Noise and error models.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from scipy import signal"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple white noise and random walk (Brownian / Wiener process)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "rng = np.random.default_rng()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = 1000000\n",
    "white_noise = rng.standard_normal(n)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\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",
       "\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",
       "    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": {
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\" width=\"899.6363636363636\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "(-4.0, 4.0)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, (ax0, ax1) = plt.subplots(1, 2, figsize=(9, 4), gridspec_kw={\"width_ratios\":[4, 2]})\n",
    "\n",
    "ax0.plot(white_noise)\n",
    "\n",
    "_ = ax1.hist(white_noise, bins=20)\n",
    "ax1.set_xlim(-4, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "white_noise_rw = np.cumsum(white_noise)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\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",
       "\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",
       "    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"
    },
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width=\"899.6363636363636\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x20fb1d42888>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(9, 4*2))\n",
    "\n",
    "ax0.set_title(\"White Noise\")\n",
    "ax0.plot(white_noise)\n",
    "\n",
    "ax1.set_title(\"Random Walk (Brownian / Wiener Process)\")\n",
    "ax1.plot(white_noise_rw)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\sigma_{rw} \\propto \\sigma \\sqrt{n}$ "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Std white noise: 0.9997185149009024\n",
      "Std white noise RW: 491.2733474948447\n",
      "sqrt(n): 1000.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Std white noise: {white_noise.std()}\")\n",
    "print(f\"Std white noise RW: {white_noise_rw.std()}\")\n",
    "print(f\"sqrt(n): {np.sqrt(n)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Time-dependent white noise and random walk"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "White noise in continous-time may be expressed as:\n",
    "\n",
    "$x\\left(t\\right) = \\sigma \\epsilon\\left(t\\right)$\n",
    "\n",
    "where $\\sigma$ is the process standard deviation and $\\epsilon\\left(t\\right)$ is white noise with unit variance.\n",
    "\n",
    "Discretizion yields:\n",
    "\n",
    "$x_{k} = \\sigma \\epsilon_{k}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It may be tempting to express a random walk as:\n",
    "\n",
    "$\\frac{x\\left(t\\right)}{dt} = \\sigma \\epsilon\\left(t\\right)$\n",
    "\n",
    "However, the proper expression is:\n",
    "\n",
    "$\\frac{x\\left(t\\right)}{dt} = \\sigma \\frac{W\\left(t\\right)}{dt}$\n",
    "\n",
    "where $W\\left(t\\right)$ is the random walk (Brownian / Wiener process) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The subtle difference is best understood when we discretize the SDE (Stochastic differential equation):\n",
    "\n",
    "$\\frac{x\\left(t\\right)}{dt} = \\sigma \\epsilon\\left(t\\right) \\rightarrow \\frac{x_{k+1} - x_{k}}{\\Delta t} = \\sigma \\epsilon_{k} \\rightarrow x_{k+1} = x_{k} + \\sigma {\\Delta t} \\epsilon_{k}$\n",
    "\n",
    "whereas\n",
    "\n",
    "$\\frac{x\\left(t\\right)}{dt} = \\sigma \\frac{W\\left(t\\right)}{dt} \\rightarrow \\frac{x_{k+1} - x_{k}}{\\Delta t} = \\sigma \\frac{W_{k+1} - W_{k}}{\\Delta t} \\rightarrow x_{k+1} = x_{k} + \\sigma \\eta_{k}$\n",
    "\n",
    "where $\\eta_{k} = W_{k+1} - W_{k}$ is i.i.d normal distributed with variance $\\Delta t$\n",
    "\n",
    "Accordingly, the proper discrete model may be expressed as:\n",
    "\n",
    "$x_{k+1} = x_{k} + \\sigma \\sqrt{\\Delta t} \\epsilon_{k}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, note that the random walk standard deviation is defined as $\\sigma_{rw} = \\sigma \\sqrt{\\Delta t}$, which yields:\n",
    "\n",
    "Model 1:\n",
    "\n",
    "$x_{k+1} = x_{k} + \\frac{\\sigma_{rw}}{\\sqrt{\\Delta t}} \\epsilon_{k}$\n",
    "\n",
    "or\n",
    "\n",
    "$x_{k+1} = x_{k} + \\sigma\\Delta t \\epsilon_{k}$\n",
    "\n",
    "Model 2:\n",
    "\n",
    "$x_{k+1} = x_{k} + \\sigma_{rw} \\epsilon_{k}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulate models ($\\frac{x\\left(t\\right)}{dt} = \\sigma \\epsilon\\left(t\\right)$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "duration = 100_000.  # s\n",
    "fs = 40.  # Hz\n",
    "n = int(duration * fs)\n",
    "\n",
    "sigma = 1.\n",
    "t = [0.]\n",
    "x1 = [0.]\n",
    "x2 = [0.]\n",
    "\n",
    "for i in range(n):\n",
    "    t.append(t[-1] + 1./fs)\n",
    "    \n",
    "    eps = rng.standard_normal(1)[0]\n",
    "    \n",
    "    x1.append(x1[-1] + sigma * 1./fs * eps)\n",
    "    x2.append(x2[-1] + sigma * eps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\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",
       "\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",
       "    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>"
      ]
     },
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     "output_type": "display_data"
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\" width=\"899.6363636363636\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x20fec486048>]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(9, 4*2))\n",
    "\n",
    "ax0.set_title(f\"Model 1  - Std: {np.std(x1)}\")\n",
    "ax0.plot(t, x1)\n",
    "\n",
    "ax1.set_title(f\"Model 2  - Std: {np.std(x2)}\")\n",
    "ax1.plot(t, x2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compare the different models by varying the sampling rate. Theoretically, increasing the sampling frequency by factor 4 should increase the random walk standard deviation by factor 2.\n",
    "\n",
    "Model 2 have this property, whereas Model 1 exhibit the opposite trend!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sampling @ 5.0\n",
      "Model 1 std (average): 46.134517594048866\n",
      "Model 2 std (average): 230.6725879702452\n",
      "Sampling @ 10.0\n",
      "Model 1 std (average): 35.74766147446546\n",
      "Model 2 std (average): 357.47661474465195\n",
      "Sampling @ 20.0\n",
      "Model 1 std (average): 24.406218475895777\n",
      "Model 2 std (average): 488.12436951791443\n",
      "Sampling @ 40.0\n",
      "Model 1 std (average): 20.159714393152168\n",
      "Model 2 std (average): 806.3885757260947\n"
     ]
    }
   ],
   "source": [
    "duration = 100_000.  # s\n",
    "sigma = 1.\n",
    "\n",
    "for fs in [5., 10., 20., 40.]:  # Hz\n",
    "    n = int(duration * fs)\n",
    "\n",
    "    x1_std = []\n",
    "    x2_std = []\n",
    "\n",
    "    for j in range(25):\n",
    "        t = [0.]\n",
    "        x1 = [0.]\n",
    "        x2 = [0.]\n",
    "\n",
    "        for i in range(n):\n",
    "            t.append(t[-1] + 1./fs)\n",
    "\n",
    "            eps = rng.standard_normal(1)[0]\n",
    "\n",
    "            x1.append(x1[-1] + sigma * 1./fs * eps)\n",
    "            x2.append(x2[-1] + sigma * eps)\n",
    "\n",
    "        x1_std.append(np.std(x1))\n",
    "        x2_std.append(np.std(x2))\n",
    "\n",
    "    print(f\"Sampling @ {fs}\")\n",
    "    print(f\"Model 1 std (average): {np.mean(x1_std)}\")\n",
    "    print(f\"Model 2 std (average): {np.mean(x2_std)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1st order Gauss-Markov models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1st order Gauss-Markov models may be used to model more \"complicated\" noise and error sources; resamble random walk in short-term, but are bounded in long-term. Typically, 1st order Gauss-Markov models are used to approximate \"flicker\" noise."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In continuous-time, the 1st order Gauss-Markov model is defined as:\n",
    "\n",
    "$\\frac{dx\\left(t\\right)}{dt} = \\beta x\\left(t\\right) + \\epsilon\\left(t\\right)$\n",
    "\n",
    "which is an SDE."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The relation between white noise variance (short-term) and the process (long-term) variance may be expressed as:\n",
    "\n",
    "$\\sigma_{x}^2 = \\frac{\\sigma^2 \\Delta t}{1 - e^{-2\\beta\\Delta t}} = \\frac{\\sigma_{rw}^2}{1 - e^{-2\\beta\\Delta t}}$\n",
    "\n",
    "This relationship is derived directly from AR(1) process, see https://en.wikipedia.org/wiki/Autoregressive_model\n",
    "\n",
    "Accordingly, for the continuous case:\n",
    "\n",
    "$\\lim_{\\Delta t \\to 0} \\sigma_{x}^2 = \\frac{\\sigma^2 \\Delta t}{2\\beta\\Delta t}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1st order Gauss-Markov models can be viewed as short-term random walks which are bound in the long-term. See example below where the 1st order Gauss-Markov can be compared to a random walk."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "duration = 25000.  # s (increase/decrease to see effect of short-/long-term effects)\n",
    "fs = 10.  # Hz\n",
    "n = int(duration * fs)\n",
    "tc = 50.  # low value -> white noise | high value -> random walk (bounded)\n",
    "\n",
    "sigma = 1.\n",
    "t = [0.]\n",
    "x1 = [0.]\n",
    "x2 = [0.]\n",
    "\n",
    "\n",
    "for i in range(n):\n",
    "    t.append(t[-1] + 1./fs)\n",
    "    \n",
    "    eps = rng.standard_normal(1)[0]\n",
    "    \n",
    "    x1.append((1. - 1./(fs*tc)) * x1[-1] + sigma * np.sqrt(1. - np.exp(-2./(fs*tc))) * eps)\n",
    "    x2.append(x2[-1] + sigma * eps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\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",
       "\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",
       "    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": {
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\" width=\"899.6363636363636\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x20fc76c6148>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, (ax0, ax1) = plt.subplots(2, 1, figsize=(9, 4*2), sharex=True)\n",
    "\n",
    "ax0.set_title(f\"Model 1  - Std: {np.std(x1)}\")\n",
    "ax0.plot(t, x1)\n",
    "\n",
    "ax1.set_title(f\"Model 2  - Std: {np.std(x2)}\")\n",
    "ax1.plot(t, x2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1st order Gauss-Markov models can also be used to approximate flicker noise at specific frequencies; the model will transition from white noise to random walk, and in the intermediate region it will resemble flicker noise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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",
       "    if (this.ratio !== 1) {\n",
       "        fig.send_message('set_dpi_ratio', { dpi_ratio: this.ratio });\n",
       "    }\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",
       "    var resizeObserver = new 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 (width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    resizeObserver.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.one(\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",
       "\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",
       "    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": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\users\\ace\\workspace\\noise_error_models\\.venv\\lib\\site-packages\\ipykernel_launcher.py:8: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  \n",
      "c:\\users\\ace\\workspace\\noise_error_models\\.venv\\lib\\site-packages\\ipykernel_launcher.py:9: RuntimeWarning: divide by zero encountered in true_divide\n",
      "  if __name__ == '__main__':\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x20fc7702e08>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f, ps = signal.welch(x1, 10., nperseg=1024*50)\n",
    "\n",
    "plt.figure()\n",
    "plt.loglog(f, ps, label=\"1st order Gauss-Markov\")\n",
    "\n",
    "scale = tc * 2.*np.pi  # arbitrary\n",
    "\n",
    "plt.loglog(f, (1./scale)/f**2, \":\", label=\"Brown (1/f**2)\")\n",
    "plt.loglog(f, 1/f**1, \":\", label=\"Pink (1/f)\")\n",
    "plt.loglog(f, scale/f**0, \":\", label=\"White (C)\")\n",
    "plt.grid()\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}