LED simulator.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "import numpy as np\n",
    "from time import sleep\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_trapezoid(ax, base1, base2, height, offset, colors, n_points=160):\n",
    "    # Calculate coordinates of the trapezoid\n",
    "    x1, y1 = offset, 2\n",
    "    x2, y2 = x1 + base2, 2\n",
    "    x3, y3 = x1 + (base2 - base1) / 2, height\n",
    "    x4, y4 = x2 - (base2 - base1) / 2, height\n",
    "\n",
    "    side_lengths = [\n",
    "        40, 20, 40, 60,\n",
    "    ]\n",
    "\n",
    "    # Interpolate points along the edges\n",
    "    left_side_x = np.linspace(x1, x3, side_lengths[0])\n",
    "    left_side_y = np.linspace(y1, y3, side_lengths[0])\n",
    "    top_side_x = np.linspace(x3, x4, side_lengths[1])\n",
    "    top_side_y = np.linspace(y3, y4, side_lengths[1])\n",
    "    right_side_x = np.linspace(x2, x4, side_lengths[2])\n",
    "    right_side_y = np.linspace(y2, y4, side_lengths[2])\n",
    "    bottom_side_x = np.linspace(x1, x2, side_lengths[3])\n",
    "    bottom_side_y = np.linspace(y1, y2, side_lengths[3])\n",
    "\n",
    "    # Combine points\n",
    "    x_points = np.concatenate(\n",
    "        [left_side_x, top_side_x, right_side_x, bottom_side_x])\n",
    "    y_points = np.concatenate(\n",
    "        [left_side_y, top_side_y, right_side_y, bottom_side_y])\n",
    "\n",
    "    # Mark the interpolated points\n",
    "    ax.scatter(x_points, y_points, s=10, c=colors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_tapestries(colors, fig, ax):\n",
    "    # Common height for all trapezoids\n",
    "    height = 7\n",
    "\n",
    "    colors = [(r / 255, g / 255, b / 255) for (r, g, b) in colors]\n",
    "\n",
    "    # Draw multiple trapezoids\n",
    "    for i in range(6):\n",
    "        draw_trapezoid(ax, 3, 5, height, i * 6 + 3, colors[160 * i: 160 * (i + 1)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_leds = [\n",
    "    160,\n",
    "    160,\n",
    "    160,\n",
    "    160,\n",
    "    160,\n",
    "    160,\n",
    "]\n",
    "\n",
    "side_lengths = [\n",
    "    40, 20, 40, 60,\n",
    "]\n",
    "\n",
    "N_LEDS = sum(n_leds)\n",
    "\n",
    "\n",
    "def side_index(tapestry_idx, idx, side, direction):\n",
    "    tapestry_padding = 0\n",
    "\n",
    "    i = 0\n",
    "    while i < tapestry_idx:\n",
    "        tapestry_padding += n_leds[i]\n",
    "\n",
    "        i += 1\n",
    "\n",
    "    side_padding = 0\n",
    "    i = 0\n",
    "    while i < side:\n",
    "        side_padding += side_lengths[i]\n",
    "\n",
    "        i += 1\n",
    "\n",
    "    if idx >= side_lengths[side]:\n",
    "        return N_LEDS\n",
    "\n",
    "    if direction == 0:\n",
    "        return tapestry_padding + side_padding + idx\n",
    "    else:\n",
    "        return tapestry_padding + side_padding + (side_lengths[side] - idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def simulate_leds(update_fn, fig_size_multiplier=2):\n",
    "    # set parameters\n",
    "    frames = 1000\n",
    "\n",
    "    # init the figure\n",
    "    fig, ax = plt.subplots(figsize=(9 * fig_size_multiplier, 5 * fig_size_multiplier))\n",
    "\n",
    "    def _update(i):\n",
    "        # clear the axis each frame\n",
    "        ax.clear()\n",
    "\n",
    "        colors = update_fn(i)\n",
    "\n",
    "        draw_tapestries(colors, fig, ax)\n",
    "\n",
    "        # Set limits and labels\n",
    "        ax.set_xlim(0, 40)\n",
    "        ax.set_ylim(0, 10)\n",
    "        ax.set_xlabel('X-axis')\n",
    "        ax.set_ylabel('Y-axis')\n",
    "        ax.set_title('Trapezoids with 160 Points Each')\n",
    "\n",
    "    return animation.FuncAnimation(fig, _update, frames=frames, interval=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def turn(tapestry_idx, colors, color):\n",
    "    padding = sum(n_leds[i] for i in range(tapestry_idx))\n",
    "\n",
    "    for i in range(n_leds[tapestry_idx]):\n",
    "        colors[padding + i] = color"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def circling_dot(i):\n",
    "    # pattern changing\n",
    "    colors = [(0, 0, 0) for _ in range(160 * 6 + 1)]\n",
    "\n",
    "    # 0 to 1\n",
    "    pattern_progress = (i % 100) / 100.0\n",
    "\n",
    "    tapestry_progress = (pattern_progress * 6) % 1\n",
    "    tapestry_idx = int(pattern_progress * 6)\n",
    "\n",
    "\n",
    "    side = 1\n",
    "    side_idx = int(tapestry_progress * side_lengths[side])\n",
    "    transformed_idx = side_index(tapestry_idx, side_idx, side, 0)\n",
    "    colors[transformed_idx] = [255, 0, 0]\n",
    "\n",
    "    side = 3\n",
    "    side_idx = int(tapestry_progress * side_lengths[side])\n",
    "    transformed_idx = side_index(tapestry_idx, side_idx, side, 0)\n",
    "    colors[transformed_idx] = [255, 0, 0]\n",
    "\n",
    "    return colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def circular_idx(idx, side):\n",
    "    tapestry_idx = idx // side_lengths[side]\n",
    "\n",
    "    side_idx = idx % side_lengths[side]\n",
    "\n",
    "    transformed_idx = side_index(tapestry_idx, side_idx, side, 0)\n",
    "    return transformed_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# pulse(i % 10, 5)\n",
    "# min value will be 0 max will be 5\n",
    "def pulse(n, max_val):\n",
    "    if n > max_val:\n",
    "        n -= max_val * 2\n",
    "        n *= -1\n",
    "\n",
    "    return n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def circling_pulse(idx):\n",
    "    colors = [(0, 0, 0) for _ in range(160 * 6 + 1)]\n",
    "\n",
    "    side = 1\n",
    "    maximum = side_lengths[side] * 6\n",
    "\n",
    "    n_dots = 20\n",
    "    for t in range(n_dots):\n",
    "        i = (idx + t) % maximum\n",
    "        transformed_idx = circular_idx(i, side)\n",
    "\n",
    "        intensity = pulse(t, n_dots / 2) / (n_dots / 2)\n",
    "        color = 255 * pow(intensity, 1.3)\n",
    "        colors[transformed_idx] = [color, 0, 0]\n",
    "\n",
    "    return colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
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       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.canvas_div.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "function getModifiers(event) {\n",
       "    var mods = [];\n",
       "    if (event.ctrlKey) {\n",
       "        mods.push('ctrl');\n",
       "    }\n",
       "    if (event.altKey) {\n",
       "        mods.push('alt');\n",
       "    }\n",
       "    if (event.shiftKey) {\n",
       "        mods.push('shift');\n",
       "    }\n",
       "    if (event.metaKey) {\n",
       "        mods.push('meta');\n",
       "    }\n",
       "    return mods;\n",
       "}\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    // from https://stackoverflow.com/q/1114465\n",
       "    var boundingRect = this.canvas.getBoundingClientRect();\n",
       "    var x = (event.clientX - boundingRect.left) * this.ratio;\n",
       "    var y = (event.clientY - boundingRect.top) * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        modifiers: getModifiers(event),\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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\" width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.animation.FuncAnimation at 0x10cc80490>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulate_leds(circling_pulse, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}