Method get_sources

mne/preprocessing/ica.py:1222–1268

Estimate sources given the unmixing matrix. This method will return the sources in the container format passed. Typical usecases: 1. pass Raw object to use `raw.plot ` for ICA sources 2. pass Epochs object to compute trial-based statistics in ICA sp

(self, inst, add_channels=None, start=None, stop=None)

        return var_explained_ratio

    def get_sources(self, inst, add_channels=None, start=None, stop=None):
        """Estimate sources given the unmixing matrix.

        This method will return the sources in the container format passed.
        Typical usecases:

        1. pass Raw object to use `raw.plot <mne.io.Raw.plot>` for ICA sources
        2. pass Epochs object to compute trial-based statistics in ICA space
        3. pass Evoked object to investigate time-locking in ICA space

        Parameters
        ----------
        inst : instance of Raw, Epochs or Evoked
            Object to compute sources from and to represent sources in.
        add_channels : None | list of str
            Additional channels  to be added. Useful to e.g. compare sources
            with some reference. Defaults to None.
        start : int | float | None
            First sample to include. If float, data will be interpreted as
            time in seconds. If None, the entire data will be used.
        stop : int | float | None
            Last sample to not include. If float, data will be interpreted as
            time in seconds. If None, the entire data will be used.

        Returns
        -------
        sources : same type as the input data
            The ICA sources time series.
        """
        if isinstance(inst, BaseRaw):
            _check_compensation_grade(
                self.info, inst.info, "ICA", "Raw", ch_names=self.ch_names
            )
            sources = self._sources_as_raw(inst, add_channels, start, stop)
        elif isinstance(inst, BaseEpochs):
            _check_compensation_grade(
                self.info, inst.info, "ICA", "Epochs", ch_names=self.ch_names
            )
            sources = self._sources_as_epochs(inst, add_channels, False)
        elif isinstance(inst, Evoked):
            _check_compensation_grade(
                self.info, inst.info, "ICA", "Evoked", ch_names=self.ch_names
            )
            sources = self._sources_as_evoked(inst, add_channels)
        else:
            raise ValueError("Data input must be of Raw, Epochs or Evoked type")
        return sources

    def _sources_as_raw(self, raw, add_channels, start, stop):
        """Aux method."""