def masks(list_of_index_lists, n):
    """Make an array in which rows store 1d mask arrays from list of index lists.

    Parameters
    ----------
    n : int
        Maximal index / number of samples.
    """
    # make a list of mask arrays, it's easier to store
    # as there is a hdf5 equivalent
    for il,l in enumerate(list_of_index_lists):
        mask = np.zeros(n,dtype=bool)
        mask[l] = True
        list_of_index_lists[il] = mask
    # convert to arrays
    masks = np.array(list_of_index_lists)
    return masks
Make an array in which rows store 1d mask arrays from list of index lists.

    Parameters
    ----------
    n : int
        Maximal index / number of samples.