Method apply

mne/decoding/ssd.py:359–385

Remove selected components from the signal. This procedure will reconstruct M/EEG signals from which the dynamics described by the excluded components is subtracted (denoised by low-rank factorization). See :footcite:`HaufeEtAl2014b` for more information. ..

(self, X)

        raise NotImplementedError("inverse_transform is not yet available.")

    def apply(self, X):
        """Remove selected components from the signal.

        This procedure will reconstruct M/EEG signals from which the dynamics
        described by the excluded components is subtracted
        (denoised by low-rank factorization).
        See :footcite:`HaufeEtAl2014b` for more information.

        .. note:: Unlike in other classes with an apply method,
           only NumPy arrays are supported (not instances of MNE objects).

        Parameters
        ----------
        X : array, shape ([n_epochs, ]n_channels, n_times)
            The input data from which to estimate the SSD. Either 2D array
            obtained from continuous data or 3D array obtained from epoched
            data.

        Returns
        -------
        X : array, shape ([n_epochs, ]n_channels, n_times)
            The processed data.
        """
        X_ssd = self.transform(X)
        pick_patterns = self.patterns_[: self.n_components].T
        X = pick_patterns @ X_ssd
        return X


@verbose