Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import subprocess\n",
    "import numpy as np\n",
    "import h5py\n",
    "\n",
    "from numpy import genfromtxt\n",
    "from matplotlib import pyplot as plt\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "h5f = h5py.File('data.h5','r')\n",
    "X = h5f['X'][:]\n",
    "h5f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6c8HOGzBFnl0vqT2OfehEio6A2zW8rS+mjIr3rY8m0sS4Axgu8NaE22+8zuHM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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d2c7990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(X.T, cmap=plt.cm.Blues)\n",
    "plt.title('X')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "out: \n",
      "err: \n",
      "CPU times: user 1 ms, sys: 4.25 ms, total: 5.25 ms\n",
      "Wall time: 3.1 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "proc = subprocess.Popen(['g++', '-O3', '-DNDEBUG', 'algos.cpp', '-o', 'algos', '-larmadillo', '-llapack', '-lblas'],\n",
    "                        stdin = subprocess.PIPE,\n",
    "                        stdout = subprocess.PIPE,\n",
    "                        stderr = subprocess.PIPE)\n",
    "\n",
    "(out, err) = proc.communicate()\n",
    "print 'out:', out\n",
    "print 'err:', err"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "out: Reading X...  read 6 rows and 8 cols!\n",
      "U S V created\n",
      "Error obtained: 6.59541\n",
      "Error obtained: 5.01806\n",
      "Error obtained: 4.89341\n",
      "Error obtained: 4.84618\n",
      "Error obtained: 4.8322\n",
      "Error obtained: 4.82017\n",
      "Error obtained: 4.80821\n",
      "Error obtained: 4.79531\n",
      "Error obtained: 4.78082\n",
      "Error obtained: 4.76427\n",
      "Error obtained: 4.74488\n",
      "Error obtained: 4.72215\n",
      "Error obtained: 4.69489\n",
      "Error obtained: 4.66236\n",
      "Error obtained: 4.62283\n",
      "Error obtained: 4.57499\n",
      "Error obtained: 4.51637\n",
      "Error obtained: 4.44467\n",
      "Error obtained: 4.35624\n",
      "Error obtained: 4.24714\n",
      "Error obtained: 4.11195\n",
      "Error obtained: 3.9449\n",
      "Error obtained: 3.7398\n",
      "Error obtained: 3.49244\n",
      "Error obtained: 3.20172\n",
      "Error obtained: 2.87023\n",
      "Error obtained: 2.5004\n",
      "Error obtained: 2.09519\n",
      "Error obtained: 1.67167\n",
      "Error obtained: 1.27629\n",
      "Error obtained: 0.955223\n",
      "Error obtained: 0.713373\n",
      "Error obtained: 0.529275\n",
      "Error obtained: 0.387138\n",
      "Error obtained: 0.27939\n",
      "Error obtained: 0.200685\n",
      "Error obtained: 0.14486\n",
      "Error obtained: 0.105923\n",
      "Error obtained: 0.078838\n",
      "Error obtained: 0.0598943\n",
      "Error obtained: 0.0464928\n",
      "Error obtained: 0.0368695\n",
      "Error obtained: 0.0298374\n",
      "Error obtained: 0.024599\n",
      "Error obtained: 0.0206193\n",
      "Error obtained: 0.0175365\n",
      "Error obtained: 0.0151042\n",
      "Error obtained: 0.0131523\n",
      "Error obtained: 0.0115616\n",
      "Error obtained: 0.0102473\n",
      "Error obtained: 0.0091478\n",
      "Error obtained: 0.00821786\n",
      "Error obtained: 0.00742366\n",
      "Error obtained: 0.00673942\n",
      "Error obtained: 0.00614538\n",
      "Error obtained: 0.00562599\n",
      "Error obtained: 0.00516913\n",
      "Error obtained: 0.00476493\n",
      "Error obtained: 0.00440558\n",
      "Error obtained: 0.00408456\n",
      "Error obtained: 0.00379665\n",
      "Error obtained: 0.00353735\n",
      "Error obtained: 0.00330308\n",
      "Error obtained: 0.00309064\n",
      "Error obtained: 0.00289749\n",
      "Error obtained: 0.00272131\n",
      "Error obtained: 0.00256025\n",
      "Error obtained: 0.00241258\n",
      "Error obtained: 0.00227694\n",
      "Error obtained: 0.00215201\n",
      "Error obtained: 0.00203676\n",
      "Error obtained: 0.00193019\n",
      "Error obtained: 0.0018315\n",
      "Error obtained: 0.0017399\n",
      "Error obtained: 0.00165478\n",
      "Error obtained: 0.00157552\n",
      "Error obtained: 0.00150165\n",
      "Error obtained: 0.00143264\n",
      "Error obtained: 0.00136814\n",
      "Error obtained: 0.00130773\n",
      "Error obtained: 0.00125111\n",
      "Error obtained: 0.00119795\n",
      "Error obtained: 0.001148\n",
      "Error obtained: 0.00110099\n",
      "Error obtained: 0.00105672\n",
      "Error obtained: 0.00101497\n",
      "Error obtained: 0.000975578\n",
      "Error obtained: 0.000938345\n",
      "Error obtained: 0.000903146\n",
      "Error obtained: 0.000869816\n",
      "Error obtained: 0.00083825\n",
      "Error obtained: 0.000808307\n",
      "Error obtained: 0.000779903\n",
      "Error obtained: 0.000752914\n",
      "Error obtained: 0.000727272\n",
      "Error obtained: 0.00070287\n",
      "Error obtained: 0.000679653\n",
      "Error obtained: 0.000657527\n",
      "Error obtained: 0.000636445\n",
      "Error obtained: 0.000616328\n",
      "Error obtained: 0.000597135\n",
      "Error obtained: 0.000578797\n",
      "Error obtained: 0.000561281\n",
      "Error obtained: 0.000544526\n",
      "Error obtained: 0.000528502\n",
      "Error obtained: 0.000513157\n",
      "Error obtained: 0.000498467\n",
      "Error obtained: 0.000484383\n",
      "Error obtained: 0.000470887\n",
      "Error obtained: 0.000457935\n",
      "Error obtained: 0.000445511\n",
      "Error obtained: 0.000433576\n",
      "Error obtained: 0.000422117\n",
      "Error obtained: 0.000411099\n",
      "Error obtained: 0.000400511\n",
      "Error obtained: 0.000390322\n",
      "Error obtained: 0.000380522\n",
      "Error obtained: 0.000371083\n",
      "Error obtained: 0.000361997\n",
      "Error obtained: 0.000353238\n",
      "Error obtained: 0.000344801\n",
      "Error obtained: 0.000336661\n",
      "Error obtained: 0.000328814\n",
      "Error obtained: 0.000321237\n",
      "Error obtained: 0.000313928\n",
      "Error obtained: 0.000306866\n",
      "Error obtained: 0.000300048\n",
      "Error obtained: 0.000293457\n",
      "Error obtained: 0.000287089\n",
      "Error obtained: 0.000280928\n",
      "Error obtained: 0.000274972\n",
      "Error obtained: 0.000269207\n",
      "Error obtained: 0.00026363\n",
      "Error obtained: 0.000258227\n",
      "Error obtained: 0.000252998\n",
      "Error obtained: 0.00024793\n",
      "Error obtained: 0.000243021\n",
      "Error obtained: 0.000238261\n",
      "Error obtained: 0.000233648\n",
      "Error obtained: 0.000229172\n",
      "Error obtained: 0.000224833\n",
      "Error obtained: 0.00022062\n",
      "Error obtained: 0.000216533\n",
      "Error obtained: 0.000212564\n",
      "Error obtained: 0.000208711\n",
      "Error obtained: 0.000204967\n",
      "Error obtained: 0.000201332\n",
      "Error obtained: 0.000197797\n",
      "Error obtained: 0.000194364\n",
      "Error obtained: 0.000191024\n",
      "Error obtained: 0.000187778\n",
      "Error obtained: 0.000184619\n",
      "Error obtained: 0.000181547\n",
      "Error obtained: 0.000178557\n",
      "Error obtained: 0.000175648\n",
      "Error obtained: 0.000172816\n",
      "Error obtained: 0.000170059\n",
      "Error obtained: 0.000167373\n",
      "Error obtained: 0.000164758\n",
      "Error obtained: 0.000162209\n",
      "Error obtained: 0.000159727\n",
      "Error obtained: 0.000157306\n",
      "Error obtained: 0.000154948\n",
      "Error obtained: 0.000152648\n",
      "Error obtained: 0.000150406\n",
      "Error obtained: 0.000148218\n",
      "Error obtained: 0.000146085\n",
      "Error obtained: 0.000144003\n",
      "Error obtained: 0.000141973\n",
      "Error obtained: 0.00013999\n",
      "Error obtained: 0.000138056\n",
      "Error obtained: 0.000136167\n",
      "Error obtained: 0.000134323\n",
      "Error obtained: 0.000132521\n",
      "Error obtained: 0.000130762\n",
      "Error obtained: 0.000129043\n",
      "Error obtained: 0.000127365\n",
      "Error obtained: 0.000125723\n",
      "Error obtained: 0.00012412\n",
      "Error obtained: 0.000122552\n",
      "Error obtained: 0.00012102\n",
      "Error obtained: 0.000119522\n",
      "Error obtained: 0.000118057\n",
      "Error obtained: 0.000116624\n",
      "Error obtained: 0.000115223\n",
      "Error obtained: 0.000113851\n",
      "Error obtained: 0.00011251\n",
      "Error obtained: 0.000111197\n",
      "Error obtained: 0.000109912\n",
      "Error obtained: 0.000108655\n",
      "Error obtained: 0.000107424\n",
      "Error obtained: 0.000106219\n",
      "Error obtained: 0.000105039\n",
      "Error obtained: 0.000103883\n",
      "Error obtained: 0.000102752\n",
      "Error obtained: 0.000101643\n",
      "Error obtained: 0.000100557\n",
      "Error obtained: 9.94927e-05\n",
      "Error obtained: 9.84505e-05\n",
      "Error obtained: 9.74285e-05\n",
      "Error obtained: 9.64275e-05\n",
      "Error obtained: 9.54458e-05\n",
      "Du: \n",
      "   2.2597        0        0\n",
      "        0   2.2398        0\n",
      "        0        0   2.2558\n",
      "Dv: \n",
      "   4.1509        0\n",
      "        0   4.1586\n",
      "Time taken: 0.003821\n",
      "\n",
      "err: \n",
      "CPU times: user 1.44 ms, sys: 5.74 ms, total: 7.19 ms\n",
      "Wall time: 18 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "proc = subprocess.Popen(['./algos', 'onmtf', '3', '2', '10000'],\n",
    "                        stdin = subprocess.PIPE,\n",
    "                        stdout = subprocess.PIPE,\n",
    "                        stderr = subprocess.PIPE)\n",
    "\n",
    "(out, err) = proc.communicate()\n",
    "print 'out:', out\n",
    "print 'err:', err"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.00037281"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "float(open('error.csv').read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "U = genfromtxt('U.csv', delimiter=',')\n",
    "S = genfromtxt('S.csv', delimiter=',')\n",
    "V = genfromtxt('V.csv', delimiter=',')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    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 overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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>"
      ]
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     "output_type": "display_data"
    },
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KVADvwrHHHBCAAE6wc6gna4Ap6enNTLy7Fufs6/Ev31zTn1DKxYPz74ROj2Ot8Ewv8oSQIBlSbFfnQS4B1gnXc59TwIIkMnhAwEE6EMKEdaAACMM3cOWcwI8d/aMtm7bvlhmdgl8a/aqBlauK1wCp8exBPYwYU9LQoCeBhNZWTkBnj51Ujt27ioW4MwVDQyvLxRgehwCjGz2LKNdBLgMeBzaNQIsgbuGkhNVIYAAq9Bi37oIIMC6yHLejgQQIBPEBwI5ATabTTUajcIl8O2FefX1DxYugdPjWAL7EGkYNSDAMHKyXmVOgAfG9+nwxNFCAd68dl5Da7cUCjA9DgFany7d6w8Bdo8lZ1o6Aa4Al86OI5dBAAEuAx6Hdo0A9wC7hpITVSGAAKvQYt+6CCDAushyXh6CMAe8J8DnAL2PyGaBXAHazDW0rvgmSGiJGakXARoJMvA2WAIHHmCo5SPAUJOzVTcCtJVnMN0gwGCiMl1oToC8D9B01l41hwC9iiPaYngjdLTRu20cAbrlz+h3CbAEZiY4IYAAnWBn0DYCCJAp4YQAAnSCnUERIHPABwII0IcUqCF3BXji+DHt3rN3kUr2jdDzNy5pcPXGxW3ZH0VKj+NlCEyosgQQYFlS7FcngZwAL0xOavPYWKEAF+am1b/i2V+MywowPQ4B1hmVrXMjQFt5htoN9wBDTS7wuhFg4AEaKR8BGgkytDYQYGiJ2aw3J8DLU1PaMDpavARuzqi/MVx4DzA9jiWwzUlSR1cIsA6qnLMqgZwAJ44c0vj+g8UPQa5f1OCaTYUCTI9DgFXxx7s/Aow3e586ZwnsUxoR1YIAIwrb41YRoMfhWC4NAVpON5zeEGA4WZmqFAGaijPYZrgHGGx0YReOAMPOz0r1PAW2kmRgfSDAwAIzWi5LYKPB+t4WAvQ9oTjqQ4Bx5OxdlwjQu0iiLIjvAkcZu/umEaD7DKig7YWovA2GKdErAgiwV6QZpxMBlsDMDycEEKAT7AzaRgABMiWcEECATrAzKAJkDvhAAAH6kAI18KtwzAEnBBCgE+wM2ukKkN8FZn70igAC7BVpxuEhCHPAOwII0LtIoiyIhyBRxu6+aQToPgMqaPsc4LmzZ7R12/ZFLtlfhbs1e1UDK9ctbsv+KFJ6HC9EZUqVJYAAy5JivzoJ5K4AT586qR07dxULcOaKBobXFwowPQ4B1hmVrXMjQFt5htoNS+BQkwu8bgQYeIBGykeARoIMrQ0EGFpiNuvNCbDZbKrRaBQugW8vzKuvf7BwCZwexxLY5iSpoysEWAdVzlmVQE6AB8b36fDE0UIB3rx2XkNrtxQKMD0OAVbFH+/+CDDe7H3qnCtAn9KIqBYEGFHYHrfKPUCPw7FcGgK0nG44vSHAcLIyVSkCNBVnsM3wOcBgowu7cAQYdn5Wqs8JkG+CWInV/z4QoP8ZxVAhS+AYUvawRwToYSgRloQAIwzdh5YRoA8pUENOgLwPkAnRKwIIsFekGacTAd4IzfxwQgABOsHOoG0EWAIzJZwQQIBOsDMoAmQO+EAAAfqQAjVwBcgccEIAATrBzqCdrgBPHD+m3Xv2Lu6SfSP0/I1LGly9cXFb9o3Q6XG8DIH5VZYAAixLiv3qJJC7ArwwOanNY2OFAlyYm1b/ipFCAabHIcA6o7J1bgRoK89Qu2EJHGpygdeNAAMP0Ej5CNBIkKG1gQBDS8xmvTkBXp6a0obR0eIlcHNG/Y3hwiVwehxLYJuTpI6uEGAdVDlnVQI5AU4cOaTx/QeLH4Jcv6jBNZsKBZgehwCr4o93fwQYb/Y+dc4S2Kc0IqoFAUYUtsetIkCPw7FcGgK0nG44vSHAcLIyVSkCNBVnsM1wDzDY6MIuHAGGnZ/r6n9F0hsl/aCkOUlfknRA0l9mCnulpI9JSp5cPCPpuKQPtBXOU2DXSUY6PgKMNPgutf1BSaclfVPSCkn/RtIjkn64df4XSvozSZ+U9Jik9ZJ+T9KHJH0kUwNL4C4FwmmqEUCA1Xixd2cCPyTpoqTkg3rJ1d7bJB2W9JCkhdahPycp+eelCJDp5JoAAnSdgK3xk+Xvv5L091ttfVhS8onmN2TafLWk85KSq77vtv473wW2NQ+C6QYBBhOV94W+TtLnJP20pLOtaj/RWhq/JVP9yyR9S9KLJD1dJEDeBuN91mYKRIBmonTayE9K+g+S3i7ptzOVHG3dE3x9mSvA127dpkceefmdXX/8Nf9IX/7SH+ixJz6oh350/M5/uzVzRRp4vgZWrrvz77dvzuldbxrR408+peSnNJN/Ln3zG1q16kF97rOfSXZZJWnWKRkG95oAAvQ6niCK+2eSPi7pzZJ+v63it0o6IunhxF+tbe+W9M7WA5F0dx6CBBG1vSIRoL1Me9lRIrLk6e5PSfqjgoEfyDwFfqIlvc9LSq4MeQrcy6QYq5AAAmRiLIdA8mT3pqTvtZ0kWfKmQnxF6wrxVa3l6K+1pJk9hF+FW04KHLtkAghwyeg4sIsE+F3gLsLkVOUJIMDyrNizPgLcA6yPLWfuQAABMj18IIAAfUghwhoQYIShe9hyToDJx1m2btu+WGb2V+FuzV5d/BhMskP2V+HS43ghqocJe1oSAvQ0mMjKygnw9KmT2rFzV7EAZ65oYDj5SvHdv6wA0+MQYGSzZxntIsBlwOPQrhFgCdw1lJyoCgEEWIUW+9ZFAAHWRZbzdiSAAJkgPhDICbDZbKrRaBQugW8vzKuvf7BwCZwexxLYh0jDqAEBhpGT9SpzAjwwvk+HJ5Ivi9z9yz4EuXntvIbWbikUYHocArQ+XbrXHwLsHkvOtHQCXAEunR1HLoMAAlwGPA7tGgHuAXYNJSeqQgABVqHFvnURQIB1keW8HQkgQCaIDwT4HKAPKURYAwKMMHQPW+abIB6GEkNJCDCGlP3vkSWw/xmZrBABmow1uKYQYHCR2SgYAdrIMfQueB9g6AkGWj8CDDQ4Y2XzRmhjgYbSDgIMJSnbdbIEtp2vt90hQG+jiaowBBhV3P40iwD9ySLmShBgzOk77B0BOoTP0IsEcgI8cfyYdu/Zu7gx+zKE+RuXNLh64+K27AtR0+N4GQIzqywBBFiWFPvVSSAnwAuTk9o8NlYowIW5afWvGCkUYHocAqwzKlvnRoC28gy1G5bAoSYXeN0IMPAAjZSPAI0EGVobCDC0xGzWmxPg5akpbRgdLV4CN2fU3xguXAKnx7EEtjlJ6ugKAdZBlXNWJZAT4MSRQxrff7D4Icj1ixpcs6lQgOlxCLAq/nj3R4DxZu9T5yyBfUojoloQYERhe9wqAvQ4HMulIUDL6YbTGwIMJytTlSJAU3EG2wz3AIONLuzCEWDY+VmpnqfAVpIMrA8EGFhgRstlCWw0WN/bQoC+JxRHfQgwjpy96xIBehdJlAXxXeAoY3ffNAJ0nwEVSLwNhlnghAACdIKdQdsIsARmSjghgACdYGdQBMgc8IEAAvQhBWrgCpA54IQAAnSCnUE7XQG+773v0eNPPrW4S/aN0Def/qqGHn50cVv2jdDpcbwMgflVlgACLEuK/eokwO8C10mXc9+TAAJkcvhAgCWwDylEWAMCjDB0D1tGgB6GEkNJCDCGlP3vMSfAc2fPaOu27YX3AG/NXtXAynWF9wDT47gH6H/gvlSIAH1JIu46cgI8feqkduzcVSzAmSsaGF5fKMD0OAQY92Sq0j0CrEKLfesiwBK4LrKctyMBBMgE8YEAAvQhhQhrQIARhu5hyzkBNptNNRqNwiXw7YV59fUPFi6B0+NYAnuYsKclIUBPg4msrJwAD4zv0+GJo4UCvHntvIbWbikUYHocAoxs9iyjXQS4DHgc2jUCXAF2DSUnqkIAAVahxb51EeAeYF1kOS8PQZgD3hNAgN5HZLNArgBt5hpaV3wOMLTEjNSLAI0EGXgbfBMk8ABDLR8BhpqcrbpZAtvKM5huEGAwUZkuFAGajtff5hCgv9nEVBnvA4wpbY96RYAehRFxKTkB8kboiGdCj1tHgD0GznCFBFgCMzGcEECATrAzaBsBBMiUcEIAATrBzqAIkDngAwEE6EMK1JC7Ajxx/Jh279m7SCX7q3DzNy5pcPXGxW3ZX4VLj+NlCEyosgQQYFlS7FcngZwAL0xOavPYWKEAF+am1b9ipFCA6XEIsM6obJ0bAdrKM9RuuAcYanKB140AAw/QSPkI0EiQobWBAENLzGa9OQFenprShtHR4iVwc0b9jeHCJXB6HEtgm5Okjq4QYB1UOWdVAjkBThw5pPH9B4sfgly/qME1mwoFmB6HAKvij3d/BBhv9j51zhLYpzQiqgUBRhS2x60iQI/DsVwaArScbji9IcBwsjJVKQI0FWewzXAPMNjowi4cAYadn5XqeQpsJcnA+kCAgQVmtFyWwEaD9b0tBOh7QnHUhwDjyNm7LhGgd5FEWRDfBY4ydvdNI0D3GVCBxNtgmAVOCCBAJ9gZtI0AS2CmhBMCCNAJdgZFgMwBHwggQB9SoAauAJkDTgggQCfYGbTTFSC/Csf86BUBBNgr0ozTiQC/C8z8cEIAATrBzqDcA2QO+EAAAfqQAjVwD5A54IQAAnSCnUE7XQGeO3tGW7dtX9wl+6twt2avamDlusVt2V+FS4/jhajMr7IEEGBZUuxXJ4HcFeDpUye1Y+euYgHOXNHA8PpCAabHIcA6o7J1bgRoK89Qu2EJHGpygdeNAAMP0Ej5CNBIkKG1gQBDS8xmvTkBNptNNRqNwiXw7YV59fUPFi6B0+NYAtucJHV0hQDroMo5qxLICfDA+D4dnjhaKMCb185raO2WQgGmxyHAqvjj3R8Bxpu9T51zBehTGhHVggAjCtvjVrkH6HE4lktDgJbTDac3BBhOVqYqRYCm4gy2GT4HGGx0YReOAMPOz0r1OQHyTRArsfrfBwL0P6MYKmQJHEPKHvaIAD0MJcKSEGCEofvQMgL0IQVq4H2AzAEnBBCgE+wM2kYgJ0DeCM386BUBBNgr0ozTiQBLYOaHEwII0Al2Bu10BdhOJ/s+wPZt2fcBptv4KhzzqywBBFiWFPvVSYArwDrpcu57EkCATA4fCOQEeOL4Me3es3exruwV4PyNSxpcvXFxW/YKMD2OK0AfIg2jBgQYRk7Wq8wJ8MLkpDaPjRUKcGFuWv0rRgoFmB6HAK1Pl+71hwC7x5IzLZ0AS+Cls+PIZRBAgMuAx6FdI4AAu4aSE1UhgACr0GLfugjkBHh5akobRkeLl8DNGfU3hguXwOlxLIHrisneeRGgvUxD7CgnwIkjhzS+/2DxQ5DrFzW4ZlOhANPjEGCIU8BNzQjQDXdGzRNgCcyMcEIAATrBzqBtBBAgU8IJAQToBDuDIkDmgA8EEKAPKVAD9wCZA04IIEAn2Bm00xUgT4GZH70igAB7RZpxOhHgHiDzwwkBBOgEO4NyD5A54AMBBOhDCtTAd4GZA04IIEAn2Bm00xUgb4NhfvSKAALsFWnG4R4gc8A7AgjQu0iiLIiHIFHG7r5pBOg+AyqQECCzwAkBBOgEO4N2ugfIr8IxP3pFAAH2ijTjlL4HOD09rZGRZ9/6nH0l/u2bc+obWrF4ruwr8dPjeBsMk60sAQRYlhT71UmAJXCddDn3PQkgQCaHDwQQoA8pRFgDAoww9Jpa/qykfyxpq6T/3BrjlZI+Jil5g+kzko5L+kDB+DkBnjt7Rlu3bV/cLbsEvjV7VQMr1xUugdPjWALXlLDB0yJAg6E6aOmtkv6ppG2SXifpi5JeKOnPJH1S0mOS1kv6PUkfkvSRTg9BTp86qR07dxULcOaKBoaTU939y94DTI9DgA5mQKBDIsBAg/Oo7BdJ+iNJWyT9RUaAb5N0WNJDkhZa9f6cpOSfl3YSYHtv2SvA9m1ZAabbEKBHs8PzUhCg5wF5Xl4yf85IOiXpREt06RXghyUlv2z0hkwPr5Z0Xnc/9/fdzH/nHqDnQVstDwFaTbY3fb2jdd8vvWGXXOmlAvyEpOTzKm/JlPIySQqhYjsAACAASURBVN+SlFw1Pn0vATabTTUajcIl8O2FefX1DxYugdPjuALsTfgWRkGAFlJ008M/kPSHksYkXW2VkAgwfQhyVNIjkl5f9QrwwPg+HZ5IDr/7l10C37x2XkNrk9X23b/sEjg9DgG6mRAhjooAQ0zNj5rfLumYpNlMOT/Q+veTrfuCRyQ9LOlWa593S3pn64FItos7S+DXbt2mRx55uW7Nz+snXrdVX/7SH+ixJz6oh350/M6+t2auSP2DGlj1kjv/nnwo+l1vGtHjTz6l5AnwF3738/rTP/0TrVr1oD732c8ku6xqq88PclThDQEE6E0UwRXyfcnFWabqZC7919aS96yk+cxT4Cda0vu8pOTSruNT4HYSPAQJbm4EUzACDCaqIArN3gNMCn6FpI9LelXrSuzXWh+JaW+GhyBBxGuvSARoL9MQO8oJkM8BhhhhmDUjwDBzs1Y13wSxlmgg/SDAQIIyXiZLYOMB+9oeAvQ1mbjqQoBx5e1NtwjQmyiiLiQnQN4HGPVc6GnzCLCnuBnsHgRyAuSN0MyTXhFAgL0izTidCLAEZn44IYAAnWBn0DYCCJAp4YQAAnSCnUERIHPABwII0IcUqCF3BXji+DHt3rN3kUr2q3DzNy5pcPXGxW3ZlyGkx/EyBCZUWQIIsCwp9quTQE6AFyYntXksecnM3b+sABfmptW/4tlfjMsKMD0OAdYZla1zI0BbeYbaDfcAQ00u8LoRYOABGikfARoJMrQ2EGBoidmsNyfAy1NT2jCavE2/YAncnFF/49m3cGWXwOlxLIFtTpI6ukKAdVDlnFUJ5AQ4ceSQxvcfLBTg/PWLGlyT/Mrm3b+sANPjEGBV/PHujwDjzd6nzlkC+5RGRLUgwIjC9rhVBOhxOJZLQ4CW0w2nNwQYTlamKkWApuIMthnuAQYbXdiFI8Cw87NSPU+BrSQZWB8IMLDAjJbLEthosL63hQB9TyiO+hBgHDl71yUC9C6SKAviu8BRxu6+aQToPgMqkHgbDLPACQEE6AQ7g7YRYAnMlHBCAAE6wc6gCJA54AMBBOhDCtTAFSBzwAkBBOgEO4N2ugLkV+GYH70igAB7RZpxOhHgd4GZH04IIEAn2BmUe4DMAR8IIEAfUqAG7gEyB5wQQIBOsDNopyvAc2fPaOu27Yu7ZH8U6dbsVQ2sXLe4LftC1PQ4XojK/CpLAAGWJcV+dRLIXQGePnVSO3buKhbgzBUNDK8vFGB6HAKsMypb50aAtvIMtRuWwKEmF3jdCDDwAI2UjwCNBBlaGwgwtMRs1psTYLPZVKPRKFwC316YV1//YOESOD2OJbDNSVJHVwiwDqqcsyqBnAAPjO/T4YmjhQK8ee28htZuKRRgehwCrIo/3v0RYLzZ+9Q5V4A+pRFRLQgworA9bpV7gB6HY7k0BGg53XB6Q4DhZGWqUgRoKs5gm+FzgMFGF3bhCDDs/KxUnxMg3wSxEqv/fSBA/zOKoUKWwDGk7GGPCNDDUCIsCQFGGLoPLSNAH1KgBt4HyBxwQgABOsHOoG0EcgLkjdDMj14RQIC9Is04nQiwBGZ+OCGAAJ1gZ9BOV4DtdLLvA2zfln0fYLqNr8Ixv8oSQIBlSbFfnQS4AqyTLue+JwEEyOTwgUBOgCeOH9PuPXsX68peAc7fuKTB1RsXt2WvANPjuAL0IdIwakCAYeRkvcqcAC9MTmrz2FihABfmptW/YqRQgOlxCND6dOlefwiweyw509IJsAReOjuOXAYBBLgMeBzaNQIIsGsoOVEVAgiwCi32rYtAToCXp6a0YXS0eAncnFF/Y7hwCZwexxK4rpjsnRcB2ss0xI5yApw4ckjj+w8WPwS5flGDazYVCjA9DgGGOAXc1IwA3XBn1DwBlsDMCCcEEKAT7AzaRgABMiWcEECATrAzKAJkDvhAAAH6kAI1cA+QOeCEAAJ0gp1BO10Btj8Fzu5b5gnx7Vvf09998zeSw1ZJmoU2BO5FAAEyN3wg0PEeYKcCi16UgAB9iDSMGhBgGDlZrxIBWk/Y0/4QoKfBRFZWx+8CZ1mU+Z4wV4CRzZ5ltIsAlwGPQ7tGoOPbYLKjlHlTDALsWi7mT4QAzUccRIMsgYOIyV6RCNBepiF2hABDTM1AzQjQQIgGWkCABkIMsQUEGGJq9mru+Ktw2XbL/GIc9wDtTZC6OkKAdZHlvFUIdPxd4OyJpqenNTLy7Buhs58DvH1zTn1DK4QAq6CPe18EGHf+vnTPEtiXJCKrAwFGFrin7SJAT4OxXhYCtJ5wGP3lBHju7Blt3ba9sPL2bdkl8K3ZqxpYuY4lcBiZe1ElAvQihuiLyAnw9KmT2rFzVyGU9m05Ac5c0cDwegQY/XQqDwABlmfFnvURYAlcH1vO3IEAAmR6+EAAAfqQQoQ1IMAIQ/ew5ZwAm82mGo1GYZnt23Ifg1mYV1//IEtgDwP2tSQE6GsycdWVE+CB8X06PHG0kED7tqwAb147r6G1WxBgXHNnWd0iwGXh4+AuEeAKsEsgOU01AgiwGi/2rocA9wDr4cpZ70MAATJFfCCAAH1IIcIaEGCEoXvYMp8D9DCUGEpCgDGk7H+PfBPE/4xMVogATcYaXFMsgYOLzEbBCNBGjqF3gQBDTzDQ+hFgoMEZK5v3ARoLNJR2EGAoSdmukzdC287X2+4QoLfRRFUYS+Co4vanWQToTxYxV4IAY07fYe8I0CF8hl4kgACZDE4IIEAn2Bm0jUBOgCeOH9PuPXsLIbVvy74MYf7GJQ2u3sjLEJhepQkgwNKo2LFGAjkBXpic1OaxscLh2rdlBbgwN63+FSMIsMagrJ0aAVpLNMx+WAKHmVvwVSPA4CM00QACNBFjeE0gwPAys1hxToCXp6a0YXS0sM/2bbklcHNG/Y1hlsAWZ0hNPSHAmsBy2koEcgKcOHJI4/sPFp6gfVvuIcj1ixpcswkBVkIf984IMO78femeJbAvSURWBwKMLHBP20WAngZjvSwEaD3hMPpDgGHkZK5KBGgu0iAb4h5gkLGFXzQCDD9DCx3wFNhCigH2gAADDM1gySyBDYYaQksIMISU7NeIAO1n7GWHCNDLWKIriu8CRxe5Hw0jQD9yiL0K3gYT+wxw1D8CdASeYXMEWAIzIZwQQIBOsDNoGwEEyJRwQgABOsHOoAiQOeADAQToQwrUwK/CMQecEECATrAzaKcrwOnpaY2MjBRCat+WfRvM7Ztz6htawdtgmF6lCSDA0qjYsUYC3AOsES6nvjcBBMjs8IEAAvQhhQhrQIARhu5hyzkBnjt7Rlu3bS8ss31bdgl8a/aqBlauYwnsYcC+loQAfU0mrrpyAjx96qR27NxVSKB9W06AM1c0MLweAcY1d5bVLQJcFj4O7hIBlsBdAslpqhFAgNV4sXc9BBBgPVw5630IIECmiA8EcgJsNptqNBqFdbVvy30MZmFeff2DLIF9SDSQGhBgIEEZLzMnwAPj+3R44mhhy+3bsgK8ee28htZuQYDGJ0s320OA3aTJuZZKgCvApZLjuGURQIDLwsfBXSLAPcAugeQ01QggwGq82LseAgiwHq6clYcgzIEACPA5wABCslgiV4AWUw2vJ74JEl5mJipGgCZiDL4JlsDBRxhmAwgwzNx8qvpRSU9K+hFJtyT9iaQtkm5LeqWkj0naJOkZScclfaCgeAToU6IR1YIAIwq7hlYT+f2upHdJ+o+SvifpVZK+JumFkv5M0iclPSZpvaTfk/QhSR9pqyUnQN4HWENSnLKQAAJkYiyHwB9KmpS0v+Akb5N0WNJDkhZa239OUvLPSzsJ8H3vfY8ef/Kpwrrat+U+CP30VzX08KN8EHo5iUZ2LAKMLPAutvsCSbOtK7rXSPoHkv5fSR+U9J8kfVjSqKQ3ZMZ8taTzkpIrvu9m/jtL4C4Gw6nKE0CA5VmxZ57AiyRdlXRd0k9K+mNJ/1jSpyX9uKTdkh6Q9JbMYS+T9C1JybFPI0CmlGsCCNB1AuGOv0rSjKRDkt6TaeMLkv4vSc+T9Iik13MFGG7I1itHgNYTrre/K62HH1kBnpF0UdKfSjoi6eHW0+GkkndLemfrgUi2sjtL4Ndu3aZHHnm5Ln3zG/rZd71bX/7SH+ixJz64+GaY5GWok//nH+lDH/nf7hybPCx56avedOe+X/I26Pm/SoaV+gaer4Vnvp38z0TSyTKdPwgUEkCATIzlEEgeaCTyS67yvtlaCp+U9GMtAaZPgZ9oSe/zkpLXvHR8CnxhclKbx8YK62rfln0IsjA3rf4VIzwEWU6ikR2LACMLvIZ2f1HSOyQ92PrYS/I5v99pjfMKSR9vfTQmuRL7tdZHYtrL4CFIDcFwyvsTQID3Z8Qe9RNAgPUzZoQCAgiQaeEDgZwAL09NacNo8gma5/61b8stgZsz6m8MswT2IdFAakCAgQRlvMycACeOHNL4/oOFLbdvywpw/vpFDa7ZhACNT5ZutocAu0mTcy2VAEvgpZLjuGURQIDLwsfBXSKAALsEktNUI4AAq/Fi73oIIMB6uHLW+xBAgEwRHwhwD9CHFCKsAQFGGLqHLfMU2MNQYigJAcaQsv89sgT2PyOTFSJAk7EG1xQCDC4yGwUjQBs5ht5FToB8Fzj0OMOpHwGGk5XlSnMCPHH8mHbv2VvYb/u23Aehb1zS4OqNfBDa8kzpcm8IsMtAOd2SCLAEXhI2DlouAQS4XIIc3w0CCLAbFDlHZQIIsDIyDqiBAAKsASqnvD8BBHh/RuxRP4GcAPlVuPqBM8JdAgiQmeADAX4X2IcUIqwBAUYYuoctswT2MJQYSkKAMaTsf48I0P+MTFaIAE3GGlxTOQGeO3tGW7dtL2yifVv2c4DJL8MNrFzH5wCDi99dwQjQHXtGfpZAToDJz1/u2LmrkE/7tpwAZ65oYHg9AmRmlSaAAEujYscaCbAErhEup743AQTI7PCBAAL0IYUIa0CAEYbuYcs5ATabTTUajcIy27dll8C3F+bV1z/IEtjDgH0tCQH6mkxcdeUEeGB8nw5PHC0k0L4tK8Cb185raO0WBBjX3FlWtwhwWfg4uEsEuALsEkhOU40AAqzGi73rIcA9wHq4ctb7EECATBEfCCBAH1KIsAYEGGHoHrbM5wA9DCWGkhBgDCn73yPfBPE/I5MVIkCTsQbXFEvg4CKzUTACtJFj6F0gwNATDLR+BBhocMbK5n2AxgINpR0EGEpStuvkjdC28/W2OwTobTRRFcYSOKq4/WkWAfqTRcyVIMCY03fYOwJ0CJ+hFwkgQCaDEwII0Al2Bm0jkBPgiePHtHvP3kJI7duyL0OYv3FJg6s38jIEpldpAgiwNCp2rJFAToAXJie1eWyscLj2bVkBLsxNq3/FCAKsMShrp0aA1hINsx+WwGHmFnzVCDD4CE00gABNxBheEwgwvMwsVpwT4OWpKW0YHS3ss31bbgncnFF/Y5glsMUZUlNPCLAmsJy2EoGcACeOHNL4/oOFJ2jflnsIcv2iBtdsQoCV0Me9MwKMO39fumcJ7EsSkdWBACML3NN2EaCnwVgvCwFaTziM/hBgGDmZqxIBmos0yIa4BxhkbOEXjQDDz9BCBzwFtpBigD0gwABDM1gyS2CDoYbQEgIMISX7NSJA+xl72SEC9DKW6Iriu8DRRe5HwwjQjxxir4K3wcQ+Axz1jwAdgWfYHAGWwEwIJwQQoBPsDNpGAAEyJZwQQIBOsDMoAmQO+EAAAfqQAjXwq3DMAScEEKAT7Aza6QpwenpaIyMjhZDat2XfBnP75pz6hlbwNhimV2kCCLA0KnaskQD3AGuEy6nvTQABMjt8IIAAfUghwhoQYIShe9hyToDnzp7R1m3bC8ts35ZdAt+avaqBletYAnsYsK8lIUBfk4mrrpwAT586qR07dxUSaN+WE+DMFQ0Mr0eAcc2dZXWLAJeFj4O7RIAlcJdAcppqBBBgNV7sXQ8BBFgPV856HwIIkCniA4GcAJvNphqNRmFd7dtyH4NZmFdf/yBLYB8SDaQGBBhIUMbLzAnwwPg+HZ44Wthy+7asAG9eO6+htVsQoPHJ0s32EGA3aXKupRLgCnCp5DhuWQQQ4LLwcXCXCHAPsEsgOU01AgiwGi/2rocAAqyHK2flIQhzIAACfA4wgJAslsgVoMVUw+uJb4KEl5mJihGgiRiDb4IlcPARhtkAAgwzN2tVI0BriQbSDwIMJCjjZeYEyPsAjaftUXsI0KMwIi6FN0JHHL7L1hGgS/qMnRJgCcxccEIAATrBzqBtBBAgU8IJAQToBDuDIkDmgA8EEKAPKVBD7grwxPFj2r1nbyGV9m3ZlyHM37ikwdUbeRkC86k0AQRYGhU71kggJ8ALk5PaPDZWOFz7tqwAF+am1b9iBAHWGJS1UyNAa4mG2Q/3AMPMLfiqEWDwEZpoAAGaiDG8JhBgeJlZrDgnwMtTU9owOlrYZ/u23BK4OaP+xjBLYIszpKaeEGBNYDltJQI5AU4cOaTx/QcLT9C+LfcQ5PpFDa7ZhAAroY97ZwQYd/6+dM8S2JckIqsDAUYWuKftIkBPg7FeFgK0nnAY/SHAMHIyVyUCNBdpkA1xDzDI2MIvGgGGn6GFDngKbCHFAHtAgAGGZrBklsAGQw2hJQQYQkr2a0SA9jP2skME6GUs0RXFd4Gji9yPhhGgHznEXgVvg4l9BjjqHwE6As+wOQIsgZkQTgggQCfYGbSNAAJkSjghgACdYGdQBMgc8IEAAvQhBWrgV+GYA04IIEAn2Bm00xUgvwvM/OgVAQTYK9KM04kA9wCZH04IIEAn2BmUe4DMAR8IIEAfUqCG3BXgubNntHXb9kIq7duyL0S9NXtVAyvX8UJU5lNpAgiwNCp2rJFAToCnT53Ujp27Codr35YT4MwVDQyvR4A1BmXt1AjQWqJh9sM9wDBzC75qBBh8hCYaQIAmYgyvCQQYXmYWK84JsNlsqtFoFPbZvi27BL69MK++/kGWwBZnSE09IcCawHLaSgRyAjwwvk+HJ44WnqB9W1aAN6+d19DaLQiwEvq4d0aAcefvS/dcAfqSRGR1IMDIAve0Xe4BehqM9bIQoPWEw+gPAYaRk7kqEaC5SINsiM8BBhlb+EUjwPAztNAB3wSxkGKAPSDAAEMzWDJLYIOhhtASAgwhJfs1IkD7GXvZIQL0MpboisoJkPcBRpe/s4YRoDP0DJwhwBuhmQ5OCCBAJ9gZtI0AS2CmhBMCCNAJdgZFgMwBHwggQB9SoAauAJkDTgggQCfYGbTTFeCJ48e0e8/eQkjt27IvQ5i/cUmDqzfyMgSmV2kCCLA0KnaskUDuCvDC5KQ2j40VDte+LSvAhblp9a8YQYA1BmXt1AjQWqJh9sMSOMzcgq8aAQYfoYkGEKCJGMNrAgGGl5nFinMCvDw1pQ2jo4V9tm/LLYGbM+pvDLMEtjhDauoJAdYEltNWIpAT4MSRQxrff7DwBO3bcg9Brl/U4JpNCLAS+rh3RoBx5+9L9yyBfUkisjoQYGSBd7nd75f0IUmvl5T8itGfSvpFSV9pjfNKSR+TtEnSM5KOS/pAQQ0IsMvBcLpyBBBgOU7sVUzgU5JeLOmnJc1I+teSflnSOkm3JP2ZpE9KekzSekm/1xLmR9pOhwCZYU4IIEAn2M0M+s3WVd1HWx09IGlW0mZJj0g6LOkhSQut7T8nKfnnpZ0EyD1AM/PD+0YQoPcReV1gcmX3E5LeLOm/Sdon6V9ISpa+T0lKHuW+IdPBqyWdl5Rc8X038995Cux1zHaLQ4B2s+1FZ98n6bOStrWWvIkE/4mkr0r6hKQVkt6SKeRlkr4l6UWSnr6XAKsUnn0KnB53+9b39Hff/I3kX1e1rkirnJJ9IyKAACMKu4ZW/7B1n+8XWqL5SUm/KenHJb2ttQxOHpCkfx2vAF+7dZseeeTld/b98df8I335S3+gx574oBqN5PmKdPrUST344IPaum37nX9PXpz60le9SUMPP6pbs1e18DdXtfD/3VDfwPO18My3EWANgVs7JQK0lmjv+lkt6a8k/bCk/zsz7NclnUz8JOmIpIdbV4fJLu+W9M7WA5FspXwXuHe5MVKGAAJkOiyHwHck/X7r3t+cpDdK+o+t//tfMk+Bn2hJ7/OSjkrq+BSYt8EsJxKOrUIAAVahxb7tBJL1avKk97+X9DxJVyX9qqQTrR1fIenjkl7VWiL/WusjMe3n4WMwzC0nBBCgE+wM2kYAATIlnBBAgE6wMygCZA74QAAB+pACNfCrcMwBJwQQoBPsDNrpCpDfBWZ+9IoAAuwVacbpRIB7gMwPJwQQoBPsDMo9QOaADwQQoA8pUEPuCvDc2TOL3/ZoR9O+LftVuOTbIAMr1/FCVOZTaQIIsDQqdqyRQE6AyVfeduzcVThc+7acAGeuaGB4PQKsMShrp0aA1hINsx/uAYaZW/BVI8DgIzTRAAI0EWN4TSDA8DKzWHFOgM1mc/ENMO3Ntm/LLoFvL8yrr3+QJbDFGVJTTwiwJrCcthKBnAAPjO/T4YnknQnP/WvflhXgzWvnNbR2CwKshD7unRFg3Pn70j1XgL4kEVkdCDCywD1tl3uAngZjvSwEaD3hMPpDgGHkZK5KBGgu0iAb4nOAQcYWftEIMPwMLXTAN0EspBhgDwgwwNAMlswS2GCoIbSEAENIyX6NCNB+xl52iAC9jCW6onIC5H2A0eXvrGEE6Aw9A2cI8EZopoMTAgjQCXYGbSPAEpgp4YQAAnSCnUERIHPABwII0IcUqIErQOaAEwII0Al2Bu10BXji+DHt3rO3EFL7tuzLEOZvXNLg6o28DIHpVZoAAiyNih1rJJC7ArwwOanNY2OFw7VvywpwYW5a/StGEGCNQVk7NQK0lmiY/bAEDjO34KtGgMFHaKIBBGgixvCaQIDhZWax4pwAL09NacPoaGGf7dtyS+DmjPobwyyBLc6QmnpCgDWB5bSVCOQEOHHkkMb3Hyw8Qfu23EOQ6xc1uGYTAqyEPu6dEWDc+fvSPUtgX5KIrA4EGFngnraLAD0NxnpZCNB6wmH0hwDDyMlclQjQXKRBNsQ9wCBjC79oBBh+hhY64CmwhRQD7AEBBhiawZJZAhsMNYSWEGAIKdmvEQHaz9jLDhGgl7FEVxTfBY4ucj8aRoB+5BB7FTkB8jaY2KdD7/pHgL1jzUj3JsASmNnhhAACdIKdQdsIIECmhBMCCNAJdgZFgMwBHwggQB9SoAZ+FY454IQAAnSCnUE7XQHyu8DMj14RQIC9Is04nQhwD5D54YQAAnSCnUG5B8gc8IEAAvQhBWrIXQGeO3tGW7dtL6TSvi37QtRbs1c1sHIdL0RlPpUmgABLo2LHGgnkBHj61Ent2LmrcLj2bTkBzlzRwPB6BFhjUNZOjQCtJRpmP9wDDDO34KtGgMFHaKIBBGgixvCaQIDhZWax4pwAm82mGo1GYZ/t27JL4NsL8+rrH2QJbHGG1NQTAqwJLKetRCAnwAPj+3R44mjhCdq3ZQV489p5Da3dggAroY97ZwQYd/6+dM8VoC9JRFYHAowscE/b5R6gp8FYLwsBWk84jP4QYBg5masSAZqLNMiG+BxgkLGFXzQCDD9DCx3wTRALKQbYAwIMMDSDJbMENhhqCC0hwBBSsl8jArSfsZcdIkAvY4muqJwAeR9gdPk7axgBOkPPwBkCvBGa6eCEAAJ0gp1B2wiwBGZKOCGAAJ1gZ1AEyBzwgQAC9CEFauAKkDnghAACdIKdQTtdAZ44fky79+wthNS+LfsyhPkblzS4eiMvQ2B6lSaAAEujYscaCeSuAC9MTmrz2FjhcO3bsgJcmJtW/4oRBFhjUNZOjQCtJRpmPyyBw8wt+KoRYPARmmgAAZqIMbwmEGB4mVmsOCfAy1NT2jA6Wthn+7bcErg5o/7GMEtgizOkpp4QYE1gOW0lAjkBThw5pPH9BwtP0L4t9xDk+kUNrtmEACuhj3tnBBh3/r50zxLYlyQiqwMBRha4p+0iQE+DsV4WArSecBj9IcAwcjJXJQI0F2mQDXEPMMjYwi8aAYafoYUOeApsIcUAe0CAAYZmsGSWwAZDDaElBBhCSvZrRID2M/ayQwToZSzRFcV3gaOL3I+GEaAfOcReRU6AvA0m9unQu/4RYO9YM9K9CbAEZnY4IYAAnWBn0DYCCJAp4YQAAnSCnUERIHPABwII0IcUqIFfhWMOOCGAAJ1gZ9BOV4D8LjDzo1cEEGCvSDNOJwLcA2R+OCGAAJ1gZ1DuATIHfCCAAH1IgRpyV4Dnzp7R1m3bC6m0b8u+EPXW7FUNrFzHC1GZT6UJIMDSqNixRgI5AZ4+dVI7du4qHK59W06AM1c0MLweAdYYlLVTI0BriYbZD/cAw8wt+KoRYPARmmgAAZqIMbwmEGB4mVmsOCfAZrOpRqNR2Gf7tuwS+PbCvPr6B1kCW5whNfWEAGsCy2krEcgJ8MD4Ph2eOFp4gvZtWQHevHZeQ2u3IMBK6OPeGQHGnb8v3XMF6EsSkdWBACML3NN2uQfoaTDWy0KA1hMOoz8EGEZO5qpEgOYiDbIhPgcYZGzhF40Aw8/QQgd8E8RCigH2gAADDM1gySyBDYYaQksIMISU7NeIAO1n7GWHCNDLWKIrKidA3gcYXf7OGkaAztAzcIYAb4RmOjghgACdYGfQNgIsgZkSTgggQCfYGRQBMgd8IIAAfUiBGrgCZA44IYAAnWBn0E5XgCeOH9PuPXsLIbVvy74MYf7GJQ2u3sjLEJhepQkgwNKo2LFGArkrwAuTk9o8NlY4XPu2rAAX5qbVv2IEAdYYlLVTI0BriYbZD0vgMHMLvmoEGHyEJhpAgCZiDK8JBBheZhYrzgnw8tSUNoyOFvbZvi23BG7OqL8xzBLY4gypqScEWBNYTluJQE6AE0cOaXz/wcITtG/LPQS5flGDazYhwEro494ZAcadvy/dh+k3CgAAIABJREFUswT2JYnI6kCAkQXuabsI0NNgrJeFAK0nHEZ/CDCMnMxViQDNRRpkQ9wDDDK28ItGgOFnaKEDngJbSDHAHhBggKEZLJklsMFQQ2gJAYaQkv0aEaD9jL3sEAF6GUt0RfFd4Ogi96NhBOhHDrFXkRMgb4OJfTr0rn8E2DvWjHRvAiyBmR1OCCBAJ9gZtI0AAmRKOCGAAJ1gZ1AEyBzwgQAC9CEFauBX4ZgDTgggQCfYgxj0LZJ+VtIrJb1Q0qCkhUzlyX//mKRNkp6RdFzSB9o6S/59t6RVkr4u6R2SvlXQPb8LHMSUsFckArSXabc62iZpWNILJH2iTYCJEP9M0iclPSZpvaTfk/QhSR9pFbBf0rskvUHSn0t6v6S3StogaY4lcLdi4jzLIYAAl0MvjmNfI+mLbQJ8m6TDkh7KXBX+nKTkn5e2sHxH0lFJH239+4CkpyX9gqRPFQnw+a/4l+obeN5zqM58LbnQLP83OzurNT+QXHTeufKcLX8ke8ZGAAHGlnj1fosE+GFJySubk6u79O/Vks5LSpaziexmJD0q6UJmnzOSLrUkmK3kzhI4FeCt2asaWLlucXtWgOfOntHWbdsLu0i3IcDqIcd6BAKMNfnyfRcJMFkSr5CU3CdM/17Wur/3opYA/0JS8t8uZ/b5dOuKbE+nK8BbM1c0MJysqu/+ZQV4+tRJ7di5q7D6dBsCLB9u7HsiwNhnwP37LxJgsrR9RNLrK14BnpX0DUnjRQLse+DF6v++77+zqf+BtVr47jUNPjSmv/76r9/5b4ngHnzwwcUrwOnpaX38o7+qx598SsnVX/LPpW9+Q6tWPajPffYzySEsge+fb9R7IMCo4y/VfJEAk4cZRyQ9LOlW6yzvlvTO1gOR5D99W1KyVE7vASZPkZN7gD8v6bc6XQG2V8U9wFI5sdMSCCDAJUCL5JB+SckTiR+T9AVJD7QeePxda/mbPgV+oiW9z7ceeqRPgZOrvOQp8BtbMkyeAv9M6ynw33YS4O2FefX1J7587hK42Wyq0WgURpBuYwkcyQztQpsIsAsQjZ7i7a2PuSTt3ZaUzpXkivArkl4h6eOSXtW6r/drrY/EZHEknwNM7vclDzm+1vpc4T0/B5g+BLl57byG1m4pFOCB8X06PJGswJ/7l25DgEZnZA1tIcAaoHLKygRyT4G5AqzMjwOWSAABLhEch3WVQE6A7WfmHmBXWXOyDAEEyHTwgQAC9CGFCGtAgBGG7mHL+Q9C8zlADyOyWRICtJlraF3xTZDQEjNSLwI0EmTgbbAEDjzAUMtHgKEmZ6tuBGgrz2C6QYDBRGW60PzHYG7OqW8o+arx3b/sU+Dk628jIyOFMNJtfA7Q9FzpanMIsKs4OdkSCeQEePPpr2ro4eRFMs8V4Pve+5473/0t+ku3IcAlphDhYQgwwtA9bJklsIehxFASAowhZf97RID+Z2SyQgRoMtbgmkKAwUVmo2AEaCPH0LvICXD+xiUNrt5YeA/wxPFj2r1nb2G/6TbuAYY+HXpXPwLsHWtGujeBnAAX5qbVv+LZJ73Zp8AXJie1eWys8EzpNgTIVCtLAAGWJcV+dRJgCVwnXc59TwIIkMnhAwEE6EMKEdaAACMM3cOW80vg5oz6G8lPEt/9yy6BL09NacNo8oN0z/1Lt7EE9jBhT0tCgJ4GE1lZ+Ycg1y9qcM2mQgFOHDmk8f0HC/Gk2xBgZLNnGe0iwGXA49CuEWAJ3DWUnKgKAQRYhRb71kUAAdZFlvN2JIAAmSA+EECAPqQQYQ0IMMLQPWyZe4AehhJDSQgwhpT975GnwP5nZLJCBGgy1uCaYgkcXGQ2CkaANnIMvQsEGHqCgdaPAAMNzljZfBfYWKChtIMAQ0nKdp28DcZ2vt52hwC9jSaqwlgCRxW3P80iQH+yiLkSBBhz+g57R4AO4TP0IgEEyGRwQgABOsHOoG0E+FU4poQTAgjQCXYG7STA2/wuMBOkRwQQYI9AM0xHAiyBmSBOCCBAJ9gZtNMVYDud7AtRy5DjfYBlKLFPQgABMg98IJC7Arw1e1UDK9ct1pUV4LmzZ7R12/bCmtNtCNCHSMOoAQGGkZP1KvMCnLmigeH1hQI8feqkduzcVcgj3YYArU+X7vWHALvHkjMtnQD3AJfOjiOXQQABLgMeh3aNAALsGkpOVIUAAqxCi33rIpAT4O2FefX1DxYugZvNphqNRmEd6TaWwHXFZO+8CNBepiF2lP8g9LXzGlq7pVCAB8b36fDE0cIe020IMMQp4KZmBOiGO6PmCXAFyIxwQgABOsHOoG0EuAfIlHBCAAE6wc6gCJA54AMBBOhDCtTA5wCZA04IIEAn2Bm00xUg3wRhfvSKAALsFWnG6USAe4DMDycEEKAT7AzKPUDmgA8EEKAPKVBD/mMwvA+QGdEjAgiwR6AZpiMB3gjNBHFCAAE6wc6gLIGZAz4QQIA+pEANPARhDjghgACdYGdQrgCZAz4QQIA+pEANuSvA+RuXNLh64yKV7BuhTxw/pt179hYSS7fxMgQmVFkCCLAsKfark0BOgAtz0+pfMVIowAuTk9o8NlZYS7oNAdYZla1zI0BbeYbaDfcAQ00u8LoRYOABGikfARoJMrQ2EGBoidmsN78Ebs6ovzFcuAS+PDWlDaOjhRTSbSyBbU6SOrpCgHVQ5ZxVCeQfgly/qME1mwoFOHHkkMb3Hyw8f7oNAVbFH+/+CDDe7H3qnCWwT2lEVAsCjChsj1tFgB6HY7k0BGg53XB6Q4DhZGWqUgRoKs5gm+EeYLDRhV04Agw7PyvV8xTYSpKB9YEAAwvMaLksgY0G63tbCND3hOKoDwHGkbN3XSJA7yKJsiC+Cxxl7O6bRoDuM6ACibfBMAucEECATrAzaBsBlsBMCScEEKAT7AyKAJkDPhBAgD6kQA1cATIHnBBAgE6wM2inK8CbT39VQw8/urhL9o3Q73vve/T4k08VAky38TIE5ldZAgiwLCn2q5MAvwtcJ13OfU8CCJDJ4QMBlsA+pBBhDQgwwtA9bBkBehhKDCUhwBhS9r/HnABvzV7VwMp1hfcAz509o63bthd2lG7jHqD/gftSIQL0JYm468gLcOaKBobXFwrw9KmT2rFzVyGtdBsCjHsyVekeAVahxb51EWAJXBdZztuRAAJkgvhAAAH6kEKENSDACEP3sOX8x2AW5tXXP1i4BG42m2o0GoUtpNtYAnuYsKclIUBPg4msrJwAb147r6G1WwoFeGB8nw5PHC3Ek25DgJHNnmW0iwCXAY9Du0aAK8CuoeREVQggwCq02LcuAtwDrIss5+UhCHPAewII0PuIbBbIFaDNXEPris8BhpaYkXoRoJEgA2+Db4IEHmCo5SPAUJOzVTdLYFt5BtMNAgwmKtOFIkDT8frbHAL0N5uYKuN9gDGl7VGvCNCjMCIuJf9BaN4IHfFU6G3rCLC3vBmtmABLYGaGEwII0Al2Bm0jgACZEk4IIEAn2BkUATIHfCCAAH1IgRpyV4DzNy5pcPXGRSrZX4U7cfyYdu/ZW0gs3cbLEJhQZQkgwLKk2K9OAjkBLsxNq3/FSKEAL0xOavPYWGEt6TYEWGdUts6NAG3lGWo33AMMNbnA60aAgQdopHwEaCTI0NpAgKElZrPe/BK4OaP+xnDhEvjy1JQ2jI4WUki3sQS2OUnq6AoB1kGVc1YlkH8Icv2iBtdsKhTgxJFDGt9/sPD86TYEWBV/vPsjwHiz96lzlsA+pRFRLQgworA9bhUBehyO5dIQoOV0w+kNAYaTlalKEaCpOINthnuAwUYXduEIMOz8rFTPU2ArSQbWBwIMLDCj5bIENhqs720hQN8TiqM+BBhHzt51iQC9iyTKgvgucJSxu28aAbrPgAok3gbDLHBCAAE6wc6gbQRYAjMlnBBAgE6wMygCZA74QAAB+pACNXAFyBxwQgABOsHOoJ2uAG/yq3BMkB4RQIA9As0wHQnwu8BMECcEEKAT7AzKPUDmgA8EEKAPKVAD9wCZA04IIEAn2Bm00xXgrdmrGli5bnGX7K/CnTt7Rlu3bS8EmG7jhajMr7IEEGBZUuxXJ4HcFeCtmSsaGF5fKMDTp05qx85dhbWk2xBgnVHZOjcCtJVnqN2wBA41ucDrRoCBB2ikfARoJMjQ2kCAoSVms978x2AW5tXXP1i4BG42m2o0GoUU0m0sgW1Okjq6QoB1UOWcVQnkBHjz2nkNrd1SKMAD4/t0eOJo4fnTbQiwKv5490eA8WbvU+dcAfqURkS1IMCIwva4Ve4BehyO5dIQoOV0w+kNAYaTlalKEaCpOLvazFsk/aykV0p6oaTkqcRCa4TNkn5J0o9IeoGkv5CU3Jj7d20VfEDSbkmrJH1d0jskfaugSj4H2NXoOFlZAgiwLKn49tsmabgluE+0CfANkv6epN+VdEPSayT9tqS3tv5vQmu/pHdJSvb9c0nvb23fIGmuDWdegHwTJL7Z5qhjBOgIfEDDJnL7YpsAi8r/bOtK8F+3Nn6ndVX40da/D0h6WtIvSPpUJwG2nzz7Vbgy3HgKXIYS+yQEECDz4H4EyggwuYKbkvSLkn6zteSdkfSopAuZAc5IutSSYHZc7gHeLwW210IAAdaC1dRJ7yfA57WWvcn/3dq6T/ji1tXgyyRdztD4tKRZSXs6XQHevjmnvqEVi7tkrwCnp6c1MjJSCDjdxhWgqflXazMIsFa8Jk7eSYDJA5D/1Foe/w+S/rbVcfLQo+gK8Kykb0ga7yRA3ghtYt4E0QQCDCImp0XeS4DJA5LPtx6CvFnS99qq/LakD0tK7wEmT5GTe4A/L+m3igTY98CL1f99339nU/8Da7Xw3WsafGhMf/31X7/z35K3vTz44IOLr8NKrvg+/tFf1eNPPqXkVVjJP5e++Q2tWvWgPvfZzySHJCJOrjj5g0AhAQTIxLgXgX5JybL2xyR9QdIDreXt30laIym5mvsTST8jab7gJMlVXvIU+I2SEhkmT4GTfZOnwOmVYnoY9wCZh04IIEAn2IMY9O2SPtmq9HbrgVnyf39C0o9L+uWCj7N8RdKbMt0lnwNM7vclgvta63OF9/0cYDsdngIHMV+CLBIBBhmbuaJzV4DzNy5pcPXGxSazAjxx/Jh279lbCCDdxkMQc/OjtoYQYG1oOXEFAjkBLsxNq3/Fs096swK8MDmpzWNjhadOtyHACuQj3xUBRj4BPGmfe4CeBBFbGQgwtsT97BcB+pmL+aoQoPmIg2gwvwRuzqi/kXzK5u5fdgl8eWpKG0ZHC5tKt7EEDiJzL4pEgF7EEH0R+Ycg1y9qcM2mQgFOHDmk8f0HC4Gl2xBg9POpNAAEWBoVO9ZIgCVwjXA59b0JIEBmhw8EEKAPKURYAwKMMHQPW0aAHoYSQ0kIMIaU/e+Re4D+Z2SyQgRoMtbgmuIpcHCR2SgYAdrIMfQuWAKHnmCg9SPAQIMzVjYCNBZoKO0gwFCSsl0n3wW2na+33SFAb6OJqjDeBhNV3P40iwD9ySLmSlgCx5y+w94RoEP4DL1IAAEyGZwQQIBOsDNoGwEEyJRwQgABOsHOoJ0EyK/CMT96RQAB9oo043QikLsC5HeBmSy9IoAAe0WacUoLsH1HfhSJyVMXAQRYF1nOW4UA9wCr0GLfrhFAgF1DyYmWQSAnwFuzVzWwct3i6bJXgMmPn2/dtr1wqHQbL0RdRhKRHYoAIwvc03bzApy5ooHh9YUCPH3qpHbs3FXYRroNAXqasodlIUAPQ4mwJJbAEYbuQ8sI0IcUqAEBMgecEECATrAzaBuB/MdgFubV1z9YuARuNptqNBqFANNtLIGZX2UJIMCypNivTgI5Ad68dl5Da7cUCvDA+D4dnjhaWEu6DQHWGZWtcyNAW3mG2g1XgKEmF3jdCDDwAI2Uzz1AI0GG1gYCDC0xm/UiQJu5et8VAvQ+oigK5HOAUcTsX5MI0L9MYqyIb4LEmLoHPSNAD0KgBLEEZhI4IYAAnWBn0DYCCJAp4YQAAnSCnUE7CZD3ATI/ekUAAfaKNON0IpD/IPTTX9XQw48u7p99G8z73vsePf7kU4XnSrfxQWgmW1kCCLAsKfarkwBL4Drpcu57EkCATA4fCCBAH1KIsAYEGGHoHraMAD0MJYaSEGAMKfvfY06A8zcuaXD1xsJ7gCeOH9PuPXsLO0q3cQ/Q/8B9qRAB+pJE3HXkBLgwN63+FSOFArwwOanNY2OFtNJtCDDuyVSlewRYhRb71kWAJXBdZDlvRwIIkAniAwEE6EMKEdaAACMM3cOW80vg5oz6G8OFS+DLU1PaMDpa2EK6jSWwhwl7WhIC9DSYyMrKPwS5flGDazYVCnDiyCGN7z9YiCfdhgAjmz3LaBcBLgMeh3aNAEvgrqHkRFUIIMAqtNi3LgIIsC6ynJeHIMwB7wkgQO8jslkgV4A2cw2tK+4BhpaYkXoRoJEgA2+Dp8CBBxhq+Qgw1ORs1c0S2FaewXSDAIOJynShCNB0vP42hwD9zSamyvgucExpe9QrAvQojIhL4W0wEYfvsnUE6JI+Y6cEWAIzF5wQQIBOsDNoGwEEyJRwQgABOsHOoAiQOeADAQToQwrUwK/CMQecEECATrAzaKcrQH4XmPnRKwIIsFekGacTAe4BMj+cEECATrAzKPcAmQM+EECAPqRADbkrwFuzVzWwct0ilZmvfWzxf587e0Zbt20vJJZu44WoTKiyBBBgWVLsVyeBvABnrmhgeH2hAE+fOqkdO3cV1pJuQ4B1RmXr3AjQVp6hdsM9wFCTC7xuBBh4gEbKR4BGggytDQQYWmI2680J8PbCvPr6BwuXwM1mU41Go5BCuo0lsM1JUkdXCLAOqpyzKoH8B6GvndfQ2i2FAjwwvk+HJ44Wnj/dhgCr4o93fwQYb/Y+dc4VoE9pRFQLAowobI9b5R6gx+FYLg0BWk43nN4QYDhZmaoUAZqKM9hm+BxgsNGFXTgCDDs/K9XzTRArSQbWBwIMLDCj5bIENhqs720hQN8TiqM+BBhHzt51iQC9iyTKgvIfg7k5p76hFYsgsi9DmJ6e1sjISCGkdBufA4xyDi2paQS4JGwc1GUCvBG6y0A5XTkCCLAcJ/aqlwBL4Hr5cvZ7EECATA0fCCBAH1KIsAYEGGHoHraMAD0MJYaSEGAMKfvfY06A8zcuaXD1xsKHICeOH9PuPXsLO0q38RDE/8B9qRAB+pJE3HXkBLgwN63+Fc8+6c0+Bb4wOanNY2OFtNJtCDDuyVSlewRYhRb71kWAJXBdZDlvRwIIkAniAwEE6EMKEdaAACMM3cOW80vg5oz6G8OF9wAvT01pw+hoYQvpNpbAHibsaUkI0NNgIisr/xDk+kUNrtlUKMCJI4c0vv9gIZ50GwKMbPYso10EuAx4HNo1AiyBu4aSE1UhgACr0GLfugggwLrIcl4egjAHvCeAAL2PyGaBXAHazDW0rrgHGFpiRupFgEaCDLwNngIHHmCo5SPAUJOzVTdLYFt5BtMNAgwmKtOFIkDT8frbHAL0N5uYKuO7wDGl7VGvCNCjMCIuhbfBRBy+y9YRoEv6jJ0SYAnMXHBCAAE6wc6gbQQQIFPCCQEE6AQ7gyJA5oAPBBCgDylQA78KxxxwQgABOsHOoJ2uAG/zu8BMkB4RQIA9As0wHQlwD5AJ4oQAAnSCnUG5B8gc8IEAAvQhBWrIXQHemr2qgZXrFqlkfxTp3Nkz2rpteyGxdBsvRGVClSWAAMuSYr86CeQFOHNFA8PrCwV4+tRJ7di5q7CWdBsCrDMqW+dGgLbyDLUb7gGGmlzgdSPAwAM0Uj4CNBJkaG0gwNASs1lvToC3F+bV1z9YuARuNptqNBqFFNJtLIFtTpI6ukKAdVDlnFUJ5D8Ife28htZuKRTggfF9OjxxtPD86TYEWBV/vPsjwHiz96lzrgB9SiOiWhBgRGF73Cr3AD0Ox3JpCNByuuH0hgDDycpUpQjQVJzBNsPnAIONLuzCEWDY+Vmpnm+CWEkysD4QYGCBGS2XJbDRYH1vCwH6nlAc9SHAOHL2rksE6F0kURaU/xgM7wOMchK4aBoBuqDOmO0EeCM0c8IJAQToBDuDthFgCcyUcEIAATrBzqAIkDngAwEE6EMK1MAVIHPACQEE6AQ7g3a6Apy/cUmDqzcu7pJ9I/SJ48e0e8/eQoDpNl6GwPwqSwABliXFfnUSyF0BLsxNq3/FSKEAL0xOavPYWGEt6TYEWGdUts6NAG3lGWo3LIFDTS7wuhFg4AHWWP5bJP2spFdKeqGk5A2lCwXjvUrSZOufH23b/gFJuyWtkvR1Se+Q9K2CcyDAGoPk1PcmgACZHfcisE3SsKQXSPrEPQSYvJr5a5KmJT1f0o9lTrZf0rskvUHSn0t6v6S3Stogaa7TPcCF5oz6G8nQd/+y9wAvT01pw+hoYc3pNpbATOqyBBBgWVLx7vcaSV+8hwA/JCmZQ89Iep2k7BXgdyQlr27+aAvdgKSnJf2CpE91EuD89YsaXLOpUIATRw5pfP/BwjTSbQgw3slatXMEWJVYfPvfS4DJ1d5xST8k6RclvTYjwGTJOyPpUUkXMsjOSLrUkmCWJEvg+OaVFx0jQC9i8LqIIgE+IOmPJf1zSecl/XKbAF8s6S8kvUzS5Ux3n5Y0K2lPpyvAdhrZJXAZUlwBlqHEPgkBBMg8uB+BIgH+uqS/k/Tu1sHtArzXFeBZSd+QNI4A74ed7b0ggAB7QTnsMYoEmNzfe1DSfKu15EHJUOte4GZJ32798+HMPcDkKXJyD/DnJf1WkQD7Hnix+r/v+7Xwt3+lwf/uh7Xw3WsafGhMf/31xLfS6VMn9fvnzurYbyTPZKTp6Wl9/KO/qseffErnzp7Rr3zwCT3/+c/XqlUP6nOf/UyySyLi5IqTPwgUEkCATIx7EeiX9LzWk90vSEqWvcnHYJIrv7/XeiiSriL2SUp+x/KfSLou6VbrKi95CvzGlgyTp8A/03oK/LedrgB5Csyk7BUBBNgr0uGN83ZJn2yVfTtzuyS5IvxKWzv/a+seYPZjMMkuyecAk/t9yUOO5OMyyecK+RxgeHPBbMUI0Gy0QTXGU+Cg4rJTLAK0k2XInfBd4JDTC7h2BBhweIZKzwmQt8EYStbzVhCg5wFFUh5L4EiC9q1NBOhbInHWgwDjzN151wjQeQQU0HpK/MzzX/Ev1TeQfPIm/8c3QZgjdRFAgHWR5bxVCPCrcFVosW/XCCDArqHkRMsgwO8CLwMehy6dAAJcOjuO7B4B7gF2jyVnqkAAAVaAxa61EUCAtaHlxJ0IIEDmhw8EcgK8NXtVAyvXLdaVfQiSvPRg67bthTWn23gdlg+RhlEDAgwjJ+tV5gU4c0UDw+sLBZi8EWbHzl2FPNJtCND6dOlefwiweyw509IJsAReOjuOXAYBBLgMeBzaNQIIsGsoOVEVAgiwCi32rYtA/mMwC/Pq60/en3r3L3sPsNlsqtFIfozuuX/pNpbAdcVk77wI0F6mIXaU/yD0tfMaWpu8X/W5Ajwwvk+HJ5Ifm3vuX7oNAYY4BdzUjADdcGfUPAGuAJkRTgggQCfYGbSNAPcAmRJOCCBAJ9gZFAEyB3wggAB9SIEa+Bwgc8AJAQToBDuDdroC5JsgzI9eEUCAvSLNOJ0IcA+Q+eGEAAJ0gp1BuQfIHPCBAAL0IQVq4H2AzAEnBBCgE+wM2ukK8ObTX9XQw48u7pL9Jsj73vsePf7kU4UA0218EJr5VZYAAixLiv3qJMA9wDrpcu57EkCATA4fCCBAH1KIsAYEGGHoHraMAD0MJYaSEGAMKfvfY06A8zcuaXD1xsJ7gCeOH9PuPXsLO0q3cQ/Q/8B9qRAB+pJE3HXkBLgwN63+FSOFArwwOanNY2OFtNJtCDDuyVSlewRYhRb71kWAJXBdZDlvRwIIkAniAwEE6EMKEdaAACMM3cOW80vg5oz6G8OFS+DLU1PaMDpa2EK6jSWwhwl7WhIC9DSYyMrKPwS5flGDazYVCnDiyCGN7z9YiCfdhgAjmz3LaBcBLgMeh3aNAEvgrqHkRFUIIMAqtNi3LgIIsC6ynJeHIMwB7wkgQO8jslkgV4A2cw2tK+4BhpaYkXoRoJEgA2+Dp8CBBxhq+Qgw1ORs1c0S2FaewXSDAIOJynShCNB0vP42hwD9zSamyvgucExpe9QrAvQojIhL4W0wEYfvsnUE6JI+Y6cEWAIzF5wQQIBOsDNoGwEEyJRwQgABOsHOoAiQOeADAQToQwrUkLsC5FfhmBC9IoAAe0WacToR4HeBmR9OCCBAJ9gZlCUwc8AHAgjQhxSogYcgzAEnBBCgE+wM2ukK8NbsVQ2sXLe4y8zXPrb4v8+dPaOt27YXAky38UJU5ldZAgiwLCn2q5NA7grw1swVDQyvLxTg6VMntWPnrsJa0m0IsM6obJ0bAdrKM9RuWAKHmlzgdSPAwAM0Uj4CNBJkaG0gwNASs1lv/mMwC/Pq6x8sXAI3m001Go1CCuk2lsA2J0kdXSHAOqhyzqoE8h+EvnZeQ2u3FArwwPg+HZ44Wnj+dBsCrIo/3v0RYLzZ+9R5/iHIM9/RwKqXFArw8//H7+hNP/lThbWn2xCgT9H6XQsC9DufWKrjCjCWpD3rEwF6Fkik5SDASIN33TYCdJ0A4ycE7gjweY+8TX0Dz9P3vvMFPe8lr18kc/VLE4v/+5++ZYf+90+fLqSWbvub2Vm99CUvTvZZJWkWxBC4FwEEyNzwgcBaSX9ZQyEvknSthvNySiMEEKCRIANvI5mHD0v6my728UJJT0u63cVzcipjBBCgsUBpBwIQKE8AAZZnxZ4QgIAxAgjQWKC0AwEIlCeAAMuzYk8IQMAYAQRoLFDagQAEyhNAgOVZsScEIGCMAAI0FijtQAAC5QkgwPKs2BMCEDBGAAEaC5R2IACB8gQQYHkSpXPdAAAEQUlEQVRW7AkBCBgjgACNBUo7EIBAeQIIsDwr9oQABIwRQIDGAqUdCECgPAEEWJ4Ve0IAAsYIIEBjgdIOBCBQngACLM+KPSEAAWMEEKCxQGkHAhAoTwABlmfFnhCAgDECCNBYoLQDAQiUJ4AAy7NiTwhAwBgBBGgsUNqBAATKE0CA5VmxJwQgYIwAAjQWKO1AAALlCSDA8qzYEwIQMEYAARoLlHYgAIHyBBBgeVbsCQEIGCOAAI0FSjsQgEB5AgiwPCv2hAAEjBFAgMYCpR0IQKA8AQRYnhV7QgACxgggQGOB0g4EIFCeAAIsz4o9IQABYwQQoLFAaQcCEChPAAGWZ8WeEICAMQII0FigtAMBCJQngADLs2JPCEDAGAEEaCxQ2oEABMoTQIDlWbEnBCBgjAACNBYo7UAAAuUJIMDyrNgTAhAwRgABGguUdiAAgfIEEGB5VuwJAQgYI4AAjQVKOxCAQHkCCLA8K/aEAASMEUCAxgKlHQhAoDwBBFieFXtCAALGCCBAY4HSDgQgUJ4AAizPij0hAAFjBBCgsUBpBwIQKE8AAZZnxZ4QgIAxAgjQWKC0AwEIlCeAAMuzYk8IQMAYAQRoLFDagQAEyhNAgOVZsScEIGCMAAI0FijtQAAC5QkgwPKs2BMCEDBGAAEaC5R2IACB8gQQYHlW7AkBCBgjgACNBUo7EIBAeQIIsDwr9oQABIwRQIDGAqUdCECgPAEEWJ4Ve0IAAsYIIEBjgdIOBCBQngACLM+KPSEAAWMEEKCxQGkHAhAoTwABlmfFnhCAgDECCNBYoLQDAQiUJ4AAy7NiTwhAwBgBBGgsUNqBAATKE0CA5VmxJwQgYIwAAjQWKO1AAALlCSDA8qzYEwIQMEYAARoLlHYgAIHyBBBgeVbsCQEIGCOAAI0FSjsQgEB5AgiwPCv2hAAEjBFAgMYCpR0IQKA8AQRYnhV7QgACxgggQGOB0g4EIFCeAAIsz4o9IQABYwQQoLFAaQcCEChPAAGWZ8WeEICAMQII0FigtAMBCJQngADLs2JPCEDAGAEEaCxQ2oEABMoTQIDlWbEnBCBgjAACNBYo7UAAAuUJIMDyrNgTAhAwRgABGguUdiAAgfIEEGB5VuwJAQgYI4AAjQVKOxCAQHkCCLA8K/aEAASMEUCAxgKlHQhAoDwBBFieFXtCAALGCCBAY4HSDgQgUJ4AAizPij0hAAFjBBCgsUBpBwIQKE8AAZZnxZ4QgIAxAgjQWKC0AwEIlCeAAMuzYk8IQMAYAQRoLFDagQAEyhNAgOVZsScEIGCMAAI0FijtQAAC5QkgwPKs2BMCEDBGAAEaC5R2IACB8gQQYHlW7AkBCBgjgACNBUo7EIBAeQIIsDwr9oQABIwRQIDGAqUdCECgPAEEWJ4Ve0IAAsYIIEBjgdIOBCBQngACLM+KPSEAAWMEEKCxQGkHAhAoT+D/By5tQWeZP8jqAAAAAElFTkSuQmCC\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(U, cmap=plt.cm.Blues)\n",
    "plt.title('U')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(S, cmap=plt.cm.Blues)\n",
    "plt.title('S')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            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",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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",
       "            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",
       "            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",
       "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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\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",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // 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 + '\">');\n",
       "    fig.send_message('closing', {});\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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 = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\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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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(V.T, cmap=plt.cm.Blues)\n",
    "plt.title('V')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def generate_dataset(option, noise=1, noise_background=True, shuffle=False):\n",
    "    shape = (150, 150)\n",
    "    n, m = shape\n",
    "    \n",
    "    # values can't be a lot far...\n",
    "    centers = [20, 40, 60, 80, 100, 120, 140, 160, 180]\n",
    "    \n",
    "    y_row = np.zeros(150)\n",
    "    y_col = np.zeros(150)\n",
    "\n",
    "    if noise_background:\n",
    "        data = np.random.rand(n, m) * 100\n",
    "    else:\n",
    "        data = np.zeros(n * m).reshape(shape) + np.random.uniform(0, 1, n*m).reshape(shape)\n",
    "\n",
    "    if option == 'a':\n",
    "        data[60:110][:, 70:140] = np.random.rand(50, 70) * noise + centers[0]\n",
    "        y_row[60:110] = 1\n",
    "        y_col[70:140] = 1\n",
    "    elif option == 'b':\n",
    "        data[0:50][:, 0:50] = np.random.rand(50, 50) * noise + centers[3]\n",
    "        y_row[0:50] = 0\n",
    "        y_col[0:50] = 0\n",
    "\n",
    "        data[50:100][:, 50:100] = np.random.rand(50, 50) * noise + centers[1]\n",
    "        y_row[50:100] = 1\n",
    "        y_col[50:100] = 1\n",
    "\n",
    "        data[100:150][:, 100:150] = np.random.rand(50, 50) * noise + centers[2]\n",
    "        y_row[100:150] = 2\n",
    "        y_col[100:150] = 2\n",
    "    elif option == 'c':\n",
    "        data[0:50][:, 0:50] = np.random.rand(50, 50) * noise + centers[0]\n",
    "        y_row[0:50] = 0\n",
    "        y_col[0:50] = 0\n",
    "\n",
    "        data[0:50][:, 50:100] = np.random.rand(50, 50) * noise + centers[7]\n",
    "        y_col[50:100] = 1\n",
    "\n",
    "        data[0:50][:, 100:150] = np.random.rand(50, 50) * noise + centers[3]\n",
    "        y_col[100:150] = 2\n",
    "\n",
    "        data[50:100][:, 0:50] = np.random.rand(50, 50) * noise + centers[2]\n",
    "        y_row[0:50] = 1\n",
    "\n",
    "        data[50:100][:, 50:100] = np.random.rand(50, 50) * noise + centers[4]\n",
    "\n",
    "        data[50:100][:, 100:150] = np.random.rand(50, 50) * noise + centers[8]\n",
    "\n",
    "        data[100:150][:, 0:50] = np.random.rand(50, 50) * noise + centers[6]\n",
    "        y_row[100:150] = 2\n",
    "\n",
    "        data[100:150][:, 50:100] = np.random.rand(50, 50) * noise + centers[1]\n",
    "\n",
    "        data[100:150][:, 100:150] = np.random.rand(50, 50) * noise + centers[5]\n",
    "    elif option == 'd':\n",
    "        data[0:50][:, 0:70] = np.random.rand(50, 70) * noise + centers[0]\n",
    "        y_row[0:50] = 0\n",
    "        y_col[0:70] = 0\n",
    "\n",
    "        data[50:100][:, 50:100] = np.random.rand(50, 50) * noise + centers[2]\n",
    "        y_row[50:100] = 1\n",
    "        y_col[50:100] = 1\n",
    "\n",
    "        data[100:150][:, 80:150] = np.random.rand(50, 70) * noise + centers[1]\n",
    "        y_row[100:150] = 2\n",
    "        y_col[80:150] = 2\n",
    "    elif option == 'e':\n",
    "        data[0:70][:, 0:50] = np.random.rand(70, 50) * noise + centers[3]\n",
    "        y_row[0:70] = 0\n",
    "        y_col[0:50] = 0\n",
    "\n",
    "        data[50:100][:, 50:100] = np.random.rand(50, 50) * noise + centers[1]\n",
    "        y_row[50:100] = 1\n",
    "        y_col[50:100] = 1\n",
    "\n",
    "        data[80:150][:, 100:150] = np.random.rand(70, 50) * noise + centers[2]\n",
    "        y_row[80:150] = 2\n",
    "        y_col[100:150] = 2\n",
    "    elif option == 'f':\n",
    "        data[0:50][:, 0:40] = np.random.rand(50, 40) * noise + centers[4]\n",
    "        y_row[0:50] = 0\n",
    "        y_col[0:40] = 0\n",
    "\n",
    "        data[50:150][:, 0:40] = np.random.rand(100, 40) * noise + centers[0]\n",
    "        y_row[50:150] = 1\n",
    "\n",
    "        data[110:150][:, 40:95] = np.random.rand(40, 55) * noise + centers[2]\n",
    "        y_row[110:150] = 2\n",
    "        y_col[40:95] = 1\n",
    "\n",
    "        data[110:150][:, 95:150] = np.random.rand(40, 55) * noise + centers[1]\n",
    "        y_col[95:150] = 2\n",
    "    elif option == 'g':\n",
    "        data[0:110][:, 0:40] = np.random.rand(110, 40) * noise + centers[0]\n",
    "        data[110:150][:, 0:110] = np.random.rand(40, 110) * noise + centers[2]\n",
    "        data[40:150][:, 110:150] = np.random.rand(110, 40) * noise + centers[1]\n",
    "        data[0:40][:, 40:150] = np.random.rand(40, 110) * noise + centers[3]\n",
    "    elif option == 'h':\n",
    "        data[0:90][:, 0:90] = np.random.rand(90, 90) * noise + centers[0]\n",
    "        data[35:55][:, 35:55] = (np.random.rand(20, 20) * noise + centers[1]) + data[35:55][:, 35:55]\n",
    "        data[110:140][:, 35:90] = np.random.rand(30, 55) * noise + centers[4]\n",
    "        data[0:140][:, 110:150] = np.random.rand(140, 40) * noise + centers[2]\n",
    "        data[0:55][:, 130:150] = (np.random.rand(55, 20) * noise + centers[3]) + data[0:55][:, 130:150]\n",
    "    elif option == 'i':\n",
    "        data[20:70][:, 20:70] = np.random.rand(50, 50) * noise + centers[0]\n",
    "        data[20:70][:, 100:150] = np.random.rand(50, 50) * noise + centers[1]\n",
    "        data[50:110][:, 50:120] = np.random.rand(60, 70) * noise + centers[2]\n",
    "        data[120:150][:, 20:100] = np.random.rand(30, 80) * noise + centers[3]\n",
    "\n",
    "    if shuffle:\n",
    "        np.random.shuffle(data)\n",
    "        np.random.shuffle(data.T)\n",
    "\n",
    "    return data, y_row, y_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pwUdRniIw+VSbfNJU1gzoRyGg6Y8f2zf2PKdpMfyWB84/wz7qGgdYLEPv7+/ttTQCU5Z3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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10696a1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "X, y_row, y_col = generate_dataset('e', noise_background=False)\n",
    "plt.matshow(X.T, cmap=plt.cm.Blues)\n",
    "# plt.title('data')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "h5f = h5py.File('data.h5','w')\n",
    "h5f.create_dataset('X', data=X.T) \n",
    "h5f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "k = 5\n",
    "l = 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "out: Reading X...  read 150 rows and 150 cols!\n",
      "U S V created\n",
      "Computing S... done!\n",
      "Computing V...\n",
      "  - for cluster 0... done!\n",
      "  - for cluster 1... done!\n",
      "  - for cluster 2... done!\n",
      "  - for cluster 3... done!\n",
      "  - for cluster 4... done!\n",
      "Done computed V!\n",
      "Computing U... done!\n",
      "Error obtained: 23351907.79336075857\n",
      "Computing S... done!\n",
      "Computing V...\n",
      "  - for cluster 0... done!\n",
      "  - for cluster 1...observations_cluster_i empty!!!!\n",
      "  - for cluster 2... done!\n",
      "  - for cluster 3...observations_cluster_i empty!!!!\n",
      "  - for cluster 4...observations_cluster_i empty!!!!\n",
      "Done computed V!\n",
      "Computing U... done!\n",
      "Error obtained: 18947951.21042517200\n",
      "Computing S... done!\n",
      "Computing V...\n",
      "  - for cluster 0... done!\n",
      "  - for cluster 1...observations_cluster_i empty!!!!\n",
      "  - for cluster 2... done!\n",
      "  - for cluster 3...observations_cluster_i empty!!!!\n",
      "  - for cluster 4...observations_cluster_i empty!!!!\n",
      "Done computed V!\n",
      "Computing U... done!\n",
      "Error obtained: 8714929.17141235247\n",
      "Computing S... done!\n",
      "Computing V...\n",
      "  - for cluster 0... done!\n",
      "  - for cluster 1... done!\n",
      "  - for cluster 2... done!\n",
      "  - for cluster 3...observations_cluster_i empty!!!!\n",
      "  - for cluster 4...observations_cluster_i empty!!!!\n",
      "Done computed V!\n",
      "Computing U... done!\n",
      "Error obtained: 3235785.45028523915\n",
      "Computing S... done!\n",
      "Computing V...\n",
      "  - for cluster 0... done!\n",
      "  - for cluster 1... done!\n",
      "  - for cluster 2... done!\n",
      "  - for cluster 3...observations_cluster_i empty!!!!\n",
      "  - for cluster 4...observations_cluster_i empty!!!!\n",
      "Done computed V!\n",
      "Computing U... done!\n",
      "Error obtained: 2743711.19908188004\n",
      "Computing S... done!\n",
      "Computing V...\n",
      "  - for cluster 0... done!\n",
      "  - for cluster 1... done!\n",
      "  - for cluster 2... done!\n",
      "  - for cluster 3...observations_cluster_i empty!!!!\n",
      "  - for cluster 4...observations_cluster_i empty!!!!\n",
      "Done computed V!\n",
      "Computing U... done!\n",
      "Error obtained: 2743711.19908188004\n",
      "Time taken: 0.02168900000\n",
      "\n",
      "err: \n",
      "CPU times: user 1.5 ms, sys: 6.23 ms, total: 7.74 ms\n",
      "Wall time: 34.5 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "k = 5\n",
    "l = 2\n",
    "proc = subprocess.Popen(['./algos', 'binovnmtf', str(k), str(l), '100000'],\n",
    "                        stdin = subprocess.PIPE,\n",
    "                        stdout = subprocess.PIPE,\n",
    "                        stderr = subprocess.PIPE)\n",
    "\n",
    "(out, err) = proc.communicate()\n",
    "print 'out:', out\n",
    "print 'err:', err"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "k = 5\n",
    "l = 2\n",
    "U = genfromtxt('U.csv', delimiter=',')\n",
    "S = genfromtxt('S.csv', delimiter=',')\n",
    "R = genfromtxt('Reconstruction.csv', delimiter=',')\n",
    "h5f = h5py.File('V.hdf5','r')\n",
    "V = h5f['dataset'][:]\n",
    "h5f.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5QAAAA+CAYAAABUWVRdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAC3dJREFUeJzt3W2spOVdx/Hvj2W3gLBgW4t2d92DhCaUlF0IViTqNgbN\n2iDoGy0+gSg1sbaLqbYFG4poUk2tLn16YS1Ym5S2waaCqWlpLYumpgXLWbCABfVsWRoWtGVLmyU8\n7N8XM2d3enKemL3Pnplrvp9X87/u+8y54Jede/4z132dVBWSJEmSJL1Qx6z2BCRJkiRJ48mGUpIk\nSZI0FBtKSZIkSdJQbCglSZIkSUOxoZQkSZIkDcWGUpIkSZI0FBtKSZIkSdJQbCglSVqGJAeT/Mic\nseuSfGS15iRJ0mqzoZQkaXi12hOQJGk1ddZQJtme5MEkDyV5a1fPq6MvyaYkX0jy1ST/keRN/fEX\nJ7k9ydeSfDbJKas9Vw0nyZok9yS5rV+bbQOSnJLkliQPJLk/yY+Z7YrLUfklydX91+T7knw0yYvM\ndjwluTHJviT3DYwtmGU/+4f677F+dnVmreVYINt39V+Tdyf5ZJKTB46Z7ZiYL9uBY2/ur2B58cDY\nRGXbSUOZZA3wPmA78Erg0iRndvHcWhXPAr9fVWcB5wNv6Of5NuD2qnoF8Pl+rfG0A7ifw9+umG0b\nbgA+XVVnAmcDD2K2Yy/JFHAlcG5VvQpYA7wOsx1XN9F7vzRo3iyTvBL4ZXrvrbYDH0ji6rLRNV+2\nnwXOqqotwNeAq8Fsx9B82ZJkE/AzwJ6BsYnLtqv/uFcDD1fVTFU9C3wMuKSj59ZRVlWPVdV0//F3\ngAeADcDFwIf7p30Y+IXVmaGORJKNwGuBv+HwtytmO+b6n3r/ZFXdCFBVz1XVfsy2Bd+m90HfCUmO\nBU4AvoHZjqWq+hfgW3OGF8ryEuDmqnq2qmaAh+m959IImi/bqrq9qg72yy8BG/uPzXaMLPDvFuAv\ngbfMGZu4bLtqKDcAjwzUe/tjGnP9T8bPofcieGpV7esf2gecukrT0pH5K+APgYMDY2Y7/k4Dnkhy\nU5KvJPlgku/DbLv0PLB2zthaes3eiqmqbwLvBr5Or5F8sqpux2xbslCWL6f3nmqW76/G2xXAp/uP\nzXbMJbkE2FtV9845NHHZdtVQuilBg5KcCPw9sKOqnho8VlWFuY+dJBcBj1fVPSxw75fZjq1jgXOB\nD1TVucB3mbME0myP2NfpNe6DTgNmVvKXJjkduAqYovdG5cQkvzZ4jtm2YxlZmvMYSvJHwDNV9dFF\nTjPbMZHkBOAa4B2Dw4v8SNPZdtVQPgpsGqg38b2ducZMkrX0msmPVNWn+sP7kvxg//gPAY+v1vw0\ntAuAi5P8D3Az8NP9P3lgtuNvL71PSu/q17fQazAfM9vOfBx4e5INSY5JciFwEb3/1yvpPOCLVfV/\nVfUc8EngxzHbliz0Gjz3/dXG/pjGSJLL6d1q8qsDw2Y73k6n9yHf7v57qo3Avyc5lQnMtquG8m7g\njCRTSdbRuxH11o6eW0dZkgAfAu6vqp0Dh24FLus/vgz41Nyf1WirqmuqalNVnUZvU49/rqpfx2zH\nXlU9BjyS5BX9oQuBrwK3YbZduR74IvCvwDeBPwN+paruX+Hf+yBwfpLj+6/PF9LbVMts27HQa/Ct\nwOuSrEtyGnAG8OVVmJ+GlGQ7vdtMLqmqpwcOme0Yq6r7qurUqjqt/55qL72N0/Yxgdmmt7KigydK\nfg7YSW/3uQ9V1Ts7eWIddUl+ArgTuJfDX9FfTe8fwyeAH6a3xOuXqurJ1ZijjlySbcCbq+ri/lbX\nZjvmkmyht9nSOuC/gN+k95pstmMuyVvoNRoHga8Avw2chNmOnSQ3A9uAl9K7X/Ja4B9YIMsk19C7\n9+45eregfGYVpq1lmCfbd9B7/7SO3odQAP9WVb/bP99sx8RAti+ht4Lg2qq6aeD4fwPn9e95n7hs\nO2soJUmSJEmTpem/iSJJkiRJWjk2lJIkSZKkodhQSpIkSZKGsmRDmWR7kgeTPJTkrUdjUpIkSZKk\n0bfopjxJ1gD/SW+L8keBu4BLq+qBgXPc1UeSJEmSGlZVmW/82CV+7tXAw1U1A5DkY8AlwAODJx14\nttdTXnnF5Xzwxr89wqlqVJlvu8y2XWbblu//0d879PiZPZ9j3eYLV3E2Wilm2y6zbVfr2T49/f4F\njy215HUD8MhAvbc/JkmSJEmacEt9Q7ms5axXXnE5m6em2LNnhvfesJMtW7fyU9teA8Cdu+4AsG6g\n3jw1NVLzse6u3jw1NVLzse62njUq87Eevn7+qUdZc9Lhz3UH6+efehTAuoE669aP1Hysu6uzbv1I\nzce623rWqMznSOqDB56A558BoJ75NotZ6h7K84Hrqmp7v74aOFhVfz5wTs0ueb1z1x2HLnxqj/m2\ny2zbZbZtGVzyOre5VDvMtl1m267Ws316+v1D30N5N3BBkieAfcBzwKUdz0+SpKEMNliT4Ft3ve/Q\nYz8saJfZtsts29V6tsevHfIeyqp6Drge+C5wBvDxwR1eJUmSJEmTa9Elr4dOSqaA26rqVfMcO7Tk\nVZKko2mSv6GUJOloOX5tFlzyutQur5IkSZIkzWupeyiX5dAurzMznL1lq7u8NloP7hg5CvOx7nYX\n0MGMV3s+1t3Vu6eneeOOq0ZmPl3Xk7bL6eA9Ou6q3m7t9bbdenZsVOZj3V3d2vV29/Q0+/c/CcCe\nmRkW0+mS18ELndpjvu0y23a1nu0kL3ltPdtJZrbtMtt2tZ7tYktel2wok2wCPgGcAzwM/HVVvWfg\neB239Q0dTleSpOXxnkJJklbekd5D+R7gdCDAKcDVSc7scH6SJEmSpDG0ZENZVb9YVS+rqhdV1Ubg\nS8DL5zt39n4Ptcl822W27TLbdg3ek6W2mG27zLZdk5ztC9rltX8v5Tn0mkpJkiRJ0gRb9i6vSU4E\nbgF2VNV3Bo89s+dzZN16AA4eeIJjjv+BkdoVz7qbes1JG0ZqPtbW1surZ43KfFZq19NR2BXvaNaz\nY6MyH+vuancBtbYez3rWqMxn1HZ5XQv8I/BPVbVzzjE35ZEkrQo35ZEkaeUd0aY8SY4DvkFvqevr\nk7xzoXO9V6dt5tsus22X2bZrku/XaZ3Ztsts2zXJ2S5nyet5wEuAe4EC3pTkf6vq3bMnzH5C3Prf\nX5l05tsus22X2UqSpJW0rCWvh05OTgB2AZdV1f39sTrw7PKfQ5IkSZI0Po7071CS5Jgk08A+4Auz\nzaQkSZIkaXIta5fXqjoIbE1yMvCZJK+pqjtmj195xeVsnppiz8wMZ2/ZypatW0dqlyLrburBteGj\nMB/rbnclG8x4tedj3V29e3qaN+64amTmY91d/d4bdnq9bbT2ettuPTs2KvOx7q5u7Xq7Eru8rgHu\nBvYCXwYOVNVf9I8dWvJ65647Dk1E7THfdpltu8y2XWbbLrNtl9m2q/VsF1vyumRDmeSlwOuBs4CT\ngfXAH1fV5/vHvYdSkiRJkhq1WEO5nCWvW4G3AY8DLwP+ZLaZlCRJkiRNruVsyvM7wDbgt4BdVfWu\nhU4cXB+u9phvu8y2XWbbLrNtl9m2y2zbNcnZLtpQJrkIeLyq7gHm/Ypz0O7p6a7mpRFkvu0y23aZ\nbbvMtl1m2y6zbdckZ7vUktcLgIuTvBY4Dlif5O+q6jcGT5rd5XW2M3fXuTbr/fufHKn5WHdXz+7i\nNSrzse6uvnf34QvcKMzHurv63t3T37MJxGrPx7q72uttu7XX23br1q63ne/yCpBkG/AHVfXzc8YP\nbcrzp9dfx9uvvW5Zz6fxY77tMtt2mW27zLZdZtsus21X69kutinPcu6hHLRo97lU96rxZr7tMtt2\nmW27zLZdZtsus23XJGe77G8oF3yCxL8ZIkmSJEkNG/rvUEqSJEmSNJ8XuuRVkiRJkiTAhlKSJEmS\nNCQbSkmSJEnSUGwoJUmSJElDsaGUJEmSJA3FhlKSJEmSNBQbSkmSJEnSUP4fX7mFc+NnlooAAAAA\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x107250e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(U.T, cmap=plt.cm.Blues)\n",
    "plt.title('U')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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t+JwiAICJ3fxI/luTfCDJM6rq7qp6+fkf6+jQNfS28rvx7ty93ty9vlY+u+m7kzHGdYcx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\nIgCAJJYiAIAkliIAgCTJ/wIe0u7Cb8rYVQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106853e50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(S.T, cmap=plt.cm.Blues)\n",
    "plt.title('S')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5QAAAArCAYAAAAHQsd1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106d91190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x106837fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
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      "text/plain": [
       "<matplotlib.figure.Figure at 0x106a7b710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5QAAAArCAYAAAAHQsd1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106b98850>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA5QAAAArCAYAAAAHQsd1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niQWlJEmSJGkkvwPV+Rw1IOXyXgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x106d7f4d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for i in xrange(k):\n",
    "    plt.matshow(V[i], cmap=plt.cm.Blues)\n",
    "    plt.title('V[%s]' % i)\n",
    "    plt.grid()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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OBoYCVwB7AEuBT0TEC3XH2SNoEXsEJm+aDQTthgZExFzgwAabjmz3nMaYcvCzBhXVrcr9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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10434a990>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.matshow(R, cmap=plt.cm.Blues)\n",
    "plt.title('recostruction')\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}