diff --git a/StoDIG/Facies_classification_StoDIG_2.ipynb b/StoDIG/Facies_classification_StoDIG_2.ipynb new file mode 100644 index 0000000..2db5887 --- /dev/null +++ b/StoDIG/Facies_classification_StoDIG_2.ipynb @@ -0,0 +1,1076 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Facies classification using Convolutional Neural Networks #\n", + "## Team StoDIG - Statoil Deep-learning Interest Group ##\n", + "### _[David Wade](https://no.linkedin.com/in/david-wade-79918023), [John Thurmond](https://www.linkedin.com/in/john-thurmond-098b774) & [Eskil Kulseth Dahl](https://www.linkedin.com/in/eskil-k-dahl-87a94679)_###" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this python notebook we propose a facies classification model, building on the simple Neural Network solution proposed by LA_Team in order to outperform the prediction model proposed in the [predicting facies from well logs challenge](https://github.com/seg/2016-ml-contest). \n", + "\n", + "Given the limited size of the training data set, Deep Learning is not likely to exceed the accuracy of results from refined Machine Learning techniques (such as Gradient Boosted Trees). However, we chose to use the opportunity to advance our understanding of Deep Learning network design, and have enjoyed participating in the contest. With a substantially larger training set and perhaps more facies ambiguity, Deep Learning could be a preferred approach to this sort of problem.\n", + "\n", + "\n", + "We use three key innovations:\n", + " - Inserting a convolutional layer as the first layer in the Neural Network\n", + " - Initializing the weights of this layer to detect gradients and extrema\n", + " - Adding Dropout regularization to prevent overfitting" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Problem Modeling\n", + "----\n", + "\n", + "The dataset we will use comes from a class excercise from The University of Kansas on [Neural Networks and Fuzzy Systems](http://www.people.ku.edu/~gbohling/EECS833/). This exercise is based on a consortium project to use machine learning techniques to create a reservoir model of the largest gas fields in North America, the Hugoton and Panoma Fields. For more info on the origin of the data, see [Bohling and Dubois (2003)](http://www.kgs.ku.edu/PRS/publication/2003/ofr2003-50.pdf) and [Dubois et al. (2007)](http://dx.doi.org/10.1016/j.cageo.2006.08.011). \n", + "\n", + "The dataset we will use is log data from nine wells that have been labeled with a facies type based on oberservation of core. We will use this log data to train a classifier to predict facies types. \n", + "\n", + "This data is from the Council Grove gas reservoir in Southwest Kansas. The Panoma Council Grove Field is predominantly a carbonate gas reservoir encompassing 2700 square miles in Southwestern Kansas. This dataset is from nine wells (with 4149 examples), consisting of a set of seven predictor variables and a rock facies (class) for each example vector and validation (test) data (830 examples from two wells) having the same seven predictor variables in the feature vector. Facies are based on examination of cores from nine wells taken vertically at half-foot intervals. Predictor variables include five from wireline log measurements and two geologic constraining variables that are derived from geologic knowledge. These are essentially continuous variables sampled at a half-foot sample rate. \n", + "\n", + "The seven predictor variables are:\n", + "* Five wire line log curves include [gamma ray](http://petrowiki.org/Gamma_ray_logs) (GR), [resistivity logging](http://petrowiki.org/Resistivity_and_spontaneous_%28SP%29_logging) (ILD_log10),\n", + "[photoelectric effect](http://www.glossary.oilfield.slb.com/en/Terms/p/photoelectric_effect.aspx) (PE), [neutron-density porosity difference and average neutron-density porosity](http://petrowiki.org/Neutron_porosity_logs) (DeltaPHI and PHIND). Note, some wells do not have PE.\n", + "* Two geologic constraining variables: nonmarine-marine indicator (NM_M) and relative position (RELPOS)\n", + "\n", + "The nine discrete facies (classes of rocks) are: \n", + "1. Nonmarine sandstone\n", + "2. Nonmarine coarse siltstone \n", + "3. Nonmarine fine siltstone \n", + "4. Marine siltstone and shale \n", + "5. Mudstone (limestone)\n", + "6. Wackestone (limestone)\n", + "7. Dolomite\n", + "8. Packstone-grainstone (limestone)\n", + "9. Phylloid-algal bafflestone (limestone)\n", + "\n", + "These facies aren't discrete, and gradually blend into one another. Some have neighboring facies that are rather close. Mislabeling within these neighboring facies can be expected to occur. The following table lists the facies, their abbreviated labels and their approximate neighbors.\n", + "\n", + "Facies |Label| Adjacent Facies\n", + ":---: | :---: |:--:\n", + "1 |SS| 2\n", + "2 |CSiS| 1,3\n", + "3 |FSiS| 2\n", + "4 |SiSh| 5\n", + "5 |MS| 4,6\n", + "6 |WS| 5,7\n", + "7 |D| 6,8\n", + "8 |PS| 6,7,9\n", + "9 |BS| 7,8" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Setup\n", + "---\n", + "\n", + "Check we have all the libraries we need, and import the modules we require. Note that we have used the Theano backend for Keras, and to achieve a reasonable training time we have used an NVidia K20 GPU." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: pandas in /home/dawad/anaconda3/lib/python3.5/site-packages\n", + "Requirement already satisfied: python-dateutil>=2 in /home/dawad/anaconda3/lib/python3.5/site-packages (from pandas)\n", + "Requirement already satisfied: pytz>=2011k in /home/dawad/anaconda3/lib/python3.5/site-packages (from pandas)\n", + "Requirement already satisfied: numpy>=1.7.0 in /home/dawad/anaconda3/lib/python3.5/site-packages (from pandas)\n", + "Requirement already satisfied: six>=1.5 in /home/dawad/anaconda3/lib/python3.5/site-packages (from python-dateutil>=2->pandas)\n", + "Requirement already satisfied: scikit-learn in /home/dawad/anaconda3/lib/python3.5/site-packages\n", + "Requirement already satisfied: keras in /home/dawad/anaconda3/lib/python3.5/site-packages\n", + "Requirement already satisfied: six in /home/dawad/anaconda3/lib/python3.5/site-packages (from keras)\n", + "Requirement already satisfied: theano in /home/dawad/anaconda3/lib/python3.5/site-packages (from keras)\n", + "Requirement already satisfied: pyyaml in /home/dawad/anaconda3/lib/python3.5/site-packages (from keras)\n", + "Requirement already satisfied: scipy>=0.11 in /home/dawad/anaconda3/lib/python3.5/site-packages (from theano->keras)\n", + "Requirement already satisfied: numpy>=1.7.1 in /home/dawad/anaconda3/lib/python3.5/site-packages (from theano->keras)\n", + "Requirement already satisfied: sklearn in /home/dawad/anaconda3/lib/python3.5/site-packages\n", + "Requirement already satisfied: scikit-learn in /home/dawad/anaconda3/lib/python3.5/site-packages (from sklearn)\n" + ] + } + ], + "source": [ + "%%sh\n", + "pip install pandas\n", + "pip install scikit-learn\n", + "pip install keras\n", + "pip install sklearn" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Using Theano backend.\n", + "Using gpu device 0: Tesla K20c (CNMeM is enabled with initial size: 80.0% of memory, cuDNN 5105)\n", + "/home/dawad/anaconda3/lib/python3.5/site-packages/theano/sandbox/cuda/__init__.py:600: UserWarning: Your cuDNN version is more recent than the one Theano officially supports. If you see any problems, try updating Theano or downgrading cuDNN to version 5.\n", + " warnings.warn(warn)\n" + ] + } + ], + "source": [ + "from __future__ import print_function\n", + "import time\n", + "import numpy as np\n", + "%matplotlib inline\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.colors as colors\n", + "from mpl_toolkits.axes_grid1 import make_axes_locatable\n", + "from keras.preprocessing import sequence\n", + "from keras.models import Model, Sequential\n", + "from keras.constraints import maxnorm, nonneg\n", + "from keras.optimizers import SGD, Adam, Adamax, Nadam\n", + "from keras.regularizers import l2, activity_l2\n", + "from keras.layers import Input, Dense, Dropout, Activation, Convolution1D, Cropping1D, Cropping2D, Permute, Flatten, MaxPooling1D, merge\n", + "from keras.wrappers.scikit_learn import KerasClassifier\n", + "from keras.utils import np_utils\n", + "from sklearn.model_selection import cross_val_score\n", + "from sklearn.model_selection import KFold , StratifiedKFold\n", + "from classification_utilities import display_cm, display_adj_cm\n", + "from sklearn.metrics import confusion_matrix, f1_score\n", + "from sklearn import preprocessing\n", + "from sklearn.model_selection import GridSearchCV" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data ingest\n", + "---\n", + "We load the training and testing data to preprocess it for further analysis, filling the missing data values in the PE field with zero and proceeding to normalize the data that will be fed into our model. We now incorporate the Imputation from Paolo Bestagini via LA_Team's Submission 5." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "filename = 'train_test_data.csv'\n", + "data = pd.read_csv(filename)\n", + "data.head(12)\n", + "\n", + "# Set 'Well Name' and 'Formation' fields as categories\n", + "data['Well Name'] = data['Well Name'].astype('category')\n", + "data['Formation'] = data['Formation'].astype('category')\n", + "\n", + "# Normalize the rest of fields (GR, ILD_log10, DelthaPHI, PHIND,NM_M,RELPOS)\n", + "correct_facies_labels = data['Facies'].values\n", + "feature_vectors = data.drop(['Formation'], axis=1)\n", + "well_labels = data[['Well Name', 'Facies']].values\n", + "data_vectors = feature_vectors.drop(['Well Name', 'Facies'], axis=1).values\n", + "\n", + "# Fill missing values and normalize for 'PE' field\n", + "imp = preprocessing.Imputer(missing_values='NaN', strategy='mean', axis=0)\n", + "imp.fit(data_vectors)\n", + "data_vectors = imp.transform(data_vectors)\n", + "\n", + "scaler = preprocessing.StandardScaler().fit(data_vectors)\n", + "scaled_features = scaler.transform(data_vectors)\n", + "data_out = np.hstack([well_labels, scaled_features])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Split data into training data and blind data, and output as Numpy arrays" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "def preprocess(data_out):\n", + " \n", + " data = data_out\n", + " well_data = {}\n", + " well_names = ['SHRIMPLIN', 'ALEXANDER D', 'SHANKLE', 'LUKE G U', 'KIMZEY A', 'CROSS H CATTLE', \n", + " 'NOLAN', 'Recruit F9', 'NEWBY', 'CHURCHMAN BIBLE', 'STUART', 'CRAWFORD']\n", + " for name in well_names:\n", + " well_data[name] = [[], []]\n", + "\n", + " for row in data:\n", + " well_data[row[0]][1].append(row[1])\n", + " well_data[row[0]][0].append(list(row[2::]))\n", + "\n", + " chunks = []\n", + " chunks_test = []\n", + " chunk_length = 1 \n", + " chunks_facies = []\n", + " wellID=0.0\n", + " for name in well_names:\n", + " \n", + " if name not in ['STUART', 'CRAWFORD']:\n", + " test_well_data = well_data[name]\n", + " log_values = np.array(test_well_data[0])\n", + " facies_values = np.array(test_well_data[1])\n", + " for i in range(log_values.shape[0]):\n", + " toAppend = np.concatenate((log_values[i:i+1, :], np.asarray(wellID).reshape(1,1)), axis=1)\n", + " chunks.append(toAppend)\n", + " chunks_facies.append(facies_values[i])\n", + " else:\n", + " test_well_data = well_data[name]\n", + " log_values = np.array(test_well_data[0])\n", + " for i in range(log_values.shape[0]):\n", + " toAppend = np.concatenate((log_values[i:i+1, :], np.asarray(wellID).reshape(1,1)), axis=1)\n", + " chunks_test.append(toAppend)\n", + " \n", + " wellID = wellID + 1.0\n", + " \n", + " chunks_facies = np.array(chunks_facies, dtype=np.int32)-1\n", + " X_ = np.array(chunks)\n", + " X = np.zeros((len(X_),len(X_[0][0]) * len(X_[0])))\n", + " for i in range(len(X_)):\n", + " X[i,:] = X_[i].flatten()\n", + " \n", + " X_test = np.array(chunks_test)\n", + " X_test_out = np.zeros((len(X_test),len(X_test[0][0]) * len(X_test[0])))\n", + " for i in range(len(X_test)):\n", + " X_test_out[i,:] = X_test[i].flatten()\n", + " y = np_utils.to_categorical(chunks_facies)\n", + " return X, y, X_test_out\n", + "\n", + "X_train_in, y_train, X_test_in = preprocess(data_out)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data Augmentation\n", + "---\n", + "\n", + "We expand the input data to be acted on by the convolutional layer." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(4149, 11, 8)\n", + "(830, 11, 8)\n" + ] + } + ], + "source": [ + "conv_domain = 11\n", + "\n", + "# Reproducibility\n", + "np.random.seed(7) \n", + "# Load data\n", + "\n", + "def expand_dims(input):\n", + " r = int((conv_domain-1)/2)\n", + " l = input.shape[0]\n", + " n_input_vars = input.shape[1]\n", + " output = np.zeros((l, conv_domain, n_input_vars))\n", + " for i in range(l):\n", + " for j in range(conv_domain):\n", + " for k in range(n_input_vars):\n", + " output[i,j,k] = input[min(i+j-r,l-1),k]\n", + " return output\n", + "\n", + "X_train = np.empty((0,conv_domain,8), dtype=float)\n", + "X_test = np.empty((0,conv_domain,8), dtype=float)\n", + "\n", + "wellId = 0.0\n", + "for i in range(10):\n", + " X_train_subset = X_train_in[X_train_in[:, 8] == wellId][:,0:8]\n", + " X_train_subset = expand_dims(X_train_subset)\n", + " X_train = np.concatenate((X_train,X_train_subset),axis=0)\n", + " wellId = wellId + 1.0\n", + " \n", + "for i in range(2):\n", + " X_test_subset = X_test_in[X_test_in[:, 8] == wellId][:,0:8]\n", + " X_test_subset = expand_dims(X_test_subset)\n", + " X_test = np.concatenate((X_test,X_test_subset),axis=0)\n", + " wellId = wellId + 1.0\n", + " \n", + "print(X_train.shape)\n", + "print(X_test.shape)\n", + "\n", + "# Obtain labels\n", + "y_labels = np.zeros((len(y_train),1))\n", + "for i in range(len(y_train)):\n", + " y_labels[i] = np.argmax(y_train[i])\n", + "y_labels = y_labels.astype(int)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Convolutional Neural Network\n", + "#### We build a CNN with the following layers (no longer using Sequential() model):\n", + "\n", + " - Dropout layer on input\n", + " - One 1D convolutional layer (7-point radius)\n", + " - One 1D cropping layer (just take actual log-value of interest)\n", + " - Series of Merge layers re-adding result of cropping layer plus Dropout & Fully-Connected layers\n", + " \n", + "#### Instead of running CNN with gradient features added, we initialize the Convolutional layer weights to achieve this\n", + "- This allows the CNN to reject them, adjust them or turn them into something else if required" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "____________________________________________________________________________________________________\n", + "Layer (type) Output Shape Param # Connected to \n", + "====================================================================================================\n", + "input_1 (InputLayer) (None, 11, 8) 0 \n", + "____________________________________________________________________________________________________\n", + "dropout_1 (Dropout) (None, 11, 8) 0 input_1[0][0] \n", + "____________________________________________________________________________________________________\n", + "convolution1d_1 (Convolution1D) (None, 1, 88) 7832 dropout_1[0][0] \n", + "____________________________________________________________________________________________________\n", + "cropping1d_1 (Cropping1D) (None, 1, 8) 0 dropout_1[0][0] \n", + "____________________________________________________________________________________________________\n", + "flatten_1 (Flatten) (None, 88) 0 convolution1d_1[0][0] \n", + "____________________________________________________________________________________________________\n", + "flatten_2 (Flatten) (None, 8) 0 cropping1d_1[0][0] \n", + "____________________________________________________________________________________________________\n", + "merge_1 (Merge) (None, 96) 0 flatten_1[0][0] \n", + " flatten_2[0][0] \n", + "____________________________________________________________________________________________________\n", + "dropout_2 (Dropout) (None, 96) 0 merge_1[0][0] \n", + "____________________________________________________________________________________________________\n", + "dense_1 (Dense) (None, 32) 3104 dropout_2[0][0] \n", + "____________________________________________________________________________________________________\n", + "merge_2 (Merge) (None, 40) 0 dense_1[0][0] \n", + " flatten_2[0][0] \n", + "____________________________________________________________________________________________________\n", + "dropout_3 (Dropout) (None, 40) 0 merge_2[0][0] \n", + "____________________________________________________________________________________________________\n", + "dense_2 (Dense) (None, 32) 1312 dropout_3[0][0] \n", + "____________________________________________________________________________________________________\n", + "dense_3 (Dense) (None, 9) 297 dense_2[0][0] \n", + "====================================================================================================\n", + "Total params: 12,545\n", + "Trainable params: 12,545\n", + "Non-trainable params: 0\n", + "____________________________________________________________________________________________________\n", + "Load time = 0\n", + "(11, 1, 8, 88)\n", + "(88,)\n" + ] + }, + { + "data": { + "image/png": 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UbwQOH/rhjBjjSElNvbiMG/rhDA1JIr3jfCQi+u8VKk0sJE0E/pO0Q/jvgNMi4nlJx1GS\nGABkyezRpI+XapXm9UD69OI80kzleOBbwL9nr5MyxQHgEOAbpNtz/ob0Edotkn4fEUsoXzwATgM+\nAvwge1ymGCwgzbg9J6mXdBvZVRFxV1ZfpliMmITOrNptwJGkd1pl9BxwFOkf6T8Dbpd04vAOaWhJ\n+jgpqT85It4f7vEMp4hYWfVwnaRVwK+BM0mvlTLpAlZFxDXZ4zVZYjsbWDJ8wxpWXwX+NSJeH+6B\nDIOzgFnATGA96Q3gzZI2ZAl+qRT2kasGt2J1M9BLuum32oFAGV+k/V4n3UtYmrhIuhWYAfxxRPRU\nVZUmFhHxQUT8MiKeioirSIsBLqNEMSDdgnEA8KSk9yW9D5wEXCbpf0jvsMsSix1ExNvAz4FDKddr\nAqAHeLam7FngoOz7UsVD0kGkRWTfqyouUwyuBxZExN0R8UxE3AHcCFyZ1ZcpFsXM0FWtWL0QWAXM\nIa0qOSwiNtdcux9ptdLzwExJr1ZVTwfuql2S3uEOqfl53wTOlXRn9ng08DlgeQfG5QrSH+2/APav\ns8K5TLGo9hHgY8BHKU8M3iDNQFW7FngJ+D7pHsuyxKLWXqRbUR6mXK8JSLMwx9T8XFOBzVVlZYrH\n10n3GfeU9O/G/wL+d83PNA7Yq4NeD6OAg4GVEfFmowuVrfpoKUmPA09ExGXZY5G2Y7glIq6vuXYW\ncEfLB2FmZmbWGc6JiDsbXdDyGbqqFat/218WESEpb8Xqr9J/TietjQBYQZqcK7tm45CflF+4w0x8\nc77coO4UVtYt/9rqpbltuqYszq3rW31eU21WkqZxAXpXn5/7fP84Zffcus7g343EcahwLBLHocKx\nSDohDpuBf4btuVK+Ij5yHeyK1W2VZuOzolFV35dZs3HIT+h2JYqf3oXa8ZN/ktui0Y2afZPrLzSq\nbVMdid6cNknn7RW5I/9uJI5DhWOROA4VjkXSUXHYtrMLRtAq1xWk4AO8BiwFJgKThm1EZmZmZkNj\nLelQmGo7zeO2KyKh28UVq9OpZNJLgbMLGJqZmZnZSDSJgZNYPcCiplq3fNuSbM+onwHT+suyRRHT\nSLs6m5mZmVkLFfWR6w3AYkk/o7Jtyd7A4uaaTyxoWO3GcejnSPRzJBLHocKxSByHCsciKVccCkno\nImJZtofYfNJHrU8Dp0TEG809g++bS6rjMLvBdfmLImYzf9C9jv1Rg8pNtZ+kZ6TcJn29c3PruroX\nNNXmSKAv+76769sNBjivQV0n8O9G4jhUOBaJ41DhWCTlikNhiyIi4jbSEU5mZmZmVqDCjv4yMzMz\ns6HhhM7MzMyszbU8oZN0paRVkt6RtFHSPZIOa3U/ZmZmZpYUMUM3FVgIHAucDOwO/FjSXgX0ZWZm\nZlZ6LV8UEREzqh9LOg/YRDrf9ZFW91cax+asLgUarXI98BM5FfmLUrn9jDNy687g9pwh5I+ha7f6\nK1mh8QpYMzMza85Q3EM3hpRxvDUEfZmZmZmVTqEJXXZCxE3AIxGxvsi+zMzMzMqqsH3oMreR9oQ9\nvuB+zMzMzEqrsIRO0q3ADGBqRPTsvMUKYFRN2UTKttOzmZmZldFaYF1N2bamWxeS0GXJ3JeAkyLi\n5eZaTQfGFzEcMzMzsxFuEgMnsXqARU21bnlCJ+k24GzgVGCLpP7lmW9HRPOpppmZmZk1pYgZutmk\nVa0/rSk/H/L2vLCd+kqDfUYa0Nj65fmbjMClWxfm1r0wekLd8lu5JLdN3wf5W5N0ddff0sTbmZiZ\nmTWviH3ofJyYmZmZ2RBy8mVmZmbW5pzQmZmZmbW5whM6SXMl9Um6oei+zMzMzMqo6JMiPgNcCKwp\nsh8zMzOzMityY+F9gB8CFwDXFNVPWYw+743cOjVYs/rG6NF1yyPyV82+e/wBuXVjD/pd/Yq78sfQ\ntVv9layQvwI2b/UrQG+jFbDd+VVmZmadqsgZuu8A90fEwwX2YWZmZlZ6RZ0UMRM4GphSxPObmZmZ\nWUURJ0V8HLgJODki3m/185uZmZnZjoqYoTsGOAB4UlL/jVrdwImSLgH2jIg6N1ytAEbVlE1k4Llm\nZmZmZp1mLbCupqz5E1OLSOgeZGAWthh4FlhQP5kDmA6ML2A4ZmZmZiPdJAamTz3AoqZaF3H01xZg\nfXWZpC3AmxHxbKv7MzMzMyu7wrYtqdHoLHhrwozRy3Pr8jcggeWaUbe80f+QeHx+bt21T+RU/Ch/\nFHlbk0D+liaN2nQ32NIE5jWoMzMz60xDktBFxOeHoh8zMzOzMvJZrmZmZmZtzgmdmZmZWZtzQmdm\nZmbW5gpJ6CR9TNISSZslbZW0RtLkIvoyMzMzK7siTooYAzwKPAScAmwGJgC/aXVfZmZmZlbMKte5\nwMsRcUFV2a8L6KdD1d9QZIbyty1pZDl525Y02Ozk2D/Prfrrg66tWz4vb79o8rcmAejrzd+exMzM\nzJpTxEeuXwRWS1omaaOkJyVdsNNWZmZmZrZLikjoDgG+ATwP/AnwXeAWSfnTPmZmZma2y4r4yLUL\nWBUR12SP10iaCMwGluQ3WwGMqimbyMBzzczMzMw6zVpgXU3ZtqZbF5HQ9QC1Z7Y+C5zeuNl0YHwB\nwzEzMzMb6SYxcBKrB1jUVOsiPnJ9FDi8puxwvDDCzMzMrBBFzNDdCDwq6UpgGXAscAHwFwX0VRoz\nyF/lGpG/YvXSrQsH3dc+D27Ords8ep/6FcofQ98H+StZu7rrr4D16lczM7PmtXyGLiJWA6cBZ5M+\nEL4KuCwi7mp1X2ZmZmZWzAwdEbEcGkwpmZmZmVnL+CxXMzMzszbnhM7MzMyszbU8oZPUJek6Sb+U\ntFXSi5KubnU/ZmZmZpYUdZbr14FzgfXAFGCxpN9GxK0F9GdmZmZWakUkdMcB90bEiuzxy5JmAZ8t\noK/SOODud3PrgvwtQ97ddMCg+/r+RTNz6y5V/W1QDovnc9t07VZ/axLI39IkbzsTgN5GW5p051eZ\nmZl1qiLuoXsMmCZpAoCko4Dj8apXMzMzs0IUMUO3ANgXeE5SLylpvMr70JmZmZkVo4iE7ixgFjCT\ndA/d0cDNkjZExJL8ZiuAUTVlExl4rpmZmZlZp1kLrKsp29Z06yISuuuBb0fE3dnjZyQdDFwJNEjo\npgPjCxiOmZmZ2Ug3iYGTWD3AoqZaF3EP3d5Ab01ZX0F9mZmZmZVeETN09wNXS3oVeAaYDMwB/r6A\nvszMzMxKr4iE7hLgOuA7wFhgA/DdrMx2ke5uVBv5Va/kbWmS3+bcsfmdnb+p/tqWqy++KrdN3tYk\nkL+lSaM23Q22NIF5DerMzMw6U8sTuojYAvxl9mVmZmZmBfN9bWZmZmZtzgmdmZmZWZsbdEInaaqk\n+yS9JqlP0ql1rpkvaYOkrZIekHRoa4ZrZmZmZrV2ZYZuNPA0cBF17qyXdAVpYcSFpPNbtwArJe3x\nIcZpZmZmZjkGvSgiIlaQjnVAUr0llJcB10XEv2TXnAtsBP4UWLbrQy23jQ1WuTZY40oK/eBabTqz\nwTMq5/kuym+Tt5IVoK83fzWrmZmZNael99BJ+iQwDniovywi3gGeAI5r/pnWtnJYbaz2CJDyWrd0\n/XAPYYTw70biOFQ4FonjUOFYJOWKQ6sXRYwjTf3UTuNszOqa5EQmcRz6PXOXE7rEr4nEcahwLBLH\nocKxSMoVB69yNTMzM2tzrd5Y+HVAwIHsOEt3IPBU46YrgFHZ968BS4GJDDyo1szMzKzTrGXgrOK2\nplu3NKGLiJckvQ5MA/4bQNK+wLGko8AamA6Mz75fCpzdyqGZmZmZjWCTGDiJ1QMsaqr1oBM6SaOB\nQ0kzcQCHSDoKeCsiXgFuAq6W9CLwK9IZrq8C9+Y8ZTYtt7mqaBvphyij6tWilTj8d5MtBsprmd+q\nUV9E/dqeJ1/PbdLVYIB9DdpV+/1vf7+9j8b3CXT666bMvxvVHIcKxyJxHCoci6QT4rA9NxrV6CoA\nRTROBwY0kE4CfsLAjOAHEfHV7JpvkfahGwP8B3BxRLyY83yzgDsGNQgzMzOz8jgnIu5sdMGgE7pW\nk7QfcAppNq/5D4vNzMzMOtso4GBgZUS82ejCYU/ozMzMzOzD8bYlZmZmZm3OCZ2ZmZlZm3NCZ2Zm\nZtbmnNCZmZmZtbkRldBJuljSS5Lek/S4pM8M95iKJmmqpPskvSapT9Kpda6ZL2mDpK2SHpB06HCM\ntUiSrpS0StI7kjZKukfSYXWu6+hYSJotaY2kt7OvxyRNr7mmo2NQj6S52e/HDTXlHR8LSfOyn736\na33NNR0fh36SPiZpiaTN2c+7RtLkmms6Oh7Z38na10SfpIVV13R0DAAkdUm6TtIvs5/zRUlX17mu\n42MBIyihk3QW8HfAPOCPgDXASkn7D+vAijcaeBq4iDq7/Uq6AriEtK/fZ4EtpLjsMZSDHAJTgYWk\nU0VOBnYHfixpr/4LShKLV4ArgMnAMcDDwL2SjoDSxGAH2Ru7C0n/JlSXlykW60hHKI7Lvk7oryhT\nHCSNAR4Ffk/a7uoI4JvAb6quKUM8plB5LYwDvkD6+7EMShMDgLnA10l/P/8AuBy4XNIl/ReUKBYQ\nESPiC3gcuLnqsUgnTFw+3GMbwhj0AafWlG0A5lQ93hd4DzhzuMdbcCz2z+JxgmPBm8D5ZYwBsA/w\nPPB50obmN5Tt9UB6k/tkg/pSxCH72RYA/7aTa0oTj6qf8Sbg52WLAXA/8L2asn8Cbi9bLCJiZMzQ\nSdqdNBvxUH9ZpMg/CBw3XOMabpI+SXr3VR2Xd4An6Py4jCG943wLyhmL7OOEmcDewGNljAHpDOj7\nI+Lh6sISxmJCdlvGLyT9UNInoJRx+CKwWtKy7NaMJyVd0F9Zwnj0//08B/iH7HGZYvAYME3SBACl\nY0iPB5Znj8sUi8Gf5VqQ/YFuYGNN+Ubg8KEfzogxjpTU1IvLuKEfztCQJNI7zkciov9eodLEQtJE\n4D9JO4T/DjgtIp6XdBwliQFAlsweTfp4qVZpXg+kTy/OI81Ujge+Bfx79jopUxwADgG+Qbo9529I\nH6HdIun3EbGE8sUD4DTgI8APssdlisEC0ozbc5J6SbeRXRURd2X1ZYpFcQmdpIuBvyIFbQ1waUT8\nV1H9WUe5DTiS9E6rjJ4DjiL9I/1nwO2SThzeIQ0tSR8nJfUnR8T7wz2e4RQRK6serpO0Cvg1cCbp\ntVImXcCqiLgme7wmS2xnA0uGb1jD6qvAv0bE68M9kGFwFjALmAmsJ70BvFnShizBL5VCPnLdhQUO\nm4Fe0k2/1Q4Eyvgi7fc66V7C0sRF0q3ADOCPI6Knqqo0sYiIDyLilxHxVERcRfr9uYwSxYB0C8YB\nwJOS3pf0PnAScJmk/yG9wy5LLHYQEW8DPwcOpVyvCYAe4NmasmeBg7LvSxUPSQeRFpF9r6q4TDG4\nHlgQEXdHxDMRcQdwI3BlVl+mWBQ2QzcH+D8RcTukrRiA/5f0TuL66gsl7UdarfQ8MFPSq1XV04G7\napekd7hDan7eN4FzJd2ZPR4NfA5Y3oFxuYL0R/svgP3rvAEoUyyqfQT4GPBRyhODN0gzUNWuBV4C\nvk+6x7Issai1F+lWlIcp12sC0izMMTU/11Rgc1VZmeLxddJ9xj0l/bvxv4D/XfMzjQP26qDXwyjg\nYGBlRLzZ6EJlqz5aJrtBcyvw5Yi4r6p8MfCRiDit5vpZwB0tHYSZmZlZ5zgnIu5sdEERM3SDXeDw\nq/Sf07OmACtIk3Nl5zhUfNhY5L9xuXCHTyua8+UGdaewsm7511YvzW3TNWVxbl3f6vO2f//AnIf4\nwo3Tdtqmd/X5uXX/OGX33Lr24d+NCscicRwqHIukE+KwGfhn2J4r5RsJq1y3pf/sT1rABWmGcXzO\n5WXiOFR82FjkJ3S78qyf3oXa8ZN/ktui0c2sfZMri7H2HLMn47PHjdr0Tm60gKsT9tP070aFY5E4\nDhWORdJRcdi2swuKSOh2cYHDClLwAV4DlgITgUktH6CZmZnZyLKWdChMtZ3mcdu1PKGLiPcl/QyY\nBtwH2/cVmwbckt9yOpVMeilwdquHZmZmZjZCTWLgJFYPsKip1kV95HoDsDhL7FaRVr3uDSwuqD8z\nMzOz0iqyxoDVAAAgAElEQVQkoYuIZdmWE/NJH7U+DZwSEW809wwTixhWG3IcKpqNxeyc8vx76GYz\nf9CjGfujBpWbau82yEi5Tfp65+bWdXUv2P79pKg8btSmu+vbDQY4r0Fdu/DvRoVjkTgOFY5FUq44\nFLYoIiJuI+34vwt831ziOFQ4FgAT83PCkvHrocKxSByHCsciKVccCjkpwszMzMyGjhM6MzMzszbn\nhM7MzMyszbU8oZN0paRVkt6RtFHSPZIOa3U/ZmZmZpYUMUM3FVgIHAucDOwO/FjSXgX0ZWZmZlZ6\nRWwsPKP6saTzgE3AMcAjre7PbAfH5mwZ0mDbkgM/kVPRYEXp7WeckVt3BrfnDCF/DF27Lcita7Q9\niZmZGQzNPXRjSH9N3xqCvszMzMxKp9CELjvy6ybgkYhYX2RfZmZmZmVV2MbCmduAI4Hjd37pCmBU\nTdlEyrYxoJmZmZXRWmBdTdm2plsXltBJuhWYAUyNiJ6dt5gOjC9qOGZmZmYj2CQGTmL1AIuaal1I\nQpclc18CToqIl4vow8zMzMySlid0km4DzgZOBbZI6l92+HZEND93aGZmZmZNKWKGbjZpVetPa8rP\nh7z9HMxa5CuDP71eY+uX528yApduXZhb98LoCXXLb+WS3DZ9H+RvTdLVXX9LE29nYmZm/YrYh87H\niZmZmZkNISdfZmZmZm3OCZ2ZmZlZmys8oZM0V1KfpBuK7svMzMysjIo+KeIzwIXAmiL7MTMzMyuz\nIjcW3gf4IXABcE1R/ZhVG33eG3XL1WDN6hujR9ctj8hfMfvu8Qfk1o096Hf1K+7KH0PXbvVXskL+\nCti81a8AvY1WwHbnV5mZWXsqcobuO8D9EfFwgX2YmZmZlV5RJ0XMBI4GphTx/GZmZmZWUcRJER8H\nbgJOjoj3W/38ZmZmZrajImbojgEOAJ6U1H8TUjdwoqRLgD0jos7NRCuAUTVlExl4UK2ZmZlZp1kL\nrKspa/7E1CISugcZmIUtBp4FFtRP5gCmA+MLGI6ZmZnZSDeJgelTD7CoqdZFHP21BVhfXSZpC/Bm\nRDzb6v7MzMzMyq6wbUtqNDrn3KxlZoxeXrc8fwMSWK4ZdcsbvWjj8fm5ddc+kVPxo/xR5G1NAvlb\nmjRq091gSxOY16DOzMza0ZAkdBHx+aHox8zMzKyMfJarmZmZWZtzQmdmZmbW5gpJ6CR9TNISSZsl\nbZW0RtLkIvoyMzMzK7siNhYeAzwKPAScAmwGJgC/aXVfZmZmZlbMooi5wMsRcUFV2a8L6MfMzMzM\nKCah+yKwQtIy4CTgNeC2iPj7AvqyUsrfUGSG6m9b0shy8rYtabDZybF/nlv11wddW7d8Xt6e2uRv\nTQLQ15u/PYmZmRkUcw/dIcA3gOeBPwG+C9wiKf8voJmZmZntsiJm6LqAVRFxTfZ4jaSJwGxgSQH9\nmZmZmZVaEQldD+nc1mrPAqc3brYCGFVTNpGB55qZmZmZdZq1wLqasm1Nty4ioXsUOLym7HB2ujBi\nOjC+gOGYmZmZjXSTGDiJ1QMsaqp1EffQ3Qh8TtKVkj4laRZwAXBrAX2ZmZmZlV7LZ+giYrWk04AF\nwDXAS8BlEXFXq/syqzWD+qtcI/JXrF66deGg+9nnwc25dZtH71O/Qvlj6PsgfyVrV3f9FbBe/Wpm\nZv2K+MiViFgOOX9ZzczMzKylfJarmZmZWZtzQmdmZmbW5pzQmZmZmbW5lid0krokXSfpl5K2SnpR\n0tWt7sfMzMzMkiIWRcwFvg6cC6wHpgCLJf02Irx1iZmZmVmLFZHQHQfcGxErsscvZ3vRfbaAvsx2\ncMDd79YtD/K3DHl30wGD7uf7F83MrbtU9bdBOSyez23TtVv9rUkgf0uTvO1MAHobbWnSnV9lZmbt\nqYh76B4DpkmaACDpKOB4vI2JmZmZWSGKmKFbAOwLPCepl5Q0XuWNhc3MzMyKUURCdxYwC5hJuofu\naOBmSRsiYkl+sxXAqJqyiQw818zMzMys06wF1tWUbWu6dREJ3fXAtyPi7uzxM5IOBq4EGiR004Hx\nBQzHzMzMbKSbxMBJrB5gUVOti7iHbm+gt6asr6C+zMzMzEqviBm6+4GrJb0KPANMBuYAf19AX2Y7\n0N15NZHf6JW8FbD5bc4dm9sR52+qf7vo1RdfldsmbyUr5K+AbdSmu8EKWJjXoM7MzNpREQndJcB1\nwHeAscAG4LtZmZmZmZm1WMsTuojYAvxl9mVmZmZmBfN9bWZmZmZtzgmdmZmZWZsbdEInaaqk+yS9\nJqlP0ql1rpkvaYOkrZIekHRoa4ZrZmZmZrV2ZYZuNPA0cBF1lgFKuoK0MOJC0vmtW4CVkvb4EOM0\nMzMzsxyDXhQREStIxzogqd5+D5cB10XEv2TXnAtsBP4UWLbrQzXbuY05u4k02LSE9PIcXKtNZzZ4\nRuU830X5bfK2JgHo683fnsTMzAxafA+dpE8C44CH+ssi4h3gCeC45p9pbSuH1cYchwrHAmDd0vXD\nPYQRwq+HCscicRwqHIukXHFo9aKIcaRpjdopio1ZXZNqzzIrK8ehwrEAeOYuJ3SJXw8VjkXiOFQ4\nFkm54lDExsK7aAUwKvv+NWApMJGB55qZmZmZdZq1DExCtzXdutUJ3euAgAPZcZbuQOCpxk2nA+Oz\n75cCZ7d4aGZmZmYj1SQGTmL1AIuaat3Sj1wj4iVSUjetv0zSvsCxwGOt7MvMzMzMkkHP0EkaDRxK\nmokDOETSUcBbEfEKcBNwtaQXgV+RznB9Fbg35ylHAUyY0Mfee/cB8NJLwSc/2TfYoXUcx6Gi2Vis\n56i65Y1WuR5F3n1p+a3y+gE4SvWfL56styg8qzsq//l2aPfbxs/TzPMdRfu/pvy7UeFYJI5DhWOR\ndEIctm7t44UXgMo9abkU0XhDhwENpJOAnzDwr90PIuKr2TXfIu1DNwb4D+DiiHgx5/lmAXcMahBm\nZmZm5XFORNzZ6IJBJ3StJmk/4BTSbF7zd/+ZmZmZdbZRwMHAyoh4s9GFw57QmZmZmdmH0+p96MzM\nzMxsiDmhMzMzM2tzTujMzMzM2pwTOjMzM7M2N6ISOkkXS3pJ0nuSHpf0meEeU9EkTZV0n6TXJPVJ\nOrXONfMlbZC0VdIDkg4djrEWSdKVklZJekfSRkn3SDqsznUdHQtJsyWtkfR29vWYpOk113R0DOqR\nNDf7/bihprzjYyFpXvazV3+tr7mm4+PQT9LHJC2RtDn7eddImlxzTUfHI/s7Wfua6JO0sOqajo4B\ngKQuSddJ+mX2c74o6eo613V8LGAEJXSSzgL+DpgH/BGwBlgpaf9hHVjxRgNPAxdRZydbSVcAl5D2\n9fsssIUUlz2GcpBDYCqwkHSqyMnA7sCPJe3Vf0FJYvEKcAUwGTgGeBi4V9IRUJoY7CB7Y3ch6d+E\n6vIyxWId6QjFcdnXCf0VZYqDpDHAo8DvSdtdHQF8E/hN1TVliMcUKq+FccAXSH8/lkFpYgAwF/g6\n6e/nHwCXA5dLuqT/ghLFAiJiRHwBjwM3Vz0W6YSJy4d7bEMYgz7g1JqyDcCcqsf7Au8BZw73eAuO\nxf5ZPE5wLHgTOL+MMQD2AZ4HPk/a0PyGsr0eSG9yn2xQX4o4ZD/bAuDfdnJNaeJR9TPeBPy8bDEA\n7ge+V1P2T8DtZYtFRIyMGTpJu5NmIx7qL4sU+QeB44ZrXMNN0idJ776q4/IO8ASdH5cxpHecb0E5\nY5F9nDAT2Bt4rIwxAL4D3B8RD1cXljAWE7LbMn4h6YeSPgGljMMXgdWSlmW3Zjwp6YL+yhLGo//v\n5znAP2SPyxSDx4BpkiYAKB1DejywPHtcplgM/izXguwPdAMba8o3AocP/XBGjHGkpKZeXMYN/XCG\nhiSR3nE+EhH99wqVJhaSJgL/Sdoh/HfAaRHxvKTjKEkMALJk9mjSx0u1SvN6IH16cR5ppnI88C3g\n37PXSZniAHAI8A3S7Tl/Q/oI7RZJv4+IJZQvHgCnAR8BfpA9LlMMFpBm3J6T1Eu6jeyqiLgrqy9T\nLIpL6CRdDPwVKWhrgEsj4r+K6s86ym3AkaR3WmX0HHAU6R/pPwNul3Ti8A5paEn6OCmpPzki3h/u\n8QyniFhZ9XCdpFXAr4EzSa+VMukCVkXENdnjNVliOxtYMnzDGlZfBf41Il4f7oEMg7OAWcBMYD3p\nDeDNkjZkCX6pFJLQVS1wuBBYBcwh3YR4WERsrrl2P9JN8L3AcZKq//E+AnivdgVThzuk6ufdj3Qv\n4R9LeqHqmk8Bz3doXK4ATgS+BoyXND4rL2MsAP4vMA24jvQOvCwxOAk4AHgqTdgCaRb/REmXAqdT\nnljU8yppYcQblCsObwKban6ud4FPZWVl+3diHOnv5zdL+nfjRuD7wC+APYFngbuAayU9Q2fEYnjP\ncpX0OPBERFyWPRZp9d4tEXF9zbWzgDtaPggzMzOzznBORNzZ6IKWz9BVLXD42/6yiAhJeQscfpX+\nczrpVjqAFcD0OpeWjeNQ4VgkRcYh/83dhXxv0M/25QZ1p7Ayt+5rq5fWLe+asnj79ytJe1b061t9\n3k7b1OpdfX5u3T9O2T23buTx70biOFQ4FkknxGEz8M+wPVfKV8RHroNd4LCt0qz/07VRVd+XmeNQ\n4VgkRcYhP6HblR4/vYu14yf/pG559ZL82ij0Ta5/f3OjZfy9OW2Sdtqiyr8bieNQ4VgkHRWHbTu7\nYERsW2JmZmZmu66IGbrNpAUOB9aUHwg0WIWzgpRNA7wGLAUmApNaPkAzMzOzkWUt6VCYajudmNuu\n5QldRLwv6WeklXn3wfZFEdOAW/JbTqcyNboUOLvVQzMzMzMboSYxcBKrB1jUVOui9qG7AVicJXb9\n25bsDSxurvnEgobVbhyHCscicRzAUdiRo5E4DhWORVKuOBSS0EXEMkn7A/NJH7U+DZwSEW809wz+\nmDVxHCoci6QVcZidU56/KGI28wfdy9gfNajcVHtHRpXKvnM76Oudu/37I0kH/fbr6l6w0za1uru+\n3WCA8xrUjTT+3UgchwrHIilXHAo7KSIibiPt+G9mZmZmBfIqVzMzM7M254TOzMzMrM05oTMzMzNr\ncy1P6CRdKWmVpHckbZR0j6TDWt2PmZmZmSVFzNBNBRYCxwInA7sDP5a0VwF9mZmZmZVeERsLz6h+\nLOk8YBNwDPBIq/szs0E6Nm/LkPxtSw78RIPnq7/LCLefcUZukzO4Pf/5ov44unarvzUJNN6exMys\nDIbiHroxpL8Ubw1BX2ZmZmalU2hClx35dRPwSESsL7IvMzMzs7IqbGPhzG2kTd2P3/mlK4BRNWUT\nKdtOz2ZmZlZGa4F1NWXbmm5dWEIn6VZgBjA1Inp23mI6ML6o4ZiZmZmNYJMYOInVAyxqqnUhCV2W\nzH0JOCkiXi6iDzMzMzNLWp7QSboNOBs4FdgiqX9J3dsR0fzcoZkV4ys5y1Ib0Nj8ury1sZduXZjb\n5oXRE3LrbuWSuuV9H+SvZO3qrr8C1qtfzawsilgUMRvYF/gpsKHq68wC+jIzMzMrvSL2ofNxYmZm\nZmZDyMmXmZmZWZtzQmdmZmbW5gpP6CTNldQn6Yai+zIzMzMro6JPivgMcCGwpsh+zMzMzMqsyI2F\n9wF+CFwAXFNUP2Y2OKPPe6NuuXI3IIE3Ro/OrYuovw3Ku8cfkNtm7EG/y63jrvrj6Nqt/tYkkL+l\nSd52JgC9jbY06c6vMjMbiYqcofsOcH9EPFxgH2ZmZmalV9RJETOBo4EpRTy/mZmZmVUUcVLEx4Gb\ngJMj4v3mW64ARtWUTWTguWZmZmZmnWYtsK6mrPkDtoqYoTsGOAB4UlL/zTXdwImSLgH2jIg6N8lM\nB8YXMBwzMzOzkW4SAyexeoBFTbUuIqF7kIEjWgw8Cyyon8yZmZmZ2a4q4uivLcD66jJJW4A3I+LZ\nVvdnZmZmVnaFbVtSw7NyZiPEjNHL65bX33wkWa4ZuXV5v9zx+PzcNtc+0aCzH9UfSd7WJJC/pUmj\nNt0NtjSBeQ3qzMxGniFJ6CLi80PRj5mZmVkZ+SxXMzMzszbnhM7MzMyszRWS0En6mKQlkjZL2ipp\njaTJRfRlZmZmVnZFbCw8BngUeAg4BdgMTAB+0+q+zMzMzKyYRRFzgZcj4oKqsl8X0I+Z5cpfWD5D\n9Ve5NrKcRqtcc9bHHvvnuW3++qBrc+vm5WxVmbeSFaCvN381q5lZGRTxkesXgdWSlknaKOlJSRfs\ntJWZmZmZ7ZIiErpDgG8AzwN/AnwXuEVS/tt1MzMzM9tlRXzk2gWsiohrssdrJE0EZgNLCujPzMzM\nrNSKSOh6SOe2VnsWOL1xsxXAqJqyiQw8FtbMzMys06wF1tWUbWu6dREJ3aPA4TVlh7PThRHTgfEF\nDMfMzMxspJvEwEmsHmBRU62LuIfuRuBzkq6U9ClJs4ALgFsL6MvMzMys9Fo+QxcRqyWdBiwArgFe\nAi6LiLta3ZeZDd4M6m9bEpGz/Qhw6daFg+5nnwc359ZtHr1PfkPVH0ffB/lbk3R119/SxNuZmFlZ\nFPGRKxGxHHL+apiZmZlZS/ksVzMzM7M254TOzMzMrM21PKGT1CXpOkm/lLRV0ouSrm51P2ZmZmaW\nFHWW69eBc4H1wBRgsaTfRoRXupqZmZm1WBEJ3XHAvRGxInv8crZ1yWcL6MvMzMys9IpI6B4D/kLS\nhIh4QdJRwPHAnAL6MrNBOuDud+uWB/nblry76YBB9/P9i2bm1l2q/G1QDovn65Z37VZ/axLI39Ik\nbzsTgN5GW5p051eZmY1ERSR0C4B9geck9ZLu07vK+9CZmZmZFaOIhO4sYBYwk3QP3dHAzZI2RMSS\nAvozMzMzK7UiErrrgW9HxN3Z42ckHQxcCTRI6FYAo2rKJjLwXDMzMzOzTrMWWFdTtq3p1kUkdHsD\nvTVlfex0i5TpwPgChmNmZmY20k1i4CRWD7CoqdZFJHT3A1dLehV4BphMWhDx9wX0ZWZmZlZ6RSR0\nlwDXAd8BxgIbgO9mZWY2zHR3Xk3kN3olfwVsXrtzx+Z2xPmb8tdIXX3xVXXL81ayQv4K2EZtuhus\ngIV5DerMzEaelid0EbEF+Mvsy8zMzMwK5rNczczMzNqcEzozMzOzNueEzszMzKzNDTqhkzRV0n2S\nXpPUJ+nUOtfMl7RB0lZJD0g6tDXDNTMzM7NauzJDNxp4GriIOsvbJF1BWul6IfBZYAuwUtIeH2Kc\nZmZmZpZj0KtcI2IF6VgHJNXby+Ay4LqI+JfsmnOBjcCfAst2fahm1gobc3YTabBpCelXOE/9lpvO\nbPCMavB8F9Vvl7c1CUBfb/72JGZmZdDSe+gkfRIYBzzUXxYR7wBPAMc1/0xrWzmsNuY4VDgWieMA\nsK5x9lkyfk0kjkOFY5GUKw6tXhQxjvR2vfbt98asrkm1Z5mVleNQ4VgkjgM4CjtyNBLHocKxSMoV\nhyJOithFK4BR2fevAUuBiQw818zMzMys06xlYBK6renWrU7oXgcEHMiOs3QHAk81bjodGJ99vxQ4\nu8VDMzMzMxupJjFwEqsHWNRU65Z+5BoRL5GSumn9ZZL2BY4FHmtlX2ZmZmaWDHqGTtJo4FDSTBzA\nIZKOAt6KiFeAm4CrJb0I/Aq4DngVuDfnKUcB/PCHJ3LEEUcAMGfOT7jxxgHb25WO41DhWCStiMNr\nfGnQbX7Ga4Nus4GfNXi+DfkNnzqjfvnqSvlP58zhSzfeWNVmsKMDfpbTD+xChIaPfzcSx6HCsUg6\nIQ7PPvssX/nKIqjck5ZLEYNbLibpJOAnDNyr4AcR8dXsmm+R9qEbA/wHcHFEvJjzfLOAOwY1CDMz\nM7PyOCci7mx0waATulaTtB9wCmk2r/m7/8zMzMw62yjgYGBlRLzZ6MJhT+jMzMzM7MNp9T50ZmZm\nZjbEnNCZmZmZtTkndGZmZmZtzgmdmZmZWZsbUQmdpIslvSTpPUmPS/rMcI+paJKmSrpP0muS+iQN\n2DRH0nxJGyRtlfSApEOHY6xFknSlpFWS3pG0UdI9kg6rc11Hx0LSbElrJL2dfT0maXrNNR0dg3ok\nzc1+P26oKe/4WEial/3s1V/ra67p+Dj0k/QxSUskbc5+3jWSJtdc09HxyP5O1r4m+iQtrLqmo2MA\nIKlL0nWSfpn9nC9KurrOdR0fCxhBCZ2ks4C/A+YBfwSsAVZK2n9YB1a80cDTwEUM3NsPSVcAl5D2\n9fsssIUUlz2GcpBDYCqwkHSqyMnA7sCPJe3Vf0FJYvEKcAUwGTgGeBi4V9IRUJoY7CB7Y3ch6d+E\n6vIyxWId6QjFcdnXCf0VZYqDpDHAo8DvSdtdHQF8E/hN1TVliMcUKq+FccAXSH8/lkFpYgAwF/g6\n6e/nHwCXA5dLuqT/ghLFAiJiRHwBjwM3Vz0W6YSJy4d7bEMYgz7g1JqyDcCcqsf7Au8BZw73eAuO\nxf5ZPE5wLHgTOL+MMQD2AZ4HPk/a0PyGsr0eSG9yn2xQX4o4ZD/bAuDfdnJNaeJR9TPeBPy8bDEA\n7ge+V1P2T8DtZYtFRIyMGTpJu5NmIx7qL4sU+QeB44ZrXMNN0idJ776q4/IO8ASdH5cxpHecb0E5\nY5F9nDAT2Bt4rIwxAL4D3B8RD1cXljAWE7LbMn4h6YeSPgGljMMXgdWSlmW3Zjwp6YL+yhLGo//v\n5znAP2SPyxSDx4BpkiYAKB1DejywPHtcplgM/izXguwPdAMba8o3AocP/XBGjHGkpKZeXMYN/XCG\nhiSR3nE+EhH99wqVJhaSJgL/Sdoh/HfAaRHxvKTjKEkMALJk9mjSx0u1SvN6IH16cR5ppnI88C3g\n37PXSZniAHAI8A3S7Tl/Q/oI7RZJv4+IJZQvHgCnAR8BfpA9LlMMFpBm3J6T1Eu6jeyqiLgrqy9T\nLIpL6CRdDPwVKWhrgEsj4r+K6s86ym3AkaR3WmX0HHAU6R/pPwNul3Ti8A5paEn6OCmpPzki3h/u\n8QyniFhZ9XCdpFXAr4EzSa+VMukCVkXENdnjNVliOxtYMnzDGlZfBf41Il4f7oEMg7OAWcBMYD3p\nDeDNkjZkCX6pFJLQVS1wuBBYBcwh3YR4WERsrrl2P9JN8L3AcZKq//E+AnivdgVThzuk6ufdj3Qv\n4R9LeqHqmk8Bz3doXK4ATgS+BoyXND4rL2MsAP4vMA24jvQOvCwxOAk4AHgqTdgCaRb/REmXAqdT\nnljU8yppYcQblCsObwKban6ud4FPZWVl+3diHOnv5zdL+nfjRuD7wC+APYFngbuAayU9Q2fEYnjP\ncpX0OPBERFyWPRZp9d4tEXF9zbWzgDtaPggzMzOzznBORNzZ6IKWz9BVLXD42/6yiAhJeQscfpX+\nczrpVjqAFcD0OpeWjeNQ4VgkjkMyXHHIfwN8Id8b9LN9uUHdKazMrfva6qXbv39gzkN84cZpAHRN\nWZzbpm/1ebl1ee16V5+f2+Yfp+yeWzc8/LtR4VgknRCHzcA/w/ZcKV8RH7kOdoHDtkqz/k/XRlV9\nX2aOQ4VjkTgOyXDFIT+h25XRfHoXa8dP/sn27/ccsyfjJ6f7uxttW9A3Of8e8Lx2vQ3awEjbxsu/\nGxWORdJRcdi2swtGyipXUiY9Kvv+NWApMBGYNGwjMjMzMxsaa0l7iFfbaR63XREJ3WbSAocDa8oP\nBBqswplOJZNeCpxdwNDMzMzMRqJJDJzE6gEWNdW65RsLZ1sM/Iy0Mg/YvihiGmkTQDMzMzNroaI+\ncr0BWCzpZ1S2LdkbWNxc84kFDavdOA4VjkXiOCSOQ78/nHnkcA9hhPBrosKxSMoVh0ISuohYJml/\nYD7po9angVMi4o3mnsH3zSWOQ4VjkTgOSdFxmJ1Tnr8oYjbzB93L2B81qNxUe9dKlcrefEyc9Yfb\nv+/rnZvbpKt7QW5dXrvurm83GOC8BnXDwb8bFY5FUq44FLYoIiJuI+34b2ZmZmYFavk9dGZmZmY2\ntJzQmZmZmbW5lid0kq6UtErSO5I2SrpH0mGt7sfMzMzMkiJm6KYCC4FjSYcG7w78WNJeBfRlZmZm\nVnotXxQRETOqH0s6D9hEOt/1kVb3Z2bWcsfmrTDNX+V64CcaPJ/qF99+xhm5Tc7g9vzni/rj6Npt\n8CtZzawzDMU9dGNI/wq+NQR9mZmZmZVOoQlddkLETcAjEbG+yL7MzMzMyqqwfegytwFHAscX3I+Z\nmZlZaRWW0Em6FZgBTI2Inp23WAGMqimbSNl2ejYzM7MyWgusqynb1nTrQhK6LJn7EnBSRLzcXKvp\nwPgihmNmZmY2wk1i4CRWD7CoqdYtT+gk3QacDZwKbJHUv1zs7YhoPtU0MzMzs6YUMUM3m7Sq9ac1\n5edDo3X4ZmYjxFdy9hlpQGPz6/I2O7l068LcNi+MnpBbdyuX1C3v+yB/a5Kubm9pYtbJitiHzseJ\nmZmZmQ0hJ19mZmZmbc4JnZmZmVmbc0JnZmZm1uYKT+gkzZXUJ/3/7d19kB3Vee/7728GsGA4mFNG\nIHFsDsa8xGQUiJCNuViQi0hQ6ZZJcGKQRMIFooDMS3GJT/FSQGSgHKu4FcybcR1sxzIyCIvcQ4CU\nItmA8wIEdGQZWUICG4PNi0YSAhuMhAjMPPeP1cNs7dm9NTPsnv3Sv0/VFNOre+1e+6E1+9mre62l\nG4s+l5mZmVkZFb3016eA84A1RZ7HzMzMrMyKXClib+B7wDzgmqLOY2bWaD1nv1qzXLkTkMCrPT25\n+yJqT4Py1vETc+vsf9Bvc/dxT+12dO1WZ2qSMUxp0l9vOpPu/F1mNv6K7KH7OvBgRDxS4DnMzMzM\nSq+opb9mA0cD04p4fTMzMzMbUsTSXx8FbgJOjoh3R15zOTChqqyX4euamZmZmXWatcC6qrKRr5ha\nRA/dMcBEYLWkwQdHuoETJF0EfCgiajwAMhOYXEBzzMzMzFrdFIZ3YvUBd4yodhEJ3UMMb9EiYAOw\nsBBtc8YAACAASURBVHYyZ2ZmZmZjVcRartuA9ZVlkrYBr0XEhkafz8ys0Wb1LKtZXnusarJMs3L3\n5X2LjSeuy61z7ZN1Tvb92i2pO5J1DCNgu3NGvyYL6uwzs/E2XitFuFfOzMzMrCCFzUNXKSJOGo/z\nmJmZmZWR13I1MzMza3NO6MzMzMzaXCEJnaQDJS2WtFXSdklrJE0t4lxmZmZmZVfExML7Ao8BDwOn\nAFuBw4BfN/pcZmZmZlbMoIgrgBcjYl5F2a8KOI+Z2QeQP/h+lmpPW1LPMupNW5Iz4cmxf5Fb528O\nujZ334Kc6TzrTk3Snz+liZm1vyJuuX4OWCVpqaTNklZLmrfLWmZmZmY2JkUkdIcAXwSeBf4I+AZw\ni6T8r6JmZmZmNmZF3HLtAlZGxDXZ9hpJvcB8YHF+teXAhKqyXoavImZmZmbWadYC66rKdoy4dhEJ\nXR9p3dZKG4DP1682E5hcQHPMzMzMWt0Uhndi9QF3jKh2EbdcHwOOqCo7Ag+MMDMzMytEEQnd14DP\nSLpS0ickzQXmAbcVcC4zMzOz0mv4LdeIWCXpNGAhcA3wAnBJRNzT6HOZmRVhFrWnLYnImX4EuHj7\nraM+z94Pbc3dt7Vn7/yKqt2Ogffypybp6vaUJmadrIhn6IiIZZDzF9HMzMzMGspruZqZmZm1OSd0\nZmZmZm2u4QmdpC5J10t6XtJ2Sc9JurrR5zEzMzOzpKi1XM8HzgLWA9OARZJ+ExEe6WpmZmbWYEUk\ndMcB90fE8mz7xWzqkk8XcC4zs4abeO9bNcuD/FGub22ZOOrzfOeC2bn7Llb+qNnD49ma5V271RnJ\nOoYRsP31Rr925+8ys/FXxDN0jwMzJB0GIOko4Hg86tXMzMysEEX00C0E9gGekdRPShqv8jx0ZmZm\nZsUoIqE7A5gLzCY9Q3c0cLOkjRGxuIDzmZmZmZVaEQndDcBXI+LebPtpSQcDVwJ1ErrlwISqsl6G\nL1RrZmZm1mnWAuuqynaMuHYRCd1eQH9V2QC7fF5vJjC5gOaYmZmZtbopDO/E6gPuGFHtIhK6B4Gr\nJb0MPA1MBS4FvlXAuczMzMxKr4iE7iLgeuDrwP7ARuAbWZmZWcvTvXl7Ir/SS/lTmuTVO2v/3BNx\nzpb8cWRXX3hVzfK6U5OMYUqT7pzpTJIFdfaZ2XhreEIXEduAv85+zMzMzKxgXsvVzMzMrM05oTMz\nMzNrc6NO6CRNl/SApFckDUg6tcYx10naKGm7pB9KOrQxzTUzMzOzamPpoesBngIuoMaTvpIuJw2M\nOI+0fus2YIWkPT5AO83MzMwsx6gHRUTEctIswEiqNazrEuD6iPin7JizgM3AnwBLx95UMzMzM6ul\noaNcJX0cmAQ8PFgWEW9KehI4jhEndGvxChHgOFRyLBLHISk2DptzZhOpM2kJ6Xtrnto1t5xe5xVV\n5/UuGKq3bsl6euccCexiapL+/ClNOoP/bQxxLJJyxaHRgyImkf5yVf8l2pztG6HqpS/KynEY4lgk\njkPiOAx6+p71zW5Ci/A1McSxSMoVB49yNTMzM2tzjZ5YeBMg4AB27qU7APhJ/arLgQnZ768AS4Be\nytRdamZmZmW1luG9ijtGXLuhCV1EvCBpEzAD+CmApH2AY0lLgdUxE5ic/b4EmNPIppmZmZm1sCkM\n78TqA+4YUe1RJ3SSeoBDST1xAIdIOgp4PSJeAm4Crpb0HPBL0hquLwP357xk1i23taJoB+lNlJ3j\nMMSxSByHpBFxyB+Q8NNR16hXK79mvRpE/t6+1Zve//2d37zz/nZXnQYOVNQZqfrP5LTadeh/G0Mc\ni6QT4vB+bjSh3lEAiqj/J2pYBelE4EcM/wv13Yg4Nzvmy6R56PYF/h24MCKey3m9ucBdo2qEmZmZ\nWXmcGRF31ztg1Aldo0n6CHAKqTdv5DeLzczMzDrbBOBgYEVEvFbvwKYndGZmZmb2wXjaEjMzM7M2\n54TOzMzMrM05oTMzMzNrc07ozMzMzNpcSyV0ki6U9IKktyU9IelTzW5T0SRNl/SApFckDUg6tcYx\n10naKGm7pB9KOrQZbS2SpCslrZT0pqTNku6TdHiN4zo6FpLmS1oj6Y3s53FJM6uO6egY1CLpiuzf\nx41V5R0fC0kLsvde+bO+6piOj8MgSQdKWixpa/Z+10iaWnVMR8cj+5ysviYGJN1acUxHxwBAUpek\n6yU9n73P5yRdXeO4jo8FtFBCJ+kM4O+ABcDvA2uAFZL2a2rDitcDPAVcQI3ZRyVdDlxEmtfv08A2\nUlz2GM9GjoPpwK2kVUVOBnYHfiBpz8EDShKLl4DLganAMcAjwP2SPgmlicFOsi9255H+JlSWlykW\n60hLKE7Kfj47uKNMcZC0L/AY8A5puqtPAl8Cfl1xTBniMY2ha2ES8Iekz4+lUJoYAFwBnE/6/Pwd\n4DLgMkkXDR5QolhARLTED/AEcHPFtkgrTFzW7LaNYwwGgFOryjYCl1Zs7wO8DZze7PYWHIv9snh8\n1rHgNeCcMsYA2Bt4FjiJNKH5jWW7HkhfclfX2V+KOGTvbSHwr7s4pjTxqHiPNwE/K1sMgAeBb1aV\n/QNwZ9liERGt0UMnaXdSb8TDg2WRIv8QcFyz2tVskj5O+vZVGZc3gSfp/LjsS/rG+TqUMxbZ7YTZ\nwF7A42WMAWkN6Acj4pHKwhLG4rDssYxfSPqepI9BKePwOWCVpKXZoxmrJc0b3FnCeAx+fp4JfDvb\nLlMMHgdmSDoMQGkZ0uOBZdl2mWIx+rVcC7If0A1srirfDBwx/s1pGZNISU2tuEwa/+aMD0kifeN8\nNCIGnxUqTSwk9QL/QZoh/LfAaRHxrKTjKEkMALJk9mjS7aVqpbkeSHcvzib1VE4Gvgz8W3adlCkO\nAIcAXyQ9nvMV0i20WyS9ExGLKV88AE4DPgx8N9suUwwWknrcnpHUT3qM7KqIuCfbX6ZYtExCZ1bp\nduBI0jetMnoGOIr0R/rPgDslndDcJo0vSR8lJfUnR8S7zW5PM0XEiorNdZJWAr8CTiddK2XSBayM\niGuy7TVZYjsfWNy8ZjXVucA/R8SmZjekCc4A5gKzgfWkL4A3S9qYJfilUtgtV41uxOpWoJ/00G+l\nA4AyXqSDNpGeJSxNXCTdBswC/iAi+ip2lSYWEfFeRDwfET+JiKtIgwEuoUQxID2CMRFYLeldSe8C\nJwKXSPpP0jfsssRiJxHxBvAz4FDKdU0A9AEbqso2AAdlv5cqHpIOIg0i+2ZFcZlicAOwMCLujYin\nI+Iu4GvAldn+MsWimB66ihGr5wErgUtJo0oOj4itVcd+hDRa6VlgtqSXK3bPBO6pHpLe4Q6per+v\nAWdJujvb7gE+AyzrwLhcTvrQ/itgvxojnMsUi0ofBg4E/ivlicGrpB6oStcCLwDfIT1jWZZYVNuT\n9CjKI5TrmoDUC3NM1fuaDmytKCtTPM4nPWfcV9LPjf8C/Leq9zQJ2LODrocJwMHAioh4rd6BykZ9\nNJSkJ4AnI+KSbFuk6RhuiYgbqo6dC9zV8EaYmZmZdYYzI+Luegc0vIeuYsTq3w6WRURIyhux+sv0\nn8+TxkYALCd1zpWd4zDEsUgch8RxGNKKsajdUXDeTncGR+ZP6+w7hcrHCxeQOnGTv1y1pGadrmmL\ncl9vYNXZufvy6vWvOie3zt9P2z13X7Fa8Zpohk6Iw1bgf8H7uVK+Im65jnbE6o6hapOzogkVv5eZ\n4zDEsUgch8RxGNKKsaid0I2llb834r377LQ9eeqPatao9+D4wNT8gY959frr1IFmzV3bitdEM3RU\nHHbs6oAWGuW6nBR8gFeAJUAvMKVpLTIzMzMbH2tJi8JU2mUe974iEroxjlidyVAmvQSYU0DTzMzM\nzFrRFIZ3YvUBd4yodsOnLcnmjPoxMGOwLBsUMYM0q7OZmZmZNVBRt1xvBBZJ+jFD05bsBSwaWfXe\ngprVbhyHIY5F4jgkjsOQZsVifp19tZ+hm891oz7L/t+vs3NLxY2gVf83TKvYlmpWGei/IvfluroX\n5u7Lq9fd9dU6DVxQZ1+R/O8jKVccCknoImJpNofYdaRbrU8Bp0TEqyN7BT83lzgOQxyLxHFIHIch\njgUA0/yYzhBfE0m54lDYoIiIuJ20hJOZmZmZFaiwpb/MzMzMbHw4oTMzMzNrcw1P6CRdKWmlpDcl\nbZZ0n6TDG30eMzMzM0uK6KGbDtwKHAucDOwO/EDSngWcy8zMzKz0Gj4oIiJmVW5LOhvYQlrf9dFG\nn8/MzJrg2Oq54yvVnrbkgI/VqVJ7lhHu/MIXcqt8gTvrNKF2G7p2G/3UJGbtYDyeoduX9K/79XE4\nl5mZmVnpFJrQZStE3AQ8GhHrizyXmZmZWVkVNg9d5nbgSOD4XR+6HJhQVdZL2SYGNDMzszJaC6yr\nKtsx4tqFJXSSbgNmAdMjom/XNWYCk4tqjpmZmVkLm8LwTqw+4I4R1S4kocuSuT8GToyIF4s4h5mZ\nmZklDU/oJN0OzAFOBbZJGhwK9UZEjLzv0MzMzMxGpIgeuvmkUa3/UlV+DtQbY25mZm3jz3PmGalD\n++fvqz3JCFy8/dbcOj/vOSx3321cVLN84L38qUm6uj2libWvIuah83JiZmZmZuPIyZeZmZlZm3NC\nZ2ZmZtbmCk/oJF0haUDSjUWfy8zMzKyMil4p4lPAecCaIs9jZmZmVmZFTiy8N/A9YB5wTVHnMTOz\n8ddz9qu5+5QzZvXVnp7cOhG1R82+dfzE3Dr7H/Tb3H3cU7sNXbvVGck6hhGw/fVGv3bn7zJrtCJ7\n6L4OPBgRjxR4DjMzM7PSK2qliNnA0cC0Il7fzMzMzIYUsVLER4GbgJMj4t1Gv76ZmZmZ7ayIHrpj\ngInAakmDD0V0AydIugj4UETUeLhhOTChqqyX4QvVmpmZmXWatcC6qrKRr5haREL3EMOzsEXABmBh\n7WQOYCYwuYDmmJmZmbW6KQxPn/qAO0ZUu4ilv7YB6yvLJG0DXouIDY0+n5mZmVnZFTZtSZW8dZfN\nzKwNzepZlruv9gQksEyzcuvkfUjEE9fl1rn2ydxd8P3arag7NckYpjTpzpnOJFlQZ59ZY41LQhcR\nJ43HeczMzMzKyGu5mpmZmbU5J3RmZmZmbc4JnZmZmVmbKyShk3SgpMWStkraLmmNpKlFnMvMzMys\n7IpYKWJf4DHgYeAUYCtwGPDrRp/LzMzMzIoZ5XoF8GJEzKso+1UB5zEzs0Llzzg1S/nTluRZRr1p\nS3ImOzn2L3Lr/M1B1+buW5Azh33dqUn686c0MWt1Rdxy/RywStJSSZslrZY0b5e1zMzMzGxMikjo\nDgG+CDwL/BHwDeAWSflfs8zMzMxszIq45doFrIyIa7LtNZJ6gfnA4vxqy4EJVWW9DF/XzMzMzKzT\nrAXWVZXtGHHtIhK6PqB6zdYNwOfrV5sJTC6gOWZmZmatbgrDO7H6gDtGVLuIW66PAUdUlR2BB0aY\nmZmZFaKIHrqvAY9JuhJYChwLzAP+qoBzmZlZE8wif5RrRO0Rqxdvv3XU59n7oa25+7b27J1fUbXb\nMPBe/kjWrm6PgLX21fAeuohYBZwGzCHdEL4KuCQi7mn0uczMzMysmB46ImIZ1Pn6ZmZmZmYN47Vc\nzczMzNqcEzozMzOzNtfwhE5Sl6TrJT0vabuk5yRd3ejzmJmZmVlS1Fqu5wNnAeuBacAiSb+JiNsK\nOJ+ZmZlZqRWR0B0H3B8Ry7PtFyXNBT5dwLnMzKwJJt77Vu6+oPaUIW9tmTjq83zngtm5+y5W/jQo\nh8ezNcu7dqszNckYpjTprzedSXf+LrNGK+IZuseBGZIOA5B0FHA8HvVqZmZmVogieugWAvsAz0jq\nJyWNV3keOjMzM7NiFJHQnQHMBWaTnqE7GrhZ0saIWJxfbTkwoaqsl+HrmpmZmZl1mrXAuqqyHSOu\nXURCdwPw1Yi4N9t+WtLBwJVAnYRuJjC5gOaYmZmZtbopDO/E6gPuGFHtIp6h2wvoryobKOhcZmZm\nZqVXRA/dg8DVkl4GngamApcC3yrgXGZmZmalV0RCdxFwPfB1YH9gI/CNrMzMzDqA7q23N2oXv1R7\nOpN6dc7aP/9E52zJH2t39YVX1SyvOzXJGKY06c6ZziRZUGefWWM1PKGLiG3AX2c/ZmZmZlYwP9dm\nZmZm1uac0JmZmZm1uVEndJKmS3pA0iuSBiSdWuOY6yRtlLRd0g8lHdqY5pqZmZlZtbH00PUATwEX\nUOMpVkmXkwZGnEdav3UbsELSHh+gnWZmZmaWY9SDIiJiOWlZByTVGrJ0CXB9RPxTdsxZwGbgT4Cl\nY2+qmZm1is11RrnmjHElfRSMrtaW0/NfDdV5vQtq16s7krU/fwSsWatr6DN0kj4OTAIeHiyLiDeB\nJ4HjRv5KaxvZrDbmOAxxLBLHIXEchjgWAMR9zW5BC/E1kZQrDo0eFDGJ9DWr+mvT5mzfCFWvZVZW\njsMQxyJxHBLHYYhjkfxjsxvQQnxNJOWKg0e5mpmZmbW5Rk8svAkQcAA799IdAPykftXlwITs91eA\nJUAvwxeqNTMzM+s0axneq7hjxLUbmtBFxAuSNgEzgJ8CSNoHOJa0FFgdM4HJ2e9LgDmNbJqZmZlZ\nC5vC8E6sPuCOEdUedUInqQc4lNQTB3CIpKOA1yPiJeAm4GpJzwG/JK3h+jJwf85LTgDo7n4NKd0B\n7u9/h+7ueqOhysFxGOJYJI5D4jgMKTYW+SNMf1rn4yOv1m7pe/6oatU7z24aer3+996ke7eh7S2r\nt9Sso93qtDunTj31Xm+3uqN6i+N/H0knxCHiNfr7gaFbmLkUUWdIeK0K0onAjxj+r++7EXFudsyX\nSfPQ7Qv8O3BhRDyX83pzgbtG1QgzMzOz8jgzIu6ud8CoE7pGk/QR4BRSb97IbxabmZmZdbYJwMHA\nioh4rd6BTU/ozMzMzOyD8bQlZmZmZm3OCZ2ZmZlZm3NCZ2ZmZtbmnNCZmZmZtbmWSugkXSjpBUlv\nS3pC0qea3aaiSZou6QFJr0gakHRqjWOuk7RR0nZJP5R0aDPaWiRJV0paKelNSZsl3Sfp8BrHdXQs\nJM2XtEbSG9nP45JmVh3T0TGoRdIV2b+PG6vKOz4WkhZk773yZ33VMR0fh0GSDpS0WNLW7P2ukTS1\n6piOjkf2OVl9TQxIurXimI6OAYCkLknXS3o+e5/PSbq6xnEdHwtooYRO0hnA3wELgN8H1gArJO3X\n1IYVrwd4CriAGjNrSrocuIg0r9+ngW2kuOwxno0cB9OBW0mripwM7A78QNKegweUJBYvAZcDU4Fj\ngEeA+yV9EkoTg51kX+zOI/1NqCwvUyzWkZZQnJT9fHZwR5niIGlf4DHgHdJ0V58EvgT8uuKYMsRj\nGkPXwiTgD0mfH0uhNDEAuAI4n/T5+TvAZcBlki4aPKBEsYCIaIkf4Ang5optkVaYuKzZbRvHGAwA\np1aVbQQurdjeB3gbOL3Z7S04Fvtl8fisY8FrwDlljAGwN/AscBJpQvMby3Y9kL7krq6zvxRxyN7b\nQuBfd3FMaeJR8R5vAn5WthgADwLfrCr7B+DOssUiIlqjh07S7qTeiIcHyyJF/iHguGa1q9kkfZz0\n7asyLm8CT9L5cdmX9I3zdShnLLLbCbOBvYDHyxgD0hrQD0bEI5WFJYzFYdljGb+Q9D1JH4NSxuFz\nwCpJS7NHM1ZLmje4s4TxGPz8PBP4drZdphg8DsyQdBiA0jKkxwPLsu0yxWL0a7kWZD+gG4YtfLcZ\nOGL8m9MyJpGSmlpxmTT+zRkfkkT6xvloRAw+K1SaWEjqBf6DNEP4b4HTIuJZScdRkhgAZMns0aTb\nS9VKcz2Q7l6cTeqpnAx8Gfi37DopUxwADgG+SHo85yukW2i3SHonIhZTvngAnAZ8GPhutl2mGCwk\n9bg9I6mf9BjZVRFxT7a/TLEoLqGTdCHwP0hBWwNcHBH/u6jzWUe5HTiS9E2rjJ4BjiL9kf4z4E5J\nJzS3SeNL0kdJSf3JEfFus9vTTBGxomJznaSVwK+A00nXSpl0ASsj4ppse02W2M4HFjevWU11LvDP\nEbGp2Q1pgjOAucBsYD3pC+DNkjZmCX6pFHLLdQwDHLYC/aSHfisdAJTxIh20ifQsYWniIuk2YBbw\nBxHRV7GrNLGIiPci4vmI+ElEXEX693MJJYoB6RGMicBqSe9Kehc4EbhE0n+SvmGXJRY7iYg3gJ8B\nh1KuawKgD9hQVbYBOCj7vVTxkHQQaRDZNyuKyxSDG4CFEXFvRDwdEXcBXwOuzPaXKRaF9dBdCvzP\niLgT0lQMwP9F+iZxQ+WBkj5CGq30LDBb0ssVu2cC91QPSe9wh1S939eAsyTdnW33AJ8BlnVgXC4n\nfWj/FbBfjS8AZYpFpQ8DBwL/lfLE4FVSD1Sla4EXgO+QnrEsSyyq7Ul6FOURynVNQOqFOabqfU0H\ntlaUlSke55OeM+4r6efGfwH+W9V7mgTs2UHXwwTgYGBFRLxW70Bloz4aJntAczvwpxHxQEX5IuDD\nEXFa1fFzgbsa2ggzMzOzznFmRNxd74AieuhGO8Dhl+k/n8+qAiwndc6VneMwxLFIHIfEcRjiWCTt\nFofanSnn7XT3dOT+tOL3BaTubIBTWFHj6OQvVy3J3dc1bVHN8oFVZ4+6Tv+qc3Lr/P203XP3fXDt\ndk3UshX4X/B+rpSvFUa57kj/2Y80gAtSD+PknMPLxHEY4lgkjkPiOAxxLJJ2i0PthG6s7+D3Kn7f\nZ6ft3xt27Pvnmvqj3H15D9gPTM0fHJpXp79OHShyft92uybq2rGrA4pI6MY4wGE5KfgArwBLgF5g\nSsMbaGZmZtZa1pIWham0yzzufQ1P6CLiXUk/BmYAD8D784rNAG7JrzmToUx6CTCn0U0zMzMza1FT\nGN6J1QfcMaLaRd1yvRFYlCV2K0mjXvcCFhV0PjMzM7PSKiShi4il2ZQT15FutT4FnBIRr47sFXqL\naFYbchyGOBaJ45A4DkMci6QV4zC/zr7az9DN57oxnWn/7w/9ftZjsP/gtOxbqp9+qiDl7hrov6Jm\neVf3wlHX6e76an4bWFBn3wfVitdEcQobFBERt5Nm/B8DPzeXOA5DHIvEcUgchyGOReI4DJpT1jV2\nhinXNVHIShFmZmZmNn6c0JmZmZm1OSd0ZmZmZm2u4QmdpCslrZT0pqTNku6TdHijz2NmZmZmSRE9\ndNOBW4FjgZOB3YEfSNqzgHOZmZmZlV4REwvPqtyWdDawBTgGeLTR5zMzM2tJx9aZMiRn2pIDPlan\nSv4sI9z5hS/ULP8Cd9ZpQu02AHTtVnt6krypSaz5xuMZun1JV+7r43AuMzMzs9IpNKHLlvy6CXg0\nItYXeS4zMzOzsipsYuHM7cCRwAimOVwOTKgq66VsEwOamZlZGa0F1lWV7Rhx7cISOkm3AbOA6RHR\nt+saM4HJRTXHzMzMrIVNYXgnVh9wx4hqF5LQZcncHwMnRsSLRZzDzMzMzJKGJ3SSbgfmAKcC2yQN\nDvN5IyJG3ndoZmZmZiNSRA/dfNKo1n+pKj8H6o2fNjMz6yB/XmeekRzaP39f/iQjcPH2W2uW/7zn\nsNw6t3FR7r6B92pPT9LVXXs6E/CUJs1WxDx0Xk7MzMzMbBw5+TIzMzNrc07ozMzMzNpc4QmdpCsk\nDUi6sehzmZmZmZVR0StFfAo4D1hT5HnMzMzMyqzIiYX3Br4HzAOuKeo8ZmZmrajn7Fdz9ylnzOqr\nPT25dSLyR82+dfzEmuX7H/Tb3Drckz9utmu32qNZ80a/Qv4I2P56o1+783fZ6BTZQ/d14MGIeKTA\nc5iZmZmVXlErRcwGjgamFfH6ZmZmZjakiJUiPgrcBJwcEe82+vXNzMzMbGdF9NAdA0wEVksavOHf\nDZwg6SLgQxFR48b9cmBCVVkvwxeqNTMzM+s0a4F1VWUjXzG1iITuIYZnYYuADcDC2skcwExgcgHN\nMTMzM2t1UxiePvUBd4yodhFLf20D1leWSdoGvBYRGxp9PjMzM7OyK2zakir11hQ2MzPrOLN6luXu\ny5uAZJlm5dap90EaT1xXs/zaJ+tU+n7+NCh505PkTWdSr053znQmyYI6+2w0xiWhi4iTxuM8ZmZm\nZmXktVzNzMzM2pwTOjMzM7M2V0hCJ+lASYslbZW0XdIaSVOLOJeZmZlZ2RUxsfC+wGPAw8ApwFbg\nMODXjT6XmZmZmRUzKOIK4MWImFdR9qsCzmNmZtZk+WNPZyl/lGueZdQb5Zo/KpVj/6Jm8d8cdG1u\nlQV508KSP5p1oL/2SFZrviJuuX4OWCVpqaTNklZLmrfLWmZmZmY2JkUkdIcAXwSeBf4I+AZwi6Ta\nXx/MzMzM7AMp4pZrF7AyIq7JttdI6gXmA4sLOJ+ZmZlZqRWR0PWR1m2ttAH4fP1qy4EJVWW9DF/X\nzMzMzKzTrAXWVZXtGHHtIhK6x4AjqsqOYJcDI2YCkwtojpmZmVmrm8LwTqw+4I4R1S7iGbqvAZ+R\ndKWkT0iaC8wDbivgXGZmZmal1/AeuohYJek0YCFwDfACcElE3NPoc5mZmbWqWeRPWxJRewqSi7ff\nOqZz7f3Q1prlW3v2zq+k/GlQBt6rPT1JV3ft6UzAU5o0WxG3XImIZVDnSjYzMzOzhvFarmZmZmZt\nzgmdmZmZWZtzQmdmZmbW5hqe0EnqknS9pOclbZf0nKSrG30eMzMzM0uKGBRxBXA+cBawHpgGLJL0\nm4jw1CVmZmZmDVZEQncccH9ELM+2X8zmovt0AecyMzNrSRPvfSt3X1B7ypC3tkwc07m+c8HsmuUX\nK38alMPj2dx9XbvVnp4kbzoTyJ/SpL/edCbd+btsdIp4hu5xYIakwwAkHQUcj6cxMTMzMytEET10\nC4F9gGck9ZOSxqs8sbCZmZlZMYpI6M4A5gKzSc/QHQ3cLGljRCzOr7YcmFBV1svwdc3MzMzMaoMR\nZQAAF1JJREFUOs1aYF1V2Y4R1y4iobsB+GpE3JttPy3pYOBKoE5CNxOYXEBzzMzMzFrdFIZ3YvUB\nd4yodhHP0O0F9FeVDRR0LjMzM7PSK6KH7kHgakkvA08DU4FLgW8VcC4zM7OWpHvr7Y3axS/VHv1a\ntw5w1v61T3bOlvzH16++8KrcfXmjWfNGv9ar050z+jVZUGefjUYRCd1FwPXA14H9gY3AN7IyMzMz\nM2uwhid0EbEN+Ovsx8zMzMwK5ufazMzMzNqcEzozMzOzNjfqhE7SdEkPSHpF0oCkU2scc52kjZK2\nS/qhpEMb01wzMzMzqzaWHroe4CngAmoMuZF0OWlgxHmk9Vu3ASsk7fEB2mlmZmZmOUY9KCIilpOW\ndUBSrfHVlwDXR8Q/ZcecBWwG/gRYOvammpmZtY/NdaYtyZ+AZHOdV8yvteX0nH2q83oX5L9e3vQk\nA/21pyax5mvoM3SSPg5MAh4eLIuIN4EngeNG/kprG9msNuY4DHEsEschcRyGOBaJ4zDovmY3oGWU\n65po9KCISaSvENVfCTZn+0aoei2zsnIchjgWieOQOA5DHIvEcRj0j81uQMso1zVRxMTCY7QcmJD9\n/gqwBOhl+LpmZmZmZp1mLcOT0B0jrt3ohG4TIOAAdu6lOwD4Sf2qM4HJ2e9LgDkNbpqZmZlZq5rC\n8E6sPuCOEdVu6C3XiHiBlNTNGCyTtA9wLPB4I89lZmZmZsmoe+gk9QCHknriAA6RdBTwekS8BNwE\nXC3pOeCXpDVcXwbuz3nJCQBHHdXN3nun5qxfL448soXuBjeJ4zDEsUgch8RxGOJYJK0Yhw0cP+o6\nx7NhTOd6puJcb61fzzNHHpleT8/k1tlj9Ydy9+n42m2POnVG+1oAxxf45FcrXhOj9dZb3axZAww9\nk5ZLEfnDlmtWkE4EfsTw8dPfjYhzs2O+TJqHbl/g34ELI+K5nNebC9w1qkaYmZmZlceZEXF3vQNG\nndA1mqSPAKeQevNG/vSfmZmZWWebABwMrIiI1+od2PSEzszMzMw+mEbPQ2dmZmZm48wJnZmZmVmb\nc0JnZmZm1uac0JmZmZm1uZZK6CRdKOkFSW9LekLSp5rdpqJJmi7pAUmvSBqQdGqNY66TtFHSdkk/\nlHRoM9paJElXSlop6U1JmyXdJ+nwGsd1dCwkzZe0RtIb2c/jkmZWHdPRMahF0hXZv48bq8o7PhaS\nFmTvvfJnfdUxHR+HQZIOlLRY0tbs/a6RNLXqmI6OR/Y5WX1NDEi6teKYjo4BgKQuSddLej57n89J\nurrGcR0fC2ihhE7SGcDfAQuA3wfWACsk7dfUhhWvB3gKuIDhc/sh6XLgItK8fp8GtpHissd4NnIc\nTAduJa0qcjKwO/ADSXsOHlCSWLwEXA5MBY4BHgHul/RJKE0MdpJ9sTuP9DehsrxMsVhHWkJxUvbz\n2cEdZYqDpH2Bx4B3SNNdfRL4EvDrimPKEI9pDF0Lk4A/JH1+LIXSxADgCuB80ufn7wCXAZdJumjw\ngBLFAiKiJX6AJ4CbK7ZFWmHisma3bRxjMACcWlW2Ebi0Ynsf4G3g9Ga3t+BY7JfF47OOBa8B55Qx\nBsDewLPASaQJzW8s2/VA+pK7us7+UsQhe28LgX/dxTGliUfFe7wJ+FnZYgA8CHyzquwfgDvLFouI\naI0eOkm7k3ojHh4sixT5h4DjmtWuZpP0cdK3r8q4vAk8SefHZV/SN87XoZyxyG4nzAb2Ah4vYwyA\nrwMPRsQjlYUljMVh2WMZv5D0PUkfg1LG4XPAKklLs0czVkuaN7izhPEY/Pw8E/h2tl2mGDwOzJB0\nGIDSMqTHA8uy7TLFosBF1EZnP6Ab2FxVvhk4Yvyb0zImkZKaWnGZNP7NGR+SRPrG+WhEDD4rVJpY\nSOoF/oM0Q/hvgdMi4llJx1GSGABkyezRpNtL1UpzPZDuXpxN6qmcDHwZ+LfsOilTHAAOAb5Iejzn\nK6RbaLdIeiciFlO+eACcBnwY+G62XaYYLCT1uD0jqZ/0GNlVEXFPtr9MsSguoZN0IfA/SEFbA1wc\nEf+7qPNZR7kdOBLGsLJ1Z3gGOIr0R/rPgDslndDcJo0vSR8lJfUnR8S7zW5PM0XEiorNdZJWAr8C\nTiddK2XSBayMiGuy7TVZYjsfWNy8ZjXVucA/R8SmZjekCc4A5gKzgfWkL4A3S9qYJfilUkhCVzHA\n4TxgJXAp6SHEwyNia9WxHyE9BN8PHCep8o/3J4G3q0cwdbhDKt7vR0jPEv6BpJ9XHPMJ4NkOjcvl\nwAnAXwKTJU3OyssYC4D/D5gBXE/6Bl6WGJwITAR+kjpsgdSLf4Kki4HPU55Y1PIyaWDEq5QrDq8B\nW6re11vAJ7Kysv2dmET6/PxSST83vgZ8B/gF8CFgA3APcK2kp+mMWDR3LVdJTwBPRsQl2bZIo/du\niYgbqo6dC9zV8EaYmZmZdYYzI+Luegc0vIeuYoDD3w6WRURIyhvg8Mv0n8+THqUDWA7MrHFo2TgO\nQxyLxHFIHIchjkXiOAzplFjU7nA6j2+OqHZ1FP4057hTWJGzB/5y1ZLcfV3TFtUsH1h19qjrAAz8\n+JxhZVs3bOX+P38Q3s+V8hVxy3W0Axx2DFUbvLs2oeL3MnMchjgWieOQOA5DHIvEcRjSKbGondCN\n9J1VR+H3co/M3zN56o9y9+VNEzIwNX+8Rb2pRerV4/1cKV9LTFtiZmZmZmNXRA/dVtIAhwOqyg8A\n6ozCWU7KpwFeAZYAvcCUhjfQzMzMrJWsW/I0Ty/ZaVU/3nnjnRHXb3hCFxHvSvoxaWTeA/D+oIgZ\nwC35NWcy1Dm6BJjT6KaZmZmZtaTeOb9L75zf3amsb/Umvn3Md0ZUv6h56G4EFmWJ3eC0JXsBi0ZW\nvbegZrUbx2GIY5E4DonjMMSxSByHIY4FlC8KhSR0EbFU0n7AdaRbrU8Bp0TEqyN7Bd9mTRyHIY5F\n4jgkjsMQxyJxHIa0Uyzm19lXe1DEfK4b05n2/37Oji3VT4hVGJoHc5iB/itqlnd1Lxx1HYAufXV4\nWX7LhilspYiIuJ0047+ZmZmZFcijXM3MzMzanBM6MzMzszbX8IRO0pWSVkp6U9JmSfdJOrzR5zEz\nMzOzpIgeuunArcCxpEWDdwd+IGnPAs5lZmZmVnpFzEM3q3Jb0tnAFtL6ro82+nxmZmZmZVfYKNcK\n+5LGHr8+DucyMzOzdnFsnSlDcqYtOeBjdarkzzLCnV/4Qs3yL3BnnSbUbgNA1261pyepNzVJPbWa\nXuftDG/PmM46QtkKETcBj0bE+l0db2ZmZmajV3QP3e3AkcDxBZ/HzMzMrLQKS+gk3QbMAqZHRN+u\naywHJlSV9dJeM16bmZmZjd5aYF1V2Y5R1C8kocuSuT8GToyIF0dWayYwuYjmmJmZmbW0KQzvwuoD\n7hhh/YYndJJuB+YApwLbJA0+8fhGRIwm2TQzMzOzESiih24+aWjKv1SVnwP1hpKYmZlZqfz5aMZx\nJto/f1/+mFS4ePutNct/3nNYbp3buCh338B7tUezdnXXHv0KYx8BOxJFzEPn5cTMzMzMxpGTLzMz\nM7M254TOzMzMrM05oTMzMzNrc4UndJKukDQg6caiz2VmZmZWRkUv/fUp4DxgTZHnMTMzMyuzIleK\n2Bv4HjAPuKao85iZmVl76jn71dx9ypmE5NWentw6EfnToLx1/MSa5fsf9NvcOtyTPxFK1261pyfJ\nm84E6k9p0j8wvF7/6k0wbVF++ypfe0RHjc3XgQcj4pECz2FmZmZWekUt/TUbOBqYVsTrm5mZmdmQ\nIpb++ihwE3ByRLw78prLgQlVZb0MX9nMzMzMrLOsW7Kep+9Zv1PZO795Z8T1i+ihOwaYCKyWNHgz\nuxs4QdJFwIciosZN6ZnA5AKaY2ZmZtbaeuccSe+cI3cq61u9iW+P8Bm6IhK6hxjerbYI2AAsrJ3M\nmZmZmdlYFbGW6zZgpz5DSduA1yJiQ6PPZ2ZmZlZ2hU1bUsW9cmZmZraTWT3LcvflTUCyTLNy69RL\nNuKJ62qWX/tknUrfz58GJW96krzpTOrVAejqGl5vNFORjEtCFxEnjcd5zMzMzMrIa7mamZmZtTkn\ndGZmZmZtrpCETtKBkhZL2ippu6Q1kqYWcS4zMzOzsitiYuF9gceAh4FTgK3AYcCvG30uMzMzMytm\nUMQVwIsRMa+i7FcFnMfMzMxaXv7Y01nKH+WaZxn1Rrnmj0rl2L+oWfw3B12bW2VBnalz80azDvTn\nj2Stp1bL67yb4e0Z01nr+xywStJSSZslrZY0b5e1zMzMzGxMikjoDgG+CDwL/BHwDeAWSbVTYzMz\nMzP7QIq45doFrIyIa7LtNZJ6gfnA4gLOZ2ZmZlZqRSR0faR1WyttAD5fv9pyYEJVWS/Dl4U1MzMz\n6yxrgXVVZTtGUb+IhO4x4IiqsiPY5cCImcDkAppjZmZm1tqmMLwLqw+4Y4T1i3iG7mvAZyRdKekT\nkuYC84DbCjiXmZmZWek1vIcuIlZJOg1YCFwDvABcEhH3NPpcZmZm1r5mkT9tSUTtSTsu3n7rmM61\n90Nba5Zv7dk7v5LyJw4ZeK/29CRd3bWnM4GxT2kyEkXcciUilkGd/0tmZmZm1jBey9XMzMyszTmh\nMzMzM2tzDU/oJHVJul7S85K2S3pO0tWNPo+ZmZmZJUWt5Xo+cBawHpgGLJL0m4jwSFczMzOzBisi\noTsOuD8ilmfbL2ZTl3y6gHOZmZlZm5p471u5+yJnafq3tkwc07m+c8HsmuUXK3/U7OHxbO6+rt1q\nj2bNG/0K9UfA9g8Mr9e/ehNMW5RbZ6fXHtFRo/M4MEPSYQCSjgKOx6NezczMzApRRA/dQmAf4BlJ\n/aSk8SrPQ2dmZmZWjCISujOAucBs0jN0RwM3S9oYEYsLOJ+ZmZlZqRWR0N0AfDUi7s22n5Z0MHAl\nUCehWw5MqCrrZfjKZmZmZmadZd2S9Tx9z/qdyt75zTsjrl9EQrcX0F9VNsAun9ebCUwuoDlmZmZm\nra13zpH0zjlyp7K+1Zv49ggHRRSR0D0IXC3pZeBpYCpwKfCtAs5lZmZmVnpFJHQXAdcDXwf2BzYC\n38jKzMzMzADQvfX2Ru3il2pPZ1K3DnDW/rVPds6W/DGbV194Ve6+vOlJ8qYzqVcHoKtreL3RTEXS\n8IQuIrYBf539mJmZmVnBvJarmZmZWZtzQmdmZmbW5pzQmZmZmbW5USd0kqZLekDSK5IGJJ1a45jr\nJG2UtF3SDyUd2pjmmpmZmVm1sfTQ9QBPARdQYziJpMtJI13PAz4NbANWSNrjA7TTzMzMzHKMepRr\nRCwnLeuApFpjhy8Bro+If8qOOQvYDPwJsHRkZ1mLV4gAx6GSY5E4DonjMMSxSByHIe0Ti811pi3J\nn4Bkc51XrKx1H3Da+1tbTs95RdV5vQvyW5E3PclAf/7UJPXUSqjqTdAyrD1jOmsOSR8HJgEPD5ZF\nxJvAk8BxI3+ldY1sVhtzHIY4FonjkDgOQxyLxHEY4lgk/9jsBoyrRg+KmERKj6vT3c3ZPjMzMzNr\nsCJWihij5cCE7PdXgCVAL+3SbWxmZmY2VmsZ3re6YxT1G53QbSLd8j2AnXvpDgB+Ur/qTGBy9vsS\nYE6Dm2ZmZmbWmqYwvAurD7hjhPUbmtBFxAuSNgEzgJ8CSNoHOJa0tmstWbfc1oqiHaS3UXaOwxDH\nInEcEsdhiGOROA5DWi0W+QMLflporTd3Oja3VuS/Xt/qTbn7unIaOFCnTj3dNcoqMqMJNXbvRBH5\nIatZQeoBDiX1xK0mrdn6I+D1iHhJ0mXA5cDZwC+B64HfBX43Iv6zxuvNBe4aVSPMzMzMyuPMiLi7\n3gFjSehOJCVw1RW/GxHnZsd8mTQP3b7AvwMXRsRzOa/3EeAUUvI3mtvFZmZmZp1sAnAwsCIiXqt3\n4KgTOjMzMzNrLV7L1czMzKzNOaEzMzMza3NO6MzMzMzanBM6MzMzszbXUgmdpAslvSDpbUlPSPpU\ns9tUNEnTJT0g6RVJA5JOrXHMdZI2Stou6YeSDm1GW4sk6UpJKyW9KWmzpPskHV7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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Set parameters\n", + "input_dim = 8\n", + "output_dim = 9\n", + "n_per_batch = 128\n", + "epochs = 100\n", + "crop_factor = int(conv_domain/2)\n", + "filters_per_log = 11\n", + "n_convolutions = input_dim*filters_per_log\n", + "\n", + "starting_weights = [np.zeros((conv_domain, 1, input_dim, n_convolutions)), np.ones((n_convolutions))]\n", + "\n", + "norm_factor=float(conv_domain)*2.0\n", + "\n", + "\n", + "for i in range(input_dim):\n", + " for j in range(conv_domain):\n", + " starting_weights[0][j, 0, i, i*filters_per_log+0] = j/norm_factor\n", + " starting_weights[0][j, 0, i, i*filters_per_log+1] = j/norm_factor\n", + " starting_weights[0][j, 0, i, i*filters_per_log+2] = (conv_domain-j)/norm_factor\n", + " starting_weights[0][j, 0, i, i*filters_per_log+3] = (conv_domain-j)/norm_factor\n", + " starting_weights[0][j, 0, i, i*filters_per_log+4] = (2*abs(crop_factor-j))/norm_factor\n", + " starting_weights[0][j, 0, i, i*filters_per_log+5] = (conv_domain-2*abs(crop_factor-j))/norm_factor\n", + " starting_weights[0][j, 0, i, i*filters_per_log+6] = 0.25\n", + " starting_weights[0][j, 0, i, i*filters_per_log+7] = 0.5 if (j%2 == 0) else 0.25\n", + " starting_weights[0][j, 0, i, i*filters_per_log+8] = 0.25 if (j%2 == 0) else 0.5\n", + " starting_weights[0][j, 0, i, i*filters_per_log+9] = 0.5 if (j%4 == 0) else 0.25\n", + " starting_weights[0][j, 0, i, i*filters_per_log+10] = 0.25 if (j%4 == 0) else 0.5\n", + "\n", + "def dnn_model(init_dropout_rate=0.2, main_dropout_rate=0.5,\n", + " hidden_dim_1=32, hidden_dim_2=32, \n", + " max_norm=10, nb_conv=n_convolutions):\n", + " # Define the model\n", + " inputs = Input(shape=(conv_domain,input_dim,))\n", + " inputs_dropout = Dropout(init_dropout_rate)(inputs)\n", + "\n", + " x1 = Convolution1D(nb_conv, conv_domain, border_mode='valid', weights=starting_weights, activation='tanh', input_shape=(conv_domain,input_dim), input_length=input_dim, W_constraint=nonneg())(inputs_dropout)\n", + " x1 = Flatten()(x1) \n", + "\n", + " xn = Cropping1D(cropping=(crop_factor,crop_factor))(inputs_dropout)\n", + " xn = Flatten()(xn)\n", + "\n", + " xA = merge([x1, xn], mode='concat') \n", + " xA = Dropout(main_dropout_rate)(xA)\n", + " xA = Dense(hidden_dim_1, init='uniform', activation='relu', W_constraint=maxnorm(max_norm))(xA)\n", + " \n", + " x = merge([xA, xn], mode='concat') \n", + " x = Dropout(main_dropout_rate)(x)\n", + " x = Dense(hidden_dim_2, init='uniform', activation='relu', W_constraint=maxnorm(max_norm))(x)\n", + " \n", + " predictions = Dense(output_dim, init='uniform', activation='softmax')(x)\n", + " \n", + " model = Model(input=inputs, output=predictions)\n", + " \n", + " optimizerNadam = Nadam(lr=0.002, beta_1=0.9, beta_2=0.999, epsilon=1e-08, schedule_decay=0.004)\n", + " model.compile(loss='categorical_crossentropy', optimizer=optimizerNadam, metrics=['accuracy'])\n", + " return model\n", + "\n", + "# Load the model\n", + "t0 = time.time()\n", + "model_dnn = dnn_model()\n", + "model_dnn.summary()\n", + "t1 = time.time()\n", + "print(\"Load time = %d\" % (t1-t0) )\n", + "\n", + "def plot_weights():\n", + " layerID=2\n", + "\n", + " print(model_dnn.layers[layerID].get_weights()[0].shape)\n", + " print(model_dnn.layers[layerID].get_weights()[1].shape)\n", + "\n", + " fig, ax = plt.subplots(figsize=(12,10))\n", + "\n", + " for i in range(8):\n", + " plt.subplot(911+i)\n", + " plt.imshow(model_dnn.layers[layerID].get_weights()[0][:,0,i,:], interpolation='none')\n", + "\n", + " fig, ax = plt.subplots(figsize=(11,9))\n", + "\n", + " plt.subplot(919)\n", + " plt.imshow(model_dnn.layers[layerID].get_weights()[1].reshape(1,n_convolutions), interpolation='none')\n", + "\n", + " plt.show()\n", + " \n", + "plot_weights()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### We train the CNN and evaluate it on precision/recall." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/100\n", + "0s - loss: 1.8302 - acc: 0.3651\n", + "Epoch 2/100\n", + "0s - loss: 1.3809 - acc: 0.4146\n", + "Epoch 3/100\n", + "0s - loss: 1.2878 - acc: 0.4531\n", + "Epoch 4/100\n", + "0s - loss: 1.2265 - acc: 0.4743\n", + "Epoch 5/100\n", + "0s - loss: 1.2020 - acc: 0.4919\n", + "Epoch 6/100\n", + "0s - loss: 1.1843 - acc: 0.5066\n", + "Epoch 7/100\n", + "0s - loss: 1.1738 - acc: 0.5155\n", + "Epoch 8/100\n", + "0s - loss: 1.1379 - acc: 0.5331\n", + "Epoch 9/100\n", + "0s - loss: 1.1397 - acc: 0.5300\n", + "Epoch 10/100\n", + "0s - loss: 1.1423 - acc: 0.5305\n", + "Epoch 11/100\n", + "0s - loss: 1.1255 - acc: 0.5276\n", + "Epoch 12/100\n", + "0s - loss: 1.1289 - acc: 0.5283\n", + "Epoch 13/100\n", + "0s - loss: 1.1171 - acc: 0.5358\n", + "Epoch 14/100\n", + "0s - loss: 1.1199 - acc: 0.5382\n", + "Epoch 15/100\n", + "0s - loss: 1.1125 - acc: 0.5430\n", + "Epoch 16/100\n", + "0s - loss: 1.0953 - acc: 0.5418\n", + "Epoch 17/100\n", + "0s - loss: 1.0946 - acc: 0.5527\n", + "Epoch 18/100\n", + "0s - loss: 1.0941 - acc: 0.5534\n", + "Epoch 19/100\n", + "0s - loss: 1.0874 - acc: 0.5515\n", + "Epoch 20/100\n", + "0s - loss: 1.0887 - acc: 0.5452\n", + "Epoch 21/100\n", + "0s - loss: 1.0812 - acc: 0.5565\n", + "Epoch 22/100\n", + "0s - loss: 1.0856 - acc: 0.5519\n", + "Epoch 23/100\n", + "0s - loss: 1.0789 - acc: 0.5584\n", + "Epoch 24/100\n", + "0s - loss: 1.0749 - acc: 0.5495\n", + "Epoch 25/100\n", + "0s - loss: 1.0704 - acc: 0.5488\n", + "Epoch 26/100\n", + "0s - loss: 1.0738 - acc: 0.5483\n", + "Epoch 27/100\n", + "0s - loss: 1.0527 - acc: 0.5678\n", + "Epoch 28/100\n", + "0s - loss: 1.0622 - acc: 0.5611\n", + "Epoch 29/100\n", + "0s - loss: 1.0599 - acc: 0.5659\n", + "Epoch 30/100\n", + "0s - loss: 1.0340 - acc: 0.5719\n", + "Epoch 31/100\n", + "0s - loss: 1.0519 - acc: 0.5628\n", + "Epoch 32/100\n", + "0s - loss: 1.0615 - acc: 0.5563\n", + "Epoch 33/100\n", + "0s - loss: 1.0484 - acc: 0.5688\n", + "Epoch 34/100\n", + "0s - loss: 1.0591 - acc: 0.5519\n", + "Epoch 35/100\n", + "0s - loss: 1.0465 - acc: 0.5570\n", + "Epoch 36/100\n", + "0s - loss: 1.0403 - acc: 0.5705\n", + "Epoch 37/100\n", + "0s - loss: 1.0371 - acc: 0.5635\n", + "Epoch 38/100\n", + "0s - loss: 1.0347 - acc: 0.5698\n", + "Epoch 39/100\n", + "0s - loss: 1.0276 - acc: 0.5780\n", + "Epoch 40/100\n", + "0s - loss: 1.0227 - acc: 0.5828\n", + "Epoch 41/100\n", + "0s - loss: 1.0419 - acc: 0.5703\n", + "Epoch 42/100\n", + "0s - loss: 1.0355 - acc: 0.5669\n", + "Epoch 43/100\n", + "0s - loss: 1.0273 - acc: 0.5645\n", + "Epoch 44/100\n", + "0s - loss: 1.0237 - acc: 0.5662\n", + "Epoch 45/100\n", + "0s - loss: 1.0351 - acc: 0.5606\n", + "Epoch 46/100\n", + "0s - loss: 1.0223 - acc: 0.5654\n", + "Epoch 47/100\n", + "0s - loss: 1.0264 - acc: 0.5722\n", + "Epoch 48/100\n", + "0s - loss: 1.0194 - acc: 0.5748\n", + "Epoch 49/100\n", + "0s - loss: 1.0185 - acc: 0.5736\n", + "Epoch 50/100\n", + "0s - loss: 1.0279 - acc: 0.5719\n", + "Epoch 51/100\n", + "0s - loss: 1.0189 - acc: 0.5794\n", + "Epoch 52/100\n", + "0s - loss: 1.0036 - acc: 0.5715\n", + "Epoch 53/100\n", + "0s - loss: 1.0167 - acc: 0.5715\n", + "Epoch 54/100\n", + "0s - loss: 1.0069 - acc: 0.5879\n", + "Epoch 55/100\n", + "0s - loss: 1.0121 - acc: 0.5693\n", + "Epoch 56/100\n", + "0s - loss: 1.0185 - acc: 0.5804\n", + "Epoch 57/100\n", + "0s - loss: 1.0062 - acc: 0.5780\n", + "Epoch 58/100\n", + "0s - loss: 1.0045 - acc: 0.5801\n", + "Epoch 59/100\n", + "0s - loss: 1.0052 - acc: 0.5835\n", + "Epoch 60/100\n", + "0s - loss: 1.0186 - acc: 0.5828\n", + "Epoch 61/100\n", + "0s - loss: 1.0187 - acc: 0.5707\n", + "Epoch 62/100\n", + "0s - loss: 1.0072 - acc: 0.5830\n", + "Epoch 63/100\n", + "0s - loss: 1.0161 - acc: 0.5840\n", + "Epoch 64/100\n", + "0s - loss: 1.0179 - acc: 0.5830\n", + "Epoch 65/100\n", + "0s - loss: 1.0044 - acc: 0.5862\n", + "Epoch 66/100\n", + "0s - loss: 1.0047 - acc: 0.5801\n", + "Epoch 67/100\n", + "0s - loss: 1.0000 - acc: 0.5826\n", + "Epoch 68/100\n", + "0s - loss: 0.9966 - acc: 0.5854\n", + "Epoch 69/100\n", + "0s - loss: 1.0028 - acc: 0.5780\n", + "Epoch 70/100\n", + "0s - loss: 0.9994 - acc: 0.5780\n", + "Epoch 71/100\n", + "0s - loss: 1.0076 - acc: 0.5782\n", + "Epoch 72/100\n", + "0s - loss: 1.0083 - acc: 0.5770\n", + "Epoch 73/100\n", + "0s - loss: 1.0047 - acc: 0.5765\n", + "Epoch 74/100\n", + "0s - loss: 0.9740 - acc: 0.5936\n", + "Epoch 75/100\n", + "0s - loss: 0.9927 - acc: 0.5883\n", + "Epoch 76/100\n", + "0s - loss: 1.0058 - acc: 0.5965\n", + "Epoch 77/100\n", + "0s - loss: 0.9883 - acc: 0.5866\n", + "Epoch 78/100\n", + "0s - loss: 0.9831 - acc: 0.5835\n", + "Epoch 79/100\n", + "0s - loss: 1.0019 - acc: 0.5852\n", + "Epoch 80/100\n", + "0s - loss: 1.0002 - acc: 0.5847\n", + "Epoch 81/100\n", + "0s - loss: 0.9884 - acc: 0.5919\n", + "Epoch 82/100\n", + "0s - loss: 0.9883 - acc: 0.5871\n", + "Epoch 83/100\n", + "0s - loss: 0.9939 - acc: 0.5869\n", + "Epoch 84/100\n", + "0s - loss: 0.9766 - acc: 0.5973\n", + "Epoch 85/100\n", + "0s - loss: 0.9854 - acc: 0.5929\n", + "Epoch 86/100\n", + "0s - loss: 0.9909 - acc: 0.5963\n", + "Epoch 87/100\n", + "0s - loss: 0.9940 - acc: 0.5869\n", + "Epoch 88/100\n", + "0s - loss: 0.9898 - acc: 0.5813\n", + "Epoch 89/100\n", + "0s - loss: 0.9868 - acc: 0.5862\n", + "Epoch 90/100\n", + "0s - loss: 0.9769 - acc: 0.5900\n", + "Epoch 91/100\n", + "0s - loss: 0.9889 - acc: 0.5893\n", + "Epoch 92/100\n", + "0s - loss: 0.9808 - acc: 0.5866\n", + "Epoch 93/100\n", + "0s - loss: 0.9811 - acc: 0.5912\n", + "Epoch 94/100\n", + "0s - loss: 0.9860 - acc: 0.5922\n", + "Epoch 95/100\n", + "0s - loss: 0.9819 - acc: 0.5951\n", + "Epoch 96/100\n", + "0s - loss: 0.9776 - acc: 0.5903\n", + "Epoch 97/100\n", + "0s - loss: 0.9940 - acc: 0.5835\n", + "Epoch 98/100\n", + "0s - loss: 0.9650 - acc: 0.5944\n", + "Epoch 99/100\n", + "0s - loss: 0.9589 - acc: 0.5956\n", + "Epoch 100/100\n", + "0s - loss: 0.9823 - acc: 0.5811\n", + "Train time = 28 seconds\n", + "Test time = 1 seconds\n", + "\n", + "Model Report\n", + "-Accuracy: 0.672933\n", + "-Adjacent Accuracy: 0.935406\n", + "\n", + "Confusion Matrix\n", + " Pred SS CSiS FSiS SiSh MS WS D PS BS Total\n", + " True\n", + " SS 206 53 9 268\n", + " CSiS 86 581 273 940\n", + " FSiS 4 129 639 1 1 6 780\n", + " SiSh 3 3 213 50 2 271\n", + " MS 5 9 55 21 145 2 59 296\n", + " WS 2 49 8 413 11 93 6 582\n", + " D 1 7 7 4 97 25 141\n", + " PS 1 9 14 5 150 3 478 26 686\n", + " BS 2 1 1 1 8 28 144 185\n", + "\n", + "Precision 0.70 0.75 0.68 0.63 0.50 0.54 0.86 0.69 0.82 0.67\n", + " Recall 0.77 0.62 0.82 0.79 0.07 0.71 0.69 0.70 0.78 0.67\n", + " F1 0.73 0.68 0.74 0.70 0.12 0.61 0.76 0.69 0.80 0.66\n" + ] + } + ], + "source": [ + "#Train model\n", + "t0 = time.time()\n", + "model_dnn.fit(X_train, y_train, batch_size=n_per_batch, nb_epoch=epochs, verbose=2)\n", + "t1 = time.time()\n", + "print(\"Train time = %d seconds\" % (t1-t0) )\n", + "\n", + "\n", + "# Predict Values on Training set\n", + "t0 = time.time()\n", + "y_predicted = model_dnn.predict( X_train , batch_size=n_per_batch, verbose=2)\n", + "t1 = time.time()\n", + "print(\"Test time = %d seconds\" % (t1-t0) )\n", + "\n", + "# Print Report\n", + "\n", + "# Format output [0 - 8 ]\n", + "y_ = np.zeros((len(y_train),1))\n", + "for i in range(len(y_train)):\n", + " y_[i] = np.argmax(y_train[i])\n", + "\n", + "y_predicted_ = np.zeros((len(y_predicted), 1))\n", + "for i in range(len(y_predicted)):\n", + " y_predicted_[i] = np.argmax( y_predicted[i] )\n", + " \n", + "# Confusion Matrix\n", + "conf = confusion_matrix(y_, y_predicted_)\n", + "\n", + "def accuracy(conf):\n", + " total_correct = 0.\n", + " nb_classes = conf.shape[0]\n", + " for i in np.arange(0,nb_classes):\n", + " total_correct += conf[i][i]\n", + " acc = total_correct/sum(sum(conf))\n", + " return acc\n", + "\n", + "adjacent_facies = np.array([[1], [0,2], [1], [4], [3,5], [4,6,7], [5,7], [5,6,8], [6,7]])\n", + "facies_labels = ['SS', 'CSiS', 'FSiS', 'SiSh', 'MS','WS', 'D','PS', 'BS']\n", + "\n", + "def accuracy_adjacent(conf, adjacent_facies):\n", + " nb_classes = conf.shape[0]\n", + " total_correct = 0.\n", + " for i in np.arange(0,nb_classes):\n", + " total_correct += conf[i][i]\n", + " for j in adjacent_facies[i]:\n", + " total_correct += conf[i][j]\n", + " return total_correct / sum(sum(conf))\n", + "\n", + "# Print Results\n", + "print (\"\\nModel Report\")\n", + "print (\"-Accuracy: %.6f\" % ( accuracy(conf) ))\n", + "print (\"-Adjacent Accuracy: %.6f\" % ( accuracy_adjacent(conf, adjacent_facies) ))\n", + "print (\"\\nConfusion Matrix\")\n", + "display_cm(conf, facies_labels, display_metrics=True, hide_zeros=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### We display the learned 1D convolution kernels" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(11, 1, 8, 88)\n", + "(88,)\n" + ] + }, + { + "data": { + "image/png": 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dq/rrlPfFcUF5Vzny+hidFaXZgQ8R/+j8fU7J8rqo7tE86IllChzq/A3Z+ttF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BPW52uByQtReY5y+eC6mR0U17tPsbz/nr7NesEcZPlNWsua34d3gzrkKGMN3cPAUDNbH8DMtgR2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\nqZ31V/YnfldCCCGEEKJ7MnKP7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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_weights()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### In order to avoid overfitting, we evaluate our model by running a 5-fold stratified cross-validation routine." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cross Validation time = 106\n", + " Cross Validation Results\n", + "[ 0.5626506 0.52650602 0.53373494 0.50361446 0.49577805]\n", + "0.524456814166\n" + ] + } + ], + "source": [ + "# Cross Validation\n", + "def cross_validate():\n", + " t0 = time.time()\n", + " estimator = KerasClassifier(build_fn=dnn_model, nb_epoch=epochs, batch_size=n_per_batch, verbose=0)\n", + " skf = StratifiedKFold(n_splits=5, shuffle=True)\n", + " results_dnn = cross_val_score(estimator, X_train, y_train, cv= skf.get_n_splits(X_train, y_train))\n", + " t1 = time.time()\n", + " print(\"Cross Validation time = %d\" % (t1-t0) )\n", + " print(' Cross Validation Results')\n", + " print( results_dnn )\n", + " print(np.mean(results_dnn))\n", + "\n", + "cross_validate()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Prediction\n", + "---\n", + "To predict the STUART and CRAWFORD blind wells we do the following:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false + }, + "source": [ + "#### Set up a plotting function to display the logs & facies." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# 1=sandstone 2=c_siltstone 3=f_siltstone \n", + "# 4=marine_silt_shale 5=mudstone 6=wackestone 7=dolomite\n", + "# 8=packstone 9=bafflestone\n", + "facies_colors = ['#F4D03F', '#F5B041','#DC7633','#6E2C00', '#1B4F72','#2E86C1', '#AED6F1', '#A569BD', '#196F3D']\n", + "\n", + "#facies_color_map is a dictionary that maps facies labels\n", + "#to their respective colors\n", + "facies_color_map = {}\n", + "for ind, label in enumerate(facies_labels):\n", + " facies_color_map[label] = facies_colors[ind]\n", + "\n", + "def label_facies(row, labels):\n", + " return labels[ row['Facies'] -1]\n", + "\n", + "def make_facies_log_plot(logs, facies_colors):\n", + " #make sure logs are sorted by depth\n", + " logs = logs.sort_values(by='Depth')\n", + " cmap_facies = colors.ListedColormap(\n", + " facies_colors[0:len(facies_colors)], 'indexed')\n", + " \n", + " ztop=logs.Depth.min(); zbot=logs.Depth.max()\n", + " \n", + " cluster=np.repeat(np.expand_dims(logs['Facies'].values,1), 100, 1)\n", + " \n", + " f, ax = plt.subplots(nrows=1, ncols=6, figsize=(8, 12))\n", + " ax[0].plot(logs.GR, logs.Depth, '-g')\n", + " ax[1].plot(logs.ILD_log10, logs.Depth, '-')\n", + " ax[2].plot(logs.DeltaPHI, logs.Depth, '-', color='0.5')\n", + " ax[3].plot(logs.PHIND, logs.Depth, '-', color='r')\n", + " ax[4].plot(logs.PE, logs.Depth, '-', color='black')\n", + " im=ax[5].imshow(cluster, interpolation='none', aspect='auto',\n", + " cmap=cmap_facies,vmin=1,vmax=9)\n", + " \n", + " divider = make_axes_locatable(ax[5])\n", + " cax = divider.append_axes(\"right\", size=\"20%\", pad=0.05)\n", + " cbar=plt.colorbar(im, cax=cax)\n", + " cbar.set_label((17*' ').join([' SS ', 'CSiS', 'FSiS', \n", + " 'SiSh', ' MS ', ' WS ', ' D ', \n", + " ' PS ', ' BS ']))\n", + " cbar.set_ticks(range(0,1)); cbar.set_ticklabels('')\n", + " \n", + " for i in range(len(ax)-1):\n", + " ax[i].set_ylim(ztop,zbot)\n", + " ax[i].invert_yaxis()\n", + " ax[i].grid()\n", + " ax[i].locator_params(axis='x', nbins=3)\n", + " \n", + " ax[0].set_xlabel(\"GR\")\n", + " ax[0].set_xlim(logs.GR.min(),logs.GR.max())\n", + " ax[1].set_xlabel(\"ILD_log10\")\n", + " ax[1].set_xlim(logs.ILD_log10.min(),logs.ILD_log10.max())\n", + " ax[2].set_xlabel(\"DeltaPHI\")\n", + " ax[2].set_xlim(logs.DeltaPHI.min(),logs.DeltaPHI.max())\n", + " ax[3].set_xlabel(\"PHIND\")\n", + " ax[3].set_xlim(logs.PHIND.min(),logs.PHIND.max())\n", + " ax[4].set_xlabel(\"PE\")\n", + " ax[4].set_xlim(logs.PE.min(),logs.PE.max())\n", + " ax[5].set_xlabel('Facies')\n", + " \n", + " ax[1].set_yticklabels([]); ax[2].set_yticklabels([]); ax[3].set_yticklabels([])\n", + " ax[4].set_yticklabels([]); ax[5].set_yticklabels([])\n", + " ax[5].set_xticklabels([])\n", + " f.suptitle('Well: %s'%logs.iloc[0]['Well Name'], fontsize=14,y=0.94)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Run the model on the blind data\n", + " - Output a CSV\n", + " - Plot the wells in the notebook" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "collapsed": false, + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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6MLKccaZYM+udd2DZMjhwACIi4Jtv7Ls/K+bQLI7O5Y0bN9ixYwdff/01R48epVOnTlSq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VvECLC3N/zwg6ib/Qb04oFedGhBrly5+Pzzz5k1a1aGs5xYi2/Wch0S7ZD36zNIlcJVmBk8k1+C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Z07LZqPpKXnhRqULl2aKlWqcPr0aaMeZy++2ct5SNRDBr5GYjAY+KDmB7g6udJrTS8K5C7A\nmPpj1JaVoyldWixw27wZvvhCXFUNCIDhw+GNN9QrbSaxX27cuMHBgwe5ePEiMTExgGgr6+vrS0BA\nAL6+vnh5eeGQU1dczpwJv/8ueoXLJHyLkpCQwKFDh+jYsaPaUiQSXSIDXxPpWb0ncUlxDNs0jJrF\natK8XHO1JeVoDAZ49VWx7dwpAuAOHeDzz+GTT+Dtt8HZWW2VEj2TkpLC8ePHOXDgANHR0eTJk4dy\n5coRGhqKr68vHh4eWV79yRGkp8OoUTB6NPTuDW++qbYiu+Pbb79FURSaN5efORKJKcjA1wz+F/I/\nwi+H02VFF06+fxIvdy+1JUmA0FBR03ffPhg7VuQCjxwJa9eKBXESibHs37+fTZs2kZycTOnSpWnf\nvj3lypXDUV5O+BdFgc6dYf58+OorsahNYlGOHz/O119/zeDBgylZsqTaciQSXZJDr8NZBoPBwMwW\nM4lPimfDuQ3PvE/Lli1trMp09KQ1O7z0kqiidOQIxMeLtTXWxt48VBMtefn++++TnJxM79696dSp\nExUrVsxxQe9zx2PxYggLg99+g48/Fpdh1NBhp+zevZs6depQtmxZhg8fbvTj7cU3ezkPiXrIwNdM\nvPN4U65gOfZe2fvM2/tZoHyPrdCTVmMIDBT1fm/dsv6x7NVDNdCSl++//z4AZ86cUVmJemQ5Hqmp\nMHgw1K8v8orU0mGnrFy5kgYNGuDv78+2bdvImzev0fuwF9/s5Twk6iEDXwvg5uxGSnrKM29r1KiR\njdWYjp60GouiWG0C6gns2UNbo7aXiqJw/vx5wsLCuHjxIm5ubhQqVEhVTWqS5XgoCpQvD1u2wIcf\nmt2W2GQddkZaWhrDhw+ndevWNG3alI0bN1KgQAGT9mUvvtnLeUjUQ+b4momiKJyNO0uHgA5qS5Fk\ngqJAbCyY+HkhyYFcu3aN5cuXExMTQ5EiRWjVqhUBAQE4Ocm3zGfi7Ax//gk//CBWk65fD1OnQr16\naivTLbGxsbz99tts2rSJcePGMXToULl4UiKxAPJd3EwMBgMVC1dkxakVDK0t35i0yKpVIsc3NFRt\nJRI9EBUVxfz58/H09KRr1674+vrK13V2cHAQ6Q6NG0PPnvDKK9CuHXz7Lfj5qa1OVxw4cIA2bdqQ\nmJjIxo0befXVV9WWlOOIPZLAtRsqd0TSELHXE9WWYDFkqoMFGNdgHLujdxN2NOw/t61YsUIFRaah\nJ63Z5fx5sbi8Xj2oW9f6x7NHD9XC0l4qisKDBw+Ij4/n8uXLnD59moMHD7Jjxw42bNjA8uXL+e23\n35g3bx5FihShS5cu+Pn5YTAY5LhixHhUqgTh4TBvnvhZoQI0aCByfwcMELUGp0+H5ctF7cEzZ0QC\nfjbbLtrzWCQmJvLll18SEhKCt7c3Bw4csFjQay++2ct5SNRDzvhagPol69PxxY70XtObAK8AqhSp\n8s9tCxYsoHXr1iqqyz560vo80tLgxx/FVVdvb5g0yTbHtScP1eZ5XmYEsgkJCSQmJpKQkPDE78/6\nmZaW9p/9uLq64ubmhru7O+7u7gQHB1OnTh2cHyv8LMfVSA8MBujUCVq1EukPR4/CtWsQGQk3b4p2\nxulPtXx3doZChaBwYfDyevLnY78vmD6d1vXqgYeHbRL3bUBqaiq//PILI0eOJCYmhn79+vHll1+S\nO3duix3DXp7D9nIe9kShyu74lM7+gsvr59V93crA10JMbzGdEzEnaL2wNec+OIeTg7B20aJFKivL\nPnrSmhVbtsCwYbB3L/TvL2r55sljm2Pbi4da4FlepqenExYWRkxMDAkJCaQ/HTwhAtmMINbNzY0C\nBQo88ffTP7PTXU2Oq4ke5M0LI0b89//T0kT+UUyM2G7efPJnTAxcvSpqEWYEyo9mhBeBSNh3dv43\nIC5eHHx9/7v5+Gi+dWNaWhovvfQShw8fpkOHDowZM4bSpUtb/Dj28hy2l/OQqIcMfC3Ew7SHxCXF\nUSxfMRwN2n6jtVd27hSfsVu3QlAQbN8u83rtjYcPH3LhwgUqVaqEr6/vE0Gsu7s7rq6uObdNsJ5w\ndPx3Jjc7ZATKjwfGGb9fvw6XL8O2beLnnTtPHqdo0WcHxb6+ImBWeebYwcGB1NRUatasSVhYmMwn\nl0isjAx8zURRFDae38jIbSO5k3yHbV23yTcuG6Mo0KMHzJ4NlSvDypXQooXdXAWVPEbGa+vWrVvk\ny5cPFxcXcuXKRf78+XFxcVFZncRqGBMo37kjAuCoqP9uu3ZBdLSoO5xB3ryiFFujRtC0KQQHgw2r\ndxgMBsaNG0ezZs0YPnw4n376KW5ubjY7vkSS05CBr4kkpSTxW+Rv/LDnB07EnKBqkaqseGsFJfKX\nUFtajmPpUhH0Tp0KvXuLxeUS+8TFxYUGDRrwf/buPL6G6//j+GsS2ZAIsSZBlAhiTe1L7VuRtpYf\naqcopUqLVrWl32qLLlq0SlGq9pYqaqutKFq7oGIXS2JNSMg6vz+GNEgiubn3npm55/l45CG5dzLz\nns80zSf3njnnwoULnDhxgr/++iv1ufz581O4cGEKFSpE4cKFKVy4MD4+PnIKMkeTL5/2UbFi+s8n\nJ2uvEqdtiA8e1G64+/hj7XubN9ea4Fat7BK5devWvP/++3z66acsWLCASZMm0blzZ/kiiiTZgGwR\nsiE5JZnNZzczaPUgin9ZnIGrBxJYIJCtvbayb8A+GgU0euJ7+vTpY/+gFjJS1odUFd54QxvK16yZ\n+KbXiDXUq/RqqSgK9erVo2vXrrz++uu88847vPLKK4SGhlKuXDmSkpI4ePAgv/zyCzNmzODjjz9m\nzZo1NsniaPRSgxzneDj8oU4d6NwZRo7Ullq+ehX27NFmnti6Ffr107abMMEquTOjKArjx48nLCyM\nkJAQunbtSpMmTbhw4YLVjqGX65dTZjkPSRzZ+D5FckoyW85uYfCawfh+4UvT+U1Ze2otfar24eTQ\nk6zsspKGAQ0z/MvcSKvMGClrWsOHa+9cBgVBaKh2c1sWZ0ayOqPWUI+yUktXV1f8/PwICAjAx8cH\nNze31JkbXFxcKFOmDGXKlLFLFrPTSw1skuPiRZg3D778Unvr6Pp1yJMH2rSBBg2sf7wMlClThpUr\nV7JhwwZOnz5N5cqVrXYzl16uX06Z5TwkceR7gI9JUVM4EnmE7ee3s/3Cdrae28r1uOuUyFeCHpV7\n8H/B/0cN3xpZfguqa1fjrOhmpKwPKYq2Quprr8HChdrvrSZNICBAu8GtWrX/PooWtX0eI9ZQr55W\ny7i4OA4dOsT+/fu5fv06iqLg5+dHjRo1eOaZZ/D398fZSnf0y+uqnxpkKYeqwp076d8M9/hjUVHa\nDBKKAjVqaOOlWrTQxvq6usL+/bY/qcc0b96cQ4cO8eqrr9KlSxfGjRtH2bJlCQwMfOTDz88vyzdz\n6uX65ZRZzkMSx+Eb38TkRA5cPaA1uue38+eFP7l9/zauzq7U9KvJgJABhAaFUtOvphxvpWPu7tC3\nL/TpA3/8AWvWwIEDMGnSfzd5Fyv2aCNcrRqUKiVvgjMSVVW5cOEC+/bt49ixY6iqSvny5WnSpAml\nSpWy6rynko5k1shm9HlCwpP78fF5dF7gZ57RPq9UCZo2hQIF7H9uGcifPz+LFy+mS5cubNmyhfDw\ncFauXMm5c+dS39Xw8PCgdOnSTzTEgYGBFCtWTP7OyoGjca8TeydQdAzdOBsXDgwSHcMqHLLxvRRz\nibXha1l7ai2bzmzibsJdPHJ5ULd4XYbXHs5zJZ+jll8tPFw8REeVsklRtLG+zZppX6sqnD2rNcEP\nP+bM0ebSB+0+lqpVH22Gy5e3603dUjasW7eOvXv3Atq4yODgYIoVK0ZycjJRUVF4eXnh6elptVd6\nJRtQVYiL04YT3Lih/Zv24/HHHn4dH//kvjJqZNNZ+AIfH8P9YCuKwksvvcRLL72U+lhCQgLnzp0j\nPDz8kY+lS5dy/vx51AfjvPLkyUNAQAAlS5YkICAg9ePh14UKFZKNseSQjPV/AQslpySz59Ie1pxc\nw5rwNRyKPIST4kQd/zq8U/8dGgc05lnfZ3F1tv50SDt27KC+QSaTNVLWrFIU7XfhM89Ahw7/PX71\n6qPN8G+/aQtMAbi5aS8APWyEQ0K0r7Myw5AZayhKerWsUqUK7u7uxMTEcOfOHSIjIzl58iQJj726\nlzdvXry8vNL9yJcvX7abY3ldM6lBXFzWGti0j92//+R+3N21ldsefhQqpP0VmvbrQoXYERFB/ZYt\nDdnIWoOrqytly5albNmyTzwXHx/PmTNnCA8P59SpU5w7d47z58+zY8cO5s6dy71791K39fDwyLQx\nLlKkiC4bY/v+LOrv/KWcM/X/NWLiY5jxzwym7J7ClbtX8PHwoXVga0bXG03LMi0p4GH7t7UmTZpk\nmF+YRsqaU0WLarMVtW7932PR0dpCUQ+b4T17YO5c7cY5FxeYPx+6dMl8v45UQ1tLr5a+vr74+vo+\nsW18fDwxMTHExMQQHR2d+vmdO3c4e/YsMTExxKd5xVBRFLp3784zzzxjcRZHk1qDixdh0ybt448/\nIDLyyY1dXbVGtWBBrUEtWFC7+/RhE/vwsbRf586dpXFHk0JDqd+zpw3O0Pjc3NwoX7485cuXf+K5\n0NBQ5s2bx/nz5zl37twjH7t372bx4sXcvn07dXtPT08aNGhAkyZNaNy4MVWqVNHFOynyZ1HKKVM2\nvlGxUXy1+yum/z2duMQ4elXpRd9qfanpVxNnJ/v+4C5evNiux8sJI2W1hXz54LnntI+H7t+Ho0e1\nscJ9+kBgIDz7bMb7cPQaWlN2aunm5kahQoUo9NgCB6qqcvXqVY4cOcKhQ4eIi4vD29ubihUr4ufn\nZ5MspnP7NmzZwuKiRbXm9eRJrUF99lnthyI4+MkmN08emw2ed+hrkQOLFy9OXcK7atWq6W4THR2d\n2hgfPXqUrVu38t5773Hv3j28vb1p2LBhaiMcHBwsZJVEef2lnDJd47snYg8N1zdEVVVerf4qw2sP\nx88r67/grM1IK/AYKau9uLtrs0N88IG2Ityrr8Lff2e8vayh9VhSS1VVuXHjBufPn0/9iImJIXfu\n3AQHB1OpUiX8/f2z/Rauw17XjRu1ZRDj48ldpow2eP7jj6FxY2E3gjnstcihrNQtX758VK5cmcqV\nKxMaGsqYMWOIj49n7969bN68mS1btjBy5EgSEhJo3749y5cvt/twCHn9pZwyXeM7bN0wmtVrxoL2\nC+wylEEyt3v3YOJE+PRTbXjE//4nOpGUlqqqXLt2jXPnznHhwgXOnz/P3bt3URSFYsWKERwczDPP\nPEOpUqV08TatoVy8CF27am+BzJypzREoORw3NzcaNGhAgwYN+OCDD7h37x4//vgjAwcO5JdffqFD\n2psnJMkATNf41i9RnxWdV+CWy010FMnAYmPh++9h8mRtdqSRI2HMGO0dXEkfzp07x4YNG7hy5QpO\nTk74+vpSpUoVAgICKF68OG5u8v8BOfLaa9p/8AsXasMXJAntprgBAwawevVq+vTpw+HDhxk2bBgF\ndDQVnCRlxnQrtw2qPkhXTe/IkSNFR8gyI2W1ldu3tRVKAwK0hTGaNtXG+E6YkLWmV9bQejKq5Y0b\nN1iyZAnz5s3DycmJl19+mdGjR9OvXz+aNWtGmTJlrN70Otx1vXYN1q6Ft99ObXr1UgO95DAaa9ft\nhx9+4JVXXmHy5MmULFmSt99+m6ioKKseIz3y+ks5ZbpXfF2cXERHeESJEiVER8gyI2W1tqgobTqz\n6dO16UL79dNe5c3uu7uOXENrS6+WsbGxzJw5E3d3d9q3b0/FihXtMsbQ4a7rn39CcrI2lvcBvdRA\nLzmMxpp1i4+P59y5cwQHB9OuXTuWLl3KxIkTWbt2LYcPH7bacdIjr7+UU6ZrfH/991debPKi6Bip\nhg4dKjpClhkpq7VcvAiffQazZoGzMwwaBCNGWL68sSPW0FbSq2VYWBhJSUkMGDCAPHYcd+Jw17VB\nA8ibV5vPb+JEQD810EsOo7G0bnfu3OHw4cMcOHCA/fv3c+DAAcLCwkhMTERRFIKCgujatSvVqlWj\nRYsWVk79JHn9pZwyXeO7JGwJw64Oo2rR9KdrkSTQZmSaOBF+/FH7/T56NAwdqqsVS6U0rly5wj//\n/MORI0cIDAy0a9PrkAoVgjfegE8+0d4OGTNGm8tPMq2kpCROnjzJkSNHHvk4e/YsoC2cUbFiRZ59\n9lleeeUVqlWrRuXKlcmbN6/g5JKUPaZrfAO8A2i1oBU7++6kdIHSouNIOnP4sDYb07Jl2kqmn3wC\nAwaAp6foZNLjEhMTOXLkCPv27ePy5ct4enpSt25datasKTqaY3j/fe0vwcmTtdVbOneGsWOhQgXR\nyaQcio6OZvfu3Rw+fDi1wT1+/HjqIi/FihWjcuXKdOjQgUqVKlGlShXKly+Pq6v1VzeVJHszXeM7\ntfVUBuwbwIgNI/i1y6+i43DixAnKlSsnOkaWGCmrJe7c0ebc9/fXxvL27q3N02tNZq+hPc2ePZvI\nyEgCAwPp0qULgYGBQibMBwe9ri4uMHy4Nv5n7lxO/O9/lPv9d22lNoENkENeCytIW7d27drx559/\nkidPHipWrEiNGjXo27cvlSpVolKlSvj4+AhOmzF5/aWcMt2sDvk98lPHvw4x8TGiowAwatQo0RGy\nzEhZLXH/vrb88JQp2kIU1m56wfw1tKfZs2dTsmRJXn75ZYKCgoQ1veDg19XdHQYNYlSxYtq0J4mJ\nQuM49LXIgbR1i46Opl+/fsTExLB7925mzpzJ0KFDadSoka6bXpDXX8o50zW+APnc8nHgygHWnVon\nOgrTpk0THSHLjJQ1u+LitNXXALy9bXccM9fQnqKjo2nTpo1u5uKV1xWmvfqq9snFi2JzyGthkS++\n+IJffvmFNm3acPToUXx8fIT+MWkpef2lnDLef/VZ8GHjD6lbvC6tf2rNu3+8S3JKsrAsRpp6xUhZ\ns2PvXqhWTbtB/UMD09wAACAASURBVOuvtYWobMWsNbSnGzduMHfuXLy9vWnZsqXoOIC8rgAlevQA\nX1/46COxOeS1yJYzZ84wcuRI6tWrR4cOHbh+/TrffvstHzx8JcBg5PWXcsp0Y3wBfHL7sPrl1Uzc\nMZGxW8aS2yU37z73ruhYkgA3bmiLUJQvDwcPQlCQ6ETS0+zatYvo6GgCAwNTb7aRdMDdHRo1gp9/\nhnnztPn/JF27e/cutWvXJjk5mR49etCvXz8qVaokOpYkCZWtV3wVRXlVUZRDiqJEP/jYpShKq8e2\n+VBRlMuKosQpirJRUZQyjz3vpijKdEVRriuKckdRlOWKohR+bJv8iqL89OAYtxRF+V5RlGzNX+Sk\nOPFOg3d4s86bTPhzAudun8vOt0smMXWqNg//mjWy6TWK5s2b06xZMyIjI5k5cyZz587l+PHjqKoq\nOppj++UXbfniCRNk02sQs2bN4tatW+zfv58pU6bIpleSyP5Qh4vAaCAEeBbYDPyqKEp5AEVRRgND\ngAFATSAWWK8oStpbgKcAbYAOwHOAL/DzY8dZCJQHmj7Y9jngu2xmBeD9hu/j6ebJtL1ixgVNfDD5\nuxEYKWtWrV8P9epp05LagxlraG/u7u7Uq1eP+Ph4OnbsiKqqLF26lBkzZghrgB3+usbHM7FnT3jp\nJW2mB4Ec/lpkUUREBBMmTKB79+6ULFnSNHUzy3lI4mRrqIOqqmsee2isoiiDgNrAcWAY8D9VVVcD\nKIrSE4gEXgSWKoriBfQFuqiquu3BNn2A44qi1FRVde+DJrol8KyqqgcebDMUWKMoyluqql7NTua8\nrnmpV7weB68ezM63WU1cXJyQ41rCSFmzqkcPbWGK48e14Q62ZsYainLv3j2Cg4MJDg7m4sWLbN26\nlaVLl1KsWDGaNm1K6dL2m6fb4a/rkiXExcZqE1/bYYnozDj8tciCpKQkunXrhoeHB5999hlgnrqZ\n5TwkcSy+uU1RFCdFUboAuYFdiqKUAooCfzzcRlXVGGAPUOfBQ9XRmu202/wLXEizTW3g1sOm94FN\ngArUsiRrYIFAztw6Y8m35tj48eOFHNcSRsqaVf36afP2DhsG9nih0Iw1FCVtLYsXL06PHj3o1asX\n9+7dY/ny5cKyOKRduxhfuDAEBIhOIq9FFpw6dYrt27cTEhKC54PVecxSN7OchyROthtfRVEqKopy\nB4gHvgFeetC8FkVrTiMf+5bIB88BFAESHjTEGW1TFIhK+6SqqsnAzTTbZEtiSiLuuWwwaauke25u\nMHMmbNyo/SsZW4ECBYiNjSUkJER0FMcyZIh2p+jnn4tOImVBuXLlmDdvHuvWraN58+ZcvZqtN0ol\nydQsecX3BFAFbQzvt8B8RVF0s4zK888/T2hoaOpH67at+WbgN7iGP7rS0IYNGwgNDX3i+1977TVm\nz579yGP79+8nNDSU69evP/L4Bx988MR4owsXLhAaGsqJEyceeXzq1KmMHDnykcfi4uIIDQ1lx44d\njzy+aNEi+vTp80S2zp07s3LlSrucx9SpUylatChNmjRJreVwK47te/w6hYaGUqdOHZuc365dH1C6\n9EQWLPjvMXmdss6e1yqjn6nWrVsza9Yspk2bhouLC/Xr1zfUtVq0aBHNmzd/5FoZ6joVLQojRmhL\nFr/9Nh+MHWvK//cZ/jqlOb+ePXvSrVs39u3bR5kyZRg7diy3b982xXV6mNfW/++TzEnJ6Y0iiqJs\nBE4Bk4DTQFVVVQ+neX4rcEBV1eGKojRGG7aQP+2rvoqinAO+VFX1qwdjfj9TVdUnzfPOwH2go6qq\n6a5DrChKCLBv3759qa8GJack02ZhG/Ze2sueV/YQ6BOYo3O1xPXr1ylYsKDdj2uJp2Xdv38/zz77\nLGjjr/dbcoz0rpOt3b8PRYtqwx1s/S6ZHq63Na4TiLlWaV2/fp1cuXKxbds2Dh8+jKurKzVr1qRm\nzZrkyZOtSV6sksXa19Vo1+l6VBQFf/gB3n0XQkJgyRIhQx/s/TNmtOv0uJs3bzJ58mSmTJmCh4cH\no0ePZtiwYbjbYulKO8js+lvzd9RHHb+lVKGylgc1mbPXTjJ2+SBIU9uHtdrxeXWqlfbM8r4OnL5D\n/Tf/eWRf9mSNBSycADdVVc8CV9FmYgDgwc1stYBdDx7aByQ9tk0QUAL468FDfwHeiqJUS3OMpoCC\nNl44y9adWsf60+tZ1GGRkKYXoG/fvkKOawkjZc2qqCho1QpiY+Hll21/PDPWUJSePXvyww8/cOrU\nKZo1a8bw4cNp3Lix3ZtekNcVoO8rr8CoUbBjB1y7BrVrw367/86S1yKbChQowCeffEKDBg14+eWX\nGTt2LFWqVGHr1q2io1lEXn8pp7I7j+/HiqI0UBSl5IOxvp8ADYGHbyJPQZvpoZ2iKJWA+UAE8Cuk\n3uw2G/hCUZRGiqI8C8wBdqqquvfBNieA9cAsRVFqKIpSD5gKLMrujA4rT6wksEAgLUq3yM63WdW4\nceOEHTu7jJQ1K/bvh+rVtRkdNm+2zzy+ZquhKAkJCVStWpWUlBT69+9PnTp1cHV1ffo32oi8rmlq\nUKsW7NkDJUpAw4awaZOYHFK2fPrpp0ybNo1Dhw5RqFAhGjduTN++fQ03S4K8/lJOZfcV38LAPLRx\nvpvQ5vJtoarqZgBVVSehNanfob066wG0VlU1Ic0+hgOrgeXAVuAy2py+ab2c5hirge3AwGxmZefF\nnTR/pjmKwOl3jHQTjpGyPs26ddrSxEWLwr590KCBfY5rphqKFBYWhpubG926dcPLy0t0HHldeawG\nhQppf03Wrw/t2sH27WJySFn2sG4VKlRg+/btDB06lLlz5/L3338LTpY98vpLOZXdeXxfycI244Bx\nmTwfDwx98JHRNreB7tnJlp4b925QNK9FE0FIBvbTT9C7tzbEYckSyJ1bdCIpuyIjIylQoABFihQR\nHUXKSN68sGIFtG2rfWzfDlWrik4lZUFSUhLr16+nYcOGPPfcc6LjSJJdWWOMr27FJsSS1zWv6BiS\nHR06BH36QPfu2u9k2fQa07lz5/D19RUdQ3oad3dtKeP4eO0HTjKEffv2cfLkSSZMmCD0HVFJSo+i\nKHUURWn72GM9FUU5qyhKlKIoMxVFcbN0/6ZufJ0UJ1LUFKEZHp+uRc+MlDU9iYnaK73lysGMGZAr\nW+9nWIfRa6gHUVFRREZGcvz4cdFRUsnrmkkNDh6EhARo2VJsDilTaesWHh4OQIkSJUTFsZi8/g7h\nfSD44RcP7hmbjTb89VOgHfCOpTs3dePr7e5NZOzj62nY134Bdz1bykhZ0/Prr9rv4NmztYUrRDB6\nDfXgyJEjuLu7c/nyZdFRUsnrmkkNNm2CwoW1WR5E5pAy9eeff/LZZ59RuXJlevXqRfHixSlUqJDo\nWNkmr79DqEqaFX6BLsAeVVX7q6r6BfA68H+W7tzUjW9Nv5rsjtgtNMP06dOFHj87jJQ1PfPmaTec\n16ghLoPRayiaqqocOXKEChUq8M0334iOk0pe10xqcOQIVKkCTvb5dSKvRfbs2rWLVq1a8eOPPzJ2\n7FjKly/P6tWrOX36tCHn8pXX3yHk59FVgBsCv6f5+m+guKU7N3XjW7VoVU5cP/H0DSVT2LsXWrcW\nnULKiZSUFGJjY/H29hYdRcqKa9e09cDr1hWdRMrAxIkTCQsLY8aMGVy9epUlS5bQpk0bXFxcREeT\npIxEAqUAFEVxBUKAtK9iegKJlu7c1I1vAY8C3Lp/i5yuTicZh/x/ubE5OztTtmxZwsLCREeRsmLi\nRO2V3qEZTtIjCRYbG0u9evXo37+//INSMoq1wKeKojQAPgHigD/TPF8ZbaVgi5i68fX38icpJYlL\ndy6JjiLZQbFicOCA6BRSTpUvX57IyEjDTazvcFQVfvwR+vcHH5+nby8J8XBqQEkykPfQVvndBvQH\n+j+2HkRfYIOlOzd141vdtzoAey/tFZYhNDRU2LGzy0hZ09OvH6xcCWfOiMtg9BrqwcMbbvRUSz1l\nEeWJGhw79t+a4CJzSBlKSkri33//pUKFCqapm1nOQ8qYqqrXVVV9Dm2sb35VVR+fK7ETMN7S/Zu6\n8fX19KVkvpJsO7dNWIYhQ4YIO3Z2GSlrenr0AD8/qFPHrgtJPcLoNRQtOjqaVatWkStXLgYOzPZi\njTYjr2s6NfjpJ/Dygnr1xOaQMpSSkoKrqyu3b982Td3Mch7S06mqGq2qanI6j9987BXgbDF14wvQ\nqkwr1p5aK2ycb4sWLYQc1xJGypoeb2/4+2+oUAGaNoUJE+DOHftmMHoNRYqKimLWrFnExsbSt29f\nOnXqJDpSKnldH6vBrVswcyb07Wv3VWLktcg6V1dX2rZty8KFC01TN7Och5Q+RVF+URTFK83nGX5Y\negzTN76dKnTi1M1TrD65WnQUyQ4KFYING+CNN2D8eChRAsaO1W4+l/Rt//79ODk50b9/f4oVKyY6\njpSRixehfn3t82HDxGaRMqSqKt988w0rVqwgf/78ouNIUlZFA2qazzP7sIjpG98mpZrQpFQTRm8a\nTWxCrOg4kh24uMDkydpY3759YcoUKFlSu/H8/HnR6aSMREVFkS9fPtxErT4iZS45WRtEX7cuxMbC\nzp0QECA6lZSOhIQEunTpwmuvvcaAAQPYvHmz6EiSlCWqqvZRVfVOms8z/LD0GKZvfBVF4YsWX3Ax\n5iKtfmpFTHyMXY+/cuVKux4vJ4yUNSv8/eHzz7Vm9+23YdEiKF0aevYEW82WZbYa2pOfnx+XLl1i\nypQp7Nixg6VLl4qOlMqhr2tsLEyfzkp/f3jpJShTBnbtgqAgIXEc+lpkgaqq9O/fnxUrVrBs2TKm\nTp2Km5ubaepmlvOQsk9RlIaKojyvKEqO3sIwfeMLUKVoFTb22MiRyCM0m9/Mrs3vokWL7HasnDJS\n1uzw8YH339ca4M8/hy1boGJFaN9eG6poTWatoT00bdqUIUOGEBQUxNatW/noo4/YuHEj0dEWv6Nl\nNQ53XVUVDh2CUaO08UKvv84iFxfYs0f7AfL1FRbN4a5FNty4cYPBgwczf/58fvjhBzp27Jj6nFnq\nZpbzkDKmKMpoRVH+l+ZrRVGUdcAWYDVwXFGUYEv37xCNL0Bt/9ps7rWZkzdO0mFpBxKSLb4hMFuW\nLFlil+NYg5GyWiJPHm1I4unTMHcubNsGzZvDzZvWO4bZa2hrBQoUoF27dgwbNozPP/+cffv28dVX\nX7Fs2TIuXLgg7CZVh7muZ8/Cxx9rfxlWrar9oPTqBadPs+TCBahZU3RCx7kW2XDz5k3Gjh1LqVKl\nmD9/PtOmTePll19+ZBuz1M0s5yFlqjNwNM3XHYHngAZAQeAf4ANLd+4wjS9ASLEQVnZZyfbz2xm0\nepDoOJIgrq7Quzds3gznzmnNb1KS6FRSWp6enjRv3pwRI0bQunVrIiMjmTt3Lt9//z2xsXKsvtVt\n2aLdsPbMM9p0KFWrwpo1cPkyfPGFHMurU0lJSXz66acEBATw5ZdfMmjQIM6dO8drr70mOpok5UQp\n4HCar58HlququlNV1ZvAR0AdS3eeK4fhDKdRQCO+bvU1r655laG1hlK1aFXRkSRBqlSBZs20e3QU\nRXQaKT2urq7UqFGD6tWrc+rUKRYuXMjJkyepVq2a6GjmEBkJb76pzclbpw4sWAAvvAB584pOJj3F\n8ePH6dWrF/v27eP111/nnXfeoXDhwqJjmYZb5/K4V5D9wUNux5xhud0OlwuIT/N1HWBKmq8vo73y\naxGHesX3oX4h/SidvzQT/pwgOook0ObNsHQpvPsuODuLTiNlRlEUAgMDKVCgAAcPHuTs2bOkpKSI\njmVsf/yh3aC2bh3MmQM7dkC3brLp1bmYmBjGjx9PtWrViImJYdeuXXz55Zey6ZXM5DTa0AYURSkB\nlAXSLkvlD9ywdOcO2fjmcsrFgGcHsObkGpuP9e3Tx+IZN+zOSFlzIiUFPv1UG+LQuLE25Zm1OEoN\n7SG9WjZs2JDo6Gjmz5/PF198werVq+3SBJvuusbFaWt8V60K//4LffqAU+a/DvRSA73ksLfY2Fgm\nTZpEqVKl+OSTTxg2bBgHDhygVq1aWfp+s9TNbuehKCjyI/XDzm+LTgemKYoyG/gd+EtV1WNpnm8C\nHLB05w431OGhhiUbci/pHgeuHKCWf9b+x2EJI60yY6Sslrp/H7p0gV9/1V7pHTcOclnxp8ARamgv\n6dWycuXKVKpUiUuXLnHs2DGOHTvGvn37yJ07N6GhoQTZaIot013XqVO1aU6WL9emPckCvdRALzns\n5f79+8ycOZOPP/6Ymzdv0r9/f8aMGYOfn1+29mOWupnlPKSMqao6S1GUZKAd2iu94x/bxBeYY+n+\nHbbxvRanLeWVzz2fTY/TtWtXm+7fmoyU1RLx8dCxo/YO72+/Qdu21j+G2WtoTxnVUlEU/P398ff3\np3nz5ly+fJn169ezdetWmzW+pruuwcHg6QmhofDtt9q43qfQSw30ksPWEhISmDt3Lh999BGXL1+m\nV69evP/++wRYeKOhWepmlvOQMqeq6hwyaG5VVR2ck3075FAHgJ+O/ESQTxDlCpYTHUWykyFDYONG\n7dVeWzS9kv0pioKfnx+1a9fm6tWr3LTm3HRm1rYtHDsGISHw4ova2N67d0Wnkh64du0awcHBDBo0\niAYNGnD8+HHmzJljcdMrSUaiKIqvoiifKYrilc5z+RRFmawoSvbe8kjDIRvf5ceWs/joYkbUGSE6\nimRHO3fCgAEg3ykzn4iICFxdXfHw8BAdxTj8/bW3PhYsgFWroFYtOHFCdCoJ+PHHH7l48SIHDx5k\n4cKFlC1bVnQkSbKnEYCXqqpPrDamqmo04Am8Y+nOHa7x/ff6v/Rb1Y//C/4/+of0t/nxduzYYfNj\nWIuRslri/n3rjudNj9lraE9ZrWVCQgJ79+6lZs2aNmt8TXtdFUV7tffvv7XV2mrUyHA9b73UQC85\nbGnZsmW0atWKypUrW22fZqmbWc5DylQrYH4mz88HGlu6c4ca43s97jptFrbB38ufWe1maXcq2tik\nSZOoX7++zY9jDUbKaolmzeCHH+Cdd8BWM/+YvYb2lNVaOjs74+3tzenTp2nUqBHONpibzvTXtVw5\nbTnismVh9mxt0YrH6KUGeslhS6VKlWLXrl0kJibi4uJilX2apW72Oo/vtpwk90mbH8Yw4i7ZtRil\ngAuZPB8BBFi6c4dpfFVVpfPyztxJuMOmnpvwcnti6IhNLF682C7HsQYjZbXExx/Dzz/DG29o8/Xb\n4u8es9fQnrJaS2dnZ9q3b8+sWbPYvXs39erVE5bF0Dw9oVMnWLwY/vc/bY3vNPRSA73ksKUxY8ZQ\nqVIlfvzxR/paab5Fs9TNXudxec00nN0f/RnwrtKU/FWa2eX4It06tInbh/545LHk+3ZdMfMeWmOb\nUfMb8GAbizhM4/v7qd/ZfHYza19eS4B3gN2Omzt3brsdK6eMlNUSBQvC119D9+7aON/eva1/DLPX\n0J6yU8uIiAgAihQpIjyLoQ0dCt9/D6NHw7RpjzyllxroJYctVaxYkfbt2/Pxxx/Ts2dPcllhjJZZ\n6mav8/BtM4Tcfo45tjp/lWZPNPhxl05yarrth4c+sAfowaOLVqTVE9hr6c4dZozvuK3jaFCiAa3K\ntBIdRRKoWzdtwYrXXtNuapeM79q1a2zcuJEaNWpQpkwZ0XGMLTAQJk2C6dO1IQ+SMO+99x6nT59m\n2bJloqNIkr19BvR5MLND6qsZiqIUURTlc6D3g20s4hCN7+HIw/x9+W/erPOmXcb1Svr29dcQEACd\nO2sLWEnGlZSUxM8//4y3tzfNmzcXHcccBg+GgQPhlVfgrbcgOVl0IodUtWpV6taty5IlS0RHkSS7\nUlV1C/AaMAS4rCjKLUVRbgKXHzw+VFXVzZbu3yEa30VHFlEwd0FaB7a2+7FHjhxp92NaykhZcyJP\nHli6FE6f1qY3s+Zqt45SQ3t4Wi1TUlJYvXo1169fp0OHDla7CciSLKbi5KQtavHVV/Dll9oE2Oin\nBnrJYQ9NmzZlw4YNqKqa432ZpW5mOQ8pc6qqfgeUBt4CFgKLgTeBMqqqfpuTfTvEGN/wm+FUK1oN\nV2dXux+7RIkSdj+mpYyUNaeCg2HuXOjaFYoVg8mTrbNfR6qhrWVWy+TkZFasWMGxY8d48cUXKVq0\nqLAspqQo8Prr2hRnI0bAsGG6qYFectjarVu3+P7772nSpIlV3qk0S93Mch7S06mqegn40tr7dYjG\n91rcNYrlLSbk2EOHDhVyXEsYKas1dO4MUVHa73cnJ/jkE+3fnHC0GtpSRrWMiIhg3bp1XL16lU6d\nOlG+fHlhWUzv1Vfh889h8mSG6mTMr6Nci8mTJ3Pt2jVmzJhhlf2ZpW5mOQ9JHIcY6lChYAX2Xdkn\nOoakQ0OHalOWTp6szeQUa9cZW6TsiI6O5pdffmH27NkkJSXRs2dPuzS9Ds3NDdq10+b4leyqYcOG\nJCUlsXXrVtFRJMlUHKLxbR3YmlM3TxF+I1x0FEmHhg+HlSth/XqoXx/OnBGdSHrcoUOHmDZtGmfP\nniU0NJQBAwbItzztJSAAwsO1YQ+S3bRs2ZIuXbowfPhwbty4ITqOJJmGQzS+TUo1wdXZld9P/W73\nY584ccLux7SUkbJaW2go7NwJMTFQvTqsXWvZfhy5htZ24sQJUlJSWL9+PStXrqRixYoMGTKEatWq\n4ZTTMSkWZHFYK1ZA/fqc+Pdf0UkAx7oWX375JYmJiYwePTrH+zJL3cxyHpI4DtH45nXNy3Mln2Nt\nuIXdTA6MGjXK7se0lJGy2kKVKvDPP1C3LrRtCx98kP2ZnBy9htb01ltvsXjxYvbs2UPr1q0JDQ3F\nzc1NSBaHva4HD8Jff8HQobqpgV5y2EPRokWZOHEis2fPZvv2jObyzxqz1M0s5yGJ4xCNL0DrMq3Z\nem4rcYn2nbh12mOrH+mZkbLaSv78sGoVfPihtmpr27Zw82bWv1/W0Dri4+Np3Lgx586do1u3btSs\nWVPoHNwOe10XLdKWPGzTRjc10EsOe+nfvz916tRh4MCBxMfHW7wfs9TNLOchieMwje/zgc8TnxzP\nH2f+ePrGVmSkcYhGympLTk4wdiz8/jvs3QsNGmhDILJC1tA6Nm3aRFxcHD169KB06dKi4zjmdU1K\ngoULoWNHcHHRTQ30ksNenJyc+O677zh58iQLFiyweD9mqZtZzkMSx2Ea3yCfIMoVLMfPx38WHUUy\niJYttXG/ERHQvbt1F7qQMle6dGlSUlJITEwUHcVxrVql/cffv7/oJA6vUqVKlCxZkvBweYO2JOWU\nwzS+iqLwYtCLQm5wk4yrXDntRa/Vq0G+w2Y/QUFB+Pv7s2rVKq5evSo6jmOaNUsb8B4SIjqJBPj7\n+8vGV5KswGEaX4AieYsQm2DfiVonTpxo1+PlhJGy2lObNvDKKzB+PNy6lfm2sobWoSgKEREReHh4\nMGfOHMLCwoTmcbjrGh8P27bBSy+lPqSXGuglh721atWKdevWEWvhZONmqZtZzkMSx6EaX1dnV+KT\n44lPsvwGgeyKi7PvzXQ5YaSs9vbhh1ovMGFC5tvJGlpPSkoKffv2JSgoiOXLlwudxsjhruvOnXDv\nHjRpkvqQXmqglxz21rlzZ+Li4vj9d8vetTRL3cxyHpI4DtX41i9Rn6SUJLad32a3Y44fP95ux8op\nI2W1t6JFYfRomDo18wUuZA2tZ/z48bi4uNC+fXuCgoJYtWoVd+7cEZbFoSxdCiVLQrVqqQ/ppQZ6\nyWFvpUuXJjg4mNWrV1v0/Wapm1nOQxLHoRrfSoUrEeAdwJKjS0RHkQxoxAgoVAj69oWEBNFpHIei\nKISGhqIoCn/++afoOOaXkgK//AL/938gcAo56Ult2rTh999/J0XeaStJFnOoxldRFPqH9Gfh0YVc\nj7suOo5kMHnywOLF2nz+gwbJFVztKXfu3JQuXVre6GYPR4/CtWvQqpXoJNJj2rRpQ1RUFP/884/o\nKJJkWA7V+AL0D+lPfFI8q/5dZZfjXb9unAbbSFlFqV9fu9l9zhz47LMnn5c1tJ7Ha1msWDEuX75M\nRESE8CymdfcuvPUW5M0Ldeo88pReaqCXHCI8XMTl2LFj2f5es9TNLOchieNwjW+hPIXI556PG3E3\n7HK8vn372uU41mCkrCL17AnvvquN+V258tHnZA2t5/FaVq9eHV9fXxYuXMiNG/b5+c0oiylFRUHj\nxrB7t/YftofHI0/rpQZ6yWFvYWFhvPDCCzRo0IDOnTtn+/vNUjeznIckjsM1vgD53PJx81421qHN\ngXHjxtnlONZgpKyiffihNtNTnz7ai2QPyRpaz+O1dHFxoWvXruTOnZtffvkF1Y5jTRziug4eDBcu\nwPbt0LTpE0/rpQZ6yWFvn332Gbdu3WLixIl4PPZHSVaYpW5mOQ9JHIdsfEvkK8H56PN2OVaIgSZ/\nN1JW0Zyc4Msv4c4dmD//v8dlDa0nvVp6eHjQtm1bLl++zPHjx4VmMZXz52HFCm2y6qpV091ELzXQ\nSw57mzBhApUqVaJt27bs3r07299vlrqZ5TwkcRyy8S1ToAzHr9vvl6ZkTiVKQOvWsGyZ6CSOpWTJ\nknh6enLy5EnRUcxj3Trtbs3u3UUnkTLg6+vL9u3bKV26NIMGDRIdR5IMyyEb3/ol6nM48jDR96NF\nR5EMztf30aEOku0dO3aMO3fuUC3NHLNSDnl6ymlKDMDb25sXX3yRixcvio4iSYblkI1vcKFgUtQU\nwm/aft3z2bNn2/wY1mKkrHrh7AyJif99LWtoPenV8t69e2zYsIHAwEBKliwpNIupPPyPOD7jVS31\nUgO95BClVKlS3LhxI9vveJilbmY5D0kch2x8w66F4aQ4Ua5gOZsfa//+/TY/hrUYKateREeDt/d/\nX8saWk96GJbDSgAAIABJREFUtVyzZg0JCQm0adNGeBZT+flnqF0bfHwy3EQvNdBLDlFeeuklfH19\n+eijj7L1fWapm1nOQxLHIRvfvy/9TfmC5cnrmtfmx5o+fbrNj2EtRsqqF7Gx2pSnD8kaWs/jtUxM\nTOTEiRP4+fnh5eUlNIupXLmijfHt2jXTzfRSA73kEMXd3Z13332XBQsWsHPnzix/n1nqZpbzkMRx\nyMb3nyv/UN23uugYkgm4uWX67rBkRS4uLrz00kucPn2aP/74Q3Qc8/juO3Bx0Saolgxh4MCB1K5d\nm969exMbGys6jiQZikM2vuE3wqlQqILoGJIJODtDUpLoFI4jODiYkiVLcuDAAbvO42tqf/8N1as/\nOmZH0jVnZ2d++OEHLl++TPfu3UlOThYdSZIMwyEbXxUVZ8VZdAzJBOLiIE8e0Skcx+HDhzl//jyt\nWrVKXb5VyqFWrWDXLrhpn0V9JOsoW7YsS5YsYdWqVbzxxhvyD0FJyiKHbHzdc7kTlxhnl2OFhoba\n5TjWYKSsenH37qONr6yh9Txey1u3brF27VoqV65MpUqVhGYxlZde0t622Lo10830UgO95NCDtm3b\n8s033zBt2jQ+//zzTLc1S93Mch6SOA7Z+Bb3Ks6F6At2OdaQIUPschxrMFJWvXj85jZZQ+tJW0tV\nVVmxYgUeHh60bt1aaBbT8fODggXh6NFMN9NLDfSSQy8GDhzImDFjGDlyJMsyWU3HLHUzy3lI4jhk\n41ulSBXWn15PfJLt70pq0aKFzY9hLUbKqhd37z7a+MoaWk/aWsbGxnLx4kUaNmyIu7u70CymEx8P\nKSlw716mm+mlBnrJoScfffQRDRo0YObMmRluY5a6meU8JHEcsvEdWW8kl+5cYtb+WaKjSAYXGyvH\n+NpDnjx5cHNz465cJs/6Fi/Wxvf26SM6iWQhRVHw8PAgX758oqNIku45ZONbrmA5QoNCWXx0sego\nksElJ4OTQ/4U2ZeiKBQuXJioqCjRUcxn40Zt8YqyZUUnkXJAzuwgSVnjsL+ya/jWIOxamM3vhF25\ncqVN929NRsqqF97ecPv2f1/LGlrP47UsXLgwkZGRushiKlFRULz4UzfTSw30kkNvnnnmmUyXMTZL\n3cxyHpI4Dtv4lvIuxe37t4lNtO3k34sWLbLp/q3JSFn1okCBR2eBkjW0nsdr6e7uzv3793WRxVSi\noqBw4aduppca6CWHXqiqyjfffMP8+fMpUaJEhtuZpW5mOQ9JHIdtfHM55QIgOcW2bw8tWbLEpvu3\nJiNl1Yv8+eHWrf++ljW0nsdrGRUVReEsNGj2yGIqWWx89VIDveTQg6SkJDp16sRrr71G//79Wb58\neYbbmqVuZjkPSRyHbXx9PX0BOHbtmOAkkpG5uEBiougUjsHd3Z0rV67IJVqtKS4OIiPB3190EskC\nsbGxrF27lm7dujF16lQhM55IktE4bONb2782RfIUYfmxjP9ClqSnuXVLe9VXsr0WLVqgqiq//fab\n6Cjmcfw4qCpUrCg6iWSBfPnyMWLECH7++WeuXLkiOo4kGUIu0QFEcXZypnCewty8L5fplCwXEQFB\nQaJTOIa8efPSpEkTVq9ezb179/Dw8BAdyfj27IFcuSA4WHQSyUJBQUHcv3+f27dvU6xYMdFxJEfk\nm4IakJL17e9lY1sbcNhXfCNiIjgSdYRWpVvZ9Dh9DDQ3ppGy6kFSEpw69WjjK2toPenV0v/BW/L2\nntbMtNd182aoVStLk1HrpQZ6yaEXn3zyCW3atKF8+fKZbmeWupnlPCRxHLbxTUzWBmY6Oznb9DhG\nWmXGSFn14Nw5bXxv2sZX1tB60qtlwYIF8fT0ZN++fcKzmMK9e5A7d5Y21UsN9JJDT65cufLUGU/M\nUjeznIckjsM2vqXyl+LZYs+y6Khtp0bp2rWrTfdvTUbKqgf//qv9m7bxlTW0nvRq6ezsTMOGDTly\n5AhhYbafhzuzLKbQqBHs2AEJCU/dVC810EsOvfjpp58ICwvj7bffznQ7s9TNLOchieOwjS9A14pd\nWXNyDdH3o0VHkQwoJkb718dHbA5HU7VqVQIDA1m+fDmzZs0iPDzcbg2w6bi6assPpogdcydZrlq1\nanTq1Ildu3aJjiJJhuDQjW/nip2JT45n5Qm5EoyUfQ/vrbp3T2wOR+Ps7MzLL79Mr169cHFxYeHC\nhcydO5e7d++KjmY8W7ZAnTogp8EytMjISLy9vUXHkCRDcOjG19/Ln2eLPcuWc1tsdowdO3bYbN/W\nZqSsevDwld6091nJGlrP02oZEBBA79696datGzdv3uTXX3+12Su/pryud+/Chg3QKms3+OqlBnrJ\noSeNGzdm48aNDB8+nOTk9BdlMkvdzHIekjgO3fgC1PKrxd5Le222/0mTJtls39ZmpKx68Mwz2r+n\nT//3mKyh9WSlloqiUKZMGRo1asSpU6c4ePCgsCyGs3at9nZF27ZZ2lwvNdBLDj155513mDp1Kl9/\n/TVt2rThwoULT2xjlrqZ5TwkcRy+8S2YuyAx8TE22//ixYtttm9rM1JWPfDy0v5Nu5CYrKH1ZKWW\nV69e5eeff2bt2rXkyZMHT09PYVkMJyAAPD2he3dIp1F6nF5qoJccejNkyBDWrl3L4cOHKV++PBMn\nTiQhzU2LZqmbWc5DEsfhG9+b925SwKOAzfafO4tTBemBkbLqQVyc9m/adRRkDa0ns1qqqsrPP//M\nd999R0REBK1bt2bYsGGUKVPG7lkMq2ZN2LULoqOhRg24di3TzfVSA73k0KOWLVty4sQJBg4cyLvv\nvktISAg3b2qLNJmlbmY5D0kch298C+YuyKU7l0hR5V3NUvY8HGpWoYLYHI7o8uXLHD16lJYtWzJ0\n6FBq1KiBi4uL6FjGU7EizJmjDVSPiBCdRrICLy8vvvjiC/755x/Cw8OZO3eu6EiSpCsO3/jWK1GP\nm/ducuzaMdFRJINZuhSqVoXAQNFJHE9YWBh58uShZs2aODk5/P/Gcub4cXBygnLlRCeRrKhq1aq0\nb9+eGTNmEPfw7SlJkmTjW694PTxdPVl+bLlN9j9y5Eib7NcWjJRVtNhYWL0aOnd+9HFZQ+vJrJZJ\nSUl4eHjYrek17XWNi4OJE+H55x8ds5MOvdRALzmMYMyYMVy+fJnu3bvz5ptvio5jFfL6Sznl8I2v\nh4sHnSp0Yt6heSSnpD8NTE6UKFHC6vu0FSNlFW3dOq1n6NTp0cdlDa0ns1oWLlyYGzdukJSUJDyL\noX36KURGwpQpT91ULzXQSw4jqFSpEgsXLmTFihWEh4eLjmMV8vpLOeXwjS/AwOoDOXf7nE1e9R06\ndKjV92krRsoq2uXL2pz/pUs/+risofVkVsuoqCjy5s2Ls7Oz8CyGde0afPEFDBv25H/I6dBLDfSS\nwwgSExNZuHAhzs7O9O/fX3Qcq5DXX8op2fgCNf1q0vyZ5ry/9X2u3LkiOo5kECkpIFfKtb/Y2FiO\nHj1KxYoVURRFdBzjmjYNFAVGjRKdRLKRESNGsGLFCpYtW0a7du1Ex5EkXZCN7wNTWk3hbsJdan5f\nk4NXbTMJvmQeQUGQkADH5D2RdpWQkMDChQtxcnKiVq1aouMYm5MT5MoFcqlb0/L29sbFxYX69euL\njiJJuiEb3wcqFKrA3lf2UiRPEerNqce0vdOsMub3xIkTVkhnH0bKKlqDBuDmpi1+lZasofWkV8s/\n/viDa9eu0a1bN/Llyyc0i+E1agS3b8ORI1naXC810EsOI2jfvj1xcXHMmDHDNHUzy3lI4sjGNw0/\nLz+299lOj8o9GPr7UGrPrs3+K/tztM9RBnob0UhZRfPwgI4dtXeLExP/e1zW0HrSq6WTkxOurq4U\nKVJEeBbDe3hjYBYXBNBLDfSSQ89UVWXOnDk0bNiQ4sWL07p1a9PUzSznIYkjG9/H5HbJzYy2M9jV\ndxfxSfHUmFWDDks78Nu/v5GYnPj0HTxm2rRpNkhpG0bKqgejR2srvf7ww3+PyRpaT3q1rFixIrGx\nsVzIwhK7ts5ieLt3a29bZOHGNtBPDfSSQ4+Sk5P59ddfadiwIf369aNjx44cOXKE6tWrm6ZuZjkP\nSRzZ+GagTvE67Buwj6mtp3Lm1hlCF4fi/6U/I9aP4HDk4Szvx0hTrxgpqx5UqgQ9emgNcGSk9pis\nofWkV8uHN7PlypVLeBZDi4qCyZOhZ0/I4swYeqmBXnLoyZ07d/j6668JCgrixRdfJDk5mTVr1jBn\nzpzUIUFmqZtZzkMSx76/PQzGxdmFwTUGM7jGYA5ePci8g/NYcHgBX+7+kpL5SlKpSCUqFqqo/Vu4\nIkE+QbjlchMdW7KjL76A33+HwYNh+XLtJnnJ+uLi4jh+/DgHDx5EURQKFy4sOpKxff453L0LH30k\nOomUA6qqMnv2bEaOHMmdO3fo1KkTCxcupGbNmqKjSZJuycY3i6oWrUrVVlWZ1HwS606t488Lf3I0\n6ig/HfmJizsvApDLKRdlfcpSsXBFKhaqSMXCWlNcyrsUzk72mW9Usq+CBeHbb7WFLH74Afr0EZ3I\nPGJjYzlx4gTHjh3j7NmzAAQEBNCpUydcXV0FpzO4li21V3ynT4fx40WnkSxw9uxZBgwYwKZNm+jd\nuzcffvghxYsXFx1LknRPNr7Z5OLsQrugdrQL+m9OxNv3bxMWFcbRqKMciTrC0aijbDqziZv3bsIO\ncGvoRol8JSiRrwQl85WkpHfJRz739/LH1Vn8L/KJEycyevRo0TEMp2NH6N0bXn8dLlyYyAcfyBrm\n1O7du3nvvfdo0KABAQEBPP/885QvX548efIIyWO6n40mTeB//4P33oMOHaBy5ad+i15qoJccIp04\ncYIaNWpQoEAB1q9fT4sWLZ76PWapm1nOQxJHNr5W4O3uTb0S9ahXol7qY6qqcvXuVUZdH0WN5jW4\nEH2B89HnORJ1hDXha4iMjUzdVkGhmGex/5rhfA8aY+//Ps/nbvupm+Li4mx+DLMaOVJ7xffMGVnD\nnFBVlW3btrFt2zYKFy7Mm2++KazZTcuUPxtvvQUffKDd5JaFxlcvNdBLDlFUVWXw4MEUKVKE/fv3\n4+XllaXvM0vdzHIekjiy8bURRdGa2R+n/pju8/cS7xERE8H56POcv30+tTE+H32evy//zcXoiySm\n/DeLhKerJ/5e/k98+Hn6pX5ewKNAjlayGi/f8rRYmTLaegDVq8sa5kR4eDjbtm2jSZMmfPDBB6Lj\npDLlz4abG5QtC9u2wYABT91cLzXQSw5RPvvsM7Zs2cK6deuy3PSCeepmlvOQxJGNryAeLh4E+gQS\n6BOY7vPJKclExkZy/rbWDEfERBARE8GlO5c4fv04G89s5PKdy6SoKanf457LPd2GOO1jRfIWwUmR\nk3lY2/r12hLGdeuKTmIOlbPwCqRkBYMHa2N0hg0DeUOU7k2fPp1Ro0YxZswYWrZsKTqOJBmSbHx1\nytnJGV9PX3w9falTvE662ySlJBF5NzK1IX7YHEfERHAh+gJ/RfxFREwECckJqd/jkcuDsj5lKetT\nliCfIIIKBqV+bo/hFGb1448QEgLPPis6ibEVLVoUgLCwMOrKvyJs79VXYfZs6N9fG/Lg4SE6kZSB\nPXv2MGTIEEaMGMFHcjYOSbKYbHxt7Pr16xQsWNAm+87llAs/Lz/8vPwy3EZVVa7HXSciJoKLMRc5\nc+sM/17/l39v/MvOizu5fOdy6rYFKUj5EuUJ8nnQDBcMIsgniECfQPkq8VOEhUHTpra93o7Ay8uL\n2rVrs3HjRgDdNL+mva65cmmD02vXhiFDtCY4A3qpgV5y2NvixYspVqwYkydPtmhIm1nqZpbzkMSR\n3YyN9e3bV+jxFUWhUJ5CVCtWjdCgUN6o/Qbftv2Wzb02c2nEJe68c4d9A/axsP1CCmwogL+XP/uv\n7ufD7R/ywuIXKDe9HDVn1ST8RrjQ89C7a9fg5k3x19sMWrRoQdmyZXnllVdQVVV0HMDk17VKFW1O\nvjlz4MEfHOnRSw30ksPetm3bRp48eVKn9ssus9TNLOchiSNf8bWxcePGiY6QqbyueQkpFkJIsRCC\npgYREhICaK8UX7l7hQNXDvDG+jeo9l013ir1luC0+vXhhzBoELz22jjRUQzv4atZHTp0yNHNmtak\n95/jHOvVCyZOhAULoHnzdDfRSw30ksPepk6dSo8ePahcuTKTJk1i0KBBODll/bUrs9TNXufx7Lr+\nFJYjf1JF3YNTokNYiXzF18YeNpJGkDZrippC5N1Izt4+S7mC5YhNjGX8Vnk3bUZefRXGjYPp00NY\nskR0GmNLTk7m1KlTPP/886KjpDLSz7FFFEWbkHrNmgw30UsN9JLD3urVq8fhw4fp1asXQ4YMoXbt\n2mzbti3L32+WupnlPCRxZOMroaoqkXcj2Xh6I+O2jqP5j83xnuhNyMwQRqwfwfW467xZ500+b/G5\n6Ki69v770LUr9OsHx4+LTmNcqqqSkpKii/l7HUrhwiDnSNW1vHnz8s0337Bt2zZUVaVRo0a0a9eO\nY8eOiY5mOor8eOLDLORQBweQlJLEpZhLqXMGP/JvtDaH8P2k+wD4ePhQt3hd3m3wLvWK16O6b3U8\nXLT3e/bv3y/yNHRPUWDSJFi6FD76CH76SXQiY7p/X/tv0dlZLvNtVx4eEB8P+/drU5RIuvXcc8+x\nZ88eli1bxjvvvENISAirV6+mWbNmoqNJku7JxtfGZs+eTb9+/Wx6jLjEOC5GX/xvEYw0Te3529oc\nwMlqcur2Ph4+qavCPV/m+dTPw9aH8e6wd3UzrtJo7t6Fhg1nky9fP8aMEZ3GuI4dO4aTkxPbt28n\nODhYdBzAPj/HwnXtCt99B+3awZ494O//yNN6qYFecojm5ORE586deeGFF2jfvj0vvPAC69ato0GD\nBulub5a6meU8JHFk42tj+/fvz9EPaXxSPJfuXOJi9EUuxlz87980n9+8dzN1ewUFX0/f1Ga2rn/d\n1M8f/pvHNf23kDdN2ySbXgutXQtDh8LFi/vZtasfOunXDCkiIgJPT0+OHDkiOkqqnP4cG0KePLBq\nFdSqBc89B7/+CpUqpT6tlxroJYdeuLu78/PPP9OmTRuaNGnCgAEDeO+991LnxH7ILHUzy3lI4sjG\n18amT5+e6fM34m7w741/uRB9Id2mNio26pHtC3gUoLhXcYrnK07d4nXx9/JP/bpEvhL4e/nj6uxq\nk6zSky5c0Ba9WrlSm8d37drpBAWJTmVstWrVIiwsjA4dOoiOksphfjaKFYPt2+HFF6FOHW1llpde\nAvRTA73k0BMPDw/Wrl3L119/zSeffMK8efMYMWIEo0aNIm/evIB56maW85DEkY2vHaiqytW7Vzl+\n/TjHrh3j2LVjqZ+nbWw9XT0pnq84xb2KU62oNu/uw6a2uFdx/L38M3y1VrK/HTvghRfA3R2WLIFO\nnbRxvlLO+Pn50ahRIzZv3syVK1do3Lgxfn4ZL9IiWVlAAOzcCX36QPv2MH48jB0L2Zg6S7I/d3d3\nRo0aRf/+/fn000+ZPHkyV69eZebMmaKjSZKuyMbXyu4m3GXnhZ2EXQvj+LXjHLuuNbq3798GwNXZ\nlbI+ZalQqAKNSjaiQqEKlCtYjpLeJfFy8xKcXsqqpUuhZ0/tRbFffoH8+UUnMpf69evj4+PD1q1b\n+f777ylbtixNmjShSJEioqM5hjx5tL/mKleG996DQ4dg3jx48OqhpF/58+dn4sSJ5M2bl4kTJ/L5\n55/j6ekpOpYk6YZsfK3gyp0rrPp3FatOruKPM38QnxyPRy4PyhcqT4VCFWgT2IYKhSpQoVAFnsn/\nDLmcZNmNbOtW7T6gLl20xa7c3EQnMh9FUahQoQLlypXj6NGjbNu2jVmzZtGpUyeC5FgS+1AU7ZXe\nSpWge3eoW1cb91uqlOhkUhb07t2bDz74gCVLlvDKK6+IjiNJuiHfu7LQ6Zun+fjPj6n1fS18v/Bl\n8NrBxCbE8knTTzjx2gnujrnLvgH7iJ4bzZgGY3ix3IuU9Smr66Y3NDRUdATdi4qCl1+Ghg1h/vwn\nm15ZQ+sJDQ3FycmJypUrM2jQIMqWLcuSJUs4dOiQkCwO64UXYPduQk+fhho1tL/8BHLoa5ENxYsX\np1WrVsyePRswT93Mch6SOPrtwnTqr4t/8dlfn7Hi+AryuOahVZlWDKkxhOcDn8cnt88T2w8ZMkRA\nSssYKaso77wDiYnaHL3pTTMra2g9aWuZK1cuOnbsyG+//cbKlSsJCwujefPmFCpUyO5ZHFJwMEPm\nz4fp07Vxv1evgqtlN9HmlMNfi2x4OFwoJSXFNHUzy3lI4sjGN4vWhq/l4z8/ZufFnZT1Kct3bb+j\ne+XuqYs7ZKRFixZ2SphzRsoqwqlT2jDHzz7Tbn5Pj6yh9TxeSycnJ0JDQwkMDGTTpk18++23VK9e\nnaZNm+Jm4/Em8rpCiw4dIChIG/qwfr0236+IHPJaZMmMGTNYsGABs2bNwsnJyTR1M8t5SNmnKEou\nwF1V1bs52Y8c6vAUqqoydvNY2ixsg4rKys4rOf7acfo/2/+pTa9kLj/8AN7eMHCg6CSO6+HY38GD\nBxMSEsLff//NiRMnRMdyHBUrQrVq2hx+586JTiNlYMqUKQwePJghQ4bI8b2S4SiK0k5RlN6PPfYu\ncBe4rSjKBkVRLL6lXDa+mUhKSaL3r72Z8OcEJjabyI4+O3ih3As4KbJsjujvv7X7ezzk3zvCqarK\nuXPnKFq0KBUrVhQdx7GsWKFNbfbcc3DmjOg0UhqqqvLGG28wfPhw3nrrLb766ivRkSTJEiOA1Llb\nFUWpC3wI/A/4P6A48J6lO5cdXCYm75zMgsML+Kn9T4yqN8qiVc1Wrlxpg2S2YaSsIvz7L09dkU3W\n0Hoyq+WGDRuIjo6mffv2OKc32NqOWRxFag1KloQtW+DSJe1tEFE5pCds2bKFr776iq+++opJkybh\nlGbuZbPUzSznIWUqGNiV5uuOwEZVVSeoqvoL8CZg8Vgr2fhm4NTNU3y4/UNG1B7By5Vetng/ixYt\nsmIq2zJSVhESEp7+aq+sofVkVMuTJ0/yzz//0KJFC7vd3Cav62M1CA+HlBR4/nmxOaRHLF26lICA\nAIYOHfrEc2apm1nOQ8qUJ3Ajzdf1gT/SfB0G+Fq6c3lzWzpuxN0gdFEovp6+jGs0Lkf7WrJkiXVC\n2YGRsoqQlAS5nvITI2toPRnVMjw8HICCBQsKz+JIUmvw66/Qt6/29ketWuJySE84ePAg9evXT/fd\nSbPUzV7n8U/LmeT2K2uXYxlB3KWT8M0Aex3uElAeuKAoSl6gCjA8zfM+QJylO5ev+D4mNiGW5xc+\nz/W46/ze7Xe5RLCUKjERXFxEp5CaN29O6dKl+emnn1KbYMkOUlLg9dfhxRe18b3bt8s1unWmZMmS\nXLp0SXQMScqpZcAURVF6ALOAq/x/e/cdJ0WVLXD8d0gzoCBhYAAJDiDgkhRWzIACjsuKimkWXcew\nKmLCXZ8ifnQB8e0aNiAKKkbEJ6yRVRAT8swrS844pEUecQCZIQwMM/f9cWu0aSd0qO6aqj7fz6c+\nMF23bp861dV9+3bVvfCvkPW/BNbEWrk2fEMYY7hl1i2s2LGC2VfPpmMT/banrKIi2LcPdOZP79Wp\nU4chQ4YAsHTpUo+jSSHffgtPPgmPP27n6W7c2OuIVJjWrVuzefNmr8MIBhFdwpfkeQj4NzABOBn4\nrTGmJGT9UOC9WCvXSx1CvLT4pR9vZuvVspfX4ahqZNkye6lDz55eR6IAPvzwQ2rVqkX//v29DiV1\nLFtmZ225/Xbt6a2mjj32WA4ciPkXYKWqBWPMQSC3kvXnxlO/9viGeH3F6/Rt2zeum9nCXX/99a7V\nlWh+ijXZvv7aTlTVvXvl5TSH7qkol/n5+Sxbtozs7GwaNmzoaSyp5PopU+zlDosXexuHHosKFRcX\nHzWSQ6ig5C0o+6GiJyJ9RWRQPGP4gjZ8j5LVMIvdB3e7WqefZpnxU6zJNncunHEGpKdXXk5z6J6K\ncrls2TLS0tLo1q2b57GkkvOHD4dTT4XcXPCwV1GPRcXWrVtHu3btyl0XlLwFZT9UxURkpIiMC/lb\nROQDYC4wE1glIlUMLloxbfiG6JTRibzdeZSaUtfqHDp0qGt1JZqfYk2mkhL47DM4N4IfVzSH7qko\nl4cPHwZg//79nseSSob+9rd2zu4NG2DiRO/i0GNRrg0bNjBz5kzOOOOMctcHJW9B2Q9VqRxgecjf\nlwN9gHOADGA+MDrWyrXhG6Jjk44UHSni+73fex2KqkaWLoUffois4asSr0+fPqSlpTFjxgyMMV6H\nk1o6d4Ybb4RHH4XCQq+jUQ5jDDfeeCMZGRncf//9XoejVLyygNA7lwcBbxpjvjLG7AYeBsr/hhcB\nbfiG2Ll/J0BMM7Sp4Jo7117i4MGQpaocdevW5cILL2Tjxo18/71+SU26+++H3bvhjTe8jkQ5FixY\nwKeffsqECROor0PPKP+rBRwK+fsMjp7JbQu25zcm2vANMXnhZAa0G0Cb49q4VueXX37pWl2J5qdY\nk2nuXDjzTEhLq7qs5tA9leWyXbt2pKens2zZMs9jSRU/5qB1a+jXD159FTzocddj8XPTpk2jWbNm\nDKpkJr2g5C0o+6EqtQ57aQMi0gboCHwesr4VR8/sFhVt+IZYv2c9vVv2drXOxx57zNX6EslPsSbL\nkSN2nP5IL3PQHLqnvFwWFxczb948nnzySYqKikiv6m7DBMaSao7KwfDh9hvhE094G4di+/btTJ48\nmdzcXGpVMrVkUPIWlP1QlZoIPCUiLwCzgW+MMStD1p8HLIq1ch3HN0TPFj2Zv3W+q3VOnz7d1foS\nyU+xJsvixVBQEHnDV3PonvBcLl68mI8//piDBw/StWtXzjrrLDIzMz2JJRUdlYMrroB77oE//AE6\ndoQ5yvrrAAAgAElEQVRKehoTGodizJgx1K5dm1GjRlVaLih5C8p+qIoZY54TkRJgMLand2xYkZbA\ni7HWrw3fEIM6DOLOD+5k8bbFnNz8ZFfqrFevniv1JIOfYk2WWbOgQQM7ilMkNIfuCc1lcXExs2fP\nJisri+zsbBo1imsYx7hiSVU/y8Ejj9g7P++4AwYOTNp83nosjvbRRx9x3XXX0biKmfSCkrdk7ce1\n24+QVXokKc/lBxt2HuHBJD6fMeZFKmjcGmNujaduvdQhxM29bqZzRmdGfDDC61BUNfH22zB4sJ28\nQnlnzZo1HD58mAEDBiS90asqUKMGPPYYrF8PU6d6HU3Kys/Pp2XLll6HoZRvaMM3RO2atbmm+zUs\n2hrzpSMqQNautR1al17qdSSqbt261KhRg5kzZyZ1/F5Vhe7doVMne6IoTxw6dIg6+s3cdaLLz5ag\n0IZvmK2FW2nVoJVr9d1zzz2u1ZVofoo1Gd55B+rWhezsyLfRHLonNJft27fn2muvJT8/n8mTJ7N3\n717PYklVFeZg925o2tT7OFJUvXr1OBDBTHpByVtQ9kN5Rxu+YY6UHqF2TfeuVWvTxr2h0RLNT7Em\nw8cf25vajjkm8m00h+4Jz2WbNm0YNGgQBQUFEX3QJzKWVFRhDtLSIIm98HosjtapUye++eabKssF\nJW9B2Q/lHW34hsmol0H+gXzX6rvjjjtcqyvR/BRroh05At98A336RLed5tA95eUyLy+Pxo0b07x5\nc89jSTUV5qBLF1ixwvs4UtRVV13F7Nmz+eGHHyotF5S8BWU/lHe04RumbcO2bC3cysHig16Hojz0\n9dewbx+cd57XkagyxcXFrFy5km7duunsitVJ166wfLnXUaSsvXv3UqtWLT0nlIqQNnzDdGnaBYNh\nVf4qr0NRHnrnHWjeHHr18joSVaZsZIdu3bp5HYoK1bUrbNgA27d7HUnKKS0tZdKkSVxzzTUcd9xx\nXoejlC9owzfMjv07AGiQ1sCV+lavXu1KPcngp1gTacsWmDwZrrvOjtgUDc2he0JzWVpayhdffEFW\nVhZNmjTxNJZUVWEOsrOhWTP41a+gip/bExpHCjLGsGvXLrp27Vpl2aDkLSj7obyjDd8w7+e9T/tG\n7enQuIMr9d17772u1JMMfoo1kR580I7mcN990W+rOXRPaC5XrVrFjh07OOusszyPJVVVmIMWLeyd\noBs3wsUXgzHexJGCatasSevWrcnLy6uybFDyFpT9UN7RmdtCHCg+wPQV0xnWa5hrdT711FOu1ZVo\nfoo1UZYsgZdeggkTIJZfDjWH7gnNZcOGDUlPT2f27Nnk5OTQNInDZ4XHkqoqzUG3bvDaa7bX99NP\noX9/b+JIMdOmTWPdunX07t27yrJByVuy9uPlZjWpd3zNpDyXHxyQ4ORCe3xDvL3qbfYW7XW14eun\noVf8FGuijBoFJ54Iw2J8CWgO3ROay+OPP54bb7yRGjVq8Pzzz7Nr1y7PYklVVeYgO9te7ztmTEKH\nN9NjYW3bto1hw4YxdOhQrr766irLByVvQdkP5R1t+IaoITUwGOrWrut1KMoDW7bABx/AyJFQ272h\nnJVLmjRpQm5uLocPH2bbtm1eh6PCicD48bBoEZxzDmze7HVEgTZ37lwKCwsZP368juiQCCK6hC8B\noQ3fEAPaDQBgzvo5HkeivPDOO1CrFgwZ4nUkqiK1aunVWdVa//7w1VeQnw+nnQZJnmEvlSxYsIAT\nTjiBZs2aeR2KUr6inyIhmh3TjIx6GWzau8m1Oh999FFGjhzpWn2J5KdYE2H9emjXDho1ir2OVM+h\nm8rLZVpaGrVr1076lMV6XKPIQY8e8NZb0Ls3rF5tG8BexBFwu3btomXLlhGXD0rekrUfvT64iWb6\n4++PdhyEtV4H4RLt8Q3TML0h2/e7Nx5lsqdWjYefYk2Effugfv346kj1HLqpvFyKCM2aNWP16tUc\nPJi8SWb0uEaZg1at7L87d3obR4CVlpZSUFBAaWlpROWDkreg7IfyjjZ8w/TP6s/05dMpOlLkSn1j\nx451pZ5k8FOsiVBYGH/DN9Vz6KaKctmvXz927tzJM888w4YNGzyNJZVElYO6TlfZoUPexhFgOTk5\nrFixgoceeiii8kHJW7L2Q3T52RIU2vANc/cZd7Nj/w6eX/i816GoJCsoiL/hqxKvQ4cO3HLLLTRu\n3JhXXnmFf/7zn/yQhIkTVBQSPJavgkGDBjFu3DjGjh3L+++/73U4SvmGNnzDnNjkRH53yu944NMH\n2Fq41etwVBKtXQtt23odhYrEcccdR25uLhdccAF5eXk8+eSTzJo1i4KCAq9DU/DTDG46jW5C3X//\n/WRnZzN8+HD2J3AIOaWCRBu+5Xhs4GOk1UpjxAcj4q4rPz/fhYiSw0+xuu3gQdvw7dIlvnpSOYdu\nqyqXIsJpp53GnXfeybnnnsuKFSuYMGEC69atS3osqSCqHOzebf9NwCgceix+IiJMmjSJzZs389xz\nz1VaNih5C8p+KO9ow7ccjeo2Ynz2eN5Y+QYzv5sZV1033HCDS1Elnp9idduXX0JJCcQ7I24q59Bt\nkeayTp06nH322YwYMYK2bdsyY8YM13u/9LhGmYMuXaBTJ7jnHigu9i6OFLBkyRJKS0s56aSTKi0X\nlLwFZT+Ud7ThW4HfdP0N2e2zue3929h3eF/M9YwZM8a9oBLMT7G6bfZsaNEi/h7fVM6h26LNZVpa\nGpdccgmlpaW89957GBevM9XjGmUO0tPhlVfsZBaTJ3sXRwoYN24c559/PtnZ2ZWWC0regrIfyjva\n8K2AiPD0r59m5/6d/HHuH2Oup2fPni5GlVh+itVNhw7B1KmQkxP/5DSpmsNEiCWX9evXZ/DgwaxZ\ns4YFCxZ4GkvQRJ2D3r3h9NPh66+9jSPgSkpKaN++fZXlgpK3oOyH8o42fCuR1SiLsf3G8sS3T7Bq\n5yqvw1EJMn26nWhq2DCvI1Fu6Ny5M7169eLDDz9k0aJFrvb8qih162ZnckvAsGbKateuHatXr/Y6\nDKV8Qxu+VRhx+ggy6mXwzPxnvA5FJcChQzB6tJ2muHNnr6NRbsnOzqZr1668++67vPHGGzrovVdu\nvRW2boU/xv6rmapcdnY2n3/+Odu2bfM6FKV8QRu+VahTsw43nHwDU5ZMoaS0JOrtX3jhhQRElRh+\nitUt48fD5s3w5z+7U18q5jBR4sll7dq1ufjii7niiivYuHEjTz/9NCtWrIi591ePa4w56NYNxo2D\nxx+3/x454k0cAZaTk/Pjde2VCUregrIfyjva8I3AwPYD2XtoL3m786LeduHChQmIKDH8FKsb1q6F\nMWNgxAh7A7obUi2HieRGLn/xi18wfPhwWrVqxZtvvsm0adNimuxCj2scObj7bnjgARg71g6bsmaN\nN3EE1MGDBzHG0LRp00rLBSVvQdkP5R1t+EagW7NuACzfsTzqbSdOnOh2OAnjp1jjZQzcfLMdySHC\nGT8jkko5TDS3clm/fn1ycnLIyclh+/btPPvssxyK8ppTPa5x5KBmTXuSffUV7Nljb3orG+c3mXEE\n1NSpU4Gqb/oKSt6Csh/KO9rwjUD9NDuPbdGRIo8jUW558UWYOxeefRaOOcbraFQydO7cmRtuuIGi\noiJWrdKbVZPutNPgs89g3z545x2vowmE6dOnc99993HPPffQpk0br8NRyhe04RuBGmLTVGpKPY5E\nuaGgwI6rn5sLAwd6HY1KppKSEtLT0xMyu5uKQIsW9rrfjz/2OhLfy8vLIzc3l9zcXB555BGvw1HK\nN7ThG4GaUhPQhm9QPPOM7XT605+8jkQl09q1a3nuueeoV68effv29Tqc1LRhAyxbBued53Ukvjd6\n9GgyMzN59tlnqVFDP8qVipSeLRGIp8f3oosucjuchPFTrPF45RW48ko4/nj3606VHCaDm7ncvn07\nr732Gq1bt+amm24iIyPDs1j8ypUcvPwy1K8PV1/tbRw+98MPPzB9+nTuvfde0tPTI9omKHkLyn4o\n79TyOgA/EGc6r1gavrfffrvb4SSMn2KNx3HHxT9DW0VSJYfJ4GYu58yZQ6NGjcjJyaFmzZqexuJX\nruTg44/h/PPjurBejwXUrVsXYwz169ePeJug5C0o+6G8oz2+EaohNWIax/f8889PQDSJ4adY49Gl\nC8yeDfPmuV93quQwGdzKZVFREXl5efTs2TOmRq+bsfhZ3DkoLoZ//xv69PE2jgBIS0ujefPmLF8e\n+UhDQclbUPZDeUcbvhESEtRFqJLu4YftuL19+9rpinVG22BLT08nKyuLJUuWUFqq1+l7Jj/fTmBx\nwgleRxIIOTk5TJkyhaIiHW1IqWhow1elnGbNYM4cuPRSGDoUuneHv/8ddu70OjKVCPv27aNmzZrs\n3LmTHTt2eB1O6jp82P67fr23cQREly5dyM/PZ+XKlV6HopSvaMM3wWbMmOF1CBHzU6zxSk+HV1+F\nDz6Ak06CkSPtzW6XXQazZkGU8xv8KJVymGjx5tIYw4IFC5g4cSJbtmzhkksuITMz05NYgiDuHLRt\nC7fcAvfeCwsWeBdHACxatIi77rqLyy+/nJNPPjmibYKSt6Dsh/KONnwT7NFHH/U6hIj5KVY3iEB2\nNrz+OmzZAo8/Dnl5cOGF0LgxDB4MkybZEZgilWo5TKR4c5mXl8fMmTPp3Lkzt912Gz169PjxRtVk\nxxIEruRg/Hjo3BlGjfI2Dp8bN24crVq1YsqUKREPZRaUvCVrP/5TGNt2a6KfEd1X2wWBNnwTrKr5\n06sTP8XqtowMGDECliyBpUvhj3+EwkL7WLt29rP697+3N6WX/WJbnlTOodvizeXSpUvJzMzk4osv\npl69ep7GEgSu5CAtDS65xJ5oXsbhcw0bNqRhw4ZRva6Dkrdk7cd/9sW23Xd7g71dEGjDV6kQInZi\nqZEj4X//F3btgrfftjeiv/mmHYkpMxOuvRbeew/0vpLqad26daxatYoePXp4HYoKd9JJsGMH7Nnj\ndSS+1aRJE3bqTQlKxUQbvkpVokEDGDIEJk+GTZtg8WK44w6YPx8uusjeKHfVVTBjBuiAAdXD1q1b\nef3112nXrh29e/f2OhwVrkUL++/27d7G4WNr1qyhY8eOXoehlC9pw1epCIlAj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REFycjG2SbNmypRm/FcnK1z/P7CdTsZG2fEzlynDrFvTrB61awauvPrlPBuqV1a/pLNZX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\nYGsrSqkFBopEuFo1KFBAa82zJ8WLF+ejjz5i8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8zdl4cPw6pVMGsW5MnAFTVzt8sQGMrG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\nhF2WS5ZAnTpw3nnx3W/Y+QpCEHk866yzaNeuHZ9++ilffvllsd+XC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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# DNN model Prediction\n", + "y_test = model_dnn.predict( X_test , batch_size=n_per_batch, verbose=0)\n", + "predictions_dnn = np.zeros((len(y_test),1))\n", + "for i in range(len(y_test)):\n", + " predictions_dnn[i] = np.argmax(y_test[i]) + 1 \n", + "predictions_dnn = predictions_dnn.astype(int)\n", + "# Store results\n", + "test_data = pd.read_csv('../validation_data_nofacies.csv')\n", + "test_data['Facies'] = predictions_dnn\n", + "test_data.to_csv('Prediction_StoDIG_2.csv')\n", + "\n", + "make_facies_log_plot(\n", + " test_data[test_data['Well Name'] == 'STUART'],\n", + " facies_colors=facies_colors)\n", + "\n", + "make_facies_log_plot(\n", + " test_data[test_data['Well Name'] == 'CRAWFORD'],\n", + " facies_colors=facies_colors)" + ] + } + ], + "metadata": { + "anaconda-cloud": {}, + "kernelspec": { + "display_name": "Python [default]", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.5.2" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/StoDIG/Prediction_StoDIG_2.csv b/StoDIG/Prediction_StoDIG_2.csv new file mode 100644 index 0000000..787c37d --- /dev/null +++ b/StoDIG/Prediction_StoDIG_2.csv @@ -0,0 +1,831 @@ +,Formation,Well Name,Depth,GR,ILD_log10,DeltaPHI,PHIND,PE,NM_M,RELPOS,Facies +0,A1 SH,STUART,2808.0,66.27600000000001,0.63,3.3,10.65,3.591,1,1.0,3 +1,A1 SH,STUART,2808.5,77.252,0.585,6.5,11.95,3.341,1,0.978,3 +2,A1 SH,STUART,2809.0,82.899,0.5660000000000001,9.4,13.6,3.0639999999999996,1,0.956,3 +3,A1 SH,STUART,2809.5,80.671,0.593,9.5,13.25,2.977,1,0.9329999999999999,3 +4,A1 SH,STUART,2810.0,75.971,0.638,8.7,12.35,3.02,1,0.9109999999999999,3 +5,A1 SH,STUART,2810.5,73.955,0.667,6.9,12.25,3.0860000000000003,1,0.889,3 +6,A1 SH,STUART,2811.0,77.962,0.674,6.5,12.45,3.092,1,0.867,3 +7,A1 SH,STUART,2811.5,83.89399999999999,0.667,6.3,12.65,3.123,1,0.8440000000000001,2 +8,A1 SH,STUART,2812.0,84.42399999999999,0.653,6.7,13.05,3.1210000000000004,1,0.8220000000000001,2 +9,A1 SH,STUART,2812.5,83.16,0.642,7.3,12.95,3.127,1,0.8,2 +10,A1 SH,STUART,2813.0,79.063,0.6509999999999999,7.3,12.05,3.147,1,0.778,2 +11,A1 SH,STUART,2813.5,69.002,0.677,6.2,10.8,3.096,1,0.7559999999999999,2 +12,A1 SH,STUART,2814.0,63.983000000000004,0.69,4.4,9.7,3.103,1,0.733,2 +13,A1 SH,STUART,2814.5,61.797,0.675,3.5,9.15,3.1010000000000004,1,0.711,2 +14,A1 SH,STUART,2815.0,61.372,0.6459999999999999,2.8,9.3,3.065,1,0.6890000000000001,2 +15,A1 SH,STUART,2815.5,63.535,0.621,2.8,9.8,2.9819999999999998,1,0.667,2 +16,A1 SH,STUART,2816.0,65.126,0.6,3.3,10.55,2.9139999999999997,1,0.644,2 +17,A1 SH,STUART,2816.5,75.93,0.5760000000000001,3.4,11.9,2.845,1,0.6,2 +18,A1 SH,STUART,2817.0,85.07700000000001,0.584,4.4,12.9,2.8539999999999996,1,0.578,2 +19,A1 SH,STUART,2817.5,89.459,0.598,6.6,13.5,2.986,1,0.556,2 +20,A1 SH,STUART,2818.0,88.619,0.61,7.2,14.8,2.988,1,0.5329999999999999,2 +21,A1 SH,STUART,2818.5,81.593,0.636,6.4,13.9,2.998,1,0.511,2 +22,A1 SH,STUART,2819.0,66.595,0.7020000000000001,2.8,11.4,2.988,1,0.489,2 +23,A1 SH,STUART,2819.5,55.081,0.789,2.7,8.15,3.028,1,0.467,2 +24,A1 SH,STUART,2820.0,48.111999999999995,0.84,1.0,7.5,3.073,1,0.444,2 +25,A1 SH,STUART,2820.5,43.73,0.846,0.4,7.1,3.1460000000000004,1,0.42200000000000004,2 +26,A1 SH,STUART,2821.0,44.097,0.84,0.7,6.65,3.205,1,0.4,2 +27,A1 SH,STUART,2821.5,46.839,0.8420000000000001,0.8,6.6,3.2539999999999996,1,0.37799999999999995,2 +28,A1 SH,STUART,2822.0,50.348,0.843,1.1,6.75,3.23,1,0.35600000000000004,2 +29,A1 SH,STUART,2822.5,57.129,0.8220000000000001,2.2,7.3,3.237,1,0.33299999999999996,2 +30,A1 SH,STUART,2823.0,64.465,0.777,4.4,8.4,3.259,1,0.311,2 +31,A1 SH,STUART,2823.5,70.267,0.7290000000000001,7.1,9.85,3.2889999999999997,1,0.289,2 +32,A1 SH,STUART,2824.0,76.566,0.664,10.7,11.55,3.3810000000000002,1,0.244,2 +33,A1 SH,STUART,2824.5,76.778,0.643,10.7,12.25,3.452,1,0.222,2 +34,A1 SH,STUART,2825.0,73.971,0.632,9.7,12.55,3.3960000000000004,1,0.2,2 +35,A1 SH,STUART,2825.5,74.314,0.622,8.8,13.1,3.1439999999999997,1,0.17800000000000002,2 +36,A1 SH,STUART,2826.0,77.031,0.583,4.8,16.2,3.034,1,0.156,2 +37,A1 SH,STUART,2826.5,74.469,0.517,4.8,19.2,2.931,1,0.133,2 +38,A1 SH,STUART,2827.0,73.327,0.489,6.3,20.35,2.88,1,0.111,3 +39,A1 SH,STUART,2827.5,74.575,0.526,4.9,19.25,2.795,1,0.08900000000000001,3 +40,A1 SH,STUART,2828.0,70.536,0.5579999999999999,6.5,17.05,3.009,1,0.067,3 +41,A1 SH,STUART,2828.5,62.93899999999999,0.528,7.6,18.8,3.073,1,0.044000000000000004,3 +42,A1 SH,STUART,2829.0,57.137,0.511,10.9,19.15,3.313,1,0.022000000000000002,3 +43,A1 LM,STUART,2829.5,47.345,0.584,7.0,16.3,3.5269999999999997,2,1.0,8 +44,A1 LM,STUART,2830.0,35.733000000000004,0.73,6.4,10.2,3.928,2,0.987,8 +45,A1 LM,STUART,2830.5,29.326999999999998,0.873,2.7,7.85,4.33,2,0.9740000000000001,8 +46,A1 LM,STUART,2831.0,28.241999999999997,0.963,1.4,6.3,4.413,2,0.961,8 +47,A1 LM,STUART,2831.5,34.558,1.018,1.8,5.6,4.511,2,0.9470000000000001,8 +48,A1 LM,STUART,2832.0,43.754,1.054,1.8,5.2,4.412,2,0.934,6 +49,A1 LM,STUART,2832.5,53.611999999999995,1.067,1.5,5.05,4.226,2,0.9209999999999999,6 +50,A1 LM,STUART,2833.0,60.718999999999994,1.0390000000000001,1.9,4.85,3.931,2,0.9079999999999999,6 +51,A1 LM,STUART,2833.5,66.538,0.94,2.7,5.45,3.7030000000000003,2,0.895,6 +52,A1 LM,STUART,2834.0,75.52199999999999,0.8009999999999999,4.0,7.3,3.5010000000000003,2,0.882,6 +53,A1 LM,STUART,2834.5,95.979,0.6920000000000001,6.5,9.55,3.346,2,0.868,4 +54,A1 LM,STUART,2835.0,130.26,0.644,8.3,11.15,3.242,2,0.855,4 +55,A1 LM,STUART,2835.5,160.167,0.643,9.3,12.15,3.2939999999999996,2,0.8420000000000001,4 +56,A1 LM,STUART,2836.0,176.528,0.6729999999999999,9.1,12.05,3.298,2,0.8290000000000001,4 +57,A1 LM,STUART,2836.5,175.622,0.72,8.9,12.15,3.3489999999999998,2,0.816,4 +58,A1 LM,STUART,2837.0,153.965,0.7559999999999999,7.6,11.9,3.31,2,0.8029999999999999,4 +59,A1 LM,STUART,2837.5,120.07600000000001,0.7659999999999999,7.2,12.2,3.365,2,0.789,4 +60,A1 LM,STUART,2838.0,91.434,0.787,7.1,12.15,3.392,2,0.7759999999999999,4 +61,A1 LM,STUART,2838.5,69.312,0.8740000000000001,4.6,10.4,3.293,2,0.763,4 +62,A1 LM,STUART,2839.0,54.828,1.0290000000000001,0.8,8.2,3.395,2,0.75,6 +63,A1 LM,STUART,2839.5,50.854,1.149,0.3,6.85,3.5,2,0.737,6 +64,A1 LM,STUART,2840.0,54.632,1.09,1.0,7.4,3.576,2,0.7240000000000001,6 +65,A1 LM,STUART,2840.5,56.835,0.924,4.1,8.45,3.555,2,0.711,6 +66,A1 LM,STUART,2841.0,60.393,0.7879999999999999,7.1,10.05,3.591,2,0.6970000000000001,6 +67,A1 LM,STUART,2841.5,58.94,0.733,8.1,11.15,3.576,2,0.684,6 +68,A1 LM,STUART,2842.0,49.718999999999994,0.754,6.1,10.75,3.6689999999999996,2,0.6709999999999999,6 +69,A1 LM,STUART,2842.5,41.403999999999996,0.8190000000000001,3.5,9.55,3.872,2,0.6579999999999999,6 +70,A1 LM,STUART,2843.0,36.084,0.882,1.6,8.2,4.125,2,0.645,8 +71,A1 LM,STUART,2843.5,29.344,0.897,0.1,7.25,4.23,2,0.632,8 +72,A1 LM,STUART,2844.0,24.072,0.841,-0.6,6.8,4.302,2,0.618,8 +73,A1 LM,STUART,2844.5,22.62,0.733,-2.5,7.65,4.348,2,0.605,8 +74,A1 LM,STUART,2845.0,22.408,0.597,-3.8,9.5,4.29,2,0.5920000000000001,8 +75,A1 LM,STUART,2845.5,21.184,0.469,-2.7,11.05,4.255,2,0.579,8 +76,A1 LM,STUART,2846.0,21.796,0.375,-2.3,13.35,4.213,2,0.5660000000000001,8 +77,A1 LM,STUART,2846.5,23.925,0.314,-1.8,15.1,4.363,2,0.5529999999999999,8 +78,A1 LM,STUART,2847.0,24.464000000000002,0.278,-1.3,16.15,4.495,2,0.539,8 +79,A1 LM,STUART,2847.5,26.039,0.257,-1.9,16.55,4.602,2,0.526,8 +80,A1 LM,STUART,2848.0,27.491,0.247,-2.5,16.45,4.544,2,0.513,8 +81,A1 LM,STUART,2848.5,28.193,0.249,-2.4,16.3,4.587,2,0.5,8 +82,A1 LM,STUART,2849.0,28.634,0.265,-1.9,16.15,4.678,2,0.48700000000000004,8 +83,A1 LM,STUART,2849.5,29.809,0.299,-1.0,15.2,4.8660000000000005,2,0.474,8 +84,A1 LM,STUART,2850.0,31.171999999999997,0.349,-1.5,14.15,4.783,2,0.461,8 +85,A1 LM,STUART,2850.5,33.448,0.418,-1.1,12.65,4.688,2,0.447,8 +86,A1 LM,STUART,2851.0,33.514,0.503,-1.2,11.3,4.628,2,0.434,8 +87,A1 LM,STUART,2851.5,35.146,0.593,-0.5,10.05,4.387,2,0.42100000000000004,8 +88,A1 LM,STUART,2852.0,35.953,0.6709999999999999,-0.7,9.45,4.291,2,0.408,8 +89,A1 LM,STUART,2852.5,35.178000000000004,0.7290000000000001,-0.6,9.0,4.178,2,0.395,8 +90,A1 LM,STUART,2853.0,36.109,0.773,0.1,8.35,4.203,2,0.382,8 +91,A1 LM,STUART,2853.5,38.769,0.82,1.3,7.55,4.262,2,0.368,6 +92,A1 LM,STUART,2854.0,39.510999999999996,0.873,1.3,7.05,4.387,2,0.355,6 +93,A1 LM,STUART,2854.5,40.523,0.927,2.6,6.5,4.006,2,0.342,6 +94,A1 LM,STUART,2855.0,42.693999999999996,0.9640000000000001,2.8,6.8,3.718,2,0.32899999999999996,6 +95,A1 LM,STUART,2855.5,45.297,0.9590000000000001,3.0,7.3,3.594,2,0.316,6 +96,A1 LM,STUART,2856.0,48.145,0.915,3.8,8.2,3.46,2,0.303,6 +97,A1 LM,STUART,2856.5,51.041000000000004,0.862,5.9,8.75,3.333,2,0.289,6 +98,A1 LM,STUART,2857.0,56.125,0.825,7.4,9.3,3.3360000000000003,2,0.276,6 +99,A1 LM,STUART,2857.5,62.205,0.807,6.4,9.9,3.362,2,0.263,4 +100,A1 LM,STUART,2858.0,64.865,0.794,4.7,10.25,3.2439999999999998,2,0.25,4 +101,A1 LM,STUART,2858.5,68.186,0.7709999999999999,4.1,10.25,3.174,2,0.237,4 +102,A1 LM,STUART,2859.0,72.421,0.743,4.1,10.55,3.174,2,0.22399999999999998,4 +103,A1 LM,STUART,2859.5,74.322,0.73,4.5,10.65,3.187,2,0.21100000000000002,4 +104,A1 LM,STUART,2860.0,72.543,0.748,4.1,10.35,3.359,2,0.19699999999999998,4 +105,A1 LM,STUART,2860.5,65.672,0.8140000000000001,3.5,9.05,3.6180000000000003,2,0.184,6 +106,A1 LM,STUART,2861.0,57.153,0.951,1.7,6.75,3.9019999999999997,2,0.171,6 +107,A1 LM,STUART,2861.5,46.056000000000004,1.148,0.1,4.55,4.221,2,0.158,6 +108,A1 LM,STUART,2862.0,37.961,1.324,0.0,3.3,4.561,2,0.145,6 +109,A1 LM,STUART,2862.5,33.579,1.402,-0.2,2.8,4.7989999999999995,2,0.132,6 +110,A1 LM,STUART,2863.0,31.212,1.439,-0.4,2.7,4.874,2,0.11800000000000001,6 +111,A1 LM,STUART,2863.5,30.176,1.486,-0.5,2.55,4.787,2,0.105,6 +112,A1 LM,STUART,2864.0,29.858,1.507,-0.7,2.75,4.622,2,0.092,6 +113,A1 LM,STUART,2864.5,29.923000000000002,1.433,-0.6,3.3,4.375,2,0.079,6 +114,A1 LM,STUART,2865.0,34.428000000000004,1.2790000000000001,0.0,4.0,4.115,2,0.066,6 +115,A1 LM,STUART,2865.5,39.935,1.1340000000000001,0.8,4.6,3.9789999999999996,2,0.053,6 +116,A1 LM,STUART,2866.0,39.935,1.1340000000000001,0.8,4.6,3.9789999999999996,2,0.053,6 +117,A1 LM,STUART,2866.5,46.823,1.05,1.3,5.15,3.727,2,0.039,6 +118,A1 LM,STUART,2867.0,57.968999999999994,1.01,2.0,5.2,3.537,2,0.026000000000000002,6 +119,A1 LM,STUART,2867.5,71.24600000000001,0.9540000000000001,2.3,5.65,3.4819999999999998,2,0.013000000000000001,6 +120,B1 SH,STUART,2868.0,82.54799999999999,0.843,3.2,7.2,3.532,1,1.0,3 +121,B1 SH,STUART,2868.5,92.119,0.718,4.9,8.95,3.484,1,0.968,3 +122,B1 SH,STUART,2869.0,93.564,0.635,7.0,11.1,3.4019999999999997,1,0.935,3 +123,B1 SH,STUART,2869.5,86.26,0.615,9.0,11.9,3.486,1,0.903,3 +124,B1 SH,STUART,2870.0,77.097,0.637,9.5,11.25,3.56,1,0.871,2 +125,B1 SH,STUART,2870.5,67.68,0.6509999999999999,9.2,10.7,3.4730000000000003,1,0.8390000000000001,2 +126,B1 SH,STUART,2871.0,64.04899999999999,0.639,8.5,10.65,3.4010000000000002,1,0.8059999999999999,2 +127,B1 SH,STUART,2871.5,67.566,0.621,7.5,11.45,3.307,1,0.774,2 +128,B1 SH,STUART,2872.0,69.72800000000001,0.604,7.1,12.45,3.28,1,0.742,2 +129,B1 SH,STUART,2872.5,67.96600000000001,0.5820000000000001,8.3,13.45,3.253,1,0.71,2 +130,B1 SH,STUART,2873.0,65.803,0.565,9.6,13.5,3.284,1,0.677,2 +131,B1 SH,STUART,2873.5,62.351000000000006,0.575,10.1,11.85,3.405,1,0.645,2 +132,B1 SH,STUART,2874.0,59.512,0.621,10.1,9.65,3.5039999999999996,1,0.613,2 +133,B1 SH,STUART,2874.5,61.176,0.691,9.9,8.15,3.5869999999999997,1,0.581,2 +134,B1 SH,STUART,2875.0,65.75399999999999,0.7509999999999999,9.6,7.7,3.605,1,0.5479999999999999,2 +135,B1 SH,STUART,2875.5,66.66,0.768,9.0,8.2,3.505,1,0.516,2 +136,B1 SH,STUART,2876.0,64.604,0.742,8.0,8.9,3.411,1,0.484,2 +137,B1 SH,STUART,2876.5,61.699,0.696,7.0,9.2,3.319,1,0.452,2 +138,B1 SH,STUART,2877.0,58.353,0.657,5.6,9.3,3.265,1,0.419,2 +139,B1 SH,STUART,2877.5,55.928999999999995,0.64,4.2,9.2,3.167,1,0.387,2 +140,B1 SH,STUART,2878.0,57.413999999999994,0.64,4.0,9.1,3.181,1,0.355,2 +141,B1 SH,STUART,2878.5,60.393,0.64,3.8,9.3,3.133,1,0.32299999999999995,2 +142,B1 SH,STUART,2879.0,65.90100000000001,0.636,4.2,9.9,3.1630000000000003,1,0.29,2 +143,B1 SH,STUART,2879.5,71.385,0.635,5.8,10.8,3.1310000000000002,1,0.258,2 +144,B1 SH,STUART,2880.0,75.816,0.625,4.9,13.55,2.997,1,0.226,2 +145,B1 SH,STUART,2880.5,75.334,0.5870000000000001,5.6,15.9,2.938,1,0.19399999999999998,2 +146,B1 SH,STUART,2881.0,72.69,0.5579999999999999,4.8,18.5,2.969,1,0.129,3 +147,B1 SH,STUART,2881.5,68.635,0.5579999999999999,6.9,19.45,3.1039999999999996,1,0.09699999999999999,3 +148,B1 SH,STUART,2882.0,60.695,0.52,7.5,21.25,3.147,1,0.065,3 +149,B1 SH,STUART,2882.5,51.645,0.501,5.6,18.1,3.3539999999999996,1,0.032,3 +150,B1 LM,STUART,2883.0,41.918,0.5479999999999999,7.0,10.9,3.764,2,1.0,8 +151,B1 LM,STUART,2883.5,32.991,0.633,7.7,6.35,4.109,2,0.968,8 +152,B1 LM,STUART,2884.0,28.258000000000003,0.705,5.0,6.1,4.154,2,0.935,8 +153,B1 LM,STUART,2884.5,26.635,0.769,4.1,5.35,4.321000000000001,2,0.903,8 +154,B1 LM,STUART,2885.0,25.541,0.847,3.6,4.8,4.476,2,0.871,8 +155,B1 LM,STUART,2885.5,23.795,0.948,2.3,4.45,4.565,2,0.8390000000000001,8 +156,B1 LM,STUART,2886.0,20.719,1.061,2.2,3.5,4.615,2,0.8059999999999999,8 +157,B1 LM,STUART,2886.5,18.499000000000002,1.139,2.4,3.2,4.696000000000001,2,0.774,8 +158,B1 LM,STUART,2887.0,19.445999999999998,1.1179999999999999,1.5,4.65,4.668,2,0.742,8 +159,B1 LM,STUART,2887.5,21.388,1.0190000000000001,1.0,7.1,4.579,2,0.71,8 +160,B1 LM,STUART,2888.0,24.178,0.9079999999999999,1.2,9.2,4.292,2,0.677,8 +161,B1 LM,STUART,2888.5,27.638,0.812,0.0,11.1,4.046,2,0.645,8 +162,B1 LM,STUART,2889.0,31.669,0.7240000000000001,0.9,11.45,3.822,2,0.613,8 +163,B1 LM,STUART,2889.5,39.389,0.627,3.4,11.2,3.6289999999999996,2,0.581,7 +164,B1 LM,STUART,2890.0,49.385,0.535,6.4,11.5,3.517,2,0.5479999999999999,7 +165,B1 LM,STUART,2890.5,58.516000000000005,0.488,9.0,11.4,3.4739999999999998,2,0.516,4 +166,B1 LM,STUART,2891.0,66.619,0.511,9.2,10.8,3.613,2,0.484,4 +167,B1 LM,STUART,2891.5,67.296,0.602,6.4,9.5,3.862,2,0.452,4 +168,B1 LM,STUART,2892.0,57.798,0.745,3.7,8.25,4.052,2,0.419,6 +169,B1 LM,STUART,2892.5,48.169,0.912,1.1,7.45,4.2410000000000005,2,0.387,6 +170,B1 LM,STUART,2893.0,41.437,1.045,0.4,6.3,4.476,2,0.355,6 +171,B1 LM,STUART,2893.5,39.348,1.117,0.1,5.35,4.712,2,0.32299999999999995,6 +172,B1 LM,STUART,2894.0,49.312,1.1440000000000001,1.0,4.5,4.56,2,0.29,6 +173,B1 LM,STUART,2894.5,61.983999999999995,1.143,0.7,4.85,4.605,2,0.258,6 +174,B1 LM,STUART,2895.0,73.506,1.122,0.9,5.75,4.574,2,0.226,6 +175,B1 LM,STUART,2895.5,74.208,1.095,0.3,6.85,4.478,2,0.19399999999999998,6 +176,B1 LM,STUART,2896.0,67.819,1.072,-0.7,7.55,4.444,2,0.161,6 +177,B1 LM,STUART,2896.5,61.625,1.057,-1.2,7.4,4.439,2,0.129,6 +178,B1 LM,STUART,2897.0,61.625,1.057,-1.2,7.4,4.439,2,0.129,6 +179,B1 LM,STUART,2897.5,55.481,1.041,-0.9,6.55,4.335,2,0.09699999999999999,6 +180,B1 LM,STUART,2898.0,57.251000000000005,0.98,-0.1,5.75,3.907,2,0.065,6 +181,B1 LM,STUART,2898.5,67.28,0.84,-0.6,7.1,3.58,2,0.032,8 +182,B2 SH,STUART,2899.0,76.02,0.6859999999999999,0.7,9.45,3.23,1,1.0,3 +183,B2 SH,STUART,2899.5,84.45700000000001,0.603,2.5,12.45,2.967,1,0.9470000000000001,3 +184,B2 SH,STUART,2900.0,89.01899999999999,0.595,4.6,14.9,2.7939999999999996,1,0.895,3 +185,B2 SH,STUART,2900.5,89.93299999999999,0.591,3.9,18.55,2.7889999999999997,1,0.8420000000000001,3 +186,B2 SH,STUART,2901.0,89.38600000000001,0.539,4.5,22.55,2.861,1,0.789,3 +187,B2 SH,STUART,2901.5,89.427,0.479,6.2,25.4,2.935,1,0.737,3 +188,B2 SH,STUART,2902.0,87.51700000000001,0.461,7.6,24.4,3.128,1,0.684,3 +189,B2 SH,STUART,2902.5,83.74700000000001,0.485,8.7,23.15,3.284,1,0.632,3 +190,B2 SH,STUART,2903.0,78.304,0.541,6.1,21.25,3.332,1,0.579,3 +191,B2 SH,STUART,2903.5,71.858,0.635,8.5,15.95,3.485,1,0.526,3 +192,B2 SH,STUART,2904.0,64.70100000000001,0.737,5.0,15.7,3.471,1,0.474,3 +193,B2 SH,STUART,2904.5,64.293,0.752,1.7,17.15,3.45,1,0.42100000000000004,3 +194,B2 SH,STUART,2905.0,67.158,0.6859999999999999,-0.3,19.95,3.2760000000000002,1,0.368,3 +195,B2 SH,STUART,2905.5,72.47800000000001,0.631,0.2,20.4,3.1710000000000003,1,0.316,3 +196,B2 SH,STUART,2906.0,78.068,0.614,5.0,18.1,3.252,1,0.21100000000000002,3 +197,B2 SH,STUART,2906.5,73.008,0.5920000000000001,2.4,20.1,3.175,1,0.158,3 +198,B2 SH,STUART,2907.0,64.64399999999999,0.5429999999999999,1.7,22.35,3.302,1,0.105,3 +199,B2 SH,STUART,2907.5,49.801,0.5379999999999999,0.0,20.8,3.551,1,0.053,3 +200,B2 LM,STUART,2908.0,35.937,0.628,-2.8,16.8,3.96,2,1.0,8 +201,B2 LM,STUART,2908.5,24.203000000000003,0.743,-0.3,12.35,4.454,2,0.963,8 +202,B2 LM,STUART,2909.0,15.985999999999999,0.777,-0.2,11.5,4.657,2,0.9259999999999999,8 +203,B2 LM,STUART,2909.5,12.036,0.773,-0.5,10.55,4.593999999999999,2,0.889,8 +204,B2 LM,STUART,2910.0,12.745999999999999,0.787,-1.2,9.2,4.437,2,0.852,8 +205,B2 LM,STUART,2910.5,14.843,0.809,-1.6,7.7,4.351,2,0.815,8 +206,B2 LM,STUART,2911.0,17.087,0.8059999999999999,-1.0,6.8,4.242,2,0.778,8 +207,B2 LM,STUART,2911.5,17.977,0.765,0.3,6.45,4.105,2,0.741,8 +208,B2 LM,STUART,2912.0,18.834,0.701,-0.1,7.15,4.279,2,0.7040000000000001,8 +209,B2 LM,STUART,2912.5,19.258,0.644,0.4,7.4,4.669,2,0.667,8 +210,B2 LM,STUART,2913.0,19.062,0.61,0.6,7.8,5.19,2,0.63,8 +211,B2 LM,STUART,2913.5,18.637999999999998,0.6,1.8,7.6,5.527,2,0.593,8 +212,B2 LM,STUART,2914.0,19.462,0.598,3.4,6.8,6.321000000000001,2,0.556,8 +213,B2 LM,STUART,2914.5,19.552,0.581,3.1,6.95,6.16,2,0.519,8 +214,B2 LM,STUART,2915.0,20.653000000000002,0.529,0.9,8.65,5.865,2,0.48100000000000004,8 +215,B2 LM,STUART,2915.5,23.371,0.45,-1.0,11.3,5.315,2,0.444,8 +216,B2 LM,STUART,2916.0,25.468000000000004,0.391,-1.3,13.75,4.918,2,0.40700000000000003,8 +217,B2 LM,STUART,2916.5,26.291999999999998,0.377,-2.3,14.85,4.521,2,0.37,8 +218,B2 LM,STUART,2917.0,27.736,0.41100000000000003,-3.6,14.1,4.4430000000000005,2,0.33299999999999996,8 +219,B2 LM,STUART,2917.5,29.784000000000002,0.48200000000000004,-3.1,11.85,4.3469999999999995,2,0.29600000000000004,8 +220,B2 LM,STUART,2918.0,31.041,0.578,-2.2,9.4,4.416,2,0.259,8 +221,B2 LM,STUART,2918.5,30.837,0.6829999999999999,-0.4,7.4,4.394,2,0.222,8 +222,B2 LM,STUART,2919.0,32.64,0.807,1.0,5.6,4.343,2,0.185,6 +223,B2 LM,STUART,2919.5,33.571,0.9420000000000001,1.6,4.5,4.086,2,0.14800000000000002,6 +224,B2 LM,STUART,2920.0,39.56,1.003,1.9,4.55,3.8110000000000004,2,0.111,6 +225,B2 LM,STUART,2920.5,47.475,0.9309999999999999,1.5,6.15,3.625,2,0.07400000000000001,6 +226,B2 LM,STUART,2921.0,56.443000000000005,0.821,2.3,8.05,3.3930000000000002,2,0.037000000000000005,8 +227,B3 SH,STUART,2921.5,64.79899999999999,0.7509999999999999,3.4,9.6,3.12,1,1.0,3 +228,B3 SH,STUART,2922.0,69.72,0.711,3.0,12.4,3.03,1,0.95,3 +229,B3 SH,STUART,2922.5,72.51100000000001,0.637,3.5,16.35,2.984,1,0.9,3 +230,B3 SH,STUART,2923.0,74.69800000000001,0.525,5.4,20.8,2.915,1,0.85,3 +231,B3 SH,STUART,2923.5,74.69800000000001,0.525,5.4,20.8,2.915,1,0.85,3 +232,B3 SH,STUART,2924.0,73.425,0.45799999999999996,5.2,21.6,2.92,1,0.8,3 +233,B3 SH,STUART,2924.5,71.328,0.486,3.1,17.35,2.995,1,0.75,3 +234,B3 SH,STUART,2925.0,68.937,0.5870000000000001,4.1,13.25,3.122,1,0.7,3 +235,B3 SH,STUART,2925.5,66.562,0.6709999999999999,1.3,13.25,3.2430000000000003,1,0.65,2 +236,B3 SH,STUART,2926.0,64.63600000000001,0.6629999999999999,3.2,13.3,3.324,1,0.6,2 +237,B3 SH,STUART,2926.5,66.619,0.625,4.0,13.6,3.33,1,0.55,2 +238,B3 SH,STUART,2927.0,66.619,0.625,4.0,13.6,3.33,1,0.55,2 +239,B3 SH,STUART,2927.5,65.624,0.635,3.2,12.4,3.3089999999999997,1,0.5,2 +240,B3 SH,STUART,2928.0,65.322,0.68,3.3,9.65,3.315,1,0.45,2 +241,B3 SH,STUART,2928.5,67.035,0.7070000000000001,2.4,8.6,3.2319999999999998,1,0.4,2 +242,B3 SH,STUART,2929.0,68.194,0.693,3.0,8.8,3.157,1,0.35,2 +243,B3 SH,STUART,2929.5,69.149,0.6459999999999999,3.0,10.4,3.034,1,0.3,2 +244,B3 SH,STUART,2930.0,72.20100000000001,0.588,3.2,13.2,3.052,1,0.25,2 +245,B3 SH,STUART,2930.5,73.77600000000001,0.542,4.4,16.0,3.1319999999999997,1,0.2,2 +246,B3 SH,STUART,2931.0,72.609,0.525,5.5,17.55,3.31,1,0.15,3 +247,B3 SH,STUART,2931.5,66.86399999999999,0.55,5.3,16.55,3.625,1,0.1,3 +248,B3 SH,STUART,2932.0,53.702,0.62,5.7,13.75,4.003,1,0.05,3 +249,B3 LM,STUART,2932.5,40.474000000000004,0.713,4.7,11.15,4.2780000000000005,2,1.0,8 +250,B3 LM,STUART,2933.0,28.12,0.774,2.2,10.5,4.537,2,0.9,8 +251,B3 LM,STUART,2933.5,20.213,0.769,-1.1,10.95,4.6819999999999995,2,0.8,8 +252,B3 LM,STUART,2934.0,19.192999999999998,0.732,-1.0,11.1,4.546,2,0.7,8 +253,B3 LM,STUART,2934.5,20.449,0.6990000000000001,-0.7,10.65,4.386,2,0.6,8 +254,B3 LM,STUART,2935.0,21.355,0.679,-0.1,9.95,4.28,2,0.5,8 +255,B3 LM,STUART,2935.5,21.641,0.6679999999999999,1.3,8.95,4.221,2,0.4,8 +256,B3 LM,STUART,2936.0,24.203000000000003,0.653,2.6,8.3,4.099,2,0.3,8 +257,B3 LM,STUART,2936.5,34.574,0.613,2.4,9.0,3.66,2,0.2,8 +258,B3 LM,STUART,2937.0,45.231,0.5479999999999999,2.3,10.45,3.4960000000000004,2,0.1,8 +259,B4 SH,STUART,2937.5,56.427,0.498,2.9,11.35,3.338,1,1.0,2 +260,B4 SH,STUART,2938.0,67.06,0.504,1.7,11.65,3.135,1,0.9440000000000001,2 +261,B4 SH,STUART,2938.5,70.83800000000001,0.5579999999999999,2.0,10.8,3.012,1,0.889,2 +262,B4 SH,STUART,2939.0,69.932,0.612,3.3,10.05,3.0660000000000003,1,0.833,2 +263,B4 SH,STUART,2939.5,74.52600000000001,0.633,4.1,10.25,3.109,1,0.778,2 +264,B4 SH,STUART,2940.0,77.611,0.626,5.0,11.0,3.063,1,0.722,2 +265,B4 SH,STUART,2940.5,78.59,0.605,5.9,11.55,3.092,1,0.667,2 +266,B4 SH,STUART,2941.0,76.729,0.591,5.7,11.95,3.051,1,0.611,2 +267,B4 SH,STUART,2941.5,74.11,0.608,3.7,10.95,3.07,1,0.556,2 +268,B4 SH,STUART,2942.0,66.407,0.653,2.2,9.6,2.997,1,0.5,2 +269,B4 SH,STUART,2942.5,64.081,0.693,1.4,8.6,3.093,1,0.444,2 +270,B4 SH,STUART,2943.0,65.885,0.705,0.9,8.55,3.1060000000000003,1,0.389,2 +271,B4 SH,STUART,2943.5,70.29899999999999,0.696,1.4,9.0,3.085,1,0.33299999999999996,2 +272,B4 SH,STUART,2944.0,70.29899999999999,0.696,1.4,9.0,3.085,1,0.33299999999999996,2 +273,B4 SH,STUART,2944.5,74.551,0.677,3.1,9.65,3.0660000000000003,1,0.278,2 +274,B4 SH,STUART,2945.0,79.65899999999999,0.643,3.4,12.5,2.9019999999999997,1,0.222,2 +275,B4 SH,STUART,2945.5,80.402,0.573,-2.8,19.3,2.9819999999999998,1,0.16699999999999998,3 +276,B4 SH,STUART,2946.0,74.649,0.483,-0.5,23.95,3.14,1,0.111,3 +277,B4 SH,STUART,2946.5,63.428999999999995,0.461,0.2,24.2,3.3939999999999997,1,0.055999999999999994,3 +278,B4 LM,STUART,2947.0,47.916000000000004,0.598,-7.6,18.9,3.762,2,1.0,8 +279,B4 LM,STUART,2947.5,32.469,0.912,-1.4,9.8,4.314,2,0.929,8 +280,B4 LM,STUART,2948.0,20.718000000000004,1.222,-2.9,7.85,4.863,2,0.857,8 +281,B4 LM,STUART,2948.5,15.015,1.2329999999999999,-1.6,6.4,4.813,2,0.7859999999999999,8 +282,B4 LM,STUART,2949.0,14.084000000000001,1.084,-1.1,6.55,4.644,2,0.7140000000000001,8 +283,B4 LM,STUART,2949.5,15.937000000000001,0.9620000000000001,-0.4,7.4,4.6339999999999995,2,0.643,8 +284,B4 LM,STUART,2950.0,19.348,0.9009999999999999,-1.0,7.9,4.545,2,0.5710000000000001,8 +285,B4 LM,STUART,2950.5,21.469,0.9059999999999999,-1.1,6.75,4.5760000000000005,2,0.5,8 +286,B4 LM,STUART,2951.0,22.587,0.9690000000000001,-1.4,5.5,4.527,2,0.429,6 +287,B4 LM,STUART,2951.5,25.721,1.079,-0.9,4.45,4.512,2,0.35700000000000004,6 +288,B4 LM,STUART,2952.0,29.45,1.2,0.0,4.0,4.437,2,0.28600000000000003,6 +289,B4 LM,STUART,2952.5,36.313,1.169,-3.3,6.95,3.97,2,0.214,9 +290,B4 LM,STUART,2953.0,49.49100000000001,0.909,-8.9,13.85,3.695,2,0.14300000000000002,9 +291,B5 SH,STUART,2953.5,69.222,0.469,-6.0,27.9,3.3510000000000004,1,1.0,3 +292,B5 SH,STUART,2954.0,70.968,0.444,-2.5,28.85,3.49,1,0.75,3 +293,B5 SH,STUART,2954.5,65.37899999999999,0.501,-0.3,22.75,3.9,1,0.5,3 +294,B5 SH,STUART,2955.0,54.093,0.56,-0.5,16.75,4.126,1,0.25,3 +295,B5 LM,STUART,2955.5,41.633,0.541,3.9,11.55,4.482,2,1.0,8 +296,B5 LM,STUART,2956.0,33.644,0.439,3.8,11.7,4.707,2,0.976,8 +297,B5 LM,STUART,2956.5,28.976999999999997,0.321,1.3,14.45,4.447,2,0.951,8 +298,B5 LM,STUART,2957.0,24.611,0.23199999999999998,-1.1,17.25,4.481,2,0.927,8 +299,B5 LM,STUART,2957.5,24.154,0.184,-2.9,19.65,4.327,2,0.902,8 +300,B5 LM,STUART,2958.0,25.639,0.17300000000000001,-2.4,20.5,4.302,2,0.878,8 +301,B5 LM,STUART,2958.5,25.956999999999997,0.191,-2.4,19.9,4.294,2,0.8540000000000001,8 +302,B5 LM,STUART,2959.0,38.965,0.266,-2.1,17.05,4.228,2,0.805,8 +303,B5 LM,STUART,2959.5,45.354,0.301,0.2,14.8,4.127,2,0.78,8 +304,B5 LM,STUART,2960.0,53.645,0.327,2.6,12.6,3.908,2,0.7559999999999999,8 +305,B5 LM,STUART,2960.5,60.163999999999994,0.33799999999999997,3.8,12.2,3.74,2,0.732,8 +306,B5 LM,STUART,2961.0,64.032,0.33399999999999996,5.5,13.15,3.5380000000000003,2,0.7070000000000001,7 +307,B5 LM,STUART,2961.5,66.774,0.32299999999999995,7.9,14.75,3.5580000000000003,2,0.6829999999999999,7 +308,B5 LM,STUART,2962.0,68.423,0.313,8.1,15.75,3.4760000000000004,2,0.659,7 +309,B5 LM,STUART,2962.5,63.501999999999995,0.318,6.1,14.75,3.682,2,0.634,7 +310,B5 LM,STUART,2963.0,57.903999999999996,0.349,2.8,12.9,3.937,2,0.61,7 +311,B5 LM,STUART,2963.5,52.935,0.415,2.3,10.25,4.133,2,0.585,8 +312,B5 LM,STUART,2964.0,45.125,0.507,2.3,8.45,4.248,2,0.561,8 +313,B5 LM,STUART,2964.5,39.927,0.605,3.5,6.75,4.468,2,0.537,8 +314,B5 LM,STUART,2965.0,36.215,0.703,2.4,6.0,4.575,2,0.512,8 +315,B5 LM,STUART,2965.5,31.253,0.787,2.3,4.45,4.5569999999999995,2,0.488,8 +316,B5 LM,STUART,2966.0,28.445999999999998,0.8320000000000001,2.2,3.4,4.573,2,0.46299999999999997,8 +317,B5 LM,STUART,2966.5,27.296,0.821,1.2,4.4,4.79,2,0.439,8 +318,B5 LM,STUART,2967.0,28.944000000000003,0.755,-0.4,7.3,4.887,2,0.415,8 +319,B5 LM,STUART,2967.5,31.596,0.659,-1.6,11.0,4.824,2,0.39,9 +320,B5 LM,STUART,2968.0,33.211999999999996,0.574,-3.1,14.45,4.765,2,0.366,9 +321,B5 LM,STUART,2968.5,34.689,0.517,-3.0,16.4,4.766,2,0.341,9 +322,B5 LM,STUART,2969.0,39.266,0.493,-1.9,16.15,4.705,2,0.317,9 +323,B5 LM,STUART,2969.5,50.103,0.499,-2.0,14.6,4.453,2,0.293,9 +324,B5 LM,STUART,2970.0,65.167,0.525,-1.6,13.1,4.3660000000000005,2,0.268,9 +325,B5 LM,STUART,2970.5,76.436,0.557,-0.6,11.7,4.289,2,0.244,8 +326,B5 LM,STUART,2971.0,92.88600000000001,0.628,-0.2,9.4,4.272,2,0.195,8 +327,B5 LM,STUART,2971.5,99.64299999999999,0.6829999999999999,-0.3,7.95,4.395,2,0.171,6 +328,B5 LM,STUART,2972.0,101.585,0.757,0.0,6.5,4.51,2,0.146,6 +329,B5 LM,STUART,2972.5,95.775,0.85,1.6,4.9,4.53,2,0.122,6 +330,B5 LM,STUART,2973.0,87.036,0.951,2.1,3.95,4.456,2,0.098,6 +331,B5 LM,STUART,2973.5,72.331,1.0190000000000001,2.6,3.6,4.056,2,0.073,6 +332,B5 LM,STUART,2974.0,58.858999999999995,0.991,3.4,3.9,3.7119999999999997,2,0.049,6 +333,B5 LM,STUART,2974.5,60.931999999999995,0.857,1.3,7.35,3.3710000000000004,2,0.024,8 +334,C SH,STUART,2975.0,67.655,0.675,-0.8,14.4,3.1310000000000002,1,1.0,3 +335,C SH,STUART,2975.5,77.219,0.528,6.8,20.9,3.008,1,0.977,3 +336,C SH,STUART,2976.0,82.115,0.45899999999999996,10.6,24.2,2.988,1,0.953,3 +337,C SH,STUART,2976.5,84.865,0.446,9.4,23.7,3.134,1,0.93,3 +338,C SH,STUART,2977.0,84.384,0.449,13.3,21.45,3.409,1,0.907,3 +339,C SH,STUART,2977.5,81.77199999999999,0.44299999999999995,14.8,20.9,3.483,1,0.884,3 +340,C SH,STUART,2978.0,78.998,0.444,16.5,20.65,3.438,1,0.8370000000000001,3 +341,C SH,STUART,2978.5,79.896,0.457,14.9,20.15,3.423,1,0.8140000000000001,3 +342,C SH,STUART,2979.0,79.194,0.462,14.8,19.9,3.45,1,0.7909999999999999,3 +343,C SH,STUART,2979.5,78.99,0.451,13.5,19.65,3.3930000000000002,1,0.767,3 +344,C SH,STUART,2980.0,79.21,0.441,15.1,18.95,3.475,1,0.7440000000000001,3 +345,C SH,STUART,2980.5,78.1,0.451,15.6,17.5,3.478,1,0.721,3 +346,C SH,STUART,2981.0,78.59,0.489,14.3,16.75,3.505,1,0.698,3 +347,C SH,STUART,2981.5,79.439,0.544,12.7,15.25,3.478,1,0.674,3 +348,C SH,STUART,2982.0,81.29899999999999,0.5760000000000001,11.5,14.65,3.4530000000000003,1,0.6509999999999999,3 +349,C SH,STUART,2982.5,78.933,0.494,11.9,14.85,3.4789999999999996,1,0.605,3 +350,C SH,STUART,2983.0,79.471,0.441,13.4,16.3,3.4939999999999998,1,0.581,3 +351,C SH,STUART,2983.5,81.895,0.431,14.2,16.8,3.4410000000000003,1,0.5579999999999999,3 +352,C SH,STUART,2984.0,82.76799999999999,0.46799999999999997,14.3,16.05,3.4930000000000003,1,0.535,3 +353,C SH,STUART,2984.5,79.02199999999999,0.537,12.9,15.05,3.5,1,0.512,2 +354,C SH,STUART,2985.0,76.74600000000001,0.601,11.4,13.8,3.4410000000000003,1,0.488,2 +355,C SH,STUART,2985.5,73.066,0.638,11.1,13.25,3.426,1,0.465,2 +356,C SH,STUART,2986.0,70.35600000000001,0.6509999999999999,11.0,13.1,3.447,1,0.442,2 +357,C SH,STUART,2986.5,74.608,0.621,10.5,14.85,3.3989999999999996,1,0.395,2 +358,C SH,STUART,2987.0,73.008,0.585,11.1,15.15,3.3930000000000002,1,0.37200000000000005,2 +359,C SH,STUART,2987.5,70.438,0.546,12.1,15.15,3.4389999999999996,1,0.349,2 +360,C SH,STUART,2988.0,68.08,0.5,13.5,14.65,3.478,1,0.326,2 +361,C SH,STUART,2988.5,66.75,0.46,13.6,15.2,3.4610000000000003,1,0.302,2 +362,C SH,STUART,2989.0,69.45100000000001,0.455,13.4,14.8,3.4939999999999998,1,0.27899999999999997,2 +363,C SH,STUART,2989.5,75.946,0.494,14.2,14.0,3.5410000000000004,1,0.256,2 +364,C SH,STUART,2990.0,80.344,0.556,11.8,13.6,3.522,1,0.233,2 +365,C SH,STUART,2990.5,83.772,0.616,10.4,12.9,3.4760000000000004,1,0.18600000000000003,2 +366,C SH,STUART,2991.0,84.76700000000001,0.618,10.7,12.55,3.39,1,0.163,2 +367,C SH,STUART,2991.5,84.09,0.616,9.4,13.4,3.2889999999999997,1,0.14,2 +368,C SH,STUART,2992.0,86.62799999999999,0.601,8.8,14.4,3.19,1,0.11599999999999999,3 +369,C SH,STUART,2992.5,90.43,0.556,2.0,21.4,3.045,1,0.09300000000000001,3 +370,C SH,STUART,2993.0,87.07700000000001,0.498,2.0,26.4,3.088,1,0.07,3 +371,C SH,STUART,2993.5,76.623,0.479,5.3,28.45,3.2239999999999998,1,0.047,3 +372,C SH,STUART,2994.0,62.768,0.546,3.2,26.3,3.3339999999999996,1,0.023,3 +373,C LM,STUART,2994.5,43.738,0.703,1.8,19.3,3.8760000000000003,2,1.0,8 +374,C LM,STUART,2995.0,27.859,0.855,6.9,11.75,4.508,2,0.993,8 +375,C LM,STUART,2995.5,18.034000000000002,0.879,5.3,9.55,4.815,2,0.985,8 +376,C LM,STUART,2996.0,13.203,0.83,3.0,9.1,4.863,2,0.978,8 +377,C LM,STUART,2996.5,12.762,0.767,2.0,8.9,5.024,2,0.97,8 +378,C LM,STUART,2997.0,14.843,0.7020000000000001,1.8,9.2,4.6160000000000005,2,0.963,8 +379,C LM,STUART,2997.5,19.087,0.644,0.4,10.4,4.172,2,0.955,8 +380,C LM,STUART,2998.0,19.087,0.644,0.4,10.4,4.172,2,0.955,8 +381,C LM,STUART,2998.5,25.206999999999997,0.601,-0.2,10.7,3.97,2,0.948,8 +382,C LM,STUART,2999.0,27.997,0.5870000000000001,1.1,10.25,3.9330000000000003,2,0.94,8 +383,C LM,STUART,2999.5,28.822,0.602,2.2,10.0,3.875,2,0.9329999999999999,8 +384,C LM,STUART,3000.0,28.618000000000002,0.622,1.9,10.35,3.969,2,0.925,8 +385,C LM,STUART,3000.5,24.815,0.612,0.7,11.15,4.118,2,0.9179999999999999,8 +386,C LM,STUART,3001.0,23.371,0.575,0.2,11.8,4.243,2,0.91,8 +387,C LM,STUART,3001.5,23.052,0.542,0.1,12.35,4.196000000000001,2,0.903,8 +388,C LM,STUART,3002.0,23.109,0.522,-0.1,12.15,4.192,2,0.8959999999999999,8 +389,C LM,STUART,3002.5,24.138,0.511,-0.3,12.05,3.978,2,0.888,8 +390,C LM,STUART,3003.0,24.448,0.511,-0.1,11.75,3.975,2,0.8809999999999999,8 +391,C LM,STUART,3003.5,25.419,0.523,0.0,11.6,3.9619999999999997,2,0.873,8 +392,C LM,STUART,3004.0,26.724,0.56,-0.7,11.35,3.99,2,0.866,8 +393,C LM,STUART,3004.5,29.213,0.623,-0.8,10.7,3.885,2,0.858,8 +394,C LM,STUART,3005.0,34.036,0.6859999999999999,0.4,9.4,3.8160000000000003,2,0.851,8 +395,C LM,STUART,3005.5,38.157,0.716,1.7,7.75,3.66,2,0.843,8 +396,C LM,STUART,3006.0,40.45,0.701,1.8,6.8,3.5439999999999996,2,0.836,7 +397,C LM,STUART,3006.5,41.576,0.662,3.5,6.45,3.392,2,0.828,7 +398,C LM,STUART,3007.0,40.123000000000005,0.633,3.7,7.35,3.24,2,0.821,7 +399,C LM,STUART,3007.5,36.663000000000004,0.632,3.4,8.1,3.2119999999999997,2,0.813,7 +400,C LM,STUART,3008.0,32.705999999999996,0.65,3.8,8.3,3.253,2,0.8059999999999999,6 +401,C LM,STUART,3008.5,30.323,0.672,3.4,8.7,3.2889999999999997,2,0.799,6 +402,C LM,STUART,3009.0,28.601,0.6940000000000001,3.0,9.4,3.3139999999999996,2,0.7909999999999999,6 +403,C LM,STUART,3009.5,28.169,0.721,2.4,9.7,3.262,2,0.784,6 +404,C LM,STUART,3010.0,29.441999999999997,0.7559999999999999,1.4,9.8,3.31,2,0.7759999999999999,6 +405,C LM,STUART,3010.5,30.878,0.795,0.7,9.55,3.359,2,0.769,6 +406,C LM,STUART,3011.0,32.150999999999996,0.8320000000000001,0.1,9.35,3.409,2,0.7609999999999999,6 +407,C LM,STUART,3011.5,33.677,0.856,0.4,9.1,3.417,2,0.754,6 +408,C LM,STUART,3012.0,33.701,0.872,1.1,8.95,3.444,2,0.746,6 +409,C LM,STUART,3012.5,35.105,0.889,1.5,8.75,3.466,2,0.7390000000000001,6 +410,C LM,STUART,3013.0,37.104,0.914,1.6,8.6,3.49,2,0.731,6 +411,C LM,STUART,3013.5,37.349000000000004,0.9390000000000001,2.1,7.95,3.418,2,0.7240000000000001,6 +412,C LM,STUART,3014.0,37.936,0.9520000000000001,2.4,7.7,3.5039999999999996,2,0.716,6 +413,C LM,STUART,3014.5,39.086999999999996,0.953,2.1,7.75,3.511,2,0.7090000000000001,6 +414,C LM,STUART,3015.0,38.059,0.951,1.7,7.55,3.55,2,0.701,6 +415,C LM,STUART,3015.5,37.202,0.9520000000000001,2.2,7.3,3.603,2,0.6940000000000001,6 +416,C LM,STUART,3016.0,37.218,0.951,1.8,7.5,3.675,2,0.687,6 +417,C LM,STUART,3016.5,37.781,0.9490000000000001,1.4,7.6,3.741,2,0.679,6 +418,C LM,STUART,3017.0,40.164,0.948,1.5,7.35,3.735,2,0.672,6 +419,C LM,STUART,3017.5,40.955999999999996,0.95,1.6,7.3,3.747,2,0.664,6 +420,C LM,STUART,3018.0,41.013000000000005,0.9520000000000001,1.5,7.25,3.64,2,0.657,6 +421,C LM,STUART,3018.5,42.547,0.95,1.9,7.15,3.6830000000000003,2,0.649,6 +422,C LM,STUART,3019.0,41.192,0.945,2.0,7.0,3.6439999999999997,2,0.642,6 +423,C LM,STUART,3019.5,42.726000000000006,0.941,2.3,7.15,3.7039999999999997,2,0.634,6 +424,C LM,STUART,3020.0,44.407,0.9420000000000001,3.4,7.0,3.695,2,0.627,6 +425,C LM,STUART,3020.5,45.387,0.946,3.8,6.8,3.7880000000000003,2,0.619,6 +426,C LM,STUART,3021.0,45.052,0.945,2.6,7.5,3.917,2,0.612,6 +427,C LM,STUART,3021.5,46.129,0.935,2.4,7.4,3.948,2,0.604,6 +428,C LM,STUART,3022.0,47.826,0.925,2.5,7.05,4.016,2,0.597,6 +429,C LM,STUART,3022.5,50.053999999999995,0.925,2.3,6.75,3.935,2,0.59,6 +430,C LM,STUART,3023.0,55.562,0.9329999999999999,1.8,6.9,3.9739999999999998,2,0.5820000000000001,6 +431,C LM,STUART,3023.5,63.028999999999996,0.9470000000000001,2.0,6.8,3.859,2,0.575,6 +432,C LM,STUART,3024.0,75.399,0.966,1.9,6.45,3.681,2,0.5670000000000001,6 +433,C LM,STUART,3024.5,102.116,0.987,0.2,6.9,3.5610000000000004,2,0.56,6 +434,C LM,STUART,3025.0,140.778,0.993,-0.4,7.0,3.513,2,0.552,6 +435,C LM,STUART,3025.5,183.358,0.981,-0.3,7.35,3.437,2,0.545,6 +436,C LM,STUART,3026.0,213.99900000000002,0.977,0.2,7.8,3.412,2,0.537,6 +437,C LM,STUART,3026.5,220.41299999999998,1.004,0.0,8.0,3.528,2,0.53,4 +438,C LM,STUART,3027.0,200.30599999999998,1.0270000000000001,0.0,8.0,3.6710000000000003,2,0.522,4 +439,C LM,STUART,3027.5,162.149,0.9990000000000001,-0.2,8.5,3.7460000000000004,2,0.515,4 +440,C LM,STUART,3028.0,121.20200000000001,0.95,0.2,9.2,3.892,2,0.507,4 +441,C LM,STUART,3028.5,92.805,0.9159999999999999,1.3,9.95,3.924,2,0.5,4 +442,C LM,STUART,3029.0,77.758,0.894,1.9,10.65,3.9530000000000003,2,0.493,4 +443,C LM,STUART,3029.5,67.623,0.879,2.9,10.85,3.889,2,0.485,4 +444,C LM,STUART,3030.0,62.376000000000005,0.873,2.5,11.45,3.799,2,0.478,4 +445,C LM,STUART,3030.5,59.463,0.873,2.1,11.25,3.773,2,0.47,4 +446,C LM,STUART,3031.0,55.211000000000006,0.872,2.7,10.45,3.784,2,0.46299999999999997,6 +447,C LM,STUART,3031.5,51.727,0.866,2.3,10.35,3.787,2,0.455,6 +448,C LM,STUART,3032.0,52.38,0.858,2.1,10.75,3.7760000000000002,2,0.44799999999999995,6 +449,C LM,STUART,3032.5,53.122,0.851,2.5,11.05,3.7239999999999998,2,0.44,6 +450,C LM,STUART,3033.0,51.245,0.8440000000000001,2.7,11.25,3.697,2,0.433,6 +451,C LM,STUART,3033.5,52.208,0.836,1.5,11.75,3.653,2,0.425,6 +452,C LM,STUART,3034.0,54.95,0.826,1.3,12.05,3.647,2,0.418,8 +453,C LM,STUART,3034.5,54.43600000000001,0.8170000000000001,2.0,12.0,3.65,2,0.41,8 +454,C LM,STUART,3035.0,54.81100000000001,0.81,1.8,12.1,3.678,2,0.40299999999999997,8 +455,C LM,STUART,3035.5,55.603,0.8009999999999999,1.6,12.2,3.6439999999999997,2,0.396,8 +456,C LM,STUART,3036.0,54.288999999999994,0.785,1.3,12.75,3.656,2,0.38799999999999996,8 +457,C LM,STUART,3036.5,52.38,0.768,2.0,13.0,3.5980000000000003,2,0.381,6 +458,C LM,STUART,3037.0,53.645,0.758,2.0,13.7,3.582,2,0.373,6 +459,C LM,STUART,3037.5,53.93,0.757,2.1,13.75,3.5810000000000004,2,0.366,4 +460,C LM,STUART,3038.0,56.071999999999996,0.755,2.9,13.75,3.645,2,0.358,4 +461,C LM,STUART,3038.5,59.016999999999996,0.75,4.0,13.7,3.694,2,0.35100000000000003,4 +462,C LM,STUART,3039.0,62.144,0.742,4.4,14.1,3.65,2,0.34299999999999997,4 +463,C LM,STUART,3039.5,64.814,0.73,4.8,14.2,3.66,2,0.336,4 +464,C LM,STUART,3040.0,66.705,0.7140000000000001,5.6,14.6,3.6889999999999996,2,0.32799999999999996,4 +465,C LM,STUART,3040.5,67.568,0.695,6.5,15.45,3.674,2,0.321,4 +466,C LM,STUART,3041.0,67.683,0.6759999999999999,6.7,15.65,3.603,2,0.313,4 +467,C LM,STUART,3041.5,67.683,0.662,6.0,15.4,3.562,2,0.306,4 +468,C LM,STUART,3042.0,67.683,0.6659999999999999,5.7,15.25,3.57,2,0.299,4 +469,C LM,STUART,3042.5,67.683,0.701,6.0,15.2,3.603,2,0.29100000000000004,4 +470,C LM,STUART,3043.0,67.683,0.778,5.1,15.65,3.537,2,0.284,4 +471,C LM,STUART,3043.5,67.683,0.882,4.9,15.75,3.5469999999999997,2,0.276,4 +472,C LM,STUART,3044.0,67.683,0.973,4.4,15.8,3.533,2,0.26899999999999996,4 +473,C LM,STUART,3044.5,67.683,1.0170000000000001,3.5,16.25,3.495,2,0.261,4 +474,A1 LM,CRAWFORD,2972.5,49.675,0.845,3.905,11.175,3.265,2,1.0,8 +475,A1 LM,CRAWFORD,2973.0,34.435,0.879,3.085,8.175,3.8310000000000004,2,0.991,8 +476,A1 LM,CRAWFORD,2973.5,26.178,0.92,2.615,4.945,4.306,2,0.981,8 +477,A1 LM,CRAWFORD,2974.0,19.463,0.9670000000000001,0.82,3.82,4.578,2,0.972,8 +478,A1 LM,CRAWFORD,2974.5,19.26,0.995,0.32,3.63,4.643,2,0.9620000000000001,8 +479,A1 LM,CRAWFORD,2975.0,19.985,1.008,0.06,4.32,4.614,2,0.953,8 +480,A1 LM,CRAWFORD,2975.5,22.298000000000002,1.002,-0.01,5.5,4.4910000000000005,2,0.943,8 +481,A1 LM,CRAWFORD,2976.0,24.611,0.956,0.05,6.87,4.369,2,0.934,8 +482,A1 LM,CRAWFORD,2976.5,24.677,0.8240000000000001,0.31,6.94,4.047,2,0.915,8 +483,A1 LM,CRAWFORD,2977.0,24.945999999999998,0.667,0.965,5.915,3.8930000000000002,2,0.9059999999999999,8 +484,A1 LM,CRAWFORD,2977.5,29.31,0.5589999999999999,2.11,6.15,3.52,2,0.8959999999999999,6 +485,A1 LM,CRAWFORD,2978.0,37.321999999999996,0.522,3.375,8.445,3.125,2,0.887,7 +486,A1 LM,CRAWFORD,2978.5,42.141999999999996,0.51,3.985,10.785,2.843,2,0.877,7 +487,A1 LM,CRAWFORD,2979.0,52.434,0.49200000000000005,4.42,13.15,2.674,2,0.868,7 +488,A1 LM,CRAWFORD,2979.5,63.181000000000004,0.473,5.18,14.13,2.6439999999999997,2,0.858,7 +489,A1 LM,CRAWFORD,2980.0,69.405,0.465,5.52,14.56,2.6630000000000003,2,0.8490000000000001,4 +490,A1 LM,CRAWFORD,2980.5,77.785,0.475,5.82,14.94,2.68,2,0.84,4 +491,A1 LM,CRAWFORD,2981.0,83.57700000000001,0.469,5.965,15.395,2.6660000000000004,2,0.83,4 +492,A1 LM,CRAWFORD,2981.5,84.05799999999999,0.513,6.025,15.855,2.622,2,0.821,4 +493,A1 LM,CRAWFORD,2982.0,81.82,0.544,5.95,16.05,2.609,2,0.8109999999999999,4 +494,A1 LM,CRAWFORD,2982.5,80.257,0.563,5.74,16.1,2.6260000000000003,2,0.802,4 +495,A1 LM,CRAWFORD,2983.0,79.833,0.579,5.135,15.715,2.662,2,0.792,4 +496,A1 LM,CRAWFORD,2983.5,80.32300000000001,0.583,4.565,15.275,2.693,2,0.7829999999999999,4 +497,A1 LM,CRAWFORD,2984.0,84.704,0.59,4.365,15.165,2.7110000000000003,2,0.774,4 +498,A1 LM,CRAWFORD,2984.5,96.67399999999999,0.596,4.725,15.565,2.7439999999999998,2,0.764,4 +499,A1 LM,CRAWFORD,2985.0,112.662,0.609,4.88,15.71,2.824,2,0.755,4 +500,A1 LM,CRAWFORD,2985.5,131.484,0.634,5.11,15.6,2.935,2,0.745,4 +501,A1 LM,CRAWFORD,2986.0,138.16899999999998,0.659,5.33,15.1,3.0,2,0.736,4 +502,A1 LM,CRAWFORD,2986.5,135.045,0.682,5.1,14.46,3.048,2,0.726,4 +503,A1 LM,CRAWFORD,2987.0,117.726,0.7070000000000001,4.415,13.315,3.097,2,0.7170000000000001,4 +504,A1 LM,CRAWFORD,2987.5,98.382,0.7290000000000001,3.395,11.695,3.193,2,0.708,4 +505,A1 LM,CRAWFORD,2988.0,91.348,0.7709999999999999,3.235,10.985,3.3080000000000003,2,0.698,4 +506,A1 LM,CRAWFORD,2988.5,87.05,0.831,3.21,10.64,3.4930000000000003,2,0.6890000000000001,4 +507,A1 LM,CRAWFORD,2989.0,82.98,0.9279999999999999,2.835,10.115,3.5260000000000002,2,0.679,4 +508,A1 LM,CRAWFORD,2989.5,67.264,1.0190000000000001,0.475,8.435,3.217,2,0.67,6 +509,A1 LM,CRAWFORD,2990.0,57.068999999999996,1.047,-2.385,7.115,3.157,2,0.66,6 +510,A1 LM,CRAWFORD,2990.5,46.873999999999995,1.0659999999999998,-3.97,6.6,3.159,2,0.6509999999999999,6 +511,A1 LM,CRAWFORD,2991.0,39.325,1.06,-3.69,7.15,3.2239999999999998,2,0.642,6 +512,A1 LM,CRAWFORD,2991.5,43.946000000000005,1.042,-2.73,7.29,3.272,2,0.632,6 +513,A1 LM,CRAWFORD,2992.0,51.73,1.005,-0.9,7.98,3.29,2,0.623,6 +514,A1 LM,CRAWFORD,2992.5,58.373999999999995,0.956,1.46,9.41,3.2769999999999997,2,0.613,6 +515,A1 LM,CRAWFORD,2993.0,67.75399999999999,0.904,3.985,11.545,3.2960000000000003,2,0.604,4 +516,A1 LM,CRAWFORD,2993.5,71.206,0.8740000000000001,5.045,12.915,3.3280000000000003,2,0.594,4 +517,A1 LM,CRAWFORD,2994.0,69.188,0.852,4.86,12.85,3.33,2,0.585,4 +518,A1 LM,CRAWFORD,2994.5,58.452,0.841,3.455,11.265,3.332,2,0.575,6 +519,A1 LM,CRAWFORD,2995.0,38.715,0.816,2.185,9.855,3.365,2,0.5660000000000001,6 +520,A1 LM,CRAWFORD,2995.5,30.541,0.8009999999999999,0.96,8.76,3.4760000000000004,2,0.557,8 +521,A1 LM,CRAWFORD,2996.0,21.684,0.792,-0.04,8.28,3.7739999999999996,2,0.547,8 +522,A1 LM,CRAWFORD,2996.5,21.252,0.7929999999999999,-0.505,9.225,4.041,2,0.5379999999999999,8 +523,A1 LM,CRAWFORD,2997.0,23.116999999999997,0.7929999999999999,-0.555,9.895,4.292,2,0.528,8 +524,A1 LM,CRAWFORD,2997.5,28.85,0.7909999999999999,-0.46,9.89,4.371,2,0.519,8 +525,A1 LM,CRAWFORD,2998.0,36.226,0.7879999999999999,-0.085,9.175,4.112,2,0.509,8 +526,A1 LM,CRAWFORD,2998.5,42.83,0.8009999999999999,0.41,8.49,3.91,2,0.5,6 +527,A1 LM,CRAWFORD,2999.0,46.846000000000004,0.82,1.255,8.275,3.793,2,0.491,6 +528,A1 LM,CRAWFORD,2999.5,48.133,0.845,1.77,8.29,3.486,2,0.48100000000000004,6 +529,A1 LM,CRAWFORD,3000.0,43.162,0.8740000000000001,1.35,8.64,3.263,2,0.47200000000000003,6 +530,A1 LM,CRAWFORD,3000.5,36.586,0.92,1.01,8.74,3.187,2,0.462,6 +531,A1 LM,CRAWFORD,3001.0,32.746,0.955,0.625,8.535,3.173,2,0.45299999999999996,6 +532,A1 LM,CRAWFORD,3001.5,30.956999999999997,0.9740000000000001,0.565,8.555,3.315,2,0.44299999999999995,6 +533,A1 LM,CRAWFORD,3002.0,30.765,0.981,0.545,8.575,3.4410000000000003,2,0.434,6 +534,A1 LM,CRAWFORD,3002.5,31.265,0.987,0.625,8.425,3.6180000000000003,2,0.425,6 +535,A1 LM,CRAWFORD,3003.0,33.124,0.9940000000000001,0.755,8.045,3.943,2,0.415,6 +536,A1 LM,CRAWFORD,3003.5,35.211,0.997,0.635,7.555,4.07,2,0.406,6 +537,A1 LM,CRAWFORD,3004.0,36.385999999999996,0.988,0.125,7.135,3.885,2,0.396,6 +538,A1 LM,CRAWFORD,3004.5,38.016999999999996,0.951,-0.175,6.875,3.654,2,0.387,6 +539,A1 LM,CRAWFORD,3005.0,41.016000000000005,0.903,0.055,6.825,3.438,2,0.377,6 +540,A1 LM,CRAWFORD,3005.5,49.653999999999996,0.8540000000000001,1.52,7.51,3.33,2,0.368,6 +541,A1 LM,CRAWFORD,3006.0,62.068000000000005,0.799,3.1,9.13,3.2089999999999996,2,0.358,6 +542,A1 LM,CRAWFORD,3006.5,71.222,0.74,4.0,10.98,3.0869999999999997,2,0.349,6 +543,A1 LM,CRAWFORD,3007.0,73.309,0.691,4.015,12.425,2.98,2,0.34,4 +544,A1 LM,CRAWFORD,3007.5,69.469,0.627,3.19,13.37,2.904,2,0.33,4 +545,A1 LM,CRAWFORD,3008.0,65.857,0.5589999999999999,2.1,14.08,2.859,2,0.321,6 +546,A1 LM,CRAWFORD,3008.5,58.369,0.504,0.715,14.235,2.83,2,0.311,6 +547,A1 LM,CRAWFORD,3009.0,56.125,0.435,-0.775,13.415,2.786,2,0.302,6 +548,A1 LM,CRAWFORD,3009.5,56.769,0.37799999999999995,-1.155,12.805,2.7260000000000004,2,0.292,8 +549,A1 LM,CRAWFORD,3010.0,62.586999999999996,0.298,-0.18,12.87,2.588,2,0.28300000000000003,6 +550,A1 LM,CRAWFORD,3010.5,64.67399999999999,0.252,0.24,14.42,2.465,2,0.27399999999999997,7 +551,A1 LM,CRAWFORD,3011.0,64.253,0.212,0.24,16.36,2.374,2,0.264,7 +552,A1 LM,CRAWFORD,3011.5,61.553000000000004,0.166,-0.295,18.395,2.329,2,0.255,7 +553,A1 LM,CRAWFORD,3012.0,60.221000000000004,0.114,-0.59,19.27,2.315,2,0.245,7 +554,A1 LM,CRAWFORD,3012.5,59.11600000000001,0.09300000000000001,-0.655,19.655,2.302,2,0.23600000000000002,7 +555,A1 LM,CRAWFORD,3013.0,57.997,0.081,-0.8,19.69,2.258,2,0.226,7 +556,A1 LM,CRAWFORD,3013.5,57.363,0.091,-1.105,19.095,2.2430000000000003,2,0.217,7 +557,A1 LM,CRAWFORD,3014.0,57.863,0.14400000000000002,-1.27,18.12,2.261,2,0.20800000000000002,7 +558,A1 LM,CRAWFORD,3014.5,59.038000000000004,0.20600000000000002,-1.26,17.03,2.326,2,0.198,7 +559,A1 LM,CRAWFORD,3015.0,60.213,0.29,-1.04,16.68,2.4090000000000003,2,0.18899999999999997,7 +560,A1 LM,CRAWFORD,3015.5,61.16,0.368,-0.14,16.68,2.781,2,0.179,6 +561,A1 LM,CRAWFORD,3016.0,58.46,0.46799999999999997,-0.25,15.21,3.327,2,0.17,6 +562,A1 LM,CRAWFORD,3016.5,53.48,0.564,0.36,11.47,3.7960000000000003,2,0.16,8 +563,A1 LM,CRAWFORD,3017.0,51.692,0.657,0.825,8.125,4.062,2,0.151,6 +564,A1 LM,CRAWFORD,3017.5,67.238,0.807,1.7,7.13,4.173,2,0.142,6 +565,A1 LM,CRAWFORD,3018.0,74.796,0.89,2.905,7.335,4.19,2,0.132,6 +566,A1 LM,CRAWFORD,3018.5,75.743,0.925,3.055,7.765,4.302,2,0.12300000000000001,6 +567,A1 LM,CRAWFORD,3019.0,70.991,0.9279999999999999,2.325,7.785,4.444,2,0.113,6 +568,A1 LM,CRAWFORD,3019.5,57.348,0.929,1.355,7.395,4.492,2,0.10400000000000001,6 +569,A1 LM,CRAWFORD,3020.0,46.213,0.929,0.67,7.43,4.385,2,0.094,6 +570,A1 LM,CRAWFORD,3020.5,42.11600000000001,0.9259999999999999,0.19,7.17,4.2010000000000005,2,0.085,6 +571,A1 LM,CRAWFORD,3021.0,44.925,0.9179999999999999,-0.19,6.69,4.093,2,0.075,6 +572,A1 LM,CRAWFORD,3021.5,55.903,0.912,0.07,5.72,4.034,2,0.066,6 +573,A1 LM,CRAWFORD,3022.0,66.196,0.9059999999999999,0.495,5.375,3.958,2,0.057,6 +574,A1 LM,CRAWFORD,3022.5,73.52600000000001,0.894,1.44,5.26,3.82,2,0.047,8 +575,B1 SH,CRAWFORD,3032.0,72.392,0.7090000000000001,-0.74,18.41,2.6289999999999996,1,0.125,3 +576,B1 SH,CRAWFORD,3032.5,69.928,0.792,-0.69,19.32,2.616,1,0.063,3 +577,B1 LM,CRAWFORD,3033.0,64.72,0.8490000000000001,-0.96,16.33,2.9139999999999997,2,1.0,8 +578,B1 LM,CRAWFORD,3033.5,52.445,0.892,0.91,11.35,3.292,2,0.977,6 +579,B1 LM,CRAWFORD,3034.0,43.361999999999995,0.93,-0.02,6.92,3.571,2,0.955,8 +580,B1 LM,CRAWFORD,3034.5,42.06399999999999,0.9740000000000001,0.015,5.495,3.435,2,0.909,8 +581,B1 LM,CRAWFORD,3035.0,45.641999999999996,0.956,0.005,5.475,3.375,2,0.8859999999999999,6 +582,B1 LM,CRAWFORD,3035.5,53.266000000000005,0.932,-0.105,5.545,3.299,2,0.8640000000000001,6 +583,B1 LM,CRAWFORD,3036.0,59.043,0.894,0.17,6.99,3.114,2,0.841,6 +584,B1 LM,CRAWFORD,3036.5,62.331,0.8340000000000001,-0.245,9.835,2.813,2,0.818,6 +585,B1 LM,CRAWFORD,3037.0,60.946000000000005,0.884,-1.69,16.08,2.745,2,0.795,6 +586,B1 LM,CRAWFORD,3037.5,53.913999999999994,0.9179999999999999,-0.72,19.54,3.1519999999999997,2,0.773,8 +587,B1 LM,CRAWFORD,3038.0,45.287,0.922,-0.86,18.44,3.9619999999999997,2,0.75,8 +588,B1 LM,CRAWFORD,3038.5,30.049,0.925,0.445,13.565,4.571000000000001,2,0.727,8 +589,B1 LM,CRAWFORD,3039.0,23.017,0.9470000000000001,0.54,9.59,4.806,2,0.705,8 +590,B1 LM,CRAWFORD,3039.5,21.228,0.973,-0.03,7.57,4.824,2,0.682,8 +591,B1 LM,CRAWFORD,3040.0,20.109,0.985,0.225,6.725,4.81,2,0.659,8 +592,B1 LM,CRAWFORD,3040.5,19.256,0.995,0.415,6.505,4.859,2,0.636,8 +593,B1 LM,CRAWFORD,3041.0,18.38,0.9990000000000001,0.44,6.29,4.8919999999999995,2,0.614,8 +594,B1 LM,CRAWFORD,3041.5,17.275,0.987,0.185,6.075,4.91,2,0.591,8 +595,B1 LM,CRAWFORD,3042.0,16.39,0.975,0.015,5.815,4.88,2,0.568,8 +596,B1 LM,CRAWFORD,3042.5,16.197,0.963,-0.205,5.445,4.834,2,0.545,8 +597,B1 LM,CRAWFORD,3043.0,16.469,0.9570000000000001,-0.225,5.335,4.76,2,0.523,8 +598,B1 LM,CRAWFORD,3043.5,20.38,0.973,-0.295,5.255,4.669,2,0.5,8 +599,B1 LM,CRAWFORD,3044.0,31.86,1.005,-0.185,5.045,4.547,2,0.47700000000000004,6 +600,B1 LM,CRAWFORD,3044.5,39.608000000000004,1.0390000000000001,0.44,5.16,4.5169999999999995,2,0.455,6 +601,B1 LM,CRAWFORD,3045.0,43.291000000000004,1.064,0.96,5.09,4.488,2,0.43200000000000005,6 +602,B1 LM,CRAWFORD,3045.5,44.001000000000005,1.089,1.295,4.875,4.396,2,0.409,6 +603,B1 LM,CRAWFORD,3046.0,38.574,1.112,0.7,4.09,4.275,2,0.386,6 +604,B1 LM,CRAWFORD,3046.5,35.19,1.128,0.195,3.575,4.245,2,0.364,6 +605,B1 LM,CRAWFORD,3047.0,32.946,1.131,-0.215,3.205,4.434,2,0.341,6 +606,B1 LM,CRAWFORD,3047.5,31.613000000000003,1.128,-0.095,3.545,4.405,2,0.318,6 +607,B1 LM,CRAWFORD,3048.0,32.113,1.092,-0.005,4.715,4.329,2,0.295,8 +608,B1 LM,CRAWFORD,3048.5,32.368,1.052,0.29,5.42,4.285,2,0.273,8 +609,B1 LM,CRAWFORD,3049.0,31.506999999999998,0.978,0.405,5.865,4.224,2,0.25,8 +610,B1 LM,CRAWFORD,3049.5,30.849,0.88,0.445,6.595,4.04,2,0.22699999999999998,8 +611,B1 LM,CRAWFORD,3050.0,29.953000000000003,0.772,0.91,7.82,3.451,2,0.205,8 +612,B1 LM,CRAWFORD,3050.5,28.875999999999998,0.723,1.24,9.64,3.141,2,0.182,8 +613,B1 LM,CRAWFORD,3051.0,28.228,0.705,1.21,10.47,3.2060000000000004,2,0.159,8 +614,B1 LM,CRAWFORD,3051.5,28.263,0.693,1.005,10.355,3.38,2,0.136,8 +615,B1 LM,CRAWFORD,3052.0,28.754,0.693,0.47,9.35,3.6460000000000004,2,0.114,8 +616,B1 LM,CRAWFORD,3052.5,34.26,0.6940000000000001,0.34,7.94,3.9739999999999998,2,0.091,8 +617,B1 LM,CRAWFORD,3053.0,45.01,0.6940000000000001,0.485,6.185,4.2410000000000005,2,0.068,8 +618,B1 LM,CRAWFORD,3053.5,55.98,0.7070000000000001,0.665,5.945,4.093,2,0.045,8 +619,B1 LM,CRAWFORD,3054.0,67.146,0.7170000000000001,0.965,6.695,3.67,2,0.023,8 +620,B2 SH,CRAWFORD,3054.5,80.0,0.708,1.965,8.815,3.361,1,1.0,2 +621,B2 SH,CRAWFORD,3055.0,85.05,0.69,3.215,10.515,3.16,1,0.95,2 +622,B2 SH,CRAWFORD,3055.5,83.946,0.659,3.965,11.115,3.178,1,0.9,2 +623,B2 SH,CRAWFORD,3056.0,80.973,0.623,4.61,10.99,3.2110000000000003,1,0.85,2 +624,B2 SH,CRAWFORD,3056.5,78.782,0.5920000000000001,4.845,10.905,3.213,1,0.8,2 +625,B2 SH,CRAWFORD,3057.0,76.082,0.574,4.82,10.73,3.2310000000000003,1,0.75,2 +626,B2 SH,CRAWFORD,3057.5,72.925,0.562,4.535,10.405,3.217,1,0.7,2 +627,B2 SH,CRAWFORD,3058.0,72.04899999999999,0.55,4.24,10.55,3.187,1,0.65,2 +628,B2 SH,CRAWFORD,3058.5,71.391,0.535,4.115,11.005,3.128,1,0.6,2 +629,B2 SH,CRAWFORD,3059.0,70.751,0.527,4.055,11.765,3.036,1,0.55,2 +630,B2 SH,CRAWFORD,3059.5,71.26100000000001,0.5329999999999999,4.235,12.565,3.0069999999999997,1,0.5,2 +631,B2 SH,CRAWFORD,3060.0,73.11,0.518,4.44,12.8,2.978,1,0.45,2 +632,B2 SH,CRAWFORD,3060.5,75.425,0.491,3.815,12.085,2.903,1,0.4,2 +633,B2 SH,CRAWFORD,3061.0,76.828,0.47,3.265,11.525,2.687,1,0.35,2 +634,B2 SH,CRAWFORD,3061.5,75.04,0.45799999999999996,3.16,11.69,2.58,1,0.3,2 +635,B2 SH,CRAWFORD,3062.0,70.288,0.449,3.695,12.535,2.5340000000000003,1,0.25,2 +636,B2 LM,CRAWFORD,3062.5,66.266,0.44299999999999995,4.505,13.995,2.553,1,0.2,2 +637,B2 LM,CRAWFORD,3063.0,60.79,0.441,6.07,16.34,2.679,1,0.15,2 +638,B2 LM,CRAWFORD,3063.5,54.67,0.444,6.25,16.74,3.35,1,0.1,3 +639,B2 LM,CRAWFORD,3064.0,48.093999999999994,0.445,5.995,16.615,3.865,1,0.05,3 +640,B2 LM,CRAWFORD,3064.5,41.062,0.445,3.425,13.955,4.24,2,1.0,8 +641,B2 LM,CRAWFORD,3065.0,39.046,0.455,1.725,12.915,4.507,2,0.9640000000000001,8 +642,B2 LM,CRAWFORD,3065.5,38.169000000000004,0.45799999999999996,1.1,12.79,4.354,2,0.929,8 +643,B2 LM,CRAWFORD,3066.0,40.493,0.465,0.895,13.365,4.293,2,0.893,9 +644,B2 LM,CRAWFORD,3066.5,43.948,0.45899999999999996,0.68,13.98,4.248,2,0.857,9 +645,B2 LM,CRAWFORD,3067.0,46.49100000000001,0.423,0.57,14.45,4.266,2,0.821,9 +646,B2 LM,CRAWFORD,3067.5,47.21,0.392,0.565,14.945,4.331,2,0.7859999999999999,9 +647,B2 LM,CRAWFORD,3068.0,46.788999999999994,0.34600000000000003,0.765,15.325,4.395,2,0.75,9 +648,B2 LM,CRAWFORD,3068.5,45.912,0.325,0.985,15.625,4.397,2,0.7140000000000001,9 +649,B2 LM,CRAWFORD,3069.0,45.70399999999999,0.304,1.205,15.925,4.383,2,0.679,9 +650,B2 LM,CRAWFORD,3069.5,45.527,0.295,1.27,15.89,4.276,2,0.643,9 +651,B2 LM,CRAWFORD,3070.0,44.887,0.289,1.155,15.315,4.123,2,0.607,9 +652,B2 LM,CRAWFORD,3070.5,44.23,0.29,0.815,14.205,3.95,2,0.5710000000000001,8 +653,B2 LM,CRAWFORD,3071.0,44.273999999999994,0.281,0.55,12.84,3.785,2,0.536,8 +654,B2 LM,CRAWFORD,3071.5,45.221000000000004,0.247,0.545,11.605,3.647,2,0.5,8 +655,B2 LM,CRAWFORD,3072.0,46.396,0.16699999999999998,1.685,11.385,3.431,2,0.46399999999999997,8 +656,B2 LM,CRAWFORD,3072.5,46.888000000000005,0.11800000000000001,2.92,12.76,3.2,2,0.429,8 +657,B2 LM,CRAWFORD,3073.0,46.475,0.069,4.4,16.76,2.968,2,0.39299999999999996,7 +658,B2 LM,CRAWFORD,3073.5,46.738,0.042,5.065,20.085,2.815,2,0.35700000000000004,7 +659,B2 LM,CRAWFORD,3074.0,47.913999999999994,0.033,4.815,20.915,2.8480000000000003,2,0.321,7 +660,B2 LM,CRAWFORD,3074.5,51.596000000000004,0.04,4.485,20.755,2.99,2,0.28600000000000003,7 +661,B2 LM,CRAWFORD,3075.0,62.89,0.102,4.42,17.02,3.4739999999999998,2,0.25,7 +662,B2 LM,CRAWFORD,3075.5,80.38,0.22,3.955,12.965,4.067,2,0.214,7 +663,B2 LM,CRAWFORD,3076.0,105.725,0.34700000000000003,2.42,7.33,4.271,2,0.179,6 +664,B2 LM,CRAWFORD,3076.5,131.069,0.524,1.655,5.355,3.838,2,0.14300000000000002,6 +665,B2 LM,CRAWFORD,3077.0,145.018,0.636,-0.905,7.135,3.2030000000000003,2,0.107,8 +666,B2 LM,CRAWFORD,3077.5,131.376,0.726,-1.94,12.26,2.8160000000000003,2,0.071,8 +667,B3 SH,CRAWFORD,3078.0,110.21,0.792,0.27,14.14,2.678,2,0.036000000000000004,8 +668,B3 SH,CRAWFORD,3078.5,89.045,0.826,3.14,13.7,2.773,1,1.0,3 +669,B3 SH,CRAWFORD,3079.0,73.807,0.8079999999999999,4.795,11.855,3.3710000000000004,1,0.9440000000000001,3 +670,B3 SH,CRAWFORD,3079.5,73.158,0.7809999999999999,4.755,10.905,3.4930000000000003,1,0.889,2 +671,B3 SH,CRAWFORD,3080.0,73.195,0.763,3.975,10.205,3.432,1,0.833,2 +672,B3 SH,CRAWFORD,3080.5,72.325,0.748,3.68,10.0,3.387,1,0.778,2 +673,B3 SH,CRAWFORD,3081.0,71.221,0.742,3.33,9.69,3.3739999999999997,1,0.722,2 +674,B3 SH,CRAWFORD,3081.5,70.563,0.742,2.76,9.25,3.3289999999999997,1,0.667,2 +675,B3 SH,CRAWFORD,3082.0,71.51899999999999,0.733,1.75,10.04,3.145,1,0.611,2 +676,B3 SH,CRAWFORD,3082.5,74.062,0.722,2.32,12.64,2.945,1,0.556,2 +677,B3 SH,CRAWFORD,3083.0,77.061,0.71,2.765,15.055,2.7760000000000002,1,0.5,2 +678,B3 SH,CRAWFORD,3083.5,78.693,0.695,3.04,15.66,2.793,1,0.444,2 +679,B3 SH,CRAWFORD,3084.0,79.192,0.6829999999999999,2.505,14.075,2.951,1,0.389,2 +680,B3 SH,CRAWFORD,3084.5,79.192,0.6829999999999999,2.505,14.075,2.951,1,0.389,2 +681,B3 SH,CRAWFORD,3085.0,78.999,0.662,2.395,12.335,2.984,1,0.33299999999999996,2 +682,B3 SH,CRAWFORD,3085.5,78.11399999999999,0.64,2.395,11.095,2.909,1,0.278,2 +683,B3 SH,CRAWFORD,3086.0,77.24600000000001,0.625,2.705,12.075,2.708,1,0.222,2 +684,B3 SH,CRAWFORD,3086.5,76.369,0.62,2.305,15.615,2.6010000000000004,1,0.16699999999999998,3 +685,B3 SH,CRAWFORD,3087.0,72.301,0.633,0.98,21.27,2.759,1,0.111,3 +686,B3 SH,CRAWFORD,3087.5,61.107,0.667,-1.74,21.21,3.8489999999999998,1,0.055999999999999994,3 +687,B3 LM,CRAWFORD,3088.0,41.148999999999994,0.68,-2.295,18.875,4.854,2,1.0,8 +688,B3 LM,CRAWFORD,3088.5,28.419,0.6859999999999999,-0.92,14.54,5.0360000000000005,2,0.938,8 +689,B3 LM,CRAWFORD,3089.0,22.526999999999997,0.687,0.36,10.24,5.044,2,0.875,8 +690,B3 LM,CRAWFORD,3089.5,18.459,0.684,2.27,8.16,4.931,2,0.813,8 +691,B3 LM,CRAWFORD,3090.0,17.345,0.679,2.67,8.23,4.547,2,0.75,8 +692,B3 LM,CRAWFORD,3090.5,17.617,0.6759999999999999,2.855,8.725,4.328,2,0.688,9 +693,B3 LM,CRAWFORD,3091.0,19.292,0.664,2.695,9.465,4.2989999999999995,2,0.625,8 +694,B3 LM,CRAWFORD,3091.5,21.572,0.655,2.535,9.705,4.301,2,0.563,8 +695,B3 LM,CRAWFORD,3092.0,22.975,0.653,1.95,9.21,4.319,2,0.5,8 +696,B3 LM,CRAWFORD,3092.5,23.921999999999997,0.65,1.34,8.59,4.305,2,0.43799999999999994,8 +697,B3 LM,CRAWFORD,3093.0,24.869,0.657,0.63,7.42,4.291,2,0.375,8 +698,B3 LM,CRAWFORD,3093.5,27.64,0.669,0.42,6.02,4.216,2,0.313,8 +699,B3 LM,CRAWFORD,3094.0,34.058,0.67,0.44,4.4,4.109,2,0.25,8 +700,B3 LM,CRAWFORD,3094.5,41.489,0.652,1.11,4.03,3.815,2,0.188,8 +701,B3 LM,CRAWFORD,3095.0,51.235,0.631,1.73,5.19,3.444,2,0.125,8 +702,B4 SH,CRAWFORD,3095.5,55.601000000000006,0.61,2.42,7.82,3.1460000000000004,2,0.063,2 +703,B4 SH,CRAWFORD,3096.0,59.512,0.601,3.715,10.375,2.935,1,1.0,2 +704,B4 SH,CRAWFORD,3096.5,62.055,0.598,4.13,12.01,2.844,1,0.95,2 +705,B4 SH,CRAWFORD,3097.0,64.37,0.5920000000000001,3.83,12.15,2.7680000000000002,1,0.9,2 +706,B4 SH,CRAWFORD,3097.5,65.773,0.5870000000000001,3.32,11.31,2.708,1,0.85,2 +707,B4 SH,CRAWFORD,3098.0,66.036,0.593,2.635,9.895,2.6630000000000003,1,0.8,2 +708,B4 SH,CRAWFORD,3098.5,64.712,0.597,2.65,9.32,2.616,1,0.75,2 +709,B4 SH,CRAWFORD,3099.0,64.039,0.6,2.545,8.775,2.603,1,0.7,2 +710,B4 SH,CRAWFORD,3099.5,64.332,0.61,2.57,8.69,2.589,1,0.65,2 +711,B4 SH,CRAWFORD,3100.0,68.247,0.601,2.545,9.105,2.531,1,0.6,2 +712,B4 SH,CRAWFORD,3100.5,75.809,0.583,2.99,10.63,2.4859999999999998,1,0.55,2 +713,B4 SH,CRAWFORD,3101.0,84.73899999999999,0.5589999999999999,3.69,12.42,2.488,1,0.5,2 +714,B4 SH,CRAWFORD,3101.5,95.76799999999999,0.541,4.595,14.775,2.52,1,0.45,2 +715,B4 SH,CRAWFORD,3102.0,94.175,0.529,4.575,15.465,2.6,1,0.4,2 +716,B4 SH,CRAWFORD,3102.5,89.427,0.529,4.575,15.555,2.7880000000000003,1,0.35,2 +717,B4 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