What I typically do for XANES is divide mu-mu_pre_edge_line by a linear function which goes through the post-edge oscillations. This division goes over the whole data range, including pre-edge. If the data has obvious curvature in the post-edge, I'll use a higher-order polynomial. For transmission data, what sometimes linearizes the background is to change the abscissa to 1/E^2.7 (the rule-of-thumb absorption shape) and change it back afterward. All this is, of course, highly subjective and one of the reasons for taking extended XANES data (300eV, for instance). For short-range XANES, there isn't enough info to do more than divide by a constant. Once this is done, my LCF programs allow a slope adjustment as a free parameter, thus muNorm(E) = (1+a*(E-E0))*Sum_on_ref{x[ref]*muNorm[ref](E)}. A sign that this degree of freedom may be being abused is if the sum of the x[ref] is far from 1 or if a*(Emax-E0) is large. Don't get me started on overabsorption :-) mam On 5/15/2013 7:35 AM, Matt Newville wrote:
Hi Folks,
Over on the github pages for larch, Mauro and Bruce raised an issue about the "flattening" in Athena. See https://github.com/xraypy/xraylarch/issues/44
I've added a "flattened output" from Larch's pre_edge() function, but the question has been raised of whether this is "better" than the simpler normalized spectra, especially for doing PCA and/or LCF for XANES.
Currently, the "normalized" spectra is just "(mu - pre_edge_line)/edge_step". Clearly, a line fitted to the pre-edge of the spectra is not sufficient to remove all instrumental backgrounds. In some sense, flattening attempts to do a better job, fitting the post-edge spectra to a quadratic function. As Mauro, Bruce, and Carmelo have pointed out, it is less clear that it is actually better for XANES analysis. I think the main concerns are that a) it is so spectra-specific, and b) it turns on at E0 with a step function.
Bruce suggested doing something more like MBACK or Ifeffit's bkg_cl(). It would certainly be possible to do some sort of "flattening" so that mu follows the expected energy dependence from tabularized mu(E).
Does anyone else have suggestions, opinions, etc? Feel free to give them here or at the github page....
--Matt _______________________________________________ Ifeffit mailing list Ifeffit@millenia.cars.aps.anl.gov http://millenia.cars.aps.anl.gov/mailman/listinfo/ifeffit