Optimal Datasets.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split as tts\n",
    "from sklearn.ensemble import ExtraTreesClassifier as ExTC\n",
    "#from pprint import pprint\n",
    "from sklearn import metrics\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "R2 = pd.read_csv('./surrogate_performance/benchmark_test_R^2.csv', index_col=0)\n",
    "features = pd.read_csv('./features/benchmark_train.csv', index_col=0)\n",
    "\n",
    "cv_max = pd.read_csv('./surrogate_performance/benchmarkCV-score-max.csv', index_col=0)\n",
    "cv_mean = pd.read_csv('./surrogate_performance/benchmarkCV-score-mean.csv', index_col=0)\n",
    "\n",
    "R2_on_optimal = pd.read_csv('./surrogate_performance/benchmark_optimal_R^2.csv', index_col=0)\n",
    "MSE_on_optimal = pd.read_csv('./surrogate_performance/benchmark_optimal_MSE.csv', index_col=0)\n",
    "\n",
    "# Drop NANs\n",
    "features.dropna(axis = 1, inplace=True)\n",
    "\n",
    "# Drop columns with only one unique value\n",
    "cols = features.select_dtypes([np.number]).columns\n",
    "std = features[cols].std()\n",
    "cols_to_drop = std[std==0].index\n",
    "features = features.drop(cols_to_drop, axis=1)\n",
    "\n",
    "# Drop columns with inf\n",
    "features.replace([np.inf, -np.inf], np.nan, inplace=True)\n",
    "features.dropna(axis = 1, inplace=True)\n",
    "\n",
    "# Calculating Loss and Targets. Target is the modelling method with lowest loss.\n",
    "loss = -R2.sub(R2.max(axis=1), axis=0)\n",
    "targets = loss.idxmin(axis=1)\n",
    "\n",
    "# Getting data that is avalable in both targets and features\n",
    "features_available_for = targets.index.intersection(features.index)\n",
    "targets = targets.loc[features_available_for]\n",
    "######################\n",
    "loss = loss.loc[features_available_for]\n",
    "\n",
    "# Doing the same for cv_max and cv_mean\n",
    "\n",
    "cv_max = cv_max.loc[features_available_for]\n",
    "cv_mean = cv_mean.loc[features_available_for]\n",
    "cv_mean_best = cv_mean.idxmax(axis=1)\n",
    "cv_max_best = cv_max.idxmax(axis=1)\n",
    "\n",
    "#Same for optimal sets\n",
    "R2_on_optimal = R2_on_optimal.loc[features_available_for]\n",
    "MSE_on_optimal = MSE_on_optimal.loc[features_available_for]\n",
    "loss_on_optimal = -R2_on_optimal.sub(R2_on_optimal.max(axis=1), axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/bssainix/.virtualenvs/ModelSelector/lib/python3.7/site-packages/sklearn/ensemble/forest.py:245: FutureWarning: The default value of n_estimators will change from 10 in version 0.20 to 100 in 0.22.\n",
      "  \"10 in version 0.20 to 100 in 0.22.\", FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "ExtraTreesClassifier(bootstrap=False, class_weight=None, criterion='gini',\n",
       "                     max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
       "                     min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "                     min_samples_leaf=1, min_samples_split=2,\n",
       "                     min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=None,\n",
       "                     oob_score=False, random_state=None, verbose=0,\n",
       "                     warm_start=False)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selector = ExTC()\n",
    "selector.fit(features.values, targets.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "predicted_targets = selector.predict(features)\n",
    "predicted_targets = pd.DataFrame(predicted_targets, index=features.index, columns=['Prediction'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "loss_prediction = pd.DataFrame(columns=['Prediction'], index=features.index, dtype=float)\n",
    "for comp_id in features.index:\n",
    "    loss_prediction['Prediction'].at[comp_id] = loss_on_optimal[predicted_targets.loc[comp_id]].loc[comp_id]\n",
    "    \n",
    "loss_predictionCVmax = pd.DataFrame(columns=['CVmax'], index=features.index, dtype=float)\n",
    "for comp_id in features.index:\n",
    "    loss_predictionCVmax['CVmax'].at[comp_id] = loss_on_optimal[cv_max_best.loc[comp_id]].loc[comp_id]\n",
    "    \n",
    "loss_predictionCVmean = pd.DataFrame(columns=['CVmean'], index=features.index, dtype=float)\n",
    "for comp_id in features.index:\n",
    "    loss_predictionCVmean['CVmean'].at[comp_id] = loss_on_optimal[cv_mean_best.loc[comp_id]].loc[comp_id]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To get the problem characteristics out of the filename:\n",
    "\n",
    "columns = {'ProblemName':0, 'num_var':1, 'num_samples':2, 'distribution':3}\n",
    "\n",
    "characteristics = pd.DataFrame(index=loss_prediction.index, columns=columns)\n",
    "for index in characteristics.index:\n",
    "    for column in columns:\n",
    "        characteristics[column][index] = index.split('.')[0].split('_')[columns[column]]\n",
    "characteristics['num_var'] = characteristics['num_var'].astype(int)\n",
    "characteristics['num_samples'] = characteristics['num_samples'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "performance = characteristics.join(loss_prediction)\n",
    "performance = performance.join(loss_predictionCVmax)\n",
    "performance = performance.join(loss_predictionCVmean)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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       "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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"639.8333333333334\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "performance[performance['distribution']=='normal'][['Prediction', 'CVmax', 'CVmean']].boxplot()\n",
    "plt.ylim([0,50])\n",
    "plt.title('Loss Performance of various techniques on optimal datasets \\n'\n",
    "          'The surrogate model was originally trained on \\n'\n",
    "          'normal distributed DOE datasets)')\n",
    "plt.ylabel('Loss')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_var</th>\n",
       "      <th>num_samples</th>\n",
       "      <th>Prediction</th>\n",
       "      <th>CVmax</th>\n",
       "      <th>CVmean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2714.000000</td>\n",
       "      <td>2714.000000</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>16.741341</td>\n",
       "      <td>684.524687</td>\n",
       "      <td>1.439211e+06</td>\n",
       "      <td>1.434580e+06</td>\n",
       "      <td>1.430797e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>8.532508</td>\n",
       "      <td>515.307529</td>\n",
       "      <td>5.946546e+06</td>\n",
       "      <td>5.945356e+06</td>\n",
       "      <td>5.928122e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>100.000000</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>10.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>7.769468e-02</td>\n",
       "      <td>5.117813e-02</td>\n",
       "      <td>5.282617e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>16.000000</td>\n",
       "      <td>600.000000</td>\n",
       "      <td>5.183634e+00</td>\n",
       "      <td>4.642048e+00</td>\n",
       "      <td>4.686296e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>975.000000</td>\n",
       "      <td>3.004536e+01</td>\n",
       "      <td>1.774946e+01</td>\n",
       "      <td>1.766380e+01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>30.000000</td>\n",
       "      <td>2000.000000</td>\n",
       "      <td>5.253085e+07</td>\n",
       "      <td>5.283371e+07</td>\n",
       "      <td>5.253085e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           num_var  num_samples    Prediction         CVmax        CVmean\n",
       "count  2714.000000  2714.000000  2.714000e+03  2.714000e+03  2.714000e+03\n",
       "mean     16.741341   684.524687  1.439211e+06  1.434580e+06  1.430797e+06\n",
       "std       8.532508   515.307529  5.946546e+06  5.945356e+06  5.928122e+06\n",
       "min       6.000000   100.000000 -0.000000e+00 -0.000000e+00 -0.000000e+00\n",
       "25%      10.000000   300.000000  7.769468e-02  5.117813e-02  5.282617e-02\n",
       "50%      16.000000   600.000000  5.183634e+00  4.642048e+00  4.686296e+00\n",
       "75%      20.000000   975.000000  3.004536e+01  1.774946e+01  1.766380e+01\n",
       "max      30.000000  2000.000000  5.253085e+07  5.283371e+07  5.253085e+07"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "performance.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "loss_on_optimal.boxplot()\n",
    "plt.xticks(rotation=45)\n",
    "plt.title(\"Loss performance of various surrogate modelling techniques \\non optimal datasets\\n\")\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>svm_linear</th>\n",
       "      <th>svm_rbf</th>\n",
       "      <th>MLP</th>\n",
       "      <th>GPR_rbf</th>\n",
       "      <th>GPR_matern3/2</th>\n",
       "      <th>GPR_matern5/2</th>\n",
       "      <th>DecisionTree</th>\n",
       "      <th>RandomForest_10</th>\n",
       "      <th>RandomForest_100</th>\n",
       "      <th>AdaBoost_10</th>\n",
       "      <th>AdaBoost_100</th>\n",
       "      <th>ExtraTrees_10</th>\n",
       "      <th>ExtraTrees_100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.272862e+06</td>\n",
       "      <td>1.275843e+06</td>\n",
       "      <td>2.939350e+05</td>\n",
       "      <td>2.347354e+06</td>\n",
       "      <td>2.004131e+06</td>\n",
       "      <td>1.889432e+06</td>\n",
       "      <td>1.424026e+06</td>\n",
       "      <td>1.415397e+06</td>\n",
       "      <td>1.406451e+06</td>\n",
       "      <td>1.445360e+06</td>\n",
       "      <td>1.414299e+06</td>\n",
       "      <td>1.448184e+06</td>\n",
       "      <td>1.452570e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.530698e+06</td>\n",
       "      <td>5.539103e+06</td>\n",
       "      <td>2.117774e+06</td>\n",
       "      <td>1.520361e+07</td>\n",
       "      <td>9.765987e+06</td>\n",
       "      <td>1.028175e+07</td>\n",
       "      <td>5.936327e+06</td>\n",
       "      <td>5.870825e+06</td>\n",
       "      <td>5.831173e+06</td>\n",
       "      <td>5.934263e+06</td>\n",
       "      <td>5.846156e+06</td>\n",
       "      <td>5.981956e+06</td>\n",
       "      <td>5.983045e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "      <td>-0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.569527e-01</td>\n",
       "      <td>3.472579e-01</td>\n",
       "      <td>1.750200e+00</td>\n",
       "      <td>1.929708e-01</td>\n",
       "      <td>2.939155e-02</td>\n",
       "      <td>3.779417e-01</td>\n",
       "      <td>1.672709e-01</td>\n",
       "      <td>1.872001e-01</td>\n",
       "      <td>1.744215e-01</td>\n",
       "      <td>2.585289e-01</td>\n",
       "      <td>1.913955e-01</td>\n",
       "      <td>1.500834e-01</td>\n",
       "      <td>1.410917e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.179293e+00</td>\n",
       "      <td>1.981753e+00</td>\n",
       "      <td>3.842719e+02</td>\n",
       "      <td>1.069970e+01</td>\n",
       "      <td>5.125027e+00</td>\n",
       "      <td>8.999021e+00</td>\n",
       "      <td>2.000982e+00</td>\n",
       "      <td>1.964191e+00</td>\n",
       "      <td>1.961763e+00</td>\n",
       "      <td>1.885336e+00</td>\n",
       "      <td>1.891035e+00</td>\n",
       "      <td>1.889327e+00</td>\n",
       "      <td>1.869404e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>5.963556e+01</td>\n",
       "      <td>1.609958e+02</td>\n",
       "      <td>3.444881e+03</td>\n",
       "      <td>1.775007e+01</td>\n",
       "      <td>1.766088e+01</td>\n",
       "      <td>1.768990e+01</td>\n",
       "      <td>1.260804e+02</td>\n",
       "      <td>1.332571e+02</td>\n",
       "      <td>1.352649e+02</td>\n",
       "      <td>1.649417e+02</td>\n",
       "      <td>1.418729e+02</td>\n",
       "      <td>1.344031e+02</td>\n",
       "      <td>1.357511e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.140348e+07</td>\n",
       "      <td>5.147363e+07</td>\n",
       "      <td>4.307266e+07</td>\n",
       "      <td>1.794207e+08</td>\n",
       "      <td>1.181344e+08</td>\n",
       "      <td>1.305408e+08</td>\n",
       "      <td>6.026778e+07</td>\n",
       "      <td>5.311350e+07</td>\n",
       "      <td>5.174339e+07</td>\n",
       "      <td>5.225921e+07</td>\n",
       "      <td>5.283371e+07</td>\n",
       "      <td>5.228589e+07</td>\n",
       "      <td>5.253085e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         svm_linear       svm_rbf           MLP       GPR_rbf  GPR_matern3/2  \\\n",
       "count  2.714000e+03  2.714000e+03  2.714000e+03  2.714000e+03   2.714000e+03   \n",
       "mean   1.272862e+06  1.275843e+06  2.939350e+05  2.347354e+06   2.004131e+06   \n",
       "std    5.530698e+06  5.539103e+06  2.117774e+06  1.520361e+07   9.765987e+06   \n",
       "min   -0.000000e+00 -0.000000e+00 -0.000000e+00 -0.000000e+00  -0.000000e+00   \n",
       "25%    2.569527e-01  3.472579e-01  1.750200e+00  1.929708e-01   2.939155e-02   \n",
       "50%    3.179293e+00  1.981753e+00  3.842719e+02  1.069970e+01   5.125027e+00   \n",
       "75%    5.963556e+01  1.609958e+02  3.444881e+03  1.775007e+01   1.766088e+01   \n",
       "max    5.140348e+07  5.147363e+07  4.307266e+07  1.794207e+08   1.181344e+08   \n",
       "\n",
       "       GPR_matern5/2  DecisionTree  RandomForest_10  RandomForest_100  \\\n",
       "count   2.714000e+03  2.714000e+03     2.714000e+03      2.714000e+03   \n",
       "mean    1.889432e+06  1.424026e+06     1.415397e+06      1.406451e+06   \n",
       "std     1.028175e+07  5.936327e+06     5.870825e+06      5.831173e+06   \n",
       "min    -0.000000e+00 -0.000000e+00    -0.000000e+00     -0.000000e+00   \n",
       "25%     3.779417e-01  1.672709e-01     1.872001e-01      1.744215e-01   \n",
       "50%     8.999021e+00  2.000982e+00     1.964191e+00      1.961763e+00   \n",
       "75%     1.768990e+01  1.260804e+02     1.332571e+02      1.352649e+02   \n",
       "max     1.305408e+08  6.026778e+07     5.311350e+07      5.174339e+07   \n",
       "\n",
       "        AdaBoost_10  AdaBoost_100  ExtraTrees_10  ExtraTrees_100  \n",
       "count  2.714000e+03  2.714000e+03   2.714000e+03    2.714000e+03  \n",
       "mean   1.445360e+06  1.414299e+06   1.448184e+06    1.452570e+06  \n",
       "std    5.934263e+06  5.846156e+06   5.981956e+06    5.983045e+06  \n",
       "min   -0.000000e+00 -0.000000e+00  -0.000000e+00   -0.000000e+00  \n",
       "25%    2.585289e-01  1.913955e-01   1.500834e-01    1.410917e-01  \n",
       "50%    1.885336e+00  1.891035e+00   1.889327e+00    1.869404e+00  \n",
       "75%    1.649417e+02  1.418729e+02   1.344031e+02    1.357511e+02  \n",
       "max    5.225921e+07  5.283371e+07   5.228589e+07    5.253085e+07  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loss_on_optimal.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"794\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Text(55.847222222222214, 0.5, 'Loss')"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sns.stripplot(x='ProblemName',\n",
    "              y='Prediction',\n",
    "              hue='distribution',\n",
    "              order=np.sort(performance[\"ProblemName\"].unique()),\n",
    "              data=performance)\n",
    "#sns.boxplot(x='ProblemName', y='CVmean', data=CV_data[CV_data['distribution']=='uniform'])\n",
    "#sns.catplot(x='ProblemName', y='CVmean',row='distribution', kind='box', data=CV_data)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Selector loss performance for various benchmark problems\\n(Optimal datasets)')\n",
    "plt.tight_layout()\n",
    "plt.ylabel(\"Loss\")\n",
    "#plt.ylim([0, 10e3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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DVOnToWVlRX3evLkydDT0+OFvrLUqVdFFAXOhw8fKrwqBgD9+vWDjY0N91p2/I8dO1budmRk9bl27Vpu3t69exX+Dcnk5+fj2bNnSE9Ph6WlJaZNm8a9Jws7Za+YlX5PFjh//PFHMMaQlJTEWy4vLw8ikQhDhw7l5qkaOFVpW4rI6r1sF8Xi4mI0aNAA/fr1AwBcuHCB27+yx/err76CUCjkvmtkx6JsWaKiosAYQ1ZWFoCS7quMVfz4G7FYDBcXF7n57dq1w0cffcS9ltXz9u3becvJfhAr2/17yJAhcHR0VLrdFy9eID09HRMnTuS6R8swxuR6FgBvv08jIyMxZMgQmJqacj0XKiL7rKIfTbp06QInJyfutaztlu2JcurUKYU9FACgVatWvB+SZOu4fv06b7kDBw6AMYYtW7bw9lcWOIuLi2FpaYnx48fL/S3IjoGsm7Xs72vhwoW8bch+EC37A9O0adOgr6+PgoICAG+P6dq1a+X+LSOEqIcCJyFaKC8vDykpKQgMDISRkREMDQ25X7MnTpzIu9+s7NSuXTtuPWUD54ABA8r9rOwK3fz588FYyX1Q5VEWOJ2cnODh4SE3X3aiHRsbC+DtSU7Zq1zlKXsSLBQK5bqtAm/DkKwrWVpaGho2bAjGGJo3b45JkybJ3f+1bds2GBkZQV9fH25ubggLC+O6q5ZHdpL7999/8+bn5+dDX18f//vf/wCod+w8PT3RtGlThdtTFDj/97//QV9fX+6KOABYWlryurSKxWK5qyYyjDHe1Rjg7XGSddOUkZ3Q/fTTT9y8u3fvwtfXF1ZWVnL7VzoQybrUlSWrS5n+/fujYcOGCssqo069KqIocMquJJa9Lwx4GyJkA6XIylzR/aKltWrVindlbtSoUbCxseFOdoGSK16hoaFwcHCAnp4eb59K/0gjOzEufRWu7HuywCn7IUbR37Wrqys6d+7MvVY1cKrSthSR1Xvpq6oyHh4eXMjZtm1buceXMcZdLZYdi9JdQEvXwz///AMAmDBhgkojPYvFYvTv319hHZS+5162/jNnzvCWU1YeX19fmJmZ8ebt3bsXXbp0gVAo5O2bnp4ebzlFV3CBt+3UzMwMjDEcOHCg3H1T9NnSVyFlRo8eDaFQyCt7nTp1lP6gqOgHqCFDhvB+pPH19eWFO5nbt2/zfqST7a8scD558qTCvwXZrRSl7xEuraJjJbtympOTg+7du4MxBhsbGwwfPhzbtm2j8ElIJVDgJETLyf5xnDNnDoCSYKGnp4eDBw8iOTlZbjp9+jT32bKBs1+/fqhXr57CzyUnJ+PixYsAaj9wqjOqYmUDJ1ByxW3r1q0YO3Ys7OzsFJ5gPXz4EHFxcfDx8YGJiQmMjIzkrgaVpSxwFhQU8AKnOsdONmiQIuUFzrIncIDiwKls5E1FVzKVHaeyQa2wsBAtW7aEjY0N5s+fj127diE5ORkbNmwAY28HN1K2D0DlAqc69apIdQVOdbrehYWFoU6dOkhPT8ebN28gEom4vxOZL7/8Evr6+pgxYwZ27NiBQ4cOITk5GXXr1uW1Adl3RNmraKXfq0zgbNy4scLA2aNHD7nuoKq0rbJUDZyyILNo0SKl312yH1qUHYuy9aBO4FTUVsqGbmXHQFl5yv79Hz9+HHp6evD09MS6deuQlJSE5ORkjBw5ktceAMVtFHjbTocOHQpTU1O8//77CgctU0TdwKmo7dZG4JT12Bg1apTSvwXZqO7Kusqrc6yKiorw66+/Yvr06XB2dgZjDL1795bruk4IKR8FTkK03JUrV8AY405GFy5cCMbkuyIpUjZwTpo0CQYGBhU+AkPVLrWDBw9Wq0vt1q1bwZh8l9qqBE5lXWploVnZIEx5eXkYNGgQDAwMlJ6UPXnyBA0bNkT37t3LLZOqXWrVOXbqBk5lXWofP34MxuS71NZE4ExNTZW7kgmU3J9c2cCpSpdadepVEXW71Pbv319hl1p1AmdaWhoYK7lHNzExEYwxue6PFhYWct3Nc3NzYWBgUOnAWV6XWgsLC16X2g4dOvBGH5VxdHSUC5xl11VR2wJU71KbkpICxhji4+OVrktG1cCpTpfa2gic/v7+MDY2lhsltTKBUxbMhUIhBg8erPBHKGWfVbVLraK2W16XWmdn52rpUltYWAhzc3OV7peujsBZVmRkJBhjSE5OrnD7hJC3KHASoiWOHDmi8OHsCxYsAGMMUVFRAIBbt27BwMAAI0eOlFu+uLiYN5BC2cD522+/KTzBA0quxslGEczKyoK5uTnc3d3LHTRo+PDhcvcXAW/vkfnxxx956+/evbvCQYOqEjhlV5tOnTrFzcvOzkbTpk15gwaVHWACAGbNmgV9fX28fPkShYWFyMzMlFvGzc2Nd9VHkYoGDZJdOVbn2KkbOGVXj8ePH8+bP3v2bDAmP2hQTQTOy5cvgzH+Iz9kA4FUNnCqMmiQOvWqSHmDBtnZ2fFG17xy5YrSQYPUHVykbdu2eP/99/HZZ5+hQYMGcj/QWFtbY+zYsbx5snBd2cApGzSof//+vLpasWKF3NXGYcOGwc7OjncVUHavaemwVVHbUqaiQYNkI1oXFRWhWbNmaNGiBV69eiW3ntL3AasaONUZNKg2AueMGTNgYmLCG334zp073P38pakSOAEgMTERderUwWeffVZhN9CKBg0qfc+wsrYrGzSoXbt2vOCclJQkd/W0vEGDDA0Nece0dOAESkatFggECn9MLP25qgZORT9y7d+/X67nDCGkYhQ4CdESrVu3RpMmTTBjxgysXr0asbGxGDlyJAwMDOSGlJd1i+vWrRsWLlyIlStXYvbs2WjRogUvFJQNnEBJ90PGSh4xER0djdjYWPj7+8Pe3p73D/PatWvBWMkIf9999x1WrlyJCRMm8E60ZSe/06dPx48//og9e/YAePtYFIFAgG+++QbLly/nRl1V9FiUqgRO2WNRLCwsEBoaiujoaLi6ukJPT4/3WJSOHTti4MCBiIyMxNq1a/HNN99AKBTiww8/BABkZGTA1NQUvr6+iIqKwurVq/Hpp5+CMYYlS5aUW6ayj0WJi4vjHosycuRI3rKqHjt1A6dsPmMMn376KeLi4rjXih6LUhOBMz8/H82aNYONjQ0iIyOxfPly9OrVC+3bt6904ATAPbJgwIABWLp0KaKjo/Hxxx/zHouiar0qouzEVPZYlFatWmHRokWIiIiAra0trKyseN2nKxs4586dC319fZiYmPBOvGXGjBkDAwMD+Pv7Iz4+HmPHjoWDg0OVutSWLq+XlxdiY2Ph5+en8LEostGr33//faxcuRIzZ85E/fr10axZM17YqqhtKVP2sSiyx2gYGRmhefPmvPB19OhRGBkZoVGjRggLC8Pq1asRFhaGnj17YvDgwXL7VlHgBIDQ0FDub2bx4sVYvnw5xowZwxt9tbYC5+HDh8EYg4eHB1auXInw8HAuvFU2cAIlzxnV09OT+yFK2WdLPxYlIiIC1tbWqFu3Lh4+fKi07KXJ6qFLly6IiYlBYGAgTExMyn0sypgxYxAXF8c9FiUoKEhuf8s+FkUsFsPExIRrG/PmzcMnn3zCG3CsqoHT398fHTp0QEhICNasWYPIyEg0bNgQDg4OCn+cJIQoR4GTEC1x4MABfPHFF2jVqhXMzMwgEAjQvHlz+Pn5cfeklPbzzz+jR48eMDU1hampKVq1aoXJkyfzuigpCpxAyXPzOnXqBGNjY5ibm6Nt27aYPXs276QCAPbs2YNu3brB2NgYIpEI7u7uvK5O2dnZGDlyJCwtLcEY423ryZMnGDduHGxsbCAQCNC2bVte4ACqJ3ACJff9DBs2DJaWljAyMoK7u7vcL9Dx8fHo2bMn6tatyz1DbtasWdyolXl5eZg1axbat28Pc3NzmJqaon379gq7h5UlO1FJS0vDsGHDYG5uDisrK0yZMkVhl0JVjl1lAmdBQQHCw8PRpEkTGBoawtHREYGBgXLd9GoqcAIlXUX79OkDMzMz2NjY4Ouvv8alS5eqFDgLCwuxaNEitGrVCgKBALa2thgwYADOnz/PW06VelVE2YkpAPz666/o3r071wY+/PBDuW7LlQ2cN2/eBGMlA50oGmQnIyODa0NmZmbo168frl27JtcG1A2cQMljUFq1agVDQ0PY2dlh4sSJCp9XumTJEjRs2BBCoRDdu3fHuXPn5MJWRW1LGVm9b9myBYGBgahXrx6MjY0xaNAghc/iTU1Nxccff8xtRywW49NPP+XdM6hO4ASA9evXo0OHDhAKhbCysoKnpyevu2RtBU4AWLduHVq0aAGhUIhWrVohISFBYXtQJ3ACb69ez5w5U+4zij67ZMkSODo6QigUwsPDg3usU3llL23btm1cnVpbW+Pzzz/nXTUtvY7bt2/Dy8sLJiYmsLOzQ1hYmNzV2LKBEyj592Xy5MlwdHSEoaEh6tevjw8++ACrV6/mlqlq4Dx8+DB8fHxgb28PgUAAe3t7jBgxAjdu3FC674QQxShwEkJIFVU2cBBCiDaozI9/hBCiKgqchBBSRRQ4CSHvMgqchJCaRIGTEEKqiAInIeRdRoGTEFKTKHASQkgVUeAkhLzLKHASQmoSBU5CCCGEEEIIITWCAichhBBCCCGEkBpBgZMQQgghhBBCSI2gwEkIIURtCxYsgJOTk9wz8zRB0XP63oVty54TePTo0Wot07tm+PDh+OSTTzRdDEIIITWEAichhBC1ZGVlwdraGuvXr5d7Lzs7GxEREWjbti2MjY0hEonQo0cPbNy4EcXFxZXe5v79+5UGu/9i4CyvPjQhMjISiYmJlfrshQsXoK+vj4sXL1ZzqQghhGgDCpyEEELUEh0dDZFIhNzcXN78x48fo3Xr1tDX18fIkSMRHx+PpUuXomfPnmCMYfjw4SgsLKzUNidPngzGFP+TlZubi4KCgkqtt6o0FTjLqw9NMDU1ha+vb6U/7+7ujtGjR1dfgQghhGgN7fnXihBCyDuhXbt2GDVqlNz8fv36QV9fH7t375Z7b+bMmWCMYf78+ZXaprYFLBkKnCWqGjgXL14MU1NTvHr1qvoKRQghRCtoz79WhBBCtN7ff/8Nxhg2bNjAm3/69GkwxvDFF18o/FxBQQFatGgBKysr5OTkAOA/+y8qKgqNGjWCkZERevbsiStXrnCf9fX1BWNMbpIpG/pkz0W9fv06Pv/8c4hEItjY2CAkJATFxcW4d+8evL29YW5uDjs7OyxevJhX1ry8PISGhqJjx44QiUQwMTFBjx49cOTIEbn9UjVw/vvvv/Dx8YGJiQlsbW0xbdo0HDx4UC5wHj9+HMOGDYOjoyMEAgEcHBwwbdo0rs5UqY9Fixaha9eusLa2hpGRETp27IgdO3bIlenQoUPo3r07LCwsYGpqipYtWyIwMJC3zJs3byCVStGsWTOuPLNmzcKbN294dVB2koXPly9fwt/fH2KxGAKBALa2tujTpw/Onz/P286lS5fAGMPOnTsrrEtCCCHvFgqchBBCVLZ582YwxnD58mXe/KCgIDDG8Ntvvyn9rCwIJicnA3gbONu2bYvGjRtjwYIFCA8Ph7W1NWxtbfH48WMAwKlTp9C3b18wxrBp0yZuklEWOF1dXTFixAisWLECgwYNAmMMUVFRcHJywsSJE7FixQp0794djDEcO3aM+3x6ejoaNGiAGTNmYOXKlVi4cCGcnJxgaGiI1NRU3j6pEjhzcnLQsmVLGBkZYfbs2YiJiUGnTp3Qrl07ucDp5+eHgQMH4rvvvkN8fDy+/PJLGBgYYNiwYdwyFdWHg4MDJk2ahNjYWERFRcHd3R2MMezbt49b5s8//4RAIEDnzp2xdOlSrFq1CjNnzkTPnj25ZYqKiuDl5QUTExNMmzYN8fHxmDJlCurUqQMfHx9uuU2bNkEoFMLDw4Mry6lTpwAAI0eOhEAgwIwZM7B27VosWLAAH374ITZv3syro4KCAhgbG+Obb74pty4JIYS8eyhwEkIIUVlISAgYY5h0Y2UAACAASURBVHJdH4cMGQLGGDIyMpR+dufOnWCMYdmyZQDeBk5jY2Pcv3+fW+7s2bNgjGH69OncvPK6kCoLnOPHj+fmFRYWwsHBAXp6erxuvRkZGTA2NuZ1By0sLEReXh5vGxkZGbCzs5O7gqtK4IyJiQFjDNu3b+fmvX79Gs2bN5cLnKWvZMrMmzcPenp6uHv3LjevvPoou478/Hy0adMGvXv35uZFR0eDMYb09HSl5d60aRP09fVx4sQJ3vxVq1aBMYaTJ09y85R1qbWwsMDkyZOVbqO0li1bYsCAASotSwgh5N1BgZMQQojKJk6ciDp16sjN/+CDD8AYK3dQoOTkZDDGMHfuXABvA+eIESPklu3SpQucnJy415UJnCkpKbzlZKG4bMhydXWFh4eHwnUXFRXh+fPnSE9Px6BBg+Dq6lruthXx8vJCgwYN5EbpXbhwYbn3cGZnZyM9PR3Hjh0DYwy7du3i3lP1Hs4XL14gPT0dEydOhKWlJTc/ISEBjDGsXbtW6aNtvL290bp1a6Snp/OmGzdu8I4joDxwisVidO7cGQ8ePKiwrF26dIGbm1uFyxFCCHm3UOAkhBCiMmWBU50rnEuXLgXwNnBKpVK5ZUePHg2hUMi9rkzglHXJlfH19YWRkZHc5z09PdGmTRvevA0bNqBt27YwNDTk3ZvYpEmTcretiJOTk8JAu3v3brnAeffuXfj6+sLKykruvsiNGzdyy5VXH3v37kWXLl0gFAp5n9fT0+OWycnJ4boT29jYYPjw4di2bRsvfDo7Oyu8P1M2TZ06lVtWWeDctm0bjIyMoK+vDzc3N4SFheH27dsKy+3u7g53d3el9UgIIeTdRIGTEEKIymRdal++fMmbHxgYKHcvZFlz5sxReA9nTQXOslcyfX19YWpqKvd5T09PtG7dmnu9adMmMMYwZMgQfP/99zh48CCSk5PRu3dviMXicretiKqBs7CwEC1btoSNjQ3mz5+PXbt2ITk5GRs2bABjDAkJCRXWx/Hjx6GnpwdPT0+sW7cOSUlJSE5OxsiRI+WWLyoqwq+//orp06dz4bJ3797cVWonJye0bdsWycnJCqdr165x6ypvlNqHDx8iLi6OGzTJyMgISUlJcsu1aNECAwcOLLcuCSGEvHsocBJCCFGZbNCgS5cu8eafPHkSjDF8+eWXCj8nC1OKRqlVpUvtlClTai1w+vj4oGnTpnJdYLt161apwOnl5QV7e/sKu9SmpqbKXckESkaTLRs4ldWHv78/jI2NeaPIAlAYOMuKjIzk/SAwcOBANGzYUK7cipiZman0WJQnT56gYcOG6N69O29+QUEBjIyMaNAgQgjRQRQ4CSGEqOz27dtgjGHdunVy7/Xp0wf6+vrYu3ev3HsSiQSMMcybN4+bV9GgQdOmTZP7vKIuu9UdOD/++GM0bdqU1730zJkz0NPTq1TgVHXQoMuXL8s9cqa4uJgbYbd04FRWHzNmzICJiQlev37Nzbtz5w5MTEx4gfP58+dy5dy/fz9vNFvZldX4+Hi5ZXNycpCdnc29trOz441cC5T8yJCZmSn3WTc3N3Tu3Jk3T/ZYlJ9//llueUIIIe82CpyEEELU0qZNG4VXJR8+fAhnZ2fo6+tj1KhRiI+Px7Jly9CrVy8wxjB8+HDeoEKKHosSEREBa2tr1K1bFw8fPuSW3b59OxhjGD16NDZv3owtW7Zw71V34Fy/fj0YY/D29kZ8fDwCAgJgaWmJ1q1bVypwysKlkZERJBKJ0sei5Ofno1mzZrCxsUFkZCSWL1+OXr16oX379nKBU1l9HD58GIwxeHh4YOXKlQgPD0e9evW4bcn4+/ujQ4cOCAkJwZo1axAZGYmGDRvCwcGBC4lFRUUYOHAg9PT08Nlnn2H58uWIiYnBhAkTYG1tjT/++INb38CBA2FqaoolS5Zgy5YtOHPmDDIyMriutlFRUVi9ejU+/fRTMMawZMkSXh0tXrwYJiYmcl21CSGEvPsocBJCCFFLVFQUzMzMFD7C49WrV5gzZw5at24NY2NjmJubo3v37tiwYYNc10xZ4Fy0aBGWLFkCR0dH7nmOZbvsFhYWws/PD7a2ttDT0+OFp+oOnMXFxfjuu+8gFoshFArRoUMH7Nu3D76+vpUKnEDJYEDe3t4wMTGBjY0N/P39cfDgQblBg9LS0tCnTx+YmZnBxsYGX3/9NXf1r3TgLK8+1q1bhxYtWkAoFKJVq1ZISEjg6kTm8OHD8PHxgb29PQQCAezt7TFixAjcuHGDV+78/HwsWLAArVu3hlAohJWVFTp16oTw8HBkZWVxy127dg09e/aEsbExGGPw9fVFXl4eZs2ahfbt28Pc3BympqZo3749VqxYIVc/Xbp0wahRoyqsR0IIIe8eCpyEEELUkpmZCWtra6xdu7ZK6ykdOMl/V2pqKvT09JCamqrpohBCCKkBFDgJIYSobf78+XByclL6DEdVUOAkADB8+HB88sknmi4GIYSQGkKBU4tERUXBxcUFzs7O8PPzU2lkQEIIeVdR4CSEEEJ0HwVOLfH06VM0bdoUubm5KCwsRLdu3XDq1ClNF4sQQmoMBU5CCCFE91Hg1BJPnz5Fo0aNkJGRgdzcXLi5ueHWrVuaLhYhhBBCCCGEVBoFzmpy7NgxDB48GA0aNABjDImJiXLLxMbGcqMeuru74+zZs7z3ly1bBnNzc1hZWSEwMLC2ik4IIYQQQgghNYICZzVJSkpCcHAwdu7cqTBwbt26FQKBAOvXr8fVq1fx9ddfw9LSEk+ePAEAvHjxAl5eXnj+/DlycnLg6emJY8eOaWJXCCGEEEIIIaRaUOCsAYoCp7u7OyZPnsy9Lioqgr29PebNmweg5CHekyZN4t5fuHAhFixYUO523rx5g6ysLG7KyMjA7du3kZmZyZtPE0000UQTTTTRRBNNNGUhMzMT//77b5VGWSfqocBZA8oGzry8PBgYGMiF0DFjxsDb2xsAcPr0abi6unKDBg0cOBC7du0qdzuyB3nTRBNNNNFEE0000UQTTapP//77b/WHAKIQBc4awBg/cD548ACMMblRZ2fNmgV3d3fudVBQEFq1agUXFxeVHotS9grnvXv3uAak6V+PaKKJJppoookmmmiiSdumf//9F4wxZGZmVm8AIEpR4KwBlQ2cVZWVlQXGGLKysqptnYQQQgghhOgKOl+ufRQ4a0DZwKlKl9rqQA2IEEIIIYQQ5eh8ufZR4KwBZQMnUDJo0JQpU7jXRUVFaNiwITdoUHWgBkQIIYQQQohydL5c+yhwVpNXr14hNTUVqampYIwhKioKqampuHv3LoCSx6IIhUJs2LABaWlpGD9+PCwtLfH48eNqKwM1IEIIIYQQQpSj8+XaR4Gzmhw9elThCFi+vr7cMsuXL0ejRo0gEAjg7u6OM2fOVGsZqAHVgMIC4EYycHkH8OqppktDCCGEEC1SVFSE3NxcmrRoKiwsLPeY0fly7aPAqUOoAVXR0+tIWT8LQXOCMXNOOI7O+wjFc6yBMNHbKd4T+PuYpktKCCGEEA3Ly8vDtWvXkJaWRpOWTQ8fPlT6tAc6X659FDh1CDWgKnhxB3FhX0Es2QexZB+8A2KQJbXjh83S0/5Zmi4xIYQQQjSkuLgY//zzD27evInXr19r/KoeTSVTTk4Onj17xoVOReh8ufZR4NQh1IAq70liCJpLdnGB83xoR+VhUzbdP6fpYhNCCCFEA/Lz85GWlkbPctRSstCpqHstnS/XPgqcOqTSDaioCCjIq5lCvSMSY/y5sNlWsrXisBkmAo5EarrYhBBCCNGA3NxcpKWlIScnR9NFIQrk5OQgLS0Nubm5cu9R4Kx9FDh1iNoNKD8XOBAAfOdQEqDW9gX2zQCSZgMPLtZsYbXM4bXBXOB0kvyMN1LrcsPmtRBn4PcYTRebEEIIIRogC5yKAg3RvPKODwXO2keBU4eo3YB2fFH+Fbz1A4Ci8kf60hX5p9eguSSRC50/hwxUWCeFUgs8lTpggGQZkHlf08UmhBBCiAZQ4NRuFDi1CwVOHaJWA8q4B8yxrLjb6OG5NV9wLfDqn1TEBX+OXgFr/r9b7Tb8HtKVq4d8qRXWBX+KsYHh+DhgCVoF/KzpIhNCCCFEQ6o7cHp6esLf3x8AIBaLER0dXS3rLc3X1xc+Pj4Kt1nT26ptFDi1CwVOHaJWA7pzotygmRbaGudDO6JgoVPNF1wL5GfcR6HUAsVSEc6HdsS6oE8gluxD34CVGBcYATfJJu7qp1iyDz3CEzVdZEIIIYRoSE0GzqdPn+L169cqfU6dcJqZmYmMjAyF26ysO3fugDGG1NTUcrdV2yhwahcKnDpEnQaUdOYyiqQW+D2kK9YFf4LXUltet9HQID+IJfvgFrAZyVcf10LpNezqbl7gXhH8OS9glp22nrmt6RITQgghRENqMnCqQ5XAWVhYiKKiomrbZmnKAqemUeDULhQ4dYiqDaiwqBhdv/sV0wNno7lkF55KHeWucBZJLeAVsAJiyT60CE7Cveeq/dL2znpyDcXSt/ufGDJAadj8MiFF06UlhBBCiAZVJXBmZ2dj9OjRMDU1Rf369bF48WKlXWqLi4sRFhYGR0dHCAQCNGjQAH5+fgBKAiNjjDcBQEJCAiwsLLB79244OzvDwMAAd+7cUdildvLkyZg8eTJEIhHq1q2LkJAQFBcXc8swxpCYyO/VZWFhgYSEBO790pOnpycA+S61b968gZ+fH2xtbSEUCtG9e3ekpLw9nzp69CgYY/j111/RqVMnGBsbo2vXrrh27Zra9QtQ4NQ2FDh1iKoN6O6z11x48g2cq7RbbWzwKG65mOQbtbQXGhTVmtv3XGldvCfZKBc2u88/jLwC+V8JCSGEEPLfUZXAOXHiRDRq1Ai//vorLl++jMGDB8Pc3Fxh4NyxYwdEIhGSkpJw9+5dnD17FqtXrwYAPH/+HA4ODoiIiMCjR4/w6NEjACWB09DQEN26dcPJkydx7do1vH79WmHgNDMzg7+/P65du4bNmzfDxMSEWz9QceBMSUnhguKjR4/w/PlzAPKBc+rUqbC3t0dSUhKuXr0KX19fWFlZccvLAmeXLl3w22+/4erVq/Dw8EC3bt3Url+AAqe2ocCpQ1RtQFm5+WgSUBKgvg4MUxo4Vwd/xgWtiZvO1c5OaNKzW8CCptz+3wp1wqdz4rk6GLH6NO6kZ2u6lIQQQgjRsMoGzlevXkEgEGD79u3cvOfPn8PY2Fhh4FyyZAlatmyJ/Px8hetT1KU2ISEBjDFcvMh/xJ2iwOns7My7oimRSODs7My9rihwKutSW3pb2dnZMDQ0xA8//MC9n5+fD3t7eyxcuBAA/wqnzP79+8EYq1Sop8CpXShw6hB1GtCAmOMQS/bBRbIDr6T1FAbOYQGLubDVMeJQLeyBFji2SK4ekheNhN+aX3Di+BGgUPEXPiGEEEL+OyobOC9evAjGGO7evcub7+rqqjBw3rt3D46OjnBwcMBXX32FnTt3oqCggPucssApEAh4QRJQHDjHjRvHW2bXrl2oU6cOCgtLHotXHYHz0qVLYIzhn3/+4S0zZMgQbvuywPn06VPu/QsXLiisK1VQ4NQuFDh1iDoN6Pqjl1yY9AsMQr7Uihey1gd/Ited9OoDHW+YLx8B4XUVhu8xgXMhluzD4tAJwMUtmi4pIYQQQjSotgInAOTk5GDPnj3w8/ND/fr10bVrV+6Kp7LAaWFhIbftygROPT097Ny5k7eMiYlJjQXO0iPbpqamgjGGO3fuyO1LRShwahcKnDpE3Qb09caUt/cmBiRgftB4LA0eA++AGIWD5Vz+N7OG90DDLm5V2r04R1oX3gExaCLZg/vSJkDKOk2XlhBCCCEaUpUutYaGhrwutS9evICJiYlKz+G8du0aGGM4f/48AKBFixZYvHgxbxl1AqeLiwtvmYCAAF6X2nr16iEuLo57fePGDTDGuMD54MEDMMZw7hz/1quyXWoFAoFcl9qGDRti0aJFAChw6joKnDpE3QZ05K8naBqg/NEfpSePBUdQVFRc8UrfYRe2RJT7bNJboU4QS/ZiW/CHQIQNkEtfVIQQQsh/UVUGDZowYQLEYjEOHz6MK1euwNvbmxu8B+AHzoSEBKxduxZXrlzB7du3ERISAmNjYzx79gwA0LdvX3h7e+P+/ftIT0/nPqNq4DQzM8P06dNx7do1/PjjjzA1NcWqVau4ZT777DM4OzvjwoUL+OOPP9C7d28YGhpygbOgoADGxsaYO3cuHj9+jMzMTIXb8vf3h729PQ4cOMAbNOjFixcAKHDqOgqcOkSdBpRXUIRO3yarFDbbSA/i7N/Pa2EPNCf95Ru0lPyMh9LG5YbO/gFxiAnyLXl9dZemi00IIYQQDahK4Hz16hVGjRoFExMT2NnZYeHChUofi5KYmIguXbpAJBLB1NQU7733Hm9gndOnT6Ndu3YQCoVyj0UpS1HgnDRpEiZMmACRSAQrKysEBQXx7v188OABvLy8YGpqihYtWiApKYl3DycArFmzBo6OjtDX11f6WJTc3Fz4+fnBxsam3MeiUODUTRQ4dYg6DejkzXSVwmZr6UFkvtb9gXLGrDsLsWQfBgbEKh1ESRY4xZJ9CAuaAlxL0nSxCSGEEKIBVQmcpOZR4NQuFDh1iDoN6NStZ3Lhcmzgt0gN7YBcaV2khbaBX2AQmkj24NnVozVfeA1zCT3A1UPvgFXYG9JXbiAlWZda2XJX/nla8YoJIYQQonMocGo3CpzahQKnDlGnARUUFsFdmsiFp9GBkSiUyl/R8w8MwN+hTsDt32phDzSndOCUTR8ErMJTqQMQJsJzqb3cYErLD9/QdLEJIYQQogEUOLUbBU7tQoFTh6jVgE6vwJlQd7SVbINYsg+nQroo7EL6LLQhiqUiYKlrze+ABvVefFRhl+J+AXGYETgbzpKf5N5L+P1vTRebEEIIIRpAgVO7UeDULhQ4dYhaDSimHRAmwo7gQfggYBWypHblDpaDMBHwWncHDuoY8YvCwNlYshfNJYkK3zt2/Ymmi00IIYQQDaDAqd0ocGoXCpw6RJ0GVBxhg4igiW/vRwxpW3HgTNtTC3uhGe5z9ioMle0kW5ES6gZ3yffoJPkBzpKf0Pj/7+P84fQdTRebEEIIIRpAgVO7UeDULhQ4dYg6DehszHCIJXvRWLIHAUHTcT+0ScWB8+/jtbAXmvHt6h8UBs7gIH88kTriQWjJ41LypFb4KWQg2ki24+Rh3Q3ghBBCCFGOAqd2o8CpXShw6hB1GtCwJXsgluzD9uDBFQfNMBFeSBsARUW1sBeacfzkKbSTbOGFzSEB0bgb2gQ5Uhu5+jgR0g3FB4M1XWxCCCGEaAAFTu1GgVO7UODUIeo0oJ4LDuODgFUqhU2EifBSaoe83Jxa2AvNmL56Hx5LG+FMqDu+D/4YB0LeB8JESAntrLxODn6r6WITQgghRAMocGo3CpzahQKnDlGnAXksOIxZQd+oHDgRJkJx1oNa2AvN+CFsuMJ9PhPiprQ+bhzfruliE0IIIUQDKHBqNwqc2oUCpw5RK3DOP4xRgZEqh81MaX1AhwPnVaniQZMOhPRWOD9XWhdPnzzUdLEJIYQQogEUOGuHr68vfHx81P4cBU7tQoFTh6jTgNYuCcDUQAlypDY4EdINowMj4RGwDuMDpbgY6qqgS209IP1GLeyFZlyc464wWN4JbY5boU5y87fPHa3pIhNCCCFEQ6orcP71KAvRydcRvucqopOv469HFIJKo8CpGyhw6hB1GtDreS2AMBF+CXkfTSR7eIPltJDsxIXQDm+70kpFwPwmOj1o0Il1AUqv7sYHDUds8ChcDm2H30O64ufgAXgd66HpIhNCCCFEQ6oaOO+kZ+OjuN8hluxD08D9aB60H00D90Ms2YePV5zEnfTsai5xzcjLy6vR9VPg1A0UOHWIyg2oqAhFcyyBMBH6B8QqfBzIl4Hh/FFq47xqZyc0pDgnA+lSR4WB0zfwW65edgf3ffte5n1NF5sQQgghGlCVwHknPRvt5vzCBcyyU9PA/Wg355caCZ2enp7w8/PDrFmzYGVlBTs7O4SFhXHv3717F97e3jA1NYW5uTk++eQTPH78mHs/LCwM7du3x5o1a9C4cWPo6elx650yZQr8/f1haWmJevXqYfXq1cjOzsbYsWNhZmaGZs2aISkpiVtXYWEhvvjiCzRu3BhGRkZo2bIlYmJieOWlwKkbKHDqEJUbUPYzIEyEQqmFwi86sWQf3CXf865wbl3+H3gEyG+LUCR9GzTfSK2xIOhr7qrvkqBxb8PmHEvg9XNNl5gQQgghGlCVwPlR3O9Kw2bp0Dl0xclqL7enpydEIhHmzJmDGzduYOPGjdDT08OhQ4dQVFQEV1dX9OjRA+fOncOZM2fQqVMneHp6cp8PCwuDqakp+vfvjwsXLuDSpUvces3NzfHtt9/ixo0b+Pbbb2FgYIABAwZg9erVuHHjBiZOnIi6devi9evXAID8/HxIpVL88ccf+Pvvv7F582aYmJhg27Zt3PYocOoGCpw6ROUGVFiAzDB7IEyEbpIEhV90nwQs4sLVrdCWGLfy19rZCU3bOYE/Em2oM46FdMdzaUP+lc8fhmu6pIQQQgjRkMoGzr8eZZUbNMtO1X1Pp6enJ3r06MGb5+bmBolEgkOHDsHAwAD37t3j3rt69SoYY0hJSQFQEjgNDQ3x9OnTctdbWFgIU1NTjB79dsyLR48egTGG06dPKy3f5MmTMXToUO41BU7dQIFTh6jTgJaFjQfCREgIHqbwC+6X/38OZbbUFh8HLMbyw7o7YBAnNwtIngOEWZQ/au/q94GXjyteHyGEEEJ0UmUDZ3Ty9Qqvbpa+yhmTXL3nX56enpg0aRJvnre3N8aNG4elS5eicePGcp+xtLTExo0bAZQEzubNm6u03kaNGmHhwoXc6+LiYjDGsHv3bm5ebGwsOnbsCBsbG5iamsLQ0BBubm7c+xQ4dQMFTh2iagN69aYATSS7cSm0HRAmwrrgT9FFshFiyT70CliDnSEDeAHrhLQHMl/n19JeaEjWA+A7h4ofERNho+mSEkIIIUTDKhs4w/dcRfMg1QJn86D9CN9ztVrL7enpCX9/f948Hx8f+Pr6qhw427dvr9J6xWIxoqOjefMYY0hMTAQAbNmyBUZGRoiLi8OFCxdw8+ZNjB8/nrd+Cpy6gQKnDlG1ARUVFWNh+DRekCqWivBaaqswZBVJRUDGv7W0FxqyykO1Z5LOsQTevNR0aQkhhBCiQe/yFU5lgbO8LrV//PEHgOoNnFOmTEHv3r1573/wwQcUOHUQBU4dok4DerK4q2oBSzbtGFcLe6AhBXklQVLVukhZq+kSE0IIIUSDausezmuPqvdH7vICZ3FxMVxdXeHh4YHz58/j7NmzCgcNqq7AuXTpUohEIhw8eBDXr19HSEgIRCIRBU4dRIFTh6jTgIrj3lMvcC7rXAt7oCGvn8sNFLQ8eDQSQ/qVPIO0bF0saAYUvNF0qQkhhBCiIe/yKLXKAieg+mNRVFlvRYHzzZs3GDt2LCwsLGBpaYmJEyciICCAAqcOosCpQ9RqQD99pV7g3Kh+Y3+nzG8MhIkQGzya+7JPCvlAeX2s6avpEhNCCCFEQ97V53D+V1Dg1C4UOHWIWg1orZd6gfPKTzW/AxpUtMoTN0Ja8b7wL4R2LL9O7pzQdLEJIYQQogFVCZxASegcuuIkFzCbB+3nAujQFScpbFYRBU7tQoFTh6jVgCLtVQ+bh6Q1X3gNWzl3CmKCxvACZ3zwiHLrpfhEdMUrJoQQQojOqWrglPnrURZikm8gfM9VxCTfqPZ7Nv+rKHBqFwqcOkStBhSn4qBBW8fUfMG1QNeQbYgL+pwXON0l3+ORVKy0bu4d+17TxSaEEEKIBlRX4CQ1gwKndqHAqUPUakCpP6h+hXNNX6CoqOZ3QIOaBe7D5uAhaCzZywudbpJNWBU8An+FuvDqJFNqhyv/PNF0sQkhhBCiARQ4tRsFTu1CgVOHqNWAnqSpdw/nmfia3wENGh5/Cp4Ba+Ak+Unxw5clu1AsFeFcSEekS+3hFbAKxcXFmi42IYQQQjSAAqd2o8CpXShw6hC1GtDW0eoFzuVuNb8DGnTunxdwCklCE8luhYGzs2QzxgZ+i56SNf8/by/uPqcb+gkhhJD/Igqc2o0Cp3ahwKlD1GpAq3opfsaksmlxq5rfAQ27/vglhq08qfLDmOOP3dJ0kQkhhBCiARQ4tRsFTu1CgVOHqNWA9k7HqqDyR2GVTf+ENsealVE1vwNaInzPnyoFzq0pdzVdVEIIIYRoAAVO7UaBU7tQ4NQh6jSggB9OQCzZh5BAP4Uhs0hqUfLoD6kIUwID0f27Q7WwB9rjlz8foUPEIaVhs7FkH56+fKPpYhJCCCFEAyhwajcKnNqFAqcOUbUBPc7KRZOAkuDUUrITxVIRfgz2xpTAIMQGj8LMoJlwlfyIfcEfAGEirAj+HC6hB2ppL7RLTl4hPl11Si5wrjtxW9NFI4QQQoiG/FcD59GjR8EYQ0ZGBjcvMTERzZo1g76+Pvz9/TVYurcocGoXCpw6RNUGlHz1MS88XQxtjyaSPXKhyknyM/4ObYGNwUMxdMXvtbQX2un07WcI/PkSIvenIe0hfUERQggh/2XVFjgf/wkcnQccCCj57+M/q6eANSQvLw+PHj3ijdRfr149SCQSPHjwAC9fvtRg6d6iwKldKHDqEFUb0NUHWbxg2UmyWWnX0R3Bg7AmeDgu3ssod52EEEIIIf8VVQ6cz24Ba/qU3Mo0xwoIr1vy3zARsLZvyfvvgFevXoExhiNHjlRpPXl5edVUohIUOLULBU4dok4DGrzsuEoD42wL/hBZEWKgML/md4AQQggh5B1QpcD57BYwT/w2YJad5liVvF8DoVMsFiM6Opo3s14HhwAAIABJREFUr3379ggLCwMAMMawZs0aDBkyBMbGxmjevDl2797NLVu6S63s/0tPR48eBQD89NNPcHFxgUAggFgsxuLFi+XKERERgdGjR8Pc3By+vr64c+cOGGPYtm0bevToASMjI3Tu3BnXr19HSkoKOnXqBFNTU/Tv3x9Pnz4tdz8pcGoXCpw6RJ0GlP7yDRpXEDZbSBLxTNqw5MtPy7t41IhXT5F36SecPLQDa47dxKV/6SovIYQQQqoYONf0UR42S4fOtX2rvdyqBE4HBwf8+OOPuHnzJqZOnQozMzM8f/4cAD9w5uXl4fr162CM4eeff8ajR4+Ql5eHc+fOQV9fHxEREbh+/ToSEhJgbGyMhIQEXjlEIhEWL16MW7du4datW1zgbNWqFQ4ePIi0tDS899576NSpE3r16oXff/8dFy5cQPPmzTFhwoRy95MCp3ahwKlD1GlAjzJzyw2bTSW7sT148P9/6VkCLx/Xwh5okd9jUBRuw33x3wltgQ8CVmHqlgsoLCqu+POEEEII0VmVDpyP/1T9Geg18IO/KoEzJCSEey87OxuMMRw4UDJ4ZNlBgzIyMnhXNgFg5MiR6NuXH5ZnzZoFFxcXXjmGDBnCW0YWONeuXcvN27JlCxhjOHz4MDdv3rx5cHJyKnc/KXBqFwqcOkSdBvTqTQFaBCUpDJu9A+LxQNr47Zfd1lG1UHot8PwOsNYLxeF1FX7p/xXauqSb8R/3NF1SQgghhGhQpQPn0XkVX90sfZXz6PxqLbcqgXP79u2890UiETZu3FhSfBUCZ4cOHTBnzhzeOnbt2gVDQ0MUFhZy5Zg7dy5vGVngTElJ4eYdOXIEjDFeF9r169fDysqq3P2kwKldKHDqEHUb0PRtqQoD58G5H7/9ots2GsjNrOGSa4HnfwPh1hV++Q8OWIox685qurSEEEII0aBKB84DASUDBKkSOMPrlixfjZo0aYKoqCjePBcXF17gTExM5L1vYWHBdYetzsBZNvjKAmdqaio3T9FjWBISEmBhYVHuflLg1C4UOHWIug3o1ZsC/G/VL2gs2QuxZB9aB/yMlT/+DBQWAE/SgFdParjEWmR1L5W+/POkllixdG7F6yOEEEKIznpXr3C6u7tj1qxZ3OusrCwYGxtXa+BU1qW2devW3GsKnP8tFDh1iNoN6P45IMIG96VNcC60E15J65V8waWsqdmCaiNVv/zDRCgOEwF3Tmq6xIQQQgjRkNq7h/NqtZY7ICAA9evXx/Hjx3H58mUMGTIEZmZm1Ro4z58/zxs0aMOGDQoHDaLA+d9BgVOL/P333+jVqxecnZ3Rpk0bZGdnq/V5tRvQ1lFyX2y50rp4HulcEjofXqzEXrybisMs1PsHYH4TTReZEEIIIRryro5Sm5WVheHDh0MkEsHR0REbNmyQu4ezqoETePtYFENDQzRq1AiLFi3ivU+B87+FAqcW6dmzJ44fPw4AeP78OQoKCtT6vNoNqNSXXbFUhHOhHeEpWQ2xZB/6BqzAsZDuJfdwFqpXjndRXrideoEzTATkvNB0sQkhhBCiAe/qczj/KyhwahcKnFrizz//xAcffFCldajVgNL2KfyS+1faFG0k2yGW7ENzSSL+Cm0NnIqrUrneBa8XOKsfOB9d0XSxCSGEEKIBVQqcQEmYXNv3bcAMr/s2gK7tS2GziihwahcKnNXk2LFjGDx4MBo0aKCwOwIAxMbGQiwWQygUwt3dHWfPvh3tNDExET4+Phg8eDA6dOiAyMhItcugVgNa1lFpkAoLmsKNWBsUNA1Y4lLx+t5x6TE91Qub39YD3rzSdLEJIYQQogFVDpwyj/8sGRjoQEDJf6v5ns3/Kgqc2oUCZzVJSkpCcHAwdu7cqTBwbt26FQKBAOvXr8fVq1fx9ddfw9LSEk+elIwEu2PHDlhbW+PevXt48+YNevXqhUOHDqlVBpUbUH4uist5BMiWYG8ucI4JnFsyX8dHrI2ZN0u9wFnNo8YRQggh5N1RbYGT1AgKnNqFAmcNUBQ43d3dMXnyZO51UVER7O3tMW/ePADAqVOn4OXlxb2/cOFCLFy4sNztvHnzBllZWdz077//qtaAMu6WG6Yig/7HBc6ooHEl848vUbMW3i0tAvdgR8hgXj3kS/n3VhRLRbgf2hhhYbNRVFSs6SITQgghREMocGo3CpzahQJnDSgbOPPy8mBgYCAXQseMGQNvb28AQEFBAVxdXfHixQsUFRVh8ODB2Lt3b7nbCQsLA2NMbqqwARXkIWuOg8Kw+VTqCFfJj1zg/CHYp+S9raMrVxnvCK+oYxBL9qF3QDymB87G8MCFcJdsxOrgz5Aa2gEHQj7AiMD5XL38dO5fTReZEEIIIRoiCzQ5OTmaLgpRICcnhwKnFqHAWQPKBs4HDx6AMYZTp07xlps1axbc3d2510lJSWjTpg1at26N6dOnV7idSl/hBPD94m+AMBEKpBbIkDZAntQKv4S8j/cDVnOhSizZh08CFpUEzsPfqlED756oQ9d5+13R9EVCiqaLTAghhBANyc/PR1paGjIzMzVdFKLAs2fPkJaWhsLCQrn3KHDWPgqcNaCygbOq1GlAHgsO45ugWfg+6KNyg5VHwDogzELnR0v73/d/qBU4v9zwh6aLTAghhBANKS4uxj///IObN2/i9evXyM3NpUkLppycHC5sPnz4UOGxo8BZ+yhw1oDKdKmtDqo2oAcZOSoHq/8FhgK/x1RbGbWV29xktQLnkoPXNF1kQgghhGhQXl4erl27hrS0NJq0bHr48CGKixWPt0GBs/ZR4KwBygYNmjJlCve6qKgIDRs25AYNqg6qNqDn2XloHKBKsNqL6at2VVv5tFnHiENqBc6x689WvFJCCCGE6LSioiKNX9WjiT8p6kZbGgXO2keBs5q8evUKqampSE1NBWMMUVFRSE1Nxd27dwGUPBZFKBRiw4YNSEtLw/jx42FpaYnHjx9XWxnUaUDjElIqDFVOIUm4++x1tZVPmw1celytwDlyzWlNF5kQQgghhKiJAmfto8BZTY4ePapwxFhfX19umeXLl6NRo0YQCARwd/8/9u47uokzbRs4++1Jsu953zWQRgqJ6Qk1jSWFNJIQspuEbOqSRkjPJqRtwo7qCGMwmN5779XYxoVum95tig3YNNsYXCiuuEm6vj8EwkYaWSKaGWt8/c6Zs2sHNDfS3Jr7nnnmebph165dfo3BlwTKKyqvs8nakOa/Zri+G78x3aeGM+ZQjtohExEREZGP2HAqjw2nhtxMAr06JlGyqZq/84yM0dYvl0or0X3YRq+azfen7JB8LoCIiIiI6i82nMpjw6khN5NA0Sk5ko3VrpMXZIy2/skvrsDQuKN4c/wWdBTXurwfjwxchzUHc9hsEhEREQUoNpzKY8OpITeTQFVWG14dneR6F2/qjrr/soZdKq2EJeoIng7biOeHb8bIdcdQXuX5IXQiIiIiqt/YcCqPDaeG3GwCXSipgD7iEB4btB5dB2/AoDWpKKmolilKIiIiIiJ1sOFUHhtODWECERERERFJY72sPDacGsIEIiIiIiKSxnpZeWw4NYQJREREREQkjfWy8thwaggTiIiIiIhIGutl5bHh1BAmEBERERGRNNbLymPDqSFMICIiIiIiaayXlceGU0OYQERERERE0lgvK48Np4YwgYiIiIiIpLFeVh4bTg1hAhERERERSWO9rDw2nBrCBCIiIiIiksZ6WXlsODWECUREREREJI31svLYcGoIE4iIiIiISBrrZeWx4dQQJhARERERkTTWy8pjw6khTCAiIiIiImmsl5XHhlNDmEBERERERNJYLyuPDaeGMIGIiIiIiKSxXlYeG04NYQIREREREUljvaw8NpwawgQiIiIiIpLGell5bDg1hAlERERERH/U5qN5+GrOTvSeuA1hcWnIL65QOyS/Yb2sPDacGsIEIiIiIqI/YmPUPBw2dwEsQTgrtsR4w6dYHPop0mZ9h8Slo1FwMkXtEP8Q1svKY8OpIUwgIiIiIrpZFRlJqLY0QZXYFFGmXrAY+mOMoR8+0A1HsBCDYCEGbYXVCBtiAvLS1A73prBeVh4bTg1hAhERERHRzSqa9Q5Kxbvwlm6Ms8GU2iaHfAtUXVE7ZJ+xXlYeG04NYQIRERER0c26NKwTJho/qbPZDBZi0FKIxoFNK9QO2Wesl5XHhlNDmEBEREREdLOODXwUb+rGedVwBgsx+GjEcrVD9hnrZeWx4dQQJhARERER3QyrzY4kU3c8Kiz2uuFspYtRO2yfsV5WHhtODWECEREREdHNWhT2FdoKEc6G8j3dSGSbW6FIbIaj5o7QG36t1XB2HrhW7ZB9xnpZeWw4NYQJREREREQ3a9PeQ+gkLEWwEIN+uhBYxcaAJajWNtzwlbPhfH74ZrVD9hnrZeWx4dQQJhARERER3bS9s/Ef/QAY9T9iu+lJl2YTliAUivegs7AUrYQovDd5u9oR+4z1svLYcGoIE4iIiIiIbkrZRWDQXag2B2GO8T2cE4PdNpywBKFYvAvv6kZiauIJtaP2Getl5bHh1BAmEBERERHdlEMrnA3lSMOX2GvuKtlwwhKEH8cvQVlltdpR+4z1svLYcGoIE4iIiIiIbkpatLOZ3Gp6Bm/qxsIuujaa1WITWC1NUGW1qR3xTWG9rDw2nBrCBCIiIiKim1JVDoS3BCxBsItB+Eo/EP31elwS74VddPzunDkYsAShauzjakd701gvK48Np4YwgYiIiIjopp3eBoS3ct7JXGZ8E5/rB+EHvR5xppev3+ncP1/tSG8a62XlseHUECYQEREREf0h1RXAjknSz2/G/K52hH8I62XlseHUECYQEREREfnFqq9dm83FfdSO6g9jvaw8NpwawgQiIiIiIr+w2RxDZ+f/E5jXG9g7C7AG3qy0N2K9rDw2nBrCBCIiIiIiksZ6WXlsODWECUREREREJI31svLYcGoIE4iIiIiISBrrZeWx4dQQJhARERERkTTWy8pjw6khTCAiIiIiImmsl5XHhlNDmEBERERERNJYLyuPDaeGMIGIiIiIiKSxXlYeG04NYQIREREREUljvaw8NpwawgQiIiIiIpLGell5bDg1hAlERERERCSN9bLy2HBqCBOIiIiIiEga62XlseHUECYQEREREZE01svKY8OpIUwgIiIiIiJprJeVx4ZTQ5hARERERETSWC8rjw2nhjCBiIiIiIiksV5WHhtODWECERERERFJY72sPDacGsIEIiIiIiKSxnpZeWw4NYQJREREREQkjfWy8thw1jNlZWV48MEH8dtvv/n8d5lARERERETSWC8rjw1nPWMwGPDBBx+w4SQiIiIi8jPWy8pjw1mPpKen45133sGcOXPYcBIRERER+RnrZeWx4fSTpKQkvPHGG7j33nvRqFEjrF692uXPTJw4EcHBwbjtttvQrVs37N69u9Z/7927N44fP86Gk4iIiIhIBqyXlceG00/i4uJgNBoRERHhtuFcunQpbr31VsyePRupqan4+uuv0aRJE+Tl5QEAIiMj8fvvvwMAG04iIiIiIhmwXlYeG04ZuGs4u3Xrhh9++MH5s81mw3333YehQ4cCAHQ6HZo3b47g4GDccccdCAoKQkhIiMf9VFRUoKioyLllZ2czgYiIiIiIJLDhVB4bThnc2HBWVlbiz3/+s0sT2rdvX/Tu3dvl73t7h9NisaBRo0YuGxOIiIiIiMgVG07lseGUwY0NZ05ODho1aoQdO3bU+nMDBgxAt27dXP6+tw0n73ASEREREXmPDafy2HDK4I82nDeLCUREREREJI31svLYcMrgjw6pvVlMICIiIiIiaayXlceGUwZSkwb179/f+bPNZsP999/vnDTIH5hARERERETSWC8rjw2nn5SUlCA5ORnJyclo1KgRRo8ejeTkZGRmZgJwLIty2223Ye7cuUhLS8M333yDJk2aIDc3128xMIGIiIiIiKSxXlYeG04/SUhIcDtj7Geffeb8MxMmTMCDDz6IW2+9Fd26dcOuXbv8GgMTiIiIiIhIGutl5bHh1BAmEBERERGRNNbLymPDqSFMICIiIiIiaayXlceGU0OYQERERERE0lgvK48Np4YwgUirbDY7Yg/moOfoRHSxrMWLIzZjePxRpGRdQubFUpRXWdUOkYiIiAIA62XlseHUECYQaZHNZseLwzcjWIjxuL0wfDPOXipTO1wiIiKqx1gvK48Np4YwgUiL/r1gn0tz2VKIQishyuX3bQyxKCyrUjtkIiIiqqdYLyuPDaeGMIFIayqqregiLK3VVD4mLMYA/W8SdzrXQFiZonbYREREVE+xXlYeG04NYQKR1mSczUUnYVmtpnKx8S301xskh9Y+M3Sj2mETERFRPcV6WXlsODWECURacyVpHP6um4DuujmINL2GIrEZbGJjzDD2cdtsthVW44ORq9UOm4iIiOop1svKY8OpIUwg0pydkxFv7IEcsQVgCXJuheI9eF4306XhHG74Cnunfqd21ERERFRPsV5WHhtODWECkeZUFMMmBtVqNq9t+WJzDDJ8j566KXhfNwIrTK/jong/MKW72lETERFRPcV6WXlsODWECUSaNPRBtw3njZv9WmO64ku1IyYiIqJ6ivWy8thwaggTiDRp1qteNZzO7ewBtSMmIiKieor1svLYcGoIE4g06cxO75vNhe+rHS0RERHVY6yXlceGU0OYQKRZu6YBA5t4aDYbA8v7AeU89omIiEga62XlseHUECYQaZrNBqQsATaHAXtmAonhwAYLcGglUHpB7eiIiIgoALBeVh4bTg1hAhERERERSWO9rDzNN5zx8fHYunWr8+eJEyfikUcewYcffohLly6pGJn/MYFI6yqrbbDb7bDa7Nh8LA8r92Uj9uA5xBw8h3OFV9QOj0iS3W5XOwQiIgLrZTVovuHs1KkTYmNjAQCHDh3CbbfdBr1ej6eeegr9+vVTOTr/YgKRViUdz8cb47ciWIjBIwPXocvAdQgWYly2z+fsUTtUolrOXCjFN/P3orU+Fh3FtTCtPoySimq1wyIiarBYLytP8w3n//7v/+L06dMAAIvFgnfffRcAsH//fjRr1kzFyPyPCURalJJ1Ga30sW4bTHfb4JhUtUMmAgAUlVfhySEbXY7RT2buUjs0IqIGi/Wy8jTfcDZt2hSpqY4CtHv37pg2bRoA4PTp0/if//kfNUPzOyYQadE7k7Z73WwGCzForY9RO2QiAMC8Haclj9PDZwvVDo+IqEFivaw8zTecb775Jnr16oVBgwbhlltuwdmzZwEA69atQ9u2bVWOzr+YQKQ1VpsdbQze3910bGvUDpsIAGCJOiJ5nEal5KgdHhFRg8R6WXmabzgzMzPx+uuvo0uXLpg5c6bz97/88gt+/PFHFSPzPyYQaU32pTI8JixyW7C3EyLc/r6lEK122EQAgKV7MiUbzvTcYrXDIyJqkFgvK0/zDWdDwgQirSmtqMZPJhM6CctcCvbZxvfxpm6cy+9fNc9TO2wiAMCVSit6jEhwOUa/X7hf7dCIiAJCzuUrCF2Tiv+uTMHgmFQMX3sUu04WYFtGPrZnFKCovMrn12S9rDzNN5z79+/HoUOHnD9HRkbirbfegl6vR2VlpYqR+R8TiLRoxcxwHDe3R3+9Ac8Ic/CObhSiTL0ASxAWGv9Zq5BvI6xGatIqtUMmcsovroBx9SE8OWQjXhyRgHEb01FZbVM7LCKiem/UumNo4cWjNJ/O2gWrzfulp1gvK0/zDWfXrl2xcuVKAMDJkyfxl7/8BR9++CHatGmDn3/+WeXo/IsJRFpUeSQasAS53WJNL+NVYSJaCNHoqwtFUvi7gJVLThAREQWy/ZmXfJq/of8i70eOsF5WnuYbzqCgIJw4cQIAMGzYMLz66qsAgG3btqF58+ZqhuZ3TCDSouyYYSgX73DbcOoNv+I3/QDEm15ChqkdPpmaqHa41IDZbHZszyhAVEoOzhVeUTscIqKA9fmc3T41nK103s9Qz3pZeZpvOP/6178iPT0dAPDKK69g7NixAByTCf3lL39RMzS/YwKR5tisOCG2x0rjP2ATazeb+82Po50QgX/rzYAlCFViU1hGjFI7YmqgMi+U4aWR15/XbK2PxfC1R9UOi4goID0bvsnHGepjvB5Wy3pZeZpvOHv06IG+ffti/vz5uOWWW5CRkQEASExMRHBwsLrB+RkTiDTncAQuiPfXajTtYhCWGd90zlI71/ie878dNXdEQUmF2lFTA/TOZPfrxW5IzVU7NCKigPN8+Gafms22xjivX5v1svI033AePHgQnTp1QlBQEAYOHOj8ff/+/fHhhx+qGJn/MYFIc2a87HYobYHYHG2F1egqLECZeFet/xaxk3eVSFmZF8okiyDOSEtE5Lsv5+7xqeEcu+G416/Nell5mm84pZSXl6OqyveplOszJhBpzpjOkhMG/VM3GqmmjrV+d1m8F5EHMtWOmhqYY+eLJYugL+bsUTs8IqKAI0Ye9rrZHBh92KfXZr2svAbTcO7btw8LFizAggULsH+/Nq84M4FIcxb9S7Lh3Gt63OV308W+KKngLLWkLLvdjueHux/+tXg3L4AQEfkqPP6oYzIgIbLOhjMsLs2n12a9rDzNN5x5eXl48cUX8ac//QlNmzZF06ZN8ac//QkvvfQS8vPz1Q7Pr5hApDlZeyQbzppbudgU88Q+SEzLUTtiaqC2ZxTgYVP8DWvD7eaam0RENyHhWB4eElah2Hw3zphbI098AEmm7vhOb3azDudun16b9bLyNN9wfvDBB+jatSvS0q5f/UhNTUXXrl3Rp08fFSPzPyYQadKwFpKNpl0MwkFTZ8SZXkLZtF5AYbba0VIDlltUjskJJzBoTSrWp+biYmkFFu3KxLSkEzieW6x2eEREAcNut2PhGMHtuX+o4ZtaDaclItmn12a9rDzNN5xBQUHYs8f1GZrdu3ejcePGKkQkHyYQaU7hWa/ucDq3mT3VjpgIALA1vQAdzLXveA6J9W3YFxFRQ2YPe8Dtub5YbIYOwgoECzFoL6zEqeQEn16X9bLyNN9w/t///R+Sk12vfBw4cAB//etfVYhIPkwg0pxzB31rOC1BQL73M9URyaGy2oYnQje4fdZox4kLaodHRFT/nT/s8Vz/lm4M+ujDccD8GJDLZzjrO803nL1798bzzz+PnJzrz3adPXsWL7zwAt566y0VI/M/JhBpTnUlMOR+3xrOzF1qR00N3LaMAsnJLUyrfZtNkYioQUoY6t05f1hLn1+a9bLyNN9wZmVl4dFHH8Utt9yCVq1aoVWrVrjlllvw+OOPIztbW897MYFIkyL7e99shrcEqivUjpgauO0eGk5zJBtOIqI6JY2o+5wfejdw1veVJ1gvK0/zDSfgePB4/fr1GD9+PMaPH48NGzYgOzsbX3/9tdqh+RUTiDTpciYwsEndJ56BTYGUpWpHS4Qqqw1/G+x+SO3uUxfVDo+IqP67eNLzuX/SU0DVlZt6adbLymsQDac7KSkp+H//7/+pHYZfMYFIszaGuDnhNAZCmwET/gas+dXxvCdRPbH9RAE6iWudjWYLXQzC44+qHRYRUeDYNxcIucP1/B/W3PGM501ivaw8NpwawgQiTcvYAER8CyzvBxxaAdi4viHVLzabHZuP5WFq4glsTMtFYVklZm49iR8W7ceUhAwUXqlSO0QiosBSWgAkhgNz/gHMeNlxgfnCCaAgA9g2Ftg5BSg+79NLsl5WHhtODWECERGpo/BKFXpP2Fpr+OyTQzaitT7W+XN7czzWp+aqHSoRUWBLGuEY5XTtjuegO4HDK73+66yXlceGU0OYQNSgFGYDl86oHQURAMASdURyoqCaWwdzPIrLeaeTiOimSC2XMvheoLzQq5dgvaw8zTacb7/9tsetR48ebDiJAlFBBjCz5/WTzJD7gHWmm548gMgfnghd71XDGSzEIDL5rNrhEhEFps1h0hMJHVrh1UuwXlaeZhvOfv36ebVpCROINKvsIhAnAKPaAyG3uz/RzOgJWHnniNTRscYEQXVtq/Zra0kuIiJFXM5y1AFSDefhVV69DOtl5Wm24WyImECkSdYqYHJ379bh9OEZDiJ/en38Vq+azXbGWFwqrVQ8PqvNjimJJ9BjZAK6Dt6A/yxLQfalMsXjICK6aVOelT7/D7kfqCj26mVYLyuPDaeGMIFIk46s9q7ZtAQ5Zq8jUsGq/Vl1NputhUisnGJRJT7dqkMu8TwVthGXy5RvfomIfJJ3tPajNDduIbcDR2O9fjnWy8pjw6khTCDSpE2h3jecCcPUjpYaqGqrDW0NsZLN5iTDJzgrtnSsKVdZqmhs5wqvoJXefWzTkk4oGgsRkU9KC4DwVp7P/Su/8uklWS8rjw2nhjCBSJNSlnjXbIbc6Zi5lkglYuRht01dH3147WO17KKicSUdz5dshH9dmqxoLEREPtk6pu7z/8HlPr0k62XlseHUECYQaVJVOTC2S90nnOGtgeoKtaOlBuxiaSVeHpVYq6F7VFiCVHOn68fp9JcUjyvrYhla6Nw3nBM2pSseDxGR16L6ez73z3nd5wkDWS8rjw2nhjCBSIuqrTaI8+KxxvQqqsSmnk88e2erHS41cJdLKzE1MQNfztoGMdSCAvP914/PsAeA7H2qxNV/8QGXZvPRkHXIL+ZFGiKqx3ZNkz7nbxp8UxeaWS8rjw2nhjCBSItmbDnpLJA7C0tRLkosi2IJAhb3UTtcaqCsNjvC4tLwkDGuVlP3mBiNAwvNQNIIoPi8avGVV1kRFpuGR0LWobU+Fp/P2YPjud7N6EhEpJqKYulRTtNeAGw2n1+S9bLy2HBqCBOItOj18VtqFfBjDZ85TzaF4j3IFlvBLjp+Tp3wL7XDpQZqWPxRyeckHzLGobzKqnaIRESB6cAi6QvN6Rt8fjmKvFDMAAAgAElEQVTWy8pjw6khTCDSop6jE10K+CRTd/ys16G1EIlgIQYv6mZgk+l5fKgfBpvNrnbI1MBUVtvQ3hzvcUmU+TtOqx0mEVFgihOkG85lfQG7b+d91svKY8OpIUwg0qJwN3eOHhJWufyupRCNYCEGS/dkqh0yNTAXSirqXIPTtPqw2mESEQWmlV96nr9h1dc+vRzrZeWx4dQQJhBpUVF5Fd4Yv7XOgv7a9vW8vWqHTA1MaXlVncflz0sOqB0mEVHgSVvj3Uz1WXu8fknWy8pjw6khTCDSqiqrDT1GJHjVcFqij6gdLjUwWzysc3lta6WPxeVSzghLROS1/fO9W4fbEgQkDvf6ZVkvK48Np4YwgUirCsuq8LDJ8zNy1zYW9aS0Lel1NZxr0EOYhsfNqzEpIQN2H583IiJqcGxWYFQH7xvOPTO8fmnWy8pjw1mPZGVl4YUXXkD79u3RuXNnLF++3Ke/zwQirVq8OxMthWg8q5uFTsJyj8V92jke/6SsymobHh+0zuNxGW96CUViM4w0fIEx64+rHTIRUf1WnOt9sxnWHLhyyeuXZr2sPDac9ci5c+eQnJwMADh//jzuu+8+lJaWev33mUCkVRuWTcRZsSVgCUKmubXHwj6dawuSCpKO56OVTvq43G9+3Fkc6Y2/odrq+9pxREQNRnUlMPQB9w3mkPuu//8xnYEz2316adbLymPDWY916dIFWVlZXv95JhBp0pkdsA9s4jy5FIjNJYv6h03xakdLDdg/J7qf3OofwgRsNj2HMMO3mGL8CEmm7og7fE7tcImI6rfNQ1ybzYFNHQ3m+UNAzgHA5vvFO9bLymPD6UdJSUl44403cO+996JRo0ZYvXq1y5+ZOHEigoODcdttt6Fbt27YvXu329fat28fOnbs6NP+mUCkSSu+cDnhfKQf5rawH7n2mNrRUgOVeaHM7TH5sS4Mn+jDXJb1+XVpsqzx5Fy+gn1nLqKovErW/RARycZmc0wGFN7Kcf6f9BRwNPYPvyzrZeWx4fSjuLg4GI1GREREuG04ly5diltvvRWzZ89Gamoqvv76azRp0gR5eXm1/tzFixfRoUMHbN/OIQJEmP13l4Yzy9wKPXTTXYr7Y+d57JM65mw75XI8vimMxQjDl24b0UcGroPN5v/Jg8oqq/H9wv1oeXV4b3tzPMZtTPf7foiIFGOzAZVlfns51svKY8MpE3cNZ7du3fDDDz84f7bZbLjvvvswdOhQ5+8qKirw3HPPYf78+XXuo6KiAkVFRc4tOzubCUSaUxBpcPsMR445GC2FKGcB384Yh8IrvJtD6li6J1NyhlqpIeCHzxb6PQ7dqoNu9xWZfNbv+yIiCkRsOJXHhlMmNzaclZWV+POf/+zShPbt2xe9e/cGANjtdvTp0wcWi8WrfVgsFjRq1MhlYwKRVlhtdrwxdBWyxVa1mk27GIQi8W7MNb6LzsJSBAsxMEceVjtcasBSsi57tWxPzW1jaq5fYyivsqKdMc7tvvpM2+nXfRERBSo2nMpjwymTGxvOnJwcNGrUCDt27Kj15wYMGIBu3boBALZu3Yo//elPeOSRR5zboUOHJPfBO5ykddsyChAsxKCrsBCTjB+jRLzb5U7nQfMj+H3ZAVRx1k9S0ftTdvjccPp7qOul0krJffUak+TXfRERBSo2nMpjwymTm2k4/ygmEGlN/OFzzoL5B33tobXFYjPEm17CZtNzOL/bdYIuIiW10vvWbAYLMVhzMMfvcfx97Ba3+xq0JtXv+yIiCkSsl5XHhlMmNzOk9o9iApHWXCqtRDtjHP6pG4Ny8Q5nsxlh+js6CCucxXRHYQX2bF2rdrjUQB3KLvS52WxjiEVZZbXfY9l+osBlWO2z4ZuQV1zu930Rkbwik8/incnb8Wz4Jvy6NBkn80vUDkkTWC8rjw2nTKQmDerfv7/zZ5vNhvvvv7/WpEF/BBOItOjnJQdwzNzB2WyeMbdBqxqTBV1vOpcjI/2o2uFSA7T5WJ7PDee6I+dli+dkfgkGrUnFN/P3YnLCCRSUlONA5iWk5vDcQFSfFZZVQYw8jMdD16OD2fV57EdC1iHrov9ma22oWC8rjw2nH5WUlCA5ORnJyclo1KgRRo8ejeTkZGRmZgJwLIty2223Ye7cuUhLS8M333yDJk2aIDfXPxNHMIFIa7ak5+NzIQSrTP/Al/oQfKEfBL3hF4Tqv8PXeotL47nY9BYKyyrVDpsamMKyKrT2YUjtvxfsVSy2hGN5eHLIRue+e45OxPHcYsX2T0Teqay24fnhm+v8/jBGSM/tQd5hvaw8Npx+lJCQ4HbW2M8++8z5ZyZMmIAHH3wQt956K7p164Zdu3b5bf9MINKaL+fuQT99qMsJ92e9DrAEId3cHl2FBdeXfjD1wo5FoWqHTQ3QiLVHPRaJLYRoXFsipb05HilZl2WPKbeoHA+ZXO+SPDN0E6o5yRZRvRJx4KzXF61+W5asdrgBjfWy8thwaggTiLTm7+HSJ9yD5kcASxCiTa8iWIhBWyECF8X7cSb8abXDpgbKaPoNKeZHUSHejqPmjvhJr0M7IcLl2H1NNxGfTN8uezxTEk9I5s/mY3my75+IvPfTkgM+DctfsS9b7ZADFutl5bHh1BAmEGnNJ+OkT7bTjB8CliBYxcZoKURivvEdwBKEnHGvqB02NUSJ4bCLQS7L9vyiF1yO3VZCFCYbPpItlPTcYliijuDFEdLD8yIOsFglqk+GxaXiDd04BAsxeFxYhO7CbI8N598Gb1A75IDFell5bDg1hAlEWjNj/jzpgtn0d8ASBLsYhB3Gv+EbvRk5YguUHYxUO2xqiAbf49JswhKEDPPDbo/fKGNPINN/j1Rck3AsD20NrsNoa26t9bE4X8hZaxuyovIqLNh5Gl/O2YM3J2xF7wlb8emMnfjnhK34et4ezN1+GucKr6gdZoNSsW4Q4k0vYZvpaefFq2JzM0QZX8XH+qFoJ6yqlcdtDLFqhxywWC8rjw2nhjCBSGsmLFyBjsJyl4L5CWEhroh3Xr+LpBuAYCEGL+hno6raqnbY1ADZLY3dNpw2sbHz2c2a227z34ANA/0eR4+RCXUOxRuz4bjf91vfncwvwch1xzBhaQySF5kwbtBP6CbMRXthOdoJq9E9bAN2ZOSrHaYi1h05j5ZeDNlsqYvB6PUN71hRRVU5EHoPbG5GSVz/LgnCK7opzs+ny0AuBXazWC8rjw2nhjCBSGu+nLUDv+j/i3/oJjhPsn/XTUSquZPzJFwlNkFXYaHzv8cfPqd22NQA2YY0d1skpru5w9lLN8lxByNjk19jyLl8RbJ5eCRkHX5bnoJtGQV+3WcgiEw+i1a6GIwyfOH8XJYa33BzIWANzJHangG0sKzKq2az5rY1veEdM4q7eEqy0ay5HTA/6vxc/rsiRe2oAxbrZeWx4dQQJhBpjW7VQTwmLEKx2AzzjW/jgPlRlxPwAuPbtYqjqYkn1A6bGiD77hlun+FMNz+Ml3TTnMdnH304zootHf89N9WvMRSVV6GNIdZt09B31i6UVzW8u/9XrlSgsyECr+kmOT+TUvEul+GJ17YWQjQKSrQ73HjJnkyfms1gIQb/WcbGRnbH13vVcJaLtyNYiEEny1oOi/8DWC8rjw2nhjCBSGsOZRfiY0M43taNwlpTD7ysm4KtpmdQLN6NM+bWGGb4Bi2F6FrF0fYGeAeH6oc9SwYjT3wARWIznBcfRLzpJWw2PQ+b2Bgnze1wTmxRu4A8s8PvMfyyNNlt03CtEe0zbSfSzjWcc0RStOM58DHGfs73fbPpOY8N1tiN6WqHLZspCRk+N5w/LNqvdtjad3iVVw1nkeUe/LTkAE7ml6gdcUBjvaw8NpwawgQiLUqJmoA3dePwgW7E9TtDliCcNLfDG7rxtQqjPtN2qh0uNXDL92ah7Q13GXvrxqJQvGFSoWEtHM9t+VlxeRW+mrcXLXTXn8O7sYF4NGQdLpRU+H3f9dHeiZ8jWIjByBrDaXeb/+axwZq55ZTaYcvm7KUynxvOqJQctcPWvpI8YGCTupvO7ePVjlQTWC8rjw2nhjCBSJNSo7DZ9CyKxbtdTr75YnO0EyLw5JANGLPhOK5UNrwhg1S//LY8xW3RHmL43nnc2gc2BVKWyhrH2A3HXRrfhjj03DazF17QzUQ//SDnkGe7GIR/64xunuGMQQdhpeaHHn89b6/XzeZ3C/bBarOrHXLDENXfc7M5op3aEWoG62XlseHUECYQadLMVz2ehH/QG/HzkgOqhHau8ArC4tLw8Yxd0EccwrHzxarEQfVHe3O828L9IWEVVpr+gYMzvgXOH5Y1hj2nL9bZSOgjtD05jtOOSThpbouyGrNaX9vOmx/Ev/Um53vysLASK/dlqR2xIsZvTEd7k/vlc7pY1uLfC/Zha3oB7HY2m4qa1cv9uW7VN4C1Su3oNIP1svLYcGoIE4g0p7SgziFGRsPP+Gz2bsVDO3OhFE+Erq9VqLU1xmH7CT5D2pC5G8Jac0vJuix7DL9L3GWtuY3X8HOKtVRXAoNcm03n3WYxCIuMbyHG+DKsYhPgxGa1I1bEqYJSvDVxm/N4eGboJqxPzVU7LLJWA8mLgMV9gMUfArunARV8XtPfWC8rjw2nhjCBSHOuXPb4XItNbIwXdTNgWi3vHSN3pIr63hO3KR4L1Q/pucUem7zPZilzYeSb+XUPmXzYFI+i8gZyx0RijVS326gOakcrO6vNjueHb3Y5JjqKa3GxtFLt8Ihkx3pZeWw4NYQJRJq06APJ4nC6sQ/aGmJVGcr6XLhrwXZt0/ozYOTejC0nPTZ5jw9ap8ixsWiXd0tfjN/UQO5yDmzqfcNpCQLKtX0OTTiWJ3lMzNqq3QmTiK5hvaw8NpwawgQiTSrKASY9DViCUCHejv3mxxFh+js+04fiFd1UJEz6XtFwKqqtOJJTiDfGb3FbsHW2rIWNk2w0SMv2ZNXZ5MUeOid7HBXVVjwzdFOdsXw1b6/ssdQLY7qw4axhxb5syWNiWPxRtcMjkh3rZeWx4dQQJhBplt0OjO/qLAiviHciT3zg6s+NgSuXFAlj0a5MPDbI8dxmC4mCLSwuTZFYqP4pKq9CB9H9pEHXtsW7MxWJ5fuF++tsOCdubiB3OHdORol4l+MZzbqazVm91I5WdpkXypzL5ty4JR7PVzs8ItmxXlYeG04NYQKRps14WaJIbOx41lNm2zMK6izgf1l6AFVWm+yxUP218+QFyZlqW+pikH2pTJE4Jm7OuP68prDSJZZW+tgG8QynzWaHuOoA2giRaC1E4hf9AGwzPYkz5jbIMD8MuxiEE+aH8IkuDHrjf3D8qPLPg6vBuPqwx+d7zasPoaqa32WkTayXlceGU0OYQKRpOya6bzjnv63I7t+bvL3OhlONyYuo/jieW4wBK1Ik737/otDyPecuX8EzQ9ahhRCNYGENugnz8b3OgDeEcXhOmIm3dKORuHGNY0ZMjZuWdMJjzr4sTEFXYYHz59b6WJwvuqJ22LIavf64V8/4tjXE4kJJhdrhEvkd62XlseHUECYQKcpaBVQrWIxUVzqmiq/ZbI7tAlw6rcjuHzK6X7Ou5tZzdKIisVD9s/lYHtoaPB8jLYQY7Dl1QdY4Siuq0U230M3+12CaoQ/KxLuu58/QYCBP20PApZ5l7a6bja2mp53vxVlzS/TRDUOwEIN/L9yndtiyWXvkvFfN5rXtX1O3qx0ykd+xXlYeG04NCfgEKsoBLp50/b2Nw3pUU1kKZO8FCrOBggwg+idg0lNAeMury5U0Bha+D1w4oVxMWbuBHZOA1ChFF8JurY+tszh7KmwjrJwwqEHqMTLBqwK+a+gGFMs4lHXKtAke999JWI41pp7ONSgx5hHZYqkPWumu5217YQW6C7PwjjAcl8R7USw2wwxjH3yrFyEafkSaqQM+1A3FiyMS1A5bNp/P3u1Tw9lSF6N2yER+F/D1cgBiw6khAZtAqdHA8DbXr7pP6Aqc2gKsMwJDH3Q0NfN6A+dS1I60Ydk5GQh74PrnEnK7h7Xr2juaUw17ZOA6rwq0SQkZaoequE1puXhlVCLaGmLQSucYlthGH4snh2zAhE3psNu13YTnXL7iUxH/zNBNsj3LOdz4VZ37byNE4qzYErAEIdfcHDiv3aHgzvdcmI1gYQ2ChRi0EqLwo16Pl4SpLu9LhPE19J2+Ve2wZfP2pG1sOKnBC9h6OYCx4dSQgEygg8u8n6o+7AGg8KzaETcMx9f5toyAJQjYP0/tqGX1XHjdy0wECzF4NnyT2qEqpqqyHN8Pm4KnhLlXi/noGgX+HLyjG4WOwnI8P3wzKqq1uzZpcXmVV3fAa26/LE2WJZYEY3ev9j/Z+PHVGZ/vALK1O4Q0WIjGp7rBXn8uL+hm4vysj9QOWzZjNnj3/Oa1rd/s3WqHTOR3AVkvBzg2nBoScAlkrQaGtfStqdkUqnbUDcOSj3xvODeGqB21rLoP867h7CSuVTXOimor8orL5V8LNH09Rpm/RkshyuU9eFKYizyz4+54qXgXwg1fY2D0EXnjUdlbE327c9TZIs9xctjcBd2FWXXuf5ThC8AShCqxKey52n2Oc4D+P+ilm+TTZ5No7q522LJZl+r9M5wthBgcPR8g9QSRDwKuXtYANpwaEnAJlH/c96ZmeT+1o24YZr7q+2eTGql21LL6cu5er4q0b+fLf7eovMqKlfuyERabhmV7snCl0oqo5Bx0G7LBGcfD5njM2XZKngCKcyGafvH4PnyiG1Lr+PhFHChPLPXErK2nfGpqnhyyUZY4MkwPIcLwWp37TzY/BliCUCHeDuyeLkss9cEJ80N4Rpjj9efSWojELMN7isVXbbUhOesy0s4pc97WrTro03HaZeA6nC8sVyQ2IqUEXL2sAWw4NSTgEqj0guP5TF+ami0j1Y66Ydg8xLfPZcqzsi2xUFZZjfk7z+CnJQcQFpuGUwXqPCv63YJ9bguyh4SVEPU/4BlhDh4NWYeMvGJZ48grLneZoKazZa1kwbhsT6bfY8hYN82LuyPRsInX8zvRJPNdo7w0IKo/MLOnY3Kr/OMor7Ji4a4z+HHxAYREp+J4rnyfTX5xhU/DasPjj8oSxy9mCzYan0PN4c03bqLhR+fnssX0DHBohSyx1AelA++BzvCr15/LD3oj/msYoEhsm4/l4ckhG5377jUmCekyHqMAMGBFSq1/bzshAl/oQ/CFPgTthAi374nWRydQwxNw9bIGsOHUkIBMoOX9vG9qRj7saFJJfmUXgfFPePe5DGwCHFktSxhF5VXoNSapVvHT1hiHxOP5suzPk7qGTHYT5mNyVJLscdzMHQp/mzTV80yo17ZCczPncXLI3MXvcThl7QFCHfsqEe9GmXgXykKD8eao2hM9tTHEYu2R87KFsXJfNlroXN+HnqMTa/383YJ9KK+S55nWnkNWY5GxN65NkON6nM5DlrkVYAnCeTEYo8zfAVXyrTtZXF6F35Yl45VRifh4xk4s25OFguIK/LY8Ba+MSsRH03diwc4zqLLKMxt52Yx/IFtshceFRTdcKFoFk+EndBSWOy+QfKEfhDjjS/hi9i5ZYqnpfGE52rlZaunZ8E2yznS96XA2goUYvK0bjS2mp1Em3unM0cvivfhN/zseu+G96jVG/u81IiUFZL0c4NhwakhAJlB5ETCxW91NzfBWwGX/36khD8oLgXlvedd0hjYDSgv8HsL4jelui+YeIxP8vq+63HhnwN3WVliN/GJ51ybtYI73qeFsIfh/lslxS+u+k9dKiEKl2NR5jOwy/c3vcTjNfRMnze3wiT4MLYRotBKi0Es3EZ2E5Whxw52+p2Veuia38ApMqw/hncnbMWBFCpKzLgMAMvKKEXfonOx3wL+Ztxcf64Z6/Gz+JYTjqLkDOgvL8ExonGyxLNh5xuvjtN/s3fLMZnx6G6wDb0e+2ByjDJ/jHd0o/KYfgMOmzigWm2G/6THsMz+BU+Y2iDG+go7CMuzPvOT/OG4wacMRtBCi0UVYipY3HKOJR3Nl2+/SBVMxztAXdvHqsjg3fJeXiXfhBWEGzPofnRctPpi6Q7Z4iNQQkPVygGPDqSEBm0A2G7DWAITcId3QzHlD7SgbJmsVsOwz75rOXdP8vvv3pmyXLFCzLsqzrISU47nFeNhUd7M3duNx2WI4c6HUp2bz2l09fztXeMXljlHN7SlhHkYbPnMeG4XiPSgyN/N7HNeUDWqOJ4V5eE83EpMMnyDN3BHlomMZnzzxAZgMP9WK79h5eZs+NZ3KL0E3YX4dx8UafKEPQbDgWMJGDhdKKnw+VpPkGrmQtRt5097GGXMbbDI9jw90I2rtt5OwHG2F1XjYFI/le7PkiaGmDSHYYO6BXPHBqxM3NcFpU2tMM/ZBb91YrIpcJduup1s+c9to1twEw38wwvAl3taNRndhJtYczJEtHiI1BGy9HMDYcGpIwCdQTor0SXByd+D0NrUjbJhyj3jXcCYN9/uuv5y7x6UobSlE4y3DeBSdOuD3/dUlOesyPpm5Cw8JK/GlPgQjDV/gB70RbYRIZ3zCyoOy7X9K4gmfi/ifFvv/fbLb7eiv16GnbkqtJqaDsAJxppdhu6GgPW9+AOdDH/Z7HNcsH9IX6009nPs7ZW6HycaPMcX4EbLMrQFLEH43/H71ju8anCuUbwhpffD+CPfP4rnb5BhyDQDD4tJ8PlaHr5Xnudaa3hy/VXL/O08q8MjG9B51fpcWWFrAWl0ly+4LLA9evZN5p3MIeol4d639DzT8gC/1AzHX+C5eEGbKEgeRmgK+Xg5AbDg1JKATKOcAsGEgMO5xD88KNgVONJw1DuuNyjLHGqh1NZznUvy+63VHak/h/4k+zLlgPSxBwKSnHZPFKKgy7yTKLXfW+refMD/kvKuUlLhetn1P9bHh7Dk6Ubbho13FaIwzfIr9psdwxNwZF833IV9sLnl8LB3zuyxxAMDGsV8793PU3AFHzR2wyfQ8PtGHoaUQjYXGf+KYuQOChRh8Okzb68UCQErWZbTRu3+G88bNvPqwLDF8Nc+7WZ1rbmGx8ufy6PXu16FsZ4zD5bJK+XZsrXZ8X3lz8c4ShEvjX5QljOqQu1Ao3oP3dcPRVz8YLYRotBCi8Zl+MLLMrWETG+N53UwMMXyHJcbe6GWZL0scRGoK6Ho5QLHh1JCATaBNoV6fhDGzp9rRKs9uB/KOApfOqBfDlpGeP5dY+ZqJifHJeEgfha7CQpSJd7nue3Qn2WbIvdGJlRbYJd6DSNNreF03HrA0Bg4ul2X/mRfKfCrgHw1Zh7xieZY0mLg5A92F2XhGmIUIw6s4aW4jeXxkmlvjlZGbZYkDAC5O6glYgmAVa896bRMb42e9Dq2FSJw2t8EHuuHI3zpHtjjqkz2nLnp1jGTINCvqkl2ZPjecIxS4w5lXXI4nQje47Fv2ZnfvLO/Pc9e2U/6frMc+tgsmGT5x+/4/p5uF4fov0UlYjixza3yuH4SHdatxpVKeCa6I1BKw9XIAY8OpIQGZQHlpvp2AB92ldsTKOpUEjHvs+r9/Vi/g0ml1YklZAsx4BRjTGZj/NrDiS2DNL8AJ+RoJVBQD4x5FoXgvTntoaHBcnmGBNV1OjvJ4bFaLTa4vAzKms+PZZD/bmp7vcxH/23L/33kGAJvNDnPkYbQWotBCiEZvYbTke3PA/Dh+XZosSxwAYJ/zhuS+s8yt0UKIxmzje0DI7UClOsvqKK3wShVaenF8nJZpmaHKahte0M306Vgdtf6YLLHc6MyFUvy6LBndhmxArzFJmLfjtDwTFtU0903fG85VX/s/jv0L8KZunORn8LwwA4fMj2CF6Q1cW1pn4uYM/8dBpKKArJcDHBtODQnIBKrrztmN28RuakesnKJzwOB73LwHTzrueirNWu0Y0jz/bcfw5oFNgYXvOeKUy+7p3h0XKUvki+Gqk6GP+nasluT5PYafl+z3ueHsbFnr9zgAx3OctZesWYOT5nZu34uJpr6yroGJvbM9fhbv60ZgibE3MPV5+WKoR6qtNq+HXz8zdJM8S5LkpaFabIKXhMleH6sJx/yfM/XGvN6+N5wLP/B7GOVVVnQVFkh+Bh/owvGebmSt3/19HJdFIW0JyHo5wLHh1JCATKAdE307AR9YoHbEytkySvp9OL1V2VgOrwRGPOQ+ltC7gey98uw38vu6j4mBTYHCs/Ls/6ryKqvH5xNdtrDmQLX/l0f598J9PjecbfX+XxYFALamF7js63P9oFpLocAShJPmdpgev1uWGJxKLzjuXnr4TMrEO2Ud+l1fVFtt6Dd7d93HhRCBz3WOmWrjDvn/olF5rAE/6A1eH6fPCrMQf0jePFbVvjm+N5xbRvs9jCV7fB/q3HM0G07SloCslwMcG04NCcgEOhbn3Yl3dEdgzwy1o1VGdQWQshSY8pz0+xE3QLl4cg44mjpPn8/ge2VZhxNJI+o+NjYN9v9+b7D71EXsNT0hGYNNbIxKsQkuivc5frfeLEsc05J8n6X2sRB5hhsv3u2+cH1VNxnzjO9ivakHhhq+QWdhKXqMTEBekTzPkgIAon707ntk7GPyxVBPRKXkeHVc9NJNAixBCDH8gBlbTvo9jmmDvvXpOH1NmIgj6Sf8Hke9YbMCUz18p7vbZBg98tNi30dJjN0g31JPRGoIyHo5wLHh1JCATKCF73s+4U59ESi7qM4QUjWU5AMT/lZ3ITLoTsefVYK3xfz2Cf7fd3EuMPRB6X3unOL/fbqRmlOEn/SCV++DzdIYSJdnptrLZZU+F4uWqCOyxHL4bKFPcfy6TL5nON0OPZfaZL4brrZvF3h3F/w9neNiTpF4Dw5kZPs9jl4674fSthKi8JiwEDiz0+9x1Cu5qd4fpwvfkyWE9yZLr20stRVdkWeJFiK1BGS9HODYcGpIQCbQiLZ13BV0Jk0AACAASURBVJHoIt9wzfoo+mfvC5K9s+WPx24H5r/jXTzxOnli2DHZwz718uzTjX+FL6u1YPoZcxsUSAyztc5+Q7Y4XhqR4FOxWChjsdh31i6v42hvjpcniMtZvt01ypN/JlQ1/WvaDq8+j1DDv6+/J2f3+z2Ox4TFXh8bnYWl+JswF4hVcOSGGux2wNLYu+N0yH3Alct+D+Gj6Tt9bji3ZcgweqUuFcXAkdXAkQjH/yfyo4CslwMcG04NCcgEmtmz7hPvsGCgokTtSJVRVwNec9s9Xd5YDq0AxvkwUc7hlfLEcSxeep9hzYF8ZYZ7XYg2Y6epm3PfH+vDJOMqH/ygbHFkXihDCy8LxTY6eZ7fBIDDZy+jjSHW66L1IVOcPIEUnfOt4TyZKE8c9cQ/J27z4vNYgw2m5wFLEGyWJv4fulmSh+7CbI8xdBSW4ye9HgmmZ3FZvBdf6S2oWi7DrKz1SfrGOo9PW42LWnLMWRASnepzw5mS5f/G16O0NcCQ+2s03/cDadHKxlCfnNoCzHndsR721Occ52b6QwKyXg5wbDg1JCATKNXzUhPObedktSNVxuhO3r0fck+Uk7HR+yvxliBg+kuAVaY7aVXlwLAW0vue+pw8+63BarOjryEMjwhLsNH0AmxiY+gMvyLD/LDbmAqGdpY1nu0Z3i2P8ukseSbrqay24dGQdT4VrZ1kmi0XxblAyB1e5k0ToND/w0friyuVVq8vArypGwdYghBrfhXV/p6ltrIU3+lNHvf/X8NvtT6bMvEuFCev9m8c9c2Erh6Pz72mJ/CVfiCqxSayXVTMyCtBW2Oc13n77LBNfo/BnYullRi3MR39Z6xH5UA36y2H3i3PPAE1lFZUI1fOZ81vRuZO999v++erHVlAC8h6OcCx4dSQgEyg7H11T0hzrcFqCFf1Vn3tXeG8Y5K8cSyQGEY7sAlgufZ5NQbCWwIJQ+W/A52xwfMspAXpsu4+bl9GrSLsKWEeeghT8ZNe5xKLVWyMQyvDZI0HAPSrDtVZLO47c0mWfa89ct7nuySdRJkazoRhbo+JmsOfnduqb+SJoZ7IyCvx6TOZavgQ7YWVyLro/7U4V47sj2BhjftjQVju/mLN3ll+j6PeKMjw+J2eb26O9sJKBAsxiDT1gt0S5BguLoOk4/l4ZVQigoUYtNLFoPvQjWipc99snsiXf3RRXnE5ug/bhGAhBjrDr9Lvk0wTB5ZVVmPAihRnI/7SyARsri9L9Cz6l/v3YmwXtSMLaAFZLwc4NpwaEpAJtOxT7++ihTYDrshTQNcbiz/07r1YL8obx3jpGVlxORs4d1C5SYtsVsed8DGdpWM6f0jWEHRLpJ97+k5vRrL5URSJ92CPuSvSTQ+h6EqlrPFc883cPZJxybX+JgAskZih1tP2j3Fb5AlmWV/J46JabIxqsQnyxQewedIPQLUyn4taSiuq0Vrv/TDna5sck8KErnY/eVEP3XQcN7d3/5nJMfFYfRH5g8fv9M2m59BCiEawEIP+egP2mbviQon/l1ZyytqN0kWfoXLs48DYR1G04kdErF6B+TPHImrBOOzbvw92hSbrGxKb5jw+hhk8XHSV6ULrD4tcZ+5ta4jD0fP1oJbydN6rLFM7uoAVkPVygGPDqSEBmUATn/S+4bQEAQeXqR2xvDwthXLjnUY5J1PydKd1WAvHXU2bDIvF36iq3PHsiqf3YmwX2WcxDotL87p4f1hYiSW7M2WN5xq73Y5WEg3G4Jg02fZ75kKp18+RXtt2nbogTzCbpZ+lhSUIy4xvIliIQWt9rLxLs0i5chnI2i3LEhfuCCsP+vS5tBTkec5389E8l329qxuJHrrpsImuw/XtliDHXUCtuvo8vNXNv71EvBtf6i0YbvgKwUIMBhh+w9u60Yg4INPw7y0jvTjPNFZsFvA3xm9FWyECfXThyDS3ko7n4im/7zu3qNzt3d1gIQam1Yf9vj+fLXzP/fsxupPakQW0gKyXAxwbTg0JyARa/plvDafWh9XG/O79ezHoDuDsPnniyEurPWmDu23jIHn2XdOOSZ5jGHwvcEr+RcnTc4slhwe6274fv1z2mK5JOJbn0nT2GJGAonJ5lzK4NgTOm23xrjPyBVJ0zjF5lMQxMtX4oTOOHSdkanprqihxzJ4c2uyGWJo4LuRUydv0Rnu5Due17c0J8tx5ttrseHLIxlr7mmt8F+fFYJwyu06OZg9rru3lr64+nz/f8A5OmB9y/rtzxJaYa3wXG00vINf8ID7QjcB205N4RpiDuEMyXKQoyvHuMRZLkOPZwRJ5h5ZuSc9HW/0atBCi8axulnQsM16RZf8pWZclc+PLuXtk2ae3dp68gMETp6Pa0sT1/dgzU9XYAl1A1ssBjg2nhgRkAp3Z6X2DNfheoDyA/m03o6IEPk3Ws+Qj+WLJS/NYyCPsAaBaxiFfgOe7mxtClBvWC+DZkEgECzHoJszHMMM3mG7sg376UOcwuJqbWf8jkHNA1ngy8opx7HwxKqqsSMm6hOHxR/H78hSs2p+NimqrrPsGgC4DvZ806IOpO+QNJu+o22O1SmyKl3VTESzEoJU+Vt4JQSrLrg6brCN/Z/aSLwbA+WyeN1sLQb7nfAHHWq1Phzqei3tBNwNWd8/V1twUmnFaFcs+AyxB+M0wAMHCGryuG4/3dCOQbH7E7Xsxz/IRyqtkyOMDC7w/v1iCgAML/R/DVacKStHHMBJRpl7YYXoKy4xvSMex9GNZYiirrEYnca3b/Ji4Wb077ttPFDiHx3+qH4J95idQId6BkpGPyTJ7cUMTkPVygGPDqSEBmUCntng42dUo3EKbNZxp0U/v8L7plHNYTdbeuvcv9zDBBe9K77v4vLz7vsG+cR/CqP8JleLt2Gd+AitNryPN3BEbTS+gtRBZo1CJRqq5k2zrkh49X4TXxm65PiTy6nCwh03xEFYexKJdZxCVkoOyympZ9g8AhVeqJIehSW1nLvh/YhqnylJgx0RgVAfn8VEgNscPeqNz//9dcVC+/QPAyq+8L+LnyLNOa7XV5vXn0cYQK//6inY7qsd1RZKpO9IlZnSutWl4BmFcOgNYgrDE2Nv5GeglJsixiUGoGtRMnscWUiN9aziPRPg/hqvWzB3hMrza3XBrWIJknal+etJJl/x4NnwTLpVWIvtSGbZlFCg+HP9DifVSXx8v07PwDUxA1ssBjg2nhgRkAp3dL32ii/jWMS38/nlA2UW1I1VWVfnVYXn3ei4G5r4pXwxx//W871HtHRP6yOnQCuX/3RKqxj+Jy+Z78Z5uZK0C4Fu9iF/1/7368xrMM16d4Xf1v/0eQ0W1Fd0Gb/CqoehsWSvbENLI5LM+NZvBQgwmJch0tyBrj8uyOcXzP8b383aivTkeT4dtxNgN6f5f+qOmknzfinhLkGzLGjwb7t1Q5zaGWPmHGJ8/5P37MbCJ9r/nF/dBuXgHnhTmIViIQbTpVcn3I9f8gOOCrL9VlXs/pHZYsHwT01irUDjIw3JXNbdJTwEVxfLEcdXaI+fx2ezdeGP8VoTFpeHspSv4ackB54W11vpYmFYfhs2mzLBvT8tOzd9xWt7vswYgIOvlAMeGU0MCNoGkJg5K36B2ZOopLwTCpSZPuLY1BtLXyxfDtBc873/fXPn2XVOccHU5lhrFhxp3Qha8iwGG39wWACH67zHN2AfrTD2w0PhPJJq6yzLcOe7QOZ+avMcGrUdltf8LE1+fEwwWYjBhkwxL19hsjkmj3B2fx9f5f39Szh30veEcI89arQt3nfH6M3l70jZZYnDy9X3R+Hd+9Zr/wCo2xkDDDwgWYjDb+L7ke1ElNga2jvF/EJ4u8tb8nh36IHB6q//3f03+MbcxHDN3wGJjb8SYXkHeoLZA0gjHxFsK2nfmIl4ckeA2Z2ZsOalIDP+ctM1j7n47X6b5GxqIgK2XAxgbTg0J2ATKPw6Me8z15BP2gLwzsdZnc/7huTAb9xhweJW8MUzwsEh5isKzBV86Axxc7rjir9LEIrZFH+IhYZXLif8t3ViUirUXKs8TH8DeIS/7PYYpiSd8bvQ2puX6PY7jucU+x5GeK8MdirP7pI/RiO+u/pn9QGK4Y0ieXBOgVJb53nCG3CFPLAAmJWR4/blY5bxjY7e7/26X2mRe3khNpRXVSA99HBMMn0Kv/wXBQgxe001CtehmQhjL1dlsD8nwHX9mh/T7H94KCL37+s8ze8r32ETpBdhrrK1sFRvjF71Q69h8Nmw9zhVekWf/EjYfy/O4tNAroxIVicObtY7lfP5a6wK2Xg5gbDg1JKATKElimvYpz6odmfIunqy7MBvVUf7hZ/E69/ue+apjQpxNgx1Xny+dljeO+qC8CKWWe9BSiHI56e8yd3P7PiWZn/d7GFEehrK2FSIwyvAF1ph6YqzxM3QT5iNYiMHw+KN+j2PZniyfG85pSTLcGcj20HCu+gaI+U/t34U2k+fOZ9kl3xtOS2P/x3HVxM3eNZxPhCpwRzF7r+Nu2Y3/dpfvlZ7yx6KiyQkncNrcGutNL6LC3BTv60YgWIjB93oTcsUb358gHDZ3cTyb7G/VlcDwNl4fp8VTZZzkasUXzv3MN77j9hj9fI6yM8W+Pv768/G9dJOx3vQiSsW7kGlujaGGb9AtVLmRE8v2Znlcfmpa0gnFYtGagK6XAxQbTg0J6ASaKf0sC4py1I5OWae3elcMyDHcqqaSfNe7E2EPuK7RObApkLxI3ljUdmY7phk/RHthZa0TfishSvLzybW08HsYBSUVLkVHP30odpm7oUS8u9b+L4n3oaduCoav9X/DGX/Yt6G9wYJjqRa/s9mcy024bAlDpe/iVFf6Nw5r9U00nEGOofMyGLQm1avPZNxGGYY532j39NrPDIbeDSSEAWOvzc7aGFjwDlDs/zvx9clH42Idw2Svvg/l4h2YavwI7+hG4T3dCKwzvgj71Vl8z4vBOLQqXL5gUpb6dJxmn5RpTd+KElxZ0g9WS1N0u/pc641bS10MCq/Iu8TTNVU1Jt16RpiDIvEe1wuJ479SJBYAWLw702P+RiafVSwWrQnoejlAseHUkIBOoHm93Z/sGsJEEje6crn2sCapbVlf+WOpKAZ2TXUMT0wYChyLcx9LaDPFn7NR1MVTzjsSNdfjfEE3w1kk3ridGfK4LKF0slyfwv9rvUV6VkdLENabXpSlKKmotqKrl5MXXdueC9/s9zgAAGe2Oy6E1Py3r/nFsUnlzskE/8dxYwx1bUMfkG3SrQ2puR4/i/bmeITFpsk7nBYACjLg9m7mkPsdS1wVpMs/03U98d/BwySPBevVHC4X78BZcwucihwi36MD1uq6n8+/YZu2NEKWUDYdzUVbYxw6Csucx+a7upGYYPwUwwzf4GlhLoKFGFws9fMFIglL92Q6JwlqK6zGUMM3zs/m2mYfdLdiNcnYDemSOdzZslaeZXMaiICulwMUG04NCegESlni/mS38H21I1NHYnjdhcB6Ufm4NgyUjufwSuXjUdAnAye4nPSnG/tIvh850aGyxNGzxjqLh81dPB4jFZY7ZFuT82D2ZTw/fLPXDeewOP/faXUqL3RMYrV1jGOiGgCI+U36vZFjMpScFN8azoRh/o/hKpvNjn6zd7t8BuHxR3EyvwSlFfItmVOLp+8xjX9f3OhQaHfJ96LmRSub2Njxc+T38gSSKj0qw92WKz6IL2fv9HsYVVaby0Wrxca3au27UmwKy5BBft+3O+slLtKMMnzh+r6c3a9ITNtPFEh+n8rxbH5DEtD1coBiw6khAZ1AdjsQO6D2LHlTn1N8rcV6xVOxFnqPOs9Obg6TjiltjfLxKChil+vV5g2mF6Tfj0z/F2lA7efzpCYcqXXn5KB8EzzZbHbsz7yE3acuospqg91ux6h1x9zc3dyk2HICTlKTo4zqIN9yPhsHeVfIbxoizxqLNVRZbVi2NwtfzduLHxcfwOZjMk2Y5Imn7wsZj8t6qcbSPYViM6SZO2K96QXkm5s7G85r/xthfA1Jpu6OSbH8bZ3J62azSmyKf+tNGLH2mN/D2HP6Yq3viE/07o+VUvFuoFTm5XsAfDTD/bqXjwhLat/lDFXuDicAfDl3j0tMwkqZ1xRuAAK6Xg5QbDg1RBMJdDnTMftq5i61I1GX1epYB3Pg7a4n4eFtgCOR6sRVkF77osC1bVgLoErZ2QSVlpJ5yeXEv+iGK/LXtnLLXbINMa6y2vDd6EUIFmKQbm5fd+E44xVZ4pBUeBYHp3yBL3QheFs3CnPDvoftlIzLK3iSMKz28TqshfzfLYVngXAPk7JMfU7e/dcnuUckLpg1A65cUjs6ZU3v4XI3U2o7Zw5GOyECWfEyPKefNMKrZjPJ9Ax66qbgCTEKuUXlfg/jYPZl5/doCyEKRv1P+N3wOwYYfnM02zXjidf5ff836iGxDEqwEINisZkzlssRv8keS01VVhsW7crEJzN3od/s3Yg4kA27SjO1a4km6uUAw4ZTQ5hAGmGzAWO6eC4IBt0JpEWrE9/eWcCgGsuADH0QOKnMVPFqenfydpdCpLswC1Y3dxnjTPI2eecXfIt/6cLxH/2AuovHEW3kCyRtjaOhDXsAGNXeMQR+TGfXGAbfq96zepczgX1zHEM45VrE3p2to900WncDeTIOLa6PbhypEXJ7w7u7CQAZm7xqNmFxjEzoJCzH6LlL/R/H3ll17t8uBkHQ/YJf9f/F6ZiR/o8BgN1ux0sjHU3eJ7owl+/WIYbvrse09BNZYqjp2/n73DabT+vmolhshtPmthhi+BadxDgcyZFnsi9SDutl5bHh1BAmkEbsnOzdkKfB9/p/tk1vlV5wzHR4ZLWyRbyK2pvjXYqREYYv3d+hEFs4JueQgc1mR0/jbAQLjllyqz1MGuS8qyeHQyu8O06vbVvkKVzrtVNbgMUfApOeBlZ/71hzuCHKPwZsGQXsmOi4A9wQHVzmU748JcyDfrkM61BvG+db3kb96P8Yrko7V4RBlt/dNnothGicMD/kmBRtrUG2GADHusId3Hy/15wgrub21bwGuj64hrBeVh4bTg1hAmnElOe8LwYSh6sdbYPxsCnOpfDYanpa8rO5fFqe52wStlyfNKiVEIUqsWndx4lVhmUFblwyp64t9nf/x1AHu92OxOP5GBh9BKPWHcOpAhnWNSTyRmq08w7nFtPTuCzeK5krGeaHESzItOxF2hrf8nbwPY4ZheVQWYrJxk8lh7LOMr5f44LVKHliAPDdAvd3N4OFaLe/fzREubU4SR6sl5XHhlNDmEAaUHoBCLnD+2JA44ul1yfPD9/kUnhEml5z+7lYxSZYsFGeq+AL5s+oFUOM6RXPx8iIdv4Pwmb1rWi1BDmezVaQ3W7Hj4sP1HqvWutjuXYdqaO6wrlW7r/04Rhr/MxtnlSJTdFXPwTvGcejyirDxFLH1/qeu9vG+j8OAFj1LRYZ/ynZcK42/f16DCG3yzYs/7FB6yViWIOuwgKX3/cakyRLHKQc1svKY8NZj6xZswbt2rVDmzZtMGPGDJ//PhNIA7aM8q0QmPai2hE3GB9O3+FSeHyhC3H7XNZ+8+PQyTST4OGlYq0YugnzkWF+WPoY2Tpaljh8Ok5n9ZLnLqsHUmtRdrasxZVKrl9Hyjp2vhil4p2wi0F4TFiMFkI0xhn7ovDqhDRl4p1IMD2L/+r/gznG91A+/ll5AvG0Pq3UNucN/8dRmA0MbIJC8V50FJa7nR22TLyrdhzJi/wfB4CeoxPRUojGB7oR+FQ/BA8JqxAsxOBJYR5sYmMkmbrjbzUaz4W7zsgSBymH9bLy2HDWE9XV1Wjbti3Onj2LkpIStGvXDhcu+DYV+P9n77zDmrr+Py6/tlK1BRS1btx+VVytYK2rttW6R7Xar62jaq1WbR3VEAJhubc468CJVRw4EPcCxS0bUVSWMmQrmyTv3x+3uRKSQNJvzr25yXk9z32eEqjnnXPPuffzPuNzaAcyAY5p3hOo9To2nW/FZsOem/EqI9/TxW7IkDbReF/E4j+wIjDG8CIUCmBjV8wSu6oEZy1Fp7DKeTrk5ZM5edUHri0nd4C8pmzFmq7zzrxkMHY6HqF15uT6k9ec66GYNw+DzrJ9YqzTGrYtthadxKciXzQXncY3TtvJzyr6z9LfcPqOM7yOS27svx/i0gM9RXvfJWNz8sED18/UdRBKlBewZRGSpS3ZcnKlDTBbLMEmyUT2s1DXrugkOoLN+w4R0UDhFhovcw81nEbCrVu3MGrUKPbnP/74A4cO6fdgox3IBLi6XL9AYJsZHbHAM5N97qqYlmFO3hrvSbG0Dj4V+SLqJYFMhm9SATdm2d1OyXiMcNqIIU6b4C2ZhKL1nwH39wCPDgCZz8knlNLFcO4lMDOiIzP239dqOO/Fc3eOHoUCAEV+M9h+cdWlL5pr2B+4wXkS8zckE8LFnNbfcD67Zngdh35QKUMmtcYD18/w0PVTJlFQRQ2rWgNlxYbXkf5Y43eWSa0hq7B6pfjkPMOXT+EFGi9zDzWcBuLGjRsYNmwYGjZsiGrVqsHf31/tbzZv3gw7OztYWlrC0dERd+/eZX939OhRzJ49m/151apVWL16tV4aaAcyAaJP6h8MmEmWWD6JfpWr0bjslIxn70O2tBGiXewhFv+BL5ZfISOkJJ+ZuayqTaztAKQTmGEtj1e9yjVs6EzsLNIqkcvxw8bzWg1ndgFP2Z0p5supuSr944JLfwxz8kYbkT8GOm2Fv2QQ/hCLsMn5JxR5NCZjrgCgKFf/d0yUejzzP3PJTXt5p+YAS98lVVKs6wgkPzC8BgAIFOleD2EEjqmh8AKNl7mHGk4DERgYCIlEghMnTmg0nIcPH0b16tXh4+OD6Oho/PLLL7CxsUF6ejoAajgp/6BvBkE3K+Z4CgpRPM9EaTUvY0SrsVg8H0OdNqokp8krIrRn8fTvKvf/lWtzze1iay8y5Ss5PqPydrn5c7Lla+FNYgQ2L/ld474w5ZWYSQdpKBzz6GCVz/IE19awE53BcNEGcplh06L0f8cc/N7wOnKTmTOcNZSnKPffqVI7TFqxHw8Tsw2vAQAuSnWvh4CFZDRQOIfGy9xDDScBNBlOR0dHFUMpl8vRqFEjLF++HIDmJbW+vvptkKcdyAQoyAI8q5g5qnhdcuNbtcmzIvCxRuMyQ+yG1+X2cca4dsRXTn/BThQAzzPRZMSUFgL7RgBu1rjr6lB5ltr0x2Q0AMDb10wGXG1lr2wF3PIGku5W/W8ZiKLiUgyR/KXVaNqJAtBrxRXI5YT2tVIo2niTBrhVcWaumxVai07CThSAlecI9d2iPMCzrn7vmN3fktGSFg0cHFtl+Q9dP0Vn9wt4Q2IQ702a7vWw9QvDl0/hBRovcw81nASoaDhLSkrw3nvvqZnQSZMmYcSIEQCYpEGtW7fWK2lQcXEx8vLy2Cs5OZl2IFMgYKF+wcCjA3wrNnn2h8SrGZc+TrtRouEMzOeubdFcdBoDSaXOP+fMlvXKtUXlGWpTI8hoUHJzg25t9NB/OclS6xtwqVKz2VIcgMAIMkcrUChVcuLXSvtJsrTlu2RCzmfJGCwAuCDR7x1zQ7/VVnpxd4dOGno57cHfdxPJaLjspVZemdQG8ooZyHcPIlM+hXOo4eQeajgJUNFwvnr1CtWqVUNISIjK3y1atAiOjo7sz6dOnUKbNm3QqlUr/PXXX1WW4+bmhmrVqqldtAMJnLwU3QMBz7p0DycH/HbwoXqCD8kUrfdlvHgVvl573fBCsuN1bxtLGpDLUKsk7rLueu5sJ6sFwPwd2s3mRPEShK8fQ26pIoVSFXeYLLTnXb7CGKc1cBTtxzSxB0JduwFuVnB1nqvSZi9Gp5HRIZfrthfczYo5F5pkn7myRCcdXzrtxOarceR0vAoF/H8D9o+uZHD3ILnyyyOXM+elnnNizH5uMjflmhHUcHIPNZwE+LeGU1/oDKeJEn9T9yD+DM2axwW/7n+gZmB8JN9rvS8zxFL86RdmeCFnF+k5M7HK8BqUZDwFtvXWXQsHswMrTodqNZyxrh0YHaTOJaVQquLsnzjuMkStbbYRncAssUTt81txGeS0rGmne9+VlZHT8exqleXHunaAnSgAj0jt4yzPqTladNgwW15IIysDfMerlu1VH3h6kXzZZgQ1nNxDDScB/s2SWkNAO5CJEH1KtyBgY1cgn2BAQmE5GfpSLRicKvbQeF+KpLboIvob7qejDC/k6FT9DKeHLXOUiqGRlQHrO+mnhQPDmZCZj7biM2r3apzTqnc6eDyqhWLeKO7tRl+nXZUu+y6feExGcq+xn/YVGmqXXE5Oh0KhbrDKXbnSBhjltB7zDoeS01CefSO010MagWd6RUIPaS57bQdALiNfvplA42XuoYaTANqSBs2ZM4f9WS6Xo3HjxmzSIENgkh2o+C1jwKJPMv9tDmQ9r/qMwzXtgEIORnspAAC5XIFJzstVAsKOoiO46NJf7d54Os+CnSgAk3YTSJajQ6ZLtSvcz/A6YgP113F7m+F1aODGk9fov+ws7EQBaCE6jWlid2RKG7/TcWQiJzoolIq8zcvRyWzaiQLgRSrpmJLdQ3Tsu9ZkdQCArBRvb+3ENdc+uOjyJTY5T8RGySS4OP+OTqLDGLIxiLtEX5dVBxLZM0GXN2MStpHmyETt9+IloaNhzBCTjJeNHGo4DcTbt28RGhqK0NBQVKtWDevWrUNoaCgSE5lN7ocPH4alpSX27t2LmJgYzJgxAzY2NkhLM9weDZPrQLGBwLKm7x62y5owx4aYOvtHVR0E+I7jWyX3xJ5jMhpu7wucdyYzc6eN17HsweTekkk4KBmF1c5T0UJ0GnPEzjjhMhi+klH4zmktGzA6nyCQsKe0EFjbXj+jR2Ip1oO9+mnwqs9J0qCU3EIsC4zBjztv4/fl3rjn0l1dS9xl4jooSENJ0wAAIABJREFUFE3I5Qo4eGk/H5a5TmPKxpNkZzdTwnXvu551yekoR1JWgdY6+X5bSNX/gKF4kwasaQdfySj0cdoNO1EAvnXaisBjPtyUX1liKdJnK5sRJhcvCwBqOA3EtWvXNCbwmTx5Mvs3mzZtQrNmzVC9enU4Ojrizp07BtVgUh2oIItJeqIpcDXlZaTpMTqaiEt8K+WWf5JtqFzr7LlrC7GBUFTIWHhQMqrS5XCxqW/IaMlJApY01K2drLMns/8qIw66HPHAXidnV/1v/o/EZ+TjUzfV+9BW5I87ro6MhqWNgZDNxHVQKJWxM+i52vOiheg0/pYMx2nJQLiK5+D77YQN1sZuuvdd3/FktfyDQqFA/zXXND5PiSYL0sDBq+p7wZs7BeDq43TyhT+7ovk+bOgC3PkLSL5PXoMZYFLxskCghtOEMKkO9GCP9hfgvV18qyNH7DndgoBzTmT31RgTpUXACjvN9XB1GTcachJx3uUrlbJzpQ1hL/JTP3pDdAqXwhPI6jn0Q9VtZJMDc84dKTQd37OsifpA0doOjEkmzPxdgRqD1VHL/YCEW+azJN+YeHYF2Pk1s0VgQ2cmYKbA5+YL9Fx2+Z82egZfi7bjV7EUn4l8YScKQBePC+QKT43Qb3VCfDA5LRUIfpqBthLVfjxkYxC542G00HvlFY3PkvF/kZ9pzcovwY49u+AimYcjkuEoktZh9uKXvyeHfgDKSohrMWVMKl4WCNRwmhAm1YE0zWgpL1OepUi6q3sgcMWTb7XcUFmAtH80JxJScgsx2GkT8qX12LJlUmvcdXVAbycfNiDpK9qJYJeeeJySQ1bQg72VzzAub8ZkkSVN5HHg7wnMUueH+5jZ1DepwPWVwPFfgJsbudlrXPwGrq4L8LvYCV1Ef6sFisVlNNkG5yTeATzqqLfNmxv5VmYUlJTJ0dld8/LaMVtvkSv4Vah+hvMFofOEtZCYWYBV5x9jwZEw/H03EUWl3PZdmVyhdeWK41KyK4sep+ahm+dF1UzFHup5Aph+tIGoFlPHpOJlgUANpwlhUh0oO15L4hxrIPMZ3+rIcfZP3QMBz3p8q+WGt681B65uVkwKew64EpOCl9IWbLkKqRWCXHoCbkxSiXDXLohyZbK2rnGeiojkXHJiMp/ptqT24FhyGoyJJxeYmdV/vneJtA68nX/CBskUeDr/hi9FO6CgswHc8/cEze1yVSv+sm3mZwK3twKX3Jh2w+MqEenJSI2mprkoAJdjCJ2/CTDfeUNn3d4xy5tykygHIHv0ip4MWHdd472Z4kMgEVw5/rvjtkp5/xEdg0yqZWBxe1+iWkwdk4qXBQI1nCaEyXWg4HXqD1mS5woaA/qca+hmRXbJpDFx/Bf17+5RB0ghcNalBpIfntfpfqRI7dBjyQWyGRUDF+vePoLXk9NhDBTlMXszK6mDUmlt4O4OvpWaH5sdtd8XLs4zrEjiHZWBCbhZMSskeBiMKCgpQzsXLUvAN98kLyDhVpX9Bu61gbDDZHXISnHryBr8JFmFnqK9mOSxBbdDuFvCq40z4a/Q3En1vrR2Pov78eTabVGpTK0ttBcde5clt+K1rRcxLeaAycXLAoAaThPCJDtQagRw2ZNJVZ4Szrca8viO089wxnMQnBgDJQXMbKbnP0tavT9lshhzxeOzOt2PUNdPcesZ4URGe4bq10YKCc628k34Ed3rYe9wICeRb8Xmg7ZzHte252dmUZsB5jAnQGpuERYcCYO9m/ZMtSM2cWS4CrOZpe9LK6yW8KwHnJjJyWDm9b3uaCk6pbYHPvgB/+/6yzFp+H57CByWXMJkn7u4R9BsAkCpTK62f9VOFIBrLn00t1tTH3wnjEnGy0YONZwmBO1AJsDjM7oH0Msac7fcyVgofgvkpTCHhXNJUS4UnnWrvCf5V9eR1VFWzOzP1MdwnnMiq6k8sjJmkCj3JTflPTqgX1141QdeBHGjzdxJCWPqm0eDx5L5THub2D2YGdAiTGGJDH1XXa3y/E3301HEtaiQnwkErQWOTWcM6BuCy3lVys3Ad+L1mo9BWebLjQYjY6FfmFpd9HHajbfL26m22T1Dze/db2BovMw91HCaELQDmQDpj3UPnjd05m8vlDlyZwcUldyPR0v6oaiIcBAQdlg/g+Vmxc2xBnIZ8OggsLrtP+VaMzOK0aeBbIIZe9+mQ6/jWdysgC2fk9NDUSXpHnBgDLCyBbPnLNyPHx2pkVW3i+19iWYyPnwvsUqz+ZnXJbzKMRMj8fIh2omOa6yHjuITfKvjhdzCUozbHqJSF1P33IOspJBZzXF9FXOOMNcDriYIjZe5hxpOE8IkO1BhDvOATY3gWwk3FL/RfP6otsuUM/YaGwm3Kr0XeyRj8ZnXRbIJgy5K9Tecjw6Q0yMrZTQtbVSJBmvAbzK5EXltSzcru7iagaUYB9t66dYuNjsQk+B1Jlqr0eyz8grcT0eZj9kEgKI8fCverrE+BnjyNDChjVehQNQJ4gkL84vLMHhDkNr5n373yR8rZW6YZLxs5FDDaUKYXAe65a1qvnZ+wyynNHUuuuoeOBMMkAAwR1zc3MjsoTX3pYj3dlV6L7KljWAnCkD/1degIDUCHeqrv7kiOQuuT1blQBEZDWXFwK5v9KgTG26OaqEYB6lR+vWXzOdEZFQ2wxmRnIMj95MwbnsIhm8KxrqLTzg/e5IPjh/YojVT77S995GVz3N26aJcYO8w1cGz4zOIZdTdFfxCY320dzmHwMgUyEgmozMzTC5eFgDUcJoQJtGBMuKYbIJPtGQF3TuMb4XkkcuZl5ouwdGGLuR0PL0EeH2iWt7RqbweJcArEccqvRdvpfXZACHyJaFZztLCd4mTdLk8bMnoAJhgTNMePW3XsibkloLJ5UDYEei0vNb7UzIaKLqTnQBcW8HsL356kewSwbuVDxSpXTFniMgoLJGhz0r1PZyTfe7C7VSU2udDvYPM4vzYI0f/xufOvhqN1n933OZX3Kk5mtsIobNkp+29V+mS68EbgpDNtwk3EUwiXhYY1HCaEILuQG/SVLNvethqDwhyTHx5iUIBbOyq46zRYjIaZGXAmnaay4w+SaZMY8dvcqX34pjLEDYwCEvKIafj/l79Aujn18noeP1EPx1uVswSXFIErdVNw5JPGLNM4YeYM0DFBFyHfyI3E598X782mk8uy3RKbiHmHwmFvdt5dF9yCUvPxuD567doKT6r0WAce5BMTIsxsfRsjFaTFZdObl9tpchl6gOuymtLTyJFLj4aXuU+X/EJM9leRBhBx8sChRpOE0LQHUhl2UoVVxrHWfy4JvelbvWwwo7ceXaJd7SXe2QScGM1cOgHZkllegwZDcbGCjutdfLctS0cRAdgJwpArxVXyJ7DWZSrXwBNKn1+aRHgpcds64rmZHQo0edIoVehZLVQNFNWAqxqpfmeRJ0gV662wTNN18HviS2Z1MS5yBSt5sLFP5IzHXzyx9+PtNbBrTjCx0xpQ1YKrSsmCK0sepSYjRZOlRvOLh4XiJRtbgg6XhYo1HCaEILtQFkvdA8GVrc1/cysxW+rXjbpXpts4pNXj7SXXTFBjGddJrGTqVMhUFZIrXBMMgS/i53QRuTPBgRLzxI24Dc36mc4z8wnoyPrufaATNO12ZGMDiV/T9BNh2c9cgM1lMqpLPHW8V/IlZsdr5/pDPubnJYKhCfnaDUXW6+RTVJjLBy4naDx+//H5RzyON7LWiaTIyEznyl3/2jN7YPUfnQAxx8m4zOvi1rbRFdqOA2CYONlAUMNpwkh2A708oHugQCpJaTGhra9I8rrvIRs+QoF4P2ZHmaiB1k9xsCpuSrf+bW0iYrRVF4txWeRkksw2+TVpfoZzlNzyeh4sEc/HRddyehQEnFUNx0BC8nqoGinsoGs07+TLVuhAE7O1q2N+E0mq6UC3229pfYcsXc7j9dvijnVwReFJTK17Kx8GG6/+0lwXHoJdqIAtJEEwsk3CMUrKwxUbHIguuwaAErK5Pjt4EOznvUmjWDjZQFDDacJIdgOVFYCrGypWyAQd4lvtdxQUsAkDnKvrV4HK5ozZytGHCWbbCM1AljbvlzZNpXvrX2bTk6LMVBSAKz9D/t9D0pGaR2F9rn5gpyO9Bj9jF74UTI6ok/prmG9Pfn2oVAAO77SrsHDFri2nNPlkkbBmzRmibyxzOpudtR8fxJCyJedEqZbez06nbyWcmS+LcZvBx+i1T97OUdsvolQkvvAjZA3RaXYci0O47aH4Jd993E5Jo3T8oOfZmh8lkuO3gdub2W2jzw6QO54pwrkFpRixKZgFS3DNwUjt8D0sxdzgWDjZQFDDacJIegOFHYYcLepPAjY2NX0l9NW5EVQ5ZlASS2XVCIrBWIDgbs7Kl+S5mELlOST1WIM5GcCm7oDblY4IBmt1XDuCiI4Ml9aWHVfYS9rQEaoz5QV67BM0ZrJbJyfSUaDkqS7gHe3quuD8MyEUVFWApz8DfCow3x3z3rAeWf+D41Pfwxs6PzunnjWBW5u4K78c+Kq28nZP7nTU443RaXIfGses5rGxi/77mvfN+l+Hk7HIzi/NwqFAjeevMbOoOe4/uQ1ueO2zBBBx8sChRpOE0LwHejWJu0BwJYexA9dNkp0SYTy+gl5HcHrKtewtRd5DcbA9ZXsd06XNkNr0Um14KSF6DSSo++Q06DvktoIgoeop0Zon7FSXt6fkjU5r5/ofjzL/T3kdBgbl9w118Gd7XwrYwYOn19jEgXxMQgQ7ld5myG1DJ1itChnE5uLTmOm2BUnXQbhmMtQTBQvZZ/tA9fdQJnMTI8FMzEEHy8LEGo4TQjBd6Cry7QHAPd28a2Oe6JP6hhE+5DXUlVClhtryGswBirsa3UXz4ad6AwbkDQXncZ+yXfMUQyk8B2vn+E8PJGcFiWpEcD6zto15KWQKztgoe51sXc4OR3GxormWgbvPudbmXGQGqW9nYRs5lsdhWM8z0TDThQAf5dBau1hs+Qn9hl/NoLgs4zCGYKPlwUINZwmhOA7UNhh7QHAsyt8q+OW0qJKj+FQuR6fJa8ncLH28j3rMfvEzIFymWpvuPRCC9FptRnOo8smAXKCo+A+6gFRpRfpBFMFWYyRq0zDo4Pkyt8/Sve6cK9jHstqFQrty65Xt+VOR1Eucz7q/tHMnvTE2+9+V1YC5CQyzzq+ODJJvX7WtAMKs/nTROGFlNxC/Oq5XmOfkUmt0ctpD+xEAVh/iYMVRRTiCD5eFiDUcJoQgu9ApUXAuo7qD/xtvfnfd8Q1z6/rFkCvbMnssyTN6yeaj2rxqg88NZNETnf+UvnuP4hXatzv0395IDkNJfmAVwM9DJYNUPSGnB5Ac9Be8fKoA2TEkSn/govO9SGXWgFR/mR0GBvaBgGOz+Cm/KJcDcutrZnEK1eXvpuBXd4UuLaCn2d8WTGz9Hh1W+a4J78pzHE/FPOjMAeyVW20PjsWOS+EnSgAAeF0htMUEHy8LECo4TQhBN2BIo+9C06WNGACE8+6wLHpwNvXfKvjnuMzdAuifcdzp+nZVWBLz39mNW2ZA9ILzSSTYkkBsKypSt1/JjqoNcmEXE4oeM5O0G9284ILGR1KCnM0Z1LWdF32JKMhJ0ll+ahCql3DXRcHZjDHHHj1CFjWWLUOVrUGbqwCTsxk7kd2Arnyte371jbzGrKFnBYKpSoCRSiRan+W/SJ2wzdrr6OUgz2cT9Pe4FxkCp6/fku8LHNF0PGyQKGG04QQbAd6fFbzQ94c920CzNEvuhqKPUO51/f2NWPAzImke2p1P0G8QqPZ/GYtQUMjK2UGY3RtH+vtyWkBgNyXumshef5lxlNmAMS9jtbyc6UNsMjNjexyZ2Pi9lZgaTnDuaErm2GZvZY0YDJhk+DAGP0GRzZ0JqODQtGFNf/Bfslo5EvVV/KkSJvD6fB9ZBDOUltYIsO0varZcmf7PkRJmZk8szhEsPGygKGG04QQbAfa/a2WAKQL38r44cSvugdp2/vyrdY80DCzeMvlc7QUnVIznCdDX5LT8eqRfkG8mxVw9y9yeoDKz2Ytf8WeI6fh2ooqyz8v6Q9XLzfzWJ7/9KLu7WNLTzIa/Gfp104965LRIQAiX+Zi7YVYeF9+ihcZZnC8lDGytj0miFfgv+IVSJa+Oxf8qWt7DHLawslso9c/iYsqXnTfqOERbLwsYKjhNCEE24FWa983YRbBYUWOTgXcmEQFynoo/98q17Km/GgsK+GnXD45OFat/oOkffC99yXYu53H8E3B5DMYxpzR33CSMhQA4Pezbhq8PyM3s5j8QKUsbUtqxc7z8ci1G7OCwNSpKqt0xSuXwCBJ0j09zou14m61RkEWs+88LYqb8qpg5bnHqscqOQXg0N1EvmWZH+edMUMsZY+2GuG0AYOdNjPZx50CkJ5HPrlVV48LGg1nn5VXiZdtbgg2XhYw1HCaEILtQAe+0xyAbP2Cb2X88GAPSqV6BGovH5DVk/eKOTB+x1fMjOqa/zDlbuxKNvuosVGYDRz+8V0Qvc4eiD717veyMvIa8l4xCXj0MRMbupLRos95oP6/kdEAMG2zivKfuLbHPsk/z5lb3uS0GAvaVo1outxrk8vKGna43IBiJUvBveoDCbfIaCjPtRWqyc/WdwYSQsiXq4XIl7kaDUYbSSAyCS/fpFSg+A0ubfxV4/2Y7HOXEwltJYEay//M6yIn5ZsTgo2XBQw1nCaEYDtQQoiGZXnWTEKcbb2BZU2YvUd3CC8NNBLyT4v1MxQRR8mJyXvFHBNQWflhh8mVb4y8fc3sGVTO2CXdBXb/c1TJ8mbAJTeymYN1MFgq1zlnw2uQlQFLG2osL9rVHpslE7FbMg7p0n8SLZ0TGV6DEi31oZBa4a20Pp65tkOutFxm3ycXyGkxFio707jita0XWS2yUiA1EkgJY7LBViz/r37MOa6kiTmtvQ4uuZMvXwPrLj7Rmnjs2INkXjSZO95HL6Kt+N1xV99tvYX0N9wc3TPzwAONbeFPvzBOyjcnBBsvCxhqOE0IQXegCD9mz+aSBkyafG2BwdVlfCslS1EeSj0/0c9QvCa4v0MXc2OuM9EAkPkMWKLBeJ2aS67M0kJgeXPd2saShmQSPOVnaCxvifNM1Zka0QlccOnPzCol3ze8DgCIOql7X1nezDySBhVkMcuYy393bctblzYGijnKhpmTBAQsADb3YI5tiT7JTbkAM4BZWdtI4mYWqzybr8ZpNZxnwl9xrofCkJ1fgqux6Yh6lctpuQmZ+XBcekmlHfRacQUpuYWc6jAHBB0vCxRqOE0IwXagKH/dlwkua8KcRWiq3Nul9btr3Jt2bBpZPTu/0cHUNCCrwZg556S5TjxsGVNGguM6JpXa0R/II7SnVC4DVtiplHfX1UFj4NxZdBhFUlvAdxwBHXLmmaCr4by9zfAajJWiXODmRmY/Z8ACYP9o7fUSf5NvteTxGVx52zgn5lxSYmYBWorPqvWZTm7nUVDCwRJ9SqXI5ApEvszFMw6PJ8ktLIXPzReQ+Edg/+0EvC2m7YAEgo2XBQw1nCaEIDtQWQmwsqXuAaMb4Rk9vqnkEPsgl56Id22NONd2iJB2RcYpV/L7Bo9MrPp+7BpAVoMx4ztOe728fGj48kryUeWxKO42QORxw5ddkUDVpd8ezr9pna254tKXWU5paB7s0/25sfNroJSbpXFGydlFxvFMLS1i2ue9nczSdK64sbry9nGewNJzHfC7n6Syd6+T23kEPTXDs6eNjGux6ei57DJ7X0ZsCkZCpgkPdpsZgoyXBQ41nCaEIDtQ4h39zObSxqY9wxl5TOt3/1a0Gd1EvuUC+TNYce4xWT3xwZUbHPfa5pH1UxuXPTXXy5IGzAyToXl0sOo+cm+n4cvVRIVkXxWX05a/rrv0JjMwcfr3qutj30hm/7e5nR1bkbQozStJuDzLNyWsQlZya2aVABcU5QEbu2lvJ8mEk69VQk5BCU6GvsTZiBQUlsh400FheJlTqDGBz1drrkFhjpnzTRBBxssChxpOE0KQHSgtSj/DedmTb8VkkZUid/3nat/7pGSg1mA+nvS5beF+wLqOjBYPW2BteyZT7f5RwIsbZMs2dvJSgFWt1NvpFS8y5T06UHUf2diNSbJ1UUrG9CrxUt1rXCiti/MuX+F7p9WqGRZFB1Eira2a0ddQRB6vuj5SzDThxvPrTNK15c2Y7NJxl5ntC8os025WzDLbt+ncadrkoPkexQaSL7v4LbDcTst7xYN8+RTB4H35qdb37e3nmXzLoxgAQcbLAocaThNCsB1oe5+qg8Y17YBbm0z+XM7U3CJ0Ffthi+QnPHVtjyjXTvBynoUWolNaX4ALjoSSFyaXATmJ3CUXERJZz4ETM4G1HZi2fN+HXFllxcyssq4DNNv7kMmY+yZNa5kyqTV7nl0n0RHcWjkKCPU1vAYlSxtXXge3twLZ8eTKN0bu+2iui4ijzDL81Eggl+MsqKkR2u/Rsenkyw/7W3v5D/eTL58iGNxORWl93waEEz5rmcIJgo2XBQw1nCaEYDtQ1nMma6FKEGANbHYE7u4wK5Oz48ZzrS86bdeM/YSyf1KMkzt/6bcqgMR+zlehlZaZu6oLTj5MRn5eDvlBogNjdKgHa+YMVXNYViuXMUu6NdWDVz3y5/Zqo7I24zeFfPkhW7SXf3MD+fIpguFCVKrGd21r57N4/Yaej2oKCDZeFjDUcJoQgu5ALx9qTtt/8Hu+lXFKZeeyabvORdIRV7MjOwE4Og3Y0lP1IHtN10VXw5dfWlh1dtgijp5DfpN1N98BC7jRxCevHlVeBx62zNnHXCOXAxs6a9YUdYJ8+WnR2uskJZx8+RTBIJMrMGn3XbV37cbLHCa5ohBF0PGyQKGG04QQdAc6NVf7zEROEt/qOCMsKUcvszlkYxDkctNeZkyphLs7qjZZt7eSKdt/VuXlru8MXHInv0fw8VndDeeShuQzO/NNZcZKefkM5kdbQoj6QMXxGdxtlQhYqF4Xp3/npmyKoCiVyXHkfhJm7L+PeYdDceMJzRxsSgg6XhYo1HCaEILuQId+0B4c8bUEjCekJyN1Mpvd3AKQnsfdMQ+puUVIyiq3JFEuA4rfcFY+RQOBi6s2F5fcyZT9Ikg3k7euI7PnkyTen+puOk19WW1ZCao8OsfNip9ZTgAozGbOG76+Cki6x335sYHA8V+YfaOPA7gvn0Kh8I6g42WBQg2nCSHoDnTLW3NQtKK5WZ6dN3P/A7QS+aN5JcmC7EQBWHY2hriWxMwCfL89hC1z0PobCDu+msl+6WbFLOt8coG4DooGNM3YVLy29yNTtlwObNTR6F2UktEAAIm3dTebu78lp8NYKMnXrS7Wd2LuIdfI5czz3vsz5vnuNwXIiONeB4VCMVsEHS8LFGo4TQhBd6CiPGCL+nEgRDN+GimvYm7jD7GTTrOcfVddJapFJlfgy9XX1MrtLDqMXGnDd/fJow6v59iZJVnPmf14VRmL/aPIaTg2XTdzQ+IMTiVBa3U3nKGHyOkwFtJjdJvhdLNi9s5zTaBIXcfKlsCbVO61UCgUs0TQ8bJAoYbThBB8ByrKBYLXMQe1H5sGxAfzrYh78jNxy72fzns4v155kaica7HpWsveJ6mQHZSLow0o77iyRDdTQWrZYm6y7ke0HJlIRgMAPDqou+HcO4ycDmNhY1fd64PrJa35GYBnXc1ari7jVguFQjFbBB8vCxBqOE0I2oFMgJDN8HT+TWfDuX7pQqJyjtxP0lr2KucKs1s7vyGqhVKBM/OrMBTWwCWCB9rHBupobKyBFzfI6SjJB1a10t1kkTiX1FjIe6V7PbhZAU8vcauvsuXPh3/kVguFQjFbaLzMPdRwmhC0A5kA55yw1HmmTmZzmtgDxdI6zPl2hHj++i2aO2ku/5pLb9WA8ewiYjooGog+pTlwd7cBrq0knx1Wl2yoq9syM5CkSY0AtpVrj0s+0axnWRPuMqLyQW6yfoYzNpBbfW/SmOX3mrRcJjg4YoTI5QrkFpRCRrOMUyicQ+Nl7qGG04SgHcgEiDiKcNcumrPSinxx3aUXDklGIty1y7tALf4mUUnOJyLUtEwUL4VCWi5YXGEHZMcT1UGpgFwG7B+tOXg/MZMbDftHqZe9vCnwOpZJBMP1bGJ2PJCTqP24mEARt3r4QNeMvUsb8pOxV9MRWMubMmbZTDhwOwGfL7sMO1EAHJZcws6g53xLolDMChovcw81nCYE7UAmQFkJMtd9gc2SiWghOs0aPAfRftxz+UwtUCtd1hwoKyYqSaFQwP/RS0z2uYsJO29jX0g8SiJOAXuGAhu7MecxZj4jqoGihchj2g3F6yfkyy/KA4798m7WymcQ0Rl3nVEoGHPJJlWyBvwmA6WFfCsjT1oUsKRB1YaTZCKnypCVAleXMrPfnnWBg2OZGWozwf/RS40DigduJ/AtjUIxG2i8zD3UcJoQtAOZBvP2B+Gmy+cIcumJVc7T8My1LeRS9ayTCqkV5GcW8C2XwicXXLQbirC/yZd/UQqVjKie9YDYc+TL1ZW36cDz60C2mQXzOclVm86jP/MqsbBEhrj0tygoKeNVB9cM9Q7SaDi/XH2Nb2kUitlA42XuoYbThBBsB3p2FfAZAixrCmzvC0Qe51sRr/y06w42OE8G3KyQU/7okXJGk/35wHd8y6Xwibalo25W5LM8vwjWXK5HHdNOzGPs5GcC6zpWPcMZd5k3iesuPoG99DzsRAHo4HoOq8/HQmHKe2vL0dn9gkbD2dr5LN/SKBSzQbDxsoChhtOEEGQHig/WfLQCF7MzRsru4BeY6uSh2z6sfSO5FfciiMkm+Vc/4OyfzH45Cn8U5jBnGFZsF9t6k0+Os2eI9nZ5y5ts2RTt6HJczoGx3CRPKikAHuwBTv8BBK8H8jOwLyReo+Eyl32MP+26o/GK3dhfAAAgAElEQVT7j95Cdi8+hUJ5hyDjZYFDDacJIcgOpC3pifenfCvjjcISGWZ5H9XJcBbc3MadsIijUDtQfmVL81uuaGykRQE+g5n74V6bGRB4k0a+3K1faG+b553Jl0/RzO5BVT87POoA58VkdeRnApsc1Mr9yv2IRsPVZ+VVsnqMhAcJWWgjCVT57q3EZxH8NINvaRSK2SDIeFngUMNpQgiyA635j/agSGZee3vKU1ImR8aGLysNGq+79MbpR/HcCJLLgfWdNGsJMON9pGUlQNAaYHMPYEMXxmgVZvOjpTAbKH7DXXlXl2pvn5HHmb2cBVnc6aEwHJmo2+oINyvg3i5yOs6JNZZpL9JsONu5cHxEC4+EJ+fgt4MP8dWaa/hl3308SKD9hELhEkHGywKHGk4TQpAdaN8IzYHQhi58K+OfN6kaTV6WtBF+FbvCTnQGF6M5mMkCgLwU7UHrZkduNBgjh39Sr4+tvRgjaurIyoCljdS/v2fdd//tVR8IWsu3UvPi+TXdDeeGzuR0aDme5Wexp0bD+dOuO+S0UCgUSjkEGS8LHGo4TQhBdqBnV5mD6isGJg/3862Mf/JSgG29keHaGA9cPsMj127YIJmCzqLD7IxAXiHB5CyZz5i9Vzu+AvymMOZBU9DqWdc893KmRmoP5COO8q2OPNkJuhubZ1f4VmteLG+m231Z1pichu19NZYZ6doJHURHVcxme9dzCE3KIaeFQqFQyiHIeFngUMNpQgi2Az29iIItX6LMvS6yV3+K3Nv7gfwMJovi61i+1fHHwe/ZIO2oy1C0Ex1TmxX4ec89MmWnxwBLmwBuViiT2qBMqmFQoPx19k8yOoyZUF/t9XHRlW915Lm2XHfDeWw632rNi+39dLsvm7qT03Bnu9Zyn7u2hYv3Tny/PQTOJyIQl/6WnA6KdkoKmMHdCy5Mor7SIr4VUSicINh4WcBQw2lCCLEDvX5TjMEbVM8lmyb2hMzd9l2Asm8kf/vi+KIgS2Xm95bL5+ikZe9T1Ktcw5d/ZBJeS5tgjtgZrUUn0Up0Ek7iP7QGkPneXxheg7GTeFt7IP9gD9/qyLOxm+6G03c832rNi8M/6nZfljcDyorJaJDLgVNzta+KeP2ETLkU3chJUt+ysak7c3YthWLiCDFeFjrUcJoQQuxAP+7UnCI+xKVHhRmSaXxL5ZY3qex3L5LaopvokMZ6shMFwP/RS4MXL1/WHN86bVUpp63oBAqk9TQGkMGe35jNOXoq7BqgXh9r/gMUm/iMTdYL3c2mmxVwfzffis2Lvyfofm+iT5HVkhIO7PwGcPtnAM37U+DpRbJlUqrm6M+a28PpP/hWRqEQR4jxstChhtOEEFoHeplTqNVEzROLVF+CHrbcZuA0Bv7ZA3XJ5Uut9WQnCkDkS8PPcF71GqqxLB/J92oBilxqjQni5YhJEUa7MygFWYD/LGZ/q7sNM5OX+YxvVeRJjdDd0OwZSpfqcY0uZ3Eqr0cHuNFUkAVkx3Nz/ielarw+0dweVrXmWxmFQhyhxcumADWcJoTQOlD0qzytJmqK2Ev9RWhOS30Ks4Gry4Aln+Ccy1da66nXCjLJWPZscNFYXmvRSfhIvkehlMlE+kraHAvEi2EnCsDTNDMbECiPXAbICCZwMjbkMmBdx8qNzO5BTPIkc6oXYyEvBVjZomqz6V4byDX8CgmKAFjeVHObWGfPtzJ+kZUCiXeAlDC+lVAIIrR42RSghtOEEFoHKpPJ4bDkkkZjs1syTv1FePhH88iGGnlcZfT5rXsjdBD7a6ynW3FkDgu/9yis0lnV/4iOoadoL1qITsNOFIBv198gooNixDw5D3jU1W5mDnzHt0Lz5skFzRnAy1/XV/GtksIXAQs1t4nLHnwr44/Yc8DqNu/qYnMPJoEexeQQWrxsClDDaUIIsQOdjUhBCydVMzPAaZvWvYLY0JlckgtjID8D8FT/7sclg9FcdEalnpYERBOV8tNGdaM52vsa3E5Fonm5e/b5ssuITTXj2U1zJj5Yu5k5OJZvdebNls+13xufQUBCCN8KKXxSlMcsd1fps98DpYV8K+OH3GSN716st2dWdFBMCiHGy0KHGk4TQqgd6HFqHhYdDcOgDTcwxece7j1JBs4u0h4shR/hWzI57vsAblZIldrBVzIKx1yGIk/KzHYuFC9iTZ6923lEJBPITluOolIZ1l+MxdcrL6DnkgsYsSkYHqejEPkyFy8y8uF7JxHnIlNRUiYnqoNi5Ozor7mfhh7iW5n5kvW88pnNs4v4VkgxFpLvM331VSjfSvjlxmrt/SXuMt/qKAZGqPGykKGG04hISkpCv3790L59e3Tq1Al+fn56/f+m0oFOPnqJIW778KnIF187bcduyTgopOUe/teW8y2RHHd3YJdkHFqKTrHmsqPID9dcesPT+TeV2cZBG4I4kbTsbAzsRAFoITqNcU6rMVG8FDuvRHFSNkUAvI4F1rZXDdBO/Moci0Hhh4ynlRtOjzpMJltzSHBFoejCeWft/SXiKN/qKAbGVOJlIUENpxGRkpKC0FBmlDE1NRWNGjVCfn6+zv+/KXSgC9GpGvcMujj//u7h//gs3zKJERv3VOP37yQ6gp4iH7XPEzJ1bx//BmVip6FO3khybcXegxxpQ2TfO0y0bIqAKCsGok4At7cxx2BQ+GezY9VJg1a3YbLHUijmTtwlLYMztuaVsNBMMIV4WWhQw2nEdO7cGUlJSTr/vSl0oH6rrmo0XM1FZ/DStTmzfM+E91OsuRBbabKeildydgFRPZuuPEUr0UmkSu3UXsQy9zrMMQcUCsX4SLoHLG1Utem8tYlvpRQK/ygUwOGf1PvHjdV8K6MQwBTiZaFBDace3LhxA8OGDUPDhg1RrVo1+Pv7q/3N5s2bYWdnB0tLSzg6OuLu3bv/qqwHDx6gY8eOev0/ptCBWorPajVXnpt3MIkOTJiV5x7rbDZHbblJXM+u4BdqR9SEuXaFu/NsiJ3n4arfVijouXoUivERfYqZnanKcJ6ay7dSCsU4kMuAyGPAsWnAydlMUjSKSWIK8bLQoIZTDwIDAyGRSHDixAmNhvPw4cOoXr06fHx8EB0djV9++QU2NjZIT3+3HKNLly7o2LGj2vXq1Sv2b7KystChQwfcunVLL31C70AnHiVXarBm+z7kWyJxIpJzdTKbXyy/gmev3xLXk55XhHkSFzY43SkZr6Zl/hEzTzZBoRgbZSXAypZVm003K+DOdr7VUigUCqcIPV4WItRw/ks0GU5HR0fMnj2b/Vkul6NRo0ZYvlz3JDfFxcXo06cP9u/fr9Pf5uXlsVdSUhKqVauG5ORklc+Fco1feQQHJKPxzLUd7rt2xwLxYhVjszIggneNXFzLToerfO9W4rPwu/0MD5+lQOT3ECO9b2Dc1mBsvBCN1IxsolpSM7Kx4+xtZLo2Roa0CdqINJ8Hejkikfd6oxe96MVc+dEXdTKb8rUdkPf6Je966UUvetGLyys5ORnVqlVDbi7ZbP+Ud1DD+S+paDhLSkrw3nvvqZnQSZMmYcSIETr9mwqFAj/88APc3Nx0+ns3NzdUq1aNXvSiF73oRS960Yte9KKXHldycrLOcT/lf4Mazn9JtWqqhvPVq1eoVq0aQkJUD9NetGgRHB0ddfo3g4ODYWFhgS5durBXRESE1r+vOMOZk5OD58+fIzc3938e9eF7lpTqoDqoDqpD6DqMSQvVQXVQHVSH0HUYSktubi6Sk5Mhp8d3cQY1nP8SEobTGMjLM4517VQH1UF1UB1C12FMWqgOqoPqoDqErsPYtFB0hxrOf0lFw2mIJbXGgLF0ZKqD6qA6qA6h6zAmLVQH1UF1UB1C12FsWii6Qw3nv6Si4QSYpEFz5sxhf5bL5WjcuLFeSYP4xlg6MtVBdVAdVIfQdRiTFqqD6qA6qA6h6zA2LRTdoYZTD96+fYvQ0FCEhoaiWrVqWLduHUJDQ5GYmAiAORbF0tISe/fuRUxMDGbMmAEbGxukpaXxrFx3iouL4ebmhuLiYqqD6qA6qA6qw0S0UB1UB9VBdQhdh7FpoegONZx6cO3aNY1ZriZPnsz+zaZNm9CsWTNUr14djo6OuHPnDn+CKRQKhUKhUCgUCoVHqOGkUCgUCoVCoVAoFAoRqOGkUCgUCoVCoVAoFAoRqOGkUCgUCoVCoVAoFAoRqOGkUCgUCoVCoVAoFAoRqOGkUCgUCoVCoVAoFAoRqOGkUCgmj0Kh4FsCAOPRQVGF3hegpKSEbwkAgDdv3vAtgeXVq1fs0QvG0kaoDuNCLpfzLYGFTy3FxcVGVRe0fRof1HBSTAZjecAYw0OX77ooLCzkXQMAZGVloaysjG8ZePHiBeLj4wHwe29kMhlvZQNAQUEBcnNzkZ2dzX7GR31kZmbi2bNnePToEa86YmNjcebMGc7LrUhoaCj+/PNPZGVl8aojOjoaI0eOREBAAK86lFosLCwwdepUXnUkJyfj/Pnz2LdvH/sZH201JycHqamp7HPMXElNTcXly5dx7NgxpKenA+DvnZ+QkIDdu3fD1dUV0dHRvGl5/PgxRo8ejeDgYN7jn+TkZKSkpPCqgaIZajgpeqMMWvkOXnNzc5GQkICEhATWVPDxIk5LS8OtW7dw4cIFFBUVAeDnoR8VFYXly5ezP/NlbB4+fIixY8ciOTmZl/KVREZGol+/fti1axevJk8ZuDo6OvLSZ2JjY7Fw4UK2Dvjqt1FRURg+fDj+85//oF+/flixYgUvOiIjI9GjRw+0b98ezZo1w6xZs3jRkZ2djerVq8PCwgK+vr68aACAsLAwWFhYQCQS8aYBYO6LtbU15s2bh6dPn6r8juv+Gxoaio8//hgtW7ZE79698eLFC07LVxIREYGWLVuiW7du+OCDD9C7d2/edDg4OMDe3h729vYYOXIk4uPjOX2WFBQUAOB3wC4iIgLt27eHvb09GjVqhIYNGyIhIYEXXeHh4bCzs0Pv3r3Rrl07fPTRR4iMjORUg0KhgEwmw5gxY2BhYYG+ffvi3r17bF1wXScRERFo1qwZnJyc2PZCMR6o4aTohXIk6/nz5wD4G9mLjIxEnz590Lp1a7Rv3x7Tp09nzR6XREREwN7eHh06dEDTpk3Rr18/znUoFAoUFhaiSZMmsLCwwMKFC9nfcX1/wsLCUL16dcybN0/td1y+fKKjo2FtbY358+cjKSlJ5Xdc1kloaChq1qyJ7t27o2vXrrh79y6nGp49e4aGDRuievXq+Pnnn3kzndHR0ahTpw7++OMP7NixA/PmzUP37t1x6dIlznXY2NhAJBLh2rVr2Lp1K1q2bIlnz55xqkPJ0KFDMX78ePzf//0ffHx81H5Pus9ERESgZs2aEIvF7GcymYxdRsqFBgDIz8/HwIEDMXfuXLbMpKQktr9wSVhYGGrWrAkvLy/ExcXB0tISO3bs4FxHfHw8mjRpAk9PT7x8+RKxsbGwtbXFjRs3ONXx7NkzNGjQABKJBDdu3MCFCxfQqlUrdO/eHYGBgSgtLSWuISoqCg0bNsSJEycA8GM64+Li0KBBA4jFYiQlJSEmJgbDhg3DqFGjOF+O/uTJEzRo0AAuLi7Izc1FYWEhHB0dsX37dk51KNm5cydEIhEcHBzQvn173L59m3MNT58+ha2tLRYtWqSygoZiPFDDSdGZFy9ewM7ODh999BH69+/PjvpybWoeP34MW1tbLFy4EFeuXMHq1avRs2dPlSVHXBATEwNbW1uIxWLExsbi9OnTaN26Ne7fv8/+DZcvxkmTJmHu3LmoXbs2L7M2ERER+Oijj1SC1zdv3iAnJ4c1OFy0leLiYkyYMAG//fYbAOYe3L9/H6dPn0ZaWhpn9yQsLAy1atWCh4cHZDIZmjZtipkzZ3JSNgDk5eVh/PjxGDNmDJYvX45u3bph4sSJnJvOrKwsfPXVVyqDEOnp6ejUqRO8vLw40aAss1u3bli0aBH7WWJiIvr37487d+4gKCiIMy1yuRwKhQJffvklfHx8sGLFCpWZznPnzhHfy5iUlAQLCwtMmDCB/czJyQmDBw/GoEGD4OTkxH5Ous9kZGSgc+fO7LNz2LBh6NSpE2rWrIkuXbrg9OnTKiaYFDExMbCwsIBEImE/mzt3Ljp37sz5io09e/agb9++yM/PZz/75ptv4Ovriw0bNuDZs2ecGB1vb2989913Km1gyZIlsLCwQIcOHdhBAVJtJCkpCZ06dUK9evVQo0YN+Pv7Ey1PE6WlpZg+fTomTZqk8g7buHEjOnfuzJkOgNlr/cMPP2D27Nkqz/ARI0ZgwYIFmDlzJvz9/ZGamkpci7L8DRs24McffwQAdOzYEZ07d0ZcXBxEIhFng4peXl7ss0wmk+HQoUNwc3PD6dOn1VZMUPiBGk6KThQUFGDq1KkYO3Ysdu7ciW+++QZ9+vTh3HTm5uZixIgRKoZKoVBg4MCB+O9//8uJBoBZDvfFF1+oBNEymQz9+/fH4cOHceTIEaSlpXGiRfni/emnn9gHrKWlJX7//XcAwN9//43ExESiGtLT02FhYYFBgwaxn82cORO9e/dGp06dMGrUKHZ/GGmjU1xcDAcHBxw/fhwAMHDgQHTs2BG2trawsbHBpk2biO9Ve/r0KSwsLODs7Mx+tmXLFjRv3hwPHjwgWrYShUIBsViMv//+G4WFhdi+fTsvpjMmJgbjxo1jAw/ls2LhwoX49ddfOdORmZkJFxcXlX2bHh4eqFWrFtq2bYumTZuiR48eyM3NJa5F+X2lUin27t3LarGwsED37t3Ru3dvdn8YSQ2tWrXCF198gdu3b6NXr17o27cv/vjjD8yePRv169fHsGHDiGpQkpycjG7duiE2NhazZs3C4MGDERQUhKdPn2LIkCFo164d7t27B4Cc0ZDL5fDx8cGqVatUPj9+/DgaNGiAK1euAOBuoMbDwwPNmjVjZxDXrFmDDz74AF9//TXs7OzQvHlzBAYGEtfx66+/wsHBQeWzQ4cOYdGiRbC3t0evXr2Ila1QKLBmzRqMHj0aISEhmD9/Pt577z1OTWd8fDzi4+Oxbt06rF69WuV3kZGRsLOzQ3p6Oie5AuLj45GdnY3g4GBcv36d/dzLywvvv/8+xowZg1GjRsHS0hIeHh4AyNTRixcvVFYOxcXFYejQoezPXbp0gY2NDerVq8fuLSWJXC7HyJEjsXjxYgBA37594eDggC5duqBx48YYPnw4rl27RlwHpXKo4aTozPbt29llX2fOnMHXX3/NuelMT0/H1KlTWTOhfPn/9ddf7AOvfEBA8oW0efNmhISEsD97eXmhevXq6NKlC+zt7WFtbY3w8HDiOpQBybZt2+Dq6goA8Pf3R82aNdGiRQt06NCBk9HO77//Hg0bNoSfnx/69OmDL7/8EuvWrcOyZcvg4OCA5s2b4+3bt8R1ZGVloU+fPrh8+TKWLVuGb7/9FlFRUcjLy4NEIkG9evXg5+cHgFybvXLlCrZu3ary2cOHD9GgQQP2cy76S/l29/btW2zbtk3NdBYXF6OwsJCYhvT0dJUkMMpy582bh3HjxqnpJEn59nfgwAHUq1cPx44dQ1xcHBITE9GsWTN2ZpwU5b/r6tWrMXr0aPbnrl274v/+7/8glUqJalBSWloKe3t7WFhYYMyYMSqDZBcvXkSdOnU0LvU1NHK5HPb29hgxYgSmTp2Ky5cvq/zewcEBY8eOJa6j/L6v8vdJOcDKJfHx8fjkk0/Qpk0bjBw5EtWrV8fFixfZLRtcafL390fHjh2xZ88eAMwKoxo1amDXrl2IiYlBw4YNVcyPoYiPj0d6ejpCQ0Nx9OhRAMzS63nz5qmYTpKEhobC2toaBw4cQE5Ojtrvw8PD0bRpU2RnZ7PtpeIWDkNq+fjjj9X2e4eHh6N37944e/YsGwusWLECVlZWeP36NREdNjY2OHDgAPtZSkoKWrZsibi4OADAjz/+CEtLS7Rq1QqhoaHEnu8vXrxgB9OdnJywYMECbN68GQMGDMDLly8BAJcuXcLAgQMxdepUlJSUGEUyQ3OFGk5KpcTFxWH37t0af3fq1Cm1mc6ioiIiGcLi4uLYJbPl97AoHx7bt29nX77Kz0iMOMbFxbEBWPl//8SJE2jatClOnjyJ169fo6ysDN988w369+9vcA1KHcoAQMm5c+dURpv79euH999/XyVQM/TDNi4uDjt37mR//umnn2BhYYHhw4cjIyOD/Tw6Ohrt2rWDi4uLQcsvr0M5UwQA48ePR9u2bfHjjz+qLbWePn067O3tiRi+uLg4tYCgfJ0vWLAATZs2JTb7nZOTg+joaLV/X9lWCwoKsHXrVtZ0FhUVYcaMGfjhhx8MWh9KHRUHOsqXsWjRInz33Xfsz1KpVGUpoyF1aKrv69evs7NmSsaMGUNkpYQ2Hf7+/hgzZgwA4Oeff0aDBg0wY8YMVK9ench+LE06ysrKMGHCBBw5ckTtb1u0aKGSiIykjnPnzrH70C9evAjg3VEtnp6eGDJkiMF1KLVERUVpHJRTtlc/Pz+0bt2aneUkEbRqqpOEhAT89ddf8PT0ZPuo0hRv2bIFn376qcGXXlfUkZCQgBkzZqBRo0Zo3749atasidmzZwNgVvrY2tqqtZ3/ldDQUFhZWWlMppWXl6c201lcXIyLFy8adGA1LCwMNWrUUFlaDry793K5HPfv30eTJk3YAbs///wTLVq0UFkGbUgt5berKCkoKGBjLuVg+5EjR9ClSxfk5eUR11FWVobCwkIMGzYM6enpmDlzJpo0aYK7d++iW7duaNy4MR4+fGhQHcA747t//34AzIC7jY0Nhg8frpYAzdfXFzVq1GATPFH4gRpOilaioqJQv3599OjRQ2WvSPkZxPKm88mTJ/jtt9/QtWtXg+63UeqouKyn/Et/06ZNKr+XSCRq+04MpcPR0VHNzL548YKdzVQyd+5cDBw40GDlV9TRo0cPlJWVQaFQQC6X4969e+jZsycA4JdffkHDhg2xcuVKWFtbY/LkyUR1lJ8h8/LyYk15+aWbDg4ORGaPyutQtruoqCh89tlnsLCwYLUoR3/37NmD3r17G9xwVtY+lPUQHByMNm3asKPDhlye9/jxY3z77bf46quvMGfOHLXfK79vQUEBtm3bhu7du6NJkyaoUaMG7ty5w5kOJcuWLcMPP/wAABCLxfjwww8NutxYVx1KZDIZxo4diyVLlgAwnKmoTEdaWhqGDBmCPn364JNPPkFoaChKSkrw559/ok6dOgZd3qtJR/ns3hVnufPy8tC/f38cOnSI/RtSOgBmZYJyifP333+v0jemT5+OiRMnQiaTGfSZrmsbycrKQosWLYjNflelQyKRqL1LZsyYgREjRhg0SZ02HRkZGbhx4wZ27typsow3OTkZPXv2xM2bNw2mQZu5Kn/fc3NzWdN57Ngx/P7772jYsKHBBvJiY2NhY2OjkoBPU7uLjo5G48aNUVhYCGdnZ3z00UcGfZbqqqXiz3/88QdGjhxp0EytVemYMmUK3nvvPTRo0IAdyCstLcUXX3zBJpk0FNrayM8//wwLCwuMGzdOZSDm8ePH6NatG/GtRZTKoYaTohFlds3OnTujdevWyMzMVPl9+QfNqVOnMHDgQNSqVQtWVlYGfeBWpUOJr68vO8MpFotRo0YNleQ9JHVoC4B+/vlnzJ8/n00QwoWOkSNHonPnzvjkk08QFhYGgFk62KhRI4OO/mrSUd7AlR+gUCgUKC0txciRI7Fx40b2M1I6lOXv3r0bzZs3R8eOHZGUlMSWOX/+fAwZMgRFRUWc3JeKDBgwwODHG0RERKBevXqQSCR4/Pgx+/nTp09VXrzKe5SdnY0ePXqgTp06Bk2lr6sOAHB1dcXkyZOxdOlSWFpaGnQUXB8dSlxcXNC4cWODZqzVpiMuLg65ublIS0tDx44d0b59e5XvX1BQYNDlcJXVhzZT6+LighYtWhg0SNOm48mTJ5DJZMjMzMTKlStRq1Yt9OzZE7NmzcKUKVNgY2ODqKgog+moTEvFNqI0vgcOHIC1tbXBDUVlOpQzVNevX0f9+vWxePFiBAYGYv78+bC1teWk7z558kTjjJ1CoYBIJELLli0NtqpJV6MHvJvptLCwgLW1tdpqhX9LWFgYPvroI1hYWGDatGmVbgOJjY1Fx44dMW3aNFSvXt3g+/P10QIwz3VXV1eD95fKdCjfKXv27MGoUaPYPfKk9rRqaiPKPpqUlITx48ejevXq8Pb2Rnx8PORyOcRiMTp16sT7OcPmDjWcFDWUo0cSiQS3bt1CnTp1VJZHKim/dPXrr79G7dq1Df6Q00UHABw8eBCDBw+GRCKBpaWlQR/8+ugAmFE9V1dX1K9fH7GxsZzpKCgowODBg2Fvb6+SGEUmkxl02ZUu9VE+SFDWh6GD+ap0FBUV4ciRI+jQoQM++eQTjBw5EiNHjoSNjQ0iIiI406FE+WK+c+cOPv74Y3Zf0v9KUlIS2rRpo/ICBoCVK1eibt262LVrl8rsVUlJCZydnfHhhx+qzcpzqUMsFsPCwgIff/yxQfurvjqCg4Mxbdo01KtXT6XfkNahXIoeFRVl0OeEvjoq1seNGzcwadIk2NraIjQ0lBMdtra2bH3IZDJERERg3LhxGD16NCZNmmTw8wX1rRMAuHXrFhwdHdm9YVzpKC4uRk5ODtasWYNPPvkE7dq1Q69evTjru7a2tti1a5fKbFlQUBBGjx5t0D6jr7kqKyvD5MmTUbt2bcTExBhMg6WlJdzd3fHw4UNYWVnhxx9/1KhFoVAgJCQEFhYWsLKyMmhf0VcLANy+fRujRo1CixYtDPoc01VHWVlZpQOthtJSVRvJycnBjBkzUKdOHTRp0gRffPEF6tWrZ/D7Q9EfajgpKijPIFMuVUhKSoKtrS3Cw8M1jjSWlZXB3d0dNWrUYGfU+NCxbds2IsGrvjqCg8tMUUcAAA1PSURBVIMxefJkNGjQwOAP/cp0KM1MVlYW0UPK9a2PGzduYMKECQYP5nWtD7lcjuzsbLi5uWHWrFlYtGiRyug9aR2aSExMxMCBAw22n2TPnj344osvkJiYyJbp5eUFa2trDBs2DDVq1ICPjw8bQCtnJgzZX/XRoQxc9+3bh3bt2hncTOhTH8pBialTpxo8m2JVOiwtLbFr1y7i5xjqWx8HDx7Ef//7X87vy4cffojdu3erLQMkMVOib59RYugMxrrWiZKMjAwkJiZyrqNifcjlckgkEoP1GX3NlUKhwMGDB2FtbW2w931GRgZatmypklk8KCioUi35+fmYPn26wfvKv9GSnZ2N/fv3G3RQV1cdXCTi0beNXL16FQcOHMDBgwcRHx9PXB+laqjhpLAoj3Ion7gjLS0NNWvWxNWrV7X+f9u2bTPoA/ff6AgKCoKDg4NBZ1j11VFaWoqrV68a3NToqqPifkBDp+//N/Vx8eJFzJkzx6DBvK46SL8E/21/AWDQfVeTJk2Co6Ojyr+9dOlS9hgSkUiE6tWrY9u2bUTP7dNHB8CYcxLZk/XVUVBQQCRLrz46SB6poG995OfnG3Tv17/RUVJSwg4akejH+t4b5bPU0Fp00fHBBx9g27ZtRAcm9KkPQ5+H+m/MFcBsYzB0Ephbt26x/61sf1VpIfVM/TdaTFWHPm2Eq2OLKPpDDSeF5c6dOypHOZSWluLNmzews7NjjzUo/8Ilda6RvjqUR5MYen2+vjqUe3sMHTzqq6N8Fl8+dSjrw9Av5P+lnRoyYDSG+yKXyzFjxgz07NkTRUVF7Mu24ku3X79+GD58uMHL/zc6SJ7tKEQd9L6o6iBZH8akhep4hz6mhsQAhEwmQ0lJidrAQvlkb9bW1pgwYQJxg2UsWoxFhxJjML6U/w1qOCks2h7kn376KXsYtvJvXF1dUbNmTaSkpBj8BaCvDktLSyKHpOur48MPPyRy3MW/uS8kZo5ofRiHjkePHmHatGnsz5s2bYKFhQV7Fl55XTKZDEVFRZg6dSo8PT0NmpmX6qA6hKDDmLRQHarwbWri4+Ph4eGB3r17o2PHjujXrx+CgoJUVqCU11K3bl0MHz7c4MeeGJMWY9GhhO82QjEc1HBSqqR3797suVsAc16eoY8woDqoDqqjapR7RhcvXsx+lp6ejt69e8PW1lbjPllnZ2c0a9aMPZTbEFAdVIcQdBiTFqrjHcZgaiIiItCuXTt89913mDt3LubPn49u3bqhZs2a2Lhxo8Z9steuXYOdnR1evXplMB3GpMVYdADG0UYohoUaTorWJaDKkcxZs2Zh0qRJAJgXj6GzwFIdVAfVUTWVHf595coVdOnSBTY2NlizZg1u3LgBX19fTJ06FdbW1gZP2ER1UB3GrsOYtFAd7zAGU1M+2Vt2djb7eUZGBqZNmwZLS0vs378fgPrSYkPv9zYWLcaiAzCONkIxPNRwminx8fH47rvv2J8r23fo6emJb7/9FhKJxOBnTVEdVAfVUTWPHz+GlZUVFixYoPL54cOH2b0tISEhmDhxIj744AO8//77aNu2LYYOHWrQRFpUB9UhBB3GpIXqeIcxmJqYmBi8//77cHV1ZT8rv4S4uLgY48ePR7169Qx6Fq4xazEWHYBxtBEKGajhNEOKi4tx/vx51K9fH0OGDGE/1xZEe3t7s4crGzKIpzqoDqqjakpKSuDu7g4LCwvs37+fPVN1yZIlqFWrlloZjx8/xsOHD5GammrQPS1UB9UhBB3GpIXqeIcxmJqioiIcOHAAFhYW8Pf31/g3crkc169fR61atQx2VrIxazEWHYBxtBEKOajhNDMePHiAKVOm4OXLlzh79izatWuHAQMGsL/XFETfv38fgwYNQkREBNVBdVAdHOpITk5G9+7dkZmZicWLF6Nly5bw8/ODu7s76tWrh3PnzrF/S/IYGKqD6hCCDmPSQnW8wxhMzZMnTzB48GC8fPkSzs7O+OCDD+Dr66vyN8rvX1ZWBktLS/z1118G12FMWoxFB2AcbYRCFmo4zQjlwbm///47AOYYh4CAALUgWrlMoaSkBLNnz8aoUaMMeuQI1UF1UB26kZSUhKZNm2LWrFkAgBkzZqB27dr46KOP2JcyF4duUx1UhxB0GJMWqoPBGExNeHg4rK2tYWFhgfDwcADA4sWL8cEHH+DQoUMqfyuTyRAcHIyuXbsafJm3MWkxFh2AcbQRCnmo4TQTYmJiUKtWLSxbtgzAuwQn5YPob775hv37goICzJkzBx9++KFBkxZQHVQH1aE7MpkMK1euRIcOHdhzPOfMmYNGjRphz549yMvLA0A+cKU6qA4h6DAmLVSHcZia0NBQ1KhRA7NmzUKnTp1UZs9EIpFGc/Pnn39iwIAByMzMNJgOY9JiLDoA42gjFG6ghtMMiIiIQO3atVGvXj12mZ9CoWBnZirO3JSVlWHRokWoWbMmHj58SHVQHVQHhzrKJ0oAgNzcXHTu3FnF4E6aNAlt2rTBjh072P1YhobqoDqEoMOYtFAd7zAGU6PMyiuRSAAAjRo1gre3t8rfVNQilUpRu3ZtREZGGkSDsWkxFh2AcbQRCndQw2niKDN+jRgxAsOHD8fgwYMREhLC/r7izI29vT2qV6+OGjVqGDSIpzqoDqqjap49e4a6deti5MiRSE9PR0FBAQDg7t27+PDDD9kZVwCYMmUKOnToAG9vb4MnXaE6qA4h6DAmLVTHO4zB1Dx8+BAff/wxnJ2d2c8+//xzeHp6AlCd0RWJRKhVqxYGDBigMYmSqWgxFh2AcbQRCrdQw2nCxMbGwsLCgs34derUKQwcOBCDBw/G7du32b8rH0QfO3YMAwYMYJc2UB1UB9XBnY6nT5/CxsYGFhYWGDhwIDZs2MC+XBcsWIDu3bvj5s2b7N+PHTsWn332GXJycgxSPtVBdQhJhzFpoToYjMHUZGVlwdbWVu0ImFGjRuHHH38EoH6khru7O95//32DDmAakxZj0QEYRxuhcA81nCZMcHAwdu3apfJZVUF0SUmJwUdcqQ6qg+rQTvlkCACwceNGzJ8/HxKJBDNnzoSDgwPOnTuHe/fuoV27dvDw8GDLB4CUlJT/qXyqg+oQkg5j0kJ1qGIspqakpAT37t1jf1aW+fPPP6scbaVk7dq1CAkJYfezGhJj0WIsOoyljVC4hxpOE6SgoADZ2dm4cuUKXr9+rfbAqCqIpjqoDqqDOx0VDev169cxaNAgBAYGorCwEJs2bYKNjQ3WrVuHQYMGwcbGhsiSIqqD6hCCDmPSQnWoYiympiJKHatXr0bfvn0BvDPpUqkUFhYWBj1OSwha+NJhrG2EQh5qOE2MJ0+e/H979w+STBzHcZwbsoj+DWJEtISQW0hUW0hLhmlDORjEQUM0tl01BHFTU7sNueZauAQ1tEdCodgQ/oFaoragf59neNDHU6qHh+e87/36vEcV7jX8xN/39E4sLy8jEAigvb0dfX19SCQSljc48GcTHY1GcX5+TgcddDjguLu7w9DQELa2tlAsFmuPm6YJr9eLSqUC4Pe3rysrK4hEItA0DdFotOksMB10qO6QZKHj+6QMV9UODg7Q399fu6nS9vY2Ojo6HPmZphSL0w5pa4TZFwdOhcpmsxgYGMDa2hpSqRRyuRwMw4Df70cgELBctwEAR0dHmJycRDwex/PzMx100NFix+PjI3Z2dtDb24vp6Wns7e3VntN1Hbqu4+npCQBwf3+P09NTRCKR//4BTAcdbnBIstDx9zk91FTLZDLw+Xx4fX2FaZqODZuSLFIcUtYIsy8OnIqUzWbR2dmJzc3N2nUc1Q4PDxEMBjExMYGbmxvLc5lMxnJWlA466Gido9r19TUWFxfh9/sRCoWQz+eRTqeh6zpOTk4sr7Xzf/vooMMNDkkWOr5PylBTLBYxMjKC+fl5eDweR4cZKRYpDilrhNkXB04FKpVK8Hq9iMfjtcc+Pj4sG+lkMomenh4kk0kAaNpk00EHHa11NPbw8IDj42MEg0EMDw9jY2MDY2NjWF1dtf3YdNDhNockCx1fJ2WoKZVK0DQNHo8Hl5eXjhikWaQ4pKwRZl8cOBXo9vYW4+PjiMViTdeX1Z/JnJqawsLCAh100CHA8VXr6+sIh8MYHByEpmnY39+ngw46XGChozkpQ83b2xtM00Qul3PMIM0ixSFljTD74sCpSIVCAeFwGDMzM5ZNdP0GOhQKYWlpiQ466BDiaKz++GdnZzAMA93d3S3fDNBBhxsckix0fJ6UoaZqkZIUiwSHpDXC7IkDp0LVb6Lrb3jy/v6OcrmM2dlZpFIpAPZew0EHHXT8e43Hcup28HTQ4QYHIMdCx+dJGGqY7LhG1I4Dp2J99s2NYRgYHR1FuVymgw46hDkYY4wxxlSNA6eC1W+iLy4usLu7i66urpb/Lp4OOuhgjDHGGPvZceBUtEKhgLm5Ofh8PrS1tTl2xy866KCDMcYYY+znxoFT4fL5PGKxGK6uruiggw6XOBhjjDHGVIoDp+K9vLw4TQBAR2N0WKODMcYYY0zNfgGEQIRpD8OHLQAAAABJRU5ErkJggg==\" width=\"924\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0.01, 100000000.0)"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax = sns.stripplot(x='ProblemName',\n",
    "              y='Prediction',\n",
    "              hue='distribution',\n",
    "              order=np.sort(performance[\"ProblemName\"].unique()),\n",
    "              data=performance)\n",
    "#sns.boxplot(x='ProblemName', y='CVmean', data=CV_data[CV_data['distribution']=='uniform'])\n",
    "#sns.catplot(x='ProblemName', y='CVmean',row='distribution', kind='box', data=CV_data)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('Selector loss performance for various benchmark problems\\n(Optimal datasets)')\n",
    "#plt.tight_layout()\n",
    "ax.set(yscale='log')\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.ylim([0.01, 10e7])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"877\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax1 = sns.stripplot(x='ProblemName',\n",
    "              y='CVmean',\n",
    "              hue='distribution',\n",
    "              order=np.sort(performance[\"ProblemName\"].unique()),\n",
    "              data=performance)\n",
    "#sns.boxplot(x='ProblemName', y='CVmean', data=CV_data[CV_data['distribution']=='uniform'])\n",
    "#sns.catplot(x='ProblemName', y='CVmean',row='distribution', kind='box', data=CV_data)\n",
    "plt.xticks(rotation=45)\n",
    "plt.title('CV loss performance for various benchmark problems\\n(Optimal datasets)')\n",
    "ax1.set(yscale='log')\n",
    "plt.ylim([0.01, 10e7])\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(0.1, 1000000000.0)"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ax2 = (-R2_on_optimal).boxplot()\n",
    "plt.xticks(rotation=45)\n",
    "plt.ylabel(\"Negative R^2\")\n",
    "plt.title(\"Performance of various surrogate models on optimal datasets\")\n",
    "plt.tight_layout()\n",
    "ax2.set(yscale='log')\n",
    "plt.ylim([0.1, 10e8])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>svm_linear</th>\n",
       "      <th>svm_rbf</th>\n",
       "      <th>MLP</th>\n",
       "      <th>GPR_rbf</th>\n",
       "      <th>GPR_matern3/2</th>\n",
       "      <th>GPR_matern5/2</th>\n",
       "      <th>DecisionTree</th>\n",
       "      <th>RandomForest_10</th>\n",
       "      <th>RandomForest_100</th>\n",
       "      <th>AdaBoost_10</th>\n",
       "      <th>AdaBoost_100</th>\n",
       "      <th>ExtraTrees_10</th>\n",
       "      <th>ExtraTrees_100</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "      <td>2.714000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-1.556254e+06</td>\n",
       "      <td>-1.559235e+06</td>\n",
       "      <td>-5.773272e+05</td>\n",
       "      <td>-2.630746e+06</td>\n",
       "      <td>-2.287523e+06</td>\n",
       "      <td>-2.172825e+06</td>\n",
       "      <td>-1.707418e+06</td>\n",
       "      <td>-1.698790e+06</td>\n",
       "      <td>-1.689843e+06</td>\n",
       "      <td>-1.728752e+06</td>\n",
       "      <td>-1.697691e+06</td>\n",
       "      <td>-1.731576e+06</td>\n",
       "      <td>-1.735962e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.354855e+06</td>\n",
       "      <td>6.364145e+06</td>\n",
       "      <td>3.154716e+06</td>\n",
       "      <td>1.648690e+07</td>\n",
       "      <td>1.073038e+07</td>\n",
       "      <td>1.124609e+07</td>\n",
       "      <td>6.863736e+06</td>\n",
       "      <td>6.835478e+06</td>\n",
       "      <td>6.796690e+06</td>\n",
       "      <td>6.916490e+06</td>\n",
       "      <td>6.825420e+06</td>\n",
       "      <td>6.929674e+06</td>\n",
       "      <td>6.936009e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-5.184249e+07</td>\n",
       "      <td>-5.154479e+07</td>\n",
       "      <td>-4.307267e+07</td>\n",
       "      <td>-1.806257e+08</td>\n",
       "      <td>-1.182055e+08</td>\n",
       "      <td>-1.306120e+08</td>\n",
       "      <td>-6.136368e+07</td>\n",
       "      <td>-5.431853e+07</td>\n",
       "      <td>-5.229169e+07</td>\n",
       "      <td>-5.332469e+07</td>\n",
       "      <td>-5.370783e+07</td>\n",
       "      <td>-5.237158e+07</td>\n",
       "      <td>-5.258697e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-6.539313e+01</td>\n",
       "      <td>-1.675339e+02</td>\n",
       "      <td>-4.900634e+03</td>\n",
       "      <td>-1.808736e+01</td>\n",
       "      <td>-1.808650e+01</td>\n",
       "      <td>-1.808736e+01</td>\n",
       "      <td>-1.265774e+02</td>\n",
       "      <td>-1.334865e+02</td>\n",
       "      <td>-1.353827e+02</td>\n",
       "      <td>-1.656219e+02</td>\n",
       "      <td>-1.442834e+02</td>\n",
       "      <td>-1.344601e+02</td>\n",
       "      <td>-1.357183e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>-4.690512e+00</td>\n",
       "      <td>-4.936540e+00</td>\n",
       "      <td>-5.194916e+02</td>\n",
       "      <td>-1.178264e+01</td>\n",
       "      <td>-6.957627e+00</td>\n",
       "      <td>-1.025051e+01</td>\n",
       "      <td>-3.878266e+00</td>\n",
       "      <td>-3.852322e+00</td>\n",
       "      <td>-3.837389e+00</td>\n",
       "      <td>-4.051554e+00</td>\n",
       "      <td>-3.950720e+00</td>\n",
       "      <td>-3.746468e+00</td>\n",
       "      <td>-3.761977e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>-9.358635e-01</td>\n",
       "      <td>-1.178216e+00</td>\n",
       "      <td>-1.031953e+01</td>\n",
       "      <td>-3.085031e+00</td>\n",
       "      <td>-1.302052e+00</td>\n",
       "      <td>-2.975248e+00</td>\n",
       "      <td>-1.113159e+00</td>\n",
       "      <td>-1.101984e+00</td>\n",
       "      <td>-1.102598e+00</td>\n",
       "      <td>-1.266110e+00</td>\n",
       "      <td>-1.127708e+00</td>\n",
       "      <td>-1.061743e+00</td>\n",
       "      <td>-1.019319e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>9.684676e-01</td>\n",
       "      <td>9.789080e-01</td>\n",
       "      <td>9.779554e-01</td>\n",
       "      <td>1.000000e+00</td>\n",
       "      <td>9.999655e-01</td>\n",
       "      <td>9.999960e-01</td>\n",
       "      <td>9.830774e-01</td>\n",
       "      <td>9.503699e-01</td>\n",
       "      <td>9.395459e-01</td>\n",
       "      <td>9.495398e-01</td>\n",
       "      <td>9.728076e-01</td>\n",
       "      <td>9.857205e-01</td>\n",
       "      <td>9.859677e-01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         svm_linear       svm_rbf           MLP       GPR_rbf  GPR_matern3/2  \\\n",
       "count  2.714000e+03  2.714000e+03  2.714000e+03  2.714000e+03   2.714000e+03   \n",
       "mean  -1.556254e+06 -1.559235e+06 -5.773272e+05 -2.630746e+06  -2.287523e+06   \n",
       "std    6.354855e+06  6.364145e+06  3.154716e+06  1.648690e+07   1.073038e+07   \n",
       "min   -5.184249e+07 -5.154479e+07 -4.307267e+07 -1.806257e+08  -1.182055e+08   \n",
       "25%   -6.539313e+01 -1.675339e+02 -4.900634e+03 -1.808736e+01  -1.808650e+01   \n",
       "50%   -4.690512e+00 -4.936540e+00 -5.194916e+02 -1.178264e+01  -6.957627e+00   \n",
       "75%   -9.358635e-01 -1.178216e+00 -1.031953e+01 -3.085031e+00  -1.302052e+00   \n",
       "max    9.684676e-01  9.789080e-01  9.779554e-01  1.000000e+00   9.999655e-01   \n",
       "\n",
       "       GPR_matern5/2  DecisionTree  RandomForest_10  RandomForest_100  \\\n",
       "count   2.714000e+03  2.714000e+03     2.714000e+03      2.714000e+03   \n",
       "mean   -2.172825e+06 -1.707418e+06    -1.698790e+06     -1.689843e+06   \n",
       "std     1.124609e+07  6.863736e+06     6.835478e+06      6.796690e+06   \n",
       "min    -1.306120e+08 -6.136368e+07    -5.431853e+07     -5.229169e+07   \n",
       "25%    -1.808736e+01 -1.265774e+02    -1.334865e+02     -1.353827e+02   \n",
       "50%    -1.025051e+01 -3.878266e+00    -3.852322e+00     -3.837389e+00   \n",
       "75%    -2.975248e+00 -1.113159e+00    -1.101984e+00     -1.102598e+00   \n",
       "max     9.999960e-01  9.830774e-01     9.503699e-01      9.395459e-01   \n",
       "\n",
       "        AdaBoost_10  AdaBoost_100  ExtraTrees_10  ExtraTrees_100  \n",
       "count  2.714000e+03  2.714000e+03   2.714000e+03    2.714000e+03  \n",
       "mean  -1.728752e+06 -1.697691e+06  -1.731576e+06   -1.735962e+06  \n",
       "std    6.916490e+06  6.825420e+06   6.929674e+06    6.936009e+06  \n",
       "min   -5.332469e+07 -5.370783e+07  -5.237158e+07   -5.258697e+07  \n",
       "25%   -1.656219e+02 -1.442834e+02  -1.344601e+02   -1.357183e+02  \n",
       "50%   -4.051554e+00 -3.950720e+00  -3.746468e+00   -3.761977e+00  \n",
       "75%   -1.266110e+00 -1.127708e+00  -1.061743e+00   -1.019319e+00  \n",
       "max    9.495398e-01  9.728076e-01   9.857205e-01    9.859677e-01  "
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R2_on_optimal.describe()"
   ]
  }
 ],
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