CSHL 10.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import tdms\n",
    "import imp\n",
    "imp.reload(tdms)\n",
    "import plot\n",
    "import functions\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "%matplotlib notebook\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Cortical connectivity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = tdms.read_tdms(\"/Volumes/NO NAME/Cortical Connectivity/LTP_Baseline-JM_67_20hz_vc_-70_ptx.tdms\")\n",
    "# data = tdms.read_tdms(\"/Volumes/DATA/data/tdms/CHSL-6.8.1701-8ICLAMPSPIKES.tdms\")\n",
    "# data = tdms.read_tdms(\"/Volumes/DATA/data/tdms/CHSL-6.8.1702iclamp-1.tdms\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tstim1 = 200.0\n",
    "tstim2 = 235.0\n",
    "tpulsestart = 700.0\n",
    "pulsedur = 100.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "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",
       "        this.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 overriden (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",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\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=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x117188e10>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig, axi, axv = plot.plot_traces(mode='vclamp')\n",
    "\n",
    "dt = data['dt']\n",
    "meansweep = np.mean([sweep for sweep in data['AI0'][1:]], axis=0)\n",
    "meancommand = np.mean([sweep for sweep in data['AO1'][1:]], axis=0)\n",
    "for sweep, command in zip(data['AI0'][1:], data['AO1'][1:]):\n",
    "    times = np.arange(sweep.shape[0])*data['dt']\n",
    "    axi.plot(times, sweep, alpha=0.1)\n",
    "    axv.plot(times, command, alpha=0.1)\n",
    "axi.plot(times, meansweep, '-k', alpha=0.7, lw=2)\n",
    "axv.plot(times, meancommand, '-k', alpha=0.7, lw=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}