ConcreteCodeIpython.ipynb

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   "cell_type": "code",
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       "[]"
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "from scipy.io import loadmat\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import glob\n",
    "%matplotlib notebook\n",
    "\n",
    "data=[]\n",
    "TestData=[]\n",
    "NewTrainOne=[]\n",
    "NewTrainTwo=[]\n",
    "FileNames= glob.glob(\"*.mat\") #  # loading data 1\n",
    "TestFileName=glob.glob(\"testData/*.mat\") # loading data 2\n",
    "\n",
    "[data.append(loadmat(f,squeeze_me=True, struct_as_record=False)) for f in FileNames]  #loading all the data in the file\n",
    "[TestData.append(loadmat(f,squeeze_me=True, struct_as_record=False)) for f in TestFileName]\n",
    "\n",
    "## loading new data\n",
    "NewTrainingData1=glob.glob(\"Meta11/*.mat\")\n",
    "NewTrainingData2=glob.glob(\"Meta12/*.mat\")\n",
    "[NewTrainOne.append(load(f,squeeze_me=True, struct_as_record=False)) for f in NewTrainingData1]\n",
    "[NewTrainTwo.append(load(f,squeeze_me=True, struct_as_record=False)) for f in NewTrainingData2]"
   ]
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  {
   "cell_type": "markdown",
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   "source": [
    "The length of actuator signal is equals to length of the cross talk, we will use actuator signal length to zero pad the actuator signal. Frequency of actuation and sampling rate can be obtained as:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
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   "source": [
    "frequency=data[0]['setup'].signal_definition.frequency1\n",
    "# sampling rate of the signal\n",
    "sampling_rate=data[0]['setup'].sampling_rate\n",
    "#####################################################################\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we know the sampling frequency and driving frequency of the signal. The cross talk in the sensor signal will be zeropadded with length equal to length of the 5 cycle burst of actuator signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "crosstalk=[]\n",
    "frequency=[]\n",
    "sampling_rate=[]\n",
    "for signals in data:\n",
    "    frequency.append(signals['setup'].signal_definition.frequency1)\n",
    "    sampling_rate.append(signals['setup'].sampling_rate)\n",
    "    crosstalk.append(5/(signals['setup'].signal_definition.frequency1)* (signals['setup'].sampling_rate))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None, None, None, None, None]"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in range(5):\n",
    "    data[i]['s0'][1:int(crosstalk[i])]=0  #training data\n",
    "    TestData[i]['s0'][1:int(crosstalk[i])]=0  # test data\n",
    "    \n",
    "SensorData=list()\n",
    "ActuatorData=list()\n",
    "\n",
    "[SensorData.append(signal['s0']) for signal in data ]  # sensor data arranged in list\n",
    "[ActuatorData.append(signal['a0']) for signal in data]  # Actuator data arrange in list\n",
    "\n",
    "TestSensorData=list()\n",
    "TestActuatorData=list()\n",
    "\n",
    "[TestSensorData.append(signal['s0']) for signal in TestData ]  # Test data  for sensor  arranged in list\n",
    "[TestActuatorData.append(signal['a0']) for signal in TestData]  # test data for actuator  arrange in list\n",
    "   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true
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   "source": [
    "def DynamicTimeWarping(x,y):\n",
    "    DTW={}\n",
    "    len1=len(x)\n",
    "    len2=len(y)\n",
    "    for i in range(len1):\n",
    "        DTW[(i,-1)]=float('inf')\n",
    "    \n",
    "    for j in range(len2):\n",
    "        DTW[(-1,j)]=float('inf')\n",
    "    DTW[(-1,-1)]=0\n",
    "    for i in range(len1):\n",
    "        for j in range(len2):\n",
    "            \n",
    "            DistTemp= (x[i]-y[j])**2\n",
    "            DTW[(i,j)]= DistTemp + min(DTW[(i-1,j-1)], DTW[(i-1,j)], DTW[(i,j-1)])\n",
    "    return(DTW[(len1-1,len2-1)])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use Keras to  code sparse encoder to extract feature from LambWaves. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
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     "text": [
      "c:\\miniconda3\\lib\\site-packages\\ipykernel\\__main__.py:23: UserWarning: Update your `Model` call to the Keras 2 API: `Model(inputs=Tensor(\"in..., outputs=Tensor(\"de...)`\n",
      "c:\\miniconda3\\lib\\site-packages\\ipykernel\\__main__.py:26: UserWarning: Update your `Model` call to the Keras 2 API: `Model(inputs=Tensor(\"in..., outputs=Tensor(\"de...)`\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/50\n",
      "10/10 [==============================] - 1s - loss: 159.8511     \n",
      "Epoch 2/50\n",
      "10/10 [==============================] - 0s - loss: 101.7649     \n",
      "Epoch 3/50\n",
      "10/10 [==============================] - 0s - loss: 36.3315     \n",
      "Epoch 4/50\n",
      "10/10 [==============================] - 0s - loss: 13.3895     \n",
      "Epoch 5/50\n",
      "10/10 [==============================] - 0s - loss: 7.5405     \n",
      "Epoch 6/50\n",
      "10/10 [==============================] - 0s - loss: 5.7474     \n",
      "Epoch 7/50\n",
      "10/10 [==============================] - 0s - loss: 5.6287     \n",
      "Epoch 8/50\n",
      "10/10 [==============================] - 0s - loss: 5.0217     \n",
      "Epoch 9/50\n",
      "10/10 [==============================] - 0s - loss: 4.2118     \n",
      "Epoch 10/50\n",
      "10/10 [==============================] - 0s - loss: 5.4837     \n",
      "Epoch 11/50\n",
      "10/10 [==============================] - 0s - loss: 12.0617    \n",
      "Epoch 12/50\n",
      "10/10 [==============================] - 0s - loss: 11.6493     \n",
      "Epoch 13/50\n",
      "10/10 [==============================] - 0s - loss: 11.2805     \n",
      "Epoch 14/50\n",
      "10/10 [==============================] - 0s - loss: 8.0212     \n",
      "Epoch 15/50\n",
      "10/10 [==============================] - 0s - loss: 4.2007     \n",
      "Epoch 16/50\n",
      "10/10 [==============================] - 0s - loss: 3.0493     \n",
      "Epoch 17/50\n",
      "10/10 [==============================] - 0s - loss: 2.6240     \n",
      "Epoch 18/50\n",
      "10/10 [==============================] - 0s - loss: 2.3505     \n",
      "Epoch 19/50\n",
      "10/10 [==============================] - 0s - loss: 2.4459     \n",
      "Epoch 20/50\n",
      "10/10 [==============================] - 0s - loss: 2.6175     \n",
      "Epoch 21/50\n",
      "10/10 [==============================] - 0s - loss: 3.3171     \n",
      "Epoch 22/50\n",
      "10/10 [==============================] - 0s - loss: 3.2647     \n",
      "Epoch 23/50\n",
      "10/10 [==============================] - 0s - loss: 2.3183     \n",
      "Epoch 24/50\n",
      "10/10 [==============================] - 0s - loss: 2.1428     \n",
      "Epoch 25/50\n",
      "10/10 [==============================] - 0s - loss: 2.3760     \n",
      "Epoch 26/50\n",
      "10/10 [==============================] - 0s - loss: 1.9022     \n",
      "Epoch 27/50\n",
      "10/10 [==============================] - 0s - loss: 2.0359     \n",
      "Epoch 28/50\n",
      "10/10 [==============================] - 0s - loss: 1.9699     \n",
      "Epoch 29/50\n",
      "10/10 [==============================] - 0s - loss: 2.0127     \n",
      "Epoch 30/50\n",
      "10/10 [==============================] - 0s - loss: 1.9047     \n",
      "Epoch 31/50\n",
      "10/10 [==============================] - 0s - loss: 1.7676     \n",
      "Epoch 32/50\n",
      "10/10 [==============================] - 0s - loss: 1.9278     \n",
      "Epoch 33/50\n",
      "10/10 [==============================] - 0s - loss: 2.6854     \n",
      "Epoch 34/50\n",
      "10/10 [==============================] - 0s - loss: 2.3000     \n",
      "Epoch 35/50\n",
      "10/10 [==============================] - 0s - loss: 1.9604     \n",
      "Epoch 36/50\n",
      "10/10 [==============================] - 0s - loss: 2.4745     \n",
      "Epoch 37/50\n",
      "10/10 [==============================] - 0s - loss: 2.7982     \n",
      "Epoch 38/50\n",
      "10/10 [==============================] - 0s - loss: 3.3074     \n",
      "Epoch 39/50\n",
      "10/10 [==============================] - 0s - loss: 3.0384     \n",
      "Epoch 40/50\n",
      "10/10 [==============================] - 0s - loss: 6.5894     \n",
      "Epoch 41/50\n",
      "10/10 [==============================] - 0s - loss: 5.4260     \n",
      "Epoch 42/50\n",
      "10/10 [==============================] - 0s - loss: 5.0669     \n",
      "Epoch 43/50\n",
      "10/10 [==============================] - 0s - loss: 8.9694     \n",
      "Epoch 44/50\n",
      "10/10 [==============================] - 0s - loss: 3.8350     \n",
      "Epoch 45/50\n",
      "10/10 [==============================] - 0s - loss: 2.7492     \n",
      "Epoch 46/50\n",
      "10/10 [==============================] - 0s - loss: 2.9257     \n",
      "Epoch 47/50\n",
      "10/10 [==============================] - 0s - loss: 2.5553     \n",
      "Epoch 48/50\n",
      "10/10 [==============================] - 0s - loss: 2.3896     \n",
      "Epoch 49/50\n",
      "10/10 [==============================] - 0s - loss: 1.8972     \n",
      "Epoch 50/50\n",
      "10/10 [==============================] - 0s - loss: 2.2043     \n"
     ]
    }
   ],
   "source": [
    "########################\n",
    "TotalData=SensorData+TestSensorData\n",
    "TotalData=np.asarray(TotalData)\n",
    "#####################################\n",
    "#####################################\n",
    "from keras.layers import Input, Dense\n",
    "from keras.models import Model\n",
    "#from keras.optimizers import Adam\n",
    "from keras import regularizers\n",
    "\n",
    "np.random.seed(7)\n",
    "SensorData=np.asarray(SensorData) # converting list into array (training data)\n",
    "TestSensorData=  np.asarray(TestSensorData)\n",
    "InputSignal=SensorData[0]\n",
    "actual_signal_len=len(InputSignal)\n",
    "encoding_dim=100 # This going to be size of our encoded representation\n",
    "#this returns a tensor\n",
    "inputs = Input(shape=(actual_signal_len,))\n",
    "encoded=Dense(encoding_dim,activation='relu',activity_regularizer=regularizers.l1(10e-5))(inputs)\n",
    "decoded=Dense(actual_signal_len)(encoded)\n",
    "\n",
    "# this model maps an input to its encoded representation\n",
    "encoder = Model(input=inputs, output=encoded)\n",
    "\n",
    "## this model maps an input to its reconstruction\n",
    "autoencoder= Model(input = inputs, output= decoded)\n",
    "#we'll configure our model to use a mean squarred error loss, and the Adam optimizer\n",
    "# we also train autoencoder for 50 epochs\n",
    "autoencoder.compile(optimizer='adam', loss='mse')\n",
    "autoencoder.fit(TotalData, TotalData, epochs=100, batch_size=1)\n",
    "\n",
    "#######################\n",
    "#Encode the images\n",
    "encoded_signal= encoder.predict(SensorData)\n",
    "EncodedTestData= encoder.predict(TestSensorData)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "In the above code we trained an sparse autoencoder for 100 epochs, the encoded signals \"*encoded_signal* \" and the *gaps*, variable will be fitted in a linear regression. The figures below show the encoded training signals *encoded_signal* and *EncodedTestData*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
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   "outputs": [
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       "        }\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1ea8f1c5f98>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from matplotlib.pyplot import cm\n",
    "c=cm.rainbow(np.linspace(0,1,5))\n",
    "labels=['no gap','0.2 mm gap','0.3 mm gap','0.4 mm gap','0.1 mm gap']\n",
    "#%matplotlib notebook\n",
    "plt.figure()\n",
    "for c,signal,l in zip(c,encoded_signal,labels):\n",
    "    plt.plot(signal,color=c,label=l)\n",
    "plt.xlabel('Sampling Number')\n",
    "plt.ylabel('Volts')\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
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     "output_type": "display_data"
    },
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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x1ea92184a20>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c=cm.rainbow(np.linspace(0,1,5))\n",
    "labels=['no gap','0.2 mm gap','0.3 mm gap','0.4 mm gap','0.1 mm gap']\n",
    "#%matplotlib notebook\n",
    "plt.figure()\n",
    "for c,signal,l in zip(c,EncodedTestData,labels):\n",
    "    plt.plot(signal,color=c,label=l)\n",
    "\n",
    "plt.xlabel('Sampling Number')\n",
    "plt.ylabel('Volts')\n",
    "plt.legend()\n",
    "plt.title(\"Test Data\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "#DynamicWarp=[]\n",
    "#DynamicWarpTest=[]\n",
    "#[DynamicWarp.append(DynamicTimeWarping(encoded_signal[0],signal)) for signal in encoded_signal]\n",
    "#[DynamicWarpTest.append(DynamicTimeWarping(EncodedTestData[0],signal)) for signal in EncodedTestData]\n",
    "#gaps=[0,0.2,0.3,0.4,0.1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Considering \"0\" mm as a baseline data we estimate the Euclidean distance between encoded signals. *dist1* will be used as training data to fit the linear regression. Similalry, *dist2* will be used to validate the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "dist1=[]\n",
    "dist2=[]\n",
    "for x,y in zip(encoded_signal,EncodedTestData):\n",
    "    dist1.append(np.linalg.norm(encoded_signal[0]-x))\n",
    "    dist2.append(np.linalg.norm(EncodedTestData[0]-y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The regression coefficients are as:[-0.0241117, 0.0023210]\n"
     ]
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "gaps=[0,0.2,0.3,0.4,0.1]\n",
    "gaps=np.asarray(gaps)\n",
    "dist1=np.asarray(dist1)\n",
    "dist2=np.asarray(dist2)\n",
    "#lets create a regression object\n",
    "regr= linear_model.LinearRegression(fit_intercept=True,normalize=True)\n",
    "#fitting the linear regression\n",
    "regr.fit(dist1.reshape(5,1),gaps.reshape(5,1))\n",
    "print(\"The regression coefficients are as:[%.7f, %.7f]\" % (regr.intercept_ ,  regr.coef_))\n",
    "# The final prediction of the test data\n",
    "TrainingGaps=regr.predict(dist1.reshape(5,1))\n",
    "PredictionGaps=regr.predict(dist2.reshape(5,1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Now lets do a predicted v/s actual plot for predicted data sets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
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       "        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",
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       "    this.format_dropdown = undefined;\n",
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       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
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       "    this._init_toolbar(this);\n",
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       "    var fig = this;\n",
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       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
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       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
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       "\n",
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       "\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",
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       "    this.header = titletext[0];\n",
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       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
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       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
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       "\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",
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       "\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 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig=plt.figure()\n",
    "ax1=fig.add_subplot(111)\n",
    "ax1.scatter(gaps,TrainingGaps,s=20,c='red',marker='s',label='Training Data Predictions')\n",
    "ax1.scatter(gaps,PredictionGaps,s=20,c='black',marker='o',label='Test Data prediction')\n",
    "plt.xlabel('Actual Gap')\n",
    "plt.ylabel('Predicted Gap')\n",
    "plt.legend(loc='upper left');\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The figure below displays the relationship between gaps and damage metric (Euclidean distance betweeen encoded signals)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\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",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var 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);\n",
       "        canvas.attr('height', height);\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'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\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;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    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 + '\">');\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 dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\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": [
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.scatter(dist1,gaps,s=20,c='red',marker='s')\n",
    "plt.xlabel('Euclidean distance between two signal')\n",
    "plt.ylabel('Gaps')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}