Lesson18

Lesson18.ipynb

{
  "cells": [
    {
      "metadata": {},
      "cell_type": "markdown",
      "source": "## Наука о данных\n### Совместный бакалавриат ВШЭ-РЭШ, 2021-2022 учебный год\n_Илья Щуров_\n\n[Страница курса](http://math-info.hse.ru/s21/j)"
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "afraid-doubt",
      "cell_type": "code",
      "source": "import matplotlib.pyplot as plt\nimport numpy as np\n%matplotlib notebook",
      "execution_count": 2,
      "outputs": []
    },
    {
      "metadata": {
        "scrolled": false,
        "trusted": false
      },
      "id": "interested-surgeon",
      "cell_type": "code",
      "source": "x = np.linspace(-5, 5, 201)\nplt.plot(x, np.sin(x ** 2))",
      "execution_count": 4,
      "outputs": [
        {
          "data": {
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' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.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_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\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\nmpl.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\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.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    rubberband_canvas.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.rubberband_canvas.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.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\nmpl.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\nmpl.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.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\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                img.type = 'image/png';\n            }\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                img\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 https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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 * https://stackoverflow.com/a/24161582/3208463\n */\nfunction 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\nmpl.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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.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\nvar _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\nmpl.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\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\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        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.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\nmpl.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\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.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\nmpl.figure.prototype._key_event_extra = function (event, _name) {\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\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.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.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
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\" width=\"640\">",
            "text/plain": "<IPython.core.display.HTML object>"
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": "[<matplotlib.lines.Line2D at 0x11542a2f0>]"
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "silent-trail",
      "cell_type": "code",
      "source": "fig, ax = plt.subplots()\nax.plot(np.random.rand(10))\n\ndef onclick(event):\n    x = np.linspace(-5, 5)\n    ax.plot(x, event.ydata * np.sin(x))\n    ax.set_xlim(event.xdata-1, event.xdata+1)\n    print('%s click: button=%d, x=%d, y=%d, xdata=%f, ydata=%f' %\n          ('double' if event.dblclick else 'single', event.button,\n           event.x, event.y, event.xdata, event.ydata))\n\ncid = fig.canvas.mpl_connect('button_press_event', onclick)",
      "execution_count": 14,
      "outputs": [
        {
          "data": {
            "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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\nmpl.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_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\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\nmpl.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\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.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    rubberband_canvas.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.rubberband_canvas.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.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\nmpl.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\nmpl.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.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\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                img.type = 'image/png';\n            }\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                img\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 https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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 * https://stackoverflow.com/a/24161582/3208463\n */\nfunction 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\nmpl.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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.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\nvar _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\nmpl.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\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\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        var data = msg['content']['data'];\n        if (data['blob'] !== 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setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.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\nmpl.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\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.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\nmpl.figure.prototype._key_event_extra = function (event, _name) 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\" width=\"640\">",
            "text/plain": "<IPython.core.display.HTML object>"
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "developmental-hollywood",
      "cell_type": "code",
      "source": "cid",
      "execution_count": 9,
      "outputs": [
        {
          "data": {
            "text/plain": "9"
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "sharp-conspiracy",
      "cell_type": "code",
      "source": "from matplotlib import pyplot as plt\n\nclass LineBuilder:\n    def __init__(self, line):\n        self.line = line\n        self.xs = list(line.get_xdata())\n        self.ys = list(line.get_ydata())\n        self.cid = line.figure.canvas.mpl_connect('button_press_event', self)\n\n    def __call__(self, event):\n        print('click', event)\n        if event.inaxes!=self.line.axes: return\n        self.xs.append(event.xdata)\n        self.ys.append(event.ydata)\n        self.line.set_data(self.xs, self.ys)\n        self.line.figure.canvas.draw()\n\nfig, ax = plt.subplots()\nax.set_title('click to build line segments')\nline, = ax.plot([0], [0])  # empty line\nlinebuilder = LineBuilder(line)\n\nplt.show()",
      "execution_count": 10,
      "outputs": [
        {
          "data": {
            "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.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\nmpl.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_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\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\nmpl.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\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.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    rubberband_canvas.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.rubberband_canvas.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.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\nmpl.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\nmpl.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.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\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                img.type = 'image/png';\n            }\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                img\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 https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.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 * https://stackoverflow.com/a/24161582/3208463\n */\nfunction 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\nmpl.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\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.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\nmpl.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\nvar _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\nmpl.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\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar 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.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\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        var data = msg['content']['data'];\n        if (data['blob'] !== 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setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.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\nmpl.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\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.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\nmpl.figure.prototype._key_event_extra = function (event, _name) 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\" width=\"640\">",
            "text/plain": "<IPython.core.display.HTML object>"
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "normal-cemetery",
      "cell_type": "code",
      "source": "%pip install --upgrade plotly",
      "execution_count": 15,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": "Requirement already satisfied: plotly in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (5.6.0)\nRequirement already satisfied: tenacity>=6.2.0 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly) (8.0.1)\nRequirement already satisfied: six in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly) (1.16.0)\nNote: you may need to restart the kernel to use updated packages.\n"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "criminal-suicide",
      "cell_type": "code",
      "source": "%pip install --upgrade plotly_express",
      "execution_count": 16,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": "Collecting plotly_express\n  Downloading plotly_express-0.4.1-py2.py3-none-any.whl (2.9 kB)\nRequirement already satisfied: statsmodels>=0.9.0 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly_express) (0.13.1)\nRequirement already satisfied: plotly>=4.1.0 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly_express) (5.6.0)\nRequirement already satisfied: pandas>=0.20.0 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly_express) (1.3.4)\nRequirement already satisfied: scipy>=0.18 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly_express) (1.7.3)\nRequirement already satisfied: numpy>=1.11 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly_express) (1.21.4)\nRequirement already satisfied: patsy>=0.5 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly_express) (0.5.2)\nRequirement already satisfied: python-dateutil>=2.7.3 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from pandas>=0.20.0->plotly_express) (2.8.2)\nRequirement already satisfied: pytz>=2017.3 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from pandas>=0.20.0->plotly_express) (2021.3)\nRequirement already satisfied: six in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from patsy>=0.5->plotly_express) (1.16.0)\nRequirement already satisfied: tenacity>=6.2.0 in /Users/user/miniconda3/envs/py3.10/lib/python3.10/site-packages (from plotly>=4.1.0->plotly_express) (8.0.1)\nInstalling collected packages: plotly-express\nSuccessfully installed plotly-express-0.4.1\nNote: you may need to restart the kernel to use updated packages.\n"
        }
      ]
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "raised-terminal",
      "cell_type": "code",
      "source": "from plotly.graph_objects import Figure, Surface, Scatter, Scatter3d",
      "execution_count": 17,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "physical-twist",
      "cell_type": "code",
      "source": "x, y, z = np.random.multivariate_normal(np.array([1, 2, 3]),\n                                  np.array([[2, 1, 0],\n                                            [1, 1, 0.3],\n                                            [0, 0.3, 1]\n                                            ]\n                                           ), size=500).T",
      "execution_count": 33,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": false
      },
      "id": "annoying-defeat",
      "cell_type": "code",
      "source": "Figure([Scatter3d(x=x, y=y, z=z, mode='markers'),\n       Scatter3d(x=x, y=y, z=z**2, mode='markers')]\n       )",
      "execution_count": 36,
      "outputs": [
        {
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                "plotlyServerURL": "https://plot.ly"
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      "source": "x = np.linspace(-3, 3, 101)\ny = np.linspace(-3, 3, 101)\nx, y = np.meshgrid(x, y)\nFigure(Surface(x=x, y=y, z=np.sin(x ** 2 + y ** 2)))",
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