def _transform_evoked(self, evoked):
        if not hasattr(self, 'mixing_matrix_'):
            raise RuntimeError('No fit available. Please first fit ICA')

        picks = pick_types(evoked.info, include=self.ch_names, exclude='bads',
                           meg=False, ref_meg=False)

        if len(picks) != len(self.ch_names):
            raise RuntimeError('Evoked doesn\'t match fitted data: %i channels'
                               ' fitted but %i channels supplied. \nPlease '
                               'provide Evoked compatible with '
                               'ica.ch_names' % (len(self.ch_names),
                                                 len(picks)))

        data, _ = self._pre_whiten(evoked.data[picks], evoked.info, picks)
        sources = self._transform(data)

        return sources
Aux method
dataset/ETHPy150Open mne-tools/mne-python/mne/preprocessing/ica.py/ICA._transform_evoked