def read_3D_dataset(input_data_directory_with_date: str, label_name: str):
"""
Read data set under the given directory, return data and label
:param input_data_directory_with_date: input data directory with time where train.csv and test.csv exist
:param label_name: name of label column in numpy array
:return data: data in numpy array
:return label: label in series
"""
# Get file names
train_data_file_path = os.path.join(input_data_directory_with_date,
"train_data.npy")
train_label_file_path = os.path.join(input_data_directory_with_date,
"train_label.npy")
test_data_file_path = os.path.join(input_data_directory_with_date,
"test_data.npy")
test_label_file_path = os.path.join(input_data_directory_with_date,
"test_label.npy")
# Check if the given data set exist
FileUtil.is_valid_file(train_data_file_path)
FileUtil.is_valid_file(train_label_file_path)
FileUtil.is_valid_file(test_data_file_path)
FileUtil.is_valid_file(test_label_file_path)
# Read csv file
train_data = FileUtil.load_3D_array(train_data_file_path)
train_label = FileUtil.load_3D_array(train_label_file_path)
test_data = FileUtil.load_3D_array(test_data_file_path)
test_label = FileUtil.load_3D_array(test_label_file_path)
return train_data, test_data, train_label, test_label