path: root/fw/Scope.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "%matplotlib notebook\n",
    "import struct\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_data(offx=0, end=-1, signed=False, channels=1):\n",
    "    with open('/tmp/scope_dump.bin', 'rb') as f:\n",
    "        raw_data = f.read()\n",
    "        data = struct.unpack(f'<{len(raw_data)//2}{\"h\" if signed else \"H\"}', raw_data)\n",
    "    \n",
    "    fig, axs = plt.subplots(channels, 1, squeeze=False, sharex=True, figsize=(10, 5))\n",
    "    for i, ax in enumerate(axs.flatten()):\n",
    "        ax.plot([math.nan if x==-255 else x for x in data[offx:][:end][i::channels]])\n",
    "        ax.grid()\n",
    "    \n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width, fig.canvas.height);\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",
       "    {\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.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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\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,\n",
       "                             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",
       "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"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\";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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\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",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"1000\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "    data = plot_data(offx=4, signed=True, channels=1)\n",
    "#print(''.join(str(x) for x in data[4:][3::4]))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}