Hi Edmund,
in my opinion evaluating 3000 spectra is neither a heroic attempt nor
brute force. The LCF of 3000 spectra yields one beautiful plot with
3000 * components points, where the information of an enormous Gbyte
data set is included - for me that is indeed very economical. With
such a plot each reader can decide (or be convinced) which spectra are
"boring" and if you want to study high order kinetics during your
reaction you will be happy to have enough points to perform the
required fits. Of course, one can also write a program that preselects
a few spectra by evaluating the differences between the spectra. But
then I guess you need at least one (avoidable) parameter to adjust the
tolerance to distinguish between differences caused by noise and those
due to real variations in sample composition.
That´s why I´d prefer fitting all spectra and afterwards highlighting
the interesting parts. That might take 2-3 hours for a few thosand
spectra (extended lunch break) but it is still much more convenient
than finding the "interesting" spectra manually by going through all
spectra (or than finding the most suitable tolerance parameter). And
the resulting plots are worth the time imo. I am rather going to check
how much faster I can get by parallelizing the processes for
multicores...
Best regards,
Jan Stötzel
Zitat von Edmund Welter
Dear XAFS users
recently I read several mails on this list which were dealing with the problem of large data sets, as they are produced by Q-EXAFS scans or by dispersive XAFS. The question was if there are tools available to handle data sets of several 1000 spectra and perform a linear combination fit or even a full EXAFS evaluation on each of them. Evaluating 3000 spectra is a heroic attempt, but I wonder if it is also economical.
In most (that means not in ALL!) cases, the vast majority of these spectra is boring, because the spectrum with the number X looks exactly like the spectrum with the number X-1 looked and how the spectrum with the number X+1 will look and so on. Evaluating all these (basically identical) spectra is in principle a waste of time and working memory. The interesting spectra are those which were measured when something was happening in the sample. Since we do not always know at which time, or temperature or reactant concentration etc. interesting things will happen it is without any doubt justified to measure x-thousand spectra, but after that we should use a more sophisticated approach than brute force.
I think that it would be much more useful to find procedures (that means develop computer programs) that search for the (usually relatively small number of) interesting spectra. The most obvious parameter is how similar is a particular spectrum to the spectra measured before and after. The next step would probably be to identify clusters of related spectra using statistical methods. This is a problem which had to be solved in other areas like the automated analysis of images before and should also be possible with our kind of data.
Anyway, how to handle thousands of XAFS spectra will become a very important problem in the future. With all these beamlines that provide 10^12 photons per second we can measure a factor 100 -- 1000 faster than we did with 10^9 photons per second. So, I wonder if anything beyond the brute force approach is going on in the EXAFS software universe to make effective and economical use of the measured data.
Best regards, Edmund Welter
-- -------------------------------------------------------- Dr. Edmund Welter Deutsches Elektronen-Synchrotron DESY FS-Do
Notkestr. 85 Email: edmund.welter@desy.de D-22607 Hamburg Phone: +49 40 8998 4510 Germany Fax : +49 40 8998 2787 --------------------------------------------------------