOg1D70YKI0ZwGgDnzZunNsC4yWNidAoYXoZu3boZMQvzelQBAqA7Dff111+rdXeIOqAn6QFAbDrBer8nnnhCrRlcsWKFDBw4UG644Qa1HpHJWgUIgNbqm9SlY/3fnj17VODiaFOzmBZACj+RIpIXL9pGCqwPwboSrINzIgF2MEXRp08fBaB2JwKg3YqzPisVwJovfP7dtKTByv56pewvv/xS7dj9888/dTVZzxQwwntheQ92DWtpxIgR6kQSRF8wcyZHV6eSPBMBMMkNbGX3tmzZotz6JZ0jq22kMPJBRoiCtm3bqlAoTiQNAHv37q2+uOxObgRATNcA+vUEncVDA/pED6DdI8kd9REA3WGH8FZgty52786YMUN3A+HFw1o+gCQS7p21atUSbPaItAkE9/V+/fqpqWctffLJJ3LdddfJ3r17VbggJusUIABap23Sl4ypUS3AsZWdHTdunLRu3VoFQ3YiAXYQIqFXr16OxKbCdCnCz7gpbhoB0ImRmBx1EgDdaUeEcHnnnXdk2rRpuhuIMrDp44033lAgiDAwn332mWDa/4QTTlAhYrBOEHH+kBBkGtPOb775ZvEU8M0336we+FEWk7UKEACt1TepS49nDaAZAhAACYBmjCOW4Q4FCIDusEN4K7Aj94MPPpApU6YYaiBCwGiBoFu1aiXY5AHPIBIeouvUqSPvvfee+hubPp588kn58MMP5a+//lKxVs8991z1P6ce+A113mOZCYAeM5ibmmsXAGKhMCLKV6xY0ZHuO+0BRNBkTD03aNDAkf5HqpQeQNeYwnMNWbRokfJou+loQ8+JaEGDsfYO068TJ060oHQW6UYFCIButIpH2uQXAIQ5fvrpJ+nZs6f64rI7uRUAtQ0+WAeYSMIaQISawAJwJv8pQAB0p83ff/99FcMPD9xM/lCAAOgPO1vSS7sAEDGkmjdvLpUqVbKkH/EUijWAABYEOrU7EQDtVpz1WakAAdBKdfWXPXz4cEEoGGy6Y/KHAgRAf9jZkl7aBYCYktDiAFrSkTgKdRIAcTQTTk5o2LBhHC215xLtyD3UlqgHELv7cLwdPYD22MpttQAA8SCFtWBM7lEAG0BwGghOPWLyhwIEQH/Y2ZJe+g0AEbYEAZntTgRAuxVnfVYqgPGMzxEB0EqVEy/7rbfeUtEO8GLyhwIEQH/Y2ZJe2gWAkyZNkiZNmkiVKlUs6Uc8hSIQdNeuXR0DQATJbtSoUTxNteUaegBtkTkpKyEAutOsCN2CoPs//vijOxvIVpmuAAHQdEn9U6BdADh58mQFPwgR4FT69ddf1fmWZcqUsb0JmDJDQFQCoO3Ss0ILFCAAWiCqCUW+9tpragfw999/b0JpLMILChAAvWAll7aRAGiPYZIRAHHeaI8ePewRkLW4SgFsaipbtqzUrl3bVe3ye2MQvw9BoEePHu13KXzTfwKgb0xtfkdDpwHNL/1oiQhMihh41apVs7KaEsuGBxBnVuKLy+4EAMRReo0bN7a76qj1GZ0CJgC6xpS2N4QAaLvkcVX44osvqnOAsROYyR8KEAD9YWdLemkXAE6dOlUdg+YkAGJnHKLZOwGAODkBO22TBQBxyPusWbPoAbTkU+n+QgmA7rTR//73PxWf84svvnBnA9kq0xUgAJouqX8KtBMA69Wrp86SdCphcTTOtnQKANFvbIRxSzLiASQAusWKzrQDAFiuXDmpVauWMw1grREVwJm8sM2oUaOokE8UIAD6xNBWdNMuAMS6FBwbVb16dSu6EVeZAMD27durLy67Ew5Sh9YEQLuVZ31WKDB//nwpX748AdAKcQ2UifN7ly5dKiNHjjRQCrN6SQECoJes5bK2+gkAER2/bdu26ovL7kQAtFtx1melAgRAK9XVX/Yzzzwjq1atko8//lh/IczpKQUIgJ4yl7saaxcATp8+Xe0YPPHEEx0TwGkAxI7rU0891bH+h1dsdAp45syZ6mxlJv8pQAB0p82feuopWb9+vYwYMcKdDWSrTFeAAGi6pP4p0C4A/P3336VmzZpy0kknOSbuuHHjpE2bNo54ADEtU1hYSAB0zPqs2EwFAIAVKlRQn2km9yjwxBNPSG5urrz//vvuaRRbYqkCBEBL5U3uwv0GgK1bt1ZfXHYnAqDdirM+KxWYN2+eVKxYkQBopcg6yn7sscdk+/btMnz4cB25mcWLChAAvWg1l7TZLgCcMWOG1KhRQ72cSuPHj5eWLVuqLy67EwCwoKBAmjZtanfVUeszMgW8f/9+FW+MU8CuMaetDSEA2ip33JU9+uijsnv3bnn77bfjzsMLva0AAdDb9nO09XYB4B9//KHW/5188smO9ddJAFy2bJkcPnyYAOiY9VmxmQoQAM1U07yyHnroITl48KC8+eab5hXKklytAAHQ1eZxd+MIgPbYBwCYn58vzZo1s6fCOGqhBzAOkXhJRAUAgJUqVXL0gY6mOV6BBx98UD1ovv7665THJwoQAH1iaCu6aRcAYroQQaCdXDQ+YcIEad68ufrisjstX75c8vLykgoA4dXt1auX3VKyPhcogNMmKleuTAB0gS1Cm3D//fcLog289tprLmsZm2OVAgRAq5T1Qbl2AiCOgXPy5ICJEyeqKVh8cdmd3AaAWI944MABwYkeOKIuLS1NnVWsvfA3/h/6v1DNsAaQAGj3KHJPfQRA99gitCX33nuvpKeny8svv+zOBrJVpitAADRdUv8UaBcAImZc1apVfQ2Ahw4dUh5IOxLsCo8j1gMB9PAK/R3T0YC8zMxMdUIJvAahL/wvNEWCQZSPY/VCIbGk38MhM958uA7148XkDgUAgFWqVHF0U5c7lHBXK/71r39Jdna2DB061F0NY2ssU4AAaJm0/igYX+RWp1mzZinPG4JBO5XgAUQgZnxx2Z1WrFihAMxMAASwhYNdKOThfQBe6dKli1/4ctD+hqcA64WQwuEqEhSGAiLqxekmWNMYDo+Idxj+Pz1/h9soHBiNAGUk+CypPALosdaYM2eOeqBzcle/3Z9hL9R31113qaMucSYwkz8UIAD6w86W9dIvADhp0iR1Fq9TAAhoatGiRdx2BIQB0CJ58AB68CgCZAB0GtiFAh5+B9RES0Y2gaBNCO1j1RpAtC0UQo1CpZ78sQA0lgfTKKCG5ncbgBIA4/4Y23rhwIED1YM2zgRm8ocCBEB/2NmyXtoBgLNnz1bx9+rUqWNZP2IVPHnyZGnUqJHyXNidVq5cKVg3Fw6A8IwB5KJBHtbqlSpVqhjwNO+dBnrw8OmdGnUzANptn/D6wgHUKi+nVm4kQDUKoIl6OWMBbeg4IwA6PUIj13/77bcL1lo/++yz7mwgW2W6AgRA0yX1V4F2ASBO4Khbt65j4joFgIA4BILGhgvAZ+g0LeAPKdxzFwp6mKq1IhEArVDVnDJjAagdQBrek9B1oABWjEs8nMQCx3jfj+Ux1fugY45FvFHKrbfeqqblhwwZ4o0Gs5WGFSAAGpbQ3wXYAYDwGJQvX95xAGzYsKF6QjYz4csaIBcKdqFr8zCNiy9BfMFheiYU9gB6WVlZur14RvphFABxvnPv3r2NNIF5XaxASes28UCDBzp49SNdp3k0tWl8PVPwsTYileTh1GA1FlQmsmnJCwB68803q3XWTz75pItHFptmpgIEQDPV9GFZdgAgdg1ix+gpp5zimMJTpkyRBg0a6AJAfIGFb7gI/RtfVgC5aBsu1q9fL3v37lVH0bklEQDdYgnvtQNLOhDX86STTrKs8QBLM9eBhoJqPECqB0BjeTuNAGk860D/+c9/Sv369eXxxx+3zC4s2F0KEADdZQ/PtcYvADh16lR1c4zkAdRgKNpaPGiEm3fohovwzRe4+UdLq1atSioAhLdz+vTp9AB67tNuToPtAEBzWqq/lFg74eOByER2v4eXFw6g6Em0nfDvvfeeLFq0SM1CIF/r1q3VAyleffv2lQsuuEC/EA7nRJ9w78VyA6bjFSAAclQYUsAOAMTRUTk5OVKvXj1DbTWSGR5AnEUMcAsHPdxkcAPWwqZEWpOHG5DeaaDVq1erQ9pbtWplpAum5jXiASQAmmoKzxWGsE442xsvJmsUiAWgoXCJh7F169bJ2LFjFSz17NlTxQHF0pTOnTvLeeedl1AjX331VbWTODc3V81aILB0hw4dopaxa9cuwTF0X375pezYsUNNQyMW4VlnnZVQvaEX436MvnTr1k3atGkjL730ku6ykjkjATCZrWtD3+wCQIAXPHBWJS1sSrS1eLgZAuCiTdPGCptipN0EQCPqMa/bFCAAus0iRe25+uqrFSwBxvSmkSNHypVXXinDhg2Tjh07KpAbNWqU2sgWafYEQeW7du2q3nvggQfUJpS1a9eqNaJGlrxoAIhp7erVq8tjjz2mt0tJnY8AmNTmtb5z+ABHmm4ws+b58+erzQ9GATA0bEqkUy4ihU3RvHmLFy9WaxCd8FoAAPGUjKkZtyR6AN1iCe+1gwDoTptdccUVCtpwJrDehPzt27eXV155RRWBey7OcEeImUGDBh1XLEAR3kIEhs/IyNBb7XH5cH/CAzvijQ4ePFiuuuoq+cc//iG4x2tT4XpnZExrpAsKIgC6wAheboIdALhgwQI1vYpNGLGSdk5tpFMuAH1IgLpooVOihU2ZNm2a2oWMp0m705o1a2Tnzp26ADB/31bZun6uBFKyJDO7nGTmlJfM0hXU70ZugEYBEHr26dPHbilZnwsUIAC6wAgRmnD55ZerKVOcCawn4bsAMySff/65DBgwoLgIwBceYL/55pvjisU0b6VKlVQ+vI9QV5dddpncd999JQaij9U+zQOI4+3eeOMNNZ2NeuBpBAACNjdu3CgfffSRr9ciEwBjjSS+X6ICdgOgdk5tpA0X+B/CpgDiwjdcaH9jYXNJGy6idRbrZLA2xQkPYCwAzNuzUXasniR7NsyUfVuWyIEda+XQ3q2Sf2ifFAYCEbuk1ggFU4pfQUkV9UpJE0lJl2BquqSoVylJScuQlLRSkpqWKanpWZKWUfQzRf2eLemlSkt6qRxJzywtGZllJCMzRzKyykqp7HKSkVVOKlRvIGXKHw2gDRAnAPr3xoKzvTHV58TDlH9Vj91zeMhwOg+gSU8CUMGu2DCHtYNaAlBOmDBBEPopPDVu3FhwfwN83nLLLYJjL/HzjjvukEceeURPM1QezQP49ddfCxwIuP8DCrXNMnj4xUP19ddfLwjv5ddEAPSr5U3qtxUAGB42ZcOGDeqDC3ADPGBaITRsSrg3D093RrxbkaTBzQtTGVaGrohmEtwgt65fKCfn7JTdf82SfVuWyoGd6+TQPkDefgkEgiZZU38xhw4HZd8hkf15eAXVT+3vtj0vlmvufau4cDyN40uCHkD9ens5JwHQnda75JJL5LTTThOcCawn6QFAwBfuB1jmoh09ibOIMS28adMmPc1gngQUIAAmIBYvPV4BPQAYGjYl0lo8LWyKBna4BrtocRSc5snT48UzYj8nARCLord81FQkAuepfwWPvhU8cg1+4Hf8zJOysm3HnuLs2jUpKUWK4Efx7ylFvyMoDSLThIJ03uEisFNwB8g7hJ9FfxdGdjSq8tv1vEiuve9tAqCRAZhEeQmA7jTmxRdfrHbewvumJ+mZAsaOYzywjxkzprjKH3/8UbUD3wNmhG/Zs2eP/Prrr+r1f//3f2qaG5tS4FTAsiIz1x7q0c3JPARAJ9VPgrqjASC8dBrcRdpZq4VNCT/ZQvs7NGwKYlTh6RBn8TqVnAbArQBAB1JhICgFAZGJS4Kycou+BrTreaFce987BEB98iVdLgAgQiohGDSTexRAvL/zzz9fbrvtNt2NwiYQhHxB6BckfA/UqlVLlRlpEwh2/n788ceCWKfaQ/2LL74ozzzzjFqjZzRt27ZNrUf866+/1O7i1157TW666Sb55JNPZMSIEaqeZs2aGa3Gs/kJgJ41nTsavnXrVtm/f/9xJ12Eh02JtOlCc/nH6gl24MIThfUiTiXsJsP6FrzsTojRtWXEqXZXe0x9vy4I6AbAtj0vlOsIgI7az02V//nnn2o5BQHQTVYRBUoXXnihWoOnNyEMDDZ9YOMFQBBhYD777DO1yxf2RoiY0POGccpR06ZNVR7sFF6+fLlce+21ygtpJByNtgkE4In75+jRo9X09tlnny133nmnijeIINfPPvus+r9fEwHQr5Y3qd8TJ05UT3mRPHlmnVMLAERq0qSJSa1OvJg//vhDbQCB58Lu5AYAHLMwICs26+t52x4XyHWD3i3OrK0BxFnAZq/V1NdC5rJTAQKgnWrHX9e5554rl156qfKQGUkIAaMFgkbwegRhhmcQCZtMsJQHp49oCRvCsO4QZ74DDq+77jrTdgGjXkDnrbfeqoAUoInfkXCwANoGKPRrIgD61fIm9VvPGsBEq8bTI9YNEgATVc68640AYJvuf5Pr7x9e3Bis7cHJKgRA8+zjpZIAgJgWjBQY2Ev9SLa2AoQQC/CGG27wfNc0DyC8fIBOxAIEDF5zzTUKcLHp5Mwzz1SeSqxD9GsiAPrV8ib12w4A1Bbsnnqqc9Og8AAibAWmruxOmCbZ/CH67txu398WBmS5Tg9g6+4D5Ib7jz7xEwDtHkHuqg+fJYRUIgC6yy4AIgASPHBeT1oYGADeW2+9pY6ZwyYXeAABuNjxjJkIvOfEsh636EsAdIslPNoOvwAgvBZYw0IATHygtu52vtzwwPv0ACYuXVLmIAC606xnnHGG3HjjjepIuGRIGgRiLeGbb76pzlOvUqWKiv+Hh3lAoZtOV3JCcwKgE6onUZ12AOCyZctUgGcsFnYqYeciotRj6sruBA9g7oenSoqTHsBFAVmeq6/n0QAQUzN2h/PR1wPmMlMBAqCZappXFjZDYAMI1swlW8I6asQexc5irP07/fTT1bp1vycCoN9HgMH+2wGA2BmGaUMnt+s7CYAIhL3pgyaOAuDYRQFZphMAW3U9V2588MPjPIAEQIMfPo9mBwBiIwAeqJjcowACs2OHLE7lSJaEKBUIKVamTBlDR8slix7h/SAAJqtlbeqXnwAQ0wdYu2R38jwAdjlXbnyIAGj3uHFrfQiphHO1CYDushAeyP7973+rncBeT9omEOz8zc3NVYGlu3btqjaeYfo32pnvXu93ou0nACaqGK8/RgE7ABDnQyKYdPPmzR1THwfYV65c2bcAOG5RQJbq9AC27HKO/POhEcW2w5iZPHmy2p3HKWDHhrRjFRMAHZO+xIq7d+8uCMz897//3Z0N1NEq7PYdP368jB07VsaNGyebN29WBwr06NFDvRD42s9TwQRAHYOKWY4qgLV5iANoZVq5cqUKNt2iRQsrqymx7NmzZ0vFihXV1JXdCVHsN76PKWBrdS6pX+MWB2SpzqM5W3Y+W/45+CMCoN0Dx6X1EQDdaRgckYZwKRdddJE7G2hCqxBSbPjw4fLuu+/K9u3bZf78+Y6uLTehS4aKIAAako+ZCYDWjwGvA2CLTmfJTQ9/TAC0fqh4ogYA4CmnnKJ2ZDK5R4HOnTvL448/LjgSLlkS1o7DC4hg05MmTRIcXADww9QwpoQHDhwo5cuXT5buJtwPAmDCkjFDqAJ2ACDOidy7d6+0bNnSMfERpR43Cqxdsjth59pf7zX2rAeQAGj3iHF3fThXGzsxCYDushMCJQ8ZMkRNi3o9aWsA0SdsOsJ0L8LcIDA04I+pSAECIEeCIQXsAEA8wSGGE44Vcio5DoDvN5aUoHNTwOMXB2SJzingFh3PlJse+eQ4DyAi8Md7HrRTdme95itAADRfUzNKbNeunTz//POCI+G8nrAsCeuLEdPwm2++UR5neDgxzY37DmK6cv0xAdDr49zx9hMArTeB8gBiDWCw0PrKotRgBACbd+wvNz/yKQHQMeu5q2IAYP369dWmKib3KNCmTRt58cUX1Y7ZZEvTp09XG0HGjBmjpoPhge7SpYs6s5hTwMlmbfbHNgXsAMA1a9ao6O1ORm2fO3eulC1bVj1J2p02bdokGzAF7CAATlgSkMUb9fW8eYf+cvOjRwEQYwbrcegB1Ken13MRAN1pQdxfX3nlFenfv787G6ijVTgNBPeblJQUNYuE6eAff/xRPv74Y9mxY4daH+hEaC8dXbEkC6eALZHVP4X6BQDnzZsnOTk56smxpJS3J1d2rBonu9fNkL2bF8n+HWvl0L5tkn+4QPLzCyUgqRKUNAmmpIqkpEswNUNS1KuUpKSXktS0LElNz5S0jCxJyygtaaVKy+HCFDm4arSkpQQlLVUkNVUkLUUkLU0kPVUk/cjPjDRR7+NmZ3YyAoDNOvSXWwiAZpvEs+XBG9OgQQN6AF1kQYAS1ljjyDScCJIs6YsvvlDhX3AKCHb8IiA0PH+IB4h1gW3btvX1MhQCYLKMdIf6YQcArl27Vu3cwhSFUykUAAMFebJr7TTZtXaq7Nk0T/ZvXSEHd2+SvIN7pdDikDix+o8beWFA5EBeULbtFdl1UGTfIZG8wyJXdU+NlT3q+4YAsP3pcstjnxWXTQ+gbjMkRUYCoPvMiPsG4qwiRApOBPF60tYAYl0j1vudffbZasbByeNE3agpAdCNVvFQm+wAQJzjiCN98LTmVJr58XVSuHmSBPL2Sn7ePgkWBlVUvmBQJBA8/if+h5fVaef+QBHoHSgCvUOHRQ5HWSp4Ux/9ADhxSUAW6ZwCbtruNLn18VEEQKsHg0fKBwA2bNhQKlWq5JEWJ38zAYCnnnqqjBgxQgVoT8aEPuLFzR9HrUsATMaRbmOf/AKAf77YVGT/2oSVBSAiBVPS5cChw1IQEIGTEF46DRLxezFIHoFK/K2yFucX+WtHULbuETmQL5JXUFRGIunGXpg+1geBE5cGZNFfidR29NpoAIgpGB7JpE9TL+fCInycxkAAdI8VAUaNGzeWkSNHCk4ESaZ04MAB+e6779QUMDyD2ICEYNdY0+33RAD0+wgw2H87AHD9+vXqCB+4851KM19qJsF9a5yqXtX79cyA5O7W34QbemGNoD4AnLQ0IAt1A2A/ufXxz4sbrk0BEwD129LLOQmA7rMeABBeWayZQ4DkZEmYPTrnnHMEp0nBw5mRkSE4DQQ/v/32W9/HBCQAJstId6gfdgEgDvRu3769Q70UmflycwnuXe1Y/aj4m1kB2bRLfxOu74kNaLNRWgAAIABJREFUI/YD4Klt+8pt//miuOEFBQUqIj8BUL8tvZyTAOg+6wEA4RkbPXq0dOrUyX0NTLBF6A82w/3tb3+Tffv2qV2/VatWVaXAC3jllVeqHcA///yz2hji10QA9KvlTeq3HQC4YcMGQSgUZwGwpQT3rjRJNX3FGAXA63qIZGDbsI5kxAN4coP2cs51/1W77TAFjRszYhsi/AKmgLX/x/vTil3OOiRhFp0KYEdmkyZN1NnaTO5QAMCEEFc//PBDUnjFNADEGIOnDwGgQxO+UzDljRBjfj6RhgDojs+fZ1thBwDiLFy8nDzCZ+YrrSS4Z4Wjdho9KyAbDXgAnQLAuqd2lUsHDhMcz4Snb3gAcQPG7jzcqPE/7b1oP0OFB0TiFQ6M4f/T3o90bTywCdAkbJo/5AmA5mtqtER8DvFA9ssvvzj6oG20H1p+DQBr1qypTje55JJLjikacV2x2QVewAoVKphVrefKIQB6zmTuarB/ALC1BPcsd1T80bMDsnGn/iZc20OklE4P4ORlAVmwQV/dTdr0ltuf+Ko4c6JTwBokxgOK4QCp5dH+H6sM1BWawiHSKFRGg1E/gSYBUN/nyMpcGPeAJcTMczLcltl9fOCBB+Szzz6T//73vyq8Ddb+YTPIjTfeqKa8P/roIylVqpTZ1XqmPAKgZ0zlzobiyxxfrlYmTBdiIwgO9nYqzXy1jQR3L3OqelXvt7MD8pcBALymu0hmhr4pYCMA2Lh1L7njya+PA0DsNsQN2U1JxVE84qlM9Gc4XMaCztB+AwCjwaaZ0KlNwTupOQHQSfUj141xX6NGDZk8ebIKCJ0MCd9N2AF8yy23yCeffFK8/AT/P/PMM+W9994rXheYDP3V0wcCoB7VmOeYL3M7ABC7uZxcnDzz1XYS3L3EUcsbBcCru4tk6QTAKcsCMl+nB7BRq14y8ClvAKBdBtZikiUKmdGgsiTYBJiGpnimxOO5JtY0erSQQ1OmTFEBef089WbXOIu3HozHE088UXBMX7NmzeLN5trr8vPz5cknn1SbWpBOPvlk5fXLzMxUp9DUrVvXtW23s2EEQDvVTsK67PAAYgMITgNxFABfay/BXYsdteB3cwKyYYf+JlzVTSS7lD4PoDEA7CkDn/qmuOGAlQkTJqh4Y27zAOpX1705411nGQtG45lOD51Ch1czEkhiVyZisOHLONJ6Tj0eTz9NoVsx0mC3atWqyaxZs1S4FK+nRx55RJ5++mnl6StXrpx8/fXX0q9fP/n88891x0L1uiaR2k8ATEar2tgnOwAQIWCwWLdz58429uzYqma93kECOxc5Vj8qNgqAV3YVKZ2pDwCnLg/IvPX6ut+oZQ8ZOKToSRyJAKhPRy/kAiTGWmeJOGwnnXSSAsBo0BmrjEhezUS8ltq1icJmsm4MAgBiNyzWxyFIt9cTzmx/8MEH5dprr1VdmTlzptpEuHv3bl+HfQm3KwHQ6yPd4fb7BwA7SWDnAkfV/n5OQNYb8ABe0VUkxwEAbNiih9z5NAHQ0cHjosoxBYxpxvLly+tulZGNQdE2CkXzcEbbGBRtF3qs3enxgqqdXk30ESFTAOeYIvV6ysrKkmXLlkmtWrWKu5KTk6MAF+FumIoUIAByJBhSwA4AxCkgiOTepUsXQ201knnWsC4S2DHPSBGG8/4wNyDrtusv5oouIjlZ9nsAG7boLnc+/W1xw+kB1G/DZMiJjQbNmzc3BIB26qB5NePxSsaaRg9fqxn+d2i/QjcGxVpvGc2TGcvDqU3T4yeAHPfZZAAkQPbSpUsVAAJusdQEgItzqBH/L1k9uYl+LgiAiSrG649RwA4A3LJliyxfvtzRI4pmvdFVAtvnOmp9owB4eReRsjoBcNrygMzVOQXcsEU3ufPp744DQARn9XMIBkcHk4OVew0A7ZLKrI1BsTycGtCiX3l5eXLppZcWfw4rV66s1meWLl1avbBTFuFSvJbgAcSSIfxEAhCOGTNGfYfg5A/Nu/rNN0fXJnutj2a0lwBohoo+LsM/ANhNAtvnOGppwwDYWaRstj4P4LQVAZm7Tl/3GzTvKnc98z0BUJ98SZcLANiiRQu1OJ/JGQW0KXTEcUWILayNO//882X48OHKLgifcvDgQenfv39Cu7VfffVVee655wTrthFO5uWXX44rgP+nn34q//jHP1QbsGHDaHr00UdFi1GL7ygNerXvKw2S33rrLaNVeTo/AdDT5nO+8XYA4NatW5U7P/w4H6t6jz7t379fvbBjEa/8KTdL+t6FVlUZV7k/zgvI2m1xXRrxoss6i5TTCYDTVwRkjk4ArN+sq9z97FEAxM14/Pjxyp70AOq3p1dzTpo0ScEBAdA9FoQnEGfl4sQlbNDRk0aOHKnO2B02bJiK2Tp06FAZNWqUundjh3G0hOPYcC/A1HOlSpVMAUA97fdjHgKgH61uYp+9DIB4QgyFPO13PPnijFpMFWiv7T9dIcEds01ULvGifpoXkDUGAPAfnUTKl9bnATQGgF3k7md/KO4wATBx2ydTDgKg+6yJex/iACLkVvXq1XU1ENCH89pfeeUVlR+fc5wucvvtt8ugQYMilglPXI8ePdRuXYyLXbt2EQB1qa8vEwFQn27MdUQBOwBw27ZtsnjxYhU3Tk9CUFDNkxcKfHjqhQdKgzzsEtN+x/9Dd+HNfqu3FG79Q0/1puUxCoCXdBSpmOMEAHaWu5/9kQBo2kjwdkEEQPfZb+/eveokEKy3hicw0YR7LNYMIs7egAEDirNfddVVCuqirbVDvL558+bJV199JVdffTUBMFHhDV5PADQooN+z2wGA27dvl4ULF6onxWgJa1oAdJFAD54+LAYOBTyAHv6Odwpy9tt9pHDLDEfN/fP8gKzeqr8JhgBwZUDmrNVXd72mneWe5wiA+tRLvlwAwFatWqnNBkzuUACQhh2zeNjGRpBEE47rBEDimL/QeK333nuvCvqOE0bCE9aCYgPKnDlzVAxCAmCiqhu/ngBoXENfl2A3AAL0MEUb6skD9OFvtCU7OzuiRw9TukbSnLf7ScGW6UaKMJzXSQD8fWVAZusGwE5yz3M/FfdfmwLGjjwEA2bylwITJ06U1q1bEwBdZPYdO3ZInTp1ZOfOnQlt+tC6kCgAwuOIjUCvvfaaOq0DiQBo/4AgANqveVLVaBUAAhIAeoA7bALB2hR47AB6eA/TDZoXL3QKF3GvrEhz3j1dCnKnWlF03GX+Mj8gqwx4AC/uIFK5jL4pYEMAeGonued5AmDchk7yCwmA7jMwZllwPi52A+vZnJPoFDC8fngICL1fa6e7aDH8cJoHk7UKEACt1TfpSzcKgPjQh++41Tx6EA9whyCee/bsUacH4G/AX7SD5q0SfM67/aUgd7JVxcdV7q8LArJyS1yXRrzo4vYilcvqA8AZKwMyS6cHsGKFctKrZw9JL5UjaZllJCOzjGzYuFXqNW4uOeUqS2Z2BcnMqShZZSpJFn7mVDxm/aX+HjOnGxUgALrPKlj7h3h/8MzhHqsnYRMIjltD6Bck3NsxrXzbbbcdtwnk0KFDsmLFimOqeeihh1T9L774ojRs2DDu5Tl62so8RQoQADkSDCkQLwBit1ekaVvEmwLMRVqfh+lcvIdpiblz50qvXr0MtdVI5jnDz5KCTRONFGE4r1EAvKi9SBW9ALgqILPW6OtCxRyR7o3iB09M8xcGUyQQSJGApEpQ0iSQkiaSkiGSmiEpqaUkJb2UpKZlSWoGXtmSllFa0kuVlvTMMlKQVl6q1u0kLbuer6/BzGWpAgDANm3a6AYNSxvn08IRtw/Qhfsx7rt6EsLAYNPHG2+8oUAQYWA+++wzdbzcCSecoELEYJ3gkCFDIhbPKWA9qhvLQwA0pp/vcwPsAIFawu/aRgzNk4ef4aFVQoEPGzRKOvcSC5Rnz54tvXv3dkzvOe+dLQUbJzhWPyo2CoAXthep6gEAjFfk/IKAbN4jsm2vyO4DIgfzRQ4XFuU+sXYTGfz6tHiL4nU2KoBNAW3btiUA2qh5rKoQ/69JkyZqI128G+MilYkQMFogaGz0eemll1RMQCQ8wGOdIU4XiZQIgLGsZP77BEDzNfVVidg1tmHDhmLo024gkTx6WPCv54BzrEuZNWuWowA49/1z5fBf4xy17ZiFAVmxWX8TLmgnUq1c/J640Jr+WBWQmTo9gOWzRTrUS1HFpaSI4LfUlCOvVPyv6L2S0q79RbC3Y5/IvkMieQUigWD0HATAWIo69z4B0Dnto9WM00CaNm2qHuatWkftvl6zRQRAjgFDCmDqAK/wGHqGCg3LDACcOXOm9OnTx8xiEypr7gfny+ENvyWUx+yLf1sYkOUGAPBvbUVOKG8/AJ5QTuRv7SLXq6Z7A0WeO/wsCBT9xAuAN3VZULbsTVxJAmDimtmVAwDYrl07dc9gcocCOI0Du3Ixo2P3+mp3KODPVhAA/Wl303odPgVsWsEhBWEDyB9//CF9+/a1ovi4ypz74QA5vH5MXNdadZFRABzQVqS6TgD8c3VQ8NKTqpUTuSAKAMYq76s/izx/iaYTazWWwcOcDduTaJv9cj0B0H2WXrVqlZqWx25eAqD77GNViwiAVinrk3L9AoDzPrxA8tf/4qhVxy4KyLJc/U0Y0EakegV9HkACoH7dmfNYBXAONI4MowfQPSMDO3KxVg+7cwmA7rGL1S0hAFqtcJKXbwcAIjQAIsn369fPMTXnjbhI8tcdjWXnREOMAuD5bUROdAAAq5YVubC9PvCkB9CJkWZtnQRAa/XVU/qyZcukW7duKlIDAVCPgt7MQwD0pt1c02o7ABC7iKdNmyannXaaY/2e/9HfJW/tD47Vj4rHLQrIUgMewPNai5xUUR+IGfEAOgGA1Ws1loc5BezoeI1WOQAQYUIQz5PJHQogVAt26eJhmwDoDpvY0QoCoB0qJ3EdvgHAjy+VvDXfOWrJcYsDsnST/iYYAcCZq4Pyh841gEYA8OuZAcndnXifCYCJa2ZXjnHjxqnpRgKgXYrHrgdnreMBGxvuCICx9UqWKwiAyWJJh/phBwBiWmLKlCly+umnO9RLkfmfXC55q79xrH5UPH5xQJYYAMBzW4nUqKTPAzhzTVD+WKVvEwgB0NFh47rKCYCuM4nMnz9fncmLmKvxhGVyXw/YIj0KEAD1qMY8xQrYAYCITj9p0iQ544wzHFN+waf/J4dWfe1Y/WYA4DmtRE7WCYCz1gRlhsMAGJAUyc08RfIOp0opOSSZwYOSGcxTPzOkQMUY1FL1mo3k4Td+d9RerDyyAgRA940MnM173nnnyY4dOwiA7jOPZS0iAFomrT8K9g0AjrxSDq380lGjTlgSkMUb9Tfh7JYiNSvr8wAaAcAqZUUuSnATyN7CLJl8sKl8taG+bJSTZH9qeSmQ9OidDyJwYKF6pQQLJTUYkOzMTMlIS5FSaSmSmZ4qWelpkpWRJtmlMqR0ZrrkZGZI2axSUja7lJTLzpTyOVlSPidbKuZkSYUy2VK5TGmpXD5HKpfJkYyMNP3CM+cxCgAAO3XqpPvIMcppvgIItH/hhRfK1q1bCYDmy+vaEgmArjWNNxpmBwDiGDnEDuvfv79joiwcdbUcXP65Y/WjYqMAeFYLkVpVHADAMiIXdYhe77rDVWTy/mYy51BdWZ1XTbYXlJHDhbFPB7HLGMFD+yV131ZJy9srqYcPyU0D+sl/brncruqTrp6xY8dK586dCYAusizirF566aWyefNmAqCL7GJ1UwiAViuc5OXbCYCYAnZqfcrCUdfJweUjHbXmxCUBWWTAA3hmC5HaOgFw9tqg/L5S3xrAymVELg4DwLu23S4bDleWHYdzJL8QcBgQCQaPvI4cA4L/2ZyCB3aL7NshcnC3SP5BkcLDx7XgirN6yauDbrK5ZclTHQHQfbZEmK0rrrhCNm7c6Ng91n2qJH+LCIDJb2NLe2gHACI4KUJHOAqAn18vB5d9aqmWsQqftDQgC/+KdVX0990EgN1zh+Fk4NidARSGJEzvBg7sFQkWHoVFTP8Ww2Po9drvRw4gRn0pOHxYRIIpIof2iOzbLnJwbxHsBQpit0dECIBxyRT1IgKgMf2syI0wW9dcc406192ph2wr+sUyS1aAAMgRYkgBOwAwLy9PsG4Iu4CdClGw6Isb5cDSjw1pZTSzUQDs30Kkjk4P4Jy1QZluogcwbgA0KlqU/MrTt0Df0X4EQGNGAQB26dJFsrKyjBXE3KYpMHnyZLnhhhtk/fr1BEDTVHV/QQRA99vI1S0MBAJy+PDx02RmNtoNALj4y5tl/5IPzexWwmUZBcAzmovUrapvDSAB8Ki5CIAJD93iDMFgUD3MEQD1a2hFzokTJ8ott9wia9asIQBaIbBLyyQAutQwXmmWHQCIA8rhNUCg0rQ0Z3ZjLv7qVtm/+H1HzTJ5WUAWbNDfhDOaidStphMA1wVl+grz1gB62QOYWaGqVK7dUDLT0yQ7I01KlyraWVwGO4uP7Coui13FpfHKkgo52VKpbGmpVDZbKpXLkarlyqjr/Jg0AOzatatkZmb6UQJX9hlLbO644w5ZtWoVAdCVFrKmUQRAa3T1Tal2AiDOAk5PLyEUiIWqL/76dtm/aLiFNcQuesqygMw3AICnNxM5hQCohDYyBSzlTpCUkxrFNlhJV6h1iwFJDQYlLSUo6Ski6akiGalFIWvwKpMakDLBA3Je5xZy68VnGqvPJbkJgC4xRFgz8IB9zz33yIoVK9zZQLbKEgUIgJbI6p9C7QBATDH/9ttv4iQALhk9UPYteMdRwxoFwH5NReqfoM8DOHddUKbp9ABWKiPy97BdwF72AJoCgGEjKZh3QGTvVhGsTczbf8zu4+6tm8r3Lw52dOyZVTnuF/A20QNolqLmlPPrr7/KoEGDZNmyZeYUyFI8oQAB0BNmcm8j7QDAgoICGTNmjPTt21cyMjIcEWPJt3fLvvlvOlK3VunU5QGZt15/ExwDwByRv3c8Fjw9DYBlq4hUq3dkEzN2FmNbcapIaoqkYJdxjBTMPySyd5vIgZ1FsFeANbTRp9cJgLEU5ftGFfj5559l8ODBsnjxYqNFMb+HFCAAeshYbmyqXwBw6Xf/kr3zELrEueQkAM5bF5Spej2AyQaAVWpLyintIg6E4JHTSLRTSYp+Yrq3UGT3ZpGNS0uEvUiF9mjTVL4bmlwewG7dukmpUv5cB+ncHSR6zT/88IM8/vjjsnDhQjc2j22ySAECoEXC+qVYOwAQoWYwRdGnTx/HvjSWfn+v7J37mqNmnbY8IHMNeAD7nirSoHpsD1WkTs5bH5Spy/VtAqnkIwAsaYAEt6wSWTM74THUvfWp8u3/HlKL870eo02bAiYAJjwMLM3w3XffyVNPPSXz58+3tB4W7i4FCIDusofnWmMHAKKOX375RXr37u3YzsFlP9wve+a87Kh9pq8IyJx1+pvQp4lIwxP1AeD89UGZohMAK+aIXJJMU8AleACtAMDmdU+S/1x1joI/xMHETvhYr3ivQzm41q74mniYw7GOBED9n2Mrcn777bfyzDPPyNy5c60onmW6VAECoEsN45Vm+QYAf3pQ9sx60VGzGAXA3k1EGhEAlQ0N7QK2GQB7tG4qXz53nwCeor3wOcRaWfws6TrtPVyHl5Y0CDQTLDW4DPVaEgAdvYVErfzrr7+WF154QWbPTtxD7c4esVXxKEAAjEclXhNVATsAEKEjsEi5V69ejp0esPynh2X3rBccHQnTVwZkzlr9TSAAHtUueGCPyIJf9YlpMwD2bNNMvh36kL62lpBLg8BYwBgvVKIc7Vp8ZkPhMhQs9+/fLxUqVFAhnTRIxO96vJZenxI33ag6C/zyyy/l5Zdflj///FNnCczmRQUIgF60mova7BsA/OVR2f3n844q//vKgMw2AIA9G4s0OUnfFPCCDUGZvEzfGsCKpUUu6eS2XcAOAODmVSJrE/ew9GrbTEb/z3wAtGowA/7wigSWCOm0YMECadCggZrSjtdrGQqhoe2O5bHUADOe60KvtWtK3CobJFruqFGjZNiwYTJjxoxEs/J6DytAAPSw8dzQdDsAEP386aefpGfPnpKdne1It1eM+Y/smvGMI3Vrlc5YGZBZHgTACqVFLiUASlA3ADaX0f970NGxZ1blAD4cO9a9e3ddIZ0AlvF4JOO9JhRAQ6fEAaclQSMAMV6vZfi1bvRajhw5Ut555x2ZNm2aWaZmOR5QgADoASO5uYl2ASCmgPGlUbp0aUfkWDHmSdk1Y4gjdRcD4KqAzFqjvwk9GomcWkOfB3DhhqBM0ukBJAAW2YwAKMrjZwQA9Y/+2DmjeS21qe14vZWhU+GaF7SkKfFw0Ex0KlzLj3x64fLjjz+WDz74QKZMmRJbKF6RNAoQAJPGlM50xC8AuHLsENk5/UlnRD5S6x+rAjKTAGiKDRxZA6jTA9i7XXP55oXk8gD26NHDsWMdTRlACRZSkkcyHm9l6Oad8Kn10KbE8lqGv7927Vo1Jb9u3TqZOnWqvPTSS5KTk6Ne5cuXl+rVqyfYU17uJQUIgF6ylgvbahcAIgwMjo/CjcmJtGrcc7Jj2mNOVF1cp1EA7N5QpOnJ9nsAy2eL/KOzy9YAHtwjMt/mTSAEQMEawEmTJonfANCqG0dJU+Lx7AyHLT799FPZs2ePbNmyRSpVqiTYpINXkyZNZObMmQk1/dVXX5XnnntOcnNzpWXLlmpjSYcOHSKW8dZbbymvIwAUqW3btioWYbTrE2oIL45LAQJgXDLxomgK4AaUn59vuUAIBN25c2cpU6ZM3HXl7cmVLYu/lZ2rJsrm3L9k36GgpGfmSHpmWcnIKisZ2eUlE6+cipJZppJkl6ks2WWrSOmyVaV0+WqSnpFZXNfqCS/I9ikPx123FRf+uTooeOlN3RqKNNMLgH8FZdJSfXUTAIsspncKOJk8gARAvZ9ea/MNHz5cEApm7NixxRUBIBPZDIN1hFdeeaXaTNKxY0cZOnSoYHPJ0qVLpVq1asd14PLLL1cP9V26dFHRHRCH8KuvvlKnkdSoUcPaDrN0pQABkAPBkAJuAEC0Ye+mubJtyQ+yY8002bdlqRzYs1UK1Bmr+lNhQKQwkCKFwRQJBHGiV6EgukVIhIuiD1GKOga2+JWWKoJXOl5pIhl4pYuUSsPfODdWX3ISABf9FZSJJgJgj9xhEhT9WuhT8GiuoCMewJUia+ck3PQ+7ZvL1/9NjilgDQCxoQvTkUzuUAAbQHAaCM5c15sAfe3bt5dXXnlFFQGArFmzptx+++0yaNCgmMViartixYoqP0CSyXoFCIDWa5zUNdgFgLgx4QaTk11Kti8fI9tX/Ca7NsyUfdtWyaH9uyQAQnNR2nswIJt2iWzfJ7L3kEhegUi9qiL9mumbgkXXZq4Oyh8GPIBdG4g0r6mvfgJgyODSGwdws14AbCFf//cBF41u/U0hAOrXzsqcmI7FRju89CTMAmGD3ueffy4DBgwoLuKqq66SXbt2yTfffBOz2L179ypPIbyG55xzTszreYFxBQiAxjX0dQl2AOC2BZ/J0l/+Iyn5uyTvwC4pDCDOmEih8sodeTlohR37ApK7W2THPpF9eSL5BZEbU6+ayGkGAHDWmqDMWKUfdLvUF2lRSx8ALt4YlAlL9NUdaQqYHsD4B2yf9skDgACFyZMnq5BO9ADGPwasvvKNN96Q3377TX788UddVW3cuFFN22IjCZbqaOnee+9VR//9/vvvMcu95ZZbFIBiChhTwkzWK0AAtF7jpK7BDgBc+fXVsnPR5yXqGD4ti4uBK9r/9xdmy87dB9RUrsKYI1O5wRSsg8A8btFULiYlMZ2L3zGNGxpWAVMa2/aKbN4jsnO/yP48kcOF8Zv3lGoipzsIgJ3ri7R0AADLZYtcFrYJpEfu6xIUfTAav+LRr/TSFHDfDi3kq+eTwwNIADRj9JpfxmuvvabC83z//fe6CjcKgE8//bQ8++yzMn78eGnRooWuNjBT4goQABPXjDlCFLADAFd9c53sWDjSdt3Rt4KASEGhyIF8kVEz9HnAtIbXrSpyRnP90GPUA9i5nkjL2vrqN+IBJAAWjYCgzingvh1aylfP32/7+LeiQg0AcaxjIhsMrGgLyzyqANbdIQj06NGjdcliZAr4+eeflyeeeEKtP2zXrp2u+plJnwIEQH26MdcRBWwBwG9vlB3zP3ZU87yCoAyf6CwAzl4blN9X6m9Dp3oirXQC4JKNQRmvcwqYAGgMAPt1aClfEgAd/fwne+UvvviiOgcYO4H1JqzRRggXhH5BwoxJrVq15Lbbbou6CQRevyeffFJN/Xbq1Elv1cynUwECoE7hmO3Il5pFYWAAlgcOHFDxqTaPvVsK1n7rqOT5BUF51yAA1qki0r+FPg8cOj9nbVCmOwWAm4IyfrE++CyXJXJZl2P7zSng+Idzv44t5cvnksMDmJeXp06boAcwfvvbceX//vc/mTt3rnzxxRe6q0MYGGz6wHpCgCDCwHz22WeyZMkSOeGEE9TOXqwTHDKk6EQlhH15+OGHBaeQIByMlhDqK5FwX7obzIwMA8MxYEwBMzyAeFLct2+fgj28sBsMP/H/smXLStaqlyWwzlkAPFwQlHcMAmDtyiJntnQOADvWE2mt0wO4dFNQxhEAiz4sNu8CJgAau0cxd2wFXnjhBRWQGTtwjSRMJWuBoFu1aqVOFoFnEAnQX6dOHXnvvffU3/gdJ5GEp0ceeUQeffRRI81g3jgVoAcwTqF4WWQFEgVAnKepAZ4GfIA/7AgE7JUrV0698DueArFOaM0Pd8i2Oe86aoLDhUF5Z4I+D5jW8FqVRc4yAIBz1wVl2gr9behwikibOvoANPkAcK/I/F/0jSmbAfC0ji3liyTzAPbu3Vv3ubX6jMZcJSkAaEPAZnjxmPyjAAHQP7a2pKclASCme8K9epjcPah9AAAgAElEQVTWzczMPAb2AHzZ2dlRvxDW/nSXbJ31liXtj7fQgsKgvG0UACuJnNVKH4ChnV4FwLJZIpe7bgrYSwDYSr54LnYg3XjHspPXHTp0SIUKIQA6aYXj68Z07KpVq9R0LJN/FCAA+sfWlvQUAAjQO3jw4HGwh/8jOKjm0dO8ewDARNLan++WrTPfTCSL6dci9uBb4/V739CgmpVEzjYAgPPWBWWqAQ9g+7oibevqA1AjHkACYNFw1LsL+LSOBEDTP9As8BgFcAbv+vXrZcSIEVTGRwoQAH1kbCu6isj+v/zyi+AYH0zZhsNeenq64WrX/fJv2fLn64bLMVKAGwBw/vqgTFmuH0Lb1RFpd4o+AFyWG5Sxi/TVTQA0BoCnd2olnz+bXB7APn36GPk4Mq/JCiAMS25urrz//vsml8zi3KwAAdDN1vFA2+AB3L59u+Tk5FgW12vdmEGyZUbR+ZJOpUAwKG+O0wdAWptPrihyTmt9AIYyjAJg2zoi7R0AwDJZIv/HKWDdHsAzOrWWUc/e59TQN7VezBQg3hwB0FRZDRf22GOPqfv48OHDDZfFAryjAAHQO7ZyZUsT3QSipxPrf3tINv8+VE9WU/MMGxswVF6NiiLnehQAl+cG5TedHsBIANgz93UJOHoSiHfWABIADX3smDkOBbDrdvfu3fL222/HcTUvSRYFCIDJYkkH+4G1flamDWMfltzpL1hZRVxlGwbACiLnttHvAVywISiTl+n3QrapI9JBpwcwHADzpJTkp2RJVmC/ZKSUfB4eAbBoeOldA3hG59Yy6pnk8QBOnz5dbQJhco8CgwcPVnFX33zT2bXW7lHEHy0hAPrDzpb20moA/Gv8Y7Jp6nOW9iGewt8YGyg6R1hnOqmCyHkGAHDhhqBMMgKAtUU61EscQAsDKfLlpkby/bamsi2zluxLqyCFwbSjKgQCIsECSQkUSkrgsKQGCiQVP4OHJS1wGKgo1cvkS3ZqvuSk5ElOWp78dKirBFPTRNQrvejg5dQMkTS80i0PERI86B0PYP/OreUzAqDOTx2zxaPAgw8+KDjObdiwYfFczmuSRAECYJIY0sluWA6AE5+QTZOfdrKLqu43xgUkaIAATywvcn7bxAFM67hRAGxdW6RjHAC4LO8kGbu/lcw+WFfW51eRvYczbNUeywokUCgSBFgGcKYU/GdSLD7+l3dAJG+/pDTQd3wUAdBWkxZXBi/T77//Tg+gM/JHrfX+++9Xgfdfe+01l7WMzbFSAQKgler6pGyrAXDj5Kdl48QnHFfzzXEBCTgIgIv+CsrEpfobEAkAtxaUkzH7WsufB+vLyrzqsvNwtqE+WmGkYP4Bkd1bRQ7sLAK/QEFxNSkdLtRVZfDQXpF5dgeCXiGydm7C7e3fuY189sy9CedzYwYCoButInLvvfcKIjZo5/i6s5VsldkKEADNVtSH5VkOgFOek40THnNc2bfGB6TQwD6Q6uVFBhjwABoFwFa1RDrVP+qBvG3b3TL3cIMQz5rmZTvyU7k78Tu8cEd+Kq9ckYcuGCyUlBT9Hs1IBg3C87d3m8i+7SKH9okcxvrS6NDrBwA8s0sbGfm0PgA8sG2ZbJ77iWxfOUF2bN8se/fnS0palqSmZ0lqRraklcqR9Mwykp5ZVjKyy0lGVnnJLF1RMstUlOycypJVtrJkl6smpctXk8yssoY/gwDAGTNmqGPBmNyjwL/+9S8VjB/n9zL5RwECoH9sbVlPLQfAqf+VjeMfsaz98Rb89viAFBgAwBPKifytnX5gWrwxKBOW6PcAtqwp0rnB0fqv3PqwrC6sEW/3I16ngK2woGjKFp45TNeGTt9qwIifSMVz6ClFfyPP7lyRA7tF8g8W5U0gEQCPioWp812rxsmWBV/JznXTZd+OdVJw+HACapZ8KUxbGMQrTYKSJoGUdJHUUuoFoExJB1CWLoLKUmWOAGU5KVW6goLKrDKVJTXnRPlreyEB0DSrmFPQXXfdpWK44kxgJv8oQAD0j60t66nVAJg7bahsGPeQZe2Pt+C3JwSkIDE+OaZopwGwRU2RLiEAeNW2wbKq4OR4u2/JdcE9W0WWTNRdth8A8KyubeXTIf8+TqPC/IOyddGXsm3J97Jrwxw5sGezBIysUdBthegZd+4PyPrtItv2iezPE8nMLifn3fYBAdACrY0UOXDgQKlcubLgTGAm/yhAAPSPrS3rqeUAOOMV2TDG+ZMQ3pkQkMMGALBaOZELDHgAl2wMyngDHsBwALx622BZSQBM/HNRpbaknNIu4XzBzfrWAIYD4LqfBsqO5b/Iwb1bJFAYFPhWleMV3rkjP53iwC27A7Jhp8iOfSIH84+fvM/KKSfn3UoATHjwWJzh9ttvl2rVqsmzzz5rcU0s3k0KEADdZA2PtsVqANz8x+uy/tfjPSB2y/XuhIDkGwDAqmVFLmyvfwp4yaagjF+sfwq4+ckiXRserf/qbQ/JyoKadst4TH3OeQD3icz7WV/fHQbAha81ksIDW2O2PXzHer6Ulp179hdBYggo4jptVOH3lCOz86naT0ToSUGkniP/OFIzdo1u2iWycZfIzv0ih+KYbc7OKa88gD179ozZfl5gnwK33nqr1KhRQ4YMGWJfpazJcQUIgI6bwPsNQPwoFbrDorR55puy/ue7LSo9/mLfnRiQ/KMbUOPPeORKowC4dFNQxpkIgNdse1BWFNRKuB9mZvAVAOauEFlXtAs4KzVfslIKZE9hpgQkJKZiBHHP6tZWPn3q6ANQvABopp1QFs7DxhIIeMEBe5//kfhnngBotlXMKe/mm2+W2rVry5NPPmlOgSzFEwoQAD1hJnc30moA3DLrHcG0l9Np+MSA5BkAwCplRS4y4AE0CoDNThbpFuIBvHbbg7KcAJj4sNLhAayRkit9D38vLVKXyInZ+yUtpVA0fxo8coAq9QqkSn5hiuQXpkrekVep7LJySq06arduRlY52bfqR0kpPCRpaSIZqSLp+IlXukipNPx9rKcu8Q7GzpFfEJR3J+oAwDIV5Lxb36cHMLbEtl7xz3/+U+rXry+PP/64rfWyMmcVIAA6q39S1G41AG6d876s/eFWx7V6b1IgrmmuaA2tUkbkog76p4CX5QZlrM7zeNGmpjVEujc6Wv+12x6Q5QW1HdU1iJAviyfoboP+TSBWTgEHpXXaQume8ac0Tl0plYLbJSVoYO3A/7d3HnBSVfce/802dpelSxekiBQVBREUUZoaLNiwK4qixhj1GZNY4zO+JNbkJbYkPhO7xl5iiQ0b9l5AOiJtge29z7zP7+ye5TLM7E67O3d3f+eTya7svWfO/d47c3/3X6OkQ0sdReUOrl7O4dBrlIg19QHU1MXWHYb73h+DAMzO6Ym5EoBRnlH3Nz/vvPMwbtw4XH998qstuH+0egdLQAJQ10LcBNwWgPnfPoJ1L10Y9zrjnSBeAdgnBzgpDgEY3I832uMZNxg4xCEAF+Zfg5USgNFiBIIsgF1Qg+npn2Jy2jcY7vsROYEyR7mb6Kd3a4+CMj82FjZm5FYyQSMA0Fh4/szoH0pq6gK4f3H0FkBaJ6eO64mMrO6NdQjTs5CS0RXprEOY2R3pWT2Qkc1ahL1N2Ri+srr1NXUI+TOVZk+NhBM499xzMX78eLAnsEbnISAB2HnOtWtH6roA/O5xrHvxPNfWH+nED77vN5mNsQ6vCcDz8q/GivphsR5OQvZr7xbAp3e5Ej19JUZNmWSKphfr5Zl62UGZufEUEo8W+JYSPzYVNiZohMrI5XxtLQDpqj5in+gFpzFgBmjZ9KEhkAI/UhDwpSHgSwdSusDHwtamuHW2EZSVgd7YZ+a5GD1hZrTYOuX2CxYswMSJE8GewBqdh4AEYOc5164dqdsCsGDpU/jhhXNcW3+kEz/0vt9YTmIdvbsCJ0+J7ebH91y1NYBFS6O3utj1jhsEHDJm+/ufn381lksARn86HRbAd/v/1GTIRjNs1m1lTWNSBYuLW5cthaPN0LXbmTPO//OZ/5ksXZ7FFGbnmgxdHxr8fpONm1sEFLFNcgQZuUYApgDnz4j+mozVAhiPAAzH2GYjb+KxV9C13bjlzGN/hpN+qqzWSK7N+fPnY8qUKWBPYI3OQ0ACsPOca9eO1G0BWLjsOax9br5r64904oc/8JtitrGOeAXg6q0BvBmHABw7CJi+gwC8Csvrh8d6OAnZr71bAGMRgAkB55ikvqExO3zNtuhnjlUAVtcF8EAMLuCMNGDO+OgFZ/CR5RY3urNbKj8z+/ifY975ymqN5Ko444wzMG3aNNMTWKPzEJAA7Dzn2rUjdVsAFi3/N9Y8e7pr64904ngFYK+uwClxWADXbA3gjXgE4EBg+tjtN98LCq7CsrpkC8ACYNk7kZ6CnbZLdhKIFwQgoSxa6seqrdFjTIYAPHI83biNVk/rJg+uRWitnbSu0uJZVBEwgq+gPLJ6gyRx6AkX44Tzfh89lKA96Hp+d+UWfPb9KvTMykCfbtnYpUdX9OuRg/69uqFn1yz4bPHEuN8tOROcfvrpJjObPYE1Og8BCcDOc65dO1LXBeDKl7Hm6VNcW3+kEz/yoR/l1ZFuvfN2vbKBUw6I3fqxZlsAbyyJ3QU8ZiAwwyEAf1pwJb6vGxH7ASVgz0B5AfC9BGC8KNtaAFbVBvDg+9Ffi5npwIKDo/8MPPGx37i2oxmHzrsUJyyMrazJdxsLcP/7K/D2so34cVsRGhpayOI2/a79SOXLB6SlABkpPnRJ8yEzLRVZGanompGOnEy+MtAjOwM9szPRMycTvXOyPSEoTznlFBx66KG4/PLk11uN5hxr2/gISADGx097A3BbABavfhWrnzwx6awf/dCPsjgEYM9s4NQ4BODabQG8HocAHD0AmDlu+833woIrsLRuZFK5SgAmBn9HF4CPf+xHcZQCcOLMMzFt7sVIS0sz2cN8hft9c2k1HvpoNd74fgNW5xaitjbCIMrEnL4dZwkhKLMbqpBdX4oFhx+IX55xTMLf9aSTTsKRRx6JSy+9NOFza0LvEpAA9O65aTcrc1sAlqx5E6ueOC7pPB77yI/SqtiX0SMLOO3A6K0f9h0TLQB/VvBrLKnbPfYDSsCe8QpA7H9CTO63QHXsdQC7D9gNPUfti+p6P57e5ZKok0ASgG2nKd5c6sfqNnQBx2oBzEoHzo7BAhhKANL+uDVjOCoa0pEZqEJmoNK8sgJV5pwc8JOFOOjoi4z1rr6+foefhRU1eHllIT5cX4Ifi6pQk0zBF+KCCNTVAEWbAVrIa/ml02htPWHWgXjgt4kvin/CCSfg2GOPxcUXX+zG5ak5PUpAAtCjJ6Y9Lct1AfjDO1j1r6OTjiTZAvCHvABe+y56t5sFt8cAYJbDAtghBOCk4+FjKmyUIx4BOP+omfj7NReZd/zqlp47VliOch2J2rytBWBlbQAPxeACzsoAzp4W/fl65ss05BXXIj9jCNZ0OwBbMkeiIqW7iSEMHozZ8/kb4Av4jTs2zdfYKaVLagoy01KQlZ6GlXlljfuatOqmdGr+NL+nAr7Uxp/md5/ZLLW6FPVM0TYBio0vH/+egBHgvCVbgLI8gA8n/tAu5xMPnYr7/jvxVrrjjjsO8+bNw0UXNV7XGp2DgARg5zjPrh6l2wKwbP37WPHIHFePIZLJ//WRHyVxWAC7ZwGnx2EBjFcAjuoPzN5z+833ooJf4bu6UZEcumvbBMoLge/fjn1+CUDDLlYBSIF0XgxlYNpKAK6r7YcXyg7AooLdUezrhUAgypo7sV9ZzXsG6JKlQGM3F/OTypE/uUkAqCoDaLEbPLZRuDVv1xgbuEOBSGc7loZ6oGADUFkMNETmcp4+fhSuOOXwHdzZTrd2S25uu51ze5u8MnfuXJx66qm48MLkF9xPwCnTFBESkACMEJQ2C0/AdQG44SOsePiwpJ+CWOKQnIuOVwCuywvg1TgsgMEC8OcFv8K3nVQAoqYCgW9ejema6kgWwJgFYE0AD30QvTU6OwM4qwUL4Ja6nnih7EB8XDkaP9b0Rl1D9NbCmE5qFDsFKPiKcxuFW11TUHBKKnyTogtTCZRuA5YvjuKdgZNmH4g//+Ic4852urZDubnD/Z11E+1g798ffvjBxEZmZWVh+PDh6Natm3mdc845OOyw5H/vRgVIG0dFQAIwKlzaOBQBtwVg+abPsPzB5Ff0jyUTcQcBmAmcPjX2G9q6/ABe/Tb6m65dw5C+XXDAHllIRT1SUI8rSy/FkoZOagFkXNXXr0T9gU5NTcGv55+A685vzEr3igv4jSX+mOoAxioAK2oCeDgGAZiZkYITp/YC/LVIQR1S0IBUnx+pKQEsyL8OP9QN3G4xo7XMtlYxv9MS1/SzKVHCdGChu9fFMiwmHo+Cz8TjVYZu8xeDAER5IQJRWL8z0tNx9YJ5+OX86IRm8EVuOqo0xUWuXbsW27Ztw6233mpawR1wwAEoKyszr5kzZ2Ly5MlRfUbuvvtu3HbbbdiyZQv22Wcf3HnnnS3O8dRTT5n2c+vWrcOoUaNwyy23mGQUjbYhIAHYNpw79LvU1dXB+VSZ6IOtyP0Ky+4/ONHTRj3fE5/4TeHZWEe3TOCMOATgj/kB/CcOAbj/zJNw7hX/aP7yn3vPYnz8Y2Gsh5OQ/ZLmAo5QAKakpGJgv12w/157YN6MKZg7bT+kp6c1H7sEYHSXQY8+A3DrY6t22omiZMi1z6C4qqmNRxTTcl/46wG6VOmCtS8jGOmStaKxSVCaue2DVJNL2cT+Ma4vpXH7Ysbj5QM14ePxdlhiDAIwUNZ6DcxePXtiyl574PTDp+HoaROR4oh3df4eBa6Qm/7kJz/BBRdcALaEi3U88cQTOOuss/D3v//ddBX5y1/+Agq8FStWoF+/fjtN++GHH+KQQw7BTTfdhKOPPhqPPfaYEYBffvkl9tprr1iXof2iICABGAUsbRqagNsCsHLrEnz/zwOSjv/JT/woTKIAXJ8fwCvxCMAZJ+K8q+9v5jjnrkV4f01eUrkGKoqApW/FvoZYYwDDCMC09HQMHdgfU/cZi5MPnYpZ++3ZonVJAjC6U9ezz0Dc8tjKkDvteg0FYGSxcNG9a3RbBzZ9D2xaFt1OKWnwTTo2qn1CCcAuXbpgzPChmHvwJJx95HT06pYd1ZzcONga6vzvcL9TADIBhAIu1kHRt//+++Ouu+4yU9AoMGTIEFxyySW46qqrdpqWtQcrKirw0ksvNf+NFsh9993XiEgN9wlIALrPuMO/g+sCMO97fH9vdK4IN6A/9anfdCKIdeRkAmfGYQFcXxDAK9/E7gKeNH0ezr/mgeblH3HXW1gcS/+wWAGE2C9eATh51pGo8gOVdX5U1wdQ0wDUBoC6AJ2LPjQgBX6T0dmU4dm0hkCTAMzI6IKhA/vigD1HYd6M/TFx9PDmWnHOoPlw1pbOKgDLqwN45MPor8WeuwzCLY+uCHkFDb7mGZR4QgAuAygCoxipaWmYMmceymvrzbVYVdeAGl6P/gDq/EB9wAc/UhBwXIdsg+hbsRi7DuiPWfuPx/nHHooJo4c1v6vTq2KsnPbapdu76b+d/84/h/t359/sPHQDf/3111i0aBHouv3Zz35m3LexDIYBZWdn4+mnnwYziu04++yzUVxcjBdeeGGnaYcOHWoKT1922WXNf7v++uvx/PPP45tvvollGdonSgISgFEC0+Y7E3BbAFYVrMTSeyYmHX3cArALcOZBsccAbitLxbOfxW4hmTRjHs6/ersAPPLut/De6hgayCbwTMQrAAsWPYrMzIwdbo68cdoYJ9Z/s6+8kgrkFpdhW0kl8ksqMKZvFgb36bFDjThnvTj+bgcFoM2wdApDvM7Y1OiFUAIRmqlijgFMBc6bHv01WV2fggfei95d22/QCPzu/tA390FXP4PS6tiv70QxjcUC2L1rFnJff6jVJVCglVbVYEtxBUrKK7DfyMHmunJ7WDHJeL8333wTb7zxBt566y3zOZk1a5aJv5s/f37MrtfNmzdj8ODBoFv3wAMPbD4c9hZ+99138cknn+x0iBkZGXjwwQdx2mmnNf/tr3/9K2644QZs3RpDUUu3IXbA+SUAO+BJbetDclsAVhetxZK/jW/rw9rp/Z7+zI/8stiX0bULMD8OAbilJIDnv4hcbGRkpKNv/yEYMW4y9j3oOIybNAcpjpvN0X99G+/E0kA2dgQ77RmvAMxf9AiyMrskcEXbp+LNmjdOKyCdotL+nv/Y3p4QgK9/58faGLz5aTEKwEjLwDA3o1fvvhg5djImzTgZ46ceu8M16DxxnhGAG78HNkfnAu7eNRu5rz/oynUYz6T8bv7000+N4OPr22+/NckZdPnOmTMHU6dORXp6ejxvYfaVAIwbYVImkABMCvaO9aZuC8CakvX47u5xSYf2zGd+5CVRAG4tCeC5FgRgTk43DNptD4zZdyYmzTwF/YeMaZHZ3L+9jbdXJvdJ21dZDP+SRTGf27xFDyM7MzPm/SnwGBcVaxapV1zAbS4AQ5SB8cOHDdnjUdhlN/TK6YqRw0dhr/GTMaB3L/Tr2RX9e3bDoD7d0TXM+Rp41dMoq4neqhjzyQ+zY2DjUmDz8qim7ZGTjc2vJV8A8qElNze3WfDRykcLI8u5WNE3YMCAmK/3cFDkAo7qcvHMxhKAnjkV7XchbgvA2rJcfHtncsuV8Ow8+5kf2+IQgCyBcczk7kgJ1CHVV49UXwPSfH7QCsMExNaGFYDshvBjt/1QkjEIKf4AenXvgcEDB6NP9xz07JqJ3t2y0bd7V/TtwZtuDgb06o5BvbvvkL3K9zrmb2/jrSQLQFNT7bvXWzv0kH9PS01F7msPIDsrcgHor69D/ooXsfW751C0/jNUlGxFfYMfDX6gIZCCANIQSElHICUDvtRMpKRlISUjG2kZOUjL7Ib0zB7IyOqJLl17ITNnF2x5+0qkpwaQkQZkpMKcy1jFZEwQmnaKWQCmACcemGPKAqX5GpCawu4ZAaS24hWurAngwQ8CyM3aA+t7Hoi8LiNQ1pDRHIPW4rFQdLP8C2mzS0dKY5eOgopqU+XFDFPWxbc9dtN25UhNA/hK4U+eIxfcp7krEdjwXVSnY9yIofjs4T9FtU+iNqb4+vjjj/H6668b9+7SpUux3377NQs+JmcwbMHtwfdh2RiWfuHgwxXj/NheLlwSSGVlJV588cXmpdEiyXI0SgJx+2w1fcwCwVGkbfO+epcORMB1AVi+Dd/eMSLpxJ793I9tpbEvw1kCgx87G29GflVlBagq2YTKkq2oKduKmvJ81FUVoKqiBIu3ZeOjot5YWdkThbVdIrvJhlqmvwEpAYai+5HuA2pZC4zKxzlMOyzeeKlkUhw321QgNd28fLwBJ2hEIwBT09IxZGA/TB0/BifNnorDJu/dqthqqK3CtiVPY9v3/0bRxq9QVZoPf6j+YQk6ngZ/oFFMNpWsY81dQ5gVSGznMeJtelFosRYfdUxmWgC9c6KPx+P0sQrALlk5+NNT63fqlVtdVYaq4lxUl21BTVkeaivyUVdZiOWFdXg1twe+KemBbTVxXIsJ4m1aqJnOG45yL/y3yhKgtgK+0dOifqfA5hXAxiUt7sdrcfehgzFn6kRccNyhGDawb9TvE+sO/O7YsGGDsfJR9DHGLjMzE4cffrgRfXz17du31c9GrO8fbj+WgWHSxz333GOEIMvAPPnkk1i+fDn69+9vMowZJ8iyLxyMF5w+fTpuvvlmHHXUUXj88cdx4403qgxMok9MC/PJAtiGsDvqW7khAPlUW1JSYjLIireth+/d6EosuMH6uc/92BqPAOzdH7f+a3WLS1tfWIbHPl6FRUs3YNmmAhSXVXoixsy5aHPTZfkW1kmrLgN23Qu+XYbEhLwlAZjRpQtG7DoIh0zcE2f8ZBomjR3Z6nvUVZdg6zf/Qt6yV1C86VtUlRd5IEUj9LK3lPixsRAoLAeY+9C/O3D8pNgE4Gvf+fFDDDGAFIB3PJ8bluuqrSW4b/EyvLFkPdZsKQQ/614cAQo+252jvrZ5ib7J86JeboDuX7qBncPnQ78+vXHQvuOw4KgZmL1/6w8fUb9xCztUV1cbwWStfCtXrjQii3F8FHyTJk1qk2SS1o6JJWBsIWiWc7njjjtMTUCOGTNmYNiwYXjgge2JaKwT+Jvf/Ka5EDQLUqsQdGuUE/d3CcDEsey0M8UrAOkqKC8vbxR7TS+6BlhWoGfPnuienY78J/dPOt/nv/BjS0nsy+jeqx9ue3xN8wR8kn9n+WY888VafLhqM37cVoya2u03r9jfKbF7GsFXnt8o+Oiyra/Z4Q16DRuLjH67ocYP1LLkhenvwPIrLK7bZEkMsySnAGQrqpFDBmL6hHGm8O0eQwca1xVfLRW9LVr+AjZ9/g8Ub1qCyrJC1NMYlFgECZmNgm9TIUwpoVDJrskQgJlZObg9jAAceu0zKCyraup84ejKwQLLJGz74tL6Rjuno8VYQoC1MEmgthoo3gx20wBL+oQ5430m/QR1pixQY0mg7WWBjK8+5DtYAcjrka7dudMmYf6cg9CjW05zJngiizCHWgS/G9iizSZvvPfee6Y9m7Xw0drXu3fvNrfyuX1eNX/bEpAAbFveHfLdohWAfJpttu4VF6O0tNR8kfXo0cMIPr74O8sEcPjrq/Hlrbsknd2rSzOwbmtT788YVtOtZ1/88Ym1zXtOufU/WLq5uMk/2CRZbOsr46Z0tL3aoQVW08230bmY8BGorwPYp5Str9gJgR0WWhi3XbYAF5101A7C1mbJ8trIL63A5qIy5BaVY1tJBfLKqlBYXo2iylpUVlZhWEYV5kwagx7ZmTtl3NoIleAyLM5SLA0fLESgZMfacsFeXkPTapim3028mS8FmwooYJr8s03hZ04XbawxfVsdFr5IytvFIwDfX5uNJeuiL1KZmd0Nt9pZxDEAACAASURBVD+3OeTZ7faLx6MX0oEAUn0B1NdUN3bnaO7MQVetfdlr275ts3O8qRtHY0cOHx8gmkaAcxVvBcrygOryxrlaGbxmSt973MSiBWdw87rcVlJuyrFs5TVZWoWC8ioUVtTAV12G2WMGYXCf7jvtZ69HXhP24SRUeSDn9dnS7/a65qFUVVVh8eLFzaKPApAlVayVb8KECS0+CLXGQ38XgWACEoC6JuIm0JIA5BcvBZ5T8FEA5uTkNIs9Cr6uXbuGfZr1++vx5c09415nvBO88rUf66PsnJaS4kOv3v0wZPfxmHjwSZhy6PaaV/ve+BJW50V/03YehxFrwW2wTExUk3hsFpHcq0lk2gB7c4P1AQ21QMlWoKLJmmIsOpGPWy5dgItP2S4AI9+z5S1bKsPirNdX+vqp8BdHl7UZ6RpNrKYfqKsH6hpgfqeFsSHQFOdn29M2icqNBQGso6E0Bk9pPALwre/9WLklsqPi6e/Zsw9GjpuM/WefiX0POibkjjm/eDyyCV3aKmBbu9GlG0OiUCoF4OInEra6cNdjqPJAwfUkQ23DhT377LMm9o0xfPR6UFj26dMHgwYNMokcjKeL9QEkYQeuiTosAQnADntq2+7ArADkFySfYoOte6wzFWzday0rzVnRnl+e39zWq+0OKMw7vfKNH+sLWl4GG7b3HbArRoydjH2mHoc9Jx8Rtu7ZhJtexqp40ooTRCSw4gOgJEL1EOI9b77kbFxy6tEJWk300yx/YDqqtn4d/Y4u7LFoqR+xllZ0UwB269Ydu40ab+pBTjn0TGRkdm316JMtAO0CA3wg+fz5VtcbvEGiBWDUCwjagd9pFHlM2qBrlz8LCgpM6zNmvo4dO9aIP4bDlJWVGQsj+/NqiIBbBCQA3SLbieZdt26dqT3F+D2Kwe7du+8g+BhL09JTbHD7IvukTYT2b3lrPkBR3o+oNRmJeaitLER9dTH8NaXw15YjUF8OX30V4K9BSqAGqagzET9pEZa1iOR0/edbP37M33FLWjIHDt0Do/eZjkkzT8XA3SKvVzjxppex0gMCMGvDV6jM3e6ajoSFc5ubLj4Ll542N9rdEra9BCAQbAFk/Oyuw8di/JSjcOCcBcjpEX2WqlcEoC/gh/+z56K+XlJT6QJOnAUw6gU0lUJhFqyN5WMix8CBA5tj+WbPnm1i+2Tli4Wu9omXgARgvAS1v8ngolvXJGx0795qNppT8NkWRaGqEdkvxda+HDkHm4pTgFrrIy2RFGe0PPLVJS2Ahqp8VJVsQVXpFlSXbkVdZYERkg3VJWioLUHACMlK+Bqq4PNXIyVQa+qjsWYf6/W9szwFedXd0Kv/CAweNRlDxs1Cdk6P5lggGxMUKjYo1N8m3/YaVsSTVpygay+w+lOgcENUs7Fp/cihg3HIvmNx+WlHY3D/5MVodhQBOHj4OJy68FpUl+WhpjwPdVWFpvRKg3nIKTXXJxoqgfoq+AJN16epKdmAz39MQ0FdXwwcuR9GTjgK3fvsusN16YxTC45JC3W98jPnFQEYrQWwR/fu2H/PPTD/iENw4uztbcmiusBj3JjfY7TevfPOOyZjl3122X7t4IMPNqKPGa6jR49WLF+MfLVbYglIACaWZ6eczca7hDr4SKx7zk4MrYk9vgetjFbsUfDxxf0oPm0CCUVfIlocOY/JtgUL1WfW2XO2tb9bJpe+W4QNFa0Hs7t9UUUiAGnF3WO3XTFz/71x5hGHYOxug91eVsTzr3hwBiq3fBXx9m5uGI8LeMTYKbjyL29GvbxQSQ7O6zE4Hq2l/7ZvTsF47ItbEWCMaJJHawIwPSMDY4YPxVHTJuH8Y2djQJ+2jRcmfxZftla+jz76CLvttpupy8cEjpkzZ7YY45xkvHr7TkxAArATn/xEHbpTACbausf5aN2zlj3+5H/TxWXjCvmT1r5IxGOijjmeeayQXJ1biGUb80wW4rbSChSU16CoogYlVbUoralDeU0Dqur9qKoPoKZhe4kVU8o5hQWbw5eyiGZ9gTWfAgU7WgC7d+uGcSN2w+EH7oP5cw7BoL69o5myTbftKAJw5LgpuOLP0QvARMHmZ8358LK1qAybCsuwpbgc20orTfZ2UXk1iqtqUVxVh7KaOlTUNqCyzo/q+gCqeY0GgPqmkit+XyoCvEZ5rcYxggUgs4MH9u+L6RP3wrlzZ2Hq+D3imD36XcmJ30Nss0bRx+4bfCA95JBDjOA74ogjMGrUqHbzfRQ9Ae3RUQhIAHaUM5mk47AFSinAGMtiX1aMscxBpK5cHgLFpLXqWSsfBZN15QaXiEnSYSf9bXkTqqmpw8aCEvPiTZolLfLLWM6iscRKaVWt6a1abm7SDY036KZafaYmmi/F3KB9675C1+oCjBzUFweOHYafTBoLNrcPdluHcx06t6PlqK2F+IoHZ6Jyy5dJPydcwDsrUrF8UwwpwAASJQB5bby2ZAMe/Wgllq3bhLrKMmRnpKFbZjq6Z2WYcju9cjLROycLu5iWgWwX2M282DKwS0Z6XCxtDK8Vk0XlldhcUNp4jZqSK5XbH3aqa1FaXY/ymnojJPnAw4cd1pS0tfvYuSVj2VsYtWt/zJwwGodPHG36P7dWhiXc32Op4cfvoG+++abZyvfpp59i5MiRxq1LwUfxx4dSDRFoTwQkANvT2fLgWhn/N23aNBP3wnIvdlAI0iVrX87/5u8UdPxJAbl161Zs2rQJCxcuNDW76Lql0OvVq5f5SXFJYaGReALOlnShXIOtuRLt33mztyM43ixYIIYSlqFqpUUqJL0kAN9b7sf3ocvqtXjyeKyTps/DeVffH9NJ/vLHPNy3eDneWbYB6/OK4Xecj6gnbGoZyHp+7NObkeJDl7QUZKWnomuXNOR0SUe3rAz0zO7S2Hs6Jwt9umcbIdmfr17dMLhPD3TLjrxHc7g1tubeDg63aOm/7XtQALYUr8vPxKOPPgrGufIh9Pvvv8d3331nvqtYl49ty4477jgMHz68zR92oj6X2kEEWiAgAajLI24C/JLmDYxfvhSCwRY8WweQ/25/X7JkCfgUzXi+fv36mR6RFHz8omXQNAe/gJ0C0opGp7B0/pv9nT/tNk7XcKSCIm4gnXCCYCEZLBydQrGlvzmFZKRJNSWvn476gu88QT0aAcjal0NH7o19ps7FlMPmIzsn8lJH6/LL8M/3luG179ZhVa5HW7TxeyHQgIyaUmRWF2LcoN544+7fJuU8Od3b4UQi209u3rwZq1evxr333mtKtjDchNcrr0V+V/E7jO3NLrzwwqQch95UBBJJQAIwkTQ1V8QE1q9fj40bN2LixImmCKqNHaSYtJ1CbNwfRSWfxIOFZKj/5r/xxS9uDj7tUwy2ZJF0CkpbwsbuY13PzrqFEpIRn+aoNwy2+ESSXFP39Y1o2PYxGupr4PPXNpX+CdvpK+o1RbNDSwKQ1/ng3UZj7ylzMHXOuejRZ1DEUxdVVOPBD1bg31/9gCUb8lBZFXtHmojfNMYNA2zNZtq0Fe3Qpq1/n55Y++97Y5w18bvxOycvL8/E8DGWjxm7vN5mzZrV7NodMmTITlY+XqOxuJETfwSaUQTiIyABGB8/7e0hAs5SMnxaDxaIThHJv/G/nRZL+7sVkfxpLVKM7wklIkNZJcOJSGc9RIlIdy+c+ro6VBRvRkXRRlP6p7J0CyqLG3/WVjSW/kF9eWPNyACFYzVSTdmfOqSa0j+sIRlAWpSRB04BmJ6ehv6DhmPMhJk44PAFGDx8z5iEw8KHP8KTX/yAwA7dXZr62sGPLJ8fPn8DauvqUM82JSZxl+3U2iaDNxDwI6umBOlVRagvL0ZlRejuNiN2HYDvnrjT3RPfyuwUeJ999llzLN/XX3+Nvffeu1nwTZ06tbkFZVIXqjcXgTYgIAHYBpD1Fu2LgNMaSTeQ06XtFJVOl7YVjfbfnCKSNQk5aEUMFpFO66R1XdttQrm0nXUWJSJbvq7IvaioCIWFheZnTU2NiT1lqEHv3r3N7y3FlvI6qKupQjmFZOEGUzuyqnQraivyTQ3JuqpiNNSUwF9bhkBdBXwNlVidl4HarqMxbPzh6DlgtLEo8SHC2dM4muQaru+UR77Ep+uLov8QNffhZWtAvhz9ePm7aRNohaTtRW17IlNAhheSgcrSxn7RlcU7WPl2XKQPfXr3xIHjx2D+ETNw1EET2jxmjty3bNnSLPiYucvPzaGHHmpEH7N22XZNn6XoLy/t0f4JSAC2/3OoI/AgAac1krFFThFpXdpOsegUk6FEJAWlnZNxjcFu7VDCMlhA2uQb/jvdkXZ0lJsfBR7FnhV8DCUgJyv4mFCUjGSi4B6ykSbW2O2uX7wFn26pbmzvbPo3t+GgQLRCMsDGxw0ILHsXqAvtguZ1tefIYThuxhQsPGYWeuS0fWYsrf8ff/yxce2yGDPjjSdMmNBs5TvggAPMw5iGCHR2AhKAnf0K0PF7moDTGskeodaN7SyEHS420mmFtL9TJHFkZGSEtEYGWySd1sjg5BsKURsLlQwRSWFtxR5/0lrL9dK6R9HHV0e60TP2rLCsEhvzS7C5qBS5RawfWWlK/zBGsJilf6pZn68eFaY2n7+59A9r89WzfqSpyxdf/cjAFy8CDbXmOvKlpGDowAGYNXk8fnrcYdh796Ft/nniZ4RVBBjHR8HHHrusJHDYYYc1t1zr37+/rHxtfmb0hl4nIAHo9TOk9YlAnAScxbkpAJ0iMtil7YyJtH+zP22pH/40N3+fr1lEhkuyCc7SDpVwQzEaiTWSlh2nS5eCmCLUKfgS3f0lTvSe3J1CcktRKTbmlyK3uAxbihoLPeeXsX5kDUooJJsKkTtr89kiz13WfITdB/TCjL1HYtq43ZCWmmosq5FmbYdrleisGdoaOF7H7LhBwUdLH/vt7r///qb7Buvy8fdkWHtbW7f+LgJeIiAB6KWzobWIgIcJWCFJ16S1RlrXtv0ZTlA6rZHWxc15OOg2DLY8Utgx8Ybvw1d+fj5+97vfme0pFJhQY2tFUmSypEo0Bcc9jLndLK2ljO1Iyv7Y+EjbD5znL1zNyLvvvtvUCGVc54oVK0ypFl43kydPNoJv/vz56NOnj6x87ebq0UK9QEAC0AtnQWsQgU5CILjcT7A10mZm06Lzv//7v0YYsq8q60RS+LFGpBWQtEQGl/sJV3g8VGZ2sEub/61yP21/IdrWiMGxkRR7K1euxKpVq/DUU0+ZBwEbT8mHA9uSjQKQAlFDBEQgOgISgNHx0tYiIAJtQIBigNmbu+66607vFlzuxwrC4FqR/HdnDclwLm1uZ61QFBah6kYGd7VxFhu3f7P/pnI/sV0gPK9r1qxpzthdvHixsfIyW5cvunf538mIN43tiBK313vvvYfbbrsNX3zxBXJzc/Hcc8+ZbiR2kN31119vCljzc3DQQQfhb3/7m+lJbAfjZC+55BK8+OKL5mFq3rx5uP32200YhUbnJCAB2DnPu45aBDo9geByP8GJNeEEpXV325hIKzSd5X7CJdMEx0DazGxroXS2SbQxbB1V8JA/E3co9GwsHwvEsxaf7bE7fvz4mGondrSL+z//+Q8++OAD7LfffjjhhBN2EoC33HILbrrpJjz44IOmRd11111nuiqxjZ3N+KellOLxnnvuMV1NzjnnHBMr+dhjj3U0XDqeCAlIAEYISpuJgAiIQDABpzWSiQnOmEhbbNxpeQyXsW3FZKhyP+FK/gRbIUMl3Hit3A8trXTrMmOXL4oatoK0Vj7W5+PxdlTRm4hPENk4LYC8BlnL8Je//CV+9atfmbfgdcjM5wceeACnnnoqli1bhnHjxpki2JMmTTLbvPrqqzjyyCNNRybur9H5CEgAdr5zriMWARHwGAErJFk0mrFu4YqPt1Tyx9nJhiVyOJhhHdxPuzUXtzNekr/HU+6Hx8XjYWkWWvnYbo1WqGnTphnRRwEyduxYWfmiuB6DBeDatWsxcuRIfPXVV9h3332bZ5o+fbr5b7p577vvPiMQmUVvB8Ms+IDA+Mrjjz8+ihVo045CQAKwo5xJHYcIiECnJhCq3I8zOzu4FWJw8XGngOTvznI/LRUed7qxrdjk3D/++CM+/PBDU66FsZy2RMvMmTONqJSVL7bLNVgAkjFj/jZv3oyBAwc2T3ryyScbxk888QRuvPFG4x5mBrVz0Pp6ww034Gc/+1lsi9Fe7ZqABGC7Pn1avAiIgAgkloCz3I+za01wqZ9Q1kj7byzTwgSEs88+21j59thjDwm+BJ2mziAAP//8c7z88ss4+uijTdwjLeOq65igC8gxjQRg4plqRhEQARHo1AQY62e7xHRqEC4cfEd2AfPhg8e3YcMG3HXXXUYEfvnllyaUQSPxBCQAE89UM4qACIiACIiAKwTCJYEwAYRxfhy0xNK9G5wEQssaLWocjMmcM2eOJ5JAKPxo5eNDg/PBgX2b6d5miRuGF2gkloAEYGJ5ajYREAEREIFOSoClWJ599lnTmo71IFnShiVaRo8e3UykurraCLXHH38czBxnMsxf//pXk7UbbjCRhm51jgkTJpgi6YylZBvEoUOHmve4+eabdygD8+233+5UBmbr1q34+9//3lwGhhnBbVEGhgKP1jyumV177GAiSnC/blqPKXKt0P3DH/6Aiy66COeee65cwQn+XEkAJhhoR52utUKk8R43y0Ewa22vvfbC119/He902l8EREAE2pwALWosu8L6ehQ311xzDZYsWWKEmBU+TLigGKJ1jqV7Lr74YmP14ndguPHOO+8Y8RQ8GGPJeWwh6P/7v/8zhaCZZU1RydhLO1gImu/lLAR9xx13tEkhaIpedvNhNji/44NHXl4e/vznPxsuLAX005/+1KydlswrrrjClK9hEWyNxBKQAEwszw47W2uFSOM5cH5h0S2x++67g0+oEoDx0NS+IiACXiFAYUNXLIXPIYccYsr79O3b11jdTjzxRLNMWgtZCofZ0nR5dsTxr3/9C88//zzuvPNOw8OOhx56CI888ogpbs1sZrZ9fOGFF0wxa/7kYKFwit+lS5fuYEntiJza+pgkANuaeAd4v+AYFB4SXRnXXnst+EGnoONTHt0SM2bMaPWI+cTMjEFmefFLQgKwVWTaQAREoB0QsNnQ7MrB78S33noLs2fPNvX42NbODgqfyy67DL/4xS/awVFFvkSbDMTuI2xNx+92Z0YvBeCCBQtwyimnGItlr169QCsmezu//fbbxsXNDjvDhg0zLm52L7GJIpGvQluGIyABqGsjagKhBOD5559v3Bz8kLKqPCvV/+Y3vzHtiJz9KIPf7P777zdfDHz6+/3vfy8BGPXZ0A4iIAJeJEDxc8wxx5gH4vfff98skZY/ihg+MDvH5MmTjZWLD83tbUQiyPg9z2OjtdM5nnzySRPbRysfYxs5aET4xz/+Ye4ldKWzqPncuXONVZDxiyoJk7grRAIwcSw7zUzBApD9O0eMGAH+dLYUYiwHv9hYhDTUWLVqlYlV4Yef8R6//e1vJQA7zVWkAxWBjk2AsX4MnaH4YyHsjiQAnYkakZxFxvfRpcuOJLxXWBHHLiQUhrfddltzjCPjAH/3u9+ZRBcm0bAW5ZVXXgnGMDJxRiNxBCQAE8ey08wULABtwU5ndhdh8CmXsR2sRM/K/3aceeaZxsTPeJeFCxfiwgsvNH+SAOw0l5AOVAQ6NAEmW1DwMHmOlis72qMLmBY+K/iCazuy+wgTVPgATwtecLFm6wJmFxK6dv/7v//bZD3X1dUhPT3dPPwz4YMu4oMPPthg4pyMiWTcpG1tN2/ePGMNpBBUB5nEfXQkABPHstPMFCwAKfDOOOMME6Qb/AVA4TdgwIDmEgaExHpOLOzJeA/n9vyy4JcN/401qmbNmtVpmOpARUAE2j8Bfn9dcsklJgSGwig4/MUmgdDNSVHDwfZsY8aMSWoSCBNQaGE76qijzJr4XcwXv4tDCS62+bv88svx2muvGfFHNy29OfT2MG7PuoXtT5akYZgQDQIUcVYYsrzNLrvsYljRIGC3pzGBDNk+kIO1AE877TSTxawi44n7nEgAJo5lp5kpWACuXLnSZGfxadc+xbUGgx9ixgw6B4OA+YT89NNPm6fmYItia3Pq7yIgAiIQTKC1Ela2hMq9995r4vUoNhiX3FLscjjKrFfHOD9a/5y1/1juhXUBOegafuWVV0z5Fj4MUzByMA46WYOJePzupjUuuC7funXr8NJLLxlrHUXYcccdZ7w1TNKgkGXYzyeffGL+bdy4cfjTn/4UUqQx1m/Lli3GI8T+0VbIcX9mB1tBvG3bNpMh/fOf/9wkh9AiyARD/p2t4TQSR0ACMHEsO/RMrRUipVuXdaz44acrgOUPFi1ahPHjxzc/VbYGSC7g1gjp7yIgAtESaK2EFWPQWMCZbko+eF533XUmeY0PqJmZmVG9XTj3JJMgmO3KYQtBUzw5C0HTU9KWgwKMI1TLPnpzWH+PbdgoilmkmjHejz76qHHhHnHEESYhg9/19Naw+DX50U3L7326d+2wVj1uxyxndixhIgwHBSGtjocddphJ+uAItvDRasowI4pCtYRL7BUiAZhYnh12ttYKkTKmg1m8TOvftGmTMevTpH/DDTdg7733joiLBGBEmDy5UWtWllgWHe6ay83NNWEFGiIQLYFwbdTYmYPChIOCg4LHtlGL9j28vL0zzMYp0ChE//3vf5vSNHS70rXLTNyzzjrLFGamqGNVB1opacns0qWLcVuzZy+tmLQe0jLIWofOOn/BLCiuX331VWM5ZN1XJngsW7bMzBXc6k3Zvu5fSRKA7jPWO4hAhyfQmpUlFgBWADJGynlz4A0mlNUilvfQPp2LQLAAXLt2LUaOHImvvvqqOeGARNiViAkIt99+e4cERHH15ptvgg9TtEzSykfrHcUfE/SCBz05tMAxiYPdOWi142eQyRvk57T4cS5njUPnXPQk/frXvwZjAlvqfNIhoXvwoCQAPXhStCQRaM8EElUo3ArA4KK57ZmN1p5cAsHXJi1ajPljnNnAgQObF3fyySeb5AfGq3WkwU5LdMMyRpGxd7S8Md6RZWrOO+88U6D6L3/5C4YMGWISO+hyfeaZZ4x1lA953J6DIo5JGozZZi9iDs7NMi20njKmMNygC5xC8vjjjzdeImX1Ju8KkwBMHnu9swh0SAKJKhRuBSC7JNBFxU4KDBPgDVtDBGIh0N4FYKiiyzZjNzh5IxSfP/zhD8byx7p7kyZNArN5WY2BFnYmwdDt+z//8z8mzo/vxRfFnBXD7G/M92GixrHHHmvCfZisQfHHpJDs7GxT148ZwaGGXX9lZaVxJUv8xXIVJ24fCcDEsdRMIiACgPlSp3WAMUEcsRYKp+uXIpA3KgpA3pwefvhhk3E4ceJEsRaBqAm0VxcwY+VYdoUPQ4zFCzfYNs1mGzu3scKLrlsKOFoAmajH7GSbWMFYPCbzMdPXxkPSVUvX8JIlS5qzovPz802pl4KCApPxTEFJl/JJJ51kMnWDY/miPknaoc0ISAC2GWq9kQh0DgKJKBTODMNQg7FZdDlRCGqIQLQEwiWBUPAwEYSDMW6MM/VaEgjj8/r27Yu77rrLWO1stiw7jbDTBjN22TmDpVIo4kINJl+wDE2fPn1MjCN5sNYfu24MHjwYRx55pEmwYuwjS7WwLAytfay/xyxeuoOZJEPhx8zdUCOS1nDRnjdt7w4BCUB3uGpWEei0BBJRKDxcJiFjj3jDY+FaDRGIhEBrJazosmQJEmcZGFq+YikDE8l6ItnGWaLFZsNyjawfeOutt5rYOQ6Wa2GBZYZH0LpHEci4RQpaxvSFEmO02NF6R6HLn7SsUziyggNbsLEDxx//+EcjEPfZZx9TEodikG09KSxp5aPl0FmuhWvkCG4EEMmxapvkEZAATB57vbMIdEgCiSgUHg4MrQ68GbHumIYIREKgtRJWthA0W5Uxg5XxayxKzw4XbTnC9de1Io4PPpdeeqmx4FH0MSzi6quvBl2yFG8cjK1jtu7y5cuNGAyXjes8Lhav/vzzz/Hpp5+aUjD8b8YIMvaPSR60CO655547oJCVry2vDPfeSwLQPbaaWQQ6DYHWrCyxFApnNiIL8/Lmw8xBWirYMYCuqNmzZ3catjrQzkeAgoxlUmjZs9c6PwNMzmDxZRbcp7WN2bt0XdOa99RTT5l422HDhpl4PLpt6Sp2Dgo3xvqxfh9DKVjvj5m7rPdH4UcByZI4U6ZM2akjCBNArMu4852RjnnEEoAd87zqqDxAwLpx7NMyvzw7atZba1aWWAqF09VFqwwzDZldyFpkLB8xc+ZMD5xdLUEEYiMQrsAxP0Msw8IkJ1r0KO5++OEHXHbZZUbM0e16wQUXmJI1jNmjhZJuX5ZnYcIVe6fPmTPHFFgON/id9MYbb5hs+jVr1hjrHl3FCxcuDNt6U9a+2M5ze9hLArA9nCWtUQREQAREoN0RoHiygi/44Y+ZteyYxLp5/BvbqzH2kA86TPRggWXGJ7KNHK1zdP/ed999xj1NAcdkj6uuugpPPvkkWNDaOTgPH5w4Z/CgtZ7Ckr2K1Vqt3V1SCV2wBGBCcWoyEWgksHLlSlNglV/ELLtAVybbJPGJnU/ydrTF03W42CKdKxEQAXcIBPez5bvQCs6OGS+++KKpnVdYWGhKHDGxid8LFHqM76Ooo8DjYFkXCj+6hOmaXbVqlUnEOOGEE3DNNddg3bp1JlGD/02RSPcv6/HRrct4WVr2WhJ5NnmDXT06qnfCnTPcMWaVAOwY51FH4SECLGFy7bXXmlp1dFfyZlBRUWFib5i9R3dOTk5Oqyu2fTv5xexsfRYs6CIVkc7tGEfHRuyM/dEQARGInUBLnz+WUPnnP/9pQhn2228/k0FLEccMW7pwma1LEUdrIBM3WFz5lFNOMcWYOS8/TZcBxQAAEI9JREFU60x44ueU5Vco5o455hgT28fSL6zHx7/fcccdoGWPczNJ6owzzjAi03bpiP3otGdHJiAB2JHPro6tzQmwwOo555yD008/3bhvunbtatbAJ22WV2DFfDZXZz0vFjpmIDddQPzyZpwbv7zD9bmNVOjx/awFYvHixcadxCSMuXPnNrd3mj9/Pr755hvzsturhEObXy56Qw8TcJZiCV6mfTgL95lhqRUKNLZb4+d53LhxJqnj6aefxoUXXmjcuBwbN240Io3bM4aPtf64D70HtqDz888/jyuuuMIkedDax1IttCIyEeTggw828/AB8+uvvzb70tugIQKREJAAjISSthGBCAnwyZvlFygE+YQfLuCb0/FJ/+OPPzYuHVuDjMHffMpnsgNvCnQX0y1EVw5vCKxN9sUXX5hSFfyip4uIQpKFXdm/0yn++DvnoDXy97///Q6FW88++2ywu0A05VSsRYI3NHtztDdA+98dOdElwktAm3UwArS8sWcwH9BYCy+40waTNnjd82920BLHhAxm7r788svG4sffKfb42WOZFTv4b3xgZJ0/dvlgnB+thjZ+j9szxo8lWmj5Y2kWZsjzc81s3eDh/JzKrdvBLsYEH44EYIKBarrOS4DN01lQlcKPLh/r5uWX9aJFi0xQN7+wGZvD4G/W8uIXPb/IaRXg9szwY1YeY4WY/Uf3EPf/r//6L9PEnTciWu+uv/564xbizYA3GpaKePTRR41LiDFDLPDKzEBmC/IGxRZSFGsUkywbwZgjCka+B2OLKCAZj8T9Q41orI92f2uF5A2Q6+D6Gbhu+4lyO3uz4u/Bru7OeyXpyJNNgGKND2N0rbJfLh+22IOaWbgsw8KHLvbVfemll4yVnw9qDPmw9fi4/uOPP94kYrB+n43Do4uXQpKfaVr+Odhtgw+NrMPHTGBa6mnJYymX1atXG8shH+AWLFiQbCx6/w5GQAKwg51QHU7yCLCGFm8OFHh0z3Tp0sUshgHZDOKm+8e2mKJLiC4fWghphaMA42AAOF3FrHdHQcZxySWXGPcOg8RZ4oFZghSBDB6npZDz8wZFkcWaebREUBDedNNN5sbBmxK3p7gbNWqUcTPRupCbm2tcSLz58IbGGw5vasEi0FoxKRy5TtYmY+YhswgpNmkh4RwUfBS2/Hd7c+P66boiD66PAtmOWERl8s6u3rkzEaDblXF45557ronL48MJkzb4+aEFkN02KMxoxacwZCgFQzv4+eEDHK3kfEhjQgavffbT5bj77rvBGGE++FmLIbfhg9Fnn32GgQMHmlp//OzzM8Q4Xb7HjBkzdsIfKtGkM50jHWv8BCQA42eoGUSgmQCFHS0BjPFhU3SnyKEFjOUXGBtEwUa3EG8eVizyJkPhNmLECGMhsPGDLNbKgG4WQuaNgNvwfSgS6QqmoKPlgGKPApPijvvTysf4P/b/5L5jx45tXiczkummoruJ27OWGDsIsP8phaBz3dZixz6hr776qolxZKwib1C0TPJmRusj3dEsSEsBSHcWj4/JJlw7a46xKwG3YYYj98vMzDQ3Pba34s2M4pXWTDWT1wcqmQT4wMNYOwo6PkQFu3y5NrZgowWd1yrds7TM8zrnZ5OfS/bVZb29K6+80jwkWesdt2Vi2I033mgSNeygYOQDHt297MDBQaEYSSePZLLSe7dvAhKA7fv8afUeI8Cnf1r0GKvHIqsc1oJG9yutCBRnfNKn0KNljlY8W4aBVgGKM4o5CiQOuo9piaAFkZYEWuLoWuIN5/LLLzf/TncT44r4vgwQp6WB1goKMf43hR6FmbUa0JJoXckWIV3XXCOFqnNYAcgbF11StDhSuNpB6ybLT9D6R+FIqyLfm0KXNzBaRWgx5LopGpkAQ5HMGx5fdInxWDk33V8sb0GBqSECbU3APvgwXIMhFHw446C1nOWceO3awX+juKP44/b8DDz33HPG6kcLHmNs+XDFzwoTwuzgwx+t/7fffntzmAgFJR/q+BBIAUkLI5M9+JljaInq9bX1ldA53k8CsHOcZx1lGxGgy4Zf/rTEUQDxy583Dsbk8WZAUUgrG92sFIF041Jw2WDtk08+2Yg0um0pjDg4z7333mssZbzJUExR7FEo8iZDKx/jATk/LY+0XLBHKGMKrRvqscceM50FeIPji+9NcUhrnhWFDEbnWoIFoBWwY8aMMTcu3qAYT2hvlhSITGbhMTLWkMHqtPzR6sh9+D6MlXr44YebMxQpYCn2KGCZoczBeEe6iJkBSbebhgi0NQH7WaDwY/wfH8wYj0uLHn8yrIMZuXzI4cMShRs/nyzxwhAQPvDQcsfPIz/3fHBjpi//jQ98HLSY83PCzxLnt58j+5Mxu3T78jPM+EANEXCLgASgW2Q1b6clwCLQtOoxbo83FGbuUfCxeTsFF7/c+UTPL3+KKVry7GDAOGOAaDFg5i8TNCjsaD3jDYE3IYonikwKRCaQ8CZDawKDyOnupQVi+vTpZkr+nf9OiwLXwPXQokBLHK2CrEtmbzy04FGs0YrpHPamyMB0WjwoWm32b3FxsUkk4Y2Qx0dBSisng+Lfe+89I1jJgi5qK0I5NwUu56HLjNvwZslj4o2TNz1aQHmsGiKQDAIs2syHGlr36OblQ1B+fr4JleDnj59xhiwweYtuXg7GuLKuHz+P/PwyXpbCj6WYbrjhhhZbtAUfI8MzaEXXEAE3CUgAuklXc3daAuzpSZcmm65TJNFywOSNvffeu5kJhR4tYPzpHLTi0QJBixrFI2P8KMycjd0p1ii0eCOiO5duWGYY03XKG5SNH/zjH/9o3MGMteM+HEzaoDWQge620Tz/nTc6WicYA+gcViDSusGYKFo+7KC1jjc3unIZj8j3p8uXZW1446PQpNBjkggtlzbZhXGAjBtkYWzOT17kxBstRSBFqNxenfbj49kD50MdP6+8dvlAw2ucn03W4eM1TpHIhzZm5/PaD5eo0VJ5KM8evBbW4QhIAHa4U6oDau8EKIgo/vLy8kzJFMYMBXcOobWBCSW0IHLQ+mZdtHS9Wpcy3U/sHGC7CNDyRkseA9hpoaNo42DZC1oUGS/I5JFQg2ugK5p1C+247rrrjJCkwGQcH0Uc4xEZH8V6hRSiFLnsgsLYSBtQz3VT5NLtqyEC7YUAH5D4QMNrnp8jWqoZ3sCHI9bwY2JHsOXahl2EK/DeXo5d6+x4BCQAO9451RGJwA4EaIWkNZJdSJhFTFFGlzGtbDZRhZ1IGFN4zz33NJesCMbIGxhdzHRh20H3MrOHWfqG1k0KPcYA0gXMhBTuQ3cYXWFOKyStlEw6YcIHYw4pPul24zoZK2VL6OhUikCyCPAzwUxeZgQzbILlmWj1Y3Y7Pz8czGqnlc9a3O1aVeIoWWdN7xsNAQnAaGhpWxHoxARo0aM4c7qiiYNZwXyxBAwTOyjeaElkvBQHi1vTKshSMIz1Y2FoBs3TbUxLIJNPmJTCv3Fb/hutKxoikEwCtJ7z4YaDoRa8Jpk5zxg/ZzYw/04RyBevYQ0RaC8EJADby5nSOkWgHROgNYUZ0nRFM7jd1vpjqzrGS9FlTBcyy+AwBlB9idvxye5AS6eFm+EVLFsUbOXrQIepQ+mkBCQAO+mJ12GLgAiIgAhEToAWPrp2bc3OyPfUliLgTQISgN48L1qVCIiACIiABwgons8DJ0FLcIWABKArWDWpCIiACIiACIiACHiXgASgd8+NViYCIiACIiACIiACrhCQAHQFqyYVAREQAREQAREQAe8SkAD07rnRykRABERABERABETAFQISgK5g1aQiIAIiIAIiIAIi4F0CEoDePTdamQiIgAiIgAiIgAi4QkAC0BWsmlQEREAEREAEREAEvEtAAtC750YrEwEREAEREAEREAFXCEgAuoJVk4qACIiACIiACIiAdwlIAHr33GhlIiACIiACIiACIuAKAQlAV7BqUhEQAREQAREQARHwLgEJQO+eG61MBERABERABERABFwhIAHoClZNKgIiIAIiIAIiIALeJSAB6N1zo5WJgAiIgAiIgAiIgCsEJABdwapJRUAEREAEREAERMC7BCQAvXtutDIREAEREAEREAERcIWABKArWDWpCIiACIiACIiACHiXgASgd8+NViYCIiACIiACIiACrhCQAHQFqyYVAREQAREQAREQAe8SkAD07rnRykRABERABERABETAFQISgK5g1aQiIAIiIAIiIAIi4F0CEoDePTdamQiIgAiIgAiIgAi4QkAC0BWsmlQEREAEREAEREAEvEtAAtC750YrEwEREAEREAEREAFXCEgAuoJVk4qACIiACIiACIiAdwlIAHr33GhlIiACIiACIiACIuAKAQlAV7BqUhEQAREQAREQARHwLgEJQO+eG61MBERABERABERABFwhIAHoClZNKgIiIAIiIAIiIALeJSAB6N1zo5WJgAiIgAiIgAiIgCsEJABdwapJRUAEREAEREAERMC7BCQAvXtutDIREAEREAEREAERcIWABKArWDWpCIiACIiACIiACHiXgASgd8+NViYCIiACIiACIiACrhCQAHQFqyYVAREQAREQAREQAe8SkAD07rnRykRABERABERABETAFQISgK5g1aQiIAIiIAIiIAIi4F0CEoDePTdamQiIgAiIgAiIgAi4QkAC0BWsmlQEREAEREAEREAEvEtAAtC750YrEwEREAEREAEREAFXCEgAuoJVk4qACIiACIiACIiAdwlIAHr33GhlIiACIiACIiACIuAKAQlAV7BqUhEQAREQAREQARHwLgEJQO+eG61MBERABERABERABFwhIAHoClZNKgIiIAIiIAIiIALeJSAB6N1zo5WJgAiIgAiIgAiIgCsEJABdwapJRUAEREAEREAERMC7BCQAvXtutDIREAEREAEREAERcIWABKArWDWpCIiACIiACIiACHiXgASgd8+NViYCIiACIiACIiACrhCQAHQFqyYVAREQAREQAREQAe8SkAD07rnRykRABERABERABETAFQISgK5g1aQiIAIiIAIiIAIi4F0CEoDePTdamQiIgAiIgAiIgAi4QkAC0BWsmlQEREAEREAEREAEvEtAAtC750YrEwEREAEREAEREAFXCEgAuoJVk4qACIiACIiACIiAdwlIAHr33GhlIiACIiACIiACIuAKAQlAV7BqUhEQAREQAREQARHwLgEJQO+eG61MBERABERABERABFwhIAHoClZNKgIiIAIiIAIiIALeJSAB6N1zo5WJgAiIgAiIgAiIgCsEJABdwapJRUAEREAEREAERMC7BCQAvXtutDIREAEREAEREAERcIWABKArWDWpCIiACIiACIiACHiXgASgd8+NViYCIiACIiACIiACrhCQAHQFqyYVAREQAREQAREQAe8SkAD07rnRykRABERABERABETAFQISgK5g1aQiIAIiIAIiIAIi4F0CEoDePTdamQiIgAiIgAiIgAi4QkAC0BWsmlQEREAEREAEREAEvEtAAtC750YrEwEREAEREAEREAFXCEgAuoJVk4qACIiACIiACIiAdwlIAHr33GhlIiACIiACIiACIuAKAQlAV7BqUhEQAREQAREQARHwLgEJQO+eG61MBERABERABERABFwh8P/Gv7Hi4c/79wAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}