t-SNE demo from Kobak & Behrens 2019 using scikit-learn t-SNE

tsne_demo.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tutorial rewritten without FIt-SNE dependency\n",
    "\n",
    "See original notebook from Dmitry Kobak here: https://github.com/berenslab/rna-seq-tsne/blob/master/demo.ipynb\n",
    "\n",
    "I have substituted fast_tsne with TSNE from scikit-learn.\n",
    "\n",
    "This notebook should run fine in your base Anaconda environment (all the dependencies are installed in Anaconda).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The art of using t-SNE for single-cell transcriptomics. Tutorial\n",
    "\n",
    "This tutorial uses the data set from https://www.nature.com/articles/s41586-018-0654-5.\n",
    "\n",
    "This notebook is self-contained. All functions that one needs to run this notebook are defined below.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "import numpy as np\n",
    "import pylab as plt\n",
    "import seaborn as sns; sns.set()\n",
    "import pandas as pd\n",
    "import pickle\n",
    "import scipy\n",
    "import matplotlib\n",
    "from scipy import sparse\n",
    "import sklearn\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.manifold import MDS\n",
    "from sklearn.manifold import TSNE\n",
    "import sys\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Python version 3.7.6 (default, Jan  8 2020, 20:23:39) [MSC v.1916 64 bit (AMD64)]\n",
      "Numpy 1.18.1\n",
      "Matplotlib 3.1.3\n",
      "Seaborn 0.10.0\n",
      "Pandas 1.0.1\n",
      "Scipy 1.4.1\n",
      "Sklearn 0.22.1\n"
     ]
    }
   ],
   "source": [
    "print('Python version', sys.version)\n",
    "print('Numpy', np.__version__)\n",
    "print('Matplotlib', matplotlib.__version__)\n",
    "print('Seaborn', sns.__version__)\n",
    "print('Pandas', pd.__version__)\n",
    "print('Scipy', scipy.__version__)\n",
    "print('Sklearn', sklearn.__version__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the data\n",
    "Download the data from here: http://celltypes.brain-map.org/rnaseq and unpack. Direct links:\n",
    " * VISp: http://celltypes.brain-map.org/api/v2/well_known_file_download/694413985\n",
    " * ALM: http://celltypes.brain-map.org/api/v2/well_known_file_download/694413179\n",
    " \n",
    "Download the cluster colors and labels (`sample_heatmap_plot_data.csv`), from their github: https://github.com/berenslab/rna-seq-tsne/blob/master/data/tasic-sample_heatmap_plot_data.csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ".............................................. done\n",
      "Wall time: 4min 31s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# Load the Allen institute data. This takes a few minutes\n",
    "\n",
    "# This function is needed because using Pandas to load these files in one go \n",
    "# can eat up a lot of RAM. So we are doing it in chunks, and converting each\n",
    "# chunk to the sparse matrix format on the fly.\n",
    "def sparseload(filenames):\n",
    "    genes = []\n",
    "    sparseblocks = []\n",
    "    areas = []\n",
    "    cells = []\n",
    "    for chunk1,chunk2 in zip(pd.read_csv(filenames[0], chunksize=1000, index_col=0, na_filter=False),\n",
    "                             pd.read_csv(filenames[1], chunksize=1000, index_col=0, na_filter=False)):\n",
    "        if len(cells)==0:\n",
    "            cells = np.concatenate((chunk1.columns, chunk2.columns))\n",
    "            areas = [0]*chunk1.columns.size + [1]*chunk2.columns.size\n",
    "        \n",
    "        genes.extend(list(chunk1.index))\n",
    "        sparseblock1 = sparse.csr_matrix(chunk1.values.astype(float))\n",
    "        sparseblock2 = sparse.csr_matrix(chunk2.values.astype(float))\n",
    "        sparseblock = sparse.hstack((sparseblock1,sparseblock2), format='csr')\n",
    "        sparseblocks.append([sparseblock])\n",
    "        print('.', end='', flush=True)\n",
    "    print(' done')\n",
    "    counts = sparse.bmat(sparseblocks)\n",
    "    return (counts.T, np.array(genes), cells, np.array(areas))\n",
    "\n",
    "######################################################################\n",
    "### PUT THE LOCAL PATH TO THE DATA HERE (wherever you unpacked it)\n",
    "# (put all the csv's into the same folder)\n",
    "root_data = 'C:/DATA/tasic_2018/'\n",
    "\n",
    "filenames = [os.path.join(root_data, 'mouse_VISp_2018-06-14_exon-matrix.csv'),\n",
    "             os.path.join(root_data, 'mouse_ALM_2018-06-14_exon-matrix.csv')]\n",
    "counts, genes, cells, areas = sparseload(filenames)\n",
    "\n",
    "genesDF = pd.read_csv(os.path.join(root_data, 'mouse_VISp_2018-06-14_genes-rows.csv'))\n",
    "ids     = genesDF['gene_entrez_id'].tolist()\n",
    "symbols = genesDF['gene_symbol'].tolist()\n",
    "id2symbol = dict(zip(ids, symbols))\n",
    "genes = np.array([id2symbol[g] for g in genes])\n",
    "\n",
    "clusterInfo = pd.read_csv(os.path.join(root_data, 'tasic-sample_heatmap_plot_data.csv'))\n",
    "goodCells  = clusterInfo['sample_name'].values\n",
    "ids        = clusterInfo['cluster_id'].values\n",
    "labels     = clusterInfo['cluster_label'].values\n",
    "colors     = clusterInfo['cluster_color'].values\n",
    "\n",
    "clusterNames  = np.array([labels[ids==i+1][0] for i in range(np.max(ids))])\n",
    "clusterColors = np.array([colors[ids==i+1][0] for i in range(np.max(ids))])\n",
    "clusters   = np.copy(ids) - 1\n",
    "\n",
    "ind = np.array([np.where(cells==c)[0][0] for c in goodCells])\n",
    "counts = counts[ind, :]\n",
    "\n",
    "tasic2018 = {'counts': counts, 'genes': genes, 'clusters': clusters, 'areas': areas, \n",
    "             'clusterColors': clusterColors, 'clusterNames': clusterNames}\n",
    "counts = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of cells: 23822\n",
      "Number of cells from ALM: 15413\n",
      "Number of cells from VISp: 10068\n",
      "Number of clusters: 133\n",
      "Number of genes: 45768\n",
      "Fraction of zeros in the data matrix: 0.20\n"
     ]
    }
   ],
   "source": [
    "print('Number of cells:', tasic2018['counts'].shape[0])\n",
    "print('Number of cells from ALM:', np.sum(tasic2018['areas']==0))\n",
    "print('Number of cells from VISp:', np.sum(tasic2018['areas']==1))\n",
    "print('Number of clusters:', np.unique(tasic2018['clusters']).size)\n",
    "print('Number of genes:', tasic2018['counts'].shape[1])\n",
    "print('Fraction of zeros in the data matrix: {:.2f}'.format(\n",
    "    tasic2018['counts'].size/np.prod(tasic2018['counts'].shape)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pre-processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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       "    canvas.addClass('mpl-canvas');\n",
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       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
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       "\n",
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       "\n",
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       "\n",
       "\n",
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       "\n",
       "\n",
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       "    };\n",
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       "\n",
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       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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30RyFeFWn/rmnmIRqxDkFAkUlykAwWo7fVbEc2OVSOm5BNWDxOuDz63YKK+scPGKu+OHm8cdSNy92YAg4i4JljdnyfGofiFYotsQ7sKnxvQmkK43lmQqawTBKoE/0YfFzA3ICb+9RYklld2dEPKEdAKCrSvdAgTBgjVKnaBYSBEj3twDNFoJcdktxCNHmMgnF/e0GtxtZIExIhDqB18kWQY/bbG0YPlpN+JnLkF80ccD+kHEXRKseDh5GnP0C8FSkkEXl1JyUoiuPKc1nXd6U3rpfxs0g9w9TslXCUkz5E9XcJQHvXMx0Ei6V2KMFmZRQbS0ctYpQe5cTwu3CvlYZWUs1YuR5IERqRKBMCIiXAcrtcdZLMu9SMjQjygsGqdfJ19OO4gvHF8CrZqUxN2bXQoi7pJgeXOWHI/qJcESpRpAplC4JQvB79df1E4hWZBtqJuWQvsrUur4jWCZ2Qgu1XA0VI2qJ5QnSkZBuhumsF5aykiPEoiu7jQhgaXBQbwVl2tgVUIhOmnW7LDaIDthMV7qm4saufZaTZlaaRmcpBkppRutn5OplIYNqfVTUxnBihcLltHa/P55EF84fscc85O4e7NLQcRdEixvzpLjUb0kWJxMwSXIcxKKGljcVcgXKboRHS/cgw4g1dAzZz3tSm1IHY8c06hCXBRu+qHAfYciJhXmN/3EFCaJaWmKwjs0rtQWLFGLipMy8Vah2o0I3SutoHczBMuMlQt11BYsM1tgpm8z/VTlOl6/cPy0h7Gci9e4V9UzH0TcJcGK09PsBcHiliuQKa6BxRM+w3LV9eTG7O/i54A3XiUbIJYKCfei4lKmLTpu+7uUUlye3DqsJCQoRAuEi2tVQTRUFB5lsVrCDUQeIK+2CCHuipM2rcTG4thmbg5y4qcmY0axV3wcOw8+s33H6dcvJtO2g7ubE/PTHsZyLl7j7uYexlNfQcRdEqx4OoHCXL0gWKLlCsHsKCBdby7NZJpYCBivkZrE/g6ZBlEjq1pyiLmX4jEhNNYBna87f3uXUks0CJbBGRJjpor371ckHtRSDNydZ+VlYsZdp1jFVBIQZq0Cdh58ZvuO069fTKZtB3c3J+anPYzlXLzG3c09jKe+goi7JFjxdAI9JlhasVc8yD0vvxha56yIgqP4HVYuuBIRrzX2uRVxp5EFSxasWFfU+JM67v5eydnH8gEiHgv/Rxod9Y1BLF4VM8UTNuNno+uHMokHtTtvx6OTmRsRMV4tHphs+oQaWbP03Il8AL2XmPjg27dsGXODWr3JaHoRsqKCQBBfOPGwvRJ3b3YpiLhLguXNWXI8qhcWLK1Ji8mf+ef8JqFY/5E5a2j7X7mO1+1lBzy2jBMRMahdtFKJcVaI02p41TVs2lyWQR0zpSY2m0beXJ7zkIi4G9HMus3qWun1pUfQxAffpvHj2K1BLSV5M3OUdcwjEMQXjvnVe1dT4u4N9kHEXRIsb86S41H9QrC0rFpai7v5yeWO1+xVB5By6HJ4M/XJ/YXST24XfhMQigsVJEqMl1LccjBi1axJSJpstvw5a4aiCC/mKNRrryZoVlyMYp9WLFhi4L7WLUaza3WzXizdSG7OW68vJy+coGERC7z5GE5wj+U8gzZWEHGXBCtOT6mXBMssqRKhFS1YkGqAPzG99jH5Bj9vAwL47/rrf5SUe4DKENCOiHeh8DQ2ottMJElmVNjV6zfSphLddGpC5fbLVevB5/YYbuy/XWLpxtjR6MPJCydoWEQD32gQ21jOM2hjOTnvfsVCEiy/7ozBvLwkWFrB7urpapGw4U8uV+K0UB+xTYXF5a4wvxZwQZTTKqQastIaU/vQwfLEz2syygPWK8S9RGuTIhZqYMGyQ1TsECo748Tbv+idrNGP58/JCydoWMRyf5zgHst5Bm2sIOIuCVacnlIvCZaRBUu8WShqYo16+gvfEyr1ccDtx8KichIIPaxzD2+k5oOuYMHpeImxVDb5+SxmKq1rN0XXSlRj58HsWkdNJEuwgGW99w4heJ73xcdAW61UOtwtaRR/5cSiEcQHn9mvvZdEpSrjbnZ/olEv6Lh7eaYj7ZdXuEcTD0mwovENjUGfXhIsreWJpEvUxuKq7mjD6xw4XKiZm9BMXsAYQFtpCLgIIUPBFd3FgHZ1oDvikbRIkd68mStx7RpK69KVCYYigJyVCpV3MZYrUjyWnhQDH9eKy1E9V68efF7stXpMJ8TU6fyrMu5OsXPSPui4e3mm/UiwoolHlSBYubm5tGrVKsrLy6MyVfwMNvyKK65w8n30pK3fCJaWujuXZuAAgWC9+9nmuLNi8fmLFizEQPHbdPicWbFKSljAO8RGkaCZSzTgcz1pA/7lRiA8k30oLGTDcZV3s2TNyIIViWip1eO5pYy3CfoLJ9IXOJr/ujV6cHiNu5drN8Immp97jXs014a+/bqvXuEeTTwCT7C+/PJLuvPOOyk/P1+TXCUkJNDGjRujfaZd799vBAvJnZF3EGrut1zWUVmvlmXLdTCi0KGeNe2sgq109v4fGBkCkeJkRJRWAFkqPXq0XGpBSPKsJW3Av9xQfOfkyk0JBDM3DFFn71tzFWkItaXMqwdfFLY1rrr0Gvdo/svezxvhNe5+xiaacwsi7oEnWJdffjklJSXRvffeS40bN6YQ1KxVpWnT8oTF8VT8RrCMVN553sJ4sWBxsdS0GtUU/S7Eso+vuE2Is8KJCAgKi50qLFQkG/A5Jy1aOQkRbyVatcSYLeQghAVMTXT0/qUV6V9gZgPiI1nKgvjgi4fvute4R/Nf9n7G32vc/YxNNOcWRNwDT7BOOeUUmj59OvXp0yeaZyPmffuNYGlZsDjpQgwTj8WCRWvuksyw24QxB8/EgCBYnVrVZ1Y5xF+hMBfh/h+oWkIpJaVUU6xXWv/SjxScLgqRiiSNE66jmzKVuCwxGbSeRSGSpcGNl6TVB58bY5rYosBXsYp74AGJ0QIl7jECWjVMEHEPPMG6+OKLmYuwX79+3pyaKI3qB4Kl5f6LlCYHUHDSxfMWNqxbnX7fk0tw1ZaUlrF8hlxlyuugd/X4PMi9lBKoyZChbGf11Nkjpa3ZO/d15VRoKbUbpbxRp6kRA+VFQubW0bP64KuqriW38Ob9WMVdHF+SXPu74QR3+6PKlkHEPfAEa8GCBTR79myaOXMmNWvWLDCn2A8ESyuwPb+whOUahNUK8Vhbdh1Q8hACfDHQHQrpKCBWWmXoxe1o7tJMJjXlhwIL1kVZGRSiMqbOzuOsRFeeUbC5eCsQ+QtPeuk/lYJOrb4co01otB58Tm4ler2XVvH1ar5OXjjRPhNeYRKLcZ3gHov5BXWMIOIeeIJ100030fr16+nw4cNUr149Sk1NDTufsJwsW7Ys7s6sHwiWXvLnN5dmMrcalzcQtbAA9IgpyxW3mx7waJuU6D8hUpCs3gc3UJ3ksrCbglyPyujFxgLKKyxYXOHdqI3R4TRDGMzU0RtH/eATg+LNpPLR69fsnMzWM8KJf+4Ub7PjOK3n5IXjNmZO1xJP7Z3gHk/r9Ntcg4h74AkWgtuNyhNPPGFUxXef+4Fg6YHCiVebZnUrWbDQBvFaGb/soVAogd3s1DFgeY45LGxq6xr+llotkYbU30cN13/NFN3F5M1m3HWbx4xUAuLbTp8Vk2vTTkiF+sEnam41um4IE121U8zOyWw9s3OIF/IRxBeO2T3ysp7E3Rv0g4h74AlWNI5KaWkpvfjiizRv3jw6dOgQnXnmmfTQQw9RixYtNIfLysoikLivv/6afd6jRw92q7FJkya2p+dngmVlUWIgPFyBPvEGhi0Bjsx6tVOYq5OLqHKrHL/9x/MRcuFRUWoBnWndGDSTBNouGVC347+zAPvff2fCpmbjtbQsWHq6Xlb23uzazNazMnY81A3iC0fiHg8IeDPHIJ73KkOwvvrqK1q9ejUjROnp6dSlSxfbNwtBrt566y1GmiD98NRTT9HOnTvpo48+omrVqlU6nUOGDKGSkhL65z//yT57+OGHqaioiBAfZrcEgWDB0rXgy60MgivPaU3zv9xKefnFdiGx3Q6WtNIIZrSWTdLowWFdWfzYpg8W0ZlZP1JJr/Op+9ArSZRXQLAYiFZZcTElJCUxKxVcaChMoT0UIlh81IRLnLiebpVZbSzenhM9tQtP0euqUIo3A1oQH3xm1u11HYm7NzsgcZe4u4VA4AlWYWEhjRkzhlauXEmJiYmMXOXk5BCsULAkvfTSS5qkSA9g9Id2EyZMoGuvvZZVA2mDDMTjjz9O/fv3D2uKz7p27UozZsygvn3LXSmfffYZmxPU5TEfO8XPBEsvV6HadZh7tIjl+YPbzS+uQi23IKxVcHeu/mVPWLocpMXhLsGU5s2pKCuLSvPyWAJoTojgQjz8wzpFRNQoZklPt0qLMGlJQYjK8KHUVHLjxqF84dj5hjpvI3F3jqGdHiTudlBz3iaIuAeeYE2dOpXmzp3LrEYgPyBZxcXFzNqEv914441MxsFs+emnn2jw4MH0ySef0Iknnqg0A9lq164dTZ48OayrgoICRsg4AcOH9913H2VmZtLixYs1hU/NzMXPBEtLdBRrEt2BMBh5LcOghbPWnETSJabLQXsuJgripOQlTEggnuA57NYgUgzWrKnoZ2mNr7ZgiQQOau8iYRL75u7GaLjT4vXBFw0szHw33aoTr7i7tX6v+pG4e4N8EHEPPME677zzCC664cOHVzo1//nPf+jtt9+2dItw6dKlNHbsWPrxxx/DbiTecccdLB0PLGLq8vHHH9MjjzxCBw4cYHpPDRs2ZKSvefPmtk+ynwmWWQsWD4LPPlRgGwcvGkLr64U7zw5zD4JQiWruCF5HYTfu3nyDWbUIUvBlZWEK8DyWCXW14prEFDxqzSyxbzGey21ioffgi6T+7sW+qMd0Ozg+1msK4gsn1hjaGU/ibgc1522CiHvgCdZpp53GNLB69uxZ6QR8++23NHLkSPr5559Nn44PP/yQ7rnnHpa/UEy7g7/t3buX5syZE9YXXF/PPfccbdq0iUaMGMFisZ599lkmGwFyV6tWLdNjixVBsA4dOmqrrd8aTf/gZ1q1YY/fpqXMBxYsFqNVzo+oWlKIXpnUlzaOHKHcBjx51iuVfucd7F++nLIXLaTqbdrS0S2bqX7/AVSvb1/aPH4cFWVnU3JFnBb/77ZTn1XG3jVjOh1avar891CImgy5gbVV9837xN/FfsW+7AKcmBii2rWrs/OGc8cLHwe/Yw1aY/G1i/OzOw+r7bwc2+pcterr4e5G37IPfQQk7t6cjiDijucm1uVGSSgDm/BZGTBgAF144YV0++23V5oZiA+sS7BKmS1LlixhfWlZsBCfhVgrsXBX5Oeff66QqYMHDxIsa7B6wUVppwBqWMOCUBZ/8xvNXPCTb+UatDAeM+hUqjN1khLQfuKIm2nbzHKrVSglhXq+95bh1vy5eAntnv8BNR00kNXl/31cv4vD2qLetlmvsGTMKQ0bUpdXZkbsW+xX3ZfhpCxUwDi/zy1fZ/Mh15HWWGtHjKKCrCxT87YwtKwqEZAISASqFAK+JFhvvvkmu+0HUvS3v/2NGjRoQPv27aOFCxfSCy+8wNx9t9xyi+mN4jFYn376aZiLDzFY7du3Z3INYkGc14YNG+i9994L+/ugQYPo1FNPrVTf7ETi2YK1/LtdtPCb7dS2WR3avOsg5eYVsmD3eCr166TSP74rJ1QosODAAoWCm4SwaBkVLQuLntVF/XervxvNJdLnTv5lGe9WJCe4OW3rBHenY1fl9hJ3b3Y/iLgH3oKF24KQR5g/f36YxQcWoIEDB7Kbf1YsQbBSwd04adIkFuyOEukW4axZswixXitWrKCUlBRW/+jRo3TuuefS6NGjadiwYbZOs59jsLAgMQ4Lv0M/CjpSKGqldx5Yzn9yBXhbwLjYqFpySJf4de/QmPp+8rziIqzV+XTKzVhdProQ5K41nUhSCmYTNyNeC9IP/Faiup2b8dSis+kAACAASURBVEd+iI1wO67MxWMSta78gHvUFufjjiXu3mxOEHEPfAwWPypbtmyhjIwMRobq1KlD3bp1o9atW9s6SYiheueddxg5a9q0KdPB2rVrF7OK4Zbi/v37KS0tjQXBIy4LbsozzjiDuQRR4JqEVWvRokVUu3ZtW3PwO8ESbxJigQhkh9wB/28xVyEPdsfPNRv3+MZVCP2r7X/lau5P97wtdNafGZRUVky1u3WnIxvWl6fOqShqOQaRIHBypKVtFYlIiKQJtwnFoHixHaaw74P5bCYNBg4yVFo3Ii/ig2/fsmWawfi2DrGFRm4SRgvDelo1iC8cTwE1ObjE3SRQLlcLIu5VhmC5eRYQqP7MM88woVDcHITO1YMPPsiSSYNonX/++cwteeWVV7Jht27dykjYunXrWGA8RE4nTpzoKPm03wmWngVr084DjEQhEfQtl3Vkli4uNtqpVX1av63czYaE0V4WWNMQ4ibqjyK4nWtLDN8yj+oUlxMqUaKBK7qr9adEggBtrNy1ayypqWMcIyLEP4ecA0ROzSjFo18j8iI++DaNHxdmOYv2HvE1qVMSRXtcP/QfxBeOH3A1moPE3Qih6HweRNwDSbBAcKZNm8ZioiDuGckFKJM9R+fLoterWiOL/476oquQkxuv3IWwXu3cezgsFyEscHBzwsV56oFMOid7HVVLTqTjKlzFkdLHaFmwjERHre6MootVIQehJlh6BM2IuOHBl79qJe2cN59SVbkXrc7Ran0j8me1P6/qG2GsNa8gvnC8wt/KuBJ3K2i5VzeIuAeSYCHPH5TSTzjhBBYrZRRjJZM9u/clMepJrZElJn5WJ1Y26itWn3OZhmRYsIiosLiUkcEhF7ej805vankadl62ZgYxsvbYJSt48G2dMJ7dBnSbFBqtK1pYGY3r9ud2sA/iC8dtXKPRn8Q9Gqga9xlE3ANJsIy3Mv5r+N1FaBZhtbq7aMky20e06+mpu9etVY1ZtMySLL0EzGp3ot563G5vFjfRgpXer79hTJfZfqtSPTtEMYgvnHjYc4m7N7sURNyrBMGCqOeRI0dYYmbcAnz99dfpr7/+oosvvpjFT8VjCQrBEvMT8vgrJH5+Y0mmb7ZF6zYhJ11wGz41prfmXNVK5zy4HcFdoRo1WBsExpu1CkXzpmAksL148NkhJL45MC5NxAvcXZp6XHcjcfdm+4KIe+AJFnSroKB+1VVX0d13382C0aFJhdt7IF7QwkLMVryVoBAsEXce8F5UUkolJWVh8U9e7U9FOBNzCdZITSIE4m/ZdYAlf8ZPbsHiOQPTunSl40aOZtMVcwWCRMFSxXMX4nMxIfTRrVsqJWZWr1nLgmX2tqATwhKtB5/ZG5NIql0VS7Rwr4pYWlmzxN0KWu7VDSLugSdYN910E9Odwi0+5ACEhhX0r0C08H+kvJk3b557pyRGPfmJYOnlHrQCBfqYuySTfJcKQFgEAu6vv+hY3JW47qYz/smU1pHO5qRZs1krRrrWZFBCcjI1vOoa5lpTW7VQT0wYbZVMmI3tMaoXiezwB9/W+Qtp36KFhkTQ7L6b1fwCblWxBPGFEw/7KHH3ZpeCiHvgCRb0p6Bbdc455xDS1SD4HRpWyFG4atUqGjVqFP3www/enCgHo/qJYKlvBuotKxIRE28TOoAl6k0h1ZBWI5lZsFb/Up4/ES7Eh9I2hkkvsETMb81lpEt0AaoD0Uvz88v1s0IhanTdEMvxTWr9K72bjEYWrEhkhz/4Mm4eydTqzbo0zVjgIt28jPpm+nyAIL5wfA45m57E3ZtdCiLugSdY0JyCGxCWq8mTJ9PixYsZseLyDA888AD7Pd6KnwiWWQtWJCKG24ScsPhxL7irkM9NHfg+e1K4lUWUTEC8FRf8VP4eCjHyZVVsNFpuNasWLOBglRwZWdHc3ncjUun2eG73F8QXjtsYRaM/iXs0UDXuM4i4B55gIRVN/fr1aciQIcxahRQ1U6ZMoezsbGbNguL6K68Y540zPh6xreEngmV25WoiJga4i+TKK+0rrANxVnkaIqdqQgVLFuQauAVr5vhzw2DgL3duoeJWHyMpBXQikjC1VcuqW80NkqH14LNDltyYi9mzJuJo1+JmZaxo1A3iCycaOKFPN8+WxD1auxS53yDiHniC9csvv7Agd6SvqVevHr311lvUsmVLZtFCnkLkCezUqZM3J8rBqPFIsNTL1ZNoqFc7haXW8UupWRHcztP4qAPeI0k1WHnwi+QLSu9q96KdF4kdIqTGXevBZ2VdXu1jPMwxEjZBfOFE6yy4cc753CTu0dolSbCcIJtQhgzKDss//vEPuueee6ht27a0Zs0a6tChA9WsWdNRr7gtiHQ16LNGxfX4JUuWsPyACHyPxxIEggW3IEhL88Zp9Ef2ESWxMlTUsw4c9TxdjngukNz5pBPqsqTV+YUlbG5aEg1aL3WzL/pIuQbtnlGt241W+5IvHKuIuVNf4m4eR7PfMTM9StzNoOR+nSDi7jsL1imnnEIvv/wy9ejRg04++WR699136dRTT3V1NyHdAB0sjGE32bKrE7LRWbwTLLgHkXIGuf44URn+5HJ2i5CrpL/72WbFDWcDIlebwG35ysS+LHfiW59uYhISsLRhrqIFa8sdt7KgdTEnIde/MnJV6bkP1TcPxVt1Ri8Wqy5FLdCC+OBz9XBEqTOJe5SANehW4i5xdwsB3xEsiH+iwLr0wQcfsJip9PR0zfUiUP3xxx+PiEVWVhaNHz+eunfvTrfeeisTGUVqHBjb6tatS2+88QazbMVbiXeCJboHufTBqKe/YISK39Tzyk0oxlfx2CtY1R4c1pXGPreikmVNlG/gBItlii4rYzfuoH+lFRCuR454HzyXoKinpQ6KN3KNuBEUL1843jwdJO4Sd28Q8GbUIJ533xGsjIwMFoR+4MAB+uOPP1iAerVq1XQJ1meffRbxNEyYMIG+/fZbRqp69+5NZ599NrVr147w90cffZRq1apFM2fO9OZEORg13gmWGPAOGOB64+Kd+AlVd7jhvCjijUFOsDiJWvDlVmVeIF2/78lliZ97H9xAra+6kk036713qKywkFmxuP4VX4fosoO4aHF2NrtJyAtuG0I8FFYwTrBECxbqiervZoLmRQzNyjqIbYL44PPiXFkdU+JuFTF36kvc3cHRai9BxN13BEvclPbt2zPVdScuQgSz33fffTRgwAD6/vvv6brrrqOXXnqJ6WJ98cUXTN197dq1Vs+C5/XjnWCJAKrlG7iVSFFRTyCqkZLkCeFComeehJrPB3+77sKT2BJAuG7MfJdqFx3TslLU2gXRUb7eTSNvVgRJcUMQli1FC6tC3V0kW2qRTT2LlJEli/dptp4kWJ5/xaUek0dbEMQXvUdQWho2iLj7mmDt3r2bGjVqRMnJyUyNHcHqcOvhd7MFgqKQYUDOQQiOvvrqqyx4PiUlhb755hsaO3Ysfffdd2a78029eCJYejpZCHLP+GUPhUIJlFotkZCDEImTFYJFpCi7eyndoLXp0L3i8zz9YCZdtC+DEipcgtVbt6mk4M772PHoZCrYvp1SWrakFg9MZn+OZKEye+CMYrF4P2brSYJlFvno1QviCyd6aLnXs8TdPSyt9BRE3H1NsLA5sC4hzc3PP//M4qZQYNEaN24cC1I3KpdffjldcsklNHz4cGbFOuGEExTdq0mTJtHmzZtp/vz5Rt347vN4Ilh6AqMjpixnQe4o4o08vduFftkEbsES3YXd87bQhQWZShoZPS0rIwuS2VuIkYiSHRIVCdsgPvj8cpYk7v7bCXnevdmTIOLua4IFl94NN9zASFH//v2pQYMGtHfvXlq0aBHBuoUA9dNPPz3iafj4449ZvFVqaiqzguGGImKxBg8eTBs2bKCnn36aLr30Um9OlINR44lgGVmwkpNCdPX5bZn1CkUkZFwSwQFUUWkKi1rXkxszCxw4IrSyXrjzbDYWt0iV5uUpge48x6DVmCn0p0XKIhE1IxJnFZAgPvisYuBFfYm7F6jLVDneoB5M3H1NsECuQqEQEwNNTExU9h0CobBI4Rbh7NnliXUjFbgA8f9u3bpR586dWVUE0vfq1Yv69Olj1NyXn8cTwdICUCvIncsdiJ+JViK/bQRIFdyaCNDH3OEqFGOq+I0/uAwR0I6fRzasP3aOjxzRzOuntkCZtWrxjqUFy28nxd58JMGyh5vTVhJ3pwjaax9E3H1NsGCdmjp1KvXtG57nDduH24MTJ060HKBeUFDAbiWCnMVziXeCJVqpsA+QZIA8QnFJKbMM3XJZR7Y9ol6WX/aLB75zvS5ueeOWIz0pBXH+6puDYjC7KPXQ6PqhlhNAm8HJCgkL4oPPDEZe15G4e7MDEneJu1sI+JpgnXXWWfTggw/SRRddVGm9n3zyCd1///2mAtS3bdtG//73v1lQOwLl582bx/7funVrGjp0qFtYxrSfeCdYWhas/YcKlKB2kBfuOty084DiilODrM4RGItNEG8WcvkGjHv0rf9Q6wO/Ue2u3ei4kaOVqYDMKDcLExKIJ3/mAqQUCpGYc1AhWBW3Cts8P831ZandiJEIl3zhuA6/qQ4l7qZgcr2SxN11SE11GETcfU2wbr/9dtq1axeLtRLT5YAkwX2INDeQXIhUNm7cSNdffz3T04IGFnIRvv/++/Tf//6X5s6dy4RKBw4caOoA+KlSvBMsLSx5cDsPfEcdEJjqHkk0aM2xWnKIiopKFSKIOvhbYVEpjd4+n+oUl+tX8QJdK1in1Clr1HFaIslihOzNN1j8FgRLzVixrFikMDd1/UhxW0F88Pnpu6w3F4m7N7skcZe4u4WArwnWjh076Morr2QuPSi6g1BBmR36VXD1gSxBKytSGTZsGEvqzGO1kNgZtwY7duxI//znP2n9+vVMMT7eShAJFt8DLt/AE1vCdQhrVlFxqeepc2C9OqFRLdr+Vy4Ta4c+V15+MSNcnQ9m0gX5mZRckMeERlF4ehw1gRFT6pQVF1dK7MwIWcbqsD7cUGXXO+eR+j604gvKWbyI0vv1p9pnnxu1r4pVkhi1ifikY/mi92YjJO4Sd7cQ8DXBwiKRpPmFF15g2lUHDx6kOnXqME2r2267jdq0aWOIA4Lan3nmGRbHVVJSwogVJ1hQeB8zZgytW7fOsB+/VQgiweIWrLppKXQgt4DFyUHkE6SmtLQszGrk5X6ILkLIS0B5HkmreezY5jEjFYLVaMgNzIKlJg9iOpyaHTtR7to1lNalq+Ja1JJ5cCOvoJb1ygjL3yaOp6LsbEquX59OnDLVqLrtz92+/Wh7IlFoaIc8yhd9FDbCRJcSdxMgRaFKEHH3PcFyuo/IQfjQQw8xKQY1wVq8eDFNnjyZVq8utxTEU4kXgqUn0aCFNU/2zD9DfBUSKouxWV7sEYRQQfDUhQe54+/8JiEC3tW5BNWkBr8jHQ4KXIhasVhWbw5aIU5WiYy0YDk/dVYxx4hBfOE4RzL6PUjco4+x1ghBxD3wBOuuu+6iX375hebMmcNcjLBgLViwgFq0aEFwHzZr1owpvMdbiReCpScyqoX3qKlfsFgmXkCuQGLSalRjLjmx4LPcvCLmNox1wZxqVEg0gFCp1ygqs4NAofAgd8RnlR49GpYuR/ycuxTtrMnsS9yqNSWIDz47+DppYxVzSbCcoO2srTzvzvCz2zqIuAeeYP3555909dVX06FDh1i81o8//shcjL/99htThn/77beZkGm8lXghWNztJ0ov6GGNuqt/2aN8zG8IKnpTq3ZQQVEJHc4rUgLLvdo3uAahfaVOUr1l1wH29xbvPMMSOYMwoeC/UZAAmsdnsZdo/fpM/V20aKnzD5pdo52XuJm+g/jgM7Nur+tI3L3ZAYm7xN0tBAJPsABUTk4Os2CtWrWKDhw4QGlpaYxk3XTTTSzXYTyWeCFYVixYvC63EPGgdgS5p9VIpgG9T6RFq3ZQVs7RmG9ZyyZp9Ef2EcXCpo4L44H4R/KLWdqf+zsUKKSJx1hRaalyw7CsqKiccFXk1SzVER0VF2qVQFmtrwdqrF84bs075odEZ0C764k17n7By+t5SNy92YEg4h54gjVz5kw6//zzqW3btt6cmiiNGi8Ey0oMlroufoeSO7+lB0sWCIwXxYzeFuaHpNVc1V3UvuJECj9BrpgVC9cQy8oY6Qqlpip5DPXir3h/Zt2IZl2GRnjG4sEnrpnHpJldp9H8vf7c7j7EAnevsfHj+BJ3b3YliLj7mmBNmzaNyTQcd9xxtne8S5cu7BYhNLCCVOKFYDnFnFu10A+sRIUexFxhbPHmIF8TSFeLJmm0469cQiA8yBVS5yAuS7kFqAVABbGCuzAxLU0hVryqliK8nihpJHztWk54n7x9g/4DqPWgAZSTc4SKo4S/SELgMsV68dOuu9TpuXOzvd19COILx01co9WXxD1ayEbuN4i4+5pgIXcgREVxExBEC4ruKSkplnb/73//O/Xr14/lLgxSCRLB0rJc8dimtb/uZVINjGBVCHqKBKfy3b7Y7LKYJkdM58OV3XleQuQfzF2TUS4aihIKMTkG5CYEgUBRkwn+Qi7NzyfuOvSCdHDSA3mGbrNnRZVg2SUhsdltb0YJ4gvHGyStjSpxt4aXW7WDiLuvCVZhYSEtW7aMqa5//fXXVL16dSa3AOV15Ck0U1588UWCmxB6WHATQtFdLNBauvXWW810pdSBcCn6RbodBM+feeaZTAoCNxO1SlFREUvVg3Xk5uYSxE6R5ufkk0+2NK5YOUgESx2nxX8HWRHVEUQrEqxZM+8+l25+crltDJ00RExWbl6hEuiOXIq8IAbrqTG9Fe0rnuQZhAlxWGlCKh23tK2crIW31UsyHQsLlhvzD1ofQXzhxMMeSdy92aUg4u5rgiVu8969e+l///sfQbsKsgstW7ZkVi38X02axHZGSu8gWEinY6WAXEFF/oknnqDGjRvTU089RTt37qSPPvqIqc6rC8jU8uXLWX3cWIQsxA8//MDWgoB7OyVIBEt905BbtCDguW5zlhJYLsZBcRV1r2KyRDLFZST4nNRuQh5jVbx/v5L+JqlePUMLlugiU0s/RMN1pkf2gvjgs/Odi3UbiXusES8fT+IucXcLgbghWFgwLFpffvklvf7660zZHeQoMTGRWbQmTpxItWrVcgsX3X4whx49etCECRPo2muvZfVgxerTpw/La9i/f7nbhxcQrwsuuIDlTES6H17/iiuuoMcee4x69uxpa85BIlhjn1vBgtf5bUEEiSOOiRdOuNqeUJdWbTgm42ALOJcbde/QmKm4c0sbt15hGLWrj0k0FBdTQlISC3LXC+LWikfi7kL2Aqhfn1pFQVFdz00nXzguHxqT3UncTQLlcjWJu8uAmuwuiLjHBcHKyMigDz/8kJYsWUJ5eXmM4CC26pxzzmGE65FHHqFTTjmFXn755YhbCe0rkCFYvCAwaqf89NNPNHjwYPrkk0/oxBNPVLoA2WrXrh1ThhcLdLYQZA+1+FAoZGdIzTZBJFjcQsVJihibBRA+XrWD0mun0padB1zD0WlHPFVOxi97KgW68761XG+RdK+0btRpJZB2Onez7d148MkYK220I+HiBu5m91jWO4aAxN2b0xBE3H1NsOBKW7hwIUEsFDcJuUvw+OOPDzsBqAerll5OwTfffJNmzJhB2RVij2iMPsaPH89iuqyUpUuX0tixY5lgaWpqqtL0jjvuoPz8fGapEgvcgrC2jRw5kmbNmkV79uyhDh060KRJk6h169ZWhg6rGySCJboEIdQJ1yB+5heWMMsWSAwK4pwQl5WU6N1tQnETEBN23YUnKdY2tY4XdxVqvUTNXt33AzFx48Fndr22vxBx2jASLm7gHqeweDptibs38AcRd18TrFNPPZW51wYNGkS9evViLkGtgkD43bt304033ljpY5Crf/3rX0wLC7cQYb3at28fs0DB+oVE0hjDbIEl7Z577mFxW6JFCn9DnBgETcWC+CtY3kDoUKd27dqM7H3//ff08ccfR4wfizQnEKxDh2IvuGkWJyf1xr2wkrIP5hPTlUpJogG9WrLuXlv8K0v4nJiYQGWlZWEB8E7Gs9O2R8fGrBksV906NKYxA0+h5d/totc/+fWYu7BOKj079izaPH4cS5aMG4RNhtxA9fr2pf3Ll1P2ooVUv/8A9jsven/X+1ysz0ioRp921hdGJBNDVLt2dXbecO7sFKN12ekzCG0i4ZLoAu5BwCjWa5C4xxrx8vGCiDuem1iXGyWhDLlnXCwHDx6kOnXqUFZWFssjiIK/waJlFLzOpwFSddZZZ9GDDz5YaWb4288//0wffPCB6VmDLN1+++2aFizEZ4E8iQUuQ7gJQaa4xQqWLrg3//GPf9CIESNMjy1WBNR6hNNWhx42WvzNbzRv+WYa3Lct9et1IuH3//xvAxUWlVAf5Pob0oXN7tp/fszS5Pih1KqRHDaXMYNOZWs4uWU9Wr3+TyooKqWU5BANv6wTdT64ibbNeoXdIExp2JC6vDJTWULm08/Svq+/oQa9e1G7u8fR2hGjqCArS6n35+IltHv+B9R00EA6rt/FtPr6G6n48GFKqlWLur/5Wlh9dCq2tYKTOA7aiWNa6UfWlQhIBCQCEgH3EXCdYEHSAGQGhAoWJ5QVK1Ywd1vfvn1p6tSpTLohUjnttNNo+vTp1Lt370rVIP0wZswYRpbMFh6D9emnn1Lz5s2VZojBAumDXINYIBEBK9mGDRvC/o4YMsg1qGO2zM4jKBYsWH24ZQoWqxl3l18EGPbYMmYJgkvwhkva08JvttNJJ9SlLbsPepIqx2hfuKRE/TrlbmNY4FDOKtxG5x3ZSNXbtKWjWzYzixX7vMLS9Ncbryk3Czu8+hrtmjGdDq3JoNpdu1Gz0WMU6xe0qNpOfZZ+vXU008ZCTFb7aTPCLGFiv6JVLNLcuQWlpEJzC+OgwOLGxwzivyyN9tMPn0vcvdkFibvE3S0EfG3BgoUJ8gb4CUsUCqxEK1euZMQEN/ZwezBSGTJkCCMyiHlSF8gtgLC99957pvHE+Lj5h/4Q7I4S6Rbh2rVr6frrr6f333+fBeKjcAvWqFGjWD5EOyUoMViiUjsI1gt3livui9INiMdC/BXIy5wHL6ZBExeGKbrXSE2io/nFLMi8tKxM0fS0g6uTNlxkFH0gxQ/K6B0LKCn3gHLzDzFVYsqbktxcdqMQNwwbXnVN2Ge4KainTQVtLYiV8p9mVM8jxYKJ6Xowb1H81K3YCD/EkznZ31i3dQv3WM873seTuHuzg0HE3dcxWHDtgUANGFD+r36xQLTzueeeoy+++CLiaYCV6q677qILL7yQLrvsMpbcGQmfQdwQL3XfffeFBZsjCbRRQVD9O++8w2QZmjZtynSwdu3axQLyIRuxf/9+pm/Fg+BBohDcjtuOdevWZaKjIF7QzapXr57RcJqfB4Vg8XyDWCQPClcvmAfBI9nztr9yacW63awKFx5VC5LaAtRGI4ybnpZCXAcLXUCAtM9pxxOU6CE30X7N/yh37Rqm3n7cyNFhKXRSWrakoqwsNrKYEBq/47MWDxy7karWwRJT58D1aEa6QSug2gzpcevBJwPdrR0yt3C3NqqsLXH35gwEEXdfEyyotYNEIV5JXb766iu67bbbDN17YqyWGLMkhovh7zymyYzoaElJCZNeWLBgAbNGgZTBygbpBxAtBNTj9iBuPaIg3c/TTz/N3Jyof8YZZzBi16ZNG9snOV4JlpXkz2pwVvz4B81Z/KvyZ1x5SPY4P2FpaRkLvBcLbj0yi1vtFLpp8zxmwSpOq0sdnn2OWaSUJNCQ7aggR9ySpfQTCtFJs2Yrv4q5DUXJBhAznnbHSHzUDJnSOpBuPfjsjm/7SxLnDd3CPc5hiPn0Je4xh5wNGETcfU2w4N6DhQcWH3UZN24cuzlo5N6D/pSVYHDkP4yHEq8ES50WR49waf19woxvlNgm7FG92im0X0hRE6t9g0syv6BY8xYjl27gFqzf/vcxnfLnD/TzcZ3p5of+wabIiYbo5svNWH1s+hX5CmHx4kW0YOFvPEehHcFRq0QniA++WJ0VJ+NI3J2gZ7+txN0+dk5aBhF3XxMsuPdw0w5WKLj4ILEA99tnn33GgsYRQH722eUxO3oFMVNa6Wt4/W3btlGrVq2cnAtP2sYrwVITJzXh4mBq/X3Wwg2KLMLIAR1pxJTlCskR8xTGekOgHgJLWnJiSHFzqrW9uDq9FrnZcsetjDCh8FgsuAD14qusEiQ1HlZddZEefE7n4rR9rPc6luMF8YUTS/zsjiVxt4ucs3ZBxN3XBAvbBa0qWLCQf5C78ZAkGbcLeeqZSNuKQHjcNtSSdZg9ezbrG3kB463EK8FS4xzJgsUDxXlsFrdgIdj9qdG96O7pXzMLFixZBRWipF7tI1Lm3HJZRzY81vTm0kxG/sTUOfiMkxsxqByq7oxgJSRQo+uHsgDz4grdLLPxVVbWbZXURHrwWSVrTsmelXXGe12rLxyr+xrv+ERr/lZxj9Y8qlq/QcTd9wSLH7KCggIWnI7g8Ro1apg+e3/7299ox44dBKV1rjmF/IC4Bfjdd99Rv379WPLleCvxSrCsxGCprViIwVq0agf179GCzj7teBr+5PKw+KdqyeWCboVF9sQwnZ4B3IIEGYR7EDFYKAh6b7bjB+r1ZwaFSoopKT2dig8cCMtHiBuA/Nbe0U2ZlLsmgxKSk6lW59NNx1dFmrudF++ORydTwfbtLNi+9eRHKD29JuXkHKHi4nBs7fQtztVpe6d75uf2Vl84Tsmun7FwY25mz5pV3N2Ym+xDxmAZnQHXdbD4gBAXPXr0KJWWVn5xqtPmqCcJFyEI1GuvvUZdunRhLsVp06ZReno606zSCqA3WqgfPo8HgqUZRzX9ayUA/Kkx4dpk6vpaz+nXCwAAIABJREFUuQivvuAk6nFyI5q24Gda/UvlxM9IGF2oIgGx3C9YrOAO5BYs3DS85bf5VKe43AXIC0/8zG8X8od/8f795bpYqiB3q2vQymco3jQ0etlsGjFMGbLDnNd1CZbVecn65hGw+qI32lPzIwezplkCahX3YKIV+1UFEXdfW7C2b9/OLE2RhEDN3PrDUYGcA0RF4WaEixEpdIxESmN/xMyP6GeCxYmRmEuQk6lIFiy9eCygwj9rmF6dWbDE24Ri/JXXNwuHXtyObSJ3bzasW53qZa6lC/atoVBZKSVBliMhgcRbg2ndujNLFdyCauJl/kSE1xRfJqKFjN80NHrZmLVg2Z1ftNsFgWw4feEEAQM3z4lZPJzi7uacq1JfQcTd1wRr+PDhLJh96NCh1KRJk7Dcf/zgDRw40PAMIhXO//3f/zELGBTdFy9eTD169GC6VCeccIJhez9W8DPB4mSI5RKslsgsOued3jQijEZ6WIyYrdpBHVvVp6/W7VZcg4h9gsI7CE1efjH7O6xIuXlFMbdkcaFUkShi0XAX3vr7AkorPKzoVYmB7bBWNbpuSJi4p9MzZ/QyMfpcHJ8/+LbOX0j7Fi0kM6KmTufvtL0RgXTafyzaO33hBAGDWOCsHsMp7l7MOQhjBhF3XxMspLl57LHHCHFUdgsSQGdkZDBXIJI+I6fht99+y3SoENM1duxYuvnmm+1271k7PxMsK3FWHMBI1iteB1/AMc98qeQA5DFP3B0nEjoQriP5xTHdH8SAXd23bZgFq1Or+rRuUxZ1yN5IPXPWU2nv86n70CuZVEPWe+9QWVERpXXtxkRInRSRMKEfUYndTr9ifw0uuIC5CDNuHslS6JgRNbUzppttrBBIO+NGu3/MyekLJxZztIOd39s4xd3v6/Pr/IKIu68JFqxNTz75JPXp08f2mYAI6L333quIfvKOIP4JJXZYt8y6GW1PIgoN/Uyw7CzXDClDkPtrn/yqpMJBAHluXqESUI7bhE+P6c3S7GjFZ9mZl9U2/NagSBhzcgvYjcLOBzOp98ENdHznjkrwOidDVlLeaM1JtFbgc7gbnRAhsb+Tpj7LCJZowXKDxFnFNhb1zZKSWFiHgvjCicUeOh1D4u4UQXvtg4i7rwkW3HrQqZoxY4YlsVBxe//66y/mXtQryEVopKVl77hEt1XQCJYeWiLxUluleO6/N5ZkKs3hMow1uQqLAUMQWBlRiyZplHXgKJtXSrVEJicxent5sHtZQgIllJUxAsTJENyEZiUZtEhALCxY4i3CWBCM6H6DtHs3uy6zRIyPYrU+2gXxhePFnlodU+JuFTF36gcRd18TrBdeeIFef/11qlOnDkuUzHP78e2EQjusUGbK1q1bCcKle/fuZTFdkGqANlatWrXMNPddnapCsLglCGQqKbH8hiCEPXHRjuf9EwmWFxuFeWz/KzdsaPAszBOWK15OP5hJPXLWU1ZaY2ofOshimVAiiYpqrccsCXALC60Hnx3C4NZ8otlPtNZlZ8+C+MKJ5t651bfE3S0krfUTRNx9TbD69u0bcYdAsKDqHqkgbyDkGObPn68Ilb7//vssNyBI1ty5cyNauKwdkdjV9jPBMuPuM4uUKNqJGKuEUAIdyStSgtnRD9ecMttnLOppKcsjRiutenJY0P+fs2aEJYPWmpv6pY/fIU6K0mDgIDLKQeh0vUF88DnFxGp7O8RN4m4VZXfqS9zdwdFqL0HE3dcEy+oGadV/8cUX6eWXX2bJmKH8jrgukK3ExEQm24AYrSlTprgxVEz78DPBMhOwbgUsTtjanlCXpcrhViFoXp1+UkPasusApdWoVsmKZGUMN+syqYjkUCXBU8wXKXW4Mj3G3DTyZuYaVOteGelYKcmfK24gqkmW3gtdvujd3Ono9hXEF050EXOnd4m7Ozha7SWIuMcFwYK8wqZNm5h774wzzqDi4mKqW7euqf0777zzCEmjIfkAa1bHjh0ZwcLP//73v8yStXLlSlN9+amSnwmWmxYsYK7W1RL3gUsjiDIPsb49qHUuQKaKS0oZGYR7s3pKknKrkc8Z7US9qRYPTFa6MtKxAlHa+9Zc3bgtPZdUrF1VdghdtL9nfpyTuGY+vwb9B1DrQQM0FfSjjVFV7j+IL/p42M8g4u57gvXhhx+yXIIgV3AJwr2H2Kzk5GT290iJnHGoELv10ksvUa9evSoRLMg13HLLLfTTTz/Fw/kLm6OfCZYTMHEDcM3GPdT15GO5/URdrRrVk2n/wXwqqTBjwVo05OJ2SnoakBmcE/65k7k4aYt5devQmFnXoAOGMndJJnNtigRLj/CYsUChTz05BjPtzboW1Q8+KwTFKqGz0rfd/bE6J7vj2G3H55dcvz51mz1LEiy7QNpsF8QXvU0oYtosiLj7mmB9/PHHdNddd9Fll11GsESNGzeOWZ8yMzPp4YcfpptuuonuvPPOiIcAGlpwC0KqQW3Bev7552nZsmW0cOHCmB4kNwYLKsEaMWW5YvV5ZWJ5DB63YA3ofSINuqAdXXP/ojCNK3V6GhCYowXFYQHmbmButQ8u2cBJY/PG5bISovCqOp4qEmnCZ16QA/WDz8ocrBImK31b3Q9eP9YxbHrzNCLB0oJld4edtQvii94ZIrFpHUTcfU2wQKzgEpw8eXIlcoS4qvfee48+/fTTiLs/b948Fn917bXXMpI2cuRIZvmCfAMIFlLx4LN4K/FEsKy4DLUsWHxv+Bdw/rJMev2TXxmBgqWoRkWS5a9+/IPFYfnhdiGXkICCvRZpFM9bJA0rrQD3SCKiZgmN2XqYpxMLltH3yur6jPoz+3ksiJzRXIzmEMQXjhEmfvhc4u7NLgQRd18TLLj3Zs6cySxQausT1NlHjBhhyr0HFyH6yc/PZzcJUeBiRPs77rjDm9PkcNR4IlhuBb1DaHTRqh0sF+HGHTnMlYgvZWFRKXO7ibFX+L2opLRSoLlD2E03R05CkCuQy3c/20xFxaXMZXjLZR0r9RFJw8roJazuTC/4XU1krPQb6cFnhahpgWdlHlYtQZE2y+m8TR+ECBWN5hDEF44buEW7D4l7tBHW7j+IuPuaYOHWH9LY3HDDDZUI1ttvv02zZs2izz//3NRpgHL7unXrWHqc2rVrE9LwmA2UNzVAjCvFE8EysmAZfc6hnTDjG8o+mE/166QyISzIM/D0OAcOF1aKu0KgOXSzvCggWJt2HlBET8Vg/I+/3W4qPyPmbfQSVq9NL/hdTWSs9BvpweeUIFmZh94+Op2DF+fDzJhBfOGYWbfXdSTu3uxAEHH3NcGCkjvcgI8++ijLJXj66afTggULWNLm0aNHsxyFEydO9OY0eDxqPBEsI6jMWri4Bav18bXp563ZrFsueTD8yeVKAmhoUKF4GehePgMm6s6KViLop8b01oTGKenQau+kz2hasIzOhpnPnazNTP9e1QniC8crLK2MK3G3gpZ7dYOIu68JVmFhIdOqgoxCKBRixKpmzZqUl5dHXbp0YfpWanV397bb3z0FiWCZtWDxLyAPcufJnmEREnWwKrLVeL6BXGwUP7u0b8RuFLZpVjfspxjwzidsJNEgLswNcmHURxAffJ4fDhMTkLibACkKVSTuUQDVRJdBxN3XBIvvCVLcQFLh4MGDlJaWRt26dWMWLVzHr6olSATL7B6qCRYPcEfsFW7sgbzEOg9hpLnDkMZFUXmMmPrGI79pqCZNUGovKypi/4c7NFSzJoVSU1l6HVFeQcs9ZvWWnJGLLYgPPrNnzst6Endv0Je4S9zdQiAuCJZbiw1SP1WRYIkuQq7oDuIiFj+IjIrEis+Nq7uXlJQprkt+0xA5CtX5CPF7cXa5GxQq76Hq1an0yBGWILrVlKnKkrWsT0qgO24AquprfQekBcufTwb5ovdmXyTuEne3EPA1wUKaG6Ny2223GVUJ5OdVkWDxIHeRVCEGCy5CHvDO9a+8chPWq51Ch/OKTAXXcxdni3eeKSdToZCizA5LlZhvEIc4kjyDlgUMf3MjV6F84XjzCJG4S9y9QcCbUYN43n1NsNq3b6+707Vq1aJGjRoRxEiNCmK5EBy/evVqOnToEKWnp7MYroEDB1JKSopRc19+HgSCZTb2im8At2DlHS1ikgzcvSamyWlYt7qnOQnNEDvUCYXK1ea7522hvvvWMldgUno6FR84QGldutJxI0f75twF8cHnG3AjTETi7s0uSdwl7m4h4GuCpbVIBLh/9913THwUtwt79uwZEQsQKsg8/Prrr3T88cdTw4YNKSsri/744w9q27YtvfXWWyyuK95KEAiWmduDIglDsDh0sHCLcPPO8hQ00JpC4X1x95ya6PDYp7lLMxHSFLXCwwIjjcE0uopLmZVr9Pb5VKf4SPl8BAuW6AaM2mRNdixfOCaBcrmaxN1lQE12J3E3CZTL1YKIe9wRLL6nsEi98cYb9MEHH0Tc5oceeoiWLFlCcDfCasXL2rVr6fbbb6dLL72UHnjgAZePSvS7iweCZWShMvpcJE4gSJSQoOhgXdqjBXMNcpIFBXgxwF2MgwIxS62WSGrrFtx5+w8VRH+zNEbgGl2dD2bSOdnrqFpyItU97VQ6unULVW/dhv1UB7Q7nahRrJVe/+KDb9+yZZXixczmNHQ6/6rWPogvnHjYQ4m7N7sURNzjlmCZTdR81llnEeK0rrnmmkqn5p133qHp06fTihUrvDlRDkaNB4JlxkJlBIGWBQtK7vM+38LchGp9Ka3+zLjtjObhxudI4YNUPiiwdIlWLvE2odGtPrtEyahfMwRr0/hxleLFtKxtdufoFOdI43o1J7trCuILxy4WsWwncY8l2sfGCiLucUewkOrmzz//ZFYn/Fy8eHHE0wBxUlivkG5HXSD/AMHSn376yZsT5WDUeCBYZixUZiFgfa3aQVdfcBL1OLkRjX76CyU1DkhWp1b1wyxYXIPKbP/RrgeSB4sZgvHVhQe7c3enERGwS5SM+o1EsPJXraSd8+ZTaoV1zcjKZneOTvch0rhezcnumoL4wrGLRSzbSdxjibYkWGbRTijjif7MtjCohyB3Pa0rDAWldySEjlQGDRrEFOC13ICPPPIIrVmzhhYuXOjSjGPXTTwQLDfR4NawhunVaeqtvenTNTvpzaWZis4UXIJdT27MRDzhNkR5Y0mmm1Nw1BcXG4W8BELARAuWlhZWpMH+nDWDctdkUEJyMjW86powXSytdnaJFe8LL5ytE8ZTQVaWKdkHtHM6pl2wpQXLLnKynXje09NrUk7OESr2KNVWVdyNIBJbX1uwXnjhBU2ChRuEyFPYsmX5izRSwS3Du+66i6666ioaMGAANWjQgPbt28dI1bx581iw/NVXX23Uje8+r2oES23BwoOP3x7k2lewEg2pSLKMDRPT5/hlA7t3KCeBuUeLlETU1ZJDdHXftkrAPp+rHlmwqnPlJA8h5oIHH7dgpauETv2CaxDnEcQXTjzsk8Tdm10KIu6+JlhubTPirGbOnElFUMVGfriyMqpWrRqNHDmSxWdZLUjZA7cjCBpuKZ555pmEYPoWLVoYdgVid/fdd9Nnn31GzZo1M6yvVyHoBEvLvaj3BRz73ArFXShagxD4zi1GtoF2uSEnge9+tjlMKwtyDRcWZIYFtuu5tLSU2plVa+0aTYkHNVGz6ioL4oPP5W2NSncS96jAatipxN0QoqhUCCLuviZYkFKwUiDDoC5bt26l1q1bMyL0ww8/sHQ7derUodNOO439tFNAriDv8MQTT1Djxo3pqaeeop07d9JHH33EiJte2b17N11++eWUm5srCRYRs0CJNwFF3LQC5PW+gKIOFk/+zPvi/UTaZ5Cebh0ax4yMIeYqL79YSQSNuY3ZMZ9qF4UrtauJUST316aRNzORUhSk1YkkMGrVfRfEB5+d732s20jcY414+XgSd4m7Wwj4mmBFisHSAmDjxo2V/gxX4p133klXXHGFK5hBtLRHjx40YcIEuvbaa1mfIG99+vShxx9/nPr37685DqxeQ4YMoeTkZFq1apUkWIJ2lVYMkhULlhpwtIWFCFpTLZqk0Y6/csPIjJfyDJgrl2hA3Fjzxmn0+55curz6n9Rx9/cRpRkiWZ6YBStjtQIFSFab56eFQcOJlV6Auh7xki8cVx4dljuRuFuGzJUGEndXYLTcSRBx9zXB+uSTT5jrrWPHjiyYHdainJwcWr58Obs9iBuATZuWC02iQJldXSDT8Nhjj7Hk0G4U3DgcPHgwYW4nnnii0iXIVrt27VhMl1aBm/Lzzz+ncePG0U033SQJloEFSwtD8QuIIHfR+sUJGRI+r9m4p1Lwu55GlhtnwmofYqqfopJSFouFOKy06smKrpcW2TFDkPa++YaSHFpNsJTYLVVKHp6Ch+c/VCeW9suDz6rlzeq++K2+X3D3Gy7Rno/EPdoIa/cfRNx9TbBGjRrF0trAFacu+NvmzZtp9uzZEU8D4qRmzZpF6AvK7QhyVxct16Jep0uXLqWxY8fSjz/+SKmpqUq1O+64g/Lz8+mll16q1BSk7Oabb6b333+f9uzZw5TlZQyW9S+x+AUc9++vmOQBt37xOCy15hUPKufyCPgcVi2uR6WeBW73tWis/7n1WVduIc6Jz5f/5OsRrVUQHBXzEEayZJm5RSdasDipQlJoPk5pfj5LLM2JVoP+A6j1oAGe36qyGjvmxl552UcQXzhe4ml2bIm7WaTcrRdE3H1NsDp37kzTpk3T1bAaM2YMIzqRCqxfJSUlrIqe5IOWa1Gvzw8//JDuueceQpsQLAEVBX/bu3cvzZkzJ6wpUvvAPQmCBbFT5EN0i2AdOnTU3RPu894SE0NUu3Z1wro/zfidFn6znQb0akl9z2ym6GKJ+lewFKWmJFHtGsnMTYj9R/6/SAVEJzkpZCpZs1244BpEzNfmXQepbbM6YT/5evYvX07ZixZS/f4D2M+i7GxKrl+f2k59lsTPMAder17fvqamFKk9Pts7f57SD4hWcv0G1G32Swx3XK7wqojzNrtWr+bqxrjiefcSdzfWEk99SNy92a0g4o73FdblRnFdB+u8886jv//973TrrbdWmh80sJYtW0awKEUqRql00FbLtajXJ9LuIMWOlgUL8VkzZswIa3rfffcxWQhY0VDcIli4CalHGN3YTD/2sfib32je8s00uG9b6ter3D3L/3Zyy3r0feZeOnK0iCmkg8SEEhKo2IBQebVOWMpaN6tL23YdoLM6N6UJQ46lcVLP6c/FS+j3uW+xPzcfch0d1+9ipcraEaOYPlVKw4bU5ZWZlPn0s7Tv62+oQe9e1O7ucZWWh762zXqFBcTzNmIlsb+mgwbS7vkfEH6KY3qFmRw3OgjgTMh9jg62sleJgFsIuE6wYL0CYRk2bBj17duX6tWrx8gKtK2Q5ubBBx/UTIHj1oK0+uExWJ9++ik1b95cqYIYLATlI2ZMLIjLws3CpKQk9mdY0woKCqh69eosrgxip3YK/kVb1SxYd72wkvYdzKcGdVLpmbFnMdjGvbBSyU+I37MP5jNydcMl7WnO4l8VaMXchHbwjmYbWM1ee+ACWv7dLpYCqNP+X+ns3F+o6cAriFtqNo8fp1ixuFULP9maKyxdqPvLzcPKbxOGQtRhdrg1FXV/vXU0c/9B6bTJ0BuV/vn6tKxEQfyXZTT3062+Y4W7eLZgIa3qJVa4V3Wc1esPIu6+tmDBSjNlyhSaO3eu4ubD30BOYNUaMWKEqTMKyxLin7755hvKyspit/0yMjJY8Pypp55qqg9eCX317NmTJk2axILdUSLdItyxY0dY/7B84QYiElVDPqJ+/fqWxueVg66DpQXKih//oEWrdhByEZ59WrkkhyjRgHQ5XMkdaWeGT1mu5PvTEvi0BXyUGsGdyQPeR2+fT3WK9SUbxLgpdR5ALT0sMS5r3wfzlfgqMQg+UuxWEGMjorSNrnYbK9yr2uUBo02KFe5G86hqnwcRd1/HYPEDJmpYIegdsVlQczdT9u/fTzfeeCNt27aNWrVqRVu2bGFkCyrxSBiNmCmk0rFSnn32WWZBA1HDLUboYO3atYupwycmJhLGTEtLCwuC5/275SKsigRL7wvIta5YzFW1ROUmnqjkDgvW9Re1Y9vgpxQ6Wueu88FMOvfwRmo+6ArNNDiRREW1+osUMM/rRwogD+KDz8r3PVp1jYiNxD1ayEfuV+IucXcLgbggWNCQ2rRpEwsiP+OMM6i4uJjq1q1rCgNYmmCtevXVVxkZ6tSpE82fP5/atGlDw4cPZ7pU+MxKgZvvmWeeoQULFrCbg127dmXuSiizg2idf/757ObjlVdeWalbSbCsIB1eN5LQKCQb8gtLmKI7XG41UpMopVoi7ReSKzMrUXFpVAPYzaxOzEOoVz9SfkItMqT3shZV32t27ERHt27R1NqSFiwzO+duHaNbkfJF7y7eZnuTuJtFyt16QcTd9wQLt/amTp3KXHsI6obsAqxPIEb4eyTldGx/9+7dCYHmUFAHMYJbEAQLP6GnxQmYu0cl+r1JC1b4bTZ1XkLsAI+74oTLD+RK62SopSW4tQ1uTrFwy1VK8+ZUkpsbRpS23HGrputPfImjr+Ls7EoJm+1aUozaRf9bYG4Ev87TaF7x8sIxWoe5XfJPrXjB3T+IuTOTIOLua4LFEzUjGBw3CiHSCXKUmZlJDz/8MBPshEp7pAJ34vPPP8+ERtUE68svv2Tt161b584JiWEvkmCFEyzuJhR1pcT0NxDyLCoqDVN0j7RdUFtHKSyOviwBlOVzDhUoc0O82C2Xdaw0PSUdTihEJ806pv+GF5yWwKg6ZyE6FPW0+ABGLkS9B5+RBcaNr4MbL+9YzFNrrU7nHi8vHK/wdeN8afURL7hHa/1e9RtE3H1NsECs4BKEOrqaHL388sv03nvvEW7zRSpDhw6lGjVqMAFQdR9IugzhTwScx1uRBKuyBQtuQii5i4HuegKkZvZbbVky08ZuHZ4+B+3hynzhzrMrdaUXe8WtV7gZ2Oj6oUrclvrFp/fCFy1jBb//zm4hQniUB9DrPficEggzWLnx8o7FPLXW4nTu8fLC8QpfM+fHTp14wd3O2vzcJoi4+5pgnXLKKTRz5kwmNKomR4irwi1CyCZEKmvXrmUyD7ixBysWiBl+/+2332jlypX0yiuvsNyC8VYkwdImWJf2bEmia01MoQPiBQImps3x075zQicSLKP0OJi/nntQ/eLTe+GrU+hA4qHRdUMUonZoxReUs3gRpffrT7XPPjemkMXzy9vp3IP4wonp4bE5mMTdJnAOmwURd18TLCRqhgI6lM/VBOvtt99m4p3I72dU1qxZw+K1QMYQMI9Yrg4dOtBdd92lqRJv1J8fPpcEK5xgcUuVnvVH3DNe1+t9BKFKr52iBOJDhT4xMYGSE0N05TmtGVFUyA+fbGIinfTSf8KmbvZFHikQHq5DvSTQv00czzS41DkKvcYv6OMH8YUTD3smcfdml4KIu68JFtTa4QZ89NFHmfUJcgq4uQeShETPf/vb32jixImmTwNu/B08eJBJPNSsWdN0Oz9WlASrnGBxC9WBw4UsDQ5cbTPvjmxlQRu/SzXwW4TcfcfEQyvKSa8cExA1S66MznCkfrgFqygvjwXSi+5Do37Vnzudr9P2VufrZf0gvnC8xNPs2BJ3s0i5Wy+IuPuaYEHUE/kG4cpD3j8QKxAj5Pfr0qULc/eJCZe1tvvee++lQYMGsfrqgnyCt912G0u8HG9FEqxywqEObteyYHESBvchCmK1cvOKYhLAbvdcQWYiL7+YuOhoaShEIaS3admSWjwwmTjR4ImZOemxS0AiBbrzB9/W+Qtp36KFmjIPZtdpRWJCq0+ncU1m5+mHekF84fgBV6M5SNyNEIrO50HE3dcEi2/j119/TatWraIDBw4wAc9u3boxi5aZXHxIX4M0Nf/85z/p6quvDjsZUFVHAmYryZ6jc7Ss9yoJVrgFSx3cLiLKSRisQijZhwpYIDkITOTUz9b3xe0WEB3tmbOestIa00mFe1j3DQYOYrcBIbmgdtvpxWMZzUskZmqleDcffFoE0Appsksgjdbvx8/dxN2P6/PrnCTu3uxMEHH3NcEaNWoUi7/q1auX7R0HwYLwJ6xUyBf4wAMPMLV1FEmwbMPqakPRwqTWfhIHsvMFRN/vfraZWasQ44RSWlpGkHBYvy2bCZOicItRpIWx1gmkpN9xFYQInWHe4/78kJJyD7BasFbV69dfU3LBLsESh1fLOzS44AJKT69JOTlHqDgKshV+IE1+mIP6CNg577E6k0EeR+Luze4GEXdfE6wzzzyTpk+fzsRC7RYQLMRxQWEdgqO4mQihUijBS4JlF1V324kWpqfG9Nbt3M4XkPet7hRkKTk5FBZQ7pfgd/VcwQv/lZ5JuWsyWBLnUGoqaamygyRkvfcOlRUVUVrXbnTcyNG2N0q0Kp009dkwguVHMmJ7oRUNrVjRnI5ltr2d8262b1lPHwGJuzenI4i4+5pg3X777Uyp/bHHHqOUlHL3jtXCCRaSOm/YsIHFdMFlCOKGlDt///vfpYvQKqgu14+2BWvBl1sVSxWmLupbiSlp/EawIEB6ILeAup7cmC78ejZzCYJgsYD3ip+ii5C79riVCzpWdsmQ2E5twTISJnX5eMSkO7s4RXNyQXzhRBMvt/qWuLuFpLV+goi7rwnWhAkTaPHixcylhzx/9evXD9sxxGC99tprEXdRJFioiJQ7CGxHbkPcRETiZhmDZe2L4FVtJ1/Al/63gdZs3MPIykkn1FXchrh1ePX5bZkkgh9uF4ZCCVRWWkbJwryAt1oPC5IKRzasp9K8vHKfZShEaV26sr/BgpWQnBwWq2Xm5p8eyVDjHiley6uzEcRxnZz3IOIRqzVJ3GOFdPg4QcTd1wQLKuxGxUiFXU2w0B9uJyLoHXnvLzuXAAAgAElEQVQOQdIkwTJC2R+fa30BtW4IqsVGxdlzooW+CovKA+VBskBoUI4WFFOpTyLftRI+a5EbZX0VAqH7Ppiv5CXkAfGI2ap7bt+IG6nnJot0i9Cq5cdqfX+cPG9mEcQXjjdIWhtV4m4NL7dqBxF3XxMsNzbuxRdfpMGDB1Pjxo0rdffqq6+yhM9GJM2NebjdR1W/Rfjpmp1MbiG/sIS5/8QbglrEhOM/Yspy3xAoozPRskka/bHvCCFJNYLykZ9Qyz0Ha1bu2jVKihsu3YD+4UIEyTIiV6KVTE3G3NTB8mOsk9E+mP3cbfIYxBeOWSy9rCdx9wb9IOLuO4K1cOFC6tOnDwtCj0b573//yxJH16lTJxrdx6zPoBEsM3FY4hdw3L+/UuQWUqslEte4QrwVCldC5xuC/vEZCBluEcJiFYtEzm4dCAS6w71Z+O0K6pGznkp7n0/dh16pdC++3PHHvW/NLY/Vqrh1yPMKquejvjGoRcTcVHJ3m4S4ha/VfpzKTZgZL4gvHDPr9rqOxN2bHQgi7r4jWCeffDK9++67hKB0XpCPEMHoDRo0cLTzSLfTqVMnev/996ljx46O+vK6cdAIlpmbhOIXkFuw1O5AvX7E24ScrECmoaiklFmIEMbES0KFFAPqxcJdiPHqpaWwPImYE0ggVOnFopaROKtgK52b9ytLb4O4KxTRUmX2RqGYikeM0xITS9dsf7JnuQi9/p7pje9UMNXMuoL4wjGzbq/rSNy92YEg4u47gqWOmXKTFKnzGXpzjNwZNWgES23B0rJomfkC6lnCuAWL615xxXctGQcQq+opSeE3D6OsfwV3YNaBo2Fj6p0UxIzdvvu/5bpY/FahhqVKTOIsJm9WW7sQs6UmaJtG3qzcVuwwe46uDpbakmOU79BMLJjWuv1m+YrFfMycd3eeJrIXEQGJuzfnIYi4xwXBgrVp/vz5jq1ObpI1b47gsVGDRrDUeGpZotRfQE6muIq7Ws1di7TNXZLJ1Ns5wULQ++pfyhXSxYLPYd3igfBe7zcfn0s3XF79T+q4+3tdCxbqgwTsffMNdssQsVhtnp/GutGLgxJJw9FNmSyuCzcTTxhzqy7BUvel/l0vpY9VPGMZuxUL8mRm/UF84ZhZt9d1JO7e7EAQca9yBMstsubNEaw6BMuMBYuTMO7K4z95kLuapInWKi7PgEB5pM7hbaGRBXdcp1b1acuuA0oQvdF+c7eiUT0nn5fr0JOS3mfoxe2YvAQvWvFUWsruagsW9LO4Mjy0ttSSDpEefEYWLE6M1Cl9RBzMEBozsWJOsBXbOiFzZtZidp5BfOGYXbuX9STu3qAfRNwDT7AQ1N6jRw9q0qQJOzW7d++mRo0aUXJysjenyKVRg27B0oLJDQvWm0szlbiqaskhurpvW3YbEdYv6GQh9Emds1ArJsqlbbTcDYghD85X35bUiqcyS4Aipd/RevCZJRJm6pklNGbrWQZV1cDMnPXGcHOOQXzhON2bWLSXuMcC5cpjBBH3uCFYCxYsoA4dOljeeaTZgRL8BRdcYLmtnxtIglV+Q44XM7cQUVcUE4VF6D+TjmlDiWKkqAvC1bxxGm3/K9cXRwGEigfCY0Lqm5JmrDzquCz0wy1YelIOWg8+N4mEmXljnk6IT6w20M05BvGFE6t9cDKOxN0JevbbBhF3XxKshg0bshQ5vOhZnSASumzZsog7eumll9KIESPoyiuPXWm3fwT801ISrHCCZeYWIidhiMHaf6iAEM8EksVvIop9YKfhOhTT6kTa/Wi7CJHwuUv7RoqVDTFiXJ6Cuwn1YqjEnIQsLqtCwsGMujvWbMWCZYZgxELiwD/fVPszCeILxz4asWspcY8d1uJIQcTddwTr3nvvtbS7TzzxRMT6c+bMoeeee44uvvhiatu2rabUwxVXXGFpTD9UrqoEa9XGvfTusk10aY8WYfFHZixYejFbnKxw4sXJDCQT+K1D7DnqITYr45c9ShxUtM4CyB9IoFg42eNxYlxglSfIFq1Kxfv3l6fQIaJGQ24IExo1Q4IiPfgitTdj2YqFxEG09iWW/QbxhRNL/OyOJXG3i5yzdkHE3XcEy9kWVW4N2YfIlgeZKsdtzKPVH76A46d9TVk5R1mcFCcWZsfTu3WYm1ekKToKogU9KhCa5OTy1DqcZGndPDQ7DzP1ImlwiURPzFnIiQ9Tds9YrQzDLVVWiJVYN1KyZ7WAqRmZBkzMyC1pBqOg1wniCyce9kzi7s0uBRH3wBMsuBeNStOmx25iGdX1y+dBtGAZWaHwBdSzYDnZl7HPrWCWKhAqqLyrUxEiGF6Ua1D/7mRsO20R6A7ix8VIQbh4QVxWi3eeIdwGpIQElvQZhf8sPXKk0i1BrTmIVqaTpj4bJtNghajxvs1YtuxgYaaNnfma6TfadYL4wok2Zm70L3F3A0XrfQQR98ATLKNtLisrYwmf460EkWAZxVFF4wuIwHa4/GChwo1CxDPxv4VCCSzOCUrvXqfV0XIZap1ZkK1/dS5WLEQ88TPqRpJKUPclKrlH0sEy+73xkuR4Se7M4qNVLxrn3cl8qkpbibs3Ox1E3KsEwVq0aBFlZGRQUVERgVCh4GdeXh798MMPtGLFCm9OlINRg0iwzFiw0tNrUk7OESouDg9yF6E06kesO/zJ5cxipb5RyK1asBaxVDpCI+46dLB9lpuK8gyRGsO6NnP8uUoVroMFa1aj64eyWCwzZCeSBcvy5D1uYGa9Hk9Rc/ggvnD8iLN6ThJ3b3YpiLgHnmC9+OKLhP+npaVRcXEx079KSkqi/fv3UygUosGDB9PDDz/szYlyMGoQCZYRHGa/gHqWME680mpUo9/35LLkyes2ZzH3H9fEevezzYxQwXrF46/ULkOjecbycxhfkxOPaWNxhXo+B7s39iLFYNldXzSITjT6tLs+t9uZPe9uj1vV+5O4e3MCgoh74AnW+eefT2eeeSZNmTKF/v3vf9Mff/zB/nv9+vU0cuRIGjNmDA0ZMsSbE+VgVEmwrFmwQK5EkVEOffcOjVmCZZAq0VIFixbccpyMQQ8LpEzMwaxOwKzeTrMSD0bHAAHvePio0/aATCHmiq+LJ7GGAr06CbY4hhYpiURUnDz4xH4R2K6lFG+0/kifx6v7z8yaneBupn9ZRxsBibs3JyOIuAeeYHXq1Ileeukl6t27N9PM+r//+z9aunQpO0Gvv/46y3H44YcfenOiHIwqCZY+wdKCVZRoEMVDRdV23g7EqEWTNMrNKwxLlYOEzKLoqFsEyugYaLkkOZkSJSPYbccKpXes6/4OBbq39dTinpHIz6EVX1DO4kWU3q8/1T77mPvRaN74XCRASMejlVjaTD96daQFywl6sq0WAkF80cfDTgcR98ATrG7dujEdrF69etGWLVvosssuo++//55SU1NpzZo1NGrUKPruu+/i4fyFzVESLGOCJcZiATykxOGWHfGzTTsPKAmfQaIeHNaVxJuF/LaennSC2fgoNw8ZyBR3Y6r7hbsTQWMjts6j2kVHUJEaXTckTAtLnVaH5yLETxRRRuG3ieOpKDubkuvXpxOnTDWM4RJJj7qvIFuc3Nxf9BXEF47bGEWjP4l7NFA17jOIuAeeYA0fPpzq1atHTz31FBUWFjJ34fPPP099+/ald955h/33t99+a7z7PqshCdYxgqUX1G50K5FvqZgEGiTqlYl9FYIlWqm8CG63c+w4Eex8MJMuysqgEJUp0gyiVtaRDetZ9w0GDtIkX1w/CxasfQvep9KyMlbXyNUXiUQF2eJkZ68itQniC8dtjKLRn8Q9Gqga9xlE3ANPsGCluummm+iss86imTNn0v3330+ffvopIUfhypUrWY5CkC8rpbS0lAXOz5s3jw4dOsRI20MPPUQtWrTQ7Gbz5s1sjB9//JEF1nft2pUmTZpExx9/vJVhA2vBMnvrT+8LaBTUHikeCaBifB7c3q1DY7rlso70yJw1zB2IOKv8gmJKEgLJbW+ayw2ZukgZ+19YQexYzqEC9neQrF4H1lObq8tJlJlchGoSBNy3ThhPBVlZjKiJ1i6t/IWSRLmz0UF84biDTHR7kbhHF1+93oOIe+AJFjbz119/pczMTLr88supoKCAHn30UeYmPPXUUxnRqVOnjqUTBXL11ltvEdL0NG7cmJGnnTt30kcffRSWQxGd5uTk0IABAxipQkA9xkeQfXZ2Nn3wwQeUkpJiaWxeOUgWLLOWJr0voFmCZgXoEVOWhwW0i3IN0c47aDRPblWDRS0xMaFS8Ls6Nqx73ha6sCCTEaOjmzIVlXeQJRQmSqrhRuTzAO75q1bSznnzWRyWmlSZIVRm6hitu6p9HsQXTjzsocTdm10KIu5VgmC5eVzgZuzRowdNmDCBrr32WtY1rFh9+vShxx9/nPr3L49h4QVWrieffJK++eYbhUz99ddfdM455xDyJPbs2dPW9IJEsMwSpFh+ASE2umbjHiZCixgsI/egHtkx2txIKXGM2up9Ls4VZGvM7wsorfAw5VevTbVqJIcRKvRhlPzZCHeutQUhU+5CBJkTiZid2KuqTsqMcLd7PmS7yAhI3L05IUHEvUoQLJCi999/n5GcrKwsRoQgPNqxY0dmxbJSfvrpJ6ad9cknn9CJJ56oNAXZateuHU2ePDmsu127dhH+D1LGCydYiP+65JJLrAyv1A0SwTILgNYXMFIgu16/Zgkd2nOiJcozGM3Xi6B3cU6QbxCTVMNN2DNnPX2b3okgS9Fw/dfMmsUJ0I5HJ1PB9u2U0rIltXgg/PyiX6MHn0iwQqmpmlIMdsiSHVLGcbAzntG+xvpzI9xjPZ+qMp7E3ZudDiLugSdYEBS98cYbadu2bdSqVSt2kxBkC5pYq1atYlak008/3fSJgsTD2LFjWTwVbiLycscdd1B+fj6ThDAqEDaFPMTnn39O9SvcNEZt1J+DYB06dNRqs7iun5gYotq1q7N1Y/0o415YSdkH86l+nfK94P/97NizdNfK28B6dMMl7anvmc3C6i7/bhct/GY7DejVkv1En1qkyciqZQQ2pBSyDxUYVWOfmyVtsFh179iYVm3Yo9kv+nllUt+wz365eRhRaSlzE3aYPSfss/3Ll1P2oo/ohMFXUs3eZyu4i5XK6yyk+v0HUF7mr3RoTQbV7tqNmo0ew6qJn9frGz52pMXbbYc+N48fp9x8bDv1WVMY+62S1nn32xyDOB+Juze7GkTc8b7CutwoCWU8D40bvbnUB2KsYK169dVXCUmdoYsFctOmTRvCDUMou+MzswWaWffccw9t3LiRBazzgr/t3buXEbZIBdpbjz32GN177700bNgws8NWqhevORRtL1in4eJvfqN5yzfT4L5tWQ3+3/16HbMuqpuizcwFP7EYq4bp1Wn2AxeFVbn50aWUlXOUfXZyy3q08ofd1KpZXTp4uIByDuZTsWDOSkkOUUGRsWSEeg5WXIOYR/aBo2ExYXo4wgVYVFSiOydYsy7O+Z4SSoqpwVm9qd3d4yjz6Wdp39ffUIPevdjvYlk7YhQLbk9p2JC6vDLTcPt4fZC1ViNH0HH9LiarfRgOYqLCn4uX0O75H1DTQQPZHGSRCEgEJALxjIAvCRZuC953330swL2kpIS5BUGw8HP58uUsyB0EzGxZsmQJ3X777ZoWLLgiZ8yYodkVCBFcgvj8lltuobvuusvskJr1pAXLGqkRrVKwWKl/F0HWsmBxQmRVXDQsHioBOTAdbbvjxqO3z6c6xUeUfhKqVaPG11xHsCxpWYxEC1Z+fhFlLfwfs1SpLVG8bfU2bZkFCxYxxGQlpqYS/nZ0y2bNdo4XFOAOgvgv+njYLom7N7sURNwDb8Hq3LkzIzYIKlcTrC+//JLuvPNOWrdunekTxWOwIPXQvHlzpR1isNq3b8/kGtQFSaZhscItQwTHw3LmtMgYLGsES1Ryv/6idnTe6U01t4DHZ7VpVpeQckb8yVLq/H975wEmZXW98bOzyy7FRYoUCxLFiNiIFdRoDNhrorGhYFTEiDH27t+oMVEkaIy9xkiJscbeorEbbKixElQQk1BEkKUsW//P7+6e4c7HNzPfzM7s7sye+zw87M7c75b33tn7znvOPQfTZHN26Pr6xqZ8he2AOEXdT07BWjjdJbf2S+WOw2Tl57NC/afUN+LN48c5s1tYqIZgxHZiZTVUV0vD8uXxGFxRx2j1mhAoRp+UQlhbw71tVqkYcS96H6zRo0dL165dnW9UkGCdffbZMn/+fJk8eXLkHYVKxc0/lC+c3SmpbhHy/hlnnOFibxGeIXjLMHLHgYpGsDIjWH4uQnyfiI310EufO1TJ5wfh8uuoUqXJk3F2n/5xk18Tr3UuL01Io5NsHYlJ9W1EP6ts90LU51RNawpAOl0SPANKSqTv0aPXSK2DszhpcgYcdqisWFEj3zzxWDwOlh/egTH40d/5vRgczaNim496xXjg5AOnXLdpuOca0WjtFSPuRU+w3n77befrNGjQIKdi3X777e73L7/80gUaveOOOxJu+EXZCtdee62LAs9tRPy6iIPFTcHHHntMSktLBcf6yspK5wT/0EMPOfUKHy3S9CSoBs11ovQZrGMEKz3BCt4W9H8nbY46mEO4Jo7fRXyVS8MzkHbmlrN2Fz8ulk++SBBdU7fmWFC1ulaUuWXbcuPe8vanC5za1ZaFPIWMl6I3C7s3VEtJQ71gKvz+TbetMTxVpvDBGjRxktQ1Pw95WjB1srN5Ygrc5Lob23JqRdl3MR44hbBQhnvbrFIx4l70BIutQjT3SZMmCeY9orBzeG6++ebOD4ok0JkWlLBrrrnGkSduDhJE9JJLLpENNtjAEa2RI0e6IKSHHHKIHH/88fLaa6+FdqF1Mu2f+kawkhMsJVLVNfUuXIESKB9n6kx7bqYjPZp/kNdQtXzS5CtYxMXSiO74ZGFqVKIGEatJ4uxOXSVsOgbq19Y2rBGFPZu9kM0zShK3IYTDkg+lfueRMmz0IU51IiFzY22tlHTqJJ369JFVc+ZIrLxc+h5xlCz/9BOpevstqdhwQxfawRXYZEmJe62+qiohBEQ2Y0v2TEdTxIrxwMnlfshXW4Z7vpBN3W4x4t4hCJYuK2Tou+++k7XWWku6devWNrsoR70awUpOsFSJghxpwQxI8RM+qyql+Qd5P5iX0PfXUgJGPd+sSJtVK2oTlKxMneFpk3G0VUoeJYwD772mKRBpSCHZc+3ixU0hHVKUKOl0svkYtCQuVjb9tfUzxXjgtDWmUfo33KOglPs6xYh7hyFYEKuVK1c6BStYWpITMPfbLFqLRrDSK1j4WanChIpFwSyoipYGEd2wX6UsXNIUUwxzHs7s+rM6uvPaiuo6pzipD5dP1k79w8tOLYNYkc/wzY/nZ6xOQQhxok+mhEXbGZnV8sNF8PMp8p50m/Wvpka8K48lZWXSb9QxCQpW7cKFrppTub76KkHBSpcQOrNRNtU2BSsb1OyZTBEoxoM+Uwzaon4x4l70BGv27NnOIZ3AoMkKMa0KrRjBSu+DxZpGifTuq1Y+eVITo09CIFDH7D3YmRIhVJj6OpXGnMN7W/tY5WIPj5/zoHSvXe6CjiYoVbGY9D9mTNzJPSzJs/avZkZ+J3VOqrphY/7fbTc7M2Tl9jvIuuNOzsW0CrKNYjxwCmEhDPe2WaVixL3oCRYhET766CPhNmH//v0TgoPqNvrpT3/aNjuqBb0awYpGsKJAHPe9qm9wZIkCedLbgoRqUEVKfbJUsYrSvtZpaeT3TPoK1k0WSiIY8BTn9z2qP5OeQwZLFfGsmlWsbpsMkuVffBmP+A75Wf7Rh66bIIlqqSlv5rjj4/1settdLZl2QT9bjAdOISyI4d42q1SMuBc9wRo6dKiLnH7AAQe0za7JU69GsHJHsHSJVMlCpeLGHf8wGfpmQur26dFFZs+rWmNlgzkAw/ywgilvCOOwpGqVYKacM68q1KzY2nG2VMX78tEnZacF7zocYiUlUrdsWehuDvpcUckP2ZCpac9XsLpsOniN8A95+ki1u2aL8cBpdyCHDMhwb5tVKkbci55gcUvwqquukl133bVtdk2eejWCFU6wMknkHBbGYeqznyWkpFGFh/+7VCQmUfaXFnWK2FiQL4gSpIQSFsLBd75Xvy7qcpsxjLhB1LoGEjhH2VY+wQtTz2iTOsFQE2r2HDH7Bdl82WxXBx+sxoYGKevRQ+q+/bap+5ISiXXt6hSsVD5XLVG0wp4NI2wtNUtGwbO16xTjgdPaGGbTn+GeDWotf6YYcS96gnX11Ve7RM+kqOGqfLEUI1jhBEtNd2rKC653WCwsP4yDH2wUUrXDkNUO60o8MB8mK/S7clWdI2lhoRvYgbFYSdxfK6rZEOULH69M/byUICbrB1L31fyq0DyH586aLDHV1FRG83yzKr73PRl48aXx0A5gEuZzlamC5WMb9mwY6dLXeBZFbeMJkwr+o16MB04hLIrh3jarVIy4Fz3Buv7664UEy2uvvbZstdVWLvinXyBdBAwttGIEKzuCpWbAsJuAugeCypaSNkgOao8fLtSZEzvFXPocDeSJaqVmRlWwfDXJ/xlCRsiHyc98lnYLZhP6IW2jKSocOO9lGbJstpSWl0vvYTvKoulvSmNNzeonYjHBRypObmIx6TvqmASndp8g8WAw2ns242sNBaslpDCbOYU9U4wHTq6wyWc7hns+0U3edjHiXvQEa8SIESl3CwTr+eefb5sd1YJejWCtSbDC4lSlUrCS5SNM9ozeKtT3lRxpmh0XD2tlrQuz4JMxraepefzI7ihL22/WN56GpwVbIuWjvoKFsgYhDDNfBhth7FsN6i0ffvmtjP/grtWKloj4CtaCaVOcY3pQPfLVJtomxpbWaQ8kJhloLTFr5moNi/HAyRU2+WzHcM8nukawskW3pLHRC5yTbSv2XCQEjGCtSbB8dYrUN5n4Y0UBXQmcHw9L+/F9t4JmQMxwVStqXP5DJWPJFCtNsZMsBU+UcYbVCZoIw9S4dG03KVpzpK4kJuWN9QlEiejvlKCJMJWClQ8SkyvS1h58uuygT7cj8/O+4Z4fXNO1Woy4F72ClW5RC/V9I1jhCpYf/DNIuLJZ6zBH+L8+/29nKiSg6EkHbZEQ/V378M156gelzu2+Y3s2Y9JngjcSM20rW5Oj5jFs2GWkDB7QIyEnoTq8l1ZWuuCjfiyrYHyrXJEhf95B0halj2Ad/b2huloali9vM5+udAdOlLlluiesvkg63A2j/CBQjLgbwcrPXsl7q0aw0odpyIWCFSRpfvwr9eOCcGFuQyXin4Z3IPq7JlfmtfYSjDSqY326TQxxPHPeo1JWtcRVJekzBVLil77HjHF+WcH4VulUoijvB326gqQjikoWrKO/M59Y5855y62YDt90B06UuaXrw95fE4F0uBtm+UGgGHE3gpWfvZL3Vo1gpSdYuViEIEn7xaQX46lswhSkYGJpn6B9u3RVxulzcjGHbNsIErGweFyoWSMXvSOdGuqkpLzcdeUc4UtLyUjufud1FC2ClhLiQX23/Jt/WqfXvvu7ZyBOqiDxe9jNwCgEIx1Jo+1kChZjyTQKfbZYhz2X7sAxBSuXaK9uKx3u+enVWi1G3I1gFei+NoKVmmC1RL0KMwuq6VFT5CQzr+FAvs33+7jgpPhcUfTZmXOXZOXMnq0pr7W29smzH5S165pUq/qKLk7Ba6ytXX3jMBDiwXdyXzB1ckLOQ96j4AyvihhtlXTqlNK/yydCyVQs0v9gslz5+aw2U6UyWZNMDpxkZMtIWCaIN9XNBPfMW7cnkiFQjLgbwSrQ/W4EKzXBaon/lT6rqXL09qAf2oH0OWoC1KCiGh9Lfa6CapZuNSVwS5bVJI1r5atFjCMT8yLPEnk905hZ2X4UULF+tGiGe/yl3tvIXt+8JbHG5vUpKZHKHXaUZe/NiCtbmN3UGR4CoDcQIUCEeVg587N4LkIiuSe7oZhsvLNOO8WZKSFom1x3o1Oo/D7CbjtmO/d8PceYFz/1hAw47FDpPPyHUleXer8nU/OiqHz5mkOhtluMB30hrEUx4m4EqxB2XsgYjWDlX8FSYqVES28BBomSKlV+GIYwBYvnqJPOyR3T3Kg9N42rXxr6ob1s1XQ+XOfNusfFAXOlmWBVvTk9Yfi+yU9VFjUhxs2LsZjEunRp8ukKibEVlWBRT/voMmiTglCwlBhV9OkjgyZOSkuwTMHK3aejGA/63KGTv5aKEXcjWPnbL3lt2QhW/n2w0pkZk6lkyaLF+3G0/FAOYb5Nw5pvKN766EdZmRX9zRcMGxG2MYNJn1uyecfMfVzWXdWUTkfNm0q4ynr1cqQLouNUrdpap3A5pWrKPWt0G+Zons7sle79lsyttZ7NVMHKxbiKAbdc4FCMB30ucMl3G8WIuxGsfO+aPLVvBCs3BEvJECY/VZ2iBiCF/Lz1yXyXTmfTAT2cr1Vl1/J4PsFgtHj132JLaNodfiaSO8V/H0Jy5/kjZOyEF+JpbIK5CtMpSZmQpnz4eWk4h8q65dKUmdHFN5VYebkjVihWrsRiUtazp/O7SihJVCvf7IUjerro8IWmXikGrX3gmDmxCfnWxj1PR0TBNVuMuBvBKrht2DRgI1i5IViqQqXzmwrbJr6CxfuLlq5KqIYKhZ+WT6KmPTczwTdK/bSCflmQpx5rlScQtnxv1XSELdv+NeWOSxrtNQK94vfKHYeFK1jcRKQ0NDiVa91xJ7tffaXFTzIdRrby7X+VT9WntQ+cfM4l273TFs+1Nu5tMcf22Gcx4m4Eqz3utAhjMoKVG4IVVLCCSlYqM2EyBWvOvKqEhM4spxIpX5GC1B2912AX3V3JWnDpeW5x1aqEZMyZKFMRtlJCFfzNUiWzzrQ9rQ9523rxp7LbohlSShT4xnqnakGyGiq6SNd1+wUmQx8AACAASURBVMmq2bNTNq+3Cn0HeY0g322LLZ1jvDqwK9mKh3ooKXE3EcNuI2Y7J5+85SP9DwdO9T9flbn3Pyg92zhkRLYYFeJzxXjQF8I6FCPuRrAKYeeFjNEIVm4IVhDaoF9VsuTQPKfpcYIqVDBnISrNMXs3ESlI2Zsfz3ehDNZbp5tAxvh5m037OHNjg59JWkQwC85dsMypXmG+Wi3ZvmFmwSj+Wun61PkG1Tr/OcyHey18M57bUNWsdG3zvpIZP8l00BlelS3XXjO5cvG5/JuKb73pCFefw4/MKt5VWJLrlprZfBVpnT32kM/POUtWLVzYZtHko6xHsdUpxoO+ENaoGHE3glUIO88IlkOgNT6AvipFGhxfwVIfKQKM1tU3ODKEmoQPFv5b/q1DvSkI2SClju/fpTkNfaXITwjt5yHM1jcqirkv14RNtyn43HL27nL8VS+k/HT54R0Wd1rLOcYHneLXaKD5ViKxrOK3DpujyPtR111aHu/mIupXw8qVcYWrbvFi9zMl24jtQZOa6/OtNx2J80NRJAMhzCTnE7RNJ11rClYb/H1ujb8zbTCtdt9lMeJuBKvdb7vwAZqClR8FS1PhQHiuP323BPD1PZ/04GcFecL/ite7di6LO61rgFH+531VusLMgUqw9Bk//U7n8iZfpGSmO8gUxY97NXrvwaJttPYWV1I5/eP5GXV98IJXZPDS2TKvoqf0X7XYqVuNUiINJSVSqnG1miPDOzXKK0SCVyUqwe+quQ7R4ymYIfm5vG+/OAHjWdpDGcO0mCxxdbrJxFMBacWAk36UND5BBatnz26yePHyhDAN7d1Xqr2PL906FuNBn27O7eH9YsTdCFZ72FlZjMEIVusTLFW3NuxXKV/Nr3IKlt4UnPLMZ86fKIyYBX21UMJ8lYrl10TQkCja9NUwiB6qVyrClCwIKjkS21NJlqA6qLjpDcQ3em7phr+GOdFLxePPD/JUu3BhU+wsJDoKtxVjzfcYm1UrHOtRwfyI8a6qH4FexJGx+qoqF1ZCI8BTL+zm4pwrLnUEjlAUdUuWJPUHC/PXok2InR+1HhNhmA9W0AwZTKKdbr3zTYBaaiZNN/58v1+MB32+MctF+8WIuxGsXOyMNmjDCFbuiINvBmQpVUUKhmtI5o9FPVW3IBCVXTu5NDn6fNhtQwiRhnRQcuEHNGUcGriUMA6qggVNaOqyRRsoXX7dfG7LTMyL+JHNmV8Vj8oQZVzBkBQQrhHfvC2dGuvXMCOqAhVvt3lwvF6+3nqhqhV1MQ0qoQkSq6Rj9EhbkCglc6hXfzB10qdtddTn5zDFjbp9Dz1M5hEbDFLoqWFBQhVMop0O33QEKNOwFslyOWYa1DWbYKn5IIv5vFyQj/GmW+9077eXMRnBSr1SJY2NGtgm3ZLa+y1FwAhW7ghW0LE92c3BVDcK9b2wtDoQKd+ZXf2xlDSFRYqnPd+JHsJGfU2vA5HDSX72vKqWbqWE5zF5ZmLa07ALAd/8hDZ7da8QEl1nUpLdZlRla3lphTMjflb5Pek+Zqysf8sl8eTS6jCfkHy6mVA1rFiRkPvQKVsQmCBjbCZSFQMHyqqvvor7a/lzULOkT6DUz4t6SsB8QqSqmU+Y4s7y3hggWKWdO0utFxss6Nwf1r6Gsghi7R+ivJcqdlhwPJpyKNn65SpNT9ilAfpMRQjTkcVM9pzW5aDP1+WCfIw3mzn6z7SXMRnBMoLV0r2cs+eNYOWOYAWJU7Z5DNV5nUVOpiT5+QlTETZVxGgL0qOBTKtW1ApmP9/RPpNNpaZInunTo8saBC3TvIeZ9B2sG8URP2r7IxvnyNAvXnXhHxqkRMqkUWo7dZbS2up4kFPait9WbA5uisqy/KMPmwKf8n6zb5efxxDT3RrETAcWCP/Ay37oiHgOxmbChY+X5kVU5/pk5sfqf8+UpdP/2dSTp2BlozCF5XNM1o6+jmkUPMIIVhTClo3pMtU4wc5P6g0s+VBfTMGK+qnLbT0jWEawcrujWtCaEazcEazgMqRLkRMkUmGmwInjd3F+U+qbpX0Qwf2IEd+Pmw95Paw/n2Dhw96loik+lTrSp0v+nMzXyXfKV7KFPxj/VIVijDW1+cO3Bds+0qO+/9aAlfNlyLLZDjffvMrsrt5kjEDyzvjfI1JWtcSRmJKyMkcqUKcI4aDEyt1CxK8rWSktdTcHKWr+06TT8UdKS6XvUUe7X33SliyG1pfnndWkYEWIaL/xhElJhxZXhpqDuqrK5StGQTNkOvISRfWIUic46CjELdImaEGlYjzoWwBHqz1ajLibD1arbZ/cdmQEq+0IgH8L0Fek/BhXR4xsIlE+UdId4D/Da2GKWSqn9mTmM43+rsmn1cTo7zzfGd53pA863eszvuWM9hsauNnXVNorEQvzDwuaFj9Za6A81r/pluiwFbPkx/P+6cyAK2PlUhPrJOUNtdKlofmmYkmJLN7tQOnx0qMJkehTBSZT/67gbUe9qahKDeSpcvsdnIoWV8maCVUsFpPFTz3hgowu//ST+K1HjXzv33ZcOfMzF2iVtoJmQj9khfaPiVCVM/73g7SmImu6L6IoR1HqpPqrmA1Ba+lfWcYM5gMOO1Q6D/9h2iTb6fprKQbp2i+m941gpV5N88Fqxd1uBKvtCFY6BYttoFHa+VlvDfIzQUW33Lj3GnGxuCEIySFmFvG3fOIV3FbJ1KngDcaggqahIGgPfy6NWq9+XZluX0JBTH7ms/hj2cbs8vvFX2tJIHJ9JuOC9NXWrlbj/GfBDYYUps6dtP4Sib32vHBr8b21B0tTINTpzrwIWbp18CjZeeZzMmTZHKnts540LquSL0p7yeAVX0usoU4Wdl1H+qz4Zk0CxgA819S+x4xx/k/xvIvchsQHLOi+GotJ/2PGyKBDD3RhGj4+7tiEOnFFLeQ2pd6QVAIVd75vJm5+eiElU9k4mKdaF22vtLLS+bCFEb9065pvcpIqDllFnz4yaOKkFhOstiCJ6XBtr+8bwTKC1W72phGstiNYyTaBEi8NMhqMexX2uzqv4wTuEiGXiNxx3oh4xPdYc4wrlKOB/SulakWNVK2sDSUJmP+UnKVKYq2qWlCR8ucV9I8qi5VIRXmprFhVF+cCECyN1k79AX3XyonTPe36xNQ3X6b7AGZyu9FvKyyC/fZVM2Wfun/Lwi13kSmL1hFd12RjQAnbecE7UlJfF08FhB9YY12tu/3YfcdhTl3iYJ8/dbKUeKSK3dxY0UV6DN1alhJhvrFRlnbqJnLmZTJ8SF/5ZNzYuH+YI/DdujmT5BoJshMmVeJImZo7eQvzJUWd3P2fg/5NvBckCFFJj2+WdB3GYrLpbXelW75WfT+M/JiC1apLkNCZESwjWA6BhoYGueGGG+T++++XpUuXynbbbSe//vWvZeDAgaEILV68WK644gp5+eWX3fv77LOPXHDBBdK1a9esd7MRrPZHsHQxgz5VqX7Xm4SoKxCJTs0+WkHfLd+sGGZ2pG8/ZY+aB/WGImqVJp5O57+FivT7Zh8yxuc71vsKEG0r6fDjeGW9qZsf9JW4sKCsuVDKdIypCBnvdSqNuUsFlHQmUV9Z9P3AUMR0fdR8++F9j8bzMjbEyuTFXj+QuQO2Fnz37rrsdtnqf+85Ne2DHoNlzD6buTyOvllPHb6JvVU9e7ZT0HrXL5fSVSubpub5k/lkrKp8LVl64gXOfM2+7H77lVJZsyxpKp7pkx+SsjdekLqdRsiw0YfIx2ec7vzV6ip7yObX/sG14YcTUX/ETBWsdH6P2eypdGQw2fvFeNBng19rP1OMuJsPVha7CHI1bdo0ufLKK6Vfv34yceJEmTt3rjz++ONSXl6+RoujR4+WVatWORIGIbvoootkhx12kAkTJmTRe9MjRrDaL8HKZFH9g8WP+K6khrb8XIb87odw8BM/q4KlpMR3jvfrpSMovopGfsSSkpKEKPE6P59Q0PeMfy+MK2tKuHzFy537Xmohf45BzFCxNHdjMGxELpNdp8PCH1eqW4+QL8hYlETZfp/ghMkYnAlgi0Kp8dG0795rd5aJJ++ccBmC94KZAlDQdpr/jhAtp3rXfWTwgB4JStWsvz4or/doMoGqKXXod5/JLt995AjUA1X9XPy2sLbjRH3eR7Ltgvfl3b5DZVb/LeIBcX2Cn8n+17rZ3txN1Ve25rliPOizWZPWfqYYcTeCleEuqqmpkeHDh8s555wjRx11lHsa0rTrrrvK7373O9l///0TWpwxY4YceeSR8uSTT8qgQYPce6+++qqMHTtWXnrpJUfQsilGsIqDYPlrHwx4mio6vG8C1CTRwaTT/mHpK1h6oBOJPq6cNcfVIkI9uRUxNY6d8IKLVg8h6Na1kyxb0RTKQAuH7spVdfGI9n6S62Rqj3+L8he/fzGuDgU/A+qMH3TUT0aIgrG2wkhYmFqVi1ARjOnO81ebdcNiggX78dMqKbFO9ndg+Bb9nFlWiSYY1tU15cJUnFCRfBOmEj7aVJ+/MEKrvoKaJUAD5WpqJzVh+yomfoR+rk1+5x+hSShhila6v3GZKFhR6lJn5sNPyHYL35f6nUc69S1qiXLQpxtDuvejjqW167XluKPg3tp4tLQ/I1gZIvjBBx/IYYcdJk8//bRstNFG8achW4MHD5ZLL700ocXbb79d/vznPztSpQWSNnToUJk0aZLst99+GY6gqboRrOIjWMGNEPWPXdR6ychcMGK91tMUPzjef/7fpbJwcbP5CXNZWUy4KUlRJYWflRAFA5D6xCiYXijsA4CCFSQe9MlBriqRT/CUKOhckplRg30luzBAPV8BTPchzUQJoy0/8v4r7/83pe+aP09/HGGJxvX9sPGoagVjhrD5Y1Ayr2ppMJuBn6OTjAEQMC1K7Nkvvtro31j1MxukwzLV+0H1VhOtB9tPdtM3St9RDvp0iluqrA9RxtBWddLNK5/jioJ7PvvPR9tGsDJE9dlnn5VTTz1V3n//fencHPeGJk477TSprq6WW2+9NaFFfK+oi7+WX3baaSenYp1wwgkZjqCpOmYAHJ87UkGB4Oo6PnCWM6D1Vh7cUaeWrayVbhVl0rmiLGnn1avqnBM+BdOiFl/RWqtzmSxH+QrZvzzD+/RBW9SDVOGfRt819Q2yqqbeNYvTfXlpLKE/uqTesmqc8Zs+H2WlMWfiDEs0QX/+6z4x4b34uBtXh6fQeeUicQWXGHwcmFP8lmNznzoOnXcQW8ZBHeczVhaTmpr6eCiNKLuEMfCctq/9Kea0AZ586Py/OODa0NgY3xMLl6wm4LqOus700bt7U5ywTIu/D3wM/Hbob521V7fPM27MIvH9xM/alr+Pl66ocXMH++5dy6W6ps4pdCRu71zetNeDz4W144/Hfz8XGAQxS9d/phhr/Xy1G2U8+fz73lbzYt/7fwej4JCsTocI0/DII4/IueeeK5988ok77LXw2oIFC+Tuu+9OwAd/q9mzZ8vUqVMTXt99993l8MMPl/Hjx7cEc3vWEGh3CKyorpXlkLEunaRr506h49M6ncpKpbauPmVdv4GFi1fE/cFQYPr07CraFnwNssHr9B02Bupi7qKQM5IS/J3n/LbogxKcl/4OedPSvVu5I0gc0hzOEDTXftg3gpISN4aq5TXxCPP9encTnSN/mFGpFMf5365w89PX6TdYh3HMW7Q6ICrj8efD+3pjMoi9j63OBywp/hz99xQbXiO8hs67R2VFKGbZbNawcQXbAYd+vdJfGtK2dO8E8erv4e/XCXsu6lyifB6itqX1WjKeTPsqhvrFgFeHIFjPPPOM/OpXvwpVsDD93XzzzQn78Te/+Y1gVgxTsE466ST5+c9/Xgz71+ZgCBgChoAhYAgYAnlCoEMQLPXBeu6552TDDTeMQ4kP1mabbeZuCvoFH6wpU6Y4h3Yt6oN1zTXXyL777pun5bBmDQFDwBAwBAwBQ6AYEOgQBAtyhP/U+eef75zdKaluEb733ntyxBFHCL5bGifrlVdekXHjxsmLL76Y9S3CYtgwNgdDwBAwBAwBQ8AQSI9AhyBYwHDttdfKvffe68IyrL/++i4O1tdffy2PPfaYlJaWyrfffiuVlZXOCR6fiVGjRrk4WNwwXLFihVx44YUybNgwF0fLiiFgCBgChoAhYAgYAqkQ6DAEq76+XjDvPfTQQ+7mIEFDL7nkEtlggw0c0Ro5cqQjT4cc0hR7ZdGiRXLZZZcJylVFRUU8kjs/WzEEDAFDwBAwBAwBQ8AIlu0BQ8AQMAQMAUPAEDAEWhGBDqNgtSKm1pUhYAgYAoaAIWAIdHAEjGB18A1g0zcEDAFDwBAwBAyB3CNgBCv3mFqLhoAhYAgYAoaAIdDBETCC1cE3gE3fEDAEDAFDwBAwBHKPgBGs3GNqLRoChoAhYAgYAoZAB0fACFYH3wA2fUPAEDAEDAFDwBDIPQJGsHKPqbXYjMDf/vY3ue2222Tu3LkuRdEvf/lLSzOU591RW1srN9xwg5Dg/LvvvpMhQ4bI2WefLdtuu22ee+64zd90003yxhtvyOTJk+MgkFj+t7/9rXz44YfSo0cPGT16tJxwwgkdF6Q8zDwM9xdeeEFuvPFG+eKLL6Rnz56y9957y2mnneYCSFvJDQJhuPstX3zxxfL6668La9HRixGsjr4D8jR/DvgLLrhAzjvvPNl9993l8ccfdwf/tGnTZJtttslTr9bsH//4R7nvvvvkqquukgEDBgh5NZ966il58sknLcVTHrbH3Xff7bAmcLESrMWLF7svEnvssYccd9xxQuotghaT8/TQQw/Nwyg6XpNhuL/99tsyZswYOf300x2xmjNnjgsmTZo0y8CRmz0Shrvf8t///nc55ZRTXLYUI1giRrBys++sFQ8BUg0RGZ8/chAsLXyD33HHHeWkk04yvPKEwMEHHxzPu0kXy5Ytk+22204gXqyHldwgMH/+fLnooovknXfekf79+8s666wTJ1i33nqrTJ061R0wZWVlrkOySJDb9Omnn87NADpoK6lwR6kl5dldd90VR4cveqQ5mzFjhpSXl3dQ1Fo+7VS4a+sLFiwQ/v5ssskm8p///McIlhjBavnOsxbWQODzzz+X/fbbTx5++GHZfPPNDaFWRODYY4+VefPmyZ133inrrruu8I3zD3/4gzzxxBPOTGslNwhAnsAUtQSTFAeKKlgnnniidO/eXSZNmhTvDJMJahb/9+7dOzeD6ICtpML9448/llgsJptttlkCwTr33HOdCbdXr14dELHcTDkV7vTAl2q+QG+66abSrVs397ffFCwjWLnZfdZKAgLPP/+8jB8/3n2Lv/nmm4U/fOR8PPnkk2XEiBGGVh4RmDlzppxxxhkya9Ysl8ScA+e6665ziqKV/CBw/vnnJxCsAw88UHbbbTc555xz4h2yHvvvv7888MADstVWW+VnIB2s1SDuwenX1NTI4Ycf7j4D5KC1khsEwnD/05/+5DB+8MEHBQXXCFYT1mYizM2es1Y8BJDl+dYIqcKxnW+UzzzzjNxyyy3CBxGfCCv5QQB/q3vuucd9m+zXr5/cf//9zv9qypQpCd/s89N7x2w1eODsueeecsABBzjnai1c9MAniy8d22+/fccEKsezTkWw6urq3OUOfILAfOjQoTnuveM2F8T9008/laOPPtrhzN/666+/3ghW8/YwgtVxPyd5mzkHOioKTr2jRo2K9zNu3Dj3MzcLreQeAcxU+FlhFvQPcdaAG1WYsqzkHoFMFCwzm+cO/2QEC79DTLfTp0936q2p5rnDnJZ83FetWuUubvzkJz+RsWPHuo6MYK3G2whWbveetSYi7777rhx11FFrfFu/+uqr5cUXX3SKipXcI4B6xcHywQcfSEVFRbyDCRMmyMsvv+x8hqzkHoHgQY8PFqEZJk6cGO/MfLDyjzs94GgN/l9//bX7QjF8+PDcd9zBW/T3+5tvvulCkHTp0kVKSkocMoSKQUHkNW7PHnTQQR0WMSNYHXbp8zfx6upq2Xnnnd11XT/2D99wuFWFqdBK7hEgHMARRxzhzIJbb711vAPWAMJF/BoruUcgSLBQaO+991557rnnnB8cBYd3frdbhLnDP4g7cd+OPPJId3P2jjvukMGDB+euM2spjoCPO3/ruWHoFy57cGOW/7nQsdZaa3VY9Ixgddilz+/EOcz5I3f55Ze7wx71hFABmK+GDRuW3847aOsNDQ3u2yRX1THPEj5Ag70Sf+wHP/hBB0Umv9MOHvSLFi1ycbAwTfGlAkXx0ksvdd/mf/rTn+Z3MB2o9SDu/E68Pf7uDBo0KAEJbhAq2e1AEOVlqukuF5iJcDXsRrDysgWtURDAoR3nar7h8Afv1FNPdY6+VvKHAN/iCcuAKZafuTZ95plnuvhjVvKDQNiBA6kikjs3aPv06SPHH3+8HHPMMfkZQAdt1cedLxd8gcAnKKxws5lLN1ZajoARrOgYGsGKjpXVNAQMAUPAEDAEDAFDIBICRrAiwWSVDAFDwBAwBAwBQ8AQiI6AEazoWFlNQ8AQMAQMAUPAEDAEIiFgBCsSTFbJEDAEDAFDwBAwBAyB6AgYwYqOldU0BAwBQ8AQMAQMAUMgEgJGsCLBZJUMAUPAEDAEDAFDwBCIjoARrOhYWU1DwBAwBAwBQ8AQMAQiIWAEKxJMVskQMAQMAUPAEDAEDIHoCBjBio6V1TQEDAFDwBAwBAwBQyASAkawIsFklQyB3CNAWhuSpW6zzTYud11YOeOMM1xybFKsXHXVVbkfRBYtEsmZcb/wwgtZPJ36kblz57q8fW+//basXLlSvv/978tpp50mO+20U877sgYLD4GHHnpILrjgArHI7IW3dh1xxEawOuKq25zbBQIQrLfeesuN5R//+Iesu+66CeOCYJA0e8WKFR2CYC1ZskQOPvhg6d69u5x88skuSewDDzzgkiT/+c9/tnQ/7WLXtu0gyLP51Vdfyeabby7l5eVtOxjr3RBIg4ARLNsihkAbIQDBgjzNmjVLTj/9dDnuuOMSRkKC7N/85jfuIIFoFbuCRe5K1CvUiX79+jksyDEH6VpvvfXk1ltvbaOVsm4NAUPAEMgcASNYmWNmTxgCOUEAgkXp2bOnzJs3T+67776Edk855RSXKPjll1926o0SLEjHHXfcIffff7/873//k/XXX98lEtb2aKS+vl7uvPNOefTRR903/lgsJptttlmCuY2s97x/0UUXOWLz5ZdfurZ+8YtfOMUsWQmaCOkLEyf/5syZI7169ZIDDjjAJfeuqKiIN/Pwww/L7bffLpgBN9poI2fqOeGEE+SKK66QQw45xJlCSY589tlnr4HDF198IU899VTokKLOY8GCBXLttdfK66+/LosXL3aJsFHKRo4cGW938ODBcskll7hxoJzV1tbKrrvu6l5bZ511ZPr06TJmzJjQcYCdmk3/+9//yu9//3t59dVXXQJiEhGfd955TnmhfP31165fsGTdFy1a5H4Gh3/9618uYfeHH37o+mftzzrrLGcuTVUwq/Icz4P7j3/8Y9cn68EaHXHEEa5fcOY1Cmv/2GOPCaa3TTbZRJj///3f/7k2nn32WenSpYvst99+bk06d+7snmGfQYBramrc/Lbffnu57bbb3Dyvu+464YsB82GNwZfntXz00Udy9dVXu7mxj4cOHSqYwfmfgkL1u9/9Tt544w1ZunSpbLzxxu6Lx09+8hP3fpiJ8LXXXpMbb7xRPvvsMykrK5Mf/vCHbryqCPPMxRdfLH/5y19c26xt79695eijj5YTTzwxJ59la8QQCEPACJbtC0OgjRBQQsQfevyMMBOi1FCWLVvm/I5Qdc4999wEgsVhz6Fx0kknOf8tzIwccL/85S8FUkaZMGGCTJs2zR00HJoQOA4hiMWLL74oXbt2FYgJJIzDloMQgsDvHJocwoMGDQpFJkiwOKT/9re/ydixY904OcDoa7vttnNEsKSkxL3PYX/YYYfJ3nvvLR988IF7DwXvyiuvdMQirGA23HPPPR0Wf/zjH5MSrHTz+Oabb1wfnTp1csQPUguGzzzzjDvwDzroINc2WFVWVro+999/f0cGGd8ee+wh11xzjVsXFEe/gBdYQhQgp5AECAHkhDXhf0yckApMnuCqBAsixHpiFt1yyy0dGQbHHXbYwREASAzKHfUhYsnWhD0AERk+fLh77rvvvnNkp1u3bq5PyNHnn3/uiPO+++7r9gf7gD0E+dC9yPwZC4SH13gG0vajH/3IzVEJ1rvvviv77LOP/OxnP3PkbZdddnFkhdd/9atfuXFCUP/617+6vsAD7MB12LBhbh9AHm+++WbXB3sf3CHckDNwY+x8AWCd7rnnHvdckGA98sgj7vMBiaMP9jf7pK6uTiD0ECmeufDCCx3h+vnPf+6INZg8/vjjbg9CoK0YAvlAwAhWPlC1Ng2BCAjooYaqA4Hg4D/++OPdkxwOHGwcgigdqmChMnFAnnnmmTJu3Lh4L9S966675KWXXnLkAcVjq622cgeKFhQJ+kBpgphxYN5www1y9913x53IUV5U+dCxBKfiEyzIBkQEEyckTYsefBA/Dmfa5PC+5ZZb4nV4D+UsGcHi4OawBgPGzHzCSpR5TJw40ZEcVLABAwbEmwEf5oBKiMrHGCGGkFMtKG1PP/20zJgxY43uWY/DDz/cEQzWgIJKBjGmL0grBaIECUDBggAowTrwwAOd0qUF4gER4fAvLS11L6PkKMnUPoIDOfLII2X58uWOyOpzjI21gQBDuigQUQgl637ZZZc5VZP9BwmmMP/vfe97ToVCDaKwP1gjxoSKxr597733nJoHUaegIrFfmLuvWJ1zzjlOjWINIZioaGALxhQIJWtLmxAg1nj8+PHxvYTKxdrxGUAp8wkWX0Z22203Nybw1kKbjOHYY48V+tdnUErBV9eD9vgdxc6KIZAPBIxgC85+FQAACOdJREFU5QNVa9MQiICAEqzJkyc7QsTBgNmPgorBwYHqM2LEiDjBwsxx6aWXugOQg1ALqhGHBcoRaosW1BTMdhy2mK9QFegPwqbEhMMSlYXCgTZkyBBHxFARwopPsDgsOaiDt7pQELbeemtH8DhU99prr7iSoW3+5z//cXMLI1ioG8ydeTLfo446KimiUeYBNqg4zN0vevjSj5rIUFFQRbSgBKG0fPrppwnPQnwgV2AHDoohr0FYpk6dmlAf8xSKDKY8JVisuxJl1Lxtt93WqZDg7xcwhzxDVoKFyxA8x7ghun5BsYJQ3nTTTfH1hWyx5muvvbYzD2KG1gLBon+IrRbM0Lvvvnt8Hdi3KIK+yRaSiBr0zjvvJJiF2W+MCeK34YYbur0JceZLAsSbLxaKm+57TLgQSt6HQGGa1eITLEySEKmw/cMYwQWlKrjG2hZzon+et2II5AMBI1j5QNXaNAQiIOATrL///e/uYIOoYBrBjwTzCmYjn2Bx0CdTMegScxMHKD40EB/+h1hAHlBTMImpuUWJCb4rfuGQhVwFD3mt4xMsHQ8mP9/firqoOowd0xwKS9Acg6qDYhE8IDFv0T9mL9QFVV+SQRplHhC8LbbYwiksfkG5wrQFcYWkhM09rH1IAsTok08+cYe4mnZpm74gtckK5AYzGKqMP/f58+c7QhFGKCEwKEmoQMGizyXrD4wZoxYl6ZjGWJPg2rNvWC8tuk6oppgU/X2rdTAz6peDsHGokokvHXsGRQuCCrnCPIvKxv6pqqpyKifkDQKOqsgFDzCBKPoEi3mPGjXKKXDg5hfMtXzpYL8nC+3gf64ifFytiiGQMQJGsDKGzB4wBHKDgH9QcYhxkGBmwxcFUw6HA8U/CFBFLr/8cmfugogFCwc9BxWHtzos4w/DQYUCAinIJcFKpmChQOHHgxKH+oRaoL44OmZVRnySwWuYmlB4qO+bm1pCsJIpWA8++KDzz8EEiFN2VIKFGsXcIT2Ymvxy6KGHOtOZr4L572MmZJ5BgpVKwULNwwyHv1ewYFJkDKiFmASDBRIDwaagPHEBoX///o4cQtwwU2ph/upLpq+p2VhNbGEEi7XC1MfeCisDBw50vl1aIKiQckzJED5fydM6kDG+cKC+qT9fVAWLSx+oqIzJCFZu/l5ZK5kjYAQrc8zsCUMgJwgEDyoO0dmzZ7vDGR8pNdP4BGvmzJnuQETFwsyi5ZVXXnGHPWQBX5wwcyEhH6ZMmRL3uYqi/IRNNIoPljq1o1ygLqDq4FyMCVOL+vYowYIoQE4gAagYOHpHKVHmgd8Rh3/QBws/HZysfR+soHoXbF9JGXhiDgwWyAamN0gbsby0/Pa3v3U37SDIaiIMqnc4jbN+vg8Wqg6mNRzYMVeGFVRCTGngraW6utpdngB/VQFRSTHjcYkBVQg/Ksbat29f9xgEC2Ls32jFv4k5Ye5DRQojWDip4+CPioVpWAvkBt8/CCnBaekzaJZkndnTmDhRpPB5w4FeC2NGEQSTKD5YXEzgs8FtT0iuEawonyKrkw8EjGDlA1Vr0xCIgEDwoEJhwgSD2sQhpDfGgqYMHHf1QMOEiH8Vpq8NNtjAHXAoIShGKDKQBZyVUcMwE+FjhYmGNqMQk3QEi/chXIwXtYqbXigjOFFjmoJE6Xy40YjpCf8a/JkgW4xVlS0OYZQ5TJOYSP1CLDANcRAcU5R5LFy40N2gw1wKJlwEgARCNOgXYqcEIxXBwryHOgK+OGOj1DU2NsaHxBi5yUZfqImocfRFP5AWyANKUzKChY8VRAMc6Yf2IU2sMc8nC9WAsoU6CbHA5IZCxKWH999/3/mdESZCSa+qVpjYULxQhzTGGAQL/zFULuKPYT7GKZ8behBDShjBYl9BaPiCAC7sXRQq1oa1RIUiTAbt4jvIWFFgIbzMi30CgcRfD9Mgflv4bGES5fYmnwv2RZAs6e/+LUL2Hv5XzBf/MiNYEf4YWZW8IGAEKy+wWqOGQHoEggcVhyl+S9ymwnSiJUiwMH1wIHLTkPALXEXnlh6HUo8ePdxjKBOoNtyQ4yDDcZ2DD38jSA7f7KMQkygEi8McEoCyw3hQQzhIUR58vyx8yjB9YnKCKKCq4HvDOFC4IC2YzsKKH2MqG4LFM5qGB1MbWHODDjyCcbBSESzFLNnqqrM/Fxa4IQlhQrWCVLDeKFSUZARL1w5SA7mAWGL+w/8pXRws+oJc8BzhKPA5g5TwPGSKNYFo4bOkRU28SjIhWBBA6kPiIYeodBAcvZ0YRrBoD7KMwoZyh48ZsbIgcP4+gHRRhzFqKiSUL0g3BSIMoYIwQlT5LEB+IWQQ9TCyxJcHPg+ouyiG+JaBlx8HKyy9jvlgpf8bZTVahoARrJbhZ08bAoZABAQw76DuEDhSi8ZhgkxCdqy0PQLpLji0/QhtBIZA4SBgBKtw1spGaggULAIoEPg6obKhLGBKQqXB+TkYOqFgJ1kEAzeCVQSLaFNoNwgYwWo3S2EDMQSKFwHMPZjMcCYnNhcO2UR0x5E/7DZk8SLRvmdmBKt9r4+NrrAQMIJVWOtlozUEDAFDwBAwBAyBAkDACFYBLJIN0RAwBAwBQ8AQMAQKCwEjWIW1XjZaQ8AQMAQMAUPAECgABIxgFcAi2RANAUPAEDAEDAFDoLAQMIJVWOtlozUEDAFDwBAwBAyBAkDACFYBLJIN0RAwBAwBQ8AQMAQKCwEjWIW1XjZaQ8AQMAQMAUPAECgABIxgFcAi2RANAUPAEDAEDAFDoLAQMIJVWOtlozUEDAFDwBAwBAyBAkDACFYBLJIN0RAwBAwBQ8AQMAQKCwEjWIW1XjZaQ8AQMAQMAUPAECgABIxgFcAi2RANAUPAEDAEDAFDoLAQMIJVWOtlozUEDAFDwBAwBAyBAkDACFYBLJIN0RAwBAwBQ8AQMAQKCwEjWIW1XjZaQ8AQMAQMAUPAECgABIxgFcAi2RANAUPAEDAEDAFDoLAQMIJVWOtlozUEDAFDwBAwBAyBAkDACFYBLJIN0RAwBAwBQ8AQMAQKC4H/B7yhhu5jpWJMAAAAAElFTkSuQmCC\" width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 23.2 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# Feature selection\n",
    "\n",
    "def nearZeroRate(data, threshold=0):\n",
    "    zeroRate = 1 - np.squeeze(np.array((data>threshold).mean(axis=0)))\n",
    "    return zeroRate\n",
    "\n",
    "def meanLogExpression(data, threshold=0, atleast=10):\n",
    "    nonZeros = np.squeeze(np.array((data>threshold).sum(axis=0)))\n",
    "    N = data.shape[0]\n",
    "    A = data.multiply(data>threshold)\n",
    "    A.data = np.log2(A.data)\n",
    "    meanExpr = np.zeros(data.shape[1]) * np.nan\n",
    "    detected = nonZeros >= atleast\n",
    "    meanExpr[detected] = np.squeeze(np.array(A[:,detected].mean(axis=0))) / (nonZeros[detected]/N)\n",
    "    return meanExpr\n",
    "    \n",
    "def featureSelection(meanLogExpression, nearZeroRate, yoffset=.02, decay=1.5, n=3000):\n",
    "    low = 0; up=10    \n",
    "    nonan = ~np.isnan(meanLogExpression)\n",
    "    xoffset = 5\n",
    "    for step in range(100):\n",
    "        selected = np.zeros_like(nearZeroRate).astype(bool)\n",
    "        selected[nonan] = nearZeroRate[nonan] > np.exp(-decay*meanLogExpression[nonan] + xoffset) + yoffset\n",
    "        if np.sum(selected) == n:\n",
    "            break\n",
    "        elif np.sum(selected) < n:\n",
    "            up = xoffset\n",
    "            xoffset = (xoffset + low)/2\n",
    "        else:\n",
    "            low = xoffset\n",
    "            xoffset = (xoffset + up)/2\n",
    "    return selected\n",
    "\n",
    "x = meanLogExpression(tasic2018['counts'], threshold=32)  # Get mean log non-zero expression of each gene\n",
    "y = nearZeroRate(tasic2018['counts'], threshold=32)       # Get near-zero frequency of each gene\n",
    "selectedGenes = featureSelection(x, y, n=3000)            # Adjust the threshold to select 3000 genes\n",
    "\n",
    "plt.figure(figsize=(6,3))\n",
    "plt.scatter(x[~selectedGenes], y[~selectedGenes], s=1)\n",
    "plt.scatter(x[selectedGenes],  y[selectedGenes], s=1, color='r')\n",
    "plt.xlabel('Mean log2 nonzero expression')\n",
    "plt.ylabel('Frequency of\\nnear-zero expression')\n",
    "plt.ylim([0,1])\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of the resulting matrix: (23822, 50) \n",
      "\n",
      "Wall time: 31.8 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "counts3k = tasic2018['counts'][:, selectedGenes]  # Feature selection\n",
    "\n",
    "librarySizes = tasic2018['counts'].sum(axis=1)    # Compute library sizes\n",
    "CPM = counts3k / librarySizes * 1e+6              # Library size normalisation\n",
    "\n",
    "logCPM = np.log2(CPM + 1)                         # Log-transformation\n",
    "\n",
    "pca = PCA(n_components=50, svd_solver='full').fit(logCPM)   # PCA\n",
    "\n",
    "flipSigns = np.sum(pca.components_, axis=1) < 0             # fix PC signs\n",
    "X = pca.transform(logCPM)\n",
    "X[:, flipSigns] *= -1\n",
    "\n",
    "print('Shape of the resulting matrix:', X.shape, '\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initial data exploration (PCA/MDS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"400\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Principal component analysis\n",
    "\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.scatter(X[:,0], X[:,1], s=1, color=tasic2018['clusterColors'][tasic2018['clusters']])\n",
    "plt.title('PCA')\n",
    "plt.xlabel('PC1')\n",
    "plt.ylabel('PC2')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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d+Xpdez3PswantB9FNwcXdnPRBSztv2G5LRk9ntNt2roWL8dlh34E9pa2pjcezyszazYZ0mpyVi8bwWSUpIxrutwlHVwkX9HS7hFTiAlrAB6PCcQJVCCCneBE4j8lecf/garDm6Avq4epvWbBAsTcySlJuHuy4dwtLRDcloK9l86jISURNQqXwP3Xz1knfjecwCquFSGSFuEgPBArDi0jv3960Yd8VWtFvLvaAm3yAmkhBXACUQJFKDiXeAEIn8FEqYivWzExCbh7B0v6Ovq46HfY7yNDmPmrAaV6uHm89vIQQ4aVqrLdhvGhsaoWa4aNp3aDktTC7YbuXD/EuKS4tG1cScYGxjJv6Ml3CInkBJWACcQJVCAineBE4j8FSjG9Ij3Wez1OsQeQD4OIoy8UtGpAuyt7HHp0RWYGZmifqU6OHfPixX5ue+PKGXtKP/OKVGLnECUQBnchKUESlDhLnACka/yKMrq38uHYWigj6f+vqxx2oGUd3TF00AftgMhx7jYZOUT9BLXn92Cro4uBn7VD3u9DzDiGPv1cLXPMMEJRL5zT6bWOIHIBBuv9B4BTiBFnwqh0WE4c+c8PMpUwpFrJ5CYmv+GUHKQ0+6jZfWmqF+pLnyDX8HFzglPA3xw5cl1VHJ2R+taLXD+vhce+D1mHVo8fB4jHnUWTiBKoF1OIEqgBBXuAieQoitv0Z7lzL8hRHRFunCwssO3X/XFsn/XIC0znZ0FGdZhEM7cuYCHrx+jikslDGr7Dd+BCAH0fRmVz4UlxVjlWpQTiFzh1LjGOIHIpvLU9DQWZUUmqYnrpiM7R/rs0AZ6BkBODjtUaKhniJT0FDjbOsHM2BRh0eH43vNbONuWlq2DKlCL70CUQEmcQJRACSrcBU4g0ivv7L2LOH7jNKqXq4rBbb/B9C10ODBdUENGeobsRtL45ARW3sTAmJm86LAgnRMp51gWr0PfsM9a1WiGbk06C2pXFQtxAlECrXECUQIlqHAXOIEIVx4t+v/dOY8XQS/xLi4Sejp6zBS19cwO4Y3kKdnYowFehvghIi4ShvqG6NO8G2763EVUXBR0dfUwqG0/tU51wglEpmkj30qcQOSLp6a1xglEuMYPXD6KS4+vsgpVy1aGk01p3Pd7iPCYiHyNiHcT9Edx1BWZuyiFiTgCS7zDIOe618MrqFW+Omvv2I1TrK0J3UbBrVTuCXZ1FU4gSqBZTiBKoAQV7gInEOHKu+N7HzvO7YGpoQmyyXeRngrKVyWNtK/bhh0UJNJpU7sFjPSN2Il0avNtVBj+PLoJZkYm+LHHGDAfiRoLJxAlUC4nECVQggp3gROIdMojM9Y+r4N4/OZZvor6OnrMJ5KWkYZH/k/zfUaHCMvYOcHKzIqZqYzU8FS5dCjmluYEIgtqcq7DCUTOgGpYc5xAhCv8yZvn2Od9iGXRjYiNRERsBDIL7ECsTC0RnRAjaZTMUiGRIewMevNqTdCz2dfCH6jmJTmBKIGCOYEogRJUuAucQIQrb+OJbXga8Dz37bkAUdD5joys3DTteYUOEYpDfNvVaY1ODTyFP1DNS3ICUQIFcwJRAiWocBc4gQhX3hP/Z/jrv3+QlZX1UV4rMlEFvgv+qDFKUZKRmYHqrlXYuQ5tbW3hD1TzkpxAlEDBnECUQAkq3AVOIMKV5x/6RpJi/XO18pJJtbIe6NuyJ0yNTIQ/SENKcgJRAkVzAlECJahwFziBCFceRVzRRVExibFo5NEAV59ch2/Iq48aoDDeHs074L7vU3Rr3BlOanyaXDh6H5fkBFIU9ORUlxOInIDU0GY4gUiv+OzsbKw/vhUvgl9KKttZ2OJdbO55kNrla2DygJGIiUlCZmb+FCfkDzl16yxiEmLRrUknmBhq7s6EE4j0c0/uNTiByB1SjWqQE4gwdccmxuL8fW92WyAdJhRp60jSl9Dfxnw9DEkpSbj0+Bpa1myK1vUaFkogAeFBWHZgDXsoOdTJsa6pwglECTTPCUQJlKDCXeAEIkx5/5zfh1sv7n6yMGXPveVzFz5Bvux+89a1m8CzThvo6eQ/DEjX2S7dtxLxyYmMdCj3laYKJxAl0DwnECVQggp3gROIMOV5P7qKg1eOwtrMCvYWtihf2o2F5z549YjdeU45sa4+vSlJRUKtdmnUHm1qtfroAWQCo7rkK9Fk4QSiBNrnBKIESlDhLnACEa48OiBIV89+buGnA4YrD61DUloyxnYdhvKObp99AIX4pqQlw8zYXHhH1KQkJ5BCFHn48GFs3LgRQUFBKFOmDMaNG4cOHTqwksHBwZg/fz5u374NAwMDdO/eHZMmTYJIJJJ5SnACkRk6XhEAJxDpp4FfqD9ysnNQvnS5Qitn5WQiLjUalobW0MKnv9vpGWn438qJiIyNwOh+k1CvaiPpO6PCNTiBFFDekSNHMH36dPz8889o2bIljh8/jjVr1mDXrl2oWrUqOnfuDFdXV0YagYGBmDlzJgYMGIAJEybIPA04gcgMHa/ICUTqOUB3ddAOg6Rj/XYIjQpDi+pN4OpYFnGJsTAyMMaxGyfh/egaXB1cWFLEvJKUkoitB9eyO9C7tu6NmSsnso/bNemMfh0GS90fVa7ACSSP9ihN81dffQVPT09GIGIZOnQo6tevj9KlSzNyuXr1KszMzNjHe/fuxeLFi3H9+nXo6enJNBc4gcgEG6/0HgG+A5FuKrwKeY3VRzawSga6+uw2QSebUmhcoSa2HFgDOysHOLtVg2+IH4wNjLBgyOx8D7h05zy2HV7P/jb2m8kgQgkM9cfXrXrDzESzzFicQPJMDT8/P3Ts2BGHDh2Ch4fHR7Nyzpw58PHxwZ49eySfBQQEoF27dti/fz+qV68u3Ux+X5oTiEyw8UrFSCDxSYl49toX1cpXgrGhkcpjT5FW5Ai//+oRi8yiUNzod0G4ePMMG9vcCX/AN/Ql3Eu5w9nWOd94I6LDsWjLHLYDmTZ8HsxNLFQeD1kHwAkkD3Lnz5/HmDFj8M8//2DdunV49uwZnJycMHr0aLRu3RqjRo1ifo8VK1ZIaqWkpKBmzZpYuXIl2rdvL5MeOIHIBBuvVIwEMmvtH3jzNghV3dzx8/f5TTqqrAiyOqRlpMNATx+xCTE45nUA5ZwqoEW9VrC0NC70HIgqj1fefecEkgdR8n9MnTqVkQY5zitVqoQzZ85g/fr1+Ouvv7BhwwbY2dkxk5VY6C2mcuXK7G9du3aVST9EIPHxKTLVVbVKIpE2zMwM2Xhp3FyKjoAiMU1OTUF0XCxW796OwLC38ChXAbNGjGe38p257g2/oAA42TuiZd1GMDcxLfpglKAFcoyfvHwEz149go5ID8N7j4OlmZWgnlGSxvV7VyAkPAijv5kIZwcXQfVUtRB9l2n+yUO0cvLe9SiPFou5jZMnT2LixImYPXs2+vfvL3n6iBEj2M+UhfNTOxBytLdt21amHhNsdG0mF46AMiGQmZWFOX+uQlxiAlrWrQ9TExM0qF6DEcXz135Yu+cfSXd1RCIM7toDNStVVqYhyNSXw+cOYsv+jZK63/cchh7tekl+j46Lwq6jO+HqXA61q9TB7xt+g42lLaaNmIGQdyEYP280K9u9bU8M6TVcpj5oYiWVJ5B79+7hm2++YSasunXrSnRIuwsvLy/mSPf19WURWWKRlw+E70A08SsjnzErageSnpGBhVvXICs7m/k+6nlUx4U71xGbEIfYhPiPOq+tpYWp342GkYGhfAZWQq088LmLZdsW0G3oMDc1x7Thc1HazknSm22HN+LCjVxfSfO6X4Gc6iSTh8xCFbdqWLx1HiKiwjGiz3j4vH6KcmUqoLp7rRIajWIfy3cgefBNTU1F48aNMXbsWFDklViGDRsGHR0ddOnShYXtXrlyBSYmuQnUyKFOBHPjxg0ehSVgrvKIIQEgSVlEkZhee3gHJ69eQGBoKGwsLGDxPvrwU7vmsX2+g7W5pZQjUL7ikxaPQGx8DBrXao5hPcfn6+DBs3tw3PsA+1uHZl1x4eYZpKWnonwZd3Rv8w2WbJ3LLAp1qzTE7SfXWVqUlTO2wFgNky5yH0iBubt27Vps3rwZ8+bNY1FVJ06cwKpVq7Bt2zbmLKdzIC4uLpg8eTI7VEiEMnDgQOYzkVW4E11W5Hg9QkCRBHLu1mWcueaNyNhYkJnKyd6e+T+SU1NhYpQ/Gqu0rT2Gdvtg+lVl7Uz8fTg7E1K9Yi38OHBGvqGkpadh/d7lSE1Lwci+P+LPXUvhF+SLUrZO6NiiOzb/u5qVr1u1Ee48uQ4zEwssmZx7bkTdhBNIIRolh/nOnTsRHh4ONzc3jB8/Hm3atGElyWQ1d+5c3LlzB+bm5ujVqxf7vCi3lHECUbevVfGOR1YCoQAQEvHcTUhKxF9H98PY0BCDOvdCcHgo/rvujbDod6xcbHy8ZAdC/hFdndw8UOQ4LmXrgG879mDmq6evfZGdlYXS9o4quxtZtXMhHvjcY7uGVTO2FuqjpBQmlBIlJj4ad57eQK1KdeHj/xR/vT+kSBl+6f6Rrq37sAOH6iicQJRAq5xAlEAJKtwFWQjkbUQ45m1YwUyz88b8BCszC5y6ehGX7t2AoYEBXB3L4NytqzDU10cpOzuGjths9SnzVWXXCqjo4obDXqclaPZv3x3lnVUvW+3fRzbA6/Y52FjaYdGkNfkIJDs7C0v/+hU+/k/g6lQe/xu5QPI5RV/9umEGS22UmpYKKtu9TT90adlThWfYp7vOCUQJ1MoJRAmUoMJdkIVAvO7cwJbDuQdiJw4YhtqVq+LN22BsP76PLYY25la4/ug++9zC1JTtNgr6Pwojktb1muLC7SsSNDs1/Qp1Kst2wLYkVZKDLASG+cLWwgkZGZkICgtAafsyuHDzNDNXkXNcLCumbc53Aj0jI51hGPIuGKERIahbtaHaZu3lBFKSs/T9szmBKIESVLgLshBISloqdpw4CD1dPQzo0E1ijnoZ+BovA/2ZWevy/VvIyMxEYlISe6O2sbRkC6OYODIzM9kORizkLJ4yaBTexUThTUgQ+6x+lZpFSjRaUmoRYxoVFY8fF45khwydHFwQHBaQr0v6evoMowkDpqJ6xdol1d0Sey4nkBKD/sODOYEogRJUuAuyEMjnhhsTH4fdp44gIi6SFYtLSGC7DyIOyrxg9N55np2Tg6iYGNha5R6yq12pGjo3y/UVqrqIMY2IjMOYed8xh3k55wp4HfSSpW03NDBihwTJ90HSvmkX9Gk/SNWHLXX/OYFIDZn8K3ACkT+mmtSivAlk9Z5tuPXkAXR1dWFvZYWk5GRYWliAznmQiA+9xickICI2Fq6lS7O/9WnTBZXLVVAL6PNi+ibYH74BPmhYoyniE+NgbmoJQ31DRqinrxxFcHggerUbIPi0uloA9H4QnECUQJucQJRACSrcBXkTyP6zJ3DU+ywM9Q1Api6RtjbKli6dL9IwJj4euiId6OnqSM4/dW/ZHtUqqM5JdIpCe/PWDw7WpWBkaJxvBsgbUxWeXp/tOicQJdAsJxAlUIIKd0Hei92tpw+weve2fIi4OTvnI5CgsDB0b9UelAbp5tMHrGw9j5ro0OTj61+VFdqDZ3fjuPdBWJpZ49cJy5hZSizyxlRZMShqvziBFBVBOdTnBCIHEDW4CXkvdr9uXgn/kGBQKhMSawsL2FtZw8HGDkHhb9nf6nrUQPtGLfEmNBg7T+aeym7bsDkaVaujMprYtH81rj+8xPpL4boLflwpiZbKi2lySgr8gl6inFN56OsZqMz4iqOjnECKA+UvPIMTiBIoQYW7IC2BUHbdE1cusMy6dSpX+2jkS3esB2XhJdMV3c4XnxSPvAcHW9RphOa1GjC/B51Up3QnJCN6fAsHa1uVQTI+KQ4r/l6INyF+bCyrZ/wlMWXlxfSPbQvw0OcuKrlWwdShc1RmfMXRUU4gxYEyJxBuGlDgPJOWQNb/uxNXH9xhOZo2zFrI7sIgIZK48egubj19iMSURJgYGoEirYhM4hMT2fOLoaoAACAASURBVAVM5qamGNy5N8qWyr1kicjo6KX/YGNhBTrzoWpZpSldyZkrR1G+TCXU9qhf6Dz9ZfVURjKOtqXx2w8f7gL6lEpTUpPZ6fRSeRIwKlD9Jdo0J5AShT/34XwHogRKUOEuSEsgp6954Z+Th0G5qxaM/1ni2zh++Tz2njnGSKBXmw6o61GdpXLfffoIM2mRNKlZF73bdIK1heonTPycyvNiGhYRhluPr6GORwPY2zh+dqbQIcKfl41j50YGdB6KprVbglKa6KhhHiwCghOIEiwcnECUQAkq3IW8i11qWgYzPX1pJxAZEw1zUzMWmvsqKADODo5sV/L38QPMD7B88i+wMDVjqLyLjsTPKxeyHQqJnq4ulk78HyzN1Pf+b2lJWTx9EpMT8MPCoSzEl7LxUmp4ivCaN26pWt6XzglECRYOTiBKoAQV7oJ4sTt39QaW/7MVZRxK4ZcRP7LsuV+SbUf34/ytq2w3snDCNDx59QI2FpZwtLXPVzUqNgZnb17GicsX2N8X/TAdpQqU+dKzVOlzWQmExkik4R/8EiKRDg6f38uGPW3YPLiXVZ0QZ6G64gQiFCkFluMEokBwNaBp8WK39K+/cO5Gbh6qlVPmwMrc4oujX75zM+75PIGxgSHWzfyQFLCwipSy48Ltq8zfUZjz/YsPU6ECRSEQ8TCTU5Pw73//wMzYAl+36lWkjN3KCh0nECXQDCcQJVCCCndBvNj5vArAzhOH4eZUBp2bC0spQjcLXr53C9UqVELZUk7M57Fo2zrkZGfj5+9Hw8JUfc1Un1O5PAhEhaeU4K5zAhEMleIKcgJRHLaa0LI8F7vrj+5h7b6/GWwje/aHu1t5HL9/BaUsbeFZreEXfSvqgrc8MVUXTAobBycQJdAuJxAlUIIKd0Gei110fCzW79/JHPFj+w7GpZcPcPv1M4bOhHZ9YWmc61hXd5EnpuqMFScQJdAuJxAlUIIKd0Feix2d95i6YgEzY/3QfwgL4w2IDMW+m+fgaGGD/o092dkRTRB5YaruWHECUQINcwJRAiWocBfktdiFRoRj6sqFDIlurTzR86sOKoxK0bouL0yL1gvlr80JRAl0xAlECZSgwl2Q52J38fZ1hEa+Q9eWbfE2LgqxyQmoXbYiOwynSSJPTNUZN04gSqBdTiBKoAQV7oIiFruohFisObefodKuagM0qqB619IWRaWKwLQo/VHWupxAlEAznECUQAkq3AV5LnbXXz7CvTcvYGFsilfhQQyV7nVaonoZ9bgoSqia5Ymp0GeqYjlOIEqgNU4gSqAEFe6CvBY7Sr8x//AW5CBHgoapgREmdRigwujI1nV5YSrb01WnFicQJdAVJxAlUIIKd0Gei93Gi4cQGpt7F3opCxs0da+JyqVdlRqdGw8v47jXQbRt3Akt6gk7QPmlAckT0y89S5U/5wSiBNrjBKIESlDhLshzsTty1xsPAn1R2bEs+jRsqxKoTF8+AeFRoTA3scDyaZvk0md5YiqXDilpI5xAPqMYf39/9OjRA7NmzWL/kwQHB2P+/Pm4ffs2DAwM0L17d0yaNAkiAYnrPvUoTiBK+u1QkW7Jc7FbfnoX4lOSYGNqgbFteqsEAudvnMbRi/vRvunX6NCsq1z6LE9M5dIhJW2EE8gnFJORkYF+/frhyZMnWLhwISMQ+lvnzp3h6urKSCMwMBAzZ87EgAEDMGHCBJlVzAlEZuh4RQDSLnbk6zh815uZqnrUbQUHC2sJjn7hwbj3xgf1ynmgrG0pvI2JwN03PqhZxh3O1vkz9Koz+NJiqs5YfG5snEA+gc6yZcvw4MED3Lx5U0Igx48fx/Tp03H16lWYmeWmdNi7dy8WL16M69evQ09PT6Z5xAlEJth4pfcISLvYRSXGYc3Zfax2/XJV0KFG409iufbcv4hIiIGFkSl+8OynMZhLi6nGAFNgoJxACtE8mafGjRuHw4cPo2XLlhICmTNnDnx8fLBnzx5JrYCAALRr1w779+9H9eqyxcpzAtHUr598xi3tYpedk40Dty4gNC4Kveq1ZokSPyXH7l9mO5KqTm7oWa+1fDqsAq1Ii6kKDEkhXeQEUgDW+Ph4dO3alZmounTpgooVK0oIZNSoUczvsWLFh3uRU1JSULNmTaxcuRLt27eXSUlEIPHxKTLVVbVKIpE2zMwM2Xhp3FyKjoAiMSVzF/lEzAyNNSYTL2lEkZgWXePK0wJ9lwkreYhWDs02FRciDhrG8uXL2UjyEsh3330HOzs7ZrISS3Z2NipXrsz+RsQji9DzvnQFqSzt8jocAY4AR0BVEFB5AiGTFfk+jh07BnPz3It0hO5A1qxZg7ZtZQt75DsQVZniytlP/rYsf71wTIVhyncgeXAaOHAg7t27l88ZnpyczH4vU6YM6tWrB19fX+zatUtSi/tAhE00cSluW5YOLyGlOaZCUJKuDMdUGF7cB5IHp/DwcKSmpuZDjhzkkydPRseOHVlUFoXtXrlyBSYmJqwcOdTJfHXjxg0ehSVgzvEvpgCQpCzCMZUSMAHFOaYCQALACeQLOOU1YaWlpbFzIC4uLoxU6FAhEQrtXChqS1bhUViyIsfrEQJ8sZP/POCYCsOUE4gUBEJFyWQ1d+5c3Llzh/lJevXqhfHjx0NbW/ZIBE4gwiYrL1U4Anyxk//M4JgKw5QTiDCcFFqKE4hC4VX7xvliJ38Vc0yFYcoJRBhOCi3FCUSh8Kp949Isdu/io/EgwBfVnMuze8658F1dUeYAJ5CioCenupxA5ASkhjZDBPI8/DW8Hz9As4q1UNHR5ZNIbLhwEGFxUbA0MsUEDUpNIu3UkIaUpW1bncpzAlECbXICUQIlqHAXaLFbcGQbUtLT4GBujZGtczNHFyaH7njhUdBLuDuUwTeNPFV41IrtOicQYfhyAhGGk0JLcQJRKLxq3zgtdpde3oP3kwdoU6U+y6T7KaE8WJEJsbAxsShS4Ie6g8oJRJiGOYEIw0mhpTiBKBRetW9cvNiFhEchNS0dZoa5Z5S4yI4AJxBh2HECEYaTQktxAlEovGrfOC12Wno5mL/3L6RnZmBA4w5ws3dS+3ErcoCcQIShywlEGE4KLcUJRKHwqn3jz/2f47H/MzyJegeRjg7aVW2ARhVku1pA7cESOEBOIMKA4gQiDCeFluIEolB41brx5NRkjF7wAygrtJurO0TW1tDX0cPoNr1gamCk1mNX5OA4gQhDlxOIMJwUWooTiELhVevGMzIzMGrBD0hPT4OjSzkY29ix8Q5q2hGutqXVeuyKHBwnEGHocgIRhpNCS3ECUSi8at/4vzfP4t6rp6ju5sF2HYZ6+mhZuQ4ev3yK2IRYNK3ZGCKRSO1xkOcAOYEIQ5MTiDCcFFqKE4hC4VX7xrVFWsjWyYR2pg6ys3LvdAsKD8aM1bPZz4O7fIs2DVqpPQ7yHCAnEGFocgIRhpNCS3ECUSi8KtV4anoadEQi6Ih0BPe7sMXuXXQEpq6ciaysLIztOxINq9UX3B4vyDMcC50DnECEIqXAcpxAFAiuCjX97LUPFm9fBnMTcywYNxfGhsKc4J96Ww6LDEdiSiLKO7upEArK0VW+AxGmB04gwnBSaClOIAqFVyUaT0lLwez1vyE0IpT1d/6YX1C21KdzWuUdFF/s5K9ijqkwTDmBCMNJoaU4gSgUXpVo/OaT21izZz3ra12P2pjwzRhoaWl91Pfg8BAc9T6BGu7V0KRmI/Y5X+zkr2KOqTBMOYEIw0mhpTiBKBRepWw8PSMDqempOHX1P1RwdoObsysWbFmCrOwsTP9+CqwtrArt94p/1uDu8/vQghY2zFwNQ0NDTiAK0DAnEGGgcgIRhpNCS3ECUSi8Stf4tqM7cP6WFzNRvXkbwHYa62asREpaKg5fPAZ3l/JoXrtpof0+d/MCth/7h31W2bUSZgydwglEARqWB4GERb7FX4fWw8neGQM6D1XL5JWcQBQw+aRtkhOItIipdvmxv/+I+MQE6Orogg4CmhmbIi09DYYGRuzcBslPA39AREwkUlKT8SroNfp69kJpu1Lss9nr5uN1yBvYWtpg2U+LOIEoYDrIg0D2nf4bp68cY72bP2EZSts5K6CnJdskJ5CSxZ89nROIEihBwV1ISknCzSd3UKVcJZy8cgYXbnuzJw7pOggvA1/j8v0rkh442jogPOodS08ilsbVGyAzKwuUjt3IwAhxifHo264nnB2clIZAIrQS8FgnBE0zykMPwsOQFQy9TM3Lg0D8gnyxeudilLJzwqTBM6GjoytTX5S5EicQJdAOJxAlUIKCu7B6zzrcenIH5iZmmDF0Kn7d9DsM9A0we+RMxMTHYNepfcx05V6mPAz0DbFk+3LmIyGySMtIY+aqJ6+e5uulOFJLHotdUYefgxzUtVqAIFEMBqU0wNLE3kVtskTrKwOmJQqAwIdzAhEIlCKLcQJRJLrK0fbGA1tx+f5VidkpJyf3xLhf8Gss3LIEJkYm6NW2BzYe2MJ8Il2ad2TRViQ/fDMW24/vRGxCHPuM6hobGGHRj78xQlKGxY4IpKL1bMRqJ6Nbak1sTPhWOYCXsRfKgKmMXS/WapxAihXuwh/GCUQJlKDgLqRnpOPJq2cs2kpfzwCX712FvZUtnr/xxfFLJ9nT7a3sEB79jv3cuHpDXHt0g/1MOxbfgJeMUDo0aYc2DVpDX1cPhgaG7HNlWexO6z3Bb8an0DWtBiYnt1MwooptXlkwVewoi946J5CiY1jkFjiBFBlClWggMzMTT/ye4p7PQ1x87wOhjpeydcTb9wcIW9dviVeBrxAYFiwZ069j5+Dhi0fYf+4g23msnLoU+nr6ks9LcrFba+iFw/oPMSupI/Ya3ME+g7usXy8i58EyR9hJemVUXkliqox4fKpPnEAKIBMbG4tly5bBy8sLiYmJqFixIn766SfUrVuXlbx+/TqWLFmCV69ewcHBAWPGjEG3bt2KpHNOIEWCTyUqk0P8ty2L2U7CQE8flPNKLBXKlEdweDAszSwRn5SAxOREyWcuDmXw67jZ2HVqLzszQll1105fwXwjYimJxe6hTjAGm/2Ft9pxgBbQLL08jHL0cFbvORpmuOJg3ChoQ1sldFNYJ0sCU1UEixNIAa0NGTIEUVFRmDVrFqysrLBr1y7s378fBw8eZCW7d++OoUOHokuXLrh48SL++OMPbNmyBY0a5Z4KlkU4gciCmmrVufn4NtbszT1prqejh0nfjkdgeBDeRoTB684l9vdOTdvjxJXT7GdHGwd83bITGlSth8ysTDz0fYzImChUcnX/KLdVSSx2c4yPYa1RbiSZcbYeBqc2kvz+R0IvDExtqFoKKtDbksBUFQHjBJJHawEBAWjXrh12796N2rVrs0/IYenp6YlOnToxYvHx8cG+ffsktWh3QrsWIhFZhROIrMipTr3Xwf6Yvf5X1uHq7tUwZdCP7Of7Pg+wbOdq9nOP1l1x/fEt2FvaYnSf4ZJdBkVkPXr+AA62Dljy06KPBl0Si91L0TuMM92Nipn2WJ7YB+Ha8fjKcjlSkYETsePhkeWoOsoppKclgakqAsYJJI/W4uPjcf/+fbab0NPTk3zStm1bNGvWDDdu3ECbNm0wadIkyWe0O/ntt99YvcJyFwmZFJxAhKCkXGXoxcI34BXsrW1hYWpRaOfokCDtPJwdnOHi6MyuniXzFJmfHKztMLbvKDx+9RR0Mp3Eya40gt+FsAOGW+fk7lZIpiyZirCwIPbzr5MWwqV02XzPK47FzlcUDtMcAxjk6GKN0UV4ZDqiZ1ruS5ZY0pGJbOTAAKp/3qE4MFWuGS1bbziBfAG3U6dO4ccff8S6deswefJk9q9///6SWt7e3hgxYgTzjZDJSxYhAomPT5GlqsrVEYm0YWZmyMZL41ZVOep1ArtP/wtjQ2P8Of2PfE5t8Zj2nP4XR7xOMEKYOvgHLNjyByjcVSx9PXuiY1NPHPM+CVNjE1Bk747ju9GybjMM6zFYUu7ijYvYuHs9tLVF+GPGMrYTySuKxvS07lP0N9nCyOObtLr4y+A6e/yj2FlwyrFUVRV+tt+KxlRdQKPvMmElD9HKEQe3y6M1JWjj7t27GDZsGNuRrF27Fh4eHpg3bx569eol6R0Rx3fffQciEnKqyyIEm6y7F1mex+sUHYGN+//GwXPHmVN7z5JNjAAKys5j+7Hz+H4Y6hvg++79sXbPVkkRHW0Rxn87Ap5NPtwUOG/9Uly7fwt9PLtiSI8B+Zp74fcCxkYmcHIs/nvO1+AixmMP6898fI1ZOApHmMMX82ACg6KDyVvgCABQKwI5d+4c223UqFEDGzZsgIGBAWrVqoUpU6YUugO5desWzM3NZZoIfAciE2wlWik1LRUXb1+Cq1NZVCrrXmhf6DbA+y8ewcmuFMuuO3/jIrwM9MtX9tdxv8DNyZX9bfjccUhMToChngHW/m8lO6kuRBT9tkymqc36V2GfbYaeGbUQpB0Ny2xjmOBDKLGQfqpSGUVjqkpYfK6vfAdSCDo7d+5kfg3yfSxdulTiD+nYsSNzspNJSyzkA1mwYAFot6KtLdtWjvtA1OXr9PE4omKj8TrkNWq4V2e7zPs+D5GQnIBtR3ey338bO4flsyLZdmQHzr8/VNi0XguM7DdKEDDcXi8IJqkKcUyFwcV9IAVworDduXPnYuDAgZgxY0Y+Uvjll1/Y+Q8qIxZyqMfFxfEoLGHzTWlOTQvsbpGK0dmP8Yt+QnxSPBpUrYtx/UZL2nvxxpftMFwcy0j+9jrIH7NXzGC/t23qiUHdvxP0fL7YCYJJqkIcU2FwcQLJg5O/vz8739GyZUvMnj07H4JkwgoLC2PnQMjnQf+T34POgWzevJmfAxE23zSCQN5FR8DEyBgGegYYOnc0O8dBuw26/2Nsn5Gwt7b7JFq+/i8Q+DYAzeq1KNQxX1hFvtgJnHxSFOOYCgOLE0genNavX4/ly5cXihwRxu+//45Lly6xk+hv3ryBk5MTxo8fDzJtFUW4Caso6ClX3euPbmLtvo0wNTJBh6aeLM9VcuqHCDs669G99ddy7TRf7OQKJ2uMYyoMU04gwnBSaClOIAqFt1gbP3DuMA575V4iJL4wytTIFCJtbeiIdNC20Veo5FoR5Qqc5ShKJ/liVxT0Cq/LMRWGKScQYTgptBQnEIXCW6yNJ6cm48Tl0+z2wKCwYJy/7YWU9zuQquU9WEZebS1tLJ+8CFbmsp0bKjggvtjJX8UcU2GYcgIRhpNCS3ECUSi8xdJ4ekYGHvo+QrnSrixkVyxJKcmYtup/7AbBlnWbsyy8dHZkxeTFnzzBLm2H+WInLWJfLs8x/TJGVIITiDCcFFqKE4hC4S2Wxrce+ZuRA13wtGrqH/mi9+gukLSMdJaKnZIi2lhaw9k+N3RXHsIXO3mgmL8NjqkwTDmBCMNJoaU4gSgU3mJpfOPBreySKBOW2mSFzGeCZOmsqi922dlZOHf9EFLTU+DZpBf09XIvyipJUXVMiws7TiDFhfRnnsMJRAmUUMQu0Mn0W0/vwL1MBTjY2BexNemqq/pi9yrwKf45vooNumPz/qhXtYV0ACigtKpjqgBICm2SE0hxIc0JhCHAv5jyn3CqjmlCUhw27v8V6RlpGNJ9Kuxt5GfekxVtVcdU1nFLW48TiLSIKaA834EoAFQNalIdFjsyY1FSUZFIRyk0pw6YFgeQnECKA+UvPIMTiBIoQYW7wBc7+SuPYyoMU04gwnBSaClOIAqFV+0b54ud/FXMMRWGKScQYTgptBQnEIXCq/aN88VO/irmmArDlBOIMJwUWooTiELhVfvG+WInfxVzTIVhyglEGE4KLcUJRKHwqn3jfLGTv4o5psIw5QQiDCeFluIEolB41b5xTV3sUtOSkZAUCxtLR7lfCa2pmEr7ZeEEIi1iCijPCUQBoGpQk5q42NEdK/vPrAWRSJ0qLVHdvaFcNa6JmMoCICcQWVCTcx1OIHIGVMOa08TFLj0jFbtOrEJOTjYql6uD2h7NoK0lgo6Orly0r4mYygIcJxBZUJNzHU4gcgZUw5rThMUuIzMdZ6/tR2p6Mto07AUikGd+d2BkYIpSdi44e/1f6Ih00e2roTA2NC3yDNAETIsMkjJn442NjcWhQ4cQGBgId3d3dOvWDYaG+ZOsBQUFYe3atVi4cKE8sCixNjiBlBj0avFgTVjs3r57gzNX9zB91a3SCk9e3WTmK0cbF7iUrohr905DW6QNz6b9UMq2bJH1qgmYFhkkZSUQIo3+/fsjJiYGJiYmiIuLQ6lSpbB69WpUqVJFMu6HDx+iX79+eP78uTywKLE2OIGUGPRq8WBNWOwyszLgdesII42W9bvC+/ZRvIsOQUXXmkgIiMTl/46gXNVq+H7ULLk41DUBU3lMfqU0YdE947S72LRpE2xtbXHjxg3MmjWLEcqWLVtQo0YNNnZOIPKYAsXbRlG/mBkZ6Xj2+BZKO7vBxtaxeDuvpE8rKqZKOqzPdouc6HEJkbA0t8Oa3ybjXWgQTM0t8fOCjXIZjiZiKgtwSkkgTZs2xS+//IJ27dpJxhQdHY3Bgwfj3bt32LVrF9zc3DiByKLxEq5T1C/miUNbcf3yKRgYGGHavM1yc5qWMCxFenxRMS3SwxVYOSYuApfunkI5p0qo5l7/k0967fsU171OoA7dN1+tjlx6pK6YygWcPI0oJYHUr18fS5cuRfPmzfONNzw8HH379mWX9ezduxdv377lJix5zwgFt1fUL+aJQ3/h+uWTMDA0xrS5mziBqHGK/INnt+Dxy1vQghamDV8JPV39QmfnQe+/EBcbAXeX6ohLiEJFlxpwK1M1X9mk5HgYGZpAS0tb0Awv6jwV9BA1KKSUBDJw4EBYWVlh5cqVH0H84sUL5h8pXbo0xo0bhx9++IH7QFRoIhb1i0kmLJ+nd1DKqRysbRxUaOSK62pRMVVcz4rW8p0n3jhxaRccbctgeK/phS7+sYlROHh2IyMZsejrGqB/5x8lv3vdOgbvO8dRoUxV9O88XlCn1BVTQYOXopBSEsjNmzcxdOhQZqYis1WPHj3yDen69esYM2YMMjMz2T/uRJdC4yVcNO8X0+vcEbx68RCenb+FY+miR86U8NBK7PHqvNglpybCQM/ooyuCs7Iy2d0hQWF+OHt9P6OPrPRMJEXGoVad5mjesItEH9sO/4GAt77Q0zXA9OEfv5QWpjh1xlSeE1UpCYQGeP/+fWzcuJE5zEeNGvXRmJ89e4aZM2fCx8en2AkkOzsba9aswf79+xEfH486depg9uzZcHFxkUk3mhiFFfo2AnN+Hsjwql6rCfoM/PDGSH9LiI+BtrYIxiZmMmGqSZU0bbE7cmE7Hvhcw1cNu8PK3AY3H51j6g658wKpsYnMrKmnb4BBY2ciPMQX6chCeEokqpSvgwou1QRNDU3DVBAohRRSWgIROiCK1nJ2dhZaXC7liDzIkU/nT+zt7bFkyRIWNXb8+HHo6elJ/Qx1IJAXz+4iOPAVGjXrCCPjjw9y0Y1zd29ehImpKZq3aoPo6ERsXfcb/HwfobVnbzRt9bXEnxHg74NNq38BkIOv2vdFq3a9pMZUkypo2mK3aMtEFs5byq4sBnaegEe+N/Ay6DECbz1FUmSsRPU16jZCROgL9nunvj/g6gXynRnh677DoaP7+RPrmoaprN8XpSaQ9PR09oZvY2OTb3wnT55E69atYWBgIOu4Za5HfWrYsCGmTJmCb775hrVDfWzWrBkWLFiATp06Sd22qhNIclICFv4ylF1J2rBpB3TuMeQjDO7euohDe9ayv0+bsxIWVk7IzMzG9k0L8PL5fVSuUg8Dhk5FTHQEfJ7eBjnLSSyt7fDTzD+lxlSTKmjaYvf01V089LmKrOwMZOdko4JLdbzwv4/ExHhEBL1Fdmwq9LL10KRle7x45A0dXT1UrN4KZ4/uZtNi4OjpqFi19meniKZhKuv3RWkJ5PLly5g+fTp69uyJiRMnSsYXERHBFmsLCwusWrUKFLFVnPLo0SP07t0bp0+fhqurq+TRRCYVK1bEnDlzpO6OqhMIObaX/TaOmZ06dR+CRs06fITBi2f3sGPzQuYILe1UFtk5Ofh2yM/Yum4eIiPewt6xDFq06YF9O1bA0MgETmXKI+xtADp3H4IqNeSbKE9qBSl5BU1Y7F4FPkFQ2CvUqNgYVuZ2CAl/jf+u7WOaqVmpKV4HP2W+koTkBLy4cB0Zyakwt7LByJ/mMwJJiIvF1lXzoG9giJE//QpjU3NOIHKY10pJIOTX6NOnD8qXL89IpF69epKhZmVl4dKlS4w8/Pz8WLoTcrYXl/z333+gg450iDHvDoiiwVJTU7Fhwwapu6LqBEIDTk1JQlRkOPNZJCfFw9fnAerUbwVTM0tGLEbGZlg0ZzhotyIW98q14Pv8PnR19ZGVlQEDA2MkJ+d+/uO0lbCxK8V+fvP6OXZvWwoHRxcMGjETIpFIaozVuYK6Ewj5HP8+uoTtcJ0dyqNNo15s50G7EHp5qe3RPF8495nDO3H57BE0atUJHXsOxuOXN/DQ5xo7od6l5XcwN7X64nRQd0y/CIDAAkpJIJMmTUJwcDB27tz5SZ9CSkoK2wlUrlyZ+SCKS44cOYKpU6cyxz2dRxEL/Y0OOW7btk3qrhCBxMenSF2vuCvQl5X+GRmZfPRoIvblC35kuwl648vMSIdHtXpwca2EU0d3sP+jo8IZmZCQozMzM+Ojdho0aQcX14qoXb+l5LNjB7biqvcJ9vvk/62WEEtxj19ZnycSacPMzJDNIZpL6iZEHKcv70FwuD+a1PKER/kvHxZ88vIOHj+7gbigcKTpZMDIOjcYo457M5jqmcGtYrWPIrvy4qbumMprjtC8I6zkIVo5pGk5SKtWrUAk0qXLh1C8wpqlKKj169fj/PnzcniqsCbOnDmDCRMmFLoDIf/IYMAZuwAAIABJREFUunXrhDWUpxTBRm9HyixJiQmYM20EEhPiMH7yr/Colt+GTJ9PGt07HzlUrFQD+oaGeHT/Bgu5nLt4E2ZPHQ4KwSwo5cpXQnhYCEQ6upjyv6Wws8/dfZCEvQ3Cji0r4Ozihr4DRys9VsqsR1XtG31HKB+Wrs6Xg1QSkxOwac8fCHzgg+SwWEBLC64ta8JAzxCvLt5BRno6eg8agTad8x8PUFVs1KXfciMQCt3dvHlzPtNVYSDdunULw4cPZ4t5cYnYB3L27FmUKVNG8ljygVSqVImF80orqrADCQl6jdVLprChtev0DVp75kZGJSclstQib4P98fTRzY+GThFW5Bh3c6+KKtXqYe60wR+VGTNpISOmvzf9zj7r1mcEGjb1lArG+LgYGBoZQ1f3ywuMVA2rQGFNfFuOjY7A5hXzmL6HTZwtCfd+5ncPtx5dRHpmKkJev0Ha62iIjPXh0rAKOycScOURBfehRcce6NB1wCe1q4mYyjLVlXIH0rZtW3ZQsHv37p8d0+HDh5kv5MKFC7KMXaY6tMto1KgRpk2bxkxoJOoahZWRnsYiW8zMLXHyyHYE+b+AQ+mySE1JRuS7t9DV00NIkF8eHGkX9fEmlBzndPGPjq4+MjPSJOXJ90FOzRq1m6J2g9a4fP4w0tJT0b3PqEJDgT+lsHu3LuLgnrWwsrbHhJ+Xa1x6E02019++eg5HduX6G/sPnww9e1OcfXgUaSnJMIUhO1gYh2SkJiWjXuVmCAv1R1JGEiLehiI7OQPffvsTyjlW/OQaoImYyrIgKqUPhCKZyMewZ8+eT5oryLFGKU0cHR2xfPlyWcYucx16HvWNwnYppQr5YMhnc+zYMbU5B0L+iT9+Hct8FnS2g/JPkejpGSA9PVVm7D5V0cW1MoaPnydTu8cObMbNq2dY3enzNsPY5PMRNjI9RIkraeJil5QYj31bV0BXTx+9v5uAbd5rEJcczYjDBrn6z0EOWjfogbKlKrIXmFPee3Bt/yH2maOzK/OB9Bv6EyytbT/SriZiKssUV0oCefPmDdt9UDJFSuNe8BxIVFQUfv31V5AZiRztNWvWlGXsMtchh/GyZctw8OBBFnlFUWKUPdjJyUmmNpUxCsv/1RNsWTuXjcfe0QWx0e+Qlvaxo19LWxs52bI7brVFOsjOymQvCgOG/IxKVb7sIC0IMpGc97lDcHKpgJp1msmkA1WupOmLHR1S9Xp8CndeX4UB9NgOJFe0INLRQat63eBkXw4b9v+GYO/85m7Pbt+iWduunEBk/AIoJYHQWIgcKLIpIyODXSJFizMt3JSBl9KY6OjosDMXdFOhqosyEgiZptYtn1as0NZt+BW69fk4bU2xdkIFH6buBJKckogDZ3NT9/doMxT6eh8OEJNz/ZjXdkTFhqFGpSbsWlsK2U3NSkECkpGJbIiytDDU8ydsvbgSCU+CkRGSGypubmmNIRNmw9ru43tlhGJKO3VK5EhEpYmitARCyqD0IH///TeuXLmCsLAwtuUkkxHdFzJgwAD2szqIMhEIfSEpvcije1fx2u8pMtJSkZQUL4GZTAbkGymK2Ds4IS0tFbExkZJmnMtUQI/+Y2Frpx46LQo+0tYVuthJ266ylL/37AqOee1g3enjORKV3T5EANJ5kB1H/wDtQso4VkBKWjICol8jCR/MrDSndbV0INISwcWuAsIevYCxjjFatukJ57IVJMPMys7Eu7gw2Jk7Ql9PF5aWxoiJSWIZEwqTyNC3WD9nBts9j573O6zs7JUFsmLrh1ITCEU8hYSEsGinvFfZFhs6xfQgZSIQ8iWQT0EsRTVRFQYhOd+/Hfoz/lo3n338dY/hqN/0w+VhxQS72jxG3QkkLiEaO46tZFaHQV0msns98kpw+GsEhb5CuTIeOOm9E3FIQjreh4rnAHpZujDTIce6FrR1dRFy+xmSI3Nfin74ZQVs7XNfWg5c2w6/cB+4l6qKXk0GfpFAHly9hH/Xr2Z1+42fhKr1G6nNnBI6EKUkEIpqGjlyJB48eCAZB/k5yHnt4KB+d0AUN4HQ6e8Du9egXPmqLAsuvUElJcZh46pZSEiIQXrah7c3cQSV0An1pXK01c/KzH8OhBzo9Nxe/cehTNlPR8Z8qW1N/VzdCeRLek1Mjscu7/WITY2BuZ454tLjoA1t1C7fBO4OHjh/dT+yc7JYM9kZWfD3/rCujJ/5B+xL5Ybjbz67DNGJEbA1c8Bwz4lfJJD0tDSc2bODWUY8+w38YoLGL41DFT9XSgKZN28eDhw4wEikatWqeP36NTswSD/T+RB1k+ImkP3/rMLDu5cZjDPmb2Uhs08eXMOev3Oj2WrUaY4K7tXx7+41cofa3MIacbFRrF06sU5x/CnJiez3Og2+Qve+3AciLeiaSiBkmrrx8Cz8gp4iLCEUKcGx0LM1gY6FIYygj6bV2qOCczXsPbWapT5xKeWOSq61cXTXJrz194OlqwOsK7qgZ4uhuHZ2H1LTUmBasRyqlasHe0uHLxKItHpSx/JKSSB0Ev27775jl0mJ5dSpU5g8eTJu374NIyMjtdJFcRNIcMBLHDu4BW7u1dCu0wB2xuOa93F2TSzltCLJ3XnQmY6iJxdw96gDJ2c3XDiTm/zO2sYeJqYWqFW3JQ7v38BCMemsSa/+E+Ds8sEmrVZKVuBgNJFAQmOCEBz5Bo+fXGGmqbf3XiIlOh5aOtqo4NkQWWnkp9NCpcr1kRJHKd5z0Lzu19AR6SAlJQl7Tq9GtN9bpCQloWHjr+B725tpqHWX71CpWiNoIqayTFGlJBDaaVBOqbp160rGFB0djcaNG+PEiRPFmjxRFlClrVPcBCLuH5mqzp/ZBzqIJ94FSNt3oeVLO7tJDh2SE33ijJU4fnAbrngdY01MnrUWFpYfx+MLbV+Ty2naYpeWkYo1J39FVnYWHE1LQzs1EyFPXiI+6B1EZgawrl+OhfJSBFYK0iRhvZ5N+6GUbVls//M3vAnxRUZcMps2btVrQCczCRkZmeg1eCrMLG05gQj8QiklgVBKkH379qF69eqSYVAILznS6eyFh4eHwOGpRrGSIJCIdyG4fPEI7t28KAGJ8lUVlqdKHiiamFmgctX6ePXiAXp/Mwzl3OvA9/lDHNyzjiVa7P3tBHk8RiPb0DQCSc9Mx7pTC5GWmYqmldugoXsrULp3SmPyIuY5tEUi9G86Akdv7kFKRiIsYAxtLRHKOVVGw5rtsGnpLGSaZSP2TTgyU9Lg1rAWbIwccOPcSbhW8EDPQeNxcMca2NjZ4etvRgLg2Z8/9cVSOQIh34i6RWQVF4FERYbh9vWzzIl969p/CiOLwiZbzbrN0av/+Hxvdjs2L5bkz5r9+05myuIiPQKaRiCEUHxyLKIS3sHFrjy0tbSRkZWBVcfnsl2JrcgG8QGhMHGwZCYtEjJzsf+1tFDLvRluPTqPhNBIGFiYQN/cGOEPXiE5KoFdo9yqU2+cP7aHlR/x0zyUKVdZeqVoSA2VIxC+A5FtZpKJasufcxAWGiBbAwJrubh6IMD/GStNznn6wtIdIP2/n4LKVevlI5DbN+iWwnUoX7EGBg6bxrPsCsS4YDFNJJCCGNA5kA3/LWHEkujtj5zMbJg4WsO+StmPUE1HBqLuv0FyVG4or7apPkzcbWGTYI7SLuVRo15T7Fy/GJZWVvhu/CyIdPiLjcrtQMhMZWLyId6bHLrkQKfdh7GxsWQ8tEBt375dxq+eclRT9A6EFvDlCyfk83NQTiszC2tEvguRGwgUglu9VhMcP7SVtVmjdjN06zMSqanJeHjvCiOIZq06wdraTHJAi7749NbHRXYEOIHkYvc6/AX2X/0LiZffICc9C44VyqFywwYICH0JIo0sZLGdCPlF0p9EIDEs924aEuNGZZB8M5il5WnQvD26DxieLworIT4aOjp67LZMLh8QUModyMCBA6XS0Y4duadUVVUUTSCREaFYsfBjHwNlwk1Llc9FVlWqN0CA/wtGUnQwi9ql9tt3GcgIZM/2ZUw9A4f9jKYtWn32hK+q6rGk+s0JJBd5Ml+dvncA0dHvUNW6OqrVoGgqXVx8fBK3X+WGrZMYZIog8otEIrKRHZsOLWMRRAYixL3JJRS67nbW0q0SAnnz6hmO7l7B2vpmxFyYmn/5RsOSmgvF/VylJJDiBqGkn6doAiF/x5WLx9iNgPIIy82L1/jJS6FvYIT4uGhsXP0/9hGFBp87tYell3AtXwUdvh6M9Sum070+GDd5MTyqVuEEIsdJp04EQlcF5GTnwDCPlSEvVJR76tmDW3AoXQZ2js75UCQC+e/+ISSmJcCzZjecf3QC6anJMDY2x7PgBxBpi1CtVC288roAka4um585qemAthYMy7rC7/KdXIIx0MXIKb+hrGtZJCVn4cm9q7h0Zhf7rPugqXB0Kr4rtOU4TRTSFCcQhcAqXaPyJBBKcx8U4AsbW0eW1jzQ/4VkYZeuV18ubWvvhBHj57NtPT334n/7QRc7te/yLQsPfnDnEjp1+x616rVgBEMmLEsra35A68vQSlVCXQgkMiwUf/5vCrKzsjFqzgI4unzsvzh7dBe8zxxiB1Cn/b6Z7XLFEhj5Gnsub2K/Otu4IiryLYxhgBwtLdg7uMDRpgxquTWCb+AjPA+4jwi/l8h4Fw2RhSm0bM2gFZSA6LBQmJgYoEqtZnj+8CqMjM3Qe8gsPHtwCYZGpvCo1Yz76vLMTk4gUn1VFVNYngRy4cx+dmBPT08ffQZNxPPHt3D3pvwv3BKnJPGoVp85yAsKEcpf6+Yi8I0v+g6aCCpHoi6LnWJmgmytqgumz+/dxj/LFzMQeo0aj5pNmn8EyD/bluL57Zss++2MRVvzEQidD9l1aSMSYqOh55+FeMTB1u3D1cjZyIFLWQ88DLgD7Zwc2BnZw0jHELHxuUk92zXojcvHd8LAyASOzuVw9+pp9ncyW1nafJxCKfJtEO6eOwYrByfUbdtFI4mFE4hs31m51pIngRz9dxML0ZWHaGmJkPM+h1DB9sRZeclRXtgZDsqttfCXYaxa7fqt0KPfGE4g8lBKIW2oC4HQWa9Lxw4hMyMDrbr3KvRmyVU7/oeokBCYmJtj0oilePzyJkvvTilKaIdLcnr3Dlw5eZT9XKFHQ2QgDSLkZlbQNTNFZkY6QKYrACa6JrC2KQX9HB08v3YB6e/vvOk5eCqC/R/B0NgKHrVaFKq5exdPIeBZ7v0i7QePgaGJmYI0rLzNcgJRAt3Ii0Dorf/RvSs4dXQ76MY2+cqH62otre1gbm6NjMwMDPhuMovmKkwunT+MN6+fo/3XA2Fnn3vZlrosdvLFtmitaRKmt59449Kd42hcsx2szG1x7UHuLqFDs/5wsMlNivj87m3sWrkEFrZ2qNa/DZ4H3mOn0XNS0pH25i1c6zREWDL5A3OFzFyGadrwj/BFhpk+9KJT0aPHeNjaWcHQxB5ZWTnMREv+w7wRgzHhobh74QSsHZxQs6Un34EUbRpDKyc3eRIXKRGQF4Fcv3wKJ96H0ErZBVac3uC0RbrIysx9OxMidAEUXQQlVDRpsROKSVHLaSqmYZGBOH15NyiDQrevhsLU2EICJeW40tPXB7QB//CX8Pd/guBwP2RExCArKh6Nug3A/eeXadKzOplxiYgxyQBE2rAytILWsxAWSdiiQ3+UrVAL6xZNYxGGw36cy67D5ZKLAN+BKMFMkBeByNN8RbDQWRE9fQNmbzY1tQBFwIS9/XAQkXJXDR07B5ZWdoJR1NTFTjBAMhTUZEyTUhJYdJWB/ucTrG7ZNh/vfIJgUsocxiJtDB61AC9e38fls3uQk54ObQMjJOqkQ5SeAd24DCAnh5m87EuXg6GxJa57nWOaadO5H1p26PlJLQX6vkBkeChqNGqqEbcUcgKR4Qsr7yryIhBKk7522VQ28SmbLvkhZBWKcpnyy3p2mlwsFPa4c+ti+D67B0qOOHri71I3r8mLndRgCazAMf0yUMt/noCot6EQ6eugbKcaqORWB7EJUfD3/pALjlohG8r7TQliohORkpLOwnp1dOkemyzYOdjDSOTACvUcORYGhh+IKy46Ckt/HM2+f+36DkDzzqp/3faXkOUE8iWEiuHzohAIOR6fPb7JroJ1KOWCe7e92H0blLL9xbO7X+x93gSKpcu4ISTQj9X5ec5GmJpZflSfvhzvwoNhZW3PQimlFb7YSYvYl8tzTPNj9DLgMQvTtbJ2QD33FtDX1cfZ/bvhffQgTMtYw65uWZBHIyonFqbBqchJSaNTiLmN0H+56bMQGZGI9PR06OiIYGdvzv6WnpSDyMDcA4e9R09AjcbNJA9PjIvF0oljWBBA50FD0bBt+y8rT8VLcAJRAgUWhUC8zh5gh/aICAaPmImt6+Z+dkQikS6MjI2REE93JIBdLRv6NgB+Lx6xu0DIXEWRVY1bdFIIMnyxkz+sHNMPmNILzrbDixGJWHaTTY2y9eFZqzv8Q3xw4eoBllyRRWtlZiNaJwnlS1dBPeeGePHoBvye3EaGnhZyEnLvxLG0LY3wt+GwMDFDjnYGHMuUR0RoIOLjIhEbmoSu349G1TpN8ymUzrLERkbArUo1jXCqcwKR//dZ6hZlIRDKb0UH+CjS6ezJXRDp6GLspEVYu2waMj/jBCfT0/Dx85GemgItbREMjYxxcPefbOdC0v7rQWjasovUYxBagS92QpESXo5jmh+rc9f/xf2we8hBDuqVb4bmVTxx7OJ2xMS/y1fQ2bECWtfvxiKrvE/vw9lj+6GrK4JdWXsYG5ogMSr3fAjl8jUxsEBi6ofcWfTXmg09kRgfzQ4YNmnTSyNzunECEf49VVhJaQnk/Om9uPjfv+xwXr/Bk+Dz5A5s7ErBzsEZea+rJTIgX8jpo38jJ+f9Fh3AoOEz4F65lmQ8s6f2R1ZmBiOh8VP+YKfYFSV8sZM/shzT/JjSLoSy8r4JeIGL23dCZJQNfWdL6FqawqVURaSmJSMyJhSt6neDs2N5VvnIrg24fTXXUU7mKjJb0Q4mN0YrV6jdjIws6OnpsN+r1G6Bp/dybzLs2n8SSpetKH/lKnmLnEAKKCg0NBRLlizBzZs3mf2TLrWaNm0aKlT4cNUqXa+7evVqBAUFoWzZspgyZQqaN//41KxQ3UtLIBtWzUTQG1/2xkMmKDI7ke+ifuO2OLD7Tzx/cpsdwhr5wwKW2JBssovnjWKHpHR19dntf8Z5Dj0RGd25eZ4lPqxWs7HQbstUji92MsH22Uoc08LhuXnuDK557YW+kS5zelvW8EB190Yo5+wBAz2jfCamh7cu4ujeTdDT1YGpmWF+8tDSBnKykZaWiaTEFFhYGMPUwgaePYbj+J6V0DcwRu/vZ7AT7JomnEDyaJwIo2fPnrCysmKkoK+vjz///BO3bt3C8ePH2d9v3LiBYcOGMVJp1KgR/v33X+zcuROHDx+W+apdaQkkJMgPW9fNQ1pqMrtbPDkpnh10atSsA5q17sYy3wa+efH+XvNslouqtWcf3L1xAf6vn0EkEqF73zGwtCr+K2T5Yif/JYZjWjimiXFx2PXnfGQiAWUr1IChy//bOxOwqKv1j38FZRNRQAQXXBEQFRVQcV/ALcQltcz05u6tW3q9lvWvzLJb93Yr28xyK7M0NZfcFRUVFcUNFwQVVGRREZB9k8X/8x6cEQhkZvgN85uZ9zxPj8Gcc37nfN4f5ztne99miE28hobWdnh+yGxlobuxt3F0329IT0uotKJiU8C0GKhnZonCR3nIzspDo4b26Dk4AJ28B8HE5Mm+ivSmlX2NLCBlTBQaGopp06YhJCQEjo6O4hMSlR49euD999/H+PHjMWPGDNjY2OCrr75Slpw4cSJcXV2xZMkSjQyuroDQQw7s+k2EpO3WfSBuRIWLI7s0g+jVPwA/fPV2ufsaNBtp2rwNEuJilEtZA4eMg/+IiRq1tyaFeLCrCb3Kyxoz06tnw7B1xXdw6dwVL81dUOnGNV0IpPtMh09vRdy9aJiXmGJo34lwcCq9uf7pazNQkJ+NZu2boqWrO25fDxe/V9yKVixjUTwQ2l8sPSZf+tt+Q1/C5QtnkJ2ZgRen/xONdPClTPo3SvUaWUDKsEpOTkZkZCQGDHjq+4YEpHv37pg7d64QF29vbzH7ePHFF5UlSUwOHjyIvXv3qk6+TE5NBISKJ92Lg11jJzwqyEd6WrIQiRXfvAuaoSgSHcUltyZ0h0ORaBlr5usfibsctZ2MebDTFmtjZrpx2VJEhJ0SaBetXAdzy6feeSvyLniUhxNHt+H6uRDx0cRZi4UgrP9qKVLv3UP3Qf4YPX0Oflv3b7E5btLQGkXxpS5P6ls3Qs+BY3Bs33oUFxcqqy4oKERqSpb4ediYyeg3ZLS2zCzLellAqjHL6tWr8cUXX4glKicnJ/Ts2RMrV64sJzLr168XecLDS7+5qJs0ERCF2xJ7h6YYNW4WQkP2oIt3P2xZ/50QCwvL+vDuMQiDhk0Qs5Xwc8cwwG+suCvi2sFLLGPpIhnzYKct3sbMNPHWTezd8AtcPbthwKix1SLe+stnSEq8JfL5BU7H4V0/oaTkMTp7DUFifASKCx/Bf9wspGQlway4CIe3/ybyunv2xs1rF1D4KB8mpnWFh94NKxaJy4UPU7NQz9wKs+Z/jMaOT73/VtsYA8hgVAKSkJAAP7+q/TadOHECDg5P9wWCgoIwf/58TJo0Ce+99x7u378vhGPt2rVi/0ORaB/kgw8+ELMXTRIJSGamepEB/1j/vXDTTlNpEoV7ibHiWO+4l14TS1oD/MbA3qHUBXXM9cvYtvFHuHp0w5gJszRpomRlTE1NYGNjKfpL/eZUcwLMVHWGF8MOIeTAJtS3sYVNR1fcOxUmCnfzHYLw0wfF/3v3GY5LZ4Jh3aChiAty6ugOlBQXi7tWxcVF4mwWRSX08h2GY/tKA015ePSG/wvTVG+IgeSkv2V6/6RIsnemWFhYiLi4uCr7SieqFN/Mf//9d3z88cd47rnn8L///U9slKWlpcHX17fSGcjSpUtx/nz1N78re3jZNVVVDZGeloqgvVvg6tYZEZfP4viRfaLo1Dlvoldff5wLC0FC3C0MfW48fvv5W5wPK522f71yKywtn8aUV/V5nI8JGAqB6xHnsennr0Cb44+crDHZb6oIYrXt12XiZKPvgOEIPbJHdHf0xDnYsXGF+P9eA55DclIiYq6VunBv3aYDYq9HAXmAWxdvTJy3wFAQ6aQfshcQVanQctSqVatAsdlp5qHYMKOB3svLC++++y4mTJigrI72QA4dOoQ9e0pfOnWTJjOQh6kPsOHnL8W3JErXrpaKV4dOPhg9YRb+u3iO+HmA/xi4unfFtk0r4NahG0aNn6Fu8yTNz9+WJcUpKmOm6jE9E7Ibp4/uEIXqe7pi+ug3cfb4HuXvxk1diMgLx2HXuDF8+o1CWMgepNyPw+CAKSIU7qGda4Wn3ribV0Ud5iaWGD/zbdg7NVevIQaQ26hmIKrYi+6A0L7HwoULxYmriol+R8d5KZ8i6eIU1vHgHTiwu3R9lvY5jh/+U9wqnzzjHTR2aIaln74hTmaNe+l1cYxXLsmY1+u1ZQNmqh7ZvJwsnDy8BZbWDeA7cAxMTeqKgyjhp/bDxtYBHbr0Ucatibh4EVt/KY2S6NrZF/6B08QyVtD2VbgTcwUlj0swdPRMuHj4qNcIA8ltVHsg1dmMLg/+7W9/EzOPOXNKv8ErkpWVFerXrw/aJ5k9e7by8uDWrVtBm+jbtm2rtXsg1KbUlPtYv+YzcQ+ELhPSMcWyifxa5eRkwb6SUJzVcdDm5zzYSU+XmWqPKbk3CQ3eLh5AXh3auHbBrRsXS932UoC0emZo37EH+vq/AIrSaWyJBaSMxRctWoTNmzdX+g68/vrreOONN8RndCJr+fLlYlPdxcVFiEnZTXV1XyJNTmGp+wy55OfBTnpLMFPtMf3xy0VISnh6LJ5EpKxbIMWT3Tr3EjOTHv0D0cjOERQv/e7N62jTqRsa2FYesVP6Vtd+jSwgtc/8L09kAZGBEfS4CSwg0hsvJysVkeFHEHXlArIzUksfQJcHHz+GtY0tXDv54mr4aRTkpYsDNop7Vm6dfeEXOA171nwjHJbaN3VG/+dflr6BMqmRBUQGhmABkYER9LgJLCCqGy/1QSKO7FmHJs1ao9/QiVW6XN+39Qfcvn5ReKymZavGji1wKewwCvJz0NbNC07OHbB74yp0aNMBydkJKHlcelHXb9Q0uHXyxYk/f0dy4h208/SBZz9/1RuoZzlZQGRgMBYQGRhBj5vAAqK68UIO/I6I86WhC15+9d9oaPtXf3ChwVtx8XSQyNOkaSs4tXDB5bOH0aBhY3T2GQharsrKSMNv332CNs1bI+9RNupYmqJbnxFw7+wrypFvutzMdNRvaGvQcUFYQFR/97SWkwVEa2iNomK5CUhebrbw/FzZ4Kxrg9yLj8GB7SuFH6wR418Ty08V0y/fvo2c7HTY2Npj4qxF+HXZIuTllrorUbhtf1RQIGYd186cgLmFFdx8eldaF5Wh4//R4WEofFQAd5/eImyCoSQWEBlYkgVEBkbQ4ybISUDIM/SGHxeJY7HDx/0dbd2exp3RFWJx2Y8u/rl1UKkJ5LLk9IkdyDN/DFun5nCz74ATBzehvnVDePcNQPixY4g6Gy7C2VJY2+rSg/hYnNy5UWTrOnA42nTsWl0RvfmcBUQGpmIBkYER9LgJchKQh8l3sXFVaVhl30Fj4dVLt3HBb0ddxZpPPxTtmf7uh2jboaNKlj5+fhdi4q7C1MQUL4+cL9yYpKcmYcOKD5B8OwOF+cWwsLLClIVv4VTwNri4e8On39Mw0Ikx15CekoT2XXui6FEBDm9cI05p9R87GXZOhuMviwVEpddJu5lYQLTL19Brl5OAEOsbEWHITE+I0qC8AAAgAElEQVRBl55DUK+emU7x37x6BT//tzTMwtSF78Olc5e/tCcjLVlcCmzn7oX6DRoh7mYEwsOCYN/SGW4dfeFg6yzK0NLc+h/eR3ZaJupbNIWvfwDOhW5DXj4tb9XBC6+8i8bNW4IuKu5f+70o065Ld3TqNVCIB+2LmFtU7S1Yp6A0fDgLiIbgpCzGAiIlTeOrS24CIjcLRF++KJrU3rPypaMNP36A9IdJaOrcHmOnvInflr+PzPRk2DS0wytz/4vI8+dhZW2N9PREXD4XLELZduzaDzkZadjz23fIzHsISzNreHTuA58ho3B03xZEnDmOpnaOsGvSFJlpKfAaNAKtOnjKDU2N28MCUmOENa+ABaTmDI25BhaQmll/y9r/4sHd2yJq4YDhk/Dr8vdQUlyEDp7d4eDQARuXfS0e0NzdEY/rFAp37nSZsOfAsYg6dQzmdS2FOxRK7r0HYf3qL8T/9/ULRN69u+L/m7Z1he+I52vWUBmWZgGRgVFYQGRgBD1uAgtIzYxHjhGTEm+iaUtXPExOxNa1/xUVDhszBXlZdZQCMnjCaMTevAByE0SpZbtOYrnLzNQCdvWdhF8sv4kzsPqbD0WEwmEjJyIpOkqcuuo39mXYNikNr2BIiQVEBtZkAZGBEfS4CSwg0hmPjtxeDQ9Bfm4m/APGISu7EJHnz8GyvjVatncTR3IvnTkkvPNmpCeDLiaamVkKUfHo2gf9h08S+x3FRUWIOBmMO1GXReMCZv7zL/7qpGu17mpiAdEde+WTWUBkYAQ9bgILiGrGS74fh+tXTomLgIp46FWVrI7pw5R72Liy9HQXHRbo4ze+XFWRYScQffEs7J2air0PZ1cP1RqpZ7lYQGRgMBYQGRhBj5tQ3WCnx12TtOkbVixGeup92No74aU5pUeNNRUQ2gM5EbQJKQ8SMei5KWhk76isik5brXjnNTFbaeneCSNnlDphNcTEAiIDq7KAyMAIetwEFhDVjEcxPGKizsHFozuGjplZIwGp7ol7f/4esZFX0LnvIHQbMARWDRrCxNS0ymIkNrcjwlFcVCj8Zz0rb3XPrs3PWUBqk3YVz2IBkYER9LgJLCCqGY9mBhlpD9DQtkmVbkcUNWnKtKiwEHdvXUfMpTNIf5Ck9INlYWUNV+/eaNu5G5LibsHK2gY29k/9cD2Iv42TOzeJx3v7j0RLt06qdUrHuVhAdGwAejwLiAyMoMdN0HSw0+Mua73pmjK9ELxXuXEuGvnEBTyJV1LcHfQdNQE3L59DHRMTDJvyqoiKSCkrLRXBm34Slw37Pz9Zb8LjsoBo/VWs/gEsINUz4hxVE9B0sGOm0jCl5aeI0CNIvRsPcysr3I8tDUBlUrcuegwbg5sXz+La+dMoKiwSAhIdflrMTIZO+btY2lKk/JxsISBWDWz0xjQsIDIwFQuIDIygx01gAZHeeOowpYF/39plohHOrh3RpGUb2Ng5wLqRrQh5SynlbgLMLCyEK5MrocFwaNEardw7S9/wWq6RBaSWgVf2OBYQGRhBj5ugzmCnx92s1aarw5RmIGH7tyP1XgK6DxmFJs6tq2zruYO7EH/jqhAWuhtSmTv5Wu1oDR/GAlJDgFIUZwGRgqLx1qHOYGe8lNTruTaYZqU/xNXQI7h3OxqW1jYY9rdX9T7YFAuIeu+VVnKzgGgFq9FUqo3BzmjgVdFRqZlSfJT9a5eJG+r1LCxhZmaGPqNfQn2bRnqNmgVEBuZjAZGBEfS4CVIPdnqMQrKmq8P08onD4g5Hp94DxR2OytKj/Dzs+3kZSkpKY6dT6tJ/CNp29paszbqoiAVEF9QrPJMFRAZG0OMmqDPY6XE3a7Xp6jDdteorETSqkYMjBr0wrcp2picnieWr2MhLqFuvngiD27ydO0zrlnry1cfEAiIDq7GAyMAIetwEdQY7Pe5mrTZdHabkMJFEwd2nDxxbtX1mO+myIF0aVCQ6teUzJLBW+yblw1hApKSpYV0sIBqC42KCgDqDHSNTjYC2mN64cBpXTx1FHRNTPC4phlNrFzRp2RZ3Y67Bw3cA7Js2V62BMsnFAlKFIc6dO4cpU6Zg7dq16NmzpzJXVFQUPvnkE0RERKBRo0Yiz4wZM2pkThaQGuEz+sLaGuyMGaw2mVL8kYK8XKQkxKJxs5YiXjolWsoaNedNREdeRNjxA+jZbxjae1QeRVEutmEBqcQSWVlZGD16NBITE7Fu3TqlgKSlpWHEiBHw9/fHtGnTcPHiRXz00UdYvHgxxo0bp7FNWUA0RscFeQailXdAKgHZv/1XRFw4hcAXZ8C5lQvOHNghLhPaN3NGw8ZNRAz1Pau/EU4UzSwsETBjHpYufh0PU5Jga98EC5aUxlanzwsLCmBR31or/dW0UhaQSsgtWLAAKSkpOH36dDkBWbFiBdavX4/g4GDUfbLxtXTpUgQFBWH//v2a2oB9YWlMjgvyEpZ23gEpBKS4uBiL504UDWzv0Q29eg0Wy1dl0/BX/gHTenVx9+YN1KljIlyhhJ8/iZOHd6H34JF4btwrIAeNhzasRF52loi5LqfYIiwgFd6/HTt24JtvvsEPP/yAUaNGlROQWbNmwcbGBl9++aWyVGhoqJiN0L/29vYavc08A9EIGxd6QkCKwY5hlicgFdOgHesREX4aIydMR7PmrXBqzxYRJyQnIw11zcww+MXpKCkuRnZGGk7v2SIa0W/MJDRs4oR6T9yg5GZl4sC65eIzl6490LnPYNmYiwWkjCkSEhLw/PPPY/ny5XBycoKfn185AQkMDET//v3x1ltvKUvFxMQgICAAW7ZsQefOmvm2IQHJzMyTzUuhzYaYmprAxsZS9Jf6zanmBJhpzRlWrEFbTIsePcKd6xGoW88cdk5NcWTzOrEf0q6LD25eOieaMfiFV/6ymR4beRnpKQ/QoXtvmFtaSd9hDWukv2ViJUWq85ikVaaJxIEEoaoUEhKC+fPnw9vbG7SEpchfdg9kyJAhGDlyJObNm6esJj4+XuyJ0NKWj0/ll4iqQ0LYyDsnJybABAyXQG52NratWIbcrCzh5r1fwCgc371DdNjGzh6ZD1Nh5+iE8a8abgTDZ1lX1gJSWFiIuLi4Ktu/b98+HDp0CJs3bxZuBioTkGfNQLZv3w4PD83iHvMMxHAHjdromba+LddG2+X6DG0wDT96EGEHdsK2iaNwomjdyA6efQeBLhgmxlxHRmoyzK2s4e7dEy5duyM3M0OczFLEDFGwoi+ctKxFbt91/cXTaGYg1b2ogwcPxoMHD1CvXj2RlYyUl5cHc3Nz9OjRA6tXrwbtgdDR3c8//1xZHe+BVEe2/OdSrS2r91TDzs1MpbevNpgG/bYKMZfOCTfvNrZ2cOveB+27dhdjzd6fvhV7IYpkUb8B8nOyRGhbv4kzhNgoUviR/YiNvIhmbd3Qc8RY6TuvRo28B/IEFh3ZLSoqUqJLSkoSdzxILOgeiKOjI1auXImNGzfi4MGDMH0S35g21OlnPoWl2lunjT9M1Z5suLmYqfS21QbT2KgrIBFp2sYFfi++giOb14oTVr0DJ+DU7i3iqG5lqVWHzvAaHKD86PDGn5CZ+kDMTOgUly4TC0gV9CtbwkpNTRX3QGi2MnPmTFy+fBkffvihuAsydqzm3wT4FJYu/wT0/9naGOz0n0rNeqBtpg/iY3Fy50bRyC79h8KhRSsR0fBK6BHhV6tsqmdugZEz/6n8VXryfcRevQRnt46wb9qiZh2tYWkWEDUEhLKSaNBN9MjISDg4OGD69OmYPHlyjczAAlIjfEZfWNuDnTEClorpw/t3cS82Gq09upRz3f64pARRZ0+gsCAfHX0HiiO9ipSceAeXjx8WswxKdELLs6+/LM3AAiIDs7CAyMAIetwEqQY7PUYgedOlYrp79ddCJChKYZ9RpZcKKya6A5IYHYXmLh3E/ggl2he5e/M6UAdir0PXm+VVAWYBkfzVU79CFhD1mXGJpwSkGuyYqfRMj/7xC9Ie3BNxPyj+R2UpeNNPyEh5IOKo+71U3q9efm4Obl05D4fmLUUcdbklFhAZWIQFRAZG0OMmsIBIbzypmFIEwqy0VOH3qqpZxL5fvkd+dhbqN7RFr4DxiA4PQ3LCHXGZkFycFBeXHu7xnzQbDWyfnsaSvtfq18gCoj4zyUuwgEiO1KgqlGqwMypo1XRWm0zpuO65Q7vEPQ+foaNKT2M9KkDDxo7iJFZ2+sMqW0fHeW2bNEVBXg66Dhwu9lVKSkrEEWAKUlXbiQWktolX8jwWEBkYQY+boM3BTo+x1Kjp2mT68H4ijm39VbTPvXsf3L0Vjay0FHTqPQhJd26CTmipkly9fEUIXaorLycLvUe+IPZaajOxgNQm7SqexQIiAyPocRO0OdjpMZYaNV2bTGlZ69TuP5CbnYEu/YYidPdm0dY2nbyEo8Q7164gIvQIigsfid9bWFmjXdfuiLl4FgW52eJ3pnXriX2V6PDTyn5SiFyPnv1r1G91C7OAqEtMC/lZQLQA1Yiq1OZgZ0QYy3W1tpjSaauIk8Fio73rgGGwsXfApeMHcevyedEey/oN4O0/EvHRkchMeSAuO5PXvMLCAuHeHU/cDzq7dULn3oNgblW/Vk3GAlKruCt/GAuIDIygx02orcFOjxGp3XRdMk25G4/j29eLNrd07wQ6yxt37Yr4mWKo2zk1w6WQg8o+0b6I/6RZOjnqywKi9qslfQEWEOmZGlONuhzsDJWzLpnSrOTKycNISYxHt0HDcXrfduRnZwrUto7N4DvieRzb9htyM9OV+EfOmo96Zubi54LcHNy/cxOOrdrBQsszEhYQGfwFsIDIwAh63ARdDnZ6jO2ZTdc1U4qbXpifB9ovCT92AGn3E0V723XpLmYhR/9YK36mo7+t3DuD9j8UiTbVaaOeTmsNnPCKVk3EAqJVvKpVzgKiGifOVTkBXQ92hmgXXTGl2UdW+kOEbFmHwgo+sWgpq45JHVjWt0FuVunso+eI59GsrWs5E4RsW4/Ue/Gwc2qOAeOmaNU8LCBaxata5SwgqnHiXCwgtfUO6EpAQndtRlLcrWq76eDcGk1bt0fCjato3r4DXLp0V5Z5lJ+HB/G34eDcBuYWltXWVZMMLCA1oSdRWRYQiUAaaTW6GuwMGbeumO5a+aVw8d7ArjFauHRAyeNiXD93SlwYtLG1x73YGIG9lbsn8nIylXdGGjdvCW+/kSLIVG0mFpDapF3Fs1hAZGAEPW6CrgY7PUZWbdN1xZQEgpwo0oyC3J9QIkGhyIQh234TexuNmjih7+iXhI+sqDMnQJ59KdEdkLJ7IdV2UoIMLCASQKxpFSwgNSVo3OV1NdgZMnU5Mj3w63LkZlIo24bieO+1syfFJjrFC6Hohb0DX0BD+1LRqa3EAlJbpJ/xHBYQGRhBj5sgx8FOj3GKpsuNKfnNOrHjd+Q8ObpLokFu4ikNmjBVzEpoA55mIxQGt7YSC0htkWYBkeUfpgzMX+MmyG2wq3GHZFCBrpnmZWfizIEdMLe0QvehoxD8x1pkP0ytlAwd6/XyC0DI1l+RnpKEnsPHommb9rVCkQWkVjA/+yE8A5GBEfS4Cboe7PQYXZVN1zXT6ItnhIsTSj2HP4+w/dspzBTqmJjAuqGtcBGvSFYNbeHu0wcXDu8Wv6LAVD2Gja4Vs7CA1ApmFhAFAV3/YcrA3JI3gZlKjlTnS1gUpZAcLppZWMKhZWtcP3Py2Z2sU0fpF6uRgxMGvTAVd2/dQF5WJlp36gpT07rSQwLAAqIVrOpVyjMQ9Xhx7vIEWECkfyPkxFRxs/xZvaxrZi5iilBq1s4Vmakpyrgi5OHXpWsP6SGxgGiFqdqVsoCojYwLlCEgp8HOUAwjJ6ZXTx/DjfOnxPKV4shuHVNTPC4uVuImL7wUD4Q20q+fC8W92zeUn7l69UKbTl3F6S2pE89ApCaqQX0sIBpA4yJKAnIa7AzFLHJiSqJAS1okHnQSi4TExMRERDQsm/qMmigCSt27HY3wI/vg0KKVcLB4++pF8e/wqa9LHrWQBUQGbzwLiAyMoMdNkNNgp8cYyzVdrkxJTCjt/fk7PMrLFf9PPq8a2NqLeCJ0hLfo0SPUNTMTn105GYyYi2fE75+bPlfpsVcqO7GASEWyBvWwgNQAHhfV+YavIZpArgKiYP3w/l0RV50CUPUYOlrEAiEnjPE3rorlLvtmzmjk4ChC3lKIXNpYt6W7IiUlYgYjVWIBqUByzZo12LBhA5KTk+Hi4oKFCxfC19dXmSsqKgqffPIJIiIi0KhRI0yZMgUzZsyokT1YQGqEz+gLy32w00cDyYUpzTiiw8OEW3c3715VXhI8f2g34q5HoOxmOnFv29kLXfoPFXsjJ3dsRMq9ePj4B6JF+w6SmIUFpAzG5cuXY+XKlViyZAk8PT2xdu1a7NixAzt37oSzszPS0tIwYsQI+Pv7Y9q0abh48SI++ugjLF68GOPGjdPYICwgGqPjgjK8NW0IRpGLgFBgKDrOS4kuC1Lsj8pS8KafkZGSJELaUhjc9OT7IpuZpRU69OiLFi4e2LPma/E7unjoMyRQEjOxgDzBmJubiz59+uDNN9/Eyy+/LH5bXFyMsWPHYvr06RgzZgxWrFiB9evXIzg4GHXrlp6rXrp0KYKCgrB//36NDcICojE6LsgCopV3QC4Ckp2ehuBNa1BSUoIBz0+BrWNT0V8KOBUevFfsaXQdOBw5GWmIjbqMZm3b407kFcRdLw2BS6meuSWGTp6NO9euIDnhDjr1GiiWvqRILCBPKIaEhGD27Nk4ffq0WJqqLM2aNQs2Njb48ssvlR+HhoaK2Qj9a29vr5FNWEA0wsaFnhCQy2BnSAaRE9NH+fl4/LhEuDVRJPLEq4iL3mvkBDi1aie89h5YtxwUD0SRSv1i1UFJcREcW7YVDhelTCwgT2iuW7cO33//Pb799lt8/fXXiI2NFXsg8+fPh5eXl8gVGBiI/v3746233lLaICYmBgEBAdiyZQs6d658elmdwUhAMjOfGr26/Pr8uampCWxsLEV/qd+cak6AmdacYcUa5M6UXJkc2bwORcVFcHJuC6/Bw8Q+x+413z0TRtO27eE1cJhkcUPob5lYSZHqPFacMZOiNonrSEhIgJ+fX5W1zps3TyxROTk5YcGCBWjWrBk2bdqEP//8U/zXrl07DBkyBCNHjgTlVaT4+HixJ0JLWz4+Phq1mrDRKQpOTIAJMAFVCQRtXI/Ya5Eiu419Y/QLGIWEmzGIOn8WxcVFKC4srLQqz9594Tt0hKqPqbV8shaQwsJCxMXFVQnj8OHDYmmKNtEHDBgg8tHATrOO7t27i43yZ81Atm/fDg8PD41g8wxEI2xc6AkBuX9b1kdD6QPTiyGHEB1+phxeE9O6YrnKxMQUnv38xF2RyDMnyuXpN2YinFq1lcQsRjMDqY7Wrl27xAb6sWPHxCxEkWi2QRvsq1atAu2B0P7I559/rvyc90CqI1v+czmtLavXcvnmZqbS20YfmNLGesTJw4iNuoLiwkd/gUDBpmhzXZHMrazRbeCwSl29k+NFykvHfk3r1lMZKO+BPEF17949DBo0SOx/DB8+XDkDoSWrXr164f333xezk40bN+LgwYMwfRK0hWYt9DOfwlLtndOHP0zVeiKfXMxUelvoE9PcrEycP7QHKXfvCBC02U7iQstYJUVF5eDUrWcGD9/+aNOxm/JOSXb6Qxxcv1Lk8/AdIO6bqJpYQMqQeu+998QMhC4KtmrVCr/++qvYHKflqbZt2yI1NVXcAxk8eDBmzpyJy5cv48MPPxR3Qei4r6aJT2FpSo7LEQF9Guz0xWL6xDQx5hrI4aJitkHHett07IqE6ChcOh6ER3l5UCxtKfgr8tDPBbk5CPrtR3GKiy4ZOrt1VNlMLCBlUNE+ybJly7Bt2zZkZGSIPQ06ceXt7a3MRaJBAhMZGQkHBwdxR2Ty5MkqA68sIwtIjfAZfWF9Guz0xVj6xJSO7tIsRKQ6deA7YhzsnJqJmUjZwFTObp2QEB0p3Jn0ChgPp9YuyM/JRkToEVjUt0aL9h7C/Yk6iQVEHVpayssCoiWwRlKtPg12+mISuTOl2Oin924VAafsnVrgRvhpsXFOlwZvX70E+6bN0bydq3CBUlJShPycHOTnZIHcwPcaMQ4pd+PpeogIQnXjwmlhFr+JM9S+YMgCIoM3mgVEBkbQ4ybIfbDTR7QVmZKH25tXzsPGrnGtxRt/FreyM4s+o15EE+c2Ivv+dT8i7loEHJq3UBYvG0eEfunevS+unS09meXm0wfRF07DsoENBr8wTenFV1WbsYCoSkqL+VhAtAjXCKpmAZHeyBWZRoaFiEBNlIb97VWtBGdSpxe5WRkI27ddLFP1GD5WGeeDlrKObF6LR/mlrt4pmdatK2YiJCRtO3mhdceuOPrHL2IGMmjCVNEXii+iiZdeFhB1rKalvCwgWgJrJNWygEhv6IpMYyMviSBN9cwtMHTK32FmbiH9QyWq8cSfvyM58Y4QBI8e/ZCcGIcH8bfR0r0TvP1GiqfQjIqSIm6Ipo9mAdGUnITlWEAkhGmEVbGASG/0yphmpD6AhZV1OZ9U0j+55jU+KshH8MY1yMvOEnsk9B8d1W1CvrBGTpDU6wULSM3tVeMaWEBqjNCoK2ABkd78+sg0LzsTEaFHxUY4uXSPOntcOFCkY77kYJE22SleiLObhxCV9t16wtS01Ku4pokFRFNyEpZjAZEQphFWpY+DndzNpI9Mr5w4jJhLZwXaIS/PgZmFBfb+9J3w5Gtj54DMh8nlsLfp1E2ISH2byr2Pq2IjFhBVKGk5DwuIlgEbePX6ONjJ3ST6yJSCT9HRXuuGthj0wlQ6oat07+7Rsz8eJt3F/diYcugpnsiIaW+IjXZNEguIJtQkLsMCIjFQI6tOHwc7uZtIX5nSaSuKAaLw7k23zHMyM5SBqOgwAO2HFOTnIv5ahPB79dz0ucpTXOrahQVEXWJayM8CogWoRlSlvg52cjaRoTMtLipEQsw12Do4qX15sKzdWEBk8BazgMjACHrcBEMf7HRhGn1nGn/jKi4eC0ILlw7oNqjUOaw2EguINqiqWScLiJrAOHs5Avo+2MnRnPrO9OTOjXgQHyt8Y415dWGVR3dLiotxK+ICzC3rw9lV/XhGLCAyeHtZQGRgBD1ugr4PdnJEr+9MkxPuIOLUUbRwcRcnrZLibiH+RiTaefrAtsnTeEe3rlzApZAgYYKBE6aW+0wVu7CAqEJJy3lYQLQM2MCr1/fBTo7mMTSme9Z8I+6C2DZpioETXhEb6XQpMvluHE7v2SI23odMmg0rm4ZqmYMFRC1c2snMAqIdrsZSq6ENdnKwm6ExDdu/HXdvXodL1x5COCJCg2FpbYOhk+eAPPtSoClL6wZqo2cBURuZ9AVYQKRnakw1GtpgJwfbGRrTx48fI/NhCk7u+F3MROhn2h8JmD5PXDjUNLGAaEpOwnIsIBLCNMKqDG2wk4MJDZEpOVgkR4uUHFq0RjtPb+Ganu6K3AgPE0GomrdzVws/C4hauLSTmQVEO1yNpVZDHOx0bTtDZEqRCKPOnhAzkPZevoiLuoyGjR2RdOcm6IIhpedmzIO5haXK+FlAVEalvYwsINpjaww1G+Jgp2u7GTpTOnlFJ7DKJooL4v/yLLUcLLKA6PpNBcACIgMj6HETDH2w04VpDJlpdnoaDm9cDboDokguXXuiQ4++ars0YQHRxdtZ4ZksIDIwgh43wZAHO12ZxZCZknv3Mwf+FGidWrnA3MoKHXsPUmvpSmEXFhBdvaFlnssCIgMj6HETDHmw05VZDJFpTka6iOvu2LI1khPixEksD9/+ai1ZVbQHC4iu3lAWEBQVlciAvv43wRAHO11bxRCZntr9B8jlO3ngDZz9L0kiE7KA6PpN5T0QGVhAv5tgiIOdri1iiEwjT4fg+vlQ5W10KRizgFSgmJ2djS+++AKHDh1Cfn4+unbtinfeeQcuLi7KnKdOncLnn3+OmJgYODk54bXXXsOYMWM0tgcvYWmMjgsCMMTBTteGNUSmtGSVk5EGOm1FrkukSCwgFSi+/fbbuHz5Mj755BM0bNhQCEVUVBSCgoJgbm6OmzdvYuzYsZgxYwYCAwNx5MgRfPnll1izZg169eqlkU1YQDTCxoWeEDDEwU7XxmWmqlmABaQCJx8fH8ybNw9TpkwRn1y7dg2jR4/G1q1b0alTJ3zwwQfid5s3b1aWXLBgAdLT04WIaJJYQDShxmUUBHiwk/5dYKaqMWUBqcDJ398fTZo0wXfffYcGDRqIGcjOnTvFkhb9/Nxzz4Hy/Otf/1KW/OOPP8SMJTw8XKONKRYQ1V5WzlU5AR7spH8zmKlqTFlAKnAKCwsTex53796FqakpLC0t8fPPP8PT01Pk9PLywptvvolJkyYpSx47dgyzZ88G7Y3Y2dmpRr5MLhYQtZFxgTIEeLCT/nVgpqoxNSoBSUhIgJ+fX5VkTpw4gf3794vZxpw5c2BlZYVVq1YhIiJCLFk5OjrCw8MDS5Yswfjx45X1kHBMnToVJCS0qa5uIgHJzMxTt5he5jc1NYGNjaXoL/WbU80JMNOaM6xYAzNVjSn9LRMrKVKdx8JHsHxTYWEh4uLiqmwg7WO8/PLLCA4ORrNmzUQ+KjNixAgMHjwY7777Lrp164a33nqr0hnImTNnxMa7uomw1alTR91inJ8JMAEmYDAEZC8g1ZFevXq1WK46efJkuaxz584VR3pXrlwp9kCGDh2Kf/7zn8o8tAfy6aef4vz58zAxUV+NeQZSnWX482cR4G/L0r8fzFQ1pkY1A6kOyZ49e8Ts4ujRo2IjnVJJSQlGjhyJPn364L333hOnsOj+x4YNG5TV0YZ6RkYGn8KqDjDfWVCBkPpZeL1efWbVlWCm1REq/dyo9kCqQ5KbmyvueFAt6T4AAArGSURBVNja2uL//u//YG1tjZ9++gl79+4VJ7GcnZ0RHR0t8tCeB/1L+x50D4RmL3wPpDrCfOmtekLq5+DBTn1m1ZVgptURYgGplFBSUhL+97//gU5jFRQUoHPnzli4cCHc3Z9G6goJCRHHe2NjY9GiRQu88cYbYmlL08SnsDQlx+WIAA920r8HzFQ1pjwDUY2TVnPRJnpJiazPH0jaf1pf5hNYkiIVJ2GYKTOVlkD1tZmY1JHsAJDeb6JXj4tzMAEmwASYgDYIsIBogyrXyQSYABMwAgIsIEZgZO4iE2ACTEAbBFhAtEGV62QCTIAJGAEBFhAjMDJ3kQkwASagDQIsINqgynUyASbABIyAAAuIERiZu8gEmAAT0AYBFhBtUOU6mQATYAJGQIAFxAiMzF1kAkyACWiDAAuINqhynUyACTABIyDAAmIERuYuMgEmwAS0QYAFRBtUuU4mwASYgBEQYAExAiNzF5kAE2AC2iDAAqINqgZSJ4X7nTJlyl96QxEge/fuLX5PseXJTT4F7KLY8q+99hrGjBljIAS00w0KeLZs2TJQVMzMzEx4e3tj8eLFaNWqlXYeaGC1JiYminDVFdO///1vTJgwAVFRUfjkk08QERGBRo0aiXd4xowZBkZBHt1hAZGHHWTZil9//RXr1q0rF8mRGkox5M3MzHDz5k0RoIv+OAMDA3HkyBERqGvNmjUaB+qSJQiJG0XiQdEx//Of/8DR0VEIcHx8PHbv3i24cno2geDgYBGe+tChQ+Xckjdo0AB5eXkYMWIE/P39MW3aNFy8eBEfffSREOhx48YxWokJsIBIDNSQqlu0aBFSU1OxfPnySrtFoYKvXbuGzZs3Kz9fsGAB0tPTNQ4VbEj8KuvLo0eP4OvrK8Iwv/TSSyILzUL69euHTz/9FAEBAYaOoMb9+/HHH7Fv3z7s2LHjL3WtWLEC69evB4lM3bp1xedLly5FUFAQ9u/fX+NncwXlCbCA8BtRJYEXXnhBDHYUP76yRBEd6Zte2c9pWYaWD8LDwyULWmNIJrp8+bJYZqHBrE2bNsqukZi4ubnhww8/NKTuaqUv8+fPh4mJiZjtVkyzZs2CjY1Nuc9CQ0PFbIT+tbe310qbjLVSFhBjtXw1/aaIi15eXmKv4969e6Cwwa6urqA/Xk9PT1GaPn/zzTcxadIkZW0Ub3727Nlib8TOzo7pViBA34QpnPKlS5dgYWGh/HTevHnIz88HfYPm9GwCNEtzcHAAzeYoRDXtHdHeG83iaCm1f//+YoanSLQ/R2W2bNkiwl1zko4AC4h0LPWqpoSEBPj5+VXZ5o0bN2LixInij/Ef//iHmE3QfsjBgwexbds2uLi4wMPDA0uWLMH48eOV9ZBwTJ06FSQktKnOqTwBWnZZuHCh2Oilb9GKRL978OAB1q5dy8ieQYBEo1u3bujQoYPgaGVlhZ07d4p3kw530LLqyJEjQYKsSLS/RDNlWtry8fFhvhISYAGREKY+VVVYWIi4uLgqm9y6dWvk5uaKP1BTU1ORj04P0R9n9+7dxcYk/SHTN73KZiB0gos22zmVJ3DgwAHMnTu30hkIDY4//PADI6uGAL2XtL9R9sABHeSgLzk0U65qBrJ9+3bxpYeTdARYQKRjaRQ10eBHAx1tZNIeyNChQ8WJGEWiPRDaDD5//ny5b9hGAUeFTir2QGgm17JlS2UJ2gNxd3cXp4U4qU/gs88+w4kTJ8Ssl47u0sk2ReI9EPV5qlqCBURVUkaW7+jRo0IY6LRL06ZNRe+LioqUokF7H7RcQOvLdCRVkWhDPSMjg09hVfG+kPj26tUL77zzjthMp8SnsFT/46JTfyS2q1atKrccRXc9GjduLJa2aPmVBFoxc6bNdvqZT2GpzlnVnCwgqpIysnzZ2dkYPXo0mjVrJgY7WjJYuXIljh8/jr1794o/1ujoaHEPhPY86F/a96A/1tWrV/M9kGe8L1999ZUY5Gim1rx5c/Ftmfakdu3axfdAqvk7o2VU2puj+x40W7O1tRXHyOlLDG2S03tJ90DoouHMmTNBMz462UZLrvSOcpKWAAuItDwNqjbafKTBLSwsDAUFBeLG9Ntvvy1OYylSSEiIyEOnYVq0aCFOGNHSFqeqCRQXF4u7CXQYgU5e0Z4SzeaIH6fqCTx8+BBffPEF6N2j2Rvta9CMWLFBTqJBR8kjIyPFaa3p06dj8uTJ1VfMOdQmwAKiNjIuwASYABNgAkSABYTfAybABJgAE9CIAAuIRti4EBNgAkyACbCA8DvABJgAE2ACGhFgAdEIGxdiAkyACTABFhB+B5gAE2ACTEAjAiwgGmHjQkyACTABJsACwu8AE2ACTIAJaESABUQjbFyICTABJsAEWED4HWACWiJA/pnIK3HZVK9ePeFuY9CgQcLXWFmPxbdv38Yvv/winAKSa3eKp0Iej+fMmSMcLVaWyKsyeUMmD7TkBYATE6hNAiwgtUmbn2VUBEhAyKdYWQ+7NOBfvXpVuDIhFxy///67cENOzv7INX779u2Frydya3L//n1QXPrr16/j+++/FyJRNpEbFCpDQapef/11FhCjervk0VkWEHnYgVthgARIQCiRCFRMJAjffvstNm3aJGYa5Liyb9+++Prrr5VeZKkMiQTNMEhMKM63IorhuXPnhINAmqlQDHoWEAN8gfSgSywgemAkbqJ+EniWgChC/5JnXoofT95kSSAcHR3/0llyZnny5EnhELBJkybic3LASM4tFy1aJDzPsoDo5zui761mAdF3C3L7ZUvgWQJCoWv/85//CBfktAzVoEEDUDAuVRMta7m5uYns9C8LiKrkOJ+UBFhApKTJdTGBMgRIQB4/flwuzjkF26KNdYpRQWGDKS6Il5cXBg4cCJqNaJJYQDShxmWkIMACIgVFroMJVEKgslNYlM3ExEQE3Pr4449FQCkSENr/oD0RTRILiCbUuIwUBFhApKDIdTCBKgQkJydHbHZTotNW5ubmIkSwtbW1skRgYKD4PS1nVZYolDAFUVLsf1TMwwLCr5+uCLCA6Io8P9fgCTxrD6Rs5z/77DNx/4M21imCXsV05MgR/P3vfxdHfwMCAv7yOQuIwb9Ksu0gC4hsTcMN03cCqgoIxUMnYaB9EBIJU1NTZdcp9jcd401MTMTRo0dhZWXFAqLvL4YBtZ8FxICMyV2RFwFVBYRavX37drz33nvw9PQUFwlpmSsuLk5swN+5cwerVq0S+yaVJZ6ByMvuxtQaFhBjsjb3tVYJqCMg1LALFy6IpaxLly4hNTVVLGeRK5NXX30VLi4uVbadBaRWzcoPK0OABYRfBybABJgAE9CIAAuIRti4EBNgAkyACbCA8DvABJgAE2ACGhFgAdEIGxdiAkyACTABFhB+B5gAE2ACTEAjAiwgGmHjQkyACTABJsACwu8AE2ACTIAJaESABUQjbFyICTABJsAEWED4HWACTIAJMAGNCLCAaISNCzEBJsAEmAALCL8DTIAJMAEmoBEBFhCNsHEhJsAEmAATYAHhd4AJMAEmwAQ0IsACohE2LsQEmAATYAIsIPwOMAEmwASYgEYEWEA0wsaFmAATYAJMgAWE3wEmwASYABPQiAALiEbYuBATYAJMgAmwgPA7wASYABNgAhoRYAHRCBsXYgJMgAkwARYQfgeYABNgAkxAIwL/Dwne67bDb9ADAAAAAElFTkSuQmCC\" width=\"400\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 117 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# PCA on a subset identified in the previous figure\n",
    "\n",
    "subset = (X[:,0] < -50) & (X[:,1] < -50)\n",
    "Xsubset = PCA(n_components=2).fit_transform(X[subset,:])\n",
    "\n",
    "plt.figure(figsize=(4,4))\n",
    "plt.scatter(Xsubset[:,0], Xsubset[:,1], s=1, \n",
    "            color=tasic2018['clusterColors'][tasic2018['clusters'][subset]])\n",
    "plt.title('PCA on a subset')\n",
    "plt.xlabel('PC1')\n",
    "plt.ylabel('PC2')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 676 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "# If clustering results are available, do PCA and/or MDS on the cluster means\n",
    "\n",
    "C = np.unique(tasic2018['clusters']).size\n",
    "clusterMeans = np.zeros((C, X.shape[1]))\n",
    "for c in range(C):\n",
    "    clusterMeans[c,:] = np.mean(X[tasic2018['clusters']==c,:], axis=0)\n",
    "\n",
    "clusterMeansPCA = PCA(n_components=2, svd_solver='full').fit_transform(clusterMeans)\n",
    "clusterMeansMDS = MDS(n_components=2, random_state=42).fit_transform(clusterMeans)\n",
    "\n",
    "plt.figure(figsize=(8,4))\n",
    "plt.subplot(121)\n",
    "plt.scatter(clusterMeansPCA[:,0], clusterMeansPCA[:,1], s=10, color=tasic2018['clusterColors'])\n",
    "plt.title('PCA on cluster means')\n",
    "plt.subplot(122)\n",
    "plt.scatter(clusterMeansMDS[:,0], clusterMeansMDS[:,1], s=10, color=tasic2018['clusterColors'])\n",
    "plt.title('MDS on cluster means')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standard t-SNE visualisation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# run this cell to see more info about the t-SNE model and how it's run\n",
    "TSNE?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 2min 43s\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This uses perplexity=30 (default) and random initialisation\n",
    "# The result will depend on the random seed (here, 42)\n",
    "\n",
    "%time model = TSNE(random_state=42).fit(X)  \n",
    "tsne_default = model.embedding_\n",
    "\n",
    "plt.figure(figsize=(5,5))\n",
    "plt.gca().set_aspect('equal', adjustable='datalim')\n",
    "plt.scatter(tsne_default[:,0], tsne_default[:,1], s=1, \n",
    "            color=tasic2018['clusterColors'][tasic2018['clusters']])\n",
    "plt.title('t-SNE, perplexity = 30')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Our recommended t-SNE settings\n",
    "Here we use scaled PCA as initialisation, learning rate n/12.\n",
    "\n",
    "*If you want to have multiple perplexities you need FIt-SNE.*\n",
    "\n",
    "**NOTE:** I tried perplexity 30 and 50 and saw no major differences between the two. Saw some changes based on changing learning rate (default is 200., new is 1985.). But biggest difference from above is the initialization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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\" width=\"498.88890210493145\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 3min\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "pcaInit = X[:,:2] / np.std(X[:,0]) * 0.0001\n",
    "\n",
    "model = TSNE(init=pcaInit, learning_rate = X.shape[0]/12, perplexity=50).fit(X)\n",
    "tsne_ours = model.embedding_\n",
    "\n",
    "\n",
    "plt.figure(figsize=(5,5))\n",
    "plt.gca().set_aspect('equal', adjustable='datalim')\n",
    "plt.scatter(tsne_ours[:,0], tsne_ours[:,1], s=1,\n",
    "            color=tasic2018['clusterColors'][tasic2018['clusters']])\n",
    "plt.title('A better t-SNE, perplexity=50')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        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=\"500\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 896 ms, sys: 92 ms, total: 988 ms\n",
      "Wall time: 2min 1s\n"
     ]
    }
   ],
   "source": [
    "### DO NOT RUN THIS CELL!!!!\n",
    "### THEIR VERSION WITH MULTIPLE PERPLEXITIES\n",
    "### YOU CAN COMPARE TO ABOVE\n",
    "#%%time\n",
    "#pcaInit = X[:,:2] / np.std(X[:,0]) * 0.0001\n",
    "#tsne_ours = fast_tsne(X, initialization = pcaInit,\n",
    "#                      learning_rate = X.shape[0]/12,\n",
    "#                      perplexity_list = [30, int(X.shape[0]/100)])\n",
    "#plt.figure(figsize=(5,5))\n",
    "#plt.gca().set_aspect('equal', adjustable='datalim')\n",
    "#plt.scatter(tsne_ours[:,0], tsne_ours[:,1], s=1, color=tasic2018['clusterColors'][tasic2018['clusters']])\n",
    "#plt.title('A better t-SNE')\n",
    "#plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mapping new cells to an existing visualisation\n",
    "We randomly select 100 cells as a \"test set\" and use all other cells as the \"training set\". We map the test set onto the t-SNE done on the training set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We use correlation across 3000 genes as the similarity metric to map test set points\n",
    "# In this case we could use Euclidean distance as well, but in general correlaion should be\n",
    "# more robust against possible batch effects, when mapping cells from other experiments\n",
    "\n",
    "def map_to_tsne(referenceCounts, newCounts, referenceAtlas, knn=10, batchsize=1000):\n",
    "    referenceCounts = np.array(np.log2(referenceCounts.todense() + 1))\n",
    "    newCounts = np.array(np.log2(newCounts.todense() + 1))\n",
    "    \n",
    "    assignmentPositions = np.zeros((newCounts.shape[0], 2))\n",
    "    batchCount = int(np.ceil(newCounts.shape[0]/batchsize))\n",
    "\n",
    "    def corr2(A,B):\n",
    "        A = A - A.mean(axis=1, keepdims=True)\n",
    "        B = B - B.mean(axis=1, keepdims=True)\n",
    "        ssA = (A**2).sum(axi