Concrete_NewDataLambWave.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "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",
    "import os\n",
    "%matplotlib notebook\n",
    "NewTrainOne=[]\n",
    "NewTrainTwo=[]\n",
    "#NewTrainingData1=sorted(glob.glob(os.path.join(\"*.mat\")))\n",
    "#NewTrainingData2=glob.glob(\"Metal2/*.mat\")\n",
    "#NewTrainingData10=sorted(NewTrainingData1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test01.mat\n",
      "test02.mat\n",
      "test03.mat\n",
      "test04.mat\n",
      "test05.mat\n",
      "test06.mat\n",
      "test07.mat\n",
      "test08.mat\n",
      "test09.mat\n",
      "test10.mat\n",
      "test11.mat\n",
      "test12.mat\n",
      "test13.mat\n",
      "test14.mat\n",
      "test15.mat\n",
      "test16.mat\n",
      "test17.mat\n",
      "test18.mat\n",
      "test19.mat\n",
      "test20.mat\n",
      "test21.mat\n",
      "test22.mat\n",
      "test23.mat\n",
      "test24.mat\n",
      "test25.mat\n"
     ]
    }
   ],
   "source": [
    "NewTrainingData1=[]\n",
    "NewTrainingData2=[]\n",
    "def key_func(x):\n",
    "        return os.path.split(x)[-1]\n",
    "for data_file1,data_file2 in zip(sorted(os.listdir(\"Metal1/\"),key=key_func),sorted(os.listdir(\"Metal2/\"),key=key_func)):\n",
    "    NewTrainingData1.append(data_file1)\n",
    "    NewTrainingData2.append(data_file2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "folderPath=\"C:/Users/Spandan Mishra/Documents/GitHub/LambWave/Metal1\"\n",
    "[NewTrainOne.append(loadmat(os.path.join(folderPath,f),squeeze_me=True, struct_as_record=False)) for f in NewTrainingData1]\n",
    "[NewTrainTwo.append(loadmat(os.path.join(folderPath,f),squeeze_me=True, struct_as_record=False)) for f in NewTrainingData2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "frequency=NewTrainOne[4]['setup'].signal_definition.frequency1\n",
    "# sampling rate of the signal\n",
    "sampling_rate=NewTrainOne[0]['setup'].sampling_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "crosstalk=[]\n",
    "frequency=[]\n",
    "sampling_rate=[]\n",
    "for signals in NewTrainOne:\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": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "for i in range(25):\n",
    "    NewTrainOne[i]['s0'][1:int(crosstalk[i])]=0  #training data\n",
    "    NewTrainTwo[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 NewTrainOne ]  # sensor data arranged in list\n",
    "[ActuatorData.append(signal['a0']) for signal in NewTrainOne]  # Actuator data arrange in list\n",
    "##############################################################################################################\n",
    "TestSensorData=list()\n",
    "TestActuatorData=list()\n",
    "\n",
    "[TestSensorData.append(signal['s0']) for signal in NewTrainTwo ]  # Test data  for sensor  arranged in list\n",
    "[TestActuatorData.append(signal['a0']) for signal in NewTrainTwo]  # test data for actuator  arrange in list\n",
    "   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n",
      "c:\\miniconda3\\lib\\site-packages\\ipykernel\\__main__.py:22: 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:25: 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 1/100\n",
      "50/50 [==============================] - 14s - loss: 33.5802    \n",
      "Epoch 2/100\n",
      "50/50 [==============================] - 8s - loss: 7.8205     \n",
      "Epoch 3/100\n",
      "50/50 [==============================] - 9s - loss: 3.5137     \n",
      "Epoch 4/100\n",
      "50/50 [==============================] - 9s - loss: 2.2234     \n",
      "Epoch 5/100\n",
      "50/50 [==============================] - 9s - loss: 2.0831     \n",
      "Epoch 6/100\n",
      "50/50 [==============================] - 9s - loss: 1.8545     \n",
      "Epoch 7/100\n",
      "50/50 [==============================] - 10s - loss: 1.3134    \n",
      "Epoch 8/100\n",
      "50/50 [==============================] - 10s - loss: 1.0896    \n",
      "Epoch 9/100\n",
      "50/50 [==============================] - 9s - loss: 0.9316     \n",
      "Epoch 10/100\n",
      "50/50 [==============================] - 12s - loss: 0.6245    \n",
      "Epoch 11/100\n",
      "50/50 [==============================] - 10s - loss: 0.8491    \n",
      "Epoch 12/100\n",
      "50/50 [==============================] - 10s - loss: 2.5073    \n",
      "Epoch 13/100\n",
      "50/50 [==============================] - 9s - loss: 1.4951     \n",
      "Epoch 14/100\n",
      "50/50 [==============================] - 8s - loss: 0.7226     \n",
      "Epoch 15/100\n",
      "50/50 [==============================] - 8s - loss: 0.6841     \n",
      "Epoch 16/100\n",
      "50/50 [==============================] - 8s - loss: 0.6664     \n",
      "Epoch 17/100\n",
      "50/50 [==============================] - 8s - loss: 0.6152     \n",
      "Epoch 18/100\n",
      "50/50 [==============================] - 8s - loss: 0.5894     \n",
      "Epoch 19/100\n",
      "50/50 [==============================] - 8s - loss: 0.6342     \n",
      "Epoch 20/100\n",
      "50/50 [==============================] - 8s - loss: 2.9864     \n",
      "Epoch 21/100\n",
      "50/50 [==============================] - 8s - loss: 1.4633     \n",
      "Epoch 22/100\n",
      "50/50 [==============================] - 9s - loss: 0.6200     \n",
      "Epoch 23/100\n",
      "50/50 [==============================] - 9s - loss: 0.5724     \n",
      "Epoch 24/100\n",
      "50/50 [==============================] - 9s - loss: 0.4845     \n",
      "Epoch 25/100\n",
      "50/50 [==============================] - 9s - loss: 0.5225     \n",
      "Epoch 26/100\n",
      "50/50 [==============================] - 9s - loss: 0.5437     \n",
      "Epoch 27/100\n",
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      "50/50 [==============================] - 8s - loss: 1.3363     \n",
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      "50/50 [==============================] - 8s - loss: 0.8307     \n",
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      "50/50 [==============================] - 8s - loss: 0.5316     \n",
      "Epoch 38/100\n",
      "50/50 [==============================] - 8s - loss: 0.6057     \n",
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      "50/50 [==============================] - 8s - loss: 1.1662     \n",
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      "50/50 [==============================] - 9s - loss: 1.1745     \n",
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      "50/50 [==============================] - 8s - loss: 0.5544     \n",
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      "50/50 [==============================] - 9s - loss: 0.3683     \n",
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      "50/50 [==============================] - 9s - loss: 0.3354     \n",
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      "50/50 [==============================] - 8s - loss: 0.3252     \n",
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      "50/50 [==============================] - 8s - loss: 1.1313     \n",
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      "Epoch 74/100\n",
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      "Epoch 89/100\n",
      "50/50 [==============================] - 7s - loss: 0.2860     \n",
      "Epoch 90/100\n",
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      "Epoch 91/100\n",
      "50/50 [==============================] - 7s - loss: 1.4382     \n",
      "Epoch 92/100\n",
      "50/50 [==============================] - 8s - loss: 0.3859     \n",
      "Epoch 93/100\n",
      "50/50 [==============================] - 8s - loss: 0.2785     \n",
      "Epoch 94/100\n",
      "50/50 [==============================] - 8s - loss: 0.2793     \n",
      "Epoch 95/100\n",
      "50/50 [==============================] - 8s - loss: 0.2654     \n",
      "Epoch 96/100\n",
      "50/50 [==============================] - 8s - loss: 0.2498     \n",
      "Epoch 97/100\n",
      "50/50 [==============================] - 8s - loss: 0.2532     \n",
      "Epoch 98/100\n",
      "50/50 [==============================] - 8s - loss: 0.2931     \n",
      "Epoch 99/100\n",
      "50/50 [==============================] - 8s - loss: 0.2706     \n",
      "Epoch 100/100\n",
      "50/50 [==============================] - 7s - loss: 0.2866     \n"
     ]
    }
   ],
   "source": [
    "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=500 # 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": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[17.310817039765851, 10.014055072219834, 11.918686722914963, 14.245636758645661, 22.801814484026046, 103.84616433239211, 107.01695368360856, 107.47415247078402, 105.83491304947056, 102.77500007565462, 116.01207342627114, 123.58891583091255, 116.06127022769836, 114.49045564498633, 121.56048561110589, 129.00626483758967, 127.39080919228691, 129.28557650846386, 129.16302763298037, 133.98230423388219, 111.12742907250669, 117.54354361019104, 113.78996665105258, 118.01263267074117, 112.28601859237347]\n",
      "[0.0, 11.572702, 28.909082, 31.207916, 40.027046, 111.55247, 114.6571, 114.7407, 113.13988, 110.64439, 123.96223, 132.16899, 125.43304, 123.5004, 130.40822, 138.49493, 137.05562, 139.41145, 139.11121, 144.53746, 124.67908, 131.27852, 127.39731, 131.6994, 126.08643]\n"
     ]
    }
   ],
   "source": [
    "dist1=[]\n",
    "dist2=[]\n",
    "def mean(a):\n",
    "    return sum(a)/len(a)\n",
    "MeanBaseline=[]\n",
    "MeanBaselineTest=[]\n",
    "[MeanBaseline.append(i) for i in    map(mean,zip(*encoded_signal[0:4]))]\n",
    "[MeanBaselineTest.append(i) for i in    map(mean,zip(*EncodedTestData[0:4]))]\n",
    "\n",
    "for x,y in zip(encoded_signal,EncodedTestData):\n",
    "    dist1.append(np.linalg.norm(MeanBaseline-x))\n",
    "    dist2.append(np.linalg.norm(EncodedTestData[0]-y))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[None, None, None, None]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SelectedDist=[]\n",
    "SelectedDistTest=[]\n",
    "index=[0,5,10,15]\n",
    "[SelectedDist.append(dist1[i]) for i in index]\n",
    "[SelectedDistTest.append(dist2[i]) for i in index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The regression coefficients are as:[-13.0180913, 0.0967936]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[  1.18579243e-05],\n",
       "       [  5.14861453e-02],\n",
       "       [  1.67150638e-01],\n",
       "       [  5.87955097e-01]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "from math import log\n",
    "from numpy import exp\n",
    "gaps=[0.00001,0.1,0.2,0.3]\n",
    "logGap=[]\n",
    "[logGap.append(log(i))  for i in gaps]\n",
    "SelectedDist=np.asarray(SelectedDist)\n",
    "logGap=np.asarray(logGap)\n",
    "\n",
    "expRegr=linear_model.LinearRegression(fit_intercept=True,normalize=True)\n",
    "expRegr.fit(SelectedDist.reshape(4,1),logGap.reshape(4,1))\n",
    "print(\"The regression coefficients are as:[%.7f, %.7f]\" % (expRegr.intercept_ ,  expRegr.coef_))\n",
    "TrainingGapsExp=expRegr.predict(np.asarray(SelectedDist).reshape(4,1))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "It can be seen that exponential regression was used to fit between damage size and Damage Index. The above figure shows the prediction for the training data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  1.18579243e-05]\n",
      " [  5.85160612e-06]\n",
      " [  7.03622929e-06]\n",
      " [  8.81369171e-06]\n",
      " [  2.01759241e-05]\n",
      " [  5.14861453e-02]\n",
      " [  6.99810861e-02]\n",
      " [  7.31475726e-02]\n",
      " [  6.24153342e-02]\n",
      " [  4.64153794e-02]\n",
      " [  1.67150638e-01]\n",
      " [  3.48028935e-01]\n",
      " [  1.67948497e-01]\n",
      " [  1.44259318e-01]\n",
      " [  2.85987033e-01]\n",
      " [  5.87955097e-01]\n",
      " [  5.02846392e-01]\n",
      " [  6.04067637e-01]\n",
      " [  5.96944546e-01]\n",
      " [  9.51747310e-01]]\n"
     ]
    }
   ],
   "source": [
    "testData=np.asarray(dist1)\n",
    "\n",
    "Pred=expRegr.predict(testData[:-5].reshape(20,1))\n",
    "PredictedGap=exp(Pred)\n",
    "print(PredictedGap)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "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"
    }
   ],
   "source": [
    "x=[0.00001,0.1,0.2,0.3]\n",
    "GapVec=[]\n",
    "[GapVec.append(np.tile(i,(1,5))) for i in x]\n",
    "plt.figure()\n",
    "plt.scatter(SelectedDist,gaps,color='blue',label='Data used to Train')\n",
    "plt.plot(SelectedDist,exp(TrainingGapsExp),color='red',label='Prediction on Training data')\n",
    "plt.scatter(testData[:-5],PredictedGap,color='green',label='Prediction on Test data')\n",
    "plt.ylabel('Gaps (mm)')\n",
    "plt.xlabel('Damage Index')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[  1.18579243e-05]\n",
      " [  5.85160612e-06]\n",
      " [  7.03622929e-06]\n",
      " [  8.81369171e-06]\n",
      " [  2.01759241e-05]\n",
      " [  5.14861453e-02]\n",
      " [  6.99810861e-02]\n",
      " [  7.31475726e-02]\n",
      " [  6.24153342e-02]\n",
      " [  4.64153794e-02]\n",
      " [  1.67150638e-01]\n",
      " [  3.48028935e-01]\n",
      " [  1.67948497e-01]\n",
      " [  1.44259318e-01]\n",
      " [  2.85987033e-01]\n",
      " [  5.87955097e-01]\n",
      " [  5.02846392e-01]\n",
      " [  6.04067637e-01]\n",
      " [  5.96944546e-01]\n",
      " [  9.51747310e-01]]\n",
      "[  17.31081704   10.01405507   11.91868672   14.24563676   22.80181448\n",
      "  103.84616433  107.01695368  107.47415247  105.83491305  102.77500008\n",
      "  116.01207343  123.58891583  116.06127023  114.49045564  121.56048561\n",
      "  129.00626484  127.39080919  129.28557651  129.16302763  133.98230423\n",
      "  111.12742907  117.54354361  113.78996665  118.01263267  112.28601859]\n"
     ]
    }
   ],
   "source": [
    "print(PredictedGap)\n",
    "print(testData)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The graph below shows the actual versus predicted damage size. A very accurate prediction should lie as close as possible to line passing midway between x and y-axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "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": {
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lMnJYWkfwJZ4o+Z6RAGI+rN4ccQee0RcdVXE4V6UDwDFQgFYjCHgaqIARP0ZOzZizpyIW27RMwBPAQCKhwKwc7aBMQ/5nqrsXzoDkI0FCyJ+8IPklm8UfwBQWFkUgL6N2leTw5JjFd+P17dcu0c5QgGQBW99cNRREf2aW5QPACiKLArAQxSvqi3zKtzTFd+X13cD8b16AVSbb/X2298m9/0FABRaFgXgO5Unk8PYVdlJ+VHpLOJyZe/kEEDVeDuxMWMiTj1VP4H+EQQAFFkWBeAKpbzPxH7KP5TyhMvlyqbJIYCqufHGiPnzk33/AACFl0UBOFcZlhzGUMXz/8p2VnxfXgDVskK/g3nl7znnRLBaHQAgWRSAvsv8dMWFnjcd+75S9lnlL8khgKrwhs9v04/68cenDQCAostqH4hdFA//+i4cT7shNVB5SfHdOOoR+wCitul7M3r3jvjJTyI+/em0EQCKjX0As+kBtKeUGUpl8Wf/p9Rr8QfUvgsuiNhnn4gj2G0JALBWVgUggKwtXJjc83fqVDZ9BgC8CQUgkFdnnRUxZEjE/txwBwDwZhSAQB7dd1/E9ddHnH9+2gAAwFoUgEDeeNPn006L+PrXI3bx+isAAN4s6wLwQ4rvDXxT6SxiX8UrgQF0lJkzIx54IGLcuLQBAIA3y7IAPErRK1PJwemjP773CQTQEVauTHr/JkyI2GqrtBEAgDfLsgA8S/FG0F9VVrlBHlT6JocA2u2nP41oaIg44YS0AQCAt8qyAOyl3J0cRmP6qFeqNfcJBtAer7yS9Px577+uXdNGAADeKssCcIHSPzlcw3cHeSI5BNAu3u/Pd/3w1i8AAKxDlgXgNOUGZYTiXr+jlauV7yoA2mPRoqQAZNNnAEArZP1KMVwZqeypPKtcpHxfqVfcCxi14bjjIpYti7j22rQBANAS7gWcfQGYNxSA6Hxz50YccEDEQw9F7L572ggAaAkFYLZDwACqYezYiBNPpPgDALRalgXgasXbvzTNa8p85UyliwKgtWbNirj33uS+vwAAtFKWBeBo5THlFOXT6eM/lG8qP1K8cdlEBUBrrNLvT970+eyzI7beOm0EAGD9spwD+BfFK38fLZ0l9lKuUj6o7K9cp9TTOBZzANF5rrgi4lvfipg/P2LTTdNGAMD6MAcw2x7AdytN9/x7UnlPchh/Vd6ZHAJYp1dfTYZ9J0+m+AMAtFmWBeAjyunJ4RpjFLfbTsqS5BDAOk2bFtGrV8TQoWkDAACtl+UQsId5b1Z8+7eFim8N5/tVfULx8PBHFfcG/lCpFwwBI3vPPRex554RM2dGDByYNgIAWosh4Oz3AfSFPkLZUVmk/I9Sz71+FIDI3gknRPz73xEzZqQNAIC2oABkI+j2ogBEtubNi9hvv4gHHojYy2uoAABtRQGYfQG4t+KhXi/2qPzYE9LHekMBiGx96lPJhs/fr+c7KAJA56IAzLYA/JxyjTJP6ZM+7qP8n3KIUo8oAJGd226LGDIk4vHHI7bZJm0EALQVBWC2q4B9q4KvKf2UV9PHUcpdCoB1Wb06YsyYiPHjKf4AAO2WZQHoDZ5/nhyu6Xn0HUD+MzkE0KKrr4548cWIU3wDHQAA2ifLAtD3/PW2L/aS8i5lE6XUBwugBa+/HnHmmRGTJkVstlnaCADAhsuyAJytDE4O41bF8wF/rdznBgAtuOiiiG23jfjiF9MGAADaJ8sCcITiItDGKg8rixWGgIGWPP98cru3qVP105rljysAIM/YB7B9WAWM6jr55Iinn4648ca0AQDQXqwCzr4A9Ly/fZUtS2dreTi4HlEAonoeeSSiX7+I++6L2NtbaAIAOgIFYLYF4FeV6crriheElDUqvjVcPaIARPV4z7/tt4+45JK0AQDQESgAsy0Afe9f72HhhR95QQGI6rjrrohPfCLisccittsubQQAdAQKwGwXgWyqcPd6YH286fPo0RFnnEHxBwCoiiwLwOuUTyeHAFp0nX5UnnkmYuTItAEAgI6V5RBwd+XPykLlWTdUqNetYBgCRsd6442I97wnYuLEiOHD00YAQEdiCDjbHsDvKzsoXgTSpUkA2PTpEVttFTFsWNoAAEDHy7IH8BXlvcqC0lk+0AOIjuN7/fbuHXH99RGHHpo2AgA6Gj2A2fYA6tUtnkkOAbzFeedFDBhA8QcAqLosC8ALFL3CxcalMwBrebuXSy+NmDIlbQAAoHqyHAL24o/tlRXKC26osHP6WG8YAkbH+Pznk7l/l12WNgAAqoUh4GwLwGPSx+ZcmT7WGwpAtN8990QMGhTxj39E7OB1UgCAaqIAzLYAzCMKQLRPY2PEQQdFfPzjydYvAICqowDMdg5g2RbKbsruFQGK6de/jnjyyYgxY9IGAACqL8sCcFflbsWV9mPKPyoCFE9DQ3K7t299K6K790kHACAbWRaAFynPK/sry5T9lJnKsUq1naMsUrwX4R3KPkpztlV+pjyhuFD14ySlqwJ0rEsuiejWTT8BWfwIAACwVpYF4IGKX+nmKI3K/cpXlWrf8PQ0xffUGqRso7gXcpayudKUu2EeVj6meFKfN2T7pPJtBeg4L78cce65ybYvG7MzEgAgW1kWgJsoLyWH8ZriAswbQ+/hhio6UfHmavOU5crZim8/N0Rp6knFxZ4fzT2AP1UOKZ2hcFasWBHXXnttjBs3rvTo80qvvfZafOMb34gDDzyw9OjzVpk0KWLffSMOOyxtqK71fR0bqlrvFwBQXVmuAv6r4h7AB5VblZuVxYoLMi8KqQb34vljuPfxXjek3APoz6M1M+//V3lOOa509masAs4xFzMHHzw45sx5Sscfiy5d/hD9++8Sf/zjLB13KRV72223Wyxb5t9tXMj9Lrp3Xxn/+teTsfnmzXUwpxYsiOjTJ+LuuyP69Usbq2d9X8eGqtb7BYBqYxVwtj2A7lkrb3L2LcV7XlyqfNMNVVKuylwEVnpZaU3F5uLUr9B+RMHMmDGjVNy88cbcWLXqx6XHOXMWlNrNvV5J8feo8pPSo8/dvk7jx0cMHZpJ8Wfr+zo2VLXeLwCg+rIsAH+l3JIcxh+VdyhvV37uhiopV/VbpY9l/rjrq/hdpB6vHKys8x7G4/WCPmrUqFJmzXLnIvLg/vvvL/VsJTsX2RY6P7TUbn/5y1/0p3v+1v69z5P2FsyeHfHb3yb3/c3I+r6ODVWt9wsA1eDX5/JrtV+3iy7LAtALLLwQ4wvp46bKq0o1uchboHygdJbwjPv+ihejtORi5ShloOIta9Zp0qRJMW3atFIGDx6ctqLe9evXrzSsufbb9FWd31pqtw9+8IP683el9oQff5e2N8ObPnu/v5EjI3baKW2svvV9HRuqWu8XAKrBr8/l12q/bhddVnMA3ZP2XWXL0lnCW8F4Dt6PS2fV449xsuLVvF7UMUE5Wnm30nTGvotD90i+T/EK4H8p68IcwBxbO8dtQalny8VN//67bvgcQPf8jRihXyn0O0WG3y/r+zo2VLXeLwBUG3MAsykAP6TcrlygXKU8reysuAgbq3gM6U9KNXm+4dcUF6BejHKS8pDSS/HqYL96+3P4sOLP1auFVyrma+Rta5p7xaYAzDkXOZ7T5mFN92wdeeSRbypuXAR6zp+Hfd3zN3ny5OaLP72f6Ns34tRTI070wvRsre/r2FDVer8AUE0UgNkUgFcrLraa6289Q3Fv25dKZ/WHAhCtc/HFEdOnR8ydG6qQ0kYAQGegAMxmDuABypXJ4Vt4uHVAcgjklH5BiIkTI77zHYo/AEBNyKIA9Gpf34atOV5du3VyCOTUBRdE7LNPxKc+lTYAANC5sigA1/cxstyMGsjWwoURF14YMXWqvtP5VgcA1IYsXpFeV/5LaeljTVfWcduEmsYcQKzbMcdErFoVcZXXPwEAagFzALMpAL0Pn1fRrku1bgVXbRSAaNl990UMHBgxf37ELrukjQCAzkYByPBre1EAonne9PnQQyP23z+ZAwgAqBkUgNneCQQojpkzIx54wDcMThsAAKgdFIBAR1u5MuK00yImTIjYqultqAEA6HwUgEBH++lPIxoaIk44IW0AAKC2UAACHemVV5KeP8/769o1bQQAoLZQAAIdyfv99e4dMWRI2gAAQO2p9irgr6SP6+NbwtUjVgFjrUWLIvbaK+IPf4gYwB0OAaBWsQq4+gXgwvSxbDtlY+Ul5e3KauU5ZWelHlEAYq3jjotYtizi2mvTBgBALaIArP4QcK+KTFF8OwQXftsqvkfwlYrbgfo2d27ENddETJ6cNgAAULuy3AjavYF7Kb41XNkWysOKC8R6RA8gEocdFtGnT8S0aWkDAKBW0QOY7SKQzZSmm6L5wtfrfYCBxC23RNx7b8RZZ6UNAADUtiwLwN8qNymfUPqkj79JA9SnVauSTZ/PPjti663TRgAAaluWBeApyn3Kr5W/p48PKN9QgPr0858ne/+ddFLaAABA7ctyDmCZP6YXgTyvNLqhjjEHsMhefTXZ9sXz/o46Km0EANQ65gBmvxG0t4A5UDlEcfHXTdlUAeqPC79evSKGDk0bAACoD1kWgLspc5VblZ+6QTwP8LLkEKgjzz0X8Z3vJHf+2KgzOtIBANhwWRaAP1BuVLZUGtwgtysfTg6BOjJxYsSgQREDB6YNAADUjyy7Ljznb0dlheI7gZSXTC5RSgPxdYg5gEU0b17EfvtFPPBAMgcQAFBXmAOYbQ/gq0rTPf+8GOTF5BCoE6efHjFiBMUfAKBuZVkAzlQ8DFwuAr0gZJLivQGB+nDbbRF33hkxYULaAABA/cmyADxD8S3fPPzrLtdXlPcrvJKiPqxeHTFmTMT48RHbbJM2AgBQf7IsAD3Xz9u/eBuYLyqHKQMUtwO175prIl58MeIU72kOAED9yroH0OYo1yl3KquVsQpQ215/Pen5mzQpYjPf1hoAgPqVZQGoV89mlQtDoHZddFHEtttGfNGd1wAA1LcsCkB/DC/48JYzjs/L6aN4Wxigdj3/fMTkycmmz2/L4kcGAIDqyuLVbKXijZ+9+tfHLvjKeVD5bwWoXeeeG3HwwRGHeAorAAD1L4uNoPXKWfo4NyuHuyHl+X/PKf8ondUnNoLOu0ceiejXL+K++yL23jttBADUMzaCzvZOIN4CZmFymBsUgHk3ZEjE9ttHXHJJ2gAAqHcUgNkMAZd9QTkgOVzD28CMSQ6BGnPXXRG33prc9xcAgBzJsgD8uvJIcriGz9lUDbXHmz6PHp3c9m277dJGAADyIcsCcCtlcXK4xsvK25NDoIZcd13EokURo0alDQAA5EeWBaDn/+2XHK7hc73KAjVk+fKIceMizj8/YvPyrasBAMiPLAvAnyje8mWIsk/6eLVyuQLUjunTIzw5eNiwtAEAgHzJchWwN4M+R/Gcv+7KMuUHytmKt4SpR6wCzhvf67d372QIeNCgtBEAkCesAs62AKy0jfJCcljXKADzZuTIiIcfjpg5M20AAOQNBWC2Q8CV8lD8IW8efzzi0ksjpkxJGwAAyKdqF4Dz00fzIpCnWwjQ+bzw48tfjujbN20AACCfqj0E/CXlmuQwjkkfm3Nl+lhvGALOi3vuSeb8PfpoxI47po0AgDxiCLjz5gDmBQVgHjQ2RgwcmBSA3PUDAHKPArD6Q8A7tzJA55kxI+KJJyLGcFdCAEAxVLsH0Nu7NCaH6+QtYuoRPYD1rqEhok+f5JZvI0akjQCAPKMHsPo9gHsqe6X5mvJX5TPK+9LHvyhfVYDOccklEd26RRx7bNoAAED+ZTkH8CHFO+s+UzpLvEu5RfGdQeoRPYD1bPHiiD32iLjqqojDD08bAQB5Rw9gtvsA7qS8lByu8bLidiB7kyZF9O8fcdhhaQMAAMWQZQE4W5mu+DZwtqVykeJhYSBbCxYk9/ydOjViIxbDAwCKJcsC0HP9DlTc6/dvxb2BBynMAUT2zjwzYujQiH790gYAAIoj664PF5wuAj3375/KvcoqpV4xB7AezZ4d8ZGPRDzySMROzEAAgKJhDmC2PYDmbWHuVu5KH+u5+EM98qbP3u/v1FMp/gAAhZVlAbi58mPldeUxN4i3gjkzOQQycNNNEfPnJ/v+AQBQUFkWgFOUXZWPKSvcIPcpX0wOq+ocZZHyinKHsq5tZ76l+PNartzpBuTECn3bjR2b3O6NIXsAQIFlWQB+WvmC8ifFQ8G2UPF8wGo6TRmueA/CbRQPPc9S3CPZHPdOnq24txJ5ctllySN3/AAAFFyWi0CeUzzpaqXiFcBbK5spjys7KtXyhDJN8RY05tvOeTPqUcrVbmjBNxX3Vn64dNY8FoFUwYoVK2LGjBnxt7/9LZYvXx6bbrpp7LfffnHEEUfETTfdFPfff3/07ds3Vq5cGTfccEPp33z+85+PoUOHRpcuXUrnb7F0aUTv3hGXX65fRfy7CACgqFgEkm0BeJPye+X7SrkAPFFxz9yRSjW4KluseOWxVxyXuQfwQWVdd/+nAOwELv4OPnhwzJnzVLzxxkfU8jtlk+ja9W3Kayr6uuttPhqrV8+Mxkb/175d+XhstNGsOOCAPePOO29pvgj0ti9/+lPE7bez7x8AFBwFYLZDwB6KPUvxEPAWyq3KecoZSrWUqzJXCpW8FyEVWw1yz19S/M3V2U+UR5WNo6Hh8Fi2bJNS+6pVl6n4e0Tt/rn1t9BPSud/+9sTpX//FgsXRnzve2z6DABAKssC8GFlb+VXil/ZvcDCu/D6Fb5aylX9VuljmbuNOqziHz9+fIwaNaqUWbPcuYgN5eHdFSvc8erfEcyPhypzFN+yrbLd5/62si1i5cpBpX//Fmfp947PfjZi//3TBgBA0fj1ufxa7dftosuqO6SrcqHieXdvuCFDzc0BfFYZqTAHsMZce+21MXz4+LQH0EXeq8p7FRd7v1X8+0K5fS9lknJM6bxLlz7xi198J4466iidp+aocDzooIh58yJ29SJ0AEDRMQScXQ9gg+IVwFkXf/ZDxXP9vPWLF514zNBbvCSrB95qE6Wb4olkLpA3TYMMHHnkkdG//y7RrZuLvuMUF3mromvXm6N795Wl9o03HhEbbfRutS9RvI3kcaXz/fbbvfTv1yhv+nzyyRR/AABUyHJC1H8rP1M6Y4x0ovI1ZUvlr8pJykNKL2We4u4lz020KxR3Kal6KPE18rF7DpuiB7AKOmwV8M03RwwbFvH44xFbNZ0FAAAoKnoAsy0Af6B4P74blSeV8l6ANiF9rDcUgLVKxWG8//0q+1X3n3JK2ggAAAWgZbkIpK/i3jfv+XeQ8v/SDFSAjnXFFRENDREnnJA2AACAsix7APOIHsBatGxZsunzxRdH/Md/pI0AACToAcyuB9Arab3q1j1/QHVNmRKxxx5eUZI2AACASlkUgP+p3KF4050/KkcrQHU880zEd7+bhE2fAQBoVhYF4KnKMGVb5VjlGwpQHRMmRHzykxEDBqQNAACgqSy6SMo3bC1vpeJNmN+p5AFzAGvJ3LkRBxwQ8dBDEbvvnjYCAPBmzAHMpgfQH6O8p94qxRstAx1v7NiIE0+k+AMAYD2y6AH0XTcuSA5LTlOmJIdrsA8g2ueWWyJ8Czhv+rz11mkjAABvRQ9gNgWgF4CUewCb47/7aHJYdygAa8GqVRH77hvxla9EjB6dNgIA0DwKQPYBbC8KwFrgTZ/PPTfi4YcjNuW2zQCAdaMAzG4fQKA6Xnst4qyzIr79bYo/AABaiQIQ9W3atIhevSKGDk0bAADA+lAAon4991zEBRdETJ3Kps8AALQBBSDq18SJEYMGRQwcmDYAAIDWoABEfZo3L+LKK5O5fwAAoE0oAFGfTj89YsSIiL32ShsAAEBrUQCi/tx+e8Sddyb3/QUAAG1GAYj6snp1xJgxEePHR2yzTdoIAADaggIQ9eWaayJeeCHilFPSBgAA0FYUgKgfr7+e9Pydf37EZpuljQAAoK0oAFE/LrooYtttI770pbQBAABsCApA1Ifnn4+YPDnZ9PltfNsCANAevJKiPpx7bsTBB0ccckjaAAAANhQFIGrfo49GXH55cts3AADQbhSAqH1nnBExfHjE3nunDQAAoD0oAFHb7ror4ve/T+77CwAAOgQFIGqXN30ePTq57dt226WNAACgvSgAUbuuuy5i0aKIUaPSBgAA0BEoAFGbli+PGDcu2fR5883TRgAA0BEoAFGbpk+P6NkzYtiwtAEAAHQUCkDUnpdeijjvvIgpUyI23jhtBAAAHYUCELXHxd+AARGDBqUNAACgI1EAorY8/njEJZckvX8AAKAqKABRW7zw4+ijI/r2TRsAAEBHowBE7bjnnoibb07u+wsAAKqGAhC1obExYsyYJDvskDYCAIBqoABEbZgxI+KJJ5ICEAAAVBUFIDpfQ0NyuzcP/XbvnjYCAIBqoQBE57v00ohu3SKOPTZtAAAA1UQBiM61eHHEOeck275ssknaCAAAqokCEJ1r0qSIffeNOOywtAEAAFQbBSA6z4IFyT1/3fu30UZpIwAAqDYKQHSeM8+MGDo0ol+/tAEAAGSBAhCdY/bsiN/8JrnvLwAAyBQFILJX3vR55MiInXZKGwEAQFYoAJG9m26KmD8/YuzYtAEAAGSJAhDZWrEiKfy89UuPHmkjAADIEgUgsnXZZcmK3+OPTxsAAEDWKACRnaVLIyZOjLjggoguXdJGAACQNQpAZMeFX58+EUcckTYAAIDOQAGIbCxcGHHhhRFTp7LpMwAAnYwCENk466yIIUMi9t8/bQAAAJ2FAhDVN2dOxPXXR5x/ftoAAAA6EwUgqqu86fPXvx6xyy5pIwAA6ExFKQDPURYpryh3KPsoLdlKuVpZrLyk/ELpqWBDzJwZ8cADEePGpQ0AAKCzFaEAPE0ZrgxStlHuVmYpmyvNcfG3rbKb0lvZXrlSQVutXKmrr8s/YYLKatfVAACgFhShADxRmaLMU5YrZyvehG6I0tTOyuHKKOVlxT2Ao5VPK9y0tpWeffbZ2GWXXeKEbt3iyUcfjWc/85n0bwAAQC3IewHoe43tqswunSVWKfcr/Utnb9ZPeUP5e+ksMVdpUPx3WA8Xfzvu2DtefLohJq7qGqNXbhk77tqn1A4AAGpDEQpA83y+Su7da+5GtG5bkhy+if89N65thQEDBujPreK0GB6Pxb5xQzyt855pOwAAqAV535HXRZuLtwOVe92Q8hzAB5UxpbO1PNT7S6Xp/ED3Cn5O+Z/S2VqlgvGkk06Krl27lhoGDx5cSlH5OqxYMSy+Fh+I+1QAzo4PqvW46NLlF9HQ4I5UAACyN2vWrFLMr0cXX3yxD73Ic6kPiqYIt2R4QpmmTC+dRWyseDxypOIFH5U8B/BJ5f1KeRjYx/cp3sPkn26oUCoAJXr0oIPQPPfv6adX6uhRZQvlVWXP2HnnLvHUU0/pGACAzrV06dLo2bO0wUdhC8AiLAL5oeKePm/9splynuLFIDcoTXm88mZlqvIOxauGfXyj0rT4QzP+/Oc/6093uu6pHJc+LknbAQBALShCAegC7mfKrcrzioeDD1NeU3op3hvwIKVsmPKC8rjyD8W9hccoaIUddtghnnnmsVKPn4d9/ehztwMAgNrAXfnbhyFgAADqDEPAxegBBAAAQAUKQAAAgIKhAAQAACgYCkAAAICCoQAEAAAoGApAAACAgqEABAAAKBgKQAAAgIKhAAQAACgYCkAAAICCoQAEAAAoGApAAACAgqEABAAAKBgKQAAAgIKhAAQAACgYCkAAAICCoQAEAAAoGApAAACAgqEABAAAKBgKQAAAgIKhAAQAACgYCkAAAICCoQAEAAAoGApAAACAgqEABAAAKBgKQAAAgIKhAAQAACgYCkAAAICCoQAEAAAoGApAAACAgqEABAAAKBgKQAAAgIKhAAQAACgYCkAAAICCoQAEAAAoGApAAACAgqEABAAAKBgKQAAAgIKhAAQAACgYCkAAAICCoQAEAAAoGApAAACAgqEA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      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x212bebf3e10>"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d=[0,0.1,0.2,0.3,0.4]\n",
    "plt.figure()\n",
    "plt.scatter(PredictedGap,GapVec)\n",
    "plt.plot(d,d,color='red')\n",
    "plt.xlabel('Actual Damage Size')\n",
    "plt.ylabel('Predicted Damage Size')\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
}