GCN.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from networkx import to_numpy_matrix\n",
    "import networkx as nx\n",
    "zkc = nx.karate_club_graph()\n",
    "order = sorted(list(zkc.nodes()))\n",
    "A = to_numpy_matrix(zkc, nodelist=order)\n",
    "I = np.eye(zkc.number_of_nodes())\n",
    "A_hat = A + I\n",
    "D_hat = np.array(np.sum(A_hat, axis=0))[0]\n",
    "D_hat = np.matrix(np.diag(D_hat))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_graph(G, weight_name=None):\n",
    "    '''\n",
    "    G: a networkx G\n",
    "    weight_name: name of the attribute for plotting edge weights (if G is weighted)\n",
    "    '''\n",
    "    %matplotlib notebook\n",
    "    import matplotlib.pyplot as plt\n",
    "    \n",
    "    plt.figure()\n",
    "    pos = nx.spring_layout(G)\n",
    "    edges = G.edges()\n",
    "    weights = None\n",
    "    \n",
    "    if weight_name:\n",
    "        weights = [int(G[u][v][weight_name]) for u,v in edges]\n",
    "        labels = nx.get_edge_attributes(G,weight_name)\n",
    "        nx.draw_networkx_edge_labels(G,pos,edge_labels=labels)\n",
    "        nx.draw_networkx(G, pos, edges=edges, width=weights);\n",
    "    else:\n",
    "        nodelist1 = []\n",
    "        nodelist2 = []\n",
    "        for i in range (34):\n",
    "            if zkc.nodes[i]['club'] == 'Mr. Hi':\n",
    "                nodelist1.append(i)\n",
    "            else:\n",
    "                nodelist2.append(i)\n",
    "        #nx.draw_networkx(G, pos, edges=edges);\n",
    "        nx.draw_networkx_nodes(G, pos, nodelist=nodelist1, node_size=300, node_color='r',alpha = 0.8)\n",
    "        nx.draw_networkx_nodes(G, pos, nodelist=nodelist2, node_size=300, node_color='b',alpha = 0.8)\n",
    "        nx.draw_networkx_edges(G, pos, edgelist=edges,alpha =0.4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/caijie/anaconda3/lib/python3.6/site-packages/networkx/drawing/nx_pylab.py:565: MatplotlibDeprecationWarning: isinstance(..., numbers.Number)\n",
      "  if cb.is_numlike(alpha):\n"
     ]
    }
   ],
   "source": [
    "plot_graph(zkc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: array([0.17316725, 0.15485933]),\n",
       " 1: array([0.35673093, 0.1590224 ]),\n",
       " 2: array([0.42606545, 0.18924189]),\n",
       " 3: array([0.11998781, 0.12769139]),\n",
       " 4: array([0.16776708, 0.1854183 ]),\n",
       " 5: array([0.26892449, 0.31716022]),\n",
       " 6: array([0.31187327, 0.34523961]),\n",
       " 7: array([0.10408574, 0.08783403]),\n",
       " 8: array([0.0257537 , 0.06887242]),\n",
       " 9: array([0.4800188 , 0.28067498]),\n",
       " 10: array([0.11716026, 0.23907938]),\n",
       " 11: array([0., 0.]),\n",
       " 12: array([0.       , 0.1409091]),\n",
       " 13: array([0.21382719, 0.13734536]),\n",
       " 14: array([0.26954192, 0.28380868]),\n",
       " 15: array([0.25373006, 0.36027312]),\n",
       " 16: array([0.45463975, 0.45201514]),\n",
       " 17: array([0.04702888, 0.10923464]),\n",
       " 18: array([0.38712661, 0.20017034]),\n",
       " 19: array([0.15388204, 0.16259975]),\n",
       " 20: array([0.15955311, 0.35076651]),\n",
       " 21: array([0.03746532, 0.10339757]),\n",
       " 22: array([0.40088639, 0.38652674]),\n",
       " 23: array([0.65698248, 0.37757668]),\n",
       " 24: array([0.51802199, 0.30623565]),\n",
       " 25: array([0.53926292, 0.38728339]),\n",
       " 26: array([1.17976601, 0.69390964]),\n",
       " 27: array([0.4353924 , 0.28619489]),\n",
       " 28: array([0.47349746, 0.18840298]),\n",
       " 29: array([0.92199488, 0.552983  ]),\n",
       " 30: array([0.        , 0.06906132]),\n",
       " 31: array([0.32223879, 0.22717713]),\n",
       " 32: array([0.58589566, 0.42552769]),\n",
       " 33: array([0.8305983 , 0.48469059])}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "W_1 = np.random.normal(loc=0,scale=1,size=(zkc.number_of_nodes(),4))\n",
    "W_2 = np.random.normal(loc=0,scale=1,size=(W_1.shape[1],2))\n",
    "\n",
    "def relu(x):\n",
    "    return (abs(x)+x)/2\n",
    "\n",
    "def gcn(D_hat,X,A_hat,W):\n",
    "    return relu(D_hat**-1*A_hat*X*W)\n",
    "\n",
    "H_1 = gcn(D_hat,I,A_hat,W_1)\n",
    "H_2 = gcn(D_hat,H_1,A_hat,W_2)\n",
    "output = H_2\n",
    "\n",
    "feature_representations = {\n",
    "    node: np.array(output)[node] \n",
    "    for node in zkc.nodes()}\n",
    "feature_representations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "for i in range (34):\n",
    "    if zkc.nodes[i]['club'] == 'Mr. Hi':\n",
    "        plt.scatter(np.array(output)[i,0],np.array(output)[i,1] ,color = 'b',alpha=0.5,s = 100)\n",
    "    else:\n",
    "        plt.scatter(np.array(output)[i,0],np.array(output)[i,1] ,color = 'r',alpha=0.5,s = 100)\n",
    "#plt.scatter(np.array(output)[:,0],np.array(output)[:,1])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
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