Notebook_3_Transmission.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "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>"
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     "output_type": "display_data"
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\" width=\"639.9999861283738\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "51551ef8752148abb7db5c3e04ec224b"
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from pylab import *\n",
    "from ipywidgets import *\n",
    "import matplotlib.patches as patches\n",
    "%matplotlib notebook\n",
    "\n",
    "#initial values\n",
    "m0 = 2\n",
    "L0 = 1\n",
    "\n",
    "#create plot and data\n",
    "ev1 = arange(0.01, 1.0, 0.01)\n",
    "ev2 = arange(1.001, 4.0, 0.001)\n",
    "\n",
    "def kappa(EV, m):\n",
    "    return sqrt(2*m*(1-EV))\n",
    "def kappa_prime(EV, m):\n",
    "        return sqrt(2*m*(EV-1))\n",
    "\n",
    "def T1(EV, m, L):\n",
    "    return 1.0 / (1+(exp(kappa(EV, m)*L)-exp(-kappa(EV, m))*L)**2/(16*EV*(1-EV)))\n",
    "    \n",
    "def T2(EV, m, L):\n",
    "    return 1.0 / (1+(sin(kappa_prime(EV, m)*L))**2/(4*EV*(EV-1)))\n",
    "    \n",
    "t1 = T1(ev1, m0, L0)\n",
    "t2 = T2(ev2, m0, L0)\n",
    "\n",
    "fig1 = figure()\n",
    "ax1 = fig1.add_subplot(111)\n",
    "p = ax1.add_patch(patches.Rectangle((1.0, 0.0), 3.0, 1.0, alpha=0.2))\n",
    "p_real, = plot(ev1, t1, lw=2, color='red')\n",
    "p_imag, = plot(ev2, t2, lw=2, color='red')\n",
    "axis([0, 4, 0, 1])\n",
    "xlabel('E/V')\n",
    "ylabel('Transmissionswahrscheinlichkeit')\n",
    "\n",
    "@interact(m=(2, 100.0, 1))\n",
    "def update(m=m0):\n",
    "    p_real.set_ydata(T1(ev1, m, L0))\n",
    "    p_imag.set_ydata(T2(ev2, m, L0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}