autoreject.py 文件源码

def fit(self, X, y=None):
        """Fit it.

        Parameters
        ----------
        X : array, shape (n_epochs, n_times)
            The data for one channel.
        y : None
            Redundant. Necessary to be compatible with sklearn
            API.
        """
        deltas = np.ptp(X, axis=1)
        self.deltas_ = deltas
        keep = deltas <= self.thresh
        # XXX: actually go over all the folds before setting the min
        # in skopt. Otherwise, may confuse skopt.
        if self.thresh < np.min(np.ptp(X, axis=1)):
            assert np.sum(keep) == 0
            keep = deltas <= np.min(np.ptp(X, axis=1))
        self.mean_ = _slicemean(X, keep, axis=0)
        return self