dafDiscovery_Case I - option 5.ipynb

{
 "cells": [
  {
   "attachments": {
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     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "275d6247",
   "metadata": {},
   "source": [
    "![dafDISCOVERY_icon_small-01-01.png](attachment:dafDISCOVERY_icon_small-01-01.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58bfdc43",
   "metadata": {},
   "source": [
    "# Data Fusion Discovery Pipeline (DAF*discovery*)\n",
    "\n",
    "\n",
    "This is the Jupyter Notebook related to [Paper on: LAABio](https://laabioippn.wordpress.com/) for more information\n",
    "\n",
    "This is a pipeline to merge __previously processed__ data from different (spectral) techniques. \n",
    "\n",
    "- Projects might be orgaized into different folders\n",
    "- Data must be accompanied to a __Metdata__ with a common ID header to index different data from the same sample.\n",
    "\n",
    "Example: \n",
    "\n",
    "Metadata with at least: (1) sample name; (2) NMR code per sample; __Optional:__ (3) MS code per sample; (4) Grouping information; (5) Sample Comment \n",
    "\n",
    "processed NMR data (e.g. MNova, TopSpin) and peak intensities/areas exported to a .CSV file \n",
    "\n",
    "processed MS data (feature list; e.g. MZmine, MSDial) and peak intensities/areas exported to a .CSV file \n",
    "\n",
    "> There are some possibilities to explore: (1) NMR only; (2) NMR + MS; (3) NMR + Bioactivity/Phenotipic data; (4) MS + Bioactivity/Phenotipic data; (5) NMR + MS + Bioactivity/Phenotipic data\n",
    "\n",
    "> 1. When there is only NMR data, the STOCSY calculation should be done as it is.\n",
    "\n",
    "\n",
    "> 2. When there are NMR and MS data, and the \"STOCSY driver\" is chosen from the MS data (a specific feature number), the correlation in the direction of NMR results in a highligthed NMR spectra.\n",
    "\n",
    "> 3. When there are NMR and MS data, and the \"STOCSY driver\" is chosen from the NMR data (a specific chemical shift/peak), the correlation in the direction of MS results in a .CSV table with MS feature number + indexed correlation results.\n",
    "\n",
    "> 4. When there are Bioactivity/Phenotipic data, the \"STOCSY driver\" should always be chosen from this Bioactivity/Phenotipic data and the correlation in the direction of NMR results in a highligthed NMR spectra and/or the correlation in the direction of MS results in a .CSV table with MS feature number + indexed correlation results.\n",
    "\n",
    "\n",
    "Note that the output from (1) NMR data is a color coded spectra modulated by Covariance and Correlations, and (2) MS data is a matrix (2 x X samples) indexed by MS feature list and the correlation results so we can add it into Cytoscape to color code MSMS base Molecular Networks.\n",
    "#### Option 1: NMR + MS + Bioact\n",
    "#### Option 2: NMR + MS\n",
    "#### Option 3: NMR + Bioact\n",
    "#### Option 4: MS + Bioact\n",
    "#### Option 5: NMR only\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5f6823b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dependencies to install and import\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import warnings\n",
    "import matplotlib as plt\n",
    "import matplotlib.pyplot as pltpy\n",
    "plt.rcParams['pdf.fonttype'] = 42 #set up for Acrobat Illustrator manipulation\n",
    "plt.rcParams['ps.fonttype'] = 42  #set up for Acrobat Illustrator manipulation\n",
    "import os\n",
    "import os.path"
   ]
  },
  {
   "attachments": {
    "pipeline2-01.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "d9746e9a",
   "metadata": {},
   "source": [
    "# Import\n",
    "\n",
    "![pipeline2-01.png](attachment:pipeline2-01.png)\n",
    "\n",
    "\n",
    "Import each data already processes. __DAF*discovery*__ does not preprocess data; we assume this part is covered (add REF)\n",
    "\n",
    "__Metadata__ (as .csv) should have 'Samples', 'NMR_filename', 'MS_filename' and/or 'BioAct_filename' as headers\n",
    "\n",
    "This section will get filenames from the __Metadata__ to reorder the actual data exported from the previous processing steps\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "905adbb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set Project and Project path inside your main folder\n",
    "Project = 'CaseI';\n",
    "\n",
    "os.chdir(Project) # navigate to the Project folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "74a9c0e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "You are about to work with NMR data alone. Have a look in what more you could do with additional data. . Go for Option 5\n",
      "Data in Use: ['NMR']\n"
     ]
    }
   ],
   "source": [
    "Metadata = pd.read_csv('Metadata.csv', sep=',',header=0) # Rename the Metadata filename accordingly to your specific case\n",
    "\n",
    "# Set order from Metadata\n",
    "if ('NMR_filename') in Metadata.columns and ('MS_filename') in Metadata.columns and ('BioAct_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist() \n",
    "    Ordered_MS_filename = Metadata['MS_filename'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()\n",
    "    Ordered_BioAct_filename = Metadata['BioAct_filename'].values.tolist()\n",
    "    print('You are about to merge data from: NMR + MS + BioAct. Go for Option 1')\n",
    "    data_inuse = ['NMR', 'MS', 'BioAct']\n",
    "    \n",
    "elif ('NMR_filename') in Metadata.columns and ('MS_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_MS_filename = Metadata['MS_filename'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()  \n",
    "    print('You are about to merge data from: NMR + MS. Go for Option 2')\n",
    "    data_inuse = ['NMR', 'MS']\n",
    "    \n",
    "elif ('NMR_filename') in Metadata.columns and ('BioAct_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()\n",
    "    Ordered_BioAct_filename = Metadata['BioAct_filename'].values.tolist()\n",
    "    print('You are about to merge data from: NMR + BioAct. Go for Option 3')\n",
    "    data_inuse = ['NMR', 'BioAct']\n",
    "\n",
    "elif ('MS_filename') in Metadata.columns and ('BioAct_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_MS_filename = Metadata['MS_filename'].values.tolist()\n",
    "    Ordered_BioAct_filename = Metadata['BioAct_filename'].values.tolist()\n",
    "    print('You are about to merge data from: MS + BioAct. Go for Option 4')\n",
    "    data_inuse = ['MS', 'BioAct'] \n",
    "    \n",
    "elif ('NMR_filename') in Metadata.columns:\n",
    "    Ordered_Samples = Metadata['Samples'].values.tolist()\n",
    "    Ordered_NMR_filename = Metadata['NMR_filename'].values.tolist()    \n",
    "    print('You are about to work with NMR data alone. Have a look in what more you could do with additional data. . Go for Option 5')\n",
    "    data_inuse = ['NMR']\n",
    "\n",
    "    \n",
    "else: print('Error (sorry!), please check your Metadata')\n",
    "\n",
    "print(f'Data in Use: {data_inuse}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f11f5d0",
   "metadata": {},
   "source": [
    "___\n",
    "___\n",
    "## Option 5: NMR only\n",
    "\n",
    "__Use this cell to work 'NMR' data only__. Check [Paper on: Data Integration ADDref](https://pubs.rsc.org/en/content/articlelanding/2019/fd/c8fd00227d) for more information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0eb02a07",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data from NMR is reordered according to the Matadata.\n"
     ]
    }
   ],
   "source": [
    "if data_inuse == ['NMR']:\n",
    "    # NMR\n",
    "    NMR = pd.read_csv('NMR.csv', sep=',',header=0)   # assuming the NMR data was exported and saved as NMR.csv\n",
    "    NMRdata = NMR.drop([\"Unnamed: 0\"], axis=1)\n",
    "    ppm = NMR[\"Unnamed: 0\"]\n",
    "    \n",
    "else: print('Try the next one')\n",
    "\n",
    "# REORDERING data according to the Metadata (Ordered_Samples)\n",
    "\n",
    "NMR = NMR[Ordered_NMR_filename] # reorder columns according to the sampleIDs\n",
    "NMR.rename(columns={i:j for i,j in zip(Ordered_NMR_filename,Ordered_Samples)}, inplace=True) # rename column headers as sampleIDs\n",
    "\n",
    "print('Data from NMR is reordered according to the Matadata.')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f596ef1",
   "metadata": {},
   "source": [
    "### STOCSY calculations\n",
    "\n",
    "Use this cell to apply STOCSY on a given driver peak.\n",
    "\n",
    "The driver peak should be infromed by the user __in line 5__."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "99680cb3",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<img 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\" width=\"1600\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Chose driver to produce highlighted NMR spectra showing highly correlated peaks\n",
    "from STOCSY import *\n",
    "%matplotlib notebook\n",
    "\n",
    "# DRIVER FROM THE NMR DATA\n",
    "driver = 3.97795 # Hippuric_acid\n",
    "\n",
    "corr, covar = STOCSY(driver,NMRdata,ppm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "75a0cd9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Chose driver to produce highlighted NMR spectra showing highly correlated peaks\n",
    "from STOCSY import *\n",
    "%matplotlib notebook\n",
    "\n",
    "# DRIVER FROM THE NMR DATA\n",
    "driver = 2.5372 # citrate\n",
    "\n",
    "corr, covar = STOCSY(driver,NMRdata,ppm)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3df24eae",
   "metadata": {},
   "source": [
    "### REFERENCES\n",
    "\n",
    "Cloarec O et. al. Statistical total correlation spectroscopy: an exploratory approach for latent biomarker identification from metabolic 1H NMR data sets. Analytical Chemistry. 2005. [link](https://pubmed.ncbi.nlm.nih.gov/15732908/)\n",
    "\n",
    "Crockford DJ et. al. Statistical Heterospectroscopy, an Approach to the Integrated Analysis of NMR and UPLC-MS Data Sets:  Application in Metabonomic Toxicology Studies. 2006. [link](https://pubs.acs.org/doi/10.1021/ac051444m)\n",
    "\n",
    "Borges RM et al. Exploring correlations between MS and NMR for compound identification using essential oils: A pilot study. Phytochemical Analysis. 2022. [link](https://pubmed.ncbi.nlm.nih.gov/35098600/)\n",
    "\n",
    "Kuhn S. An integrated approach for mixture analysis using MS and NMR techniques. 2019. [link](https://pubs.rsc.org/en/content/articlelanding/2019/fd/c8fd00227d)"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
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  "toc": {
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