see label.smooth method. I'm not sure it required for illustration though.
Aud-lh should give reasonable results.


On Mon, Sep 16, 2013 at 7:13 PM, Roman Goj <notifications@github.com> wrote:

> In examples/inverse/plot_tf_dics.py:
>
> > +
> > +import logging
> > +logger = logging.getLogger('mne')
> > +
> > +import mne
> > +
> > +from mne.fiff import Raw
> > +from mne.datasets import sample
> > +from mne.beamformer import tf_dics
> > +
> > +data_path = sample.data_path()
> > +raw_fname = data_path + '/MEG/sample/sample_audvis_raw.fif'
> > +event_fname = data_path + '/MEG/sample/sample_audvis_raw-eve.fif'
> > +fname_fwd = data_path + '/MEG/sample/sample_audvis-meg-eeg-oct-6-fwd.fif'
> > +subjects_dir = data_path + '/subjects'
> > +label_name = 'Aud-lh'
>
> smooth? the label? what do you mean?
>
> What I meant is that the maximum for the dics_source_power (as discussed
> above, oops, forgot to add that as an issue to the list above) isn't in
> Aud-lh but somewhere nearby, where it shouldn't be, but where it also is
> for LCMV, so maybe using that nearby label would be better? But what did
> you mean by smoothing?
>
> —
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> .
>