def METHOD_NAME(spike_train: np.ndarray, censored_period: int, seed: int) -> np.ndarray:
    # random seed
    rng = np.random.RandomState(seed=seed)
    indices_of_duplicates = []
    while not np.all(np.diff(np.delete(spike_train, indices_of_duplicates)) > censored_period):
        (duplicates,) = np.where(np.diff(spike_train) <= censored_period)
        duplicates = np.unique(np.concatenate((duplicates, duplicates + 1)))
        duplicate = rng.choice(duplicates)
        indices_of_duplicates.append(duplicate)
    return np.array(indices_of_duplicates, dtype=np.int64)