diff --git a/.ipynb_checkpoints/DryVR_Notebook-checkpoint.ipynb b/.ipynb_checkpoints/DryVR_Notebook-checkpoint.ipynb
index 2fd6442..eb9eac2 100644
--- a/.ipynb_checkpoints/DryVR_Notebook-checkpoint.ipynb
+++ b/.ipynb_checkpoints/DryVR_Notebook-checkpoint.ipynb
@@ -1,6 +1,973 @@
 {
- "cells": [],
- "metadata": {},
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from src.core.dryvrmain import verify\n",
+    "%matplotlib notebook\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "IndentationError",
+     "evalue": "unindent does not match any outer indentation level (<ipython-input-7-7dc114d23758>, line 11)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-7-7dc114d23758>\"\u001b[0;36m, line \u001b[0;32m11\u001b[0m\n\u001b[0;31m    time.sleep(1)\u001b[0m\n\u001b[0m                 ^\u001b[0m\n\u001b[0;31mIndentationError\u001b[0m\u001b[0;31m:\u001b[0m unindent does not match any outer indentation level\n"
+     ]
+    }
+   ],
+   "source": [
+    "from scipy.integrate import odeint\n",
+    "import numpy as np \n",
+    "import time\n",
+    "\n",
+    "def thermo_dynamic(y,t,rate):\n",
+    "    dydt = rate*y\n",
+    "    return dydt\n",
+    "\n",
+    "def TC_Simulate(Mode,initialCondition,time_bound):\n",
+    "    time_step = 0.05;\n",
+    "    time.sleep(1)\n",
+    "    time_bound = float(time_bound)\n",
+    "    initial = [float(tmp)  for tmp in initialCondition]\n",
+    "    number_points = int(np.ceil(time_bound/time_step))\n",
+    "    t = [i*time_step for i in range(0,number_points)]\n",
+    "    if t[-1] != time_step:\n",
+    "        t.append(time_bound)\n",
+    "\n",
+    "    y_initial = initial[0]\n",
+    "\n",
+    "    if Mode == 'On':\n",
+    "        rate = 0.1\n",
+    "    elif Mode == 'Off':\n",
+    "        rate = -0.1\n",
+    "    else:\n",
+    "        print('Wrong Mode name!')\n",
+    "    sol = odeint(thermo_dynamic,y_initial,t,args=(rate,),hmax = time_step)\n",
+    "\n",
+    "    # Construct the final output\n",
+    "    trace = []\n",
+    "    for j in range(len(t)):\n",
+    "        #print t[j], current_psi\n",
+    "        tmp = []\n",
+    "        tmp.append(t[j])\n",
+    "        tmp.append(sol[j,0])\n",
+    "        trace.append(tmp)\n",
+    "    return trace"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "args = {\n",
+    "    \"vertex\" : [\"On\",\"Off\",\"On\"],\n",
+    "    \"edge\":[[0,1],[1,2]],\n",
+    "    \"variables\":[\"temp\"],\n",
+    "    \"guards\":[\"And(t>1.0,t<=1.1)\",\"And(t>1.0,t<=1.1)\"],\n",
+    "    \"initialSet\":[[75.0],[76.0]],\n",
+    "    \"unsafeSet\":\"@On:temp>91@Off:temp>91\",\n",
+    "    \"timeHorizon\":3.5,\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "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, 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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": {
+      "text/html": [
+       "<img 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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "transit time 1.05 remain time 2.45\n",
+      "transit time 1.05 remain time 1.4\n",
+      "transit time 1.4 remain time 0.0\n",
+      "Verification Begin\n",
+      "===============================================\n",
+      "Mode: 0\n",
+      "stack size: 1\n",
+      "remainTime: 3.5\n",
+      "\n",
+      "Lower Bound: [75.0]\n",
+      "Upper Bound: [76.0]\n",
+      "Delta: [0.5]\n",
+      "\n",
+      "current mode label: On\n",
+      "Off 1.0 [[82.88456685675527], [85.26238230178342]] And(t>1.0,t<=1.1)\n",
+      "Mode 0 check bloated tube safe\n",
+      "Child exist in cur mode inital 1 is curModeStack Now\n",
+      "===============================================\n",
+      "Mode: 1\n",
+      "stack size: 1\n",
+      "remainTime: 2.5\n",
+      "\n",
+      "Lower Bound: [82.88456685675527]\n",
+      "Upper Bound: [85.26238230178342]\n",
+      "Delta: [1.1889077225140738]\n",
+      "\n",
+      "current mode label: Off\n",
+      "On 1.0 [[73.88049578331416], [77.1441588158632]] And(t>1.0,t<=1.1)\n",
+      "Mode 1 check bloated tube safe\n",
+      "Child exist in cur mode inital 2 is curModeStack Now\n",
+      "===============================================\n",
+      "Mode: 2\n",
+      "stack size: 1\n",
+      "remainTime: 1.5\n",
+      "\n",
+      "Lower Bound: [73.88049578331416]\n",
+      "Upper Bound: [77.1441588158632]\n",
+      "Delta: [1.6318315162745165]\n",
+      "\n",
+      "current mode label: On\n",
+      "Mode 2 check bloated tube safe\n",
+      "No child exist in current initial, pop\n",
+      "back flag safe from 2 to 1\n",
+      "No child in prev mode initial, pop, 1 is curModeStack Now\n",
+      "back flag safe from 1 to 0\n",
+      "No child in prev mode initial, pop, 0 is curModeStack Now\n",
+      "System is Safe!\n",
+      "simulation time 0.0420598983765\n",
+      "verification time 0.522380113602\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<src.core.reachtube.ReachTube instance at 0x117b9d7a0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "verify(args, TC_Simulate)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 2",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.10"
+  }
+ },
  "nbformat": 4,
  "nbformat_minor": 2
 }
diff --git a/DryVR_Notebook.ipynb b/DryVR_Notebook.ipynb
index b59c7f4..6204502 100644
--- a/DryVR_Notebook.ipynb
+++ b/DryVR_Notebook.ipynb
@@ -2,59 +2,62 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from src.core.dryvrmain import verify"
+    "from src.core.dryvrmain import verify\n",
+    "%matplotlib notebook\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
     "from scipy.integrate import odeint\n",
     "import numpy as np \n",
+    "import time\n",
     "\n",
     "def thermo_dynamic(y,t,rate):\n",
-    "\tdydt = rate*y\n",
-    "\treturn dydt\n",
+    "    dydt = rate*y\n",
+    "    return dydt\n",
     "\n",
     "def TC_Simulate(Mode,initialCondition,time_bound):\n",
-    "\ttime_step = 0.05;\n",
-    "\ttime_bound = float(time_bound)\n",
-    "\tinitial = [float(tmp)  for tmp in initialCondition]\n",
-    "\tnumber_points = int(np.ceil(time_bound/time_step))\n",
-    "\tt = [i*time_step for i in range(0,number_points)]\n",
-    "\tif t[-1] != time_step:\n",
-    "\t\tt.append(time_bound)\n",
+    "    time_step = 0.05;\n",
+    "    time.sleep(0.1)\n",
+    "    time_bound = float(time_bound)\n",
+    "    initial = [float(tmp)  for tmp in initialCondition]\n",
+    "    number_points = int(np.ceil(time_bound/time_step))\n",
+    "    t = [i*time_step for i in range(0,number_points)]\n",
+    "    if t[-1] != time_step:\n",
+    "        t.append(time_bound)\n",
     "\n",
-    "\ty_initial = initial[0]\n",
+    "    y_initial = initial[0]\n",
     "\n",
-    "\tif Mode == 'On':\n",
-    "\t\trate = 0.1\n",
-    "\telif Mode == 'Off':\n",
-    "\t\trate = -0.1\n",
-    "\telse:\n",
-    "\t\tprint('Wrong Mode name!')\n",
-    "\tsol = odeint(thermo_dynamic,y_initial,t,args=(rate,),hmax = time_step)\n",
+    "    if Mode == 'On':\n",
+    "        rate = 0.1\n",
+    "    elif Mode == 'Off':\n",
+    "        rate = -0.1\n",
+    "    else:\n",
+    "        print('Wrong Mode name!')\n",
+    "    sol = odeint(thermo_dynamic,y_initial,t,args=(rate,),hmax = time_step)\n",
     "\n",
-    "\t# Construct the final output\n",
-    "\ttrace = []\n",
-    "\tfor j in range(len(t)):\n",
-    "\t\t#print t[j], current_psi\n",
-    "\t\ttmp = []\n",
-    "\t\ttmp.append(t[j])\n",
-    "\t\ttmp.append(sol[j,0])\n",
-    "\t\ttrace.append(tmp)\n",
-    "\treturn trace"
+    "    # Construct the final output\n",
+    "    trace = []\n",
+    "    for j in range(len(t)):\n",
+    "        #print t[j], current_psi\n",
+    "        tmp = []\n",
+    "        tmp.append(t[j])\n",
+    "        tmp.append(sol[j,0])\n",
+    "        trace.append(tmp)\n",
+    "    return trace"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -71,16 +74,808 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 11,
    "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, 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\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\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": {
+      "text/html": [
+       "<img 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\" width=\"640\">"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "transit time 1.05 remain time 2.45\n",
-      "transit time 1.0 remain time 1.45\n",
-      "transit time 1.45 remain time 0.0\n",
+      "transit time 1.1 remain time 2.4\n",
+      "transit time 1.05 remain time 1.35\n",
+      "transit time 1.35 remain time 0.0\n",
       "Verification Begin\n",
       "===============================================\n",
       "Mode: 0\n",
@@ -92,7 +887,7 @@
       "Delta: [0.5]\n",
       "\n",
       "current mode label: On\n",
-      "Off 1.0 [[82.88479750557151], [84.83713438129338]] And(t>1.0,t<=1.1)\n",
+      "Off 1.0 [[82.88456683811637], [85.26238232238468]] And(t>1.0,t<=1.1)\n",
       "Mode 0 check bloated tube safe\n",
       "Child exist in cur mode inital 1 is curModeStack Now\n",
       "===============================================\n",
@@ -100,12 +895,12 @@
       "stack size: 1\n",
       "remainTime: 2.5\n",
       "\n",
-      "Lower Bound: [82.88479750557151]\n",
-      "Upper Bound: [84.83713438129338]\n",
-      "Delta: [0.9761684378609345]\n",
+      "Lower Bound: [82.88456683811637]\n",
+      "Upper Bound: [85.26238232238468]\n",
+      "Delta: [1.1889077421341554]\n",
       "\n",
       "current mode label: Off\n",
-      "On 1.0 [[73.88070144522607], [76.76017197110366]] And(t>1.0,t<=1.1)\n",
+      "On 1.0 [[73.88049583544938], [77.14415877097372]] And(t>1.0,t<=1.1)\n",
       "Mode 1 check bloated tube safe\n",
       "Child exist in cur mode inital 2 is curModeStack Now\n",
       "===============================================\n",
@@ -113,9 +908,9 @@
       "stack size: 1\n",
       "remainTime: 1.5\n",
       "\n",
-      "Lower Bound: [73.88070144522607]\n",
-      "Upper Bound: [76.76017197110366]\n",
-      "Delta: [1.4397352629387967]\n",
+      "Lower Bound: [73.88049583544938]\n",
+      "Upper Bound: [77.14415877097372]\n",
+      "Delta: [1.6318314677621686]\n",
       "\n",
       "current mode label: On\n",
       "Mode 2 check bloated tube safe\n",
@@ -125,9 +920,19 @@
       "back flag safe from 1 to 0\n",
       "No child in prev mode initial, pop, 0 is curModeStack Now\n",
       "System is Safe!\n",
-      "simulation time 0.0378980636597\n",
-      "verification time 0.317549943924\n"
+      "simulation time 0.343491077423\n",
+      "verification time 3.9116358757\n"
      ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<src.core.reachtube.ReachTube instance at 0x1181dcea8>"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
diff --git a/output/Traj.txt b/output/Traj.txt
index 466882a..1ba73f2 100644
--- a/output/Traj.txt
+++ b/output/Traj.txt
@@ -1,73 +1,73 @@
-0.0 75.36513494111749
-0.05 75.74290472019997
-0.1 76.12256805264495
-0.15 76.50413412129275
-0.2 76.8876125779359
-0.25 77.27301334178641
-0.3 77.66034593510459
-0.35 78.04962003929238
-0.4 78.44084538715921
-0.45 78.83403176075774
-0.5 79.2291889893958
-0.55 79.6263269518851
-0.6 80.02545557669117
-0.65 80.42658484205006
-0.7 80.82972477621979
-0.75 81.23488545772014
-0.8 81.64207701558806
-0.85 82.05130962963354
-0.9 82.46259353069325
-0.95 82.87593900088615
-1.0 83.29135637387051
-1.05 83.70885603510236
-1.1 84.12844842209492
-1.1 84.55014402467971
-1.15 84.12844790272061
-1.2 83.70885503178842
-1.25 83.29135526422652
-1.3 82.87593802293648
-1.35 82.46259255970634
-1.4 82.0513086656841
-1.45 81.64207605667998
-1.5 81.23488450289511
-1.55 80.82972382600354
-1.6 80.42658389656496
-1.65 80.02545463591274
-1.7 79.62632601579885
-1.75 79.22918805798723
-1.8 78.83403083400262
-1.85 78.44084446489346
-1.9 78.04961912098125
-1.95 77.66034502161216
-2.0 77.27301243491343
-2.05 76.88761167755021
-2.1 76.50413311448351
-2.1 76.12256715872924
-2.15 76.50413358731487
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-2.25 77.27301347130742
-2.3 77.6603459505988
-2.35 78.04962005661837
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-2.55 79.62632697191884
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-2.95 82.87593902175118
-3.0 83.29135639484016
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-3.1 84.12844844327533
-3.15 84.55014404596632
-3.2 84.9739534066621
-3.25 85.39988712061879
-3.3 85.82795583620141
-3.35 86.25817025515012
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+0.0 75.24412111137498
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+1.2 81.91955884152385
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+1.5 79.49846999154036
+1.55 79.10196971830106
+1.6 78.70744699842905
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+1.7 77.92429481562
+1.75 77.53564577383167
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+1.85 76.76415320801647
+1.9 76.38129039663538
+1.95 76.00033712149241
+2.0 75.62128385873584
+2.05 75.24412113201433
+2.05 74.8688395122401
+2.1 75.244121596894
+2.15 75.62128476583325
+2.2 76.00033813992002
+2.25 76.38129130965865
+2.3 76.76415412757744
+2.35 77.14893605345601
+2.4 77.53564670494087
+2.45 77.92429575075286
+2.5 78.31489290852511
+2.55 78.70744794283736
+2.6 79.10197066744756
+2.65 79.49847094544012
+2.7 79.8969586893423
+2.75 80.2974438613739
+2.8 80.69993647368553
+2.85 81.10444658861223
+2.9 81.51098431892787
+2.95 81.91955982809682
+3.0 82.33018333052813
+3.05 82.74286509183072
+3.1 83.15761542907016
+3.15 83.57444471102646
+3.2 83.99336335845337
+3.25 84.41438184433886
+3.3 84.83751069416705
+3.35 85.26276048618121
+3.4 85.6901418516483
+3.45 86.11966547512472
+3.5 86.55134209472342
diff --git a/playground/.ipynb_checkpoints/GraphProgressPlotter-checkpoint.ipynb b/playground/.ipynb_checkpoints/GraphProgressPlotter-checkpoint.ipynb
index a90a622..6b27e22 100644
--- a/playground/.ipynb_checkpoints/GraphProgressPlotter-checkpoint.ipynb
+++ b/playground/.ipynb_checkpoints/GraphProgressPlotter-checkpoint.ipynb
@@ -2,16 +2,9 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Warning: Cannot change to a different GUI toolkit: notebook. Using nbagg instead.\n"
-     ]
-    },
     {
      "data": {
       "application/javascript": [
@@ -795,7 +788,7 @@
     {
      "data": {
       "text/html": [
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\" 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\" width=\"640\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -803,6 +796,14 @@
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[('A', 'C'), ('E', 'C')]\n",
+      "[]\n"
+     ]
     }
    ],
    "source": [
@@ -815,16 +816,17 @@
     "ax = fig.add_subplot(111)\n",
     "\n",
     "def draw(red_edges):\n",
+    "    ax.clear()\n",
     "    print(red_edges)\n",
     "    G = nx.DiGraph()\n",
     "    G.add_edges_from(\n",
     "        [('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),\n",
-    "         ('B', 'H'), ('B', 'G'), ('B', 'F'), ('C', 'G')])\n",
+    "         ('B', 'H'), ('B', 'G'), ('B', 'F')])\n",
     "\n",
     "    val_map = {'A': 1.0,\n",
     "               'D': 0.5714285714285714,\n",
     "               'H': 0.0}\n",
-    "    red_edges = [('A', 'C'), ('E', 'C')]\n",
+    "#     red_edges = [('A', 'C'), ('E', 'C')]\n",
     "\n",
     "    values = [val_map.get(node, 0.25) for node in G.nodes()]\n",
     "\n",
@@ -839,13 +841,13 @@
     "    nx.draw_networkx_nodes(G, pos, cmap=plt.get_cmap('jet'), node_size = 500)\n",
     "    nx.draw_networkx_labels(G, pos)\n",
     "    nx.draw_networkx_edges(G, pos, edgelist=red_edges, edge_color='r', arrows=True)\n",
-    "    nx.draw_networkx_edges(G, pos, edgelist=black_edges, arrows=False)\n",
+    "    nx.draw_networkx_edges(G, pos, edgelist=black_edges, arrows=True)\n",
     "\n",
-    "plt.show()    \n",
     "red_edges_1 = [('A', 'C'), ('E', 'C')]\n",
     "red_edges_2 = []\n",
     "draw(red_edges_1)\n",
-    "ax.clear()\n",
+    "fig.canvas.draw()\n",
+    "time.sleep(2)\n",
     "draw(red_edges_2)\n",
     "\n"
    ]
diff --git a/playground/GraphProgressPlotter.ipynb b/playground/GraphProgressPlotter.ipynb
index df0ea0a..4333d26 100644
--- a/playground/GraphProgressPlotter.ipynb
+++ b/playground/GraphProgressPlotter.ipynb
@@ -2,16 +2,9 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Warning: Cannot change to a different GUI toolkit: notebook. Using nbagg instead.\n"
-     ]
-    },
     {
      "data": {
       "application/javascript": [
@@ -795,7 +788,7 @@
     {
      "data": {
       "text/html": [
-       "<img 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\" 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+       "<img 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\" width=\"640\">"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -803,14 +796,6 @@
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[('A', 'C'), ('E', 'C')]\n",
-      "[]\n"
-     ]
     }
    ],
    "source": [
@@ -822,12 +807,13 @@
     "fig = plt.figure()\n",
     "ax = fig.add_subplot(111)\n",
     "\n",
-    "def draw(red_edges):\n",
-    "    print(red_edges)\n",
-    "    G = nx.DiGraph()\n",
-    "    G.add_edges_from(\n",
-    "        [('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),\n",
-    "         ('B', 'H'), ('B', 'G'), ('B', 'F'), ('C', 'G')])\n",
+    "def draw(red_edges, G, pos):\n",
+    "    ax.clear()\n",
+    "#     print(red_edges)\n",
+    "#     G = nx.DiGraph()\n",
+    "#     G.add_edges_from(\n",
+    "#         [('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),\n",
+    "#          ('B', 'H'), ('B', 'G'), ('B', 'F')])\n",
     "\n",
     "    val_map = {'A': 1.0,\n",
     "               'D': 0.5714285714285714,\n",
@@ -843,20 +829,24 @@
     "\n",
     "    # Need to create a layout when doing\n",
     "    # separate calls to draw nodes and edges\n",
-    "    pos = nx.spring_layout(G)\n",
+    "#     pos = nx.spring_layout(G)\n",
     "    nx.draw_networkx_nodes(G, pos, cmap=plt.get_cmap('jet'), node_size = 500)\n",
     "    nx.draw_networkx_labels(G, pos)\n",
     "    nx.draw_networkx_edges(G, pos, edgelist=red_edges, edge_color='r', arrows=True)\n",
-    "    nx.draw_networkx_edges(G, pos, edgelist=black_edges, arrows=False)\n",
-    "    plt.show()    \n",
+    "    nx.draw_networkx_edges(G, pos, edgelist=black_edges, arrows=True)\n",
+    "    fig.canvas.draw()\n",
+    "\n",
+    "G = nx.DiGraph()\n",
+    "G.add_edges_from(\n",
+    "    [('A', 'B'), ('A', 'C'), ('D', 'B'), ('E', 'C'), ('E', 'F'),\n",
+    "     ('B', 'H'), ('B', 'G'), ('B', 'F')])\n",
+    "pos = nx.spring_layout(G)\n",
     "\n",
     "red_edges_1 = [('A', 'C'), ('E', 'C')]\n",
     "red_edges_2 = []\n",
-    "draw(red_edges_1)\n",
-    "fig.canvas.draw()\n",
+    "draw(red_edges_1, G ,pos)\n",
     "time.sleep(2)\n",
-    "ax.clear()\n",
-    "draw(red_edges_2)\n",
+    "draw(red_edges_2, G, pos)\n",
     "\n"
    ]
   },
diff --git a/src/common/utils.py b/src/common/utils.py
index c5e9de1..042624d 100644
--- a/src/common/utils.py
+++ b/src/common/utils.py
@@ -243,3 +243,16 @@ def checkSynthesisInput(data):
 
     if data["bloatingMethod"] == "PW":
         assert 'kvalue' in data, "kvalue need to be provided when bloating method set to PW"
+
+def isIpynb():
+    """
+    Check if the code is running on Ipython notebook
+    """
+    try:
+        cfg = get_ipython().config 
+        if "IPKernelApp" in cfg:
+            return True
+        else:
+            return False
+    except NameError:
+        return False
diff --git a/src/core/dryvrmain.py b/src/core/dryvrmain.py
index c577e14..3b061eb 100644
--- a/src/core/dryvrmain.py
+++ b/src/core/dryvrmain.py
@@ -6,10 +6,11 @@
 
 from src.common.constant import *
 from src.common.io import parseVerificationInputFile, writeReachTubeFile, parseRrtInputFile, writeRrtResultFile
-from src.common.utils import importSimFunction, randomPoint, buildModeStr
+from src.common.utils import importSimFunction, randomPoint, buildModeStr, isIpynb
 from src.core.distance import DistChecker
 from src.core.dryvrcore import *
 from src.core.goalchecker import GoalChecker
+from src.core.graph import Graph
 from src.core.guard import Guard
 from src.core.initialset import InitialSet
 from src.core.initialsetstack import InitialSetStack, GraphSearchNode
@@ -39,6 +40,9 @@ def verify(data, simFunction):
         params.resets
     )
 
+    # Build the progress graph for jupyter notebook
+    progressGraph = Graph(params, isIpynb())
+
     # Make sure the initial mode is specfieid if the graph is dag
     # FIXME should move this part to input check
     # Bolun 02/12/2018
@@ -143,6 +147,8 @@ def verify(data, simFunction):
             print "current mode label:",curLabel
             curSuccessors = graph.successors(curVertex)
             curInitial = [curStack[-1].lowerBound, curStack[-1].upperBound]
+            # Update the progress graph
+            progressGraph.update(buildModeStr(graph, curVertex), curModeStack.bloatedTube[0], curModeStack.remainTime)
 
             if len(curSuccessors) == 0:
                 # If there is not successor
diff --git a/src/core/graph.py b/src/core/graph.py
new file mode 100644
index 0000000..3a0ec47
--- /dev/null
+++ b/src/core/graph.py
@@ -0,0 +1,73 @@
+"""
+This file contains graph class for DryVR
+"""
+import matplotlib.pyplot as plt
+import networkx as nx
+
+
+class Graph():
+    """
+    This is class to plot the progress graph for dryvr's
+    function, it is supposed to display the graph in jupyter
+    notebook and update the graph as dryvr is running
+    """
+    def __init__(self, params, isIpynb):
+        """
+        Guard checker class initialization function.
+
+        Args:
+            params (obj): An object contains the parameter
+            isIpynb (bool): check if the code is running on ipython or not
+        """
+        vertex = []
+        # Build unique identifier for a vertex and mode name
+        for idx,v in enumerate(params.vertex):
+            vertex.append(v+","+str(idx))
+
+        edges = params.edge
+        self.edgeList = []
+        for e in edges:
+            self.edgeList.append((vertex[e[0]], vertex[e[1]]))
+        # Initialize the plot
+        self.fig = plt.figure()
+        self.ax = self.fig.add_subplot(111)
+
+        # Initialize the graph
+        self.G = nx.DiGraph()
+        self.G.add_edges_from(self.edgeList)
+        self.pos = nx.spring_layout(self.G)
+        self.colors = ['green'] * len(self.G.nodes())
+        self.fig.suptitle('', fontsize=10)
+        # Draw the graph when initialize
+        self.draw()
+        if isIpynb:
+            plt.show()
+
+
+
+    def draw(self):
+        """
+        Draw the white-box transition graph.
+        """
+
+        # Delete old plot
+        nx.draw_networkx_nodes(self.G, self.pos, node_color=self.colors, cmap=plt.get_cmap('jet'), node_size = 1000)
+        nx.draw_networkx_labels(self.G, self.pos)
+        nx.draw_networkx_edges(self.G, self.pos, edge_color='b', arrows=True)
+        self.fig.canvas.draw()
+
+    def update(self, curNode, title, remainTime):
+        """
+        update the graph 
+        Args:
+            curNode (str): current vertice dryvr is verifiying
+            title (str): current transition path as the title
+            remainTime (float): remaining time
+        """
+        self.ax.clear()
+        self.colors = ['green'] * len(self.G.nodes())
+        self.colors[list(self.G.nodes()).index(curNode)] = 'red'
+        self.fig.suptitle(title, fontsize=10)
+        self.ax.set_title("remain:"+str(remainTime))
+        self.draw()
+
diff --git a/src/core/reachtube.py b/src/core/reachtube.py
index 16bc0da..b98c957 100644
--- a/src/core/reachtube.py
+++ b/src/core/reachtube.py
@@ -20,8 +20,6 @@ def __init__(self, tube, variables, modes):
         self.tube = tube
         self.variables = variables
         self.modes = modes
-        print(variables)
-        print(modes)
 
         # Build the raw string representation so user can print it