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)
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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