That's valid reasoning. But maybe you as developer of this new functionality feel inclined to do some experimentation across frequency ranges before settling presets ;-)
If you come to the conclusion that presets won't work well that's another thing.

On 19.08.2013, at 18:13, Roman Goj <notifications@github.com> wrote:

> In examples/inverse/plot_dics_source_power.py:
> 
> > +
> > +# Compute DICS spatial filter and estimate source time courses on evoked data
> > +stc = dics_source_power(epochs.info, forward, noise_csds, data_csds, freqs)
> > +
> > +# Plot source power separately for each frequency of interest
> > +for i, freq in enumerate(freqs):
> > +    message = 'DICS source power at %0.1f Hz' % freq
> > +    brain = stc.plot(surface='inflated', hemi='rh', subjects_dir=subjects_dir,
> > +                     time_label=message, figure=i)
> > +    data = stc.data[:, i]
> > +    pow_max = data.max()
> > +    pow_min = (pow_max + data.min()) / 2.
> > +    pow_mid = (pow_min + pow_max) / 2.
> > +    brain.set_data_time_index(i)
> > +    brain.scale_data_colormap(fmin=pow_min, fmid=pow_mid, fmax=pow_max,
> > +                              transparent=True)
> @dengemann, from your previous line comments :
> 
> Thinking about it for one moment I would prefer preset fmin/mid/max for better comparability + code decluttering.
> 
> Hmm. I agree about better comparability, i.e. making fmin/mid/max preset will emphasize that we are really looking at slightly different values. On the other hand I like it how not using any presets would allow the user to experiment with the frequency ranges, so I like it this way, wdyt?
> 
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