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, "%")