Hi Samy,
On Wed, Jul 10, 2019 at 2:08 AM Samy Ould-Chikh
wrote:
> 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_wavelet_fit.lar
>
> 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.ouldch...@kaust.edu.sa
> Website: http://kcc.kaust.edu.sa/Pages/Home.aspx
>
>
>
>
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--Matt
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