2401 lines
1.7 MiB
2401 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": "2024-03-19T07:38:28.509554Z",
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||
"start_time": "2024-03-19T07:38:28.504225Z"
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||
}
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||
},
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||
"id": "2aa3c6c09e8645d1",
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||
"execution_count": 77
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||
},
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||
{
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||
"cell_type": "code",
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||
"outputs": [],
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||
"source": [
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"# Define the directory where the dataset is located\n",
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"DATASET_DIR = './UWB-LOS-NLOS-Data-Set/dataset'\n",
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"\n",
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"def load_data(dataset_dir):\n",
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||
" # Load the data\n",
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" # file_paths = [os.path.join(dirpath, file) for dirpath, _, filenames in os.walk(dataset_dir) for file in filenames if 'uwb_dataset_part7.csv' not in file]\n",
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||
" file_paths = [os.path.join(dirpath, file) for dirpath, _, filenames in os.walk(dataset_dir) for file in filenames]\n",
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||
" data = pd.concat((pd.read_csv(file_path) for file_path in file_paths))\n",
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||
" print(f\"Original data shape: {data.shape}\")\n",
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||
" return data\n"
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||
],
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||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
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||
"end_time": "2024-03-19T07:38:29.082256Z",
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||
"start_time": "2024-03-19T07:38:29.077981Z"
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||
}
|
||
},
|
||
"id": "7bcd7cfc8dd11cbb",
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||
"execution_count": 78
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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": "2024-03-19T07:38:29.145811Z",
|
||
"start_time": "2024-03-19T07:38:29.141799Z"
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||
}
|
||
},
|
||
"id": "9e0b1ed6f23a17cf",
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||
"execution_count": 79
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||
},
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||
{
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||
"cell_type": "markdown",
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"source": [
|
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"# Channel Impulse Response (CIR) Graphs\n",
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"\n",
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"This code block defines a function `cir_graphs` to plot the Channel Impulse Response (CIR) for Line of Sight (LOS) and Non-Line of Sight (NLOS) data. The CIR is a sequence of values representing the channel response to a single impulse. It is used to characterize the channel in wireless communication systems."
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||
],
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||
"metadata": {
|
||
"collapsed": false
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||
},
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||
"id": "1dd92fe7b6881ea6"
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||
},
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||
{
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||
"cell_type": "code",
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||
"outputs": [],
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||
"source": [
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||
"def cir_graphs(data):\n",
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" # Separate the data into LOS and NLOS\n",
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" data_los = data[data['NLOS'] == 0]\n",
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" data_nlos = data[data['NLOS'] == 1]\n",
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"\n",
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" # Extract the CIR columns\n",
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" cir_columns = [col for col in data.columns if 'CIR' in col]\n",
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" data_los_cir = data_los[cir_columns]\n",
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" data_nlos_cir = data_nlos[cir_columns]\n",
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"\n",
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" # Calculate the magnitude and time for each CIR column\n",
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" time_los = np.arange(len(data_los_cir.columns))\n",
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" magnitude_los = np.linalg.norm(data_los_cir.values, axis=0)\n",
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"\n",
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" time_nlos = np.arange(len(data_nlos_cir.columns))\n",
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" magnitude_nlos = np.linalg.norm(data_nlos_cir.values, axis=0)\n",
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"\n",
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" # Plot the magnitude vs time for LOS\n",
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" plt.figure(figsize=(20, 10), dpi=300) # Increase figure size and DPI\n",
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" plt.plot(time_los, magnitude_los, linewidth=2) # Increase line width\n",
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" plt.title('Magnitude vs Time for LOS')\n",
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" plt.xlabel('Time (ns)')\n",
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" plt.ylabel('Magnitude')\n",
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||
" plt.xlim([600, max(time_los)]) # Set x-axis limits\n",
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||
" plt.ylim([0, 2e6])\n",
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||
" plt.show()\n",
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"\n",
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" # Plot the magnitude vs time for NLOS\n",
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" plt.figure(figsize=(20, 10), dpi=300) # Increase figure size and DPI\n",
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" plt.plot(time_nlos, magnitude_nlos, linewidth=2) # Increase line width\n",
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||
" plt.title('Magnitude vs Time for NLOS')\n",
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" plt.xlabel('Time (ns)')\n",
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||
" plt.ylabel('Magnitude')\n",
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||
" plt.xlim([600, max(time_los)]) # Set x-axis limits\n",
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||
" plt.ylim([0, 2e6])\n",
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||
" plt.show()\n",
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||
" "
|
||
],
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||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-19T07:38:29.222171Z",
|
||
"start_time": "2024-03-19T07:38:29.215487Z"
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||
}
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||
},
|
||
"id": "308d64639b199bc7",
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||
"execution_count": 80
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||
},
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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."
|
||
],
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||
"metadata": {
|
||
"collapsed": false
|
||
},
|
||
"id": "bfd97fbe797a7067"
|
||
},
|
||
{
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||
"cell_type": "code",
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||
"outputs": [],
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||
"source": [
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||
"\n",
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"def snr_graph(data):\n",
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" # Separate the data into LOS and NLOS\n",
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||
" data_los = data[data['NLOS'] == 0]\n",
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" data_nlos = data[data['NLOS'] == 1]\n",
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"\n",
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" # Extract the SNR values\n",
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" snr_los = data_los['SNR']\n",
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" snr_nlos = data_nlos['SNR']\n",
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"\n",
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" # Create a new figure\n",
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" plt.figure(figsize=(10, 5))\n",
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"\n",
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" # Plot SNR for LOS\n",
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" plt.plot(snr_los, label='LOS')\n",
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"\n",
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" # Plot SNR for NLOS\n",
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" plt.plot(snr_nlos, color='red', label='NLOS')\n",
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"\n",
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||
" # Set title and labels\n",
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" plt.title('SNR for LOS and NLOS')\n",
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||
" plt.xlabel('Index')\n",
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" plt.ylabel('SNR')\n",
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"\n",
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||
" # Add a legend\n",
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||
" plt.legend()\n",
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||
"\n",
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||
" # Show the plot\n",
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||
" plt.show()\n",
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||
" "
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-19T07:38:29.252847Z",
|
||
"start_time": "2024-03-19T07:38:29.248689Z"
|
||
}
|
||
},
|
||
"id": "4afc8d71b3271351",
|
||
"execution_count": 81
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||
},
|
||
{
|
||
"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",
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||
" reds = labels == 1\n",
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||
" blacks = labels == 0\n",
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||
" plt.scatter(data[reds][feature1], data[reds][feature2], c=\"red\", s=20, edgecolor='k')\n",
|
||
" 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": "2024-03-19T07:38:29.355179Z",
|
||
"start_time": "2024-03-19T07:38:29.351040Z"
|
||
}
|
||
},
|
||
"id": "ac4db13fed3f9916",
|
||
"execution_count": 82
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||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"source": [
|
||
"## denoise_cir Function\n",
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||
"\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",
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||
"\n",
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||
"1. **Wavelet Decomposition:**\n",
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||
"\n",
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||
" The input signal `x` is passed through two complementary filters and emerges as two signals. The filter outputs are decimated by 2 (down-sampled) to get the approximation coefficients (cA) and detail coefficients (cD).\n",
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||
"\n",
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||
" The approximation coefficients represent the high-scale, low-frequency component of the signal, while the detail coefficients represent the low-scale, high-frequency component.\n",
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||
"\n",
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||
"2. **Thresholding:**\n",
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||
"\n",
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||
" The detail coefficients are thresholded to remove noise. The thresholding function `T` applied to the detail coefficients `x` is defined as:\n",
|
||
"$$\n",
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||
"T(x) = x * I(|x| > \\text{{value}}) \\quad \\text{{for 'hard' thresholding}}\n",
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||
"$$\n",
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||
"\n",
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||
"$$\n",
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||
"T(x) = \\text{{sign}}(x)(|x| - \\text{{value}})_+ \\quad \\text{{for 'soft' thresholding}}\n",
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||
"$$\n",
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||
"\n",
|
||
"where $I$ is the indicator function that is one if the argument is true and zero otherwise, $\\text{{value}}$ is the threshold value, and $(x)_+$ equals $x$ if $x > 0$ and zero otherwise.\n",
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||
"\n",
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||
"3. **Wavelet Reconstruction:**\n",
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||
"\n",
|
||
" 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",
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||
" # 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": "2024-03-19T07:38:29.387344Z",
|
||
"start_time": "2024-03-19T07:38:29.383183Z"
|
||
}
|
||
},
|
||
"id": "fe3089568e99a58d",
|
||
"execution_count": 83
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:29.471791Z",
|
||
"start_time": "2024-03-19T07:38:29.468045Z"
|
||
}
|
||
},
|
||
"id": "670e8c2cf19126ea",
|
||
"execution_count": 84
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:29.538972Z",
|
||
"start_time": "2024-03-19T07:38:29.521823Z"
|
||
}
|
||
},
|
||
"id": "685463c2d6065b08",
|
||
"execution_count": 85
|
||
},
|
||
{
|
||
"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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|
||
},
|
||
"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": "2024-03-19T07:38:35.802067Z",
|
||
"start_time": "2024-03-19T07:38:29.639920Z"
|
||
}
|
||
},
|
||
"id": "79c2c23691b26753",
|
||
"execution_count": 86
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.808993Z",
|
||
"start_time": "2024-03-19T07:38:35.804164Z"
|
||
}
|
||
},
|
||
"id": "12e16974341e6266",
|
||
"execution_count": 87
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.814147Z",
|
||
"start_time": "2024-03-19T07:38:35.809900Z"
|
||
}
|
||
},
|
||
"id": "54d2a6506b584a03",
|
||
"execution_count": 88
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.817950Z",
|
||
"start_time": "2024-03-19T07:38:35.815699Z"
|
||
}
|
||
},
|
||
"id": "dc485f3de9f8936f",
|
||
"execution_count": 89
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.821333Z",
|
||
"start_time": "2024-03-19T07:38:35.818980Z"
|
||
}
|
||
},
|
||
"id": "702b4f40dda16736",
|
||
"execution_count": 90
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.824585Z",
|
||
"start_time": "2024-03-19T07:38:35.822302Z"
|
||
}
|
||
},
|
||
"id": "1f6f826d6234591c",
|
||
"execution_count": 91
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.828064Z",
|
||
"start_time": "2024-03-19T07:38:35.825616Z"
|
||
}
|
||
},
|
||
"id": "c970b0c1593d955c",
|
||
"execution_count": 92
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.831341Z",
|
||
"start_time": "2024-03-19T07:38:35.829061Z"
|
||
}
|
||
},
|
||
"id": "ee7506f4aa805faf",
|
||
"execution_count": 93
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.834627Z",
|
||
"start_time": "2024-03-19T07:38:35.832326Z"
|
||
}
|
||
},
|
||
"id": "a44d38efa4b86d93",
|
||
"execution_count": 94
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.839045Z",
|
||
"start_time": "2024-03-19T07:38:35.836876Z"
|
||
}
|
||
},
|
||
"id": "a3646a4965b0707c",
|
||
"execution_count": 95
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.841992Z",
|
||
"start_time": "2024-03-19T07:38:35.839886Z"
|
||
}
|
||
},
|
||
"id": "c7ecae5d021ad44f",
|
||
"execution_count": 96
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.845078Z",
|
||
"start_time": "2024-03-19T07:38:35.842804Z"
|
||
}
|
||
},
|
||
"id": "4a8a1c3a7289ef7a",
|
||
"execution_count": 97
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.848207Z",
|
||
"start_time": "2024-03-19T07:38:35.845893Z"
|
||
}
|
||
},
|
||
"id": "705c62e64bf6d614",
|
||
"execution_count": 98
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.855493Z",
|
||
"start_time": "2024-03-19T07:38:35.849066Z"
|
||
}
|
||
},
|
||
"id": "cf4df4ef7bbfd74",
|
||
"execution_count": 99
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.858829Z",
|
||
"start_time": "2024-03-19T07:38:35.856406Z"
|
||
}
|
||
},
|
||
"id": "faabcf63e34005a9",
|
||
"execution_count": 100
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.862410Z",
|
||
"start_time": "2024-03-19T07:38:35.859769Z"
|
||
}
|
||
},
|
||
"id": "2ed22b3fc59f74e6",
|
||
"execution_count": 101
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.866196Z",
|
||
"start_time": "2024-03-19T07:38:35.863458Z"
|
||
}
|
||
},
|
||
"id": "4ac86c268055c1b8",
|
||
"execution_count": 102
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.869492Z",
|
||
"start_time": "2024-03-19T07:38:35.867256Z"
|
||
}
|
||
},
|
||
"id": "3d984228fb1d3026",
|
||
"execution_count": 103
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.872527Z",
|
||
"start_time": "2024-03-19T07:38:35.870543Z"
|
||
}
|
||
},
|
||
"id": "98cd350871bc3201",
|
||
"execution_count": 104
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.875735Z",
|
||
"start_time": "2024-03-19T07:38:35.873516Z"
|
||
}
|
||
},
|
||
"id": "305a796294814705",
|
||
"execution_count": 105
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.878936Z",
|
||
"start_time": "2024-03-19T07:38:35.876716Z"
|
||
}
|
||
},
|
||
"id": "494bb537046bf5a7",
|
||
"execution_count": 106
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.882165Z",
|
||
"start_time": "2024-03-19T07:38:35.879899Z"
|
||
}
|
||
},
|
||
"id": "62401c8d1a4d61cc",
|
||
"execution_count": 107
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.886210Z",
|
||
"start_time": "2024-03-19T07:38:35.883249Z"
|
||
}
|
||
},
|
||
"id": "f0f5284581e70e6e",
|
||
"execution_count": 108
|
||
},
|
||
{
|
||
"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": "2024-03-19T07:38:35.889775Z",
|
||
"start_time": "2024-03-19T07:38:35.887276Z"
|
||
}
|
||
},
|
||
"id": "82c7ba8cbb2aa17a",
|
||
"execution_count": 109
|
||
},
|
||
{
|
||
"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": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Epoch 1/20\n",
|
||
"1050/1050 [==============================] - 27s 24ms/step - loss: 0.7427 - accuracy: 0.6574 - val_loss: 0.5271 - val_accuracy: 0.7883\n",
|
||
"Epoch 2/20\n",
|
||
"1050/1050 [==============================] - 24s 22ms/step - loss: 0.5889 - accuracy: 0.7495 - val_loss: 0.5016 - val_accuracy: 0.8063\n",
|
||
"Epoch 3/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.5518 - accuracy: 0.7736 - val_loss: 0.4923 - val_accuracy: 0.8000\n",
|
||
"Epoch 4/20\n",
|
||
"1050/1050 [==============================] - 25s 24ms/step - loss: 0.5361 - accuracy: 0.7816 - val_loss: 0.4788 - val_accuracy: 0.8023\n",
|
||
"Epoch 5/20\n",
|
||
"1050/1050 [==============================] - 26s 24ms/step - loss: 0.5252 - accuracy: 0.7882 - val_loss: 0.4801 - val_accuracy: 0.7985\n",
|
||
"Epoch 6/20\n",
|
||
"1050/1050 [==============================] - 30s 29ms/step - loss: 0.5155 - accuracy: 0.7903 - val_loss: 0.4737 - val_accuracy: 0.7986\n",
|
||
"Epoch 7/20\n",
|
||
"1050/1050 [==============================] - 29s 28ms/step - loss: 0.5119 - accuracy: 0.7888 - val_loss: 0.4711 - val_accuracy: 0.8002\n",
|
||
"Epoch 8/20\n",
|
||
"1050/1050 [==============================] - 25s 24ms/step - loss: 0.5065 - accuracy: 0.7913 - val_loss: 0.4709 - val_accuracy: 0.7985\n",
|
||
"Epoch 9/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4934 - accuracy: 0.7966 - val_loss: 0.4697 - val_accuracy: 0.7967\n",
|
||
"Epoch 10/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4855 - accuracy: 0.8002 - val_loss: 0.4653 - val_accuracy: 0.7982\n",
|
||
"Epoch 11/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4875 - accuracy: 0.7966 - val_loss: 0.4625 - val_accuracy: 0.7986\n",
|
||
"Epoch 12/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4800 - accuracy: 0.8008 - val_loss: 0.4673 - val_accuracy: 0.7964\n",
|
||
"Epoch 13/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4779 - accuracy: 0.8024 - val_loss: 0.4541 - val_accuracy: 0.8037\n",
|
||
"Epoch 14/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4718 - accuracy: 0.8054 - val_loss: 0.4544 - val_accuracy: 0.8020\n",
|
||
"Epoch 15/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4663 - accuracy: 0.8088 - val_loss: 0.4743 - val_accuracy: 0.8013\n",
|
||
"Epoch 16/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4671 - accuracy: 0.8073 - val_loss: 0.4617 - val_accuracy: 0.7995\n",
|
||
"Epoch 17/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4599 - accuracy: 0.8109 - val_loss: 0.4384 - val_accuracy: 0.8115\n",
|
||
"Epoch 18/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4515 - accuracy: 0.8163 - val_loss: 0.4541 - val_accuracy: 0.8004\n",
|
||
"Epoch 19/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4509 - accuracy: 0.8191 - val_loss: 0.4313 - val_accuracy: 0.8170\n",
|
||
"Epoch 20/20\n",
|
||
"1050/1050 [==============================] - 24s 23ms/step - loss: 0.4500 - accuracy: 0.8205 - val_loss: 0.4385 - val_accuracy: 0.8138\n",
|
||
"263/263 [==============================] - 1s 3ms/step\n"
|
||
]
|
||
}
|
||
],
|
||
"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",
|
||
"# 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 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,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-19T08:55:16.427854Z",
|
||
"start_time": "2024-03-19T08:46:55.875862Z"
|
||
}
|
||
},
|
||
"id": "1c1dd203ad7db076",
|
||
"execution_count": 123
|
||
},
|
||
{
|
||
"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: 0.43853795528411865\n",
|
||
"Test accuracy: 0.8138095140457153\n",
|
||
"Classification Report: \n",
|
||
" precision recall f1-score support\n",
|
||
"\n",
|
||
" 0 0.75 0.95 0.84 4192\n",
|
||
" 1 0.93 0.68 0.78 4208\n",
|
||
"\n",
|
||
" accuracy 0.81 8400\n",
|
||
" macro avg 0.84 0.81 0.81 8400\n",
|
||
"weighted avg 0.84 0.81 0.81 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": "2024-03-19T08:55:16.895129Z",
|
||
"start_time": "2024-03-19T08:55:16.429136Z"
|
||
}
|
||
},
|
||
"id": "89aa08d7d1866179",
|
||
"execution_count": 124
|
||
},
|
||
{
|
||
"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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29q5du+rjjz+Wr6+v3UcYe3t7a8aMGRozZowGDBig2NhYNWvWTMePH9f27dvVoEEDvfbaa2XuKzAwUCNHjtSSJUv08MMP65ZbbtHevXv18ccfq0mTJpe8YnIp7du31+rVq/XKK6+odevW8vf3V/fu3dW/f3/ddNNNat++vRo3bqxvvvlGW7ZsueSD/wBQVcxXzpmvpIt/f2vUqFHq27evDhw4oFWrVqlz58667bbbyl3n1ltv1XvvvacJEybo1ltv1eHDh7VmzRq1bdtWZ8+etS33zDPP6NSpU7r55pvVrFkzHT16VCtWrFBoaKjatGljG98PP/xQDz/8sAYNGqT27dsrPz9f33//vbZs2aIPPvhA/v7+FdoWahdCC2xCQkK0ePFiJSUlae7cuWrevLkmTZqkzMxMu0lAkh566CFdd911+sc//qH58+dLuvgAY48ePRQTE+Pwvu+77z5t2rRJycnJOnv2rJo3b64RI0Zo/PjxtmUCAwP15ptvav78+Xr//fe1evVqNW7cWG3btrV9RntFHT58WHPmzLFrK/n6pptusk0CnTt3Vlpamt555x2dPHlSderU0fXXX6+nnnqqwr+Y33DDDQoICFBWVpbdFZWS/4+IiCj114W7deumN954Q6+88opWrFihs2fPqmnTpoqIiNB99913yf098cQTqlu3rt58802lpqaqY8eOWrx4sYYNG1bpv2I8YcIEHT16VIsWLVJeXp5uuukmde/eXSNGjNCHH36ozz77TAUFBbrmmmv06KOPOvxLAAA4gvnKOfOVJD377LPatGmT5s6dqwsXLqh///565plnLvmmV2xsrE6ePKk33nhDn376qdq2bav//d//1ebNm+0C2l133aW1a9dq1apVOn36tJo2baq+fftq0qRJtucrr7rqKi1fvlwLFizQ5s2btXHjRjVo0EDXXXedJk2apIYNG1Z4W6hdvKyKPG0LoEY7ffq0unbtqkcffVTjxo1zdzkAAAAOIYoCtcy5c+dKtS1dulTSxXflAAAAahpuD0Otkp2draKionK/f8UVV6hx48auK8gNUlJStGHDBv3+979XvXr19NVXX+ntt99WdHS03e1pAAD3Yb4CHENoQa1y7733XvIPYN10001avny5CytyveDgYPn4+NiePwkICNDIkSP16KOPurs0AMD/Y74CHMMzLahVdu3aZftM+rL4+flV+GMfAQBwFuYrwDGEFgAAAABG40F8AAAAAEYjtAAAAAAwGqEFAAAAgNHc9ulhWVlnVNOepvHykgICGtbI2k3COFYfxrJ6eMo4lvQTZTPx+HvKuVke+k//6X/t739F5ya3hRbLUo09ADW5dpMwjtWHsawejKNnM/n4m1ybK9B/+k//3V2F+3F7GAAAAACjEVoAAAAAGI3QAgAAAMBohBYAAAAARiO0AAAAADAaoQUAAACA0QgtAAAAAIxGaAEAAABgNEILAAAAAKMRWgAAAAAYjdACAAAAwGgOhZZ58+YpODjY7r8777zTWbUBADzMjh079PDDDys6OlrBwcHaunXrZdfZvn27Bg0apLCwMN1+++166623XFApAMCV6ji6wo033qjk5GTb1z4+PtVaEADAc509e1bBwcEaPHiwJk6ceNnlDx06pLFjx2ro0KGaNWuWUlNT9cwzz6hp06a65ZZbXFAxAMAVHA4tPj4+atq0qTNqAQB4uJ49e6pnz54VXn7NmjVq0aKFnnzySUlSmzZttGvXLv3jH/8gtABALeLwMy0//fSToqOjddttt2ny5Mk6evSoM+oCAOCydu/ere7du9u1RUdHa/fu3e4pCADgFA5daYmIiFBSUpKuv/56ZWZmav78+Ro+fLg2bdqkBg0aOLRjLy+HFjdCSc0+Pl6S3NcBy7JUXGy5bf9VVTKONfEcMA1jWT08ZRxrY/9OnjypwMBAu7bAwEDl5ubq3Llzqlu3boW3ZeL4eMq5WR76b/9veby9veTlxkFy1u8lHH/7f2urivbPodDy60v2ISEh6tChg3r16qV3331XcXFxDhUYENDQoeVN4teovny83XcGFRVbbt1/danJ54BpGMvqwTh6NpOPv8m1uQL9v3T/3f17gbP3z/H37P6XcPiZll/z8/PTddddp4MHDzq8blbWGVk17GKBl9fFE8fH20t/XJOmfSdyXV5D29810JyhkcrJyVNRUbHL918dSsaxJp4DpmEsq4enjGNJP2uTwMBAnTx50q7t5MmTatCggUNXWSQz5yVPOTfLQ/8v338fH281aVK/Vv5ewvH3jP5XdG6qUmjJy8vToUOHKvVgvmWpRh+AfSdylXH0tFtrqMnjJ9X8c8AkjGX1YBxrno4dO+rjjz+2a/v888/VsWNHh7dl8vE3uTZXoP+X739t/r2E4+/Z/S/h0IP4L7zwgr788ksdPnxYX331lSZOnChvb28NGDDAWfUBADxIXl6evvvuO3333XeSpMOHD+u7776zfejL7NmzNWXKFNvyQ4cO1aFDh/Q///M/+uGHH7Ry5Uq9++67GjVqlDvKBwA4iUNXWn7++Wc9/vjj+uWXX+Tv76/OnTtr7dq18vf3d1Z9AAAPsmfPHo0cOdL2dVJSkiRp0KBBev7555WZmaljx47Zvt+yZUstWLBASUlJWrZsmZo3b64ZM2bwcccAUMs4FFr+/ve/O6sOAADUrVs37d27t9zvP//882Wus3HjRidWBQBwN4f/TgsAAAAAuBKhBQAAAIDRCC0AAAAAjEZoAQAAAGA0QgsAAAAAoxFaAAAAABiN0AIAAADAaIQWAAAAAEYjtAAAAAAwGqEFAAAAgNEILQAAAACMRmgBAAAAYDRCCwAAAACjEVoAAAAAGI3QAgAAAMBohBYAAAAARiO0AAAAADAaoQUAAACA0QgtAAAAAIxGaAEAAABgNEILAAAAAKMRWgAAAAAYjdACAAAAwGiEFgAAAABGI7QAAAAAMBqhBQAAAIDRCC0AAAAAjEZoAQAAAGA0QgsAAAAAoxFaAAAAABiN0AIAAADAaIQWAAAAAEYjtAAAAAAwGqEFAAAAgNEILQAAAACMRmgBAAAAYDRCCwAAAACjEVoAAAAAGI3QAgAAAMBohBYAAAAARiO0AAAAADAaoQUAAACA0QgtAAAAAIxGaAEAAABgNEILAAAAAKMRWgAAAAAYjdACAAAAwGiEFgAAAABGI7QAAAAAMBqhBQAAAIDRCC0AAAAAjEZoAQAAAGA0QgsAAAAAoxFaAAAAABiN0AIAAADAaIQWAAAAAEYjtAAAAAAwGqEFAAAAgNEILQAAAACMRmgBAAAAYDRCCwAAAACjEVoAAAAAGI3QAgAAAMBoVQotCxcuVHBwsGbOnFld9QAAPNzKlSsVExOj8PBwxcXFKT09/ZLL/+Mf/1CfPn0UERGhnj176rnnntP58+ddVC0AwBUqHVrS09O1Zs0aBQcHV2c9AAAPlpKSoqSkJE2YMEEbNmxQSEiIEhISlJWVVebymzZt0uzZszVx4kSlpKRo5syZSklJ0YsvvujiygEAzlSp0JKXl6c//elPmjFjhho1alTdNQEAPFRycrKGDBmiwYMHq23btkpMTFTdunW1fv36MpdPS0tTp06dNHDgQLVo0ULR0dEaMGDAZa/OAABqljqVWWnatGnq2bOnoqKi9Oqrr1Zqx15elVrNrUyr2bR6Kqqk7ppav0kYy+rhKeNoev8KCgqUkZGhsWPH2tq8vb0VFRWltLS0MteJjIzUv/71L6WnpysiIkKHDh3Stm3bdPfddzu8fxPHx1POzfLQf/t/TVfddda0/lc3T+l/RfvncGh555139O2332rdunWOrmonIKBhldb3dE2a1Hd3CVXGOVB9GMvqwTi6V05OjoqKihQQEGDXHhAQoP3795e5zsCBA5WTk6Nhw4bJsiwVFhZq6NChevjhhx3ev8nH3+TaXIH+m99/Z/5eUhP670ye3v8SDoWWY8eOaebMmVqyZImuvPLKKu04K+uMLKtKm3A5Ly9zTpycnDwVFRW7u4xKKRnHmngOmIaxrB6eMo4mvYZVl+3bt2vBggX661//qoiICB08eFAzZ87U/PnzNWHCBIe2ZeLx95Rzszz0//L99/HxNuKNTGf8XsLx94z+V3Rucii0ZGRkKCsrS7Gxsba2oqIi7dixQytXrtQ333wjHx+fCm3LslSrD4Ar1PTx4xyoPoxl9WAc3atJkyby8fEp9dB9VlaWAgMDy1xnzpw5uuuuuxQXFydJCg4O1tmzZ/Xss89q3Lhx8vau+KObJh9/k2tzBfpfM/rvrBprSv+dxdP7X8Kh0HLzzTdr06ZNdm1PPfWUbrjhBo0ZM6bCgQUAgN/y9fVV+/btlZqaqt69e0uSiouLlZqaqvj4+DLXOXfuXKlgUjIXWczyAFBrOBRaGjRooKCgILu2evXqqXHjxqXaAQBw1OjRozV16lSFhYUpIiJCS5cuVX5+vu0K/5QpU9SsWTNNnjxZktSrVy8lJyerXbt2ttvD5syZo169evFGGgDUIpX69DAAAJyhX79+ys7O1ty5c5WZmanQ0FAtWrTIdnvYsWPH7K6sjBs3Tl5eXnrppZd0/Phx+fv7q1evXnrsscfc1QUAgBNUObQsX768OuoAAECSFB8fX+7tYL+dc+rUqaOJEydq4sSJrigNAOAmlfrjkgAAAADgKoQWAAAAAEYjtAAAAAAwGqEFAAAAgNEILQAAAACMRmgBAAAAYDRCCwAAAACjEVoAAAAAGI3QAgAAAMBohBYAAAAARiO0AAAAADAaoQUAAACA0QgtAAAAAIxGaAEAAABgNEILAAAAAKMRWgAAAAAYjdACAAAAwGiEFgAAAABGI7QAAAAAMBqhBQAAAIDRCC0AAAAAjEZoAQAAAGA0QgsAAAAAoxFaAAAAABiN0AIAAADAaIQWAAAAAEYjtAAAAAAwGqEFAAAAgNEILQAAAACMRmgBAAAAYDRCCwAAAACjEVoAAAAAGI3QAgAAAMBohBY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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",
|
||
"\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": "2024-03-19T07:46:58.704422Z",
|
||
"start_time": "2024-03-19T07:46:57.715817Z"
|
||
}
|
||
},
|
||
"id": "dd49203934ca9cf6",
|
||
"execution_count": 112
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": "<IPython.core.display.Image object>"
|
||
},
|
||
"execution_count": 113,
|
||
"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": "2024-03-19T07:46:58.834099Z",
|
||
"start_time": "2024-03-19T07:46:58.707483Z"
|
||
}
|
||
},
|
||
"id": "81f2d793ada5c410",
|
||
"execution_count": 113
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [
|
||
"# Save the model\n",
|
||
"model.save('CNN.keras')"
|
||
],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-19T07:46:58.905473Z",
|
||
"start_time": "2024-03-19T07:46:58.835341Z"
|
||
}
|
||
},
|
||
"id": "6b7329b28452b82a",
|
||
"execution_count": 114
|
||
},
|
||
{
|
||
"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 [==============================] - 4s 3ms/step - loss: 1.1722 - accuracy: 0.5191 - val_loss: 0.8536 - val_accuracy: 0.5964\n",
|
||
"Epoch 2/20\n",
|
||
"1050/1050 [==============================] - 3s 2ms/step - loss: 1.0232 - accuracy: 0.5542 - val_loss: 0.7996 - val_accuracy: 0.6723\n",
|
||
"Epoch 3/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.9261 - accuracy: 0.5910 - val_loss: 0.7433 - val_accuracy: 0.7343\n",
|
||
"Epoch 4/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.8425 - accuracy: 0.6354 - val_loss: 0.6909 - val_accuracy: 0.7683\n",
|
||
"Epoch 5/20\n",
|
||
"1050/1050 [==============================] - 3s 2ms/step - loss: 0.7747 - accuracy: 0.6860 - val_loss: 0.6489 - val_accuracy: 0.7910\n",
|
||
"Epoch 6/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.7126 - accuracy: 0.7308 - val_loss: 0.6149 - val_accuracy: 0.8049\n",
|
||
"Epoch 7/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6693 - accuracy: 0.7569 - val_loss: 0.5886 - val_accuracy: 0.8145\n",
|
||
"Epoch 8/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6431 - accuracy: 0.7805 - val_loss: 0.5714 - val_accuracy: 0.8160\n",
|
||
"Epoch 9/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.6177 - accuracy: 0.7946 - val_loss: 0.5537 - val_accuracy: 0.8250\n",
|
||
"Epoch 10/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5935 - accuracy: 0.8061 - val_loss: 0.5416 - val_accuracy: 0.8262\n",
|
||
"Epoch 11/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5787 - accuracy: 0.8136 - val_loss: 0.5295 - val_accuracy: 0.8301\n",
|
||
"Epoch 12/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5621 - accuracy: 0.8192 - val_loss: 0.5205 - val_accuracy: 0.8317\n",
|
||
"Epoch 13/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5490 - accuracy: 0.8253 - val_loss: 0.5116 - val_accuracy: 0.8339\n",
|
||
"Epoch 14/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5305 - accuracy: 0.8316 - val_loss: 0.5017 - val_accuracy: 0.8355\n",
|
||
"Epoch 15/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5187 - accuracy: 0.8344 - val_loss: 0.4928 - val_accuracy: 0.8370\n",
|
||
"Epoch 16/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.5115 - accuracy: 0.8362 - val_loss: 0.4860 - val_accuracy: 0.8377\n",
|
||
"Epoch 17/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4997 - accuracy: 0.8411 - val_loss: 0.4813 - val_accuracy: 0.8363\n",
|
||
"Epoch 18/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4881 - accuracy: 0.8428 - val_loss: 0.4746 - val_accuracy: 0.8398\n",
|
||
"Epoch 19/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4827 - accuracy: 0.8427 - val_loss: 0.4726 - val_accuracy: 0.8371\n",
|
||
"Epoch 20/20\n",
|
||
"1050/1050 [==============================] - 2s 2ms/step - loss: 0.4750 - accuracy: 0.8453 - val_loss: 0.4660 - val_accuracy: 0.8393\n",
|
||
"263/263 [==============================] - 0s 1ms/step\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 1200x600 with 1 Axes>",
|
||
"image/png": 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"
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Test loss: 0.4660448729991913\n",
|
||
"Test accuracy: 0.8392857313156128\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": "2024-03-19T07:47:53.189659Z",
|
||
"start_time": "2024-03-19T07:46:58.907035Z"
|
||
}
|
||
},
|
||
"id": "c8745832a585d5ec",
|
||
"execution_count": 115
|
||
},
|
||
{
|
||
"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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lpKSoX79+F9zfs88+q6ioKL333ntav369OnXqpBdeeEE33XRTpX+Re9y4cXr66ac1Z84c/fbbb+rbt6+mTJmiO++8U//5z3/08ccfy7IsXX755Zo4cWKZq80BgKcxZ3lnzpKkOXPmaO7cuZo9e7aCg4N1991364knnrjgY4YMGaKTJ09q3bp1ev/993XVVVdp0aJFmj17tst6nuy7imwLNUuQVZFvJAMw3r59+3Tbbbfpr3/9q2699VZ/lwMAAOA2vvMDoIzyfsfhtddek81mc7mwAgAAQHXCx96Acxw5csTltwXOVatWLZffG6iJlixZot27d+uPf/yj7Ha7Pv30U3366acaOHCg83KnAAD/Y84C3MPH3oBzdO/eXT///PN577/mmmu0fPlyH1bke//5z3/04osv6vvvv9eJEyd06aWX6k9/+pOGDBlS5sf8AAD+w5wFuIfwA5xj27ZtOnXq1HnvDwsLU0JCgg8rAgCgfMxZgHsIPwAAAACMwAUPAAAAABiB8AMAAADACIQfAAAAAEao1pdtyssrVKB8YykoSIqMbBBQNQUC+qV89Ev56JeyAq1PSuvB+QXKsbqYQHtueQJtqh5oU/VQndrkztxUrcOPZSngDkYg1hQI6Jfy0S/lo1/Kok+qj+p2rKpbvRVBm6oH2lQ91LQ28bE3AAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEdwKPytXrtQtt9yi5ORkJScna+DAgdq4caPz/lOnTmny5Mnq2LGjkpKSNGzYMOXm5rpsIysrS4MHD1a7du2UmpqqZ599VmfOnPFMawAAqKRff/1Vo0ePVseOHZWYmKhbbrlFX3/9tb/LAgB4ULA7Kzdp0kSjR49WixYtZFmW3nnnHT366KNau3atrrzySk2fPl0bN27UnDlz1KBBA02dOlVDhw7V6tWrJUklJSV66KGHFBUVpdWrVys7O1tjx45VrVq1NHLkSK80EACAizl27JjuvPNOdezYUYsXL1ajRo20f/9+hYeH+7s0AIAHuRV+unfv7nL78ccf16pVq7Rjxw41adJEb7/9tmbNmqXU1FRJ0vTp09WrVy/t2LFD7du31+eff67MzEwtW7ZMUVFRat26tUaMGKFZs2Zp6NChCgkJ8VzLAACooMWLF6tJkyaaMWOGc1nz5s39WBEAwBsq/Z2fkpISvffeezpx4oSSkpK0e/duFRcXq1OnTs51YmJi1LRpU+3YsUOStGPHDsXFxSkqKsq5TlpamoqKipSZmVn5VgAAUAX/+7//q4SEBA0fPlypqam67bbbtGbNGn+XBQDwMLfe+ZGkjIwM3XHHHTp16pTq1aunBQsWKDY2Vvv27VOtWrUUFhbmsn5kZKRycnIkSbm5uS7BR5Lzduk67ggKcvshXlNaSyDVdCE2W5CCfFBs6S6Cg22yrP8utyxLDodV/oMMUN2eL75Cv5QVaH0SKHV42sGDB7Vq1Sr95S9/0ZAhQ/T1119r2rRpqlWrlvr27evWtqpLHwXac8sTaFP1cL42+epvk/Opyt8mJh2nQOROjW6Hn5YtW+qdd95RYWGhPvroI40dO1YrVqxwdzMeERnZwC/7vZBArKk8JQ5Ldpvvns0NG9b36/4DVXV5vvga/VIWfeJdlmUpISHB+f3Tq666St99951Wr17tdvipbsequtVbEbSpeji3Tf7+28AT+zfhOFV3boefkJAQtWjRQpKUkJCgr7/+Wq+//rpuvvlmFRcXq6CgwOXdn7y8PEVHR0s6+y7Prl27XLZXejW40nXckZdX6PJugj8FBZ19cgRSTedjt9vUqFF9jVi9XZnZRT7ff2zjUM29I0lHjx5XSYnD5/sPBNXp+eJL9EtZgdYnpfXUNNHR0YqJiXFZ9oc//EEfffSR29sKlGN1MYH23PIE2lQ9lNem6v63iSnHKVC5Mze5HX7O5XA4dPr0aSUkJKhWrVravHmzevbsKUn64YcflJWVpfbt20uS2rdvr4ULFyovL0+RkZGSpE2bNik0NFSxsbFu79uyFHAHIxBrOp/M7CLtySrwaw3Vpa+8pTo9X3yJfimLPvGu5ORk/fjjjy7LfvrpJ1122WVub6u6HavqVm9F0Kbqobw2Vfe/TUw5TtWZWxc8mD17trZu3apDhw4pIyNDs2fP1pYtW3TLLbeoQYMG6t+/v2bOnKkvvvhCu3fv1vjx45WUlOQMP2lpaYqNjdUTTzyhb775Rp999pnmzJmj9PR0rvQGAPCb++67Tzt37tTChQu1f/9+rVu3TmvWrNFdd93l79IAAB7k1js/eXl5Gjt2rLKzs9WgQQPFx8dr6dKl6ty5syRp/PjxstlsGj58uE6fPq20tDRNnDjR+Xi73a6FCxdq0qRJGjhwoOrWrau+fftq+PDhnm0VAABuSExM1Isvvqjnn39eCxYsULNmzTR+/Hjdeuut/i4NAOBBboWf6dOnX/D+2rVra+LEiS6B51yXXXaZFi9e7M5uAQDwum7duqlbt27+LgMA4EWV/p0fAAAAAKhOCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMEOzvAmAuu91/2dvhsORwWH7bPwAAAHyP8AOfiw6trRKHpbCwun6r4UyJQ8fyTxCAAAAADEL4gc+F1Q2W3RakEau3KzO7yOf7j20cqrl3JMlmCyL8AAAAGITwA7/JzC7SnqwCf5cBAAAAQ3DBAwAAAABGIPwAAAAAMALhBwAAAIAR+M4PYCCbLUg2W5Df9s+lxgEAgD8QfgDD2GxBCm9YT8F+/J0lLjUOAAD8gfADGMZmC1Kw3calxgEAgHEIP4ChuNQ4AAAwDRc8AAAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIwf4uAPAXu91/2d+yLL/tO1BcqP+9fWwcDksOB8cAAADTEH5gnOjQ2ipxWAoLq+u3Gs6UOPy2b3+rSP83alTfqzWcKXHoWP4JAhAAAIYh/MA4YXWDZbcFacTq7crMLvL5/mMbh2ruHUk+32+gCJT+t9mCCD8AABiG8ANjZWYXaU9Wgb/LMBb9DwAAfI0LHgAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABghGB/FwCYzG73/esP/tgnAABAIHAr/CxatEgff/yxfvjhB9WpU0dJSUkaPXq0/vCHPzjXueeee7RlyxaXxw0cOFBTpkxx3s7KytKkSZP05Zdfql69errttts0atQoBQeTxVDzRYfWVonDkt0WpEaN6vu7HACS5s+frxdffNFlWcuWLfXhhx/6qSIAgDe4lTa2bNmi9PR0tW3bViUlJXr++ec1aNAgvffee6pXr55zvdtvv13Dhw933q5bt67z/yUlJXrooYcUFRWl1atXKzs7W2PHjlWtWrU0cuRIDzQJCGxhdYNltwVpxOrtyswu8vn+r4uP1pierXy+XyDQXXnllVq2bJnztt1u92M1AABvcCv8LF261OX2zJkzlZqaqj179ujqq692Lq9Tp46io6PL3cbnn3+uzMxMLVu2TFFRUWrdurVGjBihWbNmaejQoQoJCalEM4DqJzO7SHuyCny+35ho3m0CymO32887dwEAaoYqffi/sLBQkhQeHu6yfN26derYsaP69Omj2bNn6+TJk877duzYobi4OEVFRTmXpaWlqaioSJmZmVUpBwCAStu/f7/S0tJ0/fXXa9SoUcrKyvJ3SQAAD6v0l2wcDoemT5+u5ORkxcXFOZf36dNHTZs2VePGjZWRkaFZs2bpxx9/dH6WOjc31yX4SHLezsnJcauGoKDKVu95pbUEUk0ALqw6nK+BNrYESh2elpiYqBkzZqhly5bKycnRggULlJ6ernXr1ik0NNStbVWXPirvuWWzBSnIjw2wLEsOh1Xpxwfa+eKu8vq/9GZwsE1W5bumQqra/xUV6MepMnUFepsqozq1yZ0aKx1+Jk+erO+++04rV650WT5w4EDn/+Pj4xUdHa37779fBw4c0OWXX17Z3ZUrMrKBR7fnCYFYE4CyqtvFJhhbvKtr167O/7dq1Urt2rVTt27d9MEHH2jAgAFubau6Havf11t6MRZ/8dT+q9sxKHWh9jds6P0xy9fHPxCPU1XnhkBsU1XVtDZVKvxMmTJFn3zyiVasWKEmTZpccN127dpJOvtxgssvv1xRUVHatWuXyzq5ubmS5PZnrfPyCr3+KkhFBQWdfXIEUk3nY7fbqt0ffoCnHT16XCUlDn+XcVGBNraU1lPThYWF6YorrtCBAwfcfmygHKuLOfe5VTo3+OtiLLGNQzX3jqQqnZuBdr64oyb0f0WVd5wC5W+Tyra/Oj/3zqc6tcmducmt8GNZlqZOnar169dr+fLlat68+UUfs2/fPkn/DTbt27fXwoULlZeXp8jISEnSpk2bFBoaqtjYWHfKkWUp4A5GINYEoHzV6VxlbPGt48eP6+DBg5W6AEJ1O1bn1uuvi7H8XlX7r7odg9+rCf3vzn4C8ThVpaZAbVNV1LQ2uRV+Jk+erHfffVcvvfSS6tev7/yOToMGDVSnTh0dOHBA69atU9euXdWwYUNlZGRoxowZuvrqq9Wq1dlL66alpSk2NlZPPPGExowZo5ycHM2ZM0fp6elc6Q0A4BfPPvusunXrpqZNmyo7O1vz58+XzWZTnz59/F0aAMCD3Ao/q1atknT2h0x/b8aMGerXr59q1aqlzZs36/XXX9eJEyd06aWXqkePHnrkkUec69rtdi1cuFCTJk3SwIEDVbduXfXt29fld4EAAPClw4cPa+TIkcrPz1dERIQ6dOigNWvWKCIiwt+lAQA8yK3wk5GRccH7L730Uq1YseKi27nsssu0ePFid3YNAIDXvPDCC/4uAQDgA1X6nR8AAAAAqC4IPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACM4Fb4WbRokfr376+kpCSlpqbqkUce0Q8//OCyzqlTpzR58mR17NhRSUlJGjZsmHJzc13WycrK0uDBg9WuXTulpqbq2Wef1ZkzZ6reGgAAPOCVV15RfHy8nnnmGX+XAgDwILfCz5YtW5Senq41a9Zo2bJlOnPmjAYNGqQTJ04415k+fbr+7//+T3PmzNHy5cuVnZ2toUOHOu8vKSnRQw89pOLiYq1evVozZ87U2rVrNW/ePM+1CgCAStq1a5dWr16t+Ph4f5cCAPAwt8LP0qVL1a9fP1155ZVq1aqVZs6cqaysLO3Zs0eSVFhYqLffflvjxo1TamqqEhISNH36dG3fvl07duyQJH3++efKzMzUX//6V7Vu3Vpdu3bViBEj9MYbb+j06dMebyAAABV1/PhxjRkzRtOmTVN4eLi/ywEAeFiVvvNTWFgoSc4JYvfu3SouLlanTp2c68TExKhp06bO8LNjxw7FxcUpKirKuU5aWpqKioqUmZlZlXIAAKiSKVOmqGvXri7zGACg5giu7AMdDoemT5+u5ORkxcXFSZJyc3NVq1YthYWFuawbGRmpnJwc5zq/Dz6SnLdL16mooKDKVu95pbUEUk0ALqw6nK+BNrYESh3e8N5772nv3r166623qrSd6tJHgfbc+r3K1lTVNtlsQQryU4fY7YFzDSpvd0EgP/ekytUV6G2qjOrUJndqrHT4mTx5sr777jutXLmyspuossjIBn7b9/kEYk0AymrUqL6/S3ALY4t3/fLLL3rmmWf0t7/9TbVr167StqrbsQq0ej1xbla2TSUOS3ZbNfhLz4t8OTYG2nNPqnr7A7FNVVXT2lSp8DNlyhR98sknWrFihZo0aeJcHhUVpeLiYhUUFLi8+5OXl6fo6GjnOrt27XLZXunV4ErXqai8vEJZVmVa4HlBQWefHIFU0/nY7bZq94cf4GlHjx5XSYnD32VcVKCNLaX11DR79uxRXl6e+vXr51xWUlKirVu36o033tDXX38tu91eoW0FyrG6mHOfW4EyN1Tl3KzK+VLa/hGrtyszu6hS+6+K6+KjNaZnK5/v91y+GBvLO07V/fkXaGO1J1SnNrkzN7kVfizL0tSpU7V+/XotX75czZs3d7k/ISFBtWrV0ubNm9WzZ09J0g8//KCsrCy1b99ektS+fXstXLhQeXl5ioyMlCRt2rRJoaGhio2NdaccWZYC7mAEYk0AyledzlXGFu/64x//qHXr1rkse/LJJ/WHP/xBDz74YIWDj1T9jlUg1lvVeqrSpszsIu3JKqhaAZUQE+3/P/xL+er5EIjPPalqNQVqm6qiprXJrfAzefJkvfvuu3rppZdUv35953d0GjRooDp16qhBgwbq37+/Zs6cqfDwcIWGhmratGlKSkpyhp+0tDTFxsbqiSee0JgxY5STk6M5c+YoPT1dISEhHm8gAAAXExoa6vz+aql69eqpYcOGZZYDAKovt8LPqlWrJEn33HOPy/IZM2Y4Pyowfvx42Ww2DR8+XKdPn1ZaWpomTpzoXNdut2vhwoWaNGmSBg4cqLp166pv374aPnx4VdsCAAAAAOflVvjJyMi46Dq1a9fWxIkTXQLPuS677DItXrzYnV0DAOBTy5cv93cJAAAPC5zrKgIAAACAFxF+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYIRgfxcAAP5gt/vvtR+Hw5LDYflt/wAAmIrwA8Ao0aG1VeKwFBZW1281nClx6Fj+CQIQAAA+RvgBYJSwusGy24I0YvV2ZWYX+Xz/sY1DNfeOJNlsQYQfAAB8jPADwEiZ2UXak1Xg7zIAAIAPccEDAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACO4HX62bt2qIUOGKC0tTfHx8dqwYYPL/ePGjVN8fLzLv0GDBrmsk5+fr1GjRik5OVkpKSkaP368jh8/XrWWAAAAAMAFBLv7gBMnTig+Pl79+/fX0KFDy12nS5cumjFjhvN2SEiIy/2jR49WTk6Oli1bpuLiYo0fP15PP/20Zs+e7W45AABU2cqVK7Vq1Sr9/PPPkqQrr7xSjzzyiLp27ernygAAnuR2+OnatetFJ4OQkBBFR0eXe9/333+vzz77TG+99Zbatm0rSZowYYIGDx6sJ554Qpdccom7JQEAUCVNmjTR6NGj1aJFC1mWpXfeeUePPvqo1q5dqyuvvNLf5QEAPMTt8FMRW7ZsUWpqqsLCwvTHP/5Rjz32mBo1aiRJ2r59u8LCwpzBR5I6deokm82mXbt26cYbb/RGSQHHZguSzRbkl33b7XzVCwB+r3v37i63H3/8ca1atUo7duwg/ABADeLx8NOlSxfdeOONatasmQ4ePKjnn39eDz74oN58803Z7Xbl5uYqIiLCtYjgYIWHhysnJ8etfQX5JzuUq7SWitRkswUpLLyeggkhgNEqMl64M7b4QqDU4U0lJSX68MMPdeLECSUlJbn9+OrSR4H23CpVlRfoStsSHGyTZfluvzWJL/qhvOMUSP1fmXMiUM+nqqhObXKnRo+Hn969ezv/X3rBgxtuuMH5bpAnRUY28Oj2PMGdmkas3q7M7CIvVlO+6+KjNaZnK5/vF8B/NWpU3631A3G8q2kyMjJ0xx136NSpU6pXr54WLFig2NhYt7dT3Y5VoNQbHVpbJQ5LYWF1q7ythg3dO7/g2f6vqEA8Tu6OzecKlPPJk2pam7zysbffa968uRo1aqT9+/crNTVVUVFROnLkiMs6Z86c0bFjx877PaHzycsrdPuVHW8JCjr75KhITXa7TY0a1VdmdpH2ZBX4psDfiYkOvMEGMM3Ro8dVUuK46HrujC2+UFpPTdSyZUu98847Kiws1EcffaSxY8dqxYoVbgegQDlWF3Puc6t0bvKXsLrBstuCeGHQT+j/syo6Np8r0MZqT6hObXJnbvJ6+Dl8+LDy8/OdwSYpKUkFBQXavXu3EhISJElffPGFHA6HEhMT3dq2ZSngDkYg1gQgMLkzVjC2eF9ISIhatGghSUpISNDXX3+t119/XVOmTHFrO9XtWAVavbww6F/0f9XOh0A7nzyhprXJ7fBz/PhxHThwwHn70KFD2rdvn8LDwxUeHq4XX3xRPXv2VFRUlA4ePKi//vWvatGihbp06SJJiomJUZcuXfTUU09p8uTJKi4u1tSpU9W7d2+u9AYACBgOh0OnT5/2dxkAAA9yO/zs3r1b9957r/N26e/59O3bV5MmTdK3337r/NhA48aN1blzZ40YMcLlt35mzZqlqVOn6r777pPNZlOPHj00YcIEDzQHAAD3zZ49W9dee60uvfRSHT9+XO+++662bNmipUuX+rs0AIAHuR1+OnbsqIyMjPPeX5GJomHDhvygKQAgYOTl5Wns2LHKzs5WgwYNFB8fr6VLl6pz587+Lg0A4EFe/84PAACBbvr06f4uAQDgA4FzUXUAAAAA8CLCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjuB1+tm7dqiFDhigtLU3x8fHasGGDy/2WZWnu3LlKS0tTYmKi7r//fv30008u6+Tn52vUqFFKTk5WSkqKxo8fr+PHj1epIQAAVNaiRYvUv39/JSUlKTU1VY888oh++OEHf5cFAPAwt8PPiRMnFB8fr4kTJ5Z7/+LFi7V8+XJNmjRJa9asUd26dTVo0CCdOnXKuc7o0aOVmZmpZcuWaeHChfrqq6/09NNPV74VAABUwZYtW5Senq41a9Zo2bJlOnPmjAYNGqQTJ074uzQAgAcFu/uArl27qmvXruXeZ1mWXn/9dT388MO64YYbJEnPPfecOnXqpA0bNqh37976/vvv9dlnn+mtt95S27ZtJUkTJkzQ4MGD9cQTT+iSSy6pQnMAAHDf0qVLXW7PnDlTqamp2rNnj66++mo/VQUA8DS3w8+FHDp0SDk5OerUqZNzWYMGDdSuXTtt375dvXv31vbt2xUWFuYMPpLUqVMn2Ww27dq1SzfeeGOF9xcU5Mnqq6a0lkCqCUBgq8h4EWhjS6DU4W2FhYWSpPDwcLcfW5U+stmCFOSjTi7dTXCwTZYl2e18DRiQKncOe2Ks9uX5Xx7LsuRwWM7bgTb/XIg7NXo0/OTk5EiSIiMjXZZHRkYqNzdXkpSbm6uIiAjXIoKDFR4e7nx8RUVGNqhCtd4RiDUBCDyNGtV3a33GFt9xOByaPn26kpOTFRcX5/bjq3KsShyW7Dbf/qXRsKF7z0WgJnN3bD5XdTv/K7L/mjb/eDT8+FpeXqEs6+Lr+UJQ0NknR0VqstttVT65AFRvR48eV0mJ46LruTO2+EJpPTXZ5MmT9d1332nlypWVenxlj1Xp3DBi9XZlZhdVat9VcV18tMb0bOXz/QKBpKJj87mqOlb7+/yPbRyquXckubQ/0OafC3FnbvJo+ImOjpYk5eXlqXHjxs7leXl5atXq7IAaFRWlI0eOuDzuzJkzOnbsmPPxFWVZCriDEYg1AQhM7owVjC2+MWXKFH3yySdasWKFmjRpUqltVPVYZWYXaU9WQeU3UEkx0bwoB0hVO3+r6/n/e+fWX9PmH49+wLdZs2aKjo7W5s2bncuKioq0c+dOJSUlSZKSkpJUUFCg3bt3O9f54osv5HA4lJiY6MlyAACoEMuyNGXKFK1fv16vvfaamjdv7u+SAABe4PY7P8ePH9eBAwectw8dOqR9+/YpPDxcTZs21b333quXX35ZLVq0ULNmzTR37lw1btzYefW3mJgYdenSRU899ZQmT56s4uJiTZ06Vb179+ZKbwAAv5g8ebLeffddvfTSS6pfv77zO6gNGjRQnTp1/FwdAMBT3A4/u3fv1r333uu8PWPGDElS3759NXPmTD344IM6efKknn76aRUUFKhDhw5asmSJateu7XzMrFmzNHXqVN13332y2Wzq0aOHJkyY4IHmAADgvlWrVkmS7rnnHpflM2bMUL9+/fxREgDAC9wOPx07dlRGRsZ57w8KCtKIESM0YsSI867TsGFDzZ49291dAwDgFRea1wAANQcX9QcAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACN4PPzMnz9f8fHxLv9uuukm5/2nTp3S5MmT1bFjRyUlJWnYsGHKzc31dBkAALhl69atGjJkiNLS0hQfH68NGzb4uyQAgId55Z2fK6+8Up9//rnz38qVK533TZ8+Xf/3f/+nOXPmaPny5crOztbQoUO9UQYAABV24sQJxcfHa+LEif4uBQDgJcHe2Kjdbld0dHSZ5YWFhXr77bc1a9YspaamSjobhnr16qUdO3aoffv23igHAICL6tq1q7p27ervMgAAXuSV8LN//36lpaWpdu3aat++vUaNGqWmTZtq9+7dKi4uVqdOnZzrxsTEqGnTppUKP0FBHi68CkprCaSaAAS2iowXgTa2BEodgYw+Aqovu71yH4oqPe+Dg22yLN/t19N+X0dV2+Quy7LkcFRuR+6Mux4PP4mJiZoxY4ZatmypnJwcLViwQOnp6Vq3bp1yc3NVq1YthYWFuTwmMjJSOTk5bu8rMrKBp8r2mECsCUDgadSovlvrM7ZUHxwroPqJDq2tEoelsLC6VdpOw4buje2B4kLt91WbShyW7Dbvv3rk8fDz+48MtGrVSu3atVO3bt30wQcfqE6dOh7dV15eoU+SaEUEBZ2d8CpSk91uc/sPHwA1y9Gjx1VS4rjoeu6MLb5QWg/Or7LHirkB8J+wusGy24I0YvV2ZWYX+Xz/18VHa0zPVj7fbyl/tz+2cajm3pFU4bnxXO7MTV752NvvhYWF6YorrtCBAwfUqVMnFRcXq6CgwOXdn7y8vHK/I3QxlqWA+GPg9wKxJgCByZ2xgrGl+uBYAdVXZnaR9mQV+Hy/MdGB8cKHv9r/e94eP73+AcPjx4/r4MGDio6OVkJCgmrVqqXNmzc77//hhx+UlZXFxQ4AAAAAeJXH3/l59tln1a1bNzVt2lTZ2dmaP3++bDab+vTpowYNGqh///6aOXOmwsPDFRoaqmnTpikpKYnwAwDwq+PHj+vAgQPO24cOHdK+ffsUHh6upk2b+rEyAICneDz8HD58WCNHjlR+fr4iIiLUoUMHrVmzRhEREZKk8ePHy2azafjw4Tp9+rTS0tL4TQUAgN/t3r1b9957r/P2jBkzJEl9+/bVzJkz/VUWAMCDPB5+XnjhhQveX7t2bU2cOJHAAwAIKB07dlRGRoa/ywAAeFFgXFQcAAAAALyM8AMAAADACIQfAAAAAEbw+u/8AADKstvde+3J3fUvxOGw5HDwQzQAAPMQfgDAh6JDa6vEYSksrK5bj2vUyHM/gHemxKFj+ScIQAAA4xB+AMCHwuoGy24L0ojV25WZXeTz/cc2DtXcO5JkswURfgAAxiH8AIAfZGYXaU9Wgb/LAADAKFzwAAAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABjB2Ku92WxBstmCPL7divwQoSd/rBAAAABAxRgZfmy2IIU3rKdgL4QQT/4QIQAAAADPMTb8BNttfvuRweviozWmZyuf7xcAAAAwmZHhp5S/fmQwJpp3hwAAAABf48snAAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYATCDwAAAAAjEH4AAAAAGIHwAwAAAMAIhB8AAAAARiD8AAAAADAC4QcAAACAEQg/AAAAAIxA+AEAAABgBMIPAAAAACMQfgAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEv4afN954Q927d1fbtm01YMAA7dq1y5/lAAAMx7wEADWb38LP+++/rxkzZujRRx/V2rVr1apVKw0aNEh5eXn+KgkAYDDmJQCo+fwWfpYtW6bbb79d/fv3V2xsrCZPnqw6dero7bff9ldJAACDMS8BQM0X7I+dnj59Wnv27NFDDz3kXGaz2dSpUydt3769wtux2STLqnwdbZqGqW6IvfIbqKSY6FD2z/7ZP/v3y/7/EFXf+X9bJV7+CgryYDEBxFPz0tnHMTexf/bP/tm/O3w5NwVZVlWG6Mr59ddfde2112r16tVKSkpyLn/uuee0detW/f3vf/d1SQAAgzEvAYAZuNobAAAAACP4Jfw0atRIdru9zJdI8/LyFBUV5Y+SAAAGY14CADP4JfyEhISoTZs22rx5s3OZw+HQ5s2bXT5uAACALzAvAYAZ/HLBA0n6y1/+orFjxyohIUGJiYl67bXXdPLkSfXr189fJQEADMa8BAA1n9/CT69evXTkyBHNmzdPOTk5at26tZYsWcLHCwAAfsG8BAA1n1+u9gYAAAAAvsbV3gAAAAAYgfADAAAAwAiEHwAAAABGIPwAAAAAMALhpwry8/M1atQoJScnKyUlRePHj9fx48cvuP7UqVPVs2dPJSYm6rrrrtO0adNUWFjow6q9z91+kaQ333xT99xzj5KTkxUfH6+CggIfVes9b7zxhrp37662bdtqwIAB2rVr1wXX/+CDD3TTTTepbdu2uuWWW7Rx40YfVepb7vTLd999p2HDhql79+6Kj4/Xq6++6rtCfcidPlmzZo3uuusuXX311br66qt1//33X/S5BTN4esyxLEtz585VWlqaEhMTdf/99+unn37yYgvK8nSbxo0bp/j4eJd/gwYN8mYTyvDGGOhuP3map9s0f/78Msfppptu8mILyvL0uBwI55Pk+XYFwjnlNguVNmjQIOvWW2+1duzYYW3dutW68cYbrZEjR553/YyMDGvo0KHWv//9b2v//v3Wpk2brB49eljDhg3zYdXe526/WJZlLVu2zFq0aJG1aNEiKy4uzjp27JiPqvWO9957z2rTpo311ltvWd999501YcIEKyUlxcrNzS13/W3btlmtW7e2Fi9ebGVmZlovvPCC1aZNGysjI8PHlXuXu/2yc+dOa+bMmda7775rde7c2Vq2bJlvC/YBd/tk5MiR1ooVK6y9e/damZmZ1rhx46wOHTpYhw8f9nHlCCTeGHMWLVpkdejQwVq/fr21b98+a8iQIVb37t2t3377rdq2aezYsdagQYOs7Oxs57/8/HyftMeyvDMGurtNT/NGm+bNm2f17t3b5Tjl5eV5uSX/5Y1x2d/nk2V5p13+Pqcqg/BTSZmZmVZcXJy1a9cu57KNGzda8fHxbv0R8v7771tt2rSxiouLvVGmz1W1X7744osaEX7+/Oc/W5MnT3beLikpsdLS0qxFixaVu/6IESOswYMHuywbMGCA9dRTT3m1Tl9zt19+r1u3bjUy/FSlTyzLss6cOWMlJSVZa9eu9VKFqA48PeY4HA6rc+fO1pIlS5z3FxQUWAkJCda7777rhRaU5Y1xdOzYsdbDDz/snYIrwBtjYFXHkKryRpvmzZtn3XrrrZ4s0y2eHpcD4XyyLO/MN/4+pyqDj71V0vbt2xUWFqa2bds6l3Xq1Ek2m82tt5uLiooUGhqq4GC//d6sR3mqX6qz06dPa8+ePerUqZNzmc1mU6dOnbR9+/ZyH7Njxw6lpqa6LEtLS9OOHTu8WapPVaZfajpP9MnJkyd15swZhYeHe6tMBDhvjDmHDh1STk6OyzYbNGigdu3a+eR89eY4umXLFqWmpqpnz56aOHGijh496vH6y+ONMdDf46o3979//36lpaXp+uuv16hRo5SVlVXVcivEG+Oyv88nybvzjb/Oqcoi/FRSbm6uIiIiXJYFBwcrPDxcOTk5FdrGkSNH9NJLL2ngwIHeKNEvPNEv1d3Ro0dVUlKiyMhIl+WRkZHKzc0t9zG5ubllfkX+QutXR5Xpl5rOE30ya9YsNW7c2GVCg1m8MeaUjtf+Ol+9NY526dJFzz77rF599VWNGTNGW7du1YMPPqiSkhLPN+Ic3hgD/T2uemv/iYmJmjFjhpYsWaJJkybp559/Vnp6uoqKiqpa8kV5Y1z29/kkeW++8ec5VVk14+0GD5o1a5YWL158wXXef//9Ku+nqKhIDz30kGJiYjR06NAqb8/bfNUvACrulVde0fvvv6/XX39dtWvX9nc5QMDr3bu38/+lX86+4YYbnK9cIzB07drV+f9WrVqpXbt26tatmz744AMNGDDAj5VdXE0dl8/Xrup4ThF+zvE///M/6tu37wXXad68uaKionTkyBGX5WfOnNGxY8cUHR19wccXFRXpgQceUP369bVgwQLVqlWrynV7my/6paZo1KiR7Ha78vLyXJbn5eWVeVWyVFRUVJlXXi60fnVUmX6p6arSJ0uXLtUrr7yiZcuWqVWrVt4sEwHOG2NO6Xidl5enxo0bu6zji+ebr8bR5s2bq1GjRtq/f7/X/1Dzxhjo73HVV/sPCwvTFVdcoQMHDnhsm+fjjXHZ3+eT5Lv5xpfnVGXxsbdzREREKCYm5oL/QkJClJSUpIKCAu3evdv52C+++EIOh0OJiYnn3X5RUZEGDRqkWrVq6eWXX642rwp4u19qkpCQELVp00abN292LnM4HNq8ebOSkpLKfUz79u31xRdfuCzbtGmT2rdv781Sfaoy/VLTVbZPFi9erJdeeklLlixx+X4dzOSNMadZs2aKjo522WZRUZF27tzpk/PVV+Po4cOHlZ+f75MX57wxBvp7XPXV/o8fP66DBw8G9HG60Ljs7/NJ8t1848tzqtL8fcWF6mzQoEHWbbfdZu3cudP66quvrB49erhc0vnw4cNWz549rZ07d1qWZVmFhYXWgAEDrD59+lj79+93uSzgmTNn/NUMj3O3XyzLsrKzs629e/daa9asseLi4qytW7dae/futY4ePeqHFlTde++9ZyUkJFj/+Mc/rMzMTOupp56yUlJSrJycHMuyLGvMmDHWrFmznOtv27bNuuqqq6ylS5damZmZ1rx582rspa7d6ZdTp05Ze/futfbu3Wt17tzZmjlzprV3717rp59+8lcTPM7dPlm0aJHVpk0b68MPP3QZQ4qKivzVBAQAb4w5ixYtslJSUqwNGzZY33zzjfXwww/7/FLXnmxTUVGRNXPmTGv79u3WwYMHrU2bNll9+/a1evToYZ06dSog21SRMfBi26yObZo5c6b15ZdfWgcPHrS2bdtm3X///VbHjh19drlrb4zL/j6fvNGuQDinKoOPvVXBrFmzNHXqVN13332y2Wzq0aOHJkyY4Ly/uLhYP/74o06ePClJ2rNnj3bu3ClJuvHGG1229e9//1vNmjXzXfFe5G6/SNLq1av14osvOm+np6dLkmbMmKF+/fr5rngP6dWrl44cOaJ58+YpJydHrVu31pIlS5xvLf/yyy+y2f77xmtycrJmzZqlOXPm6Pnnn9cVV1yhBQsWKC4uzl9N8Ap3+yU7O1u33Xab8/bf/vY3/e1vf9M111yj5cuX+7p8r3C3T1avXq3i4mINHz7cZTtDhw7VsGHDfFo7Aoc3xpwHH3xQJ0+e1NNPP62CggJ16NBBS5Ys8dknFjzdJrvdrm+//VbvvPOOCgsL1bhxY3Xu3FkjRoxQSEhIQLapImPgxbZZHdt0+PBhjRw5Uvn5+YqIiFCHDh20Zs2aMhdUCpQ2VWRc9vf55I12BcI5VRlBlmVZ/i4CAAAAALyN7/wAAAAAMALhBwAAAIARCD8AAAAAjED4AQAAAGAEwg8AAAAAIxB+AAAAABiB8AMAAADACIQfAAAAAEYg/AAAAAAwAuEHAAAAgBEIPwAAAACMQPgBAAAAYIT/DzZS0st1uBGOAAAAAElFTkSuQmCC"
|
||
},
|
||
"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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FaN68Ofbv34/ExMRC+//3NlPnzp3x5MkTnD59utB+73+dd+3aFQkJCThw4EChffLy8tjRT8Wxs7ODg4MDTp48iZMnT8LCwkIpKREIBPDx8cGpU6eK/EP9JcsxNG7cGK1bt8bhw4eVhuq/t2rVKsTExOC7774r9Ev9zJkzSv0zIiIi8ODBA7Rr1w4AVHqfP6WoSfR2794NuVyuVKarqwvgy2+X/ZerqytMTExw4MAByGQytvz48ePIyMj47PHVq1dHv379cPnyZezevbvQ8wqFAv/73//w9u1bleJ6/558fJvw0KFDZX4ODw8P6OvrY/PmzcjPz1d67r/H6urqFvnef+nnoyhyubzQtcRiMSwtLZWG5BcX08fMzMzQrFkzHDp0iL0d+l5ZtQ6Syo1ahEilN3LkSPzwww84fPgwBg4ciDlz5mDQoEHo0aMH+vfvj5o1ayI5ORn379/H27dvcezYMfa4U6dO4YcffkDfvn3h4uKCjIwMhIeHY968eXBycsJXX32FkJAQzJkzBzdu3EDjxo0hl8vx4sULhIaGYuvWrZ9dQsHX1xdBQUHQ1tbG119/XejWyJQpU3Djxg30798f/fr1g729PTIyMvDo0SNcu3YNN2/eLPV7s2zZMgwfPhxjx45F9+7d0bRpU0gkEoSFheHmzZvw9fXFyJEjCx1Xq1YtDBw4EAMHDoREIsGuXbtgYmKC7777jt2npO/zp3To0AFHjx6FgYEB7O3tcf/+fVy9ehUmJiZK+zk7O0MgEOC3335DZmYmtLS00LJlS4jF4lK/N1paWpgwYQIWLFiAYcOGoWvXroiPj8fhw4dLfPt0xowZiIuLw8KFCxEWFgZPT08YGRnhzZs3CA0NxYsXL5RaAEuiTZs2EIlEGDNmDAYMGIDs7GwcPHgQYrEYSUlJZXoOAwMDBAYG4qeffsLXX3+N7t27w8jICE+ePEFeXh6WLVsGAHBxccHJkyexZMkSNGjQAHp6evDy8iqTz8fHsrOz0b59e/j4+MDJyQl6enq4evUq/v77b6WWw+JiKspPP/2EgQMHonfv3vjmm29Qo0YNxMfH4/z58zh69KhK8ZGqhxIhUul17twZtWrVwv/+9z/0798f9vb2OHToENatW4cjR44gPT0dZmZmqF+/PsaNG8cep6+vjz179mDt2rU4ffo0jhw5ArFYjFatWrGdfPl8PtavX48dO3bg6NGjOH36NHR1dVGjRg0MGTKEnbPlU3x9fbF69Wrk5uaia9euhZ43NzfHwYMHsX79epw+fRp79+6FiYkJ7O3tMXXq1C96bywtLXHw4EF2rbGwsDAIBAI4Ojpi6dKl6NWrV5G3GHr16gU+n4+dO3ciJSUFbm5u+Pnnn2FpacnuU9L3+VNmzZoFPp+P48ePIz8/H40bN8b27duVEi4AsLCwwLx587B582bMmjULcrkcu3bt+qJECAD8/PzAMAy2b9+OZcuWwcnJCRs3bsTChQtLNDuxrq4ufvvtNxw+fBjBwcHYsGED8vLy2LXGVqxYofI6eHXr1kVQUBBWr16NZcuWwdzcHAMHDoSZmRlmzpxZ5ufo168fxGIxtmzZgg0bNkAoFKJu3bpK81cNGjQIjx8/xuHDh7Fjxw7Y2NjAy8urTD4fH9PR0cHAgQNx5coVhIWFgWEY1KpVi028PxdTUZycnHDgwAGsWbMGe/fuRX5+PqytrYv8PBLNw2OobZAQ8q9Xr17B29sbP/74Y5EtRZpAoVCgVatW6NSpExYuXMh1OISQckZ9hAghGis/P79QP5Hg4GCkp6ejefPmHEVFCKlIdGuMEKKx7t+/jyVLlqBLly4wMTFBZGQk/vzzTzg4OKBLly5ch0cIqQCUCBFCNJaNjQ2qVauG3bt3IyMjA8bGxvjqq68wdepUTle1J4RUHOojRAghhBCNRX2ECCGEEKKxKBEihBBCiMaiRIgQQgghGosSIUIIIYRoLI0dNZaamokyWoCZlBKPB4jFhkhJyQR12ece1Yf6oLpQH1QX6oPPB8zMDMv8vBqbCDEM6B+1mqC6UC9UH+qD6kJ9UF1wr7zef7o1RgghhBCNRYkQIYQQQjQWJUKEEEII0ViUCBFCCCFEY1EiRAghhBCNRYkQIYQQQjQWJUKEEEII0ViUCBFCCCFEY1EiRAghhBCNRYkQIYQQQjQWp4nQrVu3MGbMGHh4eMDR0RFnzpz57DE3btxA79694erqik6dOuHw4cMVECkhhBBCqiJOE6GcnBw4Ojpizpw5Jdo/Li4Oo0ePRosWLXD06FEMGzYMP/30Ey5dulTOkRJCCCGkKuJ00dX27dujffv2Jd5/3759qFGjBmbMmAEAsLOzw507d7Bjxw60bdu2vMIkhBBCSBVVqVafv3//Plq1aqVU5uHhgcWLF3MUESGEEEI+iWHAy0sET54Hfm4CePL8f8vlEKY8ACPQBo+RA4wCYOQAIwePkUH09hLkhnaAQgpGLsXTNwYQj99a5uFVqkQoOTkZ5ubmSmXm5ubIyspCXl4edHR0SnwuHq/gP8Kd9+8/1YN6oPpQH1QX6oPq4gNeXgp4shzwc99CmHIfwqQbYIQG4CmkgEIKrddnITewBfgiiBKvQaFlAp4sFzxFfukv+vYi3rwzwIj9vXAvyRYJ48vu9bxXqRKhsmRmZsh1CORfYjHVhTqh+lAfVBfqo1LXRX4GIMsraG1RyAEoCv7PyIHcZCA3BUh5BKQ+Lcj4UiKBvBQg7TkgMigok2SW6FL8vKQPjyXpXxz60YeO+O5gTyRn68PQsHxSlkqVCJmbmyM5OVmpLDk5GQYGBiq1BgFAamomFIqyjI6oiscr+OOSkpIJhuE6GkL1oT6oLtSHOtQFLy8FgnfPwZNmQ5D+GBBoAXIJhKkRAF8Ehq8FHiP7N9GRQTv2GHiyHCi0TL48GZFmfdHhjEAXcmNH8DOjITdrCLl+DQgynkJavcO/O8jBU0ggtWgO8ATsfwyPj+Q0BoN/fobs3IIva0tz7S97LcWoVIlQo0aNcPHiRaWyq1evolGjRiqfi2FAf2DUBNWFeqH6UB9UF+qjzOqCYf5NWCQQJd2E7uMN4Ge/BqNlXJDMKGQAI4Mo5R4Y8MBD6S9aFi0y70lN3SDIeQW5gW1BYpPzGtJq7SEza/Dv7TAhGJ4IjMgAjMjg3wC0AF7pB6cb1QAWLKqJyZNPo2tXO6xZ41NGr0YZp4lQdnY2YmNj2e1Xr17h8ePHMDY2hrW1NX799VckJCRg+fLlAIABAwZgz549WL58Ofr27Yvr168jJCQEmzdv5uolEEII0TC8vBQIMqPAk0vYxEWQ9RKC7Fdg+ELwFDLoPt5YkCBAAZ5CCp40C/y8JJWSmy9Jgv5Lrlsd4PEgM29S0NoCfkGCwi9ofeFnvYS0WnswWkaQ69eC3MgejMgACj3rL0pkVI5TroBMpoC29ofUZPBgV1hbG8LT0xYCQfl01OI0EXr48CGGDh3Kbi9ZsgQA0Lt3byxduhRJSUl48+YN+3zNmjWxefNmLFmyBLt27UK1atWwcOFCGjpPCCGk5BgGvPxU8POSwc9LgjD1PnjSzH9v08ggij8DuZH9vy00UuBVCEyM7AGGgTAzusSXEWY8KVRWkuSG4fEBnhA8hQQAINezASMygNzAFjLLluBJ3kEmbgSGrwUwCigMaoHhiwCeEOALwPCEYLTNwGgZlfw94Vh8fCbGjw+Bk5M5lizxYst5PB68vGqX67V5DKOZDa8pKdRHiGs8HmBubojkZOoHoQ6oPtQH1UUpSLPBk+WAp5CAn/MaPFk2hGkPYXB7JgBAoWMJKKT/7vMFo5hKQaFtBvCEYPgiCHLiITNxLoiHUUCQGY3sJgsgsfEBI9T7t4+MZg1RO3r0KaZOPYOMjIJ6+eOPXujYsW6h/fj88um0Xqn6CBFCCNEcPEkGBGmR4DFS8CSZEGT9A4avDX5+MvQfLAHD1wKjZaw0Uqk4/LzEMolJoWMJXn4yFHo2kBvVg9S8CcAXFrTGyHMhM3MDoy0GwxdBYVCr4PYSKVJmZj5mzjyH/fsj2TIbG0MYGGhVaByUCBFCCKk4ChkEWTHg5yZC99FqCNMfQ25Yt6C1RiGFKOkGGIEuePLcz56Kp5CAV4Ik6D25QW0wAm2ALyoYuWTZCjx5HqSWrQDwIbVsCUakD4YnAoR6UOhaAHwRxBamSM5QFNyKImXi1q3XGDs2BC9fZrBlvXo5Yvlyb5iYqDYK/EtRIkQIIUQ10izw5PngKaTgZ70EPy8ZPEU++Dmvwc9LASPQgtbrcMgNagEKOXiMFNqxx4s9nSDrpdJ2SZKg/5IZO4InyQCPUUBq2QoMTwB+XkLBEG2FFFLLVpBae5fmlRbcpdIxBLIyUUZ9lzWaTKbAqlU3sHLldcjlBW+ogYEWli71Qr9+zuBxcFuQEiFCCNE0DAMopBCmPYQg/TF40kyIEq9DlHrv39aZgk7CWolXoRAagBEZgsdIAYVMpSHZoqQbXxSmzKgehO+eI9fxeyi0xeDJ86HQNoVCv2bB8+KGkBvZf9E1SMVJTc2Fn18wbt/+MAiqWTNrbNjQFba2xpzFRYkQIYRUYjzJO/DzEiBMeQBBxlOAL4To7WUodMwBhoH2yyOQm7oWrOuUXtAX41NDuAWZ/yht82VZgOzLJtX7mFy/FmSm9SE3rAuFjiXy6g0DI9IHeKKC4doa1llYUxgba0MoLBiOLxDwMGVKS0yc2IIt4wolQoQQom4YBsh/B9GbC+BnxkKYeB1ab8ILFq3MTwXDEwICbfBk2SU6nTDtb6Xt0sxPIzeoDYYvLOhfkxkDuZ415CbOBSOhsmORb9sHjEALPLkEcoNaYLRNwQh0odC1+nf244LJ9iCo2P4fRH0IBHysX98VI0Ycw9KlXmjaVD06klMiRAghFYVhgH+HePPk+eBnx0In+g9ALoFO9J5CCUpxNwt4jAyQyVS+vELLBDxpFniMDFKLloAsBwq96pAb1oHMojkU2mLITZyhEBkCfNG/o6G4/bVOKq+rV+OgoyNE48bV2bKaNY1w+vRgTvoCFYcSIUIIKWvyfOg/WArBuyjws16C0RFD6/XZMr+MzKQ+wMghePccefbDIEx/hDz7IZAb2ILha0Ohbw3wtaHQNqGWGFJhJBI5li+/irVrb6FWLWOcOzdEaUi8OiVBACVChBBScgwDXl4yRIlXIciJh87TrZAbOYAnz4Mo8RrA45f4dtVnVW8J5u0tSKu1g9SqDRQ65pBatobc2JH60BC1FRWVijFjTiIiomDeppcvM7B9+wNMmNCM48iKR4kQIYS8p5CCnx0PUfId8LNfQetNOIQp98CXpIMR6heZ5AjfRZX49AyPXzDE26IFFDrm4EkyoNCzhtywLvLshxT0pxFosTNLp9DM0qSSYBgGu3f/jZ9/Po/c3ILbtiIRH4GBbTB2bFOOo/s0SoQIIZrn35YdYep9CN89hzD5DnT+OfjJQ1Rp6VFomYIvSYPEuiOy3X8u6Ggs1P3i1bgJUUfJyTmYPPk0QkM/rMNmb2+KTZt84eZmxWFkJUOJECGkapDngZ+bBH7uW/AkGeDnvoXBnZ/AaBkDshwIchOgEBmCJ5d80VpTUrE7eNJMyMwaQlKzG+SGdSA3qgdGoFUw/JsvKMMXRYh6Cw+PQUDAKSQmfvihMGyYG+bNaw89PRGHkZUcJUKEkMpJlgvBu+fQid4L3WfbwJPnFb1ffir7kC/NLNGp8+r0A0+ajfw6fSE3qAWZiSsg0i+LqAmpMhITszF8+FHk5ckBAGKxLlav7gwfHzuOI1MNJUKEEPXFMODnJhT008l9C/37CyA3qANR8i2VT6UQGoAvy4LMpD4YoS54slyAUUChZw1Jjc6Q61lDWr0DGC2Tsn8dhFRBlpb6+Omntvjpp/Pw9LRFUFAXWFlVvh8MlAgRQrgly4Ew4zkE76Kg83wntN6eZ5dWKAo/L/mTp8urOxD8nNeQWrUGIzKE3NAOkppdyyNyQjSKQsFALldAJPpw+/e779xRvboBunWrBz6/co5mpESIEFI+GEVBv528JPCkmeApCtaq4knSwc9LhN6jteySDx8rLgkqSq6dHxhdK+TWGwqFQW0aWk5IOUhIyMKECafg6mqB2bPbseV8Pg89ejhwGNmXo0SIEFI2GAaixKvQfbgS2vGnwfCEBTMgfwG5gS0EWS8hM7KHzLwZpBbNIDesC6lFc0BkUEaBE0I+JSQkCpMmhSE1NQ8XLryEp2dttG1bi+uwygwlQoSQUuPlpUCUcAXGF/wKP6diEiQ1dYO0WhtIrdpBUsOnYHkHQghnsrOlmDPnAnbtimDLLCwqXx+gz6G/NISQ4jEM+NmvwM9PhjDpJgTvoiHMeAZBxhMIcl6X6BSSah0gyIqBxKZjwWKhfBF4kgzIjR0gtfKAzLxxOb8IQoiqHjxIwJgxJxEdncaWdelih1WrOkMs1uUwsrJHiRAhmoxhIMiMgs7TreDJ84Fn/4OJqSsgy4UwM/rzxxdBat4EOS4/QFLDFxBoff4AQojakMsVWL/+NpYuvQqZTAEA0NMTYsGCDvDza6B264SVBUqECNEkjALaL/bB4OY0KHQsIMx8UWgXYdpD1U7JF0FSowtyXCZCZqG+6wkRQj4tJSUX3313HFeuvGLLGja0wqZNvrCzM+UwsvJFiRAhVRQ/Kw5a8WEQJt+BIPsVtN6eV37+M5MLKnQsC/bLS4TM2BGS6p4AXwtSyxaQG9WD3Mie+vEQUoUYGWkhO1sKoGDwZUBAc0yb1gpaWlV7tnT6K0ZIVcEw4GfFQJRwBUZXx6p0qMyoHiQ1ukCv4UCkoCYUIuNyCpIQoq5EIgE2bvTFsGFHsXy5N1q3rsl1SBWCEiFCKjOFFLqRG6AXsQx8WVaJD8u36YSsZsuhMPowFT6PB+iZG4JJzgRoxXNCqrxbt15DV1cEV1cLtszOzhQXLw6rtJMjlgYlQoRUQjpPtsDg1nTwGPln982pPwHSah6QmTYouN1FHZgJ0WgymQKrVt3AypXXYWdnirCwwUoLpGpSEgRQIkSI+mMYaMUehXZcCHRe7P3s7lKL5pDr10Ku02jILFtUQICEkMoiJiYdY8eG4PbtNwCAZ89SsX37A4wb15TjyLhDiRAh6oZhIEiPhCj5NkSvw6Hz8shnD8mv2R1ZLVZCoVetAgIkhFQ2DMPgwIHHCAwMR1aWBAAgEPAwdWorjB6t2XN5USJECId40kwIU+5B5/lOKLTNoBv1O3iy7BIfn9I3Egr9GuUYISGksktPz8O0aWdw9Ogztqx2bWNs2NAVTZtacxiZeqBEiJDywigAWQ548jwI0x5CkPEcOlG7IDe0g3ZsMHiMQuVTZnjuh6R6e0CoVw4BE0KqmitX4jBuXAhev/4wmGLgQBcsWuQJAwPqLwhQIkRI2WAU0I45An52LPiSd9B7+Guxu4pSH5T4tDlOYyCt7knJDyFEZQkJWfjmm8OQSAoGVZiYaGPFik7o2bNyrxZf1igRIqS0pNnQe7wOOk+3QpCb8EWnyq/ZDdJqbSGp1g4K3epgdMRlFCQhRFNZWRlg6tSWWLz4Cjw8amLdui6wtjbkOiy1Q4kQISUkenMB2i/2Qzf6d5WOk1T3BCPQARg5pJatIDd1gcysERQ65jQzMyGkzDAMA4WCgUDAZ8smTGgGa2tDfP21s8YNiy8p+itMyMek2dB+GQx+XhK03l6EMPk2+JL0Eh3KCPXxzuM3MCIDyI3qQaFvU76xEkIIgOTkHEyefBoNGlhi2rRWbLlAwEf//vU5jEz9USJECAB+Vix0n26D3qNVKh0nM7KHtFo75Lj8AIVB7YLpmQkhpAKFh8cgIOAUEhOzcfr0C3ToYItmzWg0WElRIkQ0F6OAaXATCDOjVToss9V6SKy9qLWHEMKpvDwZFi26jM2b77JlJiY67DxBpGQoESKagWGgFXcSus+2AvJ8aCVc/vTufG1IanRGnv1QMCIDyIydwGibUYsPIUQtREYmwd8/BI8fJ7Nlnp62CArqAisrfQ4jq3woESJVE6OAKPE6tF6FQO/RmhIdotAyQa5LAHIdRoLRNi3nAAkhRHUKBYOtW+9hwYJLyM8vGBavrS3A7NltMXKkO3WILgVKhEjVwDDQivsLOlF7oP3qpMqHJw3JoNYeQohaS03Nhb//SZw795Itc3Y2x6ZNvnB2NucwssqNEiFSecklMDvSCIKcVyU+RGLVFtlNFkBm7FgwQSElP4SQSkJPT4S3bz/MED16dGPMmuUBHR36Kv8S9O6RyoFRQJhyH7z8FGi/PAbdqJ0lOkxSrR3y6/RHvm1PMFom5RsjIYSUIx0dITZu9MXQocfwyy/e8PSszXVIVQIlQkR9MAoI3kWBJ8uB4N1zCNIfQ5R4DVoJV0p8CpmRPbKa/wqpVStAoFOOwRJCSPl68CABenoi1KtnxpbVr2+B69dHQCjkf+JIogpKhAi3Yk7D/FDnLzqFzNgRaT2uA3xBGQVFCCHckcsVWL/+NpYuvQonJzFCQgZCW/vD1zUlQWWLEiHCCd2Ha2Bw92eVj5OaNUJ+7d4AX4S8ugNpTS5CSJUSH5+JceNCcPVqQd/Hhw+TsH37A4wZ04TjyKouSoRIheJnx0N8yLnY5xmhPiRWHpAb1gFPIYFM3ARSi2aQG9YBBNoVGCkhhFSso0efYurUM8jIyAdQMJYjIKA5vv22EbeBVXGUCJEKI3gXBbPgxkU+l97pGKTVO1RsQIQQogYyM/Mxc+Y57N8fyZbZ2Bhi/fouaN26JoeRaQZKhEi5E6Q/hl7EcujEHCr85Lg0JGcJwDAVHxchhHDt1q3XGDs2BC9fZrBlvXo5Yvlyb5iY0ICPikCJECl7DAPR2wvQvzsXopS7Re6S4zQGOS2Ww1zHEMjKrOAACSGEe2/eZKJ374OQSApmiDYw0MLSpV7o188ZPJrjrMJQIkTKDC8/DWZHGoIvSf/kfjlOo5HdfDnoY04I0WTVqxti7NgmWL36Jpo1s8aGDV1ha2vMdVgahxIhUmqCd1EQJt+F1ptw6ET/8dn9M1uuQZ7dQJrfhxCikZh/+wD8t7Vn2rRWsLExwuDBrjQsniOUCBGViN5egvHpnuAx8s/uy/C1kdViJfLsBwM8+oATQjRXenoepk07g0aNqmHcuKZsuUgkwLBhbhxGRigRIiUmPlAX/Lzkz+6XV/trZLb7XwVERAgh6u/KlTiMGxeC16+zcPJkFNq1q4UGDSy5Dov8ixIh8km83EQYnx8MUdKNIp9n+CLkuM2AzMQJ0mrtwGjR/W1CCAEAiUSOZcuuYt26W+zIWH19ERITs7kNjCihRIgUS+/vFdC/N7/I51J7XIPc1KWCIyKEkMohKioVY8acREREIlvm4VET69Z1gbW1IYeRkY9RIkQKEabcg+mJ9sU+n+SXCvDpnw4hhHyMYRjs2vU3Zs8+j9xcGQBAJOIjMLANxo5tCj6fxsuqG/o2IyyeNBPme22KfC670SzkuE4G+KIKjooQQiqHtLRc/PBDGEJDo9kye3tTbNrkCzc3Kw4jI59CiRABAIjiT8PkbN8in0v96g7kxvUqOCJCCKlctLSEeP48ld0ePrwh5s5tBz09+gGpzigRIjA91gLC9MeFytM7n4S0mgcHERFCSOWjry/Cxo1dMXToUfzyS0f4+NhxHRIpAUqENJz+zWmFkqBcx++R1eJXjiIihJDKITIyCXp6ItSubcKWNWpUDbdujYS2Nn29VhY0y50G04tYBr0nm5XK0rpdoCSIEEI+QaFgsGXLXfj4/AF//xDIZAql5ykJqlyotjSNQgbDaxOgE72n0FNJA98AIn0OgiKEkMohISELEyacwvnzLwEAd+68wY4dD/Ddd+4cR0ZKi/MWoT179sDLywsNGjRAv379EBER8cn9d+zYAR8fH7i5uaF9+/ZYvHgx8vPzKyjayosnSYfFLiNY/G5WZBKU4bmPkiBCCPmEkJAotG+/i02CAGD06Mbw82vAYVTkS3HaInTy5EksWbIE8+bNQ8OGDbFz506MHDkSoaGhEIvFhfY/fvw4fv31VyxevBju7u6IiYnBjBkzwOPxEBgYyMErqBx4kgyY76tV5HMyYwekdz4BRpeGdhJCSFGysyWYOvUMdu788EPdykofQUE+8PSszV1gpExwmght374d/fv3R9++BcO2582bh/Pnz+PQoUMYNWpUof3v3buHxo0bo0ePHgCAGjVqoHv37njw4EGFxl3ZmO+rWahMoS1Guk8o5CaOHERECCGVw4MHCRg7NhTPnqWwZV272mHlys4Qi3U5jIyUFc4SIYlEgkePHmH06NFsGZ/PR+vWrXHv3r0ij3F3d8exY8cQEREBNzc3xMXF4cKFC/jqq69Uvj6PV/BfVSZ6FQrjs/0LlScPe8c+5vIteP/+V/V6qCyoPtQH1YV6iI/PhK/vPkgkcgCAnp4QCxd6ws/PFTyqnApXXm85Z4lQWloa5HJ5oVtgYrEYL168KPKYHj16IC0tDYMGDQLDMJDJZBgwYADGjBmj8vXNzKrwWi/npwJ3ihn5NYWBecVG81licRWui0qI6kN9UF1wy9zcEGPHNsXq1TfQpEl1/PFHXzg4FO62QSq3SjVq7MaNG9i8eTPmzJkDNzc3xMbGYtGiRVi/fj3GjRun0rlSUzOhUHx+v8pE99Fa6N+eVezzycPeAcmZFRjRp/F4BX/oU1Iy2ZWZCXeoPtQH1QV3GIZRau2ZOrUFatUyxoABzhCJBEhWo7+hmobPL59GDM4SIVNTUwgEAqSkpCiVp6SkwNy86DaLNWvWoGfPnujXrx8AwNHRETk5OZg9ezb8/f3B55d8EBzDoEr9gbHYZVRkuULHHBleByEzbwKo6eutanVR2VF9qA+qi4qTmZmPmTPPwd29Gr79thFbrq0txKRJrZCcTEkp18rr/eds+LyWlhZcXFxw7do1tkyhUODatWtwdy96Poa8vLxCyY5AIABQkMVrIq2XR4tNgpK/eYmU/i8KkiBCCCFFunXrNTw9f8f+/ZGYO/eCUsdoUvVxemtsxIgRmD59OlxdXeHm5oadO3ciNzcXffr0AQD8+OOPsLKywpQpUwAAnp6e2L59O+rXr8/eGluzZg08PT3ZhEhT8DNfQHykUZHPpXz9DAq9ahUbECGEVDIymQIrV17HqlU3IJcX/JgWCgWIicmgvkAahNNEyNfXF6mpqQgKCkJSUhKcnZ2xdetW9tbYmzdvlFqA/P39wePxsHr1aiQkJMDMzAyenp6YNGkSVy+BM8UlQcnfxIDRNqvYYAghpJKJiUnH2LEhuH37DVvWrJk1NmzoCltbYw4jIxWNx2joPaWUlMrZWVrn2Q4YXg8oVJ7S5yEUBkVPmqiueLyCURl07109UH2oD6qL8sMwDPbvj0RgYDiys6UAAIGAhylTWmLixBYQCpW7X1BdqA8+v3xGUlaqUWOaTu/+YuhHLC1UnjT0XRF7E0II+a+MjDxMnXoGR48+Y8tsbY2xcWNXNG1qzWFkhEuUCFUSeg+WFp0EDcngIBpCCKl8eDwe7t59y24PGOCCxYs9YWCgxWFUhGuUCKk5QVokzI63LFSe0W4nJLV7cxARIYRUTkZG2li/vgtGjDiOZcu80bOnA9chETVAiZC6Ushg8XvRnZ5Tv7oDuXG9Cg6IEEIql6ioVOjpiWBt/aFfScuWNXD79nfQ1xdxGBlRJ5zNI0Q+rbgkKLNlECVBhBDyCQzDYOfOCHh7/47x40OhUCj3cqYkiPwXtQipGd2/V8Lg3txC5Wk+pyCzalXxARFCSCWSnJyDyZNPIzQ0GgBw+XIcdu2KwPDhDTmOjKgrSoTUiOHFb6ET82eh8qQhGbQMNSGEfEZ4eAwCAk4hMTGbLRs2zA39+9fnMCqi7igRUhey3KKToEFvKQkihJBPyMuTYdGiy9i8+S5bJhbrYvXqzvDxseMwMlIZUCKkBnj5qTDfX1upLLlfNBhdC24CIoSQSiIyMgn+/iF4/DiZLfP0tEVQUBdYWelzGBmpLCgRUgNmh1yVthmBDiVBhBDyGXFx7+Dj8wfy8+UAAG1tAWbPbouRI93B51NLOikZGjXGMUFqBPiyLHZbZmSP5MGJHEZECCGVQ82aRmz/H2dnc4SFDcb33zemJIiohFqEOKbzj3K/oLSeNzmKhBBCKp/58zugRg0j+Ps3gY4OfaUR1VGLEId4ecnQe7Sa3c5qthTg0weZEEI+lp0txdSpZ7Bv3yOlcn19ESZNakFJECk1+pfDFVkOzA/UVSrKr/UVR8EQQoj6evAgAf7+JxEVlYZDhx6jRQsb1KljwnVYpIqgFiGOWPxRTWlbITKGQt+Go2gIIUT9yOUKBAXdRNeuexEVlQagYNboJ0+SP3MkISVHLUIcMD6t3PKj0LFESv8ojqIhhBD1Ex+fiXHjQnD16iu2rGFDK2za5As7O1MOIyNVDSVCFYwnyYDWm3NKZZQEEULIB0ePPsXUqWeQkZEPoGBO2YCA5pg2rRW0tAQcR0eqGkqEKpBW7AkYnx+oVJY0JJ2bYAghRM1kZUkQGBiO/fsj2TIbG0OsX98FrVvX5DAyUpVRIlRBtP85BKNLI5TKst1mADzqpkUIIQCQny/H+fMv2e1evRyxfLk3TEx0OIyKVHX0LVwRFNJCSZDE2hs5DQM5CogQQtSPWKyLtWu7wNBQC+vWdcHmzb6UBJFyRy1C5YyXlwLzA3WUyt55/Ib8ut9wFBEhhKiHmJh06OmJYGn5YU2wDh1scffudzA2pgSIVAxqESpH/KyXhZIgqWUrSoIIIRqNYRjs2/cInp67MXFiGBiGUXqekiBSkSgRKi8MA/HhBoWK0zse4SAYQghRD+npeRg16gQCAk4hO1uKM2f+wd69jz5/ICHlhG6NlROjcwOUtvNr9cC7Dns4ioYQQrh35Uocxo0LwevXHxaaHjDABT17OnAYFdF0lAiVB4aB9qsQpSJKggghmkoikWPZsqtYt+4W3t8FMzHRxooVnSgJIpyjRKgc6DzZrLSdNDiJo0gIIYRbz5+nwt//JCIiEtkyD4+aWLeuC6ytDTmMjJAClAiVA0HWPx8VaHMTCCGEcCgmJh0dO/6O3FwZAEAk4iMwsA3Gjm0KPp/HcXSEFKDO0mWMl5cCvccb2e3MVus5jIYQQrhTu7YJfH3tAQD29qYICRmI8eObURJE1Aq1CJWxj4fLS6y9OIqEEEK4t2yZN2rWNMLEiS2gpyfiOhxCCvmiFqH8/PyyiqNK4OUq9wVi+FpQ6NtwFA0hhFScvDwZfv75PI4de6ZUbmSkjZkzPSgJImpL5URIoVBg/fr1aNu2Ldzd3REXFwcAWL16NQ4ePFjmAVYm5gftlLaT/ZI5ioQQQipOZGQSfHz+wObNdzFlymnEx2dyHRIhJaZyIrRhwwYcOXIE06ZNg0j0IcN3cHDAn3/+WabBVSb8nDdK2zn1AziKhBBCKoZCwWDLlrvw8fkDjx8X/PDLy5Ph/v23HEdGSMmpnAgdPXoUCxYsQM+ePcHnfzjc0dERL168KNPgKhNBeqTSdnbThRxFQggh5S8hIQsDBx7GTz+dR36+HADg7GyOsLDB6NatHsfREVJyKneWTkhIQK1atQqVMwwDmUxWJkFVOowCJmd6s5s5rpM5DIYQQspXSEgUJk8+jZSUXLZs9OjGmDXLAzo6NAaHVC4q/4u1t7fH7du3YWOj3Ak4NDQUzs7OZRZYZWJ4xV9pW65nzVEkhBBSfrKzpZgz5wJ27Ypgy6ys9BEU5ANPz9rcBUbIF1A5ERo7dixmzJiBhIQEMAyDsLAw/PPPPwgODsbmzZs/f4IqSOfFXqXtPMfvOIqEEELKT1ZWPk6ceM5ud+1qh5UrO0Ms1uUwKkK+jMp9hDp27IhNmzbh2rVr0NXVRVBQEKKjo7Fp0ya0adOmPGJUa1ovjyptJ/f/B+DRPJWEkKrHysoAK1d2gp6eECtXdsKOHT0pCSKVHo9h3i+Bp1lSUjKhUHz5eSx2GSltJw199+Un1RA8HmBubojk5Exo5r9C9UL1oT7UpS7i4zOhpyeEqalyspOUlAMLCz2OoqpY6lIXBODzAbG47NenU7npwtvbG2lpaYXK3717B29v7zIJqrLg57xW2qblNAghVcXRo0/RocMuTJ16Bh//XtaUJIhoBpUTofj4eCiKaEqRSCRISEgok6AqC/GfTkrbefZ+HEVCCCFlIzMzHxMmhOL7708gIyMfx48/x6FDT7gOi5ByU+LO0mfPnmUfX7p0CYaGH5qnFAoFrl27VmgkWVXGk6QrbefZ9iloQyWEkErq1q3X8PcPQWxsBlvWq5cjOnas84mjCKncSpwIjRs3DgDA4/EwY8YM5ZMIhbCxsSlUXpWZ71OeSymz/Q5uAiGEkC8kkymwatUNrFx5HXJ5wW0wAwMtLF3qhX79nMGjH3mkCitxIvTkSUHTqJeXF/7880+YmZmVW1DqTph8R2lbYqV5o+UIIVVDTEw6xo4Nwe3bH5YJatbMGhs2dIWtrTGHkRFSMVSeRyg8PLw84qhUDK9NUNrO6PQXR5EQQkjpvXiRho4d9yArSwIAEAh4mDKlJSZObAGhkKYBIZqhVHOh5+Tk4NatW3j9+jWkUqnSc0OHDi2TwNSZMO0h+zir8XyAL+AwGkIIKZ06dUzQtm1NhIREw9bWGBs3dkXTpjQzPtEsKidCkZGRGDVqFHJzc5GbmwtjY2OkpaVBV1cXZmZmVT4R4me/UtrOdfYvZk9CCFFvPB4PK1d2Rs2a1zFjRhsYGGhxHRIhFU7lts8lS5bA09MTt27dgra2Ng4cOIBz587BxcUF06dPL48Y1YpJqI9ygUCbm0AIIUQFEokcCxZcwunTL5TKxWJdLFzoSUkQ0VgqJ0KPHz/GiBEjwOfzIRAIIJFIUL16dUybNg0rV64sjxjViiA7jn2c1Xg+h5EQQkjJREWlwtd3L9auvYUffghDYmI21yERojZUToSEQiH4/ILDxGIxXr8umF3ZwMAAb9++Ldvo1Izx6a+UtnNdfuAoEkII+TyGYbBzZwS8vX9HREQiACAjIw83b77+zJGEaA6V+wjVr18ff//9N2rXro1mzZohKCgIaWlpOHr0KOrVq1ceMaoHhRxab84pl9HcGoQQNZWcnIPJk08jNDSaLbO3N8WmTb5wc7PiMDJC1IvKLUKTJk2ChYUF+9jIyAhz585FWloa5s+vureKdJ7vUNpO7v8PN4EQQshnhIfHoEOH3UpJ0PDhDXHmjB8lQYR8ROUWoQYNGrCPxWIxtm3bVqYBqSvDG5PYxzLDumB0xBxGQwghheXlybBo0WVs3nyXLROLdbF6dWf4+NhxGBkh6qvMZsx69OgRRo8eXVanUy8frbyc3WwZR4EQQkjxkpNzsHfvI3bby6s2zp8fSkkQIZ+gUiJ06dIlLFu2DCtXrkRcXMHoqejoaIwdOxZff/11kavSVwW8/FSlbUkNn2L2JIQQ7tSoYYTly72hrS3A4sWe2Lu3N6ys9LkOixC1VuJbYwcPHsTPP/8MY2NjvHv3DgcPHsSMGTOwcOFCdO3aFX/99Rfs7Krmrw5+btUeDUcIqZwSErKgpyeCoeGH+cz69HFCixY2sLEx5DAyQiqPErcI7dq1C1OnTsWNGzewevVqpKWlYe/evTh+/Djmz59fZZMgADC8MZl9TAusEkLUQUhIFDp02I2ZM88Veo6SIEJKrsSJUFxcHLp06QIA6Ny5M4RCIaZNm4Zq1aqVW3DqQpR4jX0stWzNYSSEEE2XnS3F1KlnMGzYMaSk5GL//kgcP/6M67AIqbRKfGssLy8Purq6AArWpxGJRLC0tCy3wNSGXKK0mdNgKkeBEEI03YMHCRgz5iSio9PYsq5d7dC6dU0OoyKkclNp+PzBgwehp6cHAJDL5Th8+DBMTU2V9qlqi64aXRyuXCDU5SQOQojmkssVWL/+NpYuvQqZrGBQip6eEAsXemLwYFfwaHJXQkqtxImQtbU1Dhw4wG6bm5vj6NGjSvvweDyVE6E9e/Zg27ZtSEpKgpOTE37++We4ubkVu/+7d++watUqnD59Gunp6bCxscHMmTPRvn17la5bUtpxf7GPGb6oXK5BCCHFiY/PxLhxIbh69RVb1rChFTZt8oWdneknjiSElESJE6Hw8PAyv/jJkyexZMkSzJs3Dw0bNsTOnTsxcuRIhIaGQiwuPGGhRCLBiBEjIBaLsWbNGlhZWeH169cwMjIq89gAAAqp0mbqV3fK5zqEEFKE6Og0+Pj8gYyMfAAFq/oEBDTHtGmtoKUl4Dg6QqoGlWeWLkvbt29H//790bdvXwDAvHnzcP78eRw6dAijRo0qtP+hQ4eQkZGBffv2QSQqaJ2pUaNGucUn3mertK0wrF1u1yKEkI/VqWOCxo2r4dy5l7CxMcT69V2oPxAhZazMZpZWlUQiwaNHj9C69YdRWHw+H61bt8a9e/eKPCY8PByNGjXC/Pnz0bp1a3Tv3h2bNm2CXC4v+wAZBfiyLHZToWVS9tcghJBP4PN5CArywZAhDXDu3BBKgggpB5y1CKWlpUEulxe6BSYWi/HixYsij4mLi8P169fRo0cPbNmyBbGxsZg3bx5kMhnGjx+v0vV5vE8vHi9MVr4NljoghhabL2Pv3096X9UD1Qe3ZDIFVq26gZYtbdCuXS0ABXVRrZoBVq7sxHF0mos+F+qjvOqA01tjqmIYBmKxGAsWLIBAIICrqysSEhKwbds2lRMhM7PPTDgW+7fSprmFsarhkhISi2nyN3VC9VHxXrxIg5/fYVy79go2NoaIiPAHQHWhTqguqi7OEiFTU1MIBAKkpKQolaekpMDc3LzIYywsLCAUCiEQfOgkWLduXSQlJUEikUBLS6vE109NzcSnlkYzPzeRfZzjOhE5yZklPjcpGR6v4I9LSkrmx+vaEg5QfVQ8hmFw4MBjzJgRjqysgjnL3r7NwrFjkRg+vAnVhRqgz4X64PNL0IhRCqVKhGJjY3Ho0CHExcVh1qxZEIvFuHDhAqytrVGvXr0SnUNLSwsuLi64du0aOnbsCABQKBS4du0a/Pz8ijymcePG+Ouvv6BQKMDnF3RviomJgYWFhUpJEFCwoHxJ/1FLLVrRB6AcqVIXpPxRfVSM9PQ8TJt2BkePfpgV2tbWGBs3dkWzZtYAqC7UCdUF98rr/Ve5s/TNmzfRo0cPREREICwsDDk5OQCAp0+fYu3atSqda8SIEThw4ACOHDmC6OhozJ07F7m5uejTpw8A4Mcff8Svv/7K7j9w4ECkp6dj0aJF+Oeff3D+/Hls3rwZgwcPVvVlfJosR2lTUrNr2Z6fEKLRrlyJQ4cOu5SSoAEDXHDu3BA0bWrNYWSEaB6VW4R+/fVXTJw4ESNGjIC7uztb3rJlS/z+++8qncvX1xepqakICgpCUlISnJ2dsXXrVvbW2Js3b9iWHwCoXr06tm3bhiVLlqBnz56wsrLC0KFD8f3336v6Mj5JlHC1TM9HCCEAIJHIsXz5Vaxde4v9dWtsrI1ff+2Enj0duA2OEA2lciL07NkzrFixolC5mZkZ0tLSijji0/z8/Iq9FbZ79+5CZe7u7kozXJcHnagPCZ3UrGG5XosQojlev87E1q332SSoTZsaWLeuK60WTwiHVL41ZmhoiKSkpELljx8/hpWVVZkExTWdl4fZx3JTFw4jIYRUJbVrm2DRog4QifiYPbstDh3qR0kQIRxTORHq1q0bVqxYgaSkJPB4PCgUCty5cwfLli1Dr169yiHECibPV9rMbhjIUSCEkMouJSUXOTnKS/UMGuSKS5eGYfz4ZuDzaXIaQrimciI0adIk1K1bFx06dEBOTg66desGPz8/uLu7w9/fvzxirFBab84rbSsMbIvekRBCPiE8PAbt2+/CvHkXlcp5PB7q1qXFUglRFyr3EdLS0sLChQsxduxYPH/+HNnZ2ahfvz5q165dDuFVPJ4knX2cb9OZu0AIIZVSXp4MixZdxubNdwEA27c/QMeOddCpU12OIyOEFEXlROj27dto2rQprK2tYW1d9YZ56j1cxT6W2NC09oSQkouMTIK/fwgeP05my7y8asPNrWr0nySkKlI5ERo+fDgsLS3RvXt39OzZE/b29uURF2eE6ZH/2eJsTVpCSCWiUDDYuvUeFiy4hPz8gkWgtbUFmDOnHUaObAQeLVRFiNpSORG6ePEiTp48ib/++gtbtmyBo6MjevToge7du6NatWrlEWPFYZTX3MizL3pYPyGEvJeQkIWAgFM4d+4lW+bsbI5Nm3zh7Fz0ckGEEPWhcpOHmZkZ/Pz8sG/fPpw+fRpdunRBcHAwvLy8MHTo0PKIscKIXocrFwh1uQmEEFIpREWlokOH3UpJ0OjRjXHq1CBKggipJL5o0dWaNWti1KhRcHJywpo1a3Dr1q2yiosTWgmX2ceMUI/DSAghlUGdOiZwcDDDtWvxsLLSR1CQDzw9a3MdFiFEBaVOhO7cuYPjx4/j1KlTyM/Ph7e3NyZPnlyWsVU4vYcr2ce5TmM4jIQQUhkIBHysX98VS5Zcwfz5HSAWUysyIZVNqdYaO3HiBBITE9GmTRvMmjUL3t7e0NWtWn8AJNU7cB0CIUSNyOUKrF9/Gy1b1kDz5h9GzNaoYYT162lhZkIqK5UToVu3bmHkyJHo2rUrzMzMyiMmbrxf/Odf0mrtOQqEEKJu4uMzMW5cCK5efYVatYxx7pwfDA21uQ6LEFIGVE6E9u3bVx5xcI4nzfyogIa7EkKAo0efYurUM8jIKFh+Jy4uA+fPv0SPHrRaPCFVQYkSobNnz6Jdu3YQiUQ4e/bsJ/f19vYuk8AqGi8/lesQCCFqJDMzHzNnnsP+/R/mFrOxMcT69V3QunVNDiMjhJSlEiVC48aNw5UrVyAWizFu3Lhi9+PxeHj8+HGZBceVvNpfcx0CIYRDt269xtixIXj5MoMt69XLEcuXe8PERIfDyAghZa1EidCTJ0+KfFyV6D1awz7myfM4jIQQwhWZTIFVq25g5crrkMsL+g0aGGhh6VIv9OvnTDNEE1IFqTyhYnBwMCQSSaFyiUSC4ODgsoiJE7rPtrGPhcmVez4kQkjpxMSkIyjoJpsENWtmjXPnhqB///qUBBFSRamcCAUGBiIzM7NQeXZ2NgIDA8skKK6ldwnjOgRCCAfs7c0we3ZbCAQ8/PhjKxw92h+2tsZch0UIKUcqjxpjGKbIX0YJCQkwNDQsk6AqGk+SobStMKzDUSSEkIqUnp4HXV0htLU//Cn87jt3eHjUoiUyCNEQJU6EevXqBR6PBx6Ph2HDhkEo/HCoXC7Hq1ev0LZt23IJstwpZB8eCg04DIQQUlGuXInDuHEh6NXLEXPnfpg3jMfjURJEiAYpcSLUsWNHAMDjx4/h4eEBfX199jmRSAQbGxt07ty57COsADzFhz5P0moeHEZCCClvEokcy5dfxdq1t8AwwIYNd+DlVQft2tXiOjRCCAdKnAiNHz8eAGBjYwNfX19oa1edWVVFCVc+PE6+w2EkhJDyFBWVijFjTiIiIpEt8/CoCXt7Uw6jIoRwSeU+Qr179y6PODglePecfSwzbcBhJISQ8sAwDHbt+huzZ59Hbm7BrXCRiI/AwDYYO7Yp+HwaEUaIpipRItS8eXOEhobCzMwMzZo1++Qw0ps3b5ZZcBWF0fowKkRmRokQIVVJcnIOJk8+jdDQaLbM3t4Umzb5ws3NisPICCHqoESJUGBgIAwMDNjHVW0+DX72a/axzMyNw0gIIWUpKioVvXodRGJiNls2fHhDzJ3bDnp6Ig4jI4SoixIlQv+9HdanT59yC4Yr2rHH2Mc8Gc0qTUhVYWtrDBsbAyQmZkMs1sXq1Z3h42PHdViEEDWi8oSKjx49wtOnT9ntM2fOYOzYsVi5cmWRM05XBjLjeuxjuVFdDiMhhJQlkUiAjRt90a2bPc6fH0pJECGkEJUTodmzZyMmJgYAEBcXh0mTJkFXVxehoaH45Zdfyjq+iiH8MBWA3KA2d3EQQkpNoWDw22938fffiUrldeuaYvv2nrCy0i/mSEKIJlM5EYqJiYGzszMAICQkBM2bN8evv/6KJUuWICyMlqYghFS8hIQsDBx4GLNmnceYMSeRkyPlOiRCSCWhciLEMAwUCgUA4Nq1a2jXrh0AoHr16khLSyvb6Agh5DNCQqLQocNunDv3EgDw/Hkqzp79h+OoCCGVhcqJkKurKzZu3Ijg4GDcunULHTp0AAC8evUK5uaVc1p67ZfBXIdACFFRdrYUU6eewbBhx5CSkgsAsLLSx/79fdCjhwPH0RFCKguVJ1ScOXMmpk2bhjNnzmDMmDGwtbUFAJw6dQru7u5lHmBFU2iZcB0CIeQzHjxIwJgxJxEd/aEVumtXO6xc2RlisS6HkRFCKhuVEyEnJyccP368UPmPP/4IPl/lBibO8fI/up0nog6VhKgruVyB9etvY+nSq5DJCm7R6+kJsWBBB/j5Nahyc5wRQsqfyonQew8fPkR0dMFMrfb29nBxcSmzoCqSVtxJrkMghJTQ8+epSklQw4ZW2LTJF3Z2tFYYIaR0VE6EUlJSMHHiRNy6dQtGRkYAgHfv3qFFixZYtWoVzMzMyjzI8iTIesk+zqs7gMNICCGf4+RkjhkzWmPRossICGiOadNaQUtLwHVYhJBKTOV7WQsWLEBOTg5OnDiBmzdv4ubNm/jrr7+QlZWFhQsXlkeM5Ur38Ub2sczUlcNICCEfy8qSsK0/740b1xSnTg3CrFkelAQRQr6YyonQpUuXMGfOHNjZfZih1d7eHnPmzMHFixfLNLiKwAj12McyE2cOIyGE/NetW6/h6bkbK1deVyoXCPho1KgaR1ERQqoalRMhhUIBkajwYoVCoZCdX6gykRs7so9lli05jIQQAgAymQK//HINPXvux8uXGVi58gZu3nz9+QMJIaQUVE6EWrZsiUWLFiEhIYEtS0hIwJIlS9CqVasyDa6iMaq/HYSQMhQTk46ePffjl1+uQS5nAABNmlSn5TEIIeVG5c7Ss2fPhr+/P7y9vVGtWkHz9Nu3b1GvXr1KudaY4F0U1yEQovEYhsGBA48RGBiOrKyCxZsFAh6mTGmJiRNbQCikHymEkPKhciJUvXp1HDlyBNeuXWOHz9vZ2aF169ZlHlxFEOS8+rBBc5AQUuHS0/Pw449nERz8lC2ztTXGxo1d0bSpNYeREUI0gUqJ0MmTJ3H27FlIpVK0atUKQ4YMKa+4Kobio4UZ/9NxmhBS/qKiUtGv3yHEx2eyZQMGuGDxYk8YGGhxGBkhRFOUOBH6448/MH/+fNja2kJHRwenT59GbGwspk+fXp7xlatCs0oTQipUjRpGMDLSRnx8JkxMtLFiRSf07EnrhBFCKk6Jb7zv2bMH48ePx6lTp3D06FEsXboUe/fuLc/YKlS+TSeuQyBE4+joCLFpky86dqyD8+eHUhJECKlwJU6E4uLi0KtXL3a7R48ekMlkSExMLI+4Kh6v8JQAhJCywzAMdu2KwNOnKUrlzs7m+OOP3rC2NuQoMkKIJivxrTGJRAI9vQ99aPh8PkQiEfLz88slMEJI1ZGcnIPJk08jNDQaLi4WCA0dCG3tUi91SAghZUalv0SrV6+Grq4uuy2VSrFx40YYGn74JRcYGFh20RFCKr3w8BgEBJxCYmI2AODRoySEhb1Ajx50G4wQwr0SJ0LNmjXDP//8o1Tm7u6OuLg4dptX6YafM1wHQEiVlZcnw8KFl7Blyz22TCzWxerVneHjY/eJIwkhpOKUOBHavXt3ecbBCVHKhz/Q/Jx4DiMhpGqJjEyCv/9JPH78oT+Qp6ctgoK60CzRhBC1otk36WW57EOeNIvDQAipGhQKBlu33sOCBZeQny8HAGhrCzB7dluMHOkOPr+ytRoTQqo6zU6EeB8GzeXbDeIwEEKqhsjIZMyefQEKRcFtZ2dnc2za5AtnZ3OOIyOEkKJp9AI+PIWMfcwItDmMhJCqwdXVAhMnNgcAjB7dGKdODaIkiBCi1jS6RUj34aoPG4ycu0AIqaRycqTQ0REq3fKaMqUlOnSwRcuWNTiMjBBCSkajW4REaRHsY548j8NICKl8HjxIgLf379iw4bZSuUgkoCSIEFJplCoRun37NqZOnYpvvvkGCQkJAIDg4GDcvn37M0eqF4YnYB/nOozkMBJCKg+5XIGgoJvo2nUvoqPTsGTJFUREJHAdFiGElIrKidCpU6cwcuRI6OjoIDIyEhKJBACQlZWFzZs3l3mA5Yn3n9thjK4lh5EQUjnEx2eib98/sXDhZchkCgBA/foW0NenleIJIZWTyonQxo0bMW/ePCxcuBBC4YcuRo0bN0ZkZGSZBleuGAXXERBSqRw9+hQdOuzC1auvAAA8HvDDD81x4sQA2NmZchwdIYSUjsqdpf/55x80bdq0ULmhoSHevXtXJkFVCLmE6wgIqRQyM/Mxc+Y57N//4YeOjY0h1q/vgtata3IYGSGEfDmVEyFzc3PExsaiRg3lzpB37txBzZqV548iT/ohaZNatOAwEkLUV1RUKgYOPIKXLzPYsl69HPHLL94wNtbhMDJCCCkbKt8a69+/PxYtWoQHDx6Ax+MhISEBx44dw7JlyzBw4MDyiLFc8HPesI8F6U84jIQQ9VW9uiGEwoI/EwYGWli3rgs2b/alJIgQUmWonAiNGjUK3bt3x/Dhw5GTkwM/Pz/89NNP+OabbzBkyJBSBbFnzx54eXmhQYMG6NevHyIiIj5/EIATJ07A0dERY8eOVfmawqSb7GO5Ma2CTUhR9PVF2LTJF23a1MC5c0PQv3/9Sri4MiGEFE/lW2M8Hg/+/v4YOXIkYmNjkZOTAzs7O+jrl24hxZMnT2LJkiWYN28eGjZsiJ07d2LkyJEIDQ2FWCwu9rhXr15h2bJlRfZXKglhxlP2sdygVqnOQUhVwjAMdu16AGdnM9SubcKWN2xohcOH+1ECRAipkko9oaKWlhbs7e3h5uZW6iQIALZv347+/fujb9++sLe3x7x586Cjo4NDhw4Ve4xcLsfUqVMxYcKEUvdLEqY+Yh/LzJuU6hyEVBXp6Xn4/vsTGDYsGP7+JyGVKs+0TkkQIaSqUrlFaMiQIZ/8o7hr164Sn0sikeDRo0cYPXo0W8bn89G6dWvcu3ev2OPWr18PsViMfv364c6dOyW+3n/xc16zj2WWLUB/5yve+/ec3ntuXbkSh7FjQ/D6dRYA4M6dtzh9+gW6davHcWSaiz4b6oPqQn2UVx2onAg5OzsrbctkMjx+/BjPnz9Hr169VDpXWloa5HJ5oVtgYrEYL168KPKY27dv488//0RwcLBK1/oY37g2kPkPAMCkphNgYPhF5yOlJxbTe88FiUSO2bPPYfnyK2AKFouHqakOtmzpga+/rs9tcAQAfTbUCdVF1aVyIjRz5swiy9euXYucnJwvDuhTsrKy8OOPP2LBggUwMzP7spMlflgOJDlbBORlfmF0RFU8XsEfl5SUTPaLmFSMqKhUjB59EhERiWyZh0dN7N37NXR1eUhOps8Dl+izoT6oLtQHnw+YmZV9Qlpmq8/37NkT/fr1w/Tp00t8jKmpKQQCAVJSUpTKU1JSYG5uXmj/uLg4xMfHw9/fny1TKN5P818foaGhqFWrZB2fFTqW4EsK/tgzEAL0D5wzDAP6A1NBCjpE/43Zs88jN1cGABCJ+AgMbINx45rC0tIIycn0B19d0GdDfVBdcK+83v8yS4Tu3bsHLS3V1hvS0tKCi4sLrl27ho4dOwIoSGyuXbsGPz+/QvvXrVsXx48fVypbvXo1srOzMWvWLFSrVq3E1+bnJf5no8zeBkLU2t9/J2LatDPstr29KTZt8oWbmxX1gSCEaCSVM4Dx48crbTMMg6SkJDx8+LBU8/mMGDEC06dPh6urK9zc3LBz507k5uaiT58+AIAff/wRVlZWmDJlCrS1teHgoDznj5GREQAUKi8phi8q1XGEVEZublYYM6YJNm26g+HDG2Lu3HbQ06PPACFEc6mcCBkaKt+f4/F4qFOnDgICAuDh4aFyAL6+vkhNTUVQUBCSkpLg7OyMrVu3srfG3rx5Az6/1KP8P4unkJbbuQnhWn6+DFpaAqWRnrNmtYGXV2106GDLYWSEEKIeeAxT8rtucrkcd+/ehYODA4yNjcszrvK31giQZEJS3QsZnYK5jkYj8XiAubkh9UkpJ5GRSfD3P4lhwxri228bfXZ/qg/1QXWhPqgu1AefXz6j91RqahEIBPj2228r1yrzn8GISj8ZJCHqSKFgsGXLXfj4/IHHj1Mwd+4FPH2a8vkDCSFEA6l8a6xevXp49epVpVpp/lMEmTFch0BImUlIyEJAwCmcO/eSLatTx5TDiAghRL2p3Plm4sSJWLZsGc6dO4fExERkZWUp/VfZMCIDrkMgpEyEhEShQ4fdSknQ6NGNcerUIDg6Fr9uHyGEaLIStwitW7cO3377LUaNGgUA8Pf3V+qAyTAMeDweHj9+XPZRliOZEa08Tyq37Gwp5sy5gF27ItgyKyt9BAX5wNOzNneBEUJIJVDiRGj9+vUYOHCgSmuJVQYSay+uQyCk1KKj0+DnF4zo6DS2rGtXO6xc2RlisS6HkRFCSOVQ4kTo/eCy5s2bl1swnOCV39B8QsqbhYUeu1K8np4QCxd6YvBgV1otnhBCSkilLID+uBKiXoyMtLF+fVc0aVINZ88OgZ9fA/qcEkKIClQaNebj4/PZP7I3b978ooAIIcU7duwZmjSpDhubD3NptGhhg5MnB1ICRAghpaBSIjRhwoRCM0sTQspfZmY+Zs48h/37I9GmTQ38+efXEAg+NOhSEkQIIaWjUiLUrVs3iMU0DJeQinTr1muMHRuCly8zAABXrrxCWNgLdO1qz3FkhBBS+ZU4EaJfnIRULJlMgVWrbmDlyuuQywsGKxgYaGHpUi906WLHcXSEEFI1qDxqjBBS/mJi0jF2bAhu337DljVrZo0NG7rC1raSr/NHCCFqpMSJ0JMnT8ozDkIICn5wHDjwGIGB4cjKkgAABAIepkxpiYkTW0AopOkeCCGkLKm81hghpPzcv5+ACRNC2W1bW2Ns3NgVTZtacxgVIYRUXfTzkhA14u5eDUOHugEABgxwwblzQygJIoSQckQtQoRwSCqVQyjkKw1GmDevPTp2rEMdogkhpAJofIsQTyHlOgSioaKiUtG1617s3x+pVK6vL6IkiBBCKojGJ0Jyw9pch0A0DMMw2LkzAt7evyMiIhGBgeF48SLt8wcSQggpcxp/a0yhW43rEIgGSU7OweTJpxEaGs2WVa9ugLw8GYdREUKI5tL4RIjha3MdAtEQ4eExCAg4hcTEbLZs2DA3zJvXHnp6Ig4jI4QQzaXxiRAh5S0vT4ZFiy5j8+a7bJlYrIvVqzvDx4f6AhFCCJcoESKkHL14kYYRI47j8eNktszLqzbWrPGBlZU+h5ERQggBKBECI9TjOgRShZmY6CAtLRcAoK0twJw57TByZCNau48QQtSExo8ag4h+lZPyY2ami6CgLnBxsUBY2GB89507JUGEEKJGKBEipAydOhWNhIRspbIOHWxx5sxgODubcxQVIYSQ4mh0IsSAfpmTspGdLcXUqWcwZMhRTJx4CgzDKD0vEGj0R40QQtSWRv915oH5/E6EfMaDBwno2PF37NoVAQA4ezYGYWEvOI6KEEJISWh0Z2mp2J3rEEglJpcrsH79bSxdehUymQIAoKcnxMKFnujcuS7H0RFCCCkJjU6EGC0TrkMglVR8fCbGjQvB1auv2LKGDa2waZMv7OxMOYyMEEKIKjQ6ESKkNIKDn2LatDPIyMgHAPB4QEBAc0yb1gpaWgKOoyOEEKIKjU6ERInXuA6BVDK3b7/GqFEn2G0bG0OsX98FrVvX5DAqQgghpaXRnaXletZch0AqmaZNrdGvnzMAoFcvR5w7N4SSIEIIqcQ0ukUop8FUrkMgak6hYMDnK0+zsHSpFzp1qouvvnKgyREJIaSS0+gWIdA8QuQTYmLS0b37Phw9+lSp3NBQG716OVISRAghVYBGtwgRUhSGYXDgwGMEBoYjK0uC58/PoGlTa9jYGHIdGiGEkDJGiRAh/5Genodp087g6NFnbJmJiQ5SU3MpESKEkCpIwxMhmlmafHDlShzGjQvB69dZbNmAAS5YvNgTBgZaHEZGCCGkvGh0IsRTSLkOgagBiUSOZcuuYt26W3i/RJixsTZ+/bUTevZ04DY4Qggh5UqjEyFpNQ+uQyAci4lJx3ff/YWIiES2rE2bGli3rivdCiOEEA2g0YkQo+mD5gh0dYWIj88EAIhEfAQGtsHYsU0LDZknhBBSNVEmQDSalZUBVq3qjHr1zBASMhDjxzejJIgQQjSIRrcIKWhmaY1z4cJLNGhgCTMzXbasSxc7eHvXhkhE64QRQoim0ewWIR598WmKvDwZfv75PPr1O4SpU8+AYZRHDFISRAghmkmzEyGiESIjk+Dj8wc2b74LAPjrr+cID4/hNihCCCFqQaNvjZGqTaFgsHXrPSxYcAn5+XIAgLa2AHPmtIOXV21ugyOEEKIWKBEiVVJCQhYCAk7h3LmXbJmzszk2bfKFs7M5h5ERQghRJ5QIkSonNDQakyaFISUlly0bPboxZs3ygI4O/ZMnhBDyAX0rkCrlxo14DB16lN22tNTH2rU+8PSszV1QhBBC1BZ1liZVSvPm1vD1tQdQMCz+woWhlAQRQggpFrUIkUqNYRjweB8mQOTxeFi5shO6dLHDN9/UV3qOEEII+ZhmtwjxRVxHQL5AfHwm+vQ5iLCwF0rlZma6GDDAhZIgQgghn6WxLUKMQAegL8pK6+jRp5g69QwyMvLx9GkKzp0bCisrfa7DIoQQUslobiIkMuI6BFIKmZn5mDnzHPbvj2TLtLWFSEjIokSIEEKIyjQ2ESKVz61br+HvH4LY2Ay2rFcvRyxf7g0TEx0OIyOEEFJZUSJE1J5MpsDKldexatUNyOUFa4QZGGhh6VIv9OvnTH2BCCGElBolQkStxcZmYMyYk7h9+w1b1qyZNTZs6ApbW2MOIyOEEFIVUCJE1Bqfz8OzZ6kAAIGAhylTWmLixBYQCjV7wCMhhJCyQd8mRK3VqGGEX37xhq2tMY4f/wZTp7aiJIgQQkiZoRYholauX38FFxcLGBpqs2W9ezuha1d7WieMEEJImVOLn9Z79uyBl5cXGjRogH79+iEiIqLYfQ8cOIBBgwahWbNmaNasGYYPH/7J/UnlIJHIsWDBJXz11QEEBp4r9DwlQYQQQsoD54nQyZMnsWTJEowbNw5HjhyBk5MTRo4ciZSUlCL3v3HjBrp164Zdu3Zh3759qF69Or799lskJCRUcOSkrERFpcLXdy/Wrr0FhgEOHIjEuXMxXIdFCCFEA3CeCG3fvh39+/dH3759YW9vj3nz5kFHRweHDh0qcv9ff/0VgwcPhrOzM+zs7LBw4UIoFApcu3atgiMnX4phGGzefBteXr8jIiIRACAS8TF7dlu0b2/LcXSEEEI0Aaf3GyQSCR49eoTRo0ezZXw+H61bt8a9e/dKdI7c3FzIZDIYG6s+lJqmn+FOcnIOJk06jdDQaLbM3t4Umzb5omFDKw4j01zvPw/0ueAe1YX6oLpQH+VVB5wmQmlpaZDL5RCLxUrlYrEYL168KOYoZStWrIClpSVat26t0rX5fB7MzQ1VOoaUjVOnojB8+FG8fZvFlvn7N8WKFZ2hp0cL4XJNLKbPhbqgulAfVBdVV6XugbplyxacPHkSu3btgra29ucP+A+FgkFqcmY5RUaKc+3aK/TseYDdNjfXw+rVneDjY4ecnDzk5ORxGJ1m4/EK/tinpGSCYbiORrNRXagPqgv1wecDZmZln5BymgiZmppCIBAU6hidkpICc3PzTx67bds2bNmyBdu3b4eTk1Oprk//qCteixY28PKqjfDwGHh51caePX0hFDJUF2qEYeizoS6oLtQH1QX3yuv957SztJaWFlxcXJQ6Or/v+Ozu7l7scb/99hs2bNiArVu3okGDBhURKikjPB4Pa9b4YNkyb+zb1xvVqhlwHRIhhBANxvmosREjRuDAgQM4cuQIoqOjMXfuXOTm5qJPnz4AgB9//BG//voru/+WLVuwZs0aLF68GDY2NkhKSkJSUhKys7O5egmkGAkJ2Rg06AguXoxVKrey0seIEQ1psVRCCCGc47yPkK+vL1JTUxEUFISkpCQ4Oztj69at7K2xN2/egM//kK/t27cPUqkUAQEBSucZP348JkyYUKGxk+KFhkZj0qQwpKTk4tGjJJw7NwRmZrpch0UIIYQo4TwRAgA/Pz/4+fkV+dzu3buVtsPDwysiJFJK2dlSzJlzAbt2fZjtW6FgEBf3jhIhQgghakctEiFSNTx4kAB//5OIikpjy7p2tcPKlZ0hFlMSRAghRP1QIkS+mFyuwPr1t7F06VXIZAoAgJ6eEAsXemLwYFfqC0QIIURtaW4ixMi5jqBKeP06E+PGheDKlVdsWcOGVti0yRd2dqYcRkYIIYR8nsYmQvz8ohd1JarJy5Ph3r2CBW95PCAgoDmmTWsFLS0Bx5ERQgghn8f58HmuSM0acR1ClVC3rikWL/aEjY0hjhzph1mzPCgJIoQQUmlobIsQraBXOnfvvoGTk7nSmmADB7qgZ08HGBhocRgZIYQQojqNbREiqpHJFPjll2vo1m0f5s69qPQcj8ejJIgQQkilRIkQ+ayYmHT07Lkfv/xyDXI5gx07HuDy5djPH0gIIYSoOc29NUY+i2EYHDjwGIGB4cjKkgAABAIepkxpiZYta3AcHSGEEPLlKBEiRUpPz8OPP55FcPBTtszW1hgbN3ZF06bWHEZGCCGElB1KhEghV6/GYdy4UMTHZ7JlAwa4YPFiT+oLRAghpEqhRIgouXo1Dr17HwTDFGybmGhjxYpO6NnTgdvACCGEkHJAnaWJkhYtbNCqVUH/Hw+Pmjh/figlQYQQQqosahEiSgQCPtav74pjx55h9OjG4PNpviVCCCFVF7UIabDk5ByMGHEMN27EK5Xb2BjC378JJUGEEEKqPGoR0lDh4TEICDiFxMRs/P13Is6dGwJDQ22uwyKEEEIqFLUIaZi8PBl++ukcBgw4jMTEbABAdrYU0dFpHEdGCCGEVDxqEdIgkZFJ8Pc/icePU9gyL6/aWLPGB1ZW+hxGRgghhHCDEiENoFAw2Lr1HhYsuIT8fDkAQFtbgDlz2mHkyEbg0QK0hBBCNBQlQlVcQkIWAgJO4dy5l2yZs7M5Nm3yhbOzOYeREUIIIdyjRKiKS0vLw9Wrr9jt0aMbY9YsD+joUNUTQggh1Fm6inNyMsecOe1gaamP/fv7YMGCDpQEEUIIIf+ib8Qq5uHDJNSrZwpt7Q9VO3JkI3z9tTNMTHQ4jIwQQghRP9QiVEXI5QoEBd1E5857sHjxFaXneDweJUGEEEJIESgRqgLi4zPRt++fWLjwMmQyBTZuvIPr1+M/fyAhhBCi4ejWWCV39OhTTJ16BhkZ+QAAHg8ICGiOxo2rcRwZIYQQov4oEaqkMjPzMXPmOezfH8mW2dgYYv36LmjduiaHkRFCCCGVByVCldCtW68xdmwIXr7MYMt69XLE8uXe1BeIEEIIUQElQpXMlStx+PrrPyGXMwAAAwMtLF3qhX79nGmGaEIIIURF1Fm6kmne3BoNG1oBAJo1s8a5c0PQv399SoIIIYSQUqAWoUpGJBJgw4auOHr0GSZMaAahkHJZQgghpLQoEVJj6el5mDEjHP7+TdhWIACoW9cUkya14DAyQjQLwzBQKORQKBQVcj0eD8jLy4NUKgHDVMglSTGoLiqWQCAEn1+xP/ApEVJTV67EYdy4ELx+nYWIiAScOeMHPT0R12ERonFkMikyMlIhleZV6HVTU/kVlniRT6O6qEg8mJpaQFtbt8KuSImQmpFI5Fi27CrWrbvF/vpITs7B06cpcHenuYEIqUgMwyAl5S34fD6Mjc0hEAgrrD+eQMBjB0UQblFdVAyGYZCVlYG0tCRYWtaosJYhSoTUSFRUKsaMOYmIiES2zMOjJtat6wJra0MOIyNEM8lkUjCMAsbGFtDSqtipKYRCPmQyaoVQB1QXFcfAwBipqbmQy2Xg87Uq5JqUCKkBhmGwa9ffmD37PHJzZQAAkYiPwMA2GDu2Kfh8GhFGCJd4PBqUQEhF4GIENCVCHEtOzsHkyacRGhrNltnbm2LTJl+4uVl94khCCCGEfCmN/ZkjTLnPdQgAgNevM3HmzD/s9vDhDXHmjB8lQYQQQkgF0NhESGrZmusQAABublaYMaM1xGJd7N79FZYv96bRYYQQwqHY2Bj07OmDnJxsrkOpckaNGo7z589yHYYSjb01xmibcnLd589TUbu2MUQiAVs2blxTDBzoCgsLPU5iIoRUPYsWzUVIyF8AAIFAAEtLK3h6emPkyDHQ1tZW2vfKlUvYu3c3nj59AoVCjjp17NCnTz/4+vYodN7z58/izz/34/nzp1AoFLC2tkGHDt7o27c/jIyMK+S1lbdNm9ajb9/+0NPT5zqUcnPo0AHs3bsbqakpsLOrh0mTpqF+fddi95fJZNi9eztCQv5CcnISata0hb//BLRs+aFR4f79u/jjj914+vQxUlKSsXjxCrRr10HpPMOGjcTatSvRrp1nhc8XVBz1iEIDKBQMtmy5Cy+v3Vi58obScwIBn5IgQkiZa9GiNY4eDcWBA0cxYcJkHD16GNu2bVba588/9yEwcAoaNGiILVt2YOfOffD27owVK5Zg3brVSvtu3rwec+bMhLOzC1asCMKuXfsxfvxEREU9Q2joyQp7XVKptNzO/fbtW1y9eqnIJFAV5Rnjlzp7Ngzr1q3CiBHfY9u232Fv74DJkycgLS212GO2bNmAo0cPY9Kkadi9+wB69eqLmTOn4dmzJ+w+ubm5sLevh8mTpxd7npYtWyMnJwfXr18t09f0JTS2RagiJSRkISDgFM6dewkAWLXqBjp1qoPGjatzHBkhpCrT0hJBLDYHAFhZVcOpU81x+/aHH2IJCW+xbt1q9Os3EKNHj2PLBw70g0gkxOrVK+Dp2REuLq6IjHyI3bu3IyBgCvr3H8juW726NZo1a4nMzMxi40hMTMD69Wtw8+Z1SKUS2NrWweTJ0+Hi4opFi+YiKysTS5b8yu6/Zs2veP78Kdat2wIAGD9+FOrWtYNAIERY2EnUrWsPsdgcCoUC8+cvYY+TyWT46isfjB8/CV27dodCocCePTtx7NgRpKSkoGbNWhg+fCQ8PTsWG2t4+GnY2zvAwsKSLcvISMfy5Uvx4ME9ZGa+g41NDQwZMgKdOnVh9ykqxrVrN+PFiyisXx+EiIh70NHRRfPmLTBhwhSYmJgAAK5fv4qdO7fhn3+iwecL4OraAD/8MBU2NjWKjfFL7du3Bz169EK3bj0BANOmBeLatcv4669jGDJkeJHHnDp1EkOHfotWrTwAAL17f43bt29g3749mD17AQCgVas2aNWqzSevLRAI0LJla5w9ewqtW3uU3Yv6ApQIlbOQkChMnnwaKSm5bNn337ujfn0LDqMihHwJrZgj0H+wCDxpVrldgwfg/RR+jMgA2Y1+gsS2V6nP9+JFFB4+jICV1YcfYOfPn4VMJsPAgUMK7f/VV32xefMGnDlzCi4urggLC4Wurh769OlX5PkNDYue6ywnJwfjx4+ChYUlli5dCbFYjKdPn4BhVJuXJyTkBHr37ouNG7cBAF69eoWff56OnJwc6OkVtKjfuHENeXl5aN/eEwCwe/d2hIWFYOrUQNSoURMPHtzDggWzYWJiCnf3JkVeJyLiHpycnJXK8vMlcHR0hp/fMOjp6ePatctYuHAObGxqKN1O+jjGzMxMBAT4o0ePXggImIz8/Dxs3LgWs2fPQFDQJgBAXl4uBgwYDDu7esjNzcHWrZswc+ZUbN/+R7G3jnbt+h92797+yfdr9+6DqFat8CS8UqkUz549wZAhI9gyPp+Ppk2b49GjiGLPJ5VKoa2tPK+PtrYOIiLufzKOotSv74Lff9+p8nHlhRKhcpKdLcWcORewa9eHf1iWlvpYu9YHnp61uQuMEPLF9B6tgTDjWYVfU9VE6OrVy+jUqS3kcjkkEgn4fD4mTfqRfT4uLhYGBgYwNzcvdKxIJIK1tQ3i4gpasl+9ioW1tQ2EQtW+Nk6fDkV6ejq2bt3F9iGqUaOmSucAgJo1a2Ls2B/YbWvrGtDV1cXFi+fQpUs39loeHu2gp6cPiUSC3bu3Y/XqDXB1dQMA2NjUQETEfRw9erjYROjt27dwcqqvVGZpaYlBgz4ki19/PQA3b15HePgZpUTo4xh37NgKBwdHpda2wMDZ6NOnG2JjX6JWLVt06OCtdK3AwDno3r0jYmJeoG5d+yJj7NWrL7y8On3y/SqqToGC1i25XA4zMzOlcjMzM7x8GVPs+Zo3b4l9+/5Aw4aNYWNTA3fu3MSFC+GlWnrE3NwCiYkJUCgUatFPiBKhcvDgQQLGjDmJ6Og0tqxLFzusWtUZYnHFrZ9CCCkfOa4ToX9/YYW2COW4/PCp3Yvk7t4EU6cGIjc3FwcO/AGBQFDoi7ekSrvg6PPnz+Dg4PjFHakdHZVbaYRCITw9OyEsLBRdunRDbm4uLl++gLlzFwMAXr2KQ15eHiZNGqd0nFQqRb16jsVeJz8/D1payi0fcrkcO3ZsQ3j4aSQlJUEmk0IikUBbW3m28Y9jjIp6jrt3b6NTp7aFrhMf/wq1atkiLi4WW7duQmTkI2RkpLMtZQkJb4tNhIyMjCu8Y/oPP0zF8uULMXjw1+DxeLC2toGvb0+cOHFM5XNpa2tDoVBAKi38HnKBEqEydulSLL755jA7HbuenhALFnSAn18DTmbMJISUPYltry+6TVUSZbGsg66uLtv6Ehg4G8OHD8RffwWje/deAICaNWshKysLyclJMDdXvl0vlUrx+vUrNG7clN03IuI+ZDKZSq1CH49Q+xiPxwPzUZYlk8kK7aejU/hHZOfOXTB+/CikpaXi1q0b0NbWZkcx5eYWdEdYvny1Un8foKC1qzgmJiaF+jvt2bMLBw/uRUDAFNStaw9dXV0EBf0KmUy5Q/THMebm5qJNm7bw9w8odJ33fbemT5+EatWqY/r0WTA3t4BCocDQod9AKi38Hrz3JbfGjI1NIBAIkJqq3DE6NTUVYrG42POZmppiyZJfkZ+fj3fvMmBuboGNG9fC2trmk3EU5d27d9DV1VWLJAigRKjMNW9uDQcHM0RGJqNhQyts2uQLOztuhuoTQsh7fD4fQ4aMwLp1q9CpUxdoa+ugfXtvbNy4Fnv3/o4JEyYp7R8cfAi5ubno2NEHANCpUxf8+ec+HD58UKmz9HuZmZlF9hOyt6+Hv/4Kxrt3GUW2YpiYmOKff6KVyqKinkIg+PzXU4MGDWFpWQ1nz4bh+vWr8PTsyCZpderUgZaWFhIS3hZ7G6wo9eo5IibmhVLZgwf34eHRHj4+vgAAhUKB2NhY1KlT55PncnBwxIUL4ahWrXqRyWNGRjpiY19i+vSf0LChO3utz/mSW2MikQgODk64c+cmO7RdoVDgzp1b6NOn/2evra2tDQsLS8hkMly4EP7ZOIry4kX0J1vlKholQmVMW1uITZt8ceTIU0yZ0hJaWoLPH0QIIRXA07MjNmwIwqFDBzFo0BBUq1YNY8cGYN261dDS0kKXLt0gFApx6dJ5bNmyAQMG+MHFpaAPjIuLKwYNGor161cjOTkR7dp5wtzcAq9exSE4+BDc3BoVmSB17OiDXbv+h8DAqRg9ehzEYnM8f/4U5uYWcHV1Q5MmzbB3726EhPwFV1c3hIWFqPRF2amTD4KDDyMu7iWCgj5MDaCnp48BA/ywdu1KMAwDN7dGyMrKwt9/34e+vgG6du1e5PmaN2+FZcsWQi6XQyAo+Ptds2YthIefwd9/P4ChoRH279+DtLSUzyZCffv2x/HjwZg7dxYGDx4KIyNjvHoVh7NnwzB9+k8wNDSCsbExjh07DLHYHAkJb7Fp09rPvuYvvTU2YMBgLFo0F05O9eHs7IIDB/5Abm4uunX7MGXAggWzYWFhiTFjxgMAHj16iOTkRNjbOyA5OQn/+98WKBQMBg0ayh6Tk5OD+Pg4dvvNm3g8f/4UhobGSq1TDx7cQ/PmLUsdf1mjROgLZGbmY86cCxg1qjGcnD5k305O5ggMLDobJ4QQrgiFQvTp0x9//LELvXt/DV1dXfTvPwjW1jbYu/d3/PnnPsjlCtSpUxdTpsxgh1e/N3ZsABwdnXHkyEEEBx8GwyhgbV0Dnp7exSYWIpEIq1atx7p1qzBt2g+Qy+WoXbsuJk8u6LTdokUrDB/+HTZuXAuJJB/duvVEly7dEB0dVaLX1LlzV+za9T9Uq1Ydbm4NlZ77/nt/mJiYYvfu7Xj9Oh4GBoZwcHDC0KEjijlbwTw3AoEAt2/fRIsWrQAAI0Z8h/j4V5g8eQJ0dHTQs2dvtG3bAdnZn+4jVnD7aBs2blyLSZPGQyqVoFq16mjRohX4fD54PB7mzl2MNWtWYOjQb1Czpi0mTpyKCRNGl+i1l5a3d2ekp6dh69ZNSE1Ngb29A379dS3MzD7cGktIeKvUkVkiycdvv23E69fx0NXVRcuWbfDzz/OVWgGfPIlEQMAYdnvt2lUAgK5du2PWrLkAgKSkRDx8GMEOuVcHPObjm7MaIj94EN612fz5HYtx69ZrjB0bgpcvM1C/vjlOnRoEbW3KK1XB4wHm5oZITs4sdUdMUnaoPgqTSiVISXkDsbg6RCKtzx9QhsqijxApnUOHDuDKlYtYuXIdAKqLsrRhQxAyMzMxffqsIp//1GeOzwfE4qKnafgS9M2tIplMgVWrbmDlyuuQywu+LWJj3yEyMhnu7oU7phFCCKlcvvqqD7KyMpGTk12ll9nggqmpGQYMGMx1GEooEVJBTEw6xo4Nwe3bb9iyZs2ssWFDV9jaVo01dgghRNMJhUIMGzaS6zCqpIED/bgOoRBKhEqAYRgcOPAYgYHhyMqSAAAEAh6mTGmJiRNbQCjkfkIoQgghhKiOEqHPSE/Pw48/nkVw8FO2zNbWGBs3dkXTptYcRkYIIYSQL0WJ0Gc8e5aKY8c+TKU/YIALFi/2hIFBxXacJIRwR0PHlBBS4bj4rNE9nc9o3twaEyc2h7GxNrZu7Y6gIB9KggjREO/nkZFI8jmOhBDNIJcXzKhdkWuQUYvQR16+zECNGoYQCD5UwpQpLTFsmBuqVy/7YXuEEPXF5wugq2uArKyCdQO1tLQrbKkchYLHjkwl3KK6qBgMo0BmZjq0tHTA51fcZMSUCP2LYRjs2vU3Zs8+jylTWiIgoDn7nEgkoCSIEA1lZFSwSvf7ZKii8Pn8Uq3sTcoe1UXF4fH4MDIyq9C1OSkRApCcnIPJk08jNLRgvZulS6/C07M2GjSw/MyRhJCqjsfjwdhYDENDU7bZvvyvCZia6iMtLZsmt+QY1UXFEgpFFb5AuVokQnv27MG2bduQlJQEJycn/Pzzz3Bzcyt2/5CQEKxZswbx8fGoXbs2pk6divbt25fq2uHhMQgIOIXExGy2bPBgV1oolRCihM/ng8+vmP6BPB6go6MDkUhKX74co7qo+jjvLH3y5EksWbIE48aNw5EjR+Dk5ISRI0ciJSWlyP3v3r2LKVOm4Ouvv0ZwcDC8vb0xbtw4PHv2rMj9i5Mn4eGnn85hwIDDbBIkFuti9+6v8MsvHaGnJ/ri10YIIYQQ9cZ5IrR9+3b0798fffv2hb29PebNmwcdHR0cOnSoyP137dqFtm3b4rvvvoOdnR0mTpyI+vXr4/fff1fpup3n2mPLlnvstpdXbZw/PxQ+PnZf9HoIIYQQUnlwmghJJBI8evQIrVu3Zsv4fD5at26Ne/fuFXnM/fv30apVK6UyDw8P3L9/X6VrP36lAwDQ1hZg8WJP7N3bG1ZWtKYMIYQQokk47SOUlpYGuVwOsVisVC4Wi/HixYsij0lOToa5uXmh/ZOTk1W6tqGhFpycxFi9ujMcHcWfP4CUuff94fh80L13NUD1oT6oLtQH1YX6KK8+1GrRWZoL8fFTuA6B/MvMjKYmUCdUH+qD6kJ9UF1UXZzeGjM1NYVAICjUMTolJaVQq8975ubmhVp/PrU/IYQQQkhxOE2EtLS04OLigmvXrrFlCoUC165dg7u7e5HHNGrUCNevX1cqu3r1Kho1alSeoRJCCCGkCuJ81NiIESNw4MABHDlyBNHR0Zg7dy5yc3PRp08fAMCPP/6IX3/9ld1/6NChuHTpEv73v/8hOjoaa9euxcOHD+Hn58fVSyCEEEJIJcV5HyFfX1+kpqYiKCgISUlJcHZ2xtatW9lbXW/evFFafK1x48ZYsWIFVq9ejZUrV6J27dpYv349HBwcuHoJhBBCCKmkeAwXa94TQgghhKgBzm+NEUIIIYRwhRIhQgghhGgsSoQIIYQQorEoESKEEEKIxqJEiBBCCCEaq0omQnv27IGXlxcaNGiAfv36ISIi4pP7h4SEoEuXLmjQoAF69OiBCxcuVFCkVZ8qdXHgwAEMGjQIzZo1Q7NmzTB8+PDP1h1RjaqfjfdOnDgBR0dHjB07tpwj1Byq1sW7d+8wb948eHh4wNXVFT4+PvS3qoyoWhc7duyAj48P3Nzc0L59eyxevBj5+fkVFG3VdevWLYwZMwYeHh5wdHTEmTNnPnvMjRs30Lt3b7i6uqJTp044fPiw6hdmqpgTJ04wLi4uzJ9//sk8f/6c+emnn5imTZsyycnJRe5/584dxtnZmfntt9+YqKgoZtWqVYyLiwvz9OnTCo686lG1LiZPnsz8/vvvTGRkJBMVFcXMmDGDadKkCfP27dsKjrxqUrU+3ouLi2Patm3LDBo0iPH396+gaKs2VesiPz+f6dOnD/P9998zt2/fZuLi4pgbN24wjx8/ruDIqx5V6+LYsWOMq6src+zYMSYuLo65dOkS06ZNG2bx4sUVHHnVc/78eWblypVMWFgY4+DgwJw+ffqT+8fGxjINGzZklixZwkRFRTG7d+9mnJ2dmYsXL6p03SqXCH399dfMvHnz2G25XM54eHgwmzdvLnL/H374gRk1apRSWb9+/Ziff/65XOPUBKrWxcdkMhnj7u7OHDlypJwi1CylqQ+ZTMZ88803zIEDB5jp06dTIlRGVK2LP/74g/H29mYkEklFhagxVK2LefPmMUOHDlUqW7JkCTNgwIByjVPTlCQRWr58OdOtWzelsokTJzLffvutSteqUrfGJBIJHj16hNatW7NlfD4frVu3xr1794o85v79+2jVqpVSmYeHB+7fv1+eoVZ5pamLj+Xm5kImk8HY2Li8wtQYpa2P9evXQywWo1+/fhURpkYoTV2Eh4ejUaNGmD9/Plq3bo3u3btj06ZNkMvlFRV2lVSaunB3d8ejR4/Y22dxcXG4cOEC2rdvXyExkw/K6vub8yU2ylJaWhrkcjnEYrFSuVgsxosXL4o8Jjk5udDK9WKxuNAK90Q1pamLj61YsQKWlpZKf6RI6ZSmPm7fvo0///wTwcHBFRCh5ihNXcTFxeH69evo0aMHtmzZgtjYWMybNw8ymQzjx4+viLCrpNLURY8ePZCWloZBgwaBYRjIZDIMGDAAY8aMqYiQyX8U9f1tbm6OrKws5OXlQUdHp0TnqVItQqTq2LJlC06ePIl169ZBW1ub63A0TlZWFn788UcsWLAAZmZmXIej8RiGgVgsxoIFC+Dq6gpfX1+MGTMG+/bt4zo0jXPjxg1s3rwZc+bMweHDh7Fu3TpcuHAB69ev5zo0UkpVqkXI1NQUAoEAKSkpSuUpKSmFssb3zM3NC7X+fGp/UjKlqYv3tm3bhi1btmD79u1wcnIqzzA1hqr1ERcXh/j4ePj7+7NlCoUCAFC/fn2EhoaiVq1a5Rt0FVWaz4aFhQWEQiEEAgFbVrduXSQlJUEikUBLS6tcY66qSlMXa9asQc+ePdnbxY6OjsjJycHs2bPh7++vtEg4KV9FfX8nJyfDwMCgxK1BQBVrEdLS0oKLiwuuXbvGlikUCly7dg3u7u5FHtOoUSNcv35dqezq1ato1KhReYZa5ZWmLgDgt99+w4YNG7B161Y0aNCgIkLVCKrWR926dXH8+HEEBwez/3l5eaFFixYIDg5GtWrVKjL8KqU0n43GjRsjNjaWTUYBICYmBhYWFpQEfYHS1EVeXl6hZOd9gsrQGuYVqsy+v1Xrx63+Tpw4wbi6ujKHDx9moqKimJ9//plp2rQpk5SUxDAMw0ybNo1ZsWIFu/+dO3eY+vXrM9u2bWOioqKYoKAgGj5fRlSti82bNzMuLi5MaGgok5iYyP6XlZXF1UuoUlStj4/RqLGyo2pdvH79mnF3d2fmz5/PvHjxgjl37hzTqlUrZsOGDVy9hCpD1boICgpi3N3dmb/++ouJjY1lLl++zHTs2JH54YcfOHoFVUdWVhYTGRnJREZGMg4ODsz27duZyMhIJj4+nmEYhlmxYgUzbdo0dv/3w+eXLVvGREVFMb///nuphs9XqVtjAODr64vU1FQEBQUhKSkJzs7O2Lp1K9vM+ebNG6VsvnHjxlixYgVWr16NlStXonbt2li/fj0cHBy4eglVhqp1sW/fPkilUgQEBCidZ/z48ZgwYUKFxl4VqVofpPyoWhfVq1fHtm3bsGTJEvTs2RNWVlYYOnQovv/+e65eQpWhal34+/uDx+Nh9erVSEhIgJmZGTw9PTFp0iSuXkKV8fDhQwwdOpTdXrJkCQCgd+/eWLp0KZKSkvDmzRv2+Zo1a2Lz5s1YsmQJdu3ahWrVqmHhwoVo27atStflMQy15RFCCCFEM9HPP0IIIYRoLEqECCGEEKKxKBEihBBCiMaiRIgQQgghGosSIUIIIYRoLEqECCGEEKKxKBEihBBCiMaiRIgQouTw4cNo2rQp12GUmqOjI86cOfPJfWbMmIGxY8dWUESEEHVW5WaWJoQUfNEfOXKkUHlYWBhsbW05iOiDw4cPIzAwEADA4/FgaWmJNm3aYOrUqRCLxV98/suXL8PY2BgA8OrVK3h7eyM4OBjOzs7sPrNmzSr3daHWrl2LdevWAQD4fD4sLS3Rrl07TJkyBSYmJiU+z4wZM/Du3Tts2LChnCIlRLNRIkRIFdW2bVt2ivr3zMzMOIpGmYGBAUJDQ6FQKPDkyRPMnDkTiYmJ2LZt2xef28LC4rP7GBoafvF1SqJevXrYvn07FAoFoqOjMXPmTGRmZmL16tUVcn1CyOfRrTFCqigtLS1YWFgo/ScQCLB9+3b06NEDjRo1Qvv27TF37lxkZ2cXe54nT55gyJAhcHd3R+PGjdGnTx/8/fff7PO3b9/GoEGD4Obmhvbt22PhwoXIycn5ZGw8Hg8WFhawsrJC+/btMWTIEFy9ehV5eXlQKBRYt24d2rVrB1dXV3z11Ve4ePEie6xEIsH8+fPh4eGBBg0awNPTE5s3b2af/++tMW9vbwBAr1694OjoiCFDhgBQvjW2f/9+eHh4KK3sDhSsKfW+5QoAzpw5g969e6NBgwbw9vbGunXrIJPJPvk6BQIB+zpbt26NLl264OrVq+zzcrkcM2fOhJeXF9zc3ODj44OdO3eyz69duxZHjhzB2bNn4ejoCEdHR9y4cQNAwRpYP/zwA5o2bYrmzZvD398fr169+mQ8hJDCKBEiRMPweDzMmjULf/31F5YuXYrr16/jl19+KXb/qVOnolq1avjzzz9x+PBhfP/99xCJRACA2NhYfP/99+jcuTOOHTuGVatW4c6dO1iwYIFKMeno6EChUEAmk2HXrl3Yvn07pk+fjmPHjsHDwwNjx45FTEwMAGD37t0IDw/H6tWrERoail9++QU2NjZFnvfgwYMAgB07duDy5ctYu3ZtoX26dOmC9PR0NsEAgPT0dFy6dAk9e/YEUJDsTZ8+HUOHDsXJkycxf/58HD58GJs2bSrxa3z16hUuX77MvncAoFAoUK1aNaxZswYnTpzAuHHjsGrVKpw8eRIA8O2336Jr165o27YtLl++jMuXL8Pd3R1SqRQjR46Evr4+9uzZg71790JPTw/fffcdJBJJiWMihNCtMUKqrPPnz8Pd3Z3dbtu2LYKCgjB8+HC2rEaNGpg4cSLmzJmDuXPnFnme169fY+TIkbCzswMA1K5dm31u8+bN6NGjB3vO2rVrY9asWRgyZAjmzp0LbW3tz8YZExODvXv3wtXVFQYGBti2bRu+//57dOvWDQAwbdo03LhxAzt37sScOXPw5s0b2NraokmTJuDxeMUmQcCHW4EmJibF3jIzNjZGu3btcPz4cbRq1QoAcOrUKZiamqJFixYAgHXr1mHUqFHo3bs3gIJVr3/44Qf88ssvGD9+fLHXf/bsGdzd3SGXy5Gfnw8ASq1MIpEIAQEB7HbNmjVx//59hIaGwtfXF/r6+tDR0YFEIlGK/+jRo1AoFFi0aBF4PB6AgpW6mzVrhps3b8LDw6PYmAghyigRIqSKatGihVJyo6urCwC4evUqNm/ejBcvXiArK4v9ks7NzWX3+a8RI0bgp59+wtGjR9nbO7Vq1QJQcNvs6dOnOH78OLs/wzBQKBR49eoVmzx9LDMzE+7u7lAoFMjPz0eTJk2wcOFCZGVlITExEY0bN1bav3Hjxnjy5AkAoHfv3vj222/RpUsXtG3bFh06dPjiL/4ePXrg559/xty5c6GlpYXjx4+jW7du4PP57Ou8e/euUgvQ5943AKhTpw42btyI/Px8HDt2DI8fP4afn5/SPnv27MGhQ4fw+vVr5OfnQyqVwsnJ6ZPxPnnyBLGxsYXep/z8fMTGxpbmLSBEY1EiREgVpaurW2iE2KtXrzB69GgMHDgQkyZNgrGxMe7cuYNZs2ZBKpUW+YU+YcIEdO/eHRcuXMDFixcRFBSEVatWoVOnTsjJycGAAQPYvjf/Vb169WJj09fXx5EjR8Dn82FhYQEdHR0AQFZW1mdfl4uLC86ePYuLFy/i6tWrmDhxIlq3bo2goKDPHlscLy8v/PTTTzh//jwaNGiA27dvK7Xc5OTkYMKECejcuXOhYz/V6iUSidg6mDp1KkaNGoV169Zh4sSJAIATJ05g2bJlmD59Otzd3aGvr49t27bhwYMHn4w3JycHLi4uWLFiRaHn1KVDPCGVBSVChGiQR48egWEYzJgxg23tCAkJ+exxderUQZ06dTB8+HBMnjwZhw4dQqdOnVC/fn1ERUWpPCSfz+cXeYyBgQEsLS1x9+5dNG/enC2/e/cu3NzclPbz9fWFr68vfHx88N133yE9Pb3QsPT3/XHkcvkn49HW1kbnzp1x/PhxvHz5EnXq1IGLiwv7fP369fHPP/988dQD/v7+GDZsGAYOHAgrKyvcvXsX7u7uGDx4MLvPxy06IpGoUEduFxcXhISEQCwWw8DA4ItiIkTTUWdpQjSIra0tpFIpdu/ejbi4OAQHB2Pfvn3F7p+Xl4f58+fjxo0biI+Px507d/D333+zt7y+//573Lt3D/Pnz8fjx48RExODM2fOYP78+aWO8f/t3C9Iu1scx/G3Y0EQlCFiMAgaXDEIAzVYDcqTRJGFIYhBtGiZgtFgGDrEifgIgrMaBBWjsKQYBRXZhlgMYwj+KYZ7wwW58vvd4IULF573q57Dc85pH77P95zp6WnCMOTs7IxKpUIul+Pu7o5MJgPA/v4+JycnlMtlqtUq5+fntLW10dzc/Mu3WltbaWxspFQqUavVeH19/cd1gyDg4uKCo6MjgiD4NjY3N8fx8TFbW1s8PDxQLpc5PT1lY2PjR2fr6+ujp6fn65ZbZ2cnNzc3lEolqtUq+Xz+2408gI6ODu7v76lUKtTrdT4/PwmCgEQiwezsLNfX1zw9PXF5ecnq6irPz88/2pMUdVaEpAhJJpMsLy8ThiHr6+ukUikWFxfJZrO/nR+LxXh5eSGbzVKr1UgkEgwPD381+CaTSYrFIvl8nnQ6DfzV8DsyMvKv95jJZHh7e2NtbY16vU53dzfb29tfTdpNTU3s7e3x+PhILBajt7eX3d3drwrX38XjcVZWVigUCmxubpJKpSgWi79dd2BggJaWFqrV6i9BaGhoiJ2dHQqFAmEYEo/H6erqYnx8/Mfnm5qaYmlpiZmZGSYnJ7m9vWVhYYGGhgZGR0dJp9PfnguYmJjg6uqKsbExPj4+ODg4oL+/n8PDQ3K5HPPz87y/v9Pe3s7g4KAVIumHGv74r59XlSRJ+p/y15gkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYosg5AkSYqsPwGQw2tQiRjxzwAAAABJRU5ErkJggg=="
|
||
},
|
||
"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": "2024-03-19T07:47:55.242503Z",
|
||
"start_time": "2024-03-19T07:47:53.191160Z"
|
||
}
|
||
},
|
||
"id": "41091791008ff727",
|
||
"execution_count": 116
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"outputs": [],
|
||
"source": [],
|
||
"metadata": {
|
||
"collapsed": false,
|
||
"ExecuteTime": {
|
||
"end_time": "2024-03-19T07:47:55.245679Z",
|
||
"start_time": "2024-03-19T07:47:55.243641Z"
|
||
}
|
||
},
|
||
"id": "48396392f3b959d5",
|
||
"execution_count": 116
|
||
}
|
||
],
|
||
"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
|
||
}
|