def fit(self, sequences, y=None):
        """Fit a BACE lumping model using a sequence of cluster assignments.

        Parameters
        ----------
        sequences : list(np.ndarray(dtype='int'))
            List of arrays of cluster assignments
        y : None
            Unused, present for sklearn compatibility only.

        Returns
        -------
        self
        """
        super(BACE, self).fit(sequences, y=y)
        if self.n_macrostates is not None:
            self._do_lumping()
        else:
            raise RuntimeError('n_macrostates must not be None to fit')

        return self
def fit ( self , sequences , y = None ) : super ( BACE , self ) . fit ( sequences , y = y ) if self . n_macrostates is not None : self . _do_lumping ( ) else : raise RuntimeError ( 'n_macrostates must not be None to fit' ) return self
Fit a BACE lumping model using a sequence of cluster assignments.

        Parameters
        ----------
        sequences : list(np.ndarray(dtype='int'))
            List of arrays of cluster assignments
        y : None
            Unused, present for sklearn compatibility only.

        Returns
        -------
        self