PCA and feature extraction from images .ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ANS=62.93%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.9440559440559441\n"
     ]
    }
   ],
   "source": [
    "from sklearn.datasets import load_breast_cancer\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "cancer = load_breast_cancer()\n",
    "X_train, X_test, y_train, y_test = train_test_split(cancer.data, cancer.target,\n",
    "random_state=0)\n",
    "svm = SVC(C=100)\n",
    "svm.fit(X_train, y_train)\n",
    "print(svm.score(X_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1.799e+01, 1.038e+01, 1.228e+02, ..., 2.654e-01, 4.601e-01,\n",
       "        1.189e-01],\n",
       "       [2.057e+01, 1.777e+01, 1.329e+02, ..., 1.860e-01, 2.750e-01,\n",
       "        8.902e-02],\n",
       "       [1.969e+01, 2.125e+01, 1.300e+02, ..., 2.430e-01, 3.613e-01,\n",
       "        8.758e-02],\n",
       "       ...,\n",
       "       [1.660e+01, 2.808e+01, 1.083e+02, ..., 1.418e-01, 2.218e-01,\n",
       "        7.820e-02],\n",
       "       [2.060e+01, 2.933e+01, 1.401e+02, ..., 2.650e-01, 4.087e-01,\n",
       "        1.240e-01],\n",
       "       [7.760e+00, 2.454e+01, 4.792e+01, ..., 0.000e+00, 2.871e-01,\n",
       "        7.039e-02]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cancer.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 96.50 - SCALED THE DATA TO BRING THE ENTIRE DATA IN  0-1 RANGE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.965034965034965"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# preprocessing using 0-1 scaling\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler()\n",
    "\n",
    "scaler.fit(X_train)\n",
    "X_train_scaled = scaler.transform(X_train)\n",
    "X_test_scaled = scaler.transform(X_test)\n",
    "# learning an SVM on the scaled training data\n",
    "\n",
    "svm.fit(X_train_scaled, y_train)\n",
    "# scoring on the scaled test set\n",
    "svm.score(X_test_scaled, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA USED IN FEATURE EXTRACTION IN IMAGES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, 'some_faces')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.datasets import fetch_lfw_people\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "people = fetch_lfw_people(min_faces_per_person=20, resize=0.7)\n",
    "image_shape = people.images[0].shape\n",
    "fix, axes = plt.subplots(2, 5, figsize=(15, 8), subplot_kw={'xticks': (), 'yticks': ()})\n",
    "\n",
    "for target, image, ax in zip(people.target, people.images, axes.ravel()):\n",
    "    ax.imshow(image)\n",
    "    ax.set_title(people.target_names[target])\n",
    "plt.suptitle(\"some_faces\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# There are 3023 images, each 87 x 65 pixels large, belonging to 62 different people"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3023, 87, 65)\n",
      "62\n"
     ]
    }
   ],
   "source": [
    "print(people.images.shape)\n",
    "print(len(people.target_names))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alejandro Toledo           39 Alvaro Uribe               35 Amelie Mauresmo            21 \n",
      "Andre Agassi               36 Angelina Jolie             20 Ariel Sharon               77 \n",
      "Arnold Schwarzenegger      42 Atal Bihari Vajpayee       24 Bill Clinton               29 \n",
      "Carlos Menem               21 Colin Powell              236 David Beckham              31 \n",
      "Donald Rumsfeld           121 George Robertson           22 George W Bush             530 \n",
      "Gerhard Schroeder         109 Gloria Macapagal Arroyo    44 Gray Davis                 26 \n",
      "Guillermo Coria            30 Hamid Karzai               22 Hans Blix                  39 \n",
      "Hugo Chavez                71 Igor Ivanov                20 Jack Straw                 28 \n",
      "Jacques Chirac             52 Jean Chretien              55 Jennifer Aniston           21 \n",
      "Jennifer Capriati          42 Jennifer Lopez             21 Jeremy Greenstock          24 \n",
      "Jiang Zemin                20 John Ashcroft              53 John Negroponte            31 \n",
      "Jose Maria Aznar           23 Juan Carlos Ferrero        28 Junichiro Koizumi          60 \n",
      "Kofi Annan                 32 Laura Bush                 41 Lindsay Davenport          22 \n",
      "Lleyton Hewitt             41 Luiz Inacio Lula da Silva  48 Mahmoud Abbas              29 \n",
      "Megawati Sukarnoputri      33 Michael Bloomberg          20 Naomi Watts                22 \n",
      "Nestor Kirchner            37 Paul Bremer                20 Pete Sampras               22 \n",
      "Recep Tayyip Erdogan       30 Ricardo Lagos              27 Roh Moo-hyun               32 \n",
      "Rudolph Giuliani           26 Saddam Hussein             23 Serena Williams            52 \n",
      "Silvio Berlusconi          33 Tiger Woods                23 Tom Daschle                25 \n",
      "Tom Ridge                  33 Tony Blair                144 Vicente Fox                32 \n",
      "Vladimir Putin             49 Winona Ryder               24 "
     ]
    }
   ],
   "source": [
    "# count how often each target appears\n",
    "import numpy as np\n",
    "counts = np.bincount(people.target)\n",
    "\n",
    "# print counts next to target names:\n",
    "\n",
    "for i, (count, name) in enumerate(zip(counts, people.target_names)):\n",
    "    print(\"{0:25} {1:3}\".format(name, count), end=' ')\n",
    "    if (i + 1) % 3 == 0:\n",
    "        print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#To make the data less skewed, we will only take up to 50 images of each person.\n",
    "#Otherwise the feature extraction would be overwhelmed by the likelihood of George\n",
    "#W Bush.\n",
    "\n",
    "mask = np.zeros(people.target.shape, dtype=np.bool)\n",
    "for target in np.unique(people.target):\n",
    "    mask[np.where(people.target == target)[0][:50]] = 1\n",
    "X_people = people.data[mask]\n",
    "y_people = people.target[mask]\n",
    "# scale the grey-scale values to be between 0 and 1\n",
    "# instead of 0 and 255 for better numeric stability:\n",
    "X_people = X_people / 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.23255813953488372"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "# split the data in training and test set\n",
    "X_train, X_test, y_train, y_test = train_test_split(\n",
    "X_people, y_people, stratify=y_people, random_state=0)\n",
    "# build a KNeighborsClassifier with using one neighbor:\n",
    "knn = KNeighborsClassifier(n_neighbors=1)\n",
    "knn.fit(X_train, y_train)\n",
    "knn.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1547, 100)\n"
     ]
    }
   ],
   "source": [
    "#ONLY USE FIRST 100 COMPONENTS\n",
    "\n",
    "from sklearn.decomposition import PCA\n",
    "pca = PCA(n_components=100, whiten=True).fit(X_train)\n",
    "X_train_pca = pca.transform(X_train)\n",
    "X_test_pca = pca.transform(X_test)\n",
    "\n",
    "print(X_train_pca.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.30426356589147285"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn = KNeighborsClassifier(n_neighbors=1)\n",
    "knn.fit(X_train_pca, y_train)\n",
    "knn.score(X_test_pca, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x864 with 15 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pca.components_.shape\n",
    "(100, 5655)\n",
    "fix, axes = plt.subplots(3, 5, figsize=(15, 12),\n",
    "subplot_kw={'xticks': (), 'yticks': ()})\n",
    "for i, (component, ax) in enumerate(zip(pca.components_, axes.ravel())):\n",
    "    ax.imshow(component.reshape(image_shape),cmap='viridis')\n",
    "    ax.set_title(\"%d. component\" % (i + 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\LILENDAR\\Anaconda3\\lib\\site-packages\\sklearn\\externals\\six.py:31: DeprecationWarning: The module is deprecated in version 0.21 and will be removed in version 0.23 since we've dropped support for Python 2.7. Please rely on the official version of six (https://pypi.org/project/six/).\n",
      "  \"(https://pypi.org/project/six/).\", DeprecationWarning)\n",
      "C:\\Users\\LILENDAR\\Anaconda3\\lib\\site-packages\\sklearn\\externals\\joblib\\__init__.py:15: DeprecationWarning: sklearn.externals.joblib is deprecated in 0.21 and will be removed in 0.23. Please import this functionality directly from joblib, which can be installed with: pip install joblib. If this warning is raised when loading pickled models, you may need to re-serialize those models with scikit-learn 0.21+.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "________________________________________________________________________________\n",
      "[Memory] Calling mglearn.plot_pca.pca_faces...\n",
      "pca_faces(array([[0.535948, ..., 0.243137],\n",
      "       ...,\n",
      "       [0.043137, ..., 0.596078]], dtype=float32), \n",
      "array([[0.237908, ..., 0.269281],\n",
      "       ...,\n",
      "       [0.4     , ..., 0.254902]], dtype=float32))\n",
      "________________________________________________________pca_faces - 5.7s, 0.1min\n",
      "Error in callback <function install_repl_displayhook.<locals>.post_execute at 0x000001F8577EDE18> (for post_execute):\n"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "Failed to process string with tex because latex could not be found",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36m_run_checked_subprocess\u001b[1;34m(self, command, tex)\u001b[0m\n\u001b[0;32m    303\u001b[0m                                              \u001b[0mcwd\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtexcache\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 304\u001b[1;33m                                              stderr=subprocess.STDOUT)\n\u001b[0m\u001b[0;32m    305\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mFileNotFoundError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36mcheck_output\u001b[1;34m(timeout, *popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    394\u001b[0m     return run(*popenargs, stdout=PIPE, timeout=timeout, check=True,\n\u001b[1;32m--> 395\u001b[1;33m                **kwargs).stdout\n\u001b[0m\u001b[0;32m    396\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    471\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 472\u001b[1;33m     \u001b[1;32mwith\u001b[0m \u001b[0mPopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mpopenargs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mprocess\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    473\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, encoding, errors, text)\u001b[0m\n\u001b[0;32m    774\u001b[0m                                 \u001b[0merrread\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrwrite\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 775\u001b[1;33m                                 restore_signals, start_new_session)\n\u001b[0m\u001b[0;32m    776\u001b[0m         \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36m_execute_child\u001b[1;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_start_new_session)\u001b[0m\n\u001b[0;32m   1177\u001b[0m                                          \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfspath\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcwd\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mcwd\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32melse\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1178\u001b[1;33m                                          startupinfo)\n\u001b[0m\u001b[0;32m   1179\u001b[0m             \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 2] The system cannot find the file specified",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\pyplot.py\u001b[0m in \u001b[0;36mpost_execute\u001b[1;34m()\u001b[0m\n\u001b[0;32m    107\u001b[0m             \u001b[1;32mdef\u001b[0m \u001b[0mpost_execute\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    108\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mis_interactive\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 109\u001b[1;33m                     \u001b[0mdraw_all\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    110\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    111\u001b[0m             \u001b[1;31m# IPython >= 2\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\_pylab_helpers.py\u001b[0m in \u001b[0;36mdraw_all\u001b[1;34m(cls, force)\u001b[0m\n\u001b[0;32m    126\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mf_mgr\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcls\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_all_fig_managers\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    127\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0mforce\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0mf_mgr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstale\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 128\u001b[1;33m                 \u001b[0mf_mgr\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw_idle\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    129\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    130\u001b[0m \u001b[0matexit\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mregister\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mGcf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdestroy_all\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\backend_bases.py\u001b[0m in \u001b[0;36mdraw_idle\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1905\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_is_idle_drawing\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1906\u001b[0m             \u001b[1;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_idle_draw_cntx\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1907\u001b[1;33m                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1908\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1909\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdraw_cursor\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mevent\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py\u001b[0m in \u001b[0;36mdraw\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    386\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcleared\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    387\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlock\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 388\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    389\u001b[0m             \u001b[1;31m# A GUI class may be need to update a window using this draw, so\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    390\u001b[0m             \u001b[1;31m# don't forget to call the superclass.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[1;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[0;32m     36\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     37\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 38\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0martist\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     39\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     40\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\figure.py\u001b[0m in \u001b[0;36mdraw\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m   1707\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpatch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1708\u001b[0m             mimage._draw_list_compositing_images(\n\u001b[1;32m-> 1709\u001b[1;33m                 renderer, self, artists, self.suppressComposite)\n\u001b[0m\u001b[0;32m   1710\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1711\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose_group\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'figure'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\image.py\u001b[0m in \u001b[0;36m_draw_list_compositing_images\u001b[1;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[0;32m    133\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mnot_composite\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhas_images\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    134\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[1;32min\u001b[0m \u001b[0martists\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 135\u001b[1;33m             \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    136\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    137\u001b[0m         \u001b[1;31m# Composite any adjacent images together\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[1;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[0;32m     36\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     37\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 38\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0martist\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     39\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     40\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36mdraw\u001b[1;34m(self, renderer, inframe)\u001b[0m\n\u001b[0;32m   2603\u001b[0m                 \u001b[0martists\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mspine\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2604\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2605\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_update_title_position\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2606\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2607\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0maxison\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0minframe\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36m_update_title_position\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m   2552\u001b[0m                     \u001b[1;31m# this happens for an empty bb\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2553\u001b[0m                     \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2554\u001b[1;33m             \u001b[1;32mif\u001b[0m \u001b[0mtitle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_window_extent\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mymin\u001b[0m \u001b[1;33m<\u001b[0m \u001b[0mtop\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2555\u001b[0m                 y = self.transAxes.inverted().transform(\n\u001b[0;32m   2556\u001b[0m                         (0., top))[1]\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\text.py\u001b[0m in \u001b[0;36mget_window_extent\u001b[1;34m(self, renderer, dpi)\u001b[0m\n\u001b[0;32m    888\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Cannot get window extent w/o renderer'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    889\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 890\u001b[1;33m         \u001b[0mbbox\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minfo\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdescent\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_layout\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_renderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    891\u001b[0m         \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_unitless_position\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    892\u001b[0m         \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_transform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtransform_point\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\text.py\u001b[0m in \u001b[0;36m_get_layout\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m    289\u001b[0m         _, lp_h, lp_d = renderer.get_text_width_height_descent(\n\u001b[0;32m    290\u001b[0m             \u001b[1;34m\"lp\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fontproperties\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 291\u001b[1;33m             ismath=\"TeX\" if self.get_usetex() else False)\n\u001b[0m\u001b[0;32m    292\u001b[0m         \u001b[0mmin_dy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mlp_h\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mlp_d\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_linespacing\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    293\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py\u001b[0m in \u001b[0;36mget_text_width_height_descent\u001b[1;34m(self, s, prop, ismath)\u001b[0m\n\u001b[0;32m    199\u001b[0m             \u001b[0mfontsize\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mprop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_size_in_points\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    200\u001b[0m             w, h, d = texmanager.get_text_width_height_descent(\n\u001b[1;32m--> 201\u001b[1;33m                 s, fontsize, renderer=self)\n\u001b[0m\u001b[0;32m    202\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mh\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0md\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    203\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36mget_text_width_height_descent\u001b[1;34m(self, tex, fontsize, renderer)\u001b[0m\n\u001b[0;32m    446\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    447\u001b[0m             \u001b[1;31m# use dviread. It sometimes returns a wrong descent.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 448\u001b[1;33m             \u001b[0mdvifile\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmake_dvi\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    449\u001b[0m             \u001b[1;32mwith\u001b[0m \u001b[0mdviread\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDvi\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdvifile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m72\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mdpi_fraction\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mdvi\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    450\u001b[0m                 \u001b[0mpage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdvi\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36mmake_dvi\u001b[1;34m(self, tex, fontsize)\u001b[0m\n\u001b[0;32m    336\u001b[0m                 self._run_checked_subprocess(\n\u001b[0;32m    337\u001b[0m                     [\"latex\", \"-interaction=nonstopmode\", \"--halt-on-error\",\n\u001b[1;32m--> 338\u001b[1;33m                      texfile], tex)\n\u001b[0m\u001b[0;32m    339\u001b[0m             \u001b[1;32mfor\u001b[0m \u001b[0mfname\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mglob\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mglob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbasefile\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m'*'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    340\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mfname\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mendswith\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'dvi'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'tex'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36m_run_checked_subprocess\u001b[1;34m(self, command, tex)\u001b[0m\n\u001b[0;32m    306\u001b[0m             raise RuntimeError(\n\u001b[0;32m    307\u001b[0m                 \u001b[1;34m'Failed to process string with tex because {} could not be '\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 308\u001b[1;33m                 'found'.format(command[0])) from exc\n\u001b[0m\u001b[0;32m    309\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0msubprocess\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mCalledProcessError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    310\u001b[0m             raise RuntimeError(\n",
      "\u001b[1;31mRuntimeError\u001b[0m: Failed to process string with tex because latex could not be found"
     ]
    },
    {
     "ename": "RuntimeError",
     "evalue": "Failed to process string with tex because latex could not be found",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36m_run_checked_subprocess\u001b[1;34m(self, command, tex)\u001b[0m\n\u001b[0;32m    303\u001b[0m                                              \u001b[0mcwd\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtexcache\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 304\u001b[1;33m                                              stderr=subprocess.STDOUT)\n\u001b[0m\u001b[0;32m    305\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0mFileNotFoundError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36mcheck_output\u001b[1;34m(timeout, *popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    394\u001b[0m     return run(*popenargs, stdout=PIPE, timeout=timeout, check=True,\n\u001b[1;32m--> 395\u001b[1;33m                **kwargs).stdout\n\u001b[0m\u001b[0;32m    396\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36mrun\u001b[1;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[0;32m    471\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 472\u001b[1;33m     \u001b[1;32mwith\u001b[0m \u001b[0mPopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0mpopenargs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mprocess\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    473\u001b[0m         \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, encoding, errors, text)\u001b[0m\n\u001b[0;32m    774\u001b[0m                                 \u001b[0merrread\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrwrite\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 775\u001b[1;33m                                 restore_signals, start_new_session)\n\u001b[0m\u001b[0;32m    776\u001b[0m         \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\subprocess.py\u001b[0m in \u001b[0;36m_execute_child\u001b[1;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_start_new_session)\u001b[0m\n\u001b[0;32m   1177\u001b[0m                                          \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfspath\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcwd\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mcwd\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m \u001b[1;32melse\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1178\u001b[1;33m                                          startupinfo)\n\u001b[0m\u001b[0;32m   1179\u001b[0m             \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 2] The system cannot find the file specified",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[1;31mRuntimeError\u001b[0m                              Traceback (most recent call last)",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\IPython\\core\\formatters.py\u001b[0m in \u001b[0;36m__call__\u001b[1;34m(self, obj)\u001b[0m\n\u001b[0;32m    339\u001b[0m                 \u001b[1;32mpass\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    340\u001b[0m             \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 341\u001b[1;33m                 \u001b[1;32mreturn\u001b[0m \u001b[0mprinter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    342\u001b[0m             \u001b[1;31m# Finally look for special method names\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    343\u001b[0m             \u001b[0mmethod\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mget_real_method\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprint_method\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\IPython\\core\\pylabtools.py\u001b[0m in \u001b[0;36m<lambda>\u001b[1;34m(fig)\u001b[0m\n\u001b[0;32m    242\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    243\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[1;34m'png'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mformats\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 244\u001b[1;33m         \u001b[0mpng_formatter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfor_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mlambda\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mprint_figure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'png'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    245\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[1;34m'retina'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mformats\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;34m'png2x'\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mformats\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    246\u001b[0m         \u001b[0mpng_formatter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfor_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mFigure\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mlambda\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mretina_figure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\IPython\\core\\pylabtools.py\u001b[0m in \u001b[0;36mprint_figure\u001b[1;34m(fig, fmt, bbox_inches, **kwargs)\u001b[0m\n\u001b[0;32m    126\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    127\u001b[0m     \u001b[0mbytes_io\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 128\u001b[1;33m     \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mprint_figure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbytes_io\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkw\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    129\u001b[0m     \u001b[0mdata\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mbytes_io\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    130\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mfmt\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m'svg'\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\backend_bases.py\u001b[0m in \u001b[0;36mprint_figure\u001b[1;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, **kwargs)\u001b[0m\n\u001b[0;32m   2054\u001b[0m                         \u001b[0morientation\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0morientation\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2055\u001b[0m                         \u001b[0mdryrun\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2056\u001b[1;33m                         **kwargs)\n\u001b[0m\u001b[0;32m   2057\u001b[0m                     \u001b[0mrenderer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_cachedRenderer\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2058\u001b[0m                     \u001b[0mbbox_artists\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"bbox_extra_artists\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py\u001b[0m in \u001b[0;36mprint_png\u001b[1;34m(self, filename_or_obj, metadata, pil_kwargs, *args, **kwargs)\u001b[0m\n\u001b[0;32m    525\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    526\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 527\u001b[1;33m             \u001b[0mFigureCanvasAgg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    528\u001b[0m             \u001b[0mrenderer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    529\u001b[0m             \u001b[1;32mwith\u001b[0m \u001b[0mcbook\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_setattr_cm\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdpi\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdpi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py\u001b[0m in \u001b[0;36mdraw\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    386\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrenderer\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_renderer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcleared\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    387\u001b[0m         \u001b[1;32mwith\u001b[0m \u001b[0mRendererAgg\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlock\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 388\u001b[1;33m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    389\u001b[0m             \u001b[1;31m# A GUI class may be need to update a window using this draw, so\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    390\u001b[0m             \u001b[1;31m# don't forget to call the superclass.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[1;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[0;32m     36\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     37\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 38\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0martist\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     39\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     40\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\figure.py\u001b[0m in \u001b[0;36mdraw\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m   1707\u001b[0m             \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpatch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1708\u001b[0m             mimage._draw_list_compositing_images(\n\u001b[1;32m-> 1709\u001b[1;33m                 renderer, self, artists, self.suppressComposite)\n\u001b[0m\u001b[0;32m   1710\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1711\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mclose_group\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'figure'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\image.py\u001b[0m in \u001b[0;36m_draw_list_compositing_images\u001b[1;34m(renderer, parent, artists, suppress_composite)\u001b[0m\n\u001b[0;32m    133\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mnot_composite\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mhas_images\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    134\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[1;32min\u001b[0m \u001b[0martists\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 135\u001b[1;33m             \u001b[0ma\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    136\u001b[0m     \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    137\u001b[0m         \u001b[1;31m# Composite any adjacent images together\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[1;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[0;32m     36\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     37\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 38\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0martist\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     39\u001b[0m         \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     40\u001b[0m             \u001b[1;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36mdraw\u001b[1;34m(self, renderer, inframe)\u001b[0m\n\u001b[0;32m   2603\u001b[0m                 \u001b[0martists\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mspine\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2604\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2605\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_update_title_position\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2606\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2607\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0maxison\u001b[0m \u001b[1;32mor\u001b[0m \u001b[0minframe\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py\u001b[0m in \u001b[0;36m_update_title_position\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m   2552\u001b[0m                     \u001b[1;31m# this happens for an empty bb\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   2553\u001b[0m                     \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 2554\u001b[1;33m             \u001b[1;32mif\u001b[0m \u001b[0mtitle\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_window_extent\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mymin\u001b[0m \u001b[1;33m<\u001b[0m \u001b[0mtop\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   2555\u001b[0m                 y = self.transAxes.inverted().transform(\n\u001b[0;32m   2556\u001b[0m                         (0., top))[1]\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\text.py\u001b[0m in \u001b[0;36mget_window_extent\u001b[1;34m(self, renderer, dpi)\u001b[0m\n\u001b[0;32m    888\u001b[0m             \u001b[1;32mraise\u001b[0m \u001b[0mRuntimeError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'Cannot get window extent w/o renderer'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    889\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 890\u001b[1;33m         \u001b[0mbbox\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minfo\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdescent\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_layout\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_renderer\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    891\u001b[0m         \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_unitless_position\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    892\u001b[0m         \u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_transform\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtransform_point\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0my\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\text.py\u001b[0m in \u001b[0;36m_get_layout\u001b[1;34m(self, renderer)\u001b[0m\n\u001b[0;32m    289\u001b[0m         _, lp_h, lp_d = renderer.get_text_width_height_descent(\n\u001b[0;32m    290\u001b[0m             \u001b[1;34m\"lp\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fontproperties\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 291\u001b[1;33m             ismath=\"TeX\" if self.get_usetex() else False)\n\u001b[0m\u001b[0;32m    292\u001b[0m         \u001b[0mmin_dy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mlp_h\u001b[0m \u001b[1;33m-\u001b[0m \u001b[0mlp_d\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_linespacing\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    293\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\backends\\backend_agg.py\u001b[0m in \u001b[0;36mget_text_width_height_descent\u001b[1;34m(self, s, prop, ismath)\u001b[0m\n\u001b[0;32m    199\u001b[0m             \u001b[0mfontsize\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mprop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_size_in_points\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    200\u001b[0m             w, h, d = texmanager.get_text_width_height_descent(\n\u001b[1;32m--> 201\u001b[1;33m                 s, fontsize, renderer=self)\n\u001b[0m\u001b[0;32m    202\u001b[0m             \u001b[1;32mreturn\u001b[0m \u001b[0mw\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mh\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0md\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    203\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36mget_text_width_height_descent\u001b[1;34m(self, tex, fontsize, renderer)\u001b[0m\n\u001b[0;32m    446\u001b[0m         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    447\u001b[0m             \u001b[1;31m# use dviread. It sometimes returns a wrong descent.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 448\u001b[1;33m             \u001b[0mdvifile\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmake_dvi\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfontsize\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    449\u001b[0m             \u001b[1;32mwith\u001b[0m \u001b[0mdviread\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDvi\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdvifile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m72\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mdpi_fraction\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mdvi\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    450\u001b[0m                 \u001b[0mpage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mdvi\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36mmake_dvi\u001b[1;34m(self, tex, fontsize)\u001b[0m\n\u001b[0;32m    336\u001b[0m                 self._run_checked_subprocess(\n\u001b[0;32m    337\u001b[0m                     [\"latex\", \"-interaction=nonstopmode\", \"--halt-on-error\",\n\u001b[1;32m--> 338\u001b[1;33m                      texfile], tex)\n\u001b[0m\u001b[0;32m    339\u001b[0m             \u001b[1;32mfor\u001b[0m \u001b[0mfname\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mglob\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mglob\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbasefile\u001b[0m \u001b[1;33m+\u001b[0m \u001b[1;34m'*'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    340\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0mfname\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mendswith\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'dvi'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'tex'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\lib\\site-packages\\matplotlib\\texmanager.py\u001b[0m in \u001b[0;36m_run_checked_subprocess\u001b[1;34m(self, command, tex)\u001b[0m\n\u001b[0;32m    306\u001b[0m             raise RuntimeError(\n\u001b[0;32m    307\u001b[0m                 \u001b[1;34m'Failed to process string with tex because {} could not be '\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 308\u001b[1;33m                 'found'.format(command[0])) from exc\n\u001b[0m\u001b[0;32m    309\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[0msubprocess\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mCalledProcessError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    310\u001b[0m             raise RuntimeError(\n",
      "\u001b[1;31mRuntimeError\u001b[0m: Failed to process string with tex because latex could not be found"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1080x864 with 15 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import mglearn\n",
    "mglearn.plots.plot_pca_faces(X_train, X_test, image_shape)\n",
    "plt.suptitle(\"pca_reconstructions\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
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