Module 3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "\n",
    "_You are currently looking at **version 1.0** of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the [Jupyter Notebook FAQ](https://www.coursera.org/learn/python-machine-learning/resources/bANLa) course resource._\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Applied Machine Learning: Module 3 (Evaluation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluation for Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preamble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 178\n",
      "1 182\n",
      "2 177\n",
      "3 183\n",
      "4 181\n",
      "5 182\n",
      "6 181\n",
      "7 179\n",
      "8 174\n",
      "9 180\n"
     ]
    }
   ],
   "source": [
    "%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": {
    "collapsed": false
   },
   "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": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1615,  182])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.bincount(y_binary_imbalanced)    # Negative class (0) is the most frequent class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.90888888888888886"
      ]
     },
     "execution_count": 4,
     "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",
    "\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)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dummy Classifiers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "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."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "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,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9044444444444445"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dummy_majority.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.97777777777777775"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svm = SVC(kernel='linear', C=1).fit(X_train, y_train)\n",
    "svm.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Confusion matrices"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Binary (two-class) confusion matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most frequent class (dummy classifier)\n",
      " [[407   0]\n",
      " [ 43   0]]\n"
     ]
    }
   ],
   "source": [
    "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": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random class-proportional prediction (dummy classifier)\n",
      " [[364  43]\n",
      " [ 40   3]]\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": {
    "collapsed": false,
    "scrolled": true
   },
   "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": {
    "collapsed": false
   },
   "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": {
    "collapsed": false
   },
   "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": "markdown",
   "metadata": {},
   "source": [
    "### Evaluation metrics for binary classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy: 0.95\n",
      "Precision: 0.79\n",
      "Recall: 0.60\n",
      "F1: 0.68\n"
     ]
    }
   ],
   "source": [
    "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": {
    "collapsed": false
   },
   "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": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random class-proportional (dummy)\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "      not 1       0.90      0.89      0.90       407\n",
      "          1       0.07      0.07      0.07        43\n",
      "\n",
      "avg / total       0.82      0.82      0.82       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": "markdown",
   "metadata": {},
   "source": [
    "### Decision functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, -23.172292973469546),\n",
       " (0, -13.542576515500063),\n",
       " (0, -21.717588760007867),\n",
       " (0, -18.903065133316439),\n",
       " (0, -19.733169947138638),\n",
       " (0, -9.7463217496747667),\n",
       " (1, 5.2327155658831135),\n",
       " (0, -19.308012306288916),\n",
       " (0, -25.099330209728528),\n",
       " (0, -21.824312362996),\n",
       " (0, -24.14378275072049),\n",
       " (0, -19.578811099762508),\n",
       " (0, -22.568371393280199),\n",
       " (0, -10.822590225240777),\n",
       " (0, -11.907918741521932),\n",
       " (0, -10.977026853802803),\n",
       " (1, 11.206811164226373),\n",
       " (0, -27.64415761980748),\n",
       " (0, -12.857692102545409),\n",
       " (0, -25.848149140240199)]"
      ]
     },
     "execution_count": 16,
     "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_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": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 8.6377579220606777e-11),\n",
       " (0, 1.3138118599563783e-06),\n",
       " (0, 3.6997386039099529e-10),\n",
       " (0, 6.1730972504865465e-09),\n",
       " (0, 2.6914925394345074e-09),\n",
       " (0, 5.8506057771143608e-05),\n",
       " (1, 0.99468934644404694),\n",
       " (0, 4.1175302368500096e-09),\n",
       " (0, 1.2574750894253029e-11),\n",
       " (0, 3.3252290754668869e-10),\n",
       " (0, 3.2695529799373086e-11),\n",
       " (0, 3.1407283576084884e-09),\n",
       " (0, 1.5800864117150149e-10),\n",
       " (0, 1.9943442430612578e-05),\n",
       " (0, 6.7368003023860014e-06),\n",
       " (0, 1.7089540581641637e-05),\n",
       " (1, 0.9999864188091131),\n",
       " (0, 9.8694940340195476e-13),\n",
       " (0, 2.6059983600823893e-06),\n",
       " (0, 5.9469113009063784e-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": "markdown",
   "metadata": {},
   "source": [
    "### Precision-recall curves"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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": "markdown",
   "metadata": {},
   "source": [
    "### ROC curves, Area-Under-Curve (AUC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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": {
    "collapsed": false,
    "scrolled": false
   },
   "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "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": "markdown",
   "metadata": {},
   "source": [
    "### Evaluation measures for multi-class classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multi-class confusion matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"550\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "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": "markdown",
   "metadata": {},
   "source": [
    "#### Multi-class classification report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "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": [
    "print(classification_report(y_test_mc, svm_predicted_mc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Micro- vs. macro-averaged metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "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": [
    "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": {
    "collapsed": false
   },
   "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": "markdown",
   "metadata": {},
   "source": [
    "### Regression evaluation metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "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>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%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": "markdown",
   "metadata": {},
   "source": [
    "### Model selection using evaluation metrics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Cross-validation example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "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": [
    "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": "markdown",
   "metadata": {},
   "source": [
    "#### Grid search example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "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": [
    "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_)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Evaluation metrics supported for model selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "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": [
    "from sklearn.metrics.scorer import SCORERS\n",
    "\n",
    "print(sorted(list(SCORERS.keys())))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Two-feature classification example using the digits dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Optimizing a classifier using different evaluation metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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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): 0.5345370664969774\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): 0.5123880000895094\n",
      "Grid best parameter (max. roc_auc): {'class_weight': {1: 20}}\n",
      "Grid best score (roc_auc): 0.8890937829385455\n"
     ]
    }
   ],
   "source": [
    "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": "markdown",
   "metadata": {},
   "source": [
    "#### Precision-recall curve for the default SVC classifier (with balanced class weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "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": {
      "text/html": [
       "<img src=\"data:image/png;base64,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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"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAyAAAAImCAYAAACrXu7BAAAgAElEQVR4XuydB5hU1dnH33NnttAFpYgYKTt3KIIaRFASe2I0mliiMc2WGGsM1kT9LLFGE4kxscREk6gxJqZpbCkWjAULNhCYMwMigqgoCCwLy87c8z3vMLMOy5a7s++de2bmf5/nez7DnvOe9/zeMzPv/56mCA8IgAAIgAAIgAAIgEA7BBQRGZABARAQJsCfLDwgAAIgAAIgAAIgAAIgAAIgUBICECAlwYxGQAAEQAAEQAAEQAAEQAAEmAAECMYBCIAACIAACIAACIAACIBAyQhAgJQMNRoCARAAARAAARAAARAAARCAAMEYAAEQAAEQAAEQAAEQAAEQKBkBCJCSoUZDIAACIAACIAACIAACIAACFSpAcGwehjYIgAAIgAAIgAAIgAAI2EigQgWIjajhEwiAAAiAAAiAAAiAAAiAAAQIxgAIgAAIgAAIgAAIgAAIgEDJCECAlAw1GgIBEAABEAABEAABEAABEIAAwRgAARAAARAAARAAARAAARAoGQEIkJKhRkMgAAIgAALlTQAHnJR3/OA9CICALQQgQGyJBPwAARAAARAAARAAARAAgSogAAFSBUFGF0EABEAABLoigNmNrgjh7yAAAiAgRQACRIok7IAACIAACIAACIAACIAACHRJAAKkS0QoAAIgAAIgAAIgAAIgAAIgIEUAAkSKJOyAAAiAAAiAAAiAAAiAAAh0SQACpEtEKAACIAACIAACIAACIAACICBFAAJEiiTsgAAIgAAIgAAIgAAIgAAIdElAWIDgFJEuiaMACIAACIAACIAACIAACFQxAWEBUsUk0XUQAAEQAAEQAAEQAAEQAIEuCUCAdIkIBUAABEAABEAABEAABEAABKQIQIBIkYQdEAABEAABEAABEAABEACBLglAgHSJCAVAAARAAARAAARAAARAAASkCECASJGEHRAAARCwjgAOBrEuJHAIBEAABECAIEAwCEAABEAABEAABEAABEAABEpGAAKkZKjREAiAAAiAAAiAAAiAAAiAAAQIxgAIgAAIgAAIgAAIgAAIgEDJCECAlAx1dxvC2u3uEkN5EAABEAABEAABEAAB+wlAgNgfI3gIAiAAAiAAAiAAAiAAAhVDAAKkYkKJjoCAFAHMvkmRhB0QAAEQAAEQAIGtCUCAYFSAAAiAAAiAAAiAAAiAAAiUjAAESMlQoyEQAAEQAAEQAAEQAAEQAAEIEIwBEAABEAABEAABEAABEACBkhGAACkZajQEAiBQPgSwD6Z8YgVPQQAEQAAEyo0ABEi5RQz+ggAIgAAIgAAIgAAIgEAZE4AAKePgwXUQAAEQAAEQAIH2CGAW8xMqYIHPiH0EIEDsiwk8AoGACYT9YxR2+wHjhXkQAAEQAAEQAIFOCUCAYICAAAiUCQEIlzIJFNwEARAAARAAgXIWIEg4MH5BAARAAARKQQC/N6WgjDZAAARAgAlgBgTjAARAAARAAARAAARAAARAoGQEIEBKhhoNgQAIgAAIgAAIgAAIgAAIlEiAYGobQw0EQAAEQAAEQAAEQAAEQABLsDAGQAAEQAAEQAAEQAAEQAAESkigRDMgJewRmgIBEACBiieAWeWKDzE6CAIgAAIVTAACpOTBReJQcuQlatB13d8R0fFtmmshosVKqT9EIpHr5s+fvylod1zXvZyILtu0aVOvJUuWbOyqve6W78peOfzddV1jjLkumUz+cOzYsft6nvekUurgRCLxWDn43xMfGxoapjmOM0MptacxZhgR8ZhcYIz5TTKZvJ1tu677b6VUPJFIjCIir732YrHYy0qpWq31pPzfXdedQkTnEdHeRDSIiD4koteMMbcmk8mHeuJ327rVFrexY8eO9DzvLWPMaclk8ja/LHmsE9GPtNb8vVDyJxaLnaCU+q3WOptvFH72euJM3i4RjdNaL+yJrVLWdV13tlJqYyKR2Dc/hh3HGbVw4cIlpfQDbYFA2AQgQMKOANqvGAI5AXJINBptTcjS6fQ2RHSgUuo6Y8yDWuuvBd3h8ePH9yWivvPnz3/PT1vdLe/Hpu1lqlWA5BKe/yql/mSM+Xkmk1lRU1MzxPO8E4joTCI6V2s903XdrxLRfcaYzyWTyf+2jee4ceN2zmQyc40x308mkzfx32Ox2HeVUrcS0T1E9OtIJPJOOp3eSSl1MhF9Uyl1VSKRuERqbFSbACGiyPjx4wevXbt2zbJlyzb45ehHgMTj8f2MMSwSRvq167ccBMiWpCBA/I4clKt0AhAglR5h9K9kBHIC5Ataa36rvMXjuu6PiOhSz/N2TKVSy0rmFBpql0C1ChDXdf+klJqWSCQ40eQ3462P67q/McbUJ5PJbzY0NNQ5jrPcGPMY/++2EOPx+E+MMd+rqakZ/uabb66Kx+OTjDFzlFI3JhKJ89sZ/zcQ0VmO40xYuHChlhiWVShAisLmR4DEYrGLWShCgBSFuFuVIEC6hQuFK5gABEgFBxddKy2BzgRILBY7Uin1V8dxpi9cuPC5eDz+lDHmY6UUv0WeQUQXaq1/2dDQ0N9xnKuNMQcppT5FRMuVUrcnEonrCxJGx3Xds4noVCIaQURvG2Nuyb+JbrukKpcc/piIeHkMz47wMg5eEvMLJtTeEqzcW8tz+M9E1KyU4mUDFy1cuHAO18m/1YxEIhMzmQz79lkiajTG3JdMJs/taNlOrj1eqrarMeY2pdQ1RHSn1vq88ePH17a0tPyfUuooIhrNy3eMMX8wxlyWSqWa89F0Xfd4Y8x5SqkGInqXy+ywww5XPPXUU2kuE4/Hv2CMYTu78TorItLGmKuSyeTfCmx0dwlWt5h30c4xnuddqpQaqpT6lTHmfKXU4EQisS5fL7dM6nkiOlJr/ffx48cPS6fTec7bE9EipdQNiUTizoK2mGu7AjhfJh6PP2iM+XQ0Gh3d1XLAWCx2o+M4J2cyme1TqdTagk9TxHVdFtFP5Wf0YrHYHRy3xsbG4e+++25T20/e8OHDe9fV1fV766233u/Op9J13UOIiJcOTSSilUT0AI9DZtWeAInH498wxvD4G8/jlojmep53cSqVmpVvl2dqiOh7juOMNsbw8rOXPM/7YSqVeoXLNDQ07OM4zhVENImXmBljEkR0vdb6Pj++u67LMz63ep43KM8t92+8vO1MrfXNbGfkyJH1tbW1H/Pnn5dUjR071vU871oimkpE2xpj3jTG/CiVSv2Ty7e3BMt13cOJiOvwUrkUEV2glPo+EdXxEp/c5y27BIuIeHzx98ZgInrVGHNiMplc0M7SUdHlWh3MgPBY5u8VjgXPEr/AYy0vTvfdd9/o8uXL+TPC4ndHIvpIKfWMUuq8/FKl9pZgxePxGcYYtsnfDeuUUi8T0fmJROKNHMPsckvHcfbzPI/L8fji742H6+vrT3/jjTfW58YAC/BLiehbRLRd7juEl2z+seCzxN8zF+bGZpSInuGxx0wLynyZl3rm4vOWUupSY8w5WILl55OEMpVOAAKk0iOM/pWMQGcCJB6P/8AY8+NMJvOpRYsWvZMTIPzD+pJS6rKWlpb3Fi9evMZ1XV7usqtS6vRMJsNvlA9QSv2ckwytNSdFLBguUkpdzGvBPc97NhKJ7GOM4eTmLK31LW0Fheu6S4noOc/zroxGo+s9z/scEXES9C2t9Z/aESwnGWPuMMZcqZS6VynV1xjDCcPunueN5xmcgh9//tH9Ga/zV8o5jshcRkRf6yxZy3E60BgzLxKJnB+JRJbzW3R+A09E3+B+eJ73RCQSmcxCSSn1QCKROCknfL6ulLqLE5F0Ov1QJBLZmYju5qU/iUTigoaGhjGO43ACcBfvuWlpafEcx/kOJyGe501JpVKv5pOy7uwB6S7zzgQIEb3OMef4Oo7DgpD3X3wjmUzeW5Ak/0wpdVw0GmWxQel0+jUiqudx4TjOokwmwyKNxdsJWuu7uMzo0aMHOI5Tm0qlOFFv94nH46exWCWiFzmmmUzmvzzu2is8duzYiZ7nceLGb8Y5NtknJwoe5qWFWuvHc/+2iIje0FofIfWBc133M0TEwoHF891EtAPHlYie1Vof01aAxGKxvZVSs3ipF4taImLx8EMi+kpuP8u7ruseQET/NsZ8OxqNPul53gBjzEVE9LnGxsYd6+vra6LR6DKl1J1KqZvT6XTGcRxejnaV53l7pVKp2V31b9y4cTtlMhlez3+I1vrRHB9OXKcT0Wz2nf8tHo/vb4x5nNf/c7Lsed6bRLSCxZEx5iMi4iVtZymlDkwkEk+2FSANDQ0THMfhcfEvFmU50XIjEQ1USi1uI0DmExHvb/q1MWYE70njpFpr/VkeN9Fo9PdENDkajfJLisb58+c3tu2n67rs306d9P9grfX/uuKTm5FhAfuA53k8Fgc7jsPtr9da8+fZuK7LyT+/RPh6Op1+IRKJ8KzyLUopJ5FITM59F2T3luT3gLiuexwRsZ0z+LuhpqZmG/7OZSHZ1NQU42Vr+THDAkwp9UvP857i71gi4u9PfgnE5XmM8/8+nGeFMpnMPMdxOGb8YuiwZDL5cE6kPkFEf+bv1Ugk0jsnNFgoj9dafxiPx+P8HUdE/D11STqd7pN74cLC9s18fLrihb+DQMcEyntPMQQIxjYICBFoT4BMnjy5Zs2aNfs5jsM/+E9rrTlx5OSDZ0D2qqurGzp37tzVuR/UqTzTYIw5KZlM8g9r9uE30UqpkzzPG1xbW2vS6fQKY8zdyWSSZ06yTzwev8QYk9ZaX1soKCKRSP9IJMJvnY9lsZEv39DQsFttbe0K3ifSjmDhN76LtNb8djD7jBo1amhNTQ0vybk8mUxeVSBAvsczN1yG31rm3n7/UmvNsyftPvk3rjx7smDBAv6BZv+HG2Pe4URPa80iJt8vfqM5k9+Caq2Xx2KxuUop9o3f/Ob5nKqUcrnN3FvlkfX19e/k32bm/m2DMeaCZDL5E67UnSVYPDPTHeaFG//ba4eIbuAZn4I+zjHGLC1I3pXruu8opf6ZSCROy+/HUErtz4lovp7ruv8wxoxPJpM8S+X3Yduc3P2AiHrxTJUxhpOxfzuO87u2y6Nc132RN6lrrVkMZB/Xdf/MYlRrPSY/K+e67sbcrBq/YRd5XNflN/8c910LYs2fn0P69+9/6vr166cXHh4wadKkPk1NTSNHjBiRyM+Gua47lgWeUuqYRCJxfzwev4Bnx4YPHz4oX4brbdiwYWdjzGuO4+zCb+ONMdOSyeQLBe1Ora2tTbJQ9tM513X5M/Q3rTW/IWdmvB+LxcHZWuuhuTF/lTHmK1rrsbkXFNd6nhdLpVIs5vKsWTCv1Fp/vq0AcV33ap7xqKurG5L/DsmLRhZibQTIS1rrPQr6w8n8t7XWdTn/eHZnWmdLsFhYbdq0qaaj/jc3Ny/3szclJ0AWaK15lir75Gau7vE879P8ksB13e2UUtsmEgnmmH1isRh/znlmaQiL7LYzICNHjtymV69eI/LfKTm7PEvBInAPrfVLBQJki8+g67qL+SWK1vrI/Hcdv+RIJBIcs7yPPzfGzGUx7rou2+TvHP7sZbhArt7bRHSF1vqaeDzO8b0gnU4Pzov8MWPGDIlEIu/ybA4EiJ9PEspUMgEIkEqOLvpWUgK5xJrfwhUuQaknIj4J6+5oNHpO/s1iToAM4+Sj4AeW33bybMcITrbz/97Q0HCY4zgPcsLOb2SVUvONMV8vXA5Q2NE2gqI5Ho8/a4zhdm7zPO9fAwYMeG7OnDnsUz7JaT01KxqN1jqOw2/EL2Ix08YuJwNv8o90/sdfKTUlkUjwMoe8LRY7j2itT+wIfo7TV7XWnADnf9y/ZIzh5TWfSSQSz+b/PZ9Q8ZvHDRs2PN67d29mu5VvhW3FYrGjeKaA34wSUT/afN9Rn/yMB5ftjgCJxWLjusm89eSxDgTIFjNEruvykqGrotHoYB4fruvycran88v1XNdlAXZGjlfriVSxWOx7SqmbotFov/beWHc2+HNvvQ9WSvHsGS/V4fHBtllQ8lvp7JPbWP6rTCYTW7RoUWrixIkDm5ubWQDzkjaeacjHnQXerwpFcU8/fK7r8lj6h9b6lPZstbcEy3Vdnu3iscdLcPiNszLG8Nvp7MlRLLwjkQjP2vFn6I5IJPJEoehiMbJx40aeVejFgoqI/ptMJl/qbElhe765rsvLGz+ttZ6em6l42fO8oY7jvM9L4HJLn57lJUKJROL7ruvy8sCJWutYm88c7505Xmu9XTsChEXDLlprHuetTzwe5yT4rTYC5Bda67MK4pXfk1bPyxtd1+1SgPQ0ngVt85Kw32iteala9in4nGe/1/hgjEwm8wPP83gWgme+aomIlzmxYMqeetVWgPDLnrVr1/JLma8qpXimhr9fIrmZw+wJdwVj5uhEIvGXAp9YdDYlk8n9XNc9mL/DcjNevAxyq8d1XRaify3sAxeKx+O8RJXZf4VfEORESqvQ4jKu6y5USr0HASI1omCnXAlAgJRr5OC3dQRyifUXM5nMnnnnamtrW5RSPNOwxfG7OQFSr7Weli8bi8V4ycGVvBShTeecXEL0eWNMo+M4z+WWArR7rGnbGQ3+MW9pafk+vwXm5QhExALjN9Fo9CL2q7B8NBrdznEcnonghLc1Ec39cHIi9rHW+nMdHYGZe9P7mNb6BF62xGKhoC/X8JvB9maK4vH4N3lWh4j4dJ/WJDufQPJylEgk8lAmk3k3lyRnZ13aPq7r8hIgTubuJ6KbePZn06ZNJhKJJIsVIA0NDXt2l3lhstXVUq+C2Z9v8NI113W5b7yXg5NoTlh4+dO32xkX2YQsEom4CxYsSPbkA9HQ0PBpx3H49KoxmUxmx0WLFn3A9nhPUiQS4WVBP0skEv+XW8LFyfVOhSI598Y/pbX+Yk/8KKzrui7v4eDEuXW2qPDvbQVIbl/UzNyyvd9lMplVnLw6jsOzja1H1+aSXbbJiSbvh5ivlLowkUg8mOvzYH77TURHKKVYEDCLn2mteS3/Fhv3O+prLBY7lPd8NTU18Vt5FkVH5pLbWcaYP9bU1NyTTqc5if0yL9PKLb3cLzf+C83yjENtNBqt8zxveOExvK7r/oeIBhTObHBFPh7ZcZzGQgFSOPZzY2qLo7pLLUCUUj/hJZMF332jeWYzv9wvFovxywjeB8czdU+m0+mmaDR6ZG6ZU7sCJB6P8wzF94joSs/zHjDGrI1Go1ONMffkj9ju6OCCwo3hsVjsa7z0tHCGtp3vGd43wt9TbY9V5xdOL7DwdF2Xlyf2axsf13V52e16CBCpbwrYKVcCECDlGjn4bR2BzvaAtHW2PQHiuu4ZRMTJ51ROntrW6dOnz4qmpqZhjuPwZtPjtNacsLeXhHd4D8i4ceO2T6fT32ChY4z5STKZvLRQgNTV1dXwD3d7swyxWIxPL3o9mUwe7UeATJgwYdDGjRv5LojsU19fvyq312OrzdKxWOyLSikWVEfy8a5tO2WMWTlw4MCmdevWbVRKXZ5IJFiotdf3vzI/rTVv4M8KGe4zC5ceCBDeV9IVc142dnlTU1Pv/DIUFn7pdHpdVwIklxByssLi7hjXdXn267b8vQ25E6fOyGQyrcc7F3a8rq5uaVcbyvPleTka/3d798PE43HeMMvLuvZJJpNP5+vkxvW+vDzHdV1+I/yR1vrQQh9isRgv6Tmhrq5uh/xyoMK/89vpdevWndLY2Hhne5vUO4jlO8aYfyeTSRZfWz1tk0l++8ybyrXWrS8ACsRje3dn8HK03YmI94l8ORKJjGsr5OLx+ChjDAuIH/J+gMJN/519AeVizxuneQkQzzzw8p4fxeNx/tzFlFK/Y9aNjY2DmEcsFrtfKbVrJpNhUbTVs2jRosVjx479VBsBwp+Xkbl9E611XNflzc5vSwsQyT0gSqnbeHlh3uncQRmv81JRz/MedRznYyK6Lr+ELfcZ4eVsvO+pXQHiui7vm/l34VHneTHRHQGS2yfEe/H27mhPi+u6K40x//I8r727VZpz+/z4wIfR7cQnqZRaDgHS2ScIf6sGAhAg1RBl9LEkBHoqQMaOHTvZ8zy+3O3wRCLxQN7psWPHbsun8SxYsGBFLpHjTcZ/0VpzYpR9YrHYFY7jjODN2oWCora2dlsi+kzh/o9c+Qccx1GJROJL7ewB4c2mvCehNRnKJfG8L4FPILrejwDpCHp7nArWXZ+bSCR4GVr24SUxzc3NQxKJxFu5JIQ3076rtT6wIHnhjdWH8tv33L4BfjtfeDleNnHhTdfJZJLfqHZrCZYf5vF4/PvGmBv53ovFixfzpn+OCd//8h8/AiQej3OSzfdpHMVr1vNLnnJ2eEkZLxfZVWvNSVr24ZkTpVTzwoULOfHq8snFkJNTfvu81X0cuROEfuZ5XkObfQi8/4M3Fx+Zm13KnsxV2GBurwX79kee/WrrjOu6vJyPT/viI4Bbl+x15rTruo8wxsJlSbkZrrOj0eghnufxoQitF0jy/iDHcXj5y5fydl3X/VVuM/fpiUTi1ng8zvtG0oX7O3LLylYZY46KRqNzW1paxuZPniqww32bVbiMqSvguZcMvImeD1U4nE/iamho+HxuwzXv8eJ9NJ/PjUdehnd17pCK7OwTP7zsijek50792uIiwlgsxgcVnF5XVzesYA9I/jtkiz0gfmZA+GLKRCLR4SbzIPeAFJ6qZ4xZ4XkeX2CZvZMmh4JPXuMDEcbn9j0taPsd5Loun/LFd5m0LjWLx+P/MsYw4+yBAH5mQHInzvF+t8vaLDPkjem8H+fi3PfMDlrrT7f9HAwfPjzF+4tisdh1SqkZhfHJz3Yqpf4HAdLVJwh/r3QCECCVHmH0r2QEeipAcsnmY0qpCbljQl/jhNZxnJ8aY1QymeQTavInxFyilDrVcZz/ZjKZfXKn25zHR+u2WVLFb+/5h/t6z/PuNsas49OliOgOTsq11je0I0D46Ek+beiySCTyx5aWlm3ZB04GiWgCn/AiLUBySRgni7xMjJP5Z3h5DM92ENHOjY2NcX5TXHDSzcWRSOQPLS0tk/IJndb63NyyL54d4dOyXvQ8j5N3TqA5UUhEIpHjWMh1Zw9IzjfeuN0h8/ybdj5Nx/O86x3H4Xs2eJ39xNzm7E5vXOcNtLW1tbxRmZcD8S3Je+UHbu54Yj4RjfczzIhGo8lMJsPrynkpFJ88xcLA1ylYruvyngLeKH6j53l/rqmp4WRvAC/54gMGcsKW9zFt8fC6dSLqT0TO8OHDR+Q3cBcWisViJyqlfs2nLSmlZvJpXS0tLcMdx+E33TzrdiaLgBxPXip3be7NdFZctn1yl+Pxm+hb+KQ1x3F2Msbw6Vav8GEO7SzB4gTx68aYwz3PW8LHuiqleAaO94Tw8rLzcsc3n2CMOT0ajc7xPI9nhL5jjOEZpng0Gp1gjOGZhQsikQhvgt+UTqf34zf2uZPKeIbN15Mbi3xU9mDP87bhvRa5mRF+u8+nQPHyMo4H8WxhS0sLH8iQ4uVg/IbcGLOHMYZnRO/hAxbaOQUruzSQRZ/nebwfh0+T4s8pf26WdGcGJB6P38qHX/DJZsaY5clkkjdlB/LkNqHzLB8fZnC7UooPoOAZoQ+SySTPSLF41/w5cBznG5lMJqKUulopxTNipxhj+Hvv3txnu/AUrH/nBAofVLCWl28ppXhvEm9ev7q5ufmn9fX1uxaK1nwHC5dg8b/F4/E7+YAAnmnmk8Y8z+PP2E9zL4cezJ3Qxkv7bncc5zbHcTZwGWMM+3kkL+fLzerwIQL3e553hVKqn+M4fCFtXCl+97P5mGQ8IFCtBCBAqjXy6Lc4AQkBkjuRh3/E+MePj57kpVi8mZE3XvNbQX546Qi/yedz7Ifn7gG5uaN7QPjYVKXU/xlj+IhL3jfAR4TenVvT7nV0Dwi/geTTpXLr0vm4yh/kT6UJQoDkTtG6mDfd5s7+5zea2SNG8zMgueSAjwnmNfp8VwjvCbm7X79+V/HG+twmYk5yD8ut1/8nJ77GGN7wykkaH4O6f3cFSFfM2a9cwsnL6Djp5ROVzvQ872FOrpLJZKcCJFefk1tOdLbaf5M7PYf3IPAeC7b/nlLqj+vWrbssv6TJ7/iLxWIsznjGhTcv8x6IJj4WlDkmEglO4rOn+hQ+udOjOHlqnUVq7wOUm8Xjiwj35mNhiYg3XfMG3xsKj7DNjx/HceKdXUzIBzBEIpHLjTEsynnm7x8d3QPCjKLRKF+myIkdHwRwT79+/X6wdu3a65VSLIL+2K9fv++uW7eOhdbXcp8dPm6WE8wr83eF5ETu2Tz2jTG8jC+VE5HMxveTn9E0xjzF+z8Kkl3eS8WzNzunUinmnn34CGk+OtoYw8fC8vHMPJN2R+5zmungHhCeBf0/IuKTtVjA8OlzvA/mo2Qy+YXcuGq986bAh7Z7QPj0L57VGpG7U6j1hD3fHfZZMCdAuH0Wfyx6WAA/w8dl5+/4cF13Sm4vD8ed70K6NhKJ3J1Op/no2ykcT8/zvMJjeMeMGdPA8ee/G2P4e/NWPkgjHo/fz3vmWPDyfiA/AoQv4oxEIrxcjo8F588b77HiFzatd8HkZji5H/xyg/fpvZGbaWoVqbklYPxChJeE8uzjJZ7nneQ4Tj0EiM8Bg2IVSwACpGJDi46BAAiAgL0EcvtJDisQ1vY6a6lnDQ0NgwcMGPBx/lS7nIjnmbQ/aa1ZDOMBARAAASsJQIBYGRY4BQIgAAKVSyB3tDEfxcqX8+EpgkBu3w0f2HAPz0zxCr3c8rrv5C7dzN7sjgcEQAAEbCQAAWJjVOATCIAACICAdQRc193qhvC2Tiql7kkkErz3I/Bn7NixB3mex/uT+AZuXpLEhzRcwXdeBN44GgABEACBHhCAAOkBPFQFARAAARCoHgK8z8BHb9fm71HxURZFQAAEQKAqCUCAVGXY0WkQAAEQAAEQAAEQAAEQCIcABEg43NEqCFmuYWwAACAASURBVIAACIAACFhEgNMBXxe9W+QzXAEBEChXAhAg5Ro5+A0CIAACIAACIAACIAACZUgAAqQMgwaXQQAEQAAEQAAEQAAEQKBcCUCAlGvkqtDv3IkvfEP3k1rrYztB4Liuy5c/8WVjA/kiNCI6vTu3+3qeZ1atWk+ehyUJPR1qjqNo0KA+BJ49Jbm5fvnytHOJT/nylBlP0lbAU5ZoezyHDOmP3E0WM6yFQACDOAToaLL7BHI3MfPtzXwb8rLOBEgsFvueUuocY8whjuMsM8Zcwzcza6139bvIma8OXr16PaXTfBEynp4QiEYdGjiwD4FnTyh+Uhc8ZTjmrYAneMoSkLXW3viEAJFlDGvhEIAACYc7Wu0mgVgsdlYmk/l9NBr9ORHVdyZAXNedZ4y5PZlM3sTNxOPxfsaYVZ7nfTaVSs320zQEyGZKxhhSqmdfE0jw/Iw4/2XA0z8rPyXB0w8l/2XA0z8rPyUhQPxQQplyJNCzzKIcewyfy5qA67q/60yAjBgxolfv3r3X52Y8nsl31nXd+caYW5PJ5C/8AGABsnbtBspkqncG5I//1fTcvPfo7GN2pdHD+/vB1m6ZSMSh/v17UbXzLBpgm4rgKUVysx3wBE9ZArLW2hufgwb1Re4mixnWQiCAQRwCdDRZPIGuBEg8Hh9ujFnued7OqVTqzQIBwmLkca31ZX5aZwHip1ylluG9L1+58CFqSXt04qHj6cj9YpXaVfQLBEAABMqKgOrptHRZ9RbOVioBCJBKjWyF9suvAIlEIhMXLFgwrycCpJrf2K9au5Fm3LR5Aun0I3amaROGFT2i8Ia5aHTtVgRP8JQlIGsN4zN4npgBkWUMa+EQgAAJhztaLZJAVwJk5MiR9bW1tes9z9s/lUrNKhAgC4jol1rrm/00Xe17QBJLV9N1976aRfV/x+3eoyVYWBPuZ8T5LwOe/ln5KQmefij5LwOe/ln5KYk9IH4ooUw5EoAAKceoVbHPXQkQRuO67utE9Hut9Uz+3yNHjtymtrZ2pVJqz0Qi8bIffNUuQJ55YwXd+QhrNqKfn/UZ6te71g+2dssgISkaHXjKogNP8CwBAdkmIEBkecKaPQQgQOyJBTzxQaA9AeK67g68v0MpdXAikXgrFoud6jjOhcaYg5RSy40xPyWi3bTWe/hoIluk2gXI359eTP98bgnV10bo5rP37tFJWBAgfkedv3Lg6Y+T31LlwdPOO1TaY1wePP2OjvDLQYCEHwN4EAwBCJBguMKqMAHXdTfmTNbk/n8L/3+tdf3YsWNHep73FhGN01ovJCLluu7lRHQqEfXjiws9zzsllUot8+tWtQuQ2//5Js1+833acUhf+tFJvnVblb1hDicpRILn91Psrxx4+uPktxR4+iXlrxwEiD9OKFV+BCBA2o1ZOIlF+Q2fyvW42gXI1Xe/TIuWr6VPu4PpzCMn9ijQSEh6hG+ryuAJnrIEZK1hfAbPExcRyjKGtXAIQICEwx2tWk6g2gXIjF88Q2vXb6KD9tiRvrp/z47gRUIiO9jBEzxlCchaw/gMnicEiCxjWAuHAARIONzRquUEqlmANG/K0GkzNx8g9plJ29OJB4/FHhCLxisSPNlggCd4yhJga3KrKLAESz46sGgHAQgQO+IALywjUM0CZPmH6+mS37zQGpGj9xtDB0/dqegIIcErGl27FcETPGUJyFrD+AyeJ2ZAZBnDWjgEIEDC4Y5WLSdQzQJkU0uGfvCr52lN46ZslPbeZXs64eBxRUcMCUnR6CBAZNGBJ3iWgIBsE5gBkeUJa/YQgACxJxbteCI3jWt1Ny10rpoFCIejuSVDp92weRnWUfuMpi/uObLoKEGAFI0OCbMsOvAEzxIQkG0CAkSWJ6zZQwACxJ5YwBOLCFS7APlwzQa64NbnsxE57fCdacrYIUVHBwKkaHRImGXRgSd4loCAbBMQILI8Yc0eAhAg9sQCnlhEoNoFyIIlq+gn972WjchlJ0yhnYbxdSrFPRAgxXHrqBZ4gqcsAVlrGJ/B88QeEFnGsBYOAQiQcLijVcsJVLsAmfXacvr9Y4lslH45Y2/qXR8tOmJISIpGhzf2sujAEzxLQEC2CcyAyPKENXsIQIDYEwt4YhGBahcg9z+ZokdfWEp9e9XQTd//bI8iAwHSI3xbVQZP8JQlIGsN4zN4npgBkWUMa+EQgAAJhztatZxAtQuQm/8+l+YkVtKo7fvTJcfv3qNoISHpET4IEFl84AmeAROQNY8ZEFmesGYPAQgQe2IBTywiUO0C5PI7X6SlHzTS1PFD6ZQvTehRZCBAeoQPCbMsPgt4Vvbphvi8yw5YCBBZnrBmDwEIEHtiAU8sIlDNAsQYQ2f87GnauCmTnQGZNGZbmjZhKA0d2LuoCCEhKQpbh5XAEzxlCchaw/gMnieWYMkyhrVwCECAhMMdrVpOoJoFSOEdIPkwxUYMoAu/ObmoqCEhKQobBIgsNvAEzxIRkG0GMyCyPGHNHgIQIPbEAp5YRKCaBQiH4Q//1vTSwvdp/cY0ZTxDo4f3p/87rri9IBAgsgMbPMFTloCsNYzP4HliBkSWMayFQwACJBzuaNVyAtUuQPLhufSOF2nZykbac8JQOvmw4vaCICGRHezgCZ6yBGStYXwGzxMCRJYxrIVDAAIkHO5otaQEur/pEwKEiPeCnDZzFm1q8ejLnxmV/b9iHiQkxVDruA54gqcsAVlrGJ/B84QAkWUMa+EQgAAJhztatZwABAjR6nXNdO7Nz2Yj9d3DxtO0CcOKihoSkqKwdVgJPMFTloCsNYzP4HlCgMgyhrVwCECAhMMdrVpOAAKEKLF0NV1376vZSPH+D94HUsyDhKQYapgBkaUGnuBZKgKy7WATuixPWLOHAASIPbGAJxYRgAAhevr1d+l3jy7MRoVvQ+db0Yt5IECKoYaEWZYaeIJnqQjItgMBIssT1uwhAAFiTyzgiUUEIECI/vLUInpk9tvUpz5Kv5ixd9HRgQApGl27FcETPGUJyFrD+AyeJ5ZgyTKGtXAIQICEwx2tWk4AAoTo5r/PpTmJldnLCC85vrgjeDnMSEhkBzt4gqcsAVlrGJ/B84QAkWUMa+EQgAAJhztatZwABAjRZXe+SO980JiN1K8v2JcijlNU1JCQFIWtw0rgCZ6yBGStYXwGzxMCRJYxrIVDIGQB0v3jUcPBhFarjQAECNF3f/IUpTNeNvQ8A8IzIcU8SEiKodZxHfAET1kCstYwPoPnCQEiyxjWwiEQsgAJp9NoFQS6IgABQnTvfzT9d86yLKprvjuNhg3q3RW2dv+OhKQobB1WAk/wlCUgaw3jM3ieECCyjGEtHAIQIOFwr4BWK3v2CgKE6NEX3qb7n1xEjlJ023n7UDSCJVg2fHCR4MlGATzBU5aArDWcgiXLE9bsIQABYk8s4IlFBCBAKHsELx/FO2SbXvTjU/csOjpI8IpGV+EzSna8xMD4xPiUJSBrDQJElies2UMAAsSeWMATiwhAgBBdf+8rtHDpx7Tz6EF0zjG7Fh0dJHhFo6twASLLpVhrGJ/Fkmu/Xvg87RC2UlQhQKRIwo5tBCBAbIsI/LGCAAQI0bk3P0ur1zXTAZNH0Dc+5xYdl/ATkqJdt7IieMqGBTzBU5aArDUIEFmesGYPAQgQe2IBTywiUO0CpLklQ6fdMCsbka8fGKMDd9+x6OggwSsaHWZAZNGBJ3iWgIBsExAgsjxhzR4CECD2xAKeWESg2gUI3//B94Dwc/Yxu9DE0dsWHR0IkKLRIWGWRQee4FkCArJNQIDI8oQ1ewhAgNgTC3hiEYFqFyAvL/yAbvnHvGxErj55Kg0d2Jscp7ivCwgQ2YFdPjzLYy1++fCUHUdBWQNPWbIQILI8Yc0eAsVlFPb4D09AIBAC1S5AHn5+Cf111uJWthFH0Zemj6TDpo/qNm8kJN1G1mkF8ARPWQKy1jA+g+eJe0B6yrg8Xo70tJe214cAsT1C8C8UAtUuQJ56dTnd9a/EFux3GNyHrvz21G7HAwlJt5FBgMgiA0/wLCEB2aYwAyLLE9bsIQABYk8s4IlFBKpdgGQ8j15LfkRr1jfTo7Pfpo/WNtOkMdvSjKN36XaUIEC6jQwJsywy8ATPEhKQbQoCRJYnrNlDAALEnliE6AmmI9vCr3YBUshjxk3/o7VNLfT5KTvSsQfEuj1OIUC6jQwJsywy8ATPEhKQbQoCRJYnrNlDAALEnljAE4sIQIBsDkbTxhY688b/Zf/7uIPitO9uO3Q7ShAg3UaGhFkWGXiCZwkJyDYFASLLE9bsIQABYk8s4IlFBCBANgdj8btr6aq7Xs7+9wVf243G7jSw21GCAOk2MiTMssjAEzxLSEC2KQgQWZ6wZg8BCBB7YgFPLCIAAbI5GM/NW0G/eWhB9r9nnjmdtulb1+0oQYB0GxkSZllk4AmeJSQg2xQEiCxPWLOHAASIPbGAJxYRgADZHIy/Pb2YHnpuCdXVRuiWs/cmpbr/lQEBIjuwwRM8ZQnIWsP4DJ4njuGVZQxr4RDofjYRjp9oFQRKSgACZDNuvoyQLyXcaVg/uuyEKUXFAAlJUdg6rASe4ClLQNYaxmfwPCFAZBnDWjgEIEDC4Y5WLScAAbI5QJfe8SItW9lI7o7b0GHTR3YYNf4iGTN8QHampO2DhER2sIMneMoSkLWG8Rk8TwgQWcawFg4BCJBwuKNVywlAgBAZY+j0mU9Tc0vGV7SGDupN15w8datlWkhIfOHzXQg8faPyVRA8fWHyXaiyeZb+yHrsAfE99FCwzAhAgJRZwOBuaQhAgGzm/NP7XqX5S1b7gh5xFN123j4UcZwtyld2QuILjWgh8BTFSeAJnrIEZK1BgMjyhDV7CECA2BMLeGIRAQiQzcHwjKH3VzWRZzoOzp+eSNK8xatoxOA+dMW3p25VEAme7MAGT/CUJSBrDeMzeJ5YgiXLGNbCIQABEg53tGo5AQgQ/wHK7xPZY9wQOvXLO0OA+EdXVEkkeEVh67ASeIKnLAFZa5gBkeUJa/YQgACxJxbwxCICECD+gpHxPDrthlmUzhg6Yu/RdNheW29UR4Lnj6XfUuDpl5S/cuDpj5PfUuDpl5S/chAg/jihVPkRgAApv5jB4xIQgADxB3nFR+vp4l+/kC185pET6dPuYMyA+ENXdCkkeEWja7cieIKnLAFZaxAgsjxhzR4CECD2xAKeWEQAAsRfMPiOEL4rhJ9rT5lGQwf2hgDxh67oUkiYi0YHASKLDjxD4ok9ICUAjyYCJwABEjhiNFCOBCBA/EXtgWfeIv6/mqhDt56zDznO1l8pSJj9sfRbCjz9kvJXDjz9cfJbCjz9kvJXDjMg/jihVPkRgAApv5jB4xIQgADxBzl/U/qnhvaly0/cA29E/WHrUSkkeD3Ct1Vl8ARPWQKy1iBAZHnCmj0EIEDsiQU8sYgABIi/YPzfb16gdz9cT3wJ4WcmDqO9dxlO/XrXblEZCZ4/ln5LgadfUv7Kgac/Tn5LgadfUv7KQYD444RS5UcAAqT8YgaPS0AAAsQf5NNnzqKNmz65Kf3AySPo659zIUD84SuqFBK8orB1WAk8wVOWgKw1CBBZnrBmDwEIEHtiAU8sIgAB4i8Yf3t6Mc16bTmta2rJVjhk2k70lX3HQID4w1dUKSTMRWGDAOkWNk4NOrl9tBNbGJ/dAt1lYQiQLhGhQJkSgAAp08DB7WAJQID45/vRmo10/q3PZSucfNh42nPCMAgQ//i6XRIJXreRdVoBPMFTloCsNQgQWZ6wZg8BCBB7YgFPLCJgtwAp/u1kEIhfT31IP//LG1nTPzppD9pxSF8IkCBA52wiYZaFC57gKUtA1hoEiCxPWLOHAASIPbGAJxYRsFuAWASKiB5+fgn9ddZiijiKbj13H4pGHAiQAEOEhFkWLniCpywBWWsQILI8Yc0eAhAg9sQCnlhEAALEfzBuf/BNmj3/fdphuz505XemblURCZ5/ln5KgqcfSv7LgKd/Vn5KgqcfSv7LQID4Z2VXSbtWKtjFZrM3ECA2RgU+hU4AAsR/CC694wVatnI97TFuCJ365Z0hQPyjK6okEryisHVYCTzBU5aArDUIEFmesGYPAQgQe2IBTywiEJwAqay3IumMR6fdMIsynqEj9x5Nh+41EgIk4HGMhFkWMHiCpywBWWsQILI8Yc0eAhAg9sQCnlhEIDgBYlEnBVxZtrKRLr3jxayls46aRLvGtoMAEeDamQkkzLKAwRM8ZQnIWoMAkeUJa/YQgAApWSwq6813cdjKhwEEiL8Iz57/Ht3+4Pxs4U8N6Ut1tZEtKiql6LOTtqfD93dp9er1lE57/gyjVIcEkDDLDg7wBE9ZArLWIEBkecKaPQQgQOyJBTyxiAAEiL9g/Oeld+iPjyc7LTywXx3ddfkXIED8Ie2yFBLmLhF1qwB4dgtXl4XBs0tE3SoAAdItXChcRgQgQMooWHC1dAQgQPyxbtzQQnwbemPTpq0qLFz6MfHfG0YMoJ+dvS8EiD+kXZZCgtclom4VAM9u4eqyMHh2iahbBSBAuoULhcuIAARIGQULrpaOAARIz1mfe/OztHpdMx0weQTN+PpkCJCeI81aQIInBDJnBjzBU5aArDUIEFmesGYPAQgQe2IBTywiAAHSs2CsbdpEM256JmvkxEPG0ZEHYA9Iz4h+UhsJsxTJzXbAEzxlCchagwCR5Qlr9hCAALEnFvDEIgIQID0Lxry3PqKZf3o9a+Tyk/agyRO2xwxIz5C21kbCLAQyZwY8wVOWgKw1CBBZnrBmDwEIEHtiAU8sIgAB0rNgPDr7bbr/qUXkKEW3/2BfGjq4PwRIz5BCgAjxa2sGAkQWLHgGz3PIkP7I3WQxw1oIBDCIQ4COJu0nAAHSsxjd9sA8enHBB7TD4D507Sl70sCBfSBAeoYUAkSIHwRIQCAxoxQIWMyABIIVRi0gAAFiQRDggn0EIEB6FpOLfz2bVnzURHtOGEanHbEzBEjPcG5RG2+YBWFiD4gsTPAsCU/MgIhj7oHB8rnfrAedDKQqBEggWGG03AlAgBQfweZNGTp95iwyRHTMfg106PSRECDF49yqJgRIezCLTwLAU3BwQoDIwuyAJwSIOGYYDIEABEgI0NGk/QQgQIqPUWr5Grrm7jmtBq46eSrtMnYYlmAVjxQzIELs2jMDASILFzyD5wkBIssY1sIhAAESDne0ajkBCJDiA7Ro+Rq6ukCAnPTFcXTE/jiGt3iiW9ZEgidFcrMd8ARPWQKy1rAHRJYnrNlDAALEnljAE4sIQID0LBj3P5miR19YmjVyyQm70x4Td8AMSM+QttZGwiwEMmcGPMFTloCsNQgQWZ6wZg8BCBB7YgFPuiAwbty4nTKZzC1ENE0p1eh53n3JZPJCIvLaVHVc172MiI4nou2IaDERXa21/pNfyBAgfkm1X+6xF5bSn59MkVJEt5+/Hw0bimN4e0b0k9pImKVIbrYDnuApS0DWGgSILE9Ys4cABIg9sYAnXRCIx+NzjDFz0un0+XV1dUPS6fTDSqnbtNYzC6u6rns6EV2slNo/kUikYrHYwUqpvyulJicSiTf8gIYA8UOp4zK3P/gmzZ7/Pg3frg/9+FSbjuEtfrNyz4jI1UbCLMcSAkSWJXiWhif2gMhzhsXSE4AAKT1ztFgEgXg8vrsxZnZdXd3guXPnrmYTsVjsVKXUDK312EKTsVjsDqVUX631V/P/7rrue0qp8xKJxD1+mocA8UOp4zKfHMM7lE47YiJOweoZzi1qQ4AIwsQMiCxM8CwJTwgQccwwGAIBRVT+bwRD4IYmS0wgFoudopQ6X2vdUCAq9iCiF5RS/ROJxLr8v8disSOVUrcaYw6qqamZn8lkvmCMuSeTyUxYtGjRO35cZwGydu0GymTaru7yU7u6y2zclKZTrn8qewzv1w6M0aHTR1H//r0IPGXGRSTigKcMyqwV8BSECZ6yMDvgOWhQX7w8FicNg6UmgEFcauJorygCruteRERHaK2n5A2MGTOmIRKJJJVSoxOJxFuFhmOx2BVKqUv435RSTZ7nHZdMJv/qt3EWIH7LotyWBBa8tYou+OX/sv94zWnTaWIDb8PBAwIgAAIgIEFAKd5dhwcEypsABnF5x69qvGcBYow5MplM7t6VAHFd91tKqauMMV/ZtGnT3JqamgOUUvcS0YFa65f8QMMMiB9K7Zf5z0vv0N3/SmT/eOt5+1D/PnV4Y188zq1q4o29IEy8sZeFCZ4l4YkZEHHMMBgCAQiQEKCjye4TcF33ZCK6SGs9Kl87FotNVUo9H41G+8+fP78x/++u675IRP/QWl9T8G9/J6J3tNZn+Wkde0D8UGq/zJ0PL6Bn5q6gvr1q6NQvT8gucenXt57WNW7MLmkb2K+Ott+2T/ENVHlN7AGRHQCVxTP8JdWVxVN2rBVjDadgFUMNdcqBAARIOUQJPlJDQ8NujuO8TERDtdYfMhLXdc8kolO11jsXIuLTsliAJBKJKwsEyCNElIIACX4w/ei3L9Hb77duyWm3wYu+NZkadhgQvDMV2AISPNmggid4yhKQtQYBIssT1uwhAAFiTyzgSRcEXNedTUTzPM87x3Gc4UTEouIGrfXNrusuJKLvaK2f4TtAlFInEdFh22+//fxly5bt7zjOP5VSBycSiSf8gMYMiB9K7Ze57YF59OKCDzo1cNZRk2jXGPaGFEMZCXMx1DquA57gKUtA1hoEiCxPWLOHAASIPbGAJ10QaGhoGOE4zu1EtC8RrSUivgPkR0RkXNc1OYHx2OTJk2saGxsvNcZ8g4iGENESIrpea32XX8gQIH5JbV3OM4beX9VEGW/zPv5o7tSm/8xeQg88s/msgJlnTqdt+tYV30gV10TCLBt88ARPWQKy1iBAZHnCmj0EIEDsiQU8sYgABIhcMPI/oDPveZmefHV5dg/IDWdMl2ugyiwhYZYNOHiCpywBWWsQILI8Yc0eAhAg9sQCnlhEAAJELhj5H9Azf/IEvf3eOprsDqYzjpwo10CVWULCLBtw8ARPWQKy1iBAZHnCmj0EIEDsiQU8sYgABIhcMPgHtHffejrmwoeJl2cdtc9o+uKeI+UaqDJLSJhlAw6e4ClLQNYaBIgsT1izhwAEiD2xaMeT8I9UtBpPgM5BgMjB5R/Q9z5ubr2c8Pxjd6VxIwfJNVBllpAwywYcPMFTloCsNQgQWZ6wZg8BCBB7YgFPLCIAASIXDP4B/d/c9+jXD8zLGv3ljL2pd31UroEqs4SEWTbg4AmesgRkrUGAyPKENXsIQIDYEwt4YhEBCBC5YPAP6B0PL6RZry6j7bftTVefPE3OeBVaQsIsG3TwBE9ZArLWIEBkecKaPQQgQOyJBTyxiAAEiFww+Af0h7c9T+9+uJ5Gbd+PLjl+ipzxKrSEhFk26OAJnrIEZK1BgMjyhDV7CECA2BMLeGIRAQgQwWAoopOu/eT+xzt/uD+ptWuo7v77qO6hB8l5dzmp9evJ9OlD3vAdqPnQL1HzMV8j06+/oBOVYwoJs2wswRM8ZQnIWoMAkeUJa/YQgACxJxbwxCICECByweAf0OOu+m/W4LT+LXTO4kep/i9/ItW0vsNGTO8+tPHoY6lpxrnk7TBCzpkKsISEWTaI4AmesgRkrUGAyPKENXsIQIDYEwt4YhEBCBC5YDiOolN/+hSNemseXfHwj6m+cY1v496gQbTmrj9Reo+pvutUekEkzLIRBk/wlCUgaw0CRJYnrNlDAALEnljAE4sIQIDIBWPFqia657Lf0pV/uYzqMpu6bdjU19PH9z9I6anYvM7wkDB3ewh1WgE8wVOWgKw1CBBZnrBmDwEIEHtiAU8sIgABIheMVx5/hfY88TDqv3HdFkZNJEKbvvBFaj7kUPIGDyFn5QdU9/A/qfaxh0l53hZleSZk9ePPYDkWBIjcwMxZggCRRQqewfMcMqQ/cjdZzLAWAgEM4hCgo0n7CUCAyMVo+bEn0q5P/HULg5v2O4DW3XATeSN23KohZ9k71O/cs6j2yce3+NuG479NjT/5mZxjZWoJCZ5s4MATPGUJyFrDDIgsT1izhwAEiD2xgCcWEYAAkQmGWreW+o1roLpNG1sNsvhY84f7eS1Rx42k0zTgG0dvIUK8Pn1p1RsLq/50LCTMMmMzbwU8wVOWgKw1CBBZnrBmDwEIEHtiAU8sIlBZAoQ/5qabdIups3UT0V/dSgMv+UHrH3jZ1aqX5/paSsUzIYOmTCKVybTWX3ftT2njt7/bzb5UVnEkzLLxBE/wlCUgaw0CRJYnrNlDAALEnljAE4sIVJYACQ9s7cEH0YA5z7c60PzFL9Ha397j26H+J3yD6h755yezJ9M/S2v+/rDv+pVYEAmzbFTBEzxlCchagwCR5Qlr9hCAALEnFvDEIgIQIDLBqNtlZ+q/YmmrsT98/SJ6ZffP+TY++eV/09fvvba1fHr0GFo9+1Xf9SuxIBJm2aiCJ3jKEpC1BgEiyxPW7CEAAWJPLOCJRQQgQGSC0dsdRX0+/qjV2CVHXU6v7bSrb+O7LXmVrvjbj1rLZ4YMpVXzkr7rV2JBJMyyUQVP8JQlIGsNAkSWJ6zZQwACxJ5YwBOLCECAyASj/5RdqO7tt1qN/e3ES+mNaQf5Nj7gH/fT2Y/eiBmQAmJImH0PH18FwdMXJt+FwNM3Kl8FIUB8YUKhMiQAAVKGQYPLwROAAJFhPOCIL1Lts/9rNdadPSCr1m6kj77wJdorNbu1/ibsAcFFhDJDs9UKEmZZoOAZPE/cAyLLuGtrMoeydN1OdZWAAKmueKO3PglAgPgE1UWx+jt+Rf0uPL+1VHdOwXrtiVdo/6/tTxHzyaWEOAULN6HLjMxPrCBhliUKnsHzhACRZQxr4RCAAAmHO1q1nAAEiEyA+B6QbSfFSa1f/8kshs97QBo/fzCNmvdCVhivhgAAIABJREFUaz3cA7IZBRI8mbGZtwKe4ClLQNYalmDJ8oQ1ewhAgNgTC3hiEQEIELlg9P/B2VT32zu2MNjlTejnfI9qn3piizq4CR0CRG5UYgYkCJYQyPJUIUDkmcKiHQQgQOyIA7ywjAAEiFxAat57l7bZbzrRR5+chsXWeTnWpoMOoeZDDiVv8BByVn5AdQ//k2r/9Qgp75NlV1zWGzSIVj/+jK8LDOU8t9MS3tjLxgU8wVOWgKw1CBBZnrBmDwEIEHtiAU8sIgABIheM7A/o/NfIHHggqY0bfRjecsOfV1dPa/76T0rvMdVH3covgoRZNsbgCZ6yBGStQYDI8oQ1ewhAgNgTC3hiEQEIELlg5H9A1z76X+r7za+Ss2qVb+PrevWnlj//hVp8iA/+MlOq8r/SkDD7Hj6+CoKnL0y+C4Gnb1S+CkKA+MKEQmVIoPJ/rcswKHA5fAIQIHIxKPwB9d5eSr1vvIHq77+PVNMnG9Pbtraxthc9MXYfun/qUfRhv8G+nKmJOnTcQXGaPnF7X+XLtRASPNnIgSd4yhKQtQYBIssT1uwhAAFiTyzgiUUEIEDkgtHeDyifjlX35/uo7qEHyFnxLqnGRjJ9+5K3/XBqPvTLdOH6MfR2U/e/nqZPHEbf/uJ4OecttISEWTYo4AmesgRkrUGAyPKENXsIdP8X3h7f4QkIBEYAAkQObTEJ3vurm2je4lVkjOnSkdWNzfTo7KXZcsd/IU777LpDl3XKuUAxPMu5v0H7Dp6yhMEzeJ64B0SWMayFQwACJBzuaNVyAhAgcgEKOiF56rXldNdjiazD15+6J223TS855y20FDRPC7scqEvgKYsXPIPnCQEiyxjWwiEAARIOd7RqOQEIELkABZ2Q3PL3ufRyYiUNGdiLfnzKnnKOW2opaJ6Wdjswt8BTFi14Bs8TAkSWMayFQwACJBzuaNVyAhAgcgEKMiHxPEPfv+l/tH5jmvbbbQf61kFxOccttRQkT0u7HKhb4CmLFzyD5wkBIssY1sIhAAESDne0ajkBCBC5AAWZkLy1Yi1d+fuXs86eccREmhz3d2KWXO9KbylInqXvTfgtgqdsDMAzeJ4QILKMYS0cAhAg4XBHq5YTgACRC1CQCclDzy2hvz29mPj6j198/7PUu75GznFLLQXJ09IuB+oWeMriBc/geUKAyDKGtXAIQICEwx2tWk6gMgXIljeMlyoEQSYk19/7Ci1c+jGNGd6fLj5u91J1KdR2guQZasdCahw8ZcGDZ/A8IUBkGcNaOAQgQMLhjlYtJ1CZAiQc6EElJM2bMnTmjU9TxjM0ZewQOmDyCBq1fT+qiUbC6WiJWg2KZ4nct64Z8JQNCXgGzxMCRJYxrIVDAAIkHO5o1XICECByAQoqIXlzySq64b7XtnB09/hgOv2IiXLOW2gpKJ4WdrUkLoGnLGbwDJ4nBIgsY1gLhwAESDjc0arlBCBA5AIUVEKyfGUjXf7bl7IzIPln/MiBdN6xu8k5b6GloHha2NWSuASespjBM3ieECCyjGEtHAJVLkDCWRMfTqjRancIQIB0h1bnZYNMSNY1baJ3P1xP1937ataJr+w7hg6ZtpOc8xZaCpKnhd0N3CXwlEUMnsHzhACRZQxr4RCocgESDnS0aj8BCBC5GAWdkLy44H267YE3sw5ffuIU+tTQfnLOW2gpaJ4WdjlQl8BTFi94Bs8TAkSWMayFQwACJBzuaNVyAhAgcgEKOiG58+EF9MzcFTSgTy3NPHM6KT6Tt4KfoHlWMLp2uwaeshEHz+B5QoDIMoa1cAhU9i91OEzRagUQgACRC2JwCYkiYzw69+Zn6ePGTbTXzsPoO4eOl3PcUkvB8bS0wwG7BZ6ygMEzeJ4QILKMYS0cAhAg4XBHq5YTgACRC1CQCcmylY106R0vZp397mHjadqEYXKOW2opSJ6WdjlQt8BTFi94Bs8TAkSWMayFQwACJBzuaNVyAhAgcgEKMiF57IWl9OcnU8RfZD876zPUv3etnOOWWgqSp6VdDtQt8JTFC57B84QAkWUMa+EQgAAJhztatZwABIhcgIJMSH5636s0f8lqGjmsH116whQ5py22FCRPi7sdmGvgKYsWPIPnCQEiyxjWwiEAARIOd7RqOQEIELkABZWQ8E3o3/v505TOGNppWD/aZcy2ck77tFRfG6XPTNqe+vaq8Vmj58WC4tlzz8rTAnjKxg08g+cJASLLGNbCIQABEg53tGo5AQgQuQAFlZAkl31M197zipyjRVo6aI8d6av7x4qs3f1qQfHsvieVUQM8ZeMInsHzhACRZQxr4RCAAAmHO1q1nAAEiFyAgkpI1m9soRvvf53e+6hJzlmfltKeIZ6B4eeY/RroC1M/5bNmz4sFxbPnnpWnBfCUjRt4Bs8TAkSWMayFQwACJBzuaNVyAhAgcgGqxIQkv/mdKV1/6p603Ta95IB1YakSeZYMXjsNgacsffAMnicEiCxjWAuHAARIONzRquUEIEDkAlSJCcnVd71Mi95dS6O270eXHF/aze+VyFNutHXfEnh2n1lnNcAzeJ4QILKMYS0cAhAg4XBHq5YTgACRC1ClJSSr1m6k8255Lgvo6P3G0MFTd5KD5cNSpfH00eVAi4CnLF7wDJ4nBIgsY1gLhwAESDjc0arlBCBA5AJUaQnJv19cSvc9kcoCuu7UPWlwCZdfcZuVxlNupBVnCTyL49ZRLfAMnicEiCxjWAuHAARIONzRquUEIEDkAlRpCck1d8+h1PI1od09Yj9P/lkxcgMoYEv28wwYgLB58JQF2h5PCBBZxrAWDgEIkHC4o1XLCUCAyAWokhKSLZZf7TuGDp5W2uVXmAGRG5d5S5U0PuXpdN8ieHafWWc1IEBkecKaPQQgQOyJBTyxiAAEiFwwKikh+c9L79AfH09m4YSx/AoCRG5cQoDIs8T4lGcKASLPFBbtINADAVJe0+x24IYX5ULAHgFS/p+zShIg19wzh1LL1pCjFDWMGBDKcFaK94FEKJ3OkOlipdPgberpW5+PU21NJBRfy6HRShqfNvAGT9koQIDI8oQ1ewj0QIDY0wl4AgLSBOwRINI9K729SkpITp85izbmLiAsPcniWpxx9C40acy2xVWuglqVND5tCBd4ykYBAkSWJ6zZQwACxJ5YwBOLCECAyAWjkhKS2fPfozkLV4a6xZpnQGpro7RpU7rDGZBFy9fQmvWbKBpRNPPMz1DfXjVyAa0wS5U0Pm0IDXjKRgECRJYnrNlDAALEnljAE4sIQIDIBQMJiRxLttQVz3TGo3N++Sw1bmihKWOH0GmH7yzrQIVZ64pnhXU38O6ApyxiCBBZnrBmDwEIEHtiAU8sIgABIhcMJCRyLP0IkDmJD+jmv8/LNnr2MbvQxNFYftVZBDA+Szs+ZVurfGsQIJUf42rtIQRItUYe/e6UAASI3ABBgifH0o8AufH+1+mNRR/RwH519JPT9iLHwdc8BIjsGLSTZ/kf2NEeVwiQ0o1dtFRaAvhlKi1vtFYmBCBA5AIFASLHsisBsnpdM513y7PZvSFf3HMnOmqfMbKNV6A1jE/ZoIJn8DxxEaEsY1gLhwAESDjc0arlBCBA5AKEhESOZVcC5JHZb9NfnlqUbfDaU6bR0IG9ZRuvQGsYn7JBBc/geUKAyDKGtXAIQICEwx2tWk4AAkQuQEhI5Fh2JkCMMXTxr1+g91Y1kTtiAP3wm5NlG65QaxifsoEFz+B5QoDIMoa1cAhAgITDHa1aTgACRC5ASEjkWHYmQPiCRL4okZ8TDxlLn500XLbhCrWG8SkbWPAMnicEiCxjWAuHAARIONzRquUEIEDkAoSERI5lZwLk948tpFmvvSvbWA+tTRg5kM4+ZlerN8JjfPYwyG2qg2fwPCFAZBnDWjgEIEDC4Y5WLScAASIXICQkciw7EyA3/30uzUmslG2sh9b40sRbz9mHamsiPbQUXHWMT1m24Bk8TwgQWcawFg4BCJBwuKNVywlAgMgFCAmJHMvOBMja9ZvoFb2SWjKebIPdtJbJGLr/yVT2tvhdG7ajs74yqZsWSlsc41OWN3gGzxMCRJYxrIVDAAIkHO5o1XICECByAUJCIseyMwEi20rx1l5c8D7d9sCbWQMzjp5Ek8ZsV7yxEtTE+JSFDJ7B84QAkWUMa+EQgAAJhztatZwABIhcgJCQyLEsBwFy/b2v0MKlH9O2/evpulP3tHr/RznwlB09wVvD512WMS4ilOUJa/YQgACxJxbwxCICECBywUBCIsfS9oR5xUfrs0cB83Pk3qPp0L1GynY+AGsYn7JQwTN4npgBkWUMa+EQgAAJhztatZwABIhcgJCQyLG0XYDc93iS/v3SOxRxFP309L1oQN862c4HYA3jUxYqeAbPEwJEljGshUMAAiQc7mjVcgIQIHIBQkIix9JmAbKpJUPn3vwsrd+Ypt3HDqHTD99ZtuMBWcP4lAULnsHzhACRZQxr4RCAAAmHO1otgsC4ceN2ymQytxDRNKVUo+d59yWTyQuJaKtjf1zXHauUus0YswcRfUREM7XWP/PbLASIX1Jdl0NC0jWj7pSwleezc1fQHQ8vyHbl/GN3pXEjB3WnW6GVtZVnaEB62DB49hBgm+rYAyLLE9bsIQABYk8s4EkXBOLx+BxjzJx0On1+XV3dkHQ6/TCLDK31zMKqI0aM6NWnT5+Fnuf9cv369Tf37dt3AhH9loi+orVe6Ac0BIgfSv7KICHxx8lvKVt5Xn33y7Ro+VrqUx+l04+YSH5+XPr1qaXh2/YmxReGhPTYyjMkHD1uFjx7jHALAxAgsjxhzR4C4X3r28MAnpQBgXg8vrsxZnZdXd3guXPnrmaXY7HYqUqpGVrrsYVdcF33eCI6V2td9AUEECBygwIJiRxLtmQjzw9WN9EPfzW7qI6eccTONDk+pKi6EpVs5CnRr7BsdMyT0w2+HQZPdwh0LUDAtTs8UdYeAhAg9sQCnnRCIBaLnaKUOl9r3ZAv5rouL696QSnVP5FIrCv4918rpXoTUbMx5kgiek8pdWUikfiDX8gQIH5JdV0OCV7XjLpTwkaeq9c108W/nk0bN2W605Vs2e8eNp6mTRjW7XpSFWzkKdW3MOyApyz1rgWIbHuwBgKlIgABUirSaKdHBFzXvYiIjtBaT8kbGjNmTEMkEkkqpUYnEom3CgTIo0qpvT3PO3n9+vX/6Nu379FEdKfnebunUqlX/TjCAmTt2g2UCflWaT++2l4mEnGof/9eBJ4ykeo+z9K8IW3amKYP12zw1cnfP7qQksvWUJ9eNfTzsz5DtTURX/WCKNR9nkF4UTk2wVM2lu3xHDSoL3I3WcywFgIBDOIQoKPJ7hNgAcKzGclkcveuBEgsFnuMZ0C01nsXiJLniehJrTULmS4fFiBdFkIBEACBbhPg5VonX/0f8gzRkfs20ImH8RYtPCAAAn4JqDA3Tfl1EuVAoAsCECAYImVBwHXdk4noIq31qLzDsVhsqlLq+Wg02n/+/PmNBWLjd0qpQYlE4ksF//ZHpdSGRCJxkp8OYwbEDyV/ZfBG1B8nv6XKnef9T6bon88uyW5S/+kZ02nwwF5+ux5IuXLnGQiUHhgFzx7Aa6cqZkBkecKaPQQgQOyJBTzphEBDQ8NujuO8TERDtdYfclHXdc8kolO11ltcOBCPxy8wxpyeEyvZmQzXdXkG5DGt9Y/8gMYeED+U/JXBmnB/nPyWKmeeLWm+K+Q5atzQQrs2bEdnfaXocyL84uqyXDnz7LJzIRQAT1no2AMiyxPW7CEAAWJPLOBJFwRc1+VjduZ5nneO4zjDiegRIrpBa32z67p8vO53tNbPxOPx4cYYbYy5dsOGDTN79ep1uFLq957njUulUov8gIYA8UPJXxkkJP44+S1Vzjyfm7eCfvPQ5rtCzvnqLrTzqG39djuwcuXMMzAoPTAMnj2A105VCBBZnrBmDwEIEHtiAU+6INDQ0DDCcZzbiWhfIlpLRHwHCM9oGNd1jVLq4EQi8RibaWho2MdxnJ8T0VhjzFKl1Pe11o/6hVwdAqQ0m5ORkPgddf7KlTPPq+56mRa/u5aGDupNV588lZwQ7//I0y5nnv5GTGlLgacsbwgQWZ6wZg8BCBB7YgFPLCJQHQKkNMCRkMhyLleeb61YS1f+nldREn3twBh9bvcdZcEUaa1ceRbZ3cCrgacsYggQWZ6wZg8BCBB7YgFPLCIAASIXDCQkcizZUrnyvOOh+fTsvPeyMFh89KoL7+hd9oEPEpowahCN3WkgDRzYh1avXk/ptCcbrCq0Vq7j09ZQQYDYGhn41VMCECA9JYj6FUkAAkQurEhI5FiWswA5beYsai7iokJZeltaq6+N0K/O35cGDeoLASIEGp93IZA5MxAgsjxhzR4CECD2xAKeWEQAAkQuGEhI5FiWswC5+18JenHB+xT2DTt8LN6G5nQ2KCMG96FrTtkTMyCCQxSfd0GYHcx4DhnSH7mbLGZYC4EABnEI0NGk/QQgQORihIREjmU5CxBZCsVbSyxdTdfd+2rWwHEHxenAKTtCgBSPc6ua+LwLwoQAkYUJa1YRgACxKhxwxhYC9gmQ0pxYFQR/JCSyVMGzZzxv+ftcejmxknrXRemGM6ZTn941ECA9Q7pFbYxPQZgQILIwYc0qAhAgVoUDzthCwD4BYguZ7vuBhKT7zDqrAZ7F81y1diNdcOvz5BlDn5+yIx17QKxsN/UXTyHYmhifsnyxB0SWJ6zZQwACxJ5YwBOLCECAyAUDCYkcS7YEnsXz/OusRfTw828T//Bde8o0GjKwN3gWj7PdmhifskAhQGR5wpo9BCBA7IlF2Xniuu4TPXDaaK0P6EH9QKtCgMjhRUIixxICpHiWLekMnXvzc9S4oYUmjdmWZhy9S9YYxmfxTNurCZ7B88QmdFnGsBYOAQiQcLhXRKuu6/bk0HwWIOFeBNBJFCBA5IYoEhI5lkiYi2f57NwVdMfDC7IGzjlmF9p59LYQIMXj7LAmPu+yUDEDIssT1uwhAAFiTyzKzpOGhoZ9euJ0KpWa1ZP6QdaFAJGji4REjiUESHEsjTHZW9iXvLeOhg7sRVd/dxo5avPPH8ZncUw7qgWewfPEDIgsY1gLhwAESDjc0arlBCBA5AKEhESOJRLm4lguencNXX3XnGzlAX1raftBvVsN8Y3o0WiE0ukMsVApfPr1rqWvHRijbfrWFddwFdbC51026JgBkeUJa/YQgACxJxbwxCICECBywUBCIseycgRIaY+V/veLS+m+J1I+A7Glb18/MEYH7r6jz7oohs+77BiAAJHlCWv2EIAAsScWZecJNqGXXchCcRgJiSx28Ow+z7VNm+hvsxbTuqZNW1V2HEU1NRFqacmQ522eAeGlWqvXNWf/+8rvTKUdtuvT/UartAbGp2zgIUBkecKaPQQgQOyJRdl5gk3oZReyUBxGQiKLHTyD5dmS9uj8W5+jtes30YRRg+jcr+4q22CFW8P4lA0wBIgsT1izhwAEiD2xKDtPsAm97EIWisNISGSxg2ewPJ+bt4J+89Dm07JmHD2JJo3ZTrbBCreG8SkbYAgQWZ6wZg8BCBB7YlE1njQ0NIzgvaCpVOpNWzuNPSBykUFCIseSLYFncDx5GdYVv3uZ3n5/HQ0d1JuuPnlq62lZsq1WrjWMT9nYQoDI8oQ1ewhAgNgTi6rxJB6PX2KMOUVrzULEygcCRC4sSEjkWEKAyLJsy3P+W6vox394JdvINz7n0gGTrf2KkgchZBGfdyGQOTMQILI8Yc0eAhAg9sSiYjyJx+NfIKJJxpj6tp0yxgxUSn2LiGq11v1t7TQEiFxkkJDIsYQAkWXZludN979OLydWUq+6KN1wxl5UXxuVb7DCLeLzLhtgCBBZnrBmDwEIEHtiUfaeTJo0qc/GjRsfI6K9uugMj7s/a62PtbXTECBykUFCIscSAkSWZSHP5Fsf0rk3P0t8FchBe+xIX90/Jt9YFVjE5102yJUlQEp7/LZsJGBNmgAEiDTRKrbnuu7VRHQhEb1HRP8loo1E9B0ieoCIPiSi/YioXil1diKR+BsRZWzFBQEiFxkkJHIsIUBkWRbyvPUvr9Ejz79NfEH6dafsSdtt00u+sSqwiM+7bJArS4DIsoG18iYAAVLe8bPKe9d1+egYp76+/tNvvPHG+nHjxu2UyWTeUkodnkgkHuS/ua77K6VULJPJHJRKpTYftG/hAwEiFxQkJN1l2flbQvDsLs/OyzPPPn3r6VuXP0ZNG9OyxmGtXQIRR9Hnp+xIR+/XAEJdEIAAwRCpVAIQIJUa2RD65bruBiK6UWvNsyDUjgCh8ePH16bT6deJ6I9a6ytCcNNXkxAgvjD5KoSE2Rcm34XA0zcqXwWZp1MTpeN/9C/K5C4i9FURhXpEYMTgPnTFt6f2yEY1VIYAqYYoV2cfy1yAYD2hTcOWBYgx5qpkMslLsWjUqFFDa2pqVhhjvplMJu/N++q67rVEdLjWepxN/hf6AgEiFxkkzHIs2RJ4BsPzxbnLKfXOGlnjVWjNiSjq3auWmjZsIi+z+Wb5/MMC7/4nU8T/ut+nd6BvfT5ehYS612UIkO7xQunyIVDmAqR8QFeDp67rpohortb6iFx/I67rbiKi67TWFxUIkEuJ6AKtdV9buUCAyEUGCbMcSwgQWZbgWVqe+p2PW485Pusrk2jXBlzy2FUE7BQg1fbyt9r629WolPk7BIgMR1gholgsdotS6hQi+m06nb5i8eLFS13XXUhEAzOZzPRFixalxo8f3zedTj9DRNtorUfaCg4CRC4yECByLJEwy7IEz9Ly/OusRfTw829TNKLoF9/fm+pqI/IOVJhFOwVIhUFGd0IhAAESCvbKbHTcuHHbZzKZOUQ01HGcQxYuXPgv13XPJaKfEBHPhCSI6FNExPd//EZrzWLFygcCRC4sECByLJEwy7IEz9LyvPy3L9LS9xtpwsiBdO6xu8k3XoEWIUAqMKjoUpYABAgGgiiB8ePHD0un06caY+5KJpOLeYzxyVdEdBKfgpUddEr9p7a29ti5c+euFm1c0BgEiBxMCBA5lkiYZVmCZ+l4rmlsprN/+Wy2wa/u30AH7cHvovB0RQACpCtC+Hu5EoAACT1y1bG2kDekR6PRkUqpZVrr5aFj78IBCBC5CEGAyLFEwizLEjxLx/OZN1bQnY/wSe1EV31nKg3fro984xVoEQKkAoOKLmUJQIBYPxAqSqDwDIhnPXIiggCRixIEiBxLJMyyLMGzdDxve2AevbjgA9q2fz1df9qePBMu33gFWoQAqcCgoksQIBgD8gTi8fgoY8zPlFJPJhKJnxe24Lrun4moj+d556dSqfnyrctZhACRYwkBIscSCbMsS/AsDc+M59GMm56h9RvTtO9uO9BxB+H4Xb/kIUD8kkK5ciOAVxDlFjGL/XVddwcieo2IBhljfpJMJn/YRoD8iYiOJqKPlVKTE4nEW7Z2BwJELjIQIHIskTDLsgTP0vBMLVtD19zD55MQfe+oibRbbLB8wxVqEQKkQgOLbmEJFsaAHAHXdW/nzeZKqe81Nzf/dsmSJRvbWFexWOxYpdTviegPWusT5VqXtQQBIscTAkSOJRJmWZbgWRqef3lqET0ye/Pxuzd9/7NUXxuVb7hCLUKAVGhg0S0IEIwBOQKu6/Kt548nk8lvdmY1Fovdo5TaX2s9XK51WUsQIHI8IUDkWCJhlmUJnqXhefGvZ9OKj5po4uht6exjdpFvtIItQoBUcHCrvGtYglXlA8Bf9/1thHddt5mILtdaX9uZXdd1+Vb0S7XW9f7aL30pCBA55hAgciyRMMuyBM/geb6/qokuvH12tiHe+8F7QPD4JwAB4p8VSpYXAQiQ8oqX1d7G4/G3jTH/0lp/twsBcjcR7au13rH4DvkTRe3b77ouBEjxkWlbEwJEjiUSZlmW4Bk8z8deWEp/fjKVbeiGM6bTwH518o1WsEUIkAoObpV3DQKkygeAZPdzFw5+i4gO01o/3o5tFY/HTzTG8MWE92APiCR9e21BgMjGBjzBU5aArLW24/PHf3iF9Dsf06jt+9Elx0+RbawKrEGAVEGQq7SLECBVGvggup07BWsuEQ0goteVUq8ZY/i2c37lxcee7E1EQ4hojeM4n164cOGSIPyQsIkZEAmKm20gYZZjCZ6yLMEzWJ6r126kGb94howhOuKzo+iw6aPkG6xwixAgFR7gKu4eBEgVBz+Irsfj8bgx5h4imtyBfT6L8Tta69eDaF/KJgSIFEkIEDmSEHTSLCFA5IkWJsyzXl1Odzy8+fbzK07ag0YM6SvfYIVbhACp8ABXcfcgQKo4+EF23XVdPuqE59t5xsMzxrwfjUZfWrBgwbwg25WyDQEiRRICRI4kBIg0SwgQeaKFCfPP73+d5iRW0nYD6um6U3H7eTG0IUCKoYY65UAAAqQcogQfS04AAkQOOZZgybFEwizLEjyD4/n+yrV0xg1PU3NLhg6cPIK+/jlXvrEqsAgBUgVBrtIuQoBUaeCD7nZDQ8OeSqkpSqlhnufdk0ql5nObo0ePHrB48eI1QbffU/sQID0l+El9CBA5lkiYZVmCZ3A8n3zxbZr5p9eyDZx/7K40buQg+caqwCIESBUEuUq7CAFSpYEPqtsNDQ3THMf5LRG1vu5SSh2RSCQebGhoqHMc510iukRrfUtQPkjYhQCRoLjZBgSIHEvwlGUJnsHxvP73L9L/3lhBfeqj/9/encfJVZX5H3/OrU6aJE0UZCdCIFW3OmyKbKKAiI6CiAq4Di6jwIAOmyzzU5xREZcZZ0BUNvHnCIgziDiiiID+FBCU3SUh3X1PNSRgCLto0kkg6brn9zpNNRShk7rV/VT3uVWf+mfG5Nynnvt+bpPz7aq6JV87cT/pKkT6T9YBFQkgHTDkDj1FAkiHDr68/Pq+AAAgAElEQVQVp93b2xunafp7EZkpIreKyID/wPloAKndJes2EdnOOXdwpVL5ZSv60KhJANFQJIDoKb5QiUCnq4qnvmfPxjPkg5+7XlY9Myz77ba1fOxt83WfpIOqEUA6aNgddqoEkA4beCtPN47jy0TkKOfcOyuVynXz58/fvlqtLjbGvMu/AuKfe/78+VtXq1V/q97brbWHtbKfidQmgExE78XHssHTs+Q39rqWeLbG84HHhuTz337u288/+d5Xya47vkL/iTqkIgGkQwbdgadJAOnAobfqlOM4/rOI/NZa+/5a2HhJAPF/Xi6XL3LOHWmt9XfICvJBANEbCwFEz5INs64lnq3x/N4vrPzyrod4+5UCLwFEAZESQQoQQIIcSz6biuP4WWPMF5MkOXtDASSO40+LyFnW2umhnikBRG8yBBA9SzbMupZ46nuKETn567fKilVr5fW7biVHH7pTC56kc0oSQDpn1p12pgSQTpt4C883juMnROQqa+0/NXgF5GLn3BG8AtLCYQRUmgCiOww88dQV0K3W/+DT8h//84eRoqe8ZzfZbd5muk/QYdUIIB028A46XQJIBw271acax/HPRWTPQqHwqv7+/kfG+gxIHMe9InKXiNzCZ0BaPZEw6rNh1p0DnnjqCuhWu/zGRG7+w8Mys7tLzjuJu19NVJcAMlFBjg9VgAAS6mRy2FepVHqzMeZGEVnmnPtqFEWPOeeuFJHTnXOJiPydMeajItIjIm+x1v4q1NPkLVh6k2HDrGfpK+GJp66AXrVqmsqp5/+29varreXoQ7n71UR1CSATFeT4UAUIIKFOJqd9lUqlk4wx54jIWDd999dbVUT+2Vr7tZBPkQCiNx02zHqWBBBdSzx1PRct+Yucc+VzXz645aYzZZOe7B/zK0RGDtx9juxR3ly3qZxXI4CMDtBvH1zOp0n79QIEEK4HdQH/fSDOuWOdc/uIiL/Tld/PP2qMucMYc2mSJP7VkKAfBBC98RBA9CzZMOta4qnrecOdD8lVNw2Ou+i2m8+Ss4/2/2zwGBUggHAttKsAAaRdJ8t5TUiAADIhvhcdTADRs2TDrGuJp67n8pVr5Me3PiDPrE1l7dqq/81TwydIUyd/uv+pkXWv32UrOfrt3DWrHo0A0vASYkFOBQggOR1caG2Xy+Vt0jQ90BiTRlH0+4GBAbu+HmsfTr/QWntoaOcx2g8BRG8yBBA9SzbMupZ4Tr2n/fNf5d++//uRRk44Yld5TcxbsAgg+tclFcMTIICEN5PcdVQul09xzv2biEyra/6/rLXHiUha92dRqVQ6zRjzWRGZaa0thHqyBBC9yRBA9CzZMOta4jn1nj/4dUVuvOvPMr0rkq+fvL90Twvln4UwPnPAKyD61ygVwxAggIQxh9x2EcfxfiLyGxEZFpFf1gLH/iKysYh8xlrrg4nEcby3iFwiIrvWTvZya62/I1aQDwKI3lgIIHqWbJh1LfGcWk//Fq1Pf+sOefyvq2X30mZy4pG76TeU84oEkJwPkPbXK0AA4eKYkEC5XP6+c+59xpi3JEnya1+sWCzOiaLI32J34zRNe6Mo+rKI+FdDCs653zvnThgcHLxjQk/c4oMJIHrABBA9SzbMupZ4Tq3n0ieG5LPf8V8LJfKxt82X/XbbWr+hnFckgOR8gLRPAOEaaI1AHMeLRaTfWvu2+meI4/jDInKpiPhPF75CRP7inPtMpVLxr4I0/mRia9rNXJUAkpmq4UICSEOiphbg2RRXw8V4NiRqakEzntf+bon8+DcPiDEi5524n2w8M/tte5tqKseLCSA5Hh6tb1CAV0C4QCYkEMfxahH5mrX2zPpCxWJx9yiK7vVvyTLGfLurq+szixYt+suEnmwSDyaA6GE3syHRe9b2rYSn7mzxnDrPL1x6tyx5dIXEr3y5fOqo1+g20ibVCCBtMkhO4yUCBBAuigkJxHHsP2R+urX23PpCtTtdLXbOHV2pVL47oSeZgoMJIHrobPD0LH0lPPHUFdCtlvX6/MvyZ+T0C3838uTvP6gob9l7O91G2qQaAaRNBslpEEC4BnQFGgUQY8y7kiT5qe6ztr4aAUTPOOuGRO8Z27sSnrrzxXNqPH/9+6VyxS9euFv7eH4bOqO7S45/586yy47+Xb7t+SCAtOdcOSuR8fzM44bA8wIEEC6GRgJs8BoJNff3eDbn1Wg1no2Emvv7rJ7X3b5EfnTLA80VH2P121+3vRxxwLwJ1wm1AAEk1MnQ10QFCCATFezw4wkgHX4BZDj9rBuSDKVYwluw1K8Brk9d0qyea9ZW5c7+x2T1M/4O7s09lj65Um5b8MjIQae851Wy2zxeAWlOkNUITL2Aee5FkOBvSjT1UnQwpkAtgJxmrf1a/YLRz4CkafrOwcHBa/PGx1uw9CaWdUOi94ztXQlP3fnimT/PH91yv1x3+4PSVYjkm6eE9OWFupa+Gq+A6JtSMQwBXgEJYw657aIWQFaKiL8bVv0jEpFNRGSFiKwZ4wSdtXbLUE+cAKI3GTZ4epbr25DoPkNnVeP61J33ZHie9d275cHHVsjOczeR096/u+4JBFaNABLYQGhHTYAAokbZmYVqAWQ8J+8DSGE8B07GMQQQPeXJ2JDodRt+JTx1Z4Rnvjz/tnKNfPKbt400/b6DivLWNr97FgFE9/psrhrvEGrOq7nVBJDmvFi9joB/q9V4Ufr7+x8c77GtPo4AoifMBk/P0lfCE09dAd1qrb4+b7/vUfn2z/pGmj77mH1k281m6Z5AYNUIIIENhHbUBAggapQUaicBAojeNFu9IdHrNB+V8NSdE5758rzk2kVyx6LHZJONu+U/P/E6Mf5r1Nv4QQBp4+F2+Km1909uhw+X0x+/AAFk/HbrHskGT89y4q+A8JYCrk/d63EyPVPnRt5+tWLVWjngVVvLPxwyv7UnE0B1AkgAQ6CFlggQQFrCStG8CxBA9CZIANGznHgA0e2lHapxfepOsZWeSx5dLl+49J6Rhj/xrl1kz94tdJsPsBoBJMCh0JKKAAFEhZEi7SbwQgDxt6jmNtUTmW8rNyQT6Suvx+KpOzk88+N57e+WyI9/84BExsg3Tt5PZm40Tbf5AKsRQAIcCi2pCBBAVBgp0m4CvAKiN1E2eHqWvAKia4lnvjy/ePk98sCy5VKc8zI584N76DcfYEUCSIBDoSUVgRwGEN7DrDJ5imxQgACid4EQQPQs2TDrWuKZH8+/DT0rnzz/tyMNv+eN8+SQfcZ9A0b9k25hRQJIC3EpPaUCOQwgU+rFk3eIAAFEb9AEED1LNsy6lnjmx/OWPz4sl92QjDT85X98rWy16Uz95gOsSAAJcCi0pCJAAFFhpMhkCPjvHKlWqxeKyGuNMUNpml5ZqVQ+LSLp+p4/juNtRWRARM6x1n4+a58EkKxSjdcRQBobNbMCz2a0Gq/Fs7FRMyta5XneD/8kC+5/aiR4+ADSKQ8CSKdMuvPOkwDSeTPP7RmXy+V7nXP3Dg8Pn9Hd3b3F8PDwdcaYi621524ggPxIRN4kIucRQKZm9K3akEzN2Uz9s+KpOwM8w/d8dk1VTvz6rTJcTeWQfbaT97yxqNt0wNUIIAEPh9YmJEAAmRAfB0+WQLlc3tM5d0d3d/fmCxcufNo/b6lUOt4Yc4q1tnesPuI4fpt/5cOHFmPMIAFksqb14udhg6frjieeugK61Vpxfd6bPCEX/HjhSKP+w+f+Q+id8iCAdMqkO+88CSCdN/NcnnGpVDrOGHOGtfb5X33Fcby3iNxpjJmdJMmK+hObM2fOjJkzZy4yxhztnPuIiCwhgEzN6FuxIZmaMwnjWZ/znClPP71KhofX++7DMJrNQRdcn7pDaoXnd67rk98ufFQ2njlNvnbCfhJFnbN1IYDoXp9UC0egc36KwzGnk3EIxHF8pogcbq3da/TwefPmFQuFQsUYs2OSJIvry8Zx/BVjzHZJkhwVx/Gl4wkgy5evlmqVDd44xvWiQwqFSGbPniF4TlTyuePx1HEcrYJn2J5p6uTE835T+/bzbeSYw3bSbTjwamNdn5tu2sPeLfC50V5jAS7ixkasCEDABxDn3BGVSmXPRgGkWCzuFEXRLV1dXbv29fU9Ot4AEsBp0wICCCDQ0QKLHnhKPnXBbSMG++y8lRRf+fIJeczo7pI37bWd9MzI75cYGmPYu03oKuDgEAS4iEOYAj00FIjj+Fj/9l9r7Q6ji0ul0j7GmNu7urpm9/X1DdX+3MRxfLOIXGWtvcD/2XgDCL+xbziWTAv4DXMmpsyL8MxMlWkhnpmYMi/S9vzpbYvl6pvvz/z8WRYeuu/28r43lbIsnfI1vAIy5SOggRYJEEBaBEtZXYFisbh7FEX3iMiW1tona8HiBBE53lq7y+iz1W7Vu0REnqrroKd2q94Ba+1rsnTGbXizKGVb04r3hGd75vZchafuXPEM23Pw4b/JJT9dJCufWTuhRtNU5Nm11ZEahx+woxz2urkTqjdZB/MZkMmS5nkmW4AAMtniPN+4BeI4vkNE7kvT9NQoirYRkZ/Xvt/jgjiO/Xd9HGOtvb1YLG5d/yRRFPnb9C7t6ur6qn9LVpYGCCBZlLKtYYOXzSnrKjyzSmVbh2c2p6yrQvX03yHiv0vEP/J0Jy0CSNYrj3V5EyCA5G1iHdxvsVicE0XRJSJyoIgsFxH/HSBniYiL49gZYw5JkuSGdYnG+xasp59eyV2GFK63UDckCqc2JSXw1GXHszM8f3jToFx/50MyfVok559ygHQVIt0Tb1E1AkiLYCk75QIEkCkfAQ2EKMArIHpTYYOnZ+kr4YmnroButVCvz7Mvu0cWP7Jcdt5hUzntfa/WPekWViOAtBCX0lMqQACZUn6ePFQBAojeZELdkOid4eRWwlPXG8/291z97LCceN6tkjonR75hRzl033x8/mN9v3DYYovZ7N10L1uqTYEAF/EUoPOU4QsQQPRmxAZPz5JXQHQt8ewMzwX3Pynn/XDByMl+5kN7yLxt8/NN6rwCon+NUjEMAQJIGHOgi8AECCB6AyGA6FmyYda1xLMzPK+6aVBuuPMh6Z5WkG+esn9uPv/BKyD61ycVwxEggIQzCzoJSIAAojcMAoieJRtmXUs8O8Pz7MvulsWPrJBddthUTs3R5z8IIPrXJxXDESCAhDMLOglIgACiNwwCiJ4lG2ZdSzzb33PVM8Ny4td/I86JbLJxt2y16UzVk969tJm8ec9XqtasL8ZbsFpGS+EpFiCATPEAePowBQggenMhgOhZsmHWtcSz/T0femyFfP67d+ufaK1iZIxccOoBI2/vasWDANIK1Xat6bf0LjcnRwDJzahodDIFCCB62gQQPUs2zLqWeLaj54s3Yf7OV9fc+oAsfXyl6skufWJInvzbMyPfK3LhqW8QH0Ra8SCAtEKVmiEItOYnJoQzowcEJiBAAJkA3jqHEkD0LNkw61riied4BS665j65e+Bx2X7LjeVzH91rvGUaHkcAaUjEgpwKEEByOjjabq0AAUTPlwCiZ8mGWdcSTzzHK/DZ79wpS59YKa/daUv5x3fsPN4yDY8jgDQkYkFOBQggOR0cbbdWgACi50sA0bNkw6xriSee4xFIUyfHn3OLDFdTOXz/HeSw1+8wnjKZjiGAZGJiUQ4FCCA5HBott16AAKJnTADRs2TDrGuJJ57jEXj86VXyqW/dMXLoJ961i+zZu8V4ymQ6hgCSiYlFORQggORwaLTcegECiJ4xAUTPkg2zriWeeI5H4E+DT8rXr37um9XPPnpv2XbznvGUyXQMASQTE4tyKEAAyeHQaLn1AgQQPWMCiJ4lG2ZdSzzxHI+A/1Z1/+3q/sZXF592oEzrisZTJtMxBJBMTCzKoQABJIdDo+XWCxBA9IwJIHqWbJh1LfHEczwC3/15v9y64BHZcpMZ8pXj9h1PiczHEEAyU7EwZwIEkJwNjHYnR4AAoudMANGzZMOsa4knnuMR+PIV98rg0r/Jq4ubyUnv3m08JTIfQwDJTMXCnAkQQHI2MNqdHAECiJ4zAUTPkg2zriWeeDYr4JyTE8+7VVY9OyyH7LOdvOeNxWZLNLWeANIUF4tzJEAAydGwaHXyBAggetYEED1LNsy6lnji2azAX5Y/I6df+LuRw449bCfZd+etmi3R1HoCSFNcLM6RAAEkR8Oi1ckTIIDoWRNA9CzZMOta4olnswL1d8D6wsf2ljlbtO4OWOu7PrfYYjZ7t2YHx/rgBLiIgxsJDYUgQADRmwIBRM+SDbOuJZ54Nitw3e1L5Ee3PCCFyMhFp71BugqtuwMWAaTZ6bA+TwIEkDxNi14nTYAAokdNANGzZMOsa4knns0KXPyT++Su/sdlzuY98oWj92728KbX8xaspsk4ICcCBJCcDIo2J1eAAKLnTQDRs2TDrGuJJ57NCvzL/71Tlj25UvbdeUs59rCdmz286fUEkKbJOCAnAgSQnAyKNidXgACi500A0bNkw6xriSeezQisHa7Kx8/5jaTOyXveOE8O2Wf7Zg4f11oCyLjYOCgHAgSQHAyJFidfgACiZ04A0bNkw6xriSeezQg8+OgKOevSu0cO+eR7XyW77viKZg4f11oCyLjYOCgHAk0EEL/U5eCUaBGBiQsQQCZuOFqBAKJnyYZZ1xJPPJsR+O3CR+Q71/WPHPLxd+0iL5s1vZnDx7V25kZd8ur5W8lf/7pKhofTkRrcBWtclBwUmEATASSwzmlnkgU6K4BOfgBpX18CiO6PKp546groVmvn6/Oqmwblhjsf0gXLUO0d++8o737DjgSQDFYsyY8AAWRCs2rfTeOEWNrg4MkPIG2Atp5TaOcNyVRMDU9ddTzxzCpw0x8elu/dmGRdrraud/tN5MwP7UEAUROlUAgCBJAQpkAPwQkQQPRGwgZPz9JXwhNPXQHdau18fTrn5PGnV8sza6q6aOupdvXNg7JoydNCAJkUbp5kkgUIIJMMztPlQ4AAojendt6Q6Cllr4RndqssK/HMopR9DZ7ZrRqtvOia++TugccJII2g+PtcChBAcjk2mm61AAFET5gNiZ4lr4DoWuKJp76AXkUCiJ4llcITIICENxM6CkCAAKI3BAKIniUbZl1LPPHUF9CrSADRs6RSeAIEkPBm0oEdhfdhfgKI3mVIANGzZMOsa4knnvoCehUJIHqWVApPgAAS3kzoKAABAojeEAggepZsmHUt8cRTX0CvIgFEz5JK4QkQQMKbCR0FIEAA0RsCAUTPkg2zriWeeOoL6FUkgOhZUik8AQJIeDOhowAECCB6QyCA6FmyYda1xBNPfQG9igQQPUsqhSdAAAlvJlPYUXifxZgqDAKInjwBRM+SDbOuJZ546gvoVSSA6FlSKTwBAkh4M6GjAAQIIHpDIIDoWbJh1rXEE099Ab2KBBA9SyqFJ0AACW8mdBSAAAFEbwgEED1LNsy6lvnwzNcr0/y8612jBBA9SyqFJ0AACW8mdBSAAAFEbwhsSPQs87Fh1j3fVlfj+tQVxlPPkwCiZ0ml8AQIIOHNhI4CECCA6A2BDYmeJQFE1xJPPPUF9CoSQPQsqRSeAAEkvJnQUQACBBC9IRBA9CzZMOta4omnvoBeRQKIniWVwhMggIQ3EzoKQIAAojcEAoieJRtmXUs88dQX0KtIANGznLxK+frM1uS5vPSZCCBTqc9zBytAANEbDQFEz5INs64lnnjqC+hVJIDoWVIpPAECSHgzoaMABAggekMggOhZsmHWtcQTT30BvYoEED1LKoUnQAAJbyZ0FIAAAURvCAQQPUs2zLqWeOKpL6BXkQCiZ0ml8AQIIOHNhI4CECCA6A2BAKJnyYZZ1xJPPPUF9CoSQPQsqRSeAAEkvJnQUQACBBC9IRBA9CzXv2Hmg4/jVeb6HK/c2MfhqedJANGzpFJ4AgSQ8GZCRwEIEED0hsCGRM+S39jrWuKJp76AXkUCiJ4llcITIICENxM6CkCAAKI3BAKIniUbZl1LPPHUF9CrSADRs6RSeAIEkPBmQkcBCBBA9IZAANGzZMOsa4knnvoCehUJIHqWVApPgAAS3kzoKAABAojeEAggepZsmHUt8cRTX0CvIgFEz5JK4QkQQMKbCR0FIEAA0RsCAUTPkg2zriWeeOoL6FUkgOhZUik8AQJIeDOhowAECCB6QyCA6FmyYda1xBNPfQG9igQQPUsqhSdAAAlvJnQUgAABRG8IBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjgIQIIDoDYEAomfJhlnXEk889QX0KhJA9CypFJ4AASS8mdBRAAIEEL0hEED0LNkw61riiae+gF5FAoieJZXCEyCAhDcTOgpAgACiNwQCiJ4lG2ZdSzzx1BfQq0gA0bOkUngCBJDwZkJHAQgQQPSGQADRs2TDrGuJJ576AnoVCSB6lvmr5LfnLn9tN9ExAaQJLJZ2jgABRG/WBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjgIQIIDoDYEAomfJhlnXEk889QX0KhJA9CypFJ4AASS8mdBRAAIEEL0hEED0LNkw61riiae+gF5FAoieJZXCEyCAhDcTOgpAgACiNwQCiJ4lG2Zdy/b1nLr3j/PzrneNEkD0LKkUngABJLyZ0FEAAgQQvSGwIdGzbN8Ns65RM9W4PpvRarwWz8ZGWVcQQLJKsS6PAgSQPE6NnlsuQADRI2ZDomdJANG1xBNPfQG9igQQPUsqhSdAAJmUmUzdy+GTcnpt+CQEEL2hEkD0LNkw61riGaIn/16OToUAon99UjEcAQJIOLOgk4AECCB6wyCA6FmyYda1xBNPfQG9igQQPUsqhSdAAAlvJnQUgAABRG8IBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjgIQIIDoDYEAomfJhlnXEk889QX0KhJA9CypFJ4AASS8mdBRAAIEEL0hEED0LNkw61riiae+gF5FAoieJZXCEyCAhDcTOgpAgACiNwQCiJ4lG2ZdSzzx1BfQq0gA0bOkUngCBJDwZkJHAQgQQPSGQADRs2TDrGuJJ576AnoVCSB6llQKT4AAEt5M6CgAAQKI3hAIIHqWbJh1LfHEU19AryIBRM+SSuEJEEDCmwkdBSBAANEbAgFEz5INs64lnnjqC+hVJIDoWVIpPAECSHgzoaMABAggekMggOhZsmHWtcQTT30BvYoEED1LKoUnQAAJbyZ0tB6B+fPnb1+tVi8UkdcaY4bSNL2yUql8WkTSdQ8plUrHG2M+KSLbisigMeZzSZL8JCsuASSrVON1BJDGRs2swLMZrcZr8Wxs1MwKPJvR2vBaAoieJZXCEyCAhDcTOlqPQLlcvtc5d+/w8PAZ3d3dWwwPD19njLnYWntu/SGlUulIY8x3jDGH9vT03DU0NPRh59yFzrn5lUrlgSzABJAsStnWsCHJ5pR1FZ5ZpbKtwzObU9ZVeGaVaryOANLYiBX5FSCA5Hd2HdV5uVze0zl3R3d39+YLFy582p987VWOU6y1vfUY5XL5gyKycZIkF43+eRzHTzrnTqpUKv+dBY4AkkUp2xo2JNmcsq7CM6tUtnV4ZnPKugrPrFKN1xFAGhuxIr8CBJD8zq6jOi+VSscZY86w1hbrQsXeInKnMWZ2kiQr1gcyd+7cl0+fPv2xNE3fMjg4eEsWOAJIFqVsa9iQZHPKugrPrFLZ1uGZzSnrKjyzSjVeRwBpbMSK/AoQQPI7u47qPI7jM0XkcGvtXqMnPm/evGKhUKgYY3ZMkmTxekBMqVS6yhizpbX2gKxoPoAsX75aqtWXfLwkawnW1QQKhUhmz54heOpcEnjqOI5WwRNPXQG9auf/70K5q+8x6d1+E/nXf9jr+X+PNt20h72bHjOVpkiAi3iK4Hna5gR8AHHOHVGpVPbMGkD22GOPaUNDQ5c653Zfu3btGxcvXvxY1mf1ASTrWtYhgAACCCCgLfDvl98tt/1p2UgA+Y+TXvj9mTGGvZs2dsfV85fQ1G5zuIg77qLL5wnHcXysiJxprd1h9AxKpdI+xpjbu7q6Zvf19Q3Vn9mcOXNmzJw509/1amYURe8cGBh4qpkz5xWQZrQ2vJbfMOtZ+kp44qkroFuN61PPk1dA9CypFJ4AASS8mdDRGALFYnH3KIruERH/Vqon/ZI4jk8QkeOttbusc4h/29U1xpiuNWvWHLlkyZJnmkXlMyDNiq1/Pe8J17P0lfDEU1dAtxrXp54nnwHRs6RSeAIEkPBmkqGjqX/pLEOT6kviOL5DRO5L0/TUKIq2EZGfi8g51toL4jgeEJFjrLW3lcvlo5xzZw0NDe22bNmyVeNphAAyHrWxj2FDomdJANG1xBNPfQG9igQQPUsqhSdAAAlvJnS0HoFisTgniqJLRORAEVkuIv47QM7yb2SM49gZYw5JkuSGOI5/JSJvEJHhdUp9z1rr38rV8EEAaUiUeQEBJDNVpoV4ZmLKvAjPzFSZFuKZiSnTIgJIJiYW5VSAAJLTwdF2awUIIHq+bEj0LH0lPPHUFdCt1p7X59S864AAonttUi0sAQJIWPOgm0AECCB6g2jPDYmeT7OV8GxWbMPr8cRTV0CvGgFEz5JK4QkQQMKbCR0FIEAA0RsCGzw9S14B0bXEE099Ab2KBBA9SyqFJ0AACW8mdBSAAAFEbwgEED1LNsy6lnjiqS+gV5EAomdJpfAECCDhzYSOAhAggOgNgQCiZ8mGWdcSTzz1BfQqEkD0LKkUngABJLyZ0FEAAgQQvSEQQPQs2TDrWuKJp76AXsX2CSBT8yF+vUlQqRUCBJBWqFIz9wIEEL0REkD0LNkw61riiae+gF7F9gkgeiZUah8BAkj7zJIzURQggOhhEkD0LNkw61riiae+gF5FAoieJZXCEyCAhDcTOgpAgACiNwQCiJ4lG2ZdSzzx1BfQq0gA0bOkUngCBJDwZofx9C0AACAASURBVEJHAQgQQPSGQADRs2TDrGuJJ576AnoVCSB6llQKT4AAEt5M6CgAAQKI3hAIIHqWbJh1LfHEU19AryIBRM+SSuEJEEDCmwkdBSBAANEbAgFEz5INs64lnnjqC+hVJIDoWVIpPAECSHgzoaMABAggekMggOhZsmHWtcQTT30BvYoEkGYsudVvM1ohrCWAhDAFeghOgACiNxICiJ4lG2ZdSzzx1BfQq0gA0bOkUngCBJDwZkJHAQgQQPSGQADRs2TDrGuJJ576AnoVOyOA8MqF3hWTr0oEkHzNi24nSYAAogdNANGzZMOsa4knnvoCehU7I4DoeVEpXwIEkHzNi24nSYAAogdNANGzZMOsa4knnvoCehUJIHqWVApPgAAS3kzoKAABAojeEAggepZsmHUt8cRTX0CvIgFEz5JK4QkQQMKbCR2NKTC57xMlgOhdhgSQZiwbX+d4NuPZeC2ejY2aWYFnM1obXksA0bOkUngCBJDwZkJHAQgQQPSGwIZEz5Lf2Ota4omnvoBeRQKIniWVwhMggIQ3EzoKQIAAojcEAoie5dRsmBu/KqN7hpNbjetT1xtPPU8CiJ4llcITIICENxM6CkCAAKI3BDYkepZTE0B0+w+tGten7kTw1PMkgOhZUik8AQJIeDOhowAECCB6Q2BDomdJANG1xBNPfQG9igQQPUsqhSdAAAlvJnQUgAABRG8IBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjtQExv/edQKI2hCEAKJnyYZZ1xJPPPUF9CoSQPQsqRSeAAEkvJnQUQACBBC9IRBA9CzZMOta4omnvoBeRQKIniWVwhMggIQ3EzoKQIAAojcEAoieJRtmXUs88dQX0KtIANGzpFJ4AgSQ8GZCRwEIEED0hkAA0bNkw6xriSee+gJ6FQkgepZUCk+AABLeTOgoAAECiN4QCCB6lmyYdS3xxFNfQK8iAUTPkkrhCRBAwpsJHQUgQADRGwIBRM+SDbOuJZ546gvoVSSA6FlSKTwBAkh4M6GjAAQIIHpDyGcAGf8d1PTkxq6UT89Wq4y/Pp7jtxvrSDz1PAkgepZUCk+AABLeTOgoAAECiN4Q2JDoWfIbe11LPPHUF9CrSADRs6RSeAIEkPBmQkcBCBBA9IZAANGzZMOsa4knnvoCehUJIHqWVApPgAAS3kzoKAABAojeEAggepZsmHUt8cRTX0CvIgFEz5JK4QkQQMKbCR0FIEAA0RsCAUTPkg2zriWeeOoL6FUkgOhZUik8AQJIeDOhowAECCB6QyCA6FmyYda1xBNPfQG9igQQPUsqhSdAAAlvJnQUgAABRG8IBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjgIQIIDoDYEAomfJhlnXEk889QX0KhJA9CypFJ4AASS8mdBRAAIEEL0hEED0LNkw61riiae+gF5FAoieJZXCEyCAhDcTOgpAgACiNwQCiJ4lG2ZdSzzx1BfQq0gA0bOkUngCBJDwZkJHAQgQQPSGQADRs2TDrGuJJ576AnoVCSB6llQKT4AAEt5M6CgAAQKI3hAIIHqWbJh1LfHEU19AryIBRM+SSuEJEEDCm0kOOvKXjctBn+NvkQAyfrt1jySA6FmyYda1xBNPfQG9igQQPUsqhSdAAAlvJnQUgAABRG8IBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjgIQIIDoDYEAomfJhlnXEk889QX0KhJA9CypFJ4AASS8mdBRAAIEEL0hEED0LNkw61rimQfP9n/L7/qmQADRvz6pGI4AASScWdBJQAL5DSDh/WNNANG9sPHEU1dAtxrXp54nAUTPkkrhCRBAwpsJHQUgkN8AEgDeOi2wIdGdCZ546groVuP61PMkgOhZUik8AQJIeDOhowAECCB6Q2BDomfpK+GJp66AbjWuTz1PAoieJZXCEyCAhDcTOgpAgACiNwQ2JHqWBBBdSzzx1BfQq0gA0bOkUngCBJDwZkJHAQgQQPSGQADRs2TDrGuJJ576AnoVCSB6llQKT4AAEt5M6CgAAQKI3hAIIHqWbJh1LfHEU19AryIBRM+SSuEJEEDCm0mDjsK7y1HuCDM0TADJgJRxCQEkI1TGZXhmhMq4DM+MUBmX4ZkRKsMyAkgGJJbkVoAAktvR0XgrBQggerpsSPQs+Y29riWeeOoL6FUkgOhZUik8AQJIeDOhowAECCB6QyCA6FmyYda1xBNPfQG9igQQPUsqhSdAAAlvJnQUgAABRG8IBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjgIQIIDoDYEAome54Q0znw8bjzTX53jU1n8MnnqeBBA9SyqFJ0AACW8mdBSAAAFEbwhsSPQs+Y29riWeeOoL6FUkgOhZUik8AQJIeDOhowAECCB6QyCA6FmyYda1xBNPfQG9igQQPUsqhSfQQQGEtyeEd/mF2xEBRG82BBA9SzbME7V86b8DXJ8TNX3x8XjqeRJA9CypFJ5ABwWQ8PDpKFwBAojebNiQ6FkSQHQt8cRTX0CvIgFEz5JK4QkQQMKbCR0FIEAA0RsCAUTPkg2zriWeeOoL6FUkgOhZUik8AQJIeDOhowAECCB6QyCA6FmyYda1xBNPfQG9igQQPUsqhSdAAAlvJnQUgAABRG8IBBA9SzbMupZ44qkvoFeRAKJnSaXwBAgg4c2EjgIQIIDoDYEAomfJhlnXEk889QX0KhJA9CypFJ4AASS8mdBRAAIEEL27xhFAdC9oPPHUFdCtxvWp50kA0bOkUngCBJDwZkJHAQgQQPSGwIZEz5Lf2Ota4omnvoBeRQKIniWVwhMggIQ3EzoKQIAAojcEAoieJRtmXUs88dQX0KtIANGzpFJ4AgSQ8GZCRwEIEED0hkAA0bNkw6xriSee+gJ6FQkgepZUCk+AABLeTOgoAAECiN4QCCB6lmyYdS3xxFNfQK8iAUTPkkrhCRBAwpsJHQUgQADRGwIBRM+SDbOuJZ546gvoVSSA6FlSKTwBAkh4M6GjAAQIIHpDIIDoWbJh1rXEE099Ab2KBBA9SyqFJ0AACW8mdBSAAAFEbwgEED1LNsy6lnjiqS+gV5EAomdJpfAECCDhzYSOAhAggOgNgQCiZ8mGWdcSz/F6rv97gvh5H6/pS48jgOhZUik8AQJIeDOho/UIzJ8/f/tqtXqhiLzWGDOUpumVlUrl0yKSrntIqVQ6yRjzTyKytYgsiKLo5IGBgXuz4hJAsko1XseGpLFRMyumxlPviymbOdfJWDs1npNxZlPzHHjquY8vgLTvz6qeLJVCECCAhDAFesgkUC6X73XO3Ts8PHxGd3f3FsPDw9cZYy621p5bX6BYLB4WRdHlzrmDV69evWDWrFknOedO2WijjYoLFixYmeXJCCBZlLKtYUOSzSnrKjyzSmVbh2c2p6yr8Mwq1Xjd+AJI47qsQCAEAQJICFOgh4YC5XJ5T+fcHd3d3ZsvXLjwaX9AqVQ63hhzirW2t75AHMc/ExFrrT219udRHMdLReRUa+2VDZ9MRAggWZSyrWFDks0p6yo8s0plW4dnNqesq/DMKtV4HQGksVG+V3T2q1UEkHxfvR3TfalUOs4Yc4a1tjh60nEc7y0idxpjZidJsqLuzx/xa5MkuaLuz34uIv3W2tOyoBFAsihlW8OGJJtT1lV4ZpXKtg7PbE5ZV+GZVarxOgJIYyNW5FeAAJLf2XVU53Ecnykih1tr9xo98Xnz5hULhULFGLNjkiSL68LGGufc4ZVK5brRPyuVSlcYY6rW2o9kgfMBZPny1VKtvuTjJVkOZ02dQKEQyezZMwRPncsCTx3H0Sp44qkroFftOz/rk1v+uEx2jzeX0z+w+/P/Hm26aQ97Nz1mKk2RABfxFMHztM0J+ADinDuiUqnsmTGA+LX+rVgjj2YDSHPdsRoBBBBAAIHOfksN80egGQECSDNarJ0ygTiOjxWRM621O9SFin2MMbd3dXXN7uvrGxr98ziOH66tvazuz643xtyXJMkZU3YSPDECCCDQUgE2wC3lpTgCCKgJEEDUKCnUSoFisbh7FEX3iMiW1ton/XPFcXyCiBxvrd2l/rlLpdJPjDEPWmtPqv15IY7jZf62vEmSXN3KPqmNAAIIIIAAAgggsGEBAghXSG4E4ji+Q0TuS9P01CiKthER/8Hyc6y1F8RxPCAix1hrbyuXywc7565M0/TgVatWLejp6Tnd/92qVavKS5cuXZ2bE6ZRBBBAAAEEEECgDQUIIG041HY9pWKxOCeKoktE5EARWS4i/jtAzvJ3zY3j2BljDkmS5AZ//uVy+ePOOf8lhVuIyN2FQuHj/f3997WrDeeFAAIIIIAAAgjkRYAAkpdJ0ScCCCCAAAIIIIAAAm0gQABpgyFyCgggELoAHw4OfUL0hwACCCAweQIEkMmz5pkQQAABBBBAAAEEEOh4AQJIx18CACCAAAIIIIAAAgggMHkCBJDJs+aZEEAAAQQQQAABBBDoeAECSMdfAp0JMH/+/O2r1eqFIvJaY8xQmqZXVioVf9esdF2RUql0kv8OERHZWkQWRFF08sDAwL2dKTf2WTfpebwx5pMisq2IDBpjPpckyU/wfEGgGc/Ro+I49p7+dtT+1tSfx3N8nnEc9xpjLnbO7S0iT4nIudbar+E5Ls8ojuPPichHRGQzEXlARL5krf0Bni8I9Pb2vjVN08tF5CZr7fs3YOM9zxaRD4jIJs65O0XkE5VKxbvyQCBXAgSQXI2LZrUEyuXyvc65e4eHh8/o7u7eYnh4+Dq/6bDWnlv/HMVi8bAoii53zh28evXqBbNmzTrJOXfKRhttVFywYMFKrX7yXierZ6lUOtIY8x1jzKE9PT13DQ0Nfdg5d6Fzbj7/iL5wFWT1rL9u4jj+kYi8SUTOI4C8+Ccqq+ecOXNmzJo1ayBN0/NXrlx5QU9Pz84i8l0Rebe11oc7Hs/d5jzTfz/jOP6EiHzGGHNQkiSDpVLpEGPMj40xeyRJsgDMEct/ds4dLSJPiMjSDQWQUql0ojHmVOfc26IoWuqc+7KIHGCtfbW/HT2eCORJgACSp2nRq4pAuVze0zl3R3d39+YLFy582hctlUr+t/KnWGt719nU/UxErLX21Nqf+99ALRWRU621V6o0lPMizXiWy+UPisjGSZJcNHracRw/6Zw7qVKp/HfOKVTab8azzvBt/pUPH6qNMYMEkBeFuWZ+3v1v6k+z1u6mMsw2LNLM9VkqlfwvG3qste+ru1YfNcacniTJFW3I0/Qp+VfYq9XqZV1dXV8XkY02FEDiOL7POXdJpVL5hn+icrm8sXPuL2ma7j84OOi/qJcHArkRIIDkZlQ0qiVQKpWOM8acYa0t1v2j6N9ucacxZnaSJCvq/vwRv7b+H8s4jv03sPdba0/T6inPdZrxXPc8586d+/Lp06c/lqbpWwYHB2/Js4NW7816+t/az5w5c5Ex5mjnnN9ALyGAvDCNZjzjOP62MWamiDzrnDtCRPxm+ewkSb6vNd+812nGs1QqHWGMucg599Zp06b1VavVg51zV1Sr1Z3vv//+P+fdQrP/OI4v3VAAqf2c+1fd/Sset9X9G9XnnLuoUql8U7MfaiHQagECSKuFqR+cQBzHZ4rI4dbavUabmzdvXrFQKFSMMTsmSbK47j/ua5xzh1cqletG/6xUKl1hjKlaa/1mr+MfzXiug2VKpdJVxpgtrbUHdDxkDaBZzziOv2KM2S5JkqNqmxgCSN3F1IxnHMfXG2MOSNP02JUrV17T09PzHhH5rzRN9xwcHPwD16hIM57eq1QqfcEY86/+/zfGrErT9MOVSsW/XZDHi6/TDQaQcrm8jXPu4TRNdxkcHFxU92+UDyO/stb6z9rwQCA3AgSQ3IyKRrUE/D+g/reblUplz4wBxK/1b8UaeRBAXjyJZjxHj9xjjz2mDQ0NXeqc233t2rVvXLx48WNa8817nWY8i8XiTlEU3dLV1bVrX1/fowSQl06/Gc9SqXSDfwWkPhDHcXx77cPB/hcXHf9oxjOO4w8ZY77onHv3mjVrFk6bNu1Nxhj/Vss3W2vv7njMcQSQQqGwa39//30EEK6evAsQQPI+QfpvWiCO42NF5Exr7Q51oWIfY8ztXV1ds/v6+obq/uP+cG3tZXV/5n9Lel+SJGc0/eRteEAznv70a28l8He9mhlF0TsHBgb8nYZ41ASa8DRxHN8sIldZay/whxNAxgwgzfy8X2qM2TRJknfU/bz/jzFmdZIkH+MiHbnGmvG8S0Susdb6D0uPPOI4/rGI/NlaexKeLwg0egvW3LlzN5o+ffrKNE0Pqn+7ahzH/SJy/uh/AzBFIC8CBJC8TIo+1QSKxeLuURTdIyL+rT9P1v5RPEFEjrfW7lL/RKVS6SfGmAfr/rEsxHG8zN+WN0mSq9WaynGhZjz9uzBKpdI1xpiuNWvWHLlkyZJncnzqLWk9q2ftVr1LareKHe2lp3Yr6QFr7Wta0uCkFvX/RE3s5j5ZPf1p1e5I9InaLydGnrj2CsgN1tqzJvXUA32yJj397cqvSZLE3zp2NID4z9D5GyUQQOpm3CiA1K7FP4nIZaN3a6x9hu4JY8y+SZL4f9N4IJAbAQJIbkZFo5oCcRz7O4bcl6bpqVEUbSMi/h9F//0JF8Rx7G+3eYz/oF+5XPYfmrwyTdODV61ataCnp+d0/3erVq0qL126dLVmT3mu1YTnUc65s4aGhnZbtmzZqjyfcyt7z+h5e7FY9N9N8/wjiiJ/G+mlXV1dX/VvyWplj3mqndHT/7z799lb59xXVq9efe6MGTPeZYy5LE3T+YODg/fn6Zxb2WtWT/8dIMYY/8rRYVtvvXXf0qVLD4qi6FpjzCFJkvy6lT3mrfZYAaT23T6/qnkt9ndrjKLo0/5D/caYh51z/ykiu1tr/U1UeCCQKwECSK7GRbNaAsVicU4URZeIyIEislxE/HeA+N9wujiOXe0/+Df45yuXyx93zvkvKdxCRO4uFAofr38PrlZPea6T1TOO41+JyBtEZHid8/2etda/tYOHiGT1XBeLt2CNffk041ksFt8QRZG/JWqvc+4hY8zJ1trruTBfEMjqWfus12edc0fV/vvpX7H7qrXWf+kej+deYRt9FXhaDWSt/7/W2o16e3vnpmnqb4oyv/Y9NP5tl/5LRo/3tzP3n01K0/S4wcFBf2t4HgjkSoAAkqtx0SwCCCCAAAIIIIAAAvkWIIDke350jwACCCCAAAIIIIBArgQIILkaF80igAACCCAwlsDEP7CPKwIIIDBZAgSQyZLmeRBAAAEEEEAAAQQQQEAIIOu9CPhtUvv/fDDj9p8xZ4gAAggggAACoQkQQEKbCP0ggAACCCCAAAIIINDGAgSQNh4up4YAAggggAACCCCAQGgCBJDQJkI/CCCAAAIIIIAAAgi0sQABpI2Hy6khgAACCCCAAAIIIBCaAAEktInQDwIIINCGArVvaf+Ic+6jlUrl0mZPsfYN0J8TkbOstf7boHkggAACCORUgACS08HRNgIIdK5Ab2/v3DRNF69HYFhEnnTO3RVF0UVJktwQglS5XD44TdNdnHPXDw4OLmq2p97e3tdVq9XXFQqF3w0MDPyu2eNZjwACCCAQjgABJJxZ0AkCCCCQSWA0gBhjVqVp6l8VeP4RRdHLRGS+c+6dItLlnPv3SqXyqUyFWYQAAggggMAkCBBAJgGZp0AAAQQ0BepeAXnKWrvZWLVLpdKroyj6rXNupojsY629S7MHaiGAAAIIIDBeAQLIeOU4DgEEEJgigSwBxLcWx/E3RORE59xXK5XK/6n7HMZhxpjd/N+JyJ+ttXuPnkq5XN4zTdP/Y4zZX0Q2FZG/iMhvReTfxwoxu+666ybPPvvsZ0TkXSIyR0RWisivROSz1tqB0brr+wxIHMcfEpFjRMT30yMiTzjnFjjnLhgcHLy27nj/uY+XfAZkp512mj48PHyCc+7vjTFlEZkmIsuMMTeuXbv2Kw888MBDozV6e3sPTNP0JmPMj9auXXt0V1fXl0TEv1K0hYg8Zoz5QbVa/ZfBwcFnp2i0PC0CCCDQEQIEkI4YMyeJAALtJNBEAPmEiFwgIv9jrf37uhBwkTHm7SLyXefcI5VK5WLvUyqVjjDGXCkia4wxVznnlojIPBF5X+3tXO+tVCr/O2pZLBY3j6LobhF5pYj8wDm3yBizg4h8UEScc+7ASqVyZy0M+Q+ev+hD6HEc+7eGfUVE/PP4uk855+YYY470ocA5d3ylUvlW7fiXBJADDzywa9myZTeKyEEi0u+c+4WILDfG7CEib/NhJoqi/QYGBqyvURdArnXObW2MWZum6c9F5BXGmH8QkZcbY76RJMnJ7XS9cC4IIIBAaAIEkNAmQj8IIIBAA4GsAaRUKn3BGPOvInK+tfbE0QAiIn+LoujVAwMDfuM/8qi9kuH/dyGKon0HBgYW1gWN10RRdIeIrEjTdIfBwcHl/u/K5fLVzrkjnXPHVSqVS0bXx3HsN//XichCa61/ZcO/GjNWAFnmX2WZNm3aNosWLfKvtIw85s+fv3W1Wu0TkcXW2tesL4CUy+WTnXPnicitXV1db+7r61tT18OZIvIl59yNlUrl4PoAIiJVEfm+tfajIpLW6vtXgXxY+qu11r/y47gQEUAAAQRaI0AAaY0rVRFAAIGWCWQJIMVisdsYs9AYU3LOvb1SqVxXF0Cut9b6kPD8I47jf/JBxTn39Uqlcsq6zcdxfLmIfMgY88EkSb6/8847b7p27donaht2/xYmv6l//lEul892zq1es2bNuUuWLHlmPQFktT8gTdMtR0PNaAH/6sbNN9/s7+g18hjrNrxxHP9BRF5tjHlTkiS/rn/+uXPnbjR9+vQnRWSGiGxprX1y9BUQHy66urq26evre3Qdg7+KyMuq1eqW999//+MtGyCFEUAAgQ4XCCSA+Db4ZVOHX4ucPgIIZBSoCyBPR1E08grB6MMY0zM8PFw2xvyziPjf6vuwcaj/j+xoCDDGfClJkn9ZZ/P9Pf/WKefcGYVC4ep1W0nT9MP+OzhGA0qpVPo7Y8wvjDG3JElyYKPWxwogpVLph8aYd4tInzHmnCiKru/v739krFrrBhAfsKIo8p83iVatWjVr6dKlI2Gm/lEul3/nnNvXOfd3lUrl/9UFEP+5l+3GWP+gc267QqEwt7+//8FG58TfI4AAAgiMTyCQADK+5jkKAQQQ6ESBBt8DMkqy0hhzYbVa/dfRD1XXBZBPJkni37r0/KNcLt/onHtLBs8fWGvfXy6Xj3LOXSEi11hrD2903FgBZJtttpk5a9asS4wxH/BBolbDf3D9ukKh8K3+/v7KaN11A0jtbVr+LVzLrbX+1sMveZRKpZ8YY94hIh+w1l45GkCcc/dWKpU91z0gjmP/FrTtoyjaof7taY3Ojb9HAAEEEGhOgADSnBerEUAAgSkXqAsgK0TEvzLx/MM5N+yc8289+sO6d3OqewvWidba8+uPK5VKNxhj3mqM+Q/n3Ia+6G+ZvxtWqVT6gDHmv2uvsLzo7VxjAW3om9Dnz5+/fbVaPUxE3ioi/tUUfzcs//arY6y1l/l66waQnXbaaavh4WH/askKa+3s9Tynv4uW/7D9+621PyCATPmlSwMIIIDAiAABhAsBAQQQyJlAls+AbCgE+NvvrhtA6gLCSZVK5ZuNSMrl8kHOOX+73XustXs1Wr+hAFJ/7Jw5c2bMnDnTfzj8a8aY4Wq1urX/fMgYAcTffte/BaswNDTUs2zZslXr9hDHsf/g/D7GmIOSJLmJANJoSvw9AgggMDkCBJDJceZZEEAAATWBVgSQUql0vDHG35732iRJ/NuWXvTwrziIyFBfX9+Q/4vah9Af858t6e7u3nLhwoVP1x8Qx7G//e+21Wr1H/0HuscKIPPmzXvltGnTVg0MDDw1Rnjwt+X1b+3a21p791gfQi+Xy/c6517j3zpWqVR+WV9jp5128p+F8R8kn7ZmzZrNlyxZ8lcCiNolSCEEEEBgQgKBBZBO+zB6p53vhK5VDkYAgZpAKwJILVD4z0D0pGn6xsHBwVtGwcvl8sbOOX+Xqd38FxgmSZL4vxu9Da8x5otJkvjb/Y48ent7X5emqf/ywsRa2+v/bN0AUi6X3+Gc+4lz7upKpeK/Z2Tkdrj+UbuD1R/9YcaYOUmSLFtPAPm4c+5C/0WJXV1dB9XfhrdcLn/ROee/IPEqa62v//z3gPAZEH6UEEAAgakVCCyATC0Gz44AAgjkQaAVAaQWKN7rnPt+7baE/gsJB4wxWzrn/J2qthGRc621p40a7bjjjtt1dXX5oDHHOfdTEbnLGLO9McZ/QL2rdvvfkVcmxngFpBDH8Q0i8mbn3H1RFN3gnPPfBfKK2uc2/LeaX2it9bcHHvM2vP6D63Ec/0xEDhmtISLPOuf28XX994gUCoXXj95Zi1dA8nB10yMCCHSCAAGkE6bMOSKAQFsJ6AWQl74KG8ex/zzHGSKyv4hsJiL+blp/TNP0kkql4j90/qLHvHnztigUCp+thYat/du0ROSWNE3PHhwc9N/TMfIY6y1Ye+yxx7QVK1acUPumdf+N6y/3Hyp3zv1JRC6rVCr+A+gj92gf6xUQ/+e1Gif60ONf5HDOFfw3q/tXVwqFwlfr395FAGmrHwNOBgEEcixAAMnx8GgdAQQQQAABBBBAAIG8CRBA8jYx+kUAAQQQQAABBBBAIMcCBJAcD4/WEUAAAQQQQAABBBDImwABJG8To18EEEAAAQSmTIC7N04ZPU+MwIhAe/wMEkC4nBFAAAEEEEAAAQQ6XKA9NvZ5GSIBJC+Tok8EEEAAAQQQQAABBNpAgACiMkRSswojRRBAAAEEEEAAAQTaXoAA0vYj5gQRQAABBBBAAAEEEAhHgAASzizoBAEEEEAA0X9j/QAAAIZJREFUAQQQQACBthcggLT9iDlBBBBAAAEEEEAAAQTCESCAhDMLOkEAAQQQQAABBBBAoO0FCCBtP2JOEAEEEEAAAQQQQACBcAQIIOHMgk4QQAABBBBAAAEEEGh7AQJI24+YE0QAAQQQQAABBBBAIBwBAkg4s6ATBBBAAAEEEEAAAQTaXuD/A4f+SJmLioD+AAAAAElFTkSuQmCC\" 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": [
    "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": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}