def process_sub(subspace, gm, median, scaler1, scaler2):
    """
    Apply ROD on a 3D subSpace then process it with sigmoid
    to compare apples to apples

    Parameters
    ----------
    subspace : array-like, 3D subspace of the data
    gm: list, the geometric median
    median: float, MAD median
    scaler1: obj, MinMaxScaler of Angles group 1
    scaler2: obj, MinMaxScaler of Angles group 2

    Returns
    -------
    ROD decision scores with sigmoid applied, gm, scaler1, scaler2
    """
    mad_subspace, gm, median, scaler1, scaler2 = rod_3D(subspace, gm=gm,
                                                        median=median,
                                                        scaler1=scaler1,
                                                        scaler2=scaler2)
    return sigmoid(
        np.nan_to_num(np.array(mad_subspace))), gm, median, scaler1, scaler2

    Apply ROD on a 3D subSpace then process it with sigmoid
    to compare apples to apples

    Parameters
    ----------
    subspace : array-like, 3D subspace of the data
    gm: list, the geometric median
    median: float, MAD median
    scaler1: obj, MinMaxScaler of Angles group 1
    scaler2: obj, MinMaxScaler of Angles group 2

    Returns
    -------
    ROD decision scores with sigmoid applied, gm, scaler1, scaler2
    
pyod/models/rod.py