{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
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   "source": [
    "# Notebook 3: Handwritten Character Recognition\n",
    "\n",
    "## Using Machine Learning to Detect a 'W' in the demographic column\n",
    "\n",
    "This notebook builds upon the image processing work in the document segmentation notebook. The code from that notebook has been consolidated into a file called 'segmentation.py' and will be imported for use in this notebook. This notebook will demonstrate a machine learning approach to recognizing handwritten characters, using a layered *neural network* that is trained on the publically available EMNIST letters dataset. The E in EMNIST stands for Extended, as it is an extended version of the MNIST dataset, which is the Modified National Institute of Standards and Technology (NIST) dataset of handwritten digits. Before you can train a machine learning model (or neural network) on the digit dataset you have to download it from the NIST website. Lucky for us, the Keras toolkit now includes functions that automate the download of the dataset the first time that you use it. Be forewarned that this code will take a long time to execute the first time, depending upon your network speed.\n",
    "\n",
    "This notebook is partially based on the [Keras MNIST tutorial](https://colab.research.google.com/github/AviatorMoser/keras-mnist-tutorial/blob/master/MNIST%20in%20Keras.ipynb) written by Daniel Moser (UT Southwestern Medical Center). We modify their approach to focus on letters exclusively and explore training a NN and Convolutional NN (CNN) to specialize in recognizing the W character alone.\n",
    "\n",
    "## Install Dependencies\n",
    "The first step is to install some necessary Python libraries for machine learning. We are using the Google suite of tools, which include *TensorFlow* and *Keras*, which is a somewhat simpler API that wraps the base functions provided by TensorFlow. Please Note: There is a strange situation with Keras version 3 that requires it to be installed (or reinstalled) after you install tensorflow. (TensorFlow tries to install it's own earlier version of Keras.)\n",
    "\n",
    "Be sure to restart your Jupyter notebook kernel after these tools have been installed.\n",
    "\n",
    "Note: You may have already installed these tools via the Pipenv tool."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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      "\u001b[?25hInstalling collected packages: tensorflow-datasets\n",
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      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install --upgrade tensorflow==\"2.16.1\" numpy tensorflow-datasets==\"4.9.4\"\n",
    "%pip install --upgrade keras==\"3\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading the EMNIST image data into a TensorFlow Dataset\n",
    "\n",
    "The next step is to setup the tensorflow training dataset that contains the digits that we want to use to train a model. EMNIST includes thousands of grayscale images that are 28x28 pixels in size with 256 levels of gray. The images are numerically labelled with the letter represented in the image. For instance, a 'W' is labelled with the number 23. The following code uses the TensorFlow Datasets module to load our chosen dataset. It will download the data the first time that you run it, which can take some time. Notice that we have specified some options to the `load()` function, saying that we desire only letters. It also specifies that we want the dataset split into  both training data and testing data. The testing data will be used to measure the accuracy of our model after training. We also load information about the dataset into a separate Python dictionary.\n",
    "\n",
    "First we print out the dataset info object, then we display a grid of the first 9 images in the dataset, so that you can see what the images look like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-01-16 11:44:24.539106: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
      "2025-01-16 11:44:24.539352: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
      "2025-01-16 11:44:24.541428: I external/local_tsl/tsl/cuda/cudart_stub.cc:32] Could not find cuda drivers on your machine, GPU will not be used.\n",
      "2025-01-16 11:44:24.567261: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
      "To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2025-01-16 11:44:25.059774: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n",
      "2025-01-16 11:44:25.767387: E external/local_xla/xla/stream_executor/cuda/cuda_driver.cc:282] failed call to cuInit: CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE: forward compatibility was attempted on non supported HW\n",
      "2025-01-16 11:44:25.767406: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:134] retrieving CUDA diagnostic information for host: graeber\n",
      "2025-01-16 11:44:25.767409: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:141] hostname: graeber\n",
      "2025-01-16 11:44:25.767478: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:165] libcuda reported version is: 565.77.0\n",
      "2025-01-16 11:44:25.767488: I external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:169] kernel reported version is: 560.35.3\n",
      "2025-01-16 11:44:25.767490: E external/local_xla/xla/stream_executor/cuda/cuda_diagnostics.cc:251] kernel version 560.35.3 does not match DSO version 565.77.0 -- cannot find working devices in this configuration\n",
      "2025-01-16 11:44:25.901892: E tensorflow/core/util/util.cc:131] oneDNN supports DT_UINT8 only on platforms with AVX-512. Falling back to the default Eigen-based implementation if present.\n",
      "2025-01-16 11:44:25.937006: W tensorflow/core/kernels/data/cache_dataset_ops.cc:858] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset  will be discarded. This can happen if you have an input pipeline similar to `dataset.cache().take(k).repeat()`. You should use `dataset.take(k).cache().repeat()` instead.\n",
      "2025-01-16 11:44:25.942036: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tfds.core.DatasetInfo(\n",
      "    name='emnist',\n",
      "    full_name='emnist/letters/3.0.0',\n",
      "    description=\"\"\"\n",
      "    The EMNIST dataset is a set of handwritten character digits derived from the NIST Special Database 19 and converted to a 28x28 pixel image format and dataset structure that directly matches the MNIST dataset.\n",
      "    \n",
      "    Note: Like the original EMNIST data, images provided here are inverted horizontally and rotated 90 anti-clockwise. You can use `tf.transpose` within `ds.map` to convert the images to a human-friendlier format.\n",
      "    \"\"\",\n",
      "    config_description=\"\"\"\n",
      "    EMNIST Letters\n",
      "    \"\"\",\n",
      "    homepage='https://www.nist.gov/itl/products-and-services/emnist-dataset',\n",
      "    data_dir='/home/jansen/tensorflow_datasets/emnist/letters/3.0.0',\n",
      "    file_format=tfrecord,\n",
      "    download_size=535.73 MiB,\n",
      "    dataset_size=44.14 MiB,\n",
      "    features=FeaturesDict({\n",
      "        'image': Image(shape=(28, 28, 1), dtype=uint8),\n",
      "        'label': ClassLabel(shape=(), dtype=int64, num_classes=37),\n",
      "    }),\n",
      "    supervised_keys=('image', 'label'),\n",
      "    disable_shuffling=False,\n",
      "    splits={\n",
      "        'test': <SplitInfo num_examples=14800, num_shards=1>,\n",
      "        'train': <SplitInfo num_examples=88800, num_shards=1>,\n",
      "    },\n",
      "    citation=\"\"\"@article{cohen_afshar_tapson_schaik_2017,\n",
      "        title={EMNIST: Extending MNIST to handwritten letters},\n",
      "        DOI={10.1109/ijcnn.2017.7966217},\n",
      "        journal={2017 International Joint Conference on Neural Networks (IJCNN)},\n",
      "        author={Cohen, Gregory and Afshar, Saeed and Tapson, Jonathan and Schaik, Andre Van},\n",
      "        year={2017}\n",
      "    }\"\"\",\n",
      ")\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np                   # advanced math library\n",
    "import matplotlib.pyplot as plt      # MATLAB like plotting routines\n",
    "import tensorflow as tf\n",
    "\n",
    "#from tensorflow.keras.utils import to_categorical              # NumPy related tools\n",
    "\n",
    "# Data should be located in a folder called EMNIST\n",
    "import tensorflow_datasets as tfds\n",
    "(ds_train, ds_test), ds_info = tfds.load(\n",
    "    'emnist/letters',\n",
    "    split=['train', 'test'],\n",
    "    shuffle_files=True,\n",
    "    as_supervised=True,\n",
    "    with_info=True,\n",
    ")\n",
    "\n",
    "print(ds_info)\n",
    "\n",
    "plt.figure(figsize=(8, 8))\n",
    "for i, (img, lbl) in enumerate(ds_train.take(9)):\n",
    "    ax = plt.subplot(3, 3, i + 1)\n",
    "    plt.imshow(tf.transpose(img, perm=[1,0,2]))\n",
    "    plt.title(str(int(lbl)))\n",
    "    plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You may notice that the letters look pretty strange. They are in fact inverted horizontally and rotated 90 degrees anti-clockwise. This is a legacy of the original EMNIST dataset and is maintained in the tensorflow version for consistency. You can read this explanation in the dataset information we printed above. There are also instructions there for how to make the images match our expectations and we will follow those in steps below.\n",
    "\n",
    "**Please Note:**  The number of classes (labels) for the images is listed as 37 in the dataset information dictionary. This is in fact a typo in the TensorFlow dataset's description, as of the 3.0 version the typo is still there. The same typo occurs in the original EMNIST paper, where the number of classes in the \"letters\" subset is reported as both 37 AND 26 in different places. I discovered this discrepancy towards the end of my analysis. We can simply treat the number of classes as 26 and ignore the incorrect 37.\n",
    "\n",
    "## Census Data\n",
    "\n",
    "Let's load and preview some census demographic code images for comparison. Remember that we are training a model to recognize the census W's based entirely on these EMNIST examples. The two data sources do not resemble each other much yet, but we can take steps to bring them closer together."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x576 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# First we load the segmentation code that we developed in that notebook\n",
    "with open(\"segmentation.py\") as f:\n",
    "    code = f.read()\n",
    "exec(code)\n",
    "\n",
    "page = \"pages/43290879-California-101393-0002.jpeg\"\n",
    "cells = list(generateCellImages(page))\n",
    "plt.figure(figsize=(8, 8))\n",
    "for i, image in enumerate(cells[:9]):\n",
    "    ax = plt.subplot(3, 3, i + 1)\n",
    "    plt.imshow(image)\n",
    "    plt.title(str(i))\n",
    "    plt.axis(\"off\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you compare the Census 'W' images to the EMNIST letters, you should notice a few things:\n",
    "\n",
    "* The EMNIST images are 28 by 28 pixels square, whereas the Census cell images are taller and wider.\n",
    "* The EMNIST images are rotated and flipped, whereas the Census cell images are oriented normally.\n",
    "* The Census images contain some extraneous ink, usually a horizontal rule that marks the botton of the demographic cell. This noisy line is sometimes faint and sometimes heavy. The EMNIST image consist of clear and crisp letters with no extraneous ink.\n",
    "* EMNIST letters are centered within the 28 pixel square using a bounding box technique. This leaves an even margin on the top and bottom and on the left and right. Our 'W' images are not well centered.\n",
    "\n",
    "## Dealing with the horizontal rule\n",
    "In an earlier version of this project we addressed the noisy horizontal line by adding a similar line to our training data. We would generate some random noise and add it to a few rows near the bottom of the EMNIST characters. This worked fairly well (recognizing 2/3 of W characters). Ultimately, however, more noise will be more input that must be ignored by the recognizer function. The noise also makes it difficult to center the census code within a 28x28 box, since the edges are not crisp. After avoiding such involved techniques at first, we finally decided to try and remove the noise from the census images through computer vision techniques. \n",
    "\n",
    "The function below detects horizontal rows near the bottom of the image which have cumulative pixel values that are greater than a threshold value. These lines are erased. As erasing horizontal lines may leave some gaps in the demographic code strokes, we perform a healing operation (dilation followed by erosion), using a vertical structuring element. This replaces the erased parts of any near vertical lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "def close( img ):\n",
    "    kerns = [\n",
    "        #cv2.getStructuringElement(cv2.MORPH_RECT, (1, 3))\n",
    "        np.array([[ 1, 1, 1 ], [ 0, 1, 0 ], [0, 1, 0 ]], dtype=np.uint8),\n",
    "        #np.array([[ 0, 1, 0 ], [ 0, 1, 0 ], [0, 1, 0 ]], dtype=np.uint8),\n",
    "        #np.array([[ 1, 0, 0 ], [ 0, 1, 0 ], [0, 0, 1 ]], dtype=np.uint8),\n",
    "    ]\n",
    "    for k in kerns:\n",
    "        img = cv2.dilate(img, k, iterations=2)\n",
    "        img = cv2.erode(img, k, iterations=2)\n",
    "    return img\n",
    "\n",
    "def zap_lower_horiz_lines(img, debug=False):\n",
    "    if debug:\n",
    "        view(img, \"with horiz line\")\n",
    "    h_ink = np.sum(img, axis=1)\n",
    "    idx = np.argmax(h_ink)\n",
    "    if(idx > 20 and h_ink[idx] > 3000):\n",
    "        img[idx, :] = 0\n",
    "        view(img, \"deleted\")\n",
    "        #img[idx-1:idx+1, :] = close(img[idx-1:idx+1, :])\n",
    "        view(img, \"repaired\")\n",
    "        h_ink = np.sum(img, axis=1)\n",
    "        idx = np.argmax(h_ink)\n",
    "        if(False and idx > 20 and h_ink[idx] > 2000):\n",
    "            img[idx, :] = 0\n",
    "            view(img, \"deleted 2\")\n",
    "        img[idx-2:idx+2, :] = close(img[idx-2:idx+2, :])\n",
    "        view(img, \"repaired 2\")\n",
    "    return img"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The zap_lower_lines() function will be called by another function called crop_cell(), which will make all of the adjustments to our census images prior to recognition.\n",
    "\n",
    "After removing the horizontal line, we use the findContours() function to find all of the shapes and then we select the shape with the largest area. This is assumed to be a W, whenever the image is a W. We then make a stencil from this shape and erase all of the ink outside of this shape, giving it a crisp outline.\n",
    "\n",
    "Once we have this crisp image of the glyph, we perform an affine transform to rescale and shift the glyph into the center of a 28x28 pixel image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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g9/1lTU1N5vjx48YYYz755BOTlpZmTp06FfIx8VZHqMfkxo0bpqOjwxhjzLVr18yECRPMe++9Zx555BGzbds2Y4wx3//+981vf/vbsNRRUlJiduzYEdS+b+Xll182jz32mHnwwQeNMabX4xHyLbvq6mqlpqYqJSVFd911l4qLi1VZWRnqMsJq0qRJGjJkSLd5lZWVKikpkRS6R2bdqo5wiI+PV25uriQpJiZG6enpamxsDPmYeKsj1O6Ux6p5qyMcGhoatGfPHj399NOSJGNMr8cj5GHX2NioxMREz/dwPh7K4XBo6tSpcrlccrvdYanhCy0tLYqPj5ckxcXFqaWlJWy1bNiwQTk5OSotLQ3J7vSXnT17VidOnNDEiRPDOiZfrkMK/ZjcKY9V+/91fDEey5YtU05OjhYtWqSrV68GvY4f//jH+p//+R9FRHweWRcuXOj1eFh9guLIkSP6+9//rrfeekuvvPKK3n333XCXJOnzEA7Xv6ALFy5UXV2damtrFR8fryVLloSs70uXLqmoqEjr1q3TgAEDurWFckz+fx3hGJO+PFYtmHX84x//0OrVq/XRRx/pb3/7m9ra2rRmzZqg1vDmm28qNjZWLperT+sJedglJCSovr7e872nx0OFohZJio2N1fTp01VdXR2WOiRpxIgRam5ulvT5wxdiY2PDVkdkZKQiIiI0f/78kI1JZ2enioqKNHv2bM2YMcNTS6jHxFsd4RgTyb/HqgWzjqqqKsXHx8vhcKhfv3566qmngj4eR48e1RtvvKHk5GQVFxfrwIEDeuaZZ3o9HiEPu/Hjx+v06dM6c+aMrl27pu3bt6uwsDDUZejTTz9VR0eH5/Pbb7/d7axkqBUWFqqiokJSeB+Z9UW4SNLOnTtDMibGGM2bN0/p6elavHixZ36ox8RbHaEekzvlsWq3qmPMmDGe8TDGaNeuXUEfj9WrV6uhoUFnz57V9u3bNXnyZG3durX34xHU0yde7Nmzx6SlpZmUlBTzi1/8IhwlmLq6OpOTk2NycnJMRkZGSOsoLi42cXFxJioqyiQkJJjXXnvNtLa2msmTJ5vU1FQzZcoUc+HChbDUMWfOHJOVlWWys7PNww8/bJqamoJex+HDh40kk52dbcaOHWvGjh1r9uzZE/Ix8VZHqMfk5MmTxul0muzsbJOZmWlWrVpljPn8/9nx48ebUaNGmZkzZ5orV66EpY78/HyTlZVlMjMzzezZsz1nbEPh4MGDnrOxvR0P7qAAYAWrT1AAsAdhB8AKhB0AKxB2AKxA2AGwAmEHwAqEHQArEHYArEDYAbACYQfACoQdACsQdgCsQNgBsAJhB8AKhB0AKxB2AKxA2AGwAmEHwAqEHQArEHYArEDYAbACYQfACoQdACsQdgCsQNgBsAJhB8AKhB0AKxB2AKxA2AGwAmEHwAqEHQArEHYArEDYAbACYQfACoQdACsQdgCsQNgBsAJhB8AKhB0AKxB2AKxA2AGwAmEHwAqEHQArEHYImwULFujnP/95wNaXnJys/fv3B2x9+Hoh7BA2v/vd7/Szn/0sJH2tXbtWWVlZiomJ0T333KO1a9eGpF/cOaLCXQDuXF1dXYqKCs//IoHu2xijzZs3KycnR3V1dZo6daoSExNVXFwcsD5wZ2PLDt0kJydrzZo1ysnJ0d13362uri4dO3ZM3/zmNzVo0CCNHTtWhw4d8ix///3366c//akmTJigAQMGaNq0aWpra/O0P/LII4qLi9PAgQM1adIknTp1ytM2d+5cLV++XJJ06NAhjRw5UmvWrFFcXJyeeuop3bhxQ+Xl5Ro1apSGDh2qWbNmdVv3li1blJSUpKFDh+qXv/xlj3/Xs88+q9zcXEVFRWn06NGaNm2ajh49GqBRw1cBYYebbNu2TXv27NHFixfV0tKiBx98UMuXL1dbW5t+9atfqaioSOfPn/csv3nzZm3atEnNzc2KiorSj370I0/bAw88oNOnT+vjjz9Wbm6uZs+e7bXf//znP2pra9O5c+fkdrv1m9/8Rrt27dI777yjpqYmDR48WD/4wQ8kSR988IEWLlyoLVu2qKmpSRcuXFBDQ8Nt/X3GGB0+fFiZmZl+jhC+kgzwJUlJSWbjxo2e7+Xl5WbOnDndlpk6dap5/fXXjTHGfOc73zHPPfecp+3UqVMmOjradHV13bTu9vZ2I8lcvHjRGGNMSUmJWbZsmTHGmIMHD5ro6Gjz2WefeZYfM2aM2b9/v+d7U1OTiYqKMp2dnWbVqlXm0Ucf9bRdunTJREdHm3379vn8G1esWGFycnLMlStXfC6Lrw+O2eEmiYmJns/nzp3Tjh07tHv3bs+8zs5O5efn33L5pKQkdXZ2qrW1VcOGDdOyZcu0Y8cOnT9/XhERn+9ItLa2auDAgTf1O3z4cH3jG9/o1vf06dM9v5OkyMhItbS0qKmpqVu/d999t4YOHerzb9uwYYM2b96sw4cPq1+/fj6Xx9cHYYebOBwOz+fExEQ98cQT+v3vf+91+fr6es/nf//734qOjtawYcP0xz/+UZWVldq/f7+Sk5P13//+V4MHD5Yxxme/X/S9adMmfetb37pp2fj4eH344Yee75cvX9aFCxd6/Ls2bdqk8vJyvfvuuxo5cmSPy+Lrh2N26NGcOXO0e/du/eUvf9H169d15coVHTp0qNvxsT/84Q/64IMPdPnyZa1YsUIzZ85UZGSkOjo61K9fPw0dOlSXL1/WCy+80Ku+FyxYoGXLluncuXOSpPPnz6uyslKSNHPmTL355ps6cuSIrl27phUrVujGjRte17V161a98MIL2rdvn1JSUvwYCXzVEXboUWJioiorK/XSSy9p+PDhSkxM1Nq1a7sFyxNPPKG5c+cqLi5OV65c0a9//WtJ0pNPPqmkpCQlJCQoIyND9913X6/6fuaZZ1RYWKipU6cqJiZG9913n95//31JUmZmpl555RU9/vjjio+P1+DBg3vcWlu+fLkuXLig8ePHq3///urfv78WLFjgx4jgq8phvO1TALfh/vvv15w5c/T000+HuxSgR2zZAbACYQfACuzGArACW3YArEDYAbACYQfACoQdACsQdgCsQNgBsML/AsZWeOXLqftfAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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KxcE2ILJ+l/xuXpWenq7SExERQMlORByhZCciTlCyExEnKNmJiBOU7ETECRFbPMUKW962luBZFwT2eFb5C8CX0q0yElZCwjqssBIYxiqrYSUHl112mTlmdXMBgF/96lfmGCsFsLAyl9dff90cY2Uk1nXw9NNPm+ew94x1gWHvGbvmLKw8g13fo0aNMsdYjNY1zK57Vo7FymPYtc+6m0SLPtmJiBOU7ETECUp2IuIEJTsRcYKSnYg4IearsdaKIVshtfr0s1UntlrFVh9ZcwHr+dgqKHtdrAfD8OHDzbHt27eHPb506VLzHLbXweTJk82xCRMmmGPWfLDXNWXKFHNs/fr15hhbmbz77rvDHr/qqqvMc1paWswxq8EBAKSmpppjjHWDu9UgAOArtew8tveDtarNfpf8xsh+L6xV4aFDh5rnWPtWAGcbAUSiT3Yi4gQlOxFxgpKdiDhByU5EnKBkJyJOiJjsmpqaMHPmTBQWFqKoqAhr164FALS3t6Oqqgr5+fmoqqqiu6+LiMRbxNKTpKQkPPbYY5g8eTKOHz+OiooKVFVV4emnn8Y111yDFStWYPXq1Vi9ejUeeeSRiE/op/e8ddMwKyFhpRssMbMSBz9YjOxGejYfe/fu7XccH3zwgTm2atUqc4zd6G3FyMoYWFkEu3H8rrvuMsd+/vOfm2OWn/3sZ+bYsWPHzDFWasFY1yPbo4SVYbASKT8NCdjN/n4bVrBrxyoNY78vrBlEn+KJ9AOZmZm9dVgpKSkoKChAS0sLtmzZgpqaGgBATU0NNm/ePKBARESiqV/f2e3fvx+7du3CtGnT0NbW1rubUkZGBtra2qISoIjIYOjzHRSdnZ1YsGAB1qxZ86WtAwOBgPlRNxgMIhgMAuCV9SIi0dSnT3Y9PT1YsGABFi1ahPnz5wM4e3vGub1IW1tbkZaWFvbcuro6hEIhhEIh33/7i4gMVMRk53keli5dioKCgvPuQZw9e3bvvYzr16/HnDlzoheliMgARfwz9q233sIzzzyDkpISlJeXAwAefvhhrFixAjfddBOeeuopjBs3Ds8991y0YxUR8S1isps+fbr5Xduf//znfj2Z53nm0jIrO7DGWBmA37o/tgT/n99VnsO6QjB+yjoAIC8vL+xx9jXBucWkcCZNmmSOse9ZWfyWd955xxxj5UIrV67sdxyhUMg854UXXjDH2LXoZ98NADh06FDY46wrDuvyceLECXOMPaafPShYKQsrB2HXzsGDB8MeZ3tTsN/NvtAdFCLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJ8R0w53ExESz2wFb0rdKEliHBNYxgi2Js3IWawmebcLCyhiGDRtmjrHOGw0NDWGPsw1OLrnkEnOMlbl8/PHH5ti+ffvCHr/uuuvMc6688kpzjG24w8opPvzww7DHv//975vnsDKdjIwMc4yVfDDWhjDsGmZlGKzshz2m1XWGzQeLw89zAfbvO3ufB9qRSJ/sRMQJSnYi4gQlOxFxgpKdiDhByU5EnKBkJyJOiGnpyZkzZ2gphsVacmZL26z0hOno6DDHrO4mPT095jlsjJWesDKS1157rd/PxUoLurq6zLFz+4yEs2TJkrDHWWnPwoULzTHWeYP58Y9/HPa4VZIC8BIjVuJgNakF7E4egP1es44iLEZ27bB5tN4b1lHEb6cXVtJkzTE7x89GQl+kT3Yi4gQlOxFxgpKdiDhByU5EnKBkJyJOiOlqbEJCgnlTP1s99dMIgPF787V1kzJbfbT2rQD8NT8A7CYBDzzwgHnO7bffbo6d29c3nL///e/m2Ntvvx32eF1dnXmO3+00H374YXPsgw8+CHucrZyyVT+2rwJb6RwzZky/z2MVBey6YuexigJrFZe9LrZS67eiYPTo0WGPs+t+oFux6pOdiDhByU5EnKBkJyJOULITESco2YmIEyImu6amJsycOROFhYUoKirC2rVrAZzdoT0rKwvl5eUoLy/Htm3boh6siIhfAY+tbwNobW1Fa2srJk+ejOPHj6OiogKbN2/Gc889h+TkZNxzzz19f7JAwFziZvs4WCGypWhW1sGaEfgpZ2HL752dneYY67fPXpu1PG81KgD4vgrsxnd2c3tmZmbY4zt37vQVxxtvvGGOzZ071xyzbhBPSUkxz2Hzy244Z6UR7FfJuq78xsGuHVbyYZXcsNIvdg37LZ+y4vA795dffjlCoZA5DvShzi4zM7P3ok5JSUFBQQFaWloinSYickHp13d2+/fvx65duzBt2jQAwLp161BaWora2locPXo0KgGKiAyGPie7zs5OLFiwAGvWrMHIkSOxbNkyNDY2oqGhAZmZmVi+fHnY84LBICorK1FZWTloQYuI9Fefkl1PTw8WLFiARYsWYf78+QDO7oOZmJiIhIQE3HHHHaivrw97bl1dHUKhUMS/p0VEoilisvM8D0uXLkVBQQHuvvvu3uOtra29/71p0yYUFxdHJ0IRkUEQcYHirbfewjPPPIOSkhKUl5cDOHtT9oYNG9DQ0IBAIIDc3Fw88cQT0Y5VRMS3iKUng2nUqFH42te+FnaMlSRYXRf2799vnsOW5tlLZsv2VtkMKx84cOCAOTZ+/HhzjJXHHDlyJOxx1nWDdXNh5QPvv/++OZaenh72OCsT+cY3vmGOvfjii+YYq+O0upSwPTlYqRPrlsKuq5ycHHNs3759YY+z/T9Yxxn2frLXZi0ksu48VpcdAMjNzTXHmIqKirDHd+zYYZ7z17/+1RxLSUmJ+FWZ7qAQESco2YmIE5TsRMQJSnYi4gQlOxFxgpKdiDghphvuDB8+HJMmTQo7dvXVV5vntbe3hz2+detW8xy/5QOsU4bVHcSKD+AlAldddZU5ZpUqAHb8Y8eONc/xW2qxZcsWc8x6zy677DLzHHYPdUFBgTnGHtPqKNLY2GiewzpofPWrXzXH2Bz/61//Msfy8vLCHmdlP+fuQQ+HbarT3NxsjpWVlYU9npWVZZ7DSk+uueYac4zNx7hx48Iet/IDwLv67N271xw7R5/sRMQJSnYi4gQlOxFxgpKdiDhByU5EnKBkJyJOiGnXk2HDhpndTVj3hCFDhoQ9zvbCYEv6bFMd1sHEwsoY2GYlrIyBxWhtjsI2TTlx4oQ5xlgbowB2lxWrSw3AS3tYWQo7z5ordn1YnVIAXubC4mhqaur387HrtK2tzRxj1xybR6sUir2u48ePm2OXXHKJOcY6CFnXCCvV2rNnjzmWnp6uriciIoCSnYg4QslORJygZCciTlCyExEnxHQ1Nikpid6QbrFWig4ePGiew/a0YDfus1Uua18Ivyu/7Dy2kmWtkLKVLPZ47AZrtsKbkBD+30pr9Rzg+3+wONjqqbWyxxo+WLEDfOWaxcje6xEjRoQ97vfXj1UNsPm3Xtvo0aPNc9jvGXsuNh/W+8nOYft1FBYWajVWRARQshMRRyjZiYgTlOxExAlKdiLihIjJrru7G1OnTkVZWRmKiorwwAMPADjbNnzatGnIy8vDzTffTO+HFBGJt4ilJ57noaurC8nJyejp6cH06dOxdu1a/PrXv8b8+fNRXV2N733veygrK8OyZcvokw0dOtQsCWFL+lbpCUuwbGl+2LBh5phVXsLGWLkKm14WIyv5sJbn2U37LA6/Mfb09IQ9zkpq/JRFAHw+kpLCb6XCylVYgwbr8QA+x+w862Z6NleslOjkyZPmGCursa5htg8JK/lgv0us3Gmwy7gGpRFAIBDorVfq6elBT08PAoEAXnvtNdx4440AgJqaGmzevDnSQ4mIxE2fvrM7ffo0ysvLkZaWhqqqKkyYMAGpqam9/5JlZ2fTdjoiIvHWp2SXmJiIhoYGNDc3o76+Hu+//36fnyAYDKKyshKVlZX0TwARkWjq12psamoqZs6ciZ07d6Kjo6P3b+jm5mZz38m6ujqEQiGEQiH6XYKISDRFzD6HDh3q3ZD35MmTeOWVV1BQUICZM2fi97//PQBg/fr1mDNnTlQDFREZCHv56P+1traipqYGp0+fxpkzZ3DTTTfh+uuvR2FhIaqrq3H//ffjyiuvxNKlS2MRr4iILzHtejJ27NjevSYOHTqESy+9NFZPbVIcikNx9M+FEssX49i/fz8OHz7MT/DipKKiIl5PfR7FcT7FcT7F8WUXSiz9jUMrBiLiBCU7EXFC3JJdXV1dvJ76PIrjfIrjfIrjyy6UWPobR0wXKERE4kV/xoqIE+KS7F566SVcccUVyMvLw+rVq+MRAgAgNzcXJSUlKC8vR2VlZcyet7a2FmlpaSguLu491t7ejqqqKuTn56OqqgpHjx6NSxwrV65EVlYWysvLUV5ejm3btkU9jqamJsycOROFhYUoKirC2rVrAcR+Tqw4Yj0nF0pbNSuOJUuW4PLLL++dj4aGhqjGcc7p06dx5ZVX4vrrrwfgYz6isiZMfP7559748eO9xsZG77PPPvNKS0u9PXv2xDoMz/M8b9y4cd6hQ4di/rx/+ctfvHfffdcrKirqPfajH/3IW7Vqled5nrdq1Srv3nvvjUscDzzwgPfLX/4y6s/9RQcOHPDeffddz/M879ixY15+fr63Z8+emM+JFUes5+TMmTPe8ePHPc/zvFOnTnlTp071du7c6X3729/2NmzY4Hme5333u9/1fvOb38QljpqaGu93v/tdVJ87nMcee8xbuHCh961vfcvzPK/f8xHzT3b19fXIy8vD+PHjMXToUFRXV2PLli2xDiOuZsyYgTFjxpx3bMuWLaipqQEQu5ZZ4eKIh8zMTEyePBnA2d6FBQUFaGlpifmcWHHE2oXSVs2KIx6am5uxdetW3H777QDO9mDs73zEPNm1tLQgJyen9//j2R4qEAhg1qxZqKioQDAYjEsM57S1tSEzMxPA2T1v29ra4hbLunXrUFpaitra2pj8Of1F+/fvx65duzBt2rS4zskX4wBiPycXSlu1/4zj3Hzcd999KC0txQ9/+EPa8Haw3HXXXXj00Ud7m4kcOXKk3/Ph9ALFm2++ib/97W/44x//iMcffxw7duyId0gAzibheP0LumzZMjQ2NqKhoQGZmZlYvnx5zJ67s7MTCxYswJo1azBy5MjzxmI5J/8ZRzzmZCBt1aIZx+7du7Fq1Sq8//77eOedd9De3o5HHnkkqjG8+OKLSEtLQ0VFxYAeJ+bJLisrC01NTb3/z9pDxSIW4GxL6nnz5qG+vj4ucQBn20q3trYCONt8gbXJjnYciYmJSEhIwB133BGzOenp6cGCBQuwaNEizJ8/vzeWWM+JFUc85gTw11YtmnG89NJLyMzMRCAQwLBhw3DbbbdFfT7eeustPP/888jNzUV1dTVee+01/OAHP+j3fMQ82U2ZMgUfffQR9u3bh1OnTmHjxo2YPXt2rMNAV1dX774AXV1dePnll89blYy12bNnY/369QDi2zLrXHIBgE2bNsVkTjzPw9KlS1FQUIC7776793is58SKI9ZzcqG0VQsXx6RJk3rnw/M8bN68OerzsWrVKjQ3N2P//v3YuHEjrr76ajz77LP9n4+oLp8Ytm7d6uXn53vjx4/3HnrooXiE4DU2NnqlpaVeaWmpV1hYGNM4qqurvYyMDC8pKcnLysrynnzySe/w4cPe1Vdf7eXl5XnXXHONd+TIkbjEceutt3rFxcVeSUmJd8MNN3gHDhyIehxvvPGGB8ArKSnxysrKvLKyMm/r1q0xnxMrjljPyXvvveeVl5d7JSUlXlFRkffggw96nnf2mp0yZYo3YcIE78Ybb/S6u7vjEsfMmTO94uJir6ioyFu0aFHvim0svP76672rsf2dD91BISJOcHqBQkTcoWQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZyaAqKirC9u3b4x2GyJcEPM/z4h2ESH8sWbIE2dnZeOihh+IdivwX0Sc7EXGCkp0MqtzcXLz66qtYuXIlbrrpJixevBgpKSkoKipCKBQ67+dWrVqFwsJCjB49Grfddhu6u7sBAE8//TSmT59+3uMGAgF8/PHHCAaDePbZZ/Hoo48iOTkZN9xwQ0xfn/z3UrKTqHn++edRXV2Njo4OzJ49G3feeed5488++yz+9Kc/obGxER9++GGf/iytq6vDokWLcO+996KzsxMvvPBCtMKX/zFKdhI106dPxze/+U0kJibiO9/5Dt57773zxu+8807k5ORgzJgxuO+++7Bhw4Y4RSouULKTqMnIyOj974svvhjd3d34/PPPe4/l5OT0/ve4ceNw4MCBmMYnblGyk7hpamrq/e9///vfuOyyywAAI0aMwIkTJ3rHPvnkk/POCwQCsQlQ/qco2UncPP7442hubkZ7ezt+8Ytf4OabbwYAlJWVYc+ePWhoaEB3dzdWrlx53nnp6enYu3dvHCKW/2ZKdhI3t9xyC2bNmoXx48djwoQJuP/++wEAEydOxE9/+lNce+21yM/P/9LK7NKlS/HPf/4TqampmDt3bhwil/9GKiqWuMjNzcWTTz6Ja6+9Nt6hiCP0yU5EnKBkJyJO0J+xIuIEfbITESco2YmIE5TsRMQJSnYi4gQlOxFxgpKdiDjh/wC7lVt+Tr1I1QAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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QsBMRJ8R11ZMRI0bgwgsv9G1jaXsrHc1WkmAlH6wtyIYqrDxj3LhxZhsrEWArdlhlDKysg5VTBJ0PCzuXbD7YJjJslRKrJIh9ZlbmwkomWJkOO59BNmtipTOsDINdj+np6b7H2Yoi7DOzcVgrmwD2GNm1yEJVTk6OVj0REQEU7ETEEQp2IuIEBTsRcYKCnYg4Ia4LAZw8edLMGB4+fNjsZ2W52IPSLLtkZaQA/oC4lXliD0rn5eWZbaxfS0uL2dbT0+N73NqbAgAOHDhgtn39618328rLy822t956y/c4W4SBZXfZvgpsPoqLi32Pl5aWmn22b99utlnzC/AMKcugW21BM+EsCxpkXwj2euw6ZdnkPXv2mG3WuWZZctY2GLqzExEnKNiJiBMU7ETECQp2IuIEBTsRccKAwa6lpQVz585FSUkJSktLsXr1agCnlvmurq5GUVERqqur0dnZGfPBiogENeBCAO3t7Whvb8eMGTPQ1dWFyspKbN68GU8++SQyMjKwfPlyrFq1Cp2dnXjooYfom40aNQpTp071bWttbTX7ZWRk+B5n5SUslc5KBNjDy1ZJgjU+APjzn/9strEHrJcuXWq2/fvf/x7y6xUWFppta9euNdussg4AWL58ue/x3/72t2Yf9kA/2yeDlcBs3brV9zhbCOCRRx4x2372s5+ZbWyPhCuuuMJse/31132PB1loAeAlMGxBCKsfKy9hCxwE3TPC+u4GWYgDACZMmDD8hQBycnIwY8YMAKcCQXFxMdra2rBlyxbU19cDAOrr67F58+aBXkpEJGGG9Du73bt34+2338asWbPQ0dGBnJwcAEB2djY6OjpiMkARkWgY9BMU3d3dqK2txaOPPooxY8ac1RYKhcynGcLhMMLhMAB+qywiEkuDurPr6+tDbW0tFi9ejAULFgAAsrKy0N7eDuDU7/UyMzN9+zY2NiISiSASidDfKYmIxNKAwc7zPCxduhTFxcW4/fbb+4/X1NRg3bp1AIB169Zh3rx5sRuliMgwDXirtWPHDjz11FOYNm0aKioqAAAPPvggli9fjoULF+KJJ57ApEmT8PTTT8d6rCIigQ0Y7GbPnm2u/f73v/99SG92/Phx7Nu3z7eN7VtgrZ7AVslg6XKWwmb9rNKTDRs2mH2mTJlitrGqH7ZKibWqCFvl4/TvTf1Y5UAAH2NBQYHvcVb6wOaXrdryq1/9ymyzyoVYGcNtt91mtpWVlZltF1xwgdn2jW98w2yrqanxPf7Pf/7T7MNKpNg1zPpZ+3Ww12Pfs6D1tdYKJmz/jy/mCoZKT1CIiBMU7ETECQp2IuIEBTsRcYKCnYg4QcFORJwQ10caQqGQuUEHWz3B2pSEbVbCVrzo6uoy24KMIzs72+zDsA2D2Cow1iY+v/zlL80+RUVFZtsAC9+YrMf/WHnJ6eep/Tz88MNm2yWXXGK2sdU1LKzU4tprrw30Xqxc6L333vM9zspj2DXMNp9hK6JY54xdi+z6YKvYsFIR6zvIVh0Kcp7PpDs7EXGCgp2IOEHBTkScoGAnIk5QsBMRJyjYiYgT4lp64nmemWpnqx1Y6Wi28vHhw4fNNrbCCisFsPqd3nHND9vMhq1OwcaxcuVK3+OXX3652YeVFjCs7OC1114bcp/f/e53Ztvs2bPNNraSyoMPPuh7fOfOnWafq666ymyzVgYBgPfff99se+ONN8w2a6UaVl7Crg82x+zasfqxMq4jR46Ybayf9ZkBu3SGfWZW0jQYurMTESco2ImIExTsRMQJCnYi4gQFOxFxQlyzsUlJSeYD2CxbaK2Bzx7mZplalgFj/Y4ePep7nGXo2Odi2aW77rrLbFu4cKHZZtm4caPZtmjRIrONZf22bt3qe3zFihVmH5ZxZe+1ZMkSs23Hjh2+x1lW8p133jHb2APn1kIWAM9ajh8/3vc4G6O15wkQ/WwswxbHYPtTsPFb88iysey9BkN3diLiBAU7EXGCgp2IOEHBTkScoGAnIk4YMNi1tLRg7ty5KCkpQWlpaf9zoCtWrEBubi4qKipQUVFhZuZERM4FIW+AXHR7ezva29sxY8YMdHV1obKyEps3b8bTTz+N1NRU3HnnnYN+s1GjRmHq1Km+bS0tLbSfH/YQMivrYKl5tm7+wYMHfY+zNf8//PBDs42VMbA0u3XKtm3bZvZh+1M899xzgcZhlcD8/ve/N/uwc8bKY2655Razbdy4cb7HWRlDSopddRV0/xK2L0SQB9+tUieAj5EtgmF9bnZemKAlMNb3c/To0WYfNh+TJk1CJBIx24FB1Nnl5OT0b5KSlpaG4uJitLW1DdRNROScMqTf2e3evRtvv/02Zs2aBQBYs2YNysvL0dDQgM7OzpgMUEQkGgYd7Lq7u1FbW4tHH30UY8aMwbJly7Br1y40NzcjJycHd9xxh2+/cDiMqqoqVFVV0acTRERiaVDBrq+vD7W1tVi8eDEWLFgAAMjKykJycjKSkpJw8803o6mpybdvY2MjIpEIIpEI/T2JiEgsDRjsPM/D0qVLUVxcjNtvv73/eHt7e/+fN23ahLKystiMUEQkCga81dqxYweeeuopTJs2DRUVFQBOLYO9YcMGNDc3IxQKIT8/H4899lisxyoiEtiAwW727Nm+6WW2hr8lNTXVXPXiH//4h9kvPT3d9zgrL9m/f7/Zxn53yFausMZx0UUXmX2CrDIB8JU3rJVU2P4OV199daBxML/5zW98j7MSDLa/wx/+8AezraCgwGyzzsvYsWPNPp988onZxqSmppptrIxkwoQJQ+5j7b0C8NIZ1s8qnWGlJ6zchrVlZGSYba2trb7H2fyyMQ4mH6AnKETECQp2IuIEBTsRcYKCnYg4QcFORJygYCciThhw1ZNomjFjBl555RX/gZCNaawyDFZ6wlL6rPyBsVY3YSulsPIHtqJIkNKTffv2mX2s0geAl8ewEgc2Rgs7ZwcOHAj0XtaGMGyjGFZixN6LXVeMtZoHK7X4/PPPzTZW3sNW4dm7d6/v8aysLLNPd3e32cauD7Yh1kcffeR7nJXN9Pb2mm21tbUDrnqiOzsRcYKCnYg4QcFORJygYCciTlCwExEnKNiJiBPiuppmUlKSmYJnpSdWW9CqmdN7avgJUvLBsDGy12NlKVa/8ePHR/X1AD5+6zXZHLKSCVb+wFjjZ5+LbVgT7WuA9WOb0rAyDDZG9ppnrkN5JnbtsPKYoNhKQZbhVsnpzk5EnKBgJyJOULATESco2ImIExTsRMQJcc3GdnZ2YtOmTb5tzc3NZr+ioiLf45mZmWafoA96B3mo/+OPPzb7ZGdnm21Hjx4129gD1tbD6CxbxR6KZ5la9lC59eA+ywayLCjLxrKH4q0MI8si7tmzx2wLmtVmC0yUlJT4HrcezAf4NcCw/RhefPFF3+PsYX92Ptn1wa5va0EIq1oDAN5//32zbTB0ZyciTlCwExEnKNiJiBMU7ETECQp2IuKEAYNdb28vLr30UkyfPh2lpaW47777AJzKQM6aNQuFhYW4/vrrAy9XLSISDwPuQeF5Hnp6epCamoq+vj7Mnj0bq1evxi9+8QssWLAAdXV1uOWWWzB9+nQsW7aMvllaWhqqqqp821jpiZWOvuCCC8w+nZ2dZluQvRMAe019VuYSdH8H1i89Pd33OFujnzl8+LDZFmSO2cPy1tgBvj8FK1mxyibYeWbnjJVTsPMybtw4s+3QoUO+x3t6esw+bCEAdnPBPrdVlsJKrtjrsZIV9prWfATpA5xaWGDYe1CEQqH+eqW+vj709fUhFArhxRdfxHXXXQcAqK+vx+bNmwd6KRGRhBnU7+xOnDiBiooKZGZmorq6GgUFBUhPT++/M8nLy0NbW1tMByoiMhyDCnbJyclobm5Ga2srmpqahlTJHA6HUVVVhaqqKvpjiohILA0pG5ueno65c+fijTfewKFDh/p//m9tbUVubq5vn8bGRkQiEUQiEZx33nnDH7GISAADBrt9+/b1/2Lw888/x/bt21FcXIy5c+fiT3/6EwBg3bp1mDdvXkwHKiIyHAM+adze3o76+nqcOHECJ0+exMKFC3HNNdegpKQEdXV1uPfee3HJJZdg6dKl8RiviEggA5aeRNOECROQn58P4NQdIytriBeNQ+PQOIbmXBnLmePYvXs39u/fzzt4CVJZWZmotz6LxnE2jeNsGseXnStjGeo49LiYiDhBwU5EnJCwYNfY2Jiotz6LxnE2jeNsGseXnStjGeo44pqgEBFJFP0YKyJOSEiw27ZtG6ZOnYrCwkKsWrUqEUMAAOTn52PatGmoqKgwV2OJhYaGBmRmZqKsrKz/2MGDB1FdXY2ioiJUV1fTVVtiOY4VK1YgNzcXFRUVqKiowNatW2M+jpaWFsydOxclJSUoLS3F6tWrAcR/TqxxxHtOzpVl1axx3Hjjjbjooov654OtWBRNJ06cwCWXXIJrrrkGQID5iElOmDh+/Lg3efJkb9euXd7Ro0e98vJyb+fOnfEehud5njdp0iRv3759cX/fV155xXvzzTe90tLS/mN33XWXt3LlSs/zPG/lypXe3XffnZBx3Hfffd4jjzwS8/c+0549e7w333zT8zzPO3z4sFdUVOTt3Lkz7nNijSPec3Ly5Emvq6vL8zzPO3bsmHfppZd6b7zxhvfd737X27Bhg+d5nvfDH/7Q+/Wvf52QcdTX13t//OMfY/refn7+8597ixYt8q6++mrP87whz0fc7+yamppQWFiIyZMn4/zzz0ddXR22bNkS72Ek1Jw5c5CRkXHWsS1btqC+vh5A/JbM8htHIuTk5GDGjBkATq3hVlxcjLa2trjPiTWOeDtXllWzxpEIra2tePbZZ/GDH/wAwKl1BYc6H3EPdm1tbZg4cWL/3xO5PFQoFMKVV16JyspKhMPhhIzhtI6ODuTk5AA4tddsR0dHwsayZs0alJeXo6GhIS4/Tp9p9+7dePvttzFr1qyEzsmZ4wDiPyfnyrJqXxzH6fm45557UF5ejttuu43uDxstP/7xj/Hwww/379t74MCBIc+H0wmK119/HW+99Raee+45rF27Fq+++mqihwTgVBBO1P+gy5Ytw65du9Dc3IycnBzccccdcXvv7u5u1NbW4tFHH/3SirXxnJMvjiMRczKcZdViOY53330XK1euxPvvv49//etfOHjwIB566KGYjuGvf/0rMjMzUVlZOazXiXuwy83NRUtLS//f2fJQ8RgLAGRmZmL+/PloampKyDgAICsrq39n+/b2dmRmZiZsHMnJyUhKSsLNN98ctznp6+tDbW0tFi9ejAULFvSPJd5zYo0jEXMCBFtWLZbj2LZtG3JychAKhTBixAjcdNNNMZ+PHTt24JlnnkF+fj7q6urw4osv4kc/+tGQ5yPuwW7mzJn44IMP8PHHH+PYsWPYuHEjampq4j0M9PT0oKurq//Pzz///FlZyXirqanBunXrACR2yazTwQUANm3aFJc58TwPS5cuRXFxMW6//fb+4/GeE2sc8Z6Tc2VZNb9xXHzxxf3z4XkeNm/eHPP5WLlyJVpbW7F7925s3LgRl112GdavXz/0+Yhp+sTw7LPPekVFRd7kyZO9Bx54IBFD8Hbt2uWVl5d75eXlXklJSVzHUVdX52VnZ3spKSlebm6u9/jjj3v79+/3LrvsMq+wsNC7/PLLvQMHDiRkHN/73ve8srIyb9q0ad61117r7dmzJ+bjeO211zwA3rRp07zp06d706dP95599tm4z4k1jnjPyTvvvONVVFR406ZN80pLS73777/f87xT1+zMmTO9goIC77rrrvN6e3sTMo65c+d6ZWVlXmlpqbd48eL+jG08vPTSS/3Z2KHOh56gEBEnOJ2gEBF3KNiJiBMU7ETECQp2IuIEBTsRcYKCnYg4QcFORJygYCciTlCwExEnKNiJiBMU7ETECQp2IuIEBTsRcYKCnYg4QcFORJygYCciTlCwExEnKNiJiBMU7ETECQp2IuIEBTsRcYKCnYg4QcFORJygYCciTlCwExEnKNiJiBMU7ETECQp2IuIEBTsRcYKCnYg4QcFORJygYCciTlCwExEnKNiJiBMU7ETECQp2IuIEBTsRcYKCnYg4QcFORJygYCciTlCwExEnKNiJiBMU7ETECQp2ElWlpaV4+eWXEz0MkS8JeZ7nJXoQIkNx4403Ii8vDw888ECihyJfIbqzExEnKNhJVOXn5+OFF17AihUrsHDhQixZsgRpaWkoLS1FJBI569+tXLkSJSUlGDduHG666Sb09vYCAJ588knMnj37rNcNhUL48MMPEQ6HsX79ejz88MNITU3FtddeG9fPJ19dCnYSM8888wzq6upw6NAh1NTU4NZbbz2rff369fjb3/6GXbt24b///e+gfixtbGzE4sWLcffdd6O7uxt/+ctfYjV8+T+jYCcxM3v2bFx11VVITk7G97//fbzzzjtntd96662YOHEiMjIycM8992DDhg0JGqm4QMFOYiY7O7v/z6NGjUJvby+OHz/ef2zixIn9f540aRL27NkT1/GJWxTsJGFaWlr6//zJJ5/gwgsvBACMHj0aR44c6W/bu3fvWf1CoVB8Bij/VxTsJGHWrl2L1tZWHDx4ED/96U9x/fXXAwCmT5+OnTt3orm5Gb29vVixYsVZ/bKysvDRRx8lYMTyVaZgJwlzww034Morr8TkyZNRUFCAe++9FwAwZcoU/OQnP8EVV1yBoqKiL2Vmly5divfeew/p6en4zne+k4CRy1eRioolIfLz8/H444/jiiuuSPRQxBG6sxMRJyjYiYgT9GOsiDhBd3Yi4gQFOxFxgoKdiDhBwU5EnKBgJyJOULATESf8D7x5uPxqPhMcAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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zj0n6YfXfz+ofAL+vWGmVVVbDyqCskiuA36fsWlulRGw8evoElj7ZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScENXSk46ODnOlDDaFba0c4ndjF7YaA9v4h8UsbFOd1tZWM1ZYWGjGrDIBNoYrVqwwY++++64ZS0tLM2OXXXZZyONspRdWQsLGd/DgwWbMWonkmmuuMdswt956qxljK7qwzYmsMWFlImwc2eox7N637ke22jgrc2HnYjHrWrMVZ/ysfPNl+mQnIk5QshMRJyjZiYgTlOxExAlKdiLihKjOxl500UW44oorQsbYHgl+Zh/97AcA8Jlaa08ANqvKHrBmix/87Gc/M2NWH/fs2WO2GTNmjBm7/PLLzRjz8ccfhzzOZqAZa3YXAH7zm9+YsalTp4Y8zmZ+f/SjH5mxqqoqM8auJ5u1tO4dv3sunDx50oyxPvpZVIPtheH33rcWF2AVFizWFfpkJyJOULITESco2YmIE5TsRMQJSnYi4gQlOxFxQtjSk9raWtxxxx1obGxEIBBAeXk5Fi5ciKamJsybNw81NTXIyMjA+vXrMWTIEPpanueZDz6fOHHCbGdNz7MSB7ZePXvYmK2bb72mta8GANTV1ZkxVuaSlZVlxqySm6eeesps8+tf/9qMsbIDNo6/+tWvzJiFPdz+wAMPmLFp06aZMes+eOSRR8w2r732mhljD+cz1iIXgD3GfheKYNeFLRJg7fHA7kW2+AErL6mvrzdj1sIOR44cMduwkjG2CENn+3A/EB8fjxUrVmDv3r145513sHr1auzduxfLly/HtGnTsG/fPkybNs3cBEZE5EIQNtmlpKRgwoQJAM5m8aysLNTX12PTpk0oKSkBAJSUlGDjxo0R7aiISE906zu7mpoa7Ny5E5MnT0ZjYyNSUlIAAMnJyXT7ORGRWOvy42ItLS2YM2cOVq5ced53VIFAwPybv6KiAhUVFQD8fxciItJTXfpk197ejjlz5mD+/Pm46aabAADDhw9HQ0MDAKChocH8grC8vBzBYBDBYJBODIiIRFLYZOd5HsrKypCVlYX77ruv83hRURHWrFkDAFizZg1uuOGGyPVSRKSHAh6rOwCwY8cOXHXVVRg3blzn1O/SpUsxefJkzJ07F5988gnS09Oxfv16DB06lJ4sISEB2dnZIWMffPCB2S4xMTHkcTZtzz5FshVRWOmJVQLjt3SjpaXFjPmZ7n/55ZfNNtOnTzdjbPUY9t6s/SlYycSTTz5pxm6//XYzxsoOysrKQh5/6aWXzDbsXmUrkbDVRti9Y40Ju09ZOQjrB1ulxDofuwfY3g/sujDW7y4rm2FfgyUnJyMYDNJzhv3ObsqUKeYN//rrr4drLiJyQdATFCLiBCU7EXGCkp2IOEHJTkScoGQnIk6I6oY77e3t5koIrAzDmhZnpSdsSpyVCLApfasfrHygqanJjLHSAj8F2Ndee2232wC8PGb79u1mzFqpZuXKlWYbVl7CxmPx4sVm7E9/+lPI46yMga3Iwe4Pa9UQgJfcWNg9zMaDYRs5WfyUXIVrx8bfur8PHTpktmFjlZycbMa+oE92IuIEJTsRcYKSnYg4QclORJygZCciTlCyExEnRLX0pE+fPkhISAgZGz58uNnOWoiAre5w6tSp7nXu//Xv37/bbdgUO5suZxv1sBIH6zXZyhWsvISVOFx++eVm7K233gp5PC8vz2zDNlR5+umnzRgrZ7n00ktDHmfjwUqd/N5XbMMpa6UdVtbB7kXWbuDAgWbMunciUV7CVheyfqetawnwe7gr9MlORJygZCciTlCyExEnKNmJiBOU7ETECVGdje3o6DAfUmYzN9ba8+yhfbZ3AnvInj3Mbc2Qsgev2fti/WD9t2ZP2WwVez0Wy8jIMGPp6elmzHLjjTeasZ07d5qxAQMGmDFrJpFdSzZWx48fN2PserKZWqsdW7CC7bnA2rE9I6yxYuPBZmr97qFhvTc2E/7ZZ5+ZMWt3wy/TJzsRcYKSnYg4QclORJygZCciTlCyExEnKNmJiBPClp7U1tbijjvuQGNjIwKBAMrLy7Fw4UIsXrwYzzzzDIYNGwYAWLp0KWbNmkVfKy4uDomJiSFjbK8Ga/EANrXNShXYlD57+Jo9nG/xuwcFm2a3+sgepGd7P7AFCVhJwrFjx0Ief/TRR802H374oRkbOnSoGWPXxbqe1n3D2gC8nII9ZM9KeKxFCVgJCbuH2UIGrP/Wa7IyHVZSw66Ln/Iv9jvBylK6Imyyi4+Px4oVKzBhwgScOHEC+fn5mDFjBgBg0aJFeOCBB3rUARGRaAib7FJSUpCSkgIAGDRoELKysujOTCIiF6JufWdXU1ODnTt3YvLkyQCAVatWITc3F6WlpTh69GhEOigi0hu6nOxaWlowZ84crFy5EhdffDHuueceVFdXo6qqCikpKbj//vtDtquoqEBBQQEKCgroQpYiIpHUpWTX3t6OOXPmYP78+bjpppsAnF1ZOC4uDn369MHdd9+NysrKkG3Ly8sRDAYRDAbpyrEiIpEUNtl5noeysjJkZWXhvvvu6zze0NDQ+e8NGzZg7NixkemhiEgvCHhsfhjAjh07cNVVV2HcuHGd0+RLly7F2rVrUVVVhUAggIyMDDz99NOdExmWuLg4sxyAlQJYKxqwKXG2Nr5VMgHwFSOsfrCVMFiMnWv69OlmbNKkSSGPr1q1ymxz5ZVXmrGHH37YjL344otm7NVXXw15/KOPPjLbsPISVtrDxsoqm2DlFKzchpU4HD582IyxXyVrHwfWD4aVNFnlXYC//UvY7wtr56dM58SJE2YbZsyYMQgGg/Rnws7GTpkyJWTHwtXUiYhcSPQEhYg4QclORJygZCciTlCyExEnKNmJiBPClp70psTERBQWFoaM7d+/32z3/e9/P+RxNiWemppqxhYtWmTGcnNzzdgPf/jDbp9r48aNZuyFF14wY6WlpWbMWmmClXxs2rTJjH3x+F8o1157rRmzNmJ59tlnzTaXXHKJGZs9e7YZ++c//2nGXnvttZDHWWnSbbfdZsYyMzPNGHtvBw4cMGN5eXkhj8+bN89ss3v3bjO2bt06MzZhwgQz9q1vfSvk8erqarPNm2++acbY9bzrrrvM2MGDB0MeX716tdnmqquuMmO1tbVhS0/0yU5EnKBkJyJOULITESco2YmIE5TsRMQJSnYi4oSwCwH0plOnTuG///1vyBgrI/nDH/4Q8jhbnYKtoGGVTAC8fMOa7h85cqTZZvv27WaMlSq88sorZsxaKYNt0sMWTmVlPzt27DBjVmmHVVYA8NVLtmzZYsbq6urMmLWyDFtxhp2LlR+xFblZqcu///3vkMfZhjVshRW2Mc0HH3xgxqzVUtgGPmwcv7zU21exe99a3YS9r/fff9+Msc2VvqBPdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJ0R11ZO+fftiyJAhIWNs2t7auIOVU7ANfNj09hebCnXnNVn5AHs9NqXP+mht3sJKalg/2DiyEp4zZ8706uuxe4D132L1D+Cb47CSpuPHj5sxPxsGsTZ++8jG0cLGyrrfAL6p0YABA8yYn+vJznXFFVdo1RMREUDJTkQcoWQnIk5QshMRJyjZiYgTwi4E0NbWhsLCQnz++ec4ffo0br75ZixZsgT79+9HcXExjhw5gvz8fPz+97+nM0tfsGYZ2QPi1mwsm3300weAzyAdOXIk5PFBgwaZbdj7YjNqbDY5Li4u5HE2C8dm9thsm3UuFmPXhY193759zRibvbMWQGALI7DrzMaRXTM/Y8xmrtl1YX1krzl48OCQx9lCABdddJEZY31kM9fWa7J7h52rK8J+suvfvz/eeOMN7Nq1C1VVVdi6dSveeecd/PSnP8WiRYvw0UcfYciQIXjuued61BERkUgKm+wCgUDnJ6v29na0t7cjEAjgjTfewM033wwAKCkpobtoiYjEWpe+s+vo6MD48eORlJSEGTNmYOTIkUhMTOz8WJmWlob6+vqIdlREpCe6lOzi4uJQVVWFuro6VFZW0kX0vqqiogIFBQUoKCigVdoiIpHUrdnYxMRETJ06FW+//Taam5s7v0ysq6szN4ouLy9HMBhEMBj09YiIiEhvCJt9Dh06hObmZgBnZ7deffVVZGVlYerUqfjzn/8MAFizZg1uuOGGiHZURKQnws7lNjQ0oKSkBB0dHThz5gzmzp2L6667DtnZ2SguLsYjjzyCK6+8EmVlZeFPFh+PoUOHhoyxUouTJ0+GPM7KItgUNiuRYdPlVtkBKwNgU/qsjMHPA9asrIONr5/FDwC7tIO9Hhsrdi5WTmEtxJCYmGi2YSVBfr9u8buwg4WNFSt3YveO9XvByn6s/SIA/jvISlasa836wd5XV4RNdrm5udi5c+d5xzMzM1FZWdmjk4uIRIu+RBMRJyjZiYgTlOxExAlKdiLiBCU7EXFCz5YR6KaEhAQkJCQAOFu/N2zYsM5YZmZmNLvS6av9iBX1Q/34OvQDuHD68uV+1NTUhG/gxUh+fn6sTn0O9eNc6se51I/zXSh96W4/9GesiDhByU5EnBCzZFdeXh6rU59D/TiX+nEu9eN8F0pfutuPqG6SLSISK/ozVkScoGQnIk6ISbLbunUrrrjiCowaNQrLly+PRRcAABkZGRg3bhzGjx+PgoKCqJ23tLQUSUlJGDt2bOexpqYmzJgxA6NHj8aMGTNw9OjRmPRj8eLFSE1Nxfjx4zF+/Hi89NJLEe9HbW0tpk6diuzsbOTk5ODJJ58EEP0xsfoR7TFpa2vDpEmTkJeXh5ycHDz66KMAgP3792Py5MkYNWoU5s2bR5eAimQ/FixYgMsvv7xzPKqqqiLajy90dHTgyiuvxHXXXQfAx3hEpACGOH36tJeZmelVV1d7n3/+uZebm+vt2bMn2t3wPM/z0tPTvUOHDkX9vG+99Zb33nvveTk5OZ3HfvKTn3jLli3zPM/zli1b5j344IMx6cejjz7qPfHEExE/95cdOHDAe++99zzP87zjx497o0eP9vbs2RP1MbH6Ee0xOXPmjHfixAnP8zzv1KlT3qRJk7y3337b++53v+utXbvW8zzP+973vuc99dRTMelHSUmJ98ILL0T03KGsWLHCu+WWW7zvfOc7nud53R6PqH+yq6ysxKhRo5CZmYl+/fqhuLgYmzZtinY3YqqwsPC8RUw3bdqEkpISANHbrS1UP2IhJSUFEyZMAHB2UcqsrCzU19dHfUysfkTbhbKjn9WPWKirq8OWLVtw1113ATi7R293xyPqya6+vh4jRozo/O9Y7kwWCAQwc+ZM5Ofno6KiIiZ9+EJjYyNSUlIAAMnJyWhsbIxZX1atWoXc3FyUlpZG5c/pL6upqcHOnTsxefLkmI7Jl/sBRH9MLpQd/b7ajy/G4+GHH0Zubi4WLVpEV33uLT/+8Y/x+OOPd66CfeTIkW6Ph9MTFDt27MC//vUvvPzyy1i9ejW2b98e6y4BOJuEY/V/0HvuuQfV1dWoqqpCSkoK7r///qidu6WlBXPmzMHKlStx8cUXnxOL5ph8tR+xGJOe7OgXyX7s3r0by5Ytw/vvv493330XTU1N+OUvfxnRPmzevBlJSUnIz8/v0etEPdmlpqaitra287/ZzmTR6AsAJCUlYfbs2TFdZn748OFoaGgAcHbfj6SkpJj1Iy4uDn369MHdd98dtTFpb2/HnDlzMH/+fNx0002dfYn2mFj9iMWYAP529ItkP7Zu3YqUlBQEAgH0798fd955Z8TH4+9//ztefPFFZGRkoLi4GG+88QYWLlzY7fGIerKbOHEi9u3bh/379+PUqVNYt24dioqKot0NtLa2dm4k0traildeeeWcWcloKyoqwpo1awDEdre2L5ILAGzYsCEqY+J5HsrKypCVlYX77ruv83i0x8TqR7TH5ELZ0S9UP8aMGdM5Hp7nYePGjREfj2XLlqGurg41NTVYt24drr76ajz//PPdH4+ITp8YtmzZ4o0ePdrLzMz0HnvssVh0wauurvZyc3O93NxcLzs7O6r9KC4u9pKTk734+HgvNTXVe/bZZ73Dhw97V199tTdq1Chv2rRp3pEjR2LSj9tuu80bO3asN27cOO/666/3Dhw4EPF+/O1vf/MAeOPGjfPy8vK8vLw8b8uWLVEfE6sf0R6TXbt2eePHj/fGjRvn5eTkeEuWLPE87+w9O3HiRG/kyJHezTff7LW1tcWkH1OnTvXGjh3r5eTkePPnz++csY2GN998s3M2trvjocfFRMQJTk9QiIg7lOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QshMRJyjZiYgTlOxExAlKdiLiBCU7EXGCkp2IOEHJTkScoGQnIk5QspNelZOTg23btsW6GyLnCXie58W6EyLdsWDBAqSlpeGxxx6LdVfka0Sf7ETECUp20qsyMjLw2muvYfHixZg7dy7uuOMODBo0CDk5OQgGg+f83LJly5CdnY0hQ4bgzjvvRFtbGwDgd7/7HaZMmXLO6wYCAXz00UeoqKjA888/j8cffxwDBw7E9ddfH9X3J19fSnYSMS+++CKKi4vR3NyMoqIi3HvvvefEn3/+efz1r39FdXU1Pvzwwy79WVpeXo758+fjwQcfREtLC/7yl79EqvvyP0bJTiJmypQpmDVrFuLi4nD77bdj165d58TvvfdejBgxAkOHDsXDDz+MtWvXxqin4gIlO4mY5OTkzn8PGDAAbW1tOH36dOexESNGdP47PT0dBw4ciGr/xC1KdhIztbW1nf/+5JNPcNlllwEAEhIScPLkyc7YwYMHz2kXCASi00H5n6JkJzGzevVq1NXVoampCb/4xS8wb948AEBeXh727NmDqqoqtLW1YfHixee0Gz58OD7++OMY9Fi+zpTsJGZuvfVWzJw5E5mZmRg5ciQeeeQRAMA3v/lN/PznP8f06dMxevTo82Zmy8rKsHfvXiQmJuLGG2+MQc/l60hFxRITGRkZePbZZzF9+vRYd0UcoU92IuIEJTsRcYL+jBURJ+iTnYg4QclORJygZCciTlCyExEnKNmJiBOU7ETECf8HPLLl6rOcz3YAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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R8EYAVVVVysvLU2Njo27duqWpU6fqscceU2pqqnJzc7V48WINHjzY75d+ASDaeOAOgHseD9wBgE8RdgCsQNgBsAJhB8AKhB0AK0T0GRRxcXFKSkqSdPv6ve7du0dy802iDuqgjpa5W2r5fB3l5eWBFwh4X5Qwac4tWSKBOu5EHXeiji+6W2ppaR0cxgKwAmEHwApRC7vCwsJobfoO1HEn6rgTdXzR3VJLS+uI6NfFACBaOIwFYAXCDoAVohJ2O3bs0Ne+9jX17dtXRUVF0ShBkpSUlKSBAwdq0KBBEb2TckFBgeLj45Wenu6bVltbq+zsbPXr10/Z2dm6cOFCVOpYtmyZEhMTNWjQIA0aNEh/+ctfwl7H6dOnNWbMGKWmpiotLU2//vWvJUV+TJzqiPSYXL9+XcOHD1dmZqbS0tK0dOlSSdKJEyc0YsQI9e3bV9OmTdPNmzejUkd+fr6++tWv+sajrKwsrHV8prGxUYMHD9Zjjz0mKYjxCMsFMH40NDSYPn36mOPHj5sbN26YjIwMc+TIkUiXYYwxpnfv3ubcuXMR3+6+ffvM+++/b9LS0nzTfvCDH5iVK1caY4xZuXKl+eEPfxiVOpYuXWpeeOGFsG/78yorK837779vjDHmv//9r+nXr585cuRIxMfEqY5Ij8mtW7dMXV2dMcaYmzdvmuHDh5v33nvPPPHEE2bz5s3GGGO+853vmN/97ndRqSMvL8+8/vrrYd12U1avXm2mT59uxo8fb4wxLR6PiO/ZHTx4UH379lWfPn3Url075ebmqri4ONJlRNWoUaPUtWvXO6YVFxcrLy9PUuSe1tZUHdHgdrs1ZMgQSVLHjh2VkpKiioqKiI+JUx2Rdrc80c+pjmg4c+aMSkpKNGfOHEmSMabF4xHxsKuoqFCvXr18r6P5ZDKXy6Vx48bJ4/HI6/VGpYbPVFdXy+12S5ISEhJUXV0dtVrWrl2rjIwMFRQURORw+vPKy8t16NAhjRgxIqpj8vk6pMiPyd3yRL//r+Oz8Vi0aJEyMjI0f/583bhxI+x1fP/739cvfvELtWlzO7LOnz/f4vGw+gTF/v379cEHH+itt97SunXr9Le//S3aJUm6HcLR+gs6d+5cHT9+XGVlZXK73Vq4cGHEtn358mXl5ORozZo16tSp0x19kRyT/68jGmPSmif6hbOODz/8UCtXrtRHH32kf/7zn6qtrdWqVavCWsP27dsVHx8vj8fTqvVEPOwSExN1+vRp32t/TyaLRC2SFB8fr8mTJ+vgwYNRqUOSevTooaqqKkm3n/sRHx8ftTpiYmLUpk0bPfPMMxEbk/r6euXk5GjGjBl6/PHHfbVEekyc6ojGmEjBPdEvnHXs2LFDbrdbLpdL7du319NPPx328Xj33Xf15z//WUlJScrNzdXu3bs1b968Fo9HxMNu2LBhOnbsmE6cOKGbN29qy5YtmjhxYqTL0JUrV1RXV+f7+Z133rnjrGSkTZw4URs3bpQU3ae1fRYukrR169aIjIkxRrNnz1ZKSooWLFjgmx7pMXGqI9Jjcrc80a+pOgYMGOAbD2OMtm3bFvbxWLlypc6cOaPy8nJt2bJFY8eO1Z/+9KeWj0dYT584KCkpMf369TN9+vQxP/vZz6JRgjl+/LjJyMgwGRkZJjU1NaJ15ObmmoSEBBMbG2sSExPN+vXrTU1NjRk7dqzp27evycrKMufPn49KHTNnzjTp6elm4MCBZsKECaaysjLsdfz97383kszAgQNNZmamyczMNCUlJREfE6c6Ij0mhw8fNoMGDTIDBw40aWlpZvny5caY2+/ZYcOGmeTkZDNlyhRz/fr1qNQxZswYk56ebtLS0syMGTN8Z2wjYc+ePb6zsS0dD74uBsAKVp+gAGAPwg6AFQg7AFYg7ABYgbADYAXCDoAVCDsAViDsAFiBsANgBcIOgBUIOwBWIOwAWIGwA2AFwg6AFQg7AFYg7ABYgbADYAXCDoAVCDsAViDsAFiBsANgBcIOgBUIOwBWIOwAWIGwA2AFwg6AFQg7AFYg7ABYgbADYAXCDoAVCDsAViDsAFiBsANgBcIOgBUIOwBWIOwAWIGwA2AFwg6AFQg7AFYg7HBXefbZZ/XTn/40ZOtLSkrSrl27QrY+3Ltio10A8Hm///3vo10CvqTYs0OLNTQ0WLVdfDkQdmiWpKQkrVq1ShkZGbr//vu1f/9+ff3rX1fnzp2VmZmpvXv3+uYdPXq0fvzjH2v48OHq1KmTJk2apNraWl//E088oYSEBD3wwAMaNWqUjhw54uvLz8/X4sWLJUl79+5Vz549tWrVKiUkJOjpp5/WrVu3VFRUpOTkZMXFxWnq1Kl3rHvTpk3q3bu34uLi9POf/zz8A4N7BmGHZtu8ebNKSkr08ccfa9KkSVq8eLFqa2v1y1/+Ujk5OTp37pxv3j/84Q/asGGDqqqqFBsbq+9973u+vkcffVTHjh3T2bNnNWTIEM2YMcNxm5988olqa2t18uRJeb1e/fa3v9W2bdu0b98+VVZWqkuXLvrud78rSTp69Kjmzp2rTZs2qbKyUufPn9eZM2fCNyC4txigGXr37m1efvllY4wxRUVFZubMmXf0jxs3zrzyyivGGGO++c1vmueff97Xd+TIEdO2bVvT0NDwhfVeuHDBSDIXL140xhiTl5dnFi1aZIwxZs+ePaZt27bm2rVrvvkHDBhgdu3a5XtdWVlpYmNjTX19vVm+fLmZNm2ar+/y5cumbdu2ZufOna399fElwJ4dmq1Xr16SpJMnT+r1119X586dfW3//v2qqqr6wryS1Lt3b9XX16umpkaNjY360Y9+pOTkZHXq1ElJSUmSpJqamia32b17d913332+1ydPntTkyZN9201JSVFMTIyqq6tVWVl5x3bvv/9+xcXFhXIIcA/jbCyazeVySbodZLNmzdJLL73kOO/p06d9P586dUpt27ZVt27d9Oqrr6q4uFi7du1SUlKSLl26pC5dusgY43ebn+nVq5c2bNigkSNHfmFet9utf/3rX77XV69e1fnz51v0O+LLiz07tNjMmTP15ptv6u2331ZjY6OuX7+uvXv33vH52B//+EcdPXpUV69e1ZIlSzRlyhTFxMSorq5O7du3V1xcnK5evaqf/OQnLdr2s88+q0WLFunkyZOSpHPnzqm4uFiSNGXKFG3fvl379+/XzZs3tWTJEt26dSt0vzjuaYQdWqxXr14qLi7WihUr1L17d/Xq1UsvvPDCHcEya9Ys5efnKyEhQdevX9dvfvMbSdJTTz2l3r17KzExUampqXrooYdatO158+Zp4sSJGjdunDp27KiHHnpI//jHPyRJaWlpWrdunZ588km53W516dJFPXv2DN0vjnuayzgdPwBBGj16tGbOnKk5c+ZEuxTAhz07AFYg7ABYgcNYAFZgzw6AFQg7AFYg7ABYgbADYAXCDoAVCDsAVvgfLBXm8BXAFEcAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9F5U6XnrpJbNu3bqw9/1F9fX15sMPPzTGGPO///3PjBgxwpw8eTLiY+KrjkiPyfXr101bW5sxxphr166ZiRMnmvfff988+uijZtu2bcYYY77//e+b3//+91Gpo7Cw0OzYsSOsfd/Mb37zG/P444+bhx9+2Bhjbns8In5kd+zYMaWmpiolJUW9evVSQUGBysvLI11GVE2ePFkDBw7ssq68vFyFhYWSIvfIrJvVEQ0ul0vjxo2TJMXGxiotLU11dXURHxNfdUTanfJYNV91RENtba127dqlp59+WpJkjLnt8Yh42NXV1SkpKcn7PpqPh3I4HJo2bZrcbrc8Hk9UavhcY2OjXC6XJCkhIUGNjY1Rq2Xjxo3KyspSUVFRRE6nv6i6ulrHjx/XpEmTojomX6xDivyY3CmPVftyHZ+Px/Lly5WVlaXFixfr6tWrYa/jxz/+sX71q1+pR4/PIqu5ufm2x8PqGxSHDx/WP//5T/3tb3/TK6+8ovfeey/aJUn6LISj9T/ookWLVFVVpcrKSrlcLi1dujRifV+4cEH5+flav369+vXr16UtkmPy5TqiMSbdeaxaOOv46KOPtGbNGn3yySf64IMP1NLSorVr14a1hrffflvx8fFyu93d2k/Ewy4xMVE1NTXe9/4eDxWJWiQpPj5eM2fO1LFjx6JShyQNGTJEDQ0Nkj57+EJ8fHzU6oiJiVGPHj30zDPPRGxM2tvblZ+frzlz5uiRRx7x1hLpMfFVRzTGRArusWrhrGPPnj1yuVxyOBzq3bu3nnrqqbCPx5EjR/TXv/5VycnJKigo0P79+/Xss8/e9nhEPOwmTJigU6dO6fTp07p27Zq2b9+uvLy8SJehixcvqq2tzfv6nXfe6XJXMtLy8vJUWloqKbqPzPo8XCRp586dERkTY4wWLFigtLQ0LVmyxLs+0mPiq45Ij8md8li1m9UxatQo73gYY1RWVhb28VizZo1qa2tVXV2t7du3a8qUKXrjjTdufzzCevvEh127dpkRI0aYlJQU84tf/CIaJZiqqiqTlZVlsrKyzOjRoyNaR0FBgUlISDBOp9MkJiaa1157zTQ1NZkpU6aY1NRUM3XqVNPc3ByVOubOnWsyMjJMZmam+d73vmfq6+vDXsehQ4eMJJOZmWnGjBljxowZY3bt2hXxMfFVR6TH5MSJEyY7O9tkZmaa9PR0s3r1amPMZ39nJ0yYYIYPH25mzZplrly5EpU6cnJyTEZGhklPTzdz5szx3rGNhAMHDnjvxt7uePANCgBWsPoGBQB7EHYArEDYAbACYQfACoQdACsQdgCsQNgBsAJhB8AKhB0AKxB2AKxA2AGwAmEHwAqEHQArEHYArEDYAbACYQfACoQdACsQdgCsQNgBsAJhB8AKhB0AKxB2AKxA2AGwAmEHwAqEHQArEHYArEDYAbACYQfACoQdACsQdgCsQNgBsAJhB8AKhB0AKxB2AKxA2AGwAmEHwAqEHQArEHYArEDYAbACYQfACoQdACsQdgCsQNgBsAJhh6hZuHChfv7zn4dsf8nJydq3b1/I9oe7C2GHqPnDH/6gn/3sZxHpa926dcrIyFBsbKzuvfderVu3LiL94s7hjHYBuHN1dHTI6YzOX5FQ922M0ZYtW5SVlaWqqipNmzZNSUlJKigoCFkfuLNxZIcukpOTtXbtWmVlZalPnz7q6OjQ0aNH9c1vflP9+/fXmDFjdPDgQe/2DzzwgH76059q4sSJ6tevn2bMmKGWlhZv+6OPPqqEhATdc889mjx5sk6ePOltmz9/vlasWCFJOnjwoIYOHaq1a9cqISFBTz31lK5fv66SkhINHz5ccXFxmj17dpd9b926VcOGDVNcXJx++ctf+v25nnvuOY0bN05Op1MjR47UjBkzdOTIkRCNGr4KCDvcYNu2bdq1a5fOnz+vxsZGPfzww1qxYoVaWlr061//Wvn5+Tp37px3+y1btmjz5s1qaGiQ0+nUj370I2/bd77zHZ06dUpnz57VuHHjNGfOHJ/9fvrpp2ppadGZM2fk8Xj0u9/9TmVlZXr33XdVX1+vAQMG6Ac/+IEk6eOPP9aiRYu0detW1dfXq7m5WbW1tbf08xljdOjQIaWnpwc5QvhKMsAXDBs2zGzatMn7vqSkxMydO7fLNtOmTTOvv/66McaYb3/72+b555/3tp08edL07NnTdHR03LDv1tZWI8mcP3/eGGNMYWGhWb58uTHGmAMHDpiePXuay5cve7cfNWqU2bdvn/d9fX29cTqdpr293axevdo89thj3rYLFy6Ynj17mr179wb8GVeuXGmysrLMlStXAm6LuwfX7HCDpKQk7+szZ85ox44deuutt7zr2tvblZOTc9Pthw0bpvb2djU1NWnQoEFavny5duzYoXPnzqlHj89OJJqamnTPPffc0O/gwYP1ta99rUvfM2fO9H5OkmJiYtTY2Kj6+vou/fbp00dxcXEBf7aNGzdqy5YtOnTokHr37h1we9w9CDvcwOFweF8nJSXpySef1B//+Eef29fU1Hhf/+c//1HPnj01aNAg/fnPf1Z5ebn27dun5ORk/fe//9WAAQNkjAnY7+d9b968Wd/61rdu2Nblculf//qX9/2lS5fU3Nzs9+favHmzSkpK9N5772no0KF+t8Xdh2t28Gvu3Ll666239Pe//12dnZ26cuWKDh482OX62J/+9Cd9/PHHunTpklauXKlZs2YpJiZGbW1t6t27t+Li4nTp0iW9+OKLt9X3woULtXz5cp05c0aSdO7cOZWXl0uSZs2apbfffluHDx/WtWvXtHLlSl2/ft3nvt544w29+OKL2rt3r1JSUoIYCXzVEXbwKykpSeXl5Xr55Zc1ePBgJSUlad26dV2C5cknn9T8+fOVkJCgK1eu6Le//a0kad68eRo2bJgSExM1evRo3X///bfV97PPPqu8vDxNmzZNsbGxuv/++/WPf/xDkpSenq5XXnlFTzzxhFwulwYMGOD3aG3FihVqbm7WhAkT1LdvX/Xt21cLFy4MYkTwVeUwvs4pgFvwwAMPaO7cuXr66aejXQrgF0d2AKxA2AGwAqexAKzAkR0AKxB2AKxA2AGwAmEHwAqEHQArEHYArPB/iiGZSYp7+8gAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def crop_cell(cell_img, debug=False):\n",
    "    if debug:\n",
    "        view(cell_img, \"input\")\n",
    "    ret,cell_img = cv2.threshold(cell_img,155,255,cv2.THRESH_TOZERO)\n",
    "    cell_img = zap_lower_horiz_lines(cell_img)\n",
    "\n",
    "    contours, hierarchy = cv2.findContours(cell_img,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)\n",
    "    # Find the largest contour by area\n",
    "    areas = [cv2.contourArea(c) for c in contours]\n",
    "    contour = contours[np.argmax(areas)]\n",
    "    stencil = np.zeros(cell_img.shape).astype(cell_img.dtype)\n",
    "    stencil = cv2.drawContours(stencil, [contour], 0, 1, -1)\n",
    "    cell_img = cv2.bitwise_and(cell_img, cell_img, mask=stencil)\n",
    "    if False:\n",
    "        view(cell_img, \"first\")\n",
    "\n",
    "    # cut then resize rect area to 24x24 (2px border)\n",
    "    rect = cv2.boundingRect(contour)\n",
    "    center = ((rect[0]+int(rect[2]*0.5), (rect[1]+int(rect[3]*0.5))));\n",
    "    translate_x = 14 - center[0]\n",
    "    translate_y = 14 - center[1]\n",
    "    translation_matrix = np.float32([ [1,0,translate_x], [0,1,translate_y] ])\n",
    "    img_translation = cv2.warpAffine(cell_img, translation_matrix, (28, 28))\n",
    "    if debug:\n",
    "        view(img_translation, \"crop region\")\n",
    "    return img_translation\n",
    "\n",
    "page = \"pages/43290879-California-101393-0014.jpeg\"\n",
    "cells = list(generateCellImages(page))\n",
    "for image in cells[:20]:\n",
    "    crop_cell(image, debug=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "## Transpose ENMIST Letters to a Readable Orientation\n",
    "\n",
    "Now that we have a 28x28 square census image, let's make sure that we unrotate and unflip the EMNIST images so that they look like the normal readable letters from the Census. In order to do that we are going to use a TensorFlow *map()* operation to apply the same function, in a streaming fashion as needed, to every image in the training and testing sets. The function we will apply to every image is the TensorFlow *transpose()* function, which is the one recommended in the dataset notes. You can see that our preview grid is now readable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-01-16 11:45:06.968711: W tensorflow/core/kernels/data/cache_dataset_ops.cc:858] The calling iterator did not fully read the dataset being cached. In order to avoid unexpected truncation of the dataset, the partially cached contents of the dataset  will be discarded. This can happen if you have an input pipeline similar to `dataset.cache().take(k).repeat()`. You should use `dataset.take(k).cache().repeat()` instead.\n",
      "2025-01-16 11:45:06.973259: W tensorflow/core/framework/local_rendezvous.cc:404] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x576 with 9 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "\n",
    "import tensorflow_datasets as tfds\n",
    "(ds_train, ds_test), ds_info = tfds.load(\n",
    "    'emnist/letters',\n",
    "    split=['train', 'test'],\n",
    "    shuffle_files=True,\n",
    "    as_supervised=True,\n",
    "    with_info=True,\n",
    ")\n",
    "\n",
    "ds_train_readable = ds_train.map(\n",
    "  lambda img, label: (tf.transpose(img, perm=[1,0,2]), label),\n",
    "  num_parallel_calls=tf.data.AUTOTUNE, \n",
    "  deterministic=True)\n",
    "\n",
    "plt.figure(figsize=(8, 8))\n",
    "for i, (img, lbl) in enumerate(ds_train_readable.take(9)):\n",
    "    ax = plt.subplot(3, 3, i + 1)\n",
    "    plt.imshow(img)\n",
    "    plt.title(str(int(lbl)))\n",
    "    plt.axis(\"off\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Applying Functions (Mapping) and Normalizing to Floating Point Values\n",
    "\n",
    "We have shown some examples of the transformations that we need, both to the Census images and to the EMNIST letters training and testing data. Now we will apply those tranformation to the EMNIST training and testing data. Each transformation is applied in a series of steps using the *map()* function.\n",
    "\n",
    "This code is a bit hard to read. When training our model the TensorFlow API will pull data from the training dataset. As each training image is prepared for use, it will apply our mapped functions. This code tells the TensorFlow API which functions are mapped onto the dataset and in what order they are to be applied. The testing dataset is prepared similarly.\n",
    "\n",
    "### Further Details\n",
    "\n",
    "For those interested in more detail. The TensorFlow API likes to precache and batch training data for performance reasons. The API user has to define the size of these batches. Batches have the effect of reshaping the data, adding a dimension to the tensor arrays for holding the batch index. So instead of a 28x28 image and a label, after batching you have a 128x28x28 array of data. This can be pretty confusing to those new to TensorFlow and makes it harder to interpret training error messages about the shape and dimensionality of the training data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "initial element spec (TensorSpec(shape=(28, 28, 1), dtype=tf.uint8, name=None), TensorSpec(shape=(), dtype=tf.int64, name=None))\n",
      "final element_spec (TensorSpec(shape=(None, 28, 28, 1), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.int64, name=None))\n",
      "final test element_spec (TensorSpec(shape=(None, 28, 28, 1), dtype=tf.float32, name=None), TensorSpec(shape=(None,), dtype=tf.int64, name=None))\n"
     ]
    }
   ],
   "source": [
    "import tensorflow_datasets as tfds\n",
    "\n",
    "(ds_train, ds_test), ds_info = tfds.load(\n",
    "    'emnist/letters',\n",
    "    split=['train', 'test'],\n",
    "    shuffle_files=True,\n",
    "    as_supervised=True,\n",
    "    with_info=True,\n",
    ")\n",
    "\n",
    "print(\"initial element spec\", ds_train.element_spec)\n",
    "\n",
    "ds_train_readable = ds_train.map(\n",
    "  lambda img, label: (tf.transpose(img, perm=[1,0,2]), label),\n",
    "  num_parallel_calls=tf.data.AUTOTUNE, \n",
    "  deterministic=True)\n",
    "\n",
    "# Mapping the noisy line function to the dataset..\n",
    "#ds_train_readable_noisy = ds_train_readable.map(\n",
    "#  lambda img, label: tf.numpy_function(func=noisy_line, inp=[img, label], Tout=(tf.uint8, tf.int64)),\n",
    "#  num_parallel_calls=tf.data.AUTOTUNE, \n",
    "#  deterministic=False)\n",
    "\n",
    "# Function to convert image pixel values to floating point between 0 and 1.\n",
    "def normalize_img(image, label):\n",
    "  \"\"\"Normalizes images: `uint8` -> `float32`.\"\"\"\n",
    "  return tf.cast(image, tf.float32) / 255., label\n",
    "\n",
    "# Mapping the normalize function to the dataset\n",
    "ds_train_readable_float = ds_train_readable.map(normalize_img, num_parallel_calls=tf.data.AUTOTUNE)\n",
    "\n",
    "def set_shapes(image, label):\n",
    "  image.set_shape([28, 28, 1])\n",
    "  label.set_shape([])\n",
    "  return image, label\n",
    "\n",
    "# Assert the correct tensor shapes\n",
    "ds_train_final = ds_train_readable_float.map(set_shapes, num_parallel_calls=tf.data.AUTOTUNE)\n",
    "\n",
    "# Some additional dataset setup steps\n",
    "ds_train_final = ds_train_final.cache()\n",
    "ds_train_final = ds_train_final.batch(128)  # This changes the shape of the data, so call it after all mapped functions..\n",
    "ds_train_final = ds_train_final.prefetch(tf.data.AUTOTUNE)\n",
    "print(\"final element_spec\", ds_train_final.element_spec)\n",
    "\n",
    "# Then we need to apply the same functions and settings to the test dataset\n",
    "ds_test_readable = ds_test.map(\n",
    "  lambda img, label: (tf.transpose(img, perm=[1,0,2]), label),\n",
    "  num_parallel_calls=tf.data.AUTOTUNE, \n",
    "  deterministic=True)\n",
    "\n",
    "# ds_test_readable_noisy = ds_test_readable.map(\n",
    "#   lambda img, label: tf.numpy_function(func=noisy_line, inp=[img, label], Tout=(tf.uint8, tf.int64)),\n",
    "#   num_parallel_calls=tf.data.AUTOTUNE, \n",
    "#   deterministic=False)\n",
    "\n",
    "ds_test_readable_float = ds_test_readable.map(normalize_img, num_parallel_calls=tf.data.AUTOTUNE)\n",
    "ds_test_final = ds_test_readable_float.map(set_shapes, num_parallel_calls=tf.data.AUTOTUNE)\n",
    "ds_test_final = ds_test_final.batch(128)\n",
    "ds_test_final = ds_test_final.cache()\n",
    "ds_test_final = ds_test_final.prefetch(tf.data.AUTOTUNE)\n",
    "print(\"final test element_spec\", ds_test_final.element_spec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above you can see that the final element spec is 4-dimensional, including the dimension used for the batch index. The final datatype has changed to floating point, i.e. values between zero and one. Even the labels in the 2nd part of the element spec tuple have changed shap to reflect the batching dimension.\n",
    "\n",
    "## Defining and Training a Machine Learning Model\n",
    "\n",
    "We are going to define the most straightforward machine learning model first and customize it for our parameters and the output we want. This model is defined as a sequence that takes in a 28 by 28 tensor array. The input is first flattened into a 784 long tensor array of one dimension (28 times 28). Then each of these *input features* is connected to each of the units in the subsequent neural network layer. The dense NN layer stores weights associated with each of these connections and those weights are used to determine the value each unit will pass to the next layer in the model. These weights are adjusted during training. An activation formular (relu) is supplied to this layer. The default activation formation is \"linear\", which means that unit output pretty directly reflect input and weights. Our activation formula of [ReLU](https://www.tensorflow.org/api_docs/python/tf/keras/layers/ReLU) means that unit output never exceeds a certain maximum value and that any unit output below a certain threshold is attenuated, or lessened. This privileges the output of units that are strongly weighted and also receiving input.\n",
    "\n",
    "Each unit in the first dense layer is subsequently connected to all of the 27 units in the last dense layer. The activation there is *softmax*, not ReLU. [Softmax](https://www.tensorflow.org/api_docs/python/tf/keras/activations/softmax) is an activation that converts the output vector or 27 possibilities into a probability distribution, where all of the output values sum to 1. That makes it easier to compare the confidence of a model's predictions.\n",
    "\n",
    "After you defined the neural network structure and activations in the first step, you compile that model, adding an optimizer, a loss function, and a metrics function. The loss function compare each prediction to the expected result in the training data. The model will be trained in steps to minimize this loss. Our loss function is categorical, which means that the model is judged on how well it chooses a category (a letter) based on the input it receives. The summary function prints a nice display of the model we have constructed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential\"\u001b[0m\n"
      ]
     },
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape              </span>┃<span style=\"font-weight: bold\">    Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩\n",
       "│ flatten (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">784</span>)               │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dense (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)               │    <span style=\"color: #00af00; text-decoration-color: #00af00\">100,480</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">27</span>)                │      <span style=\"color: #00af00; text-decoration-color: #00af00\">3,483</span> │\n",
       "└─────────────────────────────────┴───────────────────────────┴────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape             \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m   Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩\n",
       "│ flatten (\u001b[38;5;33mFlatten\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m784\u001b[0m)               │          \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dense (\u001b[38;5;33mDense\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m128\u001b[0m)               │    \u001b[38;5;34m100,480\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dense_1 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m27\u001b[0m)                │      \u001b[38;5;34m3,483\u001b[0m │\n",
       "└─────────────────────────────────┴───────────────────────────┴────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">103,963</span> (406.11 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m103,963\u001b[0m (406.11 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">103,963</span> (406.11 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m103,963\u001b[0m (406.11 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model = tf.keras.models.Sequential([\n",
    "  tf.keras.Input(shape=(28,28), name='input'),\n",
    "  tf.keras.layers.Flatten(),\n",
    "  tf.keras.layers.Dense(128, activation='relu'),\n",
    "  tf.keras.layers.Dense(27, activation='softmax')\n",
    "])\n",
    "\n",
    "model.compile(\n",
    "    optimizer=tf.keras.optimizers.Adam(0.001),\n",
    "    loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),\n",
    "    metrics=[tf.keras.metrics.SparseCategoricalAccuracy()],\n",
    ")\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the summary above you can see how many trainable parameters there are within the model we have defined. Each trainable parameter is the weight of a connection between one layer and the next. So 784 inputs are each connected to all 128 units (or neurons) in the dense layer, for 784 x 128 weights or 100,480 parameters. Then in the next layer you have 128 outputs connected to 27 units, for 128 x 27 weights, or 3,483 parameters. The total therefore is 103,963 trainable connections between inputs and neuron units.\n",
    "\n",
    "Next, the *fit()* function performs the training, fitting the model to the training data. This can take a few minutes, depending upon the speed of your computer and available memory. The training is performed in 15 *epochs* and each epoch is a complete pass through the training data. As training is performed you will see metrics that show how accurate the model is at predicting labels in the test dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/jansen/.local/share/virtualenvs/census-form-image-processing-VTyG8Y6d/lib/python3.10/site-packages/keras/src/backend/tensorflow/nn.py:568: UserWarning: \"`sparse_categorical_crossentropy` received `from_logits=True`, but the `output` argument was produced by a Softmax activation and thus does not represent logits. Was this intended?\n",
      "  output, from_logits = _get_logits(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2s\u001b[0m 2ms/step - loss: 1.4317 - sparse_categorical_accuracy: 0.6024 - val_loss: 0.7360 - val_sparse_categorical_accuracy: 0.7837\n",
      "Epoch 2/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.6583 - sparse_categorical_accuracy: 0.8074 - val_loss: 0.5814 - val_sparse_categorical_accuracy: 0.8273\n",
      "Epoch 3/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.5140 - sparse_categorical_accuracy: 0.8479 - val_loss: 0.5186 - val_sparse_categorical_accuracy: 0.8444\n",
      "Epoch 4/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.4418 - sparse_categorical_accuracy: 0.8671 - val_loss: 0.4832 - val_sparse_categorical_accuracy: 0.8524\n",
      "Epoch 5/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.3969 - sparse_categorical_accuracy: 0.8780 - val_loss: 0.4634 - val_sparse_categorical_accuracy: 0.8589\n",
      "Epoch 6/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.3643 - sparse_categorical_accuracy: 0.8865 - val_loss: 0.4504 - val_sparse_categorical_accuracy: 0.8615\n",
      "Epoch 7/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.3387 - sparse_categorical_accuracy: 0.8931 - val_loss: 0.4401 - val_sparse_categorical_accuracy: 0.8649\n",
      "Epoch 8/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.3180 - sparse_categorical_accuracy: 0.9005 - val_loss: 0.4357 - val_sparse_categorical_accuracy: 0.8668\n",
      "Epoch 9/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.3007 - sparse_categorical_accuracy: 0.9061 - val_loss: 0.4335 - val_sparse_categorical_accuracy: 0.8672\n",
      "Epoch 10/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.2860 - sparse_categorical_accuracy: 0.9099 - val_loss: 0.4327 - val_sparse_categorical_accuracy: 0.8668\n",
      "Epoch 11/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.2733 - sparse_categorical_accuracy: 0.9132 - val_loss: 0.4322 - val_sparse_categorical_accuracy: 0.8670\n",
      "Epoch 12/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.2616 - sparse_categorical_accuracy: 0.9166 - val_loss: 0.4320 - val_sparse_categorical_accuracy: 0.8684\n",
      "Epoch 13/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.2514 - sparse_categorical_accuracy: 0.9196 - val_loss: 0.4323 - val_sparse_categorical_accuracy: 0.8684\n",
      "Epoch 14/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.2421 - sparse_categorical_accuracy: 0.9214 - val_loss: 0.4326 - val_sparse_categorical_accuracy: 0.8705\n",
      "Epoch 15/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 2ms/step - loss: 0.2335 - sparse_categorical_accuracy: 0.9242 - val_loss: 0.4343 - val_sparse_categorical_accuracy: 0.8691\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x79e2d4736590>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "model.fit(\n",
    "    ds_train_final,\n",
    "    epochs=15,\n",
    "    validation_data=ds_test_final,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Superb! Look at that machine learn! In my training I am seeing a accuracy of 92.5 percent. You can see that in each epoch the loss is decreasing and the accuracy is improving as the weights (or trainable parameters) are adjusted.\n",
    "\n",
    "You might wonder why the progress bars above are counting up to 694.. Can you guess? If each epoch is one pass through all the training data and each epoch is divided into 694 steps, then what is each step?\n",
    "\n",
    "The answer is that each epoch is divided into the batches of 128 we defined in the training data.\n",
    "\n",
    "The number of training examples in EMNIST letters is 88,800. This divides up into 694 batches of 128 examples, with the last batch being somewhat smaller (the remainder).\n",
    "\n",
    "## Predicting a 'W' in the Census Images\n",
    "\n",
    "Our next step is to attempt to use the model to predict if a Census image is a 'W' or not. Along the way we are going to gather some numbers so that we can measure the accuracy of this combination of image treatments and the prediction model. We measure accuracy as precision and recall, defined as follows:\n",
    "\n",
    "precision = ratio of true Ws detected to number of Ws detected (true or not)\n",
    "recall = ratio of true Ws detected to number of true Ws in total\n",
    "\n",
    "In order to measure these stats, we have restricted our test run to a certain five pages, so 150 cell images. For those pages we have made lists of of the eight cells that are *not* Ws.\n",
    "\n",
    "Let's try that with the model we've just trained.\n",
    "\n",
    "The code below is an improvement on some of the *run()* functions we have used before in the image segmentation notebook. This run function takes a folder path, a page range, and a model. Since the census images we downloaded are named with a series of page numbers encoded after a final hyphen, such as \"43290879-California-101393-0014.jpeg\", we can use a regular expression to detect if a page is within the range of integers desired. If it is not, then we simply skip it. The *glob()* function will return files within the desired folder path and the *sort()* function will ensure that those files are returned in the right page order.\n",
    "\n",
    "After we have a page image file we read in the image with OpenCV *imread()*. The image is passed to the *extract()* function from the `segmentation.py` file, which returns the properly positioned template for the main part of the census form as well as a deskewed and adjusted image we can use to extract cell images. We then use the template to calculate a list of rectangles or boxes that represent demographic cells from the census page (`demographic_cells`).\n",
    "\n",
    "For each demographic cell, we crop a little image out of the page image (`cell_img`). We crop the cell image down to a 28x28 pixel square, removing the horizontal line. The 28x28 square is then normalized, just like our training data, into a tensor of floating point values. This tensor is expanded with an empty third dimension, just so that it matches our training data, which was three dimensions after it was batched. Having done this last step, we can finally call the *predict()* function and see what the model says about the cell.\n",
    "\n",
    "The result is a tensor array of 27 floating point values that represent the probability distribution among the 27 possible categories, i.e. letters. You can print out the full result tensor if that is interesting to you. Our code selects the index with the maximum probability (highest value). For each page we plot all of the demographic cells in a 6 by 5 grid, with a view of each 28x28 cropped cell image and caption that includes the class (integer label), the letter (looked up in a list), and the probability value of the prediction.\n",
    "\n",
    "Have a good look at the resulting plots of images and their predicted categories. What sort of image features impact predictions and their confidence? Are all of the 'W's predicted accurately? What other letters are often predicted instead of 'W' and why?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pages/43290879-California-101393-0002.jpeg\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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YgQMHmlOnTjk2/0D1nZr/nTt3TE1NjTHGmNraWjNy5Ejz3nvvmaefftrs3LnTGGPMt771LfPLX/7SsdqzZs0yu3fvbvF6gWzYsME899xzZuLEicYY48jcP8vxlVxxcbEGDBighIQEdejQQdnZ2SosLHS6DceMGTNGvXr1umessLBQs2bNkiTNmjVLe/fudbS+Uzwej4YPHy5JioyMVGJiokpLSx2bf6D6TnG5XOrataskqa6uTnV1dXK5XDp8+LCmTZsmKXTzD1TbSZcuXdK+ffs0b948SZIxxpG5f5bjIVdaWqrY2Fjf85iYGMd/8CZMmKC0tDTl5+c7Vvd/VVRUyOPxSJKio6NVUVHheA+bN29WSkqKcnJyQvp2+a7z58/r5MmTGjVqVFjm/7/1Jefm39DQoNTUVEVFRSkzM1P9+/dXjx495HZ/+vtqQ/nz/9nad+e+fPlypaSkaPHixbp9+3ZIakvSd7/7Xf3sZz9Tu3afxkxVVZVjc/9fbe7Ew7vvvqt//OMf+tOf/qQtW7bonXfeCWs/LpfL8X9hFy5cqLNnz6qkpEQej0dLly4Nab1r164pKytLGzduVLdu3e7Z5sT8P1vfyflHRESopKREly5dUnFxsT788MOQ1Wqs9j//+U+tXbtWH374of7+97+rurpa69atC0ntN998U1FRUUpLSwvJ6zeF4yHn9Xp18eJF3/NLly7J6/U6Wl+SoqKiNGXKFBUXFztW+65+/fqpvLxcklReXq6oqCjH60dERKhdu3aaP39+SL8HdXV1ysrK0vTp0zV16lRffafmH6i+U/O/q0ePHsrIyNB7772nq1evqr6+XpIzP/93ax84cEAej0cul0sdO3bUnDlzQjb3Y8eO6Y9//KPi4+OVnZ2tw4cPa9GiRY7PXQpDyI0YMUJnzpzRuXPnVFtbq127dmnSpEmO1L5+/bpqamp8X7/11lv3nHV0yqRJk1RQUCBJKigo0OTJkx2tfzdgJGnPnj0h+x4YYzR37lwlJiZqyZIlvnGn5h+ovlPzv3z5sq5evSpJunnzpg4ePKjExERlZGToD3/4g6TQzd9f7ccff9w3d2OM9u7dG7K5r127VpcuXdL58+e1a9cujRs3Tjt27HBk7vcJ+akNP/bt22cGDhxoEhISzE9+8hPH6p49e9akpKSYlJQUM2TIEEdqZ2dnm+joaON2u43X6zWvvfaaqaysNOPGjTMDBgww48ePN1VVVY7WnzFjhklOTjZDhw413/zmN01ZWVlIah89etRIMkOHDjXDhg0zw4YNM/v27XNs/oHqOzX/Dz74wKSmppqhQ4eapKQks3r1amPMpz+HI0aMMP379zfTpk0zt27dcqx2RkaGSU5ONklJSWb69Om+M7ChdOTIEd/ZVSfm/lnc1gXAam3uxAOAtoWQA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDmGzYMEC/fjHP26x14uPj9ehQ4da7PVgB0IOYfOrX/1KP/rRjxyptX79eiUnJysyMlKPPfaY1q9f70hdhJ873A2g9aqvr5fbHZ4fkZaubYzRtm3blJKSorNnz2rChAmKjY1VdnZ2i9VA68RKDveIj4/XunXrlJKSoi5duqi+vl7vv/++vvSlL6lHjx4aNmyYioqKfPuPHTtWP/zhDzVy5Eh169ZNkydPVnV1tW/7008/rejoaHXv3l1jxozRqVOnfNtmz56tFStWSJKKiooUExOjdevWKTo6WnPmzNGdO3eUl5en/v37q3fv3nrmmWfuee3t27crLi5OvXv31k9/+tMHzuvFF1/U8OHD5Xa7NXjwYE2ePFnHjh1roe8aWjNCDvfZuXOn9u3bp6tXr6qiokITJ07UihUrVF1drZ///OfKysrS5cuXfftv27ZNW7duVXl5udxut77zne/4tn3961/XmTNn9PHHH2v48OGaPn16wLr/+c9/VF1drQsXLig/P1+vvPKK9u7dq7fffltlZWXq2bOnvv3tb0uSTp8+rYULF2r79u0qKytTVVWVLl269FDzM8bo6NGjSkpKCvI7hEeKAf5HXFycef31133P8/LyzIwZM+7ZZ8KECeY3v/mNMcaYJ5980vzgBz/wbTt16pRp3769qa+vv++1r1y5YiSZq1evGmOMmTVrllm+fLkxxpgjR46Y9u3bm5s3b/r2f/zxx82hQ4d8z8vKyozb7TZ1dXVm9erV5tlnn/Vtu3btmmnfvr05ePBgo3NcuXKlSUlJMbdu3Wp0Xzz6+EwO94mNjfV9feHCBe3evVtvvPGGb6yurk4ZGRl+94+Li1NdXZ0qKyvVp08fLV++XLt379bly5fVrt2nbxwqKyvVvXv3++r27dtXnTp1uqf2lClTfMdJUkREhCoqKlRWVnZP3S5duqh3796Nzm3z5s3atm2bjh49qo4dOza6Px59hBzu43K5fF/HxsZq5syZ+vWvfx1w/4sXL/q+/uijj9S+fXv16dNHv/vd71RYWKhDhw4pPj5e//3vf9WzZ08ZYxqte7f21q1b9eUvf/m+fT0ej/71r3/5nt+4cUNVVVUPnNfWrVuVl5end955RzExMQ/cF/bgMzk80IwZM/TGG2/oz3/+sxoaGnTr1i0VFRXd8/nXb3/7W50+fVo3btzQypUrNW3aNEVERKimpkYdO3ZU7969dePGDb300ktNqr1gwQItX75cFy5ckCRdvnxZhYWFkqRp06bpzTff1Lvvvqva2lqtXLlSd+7cCfhaO3bs0EsvvaSDBw8qISEhiO8EHlWEHB4oNjZWhYWFWrNmjfr27avY2FitX7/+nkCZOXOmZs+erejoaN26dUu/+MUvJEkvvPCC4uLi5PV6NWTIEI0ePbpJtRctWqRJkyZpwoQJioyM1OjRo/W3v/1NkpSUlKQtW7bo+eefl8fjUc+ePR+4OluxYoWqqqo0YsQIde3aVV27dtWCBQuC+I7gUeMygd47AA9h7NixmjFjhubNmxfuVgC/WMkBsBohB8BqvF0FYDVWcgCsRsgBsBohB8BqhBwAqxFyAKz2f4CAtt8s5UN6AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+zVHdhcufD3MnAz079S1HdesvZjqqq7yh3lFdSqSzKyhs8dipfzmqu2PcF47q5tRVOKqbsui4ozoMDUdwAKxFwAGwFgEHwFoEHABrEXAArEXAAbAWAQfAWgQcAGsRcACsxZUMXzF9wkVHdeMjxoRsm//W1Omo7uM+Z1dPHMwZ56iu+MPxjuriI3oc1V3vnm5+21HdrCiHj1/TvY7quEIhvDiCA2AtvwFXVVUlt9utrKws79jatWuVnJys3Nxc5ebmavfu3cPaJAAEwm/AVVZWau/evQPGV61apcbGRjU2Nuruu+8eluYAIBh+A66wsFDx8fEj0QsAhFTAr8FVV1crJydHVVVVam9v91lXU1OjvLw85eXlqVfdgW4OAIYsoIB76KGHdOrUKTU2NiopKUmPPvqoz9qVK1eqvr5e9fX1itLYgBsFgKEKKOASEhI0ZswYRURE6MEHH1RdXV2o+wKAoAUUcB6Px/v79u3b+51hBYDrhd83+i5btkz79+/XhQsXlJKSot/85jfav3+/Ghsb5XK5NH36dG3evHkkegWAIfEbcFu2bBkwtmLFimFpJtzyYz90VPdse07ItrnyhiZHdfem3BGybUrS1MjPHNWNcYXnddOxbyU6qtue6uw9mI09zi7auTt5jqO6GH3kqA7hxZUMAKxFwAGwFgEHwFoEHABrEXAArEXAAbAWAQfAWgQcAGsRcACs5TLGmJHaWJwrXvmukpHa3JD9z48POaqLH+Ps3f1jXVHBtNPP4S+uhOy+hmL+uND+H9hrLof0/tZdyHZU9/bs6JBuF9eHd83r6jBtPpdzBAfAWgQcAGsRcACsRcABsBYBB8BaBBwAaxFwAKxFwAGwFgEHwFoEHABrEXAArEXAAbAWAQfAWgQcAGsRcACsRcABsBYBB8BaBBwAaxFwAKwVGe4GrieV37zDUZ3z727wX1Pf7aAojJx+F8R/Gxvar/bguxYQChzBAbAWAQfAWgQcAGsRcACsRcABsBYBB8BaBBwAaxFwAKxFwAGwFlcyDKOxrigHVc6uFLjeRbmcXZHRay4PcyfAf/F7BHf69GkVFxcrIyNDmZmZ2rRpkySpra1NpaWlSktLU2lpqdrb24e9WQAYCr8BFxkZqY0bN+r48eN655139Mwzz+j48ePasGGDSkpKdPLkSZWUlGjDhg0j0S8AOOY34JKSkjRnzhxJUmxsrNLT09XS0qKdO3eqoqJCklRRUaEdO3YMa6MAMFRDOsnQ3NyshoYG5efnq7W1VUlJSZKkxMREtba2DkuDABAoxycZurq6VF5erqefflpxcXH9lrlcLrlcrkHXq6mpUU1NjSSpV91BtAoAQ+PoCK63t1fl5eVavny5Fi9eLElKSEiQx+ORJHk8Hrnd7kHXXblyperr61VfX68ojQ1R2wDgn9+AM8ZoxYoVSk9P1+rVq73jZWVlqq2tlSTV1tZq4cKFw9clAATA71PUw4cP68UXX1R2drZyc3MlSevWrdOaNWt077336vnnn9e0adP0l7/8Zbh7BYAhcRljQvtZ09cQ54pXvqtkpDYHwHLvmtfVYdp8LudSLQDWIuAAWIuAA2AtAg6AtQg4ANYi4ABYi4ADYC0CDoC1CDgA1iLgAFiLgANgLQIOgLUIOADWIuAAWIuAA2AtAg6AtQg4ANYi4ABYi4ADYC0CDoC1CDgA1iLgAFiLgANgLQIOgLUIOADWIuAAWIuAA2AtAg6AtQg4ANYi4ABYi4ADYC0CDoC1CDgA1iLgAFiLgANgLQIOgLUIOADWIuAAWIuAA2AtAg6AtQg4ANbyG3CnT59WcXGxMjIylJmZqU2bNkmS1q5dq+TkZOXm5io3N1e7d+8e9mYBYCgi/RZERmrjxo2aM2eOOjs7NXfuXJWWlkqSVq1apZ/97GfD3iQABMJvwCUlJSkpKUmSFBsbq/T0dLW0tAx7YwAQrCG9Btfc3KyGhgbl5+dLkqqrq5WTk6Oqqiq1t7cPuk5NTY3y8vKUl5enXnUH3zEAOOQyxhgnhV1dXSoqKtIvf/lLLV68WK2trZo8ebJcLpd+/etfy+Px6IUXXrjmfcS54pXvKglJ4wDwrnldHabN53JHR3C9vb0qLy/X8uXLtXjxYklSQkKCxowZo4iICD344IOqq6sLTccAECJ+A84YoxUrVig9PV2rV6/2jns8Hu/v27dvV1ZW1vB0CAAB8nuS4fDhw3rxxReVnZ2t3NxcSdK6deu0ZcsWNTY2yuVyafr06dq8efNw9woAQ+L4NbhQ4DU4AKEUktfgAGA0IuAAWIuAA2AtAg6AtQg4ANYi4ABYi4ADYC0CDoC1CDgA1iLgAFiLgANgLQIOgLUIOADWIuAAWIuAA2AtAg6AtQg4ANYi4ABYi4ADYC2/XzoTStE3Rah9+kf9xs6fP69vfOMbI9lGyNkwB8mOedgwB8mOeYzEHKKbr32MNqJfOjOYvLw81dfXh7OFoNkwB8mOedgwB8mOeVwPc+ApKgBrEXAArBX2gFu5cmW4WwiaDXOQ7JiHDXOQ7JjH9TCHsL8GBwDDJexHcAAwXMIWcHv37tUtt9yi1NRUbdiwIVxtBG369OnKzs5Wbm6u8vLywt2OY1VVVXK73crKyvKOtbW1qbS0VGlpaSotLVV7e3sYO/RvsDmsXbtWycnJys3NVW5urnbv3h3GDv07ffq0iouLlZGRoczMTG3atEnS6NsXvuYR9v1hwqCvr8/MnDnTnDp1ynR3d5ucnBxz7NixcLQStGnTppnz58+Hu40he+utt8yRI0dMZmamd+znP/+5Wb9+vTHGmPXr15vHHnssXO05MtgcnnjiCfO73/0ujF0NzdmzZ82RI0eMMcZ0dHSYtLQ0c+zYsVG3L3zNI9z7IyxHcHV1dUpNTdXMmTMVHR2tpUuXaufOneFo5WursLBQ8fHx/cZ27typiooKSVJFRYV27NgRhs6cG2wOo01SUpLmzJkjSYqNjVV6erpaWlpG3b7wNY9wC0vAtbS0aOrUqd7bKSkp18WDEQiXy6U777xTc+fOVU1NTbjbCUpra6uSkpIkSYmJiWptbQ1zR4Gprq5WTk6Oqqqqrvundl/V3NyshoYG5efnj+p98dV5SOHdH5xkCNKhQ4f0z3/+U3v27NEzzzyjAwcOhLulkHC5XHK5XOFuY8geeughnTp1So2NjUpKStKjjz4a7pYc6erqUnl5uZ5++mnFxcX1Wzaa9sXV8wj3/ghLwCUnJ+v06dPe22fOnFFycnI4Wgnal3273W4tWrRIdXV1Ye4ocAkJCfJ4PJIkj8cjt9sd5o6GLiEhQWPGjFFERIQefPDBUbE/ent7VV5eruXLl2vx4sWSRue+8DWPcO6PsATcbbfdppMnT+qjjz5ST0+Ptm7dqrKysnC0EpRLly6ps7PT+/u+ffv6ndEbbcrKylRbWytJqq2t1cKFC8Pc0dB9GQqStH379ut+fxhjtGLFCqWnp2v16tXe8dG2L3zNI+z7I1xnN3bt2mXS0tLMzJkzzVNPPRWuNoJy6tQpk5OTY3JyckxGRsaomsfSpUtNYmKiiYyMNMnJyeZPf/qTuXDhgvnud79rUlNTTUlJibl48WK427ymweZw//33m6ysLJOdnW0WLFhgzp49G+42r+ngwYNGksnOzjazZ882s2fPNrt27Rp1+8LXPMK9P7iSAYC1OMkAwFoEHABrEXAArEXAAbAWAQfAWgQcAGsRcACsRcABsNb/B/s2wGmqOtRHAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AsvFWYrtlfXw+0jnRQWpJIOnYdg8Rx+fLHV9XFFEcMvUYYzD4cOAkmthO++rHjxcP8cfWD7CBVbxv/pcWmtodbsPRQ+5mGgOfs+nfLsz27mhj+6ZWxk9MCLq9nVvagtZ/8r44vh9PdogGXETzL/MP3jevU2FWcMQcDtq22TRi8BPH57XEk8QRDuM1nqDLiIRTh+cg3W43SUlJ7aYlJyfT3NwcmJ+cnBx0vsPh6HDZE2VmZlJXV0d+fj6lpaWUl5d3WHQ1e8igD07LvnwfXpwndc+JCy8e0sliH9vx4sVnfOxiIwBROPDiwcIKuqzh1EPielNDNXsYyZUAePC0C+XjdWSQQznvHdtOFD1ICJzjO1E6WexmM4VmJG20spdtx6YfPUwt4iskkgoYPmQJe9hKXzMwcO7UiRMvn4dLBr3bHaL/7RU3oy6PIyXdEXS/uZv8OE7oe0f7MZhWPqOZRi7iMhJIZjvrWMdHjGRsu3Ze42E9q7iAgsC5WyCwbS8enLgQiaQOR5AJCQk0NbUfKTQ1NQUupHQ0v7Nlj1u5ciV1dXX85S9/YdOmTZSXl7Ns2TISEhJISEg4ZVRpMNRQ2eHhNRz9j+Y9acTnxYsTF+lWJvEkUslOVvAmscTjwIkfP05ctstatA+0Q6ae9XxEMV8NjLB8eNjLVv5pXuVDs+TYujzsZw9f5SquZDKZ9KOFZlrNZ6fUPYgSHDj4gLf5F//AgYNY4gJhmmL1xGE5cFjOwHnW44f3J/YxsB8sJ5n0oZq9GGN4Z7GbqycHHz0CJCZHtRspd7Qfg4nCQS96k2yl4bAcXMAQDlHfbkToMz4qWEEy6VxgDW63/PFtKxzlXNDhCDI/Px+v18u2bdvIy8sDYM2aNYHQKiwsZM2aNYH2O3fupLW1lfz8fKKiojpcFmD16tVMnDiR9PR0xowZE5h+2WWX4Xa7g9bkpQ0X0aTSq8OOxZOIwY+HtsC0ZhoDh6o9yeYIhymyRtFimtnJRsAQR8KxK9Z+Dptm4o4FXzON7UZWTeYgFXxAAaWkWZmB6T3JxkMbw62j/fEZLwZDCumBEPUbH05cNFJP5kmnCVxWNEWMYofZwAGqSCMjcO4zFC00k3jSe62zyWUNH/CvZekcbvFz6bh42+UvHBzN3044J3h8P568L0485D9RAslwwg+Sk3+o+I2PNXxALD0YwvAg9TcRS1y7UaVIpHQ4goyPj2fy5Mncf//9tLS0sGLFChYvXswtt9wCwLRp03j99ddZtmwZLS0t3H///UyePJnExMROl12/fj3XXHMNTz75JPHx8Vx11VWMGDGCsrKyU+ooKyujtLSU0tJS2jhCNrlBD09PZBFFL3rTSC0+fNSbA9Syn2z64TM+kkijlmpqTCUbKSeOeDLIwWm5cFhHD4l3sBGf8dJo6qhlP9EcvWLuNoeoYDmDKKGX1bvddtPIpJlGfMYHHB3BJZHKAapwm0McNLUcoBIfnsB5yxMdNm62m/V8yl76M4hP2csFHB1lHTGHaTR1eI2XNtNGK5/hw0MiKYEr4o3Ukk5Wu3Wm0BMX0fz3T+u48hsJuKLt913p6B6n1B9sX2QT/Daf3vSnliqaTSN+42cnG0khHaflwm/8rGUlDhwUMDLod3iQWnqeVL9IpFimk7uBGxoamDFjBu+88w7p6enMnTv3lPsg58yZQ319PV/72td4/vnn290Habfst7/9bebPn09cXBzGmKNXNfv0ISYmhieffLLdiPK4qqoq+vTpwyVcQ5xlf5gIsMNsYBeb2k3rRW+GWZccuy/xfVpowmCwsEgni0JGnnIfZD01x+5FHEolO8kml0bqqGYPDj4/jxdLPBdbVwGw1nxIBn3IsvoCR299KeefHOboqDiGWAYylGwrl4OmlgqWM9a6HoAas491fBRYbxRRWFj0ZzC96M16VuHm1FtshjOGZNL5gLf5CuOIsdpfADq+P377Sm8KLur44tC/XdDarv5g++L4fZAn1w9QaXawi0348JFCTwZzEbFWHAdNLR/zPlE42o0rSxhNqnX0iOBDs+ToeVbdBylh8pF5lybTEHRepwEZbg888AAJCQn86Ec/Cjo/yUpjlDUuzFWdHrdpYiP/YiRXdjrSPZP2mu20cpg8qzjo/Pt3fhJ0+sl+fMHAiNRfa/ZTzV6Kra+GbZsiHQVkxB81bGlpCVzZbmlpYcmSJRQVFUW4qi8nwUriK9a4sIYLQD9roG04no5I1d/L6q1wlHNKxF+5UFNTw/XXHz0883q9gRvIRUQiLeIBOWDAgHZXwuXsqfd1fN5Wwitx2anP4gfzhwveDKnd7Xuu7rRN/aUHQ1qXHBXxQ2wRkXNVxEeQp2N81P855y/QnMueysvvcP73tm0NUyUiXYNGkCIiNhSQIiI2FJAiIjYUkCIiNhSQIiI2FJAiIja61G0+cnZtac2OdAnnlVBvAHdZwX+58cl0E/iZpxGkiIgNjSDPA46UY+/e8fnxB3nlhYgEpxFkN+dISWbAO0fou6SN3c/1hzD/hh6RrkwB2Y15vjaCzb8YzK09l5MV04TX44Bz69d/ipzTFJDdlGPQQPZfFsNDV79EX0crG5qyYV+PSJcl0qXoHGR3ZFn0/2Mlj/VaQG+H4T8+Hcee5/IY8PyHka5MpEtRQHbAN3Y4e6+KwdPTS+5rEPPGvyJdUqfMJcPY+0M/D/V8jhbj5OmDRax7cBgZa/ad9PJWEelMtwtIy+nks2uG43dZOA/7iP5b+Rdaj+drI6i6PJqSy7YS6/CweUXhsXcanh2er40gpu4z/BUbv/A6zCXDqBwbz39d9HsA/lh/Ca9/XMLgf6zHe/jwGapU5PzR7QIyKjGRG//rDQpiq3ipYSRbllifX5g4fgW3owsVloXlcNDnoW08lvV3Brp8TNs+GUfbWby4YVnkPryVpSsLGXiX9cUupFgW++7y8+uLfse4Hoe5a/9o/vHaCPL/8wP8Z75ikfNCtwtIoiwSHUfo73ST1+MAWzj6Clq+MpRt33dROmAP694ZRL8HPzhl0b0PXELiyFqm9KtgdPwq/u4uZMaOUnr/zJC6dyO+s1h2dswhfnr1a7z8j+GYic2ndb+is28fNj6YxcPFr1IQXc+KI0ls+I9i+n+87bRqviRuGwB/Z/hpVi8nCvXtkaE+IeP2t36ZcuRL6H4B6Tfs96RwJHYvMVGewOTW9FimD1vB1YnruDHrwnaLOHqmUzl9EBdcvpuJmWvIch3i1hUzce6NJWEvmC0f4/e0ndWyW/1O8mI+5ZtZFbzmyGs3r/GWi2nJsYjyQJ/5W/DV1QfmWaVFVI9M5MaLVlAYvZ833YN4bMl1DF6zG29t7VmtWaS7634BafxsbcmiMX4z0ZYXR1oqAC1ZTu5Nr8BlOXAkeXCkpoLxgxWFZ0g/nv7ePPJcn7HTE8t/V13NoAcb8W3fdXSVYSi7wROP30SR4WwC69jdV1EOHKnJZN6+iyf6v8R+XxwP/+0mOCEgqy9Loue1ldzX6yO2eJw8vXUMA3+4UhdkRM6A7heQwCFPLEeMi2/E72LPP3oypEcV+a63iLFcACy+9Df8Y/lgPjp0AWNTN/HVHm/isvw8XHMFf/1oOIPmbMTvru9kK2fWjkM9qUpNJcvZGJgWNTSfB177A4NcXuKsHqQ5WsHR/kmYpuJW3hv0Ii6c/Pv9/5fer6zVOUeRM6T7BaTfUOVOpsGXQHKMjxuSy0l3GOIsB34MLstBrtNiUuIGhvXYQ0rUEda19uY/n72R2HpD/71tEXleuaEljgZvAnnRnwLQeu1IKq9wUuQyxFgx+DF4zOfRFxUXx5ZfDuW24cvwYCg7WEhcrRd/S0vYaxfprrpdQBpjaGzpQYs/BpflYEh0HB7jo9V4qPR+RqYjmhjLRY4jmjirhb8d7seTO8bS+78/jOhjeK1HXBz2R5NoefAW5FJ1uZOrrlh99JSAFYXf+AIjQ0d6Gt5BffmfCc9S4DrEbm8Mz667lAENRyJWv0h31O0CEqCt1UWL//O7Fg+bNspbE3iy8mvckfM+/Z0HSY7ysahpGC8+eRU9y1ZG/Bllh9NHXFQbA1wufjD/RQY4G+jttKjz+UhzxODEQdyxq577bxrMv3/3FUbHHmFTm4vH91/FgJvXgf9sXmcXOf90u4D0txxmwOM+nvmP0cwc/iIOK4qHD1zCSxUjuPAPfv4r4Vb8LgsTBa4WP1mbq/CeA7/Aoe1wNId8PXDiYGRMPc1+w/OHinjp51cz6if/4sHMD3BZDlJ/8ylfTVjD+PjtfHgkiRl/ncUFiz04/R9Hugsi3U63C0j8Pli1joO7R/HOkB7EWh5eWjOcnstdON77kJPvPDsnrvYaQ9ymGP7ZJ5+f9dxMalQsj9ddxKKPv0L+Sx+xdnZfjmT4iLFcPNXvDTwYGv0W/3fdt8h53+D8h8JR5GzofgF5TPIWBz/MvIEeMR7y/seL9cG5HSI5v/yAfc5LaB3iIcZysfjPo8l/9OjN7Ic9Lg75DT0dDlIdcWz1tLCocSR9btuPr3FThCsX6b66bUBmL9qM9Xo8WBb+T3d3iVtfYg7C4w0F7DuSRlzN54f9+/ek86feI7gvfRPvHXFx+z9/wJDHGvEd2nFGt5/l0PPaHbln+4aQ2l0aG9pvEfSZ0P5VvuIeEFI7OfO6bUD66hugviHSZZyW9I1HeO61r+E4YtFn8+e362Qsd/I//stJu9zNL5deS9b7Ufi2bI9gpSLnh24bkF2R471P6P/eqdNTFnxI8vZh/L/UcRQ8Wo13z75wlyZyXlJAdhHWR+u5cGasfm2ZSBgpILsKv09PyYiEmd5JIyJiQwEpImJDASkiYkMBKSJiQwEpImJDV7EloNnvinQJEeF+O7QnVS6JXRlSu8caCkNq9+3ktSG1+/OQrJDayZmnEaSIiI2wBeSMGTPIyMigqKgoMK2hoYHx48eTl5fH+PHjOXjwYLjKERHpVNgOsW+77Ta+//3vc+uttwamzZ07l3HjxjFnzhzmzp3L3Llz+eUvf2m7jnf8fyHJSmOUNS4cJXc7v9z1UaRLEOlSwjaCHDNmDGlpae2mLV68mOnTpwMwffp0XnvttXCVIyLSqYieg6ypqSE7OxuArKwsampqIlmOiEg758xVbMuysCwr6LyysjLKysoA8NAazrJE5DwW0RFkZmYm1dXVAFRXV5ORkRG03axZsygvL6e8vBwXMUHbiIicaRENyIkTJzJ//nwA5s+fz6RJkyJZjohIO2ELyBtvvJGLL76YLVu20KdPH373u98xZ84c3nnnHfLy8vj73//OnDlzwlWOiEinwnYOctGiRUGnv/vuu+Eq4bwXY+m92cEsLlwQUrsHD4wOqd2ulvSQ2o3ssSukdhI5epJGRMSGAlJExIYCUkTEhgJSRMSGAlJExIYCUkTEhgJSRMSGAlJExIYCUkTExjnz23zk7Gvwx0a6hLByvZcdUrtDfhNSu7XDQ2t3w6b1IbX77uqbQmrXl9DWJ2eeRpAiIjYUkCIiNhSQIiI2FJAiIjYUkCIiNhSQIiI2FJAiIjYUkCIiNhSQIiI29CTNeaTRHxfpEsJq4cBXQmr3h0OFIbXr91F8SO3eqB0aUru+/6YnZM51GkGKiNhQQIqI2FBAiojYUECKiNhQQIqI2FBAiojYUECKiNhQQIqI2FBAiojY0JM055HEqCORLuGMeHDnxyG185vQ3iFzefyWkNqNitseUrv/uGBkSO3k3KcRpIiIDQWkiIgNBaSIiA0FpIiIDQWkiIgNBaSIiA0FpIiIDQWkiIgNBaSIiA09SXMeSekmT9IMdIXWj51eV0jtBrn8IbW7ecc3QmoHNSG2k3OdRpAiIjbCFpAzZswgIyODoqKiwLQHHniAnJwcSkpKKCkp4c033wxXOSIinQpbQN522228/fbbp0y/6667qKiooKKiggkTJoSrHBGRToUtIMeMGUNaWlq4Nici8qVF/BzkvHnzKC4uZsaMGRw8eDBom7KyMkpLSyktLcVDa5grFJHzVUQDcvbs2ezYsYOKigqys7O55557grabNWsW5eXllJeX4yImzFWKyPkqogGZmZmJw+EgKiqKO+64g1WrVkWyHBGRdiIakNXV1YG/v/rqq+2ucIuIRFrYbhS/8cYbee+996irq6NPnz48+OCDvPfee1RUVGBZFv379+eZZ54JVzkiIp0KW0AuWrTolGkzZ84M1+YFaPTHRrqEDv1y10chtUuMig6p3SCXL6R239l7TUjtPrtcT8icbyJ+FVtE5FylgBQRsaGAFBGxoYAUEbGhgBQRsaGAFBGxoYAUEbGhgBQRsaGAFBGxoXfSnEfKDw+IyHZr/3dQSO2GRn8SUrsmf2jvpJm0cVpI7XpcvSukdnL+0QhSRMSGAlJExIYCUkTEhgJSRMSGAlJExIYCUkTEhgJSRMSGAlJExIYCUkTEhp6kOY9UtaaE2NJ/Rre7oPj3IbWr94e23Sv/NSukdjmTN4TUTsSORpAiIjYUkCIiNhSQIiI2FJAiIjYUkCIiNhSQIiI2FJAiIjYUkCIiNhSQIiI29CTNeeSWtA9Dancfo0JqN3NraO9yibN8IbW7pe/okNrloCdkJDw0ghQRsaGAFBGxoYAUEbGhgBQRsaGAFBGxoYAUEbGhgBQRsaGAFBGxoYAUEbGhJ2nOIwNdJqR2/1v1r5Da1fpaQ2o3s19oT8iInGvCMoLct28fY8eOpaCggMLCQp544gkAGhoaGD9+PHl5eYwfP56DBw+GoxwRkZCEJSCdTie/+tWv2LhxIytXruSpp55i48aNzJ07l3HjxrFt2zbGjRvH3Llzw1GOiEhIwhKQ2dnZDB8+HIDExESGDBlCVVUVixcvZvr06QBMnz6d1157LRzliIiEJOwXaXbv3s3q1asZNWoUNTU1ZGdnA5CVlUVNTU24yxERsRXWizRut5spU6bw+OOPk5SU1G6eZVlYlhV0ubKyMsrKygDwENqFARGRLytsI0iPx8OUKVOYNm0akydPBiAzM5Pq6moAqqurycjICLrsrFmzKC8vp7y8HBcx4SpZRM5zYQlIYwwzZ85kyJAh3H333YHpEydOZP78+QDMnz+fSZMmhaMcEZGQhOUQe8WKFSxYsIChQ4dSUlICwCOPPMKcOXO44YYb+N3vfkdubi5//vOfw1GOiEhILGNMaHcPnyOSrDRGWeMiXcY55Xd7l4fULtsRF1I7twntPO8NfS4OqZ3Iuewj8y5NpiHoPD1qKCJiQwEpImJDASkiYkMBKSJiQwEpImJDASkiYkMBKSJiQwEpImJDASkiYkOvXOgGanzRIbXr5fCF1G72ngkhblm/AV66N40gRURsKCBFRGwoIEVEbCggRURsKCBFRGwoIEVEbCggRURsKCBFRGwoIEVEbOhJmm6gypsSUrsRMYdDald/aWSekLlr+6aQ2hVF14fUbma/0V+mHBGNIEVE7CggRURsKCBFRGwoIEVEbCggRURsKCBFRGwoIEVEbCggRURsKCBFRGzoSZpu4Oq4QyG1azWhrW/hvhVfopovzmWF9vM6zuoRUrsDiweH1C5j0uaQ2sn5RyNIEREbCkgRERsKSBERGwpIEREbCkgRERsKSBERGwpIEREbCkgRERsKSBERG3qSRrocj/FFugQ5T2gEKSJiIywBuW/fPsaOHUtBQQGFhYU88cQTADzwwAPk5ORQUlJCSUkJb775ZjjKEREJSVgOsZ1OJ7/61a8YPnw4zc3NjBgxgvHjxwNw11138aMf/SgcZYiInJawBGR2djbZ2dkAJCYmMmTIEKqqqsKxaRGRLyzs5yB3797N6tWrGTVqFADz5s2juLiYGTNmcPBg8BfWl5WVUVpaSmlpKR5aw1muiJzHwhqQbrebKVOm8Pjjj5OUlMTs2bPZsWMHFRUVZGdnc8899wRdbtasWZSXl1NeXo6LmHCWLCLnsbAFpMfjYcqUKUybNo3JkycDkJmZicPhICoqijvuuINVq1aFqxwRkU6FJSCNMcycOZMhQ4Zw9913B6ZXV1cH/v7qq69SVFQUjnJEREISlos0K1asYMGCBQwdOpSSkhIAHnnkERYtWkRFRQWWZdG/f3+eeeaZcJQjIhKSsATk6NGjMebUF6JMmDAhHJuXY5r9bZEuoUMe4w+p3RWffDukdnrXjHxZepJGRMSGAlJExIYCUkTEhgJSRMSGAlJExIYCUkTEhgJSRMSGAlJExIYCUkTEht5J0w1EnWc/59LiD0e6BDlPnF//s0REToMCUkTEhgJSRMSGAlJExIYCUkTEhgJSRMSGAlJExIYCUkTEhgJSRMSGZYK9LOYc1rNnT/r3799uWm1tLb169YpMQWdQd+hHd+gDdI9+dIc+wNnvx+7du6mrqws6r8sFZDClpaWUl5dHuowvrTv0ozv0AbpHP7pDHyCy/dAhtoiIDQWkiIiNbhGQs2bNinQJZ0R36Ed36AN0j350hz5AZPvRLc5BioicDd1iBCkicjZ0+YB8++23GTRoEAMHDmTu3LmRLucL6d+/P0OHDqWkpITS0tJIlxOyGTNmkJGRQVFRUWBaQ0MD48ePJy8vj/Hjx3Pw4MEIVti5YH144IEHyMnJoaSkhJKSEt58880IVhiaffv2MXbsWAoKCigsLOSJJ54Autb3YdeHiH4fpgvzer1mwIABZseOHaa1tdUUFxebDRs2RLqs05abm2tqa2sjXcZpe//9983HH39sCgsLA9Puvfde8+ijjxpjjHn00UfNj3/840iVF5Jgffj5z39uHnvssQhWdfr2799vPv74Y2OMMU1NTSYvL89s2LChS30fdn2I5PfRpUeQq1atYuDAgQwYMIDo6GimTp3K4sWLI13WeWPMmDGkpaW1m7Z48WKmT58OwPTp03nttdciUFnogvWhK8rOzmb48OEAJCYmMmTIEKqqqrrU92HXh0jq0gFZVVVF3759A5/79OkT8R36RViWxVVXXcWIESMoKyuLdDlfSk1NDdnZ2QBkZWVRU1MT4Yq+mHnz5lFcXMyMGTPO6cPSYHbv3s3q1asZNWpUl/0+TuwDRO776NIB2V0sX76cTz75hLfeeounnnqKpUuXRrqkM8KyLCzLinQZp2327Nns2LGDiooKsrOzueeeeyJdUsjcbjdTpkzh8ccfJykpqd28rvJ9nNyHSH4fXTogc3Jy2LdvX+BzZWUlOTk5Eazoizlec0ZGBtdffz2rVq2KcEVfXGZmJtXV1QBUV1eTkZER4YpOX2ZmJg6Hg6ioKO64444u8314PB6mTJnCtGnTmDx5MtD1vg+7PkTq++jSATly5Ei2bdvGrl27aGtr48UXX2TixImRLuu0tLS00NzcHPj7kiVL2l1R7WomTpzI/PnzAZg/fz6TJk2KcEWn73igALz66qtd4vswxjBz5kyGDBnC3XffHZjelb4Puz5E9PuIyKWhM+iNN94weXl5ZsCAAebhhx+OdDmnbceOHaa4uNgUFxebgoKCLtWHqVOnmqysLON0Ok1OTo559tlnTV1dnbnyyivNwIEDzbhx40x9fX2ky+xQsD7cfPPNpqioyAwdOtRcd911Zv/+/ZEus1PLli0zgBk6dKgZNmyYGTZsmHnjjTe61Pdh14dIfh96kkZExEaXPsQWETmbFJAiIjYUkCIiNhSQIiI2FJAiIjYUkCIiNhSQIiI2FJAiIjb+P7FhHD6OI5JFAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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yZUpQGwUAf7T4+PN//OMfys/PV1NTk5qbmzVz5kytWrVKJ0+eVG5ururr6zV06FC9/PLL6tKly12L9erVS0lJSZJuh2fv3r0DNpHW6sj1O/Lcw12/I889mPUrKyt1/vx53xtNmGRmZoardIev35HnHu76HXnu4arPHQ8ArEbIAbBa2EKusLAwXKU7fP2OPPdw1+/Icw9X/ZB+7yoAhBpvVwFYjZADYLWwhNyuXbs0YMAAJScnq7i4OKS1k5KSNHjwYGVkZITkVrOCggLFxMQoLS3NO1ZfX6/s7Gz1799f2dnZunjxYkjrr169WnFxccrIyFBGRobefPPNoNSuqqrS2LFjNWjQIKWmpurnP/+5pNDN36l+qOYfzseUOdWeP3++vvCFL3jnXlFREfDa/62pqUlDhw7VV7/6VUlhekRbqK9ZuXXrlunbt685ceKEuXHjhklPTzdHjx4NWf3ExERz7ty5kNV79913zeHDh01qaqp37Lvf/a5Zu3atMcaYtWvXmu9973shrf/MM8+Y5557Lmg1P3XmzBlz+PBhY4wxn3zyienfv785evRoyObvVD9U829ubjaXL182xhhz8+ZNM2LECHPo0CEzY8YMU1JSYowx5hvf+IZ5/vnnQ1Y7Pz/fvPrqqwGv52T9+vVm9uzZ5itf+YoxxoRk7v8r5Cu5srIyJScnq2/fvnrggQeUm5ur0tLSULcRMqNHj1bPnj3vGCstLfV+1WKwH1Plq36ouN1uDRs2TJLUrVs3paSkqKamJmTzd6ofKuF8TJlT7VCqrq7Wzp07tXDhQkmSMSYsj2gLecjV1NQoISHB+3OoH9Pkcrk0YcIEZWZmyuPxhKzuf6urq5Pb7ZYkxcbGqq6uLuQ9bNy4Uenp6SooKAjq2+VPVVZW6siRIxo5cmRY5v/f9aXQzT+cjyn739qfzn3lypVKT0/XsmXLdOPGjaDUlqRvf/vb+slPfqJOnW7HzIULF8LyiLYOd+LhwIED+vvf/6633npLmzZt0l/+8pew9uNyuUL+L+ySJUt04sQJVVRUyO12a8WKFUGt19DQoJycHG3YsEFRUVF3bAvF/P+3fijn35bHlAW69j//+U+tXbtWH374of72t7+pvr5e69atC0rtN954QzExMcrMzAzK8Vsj5CEXFxenqqoq7893e0xTsOpLUkxMjKZOnaqysrKQ1f5Unz59VFtbK0mqra1VTExMyOtHRESoU6dOWrRoUVB/B42NjcrJyVFeXp6mTZvmrR+q+TvVD9X8P+XPY8oCXXvXrl1yu91yuVzq0qWLnnrqqaDN/eDBg/rjH/+opKQk5ebmau/evVq6dGnI5y6FIeSGDx+u48eP69SpU7p586a2bdumyZMnh6T2lStXdPnyZe/f33nnnTvOOobK5MmTtWXLFknheUzVpwEjSdu3bw/a78AYowULFiglJUXLly/3jodq/k71QzX/cD6mzFftgQMHeudujNGOHTuCNve1a9equrpalZWV2rZtm8aNG6ff//734XlEW9BPbfiwc+dO079/f9O3b1/z4x//OGR1T5w4YdLT0016eroZNGhQSGrn5uaa2NhYExkZaeLi4syvf/1rc/78eTNu3DiTnJxsxo8fby5cuBDS+nPmzDFpaWlm8ODB5mtf+5o5c+ZMUGq/9957RpIZPHiwGTJkiBkyZIjZuXNnyObvVD9U8//ggw9MRkaGGTx4sElNTTVr1qwxxtz+/3D48OGmX79+Zvr06eb69eshqz127FiTlpZmUlNTTV5envcMbDDt27fPe3Y1FHP/X9zWBcBqHe7EA4COhZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDu3K4sWL9aMf/Shgx0tKStKePXsCdjzcfyLD3QDw3371q1+FuwVYhpUcWu3WrVsdqi7ub4Qc7klSUpLWrVun9PR0PfTQQzpw4IC+9KUvqXv37hoyZIj279/vfe2YMWP0gx/8QCNGjFBUVJSmTJmi+vp67/YZM2YoNjZWDz/8sEaPHq2jR496t82fP19PP/20JGn//v2Kj4/XunXrFBsbq6eeekrNzc0qLi5Wv379FB0drZkzZ95x7K1btyoxMVHR0dH6v//7v+D/YtDuEXK4ZyUlJdq5c6dOnjypKVOm6Omnn1Z9fb1++tOfKicnR+fOnfO+9ne/+51eeukl1dbWKjIyUt/61re82yZOnKjjx4/r7NmzGjZsmPLy8hxr/uc//1F9fb1Onz4tj8ejX/7yl9qxY4feffddnTlzRj169NA3v/lNSdKxY8e0ZMkSbd26VWfOnNGFCxdUXV0dvF8I7g8GuAeJiYlm8+bNxhhjiouLzZw5c+7YPmHCBPPb3/7WGGPM448/br7//e97tx09etR07tzZ3Lp16zPHvXjxopFkLl26ZIwxJj8/36xcudIYY8y+fftM586dzbVr17yvHzhwoNmzZ4/35zNnzpjIyEjT2Nho1qxZY2bNmuXd1tDQYDp37mx2797d1unjPsZKDvcsISFBknT69Gm9+uqr6t69u/fPgQMHVFtb+5nXSlJiYqIaGxt1/vx5NTU1qaioSP369VNUVJSSkpIkSefPn/dZs3fv3vrc5z7n/fn06dOaOnWqt25KSooiIiJUV1enM2fO3FH3oYceUnR0dCB/BbgPcXYV98zlckm6HWBz587Viy++6Pjaqqoq798/+ugjde7cWb169dIf/vAHlZaWas+ePUpKStLHH3+sHj16yBhz15qfSkhI0EsvvaRHH330M691u93617/+5f356tWrunDhQqvmCPuwkkOrzZkzR3/605/09ttvq6mpSdevX9f+/fvv+Pzr5Zdf1rFjx3T16lWtWrVK06dPV0REhC5fvqwuXbooOjpaV69e1Q9/+MNW1V68eLFWrlyp06dPS5LOnTun0tJSSdL06dP1xhtv6MCBA7p586ZWrVql5ubmwE0c9yVCDq2WkJCg0tJSPfvss+rdu7cSEhL03HPP3REoc+fO1fz58xUbG6vr16/rF7/4hSRp3rx5SkxMVFxcnAYNGqRRo0a1qvbSpUs1efJkTZgwQd26ddOoUaP0/vvvS5JSU1O1adMmPfnkk3K73erRo4fi4+MDN3Hcl1zG6X0C4KcxY8Zozpw5WrhwYbhbAVjJAbAbIQfAarxdBWA1VnIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsNr/AxqJ9meU/CswAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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7nP/PS472hX9j5gbASj7DrbCwUNHR0UpNTfW2rVy5UvHx8crMzFRmZqZ2797drUUCQGf5DLc5c+Zo7969d7UvWrRIlZWVqqys1FNPPdUtxQGAv3yGW05OjqKionqiFgDoMn5fc9uwYYPS09NVWFioxsb2LzoXFxcrKytLWVlZapazi+IAECi/wm3BggU6deqUKisrFRcXpyVLlrTbd/78+aqoqFBFRYX66j6/CwWAzvAr3GJiYhQSEqI+ffpo3rx5Ki8v7+q6ACAgfoWb2+32/r59+/ZWd1IB4F7g8594Z82apQ8++EAXLlzQ0KFD9ctf/lIffPCBKisr5XK5NGLECL3++us9USsAOOYyxpieOlikK0rZrtyeOlyn/eb0IUf90sL6Ourn5OmDq7duONpXV3P6PRBO3ZKz74KwxSc3nI13+X9kd3Ml32yHzAE1mYY21/GEAgArEW4ArES4AbAS4QbASoQbACsRbgCsRLgBsBLhBsBKhBsAK/EdCsBtvjI3HfZkXnCv4wwBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEqEGwArEW4ArES4AbASTyjcxunn3Tv9roVRfV2BlNOtmk2Lo34hrnt3DN3hdLOzv/d8N8K9j5kbACsRbgCsRLgBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEqEGwAr8YSCHx4Mdfo5+327tQ44x3cjfPNwJgFYiXADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWIknFG6T+I/7HPWrvensyYNFJ2b47NP/ydOO9nWvq3k73VG/ETP+r0uP696R5Khf3DOfdOlxce/zOXOrra3VxIkTlZycrJSUFK1du1aS1NDQoLy8PCUmJiovL0+NjY3dXiwAOOUz3EJDQ/Xqq6+qurpaH330kV577TVVV1erqKhIubm5OnnypHJzc1VUVNQT9QKAIz7DLS4uTmPHjpUkRUREKCkpSXV1ddq5c6cKCgokSQUFBdqxY0e3FgoAndGpGwo1NTU6fPiwsrOzVV9fr7i4OElSbGys6uvru6VAAPCH4xsKHo9H06dP15o1axQZGdlqncvlkqudL+8tLi5WcXGxJKlZ1wMoFQCcczRza25u1vTp0zV79mxNmzZNkhQTEyO32y1Jcrvdio6ObnPb+fPnq6KiQhUVFeorZ3cjASBQPsPNGKO5c+cqKSlJixcv9rbn5+erpKREklRSUqIpU6Z0X5UA0Ek+35aWlZVp8+bNSktLU2ZmpiRp9erVWrFihX7wgx/ojTfe0PDhw/XOO+90d60A4JjLGGN66mCRrihlu3J76nAALHfIHFCTaWhzHY9fAbAS4QbASoQbACsRbgCsRLgBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEqEGwArEW4ArES4AbAS4QbASoQbACsRbgCsRLgBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEqEGwArEW4ArES4AbAS4QbASoQbACsRbgCsRLgBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEqEGwArEW4ArES4AbAS4QbASoQbACsRbgCsRLgBsJLPcKutrdXEiROVnJyslJQUrV27VpK0cuVKxcfHKzMzU5mZmdq9e3e3FwsAToX67BAaqldffVVjx47VlStXNG7cOOXl5UmSFi1apKVLl3Z7kQDQWT7DLS4uTnFxcZKkiIgIJSUlqa6urtsLA4BAdOqaW01NjQ4fPqzs7GxJ0oYNG5Senq7CwkI1Nja2uU1xcbGysrKUlZWlZl0PvGIAcMBljDFOOno8Hj3++OP6+c9/rmnTpqm+vl4PPPCAXC6XXnrpJbndbm3cuLHDfUS6opTtyu2SwgHgkDmgJtPQ5jpHM7fm5mZNnz5ds2fP1rRp0yRJMTExCgkJUZ8+fTRv3jyVl5d3XcUAECCf4WaM0dy5c5WUlKTFixd7291ut/f37du3KzU1tXsqBAA/+LyhUFZWps2bNystLU2ZmZmSpNWrV2vr1q2qrKyUy+XSiBEj9Prrr3d3rQDgmONrbl2Ba24AulLA19wAoLch3ABYiXADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWIlwA2Alwg2AlQg3AFYi3ABYiXADYCXCDYCVCDcAViLcAFiJcANgJZ9fENOVwgb3UeOI063azp8/ryFDhvRkGV3OhjFIdozDhjFIdoyjJ8YQVtP+/KxHvyCmLVlZWaqoqAhmCQGzYQySHeOwYQySHeMI9hh4WwrASoQbACsFPdzmz58f7BICZsMYJDvGYcMYJDvGEewxBP2aGwB0h6DP3ACgOwQt3Pbu3avRo0dr5MiRKioqClYZARsxYoTS0tKUmZmprKysYJfjWGFhoaKjo5Wamupta2hoUF5enhITE5WXl6fGxsYgVuhbW2NYuXKl4uPjlZmZqczMTO3evTuIFfpWW1uriRMnKjk5WSkpKVq7dq2k3ncu2htHUM+HCYKbN2+ahIQEc+rUKXP9+nWTnp5uqqqqglFKwIYPH27Onz8f7DI67W9/+5v5+OOPTUpKirdt2bJl5pVXXjHGGPPKK6+Yn/70p8Eqz5G2xvDyyy+b3/3ud0GsqnPOnDljPv74Y2OMMU1NTSYxMdFUVVX1unPR3jiCeT6CMnMrLy/XyJEjlZCQoLCwMM2cOVM7d+4MRinfWDk5OYqKimrVtnPnThUUFEiSCgoKtGPHjiBU5lxbY+ht4uLiNHbsWElSRESEkpKSVFdX1+vORXvjCKaghFtdXZ2GDRvmXR46dGjQXwh/uVwuPfHEExo3bpyKi4uDXU5A6uvrFRcXJ0mKjY1VfX19kCvyz4YNG5Senq7CwsJ7/u3c7WpqanT48GFlZ2f36nNx+zik4J0PbigE6MMPP9Q///lP7dmzR6+99ppKS0uDXVKXcLlccrlcwS6j0xYsWKBTp06psrJScXFxWrJkSbBLcsTj8Wj69Olas2aNIiMjW63rTefiznEE83wEJdzi4+NVW1vrXf7iiy8UHx8fjFIC9nXd0dHRmjp1qsrLy4Nckf9iYmLkdrslSW63W9HR0UGuqPNiYmIUEhKiPn36aN68eb3ifDQ3N2v69OmaPXu2pk2bJql3nov2xhGs8xGUcHv44Yd18uRJnT59Wjdu3NC2bduUn58fjFIC8uWXX+rKlSve3/ft29fqzl1vk5+fr5KSEklSSUmJpkyZEuSKOu/rQJCk7du33/PnwxijuXPnKikpSYsXL/a297Zz0d44gno+gnIbwxiza9cuk5iYaBISEsyvf/3rYJURkFOnTpn09HSTnp5ukpOTe9U4Zs6caWJjY01oaKiJj483f/zjH82FCxfM97//fTNy5EiTm5trLl68GOwyO9TWGJ5//nmTmppq0tLSzNNPP23OnDkT7DI7dPDgQSPJpKWlmYyMDJORkWF27drV685Fe+MI5vngCQUAVuKGAgArEW4ArES4AbAS4QbASoQbACsRbgCsRLgBsBLhBsBK/w/YN4cpjUefeQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pages/43290879-California-101393-0003.jpeg\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1152x1152 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hqErf8/Xv5bmHuv69PPdQ1Q/qc1cBINh4uwrAaoQcAKuFJOR27Nih3r17KzExUUVFRUGtHR8fr7S0NGVkZCgrKyvg9QoKChQVFaXU1FT3WH19vbKzs5WUlKTs7GydPXs2qPUXL16smJgYZWRkKCMjQ6+//npAaldWVmro0KHq27evUlJS9Nxzz0kK3vy91Q/W/EN5mzJvtfPz89WzZ0/33CsqKvxe+4saGxv14IMP6vvf/76kEN2iLdjfWbl27ZpJSEgwx44dM5999plJT083hw4dClr9Hj16mNOnTwet3ltvvWXef/99k5KS4h776U9/apYuXWqMMWbp0qXmqaeeCmr9Z555xixfvjxgNT9XXV1t3n//fWOMMefPnzdJSUnm0KFDQZu/t/rBmv/169fNhQsXjDHGXL161QwcONAcOHDAjB8/3mzcuNEYY8wPfvAD88c//jFotfPy8szmzZv9Xs+bFStWmEmTJpnHHnvMGGOCMvcvC/qRXFlZmRITE5WQkKD77rtPubm5KikpCXYbQTNkyBB16dLlprGSkhLl5eVJCvxtqjzVDxan06n+/ftLunHftOTkZFVVVQVt/t7qB0sob1PmrXYwnTp1Stu3b9eTTz4p6ca9KUNxi7agh1xVVZXi4uLcr4N9myaHw6Hhw4crMzNTLpcraHW/qLa2Vk6nU5IUHR2t2traoPewatUqpaenq6CgIKBvlz934sQJHTx4UIMGDQrJ/L9YXwre/EN5m7Iv1/587gsWLFB6errmzJmjzz77LCC1JenHP/6xfvOb36hNmxsxU1dXF5JbtN1zJx7279+vv//97/rrX/+q1atX6+233w5pPw6HI+j/ws6aNUvHjh1TRUWFnE6n5s2bF9B6Fy9eVE5OjlauXHnLnWiCMf8v1w/m/FtymzJ/1/7Xv/6lpUuX6siRI3rvvfdUX1+vZcuWBaT2a6+9pqioKGVmZgZk/80R9JCLiYlRZWWl+/XtbtMUqPqSFBUVpTFjxqisrCxotT/XvXt3922/a2pqFBUVFfT6YWFhatOmjWbMmBHQv0FDQ4NycnI0efJk9y29gzl/b/WDNf/P+XKbMn/X3rFjh5xOpxwOh9q1a6cnnngiYHMvLS3VX/7yF8XHxys3N1e7d+/W7Nmzgz53KQQhN2DAAB09elTHjx/X1atXtWnTJo0aNSootS9duqQLFy64f3/jjTduOusYLKNGjVJxcbGk0Nym6ovPVdiyZUvA/gbGGE2fPl3JycmaO3euezxY8/dWP1jzD+VtyjzV7tOnj3vuxhht3bo1YHNfunSpTp06pRMnTmjTpk165JFH9PLLL4fmFm0BP7Xhwfbt201SUpJJSEgw//d//xe0useOHTPp6ekmPT3d9O3bNyi1c3NzTXR0tAkPDzcxMTHmz3/+szlz5ox55JFHTGJiohk2bJipq6sLav0pU6aY1NRUk5aWZkaOHGmqq6sDUnvfvn1GkklLSzP9+vUz/fr1M9u3bw/a/L3VD9b8P/jgA5ORkWHS0tJMSkqKWbJkiTHmxn+HAwYMML169TLjxo0zV65cCVrtoUOHmtTUVJOSkmImT57sPgMbSHv27HGfXQ3G3L+My7oAWO2eO/EA4N5CyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiGHkJk5c6Z+9atf+W1/8fHx2rVrl9/2BzsQcgiZP/3pT/rFL34RlFrLly9XamqqIiIi1LNnTy1fvjwodRF64aFuAK3XtWvXFB4emv9E/F3bGKN169YpPT1dx44d0/DhwxUXF6fc3Fy/1UDrxJEcbhIfH69ly5YpPT1d999/v65du6Z33nlH3/jGN9SpUyf169dPe/fuda//8MMP6+c//7kGDhyoDh06aPTo0aqvr3cvHz9+vKKjo9WxY0cNGTJEhw4dci/Lz8/XwoULJUl79+5VbGysli1bpujoaD3xxBO6fv26ioqK1KtXL3Xt2lUTJky4ad/r169Xjx491LVrV/3617++7byeeuop9e/fX+Hh4erdu7dGjx6t0tJSP/3V0JoRcrjFxo0btX37dp07d061tbV67LHHtHDhQtXX1+u3v/2tcnJydPr0aff669at09q1a1VTU6Pw8HD96Ec/ci/73ve+p6NHj+qTTz5R//79NXnyZK91P/74Y9XX1+vkyZNyuVz6wx/+oK1bt+qtt95SdXW1OnfurB/+8IeSpMOHD2vWrFlav369qqurVVdXp1OnTt3R/Iwx2rdvn1JSUnz8C+GuYoAv6NGjh1mzZo37dVFRkZkyZcpN6wwfPty8+OKLxhhjvv3tb5uf/exn7mWHDh0ybdu2NdeuXbtl32fPnjWSzLlz54wxxuTl5ZkFCxYYY4zZs2ePadu2rfn000/d6/fp08fs2rXL/bq6utqEh4ebhoYGs2TJEjNx4kT3sosXL5q2bduanTt3NjnHRYsWmfT0dHPlypUm18Xdj8/kcIu4uDj37ydPntTmzZu1bds291hDQ4OGDh3qcf0ePXqooaFBZ86cUbdu3bRgwQJt3rxZp0+fVps2N944nDlzRh07drylbmRkpL7yla/cVHvMmDHu7SQpLCxMtbW1qq6uvqnu/fffr65duzY5t1WrVmndunXat2+f2rVr1+T6uPsRcriFw+Fw/x4XF6epU6fqhRde8Lp+ZWWl+/f//ve/atu2rbp166YNGzaopKREu3btUnx8vP73v/+pc+fOMsY0Wffz2mvXrtU3v/nNW9Z1Op3697//7X59+fJl1dXV3XZea9euVVFRkd5++23Fxsbedl3Yg8/kcFtTpkzRtm3b9Le//U2NjY26cuWK9u7de9PnXy+99JIOHz6sy5cva9GiRRo3bpzCwsJ04cIFtWvXTl27dtXly5f19NNPN6v2zJkztWDBAp08eVKSdPr0aZWUlEiSxo0bp9dee0379+/X1atXtWjRIl2/ft3rvl5++WU9/fTT2rlzpxISEnz4S+BuRcjhtuLi4lRSUqJnn31WkZGRiouL0/Lly28KlKlTpyo/P1/R0dG6cuWKfv/730uSpk2bph49eigmJkZ9+/bVQw891Kzas2fP1qhRozR8+HBFRETooYce0rvvvitJSklJ0erVq/X444/L6XSqc+fOtz06W7hwoerq6jRgwAC1b99e7du318yZM334i+Bu4zDe3jsAd+Dhhx/WlClT9OSTT4a6FcAjjuQAWI2QA2A13q4CsBpHcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGw2v8DjuQ5lTsSZaQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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mDIYPHw69/otniUNCQlS/xIOIyJMeKeS8vb1RUVGB2tpalJWV4cqVK49cwGq1IiEhAQkJCU53kojIWb36oGj48OFISkrC+fPncevWLfsUj9raWgQHByseY7FYUF5ervp+mYjInRyG3I0bN3Dr1i0AX3wXY0lJCSIjI5GUlIR33nkHAJCfn49Zs2a5taNERM5weHf1X//6FzIzM9HZ2Ymuri6kp6dj/fr1uHbtGjIyMtDc3IynnnoKb731FgYOHNhjsVGjRsFoNAL4Ijz9/f1dNpDe6s/1+/PYPV2/P4/dnfWrq6tVF9qA8BCz2eyp0v2+fn8eu6fr9+exe6o+H94iIqkx5IhIah4LOYvF4qnS/b5+fx67p+v357F7qr7DGw9ERE8yvl0lIqkx5IhIah4JuaNHj2LcuHGIiIhAbm6uprWNRiNiYmIQFxenyVSz7OxsBAQEIDo62t7W3NyM6dOnY+zYsZg+fTpu3rypaf0NGzYgODgYcXFxiIuLw9///ne31K6pqUFSUhImTJiAqKgovP766wC0G79afa3G78llytRqZ2VlYfTo0faxV1RUuLz2l3V2duKpp57C97//fQAeWqJN62dWOjo6RHh4uKiqqhL3798XJpNJXL58WbP6YWFh4saNG5rVe//998UHH3wgoqKi7G0//elPxebNm4UQQmzevFm88sormtZ/7bXXxNatW91W84H6+nrxwQcfCCGEuH37thg7dqy4fPmyZuNXq6/V+Lu6ukRLS4sQQoi2tjYxadIkcf78efHCCy+IwsJCIYQQP/zhD8Wf/vQnzWpnZmaKAwcOuLyemm3bton58+eLmTNnCiGEJmP/Ks2v5MrKyhAREYHw8HAMGDAAGRkZKC4u1robmklMTMTIkSO7tRUXFyMzMxOA+5epUqqvFYPBgPj4eACAr68vIiMjUVdXp9n41eprxZPLlKnV1lJtbS0OHz6Ml156CcAXa1N6Yok2zUOurq4OoaGh9t+1XqZJp9MhJSUFZrMZVqtVs7pfZrPZYDAYAABBQUGw2Wya9yEvLw8mkwnZ2dlufbv8QHV1NS5evIjJkyd7ZPxfrg9oN35PLlP21doPxr527VqYTCasXLkS9+/fd0ttAPjJT36C3/zmN/YFY5uamjyyRFu/u/Fw9uxZfPjhhzhy5Ah27NiB06dPe7Q/Op1O839hc3JyUFVVhYqKChgMBqxevdqt9e7cuYO0tDRs374dQ4cO7bZNi/F/tb6W4+/LMmWurn3p0iVs3rwZV65cwT//+U80Nzdjy5Ytbql96NAhBAQEqH7ZupY0D7ng4GDU1NTYf+9pmSZ31QeAgIAAzJ49G2VlZZrVfiAwMBANDQ0AgIaGBgQEBGhe39vbG15eXli2bJlbX4P29nakpaVh4cKFmDNnjr2+VuNXq6/V+B9wZpkyV9c+evQoDAYDdDodBg4ciCVLlrht7OfOncPf/vY3GI1GZGRk4MSJE1ixYoXmYwc8EHITJ07E1atX8cknn6CtrQ379u1DamqqJrXv3r2LlpYW+8/Hjh3rdtdRK6mpqcjPzwfgmWWqHgQMABw8eNBtr4EQAkuXLkVkZCRWrVplb9dq/Gr1tRq/J5cpU6o9fvx4+9iFECgqKnLb2Ddv3oza2lpUV1dj3759mDZtGt5++23PLNHm9lsbCg4fPizGjh0rwsPDxa9+9SvN6lZVVQmTySRMJpOYMGGCJrUzMjJEUFCQ0Ov1Ijg4WLz55puisbFRTJs2TURERIjk5GTR1NSkaf1FixaJ6OhoERMTI55//nlRX1/vltpnzpwRAERMTIyIjY0VsbGx4vDhw5qNX62+VuP/6KOPRFxcnIiJiRFRUVFi48aNQogv/h5OnDhRjBkzRsydO1e0trZqVjspKUlER0eLqKgosXDhQvsdWHc6efKk/e6qFmP/Kk7rIiKp9bsbD0TUvzDkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDnymOXLl+OXv/yly85nNBpRWlrqsvORHBhy5DF//vOf8Ytf/EKTWlu3bkV0dDR8fX0xevRobN26VZO65Hl6T3eAHl8dHR3Q6z3zV8TVtYUQ2LNnD0wmE6qqqpCSkoLQ0FBkZGS4rAY9nnglR90YjUZs2bIFJpMJgwcPRkdHBy5cuIApU6Zg+PDhiI2NxalTp+z7P/vss/j5z3+OSZMmYejQoZg1axaam5vt21944QUEBQVh2LBhSExMxOXLl+3bsrKysG7dOgDAqVOnEBISgi1btiAoKAhLlixBV1cXcnNzMWbMGPj5+SE9Pb3buQsKChAWFgY/Pz/8+te/7nFcr7zyCuLj46HX6zFu3DjMmjUL586dc9GrRo8zhhw9pLCwEIcPH8atW7dgs9kwc+ZMrFu3Ds3Nzfjtb3+LtLQ03Lhxw77/nj17sHv3bjQ0NECv1+PHP/6xfduMGTNw9epVfPrpp4iPj8fChQtV6/7vf/9Dc3Mzrl+/DqvVij/+8Y8oKirC+++/j/r6eowYMQI/+tGPAACVlZXIyclBQUEB6uvr0dTUhNra2kcanxACZ86cQVRUlJOvED1RBNGXhIWFiV27dtl/z83NFYsWLeq2T0pKivjrX/8qhBDiO9/5jvjZz35m33b58mXh4+MjOjo6Hjr3zZs3BQBx69YtIYQQmZmZYu3atUIIIU6ePCl8fHzE559/bt9//PjxorS01P57fX290Ov1or29XWzcuFHMmzfPvu3OnTvCx8dHlJSUOBzj+vXrhclkEq2trQ73pScfP5Ojh4SGhtp/vn79Og4cOIB3333X3tbe3o6kpCTF/cPCwtDe3o7GxkaMGjUKa9euxYEDB3Djxg14eX3xxqGxsRHDhg17qK6/vz8GDRrUrfbs2bPtxwGAt7c3bDYb6uvru9UdPHgw/Pz8HI4tLy8Pe/bswZkzZzBw4ECH+9OTjyFHD9HpdPafQ0ND8eKLL2Lnzp2q+9fU1Nh//u9//wsfHx+MGjUKe/fuRXFxMUpLS2E0GvHZZ59hxIgREEI4rPug9u7du/Htb3/7oX0NBgP+/e9/23+/d+8empqaehzX7t27kZubi9OnTyMkJKTHfUke/EyOerRo0SK8++67eO+999DZ2YnW1lacOnWq2+dfb731FiorK3Hv3j2sX78ec+fOhbe3N1paWjBw4ED4+fnh3r17ePXVV3tVe/ny5Vi7di2uX78OALhx4waKi4sBAHPnzsWhQ4dw9uxZtLW1Yf369ejq6lI919tvv41XX30VJSUlCA8Pd+KVoCcVQ456FBoaiuLiYmzatAn+/v4IDQ3F1q1buwXKiy++iKysLAQFBaG1tRV/+MMfAACLFy9GWFgYgoODMWHCBDz99NO9qr1ixQqkpqYiJSUFvr6+ePrpp/GPf/wDABAVFYUdO3ZgwYIFMBgMGDFiRI9XZ+vWrUNTUxMmTpyIIUOGYMiQIVi+fLkTrwg9aXRC7b0D0SN49tlnsWjRIrz00kue7gqRIl7JEZHUGHJEJDW+XSUiqfFKjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKp/R+Krt5a3opZnAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "error",
     "evalue": "OpenCV(4.9.0) /io/opencv/modules/imgproc/src/morph.dispatch.cpp:1022: error: (-215:Assertion failed) !src.empty() in function 'dilate'\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31merror\u001b[0m                                     Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[9], line 64\u001b[0m\n\u001b[1;32m     61\u001b[0m         plt\u001b[38;5;241m.\u001b[39mshow()\n\u001b[1;32m     62\u001b[0m     \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mprecision \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcnt_true_positive\u001b[38;5;241m/\u001b[39mcnt_detected\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m recall \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcnt_true_positive\u001b[38;5;241m/\u001b[39mWs\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m---> 64\u001b[0m \u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mpages\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpage_range\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m8\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmodel\u001b[49m\u001b[43m)\u001b[49m\n",
      "Cell \u001b[0;32mIn[9], line 44\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(path, page_range, model, debug)\u001b[0m\n\u001b[1;32m     42\u001b[0m plt\u001b[38;5;241m.\u001b[39maxis(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moff\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m     43\u001b[0m cell_img \u001b[38;5;241m=\u001b[39m grayimage[h_lines[i]\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m5\u001b[39m:h_lines[i\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m]\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m5\u001b[39m, v_lines[\u001b[38;5;241m11\u001b[39m]:v_lines[\u001b[38;5;241m12\u001b[39m]]\n\u001b[0;32m---> 44\u001b[0m prepared_cell_image \u001b[38;5;241m=\u001b[39m \u001b[43mcrop_cell\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcell_img\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     45\u001b[0m tensor, noop \u001b[38;5;241m=\u001b[39m normalize_img(prepared_cell_image, \u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m     46\u001b[0m result \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mpredict(np\u001b[38;5;241m.\u001b[39mexpand_dims(tensor, \u001b[38;5;241m0\u001b[39m), verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n",
      "Cell \u001b[0;32mIn[4], line 5\u001b[0m, in \u001b[0;36mcrop_cell\u001b[0;34m(cell_img, debug)\u001b[0m\n\u001b[1;32m      3\u001b[0m     view(cell_img, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minput\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      4\u001b[0m ret,cell_img \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39mthreshold(cell_img,\u001b[38;5;241m155\u001b[39m,\u001b[38;5;241m255\u001b[39m,cv2\u001b[38;5;241m.\u001b[39mTHRESH_TOZERO)\n\u001b[0;32m----> 5\u001b[0m cell_img \u001b[38;5;241m=\u001b[39m \u001b[43mzap_lower_horiz_lines\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcell_img\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      7\u001b[0m contours, hierarchy \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39mfindContours(cell_img,cv2\u001b[38;5;241m.\u001b[39mRETR_TREE,cv2\u001b[38;5;241m.\u001b[39mCHAIN_APPROX_SIMPLE)\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m# Find the largest contour by area\u001b[39;00m\n",
      "Cell \u001b[0;32mIn[3], line 30\u001b[0m, in \u001b[0;36mzap_lower_horiz_lines\u001b[0;34m(img, debug)\u001b[0m\n\u001b[1;32m     28\u001b[0m         img[idx, :] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m     29\u001b[0m         view(img, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdeleted 2\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 30\u001b[0m     img[idx\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m2\u001b[39m:idx\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m2\u001b[39m, :] \u001b[38;5;241m=\u001b[39m \u001b[43mclose\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[43m[\u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     31\u001b[0m     view(img, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrepaired 2\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     32\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m img\n",
      "Cell \u001b[0;32mIn[3], line 11\u001b[0m, in \u001b[0;36mclose\u001b[0;34m(img)\u001b[0m\n\u001b[1;32m      4\u001b[0m kerns \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m      5\u001b[0m     \u001b[38;5;66;03m#cv2.getStructuringElement(cv2.MORPH_RECT, (1, 3))\u001b[39;00m\n\u001b[1;32m      6\u001b[0m     np\u001b[38;5;241m.\u001b[39marray([[ \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m ], [ \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m0\u001b[39m ], [\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m0\u001b[39m ]], dtype\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39muint8),\n\u001b[1;32m      7\u001b[0m     \u001b[38;5;66;03m#np.array([[ 0, 1, 0 ], [ 0, 1, 0 ], [0, 1, 0 ]], dtype=np.uint8),\u001b[39;00m\n\u001b[1;32m      8\u001b[0m     \u001b[38;5;66;03m#np.array([[ 1, 0, 0 ], [ 0, 1, 0 ], [0, 0, 1 ]], dtype=np.uint8),\u001b[39;00m\n\u001b[1;32m      9\u001b[0m ]\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m kerns:\n\u001b[0;32m---> 11\u001b[0m     img \u001b[38;5;241m=\u001b[39m \u001b[43mcv2\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdilate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43miterations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     12\u001b[0m     img \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39merode(img, k, iterations\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m     13\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m img\n",
      "\u001b[0;31merror\u001b[0m: OpenCV(4.9.0) /io/opencv/modules/imgproc/src/morph.dispatch.cpp:1022: error: (-215:Assertion failed) !src.empty() in function 'dilate'\n"
     ]
    }
   ],
   "source": [
    "import glob\n",
    "import re\n",
    "import cv2\n",
    "\n",
    "lookup = list(\"abcdefghijklmnopqrstuvwxyz\".upper())\n",
    "not_Ws = {\n",
    "    2: [6],\n",
    "    3: [3, 4, 11, 12, 28],\n",
    "    4: [],\n",
    "    5: [],\n",
    "    6: [3,4],\n",
    "    7: []\n",
    "}\n",
    "\n",
    "Ws = 30*5-8\n",
    "\n",
    "def run(path, page_range=(2, 16), model=None, debug=False):\n",
    "    cnt_detected = 0\n",
    "    cnt_true_positive = 0\n",
    "    cnt_false_positive = 0\n",
    "    cnt_true_negative = 0\n",
    "    cnt_false_negative = 0\n",
    "    \n",
    "    for f in sorted(glob.glob(f'{path}/*')):\n",
    "        pagestr = re.search(r'-(\\d+).jpeg', f).group(1)\n",
    "        if int(pagestr) not in range(page_range[0], page_range[1]):\n",
    "            continue\n",
    "        plt.figure(figsize=(16, 16))\n",
    "        print(f)\n",
    "        image = cv2.imread(f)\n",
    "        (adjusted_img, v_lines, h_lines) = extract(image, f, debug=debug)\n",
    "        grayimage = cv2.cvtColor(adjusted_img,cv2.COLOR_BGR2GRAY)\n",
    "        grayimage = 255 - grayimage\n",
    "        demo_h_offset = v_lines[11]  # the demographic column starts the the 12th vertical line\n",
    "        demo_width = v_lines[12] - demo_h_offset  # width calculation\n",
    "        # Open CV rectangles calculation for each demographic cell\n",
    "        demographic_cells = \\\n",
    "          [ (demo_h_offset, h_lines[i], demo_width, int(h_lines[i+1]-h_lines[i])) for i in range(3, len(h_lines)-1)]\n",
    "        for i in range(3, len(h_lines)-1):\n",
    "            num = i-2\n",
    "            ax = plt.subplot(5, 6, i - 2)\n",
    "            plt.axis('off')\n",
    "            cell_img = grayimage[h_lines[i]+5:h_lines[i+1]+5, v_lines[11]:v_lines[12]]\n",
    "            prepared_cell_image = crop_cell(cell_img)\n",
    "            tensor, noop = normalize_img(prepared_cell_image, 0)\n",
    "            result = model.predict(np.expand_dims(tensor, 0), verbose=0)\n",
    "            classes_x=np.argmax(result,axis=1)\n",
    "            if classes_x[0] == 22:\n",
    "                cnt_detected += 1\n",
    "                if num in not_Ws[int(pagestr)]:\n",
    "                    cnt_false_positive += 1\n",
    "                else:\n",
    "                    cnt_true_positive += 1\n",
    "            else:\n",
    "                if num in not_Ws[int(pagestr)]:\n",
    "                    cnt_true_negative += 1\n",
    "                else:\n",
    "                    cnt_false_negative += 1\n",
    "            plt.imshow(prepared_cell_image)\n",
    "            plt.title(f'{pagestr}-{num} {classes_x[0]-1} {lookup[int(classes_x[0])-1]} ({result[0][int(classes_x[0])]:.2f})')\n",
    "        plt.show()\n",
    "    print(f'precision {cnt_true_positive/cnt_detected} recall {cnt_true_positive/Ws}')\n",
    "\n",
    "run('pages', page_range=(2,8), model=model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Results\n",
    "\n",
    "Looking at the results we see that precision is perfect, but recall is quite poor, at less than ten percent of Ws being detected. We definitely want to detect more Ws than this if we want to save researchers time.\n",
    "\n",
    "## Using a Convolutional Neural Network (CNN)\n",
    "\n",
    "A convolutional neural network is inspired by the topology of the optic nerve in animals, which includes layers of locally interconnected neurons that recognize minor features in parts of an image. A CNN defines kernels of locally connected neurons of a certain size. These \"context windows\" are 3x3 pixels in our model, which includes two such convolved layers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape              </span>┃<span style=\"font-weight: bold\">    Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩\n",
       "│ conv2d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">26</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">26</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)        │        <span style=\"color: #00af00; text-decoration-color: #00af00\">320</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ max_pooling2d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)        │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ conv2d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv2D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">11</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">11</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │     <span style=\"color: #00af00; text-decoration-color: #00af00\">18,496</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ max_pooling2d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling2D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">5</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">5</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)          │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ flatten_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1600</span>)              │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dropout (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">1600</span>)              │          <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dense_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">27</span>)                │     <span style=\"color: #00af00; text-decoration-color: #00af00\">43,227</span> │\n",
       "└─────────────────────────────────┴───────────────────────────┴────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape             \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m   Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━┩\n",
       "│ conv2d (\u001b[38;5;33mConv2D\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m26\u001b[0m, \u001b[38;5;34m26\u001b[0m, \u001b[38;5;34m32\u001b[0m)        │        \u001b[38;5;34m320\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ max_pooling2d (\u001b[38;5;33mMaxPooling2D\u001b[0m)    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m, \u001b[38;5;34m13\u001b[0m, \u001b[38;5;34m32\u001b[0m)        │          \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ conv2d_1 (\u001b[38;5;33mConv2D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m11\u001b[0m, \u001b[38;5;34m11\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │     \u001b[38;5;34m18,496\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ max_pooling2d_1 (\u001b[38;5;33mMaxPooling2D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m5\u001b[0m, \u001b[38;5;34m5\u001b[0m, \u001b[38;5;34m64\u001b[0m)          │          \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ flatten_1 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1600\u001b[0m)              │          \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dropout (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1600\u001b[0m)              │          \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼───────────────────────────┼────────────┤\n",
       "│ dense_2 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m27\u001b[0m)                │     \u001b[38;5;34m43,227\u001b[0m │\n",
       "└─────────────────────────────────┴───────────────────────────┴────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">62,043</span> (242.36 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m62,043\u001b[0m (242.36 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">62,043</span> (242.36 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m62,043\u001b[0m (242.36 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 1.3901 - sparse_categorical_accuracy: 0.5895 - val_loss: 0.4764 - val_sparse_categorical_accuracy: 0.8498\n",
      "Epoch 2/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.4958 - sparse_categorical_accuracy: 0.8448 - val_loss: 0.3770 - val_sparse_categorical_accuracy: 0.8797\n",
      "Epoch 3/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.4061 - sparse_categorical_accuracy: 0.8732 - val_loss: 0.3338 - val_sparse_categorical_accuracy: 0.8953\n",
      "Epoch 4/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.3583 - sparse_categorical_accuracy: 0.8853 - val_loss: 0.3145 - val_sparse_categorical_accuracy: 0.9000\n",
      "Epoch 5/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.3285 - sparse_categorical_accuracy: 0.8938 - val_loss: 0.2912 - val_sparse_categorical_accuracy: 0.9070\n",
      "Epoch 6/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.3080 - sparse_categorical_accuracy: 0.9002 - val_loss: 0.2831 - val_sparse_categorical_accuracy: 0.9103\n",
      "Epoch 7/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2925 - sparse_categorical_accuracy: 0.9044 - val_loss: 0.2743 - val_sparse_categorical_accuracy: 0.9116\n",
      "Epoch 8/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2780 - sparse_categorical_accuracy: 0.9085 - val_loss: 0.2633 - val_sparse_categorical_accuracy: 0.9149\n",
      "Epoch 9/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2671 - sparse_categorical_accuracy: 0.9112 - val_loss: 0.2577 - val_sparse_categorical_accuracy: 0.9167\n",
      "Epoch 10/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2595 - sparse_categorical_accuracy: 0.9127 - val_loss: 0.2535 - val_sparse_categorical_accuracy: 0.9169\n",
      "Epoch 11/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2517 - sparse_categorical_accuracy: 0.9169 - val_loss: 0.2518 - val_sparse_categorical_accuracy: 0.9182\n",
      "Epoch 12/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2457 - sparse_categorical_accuracy: 0.9177 - val_loss: 0.2473 - val_sparse_categorical_accuracy: 0.9184\n",
      "Epoch 13/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2370 - sparse_categorical_accuracy: 0.9201 - val_loss: 0.2410 - val_sparse_categorical_accuracy: 0.9187\n",
      "Epoch 14/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2322 - sparse_categorical_accuracy: 0.9216 - val_loss: 0.2439 - val_sparse_categorical_accuracy: 0.9202\n",
      "Epoch 15/15\n",
      "\u001b[1m694/694\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 7ms/step - loss: 0.2306 - sparse_categorical_accuracy: 0.9216 - val_loss: 0.2391 - val_sparse_categorical_accuracy: 0.9195\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x79e2d79c1000>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "conv_model = tf.keras.models.Sequential(\n",
    "  [\n",
    "    tf.keras.Input(shape=(28, 28, 1)),\n",
    "    tf.keras.layers.Conv2D(32, kernel_size=(3, 3), activation=\"relu\"),\n",
    "    tf.keras.layers.MaxPooling2D(pool_size=(2, 2)),\n",
    "    tf.keras.layers.Conv2D(64, kernel_size=(3, 3), activation=\"relu\"),\n",
    "    tf.keras.layers.MaxPooling2D(pool_size=(2, 2)),\n",
    "    tf.keras.layers.Flatten(),\n",
    "    tf.keras.layers.Dropout(0.5),\n",
    "    tf.keras.layers.Dense(27, activation=\"softmax\"),\n",
    "  ] \n",
    ")\n",
    "\n",
    "conv_model.compile(\n",
    "    optimizer=tf.keras.optimizers.Adam(0.001),\n",
    "    loss=tf.keras.losses.SparseCategoricalCrossentropy(),\n",
    "    metrics=[tf.keras.metrics.SparseCategoricalAccuracy()],\n",
    ")\n",
    "\n",
    "conv_model.summary()\n",
    "\n",
    "conv_model.fit(\n",
    "    ds_train_final,\n",
    "    epochs=15,\n",
    "    validation_data=ds_test_final,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pages/43290879-California-101393-0002.jpeg\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1152x1152 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 360x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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h/fv3Kz4+XmPGjNGf//xnSVJhYaEmT54c0EIBwBeNLn/+/vvvKycnR3fu3FFDQ4OmT5+un/70p/rwww+VnZ2t2tpaPfHEE/rjH/+odu3aPbSzbt26KTY2VtLd8OzevbvfBtJUrbn/1jz2UPffmsceyP7LyspUU1PjfaMJkdTU1FB13er7b81jD3X/rXnsoeqfJx4AWI2QA2C1kIVcXl5eqLpu9f235rGHuv/WPPZQ9R/U710FgGDj7SoAqxFyAKwWkpDbu3evBgwYoLi4OOXn5we179jYWCUlJSklJSUoj5rl5uYqOjpaiYmJnrba2lplZGSof//+ysjI0OXLl4Pa//LlyxUTE6OUlBSlpKTojTfeCEjf5eXlGjNmjAYNGqSEhAT9+te/lhS88Tv1H6zxh3KZMqe+58yZo69+9auesZeWlvq978+6c+eOnnjiCX3zm9+UFKIl2oJ9z8rt27dN3759zdmzZ82tW7dMcnKyOXXqVND679Onj7l48WLQ+jt06JB57733TEJCgqftRz/6kVm5cqUxxpiVK1eaH//4x0Ht/8UXXzS//OUvA9bnPZWVlea9994zxhjzySefmP79+5tTp04FbfxO/Qdr/A0NDebq1avGGGPq6urMsGHDzNGjR820adPM5s2bjTHGPPfcc+a3v/1t0PrOyckx27Zt83t/TlatWmVmzpxpJk2aZIwxQRn75wV9JldcXKy4uDj17dtXbdu2VXZ2toqKioJdRtCMHj1aXbp0ua+tqKhIOTk5kgK/TJW3/oPF7XZryJAhkqTIyEjFx8eroqIiaON36j9YQrlMmVPfwXThwgXt3r1bzz77rCTJGBOSJdqCHnIVFRXq3bu35+dgL9Pkcrk0btw4paamqqCgIGj9flZ1dbXcbreku98rW11dHfQa1qxZo+TkZOXm5gb07fI9ZWVlOn78uIYPHx6S8X+2fyl44w/lMmWf7/ve2JctW6bk5GQtWrRIt27dCkjfkvSDH/xAv/jFLxQWdjdmLl26FJIl2lrdhYfDhw/rX//6l/bs2aNXX31Vb7/9dkjrcblcQf8/7IIFC3T27FmVlpbK7XZryZIlAe3v2rVrysrK0urVq9WpU6f7tgVj/J/vP5jjb84yZf7u++TJk1q5cqVOnz6td999V7W1tfr5z38ekL537dql6OhopaamBuT8TRH0kIuJiVF5ebnn54ct0xSo/iUpOjpaU6ZMUXFxcdD6vqdHjx6qqqqSJFVVVSk6Ojro/YeHhyssLEzz5s0L6O+gvr5eWVlZmjVrlqZOnerpP1jjd+o/WOO/x5dlyvzd9969e+V2u+VyudSuXTs988wzARv7kSNH9Ne//lWxsbHKzs7WgQMHtHDhwqCPXQpByA0dOlRnzpzRuXPnVFdXpy1btigzMzMofV+/fl1Xr171/Hnfvn33XXUMlszMTBUWFkoKzTJV9wJGknbs2BGw34ExRnPnzlV8fLwWL17saQ/W+J36D9b4Q7lMmbe+Bw4c6Bm7MUY7d+4M2NhXrlypCxcuqKysTFu2bNHYsWP1+uuvh2aJtoBf2vBi9+7dpn///qZv377m5ZdfDlq/Z8+eNcnJySY5OdkMGjQoKH1nZ2ebnj17moiICBMTE2PWr19vampqzNixY01cXJxJT083ly5dCmr/3/3ud01iYqJJSkoy3/rWt0xlZWVA+v7nP/9pJJmkpCQzePBgM3jwYLN79+6gjd+p/2CN/8SJEyYlJcUkJSWZhIQE89JLLxlj7v47HDp0qOnXr595+umnzc2bN4PW95gxY0xiYqJJSEgws2bN8lyBDaS33nrLc3U1GGP/PB7rAmC1VnfhAUDrQsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohh2abM2eOXnjhhUb3i42N1ZtvvhmEiqRvfOMbWr9+fVD6QstGyKHFKSsrk8vl0u3bt0NdCixAyAGwGiGHJjt+/LiGDBmiyMhIzZgxQzdv3vRs27Vrl1JSUhQVFaUnn3xS77//vtdzNDQ0KD8/X/369VPXrl01ffp01dbWSpJGjx4tSYqKilLHjh119OhRSdLvf/97xcfHq3Pnzho/frzOnz/vOd/+/fs1cOBAPfbYY3r++edljAnU8PEFQ8ihSerq6vTtb39b3/ve91RbW6tp06bpL3/5i6S74Zebm6u1a9fq0qVLeu6555SZmalbt249cJ7f/OY32rlzpw4dOqTKykp17txZ3//+9yVJb7/9tiTpypUrunbtmkaMGKGioiKtWLFC27dv18WLF/X1r39dM2fOlCTV1NRo6tSpevnll1VTU6N+/frpyJEjQfqNoMUzQBMcOnTIuN1u09DQ4GkbMWKEWbZsmZk/f7554YUX7tv/8ccfNwcPHjTGGNOnTx+zf/9+Y4wxAwcONG+++aZnv8rKShMREWHq6+vNuXPnjCRTX1/v2T5hwgSzfv16z8937twx7du3N2VlZaawsNAMHz7cs62hocHExMSYdevW+Xfw+EJiJocmqaysVExMjFwul6etT58+kqTz589r1apVioqK8rzKy8tVWVn5wHnOnz+vKVOmePaLj49XeHi4qqurvfZ7/vx5LVy40LN/ly5dZIxRRUWFKisr1bt3b8++Lpfrvp/RuhFyaBK3262Kior7PvP66KOPJEm9e/fWsmXLdOXKFc/r008/9byt/KzevXtrz5499+178+bNBwL0s/uvXbv2vv1v3LihJ598Um63W+Xl5Z59jTH3/YzWjZBDk4wYMUIRERF65ZVXVF9fr+3bt6u4uFiSNG/ePP3ud7/TsWPHZIzR9evXtXv3bl29evWB88yfP1/Lli3zXDy4ePGiioqKJEndu3dXWFiYPvzww/v2X7lypU6dOiVJ+t///qdt27ZJkiZNmqRTp05p+/btun37tl555RV9/PHHAf094IuDkEOTtG3bVtu3b9fGjRvVpUsX/elPf9LUqVMlSWlpaVq3bp2ef/55de7cWXFxcdq4caPX8yxcuFCZmZkaN26cIiMj9bWvfU3Hjh2TJHXo0EHLli3TyJEjFRUVpXfeeUdTpkzRT37yE2VnZ6tTp05KTEzUnj17JEndunXTtm3btHTpUnXt2lVnzpzRyJEjg/L7QMvnMoZr7QDsxUwOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDV/g9S4YX+bJAwJAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ioqJCsz569GjpOp988olmfezYsZr1nTt3Srd1/1m9D+vfv79mva6uTrqtqKgo6TJ3kD2ZbuDAgZr1QYMGubIdq8LCQs36/afrPez+g+G1yB7wPGDAAM16e3u7dFvu+H+4MzySIyKlMeSISGkMOSJSGkOOiJTGkCMipdkMubt372L8+PGIj49HdHQ0XnvtNQDApUuXMGHCBERGRmLu3LloaWlxebNERPayeYO+EAK3bt3C448/jtbWVkycOBFvvPEGfvvb32LWrFnIyMjA0qVLER8fj2XLlnU6WFJSEk6ePPlI/c6dO9J1ZFNNu4PsNDoAlJaWatZTU1Nd1Y7Vn/70J+myadOmadZllzH89a9/lW4rOzvbrr76ui+//FKzLrtMBgCampo06zdv3tSsh4SESLfl5eWlWZc9KiAiIkK6LZm2tjbNemdT3x84cECz3tjYqFl35L+7bt2gr9PprM86aG1tRWtrK3Q6HY4ePYrZs2cDALKysrB//367GyMicrUufSfX3t6OhIQE6PV6TJ48GSNGjIC/v7/1Ir/Q0FDpbwsiIk/qUsh5eXmhoqICNTU1KCsrw6efftrlAcxmM5KTk5GcnIyGhgaHGyUicoRdZ1f9/f2RmpqKkydP4ubNm9bP5zU1NdLvCkwmE8rLy1FeXt7pbVJERK5gM+SuXbtm/RL0zp07KCoqQlRUFFJTU7F3714AQH5+PmbMmOHSRomIHGHz7Op///tfZGVlob29HR0dHZgzZw7WrFmDixcvIiMjA42NjRg7dizeeecd6c279w0bNgxGoxHAV+HZ2Q3CrtaXx+/L++7p8fvyvrty/KqqKvnXYcJDkpKSPDV0nx+/L++7p8fvy/vuqfF5xwMRKY0hR0RK81jImUwmTw3d58fvy/vu6fH78r57any3PneViMjd+HGViJTGkCMipXkk5A4fPoxRo0YhMjISeXl5bh3baDQiNjYWCQkJSE5Odvl4OTk50Ov1iImJsdYaGxsxefJkjBw5EpMnT5Y+GMVV469duxYhISFISEhAQkICDh065JKxq6urkZqaijFjxiA6OhpvvPEGAPftv2x8d+2/J6cpk42dnZ2Nb33rW9Z9lz3gyFna29sxduxYfO973wPgoSna3H3NSltbm4iIiBAXLlwQ9+7dE3FxceLs2bNuGz88PFxcu3bNbeN9+OGH4qOPPhLR0dHW2k9+8hOxYcMGIYQQGzZsED/96U/dOv5rr70mXn/9dZeNeV9dXZ346KOPhBBCfPnll2LkyJHi7Nmzbtt/2fju2v+Ojg7R1NQkhBCipaVFjB8/Xpw8eVK8+OKLoqCgQAghxPe//33x5ptvum3srKwssWfPHqePJ7Np0yYxb948MW3aNCGEcMu+P8ztR3JlZWWIjIxEREQE+vfvj4yMDOmj1FSQkpKCoUOHPlArLCxEVlYWANdPU6U1vrsYDAYkJiYCAHx9fREVFYXa2lq37b9sfHfx5DRlsrHdqaamBgcPHsTLL78M4Ku5KT0xRZvbQ662thZhYWHW1+6epkmn02HKlClISkqC2Wx227hfZ7FYYDAYAADBwcGwWCxu72HLli2Ii4tDTk6OSz8u31dVVYVTp05hwoQJHtn/r48PuG//PTlN2cNj39/31atXIy4uDitWrMC9e/dcMjYA/OhHP8Kvf/1r64Sa169f98gUbX3uxENpaSn+85//4O9//zu2bt2K48ePe7QfnU7n9t+wy5Ytw4ULF1BRUQGDwYBVq1a5dLzm5makp6dj8+bN8PPze2CZO/b/4fHduf/dmabM2WOfOXMGGzZswKeffop///vfaGxsxMaNG10y9oEDB6DX65GUlOSS7dvD7SEXEhKC6upq6+vOpmly1fgAoNfrMXPmTJSVlblt7PuCgoJQX18PAKivr4der3f7+F5eXujXrx+WLFni0p9Ba2sr0tPTkZmZiVmzZlnHd9f+y8Z31/7f58g0Zc4e+/DhwzAYDNDpdBgwYAAWLVrksn0/ceIE/va3v8FoNCIjIwNHjx7F8uXL3b7vgAdCbty4caisrMSlS5fQ0tKCXbt2Yfr06W4Z+9atW9Y59W/duoUjR448cNbRXaZPn478/HwAnpmm6n7AAMC+fftc9jMQQmDx4sWIiorCypUrrXV37b9sfHftvyenKdMae/To0dZ9F0Jg//79Ltv3DRs2oKamBlVVVdi1axcmTZqEd9991zNTtLn81IaGgwcPipEjR4qIiAjxy1/+0m3jXrhwQcTFxYm4uDgxZswYt4ydkZEhgoODhbe3twgJCRF//OMfRUNDg5g0aZKIjIwUaWlp4vr1624df8GCBSImJkbExsaKF154QdTV1blk7H/84x8CgIiNjRXx8fEiPj5eHDx40G37LxvfXft/+vRpkZCQIGJjY0V0dLRYt26dEOKr/w7HjRsnRowYIWbPni3u3r3rtrFTU1NFTEyMiI6OFpmZmdYzsK507Ngx69lVd+z7w3hbFxEprc+deCCivoUhR0RKY8gRkdIYckSkNIYcESmNIUdESmPIEZHSGHJEpDSGHBEpjSFHREpjyBGR0hhyRKQ0hhwRKY0hR0RKY8gRkdIYckSkNIYcESmNIUdESmPIEZHSGHJEpDSGHBEpjSFHREpjyBGR0hhyRKQ0hhwRKY0hR0RKY8gRkdIYckSkNIYcESmNIUdESmPIEZHSGHJEpDSGHBEpjSFHREpjyBGR0hhyRKQ0hhwRKY0hR0RKY8gRkdIYckSkNIYcESmNIUdESmPIEZHSGHJEpDSGHBEpjSFHREpjyBGR0hhyRKQ0hhwRKY0hR0RKY8hRj7J06VL84he/cNr2jEYjiouLnbY96n28Pd0A0df94Q9/8HQLpBgeyZHd2tra+tS41Lsx5KhLjEYjNm7ciLi4ODz22GMoLS3FU089BX9/f8THx6OkpMT63meffRY/+9nPMH78ePj5+WHGjBlobGy0Ln/xxRcRHByMIUOGICUlBWfPnrUuy87OxquvvgoAKCkpQWhoKDZu3Ijg4GAsWrQIHR0dyMvLw4gRIxAYGIg5c+Y8sO0dO3YgPDwcgYGB+NWvfuX6Hwz1eAw56rKCggIcPHgQFy9exIwZM/Dqq6+isbERv/nNb5Ceno5r165Z3/uXv/wFb7/9Nurr6+Ht7Y0f/vCH1mXf/e53UVlZiatXryIxMRGZmZnSMa9cuYLGxkZcvnwZZrMZv//977F//358+OGHqKurQ0BAAH7wgx8AAM6dO4dly5Zhx44dqKurw/Xr11FTU+O6Hwj1DoKoC8LDw8X27duFEELk5eWJBQsWPLB8ypQp4s9//rMQQohnnnlGvPLKK9ZlZ8+eFT4+PqKtre2R7d64cUMAEDdv3hRCCJGVlSVWr14thBDi2LFjwsfHR9y5c8f6/tGjR4vi4mLr67q6OuHt7S1aW1vFunXrxNy5c63LmpubhY+PjygqKuru7lMvxiM56rKwsDAAwOXLl7Fnzx74+/tb/5SWlqK+vv6R9wJAeHg4Wltb0dDQgPb2duTm5mLEiBHw8/OD0WgEADQ0NGiOOXz4cAwcOND6+vLly5g5c6Z13KioKHh5ecFisaCuru6BcR977DEEBgY680dAvRDPrlKX6XQ6AF8F2EsvvYRt27ZJ31tdXW39++effw4fHx8MGzYMO3fuRGFhIYqLi2E0GvHFF18gICAAQohOx7wvLCwMb7/9Np5++ulH3mswGPDJJ59YX9++fRvXr1+3ax9JPTySI7stWLAA7733Ht5//320t7fj7t27KCkpeeD7r3feeQfnzp3D7du3sWbNGsyePRteXl5oamrCgAEDEBgYiNu3b+PnP/+5XWMvXboUq1evxuXLlwEA165dQ2FhIQBg9uzZOHDgAEpLS9HS0oI1a9ago6PDeTtOvRJDjuwWFhaGwsJCrF+/HsOHD0dYWBhef/31BwLlpZdeQnZ2NoKDg3H37l387ne/AwAsXLgQ4eHhCAkJwZgxY/Dkk0/aNfby5csxffp0TJkyBb6+vnjyySfxr3/9CwAQHR2NrVu3Yv78+TAYDAgICEBoaKjzdpx6JZ2QfU4gctCzzz6LBQsW4OWXX/Z0K0Q8kiMitTHkiEhp/LhKRErjkRwRKY0hR0RKY8gRkdIYckSkNIYcESmNIUdESvs/OSehcIXTRU8AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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G8aSkJJWWlgakiejo6IAcBwCuxx0PAKxGyAGwGiEHwGqEHACrEXIArBbS5c/79evnfTBybW2t+vfvH6rSN7id69/Ocw93/dt57sGsX1FR4fgAcZkwycrKClfp277+7Tz3cNe/necervq8XQVgNUIOgNXCFnIFBQXhKn3b17+d5x7u+rfz3MNVP6QXHgAg1Hi7CsBqYQm5Xbt2aciQIRo0aJAKCwtDWjsxMVHp6enKzMwMyUKe+fn5io6OVlpamnesvr5e2dnZGjx4sLKzs9XQ0BDS+suXL1dsbKwyMzOVmZmpnTt3BqX2iRMnNHbsWKWkpCg1NVVr166VFLr5O9UP1fzD+RAop9pz5szRZz/7We/cy8vLA177k1paWnTPPffokUcekRSmB2CF+nLu5cuXTVJSkjl69Ki5dOmSycjIMIcOHQpZ/YSEBFNbWxuyem+99ZZ55513TGpqqnfsW9/6llm1apUxxphVq1aZb3/72yGt/9xzz5nnn38+aDWvqqqqMu+8844xxpiPPvrIDB482Bw6dChk83eqH6r5X7lyxTQ2NhpjjGlqajKjRo0y+/fvN48++qjZvHmzMcaYr371q+ZnP/tZyGrn5eWZrVu3BryekxdeeMFMnz7dPPzww8YYE5K5Xy/kZ3KlpaUaNGiQkpKS1K1bN02bNk1FRUWhbiNkxowZoz59+lwzVlRUpLy8PEnBfwiQr/qh4na7NXz4cElSjx49lJycrMrKypDN36l+qITzIVBOtUPp5MmT2rFjh+bNmydJMsaE5QFYIQ+5yspKxcfHe38P9UNwXC6Xxo8fr6ysLHk8npDV/aSamhq53W5JUkxMjGpqakLew7p165SRkaH8/Pygvl2+qqKiQgcOHNDo0aPDMv9P1pdCN/9wPgTq+tpX57506VJlZGRo4cKFunTpUlBqS9I3v/lN/fCHP1SXLh/HzKlTp8LyAKzb7sJDSUmJ/vGPf+gPf/iDXnzxRf3pT38Kaz8ulyvk/4ddsGCBjh49qvLycrndbi1evDio9c6ePavc3FytWbNGPXv2vGZbKOZ/ff1Qzr8jD4EKdO13331Xq1at0vvvv6+///3vqq+v1+rVq4NS+/XXX1d0dLSysrKCcvz2CHnIxcbG6sSJE97fW3sITrDqSx+vRjxp0qSArW7cHgMGDFB1dbWkj5eXD/XKyAMGDFBERIS6dOmi+fPnB/Vv0NzcrNzcXM2cOVOTJ0/21g/V/J3qh2r+V/nzEKhA1961a5fcbrdcLpeioqL0xBNPBG3ub7/9tn73u98pMTFR06ZN0969e/XUU0+FfO5SGEJu5MiROnLkiI4dO6ampiZt2bJFOTk5Ial97tw5NTY2en9+4403rrnqGCo5OTnauHGjpPA8BOhqwEjStm3bgvY3MMZo7ty5Sk5O1qJFi7zjoZq/U/1QzT+cD4HyVXvo0KHeuRtjtH379qDNfdWqVTp58qQqKiq0ZcsWPfTQQ/r1r38dngdgBf3Shg87duwwgwcPNklJSeb73/9+yOoePXrUZGRkmIyMDJOSkhKS2tOmTTMxMTEmMjLSxMbGmpdfftnU1dWZhx56yAwaNMiMGzfOnDp1KqT1Z82aZdLS0kx6err58pe/bKqqqoJS+89//rORZNLT082wYcPMsGHDzI4dO0I2f6f6oZr/wYMHTWZmpklPTzepqalmxYoVxpiP/zscOXKkGThwoJkyZYq5ePFiyGqPHTvWpKWlmdTUVDNz5kzvFdhg2rdvn/fqaijmfj3ueABgtdvuwgOA2wshB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcuhUnnzySX3ve98L2PESExO1Z8+egB0Pt57IcDcAfNLPf/7zcLcAy3Amh3a7fPnybVUXtzZCDjclMTFRq1evVkZGhrp3766SkhLdd9996tWrl4YNG6bi4mLvax988EF95zvf0ahRo9SzZ09NnDhR9fX13u2PPvqoYmJidNddd2nMmDE6dOiQd9ucOXO0bNkySVJxcbHi4uK0evVqxcTE6IknntCVK1dUWFiogQMHqm/fvpo6deo1x960aZMSEhLUt29f/eAHPwj+HwadHiGHm7Z582bt2LFD//nPfzRx4kQtW7ZM9fX1+tGPfqTc3FzV1tZ6X/vLX/5Sr7zyiqqrqxUZGalvfOMb3m1f+tKXdOTIEX344YcaPny4Zs6c6Vjzf//7n+rr63X8+HF5PB799Kc/1fbt2/XWW2+pqqpKvXv31te+9jVJ0nvvvacFCxZo06ZNqqqq0qlTp3Ty5Mng/UFwazDATUhISDDr1683xhhTWFhoZs2adc328ePHmw0bNhhjjPn85z9vnnnmGe+2Q4cOma5du5rLly/fcNyGhgYjyZw+fdoYY0xeXp5ZunSpMcaYffv2ma5du5oLFy54Xz906FCzZ88e7+9VVVUmMjLSNDc3mxUrVpjHHnvMu+3s2bOma9euZvfu3R2dPm5hnMnhpsXHx0uSjh8/rq1bt6pXr17efyUlJaqurr7htZKUkJCg5uZm1dXVqaWlRUuWLNHAgQPVs2dPJSYmSpLq6up81uzfv78+9alPeX8/fvy4Jk2a5K2bnJysiIgI1dTUqKqq6pq63bt3V9++fQP5J8AtiKuruGkul0vSxwE2e/Zs/eIXv3B87YkTJ7w///e//1XXrl3Vr18/vfrqqyoqKtKePXuUmJioM2fOqHfv3jLGtFrzqvj4eL3yyiu6//77b3it2+3W4cOHvb+fP39ep06datccYR/O5NBus2bN0u9//3v98Y9/VEtLiy5evKji4uJrPv/61a9+pffee0/nz5/Xs88+qylTpigiIkKNjY2KiopS3759df78eX33u99tV+0nn3xSS5cu1fHjxyVJtbW1KioqkiRNmTJFr7/+ukpKStTU1KRnn31WV65cCdzEcUsi5NBu8fHxKioq0sqVK9W/f3/Fx8fr+eefvyZQZs+erTlz5igmJkYXL17UT37yE0nS448/roSEBMXGxiolJUX33ntvu2o/9dRTysnJ0fjx49WjRw/de++9+tvf/iZJSk1N1YsvvqgZM2bI7Xard+/eiouLC9zEcUtyGaf3CYCfHnzwQc2aNUvz5s0LdysAZ3IA7EbIAbAab1cBWI0zOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABY7f8AawfuaCt/ozwAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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cpZpSU9JufR4qieZ4bY2mgQbqiMJNFeXEEEcsCXha+V0BVJgjfM5ifHg5RBG96AccP2fRxFLOEWKJO+X3HkMcDdTThI9qKoDmUX0SKUQR61+2ZMmSVkN+w4YNDBgwwP+6vLyc4uJihg0b5l82bNgwNm069Y3vZAsWLCA5ObnFvqqqqnj44Yf5zW9+E7BPbm4uhYWFVFW1/jsCcLW79xDKzs7G7XbjdDpxuVysXr061CXJOcaHF9dJ/0xchOGl8YT1YQHXW1ht9j1RqSmhmD2M5NIOqtx87brTrF6k0YujppqtrMdLQ8C6D1EEgAMn2eSyk010I7XN6rw0tqjPhxeAXWzETTzdSKWMQ/7lgThx4cRJLqPwUEEkMSccm4tdFACGDLIpZk+L37vzy33HkkAFR4gyMXhpJNqKJcF0p4IjGJooKCjg4osvDrj/iooK3O7jb1QejweA+Pjjb57x8fGnzLEHMm/ePG699VYsy/Ive+ihh5gxY0aLvxROdGzfFRUVxMW1Pjjo1CEPsHjxYrp37x7qMuQc5cSF96Sg8Z4QkO2tb2vdMZWmlI2sZCjf9I+8y81h1rEMgEhiuMC67DQrtzqs7mjLTZgJp5rygHUP5Bts4nMAYnBTRRn/Mv/AgZOeX46uT+YivMU+joWuhypGcAmWZeE1jf7lJztqPKxjGQPIJ9XKJNJEspGVjOJbOHHRSAPF7GEEl+CwnHhNy9/7sTePRLpTzhEiiSGBbgAk0I0D7MGLl549e5KVlRWwhsTExBYBHhsbCzSPwCMjI/0/n/hGEMjevXv5+OOPee655/zL1q1bx4cffsjatWtb7Xds3wkJCW1uv9OHvEgoxeDG0MRRU030lwFcTQUxX06rxBKH58s/7aE5fJrwEU0sFlabfQGqTDnr+JRBjCDJOj76TbSSGce1X7luJ87Tqrue2jbrrv3ybpVAdceeMO2TZKUwyIxgL9vbnHpyE89etvtf72U7Fha9yfXfXeShMuA2ak0Na1hCb3JJt5oD2GA4SvNIuooyDIZBnEekFX3KsQPUUEUk0SSRygFWEUU0CTQPJhPozma+wECrUzUAQ4cO5be//a3/dWJiIunp6axfv54JEyYAsH79evLy8lrdBsCLL77IRRddRJ8+ffzLPv74YwoLC+nVq/mOII/Hg8/no6CggDVrmi+Qb968mezs7DZH8dDJ5+Qty+Kyyy7jvPPOC3gVee7cuYwYMYIRI0bQSH0IKhS7c1ouUshkJwX4jJcKc4TDHCCd5n98afTiMMWUm8P4jJddFJBCJi4rrN2+HlPpH40mWxlB1eMzPgxNQPOthifeY26M8a+3sEgmgx1sarPuUlOCwXCAQpLJaJ4CsVy4SWA7G/AZL8VmD5WU+qdg2qs7nSyaaKKU43PzJ9cdQzxeGqgztew2WzjIPjLpwz520GgaqDFVFLGbdLJbbLvO1LKGJcTTje6kA82hv4ONJJFCsdnLLgroRipFFAY8dmi+/tGdNBLohpcGDrLXH/JhVjhhROCloc2QP//886moqKCoqMi/7NZbb+Wxxx6jvLycLVu28Nxzz3Hbbbe1eU5feOGFU9rcfvvt7Ny5k3Xr1rFu3TruuOMOvv3tb/Pee+/523zyySdMnDixzW1DJ79PvqioiMzMTA4dOsSECRN49tlnW/2l6z55OVNOvNc9jHByGHLKffLb2UAjDSSRQh4jA94nf3LfTeZzitmDE6d/W+1NzXxoXj9l2bes6wE4YAopoOV1qwiiaKQhYN2fmP+l8aR59mP3sG8wKzjEgS+D2aI7qQzhApyW85S6DdCEj0uZjMNqHjeWmH1sYCW9yaWvlRew7iz6E0Y4O9iIhQMHFk00YTA4cdKHPP998nXmKJ/xHpn08Y/6zQl/W2TSm74MZhUfUU8tFg6aaAIMDpwM4rxT7pMfzPm4rQQ+N/+ihmouZpJ/TnyLWcN+drFly5YWF1dPdt9999G9e3ceeOABoOV98lFRUTzwwAP+++T37t3LoEGDKCgo8I/QP/vsM771rW9x8ODBNqd1Zs+ezY4dO1rcJz9kyBBeeumlFhd6A+nUIX+i2bNnExsby7333htwvUJepGtpMPWs5uPmeXTL2X6HDnLYHKCYvQy1vtlmu5XmI6pMWdvbOnyYMWPGsHbtWqKiojqyzDa99dZbvPjii7z22mvttu20IV9TU0NTUxNut5uamhomTJjAww8/zBVXXBGwvUJeRDpSMCHfFXTaC68lJSVce23zhSev18vNN9/casCLiEhgnTbk+/Tpw/r160NdhohIl9ap764REZGvRyEvIhKAXa7xKeRFRGxMIS8iYmMKeRERG1PIi4jYmEJeRMTGFPIiIjamkBcRsTGFvIiIjSnkRURsTCEvImJjCnkRERvrtN9CKSIdz5mcjBUdiXfPvg7bphUWjqN/b0zhfppqajpsu8d3YOHsmw2WhdXQ2GG1u7J60pToxvLUYg6U0HT0aIdst7PRSF7kHLJ3eg5bHuveodt09O/NNa8vpfbiQR263WOcbjdH/2Bo+nM9W37RcbVv/nkKv37zL9T/yYf3vNYf8dfVaSQvcg5wxMSw5XeDyMo6QPnRKLAsMAZH/iC23RrHwF8V4i0+GPz2oqPZ+dAw6F2D02l4+d5vE/15Ib72u56+MBf/mf0vvqjJZldJc8gf+eEFlA9uIiGrgsqdiaSuAPffVwRXu9vNzud688O8JXxQk4vj0W6EbTxDtXcCGsmLnAOsMBfXn7eaxiYHR7cmgDGYi/LZPyGBy8esw7hjgt6Wq3cWnsuHMHT0dmYOXs43MvYT8fZqfIcPd3jdrt5ZVF6aw6jIA/y7MhN2R2MuHEbF6Dquu2gVzw15kYmj11LRP7goc/XJpuqKQTw2fCF76rrxzKrxOD5Zi6+8vMNr7ywU8iLnApeLIdH78LybRp8HPgPL4uB99fzpzjk8k7EcEx0R3HYsi+LLM7h09jJ+l/Umld5oVuzsDWfoUdHFl2fw7Yc+JtkZwe73e5Pz3AH2/Njw+wte5vHU1eSHu3g6Yxm1vRuCqv3AxAy+O/s9LowsYsnrw+n//S/OSN2diaZrRGyu+qZvYt12iEuiC3kqonl0vOfpWJ4cvIBvhHsBZ3Absix2vpTPdYM+Y6L739y8+XvULEgj9519eM9Q7Q3xFjfGf4HPhHPtDUtZM6Enb/b+E1kuF2FWeHMjA1jtvMlYFtZHGfwk4zWclmH6lP+g19attp2iOZFCXsTmapMcTOu5BrflwPpmBTviMviPAW8zJPwIEVY0TbQ/CncO6MeeySl8Z+AqNlel8dqKO4nf7CLt80q8+/afsdqbXJDqdBFmOZkUv4YLYreT5XJR7GvA4Wugd1hsu/Ufq/2pXs/zQeVg3vpkBP2/WIevru6M1d2ZKORFbM4XBcOjCgmzHPzv8LlU5ofRw+XF7WieommiKXBHy8IRG4vlclE6Kpn/veMpltdms+ijkfS//zOAIN4evjpnXBy+KEOsIxKA88Itak0FGxudbKjrR4LzKL3DqpobG6vN2t+58ykcwH988Q36372itSO2JYW8iM35ImB4eB0RVhg9XGEkmQbW1rsZFu4hzuGk0fgCzqm7emdx6P+FM6PPctLCPucvZReyZuZQ+m1ce+ZD0rJgYSx/7vXnFov/Xp3NgtGD2P7AAEaN3sx1sR9Tbxo5uSBXVk+2PZ7EtMErGBf7EW7LwU3bbiBuc9iZrrzTUciL2Nj+n15Ixvh9RFhhOLBYWufitbKLWD5/ODdO/4g7E9dS1tR0SsjXXnM+B0Y7eLz/K+yuT2Henm/SuCCFlB0FZ22aIz9hPwPCqoBYfKaJFfXw1qFh+MoOkb2ojlVNuZD9MWsaIrFqjkeZ54ZvUjzWcH/+PxkUWcT/lJ/Ph6+dj3tvE+nbKs/oXx+dke6uEbEryyLrskJ+lr2IMMuJFx+vl43k3ZXDSPvdp3xyOIca00SNaQ5IZ1wcrt5ZOAYPpGisg2svXcklUQd49+AgKpel0u2/P8NXUXnWyk8PryTJ2TylVG+8/E/5+azfnAXGEL6jhJj9zVM02+vTcNZazZ+MHdSfA5c2MWv8W9wSt5P1tVksXJdP5pOfEvfKCswXm85a/Z2FRvIiNpYZXUmyswafiWBXYyOf/P08cn79KQBe0zzGy3D6wLKompBL+c0eHhr8NgPDDxJh+fh92fnwdAo93/30rNce76whwgqj0fjY2Gjxr/nn0/83zXVsua8X3x79OQBlvhgcXnAmJDDutS941r2edGc4axvC+Z+fXU7/N1ed9do7E4W8iI2lRlQRaflY1+DlP352Nz1XFftvGwxz+IixHERYLmp/VUuvmIPcn7KSgeGH+bS2N68eGEn9UxlErd4VklsNG42LRuOj2FfLj//vvfT4/Hjt4Zk1XJnwbwAmu9fjnlzHvy4ZyPXu9RzwRfPskfNZ8+hwYj+z7ydZg6WQF7GxHTXJ/ME3lg/3DSBj4QZ8J3yBWJ03jGrTRKzDydM5r+HEEO3w8l87b2DHwWRcO6LIevezkIXkp5X9KG5M4J0Dg0j45yZ81dX+dT6fRYNpvr+/lyuKKXE7uDRmG/fsuZadZd3xFMbT780V53zAg0JexNZWbuxL/KYw0v7fp6fcEXOwws2Ghu70iq4jP9xir/co//Tk4ZjsoW9FUUjqPdHi1XmsKXCS8odTazd7Yng9awQToxfTaHwc8Br+6RlK3aQG0io2h6Tezsoy5gx9Hvksi7OSGGWND3UZnUrfzyODaresqHdQ7dKv0T+ersaVmYGpq8NXWnbquqyelHyrB9+/558sL+/H6qUD6TfvCL4tO87Y1xScDldmBuZobcDvlXGlpVIxJpv4H+2j9slMIg9UYzX6Orz2D5r+p8O2FSoayYvYmLfoQOvr9uwjeWUMzyz8DuEVFhn/bsS3eftZrK5tbdZ+sIT4dTHsfyubHp9vCfgmJs0U8iLnsKaNW+j901BX8dX4tu8i/TehuSjcleg+eRERG1PIi4jYmEJeRMTGFPIiIjamkBcRsTGFvIiIjSnkRURsTPfJ29izGcF9c2Bp2kdBtfseF32dcuQc9cb+1r8F8toe55/FSs5NGsmLiNhYyEN++vTppKSkMHjwYP+ysrIyJkyYQE5ODhMmTKA8wHdXiIhI+0L+BWVLliwhNjaWW2+9lY0bNwJw//33k5SUxKxZs3jiiScoLy/nySefbHM7+oKyU71dtCaodqVNtUG1+15PTdec68r+2T+odp/kvxRUu848XbPSfESV6frfiRPykfzYsWNJSkpqsWzhwoVMmzYNgGnTpvHmm2+GoDIRka4v5CEfSElJCenp6QCkpaVRUlIS4orOrAZTz6fmPXzm7H7V0j/fr+HmH9r7dytyrms35MvKyrj22muJiYkhKyuLl19+ucX6l19+maysLGJiYrjmmmsoKysLqu+iRYsYPXo0CQkJjBw5kqKiIqpPePLLMZZlYVkWxcXFTJo0iYyMDCzLorCwkLlz5zJixAhGjBjBUapZahax2LzJMvM2u03r331eaUpZY5bwsVnIJ+Z/+bf5jHpzfMqi0GzlM/O+f1uFZmur21pjllJotvhf15laPjSvB1xWbwI/5b6QLWSQhdNqftJNidnH5+Zf/Mu8wWrzcav7Puag2csy8zb/Mm+w3nxKo2nwrysr93H99IMk9N1Nv5F7eeUfHv+671wWQ8G2BgoKGtvdh4h0Te2G/F133UV4eDglJSXMnz+fO++8k02bmp94vmnTJn74wx/y4osvUlJSQnR0ND/60Y+C6ltZWcmDDz7IgQMH+PDDD/F6vdx3330ApKamUlxcDEBxcTEpKSk4HA6uuOIKFixY4N/+7bffzurVq1m9ejWRRHMhlzPOuoYRjOMg+zhkAj/dppEGMunDaK5kNFfiJIwCVrdok8dILmYS32AM+9nJQbMv4LYS6U45R/yvKzhMNO4Ay2KJsE59iEeT8VHMHtLo5V/mIpxe5JDNgID7PJHHVLKZNeQxkrFchQMnWzg+F/9f//cI4WEW+/+dxbw5KfznTw+zaevxN4Ebr4nlpflH292PiHRNbYZ8TU0NCxYs4NFHHyU2NpbRo0czadIkXnzxRQDmz5/PVVddxdixY4mNjeXRRx/lH//4B9XV1e32vfnmm7niiiuIjo4mPj6exMREli9fDsCkSZOYN28eAPPmzePqq68mNTWVH/3oR4wcObKVA3HitFre9n8UT8C23a10Uq0euKwwnJaLnvSlglL/+mxrAHFWIg7LQYzlJpkMKk4I7RMl0J1KSjl2/bqCI/Qih2rKWyxLoHvA/pWU4SKMSCvav6yblUqq1ZMIogL2OdFB9tKddBKtZFyWi77kcYgivKaRmqNNvPF2DbPvTyQ2xsFFoyL5zmUxzH/9+F9MF18QxYf/qm93PyLSNbUZ8tu2bcPlctG///Er6sOGDWsxkh82bJh/Xd++fQkPD2fbtm3t9j1mypQpXHDBBezfv5+dO3fyl7/8hVmzZvHBBx+Qk5PDhx9+yKxZs4I6mEKzhcXmDZaxiCZ8pNEzqH4VHCGGuIDrjDGUc4TYVtbHk0QTPqqpAKCcIySRQhSxLZYlkBywv4dKonEHVWfg/lW4ife/jrZiceDgKB627WzE5bTo3zfcv37ooHAKth6fnhmYE8a+fT6qq09+iqaI2EGbn3j1eDzExbUMt/j4eP/cucfjIT4+PuB6p9PZZt9jXnnlFT744ANuuOEGVq5c6X9T+Oij4D6FeaJsayBZZgDVVHCYA7gIa7dPtalgFwUM48KA63dRABgyyA643mE5iTNJVHCEKBODl0airVgSTHf/shqqSGxlJO+lEddX+OBx7XvNz2VtvH8VTWPTqf3O8ee0OqdEcXRWd2qPQpzbgdM6/l6eEOekpqbJvyzBbQEwdc3VRKYEfiM7JoLC066zLTmfRwTV7vbkT4Jq98PNU4NqFzdxZ1Dt5FSL818Iqt1d+ycEucVTr8NJx2pzJB8bG0tVVVWLZVVVVbjd7nbXt9f3mBUrVnDzzTfz+uuv+wN+6dKlxMbGEhsbS15e3mkdkGVZxFmJOHF+GdCtO2o8rGMZA8gn0Tp1pL3P7KCYPeRzEY4vL4oGkkgy5Rz5csTeDYAEuvmXRRJNlBUTsK+LcLx4T+MIW3JGheM72nK6xXu0HmdUOLExDqpOGqFXe5qIjXW0eA3gigkucEWka2kz5Pv374/X62X79uMP912/fr0/ePPy8li/fr1/3a5du6ivr6d///7t9gVYu3YtkyZN4vnnn2f8+OMfZBozZgwejwePx3PK9E6wmjCtzskD1Joa1rCE3uSSbmWdsr7I7KaQrQxnbIv58kASaB61V3DYP/fePFffclkgbuLbrLM90VndqNl52P+6rrgC0+gjskcS/fuG4fUZtu86fqF1/aYG8gYcn77ZvL2BiLQ4hbyITbUZ8jExMUyePJmHH36Ympoali9fzsKFC/ne974HwNSpU3nrrbdYunQpNTU1PPzww0yePBm3291u340bN3LFFVfw7LPPctVVVwVVbF1dHfX1zaPW+vp66uqab0lsamqigXoaTQPGGCpNGfvZSRIpgbdjalnDEnrSlx5W31PWF5u97GQjwxlDtBXbbl0JdMNLAwfZ6w/0MCucMCI4yN5Wp2oA4kjCSwN1J9zCaYzBZ3wYmkfZPuOjyQSeM0++dBDlK3dSuWE/vtoG9s5bRreL+uOKDicm2sG1V8byyK/KqDnaxPJVtfzvezXccv3xv6aWfFZL0sjeAbctIl1fu5PBf/jDH/zfL9OtWzf++Mc/thjJ/+lPf2Lq1KmUlpbyrW99i7/+9a9B9X366ac5fPgwM2bMYMaMGQBkZWW1OXKPijp+t8nAgQMB/HeweGlgOe9gaCKCKHrSl570C7idA+ymlhp2UcAuc3xKZ5x1LQA72UgjDaziI/jySx/SyCLXGh5we07LRZxJpIZqYk+4CJpId/azq9WLrgAOy0GGyeYge8im+ZiK2dPils7FvEE6WeTRfGfRYvMGuRtuIH5ID6Kzu9P3vyaw7Yl/4q2qI2F4Fv3uucLf9/e/TGbGTw6RNng33RKd/P6JZPIGHB+1v/qmh7T/c/ziuYjYS8i/u6ajdOXvrmkw9azmY0bxLf8Hotpz7MJrW5YMeaPN9W+9X8NLr1dT8l93BLXPiMsKg2oXLF147XoW7F8RVLv/DPLC64Fvdt4Lr/ruGukw4VYEF1qXBx3wHeWqy2L4+9y0s7pPETm7FPIiIjamkBcRsTGFvIiIjdniGa8THN/tshddv6o5A15pt02jaf8Tv9DxF1SDfbDEbzPaPwaAsABf7BbI2LTgLqiuC6qVfQxdY7Xb5pGUz4LaVkFjcNeNOvMF1XONRvIiIjamkBcRsTGFvIiIjSnkRURsTCEvImJjCnkRERtTyIuI2JhCXkTExhTyIiI2ZotPvJ6Lslztf0P0+7WBHzl4pr0/7G9BtXMQ3CdZg1XWEOzx1nTofkMle1VU+42Ax1OXtdvmNU9mUNt6YUDPoNpJ53HOj+SdeQPY8/MLcaYGfoqUiEhXdk6HvCszg9LhSVw96VPqB/fEmdz6E5zaYoWF4+zXG+eg/riye3VwlSIiX905HfKb7+/F6P+zksdT1pD52Hb2zsj5SttxZGVS+8cmRr+6nl2/im+/g4jIWWLvOXnLYsfTowjvWYPT2UTP7xXSVHN8PjY2q5LvJn4OWIyK382KuLzT3kX1jd+keFwTf+3z32ypT6eh3t6/UhHpWmyfSEPO281tGcsBmBs+Ek4I+VS3h35hdUAUbkct5nSevudwYkYNpuQCmHjev8lwVfOz7dcQuSm4i2EiImeD7UN+bLftjIg4yNbGk6ZRLIv48FoSHVF48VHijcfRGPx2nbEx7Pix4e6hi5gcu5m/Vw8m7Jlu9Hjn0449ABGRr8H2IR/rrGNZbU9+t3M8id4SAJwD+tH9b4d4IP0tnFYUThw0GQe0f1ciAEcnj+LIlKO8NuI5NjVkcNv2m3D+ZzRRewpoOoPHIiJyumx74dXVI5PKqaPoFVbK64fOo/7tFExdPQAmMoy70z4gy3X8iTmV3igcvvafoFM+7QL2X+ljZu5yKpqieKLgcg7+sxe+gm0t5vtFRDoD247k6/ulEjWtmD5hZXyxPZv+cz7FAI7oaBoTo8gNd+DCic804bQc7KhJxnW09e1ZLheO+DiyZ27jqfTFDAir4sEDVxD1ZjyJ8zRFIyKdk21D3hfp5Pzue6huCoOG43+wbHtsKL/8zivUGS/1poEwLOIckVTc34PML75odcamfnw+wx5fxwPJH7OyPo2bt15F9G2NJB1qvc+ZFGm1f+qGhB8JalvP7W3/E5GnI84RHVQ7p9Wxf0j2jgrueHv/u0N3y3fi1gfVbkDY6VzZ7zgPHhrZbpt13zgLhUhI2Ha6xjghPbyCiqYoLK+FFRHBwf9zIUPO2w3ARXPuYcrWKSysyabeeHEebcTU1wfcVvHdF3LkjqN8L+lTtjbG8cimq6j/Szq+kkOYxoazeVgiIqfFtiHf5LJIdlVTZ8IwEU1YOb1JvPIA30v/jJLGBDKf/IzCDRmsru5NE01gTh2PWxEROPIHkf7tvbyY/1eSnQ3MPXgxvhWJuF9dgfF6Q3BkIiLBs+10TZPLYkhEEXXGyQ0jPufdx3L5nwHzAVhV0wcAyweNxkGEFQbWqRddrdy+zFk4l3RnONsa4d69V+P5fjyZ2zUHLyJdg21D3jggyeElxmpiRtJyJsb9m0jLcPHbd9P7H02EmdU0pTRwvnt3i36O6Gh2PjgMZ46Hb2TsZ583ju/89Q6S13kJr/QSVrQlREckInL6bBvyDh/s90YxOLyRHk4HCY5q/nW0JwkbXYS93zwSD4vwkuyqAuDghQnE9Twfb6TF4NE7uDX9MzJc5cxYN42e79VgfdZ8cU33wYtIV2LbkHfV+Hi57Jv8OHkxDcbB1sZUHtt0JYkHfP42psmizoTRRBM//8nfqPA13xVyZcweKpsMfyodQ8bkzQHn60VEugLbhnzk0gJ23NyL/4j8AQCWz5BVU01T6V7/aDxnVhmPXz2V6x6Yw8VRpTSZIzRi+EtFPi+8PIGsBSVgdobuIEREvibbhnzT0aOwre2A9u7ZR/zudF71JDMkoojnS8ewcF0+4cVh9FpWi6+d/iIinZ1tQz5Y4eUN/HrLBCb2KuDtD0bSf9ZnoS5JRKTDnPMh7/h0A2k3R7LOmUDfhrW6sNoBvPjabwRBfyFcR38yVuRccs6HPE0+fbGYiNhWyIdI06dPJyUlhcGDB/uXzZ49m8zMTPLz88nPz+ftt98OYYUiIl1XyEP+tttu49133z1l+U9+8hPWrVvHunXruPLKK0NQmYhI1xfykB87dixJSUmhLkNExJZCHvKtmTNnDkOHDmX69OmUl5cHbDN37lxGjBhxlisTEek6OmXI33nnnezcuZN169aRnp7OPffcE7Dd7bffzurVq89ydSIiXUenDPnU1FScTicOh4OZM2eyatWqUJckItIldcqQLy4u9v/8xhtvtLjzRkREghfy++SnTJnCxx9/zJEjR+jRowc///nP+fjjj1m3bh2WZZGdnc2f//znUJcpItIlWcbY4ysW46wkRlnjQ11Gp9LRz27taJnO4J4F+2Rp7hmu5Ozo6GfBPhzEs1tBz2/9qlaaj6gyZaEu42vrlNM1IiLSMRTyIiI2ppAXEbExhbyIiI0p5EVEbEwhLyJiYwp5EREbU8iLiNiYQl5ExMZC/rUG8tXkr22/TbozqkP32dTBT8AN9lmw/5UU3CdFj5ogny3b6QX3iVeRYGgkLyJiYwp5EREbU8iLiNiYQl5ExMYU8iIiNqaQFxGxMYW8iIiNKeRFRGxMIS8iYmP6xGsns2D/iqDaxToi223jM1ZQ29rrPRpUuzuyRgfVrqN9f+ueoNp9N7Y0qHaLjsYG1W5h6fCg2u3/pieodiKhoJG8iIiNKeRFRGxMIS8iYmMKeRERG1PIi4jYmEJeRMTGFPIiIjamkBcRsTGFvIiIjVnGGBPqIjpCnJXEKGt8qMsQEZtYaT6iypSFuoyvTSN5EREbU8iLiNiYQl5ExMYU8iIiNqaQFxGxMYW8iIiNKeRFRGxMIS8iYmMKeRERG1PIi4jYWEhDft++fYwbN45BgwaRl5fHM888A0BZWRkTJkwgJyeHCRMmUF5eHsoyRUS6rJCGvMvl4umnn6agoIAVK1bw+9//noKCAp544gnGjx/P9u3bGT9+PE888UQoyxQR6bJCGvLp6ekMHz4cALfbTW5uLkVFRSxcuJBp06YBMG3aNN58880QViki0nV1mjn5wsJC1q5dy6hRoygpKSE9PR2AtLQ0SkpKQlydiEjX5Ap1AQAej4frrruO3/3ud8TFxbVYZ1kWlmUF7Dd37lzmzp0LQCP1Z7xOEZGuJuQj+cbGRq677jqmTp3K5MmTAUhNTaW4uBiA4uJiUlJSAva9/fbbWb16NatXryaMiLNWs4hIVxHSkDfGMGPGDHJzc7n77rv9yydNmsS8efMAmDdvHldffXWoShQR6dJC+mSoZcuWMWbMGIYMGYLD0fx+8/jjjzNq1ChuuOEG9u7dS1ZWFq+99hpJSUltbktPhhKRjmSXJ0Pp8X8iIgHYJeRDPicvIiJnjkJeRMTGFPIiIjamkBcRsTGFvIiIjSnkRURsTCEvImJjCnkRERtTyIuI2JhCXkTExhTyIiI2ppAXEbExhbyIiI0p5EVEbEwhLyJiYwp5EREbU8iLiNiYQl5ExMYU8iIiNqaQFxGxMYW8iIiNKeRFRGxMIS8iYmMKeRERG1PIi4jYmEJeRMTGFPIiIjamkBcRsTGFvIiIjSnkRURsTCEvImJjCnkRERtTyIuI2JhCXkTExhTyIiI2ppAXEbExhbyIiI0p5EVEbEwhLyJiYwp5EREbU8iLiNhYSEN+3759jBs3jkGDBpGXl8czzzwDwOzZs8nMzCQ/P5/8/HzefvvtUJYpItJluUK6c5eLp59+muHDh1NdXc15553HhAkTAPjJT37CvffeG8ryRES6vJCGfHp6Ounp6QC43W5yc3MpKioKZUkiIrbSaebkCwsLWbt2LaNGjQJgzpw5DB06lOnTp1NeXh6wz9y5cxkxYgQjRoygkfqzWa6ISJdgGWNMqIvweDxcfPHF/OxnP2Py5MmUlJTQvXt3LMvioYceori4mOeff77NbcRZSYyyxp+likXE7laaj6gyZaEu42sL+Ui+sbGR6667jqlTpzJ58mQAUlNTcTqdOBwOZs6cyapVq0JcpYhI1xTSkDfGMGPGDHJzc7n77rv9y4uLi/0/v/HGGwwePDgU5YmIdHkhvfC6fPlyXnzxRYYMGUJ+fj4Ajz/+OK+88grr1q3Dsiyys7P585//HMoyRUS6rE4xJ98RNCcvIh1Jc/IiItLpKeRFRGxMIS8iYmMKeRERG1PIi4jYmEJeRMTGFPIiIjamkBcRsTGFvIiIjSnkRURsTCEvImJjCnkRERtTyIuI2JhCXkTExhTyIiI2ppAXEbExhbyIiI0p5EVEbEwhLyJiYyF9kHdHCu/moDx7d4tlhw8fJjk5OUQVdRw7HIcdjgHscRx2OAY488cRXmiPMbBtHuQdyIgRI1i9enWoy/ja7HAcdjgGsMdx2OEYwD7HcabZ461KREQCUsiLiNiYrUP+9ttvD3UJHcIOx2GHYwB7HIcdjgHscxxnmq3n5EVEznW2HsmLiJzrbBvy7777LgMGDKBfv3488cQToS7nK8nOzmbIkCHk5+czYsSIUJcTtOnTp5OSksLgwYP9y8rKypgwYQI5OTlMmDCB8vLyEFbYvkDHMHv2bDIzM8nPzyc/P5+33347hBUGZ9++fYwbN45BgwaRl5fHM888A3St89HaMXTF8xESxoa8Xq/p06eP2blzp6mvrzdDhw41mzZtCnVZpy0rK8scPnw41GWctk8++cR88cUXJi8vz7/svvvuM7/85S+NMcb88pe/NPfff3+oygtKoGN45JFHzK9+9asQVnX6Dhw4YL744gtjjDFVVVUmJyfHbNq0qUudj9aOoSuej1Cw5Uh+1apV9OvXjz59+hAeHs5NN93EwoULQ13WOWPs2LEkJSW1WLZw4UKmTZsGwLRp03jzzTdDUFnwAh1DV5Sens7w4cMBcLvd5ObmUlRU1KXOR2vHIMGxZcgXFRXRs2dP/+sePXp0yf8pLMvisssu47zzzmPu3LmhLudrKSkpIT09HYC0tDRKSkpCXNFXM2fOHIYOHcr06dM79RRHIIWFhaxdu5ZRo0Z12fNx4jFA1z4fZ4stQ94uli1bxpo1a3jnnXf4/e9/z5IlS0JdUoewLAvLskJdxmm788472blzJ+vWrSM9PZ177rkn1CUFzePxcN111/G73/2OuLi4Fuu6yvk4+Ri68vk4m2wZ8pmZmezbt8//ev/+/WRmZoawoq/mWM0pKSlce+21rFq1KsQVfXWpqakUFxcDUFxcTEpKSogrOn2pqak4nU4cDgczZ87sMuejsbGR6667jqlTpzJ58mSg652P1o6hK56Ps82WIT9y5Ei2b9/O7t27aWho4NVXX2XSpEmhLuu01NTUUF1d7f/5/fffb3GnR1czadIk5s2bB8C8efO4+uqrQ1zR6TsWigBvvPFGlzgfxhhmzJhBbm4ud999t395VzofrR1DVzwfIRHqK79nyqJFi0xOTo7p06ePeeyxx0JdzmnbuXOnGTp0qBk6dKgZNGhQlzqGm266yaSlpRmXy2UyMzPNf//3f5sjR46YSy+91PTr18+MHz/elJaWhrrMNgU6hltuucUMHjzYDBkyxFx11VXmwIEDoS6zXUuXLjWAGTJkiBk2bJgZNmyYWbRoUZc6H60dQ1c8H6GgT7yKiNiYLadrRESkmUJeRMTGFPIiIjamkBcRsTGFvIiIjSnkRURsTCEvImJjCnkRERv7/4XBFF0Ll3zYAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VCDcAViLcAFiJcANgJcINgJUINwBWuij+hkJCb2efxvd/ebqbOznbLR8cdVSXH/2Jo7oIj7PfV1OU5qgOwZ1+PdFR3aZRf3NU97u6Ex3W3JYwwdG28BXO3ABYiXADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWOmiuEMhptcpR3UVzT3/nfJz3P9xVPelIpzVGWd/awHBDX57kKO6woTVjupmHLjZUV3z9TWO6uAcZ24ArES4AbAS4QbASoQbACsRbgCsRLgBsBLhBsBKhBsAKxFuAKx0Udyh0GScfbq/qnlwl+73fz5+t8Oafr36dOk+LzYnX7vCUV3xVc85qjtlnP2+X3j5REd1EncehAtnbgCsRLgBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEqEGwArEW4ArHRR3KHQ2/Wlo7pPmp19f75T6X07/nsGJaec/X65qvcJR3WDel3iqO5899MD+x3V3dRvp6O6qR/c6qgu8gfO/qYFzn+cuQGwUofhVlBQII/Ho5SUlMCypUuXyufzKS0tTWlpaVq/fn23NgkA56rDcMvPz9fGjRvPWn7XXXepvLxc5eXlmjZtWrc0BwCh6jDcMjMzFRMT0xO9AECXCfk9t5UrVyo1NVUFBQWqr69vs66oqEjp6elKT09Xs5pC3R0AnJOQwm3x4sWqrKxUeXm5vF6v7rnnnjZrFy1apLKyMpWVlam3+obcKACci5DCLTY2VhEREerVq5cWLlyoHTt2dHVfANApIYVbTc3//3bRV155pdWVVAA4H3T4Id45c+borbfe0meffab4+Hj95je/0VtvvaXy8nK5XC4NHTpUTz31VE/0CgCOuYwxpqd2Fu2KUYYrq6d2F/Cbj519ir23q+M7CiQpIbK5M+20clvCBEd18duiHNU9fflWR3VTLktzVOdU8jvO3k/9P963HNXta3Z288yDV1zjqA522m42q8HUBR3jDgUAViLcAFiJcANgJcINgJUINwBWItwAWIlwA2Alwg2AlQg3AFa6KO5QcOr/Vr/jqK7xy9OO6uY6vPugK3X1HP7r8D+PIb36OKq765PrHNUduvakozpc3LhDAcBFh3ADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWMnZF9VfJHJ8F/738f+karKjuumD33VUt/HzVEd1ldecclQncecBegZnbgCsRLgBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEqEGwArEW4ArMQdCpY58l2/o7pVGu5wi07vPADOL5y5AbAS4QbASoQbACsRbgCsRLgBsBLhBsBKhBsAKxFuAKxEuAGwEuEGwEodhltVVZUmT56sUaNGafTo0VqxYoUkqa6uTtnZ2UpOTlZ2drbq6+u7vVkAcKrDcIuMjNTy5ctVUVGhbdu2adWqVaqoqFBhYaGysrJ04MABZWVlqbCwsCf6BQBHOgw3r9ercePGSZLcbrdGjhyp6upqrV27Vnl5eZKkvLw8vfrqq93aKACci3N6z+3QoUPatWuXMjIyVFtbK6/XK0mKi4tTbW1ttzQIAKFw/JVHfr9fs2bN0hNPPKHo6OhWYy6XSy6XK+h6RUVFKioqkiQ1q6kTrQKAc47O3JqbmzVr1izNnTtXM2fOlCTFxsaqpqZGklRTUyOPxxN03UWLFqmsrExlZWXqrb5d1DYAtK/DcDPGaMGCBRo5cqTuvvvuwPKcnBwVFxdLkoqLizV9+vTu6xIAzpHLGGPaK9i6dasmTZqkMWPGqFevr7Lw0UcfVUZGhm655Rb95z//UWJiol566SXFxMS0u7NoV4wyXFld1z2Ai9p2s1kNpi7oWIfh1pUINwBdqb1w4w4FAFYi3ABYiXADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWIlwA2Alwg2AlQg3AFYi3ABYiXADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWIlwA2Alwg2AlQg3AFYi3ABYiXADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWIlwA2Alwg2AlQg3AFYi3ABYiXADYCXCDYCVCDcAVuow3KqqqjR58mSNGjVKo0eP1ooVKyRJS5culc/nU1pamtLS0rR+/fpubxYAnIrssCAyUsuXL9e4cePU2Nio8ePHKzs7W5J011136d577+32JgHgXHUYbl6vV16vV5Lkdrs1cuRIVVdXd3tjANAZ5/Se26FDh7Rr1y5lZGRIklauXKnU1FQVFBSovr4+6DpFRUVKT09Xenq6mtXU+Y4BwAGXMcY4KfT7/bruuut0//33a+bMmaqtrdWQIUPkcrn04IMPqqamRs8880y724h2xSjDldUljQPAdrNZDaYu6JijM7fm5mbNmjVLc+fO1cyZMyVJsbGxioiIUK9evbRw4ULt2LGj6zoGgE7qMNyMMVqwYIFGjhypu+++O7C8pqYm8O9XXnlFKSkp3dMhAISgwwsKb7/9tp577jmNGTNGaWlpkqRHH31Ua9asUXl5uVwul4YOHaqnnnqqu3sFAMccv+fWFXjPDUBX6vR7bgBwoSHcAFiJcANgJcINgJUINwBWItwAWIlwA2Alwg2AlQg3AFYi3ABYiXADYCXCDYCVCDcAViLcAFiJcANgJcINgJUINwBWItwAWIlwA2ClDv9ATFfqM7iX6ocebLXs2LFjuvTSS3uyjS5nwxwkO+ZhwxwkO+bRE3Poc6jt87Me/QMxwaSnp6usrCycLXSaDXOQ7JiHDXOQ7JhHuOfAy1IAViLcAFgp7OG2aNGicLfQaTbMQbJjHjbMQbJjHuGeQ9jfcwOA7hD2MzcA6A5hC7eNGzdqxIgRGjZsmAoLC8PVRqcNHTpUY8aMUVpamtLT08PdjmMFBQXyeDxKSUkJLKurq1N2draSk5OVnZ2t+vr6MHbYsWBzWLp0qXw+n9LS0pSWlqb169eHscOOVVVVafLkyRo1apRGjx6tFStWSLrwjkVb8wjr8TBhcObMGZOUlGQqKytNU1OTSU1NNXv37g1HK52WmJhojh07Fu42ztmWLVvMzp07zejRowPLfvnLX5rHHnvMGGPMY489Zn71q1+Fqz1Hgs3hoYceMsuWLQtjV+fmk08+MTt37jTGGNPQ0GCSk5PN3r17L7hj0dY8wnk8wnLmtmPHDg0bNkxJSUnq06ePcnNztXbt2nC0ctHKzMxUTExMq2Vr165VXl6eJCkvL0+vvvpqGDpzLtgcLjRer1fjxo2TJLndbo0cOVLV1dUX3LFoax7hFJZwq66uVkJCQuBxfHx82J+IULlcLt14440aP368ioqKwt1Op9TW1srr9UqS4uLiVFtbG+aOQrNy5UqlpqaqoKDgvH85902HDh3Srl27lJGRcUEfi2/OQwrf8eCCQidt3bpV7777rjZs2KBVq1appKQk3C11CZfLJZfLFe42ztnixYtVWVmp8vJyeb1e3XPPPeFuyRG/369Zs2bpiSeeUHR0dKuxC+lYfHse4TweYQk3n8+nqqqqwOMjR47I5/OFo5VO+7pvj8ejGTNmaMeOHWHuKHSxsbGqqamRJNXU1Mjj8YS5o3MXGxuriIgI9erVSwsXLrwgjkdzc7NmzZqluXPnaubMmZIuzGPR1jzCdTzCEm7XXHONDhw4oIMHD+r06dN68cUXlZOTE45WOuXEiRNqbGwM/HvTpk2trtxdaHJyclRcXCxJKi4u1vTp08Pc0bn7OhAk6ZVXXjnvj4cxRgsWLNDIkSN19913B5ZfaMeirXmE9XiE5TKGMWbdunUmOTnZJCUlmUceeSRcbXRKZWWlSU1NNampqWbUqFEX1Dxyc3NNXFyciYyMND6fz/zpT38yn332mbnhhhvMsGHDTFZWljl+/Hi422xXsDnMmzfPpKSkmDFjxpgf/ehH5pNPPgl3m+0qLS01ksyYMWPM2LFjzdixY826desuuGPR1jzCeTy4QwGAlbigAMBKhBsAKxFuAKxEuAGwEuEGwEqEGwArEW4ArES4AbDS/wL86626MxP8sgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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++mnzi1/8ImY1P9PU1GSOHDlijDHmk08+MePHjzfHjx93bP7h6js1/66uLnP+/HljjDFXrlwx99xzjzl06JB56KGHzKuvvmqMMebRRx81v/71rx2rXVxcbLZv3x71euFs2LDBLFq0yMybN88YYxyZ+xc5fiRXVVWllJQUJScna9CgQSoqKlJFRYXTbThm5syZGjZs2DVjFRUVKi4ulhT721SFqu8Uj8ejKVOmSJLi4uKUmpqqxsZGx+Yfrr5T+vI2ZeFqO+nUqVPatWuXHnnkEUmSMaZPbtHmeMg1NjYqMTEx+Njp2zS5XC7NmTNHPp9PgUDAsbqf19LSIo/HI0kaPXq0WlpaHO9h06ZNyszMVElJSUzfLn+mvr5eR48e1bRp0/pk/p+vLzk3/768TdkXa38297Vr1yozM1MrV67U5cuXY1Jbkn70ox/p5z//uQYMuBozZ86c6ZNbtPW7Ew/vvvuu/va3v2n37t164YUX9M477/RpPy6Xy/H/YZcvX67a2lrV1NTI4/Fo9erVMa134cIFFRYWauPGjRoyZMg165yY/xfrOzn/3tymLNq1//GPf2j9+vX68MMP9de//lVtbW362c9+FpPab7zxhhISEuTz+WKy/55wPOS8Xq8aGhqCj290m6ZY1ZekhIQE5efnq6qqyrHanxk1apSam5slSc3NzUpISHC8/sCBAzVgwAAtW7Yspq9Be3u7CgsLtXjxYhUUFATrOzX/cPWdmv9nIrlNWbRrV1ZWyuPxyOVyafDgwfrBD34Qs7kfPHhQf/rTn5SUlKSioiLt27dPK1ascHzuUh+E3NSpU3XixAnV1dXpypUr2rZtm/Ly8hypffHiRZ0/fz745z179lxz1tEpeXl5Kisrk9Q3t6n6LGAkaceOHTF7DYwxWrp0qVJTU7Vq1arguFPzD1ffqfn35W3KQtWeNGlScO7GGO3cuTNmc1+/fr1OnTql+vp6bdu2TbNnz9Yrr7zSN7doi/mpjRB27dplxo8fb5KTk82zzz7rWN3a2lqTmZlpMjMzzV133eVI7aKiIjN69GjjdruN1+s1W7duNa2trWb27NkmJSXF5OTkmDNnzjha/3vf+55JT083GRkZ5tvf/rZpamqKSe2//OUvRpLJyMgwkydPNpMnTza7du1ybP7h6js1/2PHjpmsrCyTkZFh0tLSzDPPPGOMufrvcOrUqWbcuHHmwQcfNJcuXXKs9qxZs0x6erpJS0szixcvDp6BjaW33347eHbVibl/EZd1AbBavzvxAKB/IeQAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QQ68tWbJETz75ZLfbJSUl6a233nKgI+m+++7T1q1bHamFWxshh1tOfX29XC6XOjo6+roVWICQA2A1Qg49dvToUU2ZMkVxcXFauHChLl26FFz3xhtvKCsrS/Hx8br33nv1/vvvh9xHV1eXSktLNW7cOA0fPlwLFixQW1ubJGnmzJmSpPj4eN1+++06dOiQJOm3v/2tUlNTNXToUN1///06efJkcH979+7VpEmTdMcdd+jxxx+XMSZW08eXDCGHHrly5Yq+853v6Pvf/77a2tr00EMP6Y9//KOkq+FXUlKizZs368yZM3r00UeVl5eny5cvX7efX/3qV9q5c6cOHDigpqYmDR06VD/84Q8lSe+8844k6dy5c7pw4YKmT5+uiooKPffccyovL9fp06f1zW9+U4sWLZIktba2qqCgQM8++6xaW1s1btw4HTx40KFXBLc8A/TAgQMHjMfjMV1dXcGx6dOnm7Vr15rHHnvMPPnkk9dsP2HCBLN//35jjDFjx441e/fuNcYYM2nSJPPWW28Ft2tqajJut9u0t7eburo6I8m0t7cH18+dO9ds3bo1+Lizs9Pcdtttpr6+3pSVlZlp06YF13V1dRmv12u2bNkS3cnjS4kjOfRIU1OTvF6vXC5XcGzs2LGSpJMnT2rDhg2Kj48PLg0NDWpqarpuPydPnlR+fn5wu9TUVA0cOFAtLS0h6548eVIrVqwIbj9s2DAZY9TY2KimpiYlJiYGt3W5XNc8Rv9GyKFHPB6PGhsbr/nM61//+pckKTExUWvXrtW5c+eCy3//+9/g28rPS0xM1O7du6/Z9tKlS9cF6Oe337x58zXbf/rpp7r33nvl8XjU0NAQ3NYYc81j9G+EHHpk+vTpcrvdev7559Xe3q7y8nJVVVVJkpYtW6bf/OY3eu+992SM0cWLF7Vr1y6dP3/+uv089thjWrt2bfDkwenTp1VRUSFJGjlypAYMGKCPPvromu3Xr1+v48ePS5I+/vhjbd++XZI0b948HT9+XOXl5ero6NDzzz+vf//73zF9HfDlQcihRwYNGqTy8nK99NJLGjZsmP7whz+ooKBAkpSdna0tW7bo8ccf19ChQ5WSkqKXXnop5H5WrFihvLw8zZkzR3Fxcfr617+u9957T5L01a9+VWvXrtWMGTMUHx+vw4cPKz8/X0888YSKioo0ZMgQpaena/fu3ZKkESNGaPv27VqzZo2GDx+uEydOaMaMGY68Hrj1uYzhXDsAe3EkB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAav8Hf7e3cfjkjT4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pages/43290879-California-101393-0003.jpeg\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1152x1152 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hqErf8/Xv5bmHuv69PPdQ1Q/qc1cBINh4uwrAaoQcAKuFJOR27Nih3r17KzExUUVFRUGtHR8fr7S0NGVkZCgrKyvg9QoKChQVFaXU1FT3WH19vbKzs5WUlKTs7GydPXs2qPUXL16smJgYZWRkKCMjQ6+//npAaldWVmro0KHq27evUlJS9Nxzz0kK3vy91Q/W/EN5mzJvtfPz89WzZ0/33CsqKvxe+4saGxv14IMP6vvf/76kEN2iLdjfWbl27ZpJSEgwx44dM5999plJT083hw4dClr9Hj16mNOnTwet3ltvvWXef/99k5KS4h776U9/apYuXWqMMWbp0qXmqaeeCmr9Z555xixfvjxgNT9XXV1t3n//fWOMMefPnzdJSUnm0KFDQZu/t/rBmv/169fNhQsXjDHGXL161QwcONAcOHDAjB8/3mzcuNEYY8wPfvAD88c//jFotfPy8szmzZv9Xs+bFStWmEmTJpnHHnvMGGOCMvcvC/qRXFlZmRITE5WQkKD77rtPubm5KikpCXYbQTNkyBB16dLlprGSkhLl5eVJCvxtqjzVDxan06n+/ftLunHftOTkZFVVVQVt/t7qB0sob1PmrXYwnTp1Stu3b9eTTz4p6ca9KUNxi7agh1xVVZXi4uLcr4N9myaHw6Hhw4crMzNTLpcraHW/qLa2Vk6nU5IUHR2t2traoPewatUqpaenq6CgIKBvlz934sQJHTx4UIMGDQrJ/L9YXwre/EN5m7Iv1/587gsWLFB6errmzJmjzz77LCC1JenHP/6xfvOb36hNmxsxU1dXF5JbtN1zJx7279+vv//97/rrX/+q1atX6+233w5pPw6HI+j/ws6aNUvHjh1TRUWFnE6n5s2bF9B6Fy9eVE5OjlauXHnLnWiCMf8v1w/m/FtymzJ/1/7Xv/6lpUuX6siRI3rvvfdUX1+vZcuWBaT2a6+9pqioKGVmZgZk/80R9JCLiYlRZWWl+/XtbtMUqPqSFBUVpTFjxqisrCxotT/XvXt3922/a2pqFBUVFfT6YWFhatOmjWbMmBHQv0FDQ4NycnI0efJk9y29gzl/b/WDNf/P+XKbMn/X3rFjh5xOpxwOh9q1a6cnnngiYHMvLS3VX/7yF8XHxys3N1e7d+/W7Nmzgz53KQQhN2DAAB09elTHjx/X1atXtWnTJo0aNSootS9duqQLFy64f3/jjTduOusYLKNGjVJxcbGk0Nym6ovPVdiyZUvA/gbGGE2fPl3JycmaO3euezxY8/dWP1jzD+VtyjzV7tOnj3vuxhht3bo1YHNfunSpTp06pRMnTmjTpk165JFH9PLLL4fmFm0BP7Xhwfbt201SUpJJSEgw//d//xe0useOHTPp6ekmPT3d9O3bNyi1c3NzTXR0tAkPDzcxMTHmz3/+szlz5ox55JFHTGJiohk2bJipq6sLav0pU6aY1NRUk5aWZkaOHGmqq6sDUnvfvn1GkklLSzP9+vUz/fr1M9u3bw/a/L3VD9b8P/jgA5ORkWHS0tJMSkqKWbJkiTHmxn+HAwYMML169TLjxo0zV65cCVrtoUOHmtTUVJOSkmImT57sPgMbSHv27HGfXQ3G3L+My7oAWO2eO/EA4N5CyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiEHwGqEHACrEXIArEbIAbAaIQfAaoQcAKsRcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGwGiGHkJk5c6Z+9atf+W1/8fHx2rVrl9/2BzsQcgiZP/3pT/rFL34RlFrLly9XamqqIiIi1LNnTy1fvjwodRF64aFuAK3XtWvXFB4emv9E/F3bGKN169YpPT1dx44d0/DhwxUXF6fc3Fy/1UDrxJEcbhIfH69ly5YpPT1d999/v65du6Z33nlH3/jGN9SpUyf169dPe/fuda//8MMP6+c//7kGDhyoDh06aPTo0aqvr3cvHz9+vKKjo9WxY0cNGTJEhw4dci/Lz8/XwoULJUl79+5VbGysli1bpujoaD3xxBO6fv26ioqK1KtXL3Xt2lUTJky4ad/r169Xjx491LVrV/3617++7byeeuop9e/fX+Hh4erdu7dGjx6t0tJSP/3V0JoRcrjFxo0btX37dp07d061tbV67LHHtHDhQtXX1+u3v/2tcnJydPr0aff669at09q1a1VTU6Pw8HD96Ec/ci/73ve+p6NHj+qTTz5R//79NXnyZK91P/74Y9XX1+vkyZNyuVz6wx/+oK1bt+qtt95SdXW1OnfurB/+8IeSpMOHD2vWrFlav369qqurVVdXp1OnTt3R/Iwx2rdvn1JSUnz8C+GuYoAv6NGjh1mzZo37dVFRkZkyZcpN6wwfPty8+OKLxhhjvv3tb5uf/exn7mWHDh0ybdu2NdeuXbtl32fPnjWSzLlz54wxxuTl5ZkFCxYYY4zZs2ePadu2rfn000/d6/fp08fs2rXL/bq6utqEh4ebhoYGs2TJEjNx4kT3sosXL5q2bduanTt3NjnHRYsWmfT0dHPlypUm18Xdj8/kcIu4uDj37ydPntTmzZu1bds291hDQ4OGDh3qcf0ePXqooaFBZ86cUbdu3bRgwQJt3rxZp0+fVps2N944nDlzRh07drylbmRkpL7yla/cVHvMmDHu7SQpLCxMtbW1qq6uvqnu/fffr65duzY5t1WrVmndunXat2+f2rVr1+T6uPsRcriFw+Fw/x4XF6epU6fqhRde8Lp+ZWWl+/f//ve/atu2rbp166YNGzaopKREu3btUnx8vP73v/+pc+fOMsY0Wffz2mvXrtU3v/nNW9Z1Op3697//7X59+fJl1dXV3XZea9euVVFRkd5++23Fxsbedl3Yg8/kcFtTpkzRtm3b9Le//U2NjY26cuWK9u7de9PnXy+99JIOHz6sy5cva9GiRRo3bpzCwsJ04cIFtWvXTl27dtXly5f19NNPN6v2zJkztWDBAp08eVKSdPr0aZWUlEiSxo0bp9dee0379+/X1atXtWjRIl2/ft3rvl5++WU9/fTT2rlzpxISEnz4S+BuRcjhtuLi4lRSUqJnn31WkZGRiouL0/Lly28KlKlTpyo/P1/R0dG6cuWKfv/730uSpk2bph49eigmJkZ9+/bVQw891Kzas2fP1qhRozR8+HBFRETooYce0rvvvitJSklJ0erVq/X444/L6XSqc+fOtz06W7hwoerq6jRgwAC1b99e7du318yZM334i+Bu4zDe3jsAd+Dhhx/WlClT9OSTT4a6FcAjjuQAWI2QA2A13q4CsBpHcgCsRsgBsBohB8BqhBwAqxFyAKxGyAGw2v8DjuQ5lTsSZaQAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 360x360 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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aJUnKycnR5s2bg9cxAATJPR1e1NTUKCMjQ3FxcRo8eLA6dOigli1bKjr60+8SJyYmOt7EAwAi6Z5CLioqSkVFRSotLdWhQ4d0/Pjxey7g9XrVs2dP9ezZM+AmASBQ9fqgqGXLlhowYIAOHDigCxcu+C7xKC0tVUJCgt998vLyVFhY6Ph+GQBCqc6QO3v2rC5cuCDp03sx7ty5UykpKRowYIDefPNNSdLq1as1fPjwkDYKAIGo8+zqv/71L+Xk5Kimpka3b9/W6NGjNW/ePJ06dUrZ2dmqqqrSY489ptdff11NmjSptVibNm3k8XgkfRqebdu2DdpE6uthrv8wzz3S9R/muYeyfnFxseNCGzIRkpmZGanSD339h3nuka7/MM89UvX58hYAqxFyAKwWsZDLy8uLVOmHvv7DPPdI13+Y5x6p+nWeeACABxlvVwFYjZADYLWIhNz27dvVuXNndezYUfn5+WGt7fF4lJaWpoyMjLBcapabm6u4uDh169bNN1ZVVaXBgwerU6dOGjx4sM6fPx/W+vPnz1dCQoIyMjKUkZGhv/3tbyGpXVJSogEDBqhr165KTU3VK6+8Iil883eqH675R3KZMqfakyZN0qOPPuqbe1FRUdBrf1ZNTY0ee+wxffvb35YUoSXawv2dlVu3bpn27dubkydPmhs3bpj09HRz9OjRsNVPTk42Z8+eDVu9d955x7z33nsmNTXVN/ajH/3ILFq0yBhjzKJFi8yPf/zjsNZ/6aWXzMsvvxyymnecOXPGvPfee8YYYy5dumQ6depkjh49Grb5O9UP1/xv375tLl++bIwx5ubNm6Z3797mwIED5tlnnzXr1683xhjzve99z/z+978PW+2cnBzzxhtvBL2ekyVLlpixY8eaZ555xhhjwjL3zwv7kdyhQ4fUsWNHtW/fXo888oiys7NVUFAQ7jbCpn///mrVqtVdYwUFBcrJyZEU+mWq/NUPF7fbrR49ekiSYmJilJKSorKysrDN36l+uERymTKn2uFUWlqqrVu36vnnn5f06dqUkViiLewhV1ZWpqSkJN/v4V6myeVyaciQIcrMzJTX6w1b3c+qqKiQ2+2WJMXHx6uioiLsPSxbtkzp6enKzc0N6dvlO4qLi3X48GH16dMnIvP/bH0pfPOP5DJln699Z+5z585Venq6Zs6cqRs3boSktiT98Ic/1K9+9SvfgrHnzp2LyBJtD92Jh3379un999/Xtm3btHz5cr377rsR7cflcoX9X9jp06fr5MmTKioqktvt1uzZs0Na78qVK8rKytLSpUvVokWLu7aFY/6frx/O+TdkmbJg1z5y5IgWLVqk48eP65///Keqqqq0ePHikNTesmWL4uLiHG+2Hk5hD7mEhASVlJT4fq9tmaZQ1ZekuLg4jRgxQocOHQpb7TvatWun8vJySVJ5ebni4uLCXj8qKkqNGjXS1KlTQ/oaVFdXKysrS+PHj9fIkSN99cM1f6f64Zr/HYEsUxbs2tu3b5fb7ZbL5VKTJk00efLkkM19//79+stf/iKPx6Ps7Gy9/fbbmjFjRtjnLkUg5Hr16qUTJ07oo48+0s2bN7VhwwYNGzYsLLWvXr2qy5cv+/68Y8eOu846hsuwYcO0evVqSZFZpupOwEjSpk2bQvYaGGM0ZcoUpaSkaNasWb7xcM3fqX645h/JZcr81e7SpYtv7sYYbd68OWRzX7RokUpLS1VcXKwNGzZo4MCB+vOf/xyZJdpCfmrDj61bt5pOnTqZ9u3bm1/84hdhq3vy5EmTnp5u0tPTTdeuXcNSOzs728THx5vo6GiTkJBgXnvtNVNZWWkGDhxoOnbsaAYNGmTOnTsX1voTJkww3bp1M2lpaeY73/mOOXPmTEhq//3vfzeSTFpamunevbvp3r272bp1a9jm71Q/XPP/4IMPTEZGhklLSzOpqalmwYIFxphP/x726tXLdOjQwYwaNcpcv349bLUHDBhgunXrZlJTU8348eN9Z2BDac+ePb6zq+GY++dxWRcAqz10Jx4APFwIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+QAWI2QA2A1Qg6A1Qg5AFYj5ABYjZADYDVCDoDVCDkAViPkAFiNkANgNUIOgNUIOQBWI+RwX5k2bZp+/vOfB+35PB6Pdu3aFbTnw4MnOtINAJ/1hz/8IdItwDIcyaHebt269VDVxYONkMM98Xg8Wrx4sdLT09WsWTPt27dP/fr1U8uWLdW9e3ft3bvX99innnpKP/3pT9W7d2+1aNFCw4cPV1VVlW/7s88+q/j4eH3lK19R//79dfToUd+2SZMm6cUXX5Qk7d27V4mJiVq8eLHi4+M1efJk3b59W/n5+erQoYNat26t0aNH3/Xca9euVXJyslq3bq1f/vKXoX9hcN8j5HDP1q9fr61bt+rUqVMaPny4XnzxRVVVVenXv/61srKydPbsWd9j16xZo1WrVqm8vFzR0dH6wQ9+4Ns2dOhQnThxQh9//LF69Oih8ePHO9b83//+p6qqKp0+fVper1e/+93vtHnzZr3zzjs6c+aMYmNj9f3vf1+SdOzYMU2fPl1r167VmTNndO7cOZWWlobuBcGDwQD3IDk52axcudIYY0x+fr6ZMGHCXduHDBli/vSnPxljjPnGN75hfvKTn/i2HT161DRu3NjcunXrC897/vx5I8lcuHDBGGNMTk6OmTt3rjHGmD179pjGjRubTz75xPf4Ll26mF27dvl+P3PmjImOjjbV1dVmwYIFZsyYMb5tV65cMY0bNzY7d+5s6PTxAONIDvcsKSlJknT69Gm98cYbatmype9n3759Ki8v/8JjJSk5OVnV1dWqrKxUTU2N5syZow4dOqhFixbyeDySpMrKSr8127Ztq6ZNm/p+P336tEaMGOGrm5KSoqioKFVUVOjMmTN31W3WrJlat24dzJcADyDOruKeuVwuSZ8G2HPPPacVK1Y4PrakpMT35//+979q3Lix2rRpo3Xr1qmgoEC7du2Sx+PRxYsXFRsbK2NMrTXvSEpK0qpVq/TEE0984bFut1v//ve/fb9fu3ZN586dq9ccYR+O5FBvEyZM0F//+le99dZbqqmp0fXr17V37967Pv96/fXXdezYMV27dk3z5s3TqFGjFBUVpcuXL6tJkyZq3bq1rl27pp/97Gf1qj1t2jTNnTtXp0+fliSdPXtWBQUFkqRRo0Zpy5Yt2rdvn27evKl58+bp9u3bwZs4HkiEHOotKSlJBQUFWrhwodq2baukpCS9/PLLdwXKc889p0mTJik+Pl7Xr1/Xb3/7W0nSxIkTlZycrISEBHXt2lWPP/54vWrPmDFDw4YN05AhQxQTE6PHH39c//jHPyRJqampWr58ucaNGye3263Y2FglJiYGb+J4ILmM0/sEIEBPPfWUJkyYoOeffz7SrQAcyQGwGyEHwGq8XQVgNY7kAFiNkANgNUIOgNUIOQBWI+QAWI2QA2C1/wP0hro/9TvB5wAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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R1vh2lYikxpAjIqn5JOROnjyJyZMnIzIyEtnZ2ZrWNplMiIuLg9VqRVJSktfrZWVlISgoCLGxsc6x5uZm2Gw2REVFwWazoaWlRdP6W7ZsgdFohNVqhdVqxYkTJ7xSu6qqCikpKYiJiYHZbMaePXsAaDd/tfpazb+trQ1Tp05FfHw8zGYzXn31VQDAtWvXMG3aNERGRuKFF15Ae3u7ZrUzMzMxceJE59xLSko8Xvururq68M1vfhPf+973AGgz9x60vmals7NTREREiPLycnH37l1hsVhEaWmpZvXDw8NFQ0ODZvXOnj0rPv74Y2E2m51jP/3pT8X27duFEEJs375dvPzyy5rWf/XVV8XOnTu9VvO+2tpa8fHHHwshhLh586aIiooSpaWlms1frb5W8793755obW0VQgjR3t4upk6dKj788EPx3HPPiby8PCGEED/4wQ/EH//4R81qZ2RkiPz8fI/XU7Nr1y6xaNEi8eyzzwohhCZzf5DmR3JFRUWIjIxEREQEhg0bhoULF6KgoEDrNjQzY8YMjB07tttYQUEBMjIyAAAZGRk4cuSIpvW1YjAYkJCQAAAIDAxEdHQ0ampqNJu/Wn2t6HQ6jBw5EgDQ0dGBjo4O6HQ6fPDBB1iwYAEA781frbaWqqurcfz4caxYsQLAl9+DqMXcH6R5yNXU1HR7PmdoaKjmL7zU1FQkJibC4XBoVver6uvrYTAYAAAhISGor6/XvIecnBxYLBZkZWV59e3yfRUVFbh8+TKmTZvmk/l/tT6g3fy7urpgtVoRFBQEm82GSZMmYfTo0dDrv/y+Wm++/h+sfX/uGzduhMViwdq1a3H37l2v1AaAH//4x/jtb3/rfE5wU1OTZnP/qiF34uHChQv45z//ib/97W/Yu3cvzp0759N+dDqd5v/Crl69GuXl5SgpKYHBYMD69eu9Wu/WrVtIT0/H7t27MWrUqG7LtJj/g/W1nL+/vz9KSkpQXV2NoqIifPrpp16r1Vftf//739i+fTs+/fRT/OMf/0BzczN27NjhldrvvPMOgoKCkJiY6JX9u0LzkDMajaiqqnL+Xl1dDaPRqGl9AAgKCsK8efNQVFSkWe37goODUVdXBwCoq6tDUFCQ5vX9/f3h5+eHlStXevVv0NHRgfT0dCxZsgTz58931tdq/mr1tZr/faNHj0ZKSgo+/PBD3LhxA52dnQC0ef3fr33y5EkYDAbodDoMHz4cL730ktfmfvHiRRw9ehQmkwkLFy7EBx98gDVr1mg+d8AHIZecnIyysjJcu3YN7e3tOHToENLS0jSpffv2bbS2tjp/fu+997qdddRKWloacnNzAQC5ubmYO3eupvXvBwwAHD582Gt/AyEEli9fjujoaKxbt845rtX81eprNf+GhgbcuHEDAPDFF1+gsLAQ0dHRSElJwdtvvw3Ae/NXqj1lyhTn3IUQOHLkiNfmvn37dlRXV6OiogKHDh3C008/jTfeeEOTuffg9VMbCo4fPy6ioqJERESE+PWvf61Z3fLycmGxWITFYhExMTGa1F64cKEICQkRer1eGI1G8frrr4vGxkbx9NNPi8jISDFz5kzR1NSkaf2lS5eK2NhYERcXJ+bMmSNqa2u9Uvv8+fMCgIiLixPx8fEiPj5eHD9+XLP5q9XXav5XrlwRVqtVxMXFCbPZLLZu3SqE+PJ1mJycLCZNmiQWLFgg2traNKudkpIiYmNjhdlsFkuWLHGegfWm06dPO8+uajH3B/G2LiKS2pA78UBEQwtDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQIyKpMeSISGoMOSKSGkOOiKTGkCMiqTHkiEhqDDkikhpDjoikxpAjIqkx5IhIagw5IpIaQ46IpMaQI59ZtWoVfvWrX3lsfyaTCadOnfLY/kgODDnymT/96U/4xS9+oUmtnTt3IjY2FoGBgZg4cSJ27typSV3yPb2vG6CBq7OzE3q9b14inq4thMCBAwdgsVhQXl6O1NRUhIWFYeHChR6rQQMTj+SoG5PJhB07dsBisWDEiBHo7OzEpUuX8MQTT2D06NGIj4/HmTNnnOs/9dRT+PnPf46pU6di1KhRmDt3Lpqbm53Ln3vuOYSEhODRRx/FjBkzUFpa6lyWmZmJTZs2AQDOnDmD0NBQ7NixAyEhIXjppZdw7949ZGdnY9KkSRg3bhyef/75bvs+ePAgwsPDMW7cOPzmN7/pdV4vv/wyEhISoNfrMXnyZMydOxcXL1700F+NBjKGHPWQl5eH48eP48aNG6ivr8ezzz6LTZs2obm5Gb/73e+Qnp6OhoYG5/oHDhzA/v37UVdXB71ejx/96EfOZbNmzUJZWRmuX7+OhIQELFmyRLXu//73PzQ3N6OyshIOhwN/+MMfcOTIEZw9exa1tbUYM2YMfvjDHwIArl69itWrV+PgwYOora1FU1MTqqurH2p+QgicP38eZrPZzb8QDSqC6CvCw8PFvn37nL9nZ2eLpUuXdlsnNTVV/OUvfxFCCPF///d/4mc/+5lzWWlpqQgICBCdnZ099t3S0iIAiBs3bgghhMjIyBAbN24UQghx+vRpERAQIL744gvn+lOmTBGnTp1y/l5bWyv0er3o6OgQW7duFS+88IJz2a1bt0RAQIAoLCzsc46bN28WFotFtLW19bkuDX78TI56CAsLc/5cWVmJ/Px8HDt2zDnW0dGBlJQUxfXDw8PR0dGBxsZGjB8/Hhs3bkR+fj4aGhrg5/flG4fGxkY8+uijPepOmDABjzzySLfa8+bNc24HAP7+/qivr0dtbW23uiNGjMC4ceP6nFtOTg4OHDiA8+fPY/jw4X2uT4MfQ4560Ol0zp/DwsKwbNky/PnPf1Zdv6qqyvnzZ599hoCAAIwfPx5vvvkmCgoKcOrUKZhMJnz++ecYM2YMhBB91r1fe//+/fj2t7/dY12DwYBPPvnE+fudO3fQ1NTU67z279+P7OxsnDt3DqGhob2uS/LgZ3LUq6VLl+LYsWN499130dXVhba2Npw5c6bb519//etfcfXqVdy5cwebN2/GggUL4O/vj9bWVgwfPhzjxo3DnTt38Morr7hUe9WqVdi4cSMqKysBAA0NDSgoKAAALFiwAO+88w4uXLiA9vZ2bN68Gffu3VPd1xtvvIFXXnkFhYWFiIiIcOMvQYMVQ456FRYWhoKCAmzbtg0TJkxAWFgYdu7c2S1Qli1bhszMTISEhKCtrQ2///3vAQAvvvgiwsPDYTQaERMTg8cff9yl2mvWrEFaWhpSU1MRGBiIxx9/HB999BEAwGw2Y+/evVi8eDEMBgPGjBnT69HZpk2b0NTUhOTkZIwcORIjR47EqlWr3PiL0GCjE2rvHYgewlNPPYWlS5dixYoVvm6FSBGP5IhIagw5IpIa364SkdR4JEdEUmPIEZHUGHJEJDWGHBFJjSFHRFL7f50PuxcTUYbyAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "ename": "error",
     "evalue": "OpenCV(4.9.0) /io/opencv/modules/imgproc/src/morph.dispatch.cpp:1022: error: (-215:Assertion failed) !src.empty() in function 'dilate'\n",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31merror\u001b[0m                                     Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[11], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mpages\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpage_range\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[38;5;241;43m8\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mconv_model\u001b[49m\u001b[43m)\u001b[49m\n",
      "Cell \u001b[0;32mIn[9], line 44\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(path, page_range, model, debug)\u001b[0m\n\u001b[1;32m     42\u001b[0m plt\u001b[38;5;241m.\u001b[39maxis(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moff\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m     43\u001b[0m cell_img \u001b[38;5;241m=\u001b[39m grayimage[h_lines[i]\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m5\u001b[39m:h_lines[i\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m1\u001b[39m]\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m5\u001b[39m, v_lines[\u001b[38;5;241m11\u001b[39m]:v_lines[\u001b[38;5;241m12\u001b[39m]]\n\u001b[0;32m---> 44\u001b[0m prepared_cell_image \u001b[38;5;241m=\u001b[39m \u001b[43mcrop_cell\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcell_img\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     45\u001b[0m tensor, noop \u001b[38;5;241m=\u001b[39m normalize_img(prepared_cell_image, \u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m     46\u001b[0m result \u001b[38;5;241m=\u001b[39m model\u001b[38;5;241m.\u001b[39mpredict(np\u001b[38;5;241m.\u001b[39mexpand_dims(tensor, \u001b[38;5;241m0\u001b[39m), verbose\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m)\n",
      "Cell \u001b[0;32mIn[4], line 5\u001b[0m, in \u001b[0;36mcrop_cell\u001b[0;34m(cell_img, debug)\u001b[0m\n\u001b[1;32m      3\u001b[0m     view(cell_img, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minput\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      4\u001b[0m ret,cell_img \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39mthreshold(cell_img,\u001b[38;5;241m155\u001b[39m,\u001b[38;5;241m255\u001b[39m,cv2\u001b[38;5;241m.\u001b[39mTHRESH_TOZERO)\n\u001b[0;32m----> 5\u001b[0m cell_img \u001b[38;5;241m=\u001b[39m \u001b[43mzap_lower_horiz_lines\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcell_img\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      7\u001b[0m contours, hierarchy \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39mfindContours(cell_img,cv2\u001b[38;5;241m.\u001b[39mRETR_TREE,cv2\u001b[38;5;241m.\u001b[39mCHAIN_APPROX_SIMPLE)\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m# Find the largest contour by area\u001b[39;00m\n",
      "Cell \u001b[0;32mIn[3], line 30\u001b[0m, in \u001b[0;36mzap_lower_horiz_lines\u001b[0;34m(img, debug)\u001b[0m\n\u001b[1;32m     28\u001b[0m         img[idx, :] \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m     29\u001b[0m         view(img, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdeleted 2\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 30\u001b[0m     img[idx\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m2\u001b[39m:idx\u001b[38;5;241m+\u001b[39m\u001b[38;5;241m2\u001b[39m, :] \u001b[38;5;241m=\u001b[39m \u001b[43mclose\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[43m[\u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     31\u001b[0m     view(img, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrepaired 2\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m     32\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m img\n",
      "Cell \u001b[0;32mIn[3], line 11\u001b[0m, in \u001b[0;36mclose\u001b[0;34m(img)\u001b[0m\n\u001b[1;32m      4\u001b[0m kerns \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m      5\u001b[0m     \u001b[38;5;66;03m#cv2.getStructuringElement(cv2.MORPH_RECT, (1, 3))\u001b[39;00m\n\u001b[1;32m      6\u001b[0m     np\u001b[38;5;241m.\u001b[39marray([[ \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m1\u001b[39m ], [ \u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m0\u001b[39m ], [\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;241m0\u001b[39m ]], dtype\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39muint8),\n\u001b[1;32m      7\u001b[0m     \u001b[38;5;66;03m#np.array([[ 0, 1, 0 ], [ 0, 1, 0 ], [0, 1, 0 ]], dtype=np.uint8),\u001b[39;00m\n\u001b[1;32m      8\u001b[0m     \u001b[38;5;66;03m#np.array([[ 1, 0, 0 ], [ 0, 1, 0 ], [0, 0, 1 ]], dtype=np.uint8),\u001b[39;00m\n\u001b[1;32m      9\u001b[0m ]\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m kerns:\n\u001b[0;32m---> 11\u001b[0m     img \u001b[38;5;241m=\u001b[39m \u001b[43mcv2\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdilate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimg\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43miterations\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     12\u001b[0m     img \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39merode(img, k, iterations\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m)\n\u001b[1;32m     13\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m img\n",
      "\u001b[0;31merror\u001b[0m: OpenCV(4.9.0) /io/opencv/modules/imgproc/src/morph.dispatch.cpp:1022: error: (-215:Assertion failed) !src.empty() in function 'dilate'\n"
     ]
    }
   ],
   "source": [
    "run('pages', page_range=(2,8), model=conv_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Results\n",
    "\n",
    "This time we see an improvement in recall. The model is seeing more Ws and this is having no impact on its precision, which remains at 1.\n",
    "To take things further we will have to look into other ways in which our training data does not match our target data. For more on this, please see [Notebook 4: Imbalanced Data](4_Imbalanced_Data.ipynb)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "Exception",
     "evalue": "File `'(pages,'` not found.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
      "File \u001b[0;32m~/.local/share/virtualenvs/census-form-image-processing-VTyG8Y6d/lib/python3.10/site-packages/IPython/core/magics/execution.py:716\u001b[0m, in \u001b[0;36mExecutionMagics.run\u001b[0;34m(self, parameter_s, runner, file_finder)\u001b[0m\n\u001b[1;32m    715\u001b[0m     fpath \u001b[38;5;241m=\u001b[39m arg_lst[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m--> 716\u001b[0m     filename \u001b[38;5;241m=\u001b[39m \u001b[43mfile_finder\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfpath\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    717\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mIndexError\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
      "File \u001b[0;32m~/.local/share/virtualenvs/census-form-image-processing-VTyG8Y6d/lib/python3.10/site-packages/IPython/utils/path.py:91\u001b[0m, in \u001b[0;36mget_py_filename\u001b[0;34m(name)\u001b[0m\n\u001b[1;32m     90\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m py_name\n\u001b[0;32m---> 91\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mIOError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFile `\u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124m` not found.\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m%\u001b[39m name)\n",
      "\u001b[0;31mOSError\u001b[0m: File `'(pages,'` not found.",
      "\nThe above exception was the direct cause of the following exception:\n",
      "\u001b[0;31mException\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mget_ipython\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_line_magic\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrun\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m(\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mpages\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m, page_range=(2,8), model=conv_model, threshold=0.04)\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/share/virtualenvs/census-form-image-processing-VTyG8Y6d/lib/python3.10/site-packages/IPython/core/interactiveshell.py:2480\u001b[0m, in \u001b[0;36mInteractiveShell.run_line_magic\u001b[0;34m(self, magic_name, line, _stack_depth)\u001b[0m\n\u001b[1;32m   2478\u001b[0m     kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlocal_ns\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mget_local_scope(stack_depth)\n\u001b[1;32m   2479\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbuiltin_trap:\n\u001b[0;32m-> 2480\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   2482\u001b[0m \u001b[38;5;66;03m# The code below prevents the output from being displayed\u001b[39;00m\n\u001b[1;32m   2483\u001b[0m \u001b[38;5;66;03m# when using magics with decorator @output_can_be_silenced\u001b[39;00m\n\u001b[1;32m   2484\u001b[0m \u001b[38;5;66;03m# when the last Python token in the expression is a ';'.\u001b[39;00m\n\u001b[1;32m   2485\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(fn, magic\u001b[38;5;241m.\u001b[39mMAGIC_OUTPUT_CAN_BE_SILENCED, \u001b[38;5;28;01mFalse\u001b[39;00m):\n",
      "File \u001b[0;32m~/.local/share/virtualenvs/census-form-image-processing-VTyG8Y6d/lib/python3.10/site-packages/IPython/core/magics/execution.py:727\u001b[0m, in \u001b[0;36mExecutionMagics.run\u001b[0;34m(self, parameter_s, runner, file_finder)\u001b[0m\n\u001b[1;32m    725\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m os\u001b[38;5;241m.\u001b[39mname \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnt\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m re\u001b[38;5;241m.\u001b[39mmatch(\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m^\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.*\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m$\u001b[39m\u001b[38;5;124m\"\u001b[39m,fpath):\n\u001b[1;32m    726\u001b[0m         warn(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mFor Windows, use double quotes to wrap a filename: \u001b[39m\u001b[38;5;132;01m%r\u001b[39;00m\u001b[38;5;124mun \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmypath\u001b[39m\u001b[38;5;130;01m\\\\\u001b[39;00m\u001b[38;5;124mmyfile.py\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 727\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(msg) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01me\u001b[39;00m\n\u001b[1;32m    728\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m:\n\u001b[1;32m    729\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m fpath \u001b[38;5;129;01min\u001b[39;00m sys\u001b[38;5;241m.\u001b[39mmeta_path:\n",
      "\u001b[0;31mException\u001b[0m: File `'(pages,'` not found."
     ]
    }
   ],
   "source": [
    "run('pages', page_range=(2,8), model=conv_model, threshold=0.04)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save(\"dense_model.keras\", overwrite=True)\n",
    "conv_model.save(\"conv_model.keras\", overwrite=True)"
   ]
  }
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