2335 lines
1.7 MiB
2335 lines
1.7 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": [
|
||
"# Load and Clean the Data\n",
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"\n",
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"This code block performs the following operations:\n",
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||
"\n",
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||
"1. Imports necessary libraries for data handling and cleaning.\n",
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"2. Defines a function `load_data` to load the data from a given directory into a pandas dataframe.\n",
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"3. Defines a function `clean_data` to clean the loaded data. The cleaning process includes:\n",
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||
" - Handling missing values by dropping them.\n",
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||
" - Removing duplicate rows.\n",
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||
" - Converting the 'NLOS' column to integer data type.\n",
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||
" - Normalizing the 'Measured range (time of flight)' column.\n",
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||
" - Creating new features 'FP_SUM' and 'SNR'.\n",
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||
" - One-hot encoding categorical features.\n",
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||
" - Performing feature extraction on 'CIR' columns.\n",
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||
" - Dropping the original 'CIR' columns.\n",
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||
" - Checking for columns with only one unique value and dropping them.\n",
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"4. Checks if a pickle file with the cleaned data exists. If it does, it loads the data from the file. If it doesn't, it loads and cleans the data using the defined functions.\n",
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||
"5. Prints the first few rows of the cleaned data and its column headers."
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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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||
"import pandas as pd\n",
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||
"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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||
"from sklearn.preprocessing import LabelEncoder\n",
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||
"from sklearn.decomposition import PCA\n",
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||
"from sklearn.ensemble import RandomForestClassifier\n",
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||
"from sklearn.metrics import accuracy_score, classification_report\n",
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||
"from sklearn.model_selection import train_test_split\n",
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||
"from sklearn.preprocessing import StandardScaler\n",
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||
"import pickle\n",
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||
"from sklearn.model_selection import cross_val_score\n",
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||
"from sklearn.metrics import roc_curve, auc\n",
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||
"import tensorflow as tf\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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||
"import matplotlib.pyplot as plt\n",
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||
"import numpy as np\n",
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||
"import pywt\n",
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||
"from skimage import restoration\n",
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||
"from tensorflow.keras.utils import to_categorical\n"
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||
],
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||
"metadata": {
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||
"collapsed": false,
|
||
"ExecuteTime": {
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||
"end_time": "2024-03-18T15:11:18.504645Z",
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||
"start_time": "2024-03-18T15:11:18.499866Z"
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||
}
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||
},
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||
"id": "2aa3c6c09e8645d1",
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||
"execution_count": 52
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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": [
|
||
"# 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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||
"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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||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
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||
"end_time": "2024-03-18T15:11:19.031515Z",
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||
"start_time": "2024-03-18T15:11:19.027111Z"
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||
}
|
||
},
|
||
"id": "7bcd7cfc8dd11cbb",
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||
"execution_count": 53
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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": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:19.064442Z",
|
||
"start_time": "2024-03-18T15:11:19.060311Z"
|
||
}
|
||
},
|
||
"id": "9e0b1ed6f23a17cf",
|
||
"execution_count": 54
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||
},
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||
{
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||
"cell_type": "markdown",
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"source": [
|
||
"# 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": {
|
||
"collapsed": false
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||
},
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||
"id": "1dd92fe7b6881ea6"
|
||
},
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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",
|
||
" "
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:19.135601Z",
|
||
"start_time": "2024-03-18T15:11:19.128782Z"
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||
}
|
||
},
|
||
"id": "308d64639b199bc7",
|
||
"execution_count": 55
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||
},
|
||
{
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||
"cell_type": "markdown",
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||
"source": [
|
||
"# 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."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "bfd97fbe797a7067"
|
||
},
|
||
{
|
||
"cell_type": "code",
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||
"outputs": [],
|
||
"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",
|
||
" # Show the plot\n",
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||
" plt.show()\n",
|
||
" "
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:19.220126Z",
|
||
"start_time": "2024-03-18T15:11:19.215563Z"
|
||
}
|
||
},
|
||
"id": "4afc8d71b3271351",
|
||
"execution_count": 56
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Scatter Plot of RX_Level and First_Path_Power_Level"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "e26e1cb8e6257696"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"def plot_features(data, labels, feature1, feature2):\n",
|
||
" reds = labels == 1\n",
|
||
" blacks = labels == 0\n",
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||
" plt.scatter(data[reds][feature1], data[reds][feature2], c=\"red\", s=20, edgecolor='k')\n",
|
||
" plt.scatter(data[blacks][feature1], data[blacks][feature2], c=\"yellow\", s=20, edgecolor='k')\n",
|
||
" plt.xlabel(feature1)\n",
|
||
" plt.ylabel(feature2)\n",
|
||
" plt.title(f\"Plot of data: {feature1} versus {feature2}\")\n",
|
||
" plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:19.296284Z",
|
||
"start_time": "2024-03-18T15:11:19.292138Z"
|
||
}
|
||
},
|
||
"id": "ac4db13fed3f9916",
|
||
"execution_count": 57
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"## denoise_cir Function\n",
|
||
"\n",
|
||
"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",
|
||
"\n",
|
||
"1. **Wavelet Decomposition:**\n",
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||
"\n",
|
||
" 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",
|
||
"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",
|
||
"$$\n",
|
||
"T(x) = x * I(|x| > \\text{{value}}) \\quad \\text{{for 'hard' thresholding}}\n",
|
||
"$$\n",
|
||
"\n",
|
||
"$$\n",
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||
"T(x) = \\text{{sign}}(x)(|x| - \\text{{value}})_+ \\quad \\text{{for 'soft' thresholding}}\n",
|
||
"$$\n",
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||
"\n",
|
||
"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",
|
||
"\n",
|
||
"3. **Wavelet Reconstruction:**\n",
|
||
"\n",
|
||
" The original signal is reconstructed from the approximation and detail coefficients."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "69413268ac5b549d"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"def denoise_cir(cir_values, wavelet='db1', level=1):\n",
|
||
" # Perform wavelet decomposition\n",
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||
" coeffs = pywt.wavedec(cir_values, wavelet, level=level)\n",
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||
"\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",
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||
"\n",
|
||
" # Perform wavelet reconstruction\n",
|
||
" denoised_cir = pywt.waverec(coeffs, wavelet)\n",
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||
"\n",
|
||
" return denoised_cir\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:19.390451Z",
|
||
"start_time": "2024-03-18T15:11:19.386423Z"
|
||
}
|
||
},
|
||
"id": "fe3089568e99a58d",
|
||
"execution_count": 58
|
||
},
|
||
{
|
||
"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": "2024-03-18T15:11:19.435012Z",
|
||
"start_time": "2024-03-18T15:11:19.431187Z"
|
||
}
|
||
},
|
||
"id": "670e8c2cf19126ea",
|
||
"execution_count": 59
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"\n",
|
||
"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",
|
||
" # 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",
|
||
" # Extract the 'CIR' columns\n",
|
||
" # cir_columns = [f\"CIR{i}\" for i in range(1015)]\n",
|
||
" # # cir_columns = [f\"CIR{i}\" for i in range(1016)]\n",
|
||
" # cir_data = data[cir_columns]\n",
|
||
" # print(\"'CIR' columns extracted.\")\n",
|
||
" # \n",
|
||
" # # Perform PCA on the 'CIR' columns\n",
|
||
" # pca = PCA(n_components=0.95)\n",
|
||
" # cir_pca = pca.fit_transform(cir_data)\n",
|
||
" # print(\"PCA performed on 'CIR' columns.\")\n",
|
||
" # \n",
|
||
" # # Create a DataFrame with the principal components\n",
|
||
" # cir_pca_df = pd.DataFrame(cir_pca, columns=[f\"PC{i}\" for i in range(1, pca.n_components_ + 1)])\n",
|
||
" # print(\"DataFrame with principal components created.\")\n",
|
||
" # \n",
|
||
" # # Drop the original 'CIR' columns from the data\n",
|
||
" # data = data.drop(columns=cir_columns)\n",
|
||
" # print(\"Original 'CIR' columns dropped.\")\n",
|
||
"\n",
|
||
" # Add the principal components to the original data\n",
|
||
" # Reset the index of both dataframes\n",
|
||
" # data = data.reset_index(drop=True)\n",
|
||
" # cir_pca_df = cir_pca_df.reset_index(drop=True)\n",
|
||
" # print(\"Indexes of both dataframes reset.\")\n",
|
||
"\n",
|
||
" # Concatenate the dataframes\n",
|
||
" # data = pd.concat([data, cir_pca_df], axis=1)\n",
|
||
" # print(\"Dataframes concatenated.\")\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",
|
||
" # Standardize the numerical columns (excluding 'NLOS')\n",
|
||
" # numerical_cols = data.select_dtypes(include=[np.number]).columns\n",
|
||
" # numerical_cols = numerical_cols.drop('NLOS')\n",
|
||
" # scaler = StandardScaler()\n",
|
||
" # data[numerical_cols] = scaler.fit_transform(data[numerical_cols])\n",
|
||
" # print(\"Numerical columns standardized.\")\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": "2024-03-18T15:11:19.532368Z",
|
||
"start_time": "2024-03-18T15:11:19.515962Z"
|
||
}
|
||
},
|
||
"id": "685463c2d6065b08",
|
||
"execution_count": 60
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Loading data from pickle file...\n"
|
||
]
|
||
},
|
||
{
|
||
"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 640x480 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"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 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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qzk21umpFuexWS87qyIb+iZhe6RjVrzpG9VrnqELx7K1FWFvt1e0ba3TTumq57IUdjDcbpmnqRCCqHV1j2tk5pl1dYxqPTf0+5dlYXuHR9WuqdN2aStWXuOd9/kI2HE7omdZhPX10SLu7xzWTX7/Lyj36rUubdOWK8hm9X5yv8uH4SypjqqU/qK6xqCq9Dm2s9Z1TvwMAAMDs5EP/AgAAMFv0MMhnBI0BiwhBYwAAIN/xAhkAABQa+hdg8fuTx47okYMDU46xWgx9/97ztKx85m+otI9E9NH/3qXEOy97/Q41xU59/Y71+ttnjp3Voqz6Epe+fP0qbVtSOuvHAlic6F8AAEAhoocBAACFJl/6l2AspWQmo2KnLeuBSP0TMT3WMqhHDw2qPRDJ6r4LVZnbrkuay3RJs18XNZXJ57JLmgy9efhAvx7c16feifiC12G1GHJY3wz6clgtb/ncmPa+ZMY8FST2xm1qHoPS8oXfY9ctG2p0x6aavApqCkQSaukP6VB/UIcGgjo+ElE0kVaxy6ZS92RwYZnbrhK3XaXuyfveCDQsddvVMxbTyx0B/apjVO0juf+/6/fY9dHtDXr/5rp5D0ecL+FESkPByZ/zCq9DJS7brMKmesaj2tk5pp1d49rZOabhcGIBq323i5rK9FuXNmldTXFW95tPBoNxPdM6rKdah/V697jO9jfW+ppi/fZlTbqgsWxe68uWXPUvyXRGOzrH9HTrsJ5rG9FYNHlqm9dp1W0banX31jrVlbgWvBYAAFBY8uX4CwAAwGzQwyCfETQGLCIEjQEAgHzHC2QAAFBo6F+AxW1395h+84f7ph137/lL9Lkrmmc9/3/v6NI/Pt9+NqVNy5B0z7Z6ffrSJrm5wjOAt6B/AQAAhYgeBgAAFBr6lzeZpql9vRN6cH+/njgypHjq3HweTseQtK6mWJc2+3XJMr/WVntlmSKcKJ0x9eqJUd2/t08vHB/RIszuKkiGJoOa7txUq8uWl8tmmXnAVDSZ1r7eCe3tGVffRFympHKPQ+VF9pO3kx9+j12+04RXBWMptQwEdag/qJaByXCx/uDCh9HlQonLpo9sb9BdW+rkddpyWksildH+vgm91jmmHSdGdbA/+Lb/jw6roQqvU5VFDlV6Har0OlXpdajC61BlkVOlHrtah0KT4WKdY1kJEJyJa1ZV6NOXNqnR78l1KQvu1L/hiVG91jmmA33BeZ1/+9JS/falTdpY55vXeRdaNvuXeCqjVzpG9UzrkJ4/FlAwnppyvMWQrlxRoXvOq9eWet+swvzwdolURi8cH9HengkNhRJaX1usq1dVqNZHkBsAoPBw/AUAABQiehjkM4LGgEWEoDEAAJDveIEMAAAKDf0LsHil0hl95L936/g0V2qvKXbqR7++/azCvNIZU7/5w73a2ztxtmWeVpPfrS9fv1qbCuzEdQDZQf8CAAAKET0MAAAoNPQvpxeKp/T44UE9uK9fhwdDuS4n6yyGtLyiSBtqi7WlvkQXNZXJ73Gc1VwDwbge2t+vB/f3aTCUmOdKcbaqvA7duqFGt22sUc1pAluCsZT29o5rT/e4dnePq2UgpPQME+PsVkN+z2ToWKnbrp7xmDpHo/P9LeS9YqdNH9xapw+dV68Stz0r+8yYptqGwnqtc0yvnRjVnu5xxRZpaKLVkG7bWKvfuHipKr3OXJcjSRoJJ9QyEFTrUFiheEpep00NpW4tKXWpodQ9o+C5dMbU0aGQdpwY02udo3q9ZyIrwZdXLi/Xpy9r0oqK3CzMm62F7l+iybR+1R7QU0eH9eLxgCLJs1vftKbKq3u21euaVZVy2CzzVt9id2QwpIcP9OuxlkGNx94e7Ga1GLppbZU+fuFSLS1z56hCAABmj+MvAACgENHDIJ8RNAYsIgSNAQCAfMcLZAAAUGjoX4DF6793dOkfn2+fdtz/uW2drlxRcdb76RyN6sPf2TUvJ7Ibkj6yvUGfvrRJTk6oBnAG9C8AAKAQ0cMAAIBCQ/8yvcMDQT24fzLsInwW5zdXFDm0srJITX6PIom0BkNxDYcTGgzG3xWeMR2P3araEqdqfa6TH05VFzsVjKd0IhDVidGITgSi6puIaYaZUJImQ6c21Pq0obZY62uLtba6+KwuXDKVVMbUy+0BPbCvTy+3B2ZV37muyuvQmupiNfk9eu3E6LyG31kM6bJl5bp9Y42S6Yx2d0+Gi7UOhXWu/RMZklZWFqnR79ErHaMKxmf3//NMihxWfWBLnT68rf5dgX2pjKne8Zg6AhGdCEz+/+0IRHRiNKpQPCW33apil00+p23y1mVTsfMdty67wvGUdnSOaUfnmEajyXmpu1A4bRZ96Lx6/dr5S1Tsmj7Ia74EIgm1DITU0h/U4YGQWgaC04YplrrtWlLqUv1bwscaSt0qcli1p3tcOzrHtKtrbNZ/G+aLIemGtVW69/wlWlGZ34FjC9G/BCIJvdwe0PPHAnq5PTCvAW/lRQ69f3Ot3r+59qyDOxe78WhSjx8e1EMHBnRkBn/nLIZ07epKfeKipVpWnt8/r/ksmc7o5faAnjgypKNDYVkNQ+c1lOjOzbVaXiDBg4XENE2Nx1IqcdlkGEauy1mUUhlTx4bDGosmtbbaK58rO2GvwExw/AUAABQiehjkM4LGgEWEoDEAWBjpjCnDkCy8KQHMGS+QAQBAoaF/ARan/omY7vqPndNeifyyZX59/fb1cz5R8b7dPfrbZ47NaY6GUpf+9/WrtaWhZE7zAFj86F8AAEAhoocBAACFhv5l5qLJtJ44MqQH9/Vrf9/Eu7bbLIaayz1aWVmklZVeraws0qrKIpVNESgST2U0HI5rOJTQYCihoVBcQ6GEJmJJeRw21fqcpwLFan0u+WYYSpBIZdQ1FtWJ0ahOBCLqHI2eCiCzWgw1lLq0vmYyWGxDbbEqvc45PTezNRSK65GDA3r44IA6R6NZ3Xe+qy9xaU21V6urvKdu3xlKc6g/qPv39unxw4PTvkeEM7Ma0urqYp3XUKKtDSXaUu87FUYRT2X0XNuwHj44oFc7RucldM1ps+j2jTVy262nwsS6RqNKnWOpe+VFDl3cVCa/x6GnW4fUPRabl3l9Lps+fsES3bWlTq4pghITqYxGIgkNhRIaDieUeMv/oTd+u77z16xhGDJNU91jMbUMBNUyENJAMD4vdeerrfU+fWBLnd6zskJ2a/5dOGo++peMaerwQEgvtQf00vGADvUHFzxg0WE1dP2aKt2zrV4rK70LvLf8l86Yeq1zVA/tH9Bzx4aVTM/+X8CQ9J6VFfrERUu1uorndCZM09ShgZAePTigxw8PnjHc8NJmvz66vUHblpQQijVHbUNh3be7Ry8cH1EgklSJy6aLmsr04W0NWldTnOvyFoXhUFw/er1XP93bp4m3/ExftsyvD2+r1/YlpfwcI+c4/gIsTqZpKpxIy2YxpnwtirOTzph66uiQHj4woNFoUktKXbp5Q40uaSrjb/s8M01Tw+GEUhlTNcVOnl+cUmg9TCie0gvHRzQRTWlZhUfnNZTKauHnebEiaAxYRAgam15HIKKH9vdrX+/kiQrra4t1y4YareCKEfNmKBTXYy2Dev7YiNpHIqoqdmr7klLduqEm76/QU0hSGVOvnRjVrq5xBSIJLSv36KoVFVpS5s51aYvGGy+mHzrQrwN9QdkshrY2lOjurXU6f2lZrssDClahvUAGAACgfwEWp9//2UE92zYy5RinzaIffnyb6kvmfrwlY5r67R/v066u8bN6/N1b6vTZK5rl5oQKADNA/wIAAAoRPQwAACg09C9np30koldPjCqSSKvG59TKyiI1+T15GcaSz0zT1Os9E/rZgX49dWTonAvNKi9yaGNtsTbV+bSuplirKr0qdtlm/PhQPKVHDw3q/n29OjYcWcBKFwebxdC6mjeDxTbX+1TkmP75HgjG9eihAf2cYLyzYrUY2lzn08VNZbqk2a+VlUWnFquapqlD/UE9fnhIvzwypJFwYs77q/I69NHzl8huMTQUTmj4ZIDjcHgyXGwsmpzzPs4lfo9dt22s0Z2balXjc+W0lngqo8MDQe3rndCB/qC6xmKKpzKq9jlVVeRQTbFTdSUu1Ze4VFfiUqXXKds7FpKG4im9dmJULx4P6OWO0Xn5mTtbN66t0mcub1Z1cXbDPnMtlkyrbTisF46N6OcHBzQYmr9/g8uW+fUbFy3V+lrfvM25mPRPxPSLlkE9emhAHYGZ/z1bU+XVR7c36OpVFbLR685YxjT14vGAfrC7Rzs7x8447ryGEn10e4MuXeaXhTCHWTs+Etb3dnbrFy2DU4YVrqws0ke2Nei6NZW8ZpsHw+GETgQictksWlXl5TmdodkcfzFNU/3BuAYm4moodakiy+Hg2ZDOmBqPJVXmtmc9zCaZzmhH55iebRvW4YGQosm0NtX5dOuGGm2uXzwXTzVNUydGo0qkMlpW7uHv+DxLZUz95PVe/WB3j3rHY7JbDW1rKNWHzqvXJc3ZCcFKpjM6NhzWoYGQjg6GNBFLaWmZW+9dWaFViyCEtyMQ0Z8/fvRUjsJbnb+0VL931fKsrfVPpTMaOnlcwWpIKyu9ctgWx/8p0zT1xJEh/cerXWobDkuavBDCB8+r1wc21/J3fh4dHgjqh3t61T4SUYnbpkuby/W+9VUzOj45H1IZU8eGwjrQP6Gjg2GF4imtqCzStasr1VB65jUGhfIeUiqd0fd29ejbr3Qqknwzp2ZJqUufv3KZrlheToDePEpnTHWORmVIWup35+z1LEFjwCJC0NjpmaapXV3j+t6ubr14PHDaMduXlupDW+t12TI/6ZpnIZpM69m2YT16cFCvdY7qTBeIWlvt1a0banT9mqpZvaGPN7UNh/XIwQE91jKo4dO8Qbextlg3rK3WdasrVeqx56DCwpdKZ/TY4UH9x6tdZzyxYduSEn36kiZtaVg8B8FyJZHKnLqiVedoRHUlLl3c5Nd7VlYsmoMG+eLIQEg7usY0EUtqdZVXFzf55XFkf4F6obxAPhsH+4P6xaEBHeoPyeu0akt9iW7ZUJ31K5cudqF4Snu6x9U5GtXSMre2NpTI66SvmG/D4YRa+oOKJtNaW11MmOkCSmdMWQxx0A3IY4u5fwHOVS8eH9EXHjg47bjfvqxJv37h0nnbb894VPf81y5FkzP/HVLrc+rL168i9BzArNC/AACAQkQPAwAACg39C/JFKJ7SE0fevKjqYmM1pFVVXm2s9WlTnU8b63yq9Tnn5TwL0zS1r3dC9+/r05NHhpSYImThXFNf4tIlzX5d3FSmbUtK53Su4RvP88MHBvTEkaG3LVjD29UUO08979uXls7ovLh0xtTu7jE93jKkp1uHFYynslDp4mO1GLpgaamuXlWhCxvL9IuWQf33ju45P58WQ7psWbk+sKVWFzaWnXHxYDiRUvdoTF1jUXWNRdU9FtVoJCmX3aqaYqdqfC7V+JwnP3eq2Gk74+/B/omY9vcFtb93Qvv7JnR4IKTUmRZ4nIbVYqj6ZPhYnc+p3om4Xu8en9UcC81ps+je8xv0sfOX5NXFuhKpjPb0jGtH55iGQnFlTKnO51R9iXsyzK3UpSqvc9o1S+FESq2DYR0eDOnwYEhHBkJqHwlrof9MXdhYqk9e1KitrJFQOJHSM63DeuTQoHZ1jmkuT31NsVP3bKvXbRtrsrYQvhCF4in9/OCAfrinR91jsRk/rsnv1ke2NejGddVyFuj6E9M0NR5LqdhpW9A1jW+sr/zuzm691H769ZVnUlHk0N1b63TnplqVuFmrNlOmaerIYEgvHAvo+WMjOjwYOrXN67TqxrXVun1jzaIItXlDMp2RzWLM63nx0x1/MU1ThwZCevrosJ5pHVLXW36HrK7y6n3rq3XDmkqVeRzzVlMuHB8J6zs7uvV824iC8ZScNovOX1qq966s0BXLyxfs/2Y0mdavOkb1TOuwXjw+olD89K/nNtX59LHtDbpiRXnBBkDGkmndv69P39/Vo4FgXJLksBq6dnWlPnRevdZUFy/o/k3TVN9EXIcHgmoZmOwD+ydi8jptumBpqW5cW62mcs+C1rDQ9vdO6K+fbFXrUPi025eVe/TR7Q26YW3VvIU0pdIZHR+JqOXk89oyEFLrUOiMQZtrq726ZUONrl9TKZ+rsP7mpTOmvr+rW//35ROKT3FRAosh3bGpVp++pGlOa9BN09RYNKmBYFz9E/HJ27d8PhCMaTiceFvegMdu1Q1rq3Tnplqtri7cv3+94zF99alWvdw+etrt9SUufebyZl2zqmJB14qNhBM61B/Uwf6gWgaC6p+Iq8xj14WNZbpuTeW8XGg7l8KJlP7lhQ795PXed70m8zqtun1jrT64tW7eA94HgnEd6JvQgb6gDvZNqGUgdNoLfRiSLl3m111b6nRR07uP+RTCe0j7eyf0V0+0ngrLO51sBhSGEykNBScveFDhnQzHXyyBn7FkWj/c06v7dvecygep9Tn10e0NunNTbda/T4LGgEWEoLG3S6YzeuLIkL6/q0dH3nIgZir1JS7dvbVOt6yvIQhrGumMqV1dY3q0ZVDPHB2e1Zu+TptFV60o160barR9aWnBHjzIlrFIUo8dHtQjBwfedlBxKlaLoUuaynTjumpdvswvVx69gZavEqmMfn5oQP/1Wpd6x2f2xsRFTWX69KVNWl+zsAeKFhvTNHWwP6hHDk6eNDIee/eb8GVuu27ZUKM7NtVMmeqMqb1xRZ/vvNalve9IoS9yWHXz+mp9YEudmvzZO9BYCC+QZyOVMfVs67B+sLvntEn/VsubB5X5XTE3x0fC+tGeXj16aOBtwQwum0XXr6nSHZtqtK6mmLCmOZgqPHZDbbHu2Fira9dU5tWJOYUolZ48mejF4wH9qn1UnWNReR1WbW0o0Y3rqnVZs5+wzXlgmqaODoX1fNuIdnePaTicUHN5kd67skJXr6rg6iCYlcXWvwC5diIQ0cH+oGwWQ6urvGrM4usRafJNmg/+165pX/s3lrn1/Xu3zfvf5Z/u7dVXnmyb0djbN9bo81cuI1gXwKzRvwAAgEJEDwMAAAoN/Qvy0bHhsB460K9fHh467cVss8VqMVRZ5FCl16HyosnF3PFURol0RolURvFURsm0qfjJr9+4P5kx5ffYtba6WBtri7Wp3qd11cVZOQd2LJrUo4cG9NO9fWe8SO1i5rJZtH1pqS5uKtPFTf4FuyhhNJnWYy2D+q/XutQzw3N1FzOfy6ZtS0q1fUmJzl9apia/e07nvyVSGf2qI6DHWob0TNuw0nkUDJWPbBZDFzWV6b0rK3TlivJ3LSKfiCX13zu6dd/untMuKJ2thlKX7txUq+pi58lAsZi6RyeDxQKR5Kzm8titk8FjPqdqil3ye+zqCES0r3dCg6Hc/f7PtiqvQ5+5vFk3rK3K2ZqU/omYXm4P6KX2Ue3oHJ32wmNWi6Fan1N1Ptdk+FiJSzU+l4ZCcR0+GSjRNRqdU7DVXG2t9+nXLlyqS5rK8uqc3HAipaMnA9iODATVNhxROJFSicuuWp9LdSVO1fpcqi1xqc7nUq3POWUPkcqYGg7FTwUjTIYixNQ3EdeurrF5+X//Vl6nVXduqtUHt9arqrgwLmIdjKU0FI4rmTZVX+JakPNXusei+tGeXj10oF/hOayJ9Hvsuntrnd6/uU6lBRCElUpn9OqJMf3yyKBePB7QRCwlm8XQuppinddQoq0NJdpU55uX5zyVMfX00SF9d2e3WgZmtibtTFw2i25eX617tjVoaYFcxDqWTOul9oB2dY0rnEhpSalb5y0p0YYa34Kcrx1PZbSza0wvHBvRC8dGZvR3eW21V7dvqtX1ayoLMpBwPJrUI4cG9ItDg2odCslhs2hdTbGuWVWp966qkH+OAV+nO/6SSKa1v3dCT7cO65nWYfWfDIU64xwWQ5c2+/W+9ZPrLAvpPPKD/UH956uderZt5IxjrBbjVOjYVSvK5xyqFoyl9MLxET3TOqxfdYxOGVj0To1lbn1ke4NuKqAAyGQ6o4cO9Ovbr3RO+X92S71PH9xar6tWVsg2x2BI0zTVOxHT4ZPBV4cHgjo8EDrtGsu3WldTrPetq9J1q6vmFBCVbROxpP7lhQ49sK9vRn1updehD22t152ba2f1tzBjmjoRiOpg/4Ra+kNqGQjq6FB4Vj/Db3BYDb1nZYVu2VCj8wtgDfzxkbD+7LGjOtg/84sQFDtt+tQljbpr88wDbnrGo3q2dUTPHxvRof7gnHrm9TXFunNzra5bXVkw699TGVM/2NWt/+/lEzP63tfVFOvzVzbrvIbSOe87FE/p8EDoVLDYof7gtH//NtYW6/o1VbpmdeWpY7SF4qXjAf31k62ngh/PxGpIV6+q1Ie31Wt9rW/W+4kk0moZCOpAX1AH+iZ0sD+oobM4rrK0zK27ttTp5vXVp35v5fN7SKF4Sv/8Qrvu3zuz38tzDSg0TVODoYQGg3ENhRMaCsY1GEpoODx5OxSMayiUeFdWSZHDqqtXVejm9TXaUu/Lq2MUM5XOmPpFy4C++WLHGfuMJr9bn79ymS5t9mfteyRoDFhECBqbNBFL6v69ffrR671n9cdcktx2i25eX6O7t2Y3fKUQHB8J65GDg3qsZWBe3oSq9Tl18/pq3by+RnUl85saW8iS6YxePB7QIwcH9GJ7YE5v9L7RSN24tlrnLSnJ+xe12RZLpvWz/f36zo6us/6ZvmJ5uX7zksZFdRWJhdA/EdMvWiZD807M8EQcQ5OBbu/fXKfLlvkX9Aoti0kyndHjhyevpnZ8JDLt+AsbS3XXlvqsPMf5/AJ5NiZiST24r18/er132gMWb9hY69M92+r1nhXlBZukPRiMq2UgpCKHVauqihb86gzpjKkXjo3oh6/3amfn2LTjV1UW6Y5NtbphbVXBhjFkTFNtQ2F1j0VV6XVqTbV3Qd/Imm14bJHDqpvWVevOTbVZSaJfCJ2jUf3y8KD29kwolkqrye/RRU1lumBp2YKFDY9Fknq5I6AXjgX0q47AlCdD+Fw2Xbu6UjeurdKmusI8CPaGcCKl9pGIvE6blpS6F/xvzBshbs+1Tb5x0Tdx+t/P5UUOvX9zre7cVFtwB8vfKWOaOj4S0VAorppilxr97qz2+6l0Rvv7gnrlxKhaByevfrqxzqcb1lQt2EnHuZAv/YtpmgpEkvK5bAV1kkMh6RmPalfXuEYjSS0pc+v8JaWLKojeNE1FkxlZDGX9DdnRSEKPHx46bYh6Y5lbV64o1xXLy7Wh1regfy9iybS+9nSbHjowMO3Yb9y1UecvLZv3GkzT1Gd/sl+vTdHfVnod+qPrVunSZv+87x/AuSFf+hcAAIDZoIcBAACFhv4F+eyNhTsTseTJIC/zzUCv9JvBXm+7/42v0xkl02+Egb09FCx5cqxpSv4iuyqLnKr0Ok5+OFXldarC61CZx16w56qapqnd3eP66d4+PdM6rFQeBzVZDWl5RZHW1hSrscytUCKtsUhSY9G3f4xHk0qf5ttYXuHRxU1+XdxUpi31JVm9MF4qY+qXhwf/f/b+Oz6uu8D3/9/TRzOjNiqj3mzZluVe0zupQBICS2gJbAjLDezCLnf5QXbv3nu/l2UXdmFZOiSBECAkpJNenR53x73b6r2XkTTt/P4YSbFsq4+qX8/HQ4+Zc3TOnI/G4zOf8zmfz/uj32yuGHN/0vnAZbNoTW6i1uYmaX1ukorT3VP2f6WytUe/fKdMLx1unJLXn6vsFpPOK/DqykWpurgoZUx9Apq6A/rt5go9vqd2Vp8T5opCr0tXLEpVic+j5w406PVjTZrs27o0I17/cFmRVmYnxqaQIwiGI9pd3dEfLtYypn7ac1Vxmluf35CrKxalTTpMY7zae4I63NClww1dgwFsEwkC9bqiIWSZCU6luG1q6wmqriMaLtbY1XfW78epZjGbdO2SNH12fa4Wps6ufriBUER7ajq0taJVW8vbdLC+c/D/p0lSQYpLyzPjVZqZoOWZ8SpKcU+on48/ENa+2g79eVeN3jzeHNNgPYfVrI+U+vTptTmzrg9jxDC0q6pdLx1q1KtHGkcNkzGbpMXpHq3OSdSanEStyk5U4hhC1CKGoc7ekNp6gnrnZIse2lk9bH/aiTJJunhBij69NltrchJnXV/nUMTQjoo2PX+oQa8fbTprv22H1awVWQlal5uktbmJKs2In/AYjxZ/QG+faNFbx5u1pXz00MnhxNnMunpxum5akaHSWT4Bu2EY2l/XqUd31+qVw43DhviYTdK63CRdtThNlxenTigIcKD9JRiOaMuJFj25o1KbjjapeYLh2olOq65ekq4bSn1a6vPMyvfZMAztqGzXb7dUjNjP8GzMJmlNbjR07PKFKUr1DB9uGY70ny96o9eNx5v92nS0Sdsq2iYdWux12fTJ1dm6ZWXmmM5dMyEcMfTCwQb9+r3yUSeuPZUv3qFPrMrSTcszxvS3GYah6vahoWKHG0YPFRuJxWzSBQXJuqHUp4uKUmZtqJthGHr+YIN+9PoJtfaML1xZio5funF5hj61JlsZCWeOPW/zB7WvrkN7azu1vz8gqKsv9hkLmQkOfaQ0Qx9e5lPmWcoxk0IRQ7/fVql73itXcIKV2wJvnP7+sgW64Cx9lg3D0PEmvzYda9LrR5t0pLF7skU+g8dh0Q1LffrYykwVpcyu+vGpDtR16rsvH9XhhvEHt15c5NXfXlKkwpSx5VWEwhEda+rWnppOHajr0IG6LpW1+CdcbzabpPV5Sbp6SbquKE6d1WMuW/0B/WDTcb14aPztWSuzEvTpdTm6dEHKWa9TwhFDJ1v82l/boX210cC2403dk26TOJXLZtH1S9P1V6uztTDdM+vuIRmGodeONuk/Xzs+oYlK4h1WffH8PP3VqqxR6851Hb3aWt6mzeWt2lreOqnvPUnKTnTqhlKfbljqmzN5JJvLWvTjN0/q6BjPnRvzk/T1SxdMy5hdgsaAeWS2B41FDEMnmvxq7g7I67apwOuK6cDYytYePbSzWn/ZVxfTmSPOL0jWrWuydV5B8qy/6d0dCOnFgw3Ri3kjegFT6HWpMCX6M94wkLaeoI43det4U7eONXVrX23nmL/MJmJ9XpJuWZmpy4tTZ/17PRV6gtHG8tePNuvFQw2TrjSdTbrHrmtLfPrEqsyzXlyfS/yBsB7bXaM/bK8a9yxQw7lqUaruvCB/Vl/QnqqzN6TXjjZqT02HLGaTFqZ6tDY3UUUprpg1lHYHQtp0tEnP7q/Xjsr2Sd0E8sU7dNPyDN20PGPEhs7ZpqY9OlNVZVuPkuNsWpaZoNLMeMVNwcB+fyCsJ/fW6o/bqyYUnJeZ4NDHVmTqxuUZk57BYjhT0ckyHDG0uaxVWyta1d0XVk6SUxvyk7XE54n590lZs18P7arWs/vrJ1zfSPfYo43KKzLnxIxJfaGIXjvaqCf31GlnVfvgemv/rC7XLU2PecN0W09QT+2t06Pv14yarn82TqtZ1yxJ180rM2ftzZ/TdfQG9Zd99Xr0/Zohs3XG2cxak5OkDflJ2pifHLNz9Inmbj13oEHPH5h4eOzyzHjdvCJTH5oDs0c0dvXp5cONeuFgw7CzcZlN0rLMBJ1XkKzzC5JV4oufcNDJQGP6Wyea9faJFu2t6ZjQd2BOklPXl/h03dJ05STNrg4Pw+kNhvXGsWY9f7BBm8taBjviJMfZdMnCFF1enKr1uUkx65zaHQhpc1mr3jjWrHdORmd1GyubxaSrl6Tr1tVZWuKLj0l5pkM4Yuj96na9dqRJm441DQnYToqzaW1/h9R1uUmTnun2bKraevReWau2lLVqe2XbsMF5a3IS9ZFlPl25KG1K6j3TpcUf0N7aTlV1BRSOGCrNSlRpSpyc03RDNhwxtLOqTc8faNCbx5vV3huSxSQtz0rQ5cWpurw4ddbdsJxrmroDeuVwo1461KC9tUNncbKYpBXZibqo0KuLFnhV6I3dtVIsdAeiMxMdbuhSiz8ofyAsfyCk7kBY3YFw/3JY3f3reoLhwRthqW671ucl6YJCr87LT56Smc0CoYjePhkNUX9njCHqXpdNFxel6JKFKdqQlxTTOsb2ijZ99+UjqmwbvUPINUvS9J0bSmJ27NM1dfXpb/6856ydYK9fmq5vXL5gykN9AcxvDHIFAABzEXUYAAAw11B/Aea/Fn9AT++r1+N7asc16Hg4C1JdSnTa1OIPqLk7qM6+sfdxMEkq8LpUkuHRUl+8SjLitSjNPab7aRHDUFdfSG09IbX6A7KYTf2BKzM/OVs4Eh3c9pvNFTrWNHV91CcjPzlOG/KTtSEvSenxDjV2BdTU3Rd97AqooatPTd0BNXYF1HbawGmH1ayVWQlalxftx1Hi80z7JKWH6jv1s7fKtLm8dVqPO5vkJ8dpfV6S1vf/O050QG11e4/uea9Czx+oj+kg1HNBcZpbVy5K1RXFaWcMrK5p79Wfd9Xoyb21I07gORZXLUrT315SeNYBpz3BsCpaelTW4ld5q19lLT2qbO1RZ19IdotZdqtZjtN+7JahyxWtPdpWMXx/qfkqO9Gpz63P0YdLMybUV7gnGFZ7T1BdgbC6+0Lq6ov2Zeka8jysrkBIHb0hnWjqVk2MQ5Fmq4uLvPr8xjytyEqYkeMPTI68taJNW8pbtauqfdiwoLNx2SxamuHRssyE/p94pbjt6g6EVNvep9qOXtV29KpmyPPeKRkrdTqTpEsXpujTa3O0KnvmJv01DEMH67v04qEGvXK4ccJ9tgcsTHVrdU6iMhMcausJqb0/HOiDkNmQOnqD0/o9tTwzQV+5uEBrc5Om76BnYRiGDtR16oVD0b6A4x0nFmcza2V24mDw2BJfvCwmqbMvpKbuaL2v2R99bOoOqLn/p7EroIrWnpgG5knRf+sbl2foupL0WRXS1BMM64WDDXpsd+24g1YsZpM25EVDxy5bmDJs/7iIYailO6Cajj7VdfSqrrNP1V0BvXaoQW0xGv83oDDFpQ8vjfbVT5sF49QihqG3jrfod1srzujPOhEmSauyE7TEF6+OvpDae4JqP+Xc0dEbivln93RxNrNuXJ6pT6/NnjX9nSOGodeONOlX75aprGXiwdcOq1nXL03XJ1dna0F/eOhAqNhAoNjB/j6+4xnjMF4eh0VXLUrTDUt9WjmD33mnK2vx63uvHNX2yvbRNx6FxWzS1YvTdG1Juipae7SvPySoOgZtNeNhUnQM/EeXZeiy4tQZD3g72til/++FI2dMAD1RFxZ69fXLipSXHKd9tZ16/WiTXj/WNKZ+17GyOidRt6yIZgxMZyD+SPyBsH75Tpke3lU9qTqW2STduDxDXzo//4yx0c3dAe2t6dDe2mhw3oG6znHVy8fDbjHpgkKvri1J14WF3lkzHtAwDL1wqEE/3HTijPa18cpKdOrWNdm6uMir4/3ZGPvqOnWwrnNar+c35Cfpi5cs0JUlPlnMphm/h1Tb0avvv3pMb59omfRr5SdHAwovLPogoNAfCGtnVZu2lLdpS1mrTrZMXTD72txE3bA0Ol7NZZ8dn+FTHW7o0k/ePKEt5W3j3nfgXPE3FxSMqf3eMAxVtfVqe2U0LLwnGFF2olO3rMwcsX5L0Bgwj8zWoLHm7oCe3lenJ/bWDbnJajWbVJji0qI0txale1Sc5lZxmmfUwI1QOKKajj5Vtvaooq1HFS1+nWzxa+ckA2xGk5ccp9s35Or6pb5pn41jNG09QT28s1p/fr9mxIvOFLc9GjrWHz5WlOJSgdclt92isha/jjV161ijfzBYbCJppLGwMitB/3z1IhWMMZ13utV29GrT0SadaPbLZbMoLzlO+d445Se7lOaxj/livLGrT7urO/R+dbv21HToSEPXtM2IYrOY9IUNebp9Q+6sueA6VVdfSG8ca9a+2g41+4Ny2czKTHAqK/GDn3SPY8zhH73BsOo7+1TXGZ19prylR0/trZ2SGxQmSdeWpOvO8/Nn3QwoUrTSuKemQ0/srRt21ojkOJvW5CZqTU7SuILHDMNQfWefylr8OtHs14G6Tr1xrDmm4Y9StHHosoUpumVlptblJs2aBrBTlTVHk9pfO9J01sYai0la7IvXyqwErcpO0IrsRKVOotNOiz+gh3fV6NFRvgfGym4x6UOL0/SJVVkqzYztjctYdrKs6+jVU3vr9Jd9dWe96ZbotGp9XrLOK4gGNE00YNEwDG0pb9Wfdlbr3ZOx62xztkbl2eRYY7ee3Fur5w82jPq58jgsurI4TdctTdfqnMQJB7wdru/Sn9+v1ouHhp/VZrwWpbn1sZWZumZJ+qxM3D/W2K2Hd1Xr+YMNY/qb0zx2bchP1nn5ydqQnyTvGEIB+0IRtfoDavEHtaemQ88dqB82bGsiPA6Lri/x6eaVmbNqdrWO3qBeO9KkFw83akdF27ivFRKd1uh73R88dmrjSihiqM0fULM/qBZ/QC3dwcFOoM3+gHZXt8d89q8VWQm6YWm6rlqcNuuCR8IRQ9sr2/T8wQZtOtIkf3Dk61K33aKLiry6ojhV5xd6xxVC1R0IqbylR4fqO/Xm8RZtrWid8Mwrp1qVnaBPrs7WZcWps+56T4peB++oioaLvX6sacwdIFLcdq3NSdTa/g6ruUnOcdeduvpC2l4RnUVic1nruG/Iue0WXbU4TR9dlqHlmbN/hrXy1h7trm7X7uoO7a7pOGsIkNVs0pqcRF20IEUXF3ljHgRoGIaONHbr+QMNeulww5AwubMp8XmioWMLU2ftdfTpAqGIatp7VdnWo8q2HlW3RZ+394bkslu0KM2tZf0zX/riHTH/3HT0BrXpaJNePNSoHZVtY77pl5Xg0IVFKbqwyKt1uUnTeoO4LxTR0cYuHajr7P+Z3MxEpzIpOrvvBYXJOr/Aq6UZkwvbPFDXqWf21+vlw6PPvDkSp9Ws8wqSdcmCFF1clDLhMLSO3qB+/OZJPbW3bkzbu+0WPfrX6yd1jTYWTd0B3b+lQi8fblQwbKjE59Fn1+fo/IIzZwQDgPFikCsAAJiLqMMAAIC5hvoLcO6I9Pcfe3x3rd463jymvr5mk7Q43aPVOYlak5OoldmJZ/SRH+jT09wd7YMyEFbQ4o8GRTitZhWmuLQ0I16L0z2zsu9TrEQH1Dfrvs0VMe3XNBFel20wWGx9XtK4+h0GQhE1dQfU6g/IZbcqO9E5a/ppb6to1U/fKtOBuskHFkwVi9mk7ESnmrsDkxr4meq2a0N+9N9vfV6yfPGxDY040dytX75Trk1Hm2L6uvPN0ox4Xdk/id5Y+tR3B0J6dn+9HtpZPamB7HaLSbeuyZEv3q6ylh6Vt/hV1uKfdLjPXOK2W3RtSbo+sixDFpN03+YKvX6sedKv63XZ9Om1ObplZeZZv5Mi/YNbjzR06Whjl440dutIQ9c59d5P1OqcRH1+Q67OL0iOeT+pUMSQP/BBqFt3X1gVrT3aWtGqbRVt4w5jGo3bbpl1YXwlPo9uXZOtDy1Ok20KAz8jhiF/IKyuvpBa/EG9ebxZLx1qmNZwjpl0fkGyvnJRoRb7PNN63PIWv1442KAXY/xeO61mRQxDgeka6DcMu8WkKxel6bPrcrQofXrf21Mdb+rWY7tr9dyB+pj8H7eaTf199L3q7AsOhhPWdUYfY9E3fDzMpmjAzu0bcrUyO3Fajy1Fz9WvHG7U/VsrdLxp6kI5ZpLFJF21OPpZnqkJwg3D0DsnW/TLd8rHHZQ3mrW5iTKZTDpc3zWuUPFYy0p06oal6bppeabSY3wdNFa9wbDu31qpB7ZVTvv/5enkddn0ydXZumVl5rQHQobCEf12a6V+s7lCoRini1rMJiXF2dQ8Q9kCA5LibPpIqU8fX5V11iDp6fLm8WZ9/9Vjqu+M3fgwp9Wsz6zLUVKcTftqO7S3pmPGgpYHxvp8fkNuzMfEjEddR6/+7ZWjMR23O5tkJ8XpCxcW6LpFqbLPwHi1UMTQwzur9ct3ymI+1v/8gmStzknUlvJW7a7uiPk5aTRxNrOuKE7VDaU+rc1NmvCY5lip6+jVL98p03MHGiY9zsdtt+jzG3L1qbU5Z4xbqm7v0Y6Kdm2vbNOOyraztrvYLSb9+JblwwZCEzQGzCN/fOeELitKmRU3owzD0M6qdj22u1abjjaN64sh3WMfDB4rSnGrozekyrYeVbT6Vdnao5qOPoVncAqYnCSnvnhevq4pSZ/xAegNnX36444qPbGnVj3B+dVBxWYx6c7z8/W5dTnTPnPT2XQHQnrtSJOePVCvHSOkaA8JHvO6lJ8cfcxNilN1e8/gYPU91e2zYpaVQq9Ld3+oWKtypr8R7HTdgZDePN6sVw436b2yllEbEixmk3zxDmUlOpWd4FRmokNpbofaeoJDQsXqOqZnxpMzymeSbij16Y7z8mf0YnZAW09Qzx2o15N763SyeXyNjqcHj+V7Xapp79XJ5uiN15PN3TrZ0qOyZv+owSKxVpji0pcvyNflxakzGloxEAax6WiTXjvaNO73WIp+v6zMStDK7EStyk5UbnKcAqGI+kJh9YUi6g1Goo+hsHpD0ed9oYh2Vrbp6f31U5ZSXuLz6NNrc3TV4rSYfO9NtpNlKBzR2yda9MTeWr13snVcF1z5yXE6ryBZG/OTtSY3UW77Bze5g+FI/zmjT3WdvaodmP2ko08VrT2qi2GD0NlszE/Sly4omLEZqQb4A2G9fLhBT+6t074JzoDii3fo2pJ0XVeSPmyAWncgpNqOPtW2fzBT1d7aDu2p6ZhM8UcUZzPrI6UZ+uL5eUoeQzjXVApFDL1xrEl/3lWjnVWTm52jOM2tjfnJykxwDoaJtfgDah0IwPIHp/WG/YqsBH12XY4uW5gyI+fl3mBYb51o0YsHG/TOyZaYNlAVel0ymaQWf3QGn5m6IrFZTLp0QYo+uz5XpRkzc5NtwNHGLj13IHpzfrQgpOE4rGadX5Csy4tTdXFRiuKd1sHw0vL+GSTLWvwqa412+proccYq3WPXJ1Zl6aYVmaOGYE+1YDiirRVteu1Io9441hyTOm26x661uUnKTY5TKGIoFDYUikT6H6PPg4PPDTV1BXSgriNmgcgF3jh9pDRD15f6pjzAZywCoYgONXQNCRabyOwnBd44XVSUoouKvFqZlTDha9jajl69cLBBzx9smFB9Uoqeqy4vTtHlxalanO6Z0TpyKGKoon8G2KrWHlW196iyrVdVrT2q7+wb83k0xW3X8sx4lWbEa3lWgkp88ROadaQnGNZbx5v14qFGvRuD7win1az1eUm6qMirC4tSYtoxOWIYOtEUDW8+UB8NFjva2D1tN14SnVZtzE/WBYVenVeQPDgTSjhiKBCOqC8YvS4JhA31hcIKhCLqDUW0t6ZDzx6on9QMb8Mxm6LB9JcsTNWlC1LGHOz92pFGff+14+O64f2PVyzQX63OnmhRAWBWYJArAACYi6jDAACAuYb6C3Buauzq01N76/TEntohA3isZpNKM+K1OidRq3MStSIrYV4Hg00VwzD0Xlmr7ttcMea+ZDaLSXnJcSrwupTvdSkrwaG+UEQdvSF19oWij70hdfT1P/YG1dkXGux777ZbtDonUevzkrQhP1kLxjg571xkGIY2HW3Sz94uO+vEa9PJYpKKUt1a6ovXEp9HJRnxWpjqlsNqlmEYausJqqp/0rKqth5VtfWqqi3a7+D0vh0eh0Vrc5L6w8WSVeCNm5Z/w8MNXXrk/Rq9MMZJRuc7myU6cd+FRSm6bGGKMic4OXDEMPTOiRY9tLNaWyvaYlvIeW59XpI+uixDly1MkfO0yT+PNXXrt5ujk6HFYrDrx1dl6YLCZJ1s9utof6DYsabueTeuaSyyE52q64zNOLdFaW7dviFXVy5KG3WSwFA4orLWHh1p6NKRhm7VdvSqqy+k7v6gq+5ANFjsXPw3GU6qO9o/9GMrMsc14WGbP6h9dR06VN+lpu7AkPe5qy/62NkXkj8QnrG+xbPJ1YvT9OULC8bcv2skPcGwWv1BtfYE1eYPqrUn2ke+rSeoVn9Qx5q6ZzykdjpdVOTV56cpCKs3GFZ5a48ON3TpmX112lU9deM8ZptV2Qm6fUOuLiz0xqROGTEMdfaGouM7egJq8wfV4g8Ojvdo7QnqYH2XasY5EfRctiYnUZ9em6OLF3inNBDEMAy194RU29mrytYePbSzRntrz43PssUkXVacqk+sytKanMQpvz7qC0XU1RfSwfpO/WDTcVWdIyGbUnSs2o3LM/XptdkTvgYaTl8oos7eoNpPaddo7wnqTzurdbSxO6bHmq0sJumKRWn6zLqcaR0/1djVpx9sOq5Xj5wbAeNWs0k3r8jUX5+XN63jfCKGoUffr9HP3iqb9nHpMyHFbdNn1+XqlpWZirONfzzMWBiGoY5T6h2NnQH9fntVzAM2Z6PMBIduXZOtm1dM3ft7NgP1jd9vr9RDO6tjHlScmeDQly8sUMQwtL2yXTsr21Q7xnySeIdVf7p97VnHOhE0BswjH/rhG+rqDepvLijQtSXpozYqToX2nqCePVCvx3fXqnyGbz5NtbzkOH3x/DxdvXj63+vK1h49sK1Szx6on9epzlI0PON/XbNIJTOQVB6OGNpe2aZn99dr09GmmCe1zia3rMzUVy4qVLxzejs1+ANhvX2iWS8fjg70numZHqaC1WzSjcsz9Ncb86Y9Cd4wDO2obNeTe2v12tGmmJ0vTNKsuwGyNCNeX724QOvzkqftmBHD0P7azsFwsep53qibnejUbRty9eGlvkmFmk60k2V1e4+e2lunv+yrj0kqvsVs0rKMeEUMQ3WdfWrqCsyKz/VVi1L1lYsLpzUF3jAMHazv0pN7a/XiwcaYNswsSnPr0oUp6g6EhwSLzUQA5IAEp1V3XVSgm5ZnTnsdrtUf0JN76/To+zXzfoa2Ep9Hd11UoI35sZ9d7VQdvUEdrOsaDGHZWt52TjQuDtiYn6QvbMyblps/UvS7r6a9V5uONum5Aw061hTbmxMWs0n5yXGq7eid8c4tDqtZHy716Y7z8pTmmdo6XG8wrPr+kNyGrujjyWa/3jnZoq6++fl5tpikCwq9+uiyDF1U5J2WcOmuvpCONnbraGNX/2O3jjV1x7yjp8dh0fkFXl1U5FVmglNmk2Q2mWQ2mwafW0wmmUySpf//7c6qNj1/sEHvx7gjRmaCQ5cXp+rqJelTfmOtNxiOdhps7NLh/s5rU/H+StHAqQWpbpVmxKswxSXDiIaahfvD8sKRD8LyBp63+oN692TLlF7Xr81N1M3LM3V5ceqE68uVrT16cm+dnj0QmzpvrLjtFvWFItM+w8xIClNcumRBii5dkKLSzPgzOps0dvXp+68eG/eMvIvTPfrdZ1bPSLsqAMQSg1wBAMBcRB0GAADMNdRfgHNbOGLocEOXqtt7lea2a4nPc0aoCybOMKJ9uB/cUa0t5a0Khg15XTble10q8MYpP9nVHywWp8wE54Tu7wXD0Xug0znwbLYIRQw9va9O97xXPuFJ/8ymM/sTnzpC7NT1dotJeckulfQHipX4PFqY6p7w/5muvpCq2nrkD4aV4LSpwOua0QnkO3tDeuZAvR59v2bGA9ymW5rHrgsKvbqo0KsN+ckTmjhuJMcau3XPe+V67ei5Mbh7IjITHPpIaYZuKPWNaXL0sha/7t9aqRcO1Mds8slzUaLTqmtL0nX9Up9KfB41dAX0513Vemx3bUwmB85Jcupz6z/ot9/VF9Kx/r5ZRxqij8ebuufl+JuzsVtMWpubpJ1V7THpj+awmnVtSbo+tSb7jEm1A6GIjjR2aV9tp/bVdmhfbee8Hycy4Lz8ZBWluvT0vnp19k2ur7/FbNJNyzPG1Ac3FDF0vLFbe2s7tK+uUyeaugfDxQjyPLvVOYn6wsZcnReDfvrdgZDKWnp0srlbJ5v9OtEcnSC6uq13VoyvmUkLU926bUOOPrQ4fcx1za6+kHZUtmtbRav21naqobNPrT3BmIRRzke5SU7duiZHH1nmm9B1mWEYau0JDhmrVNPeq7rOPtX0L8/0mITZoCjFpU+sytJ1S9Plto997HBvMKyD9V06UNepus4+dfaF1N0XGgza7A70B24GQvN+jPtYWEzSVYvT9Ln1uVqc7hnTPl19Ie2v7dSe2g4dbexWqz+gjt7QYHA634NDrc5O0GfW5ejiBSkTCikcCANq6g6ouTugZn/08YPloJq7A2rpDszouMeZ5LSa9am12frcutwJZw0YhjEYwtsdCMvf/9MdDMsfGLp+R2X7ORMAeSqvy6bPrsvRx1dljfv7LxSOaF9tdDL7xq6AWv3Rz+5ggKk/OKvGfMyERKdVn1ydrb9anaXEuLEHTJ+qqTugzWUtOtns7w/x7v8sBwc+06HB5Z5AeFa3r3yk1Kd/uXbxGesJGgPmkQ/98A0d7U+UXJDq0lcuKtRFRbFJzh6JYRjaW9upx3fX6JUjTXOi8moxm2QxKSaNqgXeON15fr6uWpw2pQnaknS0sUu/21qplw83arZ/z1vMJq3KTtCh+q5JN5RbTNJn1uXozvPzp+UmfFmzX88eqNdzB+rnRAhIrEKfUt12/eMVC3R5ceqUnjd6g2G9c7JFLx9u1NsnWubEOSPRaZU/GJ5Uo4fdYtItK7N0+4ZcpUxRqnMoHFF7b0htPUG9c6JFT+2rO+duWG/MT9JXLi6MeTihYRiq7eiLzvjTf4Nuf12nmmbR4P/pkuax6zNrc3TziswJdQgYTyfLrr6QtpS36ok9tdpS3jbRIs85VrNJf7U6S3ecl6cE58QuZocTihiqauvpvwnUrRNNfh1u6Jr3AbFnU+Lz6FtXFWvpFAWvhMIR1XX2qbqtV1XtPdpT06GXDzeecw3oa3ISdddFBTGZOaknGNbh+g9CxQ7UdaryHJrpZCQrshL01xvzdEHh5G8YDzSel7f6VdHao4rWHlW29Qw+nwt1t1hyWM369Nps3bY+d1IzDTd09mlXVbuq23sHw8TqO/vU0Nl3zt6EGOB12fTh0gzdtDwjJjPYhfu/6441detIY7eO9YeLjXXGhvlqeWaCPr02W5cVp066c22bP6jDDf2BYv3BYhWtPbO+nWK6JDqtuqHUp5uXZ6ogxTXq9n2hiF4/2qQn99Zqe2X7NJRw/klx23VxkVeXLkzRutwkPX+wQT9+88S4wxptFpPuuXXVtM54BQBThUGuAABgLqIOAwAA5hrqLwAwPUIRQ4ZhyDYNk5ida3qDYf15V40e212jmv5+FXaLSakeh9LcdqV57ErzOJTmsSvVY1ea2xF99NjHNUD9XGEYhrZVtOmx3bV641jTrBxkmJ3o1PpCrzKT4lTb1qOTjV2qbusdc39ok6RlmfG6sMiriwpTtCjdPS0TZO6obNN/vX5Ch/vHS53r0j12rc9L0vVLfVqXlzShcUxVbT363dZKPbO//pwfhDxWNotJFxel6PqlPl1QmHzW76WuvpCe2lunP+2sVn3n5PurpbjtirOZVXWO9pVNddv1iVVZunlFhpJddrX6A3p0d60e2VWj1p5gTI6xMT9Jlxen6mSzX/tqO3Wkseuc6uttMZt07ZI0fWZdjorToqEo/kBYz+yPfo4n+9lzWM26dU22blufowSnTYZhqL6zT/vrOrW3plP76zp0sL7rnOubHCuL0z36wsZcXbYwddTg3VA4opMtfh1t7Nbhhq5ooFizX3UxOFfNd1kJDn12fa4+Uuo7Y1xrMBzR3toObS1v09byNh2o65iVdcCpkJ8cp/rOvphMAJzgtOrmFZn6q1VZSo8fPpywsatPB+q6dLC+M/pT1xWz74Nzgdtu0Q1LffrEqqwz+jcbhqHy1h7tr+2MBj/WdupYY9eUf55tFpNcNsuMjqfwumzqC0ViEhY74Lz8ZH12fY425CUNXi9FDKO/vtGhvTXR9/lks3/KQx1zk5z60gUF+su+Om2raJvio02PvOQ4fXpttm5YeuZ5+VRtPUHtr+vU/tqO/sfOKf2sue2WmH6OZlKC06rPb8jVJ1ZljZrpYBiGjjf7taWsVVvKW7WnpmPevA9n43XZ1N4bikmIaHKcTZ9bP3rgWFVbjzaXtWpzWau2V7ZN6ftrs5h0foFXb59onvPjg+JsZt28IlOfWZszYv1iQFN3QK8dadKrRxq1q6p93oTumiQ9eNtaLUwbGipG0Bgwj5waNDZgVXaCvnpx4aQG9ocihtr6Ey1b/AG1dEcfm/sfozMh+Cdb/GnhcVj0sRWZ+qvV2bJbTHpyb50eeb9mwjPxnKooxaU7z8/XFYtSh22o7w2G1eIfeP8Cau8JKdx/Khw8IZ5yajROWfXuyRa9daJl0uWcaksz4nXD0nR9aHGakl129QTD2nS0SX/ZV6cdkxwwm5ccp3+6ulhrcpImtL9hGOoJRj5Iy+4Lqav/eXdfSK09Qb1xrFn76zonVc7p4LZbdNWiNN1Q6tOidLfeONas5w80aGtF66Qrb5csSNE/XrFAGQkjz2gTCkdU1tqjY43dKm/xqysQVm8wrN5QRH2hyODz09d19s2dlPJUt12fWx8NVGrvCeq+zRV6en/9pC4CnFaz/mp1tj63PkdJY0jDjRiGajt6dbLZr9qOPrX1BNXeE1R7b0jtPcHocv/zuX4BFu+wTnrmkwFXLUrVly8sUL539IH9pwuGIzrR7O8PFeseDBcb7yD1+W6iyc6nXoCEwhEdqmhRRf+MJ9Xtp/y09czZ4BWH1RyTm10JTqvuOC9Pn1iVNe5OUuEhgWL9oWLNfpW3+M+Z2avGwiTpYyszdddFBRMKdRuYGbGq//Nb1dYz+Bmu7+g9Z24SjcVFRV59+cKCMc/MEY5EG9H31HZof22HDtR16URz95xvpJpqi9Lc+sLGPF1ePPoN44hhqKa9V8ebunWsqVvlLR+EicXq+3g+SXRa9YWNefr4qiw5rGM7JwdCEb1xvFlP7a3V1vK2edPIOJXW5SbqpuWZuqw4dczvc28wrL21Hdpe2a6dlW06VN8Vk5vW81VmgkO3rsnWR5dljCs8r7zFr01Hm7TpWLMOzIFr5tlidU6ibl6RoSuK0874TJ9o7taTe+r03IH6OVvvnY0sZtOErtmtZpO+/9GlunhByhSUCgCmH4NcAQDAXEQdBgAAzDXUXwAA80XEMNTVF5JhRPstTkdw1HzX0NmnJ/fW6ok9deOe1NhttygnKU6ZCQ51BcKq7+hVXWffuPvfO6xmlfg8WpGVoOWZCVqWlSBfgvOs9Ze+UES1Hb2qae8dfKxp71NdZ69sFrN88Q6dX5Cs8wuSleyamgm3RxOOGHr2QL1+/naZmufARNGFXpcS46yqae9VwyTGK2UnOrXE59HidM/gozeG/wZ1Hb36/bYqPbWvjqCfYSzPTNANpem6alHamPvMh8IRvXKkSX/YXkVA3gSU+Dz69NocXbko9ax96HuDYT13sEF/3F6linNwsu1YcNuj4ys/uSZbvmEG3Ycjht463qwHd1RpV3XHpI4X77BqZXaCDtV3jft7cb7wumy6eEGK1ucmaVd1u1442BCzMWD5yXG6bUOuritJl81iVkdvcDBQ7Gj/mKiTLf45M5ZvMlLcdl22MEWL0j3adLRJW8snP85yQHKcTbeuydZ5Bcl6v7pdW8vbtLOqTT3B6f3+NJukK4pT1dYT1M6q9mkdX7E0I16XLUzR5QtTVZDiUltPUI/trtGfd9WoxT/5wC+L2aQPLU7TZ9ZGz00H67t0oK5TB+uj4WKxGAM+Vukeu9blJem1I00z0i/dYTWrOM2tVLddW8pbY/45W5+XpGtL0lXf0ae9/SFMHdPcl3lDXpK+eeVCpcc79PS+ej24o0rV7VMbrpoUZ9PSDI+W+OK11OdRiS9eaR67+kIRvXa0SU/vq4vppNGL0z06ryBZh+u7tK+uY1rHppokfWpttv7HhQVy2iwyDENvHm/Wj944MWUhtg6rWRnxDvniHcpI6H+Md8oX75DDatYLhxr0/IEG+YOxeR8SnVZ9fFWWPrEqSx6HVUcaurTvlGCx6QrrzUuO07evKtYSn0cPbKvUgzuqp/3aymI2qTjVrVSPXdsq2mJ2/DSPXV88P18fLfXJekq9vKmrT1sr2rSlvFVby9umpX7ntlv0t5cUqsDr0p92VOvN481TPkbLYTVrcbpHyzLjtSwzQcsy45UR71BTd0BP7KnV43vqYtI+kRRn02fX5egTq7LkslvkD4S1vbKtP1ysRZXT9Flem5uob11VrAKvS8eauvVfm45r6zwIKLSaTbqh1Kfb1ucqLzluyO+auvr02tEmvXKkSe9PY7hYituu3mB42jIhLihM1n9/bPmQdQSNAfPI2YLGBlxc5NVdFxdqYerQ//C9wbDqO/tU19mn+o7ojYDajj7Vd/apuTugFn800Gau/2fNSnTqU/0DaV32oameoXD0IuChnTXaWzu5hi9JWpjq1hWLUtXeE1Rzd1DN/aFiLf7AvA2pyYh36Lql6bq+xHdGmvWpqtp69Mz+ej2zv35Ss3PcsjJTX724cMig6IGbW6fe2Bq40dXqD6grEA0Tm8ttYmaTtCEvWTeU+nTZwpSzJgE3dfXppcONeu5Aw6RuSLhsFn3l4gLdsjJLZpPU7A/qWGO0gfFYU7eONnbrZLN/3s5e44t36PYNufrosowzBoNXtfXo3s0Vev5A/aQa49x2iz61JlufXpujeKd1MOzjRLO/Pxgo+h6fbPbP66CEpDibrlkSDc1bku7Rzqp2Pba7VpuONk3682UxSR9dnqEvnpd/RuKwYRhq7g6osq1Xla09qmyL/lS09szbz3ai06q/Wp2lNTlJenp/nV4+3BiTGwUum0UfW5mpz6zNVqrng/c5HDHU6g+ooSugxq6AGrv6oj/dQbX2hlTZ6ld1a8+8eq8z4h365Jps3bgsQ83+gB7eWa1nD9RPukE3J8mpv724UJcXp561A49hGKpu79X+2k4dqO/UgbrOeR2yYreYdM2SdF25OE3vnWzRcwcaJh2KlBRn099eUqgPl/pGnNmtvf9mzPaKNm2vbNOJ5rkRtjsRA+GxVotZT+6p1cH62HR0uGpRmv7mwnwVnBYE2dkb0r66Du2p7hicAWWuB2iORX5ynNbmJml3TXtMw5vzk+N0e/8NY6vFrLaeoI731+GONXXreFO3TjT5Y9ZAP9slx9kUZ7eoJgY3njLiHfryhQW6tiR92DC3E83dempvnZ470KA2ZkmakESnVdcv9enG5RlacFo7RiAU0b66Du2oaNf2yjbtq+0gRHMC3HaLblyeoVvXZCvzLCHThmHoaGO3Nh1t0mtHm+b1d950SHBadcNSn25Y6tPRpi49uadOu2sm3waF2CjxefTPVy/SojEGogLAXMAgVwAAMBdRhwEAAHMN9RcAADCaUDiiN48365HdtdpZ2TbY99zjsCg3KU65SXHKSY5TbpIzupwcp+Q42xl9RSOGoVZ/UHWdfarr6FVdR9/g8/rOPrX4g3LZLFqY5tbyrAStyErQojT3GQE986H+0h0I6YGtlfrD9qpZ1WfIaTVrfV6SLij06oJCr7ISP+iPMzDWpbo9Otaluq1XNR3RSZlrOnrV1ReWSVK+N64/UCxeS9I9WpTuntAkuhPR0t/v+c/v18yJcU8DAWy5SXFq8QdU09Gn2vZoKN9EJ5VPdFr7QxGcyoh3KN8bp/MKvGcMRB4PwzC0vbJNf9hepXdPtk74dc4FFpN0eXGabl2TpRVZCWMKvYwYht463qI/bq+cdBDWTMpPjtNVi9PU1RfSrqp2HW3snrJxnL54hz61Jls3Lh/fRKX7azv04I5qvXqkcU6Py/O6bDEJQxqr4jS3Li7y6pIFKSrJiB8yTqEnGNbLhxv15J66mIxnlaJhIBaTSXWTGLM5WWtzE+WwmrWlvG3C5+Pxyoh36IpFqbqiOFXLsxKGvM+NXX16/kCDnjlQr5NzvB+szWLSR0oz9Ln1OcpJin43tfoDev1Ys1470qRtlbF/z80maVV2oi4vTtVlC1OUcZb+xlK0rvPsgfp5EQDpddn0hY15unlFphzWaHDfU3vr9Mj7NartmJr/Ww6rWYvSoqGyS3welfg8Kkxxy9o/VqEnGNbrx5r03IGGmIbnzRSvy6Z/uGyBrl6SNuT7PhwxtOlok36/vSomk2LHO6wq8Xm0NCNeJRnRYDFfvGPUOkZVW4+e3l+vZ/bVTSoweCYVeOP0v65ZrBVZCWf8LhCK6OFd1bpvc8WkxmzF2cy6oDD6HbcgxS1fvEOJcaMHl3cHQnrxUKMe310bs0Bem8Ukw9C0j1G1mk26fUOuvrAxb8gY9PrOPv3qnTI9s79+yup0+clxWpoRr9KMeC3NiNeidM9gGfyBsN443qQXDzZqc3lrTL4b8pLj9Kk12aps69HW8jYda+qe9GuOx8VFXv3/rioeEpBb0dqjh3ZW6+l9dTEbQ5uXHDckVKw41T0kYO10wXBErx1p0sO7YpNPkui0qijVrb01HdP6eU50WvW1S4v04VLfkP/D0YDCFv33G8djHnbmtJqVHu9QmseuVLdd6R6H0uIdSnPbleaxy2ox69XDjXr+YEPMguxMkq5clKqPr8rS8abuaQ8Xk6Jj8T+3PkefWZej3mBYv3q3XE/sqZ2W7/affXy5NuQnDy4TNAbMIyMFjUnRE+ClC1MkRSsqdR19ap3ng55XZCXoM+tydOmClGEHgZ9qf12nHt5ZrZcPN86r4JOp4LZbdOWiVF2/1KfVOYkjhnKcLhwxtK2iVX/ZV6/XjzVNKOgm3WPXmtyk/lCx3nk9o0Gh16UbSn26riT9jLCkkRxv6tYLBxv0wsGGCTcS5iQ51d0XnvfnigE5SU59fkOurl/qO+vMJ6cqa/brnvfK9fLhxklVJOMdVmUlOlXW4j9nZgGyWUy6ZEGKrl/q0wUFyWe92GruDugv++r0xJ7aSTfEOaxm3bwiU06rORoo1tqjqrbecyZcJSPeoc+sy9GNyzMUd0pAYYs/oKf21umx3bWTCn8cYLOYtC43SR29ITV2RQNL5/JNpPFYlZ2gT63J1iULUwcbcgd09ob01L46/XlX9aQ/yyuzEvT1y4qUEe/Q/rquaKhYbacO1neqfZpnjpgJvniHPr4yUzctz1SS64OOE73BsF490qQn9tROOrBjZVaC/n9XLVRxWjRkwh8Ia1d1f7BYRZsON3TN+QDekYwUHnuwvlOP767Vi4caJh2eZzZJNyz1aWV2gvbWdmpPTYfKmv3T/t7G2cwq8Lp0uKFr2m62WMwmrclJ1EVFXl1UlDLYAcUwDB1p7NZzB+r14qHGmM24mOaxyzA0r+vKw8lLjtMlC1J06YIULc9KkMkkvXOiRQ/vqtaW8rZJv/7CVLe+enGhLihMlslkGrzh/9TeOu05R8ODshKdau4OxLxOuzwzQR8uTVdrT1DbK9u1t6bjnKk3T4eBDlqfWZetpRnx2lfbqU1Hm7TpaNOUzwqFc5PZJG3MT9YNS31Kctn01vFmvXGseUY6NzmsZv2PCwv0yTXZZ9TjAWCumw+DRAAAwLmHOgwAAJhrqL8AAIDx6OgNqsUfVJLTNqYB2FNhPtVfajt69ZM3T+rlw40zVob85DhdUOjVhYVercpJPGOC87HqDYZls5jHNOZpqnX1hfTEnlr9cUd1zPoxTsZ4A9jCEUONXX2q7ehTbUd0rNHAY2dfWPEOi3wJzmigWLxDGQkOZcRHl112y1lfM1aONXXrga2VeulQw5zoY1/gjdOGvGRtyE+S02bR/trOwYmEYzkBqy/eoWuWpOkTq7KGDbAZi321Hfrj9iq9drRpTgSw+OIdunpxmq5Zkq5F6e4h3wkdvUHtru7Qrqp27apu18G6zkl9Zixmk1ZkxutjK7N01aLUEcMSRlPX0as/7azWY7tr50w/zuxEp64tSdc1S9JVmOJSfWefdlS29f+0x7SfpNVs0trcRF2yIEUXL0g56ySwZ3O8qVtP7q3T8wfq5+S4EI/DohuW+nTLyiwV9o9BaOsJ6vWjTXr5cKO2nxK2Git5yXG6vDgaLlbi84xarzIMQwfru/Ts/nq9eKhhTr3PcTazblmZpU+vzVaaZ/hxpe09Qb15vFmvHW3SlvLWCY3XlaJjhldmJ+jyham6ZGGKvC77mPeNGIbePNasB7ZVxSxAb7okOK363LocfXJN9pCxdwNCEUNvHm/WQzurtauqfcLHcVrNWpQeDROLBovFq8DrGnMf1qauPr1wqFHPHajX0cbpDfqZLJOkW1Zm6q6LChXvHD7s0jAM7axq1x+2V+ntEy1jem2LSSpO86g0M17LMxNUmhmvvOS4cY15P104YmhrRav+srdOrx9rnhN5A2aT9Nl1ufrSBfmjXps0dQf0y7fL9Jd9dWMey5XotOqSBSm6rDhVG/KidcSJMgxDB+o69fieWr14qHHO1CsGrMxK0N1XF6soZfiQnmON3frJWycmHTic4rZreWb8YLBYiS9+xP9Dp2rzB/Xq0Ua9eKhxUueumZIcZ9P/vGKBPrQ4bdjv+vaeoJ7cW6eHd1WrcRzhgIlOq0oz47UsI0HLsuK11BevxLiJB30frO/Un3fV6KVDDbMqFH00NyxN19cuLVLyCN/3wXBED++q0b3vlU8ooNBhNWttbqI25idrbW6SshOdctstY2oXC0UMbSlv1bP76/XGsaY59d6eymKSbl6RqS+en68U99D3+nhTt370xgltLpvacPLF6R498NnVg9+NBI0B88hoQWPnCrNJuqI4TZ9em63lZ0ncHYumrj49vqdWj+2undak+ljKTnQqGI7ELDU5O9GpBaluLUx1aWlGvDbmJ0/qQmBAe09Q922u0EM7q+d1cMd4FXpd2pCfpOuW+rR0DA1eI4kYhrZXtOm/Xj8x7UnBc0WBN05f2Jinq5ekj3tw8bHGbv3q3TK9fqx5iko3Pdx2y6RSyMdiRVaCbliarqsWp415dqVwxNB7ZS16bHet3jnRMqfPEzaLacINtROxMNWtz63P0dWL00a8GRSKGHr7eLMeeb9GWyvapq18U8VhNU9L45LVbNKHFqfp1jXRUI7RxKpReaYVp7l147IMBSPGtDVMr8tN1F+tztbFC1JGPUcfa+rWk3tq9dyBBnX2Tezmj8UkXbU4TbUdfdpf1zltM+mcanVOoj6+MlM9wbC2lLdpa3nrlN3MctstuqI4VTeUji08tjsQ0osHG/T4nrqYzR4xnaxmky4s9OqaknRdXOSV02ZRZ29I2ypa9V5Z9CcW4YunSoqz6cLCZF1UlKLzCpJHnQEsFDG0tbxVzx2o1+vHmudcg/mpSnweXVuSro7ekDYdbdKJKZ4JallmvC5dkKJLF6aqwBs3bB36RHO3/ryrRs/ur5/0zBWrcxKVnxynlw83Tnld6myyEp26sjhVG/OTVdbi1/bKNu2qap+WG+Buu0Xr85J0fkGyNuQnKycpTp29Ib10uEFP76vX/hjMJDSbWM0mhQ1DM9mamZng0JWL0lTT3qt3T7bEbOaVAR6HZU7MSDpVLGaTzi9I1jVL0rUqO0G7qzv09skWvXeyZU50KslNcirZZZfbbpHbbpHLbpHbbu1/HFhnVZzNovIWv94ra9H71dM3201RiksfLvXp2pL0Mzq7DARuvnmsWW8cb56WOsaGvCR9+0PFgzP7AcB8M58GiQAAgHMHdRgAADDXUH8BAABzzXysv+yubtcPXz+hA+PoqxTvsCrfG6d8r0vZCU5FDEN9oUj0Jxx9DAwsh8LqCxnqC0X71GQlOrU+L1kXFCbP6z4HfaGInjtQr99vq1Rl29RMVuiyWeRxWOR2WOWxDzxalRhnVVGKS4vTPSpO80x5ANh0q27v0R+3V+sv++pmVf9Qr8umDfnJ2pCXpPV5ScOGfhmGoer2Xu2t7egPH+vU4YauYftb2ywmZSY4lZngUGaCU1mJTmUlOJWZGF2X6rbHNHixur1Hf95Vo6f21s1In86RJMfZdOWiVF2zJF0rshPGHH7iD4S1t6ZDO6vbtauqXdVtPQpFDCXF2QZ/EuOspy3blOS0KjHOplS3PSbj/05V39mne98r19P76mZlcJ7XZdOHFqfp2pJ0lWbEj/gZq+3o1Y7KNm2vbNeOirZRJ8xMdFqV6rEr1R39Sen/yU2K0+qcxFH7iY+kLxTR60eb9OTeWm2vnP1jTkp8Hn18ZZauXpI24mesxR/Qpv7QsZ2V7eMeF5bgtCon2aWc5Dgtz07UxpwEFSQP3098NMFwRG+faNGz++v19onmWfkZlqJ/962rs/WJ1VlKGmfwSVdfSG+daNY7J1pU1darQDgSPTc4PzhfJMbZlNh/nkjqf54UZxtz8Mdodle36/fbqvTG8dk93tJls+jTa7P1mXU5Y/7/e7i+Sw/tqtaLhxpGHCfotJr7w1I9KvHFa4nPowKvK2bhskcbu/TcgQa9cLBh1k9MvyjNrbs/VKzSzPGN9z/R3K0/bq/S8weHvte+eIeWZcZrWWaClmVE39tYf9edqs0f1POHGvTo+zWqaO2ZsuNMRlGKS/9y7WKVjmGM46kO1XfqB5uO6/3qs4cDpnvsurw4VZctTNWqnMQpmdi5szek5w7U67E9tTo5xWOOJsvjsOhvLynSTcszxlyX21reqp+8eVKHxtA/3mo2aYnPo2WZCVqeGa/lWQnKiHfE5Lxc19Grlw836qVDjWMqy0y7YWm6vn7ZgjF/BwbDEb1ypFEPbq8+4++zmk1alO7Rsoz4wUDCnCTnlATAt/oDempvnR7dXRvz8YmxlJvk1LeuKtaG/OQx79PiD+iX75TpyT2jBxQuSfdoY0GyzstP1oqsBNknGMx+qo7eoF453Khn9jfMqUDTyxam6CsXF6rA6xpxu3dPtuhHb5yY0vPg/3f9Yl1X4pNE0Bgwr8z2oDGTpPMKknXTikzZLSYdbezWkYYuHWnsVmVrz4TCY6xmk7ITncpNjlNecpyKUlw6v8Cr9Pjh07nHozcY1mO7a/XAtso5Ezi2LDNeX9iYp4uKvDKbTOrqC6msxa8TzX6dHPhp8atmmMT95DibFqS5tSDFpYWpbi1Mc6soxT3ljfN7ajr0nZeOzPoLgVPZLCalue2q7eibVPiR3WJSaUa8VmQnamVWgpZnJYy7AWgsQuGIfr+9Sve+Vz5nUltNkpb1NyDUdvTGpNHDJCnVY1dGvENFKW5dvCBFFxV5J91Ic7C+U796p1zvnBxbUvpskOi06oZSn25anql8b5xONPu1s39Wjh2VbZMaTG8xSTlJcSpMiYYTXrUoTbnJk7uZWtvRqyf6QyA75sBAfynaeHBxUYquKE7VeQXJ6g1FtKemQ7ur27W7ukMH6jtjHj62OidRt6/P1QWFyeO+2C1r9uvR3TV6Zn/9rLuxNhKL2aTLFqbopuUZWp+XrPJWv7aUt2lLWat2VLbFNIQjKc6mj63M1MdXZo44G8hIDtd36U+7qvXSKI3Ks0Wczayrl6Tr5uUZWnrajbZjjd16/mCDXjhYH7NwUynaoH79Up8+sTpLC1PHf8HaGwzr1SNNemx37ZxpOHBYzbq2JF1/tSpLi9I9Q34XMQwdbujSlrJWbalo0+7q9kl9dlw2i1bnJOq6knRdujBlQg3qhmHoQH2XnthdqxcPNcQ87CaWTJLW5ibqmiXpumJR6ohhl4ZhqKylR++VtWhzWat2VrWPqSOHSdHzg9dtk9dll9dlU77XpY35ySrNiJ9wPaM7EA3oevZAg3ZUtM2JwM3MBIeuK0nXtSW+wVmpBpS1+PX60SZtOtY8ro5dw0l0WrU8K0EXL0jRJUVepY7zvNzRG9RTe+v0yPs1qu2YvQ24p8tLjtOVi6KzcC1OPzOUOGIYOtrYHe34UNGmXdXtMQmPMpuk0v7Q6fMKklWamTDijaJjTd16el+dnj/QoNYYzmA4XeIdVq3IStDK7AStzk3SxUsz1NUX0uuHG/XCnhq9d7JlWupLCU6rrlqUputKhnYu6g2GtbmsVZuONenN481zOiDMZjEpKyHatpPqtutks1+HGrqmpSPdwHfE1UvSdUVx6llnoQlHDO2r7dDbJ1r0zsmWWTEDmC/eoaUZ8Vrq82jpOGcmOlV3IKTtFW1692Sr3j3ZMmonqfFKdFp1bUm6bij1aclZzlfDqevo1ZvHm/XGsWbtqGqPafBrgtOqv7+sSDcs9c3I7NAAMF3m4yARAAAw/1GHAQAAcw31FwAAMNfM1/pLxDD0wsEG/W5r5eBkmGaTlJ3oVL7XpbzkOBV4XdFwsWSXvC4bfQbGKBwx9NrRJv1ua+W4Jo5zWs0qTnOrOM2jReluFXhdSnBa5ekPE3PZLTEL2ZirmrsDenhXtR55v2ZG+n657RatzE7QhrxkbcxP1oJU14T/X/QGwzrc0KXjzX71BsPyuuzKTHAoK9GpFLd9zCEMsdQdCOmZffV6aFe1qqYoLG8sEpxWXbwgRdcsSdP6vOQpCeeYSeUtfv3ynXK9cqRxposil82iy4tTdE1J+oTfa8MwVNPRq701nWrxB+S0mpVyWqCYzTL5kISxKGv263fbKvX8wYYZmTh9OA6rWdcuSdfHVmZq6TjDbCSpqatPrx1t0itHmnSy2a+2nqCS42yD4YMDwYQZCdFQwowEhxJd9imrv9R29OqP26v05N7ZE/6Y6rbrM+tydPOKDLntEw+umy3Kmv16aFe1ntlfP2veYyn6Wf7Eqizdvj5XSa6JjeNt6Q+TefN4s9p7gkp127XYF68SXzRcLD85dqFiIwlHDG0pb9Wj79fo7RMts2rMictm0ZcvKtAnVmVN6juwOxDSvtpOmU1Sgdc14fF8kxUxDL15rFkPbKuaNWPVLCbp9o15umNj3oSDfAzD0BvHmvX8wQYdbexSituuVdmJuqw4VUt9Y+//PVmGYWhXdbv+tKNabxxrnlWfZUm6alGavnF50bjHLUnRz85Lhxp173vlKj8lrC7dY9eKrIRosFhWghane+SIQSDTaPbXduinb5dpe0XblB9rvDITHPr2h4p1foF3QvsbhqEjDd3aU9shm9mkolT3tL2vpwpFDL10uFG/3VKhslmUm2E1m3Tbhlz99ca8Cb8nRxq69LO3T2pzWasGqqnpHvvgWLP1eUlKdtljWOozlbX49dyBej27P7ZjmmNpeWaCvnZpoVZmJ455n1DE0BN7avXrd8vVNoZxeC6bRatyErQuN0kH6rpGvS7LTHDokS+sl8NqJmgMmE9ma9CY12XTR5dl6KYVGcpOPHvITE8wrGON3TraGA0eO9LQrWNNXeoJRmQ2SZkJTuX1h4nlJsUNBotlJDinpZGtJxjWo+/X6IFtVWM6Mc+EjflJ+vyGPK3NTRxTxb0nGFZ5i18VrdGZDFLcdi1MdSvFPbVf3iMJhCL67ZYK/XZr5axqBDvd8swEfbg0XVctTlOC06a+UESVbT0qb/GrvKVH5a0fPJ6twT85zqaV2QlakZWgVdmJWuLzTFtDoyRVtPbo3145OisvAgasyErQhxan6Yri1CHBgb3BsOo6+lTT0aua9uhPbUevqvufd/aF5LZblZHgkC/+g5+B5Yx4p9I8U9uwu6emQ798p0zbZvH7uy4vSTcvz9BlC1OHbUCIGIZONPm1o7JNO6ratXOY4DG7xaR8r0uFXpcKUlwqSnGpoP+G7FS9z529If1+e6Ue3FE9qxoZByTF2XTpwmi42Pq8pBHfh75QRIfqO/V+dYfer27X3pqOcQe82S0mpXkcWp2TqI+tyNTyrPGl+59NdyCkx3fX6o87qtU8i2c1yE1y6qblmbqh1Dfs91cgFNHe2g5tLmvVlvJWHarvGlNDU4o7GkiYmeCQLz56s2JhmlvLM2OToC1JNe29+tlbJ/XS4Zm/sXY2pRnxuml5hj60JG3UGxQRw9CuqnY9f6BBrxxpHFfwyukzVS3PStBlC1NGDIMaK8Mw9ObxZv1g0/FZGyKUleDQx1dl6aPLMs4abnI2PcGwdlW1a0t5q7ZVtKm2o1fhiNEfcBUNuUp22eR12+WN638cWOeyK8FpjelN+47eoP6wvUp/2lE9qwLHSnweXVuSrqsWpU04iLgvFNH7Ve3aU9OhZn9AcTaLvC6bUvrfU6/LLq/brqQ425Rfl1S19eiBbZV6Zn/9rAspjHdYddXiVF1X4tPKMc6yVtfRq9ePNWvT0Sa9X92u4ar/5v7w0vzk6AySBd7+Tl/Jrgnf1DtdKGLorePN+tPOau2qmp0zgBWluHRFcaquXJQ27g494YihI41d2l7Rpp1V7apuj54zbBaTrGazrGaTrGbTB8sWU/+66HOvy6YVWdGGx7Gep041MPPXX/bV6d2TLcP+W8+0rESnVmYlaFV2glZkJ6ooxTX4WT5bJ8veQEjvV7fr7RMtevtES0xnJ3JYzbq4yKtrS3y6oDB51Hp1MBzRjso2bTrarNePNc3KoHSn1azc5LhoWHxSnHKS45TTHxyf7nGccSM9FI7oWFO39tZ2an9th/bVdg65qTZZpRnxunpJmj60OG3cN5vrOnr1zsnov/vW8tYpD/JOdFqjoWKn/KROQdvNQNjmuydb9F5Zi3ZWTSzYNNFp1eqcRH241KcLCr2Tvi7s7A3p3ZMteuN4s96dZMDfhxan6RuXL5jRti8AmC7zdZAIAACY36jDAACAuYb6CwAAmGvme/3FMAw1dgUUihhKddtj1t8X0fd2S3mr7t9aqR2VQ/vYpXvsWpTu0aL+YLHiNLdykuLO+SCxserqG+i3XzXhfl8JTqsWpbmVkeDsD3OzyO2wym23yNP/eOrzgcdzIXAvHDH09okW/Wln1Rmf3fGymKSiVLfSPQ55HAPvo3Xwebyj/7k9GqoX77Qq3WM/J97ng/Wd+vlbZdpc3jqlxzGbouN1Bn6SXTalexxamZ2gCwu9E5p8e7ar6+jVH2Y4CCveYdXidLcuW5iq65f6JjQp6nAihjFqv/PpqL+0+gN6eFeNHnm/Rh3jHNM1EXE2s5L7x30kxdkGxyesyk7U2tykaQ9DmQ5t/qAe31OrP79fM2Pj1Fw2i/K9cbqg0KtbVmbOWFjVVKpp79Vju2v11N7acY9PjCWbxaSrl6TrrgsLJjyWZ7bbXd2uB7ZV6c3jzdN6XItJinfalBxn09LMeH12XY4Wps5MUMxUqmjt0Z92VOnpGQ4pNElalZ2g2zbk6qKilEm/nmEYOtniV08wojS3fcb/f2wpb9XP3jqpg/Uzn01ikvTJNdn6HxcWyGWfH3U6i8WshMQ4PfV+jX666ZhONs3MhPcum0W+BIcuXZCiD5f6lO91xeR1W/wB1bb3Krk/aHomrntC4YheOtyo+7dW6uQsCXQr8Xn0+Q25urw4dcLvSWdvSL/dUqGHd1UPGa/ktJr764uJWpeXpCW++MHxrE1dfbr5vm2jju392qVF+uy6HILGgPnkxp+8rd3Vs2dQ9Lq8JH1sRaYuW5gyoUGFEcNQIBSJDnCexhCmkfgDYf15V7X+sL1qRi+0TnXZwhR9fmOeSieQAj9bHW3s0v978cisqJwOyIh36PpSn64vSR9zJcowDLX4gypv9aupKyCH1azCFLdyk5wz3lBsGIaePVCvH71+YtZ8lpdlxuuqRWm6clGqMhKcM12cSdtR2aZfvVOmXdWzI53c67LpI8sydOOyDOUmnz30cSQDwWNHm7rUG4woxW1XodelrETnjN0EbOrq072bK/Tk3roZDydM89h1+cJUXbEoVSuzEyccNhMxDJW1+FXZ2qNg2JDTZpbDapbDapHDapbTau5/tMhpM8tuNU/pDD99oYie3V+n322rUk37zM3kcyqbxaTLF6bqphUZWpubNO6/v80f1NaKVu2p6VCLPyin1ayM/hlPosFiTqXHO6a1YX5fbYd+9PoJ7a6Z+fNFvMOq60rSddOKDBWneSb0Gn2hiN4+0awXDzXqRFO3mv2BwZmpMhOcykp0DgaLTddMVb3BsH6zpUK/31al0CxJuNmYn6RPrMrWRUXeedOZork7oPu3Vuqx3TXTHoRlklSY4hoMYNmYn6y8CXzfzQUNnX36444qPb67dkaD3RxWs84vSNZ1S326sNA7qfNmiz+gt4+3qLKtR519IfniHYOhYjmJcdPa4WtbRat+8ubMNZSbJHnddqV77MpIcKrE59FlC1NVmBKbhtyZ1tTVp2cPNOgv++piGsw1XlmJThWnuqOzZqZ7tDwzfsSbxWPppFDe4tc7J1v01okW7aluH3f4lNkkrc1N0nUl6bq8OFUex8Q6YoQjhvbWdOilw416Zn+deoLTf54Y6Dy4ON3T/+hWVsLkr4M7eoPaX9epfbWd2lfbobJmv3oH2o3MJln6A/IsQ5ZNslpMsphMSnDaVOLz6IpFqcpJis13REdvUM8faNDje2oHZ8SNBbvFpCsWpemm5RlakzO2QPlY6wmGtae6QzUdvTKkwWsRu2XgGuWDaxW71SSH1SKn1TylnRAHQvXeONasN483j3n2mXSPXd+8sliXLpz8DV4AmCvm+yARAAAwP1GHAQAAcw31FwAAMNdQf0Es1HX06niTX3F2s4pS3EqawOSVONNAv/0HtlWpeoR++1mJTi1Kc/eHu0X7ZvniZ2ZQ91xzuKFLD+2s1ouHGsbUz9kX79CyzHgty0zQsox4LfF55mWQVSxtq2jVz94q0/66zgntn+K2a1lGvBane5TitinJZVdyXDRMJclli/lk23NJiz+gP+2o1iPv10xqss6ReF02Faa4VOh1RR9TXCpMcSvFZZvRc8x01l+6AyE9uadOf9xRpcYx9k88G5Okkox4rc9LUl5ynJL7w8SSXXYlu2yKO4fPJYFQRC8dbtCDO6p1tDG2gStuu2XIeKXMBKcyE53K6n+e4LSeM9+XfaGIXj7coEfer9WBCZ6TT5WbFH1fPY4PAjY9dqvcA8/7g04HnmcmOCY9UfFccbLZrz9ur9JzB+snPI7q1PFQqW67EpzRANOEOJsS+sNLE/p/XLZzIyx2QFtPUI/vrtXDu6pjPhm7SdEA0xS3XSnu/keXXame6GOK2658b9y8DCU8lWEY2nS0ST9/uyymE8OfjdVskttukWvgxxY9pxSmuPSRZRnzLjTv1DpMKBzRg++e1L3vlsdsLFVWYnScbkp/HcPr+qC+ceq6c+EaJmIYeut4i363tUJ7ayf/vTfAajZpaUb84Pk3rj/E22U75XPc/1l29beRpLjtMTt+V19IW8pbFY4YykhwaqnPM2Lmzq/eKdO9mytGfM14h1VP3LFeXo+DoDFgvqioa9cv3zqpR96f/oH9AxKdVt1Q6tPNKzJVEKNEy9moqy+kP++q0R+2V6mzb/pDmiwm6dqSdN22IVdFKfOr4jQgFDH0px1V+tW75TOWOBxnM+vKRWm6YalPa3IT52VjZIs/oP96/YReONgwI8cv8Xn0ocVpunJRmrIS53642OkGZu755TvlE24onwyH1ay1uYm6cXmmLinyzprQxlirbO3Rr94t04uHGqfleA6rWQtS3YM36Er7bxrNx3PEgFDE0MuHG3T/lsqYBiiMx8JUtz5c6tMNS31Kcs2/G9KGYWjTsWb99M0TqmybnlA3h9WsohSXivpvAC1Od2tVduK8bjwoa/br+68d07aKtmk9rtkkZSQ4lZ3o1PLMeF1X4lPBPAkNOpu6jl7d+16Fntlfp6m6LMlKdGqpL15LMzxa2n8edttjNzvSXNDqD+ihndX68/s16uqbmhvGUvSmfV5ynPKS4qKPyXHKTY5TbtL0BoBNJ8Mw9OqRJv387ZMxPydbzSYVp0U79vjiHUr39D/2L6d57OfETTXDMLSzql1P7q3Ta0caxx3KNVZOq1kL0/oDxdI8Kk51a2Gae9whXuPtpBAxDLX3BBU2pEjEUMQwFDGi68MRQ4YhhY0P1lvMJuUkOmP+HdzZG9KTe2v10M7qMQcyjYfZJOUnu7Qo3T0YKrYoza1kV+waxucKwzC0t7ZTT+yp1cuHGyfcjlGU4tJNKzJ1fUm6EumEOSLDMHSooWswdGy4DicfX5mpr1xcOOHwPgCYqxgkAgAA5iLqMAAAYK6h/gIAAOYa6i/A7BeKGHrjWJNeP9asjt6gvC57f98st4pTPYp30gdmspq7A3psd42e3Fs3GCQUZzNracYHoWLLMuOVOs9DJaaKYRh6/Vizfv72SZW1DB+i4LCatSTdo9KBMLfMeGUQmjeqrr6QHnm/Rn/aUa3WnokFriQ4rVqU5taCVPfgWJJCr2vWjtOZifpLIBTRCwcb9MC2yjGHruQmObUhP1kb8pO1NieRPqCjMAxD2yvb9OCOar19omVc+w70x1+aEa8SX7T/cnaiU/GOcydIbDz213bokfdr9PLhsfXZ9zgsKu3/TlyemaDSjPhZe36YTRq7+vTQzho9vmf08T0JTquWZcZr+cB7nBlPP+dRBEIRvXCoQX/cXjXusa0Wk7Qg1R2tc2QkaGGaW2meaJjpfB1vPRGhiKFn99fp1++WT3jsSVKcTRvykrQxP1l5yXFy2S1yOyxy26xy2S3zdgzacM5WhwkEw3rpcIPufa9i3IFjbrtF63KTdF5Bss4rSFZOUlysizznDYxVu39LpTaXt07oNaxmk84rSNaVi1J16YLUOXUN3h0I6WP3bRs1mPGz63L0D1csJGgMmC/a2/0KBMKq6+jVr94t13MH6hWZgv9lAymtXrdN3v40y3SPQ8uzEnR+QfK8Dqc4XVdfSH/aWa0Hd1RNaHC/zWKS45SKkUkfXMieek078DQvOU6rcxJ1y8qseRnKdDaVrT3615ePaEdl+5Qex2k1y+OIJj0vSHXp4gUpurw49ZxJiH/3ZIu+98pR1XT0TWh/j8OivGSXXHaLnFaznFazHLaB5xY5bNF1zv51iXE2lfg8ykw4Nz7HhmHorRMt+tU7ZToyibR9q9mk9HiHEp1WJcbZlOi0KinOpkSnTYlx1g8e+9edK0EVAw7Xd+nn75zUuycndgFwNolO6wehCeluLUrzKN/rktV8bjY8RpOdm/XbLZUxD88zKTrrT3ZSNIwpOzEu+pjkVE5i3DnTKBkMR/To7lrd91652ntjE2bqsJpV4HUNhooV9d8Qykp0zuuAvOEYhqGXDzfqv14/oabu2IWuuO2W/s9snHL6P7vZiU7lJMUpI95xTjY+lrf49et3y/XS4ckFQSY6rVqeFb1BsTQjXkt93Kg4VSxuGNstJhWluFWQ4lJecpzy+wPFcpLizukbFqFwRE/urdM975VPevaTwhSXblqeoetL5mdg5mS09wT1/MEGPbm3VsebJhdoWuh1aW1uolbnJGqJL145SbH5rpvrnSxD4YhePdKkP+6o0sH6rkm9lttuGbxePi8/WS77uXHNPB6dvSE9f7BBT+yp1bGm0a//nFazPrQ4TTetyNTyzHg6OUxQdXuP3jreoj01HWrtCWphqlsfKfVpUbpnposGADNirtdfAADAuYk6DAAAmGuovwAAgLmG+gsAfMAwDFW398piNind45DlHB0jMlVCEUMvHmzQswfqVd7il8dh1RKfZzBUrDjVfU72r4+V3mBYT+2t0++3V6m+c/ixgLlJTi1K96g4LToeamCy5LnUT3Em6y/hiKE3jjfrd1srdeC0MVQDYSob8pO0Pi/5nBnrOxXKmv16aFe1ntlff8ZEvxaTVJTqVonPoxJfdDzJwlT3ORdWEwtt/qCe2lenx/fUqqY9Ohm7uT+AaVnmB8Fi+d64c3KsWax09YX05N46Pb2vTiea/YPv8fLMBC3Pir7P+clxc+o8PJsYhqHN5a36w7Yqba1oO+s2mQkOlWbEq7Q/QHaxz3PO5ATEQm8wrEd31+r+LRWjjm21W0xamZ2o8/KTtTE/WcXpbs4fpxipDhOORMe33vte+bChpiZJS3yewWCxFZkJ1J/H4WB9p363tVKvHWnSaHE7NotJG/OTddWiNF2yIGVOhYud7tH3a/S9V4+NuI3NYtLTf3OeluR5p6lUQxE0BsTYQNDYgONN3frF22V643jzmPY3SUrz2OW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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 ... CIR1009 CIR1010 \\\n",
|
||
"0 367.353553 744.646447 717.646447 ... 277.353553 726.646447 \n",
|
||
"1 470.646447 409.353553 332.353553 ... 486.646447 491.353553 \n",
|
||
"2 447.646447 130.353553 96.353553 ... 96.646447 271.646447 \n",
|
||
"3 239.353553 175.646447 532.646447 ... 94.353553 225.353553 \n",
|
||
"4 219.646447 110.646447 293.353553 ... 308.353553 132.353553 \n",
|
||
"\n",
|
||
" CIR1011 CIR1012 CIR1013 CIR1014 CIR1015 RX_Level \\\n",
|
||
"0 367.353553 802.646447 818.646447 466.646447 767.646447 -33.465374 \n",
|
||
"1 403.646447 334.353553 210.353553 102.353553 0.353553 -34.892422 \n",
|
||
"2 73.353553 125.353553 169.353553 182.353553 0.000000 -38.436975 \n",
|
||
"3 154.646447 171.646447 277.646447 317.646447 0.000000 -21.918230 \n",
|
||
"4 131.353553 102.353553 126.353553 162.646447 0.353553 -21.603535 \n",
|
||
"\n",
|
||
" First_Path_Power_Level SNR \n",
|
||
"0 -39.074609 37.700000 \n",
|
||
"1 -53.179491 95.794118 \n",
|
||
"2 -49.812107 55.384615 \n",
|
||
"3 -25.863535 200.859375 \n",
|
||
"4 -23.232193 152.723684 \n",
|
||
"\n",
|
||
"[5 rows x 1025 columns]\n",
|
||
"Column headers:\n",
|
||
"Index(['NLOS', 'RANGE', 'FP_IDX', 'MAX_NOISE', 'FRAME_LEN', 'PREAM_LEN',\n",
|
||
" 'CIR0', 'CIR1', 'CIR2', 'CIR3',\n",
|
||
" ...\n",
|
||
" 'CIR1009', 'CIR1010', 'CIR1011', 'CIR1012', 'CIR1013', 'CIR1014',\n",
|
||
" 'CIR1015', 'RX_Level', 'First_Path_Power_Level', 'SNR'],\n",
|
||
" dtype='object', length=1025)\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(\"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": "2024-03-18T15:11:25.612754Z",
|
||
"start_time": "2024-03-18T15:11:19.643974Z"
|
||
}
|
||
},
|
||
"id": "79c2c23691b26753",
|
||
"execution_count": 61
|
||
},
|
||
{
|
||
"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": "2024-03-18T15:11:25.619078Z",
|
||
"start_time": "2024-03-18T15:11:25.614299Z"
|
||
}
|
||
},
|
||
"id": "12e16974341e6266",
|
||
"execution_count": 62
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"The selected code is performing data standardization, which is a common preprocessing step in many machine learning workflows. \n",
|
||
"\n",
|
||
"The purpose of standardization is to transform the data such that it has a mean of 0 and a standard deviation of 1. This is done to ensure that all features have the same scale, which is a requirement for many machine learning algorithms.\n",
|
||
"\n",
|
||
"The mathematical formulas used in this process are as follows:\n",
|
||
"\n",
|
||
"1. Calculate the mean (μ) of the data:\n",
|
||
"\n",
|
||
"$$\n",
|
||
"\\mu = \\frac{1}{n} \\sum_{i=1}^{n} x_i\n",
|
||
"$$\n",
|
||
"Where:\n",
|
||
"- $n$ is the number of observations in the data\n",
|
||
"- $x_i$ is the value of the $i$-th observation\n",
|
||
"- $\\sum$ denotes the summation over all observations\n",
|
||
"\n",
|
||
"2. Standardize the data by subtracting the mean from each observation and dividing by the standard deviation:\n",
|
||
"\n",
|
||
"$$\n",
|
||
"\\text{Data}_i = \\frac{x_i - \\mu}{\\sigma}\n",
|
||
"$$\n",
|
||
"Where:\n",
|
||
"- $\\text{Data}_i$ is the standardized value of the $i$-th observation\n",
|
||
"- $\\sigma$ is the standard deviation of the data\n",
|
||
"- $x_i$ is the value of the $i$-th observation\n",
|
||
"- $\\mu$ is the mean of the data\n",
|
||
"\n",
|
||
"The `StandardScaler` class from the `sklearn.preprocessing` module is used to perform this standardization. The `fit_transform` method is used to calculate the mean and standard deviation of the data and then perform the standardization.\n",
|
||
"\n",
|
||
"**Note:** By setting the explained variance to 0.95, we are saying that we want to choose the smallest number of principal components such that 95% of the variance in the original data is retained. This means that the transformed data will retain 95% of the information of the original data, while potentially having fewer dimensions.\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "b36814c942066d6"
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"## Data Mining / Machine Learning\n",
|
||
"\n",
|
||
"### I. Supervised Learning\n",
|
||
"- **Decision**: Supervised learning is used due to the labeled dataset.\n",
|
||
"- **Algorithm**: Random Forest Classifier is preferred for its performance in classification tasks.\n",
|
||
"\n",
|
||
"### II. Training/Test Split Ratio\n",
|
||
"- **Decision**: 70:30 split is chosen for training/test dataset.\n",
|
||
"- **Reasoning**: This split ensures sufficient data for training and testing.\n",
|
||
"\n",
|
||
"### III. Performance Metrics\n",
|
||
"- **Classification Accuracy**: Measures the proportion of correctly classified instances.\n",
|
||
"- **Confusion Matrix**: Provides a summary of predicted and actual classes.\n",
|
||
"- **Classification Report**: Provides detailed metrics such as precision, recall, F1-score, and support for each class.\n",
|
||
"\n",
|
||
"The Random Forest Classifier is trained on the training set and evaluated on the test set using accuracy and classification report metrics.\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "8fefd253728ea2f0"
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Split the data into training and testing sets\n",
|
||
"\n",
|
||
"The next step is to split the data into training and testing sets. This is a common practice in machine learning, where the training set is used to train the model, and the testing set is used to evaluate its performance.\n",
|
||
"\n",
|
||
"We will use the `train_test_split` function from the `sklearn.model_selection` module to split the data into training and testing sets. We will use 70% of the data for training and 30% for testing, which is a common split ratio."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "7d64d6490fa1c2c2"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"from tensorflow.keras.utils import to_categorical\n",
|
||
"\n",
|
||
"# Assuming 'NLOS' is your target column\n",
|
||
"y = data['NLOS']\n",
|
||
"\n",
|
||
"# Convert labels to categorical one-hot encoding\n",
|
||
"y_categorical = to_categorical(y, num_classes=2)\n",
|
||
"\n",
|
||
"# Now split the data\n",
|
||
"X_train, X_test, y_train, y_test = train_test_split(data, y_categorical, test_size=0.2)\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.902835Z",
|
||
"start_time": "2024-03-18T15:11:25.620071Z"
|
||
}
|
||
},
|
||
"id": "54d2a6506b584a03",
|
||
"execution_count": 63
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Train a Random Forest Classifier\n",
|
||
"\n",
|
||
"The next step is to train a machine learning model on the training data. We will use the `RandomForestClassifier` class from the `sklearn.ensemble` module to train a random forest classifier.\n",
|
||
"\n",
|
||
"The random forest classifier is an ensemble learning method that operates by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes (classification) or mean prediction (regression) of the individual trees.\n",
|
||
"\n",
|
||
"We will use the `fit` method of the `RandomForestClassifier` object to train the model on the training data."
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "ab55160e30fd6f99"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.ensemble import RandomForestClassifier\n",
|
||
"# \n",
|
||
"# # Initialize the classifier with parameters to prevent overfitting\n",
|
||
"# classifier = RandomForestClassifier(n_estimators=200, max_depth=10, min_samples_split=10, min_samples_leaf=5, max_features='sqrt')\n",
|
||
"# \n",
|
||
"# loaded_model = train_and_save_model(classifier, X_train, y_train, 'random_forest_classifier.pkl')\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.908244Z",
|
||
"start_time": "2024-03-18T15:11:25.905116Z"
|
||
}
|
||
},
|
||
"id": "dc485f3de9f8936f",
|
||
"execution_count": 64
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Evaluate the Model\n",
|
||
"\n",
|
||
"To evaluate the performance of the trained model on the testing data, we will use the `predict` method of the `RandomForestClassifier` object to make predictions on the testing data. We will then use the `accuracy_score` and `classification_report` functions from the `sklearn.metrics` module to calculate the accuracy and generate a classification report.\n",
|
||
"\n",
|
||
"- **Accuracy:** The accuracy score function calculates the proportion of correctly classified instances.\n",
|
||
"\n",
|
||
"- **Precision:** The ratio of correctly predicted positive observations to the total predicted positive observations. It is calculated as:\n",
|
||
"\n",
|
||
" $$\n",
|
||
" \\text{Precision} = \\frac{\\text{True Positives}}{\\text{True Positives} + \\text{False Positives}}\n",
|
||
" $$\n",
|
||
"\n",
|
||
"- **Recall:** The ratio of correctly predicted positive observations to all observations in the actual class. It is calculated as:\n",
|
||
"\n",
|
||
" $$\n",
|
||
" \\text{Recall} = \\frac{\\text{True Positives}}{\\text{True Positives} + \\text{False Negatives}}\n",
|
||
" $$\n",
|
||
"\n",
|
||
"- **F1 Score:** The weighted average of precision and recall. It is calculated as:\n",
|
||
"\n",
|
||
" $$\n",
|
||
" \\text{F1 Score} = 2 \\times \\frac{\\text{Precision} \\times \\text{Recall}}{\\text{Precision} + \\text{Recall}}\n",
|
||
" $$\n",
|
||
"\n",
|
||
"- **Support:** The number of actual occurrences of the class in the dataset.\n",
|
||
"\n",
|
||
"The classification report provides a summary of the precision, recall, F1-score, and support for each class in the testing data, giving insight into how well the model is performing for each class.\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "424cc5954c9e81cc"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"\n",
|
||
"# Make predictions on the test set using the loaded model\n",
|
||
"# y_pred = loaded_model.predict(X_test)\n",
|
||
"# \n",
|
||
"# # Evaluate the loaded model\n",
|
||
"# accuracy = accuracy_score(y_test, y_pred)\n",
|
||
"# classification_rep = classification_report(y_test, y_pred)\n",
|
||
"# cross_val_score = cross_val_score(loaded_model, X_test, y_test, cv=5)\n",
|
||
"# \n",
|
||
"# print(f\"Accuracy: {accuracy}\")\n",
|
||
"# print(f\"Classification Report:\\n{classification_rep}\")\n",
|
||
"# print(f\"Cross Validation Score: {cross_val_score}\")\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.913564Z",
|
||
"start_time": "2024-03-18T15:11:25.909221Z"
|
||
}
|
||
},
|
||
"id": "702b4f40dda16736",
|
||
"execution_count": 65
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Visualize a Decision Tree from the Random Forest\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "41957f9babb74a3"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.tree import plot_tree\n",
|
||
"# import matplotlib.pyplot as plt\n",
|
||
"# \n",
|
||
"# # Select one tree from the forest\n",
|
||
"# estimator = loaded_model.estimators_[0]\n",
|
||
"# \n",
|
||
"# plt.figure(figsize=(100, 100))\n",
|
||
"# plot_tree(estimator,\n",
|
||
"# filled=True,\n",
|
||
"# rounded=True,\n",
|
||
"# class_names=['NLOS', 'LOS'],\n",
|
||
"# feature_names=data.columns,\n",
|
||
"# max_depth=5) # Limit the depth of the tree\n",
|
||
"# plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.916886Z",
|
||
"start_time": "2024-03-18T15:11:25.914597Z"
|
||
}
|
||
},
|
||
"id": "1f6f826d6234591c",
|
||
"execution_count": 66
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Support Vector Machine (SVM)"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "eef3be2c3026a909"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# import os\n",
|
||
"# from sklearn.svm import SVC\n",
|
||
"# import pickle\n",
|
||
"# \n",
|
||
"# svm = SVC(kernel='linear', random_state=42, verbose=True)\n",
|
||
"# loaded_model = train_and_save_model(svm, X_train, y_train, 'svm_classifier.pkl')\n",
|
||
"# \n",
|
||
"# # Predict the labels for the test set with each model\n",
|
||
"# y_pred_svm = loaded_model.predict(X_test)\n",
|
||
"# \n",
|
||
"# # Calculate the accuracy of each model\n",
|
||
"# accuracy_svm = accuracy_score(y_test, y_pred_svm)\n",
|
||
"# \n",
|
||
"# # Print the accuracy of each model\n",
|
||
"# print(f\"Accuracy of SVM: {accuracy_svm}\")"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.920059Z",
|
||
"start_time": "2024-03-18T15:11:25.917862Z"
|
||
}
|
||
},
|
||
"id": "c970b0c1593d955c",
|
||
"execution_count": 67
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Logistic Regression"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "cccaf1db0d5060a8"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.linear_model import LogisticRegression\n",
|
||
"# from sklearn.model_selection import cross_val_score\n",
|
||
"# \n",
|
||
"# # Logistic Regression with L2 regularization\n",
|
||
"# log_reg = LogisticRegression(penalty='l2', C=0.1)\n",
|
||
"# \n",
|
||
"# # Use the train_and_save_model function to train and save the model\n",
|
||
"# loaded_model = train_and_save_model(log_reg, X_train, y_train, 'logistic_regression_model.pkl')"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.923225Z",
|
||
"start_time": "2024-03-18T15:11:25.921024Z"
|
||
}
|
||
},
|
||
"id": "ee7506f4aa805faf",
|
||
"execution_count": 68
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"\n",
|
||
"# # Predict on the test set\n",
|
||
"# y_pred_log_reg = loaded_model.predict(X_test)\n",
|
||
"# \n",
|
||
"# # Calculate accuracy\n",
|
||
"# accuracy_log_reg = accuracy_score(y_test, y_pred_log_reg)\n",
|
||
"# print(f\"Accuracy of Logistic Regression: {accuracy_log_reg}\")\n",
|
||
"# \n",
|
||
"# # Perform 5-fold cross validation\n",
|
||
"# scores = cross_val_score(log_reg, X_train, y_train, cv=5)\n",
|
||
"# print(f\"Cross-validated scores: {scores}\")"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.926323Z",
|
||
"start_time": "2024-03-18T15:11:25.924121Z"
|
||
}
|
||
},
|
||
"id": "a44d38efa4b86d93",
|
||
"execution_count": 69
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.metrics import roc_curve, auc\n",
|
||
"# import matplotlib.pyplot as plt\n",
|
||
"# \n",
|
||
"# # Compute ROC curve and ROC area for each class\n",
|
||
"# fpr, tpr, _ = roc_curve(y_test, y_pred_log_reg)\n",
|
||
"# roc_auc = auc(fpr, tpr)\n",
|
||
"# \n",
|
||
"# plt.figure()\n",
|
||
"# lw = 2\n",
|
||
"# plt.plot(fpr, tpr, color='darkorange',\n",
|
||
"# 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": "2024-03-18T15:11:25.930923Z",
|
||
"start_time": "2024-03-18T15:11:25.928577Z"
|
||
}
|
||
},
|
||
"id": "a3646a4965b0707c",
|
||
"execution_count": 70
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Gradient Boosting Classifier"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "aeaf5eeffa7ec104"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.ensemble import GradientBoostingClassifier\n",
|
||
"# \n",
|
||
"# # Gradient Boosting Classifier\n",
|
||
"# gbc = GradientBoostingClassifier()\n",
|
||
"# \n",
|
||
"# # Use the train_and_save_model function to train and save the model\n",
|
||
"# loaded_model = train_and_save_model(gbc, X_train, y_train, 'gradient_boosting_classifier.pkl')\n",
|
||
"# "
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.933925Z",
|
||
"start_time": "2024-03-18T15:11:25.931866Z"
|
||
}
|
||
},
|
||
"id": "c7ecae5d021ad44f",
|
||
"execution_count": 71
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# y_pred_gbc = loaded_model.predict(X_test)\n",
|
||
"# accuracy_gbc = accuracy_score(y_test, y_pred_gbc)\n",
|
||
"# print(f\"Accuracy of Gradient Boosting Classifier: {accuracy_gbc}\")\n",
|
||
"# "
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.936907Z",
|
||
"start_time": "2024-03-18T15:11:25.934811Z"
|
||
}
|
||
},
|
||
"id": "4a8a1c3a7289ef7a",
|
||
"execution_count": 72
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# K-Nearest Neighbors (KNN, K=15)\n",
|
||
"\n",
|
||
"This code block is implementing the K-Nearest Neighbors (KNN) algorithm for classification. The KNN algorithm is a type of instance-based learning, or lazy learning, where the function is only approximated locally and all computation is deferred until function evaluation. \n",
|
||
"\n",
|
||
"The KNN algorithm works by finding the distances between a query and all the examples in the data, selecting the specified number examples (K) closest to the query, then votes for the most frequent label (in the case of classification) or averages the labels (in the case of regression). \n",
|
||
"\n",
|
||
"The number of neighbors, K, is set to 15 in this case. This means that the algorithm looks at the 15 nearest neighbors to decide the class of the test instance. \n",
|
||
"\n",
|
||
"The mathematical concept behind KNN is the Euclidean distance. Given two points P1(x1, y1) and P2(x2, y2) in a 2D space, the Euclidean distance between P1 and P2 is calculated as:\n",
|
||
"\n",
|
||
"$$\n",
|
||
"\\text{Distance} = \\sqrt{(x2 - x1)^2 + (y2 - y1)^2}\n",
|
||
"$$\n",
|
||
"In higher dimensional space, the formula is generalized as:\n",
|
||
"$$\n",
|
||
"\\text{Distance} = \\sqrt{\\sum_{i=1}^{n} (x_i - y_i)^2}\n",
|
||
"$$\n",
|
||
"Where:\n",
|
||
"- $n$ is the number of dimensions\n",
|
||
"- $x_i$ and $y_i$ are the $i$-th dimensions of the two points\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "25102568a6e5c457"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.neighbors import KNeighborsClassifier\n",
|
||
"# \n",
|
||
"# # K-Nearest Neighbors\n",
|
||
"# knn = KNeighborsClassifier(n_neighbors=13)\n",
|
||
"# loaded_model = train_and_save_model(knn, X_train, y_train, 'knn_classifier.pkl')\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.939889Z",
|
||
"start_time": "2024-03-18T15:11:25.937754Z"
|
||
}
|
||
},
|
||
"id": "705c62e64bf6d614",
|
||
"execution_count": 73
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# y_pred_knn = loaded_model.predict(X_test)\n",
|
||
"# accuracy_knn = accuracy_score(y_test, y_pred_knn)\n",
|
||
"# print(f\"Accuracy of K-Nearest Neighbors: {accuracy_knn}\")"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.942901Z",
|
||
"start_time": "2024-03-18T15:11:25.940823Z"
|
||
}
|
||
},
|
||
"id": "cf4df4ef7bbfd74",
|
||
"execution_count": 74
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.model_selection import GridSearchCV\n",
|
||
"# \n",
|
||
"# # Define the parameter values that should be searched\n",
|
||
"# k_range = list(range(1, 31))\n",
|
||
"# \n",
|
||
"# # Create a parameter grid: map the parameter names to the values that should be searched\n",
|
||
"# param_grid = dict(n_neighbors=k_range)\n",
|
||
"# \n",
|
||
"# # Instantiate the grid\n",
|
||
"# grid = GridSearchCV(knn, param_grid, cv=10, scoring='accuracy')\n",
|
||
"# \n",
|
||
"# # Fit the grid with data\n",
|
||
"# grid.fit(X_train, y_train)\n",
|
||
"# \n",
|
||
"# # View the complete results\n",
|
||
"# grid.cv_results_\n",
|
||
"# \n",
|
||
"# # Examine the best model\n",
|
||
"# print(grid.best_score_)\n",
|
||
"# print(grid.best_params_)"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.946023Z",
|
||
"start_time": "2024-03-18T15:11:25.943784Z"
|
||
}
|
||
},
|
||
"id": "faabcf63e34005a9",
|
||
"execution_count": 75
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# import matplotlib.pyplot as plt\n",
|
||
"# import numpy as np\n",
|
||
"# \n",
|
||
"# # Apply PCA to reduce dimensionality to 2D\n",
|
||
"# pca = PCA(n_components=2)\n",
|
||
"# X_test_2d = pca.fit_transform(X_test)\n",
|
||
"# \n",
|
||
"# # Print the number of features\n",
|
||
"# print(f\"Original number of features: {X_test.shape[1]}, reduced number of features: {X_test_2d.shape[1]}\")\n",
|
||
"# \n",
|
||
"# # Create a scatter plot\n",
|
||
"# plt.figure(figsize=(10, 7))\n",
|
||
"# \n",
|
||
"# # Create a color map\n",
|
||
"# cmap = plt.cm.viridis\n",
|
||
"# \n",
|
||
"# # Plot NLOS points\n",
|
||
"# nlos = plt.scatter(X_test_2d[y_pred_knn == 1, 0], X_test_2d[y_pred_knn == 1, 1], c='blue', label='NLOS')\n",
|
||
"# \n",
|
||
"# # Plot LOS points\n",
|
||
"# los = plt.scatter(X_test_2d[y_pred_knn == 0, 0], X_test_2d[y_pred_knn == 0, 1], c='red', label='LOS')\n",
|
||
"# \n",
|
||
"# # Add labels\n",
|
||
"# plt.xlabel('Principal Component 1')\n",
|
||
"# plt.ylabel('Principal Component 2')\n",
|
||
"# plt.title('2D Scatter Plot for LOS and NLOS')\n",
|
||
"# \n",
|
||
"# # Add a legend\n",
|
||
"# plt.legend(handles=[nlos, los])\n",
|
||
"# \n",
|
||
"# plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.949595Z",
|
||
"start_time": "2024-03-18T15:11:25.946864Z"
|
||
}
|
||
},
|
||
"id": "2ed22b3fc59f74e6",
|
||
"execution_count": 76
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.neighbors import KNeighborsClassifier\n",
|
||
"# from sklearn.metrics import accuracy_score\n",
|
||
"# import matplotlib.pyplot as plt\n",
|
||
"# \n",
|
||
"# # Define the list of numbers of neighbors (from 1-20)\n",
|
||
"# num_neighbors = np.arange(1, 100, 2)\n",
|
||
"# \n",
|
||
"# # Initialize the lists to store the accuracies\n",
|
||
"# train_acc = []\n",
|
||
"# test_acc = []\n",
|
||
"# \n",
|
||
"# # Loop over the different numbers of neighbors\n",
|
||
"# for k in num_neighbors:\n",
|
||
"# # Initialize the KNN classifier\n",
|
||
"# clf = KNeighborsClassifier(n_neighbors=k)\n",
|
||
"# \n",
|
||
"# # Fit the classifier on the training data\n",
|
||
"# clf.fit(X_train, y_train)\n",
|
||
"# \n",
|
||
"# # Make predictions on the training and test data\n",
|
||
"# y_pred_train = clf.predict(X_train)\n",
|
||
"# y_pred_test = clf.predict(X_test)\n",
|
||
"# \n",
|
||
"# # Calculate the accuracies\n",
|
||
"# train_acc.append(accuracy_score(y_train, y_pred_train))\n",
|
||
"# test_acc.append(accuracy_score(y_test, y_pred_test))\n",
|
||
"# \n",
|
||
"# # Plot the accuracies\n",
|
||
"# plt.figure(figsize=(10, 5))\n",
|
||
"# plt.plot(num_neighbors, train_acc, 'ro-', num_neighbors, test_acc, 'bv--')\n",
|
||
"# plt.legend(['Training Accuracy', 'Test Accuracy'])\n",
|
||
"# plt.xlabel('Number of Neighbors')\n",
|
||
"# plt.ylabel('Accuracy')\n",
|
||
"# plt.title('Training and Test Accuracy for Different Numbers of Neighbors in KNN')\n",
|
||
"# plt.grid()\n",
|
||
"# plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.953281Z",
|
||
"start_time": "2024-03-18T15:11:25.950580Z"
|
||
}
|
||
},
|
||
"id": "4ac86c268055c1b8",
|
||
"execution_count": 77
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Naive Bayes"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "5b9b66f92968957c"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.naive_bayes import GaussianNB\n",
|
||
"# \n",
|
||
"# # Naive Bayes\n",
|
||
"# nb = GaussianNB()\n",
|
||
"# loaded_model = train_and_save_model(nb, X_train, y_train, 'naive_bayes_classifier.pkl')"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.956545Z",
|
||
"start_time": "2024-03-18T15:11:25.954221Z"
|
||
}
|
||
},
|
||
"id": "3d984228fb1d3026",
|
||
"execution_count": 78
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# y_pred_nb = loaded_model.predict(X_test)\n",
|
||
"# accuracy_nb = accuracy_score(y_test, y_pred_nb)\n",
|
||
"# print(f\"Accuracy of Naive Bayes: {accuracy_nb}\")"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.959633Z",
|
||
"start_time": "2024-03-18T15:11:25.957637Z"
|
||
}
|
||
},
|
||
"id": "98cd350871bc3201",
|
||
"execution_count": 79
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# K-Means Clustering"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "92c8498137a5e32e"
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.cluster import KMeans\n",
|
||
"# \n",
|
||
"# # K-Means Clustering\n",
|
||
"# kmeans = KMeans(n_clusters=2, max_iter=600)\n",
|
||
"# loaded_model = train_and_save_model(kmeans, X_train, y_train, 'kmeans_clustering.pkl')"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.962781Z",
|
||
"start_time": "2024-03-18T15:11:25.960544Z"
|
||
}
|
||
},
|
||
"id": "305a796294814705",
|
||
"execution_count": 80
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# y_pred_kmeans = loaded_model.predict(X_test)\n",
|
||
"# accuracy_kmeans = accuracy_score(y_test, y_pred_kmeans)\n",
|
||
"# print(f\"Accuracy of K-Means Clustering: {accuracy_kmeans}\")\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.970224Z",
|
||
"start_time": "2024-03-18T15:11:25.963708Z"
|
||
}
|
||
},
|
||
"id": "494bb537046bf5a7",
|
||
"execution_count": 81
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# labels = loaded_model.labels_\n",
|
||
"# # Print the data table with the cluster labels\n",
|
||
"# print(f\"Data table with cluster labels:\\n{pd.concat([X_test, pd.DataFrame({'Cluster': labels})], axis=1)}\")\n",
|
||
"# \n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.973642Z",
|
||
"start_time": "2024-03-18T15:11:25.971168Z"
|
||
}
|
||
},
|
||
"id": "62401c8d1a4d61cc",
|
||
"execution_count": 82
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.cluster import KMeans\n",
|
||
"# from sklearn.metrics import accuracy_score\n",
|
||
"# from sklearn.decomposition import PCA\n",
|
||
"# from mpl_toolkits.mplot3d import Axes3D\n",
|
||
"# import matplotlib.pyplot as plt\n",
|
||
"# \n",
|
||
"# # Define the range of cluster numbers\n",
|
||
"# cluster_range = range(1, 15)\n",
|
||
"# \n",
|
||
"# # For each number of clusters\n",
|
||
"# for n_clusters in cluster_range:\n",
|
||
"# # Create a KMeans model\n",
|
||
"# kmeans = KMeans(n_clusters=n_clusters, max_iter=600)\n",
|
||
"# \n",
|
||
"# # Fit the model to the training data\n",
|
||
"# kmeans.fit(X_train)\n",
|
||
"# \n",
|
||
"# # Make predictions on the test data\n",
|
||
"# y_pred_kmeans = kmeans.predict(X_test)\n",
|
||
"# \n",
|
||
"# # Calculate the accuracy of the model\n",
|
||
"# accuracy_kmeans = accuracy_score(y_test, y_pred_kmeans)\n",
|
||
"# \n",
|
||
"# # Print the number of clusters and the corresponding accuracy\n",
|
||
"# print(f\"Number of clusters: {n_clusters}, Accuracy: {accuracy_kmeans}\")\n",
|
||
"# \n",
|
||
"# # Apply PCA to reduce dimensionality to 3D\n",
|
||
"# pca = PCA(n_components=3)\n",
|
||
"# X_test_3d = pca.fit_transform(X_test)\n",
|
||
"# \n",
|
||
"# # Create a 3D scatter plot\n",
|
||
"# fig = plt.figure(figsize=(10, 7))\n",
|
||
"# ax = fig.add_subplot(111, projection='3d')\n",
|
||
"# \n",
|
||
"# # Create a color map\n",
|
||
"# cmap = plt.cm.get_cmap('viridis', n_clusters) # We use 'viridis' colormap and we specify that we have n_clusters\n",
|
||
"# \n",
|
||
"# # Plot the points with colors according to their cluster assignment\n",
|
||
"# scatter = ax.scatter(X_test_3d[:, 0], X_test_3d[:, 1], X_test_3d[:, 2], c=y_pred_kmeans, cmap=cmap)\n",
|
||
"# \n",
|
||
"# # Add labels\n",
|
||
"# ax.set_xlabel('Principal Component 1')\n",
|
||
"# ax.set_ylabel('Principal Component 2')\n",
|
||
"# ax.set_zlabel('Principal Component 3')\n",
|
||
"# plt.title(f'3D Visualization of {n_clusters} Clusters')\n",
|
||
"# \n",
|
||
"# # Display the plot\n",
|
||
"# plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.977519Z",
|
||
"start_time": "2024-03-18T15:11:25.974608Z"
|
||
}
|
||
},
|
||
"id": "f0f5284581e70e6e",
|
||
"execution_count": 83
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# from sklearn.decomposition import PCA\n",
|
||
"# import matplotlib.pyplot as plt\n",
|
||
"# \n",
|
||
"# # Apply PCA to reduce dimensionality to 2D\n",
|
||
"# pca = PCA(n_components=2)\n",
|
||
"# X_test_2d = pca.fit_transform(X_test)\n",
|
||
"# \n",
|
||
"# # Predict the cluster labels for the data points you're plotting\n",
|
||
"# labels = loaded_model.predict(X_test)\n",
|
||
"# \n",
|
||
"# # Create a scatter plot\n",
|
||
"# plt.figure(figsize=(10, 7))\n",
|
||
"# \n",
|
||
"# # Create a color map\n",
|
||
"# cmap = plt.cm.get_cmap('viridis', 2) # We use 'viridis' colormap and we specify that we have 2 clusters\n",
|
||
"# \n",
|
||
"# # Plot the points with colors according to their cluster assignment\n",
|
||
"# plt.scatter(X_test_2d[:, 0], X_test_2d[:, 1], c=labels, cmap=cmap)\n",
|
||
"# \n",
|
||
"# # Add labels\n",
|
||
"# plt.xlabel('Principal Component 1')\n",
|
||
"# plt.ylabel('Principal Component 2')\n",
|
||
"# plt.title('2D Visualization of Clusters')\n",
|
||
"# \n",
|
||
"# # Display the plot\n",
|
||
"# plt.show()"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:11:25.981003Z",
|
||
"start_time": "2024-03-18T15:11:25.978459Z"
|
||
}
|
||
},
|
||
"id": "82c7ba8cbb2aa17a",
|
||
"execution_count": 84
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"# Convolution Neural Network\n",
|
||
"\n",
|
||
"This code block is implementing a Convolutional Neural Network (CNN) for a classification task using TensorFlow. The CNN is a class of deep learning neural networks, most commonly applied to analyzing visual imagery. They are also known as shift invariant or space invariant artificial neural networks (SIANN), based on their shared-weights architecture and translation invariance characteristics. Here's a step-by-step breakdown of what the code does: \n",
|
||
"1. Data Preparation: The target column 'NLOS' is separated from the rest of the dataset. The target values are then encoded from categorical to numerical values using LabelEncoder. These numerical values are then one-hot encoded to create binary variables for each class. \n",
|
||
"2. Data Reshaping: The input data is reshaped to fit the model. Each data instance is reshaped to a 3D array where the third dimension represents the number of input channels, which is 1 in this case. \n",
|
||
"3. Data Splitting: The data is split into training and testing sets using a 80:20 ratio. \n",
|
||
"4. Model Creation: A Sequential model is created using Keras. This model is composed of the following layers: \n",
|
||
"5. 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",
|
||
"6. 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",
|
||
"7. 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",
|
||
"9. Model Compilation: The model is compiled with the Adam optimizer, categorical cross-entropy loss function, and accuracy as the evaluation metric. \n",
|
||
"10. 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",
|
||
"11. Model Evaluation: The model's performance is evaluated on the testing set and the accuracy is printed. \n",
|
||
"\n",
|
||
"12. 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",
|
||
"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": [],
|
||
"source": [
|
||
"from tensorflow.keras.models import Sequential\n",
|
||
"from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense, Dropout, BatchNormalization\n",
|
||
"from tensorflow.keras.callbacks import EarlyStopping\n",
|
||
"from tensorflow.keras import regularizers\n",
|
||
"from tensorflow.keras.optimizers import Adam\n",
|
||
"from sklearn.metrics import classification_report\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"\n",
|
||
"# Set random seed for reproducibility\n",
|
||
"tf.random.set_seed(42)\n",
|
||
"\n",
|
||
"# 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), 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=20, batch_size=32, validation_data=(X_test, y_test), 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
|
||
},
|
||
"id": "1c1dd203ad7db076",
|
||
"execution_count": null
|
||
},
|
||
{
|
||
"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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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Test loss: 0.4177149534225464\n",
|
||
"Test accuracy: 0.8578571677207947\n",
|
||
"Classification Report: \n",
|
||
" precision recall f1-score support\n",
|
||
"\n",
|
||
" 0 0.82 0.91 0.87 4192\n",
|
||
" 1 0.90 0.80 0.85 4208\n",
|
||
"\n",
|
||
" accuracy 0.86 8400\n",
|
||
" macro avg 0.86 0.86 0.86 8400\n",
|
||
"weighted avg 0.86 0.86 0.86 8400\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"\n",
|
||
"# 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": "2024-03-19T03:07:31.960613Z",
|
||
"start_time": "2024-03-19T03:07:31.542293Z"
|
||
}
|
||
},
|
||
"id": "89aa08d7d1866179",
|
||
"execution_count": 76
|
||
},
|
||
{
|
||
"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 500x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 640x480 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"from tensorflow.keras.models import Sequential\n",
|
||
"from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense, Dropout, BatchNormalization\n",
|
||
"from tensorflow.keras.callbacks import EarlyStopping\n",
|
||
"from tensorflow.keras import regularizers\n",
|
||
"from tensorflow.keras.optimizers import Adam\n",
|
||
"from sklearn.metrics import classification_report, confusion_matrix, roc_curve, auc\n",
|
||
"import matplotlib.pyplot as plt\n",
|
||
"import seaborn as sns\n",
|
||
"\n",
|
||
"# 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",
|
||
"\n",
|
||
"# 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()\n",
|
||
"\n",
|
||
"# 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()\n"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-19T03:06:29.218619Z",
|
||
"start_time": "2024-03-19T03:06:28.205257Z"
|
||
}
|
||
},
|
||
"id": "dd49203934ca9cf6",
|
||
"execution_count": 75
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": "<IPython.core.display.Image object>"
|
||
},
|
||
"execution_count": 87,
|
||
"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": "2024-03-18T15:18:11.267954Z",
|
||
"start_time": "2024-03-18T15:18:11.152659Z"
|
||
}
|
||
},
|
||
"id": "81f2d793ada5c410",
|
||
"execution_count": 87
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# Save the model\n",
|
||
"model.save('CNN.keras')"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-18T15:18:11.363950Z",
|
||
"start_time": "2024-03-18T15:18:11.270650Z"
|
||
}
|
||
},
|
||
"id": "6b7329b28452b82a",
|
||
"execution_count": 88
|
||
},
|
||
{
|
||
"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. **Data Preparation**: The target column 'NLOS' is separated from the rest of the dataset. The remaining data is assigned to X and the target column to y.\n",
|
||
"\n",
|
||
"2. **Data Splitting**: The data is split into training and testing sets using an 80:20 ratio.\n",
|
||
"\n",
|
||
"3. **Data Scaling**: A StandardScaler object is initialized and fitted to the training data. The training and testing data are then transformed using the fitted scaler.\n",
|
||
"\n",
|
||
"4. **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",
|
||
"5. **Model Compilation**: The model is compiled with the Adam optimizer, binary cross-entropy loss function, and accuracy as the evaluation metric.\n",
|
||
"\n",
|
||
"6. **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",
|
||
"7. **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",
|
||
"8. **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: 1.0987 - accuracy: 0.5262 - val_loss: 0.8572 - val_accuracy: 0.5762\n",
|
||
"Epoch 2/20\n",
|
||
"1050/1050 [==============================] - 3s 2ms/step - loss: 0.9669 - accuracy: 0.5646 - val_loss: 0.7898 - val_accuracy: 0.6692\n",
|
||
"Epoch 3/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.8728 - accuracy: 0.6072 - val_loss: 0.7326 - val_accuracy: 0.7321\n",
|
||
"Epoch 4/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.8011 - accuracy: 0.6615 - val_loss: 0.6795 - val_accuracy: 0.7712\n",
|
||
"Epoch 5/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.7329 - accuracy: 0.7080 - val_loss: 0.6355 - val_accuracy: 0.7924\n",
|
||
"Epoch 6/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6893 - accuracy: 0.7466 - val_loss: 0.6015 - val_accuracy: 0.8089\n",
|
||
"Epoch 7/20\n",
|
||
"1050/1050 [==============================] - 3s 2ms/step - loss: 0.6469 - accuracy: 0.7716 - val_loss: 0.5766 - val_accuracy: 0.8139\n",
|
||
"Epoch 8/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6214 - accuracy: 0.7907 - val_loss: 0.5572 - val_accuracy: 0.8174\n",
|
||
"Epoch 9/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5948 - accuracy: 0.8044 - val_loss: 0.5425 - val_accuracy: 0.8208\n",
|
||
"Epoch 10/20\n",
|
||
"1050/1050 [==============================] - 3s 2ms/step - loss: 0.5739 - accuracy: 0.8142 - val_loss: 0.5299 - val_accuracy: 0.8261\n",
|
||
"Epoch 11/20\n",
|
||
"1050/1050 [==============================] - 3s 3ms/step - loss: 0.5611 - accuracy: 0.8159 - val_loss: 0.5181 - val_accuracy: 0.8288\n",
|
||
"Epoch 12/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5450 - accuracy: 0.8237 - val_loss: 0.5066 - val_accuracy: 0.8314\n",
|
||
"Epoch 13/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5323 - accuracy: 0.8292 - val_loss: 0.4986 - val_accuracy: 0.8325\n",
|
||
"Epoch 14/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5168 - accuracy: 0.8356 - val_loss: 0.4892 - val_accuracy: 0.8354\n",
|
||
"Epoch 15/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5042 - accuracy: 0.8367 - val_loss: 0.4837 - val_accuracy: 0.8363\n",
|
||
"Epoch 16/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5009 - accuracy: 0.8374 - val_loss: 0.4769 - val_accuracy: 0.8380\n",
|
||
"Epoch 17/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4875 - accuracy: 0.8409 - val_loss: 0.4718 - val_accuracy: 0.8379\n",
|
||
"Epoch 18/20\n",
|
||
"1050/1050 [==============================] - 3s 2ms/step - loss: 0.4781 - accuracy: 0.8439 - val_loss: 0.4659 - val_accuracy: 0.8392\n",
|
||
"Epoch 19/20\n",
|
||
"1050/1050 [==============================] - 3s 2ms/step - loss: 0.4715 - accuracy: 0.8453 - val_loss: 0.4630 - val_accuracy: 0.8368\n",
|
||
"Epoch 20/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4647 - accuracy: 0.8470 - val_loss: 0.4564 - val_accuracy: 0.8407\n",
|
||
"263/263 [==============================] - 0s 1ms/step\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 640x480 with 1 Axes>",
|
||
"image/png": 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ESAgr8PLy4qOPPmL+/Pm8//77eHp60qdPH9q0aUNQUJC1wwOgcePGLF++nAULFrBo0SKqVq3K+PHjuXjxYq53qel0Oj766CPL/BhnZ2e6dOnC0KFDc10pOzsajYYPP/yQuXPnsmXLFhRFsSzad/cwW0GNGjWK2rVr89lnn7Fs2TIAqlSpQrt27SwLUfr5+dG+fXt++uknwsPDcXV1xc/Pj+XLl+Pv72+pa+rUqbz++uu8//77JCcn89hjj2WZAO3YsQOTyURAQEC2cQUEBPD999/zyy+/0LlzZ+bNm4efnx/r169nwYIFlClThsaNG9O8eXPLORMmTKB69eqsXbuW9957zxLn3a/94MGDuXbtGuvXr2f//v20bNmSVatW8cwzz+T5NZs+fToajYatW7eSkpJCixYtWLVqVaa1i9zd3Vm3bh1Llixhz549bNq0CW9vb9q0aZPhLkOAChUq0K5dO37++ecCf1aEyAtFLU1/cgohSr0XX3yRf//9l927d1s7FGGnxowZw/nz57McMhOiqMgcICFEtu7dtuLSpUv88ssvPPjgg1aKSNi7GzduSO+PKBEyBCaEyFZgYCCPPfYYNWrUICQkhK+++gqdTpdpiEOIwrp69Sq//fYb69evx8nJiccff9zaIQk7JwmQECJbHTp0YPv27URERKDX6/H392fixInUrl3b2qEJO3P8+HGmTZuGj48Pb731FhUrVrR2SMLOyRwgIYQQQjgcmQMkhBBCCIcjCZAQQgghHI4kQEIIIYRwOJIACSGEEMLhyF1gOYiKukVRTxFXFPD2LlMsdZc20lb75UjtlbbaL0dqr6O0Nb2deSEJUA5UlWL7oBRn3aWNtNV+OVJ7pa32y5Ha60htzY0MgQkhhBDC4UgCJIQQQgiHIwmQEEIIIRyOJEBCCCGEcDiSAAkhhBDC4UgCJIQQQgiHIwmQEEIIIRyO1ROgdevW0alTJ5o0acKgQYM4ffp0juU/++wzunXrRtOmTenYsSNz584lJSXF8vySJUvw8/PL8NW9e/fiboYQQgghbIhVF0LcsWMH8+bNIzg4mGbNmrF69WqCgoLYtWsX3t7emcpv3bqVd999l7lz59K8eXMuXbrE1KlTURSFadOmWcrVq1ePVatWWR5rtdoSaY8QQgghbINVE6BVq1YxePBgBgwYAEBwcDD79u1jw4YNjBo1KlP5kydP0qJFC3r37g1A9erV6dWrF6dOncpQTqvVUrFixeJvgBBCCCHyzmhEd+QQmvDrmCpXIbV1W7BSJ4XVEiCDwcDZs2d5/vnnLcc0Gg1t27bl5MmTWZ7TvHlztmzZwunTp2natClXr17l559/pm/fvhnKXb58mfbt2+Ps7Iy/vz+TJk3Cx8cn3zEqSr5PyXOdxVF3aSNttV+O1F5pq/1ypPaWhrbqt23BffpktKGhlmNGHx8S5izA0KtPkVwjP+2zWgIUExOD0WjMNNTl7e3NxYsXszynd+/exMTE8OSTT6KqKmlpaTzxxBO88MILljJNmzZl3rx53HfffURERLBs2TKGDh3K1q1b8fDwyFeMed1QrSCKs+7SRtpqvxypvdJW++VI7c1TW41G2L8fwsKgalXo0KHwvTQbN8KzwzNtRKYNC8Pz2eGwfj3071+4a+STTW2GevToUT7++GNmzpxJ06ZNuXLlCnPmzGHZsmWMGTMGgI4dO1rK169fn2bNmhEQEMDOnTsZNGhQvq4nu8EXjrTVfjlSe6Wt9stm23t7GEkJv46ax2GkvLa1WHppjEa8xo1Do6pk6qBRVVRFwTR+PDHtOhU60bKJ3eC9vLzQarVERUVlOB4VFUWFChWyPGfRokX06dPHksj4+fmRmJjI66+/zujRo9FoMt/U5unpSe3atbly5Uq+Y5Td4IuGtNV+OVJ7pa32y5baq9+2BY8ZmROU+Nl5S1Byaqt+2xbKBGXupdGEhVHm2eHErVyT8RpGI0psLJqYaJSoKPO/MdFooqPvfB8VhebSfxnivZeiqmhDQnA6fIjUdh1ybUNRsVoCpNfradSoEYcPHyYwMBAAk8nE4cOHGTZsWJbnJCcnZ0py0u/wUrN5RxMSErh69apMihZCCGHT9Nu24JlNguIZlEWCkldpaSgx0XhMnQRZ9NIoqooKeI5+jrSljVBiYswJzs2bKEWYOWrCrxdZXXlh1SGwESNGMGXKFBo3bkzTpk1ZvXo1SUlJ9L89Djh58mQqV67MpEmTAAgICGDVqlU0bNjQMgS2aNEiAgICLInQ/PnzCQgIwMfHhxs3brBkyRI0Gg29evWyWjuFEEI4kOK408loxGPG5OwTFEXBY9r/uFmrNpqEeJTYWJSbsWjibpp7aeJuQnICZW5Emh/fvIlyMxbl5k008bdyvbwCkJKM7rcTmZ4zeZZF9fLCVL48qld5TF7lMXl7W77XRNzA/d35uV7DVLlK3l6LImLVBKhHjx5ER0ezePFiIiIiaNCgAStWrLAMgYWFhWXo8Rk9ejSKovD+++8THh5O+fLlCQgI4OWXX7aUuX79OhMnTiQ2Npby5cvTsmVLvvnmG8qXL1/i7RNCCOFYCjtElYnJhOZ6GM7btuQ+jBR+nfKd2+dYnXP+I8gg8YWxGHr0Mic5XuVRvbxAp8v5JKORiLV7iQo3oZC5x0hFoUJlDW6t2xYyuvxR1OzGjgSRkcUzCbpChTLFUndpI221X47UXmmr/Srq9t49RHV3L416+97sLIeoVBUlNgbtlctoLl9Ce/ky2iuX0V7+D82Vy2ivXUUxGAC4SnUiyH46RyVu4ONxE1Olyqhly6KWLYepbDnUsuVQy5bFzacS8TpXTJ5lbx8vi1quHCbPcjidPUO5QX2zrTtd7Kbt+Z6nk5ICLRo5ERHnmn3snkmcOJuGcyEztPT3NC9s6i4wIYQQojBCQhSiou6kJ15eEBNzZ6ShQgUVH58CZEO5DVEBZV6ZQEJYCNqrV80Jz5XLaC9fQnMrLseqVa2WJG8fHrhxjHCyHyaqQhi/f3oKzSPtMj2nKOBWoQzJ2SR7qe0fxujjgyYsLMt5PaqiYKrqYx7Oyye9HqrV0RN5SkVVMy/UoygqPnX06PVp+a67MCQBEkII4RBSUqBrVzciIu69Y9jd8l2lSiZOnEjId0+E7uB+QkM1RNA82zKVom5QffqULJ8zVayEsVZtjDVrYaxVC1Ot+8zf16yFyacaKgo1al0iIrUiJjLPJ9JgpLouHKV96/wFnk6rJX72AjyDhqMqSoYkKL0HK372/ALNZVIUmDo1hSeecMvyeVVVmDo1pcQXaZQESAghRKlh6aExmnA6cwolOgq1vDdpTZqBVlPwHhpu90RUU4mMzKEnwkdFr8+hkvh4nP49j/af82j/PY/TefO/af9cpj4Xc+2h+adJPzRtH7id5NTGWLM2xho1wS3r5MASGzBtXDQDFmadgJjQMm1cNIrT/TnWk5P/mvfl5uvbcFu2CG1khOW40bsSiWPGU67Fw/hkMYcnO3v3ajlzRstff2k4d04DqLdbcodWq9KkiYmAAGOB4y4oSYCEEELkWXEmKJl7aDJP6C1oDw2YeyJe6/QzA37vlOXzqqrwWqefUWiFJjwc7fm/MyU62tCQLM/VAjW5QgTZ99DU4CqpwTNJa39nDk1yMty8qXArFOLiFOLiFG7dUm5/D08/nWrJjS5UaUsZFwO3knXcnUgomKhUNpm6Tz8ItxOU5GTz3OS8dtjcee17AD0yPhkJBEOlDzO/9hERCn/+qeGvvzTExSn8738Gy3NvvunMuXM5B2A0Wqf3ByQBEkIIkUfFnaDo9VDdPZqoCK9sk4hqbjHo9blXrqqQmAixsQrR0QoxMQoJt0w8+eVwWrGJk7TAeNevQAUT3kSxY+FFdi25jCY1hSWMQ4d5XsoahvErfVFQUVxdUMuVQ/Eqh1reC9XLi0n/S2HWY/PoGf1FlvGY0JLk5MHDr7fgu++S8PQ0H58+3Zk1a7LvcurVKw03N3NSc+mShlvJmcuqaAi/6UZSUrzl2Pvv61m8WE+lSipVq6pUqWKiTh0oV05PlSomunZNo2zZO3XktXfs+++dOHpUa0l6IiPvDCe6uKi8/LLBknR165ZGgwam219G/PxMPPecK2fOaDAaFav2/oAkQEIIIfKoKBOUTFQVJT6e2bGT6MmXWRYxoWXo9ff4aVJLouN0xN5yIilFYWqzHSgpyZCSwuiDT7MnrBlRqWVIMWVMFpxIZTihzOY1uvN9xsujIZKKrOQ5SDUfe6f2Ykx+tTHW9WX70dF8/auf+Ymk219hd84f884t2r7dk1ZBxzhBK1Qy70zwR1pD+MPc4+PpaU5qypQBjUalTBnw9FTx8FDx9FTx9IQyZVSc7vot/dhjqTRqZOSdd/RcvqzBZFJQFJUqVVS6dUujSpU7PW/h4QppaQqhoQrmu+fT3y/ze3PkSDxly5rLL16s55tvnNDryTL5Mb895p6aNWt0bN9+57Z3RVG57z6V+vWN1K9vIjkZ3G9PqZo2zZCpnrvnAlmz9wckARJCCLty711O9yrMEJViMjI7bjw9yb6XY0rEK0Qse4SkuDSS4tJIjDOSGG9CTUqhR7lDKAnxKAkJfH61M3/HVyMpRUtCqp7END0JuJPASMoQRyJuGXpo0v0veQ6svfNYSxrBhx61DAjdog+h3NlkW4cBb6IoTzTeRJGMC13ZzQMc4wQtMaFFwYQPIYzmQ0Ah+ZEuGFo+wK1JRy0JSJctTlT9IwWT6c52EiaTYvne2RlSe/dh2sTjDFiYOfl5vvNftHy8Fp6eKt7ed17/6dNTmDkzb0lAs2YmmjUz4e2tWpIIVVV4770kOnXK2Ivy9tspTJ5sICxMISxMw/XrCjdvunDxYiphYUqGZOniRYXz57MfqtJoVJo2NffUREcr1Kyp0qCBkQYNTNSrZ8pt+lIGAQFG/P2N/P67Fn9/o9V6f0DWAcqRrANUONJW++VI7S2OthZXkpKSAi1auGdxl9MdOQ1RZdfWmzfhyhUNobv/4sb8tcxnCjeoBHf1cmhJw4VkEvDI8rpeRBN9V2ISyB72EphlWQ3GLHuY3LlFFcLxckuhvGcq5V2T8HJLYm6H7ejcdaguLvx104dExR0vL5Xy5U24ezqhuDqjOrug/fsvykz7HwDf0zVDL9AuutGN3UDB1rpJp6rQrevtYR6TBq3GRJMmJr7fnVRkPR2qCt26uVmSiO+/T8y17pw+x1evKly8aE6SDh7U8tVXmYfZvvoqMVOSVVA//6xl+nRn5sxJoWPHok2AZB0gIYQopbK/FfuOgs6jKehdTrduweXLGq5dM8f06KN3nuvR3Zlff0s/oeXtr8yMOHE/FzhNM/SKAXenFNx0Btx0qbjp0yjnbuDWqAWo7h6o7u48etCb+tGXcCmjwc3TCTdPJ9yjrlJx+du4kcCbvGaZp6Mljeac5BgPogCx6zImKKk8kD5qRa174kq9+/s27XBbshBNWBhdVXMv0HEe5AGO0ZXdhVrrJp2iwNRphjvDPCYNU6clF+kwj6KYe46mT3dm+vTCDyHVqKFSo4Y5ERk8OI2//tIW6zydjh2NHDiQWGT1FZQkQEIIUYKK5FbsbOR1vZUPP9Rx/LiWK1c0XL2qITb2Thxlyqhc2vk3+h/3oN+7h6q/TwR6UYlwanOJ2lyiFpf4hse5Sg1MaNGSRgt+4ycewRkD8Ru33E5Q9Le/zJJ5wfL9U1ntCmG8n/Lb96MJC8NZNVh6aIw4MZsZoCgYC5Og3LXWDYrCXPVVxrOYubwKhVzr5m4lMcxTXEnEvZ8ha8/TKU6SAAkhxD2KbbVg8rcoXFSUws2bkJCg3P7C8q/BoPD003f6N5Yt03HypJb4eAV3d5WEBLj7Vum7/5L/9FM9u3dn/O+/vEcKtZzDuD/pLG7tB+BCCgDLOYurTzl0ge0xBHTGY9r/0IRfp7P6Y4YE5U1ew01JLlwPyl0JShf2ZOih6cIeoPAJiqFXH+JWrsFjxmQCQ/dyjkbmNlStRvzs+QXbr+seRd1DU9JK0zyd4iQJkBBC3KU4VwsG2L9fy8WLGipVMhERodzTC6Ti739nuGHkSBcOHMj6v2mdTs2QAB09qmXXruw3pTQab69xozzAkCEGOjW4Rp3wI9T9exf3n9mCZ3wM3L6LWtXrMbQOwNC5C7rOXUip50tKeg+JqpZYgjI39E4Pjerjw60iSlAMvfoQ/WhP9EcPUTbxJjfdymJ4qAh2bL9LaRnmKQhbT+DySiZB50AmQReOtNV+2XN70yeYnjqlyXaIqlkzU4aJp0lJEBqqEBKiISQk47+pqbBpU5Ll/D59XDlyJPu/Pe+ebPr00+YEyN1dxd2d2//e+f6jj5Itv7N37dISEqLB85+TVPh0ITOYzQXqWoaomvMbR3mI1IcfwenffzIt6GesWRtD50Bc+/clskkrVDf3e0OzSN/x/KfQBoxnMYsZT4DPX0XWg2IOyIjuyCE04dcxVa5i7lUqwgQF7PtzfC9HaatMghZC2LVivdU7D0NU991nzPBX8eOPZ5/UaDQqqanmVXkB2rY14uWlUq2ayo4dToSFmXuBNBqVevUyTjZdvTo5z3F3724Eo4HyLQeiIZSyxN0zh+Y1NIDzL/vM7XBxIbVtewydu2DoFIixTl0UjYJrhTIQeYucdjxI70FpdeQQR8KPYKo8keiiTlC02gLfiSVEXkgCJISwKUV9F1VKijmhunFDQ+vW5uQjIMBIhQomIiMV7t27COC773QsXZpiSWp8fFTc3FSqVTNRrVrmf+9OlqZOvbM4XGBgmiXRMpkUgoMLMdyQlITr55+iNa96Z1nr5u67nNLFvxZM0nMvgKtrAS+GJCjC5kkCJISwKYW5i2rHDieOH9dy7ZrCtWsarl1TCA83J1IajcrVq/HodOZeID8/E5GRmf+LbNcujRYtjBgMd3p1Fi1KRq8n38lLwMMGmtc1cPLfcjSvG0vAw0AW699kRYm7ie7YEXRHDqM7fBCn339DSb0zJ0gB5nJnDs3doZmqVS9c8iOEHZAESAhhU/IyRKXVqnTq5EZYmMKZMwmWRGXLFic2bsw8UdjNTaV6dROxsQoVK5rHft54I4XnnzcvEGcy3VkPZePGzAvaFWjfq9vzaBbcnkez4N/xeLf6k/jZC7KcR6NERKA7cgjdkYPojhzG6ewZFJMpQxmjlxfamBjL40Du3OV0N1Pl7HcsF8JRSAIkhLAp168rltt00xdru9eJE3f+awsLMy/dD+YhpwoVzMlO9eoqNWqY/y1fXs2U1DRpYmL27OJZD0W/bYt5LRpVJZBQS5Kihil4Bg0nbuUa0pr5ozt88HbScwinf//JVI+x9n0Y2rQjtXVbUlu3xVSjJuVbNUYTFoaSxUzXoljoTwh7IQmQEKLIFdUkZaMRzp3TcOyYluPHtRw7puXaNQ0nT8Zn2wvUt6+Bdu1MluSmatU71xk4MI2BA9Py3I5iWQ/FaMRjxmTz5p/3PKWoKirgOfJpFGPGa6mKgrF+Q1LbtL2T8FSpmqn69HV0VEXJkASpRbjQnxD2QBIgIUSRKopJyj/+qOXDD/WcOGFe2O9uGo3KX39p6NQpYy9Q+hDVJ58U3boligIzZqTw2mtuzJhRNPXqjhyyTFTO8poARiOqRkNa8xaktr7dw/PgQ6he5XOt/+51dO6+jqmqT9Hepi6EjZMESAhRpPIzSTksTOHYMXPPzuOPp9K0qXlOS1ycws8/m/978vBQadXKyIMPmr9atDDicXu/zZJYsr9jRyPnzkFkpLHw66ckJ6PftSNPRW+9t5SUIcMKdJn029SLex0dIWyZJEBCiCKVl0nK7u4qrVq5c/XqnV6iSpVUmjY13yLetq2RefOSefBBIw0bmrL9vW0TS/anpqLbvw+XTRvQ79iG5lZcnk4z1bx3W898ktvUhciRJEBCOKjiWkxQVaFRIxN16xotd1Dd6+BB8389Go1Ko0YmS+9OukqVVIKCUjOdd69Su2S/yYTuyCGcN23Aedt3aKKiLE8Zq/qgxMWhJMRnscKQTFQWoqRIAiSEAyqqxQSTk2H3bif+/VfDv/9quHDB/G9cXPaZSOPGRh59NI0HHzTSsuWd4ayCKjV7LqkqTr//hvPG9Thv2YQ27K75NxUqkNLnMZL7DSTtwYfQ79hmnqgMMlFZCCuRBEgIB5TXeTo6nXmezt0JTq1aJkaNMvfOmEwQFJR5QT1FUaleXSU5GaKjlQyTlO/eQ6vUMxrRHT0EiTfRZbNhpvbPczh/tx6XTRvQXvrPctzkWZaUnr1JeWwgqe0fBqc7/93KRGUhrE8SICEcUF7m6dy8Cfff70FCQsZspU2bNEsC5OYG3bun4ukJdeuauP9+E3XrmrjvPhMuLua7uYp1knIxbpiZvlBheoJSFjD6+BA/ewFpDRvhsnkjzt9twOnPc5ZzVDc3Uro9SspjgzAEdM5xhUSZqCyEdUkCJEQpVdRzdEwmuHZNsfTk/POPBg8Plfh4uHu/K63WvCjgf/9pLY9r1VItCU6zZhknGn/+efYbdhbnJOV7ExS4k6AUtgfl7oUK76YJDcXz2WEZ5u6oej2GTl1IeWwAKV0fBffsd1HPRCYqC2E1kgAJUQoVZo7OzZvw778a4uMVOna8k3A88EDGu66yYzQqjBuXQqtW5t6cWrVMWe6rlRfFNUk52wQlLMyyknK+kyCDAU1MNEpkJGVeeSnrhQpv/6sCqQ8/QvKAwRh69EItW65gDRFCWI0kQEKUQnmdo3PokJZz5+5MPv73Xw2RkeYkp0YNc4KUrlo1E+HhCvfdd2eo6v77TSxdqufChYz7Xc2YYSiyZKXIJynntpKyouDx6ivcrFsP5eZNNLExKDHRaGKy+Tc2Bk10NEpiQpaXy4oCJL78ivTeCGHDJAESohTKyxydqVNTePttZ379NfOckcqVTdSubcJovDOl5LPPkihbNvMUk8qV1WJfTLAo5bqSsqqivR5G+YcfynfdqqKgurmhScg9GdKEX893/UKI0kMSICFKmePHNRw44MTx41q0WjXTZp/pvTQBAUZOnEijWrU7PTrpvTplymSut3w2uyjYxGKCd9Fcz1viYXJ1Ra1UGZOXF6pX+Tv/lvNCLV8ek1d5VC8vTHcdUz3Lojt8kHKP9cy9ftlRXQibJgmQEAV07yRlLy+Iibkzxya3ScomE1y4oOHECQ2DB6ehuX3qypV6Nm7UZXve3b00r7xiKHQ7Su1igvdKTMTl269wW/xunorHfbG+QENUqa3bYvTxkR3VhbBzkgAJUQDZT1K+cwfQvZOUb96E337T8uuvWk6c0PLbb1piY83ZRosWCfj6mvfB6tw5DVWFVq3M+15NnerCH39k3PCzqHtpSs1iglnQhFzD9dPluKxZhSY2Fri9YGAWc4DSnytUgqLVyo7qQjgASYCEKIC8TFKuWlW13D310Uc6Xn/dJVM5V1cVf38jiXflHoMGpTFoUJrl8bRpxb/hZ6mjqjgdP4brJx/gvH0LitGc8Blr1iZp5POYyntTZuzzxbaSsixUKIT9kwRIiALIyyTl7t1TLYlKnTrm3p3atU20bGmkVSsjDzxgpEEDE7rsR7sA25ujUygGA86bN+K6/EN0v5+8c7j9wySNHI2ha3dLYqO6uhVrgpK+UKH+6CHKJt7kZjYrQQshbJMkQEIUUHpicvp01ht+Ggx3jnXoYOTs2XgqVsz/5qI2M0enEJSICFw//xSXVSvQ3ggHQHV2JnnAYJKeewFj4yaZzimRlZTTFyqsUIbUyFvmBYCEEHZBEiAhCkhVoWFDc8/MvebPT+app+7sZu7qah7uKqjSPEcnR7lsVaH94wyuyz/EZeO3KCkp5lMqVyF5xHMkPfUsaoUKOdcvKykLIQpIEiAhCig1FU6fTv9lrgJ3Jik/80yqXfbU5Ee2W1W88RY4OeH6yQfoDx2wPJfavAVJo14kpXc/Crz0tBBC5JEkQEIUkLMzLF+exKpVej75xPwL22EmKecix720nnvqzpYSWi0pvfuSNHI0aa0exOFfOCFEiZEESIg8Mhjgrbf0uLjA5Mnm9Xfuv1/lzTdTOHZM6xiTlPMip60qbv+rKgpJYyaQFDQKU7XqJR2hEEKQ+86IQgguXVLo08eNpUudWbhQz8WLd361KwrMmJFCgwbmfx29EyN9q4qcXgZFVTF07iLJjxDCaqyeAK1bt45OnTrRpEkTBg0axOnTp3Ms/9lnn9GtWzeaNm1Kx44dmTt3Lim3J08WtE4hcrJxoxOdOrnz229aypZVWbEimTp1Mg7tdOxo5Nw5Muy+7qjyukeW7KUlhLAmqyZAO3bsYN68eYwZM4ZNmzZRv359goKCiIqKyrL81q1beffddxk7diw7duxgzpw57Nixg4ULFxa4TiGyk5AAEya48MILrsTHKzz4YBo//ZRAr15puZ/soDTh13FZtzpPZWUvLSGENVk1AVq1ahWDBw9mwIAB1K1bl+DgYFxcXNiwYUOW5U+ePEmLFi3o3bs31atXp3379vTq1StDD09+6xQiK0Yj9O3rxpdf6lAUlYkTU/juuySqV5eFYLKUlobrx8vwatMS/f5fUMl+yRxVUTD6VJO9tIQQVmW1SdAGg4GzZ8/y/PPPW45pNBratm3LyZMnszynefPmbNmyhdOnT9O0aVOuXr3Kzz//TN++fQtcZ06KYy5Hep2OME/Eltvq5ATPPJPKggUKH32UTLt2OQ9t2XJbC+Lu9jodOYzHlIk4nTsLQGqLlqT07of7G69nu1VFwpz5KE62saKyI723jtRWcKz2Okpb89M+qyVAMTExGI1GvL29Mxz39vbm4sWLWZ7Tu3dvYmJiePLJJ1FVlbS0NJ544gleeOGFAteZE2/vMvk+pzTUXdrYSlujoiAkBJo2NT9+6SV49lkoWzbr7S6yYittLRLh4XhPmQKrbw95lS8Pb72FLigInUYDTRvChAlw7ZrlFKV6dXj/fTz797dS0AXnSO+tI7UVHKu9jtTW3NjUbfBHjx7l448/ZubMmTRt2pQrV64wZ84cli1bxpgxY4r8elFRt+5dxqTQFMX8ASyOuksbW2rrwYNaRo92QauFn35KoFy5O89FRuZ+vi21tdCMRlxWr8Rj7pvmLe6B5OHPkDB9Jqq3N0QnmMs93AV+PYPuyCGU8Ouod68EHXnLig3IH0d6bx2preBY7XWUtqa3My+slgB5eXmh1WozTU6OioqiQjbL3y9atIg+ffowaNAgAPz8/EhMTOT1119n9OjRBaozJ6qaaR23IlOcdZc2pbmtaWnw7rt63ntPj8mkcP/9JiIjFcqWLVjApbmtRcHp12N4TJmE7swpANKa+nNr/ruktXzAXODetmu0GNres1WFjb4+9v7e3s2R2gqO1V5HamturJYA6fV6GjVqxOHDhwkMDATAZDJx+PBhhg0bluU5ycnJaDQZ521r03eGVtUC1SnsW0iIQlRU1oPCN24oLFig5/ffzT8GQ4akMmdOMh4eJRmhbVCionCfMwvXtebhLpNnWTTz5hI74ElUjW3M5RFCiLtZdQhsxIgRTJkyhcaNG9O0aVNWr15NUlIS/W/PD5g8eTKVK1dm0qRJAAQEBLBq1SoaNmxoGQJbtGgRAQEBlkQotzqF40hJga5d3YiIyPlmR3d3lXffTaZ/f7m9PROTCZe1q3GfMwtNTAwAyY8/ScLMN/FuUMc8lCV/TQohbJBVE6AePXoQHR3N4sWLiYiIoEGDBqxYscIyXBUWFpahx2f06NEoisL7779PeHg45cuXJyAggJdffjnPdQrHoddDtWoqkZEqqpp1L5Crq8revQmZFjZ0KNns2O506iQeUyai++0EAGkNG3PrrXdJa93G7u8kEULYP0VVZTQwO5GRxTMJukKFMsVSd2lTGtr6449anngi+7u41q5NpGvXwq/eXBraWhBZ7thepSppDRqi3/cjiqpi8ihD4tTpJD07yrw+ALbb3oKQttovR2qvo7Q1vZ15YVN3gQmRXwEBRvz9jZw6pcnQC6TVqjRpYqJLF8fduiLbHduvh+F8PQyA5P6DSAieI6s2CyHsjtX3AhOiOCkKPPCAMdMQmNGoMHWqA29cmsuO7Spg8q7ArWWfSPIjhLBLkgAJu7ZsmY7ly/UAKIq5p0OrVfH3NxIQ4Li9P7nt2K4AmqhIdEcOlWRYQghRYiQBEnZJVWHuXD3BwS4A9OljsPQCOXzvD7JjuxBCSAIk7I7JBFOnOvP++84AzJiRwvLlKfj7m3t8HL33B0DN42JHMvwlhLBXkgAJu3PqlIbPPzfv4r5gQTLjxxtQFJg+PQVfXyPTpzt478/FC7jPmgHIju1CCMcld4EJu9O8uYn3309GpyPD4oYdOxo5cCDRipFZn+7QATxHDEUTE4PRqzyamGhURclyx/b42fPN+3YJIYQdkh4gYRdu3TJve5Hu8cfTZGXnezh/uZayg/qiiYkhtXkLYn85QtynazFVrZqhnKmqD3Er12Do1cdKkQohRPGTHiBh86KiFIYMceXmTYUtWxKpXNmOV/kqCKMR99mzcFu2CIDkvv25tfhDcHXF0KsP0Y/2zHIlaCGEsGeSAAmbFhamMHiwK3//raV8eRM3biiSAN0tPh7PF5/DedcOABImTSHxlWlw96bCWi2p7TpkU4EQQtgnSYCEzfrvP4VBg9y4ckVD1aomvvkmCT8/k7XDKjU0IdcoO+xxnM6eQXV25tb7y0gZMNjaYQkhRKkgCZCwSefOaRg82JUbNzTUrm1i/fpEataUnp90Tr/9iudTQ9DeCMdUoSI3V39B2gMPWTssIYQoNWQStLA5p09r6NfPjRs3NDRoYGTrVkl+7ub83QbK9euB9kY4aQ0aEfP9T5L8CCHEPSQBEjanalUVb2+Vli2NfPedTHq2UFXc3nkLz1EjUJKTSenSjdjtuzHVqGntyIQQotSRITBhcypWVNm4MZEyZVTyuKCx/UtKoszLY3DZuB6AxBfGkjDzTbmbSwghsiEJkLAJX3/thMkEQ4aY1/apWlV6fdIp4eGUfWYIuhO/ojo5ET9/IcnDn7F2WEIIUapJAiRKvRUrdLz6qgsajYqfXyItWsidXum0Z/+g7LDBaEOuYSpXjrhP15La/mFrhyWEEKWeJECi1FJVWLhQz/z55k1NR45Mxd9fkp90+u934vn8syiJCaTdX5e4dd9grFPX2mEJIYRNkARIWFVIiEJUVOadSVUVPvxQz8aNOgAmT05h0iSDY25iajRmXKn5oTa4fvIh7sEzUFQVQ4eOxK38HLWcl7UjFUIImyEJkLCalBTo2tWNiIicb0YMDk5m9OjUEoqqdNFv24LHjMloQ0Mtx0xubmgSzZu6Jg0fQfxb74BOZ60QhRDCJkkCJKxGr4dq1VQiI1VUNauuHZWaNVVeeMFxkx/PoOHm7rC7aBITUYHkJ4YS/877OGa3mBBCFI6sAySsRlFg6tSUbJIfAIUFC5Id8/e70YjHjMmgqmTXfP0v+8Akc6KEEKIgJAESVhUQYMTf34hWm7GXQ6tV8fc3EhBgtFJk1qU7cghtaGi2yY8CaEND0B05VJJhCSGE3ZAESFhVei+Q0ZjxV73RqDB1aopj9v4AmvDrRVpOCCFERjIHSFhdnTomFOXOPCCtVqVJE5PD9v4AmCpXKdJyQgghMpIeIGF1wcHOGeYBOXrvD0BqU39UnT7b51VFwehTjdTWbUswKiGEsB+SAAmr2r9fy/btuturPJt7fBx57g8AaWl4vvgcSqoBFbh30w/1dmYYP3u+7PUlhBAFJAmQsJq0NJgxw7zK84gRqcyenYKvr5Hp0x2490dV8XjlJZy/34nq7Ezi1BmYfHwyFDFV9SFu5RoMvfpYKUghhLB9MgdIWM3q1Tr+/FOLl5fK5MkpeHnBgQOJ1g7Lqtzmz8Z13eeoGg1xH6/C0KMXiRMmZVwJunVb6fkRQohCkgRIWIWqwpo15tWLp0wxJz+OzuXT5bgvfBuA+AXvYejRy/yEVktquw5WjEwIIeyPJEDCKhQFtm9PZO1aHU895ZgrPd9Nv/U7PKb9D4CEV6aR/NQIK0ckhBD2TRIgYTXu7vD885L86A78gufo51BUlaSnniXxf1OtHZIQQtg9mQQtSpSqwp49WtnB4TbtH2fwfPpJFIOBlJ59iJ//ruztJYQQJUASIFGiduxwYuhQN/r1c3X4JEhz+RJln+iP5lYchjbtiPtwhUxuFkKIEiIJkCgxyckwc6b5tve2bY1oHPjTp0RGUvbxx9DeCCetQSPiPv8SXFysHZYQQjgMB/4VJEraRx/puXJFQ9WqJsaNM1g7HOuJj6fs0IE4XbyAsXoNbn69EbVsOWtHJYQQDkUSIFEiwsIU3n/fvLXD66+n4O5u5YCsJTWVskHD0Z38DVP58tz8ehOmKlWtHZUQQjgcSYBEiXjzTWcSExUefDCN/v3TrB2OdZhMlJnwIvqf9qK6uXFz3bcY6/laOyohhHBIkgCJYnf8uIb163UoisqcOY67zYX7G6/jsv5rVK2WuJWfk9byAWuHJIQQDkvWARLFztkZmjc30rChkWbNHPPWL9cPl+L2wWIAbr23FEPnrlaOSAghHJskQKLYNW1qYufORJKSrB2JdTiv/xqPma8CED8jmJQnhlo5IiGEEKUiAVq3bh0rV64kIiKC+vXr89prr9G0adMsyw4fPpxjx45lOt6xY0c++eQTAKZOncqmTZsyPN++fXtWrlxZ9MGLPNFocMiJz7qf9lJm/GgAEkeNJmncS9YNSAghBFAKEqAdO3Ywb948goODadasGatXryYoKIhdu3bh7e2dqfySJUtITb2zfUJsbCx9+/ale/fuGcp16NCBefPmWR7r9fria4TI0ltv6XF1heeeAzc3a0dT8px+/42yI4ahpKWR3H8gCW/Mk1WehRCilLB6ArRq1SoGDx7MgAEDAAgODmbfvn1s2LCBUaNGZSpfrly5DI+3b9+Oi4tLpgRIr9dTsWLFYotb5OzCBYXFi/WkpkKjRlo6dzZaO6QSpb34L2WfHIiSmIDh4QBuLf4Ih175UQghShmrJkAGg4GzZ8/y/PPPW45pNBratm3LyZMn81THhg0b6NmzJ273dDEcO3aMNm3a4OnpSevWrXnppZfw8vIq0vhF9l5/3YXUVIVHH4XAQCOqau2IipHRiO7oIUi8ic6tLKm176fs4P5oIiNJbepP3GdrQXoghRCiVLFqAhQTE4PRaMw01OXt7c3FixdzPf/06dOcP3+eOXPmZDjeoUMHunTpQvXq1bl69SoLFy5k5MiRfP3112jzsddScYxWpNdpzyMhP/ygZc8eJ5ycVN57T7Hrtuq3bcF9+mS0oaEAlAVUJx1KWirG2vcR9+V6KFMGe3sJHOFznE7aar8cqb2O0tb8tM/qQ2CFsX79enx9fTNNmO7Zs6flez8/P/z8/AgMDLT0CuWVt3eZIou1JOu2JoMBZs0yfz9hgoKfH4B9tpWNG+HZ4dzbvaWkmeeoaV/5H94N77dGZCXGXj/HWZG22i9Haq8jtTU3Vk2AvLy80Gq1REVFZTgeFRVFhQoVcjw3MTGR7du3M378+FyvU6NGDby8vLh8+XK+EqCoqFtFPnSjKOYPYHHUXRp89JGOv/92oWJFE2PGJAB22lajEa9x49Coapa9OypgmjuXmAFP2uUO7/b+Ob6btNV+OVJ7HaWt6e3MC6smQHq9nkaNGnH48GECAwMBMJlMHD58mGHDhuV47q5duzAYDPTp0yfX61y/fp3Y2Nh8T4pW1Ux/3BeZ4qzbWgwGWLLEPNfl1VcNlLn9GbTHtuoOH7IMe2VFAbQhITgdPkRquw4lF1gJs8f3NjvSVvvlSO11pLbmxupDYCNGjGDKlCk0btyYpk2bsnr1apKSkujfvz8AkydPpnLlykyaNCnDeevXrycwMDDTxOaEhASWLl1Kt27dqFChAlevXuXtt9+mVq1adOhgv7+ISgO9HnbtSuSzz3Q88URq7ifYME349SItJ4QQomRZPQHq0aMH0dHRLF68mIiICBo0aMCKFSssQ2BhYWFo7rl9+OLFi5w4cYJPP/00U31arZbz58/z3XffcevWLSpVqkS7du2YMGGCrAVUAqpXV5kxw2DtMIqdqXKVIi0nhBCiZCmqKp1h2YmMLJ45QBUqlCmWuq1FVeGPPzQ0aZJxny97bKuF0Uj5lo3QhIZmPQdIUTBV9SH6xB92OwfIbt/be0hb7ZcjtddR2prezryQldlEoX33nROdO7szcaKztUMpOVot8TPeyPIp9fZ9mPGz59tl8iOEEPZAEiBRKAkJEBxsTnyqVbPjPyuy4HT+LxRAvSfJMVX1IW7lGgy9cp+gL4QQwjqsPgdI2LalS/WEhmqoWdPEiy/a/9yfdJqLF3D7YDEAcSs+B69ylE28yU23shgeais9P0IIUcpJAiQK7OpVhWXLzBPLZ85MwdXVygGVII+Zr6IYDBgCOmPo0QtFo0CFMqRG3jIvAiSEEKJUkyEwUWCzZjmTnKzQrl0avXqlWTucEqPfuxvn73eiOjmZ5/nY+9ryQghhhyQBEgVy8KCWrVt1aDQqs2enOE4OYDDgPn0KAEkjR2Os52vlgIQQQhSEDIGJAklMhMqVTfTokUajRqbcT7ATrp98iNPFC5gqViLxf1OsHY4QQogCkgRI5CgkRCEqKnP3TuXKKsuXJ+Hl5TgTXjTXw3B7dz4A8a8Fo5bxtHJEQgghCkoSIJGtlBTo2tWNiIjsR0orVTJx4kQCzg6wBJD7mzPRJMST2vIBUgYPsXY4QgghCkHmAIls6fXmtX0UJeteHkVR8fFRcYQdRpyOHcXl269QFYX4uQtAIz86Qghhy+R/cZEtRYGpU1NQ1axnOKuqwtSpDjAB2mjE49VXAEh+cjhpzVtaOSAhhBCFJQmQyFFAgBF/fyNabcZeIK1Wxd/fSECA0UqRlRyXL9agO/07Js+yJLw609rhCCGEKAKSAIkcpfcCGY0Zu3mMRsfo/VFiY3CfGwxA4uRpqBUrWjkiIYQQRUESIJGrgAAjlSvfudXdkXp/3BbMRRMVRZpffZJGjLR2OEIIIYqIJEAiV6oKpruW+nGU3h/tubO4rloBQPycBaDTWTkiIYQQRUUSIJGrY8e0RERo0GjM84AcovdHVfGYPhnFaCSlV19SH37E2hEJIYQoQrIOkMiVTqcSGJgGqFy5omH6dPvv/dFv/Q79wf2oLi7Ez5pt7XCEEEIUMUmARK5atjTxxRdJqKqD7PuZkIDHzOkAJI57GVPNWlYOSAghRFGTITCRZw6R/ABuS95DG3INY42aJI59ydrhCCGEKAaSAIkcbd3qxLVrDpL5AJrLl3BbtgiA+FlzwNXVyhEJIYQoDpIAiWzFxsLo0S60aOHBxYuOkQR5vP4qSkoKhg6PYOjVx9rhCCGEKCaSAIlsbd2qw2BQaNDASJ069r/ru+6nvTjv3Iaq1RI/Z77jjPkJIYQDkgRIZGv9evMc+YED06wcSQlITcVjxhQAkoJGYazfwMoBCSGEKE6SAIksXb2qcPiwE4qi0r9/qrXDKXauKz7G6Z/zmCpUIPGVadYORwghRDGTBEhkacMG86rH7doZqVbNvoe/lPBw3N6eB0DC9FmoZctZNyAhhBDFThIgkYmqwrffpg9/2X/vj8ecWWjib5Hq35zkIcOsHY4QQogSIAmQyOTaNYVr1zS4uKj06mXf83+cThzH5at1AMTPfRs08iMhhBCOQFaCFpnUqKFy9mw8p09r8fS0djTFyGTC49VXAEh+/EnSWj1o5YCEEEKUFPlzV2TJwwPatrXvDU9dvlqH7uRvmDzKED8j2NrhCCGEKEGSAIkMkpOtHUHJUG7G4j57JgCJ/5uKWrmylSMSQghRkiQBEhlMmuTCI4+48fPPWmuHUqzc3pmPJjKStLr1SHrueWuHI4QQooTlOwHq1KkTS5cuJTQ0tDjiEVaUkADbtztx7pwWNzf7vfVd+/dfuK78GID4OQtAr7dyREIIIUpavhOgp556ij179hAYGMiIESPYvn07BoOhOGITJWzXLicSExVq1zbRqpXJ2uEUD1XF49XJKGlppHTvSWpAZ2tHJIQQwgrynQA988wzbN68mW+//Zb777+fN998k/bt2/PGG29w9uzZ4ohRlJD1682LHw4cmGp/22AZjegO7sf9tWno9+9D1euJf2OutaMSQghhJQWeA9SoUSNmzJjB/v37GTNmDN9++y0DBw6kb9++rF+/HlW13yEUe3TjhsK+feZ5P/a2+KF+2xbKt2xEucd64vbJBwCoej1Of5yxcmRCCCGspcDrAKWmprJnzx42btzIoUOHaNasGQMHDuT69eu89957HD58mHfffbcoYxXF6LvvnDAaFVq2tK+d3/XbtuAZNNy8vPVdlIQEPIOGE7dyDYZefawUnRBCCGvJdwJ09uxZNm7cyLZt29BoNPTr149p06Zx//33W8p06dKFgQMHFmmgonjdPfxlN4xGPGZMBlXl3hE9RVVRFQWPGVOIfrQnaO37rjchhBAZ5TsBGjhwIG3btmXWrFkEBgai0+kylalevTo9e/YskgBF8VNVmDQphQ0bdPTtaz9bX+iOHEKbw92KiqqiDQ1Bd+QQqe06lGBkQgghrC3fCdAPP/xAtWrVcizj5ubGvHnzChyUKFmKAt26GenWzb5WftaEXy/SckIIIexHvidBR0VFcerUqUzHT506xZkzMqlUlB6mylWKtJwQQgj7ke8E6I033iAsLCzT8fDwcN54440iCUqUnN9/1zB3rp7z5+1vUfDU1m0xVqpMdlO6VUXB6FON1NZtSzQuIYQQ1pfv33oXLlygUaNGmY43aNCAf//9t0iCEiVn3Tod77/vzJIldrgaslZLWuMmKJApCVJvL3QUP3u+TIAWQggHlO8ESK/XExkZmel4REQETk4Fu6t+3bp1dOrUiSZNmjBo0CBOnz6dbdnhw4fj5+eX6WvUqFGWMqqqsmjRItq3b0/Tpk155plnuHTpUoFis2cpKbB5s3kS+6BBdnT3122a8OvoD+4HQPX2zvCcqaqP3AIvhBAOLN8JULt27Vi4cCG3bt2yHIuLi+O9996jbdv8DyXs2LGDefPmMWbMGDZt2kT9+vUJCgoiKioqy/JLlizhwIEDlq9t27ah1Wrp3r27pczy5ctZs2YNs2bN4ptvvsHV1ZWgoCBSUlLyHZ8927vXidhYhSpVTLRrZ18ToAFcly1GSUkh9YGHiDrzD7GbthP30UpiN20n+sQfkvwIIYQDy3eXzZQpUxg6dCgBAQE0aNAAgL/++gtvb28WLFiQ7wBWrVrF4MGDGTBgAADBwcHs27ePDRs2ZOjVSVeuXLkMj7dv346Li4slAVJVlc8//5zRo0cTGBgIwIIFC2jbti0//PCD3J5/l/XrzW9///5pdjcKpERG4vr5pwAkTnwFnJzkVnchhBAW+U6AKleuzJYtW9i6dSt//fUXLi4uDBgwgJ49e2a5JlBODAYDZ8+e5fnnn7cc02g0tG3blpMnT+apjg0bNtCzZ0/c3NwAuHbtGhERERl6o8qUKUOzZs04efJkvhKg4tgPK71Oa++1dfMm7N5tfvsHDSqevb+s2Va3j5aiJCaS6t+c1M5dij2G0vK+lhRHaq+01X45Unsdpa35aV+BJu24ubnx+OOPF+TUDGJiYjAajXjfMz/D29ubixcv5nr+6dOnOX/+PHPmzLEci4iIsNRxb51ZzV3Kibd3mXyVLy1158V334HBAI0bQ8eO7sX6Q1HibY2Ohk8/AUA3ayYVKnqW2KWt/b6WNEdqr7TVfjlSex2prbkp8F5g//77L6GhoaSmZpw827lz50IHlVfr16/H19eXpk2bFkv9UVG37t1CqtAUxfwBLI668+P6dR3lyjnz2GMGoqIMxXINa7XVbcHbuMXHk9aoMbFtHoHIW7meU1il5X0tKY7UXmmr/XKk9jpKW9PbmRf5ToCuXr3KmDFjOH/+PIqiWHZ9V253Ifz55595rsvLywutVptpwnNUVBQVKlTI8dzExES2b9/O+PHjMxyvWLGipY5KlSplqLN+/fp5jg3MW0QU1welOOvOi+efT+WZZ1JJTS3+OEqyrcqtOFw++QiAxJf+h6poMt8DX4ys/b6WNEdqr7TVfjlSex2prbnJ911gc+bMoXr16hw6dAgXFxe2b9/O2rVrady4MWvWrMlXXXq9nkaNGnH48GHLMZPJxOHDh2nevHmO5+7atQuDwUCfPhnv5KlevToVK1bMUGd8fDynTp3KtU5H4+wMHh7WjqJoua78BM3NWNLq+ZLSq6+1wxFCCFFK5TsBOnnyJOPHj6d8+fJoNBoURaFVq1ZMnDiR2bNn5zuAESNG8M0337Bp0yYuXLjArFmzSEpKon///gBMnjyZd999N9N569evJzAwEC8vrwzHFUXhqaee4sMPP2Tv3r38/fffTJ48mUqVKlnuCnNkqmpe/dku/wJISMD1o6WAuffH7m5tE0IIUWTyPQRmMplwd3cHzENYN27coE6dOlSrVo3//vsv3wH06NGD6OhoFi9eTEREBA0aNGDFihWWIbCwsDA0mox52sWLFzlx4gSffvpplnWOHDmSpKQkXn/9deLi4mjZsiUrVqzA2dk53/HZmz/+0NC1qzv16xv56adEu8oRXFd/iiY6GmPt+0h5bKC1wxFCCFGK5TsBqlevHn///Tc1atSgWbNmrFixAp1OxzfffEONGjUKFMSwYcMYNmxYls9lNaxWp04d/v7772zrUxSFCRMmMGHChALFY8++/da8VIGvr8mukh+SknBbtgi43ftTwFXJhRBCOIZ8D4GNHj0ak8kEwPjx47l27RpDhw7l559/Zvr06UUeoCg6RiNs3GhODAYOtK+tL1zWrUYTcQNj9RokDyz8Eg1CCCHsW77/TO7Q4c5qurVq1WLXrl3ExsZStmxZy51gonTav1/LjRsavLxUOnWyo60vUlJwW3q792fcy6C3w41dhRBCFKl89QClpqbSsGFDzp8/n+F4uXLlJPmxAevXm4e/+vZNtascweXrL9CGhmCsUpXkIVkPpQohhBB3y1cCpNPpqFq1qmUITNiOhATYvt0Oh79SU3FbvBCApLETwMXFygEJIYSwBfmeA/TCCy+wcOFCYmNjiyEcUVz27nUiIUGhZk0TDzxgPwms84Zv0F65jKlCRZKGPWPtcIQQQtiIfM8BWrduHZcvX6ZDhw74+PhYNiFNt2nTpiILThSdXr3S2LQpkbg4xX42wzMacXv/HQASR4+Dez6LQgghRHbynQDJYoK2SaOBdu3saOIz4Lx5I04XL2Dy8iJ5RJC1wxFCCGFD8p0AjR07tjjiECJ/TCZL70/S82NQPWSHYyGEEHmX7zlAwvYMHerKq686c/26vYx9gX77Vpz++hNTGU+SgkZZOxwhhBA2Jt89QPXr18/xlvf87AYvit+//yrs2eOEVqvy8ssGa4dTNFQVt/feBiBp5POoZctZNx4hhBA2J98J0NKlSzM8TktL488//2TTpk2MGzeuyAITRSN97Z+AACMVK9rHDqj6PbvQ/XEak7sHSaNetHY4QgghbFCRTILu3r07devWZceOHQwaNKhIAhOFp6p3EiC7WftHVXFbuACA5BHPoZb3tnJAQgghbFGRzQHy9/fnyJEjRVWdKALHj2u4ckWDu7tK9+5p1g6nSOj2/YjutxOorq7mW9+FEEKIAiiSBCg5OZnPP/+cSpUqFUV1ooik9/707JlmH0vkqCrut3t/koY/g1qxopUDEkIIYavyPQT2wAMPZJgEraoqCQkJuLi48PbbbxdpcKLgDAbYvNm+hr90hw+iO3oYVa8nacwEa4cjhBDChuU7AZo2bVqGBEhRFMqXL0+zZs0oW7ZskQYnCi4pCZ54IpVDh7R06GAfCyC6vXt77s+TwzFV9bFyNEIIIWxZvhOg/v37F0ccooiVLQvBwSnWDqPIOB0/in7/PlQnJxLHvWztcIQQQti4fM8B2rBhAzt37sx0fOfOnbIPmCg2lju/Bg/BVKOmlaMRQghh6/KdAH3yySd4eXllOu7t7c1HH31UJEGJwjl0SMtPP2lJs48bv3A6dRLnvXtQNRoSx0+0djhCCCHsQL4ToNDQUKpXr57puI+PD2FhYUUSlCict9/W8/jjbixfrrN2KEXCbaF5cn1K/0GY6txv5WiEEELYg3zPAfL29ubvv//OlAT99ddflCtXrqjiEnkUEqIQFXVnUnp4uMLBg+a3tW5dE6GhCj4+trsCtPbsHzjv3IaqKCS+9D9rhyOEEMJO5DsB6tmzJ3PmzMHd3Z0HHngAgGPHjjF37lx69uxZ5AGK7KWkQNeubkREZN2RN3SoG5UqmThxIgFn5xIOroik7/ie0rsfRl8/K0cjhBDCXuQ7AZowYQIhISE888wzODmZTzeZTPTt25eXX5a7c0qSXg/VqqlERqqoauYNahVFxcdHRa+3QnBFQPvPeZy3mCfWJ778ipWjEUIIYU/ynQDp9Xref/99Ll26xJ9//omLiwu+vr5Uq1atOOITOVAUmDo1hSeeyHqZZ1VVmDo1BSVzbmQT3N5/B0VVSeneE2OjxtYORwghhB3JdwKUrnbt2tSuXbsIQxEFERBgxN/fyJkzGozGO5mOVqvSpImJgADbXARR899FnDd+C0DipMlWjkYIIYS9yfddYOPGjeOTTz7JdHz58uWMHz++SIISeZfeC3R38gNgNNp478/ihShGIymdu5DWrLm1wxFCCGFn8p0AHT9+nI4dO2Y6/vDDD/Prr78WSVAif9J7gbRa891eGo2Kv7/Rdnt/rl3F5esvAEh8WXp/hBBCFL18J0CJiYnodJnXl3FyciI+Pr5IghL5c28vkMlk470/S95DSUvD0KEjaQ8+ZO1whBBC2KF8J0C+vr7s2LEj0/EdO3ZQt27dIglK5F96LxBgm70/RiO6g/tx+XQ5LmtXA5A4UXp/hBBCFI98T4J+8cUXGTduHFevXqV169YAHD58mG3btrF48eIiD1DkzeOPu+LqqlK7tpHp022r90e/bQseMyajDQ21HFP1epSYaCtGJYQQwp7lOwHq1KkTy5Yt46OPPuL777/H2dmZ+vXrs3r1asqWLVscMYpcxMbCzz9rUVWFM2fiqVzZdlZ+1m/bgmfQcFDvidlgwDPoKeJWrsHQq491ghNCCGG3CnQb/COPPMIjjzwCQHx8PNu2bWP+/PmcPXuWP//8syjjE3lw9Kg5+alb12hTyQ9GIx4zJoOqcm+HlQKogMeMKUQ/2hO0WisEKIQQwl4VeB2g48ePs379enbv3k2lSpXo0qULr7/+elHGJvLo8GHz29imjW3N+9EdOZRh2OteiqqiDQ1Bd+QQqe06lGBkQggh7F2+EqCIiAg2bdrE+vXriY+P59FHH8VgMLBs2TKZAG1FR46Ye0dat7atBEgTfr1IywkhhBB5lecE6IUXXuD48eM88sgjvPrqq3To0AGtVstXX31VnPGJXMTHw6lT5pv52ra1rQTIVLlKkZYTQggh8irPCdAvv/zC8OHDGTJkiGyBUYocP67FaFSoWdNEtWo2NP8HSG3dFqOPD5rQ0ExzgABURcFU1YfU1m1LPDYhhBD2Lc/rAH3xxRckJCTQv39/Bg0axNq1a4mOltuUrU1VoWVLIx06pFk7lPzTaomfvSDLp9Tb9/HHz54vE6CFEEIUuTz3APn7++Pv78+rr77Kjh072LBhA2+99RYmk4mDBw9SpUoVPDw8ijNWkYVOnYx06pSY6S5yW5GWzS7vpqo+xM+eL7fACyGEKBb5vgvMzc2NgQMHMnDgQC5evMj69etZvnw57777Lm3btuWjjz4qjjhFLmxp4cO7uX62EgUwBHQmcfxENOHXMVWuYh72kp4fIYQQxaTAt8ED1KlTh8mTJzNp0iR++ukn1q9fX1RxiTyIjQUnJ7DZjrfERFy+XANAUtAoudVdCCFEicn3XmBZ0Wq1BAYGSu9PCVuxQk+9eh7Mnau3digF4rx5I5rYWIw1a2Ho3NXa4QghhHAgRZIAFca6devo1KkTTZo0YdCgQZw+fTrH8nFxcQQHB9O+fXsaN25Mt27d+Pnnny3PL1myBD8/vwxf3bt3L+5mWMXhw+Y7wKpWtcEJQKqK66fLAUh6OkiGu4QQQpSoQg2BFdaOHTuYN28ewcHBNGvWjNWrVxMUFMSuXbvw9vbOVN5gMDBixAi8vb1ZtGgRlStXJjQ0FE9Pzwzl6tWrx6pVqyyPtXb4y9VggF9/NbfL1tb/AXD67Vd0p06iOjuT/ORwa4cjhBDCwVg1AVq1ahWDBw9mwIABAAQHB7Nv3z42bNjAqFGjMpXfsGEDN2/e5KuvvkKn0wFQvXr1TOW0Wi0VK1Ys3uCt7NQpDUlJCt7eJnx9TdYOJ9/Se39S+vZHzSLZFUIIIYqT1RIgg8HA2bNnef755y3HNBoNbdu25eTJk1me8+OPP+Lv788bb7zB3r17KV++PL169WLkyJEZenkuX75M+/btcXZ2xt/fn0mTJuHj45PvGIvjzqr0Ogtb95Ej5reudWsjGqsPZGYtu7YqkZE4b94IQHLQSJu9g+1uRfW+2gpHaq+01X45Unsdpa35aZ/VEqCYmBiMRmOmoS5vb28uXryY5TlXr17lyJEj9O7dm08++YQrV64QHBxMWloaY8eOBaBp06bMmzeP++67j4iICJYtW8bQoUPZunVrvtcp8vYuU7DGlUDdv/5q/rdLFx0VKuiKIKLik6mtKz8wj+G1akW5rgHWCaqYFOdnpjRypPZKW+2XI7XXkdqaG6sOgeWXqqp4e3vz5ptvotVqady4MeHh4axcudKSAHXs2NFSvn79+jRr1oyAgAB27tzJoEGD8nW9qKhbRb7AoKKYP4CFqdtohP37PQCFJk0SiIwsnUNgWbbVaMRr2QdogVvDnyUl8pY1QywyRfG+2hJHaq+01X45Unsdpa3p7cwLqyVAXl5eaLVaoqKiMhyPioqiQoUKWZ5TsWJFnJycMgx31alTh4iICAwGA3p95tvBPT09qV27NleuXMl3jKpKsX1QClO3wQAzZqRw4oSWhg1Npf7DfHdb9Xt2o716BZOXF8n9BkApjz2/ivMzUxo5UnulrfbLkdrrSG3NjdVmj+j1eho1asThw4ctx0wmE4cPH6Z58+ZZntOiRQuuXLmCyXSnx+PSpUtUrFgxy+QHICEhgatXr9rVpGgXF3j22VSWLUu2ubvHXT/9BIDkIcPB1dXK0QghhHBUVp0+O2LECL755hs2bdrEhQsXmDVrFklJSfTv3x+AyZMn8+6771rKDxkyhNjYWObMmcN///3Hvn37+Pjjjxk6dKilzPz58zl27BjXrl3jt99+Y+zYsWg0Gnr16lXi7RMZaS/+i/6nvaiKQtIzQdYORwghhAOz6hygHj16EB0dzeLFi4mIiKBBgwasWLHCMgQWFhaG5q5bnKpWrcrKlSuZN28effr0oXLlyjz11FOMHDnSUub69etMnDiR2NhYypcvT8uWLfnmm28oX758ibevOJhM8OWXOh580EjduiabmtHv8tmnABg6d8FU+z4rRyOEEMKRKaoqo4HZiYwsnknQFSqUKXDdf/6poWNHd9zcVP75Jx5dKb4BLENbExLxblYfzc1Ybq77BkMX+1qdu7Dvq61xpPZKW+2XI7XXUdqa3s68KKUryIjsHDpknvTTqpWxVCc/93LZtB7NzViMNWtj6NTF2uEIIYRwcJIA2ZgjR2xw+wtVxSV9369nZN8vIYQQ1icJkA1R1Ts9QG3a2E4C5PTrMXRnTt3e92uYtcMRQgghJAGyJRcvKkREaHB2Vmne3HYSIJdVKwBI6TcAtbzs+yWEEML6JAGyIYcOmW/aa9HCiIuLlYPJqxs3cN68CYCkZ0fmUlgIIYQoGZIA2ZDDh21v+IuVK1EMBlKbtyCteUtrRyOEEEIANrYXmKObNy+Zxx5L5b77SufeX5kYjfDRRwAkjZDeHyGEEKWHJEA2pGxZ6NLFdnp/9Lt3wRXzvl8p/QZYOxwhhBDCQobARLFJv/U9eehT2M6kJSGEEI5AeoBsxNKlOuLiFAYPTqVu3dK/jKf2wj/o9/0IikKy7PslhBCilJEEyEasWaPnv/80t/cAK/3DYC6frTR/06MHplq1ofTnbEIIIRyIDIHZgOvXFf77T4NGo/Lgg6U/+SEhAZcv15m/HzPGurEIIYQQWZAEyAak3/7euLEJT08rB5MHLpvWo4m7ibF2bejWzdrhCCGEEJlIAmQDbGr9n7v2/Up+5jnQyEdMCCFE6SO/nWxA+gaorVuX/gTI6fgxdH+cRnVxkX2/hBBClFqSAJVyUVEKf/1lOwmQ66efAJD82EBUr/JWjkYIIYTImtwFVsr995+Cl5dK5comvL1L961Uyo0bOG/9DoBk2fdLCCFEKSYJUCnXqpWJP/+MJyJCsXYouXL94nOU1FRSW7QkrVlzSn/EQgghHJUMgdkAjQYqVy7dvT+kpeGy+lNA9v0SQghR+kkCVIqZTKCW8rwnnX73LrQh1zB5e5PSt7+1wxFCCCFyJAlQKbZ3r5bmzd154w29tUPJlWv6re9Pyr5fQgghSj9JgEqxw4e1hIZqiIkp3bNptP/+g/6Xn1AVhaSnn7V2OEIIIUSuJAEqxQ4fNs9RL+23v7t8tgIAQ5dumGrWsnI0QgghRO4kASqlEhLg1Cnz29O2bSlOgBIScPnqCwCS5NZ3IYQQNkISoFLq11+1pKUpVK9uokaN0jsT2mXDN2jibpJ2Xx1SH+ls7XCEEEKIPJEEqJRK3/+rVA9/qeqdyc+y75cQQggbIr+xSqn0BKg0D385HT2C07k/zPt+PfGktcMRQggh8kxWgi6lWrUyEh+v0KZNmrVDyZbrZ7d7f/oPkn2/hBBC2BTpASqlXnvNwN69idx/f+mc/2Pe92szIPt+CSGEsD2SAIkCcV37mXnfr5YPkNbU39rhCCGEEPkiCVApdOaMhsREa0eRg7Q0XD5fBcit70IIIWyTJEClTGoq9O7tRr16Hvz3X+lcAVq/awfa0BDzvl+9+1k7HCGEECLfJAEqZU6f1pCYqODhAbVqlc75P66rzCs/Jw99Wvb9EkIIYZPkLrBSJv3294ceSitdy+oYjeiOHMLp1En0+/fJvl9CCCFsmiRApUz6/l+laf0f/bYteMyYjDY09K6Dzjid+h1DjZrWC0wIIYQooNLUx+DwjEY4etTcA9SmTelIgPTbtuAZNBzN3ckPQEoynkHD0W/bYp3AhBBCiEKQBKgUOXdOQ1ycgoeHSqNGJmuHA0YjHjMmg6py73Ts9MceM6aYMzchhBDChkgCVIrcmf9jxKkUDE7qjhxCGxqaKflJp6gq2tAQdEcOlWhcQgghRGGVgl+zIl1gYBomUzLVq5eOu7804deLtJwQQghRWkgCVIrUqaPywgup1g7DwlS5SpGWE0IIIUoLGQIT2Upt3Rajjw/Z9UepioLRpxqprduWaFxCCCFEYVk9AVq3bh2dOnWiSZMmDBo0iNOnT+dYPi4ujuDgYNq3b0/jxo3p1q0bP//8c6HqLA0OHNDy1VdOhISUotWftVriX5+d5VOqYo4zfvZ80GpLMiohhBCi0KyaAO3YsYN58+YxZswYNm3aRP369QkKCiIqKirL8gaDgREjRhASEsKiRYvYtWsXb775JpUrVy5wnaXF55/rGD/elS++0Fk7lAy0oSEogHpPkmOq6kPcyjUYevWxTmBCCCFEIVh1DtCqVasYPHgwAwYMACA4OJh9+/axYcMGRo0alan8hg0buHnzJl999RU6nTlRqF69eqHqLA1U9c4dYKVpAUTlZixui98F4Na7izHVqo0m/DqmylXMw17S8yOEEMJGWS0BMhgMnD17lueff95yTKPR0LZtW06ePJnlOT/++CP+/v688cYb7N27l/Lly9OrVy9GjhyJVqstUJ2lwX//KYSHa9DrVVq0KD0JkOuyxWhiY0nzq0/K409KwiOEEMJuWC0BiomJwWg04u3tneG4t7c3Fy9ezPKcq1evcuTIEXr37s0nn3zClStXCA4OJi0tjbFjxxaozpwoxTAdJ73Ou+tO3/6ieXMjbm5Ff82CUK5fx+2TDwBInD4TxSn/yU9WbbVXjtRWcKz2SlvtlyO111Hamp/22dRt8Kqq4u3tzZtvvolWq6Vx48aEh4ezcuVKxo4dW+TX8/YuU+R1ZlV3eudU585OVKhQfNfMl5lTITERWrfGc9jjhfqpKc7XsbRxpLaCY7VX2mq/HKm9jtTW3FgtAfLy8kKr1WaanBwVFUWFChWyPKdixYo4OTmhvWsopk6dOkRERGAwGApUZ06iom6hFvGahIpi/gDeXfe+fe6ABn//RCIjrT8Eprl4Aa9PPkEBYqe+TlpUfIHqyaqt9sqR2gqO1V5pq/1ypPY6SlvT25kXVkuA9Ho9jRo14vDhwwQGBgJgMpk4fPgww4YNy/KcFi1asG3bNkwmExqN+Qa2S5cuUbFiRfR6PUC+68yJqlJsH5T0usPDFa5c0aDVqrRqZSwVH0y3+XNQ0tIwdAoktW17sl0IKI+K83UsbRypreBY7ZW22i9Haq8jtTU3Vr0NfsSIEXzzzTds2rSJCxcuMGvWLJKSkujfvz8AkydP5t1337WUHzJkCLGxscyZM4f//vuPffv28fHHHzN06NA811naVK6scu5cPF9/nYSHh7WjAe2Z07hsXA9AwvSZVo5GCCGEKB5WnQPUo0cPoqOjWbx4MRERETRo0IAVK1ZYhqvCwsIsPT0AVatWZeXKlcybN48+ffpQuXJlnnrqKUaOHJnnOkujChVUHn7Y+kNfAO5zgwFIfmwAaU2aWTkaIYQQongoqiqdYdmJjCyeOUAVKpQplroLS3foAOX69UB1ciL6wHFMde4vVH2lua1FzZHaCo7VXmmr/XKk9jpKW9PbmRdW3wrDkYWHKwwY4Mq77+qt/4FUVdxnzwIgedjThU5+hBBCiNJMEiArOnpUy/79Tmzb5mT1tRn0u3ag+/UYqqsriZOmWDcYIYQQophJAmRFhw6Vku0vjEbL3J+kUS9iqlzFuvEIIYQQxUwSICtK3/+rdWvrJkDO336F099/YSpXjsSxE6waixBCCFESJAGykuho+PPPUpAApaTgvmAuAInjJ6GWLWe9WIQQQogSIgmQlRw9al6BwNfXSMWK1psB7bp6JdprVzFWqUpS0CirxSGEEEKUJEmArKQ0DH8p8bdwe+9tABJfmQaurlaLRQghhChJkgBZiapCmTKqVSdAu36wBE1UFGn31yV5SP63ChFCCCFslSRAVvLmmymcPx9Pr15pVrm+EhGB64dLAUiY9ho4WXVRcCGEEKJEyW89K9JqzV/W4LboHTQJ8aQ2a46hdz/rBCGEEEJYifQAWUFionWvr7lyGdfPVgKQMGMWVl+FUQghhChhkgBZQZcu8MAD7hw5Yp3uH/e356EYDBg6PEJqxwCrxCCEEEJYkwyBlbDERDh+HFJTNVSpYirx62v/PIfzN18CkDBjZolfXwghhCgNpAeohJ04oSU1FXx8TNSqVfLr/7jPewNFVUnp1Ze05i1L/PpCCCFEaSA9QCUgJEQhKso8z+a778wvef36Rs6cMeefFSqo+PgUfzLkdOwozrt2oGq1JLz6erFfTwghhCitJAEqZikp0LWrGxERGTvbfvxRx48/6gCoVMnEiRMJODsXYyCqivts85BX8pBhGOvWK8aLCSGEEKWbDIEVM70eqlVTUZSse3gUxdz7o9cXcxw/7kF/5BCqszOJ/5tavBcTQgghSjlJgIqZosDUqSmoata3mquqwtSpKcV7J7rJhPvsYACSgp7H5FOtGC8mhBBClH6SAJWAgAAj/v5GNJqMvUBarYq/v5GAgOLdDsN503qczp7BVMaTxPEvF+u1hBBCCFsgCVAJSO8FMpkydvMYjSXQ+2Mw4P7WbACSxk5ALe9djBcTQgghbIMkQCUkvRdIqzX3ApVU74/L2tVoL1/CVLESiaNeLNZrCSGEELZCEqASkt4LZDSau3tKpPcnIQH3d+ebv500Bdzdi/FiQgghhO2QBKgEpfcCASXS++O2/EM0ETcw1qpN8rCni/VaQgghhC2RBKgEKQrMmJFCgwbmf4uz90eJjsJ1yfsAJEydQbHfZy+EEELYEFkIsYR17Gjk3DmIjDSiFuPiz26L30NzK460Rk1IeWxg8V1ICCGEsEHSA2SHNKEhuK78GLi94alG3mYhhBDibtIDZC+MRnRHDqEJv47z+m9QUlIwtGmHoVMXa0cmhBBClDqSANkB/bYteMyYjDY0NMNxQ0Bnivc2MyGEEMI2ydiIjdNv24Jn0HA09yQ/KuA+703027ZYJzAhhBCiFJMEyJYZjXjMmAyqyr39POmPPWZMAWPx3m4vhBBC2BpJgGyY7sghtKGhmZKfdIqqog0NQXfkUInGJYQQQpR2kgDZME349SItJ4QQQjgKSYBsmKlylSItJ4QQQjgKSYBsWGrrthh9fMhuPUVVUTD6VCO1ddsSjUsIIYQo7eQ2eFum1ZI4biIe0/6X6Sn19u3v8bPng1Zb0pEJIWyQyWQiOTmZ1FRDsa5UX1ooCg7TXntpq1brhKaIFveVBMjG6X/cgwKozs4oKSmW46aqPsTPno+hVx/rBSeEsAmqqhIXF01SUjwRERpMJpO1Qyox0dGO0157aaurqweenuVRCrnOnSRANky/eyfOe75H1emI+WE/msgINOHXMVWuYh72kp4fIUQepCc/Hh5euLm5ONTKGVqtgtFow10i+WDrbVVVFYMhhfj4GADKlvUuVH2SANmq5GQ8ZkwFIOn5MRj96mP0q2/loIQQtsZkMlqSHw8PT5ycNKSl2X4vQV45Unvtoa16vTMA8fExlCnjVajhMJkEbaPcPlqK9tJ/GCtXIXHiK9YORwhho4y3u3vSf7EIUdqlf1aNxrRC1SMJkA3ShFzD7f13AEiY+SaqRxkrRySEsHWFnU8hREkpqs+qJEA2yH3WDJTERFIfakPKgMHWDkcIIezGwIG9+eabL/Jc/rfffqV9+1bcunWrGKMSxUHmANkY3YFfcNm8EVWj4da8d2S3dyFE6WE0ojtyqERuxmjfvlWOz48YMZKgoOfzXe/y5Z/j6uqa5/JNmjRj8+ZdeHh45PtaBfXkkwMICwtl/fqteHtXKLHr2ptSkQCtW7eOlStXEhERQf369Xnttddo2rRplmU3btzItGnTMhzT6/WcOXPG8njq1Kls2rQpQ5n27duzcuXKog++JKWm4jF9MgDJTz+LsXETKwckhBBm+m1b8JgxGW1oqOWY0ceH+NkLimU5js2bd1m+37t3DytXfsQXX2ywHHN1dbN8r6oqRqMRJ6fcf+V5eXnlKw6dTleiScipU7+TkpLCI490ZufObQwb9kyJXTsraWlpeXpdSyOrD4Ht2LGDefPmMWbMGDZt2kT9+vUJCgoiKioq23M8PDw4cOCA5eunn37KVKZDhw4ZyixcuLA4m1EiXFctx+nPc5jKlydh6gxrhyOEEIA5+fEMGo7mruQHQBMWhmfQcPTbthT5Nb29K1i+PDw8UBTF8vjy5Ut07fowhw8f5NlnhxEQ0IbTp38nJOQaU6dOpHfvrnTp0oHnnnuKY8eOZqj33iGw9u1bsXXrd0yb9j86d27HE088xoEDP1uev3cIbMeOrXTv/ghHjx5m6NCBdOnSgYkTxxEZGWk5Jy0tjffff5vu3R+hR4/OfPDBYmbPnsm0aZNybff27Zvp0qU73br1YPv2zK/rjRvhzJz5Ko8+2onAwPYEBQ3n7Nk/LM8fOPALzz33FJ06taVnz85Mu2sh3fbtW/HLL/sy1Ne9+yPs2LEVgLCwUNq3b8XevbsZO3YUnTq1Zffundy8GcvMma/Sr9+jdO7cjqeeepw9e3ZlqMdkMrFu3Woef7wfAQFt6N+/J6tXmzslxo9/gYUL52coHxMTwyOPtObXX4/l+poUlNXTtlWrVjF48GAGDBgAQHBwMPv27WPDhg2MGjUqy3MURaFixYo51qvX63MtY0uUiAjcFswDIOHVmahe5a0ckRDCrqkqJCbmXs5oxOPVV0BVuXdAXlFVVEXBY/pkoh9+JPfhMDe3Ih3W/+ijpYwdOwEfn+qUKVOG8PBwWrdux6hRL6LT6dm1azuvvPIS69ZtoEqV7PdMXLVqOaNHj2PMmAmsX/81wcGvsWHDVjw9y2ZZPjk5mS+/XMNrr72Bomh4883XWLbsfWbOnA3AunWr2b17F9OmzaR27fv49tsv2b9/Hy1a5Dysl5iYwE8//cDHH39GrVq1SUhI4NSpkzRr1vz284mMHTuKihUr8dZbC/H29ubvv/9CVc23vh88uJ/p01/hqaeeZcaMYFJTUzly5GABX9eXqFfPD73eGYPBgJ9fA4YNexo3N3cOHz7A7NkzqVatOg0bNracs3Xrd4wfP5GmTf2JjIzkypVLAPTq1Y/33lvA2LEvo9frAdi9ewcVK1aiZcsH8h1fXlk1ATIYDJw9e5bnn78zTqvRaGjbti0nT57M9rzExEQCAgIwmUw0bNiQiRMnUq9evQxljh07Rps2bfD09KR169a89NJL+e7aLI7pNel15rdujzmz0MTdJK2pPynDnrKJqT8FbastcqS2gmO1197bmmW7VJVyvbqiO340iyfzWb+qog0LpWLd6rmWTX2wNbFbvy+yF/u5557ngQdaWx57epalXj1fy+ORI0ezf/8+Dh78mQEDHs+2nkcf7UWXLt0BeP75Maxf/xXnzp2ldTb7LKalpfHKK69SrZq5zf37D+azz1ZYnt+w4RuGDXuGjh0DAHj55ckcPpx7IvLDD7upXr0GdercD0Dnzl3Ztm2zJQHas2cXsbGxrFjxuSU5q169huX8zz5bSefOXTPMjbr79cirQYOG0LFjpwzHnnxyuOX7gQOf4NixI/z44w80bNiYxMQE1q//ipdfnsyjj/YCoFq16jRr5g9Ax44BvPfeAvbv/5nOnbsAsGPHNh59tFeOd3wpSuaPSn4+OlZNgGJiYjAajXh7Z1zN0dvbm4sXL2Z5zn333cfcuXPx8/Pj1q1bfPrppzzxxBNs377dksF36NCBLl26UL16da5evcrChQsZOXIkX3/9Ndp8TMjz9i6+28vzVffRo/DFGgCcPvqACpXLFU9QxaQ4X8fSxpHaCo7VXntta3JyMtHRGrRaBScn86wIJycNShHtt5QfinI7hnwmQBqNuXx6/Fqt+d9GjRpbjoH5j+cVKz7m4MH9REVFYjQaSUlJ4caN8AzlNBolw2NfX1/L4zJl3HF39yAuLhYnJ43lWk5OGpycNGg0Ci4uLtSqVdNyfqVKFYmJicbJSUN8/C2io6No0qRxhte7fv0GqKqa4br32rFjC92797SU6dGjJ6NHP8f//jcFd3d3Llz4Bz8/P8qXz/qP/fPnz9O372M5XuPuz8G9r8ed17VRhjJGo5HVqz9l7949RETcIDU1FYMhFVdXV5ycNFy9ehmDwcBDDz2U5bWdnFx59NGe7Ny5hW7duvHXX3/y338XeOed97IsbzIpaDQavLzccXFxybYtubH6EFh+NW/enObNm2d43KNHD7766iteeuklAHr27Gl53s/PDz8/PwIDAy29QnkVFXWryDeNUxTzf6R5rttkouzoF9EByY8/SXy9xhBpG7db5rutNsyR2gqO1V57b2tqqgGTyYTRqJKWZjKvFmxUidmyK09DYLojhyg3ZECu5WK/3GC+Kywnbm5gVIH8vdAmk7l8+irHRqP5X53OOcPKx4sWLeT48aOMGfMS1avXwNnZmddem4LBkJqhnMmkZnisKNp7HkNampG0NJPlWmlpJtLSTJhMKk5OTvfUZ56IbS6j3o4x4zVU9U6ZrPz330X++OMM586d5YMPFluOG41Gvv9+F336PIZOp0dVybYOZ2fnTNe9m6IolnakS0tLs7we6W3V6zO+rmvWrObrr79g/PhJ1KlTF1dXVxYvfheDwXD7M6XP8BplpWfPvowY8SShoWFs3bqZFi1aUbFilSzLG40qJpOJmJgEdLrUe9qQ9z9WrJoAeXl5odVqM014joqKokKFvM2q1+l0NGjQgCtXrmRbpkaNGnh5eXH58uV8JUDmD2Sei+dLXut2+WItupO/YfIoQ/yMYJv8D7g4X8fSxpHaCo7VXntta7ZtUhRwd8/1/NRHOmH08UETFoaSRWWqomCq6kPqI52svj/hmTOn6NGjt2XoKTExkbCwUPz9W5ZYDB4eHpQv782ff57D378FYE5izp//K8fhqG3bNuPv34KJEydnOL59+1a2bdtMnz6PUbduPbZt+464uJtZzk+qW7ceJ04cp2fPrO/KK1fOi6ioO5O1r169QnJycq5tOnPmFO3bd6Rbtx6AecLzlStXuO+++wAsyeaJE8fx8amWZR33318XP78GbN36HXv2fM/LL+e+w0FhfyateheYXq+nUaNGHD582HLMZDJx+PDhDL08OTF/cM7nOOH5+vXrxMbG2tykaCU2BvfZMwFIfGUaauXKVo5ICCHuodUSP3sBYE527pb+OH72fKsnPwDVq9fk559/5J9//uaff84THDzd0ntUkgYMGMzatavYv38fV65cYtGid7h1Kw4yTSM3S0tL4/vvdxAY2JU6depm+Ordux/nzv3BxYsXCAzsRvny3kyb9j/LXW/79u3ljz9OAxAUNIoffvielSs/5tKl/7hw4V/Wrv3Mcp0WLVqxceM3nD//F3/9dY533pmXp1vca9SowfHjRzlz5hSXLv3H22/PJSbmTseGs7MzQ4c+zQcfLGbnzm2EhFzjjz/OsG3bdxnq6d27H2vXfoaqqjz8cEA+X9X8s/oQ2IgRI5gyZQqNGzemadOmrF69mqSkJPr37w/A5MmTqVy5MpMmmW8PXLp0Kf7+/tSqVYu4uDhWrlxJaGgogwYNAiAhIYGlS5fSrVs3KlSowNWrV3n77bepVasWHTp0sFo7C8JtwVw0UVGk+fqR9Fz+F/QSQoiSYOjVh7iVazKtA2Sq6kP87PnFsg5QQYwb9zLz5r3BCy88S9my5Rg69GkS83KnWxEbOvRpoqOjmD17JhqNlj59HuPBB9tku7HngQM/Exd3M8ukoHbt+6hd+z62b9/MuHETee+9ZSxd+h6vvDIBo9FI7dp1LL1GLVu24s033+Kzz1awdu1nuLu7WyZQg/n1mTs3mDFjRuLtXZEJEybx999/5tqep58OIjQ0hIkTx+Hi4kKfPo/RocMjJCTEW8o888xzaLVaVq78mMjICLy9K9CvX8ah08DAbixe/C6Bgd1wdi7+vekUVbV+p+7atWstCyE2aNCAGTNm0KxZMwCGDx9OtWrVeOuttwCYO3cue/bsISIigrJly9KoUSNeeuklGjZsCJgn9I0ZM4Zz585x69YtKlWqRLt27ZgwYUKeh9XSRUYWzxygChXK5Fq39uwfeHVuj2IyEbt+C6kPP1K0gZSAvLbVHjhSW8Gx2mvvbU1NNRAVFYa3d1V0On3hdgwvwZWgi0pp2CHdZDIxdOhAOnXqwsiRo4vtOqWhrTkJCwvl8cf7sXz55/j51c+23L2f2bul/7zmRalIgEorqyVAqkrZfj3QHz5ISq++xH26pmiDKCH2/ovjbo7UVnCs9tp7W4s0AbJB1mjv9ethHDt2BH//FqSmprJhw9fs2LGVzz77ktq17yu265bW9zYtLY2bN2NZtmwRYWEhfPjhpzmWL6oEyOpDYCIz5+82oD98ENXVlfjgOdYORwghRBFSFIWdO7eybNn7qCrUqXM/77//QbEmP6XZ6dO/M378C9SoUZPZt+eTlQRJgEqb+HjcZ5m3uUgcPxFTjZq5nCCEEMKWVK5cJddeDkfSokUrDhz4tcSva/W9wERG7u+/gzYsFGPN2iSOmWDtcIQQQgi7JAlQKaK9+C+uHy4BIH72W1CIFS6FEEIIkT1JgEoLVcV9+hSU1FQMnQIxdHvU2hEJIYQQdksSoFJCv3sXznv3oOp0xM+Zb787LwohhBClgCRApUFyMh4zpgCQ9MJYjPfXy+UEIYQQQhSGJEClgNuHS9BevoSxSlUS8rD/iRBCCCEKRxIgK9Ncu4rb++8AkDDzTfDwsHJEQgghhP2TdYCszH3WDJSkJAyt25LSf5C1wxFCiHwLCVGIisp+3mKFCio+PkW7jHb79q1yfH7EiJEEBRVsD8X27Vsxd+47PJzHLYgWLJjDtm2bmTVrLp06BRbomqLkSQJkRbr9P+OyZROqRkP83Ldl4rMQwuakpEDXrm5ERGQ/oFCpkokTJxIoyv0tN2/eZfl+7949rFz5EV98scFyzNXVreguloPk5GT27t3Nk08+xfbtW6yeAKWmpqLT6awag62QBMhaUlPxmG7eoTf5mSCMjZtYOSAhhMg/vR6qVVOJjFRR1cx/xCmKufdHr8/i5ELw9r6zubWHhweKomQ4tnXrd3z11VrCwkKpUqUqAwc+Qf/bveypqaksWbKQn3/+kVu3buHlVZ5+/QYwfPgIBg7sDcCrr/4PgCpVqrJ+/dZs4/jppx+oXbsOw4Y9Q79+3QkPv07lylUszxsMBlas+IgffviemJhoKlWqzPDhz9CrVz8ALl68wEcfLeH330+iqir16vkyffosqlWrztixo6hXz48JEyZZ6ps2bRIeHmWYPn0WAAMH9qZXr75cvXqF/ft/pmPHAKZPn8UHHyzml1/2ERERTvnyFejatTsjR44C7mxOe+DAL3z22QouXvwXV1dXmjZtzrx577Bq1XJ+/HEPa9Z8k6GtzzzzJO3adSjWDVtLkiRAVuKy8hOc/voTU/nyJEyZbu1whBAik4SE7J/Tas1rtSoKTJ2awhNPZN3joqoKEyemZOjgzq5ed/dCBHuX3bt3smLFR0ycOJl69fz455+/mT9/Dq6urjz6aC++/fYrDhz4hTfeeAsfn6qEhl7nxo3rACxf/jm9e3fh1Vdn8tBDbdBoct7Nftu2zXTt+igeHh60bt2WnTu38cwzz1menz17Jn/8cZoJE/5H3br1CAsL5ebNWAAiIm4wduwomjdvweLFH+Lm5s6ZM6cwGtPy1d4vv1zDM8+M5NlnR1mOubm5MX36TCpUqMiFC/+yYMEcPDzcGTLkKQAOHTrA9Omv8NRTzzJjRjCpqakcOXIQgJ49+7Bq1XL+/PMsDRo0AuD8+b+4cOEf5swpub26ipskQCXJaER39BCEXcFt7psAJEyfhepV3sqBCSFEZvfdl/2u2oGBaXzxRRIAAQFGFCXrHiCADz/U0717kuVxq1buREVlHjK7ceNWISM2W7nyY8aOfYmOHTsB4ONTjf/+u8jmzRt59NFe3LhxnRo1atK0qT86nZaKFe/02Hh5eQHg4VEmQ49SVq5evcLZs2eYM+dtALp27cGSJe/x9NNBKIrClSuX+fHHPbz33jIeeOAhAKpVq245f+PGb3F39yA4eB5OTuZfxzVr1sp3e1u0eIAhQ4ZlOHZ3Ela1qg9Xrlxm797dlgTo888/pXPnrhnmSdWr5wtApUqVefDB1mzfvtWSAO3YsRV//xYZ4rd1kgCVEP22LXjMmIw2NBQw336n6nSYypazalxCCFFYimIeCktJyf75kpKUlERIyDXeeutNFiyYYzluNBpxdzffZfvoo715+eUxDBkygDZt2tKmTXsefLB1vq+1ffsWHnywDeXKlQOgTZt2vPXWm5w4cZxWrR7kn3/Oo9Vqad68ZZbn//PP3zRr5m9Jfgqqfv0GmY7t3bub9eu/IiQkhKSkxNvtv9PF9s8/f9O7d79s6+zd+zHmzXuDceNeRqPRsGfPLsaNm1ioOEsbSYBKgH7bFjyDhoN6z10Qqal4jnyaOM0aDL36WCc4IYTIxn//Zd8jo71nZOjPP+Pp18+NP/7QYDIpaDQqjRub+O67xExlf/01h7G1QkpKSgRgypQZNGzYOMNzGo2518nPrz7ffruZI0cOceLEcV5/fSqtWj3I7Nl5H94xGo3s3LmN6OgoOnZ8KMPx7du30KrVgzjnMus7t+c1Gg3qPb830tIyD4+5urpmePzHH6d5443XePbZUTz0UBvc3T3Yu3c3X3219q5r57zXZLt2HdDr9fzyy0/odDrS0tIICOic4zm2RhKg4mY04jFjMqgq9/4RpAAq4DFjCtGP9sz8P4oQQlhRfubkeHjAq6/emQtkMim8+mpKlkubFdVcn6yUL+9NhQoVCQ0NoWvX7PdUdHf3oHPnrnTr1p2OHTsxadI44uJu4ulZFicnJ0wmY47XOXz4IImJiXz66Tq02jvDeRcvXmDu3De4desW999fF5PJxMmTJyxDYHe7//567Ny5nbS0tCx7gcqV8yIqKtLy2Gg0cvHiBVq0yHkJgDNnTlO5chWefjrIcuz69bB7rl2XEyeO07Nn1n98Ozk50b17T3bs2IpOp6Nz5665Jk22RhZCLGa6I4fQhoZmSn7SKaqKNjQE3ZFDJRqXEEIUtYAAI/7+5sTB399IQEDOSURxCQp6njVrVvHtt19x5cplLlz4l+3bt1h6QL76ai179uzi8uVLXLlymZ9++gFvb288PMxznqpU8eHXX48TFRVJXFxcltfYvn0zbdu2o149X+rUqWv56tSpC2XKeLB7906qVvXh0Ud7MW/eG/zyyz5CQ0P47bdf2bt3DwADBgwmMTGemTOn8ddf57h69Qq7dm3nypVLALRo0YrDhw9w6NABLl++xDvvvEV8fO7zpGrUqEF4+HV++OF7QkKu8e23X/HLL/sylBkxYiQ//PA9K1d+zKVL/3Hhwr+sXftZhjK9e/fjt99+5ejRw/Ts2Tcf74BtkB6gYqYJv16k5YQQorRSFJg+PYXp052ZPj3Fakub9e7dD2dnF7788nM++GARLi6u3H9/XQYNGgKAm5s7X3zxOdeuXUWj0VK/fkPefnuRZYhs7NiXWLr0PbZu3UTFipUy3QYfHR3FoUMHmDlzTqZrazQaOnQIYPv2zQwYMJhJk6byySfLePfdt4iLu0nlylUYPnwEAGXLlmPRoo/44INFjB07Co1GS716vjRp0gyAXr368u+//zB79ky0Wi2DBz+Za+8PQPv2HXn88Sd5770FGAyptG3bjmeeCeLTTz+xlGnRohVvvvkWn322grVrP8Pd3Z1mzZpnqKdGjZo0btyUuLibNGrU+N7L2DxFvXeAUVhERt7KNG0nv3QH91PusZ65lovdtJ3Udh0Kd7FSRlGgQoUyRfI6lnaO1FZwrPbae1tTUw1ERYXh7V0VnU6Pk5OGtDSTtcMqMY7U3vy2VVVVnnjiMR57bCBPPDEs9xNKyL2f2bul/7zmhQyBFbPU1m0x+vigZvOnkKooGH2qkdq6bQlHJoQQQmQtJiaGDRu+Jjo6ih497PMmHRkCK25aLfGzF+AZNBxVUVDu+hMyPSmKnz1fJkALIYQoNXr37kK5cuV45ZXpeHp6WjucYiEJUAkw9OpD3Mo1GdYBAjBV9SF+9ny5BV4IIUSpcuDAr9YOodhJAlRCDL36EP1oT/RHD1E28SY33cpieKit9PwIIYQQViAJUEnSas0TnSuUITXylnkRICGEEEKUOJkELYQQItOKw0KUVkX1WZUESAghHJj29jC8wZDNRl5ClDLpn1WttnCDWDIEJoQQDkyj0eLq6kF8fAwAbm4uGK2zgLNVmEwKRqNj9H7ZeltVVcVgSCE+PgZXVw/LwpUFJQmQEEI4OE/P8gDEx8eQmKjBZHKMhQHBvHKzo7TXXtrq6uph+cwWhiRAQgjh4BRFoWxZbzw9vfD0dCYmJsEuV72+l6KAl5e7Q7TXXtqq1ToVuucnnSRAQgghAHMPgYuLCzpdqk3/kswrRcFh2utIbc0rmQQthBBCCIcjCZAQQgghHI4kQEIIIYRwODIHKAfZbOBeJHUWR92ljbTVfjlSe6Wt9suR2usobc1P+xRVlv8UQgghhIORITAhhBBCOBxJgIQQQgjhcCQBEkIIIYTDkQRICCGEEA5HEiAhhBBCOBxJgIQQQgjhcCQBEkIIIYTDkQRICCGEEA5HEiAhhBBCOBxJgIQQQgjhcCQBKgbr1q2jU6dONGnShEGDBnH69Okcy+/cuZPu3bvTpEkTevfuzc8//1xCkRbcxx9/zIABA2jevDlt2rThxRdf5OLFizmes3HjRvz8/DJ8NWnSpIQiLrglS5Zkirt79+45nmOL72m6Tp06ZWqvn58fwcHBWZa3pff1+PHjvPDCC7Rv3x4/Pz9++OGHDM+rqsqiRYto3749TZs25ZlnnuHSpUu51pvfn/mSkFNbU1NTefvtt+nduzf+/v60b9+eyZMnEx4enmOdBflZKCm5vbdTp07NFHtQUFCu9draewtk+fPr5+fHihUrsq2zNL+3xUU2Qy1iO3bsYN68eQQHB9OsWTNWr15NUFAQu3btwtvbO1P53377jUmTJjFx4kQCAgLYunUrY8aMYePGjfj6+lqhBXlz7Ngxhg4dSpMmTTAajSxcuJCgoCC2b9+Om5tbtud5eHiwa9cuy2PFRnbmq1evHqtWrbI81mq12Za11fc03fr16zEajZbH//zzDyNGjMjxP0NbeV8TExPx8/NjwIABjB07NtPzy5cvZ82aNbz11ltUr16dRYsWERQUxI4dO3B2ds6yzvz+zJeUnNqanJzMuXPnGD16NPXr1ycuLo45c+YwevRoNm7cmGO9+flZKEm5vbcAHTp0YN68eZbHer0+xzpt8b0FOHDgQIbHv/zyC9OnT6dbt2451lta39tio4oiNXDgQDU4ONjy2Gg0qu3bt1c//vjjLMtPmDBBHTVqVIZjgwYNUl977bVijbOoRUVFqb6+vuqxY8eyLbNhwwa1ZcuWJRhV0Vi8eLHap0+fPJe3l/c03ezZs9XAwEDVZDJl+bytvq++vr7qnj17LI9NJpParl07dcWKFZZjcXFxauPGjdVt27ZlW09+f+at4d62ZuXUqVOqr6+vGhISkm2Z/P4sWEtW7Z0yZYo6evTofNVjL+/t6NGj1aeeeirHMrby3hYlGQIrQgaDgbNnz9K2bVvLMY1GQ9u2bTl58mSW5/z++++0adMmw7H27dvz+++/F2eoRe7WrVsAlC1bNsdyiYmJBAQE0LFjR0aPHs0///xTEuEV2uXLl2nfvj2dO3dm0qRJhIaGZlvWXt5TMH+mt2zZwoABA3Ls1bHV9/Vu165dIyIiIsPPb5kyZWjWrFm2P78F+ZkvreLj41EUBU9PzxzL5ednobQ5duwYbdq0oVu3bsycOZOYmJhsy9rLexsZGcnPP//MwIEDcy1ry+9tQcgQWBGKiYnBaDRm6hr19vbOdn5MZGQkFSpUyFQ+MjKy2OIsaiaTiblz59KiRYsch3juu+8+5s6di5+fH7du3eLTTz/liSeeYPv27VSpUqUEI86fpk2bMm/ePO677z4iIiJYtmwZQ4cOZevWrXh4eGQqbw/vaboffviBW7du8dhjj2Vbxlbf13tFREQAZPnzm917V5Cf+dIoJSWFd955h549e2b5mU6X35+F0qRDhw506dKF6tWrc/XqVRYuXMjIkSP5+uuvsxzqsZf3dtOmTbi7u9O1a9ccy9nye1tQkgCJQgsODuaff/7hiy++yLFc8+bNad68eYbHPXr04KuvvuKll14q5igLrmPHjpbv69evT7NmzQgICGDnzp0MGjTIipEVvw0bNvDwww9TuXLlbMvY6vsqzFJTU5kwYQKqqmY70T2dLf8s9OzZ0/J9+iTfwMBAS6+QvdqwYQO9e/fOdg5bOlt+bwtKhsCKkJeXF1qtlqioqAzHo6KiMvUIpKtQoUKmvy5zKl/avPHGG+zbt4/Vq1fn+699nU5HgwYNuHLlSjFFVzw8PT2pXbt2tnHb+nuaLiQkhEOHDuWp6/xutvq+VqxYESBfP78F+Zn/f3v3FhJFG4cB/FHK0oxNcw0s2xalLZRt1YtF0g5kaqWYna50TaqrssQivVE8EGknzDwUqKmBRSyWZSJ0IAjUi4gUSxTEZMNEwxZrlQx3v4twPie/NPvUdZznBwvuzM74vv5512fnnZldSH78+IHk5GT09vaivLx8xp/0pxsLC5m3tzfc3NzQ09Pzn+ulXlsAeP36Nbq7u/8qwEi5tn+KAWgWOTk5wc/PD01NTcIyq9WKpqYm0SfkiXQ6HZqbm0XLGhsbodPp5rKp/5vNZkN2djaePn2KyspKeHt7z3gfY2Nj6OzsFP7xSIXFYoHJZPptu6Va01/V1NRg9erV2LFjx4y2k2pd161bB6VSKRq/3759Q0tLy2/H79+M+YViPPz09PSgoqICbm5uM97HdGNhIevr64PZbP5t26Vc23FGoxF+fn7YtGnTjLeVcm3/FKfAZlliYiJSU1Ph7+8PrVaLyspKjIyM4MCBAwCA8+fPY82aNTh79iwAwGAwID4+HuXl5di+fTvq6+vR1taG7Oxse3ZjWllZWairq0NxcTFWrFghnD+xcuVKLF++HMDkvhYWFkKn00GlUmFoaAhlZWXo7e1d8IdX8/LysHPnTnh5eaG/vx83btyAo6MjoqKiACyemk5ktVpRU1OD/fv3Y8kS8duElOtqsVhEn2g/fvyI9vZ2KBQKeHl5wWAwoKSkBCqVSrgM3tPTE2FhYcI2CQkJ2L17N+Li4gBMP+btZaq+KpVKnD59Gu/fv8etW7cwNjYmjGGFQiFcHv5rX6cbC/Y0VX8VCgUKCwsREREBDw8PmEwmXL58GSqVCqGhocI2i6G2Xl5eAH6G94aGBqSmpv7nPqRU27nCADTL9u7di8HBQRQUFGBgYACbN29GaWmpcMj006dPcHT898BbYGAgrly5gvz8fFy7dg0bNmxAUVHRgr9fzN27dwEA8fHxouUXL14U3hx+7evQ0BDS09MxMDAAhUIBPz8/3Lt3D76+vvPX8L/Q19eHlJQUmM1muLu7IygoCPfv34e7uzuAxVPTiRobG9Hb24uDBw9OWiflura1tcFgMAjPx+8JExsbi9zcXJw4cQIjIyPIyMjA0NAQgoKCUFpaKjp/wmQyia4emm7M28tUfT116hRevHgBAIiJiRFtV1VVBb1eD2ByX6cbC/Y0VX8zMzPR2dmJhw8f4uvXr/D09MTWrVtx5swZ0b2AFkNtc3NzAQBPnjyBzWb7bYCRUm3nioPNZrPZuxFERERE84nnABEREZHsMAARERGR7DAAERERkewwABEREZHsMAARERGR7DAAERERkewwABEREZHsMAAREf0BjUaDZ8+e2bsZRDRLeCdoIlrw0tLS8ODBg0nLQ0JCUFZWZocWEZHUMQARkSSEhoYKt/wfN/FrDIiIZoJTYEQkCU5OTlAqlaKHQqEA8HN6qrq6GsePH4dWq8WuXbvQ0NAg2r6jowMGgwFarRZ6vR7p6emwWCyi1xiNRuzbtw/+/v4ICQmZ9AW2X758wcmTJ7FlyxaEh4fj+fPnc9tpIpozDEBEtChcv34dERERqK2tRXR0NFJSUtDV1QUAGB4exrFjx6BQKGA0GpGfn4/Gxkbk5OQI21dXVyM7OxtHjhzB48ePUVxcjPXr14t+R2FhIfbs2YNHjx5h27ZtOHfuHMxm83x2k4hmCQMQEUnCy5cvERAQIHrcvHlTWB8ZGYnDhw9DrVYjOTkZ/v7+uHPnDgCgrq4Oo6OjyMvLw8aNGxEcHIyMjAzU1tbi8+fPAICSkhIkJiYiISEBarUaWq0WR48eFbUhNjYWUVFRUKlUSElJwfDwMFpbW+ftb0BEs4fnABGRJOj1emRmZoqWjU+BAUBAQIBonU6nQ3t7OwCgq6sLGo0GLi4uwvrAwEBYrVZ0d3fDwcEB/f39CA4OnrINGo1G+NnFxQWurq4YHBz82y4RkR0xABGRJDg7O0OlUs3JvpctW/ZHr1u6dKnouYODA6xW61w0iYjmGKfAiGhRePv2reh5S0sLfHx8AAA+Pj7o6OjA8PCwsP7NmzdwdHSEWq2Gq6sr1q5di6ampvlsMhHZEQMQEUnC6OgoBgYGRI+J008NDQ0wGo3o7u5GQUEBWltbERcXBwCIjo6Gk5MT0tLS0NnZiebmZuTk5CAmJgYeHh4AgKSkJNy+fRtVVVX48OED3r17J5xDRESLD6fAiEgSXr16hZCQENEytVotXO6elJSE+vp6ZGVlQalU4urVq/D19QXwc/qsrKwMFy5cwKFDh+Ds7Izw8HCkpaUJ+4qNjcX3799RUVGBS5cuYdWqVYiMjJy/DhLRvHKw2Ww2ezeCiOj/0Gg0KCoqQlhYmL2bQkQSwSkwIiIikh0GICIiIpIdToERERGR7PAIEBEREckOAxARERHJDgMQERERyQ4DEBEREckOAxARERHJDgMQERERyQ4DEBEREckOAxARERHJDgMQERERyc4/kWDz0EvszmkAAAAASUVORK5CYII="
|
||
},
|
||
"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"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Test loss: 0.4564070403575897\n",
|
||
"Test accuracy: 0.8407142758369446\n",
|
||
"Classification Report: \n",
|
||
" precision recall f1-score support\n",
|
||
"\n",
|
||
" 0 0.80 0.91 0.85 4192\n",
|
||
" 1 0.89 0.77 0.83 4208\n",
|
||
"\n",
|
||
" accuracy 0.84 8400\n",
|
||
" macro avg 0.85 0.84 0.84 8400\n",
|
||
"weighted avg 0.85 0.84 0.84 8400\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Import necessary libraries\n",
|
||
"from tensorflow.keras.models import Sequential\n",
|
||
"from tensorflow.keras.layers import Dense, Dropout\n",
|
||
"from tensorflow.keras.callbacks import EarlyStopping\n",
|
||
"from sklearn.model_selection import train_test_split\n",
|
||
"from sklearn.preprocessing import StandardScaler\n",
|
||
"from tensorflow.keras.layers import BatchNormalization\n",
|
||
"from tensorflow.keras import regularizers\n",
|
||
"from tensorflow.keras.optimizers import Adam\n",
|
||
"from sklearn.metrics import confusion_matrix, roc_curve, auc\n",
|
||
"import seaborn as sns\n",
|
||
"\n",
|
||
"# 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)\n",
|
||
"\n",
|
||
"# 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), 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",
|
||
"# 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",
|
||
"# Print the classification report\n",
|
||
"print('Classification Report: \\n', report)"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-19T03:10:33.868830Z",
|
||
"start_time": "2024-03-19T03:09:37.788190Z"
|
||
}
|
||
},
|
||
"id": "c8745832a585d5ec",
|
||
"execution_count": 78
|
||
},
|
||
{
|
||
"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_8, dense_9, dense_10, and dense_11) 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_8 and dense_10 introduce a slight positive bias to the activations in subsequent layers, potentially affecting the model's predictions. The biases in dense_9 and dense_11 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.\n",
|
||
"\n",
|
||
"## 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.\n",
|
||
"\n",
|
||
"## 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": "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"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 500x500 with 2 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"data": {
|
||
"text/plain": "<Figure size 640x480 with 1 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()\n",
|
||
"\n",
|
||
"# 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",
|
||
"# 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": "2024-03-19T03:10:36.004529Z",
|
||
"start_time": "2024-03-19T03:10:33.870523Z"
|
||
}
|
||
},
|
||
"id": "41091791008ff727",
|
||
"execution_count": 79
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [],
|
||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "48396392f3b959d5"
|
||
}
|
||
],
|
||
"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
|
||
}
|