Hi Samy,
On Wed, Jul 10, 2019 at 2:08 AM Samy Ould-Chikh
Dear colleagues,
I have been using more and more wavelet transform in parallel of EXAFS fitting. In addition of the statistical parameters provided after the fit, I try also to compare the wavelet transform of experimental data against various structural models to choose the best. Absolutely nothing new here.
After applying the wavelet transform to tens of structural model in a row which was bit long, I asked myself this question: Why can't we simply fit the experimental spectra in "wavelet space" instead of R space/k-space ? Does someone know about a code already doing it ?
Yes, Larch supports fitting in (Cauchy) wavelet space. Basically, you set the fitting space to 'w' and specify the k- and R-ranges for the transform: trans = feffit_transform(fitspace='w', rmin=1.2, rmax=3.0, kmin=2.5, kmax=15, kweight=2, dk=5, windows='kaiser') . # wavelet dataset = feffit_dataset(data=my_datagroup, pathlist=[path1, path2], transform=trans) result = feffit(parameters, dataset) For example, see https://github.com/xraypy/xraylarch/blob/master/examples/feffit/doc_feffit_w...
Best Regards, Samy Ould-Chikh
KAUST Catalysis Center Bldg.3,Level 4, #4231 4700 King Abdullah University of Science & Technology Thuwal 23955-6900 Kingdom of Saudi Arabia
Tel: +966 12 8084486 E-mail: samy.ouldchikh@kaust.edu.sa Website: http://kcc.kaust.edu.sa/Pages/Home.aspx
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--Matt