reflection_boundary_1.ipynb

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  {
   "cell_type": "markdown",
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   "source": [
    "<hr style=\"height: 1px;\">\n",
    "<i>This code was authored by Alex Shvonski, Copyright 2020 MIT All Rights Reserved.</i>\n",
    "<hr style=\"height: 1px;\">\n",
    "\n",
    "<h2>Initializing the program</h2>\n",
    "\n",
    "<font size=\"3\">To initialize the visualization, you may need to click \"Run all initialization cells\" above (see button location in figure).</font>\n",
    "\n",
    "<img src=\"img/binder_initialize_button.png\" alt=\"Drawing\" style=\"width: 700px;\" align=\"left\"/>\n",
    "\n",
    "<br/>\n",
    "<br/>\n",
    "<br/>\n",
    "<br/>\n",
    "<br/>\n",
    "<br/>\n",
    "<br/>\n",
    "<font size=\"3\">You should see the visualization <i>directly below this line</i>, before the next section.</font>\n",
    "\n",
    "<br/>\n",
    "<br/>\n",
    "<hr style=\"height: 1px;\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
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   "source": [
    "#This code was authored by Alex Shvonski, Copyright 2020 MIT All Rights Reserved.\n",
    "\n",
    "%matplotlib notebook\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display, clear_output\n",
    "from ipywidgets import interact, interactive, interactive_output, fixed, IntSlider, HBox, Layout, Output, VBox\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,\n",
    "                               AutoMinorLocator)\n",
    "from math import pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "init_cell": true
   },
   "outputs": [],
   "source": [
    "#Define functions\n",
    "###############################################\n",
    "###############################################\n",
    "def func1(x,t,L,polarity):\n",
    "    arg1 = (x - (t/10.)*np.ones(len(x)))\n",
    "    f1 = np.zeros(len(x))\n",
    "    for i in range(len(arg1)):\n",
    "        if arg1[i] < 0:\n",
    "            f1[i] = 0.\n",
    "        elif 0 <= arg1[i] <= 2:\n",
    "            f1[i] = 1.\n",
    "        elif 0 < arg1[i]:\n",
    "            f1[i] = 0.\n",
    "\n",
    "    x = L - x\n",
    "    arg2 = (x - (t/10.)*np.ones(len(x)))\n",
    "    f2 = np.zeros(len(x))\n",
    "    for i in range(len(arg2)):\n",
    "        if arg2[i] < 0:\n",
    "            f2[i] = 0.\n",
    "        elif 0 <= arg2[i] <= 2:\n",
    "            f2[i] = 1.\n",
    "        elif 0 < arg2[i]:\n",
    "            f2[i] = 0.\n",
    "            \n",
    "    if polarity==\"pos\":\n",
    "        return f1+f2, f1, f2\n",
    "        \n",
    "    elif polarity==\"neg\":\n",
    "        return f1-f2, f1, -f2\n",
    "\n",
    "\n",
    "def func2(x,t,L,polarity):\n",
    "    arg1 = (x - (t/10.)*np.ones(len(x)))\n",
    "    f1 = np.zeros(len(x))\n",
    "    for i in range(len(arg1)):\n",
    "        if arg1[i] < 0:\n",
    "            f1[i] = 0.\n",
    "        elif 0 <= arg1[i] <= 1.:\n",
    "            f1[i] = arg1[i]\n",
    "        elif 1. <= arg1[i] <= 2.:\n",
    "            f1[i] = 2.-arg1[i]\n",
    "        elif 0 < arg1[i]:\n",
    "            f1[i] = 0.\n",
    "\n",
    "    x = L - x\n",
    "    arg2 = (x - (t/10.)*np.ones(len(x)))\n",
    "    f2 = np.zeros(len(x))\n",
    "    for i in range(len(arg2)):\n",
    "        if arg2[i] < 0:\n",
    "            f2[i] = 0.\n",
    "        elif 0 <= arg2[i] <= 1.:\n",
    "            f2[i] = arg2[i]\n",
    "        elif 1. <= arg2[i] <= 2.:\n",
    "            f2[i] = 2.-arg2[i]\n",
    "        elif 0 < arg2[i]:\n",
    "            f2[i] = 0.\n",
    "\n",
    "    if polarity==\"pos\":\n",
    "        return f1+f2, f1, f2\n",
    "        \n",
    "    elif polarity==\"neg\":\n",
    "        return f1-f2, f1, -f2\n",
    "        \n",
    "\n",
    "\n",
    "def func3(x,t,L,polarity):\n",
    "    arg1 = (x - (t/10.)*np.ones(len(x)))\n",
    "    f1 = np.zeros(len(x))\n",
    "    for i in range(len(arg1)):\n",
    "        if arg1[i] < 0:\n",
    "            f1[i] = 0.\n",
    "        elif 0 <= arg1[i] <= 2.:\n",
    "            f1[i] = np.sqrt(1-(arg1[i]-1.)**2.)\n",
    "        elif 0 < arg1[i]:\n",
    "            f1[i] = 0.\n",
    "\n",
    "    x = L - x\n",
    "    arg2 = (x - (t/10.)*np.ones(len(x)))\n",
    "    f2 = np.zeros(len(x))\n",
    "    for i in range(len(arg2)):\n",
    "        if arg2[i] < 0:\n",
    "            f2[i] = 0.\n",
    "        elif 0 <= arg2[i] <= 2.:\n",
    "            f2[i] = np.sqrt(1-(arg2[i]-1.)**2.)\n",
    "        elif 0 < arg2[i]:\n",
    "            f2[i] = 0.\n",
    "        \n",
    "    if polarity==\"pos\":\n",
    "        return f1+f2, f1, f2\n",
    "        \n",
    "    elif polarity==\"neg\":\n",
    "        return f1-f2, f1, -f2\n",
    "        \n",
    "\n",
    "def func4(x,t,L,polarity):\n",
    "    arg1 = ((x-1) - (t/10.)*np.ones(len(x)))\n",
    "    f1 = np.exp(-(2.*arg1)**2.)\n",
    "    \n",
    "    x = L - x\n",
    "    arg2 = ((x-1) - (t/10.)*np.ones(len(x)))\n",
    "    f2 = np.exp(-(2.*arg2)**2.)\n",
    "        \n",
    "    if polarity==\"pos\":\n",
    "        return f1+f2, f1, f2\n",
    "        \n",
    "    elif polarity==\"neg\":\n",
    "        return f1-f2, f1, -f2"
   ]
  },
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   "cell_type": "code",
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       "        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",
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       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
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       "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",
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       "        '<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",
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       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"950\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d923f1fb2b0d4080bb69955c4f60c1c4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(Dropdown(description='Function:', index=3, options=(('function-1', <function func1 at 0x1155abd…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Define plot\n",
    "###############################################\n",
    "###############################################\n",
    "fig, ax = plt.subplots(2, 1, figsize=(9.5, 7))\n",
    "plt.subplots_adjust(left=0.05, bottom=None, right=0.98, top=None, wspace=None, hspace=0)\n",
    "L=16\n",
    "x0 = np.linspace(0., L, 2000)\n",
    "x1 = np.linspace(0., L/2., 1000)\n",
    "x2 = np.linspace(L/2., L, 1000)\n",
    "polarity = \"pos\"\n",
    "func=func1\n",
    "t=0.\n",
    "\n",
    "#############################\n",
    "#plot1\n",
    "line_1, = ax[0].plot(x1, func(x1,t,L,polarity)[0],\n",
    "                     '-', color='purple', lw=4, label=\"total incident/reflected wave\")\n",
    "\n",
    "ax[0].plot([L/2.,L/2.], [-2,2],\n",
    "                     'k-', lw=4, label=\"boundary\")\n",
    "\n",
    "#plot params\n",
    "#ax[0].set_title('Amplitude: $A(x,t)$', fontsize=16)\n",
    "#ax[0].set_xlabel('$x$', fontsize=16)\n",
    "ax[0].set_ylim(-2,2)\n",
    "ax[0].set_xlim(min(x1),max(x2))\n",
    "ax[0].grid(True)\n",
    "ax[0].legend(loc=1, mode=\"expand\", ncol=2, fontsize=16)\n",
    "ax[0].yaxis.set_major_locator(MultipleLocator(1))\n",
    "plt.setp(ax[0].get_xticklabels(), visible=False)\n",
    "plt.setp(ax[0].get_yticklabels(), fontsize=14)\n",
    "\n",
    "#############################\n",
    "#plot2\n",
    "y_max = max(func(x1,t,L,polarity)[0])*3\n",
    "\n",
    "ax[1].plot([L/2.,L/2.], [-2,2],\n",
    "                     'k-', lw=4)\n",
    "\n",
    "line_3, = ax[1].plot(x0, func(x0,t,L,polarity)[1],\n",
    "                     'r-.', lw=2, label=\"incident wave component\")\n",
    "\n",
    "line_2, = ax[1].plot(x0, func(x0,t,L,polarity)[2],\n",
    "                     'b--', lw=2, label=\"reflected wave component\")\n",
    "\n",
    "\n",
    "#plot params\n",
    "ax[1].set_xlabel('$x$', fontsize=16)\n",
    "ax[1].set_ylim(-2,2)\n",
    "ax[1].set_xlim(min(x1),max(x2))\n",
    "ax[1].grid(True)\n",
    "ax[1].legend(loc=1, mode=\"expand\", ncol=2, fontsize=16)\n",
    "ax[1].yaxis.set_major_locator(MultipleLocator(1))\n",
    "plt.setp(ax[1].get_xticklabels(), fontsize=14)\n",
    "plt.setp(ax[1].get_yticklabels(), fontsize=14)\n",
    "\n",
    "#Define plot updater\n",
    "###############################################\n",
    "###############################################\n",
    "def update(func,t,polarity):\n",
    "    #plot1\n",
    "    #############################\n",
    "    line_1.set_ydata(func(x1,t,L,polarity)[0])\n",
    "    line_2.set_ydata(func(x0,t,L,polarity)[2])\n",
    "    line_3.set_ydata(func(x0,t,L,polarity)[1])\n",
    "    \n",
    "    fig.canvas.draw_idle()\n",
    "    return\n",
    "\n",
    "\n",
    "#Define control elements\n",
    "###############################################\n",
    "###############################################\n",
    "s1=widgets.Dropdown(\n",
    "    options=[('function-1', func1),('function-2', func2),('function-3', func3),('function-4', func4)],\n",
    "    value=func4,\n",
    "    description='Function:')\n",
    "\n",
    "\n",
    "s1_1=widgets.Dropdown(\n",
    "    options=[('open boundary', \"pos\"),('fixed boundary', \"neg\")],\n",
    "    value=\"pos\",\n",
    "    description='Boundary:')\n",
    "\n",
    "\n",
    "s2=widgets.IntSlider(\n",
    "    min=0,\n",
    "    max=L*10,\n",
    "    step=1.,\n",
    "    value=0.,\n",
    "    layout=Layout(width='600px'),\n",
    "    description='$t$',\n",
    "    style = {'description_width': 'initial'})\n",
    "\n",
    "\n",
    "#Connect controls to plot\n",
    "###############################################\n",
    "###############################################\n",
    "out = interactive_output(update, {'func': s1, 'polarity': s1_1, 't': s2})\n",
    "\n",
    "\n",
    "#Set layout\n",
    "###############################################\n",
    "###############################################\n",
    "box_layout = Layout(display='flex', flex_flow='row', justify_content='space-between', align_items='center')\n",
    "\n",
    "\n",
    "#Display output\n",
    "###############################################\n",
    "###############################################\n",
    "d = display(HBox([s1, s1_1, s2], layout=box_layout))"
   ]
  },
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   "metadata": {},
   "source": [
    "<hr style=\"height: 1px;\">\n",
    "\n",
    "<h2>About the Visualization</h2>\n",
    "\n",
    "<font size=\"3\"><b>Plot:</b> This plot shows the reflection of an incident wave at a boundary (black vertical line). Reflection can be modeled as the superposition of identical waves traveling towards each other. \n",
    "<ul>\n",
    "    <li>(purple line, upper plot) the superposition of incident and reflected wave components</li>\n",
    "    <li>(black vertical line) the boundary</li>\n",
    "    <li>(red dot-dashed line, lower plot) the incident wave component $f_{i}(x,t)$</li>\n",
    "    <li>(blue dashed line, lower plot) the reflected (counter-propagating) wave component $f_{r}(x,t)$</li>\n",
    "    <li>The boundary condition determines \"how\" the incident wave component (red) and reflected wave component (blue) are superposed (either with positive or negative polarity)</li>\n",
    "</ul>\n",
    "</font>\n",
    "\n",
    "<br/>\n",
    "<font size=\"3\"><b>Drop-down and Sliders:</b>\n",
    "<ul>\n",
    "    <li>Function: select a function from the drop-down menu.</li>\n",
    "    <li>Boundary: choose the boundary condition (either open or fixed)</li>\n",
    "    <li>$t$: vary the time to display the functions advancing towards each other</li>\n",
    "</ul>\n",
    "</font>\n",
    "\n",
    "<br/>\n",
    "\n",
    "<hr style=\"height: 1px;\">\n",
    "\n",
    "<h2>Exploration</h2>\n",
    "\n",
    "<font size=\"3\">Consider the following questions and possible actions:\n",
    "<ul>\n",
    "    <li>What do you expect the superposition of different waveforms to look like?</li>\n",
    "</ul>      \n",
    "</font>\n",
    "\n",
    "<br/>\n",
    "\n",
    "<hr style=\"height: 1px;\">\n",
    "\n",
    "<h2>Viewing the Code</h2>\n",
    "<br/>\n",
    "<font size=\"3\">You are encouraged to click the button below to view the source code. You can alter the code and rerun it within this notebook, or download the notebook itself and run the code locally on your own machine.</font>"
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