notebooks/introduction.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from math import pi\n",
    "from spatialmath import *\n",
    "\n",
    "import ipywidgets as widgets\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib notebook\n",
    "%matplotlib notebook\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working in 3D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rotation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rotations in 3D can be represented by rotation matrices – 3x3 orthonormal matrices – which belong to the group $\\mbox{SO}(3)$. These are a subset of all possible 3x3 real matrices.\n",
    "\n",
    "We can create such a matrix, a rotation of $\\pi/4$ radians around the x-axis by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "R1 = SO3.Rx(pi/4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which is an object of type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "spatialmath.pose3d.SO3"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(R1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which contains an $\\mbox{SO}(3)$ matrix. We can display that matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which is colored red if the console supports color.\n",
    "\n",
    "The matrix, a numpy array, is encapsulated and not directly settable by the user. This way we can ensure that the matrix is proper member of the $\\mbox{SO}(3)$ group.\n",
    "\n",
    "We can _compose_ these rotations using the Python `*` operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m-1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R1 * R1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which is a rotation by $\\pi/4$ _then_ another rotation by $\\pi/4$ which is a total rotation of $\\pi/2$ about the X-axis.  We can doublecheck that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m-1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3.Rx(pi/2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could also have used the exponentiation operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m-1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R1**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also specify the angle in degrees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3.Rx(45, 'deg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visualize what this looks like by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
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       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure() # create a new figure\n",
    "SE3().plot(frame='0', dims=[-1.5,1.5], color='black')\n",
    "R1.plot(frame='1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Click on the coordinate frame and use the mouse to change the viewpoint.  The world reference frame is shown in black, and the rotated frame is shown in blue."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Often we need to describe more complex orientations and we typically use a _3 angle_ convention to do this.  Euler's rotation theorem says that any orientation can be expressed in terms of three rotations about different axes.  \n",
    "\n",
    "One common convention is roll-pitch-yaw angles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.8138  \u001b[0m \u001b[38;5;1m-0.441   \u001b[0m \u001b[38;5;1m 0.3785  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.4698  \u001b[0m \u001b[38;5;1m 0.8826  \u001b[0m \u001b[38;5;1m 0.01803 \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.342   \u001b[0m \u001b[38;5;1m 0.1632  \u001b[0m \u001b[38;5;1m 0.9254  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R2 = SO3.RPY([10, 20, 30], unit='deg')\n",
    "R2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which says that we rotate by 30&deg; about the Z-axis (yaw), _then_ 20&deg; about the Y-axis (pitch) and _then_ 10&deg; about the X-axis – this is the ZYX roll-pitch yaw convention.  Note that:\n",
    "\n",
    "1. the first rotation in the sequence involves the last element in the angle sequence.\n",
    "2. we can change angle convention, for example by passing `order='xyz'`\n",
    "\n",
    "We can visualize the resulting orientation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure() # create a new figure\n",
    "SE3().plot(frame='0', dims=[-1.5,1.5], color='black')\n",
    "R2.plot(frame='2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can convert any rotation matrix back to its 3-angle representation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.17453293, 0.34906585, 0.52359878])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R2.rpy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Constructors\n",
    "\n",
    "The default constructor yields a null rotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which is represented by the identity matrix.\n",
    "\n",
    "The class supports a number of variant constructors using class methods:\n",
    "\n",
    "| Constructor   |  rotation |\n",
    "|---------------|-----------|\n",
    "| SO3()          | null rotation |\n",
    "| SO3.Rx(theta)  |  about X-axis |\n",
    "| SO3.Ry(theta)  |  about Y-axis|\n",
    "| SO3.Rz(theta)  |  about Z-axis|\n",
    "| SO3.RPY(rpy)  |  from roll-pitch-yaw angle vector|\n",
    "| SO3.Eul(euler)  | from Euler angle vector |\n",
    "| SO3.AngVec(theta, v)  | from rotation and axis |\n",
    "| SO3.Omega(v)  | from a twist vector |\n",
    "| SO3.OA  | from orientation and approach vectors |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Imagine we want a rotation that describes a frame that has its y-axis (o-vector) pointing in the world negative z-axis direction and its z-axis (a-vector) pointing in the world x-axis direction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m-1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3.OA(o=[0,0,-1], a=[1,0,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can redo our earlier example using `SO3.Rx()` with the explicit angle-axis notation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3.AngVec(pi/4, [1,0,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3.Exp([pi/4,0,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or a more complex example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.8756  \u001b[0m \u001b[38;5;1m-0.3818  \u001b[0m \u001b[38;5;1m 0.296   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.42    \u001b[0m \u001b[38;5;1m 0.9043  \u001b[0m \u001b[38;5;1m-0.07621 \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.2386  \u001b[0m \u001b[38;5;1m 0.191   \u001b[0m \u001b[38;5;1m 0.9522  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3.AngVec(30, [1,2,3], unit='deg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Properties\n",
    "\n",
    "The object has a number of properties, such as the columns which are often written as ${\\bf R} = [n, o, a]$ where $n$, $o$ and $a$ are 3-vectors.  For example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 0., 0.])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R1.n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or its inverse (in this case its transpose)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R1.inv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the shape of the underlying matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 3)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R1.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and the order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R1.N"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "indicating it operates in 3D space."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predicates\n",
    "\n",
    "We can check various properties of the object using properties and methods that are common to all classes in this package"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[False, True, True, False, False, False]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[R1.isSE, R1.isSO, R1.isrot(), R1.ishom(), R1.isrot2(), R1.ishom2()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last four in this list provide compatibility with the Spatial Math Toolbox for MATLAB."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Quaternions\n",
    "\n",
    "A quaternion is often described as a type of complex number but it is more useful (and simpler) to think of it as an order pair comprising a scalar and a vector.  We can create a quaternions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1.0000 <  2.0000,  3.0000,  4.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 = Quaternion([1,2,3,4])\n",
    "q1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "where the scalar is before the angle brackets which enclose the vector part.  \n",
    "\n",
    "Properties allow us to extract the scalar part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.s"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and the vector part"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2, 3, 4])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and we can represent it as a numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.vec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A quaternion has a conjugate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 1.0000 < -2.0000, -3.0000, -4.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.conj()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and a norm, which is the magnitude of the equivalent 4-vector "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.477225575051661"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.norm()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can create a second quaternion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 5.0000 <  6.0000,  7.0000,  8.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q2 = Quaternion([5,6,7,8])\n",
    "q2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Operators allow us to add"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 6.0000 <  8.0000,  10.0000,  12.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 + q2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "subtract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-4.0000 < -4.0000, -4.0000, -4.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 - q2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and to multiply"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-60.0000 <  12.0000,  30.0000,  24.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 * q2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which follows the special rules of Hamilton multiplication.\n",
    "\n",
    "Multiplication can also be performed as the linear algebraic product of one quaternion converted to a 4x4 matrix  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1., -2., -3., -4.],\n",
       "       [ 2.,  1., -4.,  3.],\n",
       "       [ 3.,  4.,  1., -2.],\n",
       "       [ 4., -3.,  2.,  1.]])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and the other as a 4-vector "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-60.,  12.,  30.,  24.])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.matrix @ q2.vec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The product of a quaternion and its conjugate is a scalar equal to the square of its norm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 30.0000 <  0.0000,  0.0000,  0.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 * q1.conj()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conversely, a quaternion with a zero scalar part is called a _pure quaternion_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.0000 <  1.0000,  2.0000,  3.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Quaternion.Pure([1, 2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Unit quaternions\n",
    "\n",
    "A quaternion with a unit norm is called a _unit quaternion_ .  It is a group and its elements represent rotation in 3D space.  It is in all regards like an $\\mbox{SO}(3)$ matrix except for a _double mapping_ -- a quaternion and its element-wise negation represent the same rotation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9659 <<  0.2588,  0.0000,  0.0000 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 = UnitQuaternion.Rx(30, 'deg')\n",
    "q1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "the convention is that unit quaternions are denoted using double angle brackets.  The norm, as advertised is indeed one"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.norm()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We create another unit quaternion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9397 <<  0.0000, -0.3420,  0.0000 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q2 = UnitQuaternion.Ry(-40, 'deg')\n",
    "q2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The rotations can be composed by quaternion multiplication"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9077 <<  0.2432, -0.3304, -0.0885 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q3 = q1 * q2\n",
    "q3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can convert a quaternion to a rotation matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 7.66044443e-01, -2.77555756e-17, -6.42787610e-01],\n",
       "       [-3.21393805e-01,  8.66025404e-01, -3.83022222e-01],\n",
       "       [ 5.56670399e-01,  5.00000000e-01,  6.63413948e-01]])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q3.R"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which yields exactly the same answer as if we'd done it using SO(3) rotation matrices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.766   \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m-0.6428  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.3214  \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;1m-0.383   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.5567  \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;1m 0.6634  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO3.Rx(30, 'deg') * SO3.Ry(-40, 'deg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The advantages of unit quaternions are that\n",
    "\n",
    "1. they are compact, just 4 numbers instead of 9\n",
    "2. multiplication involves fewer operations and is therefore faster\n",
    "3. numerical errors build up when we multiply rotation matrices together many times, and they lose the structure (the columns are no longer unit length or orthogonal).  Correcting this, the process of _normalization_ is expensive.  For unit quaternions errors will also compound, but normalization is simply a matter of dividing through by the norm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unit quaternions have an inverse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9397 << -0.0000,  0.3420, -0.0000 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q2.inv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9077 <<  0.2432,  0.3304,  0.0885 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 * q2.inv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9077 <<  0.2432,  0.3304,  0.0885 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1 / q2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can convert any unit quaternion to an SO3 object if we wish"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;1m-0.5     \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.SO3()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and conversely, any `SO3` object to a unit quaternion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9659 <<  0.2588,  0.0000,  0.0000 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "UnitQuaternion( SO3.Rx(30, 'deg'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A unit quaternion is not a minimal representation. Since we know the magnitude is 1, then with any 3 elements we can compute the fourth upto a sign ambiguity. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.25881905, 0.        , 0.        ])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q1.vec3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.24321035, -0.33036609, -0.08852133])"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = UnitQuaternion.qvmul( q1.vec3, q2.vec3)\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "from which we can recreate the unit quaternion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0.9077 <<  0.2432, -0.3304, -0.0885 >>\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "UnitQuaternion.Vec3(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Representing position\n",
    "\n",
    "In robotics we also need to describe the position of objects and we can do this with a _homogeneous transformation_ matrix – a 4x4 matrix – which belong to the group $\\mbox{SE}(3)$ which is a subset of all 4x4 real matrices.\n",
    "\n",
    "We can create such a matrix, for a translation of 1 in the x-direction, 2 in the y-direction and 3 in the z-direction by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 2       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 3       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1 = SE3(1, 2, 3)\n",
    "T1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which is displayed in a color coded fashion: rotation matrix in red, translation vector in blue, and the constant bottom row in grey.  We note that the red matrix is an _identity matrix_ ."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The class supports a number of variant constructors using class methods.\n",
    "\n",
    "| Constructor   |  motion |\n",
    "|---------------|-----------|\n",
    "| SE3()      | null motion |\n",
    "| SE3.Tx(d)  |  translation along X-axis |\n",
    "| SE3.Ty(d)  |  translation along Y-axis |\n",
    "| SE3.Tz(d)  |  translation along Z-axis |\n",
    "| SE3.Rx(theta)  |  rotation about X-axis |\n",
    "| SE3.Ry(theta)  |  rotation about Y-axis|\n",
    "| SE3.Rz(theta)  |  rotation about Z-axis|\n",
    "| SE3.RPY(rpy)  |  rotation from roll-pitch-yaw angle vector|\n",
    "| SE3.Eul(euler)  | rotation from Euler angle vector |\n",
    "| SE3.AngVec(theta, v)  | rotation from rotation and axis |\n",
    "| SO3.Omega(v)  | from a twist vector |\n",
    "| SE3.OA(ovec, avec)  | rotation from orientation and approach vectors |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can visualize this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure() # create a new figure\n",
    "SE3().plot(frame='0', dims=[0,4], color='black')\n",
    "T1.plot(frame='1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can define another translation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "T12 = SE3(2, -1, -2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and compose it with `T1`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "T2 = T1 * T12"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "T2.plot(frame='2', color='red')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Representing pose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;1m-0.5     \u001b[0m \u001b[38;5;4m 2       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;4m 3       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1 = SE3(1, 2, 3) * SE3.Rx(30, 'deg')\n",
    "T1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Is a composition of two motions: a pure translation and _then_ a pure rotation.  We can see the rotation matrix, computed above, in the top-left corner and the translation components in the right-most column.  In the earlier example `Out[24]` was simply a null-rotation which is represented by the identity matrix.\n",
    "\n",
    "The frame now looks like this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure() # create a new figure\n",
    "SE3().plot(frame='0', dims=[0,4], color='black')\n",
    "T1.plot(frame='1')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Properties\n",
    "\n",
    "The object has a number of properties, such as the columns which are often written as $[n, o, a]$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.       , 0.8660254, 0.5      ])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1.o"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or its inverse (computed in an efficient manner based on the structure of the matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m-1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;4m-3.232   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m-0.5     \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;4m-1.598   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1.inv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can extract the rotation matrix as a numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.       ,  0.       ,  0.       ],\n",
       "       [ 0.       ,  0.8660254, -0.5      ],\n",
       "       [ 0.       ,  0.5      ,  0.8660254]])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1.R"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or the translation vector, as a numpy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 2., 3.])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1.t"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The shape of the underlying SE(3) matrix is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 4)"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and the order"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1.N"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "indicating it operates in 3D space."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predicates\n",
    "\n",
    "We can check various properties"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[True, False, False, True, False, False]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[T1.isSE, T1.isSO, T1.isrot(), T1.ishom(), T1.isrot2(), T1.ishom2()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A couple of important points:\n",
    "\n",
    "When we compose motions they must be of the same type.  An `SE3` object can represent pure transation, pure rotation or both.  If we wish to compose a translation with a rotation, the rotation must be an `SE3` object - a rotation plus zero translation.\n",
    "\n",
    "SUperset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transforming points"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Imagine now a set of points defining the vertices of a cube"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1,  1,  1, -1, -1,  1,  1, -1],\n",
       "       [-1, -1,  1,  1, -1, -1,  1,  1],\n",
       "       [-1, -1, -1, -1,  1,  1,  1,  1]])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P = np.array([[-1, 1, 1, -1, -1, 1, 1, -1], [-1, -1, 1, 1, -1, -1, 1, 1], [-1, -1, -1, -1, 1, 1, 1, 1]])\n",
    "P"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "defined with respect to a body reference frame ${}^A P_i$.  Given a transformation ${}^0 \\mathbf{T}_A$ from the world frame to the body frame, we determine the coordinates of the points in the world frame by ${}^0 P_i = {}^0 \\mathbf{T}_A \\, {}^A P_i$ which we can perform in a single operation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "Q = T1 * P"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which we can now plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "SE3().plot(frame='0', dims=[-2,3,0,5,0,5], color='black')\n",
    "ax = plt.gca()\n",
    "ax.set_xlabel('X'); ax.set_ylabel('Y'); ax.set_zlabel('Z');\n",
    "ax.scatter(xs=Q[0], ys=Q[1], zs=Q[2], s=20)  # draw vertices\n",
    "\n",
    "# draw lines joining the vertices\n",
    "lines = [[0,1,5,6], [1,2,6,7], [2,3,7,4], [3,0,4,5]]\n",
    "for line in lines:\n",
    "    ax.plot([Q[0,i] for i in line], [Q[1,i] for i in line], [Q[2,i] for i in line])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is often used in SLAM and bundle adjustment algorithms since it is compact and better behaved than using roll-pitch-yaw or Euler angles."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Twists\n",
    "A twist is an alternative way to represent a 3D pose, but it is more succinct, comprising just 6 values.  In constrast an SE(3) matrix has 16 values with a considerable amount of redundancy, but it does offer consider computational convenience.\n",
    "\n",
    "Twists are the logarithm of an SE(3) matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m-0.6324  \u001b[0m \u001b[38;5;1m-0.7406  \u001b[0m \u001b[38;5;1m-0.2271  \u001b[0m \u001b[38;5;4m-0.04585 \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.7672  \u001b[0m \u001b[38;5;1m 0.5583  \u001b[0m \u001b[38;5;1m 0.3156  \u001b[0m \u001b[38;5;4m 0.7525  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.1069  \u001b[0m \u001b[38;5;1m 0.3739  \u001b[0m \u001b[38;5;1m-0.9213  \u001b[0m \u001b[38;5;4m-0.1349  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T = SE3.Rand()\n",
    "T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.        ,  0.60099592, -2.7124978 , -0.67791998],\n",
       "       [-0.60099592,  0.        , -1.31423621,  0.48676492],\n",
       "       [ 2.7124978 ,  1.31423621,  0.        , -0.31757507],\n",
       "       [ 0.        ,  0.        ,  0.        ,  0.        ]])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T.log()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How do we know this is really the logarithm? Well, we can exponentiate it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m-0.6324  \u001b[0m \u001b[38;5;1m-0.7406  \u001b[0m \u001b[38;5;1m-0.2271  \u001b[0m \u001b[38;5;4m-0.04585 \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.7672  \u001b[0m \u001b[38;5;1m 0.5583  \u001b[0m \u001b[38;5;1m 0.3156  \u001b[0m \u001b[38;5;4m 0.7525  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.1069  \u001b[0m \u001b[38;5;1m 0.3739  \u001b[0m \u001b[38;5;1m-0.9213  \u001b[0m \u001b[38;5;4m-0.1349  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lg = T.log()\n",
    "SE3.Exp(lg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and we have reconstituted our original matrix. \n",
    "\n",
    "The logarithm is a matrix with a very particular structure, it has a zero diagonal and bottom row, and the top-left 3x3 matrix is skew symmetric.  This matrix has only 6 unique elements: three from the last column, and three from the skew symmetric matrix, and we can request the `log` method to give us just these"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.67791998,  0.48676492, -0.31757507,  1.31423621, -2.7124978 ,\n",
       "       -0.60099592])"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T.log(twist=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This 6-vector is a twist, a concise way to represent the translational and rotational components of a pose. Twists are represented by their own class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.67792 0.48676 -0.31758; 1.3142 -2.7125 -0.601)"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tw = Twist3(T)\n",
    "tw"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just like the other pose objects, `Twist3` objects can have multiple values.\n",
    "\n",
    "Twists can be composed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1 2.435 2.6775; 0.3 0 0)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T = SE3(1, 2, 3) * SE3.Rx(0.3)\n",
    "tw = Twist3(T)\n",
    "tw"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can compose the twists"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2 4.87 5.3549; 0.6 0 0)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tw2 = tw * tw\n",
    "tw2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and the result is just the same as if we had composed the transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2 4.87 5.3549; 0.6 0 0)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Twist3(T * T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Twists have great utility for robot arm kinematics, to compute the forward kinematics and Jacobians.  Twist objects have a number of methods.\n",
    "\n",
    "The adjoint is a 6x6 matrix that relates velocities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.        ,  0.        ,  0.        ,  0.        , -2.27496905,\n",
       "         2.7972336 ],\n",
       "       [ 0.        ,  0.95533649, -0.29552021,  3.        , -0.29552021,\n",
       "        -0.95533649],\n",
       "       [ 0.        ,  0.29552021,  0.95533649, -2.        ,  0.95533649,\n",
       "        -0.29552021],\n",
       "       [ 0.        ,  0.        ,  0.        ,  1.        ,  0.        ,\n",
       "         0.        ],\n",
       "       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.95533649,\n",
       "        -0.29552021],\n",
       "       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.29552021,\n",
       "         0.95533649]])"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tw.Ad()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and the `SE3` object also has this method.\n",
    "\n",
    "The logarithm of the adjoint is given by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.        , -0.        ,  0.        ,  0.        , -2.67746618,\n",
       "         2.43497745],\n",
       "       [ 0.        ,  0.        , -0.3       ,  2.67746618,  0.        ,\n",
       "        -1.        ],\n",
       "       [-0.        ,  0.3       ,  0.        , -2.43497745,  1.        ,\n",
       "         0.        ],\n",
       "       [ 0.        ,  0.        ,  0.        ,  0.        , -0.        ,\n",
       "         0.        ],\n",
       "       [ 0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        -0.3       ],\n",
       "       [ 0.        ,  0.        ,  0.        , -0.        ,  0.3       ,\n",
       "         0.        ]])"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tw.ad()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The name twist comes from considering the rigid-body motion as a rotation and a translation along a unique line of action.  It rotates as it moves along the line following a screw like motion, hence its other name as a _screw_.  The line in 3D space is described in Plücker coordinates by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{ -1.09 -2.435 -2.6775; 0.3 0 0}"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tw.line()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The pitch of the screw is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.3"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tw.pitch()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and a point on the line is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        , -2.67746618,  2.43497745])"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tw.pole()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working in 2D"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Things are actually much simpler in 2D.  There's only one possible rotation which is around an axis perpendicular to the plane (where the z-axis would have been if it were in 3D).\n",
    "\n",
    "Rotations in 2D can be represented by rotation matrices – 2x2 orthonormal matrices – which belong to the group SO(2). Just as for the 3D case these matrices have special properties, each column (and row) is a unit vector, and they are all orthogonal, the inverse of this matrix is equal to its transpose, and its determinant is +1.\n",
    "\n",
    "We can create such a matrix, a rotation of $\\pi/4$ radians by"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "R = SO2(pi/4)\n",
    "R"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or in degrees"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SO2(45, unit='deg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and we can plot this on the 2D plane"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
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       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
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       "        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",
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       "    this.ws = websocket;\n",
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       "    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",
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       "\n",
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       "            // Full images could contain transparency (where diff images\n",
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       "\n",
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       "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",
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       "};\n",
       "\n",
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       "\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",
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       "        '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",
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       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
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       "\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",
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       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
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       "        for (var i = 0; i < nentries; i++) {\n",
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       "                    // Firefox implements old version of spec.\n",
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       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
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       "            // 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",
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       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
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       "            } 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",
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       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
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       "\n",
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       "\n",
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       "            event.step = -1;\n",
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       "        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",
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       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure() # create a new figure\n",
    "R.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once again, it's useful to describe the position of things and we do this this with a homogeneous transformation matrix – a 3x3 matrix – which belong to the group SE(2)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 2       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T = SE2(1, 2)\n",
    "T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which has a similar structure to the 3D case.  The rotation matrix is in the top-left corner and the translation components are in the right-most column.\n",
    "\n",
    "We can also call the function with the element in a list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = SE2([1, 2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure() # create a new figure\n",
    "T.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m-0.7071  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T2 = SE2(45, unit='deg')\n",
    "T2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch (cursor) {\n",
       "        case 0:\n",
       "            cursor = 'pointer';\n",
       "            break;\n",
       "        case 1:\n",
       "            cursor = 'default';\n",
       "            break;\n",
       "        case 2:\n",
       "            cursor = 'crosshair';\n",
       "            break;\n",
       "        case 3:\n",
       "            cursor = 'move';\n",
       "            break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = 'image/png';\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.which === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.which;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which !== 17) {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    if (event.altKey && event.which !== 18) {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    if (event.shiftKey && event.which !== 16) {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data']);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager) {\n",
       "        manager = IPython.keyboard_manager;\n",
       "    }\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure() # create a new figure\n",
    "T2.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The inplace versions of operators are also supported, for example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;4m 1       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.7071  \u001b[0m \u001b[38;5;1m 0.7071  \u001b[0m \u001b[38;5;4m 2       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X = T\n",
    "X /= T2\n",
    "X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Operators\n",
    "\n",
    "## Group operators\n",
    "\n",
    "For the 3D case, the classes we have introduced mimic the behavior the mathematical groups $\\mbox{SO}(3)$ and $\\mbox{SE}(3)$ which contain matrices of particular structure. They are subsets respectively of the sets of all possible real 3x3 and 4x4 matrices.\n",
    "\n",
    "The only operations on two elements of the group that also belongs to the group are composition (represented by the `*` operator) and inversion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[spatialmath.pose3d.SE3, spatialmath.pose3d.SE3, spatialmath.pose3d.SE3]"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1 = SE3(1, 2, 3) * SE3.Rx(30, 'deg')\n",
    "[type(T1), type(T1.inv()), type(T1*T1)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we know the pose of frame {2} and a _rigid body motion_ from frame {1} to frame {2}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "T2 = SE3(4, 5, 6) * SE3.Ry(-40, 'deg')\n",
    "T12 = SE3(0, -2, -1) * SE3.Rz(70, 'deg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "then ${}^0{\\bf T}_1 \\bullet {}^1{\\bf T}_2 = {}^0{\\bf T}_2$ then ${}^0{\\bf T}_1 =  {}^1{\\bf T}_2 \\bullet ({}^0{\\bf T}_2)^{-1}$ which we write as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.766   \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.6428  \u001b[0m \u001b[38;5;4m-5.921   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.3214  \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;1m-0.383   \u001b[0m \u001b[38;5;4m-1.318   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.5567  \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;1m 0.6634  \u001b[0m \u001b[38;5;4m-1.254   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1 * T2.inv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or more concisely as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 0.766   \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.6428  \u001b[0m \u001b[38;5;4m-5.921   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.3214  \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;1m-0.383   \u001b[0m \u001b[38;5;4m-1.318   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m-0.5567  \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;1m 0.6634  \u001b[0m \u001b[38;5;4m-1.254   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1 / T2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exponentiation is also a group operator since it is simply repeated composition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 2       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;1m-0.866   \u001b[0m \u001b[38;5;4m 2.232   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.866   \u001b[0m \u001b[38;5;1m 0.5     \u001b[0m \u001b[38;5;4m 6.598   \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T1 ** 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Non-group operations\n",
    "\n",
    "Operations such as addition and subtraction are valid for matrices but not for elements of the group, therefore these operations will return a numpy array rather than a group object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2., 0., 0., 0.],\n",
       "       [0., 2., 0., 0.],\n",
       "       [0., 0., 2., 0.],\n",
       "       [0., 0., 0., 2.]])"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SE3() + SE3()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "yields an array, not an `SE3` object. As do other non-group operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2., 0., 0., 0.],\n",
       "       [0., 2., 0., 0.],\n",
       "       [0., 0., 2., 0.],\n",
       "       [0., 0., 0., 2.]])"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2 * SE3()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0., -1., -1., -1.],\n",
       "       [-1.,  0., -1., -1.],\n",
       "       [-1., -1.,  0., -1.],\n",
       "       [-1., -1., -1.,  0.]])"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SE3() - 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar principles apply to quaternions.  Unit quaternions are a group and only support composition and inversion.  Any other operations will return an ordinary quaternion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 2.0000 <  0.0000,  0.0000,  0.0000 >\n"
     ]
    },
    {
     "data": {
      "text/plain": []
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "UnitQuaternion() * 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which is indicated by the single angle brackets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## In-place operators\n",
    "\n",
    "All of Pythons in-place operators are available as well, whether for group or non-group operations.  For example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = T1\n",
    "T *= T2\n",
    "T **= 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Multi-valued objects\n",
    "\n",
    "For many tasks we might want to have a set or sequence of rotations or poses. The obvious solution would be to use a Python list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = [ SE3.Rx(0), SE3.Rx(0.1), SE3.Rx(0.2), SE3.Rx(0.3), SE3.Rx(0.4)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "but the pose objects in this package can hold multiple values, just like a native Python list can.  There are a few ways to do this, most obviously"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "T = SE3( [ SE3.Rx(0), SE3.Rx(0.1), SE3.Rx(0.2), SE3.Rx(0.3), SE3.Rx(0.4)] )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which has type of a pose object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "spatialmath.pose3d.SE3"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "but it has length of five"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "that is, it contains five values.  We can see these when we display the object's value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "1:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.995   \u001b[0m \u001b[38;5;1m-0.09983 \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.09983 \u001b[0m \u001b[38;5;1m 0.995   \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "2:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.9801  \u001b[0m \u001b[38;5;1m-0.1987  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.1987  \u001b[0m \u001b[38;5;1m 0.9801  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "3:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.9553  \u001b[0m \u001b[38;5;1m-0.2955  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.2955  \u001b[0m \u001b[38;5;1m 0.9553  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "4:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.9211  \u001b[0m \u001b[38;5;1m-0.3894  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.3894  \u001b[0m \u001b[38;5;1m 0.9211  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can index into the object (slice it) just as we would a Python list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.9553  \u001b[0m \u001b[38;5;1m-0.2955  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.2955  \u001b[0m \u001b[38;5;1m 0.9553  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T[3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or from the second element to the last in steps of two"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.995   \u001b[0m \u001b[38;5;1m-0.09983 \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.09983 \u001b[0m \u001b[38;5;1m 0.995   \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "1:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.9553  \u001b[0m \u001b[38;5;1m-0.2955  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.2955  \u001b[0m \u001b[38;5;1m 0.9553  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T[1:-1:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could another value to the end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T.append( SE3.Rx(0.5) )\n",
    "len(T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `SE3` class, like all the classes in this package, inherits from the `UserList` class giving it all the methods of a Python list like append, extend, del etc.  We can also use them as _iterables_ in _for_ loops and in list comprehensions.\n",
    "\n",
    "You can create an object of a particular type with no elements using this constructor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T = SE3.Empty()\n",
    "len(T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which is the equivalent of setting a variable to `[]`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We could write the above example more succinctly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T = SE3.Rx( np.linspace(0, 0.5, 5) )\n",
    "len(T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.9305  \u001b[0m \u001b[38;5;1m-0.3663  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0.3663  \u001b[0m \u001b[38;5;1m 0.9305  \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T[3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Consider another rotation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "T2 = SE3.Ry(40, 'deg')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we write"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = T * T2\n",
    "len(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we obtain a new list where each element of `A` is `T[i] * T2`.  Similarly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B = T2 * T\n",
    "len(B)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "which has produced a new list where each element of `B` is `T2 * T[i]`.\n",
    "\n",
    "Similarly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C = T * T\n",
    "len(C)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "yields a new list where each element of `C` is the `T[i] * T[i]`.  \n",
    "\n",
    "We can apply such a sequence to a coordinate vectors as we did earlier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.        , 0.        , 0.        , 0.        , 0.        ],\n",
       "       [1.        , 0.99219767, 0.96891242, 0.93050762, 0.87758256],\n",
       "       [0.        , 0.12467473, 0.24740396, 0.36627253, 0.47942554]])"
      ]
     },
     "execution_count": 115,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "P = T * [0, 1, 0]\n",
    "P"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "where each element of `T` has transformed the coordinate vector (0, 1, 0), the results being consecutive columns of the resulting numpy array.\n",
    "\n",
    "This is equivalent to writing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.        , 0.        , 0.        , 0.        , 0.        ],\n",
       "       [1.        , 0.99219767, 0.96891242, 0.93050762, 0.87758256],\n",
       "       [0.        , 0.12467473, 0.24740396, 0.36627253, 0.47942554]])"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.column_stack([x * [0,1,0] for x in T])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## C++ like programming model\n",
    "Lists are useful, but we might like to use a programming model where we allocate an array of pose objects and reference them or assign to them.  We can do that to!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0:\n",
       "  \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "1:\n",
       "  \u001b[38;5;1m 0.9689  \u001b[0m \u001b[38;5;1m-0.2474  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.2474  \u001b[0m \u001b[38;5;1m 0.9689  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "2:\n",
       "  \u001b[38;5;1m 0.8776  \u001b[0m \u001b[38;5;1m-0.4794  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.4794  \u001b[0m \u001b[38;5;1m 0.8776  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "3:\n",
       "  \u001b[38;5;1m 0.7317  \u001b[0m \u001b[38;5;1m-0.6816  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.6816  \u001b[0m \u001b[38;5;1m 0.7317  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n",
       "4:\n",
       "  \u001b[38;5;1m 0.5403  \u001b[0m \u001b[38;5;1m-0.8415  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0.8415  \u001b[0m \u001b[38;5;1m 0.5403  \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 0       \u001b[0m \u001b[38;5;1m 1       \u001b[0m \u001b[38;5;4m 0       \u001b[0m  \u001b[0m\n",
       "  \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 0       \u001b[0m \u001b[38;5;244m 1       \u001b[0m  \u001b[0m\n"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T = SE3.Alloc(5)  # create a vector of SE3 values\n",
    "\n",
    "for i, theta in enumerate(np.linspace(0, 1, len(T))):\n",
    "    T[i] = SE3.Rz(theta)\n",
    "T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``Alloc`` initializes every element to the identity value.  This technique works for all pose objects."
   ]
  }
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