Notebook_2_PotentialWall.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "05828543058441dfbad82d8d89c621e2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=20.0, description='E', max=200.0, step=1.0), FloatSlider(value=100.0, …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "import ipywidgets as widgets\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "import numpy as np\n",
    "\n",
    "#initial values\n",
    "E0 = 20\n",
    "V0 = 100\n",
    "a = 1\n",
    "b = 0\n",
    "k = np.sqrt(E0)\n",
    "kp = np.sqrt(V0-E0)\n",
    "\n",
    "#create plot and data\n",
    "x1 = np.arange(-3.141592, 0, 0.001)\n",
    "x2 = np.arange(0, 2, 0.001)\n",
    "y1_real = a*np.cos(k*x1)+b*np.cos(-k*x1)\n",
    "y1_imag = a*np.sin(k*x1)+b*np.sin(-k*x1)\n",
    "y2_real = a * np.exp(-kp*x2)\n",
    "y2_imag = 0*x2\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "p1_real, = ax.plot(x1, y1_real, lw=2, color='red', label='Real')\n",
    "p1_imag, = ax.plot(x1, y1_imag, lw=2, color='blue', label='Imaginary')\n",
    "p2_real, = ax.plot(x2, y2_real, lw=2, color='red')\n",
    "p2_imag, = ax.plot(x2, y2_imag, lw=2, color='blue')\n",
    "ax.set_xlim(-3.141592, 2)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('Wellenfunktion')\n",
    "ax.legend(loc='upper right')\n",
    "ax.add_patch(patches.Rectangle((0.0, -2.0), 2.0, 4.0, alpha=0.2))\n",
    "\n",
    "@widgets.interact(E=(0.0, 200, 1.0), V=(0.0, 100, 1.0))\n",
    "def update(E=E0, V=V0):\n",
    "    k = np.sqrt(E)\n",
    "    p1_real.set_ydata(a*np.cos(k*x1)+b*np.cos(-k*x1))\n",
    "    p1_imag.set_ydata(a*np.sin(k*x1)+b*np.sin(-k*x1))\n",
    "    if E < V:\n",
    "        kp = np.sqrt(V-E)\n",
    "        p2_real.set_ydata(a * np.exp(-kp*x2))\n",
    "        p2_imag.set_ydata(0*x2)\n",
    "    else:\n",
    "        kp = np.sqrt(E-V)\n",
    "        p2_real.set_ydata(a*np.cos(kp*x2)+b*np.cos(-kp*x2))\n",
    "        p2_imag.set_ydata(a*np.sin(kp*x2)+b*np.sin(-kp*x2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}