load_data_turi.py

from glob import glob

acc_files = glob(data_dir + 'acc_*.txt')
gyro_files = glob(data_dir + 'gyro_*.txt')

# Load data
data = tc.SFrame()
files = zip(sorted(acc_files), sorted(gyro_files))
for acc_file, gyro_file in files:
    exp_id = int(acc_file.split('_')[1][-2:])
    user_id = int(acc_file.split('_')[2][4:6])
    
    # Load accel data
    sf = tc.SFrame.read_csv(acc_file, delimiter=' ', header=False, verbose=False)
    sf = sf.rename({'X1': 'acc_x', 'X2': 'acc_y', 'X3': 'acc_z'})
    sf['exp_id'] = exp_id
    sf['user_id'] = user_id
    
    # Load gyro data
    gyro_sf = tc.SFrame.read_csv(gyro_file, delimiter=' ', header=False, verbose=False)
    gyro_sf = gyro_sf.rename({'X1': 'gyro_x', 'X2': 'gyro_y', 'X3': 'gyro_z'})
    sf = sf.add_columns(gyro_sf)
    
    # Calc labels
    exp_labels = labels[labels['exp_id'] == exp_id][['activity_id', 'start', 'end']].to_numpy()
    sf = sf.add_row_number()
    sf['activity_id'] = sf['id'].apply(lambda x: find_label_for_containing_interval(exp_labels, x))
    sf = sf.remove_columns(['id'])
    
    data = data.append(sf)