XRD Stacked Plot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "84c7ffd7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import math\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import scipy\n",
    "\n",
    "# Set the path to the foldercontaining text files\n",
    "folder_path = \"C:\\\\Users\\\\w16025698\\\\OneDrive - Northumbria University - Production Azure AD\\\\PhD\\\\Characterisation\\\\XRD\"\n",
    "#####\n",
    "\n",
    "folder_name1 = '230221G'\n",
    "file_name1 = \"230221G_XRD data.xlsx\"\n",
    "file_title1 = file_name1.replace(' data.xlsx', '')\n",
    "df_title1 = '_' + file_title1 + '_df'\n",
    "globals()[df_title1] = pd.read_excel(os.path.join(folder_path, folder_name1, file_name1), sheet_name='raw data')\n",
    "#####\n",
    "folder_name2 = \"230310E\"\n",
    "file_name2 = \"230310E_XRD data.xlsx\"\n",
    "file_title2 = file_name2.replace(' data.xlsx', '')\n",
    "df_title2 = '_' + file_title2 + '_df'\n",
    "globals()[df_title2] = pd.read_excel(os.path.join(folder_path, folder_name2, file_name2), sheet_name='raw data')\n",
    "#####\n",
    "# folder_name3 = \"231005E\"\n",
    "# file_name3 = \"231005Ea_fit.xlsx\"\n",
    "# file_title3 = file_name3.replace('_fit.xlsx', '')\n",
    "# df_title3 = '_' + file_title3 + '_df'\n",
    "# globals()[df_title3] = pd.read_excel(os.path.join(folder_path, folder_name3, file_name3), sheet_name='raw data')\n",
    "#####\n",
    "# folder_name4 = \"231005B\"\n",
    "# file_name4 = \"231005B_fit.xlsx\"\n",
    "# file_title4 = file_name4.replace('.xlsx', '')\n",
    "# df_title4 = '_' + file_title4 + '_df'\n",
    "# globals()[df_title4] = pd.read_excel(os.path.join(folder_path, folder_name4, file_name4), sheet_name='raw data')\n",
    "\n",
    "##### Reference patterns\n",
    "reference_path = 'C:\\\\Users\\\\w16025698\\\\OneDrive - Northumbria University - Production Azure AD\\\\PhD\\\\Characterisation\\\\XRD\\\\XRD ref patterns.xlsx'\n",
    "CZTSe_reference_df = pd.read_excel(reference_path, sheet_name='CZTSe')\n",
    "CZTS_reference_df = pd.read_excel(reference_path, sheet_name='CZTS')\n",
    "MoSe2_reference_df = pd.read_excel(reference_path, sheet_name='MoSe2')\n",
    "Mo_reference_df = pd.read_excel(reference_path, sheet_name='Mo')\n",
    "\n",
    "CZTSe_reference_df = CZTSe_reference_df.rename(columns={CZTSe_reference_df.columns[0]: 'Two Theta', CZTSe_reference_df.columns[1]: 'Intensity'})\n",
    "CZTS_reference_df = CZTS_reference_df.rename(columns={CZTS_reference_df.columns[0]: 'Two Theta', CZTS_reference_df.columns[1]: 'Intensity'})\n",
    "MoSe2_reference_df = MoSe2_reference_df.rename(columns={MoSe2_reference_df.columns[0]: 'Two Theta', MoSe2_reference_df.columns[1]: 'Intensity'})\n",
    "Mo_reference_df = Mo_reference_df.rename(columns={Mo_reference_df.columns[0]: 'Two Theta', Mo_reference_df.columns[1]: 'Intensity'})\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba1a4357",
   "metadata": {},
   "source": [
    "## Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "5be31d42",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(8, 8), gridspec_kw={'height_ratios': [8, 1]})\n",
    "\n",
    "# Plot the sum of curves on the first subplot\n",
    "ax1.plot(globals()[df_title1]['two_theta'], 120 + globals()[df_title1]['normalised intensity'], linewidth=0.8, c='b', alpha=1, label=\"500ml Volume Synthesis\")\n",
    "ax1.plot(globals()[df_title2]['two_theta'], 10+ globals()[df_title2]['normalised intensity'], c='r', linewidth=0.8, alpha=1, label=\"100ml Volume Synthesis\")\n",
    "# ax1.plot(globals()[df_title3]['two_theta'], globals()[df_title3]['base_sub_intensity'], c='g', linewidth=0.5, alpha=1, label=file_title3)\n",
    "# ax1.plot(globals()[df_title4]['two_theta'], globals()[df_title4]['base_sub_intensity'], c='b', linewidth=0.5, alpha=1, label=file_title4)\n",
    "ax1.set_ylabel(\"Offset Intensity (a.u.)\")\n",
    "ax1.set_yticklabels([]) \n",
    "ax1.set_xlim(20,60)\n",
    "ax1.set_ylim(0,230)\n",
    "ax1.xaxis.set_minor_locator(ticker.MultipleLocator(1))\n",
    "ax1.xaxis.set_major_locator(ticker.MultipleLocator(10))\n",
    "ax1.legend()\n",
    "\n",
    "# Plot the XRD reference pattern on the second subplot\n",
    "ax2.vlines(CZTSe_reference_df['Two Theta'], -20, CZTSe_reference_df['Intensity'], colors='b', label='CZTSe Reference Pattern')\n",
    "# ax2.vlines(CZTS_reference_df['Two Theta'], -20, CZTS_reference_df['Intensity'], colors='r', label='CZTS Reference Pattern')\n",
    "ax2.vlines(Mo_reference_df['Two Theta'], -20, Mo_reference_df['Intensity'], colors='y', label='Mo Reference Pattern')\n",
    "# ax2.vlines(MoSe2_reference_df['Two Theta'], -20, MoSe2_reference_df['Intensity'], colors='r', label='MoSe2 Reference Pattern')\n",
    "ax2.set_xlabel(\"2θ (degrees)\")\n",
    "ax2.set_yticks([])\n",
    "ax2.set_ylim(-20,105)\n",
    "ax2.legend(loc='upper right', fontsize='4')\n",
    "\n",
    "# Adjust spacing between subplots and set the height of the reference subplot\n",
    "plt.subplots_adjust(hspace=0.1)\n",
    "plt.tight_layout(rect=[0, 0, 1, 0.9])\n",
    "\n",
    "# Save the plot as an image file\n",
    "file_title = file_title1 + ' ' + file_title2 + ' ' + 'raw_data_sq'\n",
    "plt.savefig(os.path.join(folder_path, 'Stacked plots', file_title + '.png'), dpi=500)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18843b7b",
   "metadata": {},
   "source": [
    "## Broken Axis Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "ae6a4ff2",
   "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",
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       "    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",
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       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
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       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
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       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
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       "            if (entry.contentBoxSize) {\n",
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       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from 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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"999.9999783255842\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(10, 5), gridspec_kw={'height_ratios': [6, 1]})\n",
    "\n",
    "# Plot the sum of curves on the first subplot\n",
    "ax1.plot(globals()[df_title1]['two_theta'], 100 + globals()[df_title1]['normalised intensity']*12, c='b', alpha=0.8, label=\"500ml Volume Synthesis\" )\n",
    "ax1.plot(globals()[df_title2]['two_theta'], globals()[df_title2]['normalised intensity'], c='r', alpha=0.8, label=\"100ml Volume Synthesis\")\n",
    "# ax1.plot(globals()[df_title3]['two_theta'], globals()[df_title3]['base_sub_intensity'], c='g', alpha=0.8, label=file_title3)\n",
    "# ax1.plot(globals()[df_title4]['two_theta'], globals()[df_title4]['base_sub_intensity'], c='b', alpha=0.8, label=file_title4)\n",
    "ax1.set_ylabel(\"Offset Intensity (a.u.)\")\n",
    "ax1.set_yticklabels([]) \n",
    "ax1.set_xlim(20,60)\n",
    "ax1.set_ylim(0,300)\n",
    "ax1.xaxis.set_minor_locator(ticker.MultipleLocator(1))\n",
    "ax1.xaxis.set_major_locator(ticker.MultipleLocator(10))\n",
    "ax1.legend()\n",
    "\n",
    "# Plot the XRD reference pattern on the second subplot\n",
    "# ax2.vlines(CZTSe_reference_df['Two Theta'], -20, CZTSe_reference_df['Intensity'], colors='b', label='CZTSe Reference Pattern')\n",
    "ax2.vlines(CZTS_reference_df['Two Theta'], -20, CZTS_reference_df['Intensity'], colors='r', label='CZTS Reference Pattern')\n",
    "ax2.vlines(Mo_reference_df['Two Theta'], -20, Mo_reference_df['Intensity'], colors='y', label='Mo Reference Pattern')\n",
    "# ax2.vlines(MoSe2_reference_df['Two Theta'], -20, MoSe2_reference_df['Intensity'], colors='r', label='MoSe2 Reference Pattern')\n",
    "ax2.set_xlabel(\"2θ (degrees)\")\n",
    "ax2.set_yticks([])\n",
    "ax2.set_ylim(-20,105)\n",
    "ax2.legend(loc='upper right', fontsize='4')\n",
    "\n",
    "# Adjust spacing between subplots and set the height of the reference subplot\n",
    "plt.subplots_adjust(hspace=0.1)\n",
    "plt.tight_layout(rect=[0, 0, 1, 0.9])\n",
    "\n",
    "# Save the plot as an image file\n",
    "file_title = file_title1 + ' ' + file_title2 + ' ' + 'raw_data'\n",
    "plt.savefig(os.path.join(folder_path, 'Stacked plots', file_title + '.png'), dpi=500)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "26456696",
   "metadata": {},
   "source": [
    "## Normalised Intensity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "5739e2c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from 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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(10, 5), gridspec_kw={'height_ratios': [6, 1]})\n",
    "\n",
    "# Plot the sum of curves on the first subplot\n",
    "ax1.plot(globals()[df_title1]['two_theta'], globals()[df_title1]['normalised_intensity'], c='k', alpha=0.8, label=file_title1)\n",
    "ax1.plot(globals()[df_title2]['two_theta'], globals()[df_title2]['normalised_intensity'], c='r', alpha=0.8, label=file_title2)\n",
    "ax1.plot(globals()[df_title3]['two_theta'], globals()[df_title3]['normalised_intensity'], c='g', alpha=0.8, label=file_title3)\n",
    "# ax1.plot(globals()[df_title4]['two_theta'], globals()[df_title4]['normalised_intensity'], c='b', alpha=0.8, label=file_title4)\n",
    "ax1.set_ylabel(\"Intensity (a.u.)\")\n",
    "ax1.set_yticklabels([]) \n",
    "ax1.set_xlim(10,80)\n",
    "ax1.xaxis.set_minor_locator(ticker.MultipleLocator(1))\n",
    "ax1.xaxis.set_major_locator(ticker.MultipleLocator(10))\n",
    "ax1.legend()\n",
    "\n",
    "# Plot the XRD reference pattern on the second subplot\n",
    "ax2.vlines(CZTSe_reference_df['Two Theta'], 0, CZTSe_reference_df['Intensity'], colors='b', label='CZTSe Reference Pattern')\n",
    "ax2.vlines(CZTS_reference_df['Two Theta'], 0, CZTS_reference_df['Intensity'], colors='y', label='CZTS Reference Pattern')\n",
    "ax2.vlines(Mo_reference_df['Two Theta'], 0, Mo_reference_df['Intensity'], colors='c', label='Mo Reference Pattern')\n",
    "ax2.vlines(MoSe2_reference_df['Two Theta'], 0, MoSe2_reference_df['Intensity'], colors='r', label='MoSe2 Reference Pattern')\n",
    "ax2.set_xlabel(\"2θ (degrees)\")\n",
    "ax2.set_yticks([])\n",
    "ax2.set_ylim(0,105)\n",
    "ax2.legend(loc='upper right', fontsize='4')\n",
    "\n",
    "# Adjust spacing between subplots and set the height of the reference subplot\n",
    "plt.subplots_adjust(hspace=0.1)\n",
    "plt.tight_layout(rect=[0, 0, 1, 0.9])\n",
    "\n",
    "# Save the plot as an image file\n",
    "file_title = file_title1 + ' ' + file_title2 + ' ' + file_title3 + ' ' + 'overlap plot'\n",
    "plt.savefig(os.path.join(folder_path, 'Stacked plots', file_title + '.png'), dpi=500)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7769653",
   "metadata": {},
   "source": [
    "## Offset Intensity Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "e2cddf4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\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",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from 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.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"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.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot\n",
    "fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(10, 5), gridspec_kw={'height_ratios': [6, 1]})\n",
    "\n",
    "# Plot the sum of curves on the first subplot\n",
    "ax1.plot(globals()[df_title1]['two_theta'], globals()[df_title1]['normalised_intensity'], c='k', alpha=0.8, label=file_title1)\n",
    "ax1.plot(globals()[df_title2]['two_theta'], globals()[df_title2]['normalised_intensity']+100 , c='r', alpha=0.8, label=file_title2)\n",
    "ax1.plot(globals()[df_title3]['two_theta'], globals()[df_title3]['normalised_intensity']+200, c='g', alpha=0.8, label=file_title3)\n",
    "# ax1.plot(globals()[df_title4]['two_theta'], globals()[df_title4]['normalised_intensity'], c='b', alpha=0.8, label=file_title4)\n",
    "ax1.set_ylabel(\"Intensity (a.u.)\")\n",
    "ax1.set_yticklabels([]) \n",
    "ax1.set_xlim(10,80)\n",
    "ax1.xaxis.set_minor_locator(ticker.MultipleLocator(1))\n",
    "ax1.xaxis.set_major_locator(ticker.MultipleLocator(10))\n",
    "ax1.legend()\n",
    "\n",
    "# Plot the XRD reference pattern on the second subplot\n",
    "ax2.vlines(CZTSe_reference_df['Two Theta'], 0, CZTSe_reference_df['Intensity'], colors='b', label='CZTSe Reference Pattern')\n",
    "ax2.vlines(CZTS_reference_df['Two Theta'], 0, CZTS_reference_df['Intensity'], colors='y', label='CZTS Reference Pattern')\n",
    "ax2.vlines(Mo_reference_df['Two Theta'], 0, Mo_reference_df['Intensity'], colors='c', label='Mo Reference Pattern')\n",
    "ax2.vlines(MoSe2_reference_df['Two Theta'], 0, MoSe2_reference_df['Intensity'], colors='r', label='MoSe2 Reference Pattern')\n",
    "ax2.set_xlabel(\"2θ (degrees)\")\n",
    "ax2.set_yticks([])\n",
    "ax2.set_ylim(0,105)\n",
    "ax2.legend(loc='upper right', fontsize='4')\n",
    "\n",
    "# Adjust spacing between subplots and set the height of the reference subplot\n",
    "plt.subplots_adjust(hspace=0.1)\n",
    "plt.tight_layout(rect=[0, 0, 1, 0.9])\n",
    "\n",
    "# Save the plot as an image file\n",
    "file_title = file_title1 + ' ' + file_title2 + ' ' + file_title3 + ' ' + 'stackplot'\n",
    "plt.savefig(os.path.join(folder_path, 'Stacked plots', file_title + '.png'), dpi=500)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc3cdae9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}