Method apply

mne/preprocessing/ica.py:2175–2276

Remove selected components from the signal. Given the unmixing matrix, transform the data, zero out all excluded components, and inverse-transform the data. This procedure will reconstruct M/EEG signals from which the dynamics described by the excluded components is

(
        self,
        inst,
        include=None,
        exclude=None,
        n_pca_components=None,
        start=None,
        stop=None,
        *,
        on_baseline="warn",
        verbose=None,
    )

    @verbose
    def apply(
        self,
        inst,
        include=None,
        exclude=None,
        n_pca_components=None,
        start=None,
        stop=None,
        *,
        on_baseline="warn",
        verbose=None,
    ):
        """Remove selected components from the signal.

        Given the unmixing matrix, transform the data,
        zero out all excluded components, and inverse-transform the data.
        This procedure will reconstruct M/EEG signals from which
        the dynamics described by the excluded components is subtracted.

        Parameters
        ----------
        inst : instance of Raw, Epochs or Evoked
            The data to be processed (i.e., cleaned). It will be modified
            in-place.
        include : array_like of int
            The indices referring to columns in the ummixing matrix. The
            components to be kept. If ``None`` (default), all components
            will be included (minus those defined in ``ica.exclude``
            and the ``exclude`` parameter, see below).
        exclude : array_like of int
            The indices referring to columns in the ummixing matrix. The
            components to be zeroed out. If ``None`` (default) or an
            empty list, only components from ``ica.exclude`` will be
            excluded. Else, the union of ``exclude`` and ``ica.exclude``
            will be excluded.
        %(n_pca_components_apply)s
        start : int | float | None
            First sample to include. If float, data will be interpreted as
            time in seconds. If None, data will be used from the first sample.
        stop : int | float | None
            Last sample to not include. If float, data will be interpreted as
            time in seconds. If None, data will be used to the last sample.
        %(on_baseline_ica)s
        %(verbose)s

        Returns
        -------
        out : same type as the input data
            The processed data.

        Notes
        -----
        .. note:: Applying ICA may introduce a DC shift. If you pass
                  baseline-corrected `~mne.Epochs` or `~mne.Evoked` data,
                  the baseline period of the cleaned data may not be of
                  zero mean anymore. If you require baseline-corrected
                  data, apply baseline correction again after cleaning
                  via ICA. A warning will be emitted to remind you of this