Evaluation.ipynb

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     "text": [
      "0 178\n",
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   "source": [
    "# Evaluation for Classification\n",
    "# Preamble\n",
    "%matplotlib notebook\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.datasets import load_digits\n",
    "\n",
    "dataset = load_digits()\n",
    "X, y = dataset.data, dataset.target\n",
    "\n",
    "for class_name, class_count in zip(dataset.target_names, np.bincount(dataset.target)):\n",
    "    print(class_name,class_count)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original labels:\t [1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9]\n",
      "New binary labels:\t [1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]\n"
     ]
    }
   ],
   "source": [
    "# Creating a dataset with imbalanced binary classes:  \n",
    "# Negative class (0) is 'not digit 1' \n",
    "# Positive class (1) is 'digit 1'\n",
    "y_binary_imbalanced = y.copy()\n",
    "y_binary_imbalanced[y_binary_imbalanced != 1] = 0\n",
    "\n",
    "print('Original labels:\\t', y[1:30])\n",
    "print('New binary labels:\\t', y_binary_imbalanced[1:30])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "np.bincount(y_binary_imbalanced)   # Negative class (0) is the most frequent class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y_binary_imbalanced, random_state=0)\n",
    "\n",
    "# Accuracy of Support Vector Machine classifier\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "svm = SVC(kernel='rbf', C=1).fit(X_train, y_train)\n",
    "svm.score(X_test, y_test)"
   ]
  },
  {
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     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Dummy Classifiers\n",
    "# DummyClassifier is a classifier that makes predictions using simple rules, which can be useful as a baseline for comparison against actual classifiers, especially with imbalanced classes.\n",
    "from sklearn.dummy import DummyClassifier\n",
    "\n",
    "# Negative class (0) is most frequent\n",
    "dummy_majority = DummyClassifier(strategy = 'most_frequent').fit(X_train, y_train)\n",
    "# Therefore the dummy 'most_frequent' classifier always predicts class 0\n",
    "y_dummy_predictions = dummy_majority.predict(X_test)\n",
    "\n",
    "y_dummy_predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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     "execution_count": 6,
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   ],
   "source": [
    "dummy_majority.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
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     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "svm = SVC(kernel='linear', C=1).fit(X_train, y_train)\n",
    "svm.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most frequent class (dummy classifier)\n",
      " [[407   0]\n",
      " [ 43   0]]\n"
     ]
    }
   ],
   "source": [
    "# Confusion matrices\n",
    "# Binary (two-class) confusion matrix\n",
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "# Negative class (0) is most frequent\n",
    "dummy_majority = DummyClassifier(strategy = 'most_frequent').fit(X_train, y_train)\n",
    "y_majority_predicted = dummy_majority.predict(X_test)\n",
    "confusion = confusion_matrix(y_test, y_majority_predicted)\n",
    "\n",
    "print('Most frequent class (dummy classifier)\\n', confusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random class-proportional prediction (dummy classifier)\n",
      " [[373  34]\n",
      " [ 39   4]]\n"
     ]
    }
   ],
   "source": [
    "# produces random predictions w/ same class proportion as training set\n",
    "dummy_classprop = DummyClassifier(strategy='stratified').fit(X_train, y_train)\n",
    "y_classprop_predicted = dummy_classprop.predict(X_test)\n",
    "confusion = confusion_matrix(y_test, y_classprop_predicted)\n",
    "\n",
    "print('Random class-proportional prediction (dummy classifier)\\n', confusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Support vector machine classifier (linear kernel, C=1)\n",
      " [[402   5]\n",
      " [  5  38]]\n"
     ]
    }
   ],
   "source": [
    "svm = SVC(kernel='linear', C=1).fit(X_train, y_train)\n",
    "svm_predicted = svm.predict(X_test)\n",
    "confusion = confusion_matrix(y_test, svm_predicted)\n",
    "\n",
    "print('Support vector machine classifier (linear kernel, C=1)\\n', confusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logistic regression classifier (default settings)\n",
      " [[401   6]\n",
      " [  6  37]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "lr = LogisticRegression().fit(X_train, y_train)\n",
    "lr_predicted = lr.predict(X_test)\n",
    "confusion = confusion_matrix(y_test, lr_predicted)\n",
    "\n",
    "print('Logistic regression classifier (default settings)\\n', confusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision tree classifier (max_depth = 2)\n",
      " [[400   7]\n",
      " [ 17  26]]\n"
     ]
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier\n",
    "\n",
    "dt = DecisionTreeClassifier(max_depth=2).fit(X_train, y_train)\n",
    "tree_predicted = dt.predict(X_test)\n",
    "confusion = confusion_matrix(y_test, tree_predicted)\n",
    "\n",
    "print('Decision tree classifier (max_depth = 2)\\n', confusion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.95\n",
      "Precision: 0.79\n",
      "Recall: 0.60\n",
      "F1: 0.68\n"
     ]
    }
   ],
   "source": [
    "# Evaluation metrics for binary classification\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score\n",
    "# Accuracy = TP + TN / (TP + TN + FP + FN)\n",
    "# Precision = TP / (TP + FP)\n",
    "# Recall = TP / (TP + FN)  Also known as sensitivity, or True Positive Rate\n",
    "# F1 = 2 * Precision * Recall / (Precision + Recall) \n",
    "print('Accuracy: {:.2f}'.format(accuracy_score(y_test, tree_predicted)))\n",
    "print('Precision: {:.2f}'.format(precision_score(y_test, tree_predicted)))\n",
    "print('Recall: {:.2f}'.format(recall_score(y_test, tree_predicted)))\n",
    "print('F1: {:.2f}'.format(f1_score(y_test, tree_predicted)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "      not 1       0.96      0.98      0.97       407\n",
      "          1       0.79      0.60      0.68        43\n",
      "\n",
      "avg / total       0.94      0.95      0.94       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Combined report with all above metrics\n",
    "from sklearn.metrics import classification_report\n",
    "\n",
    "print(classification_report(y_test, tree_predicted, target_names=['not 1', '1']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random class-proportional (dummy)\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      not 1       0.91      0.92      0.91       407\n",
      "          1       0.11      0.09      0.10        43\n",
      "\n",
      "avg / total       0.83      0.84      0.83       450\n",
      "\n",
      "SVM\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      not 1       0.99      0.99      0.99       407\n",
      "          1       0.88      0.88      0.88        43\n",
      "\n",
      "avg / total       0.98      0.98      0.98       450\n",
      "\n",
      "Logistic regression\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      not 1       0.99      0.99      0.99       407\n",
      "          1       0.86      0.86      0.86        43\n",
      "\n",
      "avg / total       0.97      0.97      0.97       450\n",
      "\n",
      "Decision tree\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      not 1       0.96      0.98      0.97       407\n",
      "          1       0.79      0.60      0.68        43\n",
      "\n",
      "avg / total       0.94      0.95      0.94       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print('Random class-proportional (dummy)\\n', \n",
    "      classification_report(y_test, y_classprop_predicted, target_names=['not 1', '1']))\n",
    "print('SVM\\n', \n",
    "      classification_report(y_test, svm_predicted, target_names = ['not 1', '1']))\n",
    "print('Logistic regression\\n', \n",
    "      classification_report(y_test, lr_predicted, target_names = ['not 1', '1']))\n",
    "print('Decision tree\\n', \n",
    "      classification_report(y_test, tree_predicted, target_names = ['not 1', '1']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "[(0, -23.176547400757663),\n",
       " (0, -13.541223742469006),\n",
       " (0, -21.722500473360618),\n",
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       " (0, -19.736034587372778),\n",
       " (0, -9.7493459511792651),\n",
       " (1, 5.2349002124953099),\n",
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       " (0, -25.101015601857377),\n",
       " (0, -21.827250934235906),\n",
       " (0, -24.150855663826746),\n",
       " (0, -19.576844844946265),\n",
       " (0, -22.574902551102674),\n",
       " (0, -10.823739601445064),\n",
       " (0, -11.912425566043064),\n",
       " (0, -10.97956652705531),\n",
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       " (0, -12.859636015637092),\n",
       " (0, -25.848590145556187)]"
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     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Decision functions\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y_binary_imbalanced, random_state=0)\n",
    "y_scores_lr = lr.fit(X_train, y_train).decision_function(X_test)\n",
    "y_score_list = list(zip(y_test[0:20], y_scores_lr[0:20]))\n",
    "\n",
    "# show the decision_function scores for first 20 instances\n",
    "y_score_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 8.6010872706740499e-11),\n",
       " (0, 1.3155903495453823e-06),\n",
       " (0, 3.6816111034009875e-10),\n",
       " (0, 6.1452989618944584e-09),\n",
       " (0, 2.6837934145133791e-09),\n",
       " (0, 5.8329401240781557e-05),\n",
       " (1, 0.99470087426871634),\n",
       " (0, 4.1210362715903745e-09),\n",
       " (0, 1.2553575357627774e-11),\n",
       " (0, 3.3154719959007555e-10),\n",
       " (0, 3.2465093048358345e-11),\n",
       " (0, 3.1469099051059103e-09),\n",
       " (0, 1.5698002448420801e-10),\n",
       " (0, 1.9920533537070619e-05),\n",
       " (0, 6.706507243234968e-06),\n",
       " (0, 1.7046194538057202e-05),\n",
       " (1, 0.99998640569605668),\n",
       " (0, 9.8535912965519826e-13),\n",
       " (0, 2.6009374594983658e-06),\n",
       " (0, 5.9442892596185542e-12)]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y_binary_imbalanced, random_state=0)\n",
    "y_proba_lr = lr.fit(X_train, y_train).predict_proba(X_test)\n",
    "y_proba_list = list(zip(y_test[0:20], y_proba_lr[0:20,1]))\n",
    "\n",
    "# show the probability of positive class for first 20 instances\n",
    "y_proba_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
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       "            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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Precision-recall curves\n",
    "from sklearn.metrics import precision_recall_curve\n",
    "\n",
    "precision, recall, thresholds = precision_recall_curve(y_test, y_scores_lr)\n",
    "closest_zero = np.argmin(np.abs(thresholds))\n",
    "closest_zero_p = precision[closest_zero]\n",
    "closest_zero_r = recall[closest_zero]\n",
    "\n",
    "plt.figure()\n",
    "plt.xlim([0.0, 1.01])\n",
    "plt.ylim([0.0, 1.01])\n",
    "plt.plot(precision, recall, label='Precision-Recall Curve')\n",
    "plt.plot(closest_zero_p, closest_zero_r, 'o', markersize = 12, fillstyle = 'none', c='r', mew=3)\n",
    "plt.xlabel('Precision', fontsize=16)\n",
    "plt.ylabel('Recall', fontsize=16)\n",
    "plt.axes().set_aspect('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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      "text/plain": [
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ROC curves, Area-Under-Curve (AUC)\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y_binary_imbalanced, random_state=0)\n",
    "\n",
    "y_score_lr = lr.fit(X_train, y_train).decision_function(X_test)\n",
    "fpr_lr, tpr_lr, _ = roc_curve(y_test, y_score_lr)\n",
    "roc_auc_lr = auc(fpr_lr, tpr_lr)\n",
    "\n",
    "plt.figure()\n",
    "plt.xlim([-0.01, 1.00])\n",
    "plt.ylim([-0.01, 1.01])\n",
    "plt.plot(fpr_lr, tpr_lr, lw=3, label='LogRegr ROC curve (area = {:0.2f})'.format(roc_auc_lr))\n",
    "plt.xlabel('False Positive Rate', fontsize=16)\n",
    "plt.ylabel('True Positive Rate', fontsize=16)\n",
    "plt.title('ROC curve (1-of-10 digits classifier)', fontsize=16)\n",
    "plt.legend(loc='lower right', fontsize=13)\n",
    "plt.plot([0, 1], [0, 1], color='navy', lw=3, linestyle='--')\n",
    "plt.axes().set_aspect('equal')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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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\" 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      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gamma = 0.01  accuracy = 0.91   AUC = 1.00\n",
      "gamma = 0.10  accuracy = 0.90   AUC = 0.98\n",
      "gamma = 0.20  accuracy = 0.90   AUC = 0.66\n",
      "gamma = 1.00  accuracy = 0.90   AUC = 0.50\n"
     ]
    }
   ],
   "source": [
    "from matplotlib import cm\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y_binary_imbalanced, random_state=0)\n",
    "\n",
    "plt.figure()\n",
    "plt.xlim([-0.01, 1.00])\n",
    "plt.ylim([-0.01, 1.01])\n",
    "for g in [0.01, 0.1, 0.20, 1]:\n",
    "    svm = SVC(gamma=g).fit(X_train, y_train)\n",
    "    y_score_svm = svm.decision_function(X_test)\n",
    "    fpr_svm, tpr_svm, _ = roc_curve(y_test, y_score_svm)\n",
    "    roc_auc_svm = auc(fpr_svm, tpr_svm)\n",
    "    accuracy_svm = svm.score(X_test, y_test)\n",
    "    print(\"gamma = {:.2f}  accuracy = {:.2f}   AUC = {:.2f}\".format(g, accuracy_svm, \n",
    "                                                                    roc_auc_svm))\n",
    "    plt.plot(fpr_svm, tpr_svm, lw=3, alpha=0.7, \n",
    "             label='SVM (gamma = {:0.2f}, area = {:0.2f})'.format(g, roc_auc_svm))\n",
    "\n",
    "plt.xlabel('False Positive Rate', fontsize=16)\n",
    "plt.ylabel('True Positive Rate (Recall)', fontsize=16)\n",
    "plt.plot([0, 1], [0, 1], color='k', lw=0.5, linestyle='--')\n",
    "plt.legend(loc=\"lower right\", fontsize=11)\n",
    "plt.title('ROC curve: (1-of-10 digits classifier)', fontsize=16)\n",
    "plt.axes().set_aspect('equal')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"550\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"550\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Evaluation measures for multi-class classification\n",
    "# Multi-class confusion matrix\n",
    "dataset = load_digits()\n",
    "X, y = dataset.data, dataset.target\n",
    "X_train_mc, X_test_mc, y_train_mc, y_test_mc = train_test_split(X, y, random_state=0)\n",
    "\n",
    "\n",
    "svm = SVC(kernel = 'linear').fit(X_train_mc, y_train_mc)\n",
    "svm_predicted_mc = svm.predict(X_test_mc)\n",
    "confusion_mc = confusion_matrix(y_test_mc, svm_predicted_mc)\n",
    "df_cm = pd.DataFrame(confusion_mc, \n",
    "                     index = [i for i in range(0,10)], columns = [i for i in range(0,10)])\n",
    "\n",
    "plt.figure(figsize=(5.5,4))\n",
    "sns.heatmap(df_cm, annot=True)\n",
    "plt.title('SVM Linear Kernel \\nAccuracy:{0:.3f}'.format(accuracy_score(y_test_mc, \n",
    "                                                                       svm_predicted_mc)))\n",
    "plt.ylabel('True label')\n",
    "plt.xlabel('Predicted label')\n",
    "\n",
    "\n",
    "svm = SVC(kernel = 'rbf').fit(X_train_mc, y_train_mc)\n",
    "svm_predicted_mc = svm.predict(X_test_mc)\n",
    "confusion_mc = confusion_matrix(y_test_mc, svm_predicted_mc)\n",
    "df_cm = pd.DataFrame(confusion_mc, index = [i for i in range(0,10)],\n",
    "                  columns = [i for i in range(0,10)])\n",
    "\n",
    "plt.figure(figsize = (5.5,4))\n",
    "sns.heatmap(df_cm, annot=True)\n",
    "plt.title('SVM RBF Kernel \\nAccuracy:{0:.3f}'.format(accuracy_score(y_test_mc, \n",
    "                                                                    svm_predicted_mc)))\n",
    "plt.ylabel('True label')\n",
    "plt.xlabel('Predicted label');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             precision    recall  f1-score   support\n",
      "\n",
      "          0       1.00      0.65      0.79        37\n",
      "          1       1.00      0.23      0.38        43\n",
      "          2       1.00      0.39      0.56        44\n",
      "          3       1.00      0.93      0.97        45\n",
      "          4       0.14      1.00      0.25        38\n",
      "          5       1.00      0.33      0.50        48\n",
      "          6       1.00      0.54      0.70        52\n",
      "          7       1.00      0.35      0.52        48\n",
      "          8       1.00      0.02      0.04        48\n",
      "          9       1.00      0.55      0.71        47\n",
      "\n",
      "avg / total       0.93      0.49      0.54       450\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Multi-class classification report\n",
    "print(classification_report(y_test_mc, svm_predicted_mc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Micro-averaged precision = 0.49 (treat instances equally)\n",
      "Macro-averaged precision = 0.91 (treat classes equally)\n"
     ]
    }
   ],
   "source": [
    "# Micro- vs. macro-averaged metrics\n",
    "print('Micro-averaged precision = {:.2f} (treat instances equally)'\n",
    "      .format(precision_score(y_test_mc, svm_predicted_mc, average = 'micro')))\n",
    "print('Macro-averaged precision = {:.2f} (treat classes equally)'\n",
    "      .format(precision_score(y_test_mc, svm_predicted_mc, average = 'macro')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Micro-averaged f1 = 0.49 (treat instances equally)\n",
      "Macro-averaged f1 = 0.54 (treat classes equally)\n"
     ]
    }
   ],
   "source": [
    "print('Micro-averaged f1 = {:.2f} (treat instances equally)'\n",
    "      .format(f1_score(y_test_mc, svm_predicted_mc, average = 'micro')))\n",
    "print('Macro-averaged f1 = {:.2f} (treat classes equally)'\n",
    "      .format(f1_score(y_test_mc, svm_predicted_mc, average = 'macro')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linear model, coefficients:  [-698.80206267]\n",
      "Mean squared error (dummy): 4965.13\n",
      "Mean squared error (linear model): 4646.74\n",
      "r2_score (dummy): -0.00\n",
      "r2_score (linear model): 0.06\n"
     ]
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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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lJH7KCO3UT7uIAAJhpvnGAKQ7MvEmhUIH3+Y3UcZuY8ychvl4w4CkGAYAwK0wZoVAAAA6UMAArTBmhUAAADpQwACtMGaFQAAAOlDAAK0wZoVAAAA6UMAArTBmhUAAADpQwCCUEQW7NPpa3Wv6Vyma1LoVLva0tFSnz59JH+sdx4AAADJYwoxx+TaNLyxFuzTLkzaipDrC/ZF1qzYuvUT069fX3Pxxd83ffv2s2fhEqandB9l5D7KyG2UjzuYhjcYbp5jci0AKZQF+/jQdx9l5D7KyH2UkdsoH3cQgARDFyykTFsHtOUjWvChNH/ZssU53x0LAAAA4SEAQcpYsA8AAADJIgBByliwDwAAAMkiAEHKWLAPAAAAySIAQcryYcG+fJs+GAAAwHUEIEhZLi/Yp9MHa9AxatQIM2/eHLNw4QJvr2nN1/MAAAAIH1OItVFWVjZAKs63NDY2niLJ7bIt2rlz50/efffdz8vLy2+R9DS9LkKum1pbW3ubHsvXjpSv/aUcDpL8F2Q/Qc6t0XN+5eY6INO82a50wHmEtnxo8OHqOiDJTh/M1Ifuo4zcRxm5jzJyG+XjDqbhDYYWkNak7ln0W6mU7tnQ0HCipMdI+pudOnX6adNpM1S2K6VC3S+y1dXV3aMnBg0atL/sHpGvvbe+vv5oOdbpoR6RLa9/QTW40Ir64sVPmcrKyWbMmHGmqmqqWbJkueTf7p13DdMHAwAAZA/RWwvl5eUHy+7NXbt27fv2229/qHllZWXny+4XtbW1A+T8OglMLlm1atViPdeSXFctwcrXampqTtJ0v3799uzatesHxcXF31q5cuVT3kU+5FoLSC7SsR7a3SqRysopprr6eu+Yt07uo4zcRxm5jzJyG+XjDlpAgqEFpIUdO3Z8IEHE1yPBRwv7DBkypJvsB5SUlNQ0ZbUmXze8sbHxaZs069ev/0zyXpaA5VibBUcwfTAAAED2EL3FV1xWVvaM7DfKdr0EFM9LkHG37M+Q/ceSd1Ntbe2v9EK57jXJm7Nq1ap5mlaSt0h2G+WayU05iW3cuK2xuJhiSaerrrrCzJ3rDduJa9KkKebaa2/wjktKik23bl3M1q3bTX09b51cRBm5jzJyH2XkNsrHHT16dKWyFgA3L47y8vJfyG5ycXHx0fX19UdJ4HGPBBmXy36J7EfIOT0/RgKMh+Xa1Q0NDddKAHKvfq2SAOR+2e2U8xOachKT79Eo39+mkA5r1641w4YNMxs2fDFovq2+ffuaF1980ey33342BwAAoInU1aisBcDNi0GCh/8nv1s/koBgtAQVv5OsoqFDh5auWLFiU9MVXoByq+wqampqTpPjN+TaW9u2gMj3+FDOt5o5Kx5aQDJj8uSJZuHC2LNgjRkz1syZM9/m8NYpF1BG7qOM3EcZuY3ycQctIMFw86KwgUWVVE4vqK2tXdiU255cpyvsTZYA41A5XizXPyfXX9N01ju/XPL+LHmzbFZCDELPjGSnD2bgn/soI/dRRu6jjNxG+biDQejBMAi9DQkarpagobKoqEi7VjUHH2VlZdWyLbXJiCNke0sP5Gt03Y8T9FjpLFiSd2RxcbHmI4B0rFaei9MHAwAA5AOitxYkwDhEAo/X5HCWVEBbzdO6e/fu/bSFQw6vlP3DElicJsc319fXn7x69ernKyoqDpT8NyVvpuQ9KudnyPHBEsRokOK7VYMWkC80tVJM9dbs2LhRl1Vp0qtXb28F9kwucshbJ/dRRu6jjNxHGbmN8nEHLSDB0ALSggQfZ8muRLarpPK7vuVWU1Pzopz/jpy7UIKL1yXYmCbbWA0+9GtXrlz5juzOlbzxJSUlL8pxT7n+bNkTUKRIgw9drbxl8KE0rfnahQoAAAC5hejNMbSANNFuVqNGjWgXfLSk4zW0C9WAAQNtTvrw1sl9lJH7KCP3UUZuo3zcQQtIMLSAwEnz58+JG3woHTw+f/5cmwIAAEAuIACBk1itHAAAID8RgMBJ3bt3t0fxde9eao8AAACQCwhA4KSJEyd7s13Fo2NAJk7UpVgAAACQKwhA4CQdWK5T7RYVRR/jpfm6YGAmBqADAAAgPAQgcJau8zF69DivpaMlTY8ePdY7DwAAgNzCFGKOYRre9nRKXp0VSweml5b28Lpd9e8/wJ7NDKY+dJ/LZdTyd1jHN2kXw0JsveM5ch9l5DbKxx1MwxsMN88xBCBu4kPffS6WkUur+buA58h9lJHbKB93EIAEQxcsAAVBWyFmzLjSTJtW5e01nW6s5g8AQHsEIADymrZCaNChK+vPmzfHLFy4wNtrWvP1fDpogKMtH42N0Rs1NX/ZssUZCYQAAHAJAQiAvJatVghW8wcAIDoCECBNstHlB61lsxWC1fwBAIiOAAQIWba6/LjCpcArm60QrOYPAEB0BCBAyAp14LGLgVc2WyFYzR8AgOgIQIAQZbPLT7a5GHhlsxWC1fwBAIiOAAQIUaEOPHY18AqzFUL/35PtWsZq/gAAtEcAAoSoUAceuxp4hdEKEaRrmS4yOHv2XLN48VOmsnKyGTNmnKmqmmqWLFku+bcX1CKEAABEEIAAISrUgccuB15BWyHC6FqmAU519Swv6Jg58zrTv/8AewYAgMJDAAKEqFAHHrsceAVphXC1axkAALmMAAQIUaEOPM6FwCuVVggWEwQAIHwEIEDICnHgcb4GXiwmCABA+AhAgJAV6sDjfAy8WEwQAIDwRX9diazZsGFr9M7myKoOHYpNaeleZvPmT83u3Q02F9HoeAjtuqStB6WlPbxuV5kYdJ2OMtJ/i852Fa8blgZYGmzmW7e6dOA5ch9l5DbKxx19+nSjDh0ALSAAQpXKWAtX5WvXMgAAsokABADiKMQxPQAApBPNR46hC5abaPZ2X7rLKFtdy/IJz5H7KCO3UT7uoAtWMNw8xxCAuIkPffdRRu6jjNxHGbmN8nEHAUgwdMECAAAAkDEEIAAAAAAyhgAEANJMx4/MmHGlmTatyttrGgCAQkX/NccwBsRN9Lt1n4tltHv3bjN9+lSzdOniVmuJ9OrV25veV2fQyteFKaPhOXIfZeQ2yscdjAEJhhYQAEgTDT4WLXqw3UKGmtb86dOn2RwAAAoHAQgApIF2s9KWj8bG6I2amr9s2WJf3bHowgUAyCcEIACQBrpmSNuWj7Y++miDXDfXptrTLlwadIwaNcLMmzfHLFy4wNtrWvP1PAAAuYYABEBSeBvvjy5Y6MeWLZvtUXt04QIA5CMCEAC+8DY+Od27d7dH8XXvXmqPWtPALqwuXAAAuIQABIAvvI1PzsSJk73ZruLp3buPXDfJploLowsXkAwNZq+66gozfvx4b09wCyBdCEAAJMTb+OQNGDDQm2q3qCj6TI2af+qpo7zrogmjCxfgR8vWzblzbzP33Xeft6d1E0C6EIAASIi38anRdT5Gjx7ntXS0pOnRo8d652MJ2oUL8IvWTQCZRgACICHexqdGFxmcPXuuWbz4KVNZOdmMGTPOVFVNNUuWLJf82+MuQhi0CxfgB62bALKBAARAQryND0a7WVVXz/KCjpkzrzP9+w+wZ2IL2oUL8IPWTQDZQAACICHexmdHkC5cgB+0bgLIBgIQAAnxNj47gnThAvygdRNANkSvTSBrNmzYGr0jLrKqQ4diU1q6l9m8+VOze3eDzS0sOhOODkbV/uDaJSNC38Zr8KFv47NZIaaM3EcZuUfHduhsV/G6YekzrkEwLxiyj2fIHX36dKMOHQA3zzGFGIDoH0Dth6xdAfRtnHb3ce0PHR/6X2hZXqWlPbxuV37GNKQbZeQ+yshNOtWuznYVbSC6tm5qdz9tcUP28Qy5gwAkGG6eYwopAGl6oz7Vm4Gl5ds3HWug3X2y/Ua9JT703UcZuY8ycpPrrZv4As+QOwhAguHmOaaQApDEb93Gef3fXcCHvvsoI/dRRm7T1s0775xrPvuszuy1197m0kvdaN3EF3iG3EEAEgw3zzGuBiAaJPx65UPmqbVPmKlfucwM7XmoPZOaXOt3zIe++ygj91FG7qOM3Eb5uIMAJBhmwYIvf13/vJn6RKX5Xe2vzUmLjjV95nbzApJUMfc8AABAYSIAgS/77tXPHn1hyrKJXiBy2ZNTzK76XTbXH+aeBwAAKEwEIPDlwH0OMo+du9SmWlvw5v1mwPyeZtCdA8zqLbU2Nz7mngcAAChMBCDwbdi+x5gNk7aaNy5ebQ7p0X4MSN2ubebYB4/yWkVu+OtPbW50rKwNAABQmAhAkLTee/Y2y8c8b9ZXbjYTDptoc1u76aWfe4HIAXf0jTrLFStrAwAAFCYCEKSspLjEXH/iz71WkdmnRF+kavvu7abv7ft4wciHn35gc5vo3PI61a62dLSkaV34Ss8DAAAgvzCFWBtlZWUDioqKbmlsbDxFkttlW7Rz586fvPvuu5+Xl5cfJPl3yvljJf/dhoaGH65atWqxfp2Srx0p534ph4PkuhdkP6G2tnaNd9KnXF8H5P/e/pO56P/Ot6nofjzsCnP5MT+xKXdX1m6JqQ/9y9bK9pSR+ygj91FGbqN83ME0vMFw81orkiDjOQkeNktw8R/FxcU9JKC4R/IfqampuVwCjH/K8WuyXSfb2XLuqt27dx+yZs2a9wYNGrR/SUnJCsm/Wr72z/K1M+T4EAlAvix730FFvixEuHH7RjP03kE2FZu2nuQCPvQTy/bK9pSR+ygj91FGbqN83EEAEgxdsFqQ4KNCdsOlIjV+9erVb0jw8IwEIzNkGyvnTpZzg7t06TJR8t+UbZbkPy9BxyX6tbKfIAHJ3yX/Rv3aurq68ZJ9YEVFxQg9X2h6denlBRcfVn3iHceiXbN0q9tVZ3OQqzT40JXt267vomnNnz59ms0BAACFjACkhR07dnwgQcTX33777Q9tVsQ+EmwMl3Mvv/rqq5/aPPWs5Gl3LB00PVyuedrLFevXr/9Mr29oaPDOFyq5B2bF+DVeMPK1gRrDRTfozv5eILJgxf02B7lEu11py4c8AzanNc1ftmyxd10Q+vUzZlxppk2r8vZBvx8AAMg8mo/iKy4rK3tG9hulIv2eVKJ619bWjmk65bWYVMluSk1NzaFy3Wtyfs6qVavmNZ31xoQskt1G+ZrJTTmJbdy4rbG4OL+LZdm7S815fzjbpqIrkv8+nrbNprKvpKTYdOvWxWzdut3U19Ps3dZVV11h5s69zaZimzRpirn22htsyj/t3vWDH0w2f/7z/5nNmzfZXGN0zNDXv36GueWWOaZTp46UkeN4jtxHGbmN8nFHjx5dqUMHwM2LQwKMX8hucnFx8dH19fWXSRDSQYKNi5rOGlNRUXGJBB0/kbwhcu3qhoaGayUAudee1gBEX+fvlABkQlNOYvI9GrXVoBB8uvNT03VWV5uKrWFGQ8zpehG+tWvXmptvvlkq+pulgl9qLrvsMrPffvvZs9GNHz/e3HfffTYV28UXX2zuvbf5EfHtoosuMvffH7t1TM/7+fkAAIRB6iVUTALg5sUgwcP/k9+tH0lAMFqCit9Jeo5k92zbAiIBSJXkHS7Hb8i1t7ZtAZHv8aEEKL47vxdCC0g0PWYnDkSeGfuCObTXl2wqswrhrVOklWHp0iXmo4822NymaZFHjhzltTLEGkSuX/fAA7+yqdguvPAi7/skY926deboo48wO3Z8bnPa69y5s3nppVfN0KFlvBl0GG9v3UcZuY3ycQctIMFw86KQYEIXoNDg4gIJLhZqngQTP5Fg4jQJJk7StJK8mZI3XPJOl69ZLNc/J9dfY0/r91kueX+WvFk2K6F8mQUrVVVLJpjf1f7apqL7cu8jzZLzlttUZhTCzCM6rkIHi8vvrM35gr7o0TVbZs+ea3Na+/73x5tHHvmdTcV2zjnfNvPnJ9cCctllU8yCBYnHBmlwc//99zE7jMOYwcd9lJHbKB93MAtWMAxCb0OChqulAlYpFa4xkeBDSfoFyf/KwIEDu9gsdYLk6XofWmnT/Ql6rPr167en5B1ZXFzsnYc/t4+6yxuw/sR3/2Jz2nvlo380z56FcAQdRL5ixRv2KL433vB3XUsvvvg3exSf3+sAAEB2EYC0UFZWdojs/luCjRtKSkqeHTp06L6RraamZrnkr+3Spcu9gwcPPlQClSvk2mPq6+vv1q+VQOMeOX+85uv5rl276mvet1euXPmUnkdyvtTrsOZpfOOJBCJbPt9sc5AKXTiw7fS5bWm3rPnzo7eA+O0Jm0qPWb9fEyt4AgAAbiEAaUECiLNkVyKbLjC4vuUmeRJr1J8l1/ST4OQlSV8g2zm6CKHsjQQa78juXKkEjZfzL8pxT7lWp3qiVhSA3EMvENEtnvJ7DvACkWueu8rmIBm6arkfW7ZED/SGDvU3NsfvdS0NG/ZVexTfMccMt0cAAMBl9F9zTKGPAfHjpr//zNzwt2ttKrZEQUsyUul3q92VtGVBK/fdu3c3EydONgMGDLRn3aJrasybl3hweGXlFFNdfb1NfcHvOI1x4y4yN9+sQ6z80/s4fPiRuk6PzWmvU6fO5sUX/2kOO6yCvtEOo/+6+ygjt1E+7mAMSDC0gCDnTB92uRdcvDn+bZsTXaR7Vqa75uhsUjqge9SoEV6lfuHCBd5e05qv512jwVGvXr1tKjqdDWvixEk21Vp9fb09iq++Pvl/uwZtZ511rk1Fd9ZZ55iBA90M7pAdGriyaCUAuIkABDmrZ5eevrpn9b19Hy8Q+eOqh21Oek2fPtWbTartmApNa/706b5nZc4YreSPHHma1+UtGs0/9dRRMVtwtIXHj+7dS+1Rcn75yzlmzJgLTI8ePW1OE02PGTPOOw+oXHwBAACFhuYjx9AFKxgNNPxItnuW32ZvfcuqFZ14A7q1JWHx4qec646lFTMNjnS2q7brgGjwcdNNt8p9iL4OSKb+3fpzIt3adBV0bZHp33+Ad46uCe7LRBlpkJHqdNLgOXId5eMOumAFw81zDAFIOBa/83/mgsdG21RsfgMRvx/6QcdSuCBeJT+exBW/sVLxu93mhI8/zO5Ldxnl8gsAV/AcuY3ycQcBSDB0wUJeOu3AM7zg4oOq+LM7RcaJbPjsizf+QQSdTcoFWjGrrp7lBQszZ17nK/hQ2kKib5e1gteSpjX40PNAOgWdThoAkBkEIMhrxUXFvsaJfOm+IV4gMviuYG9F0z0WwmXaPUu7tujb5crKyd7YjKqqqWbJkuVeMBOr+xYQlnx4AQAAhYAABAUjEogc0uNQm9Petp1bm1tFUhF0Nql8kGoLChBUIb8AAIBcQgCCgrN8zPNeIPLCuH/YnOgigUgy0/hq5TvIbFKIT/v4M7UqYuEFAADkBgIQFKxB+wz21T1Lp/HtMbur+enyn9qc+BgLET6mVoUfvAAAgNzACH7HMAtWdvntepUoaFGpziaF9vxMrTp37jxmh3FcJmbwCTKdNJhlyXWUjzuYBSsYbp5jCEDc8B/LLzO/euNum4rNTyCCYPxOrbps2dPmsMMq+MPssExWnngBkBoquG6jfNxBABIMN88xBCBu2Vm/0wyc38umYvvruH+ag/YZZFMIk9+1VSZNmmLmzLmVP8wOo/LkPsrIbZSPOwhAgmEMCBBHx5KOXivHpml1Nie6ry44ItDsWYjN/9Sq/q6DO5hUAAAKEwEI4FPj1Y0JAxFFIBIu/1Or+rsuG6hot8akAgBQ2Gg+cgxdsDKrZT9xrcDqNJ7RZsiJ1uy9fO2T5rxHz/KO42GcSDBaRrk6BqRpQPRUs3Tp4lb//zpVrM7WVGgDoiPP0dixF0jQEX9SAV3UEplHFx+3UT7uoAtWMNw8xxCAZEayFcNEH/p+WjzOLfuOmTfqHptCMhLPgjXWzJ0737k/zIn/vwuroq3PUV3dJnPUUcNazVDVlgaUuqI+0+VmHhVct1E+7iAACYab5xgCkMxItmLo90Pfb9crbRXx2/oCf1Ordu7c0ak/zH5bbnK5op3s77A+Rz/96X+bm2++2ebEVlk5xVRXX29TyBQquG6jfNxBABIMN88xBCDpl0rFMNkP/WEPHGbe2/auTcVxjd2LMLvl5Gtw0/Lf1XZqVdf+MPudvSsXK9qpdi3TMpo+fYq57777bE5sY8boS4DbbQqZQgXXbZSPOwhAgmEQOgqOVmDjBR9K37LPn59615i/X/ia18qxekKCwcYagOjWx3j/T9oqo2/6U6UVw3we3KtBVHX1LK9iOnPmdU6v66BBkh9btmy2R7lDgw/9XW37HPn5HS4tLbVH8XXv7u86AEDuIQBBwclkxXDvjt28QCThQPRJskkgojNtaTcjfdOfiiAVQ4TL76xcuVbR1t9NbfmI1n1RaX683+HLLrvMa2GMR89r6xYAID8RgKDgZKtiqEFI5QeTbSq2jyZvMEf+YahN+Re0Yohwabc37ZIUTy5WtIO2IO63335m5MhR3liraDRfx/XkQ5dBAEB0BCAoONmsGHqtL5FuV//nZcWU7HoimehaBv+0Aq3jIfKtoh1GC+Itt8zxJnpo2xKiaZ3RTMeQZJMG6azbAgDpQwCCvBatIpHNimGr1pe/yhYJRuKIBCLf/uO3bE50+TzmIFdpRdrlinYqwmhB1AHqOsucTvRQWTnZG3BeVTXVLFmy3Bvfk621UfJ9DBUAuIIR/I5hFqxwJJql52c/u9lcfvn0uNO6JrMOiF8aAMWdgStBMBIRbUxJPs+65IfLs8NouceavSvXJPwdFvocRZte2PUZfDTI0LFSfqfnzkfMsuQ2yscdzIIVDDfPMQQg4fBbkfBbMQzzQz/x/9tYs/DgBTYnvpaBSJCKYT7gD3Pm+PkdjjaFrstlVOjPTwTPkdsoH3cQgARDFyzkHa1I+B2MrRWJTE/r6qdbTmTmrNcvXmXPRhfpnrXmk9XevyUfxxzAPfnYtYwxVACQOQQgyDuuVyQi/d/vv/8hc9hhXzYHHjjIHH74EeaBBxZ6gVDLrl999uzTHIzEM3zBkV4goi0n+VYxhHtcHcMRBGOoACBzCECQd1yvSEQGul544Rjz2muvmHfeWWNeffWf5oILRnv5sQa6+glE1MKD/8ebyjdfKoZwVzZaENMlX9dtAQAXEYAg7yRTkdBuWJmebjPoYoGRQOT8gy+wOdHN23eO1yKS6xVDxJeN3+F8lK/rtgCAixhA4xgGoQenFbBEg0m1onHccceb5577S6vrIrNkaVellq0FYQ388/P/ppWcZAe6averRM4t+46ZN+oem8o/hTY4M9FMb21/h13gehmlOrg+nzDI2W2UjzsYhB4MLSDIO34GY++9997m0Uf/0C4Q0LSfVohUpWt8ip/uWb+v/W3zoPVcxdv+LwRtSUN7+Ti4HgBcRPTmGFpAwtH0dnha1HU+hg8/zjz/fOuWj7batkKE9dZJK866uFkiOnYjyJtWv0GGnzElLvDztr9z544F82YwXS1p6ZYrb2/1/ubLui3J4g272ygfd9ACEgwtIMhL8WbpGTBgQNyKm0rXLFmZGugaaRF5+cI3bE50kRaRf9W9b3PcxNv+1pgyNr3yaXA9ALiIAAR5LVpFIpuzZGV6oOvAvffz1T3riPsPcbZ7lr6N9rOuy7p1hdMdiyljAQC5jAAEBSeb0236GZ+SrsUC/QQiyrVAxO/b/nnzbrOp/MeUsQCAXEYAgoKT7ek2sz3QNRKInHnQN21OdK4EIv7f9vu7Lh8wZSwAIJcRgKDgZLMVQsUbn6JdxTI1dep9Zyzw1SoSCUQmPH6Rzcks/2/7/V2XD7L9OwwAQBCM4HcMs2BlRmSWrMcff8xs3rzJ5hpvxpvTTz/Da4VIxzogrvPb4uGnK1csLWcY0qBB3+bHqyj7nfFp2bKnzWGHVRTM7DDxZnrT4KPt77ALmMHHfZSR2ygfdzALVjC0gKCANZri4tafH23ThcZPi4hKpXuWVph1GmINJubNm+NNR6x7TWu+no/G79v+gQML622/Ky1pAAAki+jNMbSAZEbiFY91HY4vpjAt1LdOKz5+w5y06Fibiu31i1eZPnu2HtPSVrL3vCU/b/sLaR2QXMXbW/dRRm6jfNxBC0gw3DzHEICkXyqLuPGhH6x7Vir3PJqW3bfaLhBHGbmPMnIfZeQ2yscdBCDB0AULBYdF3FITpHtWWPdcgxMWiAMAILcRgKDgsIhbMJFA5PDeR9ic6FoGItxzAAAQQQCCgsMibuFYet7TvlpFNAhZePACY+IvO+LhniNCu9vNmHGlN3ZI95oGAOQH+q85hjEg6ccYkPRp2/UqpmvsvgUdiP7YY0vNUUcdbXOSQxm5z08ZNU04MNUsXbq41TOqCy/qbGguTi+cT3iO3Eb5uIMxIMHQAoKC43da13iDoRGdnxYRjwYgbYIQnR3rD3942KZQqDT40NnS2r4g0LTm62xoAIDcRgCCnJdKVw19i6rTvmpLR0uaHj16rHceqYsEIn86d4nNiSESiHTxUowBKXD67GrLR7SpmpXm61TMdMcCgNxG85Fj6ILlXxhdNbQiE2ta15Zyrdm75b/Lz2rj6aaB4bx959hUfL5aUKKga4L7EpWR93syL/HvSWXlFFNdfb1NIUw8R26jfNxBF6xguHmOIQDxL8jCdsnKlQ99V/vPa0DUPO4myviPaJINRPjD7L5EZaTPtK6Qn4iu+q5TMSN8PEduo3zcQQASDF2wkJPoqhGdq/3nW427iTL+I5qW0/iiMDBDHQAUBgIQ5CQWE2zP9aCs3bgbG4j0ntN6HE5bkUDkP5+ebnOQr7SroLbWxaO/P9pVEgCQuwhAkJNY2K4914My7fqlXeJ0euPKysleN5qqqqlmyZLlzYPW47n39btoFclzzFAHAIWBAAQ5KRe6amhLQ7KzcwWRK0GZVh6rq2d5ffhnzryu1aB/P4GIIhDJX8xQBwD5jwE0cQwZMqRTcXHxS0VFRVNWrlz5lOaVl5ffIrtWHekbGxun1tbW3qbHZWVlI+X6X8rhIMl/QfYT5NwaPecHg9D90cp8sosJBpHMwL9sDQTPxxmElrzzZzPuse/aVGxrJrxvuu+5D4MzHZfMc6TPuJ8Z6hAuBjm7jfJxB4PQg+HmxXDAAQd07tSp04NyeI4EFCe3CEB0YYNlUoG8T9Nq8+bNW9evX//ZoEGD9i8pKVkhWVc3NDT8WYKXGXJ8iAQgX5a9r8CCAMS/xLNgjQ1tppxkPvQzOTtXS5kOyjLNb4vHpml1/GF2FJUn91FGbqN83EEAEgw3L4ohQ4YMleDhQalASn2x6PA2Acg6CS4uWbVq1WLv4hbKysqq5dqv1dTUnKTpfv367dm1a9cP5Ht9K/L1ibgcgOx96cWm8x9+b1NN6vv1t0fGlKz/l2ksLjZFDXwoAgAA/1rWJ5TWKT4/+1yz7Y7m971OIQAJhjEgUUjAMEKCjyfr6uqOtVkeCUz0FeyAkpKSmqac1iT4GC5f97RNGm0VkbyXJWBp9X1yVdvgQ+kHRGRTBB8AACBZLesTkTpF50fa1zuQHwhAoqipqbm9trb2Mg0gbJZHgolDZNcoAcV/aUtIWVnZK7Jd1HTWGwvST7amp8aS9Ieyy4spW/RNRFv6xiKyKW0BAQAASEbL+kSkThGt3oH8QPNRAhJoaD8srwuWBhtyfI8EFZfLfonsR8glv5BtjAQsD8u1qyU4uXbVqlX3el8s5Gvul91OOT+hKSe+jRu3SR2eYnFNSUmx6dati9m6dbupr4/dynPyycebV155xaZi+/KXjzBPPvmsTSEMWkb73LynTcWn40SQeX6fI2QPZeQ2yscdPXp0pbIWADcvgZYBiCSLhg4dWrpixYpNTWe98zonZEVNTc1pcvyGBCC3SgAyr+msF4Askq//UM77WoJavl5/nk0h13z3u981v/nNb2wqtvPOO8/8+te/timErWimv2eo8WrmfAAAJE/qalTWAuDmJdAmAGlHzuuSvJMlwDhUjhc3NjY+V1tbq2s8eyRvueT9WfJm2ay4aAFxy7p168y8ebd5U4H27dvbTJhQZfrZpuForrrqCjN3rjcjc1yTJk0x1157g00hDNHeDD666g/mosfGecfx/GvSRtO5Q2ebQrrw9tZ9lJHbKB930AISDDcvgZYBSFlZWbVkHSfBxMims975O2TXUwKQb7c932IWrLPk65/UvESYhtcNsdby0GlsdSXmWGt55PtUuC5LND2l32l8/SyEiNQwhaj7KCO3UT7uYBasYBgxnAQJRB6V3QgJNH48ZMiQwRJ8VEn63+vr63UciM6edY9cc7zkXzF48OBDJfjQsSBvx2o9QfppQJDKauQafOhaHm0DiY8+2uDlT58evUedBhW62GCsllnN1wCG4CPzWGUdAAA3EIAkoaam5kWpQH5HDi+UYOP1xsbGabKNXb169fN6XgKNd2R3ruSNLykpeVGOe8r1Z8ueVo0M0xYMDTq0NUJXB1+4cIG317Tm6/lYNEjRlg8pR5vTmuYvW7Y4ZjCjrSO62KC2dLSkaV0cUc8jewhEAADILpqPHJOPXbC0oj5//hxvHEX37t3NxImT094CEGQ1cm0p0WAlkcrKKaa6+nqbaq/lv7u0tIf8uyeZ/v0H2LP5KxvlrVLtmlDfUG/6zSu1qdiuP+FnZsLhlTaFVNB9xH2UkdsoH3fQBSsYbp5j8ikAiTWOolev3l43pVjjKILSCnCQcRgavGiLSSJjxmgQc7tNIVvlHRHGH2bGiaQXlSf3UUZuo3zcQQASDF2wkDaxxlFoOt44iqD07Xu84EPpWI7586O3gOhbez+6d0/81ryQZKu8w0T3rORosJ/KGCsAQGEjAEFaaEUkyDiKILTrjx9btmy2R61plyF9ax+PtqBolyo0yWZ5p0MkELnppPjjdSKByO6G2GOK8lGQMVYAABCAIC2CtkIEEbQFg5mskpfN8k6nC4Ze5KtVpP+8HgXVKpIPrV0AgOwhAEFaBG2FCCKMFoxYM1n16cNMVtFks7wzxU8govI9EMm31i4AQOYRgCAtsjmOIowWDB0srbNk6UD1ysrJZuzYC8yPfvQjqVg94w08T+dg6lzkyriZtWvXeqvRp3NMQqEHIvna2gUAyBxG8DsmX2bB0oqf35moVNjTtjbNyDTNexOrlaEI/ZnxVjKPhZlH4kumvNPRdU3L+0c/mirlvUSeoS/KOxMzcO2q32UGzO9pU7HNG3W3ObfsPJtKjt7fsJ+RVAWZJY7nyH2UkdsoH3cwC1Yw3DzH5NM0vFpR0f7g0bpqaCvEeeeN0dXj0zpta8uKW5C1OPjQTyxReWvXtXRNW5z4Z8de9yVMfls8/nHWCl8BRLanNo4myDo5PEfuo4zcRvm4gwAkGG6eY/JvHZDYrRANDQ3mN79ZmPVKox986CcWdquTX2G1voTZyuA3EPnX9zfFvSeuBFYtBbnfPEfuo4zcRvm4gwAkGG6eY/J9JfRIK4RWqLLZZSdZfOj7F1ark19BV65PZyvD6VefbP7R9yWbiu2Dqi2muKj1kLywAqt0SLW1i+fIfZSR2ygfdxCABMPNc0w+BiDRBK00Zhof+u7SynCQlevT1crQLoC4pmmXSGSAu8vPSKqtXTxH7qOM3Eb5uIMAJBhmwUJW6NtxP3J52lZkRpAZuDRISNeUstoK1Kr1QgMQH0FIZPYsl58RDS5azhKnwV1V1VSzZMlyL8hLR1c7AED+IABBVrgybWs6aaVV32LrG3bdp1KJRWJB1n1pFyREkeqUsjEDCJ+ByMKDF/i6LpvPiHb9qq6e5QUdM2del9audgCA/EEAgqwIY7FAV2n3FA06tPuNdqHR7kG617Tm63mERyvBqa77ks5WhoRBtg1EJnxQ2ZSOJRKw7O+lWsnVZwQAUNgIQJAVQSqNrtMBzTqmoO2bdU1rvvadV7SQhEfHHJx//jjTt29fm9NEK+jxVq5PZ0uc3yB78sRp/hY3vES2SDAicvkZAQAUNgbQOKZQBqGrbE3bmgq/A/80iPAzc9Hw4ceZ55//S6vrsrm2Qz7QMqqr22RuuOFnZtOmzVJeiWfg8lteqc40lXiAe/TZosKaxtc1DKB1H2XkNsrHHQxCD4ab55hCCkAitBKYyWlbU+H3Q9/vzEWxNFVKE8+61PKeBV2zIl+k+oc51SDBj6BB9v1v3Gt+vPwHNhXbh1WfeP+vrqPy5D7KyG2UjzsIQILh5jmmEAOQXOD3Q18rs36mhI0n3hv3pgqtWytjuyLVP8yZaIkLI8j20ypy6v6jzEP/9jubcg+VJ/dRRm6jfNxBABIMN88xBCBu8vuhH7QFJCLW2g6J39a7s3p8pgX9w5wLLXHKb/eshGNKsoDKk/soI7dRPu4gAAmGm+cYAhA3+f3Q9zOmwI9oi+b5+d5BxivkukL7w5yLgQiVJ/dRRm6jfNxBABIMs2ABIdKKf7zZvfyKNutSOtesQO4Z89Y4UzRTfs+usxkxaKCi21ub3rQ5AABkFwEIEDIdM6BdobQ1oiVNf+tbZ5uOHTvanOg6dersdf9pK51rViC3aGtY8wruuySjxfS8sXxt4VebgxEAALKJAAQImQ5Y1nEY2hWqsnKy152qqmqqWbJkuZk58/qUW0cKYfV4+BOzNcxHIKIIRAAA2UQAAqSJdseqrp7ljeWYOfM6b0CzVhx37Nhhr4hux47Po3ajyufV45GchK1hNhA5ev1Xm9IxEIgAALKBAATIoCDdqBKNL9F8VsYuDH5bw44qOtrXKuuRQOQnz/yHzQEAIH0IQIAMCtqNKt74El0wT88j/6XSGuYnELnrtfm0igAA0o4pxBzDNLxuCmvqw7Cm0s3mmhUtf7ZLq7AX2vSUQVdw9xtkhDmNL1OIuo8ychvl4w6m4Q2Gm+cYAhA3hfmhH7TimC2ur8Key3+YUwnqwlrBfdvOrWbwXYkDyL9f8JrZv9sBNpUaKk/uo4zcRvm4gwAkGG6eYwhA3BTmh35YFcdMc30V9lz8wxxGUBdma1i6W0WoPLmPMnIb5eMOApBguHmOIQBxUzo+9LPZjSpZ+v/q+irsufiH2dWgLl2BCJUn91FGbqN83EEAEgw3zzEEIG4q9A/9GTOuNPPmzbGp2Corp5jq6uttKrNyrYxyIah7YMV95kdPTbOp2PwGIlSe3EcZuY3ycQcBSDDMggUgIW2l8YNV2P3T1q94wYfSLnrR1oTJlAuHXuwFF4kCjMjMWXe/Nt/mAAAQGwEIgIRYhT18uRbU+QlErnzmP5qDEQAAYiEAAZAQq7CHL1eDukgg0q3jPjYnOgIRAEAsBCAAEtIxCKzCHq5cD+pWTVjrBSKrJ6yzOdFFApHNn2+yOQCAQkcAAsAXnRKWVdjDky9B3d4du/nqnlVxz4Gmx+yuZuicoTYHAFCoGMHvGGbBchMzj3zB1emDc7GMcnVNmET8dr1KFLQg8/iscxvl4w5mwQqGm+cYAhA38aHvvlwuo2wGdS1/tt9V2P1a9NaDZuoTlTYVG4GIO/iscxvl4w4CkGC4eY4hAHETH/ruo4ySE8Yq7Mnw0yqy8N9+b07Zf6RNIRt4jtxG+biDACQYbp5jCEDcxIe++yij5GRjFXYtIx0H4getItnBc+Q2yscdBCDBMAgdAAqMdrvSlo9owYfSfB2XoteFrfHqRrNpWp05tOdhNie6yOxZAID8QwAC5CGtOM6YcaX3llv3yVQkg3wtcoMLq7A/OfovXivHmgnv25zoIoHIZ7s+szkAgFxHAALkEe3Xr4HDqFEjzLx5c8zChQu8vaY1X8/HEuRrkVtcWoW9a8e9vUAkUZerA+/c1wtErn+h2uYAAHIVAQiQR3RQsfbrb/t2W9Oar1O+xhLka5FbXF2F3U8g8suXf0H3LADIcQQgQJ7QrlKp9usP8rXIPa6vwh4JRH73rUdtTnQEIgCQmwhAgDwRpF+/C2MCwrB27Vpz1VVXMH4lgVxZhf3EgSN8tYpEApE3P15hcwAALiMAAfJEkH79Lo0JSIWOT5k8eaIZNmyYmTv3Nsav+KDrfOhUu9rS0ZKmR48e6513iZ9AZMSi4V4gcuJDx9gcAICLCECAPBGkX7+rYwL80vErCxc+aDZs2GBzmjB+JTZdZFDX+Vi8+ClTWTnZjBkzzlRVTTVLliyX/Nu98y6KBCLfO+z7Nqe9lZvfonsWADiMRVQcw0KEbsqFxZ+0u5G+8Y/XlUrfbmuFs23XmiBfm225/P9eaNLxHNXt3GYG3TXApmJ7f+LHZo+SPWwKsbDQndsoH3ewEGEwtIAAOUgr3W3X6gjSrz/I12ZbvoxfQWr8TuM7YH5Pr0Xk8Xf+z+YAALKF6M0xtIC4yZW3TjqWQbsb6YxVLSvdOqORBhDXX/9zCRROMO+883arGa00gDjwwIPM8uUvmM6dO9vc1pq+9zRvtiutsEdo64EGHzomwMVuORqE6ZiPRLSLkXYtQvZk6jkadOcAU7drm01F163jPmbVhLU2hQjesLutEMpHX6jpiyUdm6jdg3XWPhdfftECEgw3zzEEIG5y5UNfK9s6piHadLmRIKNt8BGh53XQsfb7j6flh39paQ9vKtb+/RN3cckWbQHSAeeJVFZOMdXV19sUsiETz1GrIL1IgvTJ9kQciVpPCgkBiNvyuXwSvWBz7SUYAUgw3DzHEIC4yYUPfT9jHTTIiLWWh8rHsRB+7gtjQNyQiecoZpB+jd3H8c9/f9P07+pusJ0JBCBuy+fySfSCzc8LtEwiAAmGMSBAjvAz1iFe8KEyMRZCA4K241PSKZfHryBc+rsWc0FNDUASBCFH3H+IN07kqmf/0+YAyIS4z67QfBbDzS8EIHEMGTKkU3l5+esVFRUn2Swj6YPKysqWyv5T2VbINafZUx45N1K/RrbP5PgJ2QbZU0AgftfqSCRda3lo87kGHdoaoV2iMrkWhzbNn3/+ONO3b1+b00RbPlxc0wLp4SdI1yCk8oMp5qaTYv9O3PHq7UzjC2QQk4kUHgKQGA444IDOxcXFD8nhoU05niKJwh+R/QeyHybbA3LNw4MGDdpfT9r9I5J/b319/dFyrE+TXk8zHQLzu1ZHIulay0P77mrzeds/IppO91oc2i/4ttvmmRdffNFMmjQlZ9a0QLiSWVDzgqEXeWM/3r50vc2NLhKI1DfU2xwAYcv1xXCRPAKQKIYMGTK0U6dOL0ggMdhmecrLy0+W3eAuXbpMrK2tfVO2WXLN8yUlJZfoedlPKCoq+rvk37h69eo36urqxkv2gRUVFSP0PBCEzgSig/HiidUNKUJbBHRQedhcbD5vbGyI+f+D/JTKgpp77bGXr2l8+80r9QKRFz/4q80BEJZcXwwXySMAiaK4uHiEVFyelADiWJvlkbzhUsF7+dVXX/3UZqlnJc+7TvbD5ZqnvVyxfv36z/T6hoaGVt8HSIWfsQ46C1a88+kaC5Ht5nPt3jV58kQzbNgwM3fubRnt/gV3+AnS4wXhkUBk5P6teta28o3fj/ICkdGPnmNz2tNAO5PjoIBcF/TZRe6ha1AC5eXljVJxO3nlypVPyfGtEmD0rq2tHWNP6/kq2U2pqak5tKys7DU5P2fVqlXzms56Y0IWyW6jfI2PySC1u8q2xuJiisU1JSXFplu3Lmbr1u2mvj57M49oRfqHP5zitTZs2PDFWh19+jSt1XHjjbeYH//4hzHP33LLnLR0R9LK/0MPJV6LY+zYC7yuUmHTn79wYezZU3R8SDp+biFYt26dBHO3mc2bN5vS0lJvOuOBA1MLYjPxHCX6XRgzZqyZM2e+zYlv9ZZV5uj7j7Cp2DZNq/P2+nz+4AeT5flb0m4tnZEj0/f8hcmVzzpEl8/lE+azmwk9enSlshYANy+BlgGIBBN3y3EHCTYusqdNRUXFJfKw/ETyhsi1qxsaGq6VAORee1oDkPtlt1MCkAlNOfHJ1+vPsykgurVr15qbb77ZqxT27NlTgpIftqoUJjoftunTp3s/LxG97sYbb7SpcOi/VVs+WgZcbengdB0fst9++9kcJKKV6UsvvdQ89thj7YLZM88809x5551OVqb1//v73/++9//94Ycf2tym34Ezzjgj5f/vopmJP5fHvjvWPHTfQzErUBdffLG55557bA6AltL17KaLPNNU1gLg5iXQJgDR1c56tm0BkT82VZJ3uBy/IQHErW1bQOTrP5QAxdcIXFpA3MRbwfj0Lfmpp36t1VvftrTiunTp04ECoWhv4zWt3a4S0cHp1157g00hkXS0KmXyOYr8rjQtqNn0uzJgQPA1Pg65a7D58LMvKkdRabv3m02HLYXxDKQbn3VuK4TySdezGzZaQILh5iXQJgD5iRyfJsFE87S8kjdT8oZL3uly7WL5Y/2cBCPNs81L3nLJ+7PkzbJZcbEQoZtYnCsx7e8efxGpsd6MVKnQN2OxVsjde++9zdtvr7E5senMWKn+/Fym4w8iK9vrQE/ta51oHJB+TToWd8yn5+gv7z9jzvnDN2wqhn/JdkfTYYTrK/LzWec2yscdLEQYDIPQkyCVKJ0Z6ysDBw7sYrPUCZL3gh7Y/Ql6rPr167en5B1ZXFzsnQfyma61oSvVasW0JU0HXYsj3hS/foIPVWizp2jQluq6LMzJn9jxA070Bqy/9/3YrX6mv2yRBRBtVYVpRAGAACQpNTU1yyUIWdulS5d7Bw8efGh5efkVkn1MfX393XpeAo175Pzxmq/nu3btqmNB3tbWEz0P5DPtmzt79lzvrXhl5eTQ1uLQt/HxpvhV2sISTyHOnhJkXRbm5Pevc4fOXiBS+cFkY+K9kL5aNglEGns2JQGgkBGAJEdijfqzpLLTr6Sk5CVJXyDbOWvWrHlPT0qg8Y7szpWK0ng5/6Ic95Rrz5Y93apQMLRLTnX1LC/omDnzOtO/f7C+u37exicKTtI1/bCrEgVtmh9vXRbm5I9P71vbaXa9aUTn9m5q7Xi86bpoFvVe4E3je/0L1TYHAAoP/dccwxgQN9HvNnu0kqfdhxIZNGiQ+fTTT1vNnqItHxp8aPcvF2dsShetFGt3q0RijUfQCjVjQNqLNxZJ1+hpaGgwv/nNwi8Cv31ku6zpMJ5EiyBmEp91bqN83MEYkGBoAQHgNL9v47/+9TO9qXZ1tquwun/lqqBdqDSoSLToZaG1KqlE3dr0nV6rcVCfyHaNBChz4i+wpi0iutXt3GZzACC/Eb05hhYQN/HWKXv8vo1ftuxpc9hhFZSRCNoCopre9k/zumq1XVQv1ValXH6OkmkVUpGZx0pLe3jjjyJdEcf96Tyz5N04fbTEA2cuMqcfeIZNZRafdW6jfNxBC0gw3DzHEIC4iQ/97PIzxe/cufMpIyvMLlT6vWJVphNp+bXakjVp0tScDRLDCOpaWr72SXPeo2fZVHTH7Dvc/O+5i20qM/iscxvl4w4CkGC4eY4hAHETH/rZ5edtfOfOHSmjFvwEbelaFyXWWAktr29840zzs5/9UlK51QPY71ikZNeb2b57uzngjr42FduHVZ/E7BIXJj7r3Eb5uIMAJBhunmMIQNzEh74b4r2NT1RGbd/G+1mQL5d9/vnnZsSI4eadd95uFYRoJfbAAw8yy5e/IEFbZ5sbrkTBj66i/stf5tYaImG3gESj40ASeWHsy2ZQ9yE2FT4+69xG+biDACQYbp5jCEDcxIe++2KVUaKZi/J1hqzELSD6pj78IMBP968+ffqYxx9PbgatbPPz7/LbrS2R2S/fZK59Qefzje3Hw64wlx/zE5sKD591bqN83EEAEgyzYAHIa0EW5MtVWlkOsg5IENrKFK+SrjZsyL1V1DWoyNTMYNO+Mt2bmvdv416xOe394u83NM+eBQC5hgAEQEZppVe7s+gbet2noxIckc2KeDb5CQJ0LE06ggDt4uZHLq6irq1lrabZtTStY2r0fJgO3OcgLxDR8R/xNE/ju6vO5gCA2whAAGSEdoXSoEO7sWhfeh3Qq3tNa76eD1s2K+LZFGYQkGzAmM+rqGtXPe22pt2sKisnZ2y9GW1d0UBEtxMHnmRz2xt0Z38vEFmaYJpfAMg2+q85hjEgbqLfrX9aQY022DvdYxKilZH+zHTMXOS6MAZMpzp2Rss/H8eAuOaJ95aYMf/7bZuK7oQBXzO/P+t/bcofPuvcRvm4gzEgwdACAiAU8Vo4Jkz4d7NkyeMZ7wqVz2/j49GgTwOFeLTbkM4iFkuqY2cyOVaikJ2y/yivReTtS9fbnPaeff/p5u5ZsZ49AMgGAhAAoYhXYf3jHx8xH3+80eZEl46uUGFUxHNR0CBAA8EgY2dijZXQlo+LLrrI3HJL4tYZ+LPXHns1d8+Kp+/t+3iByNufrLE5AJA9BCAAAktUYfUr7IHJhfw2PsiA6aBjZ2KNlVi27Blz7733Ru26heAigch/HvNfNqe9ry44wgtEfvnSL2wOAGQe/dccwxgQN9HvNj6/Yw4SCbKIW6wyahrLEH8V9XyuEGtwGBmT03bxxljSNXaG5yiz1nyy2gxfcKRNxday9YQychvl4w7GgATDzXMMAYib+NCPz2+FNR4NCIIs4paojFKpiBeqMAaxR8NzlB3aMqldsBJ559IPTLcuXSkjh/EMuYMAJBi6YAEIzO9g71gy0RVKv3d19Szvjf3MmdcRfMRRqGNn8pU+X5HuWV/td6zNbe/AO/c1PWZ3NUtWL7E5AJAeBCAAAvNbYf3mN8/x9i1pOh2LuCF1hTx2Jt89es7jXiDyP2cusjntnfY/p3mByC0v3WhzACBcNB85hi5YbqLZO7HE63yM9Vof0tUVijIKVzrGzlBG7qnbuc0Muiv+89erS2/zxsWrYgakyByeIXfQBSsYbp5jCEDcxId+Ytke7E0ZpUeYASNl5DadHSuRFePXSEDSy6aQaTxD7iAACYab5xgCEDfxoe9ftgZ7U0buo4zcp2X0+PuPmvN/d77Nie7+Mxaarx90pk0hU3iG3EEAEgw3zzEEIG7iQ999lJH7KCP3tSyjdZ+8bw7/VYU9E91Zg881d55+n00h3XiG3EEAEgw3zzEEIG7iQ999lJH78qWMWrby6QxwOglDvgzIj1ZGOq5r/zv6mB31O7x0LOsmbjQdSzraFNKBzzl3EIAEw81zDAGIm/jQdx9l5L5cL6OmcU5TvVX/W64UrzPA6axh+bCoZaIyuu6FmeaWl+PPjvX0mL+ag3scYlMIE59z7iAACYab5xgCEDfxof8FV9/+Ukbuy/UySjzTm64MP9fm5Ca/ZfTyh383X//dKTYV3Yxjf2qmHPkDm0IY+JxzBwFIMNw8xxCAuIkPffff/lJG7svlMtLAe9SoEa1+99vSGd+CrObvgmTL6LNdn3kLGMbTf68B5h//voJpfEPA55w7CECCYSFCAL5o8KFvf9tWwDSt+ToFL5AMrdTPmHGl17Kge027Slv94gUfSqefnj8/t1tAkrXnHns2r7J+fP8TbW5r//r0fdP39n28aX43ff6xzQVQyAhAACSkFUNt+YjW9URpvq7/4XIFEu7Q1jQNOrRFYd68OWbhwgXeXtOar+ddo10O/diyZbM9KjwPn/0nLxCZO/JOm9Pewfcc5AUiS9993OYAKEQEIAAS4u0vwvSDH0zOudY0He/kR/fupfaocH2nfLQXiPzz39+0Oe2N/dN5XiBStWSCzQFQSAhAACTE21+EZe3atWbp0iU515qmky3oeKd4dAyILryJJv27DvACkQ+qYn9+/K72114gotuu+l02F0C+IwABkBBvfxGWm2++2Wsti8fF1jQdWK6TLcQaSK35p546Km/WAwlTcVFx8ziRSUfEbt0aML+nF4jUbq6xOQDyFQEIkCa5NMA2Ed7+plc+/a4ksnmzv1YyF1vTdKY3nWpXf9db0vTo0WO984jvmuOu9QKRP527xOa0d/xDw7xAZP4rc2wOgHzDFGKOYRpeNyUz9WG+LlamleP4ayCMNbNn325zMi8Xp6cshIXtWtIy+ulP/9trBUmksnKKqa6+3qbcogFiZC2c0tIeXuDdv/8Aeza3Zfo5+nTXp+agO/vZVHQHdjvI/O2CV2yqsDENrzuYhjcYbp5jCEDclMyHfuKKem4uVtZUWZ7m9c9v2YVG3/5q15MwKsstK3bJLnKYi3+Y8/V3JRYto7q6Teaoo4bF7Yalv1O5vp5Grsrmc/SN348yL37wV5uKruaSd033zoXb1ZMAxB0EIMFw8xxDAOImvx/6WoHO98XK0vH2N4yWgFz7w1wIvyttRcpo7NgLzMKF7ramFTIXnqOFby0w056osqnoFv7b780p+4+0qcJBAOIOApBguHmOIQBxk98Pfe2/r+sZJOJy95JsCKMlINf+MBfi70qkjD766BMp8ylpbU1Dalx6jtZue88c9cCXbCq60RVjza2nzrOp/EcA4g4CkGAYhA6EiOlqk6ctAYW4yGEh/65ocKEBpbbuVFZONmPGjDNVVVPNkiXLvZYPgg+o/fbeP+E0votWPtg8je/uBvcWsAQQHQEIEKJCmK5WA4EwZ2wq1EUOmdq4aWrb6upZXtAxc+Z1eTOQG+FqOY3vxMNjz7TXf14PLxBZvaXW5gBwFQEIEKJ8nq5Wx2lo0KHjFrTr0MKFC7y9pjVfz6eiUFsCmNoYSN5PT7jBC0T+eM7jNqe9Yx88ygtE7n5tvs0B4BoCECBE+kY3Xxcr00HiOk6jbWuFpjVfZ8hKRaG2BOjvwCmnxB9Ee/LJp+bNAHQgTMP7HesFImsmvG9z2rvymf/wApETHjra5gBwBQEIEDIdQJtvi5Wlc5wGLQHxMMYRiKdrx72bu2cd2ecrNre1ms0rm8eJfLLDX4srgPQiAAFClo8DbNM5TiOfW43i0WDtiSeW2lR0Tz65NPAYG5fpvy3M8UQobI9/5ykvELn5pNtsTntld+/vBSJPr3vK5gDIBl6vOYZpeN1U6FMfagVRx3wkosFWKus3hLHIIdPwuq/1NLyTC2YF+FyST5917259xxz9P4fbVHQXDr3Y3HjSbJtyH9PwuoNpeIOhBQRAQukep5GPrUaJJDP4Pt9aCn7wg8lpGU8EtHRAtwO9FpH1lbEnsHhgxX3N3bPqG+ptLoB0I3pzDC0gbir0t05a4XV91e58bQEpLz/YbNr0cV60FGgZ1dVtMkcdNaxVS1db2f5dKmT5/ln3n09PN/e+fpdNRffCuH+YQfsMtim30ALiDlpAgqEFBEBChTpOI538DL7v1Kmzqal5K69aCm6++ea4wYfKx3Vf4Ib/97WbvFaRR856zOa0N3zBkV6LyH2v321zAISNAASAL/k4u1c2+QnqjIndIJqrK8Rv3uxvPZd8XAEe7jhuwAleILJ6Quzn5/KnL/MCkZMWHWdzEIZ861KK1BCAAPClEMdppFu8oK68vMLs2LHD5kSXiy0FpaX+xgnl8wrwcMfeHbt5gYhuQ3t+yea2tuLj15vHiWzbudXmIlnpWswWuYn+a45hDIib6HfrvlwuI30DqFMd68D00tIe3ponN9xwbVpnHssGxoC4j88643W90taPeB4+60/m+AEn2lTm5HL5aJChXUejrSelLb76MkZfcuUKxoAEQwsIAGSZVrSrq2d5gcTMmdeZ/v0H5O0K8fvtt58ZOXIU44ngrIu/9D2vReSv4/5pc9o75w/f8FpELl8eP1BBE33Jkq7FbJGbCEAAwEH5vEL8LbfMYTwRnHfQPoO8QCTeNL73vXF3c/cspvGNLZ2L2SI3EYAAyKhsDUDM1s9NlZ9B6rnaUsB4IuSSkuKS5nEiFw4db3Pb6zev1AtEdAFEtJbMukcoDPRfcwxjQNyUjX63WkGOjAvQ7jj6RjyXu6U0rXY+NW2rX8cqo3T/3HQKY4V4lzC+wH2UkT9Pr3vKfOeP37Kp6G466VZzwdCLbCocuVo++tLHz7pHlZVTTHX19TblNsaABMPNcwwBiJsy+aGfyxXmeNI9ADFWGeXDwMeWwWhkkLqOE8k1VG7dRxkl55MdW0zZ3fvbVHRH9D7SLD5vuU0Fk6vlo59hri9mmywCkGC4eY4hAHFTJj/0822mEJWJPz7Ryigf/+jlkrateJMmTTWHHVZB5dZhBCCpO+Gho03N5pU2Fd2aCe+brh33tqnk5XL5JP7bNtbrgpkrCECCYQxIksrKys4pLy9vbLP9Vs/J/iA5v1T2n8q2YsiQIad5XwT4pBW2fJwpJFsDEBn4mB3aiqeVjbbz/Z966tfM+PHjvfNAvnn2/Be9cSKzTvyFzWlv0F0DvHEiL6x/3uYUDm29Z/IJRBCAJG+obI926NChX2TbsWPHBMkrksrhI7L/QPbDZHuguLj44UGDBsVvmwVayNcKc7YGIGby52pQmK5B7vG+dzp/bqq0C6G+6Wz7u6y/u7/61a/MD384xeYA+ed7h33fC0SeH/uSzWnvWw+f7gUiVz37nzYn/2nXYSafQATNR0kqKyv7n6Kiovdqamp+YrM85eXlp0jQ8ccuXbr0ffXVVz/VPG0Nkd2ztbW112jaD7pguSlTzd5aicy3xeeUVozTPQAxWhll4uemc8xOvO99yikjveMnnlga+s8NQgOgRN3e+vTpYx5/nG5vLqILVvh2N+w2/ef1sKnYPqjaYoqL4r8XpnzcQResYGgBSZIEH0Ml0KixyWaSN1zOvRwJPqxnJe9YewwklK+Lz2VrTYtM/NxYb/s1rfk6i1Wq4n3vX//6IW9Lx88Nwk8r3oYNdHtD4ehQ3KF5Gt8xB4+zue3te3t3r1Vk7bb3bA6Qv4jeklNUXl5eJ/s/SsBxlAQXJbL/zR577DFj9+7dN8px79ra2jFNl3qtIlWym1JTU3NoU05iGzduaywuplhcU1JSbLp162K2bt1u6uvT99Zp3bp1Xj/5llOutqVvj5cufdoMHJhbb48nT55oFi6MPQBxzJixZs6c+TYnebHKKJ0/N53l5ed7x5Ot3xO93w89lLgVb+zYC8xtt82zqeTp/Zk37zazefNmU1pa6rVi5doz4aJMfdYVuifeXWa+84ezbCq620bOM2OHXmBTTSgfd/To0ZXKGjLjkEMOOUCCCh10fl9ZWdkRdkD6WtlukeO7Zf8re6mn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width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Regression evaluation metrics\n",
    "%matplotlib notebook\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import datasets\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from sklearn.dummy import DummyRegressor\n",
    "\n",
    "diabetes = datasets.load_diabetes()\n",
    "\n",
    "X = diabetes.data[:, None, 6]\n",
    "y = diabetes.target\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "\n",
    "lm = LinearRegression().fit(X_train, y_train)\n",
    "lm_dummy_mean = DummyRegressor(strategy = 'mean').fit(X_train, y_train)\n",
    "\n",
    "y_predict = lm.predict(X_test)\n",
    "y_predict_dummy_mean = lm_dummy_mean.predict(X_test)\n",
    "\n",
    "print('Linear model, coefficients: ', lm.coef_)\n",
    "print(\"Mean squared error (dummy): {:.2f}\".format(mean_squared_error(y_test, \n",
    "                                                                     y_predict_dummy_mean)))\n",
    "print(\"Mean squared error (linear model): {:.2f}\".format(mean_squared_error(y_test, y_predict)))\n",
    "print(\"r2_score (dummy): {:.2f}\".format(r2_score(y_test, y_predict_dummy_mean)))\n",
    "print(\"r2_score (linear model): {:.2f}\".format(r2_score(y_test, y_predict)))\n",
    "\n",
    "# Plot outputs\n",
    "plt.scatter(X_test, y_test,  color='black')\n",
    "plt.plot(X_test, y_predict, color='green', linewidth=2)\n",
    "plt.plot(X_test, y_predict_dummy_mean, color='red', linestyle = 'dashed', \n",
    "         linewidth=2, label = 'dummy')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cross-validation (accuracy) [ 0.91944444  0.98611111  0.97214485  0.97493036  0.96935933]\n",
      "Cross-validation (AUC) [ 0.9641871   0.9976571   0.99372205  0.99699002  0.98675611]\n",
      "Cross-validation (recall) [ 0.81081081  0.89189189  0.83333333  0.83333333  0.83333333]\n"
     ]
    }
   ],
   "source": [
    "# Model selection using evaluation metrics\n",
    "# Cross-validation example\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "dataset = load_digits()\n",
    "# again, making this a binary problem with 'digit 1' as positive class \n",
    "# and 'not 1' as negative class\n",
    "X, y = dataset.data, dataset.target == 1\n",
    "clf = SVC(kernel='linear', C=1)\n",
    "\n",
    "# accuracy is the default scoring metric\n",
    "print('Cross-validation (accuracy)', cross_val_score(clf, X, y, cv=5))\n",
    "# use AUC as scoring metric\n",
    "print('Cross-validation (AUC)', cross_val_score(clf, X, y, cv=5, scoring = 'roc_auc'))\n",
    "# use recall as scoring metric\n",
    "print('Cross-validation (recall)', cross_val_score(clf, X, y, cv=5, scoring = 'recall'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grid best parameter (max. accuracy):  {'gamma': 0.001}\n",
      "Grid best score (accuracy):  0.996288047513\n",
      "Test set AUC:  0.999828581224\n",
      "Grid best parameter (max. AUC):  {'gamma': 0.001}\n",
      "Grid best score (AUC):  0.99987412783\n"
     ]
    }
   ],
   "source": [
    "# Grid search example\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import roc_auc_score\n",
    "\n",
    "dataset = load_digits()\n",
    "X, y = dataset.data, dataset.target == 1\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "\n",
    "clf = SVC(kernel='rbf')\n",
    "grid_values = {'gamma': [0.001, 0.01, 0.05, 0.1, 1, 10, 100]}\n",
    "\n",
    "# default metric to optimize over grid parameters: accuracy\n",
    "grid_clf_acc = GridSearchCV(clf, param_grid = grid_values)\n",
    "grid_clf_acc.fit(X_train, y_train)\n",
    "y_decision_fn_scores_acc = grid_clf_acc.decision_function(X_test) \n",
    "\n",
    "print('Grid best parameter (max. accuracy): ', grid_clf_acc.best_params_)\n",
    "print('Grid best score (accuracy): ', grid_clf_acc.best_score_)\n",
    "\n",
    "# alternative metric to optimize over grid parameters: AUC\n",
    "grid_clf_auc = GridSearchCV(clf, param_grid = grid_values, scoring = 'roc_auc')\n",
    "grid_clf_auc.fit(X_train, y_train)\n",
    "y_decision_fn_scores_auc = grid_clf_auc.decision_function(X_test) \n",
    "\n",
    "print('Test set AUC: ', roc_auc_score(y_test, y_decision_fn_scores_auc))\n",
    "print('Grid best parameter (max. AUC): ', grid_clf_auc.best_params_)\n",
    "print('Grid best score (AUC): ', grid_clf_auc.best_score_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['accuracy', 'adjusted_rand_score', 'average_precision', 'f1', 'f1_macro', 'f1_micro', 'f1_samples', 'f1_weighted', 'log_loss', 'mean_absolute_error', 'mean_squared_error', 'median_absolute_error', 'neg_log_loss', 'neg_mean_absolute_error', 'neg_mean_squared_error', 'neg_median_absolute_error', 'precision', 'precision_macro', 'precision_micro', 'precision_samples', 'precision_weighted', 'r2', 'recall', 'recall_macro', 'recall_micro', 'recall_samples', 'recall_weighted', 'roc_auc']\n"
     ]
    }
   ],
   "source": [
    "# Evaluation metrics supported for model selection\n",
    "from sklearn.metrics.scorer import SCORERS\n",
    "\n",
    "print(sorted(list(SCORERS.keys())))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"900\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Grid best parameter (max. precision): {'class_weight': {1: 2}}\n",
      "Grid best score (precision): 0.5426840654086686\n",
      "Grid best parameter (max. recall): {'class_weight': {1: 50}}\n",
      "Grid best score (recall): 0.935661321592438\n",
      "Grid best parameter (max. f1): {'class_weight': {1: 4}}\n",
      "Grid best score (f1): 0.5092829334700878\n",
      "Grid best parameter (max. roc_auc): {'class_weight': {1: 20}}\n",
      "Grid best score (roc_auc): 0.8914696383598073\n"
     ]
    }
   ],
   "source": [
    "# Two-feature classification example using the digits dataset\n",
    "# Optimizing a classifier using different evaluation metrics\n",
    "from sklearn.datasets import load_digits\n",
    "from sklearn.model_selection import train_test_split\n",
    "from adspy_shared_utilities import plot_class_regions_for_classifier_subplot\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "\n",
    "dataset = load_digits()\n",
    "X, y = dataset.data, dataset.target == 1\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "\n",
    "# Create a two-feature input vector matching the example plot above\n",
    "# We jitter the points (add a small amount of random noise) in case there are areas\n",
    "# in feature space where many instances have the same features.\n",
    "jitter_delta = 0.25\n",
    "X_twovar_train = X_train[:,[20,59]]+ np.random.rand(X_train.shape[0], 2) - jitter_delta\n",
    "X_twovar_test  = X_test[:,[20,59]] + np.random.rand(X_test.shape[0], 2) - jitter_delta\n",
    "\n",
    "clf = SVC(kernel = 'linear').fit(X_twovar_train, y_train)\n",
    "grid_values = {'class_weight':['balanced', {1:2},{1:3},{1:4},{1:5},{1:10},{1:20},{1:50}]}\n",
    "plt.figure(figsize=(9,6))\n",
    "for i, eval_metric in enumerate(('precision','recall', 'f1','roc_auc')):\n",
    "    grid_clf_custom = GridSearchCV(clf, param_grid=grid_values, scoring=eval_metric)\n",
    "    grid_clf_custom.fit(X_twovar_train, y_train)\n",
    "    print('Grid best parameter (max. {0}): {1}'\n",
    "          .format(eval_metric, grid_clf_custom.best_params_))\n",
    "    print('Grid best score ({0}): {1}'\n",
    "          .format(eval_metric, grid_clf_custom.best_score_))\n",
    "    plt.subplots_adjust(wspace=0.3, hspace=0.3)\n",
    "    plot_class_regions_for_classifier_subplot(grid_clf_custom, X_twovar_test, y_test, None,\n",
    "                                             None, None,  plt.subplot(2, 2, i+1))\n",
    "    \n",
    "    plt.title(eval_metric+'-oriented SVC')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        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 backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the 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",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\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"
    },
    {
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width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "At zero threshold, precision: 0.22, recall: 0.74\n"
     ]
    }
   ],
   "source": [
    "# Precision-recall curve for the default SVC classifier (with balanced class weights)\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import precision_recall_curve\n",
    "from adspy_shared_utilities import plot_class_regions_for_classifier\n",
    "from sklearn.svm import SVC\n",
    "\n",
    "dataset = load_digits()\n",
    "X, y = dataset.data, dataset.target == 1\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)\n",
    "\n",
    "# create a two-feature input vector matching the example plot above\n",
    "jitter_delta = 0.25\n",
    "X_twovar_train = X_train[:,[20,59]]+ np.random.rand(X_train.shape[0], 2) - jitter_delta\n",
    "X_twovar_test  = X_test[:,[20,59]] + np.random.rand(X_test.shape[0], 2) - jitter_delta\n",
    "\n",
    "clf = SVC(kernel='linear', class_weight='balanced').fit(X_twovar_train, y_train)\n",
    "\n",
    "y_scores = clf.decision_function(X_twovar_test)\n",
    "\n",
    "precision, recall, thresholds = precision_recall_curve(y_test, y_scores)\n",
    "closest_zero = np.argmin(np.abs(thresholds))\n",
    "closest_zero_p = precision[closest_zero]\n",
    "closest_zero_r = recall[closest_zero]\n",
    "\n",
    "plot_class_regions_for_classifier(clf, X_twovar_test, y_test)\n",
    "plt.title(\"SVC, class_weight = 'balanced', optimized for accuracy\")\n",
    "plt.show()\n",
    "\n",
    "plt.figure()\n",
    "plt.xlim([0.0, 1.01])\n",
    "plt.ylim([0.0, 1.01])\n",
    "plt.title (\"Precision-recall curve: SVC, class_weight = 'balanced'\")\n",
    "plt.plot(precision, recall, label = 'Precision-Recall Curve')\n",
    "plt.plot(closest_zero_p, closest_zero_r, 'o', markersize=12, fillstyle='none', c='r', mew=3)\n",
    "plt.xlabel('Precision', fontsize=16)\n",
    "plt.ylabel('Recall', fontsize=16)\n",
    "plt.axes().set_aspect('equal')\n",
    "plt.show()\n",
    "print('At zero threshold, precision: {:.2f}, recall: {:.2f}'\n",
    "      .format(closest_zero_p, closest_zero_r))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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  "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": "3.6.1"
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 },
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