Chapter2/Fig_2_2_KNN.ipynb

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   "outputs": [
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     "output_type": "stream",
     "text": [
      "//anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:36: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 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 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
    {
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width=\"600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import rpy2.robjects as robjects\n",
    "import pandas.rpy.common as com\n",
    "import pandas as pd\n",
    "from rpy2.robjects import pandas2ri\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt  # for scatter plot\n",
    "from ggplot import *\n",
    "from sklearn import neighbors\n",
    "import numpy as np\n",
    "pandas2ri.activate()\n",
    "\n",
    "## load .RData and converts to pd.DataFrame\n",
    "robj    = robjects.r.load(\"/Users/lasiadhi/Dropbox-2/Dropbox/Statistical_Learning/Chapter2/ESL.mixture.rda\")\n",
    "#myRData = com.load_data(robj)\n",
    "\n",
    "for sets in robj:\n",
    "    myRData = com.load_data(sets)\n",
    "\n",
    "# load each table to seperate dataframes\n",
    "marginal= pd.DataFrame(myRData['marginal'])\n",
    "means   = pd.DataFrame(myRData['means'])\n",
    "px1     = pd.DataFrame(myRData['px1'])\n",
    "px2     = pd.DataFrame(myRData['px2'])\n",
    "xnew    = pd.DataFrame(myRData['xnew'])\n",
    "x       = pd.DataFrame(myRData['x'])\n",
    "x.columns = ['x1', 'x2']\n",
    "x.index = x.index - 1\n",
    "\n",
    "y       = pd.DataFrame(myRData['y'])\n",
    "y.columns = ['y']\n",
    "\n",
    "mydata = x.join(y)\n",
    "\n",
    "#KNN\n",
    "knn = neighbors.KNeighborsClassifier(n_neighbors=15)\n",
    "knn.fit(x, y) \n",
    "\n",
    "# Plot the decision boundary. For that, we will asign a color to each\n",
    "# point in the mesh [x_min, m_max]x[y_min, y_max].\n",
    "h = 0.05 #step size in the mesh\n",
    "x_min, x_max = x['x1'].min() - .5, x['x1'].max() + .5\n",
    "y_min, y_max = x['x2'].min() - .5, x['x2'].max() + .5\n",
    "xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))\n",
    "Z = knn.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "\n",
    "# Put the result into a color plot\n",
    "Z = Z.reshape(xx.shape)\n",
    "plt.figure(1, figsize=(6, 4))\n",
    "plt.set_cmap(plt.cm.Paired)\n",
    "plt.pcolormesh(xx, yy, Z)\n",
    "\n",
    "# Plot also the training points\n",
    "#plt.figure(figsize=(9,11))         # initialize figure\n",
    "use_colours = {0: \"blue\", 1: \"orange\"}\n",
    "plt.scatter(mydata['x1'],mydata['x2'], c=[use_colours[i] for i in y['y']], s=40)\n",
    "plt.xlabel(\"X1\")\n",
    "plt.ylabel(\"X2\")\n",
    "plt.title(\"Fig. 2.2: A classification example in 2D (KNN)\")\n",
    "plt.xlim(xx.min(), xx.max())\n",
    "plt.ylim(yy.min(), yy.max())\n",
    "plt.xticks(())\n",
    "plt.yticks(())\n",
    "plt.show()\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
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