[Eeglablist] Time-frequency transform became 150-450% faster (without using parallel computing toolbox)

[Makoto Miyakoshi]

Dear Arno,

> Did you check the code of the timefreq function which is being used by
the newtimef function of EEGLAB to compute time-frequency decompositions?

It is about modified timefreq() function that is called by newtimef(). I
did not give it a through check, I just modified the part that my standard
process uses. I did not care backward compatibility either.

> Also, when using more than one channel, the time-frequency decomposition
of all channels is computed together using a single matrix multiplication.
If you think your solution might still be useful, it would be great to add
it to the timefreq function.

Hmm I called the newtimef() from GUI and command line newtimef(). I don't
know what you mention here.

The modified code does a single-shot matrix calculation for each channel.
As such, it is RAM-intensive.

Makoto

On Sun, Nov 29, 2020 at 4:44 PM Delorme, Arnaud <adelorme at ucsd.edu> wrote:

> Hi Makoto,
>
> Did you check the code of the timefreq function which is being used by the
> newtimef function of EEGLAB to compute time-frequency decompositions?
> There are many different variants (some commented). Also, when using more
> than one channel, the time-frequency decomposition of all channels is
> computed together using a single matrix multiplication.  If you think your
> solution might still be useful, it would be great to add it to the timefreq
> function.
>
> Cheers,
>
> Arno
>
> > On Nov 29, 2020, at 2:25 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
> wrote:
> >
> > Dear EEGLAB users,
> >
> > I ran an experiment to test if removing for-loops can speed up
> > time-frequency transformation. For epoched data, I confirmed 150%-200% of
> > processing speed. The more time/frequency point there are, the more
> > efficient it became. The most noticeable effect was found when I
> processed
> > a continuous data with it. I confirmed speed increase to 450%. If you are
> > interested in trying it out, please download the modified timefreq.m from
> > the following link.
> >
> >
> https://sccn.ucsd.edu/wiki/Makoto's_useful_EEGLAB_code#How_to_perform_time-frequency_transformation_faster_.2811.2F29.2F2020_added.29
> >
> > This is a beta test. When you encounter a bug or problems, please let me
> > know.
> >
> > Makoto
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