From e75db1f32dd6b5271dbfe537fbe75bffd7cd1291 Mon Sep 17 00:00:00 2001
From: David Wade <dawad@statoil.com>
Date: Mon, 30 Jan 2017 18:09:41 +0100
Subject: [PATCH] StoDIG submission #3

---
 StoDIG/Facies_classification_StoDIG_3.ipynb | 828 +++++++++++++++++++
 StoDIG/Prediction_StoDIG_3.csv              | 831 ++++++++++++++++++++
 2 files changed, 1659 insertions(+)
 create mode 100644 StoDIG/Facies_classification_StoDIG_3.ipynb
 create mode 100644 StoDIG/Prediction_StoDIG_3.csv

diff --git a/StoDIG/Facies_classification_StoDIG_3.ipynb b/StoDIG/Facies_classification_StoDIG_3.ipynb
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+{
+ "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\n",
+    " \n",
+    "Since our submission #2 we have:\n",
+    " - Added the distance to the next NM_M transition as a feature (thanks to geoLEARN where we spotted this)\n",
+    " - Removed Recruit F9 from training"
+   ]
+  },
+  {
+   "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: theano in /home/dawad/anaconda3/lib/python3.5/site-packages (from keras)\n",
+      "Requirement already satisfied: six 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: numpy>=1.7.1 in /home/dawad/anaconda3/lib/python3.5/site-packages (from theano->keras)\n",
+      "Requirement already satisfied: scipy>=0.11 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": [
+    "data = pd.read_csv('train_test_data.csv')\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",
+    "# Parameters\n",
+    "feature_names = ['Depth', 'GR', 'ILD_log10', 'DeltaPHI', 'PHIND', 'PE', 'NM_M', 'RELPOS']\n",
+    "facies_labels = ['SS', 'CSiS', 'FSiS', 'SiSh', 'MS','WS', 'D','PS', 'BS']\n",
+    "facies_colors = ['#F4D03F', '#F5B041','#DC7633','#6E2C00', '#1B4F72','#2E86C1', '#AED6F1', '#A569BD', '#196F3D']\n",
+    "well_names_test = ['SHRIMPLIN', 'ALEXANDER D', 'SHANKLE', 'LUKE G U', 'KIMZEY A', 'CROSS H CATTLE', 'NOLAN', 'Recruit F9', 'NEWBY', 'CHURCHMAN BIBLE']\n",
+    "well_names_validate = ['STUART', 'CRAWFORD']\n",
+    "\n",
+    "data_vectors = data[feature_names].values\n",
+    "correct_facies_labels = data['Facies'].values\n",
+    "\n",
+    "nm_m = data['NM_M'].values\n",
+    "nm_m_dist = np.zeros((nm_m.shape[0],1), dtype=int)\n",
+    "\n",
+    "for i in range(nm_m.shape[0]):\n",
+    "    count=1\n",
+    "    while (i+count<nm_m.shape[0]-1 and nm_m[i+count] == nm_m[i]):\n",
+    "        count = count+1\n",
+    "    nm_m_dist[i] = count\n",
+    "    \n",
+    "nm_m_dist.reshape(nm_m_dist.shape[0],1)\n",
+    "\n",
+    "\n",
+    "well_labels = data[['Well Name', 'Facies']].values\n",
+    "depth = data['Depth'].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",
+    "data_vectors = np.hstack([data_vectors, nm_m_dist])\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",
+    "      \n",
+    "    X = data[0:4149,0:11]\n",
+    "    \n",
+    "    y = np.concatenate((data[0:4149,0].reshape(4149,1), np_utils.to_categorical(correct_facies_labels[0:4149]-1)), axis=1)\n",
+    "    X_test = data[4149:,0:11]\n",
+    "\n",
+    "    return X, y, X_test\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": [
+      "(4069, 11, 9)\n",
+      "(830, 11, 9)\n",
+      "(4069, 9)\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,9), dtype=float)\n",
+    "X_test  = np.empty((0,conv_domain,9), dtype=float)\n",
+    "y_select = np.empty((0,9), dtype=int)\n",
+    "\n",
+    "well_names_train = ['SHRIMPLIN', 'ALEXANDER D', 'SHANKLE', 'LUKE G U', 'KIMZEY A', 'CROSS H CATTLE', 'NOLAN', 'NEWBY', 'CHURCHMAN BIBLE']\n",
+    "\n",
+    "for wellId in well_names_train:\n",
+    "    X_train_subset = X_train_in[X_train_in[:, 0] == wellId][:,2:11]\n",
+    "    X_train_subset = expand_dims(X_train_subset)\n",
+    "    X_train = np.concatenate((X_train,X_train_subset),axis=0)\n",
+    "    y_select = np.concatenate((y_select, y_train[y_train[:, 0] == wellId][:,1:10]), axis=0)\n",
+    "    \n",
+    "for wellId in well_names_validate:\n",
+    "    X_test_subset = X_test_in[X_test_in[:, 0] == wellId][:,2:11]\n",
+    "    X_test_subset = expand_dims(X_test_subset)\n",
+    "    X_test = np.concatenate((X_test,X_test_subset),axis=0)\n",
+    "\n",
+    "y_train = y_select\n",
+    "    \n",
+    "print(X_train.shape)\n",
+    "print(X_test.shape)\n",
+    "print(y_select.shape)"
+   ]
+  },
+  {
+   "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": 21,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "____________________________________________________________________________________________________\n",
+      "Layer (type)                     Output Shape          Param #     Connected to                     \n",
+      "====================================================================================================\n",
+      "input_8 (InputLayer)             (None, 11, 9)         0                                            \n",
+      "____________________________________________________________________________________________________\n",
+      "dropout_22 (Dropout)             (None, 11, 9)         0           input_8[0][0]                    \n",
+      "____________________________________________________________________________________________________\n",
+      "convolution1d_8 (Convolution1D)  (None, 1, 99)         9900        dropout_22[0][0]                 \n",
+      "____________________________________________________________________________________________________\n",
+      "cropping1d_8 (Cropping1D)        (None, 1, 9)          0           dropout_22[0][0]                 \n",
+      "____________________________________________________________________________________________________\n",
+      "flatten_15 (Flatten)             (None, 99)            0           convolution1d_8[0][0]            \n",
+      "____________________________________________________________________________________________________\n",
+      "flatten_16 (Flatten)             (None, 9)             0           cropping1d_8[0][0]               \n",
+      "____________________________________________________________________________________________________\n",
+      "merge_15 (Merge)                 (None, 108)           0           flatten_15[0][0]                 \n",
+      "                                                                   flatten_16[0][0]                 \n",
+      "____________________________________________________________________________________________________\n",
+      "dropout_23 (Dropout)             (None, 108)           0           merge_15[0][0]                   \n",
+      "____________________________________________________________________________________________________\n",
+      "dense_22 (Dense)                 (None, 20)            2180        dropout_23[0][0]                 \n",
+      "____________________________________________________________________________________________________\n",
+      "merge_16 (Merge)                 (None, 29)            0           dense_22[0][0]                   \n",
+      "                                                                   flatten_16[0][0]                 \n",
+      "____________________________________________________________________________________________________\n",
+      "dropout_24 (Dropout)             (None, 29)            0           merge_16[0][0]                   \n",
+      "____________________________________________________________________________________________________\n",
+      "dense_23 (Dense)                 (None, 32)            960         dropout_24[0][0]                 \n",
+      "____________________________________________________________________________________________________\n",
+      "dense_24 (Dense)                 (None, 9)             297         dense_23[0][0]                   \n",
+      "====================================================================================================\n",
+      "Total params: 13,337\n",
+      "Trainable params: 13,337\n",
+      "Non-trainable params: 0\n",
+      "____________________________________________________________________________________________________\n",
+      "Load time = 0\n",
+      "(11, 1, 9, 99)\n",
+      "(99,)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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8GaFWxoRaGRP9YQvwz7Azn6w2Hao3bG/8tS8wr9k0Z8TXEvzmMVGd9O7Ku75t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\nNZ5NryRJkhrvXx+zT8/5mjqPAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f21777f60b8>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Set parameters\n",
+    "input_dim = 9\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=0.375, main_dropout_rate=0.5,\n",
+    "              hidden_dim_1=20, 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(9):\n",
+    "        plt.subplot(911+i)\n",
+    "        plt.imshow(model_dnn.layers[layerID].get_weights()[0][:,0,i,:], 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": 22,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train time = 21 seconds\n",
+      "Test time = 1 seconds\n",
+      "\n",
+      "Model Report\n",
+      "-Accuracy: 0.664537\n",
+      "-Adjacent Accuracy: 0.928975\n",
+      "\n",
+      "Confusion Matrix\n",
+      "     Pred    SS  CSiS  FSiS  SiSh    MS    WS     D    PS    BS Total\n",
+      "     True\n",
+      "       SS   218    44     6                                       268\n",
+      "     CSiS    73   678   188                             1         940\n",
+      "     FSiS     5   200   563     4           1           7         780\n",
+      "     SiSh           3     3   221          37     1     6         271\n",
+      "       MS           5    10    74     6   118     5    78         296\n",
+      "       WS                 2    60     1   372    13   134         582\n",
+      "        D                 1    15           7    86    32         141\n",
+      "       PS                10    19         139     5   508     5   686\n",
+      "       BS           3                       7          43    52   105\n",
+      "\n",
+      "Precision  0.74  0.73  0.72  0.56  0.86  0.55  0.78  0.63  0.91  0.69\n",
+      "   Recall  0.81  0.72  0.72  0.82  0.02  0.64  0.61  0.74  0.50  0.66\n",
+      "       F1  0.77  0.72  0.72  0.67  0.04  0.59  0.69  0.68  0.64  0.64\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=0)\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",
+    "\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": 23,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(11, 1, 9, 99)\n",
+      "(99,)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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qtD84QkmC5ZIl30o9x+fFdT/p70MmTaIkvDIpOMilRJQM8/TclZ5CJWeipFMySZ86Mmzq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\nKcp7TviyREV1jFS2ZJYQpuqg7itZ36f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ZwPuAPN2c1ajOIH5Z1CbJ2OZeEfOg8GWHY5aI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\nREREpNvToFdEREREur3/H0zcpslJiiYmAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f215d98b898>"
+      ]
+     },
+     "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 = 108\n",
+      " Cross Validation Results\n",
+      "[ 0.59459459  0.56388206  0.56879607  0.4987715   0.44895449]\n",
+      "0.534999743751\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": 15,
+   "metadata": {
+    "collapsed": false
+   },
+   "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": 24,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Rt0Zf2ofduaznwIEDTYos85wp1szo3x8qVNAXop84Yd99WTWHZrBHLuPj41m8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RJ1s9+CXjzQiw4tyJUrF4MHD2b27NnpznJiKb5ZynVItEPer08nfoX8mBU0i7GBY5l/Yj7Tj0zH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brw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KXXhRqULVuWatWqcerUKaOeZy++2ct5SNRDBr5GYjAY+LD2h7g6uRK6OpQCuQswpuEYtWXl\naMqWFQvcNm2CsWPFVVV/fxg+HF5/Xb3SZhL75caNGxw4cIALFy4QExMDiLayvr6++Pv74+vri5eX\nFw45dcXlzJnw+++iV7hMwrcoCQkJHDx4kM6dO6stRSLRJTLwNZFeNXsRlxTHsI3DqF28Ni0rtFRb\nUo7GYIBXXhHbjh0iAO7UCT7/HD75BN56C5yd1VYp0TMpKSkcO3aM/fv3c/nyZfLkyUOFChUICQnB\n19cXDw+PLK/+5AjS02HUKBg9Gt57D954Q21Fdse3336Loii0bCk/cyQSU5CBrxn8L/h/RFyK4J3l\n73DigxN4uXupLUkChISImr5798IXX4hc4JEjYc0asSBOIjGWffv2sXHjRpKTkylbtiwdO3akQoUK\nOMrLCf+iKNC1K8ybB199JRa1SSzKsWPH+Prrrxk0aBClS5dWW45Eokty6HU4y2AwGJjZaibxSfGs\nP7v+mY9p3bq1jVWZjp60ZocXXxRVlA4fhvh4sbbG2tibh2qiJS8/+OADkpOTee+99+jSpQuVK1fO\ncUHvc8dj0SIID4fffoOPPxaXYdTQYafs2rWLevXqUb58eYYPH2708+3FN3s5D4l6yMDXTLzzeFOh\nYAX2XNnzzPv7WqB8j63Qk1ZjCAgQ9X5v3bL+sezVQzXQkpcffPABAKdPn1ZZiXpkOR6pqTBoEDRs\nKPKK1NJhp6xYsYJGjRrh5+fH1q1byZs3r9H7sBff7OU8JOohA18L4ObsRkp6yjPva9KkiY3VmI6e\ntBqLolhtAuoJ7NlDW6O2l4qicO7cOcLDw7lw4QJubm4UKlRIVU1qkuV4KApUrAibN8NHH5ndlthk\nHXZGWloaw4cPp23btjRv3pwNGzZQoEABk/ZlL77Zy3lI1EPm+JqJoiiciTtDJ/9OakuRZIKiQGws\nmPh5IcmBXLt2jWXLlhETE0ORIkVo06YN/v7+ODnJf5nPxNkZ/vwTfvhBrCZdtw6mToUGDdRWplti\nY2N566232LhxI+PGjWPIkCFy8aREYgHkjK+ZGAwGKheuzPKTy1HU7p4geSYrV4oc35AQtZVI9EB0\ndDSzZ8/GycmJbt26ERoaSrVq1WTQ+zwcHES6w/79kD8/vPyyqCd48aLaynTH/v37qVmzJgcPHmTD\nhg0MHTpUBr0SiYWQga8FGNdoHLsu7yL8SPh/7lu+fLkKikxDT1qzy7lzYnF5gwZQv771j2ePHqqF\npb1UFIUHDx4QHx/PpUuXOHXqFAcOHGD79u2sX7+eZcuW8dtvvzF37lyKFCnCO++8Q8mSJTEYDHJc\nMWI8qlSBiAiYO1fcVqoEjRqJ3N/+/UWtwenTYdkyUXvw9GmRgJ/NiQN7HovExES+/PJLgoOD8fb2\nZv/+/bzyyisW2be9+GYv5yFRDzmFYQEalm5I5xc6897q9/D38qdakWr/3Dd//nzatm2rorrsoyet\nzyMtDX78UVx19faGSZNsc1x78lBtnudlRiCbkJBAYmIiCQkJT/z8rNu0tLT/7MfV1RU3Nzfc3d1x\nd3cnKCiIevXq4fxY4Wc5rkZ6YDBAly7Qpo1IfzhyBK5dg6gouHlTtDNOf6rlu7MzFCoEhQuDl9eT\nt4/9PH/6dNo2aAAeHrZJ3LcBqamp/PLLL4wcOZKYmBj69u3Ll19+Se7cuS12DHt5DdvqPGIPJ3Dt\nhryKm0Hs9cRM7ytU1R2fstlfcHn9nLrvWxn4WojpraZzPOY4bRe05eyHZ3FyENYuXLhQZWXZR09a\ns2LzZhg2DPbsgX79RC3fPHlsc2x78VALPMvL9PR0wsPDiYmJISEhgfSngydEIJsRxLq5uVGgQIEn\nfn/6Njvd1eS4muhB3rwwYsR//56WJvKPYmLEdvPmk7cxMXD1qqhFmBEoP5oRXggiYd/Z+d+AuEQJ\n8PX97+bjo/nWjWlpabz44oscOnSITp06MWbMGMqWLWvx49jLa9hezkOiHjLwtRAP0x4SlxRH8XzF\ncTRo+x+tvbJjh/iM3bIFAgNh2zaZ12tvPHz4kPPnz1OlShV8fX2fCGLd3d1xdXXNuW2C9YSj478z\nudkhI1B+PDDO+Pn6dbh0CbZuFbd37jx5nGLFnh0U+/qKgFnlmWMHBwdSU1OpXbs24eHhMpdXIrEy\nMvA1E0VR2HBuAyO3juRO8h22dtsq/3HZGEWBnj0hLAyqVoUVK6BVK7u5Cip5jIz31q1bt8iXLx8u\nLi7kypWL/Pnz4+LiorI6idUwJlC+c0cEwNHR/9127oTLl0Xd4Qzy5hWl2Jo0gebNISgIbLiQ0WAw\nMG7cOFq0aMHw4cP59NNPcXNzs9nxJZKchgx8TSQpJYnfon7jh90/cDzm+P/Zu+/4nM7/j+Ovk8gS\nIcRMghgRJGbtUbV32lI/s1q7VpUWrWpLv10xutAqRaldLVXUaK2iaG2xYouRmEFC5vn9cUiDJJI7\n931f55z7ej4eeUju++Sc9/kc4ZP7vs51Ua1oNVZ0WUGAd4DoaA7n55+1pvebb2DAAO3mcsmcXF1d\nadasGefPn+fYsWP8/fffqc/lz5+fwoULU6hQIQoXLkzhwoXx8fGRszE4mnz5tI+QkPSfT07WXiVO\n2xDv36/dcPfJJ9r3Nm+uNcGtWtklcuvWrXn//ff57LPPmD9/PhMmTKBz587yRRRJsgHZImRDckoy\nG89sZOCqgRT/ojgDVg0gsEAgm1/ZzJ7+e3gu4LknvqdXr172D2ohI2V9SFXhjTe0oXzNmolveo1Y\nQ71Kr5aKolC/fn26du3K66+/zjvvvEPfvn0JDQ2lfPnyJCUlsX//fn755RemT5/OJ598wurVq22S\nxdHopQY5zvFw+EPdutC5M4wcqS21fOUK7NqlzTyxeTP06aNt9/HHVsmdGUVRGD9+POHh4VSvXp2u\nXbvSpEkTzp8/b7Vj6OX65ZRZzkMSRza+T5GcksymM5sYtHoQvp/70nReU9acXEOvqr04MfQEK7qs\noFFAowx/MzfSKjNGyprW8OHaO5dBQRAaqt3cJmpKZaPWUI+yUktXV1f8/PwICAjAx8cHNze31Jkb\nXFxcKFu2LGXLlrVLFrPTSw1skuPCBZg7F774Qnvr6No18PSEtm2hYUPrHy8DZcuWZcWKFaxfv55T\np05RuXJlq93MpZfrl1NmOQ9JHPke4GNS1BQORR1i67mtbD2/lc1nN3Mt7hol8pXg5cov83/B/0dN\n35pZfguqa1fjrOhmpKwPKYq2QurgwbBwofb/VpMmEBCg3eBWrdp/H0WL2j6PEWuoV0+rZVxcHAcO\nHGDv3r1cu3YNRVHw8/OjZs2alC5dGn9/f5ytdEe/vK76qUGWcqgq3LmT/s1wjz8WHa3NIKEoULOm\nNl6qRQttrK+rK+zda/uTekzz5s05cOAAr732Gl26dGHcuHGUK1eOwMDARz78/PyyfDOnXq5fTpnl\nPCRxHL7xTUxOZN+VfVqje24rf53/i1v3b+Hq7Eotv1r0r96f0KBQavnVkuOtdMzdHXr3hl694M8/\nYfVq2LcPJkz47ybvYsUebYSrVYNSpeRNcEaiqirnz59nz549HDlyBFVVqVChAk2aNKFUqVJWnfdU\n0pHMGtmMPk9IeHI/Pj6PzgtcurT2eaVK0LQpFChg/3PLQP78+Vm8eDFdunRh06ZNREREsGLFCs6e\nPZv6roaHhwdlypR5oiEODAykWLFi8v+sHDgc9zqxdwJFx9CNM3ERwEDRMazCIRvfi7cvsiZiDWtO\nruGP039wN+EuHrk8qFe8HsPrDOfZks9S2682Hi4eoqNK2aQo2ljfZs20r1UVzpzRmuCHH7Nna3Pp\ng3YfS9WqjzbDFSrY9aZuKRvWrl3L7t27AW1cZHBwMMWKFSM5OZno6Gjy5s2Ll5eX1V7plWxAVSEu\nThtOcP269mfaj8cfe/h1fPyT+8qokU1n4Qt8fAz3g60oCi+++CIvvvhi6mMJCQmcPXuWiIiIRz6W\nLl3KuXPnUB+M8/L09CQgIICSJUsSEBCQ+vHw60KFCsnGWHJIxvpXwELJKcnsuriL1SdWszpiNQei\nDuCkOFHXvy7vNHiHxgGNecb3GVydrT8d0rZt22hgkMlkjZQ1qxRF+7+wdGno2PG/x69cebQZ/u03\nbYEpADc37QWgh41w9era11mZYciMNRQlvVpWqVIFd3d3bt++zZ07d4iKiuLEiRMkPPbqXp48ecib\nN2+6H/ny5ct2cyyvayY1iIvLWgOb9rH795/cj7u7tnLbw49ChbTfQtN+XagQ2yIjadCypSEbWWtw\ndXWlXLlylCtX7onn4uPjOX36NBEREZw8eZKzZ89y7tw5tm3bxpw5c7h3717qth4eHpk2xkWKFNFl\nY2zfn0X9nb+Uc6b+V+N2/G2m/zudL3d+yeW7l/Hx8KF1YGtG1x9Ny7ItKeBh+7e1JkyYYJj/MI2U\nNaeKFtVmK2rd+r/HYmK0haIeNsO7dsGcOdqNcy4uMG8edOmS+X4dqYa2ll4tfX198fX1fWLb+Ph4\nbt++ze3bt4mJiUn9/M6dO5w5c4bbt28Tn+YVQ0VR6NGjB6VLl7Y4i6NJrcGFC/DHH9rHn39CVNST\nG7u6ao1qwYJag1qwoHb36cMm9uFjab/OnTtL444mhIbSoGdPG5yh8bm5uVGhQgUqVKjwxHOhoaHM\nnTuXc+fOcfbs2Uc+du7cyeLFi7l161bq9l5eXjRs2JAmTZrQuHFjqlSpoot3UuTPopRTpmx8o2Oj\n+WrnV0z7ZxpxiXG8UuUVelfrTS2/Wjg72fcHd/HixXY9Xk4YKast5MsHzz6rfTx0/z4cPqyNFe7V\nCwID4ZlnMt6Ho9fQmrJTSzc3NwoVKkShxxY4UFWVK1eucOjQIQ4cOEBcXBze3t6EhITg5+dnkyym\nc+sWbNrE4qJFteb1xAmtQX3mGe2HIjj4ySbX09Nmg+cd+lrkwOLFi1OX8K5atWq628TExKQ2xocP\nH2bz5s2899573Lt3D29vbxo1apTaCAcHBwtZJVFefymnTNf47orcRaN1jVBVlddqvMbwOsPxy5v1\n/+CszUgr8Bgpq724u2uzQ3zwgbYi3GuvwT//ZLy9rKH1WFJLVVW5fv06586dS/24ffs2uXPnJjg4\nmEqVKuHv75/tt3Ad9rpu2KAtgxgfT+6yZbXB8598Ao0bC7sRzGGvRQ5lpW758uWjcuXKVK5cmdDQ\nUMaMGUN8fDy7d+9m48aNbNq0iZEjR5KQkECHDh1YtmyZ3YdDyOsv5ZTpGt9ha4fRrH4z5neYb5eh\nDJK53bsHYWHw2Wfa8Ij//U90IiktVVW5evUqZ8+e5fz585w7d467d++iKArFihUjODiY0qVLU6pU\nKV28TWsoFy5A167aWyAzZmhzBEoOx83NjYYNG9KwYUM++OAD7t27x48//siAAQP45Zdf6Jj25glJ\nMgDTNb4NSjRgeefluOVyEx1FMrDYWPj+e5g4UZsdaeRIGDNGewdX0oezZ8+yfv16Ll++jJOTE76+\nvlSpUoWAgACKFy+Om5v8NyBHBg/W/sIvXKgNX5AktJvi+vfvz6pVq+jVqxcHDx5k2LBhFNDRVHCS\nlBnTrdw2sMZAXTW9I0eOFB0hy4yU1VZu3dJWKA0I0BbGaNpUG+P78cdZa3plDa0no1pev36dJUuW\nMHfuXJycnOjWrRujR4+mT58+NGvWjLJly1q96XW463r1KqxZA2+/ndr06qUGeslhNNau2w8//EDf\nvn2ZOHEiJUuW5O233yY6Otqqx0iPvP5STpnuFV8XJxfRER5RokQJ0RGyzEhZrS06WpvObNo0bbrQ\nPn20V3mz++6uI9fQ2tKrZWxsLDNmzMDd3Z0OHToQEhJilzGGDndd//oLkpO1sbwP6KUGeslhNNas\nW3x8PGfPniU4OJj27duzdOlSwsLCWLNmDQcPHrTacdIjr7+UU6ZrfH89/isvNHlBdIxUQ4cOFR0h\ny4yU1VouXIBJk2DmTHB2hoEDYcQIy5c3dsQa2kp6tQwPDycpKYn+/fvjacdxJw53XRs2hDx5tPn8\nwsIA/dRALzmMxtK63blzh4MHD7Jv3z727t3Lvn37CA8PJzExEUVRCAoKomvXrlSrVo0WLVpYOfWT\n5PWXcsp0je+S8CUMuzKMqkXTn65FkkCbkSksDH78Ufv/ffRoGDpUVyuWSmlcvnyZf//9l0OHDhEY\nGGjXptchFSoEb7wBn36qvR0yZow2l59kWklJSZw4cYJDhw498nHmzBlAWzgjJCSEZ555hr59+1Kt\nWjUqV65Mnjx5BCeXpOwxXeMb4B1Aq/mt2N57O2UKlBEdR9KZgwe12Zh++klbyfTTT6F/f/DyEp1M\nelxiYiKHDh1iz549XLp0CS8vL+rVq0etWrVER3MM77+v/SY4caK2ekvnzjB2LFSsKDqZlEMxMTHs\n3LmTgwcPpja4R48eTV3kpVixYlSuXJmOHTtSqVIlqlSpQoUKFXB1tf7qppJkb6ZrfKe0nkL/Pf0Z\nsX4Ev3b5VXQcjh07Rvny5UXHyBIjZbXEnTvanPv+/tpY3ldf1ebptSaz19CeZs2aRVRUFIGBgXTp\n0oXAwEAhE+aDg15XFxcYPlwb/zNnDsf+9z/K//67tlKbwAbIIa+FFaStW/v27fnrr7/w9PQkJCSE\nmjVr0rt3bypVqkSlSpXw8fERnDZj8vpLOWW6xje/R37q+tfl4p2LoqMAMGrUKFauXCk6RpYYKasl\n7t/Xlh/+8kt4/nnbHMPsNbSnWbNmMXjwYLp16yY6imNfV3d3GDiQUd9/z8q9eyExUWjj69DXIgfS\n1i0mJoY+ffowY8YMYb9MWspe1/+rq9twTYyw+XGMIuFWOkuTG5Sx/sZnUT63fOy7vI+1J9eKjsLU\nqVNFR8gyI2XNrrg4bfU1AG9v2x3HzDW0p5iYGNq2baubuXjldYWpr72mfXLhgtgc8lpY5PPPP+eX\nX36hbdu2HD58GB8fH8M1vSCvv5RzxvtbnwUfNv6QesXr0XpBa979812SU5KFZTHS1CtGypodu3dD\ntWraDepff60tRFpi0W8AACAASURBVGUrZq2hPV2/fp05c+bg7e1Ny5YtRccB5HUFKPHyy+DrCx99\nJDaHvBbZcvr0aUaOHEn9+vXp2LEj165d49tvv+WDh68EGIy8/lJOmW6oA4BPbh9WdVtF2LYwxm4a\nS26X3Lz77LuiY0kCXL+uLUJRoQLs3w9BQaITSU+zY8cOYmJiCAwMTL3ZRtIBd3d47jn4+WeYO1eb\n/0/Stbt371KnTh2Sk5N5+eWX6dOnD5UqVRIdS5KEylbjqyjKa8BAIODBQ+HAh6qqrk2zzYdAX8Ab\n2A4MVFX1ZJrn3YDPgc6AG7AOGKSqanSabfIDU4F2QArwMzBMVdXYrGZ1Upx4p+E73Lx/k4//+pju\nlbsT4B3w1O+TzGXKFG0e/tWrtRmaJP1r3rw5BQoUYPfu3cyYMYMSJUpQp04dypcvb5fFKqQM/PKL\ntnzx5Mmy6TWImTNncvPmTU6ePEnJkiVFxzGUUUP6UbqinBb1odNH9jNyywLRMawiu0MdLgCjgerA\nM8BG4FdFUSoAKIoyGhgC9AdqAbHAOkVR0t4J8SXQFugIPAv4ojW2aS0EKgBNH2z7LPBdNrMC8H6j\n9/Fy82LqbjHjgsIeTP5uBEbKmlXr1kH9+vZres1YQ3tzd3enfv36xMfH89JLL6GqKkuXLmX69Okc\nPXoUVVXtnsnhr2t8PGE9e8KLL2ozPQjk8NciiyIjI/n444/p0aMHJUuWNE3dzHIekjjZesVXVdXV\njz00VlGUgUAd4CgwDPifqqqrABRF6QlEAS8ASxVFyQv0BrqoqrrlwTa9gKOKotRSVXX3gya6JfCM\nqqr7HmwzFFitKMpbqqpeyU7mPK55qF+8Pvuv7M/Ot1lNXFyckONawkhZs+rll7WFKY4e1YY72JoZ\nayjKvXv3CA4OJjg4mAsXLrB582aWLl1KsWLFaNq0KWXK2G+eboe/rkuWEBcbq018LfhVd4e/FlmQ\nlJRE9+7d8fDwYNKkSYB56ma381AU+Q5TWiaqhcU3tymK4qQoShcgN7BDUZRSQFHgz4fbqKp6G9gF\n1H3wUA20ZjvtNseB82m2qQPcfNj0PvAHoAK1LckaWCCQ0zdPW/KtOTZ+/Hghx7WEkbJmVZ8+2ry9\nw4aBPV4oNGMNRUlby+LFi/Pyyy/zyiuvcO/ePZYtWyYsi0PasYPxhQtDQIDoJPJaZMHJkyfZunUr\n1atXx+vB6jxmqZtZzkMSJ9uNr6IoIYqi3AHigW+AFx80r0XRmtPHJ3uLevAcQBEg4UFDnNE2RYHo\ntE+qqpoM3EizTbYkpiTinsvKKxVIhuDmBjNmwIYN2p+SsRUoUIDY2FiqV68uOopjGTJEu1N08mTR\nSaQsKF++PHPnzmXt2rU0b96cK1ey9UapJJmaJa/4HgOqoI3h/RaYpyiKbpZRadOmDaGhoakfrdu1\n5psB3+Aa8eiE6+vXryc0NPSJ7x88eDCzZs165LG9e/cSGhrKtWvXHnn8gw8+eGK80fnz5wkNDeXY\nsWOPPD5lyhRGjhz5yGNxcXGEhoaybdu2Rx5ftGgRvXr1eiJb586dWbFihV3OY8qUKRQtWpQmTZqk\n1nK4Fcf2PX6dQkNDqVu3rk3Ob8eODyhTJoz58/97TF6nrLPntcroZ6p169bMnDmTqVOn4uLiQoMG\nDQx1rRYtWkTz5s0fuVaGuk5Fi8KIEdqSxW+/zQdjx5ry3z7DX6c059ezZ0+6d+/Onj17KFu2LGPH\njuXWrVumuE4P89r63z7JnJSc3iiiKMoG4CQwATgFVFVV9WCa5zcD+1RVHa4oSmO0YQv5077qqyjK\nWeALVVW/ejDmd5Kqqj5pnncG7gMvqaqa7jrEiqJUB/bs2bMn9dWg5JRk2i5sy+6Lu9nVdxeBPoE5\nOldLXLt2jYIFC9r9uJZ4Wta9e/fyzDPPgDb+eq8lx0jvOtna/ftQtKg23MHW75Lp4Xpb4zqBmGuV\n1rVr18iVKxdbtmzh4MGDuLq6UqtWLWrVqoWnp6fds1j7uhrtOl2LjqbgDz/Au+9C9eqwZImQoQ/2\n/hkz2nV63I0bN5g4cSJffvklHh4ejB49mmHDhuFu7fXa7SSz62/N/6MmLttCGTmrQ6pTR/Yz8qVG\nkKa2D2u1bXINqpXxyvK+9p26Q4M3/31kX/ZkjQUsnAA3VVXPAFfQZmIA4MHNbLWBHQ8e2gMkPbZN\nEFAC+PvBQ38D3oqiVEtzjKaAgjZeOMvWnlzLulPrWNRxkZCmF6B3795CjmsJI2XNquhoaNUKYmPB\nHivfmrGGovTs2ZMffviBkydP0qxZM4YPH07jxo3t3vSCvK4Avfv2hVGjYNs2uHoV6tSBvXb/P0te\ni2wqUKAAn376KQ0bNqRbt26MHTuWKlWqsHnzZtHRLCKvv5RT2Wp8FUX5RFGUhoqilHww1vdToBHw\n8E3kL9FmemivKEolYB4QCfwKqTe7zQI+VxTlOUVRngFmA9tVVd39YJtjaHP7zlQUpaaiKPWBKcCi\n7M7osOLYCgILBNKiTIvsfJtVjRs3Ttixs8tIWbNi716oUUOb0WHjRvssXmG2GoqSkJBA1apVSUlJ\noV+/ftStWxdXV9enf6ONyOuapga1a8OuXVCiBDRqBH/8ISaHlC2fffYZU6dO5cCBAxQqVIjGjRvT\nu3dvw832IK+/lFPZfcW3MDAXbZzvH2hz+bZQVXUjgKqqE9Ca1O/QXp31AFqrqpqQZh/DgVXAMmAz\ncAltTt+0uqU5xipgKzAgm1nZfmE7zUs3FzoliZFuwjFS1qdZu1ZbmrhoUdizBxo2tM9xzVRDkcLD\nw3Fzc6N79+7kzZtXdBx5XXmsBoUKab9NNmgA7dvD1q1ickhZ9rBuFStWZOvWrQwdOpQ5c+bwzz//\nCE6WPfL6SzmV3Xl8+2Zhm3HAuEyejweGPvjIaJtbQI/sZEvP9XvXKZrHookgJANbsABefVUb4rBk\nCeTOLTqRlF1RUVEUKFCAIkWKiI4iZSRPHli+HNq10z62boWqckykESQlJbFu3ToaNWrEs88+KzqO\nJNmVNcb46lZsQix5XPOIjiHZ0YED0KsX9Oih/Z8sm15jOnv2LL6+vqJjSE/j7q4tZRwfr/3ASYaw\nZ88eTpw4wccffywXaZB0R1GUuoqitHvssZ6KopxRFCVaUZQZiqK4Wbp/Uze+TooTKWqK0AyPT9ei\nZ0bKmp7ERO2V3vLlYfp0yJWt9zOsw+g11IPo6GiioqI4evSo6Cip5HXNpAb790NCArRsKTaHlKm0\ndYuIiACgRIkSouJYTF5/h/A+EPzwiwf3jM1CG/76GdAeeMfSnZu68fV29yYq9vH1NOxrr4C7ni1l\npKzp+fVX7f/gWbO0hStEMHoN9eDQoUO4u7tz6dIl0VFSyeuaSQ3++AMKF9ZmeRCZQ8rUX3/9xaRJ\nk6hcuTKvvPIKxYsXp1ChQqJjZZu8/g6hKmlW+AW6ALtUVe2nqurnwOvA/1m6c1M3vrX8arEzcqfQ\nDNOmTRN6/OwwUtb0zJ2r3XBes6a4DEavoWiqqnLo0CEqVqzIN998IzpOKnldM6nBoUNQpQo42ee/\nE3ktsmfHjh20atWKH3/8kbFjx1KhQgVWrVrFqVOnDDmXr7z+DiE/j64C3Aj4Pc3X/wDFLd25qRvf\nqkWrcuzasadvKJnC7t3QurXoFFJOpKSkEBsbi7e3t+goUlZcvaqtB16vnugkUgbCwsIIDw9n+vTp\nXLlyhSVLltC2bVtcXFxER5OkjEQBpQAURXEFqgNpX8X0AhIt3bmpG98CHgW4ef8mOV2dTjIO+W+5\nsTk7O1OuXDnCw8NFR5GyIixMe6V3aIaT9EiCxcbGUr9+ffr16yd/oZSMYg3wmaIoDYFPgTjgrzTP\nV0ZbKdgipm58/fP6k5SSxMU7F0VHkeygWDHYt090CimnKlSoQFRUlOEm1nc4qgo//gj9+oGPz9O3\nl4R4ODWgJBnIe2ir/G4B+gH9HlsPojew3tKdm7rxreFbA4DdF3cLyxAaGirs2NllpKzp6dMHVqyA\n06fFZTB6DfXg4Q03eqqlnrKI8kQNjhz5b01wkTmkDCUlJXH8+HEqVqxomrqZ5TykjKmqek1V1WfR\nxvrmV1X18bkSOwHjLd2/qRtfXy9fSuYryZazW4RlGDJkiLBjZ5eRsqbn5ZfBzw/q1rXrQlKPMHoN\nRYuJiWHlypXkypWLAQOyvVijzcjrmk4NFiyAvHmhfn2xOaQMpaSk4Orqyq1bt0xTN7Och/R0qqrG\nqKqanM7jNx57BThbTN34ArQq24o1J9cIG+fbokULIce1hJGypsfbG/75BypWhKZN4eOP4c4d+2Yw\neg1Fio6OZubMmcTGxtK7d286deokOlIqeV0fq8HNmzBjBvTubfdVYuS1yDpXV1fatWvHwoULTVM3\ns5yHlD5FUX5RFCVvms8z/LD0GAKm+LevThU78d2e71h1YhXtg9qLjiPZWKFCsH49jBkD48fDpEkw\neDAMG6Y9J+nX3r17cXJyol+/fnh6eoqOI2XkwoX/hjcMGyY2i5QhVVX59ttvWb58OTVq1BAdx3Am\nTJmBq7dcMv2hhFt2WxMhBlDTfG51pn/Ft0mpJjQp1YTRf4wmNiFWdBzJDlxcYOJEbaxv797w5ZdQ\nsqR24/m5c6LTSRmJjo4mX758uIlafUTKXHKyNoi+Xj2IjYXt2yEgQHQqKR0JCQl06dKFwYMH079/\nfzZu3Cg6kiRliaqqvVRVvZPm8ww/LD2G6RtfRVH4vMXnXLh9gVYLWnE7/rZdj79ixQq7Hi8njJQ1\nK/z9YfJkrdl9+21YtAjKlIGePcFWs2WZrYb25Ofnx8WLF/nyyy/Ztm0bS5cuFR0plUNf19hYmDaN\nFf7+8OKLULYs7NgBQUFC4jj0tcgCVVXp168fy5cv56effmLKlCm4ubmZpm5mOQ8p+xRFaaQoShtF\nUfLnZD+mb3wBqhStwoaXN3Ao6hDN5jWza/O7aNEiux0rp4yUNTt8fOD997UGePJk2LQJQkKgQwdt\nqKI1mbWG9tC0aVOGDBlCUFAQmzdv5qOPPmLDhg3ExNjk3a5scbjrqqpw4ACMGgUlSsDrr7PIxQV2\n7dJ+gHx9hUVzuGuRDdevX2fQoEHMmzePH374gZdeein1ObPUzSznIWVMUZTRiqL8L83XiqIoa4FN\nwCrgqKIowZbu3yEaX4A6/nXY+MpGTlw/QcelHUlItviGwGxZsmSJXY5jDUbKaglPT21I4qlTMGcO\nbNkCzZvDjRvWO4bZa2hrBQoUoH379gwbNozJkyezZ88evvrqK3766SfOnz8v7CZVh7muZ87AJ59o\nvxlWrar9oLzyCpw6xZLz56FWLdEJHedaZMONGzcYO3YspUqVYt68eUydOpVu3bo9so1Z6maW85Ay\n1Rk4nObrl4BngYZAQeBf4ANLd+4wjS9A9WLVWdFlBVvPbWXgqoGi40iCuLrCq6/Cxo1w9qzW/CYl\niU4lpeXl5UXz5s0ZMWIErVu3Jioqijlz5vD9998TGyvH6lvdpk3QoAGULq1Nh1K1KqxeDZcuweef\ny7G8OpWUlMRnn31GQEAAX3zxBQMHDuTs2bMMHjxYdDRJyolSwME0X7cBlqmqul1V1RvAR0BdS3fu\nUI0vwHMBz/F1q6+ZvX82+6/sFx1HEqhKFWjWTJuDX1FEp5HS4+rqSs2aNRk8eDDdunXj0qVLnDhx\nQnQs84iKgh49oEkTSEmB+fO1xxYsgDZt5BrgOnb06FHq1avHu+++S58+fThz5gxhYWGpC8BIkoHl\nAuLTfF0X2JHm60tor/xaxOEaX4A+1ftQJn8ZPv7rY9FRJIE2boSlS+Hdd8HZWXQaKTOKohAYGEiB\nAgXYv38/Z86cISUlRXQsY/vzT+0GtbVrYfZs2LYNuneHPHlEJ5Mycfv2bcaPH0+1atW4ffs2O3bs\n4IsvvqBw4cKio0mStZxCG9qAoiglgHJA2mWp/IHrlu7cIRvfXE656P9Mf1afWG3zsb69elk844bd\nGSlrTqSkwGefaUMcGjfWpjyzFkepoT2kV8tGjRoRExPDvHnz+Pzzz1m1apVdmmDTXde4OG2N76pV\n4fhx6NULnDL/70AvNdBLDnuLjY1lwoQJlCpVik8//ZRhw4axb98+ateunaXvN0vdzHIeUqamAVMV\nRZkF/A78rarqkTTPNwH2Wbpz0y9gkZFGJRtxL+ke+y7vo7Z/1v7hsISRVpkxUlZL3b8PXbrAr79q\nr/SOGwe5rPhT4Ag1tJf0alm5cmUqVarExYsXOXLkCEeOHGHPnj3kzp2b0NBQgmw0xZbpruuUKdo0\nJ8uWadOeZIFeaqCXHPZy//59ZsyYwSeffMKNGzfo168fY8aMwc/PL1v7MUvdzHIeUsZUVZ2pKEoy\n0B7tld7xj23iC8y2dP8O2/hejbsKQD73fDY9TteuXW26f2syUlZLxMfDSy9p7/D+9hu0a2f9Y5i9\nhvaUUS0VRcHf3x9/f3+aN2/OpUuXWLduHZs3b7ZZ42u66xocDF5eEBoK334Lzz//1G/RSw30ksPW\nEhISmDNnDh999BGXLl3ilVde4f333yfAwhsNzVI3s5yHlDlVVWeTQXOrquqgnOzbIYc6ACw4tIAg\nnyDKFywvOopkJ0OGwIYN2qu9tmh6JftTFAU/Pz/q1KnDlStXuGHNuenMrF07OHIEqleHF17Qxvbe\nvSs6lfTA1atXCQ4OZuDAgTRs2JCjR48ye/Zsi5teSTISRVF8FUWZpChK3nSey6coykRFUbL3lkca\nDtn4LjuyjMWHFzOi7gjRUSQ72r4d+vcH+U6Z+URGRuLq6oqHh4foKMbh76+99TF/PqxcCbVrw7Fj\nolNJwI8//siFCxfYv38/CxcupFy5cqIjSZI9jQDyqqr6xGpjqqrGAF7AO5bu3OEa3+PXjtNnZR/+\nL/j/6Fe9n82Pt23bNpsfw1qMlNUS9+9bdzxvesxeQ3vKai0TEhLYvXs3tWrVslnja9rrqijaq73/\n/KOt1lazZobreeulBnrJYUs//fQTrVq1onLlylbbp1nqZpbzkDLVCpiXyfPzgMaW7tyhGt9rcddo\nu7At/nn9mdl+JoodJm+dMGGCzY9hLUbKaolmzeCHH7R5e23F7DW0p6zW0tnZGW9vb06dOkVycrLQ\nLIZVvry2HHGePDBrVrqb6KUGeslhS6VKlWL//v0kJiZabZ9mqZtZzkPKVCngfCbPRwIBlu7cYRpf\nVVXpvKwzdxLusLrbavK6PTF0xCYWL15sl+NYg5GyWuKTT7QZm954Q3txyxbMXkN7ymotnZ2d6dCh\nA5cvX2bnzp1Csxialxd06gSLF0M6q+PppQZ6yWFLY8aM4dy5c/z4449W26dZ6mav84g5vJnru1Y8\n8hEX6RhDgeIijz1x7jGHN9szwj0yb2wDHmxjEYeZ1eH3k7+z8cxG1nRbQ4B3gN2Omzt3brsdK6eM\nlNUSBQvC119rC1W1aKEtW2xtZq+hPWWnlpGRkQAUKVJEeBZDGzoUvv8eRo+GqVMfeUovNdBLDlsK\nCQmhQ4cOfPLJJ/Ts2ZNcVhijZZa62es88oU8h6u3bf490bvc/uXJ7f/ojf8Jt6K4umWBvSLsAl7m\n0UUr0uoJ7LZ05w7ziu+4zeNoWKIhrcq2Eh1FEqh7d23BisGDtZvaJeO7evUqGzZsoGbNmpQtW1Z0\nHGMLDIQJE2DatAyHPEj28d5773Hq1Cl++ukn0VEkyd4mAb0ezOyQ+tuHoihFFEWZDLz6YBuLOETj\nezDqIP9c+oc3675pl3G9kr59/TUEBEDnztoCVpJxJSUl8fPPP+Pt7U3z5s1FxzGHQYNgwADo2xfe\negtsNG5aylzVqlWpV68eS5YsER1FkuxKVdVNwGBgCHBJUZSbiqLcAC49eHyoqqobLd2/QzS+iw4t\nomDugrQObG33Y48cOdLux7SUkbLmhKcnLF0Kp05p05tZc7VbR6mhPTytlikpKaxatYpr167RsWNH\nXFxchGUxFScnbVGLr76CL77QJsBGPzXQSw57aNq0KevXr0e1wk0JZqmbWc5Dypyqqt8BZYC3gIXA\nYuBNoKyqqt/mZN8OMcY34kYE1YpWw9XZ1e7HLlGihN2PaSkjZc2p4GCYMwe6doVixWDiROvs15Fq\naGuZ1TI5OZnly5dz5MgRXnjhBYoWLSosiykpCrz+unYX6IgRMGyYbmqglxy2dvPmTb7//nuaNGli\nlXcqzVI3s5yH9HSqql4EvrD2fh2i8b0ad5VieYoJOfbQoUOFHNcSRspqDZ07a1Obvf669iLXp59q\nf+aEo9XQljKqZWRkJGvXruXKlSt06tSJChUqCMtieq+9BpMnw8SJDNXJmF9HuRYTJ07k6tWrTJ8+\n3Sr7M0vdzHIekjgOMdShYsGK7Lm8R3QMSYeGDoXPP9de8e3UKd1ZnCSdiImJ4ZdffmHWrFkkJSXR\ns2dPuzS9Ds3NDdq31+b4leyqUaNGJCUlsXnzZtFRJMlUHKLxbR3YmpM3ThJxPUJ0FEmHhg+HFStg\n3Tpo0ABOnxadSHrcgQMHmDp1KmfOnCE0NJT+/fvLtzztJSAAIiJsN/m1lK6WLVvSpUsXhg8fzvXr\n10XHkSTTcIjGt0mpJrg6u/L7yd/tfuxjx4wz4bWRslpbaChs3w63b0ONGrBmjWX7ceQaWtuxY8dI\nSUlh3bp1rFixgpCQEIYMGUK1atVwyumYFAuyOKzly6FBA44dPy46CeBY1+KLL74gMTGR0aNH53hf\nZqmbWc5DEschGt88rnl4tuSzrImwsJvJgVGjRtn9mJYyUlZbqFIF/v0X6tWDdu3ggw+yP5OTo9fQ\nmt566y0WL17Mrl27aN26NaGhobi5uQnJ4rDXdf9++PtvGDpUNzXQSw57KFq0KGFhYcyaNYutWzOa\nyz9rzFI3s5yHJI5DNL4Arcu2ZvPZzcQl2nfi1qmPrX6kZ0bKaiv588PKlfDhh/C//2kN8I0bWf9+\nWUPriI+Pp3Hjxpw9e5bu3btTq1YtoXNwO+x1XbRIW/KwbVvd1EAvOeylX79+1K1blwEDBhAfH2/x\nfsxSN7OchySOwzS+bQLbEJ8cz5+n/7TrcY00DtFIWW3JyQnGjoXff4fdu6FhQ20IRFbIGlrHH3/8\nQVxcHC+//DJlypQRHccxr2tSEixcCC+9BC4uuqmBXnLYi5OTE9999x0nTpxg/vz5Fu/HLHUzy3lI\n4jhM4xvkE0T5guX5+ejPoqNIBtGypTbuNzISevSw7kIXUubKlClDSkoKiYmJoqM4rpUrtb/8/fqJ\nTuLwKlWqRMmSJYmIkDdoS1JOOUzjqygKLwS9IOQGN8m4ypfXXvRatQrkO2z2ExQUhL+/PytXruTK\nlSui4zimmTO1Ae/Vq4tOIgH+/v6y8ZUkK3CYxhegSJ4ixCbYd6LWsLAwux4vJ4yU1Z7atoW+fWH8\neLh5M/NtZQ2tQ1EUIiMj8fDwYPbs2YSHhwvN43DXNT4etmyBF19MfUgvNdBLDntr1aoVa9euJdbC\nycbNUjeznIckjkM1vq7OrsQnxxOfZPkNAtkVF2ffm+lywkhZ7e3DD7Ve4OOPM99O1tB6UlJS6N27\nN0FBQSxbtkzoNEYOd123b4d796BJk9SH9FIDveSwt86dOxMXF8fvv1v2rqVZ6maW85DEcajGt0GJ\nBiSlJLHl3Ba7HXP8+PF2O1ZOGSmrvRUtCqNHw5QpmS9wIWtoPePHj8fFxYUOHToQFBTEypUruXPn\njrAsDmXpUihZEqpVS31ILzXQSw57K1OmDMHBwaxatcqi7zdL3cxyHpI4DtX4VipciQDvAJYcXiI6\nimRAI0ZAoULQuzckJIhO4zgURSE0NBRFUfjrr79ExzG/lBT45Rf4v/8DgVPISU9q27Ytv//+Oyny\nTltJsphDNb6KotCvej8WHl7ItbhrouNIBuPpCYsXa/P5DxwoV3C1p9y5c1OmTBl5o5s9HD4MV69C\nq1aik0iPadu2LdHR0fz777+io0iSYTlU4wvQr3o/4pPiWXl8pV2Od+2acRpsI2UVpUED7Wb32bNh\n0qQnn5c1tJ7Ha1msWDEuXbpEZGSk8CymdfcuvPUW5MkDdes+8pReaqCXHCI8XMTlyJEj2f5es9TN\nLOchieNwjW8hz0Lkc8/H9bjrdjle79697XIcazBSVpF69oR339XG/K5Y8ehzsobW83gta9Soga+v\nLwsXLuT6dfv8/GaUxZSio6FxY9i5U/uL7eHxyNN6qYFecthbeHg4zz//PA0bNqRz587Z/n6z1M0s\n5yGJ43CNL0A+t3zcuJeNdWhzYNy4cXY5jjUYKatoH36ozfTUq5f2ItlDsobW83gtXVxc6Nq1K7lz\n5+aXX35BteNYE4e4roMGwfnzsHUrNG36xNN6qYFectjbpEmTuHnzJmFhYXg89ktJVpilbmY5D0kc\nh2x8S+QrwbmYc3Y5VnUDTf5upKyiOTnBF1/AnTswb95/j8saWk96tfTw8KBdu3ZcunSJo0ePCs1i\nKufOwfLl2mTVVaumu4leaqCXHPb28ccfU6lSJdq1a8fOnTuz/f1mqZtZzkMSxyEb37IFynL0mv3+\n05TMqUQJaN0afvpJdBLHUrJkSby8vDhx4oToKOaxdq12t2aPHqKTSBnw9fVl69atlClThoEDB4qO\nI0mG5ZCNb4MSDTgYdZCY+zGio0gG5+v76FAHyfaOHDnCnTt3qJZmjlkph7y85DQlBuDt7c0LL7zA\nhQsXREeRJMNyyMY3uFAwKWoKETdsv+75rFmzbH4MazFSVr1wdobExP++ljW0nvRqee/ePdavX09g\nYCAlS5YUmsVUHv4ljs94VUu91EAvOUQpVaoU169fz/Y7Hmapm1nOQxLHIRvf8KvhOClOlC9Y3ubH\n2rt3r82PYS1GyqoXMTHg7f3f17KG1pNeLVevXk1CQgJt27YVnsVUfv4Z6tQBH58MN9FLDfSSQ5QX\nX3wRX19fAr+f7wAAIABJREFUPvroo2x9n1nqZpbzkMRxyMb3n4v/UKFgBfK45rH5saZNm2bzY1iL\nkbLqRWysNuXpQ7KG1vN4LRMTEzl27Bh+fn7kzZtXaBZTuXxZG+PbtWumm+mlBnrJIYq7uzvvvvsu\n8+fPZ/v27Vn+PrPUzSznIYnjkI3vv5f/pYZvDdExJBNwc8v03WHJilxcXHjxxRc5deoUf/75p+g4\n5vHdd+Diok1QLRnCgAEDqFOnDq+++iqxsbGi40iSoThk4xtxPYKKhSqKjiGZgLMzJCWJTuE4goOD\nKVmyJPv27bPrPL6m9s8/UKPGo2N2JF1zdnbmhx9+4NKlS/To0YPk5GTRkSTJMByy8VVRcVacRceQ\nTCAuDjw9RadwHAcPHuTcuXO0atUqdflWKYdatYIdO+CGfRb1kayjXLlyLFmyhJUrV/LGG2/IXwQl\nKYscsvF1z+VOXGKcXY4VGhpql+NYg5Gy6sXdu482vrKG1vN4LW/evMmaNWuoXLkylSpVEprFVF58\nUXvbYvPmTDfTSw30kkMP2rVrxzfffMPUqVOZPHlyptuapW5mOQ9JHIdsfIvnLc75mPN2OdaQIUPs\nchxrMFJWvXj85jZZQ+tJW0tVVVm+fDkeHh60bt1aaBbT8fODggXh8OFMN9NLDfSSQy8GDBjAmDFj\nGDlyJD9lspqOWepmlvOQxHHIxrdKkSqsO7WO+CTb35XUokULmx/DWoyUVS/u3n208ZU1tJ60tYyN\njeXChQs0atQId3d3oVlMJz4eUlLg3r1MN9NLDfSSQ08++ugjGjZsyIwZMzLcxix1M8t5SOI4ZOM7\nsv5ILt65yMy9M0VHkQwuNlaO8bUHT09P3NzcuCuXybO+xYu18b29eolOIllIURQ8PDzIly+f6CiS\npHsO2fiWL1ie0KBQFh9eLDqKZHDJyeDkkD9F9qUoCoULFyY6Olp0FPPZsEFbvKJcOdFJpByQMztI\nUtY47H/ZNX1rEn413OZ3wq5YscKm+7cmI2XVC29vuHXrv69lDa3n8VoWLlyYqKgoXWQxlehoKF78\nqZvppQZ6yaE3pUuXznQZY7PUzSznIYnjsI1vKe9S3Lp/i9hE207+vWjRIpvu35qMlFUvChR4dBYo\nWUPrebyW7u7u3L9/XxdZTCU6GgoXfupmeqmBXnLohaqqfPPNN8ybN48SJUpkuJ1Z6maW85DEcdjG\nN5dTLgCSU2z79tCSJUtsun9rMlJWvcifH27e/O9rWUPrebyW0dHRFM5Cg2aPLKaSxcZXLzXQSw49\nSEpKolOnTgwePJh+/fqxbNmyDLc1S93Mch6SOA7b+Pp6+QJw5OoRwUkkI3NxgcRE0Skcg7u7O5cv\nX5ZLtFpTXBxERYG/v+gkkgViY2NZs2YN3bt3Z8qUKUJmPJEko3HYxreOfx2KeBZh2ZGMf0OWpKe5\neVN71VeyvRYtWqCqKr/99pvoKOZx9CioKoSEiE4iWSBfvnyMGDGCn3/+mcuXL4uOI0mGkEt0AFGc\nnZwp7FmYG/flMp2S5SIjIShIdArHkCdPHpo0acKqVau4d+8eHh4eoiMZ365dkCsXBAeLTiJZKCgo\niPv373Pr1i2KFSsmOo7kiHxTUANSsr79vWxsawMO+4pv5O1IDkUfolWZVjY9Ti8DzY1ppKx6kJQE\nJ08+2vjKGlpPerX0f/CWvL2nNTPtdd24EWrXztJk1HqpgV5y6MWnn35K27ZtqVChQqbbmaVuZjkP\nSRyHbXwTk7WBmc5OzjY9jpFWmTFSVj04e1Yb35u28ZU1tJ70almwYEG8vLzYs2eP8CymcO8e5M6d\npU31UgO95NCTy5cvP3XGE7PUzSznIYnjsI1vqfyleKbYMyw6bNupUbp27WrT/VuTkbLqwfHj2p9p\nG19ZQ+tJr5bOzs40atSIQ4cOER5u+3m4M8tiCs89B9u2QULCUzfVSw30kkMvFixYQHh4OG+//Xam\n25mlbmY5D0kch218AbqGdGX1idXE3I8RHUUyoNu3tT99fMTmcDRVq1YlMDCQZcuWMXPmTCIiIuzW\nAJuOq6u2/GCK2DF3kuWqVatGp06d2LFjh+gokmQIDt34dg7pTHxyPCuOyZVgpOx7eG/VvXticzga\nZ2dnunXrxiuvvIKLiwsLFy5kzpw53L17V3Q049m0CerWBTkNlqFFRUXh7e0tOoYkGYJDN77+ef15\nptgzbDq7yWbH2LZtm832bW1GyqoHD1/pTXuflayh9TytlgEBAbz66qt0796dGzdu8Ouvv9rslV9T\nXte7d2H9emiVtRt89VIDveTQk8aNG7NhwwaGDx9OcnL6izKZpW5mOQ9JHIdufAFq+9Vm98XdNtv/\nhAkTbLZvazNSVj0oXVr789Sp/x6TNbSerNRSURTKli3Lc889x8mTJ9m/f7+wLIazZo32dkW7dlna\nXC810EsOPXnnnXeYMmUKX3/9NW3btuX8+fNPbGOWupnlPCRxHL7xLZi7ILfjb9ts/4sXL7bZvq3N\nSFn1IG9e7c+0C4nJGlpPVmp55coVfv75Z9asWYOnpydeXl7CshhOQAB4eUGPHpBOo/Q4vdRALzn0\nZsiQIaxZs4aDBw9SoUIFwsLCSEhz06JZ6maW85DEcfjG98a9GxTwKGCz/efO4lRBemCkrHoQF6f9\nmXYdBVlD68mslqqq8vPPP/Pdd98RGRlJ69atGTZsGGXLlrV7FsOqVQt27ICYGKhZE65ezXRzvdRA\nLzn0qGXLlhw7dowBAwbw7rvvUr16dW7c0BZpMkvdzHIekjgO3/gWzF2Qi3cukqLKu5ql7Hk41Kxi\nRbE5HNGlS5c4fPgwLVu2ZOjQodSsWRMXFxfRsYwnJARmz9YGqkdGik4jWUHevHn5/PPP+ffff4mI\niGDOnDmiI0mSrjh841u/RH1u3LvBkatHREeRDGbpUqhaFQIDRSdxPOHh4Xh6elKrVi2cnBz+n7Gc\nOXoUnJygfHnRSSQrqlq1Kh06dGD69OnEPXx7SpIk2fjWL14fL1cvlh1ZZpP9jxw50ib7tQUjZRUt\nNhZWrYLOnR99XNbQejKrZVJSEh4eHnZrek17XePiICwM2rR5dMxOOvRSA73kMIIxY8Zw6dIlevTo\nwZtvvik6jlXI6y/llMM3vh4uHnSq2Im5B+aSnJL+NDA5UaJECavv01aMlFW0tWu1nqFTp0cflzW0\nnsxqWbhwYa5fv05SUpLwLIb22WcQFQVffvnUTfVSA73kMIJKlSqxcOFCli9fTkREhOg4ViGvv5RT\nDt/4AgyoMYCzt87a5FXfoUOHWn2ftmKkrKJduqTN+V+mzKOPyxpaT2a1jI6OJk+ePDg7OwvPYlhX\nr8Lnn8OwYU/+RU6HXmqglxxGkJiYyMKFC3F2dqZfv36i41iFvP5STsnGF6jlV4vmpZvz/ub3uXzn\nsug4kkGkpIBcKdf+YmNjOXz4MCEhISiKIjqOcU2dCooCo0aJTiLZyIgRI1i+fDk//fQT7du3Fx1H\nknRBNr4PfNnqS+4m3KXW97XYf8U2k+BL5hEUBAkJcETeE2lXCQkJLFy4ECcnJ2rXri06jrE5OUGu\nXCCXujUtb29vXFxcaNCggegokqQbsvF9oGKhiuzuu5sinkWoP7s+U3dPtcqY32PHjlkhnX0YKato\nDRuCm5u2+FVasobWk14t//zzT65evUr37t3Jly+f0CyG99xzcOsWHDqUpc31UgO95DCCDh06EBcX\nx/Tp001TN7OchyROLtEB9MQvrx9be21lxLoRDP19KHMPzOW7dt9RvVh1i/c5atQoVq5cacWUtmOk\nrKJ5eMBLL2nvFr/xBjycQlbW0HrSq6WTkxOurq4UKVJEeBbDe3hjYBYXBNBLDfSSQ89UVWXOnDm8\n8cYbFC9enNatW5umbvY6jyaRCyh83eaHMYzoe7BEdAgrka/4Pia3S26mt5vOjt47iE+Kp+bMmnRc\n2pHfjv9GYnJitvc3depUG6S0DSNl1YPRo7WVXn/44b/HZA2tJ71ahoSEEBsby/ksLLFr6yyGt3On\n9rZFFm5sA/3UQC859Cg5OZlff/2VRo0a0adPH1566SUOHTpEjRo1TFM3s5yHJI5sfDNQt3hd9vTf\nw5TWUzh98zShi0Px/8KfEetGcDDqYJb3Y6SpV4yUVQ8qVYKXX9Ya4Kgo7TFZQ+tJr5YPb2bLlcu+\nb1aZ7rpGR8PEidCzJ2RxZgy91EAvOfTkzp07fP311wQFBfHCCy+QnJzM6tWrmT17duqQILPUzV7n\nociPJz7MQg51yISLswuDag5iUM1B7L+yn7n75zL/4Hy+2PkFJfOVpFKRSoQUCtH+LBxCkE8Qbrnc\nRMeW7Ojzz+H332HQIFi2TLtJXrK+uLg4jh49yv79+1EUhcKFC4uOZGyTJ8Pdu/DRR6KTSDmgqiqz\nZs1i5MiR3Llzh06dOrFw4UJq1aolOpok6ZZsfLOoatGqVG1VlQnNJ7D25Fr+Ov8Xh6MPs+DQAi5s\nvwBALqdclPMpR0jhEEIKhRBSWGuKS3mXwtnJPvONSvZVsCB8+622kMUPP0CvXqITmUdsbCzHjh3j\nyJEjnDlzBoCAgAA6deqEq6ur4HQG17Kl9orvtGkwfrzoNJIFzpw5Q//+/fnjjz949dVX+fDDDyle\nvLjoWJKke7LxzSYXZxfaB7WnfdB/cyLeun+L8OhwDkcf5lD0IQ5HH+aP039w494N2AZujdwoka8E\nJfKVoGS+kpT0LvnI5/55/XF1Fv8feVhYGKNHjxYdw3BeeglefRVefx3Onw/jgw9kDXNq586dvPfe\nezRs2JCAgADatGlDhQoV8PT0FJLHdD8bTZrA//4H770HHTtC5cpP/Ra91EAvOUQ6duwYNWvWpECB\nAqxbt44WLVo89XvMUjeznIckjmx8rcDb3Zv6JepTv0T91MdUVeXK3SuMujaKms1rcj7mPOdiznEo\n+hCrI1YTFRuVuq2CQjGvYv81w/keNMbe/32ez932UzfFxcXZ/BhmNXKk9orv6dOyhjmhqipbtmxh\ny5YtFC5cmDfffFNYs5uWKX823noLPvhAu8ktC42vXmqglxyiqKrKoEGDKFKkCHv37iVv3rxZ+j6z\n1M0s5yGJIxtfG1EUrZn9ccqP6T5/L/EekbcjORdzjnO3zqU2xudizvHPpX+4EHOBxJT/ZpHwcvXC\nP6//Ex9+Xn6pnxfwKJCjlazGy7c8LVa2rLYeQI0asoY5ERERwZYtW2jSpAkffPCB6DipTPmz4eYG\n5crBli3Qv/9TN9dLDfSSQ5RJkyaxadMm1q5dm+WmF8xTN7OchySObHwF8XDxINAnkECfwHSfT05J\nJio2inO3tGY48nYkkbcjuXjnIkevHWXD6Q1cunOJFDUl9Xvcc7mn2xCnfaxIniI4KXIyD2tbt05b\nwrhePdFJzKFyFl6BlKxg0CBtjM6wYSBviNK9adOmMWrUKMaMGUPLli1Fx5EkQ5KNr045Oznj6+WL\nr5cvdYvXTXebpJQkou5GpTbED5vjyNuRnI85z9+RfxN5O5KE5ITU7/HI5UE5n3KU8ylHkE8QQQWD\nUj+3x3AKs/rxR6heHZ55RnQSYytatCgA4eHh1JO/Rdjea6/BrFnQr5825MHDQ3QiKQO7du1iyJAh\njBgxgo/kbBySZDHZ+NrYtWvXKFiwoE32ncspF355/fDL65fhNqqqci3uGpG3I7lw+wKnb57m+LXj\nHL9+nO0XtnPpzqXUbQtSkAolKhDk86AZLhhEkE8QgT6B8lXipwgPh6ZNbXu9HUHevHmpU6cOGzZs\nANBN82va65orlzY4vU4dGDJEa4IzoJca6CWHvS1evJhixYoxceJEi4a0maVuZjkPSRzZzdhY7969\nhR5fURQKeRaiWrFqhAaF8kadN/i23bdsfGUjF0dc5M47d9jTfw8LOyykwPoC+Of1Z++VvXy49UOe\nX/w85aeVp9bMWkRcjxB6Hnp39SrcuCH+eptBixYtKFeuHH379kVVVdFxAJNf1ypVtDn5Zs+GB79w\npEcvNdBLDnvbsmULnp6eqVP7ZZdZ6maW85DEkY2vjY0bN050hEzlcc1D9WLV6VqpK4umLGJhx4Xs\n6b+H22/f5uKIi6zquoqY+BiqfVeNlceNv867rXz4ISxYACVKjBMdxfAevprVsWPHHN2saU16/znO\nsVdegfLlYf78DDfRSw30ksPepkyZQnJyMpUrV2batGmkpKQ8/ZvSMEvdzHIekjiy8bWx6tWri46Q\nZWmzpqgpRN2N4sytM5QvWJ7YxFjGb5Z302bktddg3DiYNq06S5aITmNsycnJnDx5kjZt2oiOkspI\nP8cWURRtQurVqzPcRC810EsOe6tfvz4HDx7klVdeYciQIdSpU4ctW7Zk+fvNUjeznIckjmx8JVRV\nJepuFBtObWDc5nE0/7E53mHeVJ9RnRHrRnAt7hpv1n2TyS0mi46qa++/D127Qp8+cPSo6DTGpaoq\nKSkpupi/16EULgxyjlRdy5MnD9988w1btmxBVVWee+452rdvz5EjR0RHkyTDkDe3OYCklCQu3r6Y\nOmfwI3/GaHMI30+6D4CPhw/1itfj3YbvUr94fWr41sDDRbvTe+/evSJPQ/cUBSZMgKVL4aOPtKEP\nUvbdv6/9XXR2lst825WHB8THw9692hQlkm49++yz7Nq1i59++ol33nmH6tWrs2rVKpo1ayY6miTp\nnmx8bWzWrFn06dPHpseIS4zjQsyF/xbBSNPUnrulzQGcrCanbu/j4ZO6Klybsm1SPw9fF867w97V\nzbhKo7l7Fxo1mkW+fH0YM0Z0GuM6cuQITk5ObN26leDgYNFxAPv8HAvXtSt89x20bw+7doG//yNP\n66UGeskhmpOTE507d+b555+nQ4cOPP/886xdu5aGDRumu71Z6maW85DEkY2vje3duzdHP6TxSfFc\nvHORCzEXuHD7wn9/pvn8xr0bqdsrKPh6+aY2s/X866V+/vBPT9f030L+Y+ofsum10Jo1MHQoXLiw\nlx07+qCTfs2QIiMj8fLy4tChQ6KjpMrpz7EheHrCypVQuzY8+yz8+itUqpT6tF5qoJcceuHu7s7P\nP/9M27ZtadKkCf379+e9995LnRP7IbPUzSznIYkjG18bmzZtWqbPX4+7zvHrxzkfcz7dpjY6NvqR\n7Qt4FKB43uIUz1ecesXr4Z/XP/XrEvlK4J/XH1dnV5tklZ50/ry26NWKFdo8vmvWTCMoSHQqY6td\nuzbh4eF07NhRdJRUDvOzUawYbN0KL7wAdetqK7O8+CKgnxroJYeeeHh4sGbNGr7++ms+/fRT5s6d\ny4gRIxg1ahR58uQBzFM3s5yHJI5sfO1AVVWu3L3C0WtHOXL1CEeuHkn9PG1j6+XqRfF8xSmetzjV\nimrz7j5saovnLY5/Xv8MX62V7G/bNnj+eXB3hyVLoFMnbZyvlDN+fn4899xzbNy4kcuXL9O4cWP8\n/DJepEWysoAA2L4devWCDh1g/HgYOxac5L3Qeubu7s6oUaPo168fn332GRMnTuTKlSvMmDFDdDRJ\n0hXZ+FrZ3YS7bD+/nfCr4Ry9epQj17RG99b9WwC4OrtSzqccFQtV5LmSz1GxUEXKFyxPSe+S5HXL\nKzi9lFVLl0LPntqLYr/8Avnzi05kLg0aNMDHx4fNmzfz/fffU65cOZo0aUKRIkVER3MMnp7ab3OV\nK8N778GBAzB3Ljx49VDSr/z58xMWFkaePHkICwtj8uTJeHl5iY4lSbohG18ruHznMiuPr2TliZX8\nefpP4pPj8cjlQYVCFahYqCJtA9tSsVBFKhaqSOn8pcnlJMtuZJs3a/cBdemiLXbl5iY6kfkoikLF\nihUpX748hw8fZsuWLcycOZNOnToRJMeS2IeiaK/0VqoEPXpAvXrauN9SpUQnk7Lg1Vdf5YMPPmDJ\nkiX07dtXdBxJ0g353pWFTt04xSd/fULt72vj+7kvg9YMIjYhlk+bfsqxwce4O+Yue/rvIWZODGMa\njuGF8i9Qzqecrpve0NBQ0RF0LzoaunWDRo1g3rwnm15ZQ+sJDQ3FycmJypUrM3DgQMqVK8eSJUs4\ncOCAkCwO6/nnYedOQk+dgpo1td/8BHLoa5ENxYsXp1WrVsyaNQswT93Mch6SOPrtwnTq7wt/M+nv\nSSw/uhxPV09alW3FkJpDaBPYBp/cPk9sP2TIEAEpLWOkrKK88w4kJmpz9KY3zaysofWkrWWuXLl4\n6aWX+O2331ixYgXh4eE0b96cQoUK2T2LQwoOZsi8eTBtmjbu98oVcLXsJtqccvhrkQ0PhwulpKSY\npm5mOQ9JHNn4ZtGaiDV88tcnbL+wnXI+5fiu3Xf0qNwjdXGHjLRo0cJOCXPOSFlFOHlSG+Y4aZJ2\n83t6ZA2t5/FaOjk5ERoaSmBgIH/88QfffvstNWrUoGnTprjZeLyJvK7QomNHCArShj6sW6fN9ysi\nh7wWWTJ9+nTmz5/PzJkzcXJyMk3dzHIeUvYpipILcFdV9W5O9iOHOjyFqqqM3TiWtgvboqKyovMK\njg4+Sr9n+j216ZXM5YcfwNsbBgwQncRxPRz7O2jQIKpXr84///zDsWPHRMdyHCEhUK2aNoff2bOi\n00gZ+PLLLxk0aBBDhgyR43slw1EUpb2iKK8+9ti7wF3glqIo6xVFsfiWctn4ZiIpJYlXf32Vj//6\nmLBmYWzrtY3nyz+PkyLL5oj++Ue7v8dD/r4jnKqqnD17lqJFixISEiI6jmNZvlyb2uzZZ+H0adFp\npDRUVeWNN95g+PDhvPXWW3z11VeiI0mSJUYAqXO3KopSD/gQ+B/wf0Bx4D1Ldy47uExM3D6R+Qfn\ns6DDAkbVH2XRqmYrVqywQTLbMFJWEY4f56krsskaWk9mtVy/fj0xMTF06NAB5/QGW9sxi6NIrUHJ\nkrBpE1y8qL0NIiqH9IRNmzbx1Vdf8dVXXzFhwgSc0sy9bJa6meU8pEwFAzvSfP0SsEFV1Y9VVf0F\neBOweKyVbHwzcPLGST7c+iEj6oygW6VuFu9n0aJFVkxlW0bKKkJCwtNf7ZU1tJ6MannixAn+/fdf\nWrRoYbeb2+R1fawGERGQkgJt2ojNIT1i6dKlBAQEMHTo0CeeM0vdzHIeUqa8gOtpvm4A/Jnm63DA\n19Kdy8Y3HdfjrhO6KBRfL1/GPTcuR/tasmSJdULZgZGyipCUBLmecjuorKH1ZFTLiIgIAAoWLCg8\niyNJrcGvv2rLFAYHQ+3a4nJIT9i/fz8NGjRI991Js9TNLOchZeoiUAFAUZQ8QBUefQXYB4izdOey\n8X1MbEIsbRa24VrcNX7v/rtcIlhKlZgILi6iU0jNmzenTJkyLFiwILUJluwgJQVefx1eeEEb3/v/\n7d13nFTV2cDx30PbBQUpS5XiAgKGphCxBlTANURUbBs0riVGxIaJrwU/GkB8E0sKFlCxBfEVYiUK\nYkNij4TecWlBQl1AWMrCsnveP85dHcYtU+7M2bnzfD+f+4GZe+7Z5z537syZM/ee8+mnOkd3NdOu\nXTv++9//ug5DqXi9BowTkauAZ4EtwL9C1v8UWBVr5drwDWGM4cYZN7Js2zJmXjmTTk06uQ5JVRNF\nRbB3L+jMn+7VqVOHIUOGALB48WLH0aSRr7+GJ56ARx+183Q3buw6IhWmTZs2bNy40XUYSsXrAeDf\nwOPAicCvjDElIeuHAu/EWrmO4xvixYUvfn8zW+9WvV2Ho6qRJUvspQ69ermORAG8//771KpVi/79\n+7sOJX0sWWJnbbnlFu3praaOPvpo9u+P+RdgpaoFY8wBIK+S9WfHU7/2+IZ4ddmr9GvXL66b2cJd\ne+21vtWVaKkUa7J9+aWdqKpHj8rLaQ79U1EuCwoKWLJkCTk5OTRs2NBpLOnk2kmT7OUOCxe6jUOP\nRYWKi4uPGMkhVFDyFpT9UNETkX4iMiieMXxBG75HyG6Yzc4DO32tM5VmmUmlWJNt9mw47TTIzKy8\nnObQPxXlcsmSJWRkZNC9e3fnsaSTc4cPh5NPhrw8cNirqMeiYmvWrKF9+/blrgtK3oKyH6piInK3\niIwNeSwi8h4wG5gOrBCRKgYXrZg2fEN0zupM/s58Sk2pb3UOHTrUt7oSLZViTaaSEvjkEzg7gh9X\nNIf+qSiXhw4dAmDfvn3OY0knQ3/1Kztn97p1MH68uzj0WJRr3bp1TJ8+ndNOO63c9UHJW1D2Q1Uq\nF1ga8vhSoC/wMyALmAuMirVybfiG6NSkE0WHi/h297euQ1HVyOLF8N13kTV8VeL17duXjIwMpk2b\nhjHGdTjppUsXuP56ePhhKCx0HY3yGGO4/vrrycrK4t5773UdjlLxygZC71weBLxujPnCGLMTeBAo\n/xteBLThG2L7vu0AMc3QpoJr9mx7iYODIUtVOerWrcv555/P+vXr+fZb/ZKadPfeCzt3wmuvuY5E\neebNm8fHH3/M448/Tn0dekalvlrAwZDHp3HkOL6bsD2/MdGGb4iJ8ycyoP0A2h7T1rc6P//8c9/q\nSrRUijWZZs+G00+HjIyqy2oO/VNZLtu3b09mZiZLlixxHku6+D4HbdrAWWfByy+Dgx53PRY/NmXK\nFJo1a8agSmbSC0regrIfqlJrsJc2ICJtgU7ApyHrW3PkzG5R0YZviLW71tKnVR9f63zkkUd8rS+R\nUinWZDl82I7TH+llDppD/5SXy+LiYubMmcMTTzxBUVERmVXdbZjAWNLNETkYPtx+I3zsMbdxKLZu\n3crEiRPJy8ujViVTSwYlb0HZD1Wp8cCTIvI8MBP4yhizPGT9OcCCWCvXcXxD9GrZi7mb5/pa59Sp\nU32tL5FSKdZkWbgQ9uyJvOGrOfRPeC4XLlzIhx9+yIEDB+jWrRtnnHEGzZs3dxJLOjoiB5ddBnfe\nCb/7HXTqBJX0NCY0DsXo0aOpXbs2I0eOrLRcUPIWlP1QFTPGPCsiJcBgbE/vmLAirYAXYq1fG74h\nBnWpyi7PAAAf0UlEQVQcxG3v3cbCLQs5scWJvtRZr149X+pJhlSKNVlmzIAGDewoTpHQHPonNJfF\nxcXMnDmT7OxscnJyaNQormEc44olXf0oBw89ZO/8vPVWGDgwafN567E40gcffMA111xD4ypm0gtK\n3oKyH6pyxpgXqKBxa4y5KZ669VKHEDf0voEuWV0Y8d4I16GoauLNN2HwYDt5hXJn1apVHDp0iAED\nBiS90asqUKMGPPIIrF0Lkye7jiZtFRQU0KpVK9dhKJUytOEbonbN2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fQ4JdugQXb5+mvb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\naeH/AdVGq0u0mSXNAAAAAElFTkSuQmCC\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f2175f14898>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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8PPyxRPfq1asAFC1alNDQUIYPH05oaCghISFZ/nAohDVzmH/ZlFK0KNWCZiWb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uw9XlGHXZtypRXKfX3R2efPLf70sSZGbCmTNM/PVX+dXcmTPyac7iNsQAjRvLb2U895zaRbBS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\n",
+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f217d766ac8>"
+      ]
+     },
+     "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_3.csv')\n",
+    "\n",
+    "for wellId in well_names_validate:\n",
+    "    make_facies_log_plot( test_data[test_data['Well Name'] == wellId], 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_3.csv b/StoDIG/Prediction_StoDIG_3.csv
new file mode 100644
index 0000000..244d79d
--- /dev/null
+++ b/StoDIG/Prediction_StoDIG_3.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,2810.0,75.971,0.638,8.7,12.35,3.02,1,0.9109999999999999,2
+5,A1 SH,STUART,2810.5,73.955,0.667,6.9,12.25,3.0860000000000003,1,0.889,2
+6,A1 SH,STUART,2811.0,77.962,0.674,6.5,12.45,3.092,1,0.867,2
+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,2814.0,63.983000000000004,0.69,4.4,9.7,3.103,1,0.733,1
+13,A1 SH,STUART,2814.5,61.797,0.675,3.5,9.15,3.1010000000000004,1,0.711,1
+14,A1 SH,STUART,2815.0,61.372,0.6459999999999999,2.8,9.3,3.065,1,0.6890000000000001,1
+15,A1 SH,STUART,2815.5,63.535,0.621,2.8,9.8,2.9819999999999998,1,0.667,1
+16,A1 SH,STUART,2816.0,65.126,0.6,3.3,10.55,2.9139999999999997,1,0.644,1
+17,A1 SH,STUART,2816.5,75.93,0.5760000000000001,3.4,11.9,2.845,1,0.6,1
+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,2827.0,73.327,0.489,6.3,20.35,2.88,1,0.111,2
+39,A1 SH,STUART,2827.5,74.575,0.526,4.9,19.25,2.795,1,0.08900000000000001,2
+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,2839.0,54.828,1.0290000000000001,0.8,8.2,3.395,2,0.75,4
+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,2843.0,36.084,0.882,1.6,8.2,4.125,2,0.645,6
+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,-0.6,9.0,4.178,2,0.395,6
+90,A1 LM,STUART,2853.0,36.109,0.773,0.1,8.35,4.203,2,0.382,6
+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,2860.0,72.543,0.748,4.1,10.35,3.359,2,0.19699999999999998,6
+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,2881.0,72.69,0.5579999999999999,4.8,18.5,2.969,1,0.129,2
+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,2889.5,39.389,0.627,3.4,11.2,3.6289999999999996,2,0.581,6
+164,B1 LM,STUART,2890.0,49.385,0.535,6.4,11.5,3.517,2,0.5479999999999999,6
+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,2903.5,71.858,0.635,8.5,15.95,3.485,1,0.526,2
+192,B2 SH,STUART,2904.0,64.70100000000001,0.737,5.0,15.7,3.471,1,0.474,2
+193,B2 SH,STUART,2904.5,64.293,0.752,1.7,17.15,3.45,1,0.42100000000000004,2
+194,B2 SH,STUART,2905.0,67.158,0.6859999999999999,-0.3,19.95,3.2760000000000002,1,0.368,2
+195,B2 SH,STUART,2905.5,72.47800000000001,0.631,0.2,20.4,3.1710000000000003,1,0.316,2
+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,2919.0,32.64,0.807,1.0,5.6,4.343,2,0.185,8
+223,B2 LM,STUART,2919.5,33.571,0.9420000000000001,1.6,4.5,4.086,2,0.14800000000000002,8
+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,2921.0,56.443000000000005,0.821,2.3,8.05,3.3930000000000002,2,0.037000000000000005,6
+227,B3 SH,STUART,2921.5,64.79899999999999,0.7509999999999999,3.4,9.6,3.12,1,1.0,2
+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,2925.0,68.937,0.5870000000000001,4.1,13.25,3.122,1,0.7,2
+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,2931.0,72.609,0.525,5.5,17.55,3.31,1,0.15,2
+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,-1.4,5.5,4.527,2,0.429,8
+287,B4 LM,STUART,2951.5,25.721,1.079,-0.9,4.45,4.512,2,0.35700000000000004,8
+288,B4 LM,STUART,2952.0,29.45,1.2,0.0,4.0,4.437,2,0.28600000000000003,8
+289,B4 LM,STUART,2952.5,36.313,1.169,-3.3,6.95,3.97,2,0.214,8
+290,B4 LM,STUART,2953.0,49.49100000000001,0.909,-8.9,13.85,3.695,2,0.14300000000000002,8
+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,-0.5,16.75,4.126,1,0.25,8
+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,-1.6,11.0,4.824,2,0.39,8
+320,B5 LM,STUART,2968.0,33.211999999999996,0.574,-3.1,14.45,4.765,2,0.366,8
+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,-2.0,14.6,4.453,2,0.293,8
+324,B5 LM,STUART,2970.0,65.167,0.525,-1.6,13.1,4.3660000000000005,2,0.268,8
+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,2974.5,60.931999999999995,0.857,1.3,7.35,3.3710000000000004,2,0.024,6
+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
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+356,C SH,STUART,2986.0,70.35600000000001,0.6509999999999999,11.0,13.1,3.447,1,0.442,2
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