Hi Kug-Seung, I was at the XAFS conference last week, as were a bunch of the other folks who might answer a question like this. Guanghui pointed you at the Athena user guide, which will help to some extent with your questions. On 08/25/2015 08:20 AM, 이국승(에너지환경소재연구팀) wrote:
While I was processing my data, I found that the FT features are changing as I change the spline range.
I think the change is severe as my data contain a lot of noises at high-k regions (above 12k).
The change is remarkable even when FT range is fixed and even when the spline range is far from the low and high limits of FT range.
When data are imported into athena, the defalut values for spline ranges from 0 to the end of measured data and the high limit of FT range is set to a value of the high limit of spline range minus 2.
There must be a relationship.
Could anyone explain these things and general rules for setting the spline range?
Everything in Athena is based on Fourier analysis, including background removal. The algorithm for background removal is explained in http://dx.doi.org/10.1103/PhysRevB.47.14126 The basic idea is that the background spline is found by minimizing the Fourier components below Rbkg. Thus, the details of how the FT is done affects the functional form or chi(k) that results. If your data are very noisy, then the spline function will be sensitive to the noise. That's just how it works. The defaults in Athena are not chosen because they are "right" -- certainly not! When I give lectures about Athena, I explain that the defaults are chosen because they are "non-stupid". That is, they are values that often work reasonably well. If your data are fairly clean and well-behaved, then the defaults can sometimes even be used unchanged. When you have very noisy data, it is incumbent upon you, the user, to examine the background removal and normalization parameters to verify that they are chosen sensibly and that you can understand the resulting data processing. As for setting the parameters of the spline, it may help to play with Rbkg. It may help to make the k-weighting for the background removal smaller (remember that the spline is found by doing a FT, if that k-weighting is large, the noise gets weighted and the spline is yet more sensitive to the noise). It may help to limit the range to include only the cleaner part of the data. It may help to loosen the high end spline clamp (which you can read about in the Athena manual). Since you did not show us what your data looks like, it is hard to say something more specific than that. Regards, B -- Bruce Ravel ------------------------------------ bravel@bnl.gov National Institute of Standards and Technology Synchrotron Science Group at NSLS-II Building 535A Upton NY, 11973 Homepage: http://bruceravel.github.io/home/ Software: https://github.com/bruceravel Demeter: http://bruceravel.github.io/demeter/