Does Athena use a histogramming method for Fourier filtering? That's what I use. The idea is that to grid the data we don't interpolate but take averages over the data appearing within the bin, with interpolation only when there aren't any points within a bin. For those, you have to bridge across a gap. This is the best idea I've come up with for using data which may be tabulated more finely than the k-grid of the Fourier filtering process (typically dk=0.05A^-1). Something I've used in a XANES context but never tried for EXAFS is a convolution with a kernel whose width depends on energy, such that it matches the sharpest credible feature. See Manceau, A., Marcus, M. A., Lenoir, T. (2014) Estimating the number of pure chemical components in a mixture by X-ray absorption spectroscopy. J. Synchrotron Radiat. 21,1140-1147, specifically the SI. The notion is that no real feature can be narrower than the combination of the core-hole lifetime and instrumental broadening or the EXAFS wiggle corresponding to the maximum reasonable path length. This is done by transforming the data from E-space to a space in which a constant step in the abscissa corresponds to this energy-dependent minimum credible feature width. Of course, in EXAFS this is mostly a constant width in k, so some kind of smoothing would work if it's a constant kernel in k. S-G smoothing assumes uniform tabulation so unless your data were taken on a uniform k-grid, it doesn't really do the right thing. A problem with this method is that it drops off the very information you need to see what your noise floor is. I put this out there only for those who insist on smoothing. I use my data un-smoothed for EXAFS analysis, knowing that the treatment of noise and sampling finer than the k-bin is not really right. I don't really see the usefulness of smoothing for XANES or EXAFS analysis, though it might be OK for display if not overdone. mam On 4/20/2017 3:02 PM, Christopher Thomas Chantler wrote:

Note that in general any and every smoothing operation reduces the information content of the data and its ability to reveal structure. Also, many of the smoothing algorithms change the data point values at vertices, so change the data prior to analysis.

Hence in general avoid unless you know exactly the physical cause requiring smoothing.

Best wishes

-------------------------------------------------------------------------------------- Christopher Chantler, Professor, FAIP, Fellow American Physical Society Editor-in-Chief, Radiation Physics and Chemistry Chair, International IUCr Commission on XAFS President, International Radiation Physics Society School of Physics, University of Melbourne Parkville Victoria 3010 Australia +61-3-83445437 FAX +61-3-93474783 chantler@unimelb.edu.au https://owa.unimelb.edu.au/owa/redir.aspx?C=c7BoS0kVVkC1_S95-9x9l5cBu6YTjdAITgSrfUpfDAUV5oUH1LFYBcz08w8xvHMJoosZRdagfQM.&URL=mailto%3achantler%40unimelb.edu.au chantler@me.com https://owa.unimelb.edu.au/owa/redir.aspx?C=c7BoS0kVVkC1_S95-9x9l5cBu6YTjdAITgSrfUpfDAUV5oUH1LFYBcz08w8xvHMJoosZRdagfQM.&URL=mailto%3achantler%40me.com http://optics.ph.unimelb.edu.au/~chantler/xrayopt/xrayopt.html https://owa.unimelb.edu.au/owa/redir.aspx?C=c7BoS0kVVkC1_S95-9x9l5cBu6YTjdAITgSrfUpfDAUV5oUH1LFYBcz08w8xvHMJoosZRdagfQM.&URL=http%3a%2f%2foptics.ph.unimelb.edu.au%2f%7echantler%2fxrayopt%2fxrayopt.html http://optics.ph.unimelb.edu.au/~chantler/home.html https://owa.unimelb.edu.au/owa/redir.aspx?C=c7BoS0kVVkC1_S95-9x9l5cBu6YTjdAITgSrfUpfDAUV5oUH1LFYBcz08w8xvHMJoosZRdagfQM.&URL=http%3a%2f%2foptics.ph.unimelb.edu.au%2f%7echantler%2fhome.html

------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ *From:* Ifeffit on behalf of ifeffit-request@millenia.cars.aps.anl.gov *Sent:* Friday, 21 April 2017 3:00:01 AM *To:* ifeffit@millenia.cars.aps.anl.gov *Subject:* Ifeffit Digest, Vol 170, Issue 19

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Today's Topics:

1. Re: The difference of EXAFS oscillation when using Athena and when using Larch (Yuji Mahara)

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Message: 1 Date: Thu, 20 Apr 2017 19:47:20 +0900 From: "Yuji Mahara" To: "'XAFS Analysis using Ifeffit'" Subject: Re: [Ifeffit] The difference of EXAFS oscillation when using Athena and when using Larch Message-ID: <003501d2b9c3$7c75c560$75615020$@e.mbox.nagoya-u.ac.jp> Content-Type: text/plain; charset="utf-8"

Dear Matt

Thank you for your reply.

I confirmed that chi (k) becomes smooth by the Savitzky-Goley method by doing the attached lar file.

I will try on various conditions from now.

I may also ask if there is something I do not understand.

Thank you for your help again!

Bests,

Yuji Mahara

From: Ifeffit [mailto:ifeffit-bounces@millenia.cars.aps.anl.gov] On Behalf Of Matt Newville Sent: Thursday, April 20, 2017 5:26 AM To: XAFS Analysis using Ifeffit Subject: Re: [Ifeffit] The difference of EXAFS oscillation when using Athena and when using Larch

Hi Yuji,

The attached larch script (a modification of your script but note: not python, so you may have to add a bunch of '_larch=mylarch' arguments) to show the effects of smoothing with Savitzky-Golay and of interpolating onto a "classic XAFS energy grid". You might want to play around with this different options. It definitely seems that none of these methods are systematically over-smoothing the data and reducing the amplitudes of the oscillations -- one more reason to use Larch instead of Ifeffit. But it also seems like smoothing this data with a Savitzky-Golay fitler is helpful.

Also attached are plots showing k- and R-space generated from the attached script.

--Matt

Hi Chris, On Thu, Apr 20, 2017 at 5:02 PM, Christopher Thomas Chantler < chantler@unimelb.edu.au> wrote:

Note that in general any and every smoothing operation reduces the information content of the data and its ability to reveal structure.

Well, maybe. If one has mu(E) measured every 0.01 eV over an 600 eV EXAFS scan to k=12A^-1, one does not really 60,000 independent measures of the structure. Yuji's data wasn't that absurd, but it did have close to 4000 measurements for the full EXAFS spectrum out to k=18^-1. And to be clear, there is not anything wrong with that, it's just a matter of how you decide to treat it. As the plots attached in Yuji's original message and my replies show, the resulting chi(k) definitely has is amplitude suppressed when doing a simple boxcar average of data onto the 0.05 Ang^-1 grid (Athena with Ifeffit). But when using cubic spline interpolation (Larch), the amplitude of the EXAFS oscillations are not noticeably suppressed, though the high frequency noise is also much higher. Applying a Savitzky-Golay filter prior to the cubic spline interpolation did not appreciably suppress the EXAFS oscillations though the high frequency noise was reduced. Very finely-spaced energy data might reveal is at much higher R than we can hope to model with EXAFS. A k-grid of 0.05 Ang^-1 can give frequencies to 31Ang, and so is probably accurate to 16Ang without significant signal loss. That is, out to k=18Ang^-1, you really only need 360 samples, but you'd like these as noise-free as possible. Having 3600 measurements on a grid of 0.005 Ang^-1 might give you data out to 160Ang in principle, but the photo-electron tends to not cooperate. --Matt