import os
import DataLoaderService
import AnomalyDetectionService
    
if __name__ == "__main__":
    print("Manipulating Data into known format...")
    directory = "TrainingData"
    modelsDirectory = "NetworkModels"
    dataFiles = DataLoaderService.getDataFiles(directory)
    for file in dataFiles:
        if file.endswith(".csv"):
            dataDictionary = DataLoaderService.loadData(directory, file)
            #os.remove(directory + "/" + file)
            #os.remove(directory + "\metadata.json")

    print("Training and Detecting Models...")
    AnomalyDetectionService.trainModel(dataDictionary.dictionary, modelsDirectory, "TestingData\dataset1.csv")
0dcd34c05257cc3b1dfa43c6dab656c8d21995f3
<mask token>

<mask token>
if __name__ == '__main__':
    print('Manipulating Data into known format...')
    directory = 'TrainingData'
    modelsDirectory = 'NetworkModels'
    dataFiles = DataLoaderService.getDataFiles(directory)
    for file in dataFiles:
        if file.endswith('.csv'):
            dataDictionary = DataLoaderService.loadData(directory, file)
    print('Training and Detecting Models...')
    AnomalyDetectionService.trainModel(dataDictionary.dictionary,
        modelsDirectory, 'TestingData\\dataset1.csv')

import os
import DataLoaderService
import AnomalyDetectionService
if __name__ == '__main__':
    print('Manipulating Data into known format...')
    directory = 'TrainingData'
    modelsDirectory = 'NetworkModels'
    dataFiles = DataLoaderService.getDataFiles(directory)
    for file in dataFiles:
        if file.endswith('.csv'):
            dataDictionary = DataLoaderService.loadData(directory, file)
    print('Training and Detecting Models...')
    AnomalyDetectionService.trainModel(dataDictionary.dictionary,
        modelsDirectory, 'TestingData\\dataset1.csv')

import os
import DataLoaderService
import AnomalyDetectionService
    
if __name__ == "__main__":
    print("Manipulating Data into known format...")
    directory = "TrainingData"
    modelsDirectory = "NetworkModels"
    dataFiles = DataLoaderService.getDataFiles(directory)
    for file in dataFiles:
        if file.endswith(".csv"):
            dataDictionary = DataLoaderService.loadData(directory, file)
            #os.remove(directory + "/" + file)
            #os.remove(directory + "\metadata.json")

    print("Training and Detecting Models...")
    AnomalyDetectionService.trainModel(dataDictionary.dictionary, modelsDirectory, "TestingData\dataset1.csv")