def __init__(self, conformal_classifier: ConformalClassifier):
        """
        An adaptive conformal classifier class
        (see `Gibbs & Candes, 2021 <https://proceedings.neurips.cc/paper/2021/hash/0d441de75945e5acbc865406fc9a2559-Abstract.html>`_).
        It takes any conformal classifier and adds the functionality to update the coverage error to take into account
        distributional shifts in the data.

        Parameters
        ----------
        conformal_classifier: ConformalClassifier
            A conformal method for classification.
        """
        for s, m in inspect.getmembers(conformal_classifier):
            if not s.startswith("__"):
                setattr(self, s, m)

        An adaptive conformal classifier class
        (see `Gibbs & Candes, 2021 <https://proceedings.neurips.cc/paper/2021/hash/0d441de75945e5acbc865406fc9a2559-Abstract.html>`_).
        It takes any conformal classifier and adds the functionality to update the coverage error to take into account
        distributional shifts in the data.

        Parameters
        ----------
        conformal_classifier: ConformalClassifier
            A conformal method for classification.
        
fortuna/conformal/classification/adaptive_conformal_classifier.py