1921 lines
1.5 MiB
1921 lines
1.5 MiB
{
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"# CSC 3105 Project"
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],
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"metadata": {
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"collapsed": false
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},
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"id": "cda961ffb493d00c"
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Data Preprocessing and Analysis"
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],
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"metadata": {
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"collapsed": false
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},
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"id": "73fe8802e95a784f"
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},
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{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"import os\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"import pywt\n",
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"import tensorflow as tf\n",
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"from skimage import restoration\n",
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"from sklearn.metrics import classification_report\n",
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"from sklearn.model_selection import train_test_split\n",
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"from sklearn.preprocessing import LabelEncoder\n",
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"from sklearn.preprocessing import StandardScaler\n",
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"from tensorflow.keras import regularizers\n",
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"from tensorflow.keras.callbacks import EarlyStopping\n",
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"from tensorflow.keras.layers import Conv1D, Flatten, Dense, Dropout, BatchNormalization\n",
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"from tensorflow.keras.models import Sequential\n",
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"from tensorflow.keras.optimizers import Adam\n",
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"from tensorflow.keras.models import Sequential\n",
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"from tensorflow.keras.layers import Dense, Dropout, BatchNormalization\n",
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"from tensorflow.keras.callbacks import EarlyStopping\n",
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"from tensorflow.keras import regularizers\n",
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"from tensorflow.keras.optimizers import Adam\n",
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"from sklearn.metrics import classification_report, confusion_matrix, roc_curve, auc\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"\n"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-03-20T12:32:16.264433Z",
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"start_time": "2024-03-20T12:32:16.258838Z"
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}
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},
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"id": "2aa3c6c09e8645d1",
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"execution_count": 115
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Load the Data\n",
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"\n",
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"This code block defines a function `load_data` to load the dataset from the specified directory. The function uses the `os` and `pandas` libraries to load the data from multiple CSV files into a single DataFrame. The `os` library is used to traverse the directory and find all the CSV files, while the `pandas` library is used to read the CSV files and concatenate them into a single DataFrame. The function then prints the shape of the original data."
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],
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"metadata": {
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"collapsed": false
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},
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"id": "e7597045d3c34419"
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},
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{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"# Define the directory where the dataset is located\n",
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"DATASET_DIR = './UWB-LOS-NLOS-Data-Set/dataset'\n",
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"\n",
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"\n",
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"def load_data(dataset_dir):\n",
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" # Load the data\n",
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" # file_paths = [os.path.join(dirpath, file) for dirpath, _, filenames in os.walk(dataset_dir) for file in filenames if 'uwb_dataset_part7.csv' not in file]\n",
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" file_paths = [os.path.join(dirpath, file) for dirpath, _, filenames in os.walk(dataset_dir) for file in filenames]\n",
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" data = pd.concat((pd.read_csv(file_path) for file_path in file_paths))\n",
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" print(f\"Original data shape: {data.shape}\")\n",
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" return data\n"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-03-20T12:32:16.712520Z",
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"start_time": "2024-03-20T12:32:16.708317Z"
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}
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},
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"id": "7bcd7cfc8dd11cbb",
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"execution_count": 116
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Statistical Analysis and Plots\n",
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"\n",
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"This code block defines a function `stat_analysis_and_plots` to perform statistical analysis and plot boxplots of the first 15 columns of the data. The function uses the `describe` method of the DataFrame to perform statistical analysis and the `boxplot` method of the `matplotlib` library to plot boxplots of the first 15 columns of the data. The boxplot is used to check for outliers in the data."
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],
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"metadata": {
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"collapsed": false
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},
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"id": "8cdfcf73ad317dd5"
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},
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{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"def stat_analysis_and_plots(data):\n",
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" # Statistical Analysis\n",
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" print(\"Statistical Analysis:\")\n",
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" print(data.describe())\n",
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"\n",
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" # Plot Boxplot to check for outliers for the first 15 columns\n",
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" print(\"Boxplot of the first 15 columns:\")\n",
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" fig, axs = plt.subplots(15, 1, dpi=95, figsize=(7, 17))\n",
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" for i, col in enumerate(data.columns[:15]):\n",
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" axs[i].boxplot(data[col], vert=False)\n",
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" axs[i].set_ylabel(col)\n",
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" plt.show()\n"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-03-20T12:32:16.772316Z",
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"start_time": "2024-03-20T12:32:16.768310Z"
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}
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},
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"id": "9e0b1ed6f23a17cf",
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"execution_count": 117
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Channel Impulse Response (CIR) Graphs\n",
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"\n",
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"This code block defines a function `cir_graphs` to plot the Channel Impulse Response (CIR) for Line of Sight (LOS) and Non-Line of Sight (NLOS) data. The CIR is a sequence of values representing the channel response to a single impulse. It is used to characterize the channel in wireless communication systems."
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],
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"metadata": {
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"collapsed": false
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},
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"id": "1dd92fe7b6881ea6"
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},
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{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"def cir_graphs(data):\n",
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" # Separate the data into LOS and NLOS\n",
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" data_los = data[data['NLOS'] == 0]\n",
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" data_nlos = data[data['NLOS'] == 1]\n",
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"\n",
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" # Extract the CIR columns\n",
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" cir_columns = [col for col in data.columns if 'CIR' in col]\n",
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" data_los_cir = data_los[cir_columns]\n",
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" data_nlos_cir = data_nlos[cir_columns]\n",
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"\n",
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" # Calculate the magnitude and time for each CIR column\n",
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" time_los = np.arange(len(data_los_cir.columns))\n",
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" magnitude_los = np.linalg.norm(data_los_cir.values, axis=0)\n",
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"\n",
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" time_nlos = np.arange(len(data_nlos_cir.columns))\n",
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" magnitude_nlos = np.linalg.norm(data_nlos_cir.values, axis=0)\n",
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"\n",
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" # Plot the magnitude vs time for LOS\n",
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" plt.figure(figsize=(20, 10), dpi=300) # Increase figure size and DPI\n",
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" plt.plot(time_los, magnitude_los, linewidth=2) # Increase line width\n",
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" plt.title('Magnitude vs Time for LOS')\n",
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" plt.xlabel('Time (ns)')\n",
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" plt.ylabel('Magnitude')\n",
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" plt.xlim([600, max(time_los)]) # Set x-axis limits\n",
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" # plt.ylim([0, 2e6])\n",
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" plt.show()\n",
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"\n",
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" # Plot the magnitude vs time for NLOS\n",
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" plt.figure(figsize=(20, 10), dpi=300) # Increase figure size and DPI\n",
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" plt.plot(time_nlos, magnitude_nlos, linewidth=2) # Increase line width\n",
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" plt.title('Magnitude vs Time for NLOS')\n",
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" plt.xlabel('Time (ns)')\n",
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" plt.ylabel('Magnitude')\n",
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" plt.xlim([600, max(time_los)]) # Set x-axis limits\n",
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" # plt.ylim([0, 2e6])\n",
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" plt.show()\n"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-03-20T12:32:16.839860Z",
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"start_time": "2024-03-20T12:32:16.833158Z"
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}
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},
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"id": "308d64639b199bc7",
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"execution_count": 118
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Calculate Total Distance\n",
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"\n",
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"This code block defines a function `calculate_total_distance` to calculate the total distance for each data point. The total distance is calculated as the sum of the absolute values of the Channel Impulse Response (CIR) columns multiplied by the speed of light in meters per nanosecond.\n",
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"\n",
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"$$\n",
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"\\text{Total Distance} = \\sum_{i=1}^{n} |CIR_i| \\times \\text{speed of light}\n",
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"$$\n",
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"where:\n",
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"- $n$ is the number of CIR columns\n",
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"- $CIR_i$ is the $i$-th CIR column\n",
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"- $\\text{speed of light}$ is the speed of light in meters per nanosecond"
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],
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"metadata": {
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||
"collapsed": false
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||
},
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"id": "531a6ffbad89ba15"
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},
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{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"def calculate_total_distance(data):\n",
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" # Speed of light in meters per nanosecond\n",
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" speed_of_light_ns = 0.299792458\n",
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"\n",
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" # Extract the CIR columns\n",
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" cir_columns = [col for col in data.columns if 'CIR' in col]\n",
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"\n",
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" # Calculate the total distance for each row\n",
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" data['Total_Distance'] = data[cir_columns].abs().sum(axis=1) * speed_of_light_ns\n",
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"\n",
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" return data"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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||
"end_time": "2024-03-20T12:32:16.881491Z",
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"start_time": "2024-03-20T12:32:16.877190Z"
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}
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},
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"id": "80cfcfac265d9357",
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"execution_count": 119
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Signal to Noise Ratio (SNR) Graph\n",
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"\n",
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"This code block defines a function `snr_graph` to plot the Signal to Noise Ratio (SNR) for Line of Sight (LOS) and Non-Line of Sight (NLOS) data. The SNR is calculated as the ratio of the 'CIR_PWR' to the 'STDEV_NOISE' for each data point."
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],
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"metadata": {
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||
"collapsed": false
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||
},
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||
"id": "bfd97fbe797a7067"
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||
},
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||
{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"\n",
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"def snr_graph(data):\n",
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" # Separate the data into LOS and NLOS\n",
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" data_los = data[data['NLOS'] == 0]\n",
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" data_nlos = data[data['NLOS'] == 1]\n",
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"\n",
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" # Extract the SNR values\n",
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" snr_los = data_los['SNR']\n",
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" snr_nlos = data_nlos['SNR']\n",
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"\n",
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" # Create a new figure\n",
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" plt.figure(figsize=(10, 5))\n",
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"\n",
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" # Plot SNR for LOS\n",
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" plt.plot(snr_los, label='LOS')\n",
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"\n",
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" # Plot SNR for NLOS\n",
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" plt.plot(snr_nlos, color='red', label='NLOS')\n",
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"\n",
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" # Set title and labels\n",
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" plt.title('SNR for LOS and NLOS')\n",
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" plt.xlabel('Index')\n",
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" plt.ylabel('SNR')\n",
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"\n",
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" # Add a legend\n",
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" plt.legend()\n",
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"\n",
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" # Show the plot\n",
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" plt.show()\n"
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],
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"metadata": {
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||
"collapsed": false,
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||
"ExecuteTime": {
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||
"end_time": "2024-03-20T12:32:16.951436Z",
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||
"start_time": "2024-03-20T12:32:16.946803Z"
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}
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},
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"id": "4afc8d71b3271351",
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"execution_count": 120
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},
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{
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"cell_type": "markdown",
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"source": [
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"# Plot Histogram\n",
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"\n",
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"This code block defines a function `plot_histogram` to plot a histogram of a given feature in the data for Line of Sight (LOS) and Non-Line of Sight (NLOS) data."
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],
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"metadata": {
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||
"collapsed": false
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||
},
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"id": "74cbef5687382eea"
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||
},
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{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"\n",
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"\n",
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"def plot_histogram(data, feature):\n",
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" \"\"\"\n",
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" Function to plot a histogram of a given feature in the data for 'NLOS' and 'LOS'.\n",
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"\n",
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" Parameters:\n",
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" data (pd.DataFrame): The data.\n",
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" feature (str): The name of the feature to plot.\n",
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"\n",
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" Returns:\n",
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" None\n",
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" \"\"\"\n",
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" # Check if the feature exists in the data\n",
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" if feature not in data.columns:\n",
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" print(f\"The feature '{feature}' does not exist in the data.\")\n",
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" return\n",
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"\n",
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" # Separate the data into 'NLOS' and 'LOS'\n",
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" data_nlos = data[data['NLOS'] == 1]\n",
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" data_los = data[data['NLOS'] == 0]\n",
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"\n",
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" # Create a figure with two subplots side by side\n",
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" fig, axs = plt.subplots(1, 2, figsize=(10, 5))\n",
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"\n",
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" # Plot the histogram for 'NLOS'\n",
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" axs[0].hist(data_nlos[feature], bins=30, edgecolor='black')\n",
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" axs[0].set_title(f'Histogram of {feature} for NLOS')\n",
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" axs[0].set_xlabel(feature)\n",
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" axs[0].set_ylabel('Frequency')\n",
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"\n",
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" # Plot the histogram for 'LOS'\n",
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" axs[1].hist(data_los[feature], bins=30, edgecolor='black')\n",
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" axs[1].set_title(f'Histogram of {feature} for LOS')\n",
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" axs[1].set_xlabel(feature)\n",
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" axs[1].set_ylabel('Frequency')\n",
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"\n",
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" # Display the plots\n",
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" plt.tight_layout()\n",
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" plt.show()\n",
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"\n",
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"# Usage:\n",
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"# plot_histogram(data, 'First_Path_Power_Level')"
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||
],
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||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:17.025822Z",
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||
"start_time": "2024-03-20T12:32:17.020403Z"
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||
}
|
||
},
|
||
"id": "22025d6c8281fc09",
|
||
"execution_count": 121
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||
},
|
||
{
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"cell_type": "code",
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"outputs": [],
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"source": [
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"def plot_features(data, labels, feature1, feature2):\n",
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" reds = labels == 1\n",
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" blacks = labels == 0\n",
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" plt.scatter(data[reds][feature1], data[reds][feature2], c=\"red\", s=20, edgecolor='k')\n",
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" plt.scatter(data[blacks][feature1], data[blacks][feature2], c=\"yellow\", s=20, edgecolor='k')\n",
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" plt.xlabel(feature1)\n",
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" plt.ylabel(feature2)\n",
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" plt.title(f\"Plot of data: {feature1} versus {feature2}\")\n",
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" plt.show()"
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],
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||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:17.098233Z",
|
||
"start_time": "2024-03-20T12:32:17.093633Z"
|
||
}
|
||
},
|
||
"id": "ac4db13fed3f9916",
|
||
"execution_count": 122
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||
},
|
||
{
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||
"cell_type": "markdown",
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"source": [
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"## denoise_cir Function\n",
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"\n",
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"The `denoise_cir` function uses the Discrete Wavelet Transform (DWT) to denoise the Channel Impulse Response (CIR) values. The DWT is a linear transformation that operates on a data vector whose length is an integer power of two, transforming it into a numerically different vector of the same length. The DWT of a signal `x` is calculated as follows:\n",
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"\n",
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"1. **Wavelet Decomposition:**\n",
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"\n",
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" The input signal `x` is passed through two complementary filters and emerges as two signals. The filter outputs are decimated by 2 (down-sampled) to get the approximation coefficients (cA) and detail coefficients (cD).\n",
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"\n",
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" The approximation coefficients represent the high-scale, low-frequency component of the signal, while the detail coefficients represent the low-scale, high-frequency component.\n",
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"\n",
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"2. **Thresholding:**\n",
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"\n",
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" The detail coefficients are thresholded to remove noise. The thresholding function `T` applied to the detail coefficients `x` is defined as:\n",
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"$$\n",
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"T(x) = x * I(|x| > \\text{{value}}) \\quad \\text{{for 'hard' thresholding}}\n",
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"$$\n",
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"\n",
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"$$\n",
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"T(x) = \\text{{sign}}(x)(|x| - \\text{{value}})_+ \\quad \\text{{for 'soft' thresholding}}\n",
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"$$\n",
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"\n",
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"where $I$ is the indicator function that is one if the argument is true and zero otherwise, $\\text{{value}}$ is the threshold value, and $(x)_+$ equals $x$ if $x > 0$ and zero otherwise.\n",
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"\n",
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"3. **Wavelet Reconstruction:**\n",
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"\n",
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" The original signal is reconstructed from the approximation and detail coefficients."
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||
],
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||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "69413268ac5b549d"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"def denoise_cir(cir_values, wavelet='db1', level=1):\n",
|
||
" # Perform wavelet decomposition\n",
|
||
" coeffs = pywt.wavedec(cir_values, wavelet, level=level)\n",
|
||
"\n",
|
||
" # Set the detail coefficients to zero\n",
|
||
" for i in range(1, len(coeffs)):\n",
|
||
" coeffs[i] = pywt.threshold(coeffs[i], value=0.5, mode='soft')\n",
|
||
"\n",
|
||
" # Perform wavelet reconstruction\n",
|
||
" denoised_cir = pywt.waverec(coeffs, wavelet)\n",
|
||
"\n",
|
||
" return denoised_cir\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:17.163273Z",
|
||
"start_time": "2024-03-20T12:32:17.159002Z"
|
||
}
|
||
},
|
||
"id": "fe3089568e99a58d",
|
||
"execution_count": 123
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"## deconvolve_cir Function\n",
|
||
"\n",
|
||
"The `deconvolve_cir` function applies the Richardson-Lucy deconvolution algorithm to deconvolve the Channel Impulse Response (CIR) values. \n",
|
||
"\n",
|
||
"In the context of signal processing, deconvolution is the process of reversing the effects of convolution on a signal. Convolution is a mathematical operation that blends two functions together and is often used to describe the effect of a linear time-invariant system on a signal. Deconvolution, therefore, attempts to recover the original signal that was convolved with the system's impulse response to produce the current signal.\n",
|
||
"\n",
|
||
"The Richardson-Lucy algorithm is an iterative method for deconvolution. It is particularly suitable for cases where the impulse response of the system (also known as the Point Spread Function, or PSF) is known, and the noise is Poissonian (such as in astronomical images). \n",
|
||
"\n",
|
||
"The algorithm works by iteratively refining an estimate of the original signal. In each iteration, it performs a prediction step where it convolves the current estimate with the PSF to predict the observed signal, and a correction step where it computes the ratio of the observed signal to the predicted signal, convolves this ratio with the PSF, and multiplies the result with the current estimate to get the next estimate.\n",
|
||
"\n",
|
||
"This process is repeated for a fixed number of iterations, or until the estimate converges to a stable solution. The result is a denoised estimate of the original signal.\n",
|
||
"\n",
|
||
"The mathematical formulas involved in the Richardson-Lucy deconvolution algorithm are as follows:\n",
|
||
"\n",
|
||
"1. **Prediction Step:**\n",
|
||
"\n",
|
||
" The current estimate of the latent image `x` is convolved with the PSF `h` to predict the observed image `y`. This can be represented as:\n",
|
||
"\n",
|
||
"$$\n",
|
||
"y = h \\ast x\n",
|
||
"$$\n",
|
||
"\n",
|
||
"where $\\ast$ denotes the convolution operation.\n",
|
||
"\n",
|
||
"2. **Correction Step:**\n",
|
||
"\n",
|
||
"The ratio of the observed image $y$ to the predicted image $y'$ is computed, then the PSF $h$ is convolved with this ratio and multiplied with the current estimate $x$ to get the next estimate $x'$. This can be represented as:\n",
|
||
"\n",
|
||
"$$\n",
|
||
"x' = x \\cdot (h \\ast \\left(\\frac{y}{y'}\\right))\n",
|
||
"$$\n",
|
||
"\n",
|
||
"where $\\div$ denotes element-wise division and $\\ast$ denotes the convolution operation.\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "e1edd5ef4f54e752"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"\n",
|
||
"def deconvolve_cir(cir_values, psf=None, iterations=50):\n",
|
||
" # If no point spread function is provided, create a simple one\n",
|
||
" if psf is None:\n",
|
||
" psf = np.ones((5,)) / 5\n",
|
||
"\n",
|
||
" # Perform Richardson-Lucy deconvolution\n",
|
||
" deconvolved_cir = restoration.richardson_lucy(cir_values, psf, num_iter=iterations)\n",
|
||
"\n",
|
||
" return deconvolved_cir"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:17.222240Z",
|
||
"start_time": "2024-03-20T12:32:17.218618Z"
|
||
}
|
||
},
|
||
"id": "670e8c2cf19126ea",
|
||
"execution_count": 124
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Clean the Data\n",
|
||
"\n",
|
||
"This code block defines a function `clean_data` to clean the dataset. The function performs the following steps:\n",
|
||
"\n",
|
||
"1. **Drop Missing Values**: It drops any rows with missing values in the dataset.\n",
|
||
"2. **Drop Duplicate Rows**: It drops any duplicate rows in the dataset.\n",
|
||
"3. **Convert 'NLOS' Column to Integer**: It converts the 'NLOS' column to integer data type (0 for Line of Sight (LOS), 1 for Non-Line of Sight (NLOS)).\n",
|
||
"4. **Calculate 'RX_Level'**: It calculates the 'RX_Level' feature using the formula.\n",
|
||
"5. **Replace Zero Values in 'RX_Level'**: It replaces zero values in 'RX_Level' with the median of 'RX_Level'.\n",
|
||
"6. **Calculate 'First_Path_Power_Level'**: It calculates the 'First_Path_Power_Level' feature using the formula.\n",
|
||
"7. **Calculate 'SNR'**: It calculates the 'SNR' feature as the ratio of 'CIR_PWR' to 'STDEV_NOISE' for each data point.\n",
|
||
"8. **One-Hot Encode Categorical Features**: It one-hot encodes the categorical features 'CH', 'FRAME_LEN', 'PREAM_LEN', and 'BITRATE'.\n",
|
||
"9. **Denoise 'CIR' Columns**: It denoises the 'CIR' columns using the `denoise_cir` function.\n",
|
||
"10. **Drop Columns with Only One Unique Value**: It drops any columns that have only one unique value.\n",
|
||
"11. **Print the Shape of the Cleaned Data**: It prints the shape of the cleaned data.\n",
|
||
"12. **Return the Cleaned Data**: It returns the cleaned data."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "b61e454327e5acbf"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"def clean_data(data):\n",
|
||
" print(\"Starting data cleaning process...\")\n",
|
||
"\n",
|
||
" # print(\"Before Cleaning\")\n",
|
||
" # stat_analysis_and_plots(data)\n",
|
||
"\n",
|
||
" # Calculate total number of missing values in the data\n",
|
||
" total_missing = data.isnull().sum().sum()\n",
|
||
" print(f\"Total number of missing values: {total_missing}\")\n",
|
||
"\n",
|
||
" # Data has no missing values\n",
|
||
" data = data.dropna()\n",
|
||
" print(\"Missing values dropped.\")\n",
|
||
"\n",
|
||
" # Data has no duplicate rows\n",
|
||
" data = data.drop_duplicates()\n",
|
||
" print(\"Duplicate rows dropped.\")\n",
|
||
"\n",
|
||
" # Convert 'NLOS' column to integer data type (0 for LOS, 1 for NLOS)\n",
|
||
" data['NLOS'] = data['NLOS'].astype(int)\n",
|
||
" print(\"'NLOS' column converted to integer data type.\")\n",
|
||
"\n",
|
||
" # Print line where CIR_PWR is 0\n",
|
||
" print(f\"Line where CIR_PWR is 0: {data[data['CIR_PWR'] == 0]}\")\n",
|
||
"\n",
|
||
" # Calculate the expression inside the log10 function\n",
|
||
" expression = (data['CIR_PWR'] * (2 ** 17)) / (data['RXPACC'] ** 2)\n",
|
||
"\n",
|
||
" # If the expression is 0, set 'RX_Level' to 0\n",
|
||
" zero_indices = expression == 0\n",
|
||
" data.loc[zero_indices, 'RX_Level'] = 0\n",
|
||
"\n",
|
||
" # For the rest of the data where the expression is not 0, calculate 'RX_Level'\n",
|
||
" # First, update the 'expression' and 'data' to exclude zero_indices\n",
|
||
" expression = expression.loc[~zero_indices]\n",
|
||
" data = data.loc[~zero_indices]\n",
|
||
"\n",
|
||
" # Now, calculate 'RX_Level' for the rest of the data\n",
|
||
" data['RX_Level'] = 10 * np.log10(expression) - data['PRFR']\n",
|
||
"\n",
|
||
" # Calculate the median of 'RX_Level'\n",
|
||
" median = data['RX_Level'].median()\n",
|
||
"\n",
|
||
" # Create the boolean mask on the same DataFrame 'data'\n",
|
||
" zero_indices = (data['RX_Level'] == 0)\n",
|
||
"\n",
|
||
" # Replace zero values in 'RX_Level' with the median\n",
|
||
" data.loc[zero_indices, 'RX_Level'] = median\n",
|
||
"\n",
|
||
" print(\"New feature 'RX_Level' created.\")\n",
|
||
"\n",
|
||
" # Calculate new feature 'First_Path_Power_Level'\n",
|
||
" data['First_Path_Power_Level'] = (10 * np.log10(\n",
|
||
" (data['FP_AMP1'] ** 2 + data['FP_AMP2'] ** 2 + data['FP_AMP3'] ** 2) / (data['RXPACC'] ** 2))) - 64\n",
|
||
" print(\"New feature 'First_Path_Power_Level' calculated.\")\n",
|
||
" data.drop(['FP_AMP1', 'FP_AMP2', 'FP_AMP3', 'RXPACC', 'PRFR'], axis=1, inplace=True)\n",
|
||
"\n",
|
||
" # Calculate SNR as the ratio of 'CIR_PWR' to 'STDEV_NOISE' for each data point\n",
|
||
" data['SNR'] = data['CIR_PWR'] / data['STDEV_NOISE']\n",
|
||
" print(\"New feature 'SNR' created.\")\n",
|
||
" data.drop(['CIR_PWR', 'STDEV_NOISE'], axis=1, inplace=True)\n",
|
||
"\n",
|
||
" plot_histogram(data, 'First_Path_Power_Level')\n",
|
||
" plot_histogram(data, 'RX_Level')\n",
|
||
"\n",
|
||
" # One-hot encode categorical features\n",
|
||
" categorical_features = ['CH', 'FRAME_LEN', 'PREAM_LEN', 'BITRATE']\n",
|
||
" encoder = LabelEncoder()\n",
|
||
" for feature in categorical_features:\n",
|
||
" data[feature] = encoder.fit_transform(data[feature])\n",
|
||
" print(\"Categorical features one-hot encoded.\")\n",
|
||
"\n",
|
||
" # Extract the 'CIR' columns\n",
|
||
" cir_columns = [col for col in data.columns if 'CIR' in col]\n",
|
||
" cir_data = data[cir_columns]\n",
|
||
" print(\"'CIR' columns extracted.\")\n",
|
||
"\n",
|
||
" # Convert 'CIR' columns to float\n",
|
||
" cir_data = cir_data.astype(float)\n",
|
||
" print(\"'CIR' columns converted to float.\")\n",
|
||
"\n",
|
||
" # Denoise 'CIR' columns\n",
|
||
" denoised_cir_data = cir_data.apply(denoise_cir)\n",
|
||
" # denoised_cir_data = cir_data.apply(deconvolve_cir)\n",
|
||
" print(\"'CIR' columns denoised.\")\n",
|
||
"\n",
|
||
" # Replace original 'CIR' columns with denoised data\n",
|
||
" data[cir_columns] = denoised_cir_data\n",
|
||
" print(\"Original 'CIR' columns replaced with denoised data.\")\n",
|
||
"\n",
|
||
" # List of columns to check for unique values\n",
|
||
" columns_to_check = ['CH', 'PREAM_LEN', 'BITRATE']\n",
|
||
"\n",
|
||
" # Iterate over the columns\n",
|
||
" for column in columns_to_check:\n",
|
||
" # If the column has only one unique value, drop it\n",
|
||
" if data[column].nunique() == 1:\n",
|
||
" data = data.drop(column, axis=1)\n",
|
||
" print(f\"Column '{column}' dropped due to having only one unique value.\")\n",
|
||
"\n",
|
||
" # Print the shape of the cleaned data\n",
|
||
" print(f\"Cleaned data shape: {data.shape}\")\n",
|
||
"\n",
|
||
" # print(\"After Cleaning\")\n",
|
||
" # stat_analysis_and_plots(data)\n",
|
||
"\n",
|
||
" print(\"Data cleaning process completed.\")\n",
|
||
"\n",
|
||
" # Return the cleaned data\n",
|
||
" return data"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:17.340667Z",
|
||
"start_time": "2024-03-20T12:32:17.328977Z"
|
||
}
|
||
},
|
||
"id": "685463c2d6065b08",
|
||
"execution_count": 125
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Load and Clean the Data\n",
|
||
"\n",
|
||
"This code block loads the dataset from the specified directory and cleans the data using the `load_data` and `clean_data` functions. It then prints the first few rows of the cleaned data and the column headers."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "8323170f6733d41d"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Loading data from pickle file...\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x500 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 6000x3000 with 1 Axes>",
|
||
"image/png": 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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": "<Figure size 6000x3000 with 1 Axes>",
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cuXNj7dq10aRJk0T7mjVrYu7cuZWOrUrptZVeOwCwechEDlOezz//PIYNGxazZ88u816HDh1it912ixEjRsS+++6b9jHlMADAxmbMmBFTpkxJtB199NFVjqvr6y8V5ROzZs1KbGZo2rRptG3btlpzde7cOfGEjq+//jp22223ah0DANi81DSHKc+bb74Z++yzTyxcuLDMe127do099tgjjjvuuGo9vVQOAwBbjt/+9rdx4oknRnFxcURE3HrrrdGxY8cYMWJEuf2XL18eF1xwQWKT3/777x9Dhw4tt39tr8G0bds2mjRpEmvXro2I727SmD17dvTs2bPKuar7/VG613sAgPq1qfOX8nz77bdx2GGHlXujQ35+fuyyyy4xfPjwOPjggyMnJyft48pfAKDhy8/PT8TffvtttcaXV+xi+vTp0alTp0SbfTAAQF3JVP5SHntgAIBMaYg1XTJ1TlBT2fW9ABqWGTNmJOKsrKz4xS9+UW7hjNLWrFkTf/nLX+K0006LwsLCCvuV/oO4uh+s7du3Tzwhvri4OJYuXVqm35IlSxJPHsvNzY127dpVa67Sf3RX9495ACAzMpHDlGfp0qXlFv+KiFi4cGE8++yzMXr06BgxYkR89tlnaR1TDgMAbOyJJ55IxP3794++fftWOa62119K5xNLliwpt1/pjQzpbGCoai65CwD88NU0hynPwoULy934GPFdkffHH388Ro4cGaNGjSqziaAichgA2HLsuuuucfnll6ee5r5+/fq46KKL4thjj41x48bFSy+9FG+88UY89dRT8Yc//CEOPPDAePXVV1Pj99577/jzn/9c4fFrew0mIqJjx46VHvN7pXOY6s5Vep7aPE0eANh0NnX+Up41a9ZU+JTzpUuXxsSJE+Pcc8+NQw45JN555520jyt/AYCGr3v37ol4zpw51fqd/fHHH5dpW7RoUZk2+2AAgLqSqfylPPbAAACZ0hBrumTqnKCmGlXdBdJTXFwcK1euTLRdffXV8cknn0TEd4U0hgwZEvvtt1907tw5Vq9eHZ988kk89dRTsWDBgtSYt956Ky6++OK47bbbyp1n1apVibhZs2bVWmdWVlY0adIkUZW69LrLm6dp06apDRHpysvLq/SYAED9y1QOUxuffPJJHHfccXHdddfFoYceWmlfOQwA8L2SkpJ46qmnEm0VPd29tNK//0vnB1Upfb2mqKgo1q1bF40bN060l87Dqnudp7y1yV0A4IetNjlMbUyaNClGjBgRt99+e5VPIZXDAMCW5fjjj49evXrF1VdfHV988UVEfHdzRnk3aHyve/fuceqpp8Zxxx0X2dkVP5+xtntgyhtTXl6xZs2a2LBhQ63mkr8AwA/HpsxfamPmzJlx8sknx4UXXhijRo2qtK/8BQC2DN27d4+OHTsm9uM+++yz8Ytf/KLKsStXrozXXnutTHt5v/PtgwEA6kqm8pfasAcGAKithljTJVPnBDWlABh1ZsWKFYnqihER06ZNi4iI/Pz8uOOOO2LXXXdNvH/YYYfFGWecEVdccUVMmDAh1f7iiy/Gk08+GUcddVSZeUp/sDZp0qTaa23atGniw7S8D/HSH7Y1maf0GH+4AsDmJ1M5zMbatGkT+++/f+y5557Rt2/f6Ny5czRv3jxWrVoVc+fOjffffz8eeeSR+O9//5sas2bNmvjd734X7du3r/QCvBwGAPjepEmTEk/wys3NjeHDh6c1tvTv/9IbFqvStGnTMm0rV64sc5y6uM4jdwGAhqU2OczGOnfuHPvvv38MHjw4tt122+jYsWM0a9YsVqxYEbNnz47JkyfHww8/HLNmzUqNWbp0aYwZMyYefvjh6N27d4XHlsMAwJZnzz33jPHjx8ctt9wS999/f5liFBvbaqut4le/+lUMHz68yuIZdbUHprJjVtRW3bnkLwDww7Kp8peNtWjRIn784x/HPvvsE9tvv31069YtWrRoEWvWrImCgoL44IMP4vHHH4/3338/NWbDhg1x7bXXRvv27eMnP/lJhceWvwDAluOAAw6IBx98MBWPGzcujjjiiGjVqlWl48aNGxeFhYVl2tO5NmIfDABQG5nIXzZmDwwAkGkNsaZLps4JamrTPKKJLVJFH045OTkxbty4MoUzvte8efO44YYbYp999km033XXXWWKcURErF27NhHn5uZWe62lL7KvWbOmTJ9169ZlZB4AoH5lKof53g033BBvvPFGXHvttXHEEUdE3759o3Xr1tGoUaNo1apVbL/99nHCCSfEU089Fb///e8T+URRUVGcf/75ZfKhjclhAIDvPfHEE4l4//33jzZt2qQ1trbXX8rbKFleDpOp6zwAwA9HbXKYiIiWLVvGnXfeGa+++mpcddVVccghh0Tv3r2jZcuW0ahRo2jTpk0MGDAgTj311HjhhRfizDPPTNzYunz58vjd735X6fUdOQwAbHkeeuihOOCAA+Lee++ttHhGRMTcuXPj97//fQwbNizGjx9fad9M5RXlXZep7fUe+QsAbN42Vf7yvd/97nfxxhtvxM033xzHHnts7LjjjpGfnx+NGjWKFi1aRO/evePYY4+NBx98MG6//fbEDbAlJSVx6aWXxsKFCys8vvwFALYcJ598cuK7moKCgjjrrLMqvYHyySefjLvvvrvc99K5NmIfDABQG5nIXyLsgQEA6k9DrOki72FzpwAYdaaiCofHHnts7LTTTpWOzc7Ojquuuirxx+XXX38d77zzTpXzFBUVVXutpX8RlLf20h++m2oeAKB+ZSqH+d4RRxyR9pPDRo4cGTfeeGOZLwb+93//t8IxchgAIOK7p2C89NJLibYRI0akPb62119K5xMR5W+GzNR1HgDgh6G2OUxEROvWrWPo0KGJ6ykVycnJibPOOisuuuiiRPu0adPixRdfrHCcHAYAthxFRUUxduzYuOqqq1IFKvLz8+M3v/lNPProo/Huu+/G1KlT4//+3/8bd955Zxx44IGRlZUVEd89Wf3SSy+N66+/vsLjZyqvKK+tttd75C8AsHna1PnL9w499NBo3rx5Wms68MAD4+67746mTZum2lavXh133XVXhWPkLwCw5dh6663jtNNOS7RNmjQphg8fHg899FDMnj071q1bF8uWLYu33347zj777Ljwwgtjw4YNkZWVFS1btkyMzcvLKzOHfTAAQF3KRP4SYQ8MAFB/GmJNF3kPmzsFwKgzFf2Redxxx6U1vnv37rHXXnsl2t59990q5ynvqRlVKV1Jsby1l96YUJN5So+p6GcEANSfTOUwNXXQQQfFkUcemWh76qmnKuwvhwEAIiKef/75xJPE2rdvH/vuu2/a40v//i9vI2NlynuKRXk3gdTFdR65CwA0HLXNYWpq1KhRsfvuuyfaKrv+IocBgC3HVVddFS+88EIqHjhwYEyYMCHGjh0bAwcOjFatWkVubm507Ngxhg4dGrfffnvccccdiQ1+9957bzz22GPlHj9Te2DKa6vuXPIXAPhh2NT5S0396Ec/ilNPPTXRNmHChCguLi63v/wFALYsY8eOjf333z/RNmfOnLjqqqti2LBhMWDAgNh9993j5JNPjueffz7V56yzzooePXokxrVq1arM8e2DAQDq2qbOX2rKHhgAoC40xJoumTonqCkFwKgzTZs2jZycnERb8+bNo1+/fmkfY7fddkvEU6dOLdOn9Ifg6tWrq7HKiJKSkjIfxulceF+zZk2UlJRUa66Nb1Ip75gAQP3LVA5TG7/85S8T8WeffRaLFi0qt68cBgCIiHjiiScS8eGHHx6NGjVKe3zp3/+l84OqlL5e06hRo3KfbFH6mkx1r/OUtza5CwD8cNU2h6mN0tdfJk2aFOvXry+3rxwGALYMkydPjvHjx6fidu3axV/+8pfo0KFDpeOGDRsWV1xxRaLtT3/6U7k3itZ2D0x5Y8rLK8r7Pqy6c8lfAGDzl4n8pTZOOumkRE6ydOnSCvfYyF8AYMuSk5MTd9xxR5x88sllcoDy5ObmxnnnnRe/+c1vyvzOT6cAmH0wAEBtber8pTbsgQEAaqsh1nTJ1DlBTSkARp1q27ZtIt56660jOzv9f2a9evVKxN9++22ZPu3atUvE8+fPr8YKIxYtWpT4YzU7OzvatGlTpl+bNm0iKysrFRcVFZW7nsoUFBQk4tJrBwA2D5nIYWqjb9++iTyipKQkvvnmm3L7ymEAgFmzZsV7772XaBsxYkS1jlHb6y+l84nyrr1ElM3DSo+ryVxyFwD4YaqLHKY2Bg8enLimsnLlyli4cGG5feUwALBleOCBBxLxqFGjyuQBFTn66KOjZ8+eqXjp0qXx4osvlulX22swERELFiyo9JjfK7326s6V7jwAQP3JRP5SG61bty7zQL6vvvqqwv7yFwDYsuTk5MTFF18cTz/9dBx77LHRsWPHMn3y8vLiqKOOikcffTR+/etfR8R3ecvGevToUWacfTAAwKawKfOX2rAHBgCorYZY0yVT5wQ1lZlHZrPF6N27d+IPwRYtWlRrfOn+y5cvL9OndIGNefPmVWuO0v232mqrcp+80bRp09hqq61izpw5qba5c+dG+/btazzXNttsU621AgCZkYkcprY6d+6c+MN18eLF5faTwwAATz75ZOKJF/3794++fftW6xi1vf4yd+7cRFxRPtG9e/do1KhR6iL4mjVrYvHixWnfjFLe2uQuAPDDVBc5TG3k5eVF69atE5ssFy9eHF26dCnTVw4DAA1fSUlJTJo0KdG2//77pz0+Ozs7hgwZEvfdd1+q7b333osjjjgi0a+212C+/fbbxNNFc3Nzo3v37uX27dWrV+L7sLlz58ZOO+2U9lylr/eUXjsAUL8ylb/UVpcuXeLjjz9OxUuWLKmwr/wFALZMvXv3jquvvjoivrsR89tvv43Vq1dHx44do3PnztG4ceNU38WLFyfyiby8vOjdu3eZY9oHAwBsSpsif6kNe2AAgNpqiDVdMnVOUFPZ9b0AGpY+ffok4nXr1lVr/MabEiO++8AurfQH7pdfflmtOaZPn17p8TZW+kO89Ni6nAsAqD+ZyGFqq1GjZO3ejStFlyaHAYAtV0lJSTz55JOJtqOPPrrax6nt9ZfST2uvKJ8o76bU6sy1bt26mDVrVlpzAQCbr7rKYWor3esvchgAaPiWLVsWK1asSLR169atWsco3b+8J6aXzgFmzpxZre+pSn+n06NHjzI5zfd8fwQADVum8pfaKp2rFBUVVdhX/gIAdO7cOfr37x+77rpr9OjRI1E8IyLis88+S8Tbb7995OTklDmOfTAAQKbUVf5SW/bAAAC10RBrumTynKAmFACjTvXr1y8RL1q0qFrjv/3220Scn59fpk+fPn0iNzc3Fc+ZMycWLFiQ9hxTpkxJxDvssEOFfUu/98EHH6Q9z4IFCxKVJnNzc+u8EjcAUDcykcPUVuk1tWnTpsK+chgA2HK98847MXv27FScm5sbw4cPr/Zxtt9++0Q8derUSguQlpap6y9Tp05N3BTboUOHaNeuXdrjAYDNQ13lMLWxfv36xJNPI6LSp5nKYQCgYSuvCFdFhbUqUrr/hg0byvTp0KFDdOjQITHvtGnT0p4jU9dg1q9fHx9//HHacwEAmZep/KW2Su9/2VTXX+QvALBleP311xPxvvvuW24/+2AAgM1FuvlLbdgDAwDUVkOs6ZLJc4KaUACMOjVkyJDIzv7//6xmz55d5g/FypTexFi6WmNERIsWLWLXXXdNtL311ltpHb+kpKRM3/3337/C/kOGDCkzT0lJSVpz/fvf/07Ee+yxRzRv3jytsQBAZmUih6mN+fPnJ/4IjYjo0qVLhf3lMACw5XryyScT8dChQ2tUnLR3797Ro0ePVLxq1aq0L6KX7puVlVUmP9lY6fdK5yOVKX2dZ+jQoWmPBQA2H3WVw9TGf/7zn8SNHo0aNYr27dtX2F8OAwANW3m5SEFBQbWOUbp/RTdW7Lfffom4OnlF6b7V2QMzZcqUWLVqVVrzTJkyJVavXp2Ke/bsWeffhwEAtZPJ/KWm1q1bV6YoV3X2v8hfAICNbdiwIZ5//vlUnJOTE0cffXS5fe2DAQA2B9XJX2rDHhgAoLYaYk2XTJ4T1IQCYNSpdu3axaBBgxJtL730Ulpj169fHy+//HKibffddy+3b+k/AsePH5/WHJMmTUo8Qb59+/ax0047Vdh/0KBB0aZNm1Q8a9asmDx5clpzlV6TP1wBYPOVqRympkrnFV26dImePXtW2F8OAwBbplWrViU2BkREjBgxosbHq+n1l2effTZx88WOO+4YnTp1qrD/fvvtl3ii/DvvvBOzZs2qcp6SkpJ4/PHHE23Dhg1La40AwOajrnOYmnrssccS8Y9+9KNo1qxZhf3lMADQsDVu3Dg6dOiQaJs0aVK1jlG6/8Y3mW6s9DWYxx9/PK2NjDNnzox33303Fefm5pYpJraxLl26RL9+/VLxqlWr4rnnnqtynoiy14XkLwCw+clk/lJTzzzzTKIoV+PGjcvs19mY/AUAqMw///nPmDdvXired999K92fYh8MAFDfqpu/1JQ9MABAXWiINV0ydU5QEwqAUed+9rOfJeK//vWvsW7duirHPfLII7Fw4cJU3KJFi/jxj39cbt+f/OQnkZeXl4rffffdePvttys9fklJSdxxxx2JtqOPPjqysyv+v0F2dnaZm0zuuOOOKjdavv322/Hee++l4ubNm8ehhx5a6RgAoH5lIoepienTp8e9996baDvggAMqHSOHAYAt04svvpjYcNihQ4da5SXHHHNMZGVlpeJnnnkmpk+fXumYtWvXxt13351oO/bYYysdk5+fn/jCv6SkJG677bYq1zd+/PiYM2dOKu7atWvsueeeVY4DADYvdZ3D1MTkyZPjqaeeSrRVdf1FDgMADV/p39F///vfE09Lr8w777wTH3zwQaJt8ODB5fb98Y9/HJ07d07Fc+bMKXNjRnluu+22xHc/Bx10ULRs2bLSMaWv04wbNy7Wrl1b6Zjp06fHs88+m4qzs7M3ydPoAYDay1T+UhMLFy6Mm266KdG29957V3rzaYT8BQAo38yZM+OWW25Jxbm5ufHb3/620jH2wQAA9akm+UtN2AMDANSVhljTJVPnBDXhXxR1bvjw4bHddtul4m+++SauuOKKKC4urnDMhx9+GDfccEOi7fjjj69wY2K7du3ihBNOSLRddtllUVBQUOEcf/nLXxJPPm3ZsmWccsoplZ5LRMTo0aMTH+LvvPNOmQv4GysoKIhLL7000XbSSSdF27Ztq5wLAKg/mzqH+fTTT+O+++5LPMm0Kp9++mmceuqpsXLlylRb06ZNY/To0VWOlcMAwJan9FO0Dj/88MQTuapru+22S1z8LioqigsvvDAKCwvL7V9SUhJXX311fPPNN6m27t27xzHHHFPlXGPHjk1c/H7qqadiwoQJFfb/8ssv409/+lOi7YwzzojGjRtXORcAsHmpyxzm3//+dzz22GNp39ga8d0GgLPOOis2bNiQauvQoUOMHDmyyrFyGABo2I444ohE/Pnnn8fvf//7Sr87ioiYMWNGnH/++Ym2nj17xs4771xu/8aNG8fpp5+eaPvTn/4UX375ZYVzPP300/Gvf/0rFefk5MRZZ51V6boiIn7605/GVlttlYq/+eabuOaaayrcNFlYWBgXXHBBFBUVpdqGDx8effr0qXIuACDzMpG/LFiwIG699dZYtmxZ2uuaPXt2nHrqqYk9vllZWfIXACBl7ty5ae+vnT59epx88smxdOnSVNspp5xS5e97+2AAgLq0qfMXe2AAgPrWEGu6ZPKcoLoUAKPOZWdnxyWXXJJ4MsYTTzwRp5xySkydOjXRd8WKFfG3v/0tTj755MTT3Xv27Bm//vWvK53n1FNPjQ4dOqTi2bNnx89//vOYOHFi4ov9+fPnxxVXXFHmyWGnn3565OfnV3k+bdu2LbPR8sYbb4yrrroq8UFeXFwcL7/8cowcOTJRtbpjx47xq1/9qsp5AID6talzmOXLl8e1114bQ4YMicsvvzxef/31WLx4cZl+JSUl8dlnn8Uf//jHOO6442Lu3LmJ988777zo1KlTlecjhwGALcucOXPinXfeSbSVfgJGTZxzzjmJJ69//PHHccIJJ8TkyZMT/b7++usYO3Zs/POf/0y0n3/++ZGbm1vlPH369Imf/vSnibbf/e53ccsttyRuICkqKorHH388jj/++Fi+fHmqvW/fvnVyvgBAZtV1DlNQUBCXXHJJDB06NK655pqYNGlSrFixoky/DRs2xIcffhgXXnhh/OpXv0rkG9nZ2XHllVcmcqCKyGEAoGH78Y9/HHvssUei7ZFHHolf/OIX8fbbb5e54WLJkiVx7733xjHHHBMLFixIvHfuuedGTk5OhXMde+yxse2226biZcuWxQknnBBPPvlkYp6lS5fGzTffHBdccEFi/M9+9rPo1atXlefUuHHjMsU9Hn744Tj77LMTN7NGfHeTyPHHH5/4niwvLy/Gjh1b5TwAQP3IRP6ybt26uOOOO2LIkCFx/vnnx4svvljhTREzZsyIm266KY466qj473//m3jvpJNOiv79+1d5TvIXANgyvPLKKzFkyJC4+uqr45133ok1a9aU6fPZZ5/Fn/70pzjyyCMT+1133nnnGDNmTFrz2AcDANSVTZ2/2AMDAFTl/fffj7feeqvMf9OmTUv0W7t2bbn93nrrrUofThfRMGu6ZOqcoLqySip6BBLU0rhx4+LGG28s096hQ4fo1KlTrF69OmbOnJl4ylZERH5+fvz973+Pvn37VjnHu+++G6ecckqsXbs20d6qVavo1q1bLF++PObNm5eoWB0RMWzYsLjjjjsSBT4qU1xcHGPGjIlXX3010Z6TkxNbbbVVtGzZMmbPnp34gzUiomnTpnHvvffGLrvsktY8AED921Q5zOTJk+Okk04q096+ffto06ZNNG/ePFatWhUFBQUVPiX1V7/6VVx44YVpn4scBgC2HHfccUfceuutqbh///7x+OOP18mxn3nmmTj//PPLPEm9bdu20aVLl1i8eHHMnz+/zPsnnnhiXHbZZWnPs3r16vjFL35Rpvhqbm5udOvWLRo3bhyzZs1KFGCNiGjTpk089NBDad3kCgBsXuo6h3n88cfj4osvLtPeqVOnaN26deTl5UVhYWHMnTu3TE4REZGVlRWXXnppnHjiiWnPKYcBgIZt4cKFMXLkyJg9e3aZ9/Ly8qJbt27RtGnTWLp0acyaNavM9ZGI9L/fmT59ehx//PGJp79/P0+PHj1izZo1MWfOnDLfUQ0cODAeeOCBaNq0adrnddVVV8VDDz2UaMvKyoouXbpEmzZtYu7cubFkyZLE+9nZ2XHTTTfFIYcckvY8AEDmber8Zfbs2TFs2LAy7fn5+dGuXbto0aJFrFmzJhYuXFjug/EiIg455JC46aabIjs7/edYy18AoGH7xz/+EX/4wx9ScU5OTnTr1i1atWoVa9eujQULFpS5ZhIRMWDAgLj77rujTZs2ac9lHwwAUBc2df5iDwwAUJWhQ4cmimDVxIgRI+K6666rtE9DrOmSqXOC6lAAjE3qgQceiOuvv77M5sOK9OrVK+66667o2bNn2nO8/fbbcc4555T7x3B5hg8fHtdee200btw47TkivqtsefHFF8czzzyTVv/8/Py49dZbyzxNDQDY/G2KHKaiAmDpaNGiRVx55ZVxxBFHVHusHAYAtgwHHnhgzJw5MxVffvnl8Ytf/KLOjj9hwoS49NJLy31CWXl+9atfxQUXXFDti9pLly6Ns88+OyZNmpRW/65du8add96ZViF5AGDzU9c5TEWbH9PRoUOHuP7662Pvvfeu9lg5DAA0bPPmzYsLLrgg3nnnnWqNy83NjbFjx8bo0aPTvkby3//+N8aMGZP2Bs299torbrnllmjVqlW11lZcXBzXX3993HfffWn1b9asWVxzzTVx2GG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|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Data loaded successfully.\n",
|
||
"First few rows of the data:\n",
|
||
" NLOS RANGE FP_IDX MAX_NOISE FRAME_LEN PREAM_LEN CIR0 \\\n",
|
||
"0 1 6.18 749.0 3668.0 2 0 747.646447 \n",
|
||
"1 1 4.54 741.0 1031.0 2 0 123.353553 \n",
|
||
"2 1 4.39 744.0 796.0 0 0 439.646447 \n",
|
||
"3 1 1.27 748.0 1529.0 2 0 233.353553 \n",
|
||
"4 0 1.16 743.0 2022.0 0 0 82.353553 \n",
|
||
"\n",
|
||
" CIR1 CIR2 CIR3 ... CIR1010 CIR1011 \\\n",
|
||
"0 367.353553 744.646447 717.646447 ... 726.646447 367.353553 \n",
|
||
"1 470.646447 409.353553 332.353553 ... 491.353553 403.646447 \n",
|
||
"2 447.646447 130.353553 96.353553 ... 271.646447 73.353553 \n",
|
||
"3 239.353553 175.646447 532.646447 ... 225.353553 154.646447 \n",
|
||
"4 219.646447 110.646447 293.353553 ... 132.353553 131.353553 \n",
|
||
"\n",
|
||
" CIR1012 CIR1013 CIR1014 CIR1015 RX_Level \\\n",
|
||
"0 802.646447 818.646447 466.646447 767.646447 -33.465374 \n",
|
||
"1 334.353553 210.353553 102.353553 0.353553 -34.892422 \n",
|
||
"2 125.353553 169.353553 182.353553 0.000000 -38.436975 \n",
|
||
"3 171.646447 277.646447 317.646447 0.000000 -21.918230 \n",
|
||
"4 102.353553 126.353553 162.646447 0.353553 -21.603535 \n",
|
||
"\n",
|
||
" First_Path_Power_Level SNR Total_Distance \n",
|
||
"0 -39.074609 37.700000 234035.764530 \n",
|
||
"1 -53.179491 95.794118 127050.760471 \n",
|
||
"2 -49.812107 55.384615 115175.236492 \n",
|
||
"3 -25.863535 200.859375 101750.988607 \n",
|
||
"4 -23.232193 152.723684 119190.284232 \n",
|
||
"\n",
|
||
"[5 rows x 1026 columns]\n",
|
||
"Column headers:\n",
|
||
"Index(['NLOS', 'RANGE', 'FP_IDX', 'MAX_NOISE', 'FRAME_LEN', 'PREAM_LEN',\n",
|
||
" 'CIR0', 'CIR1', 'CIR2', 'CIR3',\n",
|
||
" ...\n",
|
||
" 'CIR1010', 'CIR1011', 'CIR1012', 'CIR1013', 'CIR1014', 'CIR1015',\n",
|
||
" 'RX_Level', 'First_Path_Power_Level', 'SNR', 'Total_Distance'],\n",
|
||
" dtype='object', length=1026)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"import pickle\n",
|
||
"\n",
|
||
"# File='data_original.pkl'\n",
|
||
"File = 'data.pkl'\n",
|
||
"\n",
|
||
"# Check if the file exists\n",
|
||
"if os.path.exists(File):\n",
|
||
" # If the file exists, load it\n",
|
||
" print(\"Loading data from pickle file...\")\n",
|
||
" with open(File, 'rb') as f:\n",
|
||
" data = pickle.load(f)\n",
|
||
" # plot_features(data, data['NLOS'], \"First_Path_Power_Level\", \"RX_Level\")\n",
|
||
" # plot_features(data, data['NLOS'], \"SNR\", \"RX_Level\")\n",
|
||
" # plot_features(data, data['NLOS'], \"SNR\", \"First_Path_Power_Level\")\n",
|
||
" snr_graph(data)\n",
|
||
" cir_graphs(data)\n",
|
||
" print(\"Data loaded successfully.\")\n",
|
||
"else:\n",
|
||
" # If the file doesn't exist, load and clean the data\n",
|
||
" print(\"Pickle file not found. Loading and cleaning data...\")\n",
|
||
" data = load_data(DATASET_DIR)\n",
|
||
" cir_graphs(data)\n",
|
||
" data = clean_data(data)\n",
|
||
" plot_features(data, data['NLOS'], \"First_Path_Power_Level\", \"RX_Level\")\n",
|
||
" snr_graph(data)\n",
|
||
" cir_graphs(data)\n",
|
||
" print(calculate_total_distance(data))\n",
|
||
" print(\"Data loaded and cleaned successfully.\")\n",
|
||
" print(\"Saving cleaned data to pickle file...\")\n",
|
||
" with open(File, 'wb') as f:\n",
|
||
" pickle.dump(data, f)\n",
|
||
" print(\"Cleaned data saved to pickle file successfully.\")\n",
|
||
"\n",
|
||
"print(\"First few rows of the data:\")\n",
|
||
"print(data.head())\n",
|
||
"\n",
|
||
"# Print Headers\n",
|
||
"print(\"Column headers:\")\n",
|
||
"print(data.columns)"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:22.761141Z",
|
||
"start_time": "2024-03-20T12:32:17.406422Z"
|
||
}
|
||
},
|
||
"id": "79c2c23691b26753",
|
||
"execution_count": 126
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Data Preprocessing"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "20d838f85d847ea0"
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Train and Save Model\n",
|
||
"\n",
|
||
"This code block defines a function `train_and_save_model` to train a classifier on the training data and save the trained model to a file. The function takes the following parameters:\n",
|
||
"\n",
|
||
"- `classifier`: The classifier to train and save.\n",
|
||
"- `X_train`: The training data.\n",
|
||
"- `y_train`: The training labels.\n",
|
||
"- `file_name`: The name of the file to save the trained model to."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "3e7a8932c36118eb"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"MODEL_DIR = './models'\n",
|
||
"\n",
|
||
"\n",
|
||
"def train_and_save_model(classifier, X_train, y_train, file_name):\n",
|
||
" if not os.path.exists(MODEL_DIR):\n",
|
||
" os.makedirs(MODEL_DIR)\n",
|
||
"\n",
|
||
" file_path = os.path.join(MODEL_DIR, file_name)\n",
|
||
"\n",
|
||
" # Check if the file exists\n",
|
||
" if not os.path.exists(file_path):\n",
|
||
" print(f\"Training the model and saving it to {file_path}\")\n",
|
||
" # Train the classifier\n",
|
||
" classifier.fit(X_train, y_train)\n",
|
||
"\n",
|
||
" # Save the trained model as a pickle string.\n",
|
||
" saved_model = pickle.dumps(classifier)\n",
|
||
"\n",
|
||
" # Save the pickled model to a file\n",
|
||
" with open(file_path, 'wb') as file:\n",
|
||
" file.write(saved_model)\n",
|
||
"\n",
|
||
" # Load the pickled model from the file\n",
|
||
" with open(file_path, 'rb') as file:\n",
|
||
" loaded_model = pickle.load(file)\n",
|
||
"\n",
|
||
" return loaded_model"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:22.766983Z",
|
||
"start_time": "2024-03-20T12:32:22.762778Z"
|
||
}
|
||
},
|
||
"id": "12e16974341e6266",
|
||
"execution_count": 127
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Split the Data\n",
|
||
"\n",
|
||
"This code block splits the data into training and testing sets using the `train_test_split` function from the `sklearn.model_selection` module. The training set contains 80% of the data, and the testing set contains 20% of the data.\n",
|
||
"\n",
|
||
"The target column 'NLOS' is separated from the rest of the dataset, and the input data is scaled using the `StandardScaler` from the `sklearn.preprocessing` module. The `StandardScaler` standardizes features by removing the mean and scaling to unit variance.\n",
|
||
"\n",
|
||
"The random seed is set to 42 for reproducibility."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "686f0615a70388cb"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# Set random seed for reproducibility\n",
|
||
"tf.random.set_seed(42)\n",
|
||
"\n",
|
||
"# Drop the target column 'NLOS' from the data and assign the remaining data to X\n",
|
||
"X = data.drop('NLOS', axis=1)\n",
|
||
"# Assign the target column 'NLOS' to y\n",
|
||
"y = data['NLOS']\n",
|
||
"\n",
|
||
"# Split the data into training and testing sets with a 80:20 ratio\n",
|
||
"X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
|
||
"\n",
|
||
"# Initialize a StandardScaler object\n",
|
||
"scaler = StandardScaler()\n",
|
||
"# Fit the scaler to the training data and transform it\n",
|
||
"X_train = scaler.fit_transform(X_train)\n",
|
||
"# Transform the testing data using the fitted scaler\n",
|
||
"X_test = scaler.transform(X_test)"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:32:23.828275Z",
|
||
"start_time": "2024-03-20T12:32:22.768155Z"
|
||
}
|
||
},
|
||
"id": "72c1e647b6c1992",
|
||
"execution_count": 128
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Convolution Neural Network\n",
|
||
"\n",
|
||
"This code block constructs and trains a Convolutional Neural Network (CNN) for a binary classification task using TensorFlow. CNNs are a type of deep learning model primarily used for image analysis, but they can also be applied to other types of data that have a grid-like topology. Here's a step-by-step breakdown of the code:\n",
|
||
"\n",
|
||
"1. **Model Creation**: A Sequential model is created using Keras. This model is composed of the following layers:\n",
|
||
"\n",
|
||
" - **Conv1D layers**: These are convolutional layers that will convolve the input data with a set of learnable filters, each producing one feature map in the output. The kernel size is set to 3, and the activation function used is ReLU (Rectified Linear Unit).\n",
|
||
"\n",
|
||
" - **MaxPooling1D layers**: These layers are used to down-sample the input along its spatial dimensions (height and width). The pool size is set to 2.\n",
|
||
"\n",
|
||
" - **Dense layers**: These are fully connected layers. The first Dense layer has 64 units and uses the ReLU activation function. The second Dense layer has a number of units equal to the number of classes and uses the softmax activation function to output a probability distribution over the classes.\n",
|
||
"\n",
|
||
"2. **Model Compilation**: The model is compiled with the Adam optimizer, categorical cross-entropy loss function, and accuracy as the evaluation metric.\n",
|
||
"\n",
|
||
"3. **Model Training**: The model is trained on the training data for 10 epochs with a batch size of 32. The validation data is set to the testing set.\n",
|
||
"\n",
|
||
"4. **Model Evaluation**: The model's performance is evaluated on the testing set and the accuracy is printed.\n",
|
||
"\n",
|
||
"The mathematical concept behind the Convolutional layer (Conv1D) is the convolution operation, which is a mathematical operation on two functions that produces a third function. In the context of a CNN, the two functions are the input data and the kernel or filter. The convolution operation involves sliding the kernel across the input data and computing the dot product at each position.\n",
|
||
"\n",
|
||
"The mathematical formula for the convolution operation is: $$ (f * g)(t) = \\int_{-\\infty}^{\\infty} f(\\tau)g(t - \\tau) d\\tau $$ Where: \n",
|
||
"- $f$ and $g$ are the input data and kernel respectively\n",
|
||
"- $t$ is the position of the kernel\n",
|
||
"- $\\tau$ is a dummy integration variable\n",
|
||
"\n",
|
||
"In the context of a CNN, the integral is replaced by a sum over the discrete spatial dimensions (height and width) of the input data and kernel."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "862a9b7ee430a667"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Epoch 1/30\n",
|
||
"1050/1050 [==============================] - 26s 23ms/step - loss: 0.7339 - accuracy: 0.6683 - val_loss: 0.4898 - val_accuracy: 0.8121\n",
|
||
"Epoch 2/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.5412 - accuracy: 0.7951 - val_loss: 0.4465 - val_accuracy: 0.8405\n",
|
||
"Epoch 3/30\n",
|
||
"1050/1050 [==============================] - 24s 22ms/step - loss: 0.4912 - accuracy: 0.8236 - val_loss: 0.4425 - val_accuracy: 0.8493\n",
|
||
"Epoch 4/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.4767 - accuracy: 0.8330 - val_loss: 0.4382 - val_accuracy: 0.8488\n",
|
||
"Epoch 5/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4644 - accuracy: 0.8382 - val_loss: 0.4399 - val_accuracy: 0.8474\n",
|
||
"Epoch 6/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4524 - accuracy: 0.8436 - val_loss: 0.4366 - val_accuracy: 0.8499\n",
|
||
"Epoch 7/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.4461 - accuracy: 0.8470 - val_loss: 0.4357 - val_accuracy: 0.8504\n",
|
||
"Epoch 8/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4411 - accuracy: 0.8497 - val_loss: 0.4321 - val_accuracy: 0.8505\n",
|
||
"Epoch 9/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4353 - accuracy: 0.8497 - val_loss: 0.4296 - val_accuracy: 0.8504\n",
|
||
"Epoch 10/30\n",
|
||
"1050/1050 [==============================] - 24s 22ms/step - loss: 0.4288 - accuracy: 0.8554 - val_loss: 0.4294 - val_accuracy: 0.8519\n",
|
||
"Epoch 11/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4299 - accuracy: 0.8548 - val_loss: 0.4276 - val_accuracy: 0.8527\n",
|
||
"Epoch 12/30\n",
|
||
"1050/1050 [==============================] - 25s 24ms/step - loss: 0.4219 - accuracy: 0.8566 - val_loss: 0.4262 - val_accuracy: 0.8551\n",
|
||
"Epoch 13/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4195 - accuracy: 0.8561 - val_loss: 0.4262 - val_accuracy: 0.8532\n",
|
||
"Epoch 14/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4147 - accuracy: 0.8572 - val_loss: 0.4226 - val_accuracy: 0.8531\n",
|
||
"Epoch 15/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4117 - accuracy: 0.8578 - val_loss: 0.4219 - val_accuracy: 0.8546\n",
|
||
"Epoch 16/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4110 - accuracy: 0.8600 - val_loss: 0.4197 - val_accuracy: 0.8555\n",
|
||
"Epoch 17/30\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4040 - accuracy: 0.8611 - val_loss: 0.4179 - val_accuracy: 0.8563\n",
|
||
"Epoch 18/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.4010 - accuracy: 0.8623 - val_loss: 0.4164 - val_accuracy: 0.8550\n",
|
||
"Epoch 19/30\n",
|
||
"1050/1050 [==============================] - 24s 22ms/step - loss: 0.4013 - accuracy: 0.8594 - val_loss: 0.4163 - val_accuracy: 0.8542\n",
|
||
"Epoch 20/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.4013 - accuracy: 0.8600 - val_loss: 0.4172 - val_accuracy: 0.8543\n",
|
||
"Epoch 21/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3975 - accuracy: 0.8633 - val_loss: 0.4108 - val_accuracy: 0.8571\n",
|
||
"Epoch 22/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3918 - accuracy: 0.8645 - val_loss: 0.4114 - val_accuracy: 0.8573\n",
|
||
"Epoch 23/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3954 - accuracy: 0.8633 - val_loss: 0.4073 - val_accuracy: 0.8567\n",
|
||
"Epoch 24/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3944 - accuracy: 0.8642 - val_loss: 0.4096 - val_accuracy: 0.8587\n",
|
||
"Epoch 25/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3890 - accuracy: 0.8652 - val_loss: 0.4049 - val_accuracy: 0.8615\n",
|
||
"Epoch 26/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3873 - accuracy: 0.8657 - val_loss: 0.4034 - val_accuracy: 0.8596\n",
|
||
"Epoch 27/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3852 - accuracy: 0.8683 - val_loss: 0.4070 - val_accuracy: 0.8589\n",
|
||
"Epoch 28/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3839 - accuracy: 0.8681 - val_loss: 0.4070 - val_accuracy: 0.8605\n",
|
||
"Epoch 29/30\n",
|
||
"1050/1050 [==============================] - 23s 22ms/step - loss: 0.3826 - accuracy: 0.8685 - val_loss: 0.4033 - val_accuracy: 0.8605\n",
|
||
"Epoch 30/30\n",
|
||
"1050/1050 [==============================] - 25s 24ms/step - loss: 0.3812 - accuracy: 0.8691 - val_loss: 0.4035 - val_accuracy: 0.8631\n",
|
||
"263/263 [==============================] - 1s 3ms/step\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Initialize a Sequential model\n",
|
||
"model = Sequential()\n",
|
||
"\n",
|
||
"# Add a Conv1D layer\n",
|
||
"model.add(Conv1D(filters=64, kernel_size=3, activation='relu', input_shape=(X_train.shape[1], 1),\n",
|
||
" kernel_regularizer=regularizers.l2(0.001)))\n",
|
||
"model.add(BatchNormalization())\n",
|
||
"model.add(Dropout(0.5))\n",
|
||
"\n",
|
||
"# Add another Conv1D layer\n",
|
||
"model.add(Conv1D(filters=32, kernel_size=3, activation='relu', kernel_regularizer=regularizers.l2(0.001)))\n",
|
||
"model.add(BatchNormalization())\n",
|
||
"model.add(Dropout(0.5))\n",
|
||
"\n",
|
||
"# Add a Flatten layer\n",
|
||
"model.add(Flatten())\n",
|
||
"\n",
|
||
"# Add a Dense layer\n",
|
||
"model.add(Dense(16, activation='relu', kernel_regularizer=regularizers.l2(0.001)))\n",
|
||
"model.add(BatchNormalization())\n",
|
||
"model.add(Dropout(0.5))\n",
|
||
"\n",
|
||
"# Add the output Dense layer\n",
|
||
"model.add(Dense(1, activation='sigmoid'))\n",
|
||
"\n",
|
||
"# Define early stopping\n",
|
||
"early_stopping = EarlyStopping(monitor='val_loss', patience=10)\n",
|
||
"\n",
|
||
"# Compile the model\n",
|
||
"model.compile(loss='binary_crossentropy', optimizer=Adam(learning_rate=0.0001), metrics=['accuracy'])\n",
|
||
"\n",
|
||
"# Train the model\n",
|
||
"history = model.fit(X_train, y_train, epochs=30, batch_size=32, validation_data=(X_test, y_test),\n",
|
||
" callbacks=[early_stopping])\n",
|
||
"\n",
|
||
"# Evaluate the model\n",
|
||
"scores = model.evaluate(X_test, y_test, verbose=0)\n",
|
||
"\n",
|
||
"# Make predictions\n",
|
||
"y_pred = model.predict(X_test)\n",
|
||
"y_pred_classes = (y_pred > 0.5).astype(\"int32\")\n",
|
||
"\n",
|
||
"# Generate a classification report\n",
|
||
"report = classification_report(y_test, y_pred_classes)"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:44:18.952408Z",
|
||
"start_time": "2024-03-20T12:32:23.830299Z"
|
||
}
|
||
},
|
||
"id": "1c1dd203ad7db076",
|
||
"execution_count": 129
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Plot the training and validation accuracy over epochs\n",
|
||
"\n",
|
||
"This code block plots the training and validation accuracy over epochs. The training accuracy is plotted in red, and the validation accuracy is plotted in blue. The x-axis represents the number of epochs, and the y-axis represents the accuracy. The plot shows how the accuracy changes over the course of training and validation."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "b5f3cff03a03da6a"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 640x480 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1200x600 with 1 Axes>",
|
||
"image/png": 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rLd1+++0aP368ZsyYoaSkJFmtVj311FMB6Zk+nCeffFKPPfaYJk+erBtvvFFxcXGyWCy67777Wm1JuZaui4ZISkrSm2++qRUrVmj58uVavny53njjDZ1zzjm6//77JUnHH3+8PvzwQ3388cdauXKlFi1apOeff16zZ8/2he369O3bV999952cTudhlwj88ccfFRYW5vfhy4QJE/Tkk08qPz9f0dHR+uSTTzRx4kTfihC19Txp0qTDruf+8wkiW6M3Xjr8f9Oj/bduyjUBQHtEkAcA+KxZs0aFhYWaN2+ejj/+eN/2Q4eSB1NSUpIcDod27txZ57X6tv3c5s2btWPHDt1///0655xzfNuPNqv4kXTt2lWrV6+uMzx6+/btjTrP2Wefrc8++0zLly/XO++8o+joaL+Z3t9//311795d8+bN8+vJ/PkEfQ3RpUsXSdKOHTvUvXt33/b8/Pw6oxTef/99jRw5Uvfdd5/f9uLiYr+J5n7eu3okXbt21apVq1RaWurXK19760bXrl0bfjHN1LVrV/3444/yeDx+vfK1ban9WUne2wzGjRuncePGyePx6K677tLChQt1zTXX+EaExMfHa/LkyZo8ebLKysp0ySWX6B//+McRg/ypp56q9evX67333qt3+bY9e/Zo7dq1GjVqlF/QnjBhgubNm6cPPvhAycnJKi0t9RuunpiYqKioKHk8Ho0ePbrpP6QQ0h6vCQCagnvkAQA+tUHm0J5Op9OpV155JVhN8mO1WjV69Gh9/PHHys7O9m3fuXOnPvvss6MeX9/1maapF154ocltOvnkk+VyufTqq6/6trndbr300kuNOs/48eMVERGhV155RcuXL9cvf/lLv/W3a3sqD237hg0b9PXXXze6zaNHj1ZYWJheeuklv/MdupTaoe/7857v9957z+/nL0kRERGSGnYLxcknnyy3262XX37Zb/u///1vGYbhN1y9pZ188snKycnR0qVLfdtcLpdefPFFRUZG+j7QKigo8DvOYrH4en6dTme9+0RFRalHjx6+1w/n/PPPV1JSkh588ME6oyuqqqp0xx13yDRNXXvttX6v9e3bV+np6Vq6dKmWLl2qlJQUvw/grFarzjjjDL3//vvavHlznfdti0PQ2+M1AUBT0CMPAPAZNmyY4uLidPvtt2vatGkyDENvvfVWqw5hPprrrrtOK1as0IUXXqgLL7xQHo9HL730ko455hh9//33Rzy2T58+6tGjh+6//35lZ2crOjpa77//frPutR43bpyOO+44PfTQQ9q7d6/69eunDz74oMHryNeKiorSaaedpnfeeUeS/IbVS95e2w8++EDXXnutTj31VO3Zs0cLFixQv379VF5e3qj3SkxM1OWXX66nnnpKV111lU455RR99913Wr58eZ3l3E499VQ9/vjjuuOOOzRs2DBt3rxZb7/9tl9PviT16NFDsbGxWrBggaKiohQZGanBgwfX2U/y/sxGjhypRx55RHv37lVGRoZWrlypjz/+WJdeemmdtdSba9WqVaqqqqqzffz48Tr//PO1cOFC3X777dq0aZO6du2q999/X+vWrdMf/vAH34iBP/3pTyoqKtKJJ56o1NRU7du3Ty+99JL69+/vu59+4sSJOuGEEzRgwADFx8frm2++0fvvv3/UiQ8TEhI0d+5cXXnllfrNb36jKVOmqG/fvsrNzdWSJUu0c+dO/fGPf6x3Ob8JEyZo7ty5cjgcOu+88+rc63/LLbfoiy++0NSpUzVlyhT169dPRUVF2rRpk1atWqU1a9Y09ccaNO3xmgCgsQjyAACfhIQEPfnkk7r//vv16KOPKjY2VpMmTdKoUaM0Y8aMYDdPkjRw4EA9/fTTeuCBB/TYY48pLS1NN9xwg7Zt23bUWfXDwsL05JNP6p577tFTTz0lh8Oh008/XRdffHG9Q5obwmKx6IknntB9992n//znPzIMQ+PGjdPtt9/uN3y/ISZNmqR33nlHKSkpvgnLap177rm+NdxXrFihfv366cEHH9SyZcuaFFxuuukm2e12LViwQF988YUGDx6sZ599VldddZXffv/3f/+niooKvf3221q6dKmOPfZYPfXUU3rooYf89gsLC9Pf/vY3Pfzww7rrrrvkcrk0Z86ceoN87c9s7ty5Wrp0qd544w117dpVs2bN0uWXX97oazmazz77rN4RG127dlV6erpefPFF/f3vf9eSJUtUWlqq3r17a86cOX6rOkyaNEmvvfaaXnnlFRUXFyslJUW/+tWvdP311/vC87Rp0/TJJ59o5cqVcjqd6tKli2666aYG/e6MGDFC//nPf/TUU09p2bJlysnJUXR0tIYNG6Z7773Xt/rDz02YMEGPPvqoKioq9Ktf/arO68nJyXr99df1+OOP68MPP9Srr76q+Ph49evXT7feemtDf4QhpT1eEwA0lmGGUjcLAABNdM011+inn37yW44LAACgPeIeeQBAm1NZWen3fMeOHVq+fLlOOOGEILUIAACg9TC0HgDQ5owfP16/+c1v1L17d+3du1cLFixQWFiYrrjiimA3DQAAoMUR5AEAbc5JJ52kd999Vzk5ObLb7Ro6dKhuvvlmvzW2AQAA2ivukQcAAAAAoA3hHnkAAAAAANqQkBha//LLL2v+/PnKyclRZmam7rzzTg0ePLjefadNm1bvMjunnHKK/vWvf0mSbr/9di1ZssTv9bFjx2r+/PmBbzwAAAAAAK0o6EF+6dKlmjNnjmbPnq0hQ4bo+eef14wZM7Rs2TIlJSXV2f8f//iHqqurfc8LCwv161//WmeeeabffieddJLmzJnje26321vuIgAAAAAAaCVBH1r/3HPPaerUqZo8ebL69eun2bNnKzw8XIsXL653//j4eKWkpPi+Vq5cqfDw8DpB3m63++0XFxfXGpcDAAAAAECLCmqPvNPp1KZNm3TVVVf5tlksFo0ePVrr169v0DkWL16siRMnKjIy0m/7mjVrNGrUKMXGxurEE0/UTTfdpISEhEa1Lz+/RKE8FaBhSImJMSHfToQ26giBQB0hEKgjNBc1hECgjhAITamj2mMaIqhBvqCgQG63u84Q+qSkJG3btu2ox2/cuFGbN2/Wvffe67f9pJNO0umnn65u3bpp9+7devjhhzVz5kwtXLhQVqu1we1r6A8x2NpKOxHaqCMEAnWEQKCO0FzUEAKBOkIgtFQdBf0e+eZYtGiR0tPT60yMN3HiRN/3GRkZysjI0Pjx43299A2Vlxfan8IZhpSUFBPy7URoo44QCNQRAoE6QnNRQwgE6giB0JQ6qj2mIYIa5BMSEmS1WpWXl+e3PS8vT8nJyUc8try8XO+++65uuOGGo75P9+7dlZCQoJ07dzYqyJum2sQvb1tpJ0IbdYRAoI4QCNQRmosaQiBQRwiElqqjoE52Z7fbNWDAAK1atcq3zePxaNWqVRo2bNgRj122bJmcTqcmTZp01PfJyspSYWGhUlJSmt1mAAAAAACCKehD66dPn67bbrtNAwcO1ODBg/X888+roqJC5557riRp1qxZSk1N1S233OJ33KJFizR+/Pg6E9iVlZVp3rx5OuOMM5ScnKzdu3frwQcfVM+ePXXSSSe12nUBAAAAaJvcbreqq530yKPJDEOqrKz0qyOLxSKLxSrDMJp9/qAH+QkTJig/P19z585VTk6O+vfvr2eeecY3tH7//v2yWPwHDmzbtk1r167Vs88+W+d8VqtVmzdv1ptvvqmSkhJ16tRJY8aM0Y033sha8gAAAACOqKqqQps375HL5Q52U9DG5edb5PF4/LbZ7eGKjU2UzRbWrHMbpsnnTIeTmxvaE1wYhpScHBPy7URoo44QCNQRAoE6QnNRQ2guj8ejAwf2KDw8QpGRsQHpOUXHZbUacru9f4xM05Tb7VJpaaE8Ho86depWp75q/4Y1RNB75AEAAAAgFLjdLkmmYmPjZLEwmhfNY7NZ5HId2iPvkNVqVX5+tlyuaoWFNb3GgjrZHQAAAACEHnri0TIMIzARnCAPAAAAAEAbQpAHAAAAAKANIcgDAAAAAPycd97Zeu21Vxq8/7p1X2ns2BEqKSlpwVahFpPdAQAAAEAbNXbsiCO+Pn36TM2YcVWjz/v00y8oIiKiwfsPGjREb721TNHR0Y1+r8ZYt+4r3XDD/+m99/6rmJiGzfDeHhHkAQAAAKCNeuutZb7vP/74Q82f/6ReeWWxb1tERKTve+8SaG7ZbEePgQkJCY1qR1hYmJKSkht1DJqOIA8AAAAAh2Gapir9lhBreeE2S4PXsD80PEdHR8swDN+22t7rBx98TE8//YS2bftJDz88T6mpnfWPfzysTZu+VWVlhXr27K2rrrpWxx8/0neu8847W1OnXqipUy+S5O35v+22P+nzz1dozZpVSknppOuuu0ljx57i9161PeVLl76tuXMf0uzZczR37kM6cCBbgwYN1R/+8BclJ3vb53K5NG/eI1q27F1ZLFadddavlZ+fp7KyUs2Z81CTfnbFxcV67LG/a+XKz1Rd7dTQocN10023qnv3HpKkrKz9evjhB7Rx49dyuarVuXMXXXvtDRo1aqyKi4v1yCMP6MsvV6u8vEKdOnXStGnTNXHipCa1pSUR5AEAAACgHqZp6ooFG7RxX3Grvu+QLrF6+oIhDQ7zR/Pkk/N03XU3qkuXboqJiVF2drZOPHGMrrzyGoWF2bVs2bu67bab9cori9W5c+fDnue5557W1Vdfr2uvvVGLFi3U7Nl3avHitxUbG1fv/pWVlXr11Rd1551/lWFYdPfdd+rxxx/VX/5yjyTp5Zef1wcfLNMdd/xFvXr11uuvv6rPPvtUxx135NsFjuS+++7Snj27df/9DysyMkpPPPEP/f73N+qll16XzWbTww/fr+rqaj3++NMKDw/Xjh3bfaMWnnnmCe3YsU1///tcxcXFa8+e3aqqqmpyW1oSQR4AAAAADqM9rCh/xRVX6fjjT/Q9j42N0zHHpPuez5x5tZYv/69WrvyfJk8+/7Dn+dWvztLpp58pSbrqqmu1aNECfffdJp144uh693e5XPr97/+grl27SZLOPXeq/v3vZ3yvL178mi655DKdcsovJEm/+90srVq1ssnXuXv3Lq1YsVxPPDFfgwYNkST95S9369xzJ2r58k81btx4ZWdn6ZRTxqlv336S5GubJGVnZ+mYYzKUmXmsJCktrUuT29LSCPJtWIXTrQ27C9U1whrspgAAAADtjmEYevqCISE9tL4haoNprfLycj377L+0atUK5eXlyu12q6qqStnZWUc8T9++x/i+j4iIUFRUlAoK8g+7f3h4uF9QTkpK9u1fWlqq/Pw8HXvsAN/rVqtVGRn9ZZpN+3nv3LldVqtVxx470LctLi5ePXr01M6d2yVJ5513gf7+9zn68svVGjFipE45ZZz69fNe1znnnKc//WmWNm/+USecMFInnXSq7wOBUEOQb8P+9tEWvfvdAT11/mAd1y0+2M0BAAAA2h3DMBQR1rY7zsLD/Weff/zxR/Xll1/o2mtvUrdu3eVwOPSnP92m6mrXEc/z80nyDMOQaZoB2781nH32OTrhhBO1atUKrVnzhV588Tldd91NOu+8CzRq1BgtWvSOVq9eqS+//EI33niNzj13iq677qagtrk+rCPfhjnd3l+C77NLg9wSAAAAAG3FN99s0IQJZ+uUU36hvn37KTExSVlZ+1q1DdHR0UpMTNL333/n2+Z2u7V58w9NPmfPnr3ldrv13Xff+rYVFRVq166d6tWrt29bampnnXPOebrvvgd1wQWX6O233/S9lpCQoF/96iz9+c9364YbbtZ//rOkye1pSfTIt2Fd48IlSfuKKoPcEgAAAABtRbduPfS//32iMWNOkmTomWeekMfT+j3lkydP1UsvPadu3bqpZ89eWrRooUpKitWQmQm2bftJkZGRh2wxdMwx6TrppFN0//336ve//4MiIyP15JPzlJLSSSeddKok6bHHHtKJJ45W9+49VFJSonXrvlLPnt6Q/8wzTyojI1O9e/eV0+nU55+vUM+evQJ+3YFAkG/D0uIckqT9BHkAAAAADXT99b/TnDl/1f/93+WKi4vXxRdfqrKyslZvx8UXX6r8/Dzdc89fZLFYNWnSb3TCCaNksRx94Pi11870e261WvW//32hO+74ix577O+67babVF1drSFDjtODDz7mG+bv8bj18MP3KyfngCIjozRy5CjdcMPNkry3Ajz11OPav3+fHI5wDRkyVLNn3xf4Cw8Awwz2TQohLDe3RKH80/liZ76uW/St+iRFauFlTV+iAR2bYUjJyTEhX+8IbdQRAoE6QnNRQ2iu6mqn8vL2q1OnLrJYwoLdnA7H4/Ho4ovP07hxp2vmzKuD3Zxms9kscv1sosTaGktKSlNYmN3vtdq/YQ06d8BaiVaXFusdWr+/uFKmaQZ0ZksAAAAAaElZWfu1Zs1qDR16nKqrq7V48ULt37/Pt8QdDo8g34bVBvmKao8KK6qVEGk/yhEAAAAAEBoMw9B7772txx9/VKYp9enTV48++k+/ielQP4J8G2a3WZQa61B2cZX2FVcR5AEAAAC0GampnfXEE88GuxltEsvPtXHdE7wzNTJzPQAAAAB0DAT5Nq5bQoQkZq4HAAAAgI6CIN/GdU+s6ZEvJsgDAAAAQEdAkG/janvkGVoPAAAAAB0DQb6N4x55AAAAAOhYCPJtXO3Q+v3FlfKYZpBbAwAAAABoaQT5Nq5zXLgshuR0m8ovcwa7OQAAAADaoOuuu1KPPfaQ7/l5552t11575YjHjB07QsuXf9rs9w7UeToSgnwbF2a1KDXGIUnay/B6AAAAoEOZNet3uvnm6+t9bcOG9Ro7doR++mlLo8/79NMvaNKkc5vbPD/z5z+lyy67qM72t95aphNPHB3Q9/q5pUvf1plnntqi79GaCPLtQFpsuCRpf3FVkFsCAAAAoDWdddav9dVXX+jAgew6r7377n+UmXms+vU7ptHnTUhIUHh4eCCaeFRJScmy2+2t8l7thS3YDUDzdY0L17o9RUx4BwAAAASaaUquitZ9T1uEZBgN2nX06LGKj0/Q0qVv67LLrvBtLy8v13//+7GuvfYGFRUV6uGHH9CGDetVUlKsrl27adq06Tr99DMPe97zzjtbU6deqKlTvT3ou3fv0t/+dre+/36TunTpqhtvvKXOMf/851wtX/6pcnKylZiYrF/+8kxNnz5TNptNS5e+reeee1qSdyi9JP3hD3/RhAlna+zYEbrvvr/r5JNPlSRt3fqTHnvs7/r2228UHh6uU04Zp+uv/50iI73zg917710qLS3RoEFDtXDhS6qudum0036pG2+8RTZb0yJuVlaWHn30Aa1d+6UMw6KRI0fpd7/7vRITkyRJW7Zs1ty5D+mHH76XYRjq1q27Zs36gzIzj1VW1n49/PAD2rjxa7lc1ercuYuuvfYGnXTSyU1qS0MQ5NuBtDjvJ2WsJQ8AAAAEkGkq/o3fKCzrq1Z92+q041X4mzcaFOZtNpvOPHOC3nvvHV166QwZNcf8978fyeNxa/z4M1VRUa6MjP665JJLFRkZpVWrVuiee/6irl276dhjBx71PTwej/74x98rISFJTz31b5WVlWru3Ifq7BcZGak//vEvSk5O0datP+mBB+5VZGSkLr74Up122unatm2rvvjicz366D8lSdHR0XXOUVFRoZtvvk4DBw7SM888r4KCAv3tb/fokUce0B//eJdvv3XrvlJSUrLmzn1Ke/bs1l/+coeOOSZdkyb95qjXU9/13XHHzYqIiNQ//vEvud1uPfzw/frzn+/QvHn/kiT99a9/Unp6hm699Q5ZLBZt2bJZVqs3Tj/88P2qrq7W448/rfDwcO3YsV0REZGNbkdjEOTbgS61QZ4eeQAAACCwGtgzHkwTJ/5ar7zyotavX6vjjvP2di9d+rZOPXWcoqOjFR0drYsumubb/7zzLtCaNav1yScfNSjIf/XVGu3cuUMPPzxPyckpkqQrr7xWt956g99+h44ISEvrol27durjjz/QxRdfKocjXBEREbJabUpKSj7se3344TI5nU796U9/VUREhCTp5pt/r9tuu1lXX329r4c8JiZWv/vdLFmtVvXs2UujRo3V2rVrmhTk165do23btuq1195SampnSdKf/jRb06ZN1fffb1L//gOUnZ2tiy76rXr27CVJ6t69h+/47OwsnXLKOPXt20+S1LVrt0a3obEI8u1Al1jvZHf76ZEHAAAAAscwvD3jITy0XpJ69uylQYMG6913/6PjjhuhPXt2a8OG9Zox40lJktvt1osvPqdPPvlQOTk5crmq5XQ65XA07B74HTu2q1Onzr4QL0kDBw6us9/HH3+gRYsWaO/evaqoKJfb7VZkZFSDr0OSdu7crn79jvGFeEkaNGioPB6Pdu3a6QvyvXv3kdVq9e2TlJSsbdt+atR71dqxY4c6dUr1hfja80dHx2jHju3q33+Azj//Iv3tb3dr2bKlGjHiBI0bN94X2M877wL9/e9z9OWXqzVixEidcsq4Js1L0BhMdtcO1PbIZxVXye1hLXkAAAAgYAxDCots3a8mjAKYOPHX+t//PlF5eZneffc/6tq1m4YNGy5JeuWVF/X666/q4osv1dy5T+q5517RyJGj5HJVB+zH9O23G/XXv96pE08cowceeETPPvuyfvvbywP6Hof6+b3whmHI4/G0yHtJ0owZV+nFF1/T6NFjtG7dl7rkkin63//+K0k6++xz9Nprb+mMMyZo69afdMUV07Ro0YIWa4tEkG8XUqIdslkMuTymckqZuR4AAADoaMaNO12GYdEHHyzT++8v1cSJk3z3y3/zzQaNHXuKzjhjgo45Jl1dunTVrl27GnzuXr1668CBLOXm5vq2bdr0jd8+33yzUampnXXppTOUmXmsunfvoays/X77hIWFyeNxH/G9evbsrZ9+2qKKioOjIL755mtZLBb16NGzwW1ujF69eunAgWxlZ2f5tm3fvk2lpSXq3buPb1uPHj11/vkX65FHHtfJJ/9CS5f+x/daampnnXPOebrvvgd1wQWX6O2332yRttYiyLcDVouhzjXD65nwDgAAAOh4IiMjddppp+uppx5XXl6uJkw42/da9+7d9eWXX+ibbzZox47tevDB+1RQkNfgc48YcYK6d++pe+/9i7Zs2awNG9brX//6p98+3bt3V3Z2lj766H3t3btHr7++QMuXf+q3T+fOXbR//z5t2fKjCgsL5XQ667zXL3/5K9ntdt1771+0bdtPWrfuKz3yyIM644wJvmH1TeV2e7Rly49+Xzt2bNeIESPVp09f/fWvd+rHH3/Qd999q3vu+YuGDj1OmZnHqqqqUg8/fL/WrftKWVn7tXHj1/rhh+/Us2dvSdJjjz2kL75YpX379urHH3/QunVf+V5rKdwj306kxYZrT2Gl9hdVSS0/twIAAACAEHPWWb/WO++8pVGjxvjdz37ppTO0b99e3Xzz9QoPD9ekSb/RSSedqrKy0gad12Kx6L77HtTf/na3rrzyUnXunKabbvq9brnlet8+Y8eeovPPv0iPPPKAnM5qjR49RpddNkPPPvsv3z6nnjpOy5d/ouuv/z+Vlpb4lp87VHh4uB5+eJ4ee+zvuuKKS/2Wn2uuiopyTZ9+sd+2rl27aeHCNzVnzsN69NEHdN11M/2Wn/Nev1VFRUW6556/qKAgX3Fx8TrllF9oxoyrJEkej3eW+5ycA4qMjNLIkaN0ww03N7u9R2KYpslN1YeRm1uiUP7pGIaUnByj3NwS3f3+Zr31TZauHNVTM0e3zJATtE+H1lEo1ztCG3WEQKCO0FzUEJqrutqpvLz96tSpiyyWsGA3B22czWaRy+V/335tjSUlpSkszO73Wu3fsIZgaH070SWWteQBAAAAoCMgyLcTrCUPAAAAAB0DQb6dSGMteQAAAADoEAjy7UTXmh757JIqudwtt34iAAAAACC4CPLtRGKUXXarIY8pZbOWPAAAAACEnEDNNU+QbycshqG0WO6TBwAAAJrKYvHGI5erOsgtQXvldHo7Xa3W5q0Ezzry7UhaXLh2FlR415IHAAAA0CgWi1VhYeEqLi5UbKxFhkG/J5rO4zHkdnt74E3TlNNZpdLSAkVERPs+NGoqgnw7Unuf/F4mvAMAAAAazTAMxccnqrDwgPLzs4PdHLRxFotFHo///GUREdGKjU1s9rkJ8u1I7dD6/QytBwAAAJrEZgtTenq6srMLFKDbmdEBGYaUkBClgoIyXx1ZrbZm98TXIsi3I6wlDwAAADSfxWJRWJidII8mMwwpPDxcYWHVLVJH3PTRjnRhLXkAAAAAaPdCIsi//PLLGjdunAYNGqQpU6Zo48aNh9132rRpysjIqPN15ZVX+vYxTVOPPfaYxo4dq8GDB+uyyy7Tjh07WuFKgqu2Rz6n1Cmni7XkAQAAAKA9CnqQX7p0qebMmaNrr71WS5YsUWZmpmbMmKG8vLx69//HP/6hFStW+L7eeecdWa1WnXnmmb59nn76ab344ou666679NprrykiIkIzZsxQVVX7ns09PiJM4TaLTElZJe37WgEAAACgowp6kH/uuec0depUTZ48Wf369dPs2bMVHh6uxYsX17t/fHy8UlJSfF8rV65UeHi4L8ibpqkXXnhBV199tcaPH6/MzEw98MADOnDggD766KPWvLRWZxjGIffJVwS5NQAAAACAlhDUye6cTqc2bdqkq666yrfNYrFo9OjRWr9+fYPOsXjxYk2cOFGRkZGSpD179ignJ0ejR4/27RMTE6MhQ4Zo/fr1mjhxYoPbZxgN3jUoatt3aDu7xIVrW1659hdXhXz7ERrqqyOgsagjBAJ1hOaihhAI1BECoSl11Jh9gxrkCwoK5Ha7lZSU5Lc9KSlJ27ZtO+rxGzdu1ObNm3Xvvff6tuXk5PjO8fNz5ubmNqp9SUkxjdo/WA5tZ9/UGK3Ylq+Cao+Sk9tG+xEa2kq9I7RRRwgE6gjNRQ0hEKgjBEJL1VGbXn5u0aJFSk9P1+DBg1vk/Hl5JSG95IRheAvj0HYm2K2SpK1ZxcrNLQli69BW1FdHQGNRRwgE6gjNRQ0hEKgjBEJT6qj2mIYIapBPSEiQ1WqtM7FdXl6ekpOTj3hseXm53n33Xd1www1+21NSUnzn6NSpk985MzMzG9U+01Sb+OU9tJ1ph6wl3xbajtDRVuodoY06QiBQR2guagiBQB0hEFqqjoI62Z3dbteAAQO0atUq3zaPx6NVq1Zp2LBhRzx22bJlcjqdmjRpkt/2bt26KSUlxe+cpaWl2rBhw1HP2R7UriW/r4i15AEAAACgPQr60Prp06frtttu08CBAzV48GA9//zzqqio0LnnnitJmjVrllJTU3XLLbf4Hbdo0SKNHz9eCQkJftsNw9Bvf/tbPfHEE+rZs6e6deumxx57TJ06ddL48eNb7bqCpXbW+vzyalVWuxUeZg1yiwAAAAAAgRT0ID9hwgTl5+dr7ty5ysnJUf/+/fXMM8/4htbv379fFov/wIFt27Zp7dq1evbZZ+s958yZM1VRUaE///nPKi4u1vDhw/XMM8/I4XC0+PUEW4zDpii7VWVOt/YXV6l3UmSwmwQAAAAACCDDNLnz43Byc0N7ggvDkJKTY+q086IX1mpLTpke/c1AjemTGLwGok04XB0BjUEdIRCoIzQXNYRAoI4QCE2po9pjGiKo98ijZXStnfCumPvkAQAAAKC9Ici3Q2mxB2euBwAAAAC0LwT5dqh2wrv99MgDAAAAQLtDkG+H6JEHAAAAgPaLIN8O+e6RJ8gDAAAAQLtDkG+H0uK8y+wVVbpU5nQFuTUAAAAAgEAiyLdDUXab4sJtkuiVBwAAAID2hiDfTnXxDa+vCnJLAAAAAACBRJBvp7qwljwAAAAAtEsE+Xaqdub6/QytBwAAAIB2hSDfTnVh5noAAAAAaJcI8u1Ul1iG1gMAAABAe0SQb6cO7ZE3TTPIrQEAAAAABApBvp1Ki/WuJV/mdKukirXkAQAAAKC9IMi3U+FhViVGhkniPnkAAAAAaE8I8u3YwSXoWEseAAAAANoLgnw75pvwjh55AAAAAGg3CPLtWFoca8kDAAAAQHtDkG/HDg6tJ8gDAAAAQHtBkG/HutTMXM/QegAAAABoPwjy7ViXuAhJrCUPAAAAAO0JQb4d6xzjkCGp0uVRYUV1sJsDAAAAAAgAgnw7ZrdZlBJtl8TwegAAAABoLwjy7VxaLGvJAwAAAEB7QpBv53wz19MjDwAAAADtAkG+nfOtJc8SdAAAAADQLhDk27muNUPr99IjDwAAAADtAkG+nUuL864lv58gDwAAAADtAkG+netyyNB6D2vJAwAAAECbR5Bv51KjHbIYktNtKr/MGezmAAAAAACaiSDfztmsFqXGeIfXc588AAAAALR9BPkOoHYt+f2sJQ8AAAAAbR5BvgNgLXkAAAAAaD8I8h1Al5oe+X2sJQ8AAAAAbR5BvgOgRx4AAAAA2g+CfAdw6BJ0AAAAAIC2jSDfAaTFemetzyquktvDWvIAAAAA0JYR5DuAlGiHbBZDLo+pnFJmrgcAAACAtowg3wFYLYY61/TKM+EdAAAAALRtBPkOonbm+v1F9MgDAAAAQFtGkO8g0pi5HgAAAADaBYJ8B9E1jrXkAQAAAKA9IMh3EGmx9MgDAAAAQHtAkO8gWEseAAAAANoHgnwH0aVm1vrskiq53J4gtwYAAAAA0FQE+Q4iKcouh80ijylllTBzPQAAAAC0VQT5DsIwDHWO8fbKM7weAAAAANougnwH0oUl6AAAAACgzSPIdyC+IF/M0HoAAAAAaKuCHuRffvlljRs3ToMGDdKUKVO0cePGI+5fXFys2bNna+zYsRo4cKDOOOMM/e9///O9/o9//EMZGRl+X2eeeWZLX0ab0IUl6AAAAACgzbMF882XLl2qOXPmaPbs2RoyZIief/55zZgxQ8uWLVNSUlKd/Z1Op6ZPn66kpCQ99thjSk1N1b59+xQbG+u33zHHHKPnnnvO99xqtbb4tbQFabVL0BHkAQAAAKDNCmqQf+655zR16lRNnjxZkjR79mx9+umnWrx4sa688so6+y9evFhFRUVasGCBwsLCJEndunWrs5/ValVKSkrLNr4NOji0niAPAAAAAG1V0IK80+nUpk2bdNVVV/m2WSwWjR49WuvXr6/3mE8++URDhw7VX//6V3388cdKTEzUWWedpZkzZ/r1uu/cuVNjx46Vw+HQ0KFDdcstt6hLly6NbqNhNP66WlNt+xrazq5x3lnrc0qdqnZ7ZLcF/c4KhIDG1hFQH+oIgUAdobmoIQQCdYRAaEodNWbfoAX5goICud3uOkPok5KStG3btnqP2b17t1avXq2zzz5b//rXv7Rr1y7Nnj1bLpdL1113nSRp8ODBmjNnjnr37q2cnBw9/vjjuvjii/X2228rOjq6UW1MSopp2sW1soa2M8k0FWm3qtzpVqXVqi7Jjft5oH1rK/WO0EYdIRCoIzQXNYRAoI4QCC1VR0EdWt9YpmkqKSlJd999t6xWqwYOHKjs7GzNnz/fF+RPOeUU3/6ZmZkaMmSIfvGLX+i9997TlClTGvV+eXklMs2AXkJAGYa3MBrTzs4xDm3LK9d3O/MUa4TwxaHVNKWOgJ+jjhAI1BGaixpCIFBHCISm1FHtMQ0RtCCfkJAgq9WqvLw8v+15eXlKTk6u95iUlBTZbDa/YfR9+vRRTk6OnE6n7HZ7nWNiY2PVq1cv7dq1q9FtNE21iV/exrSzS1y4tuWVa29hZZu4NrSetlLvCG3UEQKBOkJzUUMIBOoIgdBSdRS0m6TtdrsGDBigVatW+bZ5PB6tWrVKw4YNq/eY4447Trt27ZLH4/Ft27Fjh1JSUuoN8ZJUVlam3bt3M/ldDd8SdKwlDwAAAABtUlBnO5s+fbpee+01LVmyRFu3btVdd92liooKnXvuuZKkWbNm6aGHHvLtf+GFF6qwsFD33nuvtm/frk8//VRPPfWULr74Yt8+999/v9asWaM9e/Zo3bp1uu6662SxWHTWWWe1+vWFIt/M9SxBBwAAAABtUlDvkZ8wYYLy8/M1d+5c5eTkqH///nrmmWd8Q+v3798vi+XgZw1paWmaP3++5syZo0mTJik1NVW//e1vNXPmTN8+WVlZuvnmm1VYWKjExEQNHz5cr732mhITE1v9+kKRby15lqADAAAAgDbJME3u/Dic3NzQnuDCMKTk5JhGtfPH7FJd8tI6JUaG6f2rR7VsA9EmNKWOgJ+jjhAI1BGaixpCIFBHCISm1FHtMQ3BQuIdTFrNWvL55dWqrHYHuTUAAAAAgMYiyHcwseFhinZ4Z/3fx/B6AAAAAGhzCPIdUFrNzPX7i5i5HgAAAADaGoJ8B9S1ZsK7vcxcDwAAAABtDkG+A/L1yDO0HgAAAADaHIJ8B8Ra8gAAAADQdhHkOyB65AEAAACg7SLId0Bd6ZEHAAAAgDaLIN8B1a4lX1TpUmmVK8itAQAAAAA0BkG+A4qy2xQXbpPE8HoAAAAAaGsI8h3UwQnvWEseAAAAANoSgnwH5Qvy9MgDAAAAQJtCkO+gutTOXM+EdwAAAADQphDkO6g0Zq4HAAAAgDaJIN9BMbQeAAAAANomgnwHVTu0fl9RpUzTDHJrAAAAAAANRZDvoNJivWvJlzndKmEteQAAAABoMwjyHVR4mFWJkWGSuE8eAAAAANoSgnwH1tV3nzxryQMAAABAW0GQ78DSYpm5HgAAAADaGoJ8B1Y7cz1ryQMAAABA20GQ78DSWIIOAAAAANocgnwH1pWh9QAAAADQ5hDkOzBfjzxryQMAAABAm0GQ78A6xzhkSKp0eVRQUR3s5gAAAAAAGoAg34HZbRalRNslMeEdAAAAALQVBPkOrnbm+r0EeQAAAABoEwjyHVztWvL7i6uC3BIAAAAAQEMQ5Du4LnHMXA8AAAAAbQlBvoPrEsta8gAAAADQlhDkOzh65AEAAACgbSHId3BpcQ5JUlZxpTysJQ8AAAAAIY8g38GlxoTLakhOt6m8MmewmwMAAAAAOAqCfAdnsxjqFOPtlWd4PQAAAACEPoI8Dt4nz4R3AAAAABDyCPI4uJZ8EWvJAwAAAECoI8iDmesBAAAAoA0hyIO15AEAAACgDSHIgx55AAAAAGhDCPJQWmzNWvIlVXJ7WEseAAAAAEIZQR5KiXbIZjHk9pjKKWXCOwAAAAAIZQR5yGox1LmmV5775AEAAAAgtBHkIemQCe+4Tx4AAAAAQhpBHpIOTnjHWvIAAAAAENoI8pB0MMjvZWg9AAAAAIQ0gjwkHRxav5+h9QAAAAAQ0gjykCSlsZY8AAAAALQJBHlIOji0/kBplVxuT5BbAwAAAAA4nKAH+Zdfflnjxo3ToEGDNGXKFG3cuPGI+xcXF2v27NkaO3asBg4cqDPOOEP/+9//mnVOSEmRYXLYLPKYUlYJE94BAAAAQKgKapBfunSp5syZo2uvvVZLlixRZmamZsyYoby8vHr3dzqdmj59uvbu3avHHntMy5Yt0913363U1NQmnxNehmEorWYt+f1MeAcAAAAAISuoQf65557T1KlTNXnyZPXr10+zZ89WeHi4Fi9eXO/+ixcvVlFRkR5//HENHz5c3bp10wknnKDMzMwmnxMHpbGWPAAAAACEPFuw3tjpdGrTpk266qqrfNssFotGjx6t9evX13vMJ598oqFDh+qvf/2rPv74YyUmJuqss87SzJkzZbVam3TOIzGMxl9Xa6ptX6Da2bV2LfniqpC/dgROoOsIHRN1hECgjtBc1BACgTpCIDSljhqzb9CCfEFBgdxut5KSkvy2JyUladu2bfUes3v3bq1evVpnn322/vWvf2nXrl2aPXu2XC6Xrrvuuiad80iSkmIafUwwBKqd/brESRv2K6/SpeTktnHtCJy2Uu8IbdQRAoE6QnNRQwgE6giB0FJ1FLQg3xSmaSopKUl33323rFarBg4cqOzsbM2fP1/XXXddwN8vL69Ephnw0waMYXgLI1DtjLd5PwLanlOq3NyS5p8QbUKg6wgdE3WEQKCO0FzUEAKBOkIgNKWOao9piKAF+YSEBFmt1jqT0OXl5Sk5ObneY1JSUmSz2WS1Wn3b+vTpo5ycHDmdziad80hMU23ilzdQ7ex8yD3ybeG6EVhtpd4R2qgjBAJ1hOaihhAI1BECoaXqKGiT3dntdg0YMECrVq3ybfN4PFq1apWGDRtW7zHHHXecdu3aJY/n4DrnO3bsUEpKiux2e5POiYO61gT5nFKnnC7WkgcAAACAUBTUWeunT5+u1157TUuWLNHWrVt11113qaKiQueee64kadasWXrooYd8+1944YUqLCzUvffeq+3bt+vTTz/VU089pYsvvrjB58ThxUXYFBHmLQmWoAMAAACA0BTUe+QnTJig/Px8zZ07Vzk5Oerfv7+eeeYZ3zD4/fv3y2I5+FlDWlqa5s+frzlz5mjSpElKTU3Vb3/7W82cObPB58ThGYahLnHh2ppbrv3FleqZGBnsJgEAAAAAfsYwTe78OJzc3NCe4MIwpOTkmIC283dLvtWKbfm6Y3w/nTukS2BOipDWEnWEjoc6QiBQR2guagiBQB0hEJpSR7XHNERQh9Yj9NSuJb+vuCrILQEAAAAA1IcgDz9ph8xcDwAAAAAIPQR5+OlS0yPPZHcAAAAAEJoI8vDThR55AAAAAAhpBHn4qe2Rzy+vVkW1O8itAQAAAAD8HEEefmLCbYp2WCUxvB4AAAAAQhFBHnUwvB4AAAAAQhdBHnXUDq/fV8QSdAAAAAAQagjyqONgkKdHHgAAAABCDUEeddSuJc898gAAAAAQegjyqIMeeQAAAAAIXQR51NGFHnkAAAAACFkEedSRFueQJBVVulRa5QpyawAAAAAAhyLIo44ou01x4TZJ9MoDAAAAQKghyKNe3CcPAAAAAKGJII96+YJ8MWvJAwAAAEAoIcijXrUT3tEjDwAAAAChhSCPeqXV9MjvJ8gDAAAAQEghyKNeB4fWE+QBAAAAIJQQ5FGvrocMrTdNM8itAQAAAADUIsijXp1jvWvJlzndKq5kLXkAAAAACBUEedQrPMyqpCi7JNaSBwAAAIBQQpDHYXWp6ZVn5noAAAAACB0EeRwWa8kDAAAAQOghyOOw0lhLHgAAAABCDkEeh1XbI8898gAAAAAQOgjyOKwuNT3ye+mRBwAAAICQQZDHYfl65FlLHgAAAABCBkEeh5Ua45AhqdLlUUFFdbCbAwAAAAAQQR5HYLdZlBJds5Y8w+sBAAAAICQQ5HFEtcPruU8eAAAAAEIDQR5HdHDmetaSBwAAAIBQYGvKQfv375dhGOrcubMkaePGjXr77bfVr18/nX/++QFtIIKLteQBAAAAILQ0qUf+lltu0erVqyVJOTk5mj59ur755hs98sgjmjdvXkAbiOCq7ZHfx1ryAAAAABASmhTkt2zZosGDB0uS3nvvPR1zzDFasGCB/v73v2vJkiUBbSCCqws98gAAAAAQUpoU5F0ul+x272zmn3/+ucaNGydJ6tOnj3JycgLXOgRdbY98VnGlPKwlDwAAAABB16Qg369fPy1YsEBfffWVPv/8c5188smSpAMHDig+Pj6Q7UOQdYpxyGpITrepvDJnsJsDAAAAAB1ek4L8rbfeqoULF2ratGmaOHGiMjMzJUmffPKJb8g92gebxVBqjEMSw+sBAAAAIBQ0adb6kSNHavXq1SotLVVcXJxv+9SpUxURERGwxiE0pMWFa19xlfYVV2pI17ijHwAAAAAAaDFN6pGvrKyU0+n0hfi9e/fq3//+t7Zv366kpKSANhDBVzvh3f4i1pIHAAAAgGBrUpC/5ppr9Oabb0qSiouLNXXqVD333HO69tpr9corrwSyfQgBaXHMXA8AAAAAoaJJQX7Tpk0aMWKEJOn9999XUlKS/vvf/+r+++/Xiy++GNAGIvi6spY8AAAAAISMJg+tj4qKkiStWLFCv/zlL2WxWDR06FDt27cvoA1E8KWxljwAAAAAhIwmBfkePXroo48+0v79+7VixQqNGTNGkpSXl6fo6OiANhDB51tLvqRKbg9ryQMAAABAMDUpyF977bV64IEHNG7cOA0ePFjDhg2TJK1cuVL9+/cPaAMRfMlRdtkshtweUzmlTHgHAAAAAMHUpOXnzjzzTA0fPlw5OTm+NeQladSoURo/fnzAGofQYLUYSot1aHdhpfYWVapzzVB7AAAAAEDra1KQl6SUlBSlpKQoKytLktS5c2cNHjw4YA1DaEmLDdfuwkrtZ8I7AAAAAAiqJgV5j8ejf/7zn3ruuedUXl4uSYqKitL06dN19dVXy2Jp0oh9hLAuLEEHAAAAACGhSUH+kUce0aJFi3TLLbfouOOOkyStXbtW8+bNk9Pp1O9+97uANhLB5wvyxdwjDwAAAADB1KQgv2TJEt1zzz067bTTfNsyMzOVmpqq2bNnNzrIv/zyy5o/f77vnvs777zzsMP033jjDd1xxx1+2+x2u7755hvf89tvv11Llizx22fs2LGaP39+o9qFg7qwBB0AAAAAhIQmBfmioiL16dOnzvY+ffqoqKioUedaunSp5syZo9mzZ2vIkCF6/vnnNWPGDC1btkxJSUn1HhMdHa1ly5b5nhuGUWefk046SXPmzPE9t9vtjWoX/KXV9MjvJ8gDAAAAQFA16Wb2zMxMvfzyy3W2v/zyy8rIyGjUuZ577jlNnTpVkydPVr9+/TR79myFh4dr8eLFhz3GMAzfZHspKSlKTk6us4/dbvfbJy4urlHtgr/aofUHSqvkcnuC3BoAAAAA6Lia1CP/+9//XldddZU+//xzDR06VJL09ddfa//+/Xr66acbfB6n06lNmzbpqquu8m2zWCwaPXq01q9ff9jjysvL9Ytf/EIej0fHHnusbr75Zh1zzDF++6xZs0ajRo1SbGysTjzxRN10001KSEho1HXW09EfUmrb1xrtTI4Kk8NmUZXLo+zSKnWLj2j5N0WraM06QvtFHSEQqCM0FzWEQKCOEAhNqaPG7NukIH/CCSdo2bJleuWVV7Rt2zZJ0umnn67zzz9fTzzxhEaMGNGg8xQUFMjtdtcZQp+UlOQ778/17t1b9913nzIyMlRSUqJnn31WF1xwgd5991117txZkndY/emnn65u3bpp9+7devjhhzVz5kwtXLhQVqu1wdeZlBTT4H2DqbXa2S0hQltzylQmi5KT28bPBg3XVuodoY06QiBQR2guagiBQB0hEFqqjpq8jnxqamqdSe1++OEHLVq0SHfffXezG3Y4w4YN07Bhw/yeT5gwQQsWLNBNN90kSZo4caLv9YyMDGVkZGj8+PG+XvqGyssrkWkGrOkBZxjewmitdqZG27U1p0zf785XRryj5d8QraK16wjtE3WEQKCO0FzUEAKBOkIgNKWOao9piCYH+UBISEiQ1WpVXl6e3/a8vLx673uvT1hYmPr3769du3Yddp/u3bsrISFBO3fubFSQN021iV/e1mpnWu3M9YWVbeLngsZpK/WO0EYdIRCoIzQXNYRAoI4QCC1VR02a7C5Q7Ha7BgwYoFWrVvm2eTwerVq1yq/X/Ujcbrc2b96slJSUw+6TlZWlwsLCI+6Do+vKWvIAAAAAEHRB7ZGXpOnTp+u2227TwIEDNXjwYD3//POqqKjQueeeK0maNWuWUlNTdcstt0iS5s2bp6FDh6pnz54qLi7W/PnztW/fPk2ZMkWSVFZWpnnz5umMM85QcnKydu/erQcffFA9e/bUSSedFLTrbA/SWEseAAAAAIKuUUH+uuuuO+LrxcXFjW7AhAkTlJ+fr7lz5yonJ0f9+/fXM8884xtav3//flksBwcOFBcX684771ROTo7i4uI0YMAALViwQP369ZMkWa1Wbd68WW+++aZKSkrUqVMnjRkzRjfeeCNryTdT7RJ0+4sJ8gAAAAAQLIZpNnzE/h133NGg/ebMmdPkBoWS3NzQnuDCMKTk5JhWa2dhebVOf8J7G8SKG8fKYQvqnRkIkNauI7RP1BECgTpCc1FDCATqCIHQlDqqPaYhGtUj314COpomLsKmyDCryqvdyiquVM/EyGA3CQAAAAA6HLpU0WCGYSgtzrvs3D6G1wMAAABAUBDk0ShdmPAOAAAAAIKKII9G6Z3kHU7/6U95QW4JAAAAAHRMBHk0yrlD0mQ1pNU7CrRpf+NXKQAAAAAANA9BHo3SNS5Cvzo2VZL0zOpdQW4NAAAAAHQ8BHk02vSRPWQxpBXb8vVDdkmwmwMAAAAAHQpBHo3WIyFCv8zsJEmaT688AAAAALQqgjya5PKRPWTIO+ndTzllwW4OAAAAAHQYBHk0Se+kSJ2WniKJXnkAAAAAaE0EeTTZjBN7SJI+3pyj7XnlQW4NAAAAAHQMBHk0Wb+UKJ3aL0mmpGe/oFceAAAAAFoDQR7NUtsr/8EPB7SroCLIrQEAAACA9o8gj2bJTI3R2D6J8pjSv+mVBwAAAIAWR5BHs9X2yi/9Llt7i+iVBwAAAICWRJBHsw1Mi9WJPRPkNqXn1+wOdnMAAAAAoF0jyCMganvl3/42W1nFlUFuDQAAAAC0XwR5BMTQbnEa0T1OLo+pF77cE+zmAAAAAEC7RZBHwMw4sack6a1v9iuntCrIrQEAAACA9okgj4AZ3j1OQ7vGyuk29SK98gAAAADQIgjyCBjDMHz3yr+xcb/yypxBbhEAAAAAtD8EeQTUyJ4JGtA5RlUuj17+il55AAAAAAg0gjwCyjAMXTHK2yu/aMM+FZZXB7lFAAAAANC+EOQRcGN6JyqzU7Qqqj16dR298gAAAAAQSAR5BNyh98ovXL9PxZX0ygMAAABAoBDk0SJO7pekfslRKnO6tXDdvmA3BwAAAADaDYI8WoTFMHR5Ta/8q+v2qrTKFeQWAQAAAED7QJBHixl3TLJ6J0aqpMql17+mVx4AAAAAAoEgjxZjtRiafmJ3SdLLX+1RudMd5BYBAAAAQNtHkEeLOj2jk3okRKio0qXFG+iVBwAAAIDmIsijRdkshi47wdsr/9JXe1RZTa88AAAAADQHQR4t7lf9O6lLrEP55dV6Y+P+YDcHAAAAANo0gjxanM1q0WUjvTPYv/jlHlW5PEFuEQAAAAC0XQR5tIqzBqQqNcah3DKn/vNtVrCbAwAAAABtFkEerSLMatGlNffKP79mt6rd9MoDAAAAQFMQ5NFqJg3srOQou7JLqvTOpuxgNwcAAAAA2iSCPFqNw2bRtOO7SZL+/cUuueiVBwAAAIBGI8ijVZ07OE2JkWHaV1yl974/EOzmAAAAAECbQ5BHqwoPs+qSEd5e+ee+2CWXxwxyiwAAAACgbSHIo9VNHtJFceE27S6s1Ic/0isPAAAAAI1BkEeri7RbdXFtr/zq3XLTKw8AAAAADUaQR1BMGdpFMQ6btueX65MtucFuDgAAAAC0GQR5BEW0w6YLj+sqSXp29S55THrlAQAAAKAhCPIImvOP66Iou1U/5Zbpfz/lBbs5AAAAANAmEOQRNLHhYTp/WBdJ0vzVu2TSKw8AAAAAR0WQR1BdeFw3RYRZ9OOBUq3cnh/s5gAAAABAyCPII6jiI8N03hBvr/wzq+iVBwAAAICjIcgj6C4e0U0Om0Wbskr0xc6CYDcHAAAAAEJaSAT5l19+WePGjdOgQYM0ZcoUbdy48bD7vvHGG8rIyPD7GjRokN8+pmnqscce09ixYzV48GBddtll2rFjRwtfBZoqKcqucwenSaJXHgAAAACOJuhBfunSpZozZ46uvfZaLVmyRJmZmZoxY4by8g4/i3l0dLRWrFjh+/rvf//r9/rTTz+tF198UXfddZdee+01RUREaMaMGaqqqmrpy0ETTTu+m+xWQxv2FWvt7qJgNwcAAAAAQlbQg/xzzz2nqVOnavLkyerXr59mz56t8PBwLV68+LDHGIahlJQU31dycrLvNdM09cILL+jqq6/W+PHjlZmZqQceeEAHDhzQRx991BqXhCZIiXbo14O8vfLzV+8McmsAAAAAIHTZgvnmTqdTmzZt0lVXXeXbZrFYNHr0aK1fv/6wx5WXl+sXv/iFPB6Pjj32WN1888065phjJEl79uxRTk6ORo8e7ds/JiZGQ4YM0fr16zVx4sQGt88wmnBRrai2faHezoa69IRuWrJxv77aXaQNe4s0tFtcsJvUIbS3OkJwUEcIBOoIzUUNIRCoIwRCU+qoMfsGNcgXFBTI7XYrKSnJb3tSUpK2bdtW7zG9e/fWfffdp4yMDJWUlOjZZ5/VBRdcoHfffVedO3dWTk6O7xw/P2dubm6j2peUFNOo/YOlrbTzaJKTYzRlRHe9umaXnl+7V+OHdgt2kzqU9lJHCC7qCIFAHaG5qCEEAnWEQGipOgpqkG+KYcOGadiwYX7PJ0yYoAULFuimm24K6Hvl5ZUolOddMwxvYYR6OxvjgsGpeu3LXfpsS64+/WavBqbFBrtJ7V57rCO0PuoIgUAdobmoIQQCdYRAaEod1R7TEEEN8gkJCbJarXUmtsvLy/O77/1IwsLC1L9/f+3atUuSlJKS4jtHp06d/M6ZmZnZqPaZptrEL29baWdDdImL0K+OTdU7m7L1zKpdeuQ3A4PdpA6jPdURgoc6QiBQR2guagiBQB0hEFqqjoI62Z3dbteAAQO0atUq3zaPx6NVq1b59bofidvt1ubNm30Bvlu3bkpJSfE7Z2lpqTZs2NDgcyK4po/sIYshrdiWrx+yS4LdHAAAAAAIKUGftX769Ol67bXXtGTJEm3dulV33XWXKioqdO6550qSZs2apYceesi3/7x587RixQrt3r1bmzZt0u9//3vt27dPU6ZMkeSd0f63v/2tnnjiCX388cf68ccfNWvWLHXq1Enjx48PyjWicXokROiXmd7RFPNX7wpyawAAAAAgtAT9HvkJEyYoPz9fc+fOVU5Ojvr3769nnnnGN7R+//79slgOft5QXFysO++8Uzk5OYqLi9OAAQO0YMEC9evXz7fPzJkzVVFRoT//+c8qLi7W8OHD9cwzz8jhcLT69aFpLh/ZQ+9/f0Cf/pSnLTmlOiYlOthNAgAAAICQYJgmd34cTm5uaE9wYRjemd5DvZ1Ndcfb3+ujzTkan56sOWcfG+zmtFvtvY7QOqgjBAJ1hOaihhAI1BECoSl1VHtMQwR9aD1wODNO7CFJ+nhzrrbnlQe5NQAAAAAQGgjyCFn9UqJ0ar8kmZKe/YJ75QEAAABAIsgjxNX2yn/wwwHtKqgIcmsAAAAAIPgI8ghpmakxGtsnUR5TumHxN/psa16wmwQAAAAAQUWQb8Osud9LK+dKrspgN6VF3XByH6VE27W3qFI3v7lJN73xLb3zAAAAADosgnwbFrl2nvThnYr88rFgN6VF9U6K1OvTR+i3x3eXzWJo5fZ8XfD8V5r32XaVO93Bbh4AAAAAtCqCfBtWdczZkqSIr/8lS/GeILemZUXZbbr+5N5acOlwje6doGq3qefX7NZ5z32pZd8fEKsoAgAAAOgoCPJtmLP3GVKvk2S4qxS1ek6wm9MqeiZG6tHfDNRD5wxQ17hw5ZQ6defSH3TVwg3afKA02M0DAAAAgBZHkG/LDEM6416ZMhS+5S3ZstYGu0WtwjAMndw3SQsvG6Grx/RSuM2i9XuLNe2ldbr/oy0qqqgOdhMBAAAAoMUQ5Nu6tCGq6j9VkhS9YrbUgYaYO2wWXX5iD70+fYTGp6fIY0qLNuzX5Ge/1Bsb9snt6Tg/CwAAAAAdB0G+HSgf+XuZtkiFZa+T46f/BLs5ra5zbLjmnN1fT0wZrL7JkSqqdGnORz/pspfXa8PeomA3DwAAAAACiiDfDniiO6v8uGskSVGf3ye5OubSbCN6xOulacN1yy/6Ktph1Q8HSnXFgg36y3s/KLe0KtjNAwAAAICAIMi3E+VDr5I7Ok3W0r2K/PqZYDcnaGwWQxcc11WLLz9evx7YWYakpd8d0HnPfaUXv9ytarcn2E0EAAAAgGYhyLcXYREqO/EOSVLEunkyyg4EuUHBlRhp15/OSNdzFw/TgM4xKnO6NXf5dl34/Fqt3pEf7OYBAAAAQJMR5NuRqvRzVN1pqCzVZYpa82CwmxMSBnSO0bMXDdWdZ6QrMTJMOwsqdP3ib/X7tzZpb1HHvAUBAAAAQNtGkG9PDItKx/5FkhT+3QJZc78LcoNCg8UwNGlgZy2+/HhdeFxXWQ3p05/yNPW5r/Tkyh2qrHYHu4kAAAAA0GAE+XbGlXa8KvudLUNmh1uO7miiHTbd/Iu+evm3wzWiR7ycblPzV+/SlOe+0sebc2TyswIAAADQBhDk26GyUX+QaXXIvnel7Ds+CnZzQk7f5Cj987xBuv/s/uoc41BWSZVuf/t7XbvoG23LKwt28wAAAADgiAjy7ZAntrsqhsyQJEV9frfkdga5RaHHMAyNS0/R69NH6IoTe8huNfTlrkJd9PxaPfzfrSqtcgW7iQAAAABQL4J8O1U+/Hp5IpJlK9ymiG9fCHZzQlZ4mFVXjeml16aP0Kn9kuQ2pVfX7dXkZ7/Uf77Nkofh9gAAAABCDEG+nTLtMSobeaskKfLLR2RUFgS5RaGta1yEHvz1AP1j8kD1TIhQfnm17n5/s3770nr976c87p8HAAAAEDII8u1YZf8L5UrKlKWqSJFfPhrs5rQJJ/ZK1KuXDtcNJ/dWlN2qHw+U6ta3NunSl9drxTYCPQAAAIDgI8i3ZxarSsf8WZIU8e3zshZsDXKD2oYwq0XTju+uN2ecoEtP6K6IMIu+zy7V75Zs0vRXvtbn2/MJ9AAAAACChiDfzlV3P1lVPU+T4XEp6vN7g92cNiU+MkzXndRbb11xgqaN6KZwm0Wbskp04xvfasarX2v1DgI9AAAAgNZHkO8AysbcKdOwyrHjA4XtWRns5rQ5CZF23XBKH715xQm6aHhXOWwWfbO/RNcv/lYzF2zQmp0FBHoAAAAArYYg3wG4E/qpcuA0SVL0irskjzu4DWqjkqLs+t2pffXmFSfowuO6ym41tGFfsa5d9I2uWrhBa3cXBruJAAAAADoAgnwHUXbCLfI44mTL+17hP7wW7Oa0aclRdt38C2+gP39YF9mthtbvLdb/vbZR//faBq3bUxjsJgIAAABoxwjyHYQZnqDyETdJkqJWPyDDWRrcBrUDKdEO3Tqun5bMOEFThnZRmNXQ2t1FumrhRl39+kZ9vaco2E0EAAAA0A4R5DuQikGXyhXXS5aKHEWsezzYzWk3OsU4NOu0fnrj8uM1eUiabBZDX+0q1MyFG3Tdoo3auK842E0EAAAA0I4Q5DsSq11lo/8kSYr8+l+yFO8JcoPal86x4bp9/DF6Y8bxOmdQZ1kthr7YWagZr36tGxZ/o037CfQAAAAAmo8g38E4e58hZ9dRMtxVilo9J9jNaZfSYsP1x1+ma/HlIzRpYKqshrRqR4Eue+Vr3fTGt/ouqyTYTQQAAADQhhHkOxrDUNmYv8iUofAtb8mWtTbYLWq3usZF6M4zMrTo8uN11oBUWQxp5fZ8Xfryet285Fv9kE2gBwAAANB4BPkOyJUyUJWZUyVJ0StmS6yB3qK6xUfoL2dm6PXpx2vCsZ1kMaTPtuVr2kvrdeubm/TjASYeBAAAANBwBPkOqvzEWTJtkQrLXifHT/8JdnM6hB4JEZr9q0wtvGyEzuzfSYak/23N0yUvrtOs/3ynn3LKgt1EAAAAAG0AQb6D8kSlqnz4tZKkqM/vk1wVQW5Rx9ErMVJ3T/AG+l9mpMiQ9N8tubrwhbW64+3vtDWXQA8AAADg8AjyHVj50Cvlju4ia+leRX79TLCb0+H0TorUvWf116uXDtf49GRJ0kebc3XB82t123++02aG3AMAAACoB0G+I7NFqOzE2yVJEevmySg7EOQGdUx9k6M05+xj9epvh2vcMd5A/8mWXF384jrd+uYmfc+keAAAAAAOQZDv4KrSz1F1p6GyVJcpas2DwW5Oh9YvJUr3TzpWr146XKfXDLn/39Y8/fal9brpjW/1zT7WoQcAAABAkIdhUenYuyRJ4d8tkDX3u+C2B+qXHKX7zuqvhZeN0K/6d/ItW3f5q1/r+kXf6Os9RcFuIgAAAIAgIshDrrQRqux3tgyZLEcXQnonReqvEzL1+vTjdfaAVFkNafXOAs1cuEFXv7ZBa3cXyuS/FQAAANDhEOQhSSob9QeZVofse1fKvuOjYDcHh+iREKE/n5mhRZcfr3MGdZbNYuir3UX6v9c26qqFG/TFzgICPQAAANCBEOQhSfLEdlfFkCskSVGf3y25nUFuEX6uW3yE/vjLdC2ZcbzOG5KmMKuh9XuLdd2ibzTj1a+1cns+gR4AAADoAAjy8Ckffp08EcmyFW5TxLcvBLs5OIzOseG6bfwxenPGCTp/WBc5bBZ9s79EN73xrS59eb3+91MegR4AAABoxwjy8DHtMSobeaskKfLLR2RUFgS5RTiSTjEO3Tqun9684gRdPLybwm0WfZ9dqlvf2qRLXlynT7bkykOgBwAAANodgjz8VPa/UK6kTFmqihT55aPBbg4aIDnKrptO7aP/zDxBl57QXZFhVm3OKdNt//lOF72wVh/8cEBuD4EeAAAAaC8I8vBnsap0zF8kSRHfPi9rwdYgNwgNlRBp13Un9dZbM0/Q5Sf2UJTdqq255frjuz/ogue/0tLvsuUi0AMAAABtHkEedVR3P0lVPU+T4XEp6vN7gt0cNFJ8RJiuHtNLb88cqStH91SMw6Yd+RX6y3s/aupzX+rtb7PkcnuC3UwAAAAATUSQR73Kxtwp02KTY8eHCtu9ItjNQRPEhNs0c1RP/WfmCbpmbC/Fhdu0u7BSf31/syY/95WWbNyvagI9AAAA0OYQ5FEvd0I/VQyYJkmKXjlb8riD3CI0VbTDpukje+g/M0fqhpN7KzEyTPuKKnXfh1v0m/lfatHX+1Tl4r8vAAAA0FaERJB/+eWXNW7cOA0aNEhTpkzRxo0bG3Tcu+++q4yMDF1zzTV+22+//XZlZGT4fc2YMaMlmt6ulZ9wszyOONnyvlf4DwuD3Rw0U6TdqmnHd9dbV5yg353aR0lRdmWXVOlvH/2k4+/5SLe+uUkL1u3VTzllzHYPAAAAhDBbsBuwdOlSzZkzR7Nnz9aQIUP0/PPPa8aMGVq2bJmSkpIOe9yePXt0//33a8SIEfW+ftJJJ2nOnDm+53a7PeBtb+/M8ASVj7hJ0StnK2r1g6rqN0mmPTrYzUIzhYdZddHwbjp3cJr+822WXvhyt7JLnPr0pzx9+lOeJO999sO7x2l493iN6B6vXokRMgwjyC0HAAAAIIVAkH/uuec0depUTZ48WZI0e/Zsffrpp1q8eLGuvPLKeo9xu9269dZbdf3112vt2rUqLi6us4/dbldKSkqLtr0jqBh0qcK/fUG2ou2KWPe4yk+8LdhNQoCEh1k1dVhXTR7aRfsr3fr4m336aleRvt5bpMKKan28OVcfb86VJCVF2TW8W5yG9/AG++7x4QR7AAAAIEiCGuSdTqc2bdqkq666yrfNYrFo9OjRWr9+/WGPe/zxx5WUlKQpU6Zo7dq19e6zZs0ajRo1SrGxsTrxxBN10003KSEhoVHtC/WcUtu+Fm2nza7yMX9S7NIZivz6X6oacLE8sd1a8A3R2sIshob1SFCPKJsuGylVuz3alFWir3YVau3uIm3cV6y8Mqc++DFHH/yYI0nqFG33hfoR3ePUNT4iyFeBYGuVv0do96gjNBc1hECgjhAITamjxuwb1CBfUFAgt9tdZwh9UlKStm3bVu8xX331lRYtWqQ333zzsOc96aSTdPrpp6tbt27avXu3Hn74Yc2cOVMLFy6U1WptcPuSkmIavG8wtXg7kyZL3/1bxo7PlLjuQem8Z1v2/RAUh9ZRWmqcxg/xfmBTWe3W17sLtWprnlZty9PXuwp1oNSp9747oPe+OyBJ6hofoVF9kzSqT5JG9U1SF4J9h9VW/m4itFFHaC5qCIFAHSEQWqqOgj60vjFKS0s1a9Ys3X333UpMTDzsfhMnTvR9XzvZ3fjx43299A2Vl1eiUJ7zyzC8hdEa7bSO/JPid5wp49vFKsz4rVxpw1v2DdFqGlJH/WLt6jcsTdOGpamy2q2N+4r11e5CfbWrSJuySrS3sEKL1u7RorV7JEnd4sO9vfU9vD32ydGOVrwiBENr/j1C+0UdobmoIQQCdYRAaEod1R7TEEEN8gkJCbJarcrLy/PbnpeXp+Tk5Dr77969W3v37tXVV1/t2+bxeNfBPvbYY7Vs2TL16NGjznHdu3dXQkKCdu7c2aggb5pqE7+8rdFOV/IAVfafqojvFypqxWwVTn6L8UbtTEPryGGz6vgeCTq+R4I0Rip3urVhX5G+2lWktbsL9X12ifYUVmpPYZbe/CZLktQzIUIjesRrePd4De8ep8RIJp9sr9rK302ENuoIzUUNIRCoIwRCS9VRUIO83W7XgAEDtGrVKo0fP16SN5ivWrVKl1xySZ39+/Tpo7fffttv26OPPqqysjL98Y9/VOfOnet9n6ysLBUWFjL5XTOVj5yl8C1vKyx7nRJfGitXYobcicfIlXiM3AnHyBXfT7JHBbuZaGWRdqtG9UrUqF7eUTKlVS59vfdgsP/xQKl2FlRoZ0GFFm/YL0nqkxSp47rFaUBajPqnxqhXYqSsFj4YAgAAABoi6EPrp0+frttuu00DBw7U4MGD9fzzz6uiokLnnnuuJGnWrFlKTU3VLbfcIofDofT0dL/jY2NjJcm3vaysTPPmzdMZZ5yh5ORk7d69Ww8++KB69uypk046qXUvrp3xRKWqdMydil7+R1mLd8pavFPa8YHfPu6YbnIleIO9N+Sny53QT6YjLkitRmuLdtg0tk+Sxvbxzn1RXFmt9XuK9NVub7DfklOmbXnl2pZXrkU1wT4izKLMTtHq39kb7PunRqt7QoQsjPoAAAAA6gh6kJ8wYYLy8/M1d+5c5eTkqH///nrmmWd8Q+v3798vi8XS4PNZrVZt3rxZb775pkpKStSpUyeNGTNGN954I2vJB0DlwGmq6nOmbPmbZc3fLFvBlprHn2SpyJW1ZI+sJXukXf/1O84dmeoN9jUB353gDflmRNJh3gntRWx4mE7pl6xT+nl/pwvLq7VuT6E27CvW91kl+uFAqSqqPVq/t1jr9x5cSjLaYVVmaoyOTY1W/9QYHds5RmmxDpa9AwAAQIdnmCZ3fhxObm5oT3BhGFJyckzItNOoyPcG+4ItsuZv8YV8a1nWYY/xhCf+LNx7Hz1RnbkHv5UEu47cHlM7C8r1fVapvssq0ffZJdqcU6Yql6fOvnHhNvXv7B/uU6LthPsQEOw6QvtAHaG5qCEEAnWEQGhKHdUe0xBB75FH+2FGJKo6YqSqu4z0225UFcta8JOsBbXh3vtoKd4tS2W+7Pu/kPZ/4XeMxx7jDfZ+IT9DnpiuBPx2xmox1CcpSn2SojRxQKokyeX2aFteeU2wL9X32SXaklOmokqXVu8o0OodBb7jk6Ls6p8arWNrgn3/ztFMpgcAAIB2jSCPFmc6YuXqfJxcnY9T1aEvVFfIVrjV22t/SMi3Fu2QxVkiS/Y6hWWv8zuXxx4jd2KGXEmZciVlyp2UKVdipszw+Na8JLQwm9Wi9E7RSu8UrXNqtjldHv2UW+brtf8+u1TbcsuUV+bUim35WrEt33d8aozDG+47x+jY1BhlpkYrLiIsKNcCAAAABBpBHsETFiFXykC5Ugb6b3dXyVq4XdaCn7z34hds8T4WbvUG/KyvFJb1lf8hUam+UO9K6u/9PqGfZAtvxQtCS7LbLN5g3vngcKPKard+PFDq67X/PqtUO/LLlV1SpeySKn3608GlLbvGhevYzjEa2jVWQ7vGqV9KFJPpAQAAoE0iyCP0WB1y1/S2Ow/d7nbKWrhVtrwfZMv7Udb8H2TL+8E7wV5Ztqxl2bLv+p9vd9Owyh3fW67Emp77pAy5EjPliespGQ2fQLFVuCplqSqSUVkoMyxSnug0ycKv59GEh1k1pGuchnQ9uCpCmdOlH7Jrwn1N7/3uwkrtLfJ+ffhjjiQpxmHTkK6xGtY1TkO7xal/arTCrCFWFwAAAEA9SApoO6x2uZP6y53U32+IvuEskTXvR2/Az/9e1jxvwLdUFclW8JNsBT9JW9/x7W/aIuRKTK8Zmt+/phc/U2ZkcvPaZ5pSdbksVYUyKgtrHgsOeV4ko6pQlsrCuo+uCv9TWWxyx3STJ66n3LG95I7rKXdsz5rHHlJYZPPa2o5F2W0a3j1ew7vH+7YVV1br++xSfbu/WF/vKdbGfcUqqXL5Dcl32CwalBajYd3iNLRrnAZ1iVVEmDVIVwEAAAAcHrPWH0Goz1TJjJpHYJqylGf7Qr0t7wfv9wVbZLir6j3EE5HkC/XeYfoZksV6SCg/wmNNKDc81U1vsmGR6YiT4SyT4XEecV93ZKeakN/zZyG/p3dJv0YMGe+IdeTymNp8oFRf7y3S+j3er6JKl98+Vouh/qnRvh77oV1jFRvOffaH0xHrCIFHHaG5qCEEAnWEQGjpWesJ8kcQ6r+8/JFpAo9L1qIdBwN+vjfgW4t2ylBgfoimJUye8ASZjniZ4fHy/PwxPF6mo+6jaY/2Dvn3uGUpy5a1eIesRTtlLdopS7H30Vq8U5aqoiNfYliUPLXB/mch3xPTtc6QfepI8pimduSX+0L9+j1FOlDq/2GKIalvclRNj32shnWLU0q0IzgNDkHUEQKBOkJzUUMIBOoIgUCQD6JQ/+Xlj0wAVZfLlr/Z23OfX3MPfsFmybDUG7rrPib4nssW0aJL5BmVhbLWBvuinbIU75C1eJf3+9L9R/xAwrTY5InuKndcL7lje8gd11OeuJ6K7dpHBaUeeazhUliETGu4zLAIyWLvkMv9maap/cVV+npvkdbtKdLXe4q0s6Cizn7d4sN9PfbHdYtT17jwDrumPX+PEAjUEZqLGkIgUEcIBIJ8EIX6Ly9/ZFCHq9I7+V/RTu8yfsW7Dob+4l2Hva3gcEwZki1Cpi1c5iGPOuLzQ7cd3F7nPPY4eaI7h97Eg4eRV+bUhtpgv7dYmw+U1vnIJDnK7rvH/rhuceqTHNlhZsbn7xECgTpCc1FDCATqCIHQ0kGeye6A9sQWLndCP7kT+tV9zfTIUpZV04u/yzdU31q0Q2FVBfI4yyVXpQxXhQzTLUne3n1XuQxXeYs017Q6vKMD4vt4v+J6yxXfR+743jIjkkNqNEBSlF3j0lM0Lj1FklRa5dKGfcVaX9NjvymrRLllTn34Y45vZvzYcJuGdInViB7xOqFngvomRXbYHnsAAAAEDkEe6CgMizzRXeSJ7iJ1HXVwc80nf/mHflrorvbOpF8b7Gsf3ZVStffRqK7wvaY6+1Qe3MddWf+5qopkuKtky/9Rtvwf6zTXY4+pCff+Qd8d31umI67O/q0t2mHTmN6JGtM7UZJ3TftNWSXeYL+3SBv3Fau40qXPtuXrs5qZ8RMjw3R8Tag/oUe8OseGB/MSAAAA0EYR5AHUZQ2TaQ2THLEBmgKwHh6XLMW7ZSvaLmvhNlmLtsta6P3eUrJXFmeJLAc2KOzAhrqHRiTLHd9brjhv7733yxv6ZYtoqRYfUXiY1W/ZO5fbox9zyrRud6HW7CrU+j1Fyi+v1vs/5Oj9H7w99j0SInzBfkT3OGbFBwAAQINwj/wRhPp9Mdy/g0AIyTpyVdbc518T8g8N+uUHjnioO7pLTc99TS9+bciP6S5ZgxeUnS6PvtlfrDW7CvXlzgJtyiqR55CftyEpMzXa11s/pGucHLa2MX+AFKJ1hDaHOkJzUUMIBOoIgcBkd0EU6r+8/JFBILS1OjKcpYcE/EN787cdcWk+07DKE9NN7ujO8kR1licyVZ4o/y93VGcpLLJVrqO0yqW1uwv15a5CrdlZqO35/vMQ2K2GhnSN0wk1PfYZnaJltYTu/fVtrY4QmqgjNBc1hECgjhAIBPkgCvVfXv7IIBDaTR2ZpozKgjoh31YT9A1X3eXj6uOxx3iDfWTdkO97HtlJsgX2/vYDJVX6clehvtxVoDW7CpXzs3XsY8NtGt493hfsu8eH1lJ37aaOEFTUEZqLGkIgUEcIBGatB4CGMAyZEYlyRSTK1Xm4/2um6Z2xv3iXLGXZNV9Z3sdy73NraZYMV7n33nxniVTw0xHfzuOIrwn2nWuCvjfgHwz/neWJTJGs9gY1v1OMQxMHpGrigFSZpqkd+RVas7NAX+4q1Fe7C1Vc6dJ/t+Tqv1tyJUmdYxy+++uP7xGvpKiGvU9zudwelVe7Ve50q6La+32F061Kl1tDTEOxofPZAgAAQLtFkAfQ/hmGPNFp8kSnHXk3Z6l/yD806B/yAYDhrpKlqlCWqkKpnhn3D+UJT5BpsUsWiySLZLFKMmQatd9bvB+/GtZDthlKMCwaZrHqSllkdjNUVm2qqNKtokqPCqs8clca8my2yLPZ0HYZynKEKSEyXIlRDiVEhcsSHiuXPV5VtlhV2GJVZo1RmRGjEku0SswYFSpS5W5LTSB3q9zpUXm1q05Ar32sqPZ+X+0+8kfKfZMjddoxKRqXnqw+LLcHAADQIgjyAFDDtEfLbY+WO6HvEXYyZVQV+YV8b9A/JPyXZctSfkCGp1qWyoKAtM0hKbH2SX1z4LkkFdd8NVCJGaEiRanAjFahGa0iRavQjFKhap9HqbDmtcKa14oULafCFGY1FBlmVUSYVRF2q+xWi7bmlmlrbrm25u7Uv1btVK/ECI1LT9FpxyTrmJQoQj0AAECAEOQBoDEMQ2Z4vNzh8XInZRx+P9Mjo7JAlvIcyeOWIY/kcUumR5L5s22mVPO9ccjrB7cdfF3yeD9M8L3uUbnTqV355dqdX6rd+WUqraxStFGheJUq3ihTolGmBEupElSqWJUqRmWSpBijQjGqUDcjt1E/Ao8tUmZ4vExHvDzh8b7vjcxEfZtj6tt8UxvzDBUURmjjF5Fa+UWkomITNbxvD43N7K7+nWMJ9QAAAM1AkAeAlmBYZEYkyR2R1OJvZZHUq+ZLknJLq2RK3t7yMKvfbPeVkio9bhnOYlkqC2RUem8RMCoLZVQVyuJ79H/NUlUoo6pIhumRxVUulZZLpfvqtGV4zVedf12qJH0nuTcZKjMi5Q6LkS0yTo6oeJn2OJmOGHnssTIdsTLtsT97HiPTESePPUamI1ayOgL9IwQAAGhTCPIA0M4kRx8l6FqsMsMT5A5PaNyJTY8MZ0ndgF9ZIEtVoaIslaoszPHuU1Vc81gko6pEqiqS1XTJapiKVZlUXSYVZUmHXzHw8M2wOmTaY+VxxDQj1Dd9GmLTFiF3XK+ar95yx/eWO663zPD4Jp8TAACgMQjyAICGMSwyHXHe3nH19H/JkKKSY1R6uCVWTFNyV8pZVqiN2/fo6227tX3vfoW5yhRrlClG5Uq1VykzzqNeUdVKslXJ6iyW4Sz2fShgcZZ438tdJaMiR5aKnFa46PqFZa+vs80TnlAn3PtCviM2CK0EAADtFUEeANDyDEOyRcgeF6ERQ9M0YujxqnJ59MXOAn2yOUdvb81TaYVbqvDunhARplOPSdJpx6RoePc42awW73wB1aUHg31VkeSpbmgDAraf4SyStXC7rEU7ZC3aLmvhDlnLs2WpLJClsuAwIT+xTrh3x/WSO763THvD1osFAACoRZAHAASFw2bRyX2TdHLfJFW7PVqzq1CfbM7R/37KU0FFtZZszNKSjVmKC7fplH5JGpeeohN6xCvMESdJcge5/X6cZb5gbyvcLkvRDtmKtstauF2WihxZKvNlycpXWNbaOod6IpL9w70v7PeSaY8OwsUAAIBQZ5hmvYMgISn3cENEQ4RhSMnJMSHfToQ26giBEMg6crk9Wru7SB9vydGnW7yhvla0w6pT+ibpF8ek6MReCXLY6luLL7QYzhJvyC+s6cGvCfjWou2yVOQd8Vh3ZCd54nrJHdNNpi1CptUu2RwyrQ7J6pBptdd8b5dpc0gWh0ybd/vB18MPvl6zf+3xslhb6afQMPw9QnNRQwgE6giB0JQ6qj2mQfsS5A8v1H95+SODQKCOEAgtVUcuj6kNe4v08eZcfbIlV3llTt9rkWFWDe4aq5Qou5Kj7UqOctQ8Hvyyh3jQN6qKDxmi/7OQX1nQ4u9vWmySxX5I+A8/+OGALVyeiCR5IlNqvjrJE5lc85giT0SKFBYR0Pbw9wjNRQ0hEKgjBEJLB3mG1gMAQpbNYmh493gN7x6vW37RV9/sK9bHW3L1yeYcHSh1avWOI4fduHCbkqLsSqkJ+ElRDt/3yb4PAOwKDwtOz7TpiJWr02C5Og2u85pRWegL+ZbSLBnuKsldJcPtlOGulNxOGa4q72PNdrkrva+7qiTPoa9X1rxeJcP0HHwPj0vyuGS4ypvUfk9YtC/km5HJhw38nshkyWpv8s8JAAD4I8gDANoEq8XQ0G5xGtotTr87tY++yyrRtrxy5ZY6lVtW81Va5fu+2m2qqNKlokqXtuUdOahGO6xKiXIo6ZCQfzD825US7VBylF2R9tYL/GZ4vFzhQ+VKHRrYE3tckqtKhscpw1V5yAcBNaG/dpurXJaKPFnKDshSkStLeY4s5QdkKc+VpfyADHeVLNWlshSVSkXbj/62jvhDevdT/Hv6I7zB34xKlhLCA3u9AAC0QwR5AECbYzEMDUyL1cC0+pd1M01TxZUu5ZQ5lVcT9HNqQn5eWe1z72OVy6PSKrdKq8q1Pf/IgT8yzKrOsQ5ldIpWZqr3Kz0lWtGONvTPqcUm2W0yFaUmjxg1Te/KARXeUG8py/EuCegX9r1LBFrKc2R4XLJUFcpSVSgVbDnq6RPDomWGJ8gTHu99dMT7Pw+Pl+k49HmCTHtsyN3zDwBAS2lD/+cBAEDDGIahuIgwxUWEqV9y1GH3M01TZU53Taiv6c2v7eH36+l3qrzarfJqt7bllWtbXrne+/6A7zw9EiKUWRPuMzp5v+IiwlrjUoPDMGQ6YuV2xMod3+fI+5oeGVVFNSHfv1ffF/bLagJ/ZZ4M0yNLdalUXSprye4GN8mUIdMR5x/uHfHex/CEw2yPlxkW7b0pEQCANoQgDwDosAzDULTDpmiHTb2TIo+4b7nTrZzSKu0urNAP2aXerwOlyi6p0q6CCu0qqNAHP+b49u8SF+4X7jNTo5UY2QHvEzcsMsMT5A5PkDsx/ci7yqPkKLfy9+2WUVEoS2WBjKoCWSoLZVTWPFbVbK88ZHt1qQyZ3teqCqWiHQ1unmkJk+mIlcceK9MR6/0wwPd9rEx7nDy+72PlccT5XvPY4yRbOB8E/Jzp8d6+4a6ULGEsowgALYAgDwBAA0TareqZGKmeiZEa2yfJt72g3KkfDxwM9j9kl2pvUaX21Xx9siXXt2+naLsyU2OU2SlaGanRyuwUrZRouwyCoJdhkSLj5IkPkxnXiOPcTm+vf2VBTcg/JOxXFfo/Hvq6u0qGp1pGRd5RlwI8nIZ9EBAj017zWs0HAqbNUd8P4GdPf14XR3l+tP1Nl4zagO2q9P/eXSnDVVkzR0JV3e9rHnWY7/329RxcXcKUIVfKQFV3GyNn1zGq7jJSCjvyh2YAgKNj+bkjCPUlJ1gaA4FAHSEQqCN/xZXV2nygrCbYl+iH7FLtKqio9570xMgw7/32naKVURPy02IdHTLct3odVVd4A72zWEZVsSzOYhlVRYd8731+8PtiWaqKfPsbprsVGtm+mJYwuVKHydltjKq7jVF16jDJWt+HGk3D3yIEAnWEQGD5OQAA2pjY8DCN6BGvET3ifdvKnC5tOTTcHyjV9rxy5ZdX6/PtBfp8+8Gl9OLCbb7h+BmdvBPqpcWFy2GzBOFq2rGwCHnCIiR1afyxpilVl8viLDoY8hvxQYDc1T8/od8zo87/9R3leUP+L9EwZFrDZdq8X7I6Dvm+nu3WcO/IgUO/r3msfV02h++cB/cLl2l1SDaHLBV5CtuzUmF7V8q+Z6WsJXsUtn+Nwvavkb58RKYtXNVpI+XsNlrV3cbKlTyQSQsBoAHokT+CUP8Ujk8LEQjUEQKBOmqaymq3fsot0/fZpfqxZmj+1twyuTz1/xCTouxKi3Woc0y4usQ51Dk2XGmxDqXFhistNrxVl8drCdRRO2eashTvkn3PCoXt/Vz2PStlqcj128XjiFN1lxO9PfZdx3jnVWjE6BRqCIFAHSEQ6JEHAKCdCg+z1llGz+nyaFteTbivued+a26ZKl0e5dUsn/ft/pJ6zxcXbvML951jHepSE/I7xzoUG27rkEP2ESIMQ564nqqM66nKARdLpilr/o/eYL/nc4XtWyVLVZEc29+XY/v7kiRPRIqvt97ZbYw8sT2CfBEAEBoI8gAAhBC7zeKdEC/14CfypmmqqMKl/SWV2l9cpf1FldpfXKms4irtL/ZuK6lyqajSpaJK7wcA9YkMsyotribkx9T05Md5g3/n2HAlRYYR9NF6DEPupExVJGWqYsgVksclW843CtvjHYYftn+NLBU5Ct/ylsK3vCVJcsf2kLNrTbDvOlpmVKcgXwQABAdBHgCAEGcYhuIjwxQfGab+qfUPuSutch0S7L3hPqu4UvtqHvPLq1Ve7dbW3HJtzS2v9xx2q+Hr0U+NcSgizKowq0V2m0UOq0VhVkMOm0X2mm0HH41D9qnZ3+b93nHIPnxIgCOy2ORKHSZX6jBVDL9OclcpLGutL9jbDnwta/EuRRTvUsT3CyRJrsQMX7Cv7nqiFN6Y5Q4awOP2rorgcXof3dWSxynD7ZTc1b6VD2R65I7tKU90GssRAmgV3CN/BKF+Xwz37yAQqCMEAnUU+iqr3coqqfIL+Yf27ueUOuudVT+QwqyGN/z7hX3vNofNovAwq0b0TtLQzlEa0DlWNguBCAcZzlKF7ftCYXs/V9ieFQrL3eT3umlY5EoZpLBeJ6qiyhvAveHbKXmqa8K307vkYH2veWqC+qHB3fQ0qo0ee4zcielyJabLnZghV2KG3Inp8kR2IuC3IfybhkBo6XvkCfJHEOq/vPyRQSBQRwgE6qjtq3Z7lF1S5evVzyl1qsrlVpXLVLXboyq3R06Xx/u9yyOn2yOn25Sz9vvDbGtqOcSG23RCjwSN6ZOgUb0SlRRlD+j1ou0zKvK9k+bVBHtb4bYWf0/TYpdpDZOsdpkWu/fRGua9379ktwyPq97jPI44uRIzvSE/KaMm7GfIjEhq8TYHjOmRUVkg0x4d0CUDQxH/piEQCPJBFOq/vPyRQSBQRwgE6gj1MU1TLo+pKr8PAMyDwd8X/r3biyurtTG7TP/78YCKK/0DUWanaI3unaDRvRM1MC1WVnrr8TOW0n2y7/1cMeVbVV7pkWm1Sxa7TOvPw3eY32ve5w7JElazn0OmpWb/Q46RJezIvepup6yF22TL3yxr/o+y5f8oa/5mWYt2HLZn3xORXNN7ny5XYqbvezM8vmV+SPVxVchSniNL2QFZymu/cmQpy/Y++rblyjDdMi1hcicco+qUQXKlDJAreaDcycd6A347wb9pCASCfBCF+i8vf2QQCNQRAoE6QiDU1lHWgWJ9u69Yn+8o0Krt+fo+23/yvthwm0b2TNDo3vTWw19I/i1yVcpasFW2Q8K9LX+zrMU7D3uIOyq1Zmh++iGP6TLtDfsffG/veaEs5dn1h/TyAzXbcmRxFjf7Ek0Zcsf1kitloFzJA2oeB8qMTG72uYMhJOsIbQ5BPohC/ZeXPzIIBOoIgUAdIRAOV0e5ZU6t3pGvz7cX6IudBXV66/unRmtU70SN7pVAb30H16b+FlWXy1awxRvs8344GPBL9x72EHd0V1+odyccI3mch4T0HL+wfrhh/vUxrQ55IjvJE9VJnsgUeSJTvY9RnbzbI1O8jxFJspQdkC33W9lyvvU9Wsuy6m9vVOc64d4T0y3k5wtoU3VUy6+h5s+2/fz5IdsMi2Rh/vOWQJAPolD/5W2Tf2QQcqgjBAJ1hEBoSB25PKY27S/W59u9wf6HA3V760/s6R2Cf2KvBHrrO5j28LfIcJbUhPpDeu/zfpS1PLvR5/KEJx4M4YcN6Z28Pf3NCNdGRd4hwX6TbLnfylq4XUY9s2R4HHE1wX6QL+C74/tKFmuT3z/QWrSOPG5ZSvfKWrjNeytG4TZZC7fLWrRdltIseQP2EYJ3zbb6frZN5Y7uKndCP7ni+8id0E/u+L5yJ/SRJ4pVGJqDIB9Eof6PQHv4xwrBRx0hEKgjBEJT6qi2t37lNm9vfUlV3d760b0TNbp3ogZ0jqG3vp1rz3+LjMoCWfO3HByiX7hNpi3i8CE9IlmyBu+DLMNZKmvud37h3pa/2btc38+YtnC5kvrLlTzQd9+9KylTsoUHoeUBqCPTlFGeI1vRNl9gtxZu9z4W7fSuitAGeMKi5I7v4/2qCfiu+L5yx/eRwiKC3byQR5APolD/R6A9/2OF1kMdIRCoIwRCc+uotrd+ZU1v/Y8/662P891bn6hRvROUGElvfXvD36IQ566SLX9LTe/9NzUB/zsZrvI6u5qGVe7EY7yT6cX1kscRJ9MRK9MR5/3eHivTESuPI06yRQS057ihdWRUFR0M6IXbZC06+L2luuywx5lWh9xxveSO7+0NyXF9vN9Hdz04MsF3PQevy6z9/uev1bNv3Z/Hz/et2eaukrVoh2wFP8lauFXWgm2yFv7k/cDBdB/2Gry9+DXBPqFvTS9+X3rxD0GQD6JQ/0eAf6wQCNQRAoE6QiAEuo5yS6u0akeBPt+er9U7C1Ra5f8/pbW99f1To9U5NlxdYsMVE869om0Zf4vaII/bGyR9991vki3nW1kq8xt8CtMS5g31NeHedMTL44j1C/tmzQcB3n3iaj4Q8L7+8+X0/OqoukLWop1+Peu1Pe2WirzDt8mwyBPTXe743t4h6/F95I7zBndPdJeQupWgXu5qWYt3yVob8Au3ylbgfbRUFhz2MNMWKVdC35qe/L41Q/Y7Zi8+QT6IQv0fAf6xQiBQRwgE6giB0JJ15PKYNTPh199bXyvKblVabLjSYh1Kiw1X51iHusSFq3PNtoSIMBn0NoUs/ha1E6YpS+l+X7i3lGXJqCqWpapIhrNYRlWRLFXexyP1Gjf47Wzh8thre/y9Qd9u9cids0WWkn1HvB/dHZl6sGf9kLDujutR5wOC9sKoyD8k2P9U04u/VdbinUecZLG2F98d19u79KPp8f73M03JdEumRzLdMvyeew7Zz+O3r+9Yj1uSR/J4ZMjjff7zY2WofNiVqso4r/V+Th0hyL/88suaP3++cnJylJmZqTvvvFODBw8+6nHvvvuubr75Zp122mn65z//6dtumqbmzp2r119/XcXFxTruuON01113qVevXo1qV6j/I8A/VggE6giBQB0hEFqzjnJLq/T5jgKt2VmgXQUVyiquUkFF3Xt3f85hsygt1uHrwe9cE/hrg39ytF0Wgn7Q8LeogzFNqbpcFmfRwaBfVSzj58+rimv2qd1eXPOBQHGDJo3z2GMPBvX4PocMie8t0x7dChfaRtT24hdu9fXk2wq3yVrw0xF78VtLZb+zVXLGE632fu0+yC9dulSzZs3S7NmzNWTIED3//PNatmyZli37//buPTiq+v7/+Gvv2SSbkKskQGLAJighMTAOAkF/Vqq2Yh0vaFuVylDbKnVaLxWmFxC0gm11BEWrlbGoZX5laNWCl/60v9ppf0WxiiDIF1GQa5AkJNkku9nr+f2xm01W7rBh98DzMZPZk885Z/Ne/HiS1zmf8zlvqKio6LD77d69W9/5znc0bNgw5efnJwX5Z555Rs8884wWLlyooUOHatGiRfrkk0/02muvyeU69jNjmf5LgF9WSAX6EVKBfoRUSHc/8oci2ucNqMnbE/8KaJ+3R3s7AtrX2aOWruBR/+S3Wy0aHA/6ZR6XyvL7Qn5ZXpZKPS7ZT3LCvahhKBo1FDFiy5GoEW+TIobRr01Jy0YKZ7k+Vi67VYM9WadsksF09yGYTDQiS6irX+iPXfG3BrzyeNxqt5cpnD9cRlYh932fpP5X8a3e2P33hsUWe/xd4ssmw2KN/Vv3W2fE1/Xftq+tb1vjS++V1Ga1KzR47CmdQPG0D/JTp07V6NGjNWfOHElSNBrVxRdfrFtuuUXf//73D7lPJBLRTTfdpOuuu07vv/++vF5vIsgbhqFJkyZp+vTpmjFjhiSps7NTEyZM0MKFC3XllVcec22Z/kuAX1ZIBfoRUoF+hFTI9H4UDEf1RWcs6B8q8H/RGVDkKHVbLVJJrkvZTpui8QAeMXSY5eRw3hvezcZhs2joILcqC9yqLMxOes13O1L6szK9D8Ec6EdIhYEO8mmd0SUYDGrTpk36wQ9+kGizWq2aMGGC1q1bd9j9lixZoqKiIk2dOlXvv/9+0rrdu3erublZEyZMSLR5PB7V19dr3bp1xxXkM/3EW299mV4nMhv9CKlAP0IqZHo/cjmsqih0q6Lw0BM2haOGWroCavIGtLejJxH498Zf93l7FIwY+qIzMKB12iyS1WqR1WKRzWKR1SrZLJa03NvvC4YVjBja3urT9lafpOTJwQa5Haos7BfyC906uyBbQwZlyWGzHvfPy/Q+BHOgHyEVTqQfHc+2aQ3ybW1tikQiBw2hLyoq0rZt2w65z3//+1+tXLlSL7/88iHXNzc3J97jy+/Z0tJyXPUVFR3b2ZB0M0udyGz0I6QC/QipYOZ+NLhUqj3Mumg86O9u96snFJHNYpHNapHVaulbjr/arEos97X1W+4N6Ae1ZVbyiEQN7W3367PmLm1r7ta2lvhrc7f2eXvU7g+pfU9I6/d4k/azWS2qKMzW8OIcDS/J0fCSXA0vzlFVSY5Kcl1HPSlh5j6EzEE/QioMVD8y1TNWurq6dN999+mBBx5QYWHhgP+81tbMHk5jscQ6RqbXicxGP0Iq0I+QCmdCP7JKqsi269j+BDPiMzRLiva1RpO/zXhuSbVFbtUWuSUVJ9p9wYh2tvn0+QG/dhzwaUebXzvbYsv+UFTbW7q1vaVbf/+f5PfLddlUUZCduJJ/dvxK/rBBbrmdttO+D2HgnQnHIgy8E+lHvfsci7QG+YKCAtlsNrW2Jg+zam1tVXFx8UHb79q1S3v27NHtt9+eaItGY7/KzjvvPL3xxhsqKSlJvEdpaWnSe44cOfK46jPivz8znVnqRGajHyEV6EdIBfrRmcHtsKmm1KOa0uQ/Wg3DUHNXUDvafNpxwK8dbX1Bv6mjR12BiD7e16mP93Um7WeRNDjPperBeRpZnK268jzVluUp25nhz+tGxuJYhFQYqH6U1iDvdDo1atQorVmzRpMnT5YUC+Zr1qzRzTfffND2w4cP16pVq5LaHnvsMXV3d+vnP/+5Bg8eLIfDoZKSEq1Zs0bnnnuupNiV/PXr1+vb3/72wH8oAAAAnDCLxaJSj0ulHpcuqChIWhcIR7Wr3a+d8WC/I/HqV2cgrCZvQE3eZv3zk9j2NotUXZqr+iH5qi/PU/2QPJXknp7P9gZwZkn70Prp06dr1qxZqq2tVV1dnZYtWya/369rr71WknTffffprLPO0j333COXy6Xq6uqk/fPy8iQpqX3atGl66qmnVFlZmXj8XGlpaeJkAQAAAMzHZbfqnOIcnVOck9RuGIba/CHtbPOryR/W/9uyX+v3eLWvM6DNX3Rp8xdd+t8f7JEkledn6fwheaovz1PdkHwNL8qW1WSzmvWEImryBmSxSFl2q9wOm9wOmxy29ExqCODUS3uQ/8Y3vqEDBw5o8eLFam5u1rnnnqtnn302MbS+qalJVuvxzVp62223ye/3a86cOfJ6vRo7dqyeffbZ43qGPAAAAMzBYrGoMNupohynvlbs0Te+UiTDkPZ5e7Rhr1cf7vFq/Z4OfdrSrb0dPdrb0aPXPt4vSfK47KqLX62vH5Kn887yKMuR/uH4wXBUezp6tLPNr13tfu1q82tn/PVwTz6wWaSseKh3O6zKctiUZY8tux02ZTn6Qn9ivcMmt713fd+2vdv3tmXZbbJl2GSKwJks7c+Rz2SZ/uxInnGJVKAfIRXoR0gF+hFO1tH6UFcgrI1N8WC/16uNe73qCSdPHWi3WnTuWcnD8QuynQNSbzhqqKmjRzvbYxP97WrrC+z7vD2KHuH/gxxnLFj7QxGFIqfmfxiX3aoh+VkaXZ6n0WUe1ZblqcqEIxqOhmMRUuG0fo48AAAAcKrkuuy68OxCXXh27OlH4UhUnzR368M9HYkr963dQX3U1KmPmjr1Yny/igJ3fDh+vuqH5KmiwH3MQ9gjUUNfdAaSrqj3XmXf09GjyBHSerbDpmEFsRn5Kwrdqhjk1rCC2Gu+256oIRw11BOKyB+KyB+Kyh+KJH3fE46/9m875PYHb9sTiqq3wkA4qm2tPm1r9emVj/ZJip1QqI2H+tFleRpV5tEgt+OE/vsAOHYEeQAAAJyR7Darzhvs0XmDPfrO2Ni99ns6eofjd2j9Hq+2tfq0Mx6+/7rxC0lSgduh+iF5qivP0/lD8lVTmqv2+D36vWG9N7jvafcreIQr5i67VcPiAX3YILcqCrJUUZCtYQVuFWU7jumEgd1qUa7LrlxX6v+0NwxDgXAs7HcHI/qspVsfNXVqY5NXm5o61R2M6N0d7Xp3R3tin4oCd+KK/eiyPI0oyZGdYflASjG0/ggyfTgNw36QCvQjpAL9CKlAP8LJGog+1OEP6aP4cPwNezq0aV/nEYP5oThsFg3Jjwf0eFjvDe6lHpdph6aHo4Y+a+nWxiavPtrr1UdNndrZ5j9ouyx77IRJLNh7VFuep+KcgbldIRU4FiEVGFoPAAAApEm+26HG4UVqHF4kKTYJ3f/s79L6+BX7D/d0qKMnLJslNiN+35X17ERgH+zJOi0nirNbLaopzVVNaa6uqy+XJLX7Q9rU1KmPmrza2OTVxvhV+w92d+iD3R2JfcvzXLFgH7/fvro0Vw7b8U1wDZzJCPIAAADAMXLaraorjw2rv+WC2NDz1u6gBrkdshNENcjt0MThhZo4PDYPQdQwtL3VF7tqHx+Sv63Fp73egPZ6m/V/tjRLkpw2i2pKPRpd7tHosjzVlnk0OC8rnR8FyGgEeQAAAOAEWSwWFefyiOPDsVosGlGcoxHFObp6dJmk2NMDNu3rjA/Jj7129IT1UZNXHzV5Je2RJJXmOlVblqezi7KVn2VXXpZdHpdDefHl2JdDLjsnUHDmIcgDAAAAOGVyXXaNqyzQuMoCSbFRDbvae+L32ceG43/a3KX9XUH9360t0tYjv5/Lbo2HfLvys+zyZCWHfY/LEW/vC/95Lrtys+xMwgfTIsgDAAAASBuLxaKKArcqCty6ctRZkiR/KKKP93VqY1On9nl71BkIq6MnrM6esLw9IXl7wuoMhBU1Yo/Fa+4KqrkreNw/O8dpO2T4LyvMUZbFUIHbqYJsh4qyY6+D3I7Tcr4DmA9BHgAAAEBGcTtsGjtskMYOG3TYbaKGIV8woo6ekDp7Dg763p6wvIGD2zoDYXUHI5Kk7mDssXryBo6pLoti8wAUZDtUmO1QYTzgF2Y7VZjtUEHi1aGiHKfcDlsK/jWAgxHkAQAAAJiO1WJRrsuuXJddyj++fcOR6Jeu8oflDYTk9ceCfkAW7WntVpsvqAO+kA74Qurwh2RIavOH1OYPaVvr0X9Olt0aC/w5ThW444E/Jx74e08I5MTCf34WV/tx7AjyAAAAAM4odptVBdlOFWQf/Dz7wz3/Oxw11OEP6UA83Lf5+i/3Bf7e5UA4qp5wND5D/7Fd8c922JTttCnHaVOOy65sp0258e+znfZYe3w519W7bFNOv3U5Lruy7FZZLJwUOJ0R5AEAAADgKOxWi4pynCrKOTj8f5lhGPKHoklBvzX+2hYP/P1PCPRe7feFIvKFImrpPrlarRYdHPCdduW4bMp2xMJ+X3u/df32yXXGTiQ4eSpARiLIAwAAAEAKWSwWZTttyna6NXSQ+6jbh6OGvD0h+YIRdQci6g6FY6/BiLqDYfmCEXUFI+oOxJYP2R6K7WtIihpSVyCirkDkpD+Lw2ZJhPvECAGX/eDRAC67chw25bj6Tg70ji7Iddnldti4dSCFCPIAAAAAkEZ2qyU+Yd7JvU/vSABfMBwL+MGIfMH+JwViJwBi7RF1JU4MhPutj+3jD0UlSaGIoXZ/SO3+0El/TrfDmhz8DzEqoP8JgJykWwj6tndx6wBBHgAAAABOB30jAWwqPsn3CkcN+Q8K+bGTArGRAH0nBLr7nSxIPokQO1kQjsYmG/CHovKHgid964DNakk+AeC0xW8bsCdGBOT2u5XAk2XXuMqC2MSIp4nT55MAAAAAAFLCbrXIk2WXJ+vkI2MwHO07IdDv1oH+owEOdetA4gRCoO+kgSEpEjUSjxOUjm0iwf91TpF+c/Wok/4smYIgDwAAAAAYME67VU67UwUneetA1DDkD0X65hI47C0EyScBesJRff28s1LzYTIEQR4AAAAAkPGslt6J9+wqyU13NenFswQAAAAAADARgjwAAAAAACZCkAcAAAAAwEQI8gAAAAAAmAhBHgAAAAAAEyHIAwAAAABgIgR5AAAAAABMhCAPAAAAAICJEOQBAAAAADARgjwAAAAAACZCkAcAAAAAwEQI8gAAAAAAmAhBHgAAAAAAEyHIAwAAAABgIgR5AAAAAABMhCAPAAAAAICJEOQBAAAAADARgjwAAAAAACZiT3cBmcxiSXcFR9ZbX6bXicxGP0Iq0I+QCvQjnCz6EFKBfoRUOJF+dFzbGoZhHF9JAAAAAAAgXRhaDwAAAACAiRDkAQAAAAAwEYI8AAAAAAAmQpAHAAAAAMBECPIAAAAAAJgIQR4AAAAAABMhyAMAAAAAYCIEeQAAAAAATIQgDwAAAACAiRDkAQAAAAAwEYK8if3xj3/UV7/6VY0ePVpTp07Vhg0b0l0STOTxxx9XTU1N0tcVV1yR7rKQ4d577z398Ic/VGNjo2pqavTWW28lrTcMQ4sWLVJjY6Pq6up066236vPPP09PschIR+tDs2fPPujYNGPGjDRVi0z19NNP67rrrlNDQ4PGjx+vO+64Q9u2bUvaJhAIaN68eRo3bpwaGhp05513qqWlJU0VI9McSx+65ZZbDjoezZkzJ00VIxMtX75cV111lcaMGaMxY8boxhtv1D//+c/E+oE8DhHkTeq1117TggULNHPmTL300ksaOXKkZsyYodbW1nSXBhP5yle+on//+9+Jr+XLl6e7JGQ4n8+nmpoazZ0795Drf//73+uFF17Q/fffrxUrVsjtdmvGjBkKBAKnuFJkqqP1IUmaNGlS0rHp0UcfPYUVwgzWrl2rm266SStWrNBzzz2ncDisGTNmyOfzJbZ56KGH9I9//EOPPfaYXnjhBe3fv18/+tGP0lg1Msmx9CFJuuGGG5KOR/fdd1+aKkYmGjx4sO6991795S9/0Z///GddeOGFmjlzprZu3SppgI9DBkzp+uuvN+bNm5f4PhKJGI2NjcbTTz+dxqpgJosXLza++c1vprsMmFh1dbXx5ptvJr6PRqPGxIkTjWeffTbR5vV6jdraWmP16tXpKBEZ7st9yDAMY9asWcbtt9+epopgVq2trUZ1dbWxdu1awzBix55Ro0YZr7/+emKbTz/91KiurjbWrVuXpiqRyb7chwzDMG6++WbjwQcfTGNVMKMLLrjAWLFixYAfh7gib0LBYFCbNm3ShAkTEm1Wq1UTJkzQunXr0lgZzGbHjh1qbGzUpZdeqnvuuUd79+5Nd0kwsd27d6u5uTnp2OTxeFRfX8+xCcdl7dq1Gj9+vC6//HLNnTtXbW1t6S4JGa6zs1OSlJ+fL0nauHGjQqFQ0vFoxIgRKi8v14cffpiOEpHhvtyHeq1atUrjxo3TlClT9Mgjj8jv96ejPJhAJBLRq6++Kp/Pp4aGhgE/DtlP+h1wyrW1tSkSiaioqCipvaio6KB7e4DDqaur04IFC1RVVaXm5mYtWbJEN910k1atWqXc3Nx0lwcTam5ulqRDHpu4LxXHatKkSfra176moUOHateuXXr00Ud122236U9/+pNsNlu6y0MGikajeuihhzRmzBhVV1dLklpaWuRwOJSXl5e0bVFRUeJYBfQ6VB+SpClTpqi8vFylpaXasmWLfvvb32r79u164okn0lgtMs2WLVv0rW99S4FAQNnZ2VqyZInOOeccbd68eUCPQwR54Ax18cUXJ5ZHjhyp+vp6XXLJJXr99dc1derUNFYG4Ex25ZVXJpZ7J5eaPHly4io98GXz5s3T1q1bmecFJ+xwfejGG29MLNfU1KikpES33nqrdu7cqYqKilNdJjJUVVWVXn75ZXV2dupvf/ubZs2apRdffHHAfy5D602ooKBANpvtoIntWltbVVxcnKaqYHZ5eXk6++yztXPnznSXApMqKSmRJI5NSKlhw4apoKBAO3bsSHcpyEDz58/X22+/rWXLlmnw4MGJ9uLiYoVCIXm93qTtW1tbE8cqQDp8HzqU+vp6SeJ4hCROp1OVlZWqra3VPffco5EjR+r5558f8OMQQd6EnE6nRo0apTVr1iTaotGo1qxZo4aGhjRWBjPr7u7Wrl27+AMHJ2zo0KEqKSlJOjZ1dXVp/fr1HJtwwvbt26f29naOTUhiGIbmz5+vN998U8uWLdOwYcOS1tfW1srhcCQdj7Zt26a9e/fq/PPPP8XVIhMdrQ8dyubNmyWJ4xGOKBqNKhgMDvhxiKH1JjV9+nTNmjVLtbW1qqur07Jly+T3+3XttdemuzSYxMMPP6xLLrlE5eXl2r9/vx5//HFZrVZNmTIl3aUhg3V3dyeN2ti9e7c2b96s/Px8lZeXa9q0aXrqqadUWVmpoUOHatGiRSotLdXkyZPTWDUyyZH6UH5+vp544gldfvnlKi4u1q5du/Sb3/xGlZWVmjRpUhqrRqaZN2+eVq9erSeffFI5OTmJ+009Ho+ysrLk8Xh03XXXaeHChcrPz1dubq4efPBBNTQ0EOQh6eh9aOfOnVq1apUuvvhiDRo0SFu2bNGCBQt0wQUXaOTIkWmuHpnikUce0UUXXaSysjJ1d3dr9erVWrt2rZYuXTrgxyGLYRjGyX8EpMOLL76opUuXqrm5Weeee65+8YtfJIb8AEdz11136b333lN7e7sKCws1duxY3XXXXdzzhSN69913NW3atIPar7nmGi1cuFCGYWjx4sVasWKFvF6vxo4dq7lz56qqqioN1SITHakP3X///Zo5c6Y+/vhjdXZ2qrS0VBMnTtSPf/xjbs9AkpqamkO2L1iwIHFRIxAIaOHChXr11VcVDAbV2NiouXPncjUVko7eh5qamvTTn/5UW7dulc/nU1lZmSZPnqw77riDSYGR8LOf/UzvvPOO9u/fL4/Ho5qaGt12222aOHGipIE9DhHkAQAAAAAwEe6RBwAAAADARAjyAAAAAACYCEEeAAAAAAATIcgDAAAAAGAiBHkAAAAAAEyEIA8AAAAAgIkQ5AEAAAAAMBGCPAAAAAAAJkKQBwAAaVdTU6O33nor3WUAAGAK9nQXAAAA0mv27Nl66aWXDmpvbGzU0qVL01ARAAA4EoI8AADQpEmTtGDBgqQ2p9OZpmoAAMCRMLQeAADI6XSqpKQk6Ss/P19SbNj78uXL9b3vfU91dXW69NJL9cYbbyTtv2XLFk2bNk11dXUaN26cfvnLX6q7uztpm5UrV+rKK69UbW2tGhsbNX/+/KT1bW1tmjlzpurr63XZZZfp73//+8B+aAAATIogDwAAjmrRokW6/PLL9corr+iqq67S3Xffrc8++0yS5PP5NGPGDOXn52vlypV67LHH9J///EcPPPBAYv/ly5dr/vz5uuGGG7Rq1So9+eSTqqioSPoZTzzxhL7+9a/rr3/9qy666CLde++9am9vP5UfEwAAUyDIAwAAvf3222poaEj6+t3vfpdYf8UVV2jq1KmqqqrST37yE9XW1uqFF16QJK1evVrBYFAPP/ywqqurNX78eM2ZM0evvPKKWlpaJElPPfWUpk+fru9+97uqqqpSXV2dbr311qQarrnmGk2ZMkWVlZW6++675fP5tGHDhlP2bwAAgFlwjzwAANC4ceN0//33J7X1Dq2XpIaGhqR1559/vjZv3ixJ+uyzz1RTU6Ps7OzE+jFjxigajWr79u2yWCzav3+/xo8ff8QaampqEsvZ2dnKzc3VgQMHTvQjAQBw2iLIAwAAud1uVVZWDsh7u1yuY9rO4XAkfW+xWBSNRgeiJAAATI2h9QAA4Kg+/PDDpO/Xr1+vESNGSJJGjBihLVu2yOfzJdZ/8MEHslqtqqqqUm5uroYMGaI1a9acypIBADhtEeQBAICCwaCam5uTvvoPa3/jjTe0cuVKbd++XYsXL9aGDRt08803S5KuuuoqOZ1OzZ49W5988oneeecdPfDAA7r66qtVXFwsSbrzzjv13HPP6fnnn9fnn3+uTZs2Je6xBwAAx4eh9QAAQP/617/U2NiY1FZVVZV4zNydd96p1157TfPmzVNJSYkeeeQRnXPOOZJiw/KXLl2qX/3qV7r++uvldrt12WWXafbs2Yn3uuaaaxQIBPSHP/xBv/71rzVo0CBdccUVp+4DAgBwGrEYhmGkuwgAAJC5ampqtGTJEk2ePDndpQAAADG0HgAAAAAAUyHIAwAAAABgIgytBwAAAADARLgiDwAAAACAiRDkAQAAAAAwEYI8AAAAAAAmQpAHAAAAAMBECPIAAAAAAJgIQR4AAAAAABMhyAMAAAAAYCIEeQAAAAAATOT/A8u/ERcyi3nqAAAAAElFTkSuQmCC"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Test loss: 0.40349453687667847\n",
|
||
"Test accuracy: 0.863095223903656\n",
|
||
"Classification Report: \n",
|
||
" precision recall f1-score support\n",
|
||
"\n",
|
||
" 0 0.84 0.90 0.87 4192\n",
|
||
" 1 0.90 0.82 0.86 4208\n",
|
||
"\n",
|
||
" accuracy 0.86 8400\n",
|
||
" macro avg 0.87 0.86 0.86 8400\n",
|
||
"weighted avg 0.87 0.86 0.86 8400\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Plot the training and validation accuracy over epochs\n",
|
||
"plt.plot(history.history['accuracy'], 'ro-', history.history['val_accuracy'], 'bv--')\n",
|
||
"plt.title('Training and Test Accuracy')\n",
|
||
"plt.xlabel('Epoch')\n",
|
||
"plt.ylabel('Accuracy')\n",
|
||
"plt.legend(['Training Accuracy', 'Test Accuracy'])\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Plot the training and validation loss over epochs\n",
|
||
"plt.figure(figsize=(12, 6))\n",
|
||
"plt.plot(history.history['loss'], label='Training Loss')\n",
|
||
"plt.plot(history.history['val_loss'], label='Validation Loss')\n",
|
||
"plt.title('Training and Validation Loss Over Time')\n",
|
||
"plt.xlabel('Epoch')\n",
|
||
"plt.ylabel('Loss')\n",
|
||
"plt.legend()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Print the testing loss and accuracy\n",
|
||
"print('Test loss:', scores[0])\n",
|
||
"print('Test accuracy:', scores[1])\n",
|
||
"\n",
|
||
"# Print the classification report\n",
|
||
"print('Classification Report: \\n', report)\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:44:19.380929Z",
|
||
"start_time": "2024-03-20T12:44:18.953819Z"
|
||
}
|
||
},
|
||
"id": "89aa08d7d1866179",
|
||
"execution_count": 130
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Visualize Weights and Biases\n",
|
||
"\n",
|
||
"This code block visualizes the weights and biases of the model. For each Dense layer in the model, the weights and biases are extracted and plotted as histograms. The weights are plotted in the left subplot, and the biases are plotted in the right subplot. The x-axis represents the value of the weights or biases, and the y-axis represents the frequency of occurrence of each value. The histograms show the distribution of the weights and biases in each layer."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "dba8a77d06dc51f8"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x500 with 2 Axes>",
|
||
"image/png": 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WrVvr0Ucfdel42dnZmjlzptOy8tvXXnut0yQQFRWl9957T7m5uWrcuLF69uyphx56qNK/B1CZ2NhYBQcHq06dOk5P+uWl5cwiU65Pnz5q2rSp5s2bpwULFqi4uFjNmjVTfHy8+vfvf97jvfDCCwoPD9cHH3ygtWvXKiEhQX/729/Us2dPhYaGVinz2SZOnKinn35aM2bM0C+//KJ+/frpueee0913363//Oc/+uijj2RZllq2bKlnnnmmwqeXAYA7MV95Zr6SpBkzZmjmzJmaPn26QkJClJKSovHjx593mxEjRqioqEgrV67UqlWr1LZtW82dO1fTp093Ws+dY1eVfaF2CbKq8m5bAH7t66+/Vt++ffWXv/xFt912m6/jAAAAuIT3tAC1TGWfxb9w4ULZbDanN/wDAAD4Cy4PQ62Sn5/v9PnwZ7voooucPjO+Npo/f7527Nih3/3udwoODtann36qTz/9VHfeeacuvfRSX8cDAIj5CnAVl4ehVklKStKPP/54zq9fe+21Wrx4sRcTed9//vMfvfzyy9qzZ49OnDihSy+9VLfffrtGjBhR4Q+pAQB8g/kKcA2lBbXKli1bdPLkyXN+vUGDBoqOjvZiIgAAKmK+AlxDaQEAAABgNN6IDwAAAMBolBYAAAAARqO0AAAAADCazz5KKC/vmEx5N01QkGS3X2JUJleQ37f8Ob8/Z5fIX93joXL++H3k748Bdwj0MeD8OX9/P/+qzk0+Ky2WJeMG18RMriC/b/lzfn/OLpEf7uHP94M/Z3eXQB8Dzp/zr+3nz+VhAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo7lUWl566SVFRkY6/evZs6ensgEAAsymTZs0YsQIJSYmKjIyUuvWrbvgNhs3blS/fv0UHR2tm266Se+9954XkgIAvCnE1Q1++9vfKj093XE7ODjYrYEAAIHrxIkTioyM1IABAzR69OgLrr9//34NHz5cd911l6ZNm6bMzEw99dRTatKkibp06eKFxAAAb3C5tAQHB6tJkyaeyAIACHBdu3ZV165dq7x+RkaGWrRooYkTJ0qSWrVqpS1btuiNN96gtABALeLye1p++OEHJSYm6sYbb9S4ceN04MABT+QCAOCCtm3bpuuvv95pWWJiorZt2+abQAAAj3DplZb27dsrLS1NV111lXJycjR79mwNHjxYK1euVP369V06cFCQS6t7VHmWqmay2YIU5MMTsCxLZWWW47ar+U1Dft/x5+wS+at7vNokNzdX4eHhTsvCw8NVWFioX375RXXq1KnyvvxxfPz9MeAOgT4G5ecdEmKTZZ1/XU85++cSb+L+d/7fH1U1u0ul5cyX7KOionTNNdeoW7duWr16tZKTk10KaLdf4tL63lDVTKVlloJtvvvuONfxTRxTV5Dfd/w5u0R+uIc/3w/+nN1dAnkMSsssNWpUz6fH9+XPRVJg3/9SYJy/y+9pOVODBg105ZVXat++fS5vm5d3zGe/EThbUNDpO7sqmYKDbWrcuJ4eztiq3YcLvRPwDK2b1tfMu2JVUHBcpaVlklzLbyLy+44/Z5fIX93j1Sbh4eHKzc11Wpabm6v69eu79CqLZNa8VFX+/hhwh0Afg5AQmxo1MuvnEm8K9Pu/Npx/VeemGpWW48ePa//+/dV6Y75lybjBdSXT7sOFyjpw1LOBLuDsrCaOqSvI7zv+nF0ifyDr0KGDPv30U6dlGzZsUIcOHVzelz/fD/6c3V0CdQzKz9nEn0u8fexAvP/LBcL5u/RG/BdeeEFffPGFsrOz9eWXX2r06NGy2Wzq3bu3p/IBAALI8ePH9fXXX+vrr7+WJGVnZ+vrr792fOjL9OnTNX78eMf6d911l/bv368XX3xRe/bs0dKlS7V69Wrdd999vogPAPAQl15p+emnn/SnP/1JR44cUVhYmDp27Khly5YpLCzMU/kAAAFkx44duvfeex2309LSJEn9+vXT1KlTlZOTo4MHDzq+fvnll2vu3LlKS0vTokWL1Lx5c02ePJmPOwaAWsal0vK3v/3NUzkAANB1112nXbt2nfPrU6dOrXSbFStWeDAVAMDXXP47LQAAAADgTZQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKPVqLTMmzdPkZGRmjJlirvyAAAC3NKlS5WUlKSYmBglJydr+/bt513/jTfeUI8ePdS+fXt17dpVzz//vE6ePOmltAAAb6h2adm+fbsyMjIUGRnpzjwAgAC2atUqpaWladSoUVq+fLmioqI0dOhQ5eXlVbr+ypUrNX36dI0ePVqrVq3SlClTtGrVKv31r3/1cnIAgCdVq7QcP35cjz32mCZPnqyGDRu6OxMAIEClp6dr4MCBGjBggFq3bq3U1FTVqVNH7777bqXrb926VXFxcerTp49atGihxMRE9e7d+4KvzgAA/EtIdTZ67rnn1LVrVyUkJOjVV1+t1oGDgqq1mSTJZgtSUE12cI4sISE2Wdb51w0ONudtQOW5z/7f35Dfd/w5u0T+6h7PVMXFxcrKytLw4cMdy2w2mxISErR169ZKt4mNjdX777+v7du3q3379tq/f7/Wr1+v22+/3eXjmz4+lfH3x4A7BPoYmHTevsjC/e/8vz+qanaXS8sHH3ygnTt36p133nF1Uyd2+yXV3ra0zFKwzf33TqNG9dy+T09p3Lhi1pqMqQnI7zv+nF0if21RUFCg0tJS2e12p+V2u1179+6tdJs+ffqooKBAgwYNkmVZKikp0V133aURI0a4fHx/vh/8Obu7MAa+VdnPJd4U6Pd/IJy/S6Xl4MGDmjJlil5//XVdfPHFNTpwXt6xC76qUZngYJsaN66nhzO2avfhwhplqI4bIpvosR5RXj/u2QoKjqu0tEzS6YZqt19S7TH1NfL7jj9nl8hf3ePVJhs3btTcuXP1zDPPqH379tq3b5+mTJmi2bNna9SoUS7tyx+/j/z9MeAOgT4GISE2I37peubPJd4U6Pd/bTj/qs5NLpWWrKws5eXlqX///o5lpaWl2rRpk5YuXar//ve/Cg4OrtK+LEs1GtzdhwuVdeBo9XdQTa2a+P6JodzZ41fTMfU18vuOP2eXyF9bNG7cWMHBwRXedJ+Xl6fw8PBKt5k5c6Zuu+02JScnS5IiIyN14sQJPf300xo5cqRstqpf0uvP94M/Z3eXQB0Dk87Zl1kC9f4vFwjn71Jp+d3vfqeVK1c6LXv88cd19dVX64EHHqhyYQEA4GyhoaFq166dMjMz1b17d0lSWVmZMjMzlZKSUuk2v/zyS4ViUj4XWbV9BgeAAOJSaalfv74iIiKcltWtW1eNGjWqsBwAAFcNGTJEEyZMUHR0tNq3b6+FCxeqqKjI8Qr/+PHj1axZM40bN06S1K1bN6Wnp6tt27aOy8Nmzpypbt268Ys0AKhFqvXpYQAAeEKvXr2Un5+vWbNmKScnR23atNH8+fMdl4cdPHjQ6ZWVkSNHKigoSDNmzNChQ4cUFhambt266ZFHHvHVKQAAPKDGpWXx4sXuyAEAgCQpJSXlnJeDnT3nhISEaPTo0Ro9erQ3ogEAfMScPzoCAAAAAJWgtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKO5VFrefPNN9enTR3FxcYqLi9Odd96p9evXeyobACAALV26VElJSYqJiVFycrK2b99+3vWPHj2q1NRUJSYmKjo6Wj169GBuAoBaJsSVlZs3b65HH31UV1xxhSzL0ooVKzRq1CgtX75cv/3tbz2VEQAQIFatWqW0tDSlpqbqmmuu0cKFCzV06FCtWbNGdru9wvrFxcUaMmSI7Ha7Zs6cqWbNmunAgQNq0KCBD9IDADzFpdKSlJTkdPuRRx7RW2+9pW3btlFaAAA1lp6eroEDB2rAgAGSpNTUVH3yySd69913NWzYsArrv/vuu/r555+VkZGhiy66SJLUokULr2YGAHieS6XlTKWlpVqzZo1OnDih2NhYl7cPCqrukVGufAzP/t/fkN93qpPdZgtSkA9P1rIslZVZknwz9u48//LdhITYZFlV2+bM86/u8UxVXFysrKwsDR8+3LHMZrMpISFBW7durXSbf/3rX+rQoYOee+45ffzxxwoLC1Pv3r31wAMPKDg42KXjmz4+lfHn5x93CfQxMOm8fZGF+9/5f39U1ewul5Zdu3bprrvu0smTJ1W3bl3Nnj1brVu3dnU3stsvcXkb/Kpx43oVlvn7mJLfd1zJXlpmKdjmu2fHyo7vzbH3xPk3alTx8ezN45uioKBApaWlFS4Ds9vt2rt3b6Xb7N+/X59//rn69OmjefPmad++fUpNTVVJSYlGjx7t0vED5TFcWzEGvlXZzyXeFOj3fyCcv8ul5aqrrtKKFSt07Ngxffjhh5owYYKWLFnicnHJyztW5d8snik42ObzB4YJCgqOq7S0TNLphmq3X1LtMfU18vuOq9nLH38PZ2zV7sOFng94ltZN62vmXbGO739vj71p5++q8vGqTSzLkt1u16RJkxQcHKzo6GgdOnRICxYscLm0BMJjuDYK9DEICbG59IsPT6nu81JNBfr9XxvOv6pzk8ulJTQ0VFdccYUkKTo6Wv/973+1aNEiPffccy7tx7Lkt4NrirPHz9/HlPy+42r23YcLlXXgqOcCVcGZeb099qadf23RuHFjBQcHKy8vz2l5Xl6ewsPDK92mSZMmCgkJcboU7Oqrr1ZOTo6Ki4sVGhpa5eMH0mO4NgrUMTDpnH2ZJVDv/3KBcP41/jstZWVlKi4udkcWAEAACw0NVbt27ZSZmelYVlZWpszMzHO+dzIuLk779u1TWdmvv+H9/vvv1aRJE5cKCwDAbC6VlunTp2vTpk3Kzs7Wrl27NH36dH3xxRfq06ePp/IBAALIkCFDtGzZMi1fvlx79uzRs88+q6KiIvXv31+SNH78eE2fPt2x/t13360jR45oypQp+u677/TJJ59o7ty5Gjx4sK9OAQDgAS5dHpaXl6cJEybo8OHDuuSSSxQZGakFCxaoc+fOnsoHAAggvXr1Un5+vmbNmqWcnBy1adNG8+fPd1wedvDgQdlsv/6+7dJLL9WCBQuUlpam2267Tc2aNdO9996rBx54wFenAADwAJdKy/PPP++pHAAASJJSUlKUkpJS6dcWL15cYVlsbKyWLVvm6VgAAB+q8XtaAAAAAMCTKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBoLpWWuXPnasCAAYqNjdX111+vBx98UHv37vVUNgBAgFq6dKmSkpIUExOj5ORkbd++vUrbffDBB4qMjNSDDz7o4YQAAG9yqbR88cUXGjx4sJYtW6b09HSVlJRo6NChOnHihKfyAQACzKpVq5SWlqZRo0Zp+fLlioqK0tChQ5WXl3fe7bKzs/XCCy8oPj7eS0kBAN7iUmlZsGCB+vfvr9/+9reKiorS1KlTdeDAAWVlZXkqHwAgwKSnp2vgwIEaMGCAWrdurdTUVNWpU0fvvvvuObcpLS3Vo48+qjFjxujyyy/3YloAgDfU6D0tx44dkyQ1bNjQLWEAAIGtuLhYWVlZSkhIcCyz2WxKSEjQ1q1bz7nd7NmzZbfblZyc7I2YAAAvC6nuhmVlZXr++ecVFxeniIgIl7cPCqrukVGufAzP/t/fkN93/D27P+evqeqcsz+MU0FBgUpLS2W3252W2+32c76HcvPmzXrnnXe0YsWKGh3bH8bnbIH8GCgX6GNg0nn7Igv3v/P//qiq2atdWlJTU/W///1Pb775ZrW2t9svqe6hIalx43oVlvn7mJLfd/wt+9nf//6Wv6Yqe/wHqsLCQo0fP16TJk1SWFhYjfblz99H/pzdXRgD3/L181Kg3/+BcP7VKi3PPfecPvnkEy1ZskTNmzev1oHz8o7JslzfLjjY5vMHhgkKCo6rtLRM0umGardfUu0x9TXy+46r2U15/JV//3t77E07f1eVj5fJGjdurODg4Apvus/Ly1N4eHiF9ffv368ff/xRI0eOdCwrKzs9Nm3bttWaNWvUsmXLKh07EB7DtVGgj0FIiE2NGvnv81JNBfr9XxvOv6pzk0ulxbIsTZo0SWvXrtXixYtr9GZHy5LfDq4pzh4/fx9T8vuOP2Y/M68/5q+p2nq+oaGhateunTIzM9W9e3dJp0tIZmamUlJSKqx/9dVXa+XKlU7LZsyYoePHj+vJJ5906Rdr/vx95M/Z3SVQx8Ckc/ZllkC9/8sFwvm7VFpSU1P1z3/+U6+88orq1aunnJwcSdIll1yiOnXqeCQgACCwDBkyRBMmTFB0dLTat2+vhQsXqqioSP3795ckjR8/Xs2aNdO4ceN08cUXV3hfZYMGDSSpWu+3BACYyaXS8tZbb0mS7rnnHqflaWlpjskEAICa6NWrl/Lz8zVr1izl5OSoTZs2mj9/vuPysIMHD8pmq9GHXwIA/IxLpWXXrl2eygEAgENKSkqll4NJ0uLFi8+77dSpUz0RCQDgQ/yqCgAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARnO5tGzatEkjRoxQYmKiIiMjtW7dOk/kAgAEsKVLlyopKUkxMTFKTk7W9u3bz7nusmXLNGjQIHXq1EmdOnXSfffdd971AQD+x+XScuLECUVGRuqZZ57xRB4AQIBbtWqV0tLSNGrUKC1fvlxRUVEaOnSo8vLyKl1/48aNuvXWW7Vo0SJlZGTo0ksv1R//+EcdOnTIy8kBAJ4S4uoGXbt2VdeuXT2RBQAApaena+DAgRowYIAkKTU1VZ988oneffddDRs2rML606dPd7o9efJkffjhh8rMzFTfvn29ERkA4GEulxZ3CQry1ZFrj/IxPPt/f0N+3/HX7MHBp18kLs8dEmKTZXnvuCaozn3mD/dzcXGxsrKyNHz4cMcym82mhIQEbd26tUr7KCoqUklJiRo2bOjSsf1hfM7mr49hdwr0MTDpvH2Rhfvf+X9/VNXsPistdvslvjp0rdC4cb0Ky/x9TMnvO/6SvUn9i1VaZqlBg/9zWt6oUcXHQ21W2eO/tigoKFBpaansdrvTcrvdrr1791ZpH9OmTVPTpk2VkJDg0rH95XFQGX/O7i6MgW/5+nkp0O//QDh/n5WWvLxj1frNaHCwzecPDBMUFBxXaWmZpNMN1W6/pNpj6mvk9x1Xs/v68dfg/0IUbAvSwxlbtftwodePf0NkEz3WI8rrxz3bmY9/V5Tf37XZvHnztGrVKi1atEgXX3yxS9sGwmO4Ngr0MQgJsRnxi5vqPi/VVKDf/7Xh/Ks6N/mstFiW/HZwTXH2+Pn7mJLfd/wt++7Dhco6cNTrx23VxPc/GJTzp/vLFY0bN1ZwcHCFN93n5eUpPDz8vNsuWLBA8+bNU3p6uqKiXC+X/vY4OJM/Z3eXQB0Dk87Zl1kC9f4vFwjnb84F2gCAgBcaGqp27dopMzPTsaysrEyZmZmKjY0953avvfaaXnnlFc2fP18xMTHeiAoA8CKXX2k5fvy49u3b57idnZ2tr7/+Wg0bNtRll13m1nAAgMAzZMgQTZgwQdHR0Wrfvr0WLlyooqIi9e/fX5I0fvx4NWvWTOPGjZN0+pKwWbNmafr06frNb36jnJwcSVLdunVVr545r44BAKrP5dKyY8cO3XvvvY7baWlpkqR+/fpp6tSp7ksGAAhIvXr1Un5+vmbNmqWcnBy1adNG8+fPd1wedvDgQdlsv14okJGRoVOnTumhhx5y2s/o0aM1ZswYr2YHAHiGy6Xluuuu065duzyRBQAASVJKSopSUlIq/drixYudbv/rX//yRiQAgA/xnhYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNEoLQAAAACMRmkBAAAAYDRKCwAAAACjUVoAAAAAGI3SAgAAAMBolBYAAAAARqO0AAAAADAapQUAAACA0SgtAAAAAIxGaQEAAABgNEoLAAAAAKNRWgAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1WrtCxdulRJSUmKiYlRcnKytm/f7u5cAIAA5uo8s3r1avXs2VMxMTHq06eP1q9f76WkAABvcLm0rFq1SmlpaRo1apSWL1+uqKgoDR06VHl5eZ7IBwAIMK7OM19++aXGjRunO+64QytWrNCNN96oUaNG6dtvv/VycgCAp7hcWtLT0zVw4EANGDBArVu3VmpqqurUqaN3333XE/kAAAHG1Xlm0aJF6tKli+6//361atVKY8eOVdu2bbVkyRIvJwcAeEqIKysXFxcrKytLw4cPdyyz2WxKSEjQ1q1bXTqwzSZZlkubOGl3WQP9X2hw9XdQTa2a1Pfp8a8OrydJCg7+tW8GBZ3+PyTEVqMxrSrL+vWY7uBqfncf31VnH9+fx9/V7OXfd4H6+PP18csf/9Lp51BX+fJxU1XVmWe2bdum++67z2lZYmKi1q1b59KxazIvBQUFKcgHA1x+yDPnBF/w5fOyt5+DK+PL8w8J8e3zcmU/l3hToD8GzDl/S1Y1H4BVHTeXSktBQYFKS0tlt9udltvtdu3du9eVXSks7BKX1j/bi3dcU6Pta8rXx2/Q4P8qLGvUqF4la/oP8vuOq9l9/f0f6Mdv3Nh/v9cupDrzTG5ursLDwyusn5ub69Kxazov+VJt/p6oKn9+DnYHXz8vVfZziTcF+mMgEM6fTw8DAAAAYDSXSkvjxo0VHBxc4c2QeXl5FX7LBQCAq6ozz4SHh1d4VYV5CQBqF5dKS2hoqNq1a6fMzEzHsrKyMmVmZio2Ntbt4QAAgaU680yHDh30+eefOy3bsGGDOnTo4MmoAAAvcvnysCFDhmjZsmVavny59uzZo2effVZFRUXq37+/J/IBAALMheaZ8ePHa/r06Y717733Xn322Wd6/fXXtWfPHr300kvasWOHUlJSfHUKAAA3c+mN+JLUq1cv5efna9asWcrJyVGbNm00f/58XoYHALjFheaZgwcPynbGx6fFxcVp2rRpmjFjhv7617/qyiuv1OzZsxUREeGrUwAAuFmQVd3PJwMAAAAAL+DTwwAAAAAYjdICAAAAwGiUFgAAAABGo7QAAAAAMFrAlpYjR45o3LhxiouLU3x8vJ544gkdP378vOtPmjRJPXr0UPv27XXDDTdo8uTJOnbsmBdTO+dxJb8kvf3227rnnnsUFxenyMhIHT161EtppaVLlyopKUkxMTFKTk7W9u3bz7v+6tWr1bNnT8XExKhPnz5av369l5JW5Er2//3vfxozZoySkpIUGRmpN954w3tBz8GV/MuWLdOgQYPUqVMnderUSffdd98F7ytPcyX/Rx99pP79+ys+Pl4dOnTQ7bffrhUrVngvbCVc/d4v98EHHygyMlIPPvighxPC31Tn+b+cZVm6//77FRkZqXXr1nk4qWf4+/xdHf48h7qDv89jNcU8clrAlpZHH31Uu3fvVnp6uubMmaPNmzfr6aefPuf6hw8f1uHDhzVhwgT985//VFpamj777DM9+eSTXkz9K1fzS1JRUZG6dOmiESNGeCnlaatWrVJaWppGjRql5cuXKyoqSkOHDq3wF6/Lffnllxo3bpzuuOMOrVixQjfeeKNGjRqlb7/91qu5JdezFxUVqUWLFho3bpyaNGni5bQVuZp/48aNuvXWW7Vo0SJlZGTo0ksv1R//+EcdOnTIy8lPczV/w4YNNXLkSL399tt6//331b9/fz3xxBP67LPPvJz8NFfzl8vOztYLL7yg+Ph4LyWFP6nO83+5hQsXKigoyMMJPcvf529X+fMc6g7+Po/VFPPIGawAtHv3bisiIsLavn27Y9n69eutyMhI66effqryflatWmW1a9fOOnXqlCdinlNN83/++edWRESE9fPPP3sypsMdd9xhpaamOm6XlpZaiYmJ1ty5cytd/+GHH7aGDRvmtCw5Odn685//7NGclXE1+5m6detmpaenezDdhdUkv2VZVklJiRUbG2stX77cQwnPr6b5Lcuy+vbta/3tb3/zQLoLq07+kpIS684777SWLVtmTZgwwRo5cqQ3osJP1OT5f+fOnVaXLl2sw4cPWxEREdbatWs9Hdft/H3+rg5/nkPdwd/nsZpiHvlVQL7SsnXrVjVo0EAxMTGOZQkJCbLZbC69hFhYWKj69esrJMTlv9FZI+7K7w3FxcXKyspSQkKCY5nNZlNCQoK2bt1a6Tbbtm3T9ddf77QsMTFR27Zt82TUCqqT3STuyF9UVKSSkhI1bNjQUzHPqab5LctSZmamvvvuO3Xq1MmTUStV3fyzZ8+W3W5XcnKyN2LCz1T3+b+oqEjjxo3T008/bcSrwNXl7/O3q/x5DnUHf5/Haop5xJnZj1YPyc3NVVhYmNOykJAQNWzYUDk5OVXaR35+vl555RXdeeednoh4Xu7I7y0FBQUqLS2V3W53Wm6327V3795Kt8nNzXX85esz18/NzfVYzspUJ7tJ3JF/2rRpatq0qdMTprdUN/+xY8f0+9//XsXFxbLZbHrmmWfUuXNnT8etoDr5N2/erHfeecfn78OBuar7/J+WlqbY2Fh1797d0xE9yt/nb1f58xzqDv4+j9UU84izWlVapk2bptdee+2866xatarGxyksLNTw4cPVqlUrjR49usb7K+et/EBVzJs3T6tWrdKiRYt08cUX+zpOldWrV08rVqzQiRMnlJmZqalTp+ryyy/Xdddd5+to51VYWKjx48dr0qRJFX4oQ+3nyef/jz/+WJ9//rmWL19ere29wd/nb5jJX+ex6qrt80itKi1//OMf1a9fv/Ouc/nllys8PFz5+flOy0tKSvTzzz9f8GXzwsJC3X///apXr55mz56tiy66qMa5y3kjv7c1btxYwcHBFd4wlpeXV+E3QeXCw8Mr/EbofOt7SnWym6Qm+RcsWKB58+YpPT1dUVFRnox5TtXNb7PZdMUVV0iS2rRpoz179mjevHleLy2u5t+/f79+/PFHjRw50rGsrKxMktS2bVutWbNGLVu29Gxo+Iwnn/8///xz7du3r8JlkmPGjFF8fLwWL15cs/Bu4O/zt6f48xzqDv4+j9UU84izWlVawsLCqtQsY2NjdfToUe3YsUPR0dGSTj+pl5WVqX379ufcrrCwUEOHDlVoaKheffVVt7d2T+f3hdDQULVr106ZmZmOyxLKysqUmZmplJSUSrfp0KGDPv/8c913332OZRs2bFCHDh28kPhX1clukurmf+211zRnzhwtWLDA6bpxb3PX+JeVlam4uNhTMc/J1fxXX321Vq5c6bRsxowZOn78uJ588kk1b97cK7nhG558/h82bFiFa9v79Omjxx9/XN26dat5eDfw9/nbU/x5DnUHf5/Haop55Cy+/iQAXxk6dKjVt29f66uvvrI2b95s3Xzzzdaf/vQnx9d/+uknq0ePHtZXX31lWZZlHTt2zEpOTrZ69+5t/fDDD9bhw4cd/0pKSozPb1mWdfjwYWvnzp3WsmXLrIiICGvTpk3Wzp07rYKCAo9m/eCDD6zo6Gjrvffes3bv3m39+c9/tuLj462cnBzLsizrscces6ZNm+ZYf8uWLVbbtm2tBQsWWLt377ZmzZpltWvXztq1a5dHc7oj+8mTJ62dO3daO3futDp37mxNnTrV2rlzp/X99997PXt18s+dO9dq166dtWbNGqfv8cLCQr/IP2fOHOvf//63tW/fPmv37t3WggULrLZt21rLli3zi/xnq02f+gL3qc7z/9n89dPDLMv/529X+fMc6g7+Po/VFPPIr2rVKy2umDZtmiZNmqQ//OEPstlsuvnmm/XUU085vn7q1Cl99913KioqkiRlZWXpq6++kiTddNNNTvv6+OOP1aJFC++Fl+v5JSkjI0Mvv/yy4/bgwYMlnX6DZv/+/T2WtVevXsrPz9esWbOUk5OjNm3aaP78+Y6XNg8ePCib7dcPsouLi9O0adM0Y8YM/fWvf9WVV16p2bNnKyIiwmMZ3ZX98OHD6tu3r+P266+/rtdff13XXnutTy7BcDV/RkaGTp06pYceeshpP6NHj9aYMWO8ml1yPf+JEyeUmpqqn376SXXq1NHVV1+tv/zlL+rVq5fXs1cnP1AV1Xn+r038ff52lT/Poe7g7/NYTTGP/CrIsizL1yEAAAAA4FwCo5oBAAAA8FuUFgAAAABGo7QAAAAAMBqlBQAAAIDRKC0AAAAAjEZpAQAAAGA0SgsAAAAAo1FaAAAAABiN0gIAAADAaJQWAAAAAEajtAAAAAAwGqUFAAAAgNH+HyOlfY8vVjvhAAAAAElFTkSuQmCC"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Visualize Weights and Biases\n",
|
||
"for layer in model.layers:\n",
|
||
" if 'dense' in layer.name:\n",
|
||
" weights, biases = layer.get_weights()\n",
|
||
" plt.figure(figsize=(10, 5))\n",
|
||
" plt.subplot(1, 2, 1)\n",
|
||
" plt.hist(weights.flatten())\n",
|
||
" plt.title(f'{layer.name} weights')\n",
|
||
" plt.subplot(1, 2, 2)\n",
|
||
" plt.hist(biases.flatten())\n",
|
||
" plt.title(f'{layer.name} biases')\n",
|
||
" plt.show()\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:44:19.992940Z",
|
||
"start_time": "2024-03-20T12:44:19.381949Z"
|
||
}
|
||
},
|
||
"id": "9739272beb4981b6",
|
||
"execution_count": 131
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"\n",
|
||
"# Confusion Matrix\n",
|
||
"\n",
|
||
"This code block plots the confusion matrix for the model's predictions on the testing set. The confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known. The confusion matrix shows the number of true positive, true negative, false positive, and false negative predictions made by the model."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "7f3da1aa73d186e1"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 500x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Confusion Matrix\n",
|
||
"cm = confusion_matrix(y_test, y_pred_classes)\n",
|
||
"plt.figure(figsize=(5, 5))\n",
|
||
"sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')\n",
|
||
"plt.title('Confusion matrix')\n",
|
||
"plt.xlabel('Predicted class')\n",
|
||
"plt.ylabel('True class')\n",
|
||
"plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:44:20.152983Z",
|
||
"start_time": "2024-03-20T12:44:19.994211Z"
|
||
}
|
||
},
|
||
"id": "92964bc26d5c26cc",
|
||
"execution_count": 132
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"\n",
|
||
"# ROC Curve\n",
|
||
"\n",
|
||
"This code block plots the Receiver Operating Characteristic (ROC) curve for the model's predictions on the testing set. The ROC curve is a graphical plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. The curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings. The area under the ROC curve (AUC) is also calculated and printed."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "2d90420f6a5cc744"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 640x480 with 1 Axes>",
|
||
"image/png": 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UColEgrp162Lnzp149+5druX/e5qpZcuWePToEY4fP55ruQ/fztu0aYO4uDjs2rUr1zLZ2dnc1U/5cXZ2hqurK44ePYqjR4/Czs5OrSgRCoVo1aoVjh07lucv6q+ZjqF27dpo2LAh9u3bp3ap/gdLlixBVFQUfvzxx1zf1E+cOKE2PuPu3bu4c+cOmjRpAgAafc6fk9dN9LZu3QqlUqnWZmxsDODrT5f9V/Xq1WFlZYVdu3ZBoVBw7YcOHUJqauoX1y9Xrhy6du2K8+fPY+vWrbleV6lU+N///oe3b99qlOvDZ/LpacK9e/cW+TZ8fX1hamqKtWvXQiqVqr3233WNjY3z/Oy/9ucjL0qlMte+JBIJypQpo3ZJfn6ZPmVjY4M6depg79693OnQD4qqd5CUbNQjREq8gQMH4ueff8a+ffvQo0cPTJs2DT179kT79u3RrVs3VKhQAQkJCbh9+zbevn2LgwcPcusdO3YMP//8M7p06QJPT0+kpqbi1KlTmDFjBtzd3fHtt98iLCwM06ZNw5UrV1C7dm0olUo8f/4c4eHhWL9+/RenUAgMDERISAgMDQ3x3Xff5To1MnbsWFy5cgXdunVD165d4eLigtTUVNy/fx+XLl3C1atXC/3ZLFiwAP3798fQoUPRrl07+Pj4QCaTISIiAlevXkVgYCAGDhyYa72KFSuiR48e6NGjB2QyGbZs2QIrKyv8+OOP3DIF/Zw/p1mzZjhw4ADMzMzg4uKC27dv4+LFi7CyslJbzsPDA0KhEH/88QfS0tJgYGCA+vXrQyKRFPqzMTAwwIgRIzBr1iz069cPbdq0QWxsLPbt21fg06eTJk1CTEwMZs+ejYiICPj5+cHCwgJv3rxBeHg4nj9/rtYDWBCNGjWCWCzGkCFD0L17d2RkZGD37t2QSCSIj48v0m2YmZkhODgYv/zyC7777ju0a9cOFhYWePToEbKzs7FgwQIAgKenJ44ePYp58+ahRo0aMDExgb+/f5H8fHwqIyMDTZs2RatWreDu7g4TExNcvHgR//zzj1rPYX6Z8vLLL7+gR48e6NSpE77//nuUL18esbGxOHPmDA4cOKBRPlL6UCFESryWLVuiYsWK+N///odu3brBxcUFe/fuxYoVK7B//36kpKTAxsYG1apVw7Bhw7j1TE1NsW3bNixfvhzHjx/H/v37IZFI0KBBA26Qr0AgwMqVK7Fp0yYcOHAAx48fh7GxMcqXL48+ffpw92z5nMDAQCxduhRZWVlo06ZNrtdtbW2xe/durFy5EsePH8f27dthZWUFFxcXjBs37qs+mzJlymD37t3cXGMREREQCoVwc3PD/Pnz0bFjxzxPMXTs2BECgQCbN29GYmIivLy88Ouvv6JMmTLcMgX9nD9nypQpEAgEOHToEKRSKWrXro2NGzeqFVwAYGdnhxkzZmDt2rWYMmUKlEoltmzZ8lWFEAD07t0bLMti48aNWLBgAdzd3bF69WrMnj27QHcnNjY2xh9//IF9+/YhNDQUq1atQnZ2NjfX2KJFizSeB69KlSoICQnB0qVLsWDBAtja2qJHjx6wsbHB5MmTi3wbXbt2hUQiwbp167Bq1SqIRCJUqVJF7f5VPXv2xMOHD7Fv3z5s2rQJjo6O8Pf3L5Kfj08ZGRmhR48euHDhAiIiIsCyLCpWrMgV3l/KlBd3d3fs2rULy5Ytw/bt2yGVSuHg4JDnzyPRPwxLfYOEkH+9evUKAQEBmDBhQp49RfpApVKhQYMGaNGiBWbPns13HEJIMaMxQoQQvSWVSnONEwkNDUVKSgrq1q3LUypCiDbRqTFCiN66ffs25s2bh9atW8PKygoPHjzAnj174OrqitatW/MdjxCiBVQIEUL0lqOjI8qWLYutW7ciNTUVlpaW+PbbbzFu3DheZ7UnhGgPjREihBBCiN6iMUKEEEII0VtUCBFCCCFEb1EhRAghhBC9RYUQIYQQQvSW3l41lpSUhiKagJkUEsMAEok5EhPTQEP2+UfHQ3fQsdAddCx0h0AA2NiYF/l29bYQYlnQP2odQcdCt9Dx0B10LHQHHQv+FdfnT6fGCCGEEKK3qBAihBBCiN6iQogQQggheosKIUIIIYToLSqECCGEEKK3qBAihBBCiN6iQogQQggheosKIUIIIYToLSqECCGEEKK3qBAihBBCiN7itRC6du0ahgwZAl9fX7i5ueHEiRNfXOfKlSvo1KkTqlevjhYtWmDfvn1aSEoIIYSQ0ojXQigzMxNubm6YNm1agZaPiYnB4MGDUa9ePRw4cAD9+vXDL7/8gnPnzhVzUkIIIYSURrxOutq0aVM0bdq0wMvv2LED5cuXx6RJkwAAzs7OuHHjBjZt2oTGjRsXV0xCCCGElFIlavb527dvo0GDBmptvr6+mDt3Lk+JCCGEED3EsmCy48Eos8EosiDIiIFAmgRB5mtAaAiwqn//UwKsEgyrgiDtBRhFBlhDGwDsv6+zAHL+z3xoA/vJ6yxUShaP46wgGbGhyN9KiSqEEhISYGtrq9Zma2uL9PR0ZGdnw8jIqMDbYpic/wh/Pnz+dBx0Ax0P3UHHQnfoxLFQKcFIE8AoZYAyG8LMWADMfwoNFQAVGPbf4kElhzD1EVixBRiVHOI3Z6AyrQCDF3vAGkkgTH8JFVeMsDn7+LQg+aQQ+bisCgyr0urbf/PeDAN2dsSt+EqIG1H02y9RhVBRsrEx5zsC+ZdEQsdCl9Dx0B10LHSHRsdCkQ1kJQBprwB5BiB7DyQ9BkRGQOw5wMQeHwsNFaBSIqcI+fdxylMg/Q1gURF4fbFo30h6OgBAIE0q2u0WkwP33PDj7g5IyDCFuXnxlCwlqhCytbVFQkKCWltCQgLMzMw06g0CgKSkNKi0W9SSTzBMzi+XxMQ07ksJ4Q8dD91Bx0ILVEpAJQMjT8spClgloFKAYRWASgFBZizAiGAYcxiGmS8gV4m4ZcAqIZClQJj2AipDyX9O/yjBKDKLLmP6q6LbVh6UZk6AQAQWDMAIADA5/zF5PAcDlvlwfVVOmzD1CZQ2XlCalodAlgKlSXmwhtZQmZTN+VwYAcAIAUaYsy4jAKNSQGnqADCif7cjyLVPFgAYARISZeg1NQIZmUoAQBlbzf7OF1SJKoRq1aqFv//+W63t4sWLqFWrlsbbYv/TI0j4RcdCt9Dx0B10LNQx0mQIMt+AUclyxqKoZGBUCoBVAColxAnXIUx7DlZsAYAFVHIIMl9DnHQHCks3MCoZhGkvCrVvcT7tAmliod9PQbACMcAIwSizIXVsBdbAEowsBazIDEoL53+LjQ8FhwAs/n0OgFFmQ2HlAQgNwAqMoDSrCJWxPSA2K9bMRcXaHJg1W4ExY46jTRtnLFvWqlj2w2shlJGRgejoaO75q1ev8PDhQ1haWsLBwQG///474uLisHDhQgBA9+7dsW3bNixcuBBdunTB5cuXERYWhrVr1/L1FgghhHyJSgFGmgSBNAmi5HtgpMkAVDlFjEoBcdx5KM0rgfkw3uXfU0UMqwQjTYb43SUIZClfFUGU+rgo3gkA/Nu7IeQKFKVxWbAGlgAjAisQAYwAoqR/IK3UCYKMWMgd/AGwYIUmUJpXARgGKhNHsAIhgP8WMsx/ti2CyrgsIBAWWW5dp1SqoFCoYGj4sTTp1as6HBzM4efnBKGweAZq8VoI3bt3D3379uWez5s3DwDQqVMnzJ8/H/Hx8Xjz5g33eoUKFbB27VrMmzcPW7ZsQdmyZTF79my6dJ4QQvikkkOQEQNh5hsw0mQI06PAKLMhSrwFw+hDfKfjqAyswAqNwLBKCLLjIbNvDAjEECXdhrRCO+Df3pcPxYwwPRoKuzowtTBHYplvoRJbcgULKVqxsWkYPjwM7u62mDfPn2tnGAb+/pWKdd8My+pnx2tiIo0R4hvDALa25khIoHEQuoCOh+7Q1rFg5Gk5Y2TSXoJh5TkFjTQZgqy3YAUGYFRyiJLugBUaQ5RyH1BkgzUwh0HchX+vOuJn0G2W60CwQkMIM15BblsHrMjo3yImZ9yJwtoDKhMHsIwYEIhyxsGICzfwnH4uit+BA48xbtwJpKZKAQB//dURzZtXybWcQFA8FxCUqDFChBCid1gWjPz9v4N0Vf+ePlICrAKCzLdgVHJAJYMo5QFEyfegMrD8d9xMzsBecfxlsCIzsCJTCDJfQ5QWCZWhzVcXMIVZX+rUEYw0GUozJyhsvwErtsjpfRGIATBQmZQF++8ppw9jXsAIwDJCqEwccu5PQ0qNtDQpJk8+jZ07H3Btjo7mMDMz0GoOKoQIIYRPrAqMLAWMPA3CtCgIUx7C6PkOICMKElkGGJW0yHdZlL04Cks3QGAAUfI/kNv6QG5XF6zIBKyhJGdwrlEZKK3cc8bQEPKva9deY+jQMLx8mcq1dezohoULA2BlVTxXh+WHCiFCCCkOLAtB1hsI30eCkb0Ho5LC4FU4RIm3IEp9DKVxOQiz3nx2E8UxEoVlhGBYJZTmlSFMewGFlQcY2XtInTrknD5iRGDk6VCZOkJlZJdz1RIApYUzWJEJVCaOgMCAxsmQQlEoVFiy5AoWL74MpTLnXKOZmQHmz/dH164eYHj4d0WFECGEaEqlhCDzFTe1AKOUQpD5GsLM1zB6thWC7PgvbuJLRdAHCisPiFIeQmbfKOey8A/3ZREIwSiywCizIbf1AYQGgFIGhcQbKlNHsEzO2BgwQrBCI6iMywCMWK+uQiK6JSkpC717h+L69Y//9uvUccCqVW3g5MRfjyEVQoQQ/aaS55yWSn2ac08YlZwbJKwysIIgOwGGUXsBRghhZuy/g4hlRbNrkRlUZhUgSnkIqWMrMIoMKC1doTIpC1MXPyQY++SMmSGkFLC0NIRIlHOPI6GQwdix9TFqVD2ujS9UCBFCSielDML3TyFOuJFzbxplNsTxl6EycQCjlEGY+hgGb89qvFlNiiBWZAKlmROUphUht2+UM3ZGbApZhbZgDazy3wcDmNqaAwlpOdM8EVIKCIUCrFzZBgMGHMT8+f7w8XHgOxIAKoQIISUQI0uF8P1TCLLiIUq8AUaRCVHyA6iM7SBMfQJx4q1i3b/KyA6s2AxKEwcoLd0hyIyFvGxTACyUphWgtHSF0tKdxtEQvXbxYgyMjESoXbsc11ahggWOH+/Fy1ig/FAhRAjRPSolRIk3IJClwOBVOAQZsRC/PQeBIr3Ydimt2B6CzLeQVuyQc98ZgRiMUvrvFAVGUJqWh8rMiYobQr5AJlNi4cKLWL78GipWtMTp033ULonXpSIIoEKIEMInVgXxmzMQpTwAlFIYP90EYfrLIt2FtEI7KM2rQGHtCQgMwAqEUJlWACswAASinKkODCyKdJ+E6Ktnz5IwZMhR3L37DgDw8mUqNm68gxEj6vCcLH9UCBFCio8iE+J3V8CosnNm9M5OgCDzDQAVTO8uLPRmVWJzQGgEue03UNjWASsyhsLSPeduwmJzsEIjsEa21HtDiJawLIutW//Br7+eQVaWAgAgFgsQHNwIQ4f68Jzu86gQIoR8FUHmW4jfnP73rscKMLL3MHh9AgZvTn/1tuU2NSEr3was0AiyCoFQmlYAxKZFkJoQUlQSEjIxZsxxhIdHcm0uLtZYsyYQXl72PCYrGCqECCFfxGS9gyj5Hxi8OQMwIhhG7YUwParIti+3qYmsasOhMrIFayiBwqYm9eYQUgKcOhWFkSOP4d27DK6tXz8vzJjRFCYmYh6TFRwVQoSQj2TpEL09D0aeDvG7KzC593uRbFbq1BFyiTcgEINRZkNp4giVcRkobGrmnMIihJQ4795loH//A8jOVgIAJBJjLF3aEq1aOfOcTDNUCBGib1RKCDKiIU64CcPoAxC9uwRhVhz3spWGm1OaOUGY/hIZXpOgMi0PViAEWIAVm0Jezp8GIhNSSpUpY4pffmmMX345Az8/J4SEtIa9fck7dU2FECGlmCA9Bib3l0CQ8QrC95EQvX9a6G2xYJDt9iOUZk6Ql6kHlVEZqMwq0SksQvSESsVCqVRBLP54t/Mff/RGuXJmaNu2KgSCkvm7gAohQkowRvYe4rjzYBQZgEoOUcpjCDJewihqX6G3qRKbQ17OH3K7nMtdpZW6QGXqWFSRCSElUFxcOkaMOIbq1e0wdWoTrl0gYNC+vSuPyb4eFUKElCSsCsaP1sDk9jwI5KlftSm5tRcUdnWgsPZEtnMvMGJj2NqaIykhDSxN60AI+VdY2DOMHh2BpKRsnD37En5+ldC4cUW+YxUZKoQI0TGCzLcwerYlZ56stxegMi0PYcrDryp8MrwmQVahDZQWLmDF5kWYlhBSWmVkyDFt2lls2XKXa7OzK3ljgL6ECiFCtIyRpUCUdA9QycAopTCIjfj3tNZDiBOu5VpemPnqi9vMduoEednGgEAMgIHctjaUZpUAsVnRvwFCSKl3504chgw5isjIZK6tdWtnLFnSEhKJMY/Jih4VQoQUBVb1712UL8Hg7Xkw2fEQpr8AGCEM3v4NhaU7oJJBlPa88LsQGIJRSSG39gIrNkNak01QmZQtwjdBCNF3SqUKK1dex/z5F6FQqAAAJiYizJrVDL1719C5ecKKAhVChGhKngGj59th8CocBrHHweDLA2pEqY802oXKwArSyt2Q7dIbShNHmi6CEFLsEhOz8OOPh3Dhwsde6Jo17bFmTSCcna15TFa8qBAi5FOKTAjTX0KY+hRgldwpK0aeAXH85UJvlhUaQWVgCTBiCDNfIdNjGFhDq5zJP1kWcocAqAytoDKtSEUPIUTrLCwMkJEhB5DzK2jkyLoYP74BDAyEX1izZKNCiOg3lgVUcpj8swimd+d/1abkEm+AEYIVmUFaqTMUlm5QmVUAKzIFa2BFxQ0hRKeJxUKsXh2Ifv0OYOHCADRsWIHvSFpBhRDRK6LEOzC98SsM3p6BSmwOgTyt0NvKch2YM3WEvS8gKN3fmAghpc+1a69hbCxG9ep2XJuzszX+/rtfib05YmFQIURKP1YFk38WwejJJrUrsD5XBKnEFpBVbAewSsht6wJgobRyh9K0IlRmTtS7QwgpsRQKFZYsuYLFiy/D2dkaERG91CZI1aciCKBCiJRWrApGz/6E+aXhX1xUVqYhWLEpGJUCqc220SXnhJBSKyoqBUOHhuH69TcAgCdPkrBx4x0MG+bDczL+UCFESj6WhSD9BYye/QnTfxZBaV4ZwrQXn13lve86SJ06AUJDLYUkhBD+sCyLXbseIjj4FNLTZQAAoZDBuHENMHhwbZ7T8YsKIVKysCyEqY9hGH0Iprdn5blIfkWQzCEAafVDoDLTjwGAhBACACkp2Rg//gQOHHjCtVWqZIlVq9rAx8eBx2S6gQohovtUCogSb8HyROcCTzPBggEDFgqLqnjfZBOUNjWKOSQhhOieCxdiMGxYGF6/TufaevTwxJw5fjAzM+Axme6gQojoJpUCouR/YH2kaYEWl9vVA5MdD3k5P2R6joDKvEoxBySEEN0WF5eO77/fB5lMCQCwsjLEokUt0KFDyZ4tvqhRIUR0gyILwrQXMIw5DNPbs7+4uNK8MrKrdEd21QE0zQQhhOTB3t4M48bVx9y5F+DrWwErVrSGgwNNuvwpKoQIL0SJd2D8ZD0gZmH7YEuB1pGWb40s98GQOwQUczpCCCl5WJaFSsVCKBRwbSNG1IGDgzm++85D7y6LLygqhIjWiOMuwOpYG43Wkdk3hsyxBbI8f6Z79xBCSD4SEjIxZsxx1KhRBuPHN+DahUIBunWrxmMy3UeFECk2jDwNpjd+hdHTTWBYVYHWkdk3gty+EbJd+tHVXYQQUgCnTkVh5MhjePcuA8ePP0ezZk6oU4euBisoKoRIkTKM3A6LC4MLtCzLCME0XYRk8zpQmlYCa2BRzOkIIaT0yM5WYM6c81i79ibXZmVlxN0niBQMFUKkSAjSX0Kyr2CXqCe3OQGFXV0wDGBraw5lQhpYtpgDEkJIKfLgQTyCgsLw8GEC1+bn54SQkNawtzflMVnJQ4UQKTRh8n0YRW6HyYOQfJdRGpeDvKwv0usvBSumqxUIIeRrqFQs1q+/hVmzzkEqzbks3tBQiKlTG2PgQG8aEF0IVAgRjRm8OgbLU10/u0xipztQmVfWUiJCCCn9kpKyEBR0FKdPv+TaPDxssWZNIDw8bHlMVrJRIUQ+T6WAYdQ+GLwKg2H0YTAq6WcXz6j1KzK9xmspHCGE6A8TEzHevv14h+jBg2tjyhRfGBnRn/KvQZ8eyZdB9BFYnunxxeXS6v6ObOceNGs7IYQUIyMjEVavDkTfvgfx228B8POrxHekUoEKIaKOZSHIeAXxuwuwOD8o38XkNjWRXm8RFHb1tBiOEEL0x507cTAxEaNqVRuurVo1O1y+PAAikeAzaxJNUCFEAADClEewPtIUjDIrz9flNrWQWSsYcts6YI3oXDQhhBQXpVKFlSuvY/78i3B3lyAsrAcMDT/+uaYiqGhRIaTPWBWswltDHH/5s4tJHVvgfcBeLYUihBD9FRubhmHDwnDx4isAwL178di48Q6GDPmG52SlFxVCesrs8igYP/lfvq8rLKpCXrYJslwHQGnjpcVkhBCinw4ceIxx404gNTXnohSGAUaOrIsffqjFb7BSjgohfcKysApvAXH81XwXSW26FTKnb7UYihBC9FtamhSTJ5/Gzp0PuDZHR3OsXNkaDRvSVEPFjQohPSHIfAvJHtc8X5PZN0Zqy8M0qSkhhGjZtWuvMXRoGF6+TOXaOnZ0w8KFAbCyMuIxmf6gQqg0Y1kYxByG5Zle+S6S2OkuVOaVtJeJEEIIAODNmzR06rQbMlnOHaLNzAwwf74/unb1AENfTLWGCqHSiGUhSI+CZH/NfBeJ75NKPUCEEMKjcuXMMXToN1i69Crq1HHAqlVt4ORkyXcsvUOFUGnCsjD/ewCMXu7Ld5H0b2Yjy3OkFkMRQggBAPbf2aX/29szfnwDODpaoFev6nRZPE+oECot5Bmw214u35eTvr0BpWVVLQYihBDyQUpKNsaPP4Fatcpi2DAfrl0sFqJfP7oyl09UCJUCxvdDYHbjl1ztSuNyyHb/CZnVx9JpMEII4cmFCzEYNiwMr1+n4+jRZ2jSpCJq1CjDdyzyLyqESjKWhVVYAMQJ13O9FN/zLSAy4SEUIYQQAJDJlFiw4CJWrLiGf8+KwdRUjHfvMvgNRtRQIVRCmZ8fDKPn23O1Z9SagkyviTwkIoQQ8sGzZ0kYMuQo7t59x7X5+lbAihWt4eBgzmMy8ikqhEoalRx2f0ryfCmpw1Uordy1HIgQQsgHLMtiy5Z/MHXqGWRlKQAAYrEAwcGNMHSoDwQCGqaga6gQKmHyKoJYRoCE3sk0DogQQniUnJyFn3+OQHh4JNfm4mKNNWsC4eVlz2My8jlUCJUgdlsscrXF93gNiM14SEMIIeS/DAxEePo0iXvev39NTJ/eBCYmYh5TkS+hmxaUEJYR7XO1xfdJpSKIEEJ0hKmpGKtXt0HZsqbYuvVbLFwYQEVQCUA9QjpOkPYizztEx/dKoFNhhBDCowcP4mFiIkalSlZcW61aZXHt2kAYGtKf15KCeoR0XF5FUML3LwGhAQ9pCCGEqFQs1q27iVat/kJQUBgUCpXa61QElSxUCOkqpSzPMUEJ378Ea2jNQyBCCCFxceno3n0ffvnlDKRSJW7ceINNm+7wHYt8Bd4LoW3btsHf3x81atRA165dcffu3c8uv2nTJrRq1QpeXl5o2rQp5s6dC6lUqqW02mO3zTZXW3zf91QEEUIIT8LCnqFp0y04c+Yl1zZ4cG307l2Dx1Tka/Haf3f06FHMmzcPM2bMQM2aNbF582YMHDgQ4eHhkEhyXyZ+6NAh/P7775g7dy68vb0RFRWFSZMmgWEYBAcH8/AOikd+PUGEEEK0LyNDhnHjTmDz5o9f1O3tTRES0gp+fpX4C0aKBK89Qhs3bkS3bt3QpUsXuLi4YMaMGTAyMsLevXvzXP7WrVuoXbs22rdvj/Lly8PX1xft2rX7Yi9SSSKKv5qrjXqCCCGEH3fuxKF27XVqRVCbNs44c6YvFUGlBG89QjKZDPfv38fgwYO5NoFAgIYNG+LWrVt5ruPt7Y2DBw/i7t278PLyQkxMDM6ePYtvv/1W4/0zjO5ddMVkxcM6rLlaW0K/99CxmEXmw+eva8dBX9Hx0B10LHRDbGwaAgN3QCZTAgBMTESYPdsPvXtXB0MHR+uK6yPnrRBKTk6GUqnMdQpMIpHg+fPnea7Tvn17JCcno2fPnmBZFgqFAt27d8eQIUM03r+NjY7N9ZL4CNjlod7WYDpsbXUsZzGQSEr/eyxJ6HjoDjoW/LK1NcfQoT5YuvQKvvmmHP76qwtcXfOe4oiUXCXqGr8rV65g7dq1mDZtGry8vBAdHY05c+Zg5cqVGDZsmEbbSkpKg0r15eW0xXazehGU5ToQGa5jgIQ0nhIVP4bJ+UWfmJjGzcxM+EPHQ3fQseAPy7JqvT3jxtVDxYqW6N7dA2KxEAml+HeyrhMIiqcTg7dCyNraGkKhEImJiWrtiYmJsLXNfcUUACxbtgwdOnRA165dAQBubm7IzMzE1KlTERQUBIGg4EOeWBY68QuGkb2H7Y7yam2ysk2QXn8JoAP5tEFXjgXJQcdDd9Cx0J60NCkmTz4Nb++y+OGHWly7oaEIo0c3QEICFaV8K67Pn7fB0gYGBvD09MSlS5e4NpVKhUuXLsHb2zvPdbKzs3MVO0KhEEBOFV/iKKW5iiAASG15mIcwhBCin65dew0/vz+xc+cDTJ9+Fk+eJH55JVJq8HpqbMCAAZg4cSKqV68OLy8vbN68GVlZWejcuTMAYMKECbC3t8fYsWMBAH5+fti4cSOqVavGnRpbtmwZ/Pz8uIKoxGBZ2G2zy9Wc0D2GhzCEEKJ/FAoVFi++jCVLrkCpzPkyLRIJERWVSmOB9AivhVBgYCCSkpIQEhKC+Ph4eHh4YP369dypsTdv3qj1AAUFBYFhGCxduhRxcXGwsbGBn58fRo8ezddbKDTz8z/laovv+56HJIQQon+iolIwdGgYrl9/w7XVqeOAVavawMnJksdkRNsYtkSeU/p6iYn8DZY2/mcxzG5NV2vTxyKIYXKuyqBz77qBjofuoGNRfFiWxc6dDxAcfAoZGXIAgFDIYOzY+hg1qh5EIvXhF3QsdIdAUDxXUpaoq8ZKBVaVqwhK6PqMnyyEEKJHUlOzMW7cCRw48IRrc3KyxOrVbeDj48BjMsInKoS0zPz8ILXnaQ1WgjUuw1MaQgjRHwzD4ObNt9zz7t09MXeuH8zMDHhMRfjG+6Sr+sboxS7usdymJrKr9uExDSGE6A8LC0OsXNkaEokx1q9vh5CQVlQEEeoR0iajxxvUnqe0juApCSGElH7PniXBxEQMB4eP40rq1y+P69d/hKmpmMdkRJdQj5CWMPI0mF/55Oo2kTE/YQghpBRjWRabN99FQMCfGD48HCqV+ihnKoLIf1EhpCXWoT5qz1P9d/OUhBBCSq+EhEz063cQ48efQFaWAufPx2DLlrtfXpHoLTo1pgV2WyxytcnKt+IhCSGElF6nTkVh5MhjePcug2vr188L3bpV4zEV0XVUCBUzsytjcrXp4z2DCCGkuGRnKzBnznmsXXuTa5NIjLF0aUu0auXMYzJSElAhVMyMH69Xe57QNZKnJIQQUvo8eBCPoKAwPHyYwLX5+TkhJKQ17O1NeUxGSgoqhIqR+O3fas8Tv3sM1jj3/GKEEEI0FxPzHq1a/QWpVAkAMDQUYurUxhg40BsCAcNzOlJS0GDpYmQV0U7tucqkHE9JCCGk9KlQwYIb/+PhYYuIiF746afaVAQRjVCPUHFRZqs9TWl+gKcghBBSes2c2Qzly1sgKOgbGBnRnzSiOeoRKg4qBey2qU+bIXfw4ykMIYSUfBkZcowbdwI7dtxXazc1FWP06HpUBJFCo385RYyRJsF2ZyW1tmynzvyEIYSQUuDOnTgEBR3Fs2fJ2Lv3IerVc0TlylZ8xyKlBPUIFbFPiyAASGu6Ses5CCGkpFMqVQgJuYo2bbbj2bNkADl3jX70KOELaxJScNQjVMzonkGEEKK52Ng0DBsWhosXX3FtNWvaY82aQDg7W/OYjJQ2VAgVIyqCCCFEcwcOPMa4cSeQmioFADAMMHJkXYwf3wAGBkKe05HShgqhImR+YQjfEQghpMRKT5chOPgUdu58wLU5Oppj5crWaNiwAo/JSGlGhVARMor8i+8IhBBSYkmlSpw585J73rGjGxYuDICVlRGPqUhpR4OliwgjTVJ7ntDtBU9JCCGkZJJIjLF8eWuYmxtgxYrWWLs2kIogUuyoR6iIfHq1GGsk4ScIIYSUEFFRKTAxEaNMmY9zgjVr5oSbN3+EpSUVQEQ7qEeoKLAqtafS8oE8BSGEEN3Hsix27LgPP7+tGDUqAizLqr1ORRDRJiqEioDxvSVqz9832chTEkII0W0pKdkYNOgIRo48howMOU6ceIHt2+9/eUVCigmdGisCZrdmqDeIjPkJQgghOuzChRgMGxaG16/Tubbu3T3RoYMrj6mIvqNCqIgltTvPdwRCCNEpMpkSCxZcxIoV1/DhLJiVlSEWLWpBRRDhHRVCX0nwPlLtudLGi6ckhBCie54+TUJQ0FHcvfuOa/P1rYAVK1rDwcGcx2SE5KBC6CtJQr35jkAIITopKioFzZv/iawsBQBALBYgOLgRhg71gUDA8JyOkBw0WLoIvW+4iu8IhBCiMypVskJgoAsAwMXFGmFhPTB8eB0qgohOoR6hryBIj1F7LnXuxVMSQgjRTQsWBKBCBQuMGlUPJiZivuMQkstX9QhJpdKiylEiWZ7qpt7A0LccQoh+ys5W4Ndfz+DgwSdq7RYWhpg82ZeKIKKzNC6EVCoVVq5cicaNG8Pb2xsxMTm9IkuXLsXu3buLPKAuE6V8vPdFZvWxPCYhhBD+PHgQj1at/sLatTcxduxxxMam8R2JkALTuBBatWoV9u/fj/Hjx0Ms/ljhu7q6Ys+ePUUaTpeJX59We55RcyJPSQghhB8qFYt1626iVau/8PBhAoCcnqHbt9/ynIyQgtO4EDpw4ABmzZqFDh06QCD4uLqbmxueP39epOF0mdWJb9UbhHRLeEKI/oiLS0ePHvvwyy9nIJUqAQAeHraIiOiFtm2r8pyOkILTeLB0XFwcKlasmKudZVkoFIoiCaXzlDK1pykB+3gKQggh2hcW9gxjxhxHYmIW1zZ4cG1MmeILIyO6BoeULBr/i3VxccH169fh6Oio1h4eHg4PD48iC6bLrMJbqD2XOzbnKQkhhGhPRoYc06adxZYtd7k2e3tThIS0gp9fJf6CEfIVNC6Ehg4dikmTJiEuLg4syyIiIgIvXrxAaGgo1q5dWxwZdY448Rb3WGbfmMckhBCiPenpUhw58pR73qaNMxYvbgmJhOZXJCWXxmOEmjdvjjVr1uDSpUswNjZGSEgIIiMjsWbNGjRq1Kg4MuqUT6fUSPXfyVMSQgjRLnt7Myxe3AImJiIsXtwCmzZ1oCKIlHgMy36YAk+/JCamQaXSfD27LRZqz+P7vi+iRPqHYQBbW3MkJKRBP/8V6hY6HrpDV45FbGwaTExEsLZWL3bi4zNhZ2fCUyrt0pVjQQCBAJBIin5+Oo17hAICApCcnJyr/f379wgICCiSUDrrk0HSGbV+5SkIIYQUrwMHHqNZsy0YN+4EPv2+rC9FENEPGhdCsbGxUOXRlSKTyRAXF1ckoXSVMPWR2vPMGuN4SkIIIcUjLU2KESPC8dNPR5CaKsWhQ0+xd++jL69ISAlV4MHSJ0+e5B6fO3cO5uYfu6dUKhUuXbqU60qy0sbmsC/3WGlWiabUIISUKteuvUZQUBiio1O5to4d3dC8eWUeUxFSvApcCA0bNgwAwDAMJk2apL4RkQiOjo652ksVpfq8atlV+/IUhBBCipZCocKSJVewePFlKJU5p8HMzAwwf74/unb1AENf+kgpVuBC6NGjnK5Rf39/7NmzBzY2NsUWShcZvFGfUoPmFiOElAZRUSkYOjQM16+/4drq1HHAqlVt4ORkyWMyQrRD4/sInTp1qjhy6DyD2OPcY4WlO50WI4SUeM+fJ6N5821IT8+5EEQoZDB2bH2MGlUPIpHGQ0gJKZEKdS/0zMxMXLt2Da9fv4ZcLld7rW/f0nnKSJD1cRJBmWNLHpMQQkjRqFzZCo0bV0BYWCScnCyxenUb+Pg48B2LEK3SuBB68OABBg0ahKysLGRlZcHS0hLJyckwNjaGjY1NqS2EGGkK91helu4mTQgp+RiGweLFLVGhwmVMmtQIZmYGfEciROs07vucN28e/Pz8cO3aNRgaGmLXrl04ffo0PD09MXHixOLIqBMM4s5xj1UGVvwFIYSQQpDJlJg16xyOH3+u1i6RGGP2bD8qgoje0rgQevjwIQYMGACBQAChUAiZTIZy5cph/PjxWLx4cXFk5N8nN1JU2NbmKQghhGju2bMkBAZux/Ll1/DzzxF49y6D70iE6AyNCyGRSASBIGc1iUSC169fAwDMzMzw9u3bz61aYtlts1VvEIj5CUIIIRpgWRabN99FQMCfuHv3HQAgNTUbV6++5jkZIbpD4zFC1apVwz///INKlSqhTp06CAkJQXJyMg4cOICqVasWR0adIrP3/fJChBDCs4SETIwZcxzh4R8ninZxscaaNYHw8rLnMRkhukXjHqHRo0fDzs6Oe2xhYYHp06cjOTkZM2fOLPKAfDN6ukXteWrLIzwlIYSQgjl1KgrNmm1VK4L696+JEyd6UxFEyCc07hGqUaMG91gikWDDhg1FGkjXmF8art5A9w8ihOio7GwF5sw5j7Vrb3JtEokxli5tiVatnHlMRojuKrI7Zt2/fx+DBw8uqs3ppKRvr/MdgRBC8pWQkInt2+9zz/39K+HMmb5UBBHyGRoVQufOncOCBQuwePFixMTEAAAiIyMxdOhQfPfdd3nOSl+iKTLVniotXXkKQgghX1a+vAUWLgyAoaEQc+f6Yfv2TrC3N+U7FiE6rcCnxnbv3o1ff/0VlpaWeP/+PXbv3o1JkyZh9uzZaNOmDQ4fPgxn59L1rYNRZHGPVYb6NbcaIUT3xcWlw8REDHNzQ66tc2d31KvnCEdHcx6TEVJyFLhHaMuWLRg3bhyuXLmCpUuXIjk5Gdu3b8ehQ4cwc+bMUlcEAYDR8x3cY9aAJh8khOiOsLBnaNZsKyZPPp3rNSqCCCm4AhdCMTExaN26NQCgZcuWEIlEGD9+PMqWLVts4fgmjr/CPVaaV+ExCSGE5MjIkGPcuBPo1+8gEhOzsHPnAxw69ITvWISUWAU+NZadnQ1jY2MAOfPTiMVilClTptiC6QLDl6HcY6ljK/6CEEIIgDt34jBkyFFERiZzbW3aOKNhwwo8piKkZNPo8vndu3fDxMQEAKBUKrFv3z5YW1urLVNaJl0VpEWpPZdW6sRPEEKI3lMqVVi58jrmz78IhSLnohQTExFmz/ZDr17VwdBtPQgptAIXQg4ODti1axf33NbWFgcOHFBbhmEYjQuhbdu2YcOGDYiPj4e7uzt+/fVXeHl55bv8+/fvsWTJEhw/fhwpKSlwdHTE5MmT0bRpU432+yUW535Qe84a003ICCHaFxubhmHDwnDx4iuurWZNe6xZEwhnZ+vPrEkIKYgCF0KnTp0q8p0fPXoU8+bNw4wZM1CzZk1s3rwZAwcORHh4OCQSSa7lZTIZBgwYAIlEgmXLlsHe3h6vX7+GhYVFkWcTSBO5x5nVRhb59gkh5EsiI5PRqtVfSE2VAsi5n+vIkXUxfnwDGBgIeU5HSOmg8Z2li9LGjRvRrVs3dOnSBQAwY8YMnDlzBnv37sWgQYNyLb93716kpqZix44dEItzJj4tX758sWQTpr3gHmd6jiiWfRBCyOdUrmyF2rXL4vTpl3B0NMfKla1pPBAhRazI7iytKZlMhvv376Nhw4YfwwgEaNiwIW7dupXnOqdOnUKtWrUwc+ZMNGzYEO3atcOaNWugVCqLNpw8Xe0pa5i7d4oQQoqbQMAgJKQV+vSpgdOn+1ARREgx4K1HKDk5GUqlMtcpMIlEgufPn+e5TkxMDC5fvoz27dtj3bp1iI6OxowZM6BQKDB8+PA818kPw+Q/bZjZldHqywp57TgrtT58/jTOUzfQ8eCXQqHCkiVXUL++I5o0qQgg51iULWuGxYtb8JxOf9HPhe4ormNQov7CsywLiUSCWbNmQSgUonr16oiLi8OGDRs0LoRsbD5zw7HnOz8+du0GW1u6OVlxkkjo89UldDy07/nzZPTuvQ+XLr2Co6M57t4NAkDHQpfQsSi9eCuErK2tIRQKkZiYqNaemJgIW1vbPNexs7ODSCSCUPhxkGCVKlUQHx8PmUwGAwODAu8/KSkN+U2N9t+9J/osAZuQVuDtkoJjmJxfLomJaWBZvtMQOh7ax7Isdu16iEmTTiE9XQYAePs2HQcPPkD//t/QsdAB9HOhOwSCL3RiFFKhCqHo6Gjs3bsXMTExmDJlCiQSCc6ePQsHBwdUrVq1QNswMDCAp6cnLl26hObNmwMAVCoVLl26hN69e+e5Tu3atXH48GGoVCoIBDnDm6KiomBnZ6dREQQALIsC/aNWicwB+sdfrAp6LIh20PHQjpSUbIwffwIHDny8K7STkyVWr26DOnUcANCx0CV0LPhXXJ+/xoOlr169ivbt2+Pu3buIiIhAZmbODO2PHz/G8uXLNdrWgAEDsGvXLuzfvx+RkZGYPn06srKy0LlzZwDAhAkT8Pvvv3PL9+jRAykpKZgzZw5evHiBM2fOYO3atejVq5embyNfTHYC91hpUjxXpBFC9NuFCzFo1myLWhHUvbsnTp/uAx8fBx6TEaJ/NO4R+v333zFq1CgMGDAA3t7eXHv9+vXx559/arStwMBAJCUlISQkBPHx8fDw8MD69eu5U2Nv3rzhen4AoFy5ctiwYQPmzZuHDh06wN7eHn379sVPP/2k6dvIl/nlUdxjYear/BckhBANyWRKLFx4EcuXX+O+3VpaGuL331ugQwdXfsMRoqc0LoSePHmCRYsW5Wq3sbFBcnJyHmt8Xu/evfM9FbZ169Zcbd7e3mp3uC5qhtEHucdSR7pSgxBSdF6/TsP69be5IqhRo/JYsaINzRZPCI80PjVmbm6O+Pj4XO0PHz6EvX3pmoYio858viMQQkqRSpWsMGdOM4jFAkyd2hh793alIogQnmlcCLVt2xaLFi1CfHw8GIaBSqXCjRs3sGDBAnTs2LEYImqXwsqDe6y0KNjAb0IIyUtiYhYyM+VqbT17Vse5c/0wfHgdCAR0cxpC+KZxITR69GhUqVIFzZo1Q2ZmJtq2bYvevXvD29sbQUFBxZFRq0QpDwEArMiU5ySEkJLs1KkoNG26BTNm/K3WzjAMqlShyVIJ0RUajxEyMDDA7NmzMXToUDx9+hQZGRmoVq0aKlWqVAzx+MMoMviOQAgpgbKzFZgz5zzWrr0JANi48Q6aN6+MFi2q8JyMEJIXjQuh69evw8fHBw4ODnBwKF2XeTJZ7/iOQAgpwR48iEdQUBgePvx4Gw5//0rw8ipd4ycJKU00LoT69++PMmXKoF27dujQoQNcXFyKIxcvBFlxfEcghJRAKhWL9etvYdasc5BKcyaBNjQUYtq0Jhg4sBYYmqiKEJ2lcSH0999/4+jRozh8+DDWrVsHNzc3tG/fHu3atUPZsmWLIyMvslx/4DsCIaQEiItLx8iRx3D69EuuzcPDFmvWBMLDI+/pggghukPjwdI2Njbo3bs3duzYgePHj6N169YIDQ2Fv78/+vbtWxwZtYZhlXxHIISUIM+eJaFZs61qRdDgwbVx7FhPKoIIKSG+atLVChUqYNCgQXB3d8eyZctw7dq1osrFC5N/fuMeM3KaaJUQ8nmVK1vB1dUGly7Fwt7eFCEhreDnV4nvWIQQDRS6ELpx4wYOHTqEY8eOQSqVIiAgAGPGjCnKbFonTH388XF6NI9JCCElgVAowMqVbTBv3gXMnNkMEokx35EIIRoq1FxjR44cwbt379CoUSNMmTIFAQEBMDYu+b8ARKkfJ0BM95nDYxJCiK5RKlVYufI66tcvj7p1P14xW768BVaubMNjMkLI19C4ELp27RoGDhyINm3awMbGpjgy6QTlf+4wTQjRb7GxaRg2LAwXL75CxYqWOH26N8zNDfmORQgpAhoXQjt27CiOHLwTvI9Ue86KzHhKQgjRJQcOPMa4cSeQmioFAMTEpOLMmZdo355miyekNChQIXTy5Ek0adIEYrEYJ0+e/OyyAQEBRRJM2wzenFFvoPt+EKLX0tKkmDz5NHbufMC1OTqaY+XK1mjYsAKPyQghRalAhdCwYcNw4cIFSCQSDBs2LN/lGIbBw4cPiyycNomS7nCPM6uX7EHfhJCvc+3aawwdGoaXL1O5to4d3bBwYQCsrIx4TEYIKWoFKoQePXqU5+PSxPjpJu6x0rj03BiSEFJwCoUKS5ZcweLFl6FUsgAAMzMDzJ/vj65dPegO0YSUQhrfUDE0NBQymSxXu0wmQ2hoaFFk0j5FptpTaeWuPAUhhPApKioFISFXuSKoTh0HnD7dB926VaMiiJBSSuNCKDg4GGlpuW82mJGRgeDg4CIJpW0Gb86qPWeNJDwlIYTwycXFBlOnNoZQyGDChAY4cKAbnJws+Y5FCClGGl81xrJsnt+M4uLiYG5uXiShtI5VcA8Vlm48BiGEaFNKSjaMjUUwNPz4q/DHH73h61uRpsggRE8UuBDq2LEjGIYBwzDo168fRKKPqyqVSrx69QqNGzculpDF7b9XjGVX6c5fEEKI1ly4EINhw8LQsaMbpk9vyrUzDENFECF6pMCFUPPmzQEADx8+hK+vL0xNTbnXxGIxHB0d0bJly6JPqAX/nVdMmBnLYxJCSHGTyZRYuPAili+/BpYFVq26AX//ymjSpCLf0QghPChwITR8+HAAgKOjIwIDA2FoWJruqvrxVJ+0QlsecxBCitOzZ0kYMuQo7t59x7X5+laAi4s1j6kIIXzSeIxQp06diiMHr/57DyFWaMJjEkJIcWBZFlu2/IOpU88gKytnTKBYLEBwcCMMHeoDgYCuCCNEXxWoEKpbty7Cw8NhY2ODOnXqfPYy0qtXrxZZOG1hRR+LH5UJ3UOIkNIkISETY8YcR3j4x2l0XFyssWZNILy87HlMRgjRBQUqhIKDg2FmZsY9Lm330xAl3/v4REh3jSWktHj2LAkdO+7Gu3cZXFv//jUxfXoTmJiIeUxGCNEVBSqE/ns6rHPnzsUWhi+MMpt7rKK7ShNSajg5WcLR0Qzv3mVAIjHG0qUt0aqVM9+xCCE6ROMbKt6/fx+PHz/mnp84cQJDhw7F4sWL87zjtM5TKdSfl7LeLkL0mVgsxOrVgWjb1gVnzvSlIogQkovGhdDUqVMRFRUFAIiJicHo0aNhbGyM8PBw/Pbbb0Wdr/ixqo8P6bQYISWWSsXijz9u4p9/3qm1V6lijY0bO8De3jSfNQkh+kzjQigqKgoeHh4AgLCwMNStWxe///475s2bh4iIiCIPqE1y22/4jkAIKYS4uHT06LEPU6acwZAhR5GZKec7EiGkhNC4EGJZFipVTi/KpUuX0KRJEwBAuXLlkJycXLTpCCHkC8LCnqFZs604ffolAODp0yScPPmC51SEkJJC40KoevXqWL16NUJDQ3Ht2jU0a9YMAPDq1SvY2tJt6Qkh2pGRIce4cSfQr99BJCZmAQDs7U2xc2dntG/vynM6QkhJofENFSdPnozx48fjxIkTGDJkCJycnAAAx44dg7e3d5EHLG6CrLfcY2EGTa9BSElw504chgw5isjIj73Qbdo4Y/HilpBIjHlMRggpaTQuhNzd3XHo0KFc7RMmTIBAoHEHE+8YRSb3+L83ViSE6B6lUoWVK69j/vyLUChyTtGbmIgwa1Yz9O5do9Td44wQUvw0LoQ+uHfvHiIjc+7U6uLiAk9PzyILpU2CjFfcY9bAksckhJAvefo0Sa0IqlnTHmvWBMLZmeYKI4QUjsaFUGJiIkaNGoVr167BwsICAPD+/XvUq1cPS5YsgY2NTZGHLFaCjx+B0rwKj0EIIV/i7m6LSZMaYs6c8xg5si7Gj28AAwMh37EIISWYxueyZs2ahczMTBw5cgRXr17F1atXcfjwYaSnp2P27NnFkbFYMfI07rHSpByPSQghn0pPl3G9Px8MG+aDY8d6YsoUXyqCCCFfTeNC6Ny5c5g2bRqcnT/eodXFxQXTpk3D33//XaThtEH4n1NjguwEHpMQQv7r2rXX8PPbisWLL6u1C4UC1KpFU+EQQoqGxoWQSqWCWJx7skKRSMTdX6gkMX64mnusMq3AYxJCCAAoFCr89tsldOiwEy9fpmLx4iu4evU137EIIaWUxoVQ/fr1MWfOHMTFxXFtcXFxmDdvHho0aFCk4bRBmB7FPVYZ0oBLQvgUFZWCDh124rffLkGpZAEA33xTjqbHIIQUG40HS0+dOhVBQUEICAhA2bI53dNv375F1apVS+ZcY/8hderEdwRC9BLLsti16yGCg08hPT1n8mahkMHYsfUxalQ9iEQl79YchJCSQeNCqFy5cti/fz8uXbrEXT7v7OyMhg0bFnk4bWONJHxHIETvpKRkY8KEkwgNfcy1OTlZYvXqNvDxceAxGSFEH2hUCB09ehQnT56EXC5HgwYN0KdPn+LKRQjRA8+eJaFr172Ijf149Wb37p6YO9cPZmYGPCYjhOiLAhdCf/31F2bOnAknJycYGRnh+PHjiI6OxsSJE4szX/H6z12lCSHaV768BSwsDBEbmwYrK0MsWtQCHTrQPGGEEO0p8In3bdu2Yfjw4Th27BgOHDiA+fPnY/v27cWZrdgx8nS+IxCi14yMRFizJhDNm1fGmTN9qQgihGhdgQuhmJgYdOzYkXvevn17KBQKvHv3rjhyaZ20fCDfEQgp1ViWxZYtd/H4caJau4eHLf76qxMcHMx5SkYI0WcFPjUmk8lgYvJxUlKBQACxWAypVFoswbRBHH/14xNWwV8QQkq5hIRMjBlzHOHhkfD0tEN4eA8YGhZ6qkNCCCkyGv0mWrp0KYyNjbnncrkcq1evhrn5x29ywcHBRZeumImSbnOPDWMj+AtCSCl26lQURo48hnfvMgAA9+/HIyLiOdq3p9NghBD+FbgQqlOnDl68eKHW5u3tjZiYGO45wzBFl0wLWAMr7nG6z1z+ghBSCmVnKzB79jmsW3eLa5NIjLF0aUu0auX8mTUJIUR7ClwIbd26tThz8E5lQvcrIaSoPHgQj6Cgo3j48ON4ID8/J4SEtKa7RBNCdAqdpCeEFBmVisX69bcwa9Y5SKVKAIChoRBTpzbGwIHeEAhKVq8xIaT00+tCyPjRWr4jEFKqPHiQgKlTz0KlypknzMPDFmvWBMLDw5bnZIQQkje9nsBHkPGKe6wyLstjEkJKh+rV7TBqVF0AwODBtXHsWE8qggghOk2ve4QYVsk9lpdpwGMSQkqmzEw5jIxEaqe8xo6tj2bNnFC/fnkekxFCSMHob48Qy6o/L2FXvBHCtzt34hAQ8CdWrbqu1i4WC6kIIoSUGIUqhK5fv45x48bh+++/R1xcHAAgNDQU169f/8KauoORJvMdgZASSalUISTkKtq02Y7IyGTMm3cBd+/G8R2LEEIKReNC6NixYxg4cCCMjIzw4MEDyGQyAEB6ejrWri05g4+pECJEc7GxaejSZQ9mzz4PhUIFAKhWzQ6mpjRTPCGkZNK4EFq9ejVmzJiB2bNnQyT6OMSodu3aePDgQZGG05bsKj34jkCIzjtw4DGaNduCixdzLjJgGODnn+viyJHucHa25jkdIYQUjsaDpV+8eAEfH59c7ebm5nj//n2RhNI6Gh9ESL7S0qSYPPk0du78+EXH0dEcK1e2RsOGFXhMRgghX0/jQsjW1hbR0dEoX159MOSNGzdQoQL9UiSkNHn2LAk9euzHy5epXFvHjm747bcAWFoa8ZiMEEKKhsanxrp164Y5c+bgzp07YBgGcXFxOHjwIBYsWIAePegUEyGlSbly5hCJcn5NmJkZYMWK1li7NpCKIEJIqaFxITRo0CC0a9cO/fv3R2ZmJnr37o1ffvkF33//Pfr06VOoENu2bYO/vz9q1KiBrl274u7duwVa78iRI3Bzc8PQoUM13+l/7iFECMmbqakYa9YEolGj8jh9ug+6datW4iZXJoSQz2FY9tMb6hSMTCZDdHQ0MjMz4ezsDFPTwk2kePToUUyYMAEzZsxAzZo1sXnzZoSHhyM8PBwSiSTf9V69eoWePXuiQoUKsLS0xKpVqzTab+rdUFge75TzXhwCkNp8f6Hyk8JjGMDW1hwJCWm5butE+MAiLOwFPDxsUKmSlforLEsFkBbRz4buoGOhOwQCQCIxL/rtFnZFAwMDuLi4wMvLq9BFEABs3LgR3bp1Q5cuXeDi4oIZM2bAyMgIe/fuzXcdpVKJcePGYcSIEYUflyQQcw9VhjaF2wYhpURKSjZ++ukI+vULRVDQUcjl6j2mVAQRQkorjQdL9+nT57O/FLds2VLgbclkMty/fx+DBw/m2gQCARo2bIhbt27lu97KlSshkUjQtWtX3Lhxo8D7+y+BPJ17rDKvTBeO8eDDZ06fPb8uXIjB0KFheP0652fixo23OH78Odq2rcpzMv1FPxu6g46F7iiuY6BxIeTh4aH2XKFQ4OHDh3j69Ck6duyo0baSk5OhVCpznQKTSCR4/vx5nutcv34de/bsQWhoqEb7+pT5jcncYxMmDSa2Rd/dRgqmOLo6yZfJZEpMnXoaCxde4Lr8ra2NsG5de3z3XTV+wxEA9LOhS+hYlF4aF0KTJ0/Os3358uXIzMz86kCfk56ejgkTJmDWrFmwsfm601kKwzIQIafYyhCVQ1ZCWlFEJBpgmJxfLomJdO5d2549S8LgwUdx9+47rs3XtwK2b/8OxsYMEujngVf0s6E76FjoDoEAsLEp+oK0yGaf79ChA7p27YqJEycWeB1ra2sIhUIkJiaqtScmJsLW1jbX8jExMYiNjUVQUBDXplJ9uM1/NYSHh6NixYoF2rco5T73ONNtMED/wHnDsrnnwCXFg2VZbNnyD6ZOPYOsLAUAQCwWIDi4EYYN80GZMhY0KFSH0M+G7qBjwb/i+vyLrBC6desWDAw0m2/IwMAAnp6euHTpEpo3bw4gp7C5dOkSevfunWv5KlWq4NChQ2ptS5cuRUZGBqZMmYKyZcsWLrzQsHDrEVLC/PPPO4wff4J77uJijTVrAuHlZU9jIAgheknjQmj48OFqz1mWRXx8PO7du1eo+/kMGDAAEydORPXq1eHl5YXNmzcjKysLnTt3BgBMmDAB9vb2GDt2LAwNDeHq6qq2voWFBQDkav8SlhGB+73PFPriOUJKFC8vewwZ8g3WrLmB/v1rYvr0JjAxEX95RUIIKaU0LoTMzdXPzzEMg8qVK2PkyJHw9fXVOEBgYCCSkpIQEhKC+Ph4eHh4YP369dypsTdv3kAgKL5CRS7xLrZtE8I3qVQBAwOh2pWeU6Y0gr9/JTRr5sRjMkII0Q0a3VBRqVTi5s2bcHV1haWlZXHmKnbsChsw0mTIJd5IaXuW7zh6iW5UVrwePIhHUNBR9OtXEz/8UOuLy9Px0B10LHQHHQvdoRM3VBQKhfjhhx9K7izzhOgBlYrFunU30arVX3j4MBHTp5/F48eJX16REEL0kManxqpWrYpXr17RTPOE6KC4uHSMHHkMp0+/5NoqV7bmMREhhOg2jQffjBo1CgsWLMDp06fx7t07pKenq/1HCOFHWNgzNGu2Va0IGjy4No4d6wk3t/zn7SOEEH1W4B6hFStW4IcffsCgQYMAAEFBQWoDMD9Myvjw4cOiT0kIyVdGhhzTpp3Fli13uTZ7e1OEhLSCn18l/oIRQkgJUOBCaOXKlejRo4dGc4kRQopXZGQyevcORWRkMtfWpo0zFi9uCYnEmMdkhBBSMhS4EPpwcVndunWLLQwhRDN2dibcTPEmJiLMnu2HXr2q02zxhBBSQBqNEaJfroToFgsLQ6xc2QbffFMWJ0/2Qe/eNejnlBBCNKDRVWOtWrX64i/Zq1evflUgQkj+Dh58gm++KQdHx4/30qhXzxFHj/agAogQQgpBo0JoxIgRue4sTQgpfmlpUkyefBo7dz5Ao0blsWfPdxAKP3boUhFECCGFo1Eh1LZtW0gkdBkuIdp07dprDB0ahpcvUwEAFy68QkTEc7Rp48JzMkIIKfkKXAjRN05CtEuhUGHJkitYvPgylMqcixXMzAwwf74/Wrd25jkdIYSUDhpfNVZaMKyC7wiE5CsqKgVDh4bh+vU3XFudOg5YtaoNnJxK9jx/hBCiSwpcCD169Kg4c/CHVfGdgBAOy7LYteshgoNPIT1dBgAQChmMHVsfo0bVg0ik8c3gCSGEfIbGc42VNuKkO3xHIIRz+3YcRowI5547OVli9eo28PFx4DEVIYSUXnr/9VJuU4vvCIRwvL3Lom9fLwBA9+6eOH26DxVBhBBSjPS+R0hl6sh3BKLH5HIlRCKB2sUIM2Y0RfPmlWlANCGEaIHe9wgpzZz4jkD01LNnSWjTZjt27nyg1m5qKqYiiBBCtETvCyFCtI1lWWzefBcBAX/i7t13CA4+hefPk7+8IiGEkCKn96fGCNGmhIRMjBlzHOHhkVxbuXJmyM6m2zkQQggfqBAiREtOnYrCyJHH8O5dBtfWr58XZsxoChMTMY/JCCFEf1EhREgxy85WYM6c81i79ibXJpEYY+nSlmjVisYCEUIIn/S+EBKmveA7AinFnj9PxoABh/DwYQLX5u9fCcuWtYK9vSmPyQghhABUCEEh8eY7AinFrKyMkJycBQAwNBRi2rQmGDiwFs3dRwghOkLvrxpTGdrwHYGUYjY2xggJaQ1PTztERPTCjz96UxFECCE6RO8LIZlDAN8RSCly7Fgk4uIy1NqaNXPCiRO94OFhy1MqQggh+dH7QogVW/AdgZQCGRlyjBt3An36HMCoUcfAsqza60Kh3v+oEUKITqLfzoR8pTt34tC8+Z/YsuUuAODkyShERDznORUhhJCC0PvB0qyBOd8RSAmlVKqwcuV1zJ9/EQqFCgBgYiLC7Nl+aNmyCs/pCCGEFITeF0IQGvGdgJRAsbFpGDYsDBcvvuLaata0x5o1gXB2tuYxGSGEEE3odSGkMKeb2RHNhYY+xvjxJ5CaKgUAMAwwcmRdjB/fAAYGQp7TEUII0YReF0LCrLd8RyAlzPXrrzFo0BHuuaOjOVaubI2GDSvwmIoQQkhh6fdgaRVNdEk04+PjgK5dPQAAHTu64fTpPlQEEUJICabXPUJy+4Z8RyA6TqViIRCo3wBx/nx/tGhRBd9+60o3RySEkBJOv3uECPmMqKgUtGu3AwcOPFZrNzc3RMeOblQEEUJIKaDXPUKE5IVlWeza9RDBwaeQni7D06cn4OPjAEdHutUCIYSUNlQIEfIfKSnZGD/+BA4ceMK1WVkZISkpiwohQggphfS7EPpkGgSi3y5ciMGwYWF4/Tqda+ve3RNz5/rBzMyAx2SEEEKKi14XQuKEa3xHIDpAJlNiwYKLWLHiGlcbW1oa4vffW6BDB1d+wxFCCClWel0IZTt14jsC4VlUVAp+/PEw7t59x7U1alQeK1a0oVNhhBCiB/S6EAJd9aP3jI1FiI1NAwCIxQIEBzfC0KE+uS6ZJ4QQUjrp9eXzjFLKdwTCM3t7MyxZ0hJVq9ogLKwHhg+vQ0UQIYToEb3uERJkx/MdgWjZ2bMvUaNGGdjYGHNtrVs7IyCgEsRimieMEEL0jV73CCnNq/AdgWhJdrYCv/56Bl277sW4cSfAfnLFIBVBhBCin/S6EJLb+vAdgWjBgwfxaNXqL6xdexMAcPjwU5w6FcVvKEIIITpBr0+NkdJNpWKxfv0tzJp1DlKpEgBgaCjEtGlN4O9fid9whBBCdAIVQqRUiotLx8iRx3D69EuuzcPDFmvWBMLDw5bHZIQQQnQJFUKk1AkPj8To0RFITMzi2gYPro0pU3xhZET/5AkhhHxEfxVIqXLlSiz69j3APS9TxhTLl7eCn18l/kIRQgjRWXo9WJqUPnXrOiAw0AVAzmXxZ8/2pSKIEEJIvqhHiJRoLMuC+c8dwhmGweLFLdC6tTO+/76a2muEEELIp6hHiJRYsbFp6Nx5NyIinqu129gYo3t3TyqCCCGEfBH1CJES6cCBxxg37gRSU6V4/DgRp0/3hb29Kd+xCCGElDBUCJESJS1NismTT2Pnzgdcm6GhCHFx6VQIEUII0ZheF0KMIp3vCEQD1669RlBQGKKjU7m2jh3dsHBhAKysjHhMRgghpKTS60KI5horGRQKFRYvvowlS65AqcyZI8zMzADz5/uja1cPGgtECCGk0PS6EILAgO8E5Auio1MxZMhRXL/+hmurU8cBq1a1gZOTJY/JCCGElAb6XQgRnScQMHjyJAkAIBQyGDu2PkaNqgeRiC54JIQQ8vX0+q8JKzLhOwL5gvLlLfDbbwFwcrLEoUPfY9y4BlQEEUIIKTJ63SOkMrThOwL5xOXLr+DpaQdzc0OurVMnd7Rp40LzhBFCCClyOvHVetu2bfD390eNGjXQtWtX3L17N99ld+3ahZ49e6JOnTqoU6cO+vfv/9nlSckgkykxa9Y5fPvtLgQHn871OhVBhBBCigPvhdDRo0cxb948DBs2DPv374e7uzsGDhyIxMTEPJe/cuUK2rZtiy1btmDHjh0oV64cfvjhB8TFxWm+c0b4lelJUXj2LAmBgduxfPk1sCywa9cDnD4dxXcsQggheoD3Qmjjxo3o1q0bunTpAhcXF8yYMQNGRkbYu3dvnsv//vvv6NWrFzw8PODs7IzZs2dDpVLh0qVLGu9bZVLua+OTr8CyLNauvQ5//z9x9+47AIBYLMDUqY3RtKkTz+kIIYToA17PN8hkMty/fx+DBw/m2gQCARo2bIhbt24VaBtZWVlQKBSwtNT8UmqGYQC6BQ0vEhIyMXr0cYSHR3JtLi7WWLMmEDVr2vOYTH99uB0T3ZaJf3QsdAcdC91RXMeA10IoOTkZSqUSEolErV0ikeD58+f5rKVu0aJFKFOmDBo2bKjx/m1tzQEh3UtI244de4b+/Q/g7duPd/YOCvLBokUtYWIi5jEZAQCJxJzvCORfdCx0Bx2L0qtEj0Bdt24djh49ii1btsDQ0PDLK3wiISGNCiEtu3TpFTp02MU9t7U1wdKlLdCqlTMyM7ORmZnNYzr9xjA5v+wTE9PAsnyn0W90LHQHHQvdIRAANjZFX5DyWghZW1tDKBTmGhidmJgIW1vbz667YcMGrFu3Dhs3boS7u3uh9s+yAOgftlbVq+cIf/9KOHUqCv7+lbBtWxeIRCz9gtEhLAs6HjqCjoXuoGPBv+L6/HkdLG1gYABPT0+1gc4fBj57e3vnu94ff/yBVatWYf369ahRo4Y2opIiwjAMli1rhQULArBjRyeULWvGdyRCCCF6jPerxgYMGIBdu3Zh//79iIyMxPTp05GVlYXOnTsDACZMmIDff/+dW37dunVYtmwZ5s6dC0dHR8THxyM+Ph4ZGRl8vQWSj7i4DPTsuR9//x2t1m5vb4oBA2rSZKmEEEJ4x/sYocDAQCQlJSEkJATx8fHw8PDA+vXruVNjb968gUDwsV7bsWMH5HI5Ro4cqbad4cOHY8SIEVrNTvIXHh6J0aMjkJiYhfv343H6dB/Y2BjzHYsQQghRw3shBAC9e/dG796983xt69atas9PnTqljUikkDIy5Jg27Sy2bPl4t2+VikVMzHsqhAghhOgcnSiESOlw504cgoKO4tmzZK6tTRtnLF7cEhIJFUGEEEJ0DxVC5KsplSqsXHkd8+dfhEKhAgCYmIgwe7YfevWqTmOBCCGE6CwqhMhXef06DcOGheHChVdcW82a9lizJhDOztY8JiOEEEK+jAoh8lWysxW4dStnwluGAUaOrIvx4xvAwIAmtCWEEKL7eL98npRsVapYY+5cPzg6mmP//q6YMsWXiiBCCCElBvUIEY3cvPkG7u62anOC9ejhiQ4dXGFmRtOVEEIIKVmoR4gUiEKhwm+/XULbtjswffrfaq8xDENFECGEkBKJCiHyRVFRKejQYSd+++0SlEoWmzbdwfnz0V9ekRBCCNFxdGqM5ItlWeza9RDBwaeQni4DAAiFDMaOrY/69cvznI4QQgj5elQIkTylpGRjwoSTCA19zLU5OVli9eo28PFx4DEZIYQQUnSoECK5XLwYg2HDwhEbm8a1de/uiblz/WgsECGEkFKFCiGi5uLFGHTqtBssm/PcysoQixa1QIcOrvwGI4QQQooBDZYmaurVc0SDBjnjf3x9K+DMmb5UBBFCCCm1qEeIqBEKBVi5sg0OHnyCwYNrQyCgecIIIYSUXtQjpMcSEjIxYMBBXLkSq9bu6GiOoKBvqAgihBBS6lGPkJ46dSoKI0cew7t3Gfjnn3c4fboPzM0N+Y5FCCGEaBX1COmZ7GwFfvnlNLp334d37zIAABkZckRGJvOcjBBCCNE+6hHSIw8exCMo6CgePkzk2vz9K2HZslawtzflMRkhhBDCDyqE9IBKxWL9+luYNescpFIlAMDQUIhp05pg4MBaYBgaC0QIIUQ/USFUysXFpWPkyGM4ffol1+bhYYs1awLh4WHLYzJCCCGEf1QIlXLJydm4ePEV93zw4NqYMsUXRkZ06AkhhBAaLF3KubvbYtq0JihTxhQ7d3bGrFnNqAgihBBC/kV/EUuZe/fiUbWqNQwNPx7agQNr4bvvPGBlZcRjMkIIIUT3UI9QKaFUqhASchUtW27D3LkX1F5jGIaKIEIIISQPVAiVArGxaejSZQ9mzz4PhUKF1atv4PLl2C+vSAghhOg5OjVWwh048Bjjxp1AaqoUAMAwwMiRdVG7dlmekxFCCCG6jwqhEiotTYrJk09j584HXJujozlWrmyNhg0r8JiMEEIIKTmoECqBrl17jaFDw/DyZSrX1rGjGxYuDKCxQIQQQogGqBAqYS5ciMF33+2BUskCAMzMDDB/vj+6dvWgO0QTQgghGqLB0iVM3boOqFnTHgBQp44DTp/ug27dqlERRAghhBQC9QiVMGKxEKtWtcGBA08wYkQdiERUyxJCCCGFRYWQDktJycakSacQFPQN1wsEAFWqWGP06Ho8JiNEv7AsC5VKCZVKpZX9MQyQnZ0NuVwGltXKLkk+6Fhol1AogkCg3S/4VAjpqAsXYjBsWBhev07H3btxOHGiN0xMxHzHIkTvKBRypKYmQS7P1up+k5IEWiu8yOfRsdAmBtbWdjA0NNbaHqkQ0jEymRILFlzEihXXuG8fCQmZePw4Ed7edG8gQrSJZVkkJr6FQCCApaUthEKR1sbjCYUMd1EE4RcdC+1gWRbp6alITo5HmTLltdYzRIWQDnn2LAlDhhzF3bvvuDZf3wpYsaI1HBzMeUxGiH5SKORgWRUsLe1gYKDdW1OIRAIoFNQLoQvoWGiPmZklkpKyoFQqIBAYaGWfVAjpAJZlsWXLP5g69QyyshQAALFYgODgRhg61AcCAV0RRgifGIYuSiBEG/i4ApoKIZ4lJGRizJjjCA+P5NpcXKyxZk0gvLzsP7MmIYQQQr4Wfc3h2evXaThx4gX3vH//mjhxojcVQYQQQogWUCHEMy8ve0ya1BASiTG2bv0WCxcG0NVhhBDCo+joKHTo0AqZmRl8RylV5HI5vvuuPR49evDlhbVIv0+NMUKt7/Lp0yRUqmQJsfjjvocN80GPHtVhZ2ei9TyEkNJpzpzpCAs7DAAQCoUoU8Yefn4BGDhwCAwNDdWWvXDhHLZv34rHjx9BpVKicmVndO7cFYGB7XNt98yZk9izZyeePn0MlUoFBwdHNGsWgC5dusHCwlIr7624rVmzEl26dIOJiSnfUYrN3r27sH37ViQlJcLZuSpGjx6PatWq57u8QqHA1q0bERZ2GAkJ8ahQwQlBQSNQv35Dbpn9+/cgNHQP3rx5AwCoXLkK+vf/EQ0aNAIAiMVi9OjRG6tXL8eyZauL9w1qQL97hATaK4RUKhbr1t2Ev/9WLF58Re01oVBARRAhpMjVq9cQBw6EY9euAxgxYgwOHNiHDRvWqi2zZ88OBAePRY0aNbFu3SZs3rwDAQEtsWjRPKxYsVRt2bVrV2LatMnw8PDEokUh2LJlJ4YPH4Vnz54gPPyo1t6XXC4vtm2/ffsWFy+ey7MI1ERxZvxaJ09GYMWKJRgw4Cds2PAnXFxcMWbMCCQnJ+W7zrp1q3DgwD6MHj0eW7fuQseOXTB58ng8efKIW8bOrgyGDBmODRu2Yv36Lahd2wfBwWPx/PnHMbAtWrTB3bu31dr4prc9QiqjMlrbV1xcOkaOPIbTp18CAJYsuYIWLSqjdu1yWstACNE/BgZiSCS2AAB7+7I4dqwurl//+EUsLu4tVqxYiq5de2Dw4GFce48evSEWi7B06SL4+TWHp2d1PHhwD1u3bsTIkWPRrVsPbtly5RxQp059pKWl5Zvj3bs4rFy5DFevXoZcLoOTU2WMGTMRnp7VMWfOdKSnp2HevN+55Zct+x1Pnz7GihXrAADDhw9ClSrOEApFiIg4iipVXCCR2EKlUmHmzHncegqFAt9+2wrDh49GmzbtoFKpsG3bZhw8uB+JiYmoUKEi+vcfCD+/5vlmPXXqOFxcXGFn9/FvRGpqChYunI87d24hLe09HB3Lo0+fAWjRojW3TF4Zly9fi+fPn2HlyhDcvXsLRkbGqFu3HkaMGAsrKysAwOXLF7F58wa8eBEJgUCI6tVr4Oefx8HRsXy+Gb/Wjh3b0L59R7Rt2wEAMH58MC5dOo/Dhw+iT5/+ea5z7NhR9O37Axo08AUAdOr0Ha5fv4IdO7Zh6tRZAABf3yZq6wwePAyhoXvx4ME/qFLFGQBgYWGBGjVq4uTJCFSpElRM71AzelsIaUtY2DOMGXMciYlZXNtPP3mjWjU7HlMRQr6GQdR+mN6ZA0aeXmz7YAD89xZ+rNgMGbV+gcypY6G29/z5M9y7dxf29h+/gJ05cxIKhQI9evTJtfy333bB2rWrcOLEMXh6VkdERDiMjU3QuXPXPLdvbp73vc4yMzMxfPgg2NmVwfz5iyGRSPD48SOwrGb35QkLO4JOnbpg9eoNAIBXr17h118nIjMzEyYmOT3qV65cQnZ2Npo29QMAbN26ERERYRg3Lhjly1fAnTu3MGvWVFhZWcPb+5s893P37i24u3uotUmlMri5eaB3734wMTHFpUvnMXv2NDg6llc7nfRpxrS0NIwcGYT27Tti5MgxkEqzsXr1ckydOgkhIWsAANnZWejevRecnasiKysT69evweTJ47Bx41/53lBwy5b/YevWjZ/9vLZu3Y2yZXPfhFcul+PJk0fo02cA1yYQCODjUxf379/Nd3tyuRyGhur39TE0NMLdu7fzXF6pVOL06RPIzs6Cp6eX2mseHp64c+fWZ/NrExVCxSQjQ45p085iy5aP/7DKlDHF8uWt4OdXib9ghJCvZnJ/GUSpT3jZryaF0MWL59GiRWMolUrIZDIIBAKMHj2Bez0mJhpmZmawtbXNta5YLIaDgyNiYnJ6sl+9ioaDgyNEIs3+bBw/Ho6UlBSsX7+FG0NUvnwFjbYBABUqVMDQoT9zzx0cysPY2Bh//30arVu35fbl69sEJiamkMlk2Lp1I5YuXYXq1XP+EDs6lsfdu7dx4MC+fAuht2/fwt29mlpbmTJl0LPnx2Lxu++64+rVyzh16oRaIfRpxk2b1sPV1U2tty04eCo6d26L6OiXqFjRCc2aBajtKzh4Gtq1a46oqOeoUsUlz4wdO3aBv3+Lz35eeR1TIKd3S6lUwsbGRq3dxsYGL19G5bu9unXrY8eOv1CzZm04OpbHjRtXcfbsqVxTj0RGPsOQIQMgk8lgbGyMuXN/Q+XKVT7JZoe4uLefza9NVAgVgzt34jBkyFFERiZzba1bO2PJkpaQSLQ3fwohpHhkVh8F09uztd4jlOn5c36L58nb+xuMGxeMrKws7Nr1F4RCYa4/vAVV2AlHnz59AldXt68eSO3mpt5LIxKJ4OfXAhER4Wjdui2ysrJw/vxZTJ8+FwDw6lUMsrOzMXr0MLX15HI5qlZ1y3c/Umk2DAzUez6USiU2bdqAU6eOIz4+HgqFHDKZDIaG6ncb/zTjs2dPcfPmdbRo0TjXfmJjX6FiRSfExERj/fo1ePDgPlJTU7iesri4t/kWQhYWllofmP7zz+OwcOFs9Or1HRiGgYODIwIDO+DIkYNqy1Ws6ISNG/9Ceno6zpw5iTlzpmP58nVqxZChoSGys7U7d9/nUCFUxM6di8b33+/jbsduYiLCrFnN0Lt3DV7umEkIKXoyp46FPkVVUEUxrYOxsTHX+xIcPBX9+/fA4cOhaNeuIwCgQoWKSE9PR0JCPGxt1U/Xy+VyvH79CrVr+3DL3r17GwqFQqNeoU+vUPsUwzBgP6myFApFruWMjHJ/iWzZsjWGDx+E5OQkXLt2BYaGhtxVTFlZOcMRFi5cqjbeB8jp7cqPlZVVrvFO27Ztwe7d2zFy5FhUqeICY2NjhIT8DoVCfUD0pxmzsrLQqFFjBAWNzLWfD2O3Jk4cjbJly2HixCmwtbWDSqVC377fQy7P/Rl88DWnxiwtrSAUCpGUpD4wOikpCRKJJN/tWVtbY9683yGVSvH+fSpsbe2wevVyODg4qi0nFou5f3Pu7h54+PABdu/ejgkTpnDLvH+fyo2R0gVUCBWxunUd4OpqgwcPElCzpj3WrAmEs7M137EIIXpOIBCgT58BWLFiCVq0aA1DQyM0bRqA1auXY/v2PzFixGi15UND9yIrKwvNm7cCALRo0Rp79uzAvn271QZLf5CWlpbnOCEXl6o4fDgU79+n5tmLYWVljRcv1K8gevbsMYTCL/95qlGjJsqUKYuTJyNw+fJF+Pk154q0ypUrw8DAAHFxb/M9DZaXqlXdEBX1XK3tzp3b8PVtilatAgEAKpUK0dHRqFy58me35erqhrNnT6Fs2XJ5Fo+pqSmIjn6JiRN/Qc2a3ty+vuRrTo2JxWK4urrjxo2raNKkGfd+bty4hs6du31x34aGhrCzKwOFQoGzZ099MQfLqnJdQffiRSRcXfPvldM2/b18Xiktls0aGoqwZk0gRo+uhyNHulMRRAjRGX5+zSEQCLF3724AQNmyZTF06Ejs3r0da9euxMuXUYiNfYUdO/7E6tUh6N69Nzw9c8bAeHpWR8+efbFy5VKsWrUM9+7dxdu3b3D9+lX88stE7p5Fn2revBVsbCQIDh6Hu3dvIzb2Fc6cOYl793LGT37zTR08evQQYWGHERMTjQ0b1mp0aXWLFq0QGroP165dQYsWbbh2ExNTdO/eG8uXL0ZY2GHExr7C48ePsGfPjnyzAkDdug1w794/UCqVXFuFChVx7doV/PPPHURFvcBvv81FcnLiF7N16dIN79+/x/TpU/Dw4X3Exr7ClSuXMHfuDCiVSpibW8DS0hIHD+7Dq1cxuHHjGlasWPzF7VpYWKJ8+Qqf/e9zvXbdu/fCoUOhCAs7jKioF1i0aB6ysrLQtu3HWwbMmjUVa9as4J7fv38PZ8+eQmzsK9y5cwtjx46ASsWiZ8++3DJr1qzA7ds38ebNa0RGPsOaNStw69YNtGzZWm3/d+7cRp069b/4PrVFb3uEBPLUr95GWpoU06adxaBBteHu/rH6dne3RXBw3tU4IYTwRSQSoXPnbvjrry3o1Ok7GBsbo1u3nnBwcMT27X9iz54dUCpVqFy5CsaOncRdXv3B0KEj4ebmgf37dyM0dB9YVgUHh/Lw8wtAmzbt8tynWCzGkiUrsWLFEowf/zOUSiUqVaqCMWNyBm3Xq9cA/fv/iNWrl0Mmk6Jt2w5o3botIiOfFeg9tWzZBlu2/A9ly5aDl1dNtdd++ikIVlbW2Lp1I16/joWZmTlcXd3Rt++AfLYG1K/fEEKhENevX0W9eg0AAAMG/IjY2FcYM2YEjIyM0KFDJzRu3AwZGZ8fI5Zz+mgDVq9ejtGjh0Mul6Fs2XKoV68BBAIBGIbB9OlzsWzZIvTt+z0qVHDCqFHjMGLE4AK998IKCGiJlJRkrF+/BklJiXBxccXvvy+Hjc3HU2NxcW/VrlqTyaT444/VeP06FsbGxqhfvxF+/XWmWi9gcnISZs+ehsTEBJiamsHZuSoWL16uVvTcu3cX6enp8PMr3Fi14sCwn56c1RPyv5oipUX+3wq+5Nq11xg6NAwvX6aiWjVbHDvWE4aGeltXFgrDALa25khISCv0QExSdOh45CaXy5CY+AYSSTmIxQZfXqEIFcUYIVI4e/fuwoULf2Px4pweEToWRWfq1GC4uFRF374/5Pn6537mBAJAIsn7Ng1fQ39PjRWSQqHCb79dQocOO/HyZU6vUnT0ezx4kMBzMkIIIUXh2287o2ZNb5prrIjJ5XJUqeKM77/vyXcUNdSFoYGoqBQMHRqG69ffcG116jhg1ao2cHIqHXPsEEKIvhOJROjXbyDfMUodsViM/v1/5DtGLnpbCAnfF+z8MwCwLItdux4iOPgU0tNlOesLGYwdWx+jRtWDSEQda4QQQkhJpLeFkMqsUoGWS0nJxoQJJxEa+phrc3KyxOrVbeDj41BM6QghhBCiDXpbCCnNnAq03JMnSTh48OOt9Lt398TcuX4wM9PuwElCCH/09JoSQrSOj581OqfzBXXrOmDUqLqwtDTE+vXtEBLSioogQvSEUCgEkHPpMCGk+CmVOXfUzm/C2eKgtz1C+Xn5MhXly5tDKPx4EMaOrY9+/bxQrlzRX7ZHCNFdAoEQxsZmSE/PmTfQwMBQa1PlqFQMlErqidIFdCy0g2VVSEtLgYGBEQQCodb2S4XQv1iWxZYt/2Dq1DMYO7Y+Ro6sy70mFgupCCJET1lY5MzS/aEY0haBQJBrZm/CDzoW2sMwAlhY2Gh1bk4qhAAkJGRizJjjCA/Pua37/PkX4edXCTVqlPnCmoSQ0o5hGFhaSmBubs112xf/PgFra1MkJ2fQzS15RsdCu0QisdYnKNeJQmjbtm3YsGED4uPj4e7ujl9//RVeXl75Lh8WFoZly5YhNjYWlSpVwrhx49C0adNC7fvUqSiMHHkM7959vHFWr17VaY4wQogagUAAgUA74wMZBjAyMoJYLKc/vjyjY1H68T5Y+ujRo5g3bx6GDRuG/fv3w93dHQMHDkRiYt4T2t28eRNjx47Fd999h9DQUAQEBGDYsGF48uRJnsvnJ1vG4JdfTqN7931cESSRGGPr1m/x22/NYWIi/ur3RgghhBDdxnshtHHjRnTr1g1dunSBi4sLZsyYASMjI+zduzfP5bds2YLGjRvjxx9/hLOzM0aNGoVq1arhzz//1Gi/Lae7YN26W9xzf/9KOHOmL1q1cv6q90MIIYSQkoPXQkgmk+H+/fto2LAh1yYQCNCwYUPcunUrz3Vu376NBg0aqLX5+vri9u3bGu374SsjAIChoRBz5/ph+/ZOsLc31ewNEEIIIaRE43WMUHJyMpRKJSQSiVq7RCLB8+fP81wnISEBtra2uZZPSNBs0lNzcwO4u0uwdGlLuLlJvrwCKXIfxsMJBKBz7zqAjofuoGOhO+hY6I7iGkOtE4Ol+RAbO5bvCORfNjZ0awJdQsdDd9Cx0B10LEovXk+NWVtbQygU5hoYnZiYmKvX5wNbW9tcvT+fW54QQgghJD+8FkIGBgbw9PTEpUuXuDaVSoVLly7B29s7z3Vq1aqFy5cvq7VdvHgRtWrVKs6ohBBCCCmFeL9qbMCAAdi1axf279+PyMhITJ8+HVlZWejcuTMAYMKECfj999+55fv27Ytz587hf//7HyIjI7F8+XLcu3cPvXv35ustEEIIIaSE4n2MUGBgIJKSkhASEoL4+Hh4eHhg/fr13KmuN2/eqE2+Vrt2bSxatAhLly7F4sWLUalSJaxcuRKurq58vQVCCCGElFAMy8ec94QQQgghOoD3U2OEEEIIIXyhQogQQggheosKIUIIIYToLSqECCGEEKK3qBAihBBCiN4qlYXQtm3b4O/vjxo1aqBr1664e/fuZ5cPCwtD69atUaNGDbRv3x5nz57VUtLST5NjsWvXLvTs2RN16tRBnTp10L9//y8eO6IZTX82Pjhy5Ajc3NwwdOjQYk6oPzQ9Fu/fv8eMGTPg6+uL6tWro1WrVvS7qohoeiw2bdqEVq1awcvLC02bNsXcuXMhlUq1lLb0unbtGoYMGQJfX1+4ubnhxIkTX1znypUr6NSpE6pXr44WLVpg3759mu+YLWWOHDnCenp6snv27GGfPn3K/vLLL6yPjw+bkJCQ5/I3btxgPTw82D/++IN99uwZu2TJEtbT05N9/PixlpOXPpoeizFjxrB//vkn++DBA/bZs2fspEmT2G+++YZ9+/atlpOXTpoejw9iYmLYxo0bsz179mSDgoK0lLZ00/RYSKVStnPnzuxPP/3EXr9+nY2JiWGvXLnCPnz4UMvJSx9Nj8XBgwfZ6tWrswcPHmRjYmLYc+fOsY0aNWLnzp2r5eSlz5kzZ9jFixezERERrKurK3v8+PHPLh8dHc3WrFmTnTdvHvvs2TN269atrIeHB/v3339rtN9SVwh999137IwZM7jnSqWS9fX1ZdeuXZvn8j///DM7aNAgtbauXbuyv/76a7Hm1AeaHotPKRQK1tvbm92/f38xJdQvhTkeCoWC/f7779ldu3axEydOpEKoiGh6LP766y82ICCAlclk2oqoNzQ9FjNmzGD79u2r1jZv3jy2e/fuxZpT3xSkEFq4cCHbtm1btbZRo0axP/zwg0b7KlWnxmQyGe7fv4+GDRtybQKBAA0bNsStW7fyXOf27dto0KCBWpuvry9u375dnFFLvcIci09lZWVBoVDA0tKyuGLqjcIej5UrV0IikaBr167aiKkXCnMsTp06hVq1amHmzJlo2LAh2rVrhzVr1kCpVGordqlUmGPh7e2N+/fvc6fPYmJicPbsWTRt2lQrmclHRfX3m/cpNopScnIylEolJBKJWrtEIsHz58/zXCchISHXzPUSiSTXDPdEM4U5Fp9atGgRypQpo/ZLihROYY7H9evXsWfPHoSGhmohof4ozLGIiYnB5cuX0b59e6xbtw7R0dGYMWMGFAoFhg8fro3YpVJhjkX79u2RnJyMnj17gmVZKBQKdO/eHUOGDNFGZPIfef39trW1RXp6OrKzs2FkZFSg7ZSqHiFSeqxbtw5Hjx7FihUrYGhoyHccvZOeno4JEyZg1qxZsLGx4TuO3mNZFhKJBLNmzUL16tURGBiIIUOGYMeOHXxH0ztXrlzB2rVrMW3aNOzbtw8rVqzA2bNnsXLlSr6jkUIqVT1C1tbWEAqFSExMVGtPTEzMVTV+YGtrm6v353PLk4IpzLH4YMOGDVi3bh02btwId3f34oypNzQ9HjExMYiNjUVQUBDXplKpAADVqlVDeHg4KlasWLyhS6nC/GzY2dlBJBJBKBRybVWqVEF8fDxkMhkMDAyKNXNpVZhjsWzZMnTo0IE7Xezm5obMzExMnToVQUFBapOEk+KV19/vhIQEmJmZFbg3CChlPUIGBgbw9PTEpUuXuDaVSoVLly7B29s7z3Vq1aqFy5cvq7VdvHgRtWrVKs6opV5hjgUA/PHHH1i1ahXWr1+PGjVqaCOqXtD0eFSpUgWHDh1CaGgo95+/vz/q1auH0NBQlC1bVpvxS5XC/GzUrl0b0dHRXDEKAFFRUbCzs6Mi6CsU5lhkZ2fnKnY+FKgszWGuVUX291uzcdy678iRI2z16tXZffv2sc+ePWN//fVX1sfHh42Pj2dZlmXHjx/PLlq0iFv+xo0bbLVq1dgNGzawz549Y0NCQujy+SKi6bFYu3Yt6+npyYaHh7Pv3r3j/ktPT+frLZQqmh6PT9FVY0VH02Px+vVr1tvbm505cyb7/Plz9vTp02yDBg3YVatW8fUWSg1Nj0VISAjr7e3NHj58mI2OjmbPnz/PNm/enP355595egelR3p6OvvgwQP2wYMHrKurK7tx40b2wYMHbGxsLMuyLLto0SJ2/Pjx3PIfLp9fsGAB++zZM/bPP/8s1OXzperUGAAEBgYiKSkJISEhiI+Ph4eHB9avX891c75580atmq9duzYWLVqEpUuXYvHixahUqRJWrlwJV1dXvt5CqaHpsdixYwfkcjlGjhyptp3hw4djxIgRWs1eGml6PEjx0fRYlCtXDhs2bMC8efPQoUMH2Nvbo2/fvvjpp5/4egulhqbHIigoCAzDYOnSpYiLi4ONjQ38/PwwevRovt5CqXHv3j307duXez5v3jwAQKdOnTB//nzEx8fjzZs33OsVKlTA2rVrMW/ePGzZsgVly5bF7Nmz0bhxY432y7As9eURQgghRD/R1z9CCCGE6C0qhAghhBCit6gQIoQQQojeokKIEEIIIXqLCiFCCCGE6C0qhAghhBCit6gQIoQQQojeokKIEKJm37598PHx4TtGobm5ueHEiROfXWbSpEkYOnSolhIRQnRZqbuzNCEk5w/9/v37c7VHRETAycmJh0Qf7du3D8HBwQAAhmFQpkwZNGrUCOPGjYNEIvnq7Z8/fx6WlpYAgFevXiEgIAChoaHw8PDglpkyZUqxzwu1fPlyrFixAgAgEAhQpkwZNGnSBGPHjoWVlVWBtzNp0iS8f/8eq1atKqakhOg3KoQIKaUaN27M3aL+AxsbG57SqDMzM0N4eDhUKhUePXqEyZMn4927d9iwYcNXb9vOzu6Ly5ibm3/1fgqiatWq2LhxI1QqFSIjIzF58mSkpaVh6dKlWtk/IeTL6NQYIaWUgYEB7Ozs1P4TCoXYuHEj2rdvj1q1aqFp06aYPn06MjIy8t3Oo0eP0KdPH3h7e6N27dro3Lkz/vnnH+7169evo2fPnvDy8kLTpk0xe/ZsZGZmfjYbwzCws7ODvb09mjZtij59+uDixYvIzs6GSqXCihUr0KRJE1SvXh3ffvst/v77b25dmUyGmTNnwtfXFzVq1ICfnx/Wrl3Lvf7fU2MBAQEAgI4dO8LNzQ19+vQBoH5qbOfOnfD19VWb2R3ImVPqQ88VAJw4cQKdOnVCjRo1EBAQgBUrVkChUHz2fQqFQu59NmzYEK1bt8bFixe515VKJSZPngx/f394eXmhVatW2Lx5M/f68uXLsX//fpw8eRJubm5wc3PDlStXAOTMgfXzzz/Dx8cHdevWRVBQEF69evXZPISQ3KgQIkTPMAyDKVOm4PDhw5g/fz4uX76M3377Ld/lx40bh7Jly2LPnj3Yt28ffvrpJ4jFYgBAdHQ0fvrpJ7Rs2RIHDx7EkiVLcOPGDcyaNUujTEZGRlCpVFAoFNiyZQs2btyIiRMn4uDBg/D19cXQoUMRFRUFANi6dStOnTqFpUuXIjw8HL/99hscHR3z3O7u3bsBAJs2bcL58+exfPnyXMu0bt0aKSkpXIEBACkpKTh37hw6dOgAIKfYmzhxIvr27YujR49i5syZ2LdvH9asWVPg9/jq1SucP3+e++wAQKVSoWzZsli2bBmOHDmCYcOGYcmSJTh69CgA4IcffkCbNm3QuHFjnD9/HufPn4e3tzfkcjkGDhwIU1NTbNu2Ddu3b4eJiQl+/PFHyGSyAmcihNCpMUJKrTNnzsDb25t73rhxY4SEhKB///5cW/ny5TFq1ChMmzYN06dPz3M7r1+/xsCBA+Hs7AwAqFSpEvfa2rVr0b59e26blSpVwpQpU9CnTx9Mnz4dhoaGX8wZFRWF7du3o3r16jAzM8OGDRvw008/oW3btgCA8ePH48qVK9i8eTOmTZuGN2/ewMnJCd988w0Yhsm3CAI+ngq0srLK95SZpaUlmjRpgkOHDqFBgwYAgGPHjsHa2hr16tUDAKxYsQKDBg1Cp06dAOTMev3zzz/jt99+w/Dhw/Pd/5MnT+Dt7Q2lUgmpVAoAar1MYrEYI0eO5J5XqFABt2/fRnh4OAIDA2FqagojIyPIZDK1/AcOHIBKpcKcOXPAMAyAnJm669Spg6tXr8LX1zffTIQQdVQIEVJK1atXT624MTY2BgBcvHgRa9euxfPnz5Gens79kc7KyuKW+a8BAwbgl19+wYEDB7jTOxUrVgSQc9rs8ePHOHToELc8y7JQqVR49eoVVzx9Ki0tDd7e3lCpVJBKpfjmm28we/ZspKen4927d6hdu7ba8rVr18ajR48AAJ06dcIPP/yA1q1bo3HjxmjWrNlX/+Fv3749fv31V0yfPh0GBgY4dOgQ2rZtC4FAwL3PmzdvqvUAfelzA4DKlStj9erVkEqlOHjwIB4+fIjevXurLbNt2zbs3bsXr1+/hlQqhVwuh7u7+2fzPnr0CNHR0bk+J6lUiujo6MJ8BIToLSqECCmljI2Nc10h9urVKwwePBg9evTA6NGjYWlpiRs3bmDKlCmQy+V5/kEfMWIE2rVrh7Nnz+Lvv/9GSEgIlixZghYtWiAzMxPdu3fnxt78V7ly5fLNZmpqiv3790MgEMDOzg5GRkYAgPT09C++L09PT5w8eRJ///03Ll68iFGjRqFhw4YICQn54rr58ff3xy+//IIzZ86gRo0auH79ulrPTWZmJkaMGIGWLVvmWvdzvV5isZg7BuPGjcOgQYOwYsUKjBo1CgBw5MgRLFiwABMnToS3tzdMTU2xYcMG3Llz57N5MzMz4enpiUWLFuV6TVcGxBNSUlAhRIgeuX//PliWxaRJk7jejrCwsC+uV7lyZVSuXBn9+/fHmDFjsHfvXrRo0QLVqlXDs2fPNL4kXyAQ5LmOmZkZypQpg5s3b6Ju3bpc+82bN+Hl5aW2XGBgIAIDA9GqVSv8+OOPSElJyXVZ+ofxOEql8rN5DA0N0bJlSxw6dAgvX75E5cqV4enpyb1erVo1vHjx4qtvPRAUFIR+/fqhR48esLe3x82bN+Ht7Y1evXpxy3zaoyMWi3MN5Pb09ERYWBgkEgnMzMy+KhMh+o4GSxOiR5ycnCCXy7F161bExMQgNDQUO3bsyHf57OxszJw5E1euXEFsbCxu3LiBf/75hzvl9dNPP+HWrVuYOXMmHj58iKioKJw4cQIzZ84sdMaBAwfijz/+wNGjR/H8+XMsWrQIjx49Qt++fQEAGzduxOHDhxEZGYkXL14gPDwcdnZ2sLCwyLUtiUQCIyMjnDt3DgkJCUhLS8t3v+3bt8eZM2ewd+9etG/fXu21YcOG4cCBA1ixYgWePn2KyMhIHDlyBEuWLNHovXl7e8PNzY27ys3JyQn37t3DuXPn8OLFCyxdulTtijwAcHR0xOPHj/H8+XMkJSVBLpejffv2sLa2RlBQEK5fv46YmBhcuXIFs2fPxtu3bzXKRIi++387d8iiMBjHcfy3sWYQk13Lim2gBqtBoyiyIBabRcsUfAEGEREm4kzOV+MbMIpdxKDWu3AgHmfx4ODg+X7yYFv78n/+PEyEAIO4rqvhcKgoijSdTuV5nvr9voIgePm8bdu6XC4KgkCn00mpVErlcvmx4Ou6ruI41mw2k+/7kr4WfiuVyq+/sdVq6Xq9ajwe63w+K5vNarFYPJa0E4mE1uu1jsejbNtWLpfTarV6TLieOY6j0WikMAw1n8/leZ7iOH753kKhoGQyqcPh8COESqWSlsulwjBUFEVyHEeZTEb1ev3t/2u32xoMBup0Omo2m9rv9+r1erIsS9VqVb7vf7suoNFoaLfbqVar6X6/a7PZKJ/Pa7vdajKZqNvt6na7KZ1Oq1gsMiEC3mR9/PX1qgAAAP8UR2MAAMBYhBAAADAWIQQAAIxFCAEAAGMRQgAAwFiEEAAAMBYhBAAAjEUIAQAAYxFCAADAWIQQAAAwFiEEAACMRQgBAABjfQI26FtzOCbr1AAAAABJRU5ErkJggg=="
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# ROC Curve\n",
|
||
"fpr, tpr, _ = roc_curve(y_test, y_pred)\n",
|
||
"roc_auc = auc(fpr, tpr)\n",
|
||
"plt.figure()\n",
|
||
"lw = 2\n",
|
||
"plt.plot(fpr, tpr, color='darkorange', lw=lw, label='ROC curve (area = %0.2f)' % roc_auc)\n",
|
||
"plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')\n",
|
||
"plt.xlim([0.0, 1.0])\n",
|
||
"plt.ylim([0.0, 1.05])\n",
|
||
"plt.xlabel('False Positive Rate')\n",
|
||
"plt.ylabel('True Positive Rate')\n",
|
||
"plt.title('Receiver Operating Characteristic')\n",
|
||
"plt.legend(loc=\"lower right\")\n",
|
||
"plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:44:20.328279Z",
|
||
"start_time": "2024-03-20T12:44:20.154242Z"
|
||
}
|
||
},
|
||
"id": "dd49203934ca9cf6",
|
||
"execution_count": 133
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Plot the model\n",
|
||
"\n",
|
||
"This code block plots the model architecture using the `plot_model` function from Keras. The plot shows the structure of the model, including the input and output shapes, the layers, and the connections between layers."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "427d26655cf59f4d"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": "<IPython.core.display.Image object>"
|
||
},
|
||
"execution_count": 134,
|
||
"metadata": {},
|
||
"output_type": "execute_result"
|
||
}
|
||
],
|
||
"source": [
|
||
"# Plot the model\n",
|
||
"from tensorflow.keras.utils import plot_model\n",
|
||
"\n",
|
||
"# Generate the plot\n",
|
||
"plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:44:20.448825Z",
|
||
"start_time": "2024-03-20T12:44:20.329360Z"
|
||
}
|
||
},
|
||
"id": "81f2d793ada5c410",
|
||
"execution_count": 134
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Save the model"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "225526f72ffc154c"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# Save the model\n",
|
||
"model.save('CNN.keras')"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:44:20.516718Z",
|
||
"start_time": "2024-03-20T12:44:20.451223Z"
|
||
}
|
||
},
|
||
"id": "6b7329b28452b82a",
|
||
"execution_count": 135
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Multi-Layer Perceptron (MLP)\n",
|
||
"\n",
|
||
"This code block is implementing a Multi-Layer Perceptron (MLP) for a binary classification task using TensorFlow. The MLP is a class of feedforward artificial neural network that consists of at least three layers of nodes: an input layer, a hidden layer, and an output layer. Except for the input nodes, each node is a neuron that uses a nonlinear activation function. MLP utilizes a supervised learning technique called backpropagation for training.\n",
|
||
"\n",
|
||
"Here's a step-by-step breakdown of what the code does:\n",
|
||
"\n",
|
||
"1. **Model Creation**: A Sequential model is created using Keras. This model is composed of the following layers:\n",
|
||
" - Dense layers: These are fully connected layers. The first Dense layer has 64 units and uses the ReLU activation function. The second and third Dense layers have 32 and 16 units respectively, and also use the ReLU activation function. The final Dense layer has 1 unit and uses the sigmoid activation function for binary classification.\n",
|
||
" - BatchNormalization layers: These layers are used to normalize the activations of the previous layer, which speeds up learning and provides some regularization, reducing generalization error.\n",
|
||
" - Dropout layers: These layers are used to prevent overfitting. They randomly set a fraction of input units to 0 at each update during training time.\n",
|
||
"\n",
|
||
"2. **Model Compilation**: The model is compiled with the Adam optimizer, binary cross-entropy loss function, and accuracy as the evaluation metric.\n",
|
||
"\n",
|
||
"3. **Model Training**: The model is trained on the training data for 20 epochs with a batch size of 32. The validation data is set to the testing set. Early stopping is used to stop training when the validation loss has not improved for 10 epochs.\n",
|
||
"\n",
|
||
"4. **Model Evaluation**: The model's performance is evaluated on the testing data and the loss and accuracy are printed. The model also makes predictions on the testing data, converts the predicted probabilities to binary outputs, and generates a classification report.\n",
|
||
"\n",
|
||
"5. **Visualization**: The training and validation accuracy and loss over epochs are plotted.\n",
|
||
"\n",
|
||
"The mathematical concept behind the Dense layer is the dot product operation, which is a mathematical operation that takes two equal-length sequences of numbers and returns a single number. In the context of a MLP, the two sequences are the input data and the weights of the neurons. The dot product operation involves multiplying each pair of input and weight and summing the result.\n",
|
||
"\n",
|
||
"The mathematical formula for the dot product operation is: $$ a \\cdot b = \\sum_{i=1}^{n} a_i b_i $$ Where:\n",
|
||
"- $a$ and $b$ are the input data and weights respectively\n",
|
||
"- $n$ is the number of dimensions (length of the sequences)\n",
|
||
"- $a_i$ and $b_i$ are the $i$-th elements of the input data and weights respectively."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "42eff9445377f73c"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Epoch 1/20\n",
|
||
"1050/1050 [==============================] - 5s 3ms/step - loss: 1.0629 - accuracy: 0.5175 - val_loss: 0.8466 - val_accuracy: 0.6062\n",
|
||
"Epoch 2/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.9511 - accuracy: 0.5488 - val_loss: 0.8132 - val_accuracy: 0.6736\n",
|
||
"Epoch 3/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.8799 - accuracy: 0.5885 - val_loss: 0.7642 - val_accuracy: 0.7189\n",
|
||
"Epoch 4/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.8130 - accuracy: 0.6414 - val_loss: 0.7093 - val_accuracy: 0.7698\n",
|
||
"Epoch 5/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.7499 - accuracy: 0.6977 - val_loss: 0.6498 - val_accuracy: 0.8010\n",
|
||
"Epoch 6/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6981 - accuracy: 0.7429 - val_loss: 0.6020 - val_accuracy: 0.8145\n",
|
||
"Epoch 7/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6515 - accuracy: 0.7721 - val_loss: 0.5720 - val_accuracy: 0.8213\n",
|
||
"Epoch 8/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6235 - accuracy: 0.7883 - val_loss: 0.5508 - val_accuracy: 0.8239\n",
|
||
"Epoch 9/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5943 - accuracy: 0.8034 - val_loss: 0.5353 - val_accuracy: 0.8286\n",
|
||
"Epoch 10/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5726 - accuracy: 0.8155 - val_loss: 0.5220 - val_accuracy: 0.8293\n",
|
||
"Epoch 11/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5583 - accuracy: 0.8189 - val_loss: 0.5123 - val_accuracy: 0.8337\n",
|
||
"Epoch 12/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5423 - accuracy: 0.8247 - val_loss: 0.5020 - val_accuracy: 0.8371\n",
|
||
"Epoch 13/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5292 - accuracy: 0.8301 - val_loss: 0.4952 - val_accuracy: 0.8345\n",
|
||
"Epoch 14/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5147 - accuracy: 0.8343 - val_loss: 0.4870 - val_accuracy: 0.8385\n",
|
||
"Epoch 15/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5037 - accuracy: 0.8375 - val_loss: 0.4812 - val_accuracy: 0.8387\n",
|
||
"Epoch 16/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4986 - accuracy: 0.8394 - val_loss: 0.4748 - val_accuracy: 0.8395\n",
|
||
"Epoch 17/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4873 - accuracy: 0.8416 - val_loss: 0.4700 - val_accuracy: 0.8379\n",
|
||
"Epoch 18/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4769 - accuracy: 0.8465 - val_loss: 0.4655 - val_accuracy: 0.8382\n",
|
||
"Epoch 19/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4706 - accuracy: 0.8453 - val_loss: 0.4626 - val_accuracy: 0.8381\n",
|
||
"Epoch 20/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4625 - accuracy: 0.8483 - val_loss: 0.4604 - val_accuracy: 0.8387\n",
|
||
"263/263 [==============================] - 0s 1ms/step\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1200x600 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1200x600 with 1 Axes>",
|
||
"image/png": 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||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1200x600 with 1 Axes>",
|
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"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 640x480 with 0 Axes>"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Test loss: 0.4603869616985321\n",
|
||
"Test accuracy: 0.838690459728241\n",
|
||
"Classification Report: \n",
|
||
" precision recall f1-score support\n",
|
||
"\n",
|
||
" 0 0.80 0.90 0.85 4192\n",
|
||
" 1 0.88 0.78 0.83 4208\n",
|
||
"\n",
|
||
" accuracy 0.84 8400\n",
|
||
" macro avg 0.84 0.84 0.84 8400\n",
|
||
"weighted avg 0.84 0.84 0.84 8400\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Initialize a Sequential model\n",
|
||
"model = Sequential()\n",
|
||
"# Add a Dense layer with 64 units, ReLU activation function and L2 regularization\n",
|
||
"model.add(Dense(64, input_dim=X_train.shape[1], activation='relu', kernel_regularizer=regularizers.l2(0.001)))\n",
|
||
"# Add a BatchNormalization layer to normalize the activations of the previous layer\n",
|
||
"model.add(BatchNormalization())\n",
|
||
"# Add a Dropout layer to prevent overfitting\n",
|
||
"model.add(Dropout(0.5))\n",
|
||
"# Add another Dense layer with 32 units, ReLU activation function and L2 regularization\n",
|
||
"model.add(Dense(32, activation='relu', kernel_regularizer=regularizers.l2(0.001)))\n",
|
||
"# Add another BatchNormalization layer\n",
|
||
"model.add(BatchNormalization())\n",
|
||
"# Add another Dropout layer\n",
|
||
"model.add(Dropout(0.5))\n",
|
||
"# Add another Dense layer with 16 units, ReLU activation function and L2 regularization\n",
|
||
"model.add(Dense(16, activation='relu', kernel_regularizer=regularizers.l2(0.001)))\n",
|
||
"# Add another BatchNormalization layer\n",
|
||
"model.add(BatchNormalization())\n",
|
||
"# Add another Dropout layer\n",
|
||
"model.add(Dropout(0.5))\n",
|
||
"# Add the output Dense layer with 1 unit and sigmoid activation function\n",
|
||
"model.add(Dense(1, activation='sigmoid'))\n",
|
||
"\n",
|
||
"# Define early stopping to stop training when the validation loss has not improved for 10 epochs\n",
|
||
"early_stopping = EarlyStopping(monitor='val_loss', patience=10)\n",
|
||
"\n",
|
||
"# Compile the model with Adam optimizer, binary cross-entropy loss function and accuracy as the evaluation metric\n",
|
||
"model.compile(loss='binary_crossentropy', optimizer=Adam(learning_rate=0.0001), metrics=['accuracy'])\n",
|
||
"\n",
|
||
"# Train the model on the training data for 20 epochs with a batch size of 32 and validate on the testing data\n",
|
||
"history = model.fit(X_train, y_train, epochs=20, batch_size=32, validation_data=(X_test, y_test),\n",
|
||
" callbacks=[early_stopping])\n",
|
||
"\n",
|
||
"# Evaluate the model on the testing data and store the loss and accuracy in 'scores'\n",
|
||
"scores = model.evaluate(X_test, y_test, verbose=0)\n",
|
||
"\n",
|
||
"# Make predictions on the testing data\n",
|
||
"y_pred = model.predict(X_test)\n",
|
||
"# Convert the predicted probabilities to binary outputs\n",
|
||
"y_pred_classes = (y_pred > 0.5).astype(\"int32\")\n",
|
||
"# Generate a classification report\n",
|
||
"report = classification_report(y_test, y_pred_classes)\n",
|
||
"\n",
|
||
"fig, ax = plt.subplots(figsize=(12, 6))\n",
|
||
"\n",
|
||
"# Plot training & validation accuracy values\n",
|
||
"ax.plot(history.history['accuracy'], 'ro-', label='Training Accuracy')\n",
|
||
"ax.plot(history.history['val_accuracy'], 'bv--', label='Test Accuracy')\n",
|
||
"\n",
|
||
"# Plot training & validation loss values\n",
|
||
"ax.plot(history.history['loss'], 'go-', label='Training Loss')\n",
|
||
"ax.plot(history.history['val_loss'], 'yv--', label='Validation Loss')\n",
|
||
"\n",
|
||
"ax.set_title('Combined Graph')\n",
|
||
"ax.set_ylabel('Values')\n",
|
||
"ax.set_xlabel('Epoch')\n",
|
||
"ax.legend()\n",
|
||
"\n",
|
||
"# Show the figure\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Create a figure for the accuracy plot\n",
|
||
"fig1, ax1 = plt.subplots(figsize=(12, 6))\n",
|
||
"\n",
|
||
"# Plot training & validation accuracy values\n",
|
||
"ax1.plot(history.history['accuracy'], 'ro-', label='Training Accuracy')\n",
|
||
"ax1.plot(history.history['val_accuracy'], 'bv--', label='Test Accuracy')\n",
|
||
"ax1.set_title('Model Accuracy')\n",
|
||
"ax1.set_ylabel('Accuracy')\n",
|
||
"ax1.set_xlabel('Epoch')\n",
|
||
"ax1.legend()\n",
|
||
"\n",
|
||
"# Show the figure\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Create a figure for the loss plot\n",
|
||
"fig2, ax2 = plt.subplots(figsize=(12, 6))\n",
|
||
"\n",
|
||
"# Plot training & validation loss values\n",
|
||
"ax2.plot(history.history['loss'], 'ro-', label='Training Loss')\n",
|
||
"ax2.plot(history.history['val_loss'], 'bv--', label='Validation Loss')\n",
|
||
"ax2.set_title('Model Loss')\n",
|
||
"ax2.set_ylabel('Loss')\n",
|
||
"ax2.set_xlabel('Epoch')\n",
|
||
"ax2.legend()\n",
|
||
"\n",
|
||
"# Show the figure\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Show the figure\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.show()\n",
|
||
"\n",
|
||
"# Print the testing loss and accuracy\n",
|
||
"print('Test loss:', scores[0])\n",
|
||
"print('Test accuracy:', scores[1])\n",
|
||
"# Print the classification report\n",
|
||
"print('Classification Report: \\n', report)"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:45:12.758171Z",
|
||
"start_time": "2024-03-20T12:44:20.518130Z"
|
||
}
|
||
},
|
||
"id": "c8745832a585d5ec",
|
||
"execution_count": 136
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Multi-Layer Perceptron (MLP) visualization\n",
|
||
"This code block is used to visualize the performance of a trained Multi-Layer Perceptron (MLP) model. It generates three types of visualizations:\n",
|
||
"\n",
|
||
"1. Weights and Biases Visualization: This visualization is used to understand the distribution of weights and biases in the model's layers. For each layer in the model, if the layer is a dense layer, it retrieves the weights and biases, and plots histograms of their values. The x-axis of the histogram represents the value of the weights/biases and the y-axis represents the frequency of these values.\n",
|
||
"\n",
|
||
"2. Confusion Matrix: A confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known. It gives a more detailed breakdown of correct and incorrect classifications for each class.\n",
|
||
"\n",
|
||
"3. ROC Curve: The Receiver Operating Characteristic (ROC) curve is a plot that illustrates the diagnostic ability of a binary classifier system as its discrimination threshold is varied. It is created by plotting the true positive rate (TPR) against the false positive rate (FPR).\n",
|
||
"\n",
|
||
"## Weights and Biases Evaluation\n",
|
||
"\n",
|
||
"The weights and biases of the MLP model layers were visualized to understand their distributions. The weights in all layers (dense, dense_1, dense_2, and dense_3) are not close to zero, indicating they are likely being updated during training and contributing to the model's learning. The weight distributions show a spread around zero, suggesting the model is capturing complex relationships in the data.\n",
|
||
"\n",
|
||
"The biases in dense and dense_2 introduce a slight positive bias to the activations in subsequent layers, potentially affecting the model's predictions. The biases in dense_1 and dense_3 are centered around zero, with a slight spread towards positive values, introducing a small positive shift in the activations of the next layer.\n",
|
||
"\n",
|
||
"The impact of these biases would depend on the network architecture and data. Overall, the model's weights and biases suggest that it is learning effectively from the training data."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "4114f5c851874555"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# 1. Visualize Weights and Biases\n",
|
||
"for layer in model.layers:\n",
|
||
" if 'dense' in layer.name:\n",
|
||
" weights, biases = layer.get_weights()\n",
|
||
" plt.figure(figsize=(10, 5))\n",
|
||
" plt.subplot(1, 2, 1)\n",
|
||
" plt.hist(weights.flatten())\n",
|
||
" plt.title(f'{layer.name} weights')\n",
|
||
" plt.subplot(1, 2, 2)\n",
|
||
" plt.hist(biases.flatten())\n",
|
||
" plt.title(f'{layer.name} biases')\n",
|
||
" plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:45:13.997738Z",
|
||
"start_time": "2024-03-20T12:45:12.759536Z"
|
||
}
|
||
},
|
||
"id": "41091791008ff727",
|
||
"execution_count": 137
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"## Confusion Matrix Evaluation\n",
|
||
"\n",
|
||
"The confusion matrix is a table that is often used to describe the performance of a classification model on a set of test data for which the true values are known. It gives a more detailed breakdown of correct and incorrect classifications for each class.\n",
|
||
"\n",
|
||
"The confusion matrix shows that the model has a good performance in distinguishing between positive and negative instances. The majority of the instances are correctly classified, with a small number of false positives and false negatives."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "618bc6deb5ea296b"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 500x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# 2. Confusion Matrix\n",
|
||
"# Convert the predicted probabilities to binary outputs\n",
|
||
"y_pred_classes = (y_pred > 0.5).astype(\"int32\")\n",
|
||
"# Generate the confusion matrix\n",
|
||
"cm = confusion_matrix(y_test, y_pred_classes)\n",
|
||
"# Plot the confusion matrix\n",
|
||
"plt.figure(figsize=(5, 5))\n",
|
||
"sns.heatmap(cm, annot=True, fmt='d', cmap='Blues')\n",
|
||
"plt.title('Confusion matrix')\n",
|
||
"plt.xlabel('Predicted class')\n",
|
||
"plt.ylabel('True class')\n",
|
||
"plt.show()\n",
|
||
"\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:45:14.169540Z",
|
||
"start_time": "2024-03-20T12:45:13.999157Z"
|
||
}
|
||
},
|
||
"id": "6b7d586ea49a858a",
|
||
"execution_count": 138
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"## ROC Curve Evaluation\n",
|
||
"\n",
|
||
"The Receiver Operating Characteristic (ROC) curve is a graphical representation that illustrates the performance of a binary classification model at all classification thresholds. It is commonly used in machine learning to evaluate the performance of a classifier system for two-class problems.\n",
|
||
"\n",
|
||
"The ROC curve has two axes:\n",
|
||
"- The X-axis represents the False Positive Rate (FPR), which is the proportion of negative instances that are incorrectly classified as positive.\n",
|
||
"- The Y-axis represents the True Positive Rate (TPR), which is the proportion of positive instances that are correctly classified as positive.\n",
|
||
"\n",
|
||
"A perfect classifier would classify all positive instances correctly (TPR = 1) and all negative instances correctly (FPR = 0). This would be represented by a curve that goes straight up the left side of the ROC graph and then along the top to the right corner.\n",
|
||
"\n",
|
||
"The Area Under the Curve (AUC) is a numerical measure of the ROC curve’s performance. A larger AUC indicates a better performance. In our case, the AUC is 0.91, which is considered to be very good.\n",
|
||
"\n",
|
||
"In summary, the ROC curve shows that our binary classification model has a good performance in distinguishing between positive and negative instances."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "8645f7e159d38f0a"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 640x480 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"# 3. ROC Curve\n",
|
||
"# Compute ROC curve and ROC area for each class\n",
|
||
"fpr, tpr, _ = roc_curve(y_test, y_pred)\n",
|
||
"roc_auc = auc(fpr, tpr)\n",
|
||
"# Plot the ROC curve\n",
|
||
"plt.figure()\n",
|
||
"lw = 2\n",
|
||
"plt.plot(fpr, tpr, color='darkorange', lw=lw, label='ROC curve (area = %0.2f)' % roc_auc)\n",
|
||
"plt.plot([0, 1], [0, 1], color='navy', lw=lw, linestyle='--')\n",
|
||
"plt.xlim([0.0, 1.0])\n",
|
||
"plt.ylim([0.0, 1.05])\n",
|
||
"plt.xlabel('False Positive Rate')\n",
|
||
"plt.ylabel('True Positive Rate')\n",
|
||
"plt.title('Receiver Operating Characteristic')\n",
|
||
"plt.legend(loc=\"lower right\")\n",
|
||
"plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:45:14.346014Z",
|
||
"start_time": "2024-03-20T12:45:14.170762Z"
|
||
}
|
||
},
|
||
"id": "4d080bef0cf9bec4",
|
||
"execution_count": 139
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"## Learning curve"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "5d1867cb3af9788d"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 1000x600 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"def plot_learning_curve(history):\n",
|
||
" plt.figure(figsize=(10, 6))\n",
|
||
" plt.plot(history.history['loss'], label='Training Loss')\n",
|
||
" plt.plot(history.history['val_loss'], label='Validation Loss')\n",
|
||
" plt.plot(history.history['accuracy'], label='Training Accuracy')\n",
|
||
" plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n",
|
||
" plt.xlabel('Epoch')\n",
|
||
" plt.ylabel('Loss / Accuracy')\n",
|
||
" plt.title('Learning Curve')\n",
|
||
" plt.legend()\n",
|
||
" plt.show()\n",
|
||
"\n",
|
||
"\n",
|
||
"plot_learning_curve(history)\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-20T12:45:14.573591Z",
|
||
"start_time": "2024-03-20T12:45:14.347420Z"
|
||
}
|
||
},
|
||
"id": "c67bb53e5a864293",
|
||
"execution_count": 140
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 2
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython2",
|
||
"version": "2.7.6"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|