def __repr__(self):
        if self.current_fit == 'unfitted':
            s = 'no'
        elif self.current_fit == 'raw':
            s = 'raw data'
        else:
            s = 'epochs'
        s += ' decomposition, '
        s += 'fit (%s): %s samples, ' % (self.method,
                                         str(getattr(self, 'n_samples_', '')))
        s += ('%s components' % str(self.n_components_) if
              hasattr(self, 'n_components_') else
              'no dimension reduction')
        if self.info is not None:
            ch_fit = ['"%s"' % c for c in _DATA_CH_TYPES_SPLIT if c in self]
            s += ', channels used: {0}'.format('; '.join(ch_fit))
        if self.exclude:
            s += ', %i sources marked for exclusion' % len(self.exclude)

        return '<ICA  |  %s>' % s
ICA fit information
dataset/ETHPy150Open mne-tools/mne-python/mne/preprocessing/ica.py/ICA.__repr__