Activity 2B - Trajectory analysis of alkanes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "77612d86",
   "metadata": {},
   "source": [
    "# Analysis\n",
    "\n",
    "### Overview\n",
    "In this exercise we will use the MDTraj library to carry out analyses of the MD simulation trajectories that we’ve produced for ethane and butane.  We’ll also use the NGLview library to visualize the trajectories themselves.\n",
    "\n",
    "### A quick reminder/introduction\n",
    "In the previous exercise we generated trajectories (i.e., a time series of atomic coordinates) for two small molecules.  The goal of trajectory analysis is to extract useful (i.e., to a human) information from these time series.  For these molecules we’ll look at bond lengths, angles, and torsion angles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "69c59ede",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bc1ddcb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load in the trajectory using MDTraj\n",
    "import mdtraj as md\n",
    "\n",
    "temperature = \"298.15 K\"\n",
    "pdb_file = \"data/ethane.pdb\"\n",
    "\n",
    "traj = md.load(F'ethane_sim_{temperature}.dcd', top=pdb_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b55a119",
   "metadata": {},
   "source": [
    "### Visualization of Trajectory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "af268ea7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a6ace3feb1fa45f5a642d9d47666c21e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f03cd398d464427791e0b3edc484cd61",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "NGLWidget(max_frame=99999)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import nglview as ngl\n",
    "\n",
    "# Create a view (like creating a plot)\n",
    "\n",
    "view = ngl.NGLWidget()\n",
    "view.add_trajectory(traj)\n",
    "view"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72d1261d",
   "metadata": {},
   "source": [
    "## Analyzing the C-C bond length and H-C-C-H dihedral angle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4eb3082b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>serial</th>\n",
       "      <th>name</th>\n",
       "      <th>element</th>\n",
       "      <th>resSeq</th>\n",
       "      <th>resName</th>\n",
       "      <th>chainID</th>\n",
       "      <th>segmentID</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>C1</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>H11</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>H12</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>H13</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>C2</td>\n",
       "      <td>C</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>H21</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>H22</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>H23</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>ETH</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   serial name element  resSeq resName  chainID segmentID\n",
       "0       1   C1       C       1     ETH        0          \n",
       "1       2  H11       H       1     ETH        0          \n",
       "2       3  H12       H       1     ETH        0          \n",
       "3       4  H13       H       1     ETH        0          \n",
       "4       5   C2       C       1     ETH        0          \n",
       "5       6  H21       H       1     ETH        0          \n",
       "6       7  H22       H       1     ETH        0          \n",
       "7       8  H23       H       1     ETH        0          "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the atom's index of the molecule\n",
    "atoms, bonds = traj.topology.to_dataframe()\n",
    "atoms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b0c4ed2c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[0.1529543 ]\n",
      " [0.15552972]\n",
      " [0.15150344]\n",
      " ...\n",
      " [0.15370475]\n",
      " [0.15199834]\n",
      " [0.156409  ]]\n"
     ]
    }
   ],
   "source": [
    "bond_indices = [0, 4] # atoms to define the bond length\n",
    "\n",
    "# Use mdtraj library to calculate bond length.\n",
    "bond_length = md.compute_distances(traj, [bond_indices])\n",
    "print(bond_length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "aa3b37d7",
   "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_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a figure plotting the bond length\n",
    "bondcounts, binedges, otherstuff = plt.hist(bond_length, bins=120)\n",
    "plt.title('C-C bond length histogram')\n",
    "plt.xlabel('Bond length (nm)')\n",
    "plt.ylabel('Counts')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e326601a",
   "metadata": {},
   "source": [
    "### Exercise - Analyzing the H-C-C-H torsion angle\n",
    "A torsion is made up of four atoms which are bonded to each other. \n",
    "Analyze the torsion angle associated with the atoms H11-C1-C2-H21 for your trajectory. \n",
    "\n",
    "Instead of using the function compute_distance, use **compute_dihedrals**. Create a histogram plot of the torsion angles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "52c431e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-3.0268228]\n",
      " [ 3.1285424]\n",
      " [-2.9077423]\n",
      " ...\n",
      " [ 3.0960937]\n",
      " [ 3.0394037]\n",
      " [ 3.034072 ]]\n"
     ]
    }
   ],
   "source": [
    "### YOUR CODE HERE ###\n",
    "phi_indices =  # atoms to define the torsion angle\n",
    "phi = md.compute_dihedrals(traj, [phi_indices])\n",
    "\n",
    "print(phi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0884ec6c",
   "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_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "### YOUR CODE HERE ###\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3cce52d",
   "metadata": {},
   "source": [
    "## Potential of Mean Force Calculation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d2a344a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efe0af92",
   "metadata": {},
   "source": [
    "### H-C-C-P PMF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f888ef1b",
   "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_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "kB = 8.31446/1000 # Boltzmann constant in kJ/mol\n",
    "Temp = 298.15 # simulation temperature in Kelvin\n",
    "phicounts[phicounts==0] = 0.1 # get rid of any bins with 0 counts/infinite energy\n",
    "pmf = -kB*Temp*np.log(phicounts) # W(x) = -kT*ln[p(x)] = -kT*ln[n(x)] + C\n",
    "pmf = pmf - np.min(pmf) # subtract off minimum value so that energies start from 0\n",
    "\n",
    "phi_bincenters = (phi_binedges[1:] + phi_binedges[:-1])/2 # compute centers of histogram bins\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(phi_bincenters, pmf)\n",
    "plt.title('H-C-C-H torsion pmf')\n",
    "plt.xlabel(r'$\\phi$ (rad)')\n",
    "plt.ylabel('Relative free energy (kJ/mol)')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9afefa9f",
   "metadata": {},
   "source": [
    "When we examine the plot, we can see that the PMF is not smooth near the free energy maxima.\n",
    "\n",
    "To make this smoother, we could:\n",
    "    1. run a longer simulation\n",
    "    or \n",
    "    2. use a smoothing function on our data (from statsmodels.api, as shown below)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eaa63810",
   "metadata": {},
   "source": [
    "### C-C PMF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0df90507",
   "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_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://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",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api as sm\n",
    "\n",
    "bondcounts[bondcounts==0] = 0.1\n",
    "pmf = -kB*Temp*np.log(bondcounts)\n",
    "pmf = pmf - np.min(pmf)\n",
    "\n",
    "bincenters = (binedges[1:] + binedges[:-1])/2\n",
    "\n",
    "pmf_smoothed = sm.nonparametric.lowess(pmf, bincenters, frac=0.05)\n",
    "pmf_s = pmf_smoothed[:,1] - np.min(pmf_smoothed[:,1])\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(bincenters, pmf_s)\n",
    "plt.xlabel('Bond length (nm)')\n",
    "plt.ylabel('Relative free energy (kJ/mol)')\n",
    "plt.title('C-C bond length pmf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edaa7312",
   "metadata": {},
   "source": [
    "Exclude the higher energy bond lengths by subset the part of our data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "9f604084",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(bincenters[pmf_s < 15], pmf_s[pmf_s < 15])\n",
    "plt.xlabel('Bond length (nm)')\n",
    "plt.ylabel('Relative free energy (kJ/mol)')\n",
    "plt.title('C-C bond length pmf')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d25bd5d2",
   "metadata": {},
   "source": [
    "### Summary of this worked example\n",
    "\n",
    "This workflow contains all of the necessary commands to use MDTraj to carry out an analysis of your ethane simulation.\n",
    "As written, it requires the files:\n",
    "* ethane.pdb (topology)\n",
    "* ethane_sim.dcd (trajectory)\n",
    "to be imported to the notebook\n",
    "\n",
    "Briefly, this notebook carried out analyses of: \n",
    "1. The C-C bond length analysis\n",
    "2. The H-C-C-H torsion angle, specifically defined by the atoms H11-C1-C2-H21.  (This specific choice of atoms doesn’t really matter, as the resulting data would be identical for any atoms H1X-C1-C2-H2Y, where X,Y={1,2,3}.  Why?)\n",
    "\n",
    "In both cases we will first construct a histogram of the observable and then convert the histogram counts into a potential of mean force (pmf) that will recast the count data/probabilities as relative free energies."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b71ca30",
   "metadata": {},
   "source": [
    "## YOUR TURN! - Analysis of Butane Trajectory\n",
    "Create a copy of this notebook of ethane trajectory analysis and modify your code to analyze your butane trajectory.\n",
    "\n",
    "1. Read in the files butane.pdb and butane_sim.dcd and visualize using NGLview.\n",
    "2. Analyze the C-C-C-C torsion angle and compute the PMF.\n",
    "3. Analyze the C-C-C bond angle (use either C1-C2-C3 or C2-C3-C4) and compute the PMF.\n",
    "4. Make only a histogram of one of the C-H bond lengths. Pick any C-H pair. What do you notice about the distribution of this bond length?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76972a5e",
   "metadata": {},
   "source": [
    "## Optional Exercises\n",
    "1. Increase the value for integrator.setConstraintTolerance by a couple of orders of magnitude and re-run your butane simulation.  Then see how the C-H bond length distribution changes!\n",
    "2. Try changing the temperature and seeing how that affects simulation results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "262c7d68",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}