Lab_1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Linear Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Real A = -1.65955990594852 | Real B = 44.06489868843162\n",
      "Predicted A = -1.6615288716544503 | Predicted B = 44.18509925680541\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import random\n",
    "# Fixed random\n",
    "np.random.seed(1)\n",
    "random.seed(1)\n",
    "# Amount of points\n",
    "N = 100000\n",
    "# Parameters A from [-10, 10], B from [-100, 100]\n",
    "A = (np.random.sample() - 0.5) * 20\n",
    "B = (np.random.sample() - 0.5) * 200\n",
    "# Initialize X from [-100, 100], Y with uniform distribution from [-30, 30]\n",
    "X = (np.array([random.random() for i in range(N)]) - 0.5) * 200\n",
    "Y = A * X + B + np.random.uniform(-30, 30, N)\n",
    "print('Real A = ' + str(A) + \" | Real B = \" + str(B))\n",
    "\n",
    "# Parameter alpha\n",
    "alpha = 0.0001\n",
    "\n",
    "# Initialize A_0 and B_0\n",
    "A_0 = 0.\n",
    "B_0 = 0.\n",
    "\n",
    "for i in range(N):\n",
    "    error = (A_0 * X[i] + B_0) - Y[i]\n",
    "    B_0 -= alpha * error\n",
    "    A_0 -= alpha * error * X[i]\n",
    "    \n",
    "print('Predicted A = ' + str(A_0) + \" | Predicted B = \" + str(B_0))\n",
    "\n",
    "Y_0 = A_0 * X + B_0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x25abc2c5f60>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(X[0:100], Y[0:100], s=10, color='blue')\n",
    "plt.plot(X[0:100], Y_0[0:100], color='red', linewidth=2, markersize=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x25abc28b9e8>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import random\n",
    "# Fixed random\n",
    "np.random.seed(5)\n",
    "random.seed(5)\n",
    "# Amount of points\n",
    "N = 1000\n",
    "# Parameter alpha\n",
    "Alpha = 0.1\n",
    "# Generating X and Y\n",
    "A_0 = [(np.random.sample() - 0.5) * 20, (np.random.sample() - 0.5) * 20]\n",
    "A = [([np.random.normal(0, 1) * 3 + A_0[0], np.random.normal(0, 2) * 3 + A_0[1]]) for i in range(N)]\n",
    "\n",
    "# Fixed random\n",
    "np.random.seed(2)\n",
    "random.seed(2)\n",
    "B_0 = [(np.random.sample() - 0.5) * 20, (np.random.sample() - 0.5) * 20]\n",
    "B = [([np.random.normal(0, 1.5) * 3 + B_0[0], np.random.normal(0, 1.5) * 3 + B_0[1]]) for i in range(N)]\n",
    "\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(np.transpose(A)[0], np.transpose(A)[1], s=10, color='blue')\n",
    "plt.scatter(np.transpose(B)[0], np.transpose(B)[1], s=10, color='red')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "precision : 0.965\n",
      "recall : 0.946078431372549\n",
      "accuracy : 0.955\n"
     ]
    }
   ],
   "source": [
    "def Sigmoid(Z):\n",
    "    return 1. / (1. + np.exp(-Z))\n",
    "    \n",
    "def Predict(X, W):\n",
    "    X_matrix = np.c_[X, np.ones(X.shape[0])] \n",
    "    Z = np.dot(X_matrix, W)\n",
    "    return [int(i > 0.5) for i in Sigmoid(Z)]\n",
    "\n",
    "A_train = A[0:int(N * 0.8)]\n",
    "B_train = B[0:int(N * 0.8)]\n",
    "A_test = A[int(N * 0.8): None]\n",
    "B_test = B[int(N * 0.8): None]\n",
    "\n",
    "X_train = np.concatenate((A_train, B_train), axis=0)\n",
    "Y_train = np.concatenate((np.array([0] * len(A_train)), np.array([1] * len(B_train))))\n",
    "\n",
    "X_test = np.concatenate((A_test, B_test), axis=0)\n",
    "Y_test = np.concatenate((np.array([0] * len(A_test)), np.array([1] * len(B_test))))\n",
    "\n",
    "def Fit(X, Y):\n",
    "    X_matrix = np.c_[X, np.ones(X.shape[0])]    \n",
    "    W = np.random.rand(X_matrix.shape[1])\n",
    "    M = len(X)\n",
    "    \n",
    "    for i in range(M):\n",
    "        z = np.dot(X_matrix, W) \n",
    "        Y_1 = Sigmoid(z)\n",
    "        W -= Alpha * np.dot(np.transpose(X_matrix),  (Y_1 - Y)) / M\n",
    "            \n",
    "    return W\n",
    "    \n",
    "W = Fit(X_train, Y_train)\n",
    "                        \n",
    "TP = 0\n",
    "TN = 0\n",
    "FP = 0\n",
    "FN = 0\n",
    "                        \n",
    "P = Predict(X_test, W)\n",
    "\n",
    "for i in range(len(P)):\n",
    "    if (P[i] == Y_test[i]):\n",
    "        if (P[i] == 1):\n",
    "            TP += 1\n",
    "        else:\n",
    "            TN += 1\n",
    "    else:\n",
    "        if (P[i] == 1):\n",
    "            FN += 1\n",
    "        else:\n",
    "            FP += 1\n",
    "\n",
    "print(\"precision : \" + str(float(TP) / float(TP + FP)))\n",
    "print(\"recall : \" + str(float(TP) / float(TP + FN)))\n",
    "print(\"accuracy : \" + str(float(TP + TN) / float(TP + TN + FP + FN)))\n",
    "\n",
    "A_ = np.transpose(A_test)\n",
    "B_ = np.transpose(B_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x25abc3282b0>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(A_[0], A_[1], s=10, color='blue')\n",
    "plt.scatter(B_[0], B_[1], s=10, color='red')\n",
    "bord_a = min(np.concatenate([A_[0], B_[0]]))\n",
    "bord_b = max(np.concatenate([A_[0], B_[0]]))\n",
    "plt.plot([bord_a, bord_b], [W[2] - bord_a * W[0] / W[1], W[2] - bord_b * W[0] / W[1]],  color='green', linewidth=2, markersize=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Desicion Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support. ' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import random\n",
    "# Fixed random\n",
    "np.random.seed(7)\n",
    "random.seed(7)\n",
    "# Amount of points\n",
    "N = 1000\n",
    "# Generating X and Y\n",
    "A_0 = [(np.random.sample() - 0.5) * 20, (np.random.sample() - 0.5) * 20]\n",
    "A = [([np.random.normal(0, 3) + A_0[0], np.random.normal(0, 4) + A_0[1]]) for i in range(N)]\n",
    "\n",
    "# Fixed random\n",
    "np.random.seed(2)\n",
    "random.seed(2)\n",
    "B_0 = [(np.random.sample() - 0.5) * 20, (np.random.sample() - 0.5) * 20]\n",
    "B = [([np.random.normal(0, 4) + B_0[0], np.random.normal(0, 3) + B_0[1]]) for i in range(N)]\n",
    "\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.scatter(np.transpose(A)[0], np.transpose(A)[1], s=10, color='blue')\n",
    "plt.scatter(np.transpose(B)[0], np.transpose(B)[1], s=10, color='red')\n",
    "\n",
    "A_train = A[0:int(N * 0.8)]\n",
    "B_train = B[0:int(N * 0.8)]\n",
    "A_test = A[int(N * 0.8): None]\n",
    "B_test = B[int(N * 0.8): None]\n",
    "\n",
    "X_train = np.concatenate((A_train, B_train), axis=0)\n",
    "Y_train = np.concatenate((np.array([0] * len(A_train)), np.array([1] * len(B_train))))\n",
    "\n",
    "X_test = np.concatenate((A_test, B_test), axis=0)\n",
    "Y_test = np.concatenate((np.array([0] * len(A_test)), np.array([1] * len(B_test))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DesicionTreeNode(object):\n",
    "    \n",
    "    def __init__(self, Depth = 0):\n",
    "        self.X = None\n",
    "        self.Y = None\n",
    "        \n",
    "        self.Root = None\n",
    "        self.Left = None\n",
    "        self.Right = None\n",
    "        \n",
    "        self.Samples = None\n",
    "        self.Gain = None        \n",
    "        self.Threshold = None\n",
    "        \n",
    "        self.Depth = Depth\n",
    "        \n",
    "    def Impurity(self, Y):\n",
    "        return (1. - sum([(float(len(Y[Y == y])) / float(Y.shape[0]))**2. for y in np.unique(Y)]))\n",
    "    \n",
    "    def Split(self, X, Y):\n",
    "        # Splitting into left and right nodes\n",
    "        Xleft = X[X[:, self.X] <= self.Threshold]\n",
    "        Yleft = Y[X[:, self.X] <= self.Threshold]\n",
    "        self.Left = DesicionTreeNode(self.Depth + 1)\n",
    "\n",
    "        Xright = X[X[:, self.X] > self.Threshold]\n",
    "        Yright = Y[X[:, self.X] > self.Threshold]\n",
    "        self.Right = DesicionTreeNode(self.Depth + 1)\n",
    "        # Growing both nodes\n",
    "        self.Left.Grow(Xleft, Yleft)\n",
    "        self.Right.Grow(Xright, Yright)\n",
    "    \n",
    "    def Grow(self, X, Y):\n",
    "        self.Samples = X.shape[0] \n",
    "        # If only one Class then we stop recursion\n",
    "        if len(np.unique(Y)) == 1:\n",
    "            self.Y = Y[0]\n",
    "            return\n",
    "        # Initialize variables\n",
    "        MaxGain = 0.\n",
    "        BestX = None\n",
    "        BestThreshold = None\n",
    "        # Take Y, which occurs max amount of time\n",
    "        self.Y = max([(y, len(Y[Y == y])) for y in np.unique(Y)], key = lambda x : x[1])[0]\n",
    "        # Calculating current Impurity\n",
    "        ImpurityCur = self.Impurity(Y)\n",
    "        \n",
    "        for j in range(X.shape[1]):\n",
    "            Xs = (np.unique(X[:, j])[: -1] + np.unique(X[:, j])[1:]) / 2.\n",
    "            # Find max Impurity Gain and take corresponding X and Threshhold\n",
    "            for x in Xs:\n",
    "                Yleft = Y[X[:, j] <= x]\n",
    "                ImpurityLeft = self.Impurity(Yleft)\n",
    "                PercLeft = float(Yleft.shape[0]) / self.Samples\n",
    "\n",
    "                Yright = Y[X[:, j] > x]\n",
    "                ImpurityRight = self.Impurity(Yright)\n",
    "                PercRight = float(Yright.shape[0]) / self.Samples\n",
    "\n",
    "                Gain = ImpurityCur - (PercLeft * ImpurityLeft + PercRight * ImpurityRight)\n",
    "                if Gain > MaxGain:\n",
    "                    MaxGain = Gain\n",
    "                    BestX = j\n",
    "                    BestThreshold = x\n",
    "        # Save best X, Gain and Threshold and split our desicion tree\n",
    "        self.X = BestX\n",
    "        self.Gain = MaxGain\n",
    "        self.Threshold = BestThreshold\n",
    "        self.Split(X, Y)\n",
    "\n",
    "    def Fit(self, X, Y):\n",
    "        # Initialize first node\n",
    "        self.Root = DesicionTreeNode()\n",
    "        # Start recursive growing\n",
    "        self.Root.Grow(X, Y)\n",
    "        print(self.Depth)\n",
    "        self.Root.Cut(self.Depth)\n",
    "\n",
    "    def Predict(self, X):\n",
    "        return np.array([self.Root.RecursiveFall(x) for x in X])\n",
    "\n",
    "    def RecursiveFall(self, x):\n",
    "        if self.X != None:\n",
    "            if x[self.X] <= self.Threshold:\n",
    "                return self.Left.RecursiveFall(x)\n",
    "            else:\n",
    "                return self.Right.RecursiveFall(x)\n",
    "        else: \n",
    "            return self.Y\n",
    "        \n",
    "    def Cut(self, MaxDepth):\n",
    "        # Stop recursive cut\n",
    "        if self.X is None:\n",
    "            return\n",
    "        # We need to go to the furthest nodes to cut them first\n",
    "        self.Left.Cut(MaxDepth)\n",
    "        self.Right.Cut(MaxDepth)   \n",
    "        # Than we cut current node\n",
    "        if self.Depth >= MaxDepth:\n",
    "            self.Left = None\n",
    "            self.Right = None\n",
    "            self.X = None\n",
    "\n",
    "    def Print(self, Suffix = \"\"):\n",
    "        Tab = \"Depth: \" + str(self.Depth) + \"   \" + \"     \" * self.Depth + Suffix\n",
    "        if self.X != None:\n",
    "            print(Tab + \"If X[\" + str(self.X) + \"] <= \" + str(\"{:.2f}\".format(self.Threshold)))\n",
    "            self.Left.Print(\"Then \")\n",
    "            self.Right.Print(\"Else \")\n",
    "        else:\n",
    "            print(Tab + \"Class: \" + str(self.Y) + \", Samples: \" + str(self.Samples))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3\n",
      "Depth: 0   If X[1] <= -2.47\n",
      "Depth: 1        Then If X[1] <= -4.17\n",
      "Depth: 2             Then If X[1] <= -6.72\n",
      "Depth: 3                  Then Class: 1, Samples: 694\n",
      "Depth: 3                  Else Class: 1, Samples: 82\n",
      "Depth: 2             Else If X[0] <= -2.57\n",
      "Depth: 3                  Then Class: 0, Samples: 20\n",
      "Depth: 3                  Else Class: 1, Samples: 16\n",
      "Depth: 1        Else If X[0] <= -2.77\n",
      "Depth: 2             Then If X[1] <= -1.45\n",
      "Depth: 3                  Then Class: 0, Samples: 22\n",
      "Depth: 3                  Else Class: 0, Samples: 744\n",
      "Depth: 2             Else If X[1] <= 1.14\n",
      "Depth: 3                  Then Class: 1, Samples: 4\n",
      "Depth: 3                  Else Class: 0, Samples: 18\n",
      "Accuracy:  0.9925\n"
     ]
    }
   ],
   "source": [
    "Tree = DesicionTreeNode(3)\n",
    "Tree.Fit(X_train, Y_train)\n",
    "Tree.Root.Print()\n",
    "\n",
    "Y = Tree.Predict(X_test)\n",
    "print('Accuracy: ', np.mean(Y == Y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}