Support Vector Machines.ipynb

       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(8, 8))\n",
    "data.plot.scatter(x=\"x\", y=\"y\", c=\"source\", colormap='viridis', ax=ax)\n",
    "ax.set(xlabel=\"x\", ylabel=r\"y\", title=\"\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a376636d",
   "metadata": {},
   "source": [
    "The usage of the scikit-learn interface is very standard, and one does not even need to know the details of how the SVM algorithm operates. It is however important to understand the basics, to understand how it operates.\n",
    "\n",
    "The kernel choice is effectively changing the choice for $\\phi(x)$ in the explanation above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0837b3ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = svm.SVC(kernel=\"linear\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8798f857",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(kernel='linear')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(data.loc[:, [\"x\", \"y\"]], data.loc[:, \"source\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e928f498",
   "metadata": {},
   "source": [
    "Only a few vectors are needed to choose the decision boundary, since only they contribute to the minimum distance shown before. Those vectors are called the support vectors and give the name to the method. They can be accessed using the following attribute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fb5796e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.89928785,  1.61606784],\n",
       "       [ 1.84037763, -2.32486989],\n",
       "       [-0.85012761,  2.07658104],\n",
       "       [ 1.61122172, -0.01876249],\n",
       "       [ 1.07403321,  0.76558405],\n",
       "       [ 0.43013287,  2.43109401],\n",
       "       [ 0.71153203,  1.50870089],\n",
       "       [ 0.06577072,  1.77949588],\n",
       "       [ 0.91708157, -0.55767733],\n",
       "       [ 0.47773916,  1.98320156],\n",
       "       [ 0.59810349,  1.73526173],\n",
       "       [ 1.87216163, -0.44833316],\n",
       "       [ 0.64268313,  1.6935894 ],\n",
       "       [ 0.87829617,  0.46285076],\n",
       "       [ 0.38943866,  2.50118221],\n",
       "       [ 0.53677061,  2.25152824],\n",
       "       [ 1.82660042, -0.74727926],\n",
       "       [ 0.48036068,  1.86553217],\n",
       "       [ 1.07335641, -0.11085592],\n",
       "       [-0.1356701 ,  3.26030995],\n",
       "       [-1.14220795,  1.62584103],\n",
       "       [ 0.62475565,  1.88079418],\n",
       "       [ 0.24008992,  2.36889566],\n",
       "       [ 1.1000249 ,  0.63344773],\n",
       "       [ 1.79081249, -0.55555364],\n",
       "       [ 0.25963498,  2.19522536],\n",
       "       [ 0.51889272,  2.09203194],\n",
       "       [-0.97212198,  1.37607816],\n",
       "       [ 0.45909929,  1.63157132],\n",
       "       [ 1.04817098,  0.55451166],\n",
       "       [ 0.48560402,  1.6224829 ],\n",
       "       [ 2.22717977, -0.99949498],\n",
       "       [ 1.03835295,  0.367851  ],\n",
       "       [-0.86651085,  3.01169281],\n",
       "       [ 0.56361431,  2.03734301],\n",
       "       [ 1.97669747, -1.05778857],\n",
       "       [ 0.16327411,  1.93753657],\n",
       "       [ 0.77428196,  1.58457934],\n",
       "       [ 2.27218539, -1.22831925],\n",
       "       [ 1.08093087, -0.56819249],\n",
       "       [-0.15974512,  1.64246367],\n",
       "       [ 0.96478678,  1.1520126 ],\n",
       "       [ 0.53759381,  2.03858827],\n",
       "       [ 1.18807228,  0.45547861],\n",
       "       [ 1.8365105 , -0.29140191],\n",
       "       [ 0.79957624,  1.76059461],\n",
       "       [ 0.20475928,  2.41247614],\n",
       "       [ 2.10020248, -0.55754422],\n",
       "       [ 0.30463063,  1.78432726],\n",
       "       [ 1.22839638,  0.79236676],\n",
       "       [ 1.00215375,  0.79922968],\n",
       "       [ 1.40221792,  0.26836893],\n",
       "       [ 0.48763803,  1.23830378],\n",
       "       [ 2.52164685,  0.82634304],\n",
       "       [ 1.23250426,  0.86360466],\n",
       "       [ 0.71705271,  1.03992881],\n",
       "       [ 0.57605515,  1.24897513],\n",
       "       [ 0.49619766,  0.92405942],\n",
       "       [ 0.50231277,  0.90332292],\n",
       "       [ 0.50455527,  1.07879308],\n",
       "       [ 0.65138811,  1.38005541],\n",
       "       [ 0.25814932,  1.30653239],\n",
       "       [ 0.74630687,  0.86643677],\n",
       "       [ 0.13615888,  1.55662294],\n",
       "       [ 0.6181835 ,  0.8467661 ],\n",
       "       [ 0.54933302,  1.00859502],\n",
       "       [ 1.04188396,  1.14305184],\n",
       "       [ 1.04538562,  1.43403958],\n",
       "       [ 0.43897389,  0.7340289 ],\n",
       "       [ 0.5150014 ,  0.94374412],\n",
       "       [ 0.63920018,  0.76406757],\n",
       "       [ 0.75274053,  0.50039519],\n",
       "       [ 0.0119005 ,  1.44963954],\n",
       "       [ 0.70260639,  0.87638051],\n",
       "       [ 0.17608685,  1.24928585],\n",
       "       [ 0.45680766,  0.90496486],\n",
       "       [ 0.93662357,  1.14382119],\n",
       "       [ 0.57005431,  0.93968902],\n",
       "       [ 0.37356342,  1.00858314],\n",
       "       [ 1.65400377,  0.72307583],\n",
       "       [ 0.18707016,  1.18492355],\n",
       "       [ 0.68643523,  0.69175251],\n",
       "       [ 0.76929988,  0.95231351],\n",
       "       [ 0.55064555,  1.26084806],\n",
       "       [ 1.1907255 ,  1.11458574],\n",
       "       [ 0.8074369 ,  0.96826258],\n",
       "       [ 0.07631502,  1.49669736],\n",
       "       [ 0.38150452,  0.81388246],\n",
       "       [ 0.81430289,  1.15183828],\n",
       "       [ 1.9930756 ,  1.35720369],\n",
       "       [ 0.44041726,  1.10341311],\n",
       "       [ 1.53124252,  1.01215856],\n",
       "       [ 0.86827844,  1.50258859],\n",
       "       [ 0.39904218,  1.03292531],\n",
       "       [ 0.20662781,  1.15137498],\n",
       "       [ 0.44149257,  0.91728447],\n",
       "       [ 0.19784503,  1.51204837],\n",
       "       [ 1.13155102,  0.97878786],\n",
       "       [ 0.12850521,  1.48109897],\n",
       "       [ 0.63218559,  1.04065258]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.support_vectors_"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b54001fc",
   "metadata": {},
   "source": [
    "We can now predict to which class a new data point belongs to using `clf.predict(new_data_samples)`. It is however interesting to visualize the decision boundary itself.\n",
    "\n",
    "(Taken from https://scikit-learn.org/stable/auto_examples/svm/plot_separating_hyperplane.html#sphx-glr-auto-examples-svm-plot-separating-hyperplane-py -- take a look there for more resources and more examples)\n",
    "\n",
    "The code below also highlights the support vectors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cc8fc1f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",