machine-learning/04-岭回归算法/岭回归算法.ipynb · Saisimon/AIMindMap

加入 Gitee

与超过 1200万开发者一起发现、参与优秀开源项目，私有仓库也完全免费：）

克隆/下载

岭回归算法.ipynb 527.63 KB

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "创建演示数据："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "# 坐标轴起始点\n",
    "start = 0\n",
    "# 坐标轴结束点\n",
    "end = 6\n",
    "X = np.array([[1, 1], [1, 2], [1, 3], [1, 4], [1, 5]])\n",
    "y = np.array([1598, 3898, 6220, 7799, 10510])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用 Python 实现岭回归实现："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "def ridge(X, y, lambdas=0.1):\n",
    "    \"\"\"\n",
    "    岭回归\n",
    "    args:\n",
    "        X - 训练数据集\n",
    "        y - 目标标签值\n",
    "        lambdas - 惩罚项系数\n",
    "    return:\n",
    "        W - 权重系数\n",
    "    \"\"\"\n",
    "    return np.linalg.inv(X.T.dot(X) + lambdas * np.eye(X.shape[1])).dot(X.T).dot(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算权重系数："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-403.90108909, 2138.99303696])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "W = ridge(X, y, 0.1)\n",
    "W"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "def calcCost(X, y, W):\n",
    "    return np.sum(np.square(X.dot(W) - y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算标准代价值："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "234774.93790272807"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "calcCost(X, y, W)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可视化："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\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 matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['PingFang HK']  # 选择一个本地的支持中文的字体\n",
    "fig, ax = plt.subplots()\n",
    "ax.set_facecolor('#f8f9fa')\n",
    "\n",
    "x1 = X[:][:, 1]\n",
    "y1 = y\n",
    "ax.scatter(x1, y1, marker='o', s=20, c='#e63946')\n",
    "x2 = np.linspace(start, end, 100)\n",
    "y2 = W[1] * x2 + W[0]\n",
    "ax.plot(x2, y2, '#457b9d', label='岭回归, Cost: %f'%(calcCost(X, y, W)))\n",
    "for i in range(len(x1)):\n",
    "    ax.plot(np.linspace(x1[i], x1[i], 100), np.linspace(y1[i], W[1] * x1[i] + W[0], 100), '#219ebc', linestyle='--')\n",
    "ax.set_title('岭回归', color='#264653')\n",
    "ax.set_xlabel('X', color='#264653')\n",
    "ax.set_ylabel('Y', color='#264653')\n",
    "ax.tick_params(labelcolor='#264653')\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用 scikit-learn 拟合："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-403.90108909, 2138.99303696])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import Ridge\n",
    "\n",
    "# 初始化岭回归器\n",
    "reg = Ridge(alpha=0.1, fit_intercept=False)\n",
    "# 拟合线性模型\n",
    "reg.fit(X, y)\n",
    "# 权重系数\n",
    "W = reg.coef_\n",
    "W"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可视化："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\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 matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['PingFang HK']  # 选择一个本地的支持中文的字体\n",
    "fig, ax = plt.subplots()\n",
    "ax.set_facecolor('#f8f9fa')\n",
    "\n",
    "x1 = X[:][:, 1]\n",
    "y1 = y\n",
    "ax.scatter(x1, y1, marker='o', s=20, c='#e63946')\n",
    "x2 = np.linspace(start, end, 100)\n",
    "y2 = W[1] * x2 + W[0]\n",
    "ax.plot(x2, y2, '#457b9d', label='岭回归, Cost: %f'%(calcCost(X, y, W)))\n",
    "for i in range(len(x1)):\n",
    "    ax.plot(np.linspace(x1[i], x1[i], 100), np.linspace(y1[i], W[1] * x1[i] + W[0], 100), '#219ebc', linestyle='--')\n",
    "ax.set_title('岭回归', color='#264653')\n",
    "ax.set_xlabel('X', color='#264653')\n",
    "ax.set_ylabel('Y', color='#264653')\n",
    "ax.tick_params(labelcolor='#264653')\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "λ 对权重系数的影响："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            '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",
       "\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 = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(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 (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.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 = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\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 toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\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",
       "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",
       "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], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.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,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\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",
       "        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.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\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",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\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(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\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(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\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",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\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",
       "        }\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",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\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",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\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, 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",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\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\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"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\";/* global mpl */\n",
       "\n",
       "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 = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\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;\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",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\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.innerHTML =\n",
       "        '<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 / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<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 () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\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",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('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",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\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",
       "\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",
       "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(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\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": [
    "# Author: Fabian Pedregosa -- <fabian.pedregosa@inria.fr>\n",
    "# License: BSD 3 clause\n",
    "# Source: https://scikit-learn.org/stable/auto_examples/linear_model/plot_ridge_path.html\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "from sklearn import linear_model\n",
    "\n",
    "%matplotlib notebook\n",
    "\n",
    "# X is the 10x10 Hilbert matrix\n",
    "X = 1. / (np.arange(1, 11) + np.arange(0, 10)[:, np.newaxis])\n",
    "y = np.ones(10)\n",
    "\n",
    "# #############################################################################\n",
    "# Compute paths\n",
    "\n",
    "n_alphas = 200\n",
    "alphas = np.logspace(-10, -2, n_alphas)\n",
    "\n",
    "coefs = []\n",
    "for a in alphas:\n",
    "    ridge = linear_model.Ridge(alpha=a, fit_intercept=False)\n",
    "    ridge.fit(X, y)\n",
    "    coefs.append(ridge.coef_)\n",
    "\n",
    "# #############################################################################\n",
    "# Display results\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "xdatas, ydatas = [], []\n",
    "lns = []\n",
    "text = plt.text(0.008, 270, '', fontsize=12)\n",
    "for i in range(0, 10):\n",
    "    xdatas.append([])\n",
    "    ydatas.append([])\n",
    "    ln, = ax.plot([], [])\n",
    "    lns.append(ln)\n",
    "\n",
    "def init():\n",
    "    ax.set_xlim(alphas[0] , alphas[len(alphas) - 1])\n",
    "    ax.set_ylim(-200, 300)\n",
    "    ax.set_xscale('log')\n",
    "    ax.set_xlim(ax.get_xlim()[::-1])  # reverse axis\n",
    "    return lns\n",
    "\n",
    "def update(i):\n",
    "    for j in range(0, 10):\n",
    "        xdatas[j].append(alphas[i])\n",
    "        ydatas[j].append(coefs[i][j])\n",
    "        lns[j].set_data(xdatas[j], ydatas[j])\n",
    "    text.set_text(\"λ = %.10f\"%(alphas[i]))\n",
    "    return lns\n",
    "\n",
    "ani = animation.FuncAnimation(fig, update, frames = range(len(alphas) - 1, -1, -1), init_func=init, interval=50, blit=True, repeat=False)\n",
    "# ani.save('ridge.gif')\n",
    "plt.xlabel('λ')\n",
    "plt.ylabel('权重系数')\n",
    "plt.axis('tight')\n",
    "plt.show()"
   ]
  },
  {
   "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": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}

一键复制编辑原始数据按行查看历史

提交于 2021-07-12 09:31 . 更新

Python

https://gitee.com/saisimon/AIMindMap.git

git@gitee.com:saisimon/AIMindMap.git

saisimon

AIMindMap

main

Saisimon / AIMindMap

简介

发行版

贡献者

近期动态

Saisimon / AIMindMap .gitee-modal { width: 500px !important; }

简介

发行版

开源评估指数源自 OSS-Compass 评估体系，评估体系围绕以下三个维度对项目展开评估：

贡献者

近期动态

搜索帮助

Saisimon / AIMindMap