{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# QCoDeS Example with Tektronix TPS2012"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logging hadn't been started.\n",
      "Activating auto-logging. Current session state plus future input saved.\n",
      "Filename       : C:\\Users\\Jens-Work\\.qcodes\\logs\\command_history.log\n",
      "Mode           : append\n",
      "Output logging : True\n",
      "Raw input log  : False\n",
      "Timestamping   : True\n",
      "State          : active\n",
      "Qcodes Logfile : C:\\Users\\Jens-Work\\.qcodes\\logs\\201006-24644-qcodes.log\n"
     ]
    }
   ],
   "source": [
    "%matplotlib nbagg\n",
    "import logging\n",
    "from time import sleep\n",
    "\n",
    "from qcodes.instrument_drivers.tektronix import TektronixTPS2012\n",
    "from qcodes.measure import Measure\n",
    "from qcodes.plots.qcmatplotlib import MatPlot\n",
    "\n",
    "logger = logging.getLogger()\n",
    "logger.setLevel(logging.DEBUG)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to: TEKTRONIX TPS 2012B (serial:0, firmware:CF:91.1CT FV:v11.10) in 0.44s\n"
     ]
    }
   ],
   "source": [
    "tps = TektronixTPS2012('TPS1', 'ASRL1::INSTR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# For good measures, one may clear out old messages\n",
    "tps.clear_message_queue()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## SETTING UP AN ACQUISITION\n",
    "The driver supports basic setting of scales and triggers.\n",
    "\n",
    "In this example, we want to look at a 10 kHz sine, 100 mVpp with a -50 mV offset.\n",
    "\n",
    "The sine is on channel **1**, while the sync (0 V to 3 V square wave) signal from the function generator is on channel **2**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we don't want to see the ref. signal, only the sine\n",
    "tps.ch1_state('ON')\n",
    "tps.ch2_state('OFF')\n",
    "\n",
    "# horizontal\n",
    "tps.horizontal_scale.set(10e-6)\n",
    "# channel 1\n",
    "tps.ch1_scale.set(50e-3)  # V/div\n",
    "tps.ch1_position.set(2)  # divisions\n",
    "# channel 2\n",
    "tps.ch2_scale.set(1)\n",
    "tps.ch2_position.set(-3)\n",
    "# trigger\n",
    "tps.trigger_type.set('EDGE')\n",
    "tps.trigger_source.set('CH2')\n",
    "tps.trigger_level.set(1.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ACQUIRING THE CURVES FROM THE OSCILLOSCOPE\n",
    "There is a simple command to get two arrays for the horizontal and vertical data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because this is early beta version you must currently call `set_set_points` on each channel just before reading a trace from the channel. This is a limitation in the current dataset/loop of qcodes. You should also ensure that the scope has been triggered at these settings before calling set_set_points or you will get inconsitent data. \n",
    "\n",
    "In this example notebook we use force_trigger to ensure that we always have data when setting the set_points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DataSet:\n",
      "   location = 'data/2017-05-08/#006_{name}_16-21-59'\n",
      "   <Type>   | <array_id>               | <array.name>      | <array.shape>\n",
      "   Measured | TPS1_scope_measurement_0 | scope_measurement | (2500,)\n",
      "   Measured | TPS1_scope_measurement_1 | scope_measurement | (2500,)\n",
      "acquired at 2017-05-08 16:22:13\n"
     ]
    }
   ],
   "source": [
    "tps.force_trigger()\n",
    "sleep(10*tps.horizontal_scale.get_latest())\n",
    "tps.ch1_curvedata.prepare_curvedata()\n",
    "tps.ch2_curvedata.prepare_curvedata()\n",
    "data = Measure(tps.ch1_curvedata, tps.ch2_curvedata).run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": "/* Put everything inside the global mpl namespace */\nwindow.mpl = {};\n\n\nmpl.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\nmpl.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        this.ws.close();\n    }\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n}\n\nmpl.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\nmpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n\n}\n\n\nmpl.figure.prototype._root_extra_style = function(canvas_div) {\n\n}\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype.handle_figure_label = function(fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n}\n\nmpl.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\nmpl.figure.prototype.handle_message = function(fig, msg) {\n    fig.message.textContent = msg['message'];\n}\n\nmpl.figure.prototype.handle_draw = function(fig, msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n}\n\nmpl.figure.prototype.handle_image_mode = function(fig, msg) {\n    fig.image_mode = msg['mode'];\n}\n\nmpl.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.\nmpl.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\nmpl.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 */\nfunction 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\nmpl.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\nmpl.figure.prototype._key_event_extra = function(event, name) {\n    // Handle any extra behaviour associated with a key event\n}\n\nmpl.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\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\nmpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n\nmpl.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 overriden (by mpl) onmessage function.\n        ws.onmessage(msg['content']['data'])\n    });\n    return ws;\n}\n\nmpl.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\nmpl.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\nmpl.figure.prototype.close_ws = function(fig, msg){\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n}\n\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype._root_extra_style = function(el){\n    var fig = this\n    el.on(\"remove\", function(){\n\tfig.close_ws(fig, {});\n    });\n}\n\nmpl.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\nmpl.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        // 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\nmpl.figure.prototype.handle_save = function(fig, msg) {\n    fig.ondownload(fig, null);\n}\n\n\nmpl.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.\nif (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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = MatPlot(subplots=(2, 1))\n",
    "plot.add(data.TPS1_scope_measurement_0)\n",
    "plot.add(data.TPS1_scope_measurement_1, subplot=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Change horisontal scale and remember to call `prepare_curvedata` to update the setpoint array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "tps.horizontal_scale.set(25e-6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DataSet:\n",
      "   location = 'data/2017-05-08/#007_{name}_16-22-17'\n",
      "   <Type>   | <array_id>               | <array.name>      | <array.shape>\n",
      "   Measured | TPS1_scope_measurement_0 | scope_measurement | (2500,)\n",
      "   Measured | TPS1_scope_measurement_1 | scope_measurement | (2500,)\n",
      "acquired at 2017-05-08 16:22:30\n"
     ]
    }
   ],
   "source": [
    "tps.force_trigger()\n",
    "sleep(11*tps.horizontal_scale.get_latest())\n",
    "tps.ch1_curvedata.prepare_curvedata()\n",
    "tps.ch2_curvedata.prepare_curvedata()\n",
    "data2 = Measure(tps.ch1_curvedata, tps.ch2_curvedata).run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": "/* Put everything inside the global mpl namespace */\nwindow.mpl = {};\n\n\nmpl.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\nmpl.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        this.ws.close();\n    }\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n}\n\nmpl.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\nmpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n\n}\n\n\nmpl.figure.prototype._root_extra_style = function(canvas_div) {\n\n}\n\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype.handle_figure_label = function(fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n}\n\nmpl.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\nmpl.figure.prototype.handle_message = function(fig, msg) {\n    fig.message.textContent = msg['message'];\n}\n\nmpl.figure.prototype.handle_draw = function(fig, msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n}\n\nmpl.figure.prototype.handle_image_mode = function(fig, msg) {\n    fig.image_mode = msg['mode'];\n}\n\nmpl.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.\nmpl.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\nmpl.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 */\nfunction 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\nmpl.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\nmpl.figure.prototype._key_event_extra = function(event, name) {\n    // Handle any extra behaviour associated with a key event\n}\n\nmpl.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\nmpl.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\nmpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n    this.message.textContent = tooltip;\n};\nmpl.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\nmpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n\nmpl.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 overriden (by mpl) onmessage function.\n        ws.onmessage(msg['content']['data'])\n    });\n    return ws;\n}\n\nmpl.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\nmpl.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\nmpl.figure.prototype.close_ws = function(fig, msg){\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n}\n\nmpl.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\nmpl.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\nmpl.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\nmpl.figure.prototype._root_extra_style = function(el){\n    var fig = this\n    el.on(\"remove\", function(){\n\tfig.close_ws(fig, {});\n    });\n}\n\nmpl.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\nmpl.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        // 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\nmpl.figure.prototype.handle_save = function(fig, msg) {\n    fig.ondownload(fig, null);\n}\n\n\nmpl.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.\nif (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=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = MatPlot(subplots=(2, 1))\n",
    "plot.add(data2.TPS1_scope_measurement_0)\n",
    "plot.add(data2.TPS1_scope_measurement_1, subplot=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "tps.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "qcodespip310",
   "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": "3.10.8 | packaged by conda-forge | (main, Nov 24 2022, 14:07:00) [MSC v.1916 64 bit (AMD64)]"
  },
  "nbsphinx": {
   "execute": "never"
  },
  "vscode": {
   "interpreter": {
    "hash": "877bdf401a755bd1ca03bfff5025f0aef86a1f0055843840ae8b9a03952abbf7"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}