def __init__(self, dataset): self.__dataset = dataset dataset = HandManager(self.__dataset) self.__patients_paths = dataset.get_files_path() self.__patients_paths = HandManager.filter_file(self.__patients_paths, MINIMUM_SAMPLES) self.__patients = HandManager.get_ids_from_dir(dataset.get_patient_paths()) self.__patients.sort()
def execute_emothaw_experiment(self): file_manager = HandManager("ConvertedEmothaw") rhs_extraction = RHSDistanceExtract(self.__file_samples, NUM_FILE_SAMPLES) ids_task = TaskManager.get_task_from_paths(file_manager.get_files_path(), self.__test_task) for id in ids_task: paths = ids_task.get(id) for task_path in paths: tensor = rhs_extraction.extract_rhs_file(task_path) result = self.__ml_model.predict_result(tensor) counter_result = Counter(result) print("Id: ", id, "file: ", task_path) healthy = counter_result.get(0) / len(result) * 100 print("Healthy: ", healthy, "%") print("Disease: ", 100 - healthy, "%")